Are “Tech-Savvy” Owners Better for Business? Evidence From Major League Baseball

in Journal of Sport Management

Click name to view affiliation

Ted Hayduk IIIPreston Robert Tisch Institute for Global Sport, New York University, New York, NY, USA

Search for other papers by Ted Hayduk III in
Current site
Google Scholar
PubMedClose
*
DOI:
https://doi.org/10.1123/jsm.2021-0252
Keywords:
business intelligence; technology; operating margin; ownership; knowledge
First Published Online:
26 Mar 2022
In Print:
Volume 36: Issue 6
Page Range:
559–574
Restricted access

Business intelligence (BI) technologies can help firms optimize revenue and expenses if acquired and deployed proficiently. In parallel, the sport industry’s shift toward digitization is being driven by an influx of new, technology-savvy owners and managers. It follows that owners who are business intelligence experts could make their sport organizations more profitable. This paper models 14 years of Major League Baseball data to explore the degree to which owners with business intelligence career experience affect their organization’s operating margin through (a) optimizing revenue and (b) enhancing cost efficiency. It further explores owners’ knowledge accrual as a moderator in this process. Results suggest the effect of business intelligence expertise on margins is positive, but small. Margin increases were attained by spending more efficiently on labor, not by generating more revenue. These mediating effects were moderated by knowledge accrual, such that a longer tenure increased the early-tenure advantages of BI career experience.

  • Collapse
  • Expand

Journal of Sport Management

Cover Journal of Sport Management

  • Allison, P.D. (1999). Multiple regression: A primer. Pine Forge Press.

  • Ashrafi, A., Ravasan, A.Z., Trkman, P., & Afshari, S. (2019). The role of business analytics capabilities in bolstering firms’ agility and performance. International Journal of Information Management, 47(1), 1–15. https://doi.org/10.1016/j.ijinfomgt.2018.12.005

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Benaroch, M., & Kauffman, R.J. (2000). Justifying electronic banking network expansion using real options analysis. MIS Quarterly, 24(2),197–225. https://doi.org/10.2307/3250936

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Berri, D.J., Schmidt, M.B., & Brook, S.L. (2004). Stars at the gate: The impact of star power on NBA gate revenues. Journal of Sports Economics, 5(1), 33–50. https://doi.org/10.1177/1527002503254051

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bhandari, I., Colet, E., Parker, J., Pines, Z., Pratap, R., & Ramanujam, K. (1997). Advanced scout: Data mining and knowledge discovery in NBA data. Data Mining and Knowledge Discovery, 1(1), 121–125. https://doi.org/10.1023/A:1009782106822

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bharadwaj, A.S. (2000). A resource-based perspective on information technology capability and firm performance: An empirical investigation. MIS Quarterly, 24(1), 169–196. https://doi.org/10.2307/3250983

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bloom, M. (1999). The performance effects of pay dispersion on individuals and organizations. Academy of Management Journal, 42(1), 25–40.

    • Search Google Scholar
    • Export Citation

  • Bouzarth, E.L., Cromer, A.W., Fravel, W.J., Grannan, B.C., & Hutson, K.R. (2020). Dynamically scheduling NFL games to reduce strength of schedule variability. Journal of Sports Analytics, 6(4), 281–293. https://doi.org/10.3233/JSA-200428

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Can, H., Lu, M., & Gan, L. (2011). The research on application of information technology in sports stadiums. Physics Procedia, 22, 604–609. https://doi.org/10.1016/j.phpro.2011.11.093

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Canella, A.A., Park, J.H., & Lee, H.U. (2008). Top management team functional background diversity and firm performance: Examining the roles of franchise member collocation and environmental uncertainty. Academy of Management Journal, 51(4), 768–784. https://doi.org/10.5465/amr.2008.33665310

    • Search Google Scholar
    • Export Citation

  • Carpenter, M.A., Geletkanycz, M.A., & Sanders, W.G. (2004). Upper echelons research revisited: Antecedents, elements, and consequences of top management team composition. Journal of Management, 30(6), 749–778. https://doi.org/10.1016/j.jm.2004.06.001

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Carpenter, M.A., Sanders, W.G., & Gregersen, H.B. (2001). Bundling human capital with organizational context: The impact of international assignment experience on multinational firm performance and CEO pay. Academy of Management Journal, 44(3), 493–511. https://doi.org/10.5465/3069366

    • Search Google Scholar
    • Export Citation

  • Cennamo, C. (2018). Building the value of next-generation platforms: The paradox of diminishing returns. Journal of Management, 44(8), 3038–3069. https://doi.org/10.1177/0149206316658350

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Chatterjee, A., & Hambrick, D.C. (2007). It’s all about me: Narcissistic chief executive officers and their effects on company strategy and performance. Administrative Science Quarterly, 52(3), 351–386. https://doi.org/10.2189/asqu.52.3.351

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Chu, D.P., & Wang, C.W. (2019). Empirical study on relationship between sports analytics and success in regular season and postseason in Major League Baseball. Journal of Sports Analytics, 5(3), 205–222. https://doi.org/10.3233/JSA-190269

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Coates, D., & Harrison, T. (2005). Baseball strikes and the demand for attendance. Journal of Sports Economics, 6(3), 282–302. https://doi.org/10.1177/1527002504265993

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Constantinou, A.C., & Fenton, N.E. (2013). Determining the level of ability of football teams by dynamic ratings based on the relative discrepancies in scores between adversaries. Journal of Quantitative Analysis in Sports, 9(1), 37–50. https://doi.org/10.1515/jqas-2012-0036

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Daly-Grafstein, D., & Bornn, L. (2020). Using in-game shot trajectories to better understand defensive impact in the NBA. Journal of Sports Analytics, 6(4), 235–242. https://doi.org/10.3233/JSA-200400

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Davenport, T. (2014). Big data at work: Dispelling the myths, uncovering the opportunities. Harvard Business Review Press.

  • Dearborn, D.C., & Simon, H.A. (1958). Selective perception: A note on the departmental identifications of executives. Sociometry, 21(2), 140–144. https://doi.org/10.2307/2785898

    • Crossref
    • Search Google Scholar
    • Export Citation

  • El-Hodiri, M., & Quirk, J. (1971). An economic model of a professional sports league. Journal of Political Economy, 79(6), 1302–1319. https://doi.org/10.1086/259837

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Fort, R. (2015). Managerial objectives: A retrospective on utility maximization in pro team sports. Scottish Journal of Political Economy, 62(1), 75–89. https://doi.org/10.1111/sjpe.12061

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Fort, R., & Quirk, J. (1995). Cross-subsidization, incentives, and outcomes in professional team sports leagues. Journal of Economic Literature, 33(3), 1265–1299.

    • Search Google Scholar
    • Export Citation

  • García-Sánchez, E., García-Morales, V.J., & Bolívar-Ramos, M.T. (2017). The influence of top management support for ICTs on organisational performance through knowledge acquisition, transfer, and utilisation. Review of Managerial Science, 11(1), 19–51. https://doi.org/10.1007/s11846-015-0179-3

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Gratton, C., & Solberg, H.A. (2007). The economics of sports broadcasting. Routledge.

  • Grossmann, M., & Dietl, H. (2009). Investment behaviour in a two-period contest model. Journal of Institutional and Theoretical Economics, 165(3), 401–417. https://doi.org/10.1628/093245609789471998

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Grotta, A., & Bellocco, R. (2013). A review of mediation analysis in Stata: Principles, methods and applications [PDF documents]. Firenze: Italian Stata Users Group Meeting. https://www.stata.com/meeting/italy13/abstracts/materials/it13_grotta.pdf

    • Search Google Scholar
    • Export Citation

  • Gustafson, E., & Hadley, L. (2007). Revenue, population, and competitive balance in Major League Baseball. Contemporary Economic Policy, 25(2), 250–261.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hambrick, D.C., Cho, T.S., & Chen, M.J. (1996). The influence of top management team heterogeneity on firms’ competitive moves. Administrative Science Quarterly, 41(4), 659–684. https://doi.org/10.2307/2393871

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hambrick, D.C., & Mason, P.A. (1984). Upper echelons: The organization as a reflection of its top managers. Academy of Management Review, 9(2), 193–206. https://doi.org/10.2307/258434

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hausman, J.A. (1978). Specification tests in econometrics .Econometrica: Journal of the Econometric Society, 1251–1271.

  • Hayduk, T. (2021a). The impact of ownership political ideology on firm performance: Evidence from major league baseball (MLB) franchises. International Journal of Sport Policy and Politics, 13(1), 65–83. https://doi.org/10.1080/19406940.2020.1857423

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hayduk, T. (2021b). Owner–resident ideological divergence and firm performance: Evidence from major league baseball. Journal of Sport Management. Advance online publication. https://doi.org/10.1123/jsm.2020-0259

    • Search Google Scholar
    • Export Citation

  • Hayduk, T. (2020). Mega sport events as drivers of entrepreneurship: Bridging the gap between economics and psychology. International Journal of Entrepreneurship and Small Business. Advance online publication. https://doi.org/10.1504/IJESB.2020.10029494

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hayduk, T., & Walker, M. (2021). The effect of ownership marketing expertise on MLB attendance and digital consumption. Sport Marketing Quarterly, 30(1), 30–46. https://doi.org/10.32731/SMQ.301.032021.03

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hayes, A.F. (2009). Beyond baron and kenny: Statistical mediation analysis in the new millennium. Communication Monographs, 76(4), 408–420. https://doi.org/10.1080/03637750903310360

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hendricks, B., Howell, T., & Bingham, C. (2019). How much do top management teams matter in founder-led firms? Strategic Management Journal, 40(6), 959–986. https://doi.org/10.1002/smj.3006

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Huang, L.D., & Jia, J.J. (2014). Crowd disaster risk identification in large sport venues. In C. Chen, G. Li, Q. Shen, & B. Jiang (Eds.), Applied mechanics and materials (pp. 2125–2128). Scientific.net.

    • Search Google Scholar
    • Export Citation

  • Juravich, M., Salaga, S., & Babiak, K. (2017). Upper echelons in professional sport: The impact of NBA general managers on franchise performance. Journal of Sport Management, 31(5), 466–479. https://doi.org/10.1123/jsm.2017-0044

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kennedy, P. (2008). A guide to econometrics. John Wiley & Sons.

  • Késenne, S. (2006). The win maximization model reconsidered: Flexible talent supply and efficiency wages. Journal of Sports Economics, 7(4), 416–427. https://doi.org/10.1177/1527002505279347

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Lewis, M. (2004). Moneyball: The art of winning an unfair game. WW Norton & Company.

  • López-Muñoz, J.F., & Escribá-Esteve, A. (2017). An upper echelons perspective on information technology business value. European Research on Management and Business Economics, 23(3), 173–181. https://doi.org/10.1016/j.iedeen.2017.02.003

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ma-Kellams, C., Or, F., Baek, J.H., & Kawachi, I. (2016). Rethinking suicide surveillance: Google search data and self-reported suicidality differentially estimate completed suicide risk. Clinical Psychological Science, 4(3), 480–484. https://doi.org/10.1177/2167702615593475

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Manage, A.B., Kafle, R.C., & Wijekularathna, D.K. (2020). Classification of all-rounders in limited over cricket-a machine learning approach. Journal of Sports Analytics, 6(4), 295–306. https://doi.org/10.3233/JSA-200467

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Mills, B., & Fort, R. (2014). League-level attendance and outcome uncertainty in US pro sports leagues. Economic Inquiry, 52(1), 205–218. https://doi.org/10.1111/ecin.12037

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Mithas, S., & Rust, R.T. (2016). How information technology strategy and investments influence firm performance: Conjecture and empirical evidence. Mis Quarterly, 40(1), 223–245. https://doi.org/10.25300/MISQ/2016/40.1.10

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Mithas, S., Tafti, A., Bardhan, I., & Goh, J.M. (2012). Information technology and firm operating margin: Mechanisms and empirical evidence. Mis Quarterly, 36(1), 205–224. https://doi.org/10.2307/41410414

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Mithas, S., Whitaker, J., & Tafti, A. (2017). Information technology, revenues, and profits: Exploring the role of foreign and domestic operations. Information Systems Research, 28(2), 430–444. https://doi.org/10.1287/isre.2017.0689

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Morgulev, E., Azar, O.H., & Lidor, R. (2018). Sports analytics and the big-data era. International Journal of Data Science and Analytics, 5(4), 213–222. https://doi.org/10.1007/s41060-017-0093-7

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Moura, P. (2015). It’s baseball meets ‘Shark Tank’: Dodgers looking to invest in start-ups. Orange County Register .https://www.ocregister.com/2015/04/22/its-baseball-meets-shark-tank-dodgers-looking-to-invest-in-start-ups/

    • Search Google Scholar
    • Export Citation

  • Mumcu, C., & Fried, G. (2017). Analytics in sport marketing. Sport Management Education Journal, 11(2), 102–105. https://doi.org/10.1123/smej.2016-0019

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Nadkarni, S., & Herrmann, P.O.L. (2010). CEO personality, strategic flexibility, and firm performance: The case of the Indian business process outsourcing industry. Academy of Management Journal, 53(5), 1050–1073. https://doi.org/10.5465/amj.2010.54533196

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Nuti, S.V., Wayda, B., Ranasinghe, I., Wang, S., Dreyer, R.P., Chen, S.I., & Murugiah, K. (2014). The use of Google trends in health care research: A systematic review. PloS One, 9(10), Article e109583. https://doi.org/10.1371/journal.pone.0109583

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ozanian, M., & Settimi, C. (2021). The NFL’s Most Valuable Teams 2021: Average team value soars to $3.5 Billion as league shrugs off pandemic year. Forbes. https://www.forbes.com/sites/mikeozanian/2021/08/05/the-nfls-most-valuable-teams-2021-average-team-value-soars-to-35-billion-as-league-shrugs-off-pandemic-year/?sh=73ce52d1654e

    • Search Google Scholar
    • Export Citation

  • Peeters, T.L., Salaga, S., & Juravich, M. (2020). Matching and winning? The impact of upper and middle managers on firm performance in Major League Baseball. Management Science, 66(6), 2735–2751. https://doi.org/10.1287/mnsc.2019.3323

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Potts, J., & Ratten, V. (2016). Sports innovation: Introduction to the special section. Innovation, 18(3), 233–237. https://doi.org/10.1080/14479338.2016.1241154

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Preacher, K.J., Rucker, D.D., & Hayes, A.F. (2007). Assessing moderated mediation hypotheses: Theory, method, and prescriptions. Multivariate Behavioral Research, 42(1), 185–227. https://doi.org/10.1080/00273170701341316

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Quinn, J.B., & Baily, M.N. (1994). Information technology: Increasing productivity in services. Academy of Management Perspectives, 8(3), 28–48. https://doi.org/10.5465/ame.1994.9503101167

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ratten, V. (2011). Sport-based entrepreneurship: Towards a new theory of entrepreneurship and sport management. International Entrepreneurship and Management Journal, 7(1), 57–69. https://doi.org/10.1007/s11365-010-0138-z

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ray, S., & Roychowdhury, S. (2021). Cricket mix optimization using heuristic framework after ensuring Markovian equilibrium. Journal of Sports Analytics, 7(3), 155–168. https://doi.org/10.3233/JSA-200479

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Scelles, N., Helleu, B., Durand, C., & Bonnal, L. (2016). Professional sports firm values: Bringing new determinants to the foreground? A study of European soccer, 2005-2013. Journal of Sports Economics, 17(7), 688–715. https://doi.org/10.1177/1527002514538976

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Shapiro, S.L., & Drayer, J. (2014). An examination of dynamic ticket pricing and secondary market price determinants in Major League Baseball. Sport Management Review, 17(2), 145–159. https://doi.org/10.1016/j.smr.2013.05.002

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Sloane, P.J. (1971). The Economics of Professional Football: The football club as a utility maximiser. Scottish Journal of Political Economy, 18(2), 121–146. https://doi.org/10.1111/j.1467-9485.1971.tb00979.x

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Stephens-Davidowitz, S. (2014). The cost of racial animus on a black candidate: Evidence using Google search data. Journal of Public Economics, 118, 26–40. https://doi.org/10.1016/j.jpubeco.2014.04.010

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Stinson, S. (2017). Is Kris Russell valuable or terrible? Long after Moneyball, skeptics and ‘nerds’ are still fighting about analytics. National Post. https://nationalpost.com/sports/long-after-moneyball-skeptics-and-nerds-are-still-fighting-about-analytics

    • Search Google Scholar
    • Export Citation

  • Taylor, J.S., de Lourdes Machado, M., & Peterson, M.W. (2008). Leadership and strategic management: Keys to institutional priorities and planning. European Journal of Education, 43(3), 369–386. https://doi.org/10.1111/j.1465-3435.2008.00363.x

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Terrien, M., Scelles, N., Morrow, S., Maltese, L., & Durand, C. (2017). The win/profit maximization debate: Strategic adaptation as the answer? Sport, Business and Management: An International Journal, 7(2), 121–140. https://doi.org/10.1108/SBM-10-2016-0064

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Terza, J.V., Basu, A., & Rathouz, P.J. (2008). Two-stage residual inclusion estimation: Addressing endogeneity in health econometric modeling. Journal of Health Economics, 27(3), 531–543. https://doi.org/10.1016/j.jhealeco.2007.09.009

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Tippins, M.J., & Sohi, R.S. (2003). IT competency and firm performance: Is organizational learning a missing link? Strategic Management Journal, 24(8), 745–761. https://doi.org/10.1002/smj.337

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Treber, J., Mulcahy, L., & Sharma, M.B. (2018). Empty seats or empty threats? Examining the effects of the 1994-1995 and 2004-2005 lockouts on attendance and revenue in the National Hockey League. Journal of Sports Economics, 19(5), 677–695. https://doi.org/10.1177/1527002516672058

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wang, G., Holmes, Jr, R.M., Oh, I.S., & Zhu, W. (2016). Do CEOs matter to firm strategic actions and firm performance? A meta‐analytic investigation based on upper echelons theory. Personnel Psychology, 69(4), 775–862.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Watanabe, N.M., & Cunningham, G.B. (2020). The impact of race relations on NFL attendance: An econometric analysis. Plos One, 15(1). Article 0226938. https://doi.org/10.1371/journal.pone.0226938

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wiersema, M.F., & Bantel, K.A. (1993). Top management team turnover as an adaptation mechanism: The role of the environment. Strategic Management Journal, 14(7), 485–504. https://doi.org/10.1002/smj.4250140702

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wilkens, S. (2021). Sports prediction and betting models in the machine learning age: The case of tennis. Journal of Sports Analytics, 7(2), 99–117. https://doi.org/10.3233/JSA-200463

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wolf, S., Schmitt, M., & Schuller, B. (2020). A football player rating system. Journal of Sports Analytics, 6(4), 243–257. https://doi.org/10.3233/JSA-200411

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wolfe, R.A., Weick, K.E., Usher, J.M., Terborg, J.R., Poppo, L., Murrell, A.J., Dukerich, J.M., Core, D.C., Dickson, K.E., & Jourdan, J.S. (2005). Sport and organizational studies. Journal of Management Inquiry, 14(2), 182–210. https://doi.org/10.1177/1056492605275245

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wolfers, J. (2006). Point shaving: Corruption in NCAA basketball. American Economic Review, 96(2), 279–283. https://doi.org/10.1257/000282806777211757

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wooldridge, J.M. (2002). Econometric analysis of cross section and panel data (2nd ed.). MIT Press.

  • Zhang, Y., & Wiersema, M.F. (2009). Stock market reaction to CEO certification: The signaling role of CEO background. Strategic Management Journal, 30(7), 693–710. https://doi.org/10.1002/smj.772

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 1290 1122 145
Full Text Views 119 100 13
PDF Downloads 139 117 10