The effects of dynamic capabilities, culture and the role of management accountant on the relationship between big data analytics capabilities and innovation performance

Big Data Analytics (BDA) have the power to modernize traditional ways of doing business. Nevertheless, Big Data Analytics Capabilities (BDAC) impact on a firm’s innovation performance is still not fully understood. The ‘Age of Data’ is thriving because new data is being produced at an unprecedented...

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Bibliographic Details
Main Author: Munir, Sabra
Format: Thesis
Language:English
Published: 2022
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Online Access:http://eprints.utm.my/108361/1/SabraMunirPAHIBS2022.pdf.pdf
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Summary:Big Data Analytics (BDA) have the power to modernize traditional ways of doing business. Nevertheless, Big Data Analytics Capabilities (BDAC) impact on a firm’s innovation performance is still not fully understood. The ‘Age of Data’ is thriving because new data is being produced at an unprecedented rate and increasing volume due to the global usage of different electronic devices and gadgets connected through the internet and other networks. Innovation is a vital part of obtaining business value. There is very little research on how organizations need to change to leverage such innovations. An increasing number of studies have investigated and theorized about the strategies and structures that could help firms acquire the capacity to continuously innovate by introducing new products through Process Oriented Dynamic Capabilities (PODC). Most researchers explored the phenomenon of BDA from either a theoretical point of view or neglected the intermediate and moderating factors, such as PODC, Organizational Culture (OC) and the Role of Management Accountant (RMA). Drawing on the resource-based view and the socio-materiality theory and recent literature on BDA, this study attempts to fill this gap by examining the indirect relationship between BDAC and organizational innovation performance (OIP). The current study extends existing research by proposing that BDAC enable pharmaceutical companies to generate insight that can help strengthen their PODC, which positively impacts OIP. To test the proposed research model, the current study used survey data from 181 pharmaceutical companies in Pakistan. The respondents were top management of the companies. Through partial least squares structural equation modelling and bootstrapped moderated mediation analysis, the results support the current study’s assumptions regarding the indirect effect BDAC has on OIP. Specifically, the results show that PODC partially mediates the relationship between BDAC and OIP. In addition, OC moderates and enhances the relationship between BDAC and OIP. Furthermore, OC did not moderate the relationship between PODC and OIP. At the same time, with RMA as a moderator, the relationship between PODC and OIP is also significant. However, RMA did not moderate the relationship between BDAC and OIP. Building on this status of valuable knowledge and the existing literature gap, the objective of the current study was to understand whether and through what latest mechanisms BDAC can lead to enhanced OIP. This study contributes theoretically and empirically to the existing literature on BDA and innovation. The findings provide practical implications for top executives in the innovative industry on implementing BDAC to enhance innovation and effective decision making to achieve competitive advantage and business value with moderating effect of OC. Results show a need to convert big data into meaningful information for strategic decision-making. Management accountant plays a vital role with the help of new skills set in BDA to develop expertise and bridge between data analysts and business executives as a moderator.