Bridging Big Data Analytics Capability and Competitive Advantage in China’s Agribusiness: The Mediator of Absorptive Capacity
This research examines the relationship between big data analytics capability (BDAC) and competitive advantage (CA) in China’s agribusiness sector, with a specific focus on the mediating role of absorptive capacity (AC). Although BDAC has been extensively studied in other industries, its role within...
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| Format: | Article |
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MDPI AG
2024-12-01
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| Series: | Systems |
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| Online Access: | https://www.mdpi.com/2079-8954/13/1/3 |
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| author | Peng Zhang Ramayah Thurasamy |
| author_facet | Peng Zhang Ramayah Thurasamy |
| author_sort | Peng Zhang |
| collection | DOAJ |
| description | This research examines the relationship between big data analytics capability (BDAC) and competitive advantage (CA) in China’s agribusiness sector, with a specific focus on the mediating role of absorptive capacity (AC). Although BDAC has been extensively studied in other industries, its role within agribusiness remains underexplored, particularly in developing economies like China. This study addresses this gap by investigating how BDAC can be utilized to enhance competitive advantage in the unique context of agribusiness. Grounded in Resource-Based Theory (RBT), a comprehensive framework is developed to elucidate the interconnections among BDAC, CA, and AC. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) on data collected from 287 agribusiness firms in China, the findings reveal that key resources—such as data quality, infrastructure, information systems, data governance, data-driven culture, managerial expertise, and technical proficiency—significantly influence BDAC. Moreover, BDAC is shown to positively impact CA, with AC serving as a critical mediator in this relationship. These results emphasize the strategic importance of integrating BDAC and AC to enhance the competitiveness of agribusinesses, particularly amidst rapid digital transformation. This study provides valuable contributions to the literature on BDAC, enriches the theoretical foundations of RBT in agribusiness contexts, and offers practical recommendations for digital transformation strategies in the sector. |
| format | Article |
| id | doaj-art-7df28a8ac4434135b36a8e79960c1d84 |
| institution | Kabale University |
| issn | 2079-8954 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj-art-7df28a8ac4434135b36a8e79960c1d842025-01-24T13:50:25ZengMDPI AGSystems2079-89542024-12-01131310.3390/systems13010003Bridging Big Data Analytics Capability and Competitive Advantage in China’s Agribusiness: The Mediator of Absorptive CapacityPeng Zhang0Ramayah Thurasamy1School of Management, Zhengzhou Business University, Gongyi 451200, ChinaSchool of Management, Universiti Sains Malaysia, Minden 11800, MalaysiaThis research examines the relationship between big data analytics capability (BDAC) and competitive advantage (CA) in China’s agribusiness sector, with a specific focus on the mediating role of absorptive capacity (AC). Although BDAC has been extensively studied in other industries, its role within agribusiness remains underexplored, particularly in developing economies like China. This study addresses this gap by investigating how BDAC can be utilized to enhance competitive advantage in the unique context of agribusiness. Grounded in Resource-Based Theory (RBT), a comprehensive framework is developed to elucidate the interconnections among BDAC, CA, and AC. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) on data collected from 287 agribusiness firms in China, the findings reveal that key resources—such as data quality, infrastructure, information systems, data governance, data-driven culture, managerial expertise, and technical proficiency—significantly influence BDAC. Moreover, BDAC is shown to positively impact CA, with AC serving as a critical mediator in this relationship. These results emphasize the strategic importance of integrating BDAC and AC to enhance the competitiveness of agribusinesses, particularly amidst rapid digital transformation. This study provides valuable contributions to the literature on BDAC, enriches the theoretical foundations of RBT in agribusiness contexts, and offers practical recommendations for digital transformation strategies in the sector.https://www.mdpi.com/2079-8954/13/1/3agribusinessbig data analytics capabilitycompetitive advantageabsorptive capacityChina |
| spellingShingle | Peng Zhang Ramayah Thurasamy Bridging Big Data Analytics Capability and Competitive Advantage in China’s Agribusiness: The Mediator of Absorptive Capacity Systems agribusiness big data analytics capability competitive advantage absorptive capacity China |
| title | Bridging Big Data Analytics Capability and Competitive Advantage in China’s Agribusiness: The Mediator of Absorptive Capacity |
| title_full | Bridging Big Data Analytics Capability and Competitive Advantage in China’s Agribusiness: The Mediator of Absorptive Capacity |
| title_fullStr | Bridging Big Data Analytics Capability and Competitive Advantage in China’s Agribusiness: The Mediator of Absorptive Capacity |
| title_full_unstemmed | Bridging Big Data Analytics Capability and Competitive Advantage in China’s Agribusiness: The Mediator of Absorptive Capacity |
| title_short | Bridging Big Data Analytics Capability and Competitive Advantage in China’s Agribusiness: The Mediator of Absorptive Capacity |
| title_sort | bridging big data analytics capability and competitive advantage in china s agribusiness the mediator of absorptive capacity |
| topic | agribusiness big data analytics capability competitive advantage absorptive capacity China |
| url | https://www.mdpi.com/2079-8954/13/1/3 |
| work_keys_str_mv | AT pengzhang bridgingbigdataanalyticscapabilityandcompetitiveadvantageinchinasagribusinessthemediatorofabsorptivecapacity AT ramayahthurasamy bridgingbigdataanalyticscapabilityandcompetitiveadvantageinchinasagribusinessthemediatorofabsorptivecapacity |