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

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Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1393))

Abstract

Industry 4.0 is the information-intensive transformation that has taken place in manufacturing and its related activities. Blockchain Technology (BCT) is one such prominent component of the Industry 4.0 concept, which enables the workforce and end-users to access digital information at real-time, based on its data abstraction features. The aim of this paper is to analyze the determinants that influence the BCT adoption in supply chain management in the context of MSME firms in India. We consider the case of MSMEs, in developing economies such as India as MSMEs play a crucial role in enhancing the growth and development of such economies. The determinants to evaluate the implementation of BCT is based on the integrated conceptual model including features of Technology Adoption Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), and Technology-Organization-Environment (TOE) frameworks. Sixteen major determinants were selected by integrating the opinions of industry experts and from the literature. Since there are many conflicting criteria, the current paper utilizes the Multi-criteria Decision Making (MCDM) method, Fuzzy-Analytical Hierarchy Process (F-AHP) to prioritize these determinants so as to aid the decision-makers in the adoption of BCT in their supply chain. The present study integrates fuzzy theory with AHP method to incorporate the subjectivity of real-life decision making. The results of this study will aid various stakeholders, such as industry practitioners, policymakers and regulatory bodies to get a better understanding of benefits of BCT in the supply chain and provide good service to consumers such that the organization can stay ahead of the competition.

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References

  1. Lasi H, Fettke P, Kemper HG, Feld T, Hoffmann M (2014) Industry 4.0. Bus Inf Syst Eng 6(4):239–242

    Google Scholar 

  2. Lee J, Ardakani HD, Yang S, Bagheri B (2015) Industrial big data analytics and cyber-physical systems for future maintenance & service innovation. Procedia Cirp 38:3–7

    Article  Google Scholar 

  3. Kamble S, Gunasekaran A, Arha H (2019) Understanding the Blockchain technology adoption in supply chains-Indian context. Int J Prod Res 57(7):2009–2033

    Article  Google Scholar 

  4. Schmidt R, Möhring M, Härting RC, Reichstein C, Neumaier P, Jozinović P (2015) Industry 4.0-potentials for creating smart products: empirical research results. In International conference on business information system, pp. 16–27. Springer, Cham

    Google Scholar 

  5. Pendit UC, Zaibon SB, Bakar JA (2014) Mobile augmented reality for enjoyable informal learning in cultural heritage site. Int J Comput App 92(14):19–26

    Google Scholar 

  6. Holotiuk F, Moormann J (2018) Organizational adoption of digital innovation: the case of blockchain technology. Res Pap, 202

    Google Scholar 

  7. Gökalp E, Gökalp MO, Çoban S (2020) blockchain-based supply chain management: understanding the determinants of adoption in the context of organizations. Inf Syst Manag, 1–22

    Google Scholar 

  8. Francisco K, Swanson D (2018) The supply chain has no clothes: Technology adoption of blockchain for supply chain transparency. Logist 2(1):2

    Article  Google Scholar 

  9. Das S, Das KK (2012) Factors influencing the information technology adoption of micro, small and medium enterprises (MSME): an empirical study. Int J Eng Res Appl 2(3):2493–2498

    Google Scholar 

  10. Goyal P (2022) SMEs must strive to produce World Class Products; GeM to handhold Women Entrepreneurs in SME Manufacturing https://pib.gov.in/PressReleaseIframePage.aspx?PRID=1598636. Accessed 13 Sept 2020

  11. Ghobakhloo M, Arias-Aranda D, Benitez-Amado J (2011) Adoption of e-commerce applications in SMEs. Ind Manag Data Syst 111(8):1238–1269

    Article  Google Scholar 

  12. Guo Y, Liang C (2016) Blockchain application and outlook in the banking industry. Financ Innov 2(1):24

    Article  Google Scholar 

  13. Azmi F, Abdullah A, Bakri M, Musa H, Jayakrishnan M (2018) The adoption of halal food supply chain towards the performance of food manufacturing in Malaysia. Manag Sci Lett 8(7):755–766

    Article  Google Scholar 

  14. Al-Qirim N (2007) The adoption of eCommerce communication and application technologies in small business in New Zeeland. Electron Commer Res and Appl 6(4):462–473

    Article  Google Scholar 

  15. Quayle M (2002) E-commerce: the challenge for UK SMEs in the twenty-first century. Int J Oper Pro Manag 22(10):1148–1161

    Article  Google Scholar 

  16. Queiroz MM, Wamba SF (2019) Blockchain adoption challenges in supply chain: An empirical investigation of the main drivers in India and the USA. Int J Inf Manag 46:70–82

    Article  Google Scholar 

  17. Liu Z, Li Z (2020) A blockchain-based framework of cross-border e-commerce supply chain. Int J Inf Manag 52:

    Article  Google Scholar 

  18. Wong LW, Leong LY, Hew JJ, Tan GWH, Ooi KB (2020) Time to seize the digital evolution: Adoption of blockchain in operations and supply chain management among Malaysian SMEs. Int J Inf Manag 52:

    Article  Google Scholar 

  19. Tönnissen S, Teuteberg F (2020) Analysing the impact of blockchain-technology for operations and supply chain management: an explanatory model drawn from multiple case studies. Int J Inf Manag 52:

    Article  Google Scholar 

  20. Yusof H, Munir MFMB, Zolkaply Z, Jing CL, Hao CY, Ying DS,… Leong TK (2018) Behavioral intention to Adopt Blockchain technology: viewpoint of the banking institutions in Malaysia, 274–279

    Google Scholar 

  21. Abeyratne SA, Monfared RP (2016) Blockchain ready manufacturing supply chain using distributed ledger. Int J Res Eng Tech 5(9):1–10

    Article  Google Scholar 

  22. Tian F (2017) A supply chain traceability system for food safety based on HACCP, blockchain & Internet of things. In: 2017 International conference service system service management, pp. 1–6. IEEE

    Google Scholar 

  23. Verma P, Sinha N (2018) Integrating perceived economic wellbeing to technology acceptance model: The case of mobile based agricultural extension service. Technol Forecast Soc Chang 126:207–216

    Article  Google Scholar 

  24. Zheng Z, Xie S, Dai H, Chen X, Wang H (2017) An overview of blockchain technology: architecture, consensus, and future trends. In: 2017 IEEE international conference on big data (BigData congr.), pp 557–564. IEEE

    Google Scholar 

  25. Alalwan AA, Dwivedi YK, Rana NP, Simintiras AC (2016) Jordanian consumers’ adoption of telebanking. Int J Bank Mark 34(5):690–709

    Article  Google Scholar 

  26. Chi T (2018) Understanding Chinese consumer adoption of apparel mobile commerce: an extended TAM approach. J Retail Consum Serv 44:274–284

    Article  Google Scholar 

  27. Gao L, Bai X (2014) A unified perspective on the factors influencing consumer acceptance of internet of things technology. Asia Pac J Mark Logist 26(2):211–231

    Article  Google Scholar 

  28. Benbasat I, Barki H (2007) Quo vadis TAM? J Assoc for Inf Syst 8(4):7

    Google Scholar 

  29. Chand M (2020) Why do I need Blockchain https://www.c-sharpcorner.com/article/do-you-need-a-blockchain2/. Accessed 13 Sept 2020

  30. Venkatesh V, Davis F (2000) A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci 46(2):186–204

    Article  Google Scholar 

  31. Kuan KK, Chau PY (2001) A perception-based model for EDI adoption in small businesses using a technology–organization–environment framework. Inf Manag 38(8):507–521

    Article  Google Scholar 

  32. Chertow MR (2007) “Uncovering” industrial symbiosis. J Ind Ecol 11(1):11–30

    Article  Google Scholar 

  33. Oliveira T, Martins MF (2010) Understanding e-business adoption across industries in European countries. Ind Manag Data Syst 110(9):1337–1354

    Article  Google Scholar 

  34. Thong JY, Yap CS (1995) CEO characteristics, organizational characteristics and information technology adoption in small businesses. Omega 23(4):429–442

    Article  Google Scholar 

  35. Ramdani B, Chevers D, Williams DA (2013) SMEs’ adoption of enterprise applications: A technology-organisation-environment model. J Small Bus Enterp Dev 20(4):735–753

    Article  Google Scholar 

  36. Wang YM, Wang YS, Yang YF (2010) Understanding the determinants of RFID adoption in the manufacturing industry. Technol Forecast Soc Chang 77(5):803–815

    Article  Google Scholar 

  37. Chau PY, Tam KY (1997) Factors affecting the adoption of open systems: an exploratory study. MIS quarterly, 1–24

    Google Scholar 

  38. Zhu K, Kraemer K, Xu S (2003) Electronic business adoption by European firms: a cross-country assessment of the facilitators and inhibitors. Eur J Inf Syst 12:251–268

    Article  Google Scholar 

  39. Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: toward a unified view. MIS Q 27:425–478

    Article  Google Scholar 

  40. Rogers EM (1995) Diffusion of Innovations: modifications of a model for telecommunications. Die Diffuse von Innov in der Telekommun. Springer, Berlin, Heidelberg, pp 25–38

    Google Scholar 

  41. Taylor S, Todd P (1995) Decomposition and crossover effects in the theory of planned behavior: a study of consumer adoption intentions. Int J Res Mark 12(2):137–155

    Article  Google Scholar 

  42. Zhu K, Dong S, Xu SX, Kraemer KL (2006) Innovation diffusion in global contexts: determinants of post-adoption digital transformation of European companies. Eur J Inf Syst 15(6):601–616

    Article  Google Scholar 

  43. Hoti E (2015) The technological, organizational and environmental framework of IS innovation adaption in small and medium enterprises. Evidence from research over the last 10 years. Int J Bus Manag 3(4):1–14

    Google Scholar 

  44. Lu J, Yu C, Liu C, Yao J (2003) Technology acceptance model for wireless internet. Int Rese. Electron Netw Appl Policy 13(3):206–222

    Google Scholar 

  45. Jiang J, Hsu M, Klein G, Lin B (2000) E-commerce user behaviour model: an empirical study. Hum Syst Manag 19(4):265–276

    Article  Google Scholar 

  46. Tripopsakul S (2018) Social media adoption as a business platform: an integrated TAM-TOE framework. Pol J Manag Stud 18(2):350–362

    Google Scholar 

  47. Davis FD (1993) User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. Int J Man-mach Stud 38(3):475–487

    Article  Google Scholar 

  48. Opia O (2008) An exploratory study of the moderating effects of trust on e-commerce adoption behaviour of Nigerian small enterprises. Afr J Entrep 1(1):43–51

    Google Scholar 

  49. Grandon EE, Pearson JM (2004) Electronic commerce adoption: an empirical study of small and medium US businesses. Inf Manag 42(1):197–216

    Article  Google Scholar 

  50. Doom C, Milis K, Poelmans S, Bloemen E (2010) Critical success factors for ERP implementations in Belgian SMEs. J Enterp Inf Manag 23(3):378–406

    Article  Google Scholar 

  51. Alshamaila Y, Papagiannidis S, Li F (2013) Cloud computing adoption by SMEs in the north east of England: a multi-perspective framework. J Enterp Inf Manag 26(3):250–275

    Article  Google Scholar 

  52. Tuffnell C, Kral P, Durana P, Krulicky T(2019) Industry 4.0-based manufacturing systems: Smart production, sustainable supply chain networks, and real-time process monitoring. J Self-Gov and Manag Econ 7(2):7–12

    Google Scholar 

  53. Schillewaert N, Ahearne MJ, Frambach RT, Moenaert RK (2005) The adoption of information technology in the sales force. Ind Mark Manag 34(4):323–336

    Article  Google Scholar 

  54. Triandis H(1980) Values, attitudes, and interpersonal behavior. In Howe HE, Page MM (Eds), Nebraska symposium on motivation Beliefs, attitudes, and values, pp 195–259

    Google Scholar 

  55. Thompson R, Higgins C, Howell M (1994) Influence of experience on personal computer utilization: Testing a conceptual model. J Manag Inf Syst 1(1):167–187

    Article  Google Scholar 

  56. Weck M, Klocke F, Schell H, Rüenauver E (1997) Evaluating alternative production cycles using the extended fuzzy AHP method. Eur J Oper Res 100(2):351–366

    Article  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Keshav Mahavidyalaya, University of Delhi, New Delhi, India

    Rubina Mittal

  2. Department of Operational Research, University of Delhi, New Delhi, India

    Pankaj Pankaj

  3. LBSIM, Dwarka, New Delhi, India

    Sugandha Aggarwal

  4. ASMSOC, NMIMS University, Mumbai, India

    Arshia Kaul

Authors
  1. Rubina Mittal
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  2. Pankaj Pankaj
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  3. Sugandha Aggarwal
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  4. Arshia Kaul
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Editor information

Editors and Affiliations

  1. Computer Science and Engineering, Indian Institute of Technology Indore, Indore, Madhya Pradesh, India

    Aruna Tiwari

  2. Computer Science and Engineering, Indian Institute of Technology Indore, Indore, Madhya Pradesh, India

    Kapil Ahuja

  3. Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, India

    Anupam Yadav

  4. Department of Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

  5. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, India

    Kusum Deep

  6. School of Mathematics, Computer Science and Engineering, Liverpool Hope University, Liverpool, UK

    Atulya K. Nagar

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Mittal, R., Pankaj, P., Aggarwal, S., Kaul, A. (2021). Evaluation of Adoption of Blockchain Technology for Supply Chain Management: A Case of Indian MSME. In: Tiwari, A., Ahuja, K., Yadav, A., Bansal, J.C., Deep, K., Nagar, A.K. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 1393. Springer, Singapore. https://doi.org/10.1007/978-981-16-2712-5_49

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