The Behavioral and Intermediate Effects of Advertising on Firm Performance: An Empirical Investigation of the Restaurant Industry

Abstract

The purpose of this study was to identify tangible and intangible gains resulting from advertising in restaurant businesses from both the marketing and finance/accounting perspectives. Specifically, this study examined both behavioral and intermediate effects of advertising on consumer behavior and firm performance. Annual sales, profit, Tobin’s Q, and advertising expenditure of 119 restaurant firms from 1991 to 2012 were used for data analysis. The findings revealed that advertising led to an immediate increase in consumer demand, but failed to improve profit. The effect of advertising on sales and profit through brand equity was found to be insignificant. This study suggests a new angle on the use of advertising and brand strategies in the restaurant industry and discusses potential directions for future research.

Keywords

advertising brand equity firm performance panel data analysis

Introduction

Many practitioners in the restaurant industry have agreed that advertising is one of the most effective marketing activities to change consumer behavior and further contribute to firm performance (Hyun, Kim, & Lee, 2011). Thus, it has been witnessed that a significant number of restaurant firms allocate a large portion of their budget to advertising. According to Kantar Media (2013), of the industries that spent the most on advertising in 2012, the restaurant industry ranked ninth ($6.13 billion). Specifically, in 2012 McDonald’s Corporation, Yum! Brands, and Wendy’s Corporation spent the most on advertising in the restaurant industry, reporting expenditures of $957 million, $782 million, and $280 million, respectively. However, despite the growing importance of advertising, the percentage of hospitality marketing studies that focused on advertising has dropped dramatically from 14.5% in the 1990s (Bowen & Sparks, 1998) to 2.1% in the 2000s (Line & Runyan, 2012).

To date, advertising studies have primarily employed two approaches. First, they have focused on the ways that advertising influences consumer behavior from a psychological perspective. For example, Hyun et al. (2011) indicated that advertising positively affects consumers’ purchase intentions by increasing their perceived utilitarian and hedonic value. Homer (2006) reported that brand familiarity has a significant impact on the relationship of advertising-induced affects and attitudes toward brands. Second, many advertising studies have investigated the impact of advertising on the accounting and finance aspects. The roles of advertising in value creation and risk reduction processes are the primary topics in accounting/finance literature. For example, Hsu and Jang (2008) showed a positive relationship between advertising and intangible value in the restaurant industry. McAlister, Srinivasan, and Kim (2007) found that advertising significantly lowers a firm’s systematic risk. Other examples include Andras and Srinivasan (2003), Han and Manry (2004), and Luo and de Jong (2012).

Marketing studies have addressed individual consumers’ cognitive, affective, and behavioral changes due to advertising. Accounting/finance studies have practically measured the economic gains created by consumers as a whole. What is the linkage between individual consumer’s attitudinal and behavioral changes and a business’s financial gains? How does such a linkage explain the short-term and long-term effects of advertising on the business? How does the linkage justify the tangible and intangible assets of the business? Hyman and Mathus (2005) suggest that only the strategic integration of the two approaches can answer these questions and comprehensively explain the impact of advertising. However, to the best of the authors’ knowledge, only very sporadic research has focused on advertising’s influences from a multidisciplinary perspective that addresses both marketing and accounting/finance aspects.

A conceptual study of Vakratsas and Ambler (1999) suggested two types of advertising effects on consumer behavior and firm performance: behavioral and intermediate. Behavioral effects indicate that advertising produces immediate shifts in consumer purchase and product selection (Wang, Zhang, & Ouyang, 2009). Changes in brand choice have a significant impact on many measures of firm performance such as sales volume (Givon & Horsky, 1990; Joshi & Hanssens, 2010) and market share (Wang et al., 2009). Although the overall effect of advertising on firm performance is persistent, behavioral effects dissipate in 3 to 15 months (Assmus, Farley, & Lehmann, 1984; Vakratsas & Ambler, 1999). Intermediate effects suggest that advertising leads to changes in consumers’ mindset prior to behavioral responses (Vakratsas & Ambler, 1999). When consumers are exposed to advertising, they acquire perceptions or generate mental images of advertised brands (Keller, 1993). The brand image, in turn, improves firm performance through increased brand awareness and favorable brand attitude (Ailawadi, Lehmann, & Neslin, 2003; Srivastava & Shocker, 1991). Unlike behavioral effects, intermediate effects tend to be sustainable and cumulative because consumer perception is persistent and thus the perception associated with brands decays slowly influencing consumer choice over time (Wang et al., 2009).

In the analysis above, behavioral and intermediate effects cooperatively explain the role of advertising in producing tangible (firm financial performance) and intangible (brand equity) gains from the interdisciplinary perspective of marketing and accounting/finance. These effects not only show the direct and indirect paths of advertising’s impact on firm performance, but also explain how advertising has a persistent effect on firm performance over time. However, to the best of the authors’ knowledge, intermediate and behavioral effects of advertising have not been simultaneously tested, especially in the restaurant industry. The purpose of this study is to fill this gap by investigating advertising and its behavioral and intermediate effects on the restaurant businesses. Specifically, this study evaluates the role of brand equity between advertising and firm financial performance.

This study pioneers the investigation of the effects of advertising across the marketing and accounting/finance areas in restaurant research. This study sheds new light on how advertising has contemporaneous and lagged effects on brand equity and firm financial performance, which could allow marketers to develop short- and long-term advertising strategies and effectively allocate resources and maximize their organizational benefits.

Literature Review

Vakratsas and Ambler (1999) proposed two different approaches to explain the effects of advertising on consumer purchase behavior: behavioral and intermediate effects. The combination of these two effects has the potential to capture the effectiveness of advertising in creating substantial outcomes. Moreover, it addresses the persistent effect of advertising over time by separating contemporaneous impacts from lagged ones. The following discussion provides details regarding behavioral and intermediate effects.

Behavioral Effect of Advertising

Behavioral effect explains the instant consumer response to advertising, which shows the direct influence of advertising on a firm’s financial performance, including sales and market share (Wang et al., 2009). Many scholars (e.g., Chen & Lin, 2013; Luo & de Jong, 2012; Tellis, 2010) argue that advertising enhances market awareness and consumer preference, which in turn generates greater consumer demand and ultimately increases sales. Srinivasan, Vanhuele, and Pauwels (2010) noted that advertising helps increase cash flow by promoting product awareness. Increased demand for advertised products can lessen fluctuations in cash flow caused by business cycles and seasonality (Jose, Nichols, & Stevens, 1986; Wang et al., 2009). These benefits offered by advertising allow firms to create higher economic value. Specifically, Park and Jang (2012) have identified the significant influence of advertising on sales growth in the context of the restaurant industry.

The other major influence of advertising on firm financial performance is on profitability. Increased demand for products induced by advertising enables firms to achieve economies of scale in production which result in lower production cost per unit (Jose et al., 1986). High profits, in turn, allow the firms to spend more on advertising. The huge advertising expenditures of current businesses may serve as an entry barrier for new comers in the marketplace in order to protect their profitability (Jose et al., 1986; Zulfiqar, Shah, & Akbar, 2008). Several previous studies (e.g., Notta & Oustapassidis, 2001; Pritchett, Liu, & Kaiser, 1998) found that the effects of advertising on profitability vary depending on the media used (e.g., television, radio, newspaper, magazines). While many scholars (e.g., Andras & Srinivasan, 2003; Graham & Frankenberger, 2000) found a positive influence of advertising on firm profitability, others (e.g., Reekie & Bhoyrub, 1981; Ventoura-Neokosmidi, 2005) did not find such relationship. Other studies (e.g., Boyer, 1974; Greuner, Kamerschen, & Klein, 2000) suggested that advertising negatively affects profitability. For example, Greuner et al. (2000) found that advertising by an automobile firm has a significantly negative effect on its profitability. They concluded that three rival automobile firms failed to improve their profitability by increasing their advertising expenditure. In short, the effect of advertising on profitability remains controversial in the marketing area.

As discussed above, the positive effect of advertising on sales has been proven consistently, but these increased sales do not always translate into higher profits since advertising is carried as an expense in the accounting system. Because sales measures firm performance without considering expense, the relationship between sales and advertising shows only how effective advertising is in generating consumer demand. On the other hand, the relationship between profit and advertising shows advertising’s cost effectiveness in creating net organizational benefit. Although spending on advertising can increase sales, excessive spending may often results in lowering profit by increasing total costs (Ventoura-Neokosmidi, 2005). Moreover, when advertising provides consumers with product information such as price and quality, consumers have more product alternatives, and accordingly the marketplace becomes more competitive and firm profitability in the marketplace may decrease (Greuner et al., 2000).

Behavioral effects, as discussed above, tend to be short-lived and are relative to changes in consumer demands. The short lifespan of behavioral effects has been confirmed in previous studies. For example, Wang et al. (2009) applied market response models to examine the behavioral effect of advertising. Market response models have been extensively used to examine consumers’ collective responses to marketing activities (Hanssens, Leeflang, & Wittink, 2005). The models directly link advertising and financial measures without consideration of intermediate effect. Through a meta-analysis of sales response models in 91 studies, Leone (1995) investigated the average duration of advertising effect on consumer goods industries including coffee, tea, gas, liquor, cigarettes, and food. His findings showed that advertising is effective on sales for 6 to 9 months. Using the same analysis technique, Assmus et al. (1984) investigated 128 models from 22 studies and found that most effects of advertising (90%) persist for 3 to 15 months. Finally, Bagwell (2007) reviewed a significant number of studies on advertising and summarized that advertising is significantly associated with sales growth, but the duration of this effect is less than 1 year.

Intermediate Effect

Intermediate effect describes that advertising exposure causes sensory and intellectual events in the consumers’ mind-set, which consequently brings to consumers’ minds symbolic and affective wealth around brands—namely, brand equity (Arvidsson, 2006; Srinivasan et al., 2010). Brand equity is defined as “marketing outcomes that accrue to a product with its brand name” (Ailawadi et al., 2003). In order words, brand equity is the net value of benefits that branded products have compared to unbranded ones (Barth, Clement, Foster, & Kaszink, 1998). As a type of intangible asset, brand equity intermediates between marketing activities and tangible gains represented by firm performance (Peterson & Jeong, 2010). Many scholars (e.g., Keller, 2002; Luo & de Jong, 2012) agree that brand equity influences consumer loyalty, inelastic consumer response to price increases, marketing communication efficiency, and brand extension opportunities. However, other studies have shown opposite results. For example, Wang et al. (2009) determined that advertising persistently but negatively affects brand equity in 10 industries, including the operative builder industry and the furniture industry. They argue that in a highly competitive market environment, increased advertising expenditure can impair advertising effectiveness and damages a firm’s brand equity, since competitors are likely to strike back in the advertising war, which neutralizes the effects of the firm’s advertising.

In contrast with the short life of behavioral effects, intermediate effects are lagged since consumer attitude toward a brand experiences a progressive change over time (Chauvin & Hirschey, 1993; Hirschey, 1982). This lagging of intermediate effects suggests that advertising expenditures can be realized as an investment in intangible assets since advertising can affect a firm’s financial performance over the long term (Hsu & Jang, 2008; Peterson & Jeong, 2010). According to the matching principle of accounting, expenses should be matched with revenue generated by those expenses. This principle supports the argument from many scholars that advertising expenditure should be amortized over its productive period since it can contribute to revenue over a period of years. In this respect, it is reasonable for advertising expenditures to be allocated to the periods during which the assets are used for revenue generation, similar to other intangible assets (e.g., patents, goodwill).

Advertising, Brand Equity, and Firm Performance

Consistent with the discussions above, the indirect effect through brand equity between advertising and firm performance has been controversial in marketing studies. One point of view supports the positive mediation role of brand equity. For example, Peterson and Jeong (2010) confirmed the impact of advertising and research and development expenditures on firm performance through brand equity. Joshi and Hanssens (2010) investigated the effect of advertising in five leading PC manufacturing firms and four sporting goods firms (e.g., Dell, Nike) on firm performance. Their results showed that advertising is significantly related to increased sales growth and stock returns. They further suggested that the positive relationship between the three constructs is created both directly and indirectly through intangible asset including brand equity. Kim, Kim, and An (2003) suggested that strong brand equity can lead to a significant increase in sales in the lodging businesses. However, other researchers gave contradictory opinions on the relationship between advertising, brand equity, and firm performance. For example, Chu and Keh (2006) found the effects of advertising and promotion on brand equity to be negative but insignificant. In particular, when firms have a promotion budget of less than $200 million, their promotion expenditure is negatively related to brand equity. Eng and Keh (2007) showed that firms with strong brand power experience a reduction in profit margin when their advertising expenditure increases. This negative relationship can be explained by the informational view of advertising (Nelson, 1974; Stigler, 1961; Telser, 1964). This view speculates that since advertising provides consumers with various types of product information (price, quality, availability), it increases consumers’ price sensitivity and reduces brand loyalty. These changes in consumer attitude facilitate healthy market competition by lowering product prices. Empirically, many studies have found that advertising enhances price sensitivity among consumers (e.g., Chakravarti & Janiszewski, 2004; Eskin & Baron, 1977; Kanetkar, Weinberg, & Weiss, 1992; Mitra & Lynch, 1995). In particular, Kaul and Wittink (1995) reviewed 18 relevant studies on advertising and concluded that advertising leads to a reduction in product price.

Based on the above discussions, this study proposes a conceptual model which explains the relationship between advertising, brand equity, and firm financial performance in the restaurant industry. The model simultaneously represents contemporaneous behavioral effects and lagged intermediate effects of advertising. Figure 1 shows the conceptual model.

Figure 1

Proposed Research Model

Methodology

Data

Data from U.S. public restaurant firms under standard industrial classification (SIC) 5812 from 1991 through 2012 was derived from the Compustat database which offers financial, statistical, and market information about both public and private firms throughout the world. After excluding 126 restaurant firms due to data unavailability, a total of 119 restaurant firms were included in the final sample. The annual data on sales, profit, Tobin’s Q, and advertising expenditure for all 22 years were used in the study. All observations with missing values on any variable in the theoretical model were deleted in the data analysis.

Variables

The description of variables is given in Table 1. Tobin’s Q, the ratio of the market value of a firm’s assets to their replacement cost, was used to estimate firm brand equity in this study. A large body of literature has employed Tobin’s Q as a proxy for firms’ intangible assets (Joshi & Hanssens, 2010; Park & Jang, 2012). Intangible assets represented by Tobin’s Q include brand equity, firm-specific factors not related to brand equity, and market-specific factors that drive imperfect competition (Anderson, Fornell, & Mazvancheryl, 2004; Simon & Sullivan, 1993). Wang et al. (2009) investigated the relationship between brand equity and advertising using Tobin’s Q as a measure of brand equity. Their model focused on brand equity as a part of firms’ intangible assets by controlling for firm- and market-specific factors. Following Wang et al.’s (2009) study, we used Tobin’s Q as an endogenous variable to represent brand equity and calculated Tobin’s Q based on the technique proposed by Chung and Pruitt (1994).

Table 1

Descriptions of Variables

Variable	Description
Advertising Expenditure	Annual advertising expenditure of a firm, which is calculated as the sum of the cost of advertising media including radio, television, and periodicals, and promotional expenses
Tobin’s Q	Annual Tobin’s Q of a firm which is calculated as follows: [stock price * number of common stock outstanding + liquidating value of preferred stock + (current liabilities − current assets) + book value of inventories + long-term debt]/book value of total assets
Sales	Annual sales of a firm
Sales Growth	Annual sales growth rate which is calculated by dividing sales in current year by sales in previous year
Profit	Annual profit of a firm
Profit Growth	Annual profit growth rate of a firm which is calculated by dividing profit in current year by profit in previous year
Market Share	Percentage in the overall market of the restaurant industry that a firm accounts for, which is calculated as the ratio of the firm’s sales to total industry sales
Industry Size	Total annual sales of restaurant firms with SIC 5812
Industry Growth	Annual industry size growth rate which is calculated by dividing industry size in current year by industry size in previous year
Industry Competition	Ratio of top four firms’ sales to total industry sales

This study considered three individual firm variables and three industry-related variables to control for firm and market-specific effects, respectively. Because the control variables are related to product market and intangible assets not associated with brand equity (Wang et al., 2009), capturing the effect of the control variables allows this study to reveal the true correlation between brand equity, advertising and firm performance. The three firm-specific control variables are market share, sales growth, and profit growth. Market share was calculated as the ratio of each restaurant firm’s sales to the total industry sales (combined sales of all restaurant firms classed as SIC 5812). Sales growth was calculated as the difference in a restaurant firm’s sales between the current and previous years divided by the previous year’s sales. Profit growth was calculated as profit of the current year divided by profit of the previous year. The three industry-related variables are industry size, industry growth, and industry concentration. Industry size was the total sales of restaurant firms classed as SIC 5812. Industry growth was measured by the annual rate of change in industry size. Industry concentration served as an indicator of industry competition and was calculated as the total sales of the top four restaurant firms divided by total industry sales (Rao, Agarwal, & Dahlhoff, 2004). This study used multiple measures of firm performance to shape the proposed theoretical model. Specifically, this study used annual firm sales and profit as dependent variables.

Model Specification and Estimation

A structural model was developed based on dynamic panel data analysis to explore the behavioral effects of advertising on firm performance and intermediate effects through brand equity, while controlling for firm- and market-specific factors. The relationship between logarithmically transformed advertising expenditure (AD) and brand equity (BE) represented by Tobin’s Q is specified in Equation 1. Current ( ${AD}_{i t}$ ) and two lagged ( ${AD}_{i t - 1}$ and ${AD}_{i t - 2}$ ) advertising expenditures were included. The lag length was determined based on model and moment selection criteria, which was developed by Andrew and Lu (2001) for GMM estimation because widely used lag length selection criteria such as Akaike information criterion and Bayesian information criterion cannot be used in GMM context. Equation 2 gives logarithmically transformed annual sales (SA) as a function of advertising expenditure (AD) and brand equity (BE). Equation 3 gives the effect of advertising (AD) and brand equity (BE) on profit (PF). For the structural model, we assumed that behavioral effects of advertising occur contemporaneously whereas intermediate effects through brand equity are lagged. These structural equations were extended to include autoregressive (AR) terms (e.g., SA_i,t−1) and individual firm variables (v_i) to capture the impact of autocorrelation and time-invariant firm effects, respectively. Finally, market share (MS), sales growth (SG), profit growth (PFG), industry size (IS), industry competition (IC), and industry growth were used as control variables to capture the unique effects of brand equity (BE).

{BE}_{i t} = α_{0} + α_{1} {BE}_{i t - 1} + α_{2} {ln AD}_{i t} + α_{3} {ln AD}_{i t - 1} + α_{4} {ln AD}_{i t - 2} + α_{5} {MS}_{i t} + α_{6} {ln SG}_{i t} + α_{7} {PFG}_{i t} + α_{8} {ln IS}_{i t} + α_{9} {IG}_{i t} + α_{10} {IC}_{i t} + v_{i}^{B E} + ϵ_{i t}^{B E}

{ln SA}_{i t} = β_{0} + β_{1} {ln SA}_{i t - 1} + β_{2} {ln AD}_{it} + β_{3} {BE}_{i t - 1} + β_{4} {MS}_{i t - 1} + β_{5} {ln SG}_{i t - 1} + β_{6} {PFG}_{i t - 1} + β_{7} \ln {IS}_{i t - 1} + β_{8} {IG}_{i t - 1} + β_{9} {IC}_{i t - 1} + v_{i}^{R E V} + ϵ_{i t}^{R E V}

{PF}_{i t} = γ_{0} + γ_{1} {PF}_{i t - 1} + γ_{2} {ln AD}_{i t} + γ_{3} {BE}_{i t - 1} + γ_{4} {ln SA}_{i t} + γ_{5} {MS}_{i t - 1} + γ_{6} {ln SG}_{i t - 1} + γ_{7} {PFG}_{i t - 1} + γ_{8} {ln IS}_{i t - 1} + γ_{9} {IG}_{i t - 1} + γ_{10} {IC}_{i t - 1} + v_{i}^{N I} + ϵ_{i t}^{N I}

To estimate the structural equations above, this study converted Equations 2 and 3 into Models 2 and 3 by substituting brand equity (BE) in Equations 2 and 3 with Equation 1 under the assumption of independence of error terms. Because there is no correlation among error terms in the structural equations, this study can compute consistent coefficients by estimating equation by equation (Green, 2008). In the estimated models, the impact of current AD ( ${AD}_{i t}$ ) on sales (SA) or profit (PF) was examined for behavioral effect (which generally decays within 1 year) and intermediate effect (which sustains for a relatively longer time period) was tested by investigating the combination effect of lagged ADs ( ${AD}_{i t - 1}$ ${AD}_{i t - 2}$ and ${AD}_{i t - 3}$ ) divided by the AR term. As a result of the substitution of BE in Equations 2 and 3 by Equation 1, the lagged ADs ( $A D_{i t - 1}$ $A D_{i t - 2}$ and $A D_{i t - 3}$ ) were placed in Models 2 and 3. Since AD was the explanatory variable of BE in Equation 1, the coefficients of the lagged ADs ( $A D_{i t - 1}$ , $A D_{i t - 2}$ , and $A D_{i t - 3}$ ) showed intermediate or indirect effects of advertising through BE.

{BE}_{i t} = α_{0} + α_{1} {BE}_{i t - 1} + α_{2} {ln AD}_{i t} + α_{3} {ln AD}_{i t - 1} + α_{4} {ln AD}_{i t - 2} + α_{5} {MS}_{i t} + α_{6} {ln SG}_{i t} + α_{7} {PFG}_{i t} + α_{8} {ln IS}_{i t} + α_{9} {IG}_{i t} + α_{10} {IC}_{i t} + v_{i}^{B E} + ϵ_{i t}^{B E}

{ln SA}_{i t} = θ_{0} + θ_{1} {ln SA}_{i t - 1} + θ_{2} {ln AD}_{i t} + θ_{3} {ln AD}_{i t - 1} + θ_{4} {ln AD}_{i t - 2} + θ_{5} {ln AD}_{i t - 3} + θ_{6} {BE}_{i t - 2} + θ_{7} {MS}_{i t - 1} + θ_{8} {ln SG}_{i t - 1} + θ_{9} {PFG}_{i t - 1} + θ_{10} \ln {IS}_{i t - 1} + θ_{11} {IG}_{i t - 1} + θ_{12} {IC}_{i t - 1} + ζ_{i}^{S A} + e_{i t}^{S A}

{PF}_{i t} = τ_{0} + τ_{1} {PF}_{i t - 1} + τ_{2} {ln AD}_{i t} + τ_{3} {ln AD}_{i t - 1} + τ_{4} {ln AD}_{i t - 2} + τ_{5} {ln AD}_{i t - 3} + τ_{6} {ln SA}_{i t} + τ_{7} {BE}_{i t - 2} + τ_{8} {MS}_{i t - 1} + τ_{9} {ln SG}_{i t - 1} + τ_{10} {PFG}_{i t - 1} + τ_{11} {ln IS}_{i t - 1} + τ_{12} {IG}_{i t - 1} + τ_{13} {IC}_{i t - 1} + ζ_{i}^{N I} + e_{i t}^{N I}

Although the endogenous variables are not correlated with error terms, the structural model might still have an endogeneity problem caused by time-invariant firm characteristics and lagged dependent variables. In particular, a short timespan of the panel data set combined with a large quantity of observations may lead to a correlation between lagged dependent variables and error terms, creating biased estimates of the coefficients of the lagged dependent variables (Wooldridge, 2012). Accordingly, when the time period for a panel data set is insufficient, use of ordinary least squares estimator, generalized least squares estimator, or fixed effect model are not recommended because they yield inconsistent estimates (Cameron & Trivedi, 2009; Green, 2008). Consequently, this study used system generalized method of moments (GMM) technique based on the approach of Arellano and Bover (1995) and Blundell and Bond (1998) to construct consistent estimates for dynamic panel data model.

The models estimated in the GMM context addressed endogenous problems that might arise from estimating dynamic structural equations (Elitz, 2007). GMM estimation allows the expected value of the product of independent variables and error terms to be zero or close to zero by using instrument variables and minimizing objective function. Because these moment conditions are solved, the independent variables substituted by instrument variables are not correlated with error terms and accordingly GMM model will be free of endogenous problems. System GMM estimation uses both first-differenced and level data as instruments and is considered more efficient than difference GMM estimation of Arellano and Bond (1991), in particular when variables follow a random walk pattern (Wooldridge, 2012). Also, this study used two-step estimation that yields more efficient coefficients than first step estimation. Robust variance-covariance metrics were estimated in order to correct any downward bias that might be present in the two-step GMM estimation (Windmeijer, 2005). Finally, we investigated the validity of the estimated structural model. Arellano and Bond’s (1991) test was employed to examine the serial correlation in error terms. The validity of the overidentified instrument variables was tested using Hansen’s test (Green, 2008).

Results

Descriptive statistics of the data are shown in Table 2. The restaurant industry grew by an average of 5% every year in the 22-year time period under study. Annual sales growth (SG) and profit growth (PFG) were 26% and 2%, respectively. The industry concentration (IC) was .47 on average, meaning that the top four restaurant firms in terms of sales accounted for 47% of the overall sales in the restaurant industry. The average annual advertising expenditure (AD) was $33.28 million and the average profit (PF) was $45.70 million, signifying that advertising expenditure (AD) was more than 70% of profit (PF) in the restaurant industry.

Table 2

Descriptive Statistics of Variables

Variable	Mean	SD
Advertising Expenditure (AD)	33.28	94.95
Tobin’s Q (BE)	2.11	4.35
Sales (SA)	845.69	2,518.50
Sales Growth (SG)	0.26	1.87
Profit (PF)	45.70	294.31
Profit Growth (PFG)	0.02	12.63
Market Share (MS)	0.01	0.02
Industry Size (IS)	84,125.87	35,340.57
Industry Growth (IG)	.05	0.04
Industry Competition (IC)	.47	0.02

Note: Units of AD, SA, PF, and IS are U.S. million dollars.

Table 3 presents the estimation results of Models 1, 2, and 3. Arellano-Bond and Hansen tests showed that the structural equations had neither serial correlations nor overidentification problems. The coefficient for current advertising expenditure in Model 1 was significantly negative (β = −.35, p < .05), indicating that advertising expenditure ( ${AD}_{i t}$ ) had a significant negative impact on brand equity (BE) in the short term after controlling for firm- and market-specific factors. However, the findings also showed that lagged advertising expenditures ( ${AD}_{i t - 1}$ and ${AD}_{i t - 2}$ ) did not influence brand equity (BE).

Table 3

Estimated Coefficients of Variables

Independent Variables	Model 1 (BE)	Model 2 (SA)	Model 3 (PF)
AR term
BE_t−1	0.88** (.000)
SA_t−1		0.63 (.092)
PF_t−1			0.73** (.000)
AD_t	−0.35* (.038)	0.37** (.001)	−60.44** (.000)
AD_t−1	0.26 (.352)	−0.13 (.332)	7.50 (.595)
AD_t−2	0.11 (.602)	−0.06 (.390)	−6.06 (.614)
AD_t−3		0.04 (.590)	−0.50 (.932)
BE_t−2		0.00 (.904)	−6.15 (.281)
SA_t			77.86** (.007)
MS	1.51 (.239)	4.08 (.601)	6271.79** (.000)
SG	0.25 (.351)	−0.00 (.875)	0.03 (0.00)
PFG	0.00 (.537)	−0.00 (.899)	0.25 (.997)
IS	0.03 (.719)	0.18 (.166)	−54.41** (.000)
IG	0.86 (.222)	−0.01 (.938)	−224.76** (.000)
IC	−0.96 (.624)	−0.64 (.600)	584.17* (.012)
Behavioral		0.37** (.001)	−60.44** (.000)
Intermediate		−0.39 (.680)	3.41 (.956)
Arellano–Bond test
AR(1)	−1.84 (.065)	−2.78** (.005)	−1.50 (.131)
AR(2)	0.98 (.327)	−0.96 (.337)	1.36 (.173)
Hansen test	121.92	105.70	110.91

Note: Numbers in parentheses present t statistics.

p < .05. **p < .01.

The findings from Model 2 showed that advertising expenditure (AD) (β = .37, p < .01) in the current year was significantly and positively related to annual sales (SA). It suggests that advertising has behavioral or direct effects on firm sales. This significant result is consistent with that of previous studies (e.g., Duffy, 2001; Park & Jang, 2012). On the other hand, the effect of lagged brand equity ( $B E_{t - 2}$ ) on sales (SA) was insignificant. The findings from Model 3 reported a significantly negative relationship between advertising expenditure (AD) and annual profit (PF) in the current year (β = −60.44, p < .01). This indicates that increased advertising expenditure (AD) reduces profit (PF) in the short term. Current sales (SA) was found to be significantly related to profit (PF) (β = 77.86, p < .01), signifying that an increase in sales led to an increase in profit in the short term. However, the relationship between lagged brand equity ( $B E_{t - 2}$ ), and profit (PF) was negative and not statistically significant.

In Models 2 and 3, coefficients for lagged advertising expenditures ( $A D_{i t - 1}$ $A D_{i t - 2}$ and $A D_{i t - 3}$ ) were insignificantly associated with both sales (SA) and profit (PF). These lagged coefficients were collectively used to show intermediate effect in each Model. Unlike behavioral effect, intermediate effects were insignificant even if advertising (AD) significantly reduced brand equity (BE). This implies that advertising did not affect restaurant sales and profit through brand equity in the long term. Among control variables, market share (MS) (β = 6271.79, p < .01) and industry competition (IC) (β = 584.17, p < .05) both had a significant, positive impact on profit (PF). Industry size (IS) (β = -54.41, p < .01) and industry growth (β = −224.76, p < .01) were significantly, but negatively linked to profit (PF). These findings signified that industry and firm-specific characteristics had a substantial effect on determining profit (PF).

Conclusions and Implications

This study attempted to investigate two ways in which advertising helps restaurant firms earn tangible gains in sales and profit. The first is through behavioral effects, in which advertising directly affects consumer demand and thus results in gains in the short term. The second is through intermediate effects of boosting brand equity over the long term. Our findings indicate a mixed behavioral effect of advertising. Specifically, advertising has a positive effect on sales in a single year but negatively affects profit. On the other hand, the intermediate effect of advertising was proved to be insignificant, which suggests no lagged effect of advertising on sales and profit. Finally, advertising has a significantly negative relationship with brand equity in the short term, but no lagged effect of advertising on sales and profit through brand equity was found after advertising expenditure is considered.

Advertising can generate restaurant sales over the short term after controlling for industrial environments and individual firm effects. This study reported that a 1% increase in advertising spending creates a 0.37% rise in restaurant sales over 1 year. This positive effect of advertising on sales is consistent with a number of previous studies in other industry sectors, such as gas, processed meats, and premium cars (e.g., Crespo-Cuaresma & Stoeckl, 2012; Leach & Reekie, 1996; Yiannaka, Giannakas, & Tran, 2002). These findings support the strategic importance of advertising in facilitating a better and faster cash flow, thus increasing organizational benefits. Advertising can serve as a positive signal to consumers and investors of a firm’s investment in its products and financial condition, respectively (Chauvin & Hirschey, 1993; Joshi & Hanssens, 2010). According to the signal effect, individuals are likely to purchase products or stocks of firms whose brands are highly visible through advertising because advertising signifies their product quality and strong financial health (Chemmanur & Yan, 2009). The significant increase in demand resulting from advertising in the present study confirms the signaling effect.

By contrast, the present study also showed that advertising has a negative impact on restaurant firm profit in the short term. Empirically, the negative relationship between advertising and profitability is in accordance with other previous studies (e.g., Boyer, 1974; Greuner et al., 2000). This result can be understood within the context of accounting. The current U.S. accounting system recognizes advertising as an expense rather than an asset-generating investment (Zulfiqar et al., 2008). Because of all spending on advertising in a certain period must be recorded as marketing-related expenses in the income statement for the given period, it is deducted from the operating profit. Accordingly, an increase in advertising spending lowers profit in most cases. By combining the behavioral effects on sales and profit, we found that even if advertising triggers a significant rise in consumer demand, restaurant firms cannot earn profit from their advertising unless increased advertising costs are less than the gains achieved through greater consumer demand. Also, the industry environment may make it more difficult for restaurant firms to generate profit from their advertising. Competitive industries with a high level of advertising clutter (such as the restaurant industry) rarely see rapid climbs in consumer demand over a short period of time (Jose et al., 1986; Wang et al., 2009). Thus, additional advertising expenditure is likely to drive down overall profitability in restaurant businesses.

The mixed behavioral effect of advertising has implications for the allocation of advertising. The neutral or negative effect of advertising on profit suggests that restaurant firms should carefully allocate their advertising budget according to their financial goals. For example, in order to raise profit, restaurant firms need to address different aspects of their advertising budget rather than simply increasing the size of advertising expenditure. Although the total advertising budget is important, according to D’Souza and Allaway (1995), the proper allocation of advertising dollars between different product lines, and categories is essential in insuring economic benefits. On the other hand, the findings regarding behavior effect on sales indicate that restaurant firms can achieve their sales or market share goals in the short term by increasing advertising expenditure.

This study investigated the relationship between advertising, brand equity, and firm performance through an analysis of intermediate effect and found a significantly negative effect of advertising on brand equity in the short term. However, the intermediate effect of advertising on firm sales and profit via brand equity was found to be insignificant. Advertising expenditures reported on financial statements includes both advertising and promotional spending (Conchar, Crask, & Zingkhan, 2005). Therefore, in the database used in this study, advertising activities were combined with sales promotions. Sales promotions are one component of in the promotional mix in marketing whereby consumers are given an enticement to make an immediate purchase (Morrison, 2009). Widely used sales promotion practices in the restaurant industry (Kendrick, 1998; Kim, Kim, & O’Neill, 2013; Stassen & Mittelstaedt, 2002). These frequent and intensive deals run the risk that consumers will permanently undervalue the company, its products, and its services. Thus, sales promotions generally do not contribute to long-term superior financial performance (Jedidi, Mela, & Gupta, 1999) or firm value (Jose et al., 1986). Industry practitioners are advised to strategically combine sales promotions with other marketing techniques to strengthen brand equity. Many previous studies have consistently found that long-term loyal consumers contribute to both branding (Keller, 1993; Yoo & Donthu, 2001) and financial performance (Hallowell, 1996; Helgesen, 2006). Thus, frequent guest promotions should be advertised and sold with discounts to long-term clients.

It is not surprising that advertising has a negative effect on brand equity, given the fact that many chain restaurant firms have regularly engage in advertising wars over the years (Kim et al., 2013). Industry practitioners should be aware of the potentially negative effects of advertising on brand equity, and take immediate and corrective actions in line with advertising and branding practices from a long-term perspective. In order to enhance brand equity, restaurant firms should pay close attention to quality and creativity in their advertising messages and media choices. Excessive advertising and outdated advertising design are a waste of effort and financial investment and are not expected to contribute to brand equity.

Limitations and Future Research

There are some limitations to this study. First, most businesses in the restaurant industry are small and mid-sized firms, but our study drew on data for the large and publicly traded firms, so our findings may be biased. Specifically, the firms investigated in the study all have above-average marketing capabilities. Future scholars are advised to consider firm size in their evaluation of the conceptual model. Second, our model did not include all the variables that might affect firm performance, which may result in endogeneity problems and a spurious relationship between dependent and independent variables. Future studies should consider the impact of macroeconomic conditions, merger and acquisition activity, franchising, and diversification on the model. Third, this study modeled the relationship between advertising, brand equity, and firm performance based on limited information (LI) method. Because LI estimates each structural equation separately, LI estimation may be less efficient than full information (FI) estimation which considers correlations in error terms between equations by simultaneously estimating all equations. Given this, future studies may wish to use FI method as an alternative to achieve better statistical efficiency in model estimation. Fourth, this study only examined the quantitative aspect of advertising by measuring financial performance. The qualitative aspect of advertising was ignored in this study, however, including the capabilities of the primary advertising agencies, or the value or effectiveness of marketing campaigns and other promotions. A promising research direction for future studies would be a study of the combination of qualitative and quantitative aspects of advertising. Last but not least, the present authors suggest that future studies could investigate whether the asset-like characteristics of advertising influence the relationship between advertising and profitability, and could examine the behavioral and intermediate effects of advertising on market share.

Footnotes

Jewoo Kim (e-mail: jjawoo@iastate.edu) is from the Apparel, Events and Hospitality Management Department, Iowa State University, Ames, Iowa. Jinhyun Jun (e-mail: jjun@hawaii.edu) is from School of Travel Industry Management, University of Hawaii at Manoa, Honolulu, Hawaii. Liang (Rebecca) Tang (e-mail: rebeccat@iastate.edu) is from the Apparel, Events and Hospitality Management Department, Iowa State University, Ames, Iowa. Tianshu Zheng (e-mail: tzheng@iastate.edu) is from the Apparel, Events and Hospitality Management Department, Iowa State University, Ames, Iowa.

References

Ailawadi

K. L.

Lehmann

D. R.

Neslin

S. A.

(2003). Revenue premium as an outcome measure of brand equity. Journal of Marketing, 67(4), 1-17.

Anderson

E. W.

Fornell

Mazvancheryl

S. K.

(2004). Customer satisfaction and shareholder value. Journal of Marketing, 68(4), 172-185.

Andras

T. L.

Srinivasan

S. S.

(2003). Advertising intensity and R&D intensity: Differences across industries and their impact on firm’s performance. International Journal of Business and Economics, 2, 81-90.

Andrew

D. W.

(2001). Consistent model and moment selection procedures for GMM estimation with application to dynamic panel data models. Journal of Econometrics, 101, 123-164.

Arellano

Bond

(1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58, 277-297.

Arellano

Bover

(1995). Another look at the instrumental variable estimation of error-components models. Journal of Econometrics, 68, 29-51.

Arvidsson

(2006). Brand value. Journal of Brand Management, 13, 188-192.

Assmus

Farley

J. H.

Lehmann

D. R.

(1984). How advertising affect sales: Meta-analysis of econometric results. Journal of Marketing Research, 21, 65-74.

Barth

M. E.

Clement

M. B.

Foster

Kaszink

(1998). Brand values and capital market valuation. Review of Accounting Studies, 3, 41-68.

10.

Bagwell

(2007). The economic analysis of advertising. In Armstrong

Porter

(Eds.), Handbook of industrial organization (Vol. 3, pp. 1701-1844). Amsterdam, Netherlands: Elsevier.

11.

Blundell

Bond

(1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87, 115-143.

12.

Bowen

J. T.

Sparks

B. A.

(1998). Hospitality marketing research: A content analysis and implications for future research. International Journal of Hospitality Management, 17, 125-144.

13.

Boyer

K. D.

(1974). Informative and goodwill advertising. Review of Economics and Statistics, 56, 541-548.

14.

Cameron

A. C.

Trivedi

P. K.

(2009). Microeconometrics using Stata. College Station, TX: Stata Press.

15.

Chakravarti

Janiszewski

(2004). The influence of generic advertising on brand preferences. Journal of Consumer Research, 30, 487-502.

16.

Chauvin

K. W.

Hirschey

(1993). Advertising, R&D expenditures and the market value of the firm. Financial Management, 22, 128-140.

17.

Chen

C. M.

Lin

Y. C.

(2013). How do advertising expenditures influence hotels’ performance? International Journal of Hospitality Management, 33, 490-493.

18.

Chemmanur

Yan

(2009). Product market advertising and new equity issues. Journal of Financial Economics, 92, 40-65.

19.

Chu

Keh

H. T.

(2006). Brand value creation: Analysis of the interbrand-business week brand value rankings. Marketing Letters, 17, 323-331.

20.

Chung

K. H.

Pruitt

S. W.

(1994). A simple approximation of Tobin’s q. Financial Management, 23(3), 70-74.

21.

Conchar

M. P.

Crask

M. R.

Zingkhan

G. M.

(2005). Market valuation models of the effect of advertising and promotional spending: A review and meta-analysis. Journal of the Academy of Marketing Science, 33, 445-460.

22.

Crespo-Cuaresma

Stoeckl

(2012). The effect of marketing spending on sales in the premium car segment: New evidence from Germany (Working Papers in Economics and Finance No. 2012-02). Salzburg, Austria: University of Salzburg.

23.

D’Souza

Allaway

(1995). An empirical investigation of the advertising spending decisions of a multiproduct retailer. Journal of Retailing, 71, 279-296.

24.

Duffy

(2001). Advertising in consumer allocation models: Choice of functional form. Applied Economics, 33, 437-456.

25.

Elitz

(2007). Using Arellano-Bond panel GMM estimators in Stata. Bronx, NY: Economics Department, Fordham University.

26.

Eng

L. L.

Keh

H. T.

(2007). The effects of advertising and brand value on future operating and market performance. Journal of Advertising, 36, 91-100.

27.

Eskin

G. J.

Baron

P. H.

(1977). Effects of price and advertising in test-market experiments. Journal of Marketing Research, 14, 499-508.

28.

Givon

Horsky

(1990). Untangling the effects of purchase reinforcement and advertising carryover. Marketing Science, 9, 171-187.

29.

Graham

R. C.

Frankenberger

K. D.

(2000). The contribution of changes in advertising expenditures to earnings and market values. Journal of Business Research, 50, 149-155.

30.

Green

W. H.

(2008). Econometric analysis. Upper Saddle River, NJ: Prentice Hall.

31.

Greuner

M. R.

Kamerschen

D. R.

Klein

P. G.

(2000). The competition effects of advertising in the US automobile industry, 1970-94. International Journal of the Economics of Business, 7, 245-261.

32.

Hallowell

(1996). The relationships of customer satisfaction, customer loyalty, and profitability: An empirical study. International Journal of Service Industry Management, 7, 27-42.

33.

Han

B. H.

Manry

(2004). The value-relevance of R&D and advertising expenditure: Evidence from Korea. International Journal of Accounting, 39, 155-173.

34.

Hanssens

D. M.

Leeflang

P. S.

Wittink

D. R.

(2005). Market response models and marketing practice. Applied Stochastic Models in Business and Industry, 21, 423-434.

35.

Helgesen

Ø.

(2006). Are loyal customers profitable? Customer satisfaction, customer (action) loyalty and customer profitability at the individual level. Journal of Marketing Management, 22, 245-266.

36.

Hirschey

(1982). Intangible capital aspects of advertising and R&D expenditures. Journal of Industrial Economics, 30, 375-390.

37.

Homer

P. M.

(2006). Relationships among ad-induced affect, beliefs, and attitudes: Another look. Journal of Advertising, 35, 35-51.

38.

Hsu

L. T.

Jang

(2008). Advertising expenditure, intangible value and risk: A study of restaurant companies. International Journal of Hospitality Management, 27, 259-267.

39.

Hyman

M. R.

Mathus

(2005). Retrospective and prospective views on the marketing/finance interface. Journal of the Academy of Marketing Science, 33, 1-11.

40.

Hyun

S. S.

Kim

Lee

M. J.

(2011). The impact of advertising on patrons’ emotional responses, perceived value, and behavioral intentions in the chain restaurant industry: The moderating role of advertising-induced arousal. International Journal of Hospitality Management, 30, 689-700.

41.

Jedidi

Mela

C. F.

Gupta

(1999). Managing advertising and promotion for long-run profitability. Marketing Science, 18, 1-22.

42.

Jose

M. L.

Nichols

L. M.

Stevens

J. L.

(1986). Contributions of diversification, promotion, and R&D to the value of multiproduct firms: A Tobin’s q approach. Financial Management, 15, 33-42.

43.

Joshi

Hanssens

D. M.

(2010). The direct and indirect effects of advertising spending on firm value. Journal of Marketing, 74(1), 20-33.

44.

Kanetkar

Weinberg

C. B.

Weiss

D. L.

(1992). Price sensitivity and television advertising exposure: Some empirical findings. Marketing Science, 11, 359-371.

45.

Kantar Media. (2013). Kantar Media reports U.S. advertising expenditures increased 3 percent in 2012. Retrieved from http://kantarmedia.us/press/kantar-media-reports-us-advertising-expenditures-increased-3-percent-2012

46.

Kaul

Wittink

D. R.

(1995). Empirical generalizations about the impact of advertising on price sensitivity and price. Marketing Science, 14, 151-160.

47.

Keller

K. L.

(1993). Conceptualizing, measuring, and managing customer-based brand equity. Journal of Marketing, 57(1), 1-22.

48.

Keller

K. L.

(2002). Branding and brand equity. Cambridge, MA: Marketing Science Institute.

49.

Kendrick

(1998). Promotional products vs. price promotion in fostering customer loyalty: A report of two controlled field experiments. Journal of Services Marketing, 12, 312-326.

50.

Kim

H. B.

Kim

W. G.

J. A.

(2003). The effect of consumer-based brand equity on firms’ financial performance. Journal of Consumer Marketing, 20, 335-351.

51.

Kim

Y. H.

Kim

M. C.

O’Neill

J. W.

(2013). Advertising and firm risk: A study of the restaurant industry. Journal of Travel & Tourism Marketing, 30, 455-470.

52.

Leach

D. F.

Reekie

W. D.

(1996). A natural experiment of the effect of advertising on sales: The SASOL case. Applied Economics, 28, 1081-1091.

53.

Leone

R. P.

(1995). Generalizing what is known about temporal aggregation and advertising carryover. Marketing Science, 14, 141-150.

54.

Line

N. D.

Runyan

R. C.

(2012). Hospitality marketing research: Recent trends and future directions. International Journal of Hospitality Management, 31, 477-488.

55.

Luo

de Jong

P. J.

(2012). Does advertising spending really work? The intermediate role of analysts in the impact of advertising on firm value. Journal of the Academy of Marketing Science, 40, 605-624.

56.

McAlister

Srinivasan

Kim

M. C.

(2007). Advertising, research and development, and systematic risk of the firm. Journal of Marketing, 71(1), 35-48.

57.

Mitra

Lynch

J. G.

(1995). Toward a reconciliation of market power and information theories of advertising effects on price elasticity. Journal of Consumer Research, 21, 644-659.

58.

Morrison

A. M.

(2009). Hospitality and travel marketing. Mason, OH: Cengage Learning.

59.

Nelson

(1974). Advertising as information. Journal of Political Economy, 82, 729-754.

60.

Notta

Oustapassidis

(2001). Profitability and media advertising in Greek food manufacturing industries. Review of Industrial Organization, 18, 115-126.

61.

Park

Jang

S. C. S.

(2012). Duration of advertising effect: Considering franchising in the restaurant industry. International Journal of Hospitality Management, 31, 257-265.

62.

Peterson

R. A.

Jeong

(2010). Exploring the impact of advertising and R&D expenditures on corporate brand value and firm-level financial performance. Journal of the Academy of Marketing Science, 38, 677-690.

63.

Pritchett

J. G.

Liu

D. J.

Kaiser

H. M.

(1998). Optimal choice of generic milk advertising expenditure by media outlet. Journal of Agricultural & Resource Economics, 23, 155-169.

64.

Rao

V. R.

Agarwal

M. K.

Dahlhoff

(2004). How is manifest branding strategy related to the intangible value of a corporation? Journal of Marketing, 68, 126-141.

65.

Reekie

Bhoyrub

(1981). Profitability and intangible assets: Another look at advertising and entry barriers. Applied Economics, 13, 99-107.

66.

Simon

C. J.

Sullivan

M. W.

(1993). The measurement and determinants of brand equity: A financial approach. Marketing Science, 12, 28-52.

67.

Srivastava

Shocker

A. D.

(1991). Brand equity: A perspective on its meaning and measurement (Report No. 91-124). Cambridge, MA: Marketing Science Institute.

68.

Srinivasan

Vanhuele

Pauwels

(2010). Mind-set metrics in market response models: An integrative approach. Journal of Marketing Research, 47, 672-684.

69.

Stassen

R. E.

Mittelstaedt

R. A.

(2002). Do franchise systems advertise enough? U.S. restaurant expenditures and performance 1989 to 1998. Journal of Marketing Channels, 10, 3-18.

70.

Stigler

G. J.

(1961). The economics of information. Journal of Political Economy, 69, 213-225.

71.

Tellis

G. J.

(2010). Generalization about advertising effectiveness in markets. Journal of Advertising Research, 49, 240-245.

72.

Telser

L. G.

(1964). Advertising and competition. Journal of Political Economy, 72, 537-562.

73.

Vakratsas

Ambler

(1999). How advertising works: What do we really know? Journal of Marketing, 63(1), 26-43.

74.

Ventoura-Neokosmidi

(2005). Advertising, market share, and profitability in the Greek consumer industry. Journal of Business & Economics Research, 3(9), 69-76.

75.

Wang

Zhang

X. P.

Ouyang

(2009). Does advertising create sustained firm value? The capitalization of brand intangible. Journal of the Academy of Marketing Science, 37, 130-143.

76.

Windmeijer

(2005). A finite sample correction for the variance of linear efficient two-step GMM estimators. Journal of Econometrics, 126, 25-51.

77.

Wooldridge

(2012). Introductory econometrics: A modern approach. Mason, OH: South-Western Cengage Learning.

78.

Yiannaka

Giannakas

Tran

K. C.

(2002). Medium, message, and adverting effectiveness in the Greek processed meats industry. Applied Economics, 34, 1757-1763.

79.

Yoo

Donthu

(2001). Developing and validating a multidimensional consumer-based brand equity scale. Journal of Business Research, 52, 1-14.

80.

Zulfiqar

Shah

Akbar

(2008). Value relevance of advertising expenditure: A review of the literature. International Journal of Management Reviews, 10, 301-325.