Abstract
As artificial intelligence (AI) has recently gained momentum and attention, the interest and investment in AI have also accelerated. However, the impact of AI on firm value is rarely discussed. On the basis of the 119 announcements of 62 listed firms who have invested in AI, this study finds that AI investment has a negative impact on the firms’ market value. The stock prices of the firms decrease by 1.77% on the day of the announcement. Nonmanufacturing firms and firms with weak information technology capabilities or low credit ratings suffer a more negative impact compared with other firms. The findings suggest that investors perceive AI investment announcements to be unwelcome news for the majority of firms. Subsequently, the characteristics affecting the shareholders’ reaction towards AI adoption are presented. This research offers one of the first empirical evidence about the market value of AI and provides a reference for firms interested in investing in AI.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Aouadni, I., & Rebai, A. (2017). Decision support system based on genetic algorithm and multi-criteria satisfaction analysis (MUSA) method for measuring job satisfaction. Annals of Operations Research, 256(1), 3–20.
Bannerjee, G., Sarkar, U., Das, S., & Ghosh, I. (2018). Artificial intelligence in agriculture: A literature survey. International Journal of Scientific Research in Computer Science Applications and Management Studies, 7(3), 1–6.
Basri, W. (2020). Examining the impact of artificial intelligence (AI)-assisted social media marketing on the performance of small and medium enterprises: toward effective business management in the Saudi Arabian context. International Journal of Computational Intelligence Systems, 13(1), 142–152.
Benotsmane, R., Kovács, G., & Dudás, L. (2019). Economic, social impacts and operation of smart factories in industry 4.0 focusing on simulation and artificial intelligence of collaborating robots. Social Sciences, 8(5), 143.
Bharadwaj, A. S. (2000). A resource-based perspective on information technology capability and firm performance: an empirical investigation. MIS Quarterly, 24(1), 169–196.
Bose, I., & Leung, A. C. M. (2013). The impact of adoption of identity theft countermeasures on firm value. Decision Support Systems, 55(3), 753–763.
Bose, I., & Leung, A. C. M. (2014). Do phishing alerts impact global corporations? A firm value analysis. Decision Support Systems, 64, 67–78.
Bose, I., Lui, A. K. H., & Ngai, E. W. T. (2011). The impact of RFID adoption on the market value of firms: An empirical analysis. Journal of Organizational Computing and Electronic Commerce, 21(4), 268–294.
Bose, I., & Pal, R. (2012). Do green supply chain management initiatives impact stock prices of firms? Decision Support Systems, 52(3), 624–634.
Bughin, J., Seong, J., Manyika, J., Chui, M., & Joshi, R. (2018). Notes from the AI frontier: Modeling the impact of AI on the world economy. McKinsey Global Institute.
Castellano, R., & D’Ecclesia, R. L. (2013). CDS volatility: The key signal of credit quality. Annals of Operations Research, 205(1), 89–107.
Castellanos, S. (2018). Bank of America tech chief defines responsible AI projects. The Wall Street Journal Retrieved July 3, 2020 from https://blogs.wsj.com/cio/2018/12/05/bank-of-america-tech-chief-defines-responsible-ai-projects/.
Chatterjee, D., Pacini, C., & Sambamurthy, V. (2002). The shareholder-wealth and trading-volume effects of information-technology infrastructure investments. Journal of Management Information Systems, 19(2), 7–42.
Chen, T.-L., Cheng, C.-Y., & Chou, Y.-H. (2020). Multi-objective genetic algorithm for energy-efficient hybrid flow shop scheduling with lot streaming. Annals of Operations Research, 290, 813–836.
Chetthamrongchai, P., & Jermsittiparsert, K. (2020). The impact of artificial intelligence outcomes on the performance of pharmacy business in Thailand. Systematic Reviews in Pharmacy, 11(1), 139–148.
Chou, J.-S., Tai, Y., & Chang, L.-J. (2010). Predicting the development cost of TFT-LCD manufacturing equipment with artificial intelligence models. International Journal of Production Economics, 128(1), 339–350.
Chui, M., Henke, N., & Miremadi, M. (2018). Most of AI’s business uses will be in two areas. Retrieved July 3, 2020 from https://hbr.org/2018/07/most-of-ais-business-uses-will-be-in-two-areas.
Dardan, M., Stylianou, A., & Dardan, S. (2005). The valuation of eCommerce announcements during fluctuating financial markets. Journal of Electronic Commerce Research, 6(4), 312–326.
Dehning, B., Richardson, V. J., & Zmud, R. W. (2003). The value relevance of announcements of transformational information technology investments. MIS Quarterly, 27(4), 637–656.
Do, N. A. D., Nielsen, I. E., Chen, G., & Nielsen, P. (2016). A simulation-based genetic algorithm approach for reducing emissions from import container pick-up operation at container terminal. Annals of Operations Research, 242(2), 285–301.
Dos Santos, B. L., 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.
Dosdoğru, A. T., Boru İpek, A., & Göçken, M. (2020). A novel hybrid artificial intelligence-based decision support framework to predict lead time. International Journal of Logistics Research and Applications. https://doi.org/10.1080/13675567.2020.1749249.
Faggella, D. (2019). How investors feel about artificial intelligence—From 29 AI founders and executives. Retrieved May 14, 2020 from https://emerj.com/ai-market-research/how-investors-feel-about-artificial-intelligence-from-29-ai-founders-and-executives/.
Fan, W., Liu, J., Zhu, S., & Pardalos, P. M. (2020). Investigating the impacting factors for the healthcare professionals to adopt artificial intelligence-based medical diagnosis support system (AIMDSS). Annals of Operations Research, 294, 567–592.
Fethi, M. D., & Pasiouras, F. (2010). Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey. European Journal of Operational Research, 204(2), 189–198.
Fragapane, G., Ivanov, D., Peron, M., Sgarbossa, F., & Strandhagen, J. O. (2020). Increasing flexibility and productivity in Industry 4.0 production networks with autonomous mobile robots and smart intralogistics. Annals of Operations Research. https://doi.org/10.1007/s10479-020-03526-7.
Hayes, D. C., Hunton, J. E., & Reck, J. L. (2001). Market reactions to ERP implementation announcements. Journal of Information Systems, 15(1), 3–18.
Hunter, S. D. (2003). Information technology, organizational learning, and the market value of the firm. Journal of Information Technology Theory and Application, 5(1), 1–28.
Im, K. S., Dow, K. E., & Grover, V. (2001). A reexamination of IT investment and the market value of the firm—An event study methodology. Information Systems Research, 12(1), 103–117.
Jain, V. (2019). An impact of artificial intelligence on business. International Journal of Research and Analytical Reviews, 6(2), 302–308.
Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., et al. (2017). Artificial intelligence in healthcare: Past, present and future. Stroke and Vascular Neurology, 2(4), 230–243.
Joyce, L. (2018). Artificial intelligence and the banking industry’s $1 trillion opportunity. Retrieved Jun 4, 2020 from https://thefinancialbrand.com/72653/artificial-intelligence-trends-banking-industry/.
Kalayci, C. B., Polat, O., & Gupta, S. M. (2016). A hybrid genetic algorithm for sequence-dependent disassembly line balancing problem. Annals of Operations Research, 242(2), 321–354.
Karimi, J., Somers, T. M., & Bhattacherjee, A. (2007). The role of information systems resources in ERP capability building and business process outcomes. Journal of Management Information Systems, 24(2), 221–260.
Kobbacy, K. A., & Vadera, S. (2011). A survey of AI in operations management from 2005 to 2009. Journal of Manufacturing Technology Management, 22(6), 706–733.
Kobbacy, K. A., Vadera, S., & Rasmy, M. H. (2007). AI and OR in management of operations: history and trends. Journal of the Operational Research Society, 58(1), 10–28.
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.
Lam, H. K., Zhan, Y., Zhang, M., Wang, Y., & Lyons, A. (2019). The effect of supply chain finance initiatives on the market value of service providers. International Journal of Production Economics, 216, 227–238.
Lawrynowicz, A. (2011). Advanced scheduling with genetic algorithms in supply networks. Journal of Manufacturing Technology Management, 22(6), 748–769.
Lim, J.-H., Stratopoulos, T. C., & Wirjanto, T. S. (2013). Sustainability of a firm’s reputation for information technology capability: The role of senior IT executives. Journal of Management Information Systems, 30(1), 57–96.
Lu, Y., & Ramamurthy, K. (2011). Understanding the link between information technology capability and organizational agility: An empirical examination. MIS Quarterly, 35(4), 931–954.
Makridakis, S. (2017). The forthcoming artificial intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46–60.
Marr, B. (2019). The 10 best examples of how companies use artificial intelligence in practice. Retrieved Jun 3, 2020 from https://www.forbes.com/sites/bernardmarr/2019/12/09/the-10-best-examples-of-how-companies-use-artificial-intelligence-in-practice/#5591731a7978.
McNaught, K., & Chan, A. (2011). Bayesian networks in manufacturing. Journal of Manufacturing Technology Management, 22(6), 734–747.
Minevich, M. (2020). 4 Ways that you can prove ROI from AI. Retrieved May 15, 2020 from https://www.forbes.com/sites/markminevich/2020/03/03/4-ways-that-you-can-prove-roi-from-ai/#208b5fa784a7.
Mueller, J. P., & Massaron, L. (2018). Artificial intelligence for dummies. Hoboken: Wiley.
Muhanna, W. A., & Stoel, M. D. (2010). How do investors value IT? An empirical investigation of the value relevance of IT capability and IT spending across industries. Journal of Information Systems, 24(1), 43–66.
Munguia, J., Lloveras, J., Llorens, S., & Laoui, T. (2010). Development of an AI-based rapid manufacturing advice system. International Journal of Production Research, 48(8), 2261–2278.
Murry, A. (2017). Fortune 500 CEOs see A.I. As a big challenge. Retrieved May 18, 2020 from https://fortune.com/2017/06/08/fortune-500-ceos-survey-ai/.
Oh, W., Kim, J. W., & Richardson, V. J. (2006). The moderating effect of context on the market reaction to IT investments. Journal of Information Systems, 20(1), 19–44.
Ranganathan, C., & Brown, C. V. (2006). ERP investments and the market value of firms: Toward an understanding of influential ERP project variables. Information Systems Research, 17(2), 145–161.
Ross, J. W., Beath, C. M., & Goodhue, D. L. (1996). Develop long-term competitiveness through IT assets. Sloan Management Review, 38(1), 31–42.
Sohal, A. S., Moss, S., & Ng, L. (2001). Comparing IT success in manufacturing and service industries. International Journal of Operations & Production Management, 21(1/2), 30–45.
Statista. (2016). Enterprise artificial intelligence market revenue worldwide 2016–2025. Retrieved May 18, 2020 from https://www.statista.com/statistics/607612/worldwide-artificial-intelligence-for-enterprise-applications/.
Staw, B. M., Sandelands, L. E., & Dutton, J. E. (1981). Threat rigidity effects in organizational behavior: A multilevel analysis. Administrative Science Quarterly, 26(4), 501–524.
Stoel, M. D., & Muhanna, W. A. (2009). IT capabilities and firm performance: A contingency analysis of the role of industry and IT capability type. Information & Management, 46(3), 181–189.
Subramani, M., & Walden, E. (2001). The Impact of e-Commerce announcements on the market value of firms. Information Systems Research, 12(2), 135–154.
Tanriverdi, H., & Ruefli, T. W. (2004). The role of information technology in risk/return relations of firms. Journal of the Association for Information Systems, 5(11–12), 421–447.
Teo, T. S., Nishant, R., & Koh, P. B. (2016). Do shareholders favor business analytics announcements? The Journal of Strategic Information Systems, 25(4), 259–276.
White, L. J. (2010). Markets: The credit rating agencies. Journal of Economic Perspectives, 24(2), 211–226.
Yang, L., Chen, G., Rytter, N. G. M., Zhao, J., & Yang, D. (2019). A genetic algorithm-based grey-box model for ship fuel consumption prediction towards sustainable shipping. Annals of Operations Research. https://doi.org/10.1007/s10479-019-03183-5.
Acknowledgements
The authors are grateful for the constructive comments of the guest editor and referees on an earlier version of this paper.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Lui, A.K.H., Lee, M.C.M. & Ngai, E.W.T. Impact of artificial intelligence investment on firm value. Ann Oper Res 308, 373–388 (2022). https://doi.org/10.1007/s10479-020-03862-8
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10479-020-03862-8