Temporary deembedding buyer – supplier relationships: A complexity perspective
研究了买方与供应商之间临时放松嵌入关系（临时去嵌入）对绩效的影响，通过案例和仿真发现，这种临时去嵌入能激发搜索并提升双方绩效。
Research on buyer–supplier relationships has debated the advantages and disadvantages of embedded relationships. We join this debate by developing theory on the performance implications of relaxing embedded buyer–supplier relationships for a limited period of time—a previously neglected phenomenon we refer to as temporary deembedding . To capture this phenomenon's dynamic and complex nature, we use a combined‐method approach. First, we conducted a longitudinal case study of the relationship between Nissan and a strategic first‐tier supplier. This case study suggests that temporary deembedding reinvigorates search and leads to higher performance for both the buyer and supplier. Second, we built a computational simulation model using the search perspective from complexity theory to complement the theory grounded in our case study. Our simulations confirm the case findings while shedding additional light on how frequency, duration, and intensity of deembedding affect supply chain performance.