1. INTRODUCTION
Traditional retail business has been challenged by two major developments in the last decade. One is the maturing of the internet and consumers' switching from brick and mortar stores to the online channel. The other is the ongoing success of the discount concept broadening from grocery stores to a broad range of industries such as clothing, consumer electronics, or banking. Furthermore, discount stores are increasingly transferring the basic concept of lowest prices through economies of scale and a lack of advice to higher value products and thus putting substantial pressure on traditional retailers. For consumers, discount stores and online purchases often offer the opportunity to realize substantial savings compared to traditional channels. However, they create a new need for product advice and in the case of online shopping for looking at the product and testing it. In this context, many consumers may use the resources of traditional specialty stores to look at the product or to collect some advice on certain products and brands in order to prepare their purchase in a low price channel. In the current paper we discuss the roots and consequences of such behavior and conceptualize the construct of free rider advice. To make the concept meaningful, we conceptually connect free rider advice to an economic and moral perspective of consumer purchasing, namely to information seeking and to price fairness attitudes. We establish the free rider advice measure and test the developed hypotheses against data from 159 German consumers on their consumer electronics purchases. We discuss the results and their implications for future research, for companies and for consumers.
2. FREE RIDER ADVICE
We conceptualize free rider advice (FRA) as the deliberate demanding of free product advice by consumers from a specialty store, in order to be able to capitalize on price advantages in internet stores or in low-service retail outlets where no product advice is offered. In business practice, this phenomenon has attracted a great deal of attention and has been discussed as "advice theft" (German: "Beratungsklau", Stern Media Business 2004: p.3). However, this term appears to be misleading as the behavior does not describe a legal category. While scientific consideration of the FRA phenomenon is yet lacking, its consideration under economic and moral perspectives appears to be promising. Accordingly we subsequently discuss economic concerns that may result from the behavior's tendency to undermine free product advice as informational source (e.g. Nelson 1970)--comparably to free rider phenomena using public goods--and the potential disappearance of retail stores offering advice in the long run. Moreover, we investigate moral concerns that may be based on perceptions of equitable norms (Homans 1961).
Economically, free product advice can be considered to be a public good that is provided by the sales personnel of specialty retail stores and that can be accessed for free by basically anyone who is asking for it in the store. Comparable to when consuming other public goods, FRA may induce social or moral cost but is not attached to any monetary payment. Such social and moral cost can become relevant, as shown in numerous public goods experiments where people usually contributed more to the public good than can be easily explained by pure self-interest (Fischbacher and Gachter 2010). However, it has been shown that subjects learn to profit from free riding opportunities (Ledyard 1995) and contributions to the public good are reduced to a minimum, creating a "warm glow" from serving altruistic motives that assure moral freedom (e.g., Palfrey and Prisbrey 1996; 1997; Houser and Kurzban 2002; Binmore 2005). Accordingly, most individuals--at least experimentally--use free rides to optimize their personal outcomes. However, other researchers conclude from their results that social preferences and related moral concerns need to be attributed substantial behavioral relevance when aiming to explain consumers' likeliness to explore free riding opportunities (e.g., Andreoni 1995; Keser and van Winden 2000; Brandts and Schram 2001; Ashley, Ball and Eckel 2010).
Morally, equity theory (Adams 1965; Homans 1961) can be used to raise doubt regarding FRA. Equity theory integrates the economic exchange principle with consistency theories (Festinger 1957; Heider 1958) and thus suggests that any contribution in a relationship should be equalized by a corresponding contribution by the other party. Hence, both sides are expected to provide an equivalent input (Walster, Walster and Berscheid 1978). In the case of FRA, a store's contribution to the equitable advice relationship is the knowledge and time spent on delivering competent advice to the consumer. In return, an equivalent contribution from the consumer could be to honestly consider the store in his evoked set of potential suppliers when buying the product. Perhaps, one might even expect from the consumer not to consider low price providers when approaching a higher price provider for advice, except for the case where the relevant product is not available. For supporting criterion validity, we relate the FRA concept to consumer information seeking as an economic determinant ("smart shopping") and to consumer price fairness attitudes as a moral determinant.
3. HYPOTHESES DEVELOPMENT
3.1 FRA and consumer information seeking
Achieving smart deals and most value for one's money requires substantial planning, searching and comparing activities. As such smart deals and offers are often available in discount stores that do not offer advice, or on the internet, consumers need to collect information elsewhere. While the internet is a valuable source for all kind of product information (Monsuwe, Dellaert, Benedict and de Ruyter 2004), the perceived credibility is still limited for many consumers (Metzger 2004) and in-store advice is often perceived as more reliable and trustworthy (Culnan and Armstrong 1999). Also, in-store advice often goes in hand with the opportunity to test a product. Both aspects establish a positive relationship between a consumer's behavior resulting from a subjective need for information and the likeliness of collecting advice from stores without intending to buy there. Accordingly we assume a positive relationship between consumer information seeking and free rider advice.
This assumption is further supported by the fact that consumers who aim to optimize their value-for-price ratio by seeking out smart and attractive deals have a particular need for price and product information from diverse shopping locations. In contrast, consumers who put a focus on price or quality are more likely to focus on outlets that target these particular needs (e.g. EDLP for low price and brand flagships stores for high quality). Smart shoppers' great need for product information is based on the need for a detailed evaluation of the price and also the quality of a product. Qualified salesmen who offer advice are an easily accessible and relatively reliable source of such information. We thus hypothesize:
Hypothesis 1: The more consumers seek information when preparing for their purchase, the more likely they are to use free rider advice.
3.2 FRA and consumer price fairness attitudes
The general assumption is that consumers do not only care about the economic attractiveness of an offer but also about its fairness (Kahneman, Knetsch and Tahler 1986a). In this context, Xia, Monroe and Cox (2004) suggest that knowledge, beliefs and social norms influence consumers' price fairness evaluations. Along with the principle of dual entitlement (Kahneman, Knetsch and Thaler 1986b), consumers compare offers to reference transactions that entitle the company to a certain transaction profit and the receiving consumer to a certain output. Changes, e.g. in cost, disturb the reference transaction and fairness requires them to be compensated; and the DEP assumes a company's reference profit to have priority over the consumer's entitlement to the reference transaction. Accordingly, price increases are considered fair when they are based on cost increases of the same amount.
Existing price fairness research overly investigated the negative consequences of prices that consumers felt were unfair and disadvantaged themselves (e.g. Bolton, Warlop and Alba 2003; Campbell 1999; Urbany, Madden and Dickson 1989; Xia, Monroe and Cox 2004). For example, unfair price perceptions were associated with dissatisfaction and with a change of supplier. However, we assume that consumers have more holistic fairness perceptions and do not only consider their own advantage but also the stake of the suppliers. This perspective is hardly considered in existing research although it is explicitly anchored in the dual entitlement principle, stating that consumers perceive price rises as fair when these aim at maintaining current profits.
In their seminal empirical works on price fairness, Kahneman, Knetsch and Thaler (1986a, b) found that it is considered unfair when companies increase their profits through price increases. In contrast, price increases are considered fair when implied through cost increases. In this context it is particularly the expected corporate motive of a price increase that is relevant (Campbell 1999), with "positive" motives, like increased service or donation of additional profit to a good cause (e.g. Nowak 2004; Strahilevitz 2003), being accepted while "bad" motives, profit maximization in particular, are penalized. Hence, fairness is influenced by aspects that go beyond the current price of a product (Bolton, Warlop and Alba 2003; Kalapurakal, Dickson and Urbany 1991). This further supports the assumption of a relationship between advice and fairness perceptions in a way that consumers who want prices to be fair for all sides are less likely to exploit free advice in order to harvest price savings in discount channels.
Hypothesis 2: The stronger consumers' price fairness attitudes, the more likely they are to use free rider advice.
4. METHOD
4.1 Approach and Sample
In order to establish the FRA construct and to test the hypotheses, a standardized written questionnaire was compiled. Graduate marketing students surveyed German consumers as part of a course assignment based on quotas relating to the respondents' age and education levels. A total number of 159 complete and usable responses on shopping behavior in the consumer electronics industry were collected in the scope of a larger project on consumer price perceptions. Respondents were 33.8 years of average age and spread over diverse educational backgrounds. In line with the shopping habits in Germany, where consumer electronics are predominantly bought by men, 84.9 per cent of the respondents were male.
4.2 Measurement Model and Analyses
For FRA a new scale was developed. A list of possible indicators was created and extensively discussed within the research team and with two academic marketing experts, one of whom may be considered the leading academic in the field of retail research in Germany. This procedure initially produced a five-item scale. Its comprehensibility and reliability was then pretested together with the items from the abovementioned scales in 64 face-to-face interviews on clothing purchases. Marginal changes were made following the pretest. One item ("I like to get advice in the store when buying consumer electronics) was later removed based on statistical properties, resulting in a four-item measure for further analysis. Consumer Information Seeking as a specific smart shopping behavior was measured applying 3 items as suggested by Mano and Elliott (1997). Moreover, consumer price fairness attitudes were measured by applying existing price fairness measures (Urbany, Maddan and Dickson 1989) to consumers' own price fairness attitudes. Seven-point Likert-type scales were applied ranging from 'does not apply at all' to 'applies completely' in order to measure the latent constructs.
The measurement properties were first assessed with explorative and then with confirmatory factor analysis using SPSS 18.0 and AMOS 18.0 (the 2-step approach as recommended by Anderson and Gerbing 1988). Main component exploratory factor analysis applying varimax rotation extracted a three factor solution as depicted in table 1, which explained 69.5 per cent of the variance in the raw data. All three con structs showed good reliability with Cronbach a exceeding the suggested 0.7 threshold (Nunnally 1978). Confirmatory factor analysis applying the maximum likelihood algorithm (Bollen 1989) in AMOS confirmed this good fit of the measurement model with fit indices GFI = .92, CFI = .95, and NFI = .91 exceeding the suggested 0.9 threshold (Bagozzi and Yi 1988; Hair, Black, Babin and Anderson 2009) and RMSEA = .074 falling below the suggested .08 threshold (MacCallum, Browne and Sugawara 1996; Byrne 1998). Thus, particularly against the background of a limited sample size, the measurement model can be considered of good reliability and discriminant validity. In order to evaluate the hypotheses, we applied stepwise regression analysis.
5. RESULTS
For evaluating the hypotheses individually and for judging their validity when integrating them into one joint model, we calculated regressions stepwise for each determinant, for the three possible couples of determinants and for the integrated model (see Table 2). For further assuring the basic assumptions of regression analysis, each independent variable was plotted against the FRA construct without any nonlinear relationship being identified. No auto-correlation were found based on Durbin- Watson scores. Moreover, VIF scores indicated that no multicollinearity occurred between the independent variables. Heteroscedasticity was analyzed, based on plots of the residuals and no particularities were identified.
With a regression weight of .153 in the integrated model, hypothesis 1 finds significant support. Accordingly, consumers who are used to being well informed regarding the products that they purchase are more likely to collect advice from traditional specialty stores without any intention to buy there. Consumer price fairness attitudes are negatively related to FRA (-.230). Being significant, this result provides support for hypothesis 2, as consumers who expect prices and conditions to be fair along the supply chain also aim for fair prices for the retailer as the last link. Accordingly, they are less likely to engage in FRA that economically harms the retailer. With .070 for the integrated model, [R.sup.2] is limited. This is in line with our assumption that the considered determinants support the FRA construct's criterion validity but do not explain the construct in its entirety. Research on further determinants is thus one emphasis of the following discussion.
6. DISCUSSION AND IMPLICATIONS
We identified consumers' deliberate demanding of free product advice as a relevant issue for retail management and conceptualized the related FRA construct. We suggested a four-item measure and established criterion validity by connecting FRA to the meaningful constructs of information seeking and price fairness attitudes. While the construct's reliability and validity have been supported by confirmatory factor analysis, the limited [R.sup.2] value also shows that major parts of FRA are motivated by factors beyond the two considered influences.
In this study we considered consumers' general information seeking behavior. However, with regard to FRA, the informational need with regard to a specific product might be more relevant. A key determinant of FRA, which we suggest for future consideration, should thus be consumers' actual need for advice, which probably depends on the individual competence and the perceived complexity with regard to products of a particular category. Hence, product and category specific information need to be considered. Additionally, consumers' information seeking might moderate such relationships as the impact of product complexity on FRA. We further shed light on consumer price fairness attitudes as a particular, price-related aspect of consumers' fairness perceptions. Nevertheless, in the context of FRA, more general values and fairness considerations may be also explicative. Thus, we suggest considering more general values such as benevolence (e.g. Schwartz 1994) in future research. Finally, we did not consider whether product selection is based on search, experience or credence qualities. While we investigated the FRA construct for a general shopping situation in the consumer electronic industry, FRA is expected to be particularly relevant for products that have a high portion of experience qualities, where testing the product in a store may be a relevant first product experience to support a consumer's decision.
We focused on the consumer perspective. Nevertheless, one should also reflect on why companies do offer free advice, whether or not they should do so, and what alternatives they may have. When considering companies' motivation, it is important to note that product advice can be an important means to differentiate a company's offer from that of its competitors. Competent product advice should primarily be useful to attract consumers and pulling customers in your store might simulate them to buy more on impulse. Moreover, individual advice may be a basis to establish a personal relationship with a customer and thus to harvest the advantages that long-term customer relationships offer (Reicheld and Sasser 1990). However, consumer advice is a store's investment in an unsecure customer relationship and is thus attached to some risk. If the store does not manage to convert the customers who ask for advice into buyers, then the cost of advice is a loss that has to be recovered in the relationships with paying customers. The more advice is provided without being converted into sales, the higher prices have to be taken from the paying customers in order to cross finance the offered advice. Thus, the question of whether companies should offer advice for free or not does not have a clear answer, as offering advice is opportunity and risk at the same time. The opportunity to establish lasting profitable relationships is accompanied by a financial risk of not being able to convert those customers who come into the store for some product advice or for experiencing a wide variety of products into paying customers.
For avoiding the misuse of product advice, companies might charge a fee for advice in return for lower product prices. This would deter free riders but might be considered a barrier by many potential customers who do not necessarily come with a firm purchase intention but who want to be sold something in the persuasive sense of the word. In Germany, approaches of paid advice had been tested in the banking industry and in some other industries, but did not catch on. Thus, we assume that offering free advice may be an opportunity to those who provide an exciting product experience together with quality advice and with sales personnel who is able to quickly connect to and evoke trust in advice seekers for converting them into paying customers. Accordingly, while advice free riders will constitute a limited threat to those traditional stores who provide a high quality sales experience, they will particularly speed up the decline of those stores who do poor in delivering advice and product experience. This again may even help the better stores to excel over their competition.
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Mark Wendlandt, GfK Panel Services Hamburg, GERMANY
Dirk C. Moosmayer, RWTH Aachen University, GERMANY
Dr. Mark Wendlandt was trained in management and marketing at the Gottfried Wilhelm Leibniz University in Hanover, Germany. He received his Ph.D. from the institution's Institute for Marketing and Consumer Research in 2007. He is now a Marketing Consultant in the Panel Services division of Germany's leading market research agency Gesellschaft fur Konsumforschung (GfK). His research interests cover Retailing and Consumer Behavior with a special focus on consumer reactance and price perceptions.
Dirk C. Moosmayer gained a Master's degree in Information and Technology Management from the University of St. Gallen (HSG) in Switzerland. He worked as a banking consultant for The Boston Consulting Group in Germany. His research interests include pricing, values in consumer behavior, and values in management education. His work appears in peer-reviewed journals, such as Journal of International Business and Economics, Journal of Consumer Marketing, and Higher Education.
TABLE 1EXPLORATORY FACTOR ANALYSIS Free Rid- Information Price er Advice Seeking Fairness Behavior Attitude1. Sometimes I step into a .83 store determined only to get some advice from there and to shop elsewhere.2. There is nothing immoral .67 about asking for advice in a specialty store then buying in discount or on the internet.3. Good advice from a store .74 does not oblige me to buy there.4. It is completely .84 legitimate to take extensive advice but to buy the product in another store.5. I like collecting as .89 much information as possible before buying consumer electronics.6. I invest a relevant .92 amount of time for preparing consumer electronic purchases.7. I like to make use of .81 opportunities to compare etc. prices e.g. in newspaper advertisement, on leaflets, on the internet,8. I want to pay prices .72 which ensure a livelihood for suppliers.9. I find dumping prices .87 ethically doubtful.10. It is important to me .89 that prices are acceptable for both parties, i.e. also for the retailers.11. I do not support .83 unlimited price dumping. Cronbach's [alpha] .79 .85 .86Note: Based on a main component approach withvarimax rotation. Loadings < .2 are not displayed.TABLE 2STEPWISE REGRESSION ANALYSIS Model 1 Model 2 Model 3 [R.sup.2.sub.ad] [R.sup.2.sub.ad] [R.sup.2.sub.ad] = 0,025 = 0,053 = 0,070 [beta] P [beta] P [beta] PInformation 0.177 0.026 0.153 0.05SeekingPrice -0.240 0.002 -0.230 0.004FairnessAttitudes
