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Causal Linkage among Business Analytics, Supply Chain Performance, Firm Performance and Competitive Advantage


Affiliations
1 National Innovation Foundation, Gandhinagar-38272, India
2 Indian Institute of Plantation Management, Bangalore - 560056, India
 

The research work examines the causal linkage among business analytics, supply chain performance, firm performance and competitive advantage. The conceptual model and hypothesis was developed through literature review and collected data from industries were empirically tested using structural equation modeling technique. The finding suggest that companies that support their analytical capabilities with good information system are likely to be more capable of performing better and better understanding of the factors of business analytics that influences the organizational competitive advantage.

Keywords

Business Analytics, Supply Chain Performance, Firm Performance Competitive Advantage.
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  • Acar, M. F., Zaim, S., Isik, M., & Calisir, F. (2017). Relationships among ERP, supply chain orientation and operational performance: An analysis of structural equation modeling. Benchmarking: An International Journal, 24(5).

  • Ganeshkumar, C., & Mohan, G. M. (2014). Data Assumptions Checking for Estimating Structural Equation Modeling: Supply Chain Context. Anvesha, 7(4), 12.

  • Ganeshkumar, C., & Nambirajan, T. (2013). Supply Chain Management Components, Competitiveness and Organisational Performance: Causal Study of Manufacturing Firms. Asia-Pacific Journal of Management Research and Innovation, 9(4), 399-412.

  • Handfield, R. B., & Bechtel, C. (2004). Trust, power, dependence, and economics: can SCM research borrow paradigms? International Journal of Integrated Supply Management, 1(1), 3-32.

  • Li, S., Ragu-Nathan, B., Ragu-Nathan, T., & Rao, S. S. (2006). The impact of supply chain management practices on competitive advantage and organizational performance. Omega, 34(2), 107-124.

  • Limam Mansar, S., & Reijers, H. A. (2007). Best practices in business process redesign: use and impact. Business Process Management Journal, 13(2), 193-213.

  • Lockamy III, A., & McCormack, K. (2004). Linking SCOR planning practices to supply chain performance: An exploratory study. International journal of operations & production management, 24(12), 1192-1218.

  • McCormack, K., & Lockamy, A. (2005). The impact of horizontal mechanisms within sales and operations planning processes on supply chain integration and performance: a statistical study. Paper presented at the 4th Global Conference on Business & Economics, Oxford, UK.

  • McCormack, K., Willems, J., Van den Bergh, J., Deschoolmeester, D., Willaert, P., Indihar Štemberger, M., . . . Paulo Valadares de Oliveira, M. (2009). A global investigation of key turning points in business process maturity. Business Process Management Journal, 15(5), 792-815.

  • McCormack, K. P., & Johnson, W. C. (2001). Business process orientation: Gaining the e-business competitive advantage: CRC Press.

  • McCormack, K. P., & Johnson, W. C. (2016). Supply chain networks and business process orientation: advanced strategies and best practices: CRC Press.

  • Meixell, M. J., & Gargeya, V. B. (2005). Global supply chain design: A literature review and critique. Transportation Research Part E: Logistics and Transportation Review, 41(6), 531-550.

  • Muylle, S., & Basu, A. (2008). Online support for business processes by electronic intermediaries. Decision Support Systems, 45(4), 845-857.

  • Narasimhan, R., & Jayaram, J. (1998). Causal linkages in supply chain management: an exploratory study of North American manufacturing firms. Decision sciences, 29(3), 579-605.

  • Rao, P., & Holt, D. (2005). Do green supply chains lead to competitiveness and economic performance? International journal of operations & production management, 25(9), 898-916.

  • Roglinger, M., Poppelbuß, J., & Becker, J. (2012). Maturity models in business process management. Business Process Management Journal, 18(2), 328-346.

  • Stefanovic, N., & Milosevic, D. (2017). Developing Adaptive Business Intelligence Systems for Agile Supply Chain Analytics. Paper presented at the Proceedings of the 2017 International Conference on E-commerce, E-Business and E-Government.

  • Tenenhaus, M., Vinzi, V. E., Chatelin, Y.-M., & Lauro, C. (2005). PLS path modeling. Computational statistics & data analysis, 48(1), 159-205.

  • Trkman, P., McCormack, K., De Oliveira, M. P. V., & Ladeira, M. B. (2010). The impact of business analytics on supply chain performance. Decision Support Systems, 49(3), 318-327.

  • Vickery, S. K., Jayaram, J., Droge, C., & Calantone, R. (2003). The effects of an integrative supply chain strategy on customer service and financial performance: an analysis of direct versus indirect relationships. Journal of operations management, 21(5), 523-539.

  • Vinzi, V. E., Chin, W. W., Henseler, J., & Wang, H. (2010). Handbook of partial least squares: Concepts, methods and applications: Springer Science & Business Media.

  • 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.


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  • Causal Linkage among Business Analytics, Supply Chain Performance, Firm Performance and Competitive Advantage

Abstract Views: 546  |  PDF Views: 2

Authors

J. Jamshi
National Innovation Foundation, Gandhinagar-38272, India
C. Ganeshkumar
Indian Institute of Plantation Management, Bangalore - 560056, India

Abstract


The research work examines the causal linkage among business analytics, supply chain performance, firm performance and competitive advantage. The conceptual model and hypothesis was developed through literature review and collected data from industries were empirically tested using structural equation modeling technique. The finding suggest that companies that support their analytical capabilities with good information system are likely to be more capable of performing better and better understanding of the factors of business analytics that influences the organizational competitive advantage.

Keywords


Business Analytics, Supply Chain Performance, Firm Performance Competitive Advantage.

References





DOI: https://doi.org/10.23862/kiit-parikalpana%2F2017%2Fv13%2Fi2%2F164518