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Big data analytics capability for improved performance of higher education institutions in the Era of IR 4.0: A multi-analytical SEM & ANN perspective

Author

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  • Ashaari, Mohamed Azlan
  • Singh, Karpal Singh Dara
  • Abbasi, Ghazanfar Ali
  • Amran, Azlan
  • Liebana-Cabanillas, Francisco J.

Abstract

Despite the growing interest towards big data within higher education institutions (HEI), research on big data analytics capability within the HEI context is somewhat limited. This study's main objective is to have a better understanding of the utilisation of big data analytics capability for data-driven decision-making to achieve better performance from Malaysian HEIs. Despite the growing interest towards big data within higher education institutions (HEI), research on big data analytics capability within the HEI context is rather limited. This study's main objective is to have a better understanding of the utilisation of big data analytics capability for data-driven decision-making to achieve better performance from Malaysian HEIs. This study validates an integrative model by combining information processing theory and resource-based view theory. Unlike extant literature, this study proposed methodology involving dual-stage analysis involving of Partial Least Squares Structural Equation Modelling and evolving Artificial Intelligence named deep learning (Artificial Neural Network) were performed. The application of deep ANN architecture can predict 83% of accuracy for the proposed model. Besides, the outcome of data-driven decision making from the relationship between big data analytic capability and data-driven decision making towards the performance of HEIs has significant findings. Results revealed that data-driven decision making could positively play an essential role in the relationship between big data analytic capability and performance of HEIs. Theoretically, the newly integrated theoretical model that incorporates information processing theory and resource-based view provides useful guidelines to HEI's about the crucial capabilities and resources that must be put into place to reap the benefits associated with big data implementations in the wake of Industry Revolution 4.0.

Suggested Citation

  • Ashaari, Mohamed Azlan & Singh, Karpal Singh Dara & Abbasi, Ghazanfar Ali & Amran, Azlan & Liebana-Cabanillas, Francisco J., 2021. "Big data analytics capability for improved performance of higher education institutions in the Era of IR 4.0: A multi-analytical SEM & ANN perspective," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    • Handle: RePEc:eee:tefoso:v:173:y:2021:i:c:s0040162521005527
    DOI: 10.1016/j.techfore.2021.121119
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    as
    1. Mahda Garmaki & Imed Boughzala & Samuel Fosso Wamba, 2016. "The effect of big data analytics capability on firm performance," Post-Print hal-01414811, HAL.
    2. Francisco Liébana-Cabanillas & Nidhi Singh & Zoran Kalinic & Elena Carvajal-Trujillo, 2021. "Examining the determinants of continuance intention to use and the moderating effect of the gender and age of users of NFC mobile payments: a multi-analytical approach," Information Technology and Management, Springer, vol. 22(2), pages 133-161, June.
    3. Paul A. Pavlou & Omar A. El Sawy, 2006. "From IT Leveraging Competence to Competitive Advantage in Turbulent Environments: The Case of New Product Development," Information Systems Research, INFORMS, vol. 17(3), pages 198-227, September.
    4. Conboy, Kieran & Mikalef, Patrick & Dennehy, Denis & Krogstie, John, 2020. "Using business analytics to enhance dynamic capabilities in operations research: A case analysis and research agenda," European Journal of Operational Research, Elsevier, vol. 281(3), pages 656-672.
    5. Gunasekaran, Angappa & Papadopoulos, Thanos & Dubey, Rameshwar & Wamba, Samuel Fosso & Childe, Stephen J. & Hazen, Benjamin & Akter, Shahriar, 2017. "Big data and predictive analytics for supply chain and organizational performance," Journal of Business Research, Elsevier, vol. 70(C), pages 308-317.
    6. 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).
    7. Prasanna Tambe, 2014. "Big Data Investment, Skills, and Firm Value," Management Science, INFORMS, vol. 60(6), pages 1452-1469, June.
    8. Janssen, Marijn & van der Voort, Haiko & Wahyudi, Agung, 2017. "Factors influencing big data decision-making quality," Journal of Business Research, Elsevier, vol. 70(C), pages 338-345.
    9. Kathleen M. Eisenhardt & Jeffrey A. Martin, 2000. "Dynamic capabilities: what are they?," Strategic Management Journal, Wiley Blackwell, vol. 21(10‐11), pages 1105-1121, October.
    10. Constantiou, Ioanna D & Kallinikos, Jannis, 2015. "New games, new rules: big data and the changing context of strategy," LSE Research Online Documents on Economics 63017, London School of Economics and Political Science, LSE Library.
    11. repec:mpr:mprres:8142 is not listed on IDEAS
    12. Talukder, Md. Shamim & Sorwar, Golam & Bao, Yukun & Ahmed, Jashim Uddin & Palash, Md. Abu Saeed, 2020. "Predicting antecedents of wearable healthcare technology acceptance by elderly: A combined SEM-Neural Network approach," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    13. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Bryde, David J. & Giannakis, Mihalis & Foropon, Cyril & Roubaud, David & Hazen, Benjamin T., 2020. "Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations," International Journal of Production Economics, Elsevier, vol. 226(C).
    14. 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.
    15. Ghazanfar Ali Abbasi & Lee Yin Tiew & Jinquan Tang & Yen-Nee Goh & Ramayah Thurasamy, 2021. "The adoption of cryptocurrency as a disruptive force: Deep learning-based dual stage structural equation modelling and artificial neural network analysis," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-26, March.
    16. Ravi Srinivasan & Morgan Swink, 2018. "An Investigation of Visibility and Flexibility as Complements to Supply Chain Analytics: An Organizational Information Processing Theory Perspective," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1849-1867, October.
    17. Shamim, Saqib & Zeng, Jing & Shafi Choksy, Umair & Shariq, Syed Muhammad, 2020. "Connecting big data management capabilities with employee ambidexterity in Chinese multinational enterprises through the mediation of big data value creation at the employee level," International Business Review, Elsevier, vol. 29(6).
    18. Wamba, Samuel Fosso & Gunasekaran, Angappa & Akter, Shahriar & Ren, Steven Ji-fan & Dubey, Rameshwar & Childe, Stephen J., 2017. "Big data analytics and firm performance: Effects of dynamic capabilities," Journal of Business Research, Elsevier, vol. 70(C), pages 356-365.
    19. Abbasi, Ghazanfar A & Jagaveeran, Mahavithya & Goh, Yen-Nee & Tariq, Beenish, 2021. "The impact of type of content use on smartphone addiction and academic performance: Physical activity as moderator," Technology in Society, Elsevier, vol. 64(C).
    20. Higueras-Castillo, Elena & Kalinic, Zoran & Marinkovic, Veljko & Liébana-Cabanillas, Francisco J., 2020. "A mixed analysis of perceptions of electric and hybrid vehicles," Energy Policy, Elsevier, vol. 136(C).
    21. 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.
    22. Ilias O. Pappas & Patrick Mikalef & Michail N. Giannakos & John Krogstie & George Lekakos, 2018. "Big data and business analytics ecosystems: paving the way towards digital transformation and sustainable societies," Information Systems and e-Business Management, Springer, vol. 16(3), pages 479-491, August.
    23. Shamim, Saqib & Zeng, Jing & Khan, Zaheer & Zia, Najam Ul, 2020. "Big data analytics capability and decision making performance in emerging market firms: The role of contractual and relational governance mechanisms," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    24. Liébana-Cabanillas, Francisco & Marinkovic, Veljko & Ramos de Luna, Iviane & Kalinic, Zoran, 2018. "Predicting the determinants of mobile payment acceptance: A hybrid SEM-neural network approach," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 117-130.
    25. Mahda Garmaki & Imed Boughzala & Samuel Fosso Wamba, 2016. "The effect of big data analytics capability on firm performance," Grenoble Ecole de Management (Post-Print) hal-01414811, HAL.
    26. Shahzad, Fakhar & Xiu, Guoyi & Shafique Khan, Muhammad Aamir & Shahbaz, Muhammad, 2020. "Predicting the adoption of a mobile government security response system from the user's perspective: An application of the artificial neural network approach," Technology in Society, Elsevier, vol. 62(C).
    27. 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.
    28. Vidgen, Richard & Shaw, Sarah & Grant, David B., 2017. "Management challenges in creating value from business analytics," European Journal of Operational Research, Elsevier, vol. 261(2), pages 626-639.
    29. Samppa Suoniemi & Lars Meyer-Waarden & Andreas Munzel & Alex Ricardo Zablah & Detmar Straub, 2020. "Big data and firm performance: The roles of market-directed capabilities and business strategy," Post-Print hal-02957479, HAL.
    30. Jana Bouwma-Gearhart & Jennifer Collins, 2015. "What We Know About Data-Driven Decision Making In Higher Education: Informing Educational Policy and Practice," Proceedings of International Academic Conferences 2805154, International Institute of Social and Economic Sciences.
    31. Akter, Shahriar & Wamba, Samuel Fosso & Gunasekaran, Angappa & Dubey, Rameshwar & Childe, Stephen J., 2016. "How to improve firm performance using big data analytics capability and business strategy alignment?," International Journal of Production Economics, Elsevier, vol. 182(C), pages 113-131.
    32. Wang, Yichuan & Kung, LeeAnn & Byrd, Terry Anthony, 2018. "Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 3-13.
    33. Ballou, Brian & Heitger, Dan L. & Stoel, Dale, 2018. "Data-driven decision-making and its impact on accounting undergraduate curriculum," Journal of Accounting Education, Elsevier, vol. 44(C), pages 14-24.
    34. Elia, Stefano & Giuffrida, Maria & Mariani, Marcello M. & Bresciani, Stefano, 2021. "Resources and digital export: An RBV perspective on the role of digital technologies and capabilities in cross-border e-commerce," Journal of Business Research, Elsevier, vol. 132(C), pages 158-169.
    35. Awan, Usama & Shamim, Saqib & Khan, Zaheer & Zia, Najam Ul & Shariq, Syed Muhammad & Khan, Muhammad Naveed, 2021. "Big data analytics capability and decision-making: The role of data-driven insight on circular economy performance," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    36. Nicholas W. Hillman & David A. Tandberg & Jacob P. K. Gross, 2014. "Performance Funding in Higher Education: Do Financial Incentives Impact College Completions?," The Journal of Higher Education, Taylor & Francis Journals, vol. 85(6), pages 826-857, November.
    37. Steven Ji-fan Ren & Samuel Fosso Wamba & Shahriar Akter & Rameshwar Dubey & Stephen J. Childe, 2017. "Modelling quality dynamics, business value and firm performance in a big data analytics environment," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5011-5026, September.
    38. Yu, Wantao & Zhao, Gen & Liu, Qi & Song, Yongtao, 2021. "Role of big data analytics capability in developing integrated hospital supply chains and operational flexibility: An organizational information processing theory perspective," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
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