uncertainty orientation: expalaining diffeerences in purchase involvement and external search

Uncertainty Orientation: Explaining Differences in Purchase Involvement and External Search J. Brock Smith University of Victoria

Julia M. Bristor University of Houston

ABSTRACT

This study incorporates uncertainty orientation, an individual difference variable concerned with cognitive response to uncertainty, and purchase involvement in a multiple indicator model of consumer external search activity. The model is tested using partial least squares in two contexts: for durable purchase decisions and for nondurable purchase decisions. Purchase involvement was found to be a multidimensional construct and only the experienced purchase- risk dimension was captured in the measurement models. For durables, uncertainty-oriented consumers experienced greater purchase risk and engaged in greater external seach than certainty- oriented consumers. For nondurables, uncertainty-oriented consumers experienced lower purchase risk than certainty-oriented consumers. Although the results are modest, they suggest that uncertainty orientation might be fruitfully examined in other applied contexts. 0 1994 John Wiley & Sons, Inc.

Marketers have long believed that consumers seek information when faced with risk, uncertainty, or ambiguity (Bauer, 1967; Murray, 1991). Recently, however, it has been observed that not all consumers act this

Psychology & Marketing 0 1994 John Wiley & Sons, Inc.

Vol. 1 l(6): 587-607 (November/December 1994) CCC 0742-6046/94/060587-21

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way (Urbany, Dickson, & Wilkie, 1989). For example, Barsevick and Johnson (1990) and Miller and Mangon (1983) found that some people seek information in stressful health-care situations, and others avoid it. Sorrentino and Hewitt (1984) and Sorrentino, Short, and Raynor (1988) found that some people actively try to resolve uncertainty about themselves or their environment, and others do not. They describe uncertainty-oriented people as those who have been rewarded for resolving uncertainty, have developed general schemas to resolve uncertainty, and are affectively charged to do so. Certainty-oriented people are described as those whose conditioning has led to the development of schemas for safe and familiar situations and who are affectively charged not to deal with uncertainty.

The possibility of an individual difference is uncertainty orientation (cognitive response to uncertainty) is particularly intriguing from a marketing perspective: There may be certainty-oriented consumers who avoid information and do not try to resolve purchase and other marketplace uncertainty. Laboratory research by Sorrentino and his col- leagues (see also King & Sorrentino, 1988); Sorrentino & Roney, 1986) has linked uncertainty orientation (hereafter referred to as UO) to individual differences in information processing, involvement, and persuasion in a variety of uncertainty producing contexts. As consumers face uncertainty in navigating the marketplace, these studies suggest UO may be a fruitful construct in explaining differences in external search and other consumer processes.

This study begins to investigate whether differences in uncertainty orientation (hereafter referred to as UO) are manifest in the consumer context and whether UO can explain individual differences in consumer involvement and external search. UO is linked with two involvement constructs in a simple model of external search. The model is tested in two contexts: purchase decisions for durable (expensive, infrequently purchased) products and purchase decisions for nondurable (inexpensive, frequently purchased) products. The model, its constructs, and hypothesized relationships are developed in the subsequent section. This is followed by an overview of the research methodology, presen- tation of the results, and a discussion of their implications.

EXTERNAL SEARCH MODEL

Briefly, the model (see Figure 1) hypothesizes that UO is an antecedent of external search, purchase involvement, and adoption of the market maven role (general involvement with the marketplace). Further, adoption of the market maven role is hypothesized to be an antecedent of purchase involvement, and purchase involvement is hypothesized to be an antecedent of external search. These relationships are all expected to be positive for both durable and nondurable purchase decisions, with

588 SMITH AND BRISTOR

Figure 1. External search model

one exception: for nondurable purchase decisions the relationship between UO and purchase involvement is hypothesized to be negative. The model's constructs and hypothesized relationships are further elab- orated below.

External Search Adequate information search is obviously an important component of effective problem solving and decision making (Janis & Mann, 1977; Newel1 & Simon, 1972). In the purchasing context, consumers seek information from external sources to increase decision quality, or de- crease risk (Bettman, 1979; Punj & Staelin, 1983). However, a long research tradition of explaining observed external search differences with a variety of product, market, situational, and individual factors has yielded modest results, at best. (See Beatty & Smith, 1987; and Moore & Lehmann, 1980 for comprehensive reviews.)

Understanding external search behavior is further limited by other factors. First, the lack of standard measures precludes comparing results or explaining contradictory findings (Horton, 1984). Second, many studies employ single, not multiple, external search measures. Third, most studies ignore interrelationships between external search predictors; yet univariate and bivariate results often fade into insignificance when included in more complex multivariate analyses (Newman & Staelin, 1972). Finally, the theoretical generalizability of the results is limited by narrow research contexts, often involving a single durable

UNCERTAINTY ORIENTATION 589

or nondurable product. Although consumers are thought to engage in greater external search for durables than nondurables (Engel, Black- well, & Miniard, 19861, empirical research has yet to fully address this issue. This study attempts to overcome some of these limitations.

Purchase Involvement Involvement is a key motivational construct used to explain individual differences in cognitive processes such as persuasion and decision making (e.g., Johnson & Eagly, 1989, 1990). The construct, which is rooted in the Allport (1943) and Sherif and Cantril(1947) seminal treatments of ego involvement, can be generally defined as personal importance or relevance (cf. Greenwald, 1982; Ostrom & Brock 1968; Petty & Ca- cioppo, 1986). Purchase involvement is the personal relevance of a purchase decision (Hawkins, Best, & Coney, 19861, which is viewed as the outcome of the interaction between an individual’s values, goals, needs, or self-concept and the stimuli provided by the purchase decision sit- uation (Beatty, Homer, & Kahle, 1988; Mittal & Lee, 1989).

Two points need to be stressed about this construct. First, purchase involvement can vary across consumers; for the same purchase, one consumer may experience a high level, and a second consumer a low level of involvement (Zaichkowsky, 1985b). Second, issues concerning the underlying structure of purchase involvement are not fully resolved. However, there is emerging agreement that involvement is multifa- ceted (Kiesler, Collins, & Miller, 1969; Laurent & Kapferer, 1985).

That involvement should moderate consumers’ external search is well documented in the consumer psychology literature (cf. Bettman, 1986; Petty & Cacioppo, 1979). Predecision information acquisition activity has been shown to increase with uncertainty and importance (Crawford, 1974; Lanzetta & Driscoll, 1968). When highly involved, consumers have been found to engage in extended problem solving and to actively search for information (cf. Beatty & Smith, 1987; Engel et al., 1986). Conversely, when purchase involvement is low, their problem solving and external search activity is more limited (Bloch, Sherrell, & Ridg- way, 1986; Jacoby, Chestnut & Fisher, 1978). This suggests

H1: Greater purchase involvement will result in greater external search activity.

Market Maven Role

A third individual difference variable that may have an indirect influence on external search behavior relates to a consumer’s general marketplace involvement. Consumers who are highly involved in the market are called market mavens: They have been found to possess greater awareness, interest, and knowledge of general market conditions, such as places to shop, price levels, and general product availability (Feick


& Price, 1987). This notion of marketplace involvement is consistent with the previous discussion of involvement as personal relevance or importance. Here, however, the stimulus is the marketplace rather than a specific product or purchase decision. Like purchase involvement, marketplace involvement is continuous, but for simplicity, those who are more involved are termed market mavens.

As a result of being more involved in the general marketplace, market mavens are expected to experience greater purchase involvement in their own purchase decisions. Although market mavens collect general marketplace information on an ongoing basis, it does not follow that they necessarily seek more purchase-specific information. To the extent that they do so, it is expected to be mediated by involvement. Conse- quently, it is hypothesized that

H2: Market mavens are more likely than others to experience greater purchase involvement.

Uncertainty Orientation UO is a cognitive individual difference variable reflecting an individual’s cognitive response to uncertainty (cf. Sorrentino & Short, 1986). People who score high on the UO continuum are Uncertainty oriented (hereafter referred to as UnCO). They are active information seekers who challenge their belief system with new ideas: They like to discover, find meaning, and determine why. In contrast, people who score low in UO are certainty oriented (hereafter referred to as CO). They have the tendency to avoid information about themselves and their environment that requires a change in their cognitive structure (Sorrentino & Short, 1986). When faced with new and potentially confusing situations, CO people prefer to maintain clarity; they stick to the status quo. Such characteristics were evident in a study examining individual differences in the propensity to resolve uncertainty (Sorrentino & Hewitt, 1984). UnCO people engaged in activities that would resolve their uncertainty about a potentially important personal ability (one which would be tied to their self concepts), and CO people engaged in other activities which told them nothing about their ability. One explanation for these differences is that people have different beliefs about the value of new information; UnCO people may value new information more than CO people (Sorrentino & Short, 1986). This suggests that UO may be valuable in the consumer context, because belief about the value of information has been identified as a major determinant of external search (e.g., Duncan & Olshavsky, 1982). UnCO consumers are more likely to view new information as being valuable and should engage in greater external search than CO consumers. Thus, we hypothesize

H3: UnCO consumers tend to engage in greater external search than CO consumers.

UNCERTAINTY ORIENTATION 59 1

UO may also relate to observed differences in consumers’ purchase involvement. Sorrentino, Short, and Raynor (1984) found that compared to UnCO people, CO people perceived situations with relatively uncertain (unknown or risky) outcomes as being less personally relevant; those with relatively certain (known or low risk) outcomes were perceived as being more personally relevant. Sorrentino and Roney (1986) found that UnCO people were most aroused and motivated by diagnostic tasks (tasks that provided personally relevant information), whereas CO people were most aroused and motivated by nondiagnostic tasks (tasks that did not provide personally relevant information). One explanation for these findings is that motivational arousal occurs in situations relevant to a person’s UO; UnCO people learn to be aroused or motivated by situations of uncertainty, and CO people learn to be aroused or motivated by situations of certainty (King & Sorrentino, 1988).

The distinction between uncertain and certain situations corresponds closely to durable and nondurable purchase decisions. Durable purchase decisions (those made infrequently for relatively expensive items such as cars or stereos) are generally thought to involve more uncertainty than nondurable purchase decisions, (those made frequently for inexpensive items such as food or household cleaners) as durable products are more differentiated and hence consumers experience greater difficulty in coding information (cf. Engel et al., 1986). Aroused or motivated by uncertain situations, UnCO consumers may thus be more involved with durable purchase decisions than CO consumers. Aroused or mo- tivate,. by situations involving certainty, CO consumers may thus be more involved with nondurable purchase decisions. Consequently, we hypothesize that the degree of uncertainty in a purchase decision context (as reflected by the type of purchase decision, durable or nondurable) will have a moderating effect on the relationship between UO and purchase involvement, such that

H4A: UnCo consumers will tend to experience greater purchase involvement for durable purchase decisions than CO consumers.

H4B: CO consumers will tend to experience greater purchase involvement for nondurable purchase decisions than UnCO consumers.

UO may also relate to marketplace involvement. Because UnCO consumers are more involved in uncertain situations than CO consumers, and because the marketplace is an uncertain environment, UnCO consumers should be more involved in, more interested in, and more likely to collect information about the marketplace. Thus our final hypothesis is

H5: UnCo consumers are more likely be market mavens.


METHODOLOGY

Previously, UO had been examined only in the laboratory using a thematic aptitude measure and student subjects. Toward the goal of making the construct accessible to applied researchers, we operationalized UO using a self-report measure in a field setting and examined the construct’s behavior in a multivariate modeling context.

The data collection process closely adhered to Dillman’s (1978) total design method for survey research. To generate two purchase decision contexts, one relatively uncertain and the other relatively certain, respondents were asked to consider two recent purchase decisions: one for an expensive product that was not expected to be purchased again for a few years (a durable), and the other for an inexpensive, frequently purchased product (a nondurable). Respondents were then asked questions designed to measure UO, adoption of the market maven role, their intensity of purchase involvement and external search effort for the durable purchase decision, and their intensity of purchase involvement and external search effort for the nondurable purchase decision. Be- havioral measures of external search would have been preferred over self-report measures, but were infeasible because search occurs over time and places, particularly for durables. However, two steps were taken to minimize reporting errors: Respondents were requested to report on a recent purchase decision, and multiple indicators were used to measure external search. To further enhance the quality of the data, surveys with more than four unanswered questions were considered unusable. Missing data were handled by substituting the mean response of other items tapping the same construct for each case. Procedures for construct operationalization, data collection, and model estimation are described below.

Construct Operationalization Scales used to operationalize the constructs were taken from the literature and modified, where necessary, to fit this research context.

General Attitude Measures. The extent to which respondents adopted the market maven role was measured by the Feick and Price (1987) six-item scale. This scale had a reported coefficient alpha of 0.82. UO was measured using self-report items adapted from Sorrentino’s (1988) scale, which were based on the thematic aptitude measure of the construct. Sorrentino found this scale to exhibit face validity and coefficient alphas above 0.70 among student subjects. Pretest results indicated that only seven of these items were meaningful in this context (see the Appendix).

Context-Specific Measures. Purchase involvement and external search were measured in both the durable and nondurable purchase contexts.


External search was measured using the eight items of the Beatty and Smith (1987) scale relating to search from retail, media, interpersonal, and neutral sources. Although the reported coefficient alpha of this scale was low (0.63), search items need not be highly associated, as one source of information could eliminate the need to search another (Beatty & Smith, 1987). Purchase involvement was measured with 11 items from the McQuarrie and Munson (1987) scale that reflected importance, risk, and pleasure facets of the construct. This scale, a modification of Zaichkowsky’s (1985a) Personal Involvement Inventory had a reported coefficient alpha of 0.93.

Sample A pretested questionnaire was mailed to a random sample of 450 reg- istered voters listed in the city directory of a large city in Southwestern Ontario. The sampling frame is a nearly exhaustive list of adults over age 18, as Canadian voter registration is done by enumeration. Of 368 successfully delivered questionnaires, 138 were returned as usable, and 10 were unusable. This resulted in a usable response rate of 37%. The respondent profile was generally consistent with demographic statistics for the region found in the 1986 Canada Census (Statistics Canada, 1987). For example, the sample was 55% female, versus 52% female in the census. Age distributions were comparable as 34% of the sample was under age 35 and 37.5% were over age 55. Education level was slightly higher in the sample, likely due to an age boundary of 18 years for the sampling frame compared to 15 years for the census. These characteristics suggest that the sample was sufficiently heterogeneous to test for UO differences. If anything, the test may be conservative: CO consumers may be underrepresented in the sample because the task of completing the questionnaire may have been perceived as diagnostic and CO people tend to avoid diagnostic tasks (Sorrentino & Roney, 1986).

Model Estimation

Model parameters were estimated using Lohmoller’s (1981) partial- least-squares (PLS) algorithm. PLS is a powerful multivariate causal modeling technique that has a number of advantages over more traditional methods: It facilitates the modeling of multiple dependent and independent construct relationships; it incorporates unobservable constructs; it allows for multiple construct measures and empirically estimates the relative contribution of each; it produces a cleaner picture of theoretical relationships by modeling measurement error estimation; and it combines and confronts a priori knowledge and hypotheses with empirical data (Wold, 1982, 1985). Like LISREL (Joreskog & Sorbom, 1984), PLS is a second generation multivariate analysis technique

SMITH AND BRISTOR 594

(Fornell, 1982). However, PLS was better suited to this research than LISREL, because a priori theory was new to the problem and the sample was small (Fornell, 1983; Fornell & Bookstein, 1982). (For further com- parison of the differing objectives and data demands of PLS and LISREL, see Duxbury & Higgins, 1991). PLS was also more appropriate than regression, principal-components factor analysis, and canonical correlation, to which PLS is related, because the model has multiple endogenous variables. PLS, however, does not allow estimation of models with moderating variables. Consequently, the model was tested separately for uncertain (durable) purchase decisions and certain (nondurable) purchase decisions to determine if the relationship between UO and purchase involvement was indeed opposite in the two contexts.

PLS-result interpretation is straightforward. Estimated loadings between constructs and observed variables are factor loadings. Analogous to factor analysis, construct interpretation is based on the loading pattern; higher loading variables contribute more meaning to the construct. Estimated path coefficients between constructs, which are sub- scripted to match hypotheses, are standardized regression coefficients.

PLS parameter estimation does not produce a normal distribution of structural equation errors. Consequently, traditional t tests could not be used to test the significance of path coefficients. Instead, more conservative nonparametric jackknife estimates (e.g., Achen, 1982) were utilized, as suggested by Fornell and Larcker (1981).

RESULTS

In general, the results suggest that UO is a promising explanatory construct. The study was successful in demonstrating that U0.is indeed manifest in applied settings and can be measured using self-report items: Summing the UO items resulted in a mean of 31.7 and a standard deviation of 6.2. The study was also successful in manipulating the uncertain (durable) and certain (nondurable) purchase decision contexts. Consistent with theory, t tests (see Table 1) show that respondents

Table 1. Mean Differences in External Search and Purchase Involvement for Durables and Nondurables.

Mean (SD)

Construct Durables Nondurables T Valuea

External search 14.9 (6.0) 6.7 (4.7) 13.35* Purchase involvement 49.0 (8.7) 36.7 (8.2) 11.75**

Note. SD = standard deviation "Evaluated with 130 degrees of freedom. *p < .05. **p i 0.01.


experienced greater puchase involvement and engaged in greater external search for durables than for nondurables ( p < .01).

Following causal modeling procedures recommended by Anderson (1987) and Anderson and Narus (1990), the measurement and structural models were evaluated sequentially. The results, which can be interpreted as evidence for or against hypothesized relationships, are reported in the following sections.

Measurement Results Measurement results in the durables and nondurables contexts are similar, mixed, and on the whole encouraging (see Table 2). Item loadings for uncertainty orientation and market maven role are not identical in the two contexts because they are embedded in different nomological networks. One external search item relating to “TV/radio advertising” was dropped from the analysis in the durables context due to low mean and variance. For similar reasons the external search items “phone calls to retailers,” “visits to retailers,” “word of mouth,” “neutral print sources,” and “minutes in stores” were dropped in the nondurables context.

Reliabilities were calculated using Cronbach’s a. In both contexts all constructs but purchase involvement meet Nunnally’s (1978) criteria of .70 for exploratory research. Similarly, as indicated by the Fornell and Larcker (1981) measure of internal consistency (IC), reliabilities in the context of the theoretical models are adequate for all constructs except purchase involvement for both durables and nondurables. All constructs except purchase involvement in both contexts and external search in the durables context met the Fornell and Larcker (1981) criteria for convergent validity that the average variance explained in items by their respective constructs (AVE) be greater than variance unexplained (AVE > 0.50). Finally, all the constructs meet the Fornell, Tellis, and Zinkhan (1982) criteria for discriminant validity that the average variance explained in constructs (AVE) exceed the variance between them (r$.

Table 2. Measurement Properties.

Context

Durables Nondurables

Construct AVE IC ci AVE IC (Y

Uncertainty orientation 0.50 0.87 0.76 0.50 0.87 0.76 Market maven role 0.53 0.87 0.82 0.53 0.87 0.82 Purchase involvement 0.12 0.39 0.69 0.07 0.15 0.65 External search 0.30 0.74 0.74 0.60 0.81 0.76

Note. Ave = average variance explained; IC = internal consistency (reliability); u = Cronbach’s alpha.


Table 3. Measurement Loadings: Purchase Involvement. Loading

Durables Nondurables Construct Item Description Context Context

Purchase Y7 involvement Y8

Y9 Y10 Y11 Y12 Y13 Y14 Y15 Y16 Y17

was important to me of concern to me was relevant to me meant a lot to me was risky for me easy to go wrong hard to choose was appealing to me was interesting to me - was exciting for me was fun for me

0.25 0.05 0.08 0.17 0.57 0.62 0.66 0.07 0.09 0.12 0.01

0.13 0.18

- 0.02 -0.01

0.00 0.54 0.59

-0.16 - 0.16

0.22 0.05

The poor measurement results for durable purchase involvement and nondurable purchase involvement indicate that purchase involvement is a multidimensional construct. This is evident by the pattern of high, low, and negative item loadings in Table 3 (Lohmoller, 1981). Inter- preted like factor loadings, these PLS loadings suggest that only purchase risk is captured in the two model contexts, and that structural results may be different for other dimensions of the construct.

When measurement loading patterns are uneven, Anderson (1987) recommends measurement model respecification before evaluating the structural model. To avoid low construct reliability due to multidimen- sionality, it was deemed appropriate to retain the measures of the purchase risk facet of purchase involvement and eliminate the other measures. In addition, the purchase risk item “was risky for me” was dropped from the analysis in the nondurables context due to its very low loading of 0.00 (Table 3). This item may have been interpreted as financial risk, which by the nature of the purchase, would not apply in that context.

These changes precluded direct testing of the hypotheses relating to purchase involvement. It was deemed useful, however, to proceed with theory building by examining relationships between modeled constructs and the purchase risk facet of involvement.

Revised Measurement Model The measurement results of the revised model are almost identical to those previously reported in Table 2 except for minor differences in item loadings due to the change in the theoretical context (see Table 4 for item loadings). As with the other constructs, the measurement properties of purchase risk are found to be adequate for structural model interpretation in both the durable and nondurable contexts as the in-


Table 4. Measurement Loadings: Revised Model. Lo ad i n g

Durables Nondurables Construct Item Description Context Context

Purchase risk

External search

Uncertainty x1 orientation x 2

x 3 x 4 x 5 X6 x 7

Market maven Y l role Y2

Y3 Y4 Y5 Y6

Y7 Y8 Y9

Y10 Y11 Y12 Y13 Y14 Y15 Y16 Y17

challenges beliefs inquires experiments with new ideas enjoys discovering finds out why seeks to learn challenges views of world

recommends new brands asked for purchase info friends think good source knows where to shop provides info fits description

was risky easy to go wrong hard to choose

phone calls to retailers visits made to retailers number of brands examined frienddrelatives neutral print sources TV /radio advertising print advertising hours in stores

0.58 0.57 0.78 0.78 0.65 0.65 0.74 0.74 0.66 0.66 0.73 0.73 0.80 0.79

0.63 0.64 0.80 0.79 0.80 0.80 0.81 0.80 0.73 0.72 0.59 0.59

0.70 0.75 0.82 0.80 0.96

0.48 -

0.59 - 0.37 0.74 0.45 - 0.65 - - 0.72

0.54 0.82 0.69 -

Note. The results for UO and market maven role are similar, because the same data were used in the two contexts. They are not identical, because the meaning of constructs is determined, in part, by the theoretical context, which differs. - = not included in the analysis due to low mean and variance.

ternal consistencies (reliability) and average variances explained were above 0.70 and 0.50, respectively (Table 5). Structural model interpretation must be made in light of the meaning captured by indicator loadings (Fornell et al., 1982). As evident by the consistent loading patterns in Table 4, the intended meaning of constructs is generally captured. However, respondents indicated that “number of brands examined,” “phone calls to retailers,” and “friends/relatives” are not as important as other sources of prepurchase information for durables.

Table 5. Measurement Properties: Purchase Risk. Durables Nondurables

Measurement Property Context Context

Average variance explained 0.56 0.80 Internal consistency 0.79 0.89 Cronbach’s alpha 0.61 0.77


Structural Results: Durables Context Structural parameter estimates (Table 6) are modest but generally sup- portive of hypothesized relationships. The path coefficients are all significant at the 0.01 level based on jackknifed estimates. With one exception, the signs of the path coefficients are in the expected direction. Finally, the external search variance explained by the model (R2 = 0.16) is modest, but is consistent with prior findings (cf. Beatty & Smith, 1987).

HI: Purchase Risk-External Search. Purchase risk was found to be an important determinant of external search activity (PI = 0.35). This is consistent with the extensive consumer literature on decision making and perceived risk (cf. Bauer, 1967).

H2: Market Maven Role-Purchase Risk. The relationship between market maven role and purchase risk is slight (p2 = - 0.061, but in the direction opposite to that hypothesized for purchase involvement. A post-hoc explanation for this finding is that market mavens may experience less risk for durable purchases than others because of greater marketplace comfort. It remains to be investigated whether market mavens find durable purchases more pleasurable or important than other consumers.

H3: UO-External Search. As hypothesized, our results suggest that UO is a predictor of external search activity (p3 = 0.16). Although the relationship is modest, it is consistent with previously cited laboratory findings and serves as initial evidence that the construct is useful in applied settings.

H4A: UO-Purchase Risk. UO was found to be a determinant of purchse risk (p4 = 0.17). Thus, UnCO consumers appear to be more likely than others to perceive a durable purchase decision as being risky.

Table 6. Structural Results: Revised Models.

Path Coefficients Construct uo MMR P.RISK EIS Uncertainty orientation - 0.47 -0.10 - 0.02* Market maven role 0.47 - -0.01* N Purchase risk 0.17 - 0.06 - 0.22 External searcha 0.16 N 0.35 -

Note. Durables context results below the diagonal, nondurables context results above. N = not hypothe-

'Variance explained in the durables context = 16%, in the nondurables context = 5%. *p > .01. Others significant at the .01 level.

sized.


H5: UO--Market Maven Role. Finally, the results support the hypothesis that UnCO consumers are more likely to be market mavens (p5 = 0.47). Therefore, it may be possible to identify UnCO consumers, in part, by their level of marketplace interest.

Structural Model: Nondurables Context Structural parameter estimates (Table 6) provide mixed support for hypothesized relationships in the nondurables context as two of the path coefficients are not significant at the .01 level. Although the model explained only 5% of the external search variance, it yields some interesting results.

Consistent with the results of the durables context, purchase risk was found to be an important determinaiit of external search (PI = 0.22) in the nondurables context. Similarly, UO is a key predictor of adoption of the market maven role (p5 = 0.47). In contrast to our findings in the durables context, the relationship between UO and external search (H3) is nonsignificant (p3 = - 0.02) in the nondurables context, as is the relationship between market maven role and purchase risk (p2 = -0.01). The former result is consistent with previous research in its inability to identify meaningful predictors of nondurable external search. The later result may be due to both market mavens and others perceiving little purchase risk for nondurables.

The most interesting result in the nondurables context is the finding of a significant, albeit very modest, negative relationship between UO and purchase risk (P4B = -0.10). This is consistent with hypothesis H4B. Although this path coefficient is relatively low, it stands in contrast to the slightly stronger positive relationship in the durables context and is consistent with prior theorizing that motivational arousal occurs in situations relevant to a person’s uncertainty orientation. It provides some, albeit indirect, evidence that decision context uncertainty moderates the relationship between UO and purchase involvement, at least the purchase risk component, and suggests further investigation of the uncertainty orientation construct is warranted. That CO consumers appear to experience greater purchase risk than UnCO consumers for durable purchases and experience less purchase risk than UnCO consumers for nondurable purchases is consistent with individual differences in risk-taking behaviors (cf. Zinkhan & Kirande, 1991).

DISCUSSION

Based on our initial examination of UO in an applied marketing context, our results suggest that the UO construct exists outside the laboratory setting and that individuals differ in their level of UO. Our results are necessarily tentative, given the exploratory nature of the research, the measurement limitations, and the modest structural relationships.


However, UO appears to be a potentially useful construct for understanding individual differences in at least the purchase risk facet of consumer purchase involvement, as well as predecision external search. Specifically, the finding that CO consumers tend to experience less purchase risk than UnCO consumers for durable purchase decisions could have important implications if further substantiated. Marketers, policy makers, and other communications specialists, for example, might need to tailor communication strategies to account for differences in uncertainty orientation. For example, CO people maybe less open to, and less active in seeking information relating to complex and involving issues such as AIDS or abortion.

The finding that CO consumers tend to experience greater purchase risk (in terms of being hard to choose and easy to go wrong) than UnCO consumers for nondurable purchase decisions is also interesting, although the practical implications are less clear given that the levels of nondurable purchase involvement and external search are low for both CO and UnCO consumers. However, the finding might suggest that being more involved, CO people engage in more external search and are more receptive to communication campaigns for nondurables than UnCO people. Research by Sorrentino, Bobcel, Gitta, and Olson (1988) also suggests the possibility that CO people may be particularly receptive to certain types of communication campaigns for nondurables. They found that CO subjects attended more to two-sided communication and were more affected by argument strength and source expertise in situations of low personal relevance than of high personal relevance. The opposite results were found for UnCO people. Although it is clearly premature for marketers to incorporate this information into their marketing strategies, our results did find evidence of UO differences in the marketplace that if further substantiated could have interesting practical implications.

Clearly, additional research is required to more fully understand the extent of UO differences in consumer populations and further investigate its effects on external search and other consumer processes in the durables and nondurables contexts. Limitations of the research design in building the durable/nondurable moderator into the measures of purchase involvement and external search precluded use of traditional approaches to test moderating effects. Further, the small sample precluded testing differences between the durables and nondurables models using LISREL.

Our finding that an established purchase involvement scale had poor measurement properties when used in a multiple indicator context (as opposed to a traditional summed scale) suggests that further work is required. Initially, involvement was thought to be unidimensional (e.g., Zaichkowsky, 1985a). Our results add concrete evidence to the argument that involvement is actually multidimensional (e.g., Laurent & Kapferer, 1985). This suggests that the construct’s dimensions should


be operationalized separately using multiple measures. This will allow the relationship between the dimensions and other constructs to be explored. In the present case, the notion that different relationships may exist between UO and dimensions of involvement other than risk makes some post-hoc sense in that UO is a cognitive individual difference variable and may not be related to affective facets of involvement.

The moderate success of this study also implies that there are op- portunities to incorporate UO into other research streams. For example, because UO moderates cognitive response to uncertainty, it may also moderate subsequent information processing activities such as the formation of cognitive schema, memory, and recall (Roney & Sorrentino, 1987), and selection of informational inputs and the setting of processing objectives (cf. Wyer & Srull, 1986). As a second example, evidence from this study and others (cf. Sorrentino et al., 1988) concerning the relationship between UO and involvement suggests that UO may be an important construct to consider in attitude and persuasion research (cf. Petty & Cacioppo, 1986). As a final example, UO has implications for organizational and management research. As environmental uncertainty is a major influence on the internal characteristics, processes, and management of organizations (Lawrence & Lorsch, 1969; Thomp- son, 1967), the UO of top managers may affect organizational structure, systems, and strategy. Because managers have to cope with decision- making uncertainty, UO might also contribute to the emerging literature on characteristics of effective managers (cf. Luthans, 1988).

Limitations of the study provide other directions for future research. Although prepurchase external search has typically been assessed via self-report measures, the accuracy of these reports needs to be investigated and behavioral measures may need to be developed. We examined UO and external search in a relatively narrow nomological network. Other explanatory variables need to be identified before more comprehensive models of search can be constructed. It might be fruitful, for example, to include sex (a biological variable) and gender (a social variable) (Deux & Major, 1987). Finally, our difficulty in predicting nondurable external search reinforces common wisdom that nondurable purchases are very different from durable purchases. Separate nondurable external search models may need to be developed that include more variables from the realm of affect and habit (Olshavsky & Gran- bois, 1979).

SUMMARY AND CONCLUSIONS

In this study uncertainty orientation was successfully operationalized in a field setting. Modest results found using PLS, a relatively under- utilized causal model estimation technique, suggest that UO helps explain individual differences in the purchase risk component of purchase


involvement and external search. The results were consistent with previous laboratory findings and provide evidence that uncertainty orientation has promise as an explanatory construct in a variety of applied settings. With further theoretical and empirical attention, it should be particularly valuable for exploring consumer choice and other consumer behavior phenomena.

APPENDIX

Uncertainty Orientation Scale Items

X1: I believe it is important for us to challenge our beliefs. X2: If I do not understand something I find out about it. X3: I like to experiment with new ideas, even if they turn out later

to be a total waste of time. X4: I enjoy spending time discovering new things. X5: I like to find out why things happen. X6: I often put myself in situations in which I could learn something

new. X7: I enjoy thinking about ideas that challenge my views of the world.

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Funding for this research by SSHRC and the Plan for Excellence from the School of Business Administration at the University of Western Ontario is gratefully acknowledged. We are indebted to Eileen Fischer, John Hulland, Mike Lynn, Teri Munoz, Dale Rude, Richard Sorrentino, William Howell, and two anonymous reviewers for comments made on an earlier draft.

Brock Smith is Assistant Professor, School of Business Administration, The University of Victoria. Julia Bristor is Assistant Professor, College of Business Administration, University of Houston. The authors contributed equally to this research. Correspondence should be addressed to Brock Smith, School of Business, University of Victoria, Victoria, B.C., Canada, V8W 3P1.


uncertainty orientation: expalaining diffeerences in purchase involvement and external search

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