Consumer Inference As Part of Product Comprehension
ABSTRACT - Most consumer research has studied inference-making as a process of "filling in" missing information about a product attribute in order to evaluate a product, or choose among alternative brands. We examine the limitations of this approach, present an expanded view of inference formation as part of the product comprehension process, conceptualize consumers' product-related inferences in terms of the levels of means-end knowledge, and make suggestions for future research.
Citation:
Timothy R. Graeff and Jerry C. Olson (1994) ,"Consumer Inference As Part of Product Comprehension", in NA - Advances in Consumer Research Volume 21, eds. Chris T. Allen and Deborah Roedder John, Provo, UT : Association for Consumer Research, Pages: 201-207.
Most consumer research has studied inference-making as a process of "filling in" missing information about a product attribute in order to evaluate a product, or choose among alternative brands. We examine the limitations of this approach, present an expanded view of inference formation as part of the product comprehension process, conceptualize consumers' product-related inferences in terms of the levels of means-end knowledge, and make suggestions for future research. INTRODUCTION Inferences are important for understanding consumer behavior. Unfortunately, the dominant approach to studying consumers' inferences has been extremely narrow and has not produced a good understanding of the inference formation process or the types of inferences consumers form. Most consumer research has studied inference-making as a process of filling in missing information about a product attribute in order to evaluate a product, or choose among alternative brands. In this paper, we examine the limitations of this approach. We present an alternative perspective that views inference formation as an integral part of comprehension processes involved in interpreting or making sense of product information. From this perspective, inferences are formed whenever consumers comprehend product information, even when there is no obviously missing information to be filled in. We conclude the paper by identifying several issues for future research suggested by our approach. THE MISSING INFORMATION PARADIGM Most of what consumer researchers know about consumer inference has been learned through laboratory experiments based on the "missing information paradigm." In this approach, derived from social psychology, researchers manipulate the amount and type of information given to subjects. In the typical consumer inference experiment, subjects evaluate several brands described by a small set of product attributes (often only two or three). The experiment is set up so that some information is obviously "missing." Some brands are completely described in terms of the two or three attributes under study, while other brands are partially described by a subset of these attributes. The usual goal of this research is to determine whether consumers formed inferences about the "missing" attribute. To do so, researchers compare subjects' brand evaluations made under the complete and missing information conditions (Ford & Smith 1987; Huber & McCann 1982; Johnson & Levin 1985; Lim, Olshavsky, & Kim 1988; Simmons & Lynch 1991). Differences in overall evaluations are attributed to the inferences subjects supposedly made about the "missing" attributes. Typically, only these missing attribute inferences are considered. We believe this view of consumer inference as filling in missing information about specific attributes has produced a limited understanding of (1) the types of product-related inferences consumers form, (2) the circumstance under which consumers form inferences, and (3) the role of prior knowledge in consumers' inference processes. What Types Of Inferences Do Consumers Form? In most inference studies, researchers specify a priori the product attribute(s) about which consumers are presumed to form an inference (Huber & McCann 1982; Kardes 1988; Simmons & Lynch 1991). Typically, these are the experimentally manipulated "missing" attributes. However, even when researchers have included inferences about product attributes other than those for which there was "missing information," they usually restricted their analysis to inferences about other product attributes. For example, Sujan and Dekleva (1987) had subjects read an advertisement for a product and list the features they thought the product might possess (some of these features probably were inferences). But, because subjects were directed to report attributes or features, they may not have reported inferences about more abstract, product-related meanings such as what end states, values, or goals the product may help them achieve. Other researchers have used more "open" thought listing instructions ("describe what you are thinking about while evaluating these brands"), but they often coded these protocols for inferences about only product attributes (Simmons & Lynch 1991). In one exception, Gardial and Biehal (1986) asked subjects to freely verbalize their thoughts into a tape recorder while choosing between three advertised cameras. In addition to inferences about product attributes, the authors found that subjects formed inferences about product benefits and appropriateness for various users and situations. In fact, less than half of subjects' inferences concerned product attributes. Such results suggest that consumer researchers have not examined many types of inferences consumers may form while evaluating products. For instance, consumers could make inferences about various attributes or features of a product, how a product works, its uses, its relationship to other products, its appropriateness for certain users or situations, and even its ability to help consumers achieve their goals and values. Consumer researchers need to adopt a broader view of consumer inference that includes these types of product-related inferences. When Do Consumers Form Inferences? The missing attribute paradigm used in most consumer inference research seems to imply that consumers form inferences only if they recognize that information about an important attribute is missing (Gardial & Schumman 1990; Huber & McCann 1982). Otherwise, consumers are presumed to use a decision strategy that uses only the available information and does not include inferences (e.g., Burke 1990). In contrast, we do not see inferences as unusual events that occur only in special circumstances. Rather, we propose that consumers form inferences whenever they comprehend or interpret product informationCeven if there is no obviously "missing information." To date, however, researchers have not examined the inferences consumers form during ordinary comprehension of product information. We need a conceptual framework for studying consumer inference that accounts for natural inference formation processes. How Does Prior Knowledge Influence Consumers' Inferences? Consumers use their prior knowledge activated from memory to form inferences, and different types of inferences require different types of knowledge. Unfortunately, the missing attribute paradigm has focused researchers' attention on how consumers' knowledge effects only attribute inferences. Some research suggests that greater product familiarity and expertise (more product knowledge) is positively related to forming attribute inferences. Kardes, Sanbonmatsu, & Herr (1992) explain this in terms of the missing information paradigm by proposing that the knowledge structures of relative experts contain stronger linkages between attributes, which makes experts more likely to notice the absence of attribute information (and thus more likely to form an inference about a missing attribute) than novices. We need a conceptual framework for studying consumer inference that recognizes the role of product knowledge in forming inferences about aspects of products besides just attributes. Summary In sum, past research within the missing information paradigm assumes that consumers form inferences about only specific product attributes for which there is obviously missing information. Little attention has been given to the effects of prior knowledge on other types of inferences besides attributes or features. To expand their vision of inferences, researchers need a broader conceptual framework from which to work. In the next section we develop such a framework to guide the study of consumers' product-related inferences. The framework suggests that consumers form many different types of product-related inferences while comprehending (interpreting) product information, even in situations with no obviously missing information to be filled in. COMPREHENSION PROCESSES In much past research, comprehension was viewed as the process by which a person arrives at the direct or literal meaning of a message. One can find remnants of this narrow perspective in research on comprehension and recall of advertising (Jacoby & Hoyer 1982). A more modern view, based on Bartlett's (1932) pioneering work on memory, treats comprehension as a constructive process of interpretation. Constructive comprehension means that people actively generate or form the knowledge, meanings, and beliefs that represent information in the environment. From this perspective, "meaning" does not reside in the text of a message. Rather, people draw on their prior knowledge to actively construct, or create the meaning of a message (Bransford, Barclay, & Franks 1972). Inferences and Comprehension Most of the meanings that people construct during comprehension are inferences that "go beyond" the information given. People form inferences to construct more complete and more coherent meanings than is possible by only representing the literal information given. Evidence for inferences made during comprehension has come from examining the distortions subjects made in interpreting the information that was originally given to them. Bartlett (1932), for instance, found that subjects did not remember a story as an exact copy of the original text. Rather, subjects comprehended the information by forming inferences that transformed the original information. Researchers have also shown that people do not remember given information verbatim, indicating that the knowledge created during comprehension and stored in memory is not a literal representation of the presented information. Thus, people often cannot distinguish the constructed set of meanings they created largely through inferences from the information that was presented to them (Bransford, Barclay, & Franks 1972). Inferences and Prior Knowledge During comprehension, incoming (new) information is interpreted in terms of prior knowledge activated from memory. The activated knowledge acts as a filter or template to guide the interpretation of the new information (Black, Galambos, & Read 1984). The influence of activated knowledge on comprehension is illustrated in a classic study by Bransford and Johnson (1972). Two groups of subjects read a passage describing, in rather general terms, the tasks associated with doing laundry. One group was given a title, "Doing Laundry," along with the information, while the second group received no title. The group that saw the title rated the passage as more comprehensible and exhibited higher levels of recall. Apparently, the title activated subjects' "clothes washing" schema (the contents of which were not measured), and this knowledge enhanced subjects' ability to comprehend (interpret) the information in the passage and recall it later. Measuring Inferences During Comprehension Researchers have measured inferences during comprehension with a wide variety of tasks and materials; including simple sentences (Brewer 1977), complex sentences (Harris 1974), and brief stories (Johnson, Bransford, & Solomon 1973). One technique often used to demonstrate inferences during reading comprehension is the "false recognition paradigm." Many studies have found that subjects falsely recognize sentences which contain plausible inferences from the information that actually was presented (Johnson, Bransford, & Solomon 1973). A false alarm is taken to indicate that an inference had been formed during comprehension. Recently, researchers have recommended using concurrent (think out loud) protocols to directly measure the meanings inferred during comprehension. For example, Collins, Brown, and Larkin (1980) asked subjects to talk about the hypotheses they considered and rejected while reading a short text. Rumelhart (1984) asked subjects five questions (Who?, What?, Where?, When?, and Why?) after reading each new sentence of a story. These think out loud protocols are used to discover subjects' personal interpretations of the stories, including inferences, and how their interpretations change with each additional sentence. Recently, thought protocol methods have been used by consumer researchers studying advertising comprehension. Mick (1992) argued for an approach that measures the subjective meanings formed by consumers. This approach contrasts with the "traditional view" of advertising comprehension that used "objective" tests of recall for key advertised claims and implicitly assumed verbatim comprehension of message information. To study these personal meanings, Mick had subjects write down their thoughts after reading each new sentence of an advertisement. Many of these subjective meanings were probably inferences. The most widely used method for studying consumer inferences is the information integration methodology (or functional measurement) developed by Anderson (1982). In the typical consumer inference experiment, subjects evaluate a series of brands described by a small set of attributes. Some brands are completely described by all attributes under study, while other brands are partially described by a subset of these attributes. Researchers compare subjects' evaluations of the completely and partially described brands and draw conclusions (make inferences) about missing attribute inferences. For example, if subjects formed a less favorable evaluation about a partially described brand with missing information than a completely described brand (where that attribute was described as average or moderately desirable), the researcher would conclude that subjects inferred a below average value for the missing attribute. Unfortunately, information integration methodology has severe problems when measuring inferences. First, this approach does not directly measure whether inferences are actually formed. Second, the approach is designed to measure only a particular inferenceCthe value of a specific missing attribute. It does not measure other inferences subjects might form while evaluating the brands. Thus, researchers examining patterns of brand evaluations can conclude only that subjects evaluated the partially described brands "as if" they inferred a certain value for the missing attribute. PRODUCT COMPREHENSION PROCESS In the next section we integrate the ideas presented thus far into a conceptual framework that can guide future study of consumers' product comprehension and inference processes. A PROPOSED FRAMEWORK FOR CONSUMER INFERENCES The proposed framework is displayed in Figure 1. The framework treats product comprehension as a constructive process of interpreting product information in terms of activated knowledge and forming new product-related knowledge (meanings and beliefs). The product-related meanings produced during comprehension may be of two broad types. Consumers may form product-related beliefs that merely describe the product information given in the environment (Fishbein & Azjen 1975). For instance, a consumer may "see" that an advertised car is red and represent this as a descriptive belief, "this car is red." Inferential beliefs that go beyond the given product information also may be constructed. In addition to the belief, "this car is red," consumers might infer, "I will be noticed as I drive down the street in this car." Not all of the meanings consumers form while comprehending product information are necessarily related to products. For example, while considering a purchase, a consumer may comprehend, "it is very hot in this store," or "that salesman reminds me of my uncle." Consumer researchers tend to be particularly interested in the product-related meanings consumers form during comprehension of product information. The framework also shows that the meanings produced during comprehension (whether descriptive or inferential knowledge) may be integrated with prior knowledge structures in memory. Later, if activated, this knowledge may influence subsequent comprehension and inference processes, and so on, in a continuous, interactive process. The proposed model is not intended to be a theory of comprehension. Rather, it is a general, conceptual framework that identifies aspects of consumers' product comprehension and inference processes seldom addressed in previous research. Specifically, the framework highlights the role of activated prior knowledge and constructed meanings in the product comprehension process. Activated Knowledge The meanings or beliefs consumers form during comprehension are influenced by the knowledge activated at the time of comprehension. For example, Figure 2 displays knowledge concepts which might be contained in a consumer's schema for personal computers. This product-schema is rather elaborate, containing many different types of product knowledge. Some product knowledge concerns concrete computer attributes or features (two disk drives, hard drive, mouse, modem). Other product knowledge is more abstract, relating to overall quality and personally relevant consequences of using personal computers (can run many different programs, good for office or school work). The schema also contains self knowledge, including abstract personal goals, consequences, and values (spending time with family, experiencing feelings of accomplishment). Finally, some knowledge is not directly related to personal computers, and can best be described as general world knowledge (I learn quickly, Muzak is often played in offices). Attending to information about a personal computer may activate various parts of this knowledge from memory. The activated knowledge allows consumers to construct various types of product-related meanings by inferring a personal computer's attributes, benefits, negative consequences, situational appropriateness, and the abstract, self-relevant goals or values a computer might help them achieve. Means-End Inferences Recently, researchers have recognized that consumers may have product-related knowledge at different "levels" of abstraction. At relatively concrete levels, consumers possess knowledge about concrete product attributes and physical characteristics (features). Consumers also have knowledge about more abstract product benefits or consequences of product use, as well as highly abstract knowledge about their own personal goals or values. This knowledge can be modeled as a simple associative network called a "means-end chain" (Gutman 1982). Generic means-end chains linking product-related meanings at various levels of abstraction are of the following form: Attributes -> Consequences -> Values Means-end chain models of product knowledge are useful in understanding consumer inferences. "Giving meaning to a particular brand, defined by specific attributes, essentially depends upon what higher order, more personal elements the defining brand attribute(s) are linked to" (Reynolds & Rochon 1991). During product comprehension, consumers may construct inferential beliefs that certain product attributes are the causal means to achieving desired ends such as product benefits, or even personal goals or values. The means-end inferences formed during comprehension are guided by means-end knowledge activated at the time of comprehension. Consider an advertisement stating that a new brand of personal computer has two disk drives and a modern. To comprehend (interpret) this information, a consumer might activate a product-schema for personal computers similar to the one displayed in Figure 2. As previous research suggests, the consumer might infer other attributes such as a hard drive and a mouse. The consumer might also infer meaningful, personally relevant relationships between the advertised attributes and more abstract product-related meanings. Notice that within this product-schema attributes are associated with higher level meanings to form means-end chains. If this knowledge is activated, the consumer might form inferences about concepts similar to those contained in these means-end chains. The consumer may interpret the information about the modern by inferring consequences such as, "I can work at home," and "I can spend more time with my family." One would hypothesize that a meaningful association was formed in memory between buying the computer and the value C spending time with their family. Similarly, consumers may interpret the information about the two disk drives by inferring a means-end sequence of consequences: "that means it can run many different programs," "that would be great for my school work," "I could get better grades," and "I would feel like I had accomplished something." Note the differences between this view of consumer inference and the predominant view presented in past research. Rather than conceptualizing inferences as filling in missing information about a specific attribute, inferences are seen as an integral (and natural) aspect of the comprehension process of constructing coherent product meanings. To construct personal interpretations of what products mean to them, consumers may infer meaningful, personally relevant associations between a product's attributes and its uses, consequences, appropriateness to various situations and users, and even personal goals or values. Next, we discuss how the proposed conceptual framework differs from past research in terms of (1) when inferences are formed, (2) whether forming inferences is an automatic or controlled process, and (3) whether all consumers form the same inferences during product comprehension. When Are Inferences Formed? As a result of equivocal findings concerning spontaneous missing attribute inferences, researchers have assumed that consumers form inferences only when they notice that information about an important attribute is obviously missing from a brand description. While this assumption may apply to missing attribute inferences, it may not generalize to all types of inferences. The current framework proposes that consumers may form inferences whenever they comprehend product information. Inferences may be formed while comparing two or more brands, as well as evaluating a single brand for which there is no competitive context to create "missing information." In an experimental context, this means that subjects might form inferences while evaluating completely described brands as well as partially described brands. Is Inference Formation An Automatic Or Controlled Process? Past research following the missing information paradigm implicitly assumes that inference formation is an intentional, controlled, effortful process. Burke (1990), for example, suggested that consumers form inferences only when the value of more knowledge exceeds the effort (cost) to form the inference. The current framework proposes that inferences can be either automatic or controlled. The automaticity of inference formation is a function of the strength of learned associations between related concepts in memory. The more often consumers activate associations between related concepts, the stronger these associations become, and the more quickly activation spreads between them to form inferences automatically and effortlessly. If cognitive associations between concepts are not strong or frequently activated, inference formation is likely to require cognitive effort. For example, consumers' product knowledge for cars probably do not contain strong linkages between different brands and their associated yearly maintenance costs. Therefore, inferring the yearly maintenance costs for a certain brand is likely to require considerable cognitive effort and deliberation. On the other hand, consumers' car schemas may contain strong associations between a car's size and its comfort. If so, consumers can quickly and effortlessly infer that a particular small car is uncomfortable. Do All Consumers Form The Same Inferences? In nearly every past study, researchers identified a priori the specific inference(s) to be measured (usually a belief about a product claim or attribute). For example, studies following the missing information paradigm focused only on inferences about the missing information. We know, however, that inferences are highly influenced by existing knowledge in memory that is activated in the situation. Since no two consumers have exactly the same knowledge (product-schemas) it is not likely they will form the same inferences. In fact, consumers may not form the inference identified a priori by the researcher, but still form other types of inferences. DIRECTIONS FOR FUTURE RESEARCH The proposed framework views inference formation as a natural aspect of comprehension processing. This perspective offers a number of issues for future research, including the extent to which inferences are formed during product comprehension, the types (levels of abstraction) of product-related inferences consumers form, and the effects of different types of inferences on consumers' attitudes and purchase intentions. Unfortunately, past consumer inference research has been narrowly focused on missing attribute inferences. Therefore, we lack the theoretical perspective and empirical results to support precise hypotheses and predictions about inference formation in natural situations and settings. At present, we need exploratory, theory-building studies based on the framework presented here. Such research can generate empirical data from which more specific research issues, questions, and hypotheses can be developed and tested in subsequent research. For the most part, past research has examined the inferences consumers form based on relatively "simple" attribute information presented in highly artificial experimental contexts. Future research should examine the product-related inferences consumers form during comprehension of more complex product information similar to that found in real-world marketing communications (ads, brochures, sales presentations). Perhaps, experiments in natural settings that do not narrowly focus consumers' attention and comprehension processes on a small set of attribute information will reveal that many product-related inferences concern abstract, self-relevant consequences of product use. A means-end chain perspective suggests that consumers are more concerned with what products can do for them, than with their physical attributes and features. This may be especially likely for actual purchase decisions rather than simple product evaluation tasks (often used in consumer research) that have limited consequences. Past research has demonstrated that positive inferences about product attributes are positively related to consumers' brand attitudes (cf. Kardes 1988). This would be expected from any multiattribute attitude model such as Fishbein's. However, consumer researchers have not yet examined how inferences about more abstract self-relevant product consequences influence consumers' attitudes. Perhaps, inferences about self-relevant product consequences have a greater effect on consumers' brand attitudes and purchase intentions than inferences about concrete product attributes. Researchers have suggested that consumers should be more persuaded by what products can do for them, than their physical attributes and features (Macinnis & Jaworski 1989). Researchers also need to examine the key factors that influence the amount and types of inferences consumers form during product comprehension. The two most important influences are product knowledge and involvement. Prior research has found that higher knowledge consumers consider attribute information more useful and informative, whereas lower knowledge consumers consider information about more abstract benefits to be more useful and informative (Maheswaran & Sternthal 1990). Gardial & Biehal (1986) found that compared to novices, experts formed more inferences about concrete attributes, but fewer inferences about more abstract self-relevant product consequences. Our framework suggests, as consumers gain product experience, they learn meaningful associations between product attributes and corresponding consequences. More expert consumers, who have well-developed means-end chains in memory, can use this knowledge to form inferences during comprehension of product information. Thus, compared to novices, experts may be more likely to infer means-end associations between attributes and consequences or benefits. Many researchers, while not setting out to do so, have studied cognitive processes that would be considered inference formation within the current framework. For example, researchers studying decision making have used concurrent verbal protocols to measure the meanings or beliefs consumers form in choosing among products. Many of these beliefs are inferences. For instance, research on substitution-in-use has examined consumers' perceptions of product similarity and typicality for various use occasions (e.g., Ratneshwar & Shocker 1991). Two products may be perceived as similar because consumers believe they are both means to achieving a desired goal within a specific usage situation. These beliefs are inferences. As another example of inferences in other research contexts, consider Johnson's (1984) studies of noncomparable alternatives. Johnson examined the level of abstraction consumers use when making choices among different product categories. The less comparable the alternatives, the more abstract the concept consumers use in comparing them. Thus, consumers can choose between two television sets based on price, but choose between a new television set and a vacation based on a more abstract consequence such as the entertainment value of each. These beliefs about abstract consequences are inferences. A final example of inferences in other contexts is given by research on the Elaboration Likelihood Model that examined the effects of level of involvement on the types of cognitive responses consumers form in response to persuasive messages (Petty, Cacioppo, & Schumman 1983). Many of these cognitive responses are inferences. Consumers who are more involved with a particular product or decision situation, are likely to be more motivated during comprehension to interpret the relevant information (Celsi & Olson 1988). Thus, they may form more inferences than consumers who are less involved, and their inferences are likely to be more self-related (more personal consequences). This may help to explain why attitudes formed via central route processes by highly involved consumers are more enduring and more predictive of behavior than attitudes formed through peripheral route processes by less involved consumers. To obtain a deeper understanding of consumers' inferences, researchers will have to develop new methods for measuring the outcomes of consumers' comprehension processes. We have shown that the information integration methodology has limited utility for understanding consumers' inference processes. Verbal thought protocols have more promise, but we need to develop coding schemes that are sensitive to inferences of varying types. The mean-end chain of attributes, consequences, and values can provide such coding categories. Inference researchers should also consider other methods for measuring inferences such as personal interviews to follow up on verbal protocols. In a personal interview, researchers can follow up and "probe" to clarify the often cryptic meaning of the thought listings. For instance, researchers can probe to clarify the meaning of protocols (Experimenter: "What were you thinking about when you wrote modem? Subject: "Since this brand has all these other attributes, it probably also has a modem"). Interviews can identify additional inferences not mentioned in verbal protocols (Experimenter: "When you were reading this ad were there any other thoughts you had that you did not write down? Subject: "Yes, I was thinking about how this brand of computer has a color monitor I could use to make color graphs for my class projects."). Interviews can also be used to determine linkages between concepts identified in verbal protocols (Experimenter: "You wrote down homework and grades, what did you mean by that?" Subject: "Because this computer is small and has a modem, I could use it in my dorm room to do my homework, and thus get better grades."). Of course, probing interviews may be better suited for identifying the types of inferences consumers form, not whether consumers spontaneously form these inferences during product comprehension. CONCLUSIONS In conclusion, researchers interested in consumer inferences should abandon the narrow view that inferences are formed only by filling in missing information about a specific attribute. Rather, we recommend that researchers adopt a broader view of consumer inference as an integral and ubiquitous aspect of general product comprehension. 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Authors
Timothy R. Graeff, Middle Tennessee State University
Jerry C. Olson, Penn State University
Volume
NA - Advances in Consumer Research Volume 21 | 1994
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