Enhancing Supply Chain Resilience through Information Processing and Digital Integration in Managing Risks and Disruptions
DOI:
https://doi.org/10.69725/jebi.v1i2.177
Keywords:
igital Integration, Supply Chain , Resilience, Information Processing, Risk Management, DisruptionsAbstract
Purpose: This study examines the effect of information processing capabilities and digital supply chain integration on supply chain resilience considering the mediating effect of supply chain risk management in the context of the Indonesian manufacturing sector.
Method: Study implements Partial Least Squares-Structural Equation Modeling (PLS-SEM) to analyze data from professionals in the manufacturing industry in Indonesia with respect to the relations between digital tools, risk management, and resilience.
Findings: In latest study, the authors highlight how incorporating digital technology and managing for information are two key factors contributing to resilient supply chains, especially during periods of disruption. It highlights that companies using advanced technologies including real-time data analytics and cloud computing are in a better position to identify and manage risks, and therefore recover more quickly when disruptions occur.
Novelty: These findings shed new light on the relationship between digital supply chain integration, information processing, resilience, and risk management in an emerging economy such as Indonesia. It builds on existing theories by exploring this dynamic within an industrial setting which has received less attention in the literature.
Implications: The findings have important implications for practice in the field of manufacturing in Indonesia, indicating that the production companies need to invest in digital bases and a solid risk management system. These insights can help policymakers and industry leaders design robust and adaptive supply chains that can navigate effectively through global disruptions and uncertainties
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References
Belhadi, A., Kamble, S. S., Venkatesh, M., Chiappetta Jabbour, C. J., & Benkhati, I. (2022). Building supply chain resilience and efficiency through additive manufacturing: An ambidextrous perspective on the dynamic capability view. International Journal of Production Economics, 249, 108516. https://doi.org/https://doi.org/10.1016/j.ijpe.2022.108516 DOI: https://doi.org/10.1016/j.ijpe.2022.108516
Bose, R., & Luo, X. (2011). Integrative framework for assessing firms’ potential to undertake Green IT initiatives via virtualization – A theoretical perspective. The Journal of Strategic Information Systems, 20(1), 38–54. https://doi.org/https://doi.org/10.1016/j.jsis.2011.01.003 DOI: https://doi.org/10.1016/j.jsis.2011.01.003
Choi, T.-M., Wen, X., Sun, X., & Chung, S.-H. (2019). The mean-variance approach for global supply chain risk analysis with air logistics in the blockchain technology era. Transportation Research Part E: Logistics and Transportation Review, 127, 178–191. https://doi.org/https://doi.org/10.1016/j.tre.2019.05.007 DOI: https://doi.org/10.1016/j.tre.2019.05.007
Chowdhury, M. M. H., & Quaddus, M. (2017). Supply chain resilience: Conceptualization and scale development using dynamic capability theory. International Journal of Production Economics, 188, 185–204. https://doi.org/https://doi.org/10.1016/j.ijpe.2017.03.020 DOI: https://doi.org/10.1016/j.ijpe.2017.03.020
Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023). Unlocking the value of artificial intelligence in human resource management through AI capability framework. Human Resource Management Review, 33(1), 100899. https://doi.org/https://doi.org/10.1016/j.hrmr.2022.100899 DOI: https://doi.org/10.1016/j.hrmr.2022.100899
Deiva Ganesh, A., & Kalpana, P. (2022). Future of artificial intelligence and its influence on supply chain risk management – A systematic review. Computers & Industrial Engineering, 169, 108206. https://doi.org/https://doi.org/10.1016/j.cie.2022.108206 DOI: https://doi.org/10.1016/j.cie.2022.108206
Dey, S. (2023). Surviving major disruptions: Building supply chain resilience and visibility through rapid information flow and real-time insights at the “edge.” Sustainable Manufacturing and Service Economics, 2, 100008. https://doi.org/https://doi.org/10.1016/j.smse.2022.100008 DOI: https://doi.org/10.1016/j.smse.2022.100008
Dubey, R., Bryde, D. J., Dwivedi, Y. K., Graham, G., Foropon, C., & Papadopoulos, T. (2023). Dynamic digital capabilities and supply chain resilience: The role of government effectiveness. International Journal of Production Economics, 258, 108790. https://doi.org/https://doi.org/10.1016/j.ijpe.2023.108790 DOI: https://doi.org/10.1016/j.ijpe.2023.108790
Er Kara, M., Oktay Fırat, S. Ü., & Ghadge, A. (2020). A data mining-based framework for supply chain risk management. Computers & Industrial Engineering, 139, 105570. https://doi.org/https://doi.org/10.1016/j.cie.2018.12.017 DOI: https://doi.org/10.1016/j.cie.2018.12.017
Fatimah, Y. A., Govindan, K., Murniningsih, R., & Setiawan, A. (2020). Industry 4.0 based sustainable circular economy approach for smart waste management system to achieve sustainable development goals: A case study of Indonesia. Journal of Cleaner Production, 269, 122263. https://doi.org/https://doi.org/10.1016/j.jclepro.2020.122263 DOI: https://doi.org/10.1016/j.jclepro.2020.122263
García-Ten, J., Dondi, M., Vieira Lisboa, J. V. M. B., Vicent Cabedo, M., Pérez-Villarejo, L., Rambaldi, E., & Zanelli, C. (2024). Critical raw materials in the global high-throughput ceramic industry. Sustainable Materials and Technologies, 39, e00832. https://doi.org/https://doi.org/10.1016/j.susmat.2024.e00832 DOI: https://doi.org/10.1016/j.susmat.2024.e00832
Govindan, K., Shaw, M., & Majumdar, A. (2021). Social sustainability tensions in multi-tier supply chain: A systematic literature review towards conceptual framework development. Journal of Cleaner Production, 279, 123075. https://doi.org/https://doi.org/10.1016/j.jclepro.2020.123075 DOI: https://doi.org/10.1016/j.jclepro.2020.123075
Hussain, Z. (2021). Paradigm of technological convergence and digital transformation: The challenges of CH sectors in the global COVID-19 pandemic and commencing resilience-based structure for the post-COVID-19 era. Digital Applications in Archaeology and Cultural Heritage, 21, e00182. https://doi.org/https://doi.org/10.1016/j.daach.2021.e00182 DOI: https://doi.org/10.1016/j.daach.2021.e00182
Jelsma, I., Schoneveld, G. C., Zoomers, A., & van Westen, A. C. M. (2017). Unpacking Indonesia’s independent oil palm smallholders: An actor-disaggregated approach to identifying environmental and social performance challenges. Land Use Policy, 69, 281–297. https://doi.org/https://doi.org/10.1016/j.landusepol.2017.08.012 DOI: https://doi.org/10.1016/j.landusepol.2017.08.012
Katsaliaki, K., Galetsi, P., & Kumar, S. (2022). Supply chain disruptions and resilience: a major review and future research agenda. Annals of Operations Research, 319(1), 965–1002. https://doi.org/10.1007/s10479-020-03912-1 DOI: https://doi.org/10.1007/s10479-020-03912-1
Kessler, M., Arlinghaus, J. C., Rosca, E., & Zimmermann, M. (2022). Curse or Blessing? Exploring risk factors of digital technologies in industrial operations. International Journal of Production Economics, 243, 108323. https://doi.org/https://doi.org/10.1016/j.ijpe.2021.108323 DOI: https://doi.org/10.1016/j.ijpe.2021.108323
Kurniawan, T. A., Dzarfan Othman, M. H., Hwang, G. H., & Gikas, P. (2022). Unlocking digital technologies for waste recycling in Industry 4.0 era: A transformation towards a digitalization-based circular economy in Indonesia. Journal of Cleaner Production, 357, 131911. https://doi.org/https://doi.org/10.1016/j.jclepro.2022.131911 DOI: https://doi.org/10.1016/j.jclepro.2022.131911
Lagap, U., & Ghaffarian, S. (2024). Digital post-disaster risk management twinning: A review and improved conceptual framework. International Journal of Disaster Risk Reduction, 110, 104629. https://doi.org/https://doi.org/10.1016/j.ijdrr.2024.104629 DOI: https://doi.org/10.1016/j.ijdrr.2024.104629
Marzi, G., Marrucci, A., Vianelli, D., & Ciappei, C. (2023). B2B digital platform adoption by SMEs and large firms: Pathways and pitfalls. Industrial Marketing Management, 114, 80–93. https://doi.org/https://doi.org/10.1016/j.indmarman.2023.08.002 DOI: https://doi.org/10.1016/j.indmarman.2023.08.002
Nandi, S., Sarkis, J., Hervani, A. A., & Helms, M. M. (2021). Redesigning Supply Chains using Blockchain-Enabled Circular Economy and COVID-19 Experiences. Sustainable Production and Consumption, 27, 10–22. https://doi.org/https://doi.org/10.1016/j.spc.2020.10.019 DOI: https://doi.org/10.1016/j.spc.2020.10.019
Robins, J., & Wiersema, M. F. (1995). A resource-based approach to the multibusiness firm: Empirical analysis of portfolio interrelationships and corporate financial performance. Strategic Management Journal, 16(4), 277–299. https://doi.org/https://doi.org/10.1002/smj.4250160403 DOI: https://doi.org/10.1002/smj.4250160403
Rodríguez-Espíndola, O., Chowdhury, S., Dey, P. K., Albores, P., & Emrouznejad, A. (2022). Analysis of the adoption of emergent technologies for risk management in the era of digital manufacturing. Technological Forecasting and Social Change, 178, 121562. https://doi.org/https://doi.org/10.1016/j.techfore.2022.121562 DOI: https://doi.org/10.1016/j.techfore.2022.121562
Salter, A. J., & Martin, B. R. (2001). The economic benefits of publicly funded basic research: a critical review. Research Policy, 30(3), 509–532. https://doi.org/https://doi.org/10.1016/S0048-7333(00)00091-3 DOI: https://doi.org/10.1016/S0048-7333(00)00091-3
Tariq, A., Badir, Y. F., Tariq, W., & Bhutta, U. S. (2017). Drivers and consequences of green product and process innovation: A systematic review, conceptual framework, and future outlook. Technology in Society, 51, 8–23. https://doi.org/https://doi.org/10.1016/j.techsoc.2017.06.002 DOI: https://doi.org/10.1016/j.techsoc.2017.06.002
Teece, D. J. (2010). Chapter 16 - Technological Innovation and the Theory of the Firm: The Role of Enterprise-Level Knowledge, Complementarities, and (Dynamic) Capabilities. In B. H. Hall & N. B. T.-H. of the E. of I. Rosenberg (Eds.), Handbook of The Economics of Innovation, Vol. 1 (Vol. 1, pp. 679–730). North-Holland. https://doi.org/https://doi.org/10.1016/S0169-7218(10)01016-6 DOI: https://doi.org/10.1016/S0169-7218(10)01016-6
van der Have, R. P., & Rubalcaba, L. (2016). Social innovation research: An emerging area of innovation studies? Research Policy, 45(9), 1923–1935. https://doi.org/https://doi.org/10.1016/j.respol.2016.06.010 DOI: https://doi.org/10.1016/j.respol.2016.06.010
Verma, S., & Gustafsson, A. (2020). Investigating the emerging COVID-19 research trends in the field of business and management: A bibliometric analysis approach. Journal of Business Research, 118, 253–261. https://doi.org/https://doi.org/10.1016/j.jbusres.2020.06.057 DOI: https://doi.org/10.1016/j.jbusres.2020.06.057
Wang, X., Liu, Z., Li, J., & Lei, X. (2023). How organizational unlearning leverages digital process innovation to improve performance: The moderating effects of smart technologies and environmental turbulence. Technology in Society, 75, 102395. https://doi.org/https://doi.org/10.1016/j.techsoc.2023.102395 DOI: https://doi.org/10.1016/j.techsoc.2023.102395
Wong, C. W. Y., Lirn, T.-C., Yang, C.-C., & Shang, K.-C. (2020). Supply chain and external conditions under which supply chain resilience pays: An organizational information processing theorization. International Journal of Production Economics, 226, 107610. https://doi.org/https://doi.org/10.1016/j.ijpe.2019.107610 DOI: https://doi.org/10.1016/j.ijpe.2019.107610
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