Modelling the factors of agile practices in project management A case of illumination project organization

  • Authors

    • Gayathr K
    • M Suresh
    https://doi.org/10.14419/ijet.v7i2.33.14830

    Received date: June 30, 2018

    Accepted date: June 30, 2018

    Published date: June 8, 2018

  • Agile Project, Agility, Project Management, Interpretive Structural

  • Abstract

    Project management involves various activities which contribute for achieving specific goals and success criteria. The illumination compa-nies involved in project management and related fields face major issues because of rapid changes in technology and environment. The solu-tion to this issue will be to establish a flexible and quick environment in the organization which is easily adaptable to the changes in the ex-ternal environment. In this paper the various factors that influence agile project management in an illumination company has been identified. The Interpretive Structural Modelling (ISM) has been used to analyse the interrelationships among the factors. Finally, the paper concludes that the most influential factors are supervisory behaviours, employee involvement, domain expertise, nature of management.

  • References

    1. Ambika Devi Amma, T., Radhika, N., & Pramod, V. R. (2015). Ma-jor Cloud Computing Threats-An ISM Approach. International Journal of Applied Engineering Research, 10(16), 37804-37808.
    2. Bernardes, E. S., & Hanna, M. D. (2009). A theoretical review of flexibility, agility and responsiveness in the operations management literature: Toward a conceptual definition of customer responsive-ness. International Journal of Operations & Production Manage-ment, 29(1), 30-53.
    3. Charles, A., Lauras, M., & Van Wassenhove, L. (2010). A model to define and assess the agility of supply chains: building on humani-tarian experience. International Journal of Physical Distribution & Logistics Management, 40(8/9), 722-741.
    4. Conforto, E. C., Amaral, D. C., da Silva, S. L., Di Felippo, A., &Kamikawachi, D. S. L. (2016). The agility construct on project management theory. International Journal of Project Manage-ment, 34(4), 660-674.
    5. Faisal, M. N. (2010). Analysing the barriers to corporate social re-sponsibility in supply chains: an interpretive structural modelling approach. International Journal of Logistics: Research and Applica-tions, 13(3), 179-195.
    6. Hallgren, M., &Olhager, J. (2009). Lean and agile manufacturing: external and internal drivers and performance out-comes. International Journal of Operations & Production Manage-ment, 29(10), 976-999.
    7. Hoda, R., Noble, J., & Marshall, S. (2011). The impact of inade-quate customer collaboration on self-organizing agile teams. Information and Software Technology, 53(5), 521-534.
    8. Kumar, S., Luthra, S., & Haleem, A. (2013). Customer involvement in greening the supply chain: an interpretive structural modeling methodology. Journal of Industrial Engineering International, 9(1), 6.
    9. Melo, C. D. O., Cruzes, D. S., Kon, F., &Conradi, R. (2013). Inter-pretative case studies on agile team productivity and manage-ment. Information and Software Technology, 55(2), 412-427.
    10. Mehta, N., Verma, P., & Seth, N. (2014). Total quality management implementation in engineering education in India: an interpretive structural modelling approach. Total Quality Management & Busi-ness Excellence, 25(1-2), 124-140.
    11. Patri, R., & Suresh, M. (2017a). Factors influencing lean implemen-tation in healthcare organizations: An ISM approach. International Journal of Healthcare Management, 1-13.
    12. Patri, R., & Suresh, M. (2017b). Modelling the enablers of agile per-formance in healthcare organization: A TISM approach. Global Journal of Flexible Systems Management, 18(3), 251-272.
    13. Pikkarainen, M., Salo, O., Kuusela, R., &Abrahamsson, P. (2012).Strengths and barriers behind the successful agile deploy-ment—insights from the three software intensive companies in Fin-land. Empirical software engineering, 17(6), 675-702.
    14. Saleeshya, P. G., Thampi, K. S., &Raghuram, P. (2012). A com-bined AHP and ISM-based model to assess the agility of supply chain–a case study. International Journal of Integrated Supply Man-agement, 7(1-3), 167-191.
    15. Seger, T., Hazzan, O., & Bar-Nahor, R. (2008, August). Agile orien-tation and psychological needs, self-efficacy, and perceived sup-port: a two job-level comparison. In Agile, 2008.AGILE'08. Confer-ence (pp. 3-14). IEEE
    16. Serrador, P., & Pinto, J. K. (2015). Does Agile work?—A quantita-tive analysis of agile project success. International Journal of Pro-ject Management, 33(5), 1040-1051.
    17. Stare, A. (2014). Agile project management in product development projects. Procedia-Social and Behavioral Sciences, 119, 295-304
    18. Talib, F., Rahman, Z., & Qureshi, M. N. (2011). Analysis of interac-tion among the barriers to total quality management implementation using interpretive structural modeling approach. Benchmarking an International Journal, 18(4), 563-587.
    19. Thirupathi, R. M., & Vinodh, S. (2016). Application of interpretive structural modelling and structural equation modelling for analysis of sustainable manufacturing factors in Indian automotive compo-nent sector. International Journal of Production Research, 54(22), 6661-6682.
    20. Varkhedkar, N., Verma, P., & Seth, N. (2015). Demand chain man-agement implementation enablers: an interpretive structural model-ling approach. International Journal of Modelling in Operations Management, 5(1), 13-32.
    21. Vasanthakumar, C., Vinodh, S., & Ramesh, K. (2016). Application of interpretive structural modelling for analysis of factors influenc-ing lean remanufacturing practices. International Journal of Produc-tion Research, 54(24), 7439-7452.
    22. Vinodh, S., &Devadasan, S. R. (2011). Twenty criteria based agility assessment using fuzzy logic approach. The International Journal of Advanced Manufacturing Technology, 54(9-12), 1219-1231.
    23. Vinodh, S., Madhyasta, U. R., & Praveen, T. (2012).Scoring and multi-grade fuzzy assessment of agility in an Indian electric auto-motive car manufacturing organisation. International Journal of Production Research, 50(3), 647-660.
    24. Vinodh, S., Ramesh, K., & Arun, C. S. (2016). Application of in-terpretive structural modelling for analysing the factors influencing integrated lean sustainable system. Clean Technologies and Envi-ronmental Policy, 18(2), 413-428.
    25. Vinodh, S., Sundararaj, G., Devadasan, S. R., Maharaja, R., Ra-janayagam, D., &Goyal, S. K. (2008). DESSAC: a decision support system for quantifying and analysing agility. International Journal of Production Research, 46(23), 6759-6780.

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  • How to Cite

    K, G., & Suresh, M. (2018). Modelling the factors of agile practices in project management A case of illumination project organization. International Journal of Engineering and Technology, 7(2.33), 541-547. https://doi.org/10.14419/ijet.v7i2.33.14830