Social Media, Mobile and Cloud Technology Use in Accounting: Value-Analyses in Developing Economies 1839821612, 9781839821615

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Social Media, Mobile and Cloud Technology Use in Accounting

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Social Media, Mobile and Cloud Technology Use in Accounting: Value-Analyses in Developing Economies FEMI OLADELE Bowen University, Nigeria

TIMOTHY G. OYEWOLE Bowen University, Nigeria

United Kingdom – North America – Japan – India – Malaysia – China

Emerald Publishing Limited Howard House, Wagon Lane, Bingley BD16 1WA, UK First edition 2020 Copyright © 2020 Emerald Publishing Limited Reprints and permissions service Contact: [email protected] No part of this book may be reproduced, stored in a retrieval system, transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without either the prior written permission of the publisher or a licence permitting restricted copying issued in the UK by The Copyright Licensing Agency and in the USA by The Copyright Clearance Center. Any opinions expressed in the chapters are those of the authors. Whilst Emerald makes every effort to ensure the quality and accuracy of its content, Emerald makes no representation implied or otherwise, as to the chapters’ suitability and application and disclaims any warranties, express or implied, to their use. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-1-83982-161-5 (Print) ISBN: 978-1-83982-160-8 (Online) ISBN: 978-1-83982-162-2 (Epub)

Table of Contents

List of Figures

vii

List of Tables

ix

List of Selected Abbreviations/Acronyms

xi

Definitions of Selected Terms

xiii

Chapter 1

Introduction Background Research Motivation

1 1 5

Chapter 2

Literature Discourse Conceptual Review Theoretical Review Empirical Review Summary of Empirics

9 9 50 60 67

Chapter 3

Study Significance of the Study Scope of the Study Research Objective and Questions Research Hypotheses Methodology Conceptual Framework for Analysis Results Summary and Conclusions

81 81 82 83 83 83 92 95 228

vi

Table of Contents

Further Thoughts

235

Acknowledgements

237

References

239

Index

261

List of Figures

Figure Figure Figure Figure

1 2 3 4

Figure Figure Figure Figure Figure Figure

5 6 7 8 9 10

Accountants’ Training Framework in Nigeria. Accounting Profession and Custodians. Proposed PLESUT. Multidimensional Measurement of ‘Use’ of SoMoClo Technologies. Conceptual Framework for Analysis. Proposed Structural Model for PLESUT. Summary of Study Variables. Social Media WRA Statistics. Mobile Technology WRA Statistics. Cloud Technology WRA Statistics.

17 27 59 93 94 96 97 149 150 150

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List of Tables

Table 1 Table 2 Table 3 Table Table Table Table Table Table Table Table Table

4 5 6 7 8 9 10 11 12

Table 13 Table 14 Table 15 Table 16 Table Table Table Table

17 18 19 20

Table 21 Table 22 Table 23

Professional Accounting Organisations in Nigeria. List of IFAC-recognised African PAOs. Research and Policy Institutions of Accounting Education and Profession. IES and Supporting Publications of the IAESB. SoMoClo Technologies for Accounting Profession. Summary of Selected Qualitative Research. Summary of Selected Empirical Research. Response Device and Preferred Device Distribution. Primary and Secondary Specialty Distribution. Gender Distribution and Crosstab with Specialty. Age Distribution and Crosstab with Specialty. Experience, Membership Distribution and Crosstab with Age and Gender. Membership, Experience and Crosstab with Specialty. Academic Qualification Statistics. Professional Qualifications and Primary Specialty Cross-tabulation Statistics. CPD and STT Attendance with Primary Specialty Cross-tabulation Statistics. ATF Statistics. Descriptive and Reliability Statistics of Perception. Aggregate Scores for PU, PEOU and PCT. Descriptive and Cross-tabulation Statistics for WRA and Gender. Cross-tabulation Statistics for WRA and Primary Specialty. Matrix Derivation and Reliability Statistics. Statistics of Institutional Adoption of Technology.

18 20 28 31 51 67 70 98 103 111 115 119 122 126 129 131 135 136 138 141 143 146 154

x

List of Tables

Table 24 Table 25 Table 26 Table 27 Table 28 Table 29 Table 30 Table 31 Table 32 Table 33 Table 34 Table 35 Table 36 Table 37 Table 38 Table 39 Table 40 Table 41 Table 42

Ranked Statistics of the Use of SoMoClo Technologies. Use of SoMoClo Technologies and Institutional Adoption. Age, Experience and Use of SoMoClo Technologies Cross-tabulation Statistics. Specialty and Gender Cross-tabulation with Use of SoMoClo Technologies. Reciprocity and Correlation Statistics on the Use of SoMoClo Technologies. Technology Competence Statistics. Correlation Statistics for Technology Competence. Cross-tabulation of Knowledge-ability and Use of SoMoClo Technologies. Descriptive Statistics on Relationship between ATF and Technology Competence. Correlation Statistics of ATF and Technology Competence. Cross-tabulation of Qualification and Use of SoMoClo Technologies. Binary Logistic Regression Results for Use of Social Media. Binary Logistic Regression Results for Intention to Use Social Media. Binary Logistic Regression Results for Use of Mobile Application. Binary Logistic Regression Results for Use of Mobile Device. Binary Logistic Regression Results for Intention to Use Mobile Technology. Binary Logistic Regression Results for Use of Cloud Technology. Binary Logistic Regression Results for Intention to Use Cloud Technology. Summary of Predictability and Odds Ratio Statistics.

159 162 168 170 174 179 182 184 189 191 195 205 208 212 215 218 222 225 229

List of Selected Abbreviations/Acronyms

AAA ACCA AI ANAN B.Sc. BMAS CAC CBN CC CITN CPD DIT FRCN HND IAESB ICAN IES IFAC IMA IPD IR IT NAA NASB NBTE NDIC

American Accounting Association Association of Chartered Certified Accountants Artificial Intelligence Association of National Accountants of Nigeria Bachelor of Science Benchmark Minimum Academic Standard Corporate Affairs Commission Central Bank of Nigeria Cognitive Computing Chartered Institute of Taxation of Nigeria Continuing Professional Development Diffusion of Innovation Theory Financial Reporting Council of Nigeria Higher National Diploma International Accounting Education Standards Board Institute of Chartered Accountants of Nigeria International Education Standards International Federation of Accountants Institute of Management Accountants Initial Professional Development Integrated Reporting Information Technology Nigerian Accounting Association Nigerian Accounting Standards Board National Board for Technical Education Nigeria Deposit Insurance Corporation

xii

List of Selected Abbreviations/Acronyms

NUC PAOs PEOU PLESUT PU SAICA SEC SEM SME SoMoClo TAM TTF UTAUT WRA

National Universities Commission Professional Accounting Organisations Perceived Ease of Use Perceive, Learn, Setting, and Use Theory Perceived Usefulness South African Institute of Chartered Accountants Securities and Exchange Commission Structural Equation Modelling Subject Matter Expert Social Media, Mobile and Cloud Technology Acceptance Model Technology Task Force Unified Theory of Acceptance and Use of Technology Willingness, Readiness and ‘Ableness’

Definitions of Selected Terms

Ableness: This term is constructed to blend ‘ability’ with willingness and readiness. The study studied ‘use’ as a variable using a perfect combination of the three concepts (WRA). This implies that a professional accountant is said to be able to use a specific technology if she/he is willing, ready and able to use it. Accountant: We adopt the definition of an accountant as a professional accountant only; that is, someone who is a member of a PAO, that is, a member or associate of IFAC. In addition, the accountant in this study was deemed to be a member of a Nigerian PAO, that is, ANAN and/or ICAN. Accountants’ training framework: This framework is a pool of academic and professional accounting training opportunities that are open to candidates willing to become and remain professional accountants. The academic training pool is, however, limited to university and polytechnic degrees and awards, while professional training includes both IPD and CPD. Accounting education: This is used interchangeably with accountants’ training framework. It entails all forms of education open to a person, leading to becoming and remaining a professional accountant. In the popular sense, it usually denotes academic accounting education. Accounting profession: The accounting profession is held as tripartite, such as comprising accounting practice, policy and research. Demographic variables: Three variables, that is, age, experience and gender, were considered. They are collectively referred to as demographic variables for convenience sake but were measured separately. Determined factors: These are factors conceptualised based on literature and used as established proxies for certain factors. For perception, PEOU and PU, which are validated constructs, were used. Accountants’ training framework relates to two categories of academic and professional training, while accounting profession is held as tripartite including practice, policy and research. These factors were held as significant for the measurement of the target variables. New technology: Though SoMoClo technologies have been in existence for a long time, they were considered new in the study, especially amongst professional accountants in Nigeria as official technologies. The concept of new technology is

xiv

Definitions of Selected Terms

derived from the inclination of technologies that were non-existent at the time of receiving training but has become imperative. Professional accountant: Professional accountants are held as people who are members of a recognised PAO and functioning as practitioners, policymakers or researchers. SoMoClo technologies: Social media, mobile and cloud technologies are elements of technology. Social media technologies include applications that foster communication, interactions and networking amongst users such as Facebook, WhatsApp etc. Mobile technology encompasses devices such as Phones, Tablets and in some cases Laptops. It also includes operating systems such as Android, iOS, BlackBerry etc. and finally diverse applications built on both the operating system and the device. Subject matter expert (SME): This is used to refer to experts in a field with sufficient knowledge of the field to be called experts. Technology: Technology is a pervasive term to define; it is a conglomerate of ideas, objects, systems etc., whose aim is to enhance operational efficiency. Technology and SoMoClo technologies are sometimes used interchangeably in this work, albeit the latter is an element or subset of the former. Value-analysis: This is used as the measurable, attributable value of a variable/ concept from and/or against another variable/concept. In this study, two types of analyses are used, that is, predictive and interpretive. Predictive value-analysis gives insight into the use of existing training framework to predict professional accountants’ use of technology, while the interpretive value-analysis allows an indication of the quality of training a professional accountant has received by viewing and/or assessing her/his use of technology.

Chapter 1

Introduction Background A significant basis for the accounting profession is responsibility and reporting; basically between an agent and a principal. This relationship typifies the transfer of resources from owners to other economic entities (individuals, other entities and government) as managers, which in turn bestows a responsibility for accountability. The need for financial accountability inspired by a relationship of stewardship and strengthened by agency became compelling as a result of the emergence of economic activities (Eisenhardt, 1989). However, around early twentieth century, according to Wood (1972), it was discovered that laymen could no longer handle the sophistication of ensuring accountability with the growing economic activities, hence the need for the appointment of professionals. These professionals were trained under the apprenticeship method before more formal methods in schools (Chu & Man, 2012). Professional accountants have since devoted their time to activities, operations and functions to provide information to users for decision-making. However, with the enormous responsibility occasioned by the advent of emerging technologies, the need for professional accountants to use technologies became evident. In response to the need to ensure technology competency and proficiency amongst professional accountants inter alia, the Pathways Commission, which birthed in 2012 through a collaboration of the American Accounting Association (AAA) and the American Institute of Certified Public Accountants (AICPA) in the United States (Samkin & Stainbank, 2016), responded by instituting a Technology Task Force (TTF) amongst others. The aim was to explore ‘the different accounting technologies used in practice today and what will be expected in the future and the technologies currently being taught in accounting programs as well as how current and emerging educational technologies can improve accounting education’ (Pathways Commission, 2014b, p. 13). Following the achievements of the Pathways Commission, Ellington (2017) decried the non-formalisation and institutionalisation of reforms to higher accounting education in the United Kingdom and recommended the duplication and/or adoption of the work of the Pathways Commission. Earlier in South Africa, a study (Wessels, 2004) was carried on to investigate the future work of Social Media, Mobile and Cloud Technology Use in Accounting: Value-Analyses in Developing Economies, 1–7 Copyright © 2020 Emerald Publishing Limited All rights of reproduction in any form reserved doi:10.1108/978-1-83982-160-820201003

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Social Media, Mobile and Cloud Technology Use in Accounting

professional accountants with respect to the triggers of information technology (IT) and to spur research into aligning the future with current education of accountants and the research continued (Wessels, 2005) with intent to identify technology skills that are required for professional accountants to fit into the future of work. In Egypt, a study (Nokhal & Ismail, 2014) was carried out to determine the (mis)alignment of IT knowledge/skills importance and integration into the accounting curriculum and the results found a significant gap between what is expected in business and what is taught in the accounting programme. In Nigeria, Okolie and Izedonmi (2014) questioned if Nigerian professional accountants are being trained to meet international minimum acceptable competence level, albeit without specific reference to technology. These studies are indicative of the changing dynamics in the business world and the need for professional accountants to understand and prepare for the effect of the wave of change. The minimum level of technology proficiency expected of professional accountants is specified in the International Education Standards (IES), the global accounting education benchmark, issued by the International Accounting Education Standards Board (IAESB) (2017). The IES is published by the International Federation of Accountants (IFAC), which is the global association of professional accountants. The IES, as a global standard for the education of aspiring professional accountants and professional accountants, stipulates authoritative pronouncements to be used by members and associates of IFAC, that is, PAOs in all jurisdictions of the world in the education (training) of their members. The level of proficiency should be the ability to demonstrate necessary general IT and IT control knowledge as well as competencies, knowledge and understanding of at least one of the three roles of managing, designing and evaluating information systems (IAESB, 2007). This proficiency requirement exceeds general computer appreciation and front-end use of technology. The need to ensure and sustain an acceptable level of competence, adoption and use of technological applications for accounting operations, functions and activities amongst professional accountants is valid, yet it is becoming increasingly evident that there is shortage of IT competencies amongst professional accountants (Lubbe, 2016). This therefore raises concern on the ability to grasp the value of the accountants’ training framework on technology use amongst professional accountants for their varied responsibilities. The crux of the matter lies with the future relevance of professional accountants (Okolie & Izedonmi, 2014), given also that bookkeeping activity is no longer the exclusive preserve of accounting professionals; this, now being taken over by traditional accounting software packages (Oladele, 2014) and cloud-enhanced applications (Meall, 2016a). This poses a challenge to the ability of professional accountants faring in this fast-evolving technological world with an apparent shortage of an acceptable level of technology skills, given significant agreement in literature that technology will continue to shape accounting practice in the decade to come (Meall, 2016b) and make some accounting functions obsolete (Birt, Wells, Kavanagh, Robb, & Bir, 2018; IFRS Foundation, 2010b).

Introduction

3

Technology leverages its ability to substantially increase process operational efficiency beyond the outcomes of human dexterity such as is seen with expert systems (Damasiotis, Trivellas, Santouridis, Nikolopoulos, & Tsifora, 2015; IAESB, 2007; Shaoul, 1988; Sutton, Holt, & Arnold, 2016), grid computing (Sultan, 2011), artificial intelligence, cognitive computing, machine learning (Hong et al., 2016; Sutton et al., 2016) and big data analytics (He, Wang, & Akula, 2017; Sledgianowski, Gomaa, & Tan, 2017). However, accountants may increasingly bask in the assurance that technology may not be able to quickly replace professional scepticism (ACCA, 2016; Berg, Buffie, & Zanna, 2016; Meall, 2016b), a distinguishing attribute amongst professionals, despite developments in revolutionary technologies. In addition, technology may be used to enhance (not replace) the need for accountants’ professional judgement as required by the provisions of the principles-based reporting standards now globally adopted/adapted. Notwithstanding, it is true that the human race is being threatened by its own creation, albeit this is not news as God was threatened by His creation (Genesis 11). While this is true, professional accountants are not willing to be thrown to the trash can of irrelevance because of technological advancements (Meall, 2016b). This brings two suggestions; one from an idiom, that ‘…the danger of creating a monster is that one day, it will turn to harm its creator’. This raises two concerns: (1) the ability of identifying and avoiding the creation of a monster and (2) determining how monstrous technology is or will be (Worrell, Bush, & Di Gangi, 2014). Secondly, God did not allow the plans of mankind to disrupt His divine plans, so he took action (Meyers, 2012, n. Genesis 11: 6–8). In the same vein, professional accountants may not sit idly and observe (Guthrie & Parker, 2016) else the circumference moves (Oladele, 2015c) leaving them behind (ACCA & IMA, 2015). As technology continues to evolve, professional accountants will as well need to continue to evolve means of staying relevant by not only using technology for their operations and activities, but significantly influencing and being part of the development of technological applications, tools and systems as managers, designers and evaluators (IAESB, 2007). Consequently, this has significant implications for the training of professional accountants, which raises fundamental matters on how much accountants’ technology competence and use tell about the quality of training they receive. In addition, the issue of how the environment (in which professional accountants learn and eventually work) influences accountants’ technology adoption practices borders on predictive and interpretive value measurements. It is important to stress that the term technology is omnibus, and this study has limited its scope to social media, mobile and cloud technologies, abbreviated as SoMoClo technologies. SoMoClo technologies are relevant to the work of professional accountants in diverse ways and forms. Social media has always been available for personal communication and networking, yet it has been reinvented to fit into corporate livelihood in organisations. Mobile and cloud technologies have a combined capacity to surpass present organisational challenges, hence their importance to the work of professional accountants.

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The value-analyses referred to on the use of SoMoClo technologies border on understanding how the use of SoMoClo technologies can be adopted to interpret the quality of training that professional accountants have obtained, and how the training framework of accountants can be used to predict professional accountants’ use of SoMoClo technologies. However, concerns come to mind on the possibility of, and how determined factors of accountants’ training can be used to predict the use of SoMoClo technologies. How the use of SoMoClo technologies can interpret accountants’ training framework within the specialty-context of the accounting profession is likewise significant. In justifying the use of value-analyses, the researchers are of the opinion that due to the exigencies of data and information, bordering on incompleteness and inaccuracy, forecasting future outcomes are occasionally guesswork. Causal relationships, for example, help in prediction for planning (Sun & Zhang, 2006), hence justifying the use of interpretive and predictive measures. This suggests the use of predictions and estimations, leaving room for error, which has led to calls for confidence accounting in the financial accounting domain (Harris, Mainelli, & Onstwedder, 2012). Another case in point is medical science, which – as close to life as it is – still employs the use of prediction in cases such as the expected date of delivery (EDD). Most of the works of professional accountants that are measurement related are based mainly on estimates and predictions as well, and as posited by Reinstein (2000), there are evidences of claims and counter claims on the predictive abilities of financial statements prepared by professional accountants. To further substantiate the point, there is a financial accounting standard (IAS 8: Accounting Policies, Changes in Accounting Estimates and Errors) that takes care of issues around estimates and prediction in financial reporting. The adoption of predictive and interpretive value-analyses on the use of SoMoClo technologies is broadly speculative but hinged also on certain assumptions as espoused in technology use theories. One of such assumptions is the use of ‘intention to use’ or ‘behavioural intention’ to predict or measure ‘actual use’ (Watty, McKay, & Ngo, 2016) when it is in fact not possible to measure ‘use’. There is substantial literature evidence to suggest the support of the use and adoption of predictive and interpretive analyses in achieving research objectives (Belfo & Trigo, 2013; Buckless & Krawczyk, 2016; Fair, 1978; Geiger & Cooper, 1996; Hardr´e, 2016; Jamaluddin, Ahmad, Alias, & Simun, 2015; Khan, Kend, & Robertson, 2016; Sun & Zhang, 2006; Sutton et al., 2016; Wang & Shih, 2009; Wessels, 2004). In addition, a study (van Beest, Braam, & Boelens, 2009) that sought to measure quality of financial reporting using the qualitative characteristics was anchored on the predictive value of the financial statement for future outcomes. The use of prediction is therefore a sound mechanism for research, especially when combined with interpretivism, which is also recognised as a suitable method for research (Bhattacherjee, 2012; Hamilton, 2013; Lindsay, 2013). The determined factors are taken from literature, such that accountants’ training framework includes academic education and professional education (Gammie, Cargill, & Hamilton, 2010; IAESB, 2015b). It is instructive to state that within the context of academic education, tertiary training for professional

Introduction

5

accountants is optional in some climes because there are routes to becoming a professional accountant without a tertiary academic degree or award, albeit a tertiary award is desirable and has become basic amongst accounting professionals. The professional education component is made up of initial professional development (IPD) and continuing professional development (CPD). The IPD is made up of training to instil (1) technical competence, (2) professional skills and (3) professional values, ethics and attitude, and to acquire practical experience. Determined factors used to qualify perception are as popularly used by the theories of technology use with two broad categories: that is, perceived ease of use (PEOU) and perceived usefulness (PU) (Sabi, Uzoka, Langmia, & Njeh, 2016; Watty et al., 2016; Zhang, 2017). It is instructive to highlight that there are other validated constructs for the measurement of perception, such as perceived enjoyment (Sun & Zhang, 2006), perceived benefit (Richardson, Dellaportas, Perera, & Richardson, 2013), perceived resources, perceived expenditure and perceived cost (Zhang, 2017). Specialty is held as tripartite, comprising accounting practice, policy and research (Laughlin, 2011; Oladele, 2015b). The demographic factors that are considered are age, experience and gender, seeing that they have significant moderating effects on factors that influence technology use based on literature. It is noteworthy that economies that produce scientific knowledge (Dabalen, Oni, & Adekola, 2001) and maximise their knowledge workers develop rapidly and enjoy increased income (Mendivil, 2002), thereby contributing significantly to national social and economic growth and development (Dumbili, 2014). This implies that determining the value, type and dynamics of accountants’ training framework that influences technology competence and use amongst professional accountants as a precursor for effective and efficient policy directions and implementation strategies by stakeholders is key to significantly developing the economy. Given that it is the responsibility of accountants’ training framework to determine the level of competence to be attained to become and remain qualified as professional accountants (IAESB, 2015b; Wessels, 2006), if there are concerns about the quality of professional accountants’ technology competence and ultimately the use of technology, it becomes overarchingly necessary to rethink the training framework, its environment, providers and vanguards.

Research Motivation The rapidly evolving nature of IT continues to influence organisational operations, activities and functions including competence requirements (Damasiotis et al., 2015; Willis, 2016). Therefore with growing demands for professional accountants to deliver efficiently, and sustainably productively, the need for improved and constantly improving technology competence cannot be overemphasised. ACCA and IMA (2015) highlighted SoMoClo technologies as relevant to the work of professional accountants, yet it seems there is literature silence on the use of SoMoClo technologies, collectively in the professional accounting

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domain, especially in developing economies. This may be predicated on the fact that they are somewhat new technologies. It must be noted that SoMoClo technologies challenge traditional technologies, and threaten to lead to attrition, making its study significant in the professional accounting circles where there has been growing demand for increasing the number of professional accountants. The adoption of these technologies has significant impact on employee-to-employee, employer-to-employee, business-to-customer (B2C), business-to-business (B2B) and business-to-government (B2G) relationships, yet it seems literature has not fully reviewed those intricacies amongst professional accountants, especially in developing economies. Issues surrounding technology awareness and recognition precede issues that border on technology competence amongst professional accountants; hence, questions that review current practices and education of professional accountants need to be asked. Accounting, like other professions, needs to stay current and this requires constant training, such that professional accountants already in ‘practice’ can be familiar with new technologies to remain relevant. This is important given the fact that technology is not only transformative and disruptive; it is constantly evolving (receiving updates and upgrades) to counter existing challenges and enhance efficiency in service delivery. A research problem, however, is the literature silence on professional accountants as social actors in the framework of the use of SoMoClo technologies. This raised the need for a study to identify whether professional accountants in developing economies are aware of emerging SoMoClo technologies useful in their professional capacity and whether they recognise and use these technologies. Furthermore, questions that border on the awareness of the capabilities of these technologies for professional engagements as well as responsibilities of professional accountants towards their use are of significant scholarly enquiry. Significantly as well, given the fact that the world is a global village, the need for research that compares the technology competence of professional accountants in emerging economies, side-by-side with the international competence standard – the IES – cannot be overemphasised. This readily becomes imperative given that corporate entities now cross national borders, in search of professionals with requisite skill and competence to reduce cost of hiring high-priced labour (Guthrie & Parker, 2016). This is predicated on the fact that when low-priced competent labour abounds, it creates incentives for investment flow. The ascertainment of the technology competence of professional accountants in developing economies compared with international competence requirement is significant to assist to assess her contribution to the global labour market. A concern that resonates significantly is how willing multinational corporations are, to engage professional accountants from developing economies, based on their level of competence. It is significant to highlight that the provisions of the IES constitute minimum standard. However, it appears that reviews of studies that compared IT inclusion and integration in accounting curriculum found significant variances (Nokhal & Ismail, 2014); this raises significant red flags. The ATF, which incorporates all the education and training received by professional accountants, may not have received significant scholarly enquiry as

Introduction

7

required given its prominence of place as a key factor in shaping especially technology capacity and competence. First, it appears there is a silence in literature on the relationship between the ATF and the technology competence of professional accountants in developing economies and secondly, it appears the ATF has not been used as a predictor variable on the use of SoMoClo technologies. Many studies have limited education and training to a demographic variable or at best, a moderating variable, creating a significant research gap. Conclusively, studies have been done to analyse the influences of age, gender, level of education, experience, ethnicity and other variables but a significant shortcoming is that it appears that studies that analysed the influences of pickets of accountants’ training framework in developing economies are limited in scope. It also appears that studies within specialty-context on technology (or more specifically, SoMoClo technologies) competence and use amongst professional accountants are non-existent.

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Chapter 2

Literature Discourse This chapter covers significant concepts, constructs and theories, including the development of theoretical and conceptual frameworks for analyses. It has three sections. The first section details the conceptual review, while the second section highlights the review of relevant theories and documents the development of a speculative (proposed) theoretical framework, which modified popular technology theories and lent from sociological theories of discourse and practice. The third section notes some relevant empirical works. The discourse is bolstered with interjections, conjectures, critical opinions and viewpoints.

Conceptual Review This part reviews concepts and constructs amongst which includes imprints on accounting; accountants; accountants’ training framework and profession; perception, gender issues, professional competence requirements and qualification; knowledge and supply gaps as well as societal expectations; technology and social media, mobile and cloud technologies.

Accountants Accountants are knowledge workers (Damasiotis, Trivellas, Santouridis, Nikolopoulos, & Tsifora, 2015; Howieson et al., 2014; Sutton, Holt, & Arnold, 2016; Wellisz, 2016; Wessels, 2004, 2006), information providers (Carnegie & Napier, 2010; Deegan, 2016; Howieson et al., 2014) and strategists (Okolie & Izedonmi, 2014; Oladele, 2015c). Accountants have been evolving through decades from mere stereotyped number crunchers (Devonport, 2007; Gammie, Cargill, & Hamilton, 2010; Okolie & Izedonmi, 2014) to providers of information and to being involved and highly engaged strategists in management circles and decisionmaking processes (Guthrie & Parker, 2016; Howieson, 2003; Howieson et al., 2014). Accountants may be likened to historians or journalists, only reporting on the financial transactions and events of an entity using specialist competence

Social Media, Mobile and Cloud Technology Use in Accounting: Value-Analyses in Developing Economies, 9–80 Copyright © 2020 Emerald Publishing Limited All rights of reproduction in any form reserved doi:10.1108/978-1-83982-160-820201004

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Social Media, Mobile and Cloud Technology Use in Accounting

(Gaffikin, 2009). Professional accountants are generally becoming business advisors, and this is recognised as the biggest change for accountants (Bruce, 2004). Generally, professional accountants are providers of information for informed decision and literature have underscored them as agents of social phenomenon and action, which implies that accountants’ responsibility, functions and operations are subject to professional competence requirements. A professional accountant is someone with formal education and is a member of a recognised professional association (Elumilade, 2010). Okwoli (2014) adds that a professional accountant is someone who has obtained license to practise accountancy in an economy. These views are strengthened by the definition given by IFAC that a professional accountant is a member of a PAO that is a member or associate of IFAC (IAESB, 2017). Based on these definitions, only members of indigenous professional accountants can practise in their jurisdictions and raise the need to clarify the concept of the work-practise dichotomy. For example, in Nigeria, professional accountants who are not members of ANAN and ICAN can only ‘work’ but not ‘practise’ as professional accountants; this applies across some jurisdictions of the world. There are speculations, however, that the protectionist walls erected by professional affiliations may crumble soon; how true this is and how soon it will occur is left to conjectures. In the same vein, members of a PAO that is not an associate or member of IFAC may not yet claim to be professional accountants. They may attain the status of professional accountants if their association obtains membership of IFAC or if they individually secure membership of an IFAC associate or member. In the same vein, graduate accountants without professional membership affiliations to an associate or member of IFAC may not also claim to be professional accountants, no matter their level of further education. This view is strengthened by a mantra that ‘…you are not an accountant, except you are chartered’ and ‘…if you are not a chartered accountant, you are a scattered accountant’ is humorously added (Oladele, 2015c). Some hold that this view is sympathetic and protectionist. This notwithstanding, we note a significant definition of a professional accountant as an individual who achieves, demonstrates, and further develops professional competence to perform a role in the accountancy profession and who is required to comply with a code of ethics as directed by a professional accountancy organization or a licensing authority. (IAESB, 2017, p. 21) If modified, the above definition can present a professional accountant as ‘a person…after attaining requisite qualifications, undertakes a work of a professional nature’ (Oladele, 2015c, p. 18) in an accounting field of practice, policy and/or research. Kirkham and Loft (1993) explained that a professional accountant has been construed in part, as someone that is ‘not a clerk or a bookkeeper’.

Literature Discourse

11

It is necessary to state that accountants have been characterised as dull and boring (Miley & Read, 2012) and accountants’ praxis has led to a perceived social identity of conservatism, integrity and trust; high social recognition/status; stinginess; wealth and professionalism (Oladele, 2015a). Literature is rife with the categorisation of accountants such as Beechy (1985) who posited that an accountant may be employed in business, public practice or the public or nonprofit sectors. According to Welsch, Zlatkovich, Harrison, Nelson, and Zin (1986) accountants may be involved in public accounting, industrial accounting, Government and non-profits, while Taylor (1999) elucidated that a qualified accountant can choose between working in public service or as a salaried employee of an organisation. According to Bruce (2004), professional accountants in business include those who work in commerce, industry, the public sector, education and the not-for-profit sector. Categorisation of accountants as chartered accountants, certified accountants, technical accountants and professional accountants has appeared as well in literature (Oladele, 2015c; Wessels, 2004). ‘Traditionally, practitioners have been classified as public accountants, private accountants or public sector accountants’ (Gaffikin, 2009, p. 172) and by some PAOs as members in practice and members not in practice (ICAN, 2016a). Accountants may also be summarily categorised as those ‘in public practice, education, government service, industry, and commerce’ (IAESB, 2017, p. 4). Conclusively, accountants’ responsibility is ultimately in the interest of the public, thereby fulfilling an important and unique role in society (Welsch et al., 1986). In an interesting turn, it was submitted that ‘by 1930, the “professional accountant” had come to be constituted in part, as “something that is ‘not a woman’”’ (Kirkham & Loft, 1993, p. 507). This lends credence to the gendered nature of the accounting profession. However, more recently, this prejudice and gender divide is gradually diminishing with calls transcending and challenging even gender heteronormativity into recognising the Lesbian, Gay, Bisexual and Transgender (LGBT) community and their rights as bona fide members of the profession (Rumens, 2016). Social context still portrays professional accountants, however, more as men. With more than 25 years on accounting and gendering debate, there are still evidences of gender gap (Haynes, 2017; Walker, 2008) from the perspectives of interest (Stivers, Onifade, & Reynolds, 2011), enrolment (Okpechi & Belmasrour, 2009; Stollak, Vandenberg, & Resch, 2011; Wootton & Spruill, 1994) and academic performance (Flood & Wilson, 2008; MerelloGimenez & Zorio-Grima, 2016; Okafor & Egbon, 2011); membership of PAOs, competence, influence, career success and progression (Anderson, Johnson, & Reckers, 1994; Jeake, Ebimobowei, & Binaebi, 2013; Windsor & Auyeung, 2006); career involvement (Stollak et al., 2011); participation and exit (Gammie & Whiting, 2013; Wilson-Taylor Associates Inc, 2010); pay/remuneration (Blundell, Gosling, Ichimura, & Meghir, 2007; Gammie & Whiting, 2013; Schaefer & Zimmer, 2003) and stakeholders’ perception (Lee, 2014; Walker, 2008). The odds seem to always favour the male folk (Lawter, Rua, & Andreassi, 2016) and struggle for gender equality in a gendered profession like accounting is based on the position that female professional accountants should be given equal

12

Social Media, Mobile and Cloud Technology Use in Accounting

opportunity to adequately participate and enjoy the benefits the profession offers, despite their femininity. The gendered nature of a profession can either push or pull especially professional women to self-employment, predicated on factors such as the desirability for self-paced work, work–family balance and potential for higher earnings, inability to meet career requirements, stress and dissatisfaction (Lawter et al., 2016). Despite these incentivising factors to embrace self-employment, evidence suggested that in the last decade of the twentieth century there was a substantial influx of women into the accounting profession (Khlif & Achek, 2017). The involvement of women, as well as their contributions in accounting profession, is, however, limitedly reviewed in this book. The gender debate has highlighted terms such as inclusion, diversity, balance, mainstreaming and identity, which are focal points of many feminine causes. According to Haynes (2017) the reasons for the gender gap are grouped as the gendered nature of accounting profession, motherhood, work–life balance, choices and flexible working, and feminisation and segmentation. In concluding, it may be necessary to state that many PAOs have dedicated women associations as offshoots of the main association. These associations generally cater for and keep separate records of women accountants, although participation in the women association is usually voluntary and optional.

Accountants’ Training Framework The goal of accountants’ training framework is to ensure that those entering (and those in) the accounting profession possess the professional competence and capability (Howieson et al., 2014) to function appropriately. To achieve this goal, quality assurance is one of the key methods used to ensure and guarantee the adherence to ‘good practices’ by educators. For some academic vanguards, such as tertiary institutions, formal accreditation exercises (Boyle, Carpenter, Hermanson, & Mensah, 2013; Mendivil, 2002; Okafor, 2012; Wells, 1994) carried out by statutory oversight institutions are not only common practice to earn legitimacy; they serve the purpose of a badge as a quality education provider (Ahrens & Khalifa, 2015). There is, however, a fear that such timed practices inspire stage-managed appearances (Dumbili, 2014). Another method of evaluation is the assessment of the performance of students and graduates of tertiary institutions when they undertake competence-based assessments of PAOs (Samkin & Stainbank, 2016), which is not well received by university administrators for the fear that it threatens university autonomy (Wells, 1994). Given these shortcomings, it may be necessary to review the quality of tertiary training which professional accountants receive and its influence on their technology competence and use. For accountants’ training framework to continue to be a significant contribution to accounting profession over the next decade, it is important that it is not only catching up with latest trends in ¨ technology (Guney, 2014), it should lead the trend and set the pace (Guthrie & Parker, 2016).

Literature Discourse

13

Accountants’ training framework is categorised as professional accountants’ training and academic accountants’ training (Flood & Wilson, 2008; Howieson et al., 2014). The former develops candidates to become professional accountants (IAESB, 2007) leading to membership of a recognised professional association, as a chartered or certified accountant (Wessels, 2004), and to possibly obtain a practice license (Lubbe, 2014). The latter advances the study of accounting as a science, leading up from basic academic degrees to advanced degrees (Okafor, 2012). Abdullahi (2010) provides insights into the results of both climes when he quoted Claude Balthazard that said: professional credentials are ‘warrants of competence’ or ‘warrant of expertise’ whereas academic credentials are not. With professional designations, the certifying body is warranting that the certified worker (tradesperson or professional) has the essential knowledge and skills of a specified domain necessary for safe and appropriate practice of the trade or profession. With academic credentials, there is no such ‘warrant of competence,’ an academic credential means that someone has successfully completed a particular course of study not that one is competent to practise a trade or profession. (p. 24)

Academic Accounting Education Accounting academic awards and degrees include ND, HND, B.Sc., M.Sc., MBA, MPhil and PhD. ‘Accountancy’ and ‘accounting’ are two descriptive narratives used to qualify programmes, degrees and awards (Oladele, 2015c). In addition, accountancy is used in some English-speaking parts of the world, to mean the accounting profession as used in the United States (Carnegie & Napier, 2010). Full-time and part-time options are usually available in most institutions, including weekend and distance learning options. Full-time study usually takes four years (8 semesters), which is quite different from other countries such as South Africa (Lubbe, 2016) and New Zealand (Bui & Porter, 2010) with the possibility of a three-year accelerated accounting degree programme. In some universities, apart from regular degree programmes, there is a conversion programme that allows chartered accountants without a university degree and holders of an exit/terminal polytechnic diploma award to enrol for a university degree with their professional certificate and experience, entering the second or third year of study. Proliferation of higher education, which has received recognition in literature as ‘massification’ (Keneley & Jackling, 2011, p. 605), is due largely to private ownerships of tertiary institutions (Dumbili, 2014). Apart from concerns raised on the increasing number of tertiary institutions, there are serious concerns that the quality and value-added of/by tertiary education has deteriorated significantly (Dabalen, Oni, & Adekola, 2001) and more emphasis has been on quantity and a direct undermining of the core values of quality. Dumbili (2014) conceptualised this debacle as ‘McDonaldization’.

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Social Media, Mobile and Cloud Technology Use in Accounting

Tertiary institutions are relevant because they have come to be accepted as ‘protagonist in the training of productive intellectual resources; that is to say, in the training of people and the generation of knowledge that can produce riches convertible into technology, organisational intelligence, productivity and rational consumerism’ (Mendivil, 2002, p. 353). In addition, ‘universities play a crucial role in the development of knowledge societies and are leaders in technology development and adoption in nations across the world’ (Sabi, Uzoka, Langmia, & Njeh, 2016, p. 185). Considerable evidence also validates the view that universities are significant producers of highly skilled labour (Anderson, Bravenboer, & Hemsworth, 2012; Dabalen et al., 2001; Lubbe, 2016; Okafor, 2012; Razmerita, Kirchner, & Nielsen, 2016) although other reports countervail and suggest that employers prefer polytechnic graduates with respect to technical competence (Dabalen et al., 2001). It is also argued that universities are failing in their responsibility, a view that may have been influenced in part owing to an insufficient understanding of the responsibilities and roles of universities (Howieson et al., 2014). In reviewing academic framework for the training of accountants, it is important to stress that literature has made allusions to the fact that it is ‘mainly based on theoretical knowledge which can lead to static and boring learning’ (Pedrosa, Trigo, Varajão, & Silva, 2012, p. 511) and calls for a change to processoriented learning have recently heightened (Lin, 2008; Lubbe, 2016). Another concern raised about the value of academic accounting degree/diploma (Oladele, 2015c) resonates on the fact that an accounting degree is not a critical prerequisite to becoming a professional accountant in many jurisdictions (Howieson et al., 2014; Paisey & Paisey, 2006) making it less exciting for young people. This is further exacerbated by industry preference for professional accountants to graduate accountants without professional affiliations (Oladele, 2015c; Paisey & Paisey, 2006). It is also clear from literature that over the years, accounting education research has narrowly focused on teaching and learning pedagogy and outcomes mostly in universities (Aprile & Nicoliello, 2016) significantly leaving out other higher education providers.

Professional Accounting Education Providers and vanguards of accounting education and profession are numerous and significantly diverse, yet the common interest is their collective effort towards safeguarding the public interest (Everett, Neu, & Rahaman, 2007) and preserving the integrity and social identity of the profession. From the professional plain, there are basically two broad areas of professional accounting education, that is, IPD and CPD. IPD entails the phase up to qualifying as a professional accountant, while CPD continues to maintain the professional qualification. IPD for some PAOs will usually include a professional examination or programme and practical experience, while CPD can be held as a conference (professional and/or academic), seminar, workshop, webinar, and maybe mandatory, or executive training. Some PAOs include elements of international travels as well. It is important to stress as well that credit points are

Literature Discourse

15

usually awarded for attendance and/or participation in CPD engagements, which is relevant for the exercise of certain privileges. The CPD engagements can be paid or free events and may take virtual (online, webinar) or physical forms. CPD comes in different nomenclature such as Continuing Professional Education (CPE), and can be Executive (ECPE) or Executive Mandatory (EMCPE). Many PAOs require members to obtain a minimum of thirty (30) credit hours in a year. In the international scene, IFAC through the IAESB plays proactive roles in shaping the training of aspiring professional accountants and professional accountants. Regionally, in Africa, the African Accounting and Finance Association (AAFA) and Pan African Federation of Accountants (PAFA) have been steering the ship of the training of professional accountants as well. Professional accountants’ training is controlled by PAOs (Uche, 2007; World Bank, 2011) with considerable influence of IFAC, IAESB and IES, although PAOs are self-regulating, being backed by local or national legislative statutes. The integration of professional certification options into academic degree programmes has made it possible for graduates to earn both an academic degree and professional certification (Lubbe, 2016). The need for accountants’ training framework to constantly improve (IAESB, 2013; Lindsay, 2016; Lubbe, 2016) and to remain relevant (Samkin & Stainbank, 2016) both in the tertiary (Lubbe, 2016) and professional (Wessels, 2006) arenas to meet evolving realities is valid. A significant reason is the changing and increasing stakeholder and societal expectations (Belfo & Trigo, 2013), which inspire a crisis of rising demand (Nokhal & Ismail, 2014) given that the ability to meet societal expectations in most cases is a significant source of legitimacy (Ahrens & Khalifa, 2015). Another factor is the increase in the availability and accessibility of new knowledge, influenced by new legislations, and evolving accounting and auditing guidelines (Lubbe, 2014; Paisey & Paisey, 2006). Furthermore, the changing environment in which professional accountants work, influenced by steady advancements in IT (Wessels, 2004), calls for constant review of the training framework. The IAESB gave a vivid summary of the ‘pressures for change which come from many sources including, but not limited to, (a) public expectations, (b) globalization, (c) advances in technology, (d) business complexity, (e) societal changes, and (f) increase in regulation and oversight’ (IAESB, 2015a, p. 9). To meet this evolving requirements, calls have been made for curriculum reengineering (Flood & Wilson, 2008), staff development, teaching and research resource mobilisation (Okafor, 2012), practical industry engagements (Dabalen et al., 2001; Mendivil, 2002), informal and formal CPD initiatives (Lindsay, 2016), workplace experience and the involvements of PAOs (Devonport, 2007; Uche, 2007; World Bank, 2011). There is a dynamic relationship between the academic and professional framework for the training of professional accountants and there are many areas of overlap between them as well. One of such has to do with staffing, such that chartered accountants as different from academically qualified faculty referred to

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Social Media, Mobile and Cloud Technology Use in Accounting

as professionally qualified faculty (Boyle et al., 2013) or clinical faculty (Achilles, Greenfield, & Russ, 2007) represent a significant percentage of the teaching staff in many accounting departments (Pathways Commission, 2012). The most significant reason for this practice is the shortage of academically qualified faculty (Achilles et al., 2007) and this provides opportunity for chartered accountants with robust industry experience to add value to accountants’ training (Boyle et al., 2013) and even gain access to enrol and complete the doctoral degree (Pathways Commission, 2012). Apart from this, the fact that some PAOs carry on competence-based evaluation of the graduates of tertiary institutions prompts university administrators to employ professionally qualified faculty, and based on this imperative, according to Wells (1994), is prompted to make increased demand for more financial benefits, although their requests are not always met. Therefore, the lines between academic and professional accountants’ training framework are not parallel, but meet at many points to enrich the value of professional accountants and the profession. Lubbe (2014) identified tensions experienced in the education of professional accountants, due to the multiplicity of roles that especially university accounting faculty find themselves, being torn between teaching and research. It is worthy of note that a professional accountant who intends to work in the tertiary system must not only be able to teach, she/he must do research and publish as this is used as a significant performance indicator, especially for the purpose of career progression. According to a review of literature by Birt, Wells, Kavanagh, Robb, and Bir (2018) a dynamic and highly technology-driven future work environment for professional accountants has emerged. This has therefore raised the need for research to identify strategies for closing the gap between the current training framework of accountants and what will be expected from them in their profession in the future (Wessels, 2004). Fig. 1 presents different training routes for professional accountants in Nigeria, which is like what obtains in many developing jurisdictions. The diagram is, however, not exhaustive. Table 1 and Table 2 present IFAC recognised PAOs in Nigeria and Africa. BMAS specifies minimum requirements and standards for tertiary education, while self-regulating PAOs elect to adopt and/or adapt the IES in determining minimum requirements for pre- and post-qualification competence of professional accountants. Given these standards, how professional accountants in developing economies fare as industry players, government workers, policymakers and academia, by meeting the minimum professional competence requirements with respect to IT, is of paramount concern. Based on the empirical value of technology use (competent engagement), which may be used to interpret the value of training that professional accountants receive, and a predictive analysis dependent on the accountants’ training framework, a fair comparison amongst countries in Africa and globally should be attainable. It is also important to stress that while formal academic and professional accountant’s training plays a major role, if combined with other opportunities for the development of pervasive skills for technology adoption and use, a renewed imperative for the sustained relevance of the profession emerges.

Literature Discourse

Accounting Education

Phenomenon

Categories

Tertiary accounting education

Professional accounting education

Statutorily regulated by

Educational Regulators

Board / Council

Institutions

Polytechnics

Universities

PAOs (ANAN, ICAN etc.)

ABWA (ATSWA)

Basic awards

ND, HND

B.Sc.

Associate (CNA, ACA)

Technician (AAT)

Advanced awards

Post HND, PGD

PGD, M.Sc., MBA, MPhil, PhD

Fellow (FCNA, FCA)

Fig. 1.

17

Accountants’ Training Framework in Nigeria.

Accountants’ Professional Qualification Three components (academic degree, professional examination/programme and practical experience) are global requirements in the training of professional accountants (IAESB, 2017). It should be emphasised that IFAC places premium on an accounting academic degree and recommends that it should be a minimum of, or at least equivalent to, a degree (IAESB, 2015b). It should also be noted as earlier stated that many organisations with oversight of accounting profession feel that basic degrees can only cater to professional accountants’ foundational knowledge necessary for practice, while higher degrees are essential for optimal performance (Pathways Commission, 2014b).

Accounting In medieval times, many descriptions and definitions of accounting emerged in larger global contexts based on the economic development of economies. A sociologist posited that ‘accounting rules and accounting practice are methods for measuring and assigning costs and incomes to various categories for use in information systems’ (Zald, 1984, p. 4). The history of modern accounting around the world is usually tied to the work of an Italian monk, Luca Pacioli (Guthrie & Parker, 2016; Stoner & Suwardy, 2016; Wessels, 2004), whose book opened up

18

S/N

Professional Bodies (in Alphabetical Order)

Statute-backed 1. Association of National Accountants of Nigeria 2. Chartered Institute of Taxation of Nigeria 3. Institute of Chartered Accountants of Nigeria Non-statute-backed 1. Association of Cost and Management Accountants 2. Association of Financial and Management Accountants of Nigeria 3. Chartered Association of International Accountants of Nigeria

Website

YOE

YOS

Members’ Designation

ANAN

www.anan.org.ng

1979

1993

CNA, FCNA

CITN

www.citn.org

1982

1992

ACTI, FCTI

ICAN

www.icanig.org

1960

1965

ACA, FCA, RA

ACMA

www.acma.org.ng

2000

NA

ACMA, FCMA

AFMAN

www.afmng.org

2010

NA

AFMA, FFMA

CAIAN

www.caian.org

2000

NA

ACIA, FCIA

Social Media, Mobile and Cloud Technology Use in Accounting

Table 1. Professional Accounting Organisations in Nigeria.

4. 5. 6. 7. 8. 9.

Chartered Institute of Cost and Management Accountants Chartered Institute of Finance and Control of Nigeria Institute of Certified Public Accountants of Nigeria Chartered Institute of Management Accountants of Nigeria Institute of Company and Commercial Accountants of Nigeria Institute of Forensic Accountants of Nigeria

CICMA

www.cicma.org.ng

2000

NA

ACMA, FCMA

CIFCN

www.cifcnnig.org

NI

NA

ACIFC, FCIFC

ICPAN

www.icpan.org.ng

1988

NA

CPA, FCPA

CIMAN

www.cimanigeria.com

1977

NA

ACMAN, FCMAN

ICCA

www.iccaofnigeria.org

1999

NA

ACCA, FCCA

IFA

www.ifa.org.ng

NI

NA

CFA, FFA

Notes: NI no information, NA not applicable, YOE year of establishment, YOS year of regulating statute. Source: Compilation from databases and web resources.

Literature Discourse 19

Country

1.

Benin

2.

Botswana

3.

Burkina Faso

4.

Cameroon

5.

Egypt

6.

Ghana

7. 8.

Ivory Coast (Cote D’Ivoire) Kenya

9.

Liberia

Name of PAO

Ordre des Experts-Comptables et Comptables Agr´ee´ s du B´enin Botswana Institute of Chartered Accountants Ordre des Experts-Comptables et Comptables Agr´ee´ s du Burkina Faso Institute of Chartered Accountants of Cameroon (Ordre National des Experts-Comptables du Cameroon) Egyptian Society of Accountants & Auditors Institute of Chartered Accountants (Ghana) Ordre des Experts-Comptables de ˆ d’Ivoire Cote Institute of Certified Public Accountants of Kenya Liberian Institute of Certified Public Accountants

Acronym

Status

YOE

AS

MS

OECCA-Benin

Associate

2006

2011

BICA

Member

1990

ONECCA-BF

Associate

1996

ONECCA-Cameroon

Member

1985

1998

ESAA

Member

1946

1980

ICAG

Member

1963

1982

OEC-CI

Member

1995

1997

ICPAK

Member

1978

1980

LICPA

Member

1933

1987

1984 2015

Social Media, Mobile and Cloud Technology Use in Accounting

S/N

20

Table 2. List of IFAC-recognised African PAOs.

10.

Madagascar

11.

Malawi

12.

Mauritius

13.

Morocco

14.

Namibia

15.

Nigeria

Rwanda

17.

Senegal

18.

Sierra Leone

19.

South Africa

OECFM

Member

1962

1999

ICAM

Member

1969

1983

MIPA

Member

2005

OEC-Morocco

Member

1993

2004

ICAN

Member

1990

1997

ANAN

Member

1979

ICAN

Member

1965

iCPAR

Associate

2008

ONECCA-Senegal

Member

1996

2013

ICASL

Member

1988

1995

SAICA

Member

1977

1977

SAIPA

Member

1982

1995

2007

2012

2014 1977

2012 Literature Discourse

16.

21

Ordre des Experts-Comptables et Financiers de Madagascar Institute of Chartered Accountants in Malawi Mauritius Institute of Professional Accountants Ordre des Experts-Comptables du Royaume de Maroc Institute of Chartered Accountants of Namibia Association of National Accountants of Nigeria Institute of Chartered Accountants of Nigeria Institute of Certified Public Accountants Ordre National des Experts-Comptables et Comptables Agr´ee´ s du S´en´egal Institute of Chartered Accountants of Sierra Leone South African Institute of Chartered Accountants South African Institute of Professional Accountants

22

S/N

Country

20.

Swaziland

21.

Tanzania

22.

Togo

23.

Tunisia

24.

Uganda

25.

Zambia

26.

Zimbabwe

Name of PAO

Swaziland Institute of Accountants (SIA) National Board of Accountants and Auditors Ordre National des ExpertsComptables et des Comptables Agr´ee´ s du Togo Ordre des Experts Comptables de Tunisie Institute of Certified Public Accountants of Uganda Zambia Institute of Chartered Accountants Institute of Chartered Accountants of Zimbabwe

Notes: YOE year of establishment, AS associate since, MS member since. Source: IFAC (2019).

Acronym

Status

YOE

AS

MS

SIA

Member

1985

1986

NBAA

Member

1972

1986

ONECCA-Togo

Associate

2001

OECT

Member

1982

1985

ICPAU

Member

1992

1996

ZiCA

Member

1982

1984

ICAZ

Member

1918

1981

2012

Social Media, Mobile and Cloud Technology Use in Accounting

Table 2. (Continued)

Literature Discourse

23

on, particularly, the double entry bookkeeping system, which earned him the title of the ‘Father of Modern Accounting’. Welsch et al. (1986) defined accounting as an information processing system designed to capture and measure the economic essence of events that affect an entity and to report their economic effects on that entity to decision-makers. This view is echoed by another definition of accounting as the language and science of measuring business performance (Dimitriu & Matei, 2015). According to Aprile and Nicoliello (2016) accounting has been seen as a ‘science of the economic control of the firm’ and ‘as the measuring technique of economic quantities in general’ (pp. 420, 421). Bookkeeping and accounting have been and are used interchangeably, although subject matter experts (SMEs) know better such that, for example, Wood (1972) explained that accounting extends far beyond the actual making of records as it is concerned with the use to which these records are put, their analysis and interpretation. Taylor (1999) added that the principal role of an accountant is to analyse financial records and to make judgements based on the information. Accounting, therefore, can be held as a multi-dimensional, multifaceted and multifarious set of interrelated activities, operations and functions that provide information for decision making, arming users of such information (in prescribed formats as reports and/or statements) with all necessary, relevant, reliable and timely facts essential to make adequate and informed judgments about the utilization of resources. (Oladele, 2015c, pp. 15, 16) This role is more specialised than mere bookkeeping (Wessels, 2004), ‘number crunching’ or ‘bean counting’ (Baldvinsdottir, Burns, Nørreklit, & Scapens, 2010; Bruce, 2004; Bui & Porter, 2010; Carnegie & Napier, 2010; Gaffikin, 2009; Gammie et al., 2010; Hamilton, 2013). The practise-work of an accountant whether in financial accounting, cost and management accounting, public sector accounting, auditing, taxation, financial management (Beechy, 1985; Oladele, 2015c; Taylor, 1999; Welsch et al., 1986; Wood, 1972) and other professional areas (Bruce, 2004) remains that of reporting (Belfo & Trigo, 2013). Consensus of the reporting role of accounting is not only widely shared in literature (Wessels, 2004), it is premised as well on diverse theoretical interpretations such as emanate from the agency theory (Eisenhardt, 1989; Ross, 1973; Shapiro, 2005), stakeholders theory (Hill & Jones, 1992; Wessels, 2005), stewardship theory (Donaldson & Davis, 1991), resource dependence theory, institutional theory, legitimacy theory (Chen & Roberts, 2010), public interest theory and other theories of the firm, of corporate governance, of accountability, of transparency and the like. Accounting is what accountants do and has been described as a mechanism (information system) (Oladele, 2015c). Accountants as knowledge workers (Berg, Buffie, & Zanna, 2016; Kirtley, 2016; Meall, 2016b) are in the business of providing information (Taylor, 1999; Wood, 1972) for informed decisions. This

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Social Media, Mobile and Cloud Technology Use in Accounting

role of mere information provision is, however, becoming traditional (Wessels, 2004) because professional accountants are increasingly becoming strategists, being a core in management circles, and sometimes occupying other c-suite portfolios. Accounting is also taken with hilarity as ‘am counting’ (Oladele, 2015c) and asserted as the world’s oldest profession and the final profession, when we meet our Maker – God. Accounting elements, concepts, basis, principles, processes and procedures form a system that continues to remain a globally accepted information system ¨ (Guney, 2014). This system is used for preparing and presenting financial (and non-financial) aspects of transactions and events (Oladele, 2015c) by reporting entities to stakeholders such as ‘potential and existing investors, lenders and other creditors in making decisions about providing resources to the entity’ (Barth, 2010, p. 5). The need for accounting information will continue into the foreseeable future as seen by the fact that increased calls for transparency, accountability and increased performance measurement and evaluation bestow responsibility on professional accountants. However, it seems the accounting profession is constantly unable to meet this demand, thereby seeing increased calls for restructuring of the profession. One of such calls resonated that ‘conventional accounting practices are founded on positivism, managerialism, and neo-classical economics, creating a psychic prison for the accounting discipline that fails to recognise the socially constructed nature of accounting reports and their explicit valuation role’ (Lange & Kerr, 2013, p. 210). This has led to calls for unconventional forms of reporting, in the forms of narrative reporting (Lange & Kerr, 2013), dialogic accounting (Vinnari & Dillard, 2016), innovation accounting (Nelson, 2016), confidence accounting (Harris, Mainelli, & Onstwedder, 2012; Rowe, 2014), global convergence of financial reporting standards (Crawford, Helliar, Monk, & Veneziani, 2014) and integrated reporting (Vinnari & Dillard, 2016). The information provided by professional accountants should possess fundamental and enhancing qualitative characteristics (van Beest, Braam, & Boelens, 2009) and is usually to influence informed decision-making (Elumilade, 2010; Wood, 1972). This need is reinforced by the peculiarities of prevailing circumstances and environment in which businesses and non-business entities operate. In most developing economies, the internal and external business environments where entities function and operate are affected by factors such as (1) unstable and unpredictable political climate (Dike, 2005; Markovska & Adams, 2015; Otusanya, Lauwo, Ige, & Adelaja, 2015; Shehu, 2004), (2) increasing governance requirements and legislations (ACCA, 2016; Lubbe, 2016), (3) expanding financial markets (Lubbe, 2016) and high stakes of investments by public, private as well as public–private partnership sectors. Furthermore, (4) dynamics in foreign exchange (FOREX), (5) surging risks and uncertainties (Ib, Jide, & Zik-Rullahi, 2015), (6) incomplete, inconsistent, unreliable and unverifiable information, (7) security threats and challenges, (8) poor and inadequate physical and social infrastructures, (9) environmental factors and the like. These and other factors have significant potential to change the tides and fortunes of entities spontaneously leaving accountants as professionals on the spot

Literature Discourse

25

(Nokhal & Ismail, 2014). This translates to a requirement to exhibit high levels of professional competence with high regard for sound corporate governance culture, objectivity, integrity and confidentiality to provide robust, timely, relevant and at sometimes bespoke financial and non-financial information for stakeholders’ informed decisions. This stresses the essence of a profession that is central to the effective, efficient and sustainable working of (most likely) all systems – economic, political, social and cultural – and influenced by such social systems itself (Laughlin, 2014). The need to sustain the societal relevance of the accounting profession (Wessels, 2004) given that it is multifaceted, multidimensional and multifarious (Oladele, 2015c, 2015b) and finds expression in all sectors of the economy (Taylor, 1999) underscores a profession that may not be left out of the scheme of things in organisations and societies (IAESB, 2015b) of all sizes, types, structures and objectives. These and many other factors make the accounting profession special.

Accounting Profession Accounting profession, like other acclaimed professions, has as its dominant characteristics, public service and ethics (Gaffikin, 2009) and is continuously and sustainably being influenced by the public interest theory, which has made stakeholders of the profession to continually and overtly stress that their responsibilities, engagements and priority are in the interest of the public (ANAN, 2018; Bruce, 2004; IAESB, 2017; ICAN, 2016b; IFRS Foundation, 2015; Kirtley, 2016; Stephenson, 2016). With pervasive evidence on fraudulent reporting and corruption ranging from discoveries of cosmetic reporting to public sector fraud perpetuated by and with collusion of professional accountants (Bakre, 2007; Cameron & O’Leary, 2015; Carnegie & Napier, 2010; Dike, 2005; Everett et al., 2007; Martinez-Vazquez, Arze del Granado, & Boex, 2007; Ozkul & Pamukc, 2012), this widely proclaimed thrust is questionable. In contemporary times, three elements of policy, research and practice, for the accounting profession, was established (Laughlin, 2011) and further constructed as tripartite accounting (Oladele, 2015b). Accounting policy regulates the practise of accounting (Oladele, 2015c, 2015b). There have been major changes and developments with regard to accounting policy over the past decade. These changes inspire the dynamic nature of the accounting profession, requiring the meeting of stakeholders, especially the academic and practice communities (Pathways Commission, 2012). These changes in global and local policies which significantly cut across education and practice have overarching imperatives for the accounting profession. Recent global development in accounting policy for accounting practice in many developing economies is the adoption and implementation of the International Financial Reporting Standards (IFRS), and the International Public Sector Accounting Standards (IPSAS) published by the International Accounting Standards Board (IASB) and International Public Sector Accounting Standards Board (IPSASB), for corporate and public sector reporting, respectively. The adoption of these international practice standards continues to steer curriculum

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re-engineering for tertiary and professional accounting education, as well as review of professional competence requirements and ethical considerations. Accounting research is often conceived as applied with deliberate focus on technologies and technical practices used by accounting practitioners in social and organisational settings with the aim of ‘critiquing, challenging, and engaging in debate’ (Parker, Guthrie, & Linacre, 2011, p. 8). It is noteworthy to stress that research output in the forms of various publications forms a significant requirement for academic career progression, and is an important contributor to the development of knowledge and scholarship (Wright & Chalmers, 2010). However, frameworks for impact measurement in many developing economies are inchoate, unlike in the United Kingdom with the Research Excellence Framework (REF) (Harle, 2011; Johnson, 2012; Parker et al., 2011), ‘the Excellence for Research in Australia (ERA) program, and Exzellenzinitiative des Bundes in Germany’ (Johnson, 2012, p. 13). Guthrie and Parker (2016) stated that ‘there is no question that the journey for the accounting profession, accountants and academic scholars in the next 25 years is likely to encounter turbulence’ (p. 2). Academic commentaries are optimistic about a challenging future for the practise of accounting (Birt et al., 2018). The sustainability of the accounting profession which will continue to experience transformation will continue to lie on the shoulders of stakeholders of accounting education and other vanguards of the profession. Concerns have been raised in literature about the need for coordination amongst stakeholders of the profession to secure its future (Guthrie & Parker, 2016; Laughlin, 2011; Oladele, 2015b, 2015c; Parker et al., 2011) and although ‘academic researchers pay lip service to the need for their engagement with policy and practice, for many, action in this regard simply does not happen’ (Guthrie & Parker, 2016, p. 4). The threefold custodians of accounting profession (Oladele, 2015b) will continue to regulate the work of professional accountants in diverse fields and responsibilities (Bruce, 2004) and the relationship is captured in Fig. 2. Some research and policy organisations with significant and fundamental influence over accounting profession are also highlighted in Table 3.

International Education Standards The International Education Standards (IES) is a global standard for the education of aspiring professional accountants and professional accountants. It is issued by the IAESB and published by IFAC. The IAESB is an independent standard-setting body that develops education standards, guidance, and information papers for use by IFAC member bodies and other interested stakeholders in professional accounting education such as: universities and education providers, employers, regulators, government authorities, accountants, and prospective accountants. (IAESB, 2015b, p. 3)

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ELEMENTS

SPHERE OF INFLUENCE

SPECIALISATION

CUSTODIANS

Practice

Public practice and non public practice

Industry, public sector and not-forprofit

PAOs

Policy

Standards-setting, review and implementation

Public interest protection and compliance

Regulators

Research

Research and education

Behavioural and archival research, professional and tertiary education

Regulators

Fig. 2.

Accounting Profession and Custodians.

IAESB was formerly the IFAC Education Committee (Saville, 2007) and its work is autonomous, yet with supervision from some entities. This is to ensure that its responsibility is carried out in a way to promote public interest, captured thus: Under a shared standard-setting process involving the Public Interest Oversight Board (PIOB), which oversees the activities of the IAESB, and the IAESB Consultative Advisory Group, which provides public interest input, the IAESB develops its standards and guidance. IFAC provides financial, operational, and administrative support to the IAESB. This arrangement enables the highly qualified volunteers serving on the IAESB to focus purely on its standard-setting activities. (IAESB, 2015b, p. 3) Membership and composition of the IAESB is made up of 18 volunteer board members from around the world. The 18 members are drawn equally from two major groups: practitioners and non-practitioners. Amongst the non-practitioners are at least three public members ‘who are expected to reflect, and are seen to reflect, the wider public interest’ (IAESB, 2015b, p. 3). This presents a skewed structure in favour of professional practitioners. The appointment of members is finalised by the IFAC Board, based on recommendations from the IFAC Nominating Committee and with the approval of the PIOB. Board membership follows a strict adherence to practices that ensure that public interest is served; hence members of the IAESB are required to formally declare (in writing and signed) that they will ‘act in the public interest and with integrity in discharging their responsibilities’ (IAESB, 2015b, p. 3).

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S/N

Names

Acronym

Research / education 1. African Accounting and Finance Association 2. American Accounting Association

AAFA AAA

3.

IAAER

4.

International Association of Accounting Education and Research Nigerian Accounting Association

NAA

5.

Pan African Federation of Accountants

PAFA

Policy 1.

Financial Reporting Council of Nigeria

FRCN

International Accounting Education Standards Board

IAESB

2.

Focus

Regional mobilisation National mobilisation of research and education in accounting International mobilisation of research and education in accounting National mobilisation of research and education in accounting Regional mobilisation of professional accountants Corporate reporting, disclosure and compliance in Nigeria Global education standards-setting, e.g. International Education Standards (IES)

Social Media, Mobile and Cloud Technology Use in Accounting

Table 3. Research and Policy Institutions of Accounting Education and Profession.

3.

International Accounting Standards Board

IASB

4.

International Auditing and Assurance Standards Board

IAASB

5.

International Ethics Standards Board for Accountants International Federation of Accountants International Public Sector Accounting Standards Board

IESBA

6. 7. a

IFAC IPSASB

Development of International Financial Reporting Standards (IFRS) Development of International Standards on Auditing (ISA); International Standard on Quality Control (ISQC) Development of Code of Ethics for Professional Accountants (COEPA) a

Development of International Public Sector Accounting Standards (IPSAS)

Note: IFAC is an encompassing organisation with interests in practice, education and policy.

Literature Discourse 29

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In the national scene as earlier espoused, national bodies develop guidelines (such as the BMAS) for the education of professional accountants. This caused varied standards and the need for a harmonised global standard became apparent. The IES then was conceived to serve as pronouncements which can be applied in the education of aspiring professional accountants and professional accountants by IFAC member bodies (PAOs). PAOs that complete and sign the Statement of Membership Obligations (SMOs) issued by IFAC adapt/adopt the IES in developing entry criteria, training as well as lifelong training for aspiring professional accountants and professional accountants. The IES is a set of authoritative pronouncements, yet they do not override local requirements (IAESB, 2017). Given that the IES is developed and issued by the IAESB and published by IFAC, it is essential to review the standard making process: In developing its standards, independently, the IAESB is required to be transparent in its activities, and to adhere to due process as approved by the PIOB. Board meetings, including meetings by teleconference, are open to the public, and agenda papers are available at www.iaesb.org/meetings. (IAESB, 2015b, p. 3) The IES is a set of high-profile standards for the education of accounting professionals and has been revised and redrafted overtime. The first set of IES was issued in 2001 (Saville, 2007). Supporting the IES are three International Education Practice Statements (IEPS) (IAESB, 2015b) formerly known as International Education Guidelines (IEGs) (Saville, 2007), which may be revised or replaced with non-authoritative guidance materials, due its non-alignment with the revised IES (IAESB, 2015b). Currently there are eight IES with no further plans to issue additional standards (IAESB, 2017). A list of the applicable IES are shown in Table 4. The areas of relevance of the IES to technology use are within the competence areas of IT and interpersonal and communication skills under technical competence and professional skill domains, respectively. The level of proficiency required for IT falls in the intermediate level. ‘Learning outcomes at the intermediate level relate to work situations that are characterized by moderate levels of ambiguity, complexity, and uncertainty’ (IAESB, 2015b, p. 43). The IES as specified in the International Education Pronouncements includes training requirements for IPD and CPD. The IPD components include (1) technical competence, (2) professional skills, (3) professional values, ethics and attitudes and (4) practical experience.

Expectation Gaps The gap amongst business realities, employer expectations and academic and professional curriculum has been well captured in literature (Bui & Porter, 2010; Howcroft, 2017; Pincus, Stout, Sorensen, Stocks, & Lawson, 2017; Webb & Chaffer, 2016; Wells, 2018).

Table 4. IES and Supporting Publications of the IAESB. No.

IES 1

IES 2

Effective Year

Entry Requirements 2014 to Professional Accounting Education Programs Initial Professional 2015 Development – Technical Competence

Initial Professional Development – Professional Skills

2015

Competence Area

Information Technology

Interpersonal and communication

Level of Proficiency

Learning Outcomes

Intermediate

i. Analyze the adequacy of general information technology controls and relevant application controls ii. Explain how information technology contributes to data analysis and decision making iii. Use information technology to support decision making through business analytics Intermediate i. Display cooperation and teamwork when working towards organizational goals

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IES 3

Name/Title

31

32

Table 4. (Continued) Name/Title

Effective Year

Competence Area

Level of Proficiency

Learning Outcomes

ii. Communicate clearly and concisely when presenting, discussing and reporting in formal and informal situations, both in writing and orally iii. Demonstrate awareness of cultural and language differences in all communication iv. Apply active listening and effective interviewing techniques v. Apply negotiation skills to reach solutions and agreements vi. Apply consultative skills to minimize or resolve conflict, solve problems, and maximize opportunities. Present ideas and influence others to provide support and commitment

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No.

IES 4

IES 5

IES 6

IES 7

IES 8

2015

2015

2015

2014

2016

Information technology

Advanced

Evaluate the information technology (IT) environment to identify controls that relate to the financial statements to determine the impact on the overall audit strategy

Literature Discourse

Initial Professional Development – Professional Values, Ethics, and Attitudes Initial Professional Development – Practical Experience Initial Professional Development – Assessment of Professional Competence Continuing Professional Development Professional Competence for Engagement Partners Responsible for Audits of Financial Statements

33

34

Supporting Publications Short Name

Framework

IEPS IEPS 1

IEPS 2

Full Name

Framework for International Education Standards for professional accountants and aspiring professional accountants International Education Practice Statements Practical Experience Requirements – Initial Professional Development for professional accountants Information technology for professional accountants

Objective(s)

Establishes the concepts that the International Accounting Education Standards Board (IAESB) uses in its publications Assist in implementing generally accepted good practice in learning and development for professional accountants

Provides guidance for IFAC member bodies and other educators in implementing strategies in relation to the IT knowledge component of pre-qualification professional accounting education programs and further development of IT knowledge and competences postqualification

Social Media, Mobile and Cloud Technology Use in Accounting

Table 4. (Continued)

IEPS 4 IEIP IEP IEP IEP IEP

1 2 3 4

Approaches to developing and maintaining professional values, ethics and attitudes International Education Information Papers

Critically assess emerging learning and development issues and practices Recognition of Pre-Certification Education Providers by IFAC Member Bodies Towards Competent Professional Accountants Assessment Methods Approaches to the Development and Maintenance of Professional Values, Ethics and Attitudes in Accounting Education Programs

Source: IAESB, (2007, 2017) and Saville (2007).

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Social Media, Mobile and Cloud Technology Use in Accounting

It is believed that the primary goal of academic and professional accountants’ training is to develop capability and competence (Howieson et al., 2014), yet in fact it faces expectation gaps (Bui & Porter, 2010; Chaffer & Webb, 2017; Webb & Chaffer, 2016). Tertiary institutions, especially universities, are faced with an expectation gap that results in an ‘unrealistic demand’ for the production of workready accounting graduates (Ali, Kamarudin, Suriani, Saad, & Afandi, 2016; Bui & Porter, 2010; Flood & Wilson, 2008; Gambin & Hogarth, 2016; Gammie et al., 2010; Howieson, 2003; Howieson et al., 2014; Kaplan, 2011; Lin, 2008; Simons & Riley, 2014; Tucker & Schaltegger, 2016; Webb & Chaffer, 2016). Professional accountants’ training likewise faces the same problem of relevance of professional accountants, which has led to continuous curriculum reengineering, increased supervision and compliance check, CPD (Lindsay, 2016) and other initiatives to ensure that the standard and social status of the profession does not fall below expectation. Tertiary institutions and PAOs continue to churn out graduate and professional accounting and finance professionals (Okafor, 2012), yet there are critical reservations about their quality (Dabalen et al., 2001; Parker et al., 2011). One high point was clearly stated in literature and resounds thus: After more than 50 years of producing university accounting graduates, we are still being told that universities produce narrowly educated and focused graduates who can produce bank reconciliations, but cannot think critically. (Parker et al., 2011, p. 7) Skill deficiency amongst accounting professionals has been identified and is receiving significant attention in literature. Employers have been complaining about the quality of higher education graduates, especially university graduates (Dabalen et al., 2001; Simons & Riley, 2014), and the run-off of the millennial corporate scandals with accountants and auditors at the middle (Ali et al., 2016; Bakre, 2007; Okolie & Izedonmi, 2014) is no longer news. In addition, there are growing cases of corruption especially in the public sector under the noses of accountants and auditors (professionals) (Asongu, 2013; Dike, 2005; Markovska & Adams, 2015; Shehu, 2004). In the wake of the global financial crisis, it was even suggested that ‘it would be fair to say that there are accountants who have not acted in a truly professionally responsible manner’ (Gaffikin, 2009, p. 172). Furthermore, accountants’ significant role of ensuring accountability (Everett et al., 2007) and safeguarding assets has been bastardised into that of transmission channels and advisers in the ‘burial’ of embezzled funds (Gaffikin, 2009; Markovska & Adams, 2015) as well as major players in global tax avoidance scandals (Samkin & Stainbank, 2016). The above are but a few of the triggers for confirming accountants’ greed, which may be admitted in some way as a proxy for incompetence. This unacceptable status quo has heralded calls for change, reorganisation, reviews and other nomenclature amongst stakeholders, which inspire a dynamic approach to accountants’ training as an imperative and drive for the maintenance of the profession’s relevance and sustainability. If this is not

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achieved, the desire to preserve the social identity of the profession may be jeopardised, as espoused by the theory of inspired confidence (Okolie & Izedonmi, 2014). As a significant international policy stakeholder, the IAESB continues to emphasise ‘good practices’ in the education and development of professional accountants (IAESB, 2007). This has and is reinforcing the training of accountants such that the emphasis on ‘good practices’ concerning IPD (IAESB, 2015b), and CPD (Lindsay, 2016), curriculum updates, reviews and re-engineering is on the front burner in many discourses and fora. It may be true to assert that the business community and accounting practice are the most potent forces pushing for changes in accounting education; however, the challenge for tertiary institutions to produce ‘employment-ready graduates’ is on the rise (Dabalen et al., 2001; Okafor, 2012; Webb & Chaffer, 2016). This notwithstanding, the gaps, which result from students’ perceptions of accounting programmes and the profession, their ability and aptitude (Oladele, 2015b, 2015c), differences in the expectations of accounting academics and employers; institutional constraints and the ineffectiveness of university teaching (Bui & Porter, 2010), are nonetheless widening. One particular risk challenging the relevance of professional accountants is driven by constantly evolving technological advancements (Meall, 2016b; Wellisz, 2016) as it continues to widen the knowledge gap and poses continual challenge for professional accountants who need to constantly update their knowledge to stay relevant or face evident obsolesce. Apart from this, there are evidences of shortage of accountants world over like in the United States (Hammond, Danko, & Braswell, 2015), Australia (Jackling & Keneley, 2009), Malaysia (Mohd Nor, Mohd Zaini, & Md Zahid, 2013), South Africa (Lubbe, 2014) and Nigeria (World Bank, 2011). Efforts are being geared towards increasing the number of accounting and finance professionals, world over, as well, while faced with another impending challenge of machines springing up to take up more human jobs. In Nigeria, for example, there are many indigenous PAOs, including foreign ones competing for relevance and producing ‘competent professionals’, which raise a fundamental concern as to what jobs they are being groomed for, in the face of the experience with the same jobs that are being taken away by machine revolution. The need to query technology as a catalyst for inspiring a knowledge and/or supply gap, the strategies and coping patterns of providers of accounting education and vanguards of accounting profession as well as their outcomes is therefore evident. Due to the changing environment in which professional accountants work (Carnegie & Napier, 2010; Wessels, 2005), the expectation of employers is changing as ‘employers of labour expect universities to turn out accounting graduates who have acquired reasonable levels of accounting skills to enable them add value’ (Okafor, 2012, p. 206) immediately they are employed. Stakeholders are taking active roles in bridging the gap; it is also imperative to underscore the contribution of technology that is succeeding in adding a twist to the dimensions. Rudimentary assignments such as bookkeeping are being taken over by IT-driven AIS (Uthman, Ariyo, Abdul-Baki, & Mohammed, 2014). In addition, corporate

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Social Media, Mobile and Cloud Technology Use in Accounting

entities now cross national borders in what is fast becoming a global village, in search of professionals with requisite skills and competence to reduce cost of hiring high-priced labour (Guthrie & Parker, 2016). We may still be in doubt as to what factors explain these gaps. Technology inspires the need for regular update of knowledge and competence (Lindsay, 2016; Murphy, 2016; Wessels, 2004, 2005, 2006) but the ‘need’ to increase the supply of accountants despite technological solutions looks illogical, given tendencies for attrition. It is, however, important to note a wide gap between the number of entities requiring the services (demand) of accountants and the supply of accountants (World Bank, 2011) and also the need for human contact in organisations (Ahadiat, 2005), which may be significant explanatory factors. Stakeholders and vanguards of accounting education and profession are forging a peculiar stance towards bridging the knowledge and supply gaps. Key PAOs are striving towards the maintenance of high standards and reaching for international best practices in examination and assessment, continuing education (lifelong learning) and monitoring to ensure adherence and compliance with professional behaviour and a significant pursuit of a unique social identity. Tertiary institutions are re-engineering curriculum and aligning with professional associations, industry and the public sector (Mendivil, 2002), thereby enhancing graduates’ relevance. A suggested remedy to the shortage of IT competence amongst professional accountants places responsibility to engage them such that they acquire and continue to possess high levels of technical competencies, a robust edge on ethical considerations and other pervasive skills needed in both business and nonbusiness terrains. These skills may be acquired by definitive engagements with the requirements of being a professional accountant: academic degree, professional examination and practical experience (Gammie et al., 2010) and may be optimised through higher education (Pathways Commission, 2014b) and CPD. Technology use in business is widespread (Ahmed, 2003; Worrell, Bush, & Di Gangi, 2014) and provides platforms to achieve effectiveness, efficiency and sustainable productivity, yet it continues to threaten the accounting profession as it does to other professions (Samkin & Stainbank, 2016). This notwithstanding, there is empirical evidence, albeit insufficient for the purpose of generalisation, to suggest that some professional accountants are not exactly tech-savvy (Tarmidi, Rasid, Alrazi, & Roni, 2014). Conclusively, the Pathways Commission (2012) asserted that ‘numerous commissions over the past 70 years have agreed that the complexity and scope of knowledge accountants are expected to master require additional higher education’ (p. 19). This may be the missing link to shoring up competence amongst professional accountants.

Professional Competence Attention has been drawn to the issues of technology competence and how accounting education helps to deliver pedagogy to enhance accountants’

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professional use of emerging technologies (Pincus et al., 2017; Wessels, 2004, 2005, 2006). The IES stipulates professional competence to be obtained and maintained by professional accountants. Yet the evolving nature of technology raises a concern on the maintenance of professional competence by professional accountants, and this is usually taken care of through CPD (Lindsay, 2016). The IASB in a document published to accompany the conceptual framework for financial reporting reported that ‘some constituents suggested that advances in technology may make general purpose financial reporting obsolete’ (IFRS Foundation, 2010a, p. B4); hence the threat to professional accountants is real (Wellisz, 2016). Technology is driving competence requirement to an extreme, where professional accountants are now required to not only use technology, but be part of policy development and maintenance (ACCA & IMA, 2015), as well as technology infrastructural design and review (IAESB, 2007). Wessels (2004) stressed the imperative of accounting education in influencing the development and maintenance of IT professional competence amongst professional accountants. Professional competence is the ability to perform a role to a defined standard. Professional competence goes beyond knowledge of principles, standards, concepts, facts, and procedures; it is the integration and application of (a) technical competence, (b) professional skills, and (c) professional values, ethics, and attitudes. (IAESB, 2015b, pp. 9, 39, 48, 61, 179) This definition implies that knowledge and learning dynamics (accounting education) that determine and influence professional competence and issues such as require the demonstration of values, ethics, attitudes and other pervasive skills required by professional accountants may transcend classroom environments (Lubbe, 2016; Palmer, Ziegenfuss, & Pinsker, 2004; Samkin & Stainbank, 2016). Professional competence standard for professional accountants with respect to technology includes an understanding of one or a combination of the roles of a designer, manager and evaluator of information systems (IAESB, 2007). It is grossly insufficient for professional accountants to possess mere computer appreciation and use skill; ‘accounting education should provide students not only with the IT knowledge and skills required, but also with the know-how that enables students to apply those skills’ (Nokhal & Ismail, 2014, p. 47). Dabalen et al. (2001) advanced that productivity is driven by the ability of skilled labour to adopt new skills and technologies, and skilled labour is a function of higher education (Razmerita et al., 2016). These submissions stress the value of accounting education in the development of professional competence. Technological advancement in the form of cognitive computing (CC), machine learning and artificial intelligence (AI) and the like now threaten the jobs of accountants, world over (Meall, 2016b). As accountants continue to compete for machine jobs in what is now termed the ‘second machine age’ (Berg et al., 2016; Wellisz, 2016) and the war toughens, accountants are beginning to give overarching relevance to one professional quality they have traditionally carried

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Social Media, Mobile and Cloud Technology Use in Accounting

along – professional scepticism (ACCA, 2016; Berg et al., 2016; McKinney, Yoos, & Snead, 2017; Meall, 2016b) as well as professional judgement. Professional scepticism and professional judgement according to the glossary of terms of the International Auditing and Assurance Standards Board (IAASB) are explained: Professional scepticism—An attitude that includes a questioning mind, being alert to conditions which may indicate possible misstatement due to error or fraud, and a critical assessment of evidence. Professional judgment—The application of relevant training, knowledge, and experience, within the context provided by auditing, accounting, and ethical standards, in making informed decisions about the courses of action that are appropriate in the circumstances of the audit engagement. (IAESB, 2015b, p. 22) One major challenge of CC and AI technology which accountants by their professional competence can leverage is well captured by Meall (2016b) when she explained that machines still need educating. Her position to a question by a sophisticated user such as ‘what tablet is appropriate for me?’ would largely depend on the location of the user, which may be a pharmacy or a phone store. The use of accounting information even as prepared and presented using emerging technologies is beyond the figures (Wood, 1972). It transcends into how financial figures affect the environment – green accounting (Chen & Roberts, 2010) – and how they affect the social well-being (using the lens of welfare approach) of host communities and the public through corporate social responsibility (CSR) (Cullinan, Mahoney, & Roush, 2016) and other stakeholders as well as their endeavours. It also translates into the sustainability of the going concern (Berglund, Herrmann, & Lawson, 2018; Friis & Nielsen, 2010). These are few qualitative variables that are now being factored into accounting strategies, with, for instance, recent calls for integrated reporting (IR) (ACCA & IMA, 2015; Deegan, 2016; Guthrie & Parker, 2016; IAESB, 2015c; Vinnari & Dillard, 2016). This translates to increased professional competence requirements for professional accountants.

Technology Technology appears as a general term used to explain automation of processes, operations and functions. It is the possible delivery of machinery to ease the performance and activity. The use of technology is more prevalent when innovation is easily acceptable (adoption) and its diffusion amongst organisations depends largely on many facilitating factors such as affordance, infrastructure and know-how. Technology includes hardware and software and covers an array of infrastructures. Information technology consists of ‘hardware and software products, information system operations and management processes, and the human resources

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and skills required to apply those products and processes to the task of information production and information system development, management and control’ (IAESB, 2015b, p. 134). Information technology is diverse and its application in accounting function is numerous. Technology use amongst professional accountants pervade all areas of their professional and personal engagements, and as such, modern professional accountants ‘use email to communicate, search engines to perform research, and accounting software to record and analyse financial transactions for decisionmaking’ (Boulianne, 2014, p. 23). The use of technology in business is pervasive (Worrell et al., 2014) and beneficial, but can also be destructive. A quote credited to Noam Chomsky defined technology in this manner: Technology is basically neutral. It’s like a hammer… the hammer doesn’t care whether you use it to build a house or a torturer uses it to crush somebody’s skull… same with modern technology [like] the Internet. The Internet is extremely valuable if you know what you’re looking for. (Taiwo, 2018, p. 1) In addition, it has been regarded as a timesaver (Dimitriu & Matei, 2015) and a timewaster amongst employees (Wellisz, 2016) as well as a distraction amongst students (Khan, Kend, & Robertson, 2016). These benefits and challenges are summarised thus: Digital technology has given us comforts and conveniences that could scarcely be imagined even a generation ago…The benefits of the digital age are tempered by the risks… Digital distraction and its cousin, information overload, are taking a growing toll on productivity as new technologies spread across the globe and the knowledge economy expands. (Wellisz, 2016, pp. 14, 17) Studies have linked investments in technology to economic growth (Stork, Calandro, & Gillwald, 2013), while Brandas, Megan, and Didraga (2015) linked financial gain in respect of Return on Investment (ROI) and reorganisation of business strategy to the adoption of mobile technology and IT resource acquisition has been linked to firm performance (Uthman et al., 2014). These results suggest increase in IT staffing competence potentially increases performance. With few data requirements, manual computation albeit burdensome was used, but with business expansion and globalisation of trade leading to increased data – big data (Birt et al., 2018) – this responsibility became enormous such that computer-assisted systems were developed to overcome the challenge (Wessels, 2004). At inception, it was easy for ‘technical experts’ to build, manage and administer technological systems, but with the enormity of the responsibility, technology developers moved towards enhancing end-user accessibility and use (Ardito, Buono, Costabile, Lanzilotti, & Piccinno, 2012; Kreie, Cronan, Pendley,

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& Renwick, 2000), which bestows a responsibility on users of technology to learn and continue to learn their use to aid efficient and sustainable outcomes. Based on the need for end-user application of technology-assisted systems, training became imperative and the responsibility for this challenge gallantly fell on the shoulders of educators, as usual, with most new knowledge. Educators began to design ways to teach technology to end-users to ensure that they acquire the necessary technology competence to function appropriately (Pincus et al., 2017). Developers of technological systems request feedback to improve their systems, which is evidenced with updates and upgrades to existing systems. As with all other professions, technology has transformed and disrupted the practice of accounting and continues so to do. The accounting information system (AIS), whose bedrock is bookkeeping, started out with the use of crude items, which later according to Wood (1972) transformed to the use of manual bookkeeping. According to Wessels (2004) the manual bookkeeping was basically about the provision of information on financial inflows and outflows as well as outstanding balances. The practice of accounting is built around AIS that provides information to users for decisionmaking such that it is expected that professional accountants are able to provide information to users in formats that are generally acceptable across global jurisdictions in any specialty (Ahmed, 2003). It is therefore expected that professional accountants can competently engage technology for professional engagements. AIS became supplemented with technology such that computerassisted AIS has been developed over time in the forms of eXtensible Business Reporting Language (XBRL) (Ogundeji, Oluwakayode, & Tijani, 2014), spreadsheet applications (Bradbard, Alvis, & Morris, 2014), computer-assisted auditing tools and techniques (CAATTs) (Belfo & Trigo, 2013) and the like. Technology use affords many benefits for accounting profession, yet critical fear factors include information overload (Wessels, 2004), trust (Akinwunmi, Olajubu, & Aderounmu, 2015, 2016), overtrust (Hardr´e, 2016), threats to security and safety (Worrell et al., 2014) and complacency and phobia (Ahadiat, 2005; Humphrey & Beard, 2014; Kearns, 2016; Orr, Williams, & Pennington, 2009; Watty, McKay, & Ngo, 2016). Other critical challenges of technology to specific accounting issues are in the areas of ‘external and compliance reporting, strategic analysis, benchmarking, forecasting, internal auditing, internal controls, risk management, access and report on nonfinancial data, analysis of historical data, provision of tailor-made and interactive reporting’ (Belfo & Trigo, 2013, p. 539). Despite the significance and associated benefits of technology use, it is significant to restate that professional accountants must not be caught in the web of technology overtrust, especially in a ‘rush to use and implement new digital technologies without really understanding them’ (Hardr´e, 2016, p. 85). The use of IT by businesses is no longer news (Worrell et al., 2014) as it pervades all areas of business functions, activities and operations, although some businesses are still comfortable with manual accounting systems, while some are returning to manual systems, due to the failures of technology (Hardr´e, 2016). Yet many small businesses are taking advantage of technology (Brandas et al., 2015; Gupta, Seetharaman, & Raj, 2013; Sultan, 2011; Wessels, 2006) due to its

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financial advantage and technical functionality. According to Worrell et al. (2014) risks that affect the use of IT by organisations are called IT risks which are ‘the risk that an organisation’s information systems will not adequately support the organisation in achieving its business objectives, sufficiently safeguard its information resources, or deliver accurate and complete information to its users’ (p. 2). Despite the contributions of technological applications towards business efficiency, enhancing team work, trust, integrity and ethical values (Uthman et al., 2014), risk stands as one of the challenges associated with its adoption and use. These risks include cyber security, theft, digital distraction and information overload (Wellisz, 2016), new technology adoption challenges, digital inaccessibility, infrastructural inadequacy and trust.

Social Media, Mobile and Cloud Technology Social media, mobile and cloud (SoMoClo) technologies have significant potential for accounting activities and operations (ACCA & IMA, 2015). It is even helping entities meet the ever challenging real-time corporate financial reporting requirements (Belfo & Trigo, 2013). Furthermore, it has the potential of helping policymakers socialise as well as helping educators engage more innovative teaching and learning systems to achieve effective, efficient and sustainable learning outcomes. Despite its benefits, it is tempered by risks (Wellisz, 2016) requiring professional accountants’ expertise to analyse and provide guidance, thereby driving the evolving role of professional accountants (ACCA & IMA, 2015). While social, mobile and cloud technologies (‘SoMoClo’) offer great opportunities to continue the automation of processes, SoMoClo should not be seen simply as more automation. Nor is it merely about ‘mobilising’ or ‘socialising’ existing processes and putting them in the cloud. Instead, SoMoClo provokes a revisiting and questioning of all processes, which may have evolved in response to constraints that no longer exist. SoMoClo will be a crucial driver to evolving the role of the finance professional. (ACCA & IMA, 2015, p. 10) As we watch for the evolution and unfolding of more precise AI systems and other bespoke technological releases, professional accountants face a global driver for the coming century – SoMoClo technologies (ACCA, 2016). These technologies are shaping the way business is done globally (ACCA & IMA, 2015; Meall, 2016b) and professional accountants as key participants in the business world (Bruce, 2004; Carnegie & Napier, 2010; Deegan, 2016; IAESB, 2015b; Wessels, 2006) should be familiar with its workings and use (ACCA & IMA, 2015). Social media is gaining steady acceptance as formal channels of communication in formal organisations and used in interactions within, between and amongst corporate entities and governments. Mobile technology is liberalising the idea of

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the workplace and space such that people have access to do official business on the ‘go’, especially when combined with the possibilities that the cloud affords (Brandas et al., 2015). Needless to state therefore that an enquiry into the competent engagement of a burgeoning technology tool by professional accountants has significant implications for accounting education policy, strategies and outcomes and invariably professional accountants and the profession. SoMoClo was coined by the Aberdeen Group and it describes the interconnectivity, convergence, interaction and overlapping of social, mobile and cloud technologies (ACCA & IMA, 2015). SoMoClo has come to stay as a conglomerate of ICT advancements (Zlateva & Velev, 2012) and viable solutions for business growth and development. The Executive Chairman, Raffles Campus Pte Ltd. and Chairman, ACCA Accountancy Futures Academy, Ng Boon Yew, provides insights on SoMoClo technologies. He stated that ‘the most powerful processing technology can be accessed from almost anywhere. Individuals can share knowledge and work together across business and geographical boundaries with ease. Data is no longer locked away and out of date, but is on tap’ (ACCA & IMA, 2015, p. 7). A dynamic relationship exists amongst these three technologies as they interact in an interestingly interlocking fashion, relying on each other for optimal effective functioning. In addition, all three technologies are relevant to the business of professional accountants. Issues mostly considered before the adoption and use of SoMoClo technologies include (but not limited to) reliability, availability, confidentiality, integrity, safety and privacy (Huang & Nicol, 2013). There are evidences that organisations that do not officially approve of the use of SoMoClo technologies are missing out, as their employees use them anyway (ACCA & IMA, 2015) and may be used on official time leading to reduced employee productivity. It is also noteworthy that some organisations do not allow use of personal gadgets for official assignments and the visiting of specific sites during official time and on official devices, but these boundaries are gradually fading with the proliferation of Bring Your Own Device (BYOD) framework in place (ACCA & IMA, 2015; Accountancy Futures Academy, 2013; Bankosz & Kerins, 2014; Gupta et al., 2013; Zlateva & Velev, 2012) or the more specific Bring Your Own Laptop (BYOL) approach. Given the usefulness of SoMoClo technologies, organisations commit to manpower development with respect to the use of these technologies to forestall gross financial and goodwill losses to the organisation, due to unethical and improper use. ACCA and IMA (2015) interviewed some experts and a particularly informative response was from James Potter, who lamented that: …although SoMoClo offers great opportunities to make financial data more readily available to the wider business, that does not mean that users will automatically be empowered or have the necessary expertise or context to interpret and use that data… In addition businesses are caught between a rock and a hard place when it comes to encouraging staff to contribute to social media: it is becoming increasingly noticeable how poorly branded and

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presented individual pages are on social media such as LinkedIn compared with the carefully monitored ‘official’ Web presence. Unprofessional-looking profile photos, profane language, and failures of basic grammar and presentation are widespread. (ACCA & IMA, 2015, pp. 23, 24) James Potter’s lamentation resounds the evidence amongst accounting students, graduate accountants and even professional accountants, who have been found to be deficient in oral and written communication skills (Simons & Riley, 2014) and of many Nigerian graduates (Dabalen et al., 2001). This is heightening calls for social and communication skill development amongst professional accountants. Further shockingly, James continues that: …people don’t seem to realise that their professional profile on LinkedIn can impact their company’s brand, value and reputation. There are literally thousands of ‘profesionals’ and ‘mangers’ on LinkedIn. I’ve even found over 200 accountants in the UK who cannot spell ‘accountant’ correctly! (ACCA & IMA, 2015, p. 24) The adoption of SoMoClo technologies inspires changing professional competence requirements for professional accountants (IAESB, 2015b) evident from scholarly narratives. Many authors are advocating that the future accountant will require not only strong analytical skills, other pervasive skills but in addition, strong communication skills (Buckless & Krawczyk, 2016; Howieson et al., 2014; Paisey & Paisey, 2006; Simons & Riley, 2014; Wessels, 2004). Another issue of interest is if SoMoClo technologies will result ‘in a deskilling and depopulation of finance or a dispersal into more business-facing roles and a new more strategic and advisory role’ (ACCA & IMA, 2015, p. 23). SoMoClo technologies challenge manpower provision and is challenged by the ‘freemium’ model because it is almost free and when it is not, it is practically cheap although it requires more commitment (ACCA & IMA, 2015). Cloud and social media have received greater attention than mobile in accounting research literature, although social media has been reviewed more in the practice field than by academics, and practitioners and educators have been more the subject of enquiry, while policy accountants have been less studied, if at all.

Social Media Social media which is a form of hedonic IT (Qahri-Saremi & Turel, 2016) is a platform for networking and interaction (Khan et al., 2016). Popular examples of social media platforms include 2go, BlackBerry Messenger (BBM), Facebook, Google1, Imo, Instagram, LinkedIn, Pinterest, Skype, Snapchat, Twitter, WhatsApp, Yahoo Messenger and YouTube. Many organisations now encourage their employees to communicate and interact using social media platforms such as the popular ones, or bespoke/proprietary platforms such as Microsoft’s

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Yammer/Outlook or Lotus Notes (ACCA & IMA, 2015) also known as enterprise social media platforms (Razmerita et al., 2016). The benefits of social media include its ability to facilitate management and externalisation of both personal and organisational knowledge (Razmerita et al., 2016). These transformations have become relevant to the work of professional accountants such that critical financial information can be communicated to stakeholder groups before the final publication of corporate financial statements and reports. This can potentially reduce incidences of insider trading, since vital investment information required for investment decisions is in public space and on time. It is also proving to reduce the cost of paper printing and postages. Organisations are now advocating and imploring clients to opt for email-only notifications of transaction alerts on their accounts. No doubt corporate entities, even governments have embraced the use of social media for communication and publicity (ACCA & IMA, 2015), and it is enjoying political patronage. It has assumed an effective communication platform for governments to relate matters of national interest and it is widely used in political circles for election campaigns (Kalsnes, Krumsvik, & Storsul, 2014; Lorentzen, 2014). Policymakers are using social media platforms to convey critical decisions, to solicit views from stakeholders and identify issues pertaining to request for opinions on exposure drafts and calls for discussion. In corporate communications, social media is playing a significant role as it helps to ascertain the availability status of users before communication begins. According to ACCA & IMA (2015) ‘the proliferation of voicemail has made phone contact a hit and miss affair but now people can check each other’s availability before calling’ (p. 21). There are some concerns about the use of social media platforms by businesses and governments. ACCA and IMA (2015) is of the opinion that finance professionals may be unwilling to expose themselves on social media despite its potential for enterprise goodwill and other strategic communication benefits, and others still consider it an informal mode of communication. In a study referred to by Wellisz (2016) social media is listed as one of the time wasters during office hours. Social media platforms have been used to tarnish personal and corporate image as well as boost business goodwill (Favreau, 2014), and have been used successfully in crime investigation (D. Smith, 2013). In the education sector, there are concerns that social media use may be an ‘evil’ with evidences of misuse amongst students abounding (Khan et al., 2016). This concern resonates amongst employees (Wellisz, 2016). However, these fears may have to be taken with caution because they are mostly influenced by news from popular media and news networks. The use of social media by accountants should forge a new direction of professionals engaging the world of technology with a different level of professionalism and leading the way in keeping up with best practices. Social media is a communication platform and its use has been extended from personal and social interactions to corporate use such that organisations now feel comfortable to disseminate vital information through, for example, Twitter, while human resource units now feel obliged to use LinkedIn as part of their recruitment process. The importance of these technology platforms

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to accountants is hinged on the core principle of accountants’ ability to efficiently and effectively articulate and disseminate financial and non-financial information to various classes of users (clients, owners, third parties etc.). As highlighted earlier, communication skill shortage amongst accountants (Simons & Riley, 2014) further stretches a competence requirement, and apart from being able to interface with social media (technical skill), other considerations such as ethical use bordering on information security and privacy are significant. Social media studies amongst students (Hamid, Bukhari, Ravana, Norman, & Ijab, 2016; Hong et al., 2016; Khan et al., 2016; Lee, Chen, & Chan, 2017; Stainbank & Gurr, 2016), businesses (Agostino & Sidorova, 2017; Cawsey & Rowley, 2016; Dijkmans, Kerkhof, & Beukeboom, 2015; He, Wang, & Akula, 2017; Razmerita et al., 2016; Zhang, Omran, & Cobanoglu, 2017), politics (Kalsnes et al., 2014) and others (Haustein, Sugimoto, & Larivi`ere, 2015; Kaplan & Haenlein, 2010; Zhan, Sun, Wang, & Zhang, 2016) abound. However, it is surprising that there are little empirical studies as it relates to professional accountants’ use.

Mobile Technology Mobile technology can be viewed in two ways. First, it can be viewed as a service platform and second, as an infrastructure platform, where applications can be built on to function. Mobile technology can also be considered from three categories, that is, devices, operating systems and applications. Common devices are mobile phones, smart phones and tablet as well as other handheld devices such as PDA. Popular operating systems include Android, BlackBerry, iOS, Windows, Symbian and Java. Applications include mobile payments systems, automatic documents entry system, mobile customer service and mobile accounting service (Brandas et al., 2015). There is evidence of the increasing adoption of mobile devices in African countries (Adomi, 2005b; Stork et al., 2013) as well as a mobile divide compared to more developed nations (Zhang, 2017). For example, GSM services commenced in Nigeria in 2001 (Adomi, 2005b). There is also evidence of significant differences between the comparative statistics of mobile technology infrastructure and use (GSM) and internet penetration and use (Adomi, 2005a) in Africa and, for example, North America, which shows significant gap that lends credence to the argument on the digital divide between developed and developing countries (Zhang, 2017). It should also be noted that the mobile phone diffused rapidly than many other technologies in recent decades (Zhang, 2017). Businesses are going mobile (Brandas et al., 2015), and many applications (apps) both online and offline now operate on mobile devices such that subscribers can perform almost all functions of the desktop application on their mobile phones and this has led to an increase in the number of mobile applications on prominent online stores like the Android Store, Amazon, Apple Store, BlackBerry World (closing down), Google PlayStore, Windows Store and others. The increased use of mobile technology may be due in part to the proximity and portability of mobile devices compared to other big-sized

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devices such as desktop PCs. Other peculiar factors include the compact nature of mobile devices, low cost of acquisition and easy availability (Bakhsh, Mahmood, & Sangi, 2017). It may be significant to posit that it has been found that the ‘most significant features of mobile technology are mobility and portability’ (Liang, Huang, Yeh, & Lin, 2007). There is even empirical evidence to suggest that mobile device use statistics far surpass the use of other IT gadgets (Adomi, 2005b; Stork et al., 2013). Significant advantages of the mobile environment are in its operational requirements which include fewer ICT skills requirement, less financial resources and less reliance on electricity (Stork et al., 2013). The mobile environment coupled with cloud services allow the use of multiple devices and enable users to synchronise with all interconnected devices. This means that a user can access the same information on all devices at the same time, hence overcome problems related to performance, environment and security (Brandas et al., 2015). Mobile payment systems and mobile systems for capturing data in the forms of mobile payments, automatic document entry, mobile customer service and mobile accounting service are some of the dimensions of mobile technology (Brandas et al., 2015) relevant to the work of accountants. Practicing accountants use mobile technology to make real-time reporting possible, thereby supporting communication with their current and potential investors, creditors, fiscal or regulatory authorities. This significantly increases information availability to a wider range of stakeholders and thus the attraction in the organisation (Belfo & Trigo, 2013) as well as profitability (Liang et al., 2007). Mobile technology also provides a platform for varied activities, but it is basically an infrastructural facility that enhances all other activities. Social media and cloud technology usually depend on and is built into mobile technology. Mobile technology studies have appeared to favour educational use (Bomhold, ¨ 2013; Kutluk & Gulmez, 2014; Richardson, Dellaportas, Perera, & Richardson, 2013), business use (Bankole & Bankole, 2017; Bankosz & Kerins, 2014; Liang et al., 2007; Rivera, Gregory, & Cobos, 2015) and in accounting albeit combined with cloud service (Brandas et al., 2015).

Cloud Technology Cloud computing which represents the convergence of IT efficiency and business agility (Dimitriu & Matei, 2014; Marston, Li, Bandyopadhyay, Zhang, & Ghalsasi, 2011) has been defined as ‘an information technology service model where computing services (both hardware and software) are delivered on-demand to customers over a network in a self-service fashion, independent of device and location’ (Marston et al., 2011, p. 177). Cloud was conceived many decades ago (Marston et al., 2011) and has been in use for many decades, yet its application still appears an inchoate concept (Lin & Chen, 2012) while many people even use it in ignorance. In plain terms, cloud technology is the removal of physical digital space and infrastructure. It requires a device, which can be a mobile smart phone, a tablet, a laptop and/or desktop PC and connected to a network (intranet and/or internet). In addition, a software application does not necessarily need to be

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domiciled (downloaded) on the device. One of its major features is that it frees data and disk space and promotes increased demand for processing unit capacity. Cloud services are offered in many unique business models. The popular models are Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), Software-as-a-Service (SaaS) and Business-Process-as-a-Service (BPaaS) (Akinwunmi et al., 2015; Brandas et al., 2015; Gupta et al., 2013; Sultan, 2011; Tarmidi et al., 2014). In a dynamic approach to specifically enlist cloud service for education and learning, print as well as communications, Education-and-Learningas-a-Service (ELaaS) (Ramachandran, Sivaprakasam, Thangamani, & Anand, 2014), Print-as-a-Service (PrtaaS) (Nagtegaal, 2013) and CommunicationPlatform-as-a-Service (CPaaS) were conceived and developed. Cloud services can be deployed in the form of public, private, hybrid and/or community clouds (ACCA & IMA, 2015; Chang, Walters, & Wills, 2013; Gupta et al., 2013; Ramachandran et al., 2014). There is compelling evidence concerning the benefits of cloud technology to small, medium and large businesses (ACCA & IMA, 2015; Brandas et al., 2015; Dimitriu & Matei, 2014, 2015; Schmidt, 2016; Sultan, 2011; Tarmidi et al., 2014; Trigo, Belfo, & Est´ebanez, 2014). It helps businesses to reduce cost (cost saving) and offers attractive significant technological functionality (Marston et al., 2011). It, however, continues to remain the worst nightmare for some professions (Brender & Markov, 2013). Accounting is one of such professions and the slow pace of its adoption and use by professional accountants (ACCA & IMA, 2015; Wessels, 2005) and law enforcement personnel (Lau, 2015) in tackling especially cyber-fraud may be a matter for concern. It is necessary to posit that the adoption of cloud technology is increasing regulatory frameworks from assurance stakeholders as well (Akinwunmi, Olajubu, et al., 2016; Dimitriu & Matei, 2015). One prominent challenge to the adoption and use of cloud technology is trust (Akinwunmi et al., 2015) and the fact that the mechanisms of formal accreditation and audit in the cloud to ensure trust do not exist yet and are still in discussion poses a more significant challenge (Huang & Nicol, 2013). Others include risk (Dimitriu & Matei, 2015), data security and internet security vulnerabilities (Sabi et al., 2016) and security issues in the form of data loss, privacy compromise, backups and recovery issues, legal ramifications, intellectual property theft and system updates, amongst others (Brandas et al., 2015). Belfo and Trigo (2013) identified external and compliance reporting and realtime reporting as part of present challenges in accounting domain, which cloud service technology responds to with characteristics such as shared services, business process outsourcing and managed services (ACCA & IMA, 2015). According to Sultan (2011) and ACCA & IMA (2015) economic viability and efficiency are key benefits of cloud computing, especially for emerging businesses. Other benefits include cost-effectiveness and advanced security algorithms (Sabi et al., 2016), reduced payments for purchases and maintenance of hardware and software (Brandas et al., 2015; Dimitriu & Matei, 2015; Lau, 2015), increased productivity (Dimitriu & Matei, 2015), adaptability and mobility (ACCA & IMA, 2015). Cloud service for accounting and business has received generous attention in literature (Brender & Markov, 2013; Chang et al., 2013; Dimitriu & Matei,

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2014, 2015; Gupta et al., 2013; Ionescu, Ionescu, Bendovschi, & Tudoran, 2013; Lau, 2015; Lin & Chen, 2012; Marston et al., 2011; Sultan, 2011; Tarmidi et al., 2014) and in education (Ramachandran et al., 2014; Sabi et al., 2016). A list of categorisations of professional accountants and how they use SoMoClo technologies are shown in Table 5.

Theoretical Review This section expounds on the theories of technology adoption and use and learning and knowledge theories. It also documents the development of a proposed model.

Theories of Use and Technology Adoption Theories of technology use that have appeared prominently in literature, discussing and describing the dynamics of technology diffusion, adoption, expertise and use, amongst other things, abound. Some of these theories are reviewed. Diffusion of Innovation Theory Diffusion of innovation theory (DIT) is a traditional theory which provides a classical framework (Zhang, 2017) forged by five constructs of relative advantage, compatibility, complexity, trialability and observability (Lin & Chen, 2012; Zhang, 2017) and has appeared widely in literature (Kanellou & Spathis, 2013; Lin & Chen, 2012; Ram, Corkindale, & Wu, 2013; Tarmidi et al., 2014; Wang & Shih, 2009). This theory is tested by five variables, namely, perceived attributes of innovation, type of innovation decision, communication channels, nature of social system and change agents’ promotion efforts (Lin & Chen, 2012). DIT, although first studied by French sociologist Gabriel Tarde, was developed by Everett Rogers in 1962 after an extensive study of more than 500 diffusion studies (Bhattacherjee, 2012). This theory has received different permutations of nomenclature such as diffusion of innovation (DOI) (Kanellou & Spathis, 2013; Sabi et al., 2016), innovation diffusion theory (IDT) (Bhattacherjee, 2012; Wang & Shih, 2009), individual innovativeness theory (IIT) (Adejuwon, Ilori, & Taiwo, 2016) and DIT (Lin & Chen, 2012; Zhang, 2017). The significance of this theory is hinged on four elements, including innovation, communication channels, time and social system and its definition of innovations, which include new technologies, new practices or new ideas, as well as its construction of adopters as both individuals and organisations (Bhattacherjee, 2012). In addition, there is documented evidence that technology diffusion has been slow paced in many developing nations, but with the affordances of mobile devices, the rate has picked up (Sabi et al., 2016). This theory can therefore provide insights into how true this assertion is in the accounting domain. It is instructive to state that the DIT has appeared prominently in technology-related studies as expected (Lin & Chen, 2012; Rivera et al., 2015; Sabi et al., 2016; Tarmidi et al., 2014; Zhang, 2017).

Table 5. SoMoClo Technologies for Accounting Profession. Social Media Profession

Purpose

Platform

Mobile Purpose

Cloud Platform

Real-time access, cost control, financial savings, resource management Real-time access, resource management

Platform

SAP, Netsuite, Oracle ERP Cloud Services, Google Sheets Proprietary services, Google Forms

Real-time access, Dropbox, resource Google Drive, management Mendeley, One Drive

Literature Discourse

Communications Outlook, Skype, Mobility, flexibility Smart phones Twitter of work dynamics and tablets running Android, iOS etc. Mobility, flexibility Smart phones Policy Solicit opinion, LinkedIn, disseminate Twitter, of work dynamics and tablets information YouTube running Android, iOS etc. Research Networking and Twitter, Mobility, flexibility Smart phones collaboration Mendeley of work dynamics and tablets running Android, iOS etc. Practice

Purpose

51

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DIT has been criticised because it has been argued to be insufficient to account for adoption of (new) technology and does not, for example, capture the behavioural aspects that affect individual willingness to adopt any innovation (Sabi et al., 2016). DIT can provide insights into how professional accountants are adopting a technology, but not necessarily their use of the technology. The high point of the DIT is the study of how technology diffuses (adoption), not majorly on how it is used amongst key actors.

Expectancy Theories The expectancy theory of motivation (ETM), which was developed by Victor Vroom in 1964, is hinged on four significant variables of individual effort, individual performance, organisational rewards/work outcomes and personal goals (Ferris, 1977; Parijat & Bagga, 2014). ETM is one of the results of extensive theorising and empirical investigations to answer questions bordering on the motivating factors of employees as well as their satisfaction (Ferris, 1977). This makes it a significant social theory. ETM is held as a significant theory of motivation for action (Andriessen, 1975; Ferris, 1977; Lunenburg, 2011; Parijat & Bagga, 2014) and has been used to test individual motivation in a public accounting firm, although the result showed limited support for the theory (Ferris, 1977) and has been used in other settings (Andriessen, 1975; Ferris, 1977; Geiger & Cooper, 1996; Lunenburg, 2011). The use of technology promises process efficiency as well as other gratifying ends and these are expectations, which professional accountants have when they intend to and/or use technology, giving relevance to the ETM. Therefore, the motivation for professional accountants to use technology is hinged on the expectation that it will enhance their productivity and other expectations. If these expectations are promised and/or met, the professional accountant is motivated to use and/or continue to use the technology. Another expectancy theory with close ties to technology is the expectancy disconfirmation theory (EDT), which has its root in marketing research for the study of consumer satisfaction (Lankton & McKnight, 2012). EDT was proposed by Oliver in 1980 and is explained with four major constructs of expectations, perceived performance, disconfirmation and satisfaction (Akinwunmi et al., 2015). EDT has been used in studies of technology adoption, usage and finance (Gierczak, Englisch, & Bretschneider, 2015; Lankton & McKnight, 2012; de Melo Pereira, Ramos, de Andrade, & de Oliveira, 2015). The ETM and EDT have been used to identify key variables, concepts and construct that influence use of technology; however, they are limited in some ways. For instance, these theories are unable to explain ‘use’ based on availability of IT infrastructure in the sense that it may not be able to interpret or predict technology use based on the degree of technology availability. A question such as ‘what change would occur in the measure of technology use and how will it be measured, if the environment in which a competent user is domiciled changes?’ may be beyond the scope of these theories.

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Technology Acceptance Model Technology acceptance model (TAM), which is from social psychology and was specifically adapted from the theory of reasoned action (TRA) to apply to the information system fields (Rivera et al., 2015; Sabi et al., 2016), is another theory that has received wide mention in literature and has been used side-by-side with DIT (Sabi et al., 2016; Zhang, 2017). TAM is credited to the works in which Davis authored and co-authored in 1989 (Zhang, 2017) although other views suggest that TAM was proposed in 1985 (Sabi et al., 2016) and first appeared in Davis’ doctoral thesis of 1985 (Uthman et al., 2014). TAM is constantly being reviewed because it does not address some of the features of modern technology diffusion and acceptance (Sabi et al., 2016), and it is limited by its account of IT infrastructure availability and competence in the form of perceived ease of use, perceived usefulness, attitude towards use and intention to use technology (Watty et al., 2016). It is also based on utilitarian approach (Rivera et al., 2015). TAM has been reviewed giving birth to TAM 2, an extension by the inclusion of social influence process (SIP) and cognitive instrumental process (CIP) (Ogundeji et al., 2014), and TAM 3 (Venkatesh & Bala, 2008). Most studies that have used TAM measure usage through intention to use rather than actual usage (Watty et al., 2016) and it may be important to agree that actual usage of technology may be difficult to measure. In addition, ‘TAM applies individualistic perspective and neglects the impact of social systems’ (Zhang, 2017, p. 440). When IT infrastructure is available, with sufficient expertise and intention to engage, yet it is not used or does not promote a corporate culture, but advances informal use; it will result to waste and enterprise inefficiency or what has been alluded to as ‘sub-optimal utilisation’ (Watty et al., 2016, p. 2). It is also noteworthy that TAM only explains about 40–50% of technology acceptance (Ogundeji et al., 2014). Notwithstanding, TAM and its counterparts TAM 2 and TAM 3 have received wide mention in literature as significant explanatory theories of technology use (Bankole & Bankole, 2017; Gallego, Bueno, & Noyes, 2016; Gupta et al., 2013; Merello-Gimenez & Zorio-Grima, 2016; Ogundeji et al., 2014; Ramachandran et al., 2014; Tarmidi et al., 2014; Venkatesh, Morris, & Ackerman, 2000; Wang & Shih, 2009; Watty et al., 2016; Zhang, 2017). The use of technology is becoming mandatory for professional accountants (Birt et al., 2018), making acceptance of its use somewhat mandatory.

Unified Theory of Acceptance and Use of Technology The unified theory of acceptance and use of technology (UTAUT) proposed as an alternative to varied and individually inadequate theories and models of technology adoption and use (Venkatesh, Morris, Davis, & Davis, 2003) is another equally relevant and currently trending theory. This theory, which has since been cited as useful in explaining technology diffusion, acceptance and adoption (Bankole & Bankole, 2017; X.; Zhang, 2017) and validated in literature (Wang & Shih, 2009), explains about 70% in variance of technology use behaviour/ intention (Venkatesh et al., 2003). This makes it the theory with the highest

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explanatory powers in the field of technology use. UTAUT consolidates eight different theories and models of TAM, TRA, theory of planned behaviour (TPB), combined TAM and TPB (C-TAM-TPB), IDT, social cognitive theory (SCT), motivational model (MM) and model of PC utilisation (MPCU) (Venkatesh et al., 2003; Wang & Shih, 2009). The UTAUT suggests that performance expectancy, effort expectancy, social influence, and facilitating conditions are determinants of behavioral intention or use behavior; and that gender, age, experience, and voluntariness of use have moderating effects in the acceptance of IT. (Wang & Shih, 2009, p. 159) UTAUT is gaining steady acceptance as the possible conglomerate of assumptions, models and theories to understanding the use of technology; however, it is instructive to posit that it may not be exhaustive because the model has been revised serially. There is a UTAUT2 (Macedo, 2017; Morosan & DeFranco, 2016) and the original UTAUT has been modified to account for cultural dimensions in ICT innovations (Bankole & Bankole, 2017) and has been amply modified in other studies (Alshehri, 2012; Wang & Shih, 2009). The relevance of this theory touches on professional accountants’ use of technology and the factors that influence them. However, the roles of differentiation and institutional settings amongst professional accountants have not been considered using this model. This theory is noted as a theory of choice in many contemporary technology studies.

Uses and Gratifications Theory The uses and gratifications theory (UGT) staged on seven constructs, namely, convenience, entertainment, socialising, status seeking, information seeking, sharing experience and continuance intention (Gallego et al., 2016), explains that a person’s choice to use or continue to use a media is to gratify a need or wide range of needs. This theory has been used to ascertain why and how people seek to use or continue to use a media to fulfil their needs, motives and gratification (Gallego et al., 2016). With direct connection to technology, the UGT has been applied to study the use of social media (Gallego et al., 2016) and online course administration (Philpott & Pike, 2013). The UGT is a significant improvement and extension of technology use theories, especially the TAM, yet its significant limitation, is that it aligns with hedonic use of technology (Rivera et al., 2015) significantly neglecting corporate use. Given the mandatory posture of technology use amongst professional accountants in this century and for the future, the use of SoMoClo technologies may become a trigger to satisfy the need for relevance amongst professional accountants; however the factors for measuring the need to use and continue to use technology in gratifying a social need may be devoid of professionalism in an accounting corporate domain.

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Other Technology Use Theories Other relevant theories of technology adoption and use aside those mentioned as a conglomerate for the UTAUT are the theory of technology dominance (TTD) used to explain knowledge-related technologies such as expert systems (Sutton et al., 2016), classical probability theory (CPT), used to explain IT risk (Worrell et al., 2014), and actor–network theory (ANT) which is used to explain the varied classes of people and procedures affected by technology adoption and use (Kanellou & Spathis, 2013). Due to the evolving nature of technology, a single theory may be insufficient to explain adoption, use, benefits and challenges (Sabi et al., 2016), yet many theories of technology use and adoption have been able to explain and at least give insights into the issues associated with technology in many fields, as well as in accounting.

Theories of Learning and Knowledge Ample evidence suggests the clarification of knowledge in literature (Lubbe, 2016); hence knowledge description is diversified. Knowledge is ‘a collection of information and/or skills acquired through experience (practical understanding) and/or education (theoretical understanding)’ (Boulianne, 2014, p. 24). Knowledge acquisition modes and models should ordinarily translate to professional competence and capacities, yet this hypothesis may need some more testing. Declarative and procedural knowledge (Boulianne, 2014) are forms of knowledge that relate to the study and practice of accounting. This is strengthened by the submission that ‘accounting knowledge is mostly procedural, specific and pragmatic, and deals with executing, applying, and setting priorities’ (Lubbe, 2016, p. 3). Others forms in the accounting domain include competency, functional, practical and conditional knowledge (Lubbe, 2016). Learning is a social phenomenon that takes place within communities (Wilson & Peterson, 2006). In addition, learning is a ‘broad range of processes whereby an individual acquires capabilities’ (IAESB, 2015b, p. 135). One prominent classification of learning is the Gagne’s eight distinctive types of learning in ascending order from signal, stimulus–response, chaining, verbal association, multiple discrimination, concept, principle to problem-solving (Knowles, Holton III, & Swanson, 2005). According to Chaffer and Webb (2017), the constructivist theory of learning suggests that learning is an active process dependent on many interrelated factors. Hence, no variable can be attributed to improving learning outcomes. This makes learning an ambiguous construct. Knowledge is dynamic and can be acquired in diverse forms (Myers, 2016). The inclusion of accountants’ training framework as a variable, which involves learning to produce useable knowledge – competence and capability (Howieson et al., 2014) – makes learning and knowledge theories significant. According to Richardson et al. (2013) ‘learning theories suggest that learning styles and preferences influence the effectiveness with which individuals learn’ (p. 10). Furthermore, the significance of learning and knowledge is strengthened by a narrative that ‘although two students might encounter exactly the same information, as active participants in their own knowledge building, students develop

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understandings that can be qualitatively different’ (Wilson & Peterson, 2006, p. 3). This suggests that professional accountants from the same providers of accounting education may project an exhibition of different knowledge utilisation outcomes because of individual differences, work settings and other factors. Furthermore, training opportunities do not necessarily produce competence and not at the same levels amongst learners (Chaffer & Webb, 2017). Legitimation code theory (LCT) has been used to explain students’ learning perception (Myers, 2016). LCT helps to understand people’s perception in the learning process. Another theory of knowledge and learning is the curriculum theory, which has been used to explain the differences between explicit and hidden curricula (Lubbe, 2016). This is readily significant since it has been argued that ‘the business of professional and practice-based disciplines is to be concerned with managing the interaction between explicit knowledge and implicit knowledge, and between knowledge and values’ (Lubbe, 2014, p. 121). This theory explains the influence of curriculum design and delivery pedagogy on students’ comprehension and performance. However, both theories do not have embedded differentiation of the types of training frameworks – the interrelationships between and amongst academic and professional training frameworks and their constituent parts. They both do not take care of the perception of the learner with respect to use of technology. Legitimate peripheral participation (LPP) is a theory of situated learning, and ‘can be seen as a general principle of the development of knowing and theory-inuse’ (Schulz, 2005, p. 497). Peripheral participation takes place when a learner in a given setting skims through the learning process, without fully understanding or coming to terms with the learning outcomes. This theory is significant, given the fact that learning environments (such as the learning space, delivery, curriculum etc.) have significant effect on learning outcomes (Crook & Bligh, 2016). It is significant to note that LPP has been used to explain the community of practice in the field of accounting (Lindsay, 2013). Generally, learning theories explain learning and knowledge acquisition and how people learn with respect to the learner’s perception, curricula and delivery.

Theoretical Considerations Perception The primary motivation for including perception as a significant variable is borne out of the need to consider the psychological and sociological personality of professional accountants. Perception is a significant variable for adoption and use of technology and is a significant variable in most technology-related theories. Pickens (2005) asserted that ‘a person’s awareness and acceptance of the stimuli play an important role in the perception process’ (p. 54). Earlier, in defining perception he mentioned Lindsay and Norman’s (1977) definition as ‘the process by which organisms interpret and organise sensation to produce a meaningful experience of the world’ (Pickens, 2005, p. 52). Hornby (2000) defined perception in three basic ways as ‘the way you notice things, especially with the senses’, ‘the

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ability to understand the true nature of something’ and ‘an idea, a belief or an image you have as a result of how you see or understand something’ (p. 864). These definitions clearly identify core points that make the mention of perception significant. Accountants’ perception of (new) technology which is influenced by their awareness and understanding influences their competence, adoption and use. Perception has been a significant variable in assessing technology adoption and use, and many theories of technology adoption, especially the TAM, hold human perception as a significant variable in explaining technology adoption and use and it continues to receive attention in literature (Haynes, Briggs, & Copeland, 2008). Watty et al. (2016) rhetorically question the role of accounting faculty as ‘innovators or inhibitors’ based on their perception and use of educational technologies. The imperative of perception to this study is also built on the idea that technology use forges a human–technology relationship, which in turn bestows ‘agency, perception, and choice’ (Hardr´e, 2016, p. 89).

Proposed Theory It is noteworthy that theories are in themselves not sacrosanct and researchers are expected to continue to replace poorer theories by better theories with higher explanatory power (Bhattacherjee, 2012). We undertook the challenge to build a better and more comprehensive theory given that the accountants’ training framework construct eludes many of the reviewed theories. More so, all theories are based significantly on available and accessible information and evidence suggests a continuous interrogation of theories even by their early documented proponents (Wilson & Peterson, 2006). The proposed theory undertakes the arrangement, alignment and integration of theoretical and empirical perspectives on training, perception, technology use and practice within specialty-context to suggest a perceive, learn, setting and use theory (PLESUT). PLESUT integrates a professional accountant’s perception, learning and working dynamics to explain technology adoption, competence and use. The inclusion of perception depends largely on the individual’s adoption of technology in situated work dynamics (Ogundeji et al., 2014), which interestingly has been tested as a dependent variable (Sabi et al., 2016). It is only fair to posit that the constructs inherent in the proposed theory are somewhat captured by the UTAUT (Venkatesh et al., 2003), discourse theory (Kanellou & Spathis, 2013) and the theory of practice (Warde, 2005). It is therefore an abbreviated-aggregate theory. Perception of key actors in learning and within organisational work settings, for example, is very well captured by the discourse theory, while ‘knowing’ and ‘acting’ is also well captured by the theory of practice. The discourse theory ‘is a meta-theory which is partly an explanation of the social construction of (social) reality’ (Rose & Kræmmergaard, 2006, p. 222), and first appeared in 1982. The discourse theory with many recent variants is attributed to Ernesto Laclau and Chantal Mouffe – both political theorists. Discourse theory has received some mention in literature (MacKillop, 2016; Rose & Kræmmergaard, 2006; Walton &

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Boon, 2014) and in accounting technology research as well (Baldvinsdottir et al., 2010; Kanellou & Spathis, 2013; Vinnari & Dillard, 2016), although there is a concern that its appearance in AIS research is limited, despite its acclaimed significance. The significance of the discourse theory is strengthened by the narrative that …where the research focus is on organisational change, actors’ perceptions of evolving conditions, emergent planning in this face of multiple objectives, unforeseeable resource demands and changing subjective criteria for success, then theories based on the social construction of reality and interpretive and critical research methods become appropriate research approaches. (Rose & Kræmmergaard, 2006, p. 235) Furthermore, discourse theory had led to the theorising of learning discourse amongst individuals and technology discourse within organisations (Walton & Boon, 2014). The theory of practice on the other hand is embedded in both sociology and psychology and since ‘no authoritative or synthetic version is available’ (Warde, 2005, p. 132), it may be difficult to ascertain its true origin, yet it helps to reify practice. ‘From a theory of practice perspective, acting within a social situation primarily requires the ability to do, which is a practical type of knowledge’ (Schulz, 2005, p. 495). The theory of practice makes a differentiation between explicit and implicit knowledge like the curriculum theory. The integration of the discourse theory and theory of practice helps to identify that a significant part of discourse aligns with how a practice or a phenomenon is interpreted and understood (Rose & Kræmmergaard, 2006) by a community of practice. The involvement of ‘practice’ is significant because according to Warde (2005) a ‘competent practitioner requires appropriation of the requisite services, possession of appropriate tools, and devotion of a suitable level of attention to the conduct of the practice’ (p. 131). This clearly typifies the professional responsibility and requirement of a professional accountant, as someone who has acquired necessary competence to function appropriately (Oladele, 2015b; 2015c). Learning and working dynamics influence competence (Boulianne, 2014) such that an accountant is regarded as ‘qualified’ due to meeting and maintaining preand post-qualification requirements (IPD and CPD, respectively). This includes an academic degree in most cases, a professional accounting programme (IAESB, 2015b) including a location-specific work experience (Lubbe, 2014) as well as lifelong learning (H. Lindsay, 2016; Lubbe, 2014). Learning and working dynamics can influence perception (Dahan & Hauser, 2001; Wilson & Peterson, 2006), while specialty and corporate adoption practices influence user’s behavioural intention. Intention to use technology can be translated to use of technology as espoused by the UTAUT. Furthermore, perception without competence may result to intention to use only and/or improper use (Sutton et al., 2016), although a significant limitation is the insignificance of the degree of use as that may be impossible to test externally.

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Competence does not necessarily translate to efficient use, even in instances of compulsory use (Cohen, 2011), and consistent and coordinated use may qualify as practice, also known as ‘Praktik’ (Warde, 2005). Following the influence of passage of time on consistent use/misuse, habit may be formed (Jamaluddin, Ahmad, Alias, & Simun, 2015). For technology use to be effective, efficient and sustainably productive, the user should be competent – must have been trained (Razmerita et al., 2016), have access to technology and exhibit favourable perception (Ferris, 1977). Apart from these, there must be good usability, which is associated with the ‘ease of use and learnability of technology’ (Razmerita et al., 2016). A hiatus that this model recognises in other theories and intends to fill is the literature silence on the effect of corporate adoption on technology use amongst professional accountants. The theory groups the unit of analysis into two categories: professional accountants perceived to use technology because of mere opportunity and perception, as meeting and/or satisfying a need as with the UGT, and not necessarily with competence on the one hand and those engaging technology, based on competence and other supporting variables on the other hand. In addition, practitioners, policymakers and researchers are grouped and tested individually to identify peculiarities amongst the categories of professional accountants. That way, the proposed theory should be able to explain for better understanding how professional accountants’ training and perception within specialty-context influence technology competence, adoption and use. Some assumptions underline the strength of the proposed theory. First, the professional accountant works only as any of practitioner, policymaker and researcher and has undergone both academic and professional accounting education. Second, the professional accountant has a measurable perception of technology. Furthermore, it is assumed that learning leads to competence and work setting determines technology adoption. Finally, use/misuse over a period results to practice. These relationships are diagrammatically captured in Fig. 3. Given the fact that the PLESUT is still in its design stage and it has not been tested, it remains a proposal.

Competence Learning dynamics

Use/ Misuse

Perception

Specialty dynamics

Practice

Adoption Time Intention to use

Fig. 3.

Proposed PLESUT.

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Empirical Review Significant findings, methods and sample of previous studies are reviewed, while limitations are identified.

SoMoClo Technology and Its Professional Accounting Uses Information and communication technology (ICT), combined with accounting information system (AIS) and management information system (MIS), has become a system, through which human weaknesses in accounting operations, activities and functions are being overcome (Uthman et al., 2014). This is transforming the traditional role of professional accountants (Wessels, 2004) and possibly replacing human workers (Guthrie & Parker, 2016). Technology use for accounting practice is evident in the way it has transformed AIS, which by virtue of technology integration has become ‘faster, more accurate, more reliable, and able to process large volumes of transactions’ (Wessels, 2004, p. 221). Technology-assisted AIS can be categorised into electronic record (e-records) system (Oladele, 2014) also referred to as computer-based accounting system and internet or network-enabled accounting systems (Worrell et al., 2014). The former describes the use of many standalone computers to process transactions by organisations, while the latter describes the added advantage of the use of networks (internet or intranet), which allow multiple systems to interact based on interconnectivity and interoperability platforms. Function-specific technologies include software for specific accounting functions such as the audit command language (ACL) for auditing (Belfo & Trigo, 2013), spreadsheets for tax computations and other computational functions (Willis, 2016), and bespoke applications such as the Government Integrated Financial Management Information System (GIFMIS) (GIFMIS, 2013) and Integrated Payroll and Personnel Information System (IPPIS) used in the Nigerian public sector for performance and financial management. Accountants involved with policy and research use diverse technological tools and applications as well. Twitter, for example, has been used diversely in education and research (Bagley, 2012; Khan et al., 2016; Lorentzen, 2014; Zimmer & Proferes, 2014), and web-based surveys and electronic mailing technologies are being used to solicit opinions by standard-setters. Research accountants are now faced with numerous technologies for teaching and research such as collaboration and presentation tools and applications, including Mendeley, which is a free reference manager, Google classroom, Phinnx and other social media technologies used for communication between and amongst faculty and students (Watty et al., 2016) for teaching and learning. Social media studies abound (Agostino & Sidorova, 2017; Cawsey & Rowley, 2016; Dijkmans et al., 2015; Hamid et al., 2016; Haustein et al., 2015; He et al., 2017; Kalsnes et al., 2014; Stainbank & Gurr, 2016), yet it seems its use in the accounting domain has received less attention. Mobile technology studies that

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have appeared in many empirical researches include devices such as smart phones (Bankole & Bankole, 2017; Bomhold, 2013; Zhang, 2017), mobile broadband (Jamaluddin et al., 2015) and iPods (Richardson et al., 2013); however, none of these studies have considered professional accountants’ use of mobile technology, especially with the categorisation model of the tripartite accounting. Some types of cloud services include Webmail, Flickr and YouTube, which many people have been using (Lin & Chen, 2012), given that the adoption of cloud-based technologies is fast-growing. In Romania, for example, the cloud market is expected to grow five times faster than the general IT market, the fastest growth being expected for PaaS services, while the lowest for SaaS services and there are four popular cloud accounting software, which are CIEL, Saga, Expert Accounts and e-contabilitate.ro (Ionescu et al., 2013). However, in many developing economies, such statistics may not be readily available. It is important to state that there have been some combinations of SoMoClo technologies in literature, such as studies on social media and mobile (Zhang et al., 2017) and on cloud and mobile (Brandas et al., 2015). On awareness of SoMoClo technologies, social media and mobile technologies are more visible, hence well known; however, it seems cloud technology lags in awareness and adoption (Lin & Chen, 2012). According to Tarmidi et al. (2014) practicing accountants in Malaysia were only mildly aware of Google cloud service and Dropbox. Studies abound on technology use in business (ACCA & IMA, 2015; Accountancy Futures Academy, 2013), in education, for teaching (Gallego et al., 2016; Guthrie & Parker, 2016; Kaplan & Haenlein, 2010; Khan et al., 2016), for research (Bagley, 2012; Haustein et al., 2015; Johnson, 2012; Lee et al., 2017; Watty et al., 2016; Zimmer & Proferes, 2014), by accountants (Belfo & Trigo, 2013; Boulianne, 2014; Dijkmans et al., 2015; Kaplan & Haenlein, 2010; Khan et al., 2016; Lee et al., 2017) and even in politics (Kalsnes et al., 2014; Lorentzen, 2014). Mobile and cloud technologies have received significant attention in literature amongst accountants, while social media has been apparently less linked, probably due to accountants’ unwillingness to be ‘exposed’ (ACCA & IMA, 2015). Technology use studies amongst accountants in Nigeria are but few and while many international studies of technology use amongst accountants such as along lines of age as specifically highlighted between ‘old’ and ‘young’ accountants (Warawa, 2016) and gender (between men and women) (Venkatesh et al., 2000); areas of teaching, academic rank, degrees, accreditation status, work experience/age and gender (Ahadiat, 2005; Webb & Chaffer, 2016) abound, there seems to be literature silence on the ‘how’ of technology use amongst professional accountants, especially in developing economies. Amongst studies on technology use amongst accountants, the researcher considers these works (Bradbard et al., 2014; Ragland & Ramachandran, 2014; Ramachandran Rackliffe & Ragland, 2016) relevant bordering on insights to technologies used by accountants. Bradbard et al. (2014) studied management accountants’ use of electronic spreadsheet, which they claimed was introduced in 1979 (although another source claims 1974 (Willis, 2016)), using an online survey of select members of

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the Institute of Management Accountants, which they compared with expected new hires’ competence and found very strong correlation. The other studies analysed the perceptions of accounting professors, students and practitioners towards the use of Microsoft Excel and found that it is a significant tool for accountants. Other closely related studies of interest (Ahadiat, 2005; Shaoul, 1988) studied accounting faculty’s use of technology and found significant appreciation for educational technology, while Watty et al. (2016) questioned the role of accounting faculty as inhibitors or innovators as related to educational technologies used in higher education. Bradbard et al. (2014) reiterated that from a review of significant studies, spreadsheet expertise was rated the most important IT skill. Unfortunately, however, the use of spreadsheet does not fall into the scope of SoMoClo technologies entirely, although spreadsheet activities can be carried on with support from cloud services on mobile devices. Cloud computing awareness and adoption amongst accounting practitioners were examined by Tarmidi et al. (2014) in Malaysia. Their study assessed cloud technologies amongst 324 accounting practitioners and found significantly low levels of awareness and competence. Sutton et al. (2016) inspired by research that the use of artificial intelligence in supporting knowledge-based systems is alive and well amongst accounting professionals analysed how academics can take a leadership role in the application of AI techniques to support accounting decision-making and found that the use of larger integrated systems are increasing, although the use of standalone systems are waning. The main shortcomings of the studies reviewed are that they failed to draw a pattern for the use practices of technology by accountants and failed to review the three categories of accountants to show a comparison of their use practices, as such they have not been able to explain the use practices of technology amongst accountants. Significant similar empirical works avail, chief amongst them are studies that assessed the type of technology used by accounting practitioners and educators, how, why and its extent of use (Ahadiat, 2003, 2005; Humphrey & Beard, 2014; Kearns, 2016; Watty et al., 2016). These studies factored and controlled for gender, age, experience, education, attitude, competence, anxiety and restraint, teaching area, ethnicity and academic rank on technology use. Others surveyed technology use amongst accounting practitioners (Damasiotis et al., 2015; Tarmidi et al., 2014) and amongst both educators and practitioners (Lin, 2008) while we found no significant study linking policy accountants to technology adoption and use. More so, many recent researches on (new) technology adoption and use have focused more on IT expertise, cost of adoption (Uthman et al., 2014), benefits and challenges (Dimitriu & Matei, 2014; Okolie & Taiwo, 2014; Wellisz, 2016) and sustainability in business (Kanellou & Spathis, 2013; A.; Lin & Chen, 2012). There are, however, other authors who have viewed technology adoption and use beyond those confines, associating it to accounting education (Apostolou, Dorminey, Hassell, & Rebele, 2014; Damasiotis et al., ¨ 2015; Guney, 2014; Kotb, Roberts, & Stoner, 2013; Shaoul, 1988; Watty et al., 2016; Wessels, 2004; Willis, 2016). Technology use practice study is therefore

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imperative because according to Venkatesh et al. (2000, p. 34) the need to understand ‘the factors influencing user acceptance, adoption, and usage of emerging information technologies in the workplace is a critical issue for researchers and practitioners’ (p. 34).

Competence Comparison A review study on the development of ICT skills used academic and professional articles published since 2010 to give insight into the competence of professional accountants around the world. The authors sourced articles from both academic and professional outlets and used textual analysis software, Leximancer, to analyse the ICT publications reviewed (Birt et al., 2018). They found a gap in the IT skills of professional accountants generally. Empirical comparative studies of accountants’ professional IT competence with an international standard, such as the IES, are scanty. Palmer et al. (2004) reviewed the case of international knowledge, skills and abilities of auditors/ accountants. IT skill was one of the skills upheld as necessary for becoming and remaining a professional accountant. However, they did not compare the actual competence of accountants with any reputably published competence standard. They even lamented that IFAC gave a directive to member bodies but did not give specific guidelines leading to divergent approaches to the development of IT competence in different jurisdictions. Two studies (Watty, Sugahara, Abayadeera, Perera, & McKay, 2012, 2014) chronicled the development of an implementation framework and compliance with the IES in Australia, Japan and Sri Lanka. Their work was on the implementation of the IES and a comparison amongst the select countries and not the competence of professional accountants, and certainly not in the areas of IT competence. Their results showed significant differences in the accounting education systems of the three countries. Other authors (Buckless & Krawczyk, 2016; Centre for Financial Reporting Reform, 2016; Damasiotis et al., 2015; Flood & Wilson, 2008; Hamilton, 2013; Howieson et al., 2014; Mohd Nor et al., 2013; Murphy, 2016; Palmer et al., 2004; Parker et al., 2011; Sugahara & Watty, 2016; Wessels, 2004, 2005, 2006) gave passing mention of the IES, while none compared the actual competence of professional accountants with expected competencies. The study that would have been the closest (Palmer et al., 2004), however, only reviewed competencies as constructed by major accounting stakeholders internationally. A study to therefore ascertain and compare professional accountants’ IT competence with the IES IT standard is necessary, especially in developing economies given an acute technology divide. A secondary and unintended effect that the digital divide influences is a perceived significant knowledge and competence gap with potential to militate against professional accountants from emerging economies in the global, highly lucrative accounting and finance job market (Lubbe, 2016). More so, since it is a fact that technology, its advancements, adoption and use by, especially, businesses (ACCA & IMA, 2015)

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continue to influence the professional competence requirements of professional accountants world over (IAESB, 2015c), an evaluation of professional accountants’ IT competence in meeting international standard is required. The question on the implementation of IES in both academic and professional accounting education in developing economies is necessary.

Accountants’ Training Framework and Competence Dabalen et al. (2001) studied the employability prospect of university graduates in Nigeria and found that it has worsened over time, implying that the tertiary training framework, especially of universities in Nigeria, is deteriorating and may not be able to produce employment-ready graduates; their conclusion was substantiated by reports from employers. Their study was, however, not exclusive to accounting graduates nor was it on technology. Bui and Porter (2010) noted that key stakeholders of the accounting profession are criticising tertiary accounting education for its failure to equip graduates with the competencies required by members of the profession, especially given the changing business environment, where technology has remained a game-changer of a sort and called it an expectation gap. In their paper, they proposed a framework which highlights an expectation gap, a constraints gap and a performance gap and their exploratory study suggested that the expectation may not easily be met. This may, however, be fast-tracked if an institutional arrangement amongst educators and employers emerges (Pathways Commission, 2012). A significant inference from their work is the establishment of the fact that accountants’ training framework significantly influences competence amongst accountants generally, and IT competence particularly. Another study concluded that ‘holding or not holding a degree does not have a significant impact on explaining self-perceived competency’ (Chaffer & Webb, 2017, p. 12). Other studies (Damasiotis et al., 2015; Gammie et al., 2010; Howieson et al., 2014; Palmer et al., 2004; Parker et al., 2011; Watty et al., 2014; Wells, 1994; Wessels, 2004, 2005) have established a link between accountants’ training framework and IT competence, emphasising the role of universities and PAOs in the development and maintenance of IT competencies amongst professional accountants. A significant limitation of these studies is their failure to identify and/or assess how the determined factors of accountants’ training framework between the two halves (academic and professional) influence technology competence amongst professional accountants. There is no point overstressing that literature has established significant correlation between accounting education delivery and technology competence. However, we are not aware of a study that has holistically integrated the full pack of accountants’ training framework as significant in determining technology competence amongst professional accountants, especially in developing economies. Based on literature, the aim of training is to build competence and capacity (Howieson, 2003; Howieson et al., 2014; Kennedy, 2005). This leads to suggesting

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that the accountants’ training framework albeit adjudged outdated or ill-modelled to meet present challenges (Chaffer & Webb, 2017; Ellington, 2017; Pincus et al., 2017; Webb & Chaffer, 2016) stands to build competence, affording a significant relationship. A dissenting view is that SoMoClo technologies are considered ‘new technology’ and may be beyond the training received in the past. This gives rise to the need for continuing professional development (CPD) or more appropriately, lifelong learning (Lindsay, 2016). Notwithstanding this argument, the researcher aligned with views of a deficient and responsively passive higher education in Nigeria (Dabalen et al., 2001; Dumbili, 2014) but assumed a positive attitude to technology use amongst professional accountants. In the international scenery, the training of accountants is not left out such that it is reported that there is a perceived deficiency in skills and competence amongst accountants (Bui & Porter, 2010). The issue of IT skill deficiency borders on the premise that Nigerian professional accountants’ technology competence may be inconsistent with the minimum level of competence required by international standard; and this may be due to an insufficient, deficient and passive accountants’ training framework; or that accountants’ training framework may be deficient and passive (Pincus et al., 2017); hence it may not be able to produce technology-savvy professional accountants. In addition, it has been decried that despite the changes in the accounting domain, the training framework, especially in the tertiary plain, remains significantly static (Howieson, 2003). These insinuations deliberately and conveniently leave out perception and the dynamics of specialty; however, it is essential that professional specialty should be called to question, as well as the professional accountants’ perception (Howieson et al., 2014). If the responses to the above insinuations are in the affirmative, then accountants may begin to prepare for obsolescence (Birt et al., 2018).

Factors Influencing Technology Use A research carried on in a non-accounting field hinged on DIT adopted a categorisation of factors that influence technology into internal (educational qualifications, gender and income) and external (knowledge institutions/innovating units including universities and research institutes) (Adejuwon et al., 2016), which validates the essence of assessing the interpretive value of training as a significant variable. About thirty (30 years ago, an important study reviewed the impact of new technology on accounting education and how training can be used to ensure that students learn how to use new technology (Shaoul, 1988). The study named some existing technologies such as emails, social media and mobile technology; its focus was on the educational value of technology. Many of the studies that have assessed the relationship between training and use of technology have limited their factoring to level of education, that is, between and amongst educated and non-educated, degree holders and non-degree holders, those that

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received formal education, non-formal education and informal education (Ahadiat, 2005; Chaffer & Webb, 2017; Gammie et al., 2010; Tarmidi et al., 2014). In addition, their factoring of education/training was within other variables such that they were used as cross-tabulations for more ‘cogent’ independent variables. Perception has been found to be a significant predictor of technology use. Students’ perception, for example, is established in literature as a significant variable in skills development (Bui & Porter, 2010; Khan et al., 2016; Mushtaq & Khan, 2012; Richardson et al., 2013; Sabi et al., 2016), and has been used as a predictor for technology use (Alshehri, 2012; Bakhsh et al., 2017; Sun & Zhang, 2006; Zhang, 2017). From the reviews of Rivera et al. (2015), perception as with PEOU and PU was found to be significant for mobile technology adoption. They further determined that perception was a responsible factor for attitude, which also had a positive correlation with intention to use technology. Age and gender were significant varying factors in most studies. Ahadiat (2005), for example, found gender and age to be instructive in explaining intention to use technology. Perception studies in accounting are pervasive, bordering on technology use (Humphrey & Beard, 2014; Ramachandran Rackliffe & Ragland, 2016; Ragland & Ramachandran, 2014; Ramachandran; Richardson et al., 2013; Worrell et al., 2014), accounting education and practice (Ali et al., 2016; Howieson et al., 2014; Steenkamp & Baard, 2009; Stivers et al., 2011) and the accounting profession (Hamilton, 2013). Richardson et al. (2013) assessed students’ learning experience based on a perception of benefits derivable from the use of iPod using a questionnaire. They found that the most significant motivating factor was the portability of the device and students with favourable perception towards visual learning submitted that the iPod was significant to their learning. Within organisational context, specialty, signifying the environment where professional accountants function, influences their adoption of technology as highlighted in literature (Bruce, 2004; Wessels, 2006) and influences their technology use. We are unable to find any study that has studied technology adoption amongst the three categories of the accounting jurisdictions collectively. Yet, it is noteworthy that the work setting is a significant variable in determining technology use (Schulz, 2005; Warde, 2005). Waweru, Hoque, and Uliana (2004) studied changes to management accounting systems with technology as one of four factors that influence recent changes. The results from their study using four case studies in South Africa and through the lens of the contingency theory found that corporate adoption of technology changed the way management accounting system operated. Age, experience and gender were significant varying factors in most of the studie. A summary is provided in Tables 6 and 7.

Summary of Empirics

Table 6. Summary of Selected Qualitative Research. S/N

Country/ Location

Sample/Method

United States

Review of competency studies

2.

South Africa

Review

3.

Global

SWOT analysis framework

International knowledge, skills and abilities IT and education

Cloud computing

Significant Findings/ Recommendations

Gap

Remarks

Author(s)

No distinction amongst the KSA

Education Palmer et al. implication (2004)

IT is the main area of concern in the training of professional accountants in South Africa Further research should focus on cloud computing economics; cloud computing and its strategy/policy issues (including security); technology adoption and implementation issues; cloud computing and green IT and regulatory issues

Limited to education

Education Wessels, implication (2004)

Social media Research Marston and mobile are implication et al. (2011) excluded

67

Entry-level accountants possess IT knowledge, skill and ability (KSA)

Literature Discourse

1.

Variables

68

S/N

Country/ Location

Sample/Method

Variables

4.

Switzerland Review

Cloud computing

5.

Global

Reviews

Cloud and mobile technologies

6.

Global

C-suite executives/ Delphi study

SoMoClo

7.

Global

C-suite executives/ Delphi study

Diverse

Significant Findings/ Recommendations

Gap

Sufficient awareness of both the risks and the management solutions Cloud and mobile technologies have significant influences on business performances HR and marketing departments have adopted and use SoMoClo than finance department. Technology is a significant driver for accounting and finance professionals

Only reviewed risk perception

Remarks

Author(s)

Research Brender and implication Markov, (2013) Brandas Social media is Practical exempted implications et al. (2015)

No reference to Practical ACCA and the tripartite implications IMA (2015)

Only highlights Practical ACCA drivers implications (2016)

Social Media, Mobile and Cloud Technology Use in Accounting

Table 6. (Continued)

8.

Global

AIS research reviews

Expert systems/ artificial intelligence research

SoMoClo is Although AI research experienced a bit of a lull excluded around the turn of the century, artificial intelligence research in accounting has maintained a strong upward trend to date. Standalone expert system use is waning, but larger integrated systems are increasing

Research Sutton et al. implication (2016)

Literature Discourse 69

Country/ Location

Sample/Method

Theories

Variables

Gap

Focus is on technology adoption and affective factors Management The increase in Focus on management accounting global change competition and accounting only changes in technology were the two main contingent factors affecting management accounting change

1.

United States 355 staff/survey Theory of planned Gender, behaviour technology adoption and use

2.

South Africa 4 case studies/ questionnaire, interviews

Contingency theory

Significant Findings/ Recommendations

Men are focused in decision, while women are balanced

Author(s)

Venkatesh et al. (2000)

Waweru et al. (2004)

Social Media, Mobile and Cloud Technology Use in Accounting

S/N

70

Table 7. Summary of Selected Empirical Research.

United States 271 accounting Not mentioned faculty/survey

4.

Taiwan

5.

United States 32 university faculty/ interviews

Multi-case approach: 4 key informant interviews and 7 mobile applications

Use of instructional technology

Fit-viability model Mobile (FVM) technology adoption

Not mentioned

Perception, online teaching

Age, gender, education, academic rank, ethnicity etc. have varying influence on use of instructional technology by accounting faculty FVM is useful in evaluating the adoption of mobile technology. Organisations usually consider fitness but not viability of technology Value-added is a significant incentive for online teaching amongst faculty

Focus on academic accountants only

Ahadiat (2005)

Focus on mobile technology only

Liang et al. (2007)

Focus on university faculty only

Orr et al. (2009)

Literature Discourse

3.

71

72

Table 7. (Continued) Country/ Location

Sample/Method

244 users of information kiosk/ questionnaire 19 IT professionals/ interview and questionnaire

Theories

6.

Taiwan

7.

Taiwan

8.

United States 62 Not mentioned undergraduates/ online survey

Variables

Significant Findings/ Recommendations

Gap

Author(s)

Unified theory of Technology Findings acceptance and use expertise and validated the of technology use theory

Focus on Wang and Shih public users (2009) of technology

Diffusion of innovation theory

Focus on cloud technology only

Lin and Chen (2012)

Focus on mobile technology only

Bomhold (2013)

Cloud computing

Low knowledge of cloud benefits to businesses and low competence amongst IT professionals Educational Accessibility, use of mobile convenience and technology ease of use are major factors identified in the use of mobile apps

Social Media, Mobile and Cloud Technology Use in Accounting

S/N

9.

Australia

10. Canada

23 students/ questionnaire

Not mentioned

Perception of mobile technology use

1,053 students/ questionnaire and case study

Not mentioned

Accounting software, knowledge acquisition

Focus on Richardson mobile et al. (2013) technology amongst students only

Focus on students’ use of software

Boulianne (2014)

Literature Discourse

Portability of device was a significant perceptive factor. The iPod was significant to learning by students with favourable perception towards visual learning Use of both manual and automated learning enhanced knowledge acquisition

73

74

Table 7. (Continued) Country/ Location

Sample/Method

Theories

Variables

Significant Findings/ Recommendations

Gap

Author(s)

11. United States 85 management Not mentioned accountants/ online survey

Spreadsheet proficiency

Focus on management accountants only

Bradbard et al. (2014)

12. Egypt

35 technologies

Expected spreadsheet proficiencies for new management accounting hires are strongly correlated with the usage pattern of practitioners Only three technologies were aligned, hence a significant gap between expected (required) and taught IT skills

The use of only accounting academics

Nokhal and Ismail (2014)

249 accounting Not mentioned lecturers, online survey

Social Media, Mobile and Cloud Technology Use in Accounting

S/N

Excel functional skills

14. Malaysia

Diffusion of innovation theory

Adoption of cloud computing

Technology acceptance model

IT-AIS and performance

15. Nigeria

329 SMEs accounting practitioners in audit and commercial fields/ questionnaire 125 bank staff/ questionnaire

Excel is an important technological application for accountants and graduate accountants are expected to possess moderate skills at least Low levels of awareness amongst respondents and even lower levels of competence

Focus on practicing accountants and students only

Ragland and Ramachandran (2014)

Focus on practicing accountants and auditors only

Tarmidi et al. (2014)

Low IT expertise, high infrastructure investment and low turnaround performance

Focus on IT performance amongst bank staff

Uthman et al. (2014)

Literature Discourse

13. United States 113 practicing Not mentioned accountants and 82 students/ survey

75

76

Table 7. (Continued) Country/ Location

Sample/Method

Theories

16. United States 41 experts: IT Not mentioned professionals (16), IT audit professionals (14) and business management professionals (11)/Delphi study 17. United States Path analysis: Technology 914 consumers, acceptance model online survey

18. Australia

126 Accounting Not mentioned undergraduates

Variables

Significant Findings/ Recommendations

Gap

Author(s)

IT risk IT risk is perceptions of situational the three key stakeholder groups

Focus on IT perception only

Worrell et al. (2014)

Adoption and PU, attitude and use of mobile experience have apps significant positive effect on intention to use mobile apps Social media Results showed use and a relationship academic between social performance media use and academic performance

Focus on mobile technology only

Rivera et al. (2015)

Focus on social media only

Khan et al. (2016)

Social Media, Mobile and Cloud Technology Use in Accounting

S/N

19. Denmark

Online survey – Self-determination Social media, questionnaire theory and social knowledge (114 employees) dilemma theory sharing and interviews (4 organisations)

20. United States 6,885 Ethnically diverse adolescents/ dataset

Self-determination Technology theory use and academic performance

Focus on social media only

Razmerita et al. (2016)

Focus on Qahri-Saremi students only and Turel (2016)

Literature Discourse

Knowledge sharing is not a real ‘social dilemma’, but knowledge workers see the importance of knowledge sharing and the altruistic behaviour No significant influence of utilitarian IT on academic performance, while social media use influenced a negative influence on academic performance

77

78

Table 7. (Continued) Country/ Location

Sample/Method

Theories

21. Sub-Saharan 20 Academics/ Africa questionnaire (online and paper)

Diffusion of innovation and technology acceptance model

22. Australia

Technology acceptance model

13 Accounting academics/ Delphi study, interview

Variables

Cloud diffusion and adoption in education

Significant Findings/ Recommendations

88% of the variance in user intention to adopt and use cloud computing at universities was explained by the constructs in the model Technology Findings relate adoption and to faculty use amongst resistance as a accounting key barrier; faculty individual champions pushing uphill; comfortability and generational attitudes; faculty capacity and support and time/workload

Gap

Author(s)

Focus on academics only

Sabi et al. (2016)

Focus on academic accounting faculty only

Watty et al. (2016)

Social Media, Mobile and Cloud Technology Use in Accounting

S/N

23. China

263 WeChat users/online survey

Not mentioned

24. Pakistan

448 Students Technology and 162 faculty/ acceptance model tutors/ (extended) questionnaire

Modified unified theory of acceptance and use of technology

26. United Kingdom

Constructivist theory

Student and faculty behavioural intention towards the acceptance of mlearning are positively influenced by attitude, PU and prior experience Culture affects innovation in ICT significantly

Provision of better training opportunities does not always improve competence development

Zhan et al. (2016)

Focus on mobile technology only

Bakhsh et al. (2017)

Focus on mobile technology only

Bankole and Bankole (2017)

Focus on training and skills amongst trainees

Chaffer and Webb (2017)

79

1,496 CIMA trainees and 4 interview respondents/ online survey, interviews

Social factors, ICT innovation and mobile phone services Generic skills, accounting education

Social media use Focus on is both beneficial social media and dangerous only

Literature Discourse

25. South Africa 220 Respondents/ questionnaire

Social media, overload and life satisfaction Perception, m-learning

80

S/N

Country/ Location

Sample/Method

Theories

27. United States 583 Generation Social exchange Y consumers/ and social capital survey, theories structural equation modelling

28. Global

150 Countries (1991–2013)/ dataset

Diffusion of innovation theory and technology acceptance model

Variables

Significant Findings/ Recommendations

Gap

Social media and mobile technology

Active use of social media and technological sophistication with mobile technology influenced Generation Y’s attitude Global mobile divide has been reduced to a great extent during the past two decades

Focus on social media and mobile technology only

Zhang et al. (2017)

Focus on mobile technology only

Zhang (2017)

Mobile adoption, penetration and divide

Author(s)

Social Media, Mobile and Cloud Technology Use in Accounting

Table 7. (Continued)

Chapter 3

Study An empirical study was conducted using Nigeria as a case study of developing economies.

Significance of the Study Technology will no doubt shape the next generation of businesses (ACCA, 2016) as it does now; hence professional accountants should be willing, ready and able to competently engage its full potential, else become antiquated (Birt, Wells, Kavanagh, Robb, & Bir, 2018). This lends credence to ascertaining the preparedness of Nigerian professional accountants for the future, and its implications for accountants, accountants’ training and the accounting profession. Given a preliminary finding of lacuna in literature on the use of SoMoClo technologies amongst professional accountants, this study provides a solid basis to spur academic debates. Other significant gaps that make this study relevant border on the development of a measurement criteria/index for ascertaining the technology competence of professional accountants vis-`a-vis the global standard for the education of aspiring professional accountants and professional accountants. It is important as well, to note that this study used the three specialties of practice, policy and research, referred to as elements of the accounting profession (Laughlin, 2011). This study has practical implications for developers of technological applications and infrastructure such that determined use of SoMoClo technologies provides insight for the development of specialised technologies that are best suited for professional accountants. In addition, it provides a framework for selection reviewers (human resource units or departments), which may be used to assess the technology competence of professional accountants as well as information on effective and efficient means for the development of IT competencies amongst accounting professionals, especially in the areas of human capital development, which has become a burning global issue. This study also lent a voice to shaping policy in the areas of professional competence development and maintenance for professional accountants. The results of this study are useful for educational policymakers and regulators in determining, reviewing and maintaining acceptable IT competence levels amongst professional accountants. Social Media, Mobile and Cloud Technology Use in Accounting: Value-Analyses in Developing Economies, 81–233 Copyright © 2020 Emerald Publishing Limited All rights of reproduction in any form reserved doi:10.1108/978-1-83982-160-820201005

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Literature is rife with studies on the adoption of technology as a standalone variable (Lin & Chen, 2012; Tarmidi, Rasid, Alrazi, & Roni, 2014), while this study further examines use amongst the tripartite accounting key actors from the angle of corporate culture and adoption. In addition, the study contributed to existing literature on the dynamics of technology use amongst professional accountants and how it may be influenced by accountants’ training framework and perception; we provide robust empirical data. Three requirements qualify people to become professional accountants and they are an academic degree, professional examination/programme and practical experience (IAESB, 2017). These requirements including the professional accountant’s perception are collectively the object of this research, which makes it strategic for the development of the accounting profession in diverse dimensions. The work therefore has significant policy, research, practical and social implications, especially in the areas of IT competence development, adoption and use amongst professional accountants. We note a giant stride made in the United States by the Pathways Commission and the TTF. This stride was achievable due to efforts to bring professional accountants in academia and practice together under an ‘umbrella’ providing an avenue for collaboration and exchange of ideas to enhance the quality of accounting education. According to the Pathways Commission (2014b) the TTF had two sub-taskforces, one of which carried on a survey on the technologies being used in practice as well as the technologies being taught in accounting degrees. This was to ascertain a balance between training and practice. Similar studies were done in South Africa and Egypt (Nokhal & Ismail, 2014; Wessels, 2004, 2005). A framework of the professional accountants’ willingness, readiness and ‘ableness’ – ability – (WRA) was proposed and used to measure the use of SoMoClo technologies.

Scope of the Study This research covered a study of the accountants’ training framework, perception and competence (expertise) culminating to use of SoMoClo technologies amongst professional accountants. Accountants’ training framework is held as the dyad of academic education and professional education. These include some major elements, such as degrees and awards by tertiary institutions as well as IPD and CPD initiatives of PAOs. The scope of technologies considered in this study are social media, mobile and cloud technologies, prominently abbreviated as SoMoClo (ACCA & IMA, 2015; Accountancy Futures Academy, 2013; Zlateva & Velev, 2012). The use of SoMoClo technologies is held as both ‘intention to use’ and where measurable, ‘actual use’, consistent with technology use studies. This study covered professional accountants in Nigeria in response to the competence requirements for the next generation, critically assessing their crucial role in business, not-for-profits, public sector and academia as practitioners, policymakers and researchers. Perception is limited to PEOU and PU.

Study

83

Research Objective and Questions The general objective of the study is to value-analyse the accountants’ training framework on the use of SoMoClo technologies amongst Nigerian professional accountants. The study provided answers to the following research questions:

• • • •

What SoMoClo technologies do Nigerian professional accountants use? How does the technology competence of Nigerian professional accountants align with the IES IT professional competence requirement? What is the relationship between accountants’ training framework and the technology competence of Nigerian professional accountants? To what extent do accountants’ training framework and perception influence the use of SoMoClo technologies amongst Nigerian professional accountants?

Research Hypotheses Two hypotheses are formulated and tested. It is important to state that the second hypothesis has four items of SoMoClo technologies as: (1) social media; (2) mobile applications; (3) mobile devices and (4) cloud. The hypotheses are stated in the null form. H01: There is no statistically significant relationship between accountants’ training framework and technology competence of Nigerian professional accountants. H02: Accountants’ training framework and perception do not significantly affect the use of SoMoClo technologies amongst Nigerian professional accountants.

Methodology The methods used in achieving the objectives and testing the hypotheses are detailed.

Research Design The survey research design was ‘pioneered in the 1930–40s by sociologist Paul Lazarsfeld’ (Bhattacherjee, 2012, p. 73) and has become widely used in quantitative research. The use of the survey design by Keneley and Jackling (2011) provides useful insights into methods used for an explanatory research of this nature in an accounting environment. Methods that have been used for data gathering in many related researches include Delphi study (Worrell, Bush, & Di Gangi, 2014), interviews (Bui & Porter, 2010) and questionnaire (Gammie, Cargill, & Hamilton, 2010; Kotb, Roberts, & Stoner, 2013) which usually adopt snowball, convenience and purposive sampling techniques. Both descriptive and inferential statistics have also been used for data analysis. Descriptive techniques that have been used include measures of central tendency such as mode and mean, and measures of dispersion such as variance and standard deviation (Stainbank &

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Social Media, Mobile and Cloud Technology Use in Accounting

Gurr, 2016). Some inferential statistics that have been used include Chi-square, correlation and regression; however, it is noteworthy that some of the related studies (Ahadiat, 2005; Khan, Kend, & Robertson, 2016; Watty, McKay, & Ngo, 2016) used more of descriptive statistics. Few related studies, however, used inferential statistics (Bradbard, Alvis, & Morris, 2014; Chaffer & Webb, 2017; Jackson & Cossitt, 2015). Many of the studies tested for the validity and reliability of their research instruments and models. Some used the test–retest (Jeake, Ebimobowei, & Binaebi, 2013), Cronbach’s alpha (Boulianne, 2014; Flood & Wilson, 2008; Jeake et al., 2013; Kanellou & Spathis, 2013; Lin, 2008; Mandilas, Kourtidis, & Petasakis, 2014; Sabi, Uzoka, Langmia, & Njeh, 2016) and composite reliability (Appiah-Adu, Okpattah, & Djokoto, 2016; Gallego, Bueno, & Noyes, 2016; Gupta, Seetharaman, & Raj, 2013; Iyoha, 2011; Sabi et al., 2016; Wang & Shih, 2009; Zhan, Sun, Wang, & Zhang, 2016). Validity was mainly ascertained using the face and content validity tests by expert reviews of the instruments (Sabi et al., 2016). This study captured a group of SMEs and/or key informants and this is a method that has been used (Gallego et al., 2016; Kearns, 2016; Qahri-Saremi & Turel, 2016; Watty, Sugahara, Abayadeera, Perera, & McKay, 2012). The study of technology informed the development of the research design to adopt the use of an online survey using Google Forms. Google Forms is a free cloud-enhanced survey manager, with inter-platform operability functionality, such that the results from the survey can be easily transferred to other data analysis applications, such as Microsoft Office Excel and Statistical Package for the Social Sciences (SPSS), which were used. It is instructive to state, however, that Google Forms is not the only platform with such affordances; albeit a distinguishing factor is that it is free. This method of using cloud-enhanced survey applications has been used for research of this kind (Dijkmans, Kerkhof, & Beukeboom, 2015; Khan et al., 2016; Sabi et al., 2016; Worrell et al., 2014). Other cloudenhanced applications for online survey that have been used are Survey Monkey (Bradbard et al., 2014; Watty et al., 2012) and JotForm (Kolawole, 2018). Due to the issues of low response from online surveys, follow-up email reminders were sent to non-responders; this approach is recommended and has been used (Kanellou & Spathis, 2013). Afterwards, the collected responses were used for analysis. It was proposed that if the response rate was below an acceptable level, a paper questionnaire would be introduced using convenience and purposive samples or a switch to Delphi study would be adopted to supplement the data. Sax, Gilmartin, and Bryant (2003) discouraged the use of both web-based and paper-based questionnaire in one administration, due to non-response and response biases. The triangulation approach (multi-method, such as both qualitative and quantitative) as proposed (Botes, Low, & Chapman, 2014) was not adopted. We proposed an alternative method using accountants in the Nigerian ‘Big Four’ (Deloitte, Ernst & Young, KPMG and PwC) or ‘Big Four 1 One’ (Accenture) accounting firms to fairly represent practicing accountants in Nigeria, since their firms have coverage over diverse sectors of the Nigerian economy, while select members from tertiary institutions’ accounting departments could be

Study

85

sampled as accounting researchers. To cover policy accountants was a proposal to use members of five institutions that have oversight on some accounting policy functions such as ANAN and ICAN, who publish regulatory standards of professional competence, ethical conduct and practice of accounting (and auditing) as well as FRCN, CBN and SEC who issue standard policy guidelines for the practice of, especially, corporate reporting. This approach is not novel to accounting research and has been used in Nigeria (Iyoha, 2011). However, due to the efficiency and convenience that the online survey affords (Sabi et al., 2016), the online survey is preferable and was explored before the other options, which later became unnecessary. We conducted a pilot study using professional accountants from Bowen University.

Population, Sampling Techniques and Sample Size The population consisted of Nigerian professional accounting practitioners, policymakers and researchers who are members of any or both of ANAN and ICAN. It has been established in the review that only ANAN and ICAN are indigenous IFAC member bodies in Nigeria (IFAC, 2016), hence the choice. The population determined based on the total number of registered members, including members awaiting disciplinary actions and late members, is ANAN: 32,168 (ANAN, 2018) and ICAN: 43,293 (ICAN, 2018). The figure was reduced to the number of financial members of ANAN and ICAN which stood at 19,838 (ANAN, 2018) and 17,544 (ICAN, 2018), totalling 37,382 as at the end of the 2017 financial year. The responsibility for responding to the email, however, fall grossly on the potential respondents as it is their choice first to have submitted a valid electronic mail address to their PAO, which proved to be false as many addresses bounced. It is also theirs to check their mail and decide to respond to the questionnaire. These are some of the reasons for the usually low response to online surveys. Given the nature of the research, it was decided that an offline, paper questionnaire was incongruent.

Sources, Collection of Data and Research Instrument The main source of data for this research was primary – a questionnaire administered using online medium. The web-based method which is more convenient than the paper-based survey (Sax et al., 2003) was used. We embedded a link (Uniform Resource Locator – URL) to redirect to the survey in a mail containing the research thrust, confidentiality notification and respondents’ responsibility and consent. Opt-out option was available to respondents who may not like to complete the survey at any time. Reminders were sent to nonresponders that were personally contacted using personal campaigns on social media platform such as Twitter, LinkedIn, Facebook and WhatsApp. The preliminary section required respondents to declare a willingness to respond to the survey before an eligibility check. Respondents who did not meet the eligibility criteria were redirected to quit the survey; however, their timestamps

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Social Media, Mobile and Cloud Technology Use in Accounting

without any individually identifying information were recorded. The main part of the questionnaire was divided into sections and a concluding section on demographics. The inclusion of demographics at the end (rather than at the beginning) of survey is not alien to research (Hammond, Danko, & Braswell, 2015). The first section labelled ‘Section A: Social media, mobile and cloud technologies’ enquired about SoMoClo technologies that are available and used by respondents in their professional capacity. Questions in this section border on device, applications and operating system preference and use. It went further to ask about institutional adoption of SoMoClo technologies. The second section (B) sought to determine the use of technology as well as competence levels. Section C ascertained respondents’ training and perception as well as area(s) of specialty. Section D requested respondents’ demographic data such as gender, age group, experience and other professional membership-related questions. With moderate internet connectivity and speed, responding to the online survey should take about 15–20 minutes.

Definition and Measurement of Variables The main variables for the study are perception and accountants’ training framework as independent variables while use of SoMoClo technologies as the dependent variable. Demographics (age, experience and gender) were held as moderating variables, consistent with many technology studies. A comprehensive measurement of perception, especially in social fields such as psychology and sociology, may require the appropriation of a variety of concepts and constructs such as awareness, understanding, choice, attitude, trust and ‘overtrust’; however, for the purpose of this study, perception is limited to only two of many validated constructs – PEOU and PU as used by TAM. Perception was measured using self-assessment (self-reported scores); although this method has some limitations (Cote & Latham, 2016), its use is not alien to accounting research (Strong & Portz, 2015). The measurement of accountants’ training framework was limited to the dyadic variables of academic and professional education, which are the significant requirements for being recognised as a professional accountant. Measurement for accounting specialty is one-dimensional, such that primary identification of respondents as any of practitioners, policy or research accountants was used. Use of and intention to use SoMoClo technologies were measured using self-reported responses and the WRA framework. Experience was taken at face value.

Data Analysis Techniques According to a research on statistical tools used amongst Emerald authors, Microsoft Excel ranked first, followed by SPSS. It recorded further that ‘69% of Social Science and Economics scholars used SPSS’ (Flenley, 2016, p. 7). The research tools adopted for use by this study include Microsoft Excel, SPSS and AMOS. It is instructive to state that AMOS accounted for only about 2% of the

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tools used amongst Emerald authors (Flenley, 2016). Other tools that can be used for analysis are STATA, R, E-Views, MATLAB and SAT.

Techniques for Objectives and Hypotheses Testing An important area of research data analysis is the test of the research instrument to ascertain its reliability and validity. This is to forestall an incidence of incomplete data, incongruent data or any other form of ambiguities in the collected data, which may render the data from the instrument un-useful due to its irrelevance or inadequacy for the research it was collected for. ‘Reliability and validity, jointly called the “psychometric properties” of measurement scales, are the yardsticks against which the adequacy and accuracy of our measurement procedures are evaluated in scientific research’ (Bhattacherjee, 2012, p. 55). Reliability can be measured as individual item reliability through the use of factor loading (Gimenez, Sierra, Rodon, & Rodriguez, 2015; Iyoha, 2011), interrater reliability, test–retest reliability, split-half reliability and internal consistency reliability (Bhattacherjee, 2012). Inter-rater reliability is tested using the Krippendorff’s alpha (van Beest, Braam, & Boelens, 2009), while the test–retest reliability is used to determine the internal consistency of an instrument through the comparison of the Cronbach’s alpha for each administration (Jeake et al., 2013). Internal consistency reliability is tested using the Cronbach’s alpha and composite reliability as well (Gallego et al., 2016; Iyoha, 2011). Cronbach’s alpha is, however, the most commonly used measure for the internal consistency reliability of a research instrument and it is highly recommended that the Cronbach’s alpha should be closer to 1 to guarantee a reliable instrument (Bakhsh, Mahmood, & Sangi, 2017; Bankole & Bankole, 2017; van Beest et al., 2009; Gallego et al., 2016; Hong et al., 2016; Iyoha, 2011; Jeake et al., 2013; Lin, 2008; Ogundeji, Oluwakayode, & Tijani, 2014; Ram, Corkindale, & Wu, 2013; Rivera, Gregory, & Cobos, 2015; Sabi et al., 2016). There are two approaches to ascertaining the validity of a research instrument and although both approaches can be used individually and separately, it is advised to use both approaches. They are the theoretical and empirical approaches (Bhattacherjee, 2012). The theoretical approach is determined using a translational or representational validity, which are of two types, that is, face validity and content validity, and this is done by expert reviews of items in the research instrument. The use of expert panel review was adopted for this study. It has been argued that it is difficult to assess content validity of especially highly abstract and complex constructs, while face validity is quite easy to determine by using a panel of experts (Bhattacherjee, 2012). Ling and Nawawi (2010) measured content validity using pre-test (pilot study) which gave respondents the opportunity to state their understanding of the questionnaire as well as any challenges faced in filling it. Empirical approach to ascertaining the validity of a research instrument is done by examining the criterion-related validity, with four different types, that is, convergent validity, discriminant validity, concurrent validity and predictive validity. In many related studies, convergent and discriminant validity are

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measured together using the confirmatory factor analysis (CFA) and average variance extracted (AVE) (Bakhsh et al., 2017; Gallego et al., 2016; Gimenez et al., 2015; Gupta et al., 2013; Ogundeji et al., 2014; Ram et al., 2013; Sabi et al., 2016; Venkatesh, Morris, & Ackerman, 2000; Wang & Shih, 2009; Zhan et al., 2016; Zhang, Omran, & Cobanoglu, 2017). The decision rule used for convergent reliability is that the AVE should exceed 0.50, while the rule for discriminant validity entails a comparison between the square root of the AVE for each latent variable and the correlation between the latent variable and any other latent variable. Usually, the square root of AVE should be higher for the construct to be said to be adequately valid. Another method adopted in literature is the comparison of the correlation such that the correlation values of similar variables should converge around a number, while different variables should differ (Iyoha, 2011). In many of the reviewed studies, concurrent validity and predictive validity were not mentioned nor measured and this supports the claim that they are not common in social science research (Bhattacherjee, 2012). Face and content validity were tested before the administration of the pilot study by expert reviews and were retested given the fact that some items in the instrument were altered partially and completely afterwards. Reliability was tested using the results of the pilot study. Internal consistency reliability was measured using the Cronbach’s alpha (a). The choice of these tests is based on its ability to assist in determining the validity and reliability of the research instrument and its popular use in technology-related studies. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was used, as well as the F-test and the Bartlett’s test of sphericity. For hypotheses testing, there are three types of validity, that is, internal validity (causality), external validity (generalisability) and statistical conclusion validity (Bhattacherjee, 2012). For this study, it will be difficult to determine internal validity because cause and effect are measured at the same time and the researcher does not have any influence over ‘cause’ to manipulate it; this violates one of the conditions for ensuring adequate internal validity. With the population of the study, that is, ANAN and ICAN members, external validity may be assured, owing to the diverse nature of respondents; hence results from the survey should be generalisable for all Nigerian professional accountants or even to other climes with similar conditions. Finally, statistical conclusion validity was ensured such that all included variables in the test of hypotheses met the assumptions and conditions of the test and the chosen test statistic is appropriate for the hypotheses.

Proposed Technique for Theory Testing This study contributes to literature by proposing a theory called the PLESUT, and this theory needs to be tested, but not in this study. According to Bankole and Bankole (2017) ‘the predominant positivist approach for performing scientific research relies on developing sound theoretical frameworks which entails statistical rigorous testing and confirmation of theories’ (p. 498).

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We propose the testing of the proposed theory (PLESUT) using structural equation modelling (SEM). SEM is an effective technique for testing the PLESUT. ‘SEM is an extension of the General Linear Model (GLM) that enables a researcher to test a set of regression equations simultaneously’ (The Division of Statistics + Scientific Computation, 2012, p.5). SEM software should also be used for ease of analysis. Available SEM software that have been used in IT studies include EQS (Lankton & McKnight, 2012), Mplus (Lee, Chen, & Chan, 2017), SmartPLS (Gupta et al., 2013; Ram et al., 2013; Sabi et al., 2016; Zhan et al., 2016) and Warp PLS (Bankole & Bankole, 2017). AMOS appears to be the highly favoured, given that it has been used widely (Alshehri, 2012; Bakhsh et al., 2017; Klassen, 2000; Moreno-Murcia, Torregrosa, & Pedreño, 2015; Moses et al., 2015; Ogundeji et al., 2014; Qahri-Saremi & Turel, 2016; Rivera et al., 2015; Wang & Shih, 2009; Zhang et al., 2017). Others include LISREL and SEPATH (Alshehri, 2012). The purpose of the proposed theory is to ascertain if the model being proposed has higher explanatory powers than previous technology use theories and models, especially in accounting profession. The choice of SEM is because PLESUT is still in the design and exploratory stage and the measures and relationships being proposed have not been properly tested in previous studies. In addition, based on the constructs and their proposed relationships, SEM is well befitting for the proposed theory (Sabi et al., 2016; Zhan et al., 2016). SEM is a sophisticated analysis that can be used to model the outcome in one regression equation as a predictor in another equation in an interrelated system of regression equations (Bhattacherjee, 2012). Furthermore, SEM is a statistical technique for simultaneously testing and estimating causal relationships amongst multiple independent and dependent constructs (Bhattacherjee, 2012; Gupta et al., 2013). The use of SEM in technology-related studies can be seen as proof of its efficacy to demystify very complex variables and their relationships and its use is far-reaching in technology, accounting and other fields to define complex relationships (Alshehri, 2012; Appiah-Adu et al., 2016; Bakhsh et al., 2017; Bankole & Bankole, 2017; Gallego et al., 2016; Gupta et al., 2013; Hong et al., 2016; Lee et al., 2017; Ogundeji et al., 2014; Qahri-Saremi & Turel, 2016; Ram et al., 2013; Sabi et al., 2016; Wang & Shih, 2009; Zhan et al., 2016; Zhang et al., 2017).

Specific Objective One This objective highlighted most of the specific SoMoClo technologies available and identified the technologies that Nigerian professional accountants use in their professional capacity. In addition, the objective reviewed the pattern of use of SoMoClo technologies amongst Nigerian professional accountants. This was to determine the practice of use amongst the three categories of professional accountants, looking out for trend with respect to device and operating system preference and general use of SoMoClo technologies. This objective is descriptive in nature, hence was achieved using descriptive statistics. The results from respondents were presented using statistical tables and techniques such as

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frequency, percentages, mode and cross-tabulation for categorisation amongst the three categories of Nigerian professional accountants. This method of using descriptive statistics is in tandem with similar technology use studies (Ahadiat, 2005; Khan et al., 2016; Watty et al., 2016). A significant contribution of this study through this objective is the categorisation of the use of SoMoClo technologies amongst the three categories of professional accountants, which provides information as to what technologies are available to practitioners, policymakers and researchers in Nigeria and how they use the technologies in their professional capacities. This adds value to technology education policy and practice, giving insights into relevant SoMoClo technologies that are expected to be encountered by especially new graduates and professional accountants. It is expected that the findings of this study with respect to this specific objective will also add value to the development of relevant technologies that can be adopted by professional accountants in their professional capacities.

Specific Objective Two Apart from developing professional competence, other desirable outcomes of the IES are to: reduce the ‘international differences in the requirements to perform a role as a professional accountant’ and facilitate ‘the global mobility of professional accountants’ (IAESB, 2017, p. 7). This second objective seeks to ascertain if these outcomes are met by and amongst Nigerian professional accountants. This objective pertains to the comparison of the technology competence of Nigerian professional accountants and the IES IT competence standard. This study adopted the use of the IES as the benchmark for comparison with actual technology competence because (1) it is a global standard published by a globally recognised accounting education board, (2) it is a neutral benchmark of a sort for all providers of professional accounting education and (3) ANAN and ICAN are signatories (based on their membership of IFAC) to the adoption and adaption of the IES for the training of their members. Other standards that could be used are the NUC BMAS, NBTE BMAS, ANAN and ICAN IT subjects’ desired outcomes. It is, however, relevant to state that the IES is issued for adoption by IFAC members primarily, then to other interested stakeholders such as tertiary institutions. The goal of the IES is to provide guidelines in the training of aspiring professional accountants and professional accountants, hence its adoption as a measure for comparison. Preliminary investigations show that not all professional accountants go through academic accounting education (university and/or polytechnic systems), while some of the others who pass through the tertiary education system do not necessarily study accounting as their first course. This will therefore result in divergent basis for their evaluation. IES is a standard measure for professional accounting education globally, hence provides a suitable evaluation basis for all professional accountants. It should be noted that the IES is expected to be blended into academic accounting education. A related study to this objective used accounting academics in Egypt (Nokhal & Ismail, 2014), while this study

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surveyed all three categories of professional accountants in Nigeria; this is to ensure that the views of all relevant stakeholders are captured to enhance generalisation of findings. The main focus of the objective hinges on the desire to ascertain the extent of gap if any, between the competence of respondents and the IES stipulations based on three responsibilities as managers, designers and evaluators of information systems (IAESB, 2007). This is significant to ensure that professional accountants do not only acquire end-user skills but are informed about the development and control of technologies. In addition, competency and proficiency levels for other specific SoMoClo technologies were tested. Nigerian professional accountants’ competence is measured by self-reported scores, while the IT IES competence standard is as enshrined in the IES. The measurement took two levels – technical competence and professional skills. The use of self-assessment in measuring competence is approved by the IAESB (IAESB, 2015b, p. 131) despite its apparent shortcomings. Results from the survey were presented using statistical table using the cross-tabulation technique, consistent with a method adopted by a related study (Nokhal & Ismail, 2014). This objective was also tested using Chisquare and correlation tests.

Specific Objective Three The third objective is descriptive and perceptive. It examined what respondents feel about some areas of their training that influenced their technology competence. The research instrument asked respondents to specify how they feel about technology competence based on their interface with academic and professional education. Polar questions and Likert scale-type statements were used, and results were presented using tables showing frequencies, percentages and crosstabulations amongst the categories of professional accountants. An inter-item correlation test was carried out as well. This was to gain more insights into the relationships amongst the questions asked.

Specific Objective Four The fourth and last objective relates to analysing the influence of accountants’ training framework and perception on Nigerian professional accountants’ use of SoMoClo technologies. The significance of this objective is to determine what factors affect (not cause) the use of SoMoClo technologies amongst professional accountants apart from those already identified in literature. Literature is rife with technology use studies (Ahadiat, 2003, 2005; Bankosz & Kerins, 2014; Bomhold, 2013; Dowling & Leech, 2014; Liang, Huang, Yeh, & Lin, 2007; Qahri-Saremi & Turel, 2016; Rivera et al., 2015; Venkatesh et al., 2000; Wang & Shih, 2009; Willis, 2016; Zhang et al., 2017); however, the difference that this study adds to literature is the use of the training framework of professional accountants, especially the differentiation and integration of academic and professional accounting education. In addition, the objective was achieved

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within specialty-context of professional accounting and moderated with age, experience and gender.

Conceptual Framework for Analysis Producing professional accountants with robust acumen is necessary to uphold and sustain the relevance of professional accountants and the accounting profession (Awomolo, 2002). In addition, it has the significant potential to improve the value and social identity of professional accountants, while this is necessary, it is essential to verify how professional accountants are inclined to adopting new technologies and how they use technologies in enhancing their professional competence and its implications for accounting education. We draw on a number of interdisciplinary approaches to concretise a conceptual framework for analysis. It is imperative to posit that the future relevance of professional accountants may be significantly tied to their engagement (adoption and use) with the offerings of technology. One of the focal approaches to the framework for analysis is based on the concept of WRA used to explain technology use. This view is extensively supported in literature that intention can and has been used both as a predictor of use and has been used as the dependent variable for usage (Venkatesh, Morris, Davis, & Davis, 2003). Drawing from the Venn diagram model of set theory, we underscored that intention to use technology is not a unidimensional construct, but a multidimensional construct, hence was measured by a central point with significant interplay amongst the three constructs. Willingness is held as dependent on adoption, while ‘ableness’ is a function of training, leading to competence, and readiness is forged by perception. Points (p, q and r) represent an indication that a professional accountant is assumed to possess any of the three attributes without the other two, while each intersection (a, b and c) showcases that a professional accountant possesses any two combination of WRA without the third, then the centre (x) is assumed to validate a professional accountant as possessing all three values, which then qualifies as the conceptualised prerequisite for use of SoMoClo technologies. The relationship is shown in Fig. 5. The study lends from the mathematical application of matrix to draw up a 3 3 3 matrix in explaining the relationship amongst the three categories of professional accountants (tripartite accounting) and the three categories of technological focus of the study (SoMoClo technologies). A critical assessment of each class of professional accountant as against the competent engagement of each of SoMoClo technologies is shown in the matrices. Matrix 1 is a 3 3 1 matrix used to represent the three categories of professional accountants (a, b, c). Matrix 2 is a 1 3 3 matrix used to depict the use of SoMoClo technologies (x, y, z), and Matrix 3 shows the relationship between the two previous equations in a dynamic fashion. The grouped x value in Fig. 4 was used in its aggregate form as the statistic to compute category-specific professional accountants’ use of SoMoClo technologies.

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Willing q

b

a x

Ready Able p

Fig. 4.

c

r

Multidimensional Measurement of ‘Use’ of SoMoClo Technologies. 0 1 a @bA c ðx y

1 zÞ

0 1 0 1 a a; x a; y a; z @ b A 3 ð x y z Þ ¼ @ b; x b; y b; z A c c; x c; y c; z

2

3

The above matrices depict the classes of professional accountants and their usage of SoMoClo technologies where: a represents accounting practitioners; b represents policy accountants; c represents research accountants; x represents social media technology use (WRA); y represents mobile technology use (WRA) and z represents cloud technology use (WRA). Accountants’ training framework remains the mainstay of that part of education that produces professional accountants in practice, policy and research, finance professionals, business strategists and other professionals; this influences a two-side panorama. First, accountants’ training can be used for competence value prediction or estimation (Dabalen, Oni, & Adekola, 2001) and second, as a factor for social, policy and economic influence (Dumbili, 2014; Mendivil, 2002) inter alia. This is in fact obvious such that the level of competence exhibited by

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Social Media, Mobile and Cloud Technology Use in Accounting Practical experience Initial Professional Development

Professional values, ethics and attitudes Professional skills

Professional education

Technical Competence Continuing Professional Development

Accountants’ training framework

Polytechnic diploma/award Technology competence

Higher National Diploma Academic education

Bachelor University degree/training H

International Education Standards

National Diploma

Master Doctor of Philosophy Social media Other training

Use

H

Mobile app Mobile device

Perceived Usefulness

Cloud technology

Perception Perceived Ease of Use Keys Element of Affects Relates to Hypothesis H : Hypotheses

Age

Fig. 5.

Gender

Work Experience

Conceptual Framework for Analysis.

professional accountants may be used to interpret the value of training in a jurisdiction and training may itself be used as a tool for influencing the value of professional accountants’ competence. The study took cognisance of some variables that influence technology use, such as age, gender and experience which have received significant attention in literature (Ahadiat, 2003, 2005; Brender & Markov, 2013; Gallego et al., 2016; Gupta et al., 2013; Lin & Chen, 2012; Tarmidi et al., 2014; Watty et al., 2016) as moderating variables. Accountants’ training framework is a consolidation of the

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dyadic of academic and professional accounting education. The academic accounting component is limited to awards and degrees by polytechnics and universities, that is, ND, HND, B.Sc., M.Sc., Ph.D. and other training certificates. The professional accounting education component includes IPD and CPD. IPD has four components which are technical competence; professional skills; professional values, ethics and attitudes and practical experience. However, for the purpose of analysis, only technical competence and professional skills are used; this is because this study did not include areas of ethical use of technology nor is it concerned with the practical experience component of becoming a professional accountant. It is expected that all respondents for the survey have met the practical experience component of their PAO. Perception is limited to two validated constructs of PEOU and PU. A significant factor that may influence technology use is perceived expenditure (Zhang, 2017); however, given that SoMoClo technologies are mostly cheap and free (ACCA & IMA, 2015), it is not considered significant by this study. In addition, the relative cost of mobile devices compared to other big-sized devices makes it insignificant to consider their costs as relevant to the model. Within specialtycontext of accounting profession, elements of accounting profession highlighted as practice, policy and research (Laughlin, 2011) and strengthened by the construct of the tripartite accounting (Oladele, 2015b) are used to determine the collective prediction of the accounting profession. Hence the dynamics amongst the variables (accountants’ training framework and perception) are conceptualised as influencing professional accountants’ use of SoMoClo technologies. As part of the framework, a structural model for the proposed theory of the study – PLESUT – is presented in Fig. 6 to be used for further study. Conclusively, the relationship amongst the variables in this study is highlighted summarily in Fig. 7.

Results This chapter covers the presentation, analysis and discussion of data obtained by the study. The section is ordered by overview of the data, achievement of objectives and test of hypotheses.

Data Overview This section describes the primary data used by the study. Of interests are the response statistics, demographics of the respondents and some computations based on the conceptual framework, especially the WRA. Response Statistics The survey was live for approximately 12 months from 11 June 2018 to 9 May 2019. During this period, the survey recorded an overall response of 249, out of which 245 respondents agreed to proceed with filling the questionnaire, which should be after reading the introductory part of the survey. Of the 245

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Fig. 6.

Proposed Structural Model for PLESUT.

respondents who proceeded to fill the questionnaire, 203 (82.9%) respondents responded in the affirmative as professional accountants, hence eligible to complete the survey. The remaining respondents who agreed to respond to the questionnaire, that is, 42 (17.1%) respondents who claimed not to be professional accountants, were politely redirected to quit the survey. Responses from nonprofessional accountants were possibly due to personal campaign on social media and/or through referrals. The first response came in at 8.53 p.m. on the first day when the survey was live, while the last recorded response was at 6.47 p.m. on Thursday, 9 May 2019. ANAN and ICAN were officially contacted to help in the administration of the survey to their members, a request they gladly obliged. ANAN went as far as hosting the survey link on her website. The survey redirected ‘unqualified’ respondents to quit the survey, albeit their timestamps without any personally identifying information were recorded. Table 8 shows result on response device,

Study Practitioner

Policymaker

Education

Specialty

Perception

Competence

Adoption

Use

97

Professional accountant

Researcher

Designer

Social media

Fig. 7.

Manager

Mobile

Evaluator

Cloud

Summary of Study Variables.

device preference and cross-tabulation statistics as well as a correlation test result performed on the response device and preferred device data. To boost response rates, repeat reminders were sent several times to a database of professional accountants. Repeated follow-ups to ANAN and ICAN were done as well. Another method encouraged for boosting online survey response rate is to incentivise potential respondents (Deutskens, Ruyter, Wetzels, & Oosterveld, 2014; Nulty, 2008). However, given the social status of this study’s potential respondents, we were unable to afford a suitable incentive; hence this method was not adopted for the study. It should also be noted that many times, people do not like to respond to unsolicited mails, especially from addresses they do not know (Manfreda, Bosnjak, Berzelak, Haas, & Vehovar, 2018). The low response rate to online surveys remains a significant challenge (Manfreda et al., 2018) and serves as a testament to the level of technology adoption in developing economies. The paper survey method was not adopted; given that the core of the study is incongruent with the use of paper administration, as it relates to the use of SoMoClo technologies. Asides this, Sax et al. (2003) discouraged the use of both web-based and paper-based questionnaire in a single administration. It is, however, to be noted that the traditional paper-based option has the tendency of providing more responses (Manfreda et al., 2018; Nulty, 2008). Peculiar challenges to responses of online surveys include, but not limited to, facilitating and enhancing technology infrastructure such as power and internet availability which are profound challenges to technology adoption and use (Sabi et al., 2016). In addition, literature has highlighted reasons for low response to

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Membership Response Statistics PAO

ANAN ICAN Others Total

Response Frequency

6 170 43 219a

Response and Preferred Device Statistics Response Devices

Smart phone Laptop Desktop PC Tablet Other Total

Preferred

Frequency

Percentage

Frequency

Percentage

103 70 18 12 0 203

50.7 34.5 8.9 5.9 0.0 100.0

98 85 1 18 1 203

48.3 41.9 0.5 8.9 0.5 100.0

Social Media, Mobile and Cloud Technology Use in Accounting

Table 8. Response Device and Preferred Device Distribution.

Preferred Device 3 Response Device Cross-tabulation Response Device

Preferred device

Smart phone

Tablet

Desktop PC

Laptop

Frequency % within Preferred device % within Response device % of Total Frequency % within Preferred device % within Response device % of Total Frequency % within Preferred device % within Response device % of Total Frequency % within Preferred device % within Response device % of Total

Smart Phone

Tablet

Desktop PC

Laptop

Total

71 72.4% 68.9% 35.0% 4 22.2% 3.9% 2.0% 0 0.0% 0.0% 0.0% 27 31.8% 26.2% 13.3%

0 0.0% 0.0% 0.0% 7 38.9% 58.3% 3.4% 0 0.0% 0.0% 0.0% 5 5.9% 41.7% 2.5%

10 10.2% 55.6% 4.9% 2 11.1% 11.1% 1.0% 1 100.0% 5.6% 0.5% 5 5.9% 27.8% 2.5%

17 17.3% 24.3% 8.4% 5 27.8% 7.1% 2.5% 0 0.0% 0.0% 0.0% 48 56.5% 68.6% 23.6%

98 100.0% 48.3% 48.3% 18 100.0% 8.9% 8.9% 1 100.0% 0.5% 0.5% 85 100.0% 41.9% 41.9% Study 99

100

Table 8. (Continued)

Response Device

Other

Frequency % within Preferred device % within Response device % of Total Frequency % within Preferred device % within Response device % of Total

Total

Smart Phone

Tablet

Desktop PC

Laptop

Total

1 100.0% 1.0% 0.5% 103 50.7% 100.0% 50.7%

0 0.0% 0.0% 0.0% 12 5.9% 100.0% 5.9%

0 0.0% 0.0% 0.0% 18 8.9% 100.0% 8.9%

0 0.0% 0.0% 0.0% 70 34.5% 100.0% 34.5%

1 100.0% 0.5% 0.5% 203 100.0% 100.0% 100.0%

Symmetric Measures

Ordinal by ordinal Number of valid cases

Spearman’s correlation

Value

Asymp. Std. Errorb

Approx. Tc

Approx. Sig.

0.397

0.065

6.140

0.000d

203

Multiple membership amongst respondents is responsible for the figure. Not assuming the null hypothesis. c Using the asymptotic standard error assuming the null hypothesis. d Based on normal approximation. a

b

Social Media, Mobile and Cloud Technology Use in Accounting

Preferred Device 3 Response Device Cross-tabulation

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web-based survey such as security and privacy issues, web literacy and low use of the internet, amongst others (Manfreda et al., 2018; Nulty, 2008; Sax et al., 2003). Another significant challenge is data, as the researcher found that many electronic mail addresses in the provided database were not correct; hence the notification/request to respond to the survey may not have gotten to the intended recipients. Studies that have used online survey amongst professional accountants in Nigeria are limited. One significant study was on XBRL adoption in Nigeria, and it used 124 respondents from amongst professional auditors in Big Four firms (Ogundeji et al., 2014).

Device Preference Respondents were asked to identify the response device used for the survey amongst smart phone, tablet, laptop and desktop PC. The response to this question highlighted that the most used device is the smart phone with 103 (50.7%) respondents, followed by laptop with 70 (34.5%) respondents. Desktop PC was used by 18 (8.9%) respondents while tablet was used by 12 (5.9%) respondents. In order to gain better understanding on the choice of response device, a question on the personal preferred device of the respondent was asked. The trend was like that of response device result such that 98 (48.3%) respondents prefer the use of smart phone, followed by laptop with 85 (41.9%) respondents. Preference for tablet followed with 18 (8.9%) respondents, while desktop PC was preferred by only one (0.5%) respondent. Another one (0.5%) respondent chose the ‘other’ option. The use of smart phone and desktop PC in responding to the survey exceeded their personal preference, while the opposite went for tablet and laptop. The cross-tabulation result of device preference and response device showed that of the 98 respondents that preferred the use of a smart phone, 71 (73.1%) amongst them responded to the survey using a smart phone. For tablet, 18 respondents highlighted that they prefer its use; however, only seven (38.9%) used it to respond to the survey, while there was only one respondent who preferred the use of a desktop PC and the respondent used it to respond to the survey, thereby scoring 100.0%. There were 85 respondents who preferred the use of a laptop, but only 48 (56.5%) of them used a laptop to respond to the survey. It appears therefore that availability of a device was a stronger determinant of use than preference, although this thesis will have to be further tested more comprehensively for significant result. Findings also showed a positive, but weak, correlation between the preference of devices and their use as the response device for the survey. Employers may need to pay more attention to this, as it can potentially impact on the productivity of employees. The Spearman’s correlation result was 0.397 at p 5 0.000. The continued use of a device, because it is available, not based on preference may be a factor responsible for disinterest in carrying out assignments efficiently, especially in organisations where there is the heavy use of devices. This should begin to enhance the clamour for the BYOD policy, which has only been supported by some organisations as shown by the results (111 respondents, 54.7% pointed that

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their organisation allowed this policy). By the BYOD policy, employees can bring their preferred device to work and use it for their official assignments. It must be stated, however, that the BYOD policy has some challenges, especially around security of information, which must be considered before its adoption.

Specialty and Area of Expertise Based on the construct of the tripartite accounting, there are three specialties, that is, practice, policy and research. However, results from the study have added another specialty, which was not captured earlier – non-practicing professional accountants. For the purpose of discussion of results, this category was not considered significant, albeit it appears in most of the analyses. The statistical results for the primary and secondary specialties as well as the area of expertise based on the primary specialty and cross-tabulations are presented in Table 9. The specialty scope of this study is twofold in three categories due to the multiplicity of roles amongst professional accountants. The survey asked respondents to specify a primary specialty and a secondary specialty. The primary specialty is used throughout the analysis, while passing mention is given to the secondary specialty in some sub-sections, where it is considered significant. In the primary category, only 12 respondents (5.9%) were not practicing professional accountants. The remaining 191 respondents were divided amongst practitioners, policymakers and researchers in the proportion 145 (71.4%), 7 (3.4%) and 39 (19.2%), respectively. In the secondary specialty fold, respondents were able to check as many as all three specialties apart from their primary choice. Respondents were divided amongst practitioners, policymakers and researchers in the proportions 88 (43.3%), 13 (6.4%) and 38 (18.7%), respectively. In the secondary specialty, one respondent chose both the practitioner and researcher specialties while 63 (31.0%) respondents did not have a secondary specialty. Respondents who did not work in any of the three specialties were not asked further as to where they worked; it is only assumed that they may be employed and/or self-employed in non-accounting-related businesses. This may reinforce the thinking that the study of accounting is not only relevant in the field of accounting, but as well in other fields, given that it potentially broadens the horizon of graduate and professional accountants. Using the cross-tabulation technique, based on the multiplicity of roles that professional accountants are engaged in, it is revealing that of the 145 primary practitioners, 62 (42.8%) of them still highlighted that they are secondarily involved with practice. This may imply that their primary area of practice may be complemented by another area of practice. In addition, 10 (6.9%) of the primary practitioners claimed to be secondarily involved in policymaking while 21 (14.5%) were secondarily involved in teaching/research in tertiary institutions. Fifty-two (35.9%) of the primary practitioners did not have a secondary specialty, basically choosing to remain as practitioners only. The involvement of practitioners in the teaching environment is in tandem with the recommendation from major players of the accounting profession to improve the value of accounting

Table 9. Primary and Secondary Specialty Distribution. Primary Specialty Variables

Non-practicing/none Practitioner Policymaker Researcher Combination Total

Secondary Specialty

Percentage

Frequency

Percentage

12 145 7 39 – 203

5.9 71.4 3.4 19.2 – 100.0

63 88 13 38 1 203

34.5 40.1 5.6 19.7 0.5 100.0

Frequency

Percentage

61 38 22 19 17 11 11 8 7 4 3

30.0 18.7 10.8 9.4 8.4 5.4 5.4 3.9 3.4 2.0 1.5

Area of Expertise

Financial accounting and reporting Auditing (external) Taxation Corporate finance Auditing (internal) Public sector Consulting Cost and management (performance management) Investigation, assurance and forensic Risk Charities and not-for-profit

Study

Frequency

103

104

Table 9. (Continued)

Ethics Other Total

Frequency

Percentage

1 1 203

0.5 0.5 100.0

Primary Specialty

Primary specialty and secondary specialty cross-tabulation Secondary specialty NP/N Frequency % within SEC specialty % within PRI specialty % of Total PRA Frequency % within SEC specialty % within PRI specialty % of Total POL Frequency % within SEC specialty % within PRI specialty % of Total

NP/N

PRA

POL

RES

Total

8 12.7% 66.7% 3.9% 4 4.5% 33.3% 2.0% 0 0.0% 0.0% 0.0%

52 82.5% 35.9% 25.6% 62 70.5% 42.8% 30.5% 10 76.9% 6.9% 4.9%

1 1.6% 14.3% 0.5% 3 3.4% 42.9% 1.5% 2 15.4% 28.6% 1.0%

2 3.2% 5.1% 1.0% 19 21.6% 48.7% 9.4% 1 7.7% 2.6% 0.5%

63 100.0% 31.0% 31.0% 88 100.0% 43.3% 43.3% 13 100.0% 6.4% 6.4%

Social Media, Mobile and Cloud Technology Use in Accounting

Area of Expertise

RES

Frequency % within SEC specialty % within PRI specialty % of Total COMB Frequency % within SEC specialty % within PRI specialty % of Total Total Frequency % within SEC specialty % within PRI specialty % of Total Area of expertise and primary specialisation cross-tabulation AUDX Frequency % within AOE % within PRI specialty % of Total

0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0% 12 5.9% 100.0% 5.9%

21 55.3% 14.5% 10.3% 0 0.0% 0.0% 0.0% 145 71.4% 100.0% 71.4%

0 0.0% 0.0% 0.0% 1 100.0% 14.3% 0.5% 7 3.4% 100.0% 3.4%

17 44.7% 43.6% 8.4% 0 0.0% 0.0% 0.0% 39 19.2% 100.0% 19.2%

38 100.0% 18.7% 18.7% 1 100.0% 0.5% 0.5% 203 100.0% 100.0% 100.0%

0 0.0% 0.0% 0.0%

34 89.5% 23.4% 16.7%

0 0.0% 0.0% 0.0%

4 10.5% 10.3% 2.0%

38 100.0% 18.7% 18.7%

Study 105

106

Table 9. (Continued)

Area of expertise

AUDI

IAF

PS

FAR

CNP

Details

NP/N

PRA

POL

RES

Total

Frequency % within AOE % within PRI specialty % of Total Frequency % within AOE % within PRI specialty % of Total Frequency % within AOE % within PRI specialty % of Total Frequency % within AOE % within PRI specialty % of Total Frequency % within AOE % within PRI specialty % of Total

0 0.0% 0.0% 0.0% 1 14.3% 8.3% 0.5% 2 18.2% 16.7% 1.0% 4 6.6% 33.3% 2.0% 0 0.0% 0.0% 0.0%

15 88.2% 10.3% 7.4% 6 85.7% 4.1% 3.0% 8 72.7% 5.5% 3.9% 36 59.0% 24.8% 17.7% 3 100.0% 2.1% 1.5%

1 5.9% 14.3% 0.5% 0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0% 3 4.9% 42.9% 1.5% 0 0.0% 0.0% 0.0%

1 5.9% 2.6% 0.5% 0 0.0% 0.0% 0.0% 1 9.1% 2.6% 0.5% 18 29.5% 46.2% 8.9% 0 0.0% 0.0% 0.0%

17 100.0% 8.4% 8.4% 7 100.0% 3.4% 3.4% 11 100.0% 5.4% 5.4% 61 100.0% 30.0% 30.0% 3 100.0% 1.5% 1.5%

Social Media, Mobile and Cloud Technology Use in Accounting

Primary Specialty

C&M

TAX

CFN

CNS

ETS

1 12.5% 8.3% 0.5% 2 9.1% 16.7% 1.0% 1 5.3% 8.3% 0.5% 0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0%

2 25.0% 1.4% 1.0% 17 77.3% 11.7% 8.4% 14 73.7% 9.7% 6.9% 7 63.6% 4.8% 3.4% 0 0.0% 0.0% 0.0%

1 12.5% 14.3% 0.5% 0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0% 2 18.2% 28.6% 1.0% 0 0.0% 0.0% 0.0%

4 50.0% 10.3% 2.0% 3 13.6% 7.7% 1.5% 4 21.1% 10.3% 2.0% 2 18.2% 5.1% 1.0% 1 100.0% 2.6% 0.5%

8 100.0% 3.9% 3.9% 22 100.0% 10.8% 10.8% 19 100.0% 9.4% 9.4% 11 100.0% 5.4% 5.4% 1 100.0% 0.5% 0.5%

Study

Frequency % within AOE % within PRI specialty % of Total Frequency % within AOE % within PRI specialty % of Total Frequency % within AOE % within PRI specialty % of Total Frequency % within AOE % within PRI specialty % of Total Frequency % within AOE % within PRI specialty % of Total

107

108

RSK

OTH

Total

Frequency % within AOE % within PRI specialty % of Total Frequency % within AOE % within PRI specialty % of Total Frequency % of Total

1 25.0% 8.3% 0.5% 0 0.0% 0.0% 0.0% 12 5.9%

2 50.0% 1.4% 1.0% 1 100.0% 0.7% 0.5% 145 71.4%

0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0% 7 3.4%

1 25.0% 2.6% 0.5% 0 0.0% 0.0% 0.0% 39 19.2%

4 100.0% 2.0% 2.0% 1 100.0% 0.5% 0.5% 203 100.0%

Notes: AOE: Area of expertise; AUDI: Auditing (internal); AUDX: Auditing (external); C&M: Cost and management (performance management); CFN: Corporate finance; CNP: Charities and not-for-profit; CNS: Consulting; COMB: Combination; ETS: Ethics; FAR: Financial accounting and reporting; IAF: Investigation, assurance and forensic; NP/N: Non-practicing/none; OTH: Other; POL: Policymaker; PRA: Practitioner; PS: Public sector; RES: Researcher; RSK: Risk; TAX: Taxation.

Social Media, Mobile and Cloud Technology Use in Accounting

Table 9. (Continued)

Study

109

education when practitioners with practical experience are allowed to teach in universities and possibly complete their doctoral degree (Pathways Commission, 2014a). Policymaking boards such as the IAESB give a generous number of board membership seats (about 50%) to practitioners (IAESB, 2017), thereby making way for practitioners to participate in policymaking aspect of the accounting profession, which may explain the involvement of practitioners in policy. The policy specialty presented thought-provoking results. Of the seven primary policymakers, three (42.9%) were secondarily involved with practice and two (28.6%) were still involved in policy specialty while one was not involved in anything else. The last respondent amongst the primary policymakers chose a combination of practitioner and researcher as secondary specialty. The number of primary policymakers involved in research is low and this is somewhat disheartening. This implies that undergraduate and possibly postgraduate accounting students may be deprived the experience of a professional policymaker. It further means that students may only be taught the theoretical groundings of policy in accounting without an adjoining exposure to practical experience in policy matters. This may be one of the significant factors for the poor level of understanding of the tripartite accounting, especially the policy aspect amongst undergraduates as found by Oladele (2015a, 2015b). Results showed that respondents who are primarily involved in policymaking are more secondarily involved in the business of practice. The influences of practice are thought to potentially becloud the judgement of policymakers, given that practitioners who are willing to join the IAESB in the non-practitioner category must have enjoyed a cooling off period of not less than 3 years before becoming eligible for appointment (IAESB, 2017). Furthermore, from amongst the 39 primary researchers, 19 (48.7%) are secondarily involved in practice, which implies that they are possibly involved in the running of at least a firm of chartered accountants as partners and/or are affiliated as consultants or technical advisers. In addition, only one (2.6%) of the primary researchers is involved in policymaking. This is a testament to the subtle relegation of academics in the membership of policymaking boards as asserted by Salisu (2011). Seventeen (43.6%) of the primary researchers chose the specialty of research as their secondary specialty, while 2 (5.1%) of them are not into any other specialty. One respondent who is primarily a policymaker highlighted that he is secondarily a practitioner and a researcher as well; this is a true case of jack of all trade. The low involvement of researchers in other fields may be due to the demands of the academic environment, especially the publish or perish slogan. Others include administrative responsibilities, mentoring of postgraduate students and young Ph.D.s, which all contribute to compound the work of academic accountants, making them un-readily available to diversify into other fields. It is indeed to be noted that ‘…accounting academics often find themselves torn between two primary roles – their roles as teachers and the requirement in a research-led university that they be actively involved in research’ (Lubbe, 2014, p. 108). As earlier stated, 12 of the respondents do not fall within the primary specialtycontext of this study. Out of this number, four (33.3%) are secondarily involved in the practice of accounting, while the remaining eight (66.7%) are not involved in any form of accounting-related practice, policy or research work. Since the

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respondents were not asked to provide further information on their work, it can only be assumed that they probably work part-time when called upon or they are sleeping partners of a firm of chartered accountants, whose goodwill is used to boost the business image. Respondents were further asked to choose a primary area of expertise based on their primary specialty. More than 10 areas were highlighted, and the distribution showed that 61 (30.0%) of the respondents chose the financial accounting and reporting area, followed by external auditing with 38 (18.7%) respondents. This was followed by taxation with 22 (10.8%) respondents and followed closely by corporate finance with 19 (9.4%) respondents and internal auditing with 17 (8.4%) respondents. Next on the list is a tie between public sector and consulting with 11 (5.4%) respondents each, while performance management had eight (3.9%) respondents. Investigation, assurance and forensic was down the line with 3.4%, while risk had 2.0% and charities and not-for-profit had 1.5% selection, ethics and others had just one respondent each. The results of the cross-tabulation of area of expertise with primary specialty provide more insight and practitioners dominated all the areas of expertise. The respondents who chose external auditing are unequally torn between research (10.5%) and practice (89.5%). Internal auditors were shared amongst practitioners (88.2%) and policy and research in the same proportion of only 5.9% each. 85.7% of those in investigation, assurance and forensic were practitioners, while 72.7% of public sector experts were practitioners. Of the 61 respondents with primary expertise in financial accounting and reporting, more than half, that is, 36 (59.0%), are primary practitioners, 18 (29.5%) amongst them are primarily researchers, while three (4.9%) respondents amongst them are policymakers and the remaining four (6.6%) are not practicing professional accountants. All charities and not-for-profit experts are practitioners, while most of the consulting experts (73.7%) were practitioners. Ethics and ‘Other’ had one respondent each, and while the ethics expert was a researcher, the ‘other’ was a practitioner. Risk as the last expertise had four respondents and two (50.0%) are practitioners, while one is a researcher and the other is a non-practicing accountant. Given that the question on area of expertise was based on respondents’ primary specialty and a required question, the non-practicing accountants who chose an area of expertise may have done so because they did not fully understand the question or that they chose their area of interest notwithstanding the fact that they did not primarily and necessarily function as professional accountants. We are inclined to favour the latter thesis. In all the other areas of expertise, only performance management and ethics have scores in the research specialty higher than that of practice. This strengthens the reality that the practice specialty is dominant in the accounting profession and this may be the reality in other professions.

Gender Responses from the survey showed that 144 (70.9%) respondents were male; the results and its cross-tabulation with the tripartite specialties are presented in Table 10. This is representative of the population and a research bias that has

Table 10. Gender Distribution and Crosstab with Specialty. Gender

Frequency

Percent

Male Female Total

144 59 203

70.9 29.1 100.0 Specialties

Variables and Options

PRA

POL

RES

Total

8 5.6% 66.7% 3.9% 4 6.8% 33.3% 2.0% 12 5.9% 100.0% 5.9%

103 71.5% 71.0% 50.7% 42 71.2% 29.0% 20.7% 145 71.4% 100.0% 71.4%

6 4.2% 85.7% 3.0% 1 1.7% 14.3% 0.5% 7 3.4% 100.0% 3.4%

27 18.8% 69.2% 13.3% 12 20.3% 30.8% 5.9% 39 19.2% 100.0% 19.2%

144 100.0% 70.9% 70.9% 59 100.0% 29.1% 29.1% 203 100.0% 100.0% 100.0%

111

NP/N: Non-practicing/none; POL: Policymaker; PRA: Practitioner; RES: Researcher.

Study

Gender and primary specialty cross-tabulation Gender Male Frequency % within gender % within primary specialty % of Total Female Frequency % within gender % within primary specialty % of Total Total Frequency % within gender % within primary specialty % of Total

NP/N

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Social Media, Mobile and Cloud Technology Use in Accounting

been echoed for decades in the accounting profession as a gendered profession (Haynes, 2017). This is also consistent with literature that suggests that the male gender tends to respond to web-based surveys at a higher rate than the female gender (Sax et al., 2003). The results of gender distribution based on specialities present more insightful results. It was found that the tripartite specialties were dominated by the male gender with the most prominent being in practice and the least in policy with a dominance rate of approximately 70% across the specialties. However, the research specialty presented a distinct result such that within the gender frequency, more women (20.3%) were in research than men (18.8%). Within the secondary specialty, however, women dominated in the nonpracticing and policy specialty. Women’s superior involvement in policy matters may be related to their critical views being sought as a more sympathetic, firm and audacious figure, while their higher involvement with non-practicing work may be a result of their desire for self-paced work, family–life balances and other reasons adduced in literature as factors influencing their decisions in professional life. It is important to highlight further that studies have identified a strong influence of female board membership on adherence to corporate governance codes (B´aez, B´aez-Garc´ıa, Flores-Muñoz, & Guti´errez-Barroso, 2018; Briozzo, Albanese, & Santol´ıquido, 2017; Kirsch, 2018; Nadeem, Zaman, & Saleem, 2017). In the same vein their involvement in board composition has been linked to financial performance (Bibi, Balli, Matthews, & Tripe, 2018) and reduced environmental violations (Liu, 2018). However, there is divergence of findings on board composition as ´ it relates to gender diversity in corporate organisations such that Gallego-Alvarez, Garc´ıa-S´anchez, and Rodr´ıguez-Dominguez (2010) found that the composition of corporate boards as it relates to gender may have no significant effect on firm performance. Other studies (Julizaerma & Sori, 2012; Luo, Xiang, & Huang, 2017; Tejedo-Romero, Rodrigues, & Craig, 2017), however, found that women involvement in corporate boards has a statistically significant effect. This result suggests that the accounting profession in general and within specialty-context is dominated by the male gender, which is representative of the general population in the two prominent PAOs in Nigeria. In more certain terms, it appears that more men are entering the accounting profession than women. The results from a previous study (Oladele, 2015a) of accounting students in six universities of the Nigerian south-west geopolitical zone showed that the percentage of female respondents was higher and it was reported that it was representative of the general universities population. In correlation with the result of this study, it translates that more women are studying accounting as a course, but less of them are going into the profession. In supporting this claim, the number of registered members of ICAN as at the end of year 2017 is 43,293 (ICAN, 2018), while SWAN, the female arm, claimed they have about 10,000 members in 2018 (SWAN, 2018). The gender gap is not peculiar to Nigeria and has been studied as a general phenomenon (Lawter, Rua, & Andreassi, 2016; Rasmussen, 2016; Yeganeh & May, 2011) and in the accounting profession specifically (Anderson, Johnson, & Reckers, 1994; Haynes, 2017; Jeake et al., 2013; Khlif & Achek, 2017; Kirkham

Study

113

& Loft, 1993; Windsor & Auyeung, 2006). Some of the reasons adduced by Haynes (2017) for the gap are the gendered nature of accounting profession, motherhood, work–life balance, choices and flexible working, and feminisation and segmentation. There are serious indications of discrimination against women generally and in the accounting profession (Barker & Monks, 1998; Devonport, 2007; Lee, 2014; Single & Almer, 2007; Twomey, Linehan, & Walsh, 2002; Ukwu, 2010; Walker, 2008). It is significant to note, however, that many of the studies were carried out by women, giving a posturing of women fighting for the rights of women. This discrimination is mostly prominent in career progression which is widely tied to information asymmetry concerning informal organisational networks amongst women (Barker & Monks, 1998; Single & Almer, 2007), and there may be indications at the entry level as well such that favouritism is tailored towards men. In developing economies, it appears that the low number of women professional accountants is attributable more to the demands and the social conditioning of the accounting profession. This is premised on the fact that the accounting profession is traditionally seen as a man’s job (Lee, 2014), just like politics. This untrue assertion was unfortunately echoed by the fourth elected Nigerian President after the return to democratic rule in 1999, who said his wife had nothing to do in politics but belonged to the other room, while he stood side-by-side with a woman, who was in fact at that time the Chancellor of Germany. It can therefore be argued that the traditional social conditioning of many established professions is still a significant factor in the determination of which gender gets what, when and how. This discrimination usually leads to what is widely referred to as the ‘glass ceiling’ (Gammie & Whiting, 2013; Khlif & Achek, 2017; Walker, 2008; Yeganeh & May, 2011). It is important to state, however, that women have held and continue to hold peak leadership positions in the accounting profession, in their circles, industry, PAOs and the academia. Surprisingly, in self-employment it is alarming to note the occurrence of glass cage, which is ‘a phenomenon whereby self-employed women earn significantly less than self-employed men’ (Lawter et al., 2016, p. 24). Discrimination also leads to a wide gender pay gap, which women have been clamouring against, with the call heightening (Blundell, Gosling, Ichimura, & Meghir, 2007; Lawter et al., 2016). Despite widespread gender pay gap even in developed nations, Iceland has been leading in the gender equality pay index for 9 consecutive years and capping it with a zero tolerance law for gender pay disparity in 2018 (Wills, 2018). Conclusively on the results on gender and moving slightly from the heteronormativity of gender, which is what holds generally in Nigeria, there is the growing recognition of the LGBTQ. It is even advanced that public accounting has been quick to accommodate these people in many advanced economies, despite popular cultural and ideological prejudices (Lee, 2014). It is important to draw attention to the fact that this phenomenon is not recent, as people with different sexual orientation have been in existence since Bible days with specific reference to Sodom and Gomorrah. With calls from more liberal nations transcending the heteronormativity of gender, we are of the opinion that the sanctity of gender as created by God is kept.

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Age More than half of the respondents, specifically 127 (62.6%), are below the age of 40 years, albeit not less than 20 years of age. No respondent who was below 20 years of age responded to the survey. Sixty-nine (34.0%) respondents were between 40 and 59 years old, and seven (3.4%) respondents were 60 years and more. This is evidence of youthful respondents. It was expected that younger professionals will be more willing to respond to the online survey. Within specialty-context, accounting practice enjoyed more patronage from the crop of young professional accountants such that 55 (37.9%) of the respondents within age group 20–29 years are primarily practitioners. No policymaker was in that age group, while seven (17.9%) were researchers. Practitioners in the age bracket accounted for 78.6% and researchers accounted for 10.0% of total respondents in the age bracket. In the 30–39 age bracket, 39 (26.9%) were practitioners, while 3 (42.9%) were policymakers and 14 (35.9%) were researchers. This amounted to 68.4%, 5.3% and 24.6% for practitioners, policymakers and researchers in the age bracket. Respondents aged 40–49 years were 38 and out of this number 28 (73.7%) respondents were practitioners and three (7.9%) were policymakers, six (15.8%) amongst the tripartite were researchers. Twenty (64.5%) respondents amongst respondents aged 50–59 years were practitioners, while one (3.2%) was a policymaker and eight (25.8%) were researchers. The last were respondents 60 years and more and results showed that three (42.9%) respondents in the age group were practitioners and four (57.1%) of them were researchers. This result on the age of respondents confirmed the a priori expectation of a more willing youthful population responding to the online survey. This is coupled with compelling evidence in literature that older adults are more unwilling to adopt technology (Lazar, Goldstein, & Taylor, 2015; Macedo, 2017), hence may be responsible for the lower response rate from the age bracket above 40 years. We expected to see responses from the age group lower than 20 years, unfortunately none from the age group responded. The exclusion of non-practicing professional accountants in the discussion is deliberate, given that emphasis is only on the tripartite specialties (Table 11). Age has been used as a moderating factor in many studies (Ahadiat, 2005; Venkatesh et al., 2003) and continues to be a significant moderator, especially with respect to technology, which is rapidly evolving. Beyond that, however, the issue of age is prominent in the academia, where there is evidence of an ‘ageing professoriate’ (Harle, 2011, p. 29). The young generation of professional accountants is mostly unwilling to start a career in academics. According to Oladele’s (2015a) study, the NUC stipulates that employment into a research career requires a Ph.D. degree, which should take about three to four years; however, the reality is that many candidates enrolled for the Ph.D. degree spend even close to 10 years pursuing it without completion in many universities in Nigeria especially public ones due to industrial action, the behaviour of the supervisor and candidate as well as bureaucracy, amongst others. This is in gross contrast to the field of practice which usually requires a B.Sc. (or not) and a professional certification. This leads young professionals to practice, where they are readily relevant after their undergraduate study and can earn a decent living. To corroborate this view,

Table 11. Age Distribution and Crosstab with Specialty. Age

20–29 years 30–39 years 40–49 years 50–59 years 60 years and above Total

Frequency

Percent

70 57 38 31 7 203

34.5 28.1 18.7 15.3 3.4 100.0 Specialties NP/N

PRA

POL

RES

Total

Age and primary specialty cross-tabulation Age (years) 20–29 Frequency % within age % within primary specialty % of Total 30–39 Frequency % within age % within primary specialty % of Total

8 11.4% 66.7% 3.9% 1 1.8% 8.3% 0.5%

55 78.6% 37.9% 27.1% 39 68.4% 26.9% 19.2%

0 0.0% 0.0% 0.0% 3 5.3% 42.9% 1.5%

7 10.0% 17.9% 3.4% 14 24.6% 35.9% 6.9%

70 100.0% 34.5% 34.5% 57 100.0% 28.1% 28.1%

Study

Variables and Options

115

116

Table 11. (Continued)

Variables and Options

40–49

50–59

60 and above

Total

Frequency % within age % within primary % of Total Frequency % within age % within primary % of Total Frequency % within age % within primary % of Total Frequency % within age % within primary % of Total

specialty

specialty

specialty

specialty

NP/N

PRA

POL

RES

Total

1 2.6% 8.3% 0.5% 2 6.5% 16.7% 1.0% 0 0.0% 0.0% 0.0% 12 5.9% 100.0% 5.9%

28 73.7% 19.3% 13.8% 20 64.5% 13.8% 9.9% 3 42.9% 2.1% 1.5% 145 71.4% 100.0% 71.4%

3 7.9% 42.9% 1.5% 1 3.2% 14.3% 0.5% 0 0.0% 0.0% 0.0% 7 3.4% 100.0% 3.4%

6 15.8% 15.4% 3.0% 8 25.8% 20.5% 3.9% 4 57.1% 10.3% 2.0% 39 19.2% 100.0% 19.2%

38 100.0% 18.7% 18.7% 31 100.0% 15.3% 15.3% 7 100.0% 3.4% 3.4% 203 100.0% 100.0% 100.0%

Notes: NP/N: Non-practicing/none; POL: Policymaker; PRA: Practitioner; RES: Researcher.

Social Media, Mobile and Cloud Technology Use in Accounting

Specialties

Study

117

an assertion was made that ‘employment opportunities in the private sector are so attractive that talented accounting undergraduates, for example, do not find the PhD sufficiently rewarding to encourage them to pursue advanced degrees…The Nigerian situation in accounting research is dangerously low’ (Okoye, 2009, p. 14). It is commonly said that this young generation is unwilling to defer gratification to a future time. Seeing that it takes years to complete the degree of Ph.D. before an academic career blossoms, only few young ones are attracted. Apart from this, many believe that tertiary institutions provide job security and are a good place to enjoy retirement after active years of service in practice (Phillips & Pugh, 2000). This creates and influences the desire for young professional accountants to opt for accounting practice, then later resort to spend retirement as adjunct tutors or lecturers. In the same vein, the disparity in pay between practice and the academia (Okafor, 2012; Okoye, 2009) is a significant motivator for young professional accountants to venture into practice where they enjoy better remuneration packages. Furthermore, public perception (Awomolo, 2002) and the preference that practitioners enjoy on regulatory boards give incentives to many young professional accountants. The proponents of practice have also dignified the highest status designate, that is ‘Fellow’, such that it has become a pinnacle of some sort in the accounting circles, which young professional accountants aspire to attain, beyond the academic professorial chair. In addition, PAOs have been vigorous in their approach to ‘catch them young’. Amongst these factors, it, however, seems that pay (remuneration package) is the most significant factor cited by authors for disinterest in accounting research. The wide gap in the pay that corporate organisations are willing to offer, and offer compared to what obtains in the academia, has served as a consistent disincentive for scholars (researchers), as they think they can get better remuneration in practice. It has been highlighted that lecturers enjoy (or better still, endure) poor remuneration (Ezezika, 2013), while others who even start their first employment with a university later move to industry in search of greener pasture (Okafor, 2012). In addition, it has been advanced that comparative salary index reveals that accountants with higher degrees that opt for the academia are less remunerated than their colleagues in the accountancy practice (Fatokun & Ojo, 2004). In the same vein, a tweet confirmed that professionals holding the Certified Management Accountant credential continued to enjoy greater earning power (Accounting Today, 2013). This gap in remuneration serves as incentive for graduates to pursue careers in professional practice rather than research or policy-based accounting. Therefore, there is a high level of brain drain amongst graduate accountants and teaching staff towards better-paid sectors (Okafor, 2012).

Experience and Membership of PAOs The questionnaire required respondents to specify the number of years of professional experience that they have generally as a professional accountant as well

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as their membership of PAOs. The experience statistic is assumed as the composite of all accounting-relevant experiences. Apart from the fact that experience is used as a moderating factor in achieving one of the objectives, it provides information to ascertain the reliability of the data on respondents’ age as shown in Tables 12 and 13. The results showed that 82 (40.4%) respondents have one to five years of experience, 52 (25.6%), 22 (10.8%), 12 (5.9%) and 35 (17.2%) respondents have 6–10 years, 11–15 years, 16–20 years and 21 and more years of experience as professional accountants, respectively. With respect to membership of PAOs, six respondents are members of ANAN, while 170 respondents are members of ICAN and another 43 are members of other PAOs. This is in sharp contrast to the statistics provided by ANAN and ICAN at the end of the 2017 financial year, which puts the number of financial members of ANAN and ICAN at 19,838 (ANAN, 2018) and 17,544 (ICAN, 2018). It was expected that more ANAN members will respond to the survey, given that they should have had quicker access to the survey; however, results proved otherwise. Following from the age of the respondents, experience statistics was crosstabulated with age, and the results showed that of all the respondents on age range 20–29 years, none had professional experience of up to 11 years, as 66 (94.3%) and only 4 (5.7%) respondents had between 1–5 years and 6–10 years of professional experience, respectively. Respondents in the age range of 30–39 years are 57 in number distributed as 15 (26.3%) respondents with 1–5 years, 34 (59.6%) respondents with 6–10 years and 8 (14.0%) respondents with 11–15 years and none with up to 16 years of experience. The distribution of respondents within the 40–49 years of age showed that 1 had between 1–5 years of professional experience, while 13 (34.2%) respondents each had between 6–10 years and 11–15 years of professional experience. Seven (18.4%) respondents and four (10.5%) respondents had between 16–20 years and 21 and more years of professional experience, respectively. Only one respondent who is aged between 50–59 years had between 6–10 and 11–15 years of professional experience, while others within that age range had about 16 and more years of professional experience. All the respondents aged 60 years and more had professional experience spanning more than 20 years. It may be out of order (except in exceptional cases) for a professional accountant with a maximum age of 29 years to have advanced years of professional experience and in the same vein, it may not be common for older adults to have fewer years of experience, albeit, possible. The result of the cross-tabulation therefore gives some level of reliability to the age statistics. Furthermore, professional experience was cross-tabulated with both primary specialty and gender, while membership of PAOs was also cross-tabulated with primary specialty. The gender results showed that there is a lull in the 16–20 years range of professional experience for both male and female respondents with 12 (8.3%) and 0 (0.0%) respondents, respectively. We are unable to identify the reason for the lull but suggest that given that the range is preparatory to retirement, only a few keep on in their current employment, as it may be a time to really evaluate their commitment to their profession. Results showed that many of the respondents with more than 21 years of experience are male with 29 (20.1%) respondents,

Table 12. Experience, Membership Distribution and Crosstab with Age and Gender. Professional Experience

1–5 years 6–10 years 11–15 years 16–20 years 21 years and more Total Membership of PAOs

ANAN ICAN Others Total

Frequency

Percent

82 52 22 12 35 203

40.4 25.6 10.8 5.9 17.2 100.0

Frequency

Percent

6 170 43 219a

2.7 77.6 19.6 100.0 Professional Experience (Years) 1–5

11–15

16–20

1 0 3 1 16.7% 0.0% 50.0% 16.7% 1.2% 0.0% 13.6% 8.3% 0.5% 0.0% 1.5% 0.5%

‡21

Total

1 6 16.7% 100.0% 2.9% 3.0% 0.5% 3.0%

Study

ANAN membership and professional experience cross-tabulation Frequency % within ANAN members % within Professional experience % of Total

6–10

119

Table 12. (Continued) Professional Experience (Years) 11–15

16–20

‡21

Total

58 47 19 11 35 170 34.1% 27.6% 11.2% 6.5% 20.6% 100.0% 70.7% 90.4% 86.4% 91.7% 100.0% 83.7% 28.6% 23.2% 9.4% 5.4% 17.2% 83.7% 22 8 4 2 51.2% 18.6% 9.3% 4.7% 26.8% 15.4% 18.2% 16.7% 10.8% 3.9% 2.0% 1.0%

7 43 16.3% 100.0% 20.0% 21.2% 3.4% 21.2%

66 4 94.3% 5.7% 80.5% 7.7%

0 0.0% 0.0%

0 0.0% 0.0%

0 0.0% 0.0%

70 100.0% 34.5%

32.5% 2.0% 0.0% 15 34 8 26.3% 59.6% 14.0% 18.3% 65.4% 36.4%

0.0% 0 0.0% 0.0%

0.0% 0 0.0% 0.0%

34.5% 57 100.0% 28.1%

7.4% 16.7% 3.9% 0.0% 1 13 13 7 2.6% 34.2% 34.2% 18.4%

0.0% 28.1% 4 38 10.5% 100.0%

Social Media, Mobile and Cloud Technology Use in Accounting

ICAN members and professional experience cross-tabulation Frequency % within ICAN members % within Professional experience % of Total Other PAO members and professional experience cross-tabulation Frequency % within Other PAO members % within Professional experience % of Total Age and Professional Experience Cross-tabulation Age (years) 20–29 Frequency % within Age % within Professional experience % of Total 30–39 Frequency % within Age % within Professional experience % of Total 40–49 Frequency % within Age

6–10

120

1–5

Multiple membership is responsible for the difference.

11.4%

0.5% 0 0.0% 0.0%

6.4% 1 3.2% 1.9%

6.4% 1 3.2% 4.5%

3.4% 5 16.1% 41.7%

2.0% 18.7% 24 31 77.4% 100.0% 68.6% 15.3%

0.0% 0 0.0% 0.0%

0.5% 0 0.0% 0.0%

0.5% 0 0.0% 0.0%

2.5% 0 0.0% 0.0%

11.8% 15.3% 7 7 100.0% 100.0% 20.0% 3.4%

0.0%

0.0%

0.0%

0.0%

3.4%

18.7%

3.4%

44 40 19 12 29 144 30.6% 27.8% 13.2% 8.3% 20.1% 100.0% 53.7% 76.9% 86.4% 100.0% 82.9% 70.9% 21.7% 19.7% 9.4% 38 12 3 64.4% 20.3% 5.1% 46.3% 23.1% 13.6%

5.9% 0 0.0% 0.0%

14.3% 70.9% 6 59 10.2% 100.0% 17.1% 29.1%

18.7% 5.9%

0.0%

3.0%

1.5%

29.1% 121

a

1.2% 25.0% 59.1% 58.3%

Study

% within Professional experience % of Total 50–59 Frequency % within Age % within Professional experience % of Total 60 plus Frequency % within Age % within Professional experience % of Total Gender and professional experience cross-tabulation Gender Male Frequency % within Gender % within Professional experience % of Total Female Frequency % within Gender % within Professional experience % of Total

122

Table 13. Membership, Experience and Crosstab with Specialty.

Variables

PAOs and primary specialty

ANAN

ICAN

OTH

Experience (years) and primary specialty

1–5

6–10

Frequency % within ANAN members % within Primary specialty % of Total Frequency % within ICAN members % within Primary specialty % of Total Frequency % within Other PAO members % within Primary specialty % of Total Frequency % within Experience % within Primary specialty % of Total Frequency % within Experience

NP/N

PRA

POL

RES

Total

0 0.0% 0.0% 0.0% 7 4.1% 58.3% 3.4% 3 7.0% 25.0% 1.5% 8 9.8% 66.7% 3.9% 3 5.8%

5 83.3% 3.4% 2.5% 120 70.6% 82.8% 59.1% 32 74.4% 22.1% 15.8% 64 78.0% 44.1% 31.5% 35 67.3%

1 16.7% 14.3% 0.5% 6 3.5% 85.7% 3.0% 1 2.3% 14.3% 0.5% 0 0.0% 0.0% 0.0% 3 5.8%

0 0.0% 0.0% 0.0% 37 21.8% 94.9% 18.2% 7 16.3% 17.9% 3.4% 10 12.2% 25.6% 4.9% 11 21.2%

6 100.0% 3.0% 3.0% 170 100.0% 83.7% 83.7% 43 100.0% 21.2% 21.2% 82 100.0% 40.4% 40.4% 52 100.0%

Social Media, Mobile and Cloud Technology Use in Accounting

Primary Specialty

11–15

16–20

21 and more

% within Primary specialty % of Total Frequency % within Experience % within Primary specialty % of Total Frequency % within Experience % within Primary specialty % of Total Frequency % within Experience % within Primary specialty % of Total

25.0% 1.5% 0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0% 1 2.9% 8.3% 0.5%

24.1% 17.2% 15 68.2% 10.3% 7.4% 9 75.0% 6.2% 4.4% 22 62.9% 15.2% 10.8%

42.9% 1.5% 3 13.6% 42.9% 1.5% 0 0.0% 0.0% 0.0% 1 2.9% 14.3% 0.5%

28.2% 5.4% 4 18.2% 10.3% 2.0% 3 25.0% 7.7% 1.5% 11 31.4% 28.2% 5.4%

25.6% 25.6% 22 100.0% 10.8% 10.8% 12 100.0% 5.9% 5.9% 35 100.0% 17.2% 17.2%

Notes: NP/N: Non-practicing/none; OTH: Other; POL: Policymaker; PRA: Practitioner; RES: Researcher.

Study 123

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Social Media, Mobile and Cloud Technology Use in Accounting

while 6 (10.2%) respondents are female. The result also showed that there is a sharp drop in the number of female respondents as the years of professional experience increased, suggesting that many women may be dropping from the ladder as they age, due to reasons already adduced under the gender statistics. Career progression is based significantly on experience; hence given that male have more experience, it is expected that they are more likely to occupy seats of leadership compared to women. Membership of PAOs was cross-tabulated with primary specialty. Amongst the respondents who claimed to be ANAN members, five (83.3%) are primarily practitioners, while the other one is a policymaker. Out of the 170 ICAN members, 120 (70.6%) are practitioners and that amounted to 82.8% of all practitioners. All the policymakers were ICAN members and 37 (21.8%) respondents amongst ICAN members were researchers. For members of other PAOs, 32 (74.4%) respondents were practitioners and seven (11.5%) were researchers with one respondent as a policymaker. The composition of practitioners who are members of other PAOs amounted to 22.1% of practitioners while that of researchers amounted to 17.9%. Experience was also cross-tabulated with primary specialty and the results showed that of the 82 respondents with one to five years of experience, 64 (78.0%) respondents amongst them were practitioners, 10 (12.2%) were researchers and none was a policymaker. This accounted for 44.1% and 25.6% of total practitioners and researchers, respectively. Respondents with 6–10 years of experience were 52 in number, and 35 (67.3%) amongst them were practitioners, 3 (5.8%) were policymakers and 11 (21.2%) were researchers. This amounted to 24.1%, 42.9% and 28.2% of total practitioners, policymakers and researchers, respectively. In the 11–15 years category, none was a non-practicing professional accountant, while 15 (68.2%) respondents were practitioners, four (18.2%) respondents were researchers and three (5.8%) were policymakers. This made up 10.3%, 42.9% and 10.3% of total practitioners, policymakers and researchers, respectively. Respondents with 16–20 years of experience were 12 in number, and 9 (75.0%) were practitioners and 3 (25.0%) were researchers while none was a policymaker; this accounted for 6.2% and 7.7% of total practitioners and researchers, respectively. In the last category, that is, respondents with 21 years of experience or more, 22 (62.9%) respondents were practitioners, 1 (2.9%) respondent was a policymaker and 11 (31.4%) respondents were researchers. This amounted to 15.2%, 14.3% and 28.2% of total practitioners, policymakers and researchers, respectively.

Academic Qualification All the respondents have at least one academic award or degree from a tertiary institution with 134 (66.0%) having at least a B.Sc. in accounting. Forty-one (20.2%) respondents had an award of ND and/or HND in accounting, accountancy and/or finance and another six (3.0%) respondents the same award in other fields. The study found that 18 (8.9%) respondents had bachelor’s degree in fields other than accounting while 49 (24.1%) and 25 (12.3%) respondents had master’s degree in

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125

accounting and other fields, respectively. The MBA degree in accounting had been obtained by 27 (13.3%) respondents and 9 (4.4%) respondents bagged MBA in other fields. The highest academic degree (Ph.D.) in accounting was merged with its penultimate (M.Phil.) given the peculiarity in Nigeria and 19 (9.4%) respondents had earned the Accounting degree and another seven (3.4%) respondents in other fields. Nineteen (9.4%) respondents had undertaken a training at a tertiary institution. The results showed that professional accountants who go on to study for higher degrees are few. A cross-tabulation descriptive was performed using primary specialty and academic qualification. The results showed that of the 47 respondents who are holders of the ND/HND award, 36 (76.6%) respondents amongst them were primarily practitioners, eight (17.0%) of them were primarily researchers and two (4.3%) were policymakers, while one was not a practicing professional accountant. The B.Sc. Accounting degree option had the highest patronage amongst the respondents and 98 (73.1%) of them were practitioners. Followed in descending order is the researcher specialty with 24 (17.9%) respondents and the policy group with four (3.0%) respondents. Respondents with bachelor’s degree other than in accounting were unevenly distributed amongst practitioner and researcher specialties in the proportion 12 (66.6%) and 6 (33.3%), respectively. In the higher degree category, starting with the M.Sc. in accounting degree, primary practitioners and researchers had equal share (23, 46.9%), while 3 (6.1%) respondents are policymakers. However, for master’s degree in other fields, the practitioner specialty surpassed the researcher specialty with 15 (60.0%) and 5 (20.0%), respectively. A closer margin was shown in the MBA with accounting option degree such that the difference between the practitioner and researcher specialties is 6 respondents (Table 14). MBA in other fields, however, showed a divergent result with no researcher that earned the degree, while all the respondents were primarily practitioners. In a similar twist, of the 26 respondents who were holders of the highest academic degrees, 20 (76.9%) of them were researchers while others were practitioners. The distribution of respondents who had undergone any form of training in tertiary institutions was unequally distributed amongst all the specialties; howbeit, the practitioner specialty had the highest (9, 47.4%), while policy had the least (3, 15.8%). None of the non-practicing professional accountants had gone for a higher degree beyond the master’s degree level, which can explain that they may be selfemployed. The practitioner specialty also had more presence with first degree, while the researchers had more presence in higher degree. The IAESB recommends that the minimum academic degree qualification for professional accountants should be a degree (IAESB, 2017). It is, however, necessary to state that given that some primary practitioners had earned even the Ph.D., they may be inclined to cross to research, which is good for the development of accounting education (Pathways Commission, 2014b). Therefore, practitioners with higher degrees, especially the Ph.D., may have the intention of moving into academics in the latter part of their lives. It is inspiring to see that respondents who do not

Table 14. Academic Qualification Statistics.

No (%) Yes (%)

ND/HND (Others)

No (%) Yes (%)

B.Sc. (Acctg)

No (%) Yes (%)

Bachelor’s degree (Others)

No (%) Yes (%)

M.Sc. (Acctg)

No (%) Yes (%)

162 (79.8) 41 (20.2) 197 (97.0) 6 (3.0) 69 (34.0) 134 (66.0) 185 (91.1) 18 (8.9) 154 (75.9) 49 (24.1)

Cross-tabulation Details

NP/N

PRA

POL

RES

Total

Frequency % within Award % within Primary % of Total Frequency % within Award % within Primary % of Total Frequency % within Degree % within Primary % of Total Frequency % within Degree % within Primary % of Total Frequency % within Degree % within Primary % of Total

0 0.0% 0.0% 0.0% 1 16.7% 8.3% 0.5% 8 6.0% 66.7% 3.9% 0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0%

32 78.0% 22.1% 15.8% 4 66.7% 2.8% 2.0% 98 73.1% 67.6% 48.3% 12 66.7% 8.3% 5.9% 23 46.9% 15.9% 11.3%

2 4.9% 28.6% 1.0% 0 0.0% 0.0% 0.0% 4 3.0% 57.1% 2.0% 0 0.0% 0.0% 0.0% 3 6.1% 42.9% 1.5%

7 17.1% 17.9% 3.4% 1 16.7% 2.6% 0.5% 24 17.9% 61.5% 11.8% 6 33.3% 15.4% 3.0% 23 46.9% 59.0% 11.3%

41 100.0% 20.2% 20.2% 6 100.0% 3.0% 3.0% 134 100.0% 66.0% 66.0% 18 100.0% 8.9% 8.9% 49 100.0% 24.1% 24.1%

specialty

specialty

specialty

specialty

specialty

Social Media, Mobile and Cloud Technology Use in Accounting

ND/HND (Acctg, Finance)

126

Primary Specialty

Variables/Options and Frequency

Master’s degree (Others)

No (%) Yes (%)

MBA (Acctg)

No (%) Yes (%)

MBA (Others)

No (%) Yes (%)

M.Phil./Ph.D. (Acctg)

No (%) Yes (%)

M.Phil./Ph.D. (Others)

No (%) Yes (%) No (%) Yes (%)

5 20.0% 41.7% 2.5% 1 3.7% 8.3% 0.5% 0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0% 2 10.5% 16.7% 1.0%

Notes: NP/N: Non-practicing/none; POL: Policymaker; PRA: Practitioner; RES: Researcher.

15 60.0% 10.3% 7.4% 16 59.3% 11.0% 7.9% 9 100.0% 6.2% 4.4% 4 21.1% 2.8% 2.0% 2 28.6% 1.4% 1.0% 9 47.4% 6.2% 4.4%

0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0% 3 15.8% 42.9% 1.5%

5 20.0% 12.8% 2.5% 10 37.0% 25.6% 4.9% 0 0.0% 0.0% 0.0% 15 78.9% 38.5% 7.4% 5 71.4% 12.8% 2.5% 5 26.3% 12.8% 2.5%

25 100.0% 12.3% 12.3% 27 100.0% 13.3% 13.3% 9 100.0% 4.4% 4.4% 19 100.0% 9.4% 9.4% 7 100.0% 3.4% 3.4% 19 100.0% 9.4% 9.4%

127

Frequency % within Degree % within Primary specialty % of Total Frequency % within Degree % within Primary specialty % of Total Frequency % within Degree % within Primary specialty % of Total Frequency % within Degree % within Primary specialty % of Total Frequency % within Degree % within Primary specialty % of Total Frequency % within Certificate % within Primary specialty % of Total

Study

Others

178 (87.7) 25 (12.3) 176 (86.7) 27 (13.3) 194 (95.6) 9 (4.4) 184 (90.6) 19 (9.4) 196 (96.6) 7 (3.4) 184 (90.6) 19 (9.4)

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necessarily require higher degrees by virtue of their specialty have undertaken it, albeit it may be useful in other endeavours.

Professional Qualification ANAN and ICAN are the main PAOs for the study. There are different entry routes to becoming a professional accountant through the professional accounting education. Candidates for ANAN are usually admitted to the NCA, while ICAN candidates go through a professional programme, which has been refined overtime. There have been many changes to the ICAN syllabus, which has led to changes in the progressive levels leading to qualification. A recent change came on stream in 2019, albeit the changes may only affect the curriculum/syllabus. Results on professional qualification are shown in Tables 15 and 16. ATS enjoyed the patronage of 37 (18.2%) respondents, while 23 (11.3%) respondents passed through the Foundation level of ICAN. The Intermediate level of ICAN was also patronised by 36 (17.7%) respondents and the Professional stages under both the old and new structures as expected enjoyed the most patronage amongst the respondents (162, 79.8%). Six (3.0%) respondents passed through the NCA. Another peculiar entry route is through Conversion such that holders of professional certifications from other bodies can be admitted into the membership of another PAO based on certain exemptions as agreed between the PAOs. Thirty-two (15.8%) respondents used this route into membership of other PAOs. A cross-tabulation of the results with primary specialty was performed and the results in Table 15 showed that of the 37 respondents who passed through the ATS, 29 (78.4%) are primarily practitioners while four (10.8%) were researchers and one (2.7%) was a policymaker, and non-practicing specialty had three (8.1%) respondents. Using the primary specialty as the denominator, non-practicing specialty excels with 25.0%, followed by the practitioner (20.0%), and then the policy specialty (14.3%). The researcher specialty lagged with 10.3%. In a similar output, the results of the Foundation level of ICAN showed that 18 (78.3%) respondents were primarily practitioners; however, the specialty with the highest participation based on primary specialty is the non-practicing respondents (16.7%), which is then followed by practitioners (12.4%) and then the researcher specialty at 7.7%. No primary policymaker respondent went through the Foundation level of ICAN. Furthermore, in the Intermediate level of ICAN, 29 (80.6%) respondents were primarily practitioners and using the primary specialty as the denominator, they had the highest participation as well at 20.0%. It is trailed by 5 (13.9%) researchers with a 12.8% participation using the specialty denominator. In this route, no primary policymaker was recorded as well. The ultimate level leading to qualification as a qualified accountant is the Professional level and it was grossly dominated by primary practitioners at 67.9% using the level count and at 75.9% using the specialty count. Most of the policymakers and researchers had passed through this level, thereby recording 85.7% and 94.9% participation, however,

Table 15. Professional Qualifications and Primary Specialty Cross-tabulation Statistics. Primary Specialty Routes

Options

Freq.

%

ATS (ATSWA/ABWA)

No

166

81.8

Yes

37

18.2

No

180

88.7

Yes

23

11.3

No

167

82.3

Yes

36

17.7

Foundation (ICAN)

Intermediate (ICAN)

NP/N

PRA

POL

RES

Total

Frequency % within ATS % within Primary specialty % of Total Frequency % within Foundation % within Primary specialty % of Total Frequency % within Intermediate % within Primary specialty % of Total

3 8.1% 25.0% 1.5% 2 8.7% 16.7% 1.0% 2 5.6% 16.7% 1.0%

29 78.4% 20.0% 14.3% 18 78.3% 12.4% 8.9% 29 80.6% 20.0% 14.3%

1 2.7% 14.3% 0.5% 0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0%

4 10.8% 10.3% 2.0% 3 13.0% 7.7% 1.5% 5 13.9% 12.8% 2.5%

37 100.0% 18.2% 18.2% 23 100.0% 11.3% 11.3% 36 100.0% 17.7% 17.7%

Study

Cross-tabulation Details

129

130

Table 15. (Continued)

Routes

Options

Professional (ICAN)

NCA

Conversion

Freq.

%

No

41

20.2

Yes

162

79.8

No

197

97.0

Yes

6

3.0

No

171

84.2

Yes

32

15.8

Cross-tabulation Details

NP/N

PRA

POL

RES

Total

Frequency % within Professional % within Primary specialty % of Total Frequency % within NCA % within Primary specialty % of Total Frequency % within Conversion % within Primary specialty % of Total

9 5.6% 75.0% 4.4% 0 0.0% 0.0% 0.0% 2 6.2% 16.7% 1.0%

110 67.9% 75.9% 54.2% 5 83.3% 3.4% 2.5% 28 87.5% 19.3% 13.8%

6 3.7% 85.7% 3.0% 1 16.7% 14.3% 0.5% 0 0.0% 0.0% 0.0%

37 22.8% 94.9% 18.2% 0 0.0% 0.0% 0.0% 2 6.2% 5.1% 1.0%

162 100.0% 79.8% 79.8% 6 100.0% 3.0% 3.0% 32 100.0% 15.8% 15.8%

Notes: NP/N: Non-practicing/none; POL: Policymaker; PRA: Practitioner; RES: Researcher.

Social Media, Mobile and Cloud Technology Use in Accounting

Primary Specialty

Table 16. CPD and STT Attendance with Primary Specialty Cross-tabulation Statistics. Primary Specialty

CPD attendance

None

1–5

6–10

11–15

POL

RES

Total

4 9.3% 33.3% 2.0% 8 5.5% 66.7% 3.9% 0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0%

32 74.4% 22.1% 15.8% 102 70.3% 70.3% 50.2% 9 81.8% 6.2% 4.4% 2 66.7% 1.4% 1.0% 0 0.0% 0.0% 0.0%

1 2.3% 14.3% 0.5% 3 2.1% 42.9% 1.5% 1 9.1% 14.3% 0.5% 1 33.3% 14.3% 0.5% 1 100.0% 14.3% 0.5%

6 14.0% 15.4% 3.0% 32 22.1% 82.1% 15.8% 1 9.1% 2.6% 0.5% 0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0%

43 100.0% 21.2% 21.2% 145 100.0% 71.4% 71.4% 11 100.0% 5.4% 5.4% 3 100.0% 1.5% 1.5% 1 100.0% 0.5% 0.5%

131

PRA

Study

21 and more

Frequency % within CPD attendance % within Primary specialty % of Total Frequency % within CPD attendance % within Primary specialty % of Total Frequency % within CPD attendance % within Primary specialty % of Total Frequency % within CPD attendance % within Primary specialty % of Total Frequency % within CPD attendance % within Primary specialty % of Total

NP/N

132

Table 16. (Continued)

Special technology training attendance

None

1–5

6–10

11–15

Frequency % within STT attendance % within Primary specialty % of Total Frequency % within STT attendance % within Primary specialty % of Total Frequency % within STT attendance % within Primary specialty % of Total Frequency % within STT attendance % within Primary specialty % of Total

NP/N

PRA

POL

RES

Total

6 11.3% 50.0% 3.0% 4 2.9% 33.3% 2.0% 2 18.2% 16.7% 1.0% 0 0.0% 0.0% 0.0%

38 71.7% 26.2% 18.7% 100 73.0% 69.0% 49.3% 6 54.5% 4.1% 3.0% 1 50.0% 0.7% 0.5%

2 3.8% 28.6% 1.0% 5 3.6% 71.4% 2.5% 0 0.0% 0.0% 0.0% 0 0.0% 0.0% 0.0%

7 13.2% 17.9% 3.4% 28 20.4% 71.8% 13.8% 3 27.3% 7.7% 1.5% 1 50.0% 2.6% 0.5%

53 100.0% 26.1% 26.1% 137 100.0% 67.5% 67.5% 11 100.0% 5.4% 5.4% 2 100.0% 1.0% 1.0%

Notes: NP/N: Non-practicing/none; POL: Policymaker; PRA: Practitioner; RES: Researcher; STT: Special technology training.

Social Media, Mobile and Cloud Technology Use in Accounting

Primary Specialty

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133

scoring only 3.7% and 22.8% participation based on the level count, respectively. As earlier pointed out, six respondents attended the NCA and five (83.3%) are practitioners, while the other is a policymaker. For conversion from other PAOs, 87.5% are practitioners, while two (6.2%) respondents each are non-practicing and research professionals. As part of the professional qualification, two questions on CPD were asked. One was a direct questioning of the CPD engagements attended in the last one year, while the other was on the number of special technology training (STT) attended in the last one year as well. The results in Table 16 showed that 43 (21.2%) respondents did not attend any CPD engagement during the last one year, out of which 32 (74.4%) are primarily practitioners. Hundred forty-five (71.4%) respondents claimed to have attended between one and five CPD engagements within the last one year, and the research specialty had the highest attendance rate of 82.1%, while the lowest was in the policy specialty with 42.9%, although numerically, the practitioner specialty had the highest frequency of 102 (70.3%) respondents. Another 15 respondents had attended more than six CPD engagements. Only one respondent who is a policymaker claimed to have attended at least 21 CPD engagements in the last one year. Results on the special technology training showed that 53 (26.1%) respondents did not attend any special training related to technology in the last one year. It appeared as a significant number given that the bulk of the figure (38, 71.7%) is amongst the practitioner specialty where it is evident that technology has become a game-changer of some sort. However, when compared with the total number of primary practitioners, the value is low, but significant at 26.2%. Hundred fifty (69.0%) respondents have been trained on technology in at least one special training with the most trained specialty being research and the lowest is policymakers. The highest number of special technology trainings attended by respondents is at least 11, which was attended by only one practitioner and one researcher. The research specialty had the lowest number of non-attendance of STT. It therefore appears that researchers or better still professional accountants in the academia are updating their knowledge base more frequently than the others. It may be safe therefore to posit that practitioners are more inclined to their methods of doing things, enjoying satisficing rather than optimising their operations. It can also be inferred that practitioners are busier. This notwithstanding, they are to meet up with a minimum number of CPD credits in a year as determined by their PAO. It is significant to point out that since the administration of the survey spanned two years (mid-2018 to mid-2019) the coinage of the word ‘in the last one year’ for the CPD and STT may have been problematic as some respondents responded to the survey in the year 2018 while others did in 2019. Given this challenge, the researcher has decided to take the values at face value such as span from 2017 to 2018.

Accountants’ Training Framework The accountants’ training framework is the researcher’s construct of the combination of academic and professional qualifications of professional accountants;

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this is discussed here for the purpose of analysis. The academic qualifications included in the analysis are the polytechnic and university awards and degrees, while the professional qualification includes IPD and CPD. For the purpose of analysis, one point each was awarded to each academic award/degree as well as one point each for a professional certification. The maximum for the academic award/degree was 11 points and 8 points for the professional certification, making a total of 19 points. Results are shown in Table 17. Based on the aggregate approach, 112 (55.2%) respondents earned one point in the academic qualification. Another 52 (25.6%) earned two points, while 22 (10.8%) respondents earned three points and 14 (6.9%) respondents earned four points. Two (1.0%) earned five points and one (0.5%) respondent earned a maximum of six points out of 11. Summarily, the academic level had a maximum of 11 and the maximum obtained by respondents was six, which was obtained by only one (0.5%) respondent while the lowest score was one obtained by 112 (55.2%) respondents. In the professional level with a maximum attainable score of eight, the maximum attained by respondents was seven, which was achieved by two (1.0%) respondents, while the lowest score was one, which was achieved by 13 (6.4%) respondents. It is significant to note that the minimum point expected amongst respondents is one. It therefore implies that all respondents met the minimum ATF score. The mean scores were 1.74 (of a range between 1 and 11), 3.16 (of a range between 1 and 8) and 4.91 (of a range between 1 and 19) for the academic qualification, professional qualification and the ATF, respectively. It is worthy of note that the mean scores are far from the maximum (11, 8 and 19); however, given that the minimum requirement is one point each for the academic and professional qualifications, the mean scores are insignificant in explaining the ATF. Other statistics provided are the median, mode, range, minimum and maximum scores, the sum of points and the standard deviation. The standard deviation scores show that there is high variation in responses for the ATF (1.603) and professional qualification (1.226), while the academic qualification which had a high variation score of 1.021 is the least.

Perception Perception was measured using two validated constructs of PEOU and PU with two items each on a five-point Likert scale (strongly agree – 4, agree – 3, disagree – 2, strongly disagree – 1 and not sure – 0). The results are presented in Tables 18 and 19. For PU, 158 (77.8%) respondents strongly agreed that technology enhances their efficiency in carrying out their activities and operations as professional accountants. Another 43 (21.2%) respondents agreed, while 2 (1.0%) respondents disagreed. The result of the Chi-square test showed that the test’s assumption was not violated, and it was statistically significant at 5% level of significance. The assumption underlying Chi-square test is that not more than 20% of cells should have expected frequencies less than 5 (IBM Corporation, 2011). The mean score for the item was 3.77, with a median score of 4.00 and mode of 4. The sum was 765 and the standard deviation score of 0.446 shows low variations in responses.

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Table 17. ATF Statistics. Variables/Options

Frequency

Percent

112 52 22 14 2 1

55.2 25.6 10.8 6.9 1.0 0.5

203

100.0

13 46 78 39 17 8 2

6.4 22.7 38.4 19.2 8.4 3.9 1.0

203

100.0

9 32 48 46 31 26 8 2 1

4.4 15.8 23.6 22.7 15.3 12.8 3.9 1.0 0.5

203

100.0

N 5 11 Aggregate of academic qualification

1 2 3 4 5 6

Total N58 Aggregate of professional qualification

1 2 3 4 5 6 7

Total N 5 19 Aggregate of ATF

2 3 4 5 6 7 8 9 10

Total Aggregates

Mean Median Mode Range Min Max Sum

Academic qualification 1.74 Professional qualification 3.16 ATF 4.91

1.00 3.00 5.00

1 3 4

5 6 8

1 1 2

6 7 10

s

354 1.021 642 1.226 996 1.603

136

Correlations Perception Items

PU1

Spearman’s rho

Technology enhances efficiency of activities and operations (PU1)

Correlation coefficient

Technology makes it easy to perform my tasks (PU2)

Correlation coefficient

Technology is easy to use (PEOU1)

Correlation coefficient

SA

PEOU2

. 0.458**

Sig. (2-tailed) Sig. (2-tailed)

Options

PEOU1

1.000

Sig. (2-tailed)

I believe I can learn to use new technologies by myself (PEOU2)

PU2

Correlation coefficient Sig. (2-tailed)

1.000

0.000

.

0.253**

0.481**

0.000

0.000

.

0.291**

0.274**

0.342**

1.000

0.000

0.000

0.000

.

1.000

Chi-square Test

Collinearity Statistics*

A

D

SD

NS

x2

n

Sig.

Mean

Median

Mode Range Min Max Sum

s

Tol.

VIF

Perceived usefulness (PU) PU1

158 (77.8)

43 (21.2)

2 (1.0)

0 (0.0)

0 (0.0)

193.310

2

0.000

3.77

4.00

4

2

2

4

765 0.446

0.751

1.331

PU2

160 (78.8)

42 (20.7)

1 (0.5)

0 (0.0)

0 (0.0)

201.409

2

0.000

3.78

4.00

4

2

2

4

768 0.425

0.876

1.141

Perceived ease of use (PEOU) PEOU1

111 (54.7)

83 (40.9)

7 (3.4)

0 (0.0)

2 (1.0)

176.567

3

0.000

3.48

4.00

4

4

0

4

707 0.663

0.876

1.141

PEOU2

87 (42.9)

100 (49.3)

11 (5.4)

1 (0.5)

4 (2.0)

233.133

4

0.000

3.31

3.00

3

4

0

4

671 0.768

0.751

1.331

Social Media, Mobile and Cloud Technology Use in Accounting

Table 18. Descriptive and Reliability Statistics of Perception.

Reliability Statistics Bartlett’s Test of Sphericity Extracted Components

KMO

Approx. x2

df

Sig.

a

a*

Grand Mean

F

Sig.

PU (2)

1

0.500

55.538

1

0.000

0.659

0.659

3.78

0.230

0.632

PEOU (2)

1

0.500

13.337

1

0.000

0.401

0.405

3.39

8.287

0.004

Perception (4)

1

0.643

133.875

6

0.000

0.620

0.669

3.58

43.751

0.000

Perception (2)

1

0.500

46.958

1

0.000

0.592

0.627

7.17

110.347

0.000

Constructs (Items)

*Collinearity statistics was computed with ‘trust’ as the dependent variable. **Correlation is significant at the 0.01 level (2-tailed). a: Cronbach’s alpha; a*: Cronbach’s alpha with standardised items; s: Standard deviation; A: Agree; D: Disagree; Max: Maximum; Min: Minimum; NS: Not sure; r: Spearman’s rho correlation; SA: Strongly agree; SD: Strongly disagree; sig.: p-value.

Study 137

138

Social Media, Mobile and Cloud Technology Use in Accounting Table 19. Aggregate Scores for PU, PEOU and PCT. Overall Statistics

N

Valid Missing

Mean Median Mode Std. Deviation Range Minimum Maximum Sum

PU

PEOU

PCT

203 0 7.55 8.00 8 0.752 4 4 8 1,533

203 0 6.79 7.00 8 1.134 6 2 8 1,378

203 0 14.34 15.00 16 1.622 8 8 16 2,911

Aggregate Score for PU

Valid

4 5 6 7 8 Total

Frequency

Percent

1 1 23 38 140 203

0.5 0.5 11.3 18.7 69.0 100.0

1 2 5 11 58 61 65 203

0.5 1.0 2.5 5.4 28.6 30.0 32.0 100.0

Aggregate Score for PEOU

Valid

2 3 4 5 6 7 8 Total

Aggregate Score for PCT

Valid

8 9 10

1 2 3

0.5 1.0 1.5

Study

139

Table 19. (Continued) Aggregate Score for PCT

11 12 13 14 15 16 Total

4 16 30 36 51 60 203

2.0 7.9 14.8 17.7 25.1 29.6 100.0

The second item of PU enquired about how technology makes it easy to perform tasks, and respondents largely strongly agreed (160, 78.8%), and agreed (42, 20.7%), while one (0.5%) respondent disagreed and none was not sure. The mean score was a little higher than the first item at 3.78 and the standard deviation score was 0.425 showing a lower variation in responses. The Chi-square test result showed that the assumption was not violated and statistically significant at 5% level of significance. PEOU was also measured using two items. Results for the first item showed that 111 (54.7%) respondents strongly agreed and 83 (40.9%) respondents agreed that technology is easy to use. Out of the remaining nine respondents, seven (3.4%) disagreed and two (1.0%) were not sure. Its Chi-square result was statistically significant as well. Other test statistics are mean (3.48), median (4.00), mode (4) and standard deviation (0.663), which is higher than any from the two items of PU. The second item questioned respondents’ belief in their ability to learn the use of new technologies and the results showed that 87 (42.9%) respondents strongly agreed, and 100 (49.3%) respondents agreed, while 11 (5.4%) respondents disagreed, 1 (0.5%) respondent strongly disagreed and 4 (2.0%) respondents were not sure. This item had the lowest mean score (3.31) and the highest standard deviation score of 0.768, showing significant variation in responses. Using the aggregate coding, the results for PU showed that one respondent scored four and five points each, which means that the respondents in response to the two items strongly disagreed with one and was not sure with the other. 23 (11.3%) respondents scored six points, 38 (18.7%) respondents scored seven points and 140 (69.0%) respondents scored the maximum of eight points. The results for PEOU show that no respondent scored one point, while one respondent scored two points, two (1.0%) and five (2.5%) respondents scored three and four points, respectively. Eleven (5.4%) respondents scored five points and 184 (90.6%) scored six points and more. A Spearman’s correlation test was performed for PU (0.458, p 5 0.000) and PEOU (0.342, p 5 0.000). These results indicate a positive, statistically significant relationship ruling out any incidence of collinearity, given that the correlations are less than 0.8 based on a rule of thumb (Appiah-Adu et al., 2016). To further

140

Social Media, Mobile and Cloud Technology Use in Accounting

confirm that multicollinearity is not a problem for this variable, ‘trust’, another variable, was used as the dependent variable for a linear regression analysis and the results showed that all four items had VIF numbers lower than 5 (Nishishiba, Jones, & Kraner, 2013) and tolerance numbers higher than 0.20 (Appiah-Adu et al., 2016). The researcher performed reliability test on perception measurement using the Cronbach’s alpha, and F-test. The factor analysis test was performed using the principal component analysis. The KMO as well as the Bartlett’s test of sphericity were conducted. The tested construct was perception, which was measured using two validated constructs of PEOU and PU with two items each. The results are as follows: PU (KMO value of 0.50 and Bartlett’s test of sphericity (x2) 5 55.538, df. 1, p 5 0.000); PEOU (KMO value of 0.50 and Bartlett’s test of sphericity (x2) 5 13.337, df. 1, p 5 0.000); Perception (PCT) using the four items (KMO value of 0.643 and Bartlett’s test of sphericity (x2) 5 133.875, df. 6, p 5 0.000) and PCT using PU and PEOU aggregates (KMO value of 0.50 and Bartlett’s test of sphericity (x2) 5 46.958, df. 1, p 5 0.000). The KMO recommended threshold is 50%, by rule of thumb. These results generally imply that factor analysis is a good fit for the data, hence implies that factor analysis is suitable for the data and gives assurance of some sort on the reliability of the items. The Cronbach’s alpha test was also performed and the results using standardised items are as follows: PU (0.659); PEOU (0.405); PCT using four items (0.669) and PCT using PU and PEOU (0.627). The recommended threshold for reliability using the Cronbach’s alpha is 60%.

WRA Framework Two reliability tests were performed on the nine items that make up the WRA framework. A Cronbach’s alpha (a) was determined to be 0.740 (74%), which is significant in determining reliability. An adjusted a based on standardised items gave approximately 77%. In addition, factor analysis presented a KMO 5 0.686, with Chi-square value of 591.865, p 5 0.000 at 36 degrees of freedom. Using the principal component analysis, three components were extracted. A correlation test was computed as well, and the highest value is 63% between willing to use social media (WSO) and willingness to use mobile technology (WMO). More than 80% of the correlations were statistically significant. The WRA analysis was performed using gender and primary specialty and the results are shown in Tables 21 and 22. In addition, as proposed in the conceptual framework for analysis, set theory, using the Venn diagram, was used in determining the number of respondents for the analysis on the use of SoMoClo technologies. The result for willingness to use social media based on gender showed that of the 193 respondents who chose the affirmative option, 138 (71.5%) were male. For mobile technology, 55 (27.9%) of the 197 respondents were female, and for cloud technology, 53 (27.6%) of 192 respondents are female. Readiness to use SoMoClo technologies showed similar results. 139 (70.6%), 142 (71.4%) and 136 (71.2%) male respondents agreed that they were ready to use SoMoClo technologies out of

Table 20. Descriptive and Cross-tabulation Statistics for WRA and Gender. Gender

Willingness Social media

Mobile

Cloud

Readiness Social media

Yes (%)

193 (95.1)

No (%)

6 (3.0)

Yes (%)

197 (97.0)

No (%)

11 (5.4)

Yes (%)

192 (94.6)

No (%)

6 (3.0)

Yes (%)

197 (97.0)

No (%)

4 (2.0)

Yes (%)

199 (98.0)

Total

Frequency % within WSO % within Gender % of Total Frequency % within WMO % within Gender % of Total Frequency % within WCLO % within Gender % of Total

138 71.5% 95.8% 68.0% 142 72.1% 98.6% 70.0% 139 72.4% 96.5% 68.5%

55 28.5% 93.2% 27.1% 55 27.9% 93.2% 27.1% 53 27.6% 89.8% 26.1%

193 100.0% 95.1% 95.1% 197 100.0% 97.0% 97.0% 192 100.0% 94.6% 94.6%

Frequency % within RSO % within Gender % of Total Frequency % within RMO % within Gender % of Total

139 70.6% 96.5% 68.5% 142 71.4% 98.6% 70.0%

58 29.4% 98.3% 28.6% 57 28.6% 96.6% 28.1%

197 100.0% 97.0% 97.0% 199 100.0% 98.0% 98.0%

141

10 (4.9)

Female

Study

Mobile

No (%)

Male

142

Table 20. (Continued)

Cloud

Ableness Social media

Mobile

Cloud

No (%)

12 (5.9)

Yes (%)

191 (94.1)

No (%)

2 (1.0)

Yes (%)

201 (99.0)

No (%)

5 (2.5)

Yes (%)

198 (97.5)

No (%)

29 (14.3)

Yes (%)

174 (85.7)

Male

Female

Total

Frequency % within RCLO % within Gender % of Total

136 71.2% 94.4% 67.0%

55 28.8% 93.2% 27.1%

191 100.0% 94.1% 94.1%

Frequency % within ASO % within Gender % of Total Frequency % within AMO % within Gender % of Total Frequency % within ACLO % within Gender % of Total

143 71.1% 99.3% 70.4% 141 71.2% 97.9% 69.5% 125 71.8% 86.8% 61.6%

58 28.9% 98.3% 28.6% 57 28.8% 96.6% 28.1% 49 28.2% 83.1% 24.1%

201 100.0% 99.0% 99.0% 198 100.0% 97.5% 97.5% 174 100.0% 85.7% 85.7%

Social Media, Mobile and Cloud Technology Use in Accounting

Gender

Table 21. Cross-tabulation Statistics for WRA and Primary Specialty. Primary Specialty

Willingness Social media

Mobile

Cloud

PRA

POL

RES

Total

11 5.7% 91.7% 5.4% 11 5.6% 91.7% 5.4% 11 5.7% 91.7% 5.4%

139 72.0% 95.9% 68.5% 142 72.1% 97.9% 70.0% 138 71.9% 95.2% 68.0%

7 3.6% 100.0% 3.4% 7 3.6% 100.0% 3.4% 6 3.1% 85.7% 3.0%

36 18.7% 92.3% 17.7% 37 18.8% 94.9% 18.2% 37 19.3% 94.9% 18.2%

193 100.0% 95.1% 95.1% 197 100.0% 97.0% 97.0% 192 100.0% 94.6% 94.6%

Study

Frequency % within WSO % within Primary specialty % of Total Frequency % within WMO % within Primary specialty % of Total Frequency % within WCLO % within Primary specialty % of Total

NP/N

143

144

Primary Specialty

Readiness Social media

Mobile

Cloud

Ableness Social media

NP/N

PRA

POL

RES

Total

Frequency % within RSO % within Primary specialty % of Total Frequency % within RMO % within Primary specialty % of Total Frequency % within RCLO % within Primary specialty % of Total

11 5.6% 91.7% 5.4% 11 5.5% 91.7% 5.4% 10 5.2% 83.3% 4.9%

142 72.1% 97.9% 70.0% 145 72.9% 100.0% 71.4% 137 71.7% 94.5% 67.5%

7 3.6% 100.0% 3.4% 6 3.0% 85.7% 3.0% 6 3.1% 85.7% 3.0%

37 18.8% 94.9% 18.2% 37 18.6% 94.9% 18.2% 38 19.9% 97.4% 18.7%

197 100.0% 97.0% 97.0% 199 100.0% 98.0% 98.0% 191 100.0% 94.1% 94.1%

Frequency % within ASO % within Primary specialty % of Total

12 6.0% 100.0% 5.9%

144 71.6% 99.3% 70.9%

7 3.5% 100.0% 3.4%

38 18.9% 97.4% 18.7%

201 100.0% 99.0% 99.0%

Social Media, Mobile and Cloud Technology Use in Accounting

Table 21. (Continued)

Mobile

Cloud

Frequency % within AMO % within Primary specialty % of Total Frequency % within ACLO % within Primary specialty % of Total

12 6.1% 100.0% 5.9% 10 5.7% 83.3% 4.9%

141 71.2% 97.2% 69.5% 126 72.4% 86.9% 62.1%

7 3.5% 100.0% 3.4% 6 3.4% 85.7% 3.0%

38 19.2% 97.4% 18.7% 32 18.4% 82.1% 15.8%

198 100.0% 97.5% 97.5% 174 100.0% 85.7% 85.7%

Notes: ACLO: Ableness to use cloud technology; AMO: Ableness to use mobile technology; ASO: Ableness to use social media; RCLO: Readiness to use cloud technology; RMO: Readiness to use mobile technology; RSO: Readiness to use social media; WCLO: Willingness to use cloud technology; WMO: Willingness to use mobile technology; WSO: Willingness to use social media.

Study 145

146

Initial solution PRA POL RES NP/N Total Conversion to decimal PRA POL RES NP/N Total Final solution (decimal) PRA POL RES Total

Social Media

Mobile

Cloud

Total

138 7 35 11 191

139 6 35 11 191

121 5 31 9 166

398 18 101 31 548

0.95 1.00 0.90 0.92 3.77

0.96 0.86 0.90 0.92 3.63

0.83 0.71 0.79 0.75 3.09

2.74 2.57 2.59 2.58 10.49

0.95 1.00 0.90 2.85

0.96 0.86 0.90 2.71

0.83 0.71 0.79 2.34

2.74 2.57 2.59 7.91

Social Media, Mobile and Cloud Technology Use in Accounting

Table 22. Matrix Derivation and Reliability Statistics.

Final solution (%) PRA POL RES Total

95.2% 100.0% 83.3% 89.7%

95.9% 100.0% 86.7% 94.2%

94.9% 75.0% 90.0% 86.6%

92.2% 91.7% 86.7% 90.2%

Reliability Statistics Bartlett’s Test of Sphericity

Constructs (Items)

Extracted Components

KMO

Approx. Chi-Square

df

Sig.

a

aa

WRA (9)

3

0.686

591.865

36

0.000

0.740

0.768

RCLO

Correlations

WSO WMO WCLO RSO

WCLO

RSO

RMO

1.000 . 0.632** 0.000 0.348** 0.000 0.632** 0.000 0.295** 0.000

1.000 . 0.601** 0.000 0.313** 0.000 0.394** 0.000

1.000 . 0.215** 0.002 0.279** 0.000

1.000 . 0.185** 0.008

1.000 .

ASO

AMO ACLO

147

WMO

Study

RMO

Correlation coefficient Sig. (2-tailed) Correlation coefficient Sig. (2-tailed) Correlation coefficient Sig. (2-tailed) Correlation coefficient Sig. (2-tailed) Correlation coefficient Sig. (2-tailed)

WSO

148

RCLO ASO AMO ACLO

Correlation coefficient Sig. (2-tailed) Correlation coefficient Sig. (2-tailed) Correlation coefficient Sig. (2-tailed) Correlation coefficient Sig. (2-tailed)

0.329** 0.000 0.208** 0.003 0.258** 0.000 0.102 0.147

0.326** 0.000 20.017 0.805 0.160* 0.023 0.012 0.866

0.586** 0.000 0.196** 0.005 0.383** 0.000 0.213** 0.002

0.326** 0.000 0.277** 0.000 0.160* 0.023 0.095 0.178

0.265** 0.000 20.014 0.841 -0.023 0.750 0.145* 0.039

1.000 . 0.398** 0.000 0.364** 0.000 0.316** 0.000

1.000 . 0.306** 0.000 0.102 0.148

1.000 . 0.298** 1.000 0.000 .

*Correlation is significant at the 0.05 level (2-tailed). **Correlation is significant at the 0.01 level (2-tailed). ACLO: Ableness to use cloud technology; AMO: Ableness to use mobile technology; ASO: Ableness to use social media; NP/N: Non-practicing/none; POL: Policymaker; PRA: Practitioner; RCLO: Readiness to use cloud technology; RES: Researcher; RMO: Readiness to use mobile technology; RSO: Readiness to use social media; WCLO: Willingness to use cloud technology; WMO: Willingness to use mobile technology; WSO: Willingness to use social media. a Based on standardised items.

Social Media, Mobile and Cloud Technology Use in Accounting

Table 22. (Continued)

Study

149

197, 199 and 191 respondents, respectively. Results on the ableness of SoMoClo technologies showed that 58 (28.9%), 57 (28.8%) and 49 (28.2%) female respondents were affirmative in their response to use SoMoClo technologies out of 201, 198 and 174 respondents, respectively. Using the primary specialty construct, 72.0%, 3.6% and 18.7% of the affirmative respondents were practitioners, policymakers and researchers, respectively, for willingness to use social media. The result for mobile technology is similar, seeing that 72.1% were willing practitioners, while 3.6% were willing policymakers and 18.8% were willing researchers. Cloud technology willingness results showed that 71.9%, 3.1% and 19.3% were willing practitioners, policymakers and researchers, respectively. Statistics on the readiness of SoMoClo technologies showed that 97.9%, 100.0% and 94.5% of the practitioners were ready to use social media, mobile technology and cloud technology, respectively (Figs. 8–10; Table 20). All policymakers chose that they were ready to use social media technologies, while 6 (85.7%) respondents amongst policymakers chose they were ready to use both mobile and cloud technologies, while the result for researchers showed that 37 (94.9%) respondents were ready to use social media and mobile technologies, and 38 (97.47)% respondents were ready to use cloud technology. Ableness of SoMoClo technologies presented similar results. All the policymakers claimed to be able to use both social media and mobile technologies, while 6 (85.7%) respondents claimed to be able to use cloud technology. In the same vein, 38 (97.4%) respondents amongst the researcher specialty claimed to be able to use both social media and mobile technologies, and 32 (82.1%) claimed to be able to use cloud technology. Overall, cloud technology was the lowest with respect to the WRA framework.

Willingness= 193

q= 0

a= 1

b= 1

x= 191 p= 4

r= 0 c= 5

Ableness= 201

Fig. 8.

Readiness= 197

Social Media WRA Statistics.

150

Social Media, Mobile and Cloud Technology Use in Accounting

Willingness= 197

q= 0

a= 2

b= 4

x= 191 p= 2

r= 1 c= 3

Readiness= 199

Ableness= 198

Fig. 9.

Mobile Technology WRA Statistics.

Willingness= 192

q= 3

a= 2

b= 21

x= 166 p= 3

r= 1 c= 3

Ableness= 174

Fig. 10.

Readiness= 191

Cloud Technology WRA Statistics.

The Venn diagram was used to determine the number of respondents that meet the WRA framework’s threshold for the use of SoMoClo technologies. Microsoft Excel elimination function was used to derive the number of respondents who claimed to fulfil the WRA requirement for the measurement of ‘intention to use’

Study

151

and its tabular statistics is presented in Table 22. The least figure was 191 respondents for social media, while mobile and cloud technologies had 191 and 166 respondents, respectively. In the social media statistics, it was found that no respondent was willing, yet unable and unready to use the technology. Four (4) respondents were able, but unwilling and unready to use the technology; however, no respondent was ready, but unwilling and unable to use the technology. One of the respondents was willing and able, but unready to use the technology. One (1) respondent was willing and ready, but unable to use the technology while five (5) respondents were able and ready, but unwilling to use the technology. The WRA statistics is W (193), R (197) and A (201), but the x statistic, which is most important, is 191 respondents who were willing, ready and able to use the technology. It is also significant to point out that one (1) respondent claimed to be unwilling, unready and unable to use social media technology. For mobile technology the WRA statistics showed that no respondent was willing, but unready and unable to use the technology. However, one (1) respondent was ready, but unwilling and unable to use the technology, but two (2) respondents were able, but unwilling and unready to use the technology. Two (2) respondents were both willing and able, but unready to use the technology and three (3) respondents were both ready and able, but unwilling, while four (4) respondents were willing and ready, but not able to use the technology. The WRA statistics is W (197), R (199) and A (198), but the x statistic, which is most important, is 191 respondents who were willing, ready and able to use the technology. No respondent claimed to be unwilling, unready and unable to use mobile technology. Cloud technology statistics using the WRA framework showed that W (192), R (191) and A (174) gave an x statistic of 166 respondents who were willing, ready and able to use the technology. Three (3) respondents were willing, but unready and unable. In the same vein, three (3) respondents were able, but unwilling and unready. Another one (1) was ready, but unwilling and unable to use the technology. Two (2) of the respondents were willing and able, but unready, and 21 of the respondents were willing and ready, but unable, while three (3) respondents were ready and able but unwilling to use the technology. Four (4) respondents claimed to be unwilling, unready and unable to use cloud technology. A willing respondent who is unready and unable to use the technology may only be fascinated about the concept of technology and needs orientation. Three (3) respondents fell in that category and under cloud technology only. Cloud technology is inchoate in many organisations in Nigeria, which may be the explanation for the respondents’ choice. Respondents who are ready, yet unwilling and unable to use the technology, require a push and results showed that one respondent each for mobile and cloud technologies, respectively, fell in that category. Respondents who are able, but unwilling and unready to use the technology, are demotivated. Organisations may have to review their policy towards the use of technology and/or human resource development. Willing and ready respondents who are unable require training, while willing and able, yet

152

Social Media, Mobile and Cloud Technology Use in Accounting

unready respondents, may also require a push. Able and ready but unwilling respondents may have issues with institutional adoption and frameworks. The WRA framework was used to determine intention to use SoMoClo technologies and the results showed that 191 respondents each intended to use social media and mobile technologies, while 166 respondents intended to use cloud technology. In arriving at the 3 3 3 matrix, two variables, that is, the WRA framework for use of SoMoClo technologies and primary specialty, were used. The specialty-context framework was used such that only the number of practitioners, policymakers and researchers that satisfied the assumption of the framework was used, while the last option of non-practicing accountants was dropped. The statistics of each specialty that satisfied the WRA framework was obtained and the values in the matrices were computed using a representative percentage based on the specialty-context. It should be recalled that the number of respondents that met the WRA framework for social media is 191. Out of this number, 138 were practitioners, while 7 were policymakers and 35 were researchers. For mobile technology, 139, 6 and 35 respondents were practitioners, policymakers and researchers, respectively. Cloud technology showed that 121 were practitioners, 5 were policymakers and 31 were researchers. These figures were then converted to decimals and the non-practicing category was expunged to give the final solution, which was then translated into the 3 3 3 matrix. The matrix is better read in percentage such that approximately 95% of practitioners were WRA to use social media, 100% of policymakers were WRA to use social media and 90% of researchers were WRA to use social media. For mobile technology, 96%, 86% and 90% of practitioners, policymakers and researchers, respectively, were WRA to use the technology. Similarly, 83% of practitioners were WRA to use cloud technology, 71% of policymakers were WRA to use cloud technology and 79% of researchers were WRA to use cloud technology. The matrix derivation is shown in Table 22. 0

Use SoMoCloTechnologies

PRA; So ð0:95Þ ¼ @ POL; So ð1:00Þ RES; So ð0:90Þ

PRA; Mo ð0:96Þ POL; Mo ð0:86Þ RES; Mo ð0:90Þ

1 PRA; Clo ð0:83Þ POL; Clo ð0:71Þ A RES; Clo ð0:79Þ

Objective 1: Use of SoMoClo Technologies amongst Professional Accountants This section details the achievement of the first specific research objective of the study. The responses provide insightful information on professional accountants’ use of technology and especially, SoMoClo technologies. Achieving this objective was done in parts. It is assumed that the official use of especially SoMoClo technologies is significantly tied to the institutional adoption of technology generally such that it may not be expected of professional accountants working in a fully manual setting to use SoMoClo technologies in their official capacity. This necessitated the determination of the settings wherein respondents work. Other parts included specified use of social media, mobile and cloud technologies with adjoining cross-tabulations.

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Institutional Adoption of Technology This section presents results to gain insight into the environment in which professional accountants work. This is conceptualised as the institutional adoption of technology. Most of the respondents, that is, 163 (80.3%), specified that their organisation operated both manual and automated systems, while 35 (17.2%) respondents claimed to work in organisations that were fully automated and the remaining five (2.5%) respondents claimed that they worked in fully manual organisations. This indicates that only 2.5% of the respondents work in organisations where the use of new technology is non-existent. Process automation in organisations is a key component of efficiency given the offerings of advanced and new technologies, yet these technologies come at a cost, which may be out of reach for some organisations. We are of the opinion that organisations which are still fully manual may be very small in size or those whose technology has failed and felt the need to return to the ‘old school’. The statistics on the institutional adoption of technology is shown in Table 23. In light of this, for example, calls for the ‘paper-less office’ have heightened, although in many organisations, it is still a sort of myth and a front-burner discourse (Sellen & Harper, 2003). It appears from the result that Nigerian organisations are on the path to actualising the adoption of technology either fully or partially within the coming decade. Results on the institutional adoption of SoMoClo technologies using 10 items in the questionnaire are discussed. These items give direct insight into the specificities of the adoption of SoMoClo technologies in the organisations where professional accountants who responded to the survey worked or were employed. The items had four options (Yes, No, Not applicable and I don’t know). Respondents were to choose NA for ‘Not applicable’ if they felt that the item of technology was not relevant to their work as professional accountants. For the purpose of presentation, the last two options were merged while for the purpose of understanding the adoption practices, two options of ‘Yes’ or ‘No’ were used. We doubt that it is quite doubtful that professional accountants in an organisation would not be able to answer with a high degree of certainty all the questions in the 10 items, hence the invalidation of ‘Not applicable’ and ‘I don’t know’ and its subsequent conversion to a ‘No’. Social media adoption practice was measured using three items of (1) availability of at least one dedicated social media platform, (2) use of any social media platform for in-house communication and (3) use of popular social media platform for clientele and third-party communications. The results showed that 172 (84.7%) respondents affirmed that their organisation had at least one dedicated social media platform for communication. This obviously bestows responsibility on employees of the organisations to learn, be proficient and use the particular social media platform that their organisation subscribed to. It is expected that employees can use other social media platforms outside the dedicated communication channels. For in-house communication, a significant number of the total respondents, that is, 96 (47.3%), stated that the use of any social media platform is disallowed by the management of their organisations. This implies that employees are strictly expected to use the dedicated platform of the organisation for in-house

154

Variables

Process automation adoption practice Operates both manual and automated systems Operates a fully automated system Operates a fully manual system Total Variables

Social media adoption practice One (or more) dedicated social media platform(s) for communication Use of any social media platform for in-house communication Allows the use of popular social media platforms for clientele and third-party communications

Frequency

Percent

163 35 5 203

80.3 17.2 2.5 100.0

No Freq. (%)

Yes Freq. (%)

I Don’t Know/Not Applicable Freq. (%)

Total Freq. (%)

23 (11.3)

172 (84.7)

8 (3.9)

203 (100.0)

76 (37.4)

107 (52.7)

20 (9.9)

203 (100.0)

59 (29.1)

118 (58.1)

26 (12.8)

203 (100.0)

Social Media, Mobile and Cloud Technology Use in Accounting

Table 23. Statistics of Institutional Adoption of Technology.

Mobile technology adoption practice Allows ‘Bring Your Own Device’ (BYOD) policy Use of a particular type of mobile device Provides a particular mobile device to staff for official use One (or more) dedicated mobile application(s) Cloud technology adoption practice Subscribes to at least one cloud service Allows staff to access office database off the premises Allows staff to store official document in the personal cloud

74 (36.5)

111 (54.7)

18 (8.9)

203 (100.0)

112 (55.2) 96 (47.3)

60 (29.6) 82 (40.4)

31 (15.3) 25 (12.3)

203 (100.0) 203 (100.0)

47 (23.2)

134 (66.0)

22 (10.8)

203 (100.0)

40 (19.7) 75 (36.9)

138 (68.0) 106 (52.2)

25 (12.3) 22 (10.8)

203 (100.0) 203 (100.0)

121 (59.6)

55 (27.1)

27 (13.3)

203 (100.0)

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communication and thirdly and finally on social media institutional adoption, 118 (58.1%) respondents claimed that they are allowed to use popular social media platforms for clientele and third-party interactions. While this is a significant point for the convenience of employees, it poses serious security challenges such as hijacking and tapping, which may result to confidential information being leaked, corrupted or lost in the process. Four questions were used to address the issue of institutional adoption of mobile technology. The results showed that many of the organisations where professional accountants worked were liberal such that 111 (54.7%) respondents claimed that their organisations have keyed into and allowed the BYOD policy, allowing employees to bring in their preferred device and use it for official businesses. It is a cheaper way for the employer, but also comes at a cost. This is closely related to the next item on the use of a particular type of device used for official operations. Organisations where more than 70% of the respondents worked did not require employees to use a particular type of mobile device. In the same vein, 82 (40.4%) of the respondents worked in organisations where staff are provided with a particular brand of mobile device for official assignments. The last item is on mobile application and 134 (66.0%) respondents worked in organisations that had at least one dedicated mobile application. Overall, results on mobile technology adoption point to a change in era, whereby organisations are embracing and promoting the use of mobile technology. Institutional adoption practice of cloud technology was examined using three items. The first item (138, 68.0%) was on the subscription to at least one cloud service and it is revealing that many of the organisations where respondents worked subscribed to a cloud service. This shows promise towards increased adoption of cloud technology by Nigerian organisations in the coming decade. Respondents also worked in security conscious organisations such that only 55 (27.1%) of them worked in organisations that allowed staff to store official document in their personal cloud and 97 (47.8%) respondents worked in organisations that do not allow staff access to organisation’s data off the premises. Organisations that refused staff access to official data off the premises restrict access to on-site, which means that employees may not do sensitive assignments requiring access to mostly confidential information after close of work. It is necessary to posit that evidence suggests a trade-off between security and convenience and technology users are initially inclined to choose a convenient option as against a secure option (Kim & Park, 2012; Weir, Douglas, Carruthers, & Jack, 2009). It appears from the data that some of the organisations were more concerned about security than the convenience of technology use of their staff. IT risk is real and as such it is not uncommon for organisations to guide their IT resources jealously. On both fronts of institutional general and SoMoClo technologies adoption, results showed a promise towards an ICT-driven workplace for professional accountants in Nigeria. This is also a good deal for providers of accounting education such that the move towards blended learning driven by IT should become the norm. While this is good, it challenges the competence of professional

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accountants, as well as the teaching and learning policies implemented by providers of accounting education and other educators, and challenges the status quo. This implies that while professional accountants are fascinated by the offerings of technology, they must also be fascinated by the idea of unlearning old technologies, learning newer ones and relearning when the erstwhile new ones become obsolete. KPMG (2018) curated data from sources on the enormity of data creation and flow in 60 seconds around the world. The short film showed that in 60 seconds, the world sends 156,000,000 emails, and more than 29,000,000 messages using WhatsApp. 350,000 tweets are made on Twitter, 2,400,000 snaps on Snapchat, 3,800,000 Google searches, more than 500 applications are downloaded, more than 120 new accounts are created on LinkedIn, more than 2,000,000 Skype calls are made, more than 3,000,000 shares on Facebook and 16,500 videos are viewed on Vimeo. 700,000 hours of YouTube viewings were recorded in 60 seconds and more than 87,000 hours of viewing on Netflix. This is an example of the enormity of big data, which is relevant to the work of professional accountants. KPMG prided itself in the use of digital tools, automation and robotics, data and analytics as well as cognitive computing in handling big data (KPMG, 2018). Educators must begin to learn the complexities of big data and analytics to provide insights for firm innovation. Organisations as well must therefore provide the enabling environment for their employees to maximise and create corporate wealth, else they will keep working using old methodologies, with the evident threat of eviction from relevance. Recently Huawei threatened that due to the US sanctions on China, the United States may lose out of the deployment of 5G, which is the current revolution in IT (Kharpal, 2019). This situation gives insight into how the use of old technologies potentially harms businesses, while the circumference of technology moves.

Use of Social Media An item in the questionnaire listed 14 social media platforms and asked respondents to highlight the one(s) they used in their professional engagements as professional accountants. Hundred ninety-eight (97.5%) respondents highlighted that they used at least one of the listed platforms, while five (2.5%) of the respondents pointed that they do not use any social media platform in their professional capacity. The five respondents were amongst the professional accountants who worked in organisations that operated both manual and automated systems. Surprisingly, the respondents who worked in fully manual organisations claimed they use social media platforms. This may be informed by their idea of choice as personal use or the fact that despite the institutional adoption of technology by their employers, they have moved on to adopt and use technology. The other part of institutional adoption used to cross-tabulate results for the use of social media technology bordered on the specific institutional adoption practices, which was measured using three items. Amongst the 198 respondents who claimed to use social media, 169 (85.4%) worked in organisations that had one or more dedicated social media platform(s), accounting for 98.3% of

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respondents whose organisations had at least one dedicated social media platform. Hundred four (52.5%) respondents who worked in organisations that allowed staff to use any social media platform for in-house communication claimed to use social media platforms, and 115 (58.1%) respondents engaged in organisations that allowed the use of popular social media platforms for clientele and third-party communication claimed to use at least one social media platform. These accounted for 97.2% and 97.5% of respondents who worked in those organisations with such social media adoption practices. From the number of respondents who pointed to using at least one platform, 163 respondents claimed to use WhatsApp, followed closely is LinkedIn with 154 respondents and electronic mailing the next with 121 respondents who subscribed to using it professionally. Further down is Facebook with 98 respondents and YouTube with 77 respondents. Others such as Skype, Twitter, Instagram, Google Hangout, Mendeley, SnapChat, WeChat and Flickr have corresponding numbers of 75, 66, 55, 22, 14, 10, 3 and 1 respondent(s). Another 6 respondents use bespoke platforms developed by their organisation(s). The result of SoMoClo technologies is shown in Table 24. The platform with the highest patronage surprisingly is a messaging application, while a corporate profile building application followed tightly and the third one is a mailing application. This implies that communication appears to have become a major responsibility of professional accountants, yet according to Simons and Riley (2014) there are concerns to their level of apprehension and proficiency amongst professional accountants. The data on the use of social media were cross-tabulated with primary specialty as well and presented in Table 21. Amongst professional practitioners 141 (97.2%) respondents affirmed that they used at least one social media platform. All the policymakers claimed to use at least a social media platform, while 97.4% of the researchers claimed to use at least a social media technology. A similar study (Haustein, Sugimoto, & Larivi`ere, 2015) amongst academics showed that studies have identified high degrees of use of social media and networking tools with variations along demographic characteristics such as gender and age. According to the authors, other studies found that the widely used tools amongst academics were Google Scholar, collaborative authoring tools and LinkedIn, while Twitter, Mendeley, SlideShare and Academia.edu were less used. It was, however, further noted that many of the studies were ‘disciplinarily homogeneous and have shown extreme variation based on the population’ (Haustein et al., 2015). In addition, they noted country-by-country variation in the individual motivations to use social media for scholarly communication as well as across and within platforms. It was also observed that academic institutions have adopted the use of social media such as by academic libraries (Haustein et al., 2015). It has been pointed out in literature that social media has been transformed to official communication platforms such that practitioners use social media for communication in-house, with third parties and clients. According to DeFeo (2017) researchers use three major social media platforms: Facebook for prominent people and institutions, Twitter for personal message and redirecting to

Table 24. Ranked Statistics of the Use of SoMoClo Technologies. Mobile Operating Systems and Devices Social Media Platforms

Freq. Platforms

163 154 121 98 77 75 66 55 22 14 10 6 3 1 1 5

Payment system Customer service Accounting service Specialised apps Document entry Don’t use

Frequency

Cloud Technology

Freq. Operating System Phone Tablet PDA Laptop Platforms

145 43 38 35 17 39

Android iOS BlackBerry Symbian Java Windows Other None

181 20 14 0 1 10 0 2

101 17 6 0 1 27 0 59

48 7 3 0 0 42 8 96

39 10 2 0 2 156 5 2

Google Drive One Drive DropBox Audit modules Working papers SAP NetSuite Bespoke service Box Don’t use any

Freq.

154 54 89 10 46 12 2 7 1 22

Study

WhatsApp LinkedIn Email Facebook YouTube Skype Twitter Instagram Hangout Mendeley SnapChat Bespoke WeChat Flickr Telr Don’t use any

Mobile Apps

159

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personal sites for more information and LinkedIn, which is a professional curriculum builder. Others include specialised communities like Mendeley with a more narrow focus (DeFeo, 2017). A report authored by Smith and Anderson (2018) and published by Pew Research Center on the use of social media in 2018 showed that Facebook and YouTube were the most used platforms by Americans and that young adults preferred the use of Snapchat and Instagram. Their report also reported difference in use based on gender and other cultural identifiers. Age has been used as a significant explanatory variable for technology use. Amongst respondents aged 20–29 years, 67 (95.7%) claimed to use social media and this accounted for 33.8% of total users of social media. Fifty-five (96.5%) respondents amongst respondents aged 30–39 years claimed to use social media and this accounted for 27.8% of total users. All the respondents aged 40 years and above claimed to use at least one social media platform. Combined, they accounted for the remaining percentage of total users. Using experience as a denominator as well, the results showed that 77 (93.9%) respondents with one to five years of experience claimed to use social media and this amounted to 38.9% of users of social media. Respondents with experience of six years and more all claimed to use at least one social media platform. The gender cross-tabulation result showed that 143 (99.3%) male respondents claimed to use at least one social media platform, accounting for 72.2% of respondents who claimed to use at least one social media platform. Female respondents who claimed to use at least one social media platform were 55 (93.2%). This accounted for 27.8% of users of social media platforms. There is evidence to support the use of social media and its effect on career success such that it was found that ‘presence on SNSs [social networking sites] such as LinkedIn and the amount of activity therein has a strong and consistent association with metrics of professional success…’ (Sainty & Nikitkov, 2014, p. 273). This lends credence to the argument that social media is the new curriculum vitae.

Use of Mobile Technology The preference for mobile technology as highlighted in literature is influenced significantly by its unique features such as mobility, portability, fewer ICT skills requirement, less financial resources and less reliance on electricity, as well as its proximity as handheld (Adomi, 2005b; Bakhsh et al., 2017; Liang et al., 2007; Stork, Calandro, & Gillwald, 2013). The survey was disseminated using electronic mailing system and online campaigns and given the increasing use of synchronised apps on mobile devices, it was expected that many of the respondents would use their mobile phones. Mobile technology was measured in two forms, that is, mobile application and mobile devices with their operating systems. The distinct measured use of mobile application amongst professional accountants showed that 39 (19.2%) respondents did not use any mobile application in their professional capacity. Amongst the primary practitioner class, most of them found the use of mobile applications useful as 116 (70.7%) respondents claimed to use at least one mobile application.

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Six of the primary policymakers used a mobile application while 33 (84.6%) primary researchers used at least one mobile application. The most used mobile application was mobile payment system which 145 respondents highlighted they used, while the least used application apart from bespoke or employer-developed applications was automatic document entry with 17 respondents. The second item was the use of mobile device and only two (1.0%) respondents claimed they did not use any mobile device in their professional capacity. This is representative of the findings of a study that ‘the mobile phone is now the key entry point for internet use’ (Stork et al., 2013, p. 34) in many African countries. All the policymakers and researchers used a mobile device while only two (1.4%) primary practitioners did not use a mobile device. Amongst the types of mobile devices (smart phone, tablet, PDA and laptop) listed in the questionnaire, results showed that 181 respondents claimed to use the Android OS on smart phones, 14 respondents claimed to operate devices with the BlackBerry OS, 10 respondents had devices running the Windows OS, 20 respondents used the iOS and one respondent used the Java OS. Amongst respondents who claimed to use a tablet, 101 used an Android powered tablet, while 27, 17, 6 and 1 respondent(s) used Windows, iOS, BlackBerry and Java operating system powered tablets, respectively. With respect to smart phones, only one respondent claimed to use a Java enabled tablet, while none used a Symbian. Forty-eight respondents claimed to use PDA with Android OS, three respondents used BlackBerry OS, 42 respondents used Windows OS, seven respondents used iOS and eight respondents used OS other than those mentioned. The use of laptop was pervasive, although there is no consensus that laptop is a mobile device. Only two respondents chose the option of not using a laptop, while 156 used a laptop running the Windows OS. This result represents the realities of laptop use in Nigeria with Microsoft having the dominant market share. One significant finding is that accountants prefer to use Android OS for mobile devices and Windows for laptops, which is consistent with realities in the technology sphere in Nigeria. The use of mobile technology was cross-tabulated with institutional adoption practices and shown in Table 25. The results showed that of the 164 respondents who claimed to use at least one mobile application, 117 (71.3%) amongst them claimed to work in organisations that had at least one dedicated mobile application. This accounted for 87.3% of respondents who worked in organisations with such adoption practices. Two hundred one respondents claimed to use at least one mobile device and out of this number, 60 (29.9%) respondents worked in organisations that expected their staff members to use an exact type of mobile device. This number accounted for all respondents who claimed to work in organisations with that type of mobile technology adoption practice. Respondents from organisations that provided a mobile device to their staff for official use had 82 (40.8%) respondents amongst those who claimed to use at least a mobile device, and this accounted for all the respondents that worked in such organisations. Hundred eleven respondents worked in organisations that supported the BYOD policy, 110 (54.7%) respondents amongst them claimed to use a mobile device. This amounted to 99.1% of those who worked in such organisations.

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Institutional Adoption Variables, Details and Options

Social media

Mobile application

Mobile device

Cloud technology

Frequency % within Use of technology % within Institutional adoption Frequency % within Use of technology % within Institutional adoption Frequency % within Use of device % within Institutional adoption Frequency % within Use of technology % within Institutional adoption

Variables, Details and Options

So_Use: My organisation has one (or more) dedicated social media platform(s) for communication

Frequency % within Use of social media % within Institutional adoption

FMS

MAS

FAS

Total

5 2.5% 100.0% 4 2.4% 80.0% 5 2.5% 100.0% 5 2.7% 100.0%

158 79.8% 96.9% 130 79.3% 79.8% 162 80.6% 99.4% 147 80.3% 90.2%

35 17.7% 100.0% 30 18.3% 85.7% 34 16.9% 97.1% 31 16.9% 88.6%

198 100.0% 97.5% 164 100.0% 80.8% 201 100.0% 99.0% 183 100.0% 90.1%

IDK/NA

No

Yes

Total

8 4.0% 100.0%

21 10.6% 91.3%

169 85.4% 98.3%

198 100.0% 97.5%

Social Media, Mobile and Cloud Technology Use in Accounting

Table 25. Use of SoMoClo Technologies and Institutional Adoption.

So_Use: My organisation allows staff to use any social media platform for in-house communication So_Use: My organisation allows the use of popular social media platforms for clientele and third-party communications Ma_Use: My organisation has one (or more) dedicated mobile application(s) Md_Use: My organisation expects staff to use a particular type of mobile device Md_Use: My organisation provides a particular mobile device to staff for official use Md_Use: My organisation allows ‘Bring Your Own Device’ (BYOD) policy

Frequency % within Use of social media % within Institutional adoption Frequency % within Use of social media % within Institutional adoption Frequency % within Use of mobile app % within Institutional adoption Frequency % within Use of mobile device % within Institutional adoption Frequency % within Use of mobile device % within Institutional adoption Frequency % within Use of mobile device % within Institutional adoption

18 9.1% 90.0% 26 13.1% 100.0% 14 8.5% 63.6% 30 14.9% 96.8% 24 11.9% 96.0% 17 8.5% 94.4%

76 38.4% 100.0% 57 28.8% 96.6% 33 20.1% 70.2% 111 55.2% 99.1% 95 47.3% 99.0% 74 36.8% 100.0%

104 52.5% 97.2% 115 58.1% 97.5% 117 71.3% 87.3% 60 29.9% 100.0% 82 40.8% 100.0% 110 54.7% 99.1%

198 100.0% 97.5% 198 100.0% 97.5% 164 100.0% 80.8% 201 100.0% 99.0% 201 100.0% 99.0% 201 100.0% 99.0% Study 163

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Variables, Details and Options

Clo_Use: My organisation subscribes to at least one cloud service Clo_Use: My organisation allows staff to access office database off the premises Clo_Use: My organisation allows staff to store official document in the personal cloud of staff members

Frequency % within Use of cloud % within Institutional adoption Frequency % within Use of cloud % within Institutional adoption Frequency % within Use of cloud % within Institutional adoption

IDK/NA

No

Yes

Total

20 10.9% 80.0% 21 11.5% 95.5% 23 12.6% 85.2%

32 17.5% 80.0% 68 37.2% 90.7% 109 59.6% 90.1%

131 71.6% 94.9% 94 51.4% 88.7% 51 27.9% 92.7%

183 100.0% 90.1% 183 100.0% 90.1% 183 100.0% 90.1%

Notes: Clo_Use: Use of cloud technology; FAS: Fully automated system; FMS: Fully manual system; IDK/NA: I don’t know/Not applicable; Ma_Use: Use of mobile application; Md_Use: Use of mobile device; MAS: Manual and automated system; So_Use: Use of social media.

Social Media, Mobile and Cloud Technology Use in Accounting

Table 25. (Continued)

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Given evidence that age, experience and gender have moderating effect on the use of technology, a cross-tabulation was performed using age, experience and gender and the two focus areas of mobile technology use. The results on the use of mobile technology based on age statistics showed that out of the 70 respondents in the 20–29 age bracket, 50 (71.4%) of them claimed to use at least one mobile application and 69 (98.6%) of them claimed to use at least a mobile device. This translated to 30.5% and 34.3% of users of mobile application and devices, respectively. In the 30–39 age bracket, 46 (80.7%) respondents claimed to use at least one mobile application, while all of them (57, 100.0%) claimed to use a mobile device; this accounted for 28.0% and 28.4% of all users of mobile applications and devices, respectively. Respondents aged 40–49 and 50–59 years were 38 and 31, respectively. Of this number from the 40–49 bracket, 31 (81.6%) of them claimed to use mobile applications and 37 (97.4%) respondents amongst them claimed to use at least a mobile device. All the respondents in the 50–59 age bracket claimed to use both mobile applications and devices. For respondents aged 60 years and above, only one of them claimed not to use a mobile application, while they all claimed to use mobile devices. Respondents who claimed to use at least one mobile application contributed 18.9% (40–49 years); 18.9% (50–59 years) and 3.7% (60 years and above) to the total number of users of mobile applications. In the same vein, respondents who claimed to use a mobile device contributed 18.4% (40–49 years), 15.4% (50–59 years) and 3.5% (60 years and above) to the total number of respondents who claimed to use at least one mobile device. Experience statistics cross-tabulated with the use of mobile technology presented the following results: amongst respondents who claimed to have one to five years of experience, 59 (72.0%) of them claimed to use at least one mobile application, and all of them (82 (100.0%)) claimed to use a mobile device. This translated to 36.0% and 40.8% of users of mobile application and devices, respectively. Amongst respondents with 6–10 years of experience, 43 (82.7%) claimed to use at least one mobile application, while 51 (98.1%) amongst them claimed to use a mobile device, and this accounted for 26.2% and 25.4% of users of mobile application and devices, respectively. Respondents with 11–15 years of experience were 22, and 18 (81.8%) amongst them claimed to use a mobile application and this accounted for 11.0% of users of mobile application, while all of them claimed to use a mobile device, and this amounted to 10.9% of users of mobile devices. The experience bracket of 16–20 years had 12 respondents and results showed that all of them claimed to use at least one mobile application, while 11 (91.7%) claimed to use a mobile device. This accounted for 7.3% and 5.5% of users of mobile application and devices, respectively. This appeared to be the first and only bracket where users of mobile application exceeded users of mobile device. Respondents with experience of 21 years and more were 35, and 32 (91.4%) of them claimed to use a mobile application, while all of them claimed to use a mobile device, accounting for 19.5% and 17.4% of users of mobile application and devices, respectively. The use of mobile applications was cross-tabulated with gender and the results showed that 120 (83.3%) male respondents claimed to use at least one mobile

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application in their official engagements as professional accountants. Female respondents who claimed to use mobile applications were 44 (74.6%). The distribution of gender was 73.2% for male and 26.8% for female. For mobile devices, 143 (99.3%) male respondents claimed to use at least one mobile device, while 58 (98.3%) female respondents claimed to use at least one mobile device. The distribution accounted for 71.1% male and 28.9% female use of mobile devices. Literature is rife with studies on the use of mobile technology with respect to device types and applications; however, it appears that professional accountants have not been the object of enquiry. The studies have focused more on students ¨ (Bomhold, 2013; Kutluk & Gulmez, 2014; Richardson, Dellaportas, Perera, & Richardson, 2013), consumers (Li´ebana-Cabanillas, S´anchez-Fern´andez, & Muñoz-Leiva, 2014; Morosan & DeFranco, 2016) and other general users (Akinwunmi, Aworinde, & Adewale, 2016; Bankole & Bankole, 2017; Liang et al., 2007; Rivera et al., 2015; Zhang et al., 2017). Some works, however, studied the use of mobile devices and applications within professional domain, such as in the workplace (Bankosz & Kerins, 2014; Brandas, Megan, & Didraga, 2015; Jamaluddin, Ahmad, Alias, & Simun, 2015). These studies were not particularly linked to professional accountants nor in line with the specialty-context of this study.

Use of Cloud Technology As was pointed out in the literature review, many people use cloud technology without knowing. It is to be noted that users of smart phones or any web-enabled device is likely using cloud technology. The results presented here therefore represent the respondents’ understanding of the subject of cloud technology based on the highlighted proxies used in the survey. The use of cloud technology was cross-tabulated with institutional adoption practices and the results showed that 131 (71.6%) respondents who claimed to use cloud technology worked in organisations that subscribed to at least one cloud service. In the same vein, 94 (51.4%) respondents who claimed to use cloud services also claimed to work in organisations that allowed them to access office database off the premises. This implies that they can access organisational information outside the office premises. Finally, on the institutional adoption cross-tabulation results, 51 (27.9%) respondents who claimed to use at least one cloud service claimed to work in organisations that allowed staff to store official document in their personal clouds. Amongst the primary practitioners, 129 (89.0%) respondents claimed that they used at least one cloud service, while 6 (85.7%) and 36 (92.3%) of the primary policymakers and researchers, respectively, claimed to use a cloud service. The highlighted cloud service that is mostly used by respondents is Google Drive, which 154 respondents claimed to use, while the least used cloud service, which was highlighted, is Box with only one respondent. There were, however, many other services claimed to be used by respondents, such as Oracle ERP (1), Infoware (1), Weca (1) and I Cloud (1) and all these were grouped for the purpose of analysis under ‘proprietary/bespoke service’. DropBox usage was significant with

Study

167

89 respondents, while 54 respondents claimed to use One Drive. It is alarming to note that 22 respondents highlighted that they do not have any need for a cloud service in their professional engagements. One respondent chose the option of using Google Drive, DropBox and One Drive as well as the option that she has no need for them in her professional engagements. This may imply that the respondent used those services personally, but not professionally, or that the respondent did not read the question well. The researcher aligns with the former thought. It is significant to state that in Malaysia there was evidence of low awareness of cloud technology amongst professional accountants (Tarmidi et al., 2014) but this result contrast their findings. From Table 26, respondents in the age bracket of 20–29 years were 70, and 66 (94.3%) amongst them claimed to use at least a cloud service. This amounted to 36.1% of users of cloud technology. Of the respondents aged 30–39 years, 53 (93.0%) claimed to use at least one cloud service, amounting to 29.0% of total users. Thirty-four (89.5%) respondents in the 40–49 age bracket and 25 (80.6%) respondents amongst the 50–59 age bracket claimed to use at least one cloud service. Five respondents aged 60 and above claimed they did use at least one cloud service. Users of at least one cloud service amongst the respondents aged 40–49 years and 50–59 years contributed 18.6% and 13.7% to the total number of users of cloud service, while 2.7% was for respondents aged 60 years and more. Using experience as a variable, results on the use of cloud technology showed that respondents with one to five years of experience recorded 77 (93.9%) of them as users of at least one cloud service. Respondents with 6–10 years of experience were 52, and 50 (96.2%) amongst them claimed to use cloud services. Twenty-two respondents claimed to have experience of 11–15 years and amongst them 18 (81.8%) claimed to use at least one cloud service. Twelve respondents claimed to have 16–20 years of experience as professional accountants and 11 (91.7%) claimed to use cloud services, while 27 (77.1%) respondents amongst those with 21 years of experience or more claimed to use cloud services. These accounted for 42.1% (1–5 years), 27.3% (6–10 years), 9.8% (11–15 years), 6.0% (16–20 years) and 14.8% (21 years and more) of users of cloud services. The results on the use of cloud technology amongst gender showed that 129 (89.6%) male respondents and 54 (91.5%) female respondents claimed to use at least one cloud service, accounting for 70.5% and 29.5% representation between male and female, respectively. It appears from literature that the use of cloud service is gaining steady adoption, and the results on the use of cloud technology by Nigerian professional accountants support the growing rate of its adoption. Google suite appears to be the leading provider of cloud services used amongst Nigerian professional accountants in the study and it is instructive to state that the survey was powered by a Google product known as ‘Google Forms’. The results also showed that organisations are beginning to build their own clouds, and this points to an adoption of the private cloud and/or hybrid cloud models. These models allow organisations to develop their infrastructure in line with their own peculiar needs (Table 27).

168

Social Media

Variables, Details and Options Age

20–29

30–39

40–49

50–59

$60

No Frequency

Yes

Mobile Applications Total

No

Yes

Mobile Devices

Total

No

Yes

Cloud Technology Total

No

Yes

Total

3

67

70

20

50

70

1

69

70

4

66

70

% within Age

4.3%

95.7%

100.0%

28.6%

71.4%

100.0%

1.4%

98.6%

100.0%

5.7%

94.3%

100.0%

% within Tech use

60.0%

33.8%

34.5%

51.3%

30.5%

34.5%

50.0%

34.3%

34.5%

20.0%

36.1%

34.5%

2

55

57

11

46

57

0

57

57

4

53

57

% within Age

3.5%

96.5%

100.0%

19.3%

80.7%

100.0%

0.0%

100.0%

100.0%

7.0%

93.0%

100.0%

% within Tech use

40.0%

27.8%

28.1%

28.2%

28.0%

28.1%

0.0%

28.4%

28.1%

20.0%

29.0%

28.1%

0

38

38

7

31

38

1

37

38

4

34

38

% within Age

0.0%

100.0%

100.0%

18.4%

81.6%

100.0%

2.6%

97.4%

100.0%

10.5%

89.5%

100.0%

% within Tech use

0.0%

19.2%

18.7%

17.9%

18.9%

18.7%

50.0%

18.4%

18.7%

20.0%

18.6%

18.7%

0

31

31

0

31

31

0

31

31

6

25

31

% within Age

0.0%

100.0%

100.0%

0.0%

100.0%

100.0%

0.0%

100.0%

100.0%

19.4%

80.6%

100.0%

% within Tech use

0.0%

15.7%

15.3%

0.0%

18.9%

15.3%

0.0%

15.4%

15.3%

30.0%

13.7%

15.3%

0

7

7

1

6

7

0

7

7

2

5

7

% within Age

0.0%

100.0%

100.0%

14.3%

85.7%

100.0%

0.0%

100.0%

100.0%

28.6%

71.4%

100.0%

% within Tech use

0.0%

3.5%

3.4%

2.6%

3.7%

3.4%

0.0%

3.5%

3.4%

10.0%

2.7%

3.4%

Frequency

Frequency

Frequency

Frequency

Social Media, Mobile and Cloud Technology Use in Accounting

Table 26. Age, Experience and Use of SoMoClo Technologies Cross-tabulation Statistics.

Experience (years)

1–5

Frequency

5

77

82

23

59

82

0

82

82

5

77

82

% within Experience

6.1%

93.9%

100.0%

28.0%

72.0%

100.0%

0.0%

100.0%

100.0%

6.1%

93.9%

100.0% 40.4%

% within Tech use 6–10

11–15

16–20

$21

100.0%

38.9%

40.4%

59.0%

36.0%

40.4%

0.0%

40.8%

40.4%

25.0%

42.1%

Frequency

0

52

52

9

43

52

1

51

52

2

50

52

% within Experience

0.0%

100.0%

100.0%

17.3%

82.7%

100.0%

1.9%

98.1%

100.0%

3.8%

96.2%

100.0%

% within Tech use

25.6%

0.0%

26.3%

25.6%

23.1%

26.2%

25.6%

50.0%

25.4%

25.6%

10.0%

27.3%

Frequency

0

22

22

4

18

22

0

22

22

4

18

22

% within Experience

0.0%

100.0%

100.0%

18.2%

81.8%

100.0%

0.0%

100.0%

100.0%

18.2%

81.8%

100.0%

% within Tech use

10.8%

0.0%

11.1%

10.8%

10.3%

11.0%

10.8%

0.0%

10.9%

10.8%

20.0%

9.8%

Frequency

0

12

12

0

12

12

1

11

12

1

11

12

% within Experience

0.0%

100.0%

100.0%

0.0%

100.0%

100.0%

8.3%

91.7%

100.0%

8.3%

91.7%

100.0%

% within Tech use

5.9%

0.0%

6.1%

5.9%

0.0%

7.3%

5.9%

50.0%

5.5%

5.9%

5.0%

6.0%

Frequency

0

35

35

3

32

35

0

35

35

8

27

35

% within Experience

0.0%

100.0%

100.0%

8.6%

91.4%

100.0%

0.0%

100.0%

100.0%

22.9%

77.1%

100.0%

% within Tech use

0.0%

17.7%

17.2%

7.7%

19.5%

17.2%

0.0%

17.4%

17.2%

40.0%

14.8%

17.2%

Study 169

170

Table 27. Specialty and Gender Cross-tabulation with Use of SoMoClo Technologies.

Use of social media technology

No

Yes

Use of mobile app technology

No

Yes

Frequency % within Use of social media technology % within primary specialty % of Total Frequency % within Use of social media technology % within primary specialty % of Total Frequency % within Use of mobile app technology % within primary specialty % of Total Frequency % within Use of mobile app technology % within primary specialty % of Total

NP/N

PRA

POL

0 0.0%

4 80.0%

0 0.0%

1 5 20.0% 100.0%

0.0% 0.0% 12 6.1%

2.8% 2.0% 141 71.2%

0.0% 0.0% 7 3.5%

2.6% 2.5% 0.5% 2.5% 38 198 19.2% 100.0%

100.0% 5.9% 3 7.7% 25.0% 1.5% 9 5.5% 75.0% 4.4%

RES

Total

97.2% 100.0% 97.4% 97.5% 69.5% 3.4% 18.7% 97.5% 29 1 6 39 74.4% 2.6% 15.4% 100.0% 20.0% 14.3% 15.4% 19.2% 14.3% 0.5% 3.0% 19.2% 116 6 33 164 70.7% 3.7% 20.1% 100.0% 80.0% 85.7% 84.6% 80.8% 57.1% 3.0% 16.3% 80.8%

Social Media, Mobile and Cloud Technology Use in Accounting

Primary Specialty

Variables, Details and Options

Use of mobile device

No

Yes

Use of cloud technology

No

Yes

Frequency % within Use of mobile devices % within primary specialty % of Total Frequency % within Use of mobile devices % within primary specialty % of Total Frequency % within Use of cloud technology % within primary specialty % of Total Frequency % within Use of cloud technology % within primary specialty % of Total

0 0.0% 0.0% 0.0% 12 6.0% 100.0% 5.9% 0 0.0% 0.0% 0.0% 12 6.6% 100.0% 5.9%

2 0 0 2 100.0% 0.0% 0.0% 100.0% 1.4% 0.0% 0.0% 1.0% 1.0% 0.0% 0.0% 1.0% 143 7 39 201 71.1% 3.5% 19.4% 100.0% 98.6% 100.0% 100.0% 99.0% 70.4% 3.4% 19.2% 99.0% 16 1 3 20 80.0% 5.0% 15.0% 100.0% 11.0% 14.3% 7.7% 9.9% 7.9% 0.5% 1.5% 9.9% 129 6 36 183 70.5% 3.3% 19.7% 100.0% 89.0% 85.7% 92.3% 90.1% 63.5% 3.0% 17.7% 90.1% Gender

Use of social media technology

Total

143 72.2% 99.3% 70.4%

55 27.8% 93.2% 27.1%

198 100.0% 97.5% 97.5%

171

Female

Study

Count % within Use of social media technology % within What is your gender? % of Total

Male

172

Gender

Use of mobile app technology

Use of mobile device

Use of cloud technology

Count % within Use of mobile app technology % within What is your gender? % of Total Count % within Use of mobile device % within What is your gender? % of Total Count % within Use of cloud technology % within What is your gender? % of Total

Male

Female

Total

120 73.2% 83.3% 59.1% 143 71.1% 99.3% 70.4% 129 70.5% 89.6% 63.5%

44 26.8% 74.6% 21.7% 58 28.9% 98.3% 28.6% 54 29.5% 91.5% 26.6%

164 100.0% 80.8% 80.8% 201 100.0% 99.0% 99.0% 183 100.0% 90.1% 90.1%

Social Media, Mobile and Cloud Technology Use in Accounting

Table 27. (Continued)

Study

173

Reciprocity and Correlations on the Use of SoMoClo Technologies The use of SoMoClo technologies was measured as a singular variable by looking out for respondents who claimed to use all the technologies (social media, mobile application, mobile device and cloud service) and results showed that 150 (73.9%) respondents met the measurement criterion for use of SoMoClo technologies. The results are presented in Table 28. A reciprocity statistic was computed for the use of SoMoClo technologies. The results showed that 162 respondents claimed to use both social media and mobile application. This amounted to 81.8% on the social media usage side and 98.8% on the mobile application usage side. The correlation statistics (r 5 0.165, p 5 0.019) between the variables showed a somewhat weak, statistically positive and insignificant relationship. Hundred ninety-six respondents claimed to use both mobile devices and social media. This amounted to 99.0% on the social media usage side and 97.5% on the mobile device usage side with a negatively weak and statistically insignificant correlation (r 5 20.016, p 5 0.822). The results of the reciprocity test between social media and cloud service showed that 179 respondents claimed to use both technologies amounting to 90.4% on the social media usage side and 97.8% on the cloud service usage side with a positive correlation, albeit statistically insignificant (r 5 0.054, p 5 0.443). Mobile device and mobile application were expected to have a strong correlation; howbeit, it had a negatively weak and statistically insignificant correlation (r 5 20.049, p 5 0.491) with 162 respondents, which accounted for 98.8% on the mobile application usage side and 80.6% on the mobile device usage side. In another relationship, cloud service and mobile application usage had a positive and statistically significant correlation (r 5 0.174, p 5 0.013) with 152 respondents accounting for 92.7% on the mobile application usage side and 83.1% on the cloud service usage side. Finally, the relationship between the uses of cloud service and mobile device had the highest positive and statistically significant correlation (r 5 0.302, p 5 0.000) with 183 respondents, which gave 91.0% on the mobile device side and 100.0% on the cloud service side. Furthermore, a bivariate correlation was performed using the four items used to measure use of SoMoClo technologies and the 10 items used to measure institutional adoption practices of SoMoClo technologies. Availability of at least one dedicated social media platform and use of social media was positive and statistically insignificant (r 5 0.102, p 5 0.148), and the allowance of any social media platform for in-house communication and use of social media was as well positive and statistically insignificant (r 5 0.024, p 5 0.738), while the allowance of use of popular social media platforms for clientele and third-party communications with use of social media was negative and statistically insignificant (r 5 20.022, p 5 0.757). The relationship between use of mobile technology and mobile technology adoption was measured using four items. One of the four items had to do with the use of mobile application and mobile application adoption, which showed a positive and statistically significant correlation (r 5 0.235, p 5 0.001). Other items had to do with the use of mobile device and institutional adoption of mobile devices. The correlation between the use of mobile devices and BYOD policy adoption was positive, but statistically insignificant (r 5 0.045, p 5 0.527), and the relationship

174

Use social media

Use mobile application

Use mobile device

Use of SoMoClo Technologies

Frequency

Percent

No Yes Total

53 150 203

26.1 73.9 100.0

Use Social Media

Use Mobile Application

Use Mobile Device

Use Cloud Service

–

162 98.8% 0.165* 0.019 –

196 99.0% 20.016 0.822 162 80.6% 20.049 0.491 2

179 90.4% 0.054 0.443 152 83.1% 0.174 0.013* 183 100.0% 0.302** 0.000

Frequency Percentage Spearman’s rho Sig. (2-tailed) Frequency Percentage Spearman’s rho Sig. (2-tailed) Frequency Percentage Spearman’s rho Sig. (2-tailed)

162 81.8% 0.165* 0.019 196 97.5% 20.016 0.822

162 98.8% 20.049 0.491

Social Media, Mobile and Cloud Technology Use in Accounting

Table 28. Reciprocity and Correlation Statistics on the Use of SoMoClo Technologies.

Use cloud service

Frequency Percentage Spearman’s rho Sig. (2-tailed)

179 97.8% 0.054 0.443 Use of Social Media

Variables

At least one dedicated social media platform for communication Allows staff to use any social media platform for in-house communication Allows the use of popular social media platforms for clientele and third-party communications Allows ‘Bring Your Own Device’ (BYOD) policy At least one dedicated mobile application(s) Expects staff to use a particular type of mobile device

SR Sig. SR Sig. SR Sig. SR Sig. SR Sig. SR Sig.

152 92.7% 0.174 0.013* Use of Mobile App

183 91.0% 0.302** 0.000

–

Use of Mobile Device

Use of Cloud Service

0.102 0.148 0.024 0.738 20.022 0.757 0.045 0.527 0.235** 0.001 0.095 0.175 Study 175

176

Use of Social Media

Variables

Provides a particular mobile device to staff for official use Subscribes to at least one cloud service Allows staff to access office database off the premises Allows staff to store official document in the personal cloud of staff members *Correlation is significant at the 0.05 level; **Correlation is significant at the 0.01 level. Sig.: Sig. (2-tailed); SR: Spearman’s rho.

SR Sig. SR Sig. SR Sig. SR Sig.

Use of Mobile App

Use of Mobile Device

Use of Cloud Service

0.504** 0.000 0.230** 0.001 20.062 0.379 0.072 0.306

Social Media, Mobile and Cloud Technology Use in Accounting

Table 28. (Continued)

Study

177

between expectancy to use an exact type of mobile device and use of mobile device was also positive, but statistically insignificant (r 5 0.095, p 5 0.175). The item ‘provision’ of a particular mobile device for official use and use of mobile device had a positive, and statistically significant correlation (r 5 0.504, p 5 0.000). Cloud technology adoption practices correlated with the use of cloud service resulted in a positive and statistically significant correlation (r 5 0.230, p 5 0.001) for subscription to at least one cloud service. The item on allowance of staff access to office database off the premises produced a statistically insignificant and negative correlation (r 5 20.062, p 5 0.379) and the correlation between the last item, that is, allowance to store official document in personal cloud with use of cloud service, was positive, but statistically insignificant (r 5 0.072, p 5 0.306). Generally, there is a strong relationship amongst respondents who claimed to use SoMoClo technologies, although the use of mobile application was the least used technology. We are inclined to predict that in the coming decade, the issues surrounding adoption and use of SoMoClo technologies and other revolutionary technologies by professional accountants in developing economies will remain topical. Cloud technology had a somewhat low level of use as well.

Objective 2: IES and Technology Competence of Professional Accountants Descriptives Technology competence was measured using three categories (knowledge-ability, proficiency and ableness (ability)) under information system management and SoMoClo specifics. The global minimum technology competence requirement is as enshrined in the IES. The IES stipulates a minimum level of technology proficiency that professional accountants should possess, which is the ability to demonstrate necessary general IT and IT control knowledge as well as competencies, knowledge and understanding of at least one of the three roles of managing, designing and evaluating information systems (IAESB, 2007). The rating of knowledge levels as managers, evaluators and designers of information system was broken into ‘expert’, ‘knowledgeable’ and ‘not knowledgeable’, while one other option of ‘not applicable’ stood to discredit opinions. Twenty-five (12.3%) respondents claimed to be experts in managing information systems, while 20 (9.9%) respondents claimed to be expert in the evaluation of information system. Designers of information system had the least number of experts (8, 3.9%). Respondents who claimed to be knowledgeable were 121 (evaluators), 126 (managers) and 78 (designers). The trend is similar for respondents who claimed not to be knowledgeable: 36 (evaluators), 32 (managers) and 83 (designers). This result mirrors realities in technology deployment and training in Nigeria such that specialised IT professionals design systems, while others use (front-end) and audit at some points. However, it is noteworthy according to the requirements of the IES that professional accountants should be knowledgeable and understand the designing roles of technology as well. As a follow-up, using a maximum mean score of 3.00, information system management competence which was measured based on three key areas (designer, evaluator and manager) showed that respondents gave a low record of

178

Social Media, Mobile and Cloud Technology Use in Accounting

competence as designer of information system (1.30), while managers (1.77) and evaluators (1.67) of information system had somewhat high mean scores, albeit less than 2.00. The results are presented in Tables 29–31. The variation in responses as shown by the standard deviation (s) scores indicated that there were lower variations for knowledge response in designing (0.791) compared to knowledge as evaluators (0.824), which was the highest in that category. Knowledge competence as managers had relatively low score of 0.790, which was the lowest in the category. SoMoClo knowledge-ability was measured in both specific and diverse roles. In specific terms, 69 (34.0%) respondents considered themselves as experts in the use of social media, 129 (63.5%) claimed to be knowledgeable, while 3 (1.5%) claimed to not be knowledgeable in the use of social media. In the same vein, 31 (15.3%) respondents considered themselves experts in the use of cloud technology and 109 (53.7%) respondents felt they were knowledgeable in its use, while 4 (2.9%) respondents claimed not to be knowledgeable. For mobile technology, 114 (56.2%) and 88 (43.3%) respondents claimed to be experts with mobile device and application use, respectively, while 87 (42.9%) and 109 (53.7%) respondents claimed to be knowledgeable. Combinedly, 5 (2.5%) claimed not to be knowledgeable in the use of mobile device and application, with less from device use. Using the ableness construct, 201 (99.0%), 198 (97.5%) and 174 (85.7%) claimed to be able to use SoMoClo technologies, respectively. This presents a mild paradox especially for cloud technology, which had a lower rate of knowledge-ability compared to ableness of use. Social media and mobile application had a lower statistic on knowledge-ability than on ableness of use, while knowledge-ability of mobile device is higher than ableness of use. This upholds a paradoxical thesis that people can be knowledgeable about the use of something (knowledge-ability) but may not be able to use it (ableness of use) and in some cases, vice versa. With respect to more specific technologies, eight items were measured based on levels of proficiency. The eight items were unevenly distributed amongst SoMoClo technologies but gave insight into areas of strengths and weaknesses amongst professional accountants. In the questionnaire four levels of proficiency (proficient, fairly proficient, weakly proficient and zero proficiency) were highlighted. Results showed that respondents were most proficient in uploading/downloading files (162, 79.8%) and least proficient in mobile application development (18, 8.9%). Respondents were mostly fairly proficient in the use of digital analytics tools (101, 49.8%) and least in uploading/downloading files (34, 16.7%). Digital analytics tools (39, 19.2%) had the highest number of weakly proficient respondents, while internet search and retrieval (2, 1.0%) had the least. The highest number of respondents who had zero proficiency was from mobile application development (76, 37.4%), while the least was from both internet search and retrieval and mobile application usage (1, 0.5%). Thirty-six (17.7%) respondents claimed that the development of mobile application was not applicable to their job specification.

Table 29. Technology Competence Statistics. Categories

Freq. (%)

Freq. (%)

Freq. (%)

Freq. (%)

Sum

Mean

s

x2

n

Sig.

Info System (Knowledge) Evaluators

EXP

KN

NKN

NA

(609)

(3.00)

20 (9.9)

121 (59.6)

36 (17.7)

26 (12.8)

338

1.67

0.824

132.232

3

0.000

Managers

25 (12.3)

126 (62.1)

32 (15.8)

20 (9.9)

359

1.77

0.790

150.202

3

0.000

Designers

8 (3.9)

78 (38.4)

83 (40.9)

34 (16.7)

263

1.30

0.791

76.665

3

0.000

(609)

(3.00)

SoMoClo (Knowledge) Social media

129 (63.5)

3 (1.5)

2 (1.0)

468

2.31

0.550

218.970

3

0.000

114 (56.2)

87 (42.9)

1 (0.5)

1 (0.5)

517

2.55

0.537

202.261

3

0.000

88 (43.3)

109 (53.7)

4 (2.0)

2 (1.0)

486

2.39

0.582

184.094

3

0.000

31 (15.3)

138 (68.0)

27 (13.3)

7 (3.4)

396

1.95

0.651

206.517

3

0.000

Assumption was met Assumption was met Assumption was met

Assumption was met Assumption was met Assumption was met Assumption was met

Study

Mobile device Mobile application Cloud technology

69 (34.0)

Remarks

179

180

Specific Areas (Proficiency)

Creating online presence Digital communications Digital analytics tools Internet search and retrieval Up/downloading files Mobile app development

P

FP

WP

ZP

NA

59 (29.1) 89 (43.8) 43 (21.2) 138 (68.0) 162 (79.8) 18 (8.9)

98 (48.3) 91 (44.8) 101 (49.8) 61 (30.0) 34 (16.7) 41 (20.2)

26 (12.8) 11 (5.4) 39 (19.2) 2 (1.0) 4 (2.0) 32 (15.8)

11 (5.4) 9 (4.4) 13 (6.4) 1 (0.5) 2 (1.0) 76 (37.4)

9 (4.4) 3 (1.5) 7 (3.4) 1 (0.5) 1 (0.5) 36 (17.7)

Sum (812)

Mean (4.00)

s

x2

n

593

2.92

1.017

140.916

4

660

3.25

0.862

201.261

4

566

2.79

0.964

136.631

4

740

3.65

0.582

357.862

4

760

3.74

0.592

472.394

4

335

1.65

1.235

45.793

4

Sig.

Remarks

0.000 Assumption was met 0.000 Assumption was met 0.000 Assumption was met 0.000 Assumption was met 0.000 Assumption was met 0.000 Assumption was met

Social Media, Mobile and Cloud Technology Use in Accounting

Table 29. (Continued)

Mobile app usage

134 62 5 (66.0) (30.5) (2.5) 77 81 30 (37.9) (39.9) (14.8)

Managing online presence

1 (0.5) 8 (3.9)

1 (0.5) 7 (3.4)

733

3.61

0.614

334.611

4

619

3.05

0.999

129.586

4

0.000 Assumption was met 0.000 Assumption was met

Yes

No

Sum (203)

Mean (1.00)

s

x2

n

Sig.

Social media

201 (99.0)

2 (1.0)

201

0.99

0.099

195.079

1

0.000

Mobile technology Cloud technology

198 (97.5)

5 (2.5)

198

0.98

0.155

183.493

1

0.000

174 (85.7)

29 (14.3)

174

0.86

0.351

103.571

1

0.000

Ableness

Remarks

Assumption was met Assumption was met Assumption was met

EXP: Expert; FP: Fairly proficient; KN: Knowledgeable; NA: Not applicable; NKN: Not knowledgeable; P: Proficient; WP: Weakly proficient; ZP: Zero proficiency.

Study 181

1. Manager of information system 2. Designer of information system 3. Evaluator of information system

Coefficient Sig. (2-tailed) Coefficient Sig. (2-tailed) Coefficient Sig. (2-tailed)

SoMoClo Knowledge-ability

1. Social media applications 2. Mobile phones 3. Mobile applications 4. Cloud applications

Coefficient Sig. (2-tailed) Coefficient Sig. (2-tailed) Coefficient Sig. (2-tailed) Coefficient Sig. (2-tailed)

Proficiency in Specific Areas

1. Up/downloading files online 2. Creating online presence

Coefficient Sig. (2-tailed) Coefficient Sig. (2-tailed)

1

2

3

1.000 . 0.532** 0.000 0.644** 0.000

1.000 . 0.513** 0.000

1.000 .

1

2

3

4

1.000 . 0.632** 0.000 0.749** 0.000 0.466** 0.000

1.000 . 0.713** 0.000 0.306** 0.000

1.000 . 0.416** 0.000

1.000 .

1

2

3

4

1.000 . 0.322** 0.000

1.000 .

5

6

7

8

Social Media, Mobile and Cloud Technology Use in Accounting

Information System Management

182

Table 30. Correlation Statistics for Technology Competence.

3. Managing online presence 4. Digital analytical tools 5. Mobile app development 6. Digital communications 7. Mobile app usage 8. Internet search and retrieval

Coefficient Sig. (2-tailed) Coefficient Sig. (2-tailed) Coefficient Sig. (2-tailed) Coefficient Sig. (2-tailed) Coefficient Sig. (2-tailed) Coefficient Sig. (2-tailed)

Ableness

1. Social media 2. Mobile technology 3. Cloud technology

*Correlation is significant at the 0.05 level (2-tailed). **Correlation is significant at the 0.01 level (2-tailed).

0.646** 0.000 0.338** 0.000 0.365** 0.000 0.459** 0.000 0.365** 0.000 0.327** 0.000

1.000 . 0.376** 0.000 0.355** 0.000 0.481** 0.000 0.407** 0.000 0.367** 0.000

1

2

3

1.000 . 0.306** 0.000 0.102 0.148

1.000 . 0.298** 0.000

1.000 .

1.000 . 0.339** 0.000 0.419** 0.000 0.338** 0.000 0.402** 0.000

1.000 . 0.165* 0.019 0.071 0.312 0.041 0.558

1.000 . 0.560** 0.000 0.485** 0.000

1.000 . 0.523** 0.000

1.000 .

Study

Coefficient Sig. (2-tailed) Coefficient Sig. (2-tailed) Coefficient Sig. (2-tailed)

0.338** 0.000 0.339** 0.000 0.095 0.178 0.465** 0.000 0.525** 0.000 0.546** 0.000

183

184

Table 31. Cross-tabulation of Knowledge-ability and Use of SoMoClo Technologies.

Variables

Options

Details

NA

NKN

Use of social media technology 3 knowledge-ability of social media applications cross-tabulation Use of social media technology No Frequency 0 0 % within Use of social media 0.0% 0.0% % within Knowledge-ability of 0.0% 0.0% social media Yes Frequency 2 3 % within Use of social media 1.0% 1.5% % within Knowledge-ability of 100.0% 100.0% social media Use of mobile app technology 3 knowledge-ability of mobile applications cross-tabulation Use of mobile app technology No Frequency 1 2 % within Use of mobile 2.6% 5.1% application % within Knowledge-ability of 50.0% 50.0% mobile application Yes Frequency 1 2 % within Use of mobile 0.6% 1.2% application % within Knowledge-ability of 50.0% 50.0% mobile application

KN

EXP

Total

3 2 5 60.0% 40.0% 100.0% 2.3% 2.9% 2.5% 126 67 198 63.6% 33.8% 100.0% 97.7% 97.1% 97.5%

17 19 39 43.6% 48.7% 100.0% 15.6% 21.6%

19.2%

92 69 164 56.1% 42.1% 100.0% 84.4% 78.4%

80.8%

Social Media, Mobile and Cloud Technology Use in Accounting

Knowledge-ability

Use of mobile device 3 knowledge-ability of mobile devices cross-tabulation Use of mobile device No Frequency 0 0 1 1 % within Use of mobile device 0.0% 0.0% 50.0% 50.0% % within Knowledge-ability of 0.0% 0.0% 1.1% 0.9% mobile device Yes Frequency 1 1 86 113 % within Use of mobile device 0.5% 0.5% 42.8% 56.2% % within Knowledge-ability of 100.0% 100.0% 98.9% 99.1% mobile device Use of cloud technology 3 knowledge-ability of cloud applications cross-tabulation Use of cloud technology No Frequency 4 8 6 2 % within Use of cloud technology 20.0% 40.0% 30.0% 10.0% % within Knowledge-ability of 57.1% 29.6% 4.3% 6.5% cloud technology Yes Frequency 3 19 132 29 % within Use of cloud technology 1.6% 10.4% 72.1% 15.8% % within Knowledge-ability of 42.9% 70.4% 95.7% 93.5% cloud technology

2 100.0% 1.0% 201 100.0% 99.0%

20 100.0% 9.9% 183 100.0% 90.1%

EXP: Expert; KN: Knowledgeable; NA: Not applicable; NKN: Not knowledgeable.

Study 185

186

Social Media, Mobile and Cloud Technology Use in Accounting

For better understanding of the results on SoMoClo technologies, a crosstabulation was performed using the use of SoMoClo technologies. In all, 198 (97.5%) respondents claimed to use at least one social media platform, amongst which 67 (33.8%) respondents claimed to be experts and 126 (63.6%) respondents claimed to be knowledgeable. This is a high rating for both knowledge-ability and use of social media applications. In the use of mobile applications, the results showed that out of the 164 respondents who claimed to use at least one mobile application, 69 (42.1%) and 92 (56.1%) respondents claimed to be experts and knowledgeable in its use. Mobile device use presented result that 201 respondents claimed to use at least one mobile device, while 113 (56.2%) and 86 (42.8%) respondents claimed to be experts and knowledgeable in its use. On cloud technology, 183 respondents claimed to use at least one cloud service, while 29 (15.8%) claimed to be experts and 132 (72.1%) respondents claimed to be knowledgeable in its use. The number of respondents who claimed to be experts and those who claimed to be knowledgeable fluctuated amongst the SoMoClo technologies with mobile device having the highest (113, 56.2%), while cloud technology had the lowest (29, 15.8%). Amongst knowledgeable respondents, cloud technology had the highest (132, 72.1%) while mobile device had the lowest (86, 42.8%). The level of knowledge and use of cloud technology appears therefore to be low amongst Nigerian professional accountants, when compared to the other technologies. Cloud technology remains a less understood technology amongst professional accountants, supporting the views in literature that many people even use it without knowing (Lin & Chen, 2012). Social media technology, however, gained steadily strong scores on knowledge, adoption and use amongst professional accountants.

Test of First Hypothesis The study further used Chi-square (x2) test to determine the degree of significant difference between the expected competence of professional accountants and the technology competence as stipulated by the IES, held as the maximum score. For x2 test to be acceptable, an assumption that not more than 20% of the cells should have expected frequencies of less than 5 must not be violated by all the input variables (IBM Corporation, 2011) and this was the case, so the test was significant. x2 scores as well as the asymptotic significance scores based on respondents’ assessment are provided for all categories. The first category listed three significant technology competence roles of designer, manager and evaluator of information systems for which it is required by the IES that professional accountants should have knowledge and understanding of at least one role. The second category is on the knowledge-ability of SoMoClo technologies and the third displayed parameters for the measurement of competence in other specific areas of SoMoClo technologies, while the last category was on the ableness of SoMoClo technologies. The results showed an insignificant difference between the values for all three variables under all the categories. However, some items were in the extremes. For example, in the information system management category, the role

Study

187

of manager had the highest x2 value, while the role of designer had the lowest. In the SoMoClo technologies knowledge-ability category, social media and mobile application had the highest and lowest x2 values, respectively. Proficiency in uploading and downloading files and mobile application development had the highest and lowest under the specific technologies’ category and finally, social media and cloud technology came first and last in the ableness of use category, inconsistent with the SoMoClo knowledge-ability category. It is important to state that the requirement of the IES is to have ‘knowledge and understanding’ but not to be ‘competent’. Correlation statistic was determined within each of the four categories and the results showed that in the information system management category, all the variables are statistically significant and positively correlated. In the knowledgeability category of SoMoClo technologies, all the variables are statistically significant and positive. In the proficiency measurement category of specific technologies, most of the variables are statistically significant and positive. Only three variables were not statistically significant. The final correlation result was on the ableness of use of SoMoClo technologies. Two of the three variables had positive and statistically significant relationships.

Objective 3: ATF and Technology Competence Three categories with nine items in the questionnaire were measured on a fivepoint Likert scale of strongly agree, agree, disagree, strongly disagree and not sure. For the purpose of coding, ‘not sure’ was coded a zero (0), up to 4 for ‘strongly agree’. The explanation of the mean is therefore based on a minimum of 0 to a maximum of 4, and the sum is based on a maximum of 812 (203 respondents times 4). The second approach correlated 14 items used to measure technology competence in the questionnaire with three determined variables. The first variable is academic qualification (AQ) (aggregates of academic degrees and award), the second is professional qualification (PQ) (aggregate of certifications and CPD) and the third is the ATF, which is the aggregate of the earlier two variables. Under the first approach, the first category was the academic qualification under which four items were used. Seventy-three (36.0%) respondents strongly agreed that they can deliver industry acceptable professional competence in technology owing to the academic background they had, more (87, 42.9%) agreed to it. Some (36, 17.7%) of the respondents disagreed, while only a few (3, 1.5%) were not sure that their academic background had anything to do with their technology competence. The mean score of the item was 3.09, which tends strongly to agreement that academic background is perceived to be a strong predictor of respondents’ technology competence. The academic environment provides an opportunity to be familiar with the offerings of technology, hence may be the reason why respondents perceive that their academic background has been helpful in helping them demonstrate acceptable professional competence in technology. A question, however, needs to be asked on the appropriate definition

188

Social Media, Mobile and Cloud Technology Use in Accounting

of ‘acceptable professional competence’, which was, however, not asked by this study. The statistics are shown in Tables 32 and 33. The second item under academic qualification questioned respondents’ perception on the necessity of higher degrees in accounting as significant to enhancing higher technology competence. A higher degree in this context relates to a postgraduate degree including PGD, M.Sc., MBA, M.Phil. and Ph.D. This item was included based on the suggestion that higher degrees are necessary to enhance the professionalisation of professional accountants (Pathways Commission, 2014b). However, the results negate that opinion because 82 (40.4%) respondents disagreed and 22 (10.8%) respondents strongly disagreed that a higher degree in accounting is necessary to demonstrate higher technology competence. This may be influenced by the un-popular nature of higher degrees in accounting or the realities of obtaining higher degrees in Nigeria. This view is supported in literature by a finding that there is a gap between the IT skills and knowledge that students currently learn in accounting education at the university level and what accountants practice in the real world (Nokhal & Ismail, 2014). We align with the opinion of the Pathways Commission; however, it may be necessary to state that a higher degree in other fields or specialised fields such as computing, accounting information systems, data analytics, business intelligence etc. may have a higher significant effect in enhancing the technology competence of professional accountants. The result can also be explained considering realities of challenges facing tertiary institutions in Nigeria. These challenges may have influenced the opinion of respondents to align with the view that higher degrees in accounting may not be able to enhance higher technology competence. The questionnaire did not go further to ask if higher degrees in other fields would have a different effect. The last two items under the academic qualification measurement were negatively stated intentionally. Respondents were asked to agree or otherwise to the fact that academic degrees did not help them to learn the use of technologies. 35 (17.2%) and 106 (52.2%) respondents strongly agreed and agreed, respectively, that their academic degrees in fact helped them to learn the use of technologies. This supports the first item. The fourth and last item asked respondents about how academic degrees helped them to appreciate technologies. This is significant because in the use of technologies, the place of adoption cannot be overemphasised. The results showed that 49 (24.1%) and 103 (50.7%) respondents strongly agreed and agreed that they appreciate technologies largely because of their academic degrees. The mean score of the four items (3.09, 2.47, 2.73 and 2.85) is indicative of a significant relationship between academic qualifications and technology competence based on the perception of the respondents while a higher degree in accounting may not be significant in demonstrating higher competence levels of technology. This result is significant for education providers, first as a nudge to keep up the work and to work on higher degrees in accounting to enhance the capability of graduate students towards technology adoption, competence and use. The standard deviation scores also indicated the variations in responses.

Table 32. Descriptive Statistics on Relationship between ATF and Technology Competence. Items

s

SA (%)

A (%)

D (%)

SD (%)

NS (%) Sum Mean

3 (1.5)

4 (2.0)

628

3.09

0.877

0

4

73 (36.0)

87 (42.9)

36 (17.7)

0

4

39 (19.2)

53 (26.1)

82 (40.4) 22 (10.8)

7 (3.4)

501

2.47

1.031

0

4

35 (17.2) 106 (52.2) 37 (18.2) 22 (10.8)

3 (1.5)

554

2.73

0.923

0

4

49 (24.1) 103 (50.7) 29 (14.3)

16 (7.9)

6 (3.0)

579

2.85

0.974

0

4

70 (34.5) 104 (51.2) 22 (10.8)

0 (0.0)

7 (3.4)

636

3.13

0.866

0

4

38 (18.7) 105 (51.7) 38 (18.7)

19 (9.4)

3 (1.5)

562

2.77

0.912

0

4

47 (23.2) 112 (55.2) 24 (11.8)

17 (8.4)

3 (1.5)

589

2.90

0.901

Study 189

Academic qualification Delivering industry acceptable professional competence in technology, due to academic background Higher degree in accounting is necessary to demonstrate higher technology competence My academic degree(s) helps me to learn how to use technologiesa My academic degree(s) helps me to appreciate technologiesa Professional qualification Demonstrating industry minimum standard due to professional certification My professional certification helps me to learn how to use technologiesa My professional certification helps me to appreciate technologiesa

Min. Max.

190

Items

Min. Max.

Academic and professional qualification Both academic degree(s) and 0 professional certification are the perfect match for understanding technology use Experience Experience in present 0 employment is all that is needed to continue to develop technology skills Grand mean (Total)

s

SA (%)

A (%)

D (%)

SD (%)

NS (%) Sum Mean

4

53 (26.1)

74 (36.5)

56 (27.6)

14 (6.9)

6 (3.0)

560

2.76

1.013

4

42 (20.7)

72 (35.5)

77 (37.9)

5 (2.5)

7 (3.4)

543

2.67

0.945

2.82

Notes: A: Agree; D: Disagree; Max.: Maximum; Min.: Minimum; NS: Not sure; SA: Strongly agree; SD: Strongly disagree; Standard deviation. a The items were stated in the questionnaire as negative form.

Social Media, Mobile and Cloud Technology Use in Accounting

Table 32. (Continued)

Table 33. Correlation Statistics of ATF and Technology Competence. Variables Technology Competences

Designer of information system

Correlation coefficient Sig. (2-tailed)

Evaluator of information system

Correlation coefficient Sig. (2-tailed)

Use of SoMoClo technologies Use of social media applications

Correlation coefficient Sig. (2-tailed)

Use of mobile phones

Correlation coefficient Sig. (2-tailed)

Use of mobile applications

Correlation coefficient Sig. (2-tailed)

Use of cloud applications

Correlation coefficient Sig. (2-tailed)

Competence in specific technologies Uploading/downloading files online

Correlation coefficient Sig. (2-tailed)

ATF

0.072 0.309 0.006 0.929 0.095 0.176

0.154* 0.028 0.143* 0.042 0.159* 0.023

0.173* 0.014 0.129 0.066 0.187** 0.008

20.015 0.833 20.024 0.738 20.061 0.387 20.052 0.460

0.126 0.073 0.062 0.380 0.085 0.227 0.126 0.073

0.085 0.226 0.030 0.669 0.032 0.655 0.046 0.511

20.005 0.948

0.075 0.288

0.013 0.855

191

Correlation coefficient Sig. (2-tailed)

PQ

Study

Information systems Manager of information system

AQ

192

Table 33. (Continued)

Technology Competences

Creating online presence

Correlation coefficient Sig. (2-tailed)

Managing online presence

Correlation coefficient Sig. (2-tailed)

Digital analytical tools

Correlation coefficient Sig. (2-tailed)

Mobile app development

Correlation coefficient Sig. (2-tailed)

Digital communications

Correlation coefficient Sig. (2-tailed)

Mobile app usage

Correlation coefficient Sig. (2-tailed)

Internet search and retrieval

Correlation coefficient Sig. (2-tailed)

*Correlation is significant at the 0.05 level (2-tailed). **Correlation is significant at the 0.01 level (2-tailed). AQ: Academic qualification; ATF: Accountants’ training framework; PQ: Professional qualification.

AQ

PQ

ATF

0.137 0.051 0.134 0.057 0.080 0.254 0.078 0.270 0.032 0.650 20.045 0.526 0.051 0.472

0.177* 0.011 0.186** 0.008 0.009 0.904 20.001 0.985 0.130 0.065 0.101 0.153 0.111 0.115

0.217** 0.002 0.210** 0.003 0.045 0.521 0.064 0.362 0.091 0.195 0.025 0.726 0.084 0.231

Social Media, Mobile and Cloud Technology Use in Accounting

Variables

Study

193

The second item had the highest score of 1.031 with responses varying more significantly, while the first item had the lowest score of 0.877 implying lower variation in responses. In general, however, the significance of the results should be taken with caution only as perceived responses. Under the professional qualification measurement with three items, 174 (85.7%) respondents combinedly strongly agreed and agreed that they can demonstrate industry minimum standard due to their professional certification. This implies that they are satisfied that their professional certification had equipped them well to demonstrate the minimum standard of technology competence. Respondents (57, 28.1%) posited that their professional certification did not help them to learn the use of technologies, but more (159, 78.3%) strongly agreed and agreed that it was useful in helping them appreciate technologies. This implies that there is a connect between appreciation and learning of technology such that professional certification programmes exposed members to the benefits of technology use, and taught them how to use technologies. The mean score of the three items under the professional qualification albeit close to the maximum dwindled with the item of learning the use of technologies based on the professional certification. All three standard deviation scores showed significant variations in responses. Another item in the questionnaire combined both academic and professional qualification. The item asked respondents’ perception of the combined effect of both qualifications as a perfect match for understanding the use of technology. The results showed that 53 (26.1%) respondents strongly agreed, 74 (36.5%) agreed, 56 (27.6%) disagreed and 14 (6.9%) strongly disagreed that both qualifications are a perfect match, while 6 (3.0%) of respondents were not sure of their response. The new question that arises now is what then is the perfect match? Unfortunately, this study did not ask that question. The mean score of 2.76 showed a tendency to agreement and the standard deviation score of 1.013 showed high variation in responses. The ninth and final item on the perceived effect of the ATF queried the place of experience. Respondents were asked to identify if the experience in their present employment was enough to help them develop technology skills required in the workplace. Many of the respondents strongly agreed (42, 20.7%) and agreed (72, 35.5%), while 77 (37.9%) respondents disagreed and five (2.5%) respondents strongly disagreed, and seven (3.4%) respondents were not sure. The mean score is 2.67 and it shows that many of the respondents perceived that experience in their present job was enough to help them develop technology skills. The variation in response was a standard deviation score of 0.945. The correlation result shows that no statistically significant relationship exists between ATF and technology competence, proxied with 14 items, with six items showing negative correlations and the highest is 13.7%, which is between AQ and competence in ‘creating online presence’. There were five statistically significant correlations, which were between PQ and competence as (of) ‘manager of IS’, ‘designer of IS’, ‘evaluator of IS’, ‘creating online presence’ and ‘managing online presence’. There was only one negative correlation, which was between PQ and competence in ‘mobile app development’. The highest correlation (18.6%)

194

Social Media, Mobile and Cloud Technology Use in Accounting

incidentally was the most statistically significant between PQ and competence in ‘managing online presence’. ATF as an aggregate variable had four statistically significant correlations between ATF and competence as (of) ‘manager of IS’, ‘evaluator of IS’, ‘creating online presence’ and ‘managing online presence’ with the highest being 21.7% for competence in ‘creating online presence’. Conclusively, both academic and professional accounting education are necessary to continue to develop and maintain professional competence in the use of technologies.

Objective 4: Predictability of ATF and PCT on Use of SoMoClo Technologies This section documents the achievement of the fourth and last specific objective as well as the test of the second hypothesis. Two approaches were used to achieve this objective. The first approach used was interpretive value-analyses, while regression was used as the second approach. The dependent variables (use of SoMoClo technologies) were regressed separately with the independent variables such that the use of social media, mobile and cloud technologies has separate results. The ATF was measured as aggregate scores from respondents’ responses. The female gender is the reference for analysis. Interpretive Value-analyses on Use of SoMoClo Technologies Each academic and professional qualification was cross-tabulated with the use of SoMoClo technologies and the results were used to interpret the value and quality of each ATF as relates to the use of technologies. Table 34 presents the statistics of the cross-tabulation between qualifications and use of SoMoClo technologies, which was used for the interpretive value-analysis. Academic Qualification. First, the ND/HND qualification in accounting: 41 respondents are holders of this degree and 40 (97.6%) out of this number claimed to use social media, 31 (75.6%) respondents out of the lot claimed to be users of mobile applications and all of them claimed to use at least a mobile device, while 35 (85.4%) are users of cloud service. Holders of this qualification accounted for 20.2% of the users of social media, 18.9% of the users of mobile application, 20.4% of the users of mobile devices and 19.1% of the users of cloud services. Mobile device was claimed to be the most used technology amongst holders of the ND/HND accounting qualification, while mobile application was the least used amongst holders of the qualification. It can be inferred that professional accountants who are ND/HND in accounting award holders can use SoMoClo technologies. Therefore, the quality of the qualification in shaping holders’ competence in technology is good. However, it must be noted that virtually all holders of this qualification have other higher qualifications; hence it may be absolute to posit that it is the ND/HND award that developed holders with such competence. Only six respondents are holders of ND/HND award in other fields and all of them claimed to use all the SoMoClo technologies. Amongst respondents that use

Table 34. Cross-tabulation of Qualification and Use of SoMoClo Technologies. Use of SoMoClo Technologies Variables, Details and Options

ND/HND (Accounting) ND/HND (Others)

B.Sc. (Accounting)

Bachelor’s degree (Others) M.Sc. (Accounting)

41

6

134

18

49

25

Social Media

Mobile App

Mobile Device

Cloud

% Mean of Use

40 97.6% 20.2% 6 100.0% 3.0% 130 97.0% 65.7% 17 94.4% 8.6% 49 100.0% 24.7% 24 96.0% 12.1%

31 75.6% 18.9% 6 100.0% 3.7% 104 77.6% 63.4% 13 72.2% 7.9% 43 87.8% 26.2% 21 84.0% 12.8%

41 100.0% 20.4% 6 100.0% 3.0% 133 99.3% 66.2% 18 100.0% 9.0% 49 100.0% 24.4% 25 100.0% 12.4%

35 85.4% 19.1% 6 100.0% 3.3% 121 90.3% 66.1% 17 94.4% 9.3% 42 85.7% 23.0% 24 96.0% 13.1%

19.65%

3.25%

65.35%

8.70%

24.58%

12.60%

Study

Master’s degree (Others)

195

Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification

Holders

196

Table 34. (Continued)

Variables, Details and Options

MBA (Accounting)

MBA (Others)

M.Phil./Ph.D. (Accounting) M.Phil./Ph.D. (Others) Others (Tertiary)

ATS

Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification

Holders

27

9

19

7

19

37

Social Media

Mobile App

Mobile Device

Cloud

% Mean of Use

27 100.0% 13.6% 9 100.0% 4.5% 19 100.0% 9.6% 7 100.0% 3.5% 19 100.0% 9.6% 36 97.3% 18.2%

22 81.5% 13.4% 8 88.9% 4.9% 18 94.7% 11.0% 6 85.7% 3.7% 18 94.7% 11.0% 29 78.4% 17.7%

27 100.0% 13.4% 9 100.0% 4.5% 18 94.7% 9.0% 7 100.0% 3.5% 19 100.0% 9.5% 37 100.0% 18.4%

23 85.2% 12.6% 6 66.7% 3.3% 16 84.2% 8.7% 6 85.7% 3.3% 18 94.7% 9.8% 36 97.3% 19.7%

13.25%

4.30%

9.58%

3.50%

9.98%

18.50%

Social Media, Mobile and Cloud Technology Use in Accounting

Use of SoMoClo Technologies

Foundation (ICAN)

Intermediate (ICAN)

Professional stages (ICAN) NCA

Conversion course

Continuing professional development

23

36

162

6

32

160

150

23 100.0% 11.6% 36 100.0% 18.2% 160 98.8% 80.8% 6 100.0% 3.0% 29 90.6% 14.6% 159 99.4% 80.3% 148 98.7% 74.7%

18 78.3% 11.0% 29 80.6% 17.7% 132 81.5% 80.5% 6 100.0% 3.7% 23 71.9% 14.0% 136 85.0% 82.9% 125 83.3% 76.2%

23 100.0% 11.4% 36 100.0% 17.9% 160 98.8% 79.6% 6 100.0% 3.0% 32 100.0% 15.9% 158 98.8% 78.6% 149 99.3% 74.1%

21 91.3% 11.5% 31 86.1% 16.9% 144 88.9% 78.7% 6 100.0% 3.3% 31 96.9% 16.9% 144 90.0% 78.7% 138 92.0% 75.4%

11.38%

17.68%

79.90%

3.25%

15.35%

80.13%

75.10% Study

Special technology training

Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification Frequency % within Use of technology % within qualification

197

198

Social Media, Mobile and Cloud Technology Use in Accounting

each of SoMoClo technologies, the holders of this award accounted for 3.0% for both social media and mobile device, 3.7% for mobile application and 3.3% for cloud service. Holders of this degree can relatively use SoMoClo technologies; hence the quality of the award is good. Like was posited for the previous award, holders of this degree went further to earn higher degrees; hence a stationary position on the direct effect of the award on the use of SoMoClo technologies may not be accurate. The B.Sc. in accounting degree holders is 134 and not in any of the SoMoClo technologies did the results show a 100% use statistic. 130 (97.0%) use social media, 104 (77.6%) use mobile application and that is the lowest. Hundred thirtythree (99.3%) claimed to use at least a mobile device and 121 (90.3%) are users of cloud service. The use of mobile device still stood out amongst the SoMoClo technologies. The holders of this degree accounted for the highest number of users, given that amongst the academic awards and degrees, it had the highest number of holders; 65.7% was recorded for social media, 63.4% for mobile application, 66.2% for mobile device and 66.1% for cloud service. Mobile application fell short of the average in the use community. Even though the use of mobile application by both holders of ND/HND and B.Sc. was the lowest, a comparison showed that the holders of the B.Sc. in accounting degree had a higher mobile application user rate (77.6%–75.6%) and this applied in the use of cloud technologies, but not in social media and mobile device use. It can therefore be deduced that the B.Sc. degree in accounting presented an enhanced usability of SoMoClo technologies. The next is the bachelor’s degree in other fields. Eighteen respondents claimed to be holders of this degree and it is still in the mobile device use category that 100.0% was achieved. The use of social media and cloud service were both at 94.4%, while 72.2% was recorded for the use of mobile application. This is consistent with the results from the earlier discussed awards and degrees. Holders of this degree accounted for 8.6% of the users of social media, 7.9% of mobile application user, 9.0% of the users of mobile device and 9.3% of the users of cloud service. Social media and mobile application users that are holders of the degree fell short of the average of 8.7%; nonetheless, 17 of the 18 holders claimed to use social media. The use of mobile application has consistently fallen short of the other technologies and it continues that way with all the ATF identifiers. It can be inferred that holders of this degree can use SoMoClo technologies. The M.Sc. degree in accounting had 49 holders and the use of social media and mobile device both scored 100.0% while the use of mobile application scored 87.8% with 43 respondents and cloud service scored 85.7% with 42 respondents. Holders of this degree constituted 24.7% users of social media, 26.2% users of mobile applications, 24.4% users of mobile devices and 23.0% users of cloud service. Within qualification comparison for B.Sc. and M.Sc. in accounting degrees, results showed that use of mobile application came least for B.Sc., while cloud technology came least in the M.Sc. qualification. Given that all the holders of the degree claimed to use both social media and mobile devices, the result exceeded the use statistic for both technologies by holders of the B.Sc. in accounting degree. It appears that M.Sc. in accounting degree holders use social media and mobile technologies than their B.Sc. counterparts. However, like

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posited for all the degrees, given that holders of one degree also hold other degrees, the direct effect may not be ascertainable by this study. Twenty-five respondents hold a master’s degree other than in the field of accounting. It was only in the mobile device category that 100.0% was achieved. For social media and cloud service, 24 (96.0%) respondents that are holders of this qualification claimed to use at least one social media platform and a cloud service, while 21 (84.0%) holders of the master’s degree qualification in other fields claimed to use mobile applications. This accounted for 12.1% of the total users of social media, 12.8% of the users of mobile applications, 12.4% of users of mobile device and 13.1% users of cloud service. A comparison of this degree with its equivalent in accounting showed that it had a higher user rating in only one technology (cloud) and equal rating in mobile device use. The use of mobile device constantly has been the highest rated amongst the holders of academic awards and degrees. It can be inferred that holders of this award are users of SoMoClo technologies. The MBA degree in accounting is the next academic degree. Twenty-seven respondents claimed to be holders of the degree and amongst these 22 (81.5%) and 23 (96.0%) claimed to be users of mobile applications and cloud service, respectively. All the holders of the degree claimed to use social media and mobile devices. This result translates to 13.6% user rating for social media, 13.4% rating for mobile applications and mobile devices and 12.6% for cloud service. Again, mobile application was the least used technology amongst the holders of the qualification. This showed again that mobile application emerged the least used SoMoClo technologies amongst holders of this qualification, while social media and mobile device topped. Holders of this degree can be said to be able to use SoMoClo technologies. Next on the ATF identifiers in the academic category is the MBA degree in other fields with nine holders amongst the respondents to the survey. All the holders claimed to use social media and mobile devices, while eight (88.9%) claimed to use mobile application and six (85.7%) claimed to use cloud service. This accounted for 4.5% user rating for social media users, 4.9% for mobile application, 4.9% for mobile devices and 3.3% for cloud service. Cloud technology was the least used technology amongst holders of this qualification, unlike with other degrees where mobile application was the least. It can be said that holders of this degree can use SoMoClo technologies. The highest academic degree in a university is the Ph.D. A bridge between a master’s degree or other professional degrees and the Ph.D. is the M.Phil.; hence these two degrees were lumped. It is to be noted that in some institutions, the M.Phil. is a standalone degree, while in others, it is an entry route to complete the Ph.D. The M.Phil./Ph.D. degree in accounting had 19 holders amongst the survey’s respondents. Amongst holders, 18 (94.7%) respondents claimed to use mobile applications and cloud applications and all the respondents claimed to use social media and mobile device. The frequency percentage was 9.6%, 11.0%, 9.0% and 8.7% for social media, mobile application, mobile device and cloud service, respectively. Cloud service received the least use statistic amongst holders of the M.Phil./Ph.D. in accounting degree.

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Social Media, Mobile and Cloud Technology Use in Accounting

The M.Phil./Ph.D. degree in other fields had seven holders. The use of social media and mobile device had a 100.0% statistic, while six (85.7%) respondents claimed to use mobile application and cloud service. The within technology use statistics showed that users of social media and mobile device that are holders of this degree constituted only 3.5% of total users, while users of cloud service constituted 3.3% of total users and 3.7% of mobile application. A last academic option was included in the questionnaire, to capture respondents who have received a training that is not worthy of a degree/award from a tertiary institution. Nineteen respondents claimed they have attended a tertiary institution’s training and amongst this number, 18 (94.7%) claimed to use mobile applications and cloud applications, while all the holders claimed to use all the other technologies. Their individual contribution to the total number of users was 9.6%, 11.0%, 9.5% and 9.8% for social media, mobile application, mobile device and cloud service, respectively. It can be posited that specific training in tertiary institution adds value to a person’s ability to use SoMoClo technologies. However, as has been argued, the researcher is unable to verify that an award/degree can enhance and/or influence the ability of a professional accountant to use any of the SoMoClo technologies. This notwithstanding, it is significant to posit that academic awards and degrees have shown themselves to be significant in shaping professional accountants’ use of SoMoClo technologies. It is important to state that this assertion was tested in the specific objective two. Professional Qualifications. Moving onto the professional qualifications and starting with the ATS showed that 37 respondents used this route to become professional accountants. All of them claimed to use a mobile device, while 36 (97.3%) respondents amongst them claimed to use social media and cloud service. The mobile application use was the least with 29 (78.4%) respondents. Their specific contributions to the use of SoMoClo technologies were at 18.2%, 17.7%, 18.4% and 19.7% for social media, mobile application, mobile device and cloud service, respectively. Holders of this degree are therefore good users of SoMoClo technologies. It is to be noted that as with other qualifications, the use of mobile application amongst professional accountants received the least patronage. Twenty-three respondents claimed to have passed through the foundation level of ICAN’s professional education and all of them claimed to use social media and mobile devices. Eighteen (78.3%) claimed to use mobile application and 21 (91.3%) claimed to use cloud service. This resulted in individual contribution of 11.6%, 11.0%, 11.4% and 11.5% for social media, mobile application, mobile device and cloud service, respectively. Mobile application was the least used technology by holders of the foundation certificate. Now, it should be clarified that the questionnaire did not ask if respondents completed the level or merely registered, but the former is assumed. As with other qualifications, it may not be accurate to specifically state that it was the foundation level that equipped respondents for the use of SoMoClo technologies; however, it can be stated from the results that holders of this qualification are users of SoMoClo technologies. After the foundation level, ICAN had another level called the intermediate, which has gone through restructuring overtime. Thirty-six respondents claimed to

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have used this route and all of them claimed to use social media and mobile devices. Twenty-nine (80.6%) claimed to be users of mobile applications, while 31 (86.1%) claimed to be users of cloud technology. Holders of this qualification who used social media accounted for 18.2% of all users of social media. The percentage contribution to other technologies is 17.7%, 17.9% and 16.9% for mobile application, mobile device and cloud service, respectively. It is apparent that holders of this qualification use SoMoClo technologies with mobile application being the least used amongst them. The professional stage/level of ICAN’s professional education has also gone through restructuring overtime; however, it is held at face value. This stage/level is the penultimate to becoming a professional accountant, and the final stage/level to becoming a qualified accountant. After the professional stage/level, a candidate entering the professional cadre would show evidence of practical experience, which is the final requirement of the IPD. This level had the highest number of respondents. Hundred sixty-two respondents claimed to have gone through the professional stage/level of ICAN’s professional education. The highest technologies subscribed to by holders of this qualification are social media and mobile device with 160 (98.8%), while mobile application had the lowest number of subscribers (132, 81.5%). The subscribers to cloud service are even higher with 144 (88.9%) respondents. The individual contribution of holders of this qualification to the total number of users of each of the SoMoClo technologies is 80.8%, 80.5%, 79.6% and 78.7% for social media, mobile application, mobile device and cloud service, respectively. It looks like the individual contribution of mobile device and cloud service is the least; however, this should be compared with the frequency of holders. Mobile application is obviously the least used technology, yet holders of this qualification use SoMoClo technologies. The NCA is ANAN’s professional training institution. All the respondents who claimed to have attended the NCA claimed to use all the SoMoClo technologies. The specific contribution amounted to 3.0%, 3.7%, 3.0% and 3.3% for social media, mobile application, mobile device and cloud service, respectively. The conversion course allows members of other PAOs to obtain membership of another PAO. Thirty-two respondents claimed to have used this route. All of them claimed to use a mobile device. Thirty-one (96.9%) respondents amongst holders of the qualification claimed to use cloud technology, while 23 (71.9%) amongst them claimed to use mobile application. Twenty-nine (90.6%) holders of a conversion certificate claimed to use social media. Their individual contribution amounted to 14.6%, 14.0%, 15.9% and 16.9% for social media, mobile application, mobile device and cloud service, respectively. Mobile application still emerged the least used amongst holders of the qualification. Moving to the CPD, for which two items were used to measure, first is a direct questioning of the number of CPD engagements in the last one year. Hundred sixty respondents claimed they attended at least one CPD engagement of their PAO in the last one year. Amongst this number, 159 (99.4%) claimed to be users of social media and 136 (85.0%) amongst them claimed to be users of mobile application. Hundred fifty-eight (98.8%) professional accountants who claimed to have attended at least one

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Social Media, Mobile and Cloud Technology Use in Accounting

CPD engagement claimed as well that they use mobile device and 144 (90.0%) amongst them claimed to use cloud service. The individual contribution of these respondents to the total users of the technologies is 80.3%, 82.9%, 78.6% and 78.7% for social media, mobile application, mobile device and cloud service, respectively. Special technology training (STT) was the last item in the ATF framework. Hundred fifty respondents claimed to have attended at least one STT in the last one year. Amongst this number, 148 (98.7%) claimed to use at least one social media platform, while 125 (83.3%) claimed to use mobile application. Hundred forty-nine (99.3%) claimed to be users of mobile device and 138 (92.0%) claimed to be users of cloud service. Their individual contribution amounted to 74.7%, 76.2%, 74.1% and 75.4% for social media, mobile application, mobile device and cloud service, respectively. In general, mobile application and cloud technology were the least used technologies amongst holders of awards and degrees as well as professional certifications. Mobile device and social media were the highly used technologies amongst professional accountants. The results also indicate that holders of academic awards and degrees and professional certificates were users of SoMoClo technologies. Conclusively, although it was not possible to identify which specific qualification enhanced professional accountants’ use of SoMoClo technologies in this study, it is obvious that the ATF contributes to the use of technology amongst professional accountants. The direct questioning of the effect of academic and professional qualifications on the appreciation, learning and usability of technology was achieved in objective two. Model Specification The fourth objective and second hypothesis were tested using the logistic regression analysis. The use of the logistic regression is appropriate, given that the dependent variable is measured as a binary variable while the independent variables are both categorical and continuous (Olubusoye, 2016). The use of SoMoClo technologies (SoMoCloUse ) is the dependent variable. The independent variables are the accountants’ training framework (ATF) and perception (PCT). There are three moderating variables – age (AG), experience (XP) and gender (GND). It had earlier been stated that both intention to use, and where measurable, actual use can be used to measure the dependent variable; hence this study used self-reported responses of intended and/or actual use, measured using the WRA framework. The WRA framework for the measurement of SoMoCloUse is stated as follows: SoMoCloUse responses ¼ f ðWillingness 1 Readiness 1 AblenessÞ

The model for the logistic regression analysis is stated as: SoMoCloUSe ¼ f ðATF; PCTÞ ATF ¼ f ðAAE; PAEÞ

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203

AAE: Accounting academic education; AAE ¼ f ðPolytechnic award; University degreeÞ Polytechnic award ¼ f ðND; HNDÞ University degree ¼ f ðB:Sc:; M:Sc:; Ph:D:; OtherÞ

PAE: Professional accounting education; PAE ¼ f ðIPD; CPDÞ PCT ¼ f ðPEOU; PUÞ SoMoCloUse ¼ b0 1 b1 ATF 1 b2 PCT 1 «

Given that the relationship is moderated by age, experience and gender, the extended model appears as: SoMoCloUse ¼ b0 1 b1 ATF 1 b2 PCT 1 b3 AG 1 b4 XP 1 b5 GND 1 «

For the purpose of the hypotheses, each of the SoMoClo technologies were tested individually, hence the need to state the model individually as: Social mediaUse ¼ b0 1 b1 ATF 1 b2 PCT 1 b3 AG 1 b4 XP 1 b5 GND 1 « Mobile applicationUse ¼ b0 1 b1 ATF 1 b2 PCT 1 b3 AG 1 b4 XP 1 b5 GND 1 « Mobile devicesUse ¼ b0 1 b1 ATF 1 b2 PCT 1 b3 AG 1 b4 XP 1 b5 GND 1 « Cloud technologyUse ¼ b0 1 b1 ATF 1 b2 PCT 1 b3 AG 1 b4 XP 1 b5 GND 1 «

Only practical experience is excluded, given that all respondents would have met the qualification for it.

Prediction of the Use of Social Media Technology There are three primary variables in this objective: ATF, PCT and use of social media. Other variables that were used as predictors are age, gender and experience. We proposed the use of the specialty-context for analysis; however, this was not possible due to inability to meet the test criterion. The criterion is that ‘for logistic regression, the dependent value must assume exactly two values on the cases being processed’ (IBM Corporation, 2011, n. Binary Logistic Test Output) and if this is violated, execution of the test stops. We therefore used all the respondents, ignoring the specialty-context in the analysis. The use of social media was measured as a dichotomous variable, based on two approaches. First, the question on the use of social media platforms was used to arrive at respondents who used at least one social media platform and secondly the WRA framework was used to determine respondents who have behavioural intention to use a social media application. This resulted in a binary scale of 0 5 no use and 1 5 use.

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Social Media, Mobile and Cloud Technology Use in Accounting

Prediction of Use of Social Media Applications. The results showed that 198 respondents claimed to use at least one social media platform. The binary logistic regression results showed a pre-independent variable prediction of 97.5%. In addition, before including the independent variables, the constant was statistically significant (b 5 3.679, p 5 0.000). The model was good (x2 5 19.350, p 5 0.002), then the Cox & Snell R square (0.091) and the Nagelkerke R square (0.441) imply a significant prediction of the use of social media by the explanatory variables. Hosmer and Lemeshow test was also used to determine the fitness of the model; it showed a good fit (x 2 5 399, p 5 1.000, v 5 7). With the inclusion of the explanatory variables, the prediction strength dropped to 97.0%, which implies that the independent variables influenced the dependent variable. The results of the Wald test showed that the constant and experience had no effect on the dependent variable at 0.000, while other variables had significant positive figures. The b values for the variables in the equation showed that the ATF had a positive influence (b 5 1.082, p 5 0.048) and PCT was positive (b 5 0.245, p 5 0.359). Age and gender had negative and statistically insignificant effect on the dependent variable, while experience had a positive but statistically insignificant effect. The results are presented in Table 35 and the regression equation values are presented as: Social mediause ¼ 2 18:366 1 1:082ATF 1 :245PCT 1 ð 2 1:247ÞAG 1 16:4701XP 1 ð 2 2:008ÞGND

Prediction of Behavioural Intention to Use Social Media Technology. The result using the behavioural intention to use social media construct derived using the WRA framework showed that 191 respondents intended to use social media. The binary logistic regression results showed a pre-independent variable prediction of 94.1%. Before including the independent variables, the constant was statistically significant (b 5 2.767, p 5 0.000). The model was good (x 2 5 11.860, p 5 0.037), then the Cox & Snell R square (0.057) and the Nagelkerke R square (0.157) imply a significant prediction of the use of social media by the explanatory variables. Hosmer and Lemeshow test was also used to determine the fitness of the model; it showed a good fit (x2 5 8.562, p 5 0.381, v 5 8). With the inclusion of the explanatory variables, the prediction strength dropped to 93.6%, which implies that the independent variables influenced the dependent variable. The b values for the variables in the equation showed that the ATF had a negative influence (b 5 20.372, p 5 0.080) but PCT was positive (b 5 0.462, p 5 0.005). Age, experience and gender had positive and statistically insignificant effect on the dependent variable. The results are shown in Table 36, while the regression equation is presented as: Social mediaBI_use ¼ 2 2:777 1 ð 2 :372ÞATF 1 :462PCT 1 :290AG 1 :223XP 1 :016GND

Table 35. Binary Logistic Regression Results for Use of Social Media. Classification Tablea,b

Observed

Step 0

Use of social media

Predicted Use of social media No Yes 0 5 0 198

No Yes

Percentage correct 0.0 100.0 97.5

Overall Percentage Variables in the Equation

Step 0

Constant

b

S.E.

Wald

df

Sig.

Exp(b)

3.679

0.453

66.002

1

0.000

39.600

Variables not in the Equation

Step 0

Variables

df

Sig.

5.836 1.072 2.672 4.212 6.451 13.982

1 1 1 1 1 5

0.016 0.301 0.102 0.040 0.011 0.016

Study

Overall Statistics

ATF PCT AG XP GND

Score

205

206

Table 35. (Continued)

Step 1

Step Block Model

Chi-square

df

Sig.

19.350 19.350 19.350

5 5 5

0.002 0.002 0.002

Model Summary

Step 1

22 Log Likelihood

Cox & Snell R Square

Nagelkerke R Square

27.564c

0.091

0.441

Hosmer and Lemeshow Test

Step 1

Chi-square

df

0.399

7

Sig.

1.000 d

Classification Table

Observed

Step 1

Use of social media Overall Percentage

No Yes

Predicted Use of social media No 0 1

Yes 5 197

Percentage correct 0.0 99.5 97.0

Social Media, Mobile and Cloud Technology Use in Accounting

Omnibus Tests of Model Coefficients

Variables in the Equation 95% C.I. for EXP(b)

Step 1

e

ATF PCT AG XP GND Constant

b

S.E.

Wald

df

Sig.

Exp(b)

Lower

Upper

1.082 0.245 21.247 16.470 22.008 218.366

0.547 0.267 0.982 1,709.230 1.222 1,709.235

3.909 0.840 1.612 0.000 2.697 0.000

1 1 1 1 1 1

0.048 0.359 0.204 0.992 0.101 0.991

2.950 1.278 0.288 14,220,601.311 0.134 0.000

1.009 0.757 0.042 0.000 0.012

8.618 2.158 1.969 . 1.475

a

Constant is included in the model. The cut value is 0.500. c Estimation terminated at iteration number 20 because maximum iterations have been reached. Final solution cannot be found. d The cut value is 0.500. e Variable(s) entered on step 1: ATF, PCT, AG, XP and GND. b

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208

Classification Tablea,b

Observed

Step 0

Intention to use social media

No Yes

Predicted Intention to use social media No Yes 0 12 0 191

Percentage correct 0.0 100.0 94.1

Overall Percentage Variables in the Equation

Step 0

Constant

b

S.E.

Wald

df

Sig.

Exp(b)

2.767

0.298

86.467

1

0.000

15.917

Variables not in the Equation

Step 0

Variables

Overall Statistics

ATF PCT AG XP GND

Score

df

Sig.

0.909 8.745 1.602 1.046 0.983 13.332

1 1 1 1 1 5

0.340 0.003 0.206 0.307 0.322 0.020

Social Media, Mobile and Cloud Technology Use in Accounting

Table 36. Binary Logistic Regression Results for Intention to Use Social Media.

Omnibus Tests of Model Coefficients

Step 1

Chi-square

df

Sig.

11.860 11.860 11.860

5 5 5

0.037 0.037 0.037

Step Block Model

Model Summary 22 Log Likelihood

Step 1

79.296

c

Cox & Snell R Square

Nagelkerke R Square

0.057

0.157

Hosmer and Lemeshow Test

Step 1

Chi-square

df

Sig.

8.562

8

0.381

Classification Tabled

Observed

Step 1

Intention to use social media

Percentage correct 0.0 99.5 93.6

Study

Overall Percentage

No Yes

Predicted Intention to use social media No Yes 0 12 1 190

209

210

Table 36. (Continued)

95% C.I. for EXP(b)

Step 1

a

e

ATF PCT AG XP GND Constant

b

S.E.

Wald

df

Sig.

Exp(b)

Lower

Upper

20.372 0.462 0.290 0.223 0.016 22.777

0.212 0.166 0.616 0.532 0.725 2.380

3.063 7.759 0.221 0.176 0.001 1.361

1 1 1 1 1 1

0.080 0.005 0.639 0.675 0.982 0.243

0.690 1.588 1.336 1.250 1.017 0.062

0.455 1.147 0.399 0.441 0.246

1.046 2.198 4.472 3.546 4.206

Constant is included in the model. The cut value is 0.500. c Estimation terminated at iteration number 7 because parameter estimates changed by less than 0.001. d The cut value is 0.500. e Variable(s) entered on step 1: ATF, PCT, AG, XP and GND. b

Social Media, Mobile and Cloud Technology Use in Accounting

Variables in the Equation

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211

Prediction of the Use of Mobile Technology Mobile technology is divided into two areas, that is, mobile application and mobile devices. For mobile applications, 164 respondents claimed to use at least one mobile application, and 201 respondents claimed to use at least one mobile device. Prediction of the Use of Mobile Application. The initial percentage of prediction without the independent variables was 80.8% and the constant was statistically significant (b 5 1.436, p 5 0.000). The statistical significance of the explanatory variables shows that none was statistically significant. The model was good (x 2 5 12.434, p 5 0.029) and the Hosmer and Lemeshow test (x2 5 3.319, p 5 0.913) justifies the fitness of the model. The Pseudo R-squared values are rather small with the 0.059 (Cox & Snell) and 0.095 (Nagelkerke). The prediction value remained constant at 80.8% despite the inclusion of the independent variables and the b values show negative values for the constant and gender. The Wald test results showed that all the explanatory variables had effects on the dependent variables. The regression equation with the values is given below: Mobile applicationuse ¼ 2 1:404 1 :154ATF 1 :089PCT 1 :316AG 1 :121XP 1 ð 2 :151ÞGND

Prediction of the Use of Mobile Device. The use of mobile device has the highest number of respondents, that is 201, which implies that only 2 respondents claimed they do not use a mobile device and the prediction was the highest as well at 99.0%. The constant was statistically significant (b 5 4.610, p 5 0.000); however, none of the explanatory variables were significant. The omnibus tests of model coefficients showed that the model was not good (x2 5 7.276, p 5 0.201), but the Hosmer and Lemeshow test gave a different result (x2 5 0.743, p 5 0.999). The Pseudo R-squared values were relatively low at 0.035 (Cox & Snell) and 0.336 (Nagelkerke). The percentage correct prediction stood still at 99.0% and the coefficients gave insight. The Wald test showed that all the variables contributed to the model; however, they were all statistically insignificant. The results are presented in Tables 37–39. The regression for the prediction of use of mobile device is presented here below: Mobile deviceuse ¼ 2 1:337 1 :809ATF 1 :233PCT 1 3:042AG 1 ð 2 2:511ÞXP 1 ð 2 :992ÞGND

Prediction of Behavioural Intention to Use Mobile Technology. The results show that 94.1% was predicted and the constant was statistically significant (b 5 2.767, p 5 0.000), while perception was the only explanatory variable that was significant. The omnibus tests of model coefficients showed that the model was good (x2 5 12.838, p 5 0.025), and the Hosmer and Lemeshow test result (x2 5 0.3.962, p 5 0.860) confirmed the goodness of the model. The Pseudo R-squared values were 0.061 (Cox & Snell) and 0.169 (Nagelkerke). The percentage correct prediction remained 94.1%. Only perception was statistically significant. The regression equation is as follows:

212

Classification Tablea,b

Observed

Step 0

Use of mobile application

Predicted Use of mobile application No Yes 0 39 0 164

No Yes

Overall Percentage

Percentage correct 0.0 100.0 80.8

Variables in the Equation

Step 0

Constant

b

S.E.

Wald

df

Sig.

Exp(b)

1.436

0.178

64.999

1

0.000

4.205

Variables not in the Equation

Step 0

Variables

Overall Statistics

ATF PCT AG XP GND

Score

df

Sig.

4.646 0.826 8.949 7.856 2.068 11.381

1 1 1 1 1 5

0.031 0.363 0.003 0.005 0.150 0.044

Social Media, Mobile and Cloud Technology Use in Accounting

Table 37. Binary Logistic Regression Results for Use of Mobile Application.

Omnibus Tests of Model Coefficients

Step 1

Step Block Model

Chi-square

df

Sig.

12.434 12.434 12.434

5 5 5

0.029 0.029 0.029

Model Summary 22 Log Likelihood

Step 1

186.214

c

Cox & Snell R Square

Nagelkerke R Square

0.059

0.095

Hosmer and Lemeshow Test

Step 1

Chi-square

df

3.319

8

Sig.

0.913 d

Classification Table

Observed

Step 1

Use of mobile application

Percentage correct 0.0 100.0 80.8

Study

Overall Percentage

No Yes

Predicted Use of mobile application No Yes 0 39 0 164

213

214

Variables in the Equation 95% C.I. for EXP(b)

Step 1

a

e

ATF PCT AG XP GND Constant

b

S.E.

Wald

df

Sig.

Exp(b)

Lower

Upper

0.154 0.089 0.316 0.121 20.151 21.404

0.130 0.108 0.382 0.307 0.412 1.688

1.401 0.679 0.686 0.154 0.135 0.692

1 1 1 1 1 1

0.237 0.410 0.408 0.695 0.714 0.405

1.166 1.093 1.372 1.128 0.860 0.246

0.904 0.884 0.649 0.617 0.384

1.504 1.352 2.897 2.061 1.927

Constant is included in the model. The cut value is 0.500. c Estimation terminated at iteration number 5 because parameter estimates changed by less than 0.001. d The cut value is 0.500. e Variable(s) entered on step 1: ATF, PCT, AG, XP and GND. b

Social Media, Mobile and Cloud Technology Use in Accounting

Table 37. (Continued)

Table 38. Binary Logistic Regression Results for Use of Mobile Device. Classification Tablea,b

Observed

Step 0

Predicted Use of mobile device No Yes 0 2 0 201

Use of mobile device No Yes Overall Percentage

Percentage correct 0.0 100.0 99.0

Variables in the Equation

Step 0

Constant

b

S.E.

Wald

df

4.610

0.711

42.088

1

Score

df

Sig.

1.562 0.544 0.092 0.403 0.429 6.520

1 1 1 1 1 5

0.211 0.461 0.762 0.526 0.512 0.259

Sig.

Exp(b)

0.000 100.500

Variables not in the Equation

Step 0

Variables

Study

Overall Statistics

ATF PCT AG XP GND

215

216

Table 38. (Continued)

Step 1

Step Block Model

Chi-square

df

Sig.

7.276 7.276 7.276

5 5 5

0.201 0.201 0.201

Model Summary 22 Log Likelihood

Step 1

Cox & Snell R Square Nagelkerke R Square

15.185c

0.035

0.336

Hosmer and Lemeshow Test

Step 1

Chi-square 0.743

df 8

Sig. 0.999 Classification Tabled

Observed

Step 1

Use of mobile device No Yes Overall Percentage

Predicted Use of mobile device No Yes 0 2 0 201

Percentage correct 0.0 100.0 99.0

Social Media, Mobile and Cloud Technology Use in Accounting

Omnibus Tests of Model Coefficients

Variables in the Equation 95% C.I. for Exp(b)

Step 1

e

ATF PCT AG XP GND Constant

b

S.E.

Wald

df

Sig.

Exp(b)

Lower

Upper

0.809 0.233 3.042 22.511 20.992 21.337

0.656 0.361 2.355 1.329 2.079 5.478

1.520 0.418 1.668 3.571 0.228 0.060

1 1 1 1 1 1

0.218 0.518 0.196 0.059 0.633 0.807

2.245 1.263 20.942 0.081 0.371 0.263

0.621 0.622 0.207 0.006 0.006

8.121 2.563 2,116.075 1.098 21.826

a

Constant is included in the model. The cut value is 0.500. c Estimation terminated at iteration number 9 because parameter estimates changed by less than 0.001. d The cut value is 0.500. e Variable(s) entered on step 1: ATF, PCT, AG, XP and GND. b

Study 217

218

Table 39. Binary Logistic Regression Results for Intention to Use Mobile Technology.

Observed

Step 0

Predicted Intention to use mobile technology No Yes 0 12 0 191

Intention to No use mobile Yes technology Overall Percentage

Percentage correct 0.0 100.0 94.1

Variables in the Equation

Step 0

Constant

b

S.E.

Wald

df

2.767

0.298

86.467

1

Score

df

Sig.

1.757 6.705 0.251 0.000 2.711 13.074

1 1 1 1 1 5

0.185 0.010 0.616 0.987 0.100 0.023

Variables not in the Equation

Step 0

Variables

Overall Statistics

ATF PCT AG XP GND

Sig.

Exp(b)

0.000 15.917

Social Media, Mobile and Cloud Technology Use in Accounting

Classification Tablea,b

Omnibus Tests of Model Coefficients

Step 1

Step Block Model

Chisquare

df

Sig.

12.838 12.838 12.838

5 5 5

0.025 0.025 0.025

Model Summary 22 Log Likelihood

Step 1

78.318c

Cox & Nagelkerke R Square Snell R Square

0.061

0.169

Hosmer and Lemeshow Test

Step 1

Chi-square

df

Sig.

3.962

8

0.860

Classification Tabled

Observed

0.0 100.0 94.1

219

Intention to No use mobile Yes technology Overall Percentage

Percentage correct Study

Step 1

Predicted Intention to use mobile technology No Yes 0 12 0 191

220

Table 39. (Continued)

95% C.I. for EXP(b)

Step 1

a

e

ATF PCT AG XP GND Constant

b

S.E.

Wald

df

Sig.

Exp(b)

Lower

Upper

20.335 0.432 20.853 0.606 21.233 20.391

0.219 0.169 0.520 0.441 0.724 2.402

2.346 6.535 2.695 1.884 2.901 0.027

1 1 1 1 1 1

0.126 0.011 0.101 0.170 0.089 0.871

0.715 1.540 0.426 1.832 0.292 0.676

0.466 1.106 0.154 0.772 0.071

1.098 2.144 1.180 4.350 1.204

Constant is included in the model. The cut value is 0.500. c Estimation terminated at iteration number 6 because parameter estimates changed by less than 0.001. d The cut value is 0.500. e Variable(s) entered on step 1: ATF, PCT, AG, XP and GND. b

Social Media, Mobile and Cloud Technology Use in Accounting

Variables in the Equation

Study

221

Mobile technologyBIuse ¼ 2 0:391 1 ð 2 0:335ÞATF 1 0:432PCT 1 ð 2 0:853ÞAG 1 0:606XP 1 ð 2 1:233ÞGND

Prediction of the Use of Cloud Technology From the response statistics 183 respondents claimed to use at least one cloud service and 166 respondents intended to use cloud technology. Prediction of Use of Cloud Services. Prediction rate of 90.1% was achieved. The constant for the model is statistically significant (b 5 2.214, p 5 0.000) and none of the independent variables showed statistical significance. The model was good (x 2 5 11.436, p 5 0.043), and the Hosmer and Lemeshow test (x2 5 10.009, p 5 0.264) corroborated the goodness of the model. The Pseudo R-squares were 0.055 (Cox & Snell) and 0.115 (Nagelkerke) and there was no change in the predicted percentage. The contribution of each variable is shown in the regression equation: Cloud technologyuse ¼ 0:192 1 0:219ATF 1 0:181PCT 1 ð 2 0:183ÞAG 1 ð 2 0:389ÞXP 1 ð 2 0:282ÞGND

Prediction of Behavioural Intention to Use Cloud Technology. The prediction based on the use of cloud technology showed a rate of 81.1%. The constant for the model is statistically significant (b 5 1.501, p 5 0.000) and one of the independent variables (perception) showed statistical significance. The model was good however (x2 5 17.540, p 5 0.004), and the Hosmer and Lemeshow test (x2 5 13.171, p 5 0.106) corroborated the goodness of the model. The Pseudo R-squares were 0.083 (Cox & Snell) and 0.135 (Nagelkerke). The prediction changed to 82.8%. The contribution of each variable is shown in the regression equation: Cloud technologyBI_use ¼ 2 1:091 1 ð 2 0:176ÞATF 1 0:316PCT 1 ð 2 0:783ÞAG 1 0:468XP 1 ð 2 :777ÞGND

It is to be noted that of significant interest to this study is the predictability statistics. Results on cloud technology are shown in Tables 40 and 41. Test of Second Hypothesis The tests used odds ratio (Exp(b)) and a 95% Confidence Interval for odds ratio (95% C.I. for Exp(b)) from the binary logistic regression results. The decision rule is that when the odds ratio is greater than 1, then it may be inferred that the variable has a significant effect and when 1 emerges between the lower and upper bounds of the CI, then the variable is a significant predictor. The hypotheses of the study guessed that accountants’ training framework and perception do not significantly predict the use of SoMoClo technologies amongst Nigerian professional accountants. The results of the predictability of the model for SoMoClo technologies were 97.0% for social media, 80.8% for mobile application, 99.0% for mobile device and 90.1% for cloud service. Using the WRA framework, predictability of the

222

Table 40. Binary Logistic Regression Results for Use of Cloud Technology.

Observed

Step 0 Use of cloud technology

Predicted Use of cloud technology No Yes 0 20 0 183

No Yes

Overall Percentage

Percentage correct 0.0 100.0 90.1

Variables in the Equation

Step 0 Constant

b

S.E.

Wald

df

2.214

0.236

88.358

1

Score

df

Sig.

0.098 2.034 6.718 8.410 0.178 12.100

1 1 1 1 1 5

0.754 0.154 0.010 0.004 0.673 0.033

Variables not in the Equation

Step 0 Variables

Overall Statistics

ATF PCT AG XP GND

Sig.

Exp(b)

0.000 9.150

Social Media, Mobile and Cloud Technology Use in Accounting

Classification Tablea,b

Omnibus Tests of Model Coefficients

Step 1 Step Block Model

Chi-square

df

Sig.

11.436 11.436 11.436

5 5 5

0.043 0.043 0.043

Model Summary

Step 1

22 Log Likelihood

Cox & Snell R Square

Nagelkerke R Square

119.224c

0.055

0.115

Hosmer and Lemeshow Test

Step 1

Chi-square

df

10.009

8

Sig.

0.264

Classification Table

Observed

Overall Percentage

No Yes

Predicted Use of cloud technology No Yes 0 20 0 183

Percentage correct 0.0 100.0 90.1

Study

Step 1 Use of cloud technology

d

223

224

Table 40. (Continued)

95% C.I. for Exp(b)

Step 1e ATF PCT AG XP GND Constant a

b

S.E.

Wald

df

Sig.

0.219 0.181 20.183 20.389 20.282 0.192

0.175 0.136 0.464 0.341 0.606 2.037

1.578 1.777 0.155 1.302 0.217 0.009

1 1 1 1 1 1

0.209 0.183 0.694 0.254 0.641 0.925

Constant is included in the model. The cut value is 0.500. c Estimation terminated at iteration number 6 because parameter estimates changed by less than 0.001. d The cut value is 0.500. e Variable(s) entered on step 1: ATF, PCT, AG, XP and GND. b

Exp(b) Lower Upper

1.245 1.199 0.833 0.678 0.754 1.211

0.884 0.918 0.336 0.347 0.230

1.753 1.564 2.067 1.322 2.474

Social Media, Mobile and Cloud Technology Use in Accounting

Variables in the Equation

Table 41. Binary Logistic Regression Results for Intention to Use Cloud Technology. Classification Tablea,b

Observed

Step 0

Intention to use cloud technology

No Yes

Predicted Intention to use cloud technology No Yes 0 37 0 166

Overall Percentage

Percentage correct

0.0 100.0 81.8

Variables in the Equation

Step 0

Constant

b

S.E.

Wald

df

Sig.

EXP(b)

1.501

0.182

68.174

1

0.000

4.486

Variables not in the Equation

Step 0

Variables

Sig.

2.342 8.257 2.239 0.445 1.689 17.461

1 1 1 1 1 5

0.126 0.004 0.135 0.505 0.194 0.004

225

df

Study

Overall Statistics

ATF PCT AG XP GND

Score

226

Table 41. (Continued)

Step 1

df

Sig.

17.540 17.540 17.540

5 5 5

0.004 0.004 0.004

Step Block Model

Model Summary 22 Log Likelihood

Step 1

175.234

c

Cox & Snell R Square

Nagelkerke R Square

0.083

0.135

Hosmer and Lemeshow Test

Step 1

Chi-square

df

Sig.

13.171

8

0.106

Classification Tabled

Observed

Step 1

Intention to use cloud technology Overall Percentage

No Yes

Predicted Intention to use cloud technology No Yes 3 34 1 165

Percentage correct 8.1 99.4 82.8

Social Media, Mobile and Cloud Technology Use in Accounting

Omnibus Tests of Model Coefficients Chi-square

Variables in the Equation 95% C.I. for EXP(b)

Step 1

e

ATF PCT AG XP GND Constant

b

S.E.

Wald

df

Sig.

Exp(b)

Lower

Upper

20.176 0.316 20.783 0.468 20.777 21.091

0.129 0.112 0.344 0.273 0.443 1.632

1.857 8.044 5.192 2.937 3.082 0.447

1 1 1 1 1 1

0.173 0.005 0.023 0.087 0.079 0.504

0.838 1.372 0.457 1.596 0.460 0.336

0.651 1.103 0.233 0.935 0.193

1.080 1.707 0.896 2.725 1.095

a

Constant is included in the model. The cut value is 0.500. c Estimation terminated at iteration number 5 because parameter estimates changed by less than 0.001. d The cut value is 0.500. e Variable(s) entered on step 1: ATF, PCT, AG, XP and GND. b

Study 227

228

Social Media, Mobile and Cloud Technology Use in Accounting

model for SoMoClo technologies were 93.6% for social media technology, 94.1% for mobile technology and 82.8% for cloud technology. ATF and PCT Beta figures also showed that they were significant predictors for the use of SoMoClo technologies, but negative figures were recorded for ATF with respect to intention to use SoMoClo technologies. Perception was statistically significant for intention to use SoMoClo technologies. Hypothesis for Social Media. The test results for ATF and PCT are 2.950 and 1.278, respectively, which are both greater than 1. The lower bound of CI for ATF is greater than 1, although a significant result would have been having 1 between the lower and the upper bounds. Based on this result, the first null hypothesis that ATF and PCT do not significantly affect the use of social media may well be accepted for PCT, not for ATF. It should be noted, however, that ATF was statistically significant, while PCT was not. Hypothesis for Mobile Application. The test results for ATF and PCT are 1.166 and 1.093 respectively, which are both greater than 1. Both variables (ATF and PCT) have 1 between the lower and upper bounds of the CI. Based on this result, the null hypothesis that ATF and PCT do not significantly affect the use of mobile application is rejected. Hypothesis for Mobile Device. The test results for ATF and PCT are 2.245 and 1.263, respectively, which are both greater than 1. Both variables (ATF and PCT) have 1 between the lower and upper bounds of the CI. Based on this result, the null hypothesis that ATF and PCT do not significantly affect the use of mobile device is rejected. Hypothesis for Cloud Technology. The test results for ATF and PCT are 1.245 and 1.199, respectively, which are both greater than 1. Both variables (ATF and PCT) have 1 between the lower and upper bounds of the CI. Based on this result, the null hypothesis that ATF and PCT do not significantly affect the use of mobile device is rejected. The results using ‘intention to use’ showed varying odds ratio and are shown in Table 42.

Summary and Conclusions We assessed the technology competence of Nigerian professional accountants and the factors that influence them, especially the ATF and PCT. Other studies have factored age, gender, ethnicity and other extraneous variables, but it appears that, the ATF as a significant aggregate factor has been ignored. Considering this significant gap, this study held the ATF and the use of SoMoClo technologies in a twist of predictive and interpretive value-analyses. The measured use of SoMoClo technologies were used to interpret the value of training that Nigerian professional accountants have acquired, while the ATF was used to predict the use of SoMoClo technologies. This was significant because SoMoClo technologies have become actionable technologies used in many organisations. The fear was that if professional accountants in developing economies are unable to recognise, adopt

Table 42. Summary of Predictability and Odds Ratio Statistics. ATF SoMoClo Technologies Use of…

Intention to use…

Use of…

b

Sig.

b

Sig.

97.0 80.8 99.0 90.1 93.6 94.1 82.8

1.082 0.154 0.809 0.219 20.372 20.335 20.176

0.048 0.237 0.218 0.209 0.080 0.126 0.173

0.245 0.089 0.233 0.181 0.462 0.432 0.316

0.359 0.410 0.518 0.183 0.005 0.011 0.005

Mobile Application

95% C.I. for EXP(b) Exp(b)

Predictability Percentage

Social media Mobile application Mobile device Cloud service Social media Mobile technology Cloud technology Social Media

PCT

Mobile Device

95% C.I. for EXP(b)

Cloud Technology

95% C.I. for EXP(b)

95% C.I. for EXP(b)

Upper

Exp(b)

Lower

Upper

Exp(b)

Lower

Upper

Exp(b)

Lower

Upper

ATF 2.950 1.009 PCT 1.278 0.757 AG 0.288 0.042 XP 14,220,601.311 0.000 GND 0.134 0.012 Constant 0.000

8.618 2.158 1.969 . 1.475

1.166 1.093 1.372 1.128 0.860 0.246

0.904 0.884 0.649 0.617 0.384

1.504 1.352 2.897 2.061 1.927

2.245 1.263 20.942 0.081 0.371 0.263

0.621 0.622 0.207 0.006 0.006

8.121 2.563 2,116.075 1.098 21.826

1.245 1.199 0.833 0.678 0.754 1.211

0.884 0.918 0.336 0.347 0.230

1.753 1.564 2.067 1.322 2.474

Study

Lower

229

230

Table 42. (Continued)

ATF PCT AG XP GND Constant

Mobile Technology

Cloud Technology

95% C.I. for EXP(b)

95% C.I. for EXP(b)

95% C.I. for EXP(b)

Exp(b)

Lower

Upper

Exp(b)

Lower

Upper

Exp(b)

Lower

Upper

0.690 1.588 1.336 1.250 1.017 0.062

0.455 1.147 0.399 0.441 0.246

1.046 2.198 4.472 3.546 4.206

0.715 1.540 0.426 1.832 0.292 0.676

0.466 1.106 0.154 0.772 0.071

1.098 2.144 1.180 4.350 1.204

0.838 1.372 0.457 1.596 0.460 0.336

0.651 1.103 0.233 0.935 0.193

1.080 1.707 0.896 2.725 1.095

Social Media, Mobile and Cloud Technology Use in Accounting

Intention to Use…

Social Media

Study

231

and competently use these technologies, the accounting profession in those economies is not only fated, but also relegated in the global market. The response rate was low, indicating the level of adoption of online surveys. This is, however, not indicative of the use of SoMoClo technologies, which showed a high rate of self-reported adoption. It was interesting to find that there was a paradox between the response device used and respondents’ preferred device. It appeared that respondents used a device in responding to the survey because of its availability, rather than personal preference. As usual as well, most of the respondents were practitioners, followed by researchers. Non-practicing professional accountants even exceeded policy accountants. The specialty of accounting policy in many developing economies is still inchoate and may require some revisiting. Unfortunately, as well, primary policymakers were not actively involved in tertiary education, while it was thrilling to see primary practitioners participate in the training of graduate accountants in ivory towers. In addition, some researchers were closely involved in industry and it has been stressed that it helps better teaching. Financial reporting area of expertise had the highest number of respondents, followed by external auditing, while ethics had the lowest. This may be a signal to the prevalence of unethical behaviour amongst professional accountants all over the world, which has caused significant damage to the reputation of the accounting profession. The gender distribution was representative of findings that showed a significant gap and drop from the number of female students studying accounting and those who become professional accountants. Respondents were also moderately youthful with more in the 30s and 40s than in the 50s and 60s. All the respondents used for analysis were experienced and had at least a tertiary award or degree and had gone through the professional qualification of at least one PAO. Results showed extensive institutional adoption of technology such that only 5 respondents worked in organisations that operated a fully manual system. It is worthy of note that many of the respondents worked in organisations that operated a full automated system. Others worked in organisations that operated both manual and automated systems. This gives insight into the paradigm shift. It is also a testament to the transformative and disruptive abilities of technology in the workplace, which has significant implications for professional accountants. In addition, it gives all reasons to believe that professional accountants have the enabling environment to use technology, although it is important to stress that other facilitating infrastructure beyond the control of employers may still be limiting factors. For the first objective, which was to identify the SoMoClo technologies used by professional accountants in Nigeria, we found that WhatsApp was the most used social media platform. This could be attributed to the fact that it is a fast and free application that runs on most mobile phones. Payment system also emerged top in the mobile application category and is attributable to financial inclusion and cashless policy drive. Smart phones using the Android operating system were the most used amongst mobile devices and Google Drive was the mostly used

232

Social Media, Mobile and Cloud Technology Use in Accounting

cloud service. The proximity of smart phone to its user has made it a first choice of device and the fact that it can perform virtually all the functions of a laptop and/or desktop PC. Android OS is the dominant OS and most laptop users work with Windows OS. It appears that older adults use social media more than the younger ones, while those with fewer years of experience use less of technology for their professional engagement. This may be attributable to their being assigned rudimentary assignments. In addition, male respondents use social media than female respondents. These intriguing results may be explained by the fascination of the older generation with the affordances of new technology, while there is documented evidence on the difference of technology use between male and female and their causes (Ahadiat, 2005; Venkatesh et al., 2000; Webb & Chaffer, 2016). The second objective was to determine the level of alignment of technology competence of Nigerian professional accountants with the IES IT professional competence requirement. The study found that Nigerian professional accountants met the IES IT requirements of knowledge-ability and understand-ability on the use of technology. This, however, must be taken with caution, given that selfreported scores were used. In a competitive labour market coupled with twists added by globalisation and the transformative and disruptive capacities of technologies, a professional accountant without modern skills is ultimately antiqued. Given this imperative to constantly learn, unlearn and relearn the use of technology, the study reviewed the technology competence of Nigerian professional accountants in line with the requirements of a global accounting education standard. It appears that the technology competence of Nigerian professional accountants is in tandem with the IES IT stipulations, which implies that professional accountants trained in Nigeria are not at disadvantage in the global market. It is, however, important to state that more advanced technologies such as big data analytics, automation, robotics, machine learning and cognitive computing were left out of the reviewed skills. The third objective to find out the relationship between the training that professional accountants have received, both academically and professionally and their technology competence, we found that Nigerian professional accountants are of the opinion that their academic and professional qualifications have been instrumental to their appreciation, adoption, competence and use of technology. It is important to state that there were differing opinions with differing degrees on the opinions. It is also important to state that professional accountants in Nigeria do not feel that higher degrees in accounting helped to build technology competence. This implies that technologies may not be extensively used in teaching and research that can elicit an appreciation amongst graduate students. There is evidence that holders of both academic degrees and professional certifications are generally users of SoMoClo technologies, albeit the use of mobile application appeared to have the lowest levels of adoption and use amongst Nigerian professional accountants. In some few instances as well the use of cloud technology was the lowest and this may be attributed to the inchoate nature of the technology in Nigeria.

Study

233

The final objective touched on the predictability of accountants’ training framework on the use of SoMoClo technologies amongst Nigerian professional accountants and the results showed significant predictability for all the SoMoClo technologies with differing degrees, howbeit not less than 80%. Conclusively, the overarching disruptive and transformative tendencies and evidences of technology are incentives for professional accountants to constantly unlearn, relearn, initiate, adopt and adjust to emerging trends in the practice of their profession.

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Further Thoughts Recommendations Based on the results of the study, the following recommendations are presented: (1) Employers should review the BYOD/BYOL policy and develop a strategic framework for its implementation. Given security issues on SoMoClo technologies, it is expected that when employees use popular platforms and devices, they are encouraged to observe basic and even advanced security tips as issued by their IT departments. (2) The low comparable number of policymakers and researchers necessitates a recommendation that the specialty fields of policy and research should intensify in pursuing increased involvement of the young and female gender. This is in line with ICAN’s ‘catch them young’ policy. This is to ensure a diversified accounting profession, which is significant for robust interfacing for enhanced development. (3) Academic institutions should stand out in the training of graduate accountants, especially with modern technologies. This is to ensure that graduate accountants not only acquire the technical skills, but are able to use modern technologies for efficiency and productive sustainability. (4) National accounting associations should emerge to foster a relationship amongst practitioners, policymakers and researchers.

Further Studies (1) There are speculations in informal settings that the protectionist walls erected by professional affiliations may crumble soon. It may be of interest for a study to ascertain the certainty of the insinuation and possibly the timeframe for that because it will have significant implications for the accounting profession and its major players such as the PAOs. (2) IPD is said to be based on international standard as signed in the Statement of Membership Obligations. It will be of interest to evaluate whether these requirements are ethically upheld and adhered to. Its quality in shaping professional competence may be of significant interest as well.

236

Further Thoughts

(3) The direct querying of issues on facilitating and enhancing technology infrastructure such as power and internet availability which are profound challenges to technology adoption and use (Sabi et al., 2016) and abound in many developing economies may be necessary to highlight its effect on adoption and use of technology. (4) The need to query technology as a catalyst for inspiring a knowledge and/or supply gap, the strategies and coping patterns of providers of accounting education and vanguards of accounting profession as well as their outcomes is also another significant research focus. (5) This book presents results of the comparison of professional accountants’ competence with the IES, but it may be necessary to do a cross-country study for developing economies on the empirical value of technology use (competent engagement). (6) An area of study that was left out is the ethical use of technology; this is therefore recommended as an area for further study.

Acknowledgements Persons Abel Akintunde Adebamiji Ayandiji Adebola Aderibigbe Akinwale Akinwunmi Augustine Imohiosen Ayoshola Ogunojo Bamidele and Bola Alaba Dauda Adebisi David Elumilade Desire Femi-Oladele Eddy Ndekwu Emmanuel Adegun Ezekiel Adeleke Ezekiel Oyerogba Halleluyah Aworinde Ibukun Okedigba Ishola Akintoye John Ayoade Johnson Laosebikan Joshua Ogunwole Lawrence Olawuyi Mofoluwake Adeyemo Moriyike Atoyebi Odunayo Olaniyi Oladipupo Ojemola Olateju Aregbesola Olatunde Wright Olatunji and Funmi Ajani Olayinka Adenikinju Olayinka Akinlo Olufolakemi Afrogha Opeoluwa Akinsanya (Nee Balogun)

Bowen Bowen Bowen Bowen Bowen Bowen

University, University, University, University, University, University,

Iwo Iwo Iwo Iwo Iwo Iwo

Bowen University, Iwo Obafemi Awolowo University, Ile-Ife

Adeleke University, Ede Adeleke University, Ede Bowen University, Iwo Bowen University, Iwo Bowen University, Iwo Bowen University, Iwo Bowen University, Iwo Bowen University, Iwo Bowen University, Iwo Bowen University, Iwo Bowen University, Iwo Bowen University, Iwo Bowen University, Iwo Bowen University, Iwo Bowen University, Iwo Peace Baptist Church, Oluponna Bowen University, Iwo Bowen University, Iwo

238

Acknowledgements

Peace Kolawole Bowen University, Iwo Rotimi and Yetunde Taiwo Obafemi Awolowo University, Ile-Ife Rufus Akomolafe Bowen University, Iwo Samuel and Florence Bakare Seun Oladele Sola and Sayo Oladele Sunday Feyisetan Sunday Olasupo Bowen University, Iwo Sunday Omojola Bowen University, Iwo Temiloluwa Akinsola Bowen University, Iwo Temitope Worimegbe Redeemer’s University, Ede Theo and Mary Aro Tolani Femi-Oladele Tolulope and Oluyomi Ola-David Wale and Bisi Adebayo Publishing Team Emerald Publishing Institutions Association of National Accountants of Nigeria Institute of Chartered Accountants of Nigeria Timothy Olagbemiro Library, Bowen University, Iwo

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Index Ableness, 92, 149, 177, 186, 187 Academic accounting education (AAE), 13–14, 90, 203 Academic qualification (AQ), 124–128, 187 Academic vanguards, 12 Accountants, 9–12, 57, 91, 233 Accountants’ training framework (ATF), 7, 12–17, 64–65, 133–152 Accounting, 6, 17–25, 24, 49, 188 academic awards and degrees, 13 definition, 23 MBA degree, 199 M.Phil./Ph.D. degree, 199 practitioners, 62 Accounting education, 1, 13–16, 37, 56, 92, 232 Accounting information system (AIS), 42 Accounting policy, 25 Accounting profession, 1, 25–27, 82, 113, 231 Accounting research, 26 African Accounting and Finance Association (AAFA), 15 Age, 114–117 American Accounting Association (AAA), 1 American Institute of Certified Public Accountants (AICPA), 1 Artificial intelligence (AI), 3, 39, 62 Audit command language (ACL), 60 Average variance extracted (AVE), 88

Bachelor of Science (B.Sc.), 13, 95, 125, 198 Bartlett’s test of sphericity, 140 Behavioural intention, 4 Binary logistic regression, 204–210, 221 BlackBerry Messenger (BBM), 45 Bookkeeping, 2, 23, 42 Bring Your Own Laptop (BYOL) approach, 44 Business-Process-as-a-Service (BPaaS), 49 Career progression, 124 Chartered accountants, 10, 13, 15, 110 Chi-square, 84, 134, 139 Cloud, 3, 48–50, 61, 150, 232 Cognitive computing (CC), 3, 39, 157, 232 Cognitive instrumental process (CIP), 53 Communication-Platform-as-a-Service (CPaaS), 49 Competence, 13, 64–65, 232 acceptable level, 2 comparison, 63–64 professional accountants, 177–187 requirement, 47 Computer-assisted auditing tools and techniques (CAATTs), 42 Confirmatory factor analysis (CFA), 88 Continuing professional development (CPD), 5, 65 Continuing Professional Education (CPE), 15

262

Index

Correlation, 62, 88, 173–177, 187, 193 Cross-tabulation technique, 66, 101, 102, 186 Data analysis techniques, 86–92 Demographic factors, 5 Designer, 3, 39, 177, 187 Determined factors, 4, 5, 64 Developing economies, 6, 16, 61, 177, 231 Diffusion of innovation (DOI), 50 Diffusion of innovation theory (DIT), 50–52, 65 Discrimination, 113 Diversity, 12, 112 DropBox, 167 Education-and-Learning-as-a-Service (ELaaS), 49 Ethics, 5, 39, 110, 231 Evaluator, 3, 91, 178, 194 Expectancy disconfirmation theory (EDT), 52 Expectancy theory of motivation (ETM), 52 Expectation gap, 30–38, 64 Expected date of delivery (EDD), 4 Experience, 5, 26, 117–124, 165 eXtensible Business Reporting Language (XBRL), 42 Facebook, 45 Financial accountability, 1 Framework, 4, 26 SoMoClo technologies, 6 WRA, 140–152 F-test, 140 Gender, 5, 11, 110–113 Google1, 45 Google classroom, 60

Google Drive, 167 Google Forms, 84, 167 Government Integrated Financial Management Information System (GIFMIS), 60 Hypothesis, 55, 186–187 IES. See International Education Standard (IES) Imo, 45 Inclusion, 6, 12, 57, 204, 231 Individual innovativeness theory (IIT), 50 Information technology (IT), 2, 40, 41, 48 Infrastructure-as-a-Service (IaaS), 49 Initial professional development (IPD), 5, 14, 82, 134 Innovation diffusion theory (IDT), 50 Instagram, 45 Institutional adoption of technology, 153–157 Integrated Payroll and Personnel Information System (IPPIS), 60 Integrated reporting (IR), 24, 40 Intention to use, 4, 58, 82, 208–210, 225–227 International Accounting Education Standards Board (IAESB), 2, 15, 27, 30, 41, 125 International Accounting Standards Board (IASB), 25 International Auditing and Assurance Standards Board (IAASB), 40 International Education Guidelines (IEGs), 30 International Education Practice Statements (IEPS), 30

Index

263

International Education Standard (IES), 2, 26–30 International Federation of Accountants (IFAC), 2, 10, 26, 63, 90 International Financial Reporting Standards (IFRS), 25 International Public Sector Accounting Standards (IPSAS), 25 International Public Sector Accounting Standards Board (IPSASB), 25 Interpretive, 3, 4, 194–202 Inter-rater reliability, 87

social media, 45–47 technology, 47–48, 160–166 WRA framework, 140, 143, 150 Model General Linear Model (GLM), 89 Legitimation code theory (LCT), 56 motivational model (MM), 54 technology acceptance model (TAM), 53 unified theory of acceptance and use of technology (UTAUT), 53–54 uses and gratifications theory (UGT), 54

Kaiser-Meyer-Olkin (KMO), 88 Knowledge, 55–56 Knowledge-ability, 178

Netflix, 157 New technology, 43, 52, 57, 65, 153, 232

Learning, 55–56, 193 Legitimate peripheral participation (LPP), 56 Legitimation code theory (LCT), 56 LinkedIn, 45, 157 Literature cloud technology, 166 discourses, 9–80 mobile technology, 160 research, 4 SoMoClo technologies, 61, 81 technology, 2 Lotus Notes, 46

One Drive, 167

Machine learning, 39 Manager, 39, 60, 84, 182, 187, 193, 194 Massification, 13 McDonaldization, 13 Microsoft Office Excel, 84 Microsoft’ s Yammer/Outlook, 45–46 Mobile applications, 83, 156 cloud technology, 48–50 devices, 83, 156 payment systems, 48

Pan African Federation of Accountants (PAFA), 15 Pathways Commission, 1, 1878 Perceived ease of use (PEOU), 5, 53, 94 Perceived use (PU), 53 Perceived usefulness (PU), 5, 53 Perceive, learn, setting and use theory (PLESUT), 57, 59, 88, 89, 95 Perception (PCT), 140, 202 Phinnx, 60 Pinterest, 45 Platform-as-a-Service (PaaS), 49 Policymaking boards, 109 Policy specialty, 109 Practical experience, 5, 14, 38, 82, 95, 109 Praktik, 59 Predictive, 3, 4, 16, 87, 88, 228 Preference, 14, 86, 89, 97, 101–102, 117, 160 Print-as-a-Service (PrtaaS), 49 Process automation, 153

264

Index

Profession, 9, 11–16, 24–28, 37, 95, 112 Professional accounting education, 14–16, 64, 90, 95, 203 Professional accounting organisations (PAOs), 18 Professional competence, 12, 38–40, 45, 187, 232 Professional qualification (PQ), 128–228, 187 Professional values, 5, 33, 35, 39, 95 Public Interest Oversight Board (PIOB), 27 Reciprocity, 173–177 Reliability, 87 Research design, 83–85 Responses, 1, 43, 84, 95–101, 178, 231 Second machine age, 39 Self-employment, 113 Skill deficiency, 36 Skype, 45, 157 Snapchat, 45, 157 Social influence process (SIP), 53 Social media cloud technology, 48–50 definition, 45–47 mobile technology, 47–48 research, 5–7 SoMoClo technologies, 61, 86 technology uses, 65 WRA framework, 149 Social media, Mobile and Cloud (SoMoClo), 3–7, 43–45, 60–63, 149, 173–174, 200–203 Software-as-a-Service (SaaS), 49 Special technology training (STT), 133, 202 Statement of Membership Obligations (SMOs), 30 Statistical Package for the Social Sciences (SPSS), 84

Structural equation modelling (SEM), 89 Subject matter expert (SME), 23 Technology accounting education delivery, 64 definition, 3 factors influencing, 65–80 institutional adoption, 153 professional accountants, 2, 5, 6, 7, 14, 37, 81 research, 83 WRA, 140–152 Technology acceptance model (TAM), 53 Technology Task Force (TTF), 1, 82 Tertiary institutions, 14, 36 Theory diffusion of innovation theory (DIT), 50–52 expectancy disconfirmation theory (EDT), 52 expectancy theory of motivation (ETM), 52 learning and knowledge, 55–56 theoretical considerations, 56–59 unified theory of acceptance and use of technology (UTAUT), 53–54 uses and gratifications theory (UGT), 54 Theory of reasoned action (TRA), 53 Tripartite accounting, 25, 61, 82, 92, 95, 102, 109 Twitter, 45, 157 Unified theory of acceptance and use of technology (UTAUT), 53–54 Uses conceptual framework for analysis, 94

Index IT, 42 social media, 46 SoMoClo technologies, 4, 6 technological applications, 2 value-analyses, 4 WRA, 152 Uses and gratifications theory (UGT), 54 Value-analyses, 4, 194–202 Variables, 7, 52, 86, 187, 202, 204, 211, 221

265

WhatsApp, 45, 157 Willingness, Readiness and Ableness (WRA), 86, 92, 93, 140–152, 202, 204, 221 Yahoo Messenger, 45 YouTube, 45, 157

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