Big data analytics capabilities and innovation effect of dynamic capabilities, organizational culture and role of management accountants

Author:

Munir Sabra,Abdul Rasid Siti Zaleha,Aamir Muhammad,Jamil Farrukh,Ahmed Ishfaq

Abstract

Purpose This paper aims to assess the impact of big data analytics capabilities (BDAC) on organizational innovation performance through process-oriented dynamic capabilities (PODC), as a mediator, as well as the moderating roles of organizational culture (OC) and management accountants, in this artificial intelligence (AI) era. This paper also aims to provide information on the emerging trends and implications of the abovementioned relationships by focusing on these relationships and interactions. Design/methodology/approach This exploratory study used the close-ended questionnaire approach based on the resource-based view and socio-materiality theories. This included sending questionnaires to top-level management, including Chief Financial Officer/Chief Executive Officers/Chief Information Officers (CFO/CEOs/CIOs), having an in-depth understanding of the concepts, practical applications and usage of big data as well as BDAC.181 valid questionnaire-based responses were analyzed using the partial least square structural equation modelling technique and bootstrapping moderated mediation method. Findings This study provides empirical insights into how BDAC impact innovative performance through PODC as well as the moderating effects of OC and management accountants. This involves a shift in focus from almost standardized approaches to developing BDAC without contextual focus on approaches that are much more heterogeneously related to each organization and hence are more focused on the context of the pharmaceutical industry. Research limitations/implications The main aim of key research questions in this study is to increase the contributions of BDAC toward improving innovation performance in the presence of the abovementioned variables and relationships that exist between them. The chosen research approach can be improved by carrying out interviews with the top management to obtain more relevant and detailed information for developing a better understanding of the abovementioned relationships. Practical implications This study outlines how organizations that are developing BDAC approaches can focus on relevant factors and variables to help their initiatives and its role in organizational innovative performance. This will also help them develop sustainable competitive advantage in manufacturing concerns, specifically in the health industry, namely, the pharmaceutical industry. Originality/value This study investigated the effects and implications of big data on organizations in the AI era that aim to achieve innovation performance. At the same time, it provides an original understanding of the contextual importance of investing in BDAC development. It also considers the role of management accountants as a bridge between data scientists and business managers in a big data environment, especially in the pharmaceutical industry. The current study used first-time data from surveys involving CFOs, CEOs or CIOs of pharmaceutical companies in Pakistan and analyzed the proposed model using bootstrapping moderated mediation analysis.

Publisher

Emerald

Subject

Business and International Management,Management of Technology and Innovation

Reference130 articles.

1. Big data research in information systems: toward an inclusive research agenda;Journal of the Association for Information Systems,2016

2. Conceptual model development of big data analytics implementation assessment effect on decision-making;International Journal of Interactive Multimedia and Artificial Intelligence,2018

3. Integration of non‐market and market activities in cross‐border mergers and acquisitions;British Journal of Management,2017

4. How to improve firm performance using big data analytics capability and business strategy alignment?;International Journal of Production Economics,2016

5. Factors influencing adoption of mobile banking by Jordanian bank customers: extending UTAUT2 with trust;International Journal of Information Management,2017

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