Developing decision-support tools for evaluation of manufacturing reshoring decisions
Abstract: During last three decades, companies have offshored their manufacturing activities across international borders in order to pursue lower manufacturing costs. Despite having accomplished their purpose, companies have also suffered from issues, especially poor quality of products and a poor response to customer demand. Therefore, companies consider relocating some of the manufacturing activities back to the home country, a process that is known as manufacturing reshoring. There is paucity of scholarly attention on how manufacturing reshoring decisions are evaluated and supported. Therefore, the purpose of this thesis is to develop decision-support tools to evaluate manufacturing reshoring decisions. In order to fulfil this, it is important to know how industry experts reason while making manufacturing reshoring decisions (RQ1), and how their reasoning can be modeled into decision-support tools (RQ2). Therefore, three studies were conducted including a multiple case study and two modeling studies. The multiple case study addressed the criteria that are considered by the industry experts in these decisions, while the two modeling studies, based on fuzzy logic and analytical hierarchy process (AHP), used a part of these criteria to develop decision-support tools. The findings indicate that a holistic set of criteria were considered by industry experts in arriving at a manufacturing reshoring decision. A large portion of these criteria occur within competitive priority category and among them, high importance is given to quality, while low importance to sustainability. Fuzzy logic modeling was used to model the criteria from the perspective of competitive priority at an overall level. Three fuzzy logic concepts were developed to capture industry experts’ reasoning and facilitate modeling of manufacturing reshoring decisions. Furthermore, two configurations and sixteen settings were developed, of which, the best ones were identified. AHP-based tools were used to capture experts’ reasoning of the competitive priority criteria by comparing the criteria. It was observed that fuzzy logic-based tools are able to better emulate industry experts’ reasoning of manufacturing reshoring. This research contributes to theory with a holistic framework of reshoring decision criteria, and to practice with decision-support tools for evaluation of manufacturing reshoring decisions.
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