Digital Transformation in Supply Chain Management: A Commerce and Management Perspective
DOI:
https://doi.org/10.65021/mwsj.v1.i1.5Keywords:
Digital transformation, Supply chain management, Industry 4.0, IoT, Blockchain, Artificial intelligence, Big data analyticsAbstract
The digital transformation of supply chain management represents one of the most significant paradigm shifts in contemporary business operations. This paper examines the comprehensive impact of digital technologies on supply chain management from both commerce and management perspectives. The research analyzes the integration of emerging technologies including Internet of Things (IoT), artificial intelligence, blockchain, cloud computing, and big data analytics in supply chain processes. Through systematic analysis of current literature and industry practices, this study identifies key drivers, challenges, and opportunities associated with digital supply chain transformation. The findings reveal that organizations implementing comprehensive digital supply chain strategies demonstrate improved operational efficiency, enhanced visibility, reduced costs, and increased customer satisfaction. However, significant challenges persist in areas of cybersecurity, data integration, organizational change management, and technology adoption costs. The paper provides strategic recommendations for organizations seeking to navigate the digital transformation journey effectively. The research contributes to the growing body of knowledge on digital supply chain management and offers practical insights for both academic researchers and industry practitioners.
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References
1. Christopher, M. (2016). Logistics & supply chain management. Pearson UK. (Book)
2. Lambert, D. M., & Cooper, M. C. (2000). Issues in supply chain management. Industrial Marketing Management, 29(1), 65-83. https://doi.org/10.1016/S0019-8501(99)00113-3
3. Davenport, T. H. (2000). The future of enterprise applications. Information Systems Research, 11(4), 396-402. https://doi.org/10.1287/isre.11.4.396.11872
4. Lee, H. L. (2004). The triple-A supply chain. Harvard Business Review, 82(10), 102-112.
5. Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S., Nix, N. W., Smith, C. D., & Zacharia, Z. G. (2001). Defining supply chain management. Journal of Business Logistics, 22(2), 1-25. https://doi.org/10.1002/j.2158-1592.2001.tb00001.x
6. Simatupang, T. M., & Sridharan, R. (2002). The collaborative supply chain. The International Journal of Logistics Management, 13(1), 15-30. https://doi.org/10.1108/09574090210806333
7. Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, 54(15), 2787-2805. https://doi.org/10.1016/j.comnet.2010.05.010
8. Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). Internet of things and supply chain management: A literature review. International Journal of Production Research, 57(15-16), 4719-4742. https://doi.org/10.1080/00207543.2017.1402140
9. Tao, F., Qi, Q., Liu, A., & Kusiak, A. (2018). Data-driven smart manufacturing. Journal of Manufacturing Systems, 48, 157-169. https://doi.org/10.1016/j.jmsy.2018.01.006
10. Verdouw, C., Wolfert, J., Beulens, A. J., & Rialland, A. (2016). Virtualization of food supply chains with the internet of things. Journal of Food Engineering, 176, 128-136. https://doi.org/10.1016/j.jfoodeng.2015.11.009
11. Weber, R. H. (2010). Internet of Things–New security and privacy challenges. Computer Law & Security Review, 26(1), 23-30. https://doi.org/10.1016/j.clsr.2009.11.008
12. Min, H. (2010). Artificial intelligence in supply chain management: Theory and applications. International Journal of Logistics Research and Applications, 13(1), 13-39. https://doi.org/10.1080/13675560902736537
13. Kuo, Y. H., & Kusiak, A. (2019). From data to big data in production research: The past and future trends. International Journal of Production Research, 57(15-16), 4828-4853. https://doi.org/10.1080/00207543.2018.1443230
14. Baryannis, G., Validi, S., Dani, S., & Antoniou, G. (2019). Supply chain risk management and artificial intelligence: State of the art and future research directions. International Journal of Production Research, 57(7), 2179-2202. https://doi.org/10.1080/00207543.2018.1530476
15. Carbonneau, R., Laframboise, K., & Vahidov, R. (2008). Application of machine learning techniques for supply chain demand forecasting. European Journal of Operational Research, 184(3), 1140-1154. https://doi.org/10.1016/j.ejor.2006.12.004
16. Brintrup, A., Pak, J., Ratiney, D., Pearce, T., Wichmann, P., Woodall, P., & McFarlane, D. (2020). Supply chain data analytics for predicting supplier disruptions: A case study in complex asset manufacturing. IEEE Transactions on Engineering Management, 67(3), 640-653. https://doi.org/10.1109/TEM.2019.2894409
17. Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7), 2117-2135. https://doi.org/10.1080/00207543.2018.1533261
18. Kshetri, N. (2018). Blockchain's roles in meeting key supply chain management objectives. International Journal of Information Management, 39, 80-89. https://doi.org/10.1016/j.ijinfomgt.2017.12.005
19. 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. https://doi.org/10.1108/SCM-03-2018-0148
20. Kamble, S. S., Gunasekaran, A., & Gawankar, S. A. (2020). Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications. International Journal of Production Economics, 219, 179-194. https://doi.org/10.1016/j.ijpe.2019.05.022
21. Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., ... & Zaharia, M. (2010). A view of cloud computing. Communications of the ACM, 53(4), 50-58. https://doi.org/10.1145/1721654.1721672
22. Liu, S., Zhang, Y., Liu, Y., Wang, L., & Wang, X. V. (2019). An 'Internet of Things' enabled dynamic optimization method for smart vehicles and logistics tasks. Journal of Cleaner Production, 215, 806-820. https://doi.org/10.1016/j.jclepro.2018.12.254
23. Wu, L., Yue, X., Jin, A., & Yen, D. C. (2016). Smart supply chain management: A review and implications for future research. The International Journal of Logistics Management, 27(2), 395-417. https://doi.org/10.1108/IJLM-02-2014-0035
24. Oliveira, T., Thomas, M., & Espadanal, M. (2014). Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Information & Management, 51(5), 497-510. https://doi.org/10.1016/j.im.2014.03.006
25. Waller, M. A., & Fawcett, S. E. (2013). Data science, predictive analytics, and big data: A revolution that will transform supply chain design and management. Journal of Business Logistics, 34(2), 77-84. https://doi.org/10.1111/jbl.12010
26. Hazen, B. T., Boone, C. A., Ezell, J. D., & Jones-Farmer, L. A. (2014). Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications. International Journal of Production Economics, 154, 72-80. https://doi.org/10.1016/j.ijpe.2014.04.018
27. Gunasekaran, A., Papadopoulos, T., Dubey, R., Wamba, S. F., Childe, S. J., Hazen, B., & Akter, S. (2017). Big data and predictive analytics for supply chain and organizational performance. Journal of Business Research, 70, 308-317. https://doi.org/10.1016/j.jbusres.2016.08.004
28. Zhong, R. Y., Newman, S. T., Huang, G. Q., & Lan, S. (2016). Big Data for supply chain management in the service and manufacturing sectors: Challenges, opportunities, and future perspectives. Computers & Industrial Engineering, 101, 572-591. https://doi.org/10.1016/j.cie.2016.07.013
29. Schumacher, A., Erol, S., & Sihn, W. (2016). A maturity model for assessing Industry 4.0 readiness and maturity of manufacturing enterprises. Procedia CIRP, 52, 161-166. https://doi.org/10.1016/j.procir.2016.07.040
30. Bibby, L., & Dehe, B. (2018). Defining and assessing industry 4.0 maturity levels–case of the defence sector. Production Planning & Control, 29(12), 1030-1043. https://doi.org/10.1080/09537287.2018.1503355
31. Klötzer, C., & Pflaum, A. (2017). Toward the development of a maturity model for digitalization within the manufacturing industry's supply chain. Proceedings of the 50th Hawaii International Conference on System Sciences, 4210-4219. https://doi.org/10.24251/HICSS.2017.509
32. De Carolis, A., Macchi, M., Negri, E., & Terzi, S. (2017). A maturity model for assessing the digital readiness of manufacturing companies. IFIP International Conference on Advances in Production Management Systems, 13-20. https://doi.org/10.1007/978-3-319-66923-6_2
33. Kane, G. C., Phillips, A. N., Copulsky, J. R., & Andrus, G. R. (2019). The technology fallacy: How people are the real key to digital transformation. MIT Press. (Book)
34. Westerman, G., Bonnet, D., & McAfee, A. (2014). Leading digital: Turning technology into business transformation. Harvard Business Press. (Book)
35. Ross, J. W., Sebastian, I. M., & Beath, C. (2017). How to develop a great digital strategy. MIT Sloan Management Review, 58(2), 7-9.
36. Matt, C., Hess, T., & Benlian, A. (2015). Digital transformation strategies. Business & Information Systems Engineering, 57(5), 339-343. https://doi.org/10.1007/s12599-015-0401-5
37. Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118-144. https://doi.org/10.1016/j.jsis.2019.01.003
38. Singh, A., & Hess, T. (2017). How chief digital officers promote the digital transformation of their companies. MIS Quarterly Executive, 16(1), 1-17.
39. Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2013). Digital business strategy: Toward a next generation of insights. MIS Quarterly, 37(2), 471-482. https://doi.org/10.25300/MISQ/2013/37:2.3
40. Barreto, L., Amaral, A., & Pereira, T. (2017). Industry 4.0 implications in logistics: an overview. Procedia Manufacturing, 13, 1245-1252. https://doi.org/10.1016/j.promfg.2017.09.045
41. Richey, R. G., Morgan, T. R., Lindsey-Hall, K., & Adams, F. G. (2016). A global exploration of big data in the supply chain. International Journal of Physical Distribution & Logistics Management, 46(8), 710-739. https://doi.org/10.1108/IJPDLM-05-2016-0134
42. Farahani, P., Meier, C., & Wilke, J. (2017). Digital supply chain management agenda for the automotive supplier industry. In Shaping the Digital Enterprise (pp. 157-172). Springer. https://doi.org/10.1007/978-3-319-40967-2_8
43. 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. https://doi.org/10.1016/j.compind.2017.04.002
44. Lasi, H., Fettke, P., Kemper, H. G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engineering, 6(4), 239-242. https://doi.org/10.1007/s12599-014-0334-4
45. Lu, Y. (2017). Industry 4.0: A survey on technologies, applications and open research issues. Journal of Industrial Information Integration, 6, 1-10. https://doi.org/10.1016/j.jii.2017.04.005
46. Xu, L. D., Xu, E. L., & Li, L. (2018). Industry 4.0: state of the art and future trends. International Journal of Production Research, 56(8), 2941-2962. https://doi.org/10.1080/00207543.2018.1444806
47. Frank, A. G., Dalenogare, L. S., & Ayala, N. F. (2019). Industry 4.0 technologies: Implementation patterns in manufacturing companies. International Journal of Production Economics, 210, 15-26. https://doi.org/10.1016/j.ijpe.2019.01.004
48. Brynjolfsson, E., Hu, Y. J., & Rahman, M. S. (2013). Competing in the age of omnichannel retailing. MIT Sloan Management Review, 54(4), 23-29.
49. Bell, D. R., Gallino, S., & Moreno, A. (2014). How to win in an omnichannel world. MIT Sloan Management Review, 56(1), 45-53.
50. Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J. F., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356-365. https://doi.org/10.1016/j.jbusres.2016.08.009
51. Nguyen, T., Zhou, L., Spiegler, V., Ieromonachou, P., & Lin, Y. (2018). Big data analytics in supply chain management: A state-of-the-art literature review. Computers & Operations Research, 98, 254-264. https://doi.org/10.1016/j.cor.2017.07.004
52. Shah, N. (2004). Pharmaceutical supply chains: Key issues and strategies for optimisation. Computers & Chemical Engineering, 28(6-7), 929-941. https://doi.org/10.1016/j.compchemeng.2003.09.022
53. Papageorgiou, L. G., Rotstein, G. E., & Shah, N. (2001). Strategic supply chain optimization for the pharmaceutical industries. Industrial & Engineering Chemistry Research, 40(1), 275-286. https://doi.org/10.1021/ie990870t
54. Narayana, S. A., Pati, R. K., & Vrat, P. (2014). Managerial research on the pharmaceutical supply chain–A critical review and some insights for future directions. Journal of Purchasing and Supply Management, 20(1), 18-40. https://doi.org/10.1016/j.pursup.2013.09.001
55. Mackey, T. K., & Nayyar, G. (2017). A review of existing and emerging digital technologies to combat the global trade in fake medicines. Expert Opinion on Drug Safety, 16(5), 587-602. https://doi.org/10.1080/14740338.2017.1313227
56. Angelis, J., da Silva, E. R., & Nikolaou, P. (2021). Blockchain technology and the future of the pharmaceutical industry: Towards a distributed network of trust. International Journal of Pharmaceutical and Healthcare Marketing, 15(3), 455-471. https://doi.org/10.1108/IJPHM-03-2020-0023
57. Aung, M. M., & Chang, Y. S. (2014). Traceability in a food supply chain: Safety and quality perspectives. Food Control, 39, 172-184. https://doi.org/10.1016/j.foodcont.2013.11.007
58. Bosona, T., & Gebresenbet, G. (2013). Food traceability as an integral part of logistics management in food and agricultural supply chain. Food Control, 33(1), 32-48. https://doi.org/10.1016/j.foodcont.2013.02.004
59. Tian, F. (2016). An agri-food supply chain traceability system for China based on RFID & blockchain technology. 2016 13th International Conference on Service Systems and Service Management (ICSSSM), 1-6. https://doi.org/10.1109/ICSSSM.2016.7538424
60. Galvez, J. F., Mejuto, J. C., & Simal-Gandara, J. (2018). Future challenges on the use of blockchain for food traceability analysis. TrAC Trends in Analytical Chemistry, 107, 222-232. https://doi.org/10.1016/j.trac.2018.08.011
61. Kamilaris, A., Fonts, A., & Prenafeta-Boldύ, F. X. (2019). The rise of blockchain technology in agriculture and food supply chains. Trends in Food Science & Technology, 91, 640-652. https://doi.org/10.1016/j.tifs.2019.07.034
62. Büyüközkan, G., & Göçer, F. (2018). Digital supply chain: literature review and a proposed framework for future research. Computers in Industry, 97, 157-177. https://doi.org/10.1016/j.compind.2018.02.010
63. Queiroz, M. M., Ivanov, D., Dolgui, A., & Wamba, S. F. (2022). Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review. Annals of Operations Research, 319(1), 1159-1196. https://doi.org/10.1007/s10479-020-03685-7
64. Kotter, J. P. (2012). Leading change. Harvard Business Review Press. (Book)
65. Schein, E. H., & Schein, P. (2017). Organizational culture and leadership. John Wiley & Sons. (Book)
66. Weber, K., Otto, B., & Österle, H. (2009). One size does not fit all—a contingency approach to data governance. Journal of Data and Information Quality, 1(1), 1-27. https://doi.org/10.1145/1515693.1515696
67. Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data–evolution, challenges and research agenda. International Journal of Information Management, 48, 63-71. https://doi.org/10.1016/j.ijinfomgt.2019.01.021
68. Parker, G. G., Van Alstyne, M. W., & Choudary, S. P. (2016). Platform revolution: How networked markets are transforming the economy and how to make them work for you. WW Norton & Company. (Book)
69. Bauer, W., Hämmerle, M., Schlund, S., & Vocke, C. (2015). Transforming to a hyper-connected society and economy–towards an "Industry 4.0". Procedia Manufacturing, 3, 417-424. https://doi.org/10.1016/j.promfg.2015.07.200
70. Kaplan, R. S., & Norton, D. P. (1996). The balanced scorecard: Translating strategy into action. Harvard Business Press. (Book)
71. Gunasekaran, A., Patel, C., & McGaughey, R. E. (2004). A framework for supply chain performance measurement. International Journal of Production Economics, 87(3), 333-347. https://doi.org/10.1016/j.ijpe.2003.08.003
72. Davenport, T. H., & Short, J. E. (1990). The new industrial engineering: Information technology and business process redesign. MIT Sloan Management Review, 31(4), 11-27.
73. Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165-1188. https://doi.org/10.2307/41703503
74. Legner, C., Eymann, T., Hess, T., Matt, C., Böhmann, T., Drews, P., ... & Ahlemann, F. (2017). Digitalization: Opportunity and challenge for the business and information systems engineering community. Business & Information Systems Engineering, 59(4), 301-308. https://doi.org/10.1007/s12599-017-0484-2
75. Besson, P., & Rowe, F. (2012). Strategizing information systems-enabled organizational transformation: A transdisciplinary review and new directions. The Journal of Strategic Information Systems, 21(2), 103-124. https://doi.org/10.1016/j.jsis.2012.05.001
76. Batini, C., Cappiello, C., Francalanci, C., & Maurino, A. (2009). Methodologies for data quality assessment and improvement. ACM Computing Surveys, 41(3), 1-52. https://doi.org/10.1145/1541880.1541883
77. Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 12(4), 5-33. https://doi.org/10.1080/07421222.1996.11518099
78. Chen, C. P., & Zhang, C. Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on big data. Information Sciences, 275, 314-347. https://doi.org/10.1016/j.ins.2014.01.015
79. Davenport, T. H. (2013). Enterprise analytics: Optimize performance, process, and decisions through big data. FT Press. (Book)
80. Kotter, J. P., & Schlesinger, L. A. (2008). Choosing strategies for change. Harvard Business Review, 86(7-8), 130-139.
81. Armenakis, A. A., & Harris, S. G. (2009). Reflections: Our journey in organizational change research and practice. Journal of Change Management, 9(2), 127-142. https://doi.org/10.1080/14697010902879079
82. By, R. T. (2005). Organisational change management: A critical review. Journal of Change Management, 5(4), 369-380. https://doi.org/10.1080/14697010500359250
83. Schwab, K. (2017). The fourth industrial revolution. Crown Business. (Book)
84. Hecklau, F., Galeitzke, M., Flachs, S., & Kohl, H. (2016). Holistic approach for human resource management in Industry 4.0. Procedia CIRP, 54, 1-6. https://doi.org/10.1016/j.procir.2016.05.102
85. Galbraith, J. R. (2014). Designing organizations: Strategy, structure, and process at the business unit and enterprise levels. John Wiley & Sons. (Book)
86. Cross, R., Ernst, C., & Pasmore, B. (2013). The organizational network fieldbook: Best practices, techniques and exercises to drive organizational innovation and performance. John Wiley & Sons. (Book)
87. Fitzgerald, M., Kruschwitz, N., Bonnet, D., & Welch, M. (2014). Embracing digital technology: A new strategic imperative. MIT Sloan Management Review, 55(2), 1-12.
88. Warner, K. S., & Wäger, M. (2019). Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. Long Range Planning, 52(3), 326-349. https://doi.org/10.1016/j.lrp.2018.12.001
89. Hess, T., Matt, C., Benlian, A., & Wiesböck, F. (2016). Options for formulating a digital transformation strategy. MIS Quarterly Executive, 15(2), 123-139.
90. Li, L., Su, F., Zhang, W., & Mao, J. Y. (2018). Digital transformation by SME entrepreneurs: A capability perspective. Information Systems Journal, 28(6), 1129-1157. https://doi.org/10.1111/isj.12153
91. Albukhitan, S. (2020). Developing digital transformation strategy for manufacturing. Procedia Computer Science, 170, 664-671. https://doi.org/10.1016/j.procs.2020.03.173
92. Cavallo, A., Ghezzi, A., & Balocco, R. (2019). Entrepreneurial ecosystem research: present debates and future directions. International Entrepreneurship and Management Journal, 15(4), 1291-1321. https://doi.org/10.1007/s11365-018-0526-3
93. Geissbauer, R., Vedso, J., & Schrauf, S. (2016). Industry 4.0: Building the digital enterprise. PwC Global Industry 4.0 Survey.
94. Cichosz, M., Wallenburg, C. M., & Knemeyer, A. M. (2020). Digital transformation at logistics service providers: barriers, success factors and leading practices. The International Journal of Logistics Management, 31(2), 209-238. https://doi.org/10.1108/IJLM-08-2019-0229
95. Boyes, H., Hallaq, B., Cunningham, J., & Watson, T. (2018). The industrial internet of things (IIoT): An analysis framework. Computers in Industry, 101, 1-12. https://doi.org/10.1016/j.compind.2018.04.015
96. Shafiq, S. I., Sanin, C., Szczerbicki, E., & Toro, C. (2015). Virtual engineering object (VEO): toward experience-based design and manufacturing for industry 4.0. Cybernetics and Systems, 46(1-2), 35-50. https://doi.org/10.1080/01969722.2015.1007734
97. Williams, N. P., Schubert, P., & Halilovic, S. (2022). Cybersecurity in digital supply chains. International Journal of Information Management Data Insights, 2(1), 100080. https://doi.org/10.1016/j.jjimei.2022.100080
98. Gordon, L. A., Loeb, M. P., Lucyshyn, W., & Zhou, L. (2015). Increasing cybersecurity investments in private sector firms. Journal of Cybersecurity, 1(1), 3-17. https://doi.org/10.1093/cybsec/tyv011
99. Tankard, C. (2016). What the GDPR means for businesses. Network Security, 2016(6), 5-8. https://doi.org/10.1016/S1353-4858(16)30056-3
100. Voigt, P., & Von dem Bussche, A. (2017). The EU general data protection regulation (GDPR): A practical guide. Springer. https://doi.org/10.1007/978-3-319-57959-7
101. Winkelhaus, S., & Grosse, E. H. (2020). Logistics 4.0: a systematic review towards a new logistics system. International Journal of Production Research, 58(1), 18-43. https://doi.org/10.1080/00207543.2019.1612964
102. Kache, F., & Seuring, S. (2017). Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management. International Journal of Operations & Production Management, 37(1), 10-36. https://doi.org/10.1108/IJOPM-02-2015-0078
103. Stock, T., Obenaus, M., Kunz, S., & Kohl, H. (2018). Industry 4.0 as enabler for a sustainable development: A qualitative assessment of its ecological and social potential. Process Safety and Environmental Protection, 118, 254-267. https://doi.org/10.1016/j.psep.2018.06.026
104. Grieves, M. (2014). Digital twin: Manufacturing excellence through virtual factory replication. Digital Manufacturing, 1(1), 1-7.
105. Tao, F., Zhang, H., Liu, A., & Nee, A. Y. (2019). Digital twin in industry: State-of-the-art. IEEE Transactions on Industrial Informatics, 15(4), 2405-2415. https://doi.org/10.1109/TII.2018.2873186
106. Fuller, A., Fan, Z., Day, C., & Barlow, C. (2020). Digital twin: Enabling technologies, challenges and open research. IEEE Access, 8, 108952-108971. https://doi.org/10.1109/ACCESS.2020.2998358
107. Preskill, J. (2018). Quantum computing in the NISQ era and beyond. Quantum, 2, 79. https://doi.org/10.22331/q-2018-08-06-79
108. Orus, R., Mugel, S., & Lizaso, E. (2019). Quantum computing for finance: Overview and prospects. Reviews in Physics, 4, 100028. https://doi.org/10.1016/j.revip.2019.100028
109. Geissdoerfer, M., Savaget, P., Bocken, N. M., & Hultink, E. J. (2017). The circular economy–a new sustainability paradigm? Journal of Cleaner Production, 143, 757-769. https://doi.org/10.1016/j.jclepro.2016.12.048
110. De Jesus, A., & Mendonça, S. (2018). Lost in transition? Drivers and barriers in the eco-innovation road to the circular economy. Ecological Economics, 145, 75-89. https://doi.org/10.1016/j.ecolecon.2017.08.001
111. Sarkis, J. (2021). Supply chain sustainability: Learning from the COVID-19 pandemic. International Journal of Operations & Production Management, 41(1), 63-71. https://doi.org/10.1108/IJOPM-08-2020-0568
112. Kouhizadeh, M., Saberi, S., & Sarkis, J. (2021). Blockchain technology and the sustainable supply chain: Theoretically exploring adoption barriers. International Journal of Production Economics, 231, 107831. https://doi.org/10.1016/j.ijpe.2020.107831
113. Tseng, M. L., Islam, M. S., Karia, N., Fauzi, F. A., & Afrin, S. (2019). A literature review on green supply chain management: Trends and future challenges. Resources, Conservation and Recycling, 141, 145-162. https://doi.org/10.1016/j.resconrec.2018.10.009
114. Malmodin, J., & Lundén, D. (2018). The energy and carbon footprint of the global ICT and E&M sectors 2010–2015. Sustainability, 10(9), 3027. https://doi.org/10.3390/su10093027
115. Christopher, M., & Peck, H. (2004). Building the resilient supply chain. The International Journal of Logistics Management, 15(2), 1-14. https://doi.org/10.1108/09574090410700275
116. Ponomarov, S. Y., & Holcomb, M. C. (2009). Understanding the concept of supply chain resilience. The International Journal of Logistics Management, 20(1), 124-143. https://doi.org/10.1108/09574090910954873
117. Sheffi, Y. (2015). The power of resilience: How the best companies manage the unexpected. MIT Press. (Book)
118. Ivanov, D., & Dolgui, A. (2020). Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak. International Journal of Production Research, 58(10), 2904-2915. https://doi.org/10.1080/00207543.2020.1750727
119. Blackhurst, J., Dunn, K. S., & Craighead, C. W. (2011). An empirically derived framework of global supply resiliency. Journal of Business Logistics, 32(4), 374-391. https://doi.org/10.1111/j.0000-0000.2011.01032.x
120. Choi, T. Y., Dooley, K. J., & Rungtusanatham, M. (2001). Supply networks and complex adaptive systems: Control versus emergence. Journal of Operations Management, 19(3), 351-366. https://doi.org/10.1016/S0272-6963(00)00068-1
121. Surana, A., Kumara, S., Greaves, M., & Raghavan, U. N. (2005). Supply-chain networks: A complex adaptive systems perspective. International Journal of Production Research, 43(20), 4235-4265. https://doi.org/10.1080/00207540500142274
122. Parker, G., & Van Alstyne, M. (2018). Innovation, openness, and platform control. Management Science, 64(7), 3015-3032. https://doi.org/10.1287/mnsc.2017.2757
123. Gawer, A., & Cusumano, M. A. (2014). Industry platforms and ecosystem innovation. Journal of Product Innovation Management, 31(3), 417-433. https://doi.org/10.1111/jpim.12105
124. Kotter, J. P. (2014). Accelerate: Building strategic agility for a faster-moving world. Harvard Business Review Press. (Book)
125. Pan, G., Pan, S. L., & Lim, C. Y. (2015). Examining how firms leverage IT to achieve firm productivity: RBV and dynamic capabilities perspectives. Information & Management, 52(4), 401-412. https://doi.org/10.1016/j.im.2015.01.001
126. Daniel, E. M., & Wilson, H. N. (2003). The role of dynamic capabilities in e-business transformation. European Journal of Information Systems, 12(4), 282-296. https://doi.org/10.1057/palgrave.ejis.3000478
127. Zhu, K., Kraemer, K. L., & Xu, S. (2006). The process of innovation assimilation by firms in different countries: a technology diffusion perspective on e-business. Management Science, 52(10), 1557-1576. https://doi.org/10.1287/mnsc.1050.0487
128. Nguyen, T. H., Sherif, J. S., & Newby, M. (2007). Strategies for successful CRM implementation. Information Management & Computer Security, 15(2), 102-115. https://doi.org/10.1108/09685220710748001
129. Marston, S., Li, Z., Bandyopadhyay, S., Zhang, J., & Ghalsasi, A. (2011). Cloud computing—The business perspective. Decision Support Systems, 51(1), 176-189. https://doi.org/10.1016/j.dss.2010.12.006
130. Rai, A., Patnayakuni, R., & Seth, N. (2006). Firm performance impacts of digitally enabled supply chain integration capabilities. MIS Quarterly, 30(2), 225-246. https://doi.org/10.2307/25148729
131. Iyer, B., & Henderson, J. C. (2012). Business value from clouds: Learning from users. MIS Quarterly Executive, 11(1), 51-60.
132. Yang, Z., Sun, J., Zhang, Y., & Wang, Y. (2015). Understanding SaaS adoption from the perspective of organizational users: A tripod readiness model. Computers in Human Behavior, 45, 254-264. https://doi.org/10.1016/j.chb.2014.12.022
133. Chou, D. C., & Chou, A. Y. (2007). Analysis of a new information systems outsourcing practice: Software-as-a-service business model. International Journal of Information Systems and Change Management, 2(4), 392-405. https://doi.org/10.1504/IJISCM.2007.016371
134. Gupta, P., Seetharaman, A., & Raj, J. R. (2013). The usage and adoption of cloud computing by small and medium businesses. International Journal of Information Management, 33(5), 861-874. https://doi.org/10.1016/j.ijinfomgt.2013.07.001
135. Ross, P., & Blumenstein, M. (2015). Cloud computing as a facilitator of SME entrepreneurship. Technology Analysis & Strategic Management, 27(1), 87-101. https://doi.org/10.1080/09537325.2014.951621
136. Avram, M. G. (2014). Advantages and challenges of adopting cloud computing from an enterprise perspective. Procedia Technology, 12, 529-534. https://doi.org/10.1016/j.protcy.2013.12.525
137. Venters, W., & Whitley, E. A. (2012). A critical review of cloud computing: researching desires and realities. Journal of Information Technology, 27(3), 179-197. https://doi.org/10.1057/jit.2012.17
138. Garrison, G., Kim, S., & Wakefield, R. L. (2012). Success factors for deploying cloud computing. Communications of the ACM, 55(9), 62-68. https://doi.org/10.1145/2330667.2330685
139. Palfrey, J., & Gasser, U. (2016). Interop: The promise and perils of highly interconnected systems. Basic Books. (Book)
140. Laudon, K. C., & Laudon, J. P. (2020). Management information systems: Managing the digital firm (16th ed.). Pearson. (Book)
141. Turban, E., Pollard, C., & Wood, G. (2018). Information technology for management: On-demand strategies for performance, growth and sustainability (11th ed.). John Wiley & Sons. (Book)
142. Jin, X., Wah, B. W., Cheng, X., & Wang, Y. (2015). Significance and challenges of big data research. Big Data Research, 2(2), 59-64. https://doi.org/10.1016/j.bdr.2015.01.006
143. Pagani, M., & Pardo, C. (2017). The impact of digital technology on relationships in a business network. Industrial Marketing Management, 67, 185-192. https://doi.org/10.1016/j.indmarman.2017.08.009
144. Chircu, A. M., & Mahajan, V. (2009). Revisiting the digital divide: An analysis of mobile technology depth and service breadth in the BRIC countries. Journal of Product Innovation Management, 26(4), 455-466. https://doi.org/10.1111/j.1540-5885.2009.00667.x
145. Hofstede, G. (2011). Dimensionalizing cultures: The Hofstede model in context. Online Readings in Psychology and Culture, 2(1), 8. https://doi.org/10.9707/2307-0919.1014
146. Trompenaars, F., & Hampden-Turner, C. (2012). Riding the waves of culture: Understanding diversity in global business. Nicholas Brealey Publishing. (Book)
147. Hall, E. T. (1976). Beyond culture. Anchor Books. (Book)
148. Meyer, E. (2014). The culture map: Breaking through the invisible boundaries of global business. PublicAffairs. (Book)
149. Hofstede, G., & Minkov, M. (2010). Cultures and organizations: Software of the mind. McGraw-Hill Education. (Book)
150. Mackey, T. K., & Nayyar, G. (2017). A review of existing and emerging digital technologies to combat the global trade in fake medicines. Expert Opinion on Drug Safety, 16(5), 587-602. https://doi.org/10.1080/14740338.2017.1313227
151. Kang, H. S., Lee, J. Y., Choi, S., Kim, H., Park, J. H., Son, J. Y., ... & Do Noh, S. (2016). Smart manufacturing: Past research, present findings, and future directions. International Journal of Precision Engineering and Manufacturing-Green Technology, 3(1), 111-128. https://doi.org/10.1007/s40684-016-0015-5
152. Lambert, D. M., & Enz, M. G. (2017). Issues in supply chain management: Progress and potential. Industrial Marketing Management, 62, 1-16. https://doi.org/10.1016/j.indmarman.2016.12.002
153. Seuring, S., & Müller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16(15), 1699-1710. https://doi.org/10.1016/j.jclepro.2008.04.020
154. Wang, G., Gunasekaran, A., Ngai, E. W., & Papadopoulos, T. (2016). Big data analytics in logistics and supply chain management: Certain investigations for research and applications. International Journal of Production Economics, 176, 98-110. https://doi.org/10.1016/j.ijpe.2016.03.014
155. Niesten, E., & Jolink, A. (2015). Sustainable collaboration: The impact of governance and institutions on sustainable performance. Journal of Cleaner Production, 102, 316-324. https://doi.org/10.1016/j.jclepro.2015.05.006
156. Winch, G. M. (2010). Managing construction projects. John Wiley & Sons. (Book)
157. Davies, A., & Hobday, M. (2005). The business of projects: Managing innovation in complex products and systems. Cambridge University Press. (Book)
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