The impact of technology-driven data analytics on information sharing and supply chain responsiveness - A conceptual framework
DOI:
https://doi.org/10.15282/jgi.8.2.2025.12044Keywords:
Technology data driven analytics, Information sharing, Supply chain responsiveness, Supply chain management , Artificial intelligence, Operational performanceAbstract
This study examined the impact of technology-driven data analytics (TDDA) on information sharing (IS) and supply chain responsiveness (SCR), proposing a conceptual framework to understand the interrelationships between these variables. Moreover, this study identified key technological innovations, such as big data analytics (BDA), machine learning (ML), the Internet of Things (IoT), artificial intelligence (AI), and blockchain, that can facilitate the collection, processing, and sharing of information across supply chain partners. These technologies enable faster and more accurate decision-making, significantly enhancing SCR's ability to respond to fluctuating demand, disruptions, and other dynamic changes. The conceptual framework developed in this paper outlined the pathways through which data analytics influenced the effectiveness of information systems (IS) and the ability of supply chains to respond quickly to market conditions. The paper provided insights into the benefits of implementing these technologies within supply chains through a systematic review of current literature. This study contributed significantly to understanding the correlations between TDDA and SCR. Furthermore, the developed conceptual framework explained the positive mediating relationship of IS to enhance the impact of TDDA on SCR. The findings suggested that TDDA, when integrated with robust information-sharing mechanisms, can substantially improve supply chain agility, resilience, and overall operational performance. This paper contributed to understanding how technology can transform traditional supply chain practices, offering theoretical and practical implications for organizations aiming to enhance their SCR in the digital age.
References
Ahmed, S., Kalsoom, T., Ramzan, N., Pervez, Z., Azmat, M., Zeb, B., & Ur Rehman, M. (2021). Towards supply chain visibility using internet of things: A dyadic analysis review. Sensors, 21(12), 4158.
Akter, S., Wamba, S. F., Gunasekaran, A., Dubey, R., & Childe, S. J. (2016). How to improve firm performance using big data analytics capability and business strategy alignment? International journal of production economics, 182, 113-131.
Alasaari, J. (2021). Supply chain planning and analytics. IBM. Supply Chain Planning with IBM Planning Analytics
Ali, M. (2024). Big data driven innovations thrive supply chain. The Journal of Technology, Management, and Applied Engineering, 16138.
Alzoubi, H., & Yanamandra, R. (2020). Investigating the mediating role of information sharing strategy on agile supply chain. Uncertain Supply Chain Management, 8(2), 273-284.
Asamoah, D., Nuertey, D., Agyei-Owusu, B., & Akyeh, J. (2021). The effect of supply chain responsiveness on customer development. The International Journal of Logistics Management, 32(4), 1190-1213.
Awasthi, S. (2024). Artificial intelligence in supply chain management. Journal of Student Research, 13(1), 1-7.
Ayoub, H. F., & Abdallah, A. B. (2019). The effect of supply chain agility on export performance: The mediating roles of supply chain responsiveness and innovativeness. Journal of Manufacturing Technology Management, 30(5), 821-839.
Baah, C., Agyeman, D. O., Acquah, I. S. K., Agyabeng-Mensah, Y., Afum, E., Issau, K., ... & Faibil, D. (2021). Effect of information sharing in supply chains: understanding the roles of supply chain visibility, agility, collaboration on supply chain performance. Benchmarking: An International Journal, 29(2), 434-455.
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120
Barzizza, E., Biasetton, N., Ceccato, R., & Salmaso, L. (2023). Big data analytics and machine learning in supply chain 4.0: A literature review. Stats, 6(2), 596-616.
Blome, C., Schoenherr, T., & Rexhausen, D. (2013). Antecedents and enablers of supply chain agility and its effect on performance: a dynamic capabilities perspective. International Journal of Production Research, 51(4), 1295-1318.
Britt, H. (2024). How Machine Learning is Transforming Supply Chain Management. UNA. https://una.com/resources/article/how-machine-learning-is-transforming-supply-chain-management
Brown, S. (2019). Supply chain visibility boosts consumer trust, and even sales. MIT Management. https://mitsloan.mit.edu/ideas-made-to-matter/supply-chain-visibility-boosts-consumer-trust-and-even- sales
Catalan, M., & Kotzab, H. (2003). Assessing the responsiveness in the Danish mobile phone supply chain. International Journal of Physical Distribution & Logistics Management, 33(8), 668-685.
Cen, L., Hertzel, M., & Schiller, C. (2025). Speed matters: Limited attention and supply chain information diffusion. Management Science, 71(10), 8642–8669
Cohen, M. C., & Tang, C. S. (2024). The role of AI in developing resilient supply chains. Georgetown Journal of International Affairs. https://gjia.georgetown.edu/2024/02/05/the-role-of-ai-in-developing-resilient-supply-chains/
Crudu, A. (2025). How IoT is revolutionizing industrial automation and boosting supply chain efficiency. MoldStud. https://moldstud.com/articles/p-how-iot-is-revolutionizing-industrial-automation-and-boosting-supply-chain-efficiency
Difrancesco, R. M., Meena, P., & Kumar, G. (2023). How blockchain technology improves sustainable supply chain processes: a practical guide. Operations Management Research, 16(2), 620-641.
D’Souza, J., & Jambhale, R. (2025). Supply chain facts and statistics (2025). ElectroIQ. https://electroiq.com/stats/supply-chain-statistics/
Dubey, R., Gunasekaran, A., & Childe, S. J. (2018). Big data analytics capability in supply chain agility: The moderating effect of organizational flexibility. Management Decision, 57(8), 2092-2112.
Eckstein, D., Goellner, M., Blome, C., & Henke, M. (2015). The performance impact of supply chain agility and supply chain adaptability: the moderating effect of product complexity. International Journal of Production Research, 53(10), 3028-3046.
Burnett, S. (2025). Blockchain in supply chain finance statistics 2026: How blockchain is redefining supply chain finance. CoinLaw. https://coinlaw.io/blockchain-in-supply-chain-finance-statistics/
Elopre, J. L. (2023). The impact of data analytics on supply chain decision-making. Proventa International. https://proventainternational.com/the-impact-of-data-analytics-on-supply-chain-decision-making/
FasterCapital, Inc. (2024). Supply chain agility: Building supply chain agility for better coordination. FasterCapital. https://fastercapital.com/articles/Supply-Chain-Agility--Building-Supply-Chain-Agility-for-Better-Coordination.html
Flynn, B. B., Huo, B., & Zhao, X. (2010). The impact of supply chain integration on performance: A contingency and configuration approach. Journal of Operations Management, 28(1), 58-71.
Fosso Wamba, S., Queiroz, M. M., Guthrie, C., & Braganza, A. (2022). Industry experiences of artificial intelligence (AI): benefits and challenges in operations and supply chain management. Production Planning & Control, 33(16), 1493-1497.
Ghobakhloo, M., Iranmanesh, M., Foroughi, B., Tseng, M. L., Nikbin, D., & Khanfar, A. A. (2025). Industry 4.0 digital transformation and opportunities for supply chain resilience: a comprehensive review and a strategic roadmap. Production Planning & Control, 36(1), 61-91.
Giannakis, M., Spanaki, K., & Dubey, R. (2019). A cloud-based supply chain management system: effects on supply chain responsiveness. Journal of Enterprise Information Management, 32(4), 585-607.
Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645-1660.
Handanga, S., Bernardino, J., & Pedrosa, I. (2021, June). Big data analytics on the supply chain management: a significant impact. In 2021 16th Iberian Conference on Information Systems and Technologies (CISTI) (pp. 1-6). IEEE.
Handfield, R. B., & Bechtel, C. (2002). The role of trust and relationship structure in improving supply chain responsiveness. Industrial Marketing Management, 31(4), 367-382.
Hasan, R., Kamal, M. M., Daowd, A., Eldabi, T., Koliousis, I., & Papadopoulos, T. (2024). Critical analysis of the impact of big data analytics on supply chain operations. Production Planning & Control, 35(1), 46-70.
Hayat, K., Abbas, A., Siddique, M., & Cheema, K. U. R. (2012). A study of the different factors that affecting the supply chain responsiveness. Social Sciences and Humanities, 3(3), 345-356.
Holweg, M. (2005). The three dimensions of responsiveness. International Journal of Operations & Production Management, 25(7), 603-622.
Huzaifa, I. (2024). Impact of Blockchain Technology on Supply Chain Management Efficiency and Transparency in Pakistan. International Journal of Supply Chain Management, 9(1), 16 – 26.
Intellias. (2023, March 20). 18 examples of how businesses apply AI in the supply chain. Intellias. https://intellias.com/ai-in-supply-chain/
Jafari, H., Ghaderi, H., Malik, M., & Bernardes, E. (2023). The effects of supply chain flexibility on customer responsiveness: the moderating role of innovation orientation. Production Planning & Control, 34(16), 1543-1561.
Jahin, M. A., Naife, S. A., Saha, A. K., & Mridha, M. F. (2023). AI in Supply Chain Risk Assessment: A Systematic Literature Review and Bibliometric Analysis. arXiv preprint arXiv:2401.10895.
Jahin, M. A., Shahriar, A., & Amin, M. A. (2024). MCDFN: Supply Chain Demand Forecasting via an Explainable Multi-Channel Data Fusion Network Model Integrating CNN, LSTM, and GRU. arXiv preprint arXiv:2405.15598.
Karim, M. R., Rodgers, C., & Hossain, M. A. (2024). The Role of Internet of Things (IoT) in Real-Time Supply Chain Monitoring. International Journal of Research and Innovation in Social Science, 8(10), 1800-1816.
Kim, M., Suresh, N. C., & Kocabasoglu-Hillmer, C. (2013). An impact of manufacturing flexibility and technological dimensions of manufacturing strategy on improving supply chain responsiveness: Business environment perspective. International Journal of Production Research, 51(18), 5597-5611.
Li, X., Cheng, Y., Xia, X., & Møller, C. (2024). Data Governance and Data Management in Operations and Supply Chain: A Literature Review. arXiv preprint arXiv:2407.06199.
Li, X., Zhao, X., Lee, H. L., & Voss, C. (2023). Building responsive and resilient supply chains: Lessons from the COVID‐19 disruption. Journal of Operations Management, 69(3), 352-358.
Linder, J. (2025). Supply chain in the IoT industry statistics. Gitnux. https://gitnux.org/supply-chain-in-the-iot-industry-statistics
Lindert, M. te. (2021, February 25). Supply chain visibility really does improve profit. Supply Chain Movement. https://www.supplychainmovement.com/supply-chain-visibility-really-does-improve-profit/
Loftware, Inc. (2024). 90% of Industry Professionals Call for Greater Connection Across Global Supply Chains, Loftware Survey Reveals. Prnewswire. https://www.prnewswire.com/news-releases/90-of-industry-professionals-call-for-greater-connection-across-global-supply-chains-loftware-survey-reveals-302305559.html
Longo, F., Nicoletti, L., Padovano, A., d'Atri, G., & Forte, M. (2019). Blockchain-enabled supply chain: An experimental study. Computers & Industrial Engineering, 136, 57-69.
Lotfi, Z., Mukhtar, M., Sahran, S., & Zadeh, A. T. (2013). Information sharing in supply chain management. Procedia Technology, 11, 298-304.
Maheshwari, S., Gautam, P., & Jaggi, C. K. (2021). Role of Big Data Analytics in supply chain management: current trends and future perspectives. International Journal of Production Research, 59(6), 1875-1900.
Mandal, S. (2015). Supply chain responsiveness: a logistics integration perspective and impact on firm performance. International Journal of Applied Management Science, 7(3), 244-268.
Manzoor, R., Sahay, B. S., & Singh, S. K. (2022). Blockchain technology in supply chain management: An organizational theoretic overview and research agenda. Annals of Operations Research, 1-48.
Mărcuță, C. (2024). Blockchain and big data analytics - revolutionizing supply chain management. Moldstud. https://moldstud.com/articles/p-exploring-the-integration-of-blockchain-and-big-data-analytics-in-supply-chain-management
Matchette, J & Seikel, A. (2024). A meaningful payoff from supply chain collaboration. MH&L. A meaningful payoff from supply chain collaboration | Material Handling and Logistics
Pangarkar, T. (2024). AI in Supply Chain Market to Reach USD 157.6 Billion by 2033. Market.Us. Scoop. https://scoop.market.us/ai-in-supply-chain-market-news
Panigrahi, R. R., Singh, N., & Muduli, K. (2024). Digital technologies and food supply chain: A scoping view from 2010 to 2024. International Journal of Industrial Engineering and Operations Management.
Pasupuleti, V., Thuraka, B., Kodete, C. S., & Malisetty, S. (2024). Enhancing supply chain agility and sustainability through machine learning: Optimization techniques for logistics and inventory management. Logistics, 8(3), 73.
Qrunfleh, S., & Tarafdar, M. (2013). Lean and agile supply chain strategies and supply chain responsiveness: the role of strategic supplier partnership and postponement. Supply Chain Management: An International Journal, 18(6), 571-582.
Handanga, S., Bernardino, J., & Pedrosa, I. (2021, June). Big data analytics on the supply chain management: A significant impact. In 2021 16th Iberian Conference on Information Systems and Technologies (CISTI) (pp. 1-6). IEEE.
Raweewan, M., & Ferrell Jr, W. G. (2018). Information sharing in supply chain collaboration. Computers & Industrial Engineering, 126, 269-281.
Relearnx. (2024). Supply Chain Agility: The New Competitive Edge. Relearnx.com. https://www.relearnx.com/blog/supply-chain-agility-the-new-competitive-edge
Roh, J., Hong, P., & Min, H. (2014). Implementation of a responsive supply chain strategy in global complexity: The case of manufacturing firms. International Journal of Production Economics, 147, 198-210.
Saleh, Z., & Shabir, M. (2023). Industry 4.0 Technologies Study in Supply Chain Operation Management-A Bibliometric Analysis Perspective. International Journal of Innovation and Industrial Revolution, 5(14), 01-21.
Sallam, K., Mohamed, M., & Wagdy Mohamed, A. (2023). Internet of things (IoT) in supply chain management: challenges, opportunities, and best practices. Sustainable Machine Intelligence Journal, 2, 1–3.
Samuels, A. (2025). Examining the integration of artificial intelligence in supply chain management from Industry 4.0 to 6.0: a systematic literature review. Frontiers in Artificial Intelligence, 7, 1477044.
Santiago, B. D. S., Scavarda, L. F., Gusmão Caiado, R. G., Santos, R. S., & Mattos Nascimento, D. L. D. (2025). Corporate social responsibility and circular economy integration framework within sustainable supply chain management: Building blocks for industry 5.0. Corporate Social Responsibility and Environmental Management, 32(1), 269-290.
Sarker, I. H. (2021). Data science and analytics: An overview from data-driven smart computing, decision-making and applications perspective. SN Computer Science, 2(5), 377.
Singh, R. K. (2025). Measuring supply chain resilience performance: role of data analytics, collaboration and flexibility. Measuring Business Excellence.
Spears. E. (2023). Inside fashion’s smart warehouse. Vouge Business. https://www.voguebusiness.com/-technology/inside-fashions-smart-warehouses
Strategymrc. (2024). IoT for supply chain management market. Strategymrc. https://www.strategymrc.com/report/iot-for-supply-chain-management-market
Tang, Q., Zhang, Z., Yuan, Z., & Li, Z. (2022). The game analysis of information sharing for supply chain enterprises in the blockchain. Frontiers in Manufacturing Technology, 2, 880332.
Thakur, M., Patel, P., Gupta, L. K., Kumar, M., & Kumar, A. S. S. (2023). Applications of artificial intelligence and machine learning in supply chain management: a comprehensive review. European Chemical Bulletin, 8, 2838-2851.
Thatte, A. A. (2007). Competitive advantage of a firm through supply chain responsiveness and SCM practices (Doctoral dissertation, University of Toledo). http://rave.ohiolink.edu/etdc/view?acc_num=toledo1176401773
Thatte, A. A., Rao, S. S., & Ragu-Nathan, T. S. (2013). Impact of SCM practices of a firm on supply chain responsiveness and competitive advantage of a firm. Journal of Applied Business Research, 29(2), 499-530.
Tiwari, S., Wee, H. M., & Daryanto, Y. (2018). Big data analytics in supply chain management between 2010 and 2016: Insights to industries. Computers & Industrial Engineering, 115, 319-330.
Udeh, E. O., Amajuoyi, P., Adeusi, K. B., & Scott, A. O. (2024). The role of IoT in boosting supply chain transparency and efficiency. Magna Scientia Advanced Research and Reviews, 12(1), 178-197.
Van Hoek, R. I., Harrison, A., & Christopher, M. (2001). Measuring agile capabilities in the supply chain. International Journal of Operations & Production Management, 21(1/2), 126-148.
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.
Walter, A., Ahsan, K., & Rahman, S. (2025). Application of artificial intelligence in demand planning for supply chains: a systematic literature review. The International Journal of Logistics Management, 36(3), 672-719.
Wang, H., Sua, L. S., & Alidaee, B. (2024). Enhancing supply chain security with automated machine learning. arXiv preprint arXiv:2406.13166.
Wang, H., Sua, L. S., & Alidaee, B. (2024). Enhancing supply chain security with automated machine learning. arXiv preprint arXiv:2406.13166.
Wernerfelt, B. (1984). A resource‐based view of the firm. Strategic Management Journal, 5(2), 171-180.
Yapa, S. T. W. S. (2018). Factors influencing supply chain responsiveness in the apparel industry in Sri Lanka. Journal of Business and Technology, 1(2), 65-86.
Yavaprabhas, K., Pournader, M., & Seuring, S. (2024). Blockchain and trust in supply chains: A bibliometric analysis and trust transfer perspective. International Journal of Production Research, 1-28.
Zamani, E. D., Smyth, C., Gupta, S., & Dennehy, D. (2023). Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review. Annals of Operations Research, 327(2), 605-632.
Zhang, Q., Ullah, A., Ashraf, S., & Abdullah, M. (2024). Synergistic impact of internet of things and big-data-driven supply chain on sustainable firm performance. Sustainability, 16(13), 5717.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 The Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
