Issues in Research on Consumer Choice

James R. Bettman, University of California, Los Angeles
ABSTRACT - This paper discusses three studies on consumer decision making. Issues of construct definition, construct measurement, and theory development are addressed, and several priority areas for research on consumer choice are considered.
[ to cite ]:
James R. Bettman (1979) ,"Issues in Research on Consumer Choice", in NA - Advances in Consumer Research Volume 06, eds. William L. Wilkie, Ann Abor, MI : Association for Consumer Research, Pages: 214-217.

Advances in Consumer Research Volume 6, 1979      Pages 214-217


James R. Bettman, University of California, Los Angeles


This paper discusses three studies on consumer decision making. Issues of construct definition, construct measurement, and theory development are addressed, and several priority areas for research on consumer choice are considered.


The three papers presented in this session deal with the broad area of consumer decision making. Each examines some aspect of the choice process and attempts to add to our knowledge of that process. In the following, each paper is briefly discussed. Then implications for future research on consumer choice are considered.


Harvey's paper attempts to provide a framework for examining one determinant of external information search, namely the level of evaluative conflict felt by the consumer. This area is an important aspect of the consumer choice process, and search for information and conflict or related variables (e.g., arousal, incongruity) are core constructs in several consumer choice theories (Howard and Sheth, 1969; Hansen, 1972, Howard, 1977; Bettman, 1978). In addition, the framework proposed by Kelman and Baron (1968) and presented by Harvey appears to offer some interesting potential insights into how consumers respond to conflict. In particular, variables which may affect individuals' conflict reaction strategies are presented: the type and number of goals active in a choice situation, and the degree of effort required to execute a strategy, for example.

The contributions of the paper remain potential, however, due to some unresolved problems. First, the construct of evaluative conflict (EC) is not yet well delineated or defined, a problem common to many studies of consumer choice using fairly complex and abstract constructs. Prior work on specifying conflict is not addressed (e.g., Berlyne, 1957). This lack of rigorous specification makes measurement of such constructs a very difficult task. In the present paper, an intuitive measure for EC is proposed, but its goodness cannot be evaluated without further specification of the construct being measured. I would simply comment that the measure presented in Formula 1 appears to require ratio scales for SG and SB. This imposes a strong requirement on the researcher, to say the least. Also, it is not clear why the case of high positive and low negative beliefs should entail moderate conflict, as Formula 1 and Figure 1 seem to imply, rather than low conflict.

A second general concern is that there are no specific theoretical propositions advanced which could form the basis for future research. A model which depicted the relationship of several constructs to degree and direction of external search could be highly useful. Harvey's paper hints at such a model, but does not specify one in any detail. In building such a model, I would suggest that such notions as the perceived costs and benefits of search; choice environment factors (such as availability of information or time pressure); and individual differences (abilities, concern with choice optimality) be included. The focus on conflict alone seems too narrow (Bettman, 1978, Chapter 5).

Finally I would quarrel with Harvey on a more specific point, whether decisions about most innovations are single-goal decisions. Harvey claims they are, and I find this hard to accept. Harvey himself notes that there are financial, performance, and safety factors associated with innovations, and these are likely to have corresponding goals. Thus I believe that such choices are more likely to be multiple-goal decisions.

In summary, the Harvey paper alludes to some interesting vistas for research, and I would encourage him and others to flesh out some of these areas more fully.


The Raju paper explores how consumers' perceptions of innovations are related to their reactions to those innovations. Again, this is an issue which is important for understanding consumer choice, as the perceptual encoding of the choice alternatives can strongly influence how those alternatives are evaluated and compared. The types of stimulus variables proposed by Raju may provide insight into variety seeking behavior, one of the toughest and most underresearched areas in consumer choice.

In attempting to implement the study, however, some serious problems arose. First, there seam to be substantial measurement problems. Single item scales are used to measure relatively complex constructs. There is no evidence that these scales correspond to the constructs they are meant to represent; in part, this difficulty is compounded because the constructs themselves are not well-specified. The so-called behavioral response measures exemplify this problem. These measures are hypothetical cognitive responses, not behavioral measures. I also have some difficulty in determining how to differentiate investigatory and seeking responses, for example. If one picks up a package to examine it out of curiosity and looks at price and ingredients while so doing, it is not clear whether that is seeking or investigating. In addition, the "cognitive" response measure, preference, is actually an affective measure. Thus, more careful specification of constructs is needed.

Secondly, I believe the study could have been made stronger by specifying a theory a priori and manipulating the independent variables contained in that theory. Previous research on diffusion of innovations (Rogers and Shoemaker, 1971) and on the impact of consumer perceptions on innovative behavior (Ostlund, 1974) showed the impact of compatibility, for example. There would appear to be enough information from this prior research to start with a theoretical causal model and test that model. I have other problems with the study (e.g., I see the paper as using an S-O-R rather than S-R model, since perceptions of stimuli are the focus), but the two above are my major concerns. Despite these issues, I believe variety seeking is a neglected area of consumer research, and hope that Raju's exploratory efforts will stimulate other research on this topic.


The paper by Walton and Berkowitz examines some aspects of consumer choice which I feel will be of growing importance in future research: decision time and consumers' perceived freedom of choice. Examination of factors influencing choice times can lead to insights into the heuristics used in making choices and to increased knowledge about underlying choice processes (Wright, 1977; Sternberg, 1977). Consumers' perceptions of choice freedom could have important implications for consumer satisfaction research and for policy. For example, the Walton and Berkowitz study finds that for alternatives low in complexity, presenting subjects with more choice alternatives (flavors) leads to longer choice time and more perceived freedom. This might pose an interesting conflict, if shorter choice times and higher perceptions of freedom of choice are both valued by consumers. However, the very simple stimuli used make generalizations to increased numbers of brands problematic.

I have two comments on problems with the study. First, the authors, like many previous researchers, do not present the Hendrick, Mills, and Kiesler (1968) study accurately. Hendrick et. al, did not define an overall concept of choice set complexity. Rather, they noted that number of alternatives and complexity of each alternative (number of dimensions emphasized) were related to choice time. The present study thus uses number of alternatives, and not complexity as defined by Hendrick et. al. In fact, complexity in the Hendrick et. al, sense seems quite low for the Walton and Berkowitz study. In addition, Hendrick, Mills, and Kiesler's data do not show an inverted U relationship between complexity and decision time (and in fact neither Hendrick et. al, nor Walton and Berkowitz investigate such a relationship). Hendrick et. al, found that when only one dimension of the alternatives was considered (low complexity), time to choose among four attractive alternatives was significantly longer than choice time for a set of two attractive and two unattractive alternatives. When many dimensions were stressed (high complexity), these choice times were not significantly different.

A second potential problem concerns the finding that subjects drank more in the two flavor, two pitcher condition, a finding the authors attribute to complexity. However, as noted above, the authors did not vary complexity, but number of alternatives. In addition, number of different alternatives does not order the 2 flavor, 2 pitcher and 2 flavor, 1 pitcher findings (which differ in direction although the difference apparently only approaches significance). These findings seem more readily explained by noting that subjects may not feel right about drinking a lot if only one pitcher is available, but may feel more comfortable in doing so if they see two pitchers are there. This form of subject evaluation apprehension may compromise the internal validity of the experiment.

Decision time and choice freedom are worthy of further research. I would encourage examining these variables in more complex choice tasks.


Construct Definition, Construct Measurement, and Theory Development

Two major issues arose in the above discussion: problems related to construct definition and measurement and theory development, and some areas of interest for future research. Each of these topics is considered below.

Construct validity appears to be a major problem in consumer choice research. In particular, many, if not most, constructs used in consumer choice research are not rigorously defined. For example, constructs such as conflict, information search, information, perceived risk, novelty, and so on are typically not carefully delimited and differentiated from other related constructs. This lack of specificity of course makes it very difficult to determine whether a particular operationalization does or does not correspond to the construct. Such correspondence must be assessed to evaluate the strength of any test of a theory involving that construct, however (Calder, Phillips, and Tybout, 1978). Hence, one major priority for research on choice is to carefully define any constructs used in building theories. Given such construct definition, multiple measurements of each construct are desirable. Recent approaches to assessing reliability and construct validity for such multiple measurements within a structural equations framework seem highly appropriate (Bagozzi, 1978). In addition to definition and measurement of constructs, development of theory is important to progress in research on choice. Specification of particular propositions relating constructs of interest and examination of these propositions within the framework of an overall network of relationships is crucial (Bagozzi, 1977, 1978).

Priority Areas for Research on Consumer Choice

Some priority areas for research were noted above; conflict and conflict resolution strategies; information search; studies of factors which influence decision time; and perceptions of product stimuli. There are several other currently underresearched topics which seem extremely promising for extending our knowledge of consumer decision making processes in different directions than those just mentioned: memory; detailed analyses of consumer responses to information; uses of verbal report data on choice processes; and investigation of process measurement methods.

Memory.  Research on consumer memory has been a neglected area of study. However, it has become increasingly clear that what is in consumer memory must be examined to study such phenomena as information search, encoding of stimuli, the inferences made by consumers, and so on. (Bert-man, 1978; Olson, 1978b). One area of particular interest is how consumers organize information in memory, what chunks, schemas (Markus, 1977), or scripts (Abelson, 1976) are available to them. The specific inferences by consumers from product stimuli, advertising, word of mouth, and other product-related information may be heavily dependent on what data are in memory and how those data are organized (e.g., Olson, 1978a). In addition, knowledge of how memory is organized can lead to more effective presentation of information to consumers, if the organization of that information is made congruent with the organization of memory. A major research problem in this area is how to measure such constructs as schemata and scripts. In part, this problem stems from incomplete specification of these notions. For some promising attempts, see Markus (1977) and Clary, Tesser, and Downing (1978).

Detailed Analyses of Consumer Responses to Information. There has been increased interest of late in detailed examination of consumer responses to communications. In particular, the cognitive response approaches introduced by Wright (1973) are being used by more researchers (e. g., Sternthal, Dholakia, and Leavitt, 1978; Edell and Mitchell, 1978; Olson, Toy, and Dover, 1978) to test theoretical notions about how persuasive communications impact consumers. One priority for research in this area, therefore, is to develop such detailed propositions for empirical test. A second promising approach might be to use cognitive response methods to study consumer response to other stimuli. For example, cognitive responses could be elicited to probe consumers' reactions to actual experiences with a product. That is, a consumer might taste or use a product and immediately thereafter be asked to list the thoughts and reactions they had during this usage experience. Such approaches might lend insights into such important and unresearched issues as how consumers learn by forming inferences from consumption outcomes; what types of plans or instructions to themselves consumers generate based on usage experience; and how consumers integrate the information they gain from product communications and actual usage experiences.

Uses of Verbal Report Data on Choice Processes. Recently there has been some concern over what can be learned from verbal report data on choice processes. In particular, Nisbett and Wilson (1977) argue that subjects are largely unaware of their choice processes and cannot report accurately about them. This conclusion, if correct, would have serious implications for methodology in choice research (e.g., for the cognitive response research noted above). However, the Nisbett and Wilson conclusions may be overstated. Ericsson and Simon (1978a, b, c), in a masterful series of papers, outline the types of verbal data on cognitive processes that are likely to be most useful. Using an information processing framework, Ericsson and Simon argue that some internal states and intermediate steps in processing are available in subjects' memories. They argue further that subjects can accurately report these internal states and processing steps from short-term memory if concurrent protocols are taken (i.e., while the subject is performing the task of interest). Such protocols should be more accurate under general instructions to verbalize rather than under instructions to produce specific information (Ericsson and Simon, 1978a, b).

Retrospective questioning about choice processes should be more accurate when general instructions to verbalize are used (as in most cognitive response studies); when the time between process and verbalization is short; and when subjects are simply asked to report the information attended to and intermediate results they remember, rather than to report information requiring inference on the part of the subject (i.e., How did you make a choice?) "We think it very important to distinguish direct verbalization of internal states from verbalizations that are partly or primarily the results of intermediate processes like abstracting, inference, search for prototypic examples, and so on. If the aim of probing is to collect verbal data on the internal states of the cognitive processes under study, it should be the object of a verbalization procedure to keep the intermediate processes at a minimum." (Ericsson and Simon, 1978c, p. 13).

Thus, verbal report data on choice processes should be collected with general instructions to verbalize, preferably concurrently with choice, but as temporally close to choice as possible in any case. Such data might then be coded with respect to the types of information attended to, intermediate results, or other internal states that are revealed.

Process Measurement Methods. A final important area for research is study of the properties of various methods for investigating choice processes. Process methods may have non-obvious biases (e.g., see Arch, Bettman, and Kakkar (1978) for biases in information display board methods), and most process methods now available are very time-consuming and yield data which are difficult to analyze. New methods which are more efficient would be desirable. Research should also be carried out on methods such as eye movement analysis and response time analysis (Russo, 1978) to ascertain their usefulness for consumer choice research.

There is thus an array of exciting research questions on consumer choice to be investigated. By paying careful attention to construct and theory development and to appropriate use of process measurement methods, significant advances in our understanding of consumer choice processes should result.


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