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Critical Operations Capabilities in a High Cost Environment: A Grey Relational Analysis

Ewout Reitsma, Cinzia Sansone and Per Hilletofth
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Ewout Reitsma: Jönköping University, Sweden
Cinzia Sansone: Jönköping University, Sweden
Per Hilletofth: Jönköping University, Sweden

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Abstract: Operations capabilities has been a common research area for many years and several frameworks have been offered. The existing frameworks are general and do not take specific contexts into consideration, such as a high cost environment. This research gap is of interest as a manufacturing relocation process has been taking place during the last decades, resulting in a vast amount of manufacturing being moved from high to low cost environments. The purpose of this study is to analyse critical operations capabilities in a high cost environment. A survey study was conducted, which focused on the evaluation of an existing framework of operations capabilities in the specific high cost environment context. Data was collected by a questionnaire that was developed based on the existing framework and distributed to 14 managers in five Swedish manufacturing firms. Grey relational analysis (GRA) was used to rank and cluster the dimensions and operations capabilities. The findings revealed that all the dimensions and operations capabilities included in the framework were critical in a high cost environment. However, the analysis also indicated that different emphasis was put on the different dimensions and capabilities. Thus, the dimensions and capabilities were ranked in order of critically and clustered as either ‘most critical’, ‘critical’, or ‘least critical’. The most critical dimension was ‘quality’ while the least critical dimension was ‘environment’. The critical dimensions included ‘delivery’, ‘cost’, ‘flexibility’, ‘service’ and ‘innovation’. The findings increased the validity of the framework and its usefulness in a high cost environment.

Keywords: operations strategy; priority; capability; high cost environment; grey relational analysis; Sweden (search for similar items in EconPapers)
Date: 2017
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