Big data analytics capability for competitive advantage and firm performance in Malaysian manufacturing firms
Some recent studies claim that Data Analytics Capability (BDAC) is largely focused on developed countries such as the United States and the current adoption level of big data analytics in business is still very low. In the context of Malaysia, BDAC has not yet reached the optimal level and it was al...
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| Format: | Thesis |
| Language: | English |
| Published: |
2022
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| Online Access: | http://eprints.utm.my/108326/1/ChongChuLePAHIBS2022.pdf.pdf http://eprints.utm.my/108326/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:154393 |
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| Institution: | Universiti Teknologi Malaysia |
| Language: | English |
| Summary: | Some recent studies claim that Data Analytics Capability (BDAC) is largely focused on developed countries such as the United States and the current adoption level of big data analytics in business is still very low. In the context of Malaysia, BDAC has not yet reached the optimal level and it was also found that previous studies did not evaluate the impact of BDAC on competitive advantage in the manufacturing industry. A lacking study on BDAC, competitive advantage, and firm performance coupled with inconsistent findings between competitive advantage and firm performance has raised many questions, leading to an unclear direction for business decision-makers. Hence, this phenomenon has been investigated and the study was underpinned by the Resourced-Based View (RBV) and the entanglement view of sociomaterialism (EVS) theories in examining the relationships among higher order of BDAC, cost advantage, differentiation advantage, market, and operational performance. The study adopted a quantitative and cross-sectional research method by distributing the survey to the companies listed in the Federation of Malaysian Manufacturers (FMM) directory 2018 (49th edition). The sampling frame consisted of 3,828 companies. Employing a systematic sampling method, a sample size of 1,000 companies was determined for the study. A total of 689 companies agreed to participate in the research. 191 responses were usable and resulted in an effective response rate of 27.72 percent. IBM SPSS version 23 and Smart PLS version 3 were used to analyze the data. This study discovered that BDAC is a bundle of resources that consists of data, technology, data-driven culture, the intensity of organizational learning, and technical and managerial skills. Empirical findings provided adequate evidence that BDAC positively influences cost advantage and differentiation advantage and subsequently leads to superior firm performance. Additionally, the differentiation advantage was found to be a key factor in predicting market performance, however, failed to influence operational performance. Theoretically, both RBV and EVS could be used to link higher order of BDAC, differentiation advantage, and market performance to explain superior firm performance. This research outlined some limitations of the study and offered some recommendations for future research directions. |
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