J. of the Acad. Mark. Sci. (2007) 35:53–62 DOI 10.1007/s11747-006-0011-3
ORIGINAL EMPIRICAL RESEARCH
How do enhanced and unique features affect new product preference? The moderating role of product familiarity Kevin Zheng Zhou & Kent Nakamoto
Received: 29 July 2006 / Accepted: 12 October 2006 / Published online: 23 February 2007 # Academy of Marketing Science 2007
Abstract Companies often introduce products with enhanced or unique features to compete with the dominant brands in the market. This paper examines the moderating role of product familiarity in consumer preferences of products with enhanced or unique features in two experimental studies. Study 1 (208 participants) operationalizes product familiarity at the product category level and Study 2 (168 participants) measures it at the individual level as one’s prior experience with the product. The findings of two experiments show that when consumers are unfamiliar with a product category, they prefer a product with enhanced features to one with unique features. In contrast, when consumers are experienced, they perceive a product with unique features more favorably than an enhanced one. Furthermore, this effect is due to consumer perceived differentiation of and performance uncertainty about new products with enhanced or unique features. Keywords Enhanced features . Unique features . Product familiarity . Incongruity theory Companies often introduce or reintroduce their products with improved performance along existing attributers (thereafter enhanced features) or new, unique features (thereafter unique features) to compete with dominant brands in the market (Tholke, Hultink, & Robben, 2001). These enhanced and
K. Z. Zhou (*) School of Business, The University of Hong Kong, Pokfulam, Hong Kong, People’s Republic of China e-mail:
[email protected] K. Nakamoto Virginia Polytechnic Institute and State University, Blacksburg, VA, USA e-mail:
[email protected]
unique features can help firms differentiate their products, though in different ways. For instance, enhanced features enable a new product to claim superiority over competitors on the basis of a common ground (e.g., “Xerox [printer] is 3X faster than HP’s fastest.” In contrast, with unique features, a product heavily advertises that it offers something that other brands lack. For example, Enterprise Rent-a-Car advertises that “We will pick you up;” 7Up Plus emphasizes that “We contain fruit juice, calcium, and vitamin C.” Given the popularity of these practices, it is important to understand how enhanced and unique features affect consumer preference of the new product. However, researchers seem to hold different views regarding the effects of enhanced and unique features. For some, a better choice is to introduce enhanced features because consumers can easily identify their benefits through the comparison along a common dimension (Zhang & Markman, 1998). Others however suggest that adding unique features is the key because consumers tend to give more attention to something novel and thus hold a favorable attitude towards it (Carpenter, Glazer, & Nakamoto, 1994). In a more recent investigation, Ziamou and Ratneshwar (2003) find that direct comparison can receive better consumer evaluations only when the product is atypical with regard to its enhanced features. To answer this research question, we suggest that product familiarity plays a critical role in consumer preferences of products with enhanced and unique features. Building on incongruity theory, which predicts that a moderate discrepancy may generate a more favorable affective judgment than either highly congruent or extremely incongruent information (Mandler, 1982), we propose that product familiarity is an important moderator of the incongruity effect because the degree to which an attribute is perceived as incongruent depends on the consumer’s familiarity with the product. In particular, experienced
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consumers perceive unique features as moderately incongruent and enhanced features as too congruent and, consequently, prefer unique products to enhanced ones. In contrast, inexperienced consumers perceive unique features as too incongruent and enhanced features as moderately incongruent and, therefore, prefer enhanced products to unique ones. We demonstrate these effects in two studies, in which we treat product familiarity at the product category level (Study 1) and as an individual factor (Study 2).
Conceptual development Moderate incongruity effect According to the categorization perspective, when seeing a new product, people attempt to categorize it into an existing schema to identify its possible benefits and threats and to facilitate their decision making. Because most new products provide features that are both congruent and incongruent with existing schema, this categorization process often involves a mix of rapid processing of congruent attributes (e.g., shared features that are identical to existing products) and piecemeal processing of incongruent attributes (e.g., unique features). Mandler (1982) indicates that the extent of such incongruity will affect new stimulus evaluations and, in particular, that a moderate discrepancy may generate a more favorable affective judgment than either highly congruent or extremely incongruent information. A completely congruent stimulus is not arousing and can result only in a mild positive response due to familiarity. In contrast, moderate incongruity leads to mental arousal and cognitive elaboration and can be resolved through assimilation or sub-typing. Because of the achieved congruity and satisfaction that accompanies the successful categorization of novel stimuli, moderate incongruity evokes a greater positive affect than does congruity. However, highly discrepant information can be accommodated only through deep structural changes, such as creating a new mental schema or substantially modifying the existing schema. Such a major accommodation is not pleasing mentally and may not succeed, leading to a less favorable evaluation. A series of empirical studies has demonstrated this “moderate incongruity effect” that arises from new product attributes, brand extensions, and product tastes. More recently, however, Campbell and Goodstein (2001) indicate that perceived risk may overwhelm incongruity effects. They find that moderate incongruity effects only hold in situations associated with low risk perceptions. However, if perceived risk is relatively high, consumers tend to demonstrate a preference for the norm over the novel, preferring a more congruent product to an incongruent one. The preceding discussion suggests two mechanisms that underlie the moderate incongruity effect: perceived differ-
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entiation and perceived risk. An incongruent stimulus may be judged favorably because of its novelty and perceived differentiation. As Mandler (1982, p. 22) explains, “slightly incongruous events are usually interesting and positively valued.” However, if the stimulus is highly incongruent, it will be perceived as too risky, which may override the enjoyment brought by its perceived differentiation and result in a less positive evaluation (Campbell & Goodstein, 2001). In the marketing literature, perceived risk is conceptualized in terms of uncertainty and consequences: uncertainty refers to the extent that consumers are not confident about the product’s performance, and consequences refer to the possible losses associated with the purchase (Conchar, Zinkhan, Peters, Olaarrieta, 2004). Because our research focuses on new product evaluation, we define risk in terms of perceived performance uncertainty. Enhanced and unique features Although enhanced features can be distinctive, in that they advance performance along existing attributes, unique features are more differentiated in various ways. For example, new and unexpected features help a new product arouse attention, especially in today’s information-overload market (Kardes & Kalyanaram, 1992). Because novel information is interesting and consumers tend to elaborate on it, it is likely to be more salient for interbrand comparison and be encoded into long-term memory (Dhar & Sherman, 1996). The uniqueness of novel features also make them receives greater weight in preference judgments (Carpenter et al., 1994). Therefore, a product with unique features is likely to receive a more favorable evaluation in a decision-making process. Compared to unique features, enhanced ones do not cause the same level of performance uncertainty. When a feature is first introduced, perceived uncertainty associated with its utility arises (Nowlis & Simonson, 1996). To evaluate a feature, consumers must possess some experience or prior knowledge of its utility on an absolute scale (Hsee, 1996), and such experience or prior knowledge exists for enhanced but not for new features. The perceived utility uncertainty makes consumers feel less confident about whether the product will perform the promised functions. Even if a new feature’s superiority is easy to identify, its contribution to the product performance may be difficult to assess (Zhang & Markman, 1998). In contrast, an enhanced feature is comparable to existing features along a common dimension. Through comparison, a product’s relative inferiority or superiority becomes evident because its value can be assessed by retrieving the value of the contrasting attribute from existing products (Hsee, 1996). In summary, compared with a new product with enhanced features, one with unique features is perceived as more differentiated but more performance uncertain.
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Thus, the unique product may be viewed more favorably than the enhanced one because of its differentiation, or it may be perceived less favorably because of its uncertainty. On balance, which product will be preferred by consumers? The role of product familiarity Extant research has well recognized the importance of product familiarity—a consumer’s prior experience with the product category—in influencing new product learning and evaluation (Alba & Hutchinson, 1987). Consistent with Peracchio and Tybout (1996), we propose that product familiarity plays an important role in moderating the incongruity effect because the degree to which an attribute is perceived as incongruent may depend on the consumer’s familiarity with the product. For example, a moderately incongruent attribute for novices may appear relatively congruent to experts, whereas a moderate incongruity for experts may be highly incongruent for novices. In other words, consumer product familiarity may shift the perception of incongruity and thereby moderate the effects of enhancing versus unique strategies. Consumers familiar with a category usually possess superior knowledge about existing products and have developed a set of expectations about the product category, such as typical attributes, attribute importance, and relations among the attributes (Sujan & Bettman, 1989). When viewing a new product, experienced consumers naturally pay more attention to something new and interesting. Enhanced features, which fall within their expectations, tend to be perceived as too congruent or redundant (Kardes & Kalyanaram, 1992). In contrast, unique features are unexpected and are likely to attract more attention and elicit arousal (Meyers-Levy & Tybout, 1989). Therefore, for experienced consumers, unique features are the focus of the learning process and will be processed more extensively in a piecemeal mode, and consequently, will be recalled better. In addition, as consumers gain more experience with a product category, they feel more competent and tend to perceive new features as less uncertain (Heath & Tversky, 1991). That is, expert consumers may view enhanced products as too congruent and unique products as moderately congruent. As a result, compared with enhanced products, unique products will receive a more favorable evaluation and are more likely to be preferred over the dominant product. In contrast, when consumers have little prior product experience, their product learning may be a very difficult and complex task because of their impoverished knowledge structure. Initially, consumers may know only a little about the category and product attributes, which leads them to pay special attention to those aspects that are common among the compared instances so they may learn more about the pro-
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duct (Spalding & Ross, 1994). That is, as consumers seek to learn more and form a generalizeable belief about the category, they process common features extensively (Spalding & Ross, 1994). Because enhanced features provide a direct comparison to the alternatives on the attribute being judged, they become the focus of learning and receive particular attention (Zhang & Markman, 1998). In contrast, unique features may be highly incongruent because novice consumers lack the ability to comprehend them. In this way, enhanced features are more likely to be recalled. Furthermore, inexperienced consumers may perceive unique features as highly uncertain in terms of their performance because they are not familiar with and feel less competent with regard to the product category (Heath & Tversky, 1991). In other words, novices may view enhanced features as moderately incongruent and unique features as highly incongruent. Consequently, compared with unique products, enhanced products will receive a more favorable evaluation and are more likely to be preferred over the dominant product. Hypothesis 1 When consumers possess high product familiarity, they will perceive a product more favorably, prefer it over a dominant brand, and exhibit higher recall of the focal attribute when the product is marketed with unique rather than enhanced features. However, when consumers possess low product familiarity, they will perceive a product more favorably, prefer it to a dominant brand, and exhibit higher recall of the focal attribute when the product is marketed with enhanced rather than unique features. The preceding discussion also implies that perceived differentiation and perceived performance uncertainty are the mechanisms that underlie consumers’ evaluations of alternative products. Therefore, we predict that Hypothesis 2 Preference judgments are affected by perceived differentiation and perceived performance uncertainty. During new product introductions, companies may face situations in which (1) consumers as a whole know little about the product (e.g., introductory or early growth stage of the product life cycle), (2) consumers in general are very familiar with a product (e.g., simple products at maturity stage), or (3) consumer product familiarity varies considerably (e.g., complicated products). To account for these variations, we test the hypotheses in two studies. In Study 1, product familiarity is tested at the product category level, in which subjects are very familiar with one category (i.e., portable CD players) and unfamiliar with the other (i.e., instant language translators). In Study 2, product familiarity is measured at the individual level, in which subjects differ considerably in their familiarity with the product (i.e., point-and-shoot cameras).
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Study 1 Method Design Study 1 employs a 2 (product)×2 (familiarity)×2 (new feature) factorial design. The two primary independent variables are product (enhanced versus unique) and product familiarity (category level: unfamiliar versus familiar). Both factors are run between subjects. New feature represents another between-subject factor that controls for the importance of enhanced versus unique features. That is, we position the same feature as either an enhanced or unique one in alternate settings by adjusting attribute combinations. For example, for half the participants, “studio signal system” is the new feature and “digital sound control” is the enhanced one; for the other half, digital sound control is the new feature and studio signal system is the enhanced one (see Appendix A). Because the manipulation of the new feature had no impact on the results, we do not discuss it further.1 Previous studies have suggested that a me-too product is unlikely to overtake the dominant brand; and in the experimental design, the successful manipulation of the dominant brand is evident when it is rated more favorably to the me-too brand (Kardes & Kalyanaram, 1992). Therefore we add a third product type—me-too—as a control condition. Of the 208 college students who participated in the study for extra credit, 48 were in the me-too condition, and 160 experienced the enhanced/ unique product conditions, which reflect our research focus. Stimuli On the basis of the pretest, we identified a product category (portable CD players) that was well known to the subjects as a familiar product stimulus. We adopted the attributes and attribute levels of CD players from Consumer Reports, but employed fictional names for the enhanced and new features. The instant language translator, a fictional product, was used as the unfamiliar stimulus. For each product, we created five brands (see Appendix A) on the basis of the attribute levels: Brand A (the dominant brand), Brand B (a distractor), Brand C (enhanced product), Brand C′ (unique product), and Brand C″ (me-too product). Using the pretests, we designed Brands A and B to be equally attractive, Brands C/C′ as objectively superior to Brands A and B, and Brand 1
We ran a 2 (product)×2 (familiarity)×2 (new feature) MANOVA to test whether the new feature has main or interaction effects on feature recall, preference judgment, and relative preference. The results show that neither the main effects nor the interactions are significant: product × familiarity × new feature, Wilks’ Lambda=0.977, F(3,150)= 1.200, p = 0.312; product × new feature, Wilks’ Lambda = 0.954, F(3,150)=2.290, p=0.088; familiarity × new feature, Wilks’ Lambda= 0.968, F(3,150)=1.645, p=0.181; and new feature, Wilks’ Lambda= 0.975, F(3,150)=1.257, p=0.291.
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C″ as identical to Brand A. To simulate the situation in which a dominant brand already exists in the market, we describe Brand A as a successful pioneer and present it more often than the other brands. The successful manipulation of the dominant brand will be demonstrated by results showing that Brand A is preferred to Brands B and C″ (cf. Kardes & Kalyanaram, 1992). To control for the possible confounding effects of multiple attributes, Brand C/C′ was designed to surpass Brand A only on one attribute (Sujan & Bettman, 1989). This control also provides ecological validity, because manufacturers often “introduce new products that differ from existing alternatives only on one attribute” (Meyers-Levy & Tybout, 1989, p. 43). To avoid a ceiling effect, as well as a floor effect, we selected two moderately and equally important feature levels (i.e., studio signal system and digital sound control, m=6.85 versus 7.00, t=0.32, p=0.75) as the focal attributes for the experiments (Sujan & Bettman, 1989, p. 458). Procedure In the experiment, subjects were told to evaluate hypothetical products using a three-section questionnaire. In “Conceptual Development”, the questionnaire first described the product class and the attributes, and then presented the attribute information for Brand A in table format, noting that Brand A was the successful pioneer. To induce participants to study the attribute descriptions, subjects were asked to evaluate the brand on a nine-point scale (“bad”/“good,” “unsatisfactory”/“satisfactory,” “unfavorable”/“favorable”) and indicate their confidence in their judgment (Kardes & Kalyanaram, 1992). Then subjects turned to a 5-min distracter task, which helped to avoid short-term memory effects on brand evaluation in the subsequent sections. Subjects then turned to “Section 2,” which described Brand A as “the brand you saw before” to remind participants of the existence of the dominant brand (e.g., Zhang & Markman, 1998), and provided the attribute information of Brand B in table format. Again, to induce participants to study the attribute descriptions, subjects were asked to evaluate the brands. After another 5-min distracter task, subjects turned to “Section 2,” which described Brand A/B as “the brand you saw before” and provided attribute information about a new product: enhanced, unique, or me-too, in table format. Participants made preference judgments, indicated their perceptions of the new product, and answered several questions on manipulation checks. Finally, they were asked to recall as many features of the last brand as they could, without looking at the descriptions. The entire procedure took approximately 30 min to administer. Measures In “Section 3,” participants allocated 100 points among the three brands to reflect their preference judgments
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for each one (Carpenter & Nakamoto, 1989). To capture the advantages and disadvantages of the new product in comparison with the dominant brand, we used relative preference as the dependent variable to assess the difference in preference between the new and dominant brands (i.e., Δp=Brand C or C¶-Brand A). To measure feature recall, we employed a naive rater to classify recall protocols as correct or incorrect, according to both the attribute and the feature levels, and score the number of shared, enhanced, and unique features correctly recalled. One of the authors randomly coded half of the responses, and there was 99% agreement between raters. Disagreements were resolved by discussion. The proportion of correct feature recall was used as the measure. On the basis of Sujan and Bettman (1989) and our pretests, we developed a three-item, nine-point Likert-scale (1: strongly disagree, 9: strongly agree) to measure perceived differentiation. Participants indicated their agreement or disagreement with statements such as “this brand is distinctive from other brands,” “this brand is different from other brands,” and “this brand can be easily distinguished from other brands” (Cronbach’s α=0.94). The measure of perceived performance uncertainty was adapted from Shimp and Bearden (1982). It consists of three nine-point scaled items (1: strongly disagree, 9: strongly agree; reverse-coded): “I am sure that this brand will perform as described,” “I am certain that this brand will work satisfactorily,” and “I am confident that this brand will perform as expected” (α=0.93). We adapted the measure of product familiarity from Coupey, Irwin, and Payne (1998). It consists of two ninepoint scaled questions (1: not at all familiar, 9: very familiar): “Are you familiar with CD players (instant language translators)” and “Are you familiar with the product features of CD players (instant language translators)” (α=0.92). Results Manipulation checks All manipulations were successful. First, subjects were much more familiar with CD players (m=6.13) than with language translators (m=2.16, p
