Technology-Oriented Customer Touchpoints in Context of Services in Retailing: A Differentiated Analysis on Social Presence and Privacy Calculus 3658405538, 9783658405533

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Handel und Internationales Marketing Retailing and International Marketing Bernhard Swoboda · Thomas Foscht Hanna Schramm-Klein Hrsg.

Tobias Röding

Technology-Oriented Customer Touchpoints in Context of Services in Retailing A Differentiated Analysis on Social Presence and Privacy Calculus

Handel und Internationales Marketing Retailing and International Marketing Series Editors Bernhard Swoboda, Universität Trier, Trier, Germany Thomas Foscht, Karl-Franzens-Universität Graz, Graz, Austria Hanna Schramm-Klein, Lehrstuhl für Marketing, Universität Siegen, Siegen, Germany

Die Schriftenreihe fördert die Themengebiete Handel und Internationales Marketing. Diese charakterisieren – jedes für sich, aber auch in inhaltlicher Kombination – die Forschungsschwerpunkte der Herausgeber. Beide Themengebiete werden grundsätzlich breit aufgefasst; die Reihe bietet sowohl Dissertationen und Habilitationen als auch Tagungs- und Sammelbänden mit unterschiedlicher inhaltlicher und methodischer Ausrichtung ein Forum. Die inhaltliche Breite ist sowohl im Sinne eines konsumentenorientierten Marketings wie auch einer marktorientierten Unternehmensführung zu verstehen. Neben den Arbeiten, die von den Herausgebern für die Schriftenreihe vorgeschlagen werden, steht die Reihe auch externen wissenschaftlichen Arbeiten offen. Diese können bei den Herausgebern eingereicht und nach einer positiven Begutachtung publiziert werden. The book series focuses on the fields of Retailing and International Marketing. These two areas represent the research fields of the editors—each of them as a single research area, but also in combination. Both of these research areas are widely understood. Consequently, the series provides a platform for the publication of doctoral theses and habilitations, conference proceedings and edited books, as well as related methodological issues that encompass the focus of the series. The series is broad in the sense that it covers academic works in the area of consumer-oriented marketing as well as the area of marketoriented management. In addition to academic works recommended by the editors, the book series also welcomes other academic contributions. These may be submitted to the editors and will be published in the book series after a positive assessment.

Tobias Röding

Technology-Oriented Customer Touchpoints in Context of Services in Retailing A Differentiated Analysis on Social Presence and Privacy Calculus

Tobias Röding Siegen, Germany Tobias Röding, Dissertation, Universität Siegen, 2022

ISSN 2626-3327 ISSN 2626-3335 (electronic) Handel und Internationales Marketing Retailing and International Marketing ISBN 978-3-658-40553-3 ISBN 978-3-658-40554-0 (eBook) https://doi.org/10.1007/978-3-658-40554-0 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer Gabler imprint is published by the registered company Springer Fachmedien Wiesbaden GmbH, part of Springer Nature. The registered company address is: Abraham-Lincoln-Str. 46, 65189 Wiesbaden, Germany

Contents

1 Motivation and Orientation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 An Overview of Technology-Oriented Customer Touchpoints in Retailing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 The Relevance of the Customer–Retailer Relationship . . . . . . . . . 1.3 Service in the Context of the Privacy Calculus and Perceived Social Presence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 An Integrated Typology of Technology-Oriented Customer Touchpoints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1

10

2 Structure and Content of the Essays . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Focus of the Essays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Abstracts of the Essays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

19 19 22

3 Essays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Essay 1. A Classification of Information-oriented Point of Sale Technology in Relation to Customer Perception . . . . . . . . 3.2 Essay 2. How to Infuse Mobile Technologies in Frontline Service Encounters: An Experimental Analysis of Customer Responses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Essay 3. The Role of the Frontline Employee in Technology-Based Service Encounters . . . . . . . . . . . . . . . . . . . . 3.4 Essay 4. The Relevance of Corporate Information Transparency of the Use and Handling of Customers’ Data in Online Product Presentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

35

1 4 6

35

54 73

90

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Contents

3.5 Essay 5. The Impact of IT/IS, Lifestyle and Income Related Influences on Customers’ Intention to Provide Digitally Transferred Access Permission in Last Mile Delivery—an Empirical Analysis before and during the COVID-19 Pandemic . . . . . . . . . . . . . . . . . . 3.6 Essay 6. MIRROR, MIRROR…on the Shelf: The Impact of Perceived Age Similarity and Gender Congruence between the Customer and the Voice of a Smart Voice Assistant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 Essay 7. The Influence of Technology Infusion on Customers’ Information Disclosure Behaviour within the Frontline Service Encounter . . . . . . . . . . . . . . . . . . . . . . 3.8 Essay 8. Help Us to Help You: The Effects of Customer Incentivisation and Technology Infusion on Data Disclosure and Accuracy in Stationary Retail . . . . . . . . . . . . . . . . . . . . . . . . . . .

107

135

154

178

4 Discussion and Implication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 An Extended Perspective on Technology-Oriented Customer Touchpoints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Implications for Theory and Practice . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Relevance for Future Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

205 205 212 216

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

219

Abbreviations

AI ANCOVA ANOVA AR AVE CEP COVID CR DIY DAF Df DV e-commerce e.g. et al. H HiPC HiSP i.e. IS IT LLCI LoPC LoSP M MANOVA

Artificial Intelligence Analysis of Covariance Analysis of Variance Augmented Reality Average Variance Extracted Courier, Express and Parcel Services Corona Virus Disease Composite Reliability d_ Do-It-Yourself Store Dispersion Accounting For Degrees of Freedom Dependent Variable Electronic Commerce exempli gratia (for example) et alii/et aliae/et alia (and others) Hypothesis High Privacy Calculus High Social Presence id est (that is to say) Information Systems Information Technology Lower Limit Confidence Interval Low Privacy Calculus Low Social Presence Mean Multivariate Analysis of Variance

vii

viii

MDS MICOM MS N n.d. NFI p p PLS PoS Q2 QR R2 RQ SD Sig. SPSS SRMR SVA t TTF ULCI VIF VR α β

Abbreviations

Multidimensional Scaling Measurement Invariance of Composite Models Mean Square Number of Sample Size no date Normed Fit Index p-value Page Partial Least Squares Point of Sale Stone-Geisser-Kriterium Quick Response R-squared (Coefficient of Determination) Research Question Standard Deviation Significance Level Statistical Package for the Social Sciences Standardized Root Mean Square Residual Smart Voice Assistant t-statistic Task technology fit model Upper Limit Confidence Interval Variance Inflation Factor Virtual Reality Cronbach’s Alpha Beta (standardized Coefficient)

List of Figures

Figure 1.1 Figure 3.1 Figure 3.2 Figure 3.3

Figure 3.4

Figure Figure Figure Figure Figure

3.5 3.6 3.7 3.8 3.9

Figure Figure Figure Figure Figure

3.10 3.11 3.12 3.13 3.14

Figure 3.15

Social Presence—Privacy Calculus Typology of Technology-Oriented Customer-Touchpoints . . . . . . . . . . Result of MDS analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Research Model for Essay 2 . . . . . . . . . . . . . . . . . . . . . . . . . Exemplary excerpt of the video stimuli of study 2 (type of technology infusion within the service encounter: technology-free vs. technology-facilitated vs. technology-assisted) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Experimental design of study 2 (type of technology infusion within the service encounter: technology-free vs. technology-facilitated vs. technology-assisted) . . . . . . . . Research Model for Essay 3 . . . . . . . . . . . . . . . . . . . . . . . . . Supporting images for the technology . . . . . . . . . . . . . . . . . . Research Model for Essay 4 . . . . . . . . . . . . . . . . . . . . . . . . . Experimental Design for study . . . . . . . . . . . . . . . . . . . . . . . . Results of moderation-testing of customers’ privacy concerns on customers’ purchase intention . . . . . . . . . . . . . . Research Model for Essay 5 . . . . . . . . . . . . . . . . . . . . . . . . . Supporting image used in studies 1 and 2 . . . . . . . . . . . . . . Research Model for Essay 6 . . . . . . . . . . . . . . . . . . . . . . . . . Research Model for Essay 7 . . . . . . . . . . . . . . . . . . . . . . . . . Moderating Impact of perceived Benefits on Customer’s Information Disclosure . . . . . . . . . . . . . . . . . Research Model for Essay 8 . . . . . . . . . . . . . . . . . . . . . . . . .

17 45 57

63

67 79 82 94 97 102 112 116 142 157 171 185

ix

x

Figure 3.16

Figure 3.17

List of Figures

Experimental Design (Technology infusion: Not Present (Paper & Pencil) vs. Present (Tablet Computer)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Moderating Influences of Customers’ Privacy Risks and Data Control on the Dependent Variables . . . . . . . . . . .

190 199

List of Tables

Table 2.1 Table 3.1 Table 3.2 Table Table Table Table

3.3 3.4 3.5 3.6

Table 3.7

Table 3.8 Table 3.9

Table 3.10 Table 3.11 Table 3.12

Table 3.13

Overview of the Essays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Influences, Sources, Scales, Item Adaptation and Cronbach’s Alpha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of Correlation Matrix and Discriminant Validity for Essay 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R2 , F-Values and Coefficients . . . . . . . . . . . . . . . . . . . . . . . . . ANOVAs of the Identified Clusters . . . . . . . . . . . . . . . . . . . . . Results of hypotheses testing MANOVAs for study 1 . . . . . Results on the direct and indirect effect of customers’ perceived competence of the frontline employee on the dependent variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of the impact of the type of technology infusion within the service encounter on the dependent variables for study 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Implications for the frontline employee as well as for the retailer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Constructs, Sources, Scales (7-point-likert-scale: 1 = I totally disagree—7 = I totally agree), Item Adaptation and Cronbach’s Alpha for Essay 3 . . . . . . . . . . . . . . . . . . . . . Results of ANOVA-testing of the dependent variables . . . . . Results of ANOVA-testing of the mediating variables . . . . . Constructs, sources, item adaptation and Cronbach’s alpha. All scales (besides willingness to pay) were measured on a 7-point-Likert-scale: 1 = I totally disagree—7 = I totally agree . . . . . . . . . . . . . . . . . . . . . . . . . . Results of ANOVA-testing . . . . . . . . . . . . . . . . . . . . . . . . . . . .

20 42 43 45 47 64

65

69 71

83 85 86

98 101

xi

xii

Table 3.14 Table 3.15 Table 3.16 Table 3.17 Table 3.18 Table 3.19 Table 3.20

Table 3.21 Table 3.22 Table 3.23 Table 3.24 Table 3.25

Table 3.26 Table 3.27 Table 3.28

Table 3.29 Table 3.30 Table 3.31 Table 3.32 Table 3.33

List of Tables

Constructs, Source, Scale, Item Adaptation and Outer Loading for Essay 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cronbach’s Alpha, Composite Reliability, Average Variance Extracted and Variance Inflation Factor . . . . . . . . . Results of Correlation Matrix and Discriminant Validity: Before Covid-19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of Correlation Matrix and Discriminant Validity: During Covid-19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary of the results of the SmartPLS analysis . . . . . . . . Overview of the Pitch of the Stimuli used . . . . . . . . . . . . . . . Constructs, Sources, Scale (7-point-likert-scale: 1 = I totally disagree—7 = I totally agree), Item Adaptation and Cronbach’s Alpha for Essay 6 . . . . . . . . . . . . . . . . . . . . . Results of Correlation Matrix and Discriminant Validity for Essay 6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of Hypotheses Testing ANOVA (DV = Willingness to Interact) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of Hypotheses Testing ANOVA (DV = Willingness to Disclosure) . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of exploratory factor analysis . . . . . . . . . . . . . . . . . . . Constructs, Source, Scale (7-point-likert-scale: 1 = I totally disagree—7 = I totally agree), Item Adaptation and Outer Loading for Essay 7 . . . . . . . . . . . . . . . . . . . . . . . . Results of Correlation Matrix and Discriminant Validity for Essay 7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of the hypothesis testing ANOVA (DV: Dimensions of Information Disclosure) . . . . . . . . . . . . . . . . . Results of the hypothesis testing ANOVA (DV: Perceived Trust in Retailers’ Use of the Disclosed Information) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of the hypothesis testing ANOVA (DV: Experienced emotions) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of the hypothesis testing mediation analysis . . . . . . . Constructs, Sources, Scales, Item Adaptation and Cronbach’s Alpha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of Correlation Matrix and Discriminant Validity for Essay 8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of MANOVA testing of the dependent variables . . .

117 124 125 126 128 144

145 147 149 150 162

163 167 168

172 173 175 192 195 196

List of Tables

Table 4.1 Table 4.2

xiii

Overview of the integrated main variables in the eight essays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Overview of the independent and dependent variables in the eight essays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

205 206

1

Motivation and Orientation

1.1

An Overview of Technology-Oriented Customer Touchpoints in Retailing

A key challenge for retailers is to effectively combine technology and human resources to meet customers where they want to be met in an ever more technological and digitalised market (Lemon and Verhoef, 2016; Bleier et al., 2019; Kuckertz et al., 2020). The individual customer experience is closely related to the way innovative technologies are integrated into service-oriented processes (Grewal et al., 2020). The convergence and acceptance of technology-oriented customer touchpoints depends on ever-changing customer preferences. The continuing growth of the online shopping market in Germany—the growth rate was + 18.4% in 2020, excluding food (HDE, 2021)—underlines this change in shopping behaviour. However, statistics also show that, although the online share is increasing more quickly than the German retail market, the total market (excluding food) also increased by e13 billion (to e373 billion) in 2020 (HDE, 2021). The COVID-19 pandemic was also an accelerator of the more intensive use of digital devices and services as part of individual shopping behaviour (McKinsey, 2020; Deloitte, 2020; PwC, 2020). An understanding of the added values or the adaptation of these services by the customer as well as the creation of newer/developed technology-oriented customer touchpoints can be seen as part of an interdependent process between the customer and the retailer (Herhausen et al., 2019). These technologies offer very specific advantages to the customer, especially at the physical PoS, such as access to certain product-related information and the availability of goods. The immediate presentation or visualisation of products through AR- or VR-related applications as well as immediate purchasing have been made possible (Larivière et al., 2017; Marinova et al., 2017). © The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2023 T. Röding, Technology-Oriented Customer Touchpoints in Context of Services in Retailing, Handel und Internationales Marketing Retailing and International Marketing, https://doi.org/10.1007/978-3-658-40554-0_1

1

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1

Motivation and Orientation

Moreover, studies show that reducing waiting times at the counter through technological solutions (e.g. contactless payment) is important to customers in the stationary shopping process (Karjaluoto et al., 2019). Besides physical retailing, technological support can also improve post-purchase processes as the last mile of delivery for both the customer and the supplier and thus also for the retailer (Mangiaracina et al., 2019). The infusion/use of technologies before, during and after the actual purchase process is usually accompanied by the transmission of personal information from the customer to the dealer/service provider. Phelps et al. (2000) emphasised that, in principle, most customers are willing to give up part of their privacy or disclose personal data to participate in the consumer society. Customers’ privacy issues play a central role in the purchasing process. Studies have shown that, although the proportion of customers who feel secure about their data on the internet has improved slightly in recent years (20.8% in 2014 and 25.2% in 2021), almost a third of respondents in Germany (32.0%) still express a sense of insecurity in this context (DsiN-Sicherheitsindex 2021, 2021). These concerns are of great importance in purchasing processes because customers weigh the benefits of purchasing a certain product against the cost of their data potentially being disclosed (Laufer and Wolfe, 1977; Culnan and Armstrong, 1999). Berendt et al. (2005) pointed out that, under the right circumstances, customers tend to disclose even the most personal data. By providing more ‘output’ to the customer (personalised service, more appropriate products, cash discounts, etc.), the retailer can increase risk acceptance, which can lead to more data collected and better service in the medium term (Krafft et al., 2017). The privacy calculus explains the exchange of service- and product-related added values and personal data between the customer and the retailer. The disclosure and collection of personal data are essential factors in companies’ strategic advantages in the market (Wakefield, 2013). This is true not only for product improvement but also service offerings. Companies use this data to gain an optimal understanding of customer preferences to improve their customer relationship management (Malthouse et al., 2013; Bradlow et al., 2016). The effects of technology-oriented customer contact points and their perception by the customer have been discussed in the literature for some time. In particular, there has been an increasing focus on how PoS technologies should be used in the service context and what role human frontline employees can play in the physical PoS (de Keyser et al., 2019; Roggeveen and Sethuraman, 2020). The potential limitations of integrating technologies into the PoS have also been addressed and explored in depth in empirical analyses (Wünderlich et al., 2013;

1.1 An Overview of Technology-Oriented Customer Touchpoints in Retailing

3

Giebelhausen et al., 2014). These research approaches investigated customer perceptions of different technology-oriented customer touchpoints. These analyses focused on the role and importance of the human frontline employee by assuming that customers will continue to value some form of human social interaction at the physical PoS (van Doorn et al., 2017; Grewal et al., 2020). This dissertation is based on previous research and follows the research priorities of the scientific community (MSI 2016–18; MSI 2018–20; MSI 2020–22), and it further explores the issue of customer perception and reactions to the potential collection of customer data involved in service-oriented technologies at the PoS. Taking the future research direction into consideration, one focus of this study is the investigation of the data disclosure behaviour of customers concerning their interaction with frontline employees and technology. This dissertation deepens, focuses and sharpens the current understanding of customers’ perception of innovative/digital service technologies in and around brick-and-mortar retail stores. Its key objectives are to (1) shed new light on the common understanding of the benefits and boundaries of technology-oriented customer touchpoints with regard to the interaction between the customer and the service employee/service provider and seek a comprehensive understanding of how technology should be infused into a service encounter to make the outcome as optimal as possible for both the customer and the service employee/service provider, (2) deepen the knowledge of incorporating social presence and the customers’ intuitive use of the privacy calculus during concrete service interactions and support the relevant theoretical approaches from the literature with further insights, (3) point out the implications for the practitioner and (4) pave the way for future studies. An attempt will also be made to map customers’ perceptions of social exchange and the privacy calculus in technology-oriented retailing. The central framework of this dissertation was derived from the fundamental approaches of the theory of social presence and the theory of privacy calculus. To put it another way, the analyses of this dissertation follow the four objectives listed above and focus on the relevance of interpersonal influence in relation to social presence and the influence of the customer-related data calculus in the service context. In the following chapters, the relevance of stationary service in the context of technology infusion and its current challenges will be discussed. Afterwards, a general typology of the essential theoretical approaches of the social presence theory and the privacy calculus theory will be provided. The influence of technological touchpoints on physical and digital services and the importance of interpersonal and calculated data-related processes by customers will also be shown. Finally, the central framework of this dissertation is derived from

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Motivation and Orientation

the basic theoretical approaches: Social Presence—Privacy Calculus Typology of Technology-Oriented Customer-Touchpoints.

1.2

The Relevance of the Customer–Retailer Relationship

Singh et al. (2017) stated that service encounters are any form of interaction between a retailer and a customer, with the service staff/salesperson/frontline employee playing a crucial role in this interaction because they are the link between the retailer and the customer. It has always been the goal of companies to satisfy their customers in each interaction in order to generate long-term loyalty towards the company (Sherden, 1988) and especially to prevent the termination of a successful customer–retailer relationship (Bolton, 1998). The literature has emphasised the importance of dyadic communication between the parties to create the most satisfying and qualitatively appropriate level of relationship (Palmatier et al., 2006; Verma et al., 2015). The literature concering frontline service encounters has explained dyadic, role-based interactions between the two parties and emphasised the importance of social components (Solomon et al., 1985; Surprenant and Solomon, 1987). Establishing a personal connection/relationship between customers and service employees is important, as it is a key factor for the long-term success of the customer relationship (Gremler and Gwinner, 2000). Additionally, certain behaviours, such as smiling, pleasant conversations, attentive customer service and knowledge sharing, have been identified as having a positive impact on customer relationship building (Gremler and Gwinner, 2008). Customers’ perceptions of frontline service also depend on the capabilities of the service employee. In addition to the analysis of service performance (Churchil et al., 1985; Plouffe et al., 2009; Verbeke et al., 2011), a large body of literature has highlighted the importance of service competence or customer perception of service competence (Parasuraman et al., 1985; Ford et al., 1987; Rentz et al., 2002). Service competence is a conglomerate of several components. Parasuraman et al., (1985) argued that this competence is composed of knowledge and skills, but Ford et al. (1987) and Rentz et al. (2002) highlighted three dimensions of competence in relation to the skills of frontline employees in sales environments: technical knowledge (competence regarding product features), salesmanship (competence regarding the presentation of a product) and interpersonal skills (competence regarding behavior in customer interaction). The

1.2 The Relevance of the Customer–Retailer Relationship

5

expression of these dimensions is not constant, and research has shown the importance of other approaches and components, such as empathy (Parasuraman et al., 1988), communication skills (Williams et al., 1990), listening (Punwatkar and Verghese, 2014), likability (Doney and Cannon, 1997), reliability (Swan, 1988), helpfulness and sociability (Surprenant and Solomon, 1987), safety (Parasuraman et al., 1988), adaptability (Spiro and Weitz, 1990), effort (Mohr and Bitner, 1995), attentiveness and courtesy (Gremler and Gwinner, 2008), intimacy and humanity (Kellogg and Chase, 1995), product/technical knowledge/expertise (Doney and Cannon, 1997) and market knowledge (Sujan et al., 1988). Different levels of knowledge also play a central role in the service environment (Verbecke et al., 2011). Thanks to numerous digital platforms and comparison portals, customers can obtain the most important information about products and services even before the service encounter (Verbeke, Dietz and Verwaal, 2011). A customer may classify the service performance within a service encounter as less competent if the knowledge of the service employee is even slightly lower than their own (Ahearne et al., 2008). Service quality has a strong positive effect on relationship building, loyalty and retention behaviour (Berry et al., 1988; Zeithaml et al., 1996). In fact, service quality is considered a company’s most important competitive advantage, and it cannot be easily imitated by competitors (Brown and Swartz, 1989; Parasuraman and Grewal, 2000). Relationship-building behaviour, also known as customer rapport (Gremler and Gwinner, 2008; Giebelhausen et al., 2014), is largely responsible for the customer’s future attitude towards a retailer (Bitner et al., 2000). As service encounters are social interactions between the customers and the service employees, their value strongly depends on the relationship-building behaviour of the service employees. The analysis of customer history data has also been used to improve relationships between frontline employees and customers (Kumar and Reinartz, 2016). It is possible to tailor products and services to specific customer groups based on a broad range of information on the wishes and needs of individual target groups. The information from individual customer profiles can be a decisive factor, since past consumption habits can be summarised and forecasts regarding future purchase decisions can be developed. The understanding and implementation of this knowledge in concrete processes can bring about decisive advantages in competition, especially concering the strategic orientation of the retailer (Shah and Murthi, 2020; Sheth and Kellstadt, 2021). However, customer self-disclosure behaviour is also essential, especially during face-to-face services (as opposed to online shopping). Self-disclosure is any form of verbal or non-verbal communication in which a person reveals something

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Motivation and Orientation

about themselves (Greene et al., 2006). Jourard (1971) and Greene et al. (2006) distinguished involuntary self-disclosure (or self-declaration) from intentional or conscious self-disclosure. This form of self-disclosure is a process in which one’s ‘self’ is purposefully made accessible to another person to reveal what was previously unknown (Jourard and Lasakow, 1958; Joinson and Paine, 2007). According to Jourard (1971), self-disclosure is mostly an intentional disclosure of oneself, and it is not exercised accidentally. Self-disclosure can vary due to numerous factors, e.g. familiarity, intimacy and breadth and depth of information (Jourard, 1971), and it is an important prerequisite for any form of social relationship (Laurenceau et al., 1998; Taddicken, 2014). Moreover, the breadth and depth of information depend on whether the situation requires a specific disclosure or exchange of social disclosure. For example, in certain situations, individuals share only the minimal information required for a successful transaction, but in other situations, sensitive personal information is often shared to build social relationships (Jacobs et al., 2001). At the same time, the disclosed information can trigger a sense of reward in the counterpart and increase the degree of intimacy or quality of self-disclosure, which can lead to interpersonal benefits (Worthy et al., 1969; Jourard, 1971). The dynamics of selfdisclosure can apply between two people, within groups and between a person and an organisation (Joinson and Paine, 2007).

1.3

Service in the Context of the Privacy Calculus and Perceived Social Presence

During social exchange processes, the mutual transmission of information plays an essential role in ensuring the success of an interpersonal encounter, whether it is in a private, professional or service-oriented environment. As mentioned earlier, this dissertation incorporates the theory of social presence and the theory of privacy calculus. It is based on the assumptions of the theory of social exchange (Homans, 1958, 1961; Blau, 1964) in which a fundamental understanding of interdependent human relationships and information exchange are conveyed, and it deals with specific questions about customer behaviour by weighing technology versus people and service added value versus data disclosure. These approaches are used to deepen the theoretical and practical understanding of the role and behaviour of the customer in the service context and to better understand the role of the service employee/service provider in successful interpersonal exchanges. During social interactions, individuals intuitively perform a cost–benefit analysis, which is related to the social exchange theory that has helped to classify

1.3 Service in the Context of the Privacy Calculus and Perceived Social Presence

7

the general interaction behaviour between two (or more) parties. Homans (1958) and Blau (1964) formally described individual interactions between people by using the concept of exchange. They asserted that all social relations can be seen against the background of a social exchange in which individuals offer and accept (or reject) both tangible and intangible activities (Homan, 1961). Depending on their quality and depth, immaterial activities during the exchange of interpersonal information can be held in high esteem by the other person, which, in turn, encourages them to give back corresponding information (Worthy et al., 1969; Jourard, 1971). This approach assumes that people interact in order to derive as much benefit as possible from their encounters or at least a higher benefit than the costs brought in. In this way, the individual information cost–benefit trade-off plays an essential role in the social exchange theory (Homans, 1961). Blau (1964) assumed that social exchange is mostly limited to actions that are conditioned by a rewarding response from others. If these expected reactions are not achieved, it can lead to the termination of the social interaction. This means that if one of the parties feels that the costs exceed the benefits of an interaction and that the personal reactions are no longer worthwhile, then a continuation of the interaction is irrational; therefore, it is usually not continued. Homans (1974) further assumed that all sources of benefits and costs are important for the exchange of behaviour—not only those that are expected or actually received by a person in an interaction but also those that flow in casually and unconsciously. Both Homans (1961, 1974) and Blau (1964) conceptualised individual rewards, psychological pleasure and social benefits as desirable, and they viewed costs and social and psychological punishment as detrimental to the exchange. Drawing on these social exchange approaches, Turner (1988) addressed the importance of social interaction. Successful interpersonal interaction can be determined by three constituent characteristics: motivational, interactional and structuring. This means that, on the one hand, both parties should be sufficiently energised and mobilised during the interaction to want to complete it successfully, but on the other hand, basic interactional skills also play a role, such as how a party uses gestures to signal something or how these are interpreted. Structuring properties are organisational skills that bring order to an interaction with regard to time and space. According to Turner (1988), within a technology-oriented frontline employee–customer interaction, motivation, i.e. keeping people energised and mobilised, is as important to the retailer as adhering to or not deviating from a certain interaction structure. If additional technologies are infused into an interaction process that the customer is already used to, traditional gestures or signals can be misinterpreted, as these technologies may distort the customer’s attention and lead to an unclear understanding of the information provided by the frontline

8

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employee (Giebelhausen et al., 2014). Thus, not only can the learned structure of the interaction be perceived more negatively through this infusion, but customers may enter a technology-oriented service encounter with less motivation for the interaction to be successful. The infusion of technologies in a service encounter under the condition that the interaction process between the frontline employee and the customer is not disturbed but rather enriched with additional information must be efficiently moderated or facilitated by the frontline employee in the interest of both parties. The privacy calculus theory traces its origins to the social exchange theory (Laufer and Wolfe, 1977; Culnan and Armstrong, 1999), and it focuses on customers’ weighing of benefits and costs when it comes to the potential disclosure of personal information as part of a purchasing process. Customers who are asked or required to disclose personal data must conduct an intuitive benefit–cost analysis/accounting in which they assesse the relationship between the benefits resulting from the disclosure and the associated costs, such as the loss of privacy (Smith et al., 2011; Kokolakis, 2017). This means that customers’ self-disclosure behaviour and their willingness to disclose data are largely determined by the net outcome of the benefit–cost trade-off (Dinev and Hart, 2006; Xu et al., 2011; Jiang, et al., 2013; Kokolakis, 2017); however, a benefit may be anticipated even if the consequences of the disclosure are not clear from the outset. The privacy calculus theory has been widely used in privacy research to explain the impact of conflicting forces on customer privacy (Laufer and Wolfe, 1977; Stone and Stone, 1990; Culnan and Armstrong, 1999; Xu et al., 2009; Li, 2012). As a whole, this theory can be seen as a form of compromise between different parties. Li (2012) showed that the concerns of individuals regarding the use of their data by third parties follow an analogous pattern even if the most diverse, person-specific criteria influence them. External actors with an interest in personal data can be organisations (service providers), third-party organisations, private contacts, contacts from the work environment, intelligence services or even criminal third parties (Sanchez et al., 2012; Conger et al., 2013). In principle, the disclosure of personal data to external actors is accompanied by a loss of privacy (Karwatzki et al., 2017b). Research on self-disclosure has identified financial rewards (Premazzi et al., 2010), entertainment (Krafft et al., 2017) and personalised services (Chellappa and Sin, 2005) as the fundamental benefits and reasons to self-disclose during an exchange (Smith et al., 2011). However, when the perceived costs outweigh the benefits, it can result in a refusal to provide personal information, misrepresentation, direct complaints, negative word of mouth or even the termination

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of a business relationship (Martin and Murphy, 2017). Research on online privacy concerns has identified a wide range of antecedents, such as the perceived audience (Teubner and Flath, 2019), internet experience (Bellman et al., 2004) and culture (Milberg et al., 2000; Bellman et al., 2004), and socio-demographic characteristics, such as age (Bellman et al., 2004), gender (Bellman et al., 2004) and income (Graeff and Harmon, 2002). Some studies have also suggested that strict policies and government regulations (Lwin et al., 2007) and privacy information (Lutz et al., 2018) can lead to increased individual privacy concerns. It should be noted that any perception of costs and benefits is individual in nature and also depends on the privacy preferences of the individual. Consequently, calculation results and thus privacy concerns vary from customer to customer (Hong and Thong, 2013; Karwatzki et al., 2017a). Specifically, according to Laufer and Wolfe (1977) and Smith et al. (2011), privacy concerns are closely related to the environment/situation as well as interpersonal relationships. While the reasons for privacy concerns are wide-ranging, it is believed that increasing social presence within the service process may help reduce these customer privacy concerns (Li, 2012). Zimmer et al. (2010) were able to show that customers’ sense of digital social presence helps to mitigate privacy concerns. In addition, the behaviour of a service employee/service provider or the infusion of a technological solution in the service process can also change customers’ concerns about the provision of personal data or increase the perceived costs. It is important to maintain a balance between customers’ perceptions of costs or concerns and the potential benefits arising from the disclosure of personal data. If this balance is not achieved, i.e. if the customer perceives the costs of disclosing data to be higher than the expected added value, then less or no information will be shared by the customer. This dissertation argues that the theory of social presence is relevant in understanding the interaction between the customer and technology and the perception and reaction of customers when technologies are present in a service encounter. Li (2012) saw social presence as an indicator of the perception of human traits within an interaction. According to Short et al. (1976), the social presence theory states that a medium or technology has the ability to generate social presence. How strong this social presence (i.e. the feeling of a person’s presence) is depends on the medium’s ability to present information, such as facial expressions or voice, and how the interaction via the medium is perceived as personal by the addressee. Short et al. (1976) pointed out that there are different degrees of social presence and that the degree of social presence should/should not correspond to the level of interpersonal involvement required for a particular task. Gefen and Straub (2003) used the theory to illustrate the customer perception of an online shop and the importance of its perceived social presence. If a customer

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Motivation and Orientation

believes that a system has the characteristics of social presence, then traditional interpersonal criteria, such as trust in the shop, can be established more easily. Experience with these technologies also plays an important role. In line with the social presence theory, Grewal et al. (2020) suggested that different innovative PoS technologies can emit different degrees of social presence. In this work, social presence not only refers to a specific technology but also assumes that it can exist in the connection between humans and technology. Following Grewal et al. (2020), it can be argued that this connection can also be viewed differently by the customer, depending on the perceived degree of the social presence of the technology and the ability of the service employee/service provider to combine human and digital social components adequately and efficiently.

1.4

An Integrated Typology of Technology-Oriented Customer Touchpoints

According to the current literature in this field, the integration of service-oriented digital touchpoints is as diverse as it is complex (Larivière et al., 2017; van Doorn et al., 2017). Even though technological innovations can be seen as opportunities to generate a competitive advantage, these new approaches can create challenges for both physical and online services/shopping (Piotrowicz and Cuthbertson, 2014). These challenges are particularly felt by smaller or inexperienced companies and medium-sized retailers that lack the human and financial capital to manage this change (Nguyen et al., 2015). Therefore, it is important to understand how technology-oriented customer touchpoints can be efficiently and effectively integrated into current processes without incurring excessive costs or deterring customers due to improper or unprofessional integration or handling. The service encounter at the PoS no longer only involves an interaction between the employee and the customer but also includes technology for a tripartite interaction (Bitner et al., 2000; Parasuraman, 2000). Recent literature has emphasised the importance of integrating a ‘human touch’ into digital services and digital customer touchpoints to stabilise the customer–retailer relationship (Herhausen et al., 2020). A barrier-free level of interaction needs to be achieved between the customer and the service employee/service provider (Giebelhausen et al., 2014), in which the service employee/service provider can be perceived as both competent and warm (Scott et al., 2013; van Doorn et al., 2017). Infused technology in the service environment can be any combination of hardware, software, information or networks that supports the co-creation of value between a service employee/service provider and a customer (Yadav and Pavlou,

1.4 An Integrated Typology of Technology-Oriented Customer Touchpoints

11

2014; Huang and Rust, 2018). Technologies are integrated into the service process for different reasons, such as optimising the information base and better customisation. They can also speed up the exchange process between the service and customer by making it more flexible and thus simplifying it (Ahearne et al., 2008; Ahearne and Rapp, 2010; de Keyser et al., 2019). It has also been shown that integrated information within a technology-oriented interaction can be perceived as more objective, comprehensive and rich (Alexander and Kent, 2020; Riegger et al., 2021). With regard to upgrading a service experience or a product with additional visual components, technologies such as VR- or AR-oriented applications can improve the entire service experience for customers by providing different ideas about using a product or different options through the applications (Larivière et al., 2017; Marinova et al., 2017). Fundamentally, the increased use of technology has led to a change in the service environment, service delivery and service experience (Ostrom et al., 2015). A service encounter does not necessarily have to take place between humans, as it can include self-conditioning technologies (Larivière et al., 2017). According to the salesperson–customer interface technology continuum (Ahearne and Rapp, 2010), there are five forms of assistive technology integration related to service: salesperson-specific, salesperson-centric, salesperson–customer-shared, customer-centric and customer-specific. Technology integration takes place within a continuum, with salesperson-oriented technology on one side (wherein the technology is solely used by the frontline employee, and the customer does not have any contact with the technology at all) and customer-oriented technology on the other side (wherein no involvement by an employee is necessary, and the customers use the technology and its features by themselves). Larivière et al. (2017) defined a service encounter as any interaction between the customer and the service employee/service provider that is created by a service system composed of interconnected technologies (either company-owned or customer-owned) and human actors (employees and customers) in a physical or digital environment. In fact, companies in the digital space have increasingly relied on service applications based on AI (Fernandes and Oliveira, 2021). Aside from processing large amounts of data, AI can artificially generate voices and interact with customers without human intervention (Schweitzer et al., 2019; Valenzuela et al., 2019). It can communicate with customers on a social and interpersonal level by giving them the feeling of an actual, human-based service encounter (Araujo, 2018; Han, 2021; Poushneh, 2021). However, studies on the relevance and impact of technology-oriented service encounters have pointed out the challenges of these services due to a lack of human characteristics and skills,

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such as the use of body language (Beck et al., 2013), gazes (Admoni and Scassellati, 2017), motions (Castro-González et al., 2016) or humour (Zhang et al., 2021). Innovative technology-based service solutions, such as SVAs (smart voice assistants), not only facilitate market access of products or increase productivity but also have the potential to increase the knowledge of employees/service providers, thus leading to improved offerings of more appropriate, personalised products and services (Huang and Rust, 2018). Hunter and Perreault (2007) and Rust and Huang (2014) mentioned the potential of improving and stabilising interpersonal relationships between frontline employees and customers through the infusion of technology in service interactions. According to Hunter and Perreault (2007), the infusion of technology into a service can potentially improve the relationship between service employees and customers because customer contact can be personalised. Furthermore, it has been shown that the use of PoS technology during service interactions can deepen customer relationships (Huang and Rust, 2014) as well as customer loyalty (Srivastava and Kaul, 2014). Dyadic, interpersonal interaction should be a primary focus in this context, as it significantly influences customer satisfaction (Jamal and Adelowore, 2008; Bolton et al., 2018). When applied appropriately, technology infusion can also lead to more effective and enjoyable interactions (de Keyser et al., 2019). The perceived quality of service largely depends on customers’ prior experience with such technologies. Gelderman et al. (2011) showed that technology-experienced customers have a lower need for personal interaction, as they seem to prefer the technology in question. By contrast, customers without experience in the PoS technology usually opt for traditional service. Furthermore, it has been emphasised that different forms of technology infusion create different degrees of social presence (van Doorn et al., 2017; Grewal et al., 2020). Traditional self-service technologies, such as self-service checkouts and in-store kiosks, which can be operated completely autonomously by the customer and therefore almost completely replace the service employee, tend to have low social presence (Grewal et al., 2020). Van Doorn et al. (2017) separated technology-based services into human and automated social presence, while Grewal et al. (2020) focused on the infusion of technology in a shop by distinguishing between social presence and convenience. Direct technology infusion can relieve the service employee of essential product-oriented tasks, thus promoting interpersonal interaction (Hilken et al., 2017; Keyser et al., 2019). Pure self-service technologies cannot reach customers on this social level due to their lack of human interaction skills (van Doorn et al., 2017). Research has also shown that customers want to explain and discuss their

1.4 An Integrated Typology of Technology-Oriented Customer Touchpoints

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situation and share their potential anger with others, which is not possible with traditional self-service technologies (Huang, 2017; Grewal et al., 2020). Against this backdrop of the increased incorporation of technologies into service, Gremler (2017) emphasised that customers’ preference for interacting with a frontline employee can be attributed to three key aspects: (1) the lack of emotional expressions of technologies during service failures, (2) the inability of technologies to meet the customer at the right emotional level and (3) the creative weaknesses of these technologies. One result can be the build-up of psychological barriers with the customer (Giebelhausen et al., 2014). Reinders et al. (2008) showed that customers speak negatively about service providers (retailers) or break off relationships when they are forced to use self-service technologies. In fact, customers prefer to have the choice of which form of service they can use (technologyoriented, technology-based or technology-free). It is only when the use of a PoS technology is deemed meaningful and effective by customers that its inclusion in a service encounter at a brick-and-mortar retailer is considered worthwhile for both parties (Grewal et al., 2020). Consequently, in order to build a relationship between the service provider and the customer, a kind of hybrid approach to technology infusion in technology-oriented customer touchpoints, which includes some form of self-directed action, may be relevant. According to Li (2012), customers’ perceptions of social presence are directly related to their willingness to disclose information about themselves. This dissertation analyses customer interactional and data-sharing behaviour in different customer touchpoints by focusing on the issues of the privacy calculus theory and the social presence theory. It explores the function of technology as a service enabler rather than service substitute by considering the level of customer service interaction as a central element of the service encounter (Solomon et al., 1985; Surprenant and Solomon, 1987; Grewal et al., 2020), This dissertation also provides a framework that brings together the two central strands of the privacy calculus and social presence based on the typologies of Grewal et al. (2020) and van Doorn et al. (2017). In their approach, Grewal et al. (2020) systematised in-store technologies according to the degrees of social presence and convenience perceived by the customer. Van Doorn et al. (2017) examined social presence more explicitly by categorising service-oriented technologies according to the degree of automated or human social presence. It is divided into four quadrants, which are aligned with the individual importance of social presence and privacy calculations as well as the essential interplay between these two aspects. The degree of social presence is marked on the yaxis and the degree of privacy calculus on the x-axis. The y-aixs indicates the degree of interaction between the technology and the service employee/service

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Motivation and Orientation

provider in relation to the customer’s social or interpersonal perception. Grewal et al. (2020) and van Doorn et al.’s (2017) understanding of social presence slightly departs from Short et al.’s (1976) original theory in which social presence is primarily perceived through technology. Nonetheless, this dissertation assumes an interplay between the two components, i.e. technology and the service employee/service provider, and maps the perception of social presence within the framework of a superordinate service. Depending on the form of integration/interplay of technology and the service employee/service provider, different social or interpersonal perceptions by the customer can result. On the x-axis, the degree of the privacy calculus is emphasised differently in different service constellations. Depending on the interaction of the parameters (technology and service employee/service provider), customers can apply a different degree of privacy calculus. In sum, this dissertation aims to improve the understanding of the interplay between social presence and privacy calculus in technology-oriented customer touchpoints. The four quadrants are low privacy calculus–low social presence (LoPC— LoSP), low privacy calculus–high social presence (LoPC—HiSP), high privacy calculus–low social presence (HiPC—LoSP) and high privacy calculus–high social presence (HiPC—HiSP). In each of these quadrants, the relationship between the service employee/service provider, technology and the customer is shown, based on Parasuraman’s (1996) ‘pyramid model of services marketing’. Studies on the use of service technologies have increasingly taken this approach and pointed out the importance of these relationships and the relevance of the individual consideration of technology, especially when it comes to examining or concretising the role of the employee (Froehle and Roth, 2004; de Keyser et al., 2019). Technology can be a direct point of contact for the customer and significantly guide the service process or where the service process actually takes place (LoPC—LoSP and HiPC—LoSP) with a service-supporting or servive-accompanying element (LoPC—HiSP and HiPC—HiSP). Mostly, though, the technology only supports the employee and the customer (dashed line). On the one hand, in the LoPC—LoSP quadrant, there is a low degree of social presence and a low degree of privacy calculus, which means that the service interaction is primarily via technology. This takes a central position and functions in the sense of providing information even when the individual use of and approaches to these technologies are different. An employee is not needed at this point to provide the customer with the relevant service. Moreover, the potential data disclosure by the customer does not play a significant role here, as it is mainly about the communication of product/service-related content. By contrast, the HiPC—LoSP quadrant shows a low degree of social presence but a high

1.4 An Integrated Typology of Technology-Oriented Customer Touchpoints

15

degree of data protection calculation. It focuses on the customer’s direct contact with a form of technology that exudes little social presence. The technologybased interaction between the customer and the frontline service can optimise service and product perception, and the potential generation of customer information also plays an important role in meeting customer needs in a sustainable way. However, as soon as customer data or access to customer data by the retailer becomes an issue and customers are actively involved in this process (e.g. specific questions during service), they naturally weigh the added value against the costs of passing on data. These calculative approaches are commonly utilised for online shopping and last-mile delivery, and social presence is largely excluded from the investigations. On the other hand, a higher degree of social presence is found in the quadrant of LoPC—HiSP, which is mainly due to the direct integration of a human employee in the service process. Particularly in stationary retail, this person takes on a special role, which is important to investigate. At this point, data protection does not play a significant role yet, as it is solely about the perception of the employee in a technology-oriented or technology-based service encounter. The HiPC—HiSP quadrant also sees the employee as the central point of contact, but in this area, the importance of customer data protection needs to be magnified. Both the high degree of social presence and the privacy calculus are considered here, and the potential of the employee in this interaction is examined on an individual level. Each of the quadrants contains one to three individual essays that build on one another. Therefore, the question of the customer’s perception of technologyoriented customer touchpoints can only be answered by looking at the four quadrants together. Only through this differentiated presentation with individual fields of application can an overarching picture of this topic be provided: In LoPC—LoSP, the focus is on the technology-based, physical service encounter. An overview of seven technologies used at the PoS for service optimisation is provided here. These technologies are classified in essay 1, which functions as a starting point for the analyses of social presence and the privacy calculus. In LoPC—HiSP, the focus is on the service-oriented, physical service encounter. Based on the insights from three clusters in essay 1, essays 2 and 3 focus on the interaction between the frontline employee and the customer under the influence of a service-oriented PoS technology. Building on essay 1, which provides a general understanding of how customers perceive different PoS technologies in physical frontline services, essay 2 focuses on the relevance of social presence with regard to different forms of technology involvement in the service

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Motivation and Orientation

encounter. The customer’s perception of social presence or social interaction is a key aspect in the evaluation of a service in relation to technology adoption; however, the specific way in which a technology is integrated into that service is important. Furthermore, essay 3 denies the frontline employee as the central point in the service and understands technology as such. In contrast to essay 2, it argues that technology is the primary service feature. The main aim of the essay is to explore the customer response when a frontline employee merely accompanies, rather than actively manages, a technology-based service. It turns out that the emphasis on customers’ perceived social presence seems to be a key criterion in technology-oriented frontline services. In HiPC—LoSP, the focus is on the data-oriented, digital service encounter and last mile delivery. By leaving physical retailing behind, the customer’s privacy calculus becomes the centre of interest, and social presence is largely excluded. To gain an understanding of the privacy calculus, it is differentiated and detached from social presence. Essay 4 asks about the relevance of transparent communication for the utilisation of potentially disclosed data during online product presentations, while essay 5 examines customer perceptions and reactions to service- and data-related factors in relation to customers’ intentions to provide digitally transmitted access to their own homes in last-mile product delivery. In HiPC—HiSP, the focus is on data-oriented digital and physical service encounters. Essays 6 to 8 combine the social presence and privacy calculus approaches by focusing on a customer’s trade-off during a human-centred service encounter at a physical PoS. To bridge the gaps between essays 4 and 5 and essays 7 and 8, an analysis of the combination of both approaches in the context of digital/voice commerce was first conducted. Specifically, essays 7 and 8 focus on the impact of technology adoption on customers’ data disclosure behaviour, both in terms of specific forms of technology and different customer incentives. This dissertation is interested in whether the lessons learned from the previous studies are transferable to other technology-infused/technology-based customer touchpoints. Essay 7 uses two different technologies or technology-oriented PoS services from the first essay and examines customers’ data disclosure behaviour. Essay 8 extends the previous study by focusing on specific incentives within human frontline services and further analyses the relationship between data disclosure and data accuracy (Figure 1.1).

1.4 An Integrated Typology of Technology-Oriented Customer Touchpoints

17

HIGH

LoPC – HiSP

HiPC – HiSP

Service

Service

Level of Social Presence

Technology

E2 & E3

E6 – E8

Customer

Service Employee/ Service-Provider

LoPC – LoSP

Customer

Service Employee/ Service-Provider

HiPC – LoSP Service

Service Technology

Technology

E1

E4 & E5

Service Employee/ Service-Provider

LOW

Technology

Customer

Service Employee/ Service-Provider

Level of Privacy Calculus

Customer

HIGH

Figure 1.1 Social Presence—Privacy Calculus Typology of Technology-Oriented Customer-Touchpoints

2

Structure and Content of the Essays

2.1

Focus of the Essays

The aim of this dissertation is to present different perspectives on customers’ perceptions and behaviour in the context of technology-oriented customer touchpoints at and beyond brick-and-mortar retailing. Eight empirical studies examine how customers approach and interact with different types of thechnology-oriented services. The focus of this dissertation is on different forms of service-related technologies and the importance of human service employees in this context. A main goal is to investigate the reaction of customers to these services with regard to different phenomena. The individual essays here can be seen as building on each other overall, with some essays leaving the framework of stationary retail and focusing on customer behaviour in the online shopping context. It is assumed that a deeper understanding of the relevance of technology-oriented customer touchpoints from the customer perception can only take place through the combination of service-related analyses in stationary retailing, in which the role of the human frontline employee is in the foreground, with analyses in online retailing, in which the social interaction with such a person no longer plays a role and customers basically only interact with a (maximally human-like) technology. In addition, most essays include a specific approach to exploring customers’ willingness to disclose personal information in such a service environment. More specifically, the dissertation focus contrasts the influence of social presence theory and privacy calculus theory in terms of customer behaviour. Based on the four quadrants of the ‘Social Presence—Privacy Calculus Typology of Technology-Oriented Customer-Touchpoints’, both theoretical approaches are initially analysed independently, but are merged at the end in essays 6 to 8. In

© The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2023 T. Röding, Technology-Oriented Customer Touchpoints in Context of Services in Retailing, Handel und Internationales Marketing Retailing and International Marketing, https://doi.org/10.1007/978-3-658-40554-0_2

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Structure and Content of the Essays

this context, the eight essays consequently vary in research focus and design. Furthermore, all essays derive theoretical and practical insights (e.g. for marketers, companies, customer protection organisations or the customers themselves) on the topic of technology-oriented customer touchpoints. Furthermore, future research recommendations are presented based on the findings of the essays. Table 2.1 provides a detailed overview of the eight essays by introducing the corresponding theoretical and touchpoint objectives, the research design of each essay, and the form of analysis used in the essays. Within the different methodological approaches, a total of 4,069 respondents participated. Apart from essays one and five, all essays used a between-subjects experimental design. In section 2.2 a brief summary of the research focus, the implementation of the practical and scientific relevance of the essays, and the basic research question(s) is offered. It also presents the methodology used and provides an overview of the main findings and practical implications of the eight individual essays. Table 2.1 Overview of the Essays Theoretical Objective

Touchpoint Objective

Research Design

Analysis

Essay To Generally 1 Evaluate Customers’ Perception of different PoS technologies in Context of the WebQual approach and uses and gratifications theory

With specific Online survey (N regard to seven = 830) PoS technologies in Physical Service Encounter

Similarity-Matrix via Multidimensional Scaling combined with property fitting approach via SPSS.

Essay To Specify 2 Customers’ Response in Context of Social Interaction Theory and Information Integration Theory

With specific regard to the Type of Technology Infusion in Physical Service Encounter

Repeated measures MANOVA, and linear regression-based mediation- and moderation-analysis by means of SPSS.

Two multi-factorial between-subject quasi-experimental design; Online survey (N = 944; N = 465)

(continued)

2.1 Focus of the Essays

21

Table 2.1 (continued) Theoretical Objective

Touchpoint Objective

Research Design

Analysis

Essay To Specify 3 Customers’ Response in Context of Social Presence

With specific regard to the Integration of a Human Frontline Employee in Technology-Based Physical Service Encounter

A one x two factorial between-subject quasi-experimental design; Online survey (N = 222)

Repeated measures ANOVA, and linear regression-based mediation-analysis by means of SPSS.

Essay To Specify 4 Customers’ Response in Context of Information Processing Paradigm and Privacy Calculus Theory

With specific regard to the Information Transparency in Online Product Presentation

A one x two factorial between-subject quasi-experimental design; Online survey (N = 142)

Repeated measures ANOVA, and linear regression-based mediation-analysis by means of SPSS.

Essay To Specify 5 Customers’ Response in Context of Privacy Calculus Theory

With specific Online survey (N regard to the = 343) Providing of Digitally Transferred Access Permission in Unattended Home Delivery Services

Essay To Specify 6 Customers’ Response in Context of Social Presence Theory and Communication Accommodation Theory

With specific regard to Different Types of Digital Voices in Terms of Smart Voice Assistance

PLS-SEM

A two x two x two Repeated measures factorial ANOVA by means between-subject of SPSS. quasi-experimental design; Online survey (N = 439)

(continued)

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2

Structure and Content of the Essays

Table 2.1 (continued) Theoretical Objective

Touchpoint Objective

Research Design

Analysis

Essay To Specify 7 Customers’ Response in Context of Role and Script Theory

With specific regard to the Infusion of different types of PoS technologies in Physical Service Encounter

A three x two factorial between-subject quasi-experimental design; Online survey (N = 322)

Repeated measures ANOVA, and linear regression-based mediation- and moderation-analysis by means of SPSS.

Essay To Specify 8 Customers’ Response in Context of Privacy Calculus Theory

With specific regard to different types of Customers’ Incentivation and Technology Infusion in Physical Service Encounter

A three x two factorial between-subject quasi-experimental design; Online survey (N = 362)

MANOVA, and linear regression-based mediation-analysis by means of SPSS.

2.2

Abstracts of the Essays

2.2.1

Essay 1. A Classification of Information-oriented Point of Sale Technology in Relation to Customer Perception

Research Focus. Point of Sale (PoS) technologies are not only incredibly widespread these days, but they are also capable of mastering different requirements. Indeed, PoS technology can accelerate payment processes via digital payment systems, simplify product presentations through the use of digital screens or provide customers with specific or individualised information in relation to a product. For example, they can alert customers to products in other colours, shapes, patterns or sizes, or they can allow them to undertake this filtering process on their own, eliminating the need to swiftly involve an employee. However, a categorisation of PoS technologies based on customer perception is missing from scientific and practical discussions. PoS technologies are typically classified based on technological characteristics or fields of application; nevertheless, when it comes to investigating how customers use them or which elements might promote their adoption, it is important to know which characteristics are particularly relevant and important from the perspective of customers.

2.2 Abstracts of the Essays

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In relation to three more recent approaches to PoS technology systematisation, this research empirically categorises PoS innovations from the customer’s point of view and examines what influence their perceptions of ease of understanding, intuitive operation, functional fit-to-task, information quality, tailored information, innovativeness and enjoyment have on such systems. Method, Findings and Implications. We investigated PoS technologies that are information-oriented and contain an element of interactional capability. As a first step, we selected seven information-oriented PoS technologies for the research: a QR-code machine, a mobile device, a standalone kiosk, an interactive display, a smart shelf, a virtual reality (VR) device and an augmented reality (AR) display. These PoS technologies were used to generate a similarity matrix by means of multi-dimensional scaling (MDS). Data was then collected as part of an online study (N = 830). Subsequently, three independent clusters of PoS technologies were identified: (A) comprehendible PoS technologies, (B) information-integration PoS technologies and (C) entertainment-related PoS technologies. The results of a property fitting analysis were then integrated, which included different influencing factors that were developed based on the uses and gratification theory (Blumler and Katz, 1974) as well as information integration theory (e.g. Anderson, 1962) and the WebQual approach (Loiacono et al., 2007). While doing this, we empirically classified and clustered PoS technologies based on customers’ views of these innovations. Consequently, we identified two distinguishable dimensions: (1) the degree of complexity of the PoS technology and (2) the degree of innovativeness of the PoS technology. Our results address the potential for retailers to introduce the aforementioned technologies and also indicate the willingness of customers to deal with information-oriented technologies at the PoS. The findings show that customers’ assessments of PoS technology differ significantly. Brick-and-mortar retailers should ensure that adequate examples of these technologies are provided to satisfy customers’ usage needs in relation to their individual goals. The search for both haptic and digital information, which is played out via the medium, may also be relevant when choosing PoS technology, since not every device can generate the same amount of added value for the customer. This is especially true when product quality or the personalisation of the information plays a role (and no employee is available on site), meaning mobile devices or QR codes should be made available instead of permanently installed technologies. Through these mediums, it is possible to obtain information in two ways: by walking/moving around the product and touching it and by using the device to obtain additional (digital) information. On the other hand, in relation to product usability, it is important that the POS technology is above all easy to understand and utilize,

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which is the case with the likes of smart shelves, standalone kiosks and interactive displays. With such examples, a more intuitive handling of technology has been foregrounded. Conversely, for customers with an affinity for technology and innovation, an AR or VR-oriented solution may be offered, even if the information content is secondary to the hedonic way in which the product is used by them. However, the purchase price of these technologies must also be taken into account as devices like AR mirrors are in a different financial sphere than the installation and programming of a QR code. Depending on the relevance and necessity of the wealth of information, the retailer must decide individually whether tactility, digital and haptic information integration or enjoyment should also be concentrated on.

2.2.2

Essay 2. How to Infuse Mobile Technologies in Frontline Service Encounters: An Experimental Analysis of Customer Responses

Research Focus. The frontline employee must not only deal with the challenges of a customer who is significantly better informed (e.g. through the ‘online world’), but also with the constantly growing influence of digital media on the physical Point of Sale. Particularly when it comes to optimizing service and thus integrating digital service support technologies such as a mobile tablet, many physical retailers quickly reach their limits, especially when it comes to providing customers with information more quickly, competently and individually. Studies also indicate that it is not only the integration of these mobile devices per se that improves the quality of service, but also their integration within this interaction that is decisive when it comes to the perception of the frontline employee by the customers. This technology can even act as a barrier within a traditional interpersonal and dynamic interaction. Recent literature discusses the increasing relevance of technology infusion in frontline service encounters. In technology-infused frontline service encounters, the human-based service depicts a high uncertainty. Yet, no empirical evidence is available on the comparison of different types of technology infusion (technology-free vs. technology-facilitated vs. technology-assisted) within a frontline employee-orientated service encounter. Building on existing approaches of technology-infused services, this study was intended to broaden the understanding of the optimal type of technology infusion and human interaction in context of customers’ trust towards the frontline employee and their willingness to pay. In summary, this essay addresses the research question of the extent to

2.2 Abstracts of the Essays

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which different types of technology infusion within physical retailing influence customers’ service- as well as product-perception. Method, Findings and Implications. Drawing on social interaction theory and information integration theory, this paper empirically investigates different types of technology infusion within frontline service encounters. To do so, two quasi-experimental online studies (study 1: N = 944; study 2: N = 465) were conducted. Results show that technology infusion within the service encounter has a negative influence on customers’ trust towards the frontline employee, but a positive influence on customers’ willingness to pay. Study 1, moreover, shows a mediating influence of customers’ perception of frontline employees’ competence. Findings emphasize that customers place more value on a technology-facilitated encounter than a technology-assisted service. Study 2 confirms previous finding and illustrates that the number of infused devices seems to amplify previous results additionally, by decreasing customers’ perception of trust and increasing their willingness to pay. Overall, findings show that technology infusion affects the perceived level of customer-employee interaction, which in turn influences customers’ trust towards the frontline employee, with the form of technology infusion being crucial to the difference in customer perceptions. Interestingly, technology infusion increases customers’ willingness to pay, but decreases trust towards the frontline employee and negatively impacts satisfaction with the frontline service. Moreover, a clear mediation impact of customers’ perceived competence of the frontline employee on trust towards the frontline employee and satisfaction with the frontline service could be shown. Based on the findings, this paper derives implications for retail managers on different levels. Since the customer perception of the competence of frontline employees in using a technology is of high relevance for the customer, the retailer should pay more attention to the training of employees in dealing with these technologies in interaction with customers, because of the perception of service competence and other relationship-building criteria such as trust. In addition, competent handling of these technologies and customer perception of them can also affect customers’ willingness to pay and thus business success.

2.2.3

Essay 3. The Role of the Frontline Employee in Technology-Based Service Encounters

Research Focus. The importance of sales personnel in the stationary, brick-andmortar retail store as a factor influencing customer behaviour has been widely discussed in the literature for years. Specifically, the analysis of the interaction

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between the frontline employee and the customer plays a decisive role. When a business optimises its service offerings with the help of innovative technologies, the frontline employee’s involvement often does not align with the customer’s requirements or desires. In recent years, more Augmented Reality (AR) and Virtual Reality (VR)-oriented service offers have been integrated into the physical Point of Sale (PoS). An example of this is in clothing stores where changing rooms are being digitised; another is with the use of humanoid robots (such as Pepper), which are taking over more tasks traditionally performed by human, frontline employees. Customer acceptance of these PoS technologies seems to be on the rise, and the added value for the customer is becoming ever more extensive and tangible. During technology integration at the physical PoS, the role of the frontline employee changes, raising the question of how the inclusion of human service will work on an ever more digital sales floor and whether interaction with the human service employee is still necessary or desirable at all. Customers are becoming more routinised in their use of digital services — not only in the online shopping environment, but also in physical retail. Although the impact of technology on retail services has been widely studied, there is a lack of studies on the customer’s perception of the presence of the human frontline employee in a technology-based retail service. The research question this essay addresses is: to what extent is it advisable for the retailer for their customers to solely use an innovative technology at the PoS, and under what circumstances is the frontline employee accepted as a supporting element? Method, Findings and Implications. Through an online survey (N = 222), we found that while the presence of the employee reduces the expected quality of information within the service, customers’ privacy concerns about retailers’ data processing practices decrease. Customers appear to prefer the technology-based service in terms of ‘seeking and receiving’ information, but value the presence of the frontline employee in terms of the potential ‘collecting and processing’ of information by retailers. The survey’s results also showed a mediating influence of discomfort with the service and customers’ perceived social presence within the service. Moreover, the findings of this research deliver opportunities for future research and can lead to management implications. In fact, the frontline employee still could optimally design a technology-based service encounter for the customer, making it simpler and less stressful. Nevertheless, the employee should also know his/her (new) role within a purely technology-based service and give the customer the freedom to use this technology completely on their own.

2.2 Abstracts of the Essays

2.2.4

27

Essay 4. The Relevance of Corporate Information Transparency of the Use and Handling of Customers’ Data in Online Product Presentation

Research Focus. Companies are increasingly concerned with ‘transparency strategies’ within product presentations. Due to the accessibility of product information in the online sector, the dissemination of central product-oriented information has long been an important topic in order to give the customer the feeling that the right product is being purchased, especially online. However, the situation is different when it comes to the possible use of data disclosed by the customer.However, since customers are also demanding more and more information in this area or are looking for it online, some companies are also communicating such information more and more openly. In contrast to product-related information, however, the degree of disclosure can have a deterrent effect. More and more companies are trying to balance between the use of information transparency to attract new customers by presenting themselves as open companies and the associated risk of losing customers, as disclosing certain information could trigger negative sentiments. Being transparent with certain information can make the potential buying process seem more incomprehensible to the customer. Most existing literature has focused on the different aspects of information disclosure in the case of product or price transparency. However, the impact of information transparency on data use and handling as well as the relevance of customers’ privacy concerns have been disregarded so far. In summary, this essay addresses the research questions of (1) how customers respond to a higher level of information transparency in the context of a service provider’s data use and handling in terms of purchase intention and willingness to pay and (2) the extent to which customer trust in a service provider has a significant mediating influence, and the associated privacy concerns a moderating influence, on the relationship between the level of information transparency of data use and handling and the customers’ purchase intention and willingness to pay. Method, Findings and Implications. Our research makes use of the information processing model and privacy calculus theory to manipulate service providers’ communication on information transparency regarding data use and handling in product presentations. Within the framework of an online survey (N = 142), it was found that an increase in information transparency can trigger a decrease in the customers’ purchase intention and willingness to pay. Furthermore, the empirical analysis showed a mediating influence of the customers’ trust in the service provider. Customers with high levels of general data protection concerns seemed to evaluate their purchase intention more critically when there was a low

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level of transparency, whereas, with a high level of transparency, customers with high and low data protection concerns hardly showed any difference. In terms of the implications for practice and academia, the results suggested that service providers should communicate less about data use- and handling-related information in their communication strategies when selling their products. Nevertheless, this effect should be examined in more detail with regards to other products and/or communication channels.

2.2.5

Essay 5. The Impact of IT/IS, Lifestyle and Income Related Influences on Customers’ Intention to Provide Digitally Transferred Access Permission in Last Mile Delivery—an Empirical Analysis before and during the COVID-19 pandemic

Research Focus. The number of deliveries and parcels is constantly increasing, driving demand for effective and efficient home delivery services. As the importance of secure, efficient, sustainable and contactless ‘last mile’ delivery processes grows, postal service providers are trying to optimise deliveries while researchers and suppliers are showing an increased interest in integrating information technology into these processes. Users’ perceptions of courier, express, and parcel (CEP) service providers are of primary interest, particularly their views on smart lock systems deliveries, including digitally transferred access permissions. Studies emphasise that when considering delivery services, price, delivery time, quality of service and environmental sustainability levels are critical factors for customers. Moreover, the COVID-19 pandemic has forced customers to spend more time at home and adapt their work and shopping behaviours. This study presents two perspectives on this topic through two independent data collection phases: before and during the COVID-19 pandemic. To make the last mile delivery process more efficient for customers, logistics companies and retailers, the appropriate integration of innovative technologies at the customer’s doorstep could be a sensible way forward. In this regard, the integration of innovative services offers several opportunities. Nonetheless, users’ intentions to provide the relevant digitally transferred access permissions are linked to lifestyle-related benefits, and costs related to the used information technology (IT) and information systems (IS). In summary, this essay addresses the research question: How have IT, IS, lifestyle and income influenced and impacted customers’ intention to provide digitally transferred access permission before and during the COVID-19 pandemic?

2.2 Abstracts of the Essays

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Method, Findings and Implications. Using two online surveys (study 1 (before COVID-19): N = 181; study 2 (during COVID-19): N = 162), we draw on privacy calculus theory to evaluate the effect of IT/IS-, lifestyle- and income-related influences on users’ intention to provide digitally transferred access permission in the context of last mile delivery. The results show the expected adjustment in customer behaviour during COVID-19 compared to pre-pandemic behaviour. Moreover, the studies suggest practical applications and directions for future research, focusing on the increasing significance of user perceptions of environmental sustainability and work–life flexibility. In addition to the implications for future research, this research also derived implications for practice. The results give rise to the assumption that, in particular, customers’ desire for work–life flexibility from home delivery services could be an important lever for marketers to promote such services.

2.2.6

Essay 6. MIRROR, MIRROR…on the Shelf: The Impact of Perceived Age Similarity and Gender Congruence between the Customer and the Voice of a Smart Voice Assistant

Research Focus. In traditional physical retailing, the frontline employee profits from the knowledge of how customers behave or react in specific situations within a service encounter. Because service is no longer limited to the interaction with a human employee in physical retailing, digital services via Smart Voice Assistance (SVA) are steadily increasing. With this increased demand comes the question of what criteria regarding the service employee or the voice assistant are relevant for the customer in order to generate the maximal level of serviceorientated success. In addition to missing a multi-sensory experience, a digital service is also still lacking in interpersonal abilities. Literature suggests that the accommodation of the customer is of high importance in service. The feeling of accommodating the customer can be achieved through several factors. One of the easiest ways to do this is to control the gender and/or perceived age of the other person, or match the gender or age of the customer. Furthermore, the studies indicate that the level of perceived humanity, or anthropomorphism, also gives customers the feeling of being taken more seriously or results in a different form of interaction. As research emphasizes that certain congruence might improve customers’ perception of service in physical retailing, we transfer these results into the context of SVA.

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We specifically concentrate on customers’ reactions regarding their perception of age similarity and gender congruence in comparison to the digital voice. In this relation, our paper deepens the understanding of how and why to design voices (respectively the underlying AI) of Smart Voice Assistance as customer orientated as possible. Furthermore, we address the interplay between customer and designer. In this way, we are able to combine theoretical with practical components. In summary, this essay addresses the research questions (1) how should the voice of an SVA be designed regarding the level of anthropomorphism and users’ perceived convergence with the voice in terms of age and gender, and (2) what impact has such an accommodation towards the customer with respect to the user’s willingness to interact with the voice and to disclose personal information. Method, Findings & Implications. This paper differentiates between the questions of how to design such an IT artifact and why particular design options are beneficial in order to generate the maximal level of service-orientated success. By drawing on communication accommodation theory and social presence theory, we conducted a two (synthetic vs. human voice) x two (younger vs. older voice) x two (female vs. male voice) subject quasi-experimental online study (N = 439). In doing so, we provided research results demonstrating an increase of users’ willingness to interact with the voice and to disclose personal information when accommodating the customer in respect to age and gender. With regard to the use of the findings from this study, on the one hand, companies can adapt the corresponding algorithms to the characteristics of the customers. On the other hand, this information is also important for customers and their knowledge of how to use these services or for consumer protection organizations, since certain properties of an SVA have a direct influence on the data disclosure behaviour of customers. This could be used in different areas of everyday life, such as ticket machines, navigation systems or automated service offerings.

2.2.7

Essay 7. The Influence of Technology Infusion on Customers’ Information Disclosure Behavior within the Frontline Service Encounter

Research Focus. Little is known about the disclosure of customer information at the physical PoS in the context of technology-infused services by a frontline employee. Research suggests that technologies that support service employee at the physical PoS are an appropriate way to optimise the interpersonal retail service experience and encourage customer disclosure of personal information.

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This follows from the fact that previous studies have found a significant relationship between a technology-supported service encounter and improved perceived service quality, flexibility, adaptability and personalization by service employee. These factors have been shown to promote interpersonal. Technology integration does not always lead to benefits. Studies show that the integration of technology into a service encounter can be relationship-enhancing but also perceived as an interaction barrier. Transferring the role and script theory to this context, this study assume an underlying script of employee-customer interaction that might be harmed due to technology infusion and in turn will increase customers’ risk perception towards retailers’ potential information misuse. In addition, it is important to identify the influencing factors that affect customers’ data disclosure behaviour through the customer’s perceived benefits and risks of the technology-oriented service encounter. In summary, this essay addresses the research question, to what extent do different forms of technology infusion within the (traditional) customer-touchpoint of physical retailing in context of customer-frontline employee-interaction influence customers’ data disclosure behaviour. Method, Findings and Implications. Findings of a quasi-experimental online study (N = 322) point out thedifferences between technology-infused PoS services and human PoS services concerning information disclosure by systematically manipulating the technology infusion of the service (non technology-infused service (human only) versus technology-infused frontline employee service versus self-service technology (technology mainly)). Findings indicate that the infusion of technology in a frontline service encounter prevents customers disclosing information. However, an explanation of information use and security increases information disclosure by customers when technology is not infused into the PoS service and decreases such disclosure when technology is infused into the PoS service. Furthermore, it was shown that customers’ information disclosure behaviour differs in terms of demographics, finances, lifestyle and shopping habits depending on the degree of technology infusion of the PoS service. Furthermore, a moderating effect of perceived usefulness and perceived trust of customers in the retailer’s use of the disclosed information, as well as a mediating effect of experienced emotions, could be presented. If the retailer wants to collect demographic information from the customer, a PoS service with only human assistance is advisable, whereas when collecting information about the customer’s finances or lifestyle, a technology-oriented PoS frontline service without human assistance should be used.

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Structure and Content of the Essays

Essay 8. Help Us to Help You: The Effects of Customer Incentivisation and Technology Infusion on Data Disclosure and Accuracy in Stationary Retail

Research Focus. The exchange of personal data for personalised offers or financial discounts takes place regularly in online commerce. However, research is still needed on both the impact of specific customer incentives in physical retail and the impact of technology-oriented service on customers’ willingness to disclose personal information. In recent years, research in this area has covered a range of these issues in the context of online retail. However, the perception of how a frontline employee, in combination with targeted incentivisation and technological support, affects customer willingness to disclose personal information has not yet been investigated. This paper addresses how, in contrast to online retail, most customer data cannot be collected automatically in physical shops and important service-related data must be consciously provided by customers as part of the service encounter. With the aim of increasing the amount and type of data customers are potentially willing to disclose, this research integrates and examines the impact of various explanations or incentives (monetary benefits or personalised services) and technological service support on customer data disclosure. In summary, this paper addresses three research questions: (1) What impact does an incentive in the form of a financial discount or personalisation of the service have compared to no incentive on customer data disclosure and data accuracy (accuracy of the data disclosed) in a frontline service? (2) What moderating effect does the infusion of technological service assistance have with regards to the influence of an incentive on data disclosure and its accuracy? (3) What moderating effect do customers’ overall privacy concerns and data control have with regard to the influence of an incentive on data disclosure and its accuracy? Method, Findings and Implications. We draw on privacy calculus theory, conducting a quasi-experimental online study (N = 362) to investigate the impact of customer incentivisation (monetary discount versus service personalisation) on customers’ general data disclosure behaviour and the accuracy of the personal data provided. Our findings show that the offering of an incentive does not automatically result in an increase in customer data disclosure. Results suggest that customers’ accounting of benefits and costs in regards to a specific incentive vary, particularly in regards to the accuracy of the data they provide in return. Specifically, the overall accuracy of the potentially disclosed personal data decreases in the presence of an incentive, and, while the general disclosure behaviour strongly increases in cases where a monetary discount is offered, the incentive of a personalised service is ineffective at increasing data disclosure.

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The infusion of a service technology in the form of a handheld tablet computer seems to moderate the above relationship, especially when paired with a monetary incentive. In addition, we can show the moderating influence of customers’ privacy risks and data control on the impact on customers’ data disclosure and accuracy within a frontline service. Our results provide insights into customers’ accounting practices in the presence of a human frontline employee and illustrate the implications of a particular incentivisation. A particularly important finding by this study, for practitioners, is that incentives do not necessarily induce customers to share data and information. Notably, the accuracy of the data can drop significantly when incentives are included. Retailers need to be mindful of how and to what extent such an incentive is communicated with the goal of data generation. For example, the results show that the integration of a technology in connection with a monetary incentive can be valuable; in comparison, combining such a technology with a service-oriented incentive is rather counterproductive.

3

Essays

3.1

Essay 1. A Classification of Information-oriented Point of Sale Technology in Relation to Customer Perception

3.1.1

Introduction

Research into PoS technologies has demonstrated a number of positive influences on services, such as increasing flexibility, the adaptability of frontline employees and perceived customer customisation as well as improving customer satisfaction (de Keyser et al., 2019; Ahearne and Rapp, 2010; Ahearne et al., 2008). Recent literature has highlighted that more innovative service technologies, including AR or VR in particular, enrich the customer-service experience (Larivière et al., 2017; Marinova et al., 2017), heightening the entertainment value for customers and also accelerating the purchase-decision process (Huang and Liao, 2015). From the viewpoint of the customer, PoS innovations can convey the feeling of a freer and more individualistic form of time management at the PoS, which goes hand in hand with them engaging in a higher degree of self-determination (Lee and Lyu, 2019). These technologies also aid the frontline service to improve product knowledge, adaptability/flexibility and customer-perceived levels of customisation (Riegger et al., 2021; Alexander and Kent, 2020). Furthermore, innovative PoS technologies can help to increase sales, time spent in-store and the number of products purchased by customers (Roggeveen et al., 2015). However, the introduction of PoS technology in a service environment is not necessarily associated with an improvement in overall service as interaction with or via a technology can also translate into customers becoming distracted (Giebelhausen et al., 2014; Wünderlich et al., 2013; Reinders et al., 2008). Against the background of © The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2023 T. Röding, Technology-Oriented Customer Touchpoints in Context of Services in Retailing, Handel und Internationales Marketing Retailing and International Marketing, https://doi.org/10.1007/978-3-658-40554-0_3

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numerous studies on specific PoS technologies, we analysed individual customer perceptions on the most discussed examples in recent years by classifying these innovations. In context of service research, van Doorn et al. (2017) focused on a typology of service technologies, particularly in terms of their degree of automated and human social presence. Building on this, Grewal et al. (2020) presented a conceptual categorisation of PoS technologies that includes both mainstream and futuristic innovations by focusing on different degrees of convenience and social presence for the customer. In addition, Riegger et al. (2021) systematised the current literature on PoS technologies based on certain elements, including their customer benefits, and Alexander and Kent (2020) conducted a qualitative study on the general perception of different forms of technology-oriented customer experience instore, both with regard to information support and purchase-process optimisation/acceleration. Nevertheless, a categorisation of information-oriented PoS technologies based on customer perception is missing from scientific and practical discussions. In stationary retail, it is especially important to understand which PoS technologies are most promising with regard to the individual requirements or needs of the respective customers as well as in relation to the products that are to be sold. Moreover, in terms of future introductions of practical alternatives, it is pertinent to know which PoS technologies differ from each other in the eyes of customers with regard to certain capabilities or forms of application. Our study underlines these differences and the differentiation of PoS technologies, particularly in relation to customer-based perceptions of information content, their understanding of their uses and the entertainment potential these applications/devices may possess. This investigation thus extends existing categorisation approaches to PoS technologies (Riegger et al., 2021; Alexander and Kent, 2020; Grewal et al., 2020) and fills the research gap in terms of the empirical classification of information-oriented PoS technologies with regard to customer perception. We concur with the current literature in the sense that we understand one of the main tasks of PoS technologies is to support and improve in-store customer experiences by providing (product-related) information (Grewal et al., 2020). Moreover, Riegger et al. (2021) and Roggeveen and Sethuraman (2020) pointed out that this is the specific relevance of PoS technologies in current stationary retailing with regard to what they offer the customer, while Alexander and Kent (2020) presented empirical evidence that the ability to gather information has been the most prevalent perceived benefit of PoS technologies for several years. We therefore include in our analysis only those PoS technologies that can both

3.1 Essay 1. A Classification of Information-oriented Point of Sale Technology … 37

provide information to the customer and customise the output of this information with regard to individual customer needs and questions. The PoS technology should be able to not only provide certain details to the customer but also adapt the output of this information with a view to appropriately dealing with individual customers’ wishes and questions. Additionally, they should be proficient at supporting them with an individual request and thus give the customer the feeling of influence in the sense that other pages can be opened or different modes of technology-supported service will be offered at the physical PoS should the need arise. The information that ultimately results from this interaction with the aforementioned innovation should therefore be as personalised as possible (Riegger et al., 2021). In sum, this research raises the following research question (RQ): RQ:

how can information-oriented PoS technologies be empirically classified based on customer perceptions?

By exploring the research question, our study contributes to knowledge about retail marketing in several ways. Based on the selection of seven informationoriented PoS technologies using multidimensional scaling, a similarity matrix was generated. Next, three independent clusters resulted within the matrix: (A) comprehendible PoS technologies, (B) information-integration PoS technologies and (C) entertainment-related PoS technologies. We also integrated the results of a property fitting, which was based on specific elements of Loiacono et al.’s (2007) approach to WebQual, and we drew on the uses and gratifications (Blumler and Katz, 1974) and information integration (Anderson, 1962) theories to complete our research. By doing so, we were able to provide a customer-perceptionbased empirical classification and identify two distinguishable dimensions: (1) the degree of complexity of the PoS technology and (2) the degree of innovativeness of the PoS technology.

3.1.2

Theoretical Framework

As a theoretical approach, the uses and gratification model facilitates how we understand and explain the motivations of users of innovative technologies (Kim and Lee, 2013). The theory assumes that a certain medium can be used as a means of satisfying customer wishes or interests (Keeling et al., 2007; Blumler and Katz, 1974). Within this study, we focus on PoS technology that aims to provide customers with product-related information, without the need for human employees

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to be involved in the service. Thus, specific gratification (i.e., information) can be derived from the use of these innovations. However, this gratification can also be generated by means of the way in which a technology achieves certain attributes (e.g. written on a screen, interactively via a display or in the sense of AR or VR applications). Furthermore, the familiarity and general usability of the PoS technology also plays an important role in this context (e.g. easy to understand, intuitive operationality, task-to-fit functionality but also perceived enjoyment). In addition, information integration theory helps us to understand customers’ utilisation of PoS technology as it describes how an individual integrates information from different sources in order to form a robust overall judgment on a specific topic (Anderson, 1981). According to this model, actors are interested in having full access to information; moreover, the search for or the individual coordination of information about a product requires the integration of different data sources (Gaeth et al., 1991). Based on the basic assumptions of this approach, we suppose that the possibility of integrating information using (digital) PoS technology with the physically available information in the store leads to a more balanced assessment of a certain product by the customer. We can also assume that PoS technology is to be understood as a (digital) extension of the sales area on an information-oriented level (Riegger et al., 2021; Alexander and Kent, 2020; Grewal et al., 2020). Among others, Mende et al. (2019) underlined that the integration of technology into the sales process seems to result in the products on offer being perceived as more valuable. Based on the findings of Alexander and Kent (2021) and Riegger et al. (2021), it is proposed that when using PoS technologies, the quality of the information must be optimal and a degree of enjoyment when employing said innovation plays a role. Throughout this study, we specifically focus on PoS technologies that are supporting and improving the customer experience in shops by providing productoriented information (Grewal et al., 2020). In addition, there is the possibility of individually influencing the content of the innovation in order to receive the information that is personally most important for the customer (Riegger et al., 2021). We have included in our analysis only those PoS technologies that currently provide this kind of information and are also able to react to verbal or physical interactional behaviours to offer the details that are most relevant to the customer in a personalised way. Examples that only accelerate the payment process (e.g. mobile payment) or provide information that cannot be controlled (e.g. digital price tags or digital signage) have not been incorporated into this investigation. Building on the systemisation approaches of Alexander and Kent (2020)

3.1 Essay 1. A Classification of Information-oriented Point of Sale Technology … 39

and Riegger et al. (2021), we examined PoS innovations that meet the requirements of being comprehendible, have the potential to be entertaining and are able to offer tailored content. Moreover, we focused on the listing of relevant examples by Grewal et al. (2020), Roggeveen and Sethuraman (2020), Alexander and Kent (2020) and Riegger et al. (2021), selecting the seven most-commonly-used, information-oriented PoS technologies in current PoS retailing: • The QR code, which was specifically investigated by Sundström et al. (2016), offers the option to use personal smartphones to scan a code that directs customers to a separate website that includes elements like store information, prices and finalize orders. • The mobile device, which was specifically investigated by Ahearne et al. (2008), presents current offers, store information, prices and finalises orders and so on while the customer carries/holds the device in their hands (e.g. a tablet computer that is offered within the store). • The standalone kiosk, which was specifically investigated by de Moerloose et al. (2005), provides the opportunity to obtain store information/price-related details and finalize orders, etc. on a small terminal. • The interactive display, which was specifically investigated by Roggeveen et al. (2016), highlights current offers, store information, prices and advertisement, etc. and is generally presented on a large hanging screen. • The smart shelf, which was specifically investigated by Grewal et al. (2020), advises on current offers, verifies whether products are in stock, presents prices and finalises orders, etc. on a large, hanging screen. • The virtual-reality device, which was specifically investigated by Farah et al. (2019), presents current offers, prices and advertisements, etc. while customers mostly wear VR-glasses/a headset. • The augmented-reality display, which was specifically investigated by van Esch et al. (2019), presents numerous products/offers, prices (e.g. on the customers’ body or the product itself) while someone is standing in the store and generally interacting with a digital display/mirror.

3.1.3

Procedure and Method

Procedure and Sample Data collection was conducted via an online survey in Germany. Consequently, we focused on Germany’s top-selling stationary retail sectors (Retail-Index,

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2020). Each of the participants was randomly assigned to one of these sectors, and they were asked which of the listed PoS technologies in this sector they had already been actively using at the physical PoS. The contributors were equally distributed to the different sectors: sports and outdoor (53.30% female; average age: 28.46 (SD = 8.28)), electronics (46.53% female; average age: 30.46 (SD = 11.92)), do it yourself (DIY) (45.71% female; average age: 36.18 (SD = 19.10)), jewellery (51.11% female; average age: 37.21 (SD = 19.12)), furniture (46.88% female; average age: 27.17 (SD = 6.87)), fashion (61.46% female; average age: 27.67 (SD = 9.42)), toys (55.56% female; average age: 26.01 (SD = 6.90)), pharmacy (55.38% female; average age: 30.89 (SD = 10.02)) and food (55.93% female; average age: 28.81 (SD = 8.80)). During the study, the participants were asked, ‘Please indicate which of the following PoS technologies you have already experienced [using within the respective retail sector]’. Multiple answers that incorporated the aforementioned seven information-oriented PoS technology types (plus the option to indicate ‘others’) were available for selection by each participant. The results show that customers’ experiences of PoS technologies decreased in number the more innovative the technologies were (QR code: 460 mentions; mobile device: 396 mentions; standalone kiosk: 290 mentions; interactive display: 185 mentions; smart shelf: 119 mentions; virtual reality device: 91 mentions; augmented reality display: 66 mentions and total mentions: 1,607). Overall, 830 subjects (52.53% female) with an average age of 30.31 (SD = 12.66) years participated in the study. We only integrated subjects who had already experienced at least two of the mentioned PoS technologies (71 participant were therefore extracted from the sample as they had no experience with PoS technology). Within the questionnaire, first, the participants were asked to indicate perceived similarities with regard to a number of pairs of PoS technologies that they had already come into contact with (e.g. in cases where four PoS technologies had already been experienced, six comparisons resulted). Each of the participants was supposed to evaluate one of the experienced technologies in detail in relation to the included influences. When participants had experienced less than two PoS technologies so far (210 participants), no comparison was possible; however, these contributors were still allowed to evaluate the PoS technologies they had interacted with. In instances where individuals had experience with more than one example, the PoS technology that was supposed to be evaluated was randomly picked.

3.1 Essay 1. A Classification of Information-oriented Point of Sale Technology … 41

Methods To analyse the data, we employed multi-dimensional scaling (MDS). Aiming for a similarity matrix of information-oriented PoS technologies, participants had to evaluate the level of similarity between two of the PoS technologies (for example, a standalone kiosk and an augmented reality display). In relation to this, we used a 7-point Likert scale (1 = ‘not similar at all’—7 = ‘very similar’). Based on 1,289 pairwise comparisons, a proximity matrix/similarity matrix was created for each of two randomly picked experienced technologies. To do so, multi-dimensional scaling of proximity data (SPSS-PROXSCAL) was used (Borg and Groenen, 2005). The results can be understood as a perceptual map, which captures and illustrates customers’ unbiased perceptions of similarities between different types of PoS technologies. Building on the visual mapping, a cluster analysis was conducted to obtain a more coherent representation of PoS technologies. In addition, a property-fitting approach was used, which needs to be understood as a formal statistical analysis of the configurations (Padgett and Mulvey, 2007). For this, customers were asked to evaluate a randomly selected, already experienced example of PoS technology with regard to the specific influences they have on the interaction. We orientated this portion of the research using the WebQual approach by Loiacono et al. (2007), which focuses on the analysis of specific influencing factors when using a website. This instrument introduced a range of scales, including in relation to utility, ease of use, and entertainment. According to Loiacono et al. (2007), while it was originally developed to assess website quality, this approach is beneficial to understand customer behaviour and perceptions with regard to new and innovative information technologies. Meanwhile, in line with the uses and gratification theory (Blumler and Katz, 1974) and the information integration theory (e.g. Anderson, 1962), we transferred seven influences to the context of the perception of PoS technologies. Alexander and Kent (2021) and Riegger et al. (2021) indicate that in addition to usage and information-oriented aspects, the potential of the innovation must also match the customer-service requirements of the customer in the shop. Furthermore, the quality of the information should appropriately meet the customer’s needs and the use of PoS technologies should generate a certain degree of pleasure. Therefore, the influences of task-to-fit functionality, information quality and enjoyment were also integrated into the study. Below, the included constructs are presented in Table 3.1.

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Table 3.1 Influences, Sources, Scales, Item Adaptation and Cronbach’s Alpha Influences

Source

Items

α

1. Ease of Understanding

Loiacono et al. (2002)

The information displayed on or through this technology is easy to read.

0.822

The images/effects displayed on or through this technology are easy to recognise. One quickly finds one’s way around the presentation of this technology. 2. Intuitive Operation

Loiacono et al. (2002)

It is easy to learn how to use this technology.

0.831

I would find it easy to shop with this technology in the store. This technology in the store is easy to use. 3. Functional Fit-to-Task

Koufaris and Hampton-Sosa (2002)

I can shop better by using this technology.

0.857

Using this technology makes it easier for me to shop. This technology allows me to shop more effectively.

4. Information Quality

Ahn et al. (2007) This technology provides me with ways to find information when I need it.

0.874

By using this technology, I can be fully informed. This technology provides me with access to reliable information. 5. Tailored Information

Loiacono et al. (2002)

This technology in the shop allows me to receive information that is personalised for me.

0.818

This technology provides interactive features that make shopping in the shop easier. This technology provides me with options to get information in the shop according to my specific needs. 6. Innovativeness Loiacono et al. (2002)

This technology is innovative.

0.870

The integration of this technology is innovative. (continued)

3.1 Essay 1. A Classification of Information-oriented Point of Sale Technology … 43 Table 3.1 (continued) Influences

Source

α

Items The use of this technology is creative.

7. Enjoyment

Lee et al. (2006)

Shopping with the help of this technology in the store is entertaining.

0.949

Shopping with the help of this technology is pleasant. Shopping with the help of this technology is interesting. Shopping with the help of this technology is fun. Shopping with the help of this technology is exciting. Shopping with the help of this technology is appealing. Note: all influences are measured on a 7-point-Likert-scale: 1 = does not apply at all—7 = applies completely. α = Cronbach’s Alpha

By applying Fornell and Larcker’s (1981) criterion, we assessed our scales for discriminant validity. None of the used constructs shared greater levels of variance with any construct other than its own indicators (Table 3.2). Table 3.2 Results of Correlation Matrix and Discriminant Validity for Essay 1 Mean (SD)

EoU

IO

FFtT

IQ

TI

I

E

EoU

5.02 (1.40)

0.880

0.592

0.319

0.199

0.231

0.342

0.234

IO

5.06 (1.38)

0.350

0.880

0.382

0.217

0.278

0.291

0.216

FtTF

3.91 (1.52)

0.102

0.146

0.906

0.521

0.514

0.392

0.289

IQ

4.46 (1.46)

0.040

0.047

0.272

0.887

0.545

0.379

0.239

TI

4.18 (1.46)

0.053

0.077

0.264

0.297

0.896

0.360

0.257

I

4.52 (1.58)

0.117

0.085

0.154

0.144

0.129

0.908

0.442

E

4.26 (1.56)

0.055

0.047

0.084

0.057

0.066

0.195

0.616

Note: SD = Standard Deviation; EoU: Ease of Understanding, IO: Intuitive Operation, FtTF: Functional Fit-to-Task, IQ: Information Quality, TI: Tailored Information, I: Innovativeness, E: Enjoyment. Diagonal includes the AVE; values below diagonal include the square correlations; values above diagonal include the normal correlations

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3.1.4

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Results

Cluster analysis provided a more accurate representation of the localised (pairwise) positions of individual PoS technologies based on their similarities during the MDS (Mohr, 1998; Carroll and Green, 1997). Clustering methods and MDS are often used in order to investigate relational structures (Padgett and Mulvey, 2007). Our MDS analysis reveals that the seven information-oriented PoS technologies constitute three areas on the perceptual mapping. Stress I had a value of less than 0.2, which can be considered satisfactory, while Stress II was less optimal (e.g. Kruskal, 1964). However, as we analysed a two-dimensional space and the goodness-of-fit value of almost 96.5% of the dispersion (DAF) as well, which can be coupled with the good level of of interpretability of our results within the matrix, it is clear that our two-dimensional solution is adequate. The findings were then used as inputs for cluster analyses, which we performed based on Ward’s method of variance to the group in accordance with the PoS technologies and their similarities to one another. The resulting dendrogram points to a three-cluster solution; therefore, the variances within the identified groups are supposed to be smaller than any disparities between the groups. This solution also fits with regard to interpretability and consistency. Aside cluster analyses, we also used property fitting in order to improve the interpretability of the MDS configuration. This approach can be used to measure the extent to which each influence can be associated with the positions of the PoS technologies in a two-dimensional space (Robinson and Bennett, 1995; Kruskal and Wish, 1978). Moreover, it consists of a series of regressions; here, each influence was used as the dependent variable and the x and y-coordinates of the PoS technologies within the perceptual mapping were utilised as the independent variables (Padgett and Mulvey, 2007). The results of these (non-standardised) regressions (ß1 and ß2 as well as the respected F-Values, significances and R2 ) are displayed in Table 3.3. The level of the R2 value indicates how intense the effect of each individual influence in the matrix is with regard to the PoS technologies. If the R2 falls below a certain value, the corresponding influence is not relevant in this context (Padgett and Mulvey, 2007). The coefficients of ß1 and ß2 (see Table 3.3) imply that the unstandardised beta values from the regressions can be fitted as vector arrows to the perceptual map (Figure 3.1). These vectors need to be understood as forms of orientation for labelling the axes, and they contribute to the interpretation of the clusters.

3.1 Essay 1. A Classification of Information-oriented Point of Sale Technology … 45

Property Fitting

1,0 QR Codes

Dimension 2: Level of Complexity of the PoS Technology

B

0,5 Mobile Device

Virtual Reality

C

Augmented Reality Display

0,0

A

6

Smart Shelf Interactive Display

7

Standalone Terminal

-0,5

2

3 1

-1,0 -1,0

-0,5

0,0

1,0

0,5

Dimension 1: Level of Innovativeness of the PoS-Technology

Stress and Fit Measure: normalized new stress = 0.035; stress I = 0.187; stress II = 0.541; S-stress = 0.087; dispersion accounted for (DAF) = 0.965; tucker’s coefficient of congruence = 0.982.

Figure 3.1 Result of MDS analysis Table 3.3 R2 , F-Values and Coefficients Influences

R2

F-Value

ß1

ß2

1

Ease of Understanding

0.940

31.252**

–0.545*

–0.950**

2

Intuitive Operation 0.967

59.102**

–0.689**

–0.719**

3

Functional Fit-to-Task

0.876

14.165*

–0.500*

–0.428*

4

Information Quality

0.140

0.325

0.129

0.314

5

Tailored Information

0.060

0.127

–0.127

0.102 (continued)

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Table 3.3 (continued) Influences

R2

F-Value

ß1

ß2

6

Innovativeness

0.878

14.334*

1.103**

–0.312

7

Enjoyment

0.862

12.483*

0.986*

–0.523

Note: * = p < 0.05 significance level; ** = p < 0.01 significance level. ß coefficients = unstandardised beta values from the regressions

With regard to the used influences, five out of seven had a significant impact, indicating that they contributed to the interpretation of the MDS configuration. Even though we only selected information-oriented PoS technologies, the influences of information quality and tailored information did not display any significant directionality within the property fitting, meaning that all of the examined innovations are almost equally perceived in this regard. Meanwhile, ease of understanding, intuitive operation, functional fit-to-task, innovativeness and enjoyment exhibited noteworthy impacts within the property fitting and are consequently integrated as vectors within the perceptual map. The heterogeneousness of the arrows in Figure 3.1 indicates that customers evaluate these influences in terms of the different forms of PoS technologies in a divergent manner. The first three influences are primarily oriented towards south (southwest) of the matrix, while innovativeness and enjoyment are pointing towards the east (southeast). In particular, due to the direction of the vector arrow of the innovativeness of the PoS technologies, dimension one can be associated with the degree of innovation of the PoS technology. Since the comprehensibility of PoS technologies seems to increase in the south of the matrix, we can conversely assume that PoS technologies are perceived as less understandable in the north, meaning they have a more pronounced degree of complexity. Thus, dimension two can be titled the degree of complexity of the PoS technology. This conceptualisation becomes clearer when focusing on the three identified clusters of (A) comprehendible PoS technologies, (B) information-integration PoS technologies and (C) entertainment-related PoS technologies. The results of several ANOVAs illustrate that customers’ evaluations of information-oriented PoS technologies differ significantly across the single cluster for all of the seven influences. Additionally, we conducted Tukey’s post hoc test to check for significant differences between the clusters (Table 3.4). The markedly varied cluster sizes go hand in hand with the notable differences in the experiences of the participants within the framework of the survey. Prior experience with augmented reality displays and virtual reality devices is significantly lower than the number of earlier interactions with QR codes or mobile devices.

Intuitive Operation

Functional Fit-to-Task

Information Quality

Tailored Information

Innovativeness

Enjoyment

2.

3.

4.

5.

6.

7.

Cluster B (N = 455) Information-Integration PoS Technologies 4.72 (1.44)A 4.94 (1.44)A,C 3.86 (1.59)C 4.59 (1.45)A 4.31 (1.45)A 4.28 (1.54)A,C 3.90 (1.50)A,C

Cluster A (N = 299) Comprehendible PoS Technologies 5.59 (1.24)B,C 5.39 (1.13)B,C 4.10 (1.43)C 4.28 (1.48)B 4.02 (1.42)B 4.67 (1.60)B,C 4.58 (1.55)B,C

5.11 (1.45)A,B

5.39 (1.43)A,B

3.94 (1.68)

4.40 (1.53)

3.40 (1.37)A,B

4.45 (1.56)A,C

4.58 (1.37)A

Entertainment-related PoS Technologies

Cluster C (N = 76)

31.933*** (0.072)

18.644*** (0.043)

4.716** (0.011)

3.903* (0.000)

6.854** (0.016)

18.687*** (0.043)

44.553*** (0.097)

F-Value (η2 )

Note: mean (SD). Highest rating across PoS technologies is indicated in bold. 1 = does not apply at all/7 = applies completely. * = p < 0.05 significance level; ** = p < 0.01 significance level; *** = p < 0.001 significance level. Elevated letters indicate a significant difference (Tukey post hoc p < 0.05) in relation to the respective cluster

Ease of Understanding

1.

Dependent Influences

Table 3.4 ANOVAs of the Identified Clusters

3.1 Essay 1. A Classification of Information-oriented Point of Sale Technology … 47

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The first cluster (A) encompasses three PoS technologies: the smart shelf, the standalone kiosk and the interactive display. According to the results of the ANOVA, these innovations exhibit higher levels of ease of understanding, intuitive operation and functional fit-to-task, especially in comparison to cluster B. The first two influences also significantly differ in relation to cluster C. In terms of what they have in common, all three PoS technologies do not require (excessive) physical activity during use, yet they are primarily based on customers standing in front of them and engaging in behaviour like simply swiping or scrolling on it to obtain additional information. The use of these technologies is also not linked to any movement within the room as they are permanently installed in one place in the shop. This property allows the customer to concentrate completely on the essential components of these innovations, which makes their use easy to explain. In contrast to PoS technologies where a certain dynamic within the sales area is possible or also desired (mobile devices or QR codes) or where the customer has to adjust to a change in the actual service environment (augmented reality displays and virtual reality devices), these examples are relatively one-dimensional in their requirements for the user/customer. This also makes the relationship to the actual task performed by the device/application (i.e. the transmission of information to the customer) easier to understand. In other words, in these instances, the task is easier for the customer to fit with relatively easy-to-understand/comprehend PoS technology than is the case with other more complex examples (compare with cluster C). As a result, this cluster can be called ‘comprehendible PoS technologies’. The second cluster (B) includes the mobile device and QR codes. Both PoS technologies can be understood in their most basic form as flexible and portable, with portability in the second case referring to the personal smartphone that is used to display the QR code. The almost opposing directions of these PoS technologies in relation to the influence of customers’ ease of understanding (or intuitive operation) implies that a totally intuitive use of these is not completely a given. Even though the influences of information quality and tailored information could not be integrated within the property fitting analysis that were based on the ANOVAs, cluster B has a significantly higher value for both influences, especially compared to cluster A. Whether or not the PoS technologies of cluster A are easier to understand, the potential for moving around a product while searching for the necessary information or comparing digital and physical information using the device in their own hands seems to expand the customer’s information base. As a result, these PoS technologies contain a certain flexibility with regard to the positioning and mobility of customers in the store. This means that customers can harness the possibilities inherent in these innovations, without being fixed on

3.1 Essay 1. A Classification of Information-oriented Point of Sale Technology … 49

a certain point. Instead, it is possible to view or circle a desired product from different angles and check the relevant information on the screen of the mobile device or smartphone (on which the information is displayed behind the QR code) at the same time. In fact, customers can move around one or more specific products and combine product-related and physical-haptic information. Consequently, findings indicate that this cluster can be identified as ‘information-integration PoS technologies’. The last cluster (C) consists of augmented reality displays and virtual reality devices. In accordance with the first dimension, these PoS technologies can be seen as the most innovative ones. In addition, the ANOVA tests showed that customer satisfaction, particularly with regard to the perceived level of entertainment but also in relation to the degree of innovation strength of augmented reality displays and virtual reality devices, is relatively high, both in comparison with cluster A and cluster B. In spite of the fact that such technologies are no longer complete novelties within stores anymore, customers still seem to focus on their entertainment potential over their usability, e.g. they concentrate on elements like being able to project a certain piece of clothing directly onto their bodies without needing to physically get changed. Nevertheless, their understanding of how these PoS technologies work, especially with regard to the intuitive operation or their perceptions of their functional fit-to-task, can still be expanded. However, both PoS technologies generally include the potential for gamification of the service in the form of digitally offered information in the air, around a certain product or mirrored on customers’ bodies, which goes beyond the presentation of actual, physical information. By projecting a certain element/product/piece of information onto a specific environment or even by projecting oneself into another environment, the traditional parameters of the shop-based experience have been broken down. Here, testing a product or trying on a garment can be done with less effort than is required in a real environment; this leads to more flexibility and also greater speed in the service, which can ultimately result in the most unusual variations and forms of testing. Therefore, such endeavours also quickly lead to a certain playfulness being inherent in the service itself. By allowing the customer to step into a parallel reality that exists alongside the actual shop, the customer seems to feel entertained in a more satisfying way and perceives this type of PoS-technology-based service as more innovative. Indeed, customers seem to derive pleasure and entertainment from such services via the aforementioned innovations. Therefore, we summarise this cluster as ‘entertainment-related PoS technologies’.

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3.1.5

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Discussion and Implications

Regarding our research question, the findings illustrated that the seven selected information-oriented PoS technologies can be classified into three categories: comprehendible PoS technologies, information-integration PoS technologies and entertainment-related PoS technologies. When sorting them according to these three subgroups, it becomes necessary to consider challenges retailers face that are linked to the infusion of PoS technologies at the physical Point of Sale brings (Piotrowicz and Cuthbertson, 2014). On the whole, these categories are in line with earlier research on PoS devices/applications (Riegger et al., 2021; Alexander and Kent, 2020; Grewal et al., 2020). On the other hand, with regard to Riegger et al. (2021), the contrast between PoS technologies with high levels of innovative strength (entertainment-related PoS technologies) and those that exhibit lower levels, yet are easier to handle and contain a higher degree of functional fit-to-task (comprehendable PoS technologies), is plain to see. This differentiation could not be derived from literature that exists so far. Building on this assertion, the typology of PoS technologies in terms of convenience and social presence that was expressed by Grewal et al. (2020) could also be improved with further evidence as it seems that augmented reality displays and a virtual-reality devices do not automatically score highly in terms of perceived convenience; this is especially true in relation to smart shelves, standalone kiosks or interactive displays. In addition, the specific relevance of the inclusion of information in relation to mobile devices and QR codes was undermined by Alexander and Kent (2020), even though the specific delimitation of cluster B from the other two clusters, which was highlighted in our findings, has so far been missing within the related literature. By identifying technologies in cluster B as ‘informationintegration PoS technologies’, we assumed that these examples would give value to the haptic and digital information they offer the customer. Within the context of information integration theory (Anderson, 1962), customers take in a range of information from both the digital and the physical environment at the PoS within the assessment. Subsequently, customers integrate and process the incoming data, which ultimately leads to a specific reaction, such as them determining the product’s validity. In contrast to the rather traditional comprehendible PoS technologies in relation to which the customers seemed to appreciate the simplistic and familiar approach to accessing to information while using them, their varied perceptions of the single influences with regard to information-integration PoS technologies and entertainment-related PoS technologies seem to offer a clear value to common empirical research on Point of Sale systems. Even though Alexander and

3.1 Essay 1. A Classification of Information-oriented Point of Sale Technology … 51

Kent (2020) did not differentiate between the various kinds of PoS technologies, our findings can generally provide supporting evidence that efficiency in usage of such innovations as well as the quality of the displayed information are highly relevant to the customer. However, both criteria seem to be differentially distributed with regard to the selected PoS technologies in our study. Unlike Alexander and Kent (2020), we emphasise the pertinence of the level of enjoyment or entertainment experienced by the customer, particularly with regard to more pioneering PoS technologies like augmented reality display and a virtual-reality devices. While adhering to the uses and gratification theory (Blumler and Katz, 1974), we can assert that although innovative, enjoyable PoS technologies perform in a weaker fashion than their information-integration counterparts (mobile devices and QR codes) in terms of perceived information provision, they at least do not lag behind comprehendible PoS technologies (smart shelves, standalone kiosks and interactive displays) in this context. Van Doorn et al. (2017) argue that advancing technological infusion in service will bring about further challenges within physical retailing. According to our results, one of these difficulties could be finding a balance between the innovative and the entertaining and the understandable and the functional. In a similar vein, our findings also point to practical implications for both the adoption of new PoS technologies by retailers and their acceptance by customers. Our results show that the evaluation of PoS technology in stationary services differs significantly from one technology to the next. At the PoS, stationary retailers should provide PoS technologies that customers can optimally use for their individual goals. The orientation and product selection in the shop is also relevant for the choice of innovation as not every technology can generate the same added value for the customer. For example, when it comes to information-oriented products or products that require further explanation (and no frontline employee is available), mobile devices or QR codes should be made available rather than fixed technologies. This allows the customer to obtain information in two ways: by walking/moving around the product and touching it and by using a device in their hand, on which provides additional information. Conversely, if the products are simpler and customers have less of an affinity for technology, it is important that the PoS device/application is easy to understand and utilise. Consequently, a more intuitive approach to technology (cluster A) is appropriate here. Of course, the reverse is also true for technologically well-versed and innovation-savvy clients; for them an AR or VR-oriented solution should be considered if the issue of information is not paramount. Nevertheless, the price of acquiring these technologies must also be taken into account as an AR mirror is in a different financial sphere than installing and programming a QR code.

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3.1.6

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Essays

Limitations and Future Research Directions

Even though our study is able to make a contribution to the theory and practices that are relevant to this field of research, some its limitations should be mentioned. Since we deliberately decided to only include answers in the analysis that were based on previous experiences with the individual PoS technologies, we could not obtain a balanced data set, especially with regard to the more innovative technologies. For this reason, it is possible that some combinations of technologies were answered on significantly more frequently by the respondents than others in relation to the question on their distance perception within the framework of the MDS. The same limitation also applies to the responses on the individual influences as an identical problem arose. However, an evaluation purely on the basis of participants’ imaginations would have been very difficult in light of the research approach we undertook, which is why we had to accept this inaccuracy. Furthermore, we concentrated on seven information-oriented PoS technologies. Other technologies that have been discussed in the recent literature (Riegger et al., 2021; Alexander and Kent, 2020; Grewal et al., 2020; Roggeveen and Sethuraman, 2020) could also have served as forms of (interactional) information transfer (when customers’ own devices), yet they were not taken into account, either because they are not widespread enough on the German market (e.g. mobile service robots) or because they are too close to being integrated PoS technologies (e.g. interactive fitting rooms). In addition, our study was conducted in relation to the German context, and previous research has found several important differences between national markets. Among other things, there are differences in terms of personality, demographics, etc. (e.g. age, gender, etc.) between different countries. (e.g. age, gender, culture or education) as well as differences in customer behaviour (Miltgen and Peyrat-Guillard 2014). Indeed, overall national access to technologies, a country’s specific characteristics and cultural backgrounds can be important factors when analysing different PoS technologies; therefore, cross-cultural studies could provide additional insights into customers’ perceptions of the studied innovations. The investigation that was presented here is a first step to deepening our understanding of this diverse range of PoS technologies. Based on differing perceptions of their comprehensibility in cluster A or there being a slightly more favourable assessment of the information quality or the level of tailored information in cluster B, it makes sense to focus on the specific impact of these PoS technologies on the actual purchase behaviour of customers (e.g. in terms of purchase intention, repurchase intention, willingness to pay, satisfaction or word of mouth) as well as the perceptions of a human frontline employee who is

3.1 Essay 1. A Classification of Information-oriented Point of Sale Technology … 53

potentially involved in the process (e.g. through perceived competence). Research suggests that an appropriate form of technology infusion into a service interaction should be a key objective of a retailer as it influences both customer satisfaction (Srivastava and Kaul, 2014) and the perception of the interpersonal relationship between the customer and the frontline employee (Bolton et al., 2018; Jamal and Adelowore, 2008). On a practical level, the waning prevalence of technological support is influenced by the quality and reliability of today’s PoS services, which have been enhanced through improved access to (potentially) useful information (Rust and Huang, 2014). Consequently, the question for further research is whether the results of this study, which were generated without input from frontline employees, are analogous to future findings when they are involved, especially in terms of entertainment, understanding and information content. In relation to this, Kuckertz et al. (2020) emphasises the potential of technologies in the context of pandemics like the COVID-19 crisis. In fact, current challenges are forcing creative combinations of existing technologies and human capital to take place. It is therefore important to exhaust resources to create solutions with regard to today’s problems. In addition, the interaction between PoS technology and employees is a relevant field in the current literature. As was particularly the case in Cluster A, we could find a higher level of ease of understanding, intuitive operation and functional fit-to-task, yet there might be a lower level of information quality and tailored information in contrast with cluster B; it is indeed worth noting here that the integration of a frontline employee might leverage this perceived information gap. The same might apply with regard to cluster C in relation to the level of perceived innovativeness and entertainment; however, it may be lacking in terms of customers’ perceptions with regard to ease of understanding, intuitive operation and functional fit-to-task. In fact, how customers view the level of ease of understanding or intuitive operation might increase via the integration of a frontline employee, possibly leading to an even higher value of perceived entertainment. At the same time, such frontline employees could also be responsible for a lowering of the information-focused influences in cluster C, especially when s(he) passively participates in customers’ interactions with the technology (Esmark et al., 2017). On the other hand, an active integration might decrease customers’ perceptions of the entertainment value, yet it could concurrently increase the informational value that is derived from the new form of interaction. In addition, the integration of a frontline employee could also be relevant in terms of the potential disclosure of personal information. According to Li (2012) and Zimmer et al. (2010), customers’ perceptions of social presence help to decrease how

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poorly they view data-related issues. It could therefore be interesting to examine how customers perceive the topic of privacy in the context of the different forms of PoS technology and/or different forms of frontline employee interaction in this situation as well as how customers behave with regard to possible data disclosures.

3.2

Essay 2. How to Infuse Mobile Technologies in Frontline Service Encounters: An Experimental Analysis of Customer Responses

3.2.1

Introduction

Both retail practice and research argue that within service delivery and experience, the customer and the frontline employee are the “key involved actors” (de Keyser et al., 2019, p. 156). Advancing technology infusion of the frontline service raises further challenges within the relationship between service employee and customer (e.g. Bolton et al., 2018). Hence, it is of crucial relevance to understand how to meet customers’ service requirements on a level at which the infusion of technology does not e.g. undermine the human frontline service, but rather augments this service. When retailers equip their stores, and especially their employees, with technology, this changes not only the tasks employees undertake, but also the forms of interaction between the frontline employee and the customers in the context of the service processes (Grewal et al., 2020). A major challenge, therefore, is to ensure that technology does not damage or hinder face-to-face service encounters, but rather enhances it (Roggeveen and Sethuraman, 2020). This is important on three levels: (1) Personal level. Interpersonal components can be evoked by the frontline employee, for example, through his sympathetic and authentic charisma (e.g. Parasuraman et al., 1988). However, in order to build a successful and sustainable relationship with the customer, trust by the customer plays an important role in successful interpersonal interaction (Turner, 1988) and also in the context of service encounters (Johnson and Grayson, 2005). (2) Informational level. The frontline employee should be able to provide the customer with the necessary information about the respective products. Product knowledge or market knowledge (e.g. Rentz et al., 2002) is a key component for the frontline employee. If this is given, an increased willingness to pay of the customers can result (e.g. Brownstone et al., 2003; Khattak et al., 2003). (3) Skill level. The frontline employee should also have the competence to convey the necessary information to the respective customer (e.g. van Dolen

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et al., 2002; Fiske et al., 2007). Here, flexibility in dealing with the customer as well as adaptability to customer needs are important components (Alexander and Kent, 2020; Riegger et al., 2021), but also fluent/accessible communication with the customer (Parasuraman et al., 1985). Technology infusion can take place in the form of an intermediate technological information source, such as an employee equipped with a mobile information-providing tablet computer, or an additional kiosk terminal, such as a digital standalone terminal. Both provide supplementary assistance within faceto-face service encounters, and provide the individual customer with the benefits of a digital information source. Drawing on information integration theory, this might improve customers’ overall service experience (e.g. Bolton et al., 2018). Social interaction theory (Turner, 1988) implies that factors such as communication depend on the form of interpersonal contact. Literature emphasizes that interpersonal contact is bound to happen within in-store service encounters (e.g. Solomon et al., 1985) and is highly related to current customer experience (e.g. Bustamante and Rubio, 2017; Locander et al., 2018). This experience might be altered when technology is infused within the service encounter, as technology seems to influence both the nature and quality of interaction between customer and frontline service employees (Bolton et al., 2018). However, different types of technology infusion are likely to vary with regard to their impact on interactional exchanges between the parties (de Keyser et al., 2019). In addition, it is possible that a change in interaction can be triggered by an innovative character of the technology that provides further access to more, or richer product-related information (e.g. Alexander and Kent, 2020; Riegger et al., 2021), or that frontline service employees adapt their interpersonal interactions, which can even lead to customers perceiving psychological barriers between the parties (Giebelhausen et al., 2014). However, an answer regarding the optimal degree or manner of technology infusion within service encounters is missing so far. Following Parasuraman’s (1996) ‘Pyramid Model of Services Marketing’, our research objective lies on the positive and negative potentials of technology infusion in assisting and augmenting, but not substituting, the ‘direct exchange’ between the customer and frontline employee. In this context, we refer to several research that links the potentials of the three main figures in the field of technology-oriented service encounter: Customer, Service and Technology (e.g. Froehle and Roth, 2004; Njöd et al., 2020, Parasuraman, 2000). De Keyser et al. (2019) offer an overview of archetypes and differentiated the combination of the three main figures in this relationship in terms of different ways of using and embedding technology within the service. Based on our research objective, how technology should be integrated into the service encounter to ensure the

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most optimal social interaction, this paper contributes to common knowledge by examining three specific types of technology infusion: (1) technology-free, (2) technology-assisted and (3) technology-facilitated encounter. Technology infusion can assist and facilitate frontline service encounters. Our study (3) implies that the infused technology is used by both the employee and the customer within the service. For example, the display of a tablet computer facing the customer could provide additional product information that is accessible for both parties involved. Contrarily, in (2), the infused technology is used exclusively by the frontline employee, meaning that, for example, additional information is only accessible to the frontline employee (e.g. display of a tablet computer only facing the frontline employee). Nonetheless, technology infusion might impact customers’ evaluation of the frontline service negatively, as it could interfere with the unhindered personal exchange of information between the customer and employee (Giebelhausen et al., 2014). In the following, we will first show the conceptual framework of our research and develop the corresponding hypotheses on which our research is based. We will then first go into the two studies we carried out, which were carried out independently of one another and based on one another as part of online experiments. Study 1 first analyses the effects of different use of a tablet-computer within a service encounter by a frontline employee. The focus is on the specific effect of the technology-infused frontline employee on customer perception in terms of trust towards the frontline employee, their willingness to pay and the perceived service competence of the frontline employee. Based on the results of study 1, study 2 integrates another technology into the service encounter in order to examine the effects identified in study 1 in more depth.

3.2.2

Conceptual Framework and Hypotheses Development

We draw on social interaction theory (e.g. Festinger et al., 1950; Turner, 1988) and information integration theory (Anderson, 1981) to investigate the effects of technology-infused frontline service encounters on customer response. Social interaction theory explains the process of interactive behaviour between employee and customer, such as communication, feelings or similarities between the two parties (Festinger et al., 1950), and implies a motivational, followed by an interactional, form of process (Turner, 1988). In fact, social interaction is a two-way process: the dyadic interplay of action and reaction between two parties, which

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is regarded as an essential determinant within an efficient frontline employee services (e.g. Burkhardt, 1994; Solomon et al., 1985). However, in current days, this interaction is not exclusively bound to the customer and the frontline employee, but may be extended by certain service technologies, leading to the potential of concrete value within such an encounter (e.g. Bolton et al., 2018; de Keyser et al., 2019). For instance, Xin et al. (2015) and Beatson et al. (2006) emphasize that customers’ trust towards the frontline employee level varies when a technology is infused into a frontline service encounter, and Mende et al. (2019) show a positive impact of technology on customers’ willingness to pay. To explain how customers’ willingness to pay might be influenced, we refer to information integration theory, which relates to how a person integrates information to make an overall judgment (Anderson, 1981). In contrast to a frontline employee-only service, where the employee holds information exclusively, technology provides access to a greater range and depth of product-related information that is potentially immediate or even unbiased, and which is therefore likely to be valued by the customer and result in a higher willingness to pay. In addition, we suppose that, according to van Doorn et al. (2017), service outcomes are influenced not only by the kind of technology infusion, but also by customers’ perception of frontline employees’ competence to include the technology in a beneficial way in the service encounter. This will have an impact on customers’ trust towards the frontline employee and should positively influence their willingness to pay. We therefore suppose that perceived competence of the frontline employee acts as a mediator of the relationship between the type of technology infusion within the service encounter and the dependent variables under investigation. The cumulated research model is illustrated in Figure 3.2.

* just in study 1 Experimental Factors

Depending Variables

Type of Technology Infusion (within the Service Encounter) technology-free vs. technology-facilitated vs. technology-assisted

Trust towards the Frontline Employee Mediator Perceived Service Competence of the Frontline Employee*

Figure 3.2 Research Model for Essay 2

Willingness to Pay (for the Product)

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The Impact of the Type of Technology Infusion within the Service Encounter on Trust towards the Frontline Employee Regarding technology infusion in social service interaction, Burkhardt (1994) emphasized a trusting relationship between the parties as a central element. In retail, trust towards the frontline employee represents is essential in retailercustomer relationships, and is important for long-term success (Dywer et al., 1987). Wünderlich et al. (2013) points out the relevance of social interaction in the trust building process within a technology-infused frontline service encounter. Frontline employee is still of high (social) relevance for customers (e.g. Grewal et al., 2020). In cases where they need service, they might want a frontline employee to realize the service process together with them. This requires frontline employee to be able to give them the necessary feeling of being integrated within the services. The customers should thus be at, or get the feeling that they are at, the center of the service processes. Based on Solomon et al. (1985), we suppose that the highest level of interpersonal integration within the service, and thereby the possibility of an optimal social exchange, is likely to be reached in the case of a technology-free service encounter, as in here the most familiar service between the parties can be assumed. A technology-free service encounter might consequently offer the highest level of perceived integration (Giebelhausen et al., 2014), followed by a higher level of interpersonal trust, compared to situations in which technology is infused. Social interaction theory argues that the process of interaction itself can be understood as a situation in which the behaviour of one party is consciously reorganized and influenced by the behaviours of another party (Turner, 1988). According to Giddens (1984), trust is an unconscious ‘force’ behind the conscious activities or behaviour of individuals in interaction. These conscious behaviours might include customers’ perceived integration within the service, as well as their ability to engage in a rather barrier-free social exchange with the service employee. We argue that these barriers do not apply in the same manner. In fact, customers’ distraction might be lower, if they are involved in the technologyinfused service process, rather than having the technology used exclusively by the frontline employee (a technology-facilitated approach as opposed to a technologyassisted approach). This gives the customer the opportunity to actively, or just passively, be involved with the frontline employees’ handling of the device, and also gives them the potential of possible ‘intervention’. Whilst customers’ perceived integration within the service and perception of social interaction is supposed to be lower, this integration within the process means that all procedures can be followed more efficiently. We therefore propose:

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A technology-free frontline service encounter will show the highest level of trust towards the frontline employee. However, a technology-facilitated frontline service encounter will influence customers’ trust towards the frontline employee more positively than a technology-assisted frontline service encounter.

The Impact of the Type of Technology Infusion within the Service Encounter on Customers’ Willingness to Pay While technology infusion is supposed to decrease personal trust towards service employees, its influence is likely to differ when it comes to the evaluation of a concrete product. During service encounters, product-related information, such as key product data, plays an important role. According to information integration theory, actors are interested in a complete level of information access on their alternative (Anderson, 1981), as this helps them minimize the risk of negative surprises. However, information on a product is rather asymmetrically distributed between the customer and retailer with the retailer possessing all the information or knowledge (Tsai et al., 2011). The infusion of technology might be an anchor in this relation, offering a further security by evaluating the presented product from a rather unbiased perspective, and therefore lowering the risk of asymmetric distribution of information on a respected product. The integrated information within a technology-infused interaction could be perceived as more objective, more comprehensive and richer (e.g. Alexander and Kent, 2020; Riegger et al., 2021), which means that the product is easier and more stable for customers to classify, which ultimately also affects the willingness to pay of customers (e.g. Campbell et al., 2014; Gao and Schroeder, 2009). Moreover, previous studies have shown that PoS technologies point to a positive relation between customers’ service evaluation and their willingness to pay (Brownstone et al., 2003; Khattak et al., 2003). In consequence, and based on information integration theory (Anderson, 1981), we assume that such an information asymmetric can be lowered further by presenting the customer with the relevant information directly on the device, in terms of technology-facilitated frontline service. Even though customers have the opportunity to ask the frontline employee for informational access in the case of technology-assisted service, and it should not be assumed that the frontline employee is intentionally integrating different information into the service interaction as the device is present, a direct access or integration of information through a device that is facing the customer might lower customers’ perception of asymmetric information distribution. In fact, a technology-facilitated service might produce an even clearer picture on the product, increasing the potential

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price range, and thereby resulting in the highest willingness to pay. We thus propose H2:

A technology-free frontline service encounter will show the lowest level of willingness to pay for the product. However, a technology-facilitated frontline service encounter will influence customers’ willingness to pay for the product more positively than a technology-assisted frontline service encounter.

The Mediating Impact of Customers’ Perceived Competence of the Frontline Employee Literature emphasizes that infusing technology into a service can make the service as a whole more flexible and adaptable to customer needs (e.g. Alexander and Kent, 2020; Riegger et al., 2021). However, we assume that this is not necessarily the case with regard to the overall perception of competence of the frontline employee as a person, since the infusion of such a technology could push the employee’s essential characteristics and skills into the background. It can be assumed that general service-oriented skills such as knowledge about a specific product or the market on the part of the customer are no longer associated with the frontline employee alone, but are understood on the part of the technology, which reduces the competence of the frontline employee. The same can be assumed when it comes to the characteristics associated with competence, such as the ability to communicate (Parasuraman et al., 1985; Williams et al., 1990). Consequently, in the case of a technology-infused frontline employee, that same technology can result in a lowered assessment of the frontline employee’s competence, as it could be assumed that they are ‘holding on’ to the technology due to uncertainty and/or lack of knowledge. According to social exchange theory, this ‘holding on’ could undermine the social exchange potential of traditional service encounters, including face-to-face interaction and eye contact (Gidden, 1984), as the technological device might automatically attract the attention of the one party or other from time to time. This could divert the substantive flow of interaction between the two parties, and the frontline employee’s substantive argumentation could even go astray. Based on this potential distraction (e.g. Giebelhausen et al., 2014), it is more difficult for the customer to focus attention on the frontline employee, which in turn can negatively influence the perception of the competence of this employee. However, it is also reasonable to assume that technology-facilitated service encounters that integrate the customer generate a higher level of competency than technology-assisted service encounters where the frontline employee has the technology only visible to the employee.

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With the latter, it is even more complex for the customer to decide which information comes from the frontline employee themselves and which comes from the technology. Customers’ perception of frontline employee competence in retail stores is a highly discussed factor influencing customers’ evaluation of frontline service (e.g. van Dolen et al., 2002; Fiske et al., 2007). Van Doorn et al. (2017) argue that competence perception positively influences service and customer outcomes. Regarding service, we suppose that trust towards the frontline employee is a meaningful result of the service, as Fernandes et al. (2018) emphasize that service-orientated competence seems to be an important requirement of trust in the service in this relation. Consequently, we suppose a mediating effect of frontline employees’ competence on customers’ trust towards the frontline employee. Based on previous argumentation, we further assume a mediating impact of customers’ perceived competence of the frontline employee on customers’ willingness to pay for the product. In sum we hypothesize a mediating influence of frontline employees’ comptence on the relation of the type of technology infusion on trust in the frontline employee as well as on customers’ willingess to pay: H3:

The perceived competence of the frontline employee mediates the hypothesized relationships between the type of technology infusion and a) customers’ trust towards the frontline employee in a way, as well as b) customers’ willingness to pay for the product in a way.

Overview of Experimental Studies To test our hypotheses, we conducted two online experiments, using the scenario technique. In both studies, we manipulated the type of technology infusion in frontline service encounters. Study 1 analyzes the impact of a frontline employee’s usage of a tablet computer, focusing on one type of technology and concentrates on the mediating effect of customers’ perception of frontline employees’ competence with regard to the impact on the dependent variables. Based on the scenario of study 1, study 2 focused on the impact of the presence of an additional kiosk terminal in the form of an in-store kiosk terminal. We expect an amplifying effect on the results of study 1. The interaction of different technologies might increase the presumed influences of H1 and H2. At this point, we assume that the number of technologies has an additional impact on customers’ evaluation of integrated information on the product.

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3.2.3

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Study 1: The Mediating Influence of the Competence of the Frontline Employee

3.2.3.1 Method, Procedure and Stimuli Design In study 1, we conducted a quasi-experimental online between-subject study, exploring three types of technology infusion (technology-free, technologyfacilitated and technology-assisted) and two situations (an additional kiosk terminal present vs. not present). We used a tablet computer as technology stimulus in order to present product information by a frontline employee. The way in which the frontline employee utilizes the tablet computer was used to manipulate the type of technology infusion within the service encounter. With regard to the experimental design, we used a scenario in which a service employee presented a hiking backpack in a store for outdoor clothes and equipment. Hereby, we used a physical retailing environment, offering products with a certain service necessity and in which digital support is generally known. With regard to customers’ service needs, a hiking backpack is a product that combines utilitarian as well as hedonic needs and there is a need for explanation. Technology infusion in such a frontline service encounter might be helpful to offer supplementary information and to fulfil customer service requirements (Dacko, 2017). We manipulated the technology infusion within the service encounter by the way how the tablet was integrated by the frontline employee in the service process. To manipulate the type of technology infusion within the service encounter, we used three videos, each of about 42 seconds in duration, which were shot in the store. We designed all videos equally. We ensured that the frontline employee held eye contact with the camera the entire time, and in order to guarantee consistency of the product information, the employee rehearsed a standardized product presentation. The frontline employee used the same script, describing the backpack in exactly the same way in all three videos. We included a technology-free scenario in which the frontline employee did not use any technology. In the scenario to represent a technology-facilitated service encounter, the frontline employee positioned the display towards the potential customer, referring once in a while to the additional information displayed, giving the customer the opportunity to see the information directly. In the scenario representing a technology-assisted service encounter, the frontline employee used the display of the tablet computer only for himself. Hereby, the customer did not have a chance to see or even use the additional information on the tablet directly; the frontline employee used his hands to interact with the customer, as he would do usually without using a

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tablet (Figure 3.3). During the video shooting, the image section was kept constant and it was ensured that no external factors could potentially interfere or bias the results (e.g. music or voices).

Figure 3.3 Exemplary excerpt of the video stimuli of study 2 (type of technology infusion within the service encounter: technology-free vs. technology-facilitated vs. technologyassisted)

3.2.3.2 Measurements, Subjects and Manipulation Check In study 1, subjects were randomly assigned to one of the three experimental conditions and directed to watch one of the three videos. Within a pre-study (N = 121), scales were tested with respect to the understanding and clarity of items as well as with regard to the intended manipulation of the experimental factor ‘technology infusion within the service encounter’. We use trust towards the frontline employee as a central component for the level of interpersonal relationship between the frontline employee and customer. Thereby, we used a scale developed by Kim et al. (2008) (using a 7-point Likert scale: ranging from 1 = ‘I totally disagree’—7 = ‘I totally agree’; α = 0.866; “The frontline employee is trustworthy.”; “The frontline employee gives the impression that he keeps promises and commitments.”; “I believe that the frontline employee has my best interests in mind.”). To collect customers’ willingness to pay, we asked the subject what monetary price, in euros, they were willing to pay for the presented product. To measure competence, we collected customers’ perceived competence of the frontline employee (Price et al., 1994; α = 0.947; using a 7-point Likert scale, ranging from 1 = ‘I totally disagree’—7 = ‘I totally agree’, “The frontline employee is…”, “capable”; “efficient”; “organized”; “thorough”) as well as the three different dimensions of competence. We measured these items via a 7-point Likert scales ranging from 1 = ‘I totally disagree’—7 = ‘I totally agree’). To obtain construct values, mean values of the indicators per construct were calculated. To obtain construct values, the mean value of the indicators per construct was calculated.

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The main study included 944 subjects (women: 54.77%) with an average age of 32.72 (SD = 13.20) years. Overall, participants were almost evenly distributed across the three experimental conditions, as follows: technology-free: N = 312; technology-facilitated: N = 314; technology-assisted: N = 318, with no significant differences between groups with regard to age and gender. We checked if all respondents understood the manipulation by asking what type of technology was infused and how it was aligned within the video: F(1, 630) = 263.19, p < 0.001, η2 = 0.295). Supporting our primary findings, ANOVA tests showed a significant difference of customers’ perceived integration in the service process (Mtechnology-free = 4.32 (SD = 1.88), Mtechnology-facilitated = 4.01 (SD = 1.95), Mtechnology-assisted = 3.24 (SD = 1.69), F(1, 941) = 28.70, p < 0.001, η2 = 0.057). Tukey post hoc tests indicate a significant difference between technology-assisted and technology-facilitated as well as technology-free (p < 0.001), however, no clear significance between technology-facilitated and technology-free (p < 0.1). Finally, we checked that there was no significant difference in attitudes towards an outdoor store among the subjects in any of the three manipulation levels of the type of technology infusion (F(1, 941) = 0.28, p > 0.1, η2 = 0.001).

3.2.3.3 Results and Discussion To test our hypotheses, we conducted MANOVAs (Table 3.5). Table 3.5 Results of hypotheses testing MANOVAs for study 1 Type of Technology Infusion within the Service Encounter (TISE) technology-free

technology-facilitated

technology-assisted

F-Value (η2 )

M (SD)

M (SD)

M (SD)

TISE

Trust towards the Frontline Employee

4.87 (1.27)

4.58 (1.50)

3.93 (1.42)

38.07*** (0.075)

Willingness to Pay

62.64 (17.14)

66.32 (18.13)

64.85 (19.29)

3.24* (0.007)

Note: Between-subjects design. Scale on Trust in the Frontline Employee was measured by using a 7-point scale; Willingness to Pay was measured in Euro; M: mean; SD: standard deviation; Sig.: *p < 0.05, **p < 0.01, ***p < 0.001

Findings did not produce any correlation between trust towards the frontline employee and willingness to pay (p > 0.05). We find empirical support for the hypothesized influence of the type of technology infusion within the service

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encounter on trust towards the frontline employee. With regard to the post hoc analyses, Tukey tests show significant differences of trust towards the frontline employee between all types of technology infusion (p < 0.05). However, with regard to customers’ willingness to pay, significant differences can only be supported between the technology-free and the technology-facilitated condition (p < 0.05). Thus, H1 can be confirmed. H2 is only supported partially by our data. To test the proposed mediating impacts of customers’ perceived competence of the frontline employee on the relationship between the type of technology infusion within the service encounter and the dependent variables, we used PROCESS (model 4) by Preacher and Hayes (2008), as suggested by Zhao et al. (2010). We followed the approach of Baron and Kenny (1986), with respect to the conditional steps one to three for establishing a mediation. Hereby, we could already show a strong impact of the type of technology infusion on the dependent variables as well as on the mediator of customers’ perceived competence of the frontline employee (Mtechnology-free = 5.66 (SD = 1.08), Mtechnology-facilitated = 5.04 (SD = 1.42), Mtechnology-assisted = 3.79 (SD = 1.42), F(1, 941) = 163.56, p < 0.001, η2 = 0.260). Tukey post hoc tests point out an overall significant difference between each of the types of technology infusion (p < 0.001). Table 3.6 includes the direct and indirect effect of customers’ perceived competence of the frontline employee on the dependent variables. Table 3.6 Results on the direct and indirect effect of customers’ perceived competence of the frontline employee on the dependent variables

Dependent Variable

Mediating Influence

Mediator on Dependent Variable

Indirect Effect

ß

ß

T-Value

Overall Model

LLCI ULCI F-Value

R2

Trust towards the Frontline Employee

Customers’ 0.693 26.69*** –0.651 –0.74 –0.57 420.03*** 0.3947 Perceived Service Competence Willingness of the 1.138 2.54* –1.068 –1.92 –0.22 4.37** 0.0042 to Pay (for Frontline Employee the Product) Note: Scale on Trust in the Frontline Employee was measured by using a 7-point scale; Willingness to Pay was measured in Euro; ß: beta-coefficient; LLCI: lower limit confidence interval; ULCI: upper limit confidence interval; Sig.: *p < 0.05, **p < 0.01, ***p < 0.001

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Results support H3a and H3b, as the indirect effect of customers’ perceived competence of the frontline employee on trust towards the frontline employee, as well as on customers’ willingness to pay is significant, with a confidence interval that excludes 0 (Preacher and Hayes, 2008). Following Zhao et al. (2010), we have evidence for two competitive mediations. Tukey post hoc analyses (focusing on the differences between technology-free and technology-facilitated, and between technology-free and technology-assisted) confirm the mediation for both dependent variables.

3.2.4

Study 2: The Varying Amount of Technology Infusion

3.2.4.1 Method, Procedure and Stimuli Design With study 1, we were able to show an effect of the type of technology infusion within the service encounter on trust towards the frontline employee and on willingness to pay. With study 2, we intended to additionally gain insight into the stability of our results and to gain further empirical evidence with regard to our hypotheses. We focus on 1) clarifying the amplifying potential when including another technological device in the service encounter with regard to the two dependent variables and 2) answering the question to what extent our results are transferable to another retail sector and product type. With regard to the experimental design, in study 2, we used a furniture store, as these products generally still take a lot of service and are rather cost-intensive. Moreover, furniture stores, such as IKEA, are increasingly combining digital technologies and physical frontline service at the PoS (e.g. Hultman et al., 2017), which makes it easier for the respondents to refer to the scenario. The images in Figure 3.4 were taken at a well-known furniture store in a German University City, and demonstrate the different levels of technology infusion within the service encounter. In the image, the scenario of a technology-free, technologyfacilitated and technology-assisted frontline service encounter (even if static) was depicted in the same manner as in study 1. In addition, to create scenarios four to six, a digital in-store kiosk terminal was used as an additional technology, extending all three types of technology infusion situations. In this online experiment, subjects were randomly assigned to one of the six experimental conditions. They were told to imagine that this would be a product presentation at the PoS and had to answer a questionnaire.

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Figure 3.4 Experimental design of study 2 (type of technology infusion within the service encounter: technology-free vs. technology-facilitated vs. technology-assisted)

3.2.4.2 Measurements, Subjects and Manipulation Check We measured trust towards the frontline employee (α = 0.889) as well as customers’ willingness to pay analogously to study 1. Study 2 included 465 subjects (women: 53.81%) with an average age of 30.23 (SD = 10.60) years. The subjects were almost equally distributed between the experimental scenarios including the three types of technology infusion within the service encounter, with additional digital in-store kiosk not present or present. Subjects were distributed as follows, with numbers in brackets indicating the split between kiosk not present/present: technology-free: N = 150 (76/74); technology-facilitated: N = 161 (79/82); technology-assisted: N = 154 (79/75). Again, findings of study 2 are supporting our manipulation on customers’ perception of integration within the service encounter (Mtechnology-free = 5.00 (SD = 1.45), Mtechnology-facilitated = 4.41 (SD = 1.68), Mtechnology-assisted = 4.08 (SD = 1.69), F(1, 462) = 12.76, p < 0.001, η2 = 0.052). Again, tukey post hoc tests indicate a significant difference between technology-assisted and technology-facilitated as well as technology-free (p < 0.001), but no significance between technology-facilitated and technology-free (p > 0.1). Finally, we checked that there was no significant difference in attitudes towards a furniture store among the subjects in any of the three manipulation levels of the type of technology infusion (F(1, 462) = 1.88, p > 0.1, η2 = 0.004).

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3.2.4.3 Results and Discussion To test H1 and H2, we conducted two MANOVAs, the first with regard to an overall effect and the second with regard to the influence of an additional kiosk terminal (Table 3.7). Again, results show no significant correlation between trust and willingness to pay (p > 0.05). Results regarding trust in the frontline employee show a difference of the means (Mtechnology-free = 4.43 (SD = 1.20), Mtechnology-facilitated = 4.20 (SD = 1.16), Mtechnology-assisted = 4.01 (SD = 1.23)). However, tukey post hoc tests show that only between the technology-free condition and technology-assisted condition do significantly different levels of trust exist (p = 0.006). Similar results emerge with regard to H2 (Mtechnology-free = 735.09 (SD = 487.13), Mtechnology-facilitated = 903.39 (SD = 612.83), Mtechnology-assisted = 860.24 (SD = 678.35)), where Tukey post hoc analysis shows that it is the technology-free and the technology-facilitated conditions that differ significantly (p = 0.036). Summing up, our results only partly support both hypotheses. To analyze if the infusion of an additional kiosk terminal has an effect, we included the presence of an additional kiosk terminal as an independent variable in the form of a dummy coding within the MANOVAs. Overall, we can show a significant effect of the presence of the additional digital kiosk terminal on trust (Mnot_present = 4.34 (SD = 1.17), Mpresent = 4.08 (SD = 1.24) and on customers’ willingness to pay (Mnot_present = 780.15 (SD = 581.59), Mpresent = 890.17 (SD = 618.49)). Regarding the first, tukey post hoc analysis between the types of technology infusion within the two conditions of the additional kiosk terminal just show an empirical difference between technology-free and technology-assisted (p < 0.05). Regarding the latter, tukey post hoc analysis does not show any significance. Findings lead to the assumption of a significant lowering of trust when the additional kiosk terminal is included, but a general amplification of customers’ willingness to pay.

3.2.5

General Discussion and Conclusion

3.2.5.1 Summary We can emphasize the influence of different types of technology infusion within the service encounter. With our studies, we show that when retailers equip their frontline employees with technology, it is important to infuse technology that is used by frontline employees, such as tablet computers, in a manner that enables a technology-facilitated approach, and involves the customer in the technology usage. In addition, in a technology-free condition, the integration within the

883.83 (660.39)

3.212* (0.014)

4.720** (0.020)

TISE

3.911* (0.008)

5.540* (0.012)

IKT

F-Value (η2 )

0.593 (0.003)

0.326 (0.001)

TISE x IKT

Note: Between-subjects design. Scale on Trust in the Frontline Employee was measured by using a 7-point scale; Willingness to Pay was measured in Euro; M: mean; SD: standard deviation; Sig.: *p < 0.05, **p < 0.01

948.15 (655.86)

3.87 (1.29)

4.14 (1.17)

837.85 (698.44)

4.02 (1.12)

M (SD)

technology-assisted

856.92 (565.15)

4.39 (1.18)

4.35 (1.27)

present

M (SD)

M (SD)

not present 4.50 (1.14)

technology-facilitated

technology-free

Type of Technology Infusion within the Service Encounter (TISE)

Willingness to not present 640.38 (426.38) Pay present 832.35 (527.85)

Trust in the Frontline Employee

Instore Kiosk Terminal (IKT)

Table 3.7 Results of the impact of the type of technology infusion within the service encounter on the dependent variables for study 2

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service is perceived the highest from customers’ side, resulting in the highest trust towards the frontline employee (study 1 and 2). In contrast, technology infusion in the sales process, in which the technology is used as part of the interaction process and integrates customers into technology usage, yields the highest levels of customer willingness to pay. Our results from study 1 show that technology infusion in frontline service encounters does not necessarily have a positive result, but instead might act as a hurdle in terms of customers’ interpersonal perception (e.g. Giebelhausen et al., 2014); however, this depends on the way in which technology is infused in the service encounter. Findings show that the customers seem to honor barrier-free service encounters with frontline employees. Social interaction theory helps to explain customers’ appreciation of technology-free frontline service, in which they feel most integrated into the service. Nonetheless, using a PoS technology might be an option for retailers in order to profit from the positive effects that technology infusion has on customer willingness to pay (Mende et al., 2019). In addition, we show that technology infusion seems to lower competence perceptions of the frontline employee, which is problematic, because competence is an important antecedent of trust. From our mediating analysis in study 1, we can empirically confirm parts of van Doorn et al.’s (2017) conceptual assumptions on the mediating impact of frontline employee/service competence, whilst also extending their approach with regard to the relevance of frontline employee’s competence on an interpersonal and informational level, with regard to customers’ trust and willingness to pay. Customers seem to intuitively evaluate the frontline employee before deciding to trust or mistrust them, and before finalizing the amount of money they are willing to pay. Technology infusion of the frontline service, however, seems to impact competence perceptions. Furthermore, based on the results, we can assume that an ‘oversupply’ of technologies reinforces customers’ perceptions of the service in terms of interpersonal trust towards the frontline employee (negative) and customers’ willingness to pay (positive), as the results of study 2 show.

3.2.5.2 Implications for Management Retailers need to consider that technology infusion might also lead to strategic advantages in the long term, via the influence on frontline employees’ competence, as well as on trust towards the frontline employee. Results also show that, simply by implementing digital devices, retailers might profit from a higher willingness to pay, at least in the short term, resulting from technology infusion. However, if retailers’ primary interest is to optimize the overall service encounter, a lower level of technology infusion might be superior.

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Based on Parasuraman’s (1996) ‘Pyramid Model of Services Marketing’, we suggest a more consequent interplay between the retailer, the service frontline employee, the customer and the technology. In this relation, we point to three fields of improvement regarding technology infusion at the PoS (Table 3.8). Table 3.8 Implications for the frontline employee as well as for the retailer Frontline Employees’ Potentials

Retailers’ Potentials

Monetary Profit

Integrating the customer more actively within the technology-infused service enhances their information base. Even though frontline employees are generally not directly involved in monitoring processes, they include a high level of sensitivity in service encounters. This sensitivity should also be focused when considering whether, and how, a retailer should infuse a technology into services.

The infusion of technology into service encounters should be accompanied by targeted training on how to bring together a competent attitude and respected technology to optimize service for the most efficient output (e.g. Rust and Huang, 2014). In addition, the monitoring and computing of ‘if’ and ‘how’ the infusion of more innovative technologies influence customers’ willingness to pay might be important.

Customer Relationship

Frontline employees’ competence is important when customers form trust. Technology usage might center on adding service value with regard to product information. Technology usage should augment product information and might contribute aspects that cannot be verbally expressed, thus providing added value for customers.

As well as the aspect that retailers need to train their frontline employees with regard to the handling of technologies, the individual in-store opportunities of further technologies on outcomes, such as repurchase intention and word-of-mouth, need to be evaluated. In terms of long-term success, specific focus should be laid on the building of customer relationships. (continued)

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Table 3.8 (continued) Frontline Employees’ Potentials Companies’ Overall Benefit Since the ability to find a balanced way to give the customer a sense of interpersonal interaction and the ability to have control over the service encounter on the frontline contributes to business value, this is where a special focus is called for.

Retailers’ Potentials The contradictory effect of technology infusion on trust towards frontline employees and thus interpersonal relationships is a sensitive field, and retailers have to decide whether rapport building with customers on a strategic level or selling on a tactical level is their focus.

While we performed our studies focusing two specific types of technology—handheld tablet computers used by frontline employees and in-store kiosk terminals—we suppose that our results are also are transferable to more innovative and upcoming technological PoS solutions. Our study implies that technologies that augment the frontline service encounter and that integrate the customers might have long-term positive effects.

3.2.6

Limitations and Implications for Further Research

Even though our study is able to contribute to theory and practice as outlined, it comes with a number of limitations. Generally, we used an experimental approach, using two online studies with specifically created scenarios, as controlling all possibly disruptive factors within a retail store would have been hard to handle. Moreover, actual interaction includes an interplay of demands and reactions between the customer and the frontline employee. With the use of two online scenarios, we were not able to include such complex interactions and had to focus on the central elements: respondents’ perception of a technology-free, technology-facilitated or technology-assisted service. While we manipulated technology infusion, we only focused on two specific technologies: a tablet computer used by the frontline employee, and a kiosk terminal that was only displayed without being integrated in the service process. For both technologies, we did not explain the service encounter itself or technology functionality within the service process to the respondents. In retail practice, however, there are many

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further technologies that could also be used in combination, including the possibility to affect the social perception of the frontline service (de Keyser et al., 2019; Grewal et al., 2020). Based on our findings, with regard to a mobile technology infused within the service encounter, we opened the avenue to test more differentiated integration of even more innovative technologies. To reduce complexity, we did not include analyses of personal characteristics of the frontline employees. In our studies, only male frontline employees were included. However, for example, gender effects might be important, especially with regard to the effect of technology infusion (e.g. Snipes et al., 2006). Also, analyzing further retail industries might produce additional insight. Our analyses and results highlight implications for future research on the infusion of PoS technologies in physical retailing. Of particular interest is the way in which the relationship building processes with customers can be combined with a high willingness to pay through the optimal level of technology infusion and the introduction of further technologies. We address the relevance of merging strategic and tactical retailing aims through the infusion of technologies, and the corresponding integration of the customer. We moreover suppose that it is interesting to consider that the consideration of further aspects of in-store usage of technologies might be important, such as, for example, that the use of technologies might lead to customer concerns regarding the sharing of private information within the frontline service encounter. Previous literature shows a strong relationship between customer privacy concerns and trust (e.g. McCole et al., 2010).

3.3

Essay 3. The Role of the Frontline Employee in Technology-Based Service Encounters

3.3.1

Introduction

The infusion of technology in the stationary retail store necessitates ‘retooling’ the role of the human frontline employee in the future (Grewal et al., 2017). Technologies are viewed, for example, as having the potential to both increase process efficiency and improve the customer’s shopping experience (Bleier et al., 2019; Lemon and Verhoef, 2016). Innovative (AR or VR-oriented) technology is bringing about a significant change in self-service offerings. This enables easier access to certain information and offers the potential for increasing customer enjoyment of the respective service (Huang and Rust, 2017). Most literature in

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recent years has focused on investigating how the service employee can be augmented/extended or even replaced by means of different technological solutions (Larivière et al., 2017; Marinova et al., 2017). There is a lack of studies questioning to what extent the augmentation of a technology-based service by means of the frontline employee affects customers’ perception and behaviour. Specifically, the question arises: to what extent does it make sense for a retailer that the customer use the innovative technology alone at the Point of Sale (PoS), and how should the frontline employee support this technology-based service through his/her presence? In fact, the interaction potential of frontline employees within a technology-based service provided at the physical PoS has not yet been completely clarified (de Keyser et al., 2019; Grewal et al., 2020; Ostrom et al., 2019). However, previous research shows that more innovative technologies (i.e., AR or VR) seem to enrich the customer service experience (Marinova et al., 2017), optimise the purchase decision process and increase customers’ perception of being entertained during the service (Huang and Liao, 2015). Moreover, service technologies are increasingly understood as efficient and convenient when it comes to the transmission of information (Alexander and Kent, 2020). Since customer acceptance of these PoS technologies seems to be increasing, and their added value for the customer is becoming ever more extensive and tangible, we are investigating circumstances under which the frontline employee can still be a benefit to the customer in technology-based services. According to Grewal et al. (2020), it should not be in the interest of retailers to eliminate human frontline service, but to emphasise its strengths in terms of social presence and interaction. For instance, customers might want to share their personal situations and feelings with others, which would not be possible with self-service technology (Gremler, 2017). Frontline employees have the unique potential to contribute to PoS services, e.g. via their product-knowledge or emotional and interpersonal interaction abilities (Gremler, 2017; Yoo, 2017). Nonetheless, digital transformation has changed customer behaviour. For physical shops, this means that customers often are very well informed and digitally experienced, and so open to the use of self-service technologies. This changes the role and tasks of frontline employees (compared to service advice from 30 or 40 years ago) accordingly (Grewal et al., 2017). Also, in view of the increasing number of so-called self-services stores (Polacco and Backes, 2018; Ives et al., 2019), it is important to determine whether human employees are still necessary at all in technology-based store concepts and, if they are, to identify what tasks they should take on in this context. Several studies investigated the interaction of service employees and customers and its impact on service quality (Parasuraman et al., 1985; Solomon et al., 1985),

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the potential of technology in physical retailing (de Keyser et al., 2019, Grewal et al., 2020) as well as the interaction of service employees, technologies and customers with regard to a desired output (Giebelhausen et al., 2014, Wünderlich et al., 2013). However, there is a lack of analysis in the research on whether, and with what focus, a technology-based service should be supported by the human employee and in which factors such support is helpful or not in the general service. Even though PoS technologies lack social interaction, we suggest that when customers are using a technology at the PoS, they value clear, undisturbed flow of information between the two parties (Alexander and Kent, 2020). According to role and script theories (Halpern, 1997), the interaction between a frontline employee and a customer is based on an underlying script that controls and organises the interaction between the two parties in terms of their different interests. Specifically, the frontline employee is interested in selling a product and so provides essential information to the customer and answers questions. The customer, in turn, is interested in the product and asks the frontline employee the necessary questions to get a comprehensive picture of the product. In the context of our study, we assume that, based on years of experience with self-service technologies, the customer’s interaction with such technology has also strengthened the customer’s understanding of their role. This means that the distribution of tasks between the inquirer/interested party (customer) and the counterpart who answers the questions or provides additional information (technology) is also clearly regulated and understood at this point. Consequently, from our point of view, the script within a service encounter is not limited to the human-customer interaction; now, the script can be a technology-customer interaction, since here too the roles have been clearly distributed over the last few years, and the customer has also accepted this. Based on this assumption, we argue that a frontline employee, like a technology (Giebelhausen et al., 2014), can disrupt this underlying script between customer and technology by his/her integration or intrusion, which may hinder the service encounter, particularly in terms of information flow. This can be the case if the customer prefers the service via the technology to the human advisor for a specific reason, e.g. when it comes to generating sensitive information or anything they would rather not share with a human frontline employee. In fact, the high quality and customised delivery of information is of vital importance within service encounters (Xu et al., 2013). Especially in physical retailing, much research shows that the ability to convey high-quality information about products is a key component of the frontline employee (Ford et al., 1987; Rentz et al., 2002; Verbeke et al., 2011).

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This assumption could be supported by the findings of Esmark et al. (2017), according to whom frontline employees in the store who are deliberately left out of a service (e.g. because people are just looking around) can also be perceived as a disruption or even trigger feelings of discomfort. Contrastingly, following the social presence theory (Short et al., 1976), we argue that, in the context of technology-based services, there may be uncertain or unfamiliar situations where customers appreciate the presence of a frontline employee on an interpersonal level, who directly or indirectly supports the customer with making their decisions. In addition to all the information potential of self-service, interaction with technology also involves the generation of personal or behavioural information about customers. In such situations, customers may worry about their data being misused (White et al., 2014). The presence of a frontline employee may alleviate these concerns, since this is understood as an additional reassurance in this context (LaRose and Rifon, 2007). In this study, we seek a better understanding of the role of frontline employees within technology-based services at the physical PoS. We investigate whether the presence of frontline employee in a technology-based service reduces customers’ perceived expected information quality of that service or helps reduce their privacy concerns resulting from the technology interaction. We contribute to the area of technology-based frontline services in several ways. We show that, while ‘seeking and receiving’ information in a pure technology-based service may lead to a more positive assessment of the expected information quality of the service than when a frontline employee is present, the presence of a human employee seems to reduce the perception of potential misuse of customer data by the retailer and, thus, the associated privacy concerns. Moreover, we can show that discomfort with the service mediates the impact of frontline employee presence in technology-based services on the expected information quality of the service. In addition, customers’ perception of social presence within the service mediates the impact of frontline employee presence on privacy concerns related to retailers’ data-handling practices. Based on our findings, we provide theoretical and practical implications.

3.3.2

Literature, Theoretical Framework and Hypotheses Development

Besides Self-Service Stores (Polacco and Backes, 2018; Ives et al., 2019), in which no employees are visible on the sales floor and the actual processing is

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also automated in an app, the nature of traditional service encounters in brickand-mortar retailing is influenced by various environmental factors and social influences and interactions between customers and frontline employees (Solomon et al., 1985; Surprenant and Solomon, 1987). Within customers’ first encounter with the store or the frontline employee, a first impression of the respective counterpart is formed (Bitner, 1990). Research shows that customers in some situations might avoid interacting with frontline employees (Meuter et al., 2000). The presence of a frontline employee is not always perceived as positive. For example, customers may feel uncomfortable only because they want to avoid eye contact with the employee, especially if their intention for visiting the shop is only casually ‘looking around’. This can trigger uncomfortable feelings and prevent the customer from making purchases. (Esmark et al., 2017). Furthermore, research has shown that if the frontline employee gets too close to the customer or the customer has the feeling of being watched, their shopping experience decreases (Esmark Jones et al., 2019). Overall, the presence of a frontline employee is ambivalent: on the one hand, they can play a significant role in serving customers in the buying process and helping them to make the best possible choice; on the other hand, they can be perceived as a nuisance or even a disturbance. Based on role and script theories (Halpern, 1997; Wang et al., 2012), the service encounter is subject to a clear process that presupposes certain customer and employee behaviours according to a set script (Solomon et al., 1985). It is argued that the script of such an interaction consists of norms that go back to learned behaviours and run under consideration of past experiences. Based on this, the script-relevant expectations of all participants can be derived in relation to the respective interaction within the service encounter (Leigh and Rethans, 1984). The outcomes of these interactions can depend on whether customers and frontline employees adhere to their roles and follow their respective scripts. Consequently, a deviation from the expected role behaviour by one actor might lead to the respective counterpart reacting with adjustments. In the context of physical retailing, Giebelhausen et al. (2014) uses this approach to emphasise the risk that when employees are equipped with technologies, barriers between customers and employees might arise. The technology might distract the customer, and this could be seen as a violation of the underlying script, resulting in customers being unable to recall their established behaviour during the service interaction at the Point of Sale. With the number of PoS technologies and their usage by customers increasing in retail practice (Grewal et al., 2017), we argue that the ‘infusion’ of a human frontline employee within a technology-based service might change customers’ perceptions and reactions. We see the frontline employee as a support who can and should help customers

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deal with the technology, e.g. with answering usage and service-related questions that the technology cannot provide. Nevertheless, we assume that a form of service-oriented understanding of roles has also become established in the interaction between the customer and the technology. Within this understanding, the technology and the customer now play the main roles and the employee only a supporting role. However, the employee trying to step out of this sideline and take a more active role in the interaction between the customer and the technology can disrupt the script of this service encounter in the eyes of the customer. This script violation can result in the customer no longer being able to devote full interest to the information of the technology, since the frontline employee restricts the customer’s free interaction with the technology. This can be explained by the fact that the customer feels an increased degree of discomfort and, due to the limited use of technology, generates less rich/high-quality information. In fact, customers’ perception of the expected information quality of the service will decrease, as its clarity and the informative nature of it (Jarvenpaa and Todd, 1996) may be disturbed by the presence of a human frontline employee. This external (potentially even unconscious/passive) intervention is often associated with an increase in discomfort (Knapp et al., 2013). However, technologies could also be perceived as a threat when the customer’s personal data is transferred directly to the retailer’s internal/in-house data pool. Human frontline employees might be regarded as helpful in this context, reducing the potential of data misuse. At this point, we see the perceived social/interpersonal presence as a decisive factor, as the perception of social presence might be an emotional support in terms of potential data disclosure, lowering data-related issues (Lutz and Tamó-Larrieux, 2020). The value of the presenting product information depends strongly on the level of data a certain technology/algorithm has access to (Grewal and Iyer, 2017) and on the level of customised information to the user. Personal data plays an increasingly key role in retailing (White et al., 2014). However, customers’ concerns about privacy (including the use, analysis and storage of data) increase when retailers use in-store technologies (Alexander and Kent, 2020; Riegger et al., 2021). Literature offers a wide range of antecedents on online privacy concerns (Bellman et al., 2004). Research emphasises that customers’ perception of social presence (or, in terms of our study: human presence) might decrease or leverage such concerns (Li, 2012; Zimmer et al., 2010). We refer to social presence theory (Short et al., 1976) and suggest that a medium or a technology can have the ability to generate social presence. According to Grewal et al. (2020), social presence is particularly triggered by signals regarding humanity, warmth or the perception of human involvement. Social presence theory does not only refer to a medium or a technology that gives people the feeling of being in the presence of

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another person; the perception of social presence is also an important requirement for a successful direct and immediate interaction of (at least) two parties (Biocca et al., 2003; Soussignan and Schaal, 1996). Based on this theoretical approach, we assume that customers’ perceptions of social presence increase when frontline employees are present in technology-based services. This gives customers the feeling that the decision whether to share certain information is not made alone. This decision can therefore be made more confidently, and the customer’s privacy concerns are alleviated. Summing up our considerations, we assume that the assessment of the expected information quality of a service at the Point of Sale, which incorporates PoS technologies, as well as customers’ privacy concerns, will differ depending on whether customers use the PoS technologies by themselves or with a frontline employee present. In this relationship, we expect discomfort regarding the service to mediate the impact on expected information quality, and perceived social presence to mediate the impact on customer-perceived privacy concerns related to retailers’ data-handling practices. The resulting research model for our study is illustrated in Figure 3.5.

Experimental Factors

Discomfort regarding the Service

Dependent Variables Expected Information Quality within the Service

Presence of a human Frontline Service Employee (in a Technology-Based Service)

Privacy Concerns related to retailers’ data-handling practices

(not given vs. given)

Perceived Social Presence within the Service

Figure 3.5 Research Model for Essay 3

Hypotheses Development Customers value high quality information in their encounters with services (Koufaris, 2002; Lederer et al., 2000). Indeed, Ahearne and Jones (2008) pointed out that service-related technologies have the potential to improve customers’ perceptions of information presented through such a service. However, based on role and script theories (Halpern, 1997; Wang et al., 2012), we hypothesise that this improvement could be sidetracked by the infusion of a frontline employee. Given the underlying script, in which the interaction between the technology and the customer is understood as the basis, the infusion of a frontline employee could detract from the interaction process, since two potential sources of information

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are available to the customer. It could be assumed by the customer that a human and a digital source may not have the same service approach or service interest, as the technology focuses on clear information aspects and an undistorted transfer of these to the customer, while the frontline employee may also pursue strategic business approaches. This can affect the individual quality of the information the employee conveys to the customer, in the customer’s point of view. In the case of technologies, the truth of this conflict of interest may not yet be too pronounced among customers. In fact, if the frontline employee is not directly involved in the service, inappropriate intrusion into that service (by staring or similar behaviours) can make the customer uncomfortable (Esmark et al., 2017). Moreover, customers are used to searching for their information online by themselves (Verbecke et al., 2011), so a human employee might distract their intuitive way of gathering information. Furthermore, we assume that customers may feel uncomfortable with two different sources of information (human and machine), as they are not sure whether the right attention has been paid to the information being conveyed. According to Giebelhausen et al. (2014), this is especially likely if one of the sources is human, as it is in the social nature of customers to focus first on the employee and second to the technology due to the learned social exchange behaviour of customers and people in such an interaction. One result of this process can be the unfavourable evaluation of the service encounter (Giebelhausen et al., 2014). Abandoning or leaving the service encounter due to increased discomfort can also be a customer’s reaction (Esmark and Nobel, 2017). Williams and Aaker (2002) pointed out that discomfort is due to inner conflict. We can assume this inner conflict is triggered by the presence of the employee in a technology-based service, and the customer can no longer completely focus on the technology, since it is part of social nature not to be able to ignore the human frontline employee. Even if termination of service as a final decision is not rational, at this point, it can be assumed that the service will nevertheless decrease in quality. In concrete terms, this can be seen in a less favourable/less optimal perception of the quality of the information from the technology, due to the conflict of attention. Consequently, discomfort is argued to function as a mediating impact, as it might be one important reason for the assumed script violation: H1a:

H1b:

The presence of a frontline employee within a technology-based service encounter will decrease customers’ (expected) information quality within the service. The discomfort regarding the service mediates the influence of the presence of a frontline employee within a technology-based service encounter and customers’ (expected) information quality within the service.

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Literature shows that privacy concerns arise from higher social and physical distance between customers and frontline service employee (Choi et al., 2001). The increase of the human presence might be a leverage to lower customers’ concerns (Pavlou et al., 2007). Based on the argumentation of Biocca et al. (2003) and Soussignan and Schaal (1996), a higher level of emotional, empathic or interpersonal level is perceived as socially more present. We assume that, based on social presence theory, a technology-based service, infused with a human frontline employee, imparts a higher level of social presence than a purely technologybased service. When it comes to privacy concerns, while using the technology when certain personal information is required, the customer may desire a helping/social hand to feel more secure. In online contexts, Li (2012) and Zimmer et al. (2010) have shown that customers’ perception of social presence helps reduce their privacy concerns. In terms of the handling of an innovative technology at a physical PoS, we base our argument on social presence theory (Short et al., 1976), by assuming that, given the presence of some set of personal characteristics, i.e. the perception of warmth or human involvement (Grewal et al., 2020), privacy concerns on data use and handling might decrease. For example, Pavlou et al. (2007) could demonstrate the relevance of perceived social presence in reducing privacy concerns in an online shopping context. Taking up the argument of social norms driving customers to pay more attention to a human service than a technological one, we assume the increase in this social presence creates a kind of ‘social bond’ between the customer and the frontline employee regarding the potential disclosure of personal data, leading to a reduction in privacy concerns. In fact, we assume customers’ perception of social presence mediates the impact of the presence of a frontline employee within a technology-based service encounter on customers’ expected information quality within the service negatively: H2a:

H2b:

The presence of a frontline employee within a technology-based service encounter will decrease customers’ privacy concerns related to retailers’ data-handling practices. The perceived social presence within the service mediates the influence of the presence of a frontline employee within a technology-based service encounter and customers’ privacy concerns related to retailers’ data-handling practices.

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3.3.3

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Empirical Studies: Method and Procedure

We tested our hypotheses via an online experiment, in which the presence of a human frontline employee was manipulated (presence of a human frontline employee in a technology-based service encounter is not given vs. given). Within these experimental conditions, subjects were asked to imagine themselves in a technology-based service encounter located at the PoS. The technology was represented by an augmented reality mirror that allows users to interact with by using gestures, e.g. selecting different clothes, colours, etc., via swiping to the right or to the left. To increase the customers’ imagination, they were presented with an image with the corresponding technology. However, this image was only included as a supporting feature to give all participants the same idea of what technology this study is about and how to use it. To avoid any gender bias, female subjects saw an image of a woman standing in front of the augmented reality mirror and, analogously, male subjects saw an image of a man standing in front of the augmented reality mirror. We also made sure that both subjects were approximately the same age and that no colour influence in the images distorted the subjects’ perception (Figure 3.6).

Figure 3.6 Supporting images for the technology

Additionally, subjects were exposed to a written scenario, in which the presence of a human frontline employee was systematically manipulated. Subjects were randomly assigned to one of two scenarios, in which service is either (1) purely based on the technology or (2) based on the technology, but infused by a frontline employee, passively accompanying customers’ interaction with the technology. In the first scenario, subjects were only informed on the applications of the augmented reality mirror, including its potential to offer suitable clothes,

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retrieve their availability in size and colour, price and origin as well as personalised curation of different garments, depending on earlier shopping. In the second scenario, subjects got exactly the same information as in the first scenario, complemented by the aspects that a frontline employee is accompanying the service passively, in terms of standing next to the customer and supporting her/him with further information on the technology, the products or the purchase process, if the customer asks for it. In this online experiment, respondents were randomly assigned to one of the two experimental conditions. Afterwards they had to answer a corresponding questionnaire. The included constructs are presented in table 3.9. To obtain construct values, indicator values per construct were mean aggregated. Table 3.9 Constructs, Sources, Scales (7-point-likert-scale: 1 = I totally disagree—7 = I totally agree), Item Adaptation and Cronbach’s Alpha for Essay 3 construct

source

(expected) Ahn et al. information (2007) quality within the Service

scale

α

item adaptation

7-point-likert- I expect this service to provide scale complete information.

0.919

I expect this service to provide accurate information. I expect this service to provide reliable information.

Customers’ Overall Privacy Concerns

Dinev and Hart (2006)

7-point-likert- I am concerned that someone scale may find my personal information (email address, phone number, etc.) that I disclose within this service.

0.960

I am concerned that personal data I disclose within this service could be misused. I am concerned about disclosing personal information within this service because it could be used in ways that I cannot foresee. I am concerned about disclosing personal information within this service because I do not know what others might do with that information. (continued)

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Table 3.9 (continued) construct

source

Discomfort regarding the Service

Park and John 7-point-likert- In this service, I feel (2010) scale uncomfortable.

scale

item adaptation

Perceived Social Presence within the Service

Gefen and 7-point-likert- Within this service there is a Straub (1997) scale form of direct contact.

α 0.932

In this service, I feel uneasy. In this service, I feel bothered. 0.963

Within this service there is a form of personality. Within this service there is a form of sociability. Within this service there is a form of warmth. Within this service there is a form of human sensitivity.

We checked that all subjects understood and perceived the central factors of the manipulation (presence of a human frontline employee in a technology-based service: not given vs. given) by asking what kinds of services were depicted (technology-based service only; human frontline employee-based service only; technology-based service, including the presence of an additional human frontline employee; technology-based service, infused by an additional digital service technology). Nine subjects were not able to name the correct manipulation and were therefore eliminated from the dataset, leading to a final sample size of 222 subjects (women: 58.11%) with an average age of 28.83 (SD = 8.36) years. With respect to the dataset, we made sure that the subjects were equally distributed between the different technological-based service interactions (pure technology-based service encounter: N = 108; presence of a frontline employee in a technological-based service encounter: N = 114). We controlled for attitude towards PoS technology (adapted from Porter and Donthu, 2006) (F(1,220) = 0.84, p = 0.36) and for the regularity of customers to visit the stationary retailer (F(1,220) = 0.47, p = 0.49) regarding the experimental factor of not given or given the presence of a human frontline service employee. Yet we did not find any systematic distortion concerning our treatments.

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Findings

To test the hypotheses, we conducted multiple ANOVAs. The mean scores of customers’ expected information quality within the service and customers’ privacy concerns related to retailers’ data-handling practices are shown in Table 3.10 as a function of the experimental conditions. Table 3.10 Results of ANOVA-testing of the dependent variables Dependent Variables

Infusion of a human Frontline Service Employee (in a Technology-Based Service)

Mean (SD)

F-Value (η2 )

(Expected) Information Quality within the Service

not given

4.91 (1.41)

given

4.49 (1.47)

4.85* (0.022)

Privacy Concerns related to the Service

not given

4.61 (1.74)

given

3.81 (1.84)

11.11*** (0.048)

Note: SD = Standard Variation; *p < 0.05, **p < 0.01, ***p < 0.001

Findings show a significant decrease in customers’ expected information quality within the service in terms of a given human frontline employee in technology-based service encounter, leading to a confirmation of H1. Moreover, the presence of a frontline employee in a technology-based service encounter seems to decrease customers’ privacy concerns related to the service. Hence, results support our assumptions of H2. We also checked whether the findings remained constant due to the different images presented to the female and male customers. Regarding customers’ expected information quality within the service, in case of no infusion of a frontline employee, female and male customers do not show any difference (Mnot_given/female = 4.92 (SD = 1.55); Mnot_given/male = 4.91 (SD = 1.26); F(1, 106) = 0.01, p > 0.05, η2 = 0.000). Given a frontline employee within the service, findings show a certain difference, however, this is not significant (Mgiven/female = 4.67 (SD = 1.24); Mgiven/male = 4.17 (SD = 1.76); F(1, 112) = 3.21, p > 0.05, η2 = 0.028). One explanation for the slight difference could be that men are understood to be more self- or goal-oriented, while women can be seen as other or socially oriented (Meyers-Levy, 1988; Meyers-Levy and Loken, 2015). This could explain why female customers value the presence of a human frontline worker more than male customers. With respect to customers’ privacy concerns related to the service, again, no significant difference between female and male customers can be presented (Mnot_given/female = 4.58 (SD = 1.82); Mnot_given/male = 4.64 (SD = 1.67); F(1, 106) = 0.04, p > 0.05, η2 =

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0.000; Mgiven/female = 3.95 (SD = 1.78); Mgiven/male = 3.57 (SD = 1.93); F(1, 112) = 1.15, p > 0.05, η2 = 0.010). To test the two proposed mediating impacts of customers’ discomfort with the service and of customers’ perceived social presence within the service on the relationship between the form of technology-based service encounter and the dependent variables, we used PROCESS (Model 4) by Preacher and Hayes (2008) as suggested by Zhao et al. (2010). Following the approach of Baron and Kenny (1986), results of the corresponding tests confirm the fulfilment of the suggested conditional steps for a mediation for both mediating influences. In detail, first we checked the influence of the infusion of a human frontline employee on the mediators (Table 3.11). Table 3.11 Results of ANOVA-testing of the mediating variables Mediating Variables

Infusion of a human Frontline Service Employee (in a Technology-Based Service)

Mean (SD)

F-Value (η2 )

Discomfort regarding the Service

not given

2.82 (1.47)

given

3.63 (1.76)

13.60*** (0.058)

Perceived Social Presence within the Service

not given

2.35 (1.46)

given

4.34 (1.89)

84.03*** (0.276)

Note: SD = Standard Variation; *p < 0.05, **p < 0.01, ***p < 0.001

We could also confirm a significant relation between customers’ discomfort regarding the service and their (expected) information quality within the service (ß = –0.188; p < 0.01) as well as customers’ perceived social presence within the service on their privacy concerns related to the service (ß = –0.226; p < 0.001). In addition, no gender differences could be found among the mediators, either. In relation to customers’ discomfort regarding the service (Mnot_given/male = 2.84 (SD = 1.36), Mnot_given/female = 2.80 (SD = 1.56), F(1, 106) = 0.02, p > 0.05, η2 = 0.000; Mgiven/male = 3.56 (SD = 1.93); Mgiven/female = 3.66 (SD = 1.67); F(1, 112) = 0.08, p > 0.05, η2 = 0.001) as well as social presence within the service (Mnot_given/male = 2.34 (SD = 1.35), Mnot_given/male = 2.37 (SD = 1.56); F(1, 106) = 0.01, p > 0.05, η2 = 0.000; Mgiven/female = 4.46 (SD = 1.75), Mgiven/female = 4.26 (SD = 1.74), F(1, 112) = 0.34, p > 0.05, η2 = 0.003; F(1, 127) = 41.20, p < 0.001, η2 = 0.245), we could not find such an effect. Finally, results support H3a, as the indirect effect of the form of technologybased service encounter on customers’ expected information quality through

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customers’ discomfort is significant (indirect effect: β = –0.1340; LLCI = – 0.2775; ULCI = –0.0220; R2 = 0.051) with a confidence interval that excludes 0 (Preacher and Hayes, 2008). We also found a significant indirect effect of the form of technology-based service encounter on customers’ privacy concerns though customers’ perceived social presence (indirect effect: β = –0.3129; LLCI = –0.6210; ULCI = –0.0059; R2 = 0.023). Therefore, we can empirically confirm H1b and H2b. In summary, the results underline our assumption that customers develop a certain discomfort when they experience a technology-based service that is passively accompanied by a human employee. This seemed to be responsible for a decrease in expected information quality. In fact, customers seem to decide about their comfort level first, which then leads them to rank the information quality of the service. A similar effect can be explored in relation to customers’ privacy concerns about the service, which does not appear to be explained directly, but via customers’ perceptions of the social presence of the service, which is more pronounced in the case of a frontline employee involved in the technology-based service.

3.3.5

Discussion, Implications and Future Research

In contrast to previous studies considering the infusion of technology with frontline employee-based service encounters, our study focuses on the question of how customers are influenced by the presence of a frontline employee within a technology-based service encounter at a physical PoS. Our findings give reason to argue that customers react ambivalently when a human frontline employee is present, particularly with respect to the perception of information quality and privacy concerns regarding the service. We provide empirical evidence that the presence of a frontline employee in a technology-based service encounter reduces customers’ expected information quality within the service. Drawing on role and script theories (Halpern, 1997; Wang et al., 2012), findings suggest that the presence of a human frontline employee changes customers’ perception of the technology-based service, even though the employee does not intervene in the process actively. As the expected information quality of the service is higher when no frontline employee is present, the customer’s understanding of the script of a purely technology-based service primarily involves the presentation of high-quality, unbiased information on the current product topic to the customer. This process can be disturbed by an employee, who can make interaction with the technology more uncomfortable for

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the customer. Thus, the script would be disrupted by the frontline employee, and the quality of the expected information would decrease accordingly. The frontline employee disrupts this undistorted information exchange by simply being a ‘supportive’ presence. Based on Giebelhausen et al. (2014), that a technology can function as a distraction in service between the customer and the frontline employee, we find reason to assume that, in turn, a frontline employee can also distract the service between a customer and a technology, particularly in terms of customers’ perception of information quality. The mediating effect of eliciting a higher level of discomfort through the involvement of a frontline employee confirms Esmark’s et al. (2017) approach. The results show that this increased discomfort is then largely responsible for a decrease in the expected quality of information in the service. Social presence theory (Short et al., 1976) further contributes to understanding customers’ perceptions of potential privacy concerns about PoS technologies. Even if customers expect lower information quality within the service, the presence of a frontline employee at a technology-based service reduces privacy concerns related to retailers’ data processing practices. Customers need something or someone to ‘hold on to’ in this regard, as unconscious disclosure of data is now a widespread problem in both online and brick-and-mortar shopping (Huang, 2017; Wang et al., 2021). This (even if only emotional) ‘holding on’ seems to be already given to customers by the mere (passive) presence of the service employee within technology-based service. Here, a significantly higher social presence (due to the given/increased perception of human involvement) is attributed to this form of the service, which is, in the sense of the social presence theory due to the actual human presence, also the logical consequence. However, this perception of higher human/social presence is a key factor for this when it comes to a sensitive topic such as potential disclosure of data or privacy concerns or their reduction. Thus, our results are consistent with the theoretical approaches of van Doorn et al. (2017) and Grewal et al. (2020). As service encounters have continuously evolved over time, and the adoption of in-store technology at the PoS is widespread (de Keyser et al., 2019; Grewal et al., 2020), these findings highlight that the interplay between technology and frontline employee during customer interaction is a sensitive issue for retailers. Based on our findings, we suggest that retailers strike a balance that allows customers to interact with technology independently and provide them with more quality of information. However, it is also apparent that privacy concerns are heightened in this setting due to the potential collection of personal data. Research and retail practice emphasise that customer data is now essential for optimising and personalising their services (Grewal and Iyer, 2017; Huang,

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2017), making it important for retailers to alleviate these concerns as much as possible. Indeed, there is a fine line between integrating innovative technologies into the shop in a way that maximises freedom and independence in the search for the optimal product, but also does not pose a threat to customers’ privacy or personal data. Consequently, based on the findings of this study, future approaches should assess how the frontline employee can be optimally integrated into the service so the customer perceives the added value from the both technology and the frontline employee in a balanced way. It is necessary to keep customer concerns at an appropriate level, as too many concerns about the use of the technology-based service could lead to termination of that relationship; too few concerns could lead to or reinforce the customer’s intention to see no need for the frontline employee, and thus perhaps for the entire physical service. For this reason, the role of frontline employee needs to change, not in the sense of completely ‘adapting’ to technological changes, but in terms of being more sensitive to the feelings, desires and concerns of customers in the context of physical service. In the future, these competencies should be given greater consideration in the training of retail employees. Henceforth, we see the relevance of further analysis of the interplay between frontline employee competencies (Ford et al., 1987) and customer behaviour at the Point of Sale. This could contribute to a deeper understanding of how technology and frontline employee can optimally work together to create value for customers, especially considering interaction and attention-related aspects (Grewal et al., 2020). Future research should also focus on the aspect of perceived entertainment by technology within the interaction between customer, employee and technology. For example, Dabholkar and Bagozzi (2002) have shown that customers’ perceived enjoyment can help overcome potential negative feelings and discomfort when using service technologies. The impact of pleasure on customers’ privacy concerns has already been shown in general (Hwang and Kim, 2007; Pappas et al., 2012), but a more in-depth approach related to the presence of the human frontline employee is necessary to get a full picture of this area. Also, future research could consider atmospheric aspects of a physical shop environment (Eroglu et al., 2003), as well as customers’ interactions with technologies in service encounters in terms of Turner’s (1988) three process levels of interactions: motivational, interactional and structuring. Finally, as a limitation, we need to mention that the images, integrated as a support for the technology (Table 3.10), vary slightly. This might be the reason for the differences regarding female and male respondents’ expected information quality within the service when a frontline employee is present. Nonetheless, no significance could be shown, and results are in line with common literature, which gives reason to believe these variations do not affect the overall research.

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3.4

Essay 4. The Relevance of Corporate Information Transparency of the Use and Handling of Customers’ Data in Online Product Presentation

3.4.1

Introduction

For retailers, transparency strategies (Granados et al., 2010) are becoming more and more important. Not only is it paramount for retailers to provide comprehensive information on their products and processes (such as origin, shipping, manufacturing processes), customers also value transparency about the handling of their personal data. Access to the personal data of customers is of high importance for merchants and can enable them to gain a competitive advantage (Wakefield, 2013). As such, the exchange of data for certain added values is a much-discussed phenomenon in the current literature (e.g. Krafft et al., 2017). Companies must consider the trade-off between using information transparency to attract new customers and the corresponding risk of discouraging customers by collecting too much information and thus losing them to competitors (Tapscott and Ticoll, 2003). Losada-Otálora and Alkire (2019) and Zhou et al. (2018) empirically showed the positive impact of transparent communication towards the customer on key criteria, such as the attitude towards the company or even purchasing behaviour. Since this research deals with the positive effect of information transparency with regards to product or corporate communication, the focus is on information transparency in the disclosure of data use and storage in the advertising/communication of product offers by a service provider in an online product presentation. Offering such information on a company’s data use and handling is important for the customers (Kim and Kim, 2011; Tang et al., 2008; Tsai et al., 2011). An increasing number of products or applications require a constant flow of data between the customer and the service provider, the retailer or even the manufacturer (e.g. smart TVs, home assistants, smartphones). Although basic knowledge of this data flow is provided to many customers, the open presentation and communication of data do not automatically lead to an improvement of the perception of and response to these products or applications (John et al., 2011; Martin and Murphy, 2017). A problem may lie in ‘accepted obfuscation’. It can be assumed that many customers, even if they are aware of the fact of unconscious data disclosure, do not understand open data communication as a positive added value, nor do they want to. Despite the fact that transparency is increasingly becoming the focus of attention, it should be asked whether overly intensive/transparent communication on the subject of data disclosure could scare

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customers off, since they do not want to hear about the risk of potential misuse of their disclosed data, even if they are subconsciously aware of it. Consequently, we question the extent to which highlighting it could cause the customer to evaluate a product differently and adjust the purchase-related reaction accordingly. In this analysis, we refer to Bettman’s (1979) information processing model, which explains customers’ perceptions of transparent information regarding the evaluation of and reaction to certain forms of product presentations. It is assumed that the mention of higher transparency regarding the information on the use and handling of data by the company would lead to an overemphasis of this topic within the framework of information processing by customers, which could change their behaviour or reactions (Holbrook and Hirschman, 1982). Due to the differences in information processing by the customers, triggered by different levels of information transparency, the willingness to buy could decrease (Al-Qeisi et al., 2014; Everard and Galletta, 2005), and the perceived value of the product or the customers’ willingness to pay could also be affected (Chang and Wildt, 1994). In the context of potential data disclosure, the privacy calculus theory (Laufer and Wolfe, 1977) illustrates the customers’ trade-offs with respect to the benefit/cost calculation in a purchase process (Culnan and Armstrong, 1999). Based on the theory, this study assumes that when the perceptions of transparency regarding data use and handling are higher, that information is processed more intensively, and the perceived costs due to potential data disclosure increase. This upsets the balance between the costs and benefits, and customers adjust their behaviour accordingly. The higher costs can also be attributed to the company’s emphasis on data usage. This information is inherent in the transparent communication of data use and handling and could represent a corresponding trigger for the customer, which significantly influences the perceived increase in costs. Higher costs lead to a negative adjustment in the purchase-related processes associated with it. We assume that the potential increase in cost perception regarding data use and handling will increase perceived information transparency, but contrary to current literature (e.g. Granados et al., 2010; Lam et al., 2020; Losada-Otálora and Alkire, 2019; Zhou et al., 2018), we suppose that it will negatively impact retailer sales. Moreover, this study considers customer trust towards the service provider (which is responsible for the distribution of the product or advertising) as crucial for the purchase decision or willingness to pay of the customers. In addition, the fundamental data privacy concerns of customers are posited as an important moderating factor. This research thus focuses on two primary questions:

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RQ 2.

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How do customers respond to a higher level of information transparency about the service provider’s data use and handling in terms of purchase intention and willingness to pay? To what extent does customer trust in the service provider have a significant mediating influence, and the associated privacy concerns a moderating influence, on the relationship between the level of information transparency of data use and handling and the customers’ purchase intention and willingness to pay?

This research contributes to the understanding of customer behaviour in the context of information transparency in a product presentation in several ways. Based on the assumptions and implications of Bettman’s (1979) information processing model and the privacy calculus theory (Culnan and Armstrong, 1999; Laufer and Wolfe, 1977), we can show that when there is information transparency in data use and handling, customers’ purchase intentions as well as their willingness to pay decrease. We can provide empirical evidence that open/transparent communication does not automatically lead to benefits and can even backfire. Furthermore, we can show a mediating influence of customer trust towards the service provider’s data use and handling and a moderating influence of customer privacy concerns on customers’ purchase intentions. From our findings, we can derive important implications for research and future studies as well as for the retail industry. We will also highlight strategies for future product presentations and emphasise regulating the intent to present information transparency within an ad.

3.4.2

Conceptual Framework and Hypotheses Development

According to Granados et al. (2010), strategies on information transparency refer to the decision of disclosing or withholding information and includes both the quantity of information and the quality of a corresponding interface. The way information is displayed and organised in a user interface can also influence accessibility (Degeratu et al., 2000). In retail, customers often face the problem that necessary information is either not available or deliberately not provided by the company, which is one factor for the purchase-related decision-making process on the customer side (Zhou et al., 2018). Although numerous product presentations often provide plenty of information, accessibility may be poor due to an overly complex form of presentation such that buyers cannot easily use information that is important for their purchase decisions, or it is not perfectly

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accessible for them (Granados et al., 2010). Simple forms of product presentations that provide only the necessary information generally improve transparency (Galitz, 2007). In addition to several elements for transparent information communication by companies, such as product, price and storage costs, Granados et al. (2010) also emphasise the importance of the form of information presentation for transaction processes. The relevance of transparency in relation to the company’s internal management and production process, including data protection, has been addressed. Based on this basic business-to-customer transparency strategy, clear communication about the use and handling of personal data by the company during product presentations can even be counterproductive (John et al., 2011; Martin and Murphy, 2017). Based on Bettmans’ (1979) information processing model, which goes back to Miller’s (1956) processing paradigm, individuals are information processing systems (Johnson-Laird, 1993; Lachman and Lachman, 1986). In concrete terms, this means that the selection, interpretation, coding, storage and retrieval of information are relevant in explaining human behaviour (Bijttebier et al., 2003). It is precisely these processes that play an essential role in the reactions or behaviour of customers when a higher level of information or information transparency is provided on the topic of data use and handling. It can be argued that an overemphasis on certain information leads to higher complexity in customers’ information processing. This is especially likely in the matter of the data use and handling of a service provider. Accordingly, these processing procedures in relation to a more transparent information base can lead to a reduction in customers’ buying behaviour or willingness to pay (e.g. Chang and Wildt, 1994). The approach of a cost-benefit trade-off has already been frequently applied in the existing literature on information exchange relationships (Homans, 1961; Blau, 1964). The privacy calculus theory starts here and focuses on the costbenefit ratio regarding the potential disclosure of personal data by individuals (Culnan and Armstrong 1999; Dinev and Hart, 2006; Dinev et al., 2008; Jiang et al., 2013; Laufer and Wolfe, 1977; Li, 2012). In principle, it can be assumed that customers will only accept a potential (future) exchange of data, i.e. purchase the product, if the expected outcome is positive or a certain added value exceeds the calculated costs of the exchange (e.g. Culnan and Armstrong, 1999; Laufer and Wolfe, 1977). As attested by Homans (1974), customers consider all available sources when weighing the potential costs and associated rewards of the potential underlying information exchange. As such, value is understood as desirable physical objects, psychological pleasures or social benefits, which correspond to the transparent communication of information about data use and interaction in

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this study. By contrast, costs are regarded as harmful or even as social and psychological penalties, which are likely to further increase through the transparent communication of dealer use and handling of potentially disclosed customer data. We argue that customers’ inherent privacy concerns moderate this relationship. We focus on the potential impact of the service provider’s emphasis on transparency of data use and handling. Hereby, we included customers’ trust towards the service provider’s data use and handling as a mediating influence (e.g. Chang and Chen, 2008; Hong and Cha, 2013; Weisberg et al., 2011). We systematically manipulated information transparency on data use and handling according to our previous argument. The resulting research model is shown in Figure 3.7.

Moderator

Experimental Factors

Dependent Variables

Privacy Concerns

Level of Information Transparency of Data Use and Handling (low vs medium vs high)

Purchase Intention

Mediator

Willingness to Pay

Trust Towards the Service Provider

Figure 3.7 Research Model for Essay 4

Studies have shown that customers generally respond positively to the communication of information on data security (e.g. Kim et al., 2016). However, customers deal with the reception of information in very different ways. This is mainly because the selection, interpretation, encoding, storage and retrieval of information are individual processes, which in turn result in different behaviours (Bijttebier et al., 2003). However, the basis of information processing follows a typical scheme (Bettman, 1979). Within this scheme, the provision of information on the subject of data usage and handling can lead to a more intensive discussion and interpretation of this information for the customer than if, for example, it is only about product-related information. Even though more comprehensive information about a product may stimulate a purchase (Argyriou, 2012), a higher level of information transparency about data use and handling outweighs a lower level of such, with regards to information processing. It creates a higher potential for certain interpretations about the service provider’s data use and handling, thus negatively influencing purchase intention. This assumption is consistent with the exchange theory (Blau, 1964; Homans, 1961), as information about data use and handling induces a more intensive trade-off based on higher assumed costs

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of a potential data price. It is assumed that these higher costs ultimately have a negative impact on customers’ willingness to buy and pay. H1:

A higher customers’ perceived level of information transparency of data use and handling decreases (a) the customers’ purchase intention and (b) the customers’ willingness to pay.

Customers’ attitudes towards privacy imply a significant influence on their intention and behaviour in service encounters (Jahangir and Begum, 2007; Li, 2012; Shin, 2010). Research has also shown that strong privacy concerns significantly influence purchase decisions (Malhotra et al., 2004). In addition, general literature has indicated that customers with higher data privacy concerns in the online shopping context rate the purchasing process more negatively (Phelps et al., 2001). This effect is assumed to particularly apply to service providers’ low level of transparency with regards to data use and handling. This means that customers with higher privacy concerns, in contrast to those with lower privacy concerns, are more critical of transparent communication in relation to the purchasing process, since from their perspective, the information in the product presentation is not sufficiently presented in light of data use and handling. However, if transparency is higher and the customer has more leeway to process the relevant information (Bettman, 1979; Bijttebier et al., 2003), in contrast to previous literature, increases in customers’ willingness to buy and pay hardly differ in terms of the degree of privacy concerns. Therefore, we expect a moderating role of the customers’ privacy concerns on the influence of the perceived level of information transparency of data use and handling on the customers’ purchase intention. The same applies to the customers’ willingness to pay: H2:

The customers’ privacy concerns moderate the hypothesised impact of the perceived level of information transparency of data use and handling on the customers’ purchase intention (a) as well as the customers’ willingness to pay (b).

Trust is considered one of the key elements in the relationship between the company and the buyer (Hong and Cha, 2013; Lee and Turban, 2001). The purchase of digital products often automatically goes hand in hand with a long-term connection to a service provider or manufacturer; therefore, fundamental trust in the processes of a service provider is an important prerequisite for the willingness to use a product (De Reuver et al., 2015; Goh et al., 2016) and, above all, to buy it in the first place. Organisational information on the use and handling of data, which can basically be understood as part of transparent communication, has also

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been shown to have a positive effect on trust (Lwin et al., 2007; Meinert et al., 2006; Milne et al., 2012). The provider’s offer of transparency of their products and manufacturing process or composition should also positively influence this trust (Lam et al., 2020). However, based on the assumptions and explanations of Bettman (1979) and Bijttebier et al. (2003), we assume adapted information processing among customers due to the data use and handling problem, which can lead to reduced trust in the service provider caused by the customers’ reception of this transparent information on the use and handling of customers’ data. Cognition, affection and behaviour in information processing may consequently deviate from the regular scheme (Holbrook and Hirschman, 1982). As more privacyrelated information is communicated with the intention of transparency in this relationship, a loss of trust may result. This is also an additional explanation for the reduction in the customers’ purchase intention and willingness to pay. In line with several studies that motivate trust as an important mediator (e.g. Chang and Chen, 2008; Hong and Cha, 2013; Weisberg et al., 2011), we therefore assume that, with a more transparent presentation of data use and handling, customers first adjust their trust in the service provider’s data use and handling downwards, which ultimately has an impact on their willingness to purchase and pay: H3:

3.4.3

The trust towards the data use and handling of the service provider mediates the hypothesised relation of the perceived level of information transparency of data use and handling on the customers’ purchase intention (a) as well as the customers’ willingness to pay (b).

Empirical Studies: Method and Procedure

The hypotheses of this research were tested in an experiment that used a between-subject design with three scenarios in which the levels of information transparency of data use and handling were low vs medium vs high. First, all subjects were told to imagine themselves looking for a new smartphone. Then, they were asked to find the corresponding presentation of a service provider on the internet. A fictional online offer containing an actual product display of a smartphone was presented. In order to reduce the complexity of the product presentation, especially with regards to customers’ purchase intentions (e.g. in terms of knowledge about the product) (Barber et al., 2012), and because we assumed that most participants had already encountered such a product presentation, we used a common image of a product presentation of a smartphone. Across all scenarios, the subjects were informed that their personal data could be used for

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personalised advertising content on the lock screen. Moreover, to manipulate the different levels of information transparency about the conditions of data use and handling, we used a scenario technique that either contained no information transparency about data use and handling (low level of information transparency) in scenario one and successively increased this information in twosteps (medium and high levels of information transparency). Thus, each subject was exposed to one of three experimental conditions (Figure 3.8).

Level of Informaon Transparency of Data-Use and Handling: low 128 GB LTE Dual-Sim; 6.1 inch, 8 GB RAM Enjoy all your favorite videos and photos in crisp resoluon on the 6,1-inch Infinity-U display with Super AMOLED FHD+ technology. The versale quad camera shows you at your best with the 32 MP selfie camera.

Product contains personalized ads in lock screen

128 GB LTE Dual-Sim; 6.1 inch, 8 GB RAM Enjoy all your favorite videos and photos in crisp resoluon on the 6,1-inch Infinity-U display with Super AMOLED FHD+ technology. The versale quad camera shows you at your best with the 32 MP selfie camera.

Product contains personalized ads in lock screen • Adversing content is displayed silently for a few seconds on the spear screen. • Daily analysis of smartphone usage for opmal generaon of individually tailored adversing content.

128 GB LTE Dual-Sim; 6.1 inch, 8 GB RAM Enjoy all your favorite videos and photos in crisp resoluon on the 6,1-inch Infinity-U display with Super AMOLED FHD+ technology. The versale quad camera shows you at your best with the 32 MP selfie camera.

Product contains personalized ads in lock screen • Adversing content is displayed silently for a few seconds on the spear screen. • Daily analysis of smartphone usage for opmal generaon of individually tailored adversing content. Data-Security Informaon: Data is stored according to the applicable privacy policy. Guaranteed no disclosure of data to third pares. Informaon on the quanty and quality of the stored data can be requested at any me. Data is used to opmize future products and services of the company.

Level of Informaon Transparency of Data-Use and Handling: high Figure 3.8 Experimental Design for study

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In this online experiment, the respondents were randomly assigned to one of the experimental conditions. Afterwards, they answered a corresponding questionnaire. The included constructs are presented in Table 3.12. To obtain construct values, indicator values per construct were mean aggregated. Table 3.12 Constructs, sources, item adaptation and Cronbach’s alpha. All scales (besides willingness to pay) were measured on a 7-point-Likert-scale: 1 = I totally disagree—7 = I totally agree α

Construct

Source

Item Adaptation

Level of Information Transparency of Data Use and Handling

Zhou et al. (2018)

By studying all the 0.907 information from the product advertisement on the provider’s data use and handling, I could know the product and the processes of the company in the background very well. I have a clear idea of the product and the company’s processes in the background after studying all the information in the product advertisement on the provider’s data use and handling carefully. I had a clear idea of the product and the company’s processes in the background after studying all the information in the product advertisement on the provider’s data use and handling carefully. I could fully understand the product and the company’s processes in the background after studying all the information in the product advertisement on the provider’s data use and handling carefully. (continued)

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Table 3.12 (continued) Construct

Source

α

Item Adaptation Overall, the product and the company’s processes in the background were transparent to me through the product advertisement on the provider’s data use and handling.

Purchase Intention

Pavlou (2003)

It would be possible that I would buy the smartphone shown.

0.908

It would be likely that I would purchase the smartphone shown in the future. I would consider purchasing the smartphone shown. Willingess to Pay

van Westendorp (1976)

Please indicate how many euros you are willing to spend for the product, between e100 and e800.

–

Trust in the Service Provider

Sheinin et al. (2011)

The data use and handling by 0.946 the service provider is trustworthy. The data use and handling by the service provider gives the impression that he keeps promises and commitments. I believe that the data use and handling by the service provider has my best interests in mind.

Privacy Concerns

Dinev and Hart (2006)

I am concerned that the information I submit on the internet could be misused.

0.945

I am concerned that a person can find private information about me on the Internet. (continued)

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Table 3.12 (continued) Construct

Source

Item Adaptation

α

I am concerned about submitting information on the internet because of what others might do with it. I am concerned about submitting information on the internet because it could be used in a way I did not foresee.

In the study, 142 subjects (women: 50.70%) with an average age of 28.95 (SD = 9.88) years took part. All scenarios were equally distributed with respect to age, gender and overall privacy concerns. The assumed manipulation was successful (level of information transparency of data use and handling: Mlow = 2.78 (1.16), Mmedium = 2.97 (1.26), Mhigh = 3.56 (1.63), F(1, 139) = 4.14, p < 0.05). According to Tukey post hoc testing, we identified a significant difference only between the low and high levels of information transparency of data use and handling (p < 0.05). Despite this, we did not remove the middle scenario from our analysis, as this scenario illustrated the steady decrease in customer perception and response from a high to a low state. Finally, we controlled for the general privacy concerns (F(1, 139) = 1.54, p = 0.22), general affinity towards smartphones (F(1, 139) = 1.46, p = 0.23) and affinity towards personalised offers (F(1, 139) = 0.17, p = 0.84) of our respondents. Overall, we did not find any systematic distortion between our treatments.

3.4.4

Findings

In order to test the hypotheses, we conducted several ANOVAs. The mean scores of the dependent variables in the experimental conditions and the results of H1 are summarised in Table 3.13. The findings generally implied that the information transparency of data use and handling seemed to have an impact on the customers’ purchase intention as well as the customers’ willingness to pay. The results generally supported our assumptions towards an empirical confirmation of H1a and H1b, whereas post

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Table 3.13 Results of ANOVA-testing Dependent Variables Level of Information Mean (SD) Transparency of Data Use and Handling Purchase Intention

low (N = 45)

3.38 (1.47)

medium (N = 47)

2.82 (1.39)

high (N = 50) Willingness to Pay

low (N = 45)

F-Value (η2 )

6.403** (0.084)

2.39 (1.15) 430.38 (209.73) 3.490* (0.048)

medium (N = 47)

394.47 (220.99)

high (N = 50)

321.92 (183.34)

*p < 0.05, **p < 0.01, ***p < 0.001

hoc tests produced just-significant results between the low and high conditions in both cases (p < 0.05). We used PROCESS (Model 1), as suggested by Hayes (2019), to test the hypothesis of whether customers’ privacy concerns moderate the relationship between the information transparency of data use and handling and the dependent variables. We added the experimental scenario as an independent variable with dummy coding (Hayes, 2017), and the customers’ purchase intention and willingness to pay gradually as dependent variables. In line with our expectations, there was a significant moderating effect on the purchase intention of the customers (Int1: β = 0.21, p < 0.05, LLCI = 0.0379, ULCI = 0.3722, R2 = 0.0341). From this, it can be concluded that the greater the concern of the customer regarding the protection of privacy, the smaller the decrease in the customer’s intention to buy when the level of information transparency was increased. Figure 3.9 illustrates this effect. Post hoc tests only showed this result with respect to the low vs high conditions of transparency (Int1: β = 0.42, p < 0.05, LLCI = 0.0802, ULCI = 0.7549, R2 = 0.0367). A moderation of the relationship between the customers’ perceived level of information transparency of data use and handling and the willingness to pay by the customers’ privacy concerns could not be supported. In summary, we can empirically support H2a but not H2b. Concentrating on the proposed mediating impact of customers’ trust towards the service provider’s data use and handling on the relationship between the information transparency of data use and handling and the dependent variables, we used PROCESS (model 4) by Preacher and Hayes (2008), as suggested by Zhao et al. (2010). Following the approach of Baron and Kenny (1986) with respect to the conditional steps for establishing a mediation, the results of the

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5 low privacy concerns medium privacy concerns

4.5

high privacy concerns

4 3.5 3 2.5 2 1.5 low level of transparency

medium level of transparency

high level of transparency

Figure 3.9 Results of moderation-testing of customers’ privacy concerns on customers’ purchase intention

corresponding tests confirmed the fulfilment of Steps 1–3 (Step 1: included in Table 3.13; Step 2: trust in the service provider Mlow = 3.64 (1.33), Mmedium = 3.48 (1.50), Mhigh = 2.71 (1.29), F(1, 139) = 6.31, p < 0.01; Step 3: on purchase intention: β = 0.25, t = –3.14, p < 0.01 and on willingness to pay: β = 35.38, t = –2.89, p < 0.01). As Tukey post hoc testing only presented a significant difference between the low and high levels of information transparency, further steps concentrated on the mediation in this relation. The indirect effect of the level of information transparency of data use and handling on the customers’ purchase intention (β = –0.24, LLCI = –0.47, ULCI = –0.06, R2 = 0.047) and the customers’ willingness to pay (β = –32.66, LLCI = –72.93, ULCI = –5.27, R2 = 0.021) through the customers’ trust towards the data use and handling of the service provider was significant with a confidence interval that excluded 0 (Preacher and Hayes 2008). Again, post hoc analysis of the customers’ purchase intention and willingness to pay emphasised these findings, but only with regards to low vs high conditions and not with respect to the low vs medium conditions. To sum up, the findings led to the partial support of H3a and H3b. This means that, given a high or low level of transparency of data use and handling, the customers seemed to first adjust their trust in the service provider’s data use and handling. In the second step, however, this perception directly impacted their purchase intention.

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Discussion

The findings showed that a high level of information transparency during a product presentation with regards to data use and handling had a negative impact on customers’ perception of and reactions to the product presentation. The results also showed a negative effect of the perceived level of information transparency regarding customers’ purchase intention and willingness to pay. These results go against the basic assumption that data security information elicits a positive response from customers (Kim et al., 2016). On the contrary, we can support the argument of John et al. (2011) and Martin and Murphy (2017) that, under certain conditions, less information on data security improves customers’ purchase-related and willingness-to-pay responses towards organisations. Regarding the transparency of the service provider’s disclosure of data use and handling, our results imply that it impacts customer behaviour negatively, thus contradicting the findings of Losada-Otálora and Alkire (2019) and Zhou et al. (2018) as well as the basic assumptions of Granados et al. (2010) and Lam et al. (2020). Based on the information presented, customers seem to form a comprehensive picture of what could happen with the potentially disclosed data in the background on the service provider site. This goes hand in hand with the assumptions of a cognitively more complex information processing procedure (Bettman, 1979). The interpretative challenges of higher transparency perceptions affect customer behaviour accordingly, which seems to trigger an adjusted reaction/image of the product presentation, compared with lower transparency (Holbrook and Hirschman, 1982). Especially with regards to the interpretation and encoding of information (Bijttebier et al., 2003), customers seem to differentiate between the presence and absence of information on data use and handling. Although Bernstein’s (2012) research was carried out in an organisational environment, our results support the transparency paradox discussed there, i.e. a certain degree of transparency can also be an explanation for general human behaviour within advertising effectiveness research. In line with Berstein (2012), higher levels of transparency appear to lead customers to wonder about the choices a service provider can make regarding the data that may be disclosed, which ultimately leads to lower purchase intent. Customers and employees react similarly pertaining to transparent information about possible intrusions into their privacy. Our study supports low-level communication regarding certain information, but further research needs to clarify this aspect. It is possible that this reaction is not the same for every form of information. Specifically, we found no evidence for Zhou et al.’s (2018) assumption that information transparency increases customers’ purchase intention. Nevertheless,

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the results are consistent with the impression that an overemphasis on data use and handling leads to lower trust in a service provider’s protection and handling of data. Analogous to existing studies, we confirmed a mediating effect of trust in the service provider’s data use and handling on the relationship between the level of transparency and customers’ purchase intention (Chang and Chen, 2008; Hong and Cha, 2013; Weisberg et al., 2011). Furthermore, the central importance of customer trust in relation to data-related issues can be highlighted (Lwin et al., 2007; Meinert et al., 2006; Milne et al., 2012). However, the specific results regarding the negative impact of information transparency on trust is new. With regards to the customers’ evaluation and perception with the intention of improving trust (Lam et al., 2020), the field of information transparency of datarelated factors seems to need further research. Future research could investigate the extent to which information on this aspect is valuable for the customer and at what point the interest to buy decreases.

3.4.6

Implications for Management & Future Research

It is becoming more and more important for companies, retailers and service providers to generate customer-specific offers according to their preferences, requirements and potential wishes (Karwatzki et al., 2017a), which also have to be advertised with the necessary depth of information to produce positive purchase-related results (Losada-Otálora and Alkire, 2019; Zhou et al., 2018). The results of this study emphasise somewhat negative effects of information transparency on customers’ behaviour and their purchase-related reactions. Even though product-related information and information on data use and handling are two different fields, service providers and retailers must be careful with the open and transparent communication of data use and handling when facing customers. Particularly when promoting and maintaining a transparent corporate strategy, it is important to determine how much information on data use and handling should be given out or withheld or not openly communicated in the interest of corporate advantage. However, access to this information must be available to the customer at all times, even if it is not on the first page of the product presentation, because it is still true that a key challenge for service providers and retailers in both online and offline commerce is to make customers feel that their privacy is protected (Acquisti et al., 2015). Future research may need to focus more on this trade-off and the optimal level of transparency.

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As the digital transmission of data in the context of digital shopping offers is being discussed more and more intensively, it is particularly important to protect those who find it difficult to navigate this environment, in the interest of consumer protection. Against the backdrop of this study’s findings, this means that consumer protection organisations should be aware of the influence of less transparent information on data privacy on the willingness to buy and sensitise customers accordingly. It is especially important to provide customers with an understanding that they are supplying their personal data, if such information is not provided (directly) by the company/service provider. The results also suggest that higher trust in a company/service provider does not necessarily depend on the amount of information. However, customers should not make individual purchase decisions based on the degree of situational trust in a company/service provider, especially if they notice that additional information tends to have a negative impact on this. If this situation prevails, companies/service providers will have a reason to disclose less and less information on the subject of data protection. This is neither in the interest of the customer nor of the consumer protection groups. Customers should therefore be made aware that the lack of information transparency in relation to data protection may mislead them into making overly hasty decisions regarding a company/service provider. This can have serious consequences for the customer and especially for the transfer of their data. In addition, the possibilities and necessities of adapting political frameworks in this context should be discussed. If companies/service providers make more strategic use of the importance of ‘intransparency’ strategies, policymakers should protect customers with the help of laws, specific regulations or standards. They can also define the level of information that must be provided to each customer. Nevertheless, customers should always ask themselves whether they have received all relevant information and how the information provided needs to be evaluated.

3.4.7

Limitations and Future Research

The limitations of this research were seen in the investigation of only one product category. Smartphones are well established in the customers’ everyday lives (Busch and McCarthy, 2021; Goh et al., 2016), which might have offset the results. Different digital products that play a less intuitive role in customers’ current shopping habits but still include the potential of information disclosure, such as voice assistance systems or smartwatches, can be investigated.

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In general, this study supported research by Fortes and Rita (2016) and Bolton and Saxena-Iyer (2009), which state that general privacy concerns seem to influence the customers’ purchase intention. However, further research is necessary on the actual factors of customers’ internal processing (Bijttebier et al., 2003), as these seem to negatively influence purchase decisions when the possible benefits of potential disclosure are included (Culnan and Armstrong, 1999; Laufer and Wolfe, 1977). Similar to numerous studies on the perception of transparency-oriented information (e.g. Losada-Otálora and Alkire, 2019; Zhou et al., 2018), this study also focused on the processing of the information presented. However, due to the non-dynamic presentation of information on the product detail page, it was not possible to capture whether or to what extent customers would still search for further information on subpages (FAQ or imprint) during the purchase process. Especially when only partial information is provided, it would be interesting to see how intensively customers search for further information. Future studies should explore this point in depth. Another limitation of the present study was that only the information was tested or manipulated. Aspects related to the form of presentation of the transparent information were not considered. Nevertheless, the visual design of the information should also be explored in depth in future approaches. In particular, the transparent presentation of sensitive information, such as possible data use and processing, could have different effects within the purchase process of the online store. For example, this information could be presented directly on the landing page, category page, item detail page or only as part of the payment process. Since the degree of transparency exerts a significant influence on the willingness to buy, this information could also play an important role in the customer’s final decision when it is distributed on various pages or throughout the purchasing process. Furthermore, this study did not consider other forms of product presentations. In particular, the integration of the investigated transparent product presentation in social media is an exciting area for future research. For example, a recent study revealed that Facebook and Instagram are characterised by increased data-related tension (Bazarova and Choi, 2014). Customers are increasingly confronted with native advertising on social media platforms (e.g. influencer marketing), wherein companies try to blur commercial context when presenting a product by highlighting non-commercial aspects (Evans et al., 2017). It could be very interesting to see how customers process the disclosure or transparent communication of information with regards to the commercial aspect of a specific ad/product presentation in terms of advertising recognition. Recent studies suggest that this also has

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a negative impact on customer attitudes and behavioural intentions (Wojdynski and Evans, 2016). This study did not focus specifically on vulnerable customers. For these groups in particular, transparency of information about data flows and processing can lead to annoyance. It is possible that the transparent presentation of information is perceived more positively among this group than the participants of our study. Especially with regards to trust in a service provider, lower prior experience or knowledge of customers’ rights (Kawa and Zdrenka, 2016; Safari and Thilenius, 2013) may make the perception of transparent information more difficult to assess. For a topic as sensitive as data privacy, such information can create false incentives. Finally, our study was conducted in the German market. Previous research found several important differences between country markets in terms of personalities and demographics (e.g. age, gender, culture or education) as well as differences in customer behaviour regarding privacy concerns and data disclosure between countries (Mahrous, 2011; Miltgen and Peyrat-Guillard, 2014). Therefore, cross-cultural studies could provide additional insights into customers’ perceptions of information transparency in product presentations.

3.5

Essay 5. The Impact of IT/IS, Lifestyle and Income Related Influences on Customers’ Intention to Provide Digitally Transferred Access Permission in Last Mile Delivery—an Empirical Analysis before and during the COVID-19 Pandemic

3.5.1

Introduction

The steady growth of online shopping poses significant challenges for courier, express, and parcel (CEP) service providers regarding ‘last mile delivery’ design (Jindal et al., 2021; Mangiaracina et al., 2019). Generally, the primary interest of CEP companies is to provide the best service at the lowest cost (Savelsbergh and van Woensel, 2016). However, capacity and resource constraints experienced by CEP providers increase the pressure on delivery times. Recipients are often not at home when deliveries take place, resulting in negative effects such as misdeliveries, the choice of unsuitable storage locations, lost shipments, and delayed deliveries (Lu et al., 2016; Vanelslander et al., 2013). Savelsbergh and van Woensel (2016) and Perboli and Rosano (2019) emphasised that besides

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price, delivery time and quality of service, the level of environmental sustainability of the delivery is a crucial factor for customers. However, the COVID-19 pandemic showed that regard for customers’ health might also be an element to consider. The related literature emphasises that business processes and service alternatives need to adapt to the current situation, especially regarding the integration of information technology (IT) and information systems (IS) (Kuckertz et al., 2020). Innovative technologies offer possibilities for simplifying or accelerating delivery service processes for both customers and logistics companies, for example, by handling contactless service offers, since, among other things, unnecessary waiting times can be reduced (Reyes et al., 2017; Wang et al., 2018). We assume that customers’ willingness to adopt (contactless) technology-based delivery options increases during the pandemic. The integration of unattended home delivery requires balancing the benefits and costs to the CEP provider and customer (e.g. Fernie et al., 2010; Vakulenko et al., 2018). CEP providers must find a way to keep customers satisfied through consistent distribution costs and secure deliveries. Integrating innovative technologies, such as scanning parcel barcodes using a smartphone app (Ho et al., 2016), allows delivery drivers access to private areas at any time of day (Kokkinou und Cranage, 2015). The presence of a recipient or neighbour would no longer be necessary, as delivery drivers could use modern information and communication technology to gain access via the front door of a property or to a parcel locker (Hong et al., 2016). Deliveries can be made independently of the customer who will receive a message, for example, on their mobile phone, when the package has arrived (Iwan, Kijewska, and Lemke, 2016). Given the benefits of such deliveries, technology-based unattended delivery also comes with potential costs for the customer. Recent research has revisited the idea, concentrating on customers’ acceptance of self-service parcel services (Chen et al., 2018; Zhou et al., 2020). In the context of unattended home delivery, intelligent smart lock systems offer these possibilities (Reyes et al., 2017). An intelligent door system allows the owner to grant one-time access to a third party by transferring digital access permission via smartphone activation. The system requires an electronic door lock, web server, and mobile terminal for control (Ho et al., 2016). This concept has general privacy issues relating to unknown drivers having physical access to private areas. In addition, the implementation of these technologies raises further data-privacy issues (Mangiaracina et al., 2019). Accessing the front door of an apartment usually includes the potential for access to the most ‘intimate’ area of a customer’s home (e.g. the living room, kitchen area, office, or bedrooms, including those belonging to children).

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Our research aims to offer insights into customers’ motivations to integrate innovative technology-based delivery approaches into their everyday lives, given that the provision of digitally transferred access permission is an essential element. To optimise delivery routes and plan combined inner-city deliveries, delivery companies must have access to customer data (Savelsbergh and van Woensel, 2016; Taniguchi and Shimamoto, 2004). Besides location-based data, such as names and addresses, data might also include working hours or even the details of employers. In addition, studies emphasise the increasing relevance of mapping customers’ behaviour (Mangiaracina et al., 2019). By combining all these data, a CEP provider can generate a comprehensive picture of the traffic patterns of an area at a particular time of day, for example, and adjust delivery routes accordingly. Certain windows are better for deliveries (Boyer et al., 2009), avoiding traffic jams or obstructions (Savelsbergh and van Woensel, 2016). Inndeed, all necessary data are inevitably connected with digitally transfering access permission. Data safety and security are widely discussed issues concerning unattended home deliveries (Fernie et al., 2010; Mangiaracina et al., 2019; Reyes et al., 2017) and a comprehensive discussion on customer views on providing digitally transferred access permission to their front door has not taken place to date. Tsai and Tiwasing (2021) focus only on the common constructs influencing customers’ behavioural intention to use innovative technology such as a smart lock and its related IT and IS. This study concentrates on customers’ intention to provide digitally transferred access permission to a CEP provider. Based on the benefits and costs of (unattended) home delivery services identified from the literature, we derived three sub-influences argued to be decisive in terms of explaining customers’ intention to provide digitally transferred access permission: IT and IS influence (customer evaluations of issues concerning potential data sharing), Lifestyle influence (customer assessments of the (individual and altruistic) advantages of using this kind of service) and Financial influence (the impact of customers’ income level). In this way, we focus on specific factors of customer calculus, looking at privacy-related costs, which can be understood on the one hand as a combination of digital data-related privacy issues and physical privacy issues, and service-related benefits through such provision of access permission on the other. By investigating customers’ perceptions of digitally transferred access permissions concerning unattended home delivery services, our research contributes to knowledge in the field of retail. The COVID-19 pandemic forced customers to spend more time at home and adapt their work and shopping behaviours, and this study presents two perspectives on this topic through two independent data

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collection phases, (study 1) before the COVID-19 pandemic and (study 2) during the COVID-19 pandemic. Based on the assumptions and implications of the privacy calculus theory (Laufer and Wolfe 1977; Culnan and Armstrong 1999), we give an empirical answer to the research question: How have IT, IS, lifestyle and income influenced and impacted customers’ intention to provide digitally transferred access permission before and during the COVID-19 pandemic?

3.5.2

Conceptual Framework and Hypotheses Development

According to Dinev and Hart (2006) and Smith et al. (2011), the privacy calculus theory focuses on the trade-off between benefits and costs for customers regarding exchanging personal data for purchase-related added value. The starting point of this approach is the customer calculus or behavioural calculus, within the framework of which the ultimate decision-making process for the transmission of any personal data or the disclosure of privacy depends on the ‘nature’ of an individual (Laufer and Wolfe, 1977). It is important the customer understand the benefit of such a transfer, even if its consequences or the provision of personal data are not usually immediately apparent. This exchange is mainly expressed by transferring the customer’s preferences or wishes and the retailer’s corresponding provision of a suitable product. We assume that customers’ calculus for providing digitally tranferred conditional access follows the same intuition. Customers deposit some of their most private information with CEP providers and thus hand over a (digital) key able to access the most personal and intimate areas of their lives. Customer concerns in this area are primarily that property could be damaged or even stolen (Hübner et al., 2016). As a result, customers exchange information and access to their privacy to receive the most efficient, smooth and flexible delivery of goods they have ordered. In addition, according to Moor’s (1997) privacy theory, protecting customer data from access by others is a key privacy concern. In our case, these data protection concerns are not only to be understood in the context of digital concerns but also have an apparent influence on the ‘real’ world and on access to individual premises, which can increase customers’ perceived costs even more. Consequently, we understand customers’ decision-making processes concerning digitally transferred access permissions in unattended home delivery services as analogous to the process of benefit–risk calculations in the context of traditional purchasing processes in which information is exchanged in return for the best possible service, product or monetary incentive (e.g. Krafft et al., 2017; Li et al., 2011; Premazzi et al., 2010). The potential to transfer access to customers’ private

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areas to an unknown (delivery) person makes this technology approach even more sensitive. Based on discussions in the literature, we will focus on three different influences: IT and IS influence, Lifestyle influence and Financial influence. Whereas the IT, IS, and financial influences represent cost-related concerns, the lifestyle-related influence focuses on the benefits in this context. However, we consider all three influences as central antecedents for customers balancing the benefits and costs of providing digitally transferred access permission. This is consistent with Homan (1961, 1974) and Blau’s (1964) basic assumptions, which argue that an individual’s psychological pleasure and utility are conceptualised as a desirable state and costs or psychological punishment are understood as detrimental to exchanging information relating to an individual’s privacy or their access to someone else’s privacy. Therefore, the social benefit is understood as the efficient and flexible receipt of products. In contrast, the psychological punishment in this exchange relationship lies in the fact that the customer has to rely on the logistic company to store their access data securely, so they are not stolen by third parties, and the delivery driver does not carry out any improper actions such as theft or damage in the apartment. The perceived stability of, and trust in, the IT infrastructure (Söllner et al., 2016) and concerns about data misuse (Subashini and Kavitha, 2011) are assumed to impact customers’ intention to provide such digitally transferred access permission. The focus on customers’ trust in an IT infrastructure covers, as a result, the latent issue of potential misfunctions or miscommunications between the IT and IS artefacts of the smart locker and smartphone, which is required to initiate the access. Worries of this nature can arise if the front door cannot be opened upon delivery or cannot be closed again after the package has been deposited (Ho et al., 2016). Besides the IT-related technology, there are also IS-related factors influencing the customer. On the IS side, customers’ concerns about data misuse related to the CEP provider’s data management are another relevant factor. Still, these concerns are less tangible as they primarily relate to customers’ perceptions of the data security management of access permission within the IS or the CEP provider’s backend data management. Concerns related to customers’ privacy can be understood as individuals’ perceptions of data protection (Jiang et al., 2013; Malhotra et al., 2004). Customers are increasingly sensible when their personal data is transferred to a company, as these data can easily be shared without customers’ knowledge (Youn, 2009; Dinev and Hart, 2004). The literature provides reason to focus on the latent issue of the potential for criminal organisations to steal or spy on digitally transferred access permissions (Lu et al., 2011; Suryateja, 2018) and the resulting threat of finding a burglar or kidnapper in one’s home.

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Lifestyle Influences

IT and IS Influences

Moreover, Savelsbergh and van Woensel (2016) point out that customers define optimal delivery options in terms of time and environmental sustainability. For example, removing the need to collect parcels from a depot reduces traffic load, fewer missed delivery information slips left for customers reduces waste and more optimal planning of delivery routes, making delivery processes more predictable, reduces energy consumption. Studies show the increasing impact of environmental considerations on home delivery choices (Bertram and Chi, 2018; Fernie et al., 2010) and customers’ strong interest in the flexible design of leisurerelated and work-related tasks through the integration of innovative technologies (Allen et al., 2014; Chen and Karahanna, 2018). A simplified home delivery service could moreover be seen to potentially improve customers’ work–life balance, as parcels can be received independently from any fixed schedules. Lim et al. (2018) understand customers’ time flexibility as emotional costs. By decoupling home delivery processes from leisure plans, customers have the opportunity to invest the time saved in work-related tasks. In addition, the literature gives reason to assume increased levels of customer income negatively impact customers’ intention to provide digitally transferred access permission (Zukowski and Brown, 2007). The resulting research model is illustrated in Figure 3.10.

Trust in the CEP Provider’s IT Infrastructure

Concerns about Data Misuse related to the CEP Provider’s Data Management

Intention to Provide Digitally Transferred Access Permission

Perceived Environmental Sustainability of the Delivery Process

Perceived Work–Life Flexibility resulting from the Delivery Process

Income Financial Influence

Figure 3.10 Research Model for Essay 5

The expected performance of a given technology impacts the level of customers’ trust (Söllner et al., 2012). Pavlou (2003) explains that, due to the impersonal nature of transactions in the online environment, confidence in the

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applications and processes is of central importance to customer intentions to use or purchase. Smart locks on the front door should exhibit exceptional quality and integrity, as these are decisive factors in building customer trust in the technology (Söllner et al., 2016). Since customer trust plays a role in the perception of a service (e.g. Schoenbachler and Gordon, 2002; Swan et al., 1999), we assume that instilling trust in the relevant IT infrastructure is also an important aspect of unattended home delivery service. For example, functional problems or miscommunication between the IT systems involved can result in a failed delivery. Issues could include no traceable reason for the customer’s front door not opening, failing to close or unintentionally opening at another time (Ho et al., 2016). Following privacy calculus theory, we assume that the door not locking after delivery would particularly lead to a rejection of the customers’ intention to grant digitally transferred access permission, as the customers’ cost perception of unplanned and unwanted access to private areas increases. On the other hand, increased trust in the delivery service’s IT infrastructure can reduce these costs and highlight the benefits of providing digitally transferred access permission. H1:

Customers’ perception of trust in the IT infrastructure positively influences customers’ intention to provide digitally transferred access permission.

Im et al. (2011) point out that customers’ perception of a technology is an important starting point in analysing the technology’s usage, in respect of customers’ intention to get involved in the associated usage processes. Surrounding usage issues involve various factors. One aspect that has been discussed intensively in recent literature is customers’ concern when the using of such technology is directly related to the transfer of personal data (Hong and Thong, 2013; Miltgen and Smith, 2015; Krafft et al., 2017). When integrating innovative technology into everyday life or using its functions, a critical concern category is the potential of data misuse or external data attacks by third parties (e.g. Lu et al., 2011; Subashini and Kavitha, 2011; Suryateja, 2018). Customers’ intention to provide digitally transferred access permission in using an unattended home delivery service is assumed to trigger the same issue. Based on privacy calculus theory, we see customers’ concerns about data misuse as tremendous costs, mitigating customers’ intention to provide digitally transferred access permission. H2:

Customers’ concerns about data misuse related to the CEP provider’s data management negatively influences customers’ intention to provide digitally transferred access permission.

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Environmental ‘cost reductions’ in last mile delivery are a central issue in academic and political discussions (Bertram and Chi, 2018; Ranieri et al., 2018). Since customers focus increasingly on environmental sustainability (Hamari et al., 2015), we argue that environmental aspects increase customers’ intention to use such service. Examples include using delivery services that remove unnecessary journeys to collect parcels from a depot, reduce the number of information slips left in letterboxes, or offer the CEP provider more efficient route logistics due to improved reliability and predictability in single deliveries. The literature emphasises that unattended home delivery services offer an environmentally friendly alternative to traditional home delivery services (Fernie et al., 2010). H3:

Customers’ perceived environmental sustainability of the delivery process positively influences customers’ intention to provide digitally transferred access permission.

The time between ordering and receiving a parcel is an important variable in customers’ calculations of quantifiable opportunity costs (Mangiaracina et al., 2019). Whereas the customer cannot generally influence or accelerate the ordering and shipping processes, there is potential for the customer to influence the physical delivery. Failed deliveries are a frequent cause of customer dissatisfaction (Lu et al., 2016; Vanelslander et al., 2013). As undelivered parcels are often stored at a central distribution point after daily deliveries, an additional effort is required from customers to pick up their parcels, and customers desire flexible delivery windows (Xu et al., 2008). Home delivery services should emphasise the significant advantages of being more flexible based on customers’ perceptions (Lim et al., 2018). This flexibility can be mirrored in the potential to balance work, life and leisure and be more stable and stress free, given the fact that through the provision of digitally transferred access permission, CEP providers can deliver parcels safely and independent of customers’ schedules (Allen et al., 2014; Chen and Karahanna, 2018). We assume that work–life balance will improve overall if at least aspects can be made more emotionally flexible (Chen and Karahanna, 2014). In terms of customers’ life management (including household management), a transfer of digital access permission can simplify household workloads, allowing time to be used more efficiently by going to the cinema or the park, for example. In this relationship or equation, we argue that the benefits of more flexible use of individuals’ quality of homelife outweighs the potential digital privacy costs, as it is common for customers to exchange personal and private information for

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particular individual and personal benefits (Krafft et al., 2017), including in this context, time. H4:

Customers’ perceived work–life flexibility resulting from the delivery process positively influences customers’ intention to provide digitally transferred access permission.

Even though digital access permission on the last mile can be understood as an innovative approach (Mangiaracina et al., 2019; Tsai and Tiwasing, 2021) and previous studies point out that such innovations are generally accepted and adopted by customers with higher incomes (e.g. Ha and Stoel, 2004; Risselada et al., 2014), we, assume that the higher a customer’s income, the more they try to control their privacy and information. Earlier research argues that those on a lower income are more interested in the exchange of data in contrast to the specific value or compensation received (Graeff and Harmon, 2002). Those on a higher income might feel they have more to lose, which increases costs and lowers the overall potential of transferring digital access permission to receive a parcel. This, however, is in line with the general assumptions of privacy calculus theory. In sum, the literature shows overall that in terms of data transmission and privacy-related issues, the customer’s level of income functions negatively (Zukowski and Brown, 2007). Consequently, we assume that these findings can be transferred to the context of customers’ intention to provide digitally transferred access. H5:

3.5.3

Customers’ income negatively influences customers’ intention to provide digitally transferred access permission.

Methodology

3.5.3.1 Research Design and Measurements We conducted an online survey containing validated scales (Table 3.14). Participants were presented with a scenario where a parcel is about to be delivered by a CEP service provider employee. The parcel’s recipient is not present or at home. Participants were shown an image of a smartphone in front of an apartment about to gain immediate access (Figure 3.11).

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Figure 3.11 Supporting image used in studies 1 and 2

We also provided a text explaining that participants should imagine that a delivery person with an application installed on a smartphone opens the door to the participant’s apartment to leave an ordered package behind the door. This is done without ringing or waiting for the customer, contacting a neighbour or leaving a message explaining where the package can be picked up later. In this context, the apartment door must be equipped with an intelligent locking system (smart lock). We explicitly delimited this form of unattended home delivery service from having a parcel box in front of or behind the building or the capacity to leave the parcel in a separate garage. Afterwards, a corresponding questionnaire, including the measurement items, in accordance with the research focus, had to be answered. The participants’ responses were all aggregated to the mean.

Venkatesh et al. (2003)

Intention to Provide Digitally Transferred Access Permission

Confidence in the Sheinin et al. CEP provider’s IT and (2011) IS Infrastructure

Source

Construct

7-point Likert scale (1 = I totally disagree—7 = I totally agree)

7-point Likert scale (1 = I totally disagree—7 = I totally agree)

Scale

0.963 0.927

… is dependable. … is reliable.

The CEP Provider’s IT Infrastructure 0.946

0.964

0.954

I intend to use an unattended home delivery service via digitally transferred access permission frequently.

0.963

0.973

I will always try to 0.969 integrate unattended home delivery service via digitally transferred access permission into my everyday life.

(continued)

during Covid-19 0.973

before Covid-19

Outer Loading 0.973

I intend to use an unattended home delivery service via digitally transferred access permission in the future.

Item Adaptation and Characteristics

Table 3.14 Constructs, Source, Scale, Item Adaptation and Outer Loading for Essay 5

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Source

Dinev and Hart (2006)

Construct

Concerns about Data Misuse related to the CEP Provider’s Data Management

Table 3.14 (continued)

7-point Likert scale (1 = I totally disagree—7 = I totally agree)

Scale 0.965

before Covid-19

Outer Loading

I am concerned that 0.949 the information I provide to the CEP provider in the course of the digital transferred access permission could be misused.

… is trustworthy.

Item Adaptation and Characteristics

0.953

0.964

(continued)

during Covid-19

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Construct

Table 3.14 (continued)

Source

Scale

0.972

0.964

I am concerned about transferring digital access permission because of what others might do with them.

(continued)

during Covid-19 0.939

before Covid-19

Outer Loading

I am concerned that 0.943 someone may find my personal digital access permission, which I provide to the CEP provider in the course of the digital transferred access permission, on the Internet.

Item Adaptation and Characteristics

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Source

Hamari et al. (2015)

Construct

Perceived Environmental Sustainability of the Delivery Process

Table 3.14 (continued)

7-point Likert scale (1 = I totally disagree—7 = I totally agree)

Scale before Covid-19

Outer Loading

0.926

0.941 0.933

… is helpful in conserving natural resources. … is a sustainable way of consumption. … is ecological.

Unattended home delivery service via digitally transferred access permission…

I am concerned about 0.955 transferring digital access permission because they could be used in ways that I cannot foresee.

Item Adaptation and Characteristics

0.920

0.916

0.940

0.955

(continued)

during Covid-19

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Source

Ellenbecker et al. (2008)

Construct

Perceived Work–Life Flexibility resulting from the Delivery Process

Table 3.14 (continued)

7-point Likert scale (1 = I totally disagree—7 = I totally agree)

Scale

0.927

0.950

0.928

… I can better coordinate my everyday life. … I have more flexibility in my everyday life.

By integrating unattended home delivery service via digitally transferred access permission…

0.911

… is environmentally friendly.

before Covid-19

Outer Loading

… saves energy.

Item Adaptation and Characteristics

0.943

0.953

0.944

0.931

(continued)

during Covid-19

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Source

Income (monthly own creation household net income per month)

Construct

Table 3.14 (continued) Scale

Income per month: 1 = 0–500e; 2 = 501–1000e; 3 = 1001–1500e; 4 = 1501–2000e; 5 = 2001–2500e; 6 = 2501–3000e; 7 = 3001–3500e; 8 = more than 3500e

–

0.923

… I have the 0.944 possibility to make important decisions in my everyday life more independently.

during Covid-19 0.936

before Covid-19

Outer Loading 0.925

… I have sufficient control over the planning of my time.

Item Adaptation and Characteristics

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3.5.3.2 Subjects and Controls Regarding our data collection, we checked whether all participants understood the central element, the form of unattended delivery service, by including two questions on attention in the questionnaire. In total, 343 participants (54.23% female) with an average age of 33.97 years (SD = 13.50) took part in the study. We collected data at two different times. The first survey was conducted in the summer of 2019 (181 participants; 54.14% female; 33.32 years (SD = 12.89)) before the COVID-19 pandemic started. The second study took place in late autumn 2021 (162 participants; 54.32% female; 34.70 years (SD = 14.16)) during the COVID-19 pandemic. In addition, we recorded education level data (secondary school certificate or below = 18.08%; high school degree = 53.64%; university diploma/Bachelor’s or Master’s degree = 28.99%), income (0–500e = 14.58%; 501–1000e = 16.62%; 1001–1500e = 11.95%; 1501–2000e = 9.62%; 2001–2500e = 11.95%; 2501– 3000e = 13.41%; 3001–3500e = 8.75%; more than 3500e = 13.12%) and knowledge of unattended home delivery services via digital access permission (unknown = 7.00%; heard of = 80.76%; well-known = 12.24%). The data show a sufficient distribution of the German population, where the study was conducted. In addition, in both studies, we controlled for customers’ age, gender, education knowledge of the provision of unattended home delivery services via digitally transferred access permission against our dependent variable of customers’ intention to provide unattended home delivery service via digitally transferred access permission. The main results are not altered by this variable, emphasising the robustness of our research model.

3.5.3.3 Method Standardised factor loadings are all above the threshold of 0.7 (Hair et al., 2014) (Table 3.14). Moreover, we measured the models’ internal consistencies. Multicollinearity is neglectable, as variance inflation factors (VIF) are below the recommended threshold of 10 (Hair et al., 2011). Also, high levels of scale consistency can be observed since Cronbach’s Alpha, the average variance extracted as well as composite reliability are all generally satisfactory (α > 0.948; AVE > 0.860 and CR > 0.966) (Table 3.15). By applying Fornell and Larcker’s (1981) criterion, we assessed all reflective scales for discriminant validity. As a result, none of the used constructs shares more variance with any other construct but with its own indicators (Table 3.16–3.17).

0.948

0.966

0.959

0.954

CDM

ES

WLF

0.955

0.962

0.968

0.955

0.965

0.878

0.860

0.908

0.906

0.937

0.881

0.867

0.911

0.918

0.935

during Covid-19

0.966

0.968

0.975

0.967

0.978

before Covid-19

CR

0.967

0.970

0.976

0.971

0.977

during Covid-19

≤ 8.877 ≤ 7.166 ≤ 9.984 ≤ 6.515 ≤ 5.926

≤ 8.400 ≤ 6.968 ≤ 8.109 ≤ 6.141 ≤ 6.087

during Covid-19

before Covid-19

VIF

Note: ItP = Intention to Provide Digitally Transferred Access Permission; TIT = Trust in the CEP Provider’s IT Infrastructure; CDM = Concerns about Data Misuse related to the CEP Provider’s Data Management; ES = Perceived Environmental Sustainability of the Delivery Process; WLF = Perceived Work–Life Flexibility resulting from the Delivery Process; α = Cornbach’s Alpha; CR = Composite Reliability; AVE = Average Variance Extracted; VIF = Variance Inflation Factor

0.967

TIT

before Covid-19

before Covid-19

during Covid-19

AVE

α

ItP

Construct

Table 3.15 Cronbach’s Alpha, Composite Reliability, Average Variance Extracted and Variance Inflation Factor

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2.96 (1.60)

4.71 (1.79)

3.74 (1.60)

3.87 (1.77)

4.31 (2.22)

TIT

CDM

ES

WLF

I

0.159

0.305

0.222

0.171

0.414

0.937

ItP

0.108

0.214

0.227

0.074

0.906

0.643

TIT

0.027

0.030

0.029

0.908

–0.273

–0.413

CDM

0.031

0.309

0.861

–0.171

0.476

0.471

ES

0.094

0.878

0.556

–0.174

0.463

0.552

WLF

1.000

–0.307

–0.176

0.164

–0.329

–0.399

I

Note: SD = Standard Deviation; ItP = Intention to Provide Digitally Transferred Access Permission; TIT = Trust in the CEP Provider’s IT Infrastructure; CDM = Concerns about Data Misuse related to the CEP Provider’s Data Management; ES = Perceived Environmental Sustainability of the Delivery Process; WLF = Perceived Work–Life Flexibility resulting from the Delivery Process; diagonal includes the AVE; values below diagonal include the square correlations; values above diagonal include the normal correlations

2.72 (1.85)

ItP

Mean (SD)

Table 3.16 Results of Correlation Matrix and Discriminant Validity: Before Covid-19

3.5 Essay 5. The Impact of IT/IS, Lifestyle and Income Related Influences … 125

3.00 (1.77)

4.64 (1.77)

3.71 (1.59)

3.97 (1.62)

4.26 (2.52)

TIT

CDM

ES

WLF

I

0.031

0.111

0.183

0.115

0.364

0.935

ItP

0.038

0.111

0.161

0.090

0.918

0.603

TIT

0.001

0.032

0.043

0.911

–0.300

–0.339

CDM

0.032

0.237

0.862

–0.303

0.401

0.428

ES

0.068

0.881

0.483

–0.198

0.334

0.333

WLF

1.000

–0.260

0.487

–0.179

–0.194

–0.176

I

Note: SD = Standard Deviation; ItP = Intention to Provide Digitally Transferred Access Permission; TIT = Trust in the CEP Provider’s IT Infrastructure; CDM = Concerns about Data Misuse; ES = Perceived Environmental Sustainability of the Delivery Process; WLF = Perceived Work–Life Flexibility resulting from the Delivery Process; diagonal includes the AVE; values below diagonal include the square correlations; values above diagonal include the normal correlations

2.54 (1.70)

ItP

Mean (SD)

Table 3.17 Results of Correlation Matrix and Discriminant Validity: During Covid-19

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We used partial least squares (PLS) structural equation modelling to test our hypotheses. By doing so, we were able to analyse all relationships simultaneously, consider certain measurement errors in the included variables (Hair et al., 2014) because it is more suitable for small sample sizes, meaning below 250 (Reinartz et al., 2009). With a view to the applicability of the comparability of customer behaviours at the two different measurement times, we have to take measurement invariance into account. For this, we followed the three-step procedure of Henseler et al. (2016), for which (1) the configuration invariance, (2) the composition invariance and (3) the considered equality of composite means and variances were examined. (1) First, we can confirm equal parameterisation and way of estimation in both studies since the same construct structures are present, i.e. the same number of items in each construct and the same scale levels. Thus, there is configurational invariance. (2) Using the Measurement Invariance of Composite Models method (5,000 permutation runs), we ensured compositional invariance, i.e., all indicators are equally weighted in the studies. This could be shown with the help of SmartPLS 3 (Ringle et al., 2015). The permutation test shows that at a 5% level, none of the c-values differ significantly from any others (Intention to Provide Digitally Transferred Access Permission: p = 0.390; Trust in the CEP provider’s IT Infrastructure: p = 0.057; Concerns about Data Misuse related to the CEP Provider’s Data Management: p = 0.989; Perceived Environmental Sustainability of the Delivery Process: p = 0.886; Perceived Work–Life Flexibility resulting from the Delivery Process: p = 0.989, Income: p = 0.214). It was also shown that all out loadings were above the critical value of 5%. We can therefore establish compositional invariance for all compositions in our studies. We can now compare the path coefficients of customer willingness to provide digitally transferred access permission before and during the COVID-19 pandemic using a multi-group analysis. Finally, in step 3, we assessed the equality of the means and variances of the composites across time points. We found that the mean original difference falls between a 2.5% and 97.5% boundary; however, variance original difference is not fully given, indicating partial invariance. Moreover, self-reported data might generate common method bias. To avoid this issue, we conducted full collinearity testing according to Kock (2015). This approach uses a random dummy variable as a dependent factor arguing that none factor-level VIF has to be higher than 3.3. In our case, all VIFs were below 1.542, leading to the consideration that our model is fundamentally free of common method bias.

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Results

Following Dijkstra and Henseler (2015), our scenario indicated adequate specifications concerning the model’s fit criteria (SRMR ≤ 0.030; NFI ≥ 0.926). In addition, we generated an adjusted R2 of 0.560 and a Q2 (Stone-Geisser criterion) of 0.528 for study 1 and an adjusted R2 of 0.413 and Q2 of 0.396 for study 2. According to Hair et al. (2011), a highly adequate model specification can be indicated for customer behaviour research. The main findings for H1–H5 are illustrated in Table 3.18. Table 3.18 Summary of the results of the SmartPLS analysis Hypotheses and Influences (on Customers’ Intention to Provide Digitally Transferred Access Permission)

Stand. Coefficient (T-Statistics) before COVID-19

during COVID-19

Group Comparison (p-value)

H1

Trust in the CEP Provider’s IT Infrastructure

0.377*** (4.928)

0.459*** (6.445)

0.082 (0.434)

H2

Concerns – 0.229*** (4.275) about Data Misuse related to the CEP Provider’s Data Management

– 0.156* (2.427)

0.073 (0.383)

H3

Perceived 0.093 (1.337) Environmental Sustainability of the Delivery Process

0.177** (2.520)

0.084 (0.394)

H4

Perceived Work–Life Flexibility Resulting from the Delivery Process

0.054 (0.709)

– 0.187 (0.068)

0.241*** (3.489)

(continued)

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Table 3.18 (continued) Hypotheses and Influences (on Customers’ Intention to Provide Digitally Transferred Access Permission)

Stand. Coefficient (T-Statistics) before COVID-19

during COVID-19

Group Comparison (p-value)

H5

– 0.147** (2.765)

– 0.045 (0.699)

0.102 (0.220)

0.560

0.413

adj. R2

Income

Q2

0.528

0.396

SRMR

0.029

0.030

NFI

0.926

0.920

Note: PLS algorithm: maximum iterations = 300; bootstrapping procedure: 343 cases in total (181 cases before COVID-19 pandemic; 162: during COVID-19 pandemic); samples = 5,000; *p < 0.05, **p < 0.01, ***p < 0.001

Both IT and IS influences significantly affect customers’ intention to provide digitally transferred access permission. In detail, we can produce a positive impact of trust in the IT infrastructure and a negative effect on customers’ concerns about data misuse related to the CEP provider’s data management on the intention to digitally provide the respected access permission. Therefore, H1 and H2 can be empirically supported for both studies. Regarding the lifestyle-related influences, we can only find a significant positive relation between customers’ perceived work–life flexibility resulting from the delivery process and customers’ intention to provide digitally transferred access permission for study 1. This effect, however, is not shown in study 2. In reverse, the impact of customers’ perceived environmental sustainability does not show an empirical relation within study 1, but it does in study 2. Consequently, the findings can just partially support the postulated H3 and H4. The COVID-19 pandemic seems to have adjusted customer behaviour in this relation in a certain way. In addition, the assumed negative impact of the financial influence, the effect of the customers’ income, on customers’ intention to provide digitally transferred access permission (H5) can be confirmed for study 1 but not for study 2. Even though, concerning the influence of the perceived work–life flexibility on customers’ intention to provide digitally transferred access permission, studies 1 and 2 show certain variations. We could not find a clear difference between the two studies (p = 0.68).

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Discussion

By focusing on customers’ intention to provide digitally transferred access permissions, our research concentrated on the mental calculus of digitally giving access permissions to customers’ most private areas. As this form of permitting access is not widespread in Germany, it is no surprise that the mean score of intention to provide such access is below the average of the scale mid-point of 4 in both studies (Table 3.16–3.17). This result is generally in line with the findings of Kasper and Abdelrahman (2020) and Liu et al. (2019)—that customers need time to get in touch with innovative technology in order to form an opinion. The fact that we identified a mean value that is clearly lower than the mid-point can be seen in it is not just about the handling or approach towards innovation. Still, it is also connected to the uncertainty of losing something more than time or patience while trying to understand the new technology. The possibility of granting access to one’s private area to an unknown delivery person is assumed to make this technology approach even more sensitive. We integrated three areas of influence (IT and IS, lifestyle and income), concentrating on customers’ intention to provide digitally transferred access permissions by referring to privacy calculus theory to address this issue. The low level of average intention to provide digitally transferred access permissions moreover underlines the relevance of this research. First, we could give a deeper understanding of privacy calculus theory, which was, to the best of our knowledge, has not been integrated into research on this topic before. Both approaches with IT and IS influences, which are assumed to be strongly connected with customers balancing providing (including the acceptance of the issue of potential data-related mismanagement) versus not providing, withstand empirical scrutiny. In line with common literature, we can emphasise that customers’ trust in the corresponding IT and IS seems to be primarily decisive for customers’ intention to get involved in an exchange of data and, for example, the simplification of the last mile delivery process. The influence of customers’ concerns about data misuse moreover implies a clear relation towards customers’ intention to provide digitally transferred access permissions. Customers might realise that access permissions are usually just conditional and thereby only usable in a dyadic interaction, with the customer as the final recipient. In contrast, digital access to personal data could be a long-term threat (Rauschnabel, He, and Ro, 2018). In summary, we showed that trust in the IT and concerns surrounding the IS are critical determinants in customers’ calculus on providing access permission digitally or not, given the potential privacy issues concerning unattended

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home delivery services. These findings generally support the arguments of Dinev and Hart (2006) and Li et al. (2011). Second, regarding the lifestyle-related influences, customers’ perceived work– life flexibility generated only an effect before the COVID-19 pandemic. In contrast, the assumed impact of customers’ perception of environmental sustainability can only be shown during the pandemic. That customers seem to make a connection between the value of managing their private and work life more flexibly and independently by using certain delivery services gives reason to argue for balancing and calculus on, or even re-evaluation of, the benefits of creating more free space against concerns associated with privacy before the pandemic has affected everybody’s everyday life (Allen et al., 2014). These days, customers seem to understand the relevance and intention of such a service, not just concerning facilitating delivery services’ processes and workflows but also due to customers’ personal attitudes and ways of life. However, future studies might investigate if the enhanced freedom is used for ‘life’ or ‘work’. Nevertheless, during the pandemic, customers seem to be re-evaluating their intention to provide digitally transferred credentials due to the constraints brought about by COVID19. Focusing on the impact of work–life flexibility, we can assume that due to the high amount of time customers had to spend at home, they saw less need to make their daily routine more flexible. It could be interesting to see whether the pandemic abating leads to the same customer behaviour as before, how long it takes before pre-pandemic behaviours return, or whether work–life flexibility in the last mile delivery processes after the pandemic is no longer relevant to customers. Third, particularly during the pre-pandemic period, what was surprising was the lack of influence of environmental sustainability (Hamari et al., 2015; Leismann et al., 2013; Suchanek and Szmelter-Jarosz, 2019). However, customers seem to have given more weight to this aspect since the start of the pandemic. Study 2 shows that the inevitable changes in their everyday lives have made customers increasingly appreciative of the importance of environmentally sustainable deliveries. One reason for this may be that the negative effects of multiple deliveries, multiple runs by suppliers or the efforts that can arise with a delivery were only recognised through long phases spent in one’s own home. And the interest in less sustainable deliveries is growing (Kedia et al., 2017). The potential reduction in the need for flexibility due to being at home for a long time could have led to a more intensive examination of the topic of environmentally friendly delivery processes among customers. Fourth, customers’ income level is negatively related to the intention of customers to issue digitally transferred access permission. The literature shows that

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higher-income customers are often increasingly interested in being pioneers or innovators with new products (e.g. Ha and Stoel, 2004; Risselada et al., 2014). However, having more income often goes hand in hand with living in more luxurious apartments or properties. Therefore, the transfer of access permissions to unknown suppliers could be associated with more significant concerns for this group, particularly regarding potential thefts (Hübner et al., 2016). In particular, looking at study 1, the results support the general assumptions made by Zukowski and Brown (2007), underlining those customers with a higher income level weigh up data protection problems and the potential for loss more intensely. However, the time customers have to stay at home (during the pandemic) mitigates this effect, as shown in study 2. Nevertheless, it is still important to see how this trend continues and whether the ‘old’ pattern will return in the post-pandemic period.

3.5.6

Implications, Limitations, and Future Research

Our study shows the potential for adjusting current services to meet customers’ needs and attitudes. Since unattended access permission to private living areas seems to be a more sensitive issue, our study gives CEP providers a wide range of starting points to optimise customers’ level of trust in the relevant IT infrastructure and reduce customers’ concerns about data misuse, enhancing their overall perception of the delivery service and meeting customers’ needs. As both determinants generally influence customers’ intention to provide digitally transferred access permissions, CEP providers are encouraged to improve customers’ overall understanding of the entire service process (Söllner et al., 2012). With a focus on long-term corporate success, including optimisation of supply routes and general strategic business decisions, the collection and actioning of data is becoming increasingly relevant (Mangiaracina et al., 2019). These data are linked to the digital transmission of the access permission. Overall, it can be said that the integration of data from a company or value chain perspective is associated with sustainable company advantages (Wakefield, 2013). To ensure customers continue to transfer such data and information, they should be made aware of the added value of these transmissions. Studies 1 and 2 have shown where the added value lies for customers. Emphasising work–life balance seems to be particularly important in times when there is no pandemic. In contrast, the issue of the ecological sustainability of delivery processes is important during the pandemic. Customers seem to be changing or adapting their reasons for having parcels sent to their homes with the help of digital access rights in the wake of the

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COVID-19 pandemic. Even if no extensive change in behaviour is discernible, it also suggests that a degree of stability is evident regarding the general perception of this form of delivery or the associated transmission of access rights, particularly concerning the IT and IS influences. There are shifts in lifestyle and financial influences. These adjustments are also exciting for the CEP providers. The pandemic seems to have shifted the more egoistic influences of the individual through the more flexible organisation of everyday life to more altruistic influences such as the ecological sustainability of the delivery process increasing the willingness to transfer access data. Also, income, analogous to flexibility, no longer seems to have a separate effect, which can be advantageous from an entrepreneurial point of view since it is no longer necessary to differentiate between different income levels when addressing them. The pandemic and its associated restrictions and adjustments for customers certainly have influenced customers’ willingness to use digital data transmission. The more intensive engagement with digital media during the pandemic could also be an explanatory approach to explain the identified effects in more depth. Customers’ engagement with digital content and their digital interactions with retailers also increased significantly during the pandemic due to the severely restricted shopping opportunities (e.g. McKinsey, 2020; Deloitte, 2020; PwC, 2020), which may also be an indication of increased transmission of personal information as part of many services. As a result, the reference to, and concerns about, personal data and their security may also have adapted. At this point, it will be interesting to observe whether concerns about data misuse will continue to lose importance in the months after the pandemic. Given the impact of customer perception of work–life flexibility, CEP delivery could concentrate on communicating the concrete advantages for customers more intensively, with a view to a freer organisation of leisure time through digital access permissions. In general, customers appreciate managing their time more flexibly, without feeling the pressure of needing to be at home within a specific time frame to receive a package. This flexibility could play a vital communications role for companies. Also, considering environmental sustainability in the context of this research and the increasing attention given to this topic in the service (Lee et al., 2020; Hamari et al., 2015), we advocate emphasising the ecological potential of this delivery option. The question of an economically and environmentally efficient way to achieve home deliveries has been the subject of intense debate among urban logistics planners for some time (Faccio and Gamberi, 2015). The data-driven optimisation of inner-city transport concepts and plans plays an important role in this context (Perboli et al., 2018; MuñozVillamizar, 2019). Thus, ecologically sustainable delivery concepts can also be combined with the generation of customer data in corporate communication.

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Consequently, it is said that to protect the environment more efficiently and develop sustainable transport systems (Ranieri et al., 2018), an even more stable database is needed (Mangiaracina et al., 2019). Based on the results of this research, showing more flexible life models and better nature conservation through the use of digital access permissions when generating these data can be an important step. Moreover, it is necessary to look deeper at customers’ privacy concerns and their influence on customers’ intention to provide digitally transferred access permissions. On a practical level, it might be relevant to ensure that customers with a higher level of privacy concerns understand that using this form of service is safe in terms of data transfer. These customers need to be accommodated in the right manner by emphasising the advantages without giving them a feeling of losing control of their data. Based on the findings, our study also highlighted the relevance of one other influence on a deeper understanding of customers’ privacy calculations (Dinev and Hart, 2006). The results show that customers’ trust in the CEP provider’s IT infrastructure plays an increasingly significant role in the context of providing access permissions. Nonetheless, our research comes with limitations. A significant limitation of this study could be customers’ generally flattening flexibility requirements in the pandemic. This could explain the effect of work–life flexibility and the influence of income. These limitations could have manifested themselves quite intensively in customers’ minds, which could ultimately also explain the study’s findings. In addition, we only collected data for the German market, where smart lock systems are not yet a standard in home delivery services. Future studies should also recruit participants from more experienced countries to check the general validity of our results. Future studies should also acquire participants from more experienced countries to verify the general validity of our findings. Moreover, prior research shows several important differences in personality concerning sociodemographic variables such as age, culture, and education, and differences in general customer behaviours between countries (Miltgen and Peyrat-Guillard, 2014). A cross-cultural study could provide further insights into intentions to provide digitally transferred access permissions for unattended home delivery services.

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3.6

Essay 6. MIRROR, MIRROR…on the Shelf: The Impact of Perceived Age Similarity and Gender Congruence between the Customer and the Voice of a Smart Voice Assistant

3.6.1

Introduction

The areas of distribution and application of Smart Voice Assistance (SVA) are diverse and range from assistance for drivers (Strayer et al., 2017), support for the elderly (Valera Román et al., 2021) or people with special needs (Ramadan et al., 2021), to service on health issues (Liu et al., 2020). Studies estimate a steady increase in the number of SVAs in households in the coming years (eMarketer, 2020). The complexity and accuracy of technology in this area have rapidly increased over the last decade, including the ability to respond to followup questions (Hoy, 2018). The design of these systems in terms of appearing more ‘human-like’ in order to make the customer feel more socially welcome is improving as well (Schweitzer et al., 2019). In general, anthropomorphism can be understood as ‘a process of inductive inference whereby people attribute to nonhumans distinctively human characteristics’ (Waytz et al., 2014, p. 113). Anthropomorphistic traits, such as name and gender, are perceived as more trustworthy (Waytz et al., 2014) and lead to a more social perception of the entire service (Araujo, 2018; Han, 2021). The importance of customers’ perception of interpersonal approaching of digital services can be shown in several studies (Pitardi and Marriott, 2021; Putoni et al., 2021). The more socially-accepted the SVA, the higher the possibility of an adequate exchange between the customer and the SVA (Poushneh, 2021). In fact, global companies are interested in improving voices’ interactivity, not only to enable longer interactions, but to enhance customers’ overall impression of the service (AMAZON, n.d.). In physical retailing, service has the option to match the customer with frontline employees, depending on customers’ behaviour or even demographics when entering the physical store. Another possibility is mirroring the customer’s characteristics or behaviour (e.g., facial expressions, gestures, etc.) to give them a sense of understanding and thereby strengthen the bond between the parties (Chartrand and Bargh, 1999; Kulesza et al., 2014). This ‘chameleon effect’ triggers an emotional reaction or influences the mood of the other person (Ramathan and McGill, 2007). In contrast, SVA-based services lack the potential of this form of affective response. However, research on SVA shows that certain differences in the way the digital counterpart uses language, or similarities in the use of a language, can result in altered perceptions of the service by customers (Bell and Puzakova,

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2017). Bell and Puzakova (2017) also show that positive opinions of others lead to an improvement in one’s own opinion. This applies not only to products, but also to services. Negative judgments from others, on the other hand, reduce your own experience rating. The question arises as to how such an SVA, or the AI responsible for the corresponding voice, has to be designed in order to ensure optimal service. One of the strongly discussed fields in literature in order to improve service exchange and interaction, is the role of the age and gender of the counterpart in the context of service quality perception from the customers’ side (Eagly et al., 2020; Luoh and Tsaur, 2007). Just by awaking the SVA, certain information about the customer is available, such as gender and age, which could be used to adjust the voice of the respective digital counterpart right from the beginning of the interaction. In fact, besides the information about customers’ preferences, which can be used to anticipate the desires and needs of the customer (Stucke, 2017; Schroeder and Schroeder, 2019), the SVA should evaluate what kind of voice leads to an optimal level of service outcome, particularly when using such SVA for the first time. This applies not just in terms of purchasing or willingness to pay, but with regard to customers’ willingness to interact with the SVA and willingness to disclose information. We see two key issues in integrating SVA not only in home-based services but in broader domains of life: what capabilities should an SVA include, and how do they affect customers’ behavioural responses (Baskerville and Pries-Heje, 2010). We introduce communication accommodation theory (Giles, 1973) in order to analyse customers’ individual reactions to SVAs’ voice-related accommodation to customers’ voices. We see an accommodation towards the customer, however, the voice of the SVA is not dynamically adjustable within the interaction. It is argued that a fundamental accommodation in terms of convergence regarding customers’ age and gender will lead to positive customer reactions (e.g., interaction behaviour). In this way, we offer approaches for adapting SVAs to future interactions. We assume that accommodation through voice convergence of SVAs towards the user, especially with regard to age and gender, creates a basis for efficient interaction. This should apply provided there is no distortion due to visual information or other vocal information from a variety of speaking rates, melodies, etc. on the part of the SVAs (or similar). Furthermore, we draw on social presence theory (Short et, al., 1976) as it argues that engaging SVA in two-way conversations improves social presence (Grewal et al., 2020). The success of an interpersonal interaction between two parties or the willingness of customers to interact with a counterpart in a service context in the first place is fundamentally based on the motivation of both parties (Turner, 1988). This

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motivation, and thus also the perception of the social presence of the voice, is assumed to be higher if the gender and/or age corresponds to this or suits the user. This means that an accommodation on the part of the voice with regard to these factors is assessed as more positive, which can ultimately also have positive effects on further interaction. However, interpersonal/social interaction, such as an exchange or small talk about topics unrelated to service, like the weather, is often an important entry into an interaction (Blickmore and Cassell, 1999). Building on the assumption that small talk might also play role in interaction with a certain AI (Babel et al., 2021), our research distinguishes between the customers’ willingness to interact with the SVA on a service-related and an interpersonal-related level. Previous research has focused primarily on the effects of SVAs in terms of customers’ behaviour, specifically on customers’ purchase behaviour (Moriuchi, 2019; Schweitzer et al., 2019; Tassiello et al., 2021). In detail, it analysed the social exchange (Fernandes and Oliveira, 2021; McLean and Osei-Frimpong, 2019; Pitardi and Marriott, 2020), relational reaction (Fernandes and Oliveira, 2021; McLean and Osei-Frimpong, 2019; Schweitzer et al., 2019), and functional challenges (Fernandes and Oliveira, 2021; Moriuchi, 2019; Pitardi and Marriott, 2020), while interacting with such SVA. In a digital context, Nass and Lee (2001) pointed out that similarities in extroversion or introversion of the customer and a synthetic voice were evaluated more positively. Regarding SVA, Valenzuela et al. (2019) focused on customers’ accommodation or adaptation of SVAs’ voice. However, there is a research gap that focuses on customers’ behaviour and response when the SVA’s voice shows congruency with the customer’s age and gender. In detail, literature is lacking on the question of how to design such an artifact. By referring to the ‘chameleon effect’ of physical services (Chartrand and Bargh, 1999; Chartrand and Lakin, 2013), we assume that a ‘mirroring’ of the customer might also be an effective way to improve the entire SVA-based service process. Studies in traditional service environments showed no impact of age similarity and gender congruence on service-related factors (Dwyer et al., 1998). Moreover, an integrated perspective on SVA, including as well the measurement side, is missing. In summary, this new research addresses the following research questions: RQ 1.

RQ 2.

How should the voice of an SVA be designed regarding the level of anthropomorphism and customer-perceived convergence with the voice in terms of age and gender? What impact has customer-perceived convergence with the voice in terms of age and gender with respect to the customer’s willingness to interact with the voice and to disclose personal information?

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3.6.2

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Literature Background and Theoretical Framework

3.6.2.1 Anthropomorphism and Social Presence in Context of SVA Anthropomorphism is a term used to describe a tendency to ascribe human characteristics to something non-human (Epley et. al., 2007; Aggarwal and McGill, 2007; Waytz et. al., 2014). The manifestations of anthropomorphism can be expressed, for example, in terms of external appearance characteristics, motivations or emotions (Waytz et. al., 2014). Anthropomorphism can also make customers feel welcome (Schweitzer et al., 2019). Aggarwal and McGill (2007) further explain that perceiving characteristics in a product that are similar to those of the customer increases the perceived humanisation of it. The perceived similarity between a human and its behaviour with a non-human object can also promote or increase anthropomorphism (Morewedge et al., 2007). In the context of digital services, research also underlined the relevance of anthropomorphic approaches to the customer. Anthropomorphised features in the context of these services seem to lead to an increase in the customer’s more social perception and acceptance (Araujo, 2018; Han, 2021). As a basic component of SVA usage is the communication or interaction with these artifacts, we integrate the approach of social presence theory (Short et. al., 1976). The theory states that the more indicators a medium provides for people to communicate with it, the more customers can feel the human warmth, emotion and sociality of the medium (Short et. al., 1976). According to Gefen and Straub (2004), the degree of social presence required for a particular task is related to the social presence of the medium, e.g., it is also about the extent to which a medium enables a communicator to experience communication partners as psychically present (Short et. al., 1976). This in turn has a direct effect on the willingness of customers to interact actively with this medium. For example, voice chat functions have been shown to have the ability to trigger a sense of others’ presence (Zhu et al., 2010). SVA are also able to trigger a social presence due to their inherent nature of two-way communication (Grewal et al., 2019). Furthermore, Gefen and Straub (2004) argue based on Blau (1964) that social presence among customers increases when the counterpart exhibits behaviour or other indicators that are consistent with one’s expectations. Consequently, it is assumed that in the course of an SVA-based service, triggering a feeling of social presence, congruence of the voice with the individual constitutes an added value, which is ultimately also reflected in the willingness to interact with the SVA, or in other words, the voice.

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In fact, social interaction and behaviour is a two-way effect: the dyadic interplay of action and the reaction of the two parties, which is regarded as an essential determinant within services (Weber, 1978). Based on the interactional process of two parties, we additionally refer to Turner’s (1988) theoretical approach on social interaction, who differentiated three properties of interaction: motivational, interactional and structural. More precisely, individuals need to be generally energized and mobilized to interact (motivational), should be able to interpret and understand one’s own and other’s behavioural signals (gestures, etc.) (interactional) and organize interactions across time and space (structural). In conclusion, at least motivational and interactional properties are necessary in order to successfully complete such a social interaction or behaviour.

3.6.2.2 Communication Accommodation Theory in Context of SVA Communication accommodation theory (Giles, 1973) is an approach of interpersonal and intergroup communication that seeks to explain how interlocutors adapt their communication to accommodate others in order to manage social distance and understanding (Soliz and Giles, 2014). According to this theory, the addressee modulates social distance through converging or diverging addressee language patterns (Shepard et al., 2001). Thus, language is a tool used by addressees to achieve the desired social distance between themselves and others. To achieve this, communicators can use one of four strategies when speaking: convergence, divergence, maintenance and complementarity. Convergence, which is of particular interest here due to similarities with the verbal aspect of the mimicry phenomenon, occurs when addressees alter or adjust their linguistic patterns to that of their interaction partners (Mantell and Pfordresher, 2013). Basically, communication accommodation theory assumes that cognitive and/or affective goals are achieved in communication by addressees adapting their communication to converge with the other interactant’s communicative behaviour (Gallois et al., 2005; Gasiorek et al., 2015). These goals do not (yet) play an overriding role in SVA-based services due to the process-based nature of the underlying AI. SVA is also about increasing understanding and reducing social distance. Therefore, it may prove to have a positive effect if the SVA can be programmed to attempt to establish social connection by making certain parameters within the interaction more similar to those of the other interactant. In general, communication occurs in a socio-historical context, and perceptions of communicative behaviour are influenced by intergroup and interpersonal history as well as sociocultural norms and values (Giles et al., 2007). These perceptions of communicative behaviour as accommodative are subjective (Thakerar

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et al., 1982). We perceive others as accommodative based on the extent to which their convergence meets our subjective expectations or needs in a given context (Gallois et al., 2005). Valenzuela et al. (2019) examined customers’ accommodation towards a voice assistant, realizing that verbal accommodation from the customers’ side is positively influenced by the respective level of experience with SVAs. Giles et al. (1973) found that the positive response to a convergent pattern was due to sociocultural adjustment factors. Analogously, we assume that not only sociocultural adjustments but also sociodemographic accommodation in the course of SVA leads to positive effects. To achieve particular social goals or facilitate their discourse, in terms of communication accommodation theory, addressees or voices adapt their linguistic patterns (e.g., their speaking rate and style) to that of their conversational partner. As similar goals are relevant when it comes to services in general (Fiske et. al., 2007; Huang and Rust, 2018; van Doorn et al., 2017), we argue that communication accommodation theory plays an important role in further explaining services’ accommodation of the customer/customers, against the background of services ‘adapting’ to the particular customer/customers in terms of age and gender. Convergences in age and gender of interaction partners in physical interactions shows however varying results. Dwyer et al. (1998) investigated the effect of age similarities in context of perceived sales performance. Findings, however, could not prove any significance. Yet research among social interaction and behaviour pointed out a positive correlation of age similarity of employees and their engagement within a specific work task (Avery et al., 2007) and a negative correlation with regard to conflicts among employees (Jehn et al., 1997; Pelled et al., 2001). In addition, Kwok and Xie (2018) emphasized a positive effect of seller-buyer age similarity when it comes to the purchasing/selling of peer-to-peer room-sharing offers. Fischer (1997) stressed the fact that the evaluation of the quality of a certain service depends on customers’ perception of the gender of the person performing the service. We acknowledge the fact that it is a stereotypical approach to use services’ gender as a first informational basis in order to lower uncertainties (Nass et al., 1997). Given a physical-service context, same-gender interaction provokes a social comparison (Maner et al., 2009) and also promotes a certain self-endangerment (Agthe et al., 2011), which results in a reduction in service outcome. These effects could be traced back to an overall assessment of the other person, which also includes immediate visual cues such as attractiveness or appearance. If you take these visual criteria out of the overall calculation, concentrating only on the voice or the character behind the voice, we would assume different results than those from traditional face-to-face service. By approaching

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or accommodating the customer with the voice of the SVA in terms of age and gender, according to the communication accommodation theory, a positive feeling could be triggered in the customer. Although studies within brick-and-mortar retail have shown that age and gender similarity may not have a positive effect on service perception (Dwyer et al., 1998), we assume that if all visual cues are removed and customers focus on the pure voice, age similarity and gender congruency of the SVA-based services will have a positive effect on the customers’ perception of the service. The customer’s concentration is more clearly aligned here and a perceived accommodation in gender and age of the voice of the other person is not distorted by the customer because the customer is not involved in social comparison processes with the advisor (Maner et al., 2009) but rather decides what this is, understanding that it is more like a good friend dealing with similar problems and questions.

3.6.3

Conceptual Framework

We use communication accommodation theory to evaluate the potential of how the SVA should be designed, and social presence theory to deepen the understanding of customers’ behavioural reactions. We analyse three distinct issues, including the level of anthropomorphism and the potential convergence with the customer specifically in terms of age and gender. As our study concentrates primarily on customers’ willingness to interact and then disclose information, we integrate social presence theory in order to understand customers’ reactions. It should be the services’ aim to motivate the customer to interact with her/him in order to fundamentally understand the customer’s desires and thereby receive necessary information about the customer. Nonetheless, the collection and usage of customers’ personal information is a tremendous challenge for retailers (Piotrowicz and Cuthbertson, 2014). Without this information, customized or personalized services or products are not feasible (Bleier and Eisenbeiss, 2015; Krafft et al., 2017). Customers’ ‘traditional’ online purchase process is almost inevitably related to a (potentially unconscious) disclosure of private information (e.g., name, address, credit card number). Schroeder and Schroeder (2019) show that customers are more willing to disclose personal information in the case of an SVA-based service in contrast to the simple typing-based online service. The resulting research model is depicted in Figure 3.12.

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high low

Willingness to Interact service-related vs. interpersonal-related

Level of Anthropomorphism

low middle

Perceived Age Similarity

high

given

Gender Congruence

Service/Social Interaction Willingness to Disclose overall vs. accuracy

not given

Figure 3.12 Research Model for Essay 6

3.6.4

Hypotheses Development

3.6.4.1 The Impact on Customers’ Willingness to Interact Digital service is valued higher when the counterpart is perceived familiarly (Gefen, 2000). Solomon et al. (1985) point out that when customers are in familiar situations, their interaction behaviour is often automatic with little conscious attention. A higher level of anthropomorphism or human likeness is generally able to generate such familiarity (as long as the object shows a certain level of ‘natural/healthy liveliness’: uncanny valley (Mori, 1970)). Customers also assess a higher level of artificialness in service as identity-threating (Mende et al., 2019). In consequence, we assume that a lack of social perception of the SVA (Short et. al., 1976), which is essential for customers’ perception of anthropomorphic behaviour, decreases customers’ intention to interact with the voice. A similar effect is assumed with regard to gender and age congruence. More concrete, age similarity can have a positive effect on willingness to engage with a task (Avery et. al., 2007). The willingness to interact with people of not only the same age, but also the same gender, can be explained by the fact that individuals with a higher perceived similarity (e.g., in terms of age and gender) radiate a greater attraction to them and thus a more intensive relationship between them is possible (Berndt, 1982; Kunz and Seshadri, 2015). As a result, using an SVA for the first time, we hypothesize that, based on the theory of communication accommodation, a higher degree of age similarity and given gender congruence, means a higher degree of accommodation by the SVA’s voice, which ultimately increases the customer’s willingness to interact with the SVA.

3.6 Essay 6. MIRROR, MIRROR…on the Shelf: The Impact … H1a: H1b:

H1c:

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A high (vs. low) level of anthropomorphism influences customers’ willingness to interact positively (negatively). A higher (vs. lower) perceived age similarity between the customer and the voice of the SVA influences customers’ willingness to interact positively (negatively). A given (vs. not given) gender congruence between the customer and the voice of the SVA influences customers’ willingness to interact positively (negatively).

3.6.4.2 The Impact on Customers’ Willingness to Disclose Disclosure-related issues play an ongoing role in the context of SVA (McLean and Osei-Frimpong, 2019; Pitardi and Marriott, 2020; Sweeney and Davis, 2020). Schroeder and Schroeder (2019) show that SVA-based services can have positive effects on customer disclosure behaviour, especially in contrast to pure chatbot-based services. It can be demonstrated that the way an SVA interacts with the customer can lead to an increase in customers’ willingness to disclose data (Ischen et al., 2020; Rhim et al., 2022). Since social presence is crucial for the customer’s sense of security (Levav and Argo, 2010), an increase of the customer’s perception of the voice in this aspect can have a positive effect on the customer’s data-disclosure behaviour. Moreover, according to the literature, it is easier for people to build a relationship with someone who has something in common (Kunz and Seshadri, 2015). Even if age and gender are often the least they have in common, this basically helps the customer to meet them communicatively, which is the simplest point of reference in the SVA context when it comes to building a (short-term) relationship. Even though age and gender might not be central for a long-term service relationship, within the first contact with an SVA, perceiving a common factor or an accommodation in age and gender from the SVA can have a positive effect on customers’ first interaction with such a service. This positive perception might lead the customer to disclose more data if the SVA shows a different age or gender: H2a: H2b:

H2c:

A high (vs. low) level of anthropomorphism influences customers’ willingness to disclose positively (negatively). A higher (vs. lower) perceived age similarity between the customer and the voice of the SVA influences customers’ willingness to disclose positively (negatively). A given (vs. not given) gender congruence between the customer and the voice of the SVA influences customers’ willingness to disclose positively (negatively).

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3.6.5

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Method and Procedure

We tested our hypotheses in a two (synthetic vs. human voice) x two (younger vs. older voice) x two (female vs. male voice) subject experimental design. In order to manipulate the different influences, we used the context of a voice commerce/shopping-related service in our scenario, as the knowledge of service in a shopping context should be a given with most of the respondents. In detail, subjects were supposed to imagine interacting with an SVA in the context of a specific retailing interest. In this case we assume a certain habituation effect among the subjects when it comes to the potential collection and use of customer data. In addition, subjects were randomly assigned to an audio-recording, including the following sentence: ‘In order to provide the best possible service with regard to your intended purchase of a loudspeaker-box, it is necessary that you provide us with some additional information’. By testing the voice within a pre-test (N = 98), we ensured that the integrated stimuli were generally equal with respect to file quality and vocalization, and in terms of phonemes or paralinguistic parameters (Scherer et al., 1973) such as: stable volume of the recording, no background noise, a uniform speaking tempo (all recordings were at 13 or 14 seconds), as well as no accents, clearness and cleanness of articulation, no significant pauses (a stable speaking rhythm), and no significant difference with regard to confidence or doubtfulness within the voice. As the female voice and younger voices are higher pitched than that of an adult male, it was ensured that the respective pairings with regard to gender and age hold with regard to these facts and that within each group (young female, old female, young male, old male) the frequency of the voices maximumly variated with 11 hertz on average (Table 3.19). Table 3.19 Overview of the Pitch of the Stimuli used experimental conditions

average in hertz

average minimum in hertz

average maximum in hertz

given anthropomorphism/young/female (N = 59)

220

194

249

not given anthropomorphism/young/female (N = 56)

213

181

247

(continued)

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Table 3.19 (continued) experimental conditions

average in hertz

average minimum in hertz

average maximum in hertz

given anthropomorphism/old/female (N = 54)

196

167

227

not given anthropomorphism/old/female (N = 57)

199

166

233

given anthropomorphism/young/male 133 (N = 50)

116

153

not given 124 anthropomorphism/young/male (N = 56)

107

152

given anthropomorphism/old/male (N = 49)

118

106

128

not given anthropomorphism/old/male (N = 58)

107

98

130

Respondents were randomly assigned to one of the eight experimental conditions. Afterwards they were asked to answer a questionnaire. The included constructs are presented in Table 3.20. Table 3.20 Constructs, Sources, Scale (7-point-likert-scale: 1 = I totally disagree—7 = I totally agree), Item Adaptation and Cronbach’s Alpha for Essay 6 scale

α

construct

source

ServiceRelated Willingness to Interact

Gómez et al. 7-point-likert- I think it would be easy for me to (2009) scale interact with the voice on a service-oriented level.

item adaptation

0.918

I would like to interact with the voice on a service-oriented level.

Interpersonal- Gómez et al. 7-point-likert- I think it would be easy for me to Related (2009) scale interact with the voice on an Willingness interpersonal level. to Interact I would like to interact with the voice on an interpersonal level.

0.921

(continued)

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Table 3.20 (continued) construct

source

scale

item adaptation

α

Overall Willingness to Disclose

Premazzi et al. (2010) and Milne et al. (2012)

7-point-likertscale (1 = unwilling; 7 = highly willing)

email address

0.831

date of birth telephone number occupation position in the company price of last product purchased leisure activities favourite colour last product purchased

Accuracy of Willingness to Disclose

Alashoor 7-point-likert- Please specify the extent to which 0.854 et al. (2017) scale you would falsify some of your personal information towards the VA, if it is asked for by social networking website within the next three years. Please specify the extent to which you would falsify some of your personal information towards the VA, if it would be used for big data analysis within the next three years. Please specify the extent to which you would refuse to give information towards the VA, because you think it is too personal within the next three years. Please specify the extent to which you would refuse to give information towards the VA, if it would be used for big data analysis because you think it is too personal within the next three years.

We checked if all subjects understood and perceived the central factors of the manipulation. Following Kim and McGill (2011) we adapted customers’ perceived level of anthropomorphism of the voice (three items: ‘The voice sounds like a person’; ‘The voice sounds almost as if it has free will’; ‘The voice sounds almost as if it has intentions’; α = 0.769). The manipulation was perceived correctly by the participants (level of anthropomorphism: Mhigh = 5.08 (1.30),

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Mlow = 3.04 (1.21), F (1,437) = 293.59; p < 0.001). To obtain construct values, indicator values per construct were mean aggregated. According to respondents’ answers, we used respondents’ assumption of voices’ age and calculated the difference to respondents’ age. Then, we derived three groups, taking the average differences of age (M = 11.36) and increasing it by one standard-deviation (SD = 9.34) for the group of low age similarity, and decreasing it by one standard-deviation for high age similarity (Hayes and Preacher, 2013). The third group in the area plus/minus one standard-deviation can be understood as a group of average age similarity. Moreover, we asked the respondents to indicate voices’ gender (specifically the gender of the ‘person’ belonging the voice). Subjects who were not able to name the correct manipulation, were eliminated from the data set. With respect to gender congruence, once more we used customers’ gender, set it in relation to the gender of the voice and generated an index for given gender congruence and not-given gender congruence. To avoid a potential bias from the effects, all scales were randomized. We assessed discriminant validity for all variables using Fornell and Larcker’s (1981) criterion (Table 3.21). Table 3.21 Results of Correlation Matrix and Discriminant Validity for Essay 6 Mean (SD)

SRWtI

IRWtI

AoWtD

SRWtI

3.89 (1.72)

IRWtI

2.65 (1.67)

0.925

0.665

0.548

0.442

0.927

0.596

AoWtD

2.38 (1.20)

0.300

0.355

0.701

Note: SD = Standard Deviation; SRWtI: Service-Related Willingness to Interact, IRWtI: Interpersonal-Related Willingness to Interact, AoWtD: Accuracy of Willingness to Disclose; diagonal includes the AVEs; values below diagonal include the square correlations; values above diagonal include the normal correlations

The experiment was conducted online.Our sample included 439 respondents (62.87% female) with an average age of 29.00 (SD = 10.18) years. We controlled for general personal privacy concerns (Dinev and Hart, 2005), general technology affinity, experience with SVA, product involvement as well as educational background of our respondents between all experimental scenarios (level of perceived anthropomorphism, perceived age similarity, gender congruence). We did not find any systematic distortion between our treatments.

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Results

Regarding the influence of the experimental factors to interact with the service of the SVA on a service-related-basis, ANOVA testing revealed a significant influence of the level of perceived anthropomorphism, perceived age similarity as well as gender congruence (Table 3.22). Findings confirm the expected positive impact of a higher level of perceived anthropomorphism in the voice of the SVA on customers’ willingness to interact with the voice in both conditions. Customers’ interest in having small talk with the SVA is clearly lower than the willingness to interact on a service-orientated level. Regarding the perceived age similarity, both scenarios point out a significantly lower interest in interacting with the voice of the SVA the lower the perceived age similarity, whether service-related or interpersonal-related. Besides the difference in the conditions of average age similarity and low age similarity (p > 0.05), Tukey post hoc testing shows a significant difference between high age similarity and average age similarity (p < 0.05), as well as with low age similarity (p < 0.05), in terms of customers’ service-related willingness to interact. Regarding customers’ interpersonal-related willingness to interact, all conditions indicate a significant difference (p < 0.05) within the post hoc testing. It is particularly striking that in both cases a decrease can be seen between the high age similarity and the average age similarity, while the value remains almost the same from the middle to the low state. Interestingly, female (in contrast to male) customers seem to react more negatively on lower age similarity in the case of servicerelated interaction (female: F(1,273) = 4.06; male: F(1,160) = 1.12) as well as interpersonal-related interaction (female: F(1,273) = 20.68; male: F(1,160) = 3.00). Concentrating on the gender congruence, the difference between the groups of a given gender congruence and no gender congruence are only significant in the case of service-related, however not in the case of interpersonal-related, willingness to interact. In sum, the findings lead to a support of H1a, and partial support for H1b and H1c. In focusing on customers’ willingness to disclose personal information in Table 3.23, first impression shows that particularly in terms of the level of anthropomorphism, the effects are not as clear as before with regard to a more human-like voice and a synthetic voice. Findings on customers’ overall willingness to disclose personal information show a positive impact with regard to a higher level of perceived anthropomorphism, however not in terms of customers’ accuracy in providing information.

interpersonal-related

servicerelated

14.469*** (0.033)

F-Value (η2 )

2.20 (1.52)

3.11 (1.71)

M (SD)

35.821*** (0.077)

F-Value (η2 )

3.78 (1.27)

average

2.53 (1.64)

16.599*** (0.072)

3.49 (1.84)

5.117*** (0.023)

4.36 (1.57)

2.02 (1.17)

3.69 (1.79)

low

high

3.35 (1.75)

low

high 4.46 (1.47)

M (SD)

3.72 (1.75)

not given

0.047 (0.000)

2.66 (1.71)

2.61 (1.63)

4.751* (0.011)

4.01 (1.68)

given

Gender-Congruence

Note: Between-subjects design. All values are presented in M: mean (SD: standard deviation); Sig.: *p < 0.05, **p < 0.01, ***p < 0.001

Willingness to Interact

Perceived Age-Similarity

Level of Perceived Anthropomorphism

Table 3.22 Results of Hypotheses Testing ANOVA (DV = Willingness to Interact)

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average

high

low

high

low

given

not given

Gender-Congruence

5.386* (0.012)

10.161*** (0.045)

4.312* (0.010)

Note: Between-subjects design. All values are presented in M: mean (SD: standard deviation); Sig.: *p < 0.05, **p < 0.01, ***p < 0.001

F-Value (η2 ) 1.607 (0.004)

2.38 (1.21) 2.38 (1.20) 2.91 (1.36) 2.37 (1.10) 2.27 (1.16) 2.51 (1.30) 2.19 (1.03)

10.805*** (0.048)

3.11 (1.21) 2.80 (1.26) 3.54 (1.34) 2.77 (1.15) 2.83 (1.17) 3.10 (1.32) 2.74 (1.09)

F-Value (η2 ) 4.691* (0.031)

M (SD)

accuracy M (SD)

Willingness to overall Disclose

Perceived Age-Similarity

Level of Perceived Anthropomorphism

Table 3.23 Results of Hypotheses Testing ANOVA (DV = Willingness to Disclosure)

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Therefore, H2a can only be supported with regard to customers’ overall willingness to disclose. The general disclosure, as well as accuracy of disclosed personal information, decreases significantly the lower the perceived age similarity between the customer and the voice-based service of the SVA. For both dependent variables, Tukey post hoc testing shows a significant difference between high age similarity and average age similarity (p < 0.001), as well as with low age similarity (p < 0.001), however not between average age similarity and low age similarity (p > 0.05). Overall, H2b can consequently be partially confirmed. Almost analogous to the willingness to interact, there is a sharp decline in customers’ willingness to disclose, both in terms of overall disclosure and accuracy of disclosure, when the age similarity is no longer high. This means that even if the difference between the perceived age of the voice and their own age is less, the customers provide significantly less information and it is also significantly less accurate. Focusing on the gender congruence, we see a significant effect with regard to the general disclosure and the accuracy of disclosed personal information. Thus, H2c can be supported on a general level. It is worth noting that particularly in the case of data disclosure, male customers are more willing to disclose to the same gender (F(1,161) = 13.96) than female customers (F(1,274) = 0.39).

3.6.7

General Discussion and Future Research

Regarding research question one, our results state that Dwyer et al. (1998) does not necessarily hold for the digital service context. Our research is disregarding visual cues as clothes, attractiveness or gestures and mimics (or given further biases resulting from the product like haptics, olfactory etc.). By integrating eight distinct scenarios, we have demonstrated a positive reaction when customers perceive similarities with the voice of the SVA, particularly in context of age and gender. The feeling of being accommodated by the digital service with regard to age and gender is perceived positively, not just in terms of customers’ willingness to interact with the SVA, but also with regard to customers’ willingness to disclose personal information. The increase in customers’ disclosure behaviour in the case of a more anthropomorphic service regarding SVA goes against the results of Ha et al. (2020), however, generally confirms the findings of Ischen et al. (2020) and Rhim et al. (2022) from their research on chatbots. Based on the results of Valenzuela et al. (2019) we can emphasize that customers do not just react to a given digital voice in an accommodating manner, but an accommodation in terms of age and gender from the digital service side leads to a more

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positive perception of the service from the customers’ side as well. In this relation we point out the explicit relevance of communication accommodation theory for digital service, specifically, the transferability of results in physical surroundings to the digital service context (Giles et al., 1973; Thakerar et al., 1982). In sum, the level of anthropomorphism as well as the accommodation with regard to age and gender should be followed in future approaches. Even though the positive impact of an increasing level of anthropomorphism is not a surprise (Araujo, 2018; Han, 2021), the significant effect of a high level of age similarity (in contrast to average and low age similarity) goes clearly beyond common knowledge of research regarding age comparison (Avery et al., 2007; Dwyer, 1998). In contrast to Agthe et al. (2011) and Maner et al. (2009), who argue that gender congruence can trigger negative behaviours such as social comparisons or self-threats, we were able to show that these behaviours are not directly transferrable to the context of digital language-based services. Findings show that a lack of congruence leads to a lower willingness to interact, however, not to disclose personal information. Particularly with regard to customers’ disclosure behaviour, as it runs not analogously with customers’ willingness to interact with the digital counterpart, customers’ privacy calculus might need to be integrated in future approaches. The interaction of a digital counterpart on a higher level of anthropomorphism and a high level of age similarity seems to cause an increasing level of benefit in relation to the perceived risk on the customers’ side. Based on privacy calculus theory (Laufer and Wolfe, 1977; Dinev and Hart, 2006), customers’ willingness to disclose personal information depends primarily on customers’ inner conflict in balancing or calculating the respective costs and benefits.

3.6.8

Implications for Management, Limitations and Future Research

In general, it is important for retailers to create a service environment in which customers feel socially comfortable and welcome (Fiske et al., 2007; Huang and Rust, 2018; van Doorn et. al., 2017). Immediate adaptation of the SVA’s voice to customer demographics appears to improve service interaction, particularly with regard to high age similarity. But the aspect of gender congruence should also be included in the design of such algorithms. The same applies to the humanization of the voice, since this study showed that not only the willingness to interact with it increases, but also that a greater willingness to disclose data is relayed, which partially refutes the existing research in this area (Ha et al., 2020).

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This knowledge should not only be applied in practice in the context of the design of the algorithms, but customers and consumer protection organizations should also be aware of how specific properties of the SVA have a direct influence on the data-related behaviour of customers in particular. Customers should be informed of this and be mindful of it when interacting with such devices if the SVA’s voice is in a similar age range or has the same gender characteristics. One field could be the implementing of a specific voice on a ticket machine or in connection with digital services. Our findings give reason to further deepen the customer’s perception of the connection through the digital service. Even if we were able to show the relevance of age similarity and gender congruence and earlier research approaches could be confirmed, at least with regard to SVAs (Dwyer et al., 1998), other aspects could also play a role. For example, one could ask what influence a genderless voice has, which is currently being studied as part of another research project. It can be assumed that such a voice, which is generated in this project under the name ‘Q’, will reduce gender bias and discrimination (Copenhagen Pride et al., n.d.). Research also emphasized that similarity in basic attitudes increases interpersonal attraction and sympathy towards the other person (Byrne et al., 1986). Burt and Reagan (1997) showed that there is a clear tendency to be attracted to people with similar characteristics. Consequently, the specific relevance of the attractiveness of voices should be brought into the focus of further approaches. In addition, we must mention some limitations of our research. First of all, our research does not consider additional information about the environment of services or the dress, race, or gestures and facial expressions of interlocutors (Brack and Benkenstein, 2012) as they are common in physical service. Second, we concentrated on one electronic product (a speaker box) when selecting the product for this study. It should be noted that electrical goods have no longer been primarily a male domain in recent years, but in addition to electronics, other segments must also be integrated in future studies. Third, gender congruence results may not automatically apply to every retail segment or service. Especially when it comes to information that is sensitive for the customer, our results with regard to gender congruence could be significantly strengthened again. It can be assumed that women, for example, might be reluctant to reveal too much information about their body measurements to a young male voice or to ask them for service on buying underwear. Men, on the other hand, could hold back in speaking to a female voice when it comes to buying a car. Future research needs to investigate how the identified factors affect different product categories. In addition, customers’ perception of different price structures might also be related to the potential willingness to disclose (Schmidt et. al., 2020). Moreover, we conducted the study

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in Germany, and prior research has shown several important differences with respect to personal characteristics (e.g., age, culture and education) and general customer behaviour between countries and cultures (Miltgen and Peyrat-Guillard, 2014). Therefore, cross-cultural studies could provide additional insights on how the design of the SVA could be adjusted according to customers’ cultural or even ethnic backgrounds (Luoh and Tsaur, 2009).

3.7

Essay 7. The Influence of Technology Infusion on Customers’ Information Disclosure Behaviour within the Frontline Service Encounter

3.7.1

Introduction

The interest for more personalisation in advertisements, addressing customers, and products means that information on customers’ needs to be gathered and analysed to customise retail services (Bleier and Eisenbeiss, 2015). Hence, the relevance of collecting, storing, and analysing customer information to gain competitive advantage is growing (Piotrowicz and Cuthbertson, 2014). In traditional bricks-and-mortar retail stores, customer information might help improve employee-customer interactions, especially if frontline employees have knowledge of customers’ lifestyle activities, shopping habits, or financial potential. But, encouraging customers to disclose information is one of the biggest challenges for retailers today (e.g. Krawatzki et al., 2017). In contrast to online contexts, at the stationary Point of Sale (PoS) the immediate integration of customer information into service encounters is more difficult, as service employees cannot store or retrieve customer information in the same manner as efficient and effective information systems. The integration of mobile technology might help collect and store customers’ information to improve frontline customer service. Several studies focus on frontline service employee substitution at the PoS (e.g. Huang and Rust, 2018), especially the augmentation of traditional faceto-face frontline service through the infusion of technology might be a suitable measure to improve PoS services and encourage customers to disclose their information to optimise service encounters. Previous research in retailing shows many positive effects when the frontline service is infused by a certain technology, for example, in the perception of general customer services, frontline employee adaptability, customisation, and customer enjoyment (e.g. Ahearne et al., 2008; Lee and Lyu, 2019). Through the infusion of the frontline service via technology, it is possible to improve the interpersonal relationship between the customer

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and frontline employee (e.g. Hunter and Perreault, 2007; Rust and Huang, 2014). Wünderlich et al. (2013) and Giebelhausen et al. (2014) point out the importance of a deeper investigation of interpersonal exchange and interaction within a technology-infused PoS service encounter and possible psychological barriers for the customer technology infusion. Literature focusing on the interaction and relation of customers and frontline employees shows that barriers are generally a result of communication or distractions (Coulter and Coulter, 2002). A technology-infused PoS service encounter offers the potential to gather customers’ information in a more structured way. However, a general psychological barrier might prevent the customer from disclosing personal information. Our study addresses the influence of the level of technology infusion to the PoS service as a central driver for customer information disclosure in stationary retail stores. In detail, our analysis mainly focuses on customers’ information disclosure while interacting face-to-face with a frontline employee without any form of technology and the customer’s information disclosure in PoS service encounters with different levels of technology infusion. We transfer role and script (R&S) theory (Solomon et al., 1985) to the given context, assuming an underlying script between the frontline employee and customer (i.e. a regular sales dialog) that might be harmed by a technology infusion of the frontline service encounter. Moreover, we consider Thibaut and Kelley’s (1959) social exchange theory that interpersonal exchanges are related to the individual perception of risk and benefit. In a frontline service context, we argue that potential change and violation of the customer’s original assumption of the interplay (script) between frontline employee and the customer leads to an increase in risk perception towards retailers’ potential information-misuse, due to technology infusion. Our research contributes to the field of customer information disclosure within the stationary retail store environment in several ways: We shed light on differences between technology-infused PoS services and human PoS services concerning information disclosure by systematically manipulating the technology infusion of the service (non technology-infused service (human only) versus technology-infused frontline employee service versus self-service technology (technology mainly)). Moreover, we investigate the moderating impact of an explanation of the use and security of the disclosed information (explanation is not given versus given) on customer information disclosure. We also demonstrate that customer information disclosure behaviour differs concerning the customers’ demographics, finances, lifestyle, as well as shopping habits concerning the level of technology infusion of the PoS service. We furthermore analyse the moderating effect of customers’ privacy concerns and perceived benefit of general

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information disclosure as well as the mediating impact of customers’ experienced emotions of technology infusion within the frontline service. Moreover, we investigate the role of trust in retailers’ use of the disclosed information and consequently, draw relevant implications for academia and practical applications. For example, our findings indicate that the infusion of technology in a frontline service encounter prevents customers disclosing information. But, an explanation for information-use and security increases a customers’ information disclosure when no technology is included in the PoS service and decreases information disclosure when technology infuses the PoS service. Overall, our results indicate, if the retailer intends to gather demographic information from the customer, a human only PoS service is advisable, whereas, with respect to the gathering of information on customers’ finances or lifestyle, a technology-infused PoS frontline service without a human might be superior.

3.7.2

Conceptual Framework and Hypotheses Development

We adapted role and script theory to investigate the influence of the level of technology infusion of the frontline service on customer information disclosure in the stationary retail store environment and the specific differentiation of human and technology supported frontline service. Role and script theory (Sheth, 1967) suggests that a change in the understanding of the accustomed role and script on one side leads to a change of the role behaviour on the other side. In a retail store context, we argue that the integration of technology might act as a violation of the underlying script, which, in turn, might decrease customer information disclosure. We propose that the integration of technology triggers customers’ privacy concerns and leads to higher perceived risk towards retailers’ potential information-misuse compared to a human only PoS service. Therefore, we refer to social exchange theory because social individuals tend to prefer interpersonal exchanges in cases where the associated risk is lower than the (expected) benefit (Thibaut and Kelley, 1959). Hence, an increase in the level of technology-infused service in the stationary retail service environment might foster customers’ perceived risk towards retailers’ potential information-misuse in general. The resulting research model is illustrated in Figure 3.13. In summary, we transfer the assumption by Posey et al. (2010), that risk and social exchange are decisive factors in explaining customers’ information disclosure, to the stationary PoS and investigate the impact of explaining the future use and security of disclosed information to customers in contrast to a buyingoff (e.g. via a monetary discount or a product incentive, e.g. Premazzi et al.,

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Mediator

Experienced Emotions

Self-Service Technology

TechnologyInfused Frontline Employee Service

Non TechnologyInfused Service

Moderator Explanation on Information-Use and Security

LEVEL OF TECHNOLOGY INFUSION OF THE PoS SERVICE

technology-based service

Moderator Privacy Concerns Information Disclosure Demographics Finances Lifestyle Shopping-habit Moderator Perceived Benefit of Information Disclosure at the PoS

human-employee-based service

Mediator Trust in Retailers‘ Use of the Disclosed Information

Figure 3.13 Research Model for Essay 7

2010). Consequently, we implement this explanation from frontline employees’ side and analyse its potentially moderating impact on the relationship between technology-infused PoS service and customer information disclosure. With respect to role and script theory, an explanation regarding informationuse and security might interrupt a learned script (i.e. regular sales talk) leading to customers’ disclosing less information when technology is infused with the service encounter. This assumption is based on social exchange theories, where in the case of no technology integration, an explanation on information-use and security should increase a customer’s information disclosure. In this case, customers feel less vulnerable, and their general risk perception towards retailers’ potential information-misuse decreases. However, a contrary effect might occur when technology is included in the situation. Finally, customers’ privacy concerns and perception of benefits regarding information disclosure at the PoS acts as a moderator in our research model (Kraft et al., 2017; Mothersbaugh et al., 2012). In line with these assumptions, we integrate trust in the retailers’ use of disclosed information and customers’ experienced emotions as potential mediators in the retail store environment for the proposed relationships (Bansal et al., 2016). Impact of the level of technology infusion of the PoS service on customer information disclosure The process in which customers consciously decide what information they provide, hold back, or keep private is also called disclosure management (Donna and Novak, 1997). Understanding this process means having better access to

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customers’ specific needs and desires. In this context, marketers, as well as researchers, try to understand how customers’ disclosure intention changes due to the customers’ perception of technology advantages (Milne et al., 2012). However, instore technologies should not only be seen as an opportunity to collect information but mainly as service support, which creates challenges for retailers (Piotrowicz and Cuthbertson, 2014). It is important to include PoS technology successfully in the frontline service as customer treatment depends on the individual frontline employees’ service competence (van Doorn et al., 2017). Recent literature indicates that the general influence of these technologies during the service encounter can negatively influence customers’ experience and act as a psychological barrier from customers’ site towards the general frontline service (Giebelhausen et al., 2014). Thus, we propose that a higher level of technology infusion to the frontline service might lead to a higher customer’s perception of risk towards retailers’ potential information-misuse. Moreover, it will result in a violation of the underlying script between customers and frontline employees (i.e. a regular sales talk), which leads to reduced information disclosure. H1:

An increasing level of the technology infusion of PoS service will negatively influence customer information disclosure in a stationary retail environment.

Moderating the impact of an explanation of the information-use and security on customer information disclosure Berendt et al. (2005) show that when the right circumstances are given, online users disclose even the most personal details without any compelling reason to do so. However, studies show that the amount of information also depends on the perceived advantages of the incentive (Phelps et al., 2000). The exchange of customer information, which corresponds with customers’ personal needs and values, can decrease personal costs and thus the willingness to disclose personal information increases (Premazzi et al., 2010). We apply social exchange theories in the context of a stationary retail store environment arguing that within today’s discussion on individual perceptions of information issues, customers perceive a lower risk towards retailers’ potential information-misuse when the use of the disclosed information (e.g. personalisation of advertisement and addressing) (Karwatzki et al., 2017b) and its safety (e.g. privacy policies) (Parks et al., 2017) is made clear. However, when technology is used within the frontline service, an explanation of information-use and security might sensitise the customers to the potential problems of digital information storage due to information misuse and increase customers’ risk perception in this

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context. The result of the presence of such an explanation is argued to be a lower disclosure of information from the customer. H2:

An explanation of the information-use and security decreases the impact of the level of technology infusion of the PoS service on customer information disclosure in a stationary retail environment.

Moderating the impact of customers’ privacy concerns on information disclosure Studies on online customer information disclosure show that entertainment decreases general privacy concerns (Krafft et al., 2017). In the stationary retail context, entertainment, in the form of an interesting product presentation, for instance, is an important factor. As privacy is a widely discussed topic, the consideration of customers’ individual privacy concerns by retailers seems to be understandable. Considering the recent development of the retail sector (e.g. Amazon Go), it is important to address customers’ fundamental privacy concerns as a potential driver of customer information disclosure in the stationary store environment. We follow the general assumption that privacy concerns might be the most distinct obstacle to information disclosure (Andrade et al., 2002) as it negatively affects information disclosure behaviour (Bansal et al., 2016). Recent literature shows that customer concerns on privacy issues are strongly related to customers’ risk perception towards retailers’ potential information-misuse with respect to behavioural intentions as protection and regulatory preferences (e.g. Miltgen and Smith, 2015). Therefore, we assume that an increase in customers’ privacy concerns strengthens the previously proposed negative effects of information disclosure. Based on this reasoning, we hypothesise: H3:

Customers’ privacy concerns weaken the effects of the level of technology infusion of PoS service on customer information disclosure.

Moderating the impact of customers’ perceived benefit of information disclosure at the PoS on information disclosure Previous research has shown that customers balance between costs and benefits when disclosing information online (White et al., 2014). Retailers, thus, are required to offer at least as much as the disclosed information is worth (Awad and Krishnan, 2006). Studies on online information disclosure focus on the benefits information disclosure contributes in terms of providing potentially different forms of personalisation (e.g. Bleier and Eisenbeiss, 2015; Krafft et al., 2017) to satisfy customers’ desires and preferences. At the stationary PoS, customers’ intuitively weigh the personal risks and benefits to maximise their benefits and

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minimise their perceived risks (Babin et al., 1994). The infusion of technology in the PoS frontline service is argued to decrease customers’ benefit. Hence, we hypothesise: H4:

Customers’ perceived benefit of information disclosure at the PoS reinforces the effects of the level of technology infusion of the PoS service on information disclosure.

Mediating the impact of customers’ experienced emotions on the influence of the level of technology infusion of the PoS service on information disclosure Holbrook and Batra (1987) investigated the mediating impact of emotions on the relationship between a given stimulus and the corresponding response. Emotions have been found to explain the link between store environment and customers’ behavioural outcomes in online and offline environments (Eroglu et al., 2001; Menon and Kahn, 2002). Moreover, in an online context, Dinev et al. (2015) link emotions with customers’ privacy concerns and customer information disclosure. Emotions are an initial hurdle to disclosing information, as customers’ positive mood, for instance, correlates negatively with customers’ risk perception (Fedorikhin and Cole, 2004). We, therefore, assume that in interpersonal frontline service, customers’ mood or specific emotions influence the customers’ risk perception towards retailers’ potential information-misuse. In addition, Dennis et al. (2010) pointed out the relevance of experienced emotions as a mediator of customers’ perception of PoS technologies and customers’ behaviour in a stationary store environment. With respect to the assumed increase in customers’ risk perception towards retailers’ potential information-misuse and the violation of the underlying script between customer and frontline employee, we see customers’ experienced emotions acting as a mediator on the postulated main effect: H5:

Customers’ experienced emotions mediate the hypothesised relationships between the level of technology infusion of the PoS service on customer information disclosure.

Mediating the impact of customer trust in retailers’ use of the disclosed information on the influence of the level of technology infusion of the PoS service on information disclosure Numerous studies in information disclosure have investigated customers’ trust as well as risk as a central condition for customers’ disclosure behaviour (e.g. Miltgen and Smith, 2015). For instance, research indicates that trust acts as an

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antecedent of risk (e.g. Zimmer et al., 2010). Moreover, the positive influences of trust on customer information disclosure have been shown in numerous studies, e.g. trust in the business (e.g. Bansal et al., 2016), the website (e.g. Wakefield, 2013), or the general media environment (e.g. Aljukhadar et al., 2010). Besides to the immediate influence on customers’ disclosure behaviour, customers’ relationship with the retailer (White, 2004), as well as customers’ perception of familiarity of the online retailer (Li, 2012) are influential drivers that explain the effect of customers’ information disclosure behaviour. As the general relation of the customer towards the frontline service is of additional interest in this context, we argue that the integration of technology within the stationary retail store environment decreases customer information disclosure. Based on this reasoning, we hypothesise that trust in retailers’ use of the disclosed information mediates the proposed relationships. H6:

3.7.3

Customers’ trust in retailers’ use of the disclosed information mediates the hypothesised relationships between the level of technology infusion of the PoS service on customer information disclosure.

Empirical Study: Method and Procedure

Stimuli design We tested our hypotheses with a quasi-experimental online study by using a 3 (non technology-infused service (human only) versus technology-infused frontline employee service versus self-service technology (technology mainly)) × 2 (explanation on information-use and security is not given versus given) between subject experimental design. Within the experimental conditions, the subjects were asked to imagine a service encounter at a stationary PoS. The respondents were exposed to a written scenario in which the level of technology infusion to the PoS frontline service was systematically manipulated. The technology-infused PoS frontline service was described as a frontline employee using a tablet computer during the frontline service or the pure use of technology as alternative, taking place at an interactive self-service technology. We used an explanation on information-use, which was randomly given (versus not given) to the subjects to study its moderating impact. In particular, the subjects were told that all the potentially given information was going to be used in terms of service and product optimisation such as personalised offers, advertisement, and instore guidance. In addition, the subjects were assured that the collected information would be stored in the in-house information pool and would not be handed or sold to any third party.

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Measurement and procedure The customers’ willingness to disclose information was measured by adapting the scales from Milne et al. (2012) and Phelps et al. (2000) to the stationary retail context (26 items, 7-point Likert scale, 1 = no willingness—7 = high willingness). Principal component factor analysis (Varimax-rotation) was conducted to identify and verify the subordinated dimensions of customer information disclosure. Based on Kaiser and Rice (1974), Kaiser-Meyer-Olkin (KMO) Kriterium reached a sufficientlay level (KMO = 0.921, χ2 = 4477.502, df = 210, p = 0.000). Following previous research, factor loadings above 0.55 for each indicator were considered to confirm that the identified variables are represented by a particular factor (e.g. Comrey and Lee, 1992). Based on the Eigenwert criterion (> 1), the results reveal four dimensions (including 22 items) of information disclosure used as dependent variables in further analysis (Table 3.24). Table 3.24 Results of exploratory factor analysis Demographics (α = 0.901) First name

0.718

Last name

0.812

Age

0.608

Date of birth

0.710

Address/Address

0.790

Telephone number

0.748

Email address

0.833

Finance (α = 0.787)

Employer

0.552

Income

0.680

Account balance

0.877

SSN

0.819

Place of birth

0.670

SSB

0.819

Lifestyle (α = 0.910)

Educational qualification

0.753

Marital status

0.796

Nationality

0.687

Religious affiliation

0.762

Weekly sports lessons

0.732

Shopping-habit (α = 0.851)

(continued)

3.7 Essay 7. The Influence of Technology Infusion on Customers’ Information … 163 Table 3.24 (continued) Demographics (α = 0.901)

Finance (α = 0.787)

Leisure activities

Lifestyle (α = 0.910)

Shopping-habit (α = 0.851)

0.713

Last product purchased

0.840

Price of the last product purchased

0.849

Online shopping behaviour

0.615

Note: columns contain the resulting factor loadings

In line with various quantitative approaches to measuring the perception and relevance of innovative technologies that focus on our research questions, we conducted an online survey containing validated scales (Table 3.25). Table 3.25 Constructs, Source, Scale (7-point-likert-scale: 1 = I totally disagree—7 = I totally agree), Item Adaptation and Outer Loading for Essay 7 construct

source

scale

Demographics

Milne et al. (2012) / Phelps et al. (2000)

7-point-likert-scale First name (1 = no willingness Last name to 7 = high Age willingness) Date of birth

Finance

item adaptation

factor α loading 0.718

0.901

0.812 0.608 0.710

Address/Address

0.790

Telephone number

0.748

Email address

0.833

Employer

0.552

Income

0.680

Account balance

0.877

SSN

0.819

Place of birth

0.670

SSB

0.819

0.787

(continued)

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Table 3.25 (continued) construct

source

scale

Lifestyle

Shopping-habit

Customers’ Dinev and 7-point-likert-scale Overall Privacy Hart (2006) Concerns

item adaptation

factor α loading

Educational qualification

0.753

Marital status

0.796

Nationality

0.687

Religious affiliation

0.762

Weekly sports lessons

0.732

Leisure activities

0.713

Last product purchased

0.840

Price of the last product purchased

0.849

Online shopping behaviour

0.615

I am concerned that a person may find my personal information (email address, phone number, etc.) that I disclose.

0.959

I am concerned that personal data I disclose could be misused.

0.925

I am concerned about disclosing personal information because it could be used in ways that I cannot foresee.

0.955

0.910

0.851

0.960

I am concerned about 0.944 disclosing personal information because I do not know what others might do with that information. Perceived Benefit of Information Disclosure at the PoS

Kim et al. (2008)

7-point-likert-scale

I think disclosing 0.844 information at the PoS is convenient. I can save money by disclosing information at the PoS.

0.892

0.754

(continued)

3.7 Essay 7. The Influence of Technology Infusion on Customers’ Information … 165 Table 3.25 (continued) construct

source

scale

item adaptation

factor α loading

I can save time by disclosing information at the PoS.

0.876

Disclosure of information at the PoS or allowing the retailer to use my data for internal processes, enables me to accomplish a shopping task more quickly than using traditional stores.

0.859

Disclosure of 0.841 information at the PoS or allowing the retailer to use my data for internal processes, increases my productivity in shopping (e.g. make purchase decisions or find product information within the shortest time frame) PAD: Pleasure

Mehrabian and Russel (1974)

sematic-differential unhappy—happy

0.880

annoyed—pleased

0.895

dissatisfied—satisfied

0.892

0.927

melancholic—contented 0.853

PAD: Arousal

hopeful—despairing

0.812

bored—relaxed

0.821

relaxed—stimulated

0.731

calm—enthusiastic

0.616

sluggish—hectic

0.750

dull—jittery

0.811

sleepy—wide awake

0.718

unarousaled—arousaled

0.797

0.831

(continued)

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Table 3.25 (continued) construct

source

scale

PAD: Dominance

Trust in Retailers’ Use of the Disclosed Information

Sheinin et al. (2011)

7-point-likert-scale

item adaptation

factor α loading

controlled—controlling

0.839

influenced—influential

0.831

cared for—in control

0.563

awed—important

0.864

submissive—dominant

0.857

forced—free

0.861

The use of the disclosed information by the retailer is trustworthy.

0.951

0.891

0.946

The retailer gives the 0.939 impression that he keeps promises and commitments, regarding the use of the disclosed information. I believe that the retailer 0.959 has my best interests in mind, regarding the use of the disclosed information.

In a pre-test (38 participants, women: 57.89%, average age: 27.66 (SD = 9.20)), the generated questionnaire was tested concerning the understanding and clarity of the items. Minor changes in wording were made based on the results of this pilot test. By applying Fornell and Larcker’s (1981) criterion, we assessed all reflective scales for discriminant validity. Hereby none of the used construct shares more variance with any construct but with its own indicators (Table 3.26). Subjects and manipulation check In total, in our main study, 322 subjects (women: 57.76%) with an average age of 29.87 (SD = 10.60) years participated in this study. The subjects were almost equally distributed between the types of frontline employee service (non technology-infused service: N = 111; technology-infused frontline employee service: N = 116; self-service technology: N = 95) and if an explanation was given or not (not given: N = 154, given: N = 168).

3.7 Essay 7. The Influence of Technology Infusion on Customers’ Information … 167 Table 3.26 Results of Correlation Matrix and Discriminant Validity for Essay 7

PC

Mean (SD)

PC

PB

4.80 (1.67)

0.945

0.077

PB

3.48 (1.37)

0.006

0.998

EMP

3.75 (1.13)

0.068

0.006

EMA

3.94 (0.90)

0.005

0.017

EMD

3.61 (1.17)

0.007

0.001

T

3.60 (1.42)

0.005

0.986

EMP –0.261 –0.076 0,859 0.039

EMA

EMD

–0.069 0.130 –0,199

–0.083 0.025 0,521

T 0.069 0.993 –0,071

0.724

–0.170

0.127

0,272

0.029

0.809

0.023

0,005

0.016

0.001

0.999

Note: SD = Standard Deviation; PC = Pprivacy Concerns; PB = Perceived Benefit of Information Disclosure at the PoS; EMP = Experienced Emotions: Pleasure; EMA = Experienced Emotions: Arousal; EMP = Experienced Emotions: Dominance; T = Trust in Retailers’ Use of the Disclosed Information; diagonal includes the AVE; values below diagonal include the square correlations; values above diagonal include the normal

We used the subjects’ evaluations of the perceived risk towards retailers’ potential information-misuse concerning the level of technology infusion of the PoS service as a manipulation check for our experimental design. We adapted the approach of Campbell and Goodstein (2001) to measure the customers’ perceived risk (four items, e.g. 1 = not risky to 7 = extremely risky, α = 0.938). ANOVA tests were conducted to check whether the intended manipulation of the perceived risk was successful (perceived risk: Mnon technology-infused service = 3.35 (1.57), Mtechnology-infused frontline employee service = 4.53 (1.29), Mself-service technology = 4.73 (1.23), F(1,316) = 31.61, p < 0.001, η2 = 0.165). Hence, we can confirm a successful manipulation of risk perception. In addition, we controlled for the technological affinity (F(1,319) = 0.16, p = 0.85) of our respondents, yet we did not find any systematic distortion concerning our treatments.

3.7.4

Results

Impact of the level of technology infusion of the PoS service an explanation on information-use and security on customer information disclosure To analyse hypothesis 1, we conducted several ANOVAs. In Table 3.27, the mean scores of the dependent variables in the experimental conditions are summarised.

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Table 3.27 Results of the hypothesis testing ANOVA (DV: Dimensions of Information Disclosure) Dependent Variable: Demographics Level of Technology Infusion of the PoS Service (LoTIS)

Mean (SD) Explanation (E) not given

Explanation (E) given

F-Value LoTIS

E

LoTIS x E

Non Technology-Infused Service

3.43 (1.57)

3.96 (1.39)

6.078** (η2 = 0.037)

0.122 (η2 = 0.000)

2.966 (η2 = 0.018)

Technology-Infused Frontline Employee Service

3.61 (1.43)

3.33 (1.82)

Self-Service Technology

3.17 (1.55)

2.73 (1.53)

Dependent Variable: Finance Level of Technology Infusion of the PoS Service (LoTIS)

Mean (SD) Explanation (E) not given

Explanation (E) given

F-Value LoTIS

E

LoTIS x E

Non Technology-Infused Service

1.92 (1.29)

1.96 (1.04)

9.848*** (η2 = 0.059)

0.799 (η2 = 0.003)

1.229 (η2 = 0.008)

Technology-Infused Frontline Employee Service

1.51 (0.73)

1.52 (1.22)

Self-Service Technology

1.54 (0.83)

1.20 (0.32)

Dependent Variable: Lifestyle Level of Technology Infusion of the PoS Service (LoTIS)

Mean (SD) Explanation (E) not given

Explanation (E) given

F-Value LoTIS

E

LoTIS x E

Non Technology-Infused Service

3.35 (1.66)

3.78 (1.65)

4.684** (η2 = 0.029)

1.151 (η2 = 0.004)

3.253* (η2 = 0.020)

Technology-Infused Frontline Employee Service

3.25 (1.63)

2.95 (1.83)

(continued)

3.7 Essay 7. The Influence of Technology Infusion on Customers’ Information … 169 Table 3.27 (continued) Dependent Variable: Demographics Level of Technology Infusion of the PoS Service (LoTIS)

Mean (SD) Explanation (E) not given

Explanation (E) given

F-Value

Self-Service Technology

3.23 (1.83)

2.51 (1.30)

LoTIS

E

LoTIS x E

Dependent Variable: Shopping-habit Level of Technology Infusion of the PoS Service (LoTIS)

Mean (SD) Explanation (E) not given

Explanation (E) given

F-Value LoTIS

E

LoTIS x E

Non Technology-Infused Service

3.90 (1.58)

4.42 (1.78)

3.026* (η2 = 0.019)

1.442 (η2 = 0.005)

3.958* (η2 = 0.024)

Technology-Infused Frontline Employee Service

4.06 (1.85)

3.62 (1.97)

Self-Service Technology

3.96 (1.61)

3.17 (1.55)

Note: Items were measured according to Premazzi et al. (2010) using a 7-Point Likert-Scale (1 = no willingness—7 = high willingness). *p < 0.05, **p < 0.01, ***p < 0.001

In summary, customer information disclosure is significantly affected by the level of technology infusion of the PoS service (Mnon technology-infused service = 3.49 (1.26), Mtechnology-infused frontline employee service = 3.09 (1.30), Mself-service technology = 2.77 (1.12), F(1,319) = 8.92, p < 0.001, η2 = 0.053). This negative effect also holds true for the dimension of information disclosure. In detail, an analysis of the planned contrasts shows that with respect to information on demographics, the infusion of technology with frontline employee service in contrast to a self-service technology shows a significant difference (demographics: Mtechnology-infused frontline employee service = 3.47 (1.63), Mself-service technology = 2.94 (1.54), (t(1,209) = 2.405, p < 0.05). A contrary effect is shown in the results for information disclosure on finance. Here, the human frontline employee service alone seems to be specifically relevant in contrast to the two cases of technology-infused service (finance: Mnon technology-infused service = 1.94 (1.15), Mtechnology-infused frontline employee service = 1.51 (1.00), (t(1,225) =

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2.973, p < 0.01). Similar results apply to the willingness to disclose information on personal lifestyle (lifestyle: Mnon technology-infused service = 3.85 (1.66), Mtechnology-infused frontline employee service = 3.10 (1.73), (t(1,225) = 2.127, p < 0.05). Information disclosure on shopping habits, however, does not seem to be affected. In sum, the results confirm hypothesis 1. The level of technology infusion of PoS service interacts significantly with an explanation on the information-use and security (F(1,319) = 4.47, p < 0.05, η2 = 0.028) on the overall information disclosure as well as on the single dimensions. More precisely, results show an increase in information disclosure when an explanation is given in case of non technology-infused service and a decrease when technology is infused (technology-infused frontline employee service and self-service technology), supporting H2. The inclusion of an explanation on information-use and security in combination with the presence of a form of technology is sufficient to lessen information disclosure. Apart from the demographics dimension, customers do not show any particular difference concerning a human only or a technology-infused frontline employee service. The customers’ knowledge of the use of their information seems to trigger an awareness that functions as a negative multiplier on customer information disclosure. In particular, the results show the impact of the level of technology infusion of the PoS service on the four dimensions; concerning the information of demographics and finance, a contrast between a human-only service as well as the technology-infused services is observable. The customers’ willingness to disclose information on demographics seems to depend more on the presence of the frontline employee than in case of providing information on finances. In fact, the analysis shows a significant difference between technology-infused frontline employee service and self-service technology (t(1,209) = 2.405, p < 0.05) but not between human only service and technology and human service (t(1,225) = 1.216, p > 0.05). Within finance, this effect is the opposite (human only service versus technology-infused frontline employee service: t(1,225) = 2.973, p < 0.01; technology-infused frontline employee service and self-service technology (t(1,209) = 1.311, p > 0.05)). Moreover, within the information categories of lifestyle and shopping habit, no difference can be determined. Overall, in the case where an explanation on information-use and security by the retailer is given, the technology-infused service triggers a significantly lower information disclosure. Moderating the impact of customers’ privacy concerns and perceived benefit of information disclosure at the PoS on information disclosure We used PROCESS (Model 1) suggested by Hayes (2019) to determine the moderating impact of customers’ privacy concerns and customers’ perceived benefit of

3.7 Essay 7. The Influence of Technology Infusion on Customers’ Information … 171

Customers’ Information Disclosure

information disclosure at the PoS on the information disclosure dimensions. We added the scenario as an independent variable with dummy coding (Hayes, 2017), gradually the disclosure dimensions as dependent variables and as moderators the impact on customers’ privacy concerns and customers’ perceived benefit. In contrast with our expectations, the impact of customers’ privacy concerns seems to be negligible as a moderator within the overall findings as well as in terms of the four dimensions. The results show no effect of privacy concerns on the influence of the level of technology infusion of the PoS service on demographics, finance, lifestyle, or shopping habits. Instead, customers’ perceived benefit of information disclosure at the PoS effects this relation partially. We obtained a significant moderating effect with regard to the finance dimension (Int1 : β = –0.210, p = 0.031, LLCI = –0.40, ULCI = –0.019 and Int2 : β = –0.233, p = 0.022, LLCI = –0.43, ULCI = –0.03; R2 = 0.016, F(2,292) = 2.55, p = 0.07) as well as regarding shopping habit (Int2 : β = –0.508, p < 0.01, LLCI = –0.87, ULCI = –0.14; R2 = 0.026, F(2,292) = 4.33, p = 0.014). In both cases, the higher perceived benefits lead to a higher willingness of information disclosure (i.e. negative coefficients are based on the main effect). Figure 3.14 depicts the effect on finance.

low perceived benefit 16th percentile No Technology-Infused Service

high perceived benefit 50th percentile Technology-Infused Frontline Employee Service

84th percentile Self-Service Technology

Figure 3.14 Moderating Impact of perceived Benefits on Customer’s Information Disclosure

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Mediating the impact of customers’ experienced emotion and trust in retailers’ use of the disclosed information on the influence of the level of technology infusion to the PoS service on information disclosure We first investigated if our experimental conditions affect the proposed mediators as a necessary condition to test the postulated mediating impact of customers’ trust in retailers’ use of the disclosed information on the influence of the level of technology infusion of the PoS service (Zhao et al., 2010). Thus, we found a significant effect of the general level of technology infusion of the PoS service on customer information disclosure. Table 3.28 Results of the hypothesis testing ANOVA (DV: Perceived Trust in Retailers’ Use of the Disclosed Information) Level of Technology Infusion of the PoS Service (LoTIS)

Mean (SD) Explanation (E) not given

Explanation (E) given

F-Value LoTIS

Non Technology-Infused Service

4.30 (1.56)

3.91 (1.44)

10.234*** (η2 0.607 (η2 = = 0.066) 0.002)

Technology-Infused Frontline Employee Service

3.42 (1.31)

3.50 (1.36)

Self-Service Technology

3.27 (1.46)

3.21 (1.15)

E

LoTIS xE 0.812 (η2 = 0.006)

Note: Items were measured according to Sheinin et al. (2011) using a 7-Point Likert-Scale (1 = I totally disagree—7 = I totally agree). *p < 0.05, **p < 0.01, ***p < 0.001

The results indicate a significant effect of the level of the technology infusion of the PoS service, both on customers’ trust in retailers’ use of disclosed information (Table 3.28) and customers’ experienced emotion (Table 3.29). Our findings show that the infusion of technology in the PoS service seems to be an important driver of customers’ perception of the PoS and decreases customers’ trust in retailers’ use of the disclosed information. Again, no significant difference can be stated if an explanation on information-use and security is given between the different levels of technology infusion of frontline service. Focusing on the technology-infused PoS scenarios, the self-service technology leads to a lower level of customer’s than the technology-infused frontline employee service where

3.7 Essay 7. The Influence of Technology Infusion on Customers’ Information … 173

a human is present. Interestingly, in the case of an explanation on information-use is given, the results decrease when technology is not included in the PoS service. Table 3.29 Results of the hypothesis testing ANOVA (DV: Experienced emotions) Pleasure Level of Technology Infusion of the PoS Service (LoTIS)

Mean (SD) Explanation (E) not given

Explanation (E) given

F-Value LoTIS

Non Technology-Infused Service

3.95 (1.12)

4.35 (1.15)

13.446*** (η2 0.523 (η2 = = 0.078) 0.002)

Technology-Infused Frontline Employee Service

3.82 (1.04)

3.45 (0.99)

Self-Service Technology

3.54 (1.31)

3.25 (1.84)

E

LoTIS x E 4.223* (η2 = 0.026)

Arousal Level of Technology Infusion of the PoS Service (LoTIS)

Mean (SD)

F-Value

Explanation (E) not given

Explanation (E) given

LoTIS

E

LoTIS x E

Non Technology-Infused Service

3.87 (0.83)

3.76 (1.01)

3.213* (η2 = 0.020)

1.107 (η2 = 0.003)

0.470 (η2 = 0.003)

Technology-Infused Frontline Employee Service

4.10 (0.93)

4.11 (0.83)

Self-Service Technology

4.00 (0.91)

3.78 (0.81)

E

LoTIS x E

Dominance Level of Technology Infusion of the PoS Service (LoTIS)

Mean (SD)

F-Value

Explanation (E) not given

Explanation (E) given

LoTIS

Non Technology-Infused Service

3.87 (1.18)

4.22 (1.33)

13.503*** (η2 0.031 (η2 = = 0.079) 0.000)

Technology-Infused Frontline Employee Service

3.38 (0.94)

3.32 (1.09)

2.621 (η2 = 0.016)

(continued)

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Table 3.29 (continued) Pleasure Level of Technology Infusion of the PoS Service (LoTIS)

Mean (SD) Explanation (E) not given

Explanation (E) given

F-Value

Self-Service Technology

3.56 (1.16)

3.20 (0.93)

LoTIS

E

LoTIS x E

Note: Emotion were measured with the same items as reported in Mehrabian and Russel (1974) using a 7-Point sematic differential (e.g. pleasure: 1 = unhappy—7 = happy; arousal: 1 = calm—7 = excited; dominance: 1 = controlled—7 = controlling); *p < 0.05, **p < 0.01, ***p < 0.001

Concentrating on the different types of potential emotions, we found that the absence of technology leads to the strongest emotional reactions, as customers perceive the highest amount of pleasure and dominance in this scenario in contrast to technology-infused PoS services. There is a strong decrease in pleasure and dominance when an explanation is given, in comparison to the general effect of customer information disclosure. We refer to Hayes and Preacher (2013) as well as Song and Zinkhan (2008) to finally test the hypothesised mediating effect of trust in retailers’ use of the disclosed information and the experienced emotions by conducting multiple analyses of covariance (ANCOVAs). Thereby, the decrease of the mean square (MS) of the main effect or interactions indicates a mediation effect (Song and Zinkhan, 2008). We focus on the actual mediation effect because the effect of the experimental conditions holds true concerning all postulated variables. In particular, we conducted ANCOVAs where the scenario is added as an independent variable; the information disclosure dimensions gradually as dependent variables and the potential mediators as covariates one at a time. The decrease in MS shows the mediation effect, as long as a significant main effect of the covariate on the dependent variables is observed (Song and Zinkhan, 2008). Table 3.30 depicts the results of our analyses. In general, the results indicate that with regard to all four categories of information, the willingness to disclose is affected by the proposed mediators. However, we do not observe any mediation effect of arousal or dominance in cases of information on demographics. Moreover, the results indicate that the willingness to provide information on finance is mediated by customers’ trust in

3.7 Essay 7. The Influence of Technology Infusion on Customers’ Information … 175 Table 3.30 Results of the hypothesis testing mediation analysis MS without mediator

MS with mediator (percentage decrease of MS in comparison to MS without mediator)

Dimension of Information Disclosure

General Effect Perceived Trust in Experienced Retailers’ Use of Emotion the Disclosed (pleasure) Information

Experienced Emotion (dominance)

Demographics

16.146

6.664 (58.7 %)*

6.146 (61.9 %)*

–

Finance

9.577

4.318 (73.3 %)

4.212 (73.9 %) 4.672 (71.1 %)

Lifestyle

14.501

3.626 (77.5 %)*

3.795 (76.5 %)*

5.667 (64.9 %)*

Shopping-habit

10.755

2.370 (85.3 %)*

1.483 (90.8 %)*

4.077 (74.7 %)*

Note: MS: mean square; *p < 0.05

retailers’ use of the disclosed information as well as experienced emotions. However, we only identify partial mediation effects. Hence, because the main effect of the scenario does not vanish, the results also leave room for more mediators and further research in this context. The results show that customers’ process more deepened trust in retailers’ use of the disclosed information as well as experienced emotions such as more pleasure and less dominance, when no technology is infused. Consequently, H5 and H6 do not hold within all dimensions; however, a mediating effect is observable. H5 does hold for information on lifestyle and shopping habit, and H6 holds true for pleasure in the case of general information disclosure, information on demographics, lifestyle, and shopping habit. Dominance instead only holds in case of lifestyle and shopping habit.

3.7.5

Discussion and Conclusions

The findings of our study show that the level of technology infusion to the PoS service has a significant effect on customer information disclosure. In line with Giebelhausen et al. (2014), the results indicate that the use of technology within a service encounter does not necessarily enhance frontline service. Traditional frontline service leads to a higher willingness to disclose information in all scenarios, even if no explanation for how or what the information is used

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is given. Moreover, we show the relevance of a differentiated perception of the information-use explanation as a general form of incentive for customers to disclose information, especially in comparison with monetary or product incentives (e.g. Premazzi et al., 2010). Furthermore, we provide empirical evidence that technology infusion of the PoS service has a different impact on customers regarding gathering different types of information from the customer. The customers’ willingness to provide information on lifestyle and shopping habits seems to be similarly impacted by the customers’ experienced emotions. Although focusing on customers’ perceived benefits of information disclosure at the PoS, certain information, such as financial information, may be more sensitive than other information and this seems to be affected by the level of technology infusion of the PoS service. Expanding on the results of Dennis et al. (2010), we show the relevance of customers’ experienced emotions when the service encounter is technology-infused. Pleasure and dominance mediate the influence of the level of technology infusion of the PoS service, especially concerning the willingness to provide information on lifestyle and shopping habits. This indicates that customers’ perceptions of pleasure and dominance play an important role in customer information disclosure. Moreover, trust in retailers’ use of the disclosed information triggers a similar mediating effect and thus, leads to a more profound insight into customers’ individual and differentiated processing when technology is included in the PoS service. Furthermore, we demonstrate the importance of a perceived benefit of information disclosure at the PoS moderating the customers’ willingness to provide information on shopping habits and finance. Even more surprising is the result that customers’ privacy concerns do not affect the influence of the level of technology infusion on the PoS service on customers’ information disclosure at all.

3.7.6

Implications for Management

Our study highlights that the relationship between the customer and frontline employee seems to be a decisive factor in the stationary retail store environment. Therefore, the infusion of technology within the frontline service needs to be differentiated in a more personal form of interaction to build up a bond between employee and customer and to encourage information disclosure at the PoS. We suggest a smart and individual use of technologies to gather a specific type of information in this context. When it comes to information on demographics,

3.7 Essay 7. The Influence of Technology Infusion on Customers’ Information … 177

frontline employees should not leave the customer alone with a technologyinfused service. Retailers who are interested in personalised advertisements or even customer addressing should not rely on self-service technologies at this point but concentrate on a human and technological approach to the service encounter. In contrast, concerning the gathering of customers’ financial information, which is relevant when the frontline employee needs to decide what price level the potentially offered products have, technology infusion within the frontline service seems to act as a psychological barrier for the customer (Giebelhausen et al., 2014). Retailers should behave similarly when information on customers’ lifestyle behaviour is of interest. Nevertheless, smart and sensible integration of an explanation is furthermore relevant to keep the frontline employee only service constant and increase the frontline service when technology is infused in the frontline service. Moreover, retailers are advised to emphasise the customers’ perception of individual benefits of information disclosure to encourage the customers’ information disclosure not only for information on finance and shopping habits but also on demographics and lifestyle. In addition, we suggest that retailers should try to reduce customers’ experienced emotion of dominance to enhance their acceptance of the technology infused service encounter. Retailers are advised to concentrate more on strategic approaches, focusing on customers’ perceptions of pleasure and dominance as well as on enhancing customers’ trust in retailers’ use of the disclosed information when technology is included in the PoS service. The technology used (e.g. tablet) and how the frontline employees act towards the customer should offer the impression of more (self-)control to the customer (Mahardika et al., 2019). Concerning a more long-term and thereby strategic perspective, customers seem to need to understand the advantages of an in-house information pool when they are asked to provide even more information. This positive relationship should help optimise the customer experience at the PoS and help to build a competitive advantage for the retailer.

3.7.7

Implications for Further Research

Our study highlights implications for future research in the context of a technology-infused stationary retail environment. First, we showed the general impact of technology infusion of the PoS service on customers’ willingness to disclose information, the customers’ actual purchasing behaviour, and that faceto-face interaction should be addressed more intensively in a stationary retail

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environment. Following the work by Fortes and Rita (2016), who presented initial insights on customers’ online decision-making processes regarding customer information disclosure, an analogous analysis within the stationary retail store environment is required. Second, analysing the interplay between frontline employees’ competencies (Ford et al., 1987) and customers’ willingness to disclose information might help to provide a deeper understanding of the impact of technology integration at the PoS. Frontline employee competencies, their knowledge, skills, and personal characteristics (Rentz et al., 2002) might function as a specific trigger in enhancing customers’ willingness to provide information. Such findings might help optimise the general interaction between frontline employees and the customer. Third, besides the potential influence of frontline employees on customer information disclosure, one further influence might be the stationary retail store environment itself. Numerous studies focus on the impact of fundamental atmospheric aspects (Eroglu et al., 2003), the general store image (Hultman et al., 2017), store attributes (Kim et al., 2015), and the level of store design (Murray et al., 2015) on customers’ perception and or purchasing behaviour. It thus seems to be important to include the influence of the specific store environment on customers’ willingness to provide personal information to the retailer as well as the role that the integration of technology in the PoS performs in this context.

3.8

Essay 8. Help Us to Help You: The Effects of Customer Incentivisation and Technology Infusion on Data Disclosure and Accuracy in Stationary Retail

3.8.1

Introduction

A company’s current and future success is influenced by its ability to collect, store and analyse customer data (Piotrowicz and Cuthbertson, 2014). When customers wish to purchase a product online, they have to provide certain data (e.g. name, address, credit card number) in order to complete the transaction; this requirement may include private data. However, retailers often try to collect more than the necessary data in order to improve their marketing efficiency and effectiveness. They do so, for example, by optimising assortments, providing individualised offers and/or targeting customers using the data they have provided (e.g. Krafft et al., 2017). From a managerial point of view, optimised data can be considered

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179

as a source of competitive advantage; for example, it offers the opportunity to analyse purchase patterns and to segment customers. It may also potentially make online product recommendations more personal (Karwatzki et al., 2017a). How companies obtain personal data from customers in the context of online services has been the subject of intense debate in recent years (Yu et al., 2020). However, it is also important for retailers to be able to generate customer-related data at the stationary Point of Sale (PoS). If retailers want to collect customer data at their physical stores, then the hurdles they face are higher than those experienced by online retailers. As, in contrast to global online marketplaces, small stationary retailers usually lack the ability to engage in strategic data gathering, they need to establish alternative approaches. One such approach might be the infusion of technology, which can be combined with a consequent customer incentivisation within the service interaction. Various explanations or incentives (monetary advantages or personalised services) are suggested in the online context with the aim of increasing the amount and types of data customers are willing to disclose (Krafft et al., 2017; Premazzi et al., 2010). A transfer of such strategies into the brick-and-mortar realm seems reasonable; its viability and effectiveness are therefore analysed within our research. Here, we see a difference between customers’ intention to provide personal data generally (quantity) and their intention to provide personal data accurately (quality) (e.g. Luo and Hancock, 2020). In the past, the infusion of certain technologies (which can be used to gather and analyse customers’ data) into physical retail was primarily a topic discussed in the context of customer loyalty cards (e.g. Cortiñas et al., 2008). In addition to loyalty cards, data is also collected using technologies that can be employed in combination with or in the hands of a (human) frontline employee at the stationary PoS. The customer and the frontline employee are the ‘key involved actors’ in frontline service encounters (de Keyser et al., 2019). However, the growing multiplicity of technologies at the PoS and the associated variety of technological assistance within face-to-face service interaction (e.g. through digital displays or tablet computers) indicates that in-store sales processes might need to be reconfigured, as they raise further challenges within the dyadic relationship (e.g. Bolton et al., 2018; Ostrom et al., 2015). In addition to the positive effects of technologyoriented services (i.e. increased knowledge, adaptability and flexibility, as well as a perception of individualisation by customers (e.g. Alexander and Kent, 2020; Riegger et al., 2021)), it is also necessary to ensure a positive interplay of interpersonal components between the two parties (Grewal et al., 2020). However, this technology should not act as an obstacle in this social interaction (Giebelhausen et al., 2014).

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The immediate input of the above data could offer the frontline employee new alternatives in the service interaction. Especially when it comes to demonstrating clear arguments for individual service improvement through monetary or service-related benefits, technologies could offer further potential for directvalue creation for the customer. Social interaction theory (Turner, 1988) states that communication depends on the nature of the interpersonal contact; this is significantly influenced by the motivation for or the structure of this interaction between the two parties. In physical retail, interpersonal contact is a necessary occurrence in the context of service encounters (e.g. Solomon et al., 1985) and is highly related to the customer experience (e.g. Bustamante and Rubio, 2017; Locander et al., 2018). However, a differentiated view of technology infusion that considers customers’ willingness to interact socially and potentially disclose data at the physical PoS is missing from the literature. According to privacy calculus theory (Culnan and Armstrong, 1999; Laufer and Wolfe, 1977), an incentive communicated by a salesperson at a PoS might decrease customer concerns related to the provision of personal data in a physical store. It seems to be essential to maintain a balance between how customers perceive costs or concerns and the potential benefits that may result from the disclosure of personal data. Based on privacy calculus theory, we see the integration of a concrete form of incentive (e.g. a monetary discount or service personalisation) being treated as a reward for data disclosure, providing a new stimulus within the frontline service. This leads to a re-evaluation of this service situation (in contrast to situations where no incentive is offered) and results in more complex accounting by customers (Heath and Soll, 1996) in terms of their appreciation of the expected benefits or values held against any potential costs or concerns. When data disclosure takes place in the retail environment, customers’ data protection concerns can come into play. Previous studies have focused on customers’ privacy-related issues within online shopping environments (Bélanger and Crossler, 2011; Smith et al., 2011). However, there is a dearth of literature that investigates this topic in physical retail. In the context of our study, we see customers’ privacy risks and their perception of individual data control as meaningful moderating influences in this relationship. In actual fact, if retailers hope to collect customer data within their stores, they need to ensure that customers feel that their privacy is protected (Acquisti et al., 2015; Martin and Murphy, 2017). Otherwise, certain customers (particularly those who have higher privacy risks or a stricter approach to data control) might withdraw from the service.

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In summary, we analyse how customers’ data disclosure practices vary in the context of the different incentives offered and in response to the infusion of technologies within a physical retail environment. We also consider the role played by customer perception of frontline services (e.g. Keh et al., 2013; Otterbring and Lu, 2018) and examine customers’ attitude towards data-related handling (e.g. Bélanger and Crossler, 2011; Yu et al., 2020). In doing so, we focus on the following research questions: RQ1.

RQ2.

RQ3.

What impact does an incentive in the form of a financial discount or personalisation of the service have compared to no incentive on customer data disclosure and data accuracy (accuracy of the data disclosed) in a frontline service? What moderating effect does the infusion of technological service assistance have with regards to the influence of an incentive on data disclosure and its accuracy? What moderating effect do customers’ overall privacy concerns and data control have with regard to the influence of an incentive on data disclosure and its accuracy?

Based on our findings, we derive implications for future research and for retailers, providing strategies for data collection in physical retail stores. Our recommendations take both incentives and technological assistance into account, emphasising the role of the frontline human employee within the service interaction.

3.8.2

Theoretical Background and Conceptual Framework

Our study focuses on an analysis of the quantity and quality of data disclosure at the physical PoS, examining how this is influenced by the offering of an incentive and the infusion of technology within a frontline service. According to Dinev and Hart (2006) and Smith et al. (2011), privacy calculus theory focuses on the difference between benefits and costs for customers when it comes to the possible disclosure of actual personal data in view of a positive outcome (some kind of motivation or incentive) that has been offered to the customer. Based on previous research, a customer’s individual accounting focuses on behavioural factors that influence the intuition or ‘nature’ of the individual, which is responsible for decisions about sharing or granting privacy in exchange for something of some value (Laufer and Wolf, 1977). It is important that such benefits can be expected, even though the consequences of such a sharing or arrangement are often not clear in advance. We assume that customers’ willingness to disclose

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data at the PoS depends on whether there is an incentive to disclose this data and the kind of incentive that is offered. In contrast to data disclosure in impersonal and anonymous online shopping environments, customer behaviour in physical shops depends on other personal-level influences (Malhotra, Kim and Agarwal, 2004). Research commonly emphasises the positive role of incentives offered by a retailer in getting customers to provide personal data (e.g. Krafft et al., 2017; Premazzi et al., 2010). These incentives are meant to be perceived as personal benefits, and it is assumed that customer incentivisation positively influences both response rate and response quality (Deutskens et al., 2004). Based on the general understanding of social exchange (which is a prerequisite for privacy calculus), customers are interested in a certain trade that involves providing and receiving (Premazzi et al., 2010). The literature shows that customers are willing to disclose personal data when there is the prospect of additional benefits (Dinev et al., 2008; Jiang et al., 2013). Previous research has focused on the several types of incentives that companies might offer their customers in return for providing personal data; these include monetary coupons (Premazzi et al., 2011) and rewards (Xie et al., 2006). Additionally, research has considered how the data provided is used to optimise the purchase process (Thirumalai and Sinha, 2013), to create individualised/personalised advertisements (Bleier and Eisenbeiss, 2015; Pfiffelmann et al., 2019), to design more personalised communication (Krafft et al., 2017) and to create customer-specific website designs (Benlian, 2015). Incentives are used to provide customers with additional benefits and might help to provide them with superior, more efficient services (Martin and Murphy, 2017; White, 2004). If frontline employees provide customers with incentives during interactions, such incentives might act as a cause within a customer’s individual calculus (i.e., their consideration of whether to disclose their data or not). An incentive that is related to future purchases (such as the offering of a monetary discount or of a more personalised service) is especially likely to trigger a customers’ privacy calculus when they are assessing potential benefits and costs; such incentives imply to the customer that some kind of personal data ‘buy-off’ on the retailer’s side has been initiated. This perception of a ‘trade-off’ might then invoke a particular disclosure behaviour (e.g. Karwatzki et al., 2017a). Cost–benefit trade-offs frequently appear in the literature in the context of analysing (data-)exchange relationships. Privacy calculus theory suggests that customers make a cost–benefit assessment before disclosing personal data (Dinev et al., 2008; Jiang et al., 2013). More specifically, customers weigh the cost of a

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loss of privacy against the potential benefits of data disclosure (Dinev and Hart, 2006; Jiang, Heng, and Choi, 2013). A loss of privacy is understood as a central cost driver (Krafft et al., 2017). If the result of the customer’s calculation is ‘positive’ (that is, if the benefits outweigh the costs), there is a general acceptance of privacy loss and thus a willingness to disclose data (Culnan and Bies, 2003; Krafft et al., 2017), and vice versa. Perceptions of costs and benefits are individual and depend on a customer’s own privacy preferences. Consequently, the result of any calculation using these variables varies from customer to customer (Hong and Thong, 2013; Karwatzki et al., 2017a). An evaluation of individuals’ accounting of cost and benefits is a complex psychological process involving many different considerations (Li, 2012); as such, there are additional important factors that should be considered. However, the provision of data is not inevitably connected to its quality. Against other assumptions (e.g. Botosan, 2004), Beretta and Bozzolan (2008) point out that a solo analysis of the amount of data disclosed or the general willingness to disclose personal data is not a valid proxy for this issue. Research shows that a differentiation between disclosures’ quantity and quality is not unusual in the context of a rather private interaction; in the context of social media usage, for example, a gap between those aspects has been identified (Luo and Hancock, 2020). Moreover, it is stated that people’s psychological well-being (including negative/positive emotions, low/high self-esteem, anxiety/satisfaction) has a decisive impact on both the quantity and quality of disclosed data in this relation. Customer incentivisation is supposed to motivate the customer in a shopping context (e.g. Premazzi et al., 2011; Krafft et al., 2017); as such, we understand such a motivation to be the intention to improve customers’ well-being for a short moment. Consequently, post-incentivisation, we expect a clear differentiation in customers’ motivation to disclose a sufficient quality and quantity of data. In this study, we focus on social interaction theory (e.g. Festinger et al., 1950; Turner, 1988) as a means of investigating the influences of technology-infused service encounters at the physical PoS on customers’ data disclosure behaviour. Social interaction theory (Festinger et al., 1950) illustrates the process of interactive behaviour between two parties. Here, communication, feelings or similarities between the parties play an important role. These factors are also the starting point for any motivation of customers by frontline employees, and are what make a social interaction ‘successful’. Furthermore, the structural perception of this process is also relevant to the customers (Turner, 1988). An optimal social interaction therefore involves both parties to the interaction. In other words, it is about the dyadic interaction of action and reaction between

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two parties, which is considered an essential factor in efficient employee service at a physical PoS (e.g. Burkhardt, 1994; Solomon et al., 1985). In physical retail, this social interaction, or the individual components of this interaction between the parties (i.e., motivation, structure), no longer depends solely on the customer and the frontline employee, but can also be significantly influenced by certain service technologies. These technologies may be able to change concrete aspects within such an encounter (e.g. Bolton et al., 2018; de Keyser et al., 2019). Xin et al. (2015), Beatson et al. (2006) and Mende et al. (2019) have been able to show that, when a technology is incorporated into a frontline service encounter, customers’ can react by adjusting their behaviour. In fact, technology is often associated with or the starting point of data collection (i.e., in an online shopping context). We therefore suppose that technology infusion might moderate the relationship between the nature of the incentive and the disclosure of personal data. Specifically, we suppose that the act of mentioning a monetary discount in the presence of a technological adjunct will be perceived as a more understandable/clearer calculation of the discount than if the service employee were to calculate the discount without technological support. If no incentive is provided, the added value of a technological support is not immediately apparent to the customer. This statement also applies if the incentive to disclose data lies in the personalisation of the service, in which case the incentive and the technology could block each other at this point. The incentive signals to the customer that the service would like to take better care of their needs and can better accommodate them on an interpersonal level as soon as more information about them is made available. Consequently, customer behaviour within a social service interaction in which a technology is integrated affects the influence of the incentive alternatives. The basic motivation and structure of a traditional service encounter (Turner, 1988) is therefore changed by the integration of this technology, which can either support the basic social interaction (or the argumentation within this interaction) between the two parties and make it more comprehensible for the customer, or can worsen it. The technology could in fact function as a blockage in or barrier to this interpersonal approach (e.g. Giebelhausen et al., 2014). These counteracting processes could restrict customer data disclosure behaviour. According to Dinev et al. (2013) customers’ disclosure behaviour within a service is particularly connected to customers’ perception of privacy risks and data control. In this relationship, privacy risks are understood to be the perceived risk of opportunistic behaviour by a third party when certain types of data are disclosed (Dinev and Hart, 2006). Data control is understood to be the ability to manage individual data disclosure behaviour, to better assess and weigh up

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situations and decisions and to suppress impulsiveness in disclosure and thus reduce customer vulnerability (Margulis, 2003). In the context of this research, we focus on the general perception of privacy risk and data control in the context of data disclosure, including these factors as moderators. Our research concentrates on the impact of different types of incentivisation on customers’ data disclosure, given the presence (or non-presence) of assistance by a technology service. Based on the role played by technology in a customer’s privacy calculus, we suppose that the infusion of a service technology within a frontline service will moderate the assumed relationship between incentives and the likelihood of data disclosure. Specifically, the combination/moderation of incentivisation and the direct integration of a digital device might lead to a general adjustment of customers’ actions. In addition, we add customers’ privacy risks and data control (Dinev et al., 2013) as moderating influences. Our research model is presented in Figure 3.15.

Experimental Factors

Moderator Technology Infusion NOT PRESENT vs. PRESENT

DATA DISCLOSURE within the frontline service

Type of Incentivisation NO INCENTIVE vs. INCENTIVE of MONETARY DISCOUNT vs. INCENTIVE of SERVICE PERSONALISATION

Dependent Variables

Moderator Customers’ Privacy Risk

Moderator Customers’ Overall Data Control

DATA ACCURACY within the frontline service

Figure 3.15 Research Model for Essay 8

3.8.3

Hypotheses Development

The Influence of the Type of Incentive on Customers’ Data Disclosure Incentives are designed to support specific types of customer behaviour, even lowering customers’ perception of the cost of data disclosure (White et al., 2014). The integration of an incentive within a frontline service might result in a more complex customer accounting process regarding data disclosure–related costs and benefits (e.g. Heath and Soll, 1996). Incentives provide reinforcement that influences a given situation. In this context, privacy calculus theory helps to understand customers’ overall accounting when disclosing or exchanging personal data (Laufer and Wolfe, 1977). We transfer this effect to the context of data disclosure in brick-and-mortar retail shops;

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that is, offering incentives triggers a more intensive weighing of the customers’ perceived benefits against the respected costs. We assume that, if an incentive is present, this weighing leads to the customer realising what added value the disclosure of data actually has. In such a situation, data disclosure is more likely to take place in than it is if no incentive is present. Research shows that monetary incentives, in particular, seem to trigger customers’ intentions to disclose personal data in comparison to situations where no incentive is offered (Hui et al., 2013; Premazzi et al., 2010). Contrasting it to a monetary incentive, we question the relevance of a non-monetary buy-off of personal data; that is, the effect of customers’ calculus of the benefit of a product-to-customer orientated incentive at the PoS that would result in a more personalised service in future (Pfiffelmann et al., 2019). As the result of such an incentive, customers may see a more direct integration of their data into the retailer’s process. This is somewhat different to the simple exchange of money for data, in which the financial advantage plays the upstream role and the data use and processing by the retailer takes a back seat or is overshadowed by the incentive. If there is an incentive for a more personalised service, however, the customer is immediately informed that the data disclosed will be transferred to retailers’ internal data processing systems. It can be assumed that this incentive results in less data disclosure by the customer than the monetary incentive would. Moreover, an incentive for a personalised service is more effective than no incentive at all: H1:

An incentive (versus no incentive) will increase (decrease) customers’ data disclosure.

The Influence of the Type of Incentive on Customers’ Data Accuracy Although we argue that retailers ‘buy’ personal data from customers through incentivisation, we likewise assume that this approach does not necessarily imply that customers are also willing to provide this data in a detailed or completely accurate manner (Alashoor et al., 2017). We suppose that, while incentive reasoning leads to an increase in overall data disclosure behaviour, data accuracy (meaning the quality or richness of the disclosed data) decreases. The customer is willing to accept the corresponding benefit in return for their data, but reserves the right to consent to the exchange process only at a superficial level. Such behaviour allows the merchant to increase the amount of data it holds, but little inference about the customer’s person is gained. We assume that, in terms of the privacy calculus (Li et al., 2011), the customer’s calculation involves two steps, as follows. Before the actual decision

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to disclose data, the question of willingness to disclose personal data rich is answered ‘internally’. It can be assumed that it is at this point that the most important step in the calculation of the quality of the potentially disclosed data is taken; from this, any further decisions on the quantity of data are then derived. This weighing of the costs (use of the actual data by the dealer) and increase in benefit (charging of the data to an adequate monetary or service-oriented bonus) are to be understood, consequently, as primary accounting. The amount or quantity of data provided is therefore ‘only’ the result of the weighting. Specifically, we assume that, while incentives do not lead to a higher data accuracy, the customer recognises the buying-off of the data as such, allowing more intensive accounting to take place (White et al., 2014). The result will be the disclosure of less-rich data when an incentive exists, compared to the situation when no incentive is offered: H2:

An incentive (vs. no incentive) will decrease (increase) customers’ data accuracy within the frontline service.

The Moderating Impact of Technology Infusion According to the literature, the type of technology used to collect personal data affects customers’ data disclosure practices (Milne et al., 2012). Findings by Giebelhausen et al. (2014) indicate that in-store technologies do not necessarily benefit customers, because they might hinder the customer–employee relationship. This is especially true when personal data is collected directly by the service employee with a digital device during the in-store service process; that is, digital technologies might disturb the frontline service in terms of the transfer of service-related data. According to social interaction theory, the interaction process contains different constituent properties (Turner, 1988). We assume that, in the context of a service encounter in which possible data disclosure by the customer plays a role, the motivation behind and structure of the service encounter are of particular importance. This is especially true if an incentive is to incrementally influence the customer’s data disclosure behaviour within the interaction. The integration of a technology can cause customers to re-evaluate the service situation. They can see that the basic structure of the service has been changed and that data is no longer only recorded by the advisor, but can be directly typed into the technology. The incentive offered may then influence the customers’ motivation differently, depending on whether or not the technology supports this from the customers’ point of view. Specifically, the use of this technology might lead to a reduction in the amount and accuracy of data provided by customers, particularly when the

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incentive of a more personalised services is offered, as customers find it difficult to understand the benefit of technology in this relationship. In the case of an incentive via a monetary discount, we assume a reverse effect; that is, the benefits exceed the costs. This is because the technology could be perceived as a specific instrument that generates and/or calculates the resulting value for the customer, depending on the data disclosed. From a customer perspective, a possible discount on certain products could be seen as being more directly traceable, leading to higher data disclosure and accuracy at this point. This is analogous to the case of an incentive of service personalisation, in that, in terms of no incentive, we suppose that a decrease in data disclosure and accuracy will occur: H3:

Technology infusion within the frontline service moderates the hypothesised relationship between an incentive (vs. no incentive) and a) customers’ data disclosure within the frontline service positively and b) customers’ data accuracy within the frontline service negatively.

The Moderating Impact of Customers’ Privacy Risks In addition to privacy risks being an important component related to the potential disclosure of personal data (e.g. Dinev et al., 2013; Krasnova et al., 2009), they have also been described as a possible consequence of withholding data from disclosure (Petronio, 2002). According to privacy calculus theory, customers tend to stop making rational decisions in situations where the benefits provided may outweigh the potential costs; this is especially true of customers who have lower privacy risk perceptions. Specifically, central elements of privacy risks such as the potential of unauthorised access or secondary use (Culnan and Armstrong, 1999) could recede into the background with these customers, as those risks are downstream of processes or costs. It is important to understand that customers might misjudge or underestimate risks when presented with different motivational incentives (Radcliffe and Klein, 2002), potentially leading to the irrational disclosure of personal information. As a consequence, we argue that, when an incentive is incorporated, decisions made by customers with lower privacy risks are more impulsive and less thoughtful. We therefore hypothesise a lower degree of balancing that leads to an overweighting of benefits over costs and increased data disclosure in terms of both quantity and accuracy: H4:

Customers’ perceived privacy risks moderate the hypothesised relationship between an incentive (vs. no incentive) and a) customers’ data disclosure within the frontline service or b) customers’ data accuracy within the frontline service.

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The Moderating Impact of Customers’ Data Control According to Olivero and Lunt (2004), data control is considered by customers to be a key prerequisite for data disclosure. Mothersbaugh et al. (2012) show that a customer’s data control can be classified as the ability that ultimately determines whether certain personal data is disclosed with a view to individual’s expected use. Consequently, when customers decide for or against the disclosure of data, the customer’s own personal control (i.e., their ability to deal with different motivational incentives and to classify them correctly for themselves) plays an important role (e.g. McCarthy and Casey, 2008). This classification depends, of course, on previous experiences (e.g. Earp and Baumer, 2003) and results from the individual evaluation of the costs and of the potential added value to be expected within a certain situation. These assumptions are therefore strongly associated with the explanations by the privacy calculus theory. Through this association, we assume that, for a given incentive, customers with a higher level of data control will have a higher level of data disclosure and higher data accuracy, because their internal accounting of the benefit or cost of disclosure is more intensive: H5:

3.8.4

Customers’ overall data control moderates the hypothesised relationship between an incentive (vs. no incentive) and a) customers’ data disclosure within the frontline service or b) customers’ data accuracy within the frontline service.

Methodology

3.8.4.1 Procedure and Stimuli Design We tested our hypotheses in a three (Type of Incentivisation: no incentive vs. incentive of monetary discount vs. incentive of service personalisation) x two (technology infusion: not present vs. present) between-subject experimental design. We used a scenario technique to manipulate the different type of incentivisation, integrating one of the three incentive conditions. Our argument is that, according to privacy calculus theory, an incentive makes the customer realise that some kind of exchange process is happening between them and the retailer: incentive vs. data (resulting in a benefit–cost trade-off). We also propose that mention of a concrete equivalent for potentially shared data induces the customer to calculate the benefits of the respective incentive versus the underlying costs of disclosure. Where no incentive is offered, this calculus is assumed to be less intense.

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For our study, we chose images from an electronics market; this store format is generally well-known, and these stores’ products usually need a certain amount of explanation, as this area is generally highly innovative, with more new products developed and launched than in some other areas (Im et al., 2007). Within the experimental conditions, the participants were asked to picture themselves at a physical retailer. Afterwards, each subject was shown one of two experimental scenarios (Figure 3.16). In one image, the frontline employee was shown holding a paper-and-pencil clipboard (no technology infusion condition); in the other, he is shown holding a tablet computer (technology infusion condition). In addition to the images, we presented a text that explicitly emphasised the form of technological infusion used and pointed out the respective incentive conditions. Monetary discount and service personalisation were orientated according to the approaches taken in the current literature (e.g. Premazzi et al., 2010). We used the same phrase as that used by Premazzi et al. (2010) and added two additional aspects to account for the respective incentives: • Incentive of a monetary discount: (1) Depending on the quality and quantity of the data you provide, there is immediate financial added value for you with every purchase. (2) This monetary discount applies to both the sales area and the online store. • Incentive of service personalisation: (1) Your data will be used to optimise individual services at the store. (2) By providing your data, you will benefit from personalised and individual offers.

Figure 3.16 Experimental Design (Technology infusion: Not Present (Paper & Pencil) vs. Present (Tablet Computer))

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3.8.4.2 Measurements, Subjects and Manipulation Check In the online experiment, respondents were randomly assigned to one of the experimental conditions, following which they were asked to complete a corresponding questionnaire. The included constructs are presented in Table 3.31. To obtain the construct values, the indicator values per construct were mean aggregated. The questionnaire was subjected to a pre-test (91 respondents) to confirm the respondents’ ability to understand the questions, the clarity of the items and the specific manipulations incorporated in the tests. Based on the results, minor changes in wording were made. For the attention check, we checked whether all participants understood the central factors concerning 1) the type of provided (or not provided) incentive and 2) the presented (or not presented) technology infusion. We asked the participants yes/no questions to confirm whether they understood the presented incentive as a general benefit within the service encounter (‘In exchange for my data, I receive an individually perceived benefit of a monetary discount from the retailer’, and ‘In exchange for my data, I receive an individually perceived benefit of a more personalised service from the retailer’). Based on privacy calculus theory, we assumed that, given an incentivisation, customers are increasingly likely to calculate a balance between the potential benefits and costs of disclosing personal data. Referring to Kim et al. (2008), we asked the respondents for their perception of a mentioned benefit within the specific service encounter (Mno_incentive = 3.36 (1.11), Mmonetary_discount = 3.83 (1.34), Mservice_personalisation = 3.77 (1.36); F(1, 359) = 4.68). Following Dinev and Hart (2005) we adapted privacy concerns concerning data-handling by the retailer (four items; measured on a 7-point Likert scale: ‘I am concerned that other companies might find the data that I disclose within this service interaction’; ‘I am concerned that the data I provide to the retailer within this service interaction could be misused by the retailer’; ‘I am concerned that the data I provide to the retailer within this service interaction may be used in ways I cannot foresee’; ‘It worries me that I do not know what others might do with the data I give to the retailer within this service interaction’; α = 0.923). The manipulation was perceived correctly by the participants ((Mno_incentive = 4.55 (1.35), Mmonetary_discount = 4.98 (1.45), Mservice_personalisation = 5.17 (1.39); F(1, 359) = 5.98)). Tukey’s post-hoc testing shows significant difference between the non-incentive condition and both incentive conditions (p < 0.05); however, no difference is seen between the incentive conditions themselves. An increase in benefits and costs/privacy concerns towards the retailer’s data-handling practices when an incentivisation is present, can be identified.

Scale

Premazzi et al. (2010) / Milne et al. (2012). Extended on the base of two expert interviews with local retailers

Alashoor et al. (2017)

Source

Data disclosure within the frontline service

Data accuracy within the frontline service

(continued)

Please specify the extent to which you would falsify some of the personal data given to a frontline service if it would be used for big data analysis within the next three years.

7-point Likert scale (1 = to no Please specify the extent to extent—7 = to a very high which you would falsify some extent) of the personal data given to a frontline service if it would be asked for by third parties within the next three years.

Last product purchased

Favourite colour

Leisure activities

Price of last product purchased

Position in the company

Occupation

Telephone number

0.845

0.811

Date of birth

α

7-point Likert scale (1 = unwilling and 7 = highly willing) Email address

Item adaptation

Table 3.31 Constructs, Sources, Scales, Item Adaptation and Cronbach’s Alpha

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Scale

Dinev et al. (2013)

Source

Customers’ privacy risk

Table 3.31 (continued)

7-point Likert scale (1 = totally disagree—7 = totally agree)

Item adaptation

α

Personal data could be inappropriately used by third parties. (continued)

There would be high potential for privacy loss associated with giving personal data to third parties.

In general, it would be risky to 0.956 give personal data to third parties.

Please specify the extent to which you would refuse to give personal data within the frontline service if it would be used for big data analysis, because you think it is too personal for the next three years.

Please specify the extent to which you would refuse to give personal data to a frontline service, because you think it is too personal for the next three years.

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Customers’ overall data control

Source

Table 3.31 (continued)

Scale

7-point Likert scale (1 = I totally disagree—7 = I totally agree)

Item adaptation

I believe I can control the amount/content of personal data I provide to third parties.

I believe I have control over what personal data is collected by third parties.

I believe I have control over how personal data is used by third parties.

I think I have control over what personal data is released to third parties.

Providing third parties with my personal data would result in many unexpected problems. 0.872

α

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By applying Fornell and Larcker’s (1981) criterion, we assessed all reflective scales for discriminant validity. As a result, none of the used constructs shares more variance with any other construct but with its own indicators (Table 3.32). Table 3.32 Results of Correlation Matrix and Discriminant Validity for Essay 8 Mean (SD)

DA

PR

DA

2.51 (1.15)

0.689

–0.152

DC 0.229

PR

3.85 (1.47)

0.023

0.885

–0.126

DC

3.99 (1.68)

0.052

0.016

0.723

Note: SD = standard deviation; DA = data accuracy within the frontline service; PR = customers’ privacy risk; DC = customers’ overall data control. Diagonal shows the average variance extracted (AVE); values below the diagonal are the square correlations; values above diagonal are the normal correlations

Again using a yes/no question, we checked what kind of additional service assistance (paper and pencil or tablet computer) was integrated within the images. In total, 362 participants (54.42% female) with an average age of 29.98 (SD = 12.02) years participated in the main study. The participants were distributed between the types of incentivisation (no incentive: N = 111; monetary discount incentive: N = 129; service personalisation incentive: N = 122) and technology infusion (not presented: N = 180; presented: N = 182). Finally, between the respondents for the two experimental conditions (both types of incentivisation and technology infusion) we controlled for customers’ privacy risks (type of incentivisation: (F(1, 359) = 0.38; technology infusion: F(1, 360) = 0.99)), customers’ overall data control (type of incentivisation: (F(1, 359) = 0.63; technology infusion: F(1, 360) = 1.00)), and technological affinity (type of incentivisation: (F(1, 359) = 0.38; technology infusion: F(1, 360) = 1.05)). Overall, we did not find any systematic distortion in our treatment.

3.8.5

Results

To test the H1 hypothesis, we used a MANOVA test (Table 3.33). A monetary discount incentive seems to be the most effective at motivating customers’ actual data disclosure (Mno_incentive = 3.79 (1.13), Mmonetary_discount = 4.10 (1.20), Mservice_personalisation = 3.54 (1.27)). Tukey’s post-hoc analysis emphasises the significance of this finding in comparison to that of the no incentive condition (t < 0.05). Regarding the presence or absence of service

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Table 3.33 Results of MANOVA testing of the dependent variables Technology Type of Incentivisation (ToI) Infusion No Incentive: Incentive: F-value (η2 ) (TI) incentive monetary service (control discount personalisation group) M (SD)

M (SD)

M (SD)

ToI

3.88 (1.22)

3.96 (1.22)

3.81 (1.27)

6.804** 1.415 3.623* (0.037) (0.004) (0.020)

3.71 (1.04)

4.23 (1.18)

3.27 (1.21)

not present

2.81 (1.20)

2.52 (0.99)

2.54 (1.13)

present

2.71 (1.10)

2.37 (1.23)

2.26 (1.16)

Data Not present Disclosure within the present Frontline Service Data Accuracy within the Frontline Service

3.847* (0.021)

TI

ToI x TI

1.570 0.341 (0.004) (0.002)

Note: A between-subjects design was used. Data disclosure within the frontline service to the frontline employee was measured according to Milne et al. (2012), using a 7-point scale (1 = totally disagree—7 = totally agree); Data accuracy within the frontline service was measured according to Alashoor et al. (2017). M: mean; SD: standard deviation; Sig.: *p < 0.05, **p < 0.01

personalisation and monetary discount incentive, no significant difference can be produced; consequently, H1 is only partially supported. However, focusing on the sub-group (in which technology is infused), Tukey’s post-hoc analysis shows a significant difference between a monetary discount and the no incentive condition (p < 0.05) compared to service personalisation incentive (p < 0.001). As we used a male frontline employee within our image, we also checked for any gender effect on H1. The results indicate that the respondents’ gender does not have any effect (no incentive (control-group): Mfemale = 3.72 (1.02), Mmale = 3.88 (1.26); F(1, 109) = 0.51, p > 0.05, η2 = 0.005; incentive: monetary discount: Mfemale = 4.04 (1.19), Mmale = 4.16 (1.23); F(1, 127) = 0.57, p > 0.05, η2 = 0.003; incentive: service personalisation: Mfemale = 3.61 (1.19), Mmale = 3.46 (1.36); F(1, 120) = 0.49, p > 0.05, η2 = 0.004). To analyse whether the introduction of a tablet computer as the technology infusion has the expected effect on the relationship between the type of customer incentivisation and data disclosure, we included the presence of the technology as an independent variable in form of a dummy coding within the ANOVA. In

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this way, we could identify a significant interaction effect between of the type of incentivisation and the technology infusion; specifically, monetary discount and service personalisation means show in an opposite direction. That is, whereas the infusion of technology paired with a monetary incentive increases data disclosure, such an infusion paired with service personalisation has the opposite effect. Tukey’s post-hoc analysis shows a significant difference between monetary discount and service personalisation (p < 0.001) as well as between monetary discount and no incentive (p < 0.05). Overall, therefore, H3a is supported. Again, no gender effect could be determined (no technology infusion: Mfemale = 3.92 (1.18), Mmale = 3.83 (1.30); F(1, 178) = 0.23, p > 0.05, η2 = 0.001; technology infusion: Mfemale = 3.67 (1.70), Mmale = 3.83 (1.33); F(1, 180) = 0.78, p > 0.05, η2 = 0.004). With regard to customers’ data accuracy within the frontline service, the findings support our hypothesis regarding a significant difference resulting from the type of incentivisation (Mno_incentive = 2.76 (1.15), Mmonetary_discount = 2.39 (1.11), Mservice_personalisation = 2.40 (1.15)). Tukey’s post-hoc analyses on the difference between no incentive condition paired with monetary discount and no incentive condition paired with personalised service emphasises the significance of these results (p < 0.05). It can be shown that the no-incentive condition produces the highest score; given an incentive, especially a monetary discount, the findings indicate that customers will disclose more data. Customers do not seem to care whether or not the data they provide is accurate, as long as a financial benefit results. A personalised service results in a lower level of data disclosure and an analogously lower level of data accuracy. Overall, it appears that an incentive does not increase customers’ accuracy in a physical retail environment. Customers’ might understand that such incentives are an exchange-offer for their data, leading to an increase in reluctance to part with their personal information. Moreover, it appears that the infusion of technology does not produce any interaction effect in this case. Consequently, H2 can be supported, but H3b cannot. Again, no gender effect can be found within the data with regards to the incentive (no incentive (control-group): Mfemale = 2.74 (1.17), Mmale = 2.78 (1.12); F(1, 109) = 0.04, p > 0.05, η2 = 0.000; incentive: monetary discount: Mfemale = 2.48 (1.04), Mmale = 2.29 (1.20); F(1, 127) = 0.93, p > 0.05, η2 = 0.007; incentive: service personalisation: Mfemale = 2.33 (0.97), Mmale = 2.49 (1.32); F(1, 120) = 0.45, p > 0.05, η2 = 0.005) or the technology infusion (no technology infusion: Mfemale = 2.67 (1.13), Mmale = 2.46 (1.08); F(1, 178) = 1.62, p > 0.05, η2 = 0.009; technology infusion: Mfemale = 2.34 (0.98), Mmale = 2.54 (1.36); F(1, 180) = 1.29, p > 0.05, η2 = 0.007).

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We used PROCESS model 1 to examine the moderating influence of customers’ privacy risks and data control. Figure 3.17 depicts the resulting moderating analyses. By including customers’ overall privacy risks, we were able to produce a significant level of variance with regard to data disclosure (R2 = 0.156) in terms of no incentive vs monetary discount (βtype_of_incentivisation_x_privacy risks = –0.305; p < 0.001) and no incentive vs. personalised service (βtype_of_incentivisation_x_privacy risks = –0.292; p < 0.01). Results indicate that customers’ privacy risks moderate the influence of both types of incentivisation on customers’ data disclosure. The level of data control does not produce any moderating effect with respect to data disclosure. Regarding data accuracy, the moderating influence of customers’ level of privacy risk in response to no incentive vs. monetary discount can be generated (βtype_of_incentivisation_x_privacy risks = –0.292; p < 0.01; R2 = 0.038). With respect to the inclusion of data control, a significant level of variance exists in response to no incentive vs. personalised service results (βtype_of_incentivisation_x_data_control = 0.245; p < 0.05; R2 = 0.076). In summary, H4a can totally be supported, while H4b and H5b can be partially supported. The results give no empirical support for H5a, however.

3.8.6

General Discussion and Implications for Management

Our research supports the general understanding of privacy calculus theory. We can show that offering (as opposed to not offering) an incentive in physical retail can stimulate data sharing by customers. It appears that these impetuses trigger a reassessment of the service situation and a reassessment of the trade-offs between the costs and benefits of data disclosure among customers (Heath and Soll, 1996). These findings broadly coincide with studies by Culnan and Bies (2003) and Krafft et al. (2017), according to which data is only made available after an internal calculation of perceived benefits (perceived service-oriented benefits in the form of an incentive) and perceived costs (e.g. privacy concerns about data processing by the retailer). Consistent with the first research question, we can emphasise that physical retail customers seem to calculate differently between incentives (in the form of monetary benefit and personalised service) and the potential costs resulting from their behaviour. However, the question also shows that, contrary to popular belief, not offering an incentive does not seem to be the worst solution for the retailer. While an incentive in the form of a monetary rebate generates the highest willingness to disclose data (Premazzi et al., 2010), an incentive in the form of a personalised service leads to even lower

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Data Disclosure within the Frontline Service 5.00 4.50 4.00 3.50 3.00 2.50 low

middle

high

low

level of privacy risks

middle

high

level of data control

no incenve

monetary discount

service personalisaon

Data Accuracy within the Frontline Service 3.50

3.00

2.50

2.00

1.50 low

middle

low

high

level of privacy risks no incenve

middle

high

level of data control monetary discount

service personalisaon

Figure 3.17 Moderating Influences of Customers’ Privacy Risks and Data Control on the Dependent Variables

data-disclosure behaviour than when no incentive is communicated. In fact, the approach of a data buy-off seems to be attractive to the customer only if a possible immediate benefit, in the form of a monetary discount, is offered. The service-oriented integration of the data, on the other hand, seems less tangible to customers and is therefore not understood as an adequate object of exchange by the dealer. In addition, we were able to show that customer disclosure intent and customer disclosure accuracy are two different things. The results give us reason to assume that customers’ calculations work on two levels. That is, compared to the exchange ratio in terms of overall data-disclosure readiness, the results for the accuracy of the data disclosed are somewhat different when taken against

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incentive levels. Customers seem to be revealing data, especially when it comes to monetary discounts, but the data they provide is not necessarily accurate. According to research question two, we examined the interplay between technology infusion and incentive setting in the context of understanding customer data disclosure. We have shown that, on the one hand, the willingness to disclose in response to an offering of service personalisation decreases when technology is introduced (analogous to the non-incentive condition); on the other hand, however, willingness increases when a monetary discount is on offer. These results extend the findings by Premazzi et al. (2010) and Hui et al. (2007), as it appears that the infusion of technology triggers a different processing intensity in the customer. From the above, it can be concluded that the infusion of technology appears to be a factor for the customer when it comes to ‘calculating’, from the dealer side, the appropriate financial rebate resulting from the customer’s data disclosure. In the absence of technology, this ‘calculation’ could be left to the employee and their personal feelings alone, which could ultimately lead to less precise or less objective added financial value for the customer. In comparison, technology could be understood to be a disruptive element in regards to incentives for service personalisation, since contact with the service employee could decrease or be perceived as being blocked by technology (e.g. Giebelhausen et al., 2014). The frontline employee, therefore, still seems to play a very important and influencing role when it comes to customers’ willingness to disclose their data to a retailer. It can be concluded that this finding is related to customers’ perception that a personalised service within brick-and-mortar retail is strongly linked to actual interaction with a human frontline employee and cannot be ‘enforced’ via a data exchange. Even if a certain technology can provide additional information on a product or service, the sharing and collection of data through such technology in this context is not necessarily seen as a benefit from a customer perspective. These findings can be understood in line with social interaction theory (Turner, 1988), as we can identify adjustments in customers’ behaviour in regard to the specific incentive when a technology is infused. We could conclude that customers seem to recognise the actual value of a monetary incentive offered, or that it becomes more calculable for them, particularly through the infusion of technology. Customers could assume that, with the help of technology and a possibly integrated algorithm, the monetary value offered will be calculated impartially. Consequently, combining technology with a monetary incentive appears to be a useful way to generate more data. However, we must also point out that the integration of technologies is challenging, based on our results, and that there are other factors to consider (Piotrowicz and Cuthbertson, 2014).

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Regarding research question three, the moderating analysis shows the clear effect of customer privacy risks in relation to data disclosure, but none in relation to customer data control. A high level of privacy risk is shown to reduce customer data disclosure to a greater extent in the presence of each of the two inducements, compared to in the no-incentive condition. However, it can be shown that an incentive (particularly a monetary rebate) results in higher data disclosure within the low-data-protection risk group. Setting an incentive seems to trigger these customers’ disclosure behaviour very strongly, while the value without an incentive condition remains almost stable, regardless of whether customers have a high or a low level of data protection risk perception overall. In terms of data accuracy, a high privacy risk leads to a significantly larger decrease in data disclosure behaviour. This is especially the case for a monetary rebate as opposed to the (again) only slightly decreasing value in the presence of no incentive. Similar results can be presented with regard to customers’ data control, with the personalised service having a significantly lower data accuracy offered by the group with low data control and a much higher value offered by the group with high data control, in contrast to the accuracy associated with the incentive-free condition. In summary, the integration of an incentive appeals to customers differently; however, it should be noted this diversity is again modified by the level of fundamental data protection risks and data control that customers carry with them. A primary takeaway for marketing researchers and practitioners, therefore, is that incentives do not necessarily induce customers to share data and information. Crucially, the accuracy of the data can drop significantly when different incentive options are included. Retailers need to be mindful of how and to what extent such an incentive is communicated in the data collection objective. Since monetary discounts (in particular), customer benefit and cost billing seem to follow different patterns, retailers need to integrate this knowledge into their processes and convey these aspects via qualification programmes for frontline employees. Furthermore, our results imply that the use of technology under the right circumstances (e.g. in the presence of a certain incentive) is currently a potential key to a successful frontline service that aims to generate customer data. The intelligent use of incentives (particularly cash rebates), combined with the introduction of technology into frontline services, appears to help increase data disclosure. Although Giebelhausen et al. (2014) found that building a (face-to-face) relationship between customers and frontline services can degrade customer perceptions by embedding frontline service technology, our results imply that monetary rebate incentives, in particular, increase the likelihood of data disclosure. However, the question that needs to be addressed by following studies is how to increase both the quantity and the quality of the data offered.

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Limitations and Implications for Further Research

Our study comes with a number of limitations. We used an experimental approach, using an online study with specifically created scenarios, and tried to control all possible disruptive factors within a retail store. Actual interaction at the PoS includes an interplay of demands and reactions between the frontline employee and the customer. As such, we were not able to include such complex interactions and focused on the specific types of incentivisation on offer. Moreover, we manipulated the infusion of technology, as we only concentrated on one specific item: a tablet computer. We also did not explain the service encounter itself or the functionality of the technology to the respondents. In retail practice, there are numerous other technologies that can be used with the idea of affecting the social perception of the frontline service encounter (de Keyser et al., 2019; Grewal et al., 2020). To reduce complexity, we did not consider any of the frontline employee’s personal characteristics. In our studies, we only included a male frontline employee. Further studies need checked the gender effect with regard to a male and a female frontline employee. Gender congruency effects might be found to be a factor affecting data disclosure and accuracy (e.g. Snipes et al., 2006). Our study highlights important implications for future research into the impact of incentives in physical retail contexts. Attention should be paid to the mechanism and psychological phenomena affecting a customer decision as to whether to disclose more and/or accurate data. Our study delivers an initial explanation for this process; however, more in-depth analysis should be undertaken in order to create a step-by-step understanding of customers’ accounting, from receiving an incentive until deciding on whether to disclose personal data, both quantitative and qualitative. A customer’s individual privacy calculus, including an accounting of the benefits and costs of data disclosure, seems to be a fragile issue, the balance of which is highly complex. As such, it would (especially as it relates to customers’ inherent and underlying processes) benefit from further research. In addition to the relevance of customers’ data disclosure and data accuracy, literature shows that customers’ decision-making processes are influenced by other factors. We were not able to integrate these into our study, but they would benefit from additional research. For example, the perception of the physical attractiveness of the service employee (Söderlund and Julander, 2009) is regarded as important, as studies have shown that attractive persons are judged and treated more positively with respect to their behaviours and traits than unattractive persons are (Villi and Koc, 2018). One could assume that, due to a potential increase in service quality, a positive evaluation of frontline employees’ attractiveness

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might reduce customers’ privacy concerns (however, a reverse effect is also conceivable). It might also be worth considering whether gender congruence plays a role. In addition, a deeper analysis of the effects of (customer–)gender influence, particularly on customers’ data accuracy, might lead to further fruitful insights, as a general difference in frontline services’ perception regarding male vs. female customers has already been shown (Mattila et al., 2003). Our study was limited to a single product category and one retail sector; research has shown that different product categories might affect customer behaviour in different ways (Dhar and Wertenbroch, 2000). Therefore, future research needs to investigate how the identified factors affect different product categories. In addition, customer perception of different price structures might be also related to potential data disclosure (Schmidt et al., 2020). We conducted our study in Germany; prior research has shown several important differences with respect to personal characteristics (e.g. age, culture and education) and general customer behaviour in various countries and cultures (Miltgen and Peyrat-Guillard, 2014). Therefore, cross-cultural studies could provide additional insights into how the use of incentives could be adjusted according to customers’ cultural or even ethnic backgrounds (Luoh and Tsaur, 2009).

4

Discussion and Implication

4.1

An Extended Perspective on Technology-Oriented Customer Touchpoints

With regard to the dissertations’ key objective (1), new light was shed on the common understanding of the benefits and limitations of technology-oriented customer touchpoints in customer–service–technology interactions. Three levels (service-, product- and data-related variables) were derived from the variables used in the eight studies, as shown in Table 4.1. Table 4.1 Overview of the integrated main variables in the eight essays Essay

1

2

Theoretical Orientation

−

Social Presence

3

4

Privacy Calculus

5

6

Social Presence &

7

8

Main Variables

Service-related Variables

x

x

x

x

x

x

x

x

Product-related Variables

−

x

−

x

x

−

−

−

Data-related Variables

−

−

x

x

x

x

x

x

Privacy Calculus

Essay 1 was the starting point for further studies, while essays 2 to 8 focused on at least two of the three main variables. Given the potential of unique service interactions with reference to social presence and the privacy calculus, Table 4.1 shows that the essays in this dissertation covered a significant number of combinations of product- and data-related variables with some type of © The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2023 T. Röding, Technology-Oriented Customer Touchpoints in Context of Services in Retailing, Handel und Internationales Marketing Retailing and International Marketing, https://doi.org/10.1007/978-3-658-40554-0_4

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concern about the service. In particular, the service-related variables can help improve the understanding of a customer’s view of a service encounter. Nine service-related factors were systematically manipulated in six experimental essays (2, 3, 4, 6, 7 and 8). In addition, essay 5 used 4 service-related independent variables. In articles 1–8, 21 service-, product- or data-related variables were included as dependent variables. In addition, 11 service- or datarelated variables were used to examine the moderating or mediating influences in these relationships. An overview is shown in Table 4.2. Table 4.2 Overview of the independent and dependent variables in the eight essays Essay

Manipulation/Independent Variables

Moderating or Mediating Variables

Dependent Variables

1

−

−

Ease of Understanding Intuitive Operation Functional Fit-to-Task Information Quality Tailored Information Innovativeness Perceived Enjoyment

2

3

4

Type of Technology Infusion Perceived Service in the Service Competence of the (technology-free vs Frontline Employee technology-facilitated vs technology-assisted)

Trust towards the Frontline Employee

Presence of a Human Frontline Service Employee in a Technology-based Service (not present vs present)

Discomfort regarding the Service

(expected) Information Quality in the Service

Perceived Social Presence in the Service

Privacy Concerns related to Retailer’s Data-Handling Practices

Level of Information Transparency of Data Use and Handling (low vs medium vs high)

Privacy Concerns

Purchase Intention

Trust in the Service Provider

Willingness to Pay

Willingness to Pay

(continued)

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Table 4.2 (continued) Essay

Manipulation/Independent Variables

5

Trust in the CEP Provider’s − IT Infrastructure Concerns about Data Misuse related to the CEP Provider’s Data ManagementPerceived Environmental Sustainability of the Delivery Process Perceived Work–Life Flexibility resulting from the Delivery Process Income

Intention to Provide Digitally Transferred Access Permission

6

Level of Anthropomorphism − (high vs low) Age Similarity (high vs middle vs low) Gender Congruency (with vs without)

Willingness to Interact (Service-related and Interpersonal-Related)

Level of Technology Infusion of the PoS Service (non-technology-infused service vs technology-infused frontline employee service vs self-service technology)

Information Disclosure

7

Moderating or Mediating Variables

Privacy Concerns

Dependent Variables

Willingness to Disclose (Overall and Accuracy)

Perceived benefit of Information Disclosure at the PoS Emotions experienced (pleasure, arousal and dominance) Perceived Trust in the Retailer’s Use of the Disclosed Data

8

Type of Incentivisation (no Privacy Risks incentive vs with incentive, monetary discount vs service Data Control personalisation)

Data Disclosure in the Frontline Service Data Accuracy in the Frontline Service

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4

Discussion and Implication

With regard to the service-related variables, in addition to the customer’s direct perception of the services or the employees at the frontline (e.g. perceived benefit or service competence), the customer’s reactions to these services (e.g. trust, privacy concerns or experienced emotions) were determined as the primary service-related variables. Customer privacy concerns or privacy risks arising from the potential disclosure of personal data were also classified as service-related influences in this work. These concerns were related to the concerns about data mismanagement, but they also carried over to other areas of the service and reflected a broader picture of the individual’s concerns during a service encounter. Service-related variables for examining customer perception and reactions were integrated as mediating, moderating and dependent variables, whereas product-related variables were primarily used as dependent variables. Data- and service-related variables, such as the above-mentioned privacy concerns of customers, privacy risks or the data control function were also integrated into the analyses as moderation variables (essays 4, 5, 7 and 8). The product-related variables included all customer actions, such as the willingness to pay (essay 2), intention to buy and willingness to pay (essay 4) and intention to issue a digitally transmitted access authorisation (essay five). As for the data-related variables, the willingness of customers to disclose/provide personal data/information in certain situations was discussed (essays 6, 7 and 8). Essay 1 was the starting point for all further studies. In it, PoS technologies were first classified based on seven service-oriented variables. Within this categorisation, three additional categories of PoS technologies were identified: (A) comprehensible PoS technologies, (B) information-integrated PoS technologies and (C) entertainment-related PoS technologies. The distinction among these three categories offered an understanding of the customer’s perception of these PoS technologies. As part of an in-depth property fitting analysis, it was also found that cluster A had a lower degree of complexity, while cluster C had a higher degree of innovativeness. However, it was apparent that customers have become more and more intuitive and habitual in the use of such technologies (Alexander and Kent, 2020). Consequently, the role of the service employee should be rethought in increasingly digital service environments (Grewal et al., 2017). Questions have also arisen regarding the service employee’s role and influence in technology-oriented services and how PoS technologies can be integrated into thess service without hindering the interpersonal perception of the customer (Giebelhausen et al., 2014). Especially with regard to online shops, a major challenge for retailers and employees is to maintain this interpersonal quality and not superimpose over it by integrating technologies, thereby making their frontline employee obsolete. Nevertheless, it is also important in online shopping to

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take communication with customers seriously, appropriately design the exchange between a digital service or service offer and the customer in a customer-oriented manner and pick customers up where customers are actually located. Essays 4 and 6 showed the nature of this service in particular. Essays 2 to 8 examined customer-specific perceptions of technology-oriented customer touchpoints in terms of different approaches to service-, product- and data-related variables. This dissertation provides an overview and focuses on the customer touchpoints of brick-and-mortar retail, but it also extends the focus to online retail and lastmile delivery services. In summary, in addition to theoretical implications, this dissertation provides empirical evidence that the infusion of technology in the service encounter at the physical PoS does not automatically lead to an increase of service-related variables, particularly in terms of more purchases or willingness to pay, as it can also be a barrier within a service interaction. The results of essays 2, 3, 7 and 8 underlined the empirical combinations of technological infusion and customer touchpoints in a physical service interaction that are not necessarily understood as added value (Giebelhausen et al., 2014). The customer’s perception of social presence in this service interaction, i.e. the connection between frontline employees and the corresponding technology, seems to be an important factor. The integration of PoS technology can improve specific service-, product- and data-related factors for retailers (de Keyser et al., 2019) even if the manner in which it is actually perceived by the customer and what reactions are evoked depends very much on how the PoS technology is infused in the service (essay 2). Especially for the product-related variables, the presence of technology may prevent a customer from acting naturally compared with a situation in which technology is not available. Moreover, the integration of a frontline employee into a technology-based service can also reduce the added value of the service on the information-oriented level. However, the frontline employee can decrease the customers’ perception of data-related problems (essay 3). Interestingly, technology in the hands of a frontline employee can lead to clearer service- and data-related outcomes than self-service technology (essay 2, 3 and 7). Self-service technology may lead to less information transfer by the customer towards the service, and it also tends to lower perceived trust and increase privacy concerns compared with a frontline employee-infused service (essays 3 and 7); nonetheless, the frontline employee-free service has the potential to transmit better quality information to the customer than having a frontline employee attend the service (essay 3). This indicates the need for a discussion on the relevance of social presence as a whole at the PoS (whether alone or in combination with a technology).

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Discussion and Implication

Essays 2 and 7 showed that barrier-free, interpersonal integration of the customer into the service usually led to the highest success relating to the servicerelated variables. For the data-related variables, technology infusion also appeared to influence the type or category of information provided (essay 7). For example, financial status information was lower than demographic information when technology was infused. The type of incentive also played an important role in the disclosure of data by customers (essay 8). Particularly for monetary incentives, customers seemed to prefer the presence of a technology over its absence. Regarding behavioural adjustments in the context of financial aspects, the second essay showed that in addition to the positive effect of a monetary bonus from essay 8, technology infusion can also trigger a higher willingness to pay among customers. This result was consistent with the results of Mende et al. (2019), as it supported the assumption that technology infusion in a service encounter has a positive influence on the monetary results for the retailer. Nonetheless, customers’ perception of service-related variables had a tendency to decrease with the infusion of technologies. This can be traced back to a lower perceived social interaction than if the service employee were technology-free. Consequently, there was a tendency towards a contrary customer perception and behaviour in relation to service- and product-related variables on the one side and data-releated variables on the other side when digital influences are present. Essays 2, 3, 7 and 8 impled that stationary retailing must determine which goal (focus on data gathering, service optimisation, product presentation, etc.) is of central importance in order to achieve the optimal form of technology infusion in a personal service encounter. In addition, the integration of a human service employee into a service encounter should not be forced if a service-oriented added value is to be created as a whole. Essay 3 pointed out the problems and potential of an integrative and open form of customer service interaction. With regard to the mediating and moderating influences of customer perception, essays 2, 3, 4, 6, 7 and 8 emphasised the relevance and effect of certain service-related variables to explain the influence of experimental factors on certain dependent variables in more detail (Table 4.2). Essay 2 showed a mediating effect of perceived competence. Thus, the conceptual assumptions of Grewal et al. (2020) and van Doorn et al. (2017) can be confirmed. Perceived service competence directly influences the perception of the frontline employee’s service performance in the presence of technology infusion. Building on this, essay 3 identified the mediating effect of the customers’ discomfort with the service in relation to the expected information quality when the service was technologybased and a frontline employee was passively involved. When it came to the pure information content of the service, customers rated their personal discomfort

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higher when a human employee was involved than when the human employee was left outside. It can be assumed that customers were reluctant to let the employees look over their shoulder during the information search process. In addition, the perceived social presence in the service also acted as a mediator for the privacy concerns of the customer. The opposite phenomenon occurred here, namely that the involvement of a human frontline employee in the technology-based service led to a higher perception of social presence, which in turn decreased privacy concerns. In essay 4, a mediating influence of customer trust on the customer’s purchase intention was shown. Furthermore, trust in the retailer and the emotions experienced by the customer (Dennis et al., 2010) were mediators in the data disclosure-related decisions of the customer (essay 7). Similar to online shopping, this effect also manifetsed in physical retail (Dinev and Hart 2006; Li et al., 2011). Consequently, the relevance of service-related mediators with regard to different types of service-, product- and data-related dependent variables can be demonstrated within the scope of this dissertation. The moderating effect of general privacy concerns (essays 4, 5 and 7), perceived benefits of data disclosure (essay 7), privacy-related risk perception (essay 8) and perceptions of data control (essay 8) on service- and product-related dependent variables were also shown. All moderating influences were assigned to the data-related variables. The results on the influences of the data-related factors coincided with those from the literature (Krasnova et al., 2009; Dinev et al., 2013). A higher level of data-related factors usually meant that they restricted the customer’s actions more than if these factors were less pronounced. The customers with higher levels of privacy concerns and perceived privacy risk or lower levels of data control were usually highly sensitised, especially when it came to the exchange of data. The customers in whom these factors were less pronounced showed a much more diffuse and difficult-to-calculate behaviour, but it did not seem important to them whether data was disclosed or not. Regarding the results of the individual essays, i.e. essays 2, 3 and 5 that focused on service- and product-related variables and essays 4, 6, 7 and 8 that focused on data-related variables, Parasuraman’s (2000) pyramid model of services marketing states that the connection between technology and the service employee/service provider in technological customer touchpoints must be of central importance for the success of a service interaction. The ability to integrate social components into this form of service interaction can determine the customer’s perception and have a direct, positive influence on the entire service. Only when the interaction between the service employee/service provider and technology works and the customer feels the social presence of this connection can this service encounter be positively perceived. If the customer perceives this

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Discussion and Implication

connection as negative or disturbing in any way, the entire service may not deliver the results that the retailer wants. A customer may have the option to receive a service exclusively via a service employee/service provider or solely via a technology. In both cases, however, a third party may also play a role in the process. In this dissertation, two perspectives of technology-oriented retail can be distinguished: the customer–service employee perspective (essays 2, 7 and 8) and the customer–technology perspective (essays 3, 4, 5, 6 and 7). In essays 4, 5 and 6, the interaction with the service provider took place digitally. The customer–service employee perspective included the primary contact between the customer and the frontline employee, while the customer–-technology perspective emphasised the customer’s contact with the technology.

4.2

Implications for Theory and Practice

4.2.1

General Customer–Service Employee Perspective

The first part of key objective (2) is the deepening of the theoretical understanding of social presence in the physical service encounter between the customer and the frontline employee through technological service assistance. This dissertation demonstrats that technology infusion in frontline service encounters does not necessarily bring positive outcomes, but can acted as a barrier. Particularly against the background of the different objectives of the service, such a technology can on the one hand convey the feeling of being able to better classify the product relevant within the service and thus also attach a higher price to it, on the other hand, however, interpersonal factors of the exchange are pushed into the background and perceived as more negative. The customer wants to feel integrated in the frontline service during the service encounter, especially in case of a possible data exchange. Customers seemed to reward a higher level of perceived customer service interaction by disclosing more data and being more willing to pay. The theory of social presence helps to understand how customers value non-technology-based service; however, this research was able to show that technology infusion affected the dyadic interaction between the two parties. This fact was presented in essays 2, 7 and 8 wherein it became clear that the differentiated interaction between frontline employees and technology led to a changed perception of customers’ willingness to interact socially with the service. The perception of social interaction or the perceived involvement of the customer in the service also plays a central role in the infusion of a technology when it comes

4.2 Implications for Theory and Practice

213

to the effect of the service as a whole on customer trust in the service, the willingness to pay and the disclosure of personal data. Therefore, the theory of social presence is not only applicable to purely technological media (Short et al., 1976), but it also plays an important role as a link between employees and technology in the perception of the customer. Based on Turner’s (1988) approach to interpersonal interaction in the context of social presence, this dissertation also assumed that motivational, interactional and structuring components influence the willingness of customers to interact in technology-supported services. In addition to the obvious effects on the level of the interaction process, at which the customers’ ability and gestures signalled or emphasised certain arguments, this work also assumed that the process of motivating customers to engage in the respective interaction would also change. The results of the essays suggested that these interaction process tend to be lower or weaker when technology was infused, although the manner in which the technology was integrated seemed to have an influence. The decrease in perceived competence by the customer and its clear mediating effect on the service perception-related variables can also be noted in essay 2. In summary, this dissertation found that the theoretical approaches to social presence can also be interpreted from the link between technologies and employees. Short et al.’s (1976) social presence theory is therefore applicable to analysing customer perceptions and responses to service encounters in relation to technology infusion and technology-based services. Second, the social presence theory helps to explain the influence of technology-supported service on the perception and reactions of customers. The weighing of individual advantages and costs by customers, within the framework of the privacy calculus theory, seemed to explain why customers disclose personal data under certain (technology-oriented) circumstances. When data could potentially be disclosed by the customer in interpersonal service interactions, customers seemed to evaluate the service encounter differently in the case of the use of a certain technology by the frontline employee (essays 7 and 8). Furthermore, the results suggested that offering an incentive triggered a reassessment of the service situation (essay 8), resulting from a more intense cognitive assessment by the customers of the benefits and costs of the ‘acceptance’ of such incentive (Heath and Soll, 1996). This calculation appeared to play a role in the connection between incentives and the disclosure of data and also in the providing of digitally transferred access permissions (essay 5). Both essays agreed with the research by Culnan and Bies (2003) and Krafft et al. (2017), who noted that data related to the (digital) private life or access to the (physical) private life is only shared if the perceived costs are exceeded by the perceived benefits.

214

4.2.2

4

Discussion and Implication

Practical Customer–Service Employee Perspective

With respect to key objective (3), Kuckertz et al. (2020) emphasised the potential of technologies during crises. Indeed, current challenges have forced the creative combination of existing technology and human capital. In the case of technology infusion, especially in frontline service, the focus should be to ensure interpersonal interaction first of all. Only when the employee is able to reproduce this correctly can the customer’s service-related perception of the encounter be improved; thus, the smart infusion of technologies is necessary. Aligning technology integration with the skills and characteristics of frontline employees is essential, so employees should be individually trained to handle the technology. The frontline employee’s ability to provide good service may also play a role in the collection and use of customer data as well as the implementation of specific incentives. The latter in particular is highly relevant when a customer weighs the potential advantages and costs of a possible data exchange. They may help reduce concerns about the merchant’s handling of data. Therefore, it is important to further study how these processes work in order to provide dealers and frontline employees with tools to reduce customer concerns about data privacy. Retailers can focus more on trust-building processes. Since the customer’s perception of the competence of the frontline employee may also influence their trust in the frontline employee, the introduction of technology into the customer service interaction should not be done at short notice; rather, the frontline employees must receive the necessary training first. Concerning the data disclosure behaviour of customers, the results also showed that when it came to information on demographics or finances, for example, it was better for frontline employees not to leave customers alone with the technologybased service. Even retailers who offer personalised services should not rely on self-service technologies; they must aim for a combination of human and technological components. Frontline employees must be trained to handle these technologies during service interactions, they should also be familiar with the type of technology infusion (e.g. in the form of technology-facilitated oe technologyassisted service encounter). In addition, the frontline employee should also be able to determine whether a purely technology-based service makes sense or whether a human can be helpful in a technology-based service. In the interplay between social and factual/financial added value, whether and how the introduction of innovative technologies influence the attitudes of customers (e.g. in terms of customers’ willingness to pay) can be observed and calculated.

4.2 Implications for Theory and Practice

4.2.3

215

General Customer–Technology Perspective

Past studies have suggested that if technology (rather than a human agent) is the primary interaction partner in a service, the customer’s underlying calculation of data-related concerns and the potential benefits of data disclosure are central factors as well. It would therefore be interesting to observe when and how customers perceive advantages during online product presentations or digital services and convert them into concrete behaviour. However, the results showed that the customer perceived lower transparency of information about the use and handling of personal data as more valuable than higher transparency, and it resulted in positive product-related behaviour. As the primary interaction partner, technology could not keep up with the social competence of a human service employee. Pure digital-technological service generated negative data-related factors (higher privacy concerns and lower willingness to pay for data). When the role of data in the exchange of services and the social component of the human service employee were excluded, the customer became more cautious and insecure in the handling of their data. By examining these processes through the lens of the privacy calculus, it could be show that the perception of social presence in the service or of the employee played important roles. Essay 4 gives reason to take a more differentiated look at the discussion around the topic of customer empowerment, especially against the backdrop of the constantly changing digital influences in everyday customer life (e.g. Acar and Puntoni, 2016; Barile et al., 2021). The perceived control over the products offered or the alternatives available/provided by a company plays a decisive role here (e.g. Fuchs et al., 2010). Contrary to popular belief, customers also seem to be willing to relinquish this control when it comes to receiving possibly unpleasant information, especially with regard to the potential utilisation of data. The offer of empowerment in the context of incentivisation processes can also be met with a rather negative attitude. This shows that the reaction to the possibility of a more personalised service is not an increase in data sharing, but rather a decrease. However, it can also be determined that in the context of frontline service encounters, a technology that is infused into this process does not necessarily improve the customer experience and also the control over the service process, but rather the service as a product, which can be influenced by the customer, is possibly no longer understood as influenceable and as a result the perceived empowerment at the physical PoS with regard to the service as a central good of this place suffers as a whole. This must be absorbed at the physical PoS through the smart integration of these technologies as an informative added value and at the same time not as an interpersonal barrier.

216

4.2.4

4

Discussion and Implication

Practical Customer–Technology Perspective

This dissertation underlined the relevance of adapting services to the needs and desires of customers during direct interactions with technologies. Since trust in the technology and the perceived risk of external interference in data exchange processes both have mediating influences on the willingness of the customer to provide additional information, providers should improve customers’ understanding of the service. Improving the public perception of the company is important even if it is time-consuming and costly. In addition, the general environmental compatibility and individual work-life flexibility in the use of technologies and related services also seem to be of importance to the customer. Customers have to understand that technology is compatible with the customer and that purely digital services is also oriented towards the wishes and interests of the customer. Nevertheless, the social components of purely technological services should also be enhanced (i.e. the social skills of AI must be improved), which would make the customer feel well looked after, especially when it concerns their data.

4.3

Relevance for Future Studies

4.3.1

Customer Service Employee Perspective

Key objective (4) of this dissertation suggests that technology infusion within service is a challenge in retail (Piotrowicz and Cuthbertson, 2014). Focusing on the skills and traits of frontline employee is critical for achieving sustainable success, especially in the retail sector. In addition to the customer’s perception of competence examined in essay 2, perceived similarity to the frontline employee and perceived gender congruence may also be relevant in the understanding of the infusion of technology in a service encounter. In addition to the potential influence of frontline employees on service-, product- and data-related variables, the physical retail environment might also be an influencing factor in the perception of technology-oriented customer touchpoints, e.g. general store image (Hultman et al., 2017) and store attributes (Kim et al., 2015). Numerous studies have dealt with the effects of fundamental atmospheric aspects (Eroglu et al., 2003), such as shop design (Murray et al., 2015), odour and music (Knoeferle et al., 2017; Roschk et al., 2017), that may also influence perception. Essay 6 illustrats that gender congruence had a unique influence on service perception in the digital environment (Maner et al., 2009; Agthe et al., 2011).

4.3 Relevance for Future Studies

217

These approaches can be important for privacy concerns in brick-and-mortar retail stores, as same-gender interactions can lead to an adaptation of privacy concerns towards the frontline employee. For example, Mattila et al. (2003) pointed out that male customers react more negatively to an incompetent service employee, which can be examined in line with data-related factors. By contrast, Reinders et al. (2008) showed that women like to be offered a wide range of services in the service process (e.g. with, without technology or a combination). Innovative technologies may be incorporated, as they can have a stronger social presence (van Doorn et al., 2017; Grewal et al., 2020). Building on essays 2 and 8, the ambivalent relationship between servicerelated, product-related and data-related variables has an important behaviourrelated effect. The exact cognitive processes underlying this phenomenon should be further researched. It can be assumed that personal values (e.g. environmental sustainability or work–life flexibility, as mentioned in essay 5) are associated with more intensive internal processing for each data element. In other words, the calculation of the privacy of the individual customer (Culnan and Armstrong, 1999) is still a relevant topic in which some form of balance between benefits and costs is challenging to assess, especially in social interactions. Therefore, further research on the inherent and underlying processes of the customer and on the psychological phenomena responsible for these processes is needed.

4.3.2

Customer Technology Perspective

The results of the third essay underlined the importance of further analysing how different types of information sources in pure and employee-supported service interactions affect the perception and behaviour of customers. The manner in which different types of technological information sources affect the customer’s perception of the service in a given service situation should be given more focus. As the incorporation of information technology into retail practice becomes richer and broader, and shopping on physical PoS becomes more similar to online shopping, personal interaction with the customer may be the way to avoid losing customers to the online market in the long term. Nevertheless, the customer must be enabled to obtain the required information on request at a physical PoS alone. The interaction at the frontline and the perception of social presence through or supported by digital solutions, such as avatars or VR/AR solutions, can influence the need for face-to-face elements in a brick-and-mortar and change customer behaviour in relation to the perception of convenience or efficiency (Alexander and Kent, 2020; Grewal et al., 2020).

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© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2023 T. Röding, Technology-Oriented Customer Touchpoints in Context of Services in Retailing, Handel und Internationales Marketing Retailing and International Marketing, https://doi.org/10.1007/978-3-658-40554-0

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