Digital Transformation through Integrated Business Excellence: An Empirical Investigation of Auto Component Industries in Chennai's Manufacturing Ecosystem

  • Authors

    • Eugene J Faculty of Management, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu District, Tamil Nadu – 603203, India
    • Dr. Arivazhagan, R Faculty of Management, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu District, Tamil Nadu – 603203, India
    • Dr. Surjadeep Dutta Faculty of Management Studies, Dr. B.C. Roy Engineering College, Durgapur, West Bengal, Pincode- 713206, India
    https://doi.org/10.14419/p31gts14

    Received date: August 31, 2025

    Accepted date: September 17, 2025

    Published date: September 19, 2025

  • Digital transformation, Business excellence, Auto components, Manufacturing, Chennai, Industry 4.0

  • Abstract

    Purpose – This research develops and validates an integrated business excellence model that connects traditional operational excellence and digital innovation capabilities in the auto component manufacturing industry in Chennai. The research fills the gap in the literature around managing the divide between initiatives to pursue digital transformation and the ability of the organization to sustain strong business performance, considering the context of an emerging economy.

    Design/methodology/approach – A mixed-methods empirical approach was undertaken.  The research surveyed 247 auto component manufacturers in Chennai using structured questionnaires and also conducted in-depth interviews with 28 senior executives. The integrations of business excellence framework was validated (along with the key variables/topics) using square equation modelling/structures Equation modeling (SEM) and factor analysis.

    Findings – The integrated model identifies five key dimensions: Digital Process Excellence (DPE), Innovation Management Capability (IMC), Quality Systems Integration (QSI), Supply Chain Digitalization (SCD), and Performance Measurement Systems (PMS). The model shows robust, significant positive relationships between digital innovation alignment and business excellence, with Quality Systems Integration as the most robust mediator (β = 0.743, p < 0.001).

    Originality/value – In order to facilitate digital transformation while preserving operational excellence, this research has developed and experimentally tested a framework tailored to the automotive component industries in developing markets.

  • References

    1. Agarwal, S., Kumar, P. and Sharma, R. (2022), "Digital transformation in Indian auto component industry: challenges and opportunities", Interna-tional Journal of Production Economics, Vol. 245, pp. 108-125.
    2. Anderson, M. and Williams, J. (2023), "Adapting business excellence models for digital transformation", Total Quality Management & Business Excellence, Vol. 34 No. 7-8, pp. 891-908.
    3. Brown, K. and Davis, L. (2023), "Performance measurement in Industry 4.0: real-time analytics for operational excellence", International Journal of Operations & Production Management, Vol. 43 No. 4, pp. 612-634.
    4. Chen, H., Liu, Y. and Wang, Z. (2022), "Smart manufacturing technologies in automotive component production: a systematic review", Journal of Manufacturing Systems, Vol. 63, pp. 456-473.
    5. Davis, R. and Johnson, T. (2023), "Integration challenges in digital transformation: evidence from manufacturing industries", Technology Analysis & Strategic Management, Vol. 35 No. 2, pp. 234-251.
    6. Deming, W.E. (1986), Out of the Crisis, MIT Press, Cambridge, MA.
    7. EFQM (2019), The EFQM Model 2020, European Foundation for Quality Management, Brussels.
    8. Gupta, A., Krishnan, S. and Reddy, M. (2022), "Sustainable manufacturing practices in Indian automotive sector: digital enablers and performance outcomes", Journal of Cleaner Production, Vol. 378, pp. 134-147.
    9. Johnson, P. and Smith, A. (2022), "Quality management systems in automotive supply chains: digital integration perspectives", International Journal of Quality & Reliability Management, Vol. 39 No. 8, pp. 1845-1862.
    10. Juran, J.M. (1988), Juran on Planning for Quality, Free Press, New York, NY.
    11. Kaplan, R.S. and Norton, D.P. (1996), The Balanced Scorecard: Translating Strategy into Action, Harvard Business Review Press, Boston, MA.
    12. Krishnan, V. and Reddy, P. (2023), "Digital adoption patterns in Indian manufacturing: sector-wise analysis", Technological Forecasting and Social Change, Vol. 186, pp. 122-135.
    13. Kumar, R. and Sharma, S. (2023), "Indian automotive industry: economic contribution and future prospects", Economic and Political Weekly, Vol. 58 No. 12, pp. 45-52.
    14. Martinez, C. and Brown, D. (2023), "Cultural adaptation of excellence models in emerging economies", International Journal of Quality & Reliabil-ity Management, Vol. 40 No. 3, pp. 678-695.
    15. Nunnally, J.C. and Bernstein, I.H. (1994), Psychometric Theory, 3rd ed., McGraw-Hill, New York, NY.
    16. Patel, N. and Singh, K. (2022), "EFQM model application in Indian manufacturing: adaptation challenges and success factors", TQM Journal, Vol. 34 No. 5, pp. 1123-1141.
    17. Rajesh, K., Venkat, S. and Raman, L. (2022), "Chennai automotive cluster: evolution and competitive dynamics", Journal of Manufacturing Tech-nology Management, Vol. 33 No. 7, pp. 1234-1252.
    18. Raman, K. and Krishnamurthy, S. (2022), "Knowledge sharing in manufacturing clusters: evidence from Chennai automotive sector", Knowledge Management Research & Practice, Vol. 20 No. 4, pp. 567-584.
    19. Schwab, K. (2016), The Fourth Industrial Revolution, World Economic Forum, Geneva.
    20. Taylor, M., Rodriguez, A. and Kim, S. (2023), "Innovation management capabilities in emerging market manufacturing", Research Policy, Vol. 52 No. 1, pp. 234-248.
    21. Thompson, G. and Lee, H. (2022), "Evolution of business excellence models: addressing digital transformation requirements", Quality Management Journal, Vol. 29 No. 3, pp. 156-172.
    22. Venkatesh, R. and Rao, D. (2023), "Heterogeneous digital capabilities in manufacturing clusters: implications for competitive advantage", Strategic Management Journal, Vol. 44 No. 2, pp. 445-467.
    23. Wang, L. and Liu, X. (2022), "Integration benefits in digital manufacturing transformation: a multi-case study", Production Planning & Control, Vol. 33 No. 12, pp. 1178-1194.
    24. Agarwal, S., Kumar, P., & Sharma, R. (2022). Digital transformation in Indian auto component industry: challenges and opportunities. International Journal of Production Economics, 245, 108-125.
    25. Brynjolfsson, E., & McAfee, A. (2017). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W. W. Nor-ton & Company.
    26. Chen, H., Liu, Y., & Wang, Z. (2023). Smart manufacturing technologies in automotive component production: Financial implications and perfor-mance outcomes. Journal of Manufacturing Systems, 68, 234-251.
    27. Deloitte. (2025). 2025 Manufacturing Industry Outlook. Deloitte Insights.
    28. Kumar, R., & Sharma, S. (2023). Indian automotive industry: Economic contribution and financial performance analysis. Economic and Political Weekly, 58(12), 45-52.
    29. Lemberg Solutions. (2023). Digital transformation in the automotive industry: Trends and innovations to follow. Retrieved from https://lembergsolutions.com/blog/digital-transformation-automotive-industry
    30. Martinez, C., & Brown, D. (2023). Financial management in digital manufacturing environments: Evidence from emerging markets. International Journal of Production Economics, 267, 108-124.
    31. Wang, L., & Liu, X. (2022). Integration benefits in digital manufacturing transformation: A financial performance analysis. Production Planning & Control, 33(12), 1178-1194.
    32. Guo, X. (2023). The impact of digital transformation on manufacturing enterprises. Sustainability, 15(4), 3124.
    33. Krish Technolabs. (2024). Role of digital transformation in the automotive industry.
    34. Wei, J. (2025). Impact and mechanism of digital transformation on firm performance. ScienceDirect.
    35. Li, Y., Zhang, L., & Wang, H. (2024). Enterprise digital transformation, managerial myopia, and cost stickiness. Nature Communications, 15(1), 1–12.
    36. Chen, H., Liu, Y., & Wang, Z. (2023). Smart manufacturing technologies in automotive component production: Financial implications and perfor-mance outcomes. Journal of Manufacturing Systems, 68, 234–251.
    37. Kumar, R., & Sharma, S. (2023). Indian automotive industry: Economic contribution and financial performance analysis. Economic and Political Weekly, 58(12), 45–52.

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  • How to Cite

    J, E., R, D. A. ., & Dutta , D. S. . (2025). Digital Transformation through Integrated Business Excellence: An Empirical Investigation of Auto Component Industries in Chennai’s Manufacturing Ecosystem. International Journal of Accounting and Economics Studies, 12(5), 782-790. https://doi.org/10.14419/p31gts14