The impact of firms' risk-taking attitudes on advertising budgets

The Impact of Firms’ Risk-Taking Attitudes on Advertising Budgets Don Y. Lee UNIVERSITY

OF NEW ORLEANS

This study investigates a hypothesis that a firm’s

advertising budget is an

increasingfitnclion ofits risk-taking attitude resultingfrom its realized poor petjbrmances. The measure of risk attitudes is based on prospect theoty (Kahneman and Tversky, 1979). A longitudinal design is developed and datafrom U.S. brewingjrms are used to test the hypothesison afinn-byfirm basis. Results obtained using the partial least square (PM) causal modeling technique show that afirm’s previous poor performance leads to its risk-taking, which in turn leads to thefirm’s spending more on advertising. J BUSN RES 1994.

31.247-256

S

trategic marketing planning is concerned with functional decisions related to marketing-mix elements, including price, distribution, and advertising (Kerin, Mahajan, and Varadarajan, 1990, p. 5). It plays a key role in establishing a strategic fit between an organization and its changing market environment (Day, 1984, p. 3). As in the case of most business decisions, strategic marketing decisions involve uncertainty. A web of compelling evidence has been produced in the literature that suggests that attitude toward risk plays an important role in decision-making under uncertainty (e.g., Kahneman and Tversky, 1979; Schoemaker, 1982; Einhorn and Hogarth, 1985). Day (1984, p. 2) also has identified the importance of risk attitudes in strategic planning: “Strategic planning is not a way of avoiding or minimizing risks. If anything, it should increase risk-taking by ensuring that possible risks are considered and better contained.” Despite the consensus among scholars concerning the importance of attitudes toward risk in decisionmaking, this factor has not been incorporated in the research on marketing strategy. This article addresses this gap in the literature by studying the impact of a firm’s risk attitudes on its strategic decisions, specifically those decisions concerning advertising budgets. Both academics and practitioners perceive much uncertainty in advertising effectiveness. “Currently, no one knows what advertising really does in the marketplace” (Lilien, Kotler, and Moorthy, 1992, p. 263), and “most executives feel that advertising is the one part of the business for which they must allocate capital resources and for which there is little tangible justification” Uannuzzo, 1986). As long as managers perceive uncer-

Address correspondence to Don Y. Lee, College of Business Administration, University of New Orleans,

IA 70148.

Journal of Business Research 31, 247-256 (1994) 0 1994 Elsevier Science Inc. 655 Avenue of the Americas, New York, NY 10010

tainty in budgeting how much to spend on advertising, their attitudes toward risk may well play an important role in advertising budget decisions. Unfortunately, there is hardly any existing research that investigates the impact of a firm’s attitudes toward risk on its advertising budget setting. Without understanding this impact, it is difficult to evaluate a firm’s advertising strategy, which is an important element in its marketing strategy. This study attempts to investigate a firm’s attitudes towards risk-taking on its advertising budget decisions. In addition, a new measure of firms’ risk attitudes is developed. This measure is based on prospect theory (Kahneman and Tversky, 1979), which has been successfully applied to organizations (D’Aveni, 1989) and nations (Jervis, 1992; McInerney, 1992) although it was originally developed for individuals. Risk in expected utility theory is defined by the variance of the probability distribution of possible outcomes (Pratt, 1964; Arrow, 1965). Attitude toward risk is defined by the curvature of the utility function of expected monetary value: where concavity (i.e., utility increases with monetary value, but at a decreasing rate) demonstrates risk aversion while convexity (i.e., utility increases with monetary value, but at an increasing rate) shows risk-taking. Risk attitude in this study, however, is related to firms’ behavior, and is defined from a managerial point-ofview. Based on a study involving 509 top-level executives, MacCrimmon and Wehrung (1986, p. 3-38) showed that when managers think about risks they think about the chances of losses and their findings were supported by a later study (Shapira, 1986); hence, risk attitude can be defined as the willingness to take chances and to accept losses if adverse events occur. By this definition, then, an individual is risk-taking (riskaverse) if he or she is more (less) willing to take chances and accept losses. Decision makers’ risk attitudes are also dependent upon the decision-making situation (Mach and Shapira, 1987). In this study, the situation within which the decision makers’ risk attitudes are assessed is assumed to take place at the end of a fiscal year when a firm evaluates its financial performance for the past year and make advertising budget decisions for the next year. Firms’ risk attitudes are extensively studied in the strategic management area, especially in risk/return literature. A majority of these studies attempt to confirm a negative association between risk and return as posited by Bowman’s (1982) hypothesis: “Risk-seeking by troubled (i.e., poorly performing) firms” ISSN 014%2963/94/$7.00

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J Busn

Res

The Impact

of Firms’ Risk-Taking

Attitudes

on Advertising

Budgets

1994:31:247-256

(Fiegenbaum

and Thomas,

1988; Miller and Bromiley,

1990).

In this work, the Bowman hypothesis is operationalized as a causal model-poor performance leads to risk-taking attitude, in which risk attitude is a construct. This practice follows Cronbath’s (1970, p. 143) advice that “a construct should be validated by deriving a hypothesis from the theory that involves the construct and testing it empirically.” By doing so, performance

is used as a control

to improve

the construct

variable validity

for risk attitude

in order

of a firm’s risk attitude.

evrdence

relating to managers’

risk-taking

behavior m psychology and business risk-taking literatures (MacCrimmon and Wehrung, 1986). Managers are motivated to take risks, i.e., they associate risk-taking with the expectations of their jobs; and perceive risk-taking to be essential for success in business decision making (March & Shapira, 1987). These motivational factors may lead them to take more risks in business than in personal decisions (MacCrimmon and Wehrung, 1986). Although managers undoubtedly vary in their individual propensities to take risks (McClelland 1961; Atkinson, 1964) those variations are camouflaged by processes of selection that reduce the heterogeneity among them (March and Shapira, 1987). Additionally, a group as a whole is more willmg to take risks than its individual members, a behavior called “risk shift” (see Clark. 1971 for critical surveys of this issue). Although attitudes toward risk are usually pictured as stable properties of individuals (Kogan and Wallach, 1964) more recent research treats them as varying with different decisionmaking situations (Kahneman and Tversky, 1979; Lopes, 1987). Numerous studies agree that individuals tend to be risk averse in situations where they expect good outcomes from decisions; whereas they tend to be risk-taking in situations where poor outcomes are expected (Payne, Laughhunn and Crum, 1981; Fischhoff, 1983; Samuelson and Zeckhauser, 1988; Currim and Sarin, 1989). This risk-taking in adversity 1s also true for managers (Laughhunn, Payne and Crum, 1980) and organizations (Mayhew 1979; Bowman 1982; Singh, 1986; Fiegenbaum and Thomas, 1988). These findings are generally consistent with those in the aspiration level or target literature (Cyert and March.

1963;

Fishburn,

1977;

Payne,

Laughhunn,

function as random implies that effectiveness of advertising on sales 1s uncertain. A risk-neutral firm, according to expected utility theory, does not discount uncertainty involved in advertising effectiveness, as a result, it spends the same advertis-

Research Hypothesis Development There is vast empirical

That a firm’s risk attitudes play an important role in its advertising budgeting decisions is documented m Nguyen (1985). He has found that risk-averse firms spend less on advertising than do risk-neutral firms, assuming firms’ maximization of expected utility and a random sales response function of advertising expenditure. Nguyen’s treatment of the sales response

and

Crum, 1981; Lant and Montgomery, 1987; Mezias, 1988) which reports that individuals are risk taking rf their performance levels are below a previously set target or an aspiration level. The phenomenon of risk-taking in adversity or below-target has been confirmed in interviews with managers conducted by MacCrimmon and Wehrung (1986) and Shapira (1986). According to these studies managers believe that fewer risks should, and would, be taken when things are going well. Conversely, they expect riskier choices to be made when an organization is performing unsatisfactorily Following these findings, firms will be risk-averse and avoid taking actions when their performances are good, and will be risk-taking and seek to take actions when performances are poor.

ing budget regardless of whether advertising effectiveness is uncertain or deterministic. A risk-averse firm, on the other hand, prefers certainty to uncertainty m advertising effect. Consequently, tt will budget less for advertising if it perceives uncertainty in advertising effectiveness. Nguyen (1985) however, did not address the case of risk-taking firms, due to his conventional assumption concerning firms’ risk-aversiveness. Notwithstanding the conventional risky business. There are uncertainties

wisdom, advertising is a involved m its effective-

ness, (e.g., copy effect, frequency and timing, competition, etc.). A risk-taking firm, whose risk-taking attitude results from its poor performances, according to the arguments made earlier, may take actions and possibly spend more on advertising to “buy” chances for probable higher returns which may result from risky advertising. In addition, the most frequently used criterion in determming advertising budgets is to spend what can be afforded, according to Broadbent’s (1988) extensive survey of firms’ advertising budgeting practice. Therefore, there is no threat to a firm’s survival if it sets a higher advertising budget. Furthermore, there exist hardly any means for a firm to measure advertising effectiveness; as a result, managers who make advertising budget decisions have shielded themselves from the responsibility for unfavorable outcomes of advertising. Consequently, both the firm and its managers can “afford” to take risks in advertising spending Research hypothesis: If a firm perceives uncertainty in advertising effectiveness on sales, the more risk-taking the firm is, the more it will spend on advertising; and the more riskaverse the firm IS, the less it will spend on advertising, other conditions

being

equal.

It should be noted that the risk attitude here is treated cifically as resulting from a firm’s poor performance.

Risk-Taking Attitude Prospect Theory This section

briefly discusses

spe-

and

prospect

theory

(Kahneman

and

Tversky, 1979). the theoretical foundation for the development of a risk attitude measure. Prospect theory posits that when individuals are faced with a chotce with uncertainty they will compare the expected outcomes with a reference point This reference point IS status quo. An individual’s risk attitude has

J Bum Res 1994:31:247-256

D. Y. Lee

been found to vary with what he or she perceives from this comparison. If outcomes are perceived to be better than the reference point (i.e., gains are perceived), the decision maker will be risk averse; if outcomes are perceived to be worse than the reference point (i.e., losses are perceived), the decision maker will be risk-taking. The risk attitude of an individual is reflected by the curvature of a value function, the general form of which has the following features: (1) it is defined in terms of gains and losses with respect to a reference point; (2) it is S-shaped, generally concave for gains (i.e., risk-averse) and convex for losses (i.e., risk-taking); and (3) it is considerably steeper for losses than for gains (i.e., loss aversion); (Kahneman and Tversky, 1984, p. 279). Simply put, the value function of prospect theory can be analogous with a translation machine, translating values or feelings into risk attitudes in the following process. In making decisions, the individual compares the expected outcomes with a reference point and determines if a positive or negative value occurs, then the value function translates the values (or feelings) into a risk attitude according to a translating rule-the S-shaped curve, which converts negative (positive) value into a risk-taking (-averse) attitude, whose magnitude is represented by the curvature of the S-shaped curve. As stated earlier, we assume performance evaluation as the business situation within which to assess a firm’s risk attitudes. Now we use this situation to define a firm’s reference point. Each publicly held firm prepares annual reports to its shareholders and submits various financial documents to the Securities and Exchange Commission at the end of each fiscal year. Within the context of these reports and documents, it is common for management to compare the current year’s performances with those of the prior year and to appraise the chief executive officer’s (CEO) performance based on this comparison (Puffer and Weintrop, 1991). A firm’s status quo for evaluation of its performance for year t, therefore, for the purpose of this study, will be the performance level of year t - 1, This status quo of a firm is defined as its reference point, This definition is in conformity with prospect theory as well as the findings of numerous empirical studies based on prospect theory (e.g., Thaler, 1980; Fischhoff, 1983; Samuelson and Zeckhauser, 1988; Currim and Sarin, 1989). With a firm’s reference point of performance so defined, then, a firm will be risk-taking if the realized performance levels for year (t) are inferior to those for year (t - 1). This conjecture is consistent with Bowman’s (1982) hypothesis: “Risk-seeking by troubled (i.e., poorly performing) firms” in the risk/return literature. The measure of a firm’s risk-taking attitude in this study is inferred from its negative feelings about losses as reflected in the “Letter to the Shareholders” found in the U.S. brewing firms’ annual reports. Details of how to build the measure of risk attitude will be discussed in content analysis of the measurement section. Two issues are worthy discussing regarding the use of the risk attitude measure developed in this study. One is the context within which the new risk attitude measures may be ap-

249

plied. Another is the difference between decision value and experience value. Risk attitude is situation-dependent. Here we assume the year-end performance evaluation to be the situation. Firms usually set their advertising budgets once a year (Lilien et al., 1992); most firms set their advertising budgets at the end or beginning of a fiscal year (Broadbent, 1988); therefore, performance evaluation and advertising budget decisions are made almost at the same time. In this work, risk attitude is treated as only varying with the changes in reference point (previous year’s performance level), although it is generally assumed as a stable attribute (Kogan and Wallach, 1964). As a result, it is reasonable to assume that a firm’s attitude toward risk remains stable at the times when its performances are evaluated and when advertising budget decisions are made; therefore, caution should be taken in using the measure developed here in other situations. Moreover, the risk attitude measures here are inferred from a firm’s annual reports, and they can only be used for the firm’s decision making context, not for its strategic business units’ (SBUs). Another issue is the difference between the decision and experience values. Decision value, according to Kahneman and Tversky (1984, p. 349) is defined as “the contribution of an anticipated outcome to the overall attractiveness or aversiveness of an option in a choice.” Whereas the experience value is defined as “the degree of pleasure or pain, satisfaction or anguish in the actual experience of an outcome.” The negative value inferred from content analysis of a firm’s annual reports in this research results from a firm’s dissatisfaction with its realized poor performance. It is an experience value. The distinction between the decision and experience values, however, is “rarely explicit in decision theory because it is tacitly assumed that decision values and experience values coincide” (Kahneman and Tversky, 1984, p. 349). As a result of the conventional assumption, it seems reasonable to use the risk attitude measure developed here to investigate the impact of a company’s risk attitude on its advertising decisions.

Method Industry Section Firms in the U.S. brewing industry were selected for hypothesis testing. The U.S. brewing industry may be one of very few remaining industries with a low degree of diversification. For the majority of brewing firms, the average sales of beer accounted for more than 90% of their total sales. Hence, the relatively single-business characteristic reduces complications which may result from multiple businesses.

Measurement CONTENT ANALYSIS OF ANNUAL REPORTS TO INFER RISK ATTITUDE MEASURES. Content analysis, as defined by Krippendorff (1980, p. 21) is “a research technique for making replicative

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J Busn Res 1994:3 1:247-2 56

and valid inferences from data to their context.” Content analysis assumes that the language in which people choose to express themselves contains information about the nature of their psychological states (Viney, 1983). It is frequently used to generate measures for hypothesis testing (Cutler and Javalgi, 1989; D’Aveni and Macmillan, 1990). Bowman (1976, 1978) has content-analyzed annual reports of various firms and pointed out that annual report discussion is a reasonable surrogate for real activity. Results of a large-scale survey found that 91% of securities analysts and 8 1% of the individual investors trusted and relied on firms’ annual reports for investment information (USA Today, 1989). Bowman (1982,1984) used content analysis of annual reports and counted the word “new” to obtain a surrogate measure of a firm’s risk-taking attitude. The content analysis used in the present study is an improvement of Bowman’s (1982, 1984) method in that the selection of words and phrases are based on prospect theory, which facilitates consistency between the measurement and the theory. That is, both the hypothesis and the measurement are based on prospect theory. As a result, the validity of the risk attitude measures should be improved. In addition, all words in the letters to the shareholders were screened, using a computer-aided content analysis technique (the TEXTPACK V software by Mohler and Zuell, 1987). The concept of value as defined in prospect theory can generally be interpreted in terms of negative or positive expectancies, feelings or experiences (Kahneman and Tversky, 1979). The negative ones bring about a risk-taking attitude. Accordingly, the frequencies of three categories of words and phrases that carry the connotations of negative feelings related to losses were counted for each year. As such, the risk attitude measures should have a risk-taking orientation. The first category is perception of losses, and this indicator is named LOSS. The second category is low confidence in future success, which can be explained as a high subjective probability for unfavorable future outcomes. This category expresses overall negative feeling about the future, which can be viewed as the perception of future losses. It therefore, has a strong connotation of losses. This indicator is called NOFUTURE. The third category is overall perception of competition intensity. From a firm’s perspective, more competition means tougher business, which implies that it is more difficult to make profits than if there were less competition; thus, it has a loss connotation. This indicator is labeled COMPET. The Appendix gives examples for the three indicators: LOSS, NOFUTURE, and COMPET. The frequency of each indicator was divided by the number of words in the entire letter to shareholders in each annual report so as to eliminate the size effect of the letters across years. The time-series data of the three indicators comprise the multiple indicator measure for the latent variable, risk attitude (Riskatud). The content analysis dictionary was established in an mteractive way by using the outputs of word/phrase frequency and key-word-in-context (KWIC) that covered all English words contained in the letters. The words/phrases that did not ex-

The Impact of Firms’ Risk-Taking Attitudes

on Advertising

Budgets

press the meanings in accord with the indicators were deleted; the words/phrases that did express the meanings specified by the indicators were added to the dictionary. Both the final dictionaries and KWIC outputs were examined by a native English speaking person with a college education and no knowledge of the research hypothesis. No anomalies were noted. Because a firm’s annual report is a summary of its activities and performance in the past year, the risk attitude measure obtained from content analysis of annual report ensures the correct chronological sequence of measurement for testing the causal model which requires the risk attitude measure be taken subsequent to performance. In addition, the emphasis on losses in establishing the measures for risk attitude with a risk-taking orientation is consistent with managers’ conceptions about risks (chances of losses). In short, the use of content analysis to obtain measures for risk attitude offers advantages of conforming to prospect theory, consistency with managers’ conception of risks, assurance of chronological order of poor performance and risk-taking attitude required in causal framework. Nonetheless, it also renders a major limitation, i.e., small sample size due to restricted availability of annual reports (it ranges from 18 for Olympia to 35 for Anheuser-Busch). This, however, may be considered the cost of obtaining data for a longitudinal study of a firm’s risk attitude which requires a time series measure. Executives of a firm may come and go, but even if they did remain stable over a period of years it seems unlikely that the questionnaire method would appropriately reveal executives’ risk attitudes for past years. Content analysis may be the only way to retrieve a firm’s risk attitude in time series. PERFORMANCE MEASURES. In the risk/return literature, return on equity (ROE) is generally used as a measure of performance; however, unlike well diversified companies, brewing firms mainly run a single-business. Their performance objectives usually include market share, cash flow, etc., in addition to profitability (Day, 1984, p. 62). In this study, both ROE and market share are used as proxies for performance measures and serve as indicators for the construct performance. ADVERTISING BUDGET MEASURES.

The advertising budget set at the end of year (t) is measured by advertising expenditure per beer barrel (ADBL) as recorded at the end of year (t + 1). Here it is assumed that once an advertising budget has been set, managers are not able to obtain extra funds and they will spend all of the budget, therefore the advertising expenditure recorded for year (t + 1) can be used as a proxy for the advertising budget set at the end of the year (t). ADBL in 1986 constant dollars was adjusted by GNP to eliminate the inflation effect.

MEASURES OF CONTROLLING VARIABLES. The model is tested by controlling for the relevant competitive environment so as to rule out confounding effects from competition. Two variables were selected to represent the competitive environment that is associated with firms’ advertising budget. They are: (1) industry average advertising expenditure per barrel (INDADBL)

J Busn Res

D. Y. Lee

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1994:31:247-256

for six measured media (magazines, network TV, spot TV, sport radio, newspapers, and outdoor advertising) in 1986 constant dollars adjusted by GNP, similar to firms’ advertising budgets. This measure used the data recorded at the end of year (t + 1); and (2) a four-firm concentration ratio at year (t) (CONCENT). Price is not used as a variable for controlling competition As pointed out by Scherer (1980) price competition in an oligopoly is often avoided due to the interdependence among firms. These two variables can be justified as below. Lilien et al. (1992, p. 278) have pointed out that competitiveparity is one of the most common methods used by companies when making advertising budget decisions. INDADBL is used to represent this competitive-parity or “me-too” effect. While “advertising intensity is more likely to increase with increase in concentration” (Ferguson 1974, p. 24) the beer industry’s four-firm sales concentration ratio increased form 40% in 1967 to 63% in 1977 (Keithahn, 1978). The four-firm sales concentration ratio (CONCENT) is used to represent this effect. In addition to those variables related to competition, annual beer sales in 1986 constant dollars (SALES) is used as another control variable, since, it is widely reported that there is a close relationship between sales and advertising budget. For instance, Broadbent (1988) reported: “The advertising to sales ratio is the most common method used [for] advertising budgetsetting.” Sales recorded at the end of year (t + 1) is used here so as to be consistent with this sales-ratio-practice of advertising budget setting. IN LINE WITH PROSPECT THEORY. In model testing, the percentage changes of ROE, ROECH (ROECH = [ROE(t) - ROE(t - l)]/Absolute value of ROE[t - 11) and market share, MSCH (MSCH - [MKTSHARE(t) - MKTSHARE(t l)]/MKTSHARE[t - 11) are used as the indicators for the latent variable performance change (Perfh). This method of transforming variables is consistent with prospect theory, which requires outcomes be expressed as deviations from a reference point. Here the reference point is taken to be the previous year’s performance level. The percentage change of ADBL, ACBLCH (ADBLCH [ADBL(t + 1) - ADBL(t)]/ADBL[t]) is used to reflect the advertising budget setting as a comparison process in which a firm compares the advertising budget of year (t + 1) with that of year (t). The two variables associated with the competitive environment (INDADBL and CONCENT) are also represented by percentage changes as INDADCH and CONCENCH (INDADCH [INDADBL(t + 1) - INDADBL(t)]/INDADBL(t), CONCECH [CONCENT - CONCENT(t - l)]/CONCENT[t - 11) to reflect the volatility of the competitive environment. Percent change of beer sales (SALESCH) is obtained similarly (SALESCH [SALES(t + 1) - SALES(t)]/SALES[t]). VARIABLE TRANSFORMATION

Data Performance (ROE and market share) and beer sales data for brewing firms were extracted from the COMPUSTAT tape of

Standard & Poor’s Inc., Moodys’ Industrial Manual, and Standard & Poor’s Industrial Manual. Brewing firms’ advertising expenditures and data of variables pertaining competitive environment were from Keithahn (1978), The Beer Industry (1982) and Beer Industry Update (1983-1988). Measures of risk-taking attitude are obtained from content analysis of brewing firms’ letters to the shareholders of the annual reports. Five brewing firms’ data are usable for testing. They are Anheuser-Busch Companies Inc., Falstaff Brewing Corp., Olympia Brewing Co., Pabst Brewing Co. and Jos. Schlitz Brewing Co..

Estimation Method Partial Least Square Latent Path Model (PUS) is selected in this research because it accommodates small sample size (Wold, 1986, p. 588). Moreover, PI5 gives measurement assessment, which is critical to this study, partially focusing on the development of a new measure. Finally, PLS is a non-parametric model This feature is particularly attractive when there is a small sample size, which may be unable to satisfy any distribution assumption imposed by other causal models that involve latent variables (such as LISREL). Nonetheless, a jackknife procedure packaged in the PLS software (PI&PC, Version 1.8 by Lohmoeller, 1989) calculates the standard deviation for parameter estimates, which generates a t-approximate for parameter estimates. This overcomes the disadvantage of having no formal significance tests for parameters resulting from nonparametric methods. The PIS model is detailed in Bookstein (1982) and Fornell and Wold (1982). LISREL (Linear Structural Relation) model is another wellknown technique that is able to deal with latent variables and assess measurement errors. It, however, can not be used in this study because it requires a sample size of at least 50 (Hair, Anderson, Tatham and Black, 1992, p. 444). The PLS model includes a structural (or inner-) relation and a measurement (or outer-) relation. A construct can be defined as one of the two modes in the measurement relation (i.e., a reflective mode or a formative mode). The reflective mode is used for a construct that is viewed as the underlying factor giving rise to the observables, such as attitude and personality, whereas the formative mode is used for a construct that is viewed as explanatory combinations of its indicators. The construct in formative mode results from its indicators; examples of formative constructs are marketing mix or marketing strategy (Fornell and Larcker, 1982). The construct risk attitude, consequently, should be in a reflective mode, and performance change should be in a formative mode. Figure 1 shows a preliminary PLS model for Schlitz Brewing Co. (which is the only company whose entire set of annual reports was available to the author). This model is used to test the hypotheses for all five brewing firms. The Bowman hypothesis is illustrated by the path from Pelfch to Riskatud, while the research hypothesis of this study is indicated by the path form Riskatud to ADBHCH. Perfch also has a path to ADBLCH, serving as a control variable for the research

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J Busn Res 1994:31:247-256

The Impact of Firms’ Risk-Taking Attitudes

El

I

LOSS

on Advertising

Budgets

e2 I

i”

NOF'UTUR COMPET .67

.70 r--.55

I->

Riska AVE-.

tud 60

.81

1 Figure 1. PL.5 model for Schhtz Brewing Company. Note: CONCENCH was not sgnificant for any firm, and therefore was deleted from the model

>

INDADCH

ADBLCH Rscp.53 -.40 SALESCH

>

__________ ICONCENCHI____________________> __________

hypothesis. In addition, two variables associated with competition (INDADCH and CONCENCH) and SALESCH have their individual paths toward ADBLCH as well, functioning as control variables for the research hypothesis. The path coefficient

other two firms (Anheuser-Busch and Pabst), the AVEs are below 0.5, which is not satisfactory. For Anheuser-Busch the residual variance (or noise) of the indicator COMPET is almost loo%, this indicator essentially only gives noise; for Pabst the

between INDADCH and ADBLCH is expected to be positive according to competitive-parity hypothesis (Little et al. 1992) and that between CONCENCH and ADBLCH is also expected

indicator LOSS contains 97% of its variance as noise. These signify that the indicators of Riskatud for these two firms need to be adjusted by deleting the one that delivers too much noise. It is also interesting to observe that all the loadings of Riskatud for each firm have the same signs, indicating that all the three indicators (LOSS, NOFUTURE, and COMPET) communicate

to be positive in line with Ferguson (1974). No specific tionship between Perfh and ADBLCH is hypothesized.

rela-

Results CONCENCH

was not significant

for any of the five firms, which

is not unexpected. This is an industry parameter whose variance is generally lower than those in within-firm variables; in addition, this variable is relatively remote from firms’ advertising budget setting; therefore. does not offer sufficient information to explain a firm’s changes in advertising budgets. As a result, it was deleted from the PLS model. Table 1 lists the loadings, measurement errors and reliabilities for all five firms. The reliability of a construct in reflective mode such as risk attitude (Risk&u& here, as suggested by Fornell and Lacker (1981) is represented by average variance extracted (AVE). The AVEs for three firms are well above 0.5 (0.76 for Falstaff, 0.61 for Olympia and 0.60 for Schlitz), demonstrating that the construct Riskatud for these three firms has caught the majority of the variances in its indicators; however, for the

negative feelings and according prospect theory the risk attitude has a risk-taking orientation. The reliability of a construct in formative mode such as performance change (Perfch) here is represented by it commonality (see Table l), which indicates the percentage variance caught by the construct from its indicators. The commonality of Perfch of the five firms ranges from 0.44 (for Pabst, the lowest) to 0.65 (for Schlitz, the highest). The two indicators (ROECH and MSCH) for Per$h for three films carry the same signs (positive for Anheuser-Busch and Olympia, negative for Schlitz); however, they are in opposite signs for Falstaff and Pabst. For Falstaff ROECH is the dominating indicator with a loading of 0.96 whereas MSCH delivers 99% of its variance as noise with a loading of -0.10; while for Pabst MSCH is the dominating indicator with a loading of -0.93 and the indicator ROECH has 98% of its variance as noise. These indicate that it may be necessary to adjust the indicators of Pevfh for these two firms. Adjust-

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Table 1. Loadings, Measurement

Errors and R-Squares for Five Firms Falstaff

Busch

Riskatud LOSS NOFUTURE COMPET Reliability (AVE) Perfch ROECH MSCH Reliability (commonality) ADBLCH R-square Note,

Load

-

loadq;

Res

-

Load.

Res.

0.88 0.62 0.01 0.39

0.22 0.61 1.00

0.97 0.23

0.06 0.95

Load.

0.88 0.95 0.76 0 76 0.96 -0.10

Olympia

Schlitz

Pabst

ReS.

Load.

Res.

Load.

Res.

Load.

Res.

0.22 0.09 0.42

0.50 0.89 0.90 0.61

0.76 0.21 0.20

-0.17 -0.50 -0.88 0.35

0.97 0.75 0.23

0.71 0.92 0.67 0.60

0.50 0.16 0.56

0.07 0.99

0.49 1.00

0.76 0.00

0.14 -0.93

0.98 0.13

-0.55 -0.99

0.70 0.00

0.50

0.47

0.62

0.44

0.65

0.34

0.31

0.23

0.36

0.53

residual

variance;

AVE

-

average

variance

extracted

ment of the indicators for constructs Riskatud and Perfch will be discussed shortly. Table 1 also shows R-squares for the dependent variable ADBLCH. The R-square for ADBLCH reveals the percentage variance of ADBLCH that is explained by the variances in its independent variables (refer to Figure 1). It ranges from 0.23 for Olympia (the lowest) and 0.53 for Schlitz (the highest). They are deemed to be satisfactory, as indicated by Fornell, Tellis and Zinkhan (1982). Table 2 illustrates the path coefficients for all five firms. All the coefficients of “Perfch-‘Risk&d” are significant at a level better than 0.05 and support the Bowman Hypothesis. For Anheuser-Busch, Falstaff (with ROECH positive and dominating) and Olympia both the loadings of Riskatud and Pellfch are positive; therefore, the negative path coefficients (-0.294 for Anheuser-Busch, -0.427 for Falstaff and -0.759 for Olympia) support the Bowman hypothesis. For Pabst both the loadings of Riskatud and Perfch (with MSCH negative and dominating) are negative, consequently the negative path coefficient

(-0.628) supports the Bowman hypothesis. For Schlitz the loadings of Riskatud and Perfh are opposite in signs; therefore, the positive coefficient (0.698) supports this hypothesis. Among the path coefficients “Riskatud+ADBLCH” for the five firms three of them (Falstaff, Pabst and Schlitz) are significant and support the research hypothesis, that is, the more risktaking a firm is the more it spends on advertising. For Falstaff and Schlitz, this is demonstrated by both the loadings of Riskatud and the path coefficients being positive (0.189 for Falstaff with significance at 0.10,0.809 for Schlitz with significance at 0.05). For Pabst, it is indicated by both the negative loadings of Riskatud and path coefficient (-0.534 with significance at 0.05). Analogous with the most conventional way of testing regression coefficients, that assumes a two-tail test, we may assume that there is an equal chance for these coefficients to be positive, negative and insignificantly different from zero, the Bernolli trial with one-third success rate gives a significance level better than 0.05 for the research hypothesis to be refuted. Table 2 also describes the relationships between ADBLCH

Table 2. PLS Path Coefficients for Five Beer Firms and Revised Models Riskatud

Pertich

INDADCH

I

I

I

Riskatud

SALESCH

Perfch

I

ADBLCH

Anheuser Busch (revised model)

-0.294* c-0.264*)

0.048 (0.037)

0.507* (0.492*)

-0.270* (-0.268*)

-0.096 (-0.040)

Falstaff (revised model)

-0.427* (-0.343*)

0.189** (0.218*)

0.419* (0.411*)

-0.014 (-0.018)

-0.462* (-0.508*)

-0.246*

-0.759*

-0.169

0.399*

-0.628* (-0.540*)

-0.534* c-0.492*)

0.124 (0.160)

0.698*

0.809*

0.263*

Olympia Pabst (revised model) Schlitz Note.

Coeffictents

for any

firm,

with

therefore.

a single was

astertsk deleted

are signtficant from

the model

at a level better

than

0 05, those

wtth

double

astemks

are sigmftcant

0.291* (0.310*) -0.398* at a level better

than

0 10 CONCENCH

-0.176 0.117 (-0.226*+) 0.667* was not sigmficant

254

J Busn Res

The Impact of Firms’ Risk-Taking Attitudes

on Advertising

Budgets

1994:31:247-256

and its control

variables (INDADCH, SALESCH, and Perfch). It is interesting to note that all the coefficients for the path “INDADCH-ABDLCH” are positive and four out of five are significant at 0.05 level. This strongly supports the hypothesis that competitive-parity is one of the most common methods used by firms to set their advertising budgets (Lilien et al., 1992); however, the common belief that most firms use a percentage of sales for determining their advertising budgets, as reported by Broadbent (1988) is not supported by the data from brewing industry. Three out of five firms (Anheuser-Busch, Olympia and Schlitz) show a negative relationship (significant at 0.05) and one firm (Pabst) shows a significant (at 0.05 level) positive relationship between sales and advertising spending. There was no expectation for the relationship between performance and advertising budget; and the results do not display a clear pattern. As indicated earlier, the reliabilities for Anheuser-Busch, Falstaff and Pabst are not satisfactory, signifying a need to adjust the indicators for the constructs Riskatud and Pe$ch. Table 3 gives the results from the revised models, which are obtained by deleting COMPET and MSCH for Anheuser-Busch, MSCH for Falstaff, and LOSS and ROECH for Pabst. It can be seen that the reliability (AVE) for RIskatud is significantly improved for Anheuser-Busch and Pabst after deleting one indicator in this construct (AVE is increased to 0.62 from 0.39 for AnheuserBusch and increased to 0.52 from 0.39 for Pabst). The R-squares for ADBLCH have also improved, comparing the results before indicator adjustments. The path coefficients from the revised models are listed in the parentheses in Table 2. We can observe, by comparing the coefficients of the three firms before and after adjustments, that the general picture of the path coefficients remain the same.

Discussion

and Conclusion

The test results using the U.S. brewing firms’ data have supported the research hypothesis: a firm’s advertising budget is an increasing function of its risk-taking attitude. The results for all brewing firms have uniformly supported the Bowman hypothesis, that is, firms will be risk-taking if their

Table 3. Loadings, Measurement Errors and R-Squares for

Revised Models of Three Firms Busch

Riskatud: LOSS NOFUTURE COMPET Reliability CAVE) ADBLCH R-square

Falstaff

Pabst

Load.

Res.

Load.

Res.

Load.

0.84 0.73

0.29 0.47

0.88 0.96 0 75

0.23 0.08 044

-0.61 -0.81

N/A 0.62

0.75

0.33

0 38

Res.

N/A

0.52 0.40

0.63 0.34

performance levels are below reference points defined here as the previous year’s performance levels. Although all firms show a risk-taking attitude when they have experienced a poor performance, the determinants of risk-taking may be different: Olympia and Schlitz demonstrate risk-taking for both poor ROE and market share performances; AnheuserBusch and Falstaff, however, are only sensitive to ROE; whereas Pabst is only sensitive to market share performance. There seems no clear explanation for these inter-firm differences. Top managers may have changed many times during the two or three decades studied; thereby, changing the risk attitude of the firm over time. Furthermore, different management at different times might place different strategic weights on ROE and market share in their evaluation of performance. It is impossible here to clarify in what way poor ROE may be different from poor market share performance as a determinant of risk-taking attitudes due to the limited number of firms included in this study. This work limits itself to studying the impact of risk attitude on the advertising budget at the firm level, which is an aggregate of advertising budgets of all brands. Brand managers make their decisions on how to spend their shares of the firm’s advertising budget; therefore, the research problem is also embodied in brand managers’ budget decision; this, however, is not considered in this research. Another limitation of this work is the small sample size. Only five firms are included in the analysis and the time series observations are relatively short. Caution is suggested in generalizing the findings of this study. Unlike the firms in the U.S. brewing industry, many firms in other industries are well diversified, where advertising budget decisions are made at the strategic business unit (SBU) level (Day, 1984). Consequently, there may be differences in risk attitudes between the management at the corporate and SBU levels. To the best of my knowledge, this work investigates a firm’s risk-taking attitude on its advertising budgeting for the first time. The results shown here may shed some light to the understanding of some behavioral aspect of a firm’s marketing strategy and the evaluation of its advertising strategy. This study combines two causal hypotheses, that is, poorer performance leads to a higher risk-taking attitude, which in turn leads to a higher advertising budget; hence, can be considered as an extension of the risk/return literature to include the impact of a firm’s risktaking attitude on its strategic decisions, specifically the advertising budget decisions. In studies in the risk/return literature, risk attitude is either not measured or measured in a way inconsistent with prospect theory while seeking to explain the negative relation between risk and return by using prospect theory despite risk attitude being one of the tenets in this theory. This work has explicitly measured a firm’s risk attitude according to prospect theory; therefore, offers consistency between measurement and theory. This can be considered an improvement in the risk/ return literature. Because this study is longitudinal in design and has involved a wide range of environmental conditions over the period from

J Busn Res 1994:31:247-256

D. Y. Lee

1952 to 1986, and five brewing firms with individual characteristics, it has provided some confirmation to reject the notion that the relationships between poor performance and risk attitudes, and risk attitudes and advertising budgets are dependent upon environmental and firm characteristics. Future research is needed to extend the value of the findings of this study across a wider range of industries. In addition, studies that investigate the impact of firms’ risk attitudes on other strategic decisions such as new market entry, price cutting, vertical integration, etc.. are also needed. Finally, there

255

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Appendix. Illustration of Content Analysis Dictionary (Roots of Words)

Fiegenbaum, A., and Thomas. H., Dynamic and Risk Measurement Perspectives on Bowman’s Risk-Return Paradox for Strategic Management: An Empirical Study. Strat. Manage. J. 7 (1986): 395-407.

Explanation

Var. Name LOSS

COMPET

NOFUTURE

Expected or perceived loss (examples: charge, cost, debt, deficit, down, expenses increase, failure, increases in costs, insufficien, lack, los, non-operating expenses, problem, trouble, tax) Aware of competition (examples: advertising, business, campaign, challenge, compet, economy, industry, market, promotion, risk, supplier, wholesaler) No confidence in future success (examples: adverse, concern, decline, difficult, doubt, dubious, moderate, not content, problem)

in

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