THE TOBIN Q AS A COMPANY PERFORMANCE INDICATOR Developments in Business Simulation and Experiential Learning, Volume 30, 2003 THE TOBIN q AS A COMPANY PERFORMANCE INDICATOR Joseph Wolfe Experiential Adventures Jwolfe8125@aol.com Antonio Carlos Aidar Sauaia Universidade De Sao Paulo ABSTRACT Various economic indicators of a business game com- pany's performance exist. The Tobin q was examined as an indicator of the firm's effectiveness from an investment per- spective across a variety of top management games. The Tobin q was also compared to the Altman Z as another indi- cator of the firm's economic viability. The q was inconsis- tently related to each game's own performance indicator across games and may be contextual regarding its applica- bility due to game complexity and player skill level consid- erations. Students playing a business game typically want to know how well they are doing. This is a natural outcome of the competitive environments created by the simulations themselves while serving to reinforce the "business ethic" of accountability and the results by which the players will be judged in their business careers. Although there have been a number of diverse recommendations as to what should be measured all games feature economic performance meas- ures in either partial or global forms. This paper investi- gates the use of Tobin's q as a more-meaningful way to judge the comparative performance of firms in business games. The results were inconclusive and indicate further investigation would be useful. Background Top management or total enterprise (TE) business games attempt to replicate the salient features of the deci- sion-making environment faced by the firm's strategic deci- sion-makers. “A total enterprise game is a term used to refer to games that include all of the main functions of business as decisions inputs– marketing, production and finance” (Keys, 1987). Therefore the company effectiveness meas- ures used in those games report ultimate or penultimate measures which indicate either the firm's overall effective- ness or preliminary or interim measures that have empiri- cally shown their ability to indicate the firm's ultimate eco- nomic success. A review of five top management games simulating international markets in Exhibit 1 indicates all used profits or net earnings as a measure as well as the firm's stock price, or the valuation the simulated stock mar- ket placed on the firm's performance. Other common indi- cators were total sales revenue, earnings-per-share and rates-of-return on assets and equity. Four of the five games reported a summary or ultimate firm performance measure that was a weighted combination of the simulation's previ- ously generated penultimate criteria. There is a fair degree of unanimity regarding four of the criteria. There also is, however, a great deal of disagree- ment regarding what indicates company success, or what performance results playing teams should attempt to opti- mize. The Business Strategy Game (Thompson & Stappen- beck, 1998) outputs a unique Strategy Rating that reflects the relative "power" of the firm's strategy. The Multina- tional Management Game (Keys & Wells, 1997) uses the singular criteria of Quality, Return on Sales and Debt to Total Assets. These performance measures account for 33.3% of the firm's total performance score in addition to its more-standard Stock Price and Return-on-Equity yardsticks. Given both agreement and disagreement regarding the measurement standards that should be employed to judge and guide performance in a business game it is unfortunate that only limited attempts have been made to either generate the proper evaluation criteria or to assign appropriate weights to whatever penultimate criteria were chosen by game designers. Sackson (1990) performed a cluster analy- sis on player decisions and performance outcomes within The Business Strategy and Policy Game (Eldridge & Bates, 1984). It was found that product price, salesman salaries, production worker wage rates, sales training budgets and weekly labor hours generated influenced the game's out- comes of productivity, earnings per share, stock price and market share. Thus, in this case the latter indicate a com- pany's penultimate effectiveness criteria within the simula- tion tested. One year later Wheatley, Amin, Maddox and VanderLinde (1991) collected results produced by 142 MBA students playing The Carnegie Tech Management Game (Winters, Kuehn, Dill & Cohen, 1964). They deter- mined the prime indicators of a firm's success were its rates- 155 mailto:Jwolfe8125@aol.com Developments in Business Simulation and Experiential Learning, Volume 30, 2003 of-return on assets and equity followed by total sales and net income plus market share growth. The search for an additional or supplemental measure of a firm's success was pioneered by Biggs, Levin and Biggs (1995). Their examination probed the properties of the Altman Z (Altman, 1968; Altman, 1983) when applied to Micromatic (Scott & Strickland, 1992). For real-world manufacturing firms the Altman Z-score is a strong indica- tor of a firm's financial viability. Firms scoring below 1.81 are assured of bankruptcy, those scoring above 2.99 are safe and those scoring in the 1.81 and 2.99 range are in the "grey area". These companies require further analysis to deter- mine their ability to remain solvent. After finding the Altman Z applicable to this game the authors suggested Exhibit 1 Business Game Performance Criteria Criterion BPG MMG BSG CAP GBG Total Stock Price X X X X X 100% Return on Equity X X X X X 100% Return on Assets X X X X 80% Profits X X X 60% Market Share X X X 60% Sales X X 40% Return on Sales X X 40% EPS X X 40% Assets X 20% Inventory Turnover X 20% Assets Turnover X 20% Dividend/Share 20% Credit Rating X 20% Strategy Rating X 20% Debt Ratio X 20% Equity X 20% Summary X X X X 80% Total 10 9 7 5 6 100% BPG—The Business Policy Game– Cotter and Fritzsche, 1986 MMG—The Multinational Management Game– Keys, Edge and Wells, 1992 BSG—The Business Strategy Game– Thompson & Stappenbeck, 1999 CAP—CAPSTONE– Management Simulations, 2002 GBG—The Global Business Game– Wolfe, 2000 three uses of the Z-score if bankruptcy was indicated—the call for a personal intervention by the instructor, the firm's implementation of the strategic choices either of bank- ruptcy, reorganization or liquidation, or as a single-point company performance measure. Since they introduced the Altman Z to the business gaming literature, it has been added as an evaluation criterion in The Business Strategy Game (Thompson & Stappenbeck, 1999). Most recently Sauaia & Castro Junior (2001) examined the Tobin q as a measure of a company's performance in The Multinational Management Game (Keys & Wells, 1997). In that study it was found that high performing firms, as measured by the game's own performance routine, had high Tobin qs after ten rounds of play. Based on this the authors indicated the q statistic possessed predictive validity and its value should be investigated when applied to other business games. The Tobin q The Tobin q has been employed particularly by manu- facturing firms to explain a number of diverse corporate phenomena. These have entailed (a) cross-sectional differ- ences in investment and diversification decisions, (b) the relationship between managerial equity ownership and firm value, (c) the relationship between managerial performance and tender offer gains, investment opportunities and tender offer responses, and (d) financing, dividend, and compensat- ing policies (Chung and Pruitt, 1994). It is a statistic that might serve as a proxy for the firm's value from an inves- tor's perspective. By definition, it is the ratio between the market value of the firm's assets and the replacement value of those assets calculated as follows: 156 Developments in Business Simulation and Experiential Learning, Volume 30, 2003 q = (MVS + MVD)/RVA TA = Firm's assets, i.e. cash, receivables, inventory and plant book value Where: D = Debt defined as: MVS = Market value of all outstanding stock D = (AVCL – AVCA) + AVLTD MVD = Market value of all debt RVA = Replacement value of all production capacity Where: Firms with high qs, or qs > 1.00, have been found to be better investment opportunities (Lang, Stulz & Walkling, 1989), have higher growth potential (Tobin & Brainard, 1968; Tobin, 1969) and indicate management has performed well with the assets under its command (Lang, Stulz & Walkling, 1989). Given this has been found true for real- world firms the ability to apply Tobin's q, as either an ancil- lary or ultimate indicator of firm success in a business game, would be of real value. This paper's following section ex- amines the Tobin q as a single measure of a firm's summary performance, as a predictor of that summary performance and how it relates to the Altman Z as another indicator of a firm's success or failure in a business gaming environment. AVCL = Accounting value of the firm's Current Liabilities = Short Term Debt + Taxes Payable AVLTD = Accounting value of the firm's Long Term debt = Long Term Debt AVCA = Accounting value of the firm's Current Assets = Cash + Inventories + Receivables The Altman Z was used in this study as defined in its origi- nal presentation (Altman, 1983): Z = 1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + 1.0X5 Where: Methodology X1 = Working capital divided by total assets X2 = Retained earnings divided by total assets X3 = Earnings before interest and taxes divided by total as- sets The results for one industry were obtained from experi- enced users of five general business or top management games. The raw data were recorded for each game's mid- period or quarter and it's end-period or quarter. Thus, if the game ran for eight quarters the data points were the fourth and eighth periods. If the game ran for an odd number of periods the game's mid-point was chosen by the following formula: X4 = Market value of equity divided by book value of total debt X5 = Total revenues divided by total assets When the game produced summary company perform- ance measures those measures were compared to their Tobin qs. This was done to test the degree the q could act as a proxy or substitute for the game's own performance meas- ure. The Tobin q's forecasting ability was tested by compar- ing each firm's mid-point q to its end-point q. Finally, firm Z-scores and qs were compared to determine whether the Z- score's implications regarding solvency and bankruptcy were corroborated by the qs generated. The Spearman rank correlation test was performed in all cases due to the small number of firms involved in each industry and the belief that each firm's relative performance was more important than its absolute performance. MP = (P – 1)/2 Where: MP = the game's Midpoint P = Total periods of play Based on this formula an eleven decision period game's midpoint would be the fifth period A modified version of the Tobin q by Chung & Pruitt (1994) was used for consistency between the games Be- cause of their simplified balance sheets. This modified ver- sion closely approximates Tobin's original statistic and pro- duces a 96.6% approximation of the original formulation used by Lindenberg & Ross (1981): Results The results presented in Exhibit 2 indicate the Tobin q's performance varies quite widely across the four simulations that generate performance scores for their players. The q is strongly related to the performance scores generated by The Business Policy Game and The Business Strategy Game. It is moderately related to the Performance Index found in The Global Business Game. Almost the same amount of varia- tion in the performance score generated by The Multina- tional Management Game is explained by the Tobin q but in the opposite direction. The Altman Z, as another financial indicator, also varies across the four simulations. It is q = (MVS + D)/TA Where: MVS = Market value of all outstanding shares, i.e. the firm's Stock Price * Outstanding Shares 157 Developments in Business Simulation and Experiential Learning, Volume 30, 2003 strongly related to the performance scores found in BPG and MMG while almost no variance in game performance scores in BSG and GBG are explained by the Altman Z. When compared to each other the Tobin q and the Altman Z is moderately to strongly related to each other within the BPG, GBG and MMG games while basically absent within the BSG's context. Exhibit 2 End-Game Correlations Between Performance Scores, Tobin qs and Altman Zs Comparison BPG BSG GBG MMG Tobin q vs. Performance Score .829 .854 .571 -.543 Altman Z vs. Performance Score .829 .117 -.071 .886 Tobin q vs. Altman Z .829 .100 .429 -.429 The material presented in Exhibit 3 indicates the Tobin q is a relatively strong predictor of a company's perform- ance and earnings within The Business Policy Game. It is a moderate predictor of company performance for The Busi- ness Strategy Game but an even stronger predictor in the opposite direction when used with The Global Business Game. The ability to forecast company profits is negligible, or is in the opposite direction, for all five simulations exam- ined. The Tobin q's relationship to itself over a game's run is often strong but sometimes in the opposite direction. Exhibit 3 Mid-Game Tobin qs vs. Alternative End-Game Results Comparison CAP BPG BSG GBG MMG Mid-Game Tobin q vs. Performance Score n.a. .886 .550 -.690 .257 Mid-Game Tobin q vs. Total Earnings -.600 .771 .176 -.738 -.086 Mid-Game Tobin q vs. End-Game Tobin q -.700 .771 .276 -.405 -.200 Discussion It appears the Tobin q could be used as a diagnostic tool and predictor of company success when applied to The Business Policy Game. As a diagnostic tool, firms with low qs might be considered candidates for instructor-led coach- ing or counseling. In practice, the q is sensitive to the swing effects of its equation's denominator, i.e. the firm's total assets of cash, receivables, inventory and plant book value. If players can be shown how to be more efficient in their use of cash, how to produce better forecasts which allows them to lower their average inventories or obtain more output given the firm's plant and equipment, its q will increase. As a predictor of the firm's ultimate success, it might be used as a more realistic, Wall Streeter's view of the firm's worth. For this study's other simulations the associations be- tween the Tobin q, company performance and the perform- ance indicators generated by the games themselves were either trivial or in the opposite direction. This negative cor- relation may stem from two phenomena that should not be attributed to the Tobin itself but instead to the playing and learning situation serving as the appraisal's basis. These negative correlations merely reflect dramatic changes in firm performances between the game's beginning and its end for some of the simulations. This is perhaps due to the steep learning curves created by the complexity of the games themselves or the abilities of the players. Firms that are relatively strong performers early in the game can become weaker performers as the game concludes because they, or their managers, take longer to develop and show profitabil- ity. It has been observed that firms that "do nothing" early in a game can temporarily perform well as its competitors are being proactive with their assets while also making vari- ous costly technical mistakes. This proactivity causes them to perform poorly early because their decisions are some- what inaccurate and inefficient but in the correct strategic direction. Those that "do nothing" can survive temporarily by merely mimicking management's earlier decisions. This conservative approach avoids errors but cannot lead to long- term growth and development. Early investment levels nec- essarily create relatively low profit levels. Once those in- vestments take hold however, say in new plant and equip- ment, increasing the company's selling staff, or increasing the firm's advertising programs, higher profits usually en- sue. These investment and "do nothing" elements may ex- plain the strong but negative correlations found. It should also be noted the weights, or a change in the weightings used for each element in their performance measures, can effect their relationship to the Tobin q. As an example the previously cited Sauaia & Castro (2002) study The Multinational Management Game employed seven ele- ments carrying equal weights of 10 as presented in Exhibit 4. The game's current edition, and the one used in this study, changed the weightings. Thus the "Return on Equity" element counts for 19.2% of the performance index's score where before it counted for 14.3% of the result. The adop- tion of different weights within and across games can make 158 Developments in Business Simulation and Experiential Learning, Volume 30, 2003 the Tobin q a less than universal measure of company per- formance. Exhibit 4 The Multinational Management Game Performance Index Components Game Weights Performance Element Previous Current Market Share 10 7 Return on Sales 10 7 Inventory Turnover 10 7 Assets Turnover 10 7 Return on Assets 10 7 Debt to Total Assets 10 7 Return on Equity 10 10 Summary A previous paper by Sauaia & Castro Junior (2002) ex- amining the Tobin q as applied to The Multinational Man- agement Game recommended their work be repeated and that it should be extended to other business games. The results reported here disagree with those found by Sauaia & Castro regarding the direction of association between the Tobin q and the game's performance score although both correlations were statistically significant. Thus, the q has an inconsistent relationship to that game's point system for indicating a firm's success in the game. While the Tobin q appears to be a valid measuring de- vice when applied to The Business Policy Game the be- tween-study inconsistency associated with The Multina- tional Management Game may pertain to this and all other games in and outside this study. Before drawing any firm conclusions about the Tobin q as either a summary or sub- stitute measure of company success further research should be conducted across these and other simulations using a larger number of industries and a greater range of game complexities and player attributes and skill levels. References Altman, E.I. (1968) Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4): 598-609. Altman, E.I. (1983) Exploring the road to bankruptcy. The Journal of Business Strategy. 4(2): 36-41. Biggs, W.D., Levin, G.B., & Biggs, J.L. (1995) A prelimi- nary investigation of the use of a bankruptcy indicator in a simulation environment. Developments in Business Simulation and Experiential Exercises, 22: 78-82. CAPSTONE (2002) Northfield, IL: Management Simula- tions, Inc. Chung, K.H., & Pruitt, S.W. (1994) A simple approximation of Tobin's q. Financial Management, 23(3): 70-74. Cotter, R.V., & Fritzsche, D.J. The Business Policy Game. Englewood Cliffs NJ: Prentice Hall. Eldridge, D., & Bates, D.L. (1984) The Business Strategy and Policy Game. Dubuque, Iowa: Wm. C. Brown. Keys, J.B. (1987) Total Enterprise Business Games: An evaluation. Developments in Business Simulation and Experiential Exercises, 14: 104-108. Keys, J.B., Edge, A.G., & Wells, R.A. (1992) The Multina- tional Management Game. Homewood, IL: Irwin. Lindenberg, E., & Ross, S. (1981) Tobin's q ratio and indus- trial organization. Journal of Business, 54(1):1-32. Sackson, M. (1992). The use of cluster analysis for business game performance analysis. Developments in Business Simulation and Experiential Exercises, 19: 150-154. Sauaia, A.C.A., & Castro Junior, F.H.F. (2002) Is the Tobin's q a good indicator of a company's performance. Paper presented, Association for Business Simulation and Experiential Learning, Pensacola, FL. Scott, T.W., & Strickland, A.J. III (1992) Micromatic: A Management Simulation. Boston: Houghton Mifflin. Thompson, A.A., Jr., & G.J. Stappenbeck (1999) The Busi- ness Strategy Game. Boston: Irwin McGraw-Hill. Wheatley, W.J., Amin, R.W., Maddox, E.N., & Vander- Linde, C.T. (1991) Ascertaining performance variables for use in determining students' grades in courses em- ploying a business simulation. Developments in Busi- ness Simulation and Experiental Exercises, 18: 150. Winters, P.R., Kuehn, A.A., Dill, W.R., & Cohen, K.J. (1964) The Carnegie-Mellon Management Game. Pitts- burgh: Carnegie-Mellon University. Wolfe, J. (2000) The Global Business Game. Cincinnati: South-Western College Publishing. 159 Table of Contents Volume 30, 2003 The Optimal Timing For Introducing Business Simulations Can Handicapped Students Access Your Class Web Site? The Competition Game: Decision Making In A Dynamic Environment Pan-Pacific Enterprises: Strategic Decision Making Simulation Study Of Stochastic Channel Redistribution The Impact Of Business War Games: Quantifying Training Effectiveness Experiential Learning: Introducing Faculty And Staff To A University Leadership Development Program The Feasibility Of The Balanced Scorecard For Business Games A Misuse Of Pims For The Validation Of Marketing Management Simulation Games Incorporating Technology Into The 21st Century Classroom: Are We Facilitating Academic Dishonesty? Improving The Effectiveness Of Peer Evaluations The Use Of A Simulation In An Integrated Mba Curriculum Student Portfolios In Business Education Student Portfolios In Business Education At Ashland University Using SAP ERP Technology To Integrate The Undergraduate Business Curriculum Board Games And Teaching Textile Marketing And Finance Blogging: A New Threat To Student Research? The Way We Talk! Take II Strategic Management: An Evaluation Of The Use Of Three Learning Methods In Hong Kong Adoption Of Discussion-Based Teaching And Assessment In Teaching Strategic Management In Hong Kong The Tobin Q As A Company Performance Indicator Using Representative Nominal Group Technique For Course Review And An Interactive Solicitation Of Ways To Enhance Absel's Image Making Teaching Matter: The Art And Science Of Teaching Business Communication Beyond Sex, Age, And Race: Exploring The Deeper Contents Of Diversity Teaching & Learning The Facilitation Process A Brief On Debriefing: What It Is And What It Isn't Changing Perceptions Of The Importance Of Leadership: The Contribution Of Individual Spirit Harmonics In Leadership Knowledge, Skills And Sustainable Values In Learning Organizations: Some Implications From The Multicultural Virtual Classroom Challenges Of Teaching Undergraduate Organizational Behavior In A Nontraditional Time Format Interactive Online Positioning With The Web-Based Product Positioning Map Graphics Package The Longitudinal Effects Of Entrepreneurship Training On Risk Tolerance: A Look At Similarities And Differences Between Male And Female Undergraduate Students Revisiting Strategy Learning In A Total Enterprise Simulation What Are Simulations For?: Learning Objectives As A Simulation Selection Device Gaming Agency Markets Cooperate For Profits Or Compete For Market? Study Of Oligopolistic Pricing With A Business Game The Design Of A Business Simulation Using A System-Dynamics-Based Approach Modeling The Product Development Function For An Entrepreneurial Firm Simulation Performance And Forecast Accuracy? Is That All? Business Manager Identification Of Competitors In Real World And Simulation Settings Monte Carlo Simulation Analysis On The Costs Reduction Argument Of Interest Rate Swaps Ebiz Game: A Scalable Online Business Simulation Game For Entrepreneurship Training A Model For Online Education Delivery And A Look At Online Delivery Effectiveness Incorporating "Company Reputation" into Total Enterprise Simulations The Genesis And Future Of The Absel "Classicos" Initiative award: Best Paper Award Recipient 2003 - Simulation Track