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Unpacking associations between positive-negative valence and ambidexterity of big data. Implications for firm performance

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  • Luqman, Adeel
  • Wang, Liangyu
  • Katiyar, Gagan
  • Agarwal, Reeti
  • Mohapatra, Amiya Kumar

Abstract

Motivated by the importance of big data utilization and its impact on firm performance, the current study examines the influence of the perceived valence factors of the top management team (TMT) on the ambidexterity of big data utilization and firm performance. Despite the growing recognition of the significance of ambidexterity and the role of TMTs in leveraging big data, there remains a lack of empirical research that comprehensively examines the associations between TMT valence factors, the ambidexterity of big data utilization, and firm performance. By integrating valence theory and ambidexterity theory, this study fills this research gap and provides valuable insights into the relationship between TMT valence factors, big data utilization, and firm performance outcomes. Data were collected from 357 respondents, and the findings indicate that positive TMT valence factors – such as data proficiency, industry expertise, and knowledge diversity – as well as negative valence factors – such as data compatibility, complexity, and benefit disconfirmation – are negatively associated with ambidexterity. Furthermore, the findings of our study have important implications for organizations seeking to enhance their operational and financial performance through the effective utilization of big data. Notably, our results highlight that promoting ambidexterity in handling big data within firms results in improved operational and financial outcomes. These findings provide valuable insights into the relatively unexplored area of TMT valence factors and their impact on driving ambidexterity in big data utilization, ultimately leading to enhanced organizational performance.

Suggested Citation

  • Luqman, Adeel & Wang, Liangyu & Katiyar, Gagan & Agarwal, Reeti & Mohapatra, Amiya Kumar, 2024. "Unpacking associations between positive-negative valence and ambidexterity of big data. Implications for firm performance," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    • Handle: RePEc:eee:tefoso:v:200:y:2024:i:c:s0040162523007394
    DOI: 10.1016/j.techfore.2023.123054
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    1. Alberto Bertello & Alberto Ferraris & Stefano Bresciani & Paola Bernardi, 2021. "Big data analytics (BDA) and degree of internationalization: the interplay between governance of BDA infrastructure and BDA capabilities," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 25(4), pages 1035-1055, December.
    2. Patrick Mikalef & Ilias O. Pappas & John Krogstie & Michail Giannakos, 2018. "Big data analytics capabilities: a systematic literature review and research agenda," Information Systems and e-Business Management, Springer, vol. 16(3), pages 547-578, August.
    3. One-Ki (Daniel) Lee & Vallabh Sambamurthy & Kai H. Lim & Kwok Kee Wei, 2015. "How Does IT Ambidexterity Impact Organizational Agility?," Information Systems Research, INFORMS, vol. 26(2), pages 398-417, June.
    4. Mahda Garmaki & Rebwar Kamal Gharib & Imed Boughzala, 2023. "Big data analytics capability and contribution to firm performance: the mediating effect of organizational learning on firm performance," Post-Print hal-04096106, HAL.
    5. Zi-Lin He & Poh-Kam Wong, 2004. "Exploration vs. Exploitation: An Empirical Test of the Ambidexterity Hypothesis," Organization Science, INFORMS, vol. 15(4), pages 481-494, August.
    6. Murad Moqbel & Valerie Bartelt & Mohammed Al-Suqri & Azzah Al-Maskari, 2017. "Does privacy matter to millennials? The case for personal cloud," Journal of Information Privacy and Security, Taylor & Francis Journals, vol. 13(1), pages 17-33, January.
    7. Shalini Talwar & Puneet Kaur & Samuel Fosso Wamba & Amandeep Dhir, 2021. "Big Data in operations and supply chain management: a systematic literature review and future research agenda," International Journal of Production Research, Taylor & Francis Journals, vol. 59(11), pages 3509-3534, June.
    8. O'Reilly, Charles A., III & Tushman, Michael L., 2013. "Organizational Ambidexterity: Past, Present and Future," Research Papers 2130, Stanford University, Graduate School of Business.
    9. Maroufkhani, Parisa & Tseng, Ming-Lang & Iranmanesh, Mohammad & Ismail, Wan Khairuzzaman Wan & Khalid, Haliyana, 2020. "Big data analytics adoption: Determinants and performances among small to medium-sized enterprises," International Journal of Information Management, Elsevier, vol. 54(C).
    10. Shet, Sateesh.V. & Poddar, Tanuj & Wamba Samuel, Fosso & Dwivedi, Yogesh K., 2021. "Examining the determinants of successful adoption of data analytics in human resource management – A framework for implications," Journal of Business Research, Elsevier, vol. 131(C), pages 311-326.
    11. Rialti, Riccardo & Zollo, Lamberto & Ferraris, Alberto & Alon, Ilan, 2019. "Big data analytics capabilities and performance: Evidence from a moderated multi-mediation model," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
    12. Sumit Maheshwari & Prerna Gautam & Chandra K. Jaggi, 2021. "Role of Big Data Analytics in supply chain management: current trends and future perspectives," International Journal of Production Research, Taylor & Francis Journals, vol. 59(6), pages 1875-1900, March.
    13. José Luis Ferreras-Méndez & Oscar Llopis & Joaquín Alegre, 2022. "Speeding up new product development through entrepreneurial orientation in SMEs: The moderating role of ambidexterity," Post-Print hal-03603189, HAL.
    14. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    15. Jansen, J.J.P. & van den Bosch, F.A.J. & Volberda, H.W., 2005. "Managing Potential and Realized Absorptive Capacity: How do Organizational Antecedents matter?," ERIM Report Series Research in Management ERS-2005-025-STR, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    16. Zhou, Jiaying & Dahana, Wirawan Dony & Ye, Qiongwei & Zhang, Qingyu & Ye, Mingqi & Li, Xi, 2023. "Hedonic service consumption and its dynamic effects on sales in the brick-and-mortar retail context," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    17. Dursun Delen & Sudha Ram, 2018. "Research challenges and opportunities in business analytics," Journal of Business Analytics, Taylor & Francis Journals, vol. 1(1), pages 2-12, January.
    18. Brewis, Claire & Dibb, Sally & Meadows, Maureen, 2023. "Leveraging big data for strategic marketing: A dynamic capabilities model for incumbent firms," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    19. Ranjan, Jayanthi & Foropon, Cyril, 2021. "Big Data Analytics in Building the Competitive Intelligence of Organizations," International Journal of Information Management, Elsevier, vol. 56(C).
    20. Benzidia, Smail & Makaoui, Naouel & Bentahar, Omar, 2021. "The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    21. Zhang, Qingyu & Gao, Bohong & Luqman, Adeel, 2022. "Linking green supply chain management practices with competitiveness during covid 19: The role of big data analytics," Technology in Society, Elsevier, vol. 70(C).
    22. Tønnessen, Øystein & Dhir, Amandeep & Flåten, Bjørn-Tore, 2021. "Digital knowledge sharing and creative performance: Work from home during the COVID-19 pandemic," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    23. Donald F. Kuratko, 2005. "The Emergence of Entrepreneurship Education: Development, Trends, and Challenges," Entrepreneurship Theory and Practice, , vol. 29(5), pages 577-597, September.
    24. Parraguez, Pedro & Škec, Stanko & e Carmo, Duarte Oliveira & Maier, Anja, 2020. "Quantifying technological change as a combinatorial process," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    25. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Papadopoulos, Thanos & Luo, Zongwei & Wamba, Samuel Fosso & Roubaud, David, 2019. "Can big data and predictive analytics improve social and environmental sustainability?," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 534-545.
    26. Robert Wayne Gregory & Mark Keil & Jan Muntermann & Magnus Mähring, 2015. "Paradoxes and the Nature of Ambidexterity in IT Transformation Programs," Information Systems Research, INFORMS, vol. 26(1), pages 57-80, March.
    27. Tine Buyl & Christophe Boone & Walter Hendriks & Paul Matthyssens, 2011. "Top Management Team Functional Diversity and Firm Performance: The Moderating Role of CEO Characteristics," Journal of Management Studies, Wiley Blackwell, vol. 48(1), pages 151-177, January.
    28. Kaur, Puneet & Talwar, Shalini & Islam, Nazrul & Salo, Jari & Dhir, Amandeep, 2022. "The effect of the valence of forgiveness to service recovery strategies and service outcomes in food delivery apps," Journal of Business Research, Elsevier, vol. 147(C), pages 142-157.
    29. Sebastian Raisch & Julian Birkinshaw & Gilbert Probst & Michael L. Tushman, 2009. "Organizational Ambidexterity: Balancing Exploitation and Exploration for Sustained Performance," Organization Science, INFORMS, vol. 20(4), pages 685-695, August.
    30. repec:ucp:bkecon:9780226316529 is not listed on IDEAS
    31. Patrucco, Andrea S. & Marzi, Giacomo & Trabucchi, Daniel, 2023. "The role of absorptive capacity and big data analytics in strategic purchasing and supply chain management decisions," Technovation, Elsevier, vol. 126(C).
    32. Han, Hui & Trimi, Silvana, 2022. "Towards a data science platform for improving SME collaboration through Industry 4.0 technologies," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    33. Li, Xi & Dahana, Wirawan Dony & Ye, Qiongwei & Peng, Luluo & Zhou, Jiaying, 2021. "How does shopping duration evolve and influence buying behavior? The role of marketing and shopping environment," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    34. Ghasemaghaei, Maryam, 2020. "The role of positive and negative valence factors on the impact of bigness of data on big data analytics usage," International Journal of Information Management, Elsevier, vol. 50(C), pages 395-404.
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