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PurposeThe study examines how firms may transform big data analytics (BDA) into a sustainable competitive advantage and enhance business performance using BDA. Furthermore, this study identifies various resources and sub-capabilities that contribute to BDA capability.Design/methodology/approachUsing classic grounded theory (GT), resource-based theory and dynamic capability (DC), the authors conducted interviews, which involved an exploratory inductive process. Through a continuous iterative process between the collection, analysis and comparison of data, themes and their relationships appeared. The literature was used as part of the data set in the later phases of data collection and analysis to identify how the study’s findings fit with the extant literature and enrich the emerging concepts and their relationships.FindingsThe data analysis led to developing a conceptual model of BDA capability that described how BDA contributes to firm performance through the mediated impact of organizational learning (OL). The findings indicate that BDA capability is incomplete in the absence of BDA capability dimensions and their sub-dimensions, and expected advancement will not be achieved.Research limitations/implicationsThe research offers insights on how BDA is converted into an enterprise-wide initiative, by extending the BDA capability model and describing the role of per dimension in constructing the capability. In addition, the paper provides managers with insights regarding the ways in which BDA capability continuously contributes to OL, fosters organizational knowledge and organizational abilities to sense, seize and reconfigure data and knowledge to grab digital opportunities in order to sustain competitive advantage.Originality/valueThis article is the first exploratory research using GT to identify how data-driven firms obtain and sustain BDA competitive advantage, beyond prior studies that employed mostly a hypothetico-deductive stance to investigate BDA capability. While the authors discovered various dimensions of BDA capability and identified several factors, some of the prior related studies showed some of the dimensions as formative factors (e.g. Lozada et al., 2019; Mikalef et al., 2019) and some other research depicted the different dimensions of BDA capability as reflective factors (e.g. Wamba and Akter, 2019; Ferraris et al., 2019). Thus, it was found necessary to correctly define different dimensions and their contributions, since formative and reflective models represent various approaches to achieving the capability. In this line, the authors used GT, as an exploratory method, to conceptualize BDA capability and the mechanism that it contributes to firm performance. This research introduces new capability dimensions that were not examined in prior research. The study also discusses how OL mediates the impact of BDA capability on firm performance, which is considered the hidden value of BDA capability.

Despite the rising potential of the Digital Intelligence (DI) emerging concept for practitioners, only a few research studies have considered its contribution to the enterprise digital transformation. Due to its novelty, the scope, application domains, and main research themes of DI are still unclear to date. Through a Systematic Literature Review (SLR), we analyzed relevant academic literature and tentatively identified major research areas to facilitate the understanding and study of DI in the digital transformation era. The results have shown that DI is at an early stage of research and investigation. To fill the gap between theory and practice, we have proposed a research agenda of DI with several perspectives.

Big data analytics have emerged as an important area of study for both researchers and practitioners, reflects firm's ability to apply data-driven decision making. To unlock the value from big data and transform it to the intelligence, there should be implemented required capabilities for supporting analytical process. However, the predictive and prescriptive role of big data analytics, which is more than technical capabilities, raises the question of whether the IT capability constructs can be sufficient for big data analytics or should present the new capability framework. This paper attempts to conceptualize the term of ‘Big Data Analytics Capability' in line with IT capability. Accordingly, a primary study by qualitative research is implemented to adopt proposed IT capability framework for big data analytics.

Big data analytics (BDA) has emerged as an important area of study for both academics and practitioners. Despite of rising potential value of BDA, a few studies have been conducted to investigate the effect of BDA on firm performance. In this research in progress, according to the challenges of BDA dimensions (volume, variety, velocity, veracity and value) we propose the BDA capability dimensions in line with IT capability concept. BDA infrastructure capability, BDA management capability, BDA personnel capability and relational BDA capability provide the overall BDA Capability concept. The study, by employing dynamic capability, proposes that BDA capability impacts on firm financial and market performance by mediated effect of operational performance. The finding of this research by providing essential BDA capability and its effect on firm performance can apply as a roadmap and fill the gap between managers' expectation of BDA and what is emerged of BDA implementation.