Yassine Talaoui , Marko Kohtamäki , Mikko Ranta , Sotirios Paroutis
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Recovering the divide: A review of the big data analytics—strategy relationship
Research on big data analytics has been burgeoning in recent decades, yet its relationship with strategy continues to be overlooked. This paper reviews how big data analytics and strategy are portrayed across 228 articles, identifying two dominant discourses: an input-output discourse that views big data analytics as a computational capability supplementing prospective strategy formulation and an entanglement discourse that theorizes big data analytics as a socially constructed agent that (re)shapes the emergent character of strategy formation. We deconstruct the inherent dichotomies of the input-output/entanglement divide and reveal how both discourses adopt disjointed positions vis-à-vis relational causality and agency. We elaborate a semiotic view of big data analytics and strategy that transcends this standoff and provides a novel theoretical account for conjoined relationality between big data analytics and strategy.
期刊介绍：
Long Range Planning (LRP) is an internationally renowned journal specializing in the field of strategic management. Since its establishment in 1968, the journal has consistently published original research, garnering a strong reputation among academics. LRP actively encourages the submission of articles that involve empirical research and theoretical perspectives, including studies that provide critical assessments and analysis of the current state of knowledge in crucial strategic areas. The primary user base of LRP primarily comprises individuals from academic backgrounds, with the journal playing a dual role within this community. Firstly, it serves as a platform for the dissemination of research findings among academic researchers. Secondly, it serves as a channel for the transmission of ideas that can be effectively utilized in educational settings. The articles published in LRP cater to a diverse audience, including practicing managers and students in professional programs. While some articles may focus on practical applications, others may primarily target academic researchers. LRP adopts an inclusive approach to empirical research, accepting studies that draw on various methodologies such as primary survey data, archival data, case studies, and recognized approaches to data collection.
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