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

This is the author accepted manuscriptPurpose: 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

Critical barriers to business intelligence open source software adoption

Over the past few years, managers have been hard pressed to become more data-driven, and one of the prerequisites in doing so is through the adoption of Business Intelligence (BI) tools. However (1) the adoption of BI tools remains relatively low (2) the acquisition costs of proprietary BI tools are relatively high and (3) the level of satisfaction with these BI tools remain low. Given the potential of open source BI (OSBI) tools, there is a need for analyzing barriers that prevent organizations from adopting OSBI. Drawing a systematic review and a Qualitative Survey of BI Experts, this study proposes a framework that categorizes and structures 23 barriers to OSBI adoption by organizations including 4 that were identified by BI Experts but not explicitly found in the literature. This paper contributes to OSS and Information Systems (IS) research literature on BI adoption in general and provides specific insights to practitioners. Copyright © 2019, IGI Global