Abstract
The present study evaluates the agility of a medium-scale industry in the northern state of India. For evaluating agility, a ‘Total Fuzzy Agility Index’ is defined, which serves as a benchmark for assessing two parameters, namely agility level and Total Fuzzy Performance-Importance Index (TFPII). TFPII forms a basis for identifying principle obstacles in the process of increasing agility level. Once identified, principle obstacles are ranked for exploring gaps. In the present study, 132 agile enablers have been identified and used for evaluation out of which 13 have been assessed as obstacles. This study will serve as a decision support system for managements to identify obstacles, rank, and correct them for increasing agility level of the organization. This research paper analyses these issues and concludes by suggesting a future roadmap for successful implementation of agile practices.
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Srivastava, P., Khanduja, D., Agrawal, V.P., Saini, N. (2019). Total Fuzzy Agility Evaluation Using Fuzzy Methodology: A Case Study. In: Yadav, N., Yadav, A., Bansal, J., Deep, K., Kim, J. (eds) Harmony Search and Nature Inspired Optimization Algorithms. Advances in Intelligent Systems and Computing, vol 741. Springer, Singapore. https://doi.org/10.1007/978-981-13-0761-4_94
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