The Role of Prior Product Experience in Organizational Buying Behavior

Vicky L. Crittenden, Harvard University
Carol A. Scott, UCLA
Rowland T. Moriarty, Harvard University
ABSTRACT - The current research examines some of the variables typically measured by organizational buying behavior researchers (e.g., attribute importance, number of potential vendors) and shows how one information processing variable, experience, relates to these measured variables. While all outcomes were not statistically significant, the results tend to support the enrichment hypothesis frequently examined by consumer behavior researchers. The more experienced buyer tended to have a larger evoked set, have a larger number of vendors in the final consideration set, possess a larger number of selection criteria, and better discriminate among potential suppliers.
[ to cite ]:
Vicky L. Crittenden, Carol A. Scott, and Rowland T. Moriarty (1987) ,"The Role of Prior Product Experience in Organizational Buying Behavior", in NA - Advances in Consumer Research Volume 14, eds. Melanie Wallendorf and Paul Anderson, Provo, UT : Association for Consumer Research, Pages: 387-391.

Advances in Consumer Research Volume 14, 1987      Pages 387-391


Vicky L. Crittenden, Harvard University

Carol A. Scott, UCLA

Rowland T. Moriarty, Harvard University


The current research examines some of the variables typically measured by organizational buying behavior researchers (e.g., attribute importance, number of potential vendors) and shows how one information processing variable, experience, relates to these measured variables. While all outcomes were not statistically significant, the results tend to support the enrichment hypothesis frequently examined by consumer behavior researchers. The more experienced buyer tended to have a larger evoked set, have a larger number of vendors in the final consideration set, possess a larger number of selection criteria, and better discriminate among potential suppliers.


The role of prior experience (e.g., product knowledge, product familiarity) in information processing has become a major topic of investigation in the cognitive sciences (Chi, Glaser and Rees 1981; Larkin et al. 1980), and in recent years has received increased attention from consumer researchers. Prior experience, or more generally, some type of feedback mechanism from purchase experiences, has been included in traditional models of consumer behavior (cf. Bettman 1979; Hansen 1972; Howard 1977; Howard and Sheth 1969). More recently, several experimental studies have examined the relationship between prior experience and consumer choice processes (e.g., Sudan 1985; Beattie 1981; Johnson and Russo 1981, 1984). In these studies differences in "experts" and "novices" information processing strategies have been observed.

Interestingly, however, the research on prior experience has not been as pervasive in the area of organizational buying even though effects of experience, if observed in this context, could be extremely important to organizational sellers. Organizational researchers have distinguished among the different types of buying decisions, such as new task, modified rebuy, and straight rebuy (Robinson, Faris, and Wind 1967; Lehmann and O'Shaughnessy 1974) relating the newness of the problem to the organization with information requirements and to the consideration of alternative sources of supply. However, these researchers have not examined differences in information processing strategies based upon the individual's experience in purchasing the product (regardless of the particular type Purchase for the organization).

The research reported here seeks to contribute to our knowledge of organizational buying processes by examining the relationship between the prior purchase experience of organizational buyers and several information processing variables typically measured by organizational buying behavior researchers (cf. Moriarty and Galper 1978; Moriarty and Spekman 1984). In addition, it also contributes to the general literature on the effects of prior experience. It may be easier to study and detect differences due to prior knowledge or experience in organizational purchasing decisions because they often involve more complex products that require more information processing in general, and because they often take place over a longer period of time than consumer decisions (cf. Ames and Hlavacek 1984; Cyert, Simon and Trow 1956). Experience here may be more of an advantage than in consumer settings.


Two views of how prior knowledge affects information processing have been put forward in the consumer behavior literature. In the first, it is hypothesized that consumers highly familiar with a product will engage in less search for information than consumers unfamiliar with the product. Highly familiar consumers are more likely to know specific facts about existing alternatives, and therefore would not need to gather additional information. Paradoxically, according to this "inverted-U" hypothesis, consumers very unfamiliar with the product would also engage in little search. For them, however, more than a little search is too difficult and cognitively taxing. Consumers who know a moderate amount about the product would engage in the most search because they have the ability to handle the incoming information and have a motivation to acquire more.

Bettman and Park (1980), for example, used the inverted-U 5 hypothesis to interpret findings regarding the effects of | experience on the types of information processed (e.g., prior information and attribute evaluations) and the processing heuristics used (e.g., processing by attribute or by brand, comparisons to standards). In this research, the moderate experience group did more processing of currently available information and relied less on prior knowledge than did the high and low experience groups. Similarly, Johnson and Russo (1981, 1984) found that moderately experienced subjects asked to make a product choice recalled more statements about the product than ; subjects with either high or low experience, perhaps indicating greater attention to, or use of, information.

According to a second hypothesis, however, knowledge about a particular product facilitates learning new information. Highly familiar consumers should be able to encode information about additional alternatives more efficiently and thus may tend to gather more information than consumers not familiar with the product.

Support for this "enrichment" hypothesis that existing knowledge facilitates learning new information has also been found. In a complex usage situation, Brucks (1984) found that knowledge increased search efficiency by allowing faster recognition of poor or inappropriate alternatives and facilitated the asking of questions about attributes of the alternatives. And, Johnson and Russo (1984) report a linear effect in the levels of recall as a function of prior experience when subjects were asked to form a judgment about each product.

Despite the as yet unresolved differences between these two views, the research into the impact of prior experience on decision-making behavior has helped produce a better understanding of the nature of consumer buying behavior. In organizational buying behavior contexts, however, little attention has been paid to variables affecting the processing of information by members of the buying center, with the exception of studies on the sources of information used (Moriarty and Spekman 1984; Sheth 1973; Kelly and Hensel 1973; Ozanne and Churchill 1968), and information as a means of risk reduction (Webster and Wind 1972). Thus, the current study borrows heavily from the research on consumers in order to investigate the effects of prior purchasing experience on information-processing strategies employed by organizational buyers. An implicit assumption, then, is that organizational buyers will be subject to the same cognitive limitations and strategies as end use consumers.


Hypotheses regarding the effects of experience on industrial/organizational buyers were derived from the theory and research on this topic in consumer behavior. Specifically, the inverted-U and the enrichment hypotheses formed the basis for predictions regarding four dependent variables:

1. More experienced buyers will include more alternate vendors in their evoked set, i.e. the set that first came to mind when they were initially faced with the decision, than less experienced buyers.

2. More experienced buyers will include a smaller number of vendors in their final consideration set than less experienced buyers.

3. More experienced buyers will consider a larger number of attributes when waking a purchase decision than will less experienced buyers.

4. More experienced buyers will perceive greater differences between alternatives than less experienced buyers.

As in previous consumer studies, prior experience in making these kinds of purchase decisions should result in a greater awareness of, and knowledge about, alternatives. This greater knowledge base will be reflected in the number of alternatives that initially come to mind when facing a purchase decision, in the number of attributes perceived to be important, and the distinctions made between alternatives on those attributes. On the other hand greater knowledge or experience should make it easier to recognize and disregard inappropriate alternatives. Thus, more experienced buyers may ultimately consider only a few alternative vendors. Less experienced buyers' final consideration sets may be larger because they are less able to evaluate and disregard inappropriate alternatives they become aware of in their decision process.


Data was collected from decision-making units (DMUs) in approximately 300 organizations that had made major procurements of nonintelligent data terminals within the previous 24 months. These organizations represented a stratified random sample of Dun & Bradstreet companies including five industry sectors (manufacturing, business services, transportation, finance, and wholesaling/retailing) and three size classifications (100 to 249 employees, 250 to 1,000 employees, and more than 1,000 employees). For purposes of the larger study of which this was a part, a telephone snowballing technique was used to identify all participants in the decision to buy the terminals. Questionnaires were sent to all decision participants who agreed to cooperate with the study.

Analysis for the current study is based on the responses of 455 individuals involved in the buying process for 319 organizations. To be included, a respondent must have reported that he/she played at least a somewhat important role in the search process, the vendor and product evaluation process, and the vendor selection process. For example, an individual who was very involved in the initial vendor search process but not involved in the final selection of vendors w not included. Thus, our sample consists of individuals who were involved in the entire process, and not just a part of it. [Other analyses were conducted with more stringent definitions (of both experience and role) to test the sensitivity of the results to sample definition changes. While the statistical results varied slightly due to different inclusion rules, the direction of the mean responses were consistent throughout.]

Independent Variable

The independent variable in this study was the amount of prior experience the individual had in making major data terminal procurement decisions. Past experience with the product per se was not of interest, but rather the cognitive structures that were presumably caused by having been previously involved in purchasing data terminals defined the product-related experience. Of concern were the number of major data terminal system procurement decisions the individual had participated in during his/her career (not just in the current firm). As such, years of employment, years of experience in the company, length of time in a position, or position title were not reliable measures of prior experience. In addition, since participation in such a major purchase as data terminals is generally not considered to be an everyday occurrence, it was felt that the individual respondents would be able to accurately recall prior participation.

Three experience groups were created: the low prior experience group individuals reported participation in one or no previous decisions; moderate prior experience subjects had participated in two or three previous decisions; high prior experience group members had participated in four or more decisions. Three groups are the minimum needed to detect any curvilinear relationship between experience and the dependent variables and the maximum allowed by the variability in the experience measure in this sample.

Finally, an analysis was conducted to determine whether experience, as measured in this study, was related to or confounded with the position of the respondent in his/her company. A one-way analysis of variance showed no significant differences in experience as a function of position in the company.

Dependent Measures

Four dependent measures were examined separately: the number of vendors respondents reported to be in their initial evoked sets, the number of vendors he/she reported as being in the final consideration set, the importance ratings for 33 product and vendor attributes, and ratings of the degree of difference between vendors on the same attributes. For the first of these, respondents merely were asked how many possible suppliers came to mind when they first became aware of the company's needs. For the second measure, respondents were asked how many vendors there were during the final stages of selection. Ratings on 6-point Likert scales for 33 attributes formed the last two measures. For each attribute, the respondent rated its importance and the degree of difference among suppliers in the industry on that attribute.


Separate analyses of variance were used to test each hypothesis. The independent variable in each instance was the respondent's experience (low, moderate, high). When significant overall differences were found, Spjotvoll-Stoline tests (Kirk 1982) for paired comparisons were conducted to determine the location of the difference.

Number in the Evoked Set

The first hypothesis proposed that the more experienced industrial buyer would include a greater number of alternative vendors in h$s/her evoked set when faced with a purchasing decision. The analysis of variance revealed a significant effect of expertise (F = 11.043, p < .05). As shown in Table 1, the more inexperienced the purchaser, the smaller the size of the evoked set. Pairwise comparisons revealed significant differences between the low and high groups and between the moderate and high groups ( Z - .05). The difference between the low and moderate groups was not significant. However, the absolute value of the difference between these means was .82 while the critical difference that the pairwise comparison had to exceed to be declared significant was .83.

The results of this analysis demonstrate the potential influence that prior knowledge exerts on organizational buying behavior. It is not surprising that the more experienced buyer could call to mind more potential vendors when he/she first becomes aware of the company's needs. The person who has had more experience with vendors and has gone through the search process a few times is probably more aware of the vendors who offer the needed equipment.



Size of the Final Consideration Set

As suggested by the second hypothesis, it seems likely that the more experienced purchaser would be able to quickly eliminate inappropriate vendors and would consider seriously only a small number of vendors when making the final decision. The inexperienced purchaser may have a difficult time eliminating vendors due to a lack of prior knowledge pertaining to equipment or services offered and would tend to obtain the needed information from several vendors.

Contrary to our expectations, the more experienced purchaser had a much larger number of potential vendors in the final consideration set. While the overall hypothesis of equity of means could not be rejected (F = 1.755), the average size of the final consideration set became larger with increased experience (see Table 1). In fact, the experienced buyers included a larger number of alternatives in their final consideration set than in their initial evoked set, while the opposite was true for the inexperienced buyers.

These results are consistent with the "enrichment" hypothesis--greater prior knowledge facilitated the collection of more knowledge. The purchase of nonintelligent data terminals might be considered a complex usage situation, and these results would lend support to findings that knowledge increased search efficiency (Brucks 1984). The more inexperienced buyers may know so little about product attributes and about different companies that they have difficulty evaluating alternative suppliers.

Our results in this particular context also suggest that risk may be an important element in the buyer's task environment. An inexperienced buyer may perceive the purchase decision as riskier than an experienced buyer, and thus may narrow his/her search to only a few well-known suppliers. In the context stud ed here, inexperienced buyers may have relied more on IBM, and felt less able to evaluate other, perhaps riskier choices. Thus, future research will be needed to determine if these differences between experienced and inexperienced buyers persist when there is less risk, or when there is not a dominant supplier.

Number of Important Attributes

Buyers familiar with the particular product class were expected to use more evaluative criteria in making a product choice (Beattie 1981; Scrull 1983). While the more experienced buyers in the current study considered a greater number of attributes to be important than did the other groups (Table 1), the overall analysis of variance was not significant (F = 1.803).

The list of product attributes was based on initial research on the data terminal industry and on a review of several private studies conducted within the data terminal industry. For all but five attributes, over 60 percent of the respondents rated the attributes 4,5, or 6 on the importance scale of 1 (unimportant) to 6 (very important). For example, 99.1 percent of the respondents replied that the "reliability of the product" was important (i.e., a 4 5, or 6 on the measurement scale). Unfortunately, the list of attributes may have been skewed too much towards obviously important things, and respondents were not forced to prioritize them or make any kind of trade-offs among them. Thus, the lack of significant effects on attribute importance may be due to too little variability in the dependent measure, or to the fact that many attributes are important in organizational buying situations but few are deterministic.

One review of organizational buying behavior has suggested that experienced purchasers emphasize price more than inexperienced purchasers (DeBruicker and Summe 1985). In the current study, the five attributes receiving the lowest importance ratings were: lowest price, vendor's willingness to negotiate price, vendor offers large volume discounts, vendor visibility among top management people, and the aesthetics of the product (style, design, color, size). Since three of the five attributes receiving low importance ratings dealt in some way with price, future analysis should seek to determine whether there is a difference among buyers with respect to the level of experienCe and a reduced set of macro-attributes.

Vendor Differences

Consumer research has suggested that inexperienced buyers tend to perceive fewer distinctions among suppliers on product attributes than do the more experienced buyers (cf. Beattie 1981). The fourth hypothesis proposed just such a finding in the industrial arena.

Respondents were asked to indicate their opinion of the degree of difference among suppliers on each of the 33 selection criteria for which they had given importance ratings. The Likert scale ranged from l to 6, with 1 indicating that the suppliers were all about the same and 6 signifying a big difference among suppliers. One-way analysis of variance found a marginally significant overall difference between level of experience and differences among suppliers (F = 2.657, p < .10).

The average difference for the low experience group was 3.93, with the average difference for the moderate and high experience groups being 4.03 and 4.19, respectively. Analysis of the pairwise comparisons revealed that there was a marginally significant difference between the low and high experience groups (< = .10). The other pairwise comparisons were not significant. Possible explanations for this could be that it takes quite a few purchase situations for the effect of experience to impact the discriminatory processes of the buyer, or that not much is gained by having additional experience.


This research was motivated by the work being conducted in consumer behavior which examines the relationship between prior experience and consumer decision making. It was an initial attempt to empirically test consumer behavior theory in an industrial marketing context. Some results supported previous consumer behavior findings, while others did not. However, this is not unusual given the mixed results also reported in the consumer behavior literature.

Specifically, the current research tends to support the enrichment hypothesis frequently examined by consumer behavior researchers. While statistical significance was not always found, the more experienced buyer tended to:

- have a larger evoked set,

- have 6 larger number of vendors in the final consideration set,

- possess a larger number of selection criteria, and

- better discriminate among potential suppliers.

Previous organizational buyer behavior research has generally focused upon the information requirements surrounding the type of buying situation. For example, a straight rebuy situation would suggest that only a minimal amount of information was required. Based upon the current research, it now becomes questionable whether a minimal amount of information is required or if the buyer has just become more efficient in the information search process. On the other hand, a new task buying situation, based upon previous organizational behavior literature, would have had a greater information requirement. However it is suggested here that the new task buyer would not have utilized a greater amount of information.

Research concerning the presence or absence of prior experience with a product class has significant implications for the industrial marketer. Specifically, such information is paramount for communications strategy development. Insight into how experience affects the choice process can help in determining the type of information most effective for buyers with differing levels of experience. Sales presentations could easily be geared for the different levels of experience.

While fairly common in industrial marketing, the method of data collection in the current study is extremely different from the laboratory experiments typically conducted in consumer behavior research, and there may be some difficulty in studying information processing with an uncontrolled field study rather than in a controlled experimental context. Studying information processes by way of mailed questionnaires does not allow the experimenter to manipulate variables (e.g., experience) or to monitor the process (e.g., time) that the respondent uses in making decisions. Additionally, presenting the respondents with a list of "relevant" attributes and asking them to rate the degree of importance of each may tend to bias the responses, in that the respondent way not have thought of a particular characteristic but sees it as important now that he/she knows about it. Finally, retrospective reports may not be as accurate for the early as the latter stages of the decision. However, field research has the advantage of tapping actual organizational buyers regarding actual buying decisions.

The current research, of course leaves many questions regarding the information processing strategies of organizational buyers unanswered. Further studies must replicate and extend this study by including measures of many more processing variables. With a more controlled method, perhaps we might be able to track information search and use more precisely.

Beyond this, the general area of prior knowledge or experience seems to be important for understanding organizational buying behavior. Further research, for example, could examine differences between levels of experience and the macro-attributes (e.g., price) that the buyer uses. Having an idea as to whether the buyer will focus his/her final decision on price, sales competence, service, etc. would assist the industrial marketer in determining which criteria to emphasize in the sales presentation.

Finally, this study examined organizational buyers purchasing nonintelligent data terminals. Future studies could examine organizational buyers at opposite ends of the risk or complexity spectrum (such as office supplies, mainframe computers) to determine whether the level of experience has different effects with different types of products.


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