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❶Suspicions of technical malfeasance deepened because: Risk handling in consumer behavior -- an intensive study of two cases.

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Arndt also found that word-of-mouth had more effect on high- than on low-risk perceivers. That is, those who were high risk perceivers appeared to pay more attention to what they had heard, particularly to unfavorable comments. In general, Arndt views his data as supportive of the conclusion that, "word-of-mouth seemed to flow from the low to the high-risk perceivers" c, p.

In most all other regards, however, the high-risk perceivers seemed to be more "active" than the low-risk perceivers: Various other studies have asked subjects to evaluate the importance of alternative information sources,and personal sources i. For example, Roselius found that those who perceived high risk for "time", "ego", or "money" loss rated word-of-mouth more helpful as a "reliever" than did subjects in general.

And Perry and Hamm found that " The same conclusion was reached by Lutz and Reilly in their study of the effects of social and performance risk on consumer information acquisition; word-of-mouth was the most important of the four sources of information available externally to subjects word-of-mouth, mass media advertising, rating magazine, and sales clerks.

However, they did not find that variations in levels of social risk influenced information search behavior as they had hypothesized. Finally, Sheth and Venkatesan also found that the experimentally created high-risk regarding the hair-spray product category group sought personal sources of information significantly more than did the low-risk group. The research on perceived risk, word-of-mouth, and opinion leadership would seem to support the generalization that word-of-mouth functions as an important but not necessarily the most important, e.

Roselius, risk reliever across most or all types of risks. The nature and direction of word-of-mouth flow, and specifically as this relates to opinion leadership, is less clear. Certainly this is a very complex issue and one not easily amenable to investigation, especially through a self-report mode.

The drug adoption studies previously referred to e. The research subsequently would seem to strongly support this hypothesis. Both Arndt b and Cunningham b in the studies previously referred to, found evidence to this effect although not necessarily a clear relationship for all products studied , as did Schiffman in his study of the adoption of a salt substitute product among elderly consumers. Similarly, as high as 49 percent adopted the stainless steel blades immediately after they became aware" pp.

Loyalty should be stronger among those perceiving high-risk in the product category and for basically the same reason: Arndt b found that those high in perceived risk for coffee were more likely to be brand loyal and hence less likely to adopt the new coffee under study. Cunningham c similarly found supportive evidence for this relationship but it was less strong for dry spaghetti than for fabric softeners or headache remedies, thus suggesting that where risk is generally low for.

Sheth and Venkatesan studied the development of brand loyalty as a risk-reduction process in repetitive over time consumer behavior and found support for their hypothesis that brand loyalty increased over time.

It should be noted, however, that the development of brand loyalty repeat selection of brands was quicker for the low-risk than for the high-risk groups. The authors conclude that " The sufficient condition is the existence of well-known market brand s on which the consumer can rely. Hisrich, Dornoff, and Kernan hypothesized that, "If the product is intolerably ambiguous, perhaps the store, which might be far less ambiguous, can serve as a surrogate" p.

They chose draperies, furniture, and carpeting as their "ambiguous" products, but found their data rejected the hypothesis.

For all three products, and for both male and female subjects, and at every level of perceived risk, the number of store-loyal buyers was less than the number of non-loyal buyers. They conclude, "At a minimum, this suggests that these buyers did not consider repeat patronage as a viable risk-handling strategy. Indeed, depending on prior results, not shopping at a previously-patronized store might have served as a form of risk reduction" pp. Noting that many women do not order any merchandise by phone, Cox and Rich hypothesized that telephone shopping creates perceived risk of sufficient magnitude to deter many women from shopping by this mode.

Among those who did shop by phone, newspaper advertising was a favored source of information. However, that newspaper advertisements function to identify the merchandise and the store at which it is available may confound the relationship between "saw ad" and "shopped by phone" so that it might not necessarily suggest anything about the uncertainty reducing role that such advertising might play.

That is, ipso facto, the person who does shop by phone as contrasted with one who does not is more apt to say she "relies" more on newspaper advertisements. Using a paper-and-pencil questionnaire, subjects rated the overall risk they perceived in purchasing twenty different products through the ms; 1 as opposed to in a store or from a salesman in research conducted by Spence, Engel, and Blackwell Their hypothesis that people perceive more risk in buying by mail than buying in a store or from a salesman was supported, but their hypothesis that mail-order buyers of hospitalization insurance would perceive significantly less risk in mail-order buying of other products was not supported by the data, nor was there support for the hypothesis that m order buyers of hospitalization insurance would perceive significantly less risk in the mail-order purchase of such insurance than non-buyers.

The authors recognize the inconsistency between the support of the first hypothesis and the lack of support for the second and third and urge that future research be directed at the question. It may well be that the overall risk measure employed obscured particular types of risk being more prominent in one mode than in the other, particularly as these risk components might have interacted with the particular products studied.

One might further question the reliability of the difference scores between perceived risk in the two buying situations computed by the researchers and then subjected to an ANOV, as well as the logic in summing these difference scores across the twenty products for each subject to obtain an "average perceived risk difference" s core.

An issue not addressed in either of these studies is the question of the use of different shopping modes in gathering information rather than the more narrow question of actual purchase by that mode.

It would be interesting to know whether or not high risk perceivers for buying by telephone are more or less inclined to gather information by phone as compared to lower-risk perceivers.

It would also be enlightening were research conducted which simultaneously evaluated the way in which these alternative shopping modes would be used by consumers in coming to a decision rather than addressing the question one mode at a time. For example, one might create an environment where consumers could choose among these modes, each with fixed costs e. Cox a very early in the perceived risk research literature noted, at least for the two consumers in his study, that reducing uncertainty was far more common than reducing unfavorable consequences as a risk reducing strategy.

Sheth and Venkatesan state that, "Generally, the consumer cannot change the consequences of using a brand. He can, however, change his uncertainty about these consequences Although there is no research directly related to this question, subsequent researchers have restricted themselves to "uncertainty reducing" strategies. However, to the extent that the certainty and the consequences dimensions of perceived risk are not independent see Bettman, , we might construe that much of the empirical evidence is functionally addressed to both dimensions simultaneously.

The reviewer has already noted one example of an instance when different levels of overall risk seem to evoke different "relievers " or risk-reducers than when risk is low; namely, the apparent important role of word-of-mouth or personal sources in general. Arndt b found that the content of perceived risk was different for high versus low risk perceivers for coffee. And in his study of the persuasibility of purchasing agents and chemists, Levitt found that although a high credibility company source acted to "reduce risk" in both a "high risk" adoption of product and a "low risk" refer the product to someone else for serious consideration situation, credibility was more important in the high risk situation.

Thus, there is some evidence that the level of overall perceived risk might evoke different prepotencies of risk components,hence different relievers for that risk. It should be noted that research is not consistent on this point. For example, Zikmund and Scott using a multiple discriminant analysis to distinguish differences in information search activity between high versus low risk perceivers regarding lawn furniture, color TV, and stationery, did not find a statistically significant difference in these information preferences.

However, a canonical analysis performed within product categories did reveal differences. But most research has sought to specifically relate types of risk to types of relievers. A starting place seems to have been the difference in evaluation of product information as a function of the "performance" versus "psychosocial" goals of the consumer e. Wilding and Bauer, ; Ross, Subsequently, most recent research in perceived risk has been focused on the relationship between risk and reliever relationships Roselius, ; Perry and Hamm, ; Lutz and Reilly, ; Zikmund and Scott, ; Jacoby and Kaplan, ; Kaplan, Szybillo and Jacoby, ; Newton, ; and McMillan, Although they did not relate their risk components to types of relievers, Jacoby and Kaplan did address the fundamental structure of these components.

They identified five types of risk: Considering the way in which these components grouped themselves as subjects rated these risks with regard to twelve diverse consumer products, it was clear that price seemed to be the metric ordering these products on overall risk perception. Performance risk correlated most highly with overall perceived risk more highly than any other component for eight of the twelve products, and was highly correlated for the others.

For that reason, the authors suggest that performance risk could be employed as an approximation of overall perceived risk. In any event, after performance risk, the next most important risks averaging across the twelve products are in decreasing order financial, social, psychological, and last, physical. But in regressing components on the overall perceived risk score, social entered after performance risk.

The authors found that a multiple regression equation predicting overall perceived risk from component risk scores accounted for 74 percent of the variance in this criterion, and moreover, they cross-validated the regression weights derived in this study using different subjects two years later Kaplan, Szybillo, and Jacoby, and found negligible shrinkage. The cross-validation is to be applauded since it stands out as a singular event of its kind in all the perceived risk research literature.

Roselius identified another type of loss, time loss, and studied the effect of this type of loss in comparison to three others: There were eleven risk or loss relievers studied with respect to these losses using a five-point rating from housewives on "how helpful almost always, usually, rarely, almost never each reliever would be for reducing the risk posed in the situation": We are told only that the questionnaire "presented several generalized risky buying situations" in which "situations were not related to specific products or purchase methods," so there is no way for the reader to know the meaningfulness of the stimuli employed.

Of the eleven relievers evaluated, "brand loyalty" and "major brand image" evoked the most consistently favorable response, being ranked first and second, respectively, as relievers for each of the four losses. The authors constructed -a "net favorable percentage" quotient for each reliever which was the number of unfavorable responses subtracted from the number of favorable responses given to it by subjects, the difference divided by the total number of responses, then multiplied by Some relievers were consistently rated "unfavorably" by respondents; e.

One may well question the meaningfulness of a "negative" quotient sign in that it suggests a reliever was "not helpful" when it could on the average have been helpful or "unhelpful" which was not a response alternative for subjects. Some relievers had "special meaning" in the sense that high loss perceivers were particularly sensitive to them; for example, as previously noted, "word-of mouth" was a helpful reliever except for "hazard loss" "Some products are dangerous to our health or safety when they fail" , and "major brand image" seemed to function much the same as "word-of-mouth.

Six of the relievers were labeled "general-purpose" risk relievers by Roselius since there was not a significant difference in responses to them between high perceivers and "other" buyers across the types of loss; these were brand loyalty, private testing, shopping, endorsements, expensive models, and money-back guarantees.

Roselius concludes that " Lutz and Reilly specifically undertook an investigation of the effects of social and performance perceived risk on information acquisition. Subjects rated which of five types of information they would use in making a purchase decision for each of nine products selected by pretest to represent different levels of social and performance risk combinations.

They found that when performance risk was low or moderate, subjects opted for "buy" take their chances and pick a brand without search for product information , but when products were high in performance risk, "direct observation and experience" was the most preferred route and "buy" the least.

Zikmund and Scott conducted personal interviews with housewives to evoke specific risk consequences associated with purchasing in eight different product classes. These risk variables were then factor analyzed to identify principal risk dimensions. They also measured the traditional uncertainty and consequences of perceived risk and comPuted an overall risk measure by multiplying these two components. Considering color TV, lawn furniture and stationery, the factor analysis showed that all three products had " A "new" risk factor, not previously identified, was "future opportunity lost", which is associated with the expectation that an improved or lower cost product may be available at a future time which would be precluded by a current purchase -- both color TV sets and lawn furniture have this risk associated with them.

They also found a "shopping frustration" factor associated with lawn furniture and stationery but not with color TV. The authors concluded that the research " Consumers evaluate products on the basis of a few principal attributes and each represents a potential source of risk. Further, these attributes vary across product classes. Disaggregating perceived risk into product-specific components in this fashion provides much more information about why a consumer perceives risk than overall measures such as social or performance risk" p.

Cunningham a had suggested that some people have a generalized tendency to perceive either high or low risk across a range of products, but this hypothesis has not been specifically tested subsequently. Cox a noted a "clarifier"-"simplifier" cognitive style difference in the two subjects he studied intensively; the one tending to seek information to clarify or reduce ambiguity "clarifier" and the other reducing ambiguity by keeping out disturbing cognitive elements "simplifier".

Pettigrew observed that "broad categorizers seem to have a tolerance for type I errors: By contrast, narrow categorizers are willing to make type II errors. They include many positive instance by restricting their category ranges in order to minimize the number of negative instances p. Popielarz reasoned that broad categorizers would express greater willingness to buy new products than narrow categorizers and that people with broad category ranges would be more likely to perceive smaller qualitative differences between products of a given product class than narrow categorizers.

They then rated the extent to which they saw brands as qualitatively different. Category width scores correlated with willingness to buy in the hypothesized direction, but only for male subjects was the prediction supported that broad categorizers would perceive smaller qualitative differences among products; for female subjects, the relationship was reversed.

Schiffman also found that the broad categorizer was more apt to have adopted a new product salt substitute than the narrow categorizer, but the measure he employed to measure category width he refers to the construct as "error tolerance" seems to the reviewer to be criterion contaminated see "The criterion and construct definition problem" section of this review.

And although not specifically related to the perceived risk concept, Barach found that broad categorizers were more persuaded i. In sum, there is evidence that the perceptual or cognitive construct, category width, is related to willingness to adopt new products; broad categorizers being more willing than narrow categorizers to adopt.

However, the construct has not been specifically related to perceived risk. We do not know that broad categorizers are less prone to perceiving risks as a generalization. Self-confidence as a personality construct has also been studied in relationship to perceived risk. However, Cunningham c does report that those subjects medium in self-confidence were more likely to be brand loyal high brand commitment than those low or high in self-confidence. The effect of self-confidence on perceived risk remains unclear.

Several investigators have recognized that the criterion problem has not been adequately addressed e. Unless we can "know" what kinds of behaviors are manifestations of risk then it is always equivocal that we are really validly measuring risk. The criterion problem is at the same time a construct definition problem, and vice-versa. Researchers have assumed that there is risk in decision-making simply because, using the instruments they have developed to measure it, they have "measured" it.

Naturally, one could make the same observation about research difficulties associated with other similar hypothetical constructs or intervening variables such as "personality", "self-confidence", "dissonance", "attitudes", and so on. One can find numerous examples among the studies reviewed herein where the "criterion contamination" problem is severe,rendering "findings" of many of these studies equivocal, at best. For example, Arndt a measured and thus defines perceived risk by asking housewives, "How sure would you be of picking the best brand of product class: A criterion variable is "innovativeness" which he measures by asking when the consumer made her first purchase of the product ranging from not at all to three or more years ago.

He not surprisingly finds a strong negative correlation between perceived risk and innovativeness. Now if a consumer has never bought any brand in the product category and in his study, 40 percent had never bought soft margarine and 74 percent had never bought electric toothbrushes or electric dishwashers one should not be surprised to find that she is rather "unsure" that she would be able to "pick the best brand" in that product category.

Cox and Rich have a similar contamination issue wherein they measure perceived risk in telephone shopping by asking respondents to sort 20 cards, each bearing the name of a particular item of merchandise, into two piles: All respondents in this portion of the study had ordered by phone at least once during the year prior to the survey.

The 10 items about which the respondents had the most "worry" were designated "high perceived risk" items and the other 10, the "low perceived risk" items. The authors then determined the relationship between the perceived risk ratings merchandise items received and the frequency with which an item was mentioned as being purchased by the telephone in their last phone orders.

They find that " Knowing the item is low in perceived risk allows us to predict that in 85 percent of the cases the item will be medium or high in frequency of phone purchase. One might argue that this observed relationship demonstrates that people say they are apt to be less worried about doing something they have in fact done before than they are to worry about doing something they have not done before. The construct of perceived risk has become obscured by defining measuring it in a situation-specific context ordering by telephone which is the same context used to "validate" and interpret the effect of the construct.

The logic here or the lack of it is akin to the assertion that "not having a telephone is likely to be a strong deterrent to purchasing an item by telephone. All households had received a coupon worth 30 cents on the purchase of the salt substitute regularly priced at 59 cents. After two weeks, 17 percent had redeemed the household coded coupon, soon after which time interviews were held with the female member of all households.

And, "Would you say it is not important, of some importance, or quite important for you or your husband to get a salty flavor into your food Taste Risk Importance? What this demonstrates about even the existence of a "new risk-handling variable, perceived error tolerance", quite aside from the question of what such a construct could or does have to do with new product trial, is unclear. We would be led astray by many of the conclusions we would read in this area.

For example, Sheth , despite his caveats that the empirical research on the diffusion of innovations has been lacking in theoretical foundation and rather has proceeded "on the grounds of convenience and ease in implementation" p.

In fact, Sheth does not measure whether or not or the extent to which risk was perceived by adopters but simply asserts that this would be an example of a "low risk" innovation.

Although Sheth may certainly be correct in his theoretical argument that the adoption process for a "miracle drug" may be quite different than that for a stainless steel razor blade in part because of the differences in "perceived risks" among adopters for these products, we find no data in this study which are relevant to this very important issue. Why bother asking adopters when they adopted if this is not specifically to be related to some measure of risk perception?

Perry and Hamm specifically measure only two risk components, "social" "how the purchase decision will affect the opinion other people hold of the individual" and "economic" "how the purchase will affect the individuals ability to make other purchases" p. They also conclude that "These findings suggest that promotional strategies in a high-risk purchase situation But the variance finding alone does not suffice as a basis for arguing that "social benefits" would be more "risk reducing" than "economic" ones, although the finding does suggest an interesting hypothesis which ought to be empirically tested.

Unobtrusive measurement or at least disguised measures of overt risk- reduction processes:. This research mode also is likely to sensitize subjects to their "perception" of perceived risk and may therefore motivate them to behave as if there was risk when, without the intrusive measure, they might not have done so. Embedding either or both within other measures or other disguises are recommended.

Unobtrusive measures have obvious advantages where the subject of the investigation would seem to be so especially sensitive to these potentially reactive measures. With the exception of research by Sheth and Venkatesan , there is no research in this area which directly manipulates risk by experimental design although several studies expose subjects to different risk "sets" in evoking preferences for alternative kinds of information, e.

Use of such designs would give the researcher more power, especially in addressing theoretical relationships within the risk model e. As noted by Nicosia in his review of the Harvard studies Cox, c , the perceived risk literature " There is no true model of the perceived risk construct as it relates specifically to information acquisition, transmission, or handling.

Berlyne has asserted that increasing response conflict can be as important as attempts to reduce conflict, especially in monotonous environments wherein persons may engage in "diversive" exploration p. Deering and Jacoby and Copley and Callom have made provocative initial efforts in studying the conditions under which such risk enhancing activity may occur, and the question seems worthy of further study.

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