Author:
Mishra Swagatika,Sankar Mahapatra Siba,Datta Saurav
Abstract
Purpose
– The purpose of this paper is to investigate the influence of decision-makers’ (DM) risk bearing attitudes and the effect of the decision-making environment on estimating the overall degree of agility of an organization. The present study explores an extended agility model in a specific organization's hierarchy and reflects how decision-making attitudes alter an organizational agility scenario.
Design/methodology/approach
– The concept of fuzzy logic has been explored in this paper. Based on DMs’ linguistic judgments, a fuzzy appropriateness rating as well as fuzzy priority weights have been determined for different levels of agile system hierarchy. Using a multi-grade fuzzy approach the overall agility index has been determined. The concept of fuzzy numbers ranking has been explored to show the effect of decision-making attitudes on agility estimations.
Findings
– Decision-making attributes, e.g. the category of DM (neutral, risk-averse and risk-taking), affect the quantitative evaluation of the overall agility degree, which is correlated with a predefined agility measurement scale.
Research limitations/implications
– This study explores a triangular fuzzy membership function to express DMs’ linguistic judgments as fuzzy representations. Apart from triangular fuzzy numbers, trapezoidal and Gaussian fuzzy numbers may also be used for agility evaluation. The model may be used in other agile industries for benchmarking and selection of the best approach.
Practical implications
– Selecting the right decision-making group to compute and analyze the agility level for a particular organization is an important managerial decision. In the case of benchmarking of various agile enterprises the decision-making group bearing the same attitude should be utilized.
Originality/value
– Agile system modeling and development of agility appraisement platforms have been attempted by previous researchers while the influence of DMs’ risk bearing attitudes, and the effect of the decision-making environment on estimating the overall degree of agility, have rarely been studied. In this context, the authors explore an exhaustive agility model for implementing in a case study and reveal how decision-making attitudes alter organizational agility scenarios.
Subject
Business and International Management,Strategy and Management
Reference41 articles.
1. Arteta, B.M.
and
Giachetti, R.E.
(2004), “A measure of agility as the complexity of the enterprise system”, Robotics and Computer-Integrated Manufacturing, Vol. 20 No. 6, pp. 495-503.
2. Brown, S.
and
Bessant, J.
(2003), “The manufacturing strategy – capabilities links in mass customisation and agile manufacturing – and exploratory study”, International Journal of Operations & Production Management, Vol. 23 No. 7, pp. 707-730.
3. Chandna, R.
(2008), “Measurement of agility in manufacturing systems: a fuzzy logic approach”, Proceedings of the World Congress on Engineering, Vol. 2, WCE, London, July 2-4.
4. Chang, P.-L.
(1994), “A fuzzy multi criteria decision making method for technology transfer selection in biotechnology”, Fuzzy Sets and Systems, Vol. 63 No. 2, pp. 131-139.
5. Ganguly, A.
,
Nilchiani, R.
and
Farr, J.V.
(2009), “Evaluating agility in corporate enterprises”, International Journal of Production Economics, Vol. 118 No. 2, pp. 410-423.
Cited by
19 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献