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      Examining the relationship between big data analytics capabilities and organizational ambidexterity in the Malaysian banking sector


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          Drawing on previous literature on dynamic capability view (DCV), we examine the effects of data analytics capabilities (BDAC) on organizational ambidexterity and the paradoxical tensions between exploration and exploitation in the Malaysian banking sector. Although banks are often considered as mature commercial organizations, they are not free of issues concerning technological advancement and organizational changes for long-term competitiveness. Through statistical analysis by using data from 162 bank managers in Malaysia, it is confirmed that BDAC positively influences the two contradictory aspects of organizational ambidexterity (i.e., explorative dynamic capabilities and exploitative dynamic capabilities), and explorative dynamic capabilities also mediate the positive relationship between BDAC and exploitative marketing capabilities. The findings provide meaningful insights to researchers and bank managers on how to obtain sustainable competitive advances in the current digital era.

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          Most cited references53

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          A new criterion for assessing discriminant validity in variance-based structural equation modeling

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            Firm Resources and Sustained Competitive Advantage

            Jay Barney (1991)
            Understanding sources of sustained competitive advantage has become a major area of research in strategic management. Building on the assumptions that strategic resources are heterogeneously distributed acrossfirms and that these differences are stable over time, this article examines the link betweenfirm resources and sustained competitive advantage. Four empirical indicators of the potential of firm resources to generate sustained competitive advantage-value, rareness, imitability, and substitutability-are discussed. The model is applied by analyzing the potential of severalfirm resourcesfor generating sustained competitive advantages. The article concludes by examining implications of this firm resource model of sustained competitive advantage for other business disciplines.
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              Sources of method bias in social science research and recommendations on how to control it.

              Despite the concern that has been expressed about potential method biases, and the pervasiveness of research settings with the potential to produce them, there is disagreement about whether they really are a problem for researchers in the behavioral sciences. Therefore, the purpose of this review is to explore the current state of knowledge about method biases. First, we explore the meaning of the terms "method" and "method bias" and then we examine whether method biases influence all measures equally. Next, we review the evidence of the effects that method biases have on individual measures and on the covariation between different constructs. Following this, we evaluate the procedural and statistical remedies that have been used to control method biases and provide recommendations for minimizing method bias.

                Author and article information

                Front Big Data
                Front Big Data
                Front. Big Data
                Frontiers in Big Data
                Frontiers Media S.A.
                17 March 2023
                : 6
                [1] 1UKM-Graduate School of Business, The National University of Malaysia (UKM) , Bangi, Malaysia
                [2] 2Business School, Guangdong Ocean University, Yangjiang , Guangdong, China
                Author notes

                Edited by: Chang-Tien Lu, Virginia Tech, United States

                Reviewed by: Ku Ho Lin, National Chung Hsing University, Taiwan; Lulwah AlKulaib, Virginia Tech, United States; Lingyu Zhang, Samsung Research America, United States

                *Correspondence: Fei Long longfei5202005@ 123456hotmail.com

                This article was submitted to Data Mining and Management, a section of the journal Frontiers in Big Data

                Copyright © 2023 Aziz and Long.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                : 04 September 2022
                : 28 February 2023
                Page count
                Figures: 4, Tables: 6, Equations: 0, References: 53, Pages: 12, Words: 7878
                This research was funded by the Ministry of Higher Education of Malaysia, grant number FRGS /1/2019/SS01/UKM/02/4 and RHB-UKM Endowment, grant number RHB-UKM-2020-002.
                Big Data
                Original Research

                big data analytics capabilities,exploration,exploitation,ambidexterity,bank,malaysia


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