TY - JOUR
T1 - When do efficiency and flexibility determine a firm's performance? A simulation study
AU - Phillips, Fred
AU - Chang, Jinwon
AU - Su, Yu Shan
N1 - Funding Information:
This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the “IT Consilience Creative Program” (NIPA-2013-H0203-13-1001) supervised by the NIPA (National IT Industry Promotion Agency), and also by the Nuclear Research & Development of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Trade, Industry and Energy (2013T100200058), and also by the Taiwan government Ministry of Science and Technology (MOST 103-2511-S-003-045-) and National Science Council (NSC 102-2912-I-110-522).
Publisher Copyright:
© 2018 Journal of Innovation & Knowledge
PY - 2019/4/1
Y1 - 2019/4/1
N2 - 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.
AB - 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.
KW - Corporate slack
KW - Efficiency
KW - Nimble firm
KW - Requisite variety
KW - Simulation
KW - Strategy
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U2 - 10.1016/j.jik.2017.12.003
DO - 10.1016/j.jik.2017.12.003
M3 - Article
AN - SCOPUS:85064640337
SN - 2530-7614
VL - 4
SP - 88
EP - 96
JO - Journal of Innovation and Knowledge
JF - Journal of Innovation and Knowledge
IS - 2
ER -