The Impact of Big Data Analytics Capabilities on Sustainable Performance: an Application to Culinary and Fashion SME’s
Keywords:
Sustainable Performance, Big Data Analytics Capabilities, Supply Chain Management Capabilities, Circular Economy Practices
Abstract
Using the analytical capabilities of Big Data, this research investigates the mechanisms by which sustainable performance helps create sustainable value. The research also looks at how supply chain management capabilities (SCMC) and circular economy practices (CEP) act as mediators in influencing sustainable performance. The focus of this research is micro, small, and medium enterprises (MSMEs) operating in Central Java in the food and fashion industries. This study used purposive sampling method and took 100 samples from the respondent population. Data were collected through questionnaires and then processed through path analysis using SPSS version 25. The results of the path analysis conducted, it can be seen that the Big Data Analytic Capabilities variable has a direct influence on Sustainable Performance through the mediating variables of Supply Chain Management and Circular Economy Practices.
References
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Awan, U., Shamim, S., Khan, Z., Zia, N.U., Shariq, S.M. and Khan, M.N. (2021), “Big data analytics capability and decision-making: the role of data-driven insight on circular economy performance”, Technological Forecasting and Social Change, Vol. 168, 120766.
Bag, S. and Rahman, M.S. (2023), “The role of capabilities in shaping sustainable supply chain flexibility and enhancing circular economy-target performance: an empirical study”, Supply Chain Management: An International Journal, Vol. 28 No. 1, pp. 162-178, doi: 10.1108/SCM-05- 2021-0246.
Barton, D. and Court, D. (2012), “Making Advanced Analytics Work for You: a practical guide to capitalizing on big data”, Harvard Business Review, Vol. 90 No. 10, pp. 78-83.
Chiappetta Jabbour, C.J., Jabbour Lopes de Sousa, A.B., Sarkis, J. and Filho, M.G. (2019), “Unlocking the circular economy through new business models based on large-scale data: an integrative framework and research agenda”, Technological Forecasting and Social Change, Vol. 144, pp. 546-552.
Chiappetta Jabbour, C.J., Fiorini, P.D.C., Ndubisi, N.O., Queiroz, M.M. and Piato, E´.L. (2020), “Digitally- enabled sustainable supply chains in the 21st century: a review and a research agenda”, Science of the Total Environment, Vol. 725, 138177.
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Cui, L., Jin, Z., Li, Y. and Wang, Y. (2022), “Effects of control mechanisms on supply chain resilience and sustainability performance”, Australian Journal of Management, available at: https:// journals.sagepub.com/doi/pdf/10.1177/03128962211066532
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Mikalef, P., Pappas, I.O., Krogstie, J. and Giannakos, M. (2018), “Big data analytics capabilities: a systematic literature review and research agenda”, Information Systems and E-Business Management, Vol. 16 No. 3, pp. 547-578.
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Munir, M., Jajja, M.S.S., Chatha, K.A. and Farooq, S. (2020), “Supply chain risk management and operational performance: the enabling role of supply chain integration”, International Journal of Production Economics, Vol. 227, 107667.
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Nursimloo, S., Ramdhony, D. and Mooneeapen, O. (2020), “Influence of board characteristics on TBL reporting”, Corporate Governance, Vol. 20 No. 5, pp. 765-780.
Nutsugah, F.F., Anning-Dorson, T., Braimah, S.M. and Tweneboah-Koduah, E.Y. (2021), “Candle under a bushel: communicating environmental performance to improve firm performance”, International Journal of Productivity and Performance Management, Vol. 70 No. 8, pp. 1953-1971.
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Purvis, B., Mao, Y. and Robinson, D. (2019), “The concept of sustainable economic development”, Environmental Conservation, Vol. 14 No. 2, pp. 101-110.
Rai, Patnayakuni and Seth (2006), “Firm performance impacts of digitally enabled supply chain integration capabilities”, MIS Quarterly, Vol. 30 No. 2, p. 225.
Raut, R.D., Mangla, S.K., Narwane, V.S., Gardas, B.B., Priyadarshinee, P. and Narkhede, B.E. (2019), “Linking big data analytics and operational sustainability practices for sustainable business management”, Journal of Cleaner Production, Vol. 224, pp. 10-24.
Schroeder, P., Anggraeni, K. and Weber, U. (2019), “The relevance of circular economy practices to the sustainable development goals”, Journal of Industrial Ecology, Vol. 23 No. 1, pp. 77-95.
Shafiq, A., Ahmed, M.U. and Mahmoodi, F. (2020), “Impact of supply chain analytics and customer pressure for ethical conduct on socially responsible practices and performance: an exploratory study”, International Journal of Production Economics, Vol. 225, 107571.
Torasa, C. and Mekhum, W. (2020), “Impact of supply chain capabilities on supply chain performance: a case of Thai electronic industry”, International Journal of Supply Chain Management, Vol. 9 No. 1, pp. 225-231.
Wang, G., Gunasekaran, A., Ngai, E.W.T. and Papadopoulos, T. (2016), “Big data analytics in logistics and supply chain management: certain investigations for research and applications”, International Journal of Production Economics, Vol. 176, pp. 98-110.
Wu, F., Yeniyurt, S., Kim, D. and Cavusgil, S.T. (2006), “The impact of information technology on supply chain capabilities and firm performance: a resource-based view”, Industrial Marketing Management, Vol. 35 No. 4, pp. 493-504.
AlNuaimi, B.K., Khan, M. and Ajmal, M.M. (2021), “The role of big data analytics capabilities in greening e-procurement: a higher order PLS-SEM analysis”, Technological Forecasting and Social Change, Vol. 169, 120808.
Andersson, S., Svensson, G., Molina-Castillo, F.J., Otero-Neira, C., Lindgren, J., Karlsson, N.P.E. and Laurell, H. (2022), “Sustainable development—direct and indirect effects between economic, social, and environmental dimensions in business practices”, Corporate Social Responsibility and Environmental Management, available at: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ csr.2261
Arunachalam, D., Kumar, N. and Kawalek, J.P. (2018), “Understanding big data analytics capabilities in supply chain management: unravelling the issues, challenges and implications for practice”, Transportation Research Part E: Logistics and Transportation Review, Vol. 114, pp. 416-436.
Awan, U., Shamim, S., Khan, Z., Zia, N.U., Shariq, S.M. and Khan, M.N. (2021), “Big data analytics capability and decision-making: the role of data-driven insight on circular economy performance”, Technological Forecasting and Social Change, Vol. 168, 120766.
Bag, S. and Rahman, M.S. (2023), “The role of capabilities in shaping sustainable supply chain flexibility and enhancing circular economy-target performance: an empirical study”, Supply Chain Management: An International Journal, Vol. 28 No. 1, pp. 162-178, doi: 10.1108/SCM-05- 2021-0246.
Barton, D. and Court, D. (2012), “Making Advanced Analytics Work for You: a practical guide to capitalizing on big data”, Harvard Business Review, Vol. 90 No. 10, pp. 78-83.
Chiappetta Jabbour, C.J., Jabbour Lopes de Sousa, A.B., Sarkis, J. and Filho, M.G. (2019), “Unlocking the circular economy through new business models based on large-scale data: an integrative framework and research agenda”, Technological Forecasting and Social Change, Vol. 144, pp. 546-552.
Chiappetta Jabbour, C.J., Fiorini, P.D.C., Ndubisi, N.O., Queiroz, M.M. and Piato, E´.L. (2020), “Digitally- enabled sustainable supply chains in the 21st century: a review and a research agenda”, Science of the Total Environment, Vol. 725, 138177.
Cui, L., Wu, H., Lang, X. and Li, Y. (2021), “Exploring circular supply chain practices from a dual perspective: using a hybrid method under uncertainty”, International Journal of Logistics Research and Applications. doi: 10.1080/13675567.2021.1983527.
Cui, L., Jin, Z., Li, Y. and Wang, Y. (2022), “Effects of control mechanisms on supply chain resilience and sustainability performance”, Australian Journal of Management, available at: https:// journals.sagepub.com/doi/pdf/10.1177/03128962211066532
Gebhardt, M., Spieske, A. and Birkel, H. (2022), “The future of the circular economy and its effect on supply chain dependencies: empirical evidence from a Delphi study”, Transportation Research Part E: Logistics and Transportation Review, Vol. 157, 102570.
Govindan, K. and Hasanagic, M. (2018), “A systematic review on drivers, barriers, and practices towards circular economy: a supply chain perspective”, International Journal of Production Research, Vol. 56 Nos 1-2, pp. 278-311.
Hair, J.F. Jr Hult, G.T.M., Ringle, C.M. and Sarstedt, M. (2022), A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 3rd ed., SAGE Publications, Thousand Oaks, CA.
Iranmanesh, M., Zailani, S., Hyun, S.S., Ali, M.H. and Kim, K. (2019), “Impact of lean manufacturing practices on firms’ sustainable performance: lean culture as a moderator”, Sustainability, Vol. 11 No. 4, p. 1112.
Jensen, J.P., Prendeville, S.M., Bocken, N.M.P. and Peck, D. (2019), “Creating sustainable value through remanufacturing: three industry cases”, Journal of Cleaner Production, Vol. 218, pp. 304-314.
Kim, G., Shin, B. and Kwon, O. (2012), “Investigating the value of sociomaterialism in conceptualizing IT capability of a firm”, Journal of Management Information Systems, Vol. 29 No. 3, pp. 327-362.
Kristoffersen, E., Blomsma, F., Mikalef, P. and Li, J. (2020), “The smart circular economy: a digital- enabled circular strategies framework for manufacturing companies”, Journal of Business Research, Vol. 120, pp. 241-261.
Kristoffersen, E., Mikalef, P., Blomsma, F. and Li, J. (2021a), “The effects of business analytics capability on circular economy implementation, resource orchestration capability, and firm performance”, International Journal of Production Economics, Vol. 239, 108205.
Le, T.T., Behl, A. and Pereira, V. (2022), “Establishing linkages between circular economy practices and sustainable performance: the moderating role of circular economy entrepreneurship”, Management Decision, Vol. ahead-of-print No. ahead-of-print, doi: 10.1108/MD-02-2022-0150.
Lee, J.S., Kim, S.K. and Lee, S.Y. (2016), “Sustainable supply chain capabilities: accumulation, strategic types and performance”, Sustainability, Vol. 8 No. 6, pp. 1-16.
Mikalef, P., Pappas, I.O., Krogstie, J. and Giannakos, M. (2018), “Big data analytics capabilities: a systematic literature review and research agenda”, Information Systems and E-Business Management, Vol. 16 No. 3, pp. 547-578.
Modgil, S., Gupta, S., Sivarajah, U. and Bhushan, B. (2021), “Big data-enabled large-scale group decision making for circular economy: an emerging market context”, Technological Forecasting and Social Change, Vol. 166, 120607.
Munir, M., Jajja, M.S.S., Chatha, K.A. and Farooq, S. (2020), “Supply chain risk management and operational performance: the enabling role of supply chain integration”, International Journal of Production Economics, Vol. 227, 107667.
Setyawan, N. A., Utami, H., Nugroho, B. S., & Ayuwardani, M. (2022). Analysis of the Driving Factors of Implementing Green Supply Chain Management in SME in the City of Semarang. arXiv preprint arXiv:2212.12891.
Nursimloo, S., Ramdhony, D. and Mooneeapen, O. (2020), “Influence of board characteristics on TBL reporting”, Corporate Governance, Vol. 20 No. 5, pp. 765-780.
Nutsugah, F.F., Anning-Dorson, T., Braimah, S.M. and Tweneboah-Koduah, E.Y. (2021), “Candle under a bushel: communicating environmental performance to improve firm performance”, International Journal of Productivity and Performance Management, Vol. 70 No. 8, pp. 1953-1971.
Potting, J., Hekkert, M., Worrell, E. and Hanemaaijer, A. (2017), “Circular economy: measuring innovation in the product chain”, available at: https://dspace.library.uu.nl/bitstream/handle/ 1874/358310/Circular.pdf?sequence53
Purvis, B., Mao, Y. and Robinson, D. (2019), “The concept of sustainable economic development”, Environmental Conservation, Vol. 14 No. 2, pp. 101-110.
Rai, Patnayakuni and Seth (2006), “Firm performance impacts of digitally enabled supply chain integration capabilities”, MIS Quarterly, Vol. 30 No. 2, p. 225.
Raut, R.D., Mangla, S.K., Narwane, V.S., Gardas, B.B., Priyadarshinee, P. and Narkhede, B.E. (2019), “Linking big data analytics and operational sustainability practices for sustainable business management”, Journal of Cleaner Production, Vol. 224, pp. 10-24.
Schroeder, P., Anggraeni, K. and Weber, U. (2019), “The relevance of circular economy practices to the sustainable development goals”, Journal of Industrial Ecology, Vol. 23 No. 1, pp. 77-95.
Shafiq, A., Ahmed, M.U. and Mahmoodi, F. (2020), “Impact of supply chain analytics and customer pressure for ethical conduct on socially responsible practices and performance: an exploratory study”, International Journal of Production Economics, Vol. 225, 107571.
Torasa, C. and Mekhum, W. (2020), “Impact of supply chain capabilities on supply chain performance: a case of Thai electronic industry”, International Journal of Supply Chain Management, Vol. 9 No. 1, pp. 225-231.
Wang, G., Gunasekaran, A., Ngai, E.W.T. and Papadopoulos, T. (2016), “Big data analytics in logistics and supply chain management: certain investigations for research and applications”, International Journal of Production Economics, Vol. 176, pp. 98-110.
Wu, F., Yeniyurt, S., Kim, D. and Cavusgil, S.T. (2006), “The impact of information technology on supply chain capabilities and firm performance: a resource-based view”, Industrial Marketing Management, Vol. 35 No. 4, pp. 493-504.
Published
2023-10-02
How to Cite
Nanang Adie Setyawan, Bagus Yunianto Wibowo, Mellasanti Ayuwardani, Vinda Setya Kartika, & Novitasari Eviyanti. (2023). The Impact of Big Data Analytics Capabilities on Sustainable Performance: an Application to Culinary and Fashion SME’s. Asian Journal of Management, Entrepreneurship and Social Science, 3(04), 731-746. Retrieved from http://ajmesc.com/index.php/ajmesc/article/view/548
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