When do efficiency and flexibility determine a firm's performance? A simulation study
Author(s) -
Fred Phillips,
Jinwon Chang,
Yu-Shan Su
Publication year - 2018
Publication title -
journal of innovation and knowledge
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.72
H-Index - 20
eISSN - 2530-7614
pISSN - 2444-569X
DOI - 10.1016/j.jik.2017.12.003
Subject(s) - variety (cybernetics) , flexibility (engineering) , computer science , competitor analysis , industrial engineering , scale (ratio) , management science , risk analysis (engineering) , operations research , economics , engineering , artificial intelligence , management , business , physics , quantum mechanics
Purpose Using general systems theory, we present a series of simulations that shed light on the viability of business strategies in stable and turbulent business environments. Special attention is given to the impact of efficiency versus flexibility on firm performance, and on what the simulations reveal concerning successful strategies in each environment and firm type. Design/methodology/approach Large-scale Monte Carlo simulations based on Ashby's Requisite Variety principle. Findings Efficiency and flexibility do not, in general, determine performance. However, certain strategies appear to be superior, and in turbulent business environments, efficiency and flexibility appear well correlated with firm performance. Research limitations/implications Implications and limitations of the Law of Requisite Variety for strategic analysis are set forth. Limitations stem from the simplifications needed for quantitative analysis, and lack of explicit consideration of competitors’ actions. Practical implications The simulations’ realism offers insights to strategists regarding the roles of efficiency and flexibility in firm performance. The quantitative approach provides unambiguous definitions for some terms used in strategy, sharpening concepts put forth by Ashby and by Ansoff. Originality/value A back-to-basics, systems approach to the simulations, using the venerable and general requisite variety principle as its basis, ensures sound analysis and appeal to readers who may come to it from diverse traditions of strategy theory. The quantitative simulation tool is made available for other researchers to test and extend.
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