Blockchain Technology Adoption by Chain Professionals
DOI:
https://doi.org/10.61841/spp9rv10Keywords:
Blockchain, Supply Chain, Adoption, UTAUT, Sri LankaAbstract
Block chain, which was proliferated by Bit coin, is a decentralized and disseminated database to store exchange data. Instead of relying upon delegates, for example, banks in the center, this innovation lets gatherings to record exchanges legitimately on connected records known as square chains making these exchanges relatively increasingly straightforward. The digitalization has achieved new relationship models in the entire production network system, and this inclining innovation is acquiring another marvel of connections co ordinations and store network frameworks. There are numerous examinations and examinations revealed in the writing on block chain, in any case, center around singular level block chain appropriation conduct isn't greatly known. This investigation endeavors to limit this hole by helping to comprehend selection goal and desire for work force in coordination and inventory network in Sri Lanka. Remembering the innovation acknowledgment models and jumping into the developing writing on block chain innovation, inventory network frameworks and system hypothesis, this investigation proposed a revised variant of Unified Theory of Acceptance and Use of Technology model. This examination gathered quantitative information utilizing on the web survey and conveyed Partial Least Square Structural Equation Model to assess proposed model to depict the components impacting people's selection conduct. The outcomes uncovered that Performance Expectancy, Effort Expectancy, Blockchain Transparency and Trust were altogether impacting store network experts' Behavioral Intention to utilize Block chain and Behavioral Intention and Facilitating Conditions were essentially affecting their Behavioral Expectation. Discoveries of this cross-sectional examination extensively contributes the developing writing on Blockchain selection in store network the board space.
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References
[1] Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes,
50(2), 179-211.
[2] Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. Englewood
Cliffs, N.J: Prentice-Hall
[3] Akter, S., Fosso Wamba, S., & Dewan, S. (2017). Why PLS-SEM is suitable for complex modelling? An
empirical illustration in big data analytics quality. Production Planning & Control, 28(11-12), 1011-1021.
[4] Alalwan, A.A., Dwivedi, Y.K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by
Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information
Management, 37(3), 99-110.
[5] Aste, T., Tasca, P., & Di Matteo, T. (2017). Blockchain technologies: The foreseeable impact on society
and industry. Computer, 50(9), 18-28.
[6] Banerjee, M., Lee, J., & Choo, K.K.R.A blockchain future to Internet of Things security: A position paper,
Digital Communications and Networks (2017). URL: http://www. sciencedirect. com/science/article/pii S.
[7] Batara, E., Nurmandi, A., Warsito, T., & Pribadi, U. (2017). Are government employees adopting local egovernment transformation? The need for having the right attitude, facilitating conditions and performance
expectations. Transforming Government: People, Process and Policy, 11(4), 612-638.
[8] Benchoufi, M., Porcher, R., & Ravaud, P. (2017). Blockchain protocols in clinical trials: Transparency and
traceability of consent. F1000Research, 6.
[9] Biswas, K., Muthukkumarasamy, V., & Tan, W.L. (2017, December). Blockchain based wine supply chain
traceability system. In Future technologies conference (pp. 1-7).
[10] Borgatti, S.P., & Foster, P.C. (2003). The network paradigm in organizational research: A review and
typology. Journal of management, 29(6), 991-1013.
[11] Borgatti, S.P., & Li, X. (2009). On social network analysis in a supply chain context. Journal of Supply
Chain Management, 45(2), 5-22.
[12] Brown, S.A., Dennis, A.R., & Venkatesh, V. (2010). Predicting collaboration technology use: Integrating
technology adoption and collaboration research. Journal of Management Information Systems, 27(2), 9-54.
[13] Büyüközkan, G., & Göçer, F. (2018). Digital supply chain: literature review and a proposed framework for
future research. Computers in Industry, 97, 157-177.
[14] Carter, C.R., Rogers, D.S., & Choi, T.Y. (2015). Toward the theory of the supply chain. Journal of Supply
Chain Management, 51(2), 89-97.
[15] Chen, R.Y. (2018). A traceability chain algorithm for artificial neural networks using T–S fuzzy cognitive
maps in blockchain. Future Generation Computer Systems, 80, 198-210.
[16] Chen, Y. (2018). Blockchain tokens and the potential democratization of entrepreneurship and innovation.
Business Hforizons, 61(4), 567-575.
[17] Chin, W.W. (1998). Commentary: Issues and opinion on structural equation modeling.
[18] Chua, P.Y., Rezaei, S., Gu, M.L., Oh, Y., & Jambulingam, M. (2018). Elucidating social networking apps
decisions: performance expectancy, effort expectancy and social influence. Nankai Business Review
International, 9(2), 118-142.
[19] Cohen, J. (1988). Statistical power analysis for the social sciences. Lawrence Erlbaum Associates
Hillsdale, New Jersey
[20] Compeau, D.R., & Higgins, C.A. (1995). Computer self-efficacy: Development of a measure and initial
test. MIS quarterly, 189-211.
[21] Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information
technology. MIS quarterly, 319-340.
[22] Davis, F.D., Bagozzi, R.P., & Warshaw, P.R. (1992). Extrinsic and intrinsic motivation to use computers in
the workplacse 1. Journal of applied social psychology, 22(14), 1111-1132.
[23] Dwivedi, Y.K., Rana, N.P., Jeyaraj, A., Clement, M., & Williams, M.D. (2017). Re-examining the unified
theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information
Systems Frontiers, 1-16.
[24] Falk, R.F., & Miller, N.B. (1992). A primer for soft modeling. University of Akron Press.
[25] Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behaviour: An Introduction to Theory and
Research. Reading MA Addison Wesley. Fransson, N., and Garling, 369-382.
[26] Fornell, C., & Larcker, D.F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics
[27] Francisco, K., & Swanson, D. (2018). The supply chain has no clothes: Technology adoption of blockchain
for supply chain transparency. Logistics, 2(1), 2.
[28] Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101-107.
[29] George, R.P., Peterson, B.L., Yaros, O., Beam, D.L., Dibbell, J.M., & Moore, R.C. (2019). Blockchain for
business. Journal of Investment Compliance, 20(1), 17-21.
[30] Goldsby, T.J., & Zinn, W. (2016). Technology innovation and new business models: can logistics and
supply chain research accelerate the evolution? Journal of Business Logistics, 37(2), 80-81.
[31] Grandori, A., & Soda, G. (1995). Inter-firm networks: antecedents, mechanisms and forms. Organization
studies, 16(2), 183-214.
[32] Hair Jr, J.F., Hult, G.T.M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural
equation modeling (PLS-SEM). Sage publications.
[33] Henseler, J., Ringle, C.M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in
variance-based structural equation modeling. Journal of the academy of marketing science, 43(1), 115-135.
[34] Henseler, J., Ringle, C.M., & Sinkovics, R.R. (2009). The use of partial least squares path modeling in
international marketing. In New challenges to international marketing (pp. 277-319). Emerald Group
Publishing Limited.
[35] Hofmann, E., & Rüsch, M. (2017). Industry 4.0 and the current status as well as future prospects on
logistics. Computers in Industry, 89, 23-34.
[36] Kano, Y., & Nakajima, T. (2018). A novel approach to solve a mining work centralization problem in
blockchain technologies. International Journal of Pervasive Computing and Communications, 14(1), 15-
32.
[37] Kim, H., & Laskowski, M. (2017, July). A perspective on blockchain smart contracts: Reducing uncertainty
and complexity in value exchange. In 2017 26th International Conference on Computer Communication
and Networks (ICCCN) (pp. 1-6). IEEE.
[38] Kock, N. (2017). WarpPLS user manual: Version 6.0. ScriptWarp Systems: Laredo, TX, USA.
[39] Komiak, S.Y., & Benbasat, I. (2006). The effects of personalization and familiarity on trust and adoption of
recommendation agents. MIS quarterly, 941-960.
[40] Kshetri, N. (2017). Blockchain's roles in strengthening cybersecurity and protecting privacy.
Telecommunications policy, 41(10), 1027-1038.
[41] Kshetri, N. (2018). 1 Blockchain’s roles in meeting key supply chain management objectives. International
Journal of Information Management, 39, 80-89.
[42] Lamming, R.C., Caldwell, N.D., Harrison, D.A., & Phillips, W. (2001). Transparency in supply
relationships: concept and practice. Journal of Supply Chain Management, 37(3), 4-10.
[43] Lee, C.C., Kriscenski, J.C., & Lim, H.S. (2019). An Empirical Study of Behavioral Intention to Use
Blockchain Technology. Journal of International Business Disciplines, 14(1).
[44] Li, Z., Wang, W. M., Liu, G., Liu, L., He, J., & Huang, G. Q. (2018). Toward open manufacturing: A
cross-enterprises knowledge and services exchange framework based on blockchain and edge computing.
Industrial Management & Data Systems, 118(1), 303-320.
[45] Liébana-Cabanillas, F., Marinković, V., & Kalinić, Z. (2017). A SEM-neural network approach for
predicting antecedents of m-commerce acceptance. International Journal of Information Management,
37(2), 14-24.
[46] Lu, Q., & Xu, X. (2017). Adaptable blockchain-based systems: a case study for product traceability. IEEE
Software, 34(6), 21-27.
[47] Makanyeza, C., & Mutambayashata, S. (2018). Consumers’ acceptance and use of plastic money in Harare,
Zimbabwe: Application of the unified theory of acceptance and use of technology 2. International Journal
of Bank Marketing, 36(2), 379-392.
[48] Maruping, L.M., Bala, H., Venkatesh, V., & Brown, S.A. (2017). Going beyond intention: Integrating
behavioral expectation into the unified theory of acceptance and use of technology. Journal of the
Association for Information Science and Technology, 68(3), 623-637.
[49] Mayer, R.C., Davis, J.H., & Schoorman, F.D. (1995). An integrative model of organizational trust.
Academy of management review, 20(3), 709-734.
[50] McGhin, T., Choo, K.K.R., Liu, C.Z., & He, D. (2019). Blockchain in healthcare applications: Research
challenges and opportunities. Journal of Network and Computer Applications.
[51] Meunier, S. (2018). Blockchain 101: What is Blockchain and How Does This Revolutionary Technology
Work? In Transforming Climate Finance and Green Investment with Blockchains (pp. 23-34). Academic
Press.
[52] Min, H. (2019). Blockchain technology for enhancing supply chain resilience. Business Horizons, 62(1),
35-45.
[53] Mitchell, J.C. (1969). The concept and use of social networks. Social networks in urban situations.
[54] Moore, G.C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting
an information technology innovation. Information systems research, 2(3), 192-222.
[55] Morgan, T.R., Richey Jr, R.G., & Ellinger, A.E. (2018). Supplier transparency: Scale development and
validation. The International Journal of Logistics Management, 29(3), 959-984.
[56] Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. available at:
https://bitcoin.org/bitcoin.pdf.
[57] Oliveira, T., Faria, M., Thomas, M.A., & Popovič, A. (2014). Extending the understanding of mobile
banking adoption: When UTAUT meets TTF and ITM. International Journal of Information Management,
34(5), 689-703.
[58] Queiroz, M.M., & Wamba, S.F. (2019). Blockchain adoption challenges in supply chain: An empirical
investigation of the main drivers in India and the USA. International Journal of Information Management,
46, 70-82.
[59] Raza, S.A., Shah, N., & Ali, M. (2019). Acceptance of mobile banking in Islamic banks: evidence from
modified UTAUT model. Journal of Islamic Marketing, 10(1), 357-376.
[60] Riffai, M.M.M.A., Grant, K., & Edgar, D. (2012). Big TAM in Oman: Exploring the promise of on-line
banking, its adoption by customers and the challenges of banking in Oman. International journal of
information management, 32(3), 239-250.
[61] Ringle, C.M., Wende, S., & Becker, J.M. (2015). SmartPLS 3. SmartPLS GmbH, Boenningstedt. Retrieved
June, 20, 2019.
[62] Sabi, H.M., Uzoka, F.M.E., Langmia, K., & Njeh, F.N. (2016). Conceptualizing a model for adoption of
cloud computing in education. International Journal of Information Management, 36(2), 183-191.
[63] Seebacher, S., & Schüritz, R. (2017, May). Blockchain technology as an enabler of service systems: A
structured literature review. In International Conference on Exploring Services Science (pp. 12-23).
Springer, Cham.
[64] Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach. John Wiley &
Sons.
[65] Stewart, Kathy A., and Albert H. Segars (2002), "An Empirical Examination of the Concern for
Information Privacy Instrument", Information Systems Research, 13, 36-49.
[66] Stolze, H.J., Murfield, M.L., & Esper, T.L. (2015). The role of social mechanisms in demand and supply
integration: An individual network perspective. Journal of Business Logistics, 36(1), 49-68.
[67] Sun, J., & Teng, J.T. (2017). The construct of information systems use benefits: Theoretical explication of
its underlying dimensions and the development of a measurement scale. International Journal of
Information Management, 37(5), 400-416.
[68] Taylor, S., & Todd, P. (1995). Assessing IT usage: The role of prior experience. MIS quarterly, 561-570.
[69] Tenenhaus, M., Vinzi, V. E., Chatelin, Y. M., & Lauro, C. (2005). PLS path modeling. Computational
statistics & data analysis, 48(1), 159-205.
[70] Thompson, R.L., Higgins, C.A., & Howell, J.M. (1991). Personal computing: toward a conceptual model of
utilization. MIS quarterly, 125-143.
[71] Tian, F. (2017, June). A supply chain traceability system for food safety based on HACCP, blockchain &
Internet of things. In 2017 International Conference on Service Systems and Service Management (pp. 1-6).
IEEE.
[72] Tichy, N.M., Tushman, M.L., & Fombrun, C. (1979). Social network analysis for organizations. Academy
of management review, 4(4), 507-519.
[73] Toyoda, K., Mathiopoulos, P.T., Sasase, I., & Ohtsuki, T. (2017). A novel blockchain-based product
ownership management system (POMS) for anti-counterfeits in the post supply chain. IEEE Access, 5,
17465-17477.
[74] Tsanos, C.S., & Zografos, K.G. (2016). The effects of behavioural supply chain relationship antecedents on
integration and performance. Supply Chain Management: An International Journal, 21(6), 678-693.
[75] Tumasjan, A., & Beutel, T. (2019). Blockchain-Based Decentralized Business Models in the Sharing
Economy: A Technology Adoption Perspective. In Business Transformation through Blockchain (pp. 77-
120). Palgrave Macmillan, Cham.
[76] Venkatesh, V., Brown, S.A., Maruping, L.M., & Bala, H. (2008). Predicting different conceptualizations of
system use: the competing roles of behavioral intention, facilitating conditions, and behavioral expectation.
MIS quarterly, 483-502.
[77] Venkatesh, V., Morris, M.G., Davis, G.B., & Davis, F.D. (2003). User acceptance of information
technology: Toward a unified view. MIS quarterly, 425-478.
[78] Venkatesh, V., Thong, J.Y., & Xu, X. (2012). Consumer acceptance and use of information technology:
extending the unified theory of acceptance and use of technology. MIS quarterly, 36(1), 157-178.
[79] Veuger, J. (2018). Trust in a viable real estate economy with disruption and blockchain. Facilities, 36(1/2),
103-120.
[80] Wagner, S.M., & Buko, C. (2005). An empirical investigation of knowledge‐sharing in networks. Journal
of Supply Chain Management, 41(4), 17-31.
[81] Wamba, S.F., Bhattacharya, M., Trinchera, L., & Ngai, E.W. (2017). Role of intrinsic and extrinsic factors
in user social media acceptance within workspace: Assessing unobserved heterogeneity. International
Journal of Information Management, 37(2), 1-13.
[82] Wamba, S.F., Kamdjoug, K., Robert, J., Bawack, R., & Keogh, J. (2018). Bitcoin, Blockchain, and
FinTech: a systematic review and case studies in the supply chain. Production Planning and Control.
[83] Wang, C.S., Jeng, Y.L., & Huang, Y.M. (2017). What influences teachers to continue using cloud services?
The role of facilitating conditions and social influence. The Electronic Library, 35(3), 520-533.
[84] Wang, Y., Han, J.H., & Beynon-Davies, P. (2019). Understanding blockchain technology for future supply
chains: a systematic literature review and research agenda. Supply Chain Management: An International
Journal, 24(1), 62-84.
[85] Warshaw, P.R., & Davis, F.D. (1985). Disentangling behavioral intention and behavioral expectation.
Journal of experimental social psychology, 21(3), 213-228.
[86] Weerakkody, V., El-Haddadeh, R., Al-Sobhi, F., Shareef, M.A., & Dwivedi, Y.K. (2013). Examining the
influence of intermediaries in facilitating e-government adoption: An empirical investigation. International
Journal of Information Management, 33(5), 716-725.
[87] Wu, K., Zhao, Y., Zhu, Q., Tan, X., & Zheng, H. (2011). A meta-analysis of the impact of trust on
technology acceptance model: Investigation of moderating influence of subject and context type.
International Journal of Information Management, 31(6), 572-581.
[88] Yin, S., Bao, J., Zhang, Y., & Huang, X. (2017). M2m security technology of cps based on blockchains.
Symmetry, 9(9), 193.
[89] Zhang, Y., Weng, Q., & Zhu, N. (2018). The relationships between electronic banking adoption and its
antecedents: A meta-analytic study of the role of national culture. International Journal of Information
Management, 40, 76-87.
[90] Zou, J., Ye, B., Qu, L., Wang, Y., Orgun, M.A., & Li, L. (2018). A proof-of-trust consensus protocol for
enhancing accountability in crowdsourcing services. IEEE Transactions on Services Computing.
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