handled baggage, ticket oversales, and in-fiight service are significantly associated with our proxy for customer satisfaction. Using an instrumental variable for ...
Using Nonfinancial Information to Predict Financial Performance: The Case of the U.S. Airline Industry BRUCE K. BEHN* RICHARD A. RILEY, JR.**
To enhance traditional financial reporting, academics and policymakers have suggested that financial statement users be provided with nonfinancial performance information that may enhance users' ability to evaluate and predict financial performance. This study tests this proposition by examining whether timely nonfinancial performance information is a useful predictor of financial performance in the airline industry. From analysts ' written pronouncements and financial press articles we identify a number of fundamental metrics, including customer satisfaction, purportedly used by analysts and investors to assess airline performance. We empirically examine these metrics and find that on-time performance, mishandled baggage, ticket oversales, and in-fiight service are significantly associated with our proxy for customer satisfaction. Using an instrumental variable for customer satisfaction, we find that customer satisfaction, load factor, market share, and available ton miles are contemporaneously associated with operating income and revenues and that customer satisfaction and available ton miles are contemporaneously associated with expenses. Finally, using one and two months of nonfinancial data, we find that nonfinancial performance information appears to be useful in predicting quarterly revenues, expenses, and operating income.
1. Introduction The purpose of this research is to evaluate the association between nonfinancial information and financial performance in the U.S. domestic airline industry and to examine whether this nonfinancial information can be useful in predicting future financial performance. Both academics and policymakers, including Birchard •University of Tennessee **West Virginia University We would like to thank Susan Ayers, Joe Carcello, Kathleen Hethcox, Al Nagy, Terry Neal, Jan Williams. Jeff Wong, the University of Oregon seminar participants at the 1997 American Accounting Association national meeting, and Holly Johnston (the reviewer) for their helpful comments on earlier versions of this paper. We gratefully acknowledge the financial support of the University of Tennessee. 29
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(1994), the AICPA (1994) Jenkins Committee, and Wallman (1995, 1996), have expressed concern that corporate financial reporting and disclosure are not keeping pace with a dynamic and constantly changing business world. To enhance traditional financial reporting, one consistent suggestion from this group has been to provide financial statement users with nonfinancial perfonnance information that may enhance users' ability to evaluate and predict financial performance. As Birchard (1994) argues, there is a missing link between companies' progress in operating activities and companies' financial results, and this link will come from research that demonstrates that nonfinancial perfonnance variables are indicative of bottom line results. This study contributes to this debate by providing empirical evidence that timely nonfinancial perfonnance information is contemporaneously associated with, and can be useful in predicting, financial performance in the U,S. airline industry. Using analysts' written pronouncements and financial press articles we identify a number of fundamental metrics purportedly used by analysts and investors to assess airline performance. From this search, it appears that fundamental operating metrics such as load factors, market share, and available ton miles differentiate airline performance. While these measures appear to be important indicators of future earnings, customer satisfaction measures such as on-time arrival, mishandled baggage, ticket oversales (i.e., involuntarily "bumped" passengers), in-fiight service levels and customer complaints also differentiate future financial performance,' We develop hypotheses for these metrics based on analysts' and financial press suppositions. The customer satisfaction hypothesis is tested using an instrumental variables approach, and we find that on-time performance is negatively associated with customer complaints (our proxy for customer satisfaction). In contrast, mishandled baggage, ticket oversales, and crowded fiights are positively associated with customer complaints. Further, we find that load factor and market share are positively associated with contemporaneous operating income, while customer complaints (our instrumental variable for customer satisfaction) and available ton miles are negatively associated with contemporaneous operating income. With respect to revenues, customer complaints are negatively associated with revenue and load factor, and market share and available ton miles are positively associated with revenue. In addition, customer complaints and available ton miles are positively associated with operating expenses. The explanatory power of these models (i.e., adjusted R^) ranges from 0.41 to 0.71 and the results are robust to a variety of alternative measures of financial performance. We also develop and empirically test whether monthly nonfinancial information can be used to predict quarterly financial performance. Using nonfinancial
I, For example, in a recent Wall Street Journal article (Carey [1996]), John Edwardson, United Airline's (UAL) president and chief operating officer, stated the UAL is spending $386 million to replace aircraft seats, refurbish cabin interiors, upgrade passenger entertainment systems and improve food and in-flight service to bolster UAL's lackluster standing with customers. Further. UAL plans to link executive compensation to airline on-time performance.
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information provided in months 1 and 2 of a particular quarter, we develop a model to predict quarterly revenues, expenses, and operating income. The explanatory power of these models (i.e., adjusted R^) ranges from 0.35 to 0.71 and associations similar to those already noted are observed for the one- and two-month prediction periods. Based on these findings, it appears that fundamental nonfinancial performance metrics are indicators of future financial performance in the airline industry. Because many of the nonfinancial performance variables incorporated in this research are disclosed monthly, whereas financial statement data are systematically released quarterly, these results may be of particular interest to policymakers and others interested in the timely release of relevant performance metrics. This research is organized in the following manner. The accounting and financial reporting issues surrounding nonfinancial metrics are presented in Section 2. In Section 3, pertinent prior research is discussed. Section 4 includes an overview of the airline industry. Model and variable development are discussed in Section 5. The data sources and sample selection procedures are outlined in Section 6. The results are presented in Section 7. Finally, contributions, limitations and extensions are considered in Section 8.
2. Nonfinancial Performance Variables and the Accounting Profession The AICPA Jenkins Committee was charged with identifying information that companies should provide to investors and creditors. In 1994, the committee published Improving Business Reporting—A Customer Focus: Meeting the Needs of Investors and Creditors. One of the recommendations of the Jenkins Committee for meeting users' needs is that financial reporting should focus more on the factors that create value, including nonfinancial measures indicating how key business processes are performing. In addition, SEC Commissioner Wallman (1995, 1996) notes that the SEC has relied on the assistance of the accounting profession for the past 60 years to satisfy the commission's statutory responsibility to craft accounting standards for public companies. The commissioner's commentary encourages the accounting profession to consider financial reporting issues more pervasive than those addressed by the Jenkins Committee.^ As part of a preliminary proposal to enhance financial reporting, Wallman (1996) suggests a five-layer corporate reporting system that deemphasizes recognition and focuses on providing relevant information. Pertinent to our research, "layer 3 " would include information that is "highly relevant,... consistently measurable with a high degree of reliability'' but does not meet the definition of an asset, liability or component of equity. For the airline industry, performance indicators that might be included in layer 3 are measures such as load 2. For example, the commissioner suggests that the accounting profession consider how to address disclosure for "virtual" companies and intellectual assets.
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factor and on-time arrival.' These measures are readily determinable and, because of systematic collection methods, are reliable and potentially auditable. The preceding arguments and proposals are consistent with FASB Statement of Financial Accounting Concepts Number 1: financial reporting should provide information that is useful (i.e., relevant) to present and potential investors and creditors and other users in making rational investment, credit and similar decisions. Although there are many advocates of changing financial reporting, such views are not universal. For example, Francis and Schipper (1998) state that the common (and unacceptable) goal of the AICPA Jenkins Committee initiatives is to improve financial reporting by altering some or all of the elements of the current financial reporting model and/or by altering the fundamental nature of the assurance function. The authors conclude that, overall, their tests yield no systematic evidence that financial statements have lost relevance over the 43-year sample period (19511993). We contribute to this debate by examining whether nonfinancial operating metrics are contemporaneously associated with and useful predictors of short-term financial performance.
3. Prior Research While a large body of financial accounting literature examines the association between firm market values (i.e., stock prices) and accounting variables, these relationships have been tested with little regard for their underlying economic structure (Bernard and Noel [1991]). Therefore, to better understand how company fundamentals map into financial performance, Bernard and Noel (1991), Stober (1993), and others have investigated the ability of financial statement metrics to predict future eamings. These particular authors find that inventory and receivable information are leading indicators of future financial perfomiance. While this research explores the relationship between accounting financial statement metrics and financial performance, it does not investigate the association between nonfinancial metrics and traditional financial performance measures. Amir and Lev (1996), however, extend research related to nonfinancial performance metrics by examining the value-relevance of nonfinancial performance variables in the high-technology wireless communications industry. The authors note that in times of rapid change, financial information of firms, especially in fastchanging technology-based industries, may be of limited value to investors. For example, telecommunications, biotechnology, software producers, and other growth companies create value through production and investment activities; yet, key financial variables such as earnings and book value are negative or excessively depressed and appear unrelated to market values. Based on these observations. Amir and Lev (1996) examine the value-relevance of financial information and nonfinancial information using quarterly data for 14 companies over 10 years. Their 3. Amir and Lev (1996) argue that nonfinancial information will typically be industry-specific.
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analyses document the value relevance of rights acquired by potential subscribers and penetration of markets and their findings suggest that, on a stand-alone basis, traditional financial statement information is largely irrelevant for the wireless communications industry. The authors conclude that the results indicate the importance, in both practice and research, of expanding the domain of fundamental variables examined to include nonfinancial information. Two studies address the relation between nonfinancial measures and financial performance in the airline industry. Schefczyk (1993) uses data envelopment analysis (DEA) to evaluate airline operating efficiency (i.e., the ratio of outputs to inputs). The author hypothesizes that available ton kilometers may refiect aircraft capacity more accurately than fiight equipment depreciation and amortization. Further, Schefczyk (1993) argues that load factor (alone) may be an incomplete nonfinancial performance measure because nonflight inputs and outputs are ignored and inputs besides airline capacity are disregarded (e.g., operating costs). Available fiight tons per kilometer (representing fiight assets), fiight operating costs, and nonfiight assets are used as inputs and revenue per passenger kilometer and nonpassenger service revenues are used as outputs to estimate efficiency. The findings indicate that estimated efficiency, load factor, and the percentage of passenger revenues are positively associated with return on equity. Dresner and Xu (1995) examine the effect of three customer service variables on customer satisfaction and in turn on profitability for U.S. airlines, testing links in the customer service, customer satisfaction, and corporate performance chain. The study examines the effects of on-time performance, mishandled baggage, and ticket oversales on customer satisfaction (proxied by customer complaints) and the effect of these customer service variables and estimated customer satisfaction on corporate profitability. The findings suggest that increasing customer service raises customer satisfaction and improves corporate performance. Our work complements and extends that of Schefczyk (1993) and Dresner and Xu (1995). By incorporating fundamental operating measures in addition to customer satisfaction metrics in a comprehensive model, we test whether this nonfinancial airline information is contemporaneously associated with financial performance and whether this information can also be used to predict short-term revenues, expenses, and operating income. In addition to incorporating a richer set of variables, we argue that these nonfinancial measures may have different relative effects on airlines' revenues and expenses. Given the potential for differing effects on revenues and expenses, analyzing only the association between nonfinancial information and operating earnings may dampen the informational content of these airline nonfinancial metrics.
4. The Airline Industry In any industry-specific analysis, knowledge of industry economics and aspects of value relevance, including the impact of nonfinancial performance variables.
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must be developed." Since the Airline Deregulation Act became law in 1978, industry perfonnance has been turbulent.' The industry recovered from an economic slump in 1984 as the deregulation process was completed. In the latter part of the 1980s, as a result of economic recovery and relatively low fuel prices, the largest three carriers, American, Delta, and United, were profitable, and new capacity was continually added within the industry. As the 1980s came to an end, however, airlines suffered from declining revenues and spiraling costs. In addition, in 1990, Iraq invaded Kuwait, further escalating operating costs (i.e., fuel costs). An overall economic recession in the tJnited States in 1989-90 resulted in decreased consumer travel budgets, and the threat of terrorism depressed passenger levels even further. In 1991, airline traffic declined for the first time in its then 67-year history. Now defunct airlines such as Eastern hore the burden of industry decline; however, most airlines added debt to their financial structure as a result of accepting aircraft ordered during prosperous times and funding deficits. In response, airlines retreated into profitable markets, cut operating costs, restructured operations, and prepared for an immediate future of low fares and fierce competition. By 1996, airline traffic had begun to rise, capacity had leveled off, and load factor (the percentage of seats sold) had improved. Ott and Neidl (1995) argue that the turbulent financial past is a prologue for the future. Competition, especially from "no-frills" airlines such as Southwest, will continue to be problematic, and the industry will continue to be cyclical (Value Line, March 22, 1996).* O'Connor (1995) describes airline service as an undifferentiated product. In such highly competitive environments, price is usually the only factor differentiating homogeneous goods and services. However, it appears that U.S. airlines do not consider their products as commodities and have gone to great lengths to differentiate themselves and their services in the market place. U.S. airlines exhort the benefits of hub systems (Delta); nonstop flights (United); inexpensive flights (Southwest); and differences in frequent flyer programs, destinations, and anticipated service levels. As an example. Continental promotes the fact that they have been consistently ranked first or second in on-time performance.^ Amir and Lev (1996) chose to analyze wireless communications companies because the industry is emerging and dynamic and, thus, the role of traditional (historical) financial information is unclear. Similarly, in the competitive airline industry, the role of nonfinancial infonnation is also unclear. Airlines tend to have significant fixed costs related to the acquisition and operation of aircraft; therefore, the information content of historical financial statements may be limited, Nonfi4, The basis for this discussion is O'Connor (1995) and Ott and Neidl (1995), though other sources cited in the reference section were also consulted, 5, The primary effects of airline deregulation were to eliminate controls over entry and exit for both specific airline routes and the airline industry and to eliminate controls over airline ticket prices, 6, "No-frills" airlines provide minimum service levels (e,g,, no preassigned seating and limited in-flight services) and charge lower airfares (by comparison to full service airlines), 7, See Continental's full-page Wall Street Journal advertisement on Wednesdav Mav 22 1996 p, A17, }' J '
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nancial information may fill this void by providing important signals about financial performance in the airline industry.
5. Model and Variable Development Similar to Lev and Thiagarajan (1993), we review analysts' written pronouncements from Value Line and Standard & Poors and relevant financial press articles from the Wall Street Journal and the Wall Street Journal Transcripts to identify a set of nonfinancial performance variables.* We then incorporate these nonfinancial metrics in linear regression models to examine the contemporaneous relationship with quarterly financial performance and the ability of these nonfinancial metrics to predict quarterly financial performance. Based on this search we find that load factor, market share, capacity, and customer satisfaction are fundamental drivers of financial performance. These variables are discussed in the following and descriptions and predicted signs are summarized in Table 1.
5.1 Customer Satisfaction Model While metrics such as load factor, market share, and capacity are readily available from public sources, information about customer satisfaction is difficult for analysts and investors to obtain because firms do not disclose the results of internal customer satisfaction surveys. Even if airlines disclosed such information, it is unlikely that the information would be standardized across companies. Based on anecdotal evidence, it appears that analysts and investors use customer service proxies such as mishandled baggage, customer complaints, on-time arrivals, ticket oversales, and in-flight service to assess customer satisfaction. To model this relationship, similar to Dresner and Xu (1995), we create an instrumental variable (CMPLNTFT) for customer satisfaction, and use this customer satisfaction proxy in our models. Specifically, the following ordinary least-squares regression is used to develop the customer satisfaction proxy used in the contemporaneous and prediction models discussed in the next sections: 8. The following excerpt from Value Line (March 22. 1996) illustrates how analysts use nonfinancial performance measures to draw inferences about airlines' current performance and future eamings. Airline traffic is continuing to rise, although at a relatively slow pace.... The good news is that capacity has been leveling off.... Last year (1995). the available seat miles actually declined slightly (less than 1%).... The result has been that the load factor (the percentage of seats sold) has risen. L.ast year's industry load factor rose 1.6 percentage points, to 65% and this year there has been a further increase. That is generally good news for the industry. According to this excerpt, available seat miles and load factor are proposed as leading indicators of financial performance. Because it is difficult to develop a theoretical analysis that derives the effect(s) of nonfinancial performance variables on financial performance, we use analysts' and investors' interpretations as the basis for including nonfinancial performance variables in our empirical models.
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