Using power regimes to explore perceived environmental uncertainty

Eric T.G. Wang, Neil Chueh An Lee

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Purpose - This paper aims to explore and gain a better understanding of the relationship between power circumstances and the environmental uncertainty perceived by managers. Design/methodology/approach - This paper conducted a survey of 1,000 manufacturing firms selected randomly from the Top 5000 largest firms in Taiwan. The responding firms were clustered by K-means into four groups of power circumstances. The paper then applied MANOVA and ANOVA to test the differences among the three types of supply chain uncertainty across the four groups. Findings - The results show that power circumstances are associated with managers' perceptions of environmental uncertainty in terms of demand, technology, and supply. This paper finds that managers of buying firms in dominant positions perceive a lower demand uncertainty while managers facing higher supplier power perceive greater uncertainty in technology. For buying firms under ambiguous power circumstances, their managers tend to perceive higher supply uncertainty. The paper then put forth six power-based propositions on the basis of their results. Research limitations/implications - Given that the data are from large-sized firms, the generalizability of their findings to smaller firms may be limited. Practical implications - When developing strategies to tackle environmental uncertainties, managers should consider their firm's power circumstances because these tend to influence the managers' interpretation and decisions and thereby their subsequent strategies. Originality/value - Although environmental uncertainty has been addressed extensively in various management fields, how the environmental uncertainty perceived by a firm's managers is related to the power the firm holds has never been empirically examined. This study clarifies this issue.

Original languageEnglish
Article number17094911
Pages (from-to)950-966
Number of pages17
JournalIndustrial Management and Data Systems
Issue number7
StatePublished - 2013


  • Cluster analysis
  • Environmental uncertainty
  • Power regimes
  • Strategic planning
  • Supply chain management


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