Dynamics between blockchain adoption determinants and supply chain performance: An empirical investigation

Highlights

• We drew on the literature on technology adoption, supply chain and blockchain.

• We propose a model investigating blockchain adoption determinants in supply chain.

• We tested the model using data from India and the US.

• All proposed hypotheses were supported in both countries.

• We found no significant adoption behavior differences between the two countries.

Abstract

The logistics and supply chain management (SCM) field is experimenting with the integration of blockchain, a cutting-edge, and highly disruptive technology. Yet, blockchain is still nascent, and the extant literature on this technology is scarce, especially as regards the relationship between blockchain and SCM. Additionally, existing studies have not yet addressed sufficiently the enablers of blockchain adoption and the interplay with supply chain performance. In order to reduce this gap, this study aims to examine the potential influence of blockchain on supply chain performance. We draw on the literature on technology adoption and supply chain performance, as well as on the emerging blockchain literature, to develop and test a model in two countries, namely India and the US. Accordingly, we administered a survey in order to review the opinions and views of supply chain practitioners. The results support the model and indicate that blockchain applications can improve supply chain performance. In particular, our findings suggest that knowledge sharing and trading partner pressure play an important role in blockchain adoption, and that supply chain performance is significantly influenced by supply chain transparency and blockchain transparency. Another finding was the inexistence of evidence for a moderation effect of the industry variable on the outcomes. The research conclusions have substantial managerial and theoretical implications. Our model contributes mainly to the theoretical advancement of SCM-blockchain, thus allowing scholars to adapt our validated model.

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:

• Is blockchain an effective technology to support supply chain performance?

• 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.