Transparency in advertising: the effects of
information valence, product category price, and
brand trust on consumers’ willingness to pay.
Master thesis
Author: Rimko Holm (10694374)
University of Amsterdam, Faculty of Economics and Business
June 28, 2015
Under supervision of: J. Demmers MSc
Second assessor: Dr. A. Zerres
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STATEMENT OF ORIGINALITY
This document is written by Rimko Holm who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
3 TABLE OF CONTENTS Abstract 5 1. Introduction 6 2. Literature review 7 2.1 Transparency 7
2.2 Consumers’ willingness to pay 13
2.3 Source of information 14
2.4 Product category price 15
2.5 Brand trust 16 2.6 Conceptual framework 17 3. Methodology 18 3.1 The sample 18 3.2 Research design 19 4. Results 23
4.1 Normality and correlation check 23
4.2 Model testing 27
5. Discussion 32
5.1 Contribution 33
5. 2 Limitations and future research 34
References 36
Appendices 44
Appendix A; Advertisements used in the experiment 44
Appendix B; Survey example 45
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ABSTRACT
Corporate transparency is becoming an increasingly more important topic in the age of transparency in which consumers are more demanding for information while for companies it becomes harder and harder to conceal information. Prior literature has found support for both positive as negative effects of transparency on consumers’ willingness to pay. Current
experimental study examined whether, consumers’ willingness to pay is affected by
information valence and whether this relationship is moderated by product category price, and mediated by brand trust. The results showed that disclosing unfavorable information leads to a lower willingness to pay as compared to non-disclosure. No significant effects were found for disclosing favorable. The effect of information valence on consumers’ willingness to pay is shown to be moderated by product category price such that the effect was larger when the product price was higher. Furthermore, it was also found that brand trust has a mediating role between information valence and willingness to pay. This study concludes with managerial implications, limitations and suggestions for directions for future research.
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1. INTRODUCTION
The rise of social media changed the relationship between companies and customers
dramatically; companies have less control over the flow of information available to customers (Labrecque, vor dem Esche, Mathwick, Novak & Hofacker, 2013). It becomes harder and harder to “conceal” information from customers (Peppers & Rogers, 2012). The company’s loss of control over the information flow increases the probability that customers are exposed to unfavorable product information, regardless of the firm’s decisions to either or not disclose the information itself (Fournier & Avery, 2011; Labrecque et al., 2013). Consumers now have access to extensive amounts of information on which they can base (purchasing) decisions (Labrecque et al., 2013). The increased access to extensive amounts of information goes hand in hand with the increased customers´ information needs as a result of becoming better
educated and conscious about the society and environment (Bhaduri & Ha-Brookshire, 2011). The increased need for information is also mentioned by Cohn and Wolfe (2013), who state that the demand for transparent business practices has increased. Reasons for the increased demand for transparency are the general distrust towards companies because of the financial crisis (Kirby, 2012) and the increase in skepticism and distrust against firms’ business practices and advertising in particular (Darke & Ritchie, 2007). Fournier and Avery (2011) named the situation in which it is hard to conceal information from customers while the customers demand for more transparency and information the Age of Transparency.
In the majority of the advertisements initiated by a brand, consumers are exposed to positive product information. True transparency implies that brands are open about matters relevant to stakeholders irrespective of the valence of the information. Hence to be transparent also implies disclosure of negative information. Disclosing mildly negative information has even proven to result in a higher willingness to pay (WTP) than non-disclosure, providing the information is disclosed by the brand (Demmers, 2014).
6 However, despite the growing popularity and importance of transparency, little is known regarding the effect of transparency on consumers´ purchase and consumption choices (Bhaduri & Ha-Brookshire, 2011). Previous research has shown that transparency can have positive as well as negative effects on consumers’ product evaluation and WTP
(Anderson, 1971; Bagozzi & Daholakia, 1999; Dapko, 2012; Smith, 1993) but the boundary conditions remain unclear. Eisend (2006) and Einwiller, Fedorikhin, Johnson and Kamins (2006) state that an advertisement including unfavorable information can have a more positive effect as an advertisement with solely positive information. Both studies emphasize that the amount of unfavorable information must not be too large. But when does the amount of unfavorable information get too large?
The purpose of this study is to address this gap by looking at boundaries of the effect of disclosing (un)favorable product information on consumers’ WTP. We theorize that a brand disclosing too much unfavorable or favorable information at some point decreases willingness to pay. This point might vary for different priced product categories because the financial risk for different priced products might vary. Finally, the potential underlying
mediating role of brand trust on the relation of disclosed product information valence on WTP is addressed.
2. LITERATURE REVIEW
2.1 Transparency
Hultman and Axelsson (2007) distinguish four types of transparency; supply (chain) transparency, cost/price transparency, organizational transparency and technological transparency. Supply (chain) transparency refers to the disclosure of information about the firm’s supply chain. Cost/price transparency refers to the disclosure of information about the
7 distribution of costs. A firm that is organizational transparent, provides detailed information about the organization itself. Lastly, technological transparency refers to disclosing
information about product attributes. This type of transparency will be used in this research by varying the (un)favorableness of the communicated product attribute.
When looking at the effects of transparency we must look at the world in which firms currently operate. The increased demand for transparency and information by customers (Cohn & Wolfe, 2013; Bhaduri & Ha-Brookshire, 2011) provides an incentive for advertisers to provide objective and reliable advertising information (Ford, Smith, and Swasy, 1990). Transparency has become more important; about 70% of the customers consider openness and transparency in purchasing. This makes transparency the most important factor following price and quality (Cohn & Wolfe, 2013). Reasons for the increased demand for transparency are the general distrust towards companies because of the financial crisis (Kirby, 2012) and the increase in skepticism and distrust against firms’ business practices and advertising in particular (Darke & Ritchie, 2007). Transparency can be a tool to reduce consumer skepticism (Friestad & Wright (1994). Including negative information in advertising is conceived as helpful and unselfish by the customers. Therefore, customers conclude that the firm is “telling the truth” (Crowley and Hoyer, 1994).
Previous research does not provide a clear picture about the effects of transparency. Certain authors have shown that increased exposure of information might have negative impact on the firm while other authors (e.g., Chang & Wildt, 1994; Eggert & Helm, 2003) state that transparency can decrease negative effects or even have a positive impact. One important factor is the favorableness of the disclosed information. In the following section, effects of disclosing favorable and unfavorable product information will be discussed.
Disclosing unfavorable information Intuitively, disclosing unfavorable information should lower product valuation. This is acknowledged by Smith (1993), who
8 states that unfavorable information about a product should decrease customers’ evaluations of that product. This is in line with the information integration theory of Anderson (1971). This theory predicts that consumers who are exposed to unfavorable information should have a lower willingness to pay and should choose other products (Bagozzi & Daholakia, 1999).
Arpan & Roskos-Ewoldsen (2005) acknowledge the negative impact that unfavorable information might have on a firm, but suggest that firms are able to decrease this negative impact by proactively disclosing the information. They named this phenomenon the Stealing Thunder Effect. They showed that when unfavorable information about the firm is likely to be revealed, proactive disclosing this information before another source reveals it, decreases the negative impact on the firm. This illustrates that the impact of unfavorable information is less negative, when customers become aware of the unfavorable information due to company itself instead of another source (e.g., online customer reviews). This is acknowledged by Friestad and Wright (1994), who states that consumers generally do not trust marketeers but firms may be able to reduce consumer skepticism by being transparent. In the research of Ipsos-Reid (as cited in Darke & Ritchie, 2007), only a mere 17% of the respondents trusted the advertising. This suggests that transparency might be a successful tool/strategy to decrease the negative impact of unfavorable information and reduce consumer skepticism. In the automotive, the stealing thunder strategy is used quite often; several brands decided to check all the cars that might have a mechanical problem. By doing so, the brands decreased the negative impact this information might have by proactively disclosing the information.
In addition to decreasing the negative effects that unfavorable information might have, multiple authors demonstrate that disclosing unfavorable information might even lead to more positive results as disclosing favorable information. Disclosing unfavorable information might be more difficult for a firm than being transparent about favorable information because as stated before, it might lead a lower WTP and make customers switch to other products
9 (Anderson, 1971; Bagozzi & Daholakia, 1999) while being transparent about favorable
information is likely to have positive effects. In addition, Eisend (2006) demonstrated that disclosure of some unfavorable information, next to favorable information in a product related advertisement, can lead to higher source credibility, less negative cognitions and more
favorable brand attitudes as an advertisement with only positive information. These effects are only to be found under the conditions that; the amount of negative information is not too large, not about something very important, neither in the beginning nor at the end of the message, communicated before experience, disclosed voluntarily and not about an
unfavorable attribute closely related to a favorable attribute. Einwiller et al. (2006) agree with Eisend (2006) on the condition that the amount of unfavorable information must not be too large. In their research they demonstrated that boundaries for the amount of negative
information exist. Their research showed that strong brand identification mitigates the effects of moderately negative publicity but does not attenuate the effects of extremely negative publicity. In addition, Crowley and Hoyer (1994) state that including negative information in advertising is conceived as helpful and unselfish by customers. Therefore, customers conclude that the firm is “telling the truth”. Demmers (2014) builds further on these previous studies. His results demonstrate a consistent positive effect of unfavorable information disclosure on WTP and product choice. The unfavorable information only led to a higher WTP when the information was disclosed by the brand rather than another source. This illustrates that the source type influences the relationship between transparency and product
evaluation/willingness to pay. In addition, Demmers (2014) offers insight in the underlying mechanism by showing that unfavorable information disclosed by the brand is perceived as more relevant and less negative. This illustrates that the communication source can have an impact on consumers’ perceptions of information and thus on their WTP. Hence, the communication source that is used in this research is covered later in this section.
10 Disclosing favorable information Intuitively, disclosing favourable information should increase consumers’ product valuation. Integration theory Anderson (1971) confirms this view, stating that consumers form judgments by combining different pieces of
information. These judgments are formed on the basis of valence (unfavorable or favorable) and weight (unimportant or important). Building on this theory, research has shown that consumers who are exposed to favorable product information are likely to form more favorable attitudes towards that product (Smith, 1993), which should positively affect
willingness to pay and product choice (Bagozzi & Dholakia, 1999). Dapko (2012) presents a connection between transparency, reduced skepticism, increased trust, purchase intention and attitude towards a firm. When a firm is transparent, forced or voluntarily, it means that it is perceived to be open and honest with its stakeholders (Dapko, 2012). By being more
transparent, companies attempt to reduce customers’ skepticism and avoid asking consumers to trust a ‘black box’ (Kirby, 2012; Rogers & Peppers, 2012). Other positive results of transparency were found by Carter and Curry (2010), who showed that customers prefer transparent pricing over opaque pricing and Lafferty & Goldsmith (1999) who found that consumers are more likely to buy brands from firms that engaged in transparency. In addition, Johnson and Levin (1985) observed lower product ratings when the appropriate product information was missing. Communication of product attribute information also has proven to have a positive impact on perceived quality (Chang and Wildt, 1994). In addition, Eggert & Helm (2003) found significant support for their model in which transparency has a positive effect on customer satisfaction, direct and though customer value. Furthermore, customer satisfaction, and thus indirect transparency, leads to a higher repurchase intention, a higher word of mouth and a lower search for alternatives.
Next to positive effects of disclosing favorable information, disclosing favorable information can also result in negative effect on consumers’ evaluations. Nye, Zelikow and
11 King (as cited in Darke & Ritchie, 2007) state in their book that the communication between a firm and their customers is based on honesty. They state that if a firm is not perceived as honest, it leads to negative effects on customers’ attitudes. For example, a firm
communicating inaccurate extreme favorable product attributes will experience negative consequences when customers perceive the communicated information as not honest. Increased transparency may create frustration and, in some cases, may even be a source of problems (Hultman & Axelsson, 2007).
Christensen (2002) defined transparency as the public availability of relevant information. In this thesis, we focus on the communication of (un)favorable product
information in an advertisement. According to House (as cited in Dapko, 2012) this is rather disclosure as transparency. Rawlins (2008) also states that just communicating information is more accurately called disclosure. “But disclosure, alone, can defeat the purpose of
transparency” (Rawlins, 2008, p.74). Vishwanath and Kaufmann (2001) introduced five requirements for transparency; accessible, relevant, comprehensive, qualitative and reliable. According to these authors, information only is transparent when all five requirements are met. Rawlins combined previous research on transparency and defines transparency as follows: ‘‘Transparency is the deliberate attempt to make available all legally releasable information—whether positive or negative in nature—in a manner that is accurate, timely, balanced, and unequivocal, for the purpose of enhancing the reasoning ability of publics and holding organizations accountable for their actions, policies, and practices.’’(Rawlins, 2008, p.74). The information made available by the firm can be voluntarily or mandatory.
Mandatory transparency implies that legal registrations force organizations to disclose certain information (Millar, Eldomiaty, Choi & Hilton, 2005).
12 2.2 Consumers’ willingness to pay
The valence of disclosed product information is expected to have an effect on consumers’ product evaluation. In this research, consumers’ product evaluation is measured as the consumer’s willingness to pay (WTP). Managers consider the knowledge of customers’ responses to different prices as very important, particularly regarding marketing strategies (Anderson, Dipak, Pradeep, as cited in 1993 Breidert Hahsler & Reutterer, 2006). Researchers agree on the importance of WTP of customers (Breidert, Hahsler & Reutterer, 2006).
Accurate information on WTP can be used to forecast responses to price changes. This would enable an organization to set the price at exactly the point that is most profitable for the organization.
Willingness to pay is often distinguished in hypothetical- and actual willingness to pay (Johannesson, Blomquist, Blumenschein, Johansson, Liljas & O'Conor, 1999). The
hypothetical WTP refers to the WTP in a hypothetical situation of which the consumer is aware, such as a survey. In contrast, the actual WTP refers to an actual situation in which the WTP is the amount of money the consumer would spend in the real purchase situation, such as a market. The latter has real financial consequences whilst the hypothetical WTP does not have real financial consequences for the consumer (Hofstetter & Miller, as cited in Kroeze). The first author that made this distinction was Bohm (1972). Dickie, Fisher and Gerking (1987) did not find significant support to reject their null hypothesis that the actual WTP was identical to the hypothetical WTP. In contrast, other studies (Bishop & Herberlein, 1979; Cummings, Harrison & Rutström, 1995; Kealy, Montgomery & Dovidio, 1990) found that hypothetical WTP exceeded the actual WTP. Despite some contradicting results, most research suggests that the hypothetical WTP exceeds the actual WTP (Murphey, Allen, Stevens & Weatherhead, 2005). In this research consumers indicate their WTP for a product without actually purchasing the product. Thus, hypothetical consumers’ WTP is measured.
13 The consumer’s WTP for a certain product depends on different factors. The most common factor is the price the consumer has to pay for a product. From the consumer’s perspective, price is what is given up or sacrificed to obtain a product (Zeithaml, 1988). However, the consumer will only sacrifice a price to obtain a product that he or she considers as fair. Buyers’ perception of a fair price has been considered a determinant of consumers’ willingness to buy the product and a reason for consumers’ resistance to buying the product (Kahneman, Knetsch & Thaler, 1986). In this thesis, willingness to pay refers to the
consumer’s willingness to pay for a product of which (un)favorable information is disclosed by the firm.
H1: Disclosing unfavorable product information leads to a lower WTP (as compared to non-disclosure) whereas disclosing favorable product information leads to a higher WTP (as compared to non-disclosure)
2.3 Source of information
The (un)favorable product information can be communicated to the customer by either a dependent source (e.g., the firm) or an independent source (e.g., a customer). In general, there are two types of independent product information. The first type is third-party product review information from various third parties such as consumer magazines and websites. The second type of independent information is consumer-generated reviews (CRs) (Cheng & Xie, 2008). In this research, the focus is on communication by a dependent source; the brand.
Dependent communication sources are generally considered less credible and influential as independent communication sources (e.g., CRs) because the information
contained in independent source communication does not originate with the company (Arndt, 1967; Bickart and Schindler, 2001). In contrast to CRs, advertising by the brand does originate
14 with the brand. When positive information is disclosed by the brand, the source is expected to be less credible and thus lower in persuasion (Smith, De Houwer & Nosek, 2012). Traditional marketing communications by the brand namely present brands and/or products in a favorable way by presenting positive product information or associating the brand with positive
symbols (Crowley & Hoyer, 1994; Eisend, 2006). By doing so marketers attempt to influence consumers’ brand attitudes and preferences (Crowley & Hoyer, 1994). In contrast with
traditional marketing communications, organizations also have the option of being transparent and presenting unfavorable product information. In sum, there is a stream of research
suggesting that messages including certain amount unfavorable information can be more effective than if no unfavorable information is disclosed (Crowley & Hoyer, 1994; Eisend, 2006, Einwiller et al., 2006). When positive information is disclosed by the brand, the source is expected to be less credible and thus lower in persuasion (Smith et al., 2012). This suggests that disclosing very favorable information becomes incredible at some point and might backfire while also boundaries for the amount of unfavorable information exist.
Building on previous literature, it is likely that there is a point where the positive effect of brand transparency diminishes. This point might be when the information becomes too unfavorable and the negative effect of unfavorable information outweighs the positive effect of transparency or at the point where information becomes too favorable and thus not
credible. In the latter situation, the negative effect of low brand trust (Smith et al., 2012) outweighs the positive effect of the favorable information. This suggests that consumers’ WTP for a product with disclosed (un)favorable information is an inversed U- shaped line in which the upwards sloping line starts decreasing when the information becomes too favorable.
15 H2: Under disclosure conditions, there is a relation between the valence of the
disclosed information and WTP which follows and inversed U-shape with a breaking point at the positive information disclosure condition.
2.4 Product category price
The product on which the brand discloses (un)favorable product information can be of different product categories. Product prices can be unequal for different product categories; cars are more expensive as bikes while bikes are more expensive as shower gels. Consumers’ perception of price is based on the objective (actual) price and consumers’ reference price (Winer 1986; Erickson and Johansson 1985). The objective price has a positive influence on consumers’ price perception whereas reference price has a negative influence on consumers’ price perception (Chang and Wildt, 1994). In this research, the focus is on differences between product categories, thus on objective price.
Previous research shows that when the price of the product increases, so does the customers’ expectations before the use of the product (Gneezy et al., 2014; Plassmann, O’Doherty, Shiv & Rangel, 2008). It has been suggested that people are more likely to use price as an indicator of high quality for relatively expensive products (Rao & Monroe 1989). This is especially so when the consumer is faced with performance or quality uncertainty. At the moment a consumer purchases a product he exposes himself to risks. Perceived risk is associated with the purchase of a product has been identified as a critical determinant of consumers’ WTP (Grewal, Gotlieb & Marmorstein, 1994). The three types of risk that are commonly associated with purchases are; functional, social and financial (Delvecchio 2001; Delvecchio & Smith, 2005; Dowling and Staelin, 1994). In this research the focus is on the latter risk; the financial risk. Delvecchio and Smith (2005, p. 187) define financial risk as: “the economic outlays that may be lost if a product does not perform adequately. Mitchell and
16 Greatorex’ (1993) definition elaborates on the loss of non-performance of the product by defining this as money loss from product failure and/or money loss to replace the product. By doing so, they include the future financial cost of replacement.
Results of Kaplan, Szybillo and Jacoby (1974) show an increase in financial risk as the objective product price increased. The effect of product price is acknowledged by Mitchell (1999), who states that perceived risk is often been seen as antecedent of involvement, especially when product price is high and consumers thus risk losing money. Based on prior research, the financial risk is expected to be higher for product categories with a higher objective price as for product categories with a lower objective price.
The perceived financial risk is not only influenced by the price of the product; disclosing product information enables firms to influence consumers’ perceived risk. By making more product information easy available for customers, the perceived risk is decreased (Jarvenpaa & Todd, 1997). Ha (2002) states that there is a high possibility that unfavorable information increases the perceived risk whereas favorable information decreases the perceived risk. This suggests that, the effect of information valence on WTP may be affected by differences in consumers’ financial risk and thus, by different product categories. Since the financial risk is higher for higher priced products, the effect of product category price is expected to be larger for high priced products. Therefore, the following hypothesis is proposed:
H3: The effect of disclosure (as compared to non-disclosure) on WTP is moderated by product category price, such that the effect is larger when product price is higher.
17 2.5 Brand trust
Over the years, trust has received a great deal of attention in several disciplines (Delgado-Ballester, Munuera-Aleman & Yague-Guillen, 2003). Friestad and Wright (1994) state that consumers generally do not trust marketers but firms may be able to reduce consumer distrust by being transparent. Kirby (2012) states that the greater the transparency, the greater the trust. According to her, companies that are transparent do not have to ask their customers to have faith in a ‘black box’.
Brand trust is a predictor of consumer behaviors as product choice, loyalty and WTP (Chaudhuri & Holbrook, 2001). Consequently, trust is one of the most desired qualities in a relationship and the most important attribute any brand can own (Delgado-Ballester et al., 2003). Mayer, Davis, and Schoorman (1995) state that trust is the willingness to be vulnerable to the actions of another party. Barney and Hansen (1994, p. 176) define trust as “the mutual confidence that no party to an exchange will exploit another ones vulnerability”. Delgado-Ballester et al. (2003, p.11) combined relevant components of prior in their definition of trust; “feeling of security held by the consumer in his/her interaction with the brand, that it is based on the perceptions that the brand is reliable and responsible for the interests and welfare of the consumer”.
Based on the discussion above, brand transparency is suggested to positively affect consumers’ feeling of security in his/her interaction with the brand and thus several consumer behaviors (including WTP). However, prior studies found both positive and negative results of transparency. These contradicting results might be caused by favorableness of disclosed information. In addition, Demmers (2014) states that disclosure of positive information is less likely to contribute to brand trust. This suggest that the effect of transparency on WTP is mediated by brand trust.
18 H4: The effect of valence of disclosed information on WTP is mediated by brand trust.
2.6 Conceptual framework
The four proposed hypotheses are presented in Figure 1. The framework tests for the effect of information valence on WTP, the moderating effect of product category price on the effect of information valence on WTP and whether the effect of information valence on WTP is mediated by brand trust.
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3. METHODOLOGY
3.1 The sample
The population for this study consists of consumers of developed countries who have internet access. For this large research population no sampling frame could be established. Therefore, non-probability sampling was used. The study used an 8x2 mixed within-between subjects survey design. To be able to generalize conclusions over the population, the minimum sample size consist out of 225 customers. To increase the reliability of the experiment, the goal was to collect a sample as big as possible.
On May 5th 2015, the online survey experiment was distributed. On May 20th, a total of 245 respondents participated in the research. The sample as a whole was relatively young (M = 28.73, SD = 9.98). 127 of the 245 respondents were men (52%) and 118 were women (48%). 36% of the respondents had WO (n = 88) as their highest completed education. The distribution of the other respondents regarding their highest level of education was; VMBO (n = 6), HAVO (n = 24), VWO (n = 28), MBO (n = 23), HBO (n = 74) and none of the before (n = 2).
3.2 Research design
To be able to identify and explain the effect of disclosing (un)favorable product information, the product priced category and brand trust on consumers’ WTP, the independent variables had to be manipulated while holding the other variables constant. Hence, an experiment though an online survey was conducted. A pretest was used to determine the disclosed product information for the different valences of transparency used in the experiment.
The main study conducted an 8 (valence of disclosed information; very unfavorable, unfavorable, mildly unfavorable, neutral, mildly favorable, favorable, very favorable and no information) X 2 (product price; high vs. low) mixed within-between subjects factorial design
20 was developed. The levels of valence of disclosed (un)favorable product information were manipulated by using the same advertisements with minor changes. In the first eight
treatments the disclosed information regarding burn time of a tea light and the battery life of a smartphone were manipulated. In the final treatment, no product information was disclosed. In all advisements, one extra product attribute (e.g. amount of tea cups in the box and internal memory) was communicated. This product attribute was communicated because it is
considered an important determinant for the product price (e.g., the number of tea lights and the amount of internal storage). The respondents randomly get to see first one of the eight advertisement conditions for the high or low priced product followed by one random advertisement for the other product (see Appendix A for examples of advertisements).
3.2.1 Dependent variable
Consumers’ willingness to pay The dependent variable of this study is consumers’ WTP. Breidert et al. (2006) provided a systematic overview of numerous approaches to measure willingness to pay. One approach described in their article is the direct approach. In this approach the respondents are directly asked to indicate an acceptable price for a product. In this study the direct approach though an online survey was used to measure willingness to pay. Because consumers’ WTP was measured though an online survey and respondents did not actually buy the product, the hypothetical WTP for the product was measured. After communicating advertisement of both products with one of the eight conditions, respondents were asked if they would buy the product for the actual market price. By doing so, the
respondents are all familiar with the market price of the products. Especially the retail price of the smartphone might be unknown to the respondents because this product is usually not purchased for the retail price but in combination with a contract. Regardless the respondents’ answer, thereafter WTP was measured with an open-ended question. Respondents were asked
21 to indicate what would be the maximum price they are willing to pay for the product. This type of measure has been used in several studies to WTP (e.g., Krishna, 1991; Homburg, Koschate, Hoyer, 2005)
3.2.2 Manipulations
Valence of disclosed product information The first independent variable, valence of disclosed (un)favorable information, is measured for eight conditions. To determine what burn time and battery life was considered for each condition, a pretest was conducted. The results of the pre-test were used to design 16 unique advertisements for the main study. In the control condition for the low or high priced product, the advertisement was communicated without information of burning time or battery life. For the other conditions the burn time and battery life are manipulated so that they meet the results found in the pretest (see Table 1).
Product category price To test whether product category price has an moderating effect on the relationship between the valence of disclosed information and consumers’ WTP, this has to be manipulated. Therefore, both a higher priced product and a lower priced product are used in this study. For the higher priced product category, the Apple iPhone 6 plus is used. For the lower priced product category, a package tea lights of Blokker is used. For an overview of the products, product specifications and retail prices, see Table 2.
22 Brand trust Brand trust can be seen as the underlying mechanism of transparency.
Hence, respondents’ brand trust was assessed though a one-dimensional scale consisting of four items. The four items were based on Chaudhuri and Holbrook’s (2001) scale. This scale uses the following four statements; “I trust this brand”, “I rely on this brand”, “this is an honest brand” and “this brand is safe”. Respondents were answer using a seven-point Likert scale of agreement ranging from 1 (strongly disagree) to 7 (strongly agree).
3.2.3 Pre-test
To determine what burn time and battery life was considered for each condition, a pre-test was conducted. On April 2nd 2015, the online pre-test survey was distributed, yielding in 35 usable surveys on the 3th of April. The sample was 57% female (n = 20) and 43% male (n = 15). The average age of the respondents was 26.3 years (SD = 6.7), spread between 20 and 54 years. Of the sample, 9% had HAVO as the highest achieved level of education (n = 3). The other respondents were divided as followed; 6% for VWO (n = 2), 6% for MBO (n = 2), 37% for HBO and 40% for WO (n = 14).
In the pre-test, advertisements for both the low and high priced product were used and the average burn time/battery life was communicated (e.g.,, average burn time = 4,5 hours and average battery life = 10 hours). Every respondent got to see advertisements for both the high and low priced product category accompanying average burn time and battery life. The respondents were asked to indicate the burn time and battery life for every condition.
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4. RESULTS
First, a check to examine if there were any errors in the data was conducted by checking the frequencies. The respondents that had missing values were deleted from the data such that only respondents with complete data were part of the dataset. Any errors in the data due to wrongly answered questions were corrected when it was clear what the respondent wanted to answer. Examples of corrections are changing the word “gelijk” (equal) to the price stated in the text, changing the word “niks” (nothing) to 0, changing points into commas, changing “5 euro” to 5,00 and correcting negative bids to 0.
4.1 Normality and correlation check
First, a test for normality was conducted using the Shapiro-Wilk test (see, Table 3). The results showed that the very negative condition was the only valence of transparency for the low priced product that was normal distributed (p > 0,05). The positive and control group were almost significant normal distributed. For the high priced product, the very negative and control group were not normal distributed (p < 0.05). For the other six conditions significant support for a normal distribution was found (p > 0.05). In addition, transforming the data did not improve the normality. This indicated that the distribution was not normal distributed and thus a non-pragmatic test might be a better choice as a pragmatic test (Field, 2013).
The pragmatic test that fits the independent (ordinal) and dependent (continuous) variables is ANOVA. The most well-known non pragmatic alternative to the pragmatic is the Kruskal and Wallis test (1952). The advantage of the Kruskal and Wallis test is the potential greater statistical power when the data is normal distributed (Blair & Higgins, 1980).
However, non-pragmatic and pragmatic tests both assume that the data in the different groups have the same distribution. If different groups have different shaped distributions (for
24 will not provide better error control as pragmatic tests (Lix, Kesselman & Kesselman, 1996). However, the different conditions of the experiment did have different shaped distributions (see appendix C). Thus, a non-pragmatic test was not expected to provide better results as a pragmatic test. In addition, it has been suggested that the ANOVA test is robust concerning violation of the normality assumption. Recent research indeed found that the type of
distribution (e.g., non-normal or normal) does not have a significant result on ANOVA results (Schmider, Ziegler, Danay, Beyer & Bühner, 2010). Both the type I and type II error remain constant under violation of the normality assumption. Based on the previous discussion, it was decided to use pragmatic tests, despite of the non-normal distributed data.
Subsequently, a correlation check and a descriptive statistics analysis for WTP were conducted. The correlation check (see Table 3) showed that for both the low and high priced product categories, information valence was correlated with WTP and trust. For the low priced product category, information valence and WTP were correlated, r(214) = 0.24, p < 0.01. Likewise, information valence and trust were correlated, r(214) = -0.26, p < 0.01. For the high priced product category price, information valence were more strongly correlated as compared with the low priced product category, r(211) = 0.46, p < 0.01. In contrast, the correlation between information valence and trust was weaker correlated, r(211) = -0.22, p < 0.01. In addition, gender and WTP are correlated solely for low priced products, r(214) = -0.14, p < 0.05.
25 Table 4 shows the descriptive statistics for consumers’ WTP. The mean scores for consumers’ WTP for the high and low priced product category are not comparable since the retail prices differ. Therefore, a willingness to pay index is calculated. The willingness to pay index shows the index score compared with the control group without disclosing of
information (control group = 100). The WTP index scores of both products now fit in one bar chart (see Figure 2).
26 Figure 2; Visual graph of WTP index for low and high priced product categories
27 4.2 Model testing
In the following section, the proposed hypotheses will be tested with the use of statistical tests in SPSS. In this thesis, the hypotheses were tested at a significance level of p < 0,05.
The first hypothesis suggests that disclosing unfavorable product information leads to a lower WTP (as compared to non-disclosure) whereas disclosing favorable product
information leads to higher consumers’ WTP (as compared to non-disclosure). This
hypothesis is tested using One-Way ANOVA contrast tests. A contrast test was used because this test allows for testing for a difference between multiple groups and one. Levine’s test showed that equal variances were not assumed (p < 0,05). To check for the influence of (un)favorableness two contrast tests were conducted; disclosing unfavorable information compared with non-disclosure (contrast 1) and disclosing favorable information compared with non-disclosure (contrast 2). Table 5 shows the results of the tests that disclosing
unfavorable and favorable information indeed have different results. Disclosing unfavorable information leads to a lower WTP as compared to non-disclosure while in contrast disclosing favorable information leads to a higher WTP as compared to non-disclosure. However, solely the negative effect of disclosing unfavorable information on WTP as compared to
non-disclosure is significant (p < 0.01). Therefore, partial support for hypothesis has been found.
The second hypothesis suggests that there is a relation between the valence of the disclosed information and WTP which follows an inversed U-shape with the breaking point at positive information. This inversed U-shape would be realized if the WTP decrescent
28 increases since the first condition until the condition of positive information disclosure. After this condition, the WTP would have to decrease progressively up to and including the last condition. This is tested using contrast tests comparing every condition with the condition that follows. The results (see Table 6) showed that the value of contrast increased up and until the disclosure of positive information condition. The increase in WTP however, is not declining; the increase in WTP from the mildly positive condition to the positive condition seems to be bigger than the increase of the mildly negative to neutral condition as well as the increase of the neutral to the mildly positive condition. In addition, the results showed that the WTP only seemed to decrease from the positive to the very positive condition. This result however, was not significant. Therefore, hypothesis 2 is not supported.
To test the third hypothesis a moderation analysis has been conducted. It is suggested that the effect of disclosure is moderated by product category price, such that the effect is larger when the product price is higher. This moderator hypothesis is tested by using Baron and Kenny’s (1986) model for moderation (see Figure 4) including three causal paths;
a. The impact of information valence on WTP b. The impact of product category price on WTP
29 c. The impact of the interaction of information valence and product category price on
WTP
Figure 4; Baron and Kenny’s (1986) model for moderation
The three paths are tested using Hayes’ (2012) PROCESS tool. Moderation is shown up by a significant interaction effect, and in this case the interaction is highly significant, b = 6.2633, 95% CI [2.7962, 9.7304], t = 3.5508, p = 0.0004, indicating that the relationship between valence and WTP is moderated by product category price (see Table 7).
30 The graph in Figure 4 shows that the slope of the line for the high priced product category is steeper as the line representing the low priced product category. Thereby, the lines of the high and low priced product category intersect at one point in the graph which suggests that
product category price is indeed a moderator. This confirms the assumption that the effect of disclosure on WTP is moderated by product category price, such that the effect is larger when product price is higher. Thus, hypothesis 3 is supported.
Figure 4; Visual graph of moderating role of product category price on WTP
The last hypothesis suggests that the effect of Valence of disclosure on WTP is mediated by brand trust. According to Baron and Kenny (1986) brand trust is a mediator if
a. Information valence significantly affects brand trust. b. Information valence significantly affects WTP.
c. Perceived trust significantly affects WTP controlling for information valence.
31 The effect of Information valence on brand trust (a) The results show that information valence has a significant negative effect on brand trust (b = -0.4757, t = -2.2053, p = 0.0000). Information valence explains 5.46% of the variance in perceived trust.
The effect of trust on WTP (b) The proposed mediator has a significant effect on the WTP (b = 1.3794, t = 3.1907, p = 0.0015). This effect is positive which means that an increase in consumers’ trust, results in a higher WTP.
The direct effect of information valence on WTP (c) Information valence, without trust as a mediator in the model, also significantly predicts WTP (b = 7.5154, t = 8.5380, p = 0.0000). The indirect effect of information valence on WTP (c’) Using 1,000 bootstrap samples, the results give an estimate of the indirect effect of information valence on WTP (b = -0.6562) with an bootstrapped standard error of 0.2185. Assuming the sample is one of the 95% that hits the true value, it means that the true bvalue with for the indirect effect falls between -1.1666 and -0.3020. This range did not include 0. Therefore; there is likely to be a genuine indirect effect between information valence and WTP. Thus, significant results were found for the mediating role of trust between information valence and WTP. This represents a relatively small effect (Kappa-squared = 0.039, 95%, BCa CI [0.018, 0.070]). Because the effect of information valence on WTP does not decrease to zero with the inclusion of trust, partial mediation rather than perfect mediation has occurred (Preacher & Hayes, 2004).
32
5. DISCUSSION
The results of the study fail to confirm hypotheses H1 and H2; disclosing favorable product information does not lead to higher consumers’ WTP (as compared to non-disclosure) and the relation between information valance and WTP does not follow a perfect inversed U-shape. Despite the study failed to support the hypotheses, interesting results were found. For hypothesis 1, partial significant support was found; disclosure of unfavorable information leads to a lower WTP as compared to non-disclosure. In addition, disclosure of favorable information seems to have a positive effect on consumers’ WTP as compared to non-disclosure. This effect however, is not statistical significant.
Furthermore, the relation between information valance and WTP does not follow a perfect inversed U-shape but some assumptions on which this hypothesis was build were supported. For example, the WTP does increase as the information valence becomes more favorable up to and including the positive information disclosure condition. This is in line with the information integration theory of Anderson (1971) and research of Smith (1993). This increase however, does not decrease exponential. In addition, the WTP does increase up and until the positive condition. Thus, the positive effect of disclosing information has boundaries which are expected to be caused by trust. The breaking point seems to be positive information. However, no significant results for this breaking point were found.
The results do show that the effect of valence of information disclosed on consumers’ WTP is moderated by product category price so that it has larger effect when the product category price is higher. This finding is in line with hypothesis 3. The moderating effect was expected since consumers’ perceived financial risk increases as the absolute price of the product increases. Finally, the results did find statistical significant support for the mediating role of brand trust. This is a partial rather than a full mediation. Despite that fact that this
33 effect is relatively small, is shows that the effect of valence of information disclosed on
consumers’ WTP is mediated consumers’ perceived brand trust.
5.1 Contribution
This research has important implications for companies in today’s business world. Firstly, the findings showed that the favorableness of disclosed product information may affect
consumers’ WTP. Hence, companies should take the favorableness of information in account when making disclosing and non-disclosing decisions. Companies should especially be careful when the product information is unfavorable since the present study showed that this leads to a lower WTP as compared with non-disclosing. Disclosing favorable product information on the other hand seems to affect consumers’ WTP positively. However, no significant results were found for this positive relationship. Secondly, this study’s findings showed that the effect of information valence on WTP in moderated by product category price such that the effect is larger when product price is higher. Thus, companies that sell products that have a high objective price should be extra careful with disclosing product information. In the case of unfavorable information, consumers’ WTP is expected to decrease even more as compared to lower priced product categories. In the case of favorable information, companies can use the moderating effect of product category price in their advantage by disclosing favorable product information. Finally, companies should be able to increase the WTP by focusing more on brand trust. The mediating role of perceived trust between information valence and WTP shows that brand trust is partial caused by information valence and has a positive effect on consumers’ WTP. Therefore, companies can try to find other ways to increase consumers’ brand trust and thus increase WTP. However, the mediating effect of trust is relatively small.
34 5. 2 Limitations and future research
Firstly, the data is non-normal distributed and the different groups have different shaped distributions. This might decrease the statistical power of the tests and thus the validity of the results. Secondly, a couple of limitations can be identified while looking at the demographics of the sample. For example, the average age of the respondents was lower as the population of consumers in developed countries and the majority of the sample (66%) attended either the highest or second-highest education level. This possible discounts the generalizability of the results to all consumers. The next limitation are the products used in the experiment,
especially the use of a smartphone. A smartphone is almost invariably sold in combination with a subscription. When bought in combination with a subscription, the smartphone is much cheaper as sold separate or even given to the consumer for free. Despite the fact that the actual retail price has been communicated in the experiment, consumers might be less familiar with the actual price of the smartphone without subscription as for the package of tea lights. In addition, respondents might be less willing to pay an certain amount of money for the smartphone only because they are used to buying it in combination with a subscription and therefore for a lower price. Future research might use two products that can only be purchased for a standard price. The fourth limitation that should be noted is the use of products of two different brands. According to Forbes (2015), Apple is the most valuable brand of the world while Blokker is not in the top 100. This is not surprising because Blokker Holding is mainly active in the Netherlands and Belgium. By using two different brands, results may be partial caused by differences of consumers’ brand perception. A final limitation of this study is that consumers’ WTP is measured with an online survey. This survey is a hypothetical situation of which the customer is aware. Because the consequences for the customers are hypothetical rather than real, the external validity of the results is low. Future research might do a similar research in a real setting.
35 Another suggestion for future research is the relation between all variables, especially between the moderator and the mediator. Based on prior studies, there might be an
relationship between these variables. Friestad & Wright (1994) state that consumers generally do not trust marketers but firms may be able to reduce this distrust by being transparent. Transparent companies can avoid asking consumers to trust a ‘black box’ (Kirby, 2012). In addition, different definitions of trust suggest that consumers’ willingness to rely on risk are critical components of most trust (Grabner-Krauter & Kaluscha, 2003). This is acknowledged by Fischer Meffert & Perrey, (as cited in Matzler, Grabner-Kräuter & Bidmon, 2008) who state risk reduction can be seen as a basic function of a brand in the buying decision. Risk reduction is assumed to be even more important if the perceived risk is high (Matzler et al.,2008). In this study, no significant support was found for a moderating role of product category price on the effect of brand trust on WTP. This might be due to the focus on solely financial risk (e.g. objective product price) instead of all possible perceived risk indicators. Therefore, it might be interesting to study all mutual relations of disclosed information
valence, brand trust, perceived risk (including financial, functional and social risk) and WTP. Nevertheless, this study provides an important first step into establishing the
boundaries of the positive effects disclosing unfavorable and favorable product information in advertisement. Moreover, it showed that the boundaries are influenced by the objective
36
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44
APPENDICES
Appendix A; Advertisements used in the experiment
Advertisements without communication of burn time/battery life:
Blokker tea lights: Apple iPhone:
Advertisements with communication of burn time/battery life:
45 Appendix B; Survey example
46 Random example of one of the 16 possible conditions (1/2)
47 Random example of one of the 16 possible conditions (2/2)
48 End of survey
49 Appendix C; Test for normality
