Dynamics between blockchain adoption determinants and supply chain performance: An empirical investigation
Introduction
The logistics and supply chain management (SCM) field recently went through unprecedented disruptions (Büyüközkan and Göçer, 2018), thanks to the development of information and communications technologies (ICTs) (Harris et al., 2015; Frank et al., 2019; Chen, 2019; Goldsby and Zinn, 2016; Schniederjans et al., 2019). Blockchain is one of these disruptive ICTs (Kshetri, 2017a) that could have huge impacts on operations, supply chain and business models (Azzi et al., 2019; Banerjee, 2018; Chang et al., 2019; Dolgui et al., 2019; Helo and Hao, 2019; Longo et al., 2019; Schmidt and Wagner, 2019), and facilitate the execution of smart contracts between supply chain stakeholders (Dolgui et al., 2019). Indeed, blockchain technologies allow the digitalization of decentralized business models through the “implementation of autonomous algorithmic trust controls for decentralized systems” (Gartner, 2019).
Available studies have made it clear that blockchain technologies (Helo and Hao, 2019; Helo and Shamsuzzoha, 2020; Kamble et al., 2020; Wang et al., 2019; Aste et al., 2017; Y. Chen, 2018; Kshetri, 2018; Viryasitavat et al., 2018) have the potential to transform almost all SCM business models, enhance end-to-end supply chain business processes and thus improve supply chain performance. Also, blockchain could facilitate the access to product or service, thereby influencing customer perceived value of the said product or service (Morkunas et al., 2019). Considering the blockchain tamper-proof characteristic and the impact it may create in the area of logistics and supply chain (Aste et al., 2017; Viryasitavat et al., 2018), the level of blockchain adoption in this field is expected to increase significantly in order to enhance supply chain performance.
Amongst other advantages, blockchain technologies can improve complex supply chain problems (e.g., product safety, supply chain visibility, transparency, etc.), and enhance the traceability of operations (Helo and Shamsuzzoha, 2020; Chang et al., 2019; Saberi et al., 2019; Islam et al., 2018; Jeppsson and Olsson, 2017), irrespective of the area involved: food safety (Tian, 2017) and security (Saberi et al., 2019), wine industry (Biswas et al., 2017), healthcare (Benchoufi et al., 2017), e-commerce platform (Ying et al., 2018), and so forth. In the supply chain contexts, blockchain is recognized as a disruptive technology (Choi et al., 2019) that can efficiently solve complex issues such as transparency and accountability (Biswas et al., 2017; Francisco and Swanson, 2018; Kshetri, 2018; Zou et al., 2018), security (Xu et al., 2018; Rahmanzadeh et al., 2019), resilience (Xu et al., 2018), the search for trust (Kano and Nakajima, 2018; Reyna et al., 2018), uncertainty (Kim and Laskowski, 2017), fraud prevention (R. Y. Chen, 2018), confidence (Lu and Xu, 2017), and product recalls (Kshetri, 2017b), and the reduction of supply chain costs (Roeck et al., 2019), etc. Thus, integrating blockchain technology with supply chains is a robust and trusted approach for supporting and remodeling the supply chain patterns and upgrading the level of service delivery. Moreover, blockchain could be an appropriate means of achieving supply chain sustainability (Saberi et al., 2019).
While these recent studies have emphasized blockchain benefits in the supply chain field, effective applications of this technology are still in their infancy (Babich and Hilary, 2020; Queiroz et al., 2019; Schmidt and Wagner, 2019), as prior literature does not point blockchain as an enabler of supply chain performance and other features (e.g., trading partner readiness and pressure, knowledge sharing, diffusion, transparency). For example, a recent review study on bitcoin, blockchain and Fintech in the supply chain, (Fosso Wamba et al., 2018), identified very few empirical studies on these topics. Therefore, our study aims to bridge the knowledge gap identified in the literature by unlocking the value that blockchain can add to supply chain performance, and exploring cultural differences between countries. That is, this study primarily seeks to examine the antecedents of blockchain adoption, and its influence not only on supply chain transparency and blockchain transparency, but also on supply chain performance. Following previous studies on technology adoption which found important differences between countries (Fosso Wamba et al., 2016; Venkatesh and Zhang, 2014), we look forward to exploring any potential differences in blockchain adoption between countries. Therefore, the following research questions need to be addressed:
- 1.
Is blockchain an effective technology to support supply chain performance?
- 2.
Are there any differences in blockchain adoption behavior in supply chains across countries?
In order to answer these research questions, this study draws on the emerging literature on blockchain technologies, on the integration of blockchain with supply chain and on technology adoption to develop a research model that investigates the relationship between blockchain and supply chain performance. The model is tested using data collected in India and the US. In terms of contribution, the findings of this study should enrich not only the literature on logistics and SCM but also the emerging literature on the blockchain. From the managerial perspective, our proposed model contributes to enhancing the understanding of relationships between blockchain variables and supply chain performance, while imposing consideration for countries’ particularities in these relationships. From the theoretical lens, our model was validated by the strong results obtained, and this opened up opportunities for an in-depth analysis of such relationships. In addition, our model may serve as a starting-point for other studies on blockchain in logistics and SCM.
The rest of this paper is organized as follows. The theoretical foundation for the theory and constructs of interest is explained, which leads to the formulation of hypotheses and the research model. The next step is the description of the method used to evaluate the model, followed by the results and findings. Then, there is a discussion of results, which involves managerial and theoretical implications. Research limitations and future research avenues are finally presented before the main conclusions of this study are drawn.
Section snippets
Theoretical foundation
Supply chain performance plays a critical role in all types of organizations, and attaining such performance has been rendered more difficult by the increased complexity of operations in the digital age. With the integration of blockchain, we deemed it necessary to map the gaps and enable a better understanding of the relationship between blockchain and supply chain performance, so we revisited the extant literature concerning supply chain, blockchain and other technologies in order to acquire
Knowledge sharing
The organizations' necessity for innovation has been working as an essential driver for improving knowledge sharing (Lin, 2017). In the blockchain-integrated context, knowledge sharing (KS) primarily refers to the exchange of knowledge between firms through their supply chain members. With blockchain, the players of the same supply chain can share real-time information (Tian, 2017), including skills about their common systems and best practices, and how to potentialize the utilization in
Sampling design and data collection
This study is part of a large project aiming to investigate the adoption, use and impact of blockchain at the firm and supply chain levels (Queiroz and Fosso Wamba, 2019). The data collection was realized through a survey approach. The survey approach is suitable when it comes to investigating a phenomenon that is of interest (in our case, blockchain adoption and its relationship with supply chain performance). Indeed, our sample frame and data collection (Fawcett et al., 2014; Guide Jr. and
Data analysis
We used a classical structural equation modeling (SEM) (Bollen, 1989) to test the proposed model. All the analyses were performed in R 3.5.1 using the lavaan R package, version 0.6–3 (Rosseel, 2012; Rosseel et al., 2019) and the semTools R package, version 0.5–1 (Jorgensen et al., 2019). The Maximum Likelihood estimator for SEM requires the data to be multivariate normality. We used the Mardia's multivariate test of normality (Mardia, 1970) to assess the skewness of the data at the pooled and
Discussion and implications
The purpose of this paper is to examine the relationship between blockchain and supply chain performance. This study contributes to enriching the extant literature on logistics, supply chain management, and blockchain technologies, as it helps to unlock and enhance our understanding of supply chain performance and the impact of blockchain. Our findings offer significant insights from the managerial and theoretical perspectives, providing valuable input to help tackle contemporary challenges in
Conclusion
The primary objective of this study was to show strong empirical evidence of the relationship between blockchain and supply chain performance in two selected countries, with the hope that the results obtained may serve as a catalyst for further research and be generalized. Our proposed research model was strongly supported by the results obtained. In fact, they indicated that knowledge sharing and trading partner pressure are good predictors of blockchain adoption in the Indian and US contexts.
Author contribution
Idea generation and formulation Research goals and aims Theory building: selection of relevant theories Creation of the research model Guide for literature review Survey design and pilot testing Management and coordination of the final data collection by a market research firm Secure funding for the data collection Co-writing of the first draft, advanced draft, and final paper Conduct the initial data analysis and interpretation Finalize the paper Participate in theAuthor Contribution Samuel Fosso Wamba
Dr Samuel Fosso Wamba is Full Professor at Toulouse Business School. His current research focuses on business value of IT, inter-organizational systems adoption and use, supply chain management, electronic commerce, mobile commerce, electronic government, IT-enabled government transparency, blockchain, artificial intelligence in business, social media, business analytics, big data and open data. He has published papers in a number of international conferences and journals including: Academy of
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Dr Samuel Fosso Wamba is Full Professor at Toulouse Business School. His current research focuses on business value of IT, inter-organizational systems adoption and use, supply chain management, electronic commerce, mobile commerce, electronic government, IT-enabled government transparency, blockchain, artificial intelligence in business, social media, business analytics, big data and open data. He has published papers in a number of international conferences and journals including: Academy of Management Journal, European Journal of Information Systems, Journal of Cleaner Production, International Journal of Production Economics, International Journal of Production Research, Journal of Business Research, Technology Forecasting and Social Change, Production Planning & Control, Journal of Strategic Marketing, Information Systems Frontiers, Electronic Markets – The International Journal on Networked Business, Business Process Management Journal, Proceedings of the IEEE, Hawaii International Conference on Systems Science (HICSS), Pacific Asia Conference on Information Systems (PACIS), Americas Conference on Information Systems (AMCIS) and International Conference on Information Systems (ICIS). Prof Fosso Wamba is organizing special issues on IT-related topics for leading international journals. He is the coordinator of The Big Data Program in London for Toulouse Business School. He won the best paper award of The Academy of Management Journal in 2017 and the papers of the year 2017 of The Electronic Markets: The International Journal on Networked Business. He is an Associate Editor of International Journal of Logistics Management information. He serves on editorial board of five international journals. According to Google Scholar he has an h-index of 32 and over 4004 citations by January 17, 2019. Prof Fosso Wamba is CompTIA RFID + Certified Professional, Academic Co-Founder of RFID Academia.
Dr Maciel M. Queiroz is a Professor of Operations and Supply Chain Management in the Business Management Department at Paulista University (UNIP), Brazil. Maciel holds an MSc and a PhD. in Naval Architecture and Ocean Engineering from the University of Sao Paulo. His current research interests focuses on Supply Chain digital disruptions, digital supply chain capabilities, Industry 4.0, blockchain, big data, IoT, including adoption, use, and the impacts to the organizations. His research work has been published in international journals and conferences including International Journal of Logistics Management, Supply Chain Management: An International Journal, International Journal of Information Management, Benchmarking, among others. Also, his research appeared in the Proceedings of the IMAM, TMS, ISL. He serves as a reviewer for international journals and The Academy of Management Annual Meeting. Dr Maciel has been serving as a Guest Co-Editor for the International Journal of Information Management, on the topic “Blockchain in the Operations and Supply Chain Management”, Production Planning and control on the topic “Industry experiences of Artificial Intelligence (AI): benefits and challenges in operations and supply chain management”. Also, he is serving as a session chair for the Invited Session on “Blockchain in the Operations and Supply Chain Management” for IFAC MIM 2019, and as a co-chair for the minitrack “Information Technology (IT)-enabled Supply Chain Management: Co-Creating and Capturing Business Value from IT” for “The annual Americas Conference on Information Systems” (AMCIS-2019), and co-chair for the minitrack “Artificial Intelligence and the Interplay with business innovation (itAIS & MCIS, 2019). In addition, He has serving as a reviewer in top listed journals.
Laura TRINCHERA is Assistant Professor of Statistics at NEOMA Business School, France. She holds a Master Degree in Business and Economics (2004) and a PhD in Statistics (2008) from the University of Naples Federico II, Italy. Her research focuses on Multivariate Data Analysis with an emphasis on Structural Equation Modeling, Partial Least Squares (PLS) Methods and Clustering and Classification algorithms. She is member of the International Association for Statistical Computing (IASC), of the International Society of Business and Industrial Statistics (ISBIS), of the Italian Statistical Society (SIS) and of the Société Française de Statistique (SFDS). She has been elected member of the Council Committee of the Young group of the SFDS. She is co-chair of the specialised team Component-based Methods for Predictive and Exploratory Path Modeling of the working group on Computational and Methodological Statistics in the European Research Consortium for Informatics and Mathematics (ERCIM). She has been visiting researcher at University of California at Santa Barbara, University of Michigan at Ann Arbor, University of Hamburg, Charles University in Prague, HEC School of Management in Paris and external lecturer for the ESSEC PhD Programme at ESSEC Business School.