On Merging Consumer Efficiency Research Into the Stream of Consumer Information Processing Research

George B. Sproles, University of Houston
Loren V. Geistfeld, The Ohio State University
Suzanne B. Badenhop, Purdue University
ABSTRACT - This paper describes the concept of consumer efficiency and one of its operationalizations in research on consumer information processing. A factorial design is used to experimentally measure the effects of consumer information and consumer sophistication on the efficiency of consumers' performance in rating the quality of competing brands and selecting personal purchase preferences. Information was found to substantially increase consumer efficiency in choosing within one of two product classes studied. Based on findings of the research and on the general need for increased attention to consumer efficiency, more mergers of consumer efficiency research into consumer information processing research are encouraged.
[ to cite ]:
George B. Sproles, Loren V. Geistfeld, and Suzanne B. Badenhop (1980) ,"On Merging Consumer Efficiency Research Into the Stream of Consumer Information Processing Research", in NA - Advances in Consumer Research Volume 07, eds. Jerry C. Olson, Ann Abor, MI : Association for Consumer Research, Pages: 198-202.

Advances in Consumer Research Volume 7, 1980     Pages 198-202


George B. Sproles, University of Houston

Loren V. Geistfeld, The Ohio State University

Suzanne B. Badenhop, Purdue University

[Funding for this research was provided by the Institute for Family and Consumer Studies, Purdue University.]


This paper describes the concept of consumer efficiency and one of its operationalizations in research on consumer information processing. A factorial design is used to experimentally measure the effects of consumer information and consumer sophistication on the efficiency of consumers' performance in rating the quality of competing brands and selecting personal purchase preferences. Information was found to substantially increase consumer efficiency in choosing within one of two product classes studied. Based on findings of the research and on the general need for increased attention to consumer efficiency, more mergers of consumer efficiency research into consumer information processing research are encouraged.


Research on consumer information processing (CIP) has surged during the past decade. A large body of literature has been published, including several outstanding syntheses of theory and research in the area (e.g., Hughes and Ray, 1974; Wilkie, 1975; Miller, 1978; Mitchell, 1978; Bettman, 1979). These representative contributions identify CIP as a central topic in the consumer behavior and consumer affairs discipline.

Most of the CIP work to date has focused on marketing-oriented brand choice situations. Such investigations are obviously beneficial to marketers in the planning of promotional, informational and educational strategy to maintain or increase the market share for a brand. CIP research has also provided public policymakers with guidance in making regulatory decisions regarding information disclosure or truth in information which may lead to long-term benefits for users of consumer information. In some cases CIP studies may have benefited consumers and the general informational quality of the competitive market, especially when CIP research findings have led to increased quantity and/or quality of information available to consumers.

However, significantly little of the massive literature on CIP has examined the crucial issue of how information influences the efficiency -- effectiveness, goodness or quality -- of consumers' analysis of competing alternatives and their final decisions. This lack of attention to consumer efficiency in decision-making can be viewed as surprising, given that the field of human information processing on which CIP is theoretically founded often focuses on cognitive, reasoned, systematic -- rational -- processes of human thinking and decision-making. More attention to this crucial issue of consumer welfare and associated market efficiency is needed. Therefore, the central purpose of this paper is to encourage greater attention to research on how consumers' selection and use of information impacts the efficiency or quality of consumer decision-making. To properly introduce this topic, we will first briefly describe the general concept of efficiency and the specific concept of consumer efficiency. This will serve to define the concept and to indicate its legitimacy. Then we will summarize the methodology and results of a continuing research program we have conducted which overtly merges established CIP research methodology into an experimental investigation of how information affects consumer efficiency. Finally, some directions for future CIP-consumer efficiency investigations based on our findings will be suggested.


The general concept of efficiency is deeply rooted in the discipline of economics and is extensively applied in the engineering sciences. Basically the study of efficiency deals with the analysis of inputs and outputs of a system, for instance the efficiency of production, the efficiency of a gasoline engine, or the efficiency of a marketing strategy. Emphasis is frequently placed on the principle of maximizing efficiency, or obtaining the greatest useful output for a particular level of input.

In the context of consumer behavior, consumer efficiency refers to the degree to which a consumer obtains the greatest possible utility or satisfaction from a consumption decision, given a fixed set of resources allocated to the decision. This concept, and all that it implies about rational consumer decision-making, is controversial. Some consumer analysts, many of them marketers, question the very notion that consumers will overtly attempt to maximize (or optimize) utility in their consumption decisions. Indeed some behavioral scientists question the rationality of human behavior in general. They suggest that the complexity of the environment to which humans must adapt (including, implicitly, the consumer environment), and individual limits to information processing skills or personal knowledge, effectively constrain rational behavior. [See Russo (1978) for a thoughtful and detailed discussion of this issue. His paper presents a negative view on the rationality of consumer behavior, but does not fully dismiss the concept; instead he calls for more study.] Thus behavior is often viewed as adaptive rather than rational or optimizing.

But on the other hand, a small but growing number of consumer analysts of varying disciplinary backgrounds have recently given explicit or implicit support to the concept of consumer efficiency, with particular emphasis on the role of informational inputs in influencing efficiency. For instance, Maynes, a leading consumer economist, has addressed the normative perspective of how information can and will improve consumers' performance in the market (Maynes, 1976). Jacoby, a consumer psychologist, has addressed the question of information load and the quality of consumer decisions in a well-known research program which has generated debate on how information may or may not improve consumers' choices relative to their ideal choices (Jacoby, 1977a). Miller, a marketing professor, has reviewed research on product labeling and has found evidence that information may lead to better choices (Miller, 1978). Finally, John Howard, whose work in the theory of buyer behavior is seminal, has argued that consumers' choices have a basis of rationality:

...I have, on the contrary, implicitly postulated that as buyers, people are--at least in their intentions--rational; and I have presented some empirical evidence for this view. For example, feedbacks from satisfaction to attitude are seen in Chapter 13 to have a powerful effect on shifting beliefs; this is consistent with the idea of rationality. Even more significantly, consumers' choices appear to be consistent with their beliefs, choice criteria, and values--and it is in such terms that we define rational behavior in the first place. (Howard, 1977, p. 302)

While none of these works suggest the existence of repetitively rational or maximizing consumer behavior, they at least make the case for more direct attention to the concept of consumer efficiency in general and to the role of information in affecting efficient consumer performance in particular.

A principal reason that consumer efficiency remains controversial is because it is a difficult concept to operationalize in research. [The same may be said for many important concepts in consumer research, e.g. brand loyalty, information, opinion leadership, innovativeness, consumer satisfaction.] One criterion may involve comparing consumers' judgments of products to objective scientific measurements of product quality or individual product characteristics in a laboratory. Standard test methods exist for measuring the magnitude of many quality-related product characteristics, but the development of reliable and valid methods is a complex problem requiring consideration of many factors (Cary and Sproles, 1978). A second criterion may be subjective, based on measurement of the individual's perceptions of product characteristics in relation to his or her perceptions of the ideal choice. Such measures may account for individual differences in tastes or specific situations of product use, but there are operational problems in obtaining a true measure of the individual's subjective ideal. A third criterion may be based on post-purchase satisfaction with the choice, focusing on the degree to which the consumer perceives that the choice was most satisfactory following actual consumption (use). If the best product is indeed the one which satisfies the consumer's needs, then this could be regarded as an ultimate criterion for efficiency; however, there are known difficulties with the concept and measurement of consumer satisfaction (e.g., Hunt, 1977). A fourth criterion might focus on how efficient the consumer is in performing the decision-making process itself; such efficiency could be determined by the number of informational cues and sources consulted, amount of time applied to market search and evaluation of alternatives, energy expended and so on. Thus an individual might be highly efficient in decision-making process (e.g., engaging in minimal search of the market, parsimonious use of information, impulsive behavior) but be less efficient in terms of the outcome (quality of the decision, performance of the product, etc.).

Our research has used the objective criterion for judging the efficiency of consumer performance. Specifically, we have used brand testing and rating results for selected arrays of competing brands evaluated in Consumer Reports. This is perhaps the best-known and widely available source for objective analysis of major competing national brands. Testing the performance of products is done using standard scientific laboratory test methods under controlled performance conditions, and most methods used are those adopted by major independent testing organizations, Federal standards setters, and industry supported organizations (e.g., American Society for Testing and Materials, National Bureau of Standards, American Association of Textile Chemists and Colorists). In short, testing is done with the current state of the art standards. When standard methods are not available, methods are custom-designed to simulate the end use situation or actual performance of the product as closely as possible. Though this technology does not infallibly identify a single best choice for all consumers, it does present a relative ranking and discussion of special characteristics of competitive brands which can offer a reasonable guide to help consumers make their choices in a more efficient manner. [See Morris (1971), Maynes (1976) and Sproles (1977) for more extensive evaluations and applications of Consumer Reports test results and brand rankings.]


Our research program has focused on two specific variables, consumer information and consumer sophistication, as they impact consumer efficiency. In the following paragraphs we will summarize the methodology and results of the research. Readers interested in more complete reports of the research program are referred to a series of recent papers (Sproles, Geistfeld and Badenhop, 1978a and 1978b; Badenhop, Sproles and Geistfeld, 1979, in press).

Our present discussion focuses on informational effects on consumer efficiency. In taking this focus we do not wish to imply that the other major independent variable included in the research, consumer sophistication, may be of lesser importance to efficient consumer performance. In fact, the consumer literature and the popular press speak extensively of the modern, sophisticated consumer and how he/she performs more effectively in today's market; however, the role of consumer sophistication in consumer decision-making has not been empirically measured. Thus one objective of our research was to make a preliminary exploratory operationalization of this concept, and the results suggest that consumer sophistication does perform some role in efficient consumer performance that deserves further investigation. But our research focused much more centrally on specific informational effects on consumer efficiency, rather than the less tangible but perhaps extremely important dimension of consumer sophistication. Therefore, our inclusion of the consumer sophistication variable in this paper is primarily for completeness of presentation.

The research was designed as a series of two controlled laboratory experiments. The first experiment used a sample of 142 undergraduate women students in several courses in consumer and family sciences at Purdue University. The second experiment replicated the first with a sample of 150 adult women from the Lafayette, Indiana community, and demographically representative of the larger U.S. population. The experiment was performed identically with both samples.

An experimental design for simulating consumers' information seeking and decision-making in a laboratory setting was formulated. The experiment was formed as a three factor factorial design with repeated measures taken under one factor. The three fixed factors and the number of levels manipulated were consumer information (three levels), consumer sophistication (two levels) and products available for choice (four competing brands, the factor on which repeated measures were taken). Thus a 3 x 2 x 4 factorial design was used.

Subjects were randomly divided into three groups, each group having an approximately equal number of high and low sophistication consumers as determined from a preliminary questionnaire (the measurement of consumer sophistication and identification of the two levels is outlined later). Each group participated in a consumer information seeking and decision-making experiment involving first obtaining information desired on each brand, and then separately rating the quality and personal purchase preferences for four brands of blankets and four brands of slow cookers. The brands had been tested and rated in Consumer Reports, and had been shown to vary substantially in overall quality.

In order to measure the influence of information on efficient choices, each of the three groups received differing levels of information on which to make their decisions. Subjects in Group 1 (termed the "products only" group) were presented the four brands, with all packaging, labeling and other information removed. They were asked to rate the alternatives without any information other than their personal inspection of each brand. Subjects in Group 2 were presented the four brands in an identical format, and were provided "marketing information'' which included five informational cues on each brand (i.e., for blankets brand name, care instructions, colors available, fiber content and price were provided). Group 3 was also presented the four unidentified brands, and was provided "extended information" which included marketing information plus five informational cues on characteristics of each brand as described in Consumer Reports (i.e., for blankets information on the binding, durability, strength, warmth and weight were provided). At no time were subjects informed of the source of the information, or of the fact that the brands had been tested and rated prior to the experiment.

The experiment was performed similarly for slow cookers. For the marketing information treatment, cues provided were brand name, care instructions, colors available, material content, and price. For extended information cues were capacity, cord type, energy use, availability of recipe book, and storage space required. Note that these cues differ somewhat in content from those presented for blankets. Three of the five blanket characteristics were performance-oriented (e.g. durability) and two were compositional (e.g. weight); in contrast, for slow cookers there was one performance characteristic (energy use), three compositional characteristics (e.g. cord type) and one on use (recipe book). Thus the two decision-making contexts tested in the research differ in informational cues as well as product categories.

Information was presented subjects using the well-known display board method (Jacoby, 1977b). Subjects were allowed to select whatever information they desired from a brands (labeled W, X, Y and Z) by informational cues matrix mounted behind samples of the four brands. They were given as much time as they desired to make their choices (time pressure was not a factor in the experiment). They were then asked to rate the quality and personal purchase preferences for each brand on 10 point scales. Each subject was also asked to rank order the four brands on quality and purchase preferences.

Consumer sophistication was measured using an unweighted index of eight items selected as either direct or surrogate indicators of a consumer's acquired skills. For students the eight items were age, semester classification, number of college consumer courses completed, experience in 4-H programs, self-perceived knowledgeability in evaluating product quality, self-confidence in choosing quality products, brand name awareness, and level of purchasing experience in the previous year. These were measured using forced choice questions and checklists. Adult consumer sophistication was measured similarly, but student-oriented items were deleted. Raw scores for each variable were dichotomized to values of 1 and 0 for each variable, with 1 indicating a high score. The 1 and 0 scores were summed into an index with a range of 0 to 8. The index was then divided at the median of the distribution to determine "high" and "low" consumer sophistication.



The standard analysis of variance for a 2 between subjects by 1 within subjects factorial design was initially performed on the data (see Winer, 1971, for a complete description of the model and mathematics for this design). [Note that since each subject does not receive identical informational treatments (i.e. each selects their own desired information within a treatment), the ANOV should be considered a preliminary examination of the data. See our papers referenced earlier for further analyses.]   Descriptive statistics were also calculated for a variety of information seeking behaviors and performance results (consumer efficiency measures).


Table 1 summarizes the ANOV results for both student and adult samples. The table includes only the main effects and interactions which were statistically significant for either the student or adult ANOV's. This provides a ready cross-comparison of results for the two experiments.

The most important findings deal with the informational treatments effects. Note that the main effects for informational treatments were consistently significant, except for students' purchase preferences. The products effects and the products x informational treatments effects were also consistently and strongly significant. These findings strongly indicate an informational impact on consumer efficiency. However, findings on the consumer sophistication factor are modest though intriguing (see Sproles, Geistfeld and Badenhop, 1978a, for further discussion). Examination of the within-cell means on ratings of product quality and purchase preferences showed consumers' performance generally moved toward greater efficiency (i.e., greater accord with the Consumer Reports rankings) across the informational treatments.

Table 2 provides a more direct view of how information influenced efficiency. The table presents the percentage of subjects under each informational treatment who rank ordered the quality of the four brands identically to Consumer Reports. Note that for blankets the proportion of perfectly efficient consumers (those ranking identically to Consumer Reports) rises dramatically across informational treatments. The contingency table associated with these data was highly significant (P = .0001). However, for slow cookers a different perspective emerges: while efficiency of performance appears to increase across student groups, it actually appears to decrease modestly across adult groups. But neither of the contingency tables associated with these findings was statistically significant, and any inference of a trend in either direction would not be appropriate.


Our research findings suggest that more information may lead to greater consumer efficiency, in terms of an increased proportion of consumers forming preferences in line with Consumer Reports ratings. This is clearly the case regarding blankets. However, the findings for slow cookers were not so clear. Though some trends were observed, neither was statistically significant and the only appropriate inference is that information neither improved nor detracted from efficient consumer performance.

One obvious explanation for the differences in effects of information on consumer efficiency in choice of blankets vs. slow cookers lies with the types of information provided in the experiment. As we have pointed out elsewhere, there are differences in levels of information and in contents of information from one level to the next; this results in differences in values of information relative to the consumer's decision (Geistfeld, Sproles and Badenhop, 1977). The differences in consumer efficiency in choosing blankets vs. stow cookers may reflect this fact; for instance, information provided for blankets was primarily performance-oriented, while information provided for slow cookers emphasized compositional characteristics. It will be useful for future studies to more closely evaluate how differences in informational levels and values affect efficiency.

At this point it is appropriate to note that where consumer efficiency increased, it increased even though subjects had an opportunity to form their quality ratings and preferences on the basis of subjective as well as objective characteristics. For example, texture or appearance could be considered subjectively for blankets, and overall design and appearance for slow cookers. In the case of blankets efficiency clearly increased with objective information, even though the chance for important subjective factors to intervene was present. Apparently many subjects relied more on the objective rather than subjective factors in making their final choices, but still many more did not. Thus it may be true that objective information will have a measurable effect in increasing efficiency of performance in soma market segments, or in some proportion of the population, but not in others. More research is needed to determine where efficiency may be enhanced through information and where other strategies may be more appropriately applied to increase efficiency (e.g., consumer education, consumer legislation, product standardization, voluntary industry programs).



One philosophical point can be offered. A case can be made that consumers' ability to rank order brands in their order of quality should be an excellent indicator of efficient consumer performance (ideally the consumer's ratings should be on an interval or ratio scale, but this may be expecting too much). Once so informed, a consumer might still choose a product with a lower rather than higher overall rating, based on his or her personal needs or values. Even so, the consumer would still be performing efficiently -- he or she would be performing based on their objective knowledge of comparative quality levels available in the market (or in some feasible sub-set or evoked set) and on their personal needs as well. Therefore, the criterion for measuring consumer efficiency in terms of knowledge of objective product quality should be considered among the most firm baselines for future study, especially in merging CIP-consumer efficiency investigations.

In closing, we hope this brief review of our research, and of the linked concepts of consumer information, consumer sophistication and consumer efficiency, has stimulated readers' interest and consideration. If so, we again suggest our papers referenced earlier for more complete perspectives, presentation of data, and suggested directions for future research.


Badenhop, Suzanne B., Sproles, George B. and Geistfeld, Loren V. (1979), "Decision-Making Efficiency of Adult Consumers: A Research Update," Proceedings, American Council on Consumer Interests, in press.

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