Reshaping competitive advantages with analytics capabilities in service systems
تغییر شکل مزایای رقابتی با قابلیت تجزیه و تحلیل در سیستم های خدماتی-2020
Big data analytics capability can reshape competitive advantages for a service system. However, little is known about how to develop and operationalize a service system analytics capability (SSAC) model. Drawing on the resource based view (RBV), dynamic capability theory (DCT) and the emerging literature on big data analytics, this study develops and validates an SSAC model and frames its impact on competitive advantages using a thematic analysis, delphi studies (n=35) and a survey (n=251) . The main ﬁndings illuminate the varying importance of three primary dimensions (i.e., service system analytics management capability, technology capability and personnel capability) and various respective sub dimensions (i.e., service system planning, in- vestment, coordination, control, connectivity, compatibility, modularity, technology management knowledge, technical knowledge, business knowledge and relationship knowledge) in developing overall analytics cap- abilities for a service system. The ﬁndings also conﬁrm the strong mediating eﬀects of three dynamic capabilities (i.e., market sensing, seizing and reconﬁguring) in establishing competitive advantages. We critically discuss the implications of our ﬁndings for theory, methods and practice with limitations and future research directions.1.0.
Keywords: Big data | Service analytics capability | Dynamic capability | Competitive advantage