JOURNAL OF CONSUMER PSYCHOLOGY, 13(1&2), 103–112 Copyright © 2003, Lawrence Erlbaum Associates, Inc.
SCHLOS C OMPUT SE E RS R AS SI TUATI ONAL CUES
Computers as Situational Cues: Implications for Consumers Product Cognitions and Attitudes Ann E. Schlosser Department of Marketing University of Washington
Whereas the Internet itself poses unique challenges and opportunities, it is possible that the context of the Internet (a computer context) affects consumers differently than other contexts would, thereby causing people to think about and evaluate products differently. Drawing from learning theory and the functional theory of attitudes, it is predicted that computers, by being associated with the accessibilityof detailed information, will elicit a need for meaning. Consequently, when a computer is present, people may think about and seek more product information than will those evaluating the product on paper (a print context). The results of an experiment support these hypotheses. Across two diverse products, the mere presence of a computer caused people to think more about and request more information about the product than those in the print context did. Furthermore, the attitudes of those in the computer context were more representative of both dimensions described in the advertisement, whereas the attitudes of those in the print context reflectedthe valence of the dimension that is typically used when evaluating the product. Implications for promoting products and conducting market research in computer environments are discussed.
The Internet has many unique features, among which is its digital nature. One implication of this feature is that marketers are not constrained in the depth and breadth of product information they deliver to consumers through the Internet. Yet, with such unique features arise challenges, such as how to develop strategies that will take advantage of these new capabilities as well as whether such approaches are welcomed or even desired by consumers. Devising new, effective strategies is further complicated by the likelihood that consumers respond differently to products presented in computer contexts than in other traditional media settings. Computers, especially with the advent of the Internet, are devices used for information organization, dissemination, storage and retrieval. The digitalnature of the Internetallowsit to be encyclopedicin nature. Indeed, the Web and Internet are argued to have produced significant advancements in the retrieval and dissemination of information (Lawrence & Giles, 1998). Furthermore, most Internet users report spending most of theirtime, on the Internetcollectinginformation(GVU 10th Survey, 1998). Drawing on learning theory and the functional theory of attitudes,I argue that because of these computer (and Requests for reprints should be sent to Ann Schlosser, University of Washington, School of Business, Box 353200, Seattle, WA 98195–3200. E-mail:
[email protected]
Internet) characteristics, consumers may think about and evaluate products differently when in the mere presence of a computer than when a computer is absent. This article begins with an overview of research on situationalcues and cue-compatibleresponding,followed by theimplicationsof situational cues for the attitudefunctions elicited and the implicationsfor consumers cognitionsand judgments when they are in a computer environment versus not.
SITUATIONAL CUES AND LEARNING THEORY In a variety of contexts, the mere presence of objects have been shown to influence judgments (Scheier & Carver, 1980; Schwarz & Clore, 1983), intentions (Feinberg, 1986), and behavior (Berkowitz & LePage, 1967; McCall & Belmont, 1996; Scheier, Fenigstein, & Buss, 1974). Perhaps the most well-known and researched situational cue effect is what is referred to as the “weapons effect” (Berkowitz & LePage, 1967): The mere presence of a weapon enhances aggressive responding (the delivery of shocks). Applying learning theory, this effect is argued to occur because the weapon represents a conditioned stimulus that is typically associated with aggression and thus elicits a conditioned aggressive response
104
SCHLOSSER
(Berkowitz, 1974). In the consumer realm, this reasoning has been used to explain why the mere presence of a credit card or credit card insignia leads to higher tipping (McCall & Belmont, 1996) and greater intended spending (Feinberg, 1986). Because credit cards are typically associated with credit availability, they elicit a conditioned spending response. In addition to the more automatic conditioned stimulus–response explanation, two additional explanations have been proposed (Berkowitz, 1974, 1982, 1983) and tested (Carlson, Marcus-Newall & Miller, 1990). One is that situational cues might act as discriminative stimuli, which signal that performing certain behaviors will provide reinforcement. Thus, on seeing a weapon, the individualmight believe that aggressive behavior will be reinforced. A third explanation applies Leventhal’s (1980) theory of emotion. According to this account, situational cues elicit particular images that elicit a corresponding emotion and behavior. For example, in the case of the weapons effect, a weapon might elicit images of violence and thereby arouse negative affect resulting in aggression. Through a quantitativereview of published research on the weapons effect, Carlson et al. (1990) ruled out both the emotion and discriminative-stimuli interpretations in favor of a cognitive processes account. However, they admit that their conclusions are based on “soft ground” and encourage researchers to examine through experimentation the cognitive processes involved in such situational cue effects. This article examines the cognitive responses elicited in the presence of a very different situational cue: a computer. By being associated with information access, computers are argued to elicit a need for understanding, which in turn should influence how much information people in computer environments consider and seek. Indeed, there is some indication that computer environments cause people to focus on information rather than emotions: Individuals provide more informational than emotional support to others when communicating via the Internet than offline (Kiesler & Kraut, 1999). In addition, computer contexts have been argued to increase task absorption (Kiesler, Siegel, & McGuire, 1984; Kiesler & Sproull, 1992). Past research has indicated that, in comparison to face-to-face groups, those in computer-mediated groups generate a greater number of ideas (Dennis & Valacich, 1993) as well as recognize and integrate diverse perspectives (Cummings, Schlosser, & Arrow, 1996). There are several possible explanationsfor such effects, including a reduction in production blocking and more equal participation among members in computer-mediated groups (Kiesler, Siegel, & McGuire, 1984; Kiesler & Sproull, 1992). However, such performance enhancements may also be due to a heightened need for meaning when in computer contexts. Prior research provides some support for this: During the early weeks of working together, those working individually on computers while anticipating a computer-mediated discussion recognized and integrated more diverse perspectives
than did those working individuallyon paper while anticipating a face-to-face discussion (Cummings, Schlosser, & Arrow, 1996). If computers, by being associated with information access, heighten needs for understanding, then consumers in computer contexts may seek more information as well as think more about the product than they might ordinarily do. Such a heightened need coupled with the content richness capabilities of the Internet may lead consumers to seek and process more product information than they would in an offline context. Situational and Object Variations in Attitude Functions The functional theory of attitudes provides a theoretical framework within which situational effects on cognitive responses and evaluations can be predicted and interpreted. The functional theory of attitudes is unique to other attitudinal theories in that it addresses why people hold attitudes (Eagly & Chaiken, 1993). According to this theory, it is necessary to ascertain the motivational underpinnings of attitudes to identify and predict attitude change (Katz, 1960; Smith, Bruner, & White, 1956). Multiple motivational bases (or functions) of attitudes have been identified (cf. Insko, 1967, for a description of the typologies). Among the identified functions are the knowledge, utilitarian and social identity functions. The knowledge function serves to provide perceptual and cognitive structure to ones world, along the lines of Gestalt psychology (Katz, 1960). It involves a need for understanding and a search for meaning. Although all attitudes likely serve this knowledge function to some extent, the degree to which this function is heightened can vary across situations (Shavitt, 1989). The utilitarian function serves to maximize rewards and minimize punishments inherent in the object. The social identity function serves such identity goals as self-expression and aligning oneself with desirable others. The utilitarian and social identity functions have emerged in past research as the primary ones underlying product judgments (Lutz, 1981; Shavitt, 1990). Although original functional theorists assumed attitude functions to be relatively stable, recent functional theorists argue that attitude functions can vary across attitude objects and situations (Herek, 1986; Shavitt, 1989). More specifically, it is argued that attitude objects may serve a single or multiple purposes. For objects serving multiple purposes, the salient purpose can vary as a function of the situation. Take for example a university sweatshirt, which can serve such utilitarian functions as comfort and warmth and such social identity functions as displaying one’s affiliation with and support for the university. The utilitarian function is likely more salient than the social identity function when a student is considering wearing the sweatshirt for studying in his/her dorm room than attending a university football game. Be-
COMPUTERS AS SITUATIONAL CUES
cause attitude functions can vary across different situations and objects, a single message can vary in its persuasiveness and in the thoughts it evokes. That is, functional theorists propose that the saliency of thoughts and the persuasiveness of messages are influenced by their relevancy to the function elicited by the situation and/or attitude object. There exists some evidence that situational characteristics can make certain functions more or less salient. For instance, research suggests that object uncertainty coupled with expectations of further questioning about the object elicits the knowledge function (Fazio, Lenn, & Effrein, 1983; Jamieson & Zanna, 1989). Moreover, research has demonstrated that contextual factors can briefly heighten the salience of particular object features, thereby influencing evaluations of these objects (Shavitt & Fazio, 1991). That is, it appears that priming social identity or utilitarian concerns can influence perceptions of products subsequently evaluated. For instance, when the social identity function is primed by the context, subsequently presented products are evaluated more in terms of their social identity than utilitarian attributes. If, by being associated with information access, the mere presence of a computer elicits the knowledge function, then one might expect that individuals would think more about and evaluate more holistically products encountered within this situation. As a result, those in computer contexts may think about and request relatively more social identity and utilitarian attributes than when a computer is absent. Their attitudes should thus reflect this greater thinking about both attributes. In the absence of a computer, people’s attitudes should reflect the valence of the attributes relevant to the product’s primary purpose. Experimental Design and Hypotheses To examine whether the mere presence of a computer influences how people think about and thus judge products, the experimental design was a 2 (context: computer vs. print) × 2 (product type, a within–subjects factor: fast-food restaurant vs. sports car) × 2 (product order: evaluated the car vs. restaurant first) factorial. Everyone read two advertisements, which described the social identity and utilitarian attributes of the product. One of the advertisements was for a product typically evaluated more for its social identity attributes such as image and status (a sports car), and the other was for a product typically evaluated more for its utilitarian attributes such as quality and efficiency (a fast-food restaurant). Product type was manipulated to test the expectation that when a computer is present, people will evaluate the product more holistically rather than based only on the functionally most relevant dimension. When a computer is absent, people’s attitudes should reflect the valence of the attributes typically used to evaluate such products. The order in which these products were evaluated was counterbalanced. Furthermore, half of the participants were in a computer lab and anticipated evaluating the products further while online (a com-
105
puter context), whereas the other half were in a classroom without a computer and anticipated evaluating the product further on paper (hereafter referred to as the print context). Before further evaluating the product either via computers or on paper, all participants completed a series of paper-and-pencil questionnaires, the only difference being whether a computer was present or absent. Among the paper-and-pencil questionnaires was a cognitive response form to assess whether the situational cue of computers influences cognitive responses. Such thought-listing techniques have captured the salience of motives elicited by different product types (Shavitt, 1990) and situations (Schlosser & Shavitt, 1999). Additional measures were included to assess whether the presence of a computer also influences the type of product information sought as well as product attitudes. Information acquisition, as defined here, is the amount of additional information sought beyond what is already known. Information acquisition is one assessment of the depth of people’s information processing (Rudd & Kohout, 1983). If the presence of a computer increases concerns with being informed about the product, then people may seek more information overall when a computer is present than absent. Thus, the first empirical hypothesis for these cognitive dependent variables is H1: When a computer is present, individuals will list more thoughts and seek more information than when a computer is absent. If computer contexts heighten the knowledge function (and thus a need for a more organized and well-defined knowledge structure), then the attitudes of those in computer contexts should reflect the valences of all of the product dimensions described in the advertisement. In contrast, in the print context, individuals’attitudes should reflect the valence of the product information most relevant to the product’s primary function. Thus, the second empirical hypothesis is H2: When a computer is present, individuals’ attitudes should reflect both the utilitarian and social identity attributes described in the advertisement. When a computer is absent, individuals’ product attitudes should reflect the valence of the social identity attributes for the social-based product (the sports car) and the utilitarian attributes for the utilitarian-basedproduct (the fast-food restaurant). METHOD Participants One hundred forty three undergraduate students participated in partial fulfillment of an introductory course requirement. Participants were randomly assigned to either a computer or print context and to evaluate either the sports
106
SCHLOSSER
car or fast food restaurant first. Each condition had 33–38 participants. Materials The products under evaluation were a fictitious sports car and a fictitious fast food restaurant. Although cars and restaurants in general are multiple-functioned objects, it appears that certain car models and restaurant types can serve one function more than another. For instance, using adaptations of the questionnaire used by Shavitt (1990) to classify the functions of objects, past research has indicated that sports cars serve more of a social identity function than compact cars do (Ennis & Zanna, 1993). It is expected that sports cars are evaluated relatively more on the basis of their social identity than utilitarian attributes, whereas the reverse would be true for fast food restaurants. To test this assumption, a pretest was conducted, during which ten undergraduate students taking an introductory course were asked to “write down all of your thoughts and feelings that are relevant to your attitude, and try to describe the reasons for your feelings” toward sports cars and fast food restaurants (Shavitt, 1990). The results indicated that, as predicted, sports cars elicited more social identity attributes than fast food restaurants did, Ms = 2.50 versus .10, t(8) = 6, p < .001. Furthermore, sports cars elicited fewer utilitarian attributes than fast food restaurants did, Ms = 1.50 versus 4.30, t(8) = –6, p < .001. This confirms the assumption that these multiple-functioned products are evaluated either more or less on the basis of their social identity than utilitarian attributes. Each product was described in two paragraphs with the first paragraph containing utilitarian information (e.g., its performance features) and the second paragraph containing social identity information (e.g., its appearance). The order of the paragraphs was held constant because previous research has shown that the order of social identity and utilitarian information in a product description had negligible effects on product responding (Schlosser & Shavitt, 1999). The paragraphs were favorable in tone. However, the utilitarian paragraphs for both products were more favorable than the social identity paragraphs. This difference in valences allows for tracking the influence of each type of information on the attitudes reported. That is, reported attitudes should be higher if the more favorable utilitarian information has a stronger influence on attitudes than the less favorable social identity information does. Hence, if being in a computer context leads to a focus on both the social identity and utilitarian information, then they should have higher attitudes than those in the print context would when the product is typically evaluated in terms of its social identity features. To test the predicted valence of the social identity and utilitarian paragraphs, the same participants described for the pretest examining product function also rated the favorability of the social identity and utilitarian sentences describing the sports car and the fast food restaurant, using
a scale ranging from –2 (unfavorable) to +2 (very favorable). For both products, the utilitarian information was rated more favorably than the social identity information, Ms = .88 versus .22 for fast food restaurants, t(8) = 2.49, p < .05; Ms = 1.16 versus .53 for sports cars, t(8) = 3.02, p < .05. Furthermore, the favorability ratings of the utilitarian and social identity descriptions were similar across products, t(8)s < 2.07, ns. Participants in the main study listed their thoughts about the described products using thought-listing forms (Cacioppo & Petty, 1981). These forms contain eight boxes in which thoughts and feelings about the product are listed. After listing their thoughts about the focal product, participants rated their thoughts on a 5-point scale ranging from –2 (very unfavorable) to +2 (very favorable). To assess how communicationmedium might affect information seeking, participants were asked to select additional items of information that they would like to know about the product. For each product, participants could choose from three utilitarian items (e.g., performance in government crash tests for the sports car, nutrients of food items for the fast food restaurant) and three social identity items (e.g., the appearance of a sports car’s interior, the decor of a fast food restaurant). These items were chosen based on the results of a pretest, during which the same pretest participants described earlier rated the degree to which each of 12 product features (six social identity and six utilitarian features for each product) told them about the products quality (“how well the car performs”) and the products image (“the impression the car makes”) on a 5-point scale ranging from 1 (not at all) to 5 (a great deal). Three social identity and three utilitarian features for each product were selected on the basis of whether their average scores were above the neutral point (3) on the function-relevant item and near or below the neutral point on the function-irrelevant item. For instance, a utilitarian feature was selected if it was rated as being somewhat informative of product quality and not of product image. For sports cars, the three utilitarian features were more informative about product quality than product image, Ms = 3.97 versus 2.80, t(8) = 2.98, p < .05, and the three social identity features were less informative about product quality than product image, Ms = 2.40 versus 4.17, t(8) = –5.55, p < .01. Similarly, for fast food restaurants, the three utilitarian features were more informative about product quality than product image, Ms = 4.27 versus 3.67, t(8) = 2.21, p = .05, and the three social identity features were less informative about product quality than product image, Ms = 2.23 versus 3.83, t(8) = –5.04, p < .01. Procedure On arrival, participants were either seated in a classroom with individual desks (the print context) or in a computer lab (the computer context). Those in the computer context began by sitting in front of a computer with the monitor turned off. Everyone first received written instructions regarding the
COMPUTERS AS SITUATIONAL CUES
purpose of the study. This included information about the first product under investigation as well as an approaching essay-writing task about this product. Forming judgments of new products, especially in light of writing an essay about them, likely elicited the knowledge function for everyone. Nevertheless, the salience of this function was anticipated to be even greater in the computer than print context. All participants then read a description of a fast food restaurant or a sports car. After reading the description, it was collected. Participants then listed their thoughts toward the product, rated the favorability of their thoughts toward the product, and reported their attitudes. The attitude measure included three 9-point semantic differentials anchored with good–bad, like–dislike, and desirable–undesirable. For each participant, their product attitudes were calculated by averaging their responses to these three items, a = .94 for the first product evaluated and a = .89 for the second product evaluated. After reporting their attitudes, participants selected from a list of six items the additional information they would like to have about the product. On completion of these paper-and-pencil questionnaires, participants were asked to write an essay regarding their thoughts and feelings toward the product for 5 min. In the computer context, the monitors were turned on, and participants typed their essay using Microsoft Word. After 5 min elapsed, those in the computer context turned off their monitor, while those in the print context put their essay away in a folder. Participants then began reading about the second product. All of the materials and procedures for the second product were identical to the first. At the end of the experiment, participants completed a questionnaire assessing evaluation apprehension (e.g., “How at ease were you when sharing your thoughts and feelings about the products?”), stimulation (“How motivated were you to evaluate the products?”), and time pressure (e.g., “When evaluating the products, did you have as much time as you needed?”). This questionnaire was an adaptation of one used in prior research to measure affective responses in computer contexts (Dennis & Valacich, 1993) Coding Two judges independentlycoded the function of each item of the thought-listingmeasure accordingto Shavitt’s (1990) coding manual.These items were coded as social identity,utilitarian, multiple-functioned or uncodable. A social identity item captures the image and impression the product makes on others (e.g., its status, the type of customers attracted). Examples include “sleek, sophisticated—sounded young and hip” and “casual atmosphere.” A utilitarian item captures the quality and intrinsic rewards and punishments of the product (e.g., its performance features). Examples include “safety factors are important” and “fast and efficient.” A multiple-functioned item taps both the social identity and utilitarian function. An example would be “attractive while affordable.” An item that
107
does not say anything about the function of the product is judged uncodable (e.g., “it sounded good”). The judges were blind to the experimental conditions.Because this experiment was part of a larger study, the judges coded thoughts that were gathered for this experiment along with the others. Across these experiments, they independently coded 3,468 thoughts and had 89% agreement. A third judge resolved disagreements. The number of social identity and utilitarian thoughts were then tabulated for each participant. Two judgesalso independentlycoded the essays by coding each statement as either social identity, utilitarian, or uncodable. A codable statement was defined as any item that, by itself, could be coded into one of the four categories. This could be a sentence. However, a single sentence could contain multiple codable items. For instance, “it seems fast, but at the same time safe” contains two codable items (those underlined). Statements not pertaining to the focal products were judged uncodable. The judges coded 5,318 items with 82% agreement.Disagreementswere resolvedthroughdiscussion. RESULTS Cognitive Responses and Information Seeking According to H1, if computer contexts heighten the knowledge function, then when asked to list their thoughts about the product, those in a computer context should list more thoughts than those in a print context would. The number and type of thoughts listed were analyzed with a 2 (context: computer vs. print) × 2 (product order: evaluating the car first vs. restaurant first) × 2 (product type, a within–subject factor: fast food restaurant vs. sports car) × 2 (thought type, a within–subject factor: social vs. utilitarian) repeated measures analysis of variance. Although not statistically significant, the findings are directionally consistent with the predictions: those in the computer context listed slightly more thoughts than those in the print context did, Ms = 5.03 versus 4.67; F(1, 121) = 2.50, p = .058 one-tailed, see Figure 1. This difference was somewhat greater for the sports car than fast food restaurant, although the Context × Product Type interaction was nonsignificant, F(1, 121) < 1. Furthermore, context did not interact with thought type and/or order, all F(1, 121)s < 1.07, ns, thereby indicating that regardless of which product was evaluated first, participants in the computer context listed similar types of thoughts as those in the print context did. In terms of the type of thoughts listed, one might expect that the number of social identity thoughts relative to utilitarian thoughts would be greater for the sports car than fast food restaurant. Overall, however, participantslisted more utilitarian than social identity thoughts for both products, Ms = 3.09 versus 1.75, F(1, 121) = 10.95, p < .01, although this effect was moderated by both product type and the order in which products were evaluated, F(1, 121) = 5.92, p < .05. When the sports car was evaluated first, the utilitarian information
108
SCHLOSSER
FIGURE 1 listed.
Effect of computer contexts on the number of thoughts
dominated thoughts about both products, Ms = 3.18 versus 1.91, F(1, 59) = 37.41, p < .01. However, the difference between the number of utilitarian and social identity thoughts listed was greater for sports cars than fast food restaurants when the restaurant was evaluated first, Ms = 3.38 versus 1.30 for sports cars and Ms = 2.61 versus 1.88 for fast food restaurants, F(1, 62) = 15.50, p < .05. It is possible that evaluating a utilitarian-basedproduct first primed utilitarian thinking, thereby heightening utilitarian thinking about the subsequently evaluated sports car. Perhaps more surprising is that utilitarian thinking dominated product thoughts, especially for the sports car, Ms = 3.62 vs. 1.54 for the sports car and Ms = 2.91 versus 1.96 for the fast food restaurant, F(1, 121) = 10.95, p < .01 for the Product Type × Thought Type interaction. Prior research has indicated that individuals will often refer more to the functionally incongruent attributes than the functionally congruent attributes when listing their product thoughts in an attempt to be unique and/or to avoid belaboring the obvious (Schlosser & Shavitt, 2002). This prior research has also demonstrated that these thoughts are not necessarily reflective of product attitudes. Specifically, for individuals responding privately, their attitudes reflected the valence of the functionally relevant information rather than the attributes dominating their listed thoughts. Thus, even though the utilitarian information dominated peoples listed thoughts for both products, it is still likely that those in the print context will base their attitudes on the functionally relevant information, whereas those in the computer context will base their attitudes on both the social identity and utilitarian information. According to H1, computer contexts should also heighten information acquisition. To assess this, the number of social and utilitarian items sought were analyzed with a 2 (context) × 2 (product order) × 2 (product type) × 2 (information type,
a within-subjects factor: social versus utilitarian) repeated measures analysis of variance. Supporting H1, the results indicated that, regardless of product and information type, those in the computer context requested more product information than those in the print context did, M = 3.25 versus 2.93, F(1, 139) = 3.92, p = .05; see Figure 2. Although this difference between contexts is greater for sports cars than fast food restaurants, a Product type × Context interaction was not significant, F(1, 139) = 1.91, p = .17. Instead a main effect of product type was significant, F(1, 139) = 32.30, p < .01: Across contexts, participants sought more information about the sports car than the fast food restaurant, Ms = 3.43 versus 2.74. This is likely because cars in general are high-investment, high-involvement and information-rich products. As with listed thoughts, all participants sought more utilitarian than social identity attributes, Ms = 1.82 versus 1.28, F(1, 139) = 35.96, p < .01. The thoughts listed and the information sought was assessed with paper-and-pencil questionnaires that participants filled out while either in the presence of a computer or not. One might expect that the effect of a situational cue (computers) on cognitive elaboration would be greater if one were actually interacting with the cue. For the essay-writing task, those in the computer context wrote the essay by using the computer, whereas those in the print context wrote the essay on paper. The number and type of attributes mentioned in the essay were analyzed with a 2 (context) × 2 (product order) × 2 (product type) × 2 (type of attribute, a within-subjects factor: social vs. utilitarian) repeated measures analysis of variance. As expected and consistent with the reasoning underlying H1, those in the computer context mentioned more attributes overall than those in the print context did, Ms = 8.77 versus 6.75, F(1, 139) = 18.75, p < .01. Furthermore, this effect was moderated by attribute type, F(1, 139) =
FIGURE 2 Effect of computer contexts on the amount of information sought.
COMPUTERS AS SITUATIONAL CUES
109
Product Attitudes
FIGURE 3
Effect of computer contexts on essay content.
7.03, p < .01, see Figure 3. Those in the computer context listed significantly more utilitarian attributes in their essays than those in the print context did, Ms = 5.97 vs. 4.41, F(1, 139) = 18.57, p < .01. Although those in the computer context also listed more social attributes than those in the print context did, this difference was nonsignificant, Ms = 2.81 versus 2.46, F(1, 139) = 1.75, p = .19. Perhaps the effect of a computer context on elaboration was greater for the utilitarian than the social identity dimension because the utilitarian dimension may be more closely related to the knowledge function. Indeed, some functional theorists do not distinguish between the knowledge function and the utilitarian function and instead refer to them collectively as object appraisal (Smith, Bruner & White, 1956). Object appraisal captures the cognitive function of “reality testing.” The individual is motivated to categorize and understand objects to respond to the environment in a way that maximizes rewards while minimizing punishments. Perhaps interacting with the computer heightened peoples need for understanding, which may ultimately lead to a concentration on the objective, concrete (i.e., utilitarian) attributes than the self-expressive (i.e., social) attributes
Recall that the product advertisements contained more favorable information about the product’s utilitarian attributes than its social identity attributes. To examine the effectiveness of this valence manipulation in the advertisements, participants’ self-ratings of the favorability of their own social identity and utilitarian thoughtswere examined. For those who listed both social and utilitarianthoughts,the average favorabilityof each type of thought was examined with a 2 (context) × 2 (product order) × 2 (product type) × 2 (thought type, a within-subject factor: social vs. utilitarian) repeated measures analysis of variance, which yielded a significant thought type effect, F(1, 95) = 6.61,p < .05. Confirmingthe valencemanipulationin the advertisements, people’s utilitarian thoughtswere rated more favorably than their social identity thoughts, Ms = .90 versus .67. None of the interactions involving thought type were significant, F(1, 95) < 1.99, ns. For those in the print context, attitudes should reflect the valence of the functionally relevant information. Specifically, for the product that is evaluated more on its utilitarian than social identity attributes (e.g., the fast food restaurant), their product attitudes should be more favorable than when the product is evaluated more on its social identity than utilitarian attributes (e.g., the sports car). For those in the computer context, their attitudes should reflect increased thinking. Prior research has demonstrated that the impact of increased thinking on attitudes depends on the number of dimensions considered and whether the dimensions elaborated on are orthogonal or correlated (Judd & Lusk, 1984). When the dimensions are interrcorrelated, then increased thinking leads to more extreme evaluative judgments. In this experiment, the number, of dimensions were the same across conditions: The advertisements for both products promoted the utilitarian and social identity dimensions. Because both dimensions differed only in the degree to which they were favorable, it was expected that they would be interrcorrelated. To examine whether participants’ perceptions of the dimensions were correlated, the average favorability of their social identity and utilitarian thoughts were compared. For both the sports car and fast food restaurant, participants’ average favorability ratings of their own social identity and utilitarian thoughts were positively correlated, rs = .42 and .35, respectively. Thus, if computer contexts increase thinking about these dimensions, then those in computer contexts should hold more favorable product attitudes than those in print contexts would. This may especially be the case for the sports car, for which those in the print condition will likely evaluate the product more on the basis of its less favorable (social identity) than more favorable (utilitarian) attributes. A 2 (context) × 2 (product order) × 2 (product type) repeated measures analysis of variance was conducted to examine the influence of these factors on attitudes. Supporting the notion that increased thinking about intercorrelated dimen-
110
SCHLOSSER
sions should lead to more extreme attitudes, a significantcontext main effect emerged, F(1, 138) = 2.90, p < .05 one-tailed. Overall, those in the computer context held more favorable product attitudes than those in the print context did, Ms = 2.12 versus 1.75. This effect was moderated by product type, however, F(1, 138) = 5.75, p < .05; see Figure 4. Consistent with H2, those in the print context appeared to base their attitudes primarily on the functionally relevant dimension: it appears that they based their attitudes toward the utilitarian-based product (a fast-food restaurant) on the favorable utilitarian information and based their attitudes toward the social-based product (a sports car) on the less favorable social identity information. Consequently, their attitudes toward the sports car were significantlyless favorablethan theirattitudestoward the fast-food restaurant,Ms = 1.39 versus 2.11,F(1, 74) = 7.85,p < .01. In the computer condition,consistent with the notion that they would take both related dimensions into account when forming their product judgments (H2), participants’attitudes were similarly favorable for both products, F(1, 64) < 1, Ms = 2.19 versus 2.05 for the sports car and fast-food restaurant, respectively. Although those in the computer context held more extreme attitudes toward the sports car than those in the print context did, F(1, 140) = 7.32, p < .01, those in the computer context held similar attitudes toward the fast-food restaurant as those in the print context did, F(1, 141) < 1. Their attitudes are likely similar because those in the print context focused primarily on the more favorable (utilitarian) than less favorable (social identity) attributes when evaluating the fast-food restaurant, whereas those in the computer context elaborated on both. Emotion One alternateexplanationfor theeffects ofcontexton attitudes and cognitions is that the mere presence of a computer may
elicit different emotions compared to the print context. Because this population (undergraduate students) likely uses computers—especially in a computer lab setting—to complete course assignments that have some impending deadline, being in such a context might elicit feelings of evaluation apprehension, motivation or a sense of urgency. To test this, the effect of contexton all three emotionswere examined.Evaluation apprehensionwas measuredby averagingparticipants’responses to two items: how easy it was to share their product thoughts and feeling and how apprehensive they were about sharing their product thoughtsand feelings, a = .72. A 2 (context)× 2 (productorder) ANOVA yieldedno significanteffects or interactions. Those in the computer and print contexts reported similar levels of apprehension,F(1, 139) < 1, Ms = 6.18 versus 6.16 on a scale where 7 indicates feeling no apprehension. Thus, the contextresults reported earlier cannotbe due to differences in evaluation apprehension Motivation was measured with the single item, “How motivated were you to evaluate the products?” and was also analyzed with a 2 (context) × 2 (product order) ANOVA. Although those in the computer context were somewhat more motivated than those in the print context were, Ms = 4.39 versus 4.01, this effect was nonsignificant, F(1, 139) = 2.22, p = .14. This nonsignificant difference indicates that motivation cannot account for the effect of context on the cognitive and attitudinal variables. Time pressure was measured by averaging responses to two items assessing participants’ feelings of needing more time and not having enough time to express all of their product thoughts, a = .88. A 2 (context) × 2 (product order) ANOVA yielded a significant context main effect, F(1, 139) = 12.30, p < .01. Those in the computer context reported feeling more pressed for time than those in the print context did, Ms = 3.13 versus 2.21. Time pressure, however, was uncorrelated with attitudes toward sports cars (r = .05) as well as the cognitive response variables (r = .12 for the number of thoughts listed, r = .06 for the amount of information sought and r = .14 for the number of attributes mentioned in the essay) and therefore cannot account for the effect of context on these variables. DISCUSSION
FIGURE 4
Effect of computer contexts on attitudes.
The primary objective of this article is to examine whether a computer context influences how people think about and judge products. It is argued that computers, by being associated with information access, would heighten the knowledge function, or a need for understanding. A number of findings suggest that the mere presence of a computer elicits such knowledge concerns: compared to those in a print context, those in the computer context (a) listed somewhat more thoughts, (b) sought more information, and (c) mentioned more attributes (especially utilitarian attributes) when writing an essay about the product.
COMPUTERS AS SITUATIONAL CUES
The attitudinal implication of constructing such well-developed knowledge structures (when the dimensions of the knowledge structure are intercorrelated) is judgmental extremity (Judd & Lusk, 1984). Thus when, a product’s dimensions are intercorrelated, one would expect that those in computercontextswould holdmore extreme attitudesthan those in print contexts would. This expectation was supported, with those in the computercontextholdingmore favorableattitudes thanthosein the printcontextdid.However, producttypemoderated thiseffect. This is likely because the degree to which the judgment is extreme depends on how intercorrelated the dimensions are (Judd & Lusk, 1984). In the present experiment, the dimensions were moderately correlated: Both the social identity and utilitarian information were favorable. Furthermore, the social identity information was less favorable than the utilitarianinformation. Consequently,it was expected and the results indicate that a focus on the social identity dimension resulted in less favorable attitudes (print context/social-based product) than a focus on the utilitarian dimension (print context/utilitarian-based product) or both dimensions did (computer context). In contrast, a focus on the utilitarian dimension(printcontext/utilitarian-basedproduct)resultedin attitudesthatwere as favorable as attitudesformed from elaboration on both dimensions (computer context). Theoretical and Applied Implications Consistent with prior research on the weapons effect that indicates that situational cues are due to cognitive rather than affective factors (Carlson et al., 1990), the present findings suggest that the significant impact of context on cognitions and attitudes cannot be explained by such affective variables as evaluation apprehension, motivation or time pressure. This research also builds on prior research by demonstrating such an effect with a different situational cue and an experiment designed to directly test the effect of a situational cue on the cognitive processes involved. By heightening tendencies for better cognitive understanding, it is possible that placing some traditional advertisements (e.g., informationally sparse, hedonic or soft sell ads) in a computer environment could be ineffective if not accompanied by (or linked to) more detailed product specifications. Indeed, the site of a popular athletic shoe received negative feedback because it contained soft-sell and little hard-sell product information. One visitor to their site posted the following message: “Nice site … cute graphics … Maybe when you folks get tired of congratulating yourselves on how cool you are you might want to get around to actually HELPING some of your customers (and potential customers) with some useful information about [your] products … here’s a suggestion: how about a product guide????” This message stresses the importance for businesses to recognize that consumers will likely respond differently to product information that is delivered via computers versus “traditional” media such as print. Whereas Olympian endorsements of
111
shoes may be appropriate and sufficient in a traditional ad, in a computer environment, consumers may require more in-depth product information. Because consumers appear to evaluate the product more thoroughly,by seeking more information as well as thinking more about the product in computer environments, Web sites should meet such needs by containing rich product information, including a compilation of frequently asked questions and comparison charts. The inclusion of navigational tools that facilitate such heightened information seeking (e.g., a search engine, site map) may be invaluable in satisfying customer needs in cyberspace. Many guides to conducting research via the Internet list such limitations as sample quality, participant fraud, and stimuli and technique limitations (cf. Miller, 2001; Taylor, 2000). This article suggests an additionalcaution: consumers may respond differently to product information via computers than through other survey techniques such as mail surveys. If the product dimensions are interrcorrelated, computer environments can lead to attitudes that are more extreme than those reported offline. For instance, a social-related product with a good performance record but a modest image may receive overly favorable ratings via computer surveys but less favorable reactions offline. Thus, Internet advertisers and researchers should recognize that, although the Internet provides a unique opportunity to gather data quickly and inexpensively as well as to study consumers in a naturalistic environment, the Internet as a research medium is likely best reserved for studying responses to products and ads that will be encountered in a computer context.
ACKNOWLEDGMENTS I thank Carrie Joniak, Pamela Lowrey, Michelle Nelson, Chris Riegel and Heather Schlosser for assistance with data collection and coding, and to Dawn Iacobucci for her helpful suggestions.
REFERENCES Berkowitz, Leonard. (1974). Some determinants of impulsive aggression: Role of mediated associations with reinforcements for aggression. Psychological Review, 81, 165–176. Berkowitz, Leonard. (1982). Aversive conditions as stimuli to aggression. In L. Berkowitz (Ed.), Advances in experimental social psychology (pp. 249–285). Orlando, FL: Academic Press. Berkowitz, Leonard. (1983). The experience of anger as a parallel process in the display of impulsive, angry aggression. In R. Geen & E. I. Donnerstein (Eds.), Aggression: Theoretical and empirical reviews (pp. 103–133). Orlando, FL: Academic Press. Berkowitz, Leonard, & LePage, Anthony. (1967). Weapons as aggression-eliciting stimuli. Journal of Personality and Social Psychology, 7, 202–207. Cacioppo, John T., & Petty, Richard E. (1981). Social-psychological procedures for cognitive response assessment: The thought listing technique. In
112
SCHLOSSER
Thomas Merluzzi, Carol Glass, and Myles Genest (Eds.), Cognitive Assessment, New York, NY: Guilford. Carlson, Michael, Marcus-Newhall, Amy, & Miller, Norman. (1990). Effects of situational aggression cues: A quantitative review. Journal of Personality and Social Psychology, 58, 622–633. Cummings, Anne, Schlosser, Ann, & Arrow, Holly. (1996). Developing complex group products: Idea combination in computer-mediated and face-to-face groups. Computer Supported Cooperative Work, 4 (2–3), 229–251. Dennis, Alan R., & Valacich, Joseph S. (1993). Computer brainstorms: More headsare betterthan one.Journalof Applied Psychology, 78(4),531–537. Eagly, Alice H., & Chaiken, Shelley (1993). The Psychology of Attitudes. Orlando, FL: Harcourt Brace Jovanovich College Publishers. Ennis, Richard, & Zanna, Mark P. (1993). Attitudes, advertising, and automobiles: A functional approach. Advances in Consumer Research, 20, 662–666. Fazio, Russell, Lenn, Tracy M. & Effrein, Edwin A. (1983). Spontaneous attitude formation. Social Cognition, 2(3), 217–234. Feinberg, Richard A. (1986). Credit cards as spending facilitating stimuli: A conditioninginterpretation. Journal of Consumer Research, 13, 348–356. GVU (1998), GVUs 10th WWW User Survey, [http://www.gvu.gatech.edu/user _surveys/survey-1998-10/]. Herek, Gregory M. (1986). The instrumentality of attitudes: Toward a neofunctional theory. Journal of Social Issues, 42, 99–114. Insko, Chester A., (1967), Theories of Attitude Change, New York: Appleton-Century-Crofts. Jamieson, David W., & Zanna, Mark P. (1989). Need for structure in attitude formation and expression. In Anthony R. Pratkanis, Steven J. Breckler, & Greenwald, Anthony G. (Eds.), Attitude structure and function (pp. 383–406). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. Judd, Charles M., & Lusk, Cynthia M. (1984). Knowledge structures and evaluative judgments: Effects of structural variables on judgmental extremity. Journal of Personality and Social Psychology, 46, 1193–1207. Katz, Daniel. (1960). The functional approach to the study of attitudes. Public Opinion Quarterly, 24, 163–204. Kiesler, Sara, & Kraut, Robert. (1999). Internet use and ties that bind. American Psychologist, 54(9), 783–784 Kiesler, Sara, Siegel, Jane, & McGuire, Timothy M. (1984). Social psychological aspects of computer-mediated communication. American Psychologist, 39, 1123–1134. Kiesler, Sara, & Sproull, Lee. (1992). Group decision making and communication technology. Organizational Behavior and Human Decision Processes, 52, 96–123. Lawrence, Steve, & Giles, C. Lee. (1998). Searching the World Wide Web. Science, 280(5360), 98–100
Leventhal, H. (1980). Toward a comprehensive theory of emotion. In L. Berkowitz (Ed.) Advances in Experiemtal Social Psychology (Vol. 13, pp. 140–149). Orlando, FL: Academic Press. Lutz, Richard. J. (1981). A reconceptualization of the functional approach to attitudes. Research in Marketing, 5, 165–210. McCall, Michael, & Belmont, Heather J. (1996). Credit card insignia and restaurant tipping: Evidence for an associative link. Journal of Applied Psychology, 81(5), 609–613. Miller, Thomas (2001). Can we trust the data of online research? Marketing Research, 26–32. Rudd, Joel, & Kohout, Frank J. (1983). Individual and group consumer information acquisition in brand choice situations. Journal of Consumer Research, 10, 303–309. Scheier, Michael F., & Carver, Charles S. (1980). Private and public self-attention, resistance to change, and dissonance reduction. Journal of Personality & Social Psychology, 39(3), 390–405 Scheier, Michael F., Fenigstein, Allan, & Buss, Arnold H. (1974). Self-awareness and physical aggression. Journal of Experimental Social Psychology, 10(3), 264–273. Schlosser, Ann, & Shavitt, Sharon. (1999). Effects of an approaching group discussion on product responses. Journal of Consumer Psychology, 8(4), 377–406. Schlosser, Ann, & Shavitt, Sharon. (2002). Anticipated discussion and product judgments: Rehearsing what to say can affect your judgments. Journal of Consumer Research, 29, 101–115. Schwarz, Norbert, & Clore, Gerald. (1983). Mood, misattribution, and judgments of well-being: Informative and directive functions of affective states. Journal of Personality and Social Psychology, 45, 513–523. Shavitt, Sharon. (1989). Operationalizing functional theories of attitude. In A. R. Pratkanis, S. J. Breckler, and A. G. Greenwald (Eds.) Attitude Structure and Function (pp. 311–337). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. Shavitt, Sharon. (1990, March). The role of attitude objects in attitude functions. Journal of Experimental Social Psychology, 26, 124–148. Shavitt, Sharon, & Fazio, Russell H. (1991). Effects of attribute salience on the consistency between attitudes and behavior predictions. Personality and Social Psychology Bulletin, 17, 507–516. Siegel, Jane, Dubrovsky, Vitaly, Kiesler, Sara, & McGuire, Timothy W. (1986, April). Group processes in computer-mediated communication. Organizational Behavior and Human Decision Processes, 37, 157–187. Smith, Marilynn, Brewster, Bruner, Jerome S., & White, Robert W. (1956). Opinions and personality. New York: Wiley. Taylor, Humphrey. (2000). Does Internet Research Work? The Market Research Society, 51–63.
Accepted by Dawn Iacobucci.
