Despite growing interest in boundary-spanning knowledge processes, research on how the joint configuration of search depth and breadth impacts supply chain performance remains limited. This study integrates the knowledge-based view and ambidexterity theory to explore how manufacturing firms configure boundary-spanning search (BSS) to enhance supply chain performance.
Empirical data from 285 Chinese manufacturing firms were analyzed using polynomial regression and response surface analysis to examine the relationships between BSS-Depth, BSS-Breadth, and supply chain performance, and the mediating role of digital resource orchestration capability. We complemented the survey with post-hoc semi-structured interviews with 10 manufacturing managers, focusing on discriminating between BSS-Depth and BSS-Breadth, managerial views on aligned and misaligned search configurations, and process explanations for why digital resource orchestration capability does not mediate the relationship between BSS-Breadth and supply chain performance.
An aligned configuration of BSS-Depth and BSS-Breadth outperforms misaligned configurations, with the “high BSS-Breadth–high BSS-Depth” combination yielding the best supply chain performance. Under misaligned conditions, prioritizing BSS-Depth has a smaller negative impact than prioritizing BSS-Breadth. Digital resource orchestration capability mediates the relationship between BSS-Depth and supply chain performance but has no significant mediating effect for BSS-Breadth.
This study examines the role of BSS-Depth and BSS-Breadth configurations in supply chain management, enriches ambidexterity configurations, and clarifies the role of digital resource orchestration capability in knowledge management. It provides actionable insights for manufacturing firms to optimize their search approaches, align stability and flexibility, and enhance supply chain performance.
