Heribert Gierl, Sabine Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective in:

Marketing ZFP, page 22 - 39

MAR, Volume 34 (2012), Issue 1, ISSN: 0344-1369, ISSN online: 0344-1369, https://doi.org/10.15358/0344-1369-2012-1-22

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Bibliographic information
Anmerkung: The authors would like to thank two anonymous referees for their helpful and constructive comments. Heribert Gierl is Professor of Marketing at the University of Augsburg, Universitaetsstrasse 16, 86159 Augsburg, Germany, Phone: +49/821 598 4051, Fax: +49/821 598 4216, E-Mail: heribert.gierl@wiwi.uni-augsburg.de. Sabine Pagel is Research Assistant at at the University of Augsburg, Universitaetsstrasse 16, 86159 Augsburg, Germany, Phone: +49/821 598 4054, Fax: +49/821 598 4216, E-Mail: sabine.pagel@wiwi.uni-augsburg.de. Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective By Heribert Gierl and Sabine Pagel Benefit arguments can be defined as appeals that marketers use to emphasise the advertised product’s benefits. These arguments differ in strength and type. The strength of arguments causes favourable or unfavourable product evaluations. The type of benefit argument used influences viewers’ thoughts to be either promotion or prevention oriented. Combined with other situational factors or elements of advertisements that also elicit promotion or prevention oriented thoughts, conditions result where thoughts are congruent (fit condition) or incongruent (nonfit condition). First, we provide evidence that product evaluations are more extreme in the fit condition than in the nonfit condition. Second, we show that feeling right, engagement, fluency, and the perceived strength of arguments are affected by regulatory fit, providing support for a suggested theoretical framework that describes the role of fit in the process of product evaluation. 1. Introduction Stimuli elicit thoughts. Imagine that you are exposed to the word “teeth” or to a picture of teeth. You could have thoughts that can be assigned to three categories. First, you could have thoughts about conditions to be achieved (e.g., white teeth, bright smile, and strong tooth enamel). It is desirable to achieve these conditions. Second, thoughts about conditions to be prevented may be evoked (e.g., cavities, plaque, and gingivitis). It is desirable to avoid these conditions. Third, thoughts may be elicited about issues that are neither to be achieved nor to be avoided (e.g., the address of your dentist and the clothing of her/his dental nurse). Following regulatory fit theory (Higgins 1997; 2000), the first two types of thoughts will be denoted as promotion and prevention thoughts, respectively. Based on the notion of promotion and prevention thoughts, certain stimuli may elicit either predominantly promotion thoughts or predominantly prevention thoughts. We refer to stimuli as promotion stimuli if the thoughts evoked by these stimuli predominantly concern conditions to be achieved. We denote stimuli as prevention stimuli if they predominantly elicit thoughts about conditions to be avoided. People are continually exposed to numerous stimuli. Therefore, there can be situations where promotion and prevention stimuli coexist. The literature on regulatory fit denotes the situation where either promotion stimuli alone or prevention stimuli alone are present as a regulatory-fit condition (Avnet/Higgins 2006a; Higgins 2000; Werth/Förster 2007). When promotion and prevention stimuli coexist, a regulatory-nonfit condition exists [1]. Advertisements frequently contain benefit arguments. Benefit arguments describe the consequences of using a product, including the social, hedonic, and health-related consequences. They differ from functional arguments, which describe product characteristics like technical features (e.g., horsepower) and ingredients (e.g., aluminum car body), and from explanations of how a product feature (e.g., an automatic brake system) operates. Benefit arguments can differ in strength and type. They are strong if they at least indirectly express the superiority of the promoted product in terms of the highlighted benefits in comparison to the competitors’ products. Benefit arguments are weak if they do not express superiority in terms of the benefits addressed. To be more precise, arguments are strong when subjects who are instructed to think about the message generate thoughts that are predominantly favourable. They are weak when the generated thoughts are predominantly unfavourable (Petty/Cacioppo 1986, p. 32). The effect of the strength of arguments is widely discussed in the literature on models such as the elaboration-likelihood model (Petty/Cacioppo 1986) and the heuristic-systematic model (Chaiken 1980). However, the type of benefit argument matters as well. The two types of benefit arguments are promotion- 22 MARKETING · ZFP · 34. Jg. · 1/2012 · S. 22–39 oriented and prevention-oriented arguments (Mogilner/ Aaker/Pennington 2008; Zhu/Meyers-Levy 2007). Promotion-oriented arguments predominantly elicit thoughts about outcomes that are to be achieved, such as fun, feelings of freedom, or social approval. Prevention-oriented arguments predominantly produce thoughts about outcomes that are to be prevented, such as illness, bad mood, or social disapproval. To illustrate the difference, we refer to an example provided by Wang/Lee (2006). An argument for a toothpaste brand emphasising that this product whitens the teeth is likely to evoke thoughts about desirable conditions, such as a bright smile, beauty, and social recognition. An argument highlighting the toothpaste’s ability to inhibit cavities and plaque is likely to produce thoughts about undesirable conditions, such as toothaches and dental costs. In an advertising context, aside from benefit arguments, numerous additional stimuli can be present that are either promotion or prevention oriented. These are the product category, the brand, peripheral cues, and priming stimuli. A regulatory-fit condition or a regulatory-nonfit condition results from the combination of these stimuli. As a consequence, it is important for marketers to know how the condition of fit or nonfit induced by stimuli in an advertising context affects product evaluations. 2. Research Questions Our research questions are as follows: (1) How does regulatory fit affect product evaluations? (2) Why does regulatory fit affect product evaluations? 2.1. Contradictory Findings in Previous Research Numerous researchers have provided evidence that regulatory fit resulting from combinations of the type of benefit argument and another determinant of regulatory fit has a positive effect on evaluations, behavioral intentions, and behaviors (e.g., Cesario/Grant/Higgins 2004; Lee/Aaker 2004; Mishra/Mishra/Nayakankuppam 2010; Spiegel/Grant-Pillow/Higgins 2004). For instance, Holler et al. (2008) showed that people report a higher intention to pay taxes honestly in the fit condition while elaborating on arguments describing the social benefits that result from paying taxes. Regulatory fit has also been shown to influence health-related behaviours. Zhao/ Pechmann (2007) found a positive effect of regulatory fit on pupils’ intention to abstain from smoking following exposure to arguments describing the benefits of not smoking. Researchers using advertisements for consumer products as test stimuli have found the same effect: in the regulatory-fit condition, benefit arguments were shown to cause more positive product evaluations (Lee/ Keller/Sternthal 2010; Wang/Lee 2006; Werth/Förster 2007). Higgins and his co-authors often question whether regulatory fit improves or amplifies evaluations and behavioral intentions (Cesario/Higgins/Scholer 2008; Higgins/ Scholer 2009; Pham/Avnet 2009; Scholer/Higgins 2009). For instance, Avnet/Higgins (2006a, p. 8) state the following: “Regulatory fit theory predicts that fit should increase the extremity of decision makers’ evaluations, regardless of the valence of their reactions. In other words, negative reactions should produce more negative evaluations when fit is experienced (...). This part of the theory has yet to be fully tested.” We are aware of four experiments published in literature that investigated the interaction effect of argument strength and regulatory fit on evaluations. The findungs are summarised in Tab. 1. The observed effects depicted in this table demonstrate that previous research does not provide a clear answer to the question on whether fit intensifies evaluations. The findings are seemingly inconsistent. Probably, differences in the studies’ experimental designs caused the divergent findings. First, different regulatory fit manipulations have been used and checks whether manipulations indeed caused congruent or incongruent thoughts are missing. Aaker/Lee (2001) and König et al. (2009) investigated the effect of fit-primes on the persuasiveness of arguments [2]. Block/Keller (1995) used a framing technique to manipulate fit [3]. Evans/Petty (2003) created fit and nonfit conditions by combining promotion- and prevention-oriented arguments with chronic regulatory focus [4]. Second, the figures contained in Tab. 1 show that the manipulation of argument strength was ineffective in two of the studies (Aaker/Lee 2001; Block/Keller 1995). Evans/ Petty (2003) found that strong fit arguments are more persuasive than strong nonfit arguments and weak fit arguments are less persuasive than weak nonfit arguments. However, they used a heuristic cue to manipulate argument quality and considered rather neutral than weak arguments. König et al. (2009) reported the opposite finding. Since Higgins, the protagonist of research in the area of regulatory focus and fit, was the co-auther of the latter study, this result is highly noteworthy. Moreover, the type of argument (promotion- vs. prevention-oriented arguments) has only been considered in the experiment of Evans/Petty (2003). Taking the contradictory findings in previous research as a starting point of further investigations, it seems to be reasonable to focus on a more particular case. We consider the interaction effect of argument strength and fit induced by benefit arguments and other situational determinants of regulatory fit on product evaluations and intend to provide insights into the underlying mechanisms. 2.2. Practical Relevance of Answers to the Research Questions The topic of this research is relevant for advertising. In an advertising context, several stimuli could be present aside from the argument inducing the fit or the nonfit condition. Sometimes, the product category itself is promotion or prevention oriented (Mourali/Pons 2009; Werth/Förster 2007). The category of luxury perfumes will produce predominantly promotion thoughts, such as “helps me to Gierl/Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective MARKETING · ZFP · Heft 1 · 1. Quartal 2012 23 be adored” and “serves to impress others.” The category of term life insurance policies is likely to induce thoughts about issues that should be prevented; people could think about their family’s financial difficulty in the case of their own or their partner’s sudden death. Admittedly, the majority of categories are neither promotion nor prevention oriented. However, within these categories that do not fall neatly into either orientation, sometimes brands exist that elicit predominantly promotion- or preventionoriented thoughts (Aaker/Lee 2001; Chatterjee/Roy/ Malshe 2011; Ramanathan/Dhar 2010; Zhou/Pham 2004). Being exposed to a picture of a shampoo brand positioned as a means to give the hair a silky shine will produce promotion thoughts, such as “makes me attractive.” Being exposed to a picture of the automotive brand Volvo could evoke prevention thoughts about car accidents and the consequences for one’s health, fighting children in the back seat, and the difficulties when cars do not start in winter time, all of which are claimed to be attenuated by owning a Volvo. Although they have not yet been discussed in the literature, peripheral cues can elicit predominantly promotion or prevention thoughts as well. For instance, imagine a beer brand that uses promotion arguments (e.g., “It’s a pleasure to drink”). Additionally, suppose that it sponsors the Olympic Games; this strategy might produce thoughts in consumers about conditions they can achieve (e.g., excitement, pride in their country’s athletes). Conversely, suppose that the brand sponsors the reforestation of rainforests in South America by means of a “one tree per bottle sold” campaign; this strategy might evoke thoughts in consumers about conditions that can be prevented (e.g., a feeling of carelessness regarding nature). It is likely that both strategies will positively affect product evaluations, but the combination of the first one with the promotion arguments additionally creates a fit condition, whereas the latter might create a nonfit condition, which both exert an additional influence on product evaluations. Prior to exposure to a target ad, the consumer can have contact with stimuli such as editorial reports or ads for other products. Imagine that a consumer is exposed to a commercial for cosmetics showing how to limit signs of aging, a commercial for funds reminding her/him to invest in financial products to avoid poverty in old age, and a commercial for toothpaste illustrating how painful gingivitis can be before viewing a target commercial. Because of these priming stimuli, thoughts about conditions to be prevented are likely to be predominant before the target has the chance to cause promotion vs. prevention thoughts, thus creating a nonfit or fit condition (Yeo/Park 2006). These examples illustrate that there are numerous possible paths to fit and nonfit conditions through combinations of benefit arguments with other stimuli that predominantly induce promotion or prevention thoughts. 2.3. Boundary of this Research Since the original work of Higgins and colleagues, there has been a plethora of research on how regulatory-fit conditions can be created and how regulatory fit affects evaluations. Previous literature provided evidence that the presence of mental states such as fluency and feeling right depends on the way how fit and nonfit conditions are created (e.g., Higgins et al. 2003; Lee/Aaker 2004; Zhao/Pechmann 2007). Thus, the source of fit can be seen as an important aspect to distinguish between serveral streams of research. We do not consider regulatory fit resulting from (1) combinations of benefit arguments and chronic regulatory focus, (2) combinations of benefit arguments and frames, and (3) fit-primes. We focus on regulatory fit that (4) results from combinations of benefit arguments and priming stimuli that induce promotion or prevention thoughts (e.g., Lee/Keller/Sternthal 2010; Florack/Scarabis 2006; Wang/Lee 2006; Werth/Förster 2007) and (5) fit that is induced entirely internally by combinations of benefit arguments and cues contained in the target stimulus (e.g., Lee/Aaker 2004; Spiegel/Grant- Pillow/Higgins 2004). For instance, if both the type of product advertised and the benefit arguments are either promotion oriented or prevention oriented, fit is induced entirely internally. 3. Theoretical Considerations and Hypotheses Higgins postulates that regulatory fit and nonfit are accompanied by certain experiences (e.g., Cesario/Higgins 2008; Higgins 2000; 2002; 2006; Higgins et al. 2003). These states are feeling right, engagement, and fluency. Recently, Vaughn et al. (2009) added considerations about vividness of thoughts. We combine these theories by including them in a single model of the role of regulatory fit in the process of product evaluation. 3.1. Feeling Right People feel more or less confident with their evaluation of a target stimulus depending on the extent that they believe that their judgments could be incorrect. Researchers postulate that people implicitly question whether their evaluation of a target stimulus is adequate (Camacho/Higgins/Luger 2003; Cesario/Grant/Higgins 2004; Schwarz 2006; Wan/Hong/Sternthal 2009). According to this theory, the congruency of thoughts (i.e., the regulatory-fit condition) causes a tendency in individuals to answer this question affirmatively (Avnet/Higgins 2006b). Then feeling right, which can be defined as the feeling of confidence in one’s own evaluation, is expected to be evoked. In the regulatory-nonfit condition, people are thought to believe that their assessment is inadequate due to the incongruence of thoughts (Higgins et al. 2003; Vaughn et al. 2006). Cesario/Grant/Higgins (2004) denote feeling right as a non-emotional feeling. The authors postulate that people treat this feeling like a piece Gierl/Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective 24 MARKETING · ZFP · Heft 1 · 1. Quartal 2012 Manipulation Target stimulus Regulatory fit Argument strength Argument type Dependent variable Results Aaker/ Lee 2001, p. 43 Fictitious tennis racquet brand Fit-priming technique: Exposure to a scenario combining different goalorientations and goal frames Emphasis on unique product features (yes vs. no) No variation (the arguments contained both promotion and prevention arguments) Attitude toward the brand (Abrand) Block/ Keller 1995, p. 197 Measures to be taken against HPV infection Framing technique: Using either a loss or a nonloss frame to express a prevention argument Varying information about the effectiveness of the measure suggested to avoid HPV No variation (prevention argument only) Attitude toward the suggested measure (Ameasure) König et al. 2009, p. 1348 Professional training program Fit-priming technique: Combining the request to report one’s hopes and aspirations vs. one’s duties and obligations with the assessment of thoughts about ways how to achieve these goals vs. to avoid impediments to reach these goals Using different arguments regarding the content of the training program No variation (functional arguments supporting the training program) Attitude toward the program (Aprogram) Evans/ Petty 2003, p. 319 Fictitious new breakfast product Combining chronic regulatory focus with the type of benefit argument Varying the proportion of consumers recommending the new product’s usage Promotion vs. prevention argument Attitude toward the product (Aproduct) Strong argument; Weak argument. Abrand fit nonfit 7 1 5.65 4.814.73 5.18 Ameasure fit nonfit 7 1 5.77 5.27 5.38 5.36 Aprogram fit nonfit 7 1 4.73 3.44 4.44 5.35 Aproduct fit nonfit 9 1 6.84 5.124.67 6.47 Table 1: Previous Research on the Interaction Effect of Regulatory Fit and Argument Strength on Evaluations of information about the target stimulus because they mistakenly interpret it as a feature of the target stimulus (Avnet/Higgins 2006a; Cesario/Grant/Higgins 2004; Schwarz 2006; Wang/Lee 2006). This argument can be transferred to the issue discussed here. If strong benefit arguments are available, consumers evaluate a product favourably. When they additionally experience feeling right due to regulatory fit (i.e., when the favourable evaluation feels right), the perceived strength of arguments is enhanced by this feeling, and the favourable evaluation is expected to become even better. On the contrary, if only weak arguments are available, consumers evaluate the product less favourably. When consumers additionally experience feeling right due to regulatory fit (i.e., when the unfavourable evaluation feels right), the perceived strength of arguments is reduced, and the unfavourable evaluation is likely to become even worse. Thus, regulatory fit could amplify evaluations if fit elicits feeling right (Aaker/Lee 2006, p. 16). 3.2. Engagement, Fluency, and Vividness of Thoughts Moreover, researchers in the field of regulatory fit discuss engagement and fluency as consequences of regulatory fit (Higgins 2005; Lee/Keller/Sternthal 2010; Pham/ Avnet 2009). To separate these concepts from feelings and distinguish between them in this discussion, we suggest applying a cognitive-resource-based view. Supposing that people are situationally able to execute cognitive activities to a certain extent, we assume a fixed capacity of cognitive resources when people elaborate on benefit arguments. One portion of this capacity is spent on product-related activities (e.g., Werth/Förster 2007). The other portion is spent on coexisting but unrelated stimuli (e.g., watching a fly in the room). The product-related portion can be further split between resources spent on encoding the benefit arguments and resources dedicated to other product-related activities. In sum, we consider three domains of cognitive resources to be situationally available. Engagement effect: Basically, the resources available for executing product-related cognitive activities (sum of portion A and B, see Fig. 1) depend on the individual’s interest in the target stimulus. From the literature on regulatory fit, we can derive the expectation that regulatory fit increases the resources available for executing product-related cognitive activities compared to the nonfit condition. Higgins and co-authors propose that people experience enjoyment while performing tasks such as evaluating objects in the regulatory-fit condition due to Gierl/Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective MARKETING · ZFP · Heft 1 · 1. Quartal 2012 25 Regulatory-nonfit condition A B C Regulatory-fit condition A B C A: Cognitive resources needed to encode the information contained in the benefit arguments (reduced by fluency). B: Cognitive resources available to execute further product-related cognitive activities. C: Cognitive resources spent to respond to unrelated coexisting stimuli. A+B: Total cognitive resources available to respond to the product (increased by engagement). A+B+C: Total cognitive resources situationally available. Fluency effect Engagement effect Strength of benefit arguments Product evaluations Valence and vividness of retrieved autobiographical knowledge and imaginations Perceived strength of arguments Regulatory fit resulting from the type of benefit arguments and further stimuli that evoke promotion or prevention thoughts Feeling right Engagement Fluency Figure 1: A Cognitive-Resource- Based View of Engagement and Fluency Figure 2: A Model of the Role of Benefit Arguments in the Process of Product Evaluations the congruence of thoughts (Freitas/Higgins 2002; Freitas/Liberman/Higgins 2002; Higgins 2000; Higgins et al. 2003; Vaughn et al. 2006). If people experience enjoyment while evaluating a target stimulus, they are expected to deploy more cognitive resources to that target stimulus (Pierro/Kruglanski/Higgins 2006). Higgins refers to this phenomenon as strength of engagement (Higgins 2006; Higgins/Scholer 2009). Freitas/Liberman/Higgins (2002) found that people experience more task enjoyment in the fit condition, even when the task itself is difficult and thus probably unpleasant. In a related area of research, Lee/Lee/Kern (2011) also provided empirical support for this assumption. Fluency effect: As mentioned above, when evaluating a product, people execute numerous cognitive activities (Labroo 2006). Some of these cognitive activities are necessary for encoding arguments. Researchers in the field of regulatory fit postulate that the information provided is processed fluently in the regulatory-fit condition (Cesario/Higgins 2008; Cesario/Higgins/Scholer 2008; Hong/Lee 2008; Lee/Aaker 2004; Scholer/Higgins 2009). If people are able to reduce the cognitive effort necessary for encoding the information contained in the benefit arguments (i.e., if they can execute this kind of activity “fluently”), a higher proportion of resources dedicated to product-related activities is available for executing further product-related activities (i.e., B/(A+B), see Fig. 1). Vaughn et al. (2009, p. 450) contributed to this research by providing an explanation why engagement and fluency induced by regulatory fit affect evaluations. They found that regulatory fit positively affects vividness of thoughts regarding the target stimulus. Thoughts are more vivid if people retrieve information from memory or if they imagine scenarios involving the product. Although retrieved memory and fantasy are not included in the arguments, they are mentally present while elaborating on the arguments (Burns/Biswas/Babin 1993; Childers/Houston/ Heckler 1985; Kisielius/Sternthal 1984; Miller/Marks 1992). For instance, if a person imagines herself in a situation, a vivid mental image is created (Escalas 2004). Imagine an apartment is advertised and one argument contains the information that the apartment has southward facing windows. If the recipient develops thoughts about the benefit (flooded with sunlight) s/he could additionally develop imaginations about how to use the rooms (e.g., sitting in the chair and watching clouds in the sky). Thereby, the intensity and clarity of thoughts (i.e., their vividness) about this benefit increases (Keller/McGill 1994). We conclude that regulatory fit affects evaluations via influencing vididness of thoughts enabled by an increase of engagement or higher fluency while elaborating on benefit arguments. The valence of thoughts is determined by the strength of arguments. We can summarise the arguments as following: If regulatory fit increases the resources available to execute further product-related cognitive activities, then evaluations become more extreme. If strong benefit arguments are present in the fit condition, consumers intensely elaborate on these favourable pieces of information; for instance, they could imagine themselves using this product and receiving favourable responses from friends. If weak arguments are presented in the fit condition, consumers Gierl/Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective 26 MARKETING · ZFP · Heft 1 · 1. Quartal 2012 unfavourable favourable unfavourable favourable unfavourable prior beliefs/weak arguments favourable prior brand beliefs & strong benefit arguments Prior brand beliefs existent Product evaluation regulatory nonfit regulatory fit H3 H2 weak benefit arguments strong benefit arguments Prior brand beliefs nonexistent Product evaluation regulatory nonfit regulatory fit H1 not considered Figure 3: Predicted Effect of Regulatory Fit on Product Evaluations Depending on the Strength of Arguments and Prior Brand Beliefs elaborate intensely on these unfavourable pieces of information; for instance, they imagine themselves using this product and envision the unfavourable reactions of friends. On the contrary, in the regulatory-nonfit condition, consumers are expected to spend less resources on further product-related activities, which inhibits responses such as creating vivid mental images involving the product: If strong arguments are provided, consumers elaborate less intensely on favourable consequences; if weak arguments are provided, they elaborate less intensely on unfavourable consequences. 3.3. A Model of the Role of Regulatory Fit in the Process of Product Evaluation In Fig. 2, we summarise our considerations. Basically, strength of benefit arguments affects product evaluations. Additionally, benefit arguments contribute to regulatory fit or nonfit, which alters the effect of strength of arguments on product evaluations. First, fit causes an affect denoted as feeling right that contributes to the perceived strength of arguments. Second, fit increases the cognitive resources available to execute additional product-related cognitive activities and thus enables the consumer to remember autobiographical events and develop mental images. Thus, fit affects the vividness of these thoughts, and the strength of arguments influences their valence. 3.4. Hypotheses The test of hypotheses is organised as follows: in the first step, we use a black-box approach and analyse whether regulatory fit intensifies product evaluations. To derive precise hypotheses, we separate the case of unknown brands from the case of well-known brands. In the case of unknown brands, based on the strength of the benefit arguments, favourable or unfavourable product evaluations result. Regulatory fit is expected to intensify these evaluations: H1: In the case where strong benefit arguments are used to promote a product of an unknown brand, evaluations are more positive in the regulatory-fit condition than in the nonfit condition. H2: In the case where weak benefit arguments are used to promote a product of an unknown brand, evaluations are less positive in the regulatory-fit condition than in the nonfit condition. In the case of well-known brands, there exist prior favourable or unfavourable brand beliefs that affect product evaluations as well. Therefore, it is extremely difficult to credibly manipulate the strength of benefit arguments for well-known brands. As a consequence, we only consider the condition of favourably evaluated wellknown brands and strong benefit arguments and test the following hypothesis: H3: In the case of favourable prior brand beliefs and strong benefit arguments, evaluations are more positive in the regulatory-fit condition than in the nonfit condition. In Fig. 3, we depict the relations postulated in these hypotheses. In the second step, we analyse whether regulatory fit affects feeling right, engagement, and fluency. This research is critical since the assumptions of the effect of fit on engagement in literature are contradictory (Keller/Bless 2006; König et al. 2009). The literature on regulatory fit states that the effect of experiences accompanied by regulatory fit (i.e., feeling right, engagement, and fluency) on evaluations is likely to be eliminated when people become aware of the possibility that such experiences exist (Aaker/Lee 2006). Cesario/Grant/Higgins (2004) found that the effect of fit on feeling right disappeared when people were informed about the possibility that feeling right could influence their judgments. They state the following: “Unless people have reason to question the appropriateness or relevance of some experiential state that comes to mind, they tend to assume that the information it provides is relevant, and they use it” (p. 388). Asking respondents to assess feeling right, engagement, and fluency could provide a reason for them to question the relevance of these mental states for product evaluations. To conclude, Gierl/Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective MARKETING · ZFP · Heft 1 · 1. Quartal 2012 27 Weak argument Strong argument Product categories Promotion argument Prevention argument Promotion argument Prevention argument Multivitamin supplement Fun throughout the winter! Celaforte contains (short list of ingredients) Cold season? Celaforte contains (short list of ingredients) Fun throughout the winter! Remember skiing, winter walking, ice skating, visiting mountain huts, sledding, building snowmen? Celaforte contains (long list of ingredients) Cold season? Celaforte contains (long list of ingredients) Instant loan Do you want to treat yourself to something special? If you pass our credit check: 12.95 %, one year duration, maximum loan amount € 5,000. Was the car repair again more expensive than expected? If you pass our credit check: 12.95 %, one year duration, maximum loan amount € 5,000. Do you want to treat yourself to something special? 3.95 %, one year duration, maximum loan amount € 5,000. No credit check required. Was the car repair again more expensive than expected? 3.95 %, one year duration, maximum loan amount € 5,000. No credit check required. Table 2: Manipulation of Strength and Type of Benefit Arguments Used in Experiment 1 assessing multiple constructs within the same questionnaire is seen as a source of serious concern because the effects resulting from regulatory fit, as depicted in Fig. 2, cannot be analysed effectively. We limit our additional analyses to testing the following hypotheses: H4: Regulatory fit increases the sensation of feeling right. H5: Regulatory fit increases engagement. H6: Regulatory fit increases fluency. H7: In the case of the use of strong benefit arguments to promote a product of an unknown brand, the perceived strength of benefit arguments is higher in the regulatory-fit condition than in the nonfit condition. H8: In the case of the use of weak benefit arguments to promote a product of an unknown brand, the perceived strength of benefit arguments is weaker in the regulatory-fit condition than in the nonfit condition. 4. Experiments We conducted five experiments. In the first three experiments, we aimed to answer the first research question by combining a sample of promotion- or prevention-oriented stimuli with the appropriate types of benefit arguments to create fit and nonfit conditions. These combinations were the following: type of benefit argument × type of prime (Experiment 1), type of benefit argument × type of product category (Experiment 2), and type of benefit argument × type of brand (Experiment 3). In the last two experiments, we aimed to provide answers to the second research question by analysing whether regulatory fit affects feeling right, engagement, fluency, and the perceived strength of arguments. All of the experiments were conducted in Germany and used between-subjects designs. 4.1. Experiment 1 In the first experiment, we created the fit and nonfit conditions by combining each type of benefit argument with each type of priming stimulus. We used the latter factor in our introductory experiment because priming techniques are commonly used among researchers in the field of regulatory fit (e.g., Chang/Chou 2008; Jain/Agrawal/ Maheswaran 2006; Lee/Keller/Sternthal 2010; Pham/Avnet 2004; Wang/Lee 2006; Werth/Förster 2007; Yeo/Park 2006; Zhao/Pechmann 2007). Based on the results of a pretest, we used products from categories that are neither clearly promotion oriented nor clearly prevention oriented (multivitamin supplements and instant loans). The experimental design was a 2 (strength of benefit argument: strong vs. weak) × 2 (type of benefit argument: promotion vs. prevention) × 2 (type of prime: promotion vs. prevention) factorial design. The product category served as a replicate factor. Benefit arguments: Tab. 2 shows the manipulations of strength and type of benefit arguments. We will analyse whether strength was manipulated as intended in a manipulation check. In a pretest, we will show that the types of arguments differ in the thoughts elicited. In the case of the multivitamin supplement, we varied the number of ingredients. This conceptualisation conforms to the definition of argument strength used by Petty/Cacioppo (1986, p. 32) since a high number of ingredients signals that the supplement successfully fights against any cause of a cold indicating the superiority of this product. Hence, the number of ingredients does not simply represent an additional peripheral cue. Furthermore, in the prevention-argument condition, information about the percentage of people suffering from a servere cold in the winter was provided. Primes: When consumers process information, they can be affected by thoughts that are induced by stimuli to which they have previously been exposed. These stimuli are denoted as primes. In our priming condition, participants were exposed to editorial reports about national parks in South Africa. In the promotion-prime condition, participants read a report about positive events that could be experienced when visiting a national park on vacation. In the prevention-prime condition, the text contained a report about successful measures taken to end Gierl/Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective 28 MARKETING · ZFP · Heft 1 · 1. Quartal 2012 Reported thoughts Promotion thoughts only Prevention thoughts only Promotion and prevention thoughts Neither promotion nor prevention thoughts Type of benefit argument/category Promotion/multivitamin supplement 24 3 2 1 Prevention/multivitamin supplement 0 22 4 4 Promotion/instant loan 19 5 0 6 Prevention/instant loan 1 27 1 1 Prime Vacations in a national park 21 1 1 7 Poachers in a national park 0 25 0 5 Note: Figures indicate the number of participants in the pretest who gave each type of response. Table 3: Promotion/Prevention Thoughts Induced by the Manipulations Used in Experiment 1 poachers’ practice of killing elephants for their ivory. This manipulation should not cause confusion with the manipulation of conceptual fluency (e.g., Lee/Labroo 2004) because national parks in South Africa do not have commonalities with multivitamin supplements or instant loans and consumers should thus not expect to see an ad for a product in these categories after reading this kind of editorial text. Moreover, this manipulation should avoid confusion with manipulations of goal fluency (e.g., Labroo/Lee 2006); after reading a text about vacations in South Africa, respondents might consider goals such as recreation, the acquisition of new knowledge, or becoming familiar with foreign cultures, but these are not goals directly associated with multivitamin supplements or instant loans. Analogously, reading a text about measures taken against poachers should not motivate people to think about goals that can be achieved by vitamin supplements or instant loans. Furthermore, this manipulation should avoid confusion with mood manipulations; we investigate this aspect although previous literature reports that manipulations of regulatory fit does not affect mood (Cesario/Grant/Higgins 2004; Evans/Petty 2003; Higgins et al. 2003; Vaughn et al. 2006; Wan/Hong/Sternthal 2009; Yeo/Park 2006). We analyse this final premise in the pretest. Pretest: The benefit arguments and primes employed should induce either promotion or prevention thoughts. Following the suggestions of other authors (e.g., Cesario/Grant/Higgins 2004; Lee/Aaker 2004; Maheswaran/ Meyers-Levy 1990; Zhu/Meyers-Levy 2007), we conducted a pretest and asked the participants to perform a thought-listing task. For this pretest, we created six versions of stimuli. To assess the promotion or prevention orientation of thoughts elicited by the arguments for multivitamin supplements, we depicted a fictitious product on a piece of paper and included one of two short versions of the arguments (“Fit through the winter” vs. “Cold season”). The participants had to report their thoughts in as much detail as necessary using complete sentences that are suitable for fully understanding these thoughts. In the case of instant loans, participants were requested to think about this product after reading one of two arguments (i.e., “Treat yourself to something special” vs. “Car repair”) and to write down their thoughts in detail using complete sentences. Other participants were exposed to the editorial text, which described experiences during a vacation in a national park or successful measures taken to cope with poachers. They had to describe in detail the thoughts elicited by the text. A total of 180 participants took part in this pretest. They were assigned to six sample groups. Each group was exposed to a single stimulus. The pretest sample group and the sample group used in the main study did not differ with regard to age or gender. Two people classified the data [5]. They assigned each participant into the categories “reports promotion thoughts only,” “reports prevention thoughts only,” “reports both promotion and prevention thoughts,” and “reports neither promotion nor prevention thoughts.” The classifications of the two coders did not differ markedly and were further checked by the authors. The promotion argument for multivitamin supplements evoked thoughts such as “recharges your batteries for adventures;” the prevention argument elicited thoughts such as “good way to compensate for eating unhealthy food.” The promotion argument for instant loans produced thoughts such as “let’s go shopping” and “can buy many nice things;” the prevention argument evoked thoughts such as “helps me to avoid current financial distress.” In the case of the text about vacations in a national park, thoughts such as “experience pure air,” “feelings of freedom,” and “discover another fascinating world” indicated promotion thoughts; in the case of the text about successful measures taken against poachers, “reasonable activities to inhibit illegal behaviors,” “evidently successfully prohibits cruelty to animals,” and “efficient impediments to crime” represent prevention thoughts. In sum, the results of the thought-listing task summarised in Tab. 3 reveal that the stimuli used successfully manipulated the promotion/prevention orientation of participants’ thoughts. The participants who were exposed to the editorial texts were additionally asked to indicate their mood. We used a five-item (happy, pleased, cheerful, sad, and dejected), seven-point scale and found no significant effect of priming on mood. Procedure: We created an online survey. The questionnaires were located at www.voycer.de. We asked our students to post the link to the questionnaire via their social networks (e.g., Facebook and XING). Following the technique of snowball sampling (Salganik/Heckathorn 2004), the message contained the information that the Gierl/Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective MARKETING · ZFP · Heft 1 · 1. Quartal 2012 29 Weak argument Strong argument Nonfit condition Fit condition Nonfit condition Fit condition Category Promotion prime & prevention argument Prevention prime & promotion argument Promotion prime & promotion argument Prevention prime & prevention argument Promotion prime & prevention argument Prevention prime & promotion argument Promotion prime & promotion argument Prevention prime & prevention argument Multivitamin supplements 2.00 (.92) 2.30 (1.12) 1.35 (.53) 1.46 (.77) 4.39 (1.29) 4.39 (1.27) 4.87 (1.59) 4.72 (1.45) Instant loans 3.92 (.90) 3.72 (1.41) 3.50 (.97) 2.77 (1.09) 5.20 (.61) 5.22 (.54) 5.57 (.77) 5.66 (.61) Overall 3.30 (1.28) 3.30 (1.47) 2.54 (1.34) 2.30 (1.17) 4.90 (1.00) 4.92 (.98) 5.37 (1.11) 5.32 (1.05) Notes: Scale ranges from 1 (negative product evaluation) to 7 (positive product evaluation). Standard deviations in parentheses. Table 4: Impacts of Strength of Argument and Regulatory Fit between Type of Benefit Argument and Type of Prime on Product Evaluations link should be spread across all friends of the persons reached. The message contained a notice that the survey was being conducted for scientific purposes only. Additionally, leaflets were distributed in pedestrian zones requesting people to visit the website. Data collection took place in 2009 and 2010. The respondents first were exposed to one version of the editorial text and were asked to read it carefully. Then each respondent was exposed to one of the eight ad versions resulting from combinations of product category, argument strength, and type of benefit argument. Each ad contained a picture and one version of the argument. Then the respondents had to rate the product by rating the extent to which they found it “attractive,” “positive,” “appealing,” and “interesting” on seven-point scales (Cronbach’s α = .959). In the next step, the respondents indicated their familiarity with the category to which the evaluated product belongs and its importance to them on seven-point scales. Finally, they reported their age and gender. Sample: The sample consisted of 684 respondents (Mage = 27.74 years, SD = 8.79; 48.9 % female). There were no remarkable differences in category familiarity or importance across experimental conditions. Results: The results of Experiment 1 are summarised in Tab. 4. For the purpose of a manipulation check, we compared product evaluations in the weak- and strong-argument conditions. We analysed whether the strong-argument versions of the advertisements led to more positive product evaluations compared to the weak-argument versions. The manipulation of argument strength proved to be successful (Mweak = 2.88, Mstrong = 5.15, F(1, 682) = 584.18, p < .001). Since 2.88 is below the value 4 (the center of the scale ranging from 1 to 7 used to assess product evaluation) and 5.15 exceeds this center, weak arguments actually produced unfavourable evaluations and strong arguments caused favourable evaluations. Because we found no further relevant differences across experimental conditions, we collapsed the data across product categories and the different forms of induced fit and nonfit and considered the fit and nonfit conditions for weak and strong arguments. In line with H1, in the case of strong arguments, regulatory fit produced more positive product evaluations than regulatory nonfit (Mstrong, fit = 5.34, Mstrong, nonfit = 4.91, F(1, 381) = 17.01, p < .001, η = .041). In line with H2, in the case of weak arguments, regulatory fit produced less positive product evaluations than regulatory nonfit (Mweak, fit = 2.41, Mweak, nonfit = 3.30, F(1, 299) = 34.05, p < .001, η = .139). Discussion: Regarding the first research question, our results provide evidence that regulatory fit is an intensifier of evaluations. The alternative propositions that fit improves evaluations or makes them less extreme have to be rejected. However, this finding was based only on one kind of manipulation of fit/nonfit. Therefore, we test the effect of an additional manipulation of fit/nonfit in Experiment 2, in which we will demonstrate that the effect of situational fit/nonfit does not depend on how it is created. 4.2. Experiment 2 In Experiment 2, we created the fit and nonfit conditions by varying the type of benefit argument and the product category. The experimental design was a 2 (strength of benefit argument: strong vs. weak) × 2 (type of benefit argument: promotion vs. prevention) × 2 (type of product category: promotion vs. prevention) factorial design. For each product category, we considered two kinds of products. Product categories: Based on the pretest results, which are reported below, we selected mountain bikes and MP3 players as representatives of the promotion category and external hard drives for computers and term life insurance policies as representatives of the prevention category. Benefit arguments: Tab. 5 illustrates the arguments included in the various advertisement versions for a mountain bike in this experiment. We used similar manipulations to create analogous versions of argument texts for MP3 players, external hard disk drives for computers, and term life insurance policies. Pretest: The pretest procedure used to analyse whether the stimuli evoke promotion or prevention thoughts was adopted from Experiment 1. Sample groups were exposed to the product categories considered here. In this case, they saw the label of the category written on a piece of paper and were asked to write down detailed thoughts in complete sentences. Additionally, we assessed thoughts resulting from the argument’s text. We used the same sample group to assess thoughts resulting from the strong-promotion-argument condition for all four prod- Gierl/Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective 30 MARKETING · ZFP · Heft 1 · 1. Quartal 2012 Strong promotion argument Do you love a challenge? This mountain bike has an ultra-light aluminum frame, weighing less than eight kilos. You will easily conquer even steep slopes. Scientific studies show that you are likely to experience feelings of happiness because the sense of achievement will cause the brain to release endorphins. Weak promotion argument We will help you to experience nature up close! Regular mountain biking stimulates all of your senses simultaneously. Scientific studies show that you are likely to increase your overall well-being if you exercise in nature. Try this mountain bike! Strong prevention argument Looking for a convenient way to avoid illness? Because this mountain bike has an ultralight aluminum frame, its overall weight is less than eight kilos. You will easily conquer even steep slopes. Scientific studies show that regular mountain biking is one of the most efficient ways to reduce the risk of heart attack. Weak prevention argument We will help you to avoid illness! Regular mountain biking reduces the risk of illness. Scientific studies show that you are likely to reduce the risk of heart attack by mountain biking regularly. Try this mountain bike! Reported thoughts Promotion thoughts only Prevention thoughts only Promotion and prevention thoughts Neither promotion nor prevention thoughts Type of category Mountain bikes (promotion) 22 2 3 3 MP3 players (promotion) 30 0 0 0 External hard drives (prevention) 0 28 0 2 Term life insurance policies (prevention) 6 18 4 2 Strength/type of benefit argument used for mountain bikes Strong/promotion (fit) 25 0 0 5 Weak/promotion (fit) 28 0 0 2 Strong/prevention (nonfit) 3 3 22 2 Weak/prevention (nonfit) 4 3 20 3 Note: Figures indicate the number of participants in the pretest who gave each type of response. Table 5: Argument Versions Used in Ads for Mountain Bikes Table 6: Promotion/Prevention Thoughts Induced by the Manipulations Used in Experiment 2 uct categories. Three additional sample groups were exposed to the remaining conditions (i.e., the weak-promotion-argument condition, the strong-prevention-argument condition, and the weak-prevention-argument condition). The sequence of the categories was varied randomly. In total, 240 consumers were assigned to eight sample groups. The pretest results are shown in Tab. 6. For simplicity, in the case of assessing thoughts induced by the type of benefit arguments, we only report the findings related to the mountain bike. The results obtained for the other categories were rather similar. The pretest results indicate that the manipulations were successful. Mountain bikes and MP3 players induced predominantly promotion thoughts, and external hard drives and term life insurance policies induced predominantly prevention thoughts. When exposed to the promotion arguments for mountain bikes, which represent the promotion product category, a high proportion of participants reported promotion thoughts only, indicating regulatory fit. However, when participants were exposed to prevention arguments for mountain bikes, they developed incongruent thoughts. The latter finding conforms to our expectations. In this case, a promotion stimulus (mountain bikes) and a prevention stimulus (the prevention argument) are combined. Procedure, measures, and sample: For each of the four product categories considered, we created four versions of advertisements. The versions differed in the strength and in the type of benefit argument used. The ads contained a picture of the advertised product; in the case of the ads for the term life insurance policies, a young family was depicted. Additionally, a fictitious brand name was included. We asked the respondents to indicate their interest in the investigated product categories and excluded from the sample those who expressed low interest (values of 1 and 2 on the scale ranging from 1 to 7). Additionally, we assessed participants’ knowledge of each category with the item “I know a lot about (category)” (seven-point scale). The items used to assess product evaluations were adopted from Experiment 1 (Cronbach’s α = .926). In total, 828 consumers with at least some interest in the respective categories participated in an online survey. The respondents’ ages ranged from 16 to 75 years (Mage = 31.69 years, SD = 12.63), and 48.3 percent were females. The experimental groups did not differ with respect to age, gender, or category knowledge. Results: The results are summarised in Tab. 7. Across product categories and types of arguments, the ad versions containing weak arguments produced less positive evaluations than the versions containing strong arguments (Mweak = 3.46, Mstrong = 5.01, F(1, 826) = 371.42, p < .001). Again, evaluations in the case of weak arguments are below the scale center (i.e., the value 4) and evaluations in the strong-argument condition are higher than the scale center. Therefore, the strength of arguments was manipulated successfully. Similar to Experiment 1, we collapsed data across the products in both product categories because detailed analyses did not reveal product-specific differences that were relevant for the hypotheses. Since different products were used to represent either the promotion category or the prevention category, we tested H1 and H2 for each category. In the promotion category, strong promotion arguments caused higher evaluations than strong preven- Gierl/Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective MARKETING · ZFP · Heft 1 · 1. Quartal 2012 31 Weak argument Strong argument Nonfit condition Fit condition Nonfit condition Fit condition Category Promotion category & prevention argument Prevention category & promotion argument Promotion category & promotion argument Prevention category & prevention argument Promotion category & prevention argument Prevention category & promotion argument Promotion category & promotion argument Prevention category & prevention argument Promotion category Mountain bike 3.94 (.97) - 2.87 (1.14) - 4.78 (1.22) - 5.30 (1.11) - MP3 player 4.20 (.76) - 2.65 (1.07) - 4.53 (1.50) - 5.80 (.95) - Overall 4.09 (.86) - 2.73 (1.10) - 4.62 (1.40) - 5.52 (1.06) - Prevention category Ext. hard drive - 3.92 (.98) - 3.49 (1.37) - 4.75 (.86) - 5.59 (.86) Term life ins. - 3.41 (.93) - 2.53 (.85) - 4.63 (1.16) - 5.52 (.54) Overall - 3.71 (.99) - 2.90 (1.17) - 4.69 (1.02) - 5.54 (.66) Notes: Scale ranges from 1 (negative product evaluation) to 7 (positive product evaluation). Standard deviations in parentheses. Promotion argument Prevention argument Women look at men’s hair. Improve your appearance with Fructis (Alpecin) with valuable vitamins (caffeine) daily. You will experience the difference. Women do not like bald men. Take care of your hair. By using Fructis (Alpecin) with valuable vitamins (caffeine) daily, you can reduce the risk of noticeable hair loss. It is best to feel physically and emotionally refreshed. Blend-a-med Complete Impression Fruit Explosion (Elmex) whitens your teeth, freshens your breath, and strengthens your tooth enamel. It is best to avoid painful tooth illness. Blend-a-med Complete Impression Fruit Explosion (Elmex) prevents gingivitis, prevents cavities, and fights plaque buildup. Get energised! Drinking Active O2 (Heilquelle) contributes to the creation of greater energy. It improves your physical and mental fitness. And it’s simply fun to drink. Reduce the risk of illness! Active O2 (Heilquelle) is rich in calcium and thus reduces the risk of osteoporosis. It contains valuable minerals, helping to prevent organ damage by optimizing the mineral and water balance of your body. Table 7: Impacts of Strength of Argument and Regulatory Fit between Type of Benefit Argument and Type of Product Category on Product Evaluations Table 8: Promotion and Prevention Arguments Used in Experiment 3 tion arguments (Mstrong, fit = 5.52, Mstrong, nonfit = 4.62, F(1, 208) = 26.03, p < .001, η = .086) whereas weak prevention arguments produced higher evaluations than weak promotions arguments (Mweak, fit = 2.73, Mweak, nonfit = 4.09, F(1, 161) = 79.19, p < .001, η = .183). Thus, H1 and H2 are supported. In the prevention category, strong prevention arguments caused higher evaluations than strong promotion arguments (Mstrong, fit = 5.54, Mstrong, nonfit = 4.69, F(1, 210) = 44.57, p < .001, η = .081) whereas weak promotion arguments produced higher evaluations than weak prevention arguments (Mweak, fit = 2.90, Mweak, nonfit = 3.71, F(1, 241) = 31.28, p < .001, η = .106). These findings also are in line with H1 and H2. Discussion: The findings of Experiment 2 show that the effect of fit/nonfit on evaluations does not depend on how incidential fit and nonfit are created. Inducing fit/nonfit by “type of benefit argument × type of prime” combinations produced the same pattern of effects on evaluations as inducing fit/nonfit by “type of benefit argument × type of product category” combinations. Therefore, regarding H1 and H2, we can provide evidence that regulatory fit is an intensifier of product evaluations. Next, we consider the type of brand as a further potential source of promotionand prevention-oriented thoughts. 4.3. Experiment 3 In Experiment 3, we tested Hypothesis H3. In the case of well-known brands, prior brand beliefs can be more or less favourable and can be promotion or prevention oriented as a result of exposure to past advertising campaigns. In this case, the effectiveness of benefit arguments could depend on the congruence of the type of benefit argument used and the type of brand. We used a 2 (type of benefit argument: promotion vs. prevention) × 2 (brand: promotion vs. prevention) factorial design and analysed the effect of strong benefit arguments on product evaluations under the resulting fit and nonfit conditions. As a replicate factor, we considered brands from three product categories (hair shampoo, toothpaste, and mineral water). Brands: Based on pretest results that will be reported subsequently, we chose both a promotion brand and a prevention brand from three product categories. From the category of hair shampoo, we selected Garnier Fructis Daily Care and Alpecin Caffeine Shampoo; from the category of toothpaste, we selected Blend-a-med Complete Impression Fruit Explosion and Elmex, and from the category of mineral water, we chose Adelholzener Active O2 and Adelholzener Heilquelle. In the last case, we considered sub-brands of the same brand. Active O2 is positioned as a promotion-oriented sub-brand of Adelholzener, whereas Heilquelle, which is translated as “healing water,” is positioned as a prevention-oriented sub-brand. Benefit arguments: Tab. 8 lists the argument versions used in Experiment 3. To induce the strong-argument condition, we added an expert statement to all of the arguments. For instance, in the case of the promotion argument for hair shampoo, a psychologist was depicted stating that scientific research gave evidence of the argument’s validity, i.e. that research found the men using Alpecin actually feel that their appearance has improved Gierl/Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective 32 MARKETING · ZFP · Heft 1 · 1. Quartal 2012 Reported thoughts Promotion thoughts only Prevention thoughts only Promotion and prevention thoughts Neither promotion nor prevention thoughts Brands Fructis (promotion) 25 4 1 0 Alpecin (prevention) 0 27 1 2 Blend-a-med (promotion) 24 4 1 1 Elmex (prevention) 2 19 7 2 Adelholzener Active O2 (promotion) 29 0 0 1 Adelholzener Heilquelle (prevention) 3 21 4 2 Type of benefit arguments/categories Promotion/shampoo 21 0 2 7 Prevention/shampoo 2 19 5 4 Promotion/toothpaste 18 2 5 5 Prevention/toothpaste 3 22 3 2 Promotion/mineral water 21 2 1 6 Prevention/mineral water 3 20 1 6 Note: Figures indicate the number of participants in the pretest who gave each type of response. Table 9: Promotion/Prevention Thoughts Induced by the Manipulations Used in Experiment 3 compared to men who used other shampoos. In the case of the prevention argument for hair shampoo, a dermatologist stated that using the shampoo reduces hair loss to a higher extent than regular shampoo does. Note, that not the presence of an expert (a peripheral cue) but the additional information provided by the expert is regarded to create a strong argument condition. Pretest: To ensure that the brands differed regarding the induced promotion or prevention orientation of thoughts, we created stimuli consisting of pictures showing bottles of Fructis, Alpecin, Adelholzener Active O2, and Adelholzener Heilquelle and packages of Blend-a-med Complete Impression Fruit Explosion and Elmex, respectively. Again, we asked sample groups of consumers to take part in a thought-listing task. The same procedure was used to analyse the promotion/prevention orientation of thoughts that resulted from the text versions of the benefit arguments. Here, the participants received a piece of paper printed with the argument texts; the brand names were replaced by “brand X”. In total, 360 consumers were assigned to twelve sample groups; in the case of the shampoo conditions, sample groups consisted of only males because Alpecin targets male consumers. In Tab. 9, we summarise the findings of the pretest. Participants given the Fructis advertisement frequently produced thoughts such as “smells good,” “feeling well,” “fresh scent,” “clean,” “shiny hair,” “bright hair,” and “enriches the hair.” Participants exposed to the picture of a bottle of Alpecin listed thoughts such as “prevents oily hair,” “reduces dandruff,” “prevents hair loss,” “contributes to hair repair,” and “inhibits hair damage.” Therefore, the thoughts elicited by the brands are seemingly promotion and prevention oriented, respectively. When exposed to the promotion argument in the case of shampoo, participants frequently reported thoughts such as “full hair demonstrates a man’s health” and “good-looking hair actually improves impressions.” When exposed to the prevention argument, prevention thoughts such as “valuable help to fight against hair loss” and “helps men not to feel inferior” were noted. Similarly, the brands and arguments presented for toothpaste and mineral water were associated with either promotion or prevention thoughts. Procedure, measures, and sample: Again, we conducted an online survey. In the case of the shampoo, we informed the participants that we were interested in male consumers only. Each respondent was exposed to one of twelve ad versions resulting from combining two types of arguments, two brands per product category, and three product categories. The ad versions contained a picture of the product and one version of the argument. Then the respondents were asked to evaluate the product. We adopted the scales used in Experiment 1 (Cronbach’s α = .927). In the next step, the respondents rated their familiarity with brands of the relevant category and how important the category is to them (seven-point scales). Finally, they were asked to report their age and gender. The last question was used to select males for data analysis in the shampoo condition. In total, 2,880 consumers participated in the online survey. Their ages ranged from 17 to 79 years (Mage = 34.86 years, SD = 6.66). The sample groups did not differ in terms of age, familiarity with brands, or category importance. Results: The findings are shown in Tab. 10. Again, we collapsed data across the manipulations used to induce the nonfit and fit conditions. Since evaluations tend to exceed the value 4 (the center of the scale used to assess product evaluations) the arguments used were seemingly strong. In line with Hypothesis H3, product evaluations are more positive in the fit condition than in the nonfit condition (Mfit = 4.88, Mnonfit = 4.18, F(1, 2878) = 163.77, p < .001, η = .088). Discussion: Experiments 1, 2, and 3 showed that the type of benefit argument, the type of prime, the type of product category, and the type of brand can induce predominantly promotion- or prevention-oriented thoughts in consumers, thereby inducing the incidental fit or nonfit of promotion/prevention thoughts. Experiment 1 and Experiment 2 demonstrated that fit is an intensifier of evaluations of products in the case of unknown brands. For well-known brands, the results of Experiment 3 are in Gierl/Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective MARKETING · ZFP · Heft 1 · 1. Quartal 2012 33 Nonfit condition Fit condition Category Promotion brand & prevention argument Prevention brand & promotion argument Promotion brand & promotion argument Prevention brand & prevention argument Shampoo 4.19 (1.31) 4.02 (1.57) 4.75 (1.39) 4.71 (1.33) Toothpaste 4.28 (1.46) 4.29 (1.26) 4.76 (1.61) 4.80 (1.51) Mineral water 4.06 (1.49) 4.27 (1.44) 4.98 (1.52) 5.09 (1.42) Overall 4.15 (1.44) 4.20 (1.43) 4.85 (1.52) 4.90 (1.43) Notes: Scale ranges from 1 (negative product evaluation) to 7 (positive product evaluation). Standard deviations in parentheses. Nonfit condition Fit condition Dependent variable Promotion brand & prevention argument Prevention brand & promotion argument Promotion brand & promotion argument Prevention brand & prevention argument Feeling right (N = 576) 4.89 (1.21) 4.92 (1.32) 5.21 (1.13) 5.36 (.91) Engagement (N = 348) 3.79 (1.74) 3.67 (1.74) 4.61 (1.68) 4.08 (1.62) Fluency (N = 384) 4.98 (1.66) 4.76 (1.48) 5.20 (1.41) 5.21 (1.26) Notes: Scale ranges from 1 to 7. Higher values indicate more positive ratings of feeling right, engagement, and fluency. Standard deviations in parentheses. Table 10: Impact of Regulatory Fit between Type of Benefit Argument and Type of Brand on Product Evaluations in the Case of Strong Arguments Table 11: Impact of Regulatory Fit between Type of Benefit Argument and Type of Brand on Feeling Right, Engagement, and Fluency line with this expectation. Subsequently, we intend to provide answers to the second research question of why fit acts as an intensifier and investigate the roles of feeling right, engagement, fluency, and the perceived strength of arguments in two additional experiments. 4.4. Experiment 4 In Experiment 4, we investigated whether regulatory fit affects feeling right, engagement, and fluency. Here, we tested H4, H5, and H6. We conducted an experiment based on a 2 (type of benefit argument: promotion vs. prevention) × 2 (type of brand: promotion vs. prevention) × 3 (dependent variable: feeling right vs. engagement vs. fluency) factorial design. Procedure, measures, and sample: From Experiment 3, we adopted the brands of shampoo that are promotion and prevention oriented (Fructis and Alpecin, respectively) and the ad versions containing either the promotion or the prevention argument and used the same procedure. We asked respondents to imagine that they were buying shampoo and thus were in the position of evaluating products based on pieces of information provided in ads. According to researchers in the field of regulatory fit, “feeling right” can be defined as the person’s confidence in the results of her/his evaluations. Based on the measures used by Cesario/Grant/Higgins (2004) and Wan/ Hong/Sternthal (2009), we asked respondents to agree or disagree with the statements, “This information was very useful for arriving at the correct evaluation” and “I am very confident in making the correct evaluation.” Referring to the cognitive-resource-based view of engagement, we assessed the extent to which the total cognitive resources available are dedicated to the product instead of to unrelated coexisting stimuli based on the degree to which people agreed with the statements “I think other things are not likely to distract my attention from product evaluation” and “I am very engrossed in the evaluation of this product.” Chang (2010) used similar measures. We used the latter statement because Higgins (2006) and Higgins/Scholer (2009) paraphrased engagement by the state of being engrossed in the target. To assess fluency, respondents had to agree or disagree with the statements “It takes little effort to catch the meaning of the arguments” and “I can easily understand what the seller tries to communicate.” Higgins et al. (2003) used a similar item to measure respondents’ perceptions of the ease of a relevant task. The sample consisted of 1,308 males (Mage = 33.93 years, SD = 4.63). Results: The findings are listed in Tab. 11. Since data were collected in three sub-samples (i.e., one sample group assessed feeling right, another sample group answered questions regarding engagement, and a third sample group provided data regarding engagement), we could not conduct a MANOVA containing three dependent variables simultaneously and fit/nonfit as independent variable. Thus, we had to conduct an ANOVA for each dependent variable using regulatory fit as the independent variable. The data indicate that feeling right, engagement, and fluency are higher in the regulatory-fit condition than in the nonfit condition (feeling right: Mfit = 5.28, Mnonfit = 4.90, F(1, 574) = 15.88, p < .001, η = .036; engagement: Mfit = 4.29, Mnonfit = 3.73, F(1, 346) = 9.30, p < .01, η = .064; fluency: Mfit = 5.20, Mnonfit = 4.87, F(1, 382) = 5.01, p < .05, η = .032), thus supporting Hypotheses H4, H5, and H6. Discussion: Experiment 1 and Experiment 2 provided evidence that fit intensifies evaluations, while Experiment 4 shows that fit affects feeling right, engagement, and fluency. Taken together, the findings of these experiments conform to the theoretical framework suggested in Fig. 2. In our last experiment, we focus on the perceived strength of arguments and thus test a further part of the theoretical framework depicted in Fig. 2. 4.5. Experiment 5 Procedure, measures, and sample: To test H7 and H8, we replicated the procedure used in Experiment 1. We Gierl/Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective 34 MARKETING · ZFP · Heft 1 · 1. Quartal 2012 Nonfit condition Fit condition Promotion prime & prevention argument Prevention prime & promotion argument Promotion prime & promotion argument Prevention prime & prevention argument Weak argument 3.30 (.83) 3.06 (1.04) 2.51 (1.05) 2.49 (1.04) Strong argument 5.04 (.82) 5.12 (.71) 5.54 (.98) 5.59 (.80) Notes: Scale ranges from 1 (weak) to 7 (strong). Standard deviations in parentheses. Table 12: Impacts of Strength of Argument and Regulatory Fit between Type of Benefit Argument and Type of Prime on Perceived Strength of Arguments selected instant loans as the test product and conducted an experiment based on a 2 (strength of argument: weak vs. strong) × 2 (type of benefit argument: promotion vs. prevention) × 2 (prime: promotion vs. prevention) factorial design. Instead of product evaluations, we used a measure of the perceived strength of arguments as the dependent variable. To measure this variable, we asked respondents to respond to the items “I think that, compared to competitors’ offers, this offer is much worse/ much better” and “The advertisement contains a strong argument for selecting this offer if an instant loan is needed” on seven-point scales. In total, 444 consumers participated in this experiment (Mage = 30.22 years, SD = 10.45, 50.7 % female). Results: The effects of this manipulation on the perceived strength of arguments are shown in Tab. 12. In Hypothesis H7, for strong benefit arguments, we postulated that the perceived strength of arguments would be stronger in the fit condition. The results provide support for this expectation (Mstrong, fit = 5.56, Mstrong, nonfit = 5.08, F(1, 248) = 20.07, p < .001, η = .044). In Hypothesis H8, we considered the case of weak benefit arguments and expected that the perceived strength of the arguments would be stronger in the nonfit condition. The results are in line with this expectation (Mweak, nonfit = 3.18, Mweak, fit = 2.50, F(1, 192) = 22.84, p < .001, η = .110). Therefore, the results show that regulatory fit intensifies the perceived strength of benefit arguments, providing additional support for the suggested theoretical framework. 5. Discussion 5.1. Answers to the Research Questions This research was inspired by the question of whether the effectiveness of benefit arguments contained in advertisements can be influenced by the congruity of promotion/prevention thoughts elicited by the arguments and promotion/prevention thoughts induced by other determinants of regulatory fit besides consumer personality, fit-primes, and framing manipulations. Based on manipulations of the type of benefit argument, the type of product category, the type of brand, and the type of prime, we provided answers to the research questions. We questioned how regulatory fit affects product evaluations and tested the hypothesis that fit operates as an intensifier. Experiment 1 and Experiment 2 aiming to test this hypothesis provided support for this presumption in the case of unknown brands. In Experiment 3, we used wellknown brands and thus were unable to test whether fit intensifies evaluations. However, in line with our considerations, we expected that fit would improve evaluations of favourably evaluated brands in the case of strong arguments. The findings were in line with our expectations. We additionally questioned why fit affects product evaluations. We were able to show that fit increases feeling right, engagement, and fluency and makes the perceived strength of arguments more extreme. In sum, we provide evidence that the suggested theoretical framework is suitable for predicting how the effectiveness of benefit arguments can be enhanced. 5.2. Limitations of the Results Evidently, our studies suffer from several limitations. First, for well-known brands, we only investigated the effect of regulatory fit on product evaluations of favourably evaluated brands. For unfavourably evaluated wellknown brands, the question of whether fit makes evaluations more negative is still open. Second, a limitation results from the fact that we did not investigate the effect of regulatory fit in a “neutral condition.” We showed that favourable evaluations became more positive and that unfavourable evaluations became more negative in the fit condition. However, if fit operates as an intensifier, fit should not affect evaluations that are neutral due to the arguments used. To provide additional evidence for the notion that regulatory fit acts as an intensifier, more than two levels of strength of benefit arguments would need to be included in the experimental design. In the range of these levels, a region should exist where arguments are neither strong nor weak. For this region, fit is expected to have no effect. Otherwise, fit would not operate as an intensifier. Our experiments did not consider this issue. Third, we did not test all of the relations that are contained in the theoretical framework depicted in Fig. 2. For instance, we postulated that engagement and fluency facilitate product-related cognitive activities such as retrieving autobiographical knowledge from memory or developing mental images that affect product evaluations, but we did not empirically explore this part of the theoretical framework since Vaughn et al. (2009) already had provided evidence of this part of the model. 6. Implications 6.1. Theoretical Implications and Suggestions for Future Research We used ideas from theories about regulatory fit to develop a model of how benefit arguments affect product evaluations. Our starting point consisted of the question Gierl/Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective MARKETING · ZFP · Heft 1 · 1. Quartal 2012 35 Cognitive resources enjoyment fit weak nonfit strong nonfit overcoming obstacles Cognitive resources due to the interest in the target stimulus Engagement effect Figure 4: Assumptions on the Relationship between Regulatory Fit and Engagement that has frequently been asked by Higgins and his co-authors: whether regulatory fit improves or intensifies evaluations. Higgins notes that this question lacks empirical answers. The findings of our experiments contribute to answering this question. We found that regulatory fit intensifies evaluations. Additionally, we found that regulatory fit affects feeling right, engagement, fluency, and the perceived strength of benefit arguments, which can help to explain the moderating role of fit in evaluations. Based on the descriptions of the limitations of our experiments, we suggest that future research resolve these limitations. Additionally, we suggest considering peripheral promotion and prevention cues as a source of promotion/prevention thoughts in experiments. Similarly to benefit arguments and prior brand beliefs that differ in strength and favourability, respectively, and type (i.e., promotion vs. prevention), peripheral cues could be a further class of stimuli that differ in quality and type. In the introductory section, we referred to the example of sponsorship’s ability to induce promotion- or prevention-oriented thoughts. However, there are numerous peripheral cues that could affect thoughts as well. Because these cues could easily be integrated into ads, gaining knowledge about the effectiveness of classes of peripheral cues that assist in inducing regulatory fit or nonfit would likely be beneficial. Our results conform to the hypothesis that fit intensifies evaluations and contradict the finding provided by König et al. (2009, p. 1348) which has been displayed in Tab. 1. These authors found that regulatory nonfit intensifies evaluations. How can this difference be explained? Many researchers postulate that regulatory fit (compared to nonfit) increases cognitive resources that are spent on product-related mental activities via enjoyment. We adopted this perspective in our model. But since strong regulatory nonfit signals that severe difficulties exist that have to be solved, higher engagement is expected to exist in the strong nonfit condition compared to the fit condition. Pham/Avnet (2009, p. 120) conclude that the sign of the relationship between regulatory fit and engagement is ambiguous. The assumption of a u-shaped relationship between the extent of regulatory nonfit (i.e., fit, weak nonfit, strong nonfit) and cognitive resources spent on product-related activites (i.e., elaborating on arguments, retrieving biographical knowledge, and developing imaginations) could integrate the hypotheses on this issue (Fig. 4). In the case of regulatory fit, enjoyment is expected to cause a weak engagement effect. In the case of weak regulatory nonfit, individuals might neither experience enjoyment nor impediments to process information. In the case of strong nonfit, the individual’s perception that obstacles have to be overcome is expected to cause a high engagement effect. Based on this expanded approach, the findings of König et al. (2009) that contradict the findings of Evans/Petty (2003) and the results of our experiments can be explained. Probably, Evans/Petty (2003) and our experiments compared the conditions of fit to conditions of weak nonfit. The kind of manipulation used by König et al. (2009) indicates that these authors compared the condition of fit to the condition of strong nonfit. However, this expanded theory lacks empirical support and should be tested in future research. Moreover, following the ideas of König et al. (2009), we suggest analysing in future research, whether fluency and feeling right regarding the target stimulus are also present when regulatory fit is determined externally by using a fit-prime. In other words, it is unclear whether these mental states are transferred to the target object (e.g., the product) when they are created by the preceding priming stimulus. 6.2. Practical Implications We proposed a way of affecting product evaluations by means of regulatory fit. From a regulatory fit perspective, we derived recommendations for marketers who are able to use strong benefit arguments. We suggest increasing recipients’ confidence in their own judgments that the product is indeed favourable and increasing consumers’ cognitive resources available to connect the product with autobiographical knowledge and mental images. Regulatory fit theory proposes that this kind of effect could be triggered when regulatory fit exists. As a consequence, we propose to create regulatory-fit conditions when consumers elaborate on strong benefit arguments. Using the type of benefit argument that fits the product category and prior brand beliefs will induce a favourable situation. Most likely, priming stimuli can be found that induce the fit condition (e.g., a promotion- or preventionoriented television program that conforms to the type of benefit arguments presented in commercials). Moreover, marketers should have numerous possibilities for peripheral cues conforming to the type of benefit argument used. Sellers of new or unknown products often face the problem of being unable to provide benefit arguments that are perceived as credible and strong by consumers (Higgins/ Scholer 2009). According to this research, product evaluations are expected to be less unfavourable in the nonfit condition when arguments are weak. In this situation, we recommend that marketers reduce recipients’ confidence in their own judgments that the product is indeed unfavourable and reduce the resources available to execute additional product-related cognitive activities by creating the nonfit condition. To illustrate this idea, picture sports Gierl/Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective 36 MARKETING · ZFP · Heft 1 · 1. Quartal 2012 equipment of an unknown brand. Assume that the category is neither promotion nor prevention oriented and that prior brand beliefs are absent. The product’s emphasised benefit is that it enables users to have fun in their leisure time (i.e., the seller uses a promotion argument), but the seller cannot offer the additional information that using its products actually enables consumers to experience more fun than using products of well-known competitor brands. Furthermore, suppose that this seller has the option either to include a scene where a well-known soccer goalkeeper prevents a goal (i.e., a prevention stimulus) or to include a scene where a famous striker scores a goal (i.e., a promotion stimulus) in its commercial. In the case of a weak promotion argument, the nonfit condition resulting from choosing the goalkeeper is expected to result in less unfavourable product evaluations. It is likely that this seller could also use priming stimuli to evoke the nonfit condition. Zhao/Pechmann (2007) discussed television shows that are either promotion or prevention oriented. Airing a commercial for sports equipment emphasizing fun during a preventionoriented TV show could induce nonfit, which would lead viewers to develop more positive perceptions of the product. Notes [1] For the purpose of parsimony, we use the terms “promotion” and “prevention” to describe stimuli which induce thoughts about issues that are to be achieved or to be avoided and to characterise mental states where these kinds of thoughts are predominant. This dichotomy is widespread in literature. Sometimes, the dichotomy of “approach” and “avoidance” is used alternatively (e.g., Avnet/Higgins 2006; Aaker/Lee 2001; Higgins 2002). [2] The priming stimulus is the stimulus that preceeds the target stimulus. For instance, a consumer who has contact with advertising spots on TV may have watched a film previously. In this case, the film is the priming stimulus regarding the ad spots. If a priming stimulus consists of several cues that differ regarding promotion or prevention orientation, all of these cues can be promotion oriented, prevention oriented, or they can be mixed. Then, individuals elaborate on a subsequently presented target stimulus (e.g., an advertisement) in a previously created or incidentally existing fit or nonfit condition (e.g., Aaker/Lee 2001; Cesario/Grant/Higgins 2004; Förster/ Higgins 2005; Higgins et al. 2003; Hong/Lee 2008; König et al. 2009; Vaughn et al. 2006). [3] In general, framing describes the fact that substantially equivalent messages can be formulated in semantically different ways (Levin/Schneider/Gaeth 1998). In particular, promotion arguments can be expressed semantically using either the gain frame or the nongain frame. A gain frame is used when the argument promises the presence of a certain positive outcome when following the appeal. A nongain frame is used when the argument announces the absence of this positive outcome when the appeal is not followed. A prevention argument can be expressed semantically by applying either the nonloss frame or the loss frame. The nonloss frame is used when the argument promises the absence of a certain negative outcome when following the appeal. The loss frame is applied when the argument announces the presence of this negative outcome when the appeal is not followed (e.g., Block/Keller 1995; Cesario/Grant/Higgins 2004; Hasseldine/Hite 2003; Krishnamurthy/Carter/Blair 2001; Lee/Aaker 2004; Levin et al. 2002; Maheswaran/Meyers-Levy 1990; Meyerowitz/Chaiken 1987; Rothman et al. 1993; Thorsteinson/Highhouse 2003). For instance, the appeal “Buy this camera!” can be expressed as following: “If you buy this camera you can capture important moments” (gain frame), “If you do not buy this camera you cannot capture important moments” (nongain frame), “If you buy this camera you do not let important moments slip by” (nonloss frame), and “If you do not buy this camera you let important moments slip by” (loss frame) (Zhu/Meyers-Levy 2007). The gain frame and the loss frame are assumed to induce regulatory fit whereas the nongain frame and the nonloss frame are expected to induce nonfit. [4] Regulatory focus theory posits that individuals are characterised by a tendency to think about issues either in terms of gains (these people are sensitive to the presence or absence of positive outcomes) or in terms of losses (these people are sensitive to the presence and absence of negative outcomes). This kind of self-regulation is seen as a personality trait and is denoted as chronic regulatory focus (e.g., Evans/Petty 2003; Förster/Higgins/Idson 1998; Freitas/Liberman/Higgins 2002; Higgins 1997; 2000; 2002; Higgins et al. 2001, Higgins et al. 2003; Idson/Higgins 2000; Idson/Liberman/Higgins 2000; Lee/Aaker 2004; Leesch 2011; Vaughn et al. 2006). Literature suggests that situational factors can also influence the regulatory focus resulting in a situational regulatory focus (e.g., Cesario/Higgins/Scholer 2008). [5] The Kappa coefficient is used to assess intercoder reliability. This coefficient is defined as K = (PA-PE)/(1-PE) where PA is the proportion of cases the coders agree and PE is the proportion of cases the coders are expected to agree per chance. Kappa was .891 before the assignments were checked by the authors additionally. Similar values were obtained in the other experiments. References Aaker, J. L./Lee, A. Y. 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Keywords Promotion and prevention thoughts, benefit arguments, regulatory fit, advertising Gierl/Pagel, Increasing the Effectiveness of Benefit Arguments: A Regulatory Fit Perspective MARKETING · ZFP · Heft 1 · 1. Quartal 2012 39

Abstract

Benefit arguments can be defined as appeals that marketers use to emphasise the advertised product’s benefits. These arguments differ in strength and type. The strength of arguments causes favourable or unfavourable product evaluations. The type of benefit argument used influences viewers’ thoughts to be either promotion or prevention oriented. Combined with other situational factors or elements of advertisements that also elicit promotion or prevention oriented thoughts, conditions result where thoughts are congruent (fit condition) or incongruent (nonfit condition). First, we provide evidence that product evaluations are more extreme in the fit condition than in the nonfit condition. Second, we show that feeling right, engagement, fluency, and the perceived strength of arguments are affected by regulatory fit, providing support for a suggested theoretical framework that describes the role of fit in the process of product evaluation.

References

Abstract

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