understanding common attribute devaluation in · pdf file · 2014-04-22journal of...

Journal of Marketing Theory and Practice, vol. 21, no. 4 (fall 2013), pp. 389–403.© 2013 M.E. Sharpe, Inc. All rights reserved. Permissions: www.copyright.com

ISSN 1069–6679 (print) / ISSN 1944–7175 (online)DOI: 10.2753/MTP1069-6679210403

Many marketers have responded to increasingly fragmented customer needs by introducing line extensions within the same product category covering a wide array of single attributes. However, managing such large portfolios can be unprofitable due to high expense and cannibalization from firm’s existing products (Dodes 2007; Mason and Milne 1994). Therefore, marketers have recently moved to enhance category profitability by retracting portfolios and develop-ing multifunctional products (Kang 2007). An example is a smartphone, which includes video, photography, music, gaming, and GPS (global positioning system) capabilities. There are even “complete” products, such as Colgate Total toothpaste, which is positioned to include every significant function in the category (Neff 2008).

Although much research has developed multifunctional-product attitude and choice models (Ajzen 1991; Shocker and Srinivasan 1979), relatively little work has explored its effectiveness (Chernev 2007). While some theory suggests that introducing new attributes and creating multifunc-tional products is beneficial (e.g., Bertini, Ofek, and Ariely 2009), other work finds the opposite. For example, consum-ers devalue an attribute in an “all-in-one” (two-function) product that is in common with a specialized (single-function) alternative when the two products are in the same choice set (Chernev 2007). Chernev’s (2007) research is an

important extension of compensatory reasoning theory to multifunctional product judgment. However, scant research since has investigated under which circumstances common attribute devaluation may be more or less pronounced.

This is an important unanswered question both concep-tually and managerially. Conceptually, better understanding attribute devaluation and its potential boundary conditions would add value to the literature on multiattribute product perception. Managerially, common attribute devaluation represents an important risk for marketers to consider when they contemplate the launch of a multifunctional product into a category that includes specialized products. It would be helpful for managers to know if they can use any marketing strategies to mitigate or even reverse attri-bute devaluation, and thus enhance the attractiveness of multifunctional products. Furthermore, no research has examined the implications of attribute devaluation magni-tude on choice of multifunctional products. Understanding consumer’s choice behavior not only provides criterion-related validity for attribute devaluation magnitude but also assists managers in terms of knowing its potential outcomes on behavior.

Therefore, our research objectives are to investigate moderators of attribute devaluation, to explore whether it can be reversed under certain circumstances, and to obtain multifunctional-product choice data to determine its consequences on behavior. Specific contributions to existing theory include investigating the potential moderat-ing role of complete positioning on attribute devaluation, the possibility interaction effect between price level and complete positioning, and the feasible further interaction effect among supporting benefits, price level, and complete

Understanding Common attribUte devalUation in mUltifUnCtional ProdUCts

timucin ozcan and daniel a. sheinin

Multifunctional products are increasingly marketed, yet relatively little research exists on their effec-tiveness. Some research indicates that adding attributes enhances product perceptions, while other work suggests the opposite. Supporting the second conclusion, when both a multifunctional and specialized product contained the same attribute, consumers devalued the attribute in the multifunctional product when the two products were in the same choice set. This contrasting perspective is addressed by inves-tigating which marketing strategies mitigate or even reverse common attribute devaluation. In three studies, positioning, price level, and supporting benefits are examined. Complete positioning mitigates common attribute devaluation in multifunctional products, but this effect is moderated by price level and supporting benefits.

timucin ozcan (Ph.D., University of Rhode Island), Assistant Professor of Marketing, Southern Illinois University Edwardsville, Edwardsville, IL, [email protected].

daniel a. sheinin (Ph.D., Columbia University), Associate Pro-fessor of Marketing, University of Rhode Island, Kingston, RI, [email protected].

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positioning. This will add significant depth to Chernev’s (2007) attribute devaluation construct, address the sub-sequent gap in the literature on moderators of attribute devaluation, and thus extend the literature on multifunc-tional product judgment. Consistent with Chernev (2007), this research is limited to multifunctional products with two attributes. In three studies, product positioning, price level, and supporting benefits are explored.

ConCePtUal framework

The importance and topicality of better understanding multifunctional products is exhibited in the research. Multifunctional products have been studied in various contexts, such as their alignability across line extensions (Herrmann et al. 2009), relationships with new product and related categories (Shapiro, Spence, and Gregan-Paxton 2009; Singh, Hansen, and Gupta 2005), effects on brand equity (Dillon et al. 2001), and coherence among attributes (Kayande et al. 2007).

However, more fundamental issues are the extent to which and under what conditions multifunctional products are effective. Surprisingly, despite the increased prominence of multifunctional products in both theory and practice, little work has explored this question (Chernev 2007). Some research suggests that adding new attributes to create a mul-tifunctional product enhances incremental utility and thus overall judgment (Bertini, Ofek, and Ariely 2009; Mukherjee and Hoyer 2001; Nowlis and Simonson 1996), even when these attributes are less important (Brown and Carpenter 2000). In contrast, recent work has found the opposite. Multifunctional technology products were assessed less positively than specialized alternatives at high levels of technology performance (Han, Chung, and Sohn 2009). Outside the context of technology products, consumers developed postpurchase attribute fatigue with multifunc-tional products (Thompson, Hamilton, and Rust 2005).

Common attribute devaluation presents a further chal-lenge to the effectiveness of multifunctional products. It occurs when an attribute that is in both a multifunctional and specialized product is devalued in the multifunctional context when the products are evaluated concurrently. The devaluation is caused by a perception that the differentiat-ing attribute in the multifunctional alternative is superior because it is absent from the specialized alternative. Thus, consumers “compensate” by assessing the common attribute as inferior, causing common attribute devaluation (Chernev and Carpenter 2001). For example, within its toothpaste portfolio, Colgate offers specialized (Colgate Optic White),

multifunctional (Colgate Tartar Protection with Whiten-ing), and complete (Colgate Total) products. According to attribute devaluation, whitening functionality in the multi-functional and complete products would be devalued when they shared shelf placement with the specialized alternative. The application of compensatory reasoning to discover and explain attribute devaluation is a significant evolution in better understanding judgments about multifunctional products. The next step, and our main research objective, is to examine how certain marketing strategies may mitigate or even reverse attribute devaluation and to obtain behavioral data on choice of multifunctional products as a function of attribute devaluation magnitude.

The first marketing strategy investigated in this research is product positioning. Positioning is “the art of designing the company’s offering and image to occupy a distinct place in the minds of the target market” (Kotler and Keller 2009, p. 268). Product positioning is important because it influ-ences beliefs about all of a product’s attributes (Carpenter and Nakamoto 1989; Punj and Moon 2002; Sujan and Bettman 1989). Prior research proves the importance of positioning to product judgments (Blankson and Kalafatis 2001; Gwin and Gwin 2003; Kim and Meyers-Levy 2008; Pham and Muthukrishnan 2002; Punj and Moon 2002). Although Chernev (2007) used the label “all-in-one” to theoretically describe multifunctional products, his par-ticipants were never exposed to the term and thus did not interpret them within the all-in-one context. In other words, he did not examine how different product positionings may alter common attribute devaluation.

Completeness is the product positioning examined. Complete positioning is relevant to multifunctional products because of their higher attribute load. Complete-positioned products are perceived as including all the important attributes currently offered in their categories (Ozcan and Sheinin 2012). For example, Colgate Total toothpaste connotes a full attribute set. Evidence suggests that a perception of completeness leads to enhanced quality judgments, stronger support arguments, and more positive evaluative benefits. The more complete the information, the better its quality when all the other variables, such as relevance, recency, and accuracy, are held constant (Dutta-Bergman 2004; Eysenbach et al. 2002). Greater information completeness also increases argument strength, which in turn influences persuasiveness and source credibility judgments (Dutta-Bergman 2004). In a marketing context, complete positioning helps to remind consumers of forgot-ten attributes, adding positively to the product’s evaluation (Neff 2008). For example, a product message that conveys

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complete information about a product would include mul-tiple product benefits explicitly in ad copy. These findings suggest that perceived completeness should lead to stron-ger and more positive product beliefs, and more positive product attitudes.

Moreover, if a consumer judges a multifunctional product as complete, then less information processing is necessary. Multifunctional products are complex because of the need to assess and understand each of the attributes and then make an overall attitude judgment based on some combination of the attributes (e.g., Fishbein and Ajzen 1975). In general, with more complex stimuli, providing a means of processing facilitation generates positive affect (Berlyne 1974; Reber, Winkielman, and Schwarz 1998; Winkielman and Cacioppo 2001). Specifically, a clear message reduces ad processing time, making attitude toward the product more positive (Brown and Stayman 1992; Meyers-Levy and Malavia 1999). This combination of cognitive and affective benefits should lead to the mitigation of common attribute devaluation with complete positioning in multifunctional products:

Hypothesis 1: Complete positioning will mitigate common attribute devaluation in a multifunctional product when compared to a specialized product.

Price level should interact with product positioning. Price level alters judgments of otherwise identical beliefs (Grewal and Lindsey-Mullikin 2006) and signals quality across all of a product’s attributes (e.g., Cronley et al. 2005). When multifunctional products were priced higher than specialized alternatives, common attribute devaluation was mitigated (Chernev 2007). However, it is unknown how price level may change the effects of positioning.

When multifunctional products are complete posi-tioned, they should display differences in common attribute devaluation as a function of price. With a high price, common attribute devaluation would not be just mitigated but reversed, which we call “common attribute enhancement.” Higher price signals higher quality (e.g., Mitra 1995; Monroe, Della Bitta, and Downey 1977) and, as previously argued, complete positioning should also signal evaluative benefits. So, in this context, both price level and positioning signal competence and quality across multiple attributes, leading to common attribute enhance-ment. In contrast, common attribute devaluation should occur in multifunctional products with a low price as the lower-quality inference should counteract and dominate the positioning effect. Negative information dominates positive information when both co-occur in a judgment context (e.g., Kahneman and Tversky 1979), and negative

outcomes are avoided to a greater extent than positive ones are accepted (Grant, Malaviya, and Sternthal 2004):

Hypothesis 2a: Complete positioning and a high price level will lead to common attribute enhancement in a multifunctional product when compared to a special-ized product.

Hypothesis 2b: Complete positioning and a low price level will lead to common attribute devaluation in a multifunctional product when compared to a special-ized product.

stUdY 1

objective, Participants, and design

The objective of Study 1 is to test H1. Participants (n = 148) were recruited from a large, midwestern public university in exchange for extra course credit. The study follows Cher-nev’s (2007) Study 1 procedure, stimuli, and measures, with the addition of the positioning variable (see Table 1 for the stimuli). Thus, multifunctional products were operational-ized as containing two attributes. We investigate how judg-ments about them change in various contexts when they are in the same choice set as specialized (single-attribute) alternatives. Choice sets were constructed out of three prod-ucts. Product C (the multifunctional product) contained two attributes 1 and 2, while products A and B (the special-ized alternatives) contained only attribute 1 and attribute 2, respectively. A 3 (choice set: AC, BC, and ABC) × 2 (posi-tioning of product C: complete and control) × 3 (product category: shaving cream, cold relief medicine, and vitamin supplements) × 2 (product type: multifunctional and spe-cialized) mixed design was used. Choice set and positioning were between subjects and product category and product type were within subjects.

Following Chernev (2007), two binary (AC and BC) and one trinary (ABC) choice sets were created to enhance gen-eralizability. Every product was positioned, but products A and B were positioned only by their single attribute (e.g., the attribute in cold relief medicine A was “relieves chest congestion,” so the positioning was “chest congestion treatment”). Product C was positioned either as complete (“complete cold treatment”) or as a control. The control condition used a straightforward attribute positioning, to be similar with Chernev’s (2007) stimuli. The control positioning simply repeats the two attributes verbatim, so it adds no extra information or value to the product. Therefore, although Chernev did not use positioning, his


stimuli and our control condition have identical informa-tion. Thus, the control condition was important to validate our stimuli relative to Chernev’s.

Pretest

We ran a pretest to test the positioning manipulation. The pretest was run instead of using manipulation checks because of the within-subjects nature of the main studies. If perceived completeness was assessed as a manipulation check after exposure to the first stimulus set, then that could establish a demand effect when the same participants evaluated the second stimulus set. Two questions measured positioning using a seven-point semantic differential scale anchored by disagree/agree: (1) Alternative C is complete positioned and (2) Alternative C offers more attributes than Alternative A (or B if the choice set was binary, or both A and B if the choice set was trinary). No intermediate scale points were labeled. While the first item focused on the direct per-ception of the positioning, the second was included to see if the perceived positioning would lead to attribute-quantity inferences. Across all the categories, the two measures were higher under complete versus control positioning in both the binary (each p < 0.01) and trinary (each p < 0.05) choice sets. In addition, the specialized alternatives were perceived as having an equal number of attributes (p > 0.05). Thus, the manipulation of the positioning was effective.

Procedures and measures

Before viewing the research stimuli, the participants read that they would see two or three product alternatives

from each of three different product categories, evaluate the products’ attributes, and make a choice between the products. Following Chernev (2007), choice sets for each category were shown for 20 seconds on a single PowerPoint slide. The positioning was placed under the product name. After choice set exposure, the participants rated each attri-bute in every product. Attribute ratings were measured on a nine-point semantic differential scale anchored by low/high, and again no intermediate scale points were labeled. To illustrate, for the cold relief medicine category in the trinary ABC choice set, the participants were first asked “How would you rate the chest congestion relief proper-ties of cold relief medicine A?” Then, they answered the same question for the other two alternatives in the choice set. Next, the participants were asked to rate the second attribute (i.e., nasal stuffiness clearing) for all three alter-natives. Following this task, the participants chose among the alternatives conditional on one of the attributes having primary importance. For example, “Which of the three products would you choose if your primary concern is chest congestion relief?”

Then, the perceived importance of each attribute was assessed (e.g., chest congestion relief is an important attribute of cold medicine) using a seven-point semantic differential scale anchored by disagree/agree. If attribute importance is asymmetric, then it can confound the results. An attribute perceived as less important can lead to a reduction in product value due to the declining ratio between key attributes and price (Simonson, Carmon, and O’Curry 1994). Also, attri-bute covariation can occur in which judgments about one attribute spill over onto others (e.g., Aaker and Keller 1990), a significant potential issue with a multifunctional product.

Table 1Stimuli—Studies 1 and 2

Product CategoryOption A

(Specialized)Option B

(Specialized)Option C1

(Multifunctional) Price2

Study 1Cold relief medicine Relieves chest congestion Clears nasal stuffiness BothShaving cream Moisturizes Protects BothVitamin Improves memory Reduces stress Both

Study 2 Laundry detergent Protects color Removes stains Both $7.99/$9.99Shaving cream Moisturizes Protects Both $2.99/$3.99Toothpaste Prevents cavities Tartar protection Both $1.99/$2.99Vitamin Ginseng Ginkgo biloba Both $6.99/$8.99

1 Complete positioning was manipulated by using phrases such as “Complete Vitamin” in the title. Control positioning group included only the names of the attributes in the title such as “Memory Improvement & Stress Reduction.”2 Price was manipulated in Study 2.

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Although Chernev (2007) did not test for attribute impor-tance, he used well-known attributes that would appear to be equally important. Since his stimuli were used throughout the current research with a different participant population, we believed that it was important to check for any potential confounding effects of importance.

results

The binary data (AC and BC) were examined first. Like in Chernev’s (2007) study, ratings on the attribute that was common to the multifunctional and specialized products is the dependent variable. In this manner, the change in attribute rating between the two products, and therefore the extent of common attribute devaluation, could be assessed. A 3 (product category) × 2 (positioning) mixed-model analy-sis of variance (ANOVA) on the common attribute rating showed no effects of category (p > 0.05), so the data across the categories were aggregated. An analysis of covariance (ANCOVA) revealed no significant effects involving attribute importance as a covariate.

Then, to test H1, a 2 (product type) × 2 (positioning) mixed-model ANOVA on the common attribute rating was run, with product type within subjects and positioning between subjects. The main effects of positioning and product type were not significant, but the predicted inter-action was present (F1, 298 = 30.20, p < 0.0001). Strongly confirming H1 (see Table 2 for rating and significance data), with complete positioning, common attribute enhance-ment occurred (MMultifunctional = 7.57 versus MSpecialized = 6.68, t136 = 3.72, p < 0.0001). With the control positioning, repli-cating Chernev’s (2007) study, common attribute devalu-ation occurred (MMultifunctional = 6.55 versus MSpecialized = 7.29, t136 = 3.72, p < 0.0001).

Next, the same analysis sequence with the trinary data was followed. Again, data were aggregated across the cat-egories as the 3 (product category) × 2 (positioning) mixed-model ANOVA on the common attribute rating showed no effects with category. The attribute importance covariate was nonsignificant. Then, two 2 (product type) × 2 (position-ing) mixed-model ANOVAs were run to test H1 instead of the one 2 × 2 in the binary context. Recall that attribute 1 is common between alternatives A (specialized) and C (multifunctional), and attribute 2 is common between alternatives B (specialized) and C (multifunctional). For each attribute, there was a main effect of product type (F1, 145 = 9.33, p < 0.001 and F1, 145 = 11.16, p < 0.001), which was conditioned by the predicted interaction (F1, 145 = 11.19, p < 0.001 and F1, 145 = 20.60, p < 0.0001). Mean comparisons

for both attributes (see Table 2) showed complete position-ing mitigated common attribute devaluation (each p > 0.30), reconfirming H1. In contrast, common attribute devalua-tion occurred in the control condition (each p < 0.0001).

Then, the choice data were analyzed for the multifunc-tional product C to examine the implications of the attri-bute effects. Given that complete positioning mitigated common attribute devaluation, we expected choice of the multifunctional product to be greater in this context than the control. Supporting this notion, when the participants chose a product based on attribute 1, complete position-ing was preferred to the control in AC and ABC (p < 0.06 and p < 0.0001, respectively; see Table 2). The same result occurred with choice based on attribute 2 in BC and ABC (p < 0.01 and p < 0.0001, respectively).

discussion

The attribute ratings data strongly confirm H1 via multiple comparison tests and provide face and construct validity relative to Chernev (2007) through the control condition. The choice results provide criterion-related validity via concurrent validity for the common attribute devaluation differences. Although these findings provide strong empiri-cal evidence for H1, the results may have been limited to the specific categories used. Thus, one objective of Study 2 is to replicate Study 1 using some different product categories to enhance generalizability. The second objective of Study 2 is to extend Study 1 by investigating H2a and H2b.

stUdY 2

objective, Participants, design, Procedure, and measures

Chernev’s (2007) Study 2 procedure, stimuli (including price levels), and measures were adopted, with the addi-tion of the positioning variable (see Table 1 for stimuli). Undergraduate students (n = 163) from a large, midwestern state university were recruited to participate in exchange for extra credit. For parsimony, only the trinary choice set ABC was used in this study with the product price being manipulated. Therefore, the design was a 4 (price level: ABC, A+BC, AB+C, and ABC+) × 2 (positioning of product C: complete and control) × 4 (product category: toothpaste, shaving cream, laundry detergent, and vitamin supple-ments) × 2 (product type: specialized and multifunctional) mixed design. Price level and positioning were between subjects and product category, and product type were within


subjects. A higher price level was denoted by a + sign, so that ABC+ represented C being highest-priced in the choice set. In the absence of a + sign, the products were priced at parity. The parity condition ABC was included to retest H1 because the stimuli without price-based inferences should replicate the results from Study 1. As in Study 1, products A and B are specialized and contain only one attribute each (attributes 1 and 2, respectively). Product C is multifunc-tional and contains both attributes 1 and 2. Choice was measured by asking the participants to choose one of the products per choice set after they filled out the attribute rating scales (see Table 1 for stimuli).

Pretest

A pretest was run to test the positioning manipulation instead of using manipulation checks because of the within-subjects nature of the main studies. The same two measures of perceived completeness as in the Study 1 pretest were used, but with the categories used in Study 2. Across these categories, the two measures were higher under complete versus control positioning in the trinary choice set (each

p < 0.05). In addition, the specialized alternatives were per-ceived as having an equal number of attributes (p > 0.05). Thus, the manipulation of the positioning was effective.

The price-level manipulation was checked using one item (“Alternative A is more expensive than Alternative B”) measured with a seven-point semantic differential scale anchored by disagree/agree. The item was measured three times (A is more expensive than B, A is more expensive than C, and B is more expensive than C) to cover all the combina-tions. When there was price parity, no pricing manipulation check was included. The results showed that participants had a higher price perception when one alternative was priced above the others (each p < 0.0001).

results

A 4 (product category) × 2 (positioning) mixed-model ANOVA showed no effects involving product category, and we aggregated the data across all the categories. Attri-bute importance was not a significant covariate for either common attributes 1 (p > 0.10) or 2 (p > 0.20). Recall that common attribute 1 was common between the multifunc-

Table 2 Data—Study 1

Common Attribute Ratings (9-point scale)

Specialized Multifunctional Significance

BinaryComplete 6.68 7.57 t

161 = 3.72, p < 0.0001

Control 7.29 6.55 t136

= 3.72, p < 0.0001Trinary

Attribute 1Complete 7.21 7.26 n.s.Control 7.70 6.48 t

74 = 4.15, p < 0.0001


74 = 5.88, p < 0.0001

Choice* of the Multifunctional Product

Complete (Percent)

Control (Percent) Significance

Attribute 1Binary AC 40.9 28.7 χ2

2 = 3.76, p < 0.06

Trinary ABC 22.5 4.8 χ22 = 16.52, p < 0.0001

Attribute 2Binary AC 66.1 48.4 χ2

2 = 6.82, p < 0.01

Trinary ABC 24.1 3.3 χ22 = 18.79, p < 0.0001

Notes: n.s. = not significant. * Choice percentages represent percentage of participants choosing multifunctional products.

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tional product C and specialized product A, and common attribute 2 was common between the multifunctional prod-uct C and specialized product B. Using the trinary choice set ABC allowed us to examine both attributes to enhance generalizability. Then a 2 (positioning) × 2 (price level) × 2 (product type) mixed-model ANOVA was conducted on each common attribute, with product type within subjects. The between-subjects analysis for attribute 1 showed main effects of positioning (F1, 640 = 3.71, p < 0.06) and price level (F3, 640 = 3.52, p < 0.05), which were qualified by a two-way interaction (F3, 640 = 6.51, p < 0.0001). With product type, there was a product type × positioning interaction (F1, 644 = 4.60, p < 0.05) and a product type × price level interaction (F3, 644 = 3.04, p < 0.05). However, all of these effects were qualified by the predicted three-way interaction (F3, 644 = 4.95, p < 0.005). The results for attribute 2 replicated those of attribute 1, including the three-way interaction (F3, 643 = 5.82, p < 0.001).

First, the context when the multifunctional product C was complete-positioned was examined. Consistent with H1 (see Table 3 for rating and significance data), common attribute devaluation was mitigated when C was priced at parity (ABC) with both common attributes (each p > 0.30). Opposing H2a, in which common attribute enhancement was expected, common attribute devaluation occurred when C was priced high (ABC+) with both common attributes. For example, common attribute 1 was lower in the multifunc-tional product (M = 6.18) than the specialized alternative (M = 7.30, t81 = 5.40, p < 0.0001), as was common attribute 2 (p < 0.0001). Confirming H2b, common attribute devalua-tion occurred with both attributes in both conditions when C was priced low (A+BC and AB+C; each p < 0.05).

When C was control-positioned, common attribute devaluation was mitigated when C was priced high (each p > 0.20). This is consistent with Chernev’s (2007) findings. When C was priced low, common attribute devaluation occurred in both attributes in A+BC (each p < 0.0001), attribute 2 in AB+C (p < 0.05), and attribute 1 in AB+C with moderate significance (p < 0.08). Consistent with Study 1, common attribute devaluation occurred when C was priced at parity (each p < 0.01).

Then the choice results were examined (see Table 3) to better understand the implications of the attribute ratings. With complete positioning, it is expected that choice of the multifunctional product C would be highest when it was priced at parity because this was the only price level where common attribute devaluation was mitigated. Indeed, choice of the multifunctional product differed across price levels (χ2

4 = 59.72, p < 0.0001), with parity

pricing (M = 92.2 percent) being the highest (p < 0.0001 versus each of the other three price levels). In contrast, with the control, we expected choice of C to be greatest when it was priced high because this was the only price level where common attribute devaluation was mitigated. Choice of the multiattribute product across price levels was marginally different (χ2

4 = 12.95, p < 0.06), with high price (M = 71.6 percent) being the greatest (p < 0.05 versus each of the other three price levels). Interestingly, when C was priced at parity, choice of the multifunctional product was higher under complete positioning than the control (χ2

2 = 39.10, p < 0.0001), while the opposite occurred when it was priced high (χ2

2 = 10.66, p < 0.01).

discussion

Under complete positioning, H1 was supported when the multifunctional product C was priced at parity. Opposing H2a, common attribute devaluation occurred when C was priced high where common attribute enhancement was predicted. Confirming H2b, common attribute devaluation occurred when C was priced low. The choice data again pro-vide criterion-related validity via concurrent validity with the attribute ratings results. Under the control condition, stimuli and procedure were once again similar to Chernev’s (2007) study due to the consistent results when C was priced high. We thought that the surprising result for H2a should be further explored. This result might have occurred because the product’s two attributes were insufficient to support the high-competence and high-quality inferences across multiple attributes generated from the combination of complete positioning and higher price. In other words, consumers would expect such a product to strongly deliver on multiple benefits, and simply supporting it with two lone attributes may be insufficient. To test this possibility, another study was conducted in which each attribute was bolstered with three supporting benefits.

stUdY 3

Conceptual background

Consumers are aware that marketers’ claims can be readily exaggerated (Obermiller, Spangenberg, and MacLachlan 2005). This potential for exaggeration increases as claims become more difficult to substantiate (Ford, Smith, and Swasy 1990). The “claim” of a higher-priced, complete product that was used in Study 2 may be difficult to sub-stantiate when backed only by two attributes and no other


diagnostic information. Therefore, in Study 3, quantity and quality of diagnostic information are augmented by adding three distinct benefit statements to each of these attributes. Although consumers may not process the details of six benefit statements supporting two attributes because of information overload (e.g., Malhotra 1982a), they should notice the quantity of the information. Information quan-tity can signal competence across attributes (Graeff 1997).

This would better support the high-quality inferences generated from the complete positioning and higher price combination. Per Kahneman and Tversky (1979), this would be an instance of the representativeness heuristic (where available data biases judgment) and the availability heuristic (where information that can be easily imagined or recalled biases judgment). In our context, the supporting benefits would be representative of a high-quality product, and

Table 3Data—Study 2

Common Attribute Ratings (9-Point Scale)


ABCAttribute 1

Complete 7.44 7.20 n.s.Control 7.51 6.82 t

75 = 2.90, p < 0.01


75 = 2.90, p < 0.01

ABC+Attribute 1

Complete 7.30 6.18 t81

= 5.40, p < 0.0001Control 7.07 7.35 n.s.

Attribute 2Complete 7.45 6.27 t

83 = 4.93, p < 0.0001

Control 7.18 7.58 n.s.A+BC


90 = 5.25, p < 0.0001

Control 7.95 6.67 t75

= 5.61, p < 0.0001Attribute 2


= 6.68, p < 0.0001Control 8.08 6.85 t

74 = 7.20, p < 0.0001

AB+CAttribute 1


= 3.43, p < 0.01Control 7.06 6.41 n.s.


79 = 2.59, p < 0.05

Control 7.11 6.44 t71

= 2.09, p < 0.05


Complete (Percent)


ABC+ 45.2 71.6 χ22 = 10.66, p < 0.01

ABC 92.2 51.3 χ22 = 39.10, p < 0.0001

A+BC 57.6 64.5 n.s.AB+C 61.3 61.1 n.s.


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easily imagined as belonging to a high-quality (especially multifunctional) product.

The presence of supporting benefits is expected to strengthen the effectiveness of the complete positioning and higher price combination, leading to common attribute enhancement. Recall that enhancement was proposed in H2a, but instead devaluation was found. With a lower price, the combination of complete positioning and supporting benefits is expected to dominate the price-based lower-quality inferences. This would differ from Study 2, where the lower price dominated complete positioning when it was the lone positive attribute-competence cue (H2b).

Hypothesis 3a: Complete positioning and a higher price level of multifunctional products with supporting ben-efits will lead to common attribute enhancement when compared to a specialized product.

Hypothesis 3b: Complete positioning and a lower price level of multifunctional products with supporting ben-efits will mitigate common attribute devaluation when compared to a specialized product.

method

Participants (n = 174) were undergraduate students from a large, Midwestern public university who received extra course credit for their participation. The design, procedure, stimuli, and measures were identical to Study 2 except three supporting benefits were listed for each attribute presented. Therefore, a new pretest was not conducted for the positioning and price level manipulations as the Study 2 pretest confirmed them. Supporting benefits were picked from Consumer Reports’ category ratings specifying key purchase criteria. Therefore, specialized products had one attribute and three benefits (i.e., “color protection” for laundry detergent had the three benefits “color-safe bleach alternative,” “supports protection for clothing fibers,” and “no need to use chlorine anymore”) and multifunctional products had two attributes and six total benefits (for the stimuli, see Table 4).

results

As in the previous studies, data were aggregated across categories as the 4 (product category) × 2 (positioning) mixed-model ANOVA demonstrated no significant effects involving category. Attribute importance was again not a significant covariate. A 2 (positioning) × 2 (price level) × 2 (product type) mixed-model ANOVA was run on each com-

mon attribute, with product type within subjects. There was a significant main effect of product type for both common attribute 1 (F1, 688 = 44.10, p < 0.0001) and 2 (F1, 688 = 28.89, p < 0.0001). For attribute 1, there was a price level × product type interaction (F3, 688 = 2.61, p < 0.05) but no higher-order effect. Attribute 2 showed the expected three-way interac-tion (F3, 688 = 4.74, p < 0.005).

Under complete positioning, the data confirm H3a. When the multifunctional product C was complete-positioned and priced high (ABC+), common attribute enhancement occurred (for attribute rating and significance data, see Table 5). For example, the rating of common attribute 1 was higher with the multifunctional product (M = 8.13) than the specialized alternative (M = 7.16, t83 = 4.73, p < 0.0001), which was replicated with common attribute 2 (p < 0.0001). Confirming H3b, when C was priced low, common attri-bute devaluation was mitigated in both attributes with A+BC (each p > 0.50), and common attribute enhancement occurred with both attributes in AB+C (each p < 0.01). Common attribute devaluation was also mitigated for both attributes when C was priced at parity (each p > 0.30).

In the control condition, common attribute devaluation was mitigated when C was priced high (each p > 0.60). When C was priced low, common attribute enhancement occurred with both attributes in A+BC (each p < 0.01) and with com-mon attribute 1 in AB+C (p < 0.0001). Common attribute devaluation was mitigated with common attribute 2 in AB+C (p > 0.15). Common attribute devaluation was also mitigated when C was priced at parity for both common attributes (each p > 0.25).

Then choice of C was examined. With complete position-ing, we expected choice of the multifunctional product to be high and the same across the price conditions because either common attribute devaluation was mitigated or com-mon attribute enhancement occurred in each context. Con-sistent with this expectation, the four choice percentages were the same (p > 0.15) and high (each > 90 percent). With the control, we also expected choice of the multifunctional product to be the same across the conditions for the same reason. However, the percentages were in fact different (χ2

4 = 18.31, p < 0.01). Somewhat surprisingly, choice of the multifunctional product was higher when C was priced low (A+BC at 94.5 percent and AB+C at 90.6 percent) than priced high (75.0 percent; each p < 0.05). This result is likely to have occurred because the higher relative attractiveness of getting a product with many benefits for a lower price. Moreover, supporting the common attribute enhancement effect found with H3a, choice of the multifunctional product C when priced high was greater with a complete


positioning (91.6 percent) than the control (75.0 percent; χ2

2 = 9.63, p < 0.01). The same result occurred when C was priced at parity (98.8 percent versus 86.8 percent; χ2

2 = 8.64, p < 0.05). When C was priced low, choice of the multifunctional product was high (each > 90 percent) and equal between complete positioning and the control. Again, this result could be because of the strong value of multiple benefits at a lower price regardless of positioning.

discussion

These data indicated the importance of supporting benefits for multifunctional products. In each of the six positioning/price level conditions, and for both common attributes, either common attribute devaluation was mitigated or common attribute enhancement occurred. In fact, com-mon attribute enhancement occurred most strongly when the multifunctional product was complete positioned and priced high. The results in that context reverse the com-mon attribute devaluation effects found in Study 2 for the same stimuli without supporting benefits. In the presence of supporting benefits, the common attribute enhancement effects that were expected in H2a in Study 2 were found, and therefore H3a was confirmed. In confirming H3b, the

robustness of the positive effects of supporting benefits for multifunctional products was demonstrated by show-ing the mitigation of common attribute devaluation even when they are priced low. Finally, the mitigation of com-mon attribute devaluation when multifunctional products are complete positioned and priced at parity supported earlier results in which common attribute devaluation was mitigated with complete positioning both without a price-level manipulation (Study 1) and when priced at parity (Study 2). Furthermore, the results in the control condition remained consistent with those from both Studies 1 and 2 and Chernev (2007).

general disCUssion

Using three studies, we investigated marketing strategies that would change common attribute devaluation in mul-tifunctional products. In Study 1, positioning moderated common attribute devaluation. The control positioning led to common attribute devaluation, but complete positioning led to either the mitigation of attribute evaluation or attri-bute enhancement. Common attribute-devaluation mitiga-tion and common attribute enhancement in turn caused a higher choice of multifunctional products. In Study 2,

Table 4Stimuli—Study 3

Product Category Supporting Benefits

Laundry DetergentOption A—Prevents static Color-safe bleach alternative; supports protection for clothing fibers; no need to use chlorine

anymore Option B—Removes stains Cleans the top 99 most-common stains; toughest cleaning formula; no need for pretreatment

anymore Option C All six above

Shaving CreamOption A—Moisturizes Improves elasticity; retexturizes and smoothens the skin; contains soothing ingredients Option B—Protects Provides lubrication for preventing irritation; shields against razor bumps; contains antioxidants

against free radicals Option C All six above

ToothpasteOption A—Prevents cavities Fluoride mineral system for cavity protection; added calcium for strength; removes 99 percent of

cavity-causing bacteria Option B—Tartar protection Controls tartar with zinc citrate; contains xylitol to help prevent plaque; helps prevent tartar build-

up Option C All six above

Vitamin SupplementsOption A—Memory Improvement Helps to improve short-term memory; increases cognitive functions; strengthens immune functionOption B—Stress Reducing Promotes a balanced emotional, mental, and physical state; offers antioxidants to protect body;

includes herbs to calm body and mind Option C All six above

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Study 1 was replicated and extended by the finding that price level moderated positioning effects. The positioning results from Study 1 were replicated with parity pricing. With high pricing, common attribute devaluation was mitigated with the control positioning but, unexpectedly, occurred with complete positioning. With low pricing, common attribute devaluation occurred regardless of positioning. Again, choice results mirrored common attribute-devaluation

magnitude. In Study 3, these findings were extended as bolstering each attribute with supporting benefits either mitigated common attribute devaluation or lead to com-mon attribute enhancement. Specifically, the unexpected common attribute devaluation for complete positioning/high pricing in Study 2 was reversed in Study 3 where com-mon attribute enhancement occurred. In Study 3, choice of multifunctional products was consistently high.

Table 5Data—Study 3

Common Attribute Ratings (9-Point Scale)


ABC+Attribute 1


= 4.73, p < 0.0001Control 7.22 7.63 n.s.


83 = 4.93, p < 0.0001

Control 7.70 7.77 n.s.ABC

Attribute 1Complete 7.58 7.31 n.s.Control 7.40 7.68 n.s.

Attribute 2Complete 7.44 7.65 n.s.Control 7.68 7.88 n.s.

A+BCAttribute 1

Complete 7.38 7.53 n.s.Control 7.04 7.65 t

91 = 2.81, p < 0.01


91 = 3.03, p < 0.01

AB+CAttribute 1


= 3.67, p < 0.0001Control 7.00 7.85 t

95 = 3.83, p < 0.0001


83 =3.00, p < 0.01

Control 7.58 7.81 n.s.


Complete (Percent)


ABC+ 91.6 75.0 χ22 = 9.63, p < 0.01

ABC 98.8 86.8 χ22 = 8.64, p < 0.05

A+BC 98.7 94.5 n.s.AB+C 96.4 90.6 n.s.



Conceptual implications

The overall contribution of this research was to extend the literature on the perception of multifunctional products by showing that marketing strategies moderate common attri-bute devaluation and in turn that mitigating common attri-bute devaluation leads to higher choice. With some research suggesting that adding attributes increases overall product utility (e.g., Brown and Carpenter 2000), and other work suggesting the opposite (e.g., Chernev 2007; Han, Chung, and Sohn 2009), there were unanswered questions about the effectiveness of multifunctional products. Specifically, four contributions to the literature on multifunctional-product belief formation are delineated, especially relative to Chernev’s (2007) study.

Our first two contributions are the finding that com-plete positioning mitigates common attribute devaluation, with an effect so strong that at times common attribute enhancement occurred, and providing criterion-related validity for that result by demonstrating that it leads to an associated increase in choice of multifunctional products. The literature suggests that a complete positioning would lead to favorable inferences, based on product attributes being judged as better in quality (Dutta-Bergman 2004; Eysenbach et al. 2002), more persuasive (Dutta-Bergman 2004), and more positive (Neff 2008). Future work should obtain cognitive response data to better understand the exact inferences derived from complete positioning. More-over, complete positioning makes the processing of multi-functional products rapid and straightforward. Processing facilitation generates positive affect (Berlyne 1974; Reber, Winkielman, and Schwarz 1998; Winkielman and Cacioppo 2001). This combination of cognitive and affective benefits could be responsible for the mitigation of common attribute devaluation with complete positioning in multifunctional products.

The third contribution is in demonstrating that price level changes the magnitude of multifunctional-product common attribute devaluation and choice. With the control positioning, common attribute devaluation was mitigated when the multifunctional product was priced higher than a specialized alternative. The higher-quality inferences stemming from the higher price (e.g., Monroe, Della Bitta, and Downey 1977) appeared to overwhelm common attri-bute devaluation. With a lower price, it would appear that lower-quality inferences exacerbated common attribute devaluation, although more work is needed to more pre-cisely understand this inferential process. With complete positioning, the expected common attribute enhancement with a higher price failed to materialize, with common

attribute devaluation occurring instead. With a lower price level, common attribute devaluation occurred, likely indi-cating the negative perceptions from price dominated the positive perceptions from positioning. This is consistent with other research that found that negative judgments overwhelm positive ones when they are concurrent (e.g., Grant, Malaviya, and Sternthal 2004; Kahneman and Tversky 1979). Our results extend the present understanding that high price moderates common attribute devaluation (Chernev 2007) by showing that its effects in fact differ as a function of positioning.

Our fourth contribution is demonstrating the strong effects of supporting benefits on evaluations that either common attribute devaluation is mitigated or common attribute enhancement occurs in every condition. With supporting benefits, choice of multifunctional products is consistently high across all of the experimental condi-tions. The complete positioning/higher price result was surprising and was further explored. The positive inferences generated from the combination of complete positioning and higher pricing were likely insufficiently supported by two lone attributes and no other diagnostic information. Consumers know that marketers’ claims can be readily exaggerated (Obermiller, Spangenberg, and MacLachlan 2005), especially as claims become more difficult to sub-stantiate (Ford, Smith, and Swasy 1990). However, adding information quantity (Graeff 1997), in the form of sup-porting benefits, furthered our contribution by reversing some key findings with otherwise identical stimuli from the second study. With supporting benefits, common attribute devaluation was mitigated in every positioning/price level condition. This was unexpected in the control positioning/low-price context, where common attribute devaluation was predicted. Supporting benefits also reversed common attribute devaluation in the complete positioning/higher-price condition, causing common attribute enhancement. Thus, a high price level augmented the more positive judgments that ensued from the complete positioning but only when the two single attributes were bolstered by sup-porting benefits.

managerial implications

Our results provide a roadmap for managers of multifunc-tional products by finding more detailed advantages and disadvantages than previously established in the literature. Common attribute devaluation can be overcome by the right mix of marketing strategies, enhancing the potential of utilizing multifunctional products. In general, multi-functional products benefit from complete positioning,

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which mitigates the devaluation of attributes in common with specialized products, thus leading to higher choice. However, lower prices and a lack of supporting benefits can mitigate the benefits of complete positioning. Sup-porting benefits were necessary to maximize the effects of complete positioning and higher prices. Managers must be cognizant of the real possibility that customers will be negatively disposed toward multifunctional products at higher prices unless there is substantial supporting benefit information to back up the implicit higher-quality claim. This is important, as one obvious benefit of developing a complete product is the ability to charge a price higher than lower-capability specialized products. Overall, provid-ing supporting benefits unquestionably maximized the advantages of complete positioning with multifunctional products regardless of price level. Such in-depth informa-tion clearly enhanced the beneficial perceptual advantages of multifunctional products that were previously limited to particular contexts and thresholds in Studies 1 and 2. Specifically, without supporting benefits, multifunctional products required either complete positioning or higher pricing to mitigate common attribute devaluation. How-ever, supporting benefits also mitigated common attribute devaluation for attribute-positioned multifunctional prod-ucts, even at lower prices.

limitations and future research

One limitation of our research is that the perception of claim exaggeration, thought to underlie judgments about complete positioned/high price multifunctional products based only on two attributes, was not measured. Future research should better understand the process that under-lies judgments about multifunctional products, perhaps by incorporating measures on consumer skepticism (e.g., Obermiller, Spangenberg, and MacLachlan 2005). Moreover, although the literature suggests that complete positioning bestows particular judgmental advantages for multifunctional products, those thought protocols were not measured. Future work should obtain cognitive responses to better understand positioning-based inferences. In addi-tion, research is needed to explore why common attribute enhancement occurred under complete positioning in a binary choice context and common attribute devaluation was mitigated in the trinary choice context. Perhaps the binary choice context is less complex, making the effects of complete positioning more potent by operating more as a decision heuristic. In this manner, decision complexity may mediate the relationship between choice set composi-

tion and common attribute devaluation magnitude. More data should be collected with choice set quantity as an independent variable.

Future work should further explore the Study 3 findings where the low-priced complete-positioned product displayed common attribute devaluation yet also exhibited the highest choice percentage. We speculated that the result is obtained from the higher relative attractiveness of getting a product with many benefits for a lower price but did not measure attractiveness or value perception. Attractiveness and value perception may in fact mediate the relationship among product positioning, supporting benefits and price level, and choice. Research is also needed to vary attribute importance to see if asymmetric importance alters when enhancement and devaluation occur. Furthermore, like Chernev (2007), we used multifunctional products with two attributes. However, evidence from research using conjoint analysis (Malhotra 1982b) suggests that attributes may become less important as the total number of attributes increases. This suggests a need to examine multifunctional products with three or more attributes to see if attribute quantity moderates com-mon attribute devaluation magnitude, possibly mediated by perceived importance. Finally, as suggested by the previous literature, common attribute devaluation may even be more prominent in technology products. Since our research did not use any technology products as stimuli, future research may investigate this issue within those product categories.

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