A Consumer Based Approach For Establishing Priorities in Consumer Information Programs: Implications For Public Policy

Rohit Deshpande, University of Texas at Austin
S. Krishnan, Pennsylvania State University
ABSTRACT - Although there exists substantial research on the style and format of consumer information programs, little attention has been devoted to the critical issue of whether consumers need new information at all. A conceptual approach to systematically assess this information need is described along with an empirical operationalization of the approach using data gathered from a sample of elderly tonsure. Implications of this approach are discussed for public policy makers with suggestions for further research in the area.
[ to cite ]:
Rohit Deshpande and S. Krishnan (1981) ,"A Consumer Based Approach For Establishing Priorities in Consumer Information Programs: Implications For Public Policy", in NA - Advances in Consumer Research Volume 08, eds. Kent B. Monroe, Ann Abor, MI : Association for Consumer Research, Pages: 338-343.

Advances in Consumer Research Volume 8, 1981      Pages 338-343


Rohit Deshpande, University of Texas at Austin

S. Krishnan, Pennsylvania State University

[The authors wish to thank Dr. Gerald Zaltman and the University of Pittsburgh for providing the data for this study, and D. Sudharshan for his assistance. The research was supported by Administration on Aging, U. S. DHEW, Grant No. 5-38131.]


Although there exists substantial research on the style and format of consumer information programs, little attention has been devoted to the critical issue of whether consumers need new information at all. A conceptual approach to systematically assess this information need is described along with an empirical operationalization of the approach using data gathered from a sample of elderly tonsure. Implications of this approach are discussed for public policy makers with suggestions for further research in the area.


The past five years have seen an increasing amount of research being devoted to the public policy implications of consumer decision making. Paralleling the growth of this work has been a woeful disregard of the usefulness of the research in the actual policy making process. There have been some exceptions to this rule (Permut 1979), but consumer researchers have largely used a product orientation in their work, devoting themselves to tasks such as experimenting with different information presentation formats without undue emphasis on whether consumers desire the information at all. The result has been a subscription by both policy makers and marketing managers to a "more information is better" philosophy which has produced its obvious consequences discussed in the recent research controversy over information overload (Jacoby, Speller, and Kohn 1974, Russo 1974, Scammon 1977).

The dilemma has been recognized for some time now (Thorelli, Becker, and Engledow 1975); but, as McEwen (1978) notes, the suggested solutions stress what marketers or policy makers can do rather then what consumers need. The failure to use a marketing concept has produced information programs looking for people to use them. As Capon and Lutz (1979, p. 59) indicate: "Heretofore, policy makers have introduced consumer information programs without a clear idea of whether the par-titular information in the programs was desired by consumers.''

The problem becomes even more serious when one considers the current trend toward reduced governmental involvement in regulatory and information providing capacities. Recent criticism of the FTC can be traced to feelings (within and outside government) that regulatory agencies are involving themselves in areas where no intervention was required. Clearly, there is a need to assess consumer desire for additional information or other support before programs are mounted to achieve this purpose.

Further, public agencies are similar to private organizations in that limited resources of money and manpower exist. The allocation of these scarce resources among information programs implies the establishment of a set of priorities. To use the Capon and Lutz (1979) analogy, if consumer information programs are looked at as products (or services), public policy makers can develop marketing programs detailing the alternative mixes of distribution, pricing (costing), and promotion. They also must decide which programs will be most effective.

Every marketing program begins with decisions on the market segment to which the product or program will be targeted. The development of the product itself lies in the predetermined need for that product by intended consumers. It is only after the determination of this need that the development of the product can be considered.

The discussion of this paper describes a consumer need based approach for deciding which products and services should be focused upon for consumer information programs. This approach is then operationalized for a specific segment of consumers, those over 64 years of age. Finally, the policy implications of using this approach are described by relating it to other current research in the area.


The first task in the policy development process is to decide on a group of individuals to whom further information regarding products and services may be provided. Recent work in marketing literature suggests that the elderly (chronologically defined as over 64 years in age) are such a group. The lack of much empirical work describing the consumption habits of the elderly (Phillips and Sternthal 1977), their apparent disadvantages in the marketplace (Waddell 1975, Zaltman et al. 1978, Bearden et al. 1978, Deshpande and Krishnan 1979), and the growth of this age cohort as a proportion of the total U. S. population could be used as criteria for the selection of this consumer segment. These criteria are offered as illustrations, and several more could be developed to choose a target audience.

The next stage is an important one. Since information programs about a plethora of products and services cannot be practically developed (or even be needed), some method is required to determine the relative information demand for different products and services. One approach to determining this demand is obviously based on the perceived consumer need for information about a product or service. However, from an information program designer's perspective, this would be incomplete without a consider-scion of information availability. If consumers need certain kinds of information to make purchases, but this information is not difficult for them to acquire, then this is clearly not as critical a niche for program development as where both the need exists and the information is unavailable. [Both information need and availability were identified by elderly consumers during preliminary focus group interviews as being of major importance to them in making purchase decisions.] This may be called "information deficiency." When the degree of felt need for information for a product/service is high, as well as the difficulty in obtaining that information is high, a large information deficiency exists. Figure 1 shows an example of a scaling approach that can be used to describe an Information Deficiency Index for a product/service category.



On this index, it is assumed that the two dimensions (perceived need and difficulty in obtaining information) have equal weighting. This assumption has been made for lack of additional empirical information, although any alternative weighting scheme would as well be reflected in the indices given to each cell.

Information Deficiency scores for a set of "relevant" [A context specific definition of "relevance" is provided in the next section] products and services can be developed using the above scheme. However, an approach is required for comparing the relative magnitudes of information deficiencies for different products for the consumer segment being considered. This implies that a method for interpreting the ordinal measurement in interval scale terms is needed. A procedure enabling this is the Thurstone Case V scaling model (Thurstone 1959), an excellent marketing application of which is described by Green and Tull (1978, pp. 180-87). The use of this model is provided in an empirical illustration below that follows the description of the sample used for this study.


Data used in this study come from a larger research program focusing on the consumer problems of the elderly. The program investigates, among other issues, susceptibility to misleading marketing practices, information processing, and restitution mechanisms. Two structured mail questionnaires were developed from focus group discussions on these issues. The questionnaires were mailed six months apart to a national panel of 4,000 persons aged 25 to 80. The response-rates for each wave of the survey were 71.3% (2,853 responses) and 89.4% (2,551 responses from first-wave sample), respectively. In comparison with available statistics on the national level (U. S. DHEW 1978), the following were the characteristics of the overall sample:

(1)  a (naturally) disproportionate proportion of individuals over age 64 (61% to 11% nationally),

(2)  a lower representation of Blacks and Hispanics (3% and 0.1% versus 8% and 4% nationally) respectively,

(3)  a slight underrepresentation of high school graduates and a modest overrepresentation of college graduates, and

(4)  fewer individuals whose spouses were no longer living.

The analysis discussed in this paper deals with 1,747 usable responses from the elderly (over 64) subsample or 68% of the final sample.

In the first wave of the questionnaire, respondents were presented with a list of over 40 products/services and asked to indicate those where they had felt cheated or taken advantage of during recent purchase experiences. This "bad buying experience" question also had an open-ended provision for products not included in the list (the original list had been arrived at through earlier focus group discussions). Table 1 presents the incidence of bad buying experiences as reported for the above question for the more frequently cited experiences.



After consultation with an advisory council of experts and policy makers in the elderly area, products and services with the most frequent citations in the above list were selected for more intensive scrutiny. These were (1) auto repair, (2) auto purchase, (3) home repair/ improvement, (4) utility services, (5) insurance, (6) health care, (7) non-medical professional services, (8) appliance purchases, and (9) appliance repairs.

In the second wave of the study, the following question was asked:

I've listed below some different types of products or services. In Columm A, "X" all those where you feel that you, personally, need information. In Column B, "X" the products or services where you feel the information you need is difficult to get.


The data obtained from 1,747 elderly consumer responses to this question form the basis for subsequent analysis reported below.


For each respondent, an Information Deficiency (ID) score was determined as per the index described in Figure 1. Table 2 shows the median scores for each of the nine product categories being considered. Although these median values give some indication of the extent of information deficiencies present, as mentioned earlier, they still do not permit a meaningful comparison of the differences in relative magnitudes of the deficiencies for different product categories. This implies that the median values simply indicate that the information deficiency is greater for appliance repair than for home repair/improvement with no indication of how greet the relative deficiency is. To do this, the ID scores can be converted using the Thurstone Case V model.



This model is developed by first calculating the proportion of respondents for whom the ID score is higher for product category "j" than for category "k" for all possible category pairs. This is denoted by (j, k). The proportion of respondents having equal ID scores for a given category pair (j, k) were divided equally between proportions for (j, k) and (k, j). Table 3 shows the proportions matrix that results. For example, the entry in the second column and first row indicates that 37.8% of elderly consumers had a higher ID score for product category #2 (Auto Purchase) than for product category #1 (Auto Repair).



The Thurstone Case V model can be expressed simply as,

Rj B Rk = Zjk

where (Rj - Rk) is the relative distance expressing how much individuals discriminate between stimulus "j" and stimulus "k." In our case, this discriminal difference is the relative distance between the Information Deficiency for product category "j" and that for category "k." Also Zij is the standard variate (unit normal) associated with the observed proportion of cases in which the ID for "j" is perceived to be higher than that for "k." The model above assumes homogeneous perceptions of the stimuli across the respondent population. This assumption is supported to some extent in the split-half reliability test discussed below.

Table 4 reports the Zjk scores matrix where each cell entry is the standard variate associated with the corresponding entry in the Table 3 matrix (for computational procedure cf. Green and Tull 1978). The Thurstone Case V interval scale value (Information Deficiency) for each product category is then computed as the mean (Z) of the column scores of the Zjk matrix. Since this scale is unique up to an interval level, the ID values for the nine product categories can be rescaled with the lowest value (-0.254) being arbitrarily set to zero and the other values being correspondingly adjusted (R*). Figure 2 expresses the rescaled ID values for the nine product categories on a unidimensional scale.








As can be seen from Figure 2, the use of the Case V Approach provides a pictorial display of the Information Deficiency for different product categories. Since this is an interval scale, it can be used in a variety of manners for resource allocation in designing information programs. For example, we know that the difference in information deficiency between Appliance Repair and Non-medical Professional Services is approximately 4.8 times the difference between Non-medical Professional Services and Home Repair/Improvement since:

(.595 - .352) = 4.8(.403 - .352)

This provides an indication of the comparative resource allocation that can be made on information programs dealing with these specific product categories. Similar estimates of allocation can be developed for each of the nine categories described by the elderly consumer segment as requiring policy attention. Clearly, this can be a powerful tool when, as is usually the case, resources are limited and must be apportioned carefully. If the budget for an information program is extremely tight, it may even be necessary to expend resources on only three or four out of the nine categories described here.

Use of the approach outlined above then establishes the relative information demand priority for consumers. In an ordinal sense, it can be seen that more attention needs to be given to information programs on appliance repair, home repair, and non-medical professional services than, for instance, appliance purchase or automobile purchase at least as indicated by this sample of elderly consumers. More specific resource allocations can be determined using the pairwise differences rationale outlined above. Furthermore, other conceptual dimensions can also be used to determine information deficiencies or gaps. For instance, the cost of acquiring information and how understandable it is may replace the information need and availability dimensions used in our analysis.

As mentioned in the introductory comments, the use of this approach is based on consumer need for information rather than policy maker determinations of what information to provide to whom. It is possible that the use of such an approach can forestall both the criticisms of policy intervention where no intervention was desirable and that of consumers being provided with more information than they can efficiently process before making purchase decisions.

The conceptual approach suggested also has the advantage of allowing the comparison of different consumer segments which need information-program attention. For example, it is conceivable that other demographic groups besides the elderly may need information regarding appliance and home repair. It may then be more cost-effective to devise programs targeted at all of these groups with similar information needs.


It remains to tie in the approach suggested here to some of the literature on public policy implications of consumer decision making referred to earlier. Responding to criticisms that research in consumer decision making takes an overly product orientation (McEwen 1978, Thorelli et al. 1975), this paper had advocated starting by focusing on consumer demand for information. In directly employing the marketing concept (Capon and Lutz 1979), policy makers would first select a target audience or secant and then determine what its information demands are (Day and Brandt 1974). This determination would be based on both information need and information availability dimensions. Additionally, it should allow policy makers to set priorities by product or service category.

Once these priorities have been set further research can be carried out to investigate the specifics of the information needed, such as unit pricing (Russo 1974) or restitution mechanisms for product complaints (Hunt 1977), and information presentation formats (Bettman 1975, Bettman and Kakkar 1977). But, to implement these latter information program specifics exclusively would be to deny the existence of consumer need for the program. This, in turn, would in all likelihood jeopardize the program in terms of its perceived relevance or usefulness to the consumers for whom it has been designed.


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