An Index Approach to Measuring Product Differentiation: A Hedonic Analysis of Airfares

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Abstract The main objective of this paper is to introduce an Allen‐type index of differentiation based on cost functions. With this index, we create an economic measure of product differentiation that quantifies differences between products. Applied research has some generally accepted economic measures, for example, the Herfindahl–Hirschman Index for market concentration, or the Gini coefficient for inequality. Product differentiation, however, does not yet have an established measure. Our objective is to fill that gap and introduce a measure that can be used in market‐related applied research such as market power, antitrust, price indexes, or market strategy. To operationalize the index, we introduce the concept of a core product and use cost functions to measure the degree of differentiation from the core product. To demonstrate the use of the index, we study the effect of product differentiation on price formation in the airline industry using an enhanced hedonic model. The model is empirically tested on 103,980 observations of quarterly US domestic airfare data between 2002 and 2016 and shows that product differentiation has a significant effect on both price and mark‐up.

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They found that although firms in concentrated industries did not have either higher levels of returns, or more variable returns, than firms in industries with little concentration, their accounting returns were more persistent than those in less-concentrated industries. Lustgarten and Thomadakis (1980), early on, documented that stock prices responded more strongly to the earnings of firms in concentrated industries, suggesting that the information contained in earning changes is positively related to persistence.Lev (1983) was one of the first in the accounting literature to examine factors driving annual earnings persistence. Using annual data on 385 firms from the period 1947–1973, Lev (1983) examined the link between four economic variables and the auto-correlation in a firm's annual earnings, sales, and return on equity. 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(1999) found that the higher-order ARIMA models document a positive association between barriers to entry, measured at the firm level as the sum of advertising and research and development over sales, and a negative relation with durable goods and capital intensity. Like Lev (1983), they also found that sales was not related to earnings persistence. However, Baginski et al. (1993) found a positive relationship between sales and earnings persistence using quarterly earnings. Finally, in a manner suggestive of Lustgarten and Thomadakis (1980), Kormendi and Lipe (1987) linked persistence to the strength of the association between accounting earnings and returns.One noticeable shift in the research is the close link between market concentration and barriers to entry. While market concentration and barriers to entry are closely related, Bain (1956) documented that barriers to entry was the primary explanatory of high returns. Mann (1966) confirmed Bain's (1956) findings by examining return on equity measures for 30 industries a decade latter. By restricting entry, firms are able to retain abnormally high profits. The early industrial economics literature discusses four sources of barriers to entry: economies of scale, product differentiation, absolute cost advantages, and capital costs.The competitive strategy literature suggests that it is a firm's business strategy, in addition to industry characteristics, that determines the persistence of profits. That is, while many of these barriers to entry are at the industry level, firms' strategies also play an important role. For instance, the competitive strategy literature (Porter 1980; Grant 2010) argues that pursing a product differentiation strategy helps firms retain a long-run competitive advantage. 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In addition, the authors argue that entry is also made difficult because the network carriers have created a comparative advantage in running a complex hub system by developing special expertise to manage it effectively.One of the cornerstones of the paper is the delineation of competitive strategies. Rather than developing an empirical measure of strategy through survey or other empirical methods, such as in Banker et al. (2006), the study relies on the Bureau of Transportation Statistics (BTS) to define the two dominant competitive strategies in the airline industry and to identify the airlines in each group. The BTS (2005) defines a network airline as a carrier that operates "a significant portion of their flights using at least one hub where connections are made for flights on a spoke system." Alternatively, J.D. Power (2011) defines network carriers as "airlines that operate multi-cabin aircraft and use multiple airport hubs." With respect to low-cost carriers, BTS defines them as "those that the industry generally recognizes as operating under a low-cost business model." J.D. Power defines them as "airlines that operate single-cabin aircraft with typically lower fares." It would be useful to be able to determine the distinct attributes of the two operating strategies, as this would help readers understand the specific characteristics of each strategy. A more refined definition should also help facilitate generalizing the results to other industries where firms use different activities to compete. For example, descriptive statistics are provided for the two groups of airlines in Table 3 of the CRC paper. It is clear that the low-cost airlines have lower operating expenses per available seat mile and that the network airlines have higher prices per revenue passenger mile. However, there is little information on other dimensions of the two strategies, such as variety measures on customer and aircraft types, labor specialization, or hub concentration. Rather, the primary distinguishing factors seem to be that the network carriers are much larger in terms of assets, revenues, market share, and seat miles than the low-cost airlines.The theoretical and empirical work discussed above suggests that a differentiation strategy can result in barriers to entry that then lead to persistence earnings. While it is easy to argue that the empirical models used in the current study suffer from specification errors and low power, the results generally document that the profit margins of the network carriers are more persistent than those of the low-cost carriers. Turnover differences are not noticeable in the basic models. The current paper argues that network carriers adopt a business model based on a full service or differentiation strategy. There are two aspects of the paper's argument that are unclear. One deals with the nature of the network carriers and whether their business model is one of differentiation. The other is whether the margin persistence observed in the paper can be ascribed to entry barriers.Exhibit 1 presents a summary of some of the key drivers of entry barriers and persistence as discussed in the literature. Many of the factors listed in the exhibit were identified above. Other factors are identified in Waring (1996). Waring (1996) examined the persistence of firms' annual earnings using industry metrics, and found that skill level of employees, unionization, and switching costs, in addition to more traditional measures of barriers to entry, were positively related to persistence. There are aspects of the network carriers that suggest a differentiation strategy. These include the multiple classes of airlines and customers, amenities, and flying to small cities, as well as internationally. But many of these airlines are legacy carriers with high union representation and gate dominance. It is possible that rather than erecting barriers via differentiation, these network carriers create barriers by controlling scarce resources such as landing sites or concourses, wielding political clout, or predatory pricing tactics. Thus, it is not clear that a differentiation strategy is responsible for creating entry barriers, to the extent they exist.The other issue is that other factors, such as firm size, operating leverage, unionization, buyer switching costs, or some other factor, could be driving the earnings persistence, rather than entry barriers. Focusing within one industry certainly helps control for many factors, but not sufficiently to ascribe competitive strategy to the persistence differences. Thus, it is not clear if, in fact, it is the competitive strategy, through the erection of entry barriers, that is driving the observed differences in earnings persistence. For instance, conference participants were concerned about how size differences, as well as the international activities of the network airlines, could have been influencing the results. In summary, because it is very difficult to ascribe the documented differences in earnings persistence to strategy differences, future research is warranted.A very interesting aspect of the paper is the examination of how the growth, price, and productivity components of profit margin changes (and revenue growth and revenue price components of asset turnover) impact persistence differently across competitive strategies. By combining variance and productivity analysis, Banker et al. (1989) provide a framework for isolating the sources of changes in operating income. Their approach partitions operating income changes into changes in sales growth, productivity, and price recovery. Horngren et al. (2006) link these components to competitive strategy by stating that productivity gains would be more prevalent for firms following a cost leadership strategy, whereas product differentiators would be focused in price recovery. CRC use these results and construct operating income changes for the airlines in their study as follows:In the model, operating income (OI) changes are due to revenue (REV) changes and expense (EXP):In this formulation, RPM is revenue passenger miles, ASM is available seat miles, and LF is the load factor for the period. An empirical problem with their measures is that their growth measures are very closely related. In the CRC formulation, all costs are treated as varying with seat miles. Thus, growth in revenues and growth in costs are virtually identical, with a correlation coefficient reported in Table 4 of the CRC paper of 0.992. The portion of the operating income change due to growth, plus, can also be measured as:In this formulation, income growth equals the growth in revenue passenger miles times the prior period's operating income. This reformulation would allow for a more stable estimation of the relationship between overall growth and operating earnings margin persistence.Other than the measurement issue addressed above, the approach CRC use is interesting. Because there is little previous research using this partition to measure the persistence of these components, there is little theory to guide their investigation. The authors argue that because network airlines cater to more business travelers than low-cost carriers, network carriers face a more inelastic demand. This results in more persistent revenue components for the network carriers. Moreover, CRC argue that low-cost carriers are more nimble at adjusting for changes in demand and, therefore, they are able to adjust support resources more quickly than the network carriers as conditions warrant. The authors find that while the growth persistence measures are generally not different across airline type, the operating margin changes unit price and cost changes, as well as productivity gains, of network airlines are more persistent than those of the low-cost carriers. There is some difference in the turnover revenue components for the quarterly model, but no annual differences are noted. Overall, this is a very interesting approach that can be replicated in other industries.The Collins et al. (2011) study examines how the competitive strategies of airlines impact the persistence of operating earnings. It finds that that network airlines (differentiators) have more persistent operating profit margins than low-cost carriers. The study also demonstrates that partitioning the change in profit margin into growth, price recovery, and productivity more fully explains future profit margins than current profit margin alone. A very useful feature of the paper is that by focusing on one industry, the paper is able to control for many variables that have previously been associated with earnings persistence. Clearly, the paper extends our knowledge of how competitive strategy impacts the persistence of earnings.The study raises some interesting questions for future research. One avenue is to continue intra-industry research on the links between strategy and earnings persistence. A benefit of this intra-industry approach is that it controls for many of the other factors related to persistence. Another avenue, and one that is particularly relevant for management accountants, is to continue CRC's work on the links between earnings persistence, strategy, and the components of earnings changes. In this manner, we can help identify which strategic operating initiatives, such as those related to pricing or productivity, result in lasting changes in profitability.

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