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Data analytics in small and mid-size enterprises: Enablers and inhibitors for business value and firm performance

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  • Perdana, Arif
  • Lee, Hwee Hoon
  • Koh, SzeKee
  • Arisandi, Desi

Abstract

A critical question arises as to whether data analytics (DA) can bring value and improve organizational performance. The benefit offered by DA can be achieved only when organizations are able to direct their attention on the conditioning factors that amplify business value. At the same time, organizations should cautiously resolve the issues that dampen DA business value. This study applied resource-based view (RBV) and the dual factor concept to understand such factors within the Small and Mid-size Enterprises (SMEs) context. The results revealed that information and systems qualities were the catalysts for data analytics business value, whereas lack of understanding and concerns over data security and privacy were the most salient predictors that could prevent SMEs from realizing DA business value. Our study highlights the importance of understanding both enablers and inhibitors in IT business value research. We also offer strategies to stakeholders to help SMEs realize DA business value.

Suggested Citation

  • Perdana, Arif & Lee, Hwee Hoon & Koh, SzeKee & Arisandi, Desi, 2022. "Data analytics in small and mid-size enterprises: Enablers and inhibitors for business value and firm performance," International Journal of Accounting Information Systems, Elsevier, vol. 44(C).
  • Handle: RePEc:eee:ijoais:v:44:y:2022:i:c:s146708952100049x
    DOI: 10.1016/j.accinf.2021.100547
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    1. Ronald T. Cenfetelli & Andrew Schwarz, 2011. "Identifying and Testing the Inhibitors of Technology Usage Intentions," Information Systems Research, INFORMS, vol. 22(4), pages 808-823, December.
    2. Elbashir, Mohamed Z. & Collier, Philip A. & Davern, Michael J., 2008. "Measuring the effects of business intelligence systems: The relationship between business process and organizational performance," International Journal of Accounting Information Systems, Elsevier, vol. 9(3), pages 135-153.
    3. Lee, Sang-Gun & Chae, Seung Hoon & Cho, Kyung Min, 2013. "Drivers and inhibitors of SaaS adoption in Korea," International Journal of Information Management, Elsevier, vol. 33(3), pages 429-440.
    4. Lee, Lorraine & Petter, Stacie & Fayard, Dutch & Robinson, Shani, 2011. "On the use of partial least squares path modeling in accounting research," International Journal of Accounting Information Systems, Elsevier, vol. 12(4), pages 305-328.
    5. Sinan Aral & Erik Brynjolfsson & Lynn Wu, 2012. "Three-Way Complementarities: Performance Pay, Human Resource Analytics, and Information Technology," Management Science, INFORMS, vol. 58(5), pages 913-931, May.
    6. Peters, Matt D. & Wieder, Bernhard & Sutton, Steve G., 2018. "Organizational improvisation and the reduced usefulness of performance measurement BI functionalities," International Journal of Accounting Information Systems, Elsevier, vol. 29(C), pages 1-15.
    7. Raymond, Louis & Bergeron, François & Croteau, Anne-Marie & Uwizeyemungu, Sylvestre, 2019. "Determinants and outcomes of IT governance in manufacturing SMEs: A strategic IT management perspective," International Journal of Accounting Information Systems, Elsevier, vol. 35(C).
    8. Peters, Matt D. & Wieder, Bernhard & Sutton, Steve G. & Wakefield, James, 2016. "Business intelligence systems use in performance measurement capabilities: Implications for enhanced competitive advantage," International Journal of Accounting Information Systems, Elsevier, vol. 21(C), pages 1-17.
    9. Božič, Katerina & Dimovski, Vlado, 2019. "Business intelligence and analytics for value creation: The role of absorptive capacity," International Journal of Information Management, Elsevier, vol. 46(C), pages 93-103.
    10. Liu, Ying & Soroka, Anthony & Han, Liangxiu & Jian, Jin & Tang, Min, 2020. "Cloud-based big data analytics for customer insight-driven design innovation in SMEs," International Journal of Information Management, Elsevier, vol. 51(C).
    11. Lynn Wu & Bowen Lou & Lorin Hitt, 2019. "Data Analytics Supports Decentralized Innovation," Management Science, INFORMS, vol. 65(10), pages 4863-4877, October.
    12. Ghasemaghaei, Maryam, 2021. "Understanding the impact of big data on firm performance: The necessity of conceptually differentiating among big data characteristics," International Journal of Information Management, Elsevier, vol. 57(C).
    13. William H. DeLone & Ephraim R. McLean, 1992. "Information Systems Success: The Quest for the Dependent Variable," Information Systems Research, INFORMS, vol. 3(1), pages 60-95, March.
    14. Erik Brynjolfsson & Kristina McElheran, 2016. "The Rapid Adoption of Data-Driven Decision-Making," American Economic Review, American Economic Association, vol. 106(5), pages 133-139, May.
    15. Anthony Vance & Christophe M. Elie-Dit-Cosaque & Detmar W. Straub, 2008. "Examining Trust in Information Technology Artifacts: The Effects of System Quality and Culture," Post-Print halshs-00641137, HAL.
    16. Rikhardsson, Pall & Yigitbasioglu, Ogan, 2018. "Business intelligence & analytics in management accounting research: Status and future focus," International Journal of Accounting Information Systems, Elsevier, vol. 29(C), pages 37-58.
    17. Prasanna Tambe, 2014. "Big Data Investment, Skills, and Firm Value," Management Science, INFORMS, vol. 60(6), pages 1452-1469, June.
    18. Gary C. Moore & Izak Benbasat, 1991. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, INFORMS, vol. 2(3), pages 192-222, September.
    19. repec:dau:papers:123456789/2723 is not listed on IDEAS
    20. Krieger, Felix & Drews, Paul & Velte, Patrick, 2021. "Explaining the (non-) adoption of advanced data analytics in auditing: A process theory," International Journal of Accounting Information Systems, Elsevier, vol. 41(C).
    21. Jay B. Barney, 1986. "Strategic Factor Markets: Expectations, Luck, and Business Strategy," Management Science, INFORMS, vol. 32(10), pages 1231-1241, October.
    22. Sarstedt, Marko & Ringle, Christian M. & Smith, Donna & Reams, Russell & Hair, Joseph F., 2014. "Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers," Journal of Family Business Strategy, Elsevier, vol. 5(1), pages 105-115.
    23. Bouwman, Harry & Nikou, Shahrokh & de Reuver, Mark, 2019. "Digitalization, business models, and SMEs: How do business model innovation practices improve performance of digitalizing SMEs?," Telecommunications Policy, Elsevier, vol. 43(9).
    24. Erik Brynjolfsson & Lorin M. Hitt, 2000. "Beyond Computation: Information Technology, Organizational Transformation and Business Performance," Journal of Economic Perspectives, American Economic Association, vol. 14(4), pages 23-48, Fall.
    25. Andrew Burton-Jones & Camille Grange, 2013. "From Use to Effective Use: A Representation Theory Perspective," Information Systems Research, INFORMS, vol. 24(3), pages 632-658, September.
    26. 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.
    27. Michael J. Tippins & Ravipreet S. Sohi, 2003. "IT competency and firm performance: is organizational learning a missing link?," Strategic Management Journal, Wiley Blackwell, vol. 24(8), pages 745-761, August.
    28. Appelbaum, Deniz & Kogan, Alexander & Vasarhelyi, Miklos & Yan, Zhaokai, 2017. "Impact of business analytics and enterprise systems on managerial accounting," International Journal of Accounting Information Systems, Elsevier, vol. 25(C), pages 29-44.
    29. Erkki M. Lassila & Sinikka Moilanen & Janne T. Järvinen, 2019. "Visualising a “good game”: analytics as a calculative engine in a digital environment," Accounting, Auditing & Accountability Journal, Emerald Group Publishing Limited, vol. 32(7), pages 2142-2166, September.
    30. Sarstedt, Marko & Hair, Joseph F. & Ringle, Christian M. & Thiele, Kai O. & Gudergan, Siegfried P., 2016. "Estimation issues with PLS and CBSEM: Where the bias lies!," Journal of Business Research, Elsevier, vol. 69(10), pages 3998-4010.
    31. Prasad, Acklesh & Green, Peter, 2015. "Governing cloud computing services: Reconsideration of IT governance structures," International Journal of Accounting Information Systems, Elsevier, vol. 19(C), pages 45-58.
    32. 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.
    33. Koreff, Jared & Weisner, Martin & Sutton, Steve G., 2021. "Data analytics (ab) use in healthcare fraud audits," International Journal of Accounting Information Systems, Elsevier, vol. 42(C).
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