Towards Safer Global Food Supply Chains: A Comparative Analysis of Regulatory Requirements 3030933555, 9783030933555

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Towards Safer Global Food Supply Chains A Comparative Analysis of Regulatory Requirements

Dong Li

Towards Safer Global Food Supply Chains

Tram T. B. Nguyen · Dong Li

Towards Safer Global Food Supply Chains A Comparative Analysis of Regulatory Requirements

Tram T. B. Nguyen Faculty of Business Administration Ho Chi Minh City Open University Ho Chi Minh City, Vietnam

Dong Li Management School University of Liverpool Liverpool, UK

ISBN 978-3-030-93355-5 ISBN 978-3-030-93356-2 (eBook) https://doi.org/10.1007/978-3-030-93356-2 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Cover illustration: © Melisa Hasan This Palgrave Pivot imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface and Acknowledgments

Implementing a food safety management system (FSMS) is a regulatory requirement for every food firm in the global food supply chain. At any scale, it could be influenced by many factors since the global food supply chains consist of a large number of stakeholders and are involved with an enormous variety of structures, logistics that will undoubtedly change rapidly, scale-up and diversify continuously. The book contains five chapters that aim to give a systematic review of critical success factors (CSF) for food safety management in global supply chains to understand what we know about CSF. From these research gaps, we propose a model to empirical test the proposed hypotheses on critical success factors and their relationships with FSMS. Furthermore, we also explore the impact of supplier selection and supply chain relationships on food safety management in global supply chains to identify Best Practice among the surveyed firms. The book points out that apart from critical impacts of internal factors, such as management responsibility, human resources, and organisational resources on FSMS implementation, collaborative, and supportive supply chains as well as food safety governance play significant roles in food production in emerging economies, namely China and Vietnam. The evidence provided in these studies of the book facilitates food firms’ managers to target critical resources and supports, and identify effective policies, practices, and procedures to improve FSMS implementation leading to safer global food supply chains. The research findings in this v

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PREFACE AND ACKNOWLEDGMENTS

book propose the use of CSFs as a more proactive approach to identifying the mechanism to enable continuous improvement opportunities for the current FSMS according to each firm’s status, particularly for SMEs with limited resources. In addition, the book identifies Best Practice among the studied companies to provide several suggestions for other firms to improve their current practices. For instance, food processing firms should enhance collaboration with their stakeholders in global supply chains since this significantly contributes to FSMS implementation. Likewise, they should follow food safety criteria when selecting suppliers and develop a better relationship with their stakeholders in the supply chains on food safety issues. Commitment and trust should be gained among the stakeholders in food supply chains since they are highly correlated to FSMS implementation. This book also emphasises the critical roles of other parties such as government and authorities and business associations in supporting and governing food firms’ FSMS. We would like to express thankful gratitude to the Vietnamese Government and Newton Fund of British Council for their generous sponsorship for PhD study of the first author. Equally important, the financial support from Project 777742 or ‘GOLF’ (EC H2020-MSCA-RISE2017) provides the authors wonderful opportunities to do research and data collection in UK, China, and Vietnam. Furthermore, our special thanks to the colleagues from University of Liverpool Management School in UK, Faculty of Business Administration at Ho Chi Minh City Open University as well as Beijing Jiaotong University and Zhejiang University in China for supporting us to collect the empirical data. The colleagues and managers who work in project-partner universities and companies for their constructive comments and support. Additionally, the food companies’ managers of the surveyed firms for their valuable opinions and time participated in this book. Ho Chi Minh City, Vietnam Liverpool, UK

Tram T. B. Nguyen Dong Li

Contents

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2

Introducing to Food Safety Management in Global Supply Chains 1.1 Food Safety Concerns in Food Industry 1.2 Food Safety Management System 1.3 Managerial Requirements for FSMS in the Context of Global Supply Chains 1.3.1 Regulations and Standards Compliance 1.3.2 The Role of Risk Assessment 1.3.3 None of FSMS Is Perfect 1.4 Critical Success Factors for FSMS 1.5 Structure of the Book References

5 5 6 7 7 9 10

Critical Success Factors for Food Safety Management System 2.1 Introduction 2.2 CSF Theory in FSMS 2.3 What Do We Know About CSF for FSMS? 2.3.1 SLR Methodology 2.3.2 Question Formulation and Locating Studies 2.3.3 Search Strategy 2.3.4 Study Selection and Evaluation 2.3.5 Analysis and Synthesis 2.4 CSFs for FSMS

15 15 16 17 18 19 20 20 22 24

1 2 3

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CONTENTS

2.4.1 Organisational Level 2.4.2 Market Level 2.4.3 Food Safety Governance 2.5 Research Gaps 2.6 Conclusion References

24 25 26 29 32 32

Empirical Evidence on Critical Success Factor from Multi-Level Environments and Their Relationships with Food Safety Management System 3.1 Introduction 3.2 The Research Frameworks and Hypotheses Development 3.2.1 Organisational Factors 3.2.2 Market-Related Factors 3.2.3 Food-Safety Governance 3.2.4 FSMS Implementation 3.3 Research Instruments 3.4 Research Methodology 3.4.1 Sample design 3.4.2 Data Collection 3.4.3 Construction of the Instruments and Measures 3.4.4 Data Preparation 3.4.5 Method of Data Analysis 3.5 Data Analysis 3.5.1 Exploratory Factor Analysis 3.5.2 Confirmation Factor Analysis (CFA) 3.6 Discussion 3.7 Conclusion References

37 38 38 39 40 42 43 46 46 46 53 54 54 55 56 56 60 60 64 66

Practices of Supplier Selection and Collaborative Supply Chain Relationships for Food Safety Management 4.1 Introduction 4.2 Theoretical Framework 4.2.1 Supplier Selection in Food Safety Management 4.2.2 The Impact of Supply Chain Relationship on FSMS 4.3 Cluster Analysis 4.3.1 Identifying Cluster Solution

71 71 73 73 74 75 76

CONTENTS

4.4

Best Practice Identification 4.4.1 Profiling the Identified Groups 4.4.2 Examining the CSFs of Each Group 4.5 Exploring the Aspects of Supplier Selection and SC Relationships 4.6 Discussion 4.6.1 Criteria of Supplier Selection 4.6.2 The SC Relationship 4.7 Conclusion References 5

What does It Take to Achieve Safer Global Food Supply Chains? 5.1 Introduction 5.2 Understanding the Critical Food Safety Management Practice 5.2.1 CSFs at the Organisation Level 5.2.2 CSFs at the Market Level 5.2.3 CSFs at the Broad Environment Level 5.3 Understanding Impacts of Business Relationships in Global Supply Chains on Food Safety Management System implementation 5.3.1 Whether and to What Extent Do CSFs Influence FSMS of Firms in the Context of Global Supply Chains? 5.3.2 Whether the Firms That Perform Better FSMS Implementation Pay More Attention to Safety Criteria? 5.3.3 Whether the Firms That Perform Better FSMS Implementation Are in Better Supply Chain Relationships Than Other Firms? 5.4 Implications from the Research 5.4.1 Theoretical Implications 5.4.2 Practical Implications 5.5 Future Research Directions References

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79 81 83 89 93 95 97 99 100 103 103 104 104 105 105

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Appendix

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Index

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List of Figures

Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig.

2.1 2.2 2.3 2.4 2.5 2.6 3.1 3.2 4.1 4.2 4.3

Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig.

4.4 4.5 4.6 4.7 4.8 4.9 4.10 4.11 4.12

Systematic review methodology Network of researchers in the searching field Total publication by year of the selected papers Source titles of the reviewed papers VOS coupling structure The framework of literature review classification The research model The structural model Dendrogram using Ward Linkage Comparing the FSMS implementation between clusters Comparing the means of HACCP, PRP, OA between clusters Internal CSFs among the groups Food-safety governance Support Level of collaboration in the supply chain SC relationship among the groups The overall mean score of all indicators Pareto chart of supplier selecting criteria The different selecting criteria of five groups SC relationships among the groups

18 20 21 22 22 23 39 63 77 80 81 87 87 88 89 93 94 97 98 98

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List of Tables

Table Table Table Table

1.1 1.2 2.1 3.1

Table Table Table Table Table

3.2 3.3 3.4 3.5 3.6

Table Table Table Table Table Table

3.7 4.1 4.2 4.3 4.4 4.5

Table 4.6 Table Table Table Table Table

4.7 4.8 4.9 4.10 4.11

Definitions of FSMS Key common requirement for food safety standards Existing CSFs in the literature Construct and measurement items and support references Demographic information of the surveyed companies Exploratory factor analysis Reliability checks for FSMS implementation Validity check Model fit indices for CSFs, measurement, and structural models Hypotheses testing results Criteria of supplier selection in the literature Research construct Cluster membership distribution Agglomeration schedule Comparing the number of cases in each cluster in two steps Univariate F -statistics results assessing cluster solution criterion validity Multivariate F results for profile variables Cross-classifications for firm’s characteristics MANOVA results for all CSF indicators Correlations Multivariate F results

3 4 27 47 54 57 58 59 61 62 73 75 78 78 79 80 82 83 84 90 91

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LIST OF TABLES

Table 4.12 Table 4.13

The differences between the groups in supplier selection Internal CSFs of five random firms in the research sample

92 96

CHAPTER 1

Introducing to Food Safety Management in Global Supply Chains

Abstract The first chapter states a general overview of the book such as the background, objectives, and structure. It briefly outlines the incentives for the book. The chapter describes the main value of the book in reducing the complexities of decision-making and managing FSMS. Compared to other studies of CSFs for FSMS, this book not only applies CSF approach proactively to identify the enabling mechanism for continuous improvement of the FSMS implementation but also provides dynamic roadmaps based on the status of each firm’s key FSMS characteristics. The enhanced understanding of the best practice of FSMS implementation would help to mitigate failure risk and lead to safer food supply chains. The approaches presented in the book can be an easy-touse and practical method for food managers in their routine operation management. Keywords Introduction · Critical success factors · Food safety management system

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 T. T. B. Nguyen and D. Li, Towards Safer Global Food Supply Chains, https://doi.org/10.1007/978-3-030-93356-2_1

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1.1

Food Safety Concerns in Food Industry

Nowadays, food on our tables comes from every corner of the globe instead of predominantly regional productions as the latest trending to take advantage of lower costs and avoid insufficient local supplies. Hence, food supply chains move beyond regional to include global participation to reduce costs and generate better revenues in all nodes of the chain. Under the pressures for competitive advantages in the industry, food supply chains are typically associated with many issues such as extra costs, high level of vulnerability and supply risks, risks in global financing and funds transfer as well as longer lead times (Marucheck et al., 2011; Roth et al., 2008). In addition, the recent food safety incidents have raised public awareness of the ubiquity of food safety, namely dioxins in the Republic of Ireland (Bánáti, 2011), E.coli contamination of bean sprouts in Germany and France (Soon et al., 2013), Tesco horse meat scandals in the UK (Sarpong, 2014), Salmonella-contaminated peanuts in the U.S (Leighton, 2016). As a result, food is required to be safe for the consumer at the point of consumption (ISO, 2005). Food safety is the most crucial component of food quality besides sensory properties, shelf-life time, reliability and convenience (Aramyan et al., 2007). It is one of the most significant challenges in the context of global food supply chains for the following reasons. First, most of the food products are natural, perishable and could be harmful to consumers if they have not been managed in a timely and safe manner. Second, food supply networks are global, complicated, and highly interconnected, leading to higher risk exposure (Trienekens & Zuurbier, 2008). Comparatively, the globalisation of the food industry as other industries has created various risks and vulnerabilities when products are exposed to moving along the supply chain from sourcing to manufacturing, transportation, distribution and final sale to reach the consumer (Marucheck et al., 2011). Third, compared to other products, food and beverage products are more at risk of intentional or unintentional adulteration (Whipple et al., 2009). Last but not least, due to the difficulty associated with determining safety risks before consumption, end-product testing is not an efficient approach to ensure food safety in production along with the potentially devastating effects of food safety incidents on human life (Marucheck et al., 2011). For these reasons, whether food enterprises realise both industrial or economic benefits or not, breaching food safety compliance means suffering massive consequences.

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Food Safety Management System

According to CAC (2009), people have the right to expect the food they eat to be safe and suitable for consumption. Hence, all the sectors in the food supply chains have a share responsibility to guarantee and tackle food safety risks (FAO/WHO, 2001). The food industry is responsible for the establishment of an effective and efficient food safety management system (FSMS) as regulatory requirement to ensure that foods present minimal risk to the consumer in global food chains. There are many definitions in the literature that clarify the characteristics and key elements of FSMS, as illustrated in Table 1.1. No matter what differences between firms within supply chains are, the ultimate purpose of FSMS is to ensure that foods are safe concerning foodborne hazards at the time of human consumption. FSMS are included both regulatory demands and voluntary standards, such as requirement in the Regulation (CE) 852/2004, CAC (2009), and international standards, namely the British Retail Consortium’s global food safety standard (BRC), the International Food Standard (IFS), the Safe Quality Food (SQF) 2000 Level 2, and the ISO 22000:2005. The international standards common among food producers in global supply chains are summarised and compared by Mensah and Julien (2011) in Table 1.2. They are: Table 1.1 Definitions of FSMS References

Definitions

ISO (2005)

A combination of the recognised key elements to ensure food safety along the food chain: interactive communication, system management, prerequisite programmes, HACCP principles A system includes control activities to keep product and process conditions within acceptable safety limits and assurance activities to set systems requirements, evaluate system performance, and organise necessary changes A group of interacting or interdependent elements forming a network to ensure that food presents minimal risk to consumers A highly custom-made system results from the implementation of multiple quality assurance and legal requirements into each company’s production, organisation and environment

Luning et al. (2008)

Scott and Chen (2010)

Jacxsens et al. (2011)

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Table 1.2 Key common requirement for food safety standards (Adopted from Mensah & Julien, 2011) FSMS elements

BRC

HACCP

ISO 22000

SQF

IFS

Management system Prerequisite programs (PRP) HACCP Validation and verification Emergency preparedness/crisis management Quality management

✔ ✔ ✔ ✔ ✔ ✔

✔ ✔ ✔ ✔

✔ ✔ ✔ ✔ ✔

✔ ✔ ✔ ✔

✔ ✔ ✔ ✔

✔

✔

• ISO 22000:2005 is an international standard containing requirements for the food safety management systems relating to each stage of the whole food supply chain (ISO, 2005). • Global Standard for Food Safety (BRC) are the safety, quality and operational criteria required within a food manufacturing organisation to meet legal obligations concerning compliance and protection of the consumer (BRC, 2015) • Hazard Analysis and Critical Control Points (HACCP) is a system for identifying, evaluating and controlling hazards that are significant for food safety (CAC, 2009). • International Food Standard (IFS) is a quality and food safety standard as a consistent approach harmonised both elements for retailers and wholesalers of branded food products to assess suppliers’ food safety and quality systems (IFS, 2014). • The SQF Code is a HACCP-based supplier assurance code for food industry from farm to fork (SQFI, 2014). Many studies have indicated the installation of these requirements into a company forms an interacting and dynamic system that is highly customised based on differently organisation’s characteristics due to the different processes (i.e., slaughtering, butcher shops) and type of companies (i.e., industrial operations versus SMEs) along the food chains. There are various levels of FSMS from the perspective of the government to the industrial level. Scott and Chen (2010) state that there could be a horizontal FSMS that extends from farm to fork. Still, in practice, food safety efforts are segmented into multiple systems which are tailored to specific types of operations of each sector in food industry, such as farmers,

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slaughterers, manufacturers, retailers, or restaurants. Hence, the success of FSMS in preventing foodborne hazards depends on its correct implementation and application (Fotopoulos et al., 2009; Kok, 2009). Most of the standards suggest that FSMS could be applicable to any organisation involved in any aspect of the food chain as long as they want to implement systems consistently to provide safe products (ISO, 2005). Nevertheless, the success of FSMS implementation cannot be assured, leading to outbreaks of food safety incidents. In order to understand several managerial requirements for FSMS in the context of global supply chains, insights into these requirements will be discussed in the next section to clarify what we should keep in mind when we manage food safety in food businesses.

1.3 Managerial Requirements for FSMS in the Context of Global Supply Chains 1.3.1

Regulations and Standards Compliance

Addressing the vital role of FSMS in food industry, regulations and standards compliance is the essential element of all FSMS. This is the result of extensive global sourcing of food products accompanied by multiple stakeholders and activities along with the chain, for the reason that the whole supply chain includes the series of processes, operations, and entities that help to take the food from its raw material to customers’ plates. If there is one node of these series breached or contaminated, it can result in unsafe food hazardous to human health. In other words, the safety of the whole food chain is the safety of each link. To assure food safety regardless of stage in food supply chains, there is a significant evolution toward more demanding requirements and more stringent food-safety governance thanks to advances in hazard detection and epidemiology since the 1990s. Hence, a substantial increase in the number of standards seeks to enhance food safety, namely HACCP, the BRC, IFS, SQF, and the ISO 22000:2005, which become familiar to customers. Previously, these standards were encouraged as a voluntary application for food operators. In the beginning, these stringent standards caused a lot of difficulties for food producers, especially SMEs and family businesses in developing countries (e.g. Henson & Humphrey, 2010; Henson & Reardon, 2005; Schuster & Maertens, 2013). Currently, the global recognition of these standards is performing the task of a uniform framework in requirements,

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mutual acceptance of audit procedures and audits, as well as reassurance in the capability and competence of suppliers (Mensah & Julien, 2011). Subsequently, they become commonly mandatory in most countries, such as the case of HACCP principles. 1.3.2

The Role of Risk Assessment

Scientific evidence and assessment of the risk are the roots of food safety guarantees. Also, these risk assessments should be quantitative whenever feasible (FAO/WHO, 1997) because end-product testing is not an efficient approach to ensure food safety in food production. However, it is challenging to determine food safety risks before consumption associated with the potentially devastating effects of food safety incidents on human health. Consequently, the risk-based preventive approach, which specifies the necessary minimum requirements acceptable for food safety, is widely implied in FSMS. In particular, food safety incidents are proactively prevented from occurring due to various types of hazards in any food chain stages by food manufacturers. They take the necessary actions to manage and prioritise resources and activities on the risks deemed to have the most significant potential impact. This preventive method limits the possibility of unsafe end-products instead of passively correcting activities to incidents. The existing literature on risk assessment is extensive and focuses particularly on risk assessment methods to manage food safety. For instance, the study of Gkogka et al. (2013) shows two different risk assessments called ‘top-down’ or ‘bottom-up’ approaches to derive the possible appropriate level of protection (ALOP) for Salmonella in chicken meat in Netherlands. The ‘Top-down’ approach is based on epidemiological data, and the second is the ‘bottom-up’ approach, based on food supply chain data. Additionally, the concepts of fuzzy set theory and analytical hierarchy process are prevalent in proposing integrated risk assessment approaches to perform structured analysis of aggregative food safety risk in the food supply chain, such as the works of Wang et al. (2012) and Chan and Wang (2013). Their methods are practical tools in providing structured risk assessment and establishing aggregative food safety risk indicators. To this end, these methods can be effectively employed in incorporating the safety objectives into the process of operations planning in food production.

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None of FSMS Is Perfect

It is evident that none of FSMS is perfect no matter how stringent of that system through frequently certificated, well audited or inspected in the past. The audit is a visit to the facility and review of records, which is argued that can only confirm that the procedures and processes of the manufacturing system implemented as planned (Cormier et al., 2007). Likewise, the (third-party) audits and inspections receive the same criticisms because they are not enough to guarantee food safety. In reality, several foodborne illness outbreaks from commercial food operators had high scores of audits or inspections. The main reason is that they reflect only a snapshot in time and cannot guarantee the firm’s future performance (Powell et al., 2013). Hence, the existing body of research on FSMS suggests that fundamentally fulfilling the minimal requirements of regulations and standards is insufficient (Kafetzopoulos et al., 2013; Kok, 2009). Assuredly, strengthening FSMS and ongoing compliance with regulations and standards become essential for food companies to sustain operational and business objectives. A continuous improvement approach is inevitable in food industry as FSMS is an integrated process management system. It includes various procedures based on Deming’s cycle from the planning of the steps (Plan), day-to-day implementation operations (Do), verification (Check) of PRPs, control measures and system performance, and improvement (Act) by reviewing the overall system performance (ISO, 2005). Undoubtedly, FSMS is underpinned by the continual improvement of an integrative management philosophy that means a routine activity to increase the ability to fulfil requirements. In detail, this paradigm encourages firms to seek the continual improvement of machinery, materials, labour utilisation, product quality and safety, and production methods through the application of suggestions and ideas of team members. In simple words, managers should continually seek to improve the effectiveness and efficiency of the organisation’s processes rather than wait for a problem to reveal opportunities for improvement.

1.4

Critical Success Factors for FSMS

Given the importance of maintaining a good practice of FSMS implementation, the identification of enabling a mechanism for the success of FSMS implementation is critical to reduce potential failures and respond

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to the need for continuous improvement. A growing body of literature recognises the roles of the most important factors that lead to the achievement of desired FSMS (Kafetzopoulos & Gotzamani, 2014; Kirezieva, Luning, et al., 2015; Mensah & Julien, 2011). At any scale (regional, national, local, and factory), implementing FSMS could be influenced by many factors (Kirezieva et al., 2013; Kirezieva, Luning, et al., 2015). Many researchers suggest that some factors are more critical and could contribute to the system success more than others (Kafetzopoulos & Gotzamani, 2014; Kirezieva, Jacxsens, et al., 2015). Historically, the concept of ‘critical success factor’ (CSF) was first introduced by Daniel (1961) and has been renewed by John Rockart as the limited number of areas in which results, if they are satisfactory, will ensure successful competitive performance for the organisation (Rockart, 1979). The universally accepted definition of CSFs was given by Boynton and Zmud (1984) as those few things that must go well to ensure success for a manager or an organisation. Therefore, those managerial or enterprise areas must be given special and continual attention to achieve high performance. The theory of CSF has been widely used to enable the organisation to focus on the most important factors that lead to achieving their desired goals (Bai & Sarkis, 2013). Some studies have shown the application of the CSF theory in different areas, including both supply chain management (Bai & Sarkis, 2013; Dinter, 2013; Dora et al., 2021; Grimm et al., 2014; Netland, 2016; Shankar et al., 2018) and food quality management, such as Fotopoulos et al. (2009), van Asselt et al. (2010), Kafetzopoulos and Gotzamani (2014) and Habibah Abdul Talib et al. (2014). In these studies, the application of CSF theory assistances managers in reducing the complexity of food supply chains and quality management by defining and recognising critical points to improve their expected goals, such as lean implementation, sustainability supply chain, food quality and safety. Up to now, far too little attention has been directly paid to the need for a mechanism enabling successful FSMS implementation to assist food firms in recognising and understanding their critical points and consequently contributes to guaranteeing and improving food safety. For the reason that it is difficult to consider all factors equally important contributing to the system success that requires to be enhanced by firms, particularly for SMEs with finite resources. Focusing on the wrong CSFs or even not knowing their existence influences FSMS implementation and hampers businesses to make more profit (Kafetzopoulos & Gotzamani,

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2014). Some former studies reveal that CSFs for FSMS are considered precursors to the facilitation of decision-making and managing at a variety of levels by food firm’s managers. An exemplar of using leafy green production in three areas of Europe as a case study, Kirezieva, Jacxsens, et al. (2015) specifies the feasible impact of many factors from three elementary dimensions of these environments. The first is the organisation consisting of sufficient resources in each firm. The second is the market, where the organisation has an interactive relationship with others within the food chain. The last is the ‘broad context’ as defined in the research of Kirezieva, Jacxsens, et al. (2015) that could influence FSMS performance, including food-safety governance, agro-climatic (for the case of leafy green) and public policy environment, especially in the context of global supply chains. Nonetheless, researchers exploring CFSs in FSMS implementation have been dealing with some restrictions on confirmation of CSFs’ existence and also concentrating solely on one level in each study (Fotopoulos et al., 2009, 2011; Kafetzopoulos & Gotzamani, 2014; Kataike et al., 2019; van Asselt et al., 2010). In the context of the global food supply chains, food firms cannot operate on their own. On the contrary, they need to co-operate with suppliers, service providers, certificate bodies, authorities, etc. CSFs from the level of the organisation receive most of the researchers’ attention. In contrast, those from the broader levels, such as the level of market or governance, which affect food firms in terms of how they comply, collaborate, support, interact to ensure food safety, remains unknown. Therefore, one level is not sufficient to understand how CSFs from these levels impact on firm’s FSMS implementation.

1.5

Structure of the Book

Despite the increasing need for a food safety management system (FSMS) success in the food industry, there remains several gaps and fruitful research directions in identifying CSFs and their relationships with FSMS. These findings investigate the feasible use of the CSF approach to identify improvement opportunities for FSMS implementation. The book is the response to the need for strengthening FSMS in the food industry. In particular, we aim to give a systematic review of the literature in CSFs for FSMS in global supply chains to identify research gaps (Chapter 2). Based on identified research gaps in Chapter 2, the quantitative study of the book establishes a model for detecting factors that are most critical

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to FSMS implementation and their relationships among more than 300 food manufacturers and exporters in these two Asian developing countries (Chapter 3). In Chapter 4, a comparative analysis among studied firms is closely explored to examine the differences between the groups with better FSMS implementation and their counterparts. In detail, Best Practice group of the studied companies are identified regarding their CSFs, supplier selection criteria and supply chain relationships based on clustering analysis to inform and suggest potential improvement areas for other groups. Finally, the summary of the key points on CSFs, the relationship between CSFs and FSMS performance, and the role of supply chain relationships in managing and improving FSMS are discussed in Chapter 5. This final chapter discusses the book’s contributions and several practical recommendations for researchers and practitioners to enhance FSMS in global food supply chains. Altogether, this book contains the combination of various research methods to conduct a systematic review with bibliometric analysis and several quantitative techniques, including exploratory and confirmation factors analysis, structural equation modelling and clustering analysis. The novelty of this book findings lies in the fact that they help reduce the complexities of decision-making and managing FSMS to facilitate food firms’ managers in actively seeking improvement opportunities for FSMS. Compared to other studies of CSFs for FSMS, the book not only applies CSFs as a more proactive approach to identify the mechanism enabling continuous improvement for the FSMS implementation but also provide dynamic suggestions based on the status of each firm’s FSMS, which is particularly helpful for SMEs with finite resources. Moreover, this new understanding should help prevent possible failures of FSMS towards safer food supply chains by proposing a self-assess of FSMS implementation as an easy-to-use and practical method for food managers to use daily.

References Aramyan, L. H., Oude Lansink, A. G. J. M., van der Vorst, J. G. A. J., & van Kooten, O. (2007). Performance measurement in agri-food supply chains: A case study. Supply Chain Management: An International Journal, 12(4), 304–315. Bai, C., & Sarkis, J. (2013). A grey-based DEMATEL model for evaluating business process management critical success factors. International Journal of Production Economics, 146(1), 281–292.

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Bánáti, D. (2011). Consumer response to food scandals and scares. Trends in Food Science & Technology, 22(2–3), 56–60. Boynton, A. C., & Zmud, R. W. (1984). An assessment of critical success factors. Sloan Management Review, 25(4), 17–27. BRC. (2015). Global Standard for Food Safety Issue 7. CAC. (2009). Food hygiene: Basic texts, food and agriculture organization of the United Nations (4th ed.). World Health Organization. Chan, H. K., & Wang, X. (2013). Fuzzy extent analysis for food risk assessment. In Fuzzy hierarchical model for risk assessment (pp. 89–114). Springer. Cormier, R. J., Mallet, M., Chiasson, S., Magnússon, H., & Valdimarsson, G. (2007). Effectiveness and performance of HACCP-based programs. Food Control, 18(6), 665–671. Daniel, D. R. (1961). Management information crisis. Harvard Business Review, 39(5), 111–121. Dinter, B. (2013). Success factors for information logistics strategy—An empirical investigation. Decision Support Systems, 54(3), 1207–1218. Dora, M., Kumar, A., Mangla, S. K., Pant, A., & Kamal, M. M. (2021). Critical success factors influencing artificial intelligence adoption in food supply chains. International Journal of Production Research, 1–20. FAO/WHO. (1997). Risk management and food safety (FAO Food and Nutrition Paper). FAO/WHO. (2001). Assuring food safety and quality: Guidlines for strengthening national food control systems. Joint FAO/WHO Publication (pp. 1–73). Fotopoulos, C., Kafetzopoulos, D., & Gotzamani, K. (2011). Critical factors for effective implementation of the HACCP system: A Pareto analysis. British Food Journal, 113(5), 578–597. Fotopoulos, C. V., Kafetzopoulos, D. P., & Psomas, E. L. (2009). Assessing the critical factors and their impact on the effective implementation of a food safety management system. International Journal of Quality & Reliability Management, 26(9), 894–910. Gkogka, E., Reij, M. W., Gorris, L. G. M., & Zwietering, M. H. (2013). Risk assessment strategies as a tool in the application of the Appropriate Level of Protection (ALOP) and Food Safety Objective (FSO) by risk managers. International Journal of Food Microbiology, 167 (1), 8–28. Grimm, J. H., Hofstetter, J. S., & Sarkis, J. (2014). Critical factors for sub-supplier management: A sustainable food supply chains perspective. International Journal of Production Economics, 152, 159–173. Habibah Abdul Talib, H., Anuar Mohd Ali, K., & Idris, F. (2014). Critical success factors of quality management practices among SMEs in the food processing industry in Malaysia. Journal of Small Business and Enterprise Development , 21(1), 152–176.

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Henson, S., & Humphrey, J. (2010). Understanding the complexities of private standards in global agri-food chains as they impact developing countries. Journal of Development Studies, 46(9), 1628–1646. Henson, S., & Reardon, T. (2005). Private agri-food standards: Implications for food policy and the agri-food system. Food Policy. IFS. (2014). IFS Food Standard for auditing quality and food safety of food products. ISO. (2005). ISO 22000:2005 Food safety management systems—Requirements for any organization in the food chain. https://www.iso.org/obp/ui/#iso:std:iso: 22000:ed-1:v1:en Jacxsens, L., Luning, P. A., Marcelis, W. J., van Boekel, T., Rovira, J., Oses, S., Kousta, M., Drosinos, E. H., Jasson, V. & Uyttendaele, M. (2011). Tools for the performance assessment and improvement of food safety management systems. Trends in Food Science and Technology, 22(Suppl. 1), S80–S89. Kafetzopoulos, D. P., & Gotzamani, K. D. (2014). Critical factors, food quality management and organizational performance. Food Control , 40(1), 1–11. Kafetzopoulos, D. P., Psomas, E. L., & Kafetzopoulos, P. D. (2013). Measuring the effectiveness of the HACCP food safety management system. Food Control , 33(2), 505–513. Kataike, J., Aramyan, L. H., Schmidt, O., Molnár, A., & Gellynck, X. (2019). Measuring chain performance beyond supplier–buyer relationships in agrifood chains. Supply Chain Management: An International Journal, 24(4), 484–497. Kirezieva, K., Jacxsens, L., Hagelaar, G. J. L. F., van Boekel, M. A. J. S., Uyttendaele, M., & Luning, P. A. (2015). Exploring the influence of context on food safety management: Case studies of leafy greens production in Europe. Food Policy, 51, 158–170. Kirezieva, K., Jacxsens, L., Uyttendaele, M., Van Boekel, M. A. J. S., & Luning, P. A. (2013). Assessment of food safety management systems in the global fresh produce chain. Food Research International , 52(1), 230–242. Kirezieva, K., Luning, P. A., Jacxsens, L., Allende, A., Johannessen, G. S., Tondo, E. C., Rajkovic, A., Uyttendaele, M., & van Boekel, M. A. J. S. (2015). Factors affecting the status of food safety management systems in the global fresh produce chain. Food Control, 52, 85–97. Kok, M. S. (2009). Application of food safety management systems (ISO 22000/HACCP) in the Turkish poultry industry: A comparison based on enterprise size. Journal of Food Protection, 72(10), 2221–2225. Leighton, P. (2016). Mass salmonella poisoning by the peanut corporation of America: State-corporate crime involving food safety. Critical Criminology, 24(1), 75–91. Luning, P. A., Bango, L., Kussaga, J., Rovira, J., & Marcelis, W. J. (2008). Comprehensive analysis and differentiated assessment of food safety control

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systems: A diagnostic instrument. Trends in Food Science and Technology, 19(10), 522–534. Marucheck, A., Greis, N., Mena, C., & Cai, L. (2011). Product safety and security in the global supply chain: Issues, challenges and research opportunities. Journal of Operations Management , 29(7–8), 707–720. Mensah, L. D., & Julien, D. (2011). Implementation of food safety management systems in the UK. Food Control , 22(8), 1216–1225. Netland, T. H. (2016). Critical success factors for implementing lean production: The effect of contingencies. International Journal of Production Research, 54(8), 2433–2448. Powell, D. A., Erdozain, S., Dodd, C., Costa, R., Morley, K., & Chapman, B. J. (2013). Audits and inspections are never enough: A critique to enhance food safety. Food Control, 30(2), 686–691. Rockart, J. F. (1979). Chief executives define their own data needs. Harvard Business Review. https://doi.org/Article Roth, A. V., Tsay, A. A., Pullman, M. E., & Gray, J. V. (2008). Unraveling the food supply chain: Strategic insights from China and the 2007 recalls. The Journal of Supply Chain Management, 44(1), 22–39. Sarpong, S. (2014). Traceability and supply chain complexity: Confronting the issues and concerns. European Business Review, 26(3), 271–284. Schuster, M., & Maertens, M. (2013). Do private standards create exclusive supply chains? New evidence from the Peruvian asparagus export sector. Food Policy, 43, 291–305. Scott, V. N., & Chen, Y. (2010). Food safety management systems. In V. K. Juneja & J. N. Sofos (Eds.), Pathogens and toxins in foods: Challenges and interventions (pp. 478–492). ASM Press. Shankar, R., Gupta, R., & Pathak, D. K. (2018). Modeling critical success factors of traceability for food logistics system. Transportation Research Part E: Logistics and Transportation Review. https://doi.org/10.1016/j.tre.2018. 03.006 Soon, J. M., Seaman, P., & Baines, R. N. (2013). Escherichia coli O104:H4 outbreak from sprouted seeds. International Journal of Hygiene and Environmental Health, 216(3), 346–354. SQFI. (2014). SQF Code a HACCP-Based Supplier Assurance Code for the Food Industry. Trienekens, J., & Zuurbier, P. (2008). Quality and safety standards in the food industry, developments and challenges. International Journal of Production Economics, 113(1), 107–122. van Asselt, E. D., Meuwissen, M. P. M., van Asseldonk, M. A. P. M., Teeuw, J., & van der Fels-Klerx, H. J. (2010). Selection of critical factors for identifying emerging food safety risks in dynamic food production chains. Food Control , 21(6), 919–926.

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Wang, X., Li, D., & Shi, X. (2012). A fuzzy model for aggregative food safety risk assessment in food supply chains. Production Planning & Control, 23(5), 377–395. Whipple, J. M., Voss, M. D., & Closs, D. J. (2009). Supply chain security practices in the food industry, edited by Glenn Richey, R. International Journal of Physical Distribution & Logistics Management, 39(7), 574–594.

CHAPTER 2

Critical Success Factors for Food Safety Management System

Abstract This chapter presents the systematic literature review to investigate and summarise the latest findings on CSFs for FSMS implementation. It provides the theoretical background for the book and identifies the gaps of the literature that need to be filled in order to enhance the understanding of FSMS in the context of the global food supply chains. In detail, a comprehensive representation of current knowledge is generated and critically evaluated as well as analysed based on the review questions. Moreover, the review is explicitly focused on CSFs for FSMS implementation and sufficiently broad to capture their interactions from the organisation to the broader environment in which food firms operate. Keywords Systematic literature review · Bibliometric analysis · Critical success factors · Food safety management system

2.1

Introduction

This chapter presents the systematic literature review to investigate and summarise the latest findings on CSFs for FSMS implementation. It provides the theoretical background for the book and identifies the gaps

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 T. T. B. Nguyen and D. Li, Towards Safer Global Food Supply Chains, https://doi.org/10.1007/978-3-030-93356-2_2

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of the literature that need to be filled in order to enhance the understanding of FSMS in the context of the global food supply chains. In detail, a comprehensive representation of current knowledge is generated and critically evaluated as well as analysed based on the review questions. Moreover, the review is explicitly focused on CSFs for FSMS implementation and sufficiently broad to capture their interactions from the organisation to the broader environment in which food firms operate. This SLR, therefore, sets out to: • Systematic review to extract the existing CSFs for FSMS implementation from the previously published studies. • Identify research gaps related to CSFs in managing FSMS implementation. The rest of the chapter is structured as the following. The next section discusses the underpinned theory of this book, which is a critical success factor theory. Section 2.3 describes the methodology of the review that is followed to identify research gaps related to CSF. In Sect. 2.4, the known and unknown about CSFs of FSMS implementation in the context of global food supply chains are identified to establish the theoretical background as well as the research needs for the following chapters of the book. Finally, it is a brief conclusion restating the answer to the research question of SLR and summarising the value of the chapter in Sect. 2.5.

2.2

CSF Theory in FSMS

The critical success factor (CSF) was first introduced by John Rockart (Rockart, 1979). Later, the universal definition of CSFs was given by Boynton and Zmud (1984) as those few things that must go well to ensure success for a manager or an organisation. Therefore, they represent those managerial or enterprise areas that must be given special and continual attention to achieve high performance. Several researchers have applied CSF theory in enabling the organisations to focus on the most crucial factors that lead to the successful achievement of their desired goals in supply chain management (Clegg et al., 2013; Grimm et al., 2014; Luu et al., 2017; Nguyen, 2019). It is clear that the most challenging and complex tasks in any organisation are to facilitate decision making at various levels and smooth functioning of management

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17

processes. Hence, the application of CSF theory plays a crucial role in reducing this complexity by enabling the organisation to focus on the most important CSFs that lead to the successful achievement of their goals (Bai & Sarkis, 2013). A number of researchers have shown the application of the CSF theory in facilitating food manufacturers to focus only on the most important factors that lead to the achievement of desired food safety level (Kafetzopoulos & Gotzamani, 2014; Kirezieva, Luning, et al., 2015; Mensah & Julien, 2011; Nguyen, 2019). In the literature, CSFs are interchangeably used as ‘enablers’ or ‘key success factors’ and categorised as ‘critical factors’ in several studies on FSMS implementation (e.g. van Asselt et al., 2010; Kafetzopoulos & Gotzamani, 2014; Taylor & Taylor, 2015; Walsh & Leva, 2018). The purpose of identifying and evaluating CSFs is to reduce FSMS failure and to respond to the need for continuous FSMS improvement (De Boeck et al., 2018; Kafetzopoulos & Gotzamani, 2014; Mensah & Julien, 2011; Roth et al., 2008; Wilcock et al., 2011). However, in their studies, few writers have clarified the definition of CSFs, or no separation in categorisation exists between barriers and enablers in the same group of ‘critical factors’. These unclear viewpoints might lead to the misunderstanding of the definition of CSFs and influence the way practitioners to apply CSF theory to FSMS implementation. Hence, based on the discussion of CSFs in the literature, the definition of CSFs in this book is suggested as ‘those few things that must be taken into sufficient consideration by food firms to ensure success for FSMS’. To be a CSF for FSMS, two criteria need to be fulfilled. First, they are related to the management of FSMS. Second, only factors might lead to the success of FSMS implementation.

2.3

What Do We Know About CSF for FSMS?

Once an FSMS has been developed, it will interact with its surrounding environments. In the light of searching for improvement opportunities of FSMS implementation, researchers and consultants have suggested various factors that lead to successful FSMS or might impact FSMS from different perspectives in the context of complex global supply chains. These CSFs from those three levels are identified through the methodology of systematic literature review in the following subsections.

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2.3.1

SLR Methodology

A systematic literature review is a review of a clearly formulated question that uses systematic, reproducible and explicit methods to identify, select, and critically appraise relevant research and collect and analyse data from the studies included in the review (Higgins & Green, 2011). Given the critical role of literature reviews in creating and building bodies of knowledge and informing policy and practice, Denyer and Tranfield (2009) provide the guidance of five steps to conduct a systematic literature review (SLR) in the field of management and organisation studies. Durach et al. (2017) also suggest these steps of SLRs as a new paradigm accounting for the ontological and epistemological foundations of supply chain management research in their reviews. In the same manner, Thomé et al. (2016) offer an SLR guideline for operation management scholars, including eight steps by slitting the last steps and adding ‘updating the review’. In this chapter, these SLR guidelines are combined, and then a five-step SLR is applied to answer the research question related to the CSFs for FSMS implementation in global food supply chains, as illustrated in Fig. 2.1.

Fig. 2.1 Systematic review methodology (adapted from Denyer & Tranfield, 2009; Durach et al., 2017)

QuesƟon formulaƟon LocaƟng studies Study selecƟon and evaluaƟon Analyse and synthesis

ReporƟng and using the results

2

2.3.2

CRITICAL SUCCESS FACTORS …

19

Question Formulation and Locating Studies

In order to have a comprehensive search strategy, the first step is to formulate a straightforward research question that establishes the focus and criteria of the review (Denyer & Tranfield, 2009). The CIMOlogic (Context, Intervention, Mechanisms and Outcomes) is obtained to specify the four critical parts to be investigated in a well-built systematic review. It is constructed as ‘in this class of problematic Contexts, use this Intervention type to invoke these generative Mechanism(s), to deliver these Outcome(s)’ (Denyer & Tranfield, 2009; Denyer et al., 2008). Using this logic to the study, it emerges that the management of FSMS implementation has gained increasing attention in the global supply chain context due to the enormous negative impacts of food safety incidents on human heaths, society, economics, and environment. In this context, characterised by increasing global complexity and stringent food safety requirements, FSMS implementation must be successfully managed and improved by food manufacturers to ensure food safety. Hence, the central question of this study is: in the complexity of the global supply chains (Context), what are considered (Intervention) critical success factors for FSMS (Mechanism) to reduce food safety failure and respond to the need for continuous improvement (Outcome)? A set of keywords connected to the above question of the study is derived based on a brainstorming process. The search commerce involves investigating citation databases using the string keywords by combining Boolean operators with parentheses complex search. Data is collected from Dimensions, a scientific database applying machine learning and artificial intelligence technologies to use existing classification systems and automatically assign a consistent set of categories to all documents, regardless of the source (Bode et al., 2019). Web of Science and Scopus are not used in this study for the reason that in those databases, the documents are typically categorised using a journal as a proxy, with a few research categories being assigned at the journal level. Dimensions helps to create unintended consequences across research, from content coverage in databases to citation benchmarking practices. Also, it links and integrates data from multiple sources. Currently, it is the world’s largest linked research information dataset with more than 120 million publications, six million grants, nine million datasets, and so on (Hook et al., 2018).

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Fig. 2.2 Network of researchers in the searching field

2.3.3

Search Strategy

The complex string of keywords is constructed to reduce too generic and broad results instead of keywords or a simple string of keywords. The complex string of keywords is used for searching as the following: [‘Critical success factor’ OR ‘Critical success factors’ OR ‘Critical factor’ OR ‘Critical factors’] AND [‘Food safety’ OR ‘Food safety management’ OR ‘Food safety management system’] AND [‘Supply chains’ OR ‘Global supply chains’] AND [‘Management’] AND [‘Implementation’]. There are 4477 records generated based on this complex string refined by Dimensions Categories, including only Business and Management (category number 1503) and only articles for publication type. In this stage, a solid citation graph of researchers related to the keyword string is established by Dimensions to illustrate their contributions in the knowledge of this field (Fig. 2.2). 2.3.4

Study Selection and Evaluation

At this stage, the authors read the results page by page from Dimension to ensure substantive relevance by requiring that selected articles contain relevant contents. After this process, there are 180 records

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21

chosen. Besides Dimensions database, other sources containing 50 documents are used, such as records identified from Google Scholar, including reports, publications and working papers from International Organisation for Standardisation (ISO), World Health Organisation (WHO), Food and Agriculture Organisation (FAO), Codex Alimentarius Commission. In total, 230 documents are further investigated by reading abstracts to eliminate irrelevant records regarding the SLR research question. After this process, only 32 records remain. These articles are full text accessed to finalise the studies for the synthesis stage. More than 190 papers have been eliminated during this process. A structured extraction procedure is created to capture the critical elements of each study, including purpose, design/methodology/approach, contribution, and paper type. The purpose of using a set of explicit selection criteria is to assess the relevance of each study whether they do address the review question (Denyer & Tranfield, 2009). These papers have been cited 278 times, and the average citations per item are 8.6875 (Fig. 2.3). The descriptive analysis of the selected article’s sources revealed that British Food Control journal dominates in this research area accounting for seven papers taking 33.3% of the total (Fig. 2.4). The most cited study is the work of Fotopoulos et al. (2011) on International Journal of Quality & Reliability Management, with 38 times cited from 2005 to 2021. PublicaƟon years 7 6 5 4 3 2 1 0 2006

2008

2010

2012

2014

2016

2018

Fig. 2.3 Total publication by year of the selected papers

2020

2022

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T. T. B. NGUYEN AND D. LI Total Quality Management & Business Excellence ProducƟon Planning & Control Open Journal of Social Sciences Journal of Risk Research Journal of Hospitality and Tourism Management

Journal of DistribuƟon and Management Research InternaƟonal Journal of Engineering and Technology Business Process Management Journal BriƟsh Food Journal Asian Journal on Quality Agribusiness 0

Fig. 2.4

1

2

3

4

5

6

7

8

Source titles of the reviewed papers

Fig. 2.5 VOS coupling structure

2.3.5

Analysis and Synthesis

In the stage of analysis and synthesis, individual studies selected from the previous stage are broken down into constituent parts through the analysis process then made associations between elements by the synthesis

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23

CSFs from the broad environment CSFs from the market level CSFs from the organisaƟon al level

CSF theory

Fig. 2.6 The framework of literature review classification

process. The purpose of this stage is to develop and reorganise knowledge that is not apparent from reading the individual studies independently into a new arrangement (Denyer & Tranfield, 2009). The rationales used to extract, synthesise, and interpret the findings is constructed by a concise bibliometric analysis on the 32 selected papers. The VOSviewer 1.6.16 software is used to conduct a similarity analysis (van Eck & Waltman, 2010). With this rationale, the bibliographic coupling rule is suitable to investigate when two studies cite the same third study in their bibliography. It is helpful to map scientific content concerning a specific research stream or trend. A similarity matrix is constructed by VOSviewer through normalising the matrix of co-occurrences of the analysed elements represented by the common citation. A series of routines, where the nodes represent the papers and the distances between the nodes reflect their similarity in terms of shared references, form a bidimensional graphical map. VOSviewer uses the number of common citations to split papers into clusters (van Eck & Waltman, 2020). Bibliographic coupling analysis demonstrated that 23 articles were connected in terms

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of shared citations and gave form to four well-defined thematic clusters whose structures reflect the knowledge base characterising the dataset. Each cluster represents a univocal research line (Fig. 2.5). Then, based on the clustering results returned by VOSviewer, all the papers within each cluster are systematically reviewed, the main topics are discussed and the main links among the documents, and the most relevant research gaps. As Fig. 2.6 shows, it is structured to enable a holistic research analysis of this review. The first group presents CSF theory as the leading theory underpinning this research stream. The second group provides CSFs from the organisational level. The third group summaries CSFs from the market or supply chains level as well as the last group for the board environment from the published research. Collectively, they cover CSFs from three different levels in global trading.

2.4

CSFs for FSMS

2.4.1

Organisational Level

The organisation’s responsibility is to provide adequate resources for establishing, implementing, maintaining, and updating FSMS, including human resources, infrastructure, and work environment, to fulfil food safety objectives (ISO, 2005). Several attempts have been focused on the impact of the organisational environment on FSMS performance by a great deal of previous research. Among all CSFs, human resource or employee characteristic is considered the top difficulty in implementing FSMS, while it contributes as determinant factors of quality and food safety effectiveness (Fotopoulos et al., 2009; Kafetzopoulos & Gotzamani, 2014). Employee characteristics are described as an individual’s attitudes, knowledge and perceptions of food safety and hygiene control (Nyarugwe et al., 2016). In the same vein, several researchers identify human resource as the degree of employee involvement (Fotopoulos et al., 2009, 2011; Kafetzopoulos & Gotzamani, 2014; Kirezieva, Luning, et al., 2015; Luning et al., 2008), employee’s efficient knowledge and skills to ensure food safety (Kafetzopoulos & Gotzamani, 2014), awareness of the relevance and importance of their activities in contributing to food safety (ISO, 2005; Nyarugwe et al., 2018; Yiannas, 2009), training programs for employees to improve current level of the above requirements related to food safety (Kafetzopoulos & Gotzamani, 2014; Singh & Smith, 2006; Xiong et al., 2017). Also, an increased

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focus on culture, climate, and behaviour in food businesses is needed, as Sharman et al. (2020) suggest. They assess different types of culture, climate, and employees and find that different employee behaviours impact the culture and climate of an organisation. On another thing, management or leadership within food businesses is highlighted in providing commitment to support food safety objectives and ensuring the availability of required resources and adequately trained staff (Fotopoulos et al., 2009, 2011; Kirezieva, Nanyunja, et al., 2013; Kafetzopoulos & Gotzamani, 2014; Kirezieva, Jacxsens, et al., 2015; Luning et al., 2008; Trienekens & Zuurbier, 2008). It is responsible for managers to establish the food safety policy and culture within the organisation (Yiannas, 2009) and update the system continually (ISO 22000:2005). A broader perspective has been adopted by Trienekens and Zuurbier (2008), who argue that an essential factor is the enabling business environment, such as institutional and infrastructure facilities. This factor is critical for developing country producers to participate in international chains and implement standards required in Western markets. The lack of sufficient factors in the organisational environment such as financial resources, technical and labour skills within the organisation, and a shortage of infrastructures, facilities and administrative systems impact FSMS implementation significantly (Chaoniruthisai et al., 2018; Qijun & Batt, 2016; Rincon-Ballesteros et al., 2019; Trienekens & Zuurbier, 2008). Overall, all of the studies reviewed here support several CSFs from the organisational environment that highly interact with FSMS implementation and affect its success. 2.4.2

Market Level

In most previous research, the market level refers to the market and supply chain structure in which interactive relationships between organisations within the food chain are reflected that could affect FSMS performance (Kirezieva, Jacxsens, et al., 2015; Lu et al., 2021). At this level, the concepts of collaborative and supportive supply chains are central to more advanced FSMS. Comparatively, the study of Kirezieva, Luning, et al. (2015) confirmed that collaborative/supporting supply chains contribute to higher safety and quality management among the studied firms as they demonstrated more advanced knowledge and expertise than their counterparts. These factors are adopted as chain characteristics in the group of

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the context factors together with the product, production, and organisational characteristics affecting the design and operation of activities in the FSMS from several studies (Kirezieva, Nanyunja et al., 2013; Kirezieva, Luning, et al., 2015; Luning et al., 2011). Later, Despoudi et al. (2018) indicate that collaboration can reduce the level of Postharvest Food Losses and improve business performance through better quality of peach production based on a data set of Greek peach producers. Lu et al. (2021) emphasise that supply chain collaboration is essential to integrate knowledge management, education and training with Chilean food producers, processors, distributors, and end-consumers for food safety practices. However, the definition of a collaborative/supportive supply chain in these studies is limited, and it cannot reflect the relationships in the chain as well as the degree to which the organisations collaborate with others. Further works are still needed to clarify the degree of information exchange, the level of collaboration, support among stakeholders in the supply chain. Also, one question that needs to be asked is whether the impact from other parties in the market, such as government, non-profit organisations (NGOs), business associations and financial institutes, are significant on a firm’s FSMS implementation. Many authors point out that implementing FSMS requires regulatory and market opportunities information and technical and financial support from these parties (Kirezieva, Luning, et al., 2015; Qijun & Batt, 2016). Additionally, Qijun and Batt (2016) confirm that difficulty in obtaining external funds is perceived as a significant financial barrier to adopting a certificated FSMS. Nonetheless, no attempt was made to verify or quantify the degree to which these market environment factors, including support from other parties and collaborative activities in the supply chains, influenced FSMS implementation. 2.4.3

Food Safety Governance

The level of ‘broad context’ in the research of Kirezieva, Jacxsens, et al. (Kirezieva, Jacxsens, et al., 2015) could influence food firms’ FSMS are food-safety governance, agro-climatic and public policy environment. They define agro-climatic environment as climate zone and production season. Public policy environment is subsidies and other policy measures aimed at influencing the market, quality and safety of food products (Kirezieva, Jacxsens, et al., 2015). In this study, agro-climatic and public policy environments are out of the research scope as we only focus on

Broad Environment

Market Level

Commitment Awareness FS culture Human Communication resource Commitment Training Awareness Involvement Facilities and equipment Technology Standardised procedure Trust in buyer–supplier relationships Collaborative supply chains Target market (export or domestic) External support Food-safety governance X

X

USA

Sample Country

Leadership

2008 Food sectors

Year Type of Food Chain

Organisational Level

Roth et al

Existing CSFs in the literature

Authors

Table 2.1

Greece

X

X

X

X

Fotopoulos, Kafetzopoulos, Psomas 2009 Food sectors

X

X

X

X

X

Canada

Wilcock, Ball, Fajumo 2011 Food sectors

UK

X

X

X

X X

X X X

2011 Food sectors

Mensah & Julien

X X X

X X

2014 Nutrition, agricultural products, beverages Greece

Kafetzopoulos & Gotzamani

CRITICAL SUCCESS FACTORS …

(continued)

X X

X

X

12 countries

Kirezieva, Luning, et al 2015 Leafy greens

2

27

Agro-climatic environment Public policy environment

(continued)

Broad Environment

Market Level

Organisational Level

Commitment Awareness FS culture Human resource Communication Commitment Training Awareness Involvement Facilities and equipment Technology Standardised procedure Trust in buyer–supplier relationships Collaborative supply chains Target market (export or domestic) External support Food-safety governance Agro-climatic environment Public policy environment

Leadership

Year Type of Food Chain Sample Country

Authors

Table 2.1

X X X

Kirezieva, Jacxsens, et al 2015 Fresh produce Spain, Belgium, Norway 2017 Pork China

X

X

Xiong et al

X

X

van der Merwe et al 2019 Lamb South Africa

X

X

X

2021 Food sectors Chile

Lu et al

X

2021 Agro-food China

Zhao et al

28 T. T. B. NGUYEN AND D. LI

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operational and practice perspectives. Hence, food safety governance is analysed in depth. In the case of food safety, governance is aimed at assuring compliance of food companies to the food safety standards and regulations (Rouvière & Caswell, 2012). Like any other governance, food-safety governance is the result of public and or private enforcement (Kirezieva, Jacxsens, et al., 2015). There are a variety of enforcement strategies. Commonly used ones for the enforcement of food safety are audits and inspections, incentives (sanctions and stimuli), information and education, and sampling/monitoring (García Martinez & Poole, 2004; Garcia Martinez et al., 2007; Kirezieva, Jacxsens, et al., 2015; Rouvière & Caswell, 2012; Yapp & Fairman, 2006). Significant variations across countries and among value chains in global food trading are recognised in food safety governance. This issue increases the burden of auditing costs and certifications on food manufacturers when different certification frameworks are required by retailers in supplier qualifications (Mensah & Julien, 2011). In their study, Lu et al. (2021) support this by showing the inconsistency of food safety enforcement in Chile. Nevertheless, there has been no detailed investigation of the impact of food-safety governance on FSMS implementation. As an example, the influence of a public standard on the FSMS is investigated without being analysed the underlying governance mechanisms (Luning et al., 2015) investigates. To sum up the existing CSFs of FSMS implementation, a summary of existing CSFs extracted from the emerging discussion as an approach to increase the effectiveness of FSMS implementation from the reviewed papers is presented in Table 2.1.

2.5

Research Gaps

The above section has discussed that identifying CSFs for FSMS is critical to reduce the failure of FSMS implementation and respond to continuous improvement in global food supply chains. We could see that several factors related to an organisation, such as technology, strategy, market, and environment, affecting FSMS failure and success (Fotopoulos et al., 2009; Macheka et al., 2013; Qijun & Batt, 2016). Narrowing down this set to the most critical factors is very efficient for managers to provide the necessary resources and support and develop the necessary policies, practices, and procedures in time to increase the effectiveness of FSMS implementation. From the results of the systematic literature review, the

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researchers draw meticulous attention to CSFs, their interactions and relationships with the FSMS (Kirezieva, Jacxsens, et al., 2015; Luning et al., 2011). However, there are three critical research gaps in addressing the role of CSFs from a multi-level and to which degree they contribute to the success of FSMS. It is noticed that CSFs from the organisational level tend to be more concerned by many researchers, whereas the others are mainly distributed by Kirezieva, Jacxsens, et al. (2015). At the organisational level, it is evident that standardised food safety procedure, leadership and human resource-related factors are affirmed as the top most important factors to FSMS implementation in these studies. Many authors argue that this is how food enterprises respond to the requirement of stricter foodsafety governance to ensure food safety globally, as discussed in the above section. In the market environment, establishing collaboration and developing a more integrated relationship among the parties within the supply chain are essential to unify food safety assurance in the food supply chain as suggestions of these studies. Also, external supports in terms of the finance to be able to invest in structure, equipment and staff training, information to expand the market and update FSMS, industry associations and non-governmental organisations are examined (Fotopoulos et al., 2009; Mensah & Julien, 2011). These practices are essential to FSMS due to the burden and costs of more stringent food safety monitoring have a growing tendency of being shifted from importing countries to exporting countries, from developed countries to developing countries, from retailers to suppliers (Clarke, 2010; Henson & Humphrey, 2009; Liu, 2009). In the broader environment, these studies are likely to emphasise the existence of the broad context on FSMS performance without measuring their level of impacts (Kirezieva, Luning, et al., 2015; Mensah & Julien, 2011). Nevertheless, previous studies have not attempted to address the concern about factors related to the market and governance level of FSMS. The evidence from this chapter suggests that the most crucial limitation lies in the insufficient understanding of CSFs from the market level and food-safety governance. Also, the FSMS analysis from a systematic perspective requires interactions and relationships between and within firms as well as the context in which they are operating. Thus, further studies on defining the direct and indirect influences along with their

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possible magnitude on FSMS are needed. There are only a few works that investigated these environments, such as the study of Nanyunja et al. (2016) demonstrates how other stakeholders of supply chains influence FSMS in Kenya and Uganda. There is an apparent shift in more advanced FSMS and higher system output between farms and trade companies in Kenya to respond to the demand for strict voluntary food safety standards from large retailers supplying the EU premium market. While traders in Uganda only have basic FSMS and low system output present with both farmers and traders due to the less demanding EU wholesale markets, such as ethnic speciality shops. Another example of the influence of the market and food-safety governance on FSMS performance is the results from the work of Kirezieva, Luning, et al. (2015). They indicate that several factors have the dominating effect on the status of FSMSs in the global fresh produce chain. International export supply chains promote building capacity within companies in the chain to answer the stringent requirements of private brand standards. However, local institutional environments and the legislative framework in developing countries has negative consequences for the FSMSs in companies supplying the local markets. Additionally, standards play the role of an essential tool to trigger the maturation of the systems because some companies were lacking the motivation to comply with requirements. These findings, while preliminary, suggest that FSMS implementation cannot be investigated separated from its environments, especially CSFs within these environments. Moreover, none of the studies is able to suggest improvement opportunities as a result of assessing FSMS implementation considering the impact of CSFs contingent on the current situation of each enterprise. In addition, it is evident that managing FSMS implementation is deeply contextual, divergent, and practice related. Therefore, each firm will have different critical points needed to improve following their current procedures. Up to now, the research stream on CSFs of FSMS implementation has been mostly restricted to the confirmation of their presences by empirical studies or qualitative analyses. There is a need to understand CSFs and the degree to which they affect FSMS implementation. Constructed on that result, identifying improvement opportunities for FSMS could assist food firms’ managers effectively manage by prioritising CSFs to optimise available resources. Without this information, all factors seem important to FSMS implementation. Hence, firms’ managers have no idea where to make

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a change or update first. This is exemplified in works undertaken by Kafetzopoulos and Gotzamani (2014) and Kirezieva, Luning et al. (2015), which points out many critical factors without considering their interactions with each other and prioritising which factors should be improved or changed first. For large firms with potential financial and technological capabilities as well as years of global trading experiences, this approach could be easily done, but it is impossible for SMEs with limited capabilities (Luning et al., 2015).

2.6

Conclusion

In this chapter, a systematic literature review, following the research methodology of Denyer and Tranfield (2009) combined with bibliometric analysis by VOS viewer, has been undertaken to identify the knowledge gaps in the research of CSFs for FSMS implementation in the context of global food supply chains. The challenges in managing FSMS and a set of CSFs are reviewed and provided through a comprehensive analytical lens. The findings reported here emphasise and point out the main gaps in identifying CSFs from multi-level environments of food businesses as well as the relationship between them and FSMS. There are three main gaps in the research of CSFs for FSMS. First, most analysis on CSFs for FSMS implementation has been restricted to confirmation of CSFs’ presents and focused on only one level in each study. Second, the lack of studies examining the interaction between CSFs from multi-level environments and FSMS is identified. Finally, after identifying CSFs, there is a need to develop further improvement opportunities for firms using CSFs, not only confirming them. These research gaps will be addressed in the following chapters of the book.

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food safety: A case study from Chile. Production Planning & Control, 32(14), 1248–1264. https://doi.org/10.1080/09537287.2020.1796137 Luning, P. A., Bango, L., Kussaga, J., Rovira, J., & Marcelis, W. J. (2008). Comprehensive analysis and differentiated assessment of food safety control systems: A diagnostic instrument. Trends in Food Science and Technology, 19(10), 522–534. Luning, P. A., Kirezieva, K., Hagelaar, G., Rovira, J., Uyttendaele, M., & Jacxsens, L. (2015). Performance assessment of food safety management systems in animal-based food companies in view of their context characteristics: A European study. Food Control, 49, 11–22. Luning, P. A., Marcelis, W. J., Rovira, J., van Boekel, M. A. J. S., Uyttendaele, M., & Jacxsens, L. (2011). A tool to diagnose context riskiness in view of food safety activities and microbiological safety output. Trends in Food Science and Technology, 22(SUPPL. 1), S67–S79. Luu, P. H., Davies, B., & Dunne, M. P. (2017). The association between factors which affect the food safety practices of seafood distributors within the southern domestic distribution chains in Vietnam. Food Control, 73, 332–340. Macheka, L., Manditsera, F. A., Ngadze, R. T., Mubaiwa, J., & Nyanga, L. K. (2013). Barriers, benefits and motivation factors for the implementation of food safety management in the food sector in Harare Province, Zimbabwe. Food Control, 34(1), 126–131. Mensah, L. D., & Julien, D. (2011). Implementation of food safety management systems in the UK. Food Control, 22(8), 1216–1225. Nanyunja, J., Jacxsens, L., Kirezieva, K., Kaaya, A. N., Uyttendaele, M., & Luning, P. A. (2016). Shift in performance of food safety management systems in supply chains: Case of green bean chain in Kenya versus hot pepper chain in Uganda. Journal of the Science of Food and Agriculture, 96(10), 3380–3392. Nguyen, T. T. B. (2019). A study of implementation strategies for food safety management system in global supply chains. University of Liverpool. Available at https://doi.org/10.17638/03058360 Nyarugwe, S. P., Linnemann, A., Hofstede, G. J., Fogliano, V., & Luning, P. A. (2016). Determinants for conducting food safety culture research. Trends in Food Science & Technology, 56, 77–87. Nyarugwe, S. P., Linnemann, A., Nyanga, L. K., Fogliano, V., & Luning, P. A. (2018). Food safety culture assessment using a comprehensive mixedmethods approach: A comparative study in dairy processing organisations in an emerging economy. Food Control, 84, 186–196. Qijun, J., & Batt, P. J. (2016). Barriers and benefits to the adoption of a third party certified food safety management system in the food processing sector in Shanghai, China. Food Control, 62, 89–96.

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Rincon-Ballesteros, L., Lannelongue, G., & González-Benito, J. (2019). Implementation of the Brc food safety management system in Latin American countries: Motivations and barriers. Food Control, 106(June), 106715. Rockart, J. F. (1979). Chief executives define their own data needs. Harvard Business Review. Retrieved from https://hbr.org/1979/03/chief-executivesdefine-their-own-data-needs Roth, A. V., Tsay, A. A., Pullman, M. E., & Gray, J. V. (2008). Unraveling the food supply chain: Strategic insights from China and the 2007 recalls. The Journal of Supply Chain Management, 44(1), 22–39. Rouvière, E., & Caswell, J. A. (2012). From punishment to prevention: A French case study of the introduction of co-regulation in enforcing food safety. Food Policy, 37 (3), 246–254. Sharman, N., Wallace, C. A., & Jespersen, L. (2019). (2020), Terminology and the understanding of culture, climate, and behavioural change—Impact of organisational and human factors on food safety management. Trends in Food Science & Technology, 96(June), 13–20. Singh, P. J., & Smith, A. (2006). An empirically validated quality management measurement instrument. Benchmarking: An International Journal, 13(4), 493–522. Taylor, E., & Taylor, J. (2015). Improving food safety—Replicating the Abu Dhabi success story, edited by Eunice Taylor, D. Worldwide Hospitality and Tourism Themes, 7 (1), 90–96. Thomé, A. M. T., Scavarda, L. F., & Scavarda, A. J. (2016). Conducting systematic literature review in operations management. Production Planning & Control, 27 (5), 408–420. Trienekens, J., & Zuurbier, P. (2008). Quality and safety standards in the food industry, developments and challenges. International Journal of Production Economics, 113(1), 107–122. Walsh, C., & Leva, M. C. (2018). A review of human factors and food safety in Ireland. Safety Science, 119, 399–411. https://doi.org/10.1016/j.ssci.2018. 07.022 Wilcock, A., Ball, B., & Fajumo, A. (2011). Effective implementation of food safety initiatives: Managers’, food safety coordinators’ and production workers’ perspectives. Food Control, 22(1), 27–33. Xiong, C., Liu, C., Chen, F., & Zheng, L. (2017). Performance assessment of food safety management system in the pork slaughter plants of China. Food Control, 71, 264–272. Yapp, C., & Fairman, R. (2006). Factors affecting food safety compliance within small and medium-sized enterprises: Implications for regulatory and enforcement strategies. Food Control, 17 (1), 42–51. Yiannas, F. (2009). Food safety culture, edited by Intergovernmental Panel on Climate Change Food Technology, 66. Springer. Available at https://doi.org/ 10.1007/978-0-387-72867-4

CHAPTER 3

Empirical Evidence on Critical Success Factor from Multi-Level Environments and Their Relationships with Food Safety Management System

Abstract To meet both market demands and regulations, stakeholders in global food supply chains are progressively increasing food safety management within their organisations and throughout the chains to demonstrate their abilities in controlling food safety hazards to ensure that food is safe at the time of human consumption (Mensah & Julien, 2011). Based on the main gaps addressed in Chapter 2 related to CSFs for FSMS, a set of CSFs related to the organisations, market, and environment affecting the success of FSMS is identified. In detail, the degree to which CSFs from multi-level environments interacting with FSMS are explored to quantify the impact and their relationship in the context of global supply chains. Keywords Structural equation modelling · Critical success factors · Food safety management system

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 T. T. B. Nguyen and D. Li, Towards Safer Global Food Supply Chains, https://doi.org/10.1007/978-3-030-93356-2_3

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3.1

Introduction

To meet both market demands and regulations, stakeholders in global food supply chains are progressively increasing food safety management within their organisations and throughout the chains to demonstrate their abilities in controlling food safety hazards to ensure that food is safe at the time of human consumption (Mensah & Julien, 2011). In this book, Chapter 2 has addressed the main gaps in the literature related to CSFs for FSMS. A set of CSFs related to the organisations, market, and environment affecting the success of FSMS is identified based on the published research. Although FSMS implementation has been thoroughly investigated with positive and negative reviews, causal factors leading to effective FSMS implementation remain questionable. In detail, the degree to which CSFs from multi-level environments interacting with FSMS remains unknown. Thus, a quantitative approach is needed to quantify the degree these CSFs impact FSMS implementation to explore their relationship. Responding to the identified gaps in the literature and the need for further research on CSFs (see Sect. 2.5), this chapter aims to investigate whether and to what degree CSFs from multi-level environments influence FSMS implementation in the context of global supply chains. The rest of the chapter is structured as follows. The next section presents the research framework and hypotheses development of the chapter. The research instrument for the study is presented in Sect. 3.3. The research methodology includes the sampling strategy, the construction of the instruments and measures (Sect. 3.4). In Sect. 3.5, exploratory and confirmation factor analyses are conducted to uncover the underlying structure of the variables emerging from the literature based on preestablished theory. Then, structural equation model-ling is undertaken to test the proposed hypotheses. In the discussion, the research results and implications are considered before reaching the study’s conclusion in the end.

3.2 The Research Frameworks and Hypotheses Development Given the limited amount of literature on CSFs from multi-level environments investigated in the previous chapter, the hypotheses about the relationships between CSFs and FSMS implementation suggested in the research model are drawn in Fig. 3.1. Each path in the model is labelled with the associated hypothesis.

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Fig. 3.1 The research model

3.2.1

Organisational Factors

Regarding organisational factors, management responsibilities, human resources, and organisational resources have been separately studied and mainly focused on quality management in the literature, as seen in Table 2.1. They have not been empirically tested in a model that shows their positive impact on FSMS implementation. Therefore, the following research hypotheses based on the previous studies are proposed: H1 There is a significant positive impact of management responsibilities on the implementation of FSMS. H2 There is a significant positive impact of human resources on the FSMS implementation. H3 There is a significant positive impact of organisational resources, including facilities, technology, and financial condition of the firm, on the implementation of FSMS.

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3.2.2

Market-Related Factors

3.2.2.1 Collaboration From Chapter 2, supply chain collaboration and external supports for the implementation of FSMS become central issues at the level of the market environment. Supply chain collaboration is defined as two or more independent firms that form long-term relationships and work closely to plan and execute supply chain operations toward common goals, thereby achieving more benefits than acting independently (Simatupang & Sridharan, 2002), is a well-developed topic for many businesses. However, among all, the supply chain of food production needs to be paid more attention than others because of the nature of food, the difficulty associated with determining its safety risks before consumption (Mensah & Julien, 2011). Establishing collaboration and developing a more integrated relationship among the parties within the supply chain are essential to avoid corrupted connections in the food supply chain. However, many empirical studies suggest that supply chain collaboration creates opportunities for firms to experience improved quality performance, such as Fynes et al. (2005). Kirezieva, Luning et al. (2015) confirm that collaborative supply chains contribute to more advanced FSMS and better system output as companies demonstrated advanced knowledge and expertise about safety and quality management. They specify collaborative supply chain related to a high level of severe stakeholder requirement, power in supplier relationship and degree of information exchange in the supply chains. Despoudi et al. (2018) investigate the effect of different types of collaboration on the level of Postharvest Food Losses and the proportion of low-quality peaches produced using the dataset of Greek peach producers. They empirically confirm that high levels of collaboration between producers and cooperatives are associated with both low levels of PHFL and a low proportion of low-quality peaches. In addition, to identify the degree to which a company collaborates with its partners in a supply chain, many previous studies propose to measure collaboration through information sharing, joined problem-solving, continuous improvement, planning and goal-setting activities, information exchange (Cao et al., 2010; Kirezieva et al., 2013; Macheka et al., 2017; Simatupang & Sridharan, 2008). These activities are used as measurement constructs for collaboration in food supply chains. Hence, it is proposed that:

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H4 There is a significant positive impact of collaborative activities concerning food safety in the supply chains on the FSMS implementation. 3.2.2.2 Support FSMS at firms within the international food supply chains needs to be continuously improved due to the more and more stringent market demands and regulatory requirements for food safety. However, firms could deal with many difficulties in improving FSMS implementation since the burden and costs of strict food safety monitoring have a growing tendency of being shifted from importing countries to exporting countries, from developed countries to developing countries, from retailers to suppliers (Clarke, 2010; Henson & Humphrey, 2009; Liu, 2009). Retailers would be able to demand that their suppliers comply with new standards without compensating them adequately for the extra costs incurred even though most exporting firms from developing countries often lack the infrastructure, equipment, and trained personnel to meet the additional requirements of food safety standards. As a result, food manufacturers from developing countries search for external supports in terms of finance to be able to invest in structure, equipment and staff training (Qijun & Batt, 2016), information to expand the market as long as updating their FSMS to compliance with changing requirements from other stakeholders in the supply chain, industry associations and nongovernmental organisations (Fotopoulos et al., 2009; Mensah & Julien, 2011). The findings of Chapter 2 also point out that there are four sources of support enhancing the implementation of FSMS: stakeholders in supply chains, government and authorities, business associations, and financial institutions. In addition, NGOs show their critical roles in developing private regulatory/certification systems to support and encourage food firms to address food safety as well as social and environmental responsibility, using third-party certification rather than self-reports or certification by business partners (Mensah & Julien, 2011; Tran et al., 2013). Combined with the suggestion of the literature, there are five sources of external support that need to be tested in this quantitative research to investigate their impact on FSMS implementation, including support from stakeholders in supply chains, government and authorities, business associations, financial institutions, and NGOs. Therefore, the following hypothesis is proposed:

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H5 There is a significant positive impact of support related to food safety management from different parties on the firms’ FSMS implementation.

3.2.3

Food-Safety Governance

Stringent regulations and standards compliance is an essential element of all FSMS. Food-safety governance is usually used to induce compliance by the companies. It is enforced by food safety authorities and relevant parties, such as certificate bodies, which can be direct—via visits, random or scheduled or indirect—through monitoring companies’ records or third-party audits (Rouvière & Caswell, 2012). In the context of global supply chains, food-safety governance is extremely complicated due to many national and international actors involved in governance. This is evident in the study of Tran et al. (2013), they investigate the governance of the shrimp supply chain in Vietnam and conclude the public and private regulatory networks affecting the organisation and governance of shrimp supply chains. These key actors have some existing enforcement practices and strategies in food-safety governance. In detail, audits and inspections can be random or periodically performed before or after releasing products at firms, retail places (e.g. showrooms, flea markets, and supermarkets), or at exporting points by these actors (Kirezieva, Jacxsens et al., 2015; Rouvière & Caswell, 2012). From the results of regulatory inspections, audits, and sampling, regulatory sanctions, such as fines, penalties, prosecution, and recalls, will be conducted to punish firms for committing offences, non-compliance, or repeatedly breaching foodsafety regulations. They can be repressive (e.g., fines, prosecution, recall, closure of facilities, seizure of products, disqualification from the market), informative—requiring corrective actions, and ‘naming and shaming’— providing negative information to the consumers (Rouvière & Caswell, 2012). Stimuli, such as awards, labels, tax reduction, can also be employed to encourage compliance (Kirezieva, Luning et al., 2015). Besides, information and education, namely guidelines, training, advice, are used to support companies, especially in the case of small and medium enterprises (Fairman & Yapp, 2005; Garcia Martinez et al., 2007). Their impacts reflect on the roles of framing, guiding, and checking FSMS implementation for the purpose that firms are complying with regulations and standards. As a result, the following hypothesis is proposed to

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test whether and to what extent food-safety governance impacts on FSMS implementation: H6 There is a significant positive impact of food-safety governance on firms’ FSMS.

3.2.4

FSMS Implementation

In international food trading, food safety regulations and standards have become essential frameworks to control and enhance food safety management (FAO/WHO, 2001), namely BRC, IFS, HACCP, the Safe Quality Food (SQF) 2000 Level 2, and the ISO 22000:2005. Underpinned by these standards and regulations, FSMS provides a framework for uniformity in requirements, audit procedures, mutual acceptance of audits and reassure retailers and branded manufacturers of the capability and competence of suppliers (Mensah & Julien, 2011). FSMS is highly customised for each firm resulting from the implementation of various quality assurance and legal requirements into each firm. However, it must contain key elements from food safety requirements of EU legislation (EC, 2002), Code of Federal Regulation, Codex (CAC, 2009), ISO 22000 (ISO, 2005). These elements include prerequisite programmes, HACCP principles, and other components of FSMS, such as traceability, control of nonconformity, validation, verification, and improvement that are adopted to construct measurement indicators of FSMS implementation in this study. 3.2.4.1 PRPs PRPs are necessary conditions and activities to maintain a hygienic environment throughout the food chain suitable for the production, handling and provision of safe end products and safe food for human consumption (ISO, 2005). PRPs play essential roles in the context of supporting HACCP for effective FSMS. HACCP focuses on raw materials, the product, and the manufacturing process, whilst PRPs tend to focus on the hygienic operating environment and quality assurance support programs managed by people who are knowledgeable and exhibit a supportive attitude towards food safety (Mortimore & Wallace, 2013), namely Good Manufacturing Practice (GMP), Good Hygiene Practice (GHP), Sanitation Standard Operating Procedures (SSOPs). For food manufacturing in general, there are specifies detailed requirements adopted from BSI EN

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ISO22002-1 (International Organization for Standardization, 2009) as the following: • Construction and layout of buildings and associated utilities. • The layout of premises, including workspace, employee facilities, laboratory facilities, storage, and warehouse. • Supplies of air, water, energy and other utilities. • Supporting services, including waste and sewage disposal. • Suitability of equipment and its accessibility for cleaning, maintenance and preventive maintenance. • Management of purchased materials. • Measures for the prevention of physical, allergen and microbiological cross-contamination. • Cleaning and sanitising programmes are established to ensure that the food-processing equipment and environment are maintained in a hygienic condition. 3.2.4.2 Principles of HACCP The HACCP system is a science-based system created to identify specific hazards and actions to control them in order to ensure food safety and quality (Arvanitoyiannis et al., 2009). Preventing problems from occurring is the desired goal underlying any HACCP system. The HACCP consists of seven principles that outline establishing a HACCP plan for each operation to reduce the risk of a food safety failure established by Codex (CAC, 2009). Seven fundamental principles are employed in developing HACCP plans that include hazard analysis (including hazard analysis, identification, and assessment), Critical Control Points (CCPs) identification, establishing critical limits, monitoring procedures, corrective actions, verification procedures, and record-keeping and documentation. As the Codex standard, these principles have become the reference for international food safety and identified as the baseline for consumer protection. HACCP is a critical part of any FSMS, widely acknowledged as the best method of assuring product safety while becoming recognised internationally as a mandatory tool for controlling foodborne hazards in the food industry (Khandke & Mayes, 1998; Mortimore & Wallace, 2013). The significant benefit of the HACCP system is that it focuses attention on areas where problems potentially may occur and require what

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foodservice facilities to be prepared to deal with issues immediately if they arise. The success and effectiveness of the HACCP plan in preventing foodborne diseases and reducing food safety risks to an acceptable level depending on its correct implementation and application (FAO/WHO, 2001; Kok, 2009). 3.2.4.3 Other Activities Besides PRPs and HACCP principles as the basic elements, FSMS is also formed by other activities that are regulatory and standardised requirements, including traceability, control of nonconformity, validation, verification, and improved ability. • Traceability is the ability to trace and follow food movement through the specified stage(s) of production, processing and distribution according to the European Union (EU) regulation 178/2002 (EC, 2002), Codex (CAC, 2009). ISO 22000:2005 suggests that a traceability system should be established and applied by food businesses to identify product lots and their relation to batches of raw materials, processing, and delivery records. Food Standard Agency (FSA, 2002) identifies three primary characteristics for traceability systems, namely identification of units/batches of all ingredients and products, information on when and where they are moved and transformed, and a system linking these data. • Control of nonconformity is the identification and control potential unsafe products that are affected when critical limits for CCP(s) are exceeded or a loss of control of operational PRP(s) (ISO 22000:2005). To control nonconformity, a documented procedure that is well established and maintained defines the identification and assessment of affected end products to determine their proper handling, and a review of the corrections carried out. Thereupon, corrective actions are initiated, and food manufacturers have a proper procedure to handle potentially unsafe products. For instance, reprocessing or further processing within or outside the organisation to eliminate or reduce the food safety hazard to acceptable levels, destruction and/or disposal as waste, withdrawal or recall. • Validation is obtaining evidence that a control measure or combination of control measures if properly implemented, is capable of controlling the hazard to a specified outcome (CAC, 2009). Validated control measures are competent and capable of handling

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the identified food safety hazards and providing sufficient evidence for the food safety team’s specified monitoring and measuring methods and equipment. They are required to adequately ensure the implementation of the monitoring and measuring procedures (ISO, 2005). • Verification is the application of methods, procedures, tests and other evaluations, in addition to monitoring to determine whether a control measure is or has been operating as intended (CAC, 2009). Verification plays a fundamental role in ensuring that the FSMS’s functions are effective as designed. Internal audits are conducted at planned intervals to determine whether the food safety management system is implemented efficiently and updated based on evaluation and analysis of the result of verification activities. Also, all records and documents required by the food safety management system are controlled adequately at food companies (ISO, 2005). • Improvement is a must for any FSMS since FSMS is required to be improved and continually updated. Food firms are advised to actively seek certification or registration of their FSMS by an external organisation or make a self-assessment or self-declaration of conformity (ISO, 2005).

3.3

Research Instruments

As part of rigorous data collection, the research instrument plays an important role in establishing the study’s validity and reliability. Grounded on the above hypotheses development, the research instrumentation used to design the survey questionnaire is presented in the Table 3.1.

3.4

Research Methodology 3.4.1

Sample design

The chosen population for this study is food manufacturing and exporting companies in Asian developing countries. The main reason for focusing on the food industry in Asia is that they have emerged as leading sectors of global markets. In particular, China and Vietnam are top fishery,

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Table 3.1 Construct and measurement items and support references Construct

Measurement item

Management responsibilities

Managers’ commitments to food Fotopoulos et al. (2009), safety management ISO (2005), Kafetzopoulos and Gotzamani (2014), Kirezieva, Nanyunja et al. (2013), Luning et al. (2008), Macheka et al. (2017), and Trienekens and Zuurbier (2008) Responsibilities and authorities Fotopoulos et al. (2009), are defined for each person, ISO (2005), and such as food safety team, team Kafetzopoulos and leader, direct workers within the Gotzamani (2014) organisation to ensure efficient operation and maintenance of FSMS Food safety culture is established ISO (2005), Nyarugwe within the organisation et al. (2016, 2018), and Yiannas (2009) Food safety policy is established Nyarugwe et al. (2016, as the guiding principle to 2018) and Yiannas implement FSMS (2009) Knowledge and skills of the Fotopoulos et al. (2009), employees ISO (2005), Kafetzopoulos and Gotzamani (2014), and Kirezieva, Nanyunja et al. (2013) ISO (2005), Powell et al. Awareness of the personnel in the relevance and importance of (2013), and Yiannas (2009) their activities contributing to food safety management Training programs related to Lakhal et al. (2006), food safety for the employee Mensah and Julien (2011), and Singh and Smith (2006) Employee’s involvement in food Fotopoulos et al. (2009), safety management activities Kirezieva, Luning et al. (2015), Luning et al. (2008), and Macheka et al. (2017)

Human resources

References

(continued)

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Table 3.1 (continued) Construct

Measurement item

Organisational resources

Qualified facilities and equipment to ensure food safety management

Collaborative activities related to FSMS

External support to enhance food safety management from:

References

Fotopoulos et al. (2009), Kafetzopoulos and Gotzamani (2014), Kirezieva, Jacxsens et al. (2015), Kirezieva, Luning et al. (2015), Kirezieva, Nanyunja et al. (2013), Luning et al. (2008), and Mensah and Julien (2011) The company’s financial Macheka et al. (2013), condition Qijun and Batt (2016), and Xiong et al. (2017) Macheka et al. (2013), The company’s technological condition Qijun and Batt (2016), and Xiong et al. (2017) Solving emerging problems Cao et al. (2010), ISO related to product safety (2005), and Simatupang and Sridharan (2005, 2008) Having continuous improvement Cao et al. (2010), ISO programs for food safety (2005), and Simatupang and Sridharan (2005, 2008) Planning and goal-setting Cao et al. (2010) and activities Simatupang and Sridharan (2005, 2008) Communicating and exchanging Cao et al. (2010), Ding et al. (2014), Fynes et al. information related to food (2005), Luning et al. safety management (2015), and Simatupang and Sridharan (2005, 2008) Other stakeholders in our supply Fotopoulos et al. (2009), chains (such as suppliers, Macheka et al. (2017), contractors, buyers, etc.) Mensah and Julien (2011), and Qijun and Batt (2016) Government and authorities Fotopoulos et al. (2009), Macheka et al. (2017), Mensah and Julien (2011), Qijun and Batt (2016), and Tran et al. (2013)

(continued)

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Table 3.1 (continued) Construct

Measurement item

References

Financial institutions (banks)

FS governance

Fotopoulos et al. (2009), Macheka et al. (2017), Mensah and Julien (2011), Qijun and Batt (2016), and Tran et al. (2013) Business associations (such as (Fotopoulos et al. NAFIDAD, VASEP in Vietnam) (2009), Macheka et al. (2017), Mensah and Julien (2011), Qijun and Batt (2016), and Tran et al. (2013) Non-governmental organisations Fotopoulos et al. (2009), Macheka et al. (2017), Mensah and Julien (2011), Qijun and Batt (2016), and Tran et al. (2013) Food safety audits and Kirezieva (2015), inspections by regulatory Kirezieva, Jacxsens et al. agencies to induce compliance (2015), Kirezieva, by the company Nanyunja et al. (2013), Rouvière and Caswell (2012), and Yapp and Fairman (2006) Sanctions, such as penalties, Kirezieva (2015), prosecution, and recalls to Kirezieva, Jacxsens et al. punish for committing an (2015), Kirezieva, offence or repeatedly breaching Nanyunja et al. (2013), regulations Rouvière and Caswell (2012) Stimulus, such as awards, labels, Kirezieva (2015), Kirezieva, Jacxsens et al. tax reduction from regulatory (2015), Kirezieva, agencies to encourage food Nanyunja et al. (2013), safety management compliance and Rouvière and Caswell (2012) Information and education, such Garcia Martinez et al. as guidelines, training, advice (2007), Kirezieva (2015), from regulatory agencies to Kirezieva, Jacxsens et al. support company in food safety (2015), Kirezieva, management Nanyunja et al. (2013), and Rouvière and Caswell (2012)

(continued)

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Table 3.1 (continued) Construct

Measurement item

References

HACCP

Hazards that need to be prevented, eliminated, or reduced to acceptable levels are well-identified at each step from incoming raw materials to finished products The points where control is critical to assuring the safety of the product are established by HACCP team Level of efficiency in establishing critical limits at critical control points that separate acceptability from unacceptability for the prevention, elimination or reduction of identified hazards Monitoring procedures and systems at critical control points are established and implemented Corrective actions are installed when monitoring indicates that a critical control point is not under control Validation procedures ensure that the critical control points will control the hazards of concern and verify that the system is working day-to-day as planned The ability to provide efficient documents and records that demonstrates HACCP system is operating under control and that appropriate corrective action has been taken for any deviations from the critical limits Construction and layout of buildings and associated utilities

Cormier et al. (2007), ISO (2005), Mortimore and Wallace (2013), Raspor and Ambrožic (2012), and Scott and Chen (2010)

Prerequisite programs

Cormier et al. (2007), International Organization for Standardization (2009), ISO (2005), Mortimore and Wallace (2013), Raspor and Ambrožic (2012), and Scott and Chen (2010)

(continued)

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Table 3.1 (continued) Construct

Other activities of FSMS

Measurement item The layout of premises, including workspace, employee facilities, laboratory facilities, storage, and warehouse Supplies of air, water, energy and other utilities Supporting services, including waste and sewage disposal Suitability of equipment and its accessibility for cleaning, maintenance and preventive maintenance Management of purchased materials Measures for the prevention of physical, allergen and microbiological cross-contamination Cleaning and sanitising programs are established to ensure that the food-processing equipment and environment are maintained in a hygienic condition Traceability system is adequate to identify incoming material from the immediate suppliers and the initial distribution route of the end product Corrective actions are guaranteed to be initiated when critical limits are exceeded or when there is a lack of conformity with operational prerequisite programs Proper procedures to handle potentially unsafe products Control measures are effective and capable of ensuring control of the identified food safety hazards

References

Cormier et al. (2007), ISO (2005), Mortimore and Wallace (2013), and Scott and Chen (2010)

(continued)

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Table 3.1 (continued) Construct

Measurement item The ability to provide sufficient evidence that the specified monitoring and measuring methods and equipment are adequate to ensure the performance of the monitoring and measuring procedures Internal audits are conducted to determine whether the food safety management system is effectively implemented and updated based on evaluation and analysis of the result of verification activities All records and documents required by the food safety management system are appropriately controlled Internal communication is efficient in exchange information concerning food safety throughout the organisation External communication is efficient in exchange information concerning food safety throughout the food chain, such as suppliers and contractors, customers, statutory and regulatory authorities, and other organisations The ability to improve and continually update food safety management systems The active in seeking certification or registration of our food safety management system by an external organisation or make a self-assessment or self-declaration of conformity

References

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agriculture food products exporters locate (FAO, 2020). Hence, the stratification of the population for this study is used to recruit voluntary food firms in China and Vietnam that meet three key criteria. First, firm sizes are from small (11–50 employees), medium (51–250 employees) to large (more than 250 employees) companies according to the definitions of European Commission (2003) for enterprises sizes. Second, the company is currently processing and trading food products globally. Finally, respondents are required to be senior and quality-control managers who are experts in their field and currently in charge of FSMS implementation. Regarding the number of firms as the sample for the research, it depends on many factors, such as multivariate normality of the data, estimation technique, model complexity, the amount of missing data, and the average error variance among the reflective indicators (Hair et al., 2019; Tabachnick & Fidell, 2013). Obviously, the larger the sample size is, the more reliable the results are because SEM is more sensitive to sample size than other multivariate approaches. Hair et al. (2019) suggest a minimum of 300 cases is needed to produce reliable results for models with seven or fewer constructs, lower communalities (below 0.45), and/or multiple under-identified (fewer than three) constructs. A widely accepted rule of thumb is five to ten cases/observations per indicator variable in setting a lower bound of adequate sample size (Bentler & Chou, 1987; Nunnally, 1978). There are nearly 25 indicators in this study, so 250 respondents are the appropriate minimum cut-off value for the sample size. 3.4.2

Data Collection

The surveys containing structured questionnaires as the data collection method were distributed to 1000 food firms’ managers of Chinese and Vietnamese food manufacturing and exporting sector. Questionnaires were translated into Chinese and Vietnamese by the researchers. The questionnaires were sent through both online platforms, such as email, survey portals (Weixin in China and Google Form in Vietnam) as well as the door-to-door distribution method by the researcher. All participants responded voluntarily and were assured that their responses would remain confidential. A total of 324 food companies responded, giving a response rate equal to 32.4%. However, there is not an equal number in terms of responding from two countries. There are 252 valid responses from

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Table 3.2 Demographic information of the surveyed companies Type

%

Fishery

48.7 SMEs

Agricultural 41 Beverages Subsectors

6.8 3.5

Size

%

Exporting capacity

%

Positions of respondents

%

71.6 >3000 13.2 QC managers 29.7 tonnes/year >250 17.1 500–3000 37.4 Supply chain managers 29.4 employees tonnes/year 0.747, factor loadings > 0.535), explaining 66.897% of the total variance. However, the rotated component matrix suggested that two items, ‘Support from non-governmental organisations’ and ‘Support from financial institutions’, should be deleted from the construct. After the deletion, 69.605% of the total variance is explained with Kaiser–Meyer–Olkin 0.872, Bartlett’s test of Sphericity 1685.232, p = 0.00, Eigenvalue > 1, MSA > 0.743, factor loadings > 0.6. Thus, they demonstrate convergent validity for all constructs by exceeding the minimum standard for factor loadings of 0.50. Six constructs are named after the items loaded on them, as follows: ‘Human resource’, ‘Management responsibility’, ‘Collaboration’, ‘FS governance’, ‘Support’ and ‘Organisational resources’ arranged in descending coefficient size as illustrated in Table 3.3. 3.5.1.1 Construct Reliability and Validity The reliability of all FSMS implementation items is confirmed through Cronbach’s alpha coefficients that are higher than 0.750, indicating that

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Table 3.3 Exploratory factor analysis Constructs

Rotated component matrixa Code

Items

Component 1

Management responsibility (MR)

MR1 MR2 MR3 MR4

Collaboration (C)

C2 C3

C4

C1 Human resources (HR)

HR4 HR2 HR3 HR1

FS Governance (G)

G4

Organisational resource (OR)

OR2

G3 G2 G1

OR3 OR1

Support (S)

S2

Manager’s commitments Food safety policy Responsibilities and authorities Food safety culture Emerging problems Planning and goal-setting activities Continuous improvement programs Information exchange Employees’ involvement Personnel awareness Training programs Employees’ knowledge and skills Information and education Stimulus Sanctions Audits and inspections Financial condition Technological condition Qualified facilities and equipment Business associations

2

3

4

5

6

0.825 0.812 0.744 0.672 0.806 0.784

0.762

0.694 0.777 0.769 0.748 0.729

0.785 0.703 0.702 0.613 0.865 0.790 0.760

0.847

(continued)

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Table 3.3 (continued) Constructs

Rotated component matrixa Code

Items

Component 1

S3 S4

2

3

4

Stakeholders in supply chains Government and authorities

5

6 0.778 0.603

Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization a Rotation converged in 6 iterations

Table 3.4 Reliability checks for FSMS implementation FSMS implementation HACCP Prerequisite programs (PRPs) Other activities (OA)

Cronbach’s alpha

N of items

Item mean

Inter-item correlations (minimum–maximum)

Mean of item-total correlation

0.940 0.931

7 8

3.566 3.540

0.638–0.744 0.499–0.728

0.693 0.627

0.955

11

3.521

0.549–0.747

0.658

reasonably reliable items measure all factors. The mean inter-item correlations are above 0.6, suggesting quite a strong relationship among the items (Pallant, 2020). The reliabilities of all the extracted factors of CSFs have been confirmed as Cronbach’s alpha coefficients are higher than 0.75, exceeding the minimum requirement and indicating that all factors are measured by reasonably reliable items (Table 3.4). The CFA (Maximum likelihood estimation technique) is also applied in each of the sub-models (CSFs) to determine whether the extracted latent factors show an acceptable fit to the empirical data. Thus, a series of tests are performed further to determine the construct validity of the latent factors. The extracted latent factors show an acceptable fit to the empirical data (Table 3.5). In terms of other diagnostic measures, the standardised residuals are examined less than |2.5|. Then, the modification index (M.I.) associated

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Table 3.5 Validity check Constructs

Items

Human resources (HR)

HR1 HR2 HR3 HR4 MR1 MR2 MR3 MR4 OR1 OR2 OR3 C1 C2 C3 C4 G1 G2 G3 G4 S2 S3 S4 HACCP PRP OA

Management responsibility (MR) Organisational resources (OR) Collaboration (C)

FS Governance (G)

Support (S)

FSMS implementation (PER)

Factor loading 0.810 0.775 0.695 0.736 0.844 0.845 0.731 0.698 0.777 0.751 0.844 0.723 0.773 0.660 0.666 0.754 0.762 0.774 0.645 0.778 0.788 0.580 0.942 0.901 0.935

AVEa

CRb

(Corr)2, c

0.842

0.570

0.841

0.373

0.859

0.612

0.862

0.476

0.834

0.627

0.834

0.370

0.820

0.500

0.799

0.440

0.796

0.541

0.824

0.476

0.762

0.521

0.762

0.335

0.948

0.860

0.949

0.489

Cronbach’s alpha

a AVE = λ 2 /n (number of items i = 1, …, n; λ : standardized factor loading) i i b CR = (λ )2 / [(λ )2 + (δ )2 ] (number of items i = 1, …, n; λ : standardized factor loading; i i i i

δi : error term) c The highest squared correlation between the factor of interest and the remaining factors

with each of the loadings of the indicators are examined. Some of M.I. are high, indicating cross loading, such as the covariance error terms between C4 and S4 (20.997). These high values indicate a high degree of covariance between these two items that are not captured by the construct. Nevertheless, given the high loading estimates for each indicator and the variable deletion leading to violating the three-indicator rule (S4) so they are retained. Finally, construct, convergent, discriminant and nomological

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validity are confirmed, indicating strong evidence that the proposed latent factors meet rigorous tests of these types of validities. 3.5.2

Confirmation Factor Analysis (CFA)

After the constructs were confirmed as reliable and valid, the structural model results were assessed. According to Hair et al. (2019), Anderson and Gerbing (1988), a two-step SEM process consisting of one measurement model fit and one structural theory is appropriate for testing the hypothesised structural model. Following this suggestion, CFA is conducted, then the hypothesised model is tested. The fit indices of both the measurement and structural model fit the data satisfactorily and suggest that the theoretical model has an adequate level of empirical support when the sample is larger than 250, the number of the measured variables are more than 30 (Hair et al., 2019; Tabachnick & Fidell, 2013), as seen in Table 3.6. Following the above tests, the SEM procedures are applied to estimate the causal relations between the constructs to test the previously stated hypotheses (H1–H6). All of the proposed hypotheses are significantly supported at the 0.05 and 0.001 levels (two-tailed) (Table 3.7). The results of the hypothesised structural model are depicted in the following figure (Fig. 3.2).

3.6

Discussion

The first objective of this study, which sought to determine the impact of CSFs on FSMS implementation consisting of HACCP, prerequisite programs and other activities related to food safety guarantee at food production, is identified by empirical evidence. In detail, there are twenty-two indicators of six CSFs are investigated and identified from the three levels of the organisation, market, and governance. The hypotheses testing results reveals that the organisational level of CSFs include ‘management responsibility’ (managers’ commitment, responsibilities and authorities, FS policy, FS culture), ‘Human resource’ (employees’ involvement, training programs, personnel’s awareness, employees’ knowledge, and skills) and ‘other organisational resources’ (qualified equipment and facilities, technological and financial conditions) make significant contributions to FSMS implementation of the surveyed firms.

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Table 3.6 Model fit indices for CSFs, measurement, and structural models Fit indices Absolute fit indices Chi-square ( 2) Degrees of freedom (df) Probability level Root Mean Square Residual (RMR) Root Mean Square of Approximation (RMSEA) Normed chi-square ( 2/df) Incremental fit indices Incremental Fit Index (IFI) Tucker-Lewis coefficient (TLI) Comparative Fit Index (CFI) Parsimonious fit indices Parsimonious Normed Fit Index (PNFI) Goodness of Fit Index (GFI)

CSFs model

Measurement and structural model

Acceptable fit indices

285 194 0.000 0.041

348.377 254 0.000 0.038

0≤

p < 0.05 0.90

0.766

0.922

>0.5

0.923

0.918

>0.5

2 ≤ 2df

Among all organisational indicators of CSFs, FS policy, employees’ knowledge and skills, technological condition are taken into account as the most critical impact indicator in each construct. In addition, it is interesting to note that the construct ‘Management responsibility’ has the most significant impact on FSMS implementation, according to the SEM results. Contributing to the extensive research on CSFs, the finding of these internal CSFs further confirm previous studies identified by Fotopoulos et al. (2009), Mensah and Julien (2011), Kafetzopoulos and Gotzamani (2014), Kirezieva, Luning et al. (2015). Nonetheless, this study identifies additional latent constructs and clarifies the critical roles of each factor instead of equally considering their importance in the implementation of FSMS. The above results provide a vital managerial message

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Table 3.7 Hypotheses testing results Relationships H1: Management responsibility ➞ FSMS implementation H2: Human resource ➞ FSMS implementation H3: Organisational resources ➞ FSMS implementation H4: Collaboration ➞ FSMS implementation H5: Support ➞ FSMS implementation H6: FS Governance ➞ FSMS implementation

Standardised regression weights

SE

p-Value

Hypothesis test results

0.183

0.082

0.008

Accept

0.121

0.065

0.045

Accept

0.144

0.068

0.017

Accept

0.241

0.081

0.000

Accept

0.212

0.104

0.000

Accept

0.171

0.088

0.030

Accept

to those who want to improve FSMS within their firms by paying more attention and prioritising improving these organisational factors. Regarding the CSFs of market level, ‘Support’ (from government and authorities, business associations and stakeholders in SC), ‘FS governance’ (audits and inspections, stimulus, sanction, education, and information), and ‘Collaboration’ (information exchange, solving emerging problems, setting plan and goal, continuous improvement program) significantly show their critical contributions to FSMS implementation. Contrary to expectations, this study confirms a larger contribution of the market factors, including Collaboration and Support to FSMS implementation than other organisational factors according to SEM results at the surveyed firms. This outcome is contrary to the work of Kafetzopoulos and Gotzamani (2014) that found the organisational attributes greatly contributing to the effectiveness of ISO 9001 and HACPP system while the external environment did not. On the other hand, it is consistent with the study of Kirezieva, Luning et al. (2015), who confirmed collaborative/supportive

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Fig. 3.2 The structural model

supply chains and the roles of sector organisations and non-governmental organisations (NGOs) that contribute to more advanced FSMS and good system output. Likewise, Nanyunja et al. (2016) demonstrate how other stakeholders of supply chains influence FSMS in Kenya and Uganda. There is an apparent shift in more advanced FSMS and higher system output between farms and trade companies in Kenya to respond to the demand for strict voluntary food safety standards from large retailers supplying the EU premium market. Our analysis supports the arguments of Lu et al. (2021) when they identify and prioritise key institutional and operational factors for improving food safety in Chile using a Fuzzy analytic hierarchy process. Similarly, they also provide detailed and prioritised criteria for improving food safety practices, helping managers

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understand the operational and institutional environment. Their results contribute to informing food organisations and government policymaking to reduce food losses and improve the sustainability of food chains under fuzzy situations. Apart from these studies, most of the existing studies are limited to the impact of CSFs in the organisational environment on FSMS implementation, leaving the other two environments of FSMS insufficient understanding (Mensah & Julien, 2011). Hence, this is the first study to stress the strong impact of external factors on FSMS implementation while simultaneously considering all organisation, sector, and governance levels. Also, it clarifies the level of these firms collaborating with their stakeholders and what sources of support critically impact FSMS implementation. Therefore, these findings have important implications for food firms to increase their concentration on working with their stakeholders in the SC toward food safety issues and other parties in the market. Also, the results suggest that government and authorities and business associations should enhance their activities in supporting firms and governing FSMS implementation. It represents the major contribution of this study to the existing literature in the area.

3.7

Conclusion

The quantitative study is designed in this chapter to fulfil the research gaps identified in the previous chapter. In particular, a serial of analysis techniques is conducted, including EFA, CFA, SEM, to detect the most critical factors to FSMS implementation, their relationships among more than 300 food manufacturers and exporters in the two countries, China and Vietnam. We have answered the research question in this chapter about whether and to what degree CSFs influence FSMS at firms in the context of global supply chains . The investigation of CSFs on FSMS implementation consisting of HACCP, prerequisite programs and other activities related to food safety guarantee at food production has shown that there are six CSFs constituted by management responsibility, human and other organisational resources, food-safety governance, external support, and collaboration in the supply chains. Among all internal indicators of CSFs, FS policy, employees’ knowledge and skills, technological condition are proved as the most critical impact indicator

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in each construct, and the factor of ‘Management responsibility’ has the most significant impact on FSMS implementation. In the midst of the external CSFs group, ‘external support’ (from government and authorities, business associations and stakeholders in SC), ‘FS governance’ (audits and inspections, stimulus, sanction, education, and information) and ‘collaboration’ (information exchange, solving emerging problems, setting plan and goal, continuous improvement program) significantly show their critical contributions to FSMS implementation. Unexpectedly, this study confirms more considerable contributions of the external factors to FSMS implementation than the internal factors according to the SEM results at the surveyed firms. Other than that, the level of these firms collaborating with their stakeholders and support from stakeholders, government, and authorities, as well as business associations, critically impact on firm’s FSMS implementation. This also raises the critical roles of other parties such as government, authorities, and business associations in global supply chains. More significant efforts are needed to enhance their activities in supporting and governing food firms’ FSMS implementation. The discussion of insights into managing FSMS implementation by a more effective mechanism enabling continuous improvement opportunities for the current FSMS implementation based on the identification of CSFs presented in this study has specified several crucial future research directions for researchers. First, the findings and discussion of this study suggest that there are still gaps and many promising research directions needed in designing and establishing instruments for evaluating the implementation of FSMS. The most important requirement is that the outcomes of these measures should lead to clear improvement areas for firms’ current practices to ensure safe food for final consumption. Future work in this area can examine and construct more diagnostic tools to assess FSMS implementation. Second, more CSFs from all levels of organisation, sector and governance simultaneously should be identified to reduce the complexities of decision-making and managing FSMS to facilitate food firms’ managers toward a safer global food supply chain. Finally, the important contribution of external factors should be further investigated to clarify the role of supportive and collaborative supply chains to FSMS implementation.

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of food safety management systems in the fresh produce chain. Trends in Food Science & Technology, 32(2), 108–127. Kok, M. S. (2009). Application of food safety management systems (ISO 22000/HACCP) in the Turkish poultry industry: A comparison based on enterprise size. Journal of Food Protection, 72(10), 2221–2225. Lakhal, L., Pasin, F., & Limam, M. (2006). Quality management practices and their impact on performance. International Journal of Quality & Reliability Management, 23(6), 625–646. Liu, P. (2009). Private standards in international trade: Issues and opportunities. Paper Presented at the WTO’s Workshop on Environment-Related Private Standards, (July), 1–22. Lu, H., Mangla, S. K., Hernandez, J. E., Elgueta, S., Zhao, G., Liu, S., & Hunter, L. (2021). Key operational and institutional factors for improving food safety: A case study from Chile. Production Planning & Control, 32(14), 1248–1264. https://doi.org/10.1080/09537287.2020.1796137 Luning, P. A., Bango, L., Kussaga, J., Rovira, J., & Marcelis, W. J. (2008). Comprehensive analysis and differentiated assessment of food safety control systems: A diagnostic instrument. Trends in Food Science and Technology, 19(10), 522–534. Luning, P. A., Kirezieva, K., Hagelaar, G., Rovira, J., Uyttendaele, M., & Jacxsens, L. (2015). Performance assessment of food safety management systems in animal-based food companies in view of their context characteristics: A European study. Food Control, 49, 11–22. Macheka, L., Manditsera, F. A., Ngadze, R. T., Mubaiwa, J., & Nyanga, L. K. (2013). Barriers, benefits and motivation factors for the implementation of food safety management system in the food sector in Harare Province, Zimbabwe. Food Control, 34(1), 126–131. Macheka, L., Spelt, E., van der Vorst, J. G. A. J., & Luning, P. A. (2017). Exploration of logistics and quality control activities in view of context characteristics and postharvest losses in fresh produce chains: A case study for tomatoes. Food Control, 77 , 221–234. Mensah, L. D., & Julien, D. (2011). Implementation of food safety management systems in the UK. Food Control, 22(8), 1216–1225. Mortimore, S., & Wallace, C. (2013). HACCP: A practical approach. https:// doi.org/10.1007/978-1-4614-5028-3 Nanyunja, J., Jacxsens, L., Kirezieva, K., Kaaya, A. N., Uyttendaele, M., & Luning, P. A. (2016). Shift in performance of food safety management systems in supply chains: Case of green bean chain in Kenya versus hot pepper chain in Uganda. Journal of the Science of Food and Agriculture, 96(10), 3380–3392. Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill.

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Xiong, C., Liu, C., Chen, F., & Zheng, L. (2017). Performance assessment of food safety management system in the pork slaughter plants of China. Food Control, 71, 264–272. Yapp, C., & Fairman, R. (2006). Factors affecting food safety compliance within small and medium-sized enterprises: Implications for regulatory and enforcement strategies. Food Control, 17 (1), 42–51. Yiannas, F. (2009). Food safety culture. In Intergovernmental Panel on Climate Change (Ed.), Food Technology (Vol. 66). Springer. https://doi.org/10. 1007/978-0-387-72867-4

CHAPTER 4

Practices of Supplier Selection and Collaborative Supply Chain Relationships for Food Safety Management

Abstract The research objective of this chapter is to conduct a comparative analysis among the studied firms to identify Best Practice based on FSMS performance from Chapter 3. Then, the differences among them in terms of CSFs, supplier selection criteria, and supply chain relationships are explored to inform and suggest potential improvement areas where the studied firms could pay more attention to improving their current practices. This study adopts a two-step cluster analysis, which includes two steps allowing the advantages of the hierarchical method is complemented by the ability of the non-hierarchical method. In addition, multivariate analysis of variance (MANCOVA) technique is used to compare the identified groups from the findings of cluster analysis regarding their CSFs, the practices of supplier selection, and SC relationships. Keywords Supplier selection · Collaboration · Cluster analysis

4.1

Introduction

In their review, Marucheck et al. (2011) raise the issue of the management of supplier relationships potentially leading to safety problems since companies have outsourced manufacturing to developing countries © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 T. T. B. Nguyen and D. Li, Towards Safer Global Food Supply Chains, https://doi.org/10.1007/978-3-030-93356-2_4

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worldwide under pressures for lower costs combined with the additional complexity of the supply chain. Fynes et al. (2005) and Whipple et al. (2009) also identify the role of supplier selection and relationship in the food supply chain. As a result, with the aim of enhancing food safety, it is needed to investigate whether the groups that have better FSMS implementation, which has been identified in the previous chapter, pay more attention to safety criteria in supplier selection and are in a better SC relationship than their counterparts. Hence, the research objective of this chapter is to conduct a comparative analysis among the studied firms to identify Best Practice based on FSMS performance from the previous chapter. Then, the differences among them in terms of CSFs, supplier selection criteria, and supply chain relationships are explored to inform and suggest potential improvement areas where the studied firms could pay more attention to improving their current practices. Regarding the research method of this chapter, cluster analysis, which is the classification of data by natural groupings of the data themselves, is the appropriate method to analyse the data for this study. In general, cluster analysis is a group of multivariate techniques whose primary purpose is to group objects based on their characteristics, which are food companies in this case. There are two popular methods to use in cluster analysis: hierarchical or non-hierarchical methods. Each method has its pros and cons. Hence, several researchers recommend the combination approach using both methods to compensate for the weaknesses of the other (Hair et al., 2019; Milligan, 1980). This study adopts a two-step cluster analysis, which includes two steps allowing the advantages of the hierarchical method is complemented by the ability of the non-hierarchical method. In addition, multivariate analysis of variance (MANCOVA) technique is used to compare the identified groups from the findings of cluster analysis regarding their CSFs, the practices of supplier selection, and SC relationships. The rest of the chapter is structured as follows. The next section presents the research frame-work of the chapter related to supplier selection and supply chain relationship (Sect. 4.2). The two-step cluster analysis is the research methodology is presented in Sect. 4.3. In Sect. 4.4, identify Best Practice among the studied firms and explore their differences in terms of CSFs, supplier selection criteria, and supply chain relationship. In the discussion, the research results and implications are considered before reaching the study’s conclusion.

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4.2 4.2.1

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Theoretical Framework

Supplier Selection in Food Safety Management

Whether to make or buy a new product or service is the first decision that must be made in managing the supply chain, which determines where and how the supply chain will be managed following by other steps, such as purchase, movement, and storage of raw materials (Schoenfeldt, 2008). The characteristics of food supply chains are exceptional due to the continuous change in the quality of raw materials. The shelf-lives of raw, intermediate and final goods, together with the strong uncertainties in the whole chain, is a significant challenge for proper supply chain management and planning (Ahumada et al., 2012). Therefore, it requires firms to consider various aspects to make the decision; for instance, the quality and price are assumed higher for fresher raw materials from the local area. In contrast, a similar product with a low remaining shelf-life and produced with mainstream raw materials have lower quality and price (Oberholtzer et al., 2014). Given the significance of managing the supply chain and input purchasing in FSMS, food firms need to decide which suppliers to collaborate with and how to select suppliers is a very crucial decision for FSMS. In addition, other criteria that are not related to food safety requirements are selected as a result of the current literature (Table 4.1) in the research context of global food supply chains. They are price as the presentative for financial perspective, after-sale service (i.e., policy, quality assurance, and damage ratings), order flexibility (i.e. payment, freight, order frequency and amount), and distance (local or not). Table 4.1 Criteria of supplier selection in the literature References

Criteria for supplier selection

Weber et al. (1991)

Price, delivery, facilities and capacity, geographic location, technology capability Quality, delivery, price, repair service, technical capability Quality, delivery, price/cost, manufacturing capability, service, management, technology Quality, delivery, price Finance, delivery and service, quality, environment management system

Cheraghi et al. (2004) Ho et al. (2010) Thiruchelvam and Tookey (2011) Banaeian et al. (2015)

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4.2.2

The Impact of Supply Chain Relationship on FSMS

Matopoulos et al. (2007) propose that two pillars of the framework for supply chain collaboration are the design and the government of supply chain activities accompanied by the establishment and maintenance of supply chain relationships. Mutual trust, long-term commitment and interdependency are characteristics of a successful relationship needed to maintain among supply chain partners. In a supply chain context, trust is ‘the degree to which the channel member perceives that its relationship with the supplier is based upon mutual trust and thus is willing to accept short-term dislocation because it is confident that such dislocation will balance out in the long-run’ (Anderson et al., 1987). Commitment can be defined as the willingness of each partner to exert effort on behalf of the relationship and firms’ attempt to build a relationship that can be sustained in the face of unanticipated problems (Gundlach & Cadotte, 1994). Interdependency reflects the firm’s need to maintain a relationship with the partner to achieve its goals and the firm’s inability to replace a partner (Kumar et al., 1995). Altogether, these dimensions establish a business relationship that determines the degree to which each party perceives they can depend on the integrity of the promise offered by the other (Ding et al., 2014; Fynes et al., 2005). There are many studies on the SC relationship and quality management. For example, Fynes et al. (2005) study the impact of the various dimensions of SC relationships (such as trust, commitment, adaptation, communication and collaboration) SC relationships on quality performance and conclude that by focussing on the management of SC relationships organisations can also improve product quality. In the same manner, Ding et al. (2014) confirm that strategic alliance, information quality, trust, and commitment are significantly related to food quality. A summary of criteria to select suppliers and SC relationships is presented in the below table as research constructs (Table 4.2).

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Table 4.2 Research construct Construct

Measurement item

References

Criteria to select suppliers

Lower price

Burke et al. (2009), Cheraghi et al. (2004), Ho et al. (2010), Weber et al. (1991) ISO (2005), Russo et al. (2014), Xiong et al. (2017) Weber et al. (1991) Burke et al. (2009), ISO (2005) ISO (2005), Tran et al. (2013) Verma and Pullman (1998) Banaeian et al. (2015) Anderson et al. (1987), Ding et al. (2014), Fynes et al. (2005), Matopoulos et al. (2007), Whipple et al. (2009) Ding et al. (2014), Fynes et al. (2005), Gundlach and Cadotte (1994), Whipple et al. (2009) Fynes et al. (2005), Kumar et al. (1995)

Certificates fulfilment Distance Reliability Good self-inspection results

Supply chain relationships

Order flexibility After-sale service Trust

Commitment

Interdependency

4.3

Cluster Analysis

Cluster analysis is applied for data simplification, taxonomy description and relationship identification (Hair et al., 2014) among the studied firms in Chapter 3 regarding their status of FSMS implementation. In detail, the objectives of cluster analysis are to (1) identify the best practice, (2) explore the differences in their CSFs that affect FSMS implementation, and (3) investigate the practices showing how these firms manage their suppliers. This approach has been applied in many previous studies to analyse the difference among various groups of respondents (e.g. Kirezieva, Nanyunja, et al., 2013; Kirezieva et al., 2015; Macheka et al., 2017; Nguyen & Li, 2018). In this section, 310 observations from the previous chapter are classified into manageable groups based on their FSMS implementation. After that, their similarities and differences are analysed further to examine firms’ characteristics and CSFs for FSMS.

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4.3.1

Identifying Cluster Solution

Several researchers recommend the combination approach using two-step cluster analysis to compensate for the weaknesses of both hierarchical and non-hierarchical cluster analyses (Hair et al., 2019; Milligan, 1980). First, a hierarchical technique is applied as the partitioning stage to produce a complete set of cluster solutions, establish the appropriate cluster solutions and the appropriate number of clusters. Then, a non-hierarchical method follows to refine the results by allowing the switching of cluster membership and validating the final cluster solution. Step 1: Hierarchical clustering analysis Hierarchical procedures involve a series of n−1 clustering decisions (where n equals the number of observations) that combine observations into a hierarchy or a tree-like structure based on the similarity among members (Hair et al., 2019). Given the need for a repetitive clustering process combined with a clustering algorithm to define the similarity between clusters with multiple members and the moderate sample size (under 400 observations in this study), hierarchical clustering procedure is suitable to apply using the Ward Linkage and Squared Euclidean distance measure with FSMS implementation as the clustering criteria variable. The score of FSMS implementation is constructed as a weighted factor-based scale using all of the variables and taking their factor loadings into account instead of simply adding up all scores as the suggestion of de Vaus (2002). The use of a weighted factor-based score reflects a natural relationship in the scaling of the variables. In this study, FSMS implementation is constructed by the mean of HACCP, PRP and OA variables. Instead of simply adding up all the scores, a weighted factor FSMS implementation uses all of the variables and considers their factor loadings. Therefore, grounded on the factor loading column in the results of CFA (Table 3.5), the equation used to compute the variable ‘FSMS implementation’ is as the following: FSMS Implementation = 0.942HACCP + 0.901PRP + 0.935OA Considering that a natural increase in heterogeneity comes from the reduction in the number of clusters and one-member or extremely small clusters are not acceptable and should be eliminated. The Dendrogram results suggest that four or five clusters are the possible outcome according to the grouping branches in Fig. 4.1 (four-cluster solution numbered in red and five-cluster solution numbered in blue). Also, the

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Fig. 4.1 Dendrogram using Ward Linkage

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changes in agglomeration coefficient (Table 4.4) indicate that moderately homogeneous clusters are being merged with small coefficients, whereas joining two very different clusters results in a large coefficient (Hair et al., 2019). In addition, the membership distribution (Table 4.3) shows that the solutions of four or five clusters have more reasonable number of firms in each cluster (Table 4.4). Step 2: Non-hierarchical clustering analysis and the validation In this step, both four-cluster and five-cluster solutions, which are the specified cluster seed points as the result of the hierarchical process, are used to execute non-hierarchical clustering in K-mean cluster. In the case of the five-cluster solution, cluster 5 has a relatively small number of members (14) compared to the rest. Therefore, the four-cluster solution Table 4.3 Cluster membership distribution Cluster 1 2 3 4 5 6

6 Clusters

5 Clusters

4 Clusters

3 Clusters

2 Clusters

55 51 71 83 36 14

55 51 71 83 50

55 122 83 50

55 122 133

177 133

Table 4.4 Agglomeration schedule Stage

300 301 302 303 304 305 306 307 308 309

Cluster combined

Coefficients

Cluster 1

Cluster 2

2 6 8 1 3 6 2 3 1 1

4 134 30 21 13 140 8 6 2 3

23.991 29.324 37.564 48.651 62.567 90.005 139.845 322.617 518.063 1596.816

*** Note Stage 1–299 have been omitted from the table

Stage cluster first appears Next stage Cluster 1

Cluster 2

287 292 295 297 298 301 300 304 303 308

289 279 288 294 296 299 302 305 306 307

306 305 306 308 307 307 308 309 309 0

4

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Table 4.5 Comparing the number of cases in each cluster in two steps Cluster

Hierarchical cluster (First step)

K-mean (Second step)

5 clusters solution

4 clusters solution

5 clusters solution

4 clusters solution

55 51 71 83 50

55 122 83 50

62 89 99 46 14

81 96 83 50

1 2 3 4 5

is the most suitable one in this study. Comparing the two steps, there are the same cases in clusters 3 and 4, while there are significant changes in clusters 1 and 2 in the four-cluster solution (Table 4.5). Turning now to the validation, two tests are conducted to confirm the validity of the four-cluster solution while also ensuring it has practical significance following the suggestions of Hair et al. (2019). First, the stability of the cluster solution is assessed by sorting the observations in a different order and then, the cluster analysis is performed once again with the same number of clusters specified. The results reveal mostly matches between the two solutions. Second, criteria validation is also assessed to test predictive validity by using variables that have a theoretically based relationship to the clustering variables but were not included in the cluster solution. A one-way between-groups multivariate analysis of variance (MANOVA) is conducted to verify the clustering result using three FSMS-related variables, including the means of HACCP, PRP and OA and one independent variable (K-mean cluster membership). The overall F -statistic for the MANOVA (F (3, 306) = 1166.243, p = 0.000; Wilks’ Lambda = 0.08; partial eta squared = 0.92), as well as the univariate F statistics, are all significant, thus providing evidence of criterion validity in the four-cluster solution (Table 4.6).

4.4

Best Practice Identification

In order to identify Best practice, an inspection of the mean scores of FSMS implementation and HACCP, PRP, and OA indicates that cluster 1 reports the highest level of FSMS implementation (M = 12.6366, SD = 0.72) as well as the mean of HACCP, PRP, OA than other clusters

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(Figs. 4.2 and 4.3). The mean of FSMS implementation of clusters 2, 3 range from 10.46 to 6.179 and cluster 4 has the lowest mean −6.179. The mean scores of HACCP, PRP and OA of each cluster are displayed in Fig. 4.3. Based on the score of FSMS implementation, four clusters are classified as the followings: Cluster 1—‘Best Practice’ group (81 firms), Cluster 2—‘Good Practice’ (96 firms), Cluster 3—‘Average’ (83 firms), Cluster 4—‘Poor Practice’ (50 firms). The next task is to profile the four clusters to determine the characteristics of each cluster. 4.4.1

Profiling the Identified Groups

To clarify the differences among the groups, MANOVA is conducted on their profile variables. Significant chi-square values are observed for three of four profile variables except for the variable ‘kind of exporting food’ (Table 4.7). The results of the cross-classification are provided in Table 4.8. The ‘Best Practice’ group mainly includes large firms with limited liability (Ltd.) and joint-stock structure. The most popular type of food supply among groups are fisheries, fresh fruit, and vegetable. In this group, there are 37 fishery firms and 14 fresh products firms. The exporting capabilities of ‘Best Practice’ firms are remarkable since 24 firms are exporting more than 3000 tons per year, accounting for 58.54% of the sample are able to export at that amount. Meanwhile, 40 small and 38 medium firms primarily construct the ‘Good Practice’ group. There are 45 firms are Ltd., and 30 firms are private enterprises. The exporting capabilities of this group are mainly below 1000 tons per year, accounting for 78 firms over 96 firms in this group. The Average group consists of 64 Table 4.6 Univariate F -statistics results assessing cluster solution criterion validity Dependent variable HACCP PRP OA

Type III sum of squares

df

Mean square

F

Sig

Partial eta squared

1514.269 1363.448 1424.193

1 1 1

1514.269 1363.448 1424.193

13,730.910 8859.056 13,165.750

0.000 0.000 0.000

0.978 0.966 0.977

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FSMS IMPLEMENTATION 14.00 12.6366

12.00

10.4642

10.00

8.5992

8.00

FSMS

6.1790

6.00 4.00 2.00 0.00 1

2

3

4

Fig. 4.2 Comparing the FSMS implementation between clusters

1

2

3

4

Fig. 4.3 Comparing the means of HACCP, PRP, OA between clusters

2.2327

2.3125

2.1314

3.1019

OA

3.0663

PRP

3.1170

3.7547

3.7487

HACCP 3.7961

4.5410

4.4614

4.6402

FSMS ACTIVITIES

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Table 4.7 Multivariate F results for profile variables Variable

Univariate F*

Sig

7.352

0.000 0.000

4.175

0.006

1.94 2.17 2.54 2.72

8.693

0.000

2 3 4 1

2.21 2.41 2.84 2.59

2.003

0.114

2 3 4

1.82 1.67 2.42

Cluster number

Cluster mean

1 2 3 4 1

2.68 2.55 2.25 2.96 1.90

2 3 4 1

Multivariate F* 4.611

Size

Ownership structure

Average exporting/year

Kind of exporting food

* Multivariate F has 12 degrees of freedom, and univariate F s each has 3 degrees of freedom

SMEs, while there are only eight large and five micro firms. The dominant owner structure of this group is Ltd. (37 firms), and 13 firms are exporting more than 1000 tons per year. Similarly, Poor Practice group consists of 79 SMEs, but the number of micro firms accounting for 16 firms is the highest number among the groups. For the owner structure, this group contains mainly private enterprises and four cooperatives, the highest number for this type of ownership among the groups. The exporting capabilities of this group are the same as the Average group, mainly below 1000 tons per year. Surprisingly, Poor Practice group has 13 large firms, which are higher than the Good and Average groups. Private enterprise and ltd., are the most popular structures of this group.

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Table 4.8 Cross-classifications for firm’s characteristics Firm characteristics

Cluster

Size

Ownership structure

Average exporting tons/year

Kind of exporting food

4.4.2

1–10 employees 11–50 employees 51–250 employees > 250 employees Total Limited liability company Joint-stock company Private enterprise State-owned enterprise Cooperatives Others Total < 500 tons 500–1000 tons 1000–2000 tons 2000–3000 tons > 3000 tons Total Fishery Poultry Dairy Fresh fruit and vegetables Drinks and beverage Rice and grains Other Total

Total

1

2

3

4

11 29 16 25 81 33 28 16 3 1 0 81 33 16 7 1 24 81 37 7 8 14 5 6 4 81

7 40 38 11 96 45 18 30 1 1 1 96 54 24 7 3 8 96 58 5 6 18 4 1 4 96

16 34 29 4 83 33 11 35 0 4 0 83 54 15 6 3 5 83 43 6 7 18 5 1 3 83

1 13 23 13 50 17 7 18 2 2 4 50 12 18 11 5 4 50 13 10 8 11 7 1 0 50

35 116 106 53 310 128 64 99 6 8 5 310 153 73 31 12 41 310 151 28 29 61 21 9 11 310

Examining the CSFs of Each Group

To clarify differences among identified groups, MANOVA is conducted on their CSFs variables. The overall F -statistic for the MANOVA, as well as the univariate F -statistics (Table 4.9), are all significant on all clusters’ CSFs variables with F (66, 851.947) = 6.013, p = 0.000; Wilks’ Lambda = 0.319; partial eta squared = 0.317. The mean score of each cluster is also displayed in the table. A one-way between-groups MANOVA is performed to investigate each indicator of CSFs differences among the four groups. It can be seen that for most of the indicators, Best Practice has the highest mean score among

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Table 4.9 MANOVA results for all CSF indicators Variable Managers’ commitments

Food safety policy

Responsibilities and authorities

Food safety culture

Employees’ knowledge and skills

Awareness of the personnel

Training programs for employee

Employees’ involvement

Qualified facilities and equipment

Cluster number

Cluster mean

Univariate F*

Sig

1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1

4.06 3.69 3.43 2.52 4.16 3.60 3.33 2.26 3.98 3.71 3.34 2.70 4.02 3.52 3.43 2.60 3.91 3.85 3.37 2.40 3.77 3.76 3.30 2.34 3.88 3.85 3.29 2.58 3.78 3.77 3.20 2.54 3.90

31.416

0.000

44.917

0.000

25.899

0.000

24.348

0.000

31.978

0.000

26.514

0.000

26.468

0.000

22.547

0.000

26.151

0.000

2

3.70

(continued)

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85

Table 4.9 (continued) Variable

Financial condition

Technological condition

Food safety audits and inspections

Regulatory sanctions

Regulatory stimulus

Regulatory information and education

Support from business associations

Support from stakeholders in supply chains

Support from government and authorities

Information exchange

Cluster number

Cluster mean

3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1

3.43 2.58 3.96 3.73 3.61 2.88 3.94 3.77 3.43 2.40 3.94 3.82 3.27 2.24 3.85 3.67 3.33 2.32 3.79 3.65 3.14 2.52 3.69 3.45 3.02 2.62 3.56 3.32 2.99 2.40 3.41 3.14 2.77 2.36 3.88 3.60 3.28 2.74 3.47

Univariate F*

Sig

20.132

0.000

39.406

0.000

54.899

0.000

39.770

0.000

36.283

0.000

16.780

0.000

22.583

0.000

19.883

0.000

27.809

0.000

29.142

0.000

(continued)

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Table 4.9 (continued) Variable

Emerging problems

Planning and goal-setting activities

Continuous improvement programs

Cluster number

Cluster mean

2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

3.16 3.01 2.30 3.21 3.03 2.84 2.22 3.32 3.13 3.08 2.40 3.25 3.12 3.07 2.28

Univariate F*

Sig

19.249

0.000

15.314

0.000

18.250

0.000

the four groups, followed by Good Practice. The lowest mean scores for most of the indicators belong to Poor Practice group. From the mean score of each cluster presented in Table 4.9, internal CSFs and external CSFs will be discussed in detail in the below subsections. 4.4.2.1 Internal CSFs First, all internal CSFs are examined. The differences between the four groups are illustrated in Fig. 4.4. As can be seen from the figure, overall, the highest mean score of all CSFs belongs to Best Practice group, and the lowest belongs to Poor Practice group. The internal CSFs for each group range from 3.77 to 4.16 for Best Practice, from 3.52 to 3.85 for Good Practice, from 3.2 to 3.61 for Average, and from 2.26 to 2.88 for the last group. In detail, the mean score factor ‘Management responsibility’ of Best Practice significantly stands out among all factors and groups, ranging from 3.98 to 4.16. Meanwhile, the factor of Human resources and Organisational resources only shows a slight difference among the Best, Good and Average Practice groups, ranging from 3.77 to 3.96. The mean score of Poor Practice groups in all CSFs is far behind the rest in all indicators of the internal CSFs.

4

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PRACTICES OF SUPPLIER SELECTION AND COLLABORATIVE …

1

2

3

4

Managers commitments 4.50 Technological condiƟon

Food safety policy

4.00 3.50

Financial condiƟon

ResponsibiliƟes and authoriƟes

3.00 2.50 2.00

Qualified faciliƟes and equipment

Food safety culture

Employees’ knowledge and skills

Employees’ involvement Training programs for employee

Awareness of the personnel

Fig. 4.4 Internal CSFs among the groups

2.62 InformaƟon and educaƟon

3.02

2.52 SƟmulus 2.32

2.24

3.27

Audits and inspecƟons 0.50

Poor pracƟce

1.00 Average

Fig. 4.5 Food-safety governance

1.50

2.00

2.50

Good pracƟce

3.14

3.33

SancƟons

0.00

3.45 3.69

3.00

3.50

Best pracƟce

3.65 3.79 3.67 3.85 3.82 3.94 4.00

4.50

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4.4.2.2 External CSFs In the food-safety government, Fig. 4.5 demonstrates that the different gaps among the first three groups (lowest mean from 3.02 to highest mean 3.94) are relative, while the last group is far behind compared to the others. The mean score of the last group ranges from 2.24 to 2.62. Interestingly, while the first two groups agree that audits and inspections are the most impactful indicator of food-safety governance on FSMS implementation, they have different opinions on the lowest impact. According to Best Practice, the lowest impact is information and education, and Good Practice considers stimulus the lowest. Average group agrees with Best Practice on both the most and the least impact activities of food-safety governance. Poor Practice group shows different ranking perspectives on all four activities compared to the other groups, ‘information and education’ is the most critical impact indicator while ‘audits and inspects’ is the least critical to their FSMS implementation. Regarding support to FSMS, from Fig. 4.6, all the groups share the same point of view in emphasising the role of support from government and authorities on FSMS implementation despite the difference in its mean scores across the groups. Support from business associations is perceived as the second among three sources of support. Although support from stakeholders in the supply chain significantly impacts FSMS 4.50 4.00 3.50 3.00

3.88 3.56

3.41

3.32 2.99

2.50

2.77 2.40

2.00

3.60 3.28

3.14

2.74 2.36

1.50 1.00 0.50 0.00 Support from business associaƟons Best pracƟce

Fig. 4.6 Support

Support from stakeholders in supply chains Good pracƟce

Average

Support from government and authoriƟes Poor pracƟce

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PRACTICES OF SUPPLIER SELECTION AND COLLABORATIVE …

ConƟnuous improvement programs

3.25

3.13

3.07

2.28

3.32

3.13

3.08

2.40

Emerging problems

3.21

3.03

InformaƟon exchange

3.47

Planning and goal-seƫng acƟviƟes

0.00 Best pracƟce

2.00

Good pracƟce

2.84

3.16 4.00

6.00

Average

2.22 2.30

3.01 8.00

89

10.00

12.00

14.00

Poor pracƟce

Fig. 4.7 Level of collaboration in the supply chain

in the previous SEM analysis, it is the lowest impact factor among support factors. The level of collaboration in the supply chain is highest for the Best Practice group in all activities, especially information exchange, with the highest mean score of 3.47 (Fig. 4.7). It also determines solving emerging problems related to food safety is the lowest among the four indicators by the surveyed firms. The groups of Best and Good Practice share the same choice of the lowest indicator. While Average and Poor Practice make the same selections as they pay the most attention to the impact of planning and setting goals with their stakeholders on FSMS implementation than other activities.

4.5

Exploring the Aspects of Supplier Selection and SC Relationships

In this section, the practices of supplier selection and the quality of SC relationship are explored to investigate their relationships with FSMS implementation as well as the differences between groups. First, Pearson product-moment correlation coefficient is undertaken for the variables of FSMS implementation and the variable group of supplier selection and the quality of SC relationship. Generally, there are significant positive correlations between the variables at the 0.01 and 0.05 levels. The strength of correlations between FSMS implementation and the variables vary from weak to strong in Table 4.10. Cohen (1988) suggests r is weak if it is

FSMS Perform Price Certificates Distance Reliability Self-inspection Flexibility After-sale Trust Commitment Interdependency

Items

Correlations

1

– 0.124* 0.573** 0.202** 0.604** 0.618** 0.441** 0.467** 0.483** 0.555** 0.288**

Correlations

– 0.326** 0.381** 0.196** 0.211** 0.392** 0.308** 0.165** 0.182** 0.174**

2

3

– 0.271** 0.761** 0.733** 0.479** 0.520** 0.548** 0.621** 0.287**

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

1 2 3 4 5 6 7 8 9 10 11

No

Table 4.10

– 0.278** 0.200** 0.372** 0.362** 0.144* 0.199** 0.186**

4

– 0.706** 0.452** 0.555** 0.536** 0.613** 0.372**

5

– 0.433** 0.595** 0.610** 0.577** 0.412**

6

– 0.515** 0.333** 0.383** 0.383**

7

– 0.447** 0.465** 0.394**

8

– 0.747** 0.590**

9

– 0.535**

10

–

11

90 T. T. B. NGUYEN AND D. LI

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PRACTICES OF SUPPLIER SELECTION AND COLLABORATIVE …

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below 0.3; medium r ranges from 0.3 to 0.49, and r more than 0.5 means a strong relationship. The correlational analysis indicates that certificates, reliability, selfinspection results are strongly correlated to FSMS implementation, with high levels of selecting suppliers using these criteria associated with higher levels of FSMS implementation. Criteria, such as flexibility and after-sale services are medium (r = 0.441 and r = 0.467) correlated to FSMS implementation while price and distance are the weakest criteria that are correlated to FSMS implementation, r = 0.124 and r = 0.202 respectively. In terms of SC relationship, commitment is the strongest element (r = 0.555) related to high FSMS implementation. Trust is medium (r = 0.483) and interdependency shows the weakest correlation to FSMS implementation (r = 0.288). Then, a MANOVA model is also conducted to investigate the differences between groups considering the criteria of supplier selection and SC relationships. MANOVA model is selected because the dependent variables are known to correlate with each other. The overall MANOVA model is significant (F (30, 872.43) = 10.581, P = 0.000, Wilks’ Lambda = 0.402, partial eta squared = 0.262) and the individual univariate F -statistics are also significant as the results in Table 4.11. Based on the MANOVA results, the differences between the groups considering Table 4.11 Multivariate F results Dimensions

Dependent variable

Criteria of supplier selection

Price Certificates Distance Reliability Self-inspection results Flexibility After-sale service Trust Commitment Interdependency

SC relationship

Type III sum of squares

df

Mean square

F

Sig

Partial eta squared

4225.318 4170.308 4135.818 4094.023 4117.774

1 1 1 1 1

4225.318 4170.308 4135.818 4094.023 4117.774

4671.019 5581.100 6341.139 6150.068 6092.257

0.000 0.000 0.000 0.000 0.000

0.939 0.948 0.954 0.953 0.952

3801.903 3284.783 4148.278 3851.060 3192.707

1 1 1 1 1

3801.903 3284.783 4148.278 3851.060 3192.707

5976.445 4590.697 5334.242 4541.829 3058.959

0.000 0.000 0.000 0.000 0.000

0.951 0.938 0.946 0.937 0.909

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Table 4.12 The differences between the groups in supplier selection Group

Price Certificates Distance Reliability Self-inspection

Flexibility

Aftersale

Best practice Good practice Average practice Poor practice

3.79

4.41

3.95

4.43

4.44

4.06

3.84

4.10

4.32

3.85

4.19

4.27

3.88

3.66

3.96

4.11

3.83

4.06

3.99

3.70

3.54

3.36

2.28

3.42

2.30

2.32

2.80

2.38

the practices of supplier selection and the quality of SC relationship are revealed in the table and figure (Table 4.12). Best Practice selects their suppliers based on the reliability and the result of the inspections that they examined themselves first as well as certificates that suppliers possess. Good Practice group is likely to select suppliers based on self-inspection results. Good and Average Practice groups prioritise certificates to select suppliers. The most noticed result from the data is that Poor Practice prefers local and cheaper suppliers than the other selection criteria. Moreover, the SC relationship of Best Practice has the highest mean score with a high level of commitment (Fig. 4.8). While the other groups have a higher level of trust than commitment, and the interdependency is the lowest score across the groups. Both commitment and trust are strongly correlated to FSMS implementation, as the above results of the correlational analysis. Poor Practice has the lowest score of all SC relationship indicators. It shows a different pattern in their SC relationship than the rest because its interdependency has a higher score than commitment. Also, the mean gap between each indicator is relatively narrower than the other groups, about 0.2. In conclusion, the groups of firms that have better FSMS implementation pay more attention to food safety criteria than others and are in better SC relationship than their counterparts considering the correlation, the mean score and comparisons among the groups of this study in terms of criteria to select suppliers and their SC relationship.

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PRACTICES OF SUPPLIER SELECTION AND COLLABORATIVE …

Best pracƟce

Good pracƟce

2.66

Average

93

Poor pracƟce

2.40 2.64

4.02

3.75 3.45 4.07

4.14

3.56

4.26

4.31

3.58

Trust

Commitment

Interdependency

Fig. 4.8 SC relationship among the groups

4.6

Discussion

The research stream on CSFs for FSMS implementation has been mostly restricted to confirming their presence by empirical studies or qualitative analyses. To the best of our knowledge, none of the studies is able to suggest potential improvement opportunities through assessing the impact of CSFs on FSMS implementation contingent on the system status of each enterprise. Respond to these needs, apart from EFA, CFA and SEM used to investigate the determinants from the previous chapter; cluster analysis is applied in this chapter to classify all the sampled companies into distinctive groups based on their FSMS implementation. Then, the significant MANOVA on all clusters’ CSFs variables confirms that the CSFs vary across food firms depending on their different FSMS implementation (Research objective 3). This work is associated with the study of Tzamalis et al. (2016) to develop a tool providing a ‘best practice’ among the studied firms based on factors influencing the FSMS implementation. It is particularly beneficial for pointing out the differences between firms of different groups and identifying their potential improvement areas contingent on the status of FSMS implementation.

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T. T. B. NGUYEN AND D. LI

For example, Best Practice group has the finest practice overall, such as the factor ‘Management responsibility’, which is outstanding and has the highest internal impact on FSMS implementation. The comparison between Best Practice and the others offers constructive suggestions regarding improvement opportunities in many aspects (Fig. 4.9). Closer inspection of the figure shows that the Good and Average Practice groups should improve their management responsibility since their gaps with the Good Practice are apparent. For the Good Practice group, the gaps between it and the Average group indicate that human resources, in particular, more training programmes for employees should be prioritised to improve by firms. The case of Poor practice is more complicated since it has the lowest score across all factors. However, this group is mainly private enterprises with low exporting capabilities, as mentioned in Sect. 4.4.1. Therefore, it is impossible to improve everything at the same time. Alternately, these research results suggest that it should prioritise improving FS policy and awareness of the personnel within the firm, which is more critical to their FSMS implementation. Best pracƟce

Good pracƟce

Average

4.50 4.00 3.50 3.00 2.50 2.00 1.50

Fig. 4.9 The overall mean score of all indicators

Poor pracƟce

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PRACTICES OF SUPPLIER SELECTION AND COLLABORATIVE …

95

Furthermore, it is interesting to note that managers in any group could identify which area to improve based on the comparison between its score and the mean score of the group root on the cluster analysis results. For instance, there are four firms randomly picked from each cluster in Table 4.13. Comparing them to the mean score of each cluster offers some practical suggestions. Overall, the firm VN169’s practice is good compared to other firms in the same group. However, it should pay attention to setting up clear responsibilities and authorities in managing food safety in its company. Contrary to VN169, VN167 needs to make many efforts in management responsibility and increase employees’ involvement since most of them are far lower than the group’s average. Moreover, its facilities, financial and technological condition are beneath compared to most firms in the group. However, these data must be interpreted with caution because of the possible bias in the managers’ perceptiveness. The implication of these findings provides a novelty approach to identify potential factors to improve that directly impact FSMS implementation. Hence, food businesses apply the viewpoint of CSF as a more proactive approach to identify the mechanism enabling continuous improvement strategies for the current FSMS implementation, particularly for SMEs with finite resources. A further study with more focus on the different status of FSMS implementation is therefore suggested. 4.6.1

Criteria of Supplier Selection

Concerning the research objective of this chapter, it is found that each group has different priority criteria and the level of trust, commitment and interdependence with their suppliers. A Pareto or sorted histogram chart containing the mean score columns sorted in descending order and a line representing the cumulative total percentage is conducted to highlight the most popular criteria these firms used to choose suppliers (Fig. 4.10). The Pareto chart shows that the studied firms primarily choose their suppliers based on reliability, certificates, self-inspection results, flexibility, and distance, considering after-sale service and price as the least-wanted criteria. This finding provides empirical support for confirming that firms prioritise safety criteria more than the other criteria in selecting suppliers. On the other hand, comparing the groups shows the most interesting aspect of the different selecting criteria. The group of Poor practice reveals its contrary trend in evaluating distance, price, and flexibility to be more

4

3

2

1

VN169 Mean VN167 Mean VN175 Mean VN168 Mean

Management responsibility

Group Firm

Other resources

5 4.06 2 3.69 3 3.43 3 2.52

5 4.16 1 3.60 3 3.33 4 2.26

3 3.98 2 3.71 4 3.34 4 2.70

5 4.02 1 3.52 3 3.43 4 2.60

4 3.91 4 3.85 5 3.37 2 2.40

4 3.77 4 3.76 4 3.30 3 2.34

4 3.88 4 3.85 4 3.29 3 2.58

4 3.78 1 3.77 4 3.20 4 2.54

4 3.90 1 3.70 4 3.43 3 2.58

4 3.96 2 3.73 4 3.61 4 2.88

4 3.94 2 3.77 4 3.43 4 2.40

Commitments Policy Responsibilities Culture Knowledge Awareness Training Involvement Facilities Finance Technology

Human resource

Internal CSFs of five random firms in the research sample

Table 4.13

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PRACTICES OF SUPPLIER SELECTION AND COLLABORATIVE …

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Fig. 4.10 Pareto chart of supplier selecting criteria

critical than the other groups. In comparison, the rest shares the same tendency in the selecting order of these criteria. A closer inspection shows that Good Practice is likely to choose its suppliers based on inspection results and reliability; this mean score is the highest among the four groups. Overall, it is concluded that the groups with better FSMS implementation pay more attention to safety criteria since their mean scores for these criteria are higher than others (Fig. 4.11). 4.6.2

The SC Relationship

Regarding the SC relationship, the analysis shows higher levels of trust and commitment than interdependency among the studied companies with their suppliers as a whole (Fig. 4.12). One interesting finding is the commitment from Best and Good practice that has a higher commitment level than trust, which is different from the rest. It can be seen that the level of commitment, trust and interdependency are in descending order following the score of FSMS implementation of each group. The correlational analysis also points out that commitment is the strongest element related to high FSMS implementation, whereas trust is medium, and interdependency shows the

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T. T. B. NGUYEN AND D. LI

Best pracƟce

Good pracƟce

Average pracƟce

Poor pracƟce

5.00 4.50 4.00 3.50 3.00 2.50 2.00 1.50 1.00 0.50 0.00 Price

C e r Ɵ fi c a t e s

Distance

Reliability

SelfinspecƟon

Flexibility

AŌer-sale service

Fig. 4.11 The different selecting criteria of five groups

BEST PRACTICE

GOOD PRACTICE

AVERAGE PRACTICE

Fig. 4.12 SC relationships among the groups

2.64

2.40

2.66

3.45

3.75

Interdependency

4.02

4.07

Commitment

3.56

3.58

4.14

4.31

4.26

Trust

POOR PRACTICE

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99

weakest correlation to FSMS implementation. These results provide that the groups have better FSMS implementation in better SC relationships with their suppliers, especially trust and commitment. This finding is in line with the study of Fynes et al. (2005), emphasising the impact of SC relationships on product quality or the work of Ding et al. (2014), confirming that trust and commitment are significantly related to food quality of Australian beef supply chain. This study directs attention to SC relationships and FSMS implementation. It suggests that food firms should gain more commitment and develop mutual trust with their suppliers in terms of food safety management.

4.7

Conclusion

For the purpose of identifying Best Practice, the two-step cluster analysis—hierarchical and non-hierarchical clustering has been conducted to classify the surveyed firms into four distinctive groups. The significant MANOVA on all clusters’ CSFs variables confirms that the CSFs vary across four groups depending on their different FSMS implementation. This finding is particularly beneficial for pointing out the differences and gaps among firms from different groups, leading to identifying their potential improvement areas contingent on the status of each firm’s FSMS implementation. This is associated with the effort of Tzamalis et al. (2016) to develop a tool locating a ‘best practice’ among the studied firms based on factors influencing the FSMS implementation. The study has illustrated many practical suggestions for the studied firms, such as to what CSFs need to be improved and paid attention. Grounded on the results of the cluster analysis, the study explores further the aspects of supplier selection and supply chain relationship among the studied firms. It is found that each identified group has different priority criteria as well as the level of trust, commitment and interdependence with their suppliers. A Pareto analysis shows that the studied firms primarily choose their suppliers based on reliability, certificates, self-inspection results, flexibility, and distance, considering after-sale service and price as the least-wanted criteria. This finding provides empirical support for confirming that firms prioritise safety criteria more than the other criteria in selecting suppliers. Comparing among the identified groups shows the most interesting aspect, the group of Poor Practice reveals its contrary trend in evaluating distance, price, and flexibility to be more critical than the other groups. In contrast, the rest share the same

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T. T. B. NGUYEN AND D. LI

tendency in the selecting order of these criteria. Good Practice is likely to choose their suppliers based on their inspection results and reliability because this mean score is the highest among the four groups. Overall, it is concluded that the groups with better FSMS implementation pay more attention to safety criteria than their counterparts. Regarding SC relationships, the analysis shows higher levels of trust and commitment than interdependency among the studied companies with their suppliers as a whole. The groups of Best and Good Practice have a higher level of commitment than trust, which is different from the rest. It can be seen that the level of commitment, trust and interdependency are in descending order following the score of FSMS implementation of each group. The correlational analysis also points out that commitment is the strongest element related to high FSMS implementation, whereas trust is medium, and interdependency shows the weakest correlation to FSMS implementation. In conclusion, the groups have better FSMS implementation in better SC relationships with their suppliers, especially trust and commitment. This study directs attention to SC relationships and FSMS implementation. It suggests that food firms should gain more commitment and develop mutual trust with their suppliers to enhance food safety management.

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Cohen, J. (1988). Statistical power analysis for the behavioral sciences, 2nd ed. Lawrence Erlbaum Associates. http://www.utstat.toronto.edu/~brunner/old class/378f16/readings/CohenPower.pdf. Accessed 14 Apr 2019. de Vaus, D. A. (2002). Surveys in social research, 5th ed. Allen & Unwin. Ding, M. J., Jie, F., Parton, K. A., & Matanda, M. J. (2014). Relationships between quality of information sharing and supply chain food quality in the Australian beef processing industry. The International Journal of Logistics Management, 25(1), 85–108. Fynes, B., Voss, C., & de Búrca, S. (2005). The impact of supply chain relationship quality on quality performance. International Journal of Production Economics, 96(3), 339–354. Gundlach, G. T., & Cadotte, E. R. (1994). Exchange interdependence and interfirm interaction: Research in a simulated channel setting. Journal of Marketing Research, 31(4), 516–532. Hair, J. F., Babin, B. J., Anderson, R. E., & Black, W. C. (2019). Multivariate data Analysis. Cengage Learning. Hair, J. F., William, C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis, 7th ed. Pearson Education Limited. Ho, W., Xu, X., & Dey, P. K. (2010). Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research, 202(1), 16–24. ISO. (2005). ISO 22000:2005 Food safety management systems—Requirements for any organization in the food chain. https://www.iso.org/obp/ui/#iso:std:iso: 22000:ed-1:v1:en) Kirezieva, K., Jacxsens, L., Uyttendaele, M., Van Boekel, M. A. J. S., & Luning, P. A. (2013). Assessment of food safety management systems in the global fresh produce chain. Food Research International, Elsevier Ltd., 52(1), 230– 242. Kirezieva, K., Luning, P. A., Jacxsens, L., Allende, A., Johannessen, G. S., Tondo, E. C., Rajkovic, A., et al. (2015). Factors affecting the status of food safety management systems in the global fresh produce chain. Food Control, 52, 85–97. Kirezieva, K., Nanyunja, J., Jacxsens, L., van der Vorst, J. G. A. J., Uyttendaele, M., & Luning, P. A. (2013). Context factors affecting design and operation of food safety management systems in the fresh produce chain. Trends in Food Science & Technology, 32(2), 108–127. Kumar, N., Scheer, L. K., & Steenkamp, J. E. M. (1995). The effects of perceived interdependence on dealer attitudes. Journal of Marketing Research, 32(3), 348–356. Macheka, L., Spelt, E., van der Vorst, J. G. A. J., & Luning, P. A. (2017). Exploration of logistics and quality control activities in view of context characteristics and postharvest losses in fresh produce chains: A case study for tomatoes. Food Control, 77 , 221–234.

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CHAPTER 5

What does It Take to Achieve Safer Global Food Supply Chains?

Abstract This chapter summarises the knowledge presented in the book about the implications of the findings and future challenges in food safety management. The book presents critical insights into key roles and impacts of the identified critical success factors and informs good practice for successful implementation of FSMS towards safer food supply chains. Challenges and future research needs are presented for both academics and practitioners. Keywords Research needs · Critical success factors · Food safety management system

5.1

Introduction

This chapter summarises the knowledge presented in the book about the implications of the findings and future challenges in food safety management. The book presents critical insights into key roles and impacts of the identified critical success factors and informs good practice for successful implementation of FSMS towards safer food supply chains. Challenges and future research needs are presented for academics and

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 T. T. B. Nguyen and D. Li, Towards Safer Global Food Supply Chains, https://doi.org/10.1007/978-3-030-93356-2_5

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practitioners. This chapter firstly summarises the developed understanding in efficient management practice and approaches to coping with food safety management challenges in global supply chains in Sects. 5.1–5.3. In Sect. 5.4, implications of the findings on theories and practice in food safety management are summarised. Needs for future development in food safety management are also suggested in Sect. 5.5.

5.2 Understanding the Critical Food Safety Management Practice Critical success factors (CSF) for food safety management system implementation play important roles in food safety management in food industry. In this book, their roles have been identified and justified by relevant research of systematic literature review and the empirical study. The CSFs identified through systematic study of the literature have established a sound basis for further investigation on the roles and impacts of the CSFs on FSMS implementation. Supported by existing research in the literature, the CSFs can be classified into three levels, organisational level, market level and broad environment level. To understand how CSFs from a multi-level context interact with FSMS, this book presents evidence from the empirical study to develop insights into the relationships between the CSFs and FSMS implementation with quantitative delineations at the three levels. This enriches the body of knowledge derived from the existing studies. The following sections summarise the roles of CSFs at different levels. 5.2.1

CSFs at the Organisation Level

The people-related factors in an organisation contribute significantly to FSMS success. In particular, awareness of and commitment of employees to food safety policies are critical. The engagement of employees should not only be exercised by personnel who directly handle food products, but also managers and supervisors who establish responsibilities and authorities within firms, monitor food-safety management activities, and develop FS policy and culture. These factors are also perceived as high-priority CSFs since firms find them challenging to establish, control, and measure. Furthermore, the more advanced and sophisticated the facility and work environment are, the higher the capability of food-safety management could be. Consequently, these factors are considered as CSFs of FSMS

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implementation at the organisational level, besides people-related factors. It is interesting that SMEs have the tendency to perceive these aspects as more critical and with higher impact on FSMS implementation than large firms do, as the interview results revealed. This could be a result of the gap between SMEs and large firms in management capabilities and this could lead to a difference in business performance in international trade. 5.2.2

CSFs at the Market Level

The roles of supplier management, collaboration, and support from stakeholders in supply chains in implementing FSMS are perceived as critical and need to be prioritised among CSFs because they are used as multi-purpose tools by the firms to control and manage their suppliers. Additionally, they facilitate and affect the status of FSMS toward continuous improvement in firms, especially for SMEs, through collaboration with and support from stakeholders. For this reason, the nature and extent of why and how to motivate firms to support and collaborate with one another for food safety management in various contexts is an interesting research agenda. Furthermore, while the support of stakeholders in the supply chains is at the centre of the firms’ attention, the support from business associations, the public sector and financial institutions receive less consideration by firms. 5.2.3

CSFs at the Broad Environment Level

The implementation of FSMS is impacted by factors in a ‘broad context’ shaped by food-safety governance, corroborating the findings of Kirezieva, Jacxsens, et al. (2015) and Kirezieva, Luning, et al. (2015). Food governance in the findings from the studies include inspections, audits, and sampling that are periodically or randomly used as tools to examine non-conformity products or processes by regulatory authorities. As a result, sanctions may be imposed upon non-compliant activities, and stimuli are used to encourage compliance incentives. In addition, information and education (such as guidelines, training, and advice) are applied to broaden and update the knowledge of food safety management. The roles of food-safety governance in support, encouragement and enforcement contribute to the success of FSMS implementation by motivating firms to update their FSMS and ensuring continuous compliance. However, more

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considerable efforts are demanded by relevant parties such as government and authorities, certificate bodies and business associations in food safety governance to facilitate consistency, stability, and transparency in the governance exercise to ensure food safety.

5.3 Understanding Impacts of Business Relationships in Global Supply Chains on Food Safety Management System implementation 5.3.1

Whether and to What Extent Do CSFs Influence FSMS of Firms in the Context of Global Supply Chains?

In the empirical study of Chapter 3, impacts of CSFs on FSMS implementation are investigated by extracting six factors from the CSF set identified from the existing research in the literature to examine their relationships with the FSMS implementation elements (HACCP, Prerequisite programs, and other activities). The six extracted critical success factors as the construct in the analysis are management responsibility, human and other organisational resources, food safety governance, external support, and collaboration in the supply chains. Among all internal measures of these CSFs, food safety policy, employee knowledge and skills, and technological condition are proved as the most critical impact indicators on FSMS implementation. In particular, the factor “Management responsibility” has the most significant impact on FSMS implementation. In the midst of the external CSF group, the factors “external support” (from government and authorities, business associations and stakeholders in SC), “Food safety governance” (audits and inspections, stimulus, sanction, education and information) and “collaboration” (information exchange, solving emerging problems, setting plan and goal, continuous improvement program) show critical contributions to FSMS implementation. It is evidenced that the external factors more considerably contribute to FSMS implementation than the internal factors do, according to the analysis results at the more than 300 surveyed firms. It is also importantly confirmed that the level of collaboration of the firms with their stakeholders, and support from stakeholders, government, and authorities as well as business associations critically impact FSMS implementation.

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Whether the Firms That Perform Better FSMS Implementation Pay More Attention to Safety Criteria?

Grounded on the results of the cluster analysis in Chapter 4, the book presents the exploration results in the aspects of supplier selection and supply chain relationship among the studied firms. The clusters of firms manage food safety with different criteria priorities and different levels of trust, commitment and interdependence with their suppliers. A Pareto analysis shows that the studied firms with good performance of FSMS implementation primarily choose their suppliers based on reliability, certificates, self-inspection results, flexibility, and distance, and consider after-sale service and price as the least-wanted criteria. The comparison of the groups of the firms shows interestingly that the group with poor performance reveals a contrary trend in supplier selection, evaluating distance, price, and flexibility to be more critical. Among the groups, the group with the best performance (with the highest mean score in the empirical analysis) is likely to choose their suppliers based on the food safety inspection results and reliability. Therefore, it can be concluded that firms with better FSMS implementation performance pay more attention to safety criteria than their counterparts. 5.3.3

Whether the Firms That Perform Better FSMS Implementation Are in Better Supply Chain Relationships Than Other Firms?

The study of Chapter 4 shows that the groups with “Best” and “Good” performance in FSMS implementation have a higher level of commitment and trust with supply chain partners. It can be seen that the level of commitment, trust and interdependency are in descending order in line with the order of scores (performance) of FSMS implementation of each group. The cor-relational analysis also points out that commitment is the most substantial element associated with high FSMS implementation performance. In contrast, trust is medium, and interdependency shows the weakest correlation to FSMS implementation performance. In conclusion, the groups that have better-engaged relationships with their suppliers are better performed in FSMS implementation. This suggests that food firms should maintain strong commitment and develop mutual trust with their suppliers for food safety management.

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5.4

Implications from the Research 5.4.1

Theoretical Implications

Responding to the need for strengthening the success of FSMS, this book provides a systematic view of CSFs and FSMS implementation practice in the global food supply chain setting. The book contributes to the body of knowledge in the food safety management discipline and supply chain management through three main theoretical implications. First, the roles of critical success factors in FSMS implementation in global food supply chains are explored in the book. It contributes to the body of knowledge in CSFs by further developing the theory of CSF pioneered by researchers such as Rockart (1979) and Boynton and Zmud (1984) into the field of food safety management in the context of global supply chains. This book presents the first study in this topic considering the impact of CSFs from the three levels to FSMS implementation. Potential CSFs are investigated, and six CSFs are identified for the targeted context through the empirical study. The impacts of the CSFs on FSMS implementation are analysed to identify the best practice among firm clusters and consequently identify the roles of the CSFs that differentiate the FSMS implementation performance of the firm clusters. As findings presented in Sect. 5.2.1, the evidence confirms a number of the most influential factors in the internal and external groups of the CSFs. This enriches the understanding of the roles of CSFs for FSMS implementation. The knowledge is particularly adding value to supply chain management research with the insights into roles of supplier relationships and the vertical integration of food manufacturers in the FSMS implementation. Second, an enabling mechanism for continuous improvement strategies of FSMS implementation through measurement is suggested in the book. The measurement of FSMS status is vital for food manufacturers to address potential restrictions to supply chain partners. In harmony with many prior assessment tools (Jacxsens et al., 2010, 2011; Kirezieva, et al., 2013; Kafetzopoulos & Gotzamani, 2014; Kussaga et al., 2014; Luning et al., 2008, 2015; Nanyunja et al., 2015; Njage et al., 2018; Osés et al., 2012; Rajkovic et al., 2017; Sawe et al., 2014), this book proposes the measurement of FSMS implementation constructed on key activities of an FSMS implementation, rather than limiting FSMS activity to the HACCP principles and being only a part of quality management. The measurement establishes a framework based on CSFs with two distinct advantages compared with the measuring approach from previous studies. First, the

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outcomes of the measurements are able to reflect the status of firms’ FSMS implementation. Second, the measurement framework provides a mechanism to inform continuous improvement strategies of FSMS implementation with the prioritised CSFs. This also lays a groundwork for future research on approaches to identifying continuous improvement strategies for FSMS implementation through CSFs to enhance food safety management and narrow down the performance gaps among firms in the global food supply chains. Finally, incentives for firms to improve FSMS continuously in global trade are indicated in the book. FSMS improvement is associated with extra costs from investing and expanding their plants, facilities or equipment, re-designing products, hiring and training employees, etc. (Keiichiro et al., 2015). Food firms need incentives to continuously update and improve their FSMS. This book provides clear shreds of evidence that elevating the role of FSMS in the global food supply chain context is an important motivation for the manufacturing and exporting sectors. As evidenced from the empirical study, the higher level of FSMS implementation, the better level of operational performance which leads to better financial performance. The enhanced awareness of the relationship between successful FSMS implementation and business performance would motivate firms to upgrade their FSMS. These findings enrich results of a great deal of the previous work in examining the impact of FSMS implementation (Escanciano & Santos-Vijande, 2014; Fotopoulos et al., 2011; Javee & Masakure, 2005; Macheka et al., 2013; Mensah & Julien, 2011; Qijun & Batt, 2016; Whipple et al., 2009) by the clearly evidenced role of FSMS implementation in business performance improvement, which would play as an incentive for continuous FSMS improvement. 5.4.2

Practical Implications

The findings presented in this book would bring significant practical implications to the food industry. First, the set of CSFs would help reduce the complexity of decision-making in managing FSMS. The identified set of CSFs based on the status of each firm’s FSMS implementation performance plays a role as a mechanism to enable continuous improvement of FSMS implementation. Such a mechanism provides an actionable guide for food businesses to target key areas to improve FSMS efficiently. This is particularly helpful for SMEs with limited resources. Each FSMSs are

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highly customised, resulting in none of perfect FSMS for all food manufacturers. The optimal performance should come from an appropriate level of business parameters that fit the contingency (Donaldson, 1987). With the identified priorities of different CSFs in different firm clusters, firms are able to target the right CSFs with their FSMS situations. This brings a more proactive approach to food businesses for continuous FSMS improvement. Furthermore, this book suggests food safety criteria for supplier selection practice, which would lead to enhanced collaboration and a better relationship with stakeholders in supply chains in food safety management and, therefore, benefit to successful FSMS implementation. In particular, this book suggests that the activities related to the establishment of standards and guidelines, auditing and sampling provide information about the status of FSMS. The information would empower companies with helpful knowledge of improving the FSMS implementation with the feedback from those activities.

5.5

Future Research Directions

The finding of the studies of the book, in-depth discussion of the insights into managing FSMS implementation by more practical measuring and flexible continuous improvement based on the identification of CSFs presented in this book have specified several crucial future research directions for researchers. First, the book’s findings suggest that there are still gaps and many promising research directions needed in designing and establishing instruments for evaluating the implementation of FSMS. Many works have been done in this research area that has been adopted to measure FSMS within food firms around the world (e.g. Kafetzopoulos & Gotzamani, 2014; Kirezieva et al., 2013; Kirezieva, Luning, et al., 2015; Luning et al., 2008; Nanyunja et al., 2015; Njage et al., 2018). However, the measurement instruments in this book are regulatory and standard-related requirements aiming at an easy-to-use and visible improvement approach. Future work in this area can examine and construct more diagnostic tools to assess FSMS implementation in a different approach. More in detail, the question raised by this research is whether we could measure multiple aspects of an FSMS combined with other critical elements of food manufacturing performance. Also, regarding the fundamental requirements of FSMS, there would be many fruitful areas on how to build measurement metrics that must be highly

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customised based on the unique characteristics of each company production, market, and environment but still compliance with regulation and standards. Besides the evaluation of FSMS implementation, identifying CSFs of FSMS implementation is vital to prevent possible failures and seek improvement opportunities of FSMS actively. The results of this book reaffirm the critical role of well-performed FSMS towards a safer global food supply chain and provide incentives that require food manufacturers to improve their current practices continuously. The evidence from Chapter 3 suggests that the most crucial limitation lies in the insufficient understanding of CSFs in the broader environment of FSMS, including the market level and food-safety governance. In addition, the contingency of each firm’s FSMS, as well as the evaluation of the relationships amongst the CSFs, have not been taken into the current research. It is evident that managing the implementation of FSMS is deeply contextual and practice-related, a greater focus on understanding how each CSF interact with others in a specific context and how these interactions affect FSMS implementation could produce interesting findings that account more for prioritising and maximising the benefits of identified improvement areas. Additionally, considerably more work will need to be done to determine what trade-offs are when food firms’ managers decide to improve their FSMS practices. In this sense, further studies will need to provide fresher and more comprehensive decision-making tools to facilitate food firms’ managers in improving FSMS implementation based on CSFs. Furthermore, the book represents the first research in the FSMS field that investigates the direct link and empirically tests the relationship between FSMS implementation and the two dimensions of business performance. This finding has a crucial implication for the food industry since it positively encourages firms to improve and update their FSMS continuously, which leads to better operational and financial performance for firms in global trading. On the other hand, the non-significant relationship between FSMS implementation and financial performance raises several unanswered questions in need of future works. Firstly, the cost of FSMS implementation results in an increase in firms’ operational cost due to the firm’s compliance with regulatory and standards requirements by expanding their plant or equipment, re-designing products, and hiring labour for production/testing (Keiichiro et al., 2015). For instance, Ragasa et al. (2011) calculate the expenditure to comply with HACCP using survey data from seafood production firms in the Philippines. The

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impact of compliance with HACCP on the firms’ operational cost net of HACCP-related expenditure is estimated at approximately 1.6% of the total output value. Secondly, although the advantages of compliant FSMS have been discussed in many previous studies (Macheka et al., 2013; Mensah & Julien, 2011; Qijun & Batt, 2016), to understand the relationship between FSMS implementation and financial, the benefits, the cost of FSMS implementation and their trade-offs need to be studied at the same time. Thirdly, whether we need an intermediate variable in the measuring model? The works of Jacxsens et al. (2010), Kirezieva, et al. (2013), Luning et al. (2015), in which system output including information from external and internal activities (i.e., audits, consumer complaints, sampling information, non-conformity) as the outcomes of FSMS is used, requires further studies on testing and developing instrumentation for an intermediate variable among FSMS implementation and financial performance. Last but not least, the book is one of several efforts that have been put into the implementation and improvements of FSMS in global food supply chains. The multi-method research in this book has helped to compare different perspectives drawn from systematic literature review and quantitative data as well as develop better measurement instruments. In other words, two approaches have been used in this book. Nevertheless, other research approaches, frameworks and theories are still needed to measure FSMS implementation, identify CSFs and generate continuous improvements at food firms. For instance, abductive reasoning approaches such as simulations in Bayesian belief networks, stochastic programming, and agent-based modelling could be very interesting. More in detail, the application of system dynamics which uses modelling approaches to predict future changes of systems, can address the problems of simultaneous causation of several critical success factors and their change over time by updating all variables with positive and negative feedbacks and by including time delays on FSMS implementation (Sterman, 2002).

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Appendix

Survey questionnaires in English used in Chapters 3 and 4. Research Questionnaire on Critical Success Factors for Food Safety Management System in Global Supply Chains We would like to thank you for participating in the research that is expected to contribute to improving food safety management based on developing the understanding of current practices. All the information that you provide will be kept confidential. Please carefully follow the below instructions to choose appropriate options that correctly reflect the profile and food safety management activities at your company. Part One—General Information of the Company Profile 1. Please choose the number of existing employees of your company as the followings:    

1–10 employees 11–50 employees 51–250 employees More than 250 employees

2. What is your company’s ownership structure?  Limited liability © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 T. T. B. Nguyen and D. Li, Towards Safer Global Food Supply Chains, https://doi.org/10.1007/978-3-030-93356-2

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Corporation Private enterprise (Individually owned) State-owned Cooperatives

3. What is your current position at the firm?     

Supply chain manager Quality control manager Director/CEO Food safety team Other. Please specify _______________________________

4. What kind of food is your company exporting?      

Fishery Poultry Dairy Fresh fruit and vegetables Drinks and beverage Other. Please specify _______________________________

5. How many tons does your company export per year?     

Less than 500 500–1000 1000–2000 2000–3000 More than 3000

6. What certificates is your company complying? (As many as apply)        

HACCP ISO9001 ISO22000 BRC GlobalGAP SQF IFS Other. Please specify _______________________________

APPENDIX

119

Part Two—Critical Factors of Food Safety Management System To what extent do you think these factors are important to your food safety management system within the organisation?

High 5

INTERNAL FACTORS 7. Managers  commitments to food safety management 8. Food safety policy at  our company as the guiding principles to implement food safety practice  9. Responsibilities and authorities are obviously defined for each person such as food safety team, team leader, direct workers within our organisation to ensure efficient operation and maintenance of food safety management system 10. Established food  safety culture within the organization 11. Knowledge and  skills of the employees in term of ensuring food safety  12. Awareness of the personnel in the relevance and importance of their activities contributing to food safety management  13. Training programs related to food safety for the employee

Above average 4

Average 3

Below average 2

Low 1

























































(continued)

120

APPENDIX

(continued) To what extent do you think these factors are important to your food safety management system within the organisation?

High 5

Above average 4

Average 3

Below average 2

Low 1

14. The employee’s involvement in food safety management activities 15. Qualified facilities and equipment to ensure food safety management 16. Your company’s financial condition 17. Your company’s technological condition









































































EXTERNAL FACTORS 18. Food safety audits  and inspections by regulatory agencies to induce compliance by the company 19. Regulatory  sanctions such as penalties, prosecution, and recalls to punish for committing an offence or repeatedly breaching regulations  20. Stimulus such as awards, labels, tax reduction from regulatory agencies to encourage food safety management compliance  21. Information and education such as guidelines, training, advice from regulatory agencies to support your company in food safety management

(continued)

APPENDIX

121

(continued) To what extent do you think these factors are important to your food safety management system within the organisation? 22. Useful supports to enhance food safety management from: a. Other stakeholders in our supply chains (such as suppliers, contractors, buyers) b. Government and authorities c. Financial institutions (for example banks) d. Business associations (such as NAFIDAD, VASEP in Vietnam) e. Non-governmental organizations 23. Criteria to select suppliers under your food safety requirements: a. Cheaper price b. Certificates fulfilment c. Distance (local or not) d. Reliability e. Good inspection results f. Flexibility (such as payment, freight, price reduction, order frequency and amount, etc.) g. After-sale service 24. Our company regularly works with the important suppliers to improve food safety management based on:

High 5

Above average 4

Average 3

Below average 2

Low 1



















































  

  

  

  

  

 

 

 

 

 





















(continued)

122

APPENDIX

(continued) To what extent do you think these factors are important to your food safety management system within the organisation?

High 5

Above average 4

Average 3

Below average 2

Low 1

a. Solving emerging problems related to product safety b. Having continuous improvement programs c. Planning and goal-setting activities d. Communicating and exchanging all information related to food safety management









































25. We would like you to describe the relationship between your company and most of the suppliers using the following set of descriptions. For each description, please circle the number below the line to indicate where your case falls: • Level of trust

• Level of commitment

• Level of interdependency

123

APPENDIX

Part Three—Food Safety Management Activities On the scale from 1 (poor) to 5 (good), please rate the condition of the followings within your food safety management activities. Activities

Good 5

PREREQUISITE PROGRAMMES 26. Construction and layout  of buildings and associated utilities 27. Layout of premises,  including workspace, employee facilities, laboratory facilities, storage and warehouse 28. Supplies of air, water,  energy and other utilities 29. Supporting services,  including waste and sewage disposal 30. Suitability of equipment  and its accessibility for cleaning, maintenance and preventive maintenance 31. Management of  purchased materials 32. Measures for the  prevention of physical, allergen and microbiological cross-contamination 33. Cleaning and sanitising  programmes are established to ensure that the food-processing equipment and environment are maintained in a hygienic condition

Above average 4

Average

Below average

Poor

3

2

1

































































HACCP (continued)

124

APPENDIX

(continued) Activities

34. Hazards that need to be prevented, eliminated, or reduced to acceptable levels are well identified at each step from incoming raw materials to finished product 35. The points where control is critical to assuring the safety of the product are established by HACCP team 36. Level of efficiency in establishing critical limits at critical control points that separate acceptability from unacceptability for the prevention, elimination or reduction of identified hazards 37. Monitoring procedures and systems at critical control points are established and implemented 38. Corrective actions are installed when monitoring indicates that a critical control point is not under control 39. Validation procedures are carried out to assure that the critical control points will control the hazards of concern and verify that the system is working day-to-day as planned 40. The ability to provide efficient documents and records that demonstrates HACCP system is operating under control, and that appropriate corrective action has been taken for any deviations from the critical limits

Good

Average

Below average

Poor

5

Above average 4

3

2

1







































































(continued)

125

APPENDIX

(continued) Activities

Good 5

OTHER ACTIVITIES OF 41. Traceability system is effective to identify incoming material from the immediate suppliers and the initial distribution route of the end product 42. Corrective actions are guaranteed to be initiated when critical limits are exceeded or when there is a lack of conformity with operational prerequisite programmes 43. Proper procedures to handle potentially unsafe products 44. Control measures are effective and capable of ensuring control of the identified food safety hazards 45. The ability to provide sufficient evidence that the specified monitoring and measuring methods and equipment are adequate to ensure the performance of the monitoring and measuring procedures 46. Internal audits are conducted to determine whether the food safety management system is effectively implemented and updated based on evaluation and analysis of the result of verification activities 47. All records and documents required by the food safety management system are properly controlled

Above average 4

Average

Below average

Poor

3

2

1

FOOD SAFETY MANAGEMENT    































































(continued)

126

APPENDIX

(continued) Activities

48. Internal communication is efficient in exchange information concerning food safety throughout the organisation 49. External communication is efficient in exchange information concerning food safety throughout the food chains such as suppliers and contractors, customers, statutory and regulatory authorities, and other organisations 50. The ability to improve and continually update food safety management system 51. The active in seeking certification or registration of our food safety management system by an external organisation or make a self-assessment or self-declaration of conformity

Good

Average

Below average

Poor

5

Above average 4

3

2

1









































The end of the questionnaire. Many thanks for your time. Best regards!

Index

B BRC, 3–5, 43, 118

C cluster analysis, 75 Confirmatory Factor Analysis, 55 critical success factors (CSF), v, 1, 8, 9, 15–17, 19, 24, 38, 84, 95, 103, 104, 106, 108, 111, 112

E Exploratory Factor Analysis, 55

F food safety, 2, 3, 20, 26, 47, 49, 57, 84, 85, 106, 119, 120 food-safety governance, 5, 9, 26, 29, 30, 42, 43, 64, 88, 105, 111 Food safety management system (FSMS), v, 1, 3, 9, 15, 37, 46, 52, 103, 104, 106, 119–122, 125, 126

FSMS implementation, v, vi, 1, 5, 7–10, 15–19, 25, 26, 29–32, 38, 39, 41–43, 53–56, 58–62, 64, 65, 72, 75, 76, 79, 80, 88, 89, 91–95, 97, 99, 100, 104–112

G global supply chains, v, vi, 1, 3, 5, 9, 17, 19, 37, 38, 42, 64, 104, 106, 108

H Hazard Analysis and Critical Control Points (HACCP), 3–5, 43–45, 50, 58–60, 64, 76, 79–81, 106, 108, 111, 118, 123, 124

M market level, 25 multivariate analysis of variance (MANCOVA), 71, 72, 79

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 T. T. B. Nguyen and D. Li, Towards Safer Global Food Supply Chains, https://doi.org/10.1007/978-3-030-93356-2

127

128

INDEX

O organisational level, 24

P PRP, 4, 45, 59, 76, 79–81

R research gaps, 29

S structural equation modelling (SEM), 10 supplier selection, v, 10, 71–73, 89, 91, 92, 95, 99, 107, 110 supply chain relationships, v, 10, 71, 72, 74, 107 systematic literature review (SLR), 15, 17, 18, 29, 32, 104, 112 V VOS, 22, 32