Businessperson or Technologist: Stock Market Reaction to the Alignment between CIO Background and Firm Strategy

ABSTRACT

Chief Information Officers (CIOs) influence their firm’s strategy implementation and facilitate improved firm performance by effectively managing information technology (IT) resources. However, it remains unclear how firms select CIOs and how the stock market perceives the selection. We posit that firms’ preferences regarding CIO background (business acumen versus technical expertise) depend on their strategic positioning. Also, we argue that the stock market pays attention to the alignment between the appointed CIO’s background and firm strategy. To empirically examine this, we employ factor analysis on a sample of 1,287 CIOs with detailed biographic information on education, work experience, and certification to identify the CIO’s background. Utilizing these measures, we examine whether the appointed CIO’s background depends on the appointing firm’s strategic positioning in a normative model. Then, we use a predictive model to test the stock market reactions to CIO appointments. We document that cost-leadership-leaning firms are more likely to appoint a CIO with a stronger business-oriented background, while differentiation-leaning firms are more likely to appoint a CIO with a stronger technical-oriented background. Interestingly, firms with misaligned CIO appointments suffer a negative stock market reaction. We discuss theoretical and practical implications of selecting aligned versus misaligned CIOs.

KEYWORDS:

• Chief Information Officer
• CIO
• CIO appointment
• strategic positioning
• CIO background
• stock market reaction

Acknowledgments

We thank Keval Amin, Hilal Atasoy, Sudipta Basu, Chansog (Francis) Kim, Sunil Wattal, Zhifeng Yang, Hong You, colleagues at Stony Brook University, and participants at the 2017 Accounting PhD Seminar at Temple University, the 2015 Conference on Convergence of Financial and Managerial Accounting Research, the 2015 Research Seminar at Stony Brook University, the 2012 AAA Mid-Atlantic Region Meeting, the 2012 Management Accounting Section Meeting, the 2012 AAA Annual Meeting, the 2012 EMBA seminar at Singapore Management University, the 2011 Workshop on Information Systems and Economics, the 2011 Seminar at HEC Montréal, the 2011 MIS Board seminar, and the 2011 School-Wide Research Award at Temple University for their helpful comments.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

^1. The global worldwide IT spending has steadily been increasing was projected to be $4.1 trillion in 2021 earlier in that year [37]. The IT spending recovery after the dot-com bubble has sparked a new stream of technologies (e.g., artificial intelligence, blockchain, social media, mobile technology, and cloud computing), motivating firms to increase their IT budget and attract IT talent in order to remain competitive and to ensure growth.

^2. The U.S. Department of Labor estimates that the cost of a poor hiring decision is at least 30% of the individual’s first-year pay [72]. Considering the estimated median CIO pay of $208,750 in 2021 [74], hiring the wrong CIO can be quite costly. Indeed, among the top IT hiring mistakes is bringing someone on that lacks the proper skills for the job [85].

^3. See Appendix 1 for more discussion on this topic.

^4. As we develop our arguments, and for ease of exposition, we refer to firms as differentiators if they are closer to that end of the spectrum than cost leadership. Similarly, we refer to firms as cost leaders if they are closer to that end of the spectrum than they are to differentiation. However, we do not mean to suggest that “differentiators” (“cost leaders”) do not exhibit any degree of “cost leadership” (“differentiation”). A firm’s strategy could exhibit a varying degree of characteristics of both strategies. See Appendix 2 for more details on these two strategies.

^5. When replicating Chatterjee et al.’s [17] study using our CIO samples without considering CIO characteristics, we find no significant stock reactions to our CIO appointments (three-day [-1, 0, 1] cumulative abnormal stock returns = -0.006 with a p-value of 0.148).

^6. However, we are not suggesting that there is an “ideal CIO.” We argue that there must be a proper alignment between a firm’s needs and the background of the CIO being appointed.

^7. Prior CIO studies [8, 9, 17, 33, 54, 84] note that, despite being the highest IT executive, CIOs at different organizations carry various titles such as “Chief Information Officer,” “Chief Technology Officer,” “Senior Vice President of IT,” “VP of Information Systems,” and “Director of Technology.” We take advantage of Capital IQ’s unique classification by identifying CIOs by their job functions rather than job titles. This way, we attempt to ensure that our sample executives perform similar job functions as a CIO regardless which exact job title they may carry.

^8. Notably, in a 2020 CEO Council annual summit by the WSJ, Elon Musk decries business education and criticized business executives for focusing too much on financials and spreadsheets but too little on product development and innovation [87, 92].

^9. Although we pose our arguments by referencing cost leaders and differentiators pursuing business-oriented and technical-oriented CIOs for expositional simplicity, we acknowledge that most companies pursue a blend of the two strategies and tend to lean in one direction or the other. Accordingly, the type of CIO that they prefer will have a blend of backgrounds that optimally leans either toward business and/or technical, depending on the firm’s strategic positioning.

^10. We use Capital IQ’s unique classification of identifying CIOs by their job functions rather than job titles to ensure that our sample of executives perform their job functions as the highest IT executive, namely the CIO, regardless which exact job title they may carry. CIOs can carry various titles such as “Chief Information Officer”, “Chief Technology Officer”, “Senior Vice President of IT,” “VP of Information Systems,” and “Director of Technology” at different organizations, despite being the highest IT executive [8, 9, 17, 33, 54, 84]. We require CIOs to have available biographic data (used to construct our CIO type variables) and compensation data (used to validate their highest IT executive role within the firm). In addition, we exclude private firms and non-U.S. firms and require firms to exist in the Compustat database for firm-year-level financial information.

^11. If a CIO’s educational background is not provided by Capital IQ, we manually search for any missing educational background through publicly available sources, for example, corporate websites, proxies, and regulatory filings. CIOs whose educational information is not obtainable are excluded from our sample.

^12. Confounding events are identified as mergers and acquisitions, earnings announcements and change in board directors which occurred within [-2, 1] days of the CIO appointment [1].

^13. If a CIO appointment was announced on a non-trading day, we use the next business day as the announcement day when calculating cumulative abnormal returns. However, our results remain similar when excluding these announcements.

^14. A CIO is considered to have accounting and financial work experience if they have worked as CFO, Vice President of Finance, financial controller, investment banker, financial analyst, or any other major accounting and finance positions. A CIO is considered to have general business work experience if they have worked as chief operating officer or other similar executive-level general management roles.

^15. The technical certificates in our data include Professional Engineer and Chartered Engineer. They require formal engineering education and adequate work experience in engineering to be recognized. We record these certificates because they are commonly disclosed in CIOs’ public biographies along with educational information (without requiring proprietary access). There are other technical certificates, for example, ITIL; however, those are usually not disclosed publicly in CIO biographies from corporate websites and proxy statements (i.e., sources of Capital IQ database) or appointment announcement news, and cannot be looked up without knowing the certification number.

^16. The three variables AF, GB, and TC are not mutually exclusive. It is possible for a CIO to have a high value in more than one of them simultaneously, capturing a diverse CIO background.

^17. According to Bentley et al. [12], R&D over sales is chosen to capture the firm’s propensity to develop new products, employees over sales is to capture the firm’s ability to produce products, change in sales is to capture the firm’s growth or investment opportunity, marketing over sales is to capture the firm’s focus on exploiting new products, employee fluctuations is to capture organizational stability, and capital intensity the firm’s commitment to efficiency.

^18. When a CIO does not have general business or accounting/finance experience, the baseline includes CIOs with only technical-related work experience because all CIOs in our sample have technical work experience. Due to the specialized nature of the role of a CIO, we did not observe work experience falling outside of these categories to necessitate another experience classification for our sample.

^19. Since AUTOMATE is only used as the base variable in the regressions, we do not report its descriptive statistics in Table 1 Panel B.

^20. Contingency theory suggests that the predicted/expected outcome (which is the choice of CIO background in our study) derived from the normative model is considered the optimal choice and that the deviation from the optimal choice can be used to explain differential firm performance in a predictive model.

^21. The distribution of CIO appointments per year is reported in Appendix 4. Data is available upon request.

^22. We acknowledge that there are relatively fewer observations in early years of our sample period. Although we include year fixed effects in the model to control for potential unobservable factors related to the time period, to further validate our results, we focus on a more recent sample with years from 2003 to 2019 as a robustness check. We continue to find that our stock reaction results (untabulated) remain robust.

^23. Prior studies recommend the use of financial-market based measure, Tobin’s q, to evaluate the impact of increased IT capacity on firm performance due to its forward-looking character [13, 64, 65, 84]. This is particularly important in our study’s context because it may take years for the hiring of CIO to translate into other accounting-based performance measures, for example, return on assets.

^24. Data used to compute Tobin’s q are available at Compustat database.

Additional information

Notes on contributors

Rajiv D. Banker

Rajiv D. Banker ([email protected]) is the Merves Chair in Accounting and Information Technology at the Fox School of Business, Temple University. He received his doctorate in Business Administration from Harvard University. Dr. Banker is one of the most highly cited scholars in Accounting, Management, and Economics worldwide. He is recognized by the Institute for Scientific Information (Web of Science) as one of the most influential researchers in Economics and Business worldwide and has received numerous awards for his research, including several lifetime achievement awards. Dr. Banker has served as editor and on advisory boards of leading research journals in Accounting, Information Systems, and Operations Management.

Cecilia (Qian) Feng

Cecilia (Qian) Feng ([email protected]) is an assistant professor of accounting and director of MS in Accounting at the College of Business at Stony Brook University. She received her PhD in accounting from the Fox School of Business at Temple University. Dr. Feng’s research interests lie in the area of accounting information systems and include topics relating to IT leadership, the eXtensible business reporting language (XBRL) mandate, and information security breach incidents. She has received a teaching award at Stony Brook University. She has served as the session chair at various academic conferences.

Paul A. Pavlou

Paul A. Pavlou ([email protected]; corresponding author) is the Dean and Cullen Distinguished Chair Professor at C.T. Bauer College, University of Houston, and an expert on data analytics and digital business strategy. He earned his Ph.D. in Business Administration and a Master degree in Electrical Engineering from the University of Southern California. Dr. Pavlou’s research has been cited over 80,000 times; he was recognized among the “World’s Most Influential Scientific Minds” by Thomson Reuters, and was named an INFORMS Information Systems Society Distinguished Academic Fellow. Dr. Pavlou is a Senior Editor of Information Systems Research.