Information technology-enabled explorative learning and competitive performance in industrial service SMEs: a configurational analysis

Abstract

Purpose: As purveyors of knowledge-based and high value-added services to the manufacturing sector, industrial service small- and medium-sized enterprises (SMEs) must develop the information technology (IT) capabilities that, in combination with other non-IT capabilities, enable their capacity for organizational learning (OL) and for explorative learning in particular. In this context, this study aims to identify the different causal configurations that account for the nonlinear complex interplay of IT capabilities for exploration and strategic capabilities for explorative learning as they affect these firms’ competitive performance. Design/methodology/approach: Survey data obtained from 92 industrial service SMEs were analyzed with a configurational approach, using fuzzy set qualitative comparative analysis (fsQCA). Findings: As it allows for equifinality, the fsQCA analysis identified two sets of causal configurations that characterize the sampled firms’ explorative learning capability as it relates to competitive performance. In the first set, two configurations were equally associated with high innovation performance, whereas in the second set, four configurations were equally associated with high productivity. Originality/value: By viewing explorative learning as a dynamic capability that is enabled by the firm’s IT and strategic capabilities, the study contributes to OL theory by providing a more concrete or “operational” grounding, which allows for a greater practical applicability of this theory. By taking both the configurational and capability-based views of the OL-IT-performance causal framework, the authors provide an empirical basis for unraveling, explaining and understanding the complex non-linear relationships embedded within this framework.