Evaluation of Adoption of Blockchain Technology for Supply Chain Management: A Case of Indian MSME

Mittal, Rubina; Pankaj, Pankaj; Aggarwal, Sanjeev; Kaul, Arshia

doi:10.1007/978-981-16-2712-5_49

Cited by 6 publications

(8 citation statements)

References 44 publications

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“…SC incompatibility with current platforms, and SC complexities (Sumarliah et al, 2022). Consequently, the ABT models must scrutinise those elements from an enterprise perspective to identify the influential determinants of ABT in the SCs (Kumar Bhardwaj et al, 2021;Mittal et al, 2021). Thus, this study uses combined TOE-TAM frameworks to develop the research model.…”

Section: Adoption Of Blockchain Technology In the Smes' Supply Chainsmentioning

confidence: 99%

“…As mentioned earlier, only two previous studies have used this approach so far (i.e. Kumar Bhardwaj et al, 2021;Mittal et al, 2021). The variables chosen in this paper are based on the proven empirical findings of the previous works focussing on ABT (i.e.…”

Section: Research Modelmentioning

confidence: 99%

“…Consequently, the ABT models must scrutinise those elements from an enterprise perspective to identify the influential determinants of ABT in the SCs (Kumar Bhardwaj et al. , 2021; Mittal et al. , 2021).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…After conducting an in-depth survey in the Scopus database, the authors revealed that so far, only two significant ABT studies have used the TOE-TAM framework to examine the intent to adopt blockchain in the SCs (i.e. Kumar Bhardwaj et al, 2021;Mittal et al, 2021), and none of those publications has used machine learning Bayesian network approach like this study has. Some empirical publications utilise SEM to inspect users' intentions for the ABT; for example Faasolo and Sumarliah (2022).…”

Section: Introductionmentioning

confidence: 99%

“…Kumar Bhardwaj et al. , 2021; Mittal et al. , 2021), and none of those publications has used machine learning Bayesian network approach like this study has.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Forecasting blockchain adoption in supply chains based on machine learning: evidence from Palestinian food SMEs

Hamdan

Wulamu

Zhang

et al. 2022

BFJ

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PurposeThis paper seeks to discover whether the technical, organisational and technology acceptance model (TAM) factors will significantly affect the adoption of blockchain technology (ABT) amongst SMEs.Design/methodology/approachThe research employs structural equation modelling (SEM) and a machine learning approach to identify factors influencing the ABT behaviour that leaders can use to predict the prospect of the ABT in their enterprises. Information was collected from 255 respondents representing 166 SMEs in the food industry, Palestine.FindingsThe analyses reveal that the ABT is positively and significantly shaped by TAM factors: (1) perceived benefits and (2) perceived ease of using blockchain. Simultaneously, the former is significantly influenced by compatibility and upper management support, while the latter is affected by complexity. Finally, education and training affect both factors.Originality/valueThis paper is amongst the first attempts to examine the ABT behaviour in the food industry using the integration of SEM and machine learning approach.

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Section: Adoption Of Blockchain Technology In the Smes' Supply Chainsmentioning

confidence: 99%

Section: Research Modelmentioning

confidence: 99%

Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Kumar Bhardwaj et al. , 2021; Mittal et al. , 2021), and none of those publications has used machine learning Bayesian network approach like this study has.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Forecasting blockchain adoption in supply chains based on machine learning: evidence from Palestinian food SMEs

Hamdan

Wulamu

Zhang

et al. 2022

BFJ

View full text Add to dashboard Cite

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Disruption mitigation in the semiconductors supply chain by using public blockchains

2023

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Supply chain management has become increasingly complex, leading to information loss and delayed transmission, exacerbating the bullwhip effect. Furthermore, the need for more reliable information storage, traceability, and accountability has slowed supply chain management. In this context, blockchain technology (BCT) solves the bullwhip effect problem, as it supports distributed networking, information synchronization among nodes, digital encryption, traceable information, and unchangeable block content. This paper proposes using public blockchain to solve the bullwhip effect problem in the supply chain (SC), which has yet to be discussed in published academic research papers. To this end, a framework has been developed to determine the readiness of a supply chain for blockchain adoption. This framework includes a checklist to evaluate the motivation, timing, and appropriate platform for adopting blockchain. The framework has been validated using a case study of personal computer devices, which were affected by the Covid-19 pandemic and resulted in semiconductors supply chain disruption. The study involved polling four executives The study involved polling four executives (of large organizations in Egypt and some Middle Eastern countries) representing different stages in the supply chain, they are retail, distribution, manufacturing, and supply. The results showed that while the executives recognized the benefits of adopting blockchain, they were still determining if it was the right time for adoption and did not see the technology ready for their supply chains. Finally, some public blockchain platforms were introduced to help businesses choose the most suitable platform for adoption.

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Role of big data analytics capabilities to improve sustainable competitive advantage of MSME service firms during COVID-19 – A multi-theoretical approach

Behl

Gaur

Pereira

et al. 2022

Journal of Business Research

123

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Evaluation of Adoption of Blockchain Technology for Supply Chain Management: A Case of Indian MSME

Cited by 6 publications

References 44 publications

Forecasting blockchain adoption in supply chains based on machine learning: evidence from Palestinian food SMEs

Forecasting blockchain adoption in supply chains based on machine learning: evidence from Palestinian food SMEs

Disruption mitigation in the semiconductors supply chain by using public blockchains

Role of big data analytics capabilities to improve sustainable competitive advantage of MSME service firms during COVID-19 – A multi-theoretical approach

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