Big Data Analytics Capabilities and Competitive Advantage in Batik SMEs: The Mediating Roles of SCM and E-CRM

Authors

  • Nanang Adie Setyawan Politeknik Negeri Semarang, Indonesia
  • Bagus Yunianto Wibowo Politeknik Negeri Semarang, Indonesia
  • Novitasari Eviyanti Politeknik Negeri Semarang, Indonesia
  • Irin Mirrah Luthfia Politeknik Negeri Semarang, Indonesia
  • Eva Purnamasari Politeknik Negeri Semarang, Indonesia

DOI:

https://doi.org/10.24256/kharaj.v7i2.9654

Keywords:

Big Data Analytics Capabilities, Sustainable Performance, Competitive Advantage, Circular Economy Practices

Abstract

This study contributes to sustainable supply chain literature by integrating organizational and institutional perspectives within the context of traditional creative industries. This study examines how Big Data Analytics Capabilities (BDAC) contribute to sustainable performance and competitive advantage among batik micro, small, and medium enterprises (MSMEs) in Central Java. Grounded in the Resource-Based View (RBV), the research investigates the mediating roles of Supply Chain Management Capabilities (SCMC), Electronic Customer Relationship Management (e-CRM), and Circular Economy Practices (CEP) in translating data-driven capabilities into sustainability outcomes. A quantitative explanatory approach was employed using survey data collected from 150 batik MSME owners and managers across major batik-producing regions in Central Java. Data were analyzed using Structural Equation Modeling (SEM) with AMOS. The results demonstrate that BDAC has a significant positive effect on SCMC, e-CRM, and CEP. Furthermore, BDAC directly influences sustainable performance, while SCMC, e-CRM, and CEP partially mediate this relationship. Sustainable performance, in turn, significantly enhances competitive advantage. The structural model exhibits strong goodness-of-fit indices, indicating robustness and explanatory power. These findings confirm that data-driven capabilities alone are insufficient to generate competitive advantage unless they are operationalized through supply chain integration, digital customer relationship management, and circular economy practices. This study contributes to the literature by integrating big data analytics, sustainability, and competitive advantage within the context of traditional creative MSMEs. Practically, the results provide strategic guidance for MSME owners and policymakers in leveraging digital transformation to achieve sustainable and competitive business performance

Author Biography

Bagus Yunianto Wibowo, Politeknik Negeri Semarang

Manajemen Pemasaran, Manajemen, Administrasi Bisnis, Ekonomi dan Bisnis

References

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.

Andersson, R., Eriksson, H., & Torstensson, H. (2022). Sustainability performance measurement: A review and conceptual framework. Journal of Cleaner Production, 330, 129784.

Arunachalam, D., Kumar, N., & Kawalek, J. P. (2018). Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications. Transportation Research Part E: Logistics and Transportation Review, 114, 416–436.

Bag, S., Gupta, S., Wood, L. C., & Dhamija, P. (2020). Big data analytics as an operational excellence approach to enhance sustainable supply chain performance. Resources, Conservation & Recycling, 153, 104559.

Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120.

Barton, D., & Court, D. (2012). Making advanced analytics work for you. Harvard Business Review, 90(10), 78–83.

Brinch, M. (2018). Understanding the value of big data in supply chain management and its business processes. International Journal of Operations & Production Management, 38(7), 1589–1614.

Cadden, T., Marshall, D., & Cao, G. (2013). Opposites attract: Organizational culture and supply chain performance. Supply Chain Management: An International Journal, 18(1), 86–103.

Cao, G., Duan, Y., & Li, G. (2015). Linking business analytics to decision making effectiveness: A path model analysis. Decision Support Systems, 74, 37–46.

Chiappetta Jabbour, C. J., Fiorini, P. D. C., Wong, C. W. Y., Jugend, D., Jabbour, A. B. L. D. S., & Seles, B. M. R. P. (2019). First-mover firms in the transition toward the circular economy: Driving factors and performance implications. Journal of Cleaner Production, 230, 1155–1165.

Del Giudice, M., Chierici, R., Mazzucchelli, A., & Fiano, F. (2021). Supply chain management in the era of circular economy: The moderating effect of big data. Technological Forecasting and Social Change, 170, 120877.

Dubey, R., Gunasekaran, A., Childe, S. J., Wamba, S. F., Papadopoulos, T., & Fosso Wamba, S. (2019). Big data analytics capability in supply chain agility: The moderating effect of organizational flexibility. Management Decision, 57(8), 2092–2112.

Engelen, A., Brettel, M., & Neumann, M. (2014). Adoption of big data analytics: The role of management and IT capabilities. Industrial Marketing Management, 43(7), 1111–1121.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

Govindan, K., & Hasanagic, M. (2018). A systematic review on drivers, barriers, and practices toward circular economy: A supply chain perspective. Journal of Cleaner Production, 204, 542–559.

Grant, R. M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 17(S2), 109–122.

Green, K. W., Zelbst, P. J., Meacham, J., & Bhadauria, V. S. (2012). Green supply chain management practices: Impact on performance. Supply Chain Management: An International Journal, 17(3), 290–305.

Gupta, M., & George, J. F. (2016). Toward the development of a big data analytics capability. Information & Management, 53(8), 1049–1064.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). SAGE Publications.

Hart, S. L. (1995). A natural-resource-based view of the firm. Academy of Management Review, 20(4), 986–1014.

Hoffmann, S., & Novak, T. P. (2017). Consumer and object experience in the internet of things: An assemblage theory approach. Journal of Consumer Research, 44(6), 1178–1204.

Hullova, D., Laczko, P., & Frishammar, J. (2019). Customer engagement in innovation ecosystems: How customer interaction affects innovation performance. Journal of Business Research, 99, 103–117.

Hult, G. T. M., Hurley, R. F., & Knight, G. A. (2004). Innovativeness: Its antecedents and impact on business performance. Industrial Marketing Management, 33(5), 429–438.

Iranmanesh, M., Zailani, S., Hyun, S. S., Ali, M. H., & Kim, K. (2019). Impact of green innovation on firm performance and environmental performance: Evidence from SMEs. Business Strategy and the Environment, 28(6), 906–918.

Jarrahi, M. H. (2019). Artificial intelligence and the future of work: Human–AI symbiosis in organizational decision making. Business Horizons, 62(4), 577–586.

Klassen, R. D., & McLaughlin, C. P. (1996). The impact of environmental management on firm performance. Management Science, 42(8), 1199–1214.

Kristoffersen, E., Blomsma, F., Mikalef, P., & Li, J. (2021). The smart circular economy: A digital-enabled circular strategies framework for manufacturing companies. Journal of Business Research, 120, 241–261.

Lee, V.-H., Ooi, K.-B., Chong, A. Y.-L., & Lin, B. (2015). A structural analysis of green supply chain management practices and performance. International Journal of Production Economics, 161, 57–68.

Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. A. (2020). Investigating the effects of big data analytics capabilities on firm performance: The mediating role of dynamic capabilities. Information & Management, 57(2), 103169.

Modgil, S., Gupta, S., Stekelorum, R., & Bhattacharya, A. (2021). AI technologies and circular economy: A review and research agenda. International Journal of Production Research, 59(6), 1792–1811.

Munir, M., Jajja, M. S. S., Chatha, K. A., & Farooq, S. (2020). Supply chain risk management and operational performance: The enabling role of supply chain integration. International Journal of Production Economics, 227, 107667.

Nursimloo, D., Ramdhony, D., & Mooneeapen, O. (2020). Corporate governance and sustainability performance: Evidence from emerging markets. Social Responsibility Journal, 16(2), 141–165.

Nutsugah, F., Antwi, F., & Amoako, G. K. (2021). Green innovation and environmental performance: The role of green knowledge management. Business Strategy and the Environment, 30(4), 1832–1846.

Porter, M. E., & van der Linde, C. (1995). Toward a new conception of the environment–competitiveness relationship. Journal of Economic Perspectives, 9(4), 97–118.

Porter, M. E., & Kramer, M. R. (2011). Creating shared value. Harvard Business Review, 89(1–2), 62–77.

Purvis, B., Mao, Y., & Robinson, D. (2019). Three pillars of sustainability: In search of conceptual origins. Sustainability Science, 14(3), 681–695.

Rai, A., Patnayakuni, R., & Seth, N. (2006). Firm performance impacts of digitally enabled supply chain integration capabilities. MIS Quarterly, 30(2), 225–246.

Raut, R. D., Mangla, S. K., Narwane, V. S., Gardas, B. B., & Narkhede, B. E. (2019). Linking big data analytics and operational performance: The role of supply chain integration. Annals of Operations Research, 270(1–2), 1–22.

Schroeder, P., Anggraeni, K., & Weber, U. (2019). The relevance of circular economy practices to the sustainable development goals. Journal of Industrial Ecology, 23(1), 77–95.

Srivastava, S. K. (2007). Green supply-chain management: A state-of-the-art literature review. International Journal of Management Reviews, 9(1), 53–80.

Trabucchi, D., Buganza, T., Pellizzoni, E., & Verganti, R. (2019). Digital platform innovation: A systematic literature review. Technological Forecasting and Social Change, 146, 518–531.

Wamba, S. F., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165, 234–246.

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.

Wu, F., Yeniyurt, S., Kim, D., & Cavusgil, S. T. (2006). The impact of information technology on supply chain capabilities and firm performance: A resource-based view. Industrial Marketing Management, 35(4), 493–504.

Zhu, Q., & Sarkis, J. (2004). Relationships between operational practices and performance among early adopters of green supply chain management practices in Chinese manufacturing enterprises. Journal of Operations Management, 22(3), 265–289.

Zhu, Q., Sarkis, J., & Lai, K.-H. (2013). Institutional-based antecedents and performance outcomes of internal and external green supply chain management practices. Journal of Purchasing and Supply Management, 19(2), 106–117.

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Published

2025-06-30

How to Cite

Setyawan, N. A., Wibowo, B. Y., Eviyanti, N., Luthfia, I. M., & Purnamasari, E. (2025). Big Data Analytics Capabilities and Competitive Advantage in Batik SMEs: The Mediating Roles of SCM and E-CRM. Al-Kharaj: Journal of Islamic Economic and Business, 7(2). https://doi.org/10.24256/kharaj.v7i2.9654

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