Global Facility Location Decision making: an in-depth investigation into multilevel information alignment- relationships, structuring and boundaries

Abstract

Global facility location decisions (GFLDs) are essential for organizational strategy, involving the decision to set up manufacturing facilities, warehouses, and distribution centers. This study explores GFLDs, focusing on aligning micro-level attributes (firm priorities, strategies) with macro-level factors (labor, logistics, government incentives, transportation infrastructure). The COVID-19 pandemic has prompted firms to consider nearshoring or reshoring, re-evaluating their global networks and recognizing hidden costs related to non-economic macro attributes (government incentives, environmental regulations, IP protection). Managers face challenges in aligning multilevel information, especially in SMEs and MNEs, which deal with diverse international markets and resource constraints. Multilevel theory indicates that misalignments can lead to inaccuracies in specifying location constructs, acquiring comprehensive information, and structuring decision-making processes. This includes: a) Knowledge gaps on multilevel relationships for location movements, b) Lack of structured decision-making, c) Difficulty in acquiring precise location attribute information. The thesis addresses these issues through four papers: 1. A literature review identifies dominant multilevel determinants and their relationships. 2. The second and third papers explore decision-making challenges using experiments and managerial interviews. 3. The final paper examines the impact of information volume and variety on managerial decision outcomes through simulation-based experiments. Findings highlight critical relationships between macro capabilities (production, institutional, technological factors) and micro-level priorities (cost implications, quality). The research shows that more information isn't always better, identifying an optimal information volume for decision satisfaction. This study contributes to GFLD and multi-attribute decision analysis (MADA), emphasizing multilevel paradigms for offshoring and reshoring, challenging previous economic assumptions, and providing practical insights for firms and policymakers.