Blockchainembedded supply chain finance solutions for Indian MSMEs: a TISM and MICMAC approach

Abstract

Purpose To stabilise the financial flow and ensure the smooth operations of the micro, small and medium enterprises (MSMEs), supply chain finance (SCF) is one of the efficient alternative solutions suggested by various researchers and practitioners. The application of blockchain technology (BT) could maximize the capability and performance of the SCF throughout the supply chain. Therefore, this study aims to identify and analyse the factors of implementing BT-embedded SCF solutions for Indian MSMEs. Design/methodology/approach The total interpretative structural modeling (TISM) methodology is applied to explore the hierarchical as well as non-hierarchical relationships among the factors of implementing BT-embedded SCF solutions in Indian MSMEs. Thereafter, the fuzzy-cross-impact matrix-multiplication (F-MICMAC) approach is opted to classify all the factors into four groups depending upon their driving and dependence powers in the overall TISM hierarchy. Findings The result of this study revealed that “real-time exchange of information” and “transparent platform” are the most influential factors and play important role in the application of blockchain in SCF in Indian MSMEs. The real-time exchange of information ensures the easy and quick access to data by any partner across the supply chain and, also the data and information remain secure. Practical implications The findings of this study help the MSMEs and supply chain managers to implement the blockchain-embedded solutions to overcome the traditional SCF challenges and obstructions by setting up short-term as well as long-term policies and will open the door for future research work. Originality/value To the best of the author’s/authors’ knowledge, this study is the first of its kind, where the data is collected from field experts to identify the factors influencing the blockchain-embedded SCF adoption in Indian MSMEs’ perspectives, to tackle the flaws of SCF and strengthen the MSMEs.

Sustainability reporting for boosting national commitment and overcoming challenges: A hierarchical model

“…To achieve this goal, the study used an expert survey to identify and examine the key factors. To ensure robustness and mitigate potential limitations associated with experts from diverse fields, the research followed the “majority rule” principle of achieving consensus among experts (Sahoo & Thakur, 2023; Sharma et al, 2022). The results are discussed in length using the methodology described in Figure 2.…”

“…This iterative approach is a commonly adopted methodology in similar research contexts (Dubey et al, 2017; Kaur et al, 2019). This is instrumental in ensuring the research findings are robust, credible, and informed (Foli, 2022; Sahoo & Thakur, 2023).…”

“…These calculations are shown in FRM Table 5. The reachability captures all Fj with a value of 1 in Row i, whereas the antecedent set collects all Fi with a value of 1 in Column j (Sahoo & Thakur, 2023).…”

A hybrid ISM and fuzzy MICMAC approach to modeling risk analysis of imported fresh food supply chain

“…Using MICMAC together with ISM can improve the traditional MICMAC model and increase its sensitivity. Introducing a fuzzy set can enhance the robustness and effectiveness of the method by reducing the subjective impact caused by the “0” and “1” scored by the experts in the ISM model (Zhao et al , 2020; Sahoo and Thakur, 2023). The fuzzy MICMAC analysis should be done according to the fuzzy matrix synthesis operation (fuzzy matrix multiplication) based on the fuzzy direct reachable matrix instead of the data conversion based on the reachable matrix of ISM.…”

Filling the SME credit gap: a systematic review of blockchain-based SME finance literature

“…The reviewed articles encompass a diverse range of geographical contexts, shedding light on the global interest in understanding the implications of blockchain technology for SMEs. The investigation spans various regions, including India (Kaur et al ., 2022; Paliwal et al ., 2020; Sahoo and Thakur, 2023), Ghana (Asante Boakye et al ., 2022, 2023), Saudi Arabia (Alshareef and Tunio, 2022), China (Chen et al ., 2021; Sun et al ., 2021a, b), Qatar (Dahdal et al ., 2020) and Russia (Christian et al ., 2020), and examines sectors as varied as housing (Utkarsh et al ., 2022), trade finance (Dahdal et al ., 2020; Truby et al ., 2022), livestock export (Miller et al ., 2023), e-commerce (Jiang and Chen, 2021; Li et al ., 2020) and automotive retail (Chen et al ., 2020). This diverse representation underscores the ubiquity of the exploration into blockchain's potential impact on SMEs across different nations and industries.…”