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Contingency theory of capacity planning: The link between process types and planning methods
Author(s) -
Tenhiälä Antti
Publication year - 2011
Publication title -
journal of operations management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.649
H-Index - 191
eISSN - 1873-1317
pISSN - 0272-6963
DOI - 10.1016/j.jom.2010.05.003
Subject(s) - contingency theory , contingency , production planning , contingency plan , production (economics) , bounded rationality , process (computing) , task (project management) , computer science , process management , management science , inference , reliability (semiconductor) , business , knowledge management , operations management , economics , microeconomics , management , artificial intelligence , epistemology , philosophy , power (physics) , computer security , physics , quantum mechanics , operating system
Although the reliability of production plans is crucial for the performance of manufacturing organizations, most practitioners use considerably simpler planning methods than what is recommended in the operations management literature. This article employs the contingency theory of organizations to explain the gap between the practice and the academic models of production planning. Arguments on the contingency effects of process complexity lead to a hypothesis that expects simple capacity planning methods to be most effective in certain production processes. A strong inference research setting is used to test the contingency hypothesis against a conventional hypothesis that expects the most sophisticated planning techniques to always be most effective. Multisource data from the machinery manufacturing industry support the contingency hypothesis and reject the universalistic hypothesis. The findings are explained using the concepts of task interdependence and bounded rationality. The results have several managerial implications, and they elaborate how classic concepts in organization theory can bring practically relevant insights to operations management research.