A Proposed Model of External Consumer Information Search

RESEARCH NOTES

A Proposed Model of External Consumer Information Search

Jeffrey B. Schmidt Kansas State University

Richard A. Sprang Michigan State University

An enduring interest in consumer behavior is the investigation of external prepurchase information search. Past research has identified a large number offactors that have been found to influence the extent of information search. The purposes of this article are to summarize the external information search literature and then develop a more parsimonious model of information search. Specifically, we propose that the effects of these antecedents of information search are mediated by four variables: ability, motivation, costs, and benefits. This model integrates the psychological search literature by incorporating ability and motivation to search for information and the economic paradigm that centers on the perceived costs and benefits of information search. Propositions are developed based on this comprehensive model for future testing.

Nearly every introductory marketing and consumer behavior textbook depicts the consumer purchase decision process as a series of steps progressing from problem recognition, to information search, to evaluation of alternatives, to purchase decision, and finally to postpurchase behavior. In the information search stage, consumers ac- tively collect information to make potentially better purchase decisions. It should be noted that consumers also acquire product-related information even when they are

Journal of the Academy of Marketing Science. Volume 24, No. 3, pages 246-256. Copyright �9 1996 by Academy of Marketing Science.

not planning to buy the product in the near term but rather sometime in the future. The information search process may be internal or external. Internal search occurs when consumers use information already stored in memory, whereas external search involves seeking information from the environment because the required information was not previously acquired or is unable to be recalled from memory.

In the dynamic global environment of today, understanding how consumers acquire information is important at the micro level for marketing management decisions and at the macro level for public policy decisions (Srinivasan 1990; Wilkie and Dickson 1985). For marketing managers, understanding information search determinants is crucial for designing effective marketing communication cam- paigns because "Information search represents the primary stage at which marketing can provide information and influence consumers' decisions" (Wilkie and Dickson 1985, p. 85). In our information-rich society, understanding how consumers seek and use information allows public policymakers to improve the quality and accessibility of information.

First, the consumer information search literature is re- viewed, and research propositions are developed. Second, these propositions are then used to develop an integrated model of external consumer information search. This model suggests that although many variables influence search, these effects are mediated by four factors. These factors are based on two well-established theoretical per- spectives of external information search: the psychological/ information processing approach and the economics perspective. The model proposed in this article is more comprehensive than previous models because it incorporates nearly 20 determinants of external information search.

Schmidt, Spreng / EXTERNAL INFORMATION SEARCH 247

However, it is also more parsimonious because it proposes that these variables influence search through four factors, thereby providing a simpler account of the factors that influence information search.

CONCEPTUAL FOUNDATIONS AND RESEARCH PROPOSITIONS

Consumer information search is one of the most enduring literature streams in consumer research (Beatty and Smith 1987). As a field of study, marketing has been interested in consumer prepurchase information seeking since at least 1917 (e.g., Copeland 1917), and even today most consumer information processing models include prepurchase information search as one of the key components (e.g., Bettman 1979; Bettman, Johnson, and Payne 1991; Engel, Blackwell, and Miniard 1993; Howard and Sheth 1969; Olshavsky 1985).

As Srinivasan and Ratchford (1991 ) note, past research in this area has focused on developing typologies of consumer information search strategies using nearly 60 variables that influence external information search. These typologies often include aspects of the environment (e.g., difficulty of the choice task, number of alternatives, complexity of the alternatives), situational variables (e.g., previous satisfaction, time constraints, perceived risk), and consumer characteristics (e.g., education, prior knowledge, involvement). Kiel and Layton (1981) conclude that "consumer information seeking behavior can be conceptu- alized as a series of interrelated behaviors" (p. 239). How- ever, there have been few attempts to model the interrelationships among these factors. Notable exceptions are Maute and Forrester (1991), Punj and Staelin (1983), and Srinivasan and Ratchford (1991). In these three studies, models of prepurchase information search were developed and then tested using structural equation modeling. The model that we propose attempts to expand these models by including more antecedents and provides a theoretically based set of four factors that mediate the effects of this large number of variables.

External Search

Our model is designed to describe the antecedents of external information search effort, which is defined as the degree of attention, perception, and effort directed toward obtaining environmental information associated with consumption-related objects, regardless of whether the consumption objects are related to a specific purchase under consideration. Beatty and Smith (1987) defined external search effort as "the degree of attention, perception, and effort directed toward obtaining environmental data or information related to the specific purchase under consideration" (p. 85). However, we believe information that is acquired but is not specifically related to an imminent purchase should be included in a more comprehensive model such as the one proposed here. This type of search has been called "ongoing search" (Bloch, Sherrell, and

Ridgway 1986, p. 120). Although prepurchase search and ongoing search are conceptually distinct, they "are difficult to separate in practice" (p. 120). Further, Bloch et al. argue that although the purposes of prepurchase and ongoing search may be different, the activities involved would be indistinguishable to an outside observer. Finally, Babin, Darden, and Griffin (1994) argue that some consumers engage in shopping behaviors for the hedonic value they receive rather than to achieve some specific prepurchase goal. Note that the object of the information acquisition must be a consumption-related object or service to distinguish the phenomena from other types of learning that are not related to consumption.

The sources of information that are used during external search can be classified into several types: marketer con- trolled (e.g., personal selling, advertising, product information on package, product brochures) , resel ler information (e.g., catalogs by reseller, information charts, consultants), third-party independent organizations (e.g,, Consumers Union, J. D. Powers, newspaper and magazine articles), interpersonal sources (e.g., friends, acquain- tances), and direct inspection (e.g., observation, inferenc- ing) (Olshavsky and Wymer 1995).

Many studies have developed measures of search activity (see Srinivasan 1990 for a review), but the difficulty of measuring search has been long acknowledged. For example, use of product testing information such as Consumer Reports often is viewed as extensive search. However, a consumer may be subcontracting the decision to the product testing organization, as when a consumer buys the most highly rated product (Rosen and Olshavsky 1987). What looks like (and would be measured as) extensive search is in fact a simplifying choice process that requires a single piece of information (the recommended brand) from a single source. Thus the development of measures of external information search will continue to be of high priority.

Antecedents of External Information Search

According to Srinivasan (1990), there are three major theoretical streams of consumer information search literature. The first is the psychological/motivational approach, which incorporates the individual, the product class, and task-related variables. The second is the economics approach, which uses the cost-benefit framework to study information search. The third is the consumer information processing approach, which focuses on memory and cognitive information processing limitations of humans. We believe that the psychological/motivational perspective subsumes information processing theory. That is, the psychological/motivational approach involves both motivation (which is what Srinivasan primarily discusses in his "Psychological Approach" section) and ability (which would fall into Srinivasan's "Information Processing" section). Therefore, only the psychological/motivational approach and the economics approach need to be integrated.

The proposed model, shown in Figure 1, shows the hypothesized signs of the path coefficients. Each sign represents one of the propositions to follow. In particular,

248 JOURNAL OF THE ACADEMY OF MARKETING SCIENCE SUMMER 1996

FIGURE 1

I PE CEIVEDF C SAC IOE I"k SE C.

'. CX ~ BENEFITS OF I /

t I \ /+

DESIRE FOR OP'ITMUM DECISION I\Z EVOKED SET SIZE . + + +

i ~'~------------------/i~~~ PERCEIVED ~ l END SH G PRODUCT COMPLEXITY P] OSTS F URING II NE OPPIN I

ability to search and motivation to search are expected to affect search activity positively. The perceived benefits of search are proposed to increase the motivation to search, whereas the perceived costs of search are proposed to reduce the motivation to search.

Bettman and Park (1980) theorized that information search depends on both one's ability and one's motivation. Either determinant without the other inhibits information search. The notion that both ability and motivation are required to process information is consistent with Bettman's (1979) model and with Petty and Cacioppo's (1986) Elaboration Likelihood Model (ELM). The ELM suggests that both the ability to process information and the motivation to process information are necessary before someone engages in effortful cognitive processing. Simi- larly, it is logical to posit that both motivation and ability are required to acquire information via effortful search.

The other two factors that determine information search come from the cost-benefit paradigm of economics (e.g., Bettman 1979; Stigler 1961; Urban, Hulland, and Wein- berg 1993). This paradigm rests on the assumption that consumers search for information until the marginal cost of obtaining a unit of information is equal to the marginal benefit of possessing a unit of information. Thus information search will decrease as the costs of searching increase and will increase as the benefits of search increase. The proposed model indicates that the perceived costs of search have a negative effect on motivation to search, whereas the perceived benefits of search have a positive effect on motivation to search. Thus the effects of perceived costs and perceived benefits of search are mediated by motivation to search. The following sections examine the antecedents of each of the four factors.

Ability to Search

The first category of consumer search determinants is one's ability to search. Perceived ability to search is defined as the perceived cognitive capability of searching for and processing information. Ability involves cognitive processing ability, knowledge of procedures for searching, and knowledge of sources of information (Brucks 1985; Maclnnis, Moorman, and Jaworski 1991). Bettman and Park (1980) proposed that ability to search increases search activity. Duncan and Olshavsky (1982) studied information search in television purchase situations and found that the perceived ability to judge products and brands led to increased information search. Moreover, Srinivasan (1987) found that consumer ability was positively related to information search.

PI: Greater perceived ability to search increases external information search activity.

There are three factors that determine one's perceived ability to search for information: educational level, objec- t ive product knowledge, and subject ive product knowledge.

Education level. The literature contains several studies that have used educational level as a determinant of information search. Kiel and Layton (1981) found that education correlated strongly with several measures of information search for automobile purchases. Udell (1966) similarly found that people with higher levels of education shopped for appliances at more stores than did people with lower levels of education. Although the results are not


identical across all of the past studies, the basic finding is that higher levels of education lead to increased search activity (Claxton, Fry, & Portis 1974; Hempel 1969; Katona and Mueller 1955; Schaninger and Sciglimpaglia 1981). Presumably, higher levels of education increase one's ability to identify, locate, and assimilate relevant information.

Pla: Higher levels of education increase one's ability to engage in external search for information.

Consumer knowledge. Whereas past research has often treated prior knowledge as a single construct, more recent research has maintained a distinction between objective knowledge (OK) and subjective knowledge (SK) (e.g., Brucks 1985; Park, Mothersbaugh, and Feick 1994; Spreng and Olshavsky 1990). Specifically, OK is concep- tualized as what a consumer actually knows, whereas SK is defined as the consumer's perception of the amount he or she knows about the product domain. Research generally has found that although these are highly related, they are distinct. First, the correlations between measures of OK and SK often are moderate. For example, Brucks (1985) found the correlation to be .54, and Spreng and Olshavsky (1990) found correlations ranging from .04 to .70 depending on how the SK question was measured.

Second, Park et al. (1994) showed that OK and SK had different antecedents in that product-related experiences were more strongly related to SK than to OK. They attribute this to the greater accessibility of product experiences, which increases the "feeling of knowing" something about the product domain. Finally, Brucks (1985) showed that OK and SK had different effects on information search. For example, Brucks found that OK increased the number of attributes examined, whereas SK had no effect. Con- versely, those high in SK tended to rely more on their own evaluations rather than dealer recommendations, whereas OK had no effect on the use of dealer evaluations. Conse- quently, we discuss each type of consumer knowledge separately.

Another operationalization of knowledge that has been used is product-related experience, although this has been criticized by some researchers (e.g., Brucks 1985; Spreng and Olshavsky 1990). In fact, Park et al. (1994) specified experience as a distinct construct that is antecedent to both SK and OK. They found that experience was distinct and had differential effects on the two types of knowledge in that experience was more strongly related to SK. There- fore, here we do not specify experience as a distinct antecedent of information search because we believe that product-related experiences will have their effect on information search indirectly, through SK and OK, as well as other proposed antecedents such as satisfaction with past purchases. Experience can work through OK when experience is diagnostic in that the consumer learns from observing product outcomes. For some products, it is difficult for the consumer to learn from product experience, in which case the consumer's OK level does not increase with

greater experience. Experience can also work through SK by giving consumers the feeling that they know about the product domain (Park et al. 1994).

Because a consumer's OK level represents what is actually stored in memory, OK is closely related to what Alba and Hutchinson (1987) called expertise or "the ability to perform product-related tasks" (p. 411). Brucks (1985) described the various aspects of OK as dealing with termi- nology, criteria for evaluating product attributes, perceived covariance among the attributes, and situational factors that determine the importance of various attributes. One effect of higher objective product knowledge is that the processing of new information should be easier, and therefore one's ability to search should be higher. Consumers with higher knowledge levels have well-developed knowledge structures and are able to comprehend and organize information more easily than are consumers with lower knowledge levels (Chase and Simon 1973). Miyake and Norman (1979) found that subjects with a low level of knowledge did not ask many questions about difficult material and concluded that this was because they recognized that they did not have the ability to understand the answers.

Plb: Higher levels of objective knowledge increase one's ability to engage in external search for information.

Subjective knowledge. SK often is described as including both knowledge and confidence in the adequacy of one's knowledge level (Brucks 1985), and research has shown that people's self-assessments of knowledge do not always match their actual knowledge levels (Schacter 1983). Park et al. (1994) found that SK is strongly related to a consumer's past experiences with a product domain and, according to Park and Lessig (1981), may be closely related to confidence. Thus high SK means that the consumer has confidence in his or her ability to perform product-related tasks including information search (Duncan and Olshavsky 1982). Urbany, Dickson, and Wilkie (1989) found that consumers with high knowledge uncertainty (i.e., low SK about the product) had lower levels of search even though their level of knowledge was low. One explanation for this result is that these subjects recognized that they did not have the ability to engage in search activities. Thus high SK should be associated with a greater perception of one's ability to search.

Pie: Higher levels of subjective knowledge increase one's perceived ability to engage in external search for information.

In sum, education, OK, and SK all are proposed to influence perceived ability to search positively. An additional variable that may influence one's ability to search is age. Previous studies have found that a consumer's age negatively affects search (Schaninger and Sciglimpaglia 1981). Phillips and Sternthal (1977) posit that older consumers are less capable of processing information. Re-


cently, Cole and Balasubramanian (1993) found that older consumers searched less intensely and less accurately than did younger consumers. However, previous research has not investigated whether these effects are actually due to age or a cohort effect (Reynolds and Rentz 1981). That is, do consumers generally reduce their search as they age, as is suggested by the negative relationship between age and search, or do consumers from earlier cohorts search less than those in later cohorts? Because of this, no relationship between age and ability to search is proposed.

Motivation to Search

Motivation has been defined as the desire to expend effort on a task, involving both direction and intensity (Bettman 1979), and is the mechanism governing the movement from one state to a desired end state (Simon 1967). Motivation has also been described as "goal- directed arousal" (Park and Mittal 1985). Thus we define motivation to search as the desire to expend effort in the collection and processing of information, which is charac- terized by both direction (which pieces of information are collected and processed) and the intensity of the effort (the level of goal-directed arousal).

Within the context of information search, Spreng and Olshavsky (1989) suggest that the desire for information is a subgoal that arises within the context of a specific consumer behavior episode (Olshavsky 1985). Olshavsky and Wymer (1995) argue that the desire for information is related to the strength of the desire for the good in a means-end type relationship. They state, "The strength of the desire for information about a good is assumed to be directly related to the importance of the good to the consumer (i.e., the higher the involvement)" (p. 19). We extend these ideas by specifying that motivation to search is influenced by several individual difference variables: enduring involvement, need for cognition (NFC), and shopping enthusiasm. Further, as stated earlier, perceived costs and perceived benefits of search have their influence on information search by influencing motivation to search. That is, lower search costs and higher search benefits can increase the motivation to search, whereas higher search costs and lower search benefits can decrease motivation to search.

P2: Higher levels of motivation to search increase external information search activity.

Enduring involvement. The notion of consumer involvement was first introduced by Krugman (1965), and many consumer researchers view involvement as the "perceived personal relevance" of the object or situation to the consumer (Celsi and Olson 1988). Consumer behavior theories suggest that consumers engage in more search when involvement is high and less search when involvement is low (Engel et al. 1993; Hawkins, Best, and Coney 1986; Howard and Sheth 1969). Celsi and Olson (1988) found that consumers spend more time attending to information as their involvement increases.

The construct of involvement can be divided into two types of involvement, enduring (or intrinsic) and situational (Johnson and Eagley 1990; Richins and Bloch 1986), although some see these as simply two antecedents to the consumer's level of felt involvement rather than as separate types (Celsi and Olson 1988). Situational involvement is discussed in the section on perceived benefits of search. Enduring involvement refers to the perceived linkage between an object or idea and one's self-concept, and it connotes intrinsic importance to the consumer. There- fore, enduring involvement should be positively related to the motivation to search for information.

P2a: Higher enduring involvement increases one's motivation to engage in external search for information.

Need for cognition. An individual's NFC is another determinant of motivation to search. Cacioppo and Petty (1982) defined NFC as the tendency for individuals to engage in and enjoy thinking. Inman, McAlister, and Hoyer (1990) found that consumers who were low in NFC were susceptible to a promotional signal (i.e., a promotional sign without an attendant price reduction) in a simu- lated grocery purchase situation. High-NFC consumers were influenced only by a promotion with an actual price reduction and were affected more strongly by the actual price reduction than were low-NFC consumers. Their results indicated that high-NFC consumers were attending to and processing more information in the purchase environment than were low-NFC consumers. Thus we propose that consumers high in NFC will have a greater desire to process information and will gain more enjoyment in processing information in the environment.

P2b: Higher need for cognition increases one's motivation to engage in external search for information.

Shopping enthusiasm. Due to personal differences, some individuals simply enjoy the buying process more than others. Babin et al. (1994) distinguish between shopping as resulting in increased utilitarian value or for hedonic value. That is, shopping can result in instrumental rewards (e.g., lower price) or experiential rewards (e.g., enjoyment and fun). Babin et al. review research related to the hedonic value of shopping in which shopping is described as "festive" providing "freedom," "escape," and "increased arousal." Shopping enthusiasm is defined as the enjoyment an individual feels for the task of collecting and processing information about a product. Katona and Mueller (1955) reported that shopping enjoyment is one determinant of search. Thus increased shopping enthusiasm results in a motivation to search for information for the inherent enjoyment of the process of shopping and thus relates to non-goal-related information search such as browsing and ongoing search.

P2c: Higher shopping enthusiasm increases one's motivation to engage in external search for information.


Perceived Benefits of Information Search

The perceived benefits of search derive from the economics paradigm of information search. Benefits of search are defined as outcomes that increase one's utility or provide value by facilitating achievement of higher level goals or values (Gutman 1982; Olshavsky and Wymer 1995). Outcomes that increase utility (benefits) are linked to higher level values, as in a means-end chain (Gutman 1982), and would involve outcomes such as getting the product with the lowest price, getting the product with the best style/appearance or the highest quality, increased satisfaction with the decision, or increased satisfaction with the product (Bettman 1979).

Cude (1987) conducted a study that used the ratings provided in Consumer Reports publications over the 10- year period 1975-1984. The results of this study show that "there are dramatic returns possible to informed purchase decisions" (p. 94). Duncan and Olshavsky (1982) found that perceived benefits of search related positively to search activity. Srinivasan and Ratchford (1991) found a strong relationship between the benefits of information search and the level of search activity. As stated previously, we believe that the relationship between perceived benefits and search will be mediated by motivation to search.

P3: Higher perceived benefits increase motivation to engage in external search for information.

As shown in Figure 1, there are 10 variables that affect the perceived benefits of information search. Each of these factors is discussed in the following paragraphs.

Subjective knowledge. A number of researchers have suggested that a major benefit of search is the reduction of risk (Bennett and Harrell 1975; Howard and Sheth 1969) and that confidence is related to a reduction in risk (Cox 1967). SK is believed to be strongly related to confidence, which therefore implies that high SK will be associated with a lower perception of the benefits of search. Further, those who believe they know a great deal about a product domain are likely to believe they already have enough information stored in memory, and therefore more information will not be required (Johnson and Russo 1984). Urbany et al. (1989) found that consumers with high SK concerning which brand to buy (low choice uncertainty) engaged in less search. This knowledge of which brand to choose presumably reduces the benefits of searching. Brucks (1985) found that higher SK was related to a decrease in using a salesperson's recommendations. Park, Gardner, and Thukral (1988) found that low-SK consumers tended to perceive new information to be more important and to be more receptive to this new information. Thus it appears that high SK is related to a lower assessment of benefits of search. However, Srinivasan and Ratchford (1991) found a weak but positive effect of SK on perceived benefits of search. The weight of the evidence leads us to propose a negative relationship between SK and perceived benefits of search.

P3a: Higher subjective knowledge decreases the perceived benefits of external information search.

Satisfaction with previous purchases. Consumer satisfaction has been studied fairly extensively and generally has been found to influence information search negatively (Furse, Punj, and Stewart 1984; Katona and Mueller 1955; Newman and Staelin 1971, 1972; Punj and Staelin 1983). For example, Kiel and Layton (1981) found that consumers satisfied with their previous automobiles searched less for information when purchasing their next cars.

P3b: Satisfaction with previous purchases decreases the perceived benefits of external information search.

Perceived financial sacrifice. One benefit from searching is to get the lowest price for a given level of quality. Past research has shown that consumers undertake more search activity when the cost of a product is high than they do when the price is low. Udell (1966) found that consumers visit more stores when making purchases from more expensive product categories. Further, the effects of price on information search have been studied and found to positively affect search across a variety of products including automobiles (Kiel and Layton, 1981), appliances (Newman and Staelin 1973; Udell 1966), and apparel (Dommermuth 1965). We propose that perceived financial sacrifice is a more appropriate variable than product price because the critical factor deals with the relative price given the consumer's financial constraints. For example, a $500 purchase for one consumer may be a very expensive purchase, whereas the same purchase would be trivial for another consumer. Because most consumers operate on constrained budgets, the higher the relative cost of a product, the more benefit that could accrue in searching for information.

P3c: Higher perceived financial sacrifice increases the perceived benefits of external information search.

Perceived risk. Perceived risk has been suggested to increase information search because one way of reducing risk is to obtain more information. Perceived risk consists of multiple components. One aspect of risk is performance risk, which is the concern over whether the product will perform as desired. Performance risk is especially important for highly innovative products. A second facet is social risk, which is the concern over what others will think of the product. Social risk may result in the loss of status among reference groups that stems from making an infer- ior purchase decision. Social risk will be greater when there will be high observability and the product has high social value (see Gatignon and Robertson 1991, p. 324). Uncertainty risk is the concern for emerging technology standards or dominant product design (e.g., VHS vs. Beta) or for length of the life cycle (time before obsolescence) (see Gatignon and Robertson 1991, p. 324). Finally, physical risk is a concern for the safety of the consumer and others. Past research has indicated that consumers search


more when purchasing products that are more risky (Beatty and Smith 1987; Capon and Burke 1977, 1980; Cunning- ham 1967; Moore and Lehman 1980; Srinivasan 1987).

P3d: Higher levels of perceived risk increase the perceived benefits of external information search.

Situational involvement. Situational involvement is defined as the linkage between a product or situation and the outcomes or consequences of the situation. Whereas enduring involvement with a product category provides intrinsic rewards, situational involvement enhances attention and information processing because of the belief that this effort will produce favorable outcomes. Beatty and Smith (1987) found that search effort is positively related with purchase involvement.

P3e: Higher situational involvement increases the perceived benefits of external information search.

Information required for choice rule. A great deal of literature exists that shows that individuals use a variety of choice rules in making product choices (e.g., Bettman et al. 1991). As suggested by Spreng and Olshavsky (1989), the amount of information desired will be partially a func- tion of the choice rule the consumer uses. Perhaps the simplest situation is one in which the consumer subcon- tracts the decision to someone else (Rosen and Olshavsky 1987). In the situation where the consumer decides to use a recommendation, the only information desired is the name of the recommended brand. If a consumer decides to use a lexicographic choice rule, then he or she would only want information about the most important attribute for each alternative and would thus require very little information. Finally, a consumer using a linear compensatory choice process would require information on all relevant attributes for all the alternatives. Thus the decision strategy selected influences the perceived benefits of collecting information.

P3f: The greater the amount of information that is required for using the chosen choice strategy, the higher the perceived benefit of external information search.

Perceived product differences. When there is greater dispersion among brands, there will be greater benefits from searching. Schaninger and Sciglimpaglia (1981) studied information for heterogeneous products (i.e., consumer durables) and homogeneous products (i.e., conve- nience products) and found that consumers process more information for heterogeneous products. Duncan and Olshavsky (1982) found that consumers searched more when they perceived that there were large differences between brand features and prices.

P3g: The greater the perceived differences among products in a product category, the greater the perceived benefits of external information search activity.

Need to justify decision. In some cases, consumers will be required to justify their decisions to others such as their spouses, bosses, or friends (Simonson 1989). In these cases, they are likely to gain benefits from increased searching because more information will make it easier to justify their decisions. That is, even if a simple decision- making rule (e.g., lexicographic) is used, additional information will be beneficial in providing justification for the choice. Moore and Lehman (1980) studied a grocery product and found that consumers searched less when the product was purchased for one's own consumption than they did when the product was purchased at least in part for others to consume. One interpretation of this result is that when consumers were buying the product for others, information was necessary to justify the decision. Further, research by Doney and Armstrong (1996) showed that individuals who are accountable to others for decisions search for information symbolically, that is, for political reasons (to justify their decisions to others).

However, at times individuals may be motivated to justify their purchase decisions to themselves. As Kunda (1990) notes, individuals may be motivated to arrive at a particular conclusion (rather than an accurate one). For example, an individual may want to purchase a particular product, X. However, to avoid postpurchase dissonance, the individual searches for information that supports the purchase of product X while searching for information that supports the decision to not purchase products Y and Z.

P3h: The need to justify one's decision increases the benefits of external information search activity.

Desire for optimum decision. Due to either personal characteristics or the situational context, consumers may want to make the optimal decision rather than satisficing or making an acceptable decision. Swan (1969) found that making a satisfactory choice required significantly less information than making the optimal choice. Therefore, the desire to make an optimal decision positively affects information search by increasing the benefits of search.

P3i: The desire for the optimal decision rather than an acceptable decision increases the benefits of external information search activity.

Size of evoked set. The evoked set is defined as the set of brands or products that are considered or investigated in the purchase process (Howard and Sheth 1969). The evoked set size is expected to influence the perceived benefits of information search positively because there is potentially more useful information available when there are more brands in the evoked set. In addition, more information may be needed to make a choice from a larger evoked set. This effect is supported by past research. For example, Newman and Staelin (1972) found that evoked set size positively influences the amount of search, although the evoked set sizes studied were limited in range. Similarly, Srinivasan and Ratchford (1991) found that evoked set size had a positive effect on the level of external search.


P3j: Larger evoked sets increase the perceived benefits of external information search activity.

Perceived Costs of Information Search

Perceived costs of information search, like perceived benefits of search, come from the economics paradigm of information search. This construct is defined as the consumer's subjective assessment of the monetary expendi- ture (e.g., gas, purchasing informational materials), time sacrifice (e.g., ability to do something else, .delayed use of the product), physical effort (e.g., going to stores, buying informational materials, observing the product), and psychological sacrifice (e.g., psychological costs of processing information, frustration) that he or she expends searching for information (Bettman 1979). Consequently, increased perceived search costs lead to decreased motivation to search (Bettman 1979; Farley 1964; Stigler 1961).

Punj and Staelin (1983) found that search costs negatively affected search activity. Similarly, Srinivasan (1986) found that information search varied inversely with search costs. Schaninger and Sciglimpaglia (1981) found that working wives process less information than nonworking wives. Presumably, this is due to the search costs (e.g., cognitive cost, opportunity cost) being higher for working people.

P4: Perceived search costs negatively affect the motivation to engage in external information search activity.

We propose that five factors determine the perceived cost of searching for information: SK, evoked set size, product complexity, information accessibility, and time pressure. Each is discussed in the following paragraphs.

Subjective knowledge. A consumer's self-assessed level of knowledge should be associated with a perception that search costs will be lower. Knowledge generally is associated with reduced cognitive processing costs and more efficient search in that only important or diagnostic information need be processed (Brucks 1985; Johnson and Russo 1984). Whether search costs will in fact be lower is not at issue here but merely that the consumer who thinks he or she is knowledgeable will perceive that search will be easy.

P4a: Higher levels of subjective knowledge reduce the perceived cost of external information search.

Size of evoked set. A great deal of research in decision making supports the idea that a greater number of alternatives is related to an increase in cognitive processing effort (Bettman et al. 1991). When the number of alternatives increases, consumers tend to use phased strategies in which some alternatives are eliminated, followed by more effortful processing of the remaining alternatives (e.g., Olshavsky 1979; Payne 1976). Because larger evoked set sizes imply greater cognitive costs in evaluating alternatives and greater time costs in this processing, larger

evoked sets should increase the costs of information search.

P4b: Larger evoked sets increase the perceived cost of external information search.

Product complexity. More complex products have more attributes to examine or determine which are the most important. As the consumer makes the decision regarding the extent of the information search that will be conducted for a given product, the more complex the product, the more it will cost to gain a particular level of understanding through searching and processing information. In a similar way, the diffusion of innovations literature has found that complexity of the product reduces the diffusion rate because it is more difficult for the consumer to learn about the product (Gatignon and Robertson 1991).

P4c: Higher product complexity increases the perceived cost of external information search.

Information accessibility. Information accessibility deals with the extent to which information is available and accessible to the consumer in a format that the consumer can use (Bettman 1979). The more accessible the information is in the environment, the lower the cost will be to search and process the information (Bettman et al. 1991). Support for this comes from Russ o (1977), who found that unit price information was used more when the information was presented in a list of brands sorted by price. Further, Olshavsky and Wymer (1995) argued that consumers form intentions for collecting information and that the ease of collecting this information influences whether or not these intentions are fulfilled. In fact, a great deal of the public policy interest in information search deals with this idea in that the goal is to make information more accessible and easier to process so that consumers will be more informed before making purchases. It is proposed that when consumers can easily access information, their use of this information will increase because the cost of searching for the information is reduced. Information accessibility will be higher when consumers are aware of the availability of information and it is in a format that is easy to understand.

P4d: The availability of information reduces the perceived cost of external information search.

Time pressure. Time pressure reflects the consumer's perception of the availability of time and is expected to increase one's perception of time sacrifice (e.g., ability to do something else or delayed use of the product). In a study of consumer electronic appliances, Beatty and Smith (1987) found that information search increases with greater time availability. Presumably, consumers spend more time searching for products (and evaluating information) when their current product is still in operating order. Alternately, time pressure or time constraint often stems


from product failure. If one's television succumbs to old age, then typically the search process would be shortened due to this time constraint of not having a television. The notion that constraints on one's time lead to less information search has been found across numerous studies (e.g., Claxton et al. 1974; Katona and Mueller 1955; Moore and Lehman 1980; Newman and Staelin 1971, 1972; Payne, Bettman, and Johnson 1988; Wilkie and Dickson 1985).

P4e: Time pressure increases the perceived costs of external information search.

EXPLAINING INCONSISTENCIES IN PAST RESEARCH FINDINGS

The proposed model shows how the same antecedent can have countervailing effects. For example, past research has been equivocal regarding the relationship between prior knowledge and information search, finding positive, negative, and inverted-U-shaped relationships. That is, past research has found that, under certain situations, moderate-knowledge consumers search more than low- knowledge consumers (due to increasing knowledge being a facilitator for search by increasing the ability to search) and high-knowledge consumers search less than moderate- knowledge consumers (due to either their use of internal search or the increased efficiency of their search reducing the benefit of external search). This has been argued to produce an inverted-U-shaped relationship. Although Brucks (1985) found evidence for the facilitating effect of knowledge and the efficiency effect of knowledge, she did not find evidence of an inverted-U-shaped relationship between knowledge and total search.

Our proposed model shows that SK has a positive indirect effect (through a positive effect on ability to search, which has a positive effect on search, and through a negative effect on perceived search costs, which has a negative effect on search) and a negative indirect effect (through a negative effect on benefits of search, which then has a positive effect on search). Thus, depending on which variables are emphasized in a given study, the results may show either a positive or a negative relationship and, when combined, may produce an inverted-U-shaped relationship.

CONCLUSION

A comprehensive model has been developed that ex- plicitly combines the psychological (including information processing) approach and the economic streams of research into a cohesive whole. Consistent with the ELM and other past research (e.g., Bettman and Park 1980), information search activity is proposed to be driven by a consumer's ability and motivation, which varies across purchase situations. Further, the proposed model incorporates both search benefits and search costs, whereas Punj and Staelin (1983) only included search costs.

This model extends the information search literature because it goes beyond the bivariate relationships that have been researched previously. The determinants of information search exert their influence through four intermediate constructs. This allows some determinants to exert multiple, and often conflicting, influences on information search activity. This may potentially explain some of the inconsistencies found in the literature. However, contex- tual or methodological differences could account for past inconsistencies. Although not the purpose of this research, meta-analytical techniques could be used to address con- tradictory findings in the literature.

The fact that this literature has continued to grow over the years indicates that this is an important area of study. Consumer information search, as noted, is important for managerial decisions. Because ability to search is intrinsic, managers can choose to lower search costs or increase benefits of search, which will increase consumers' motivation to search. Further, during this period of rapid change, information is more ubiquitous than ever before. However, it is imperative that consumers be given quality information, in the proper form, at the right time. Only by better understanding the interrelationships among the determinants of information search can these public policy issues be sufficiently addressed.

Finally, whereas most consumer behavior textbooks simply list determinants of information search activity, the proposed model is pedagogically useful. Our model orga- nizes the determinants of information search into the four categories of ability to search, motivation to search, costs of search, and benefits of search.

ACKNOWLEDGMENTS

The authors thank four anonymous reviewers and the editor for their helpful comments and guidance on earlier drafts of this article.

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ABOUT THE AUTHORS

J e f f r e y B. Schmid t recently became an assistant professor of marketing at Kansas State University after completing his Ph.D. at Michigan State University. His research interests include new product development and international product strategy. His work has appeared in the Journal of Product Innovation Man- agement and Journal of Business and IndustriaI Marketing as well as in various conference proceedings.

R icha rd A. Spreng is an assistant professor of marketing at Michigan State University. He received his Ph.D. from Indiana University. His research interests include consumer satisfaction/dissatisfaction and issues involving consumer knowledge. His work has appeared in the Journal of the Academy of Market- ing Science, Journal of Consumer Research, Journal of Market- ing, Journal of Retailing, Journal of Services Marketing, Journal of Consumer Satisfaction, Dissatisfaction and Complaining Be- havior, and Journal of Product Innovation as well as in various conference proceedings.

A Proposed Model of External Consumer Information Search

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