Abstract
Big data has been widely discussed for several years. However, whether the implementation of big data really bring in observable benefits on firm performance remains a critical issue for the top management team. In this study, we investigate the association between big data implementation and the corresponding financial performance, productivity, and market value. Our results demonstrate that big data implementation is positively related to an improvement in financial performance and the market value but such effect is not stronger for first movers. Implications are discussed.
Similar content being viewed by others
Notes
We exclude companies from the following industries: manufacturing electronic computers (SIC code 3571), computer storage devices (SIC code 7373), computer processing and data preparation and processing services (SIC code 7374), information retrieval services (SIC code 7375), and computer facilities management services (SIC code 7376).
Note that the size effect has been included in the model since the model decomposes a ratio into a regression model. That is, regardless of the size effect, we are looking at the association between the numerator and denominator.
References
Barua, A., Kriebel, C., & Mukhopadhyay, T. (1995). Information technologies and business value: An analytic and empirical investigation. Information Systems Research, 6(1), 3–23.
Barua, A., Konana, P., Whinston, A. B., & Yin, F. (2004). An empirical investigation of net-enabled business value. MIS Quarterly, 28(4), 585–620.
Bharadwaj, A. S. (2000). A resource-based perspective on information technology capability and firm performance: An empirical investigation. MIS Quarterly, 24(1), 169–196.
Brynjolfsson, E. (1993). The productivity paradox of information technology. Communications of the ACM, 36(12), 66–77.
Brynjolfsson, E., & Hitt, L. M. (1998). Beyond the productivity paradox. Communications of the ACM, 41(8), 49–55.
Brynjolfsson, E., & Yang, S. (1996). Information technology and productivity: A review of the literature. Advances in Computers, 43, 179–214.
Brynjolfsson, E., Hitt, L. M., and Kim, H. H. (2011). Strength in numbers: How does data-driven decisionmaking affect firm performance? Available at SSRN 1819486.
Byrd, T. A., Pitts, J. P., Adrian, A. M., & Davidson, N. W. (2008). Examination of a path model relating information technology infrastructure with firm performance. Journal of Business Logistics, 29(2), 161–188.
Chatfield, A. T., & Bjorn-Andersen, N. (1997). The impact of IOS-enabled business process change on business outcomes: Transformation of the value chain of Japan airlines. Journal of Management Information System, 14(1), 13–40.
Chen, C. P., & Zhang, C.-Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on big data. Information Sciences, 275, 314–347.
Chen, D. Q., Preston, D. S., & Swink, M. (2015). How the use of big data analytics affects value creation in supply chain management. Journal of Management Information Systems, 32(4), 4–39.
Côrte-Real, N., Oliveira, T., & Ruivo, P. (2017). Assessing business value of big data Anlytics in European firms. Journal of Business Research, 70, 379–390.
Davenport, T. (2014). Big data at work: Dispelling the myths, uncovering the opportunities. Harvard Business Review Press.
Dutta, A., Lee, H., & Yasai-Ardekani, M. (2014). Digital systems and competitive responsiveness: The dynamics of IT business value. Information Management, 51(6), 762–773.
Erden, Z., Klang, D., Sydler, R., & Krogh, G. V. (2014). Knowledge-flows and firm performance. Journal of Business Research, 67(1), 2777–2785.
Francalanci, C., & Galal, H. (1998). Information technology and worker compensation: Determinants of productivity in the life insurance industry. MIS Quarterly, 22(2), 227–241.
Gartner (2013). Gartner identifies the top 10 strategic technology trends for 2013. Retrieved from http://www.gartner.com/newsroom/id/2209615.
Germann, F., Lilien, G. L., Fiedler, L., & Kraus, M. (2014). Do retailers benefit from deploying customer analytics? Journal of Retailing, 90(4), 587–593.
Han, J., Kamber, M., and Pei, J. (2011). Data mining: Concepts and techniques, 3rd Ed. Morgan Kaufman Publishers.
Hitt, L. M., & Brynjolfsson, E. (1996). Productivity, business profitability, and consumer surplus: Three different measures of information technology value. MIS Quarterly, 121–142.
Hitt, L. M., Wu, D. J., & Zhou, X. (2002). Investment in enterprise resource planning: Business impact and productivity measures. Journal of Management Information Systems, 19(1), 71–98.
Huang, C. K., Wang, T. W., & Tasi, Y. T. (2016). Market reactions to big data implementation announcements. In 20th Pacific Asia conference on information systems. Chiayi: Taiwan.
Kiron, D. (2013). Organizational alignment is key to big data success. MIT SloanManagement Review, 54(3), 1–6.
Kohli, R., & Devaraj, S. (2003). Measuring information technology payoff: A meta-analysis of structural variables in firm-level empirical research. Information Systems Research, 14(2), 127–145.
Lambrecht, A., and Tucker, C. E. (2015). Can big data protect a firm from competition? Available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2705530, retrieved on July 6th, 2018.
LaValle, S., Hopkins, M. S., Lesser, E., Shockley, R., & Kruschwitz, N. (2010). Analytics: The new path to value. MIT Sloan Management Review, 52(1), 1–25.
Le, S. A., Kroll, M. J., & Walters, B. A. (2013). Outside directors' experience, TMT firm-specific human capital, and firm performance in entrepreneurial IPO firms. Journal of Business Research, 66(4), 533–539.
Lee, B., & Barua, A. (1999). An integrated assessment of productivity and efficiency impacts of information technology investments: Old data, new analysis and evidence. Journal of Productivity Analysis, 12(1), 21–43.
Lieberman, M. B., & Montgomery, D. B. (1988). First-mover advantages. Strategic Management Journal, 9(S1), 41–58.
Loveman, G. W. (1994). An assessment of the productivity impact on information technologies. Information technology and the corporation of the 1990s: Research Studies, Allen, T. J. and M. S. Scott Morton (ed.), MIT Press, Cambridge, 84–110.
Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2011). Big data: The next frontier for innovation, competition and productivity. McKinsey global institute. Retrieved from http://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/big-data-the-next-frontier-for-innovation.
Mata, F. J., Fuerst, W. L., & Barney, J. B. (1995). Information technology and sustained competitive advantage: A resource-based analysis. MIS Quarterly, 19(4), 487–505.
Melville, N., Kraemer, K., & Gurbaxani, V. (2004). Review: Information technology and organizational performance: An integrative model of IT business value. MIS Quarterly, 28(2), 283–322.
NVP. (2016). Big data executive survey 2016. NewVantage Partners: Boston.
Piccoli, G., & Ives, B. (2005). IT-dependent strategic initiatives and sustained competitive advantage: A review and synthesis of the literature. MIS Quarterly, 29(4), 747–776.
Sabherwal, R., & Jeyaraj, A. (2015). Information technology impacts on firm performance: An extension of Kohli and Devaraj (2003). MIS Quarterly, 39(4), 809–836.
Sambamurthy, V., and Zmud, R. W. (1992). Managing IT for success: The empowering business partnership. Financial executives research foundation, Morristown.
Santos, B. L. D., & Peffers, K. (1995). Rewards to investors in innovative information technology applications: First movers and early followers in ATMs. Organization Science, 6(3), 241–259.
Santos, B. L. D., Peffers, K., & Mauer, D. C. (1993). The impact of information technology investment announcements on the market value of the firm. Information Systems Research, 4(1), 1–23.
Sharif, A. M., & Irani, Z. (2006). Exploring fuzzy cognitive mapping for IS evaluation: Aresearch note. European Journal of Operational Research, 173(3), 1175–1187.
Wade, M., & Hulland, J. (2004). The resource-based view and information systems research: Review, extension, and suggestions for future research. MIS Quarterly, 28(1), 107–142.
Wamba, S. F., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How ‘big data’can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165, 234–246.
Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J., Dubey, R., & Childe, S. J. (2017). Big data anlytics and firm performance: Effects of dyanmic capabilities. Journal of Business Research, 70, 356–365.
White, C. 2011. Using Big Data for Smarter Decisions. BI Research. ftp://public.dhe.ibm.com/software/pdf/ro/Using-Big-Data-Smarter-Decision-Making.pdf.
Whitehead, E. C. (2011). IT investment allocation and organizational performance: A study of information technology investment portfolios in federal government agencies, Ph.D. dissertation. In School of Engineering and Applied Sciences. Washington D.C: The George Washington University.
Yiu, C. (2012). The big data opportunity: Making government faster, smarter and more personal. Policy Exchange (London). Retrieved from https://policyexchange.org.uk/publication/the-big-data-opportunity-making-government-faster-smarter-and-more-personal/.
Acknowledgements
The authors are grateful to the participants’ comments from the AAA AIS Section mid-year meeting. The authors are also thankful to the financial support provided by National Chung Cheng University and DePaul University. This project is also funded by the Ministry of Science and Technology in Taiwan (MOST # 104-2410-H-194-088-MY2).
Author information
Authors and Affiliations
Corresponding author
Appendix
Appendix
Rights and permissions
About this article
Cite this article
Huang, CK., Wang, T. & Huang, TY. Initial Evidence on the Impact of Big Data Implementation on Firm Performance. Inf Syst Front 22, 475–487 (2020). https://doi.org/10.1007/s10796-018-9872-5
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10796-018-9872-5