Blockchain adoption challenges in supply chain: An empirical investigation of the main drivers in India and the USA
By Maciel Manoel de Queiroz, Samuel Fosso Wamba. International Journal of Information Management, 2019
961 citations recorded by the source corpus.
Abstract The digitalization phenomenon is leveraging new relationship models through the entire supply chain network. In this outlook, blockchain is a cutting-edge technology that is already transforming and remodeling the relationships between all members of logistics and supply chain systems. Yet, while studies on blockchain have gained a relative pace over the recent years, the literature on this topic does not report sufficient research cases on blockchain adoption behavior at the individual level. The present study, therefore, aims to bridge this gap, notably by helping understand the individual blockchain adoption behavior in the logistics and supply chain field in India and the USA. Drawing on the emerging literature on blockchain, supply chain and network theory, as well as on technology acceptance models (TAMs), we have developed a model based on a slightly-altered version of the classical unified theory of acceptance and use of technology (UTAUT). The model being developed was then estimated using the Partial least squares structural equation modeling (PLS-SEM). As the model was eventually supported, the results obtained revealed the existence of distinct adoption behaviors between India-based and USA-based professionals. In parallel, the findings appear as a useful contribution to and a sign of progress for the literature on IT adoption, SCM, and blockchain.
Subfields: Information Systems, Information Systems and Management, Marketing
View Paper: https://www.semanticscholar.org/paper/664ad6a548821db18dd0efeb6bb6c5decda00e49
How researchers see this paper
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In Information Systems
- Samuel Fosso Wamba
- Yogesh Kumar Dwivedi
- Marc de Bourmont
- Renato Telles
- Maciel Manoel de Queiroz
- Dmitry A. Ivanov
- Yichian Chen
- Shuchih Ernest Chang
In Information Systems and Management
- Samuel Fosso Wamba
- Yogesh Kumar Dwivedi
- Keng-Boon Ooi
- Voon‐Hsien Lee
- Maciel Manoel de Queiroz
- Garry Wei-Han Tan
- John S. Edwards
- Yanqing Duan
In Marketing
- Yogesh Kumar Dwivedi
- Dmitry A. Ivanov
- Samuel Fosso Wamba
- John S. Edwards
- Yanqing Duan
- Guangming Cao
- Renato Telles
- Marc de Bourmont
Citations in the corpus
- Unearthing the determinants of Blockchain adoption in supply chain management (2020, background): “For example, UTAUT, together with network theory, has been adopted to understand the motivations for Blockchain adoption among supply chain professionals in both India and the United States of America (Queiroz and Fosso Wamba 2019).”
- A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0 (2020, background): “Queiroz and Wamba (2019), Dolgui, Ivanov, and Rozhkov (2020b), and Manupati et al. (2020) extend the discussion towards Blockchain adoption challenges in SCs.”
- Evaluating the factors that influence blockchain adoption in the freight logistics industry (2020, background): “The perceived benefits of blockchain is another important factor in this context which defines the expected value that blockchain technologies can add to the logistics industry (Queiroz and Wamba, 2019).”
- Supply chain disruptions and resilience: a major review and future research agenda (2021, background): “Queiroz and Wamba (2019) A survey and statistical modeling of the employee’ attitudes towards the adoption of blockchain technology.”
- Blockchain technology for enhancing swift-trust, collaboration and resilience within a humanitarian supply chain setting (2020, background): “Hence, blockchain technology (BT) is put forward as a technology that may change organization cultures, supply chains and industries (Kewell et al. 2017; Min, 2019; Zhu et al. 2019; Zhu and Kouhizadeh, 2019; Saberi et al. 2019; Queiroz and Wamba, 2019; Dolgui et al. 2019; Wang et al. 2019a, 2019b).”
- Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making (2021, positive): “…can explain and predict intention to use ITs in organizational contexts, which has been empirically demonstrated by various prior studies (e.g. Brown et al., 2010; Hong et al., 2011; Hossain et al., 2019; Queiroz and Fosso Wamba, 2019; Shibl et al., 2013; Wang et al., 2014; Yueh et al., 2016).”