Incidental Learning of Product Information: an Exploratory Study

ABSTRACT - Given a low or no involvement condition, theories regarding consumer decision making as well as processing of advertisements predict that only knowledge regarding some brand names but no other attributes of a product category will accumulate. On the other hand studies in the incidental learning tradition suggest that in low or no involvement conditions some knowledge (brand names as well as other attributes) will accumulate. This study examines the amount of knowledge users (who are at least somewhat involved) and non-users (who are not involved) possess regarding two low involvement product categories. The methodology used entailed an interview in which respondents are asked to mention brand names (recall and recognition task) and product attributes (aided recall task). The results indicate that non-users as well as users have considerable knowledge about brand names and other attributes of the low involvement product category. Compared to non-users users mentioned more brand names and physical attributes and about the same number of augmented and derived attributes.

Citation:

M. Stokmans, S. Molenaar, and E. Razenberg (1995) ,"Incidental Learning of Product Information: an Exploratory Study", in E - European Advances in Consumer Research Volume 2, eds. Flemming Hansen, Provo, UT : Association for Consumer Research, Pages: 209-216.

European Advances in Consumer Research Volume 2, 1995      Pages 209-216

INCIDENTAL LEARNING OF PRODUCT INFORMATION: AN EXPLORATORY STUDY

M. Stokmans, Tilburg University

S. Molenaar, Tilburg University

E. Razenberg, Tilburg University

ABSTRACT -

Given a low or no involvement condition, theories regarding consumer decision making as well as processing of advertisements predict that only knowledge regarding some brand names but no other attributes of a product category will accumulate. On the other hand studies in the incidental learning tradition suggest that in low or no involvement conditions some knowledge (brand names as well as other attributes) will accumulate. This study examines the amount of knowledge users (who are at least somewhat involved) and non-users (who are not involved) possess regarding two low involvement product categories. The methodology used entailed an interview in which respondents are asked to mention brand names (recall and recognition task) and product attributes (aided recall task). The results indicate that non-users as well as users have considerable knowledge about brand names and other attributes of the low involvement product category. Compared to non-users users mentioned more brand names and physical attributes and about the same number of augmented and derived attributes.

INTRODUCTION

In recent years considerable effort is assigned to understand the processing of marketing communication. Often it is assumed that the less attentional resources are allocated to the message the less is comprehended and memorized. In the case of low involvement products this assumption means that consumers have very little or no knowledge about the product category. This last statement is challenged in this article. In order to do so we will first review the literature regarding the relationship between the allocation of attentional resources and the memory trace that results. Next we present the results of a research that invited users and non-users of two product categories (fast moving, low involvement goods) to memorize as many facts (brand names and other product attributes) about these product categories.

Most theories regarding consumer decision making assume that information about a product (or object) is only gathered if the consumer has decided or recognized that the product is of any specific use for him/her (Bettman, 1979; Engel, Blackwell & Miniard, 1986). Consumer's goals direct his/her information acquisition toward goal relevant information (Huffman & Houston, 1993). From this point of view, consumers know something about a product if they have considered buying one (in the past or the near future). In other words, they are motivated to process information about a product category and will consciously allocate processing capacity to information about the product category. Bloch, Sherrell & Ridgway (1986) suggested that this orientation is unable to account for search activities that are recreational or that occurs without a recognized consumption need. They made a distinction between prepurchase search and ongoing search. Prepurchase search is defined as: Information seeking and processing activities which one engages in to facilitate decision making regarding some goal object in the marketplace (Kelly, 1968: 273). Primary motives for prepurchase search concern enhancing the quality of the purchase outcome (Shugan, 1980; Punj & Staelin, 1983; Beach, 1990; Payne, Bettman & Johnson, 1992). Ongoing search, on the other hand, is defined as search activities that are independent of specific purchase needs or decisions (Bloch, Sherrell & Ridgway, 1986: 120). Two motives can be involved for ongoing search: First of all, to acquire a bank of information potentially useful in the future and secondly the pleasure or recreation derived from sensory stimulation (Hirschman, 1980; Bloch, Sherrell & Ridgway, 1986). According to this viewpoint, search activities are triggered if consumers are involved with the purchase of the product, as in the case of prepurchase search, or involved with the product itself as in the case of ongoing search (Bloch, Sherrell & Ridgway, 1986). For both types of search behaviour the allocation of processing capacity to the information is conscious, one is motivated to process information which results in an increased product and market knowledge.

In recent literature regarding processing of advertisements motivation to process information is a crucial component in how and what type of information is processed (see for example the Elaboration Likelihood Model [Petty & Cacioppo, 1986] or the Motivation Ability Opportunity model [McInnis & Jaworsky, 1989]). If the motivation is large enough, and the ability and opportunity to process the information do not inhibit the motivation component, consumers will process the information in a way which is very similar to cognitive learning (the central route in the Elaboration Likelihood model). If this mode of processing is followed consumers allocate attention to the information consciously and process the information thoroughly which results in specific knowledge about the product. If on the other hand the motivation is not large enough (or the ability or opportunity to process the information does inhibit the motivation component), consumers will process information comparable to the behavioral learning paradigm (the periphery route in the Elaboration Likelihood model) (Petty & Cacioppo, 1986). In this mode of processing attention payed to the information is low and the information is processed only shallow (without elaboration). Consequently, no specific product information will be stored in memory, only some global (affective) responses (Greenwald & Leavitt, 1984; Celsi & Olson, 1988). In the Elaboration Likelihood Model, motivation to process the information is among other factors affected by receiver involvement, where involvement is defined as the personal relevance of the topic to the receiver. In this perspective it is hypothesized that receivers in the high involvement condition process information according to the central route of persuasion and receivers in the low involvement condition process the information according to the peripheral route of persuasion (O'Keefe, 1990: 99-100).

To summarize, both theories about consumer decision making as well as theories regarding processing of advertisements assume that consumers will only accumulate knowledge about a product if they are motivated and able (processing capacity and opportunity) to process the information. This viewpoint is also shared by Greenwald & Leavitt (1984). They state that one can differentiate between four levels of audience involvement which each result in different enduring cognitive and attitudinal effects because of the amount of attentional capacity allocated to the stimulus. Greenwald and Leavitt (1984) explicitly state that no information about a product is stored in memory if the message is only processed superficial (feature analysis or perceptual and semantic processing). Product information is only stored if the information is processed more thoroughly (syntactic or conceptual analysis).

These considerations suggest that consumers have very little or no knowledge about a product category (in terms of brand names and product characteristics) and even no cognitive reaction to advertisements if they are not involved with the product or a purchase of the product. In that case one is not actively searching for information about the product category and no processing capacity is consciously allocated to the information about the product category. If one accidentally views information about the product category one is not interested in, the processing of this information is only superficial and no memory trace will result.

On the other hand studies on advertisement as well as on memory in the verbal learning tradition suggest that even if the allocation of attention to the information is automatic or not conscious (as in conditions of low or no involvement) cognitive reactions may occur. These studies can roughly be divided into three groups: The studies which stress the point that consumers are (if they like it or not) confronted with a lot of information. In order to make a selection out of this chaos one has to determine what is worth processing and what is not. One has to direct some 'attention' to the information to make this selection. This will result in some knowledge (familiarity, liking) about the object, especially if the consumer is confronted with the information frequently. Examples of these studies regard pre-attentive processing (Broadbent, 1977), mere-exposure (Zajonc, 1968; Sawyer, 1981) and the truth-effect (Hasher, Goldstein & Toppino, 1977; Schwartz, 1982; Hawkins & Hoch, 1992).

The second group of studies is based on the low-involvement learning hierarchy (overlearning: Krugman, 1965; low-involvement learning hierarchy: Ray, 1973) in which it is hypothesized that a shift in cognitive structure may occur (consumers may be better able to recall the name or idea of a product) as a result of overwhelming repetition of the message while the consumer is not involved with neither the advertising nor the topic (Ray, 1973; 152).

The last group of studies concern those in which respondents are instructed to perform a specific task (for example "which words contain an r") and are unexpectedly asked to memorise the words they were confronted with in the task. The kind of task determines the level of processing (incidental learning, Nelson, 1977; Maki & Schuler, 1980; Leigh & Menon, 1987 and implicit memory, Reber, 1993, Berry, 1993). Research regarding incidental learning suggest that one has some memory trace regarding the stimuli even at a very low level of processing (Nelson, 1977; Mark & Schuler, 1980). Furthermore, imagery vividness and stimulus concreteness facilitate memory (MacInnis & Price, 1987).

The effect of incidental learning are mostly studied in laboratories. And their are some difference between learning of advertisements content by the consumer in a real setting and these laboratory studies. In a laboratory setting the processing capacity allocated to the information is minimized to assure a very low level of processing. In a real setting consumers attend to marketing communication without explicitly intending to learn from or evaluate the message (Krugman, 1965: 345), but they still allocate some attentional resource to the message. Secondly, the frequency in which this information is presented to respondents is relatively low in a laboratory setting compared to a real setting, while it is often supposed in advertising that frequency has an effect on recall and recognition, especially in low involvement conditions (as suggested by studies regarding overlearning). In the incidental learning and implicit learning tradition on the other hand it is often hypothesized that rehearsal at the same level of processing will not improve memory (Chraik & Lockhart, 1972; Schwartz & Reisberg, 1991).

In this study the amount and type of product knowledge consumers possess regarding low involvement products is investigated. In order to do so three concepts need some clarification, namely involvement, product knowledge and measurements of product knowledge. In the conceptualisation of involvement a distinction is often made between antecedent, process and consequence variables (Greenwald & Leavitt, 1984, Zaichkowsky, 1985, Andrew et al, 1990). It can safely be stated that involvement will be very low or even totally absent if none of the antecedents of involvement is applicable. The antecedents are often divided into two groups, namely: personal needs, goals and characteristics versus situational and decision factors. Therefore, it is assumed that someone is not involved in a product category if one has no personal needs or goals regarding the product category and one is not considering buying such a product. On the other hand, if one has some personal needs or goals regarding the product or one is considering buying such a product, one is considered being somewhat involved.

Research regarding involvement with product categories indicate that fast moving consumer goods (such as groceries and beverages) are generally perceived as less involving than for example durables and clothing (Rossiter & Percy, 1987). For fast moving consumer goods a person will be low involved if he/she uses the product category (the users). A person will be not involved at all it the low involvement product category if he/she isn't using the product, hasn't used the product in the past and will not use the product in the near future (the non-users). For this research it is sufficient to make a distinction between two groups, one group which can be classified as not involved (non-users of the low involvement product category) and the other group as being low involved in the product category (users of the low involvement product category).

Knowledge is often represented as networks of nodes encoding particular concepts and links connecting these nodes (Hayes-Roth, 1977; Raaijmakers & Shiffrin, 1992). In the case of product knowledge the nodes represent the attributes of the product (Grunert, 1986). But what is an attribute? In economic literature product attributes are often defined as an objective physical aspect of the product (Lancaster, 1966). This definition is considered to narrow, because a lot of product characteristics used by both management and consumer are not physical aspects of the product. Therefore, a product attribute is defined in accordance with Grunert (1989), namely:

'Any aspect of the product itself or its use that can be used to compare product alternatives. Each alternative can (but need not) be characterized by all aspects, i.e. using one aspect does not preclude using another.'

This definition includes all physical attributes of a product as well as attributes which are only indirectly linked to the product. In marketing literature three types of attributes are often distinguished (Leeflang & Beukenkamp, 1987; Kotler & Armstrong, 1990):

1. Attributes of the core product (physical attributes).

2. Attributes of the product as marketed, which are not part of the core product (augmented attributes). For example: package, brand name, warrants, price and distribution (number and type of shops where one can buy the product).

3. Attributes of the total product which are not part of the augmented product (derived attributes) such as durability, user-friendliness of the product, social status.

There are different ways to retrieve product information from memory: one can recall the product information ("Mention as many brand names of a particular product category as you can") or recognize it ("Is Mars perhaps a brand name of the product category?). If one tries to recall the information a variety of cues may or may not be offered (Schwartz & Reisberg, 1991). In unaided recall (or free recall) procedures no cues are available and it is therefore a pure memory-based judgement. If cues are offered, one speaks of aided recall procedures. One can for example give some brand names of a specific product category and ask the respondent to mention some product characteristics (attributes). In recognition procedures, on the other hand, target item(s) and distracter items are given to the respondent, and he/she is asked to determine which items are target items and which are not.

It is often assumed that unaided recall procedures are the most taxing procedures for the respondent to retrieve information from memory while recognition is viewed as the least taxing procedure (Zinkhan, Locander & Leigh, 1986). In other words, given that the retrieved information is exactly the same for a recall and recognition task, it is assumed that respondents have a better memory regarding those aspects if the information is retrieved by means of a recall task compared to a recognition task. A better memory about facts is achieved when the information to be remembered is encoded and organized within the individual's existing cognitive structure. This will only take place when a lot of processing capacity is allocated to the information as in elaborative processing (see for example Greenwald & Leavitt, 1984).

In order to explore the amount and type of product knowledge consumers possess regarding low involvement product categories, a number of hypothesis are tested. As explained above, theories about consumer decision making as well as processing of advertising suggest that only users of a low involvement product category will accumulate knowledge of brand names of the product category, because of (classic and instrumental) conditioning which takes place as a result of following the peripheral route of persuasion (ELM-model) and positive experienced product usage. Furthermore, users of a low involvement product category will have minimal or no knowledge about other attributes of the product category, because acquiring this kind of knowledge means that the consumer has to process information about the product category more thoroughly. According to this viewpoint, non-users will have no knowledge (neither brand names nor characteristics) about the product category, because they haven't used the product and are not motivated to process information concerning the product category. On the other hand, incidental learning studies hypothesize that even at very low levels of processing some memory trace (in terms of brand names as well as product characteristics) will result, for both users and non-users of a low involvement product category. In stating the hypotheses the position of the 'consumer theories' is taken. Consequently it is hypothesized that regarding low involvement product categories:

H₁: Non-users will recall or recognise no brand names.

H₂: User recall or recognize a larger number of brand names than non-users.

H₃: Non-users as well as users will recall no product attributes.

H₄: The non-users and the users do not differ in the number of product attributes they recall.

H₅: The non-users and users do not differ in the number of product attributes recalled regarding each type of attribute.

METHOD

In this study knowledge structures are of interest. According to Grunert & Grunert (1991) one of the criteria for a valid instrument for measuring cognitive structures is that the "raw data should be driven more by the respondent's cognitive structure and processes than by the researcher's cognitive structure". In practice this means that an interview in which the respondent can generate the answers freely is a valid mode of data collection. Consequently, the research method in this study is a structured interview.

Design

The product categories which were included in the study should satisfy four conditions. First of all, consumers should either be regular uses (some what involved) or non-users (not involved) of the product category. Secondly, it should be a product category for which a lot of different brands are active on the marketplace and which is quite differentiate. Consequently, lots of brand names and other attributes of the product category can be mentioned. Thirdly, involvement with the product category should generally be low. In that case it is expected that users possess little knowledge and non-users should have no knowledge about the product category. And fourthly, the product category should be advertised heavily, because frequent exposure to the product information is a supposition to store some product information in memory if the consumer is low or not involved. Two product categories which satisfy these conditions are disposable diapers (five nationally advertised brands) and cat-food (ten nationally advertised brands). All respondents were asked about cat-food as well as disposable diapers, but the order in which the products were questioned was balanced.

Brand names were generated by means of unaided recall and recognition procedures. In the recognition task the respondents was confronted with existing brand names not mentioned in the recall task and three (in the case of disposable diapers) or four (in the case of cat food) fictitious brand names. The respondents were asked to indicate how sure (7-point scale, very certain - very uncertain) they are that the presented name is indeed a brand name of the mentioned product category. The number of existing brand names retrieved is viewed as an indicator of the amount of knowledge one has about the product category (the number of brand names recognised were determined by the sum of the number of brand names (correctly) recalled and the number of existing brand names recognized).

The product attributes were generated by means of an aided recall procedure: the brand names retrieved were visualized to the respondents and they were asked to mention as many product characteristics as they knew.

Procedure

All respondents were interviewed individually. The interview started with a recall question, in which the respondent was asked to name as many brand names of the product category under consideration as he/she knew. The brand names mentioned by the respondent were visualized by means of small cards. If the respondents named a brand name for which no such a card existed (because the brand name did not exist for example) the brand name was written down on such a card.

The next question regarded the product attributes. The cards with the brand names recalled were presented to the respondent and could be used as retrieval cue for the attributes. The interviewer tried to stimulate the respondent to come up with product attributes by probing techniques.

Then the cards with brand names which were not mentioned in the recall test as well as some distracter items were presented to the respondents. The respondent was asked to indicate which brand names he/she recognized and how sure he/she was about this (seven-point scale). Again the respondent was asked to come up with some attributes not already mentioned in the recall part of the interview.

TABLE 1

CATEGORIZATION OF THE RESPONDENTS

TABLE 2

NUMBER OF FALSELY IDENTIFIED BRAND NAMES

To complete the inquiry about the first product, the respondent had to fill up a few questions regarding product use and some demographic questions. Then the same inquiry started for the second product category.

Respondents

A large part of the respondents (30) were a convenience sample recruited in a shopping centre in Tilburg (the Netherlands). But no respondent in this sample used disposable diapers. In retrospect this is not surprising, because respondents with little children reacted reluctant if they are asked to participate in a research what will last for about 30 minutes. Therefor an additional 10 (disposable diapers using) respondents were interviewed at home after they had committed themselves by telephone to participate in the research. Table 1 shows how many respondents are categorised as non-users and users regarding cat food and disposable diapers. A number of respondents interviewed (7 in the case of cat food and 6 in the case of disposable diapers) were not included in the analysis because they had used the product category in the past. Those respondents can not unambiguous be categorised as consumers with low or no involvement regarding the product category.

RESULTS

Before analyzing the amount of recognised brand names, the number of falsely identified brand names as well as the certainty scores (1: very certain, 7: very uncertain) of the recognition task were examined. This analysis indicates whether or not users and non-users are equally prone to 'yea-saying'. Table 2 shows the number of falsely recognised brand names for both users and non-users of each product category. Nobody identified more than two distracter items as brand names.

A Chi-square analysis showed that regarding cat-food the number of distracter items recognised as brand names is not independent from the fact of a respondent is a user or a non-user (Chi-square=6.15, df=2, p<0.05). Regarding diapers the number of distracter items identified as a brand names is independent of the fact that one is a user or a non-user (Chi-square=0.48, df=2, p>0.05). So regarding cat-food, users identify more often a distracter item as a brand name than non-users. For diaper, no difference is found. This difference is only indicative for 'yea-saying' if users and non-users are equally certain about the recognition.

The average certainty scores for both diapers and cat-food are given in table 3. T-test indicate that users and non-users are equally certain about identifying distracter items as brand names (t₃₁=- 0.34, p>0.05 and t₃₂=- 0.58, p>0.05 for cat-food and diapers respectively) or target items as brand names (t₃₁=-0.48, p>0.05 and t₃₂=- 1.02, p>0.05 for cat-food and diapers respectively). So it can be concluded that regarding cat-food users have a larger probability of identifying a target items as a brand name than non-users (because they more often say that an item is a brand name). Regarding diapers the probability of identifying a target item as a brand names is equal for both users and non-users.

The hypothesis stated in the introduction consider the number of brand names and product attributes remembered. It regards a continues variable for which no restrictions are set to the rang of responding, so extreme values may occur. Extreme values have a strong effect on the mean estimated and therefor on the outcome of the hypotheses tested. Before testing the hypotheses the data will be checked for extreme values by means of boxplots. A value is extreme if it is more than three box-length from the upper or lower fourth of the distribution (The box-length corresponds to the interquartile range, which is the difference between the 75th and 25th percentiles) (Huizing, 1991). This inspection identified four extremes: two extreme cases regarding the number of brand names recalled as well as recognized for cat-food, another extreme case regarded the number of brand names recognized for diapers and the forth extreme case concerned the number of physical attributes mentions for diapers. These extreme cases are left out of the analysis.

Both product categories investigated in this research are low involvement products. As was stated in hypothesis one and three non-users have a neglectable amount of knowledge (brand names as well as other attributes) while users will know very few brand names and almost no other attributes regarding low involvement product categories. The average number of brand names recalled for cat-food and diapers is displayed in table 4.

Regarding cat-food the average number of brand names recalled is considerable larger than zero for non-users (m=3.37, t₁₈=8.77, p<0.05). The same can be said about the number of attributes mentioned for cat-food by non-users (m=21.10, t₁₉=8.17, p<0.05) and users (m=29.85, t₁₂=8.74, p<0.05). Similar results were found for diapers. The average number of brand names recalled by non-users is considerably larger than zero (m=2.08, t₂₃=13.18, p<0.05). This is also true for the number of attributes mentioned for diapers by both non-users (m=12.79, t₂₃=9.22, p<0.05) and users (m=19.20, t₉=5.76, p<0.05). Consequently hypothesis one and three should be rejected; regarding brand names (hypothesis one) it was shown that non-users of a low involvement product category do know a (small) number of brand names regarding this product category. And concerning the other attributes (hypothesis three) it was shown that non-users as well as users of a low involvement product category know a considerable number of attributes of this product category.

TABLE 3

THE AVERAGE CERTAINTY SCORES OF THE RECOGNIZED BRAND NAMES

TABLE 4

THE AVERAGE NUMBER OF BRAND NAMES AND ATTRIBUTES REMEMBERED

Given that users and non-users have specific knowledge about low involvement products, theories regarding consumer decision making as well as advertising predict that users know more brand names that non-users (hypothesis two), but users and non-users do not differ in the number of attributes recalled (hypothesis four). As table 4 shows, the difference between the average number of brand names recall by users and non-users is significant for both cat-food and diapers (t₂₉=3.47, p<0.05 and t₃₂=4.91, p<0.05 respectively). The same results are found for the number of brand names recognised (t_28.89=4.47, p<0.05 and t₃₂=3.48, p<0.05 for cat-foot and diapers respectively). So hypothesis two is confirmed by the data.

If the average number of attributes are investigated (table 4) it turns out that users mention more attributes than non-users for both cat-food and disposable diapers. The difference between the number of attributes mentioned is only significant for cat-food (t_24.6=2.04, p=0.052) and not for diapers (t_12.24=1.77, p>0.05). So it is not clear whether users and non-users of a low involvement product category know the same amount of attributes of this product category.

When the number of attributes mentioned regarding a particular attribute type (physical, augmented [without brand names] or derived) are examined one can inspect whether or not users know more about the product category for each type of attribute than non-users (hypothesis 5). Table 5 shows that users mention more attributes than non-users for all types of attributes distinguished. For both cat-food and diapers the number of physical attributes mention result in a significant difference ((t_26.7=2.56, p<0.05 and t₃₁=2.30, p<0.05 respectively). For the other attribute types (augmented [without brand names] and derived) the amount of attributes mentioned does not differ between users and non-users for both cat-food and diapers. These results indicate that users of a low involvement product category know more physical attributes of the product category that non-users, but users and non-users have the same amount of knowledge regarding augmented and derived attributes.

TABLE 5

THE AVERAGE NUMBER OF ATTRIBUTES MENTIONED FOR EACH CATEGORY OF ATTRIBUTES DISTINGUISHED

DISCUSSION AND CONCLUSION

According to consumer decision theories as well as information processing theories applied to advertising, consumers will only possess information about a product if they have allocated considerable attentional resources to information about the product category. This prerequisite is met when consumers are involved with the product category. In this study it was suggested that even if consumers are not involved with the product category (because they are not considering buying a particular low involvement product) they still accumulate considerable knowledge about the product category. This amount of knowledge will be less than the amount of knowledge users of the low involvement product category possess. The results indicated that users and non-users of two low involvement product categories (diapers and cat-food) have considerable knowledge about characteristics of the product category (brand names as well as other attributes). The difference between the number of characteristics mentioned by users and non-users is only significant regarding brand names and physical attributes and not for augmented and derived attributes.

The present study verifies the generally reported finding that subjects who allocate more attentional resources to product information, possess more knowledge about the product category (for example Lockhart, Craik & Jacoby, 1976; Leigh & Menon, 1987). This study is in two ways an extension to those studies. First of all, in this study the relationship is investigated for low and no involved consumers instead of low and high involved consumers. Theories regarding consumer decision making as well as advertising predict that low involved consumers know less about the product category that high involved consumers, but are less explicit about potential differences between low and no involved consumers. Secondly, this study is not an laboratory study in which respondents are confronted with the advertisements.

The methodology used in this study entailed an interview of users and non-users regarding a low involvement product category for which respondents are asked to mention brand names (recall and recognition task) and product characteristics (aided recall task). The pursued methodology is one generally used in research regarding product knowledge (see for example Zinkhan, Locander & Leigh, 1986; Singh, Rothschild & Churchill, 1988; Schwartz & Reisberg, 1991). Although the recognition task used in this study is not the one generally recommended (for example Singh, Rothschild & Churchill, 1988). In recognition procedures the means of providing the target and distracter items may by successively or simultaneously, and the response may consist in accepting or rejecting the given alternative (yes/no), rating it, assign a subjective probability to it (how sure are you) ranking it in relation to other choices, or choosing the most plausible item(s) out of a set of n items (Brown, 1976). The response mode which is often preferred is 'choosing the most plausible item(s) out of a set of n items' (forced-choice test) because this response mode is very appropriate in reducing response bias (the tendency to please the interviewer by 'yea-saying') compared to accepting or rejecting the given alternative (yes/no) (Singh, Rothschild & Churchill, 1988). In the present study a subjective probability scale (very certain, very uncertain) was offered as a response mode. The reliability of this subjective probability scale is probably larger than the reliability of the forced choice test, especially if one is not very sure about what items are target items, or if different cut-off levels are used regarding the certainty that a item is a target item (by different respondents or at different occasions during the test). The subjective probability scale offers the opportunity to determine whether or not the low and no involved respondents were equally sure about the recognized brand names. If they are, the low and no involved respondents have an equally reliable measure regarding the recognised items. Whether a forced-choice or a subjective probability procedure is the most valid and reliable measure of recognition test can be clarified in further research.

An other reason for not using the forced choice response mode in this study is the fact that in the recognition task used in this study respondents were confronted with brand names they didn't recall and three (in the case of diapers) or four (in the case of cat-food) distracter items. Consequenly the number of target items in the set differs between respondents and covaries with the amount of knowledge the respondent has about the product category. If a forced-choice test was used the probability to identify accidentally a target item is larger for respondents with little knowledge than for respondents with substantial knowledge. In that case the difference between low en no involved consumers regarding the amount of knowledge retrieved decreases. The problem does not occur if a subjective probability scale is used, because respondents have to indicate for each item (target as well as distracter) whether or not it is a target item and how sure they are about it.

An important implication of this study for models regarding processing of information is that consumers can also accumulate knowledge about a product category if they allocate very little processing capacity to the information. Most models (Elaboration Likelihood Model, Motivation, Opportunity Ability model, Audience involvement model) assume that in those conditions no knowledge will accumulate. Before concluding that these models should be revised, one should first of all, verify the findings reported in this study for more low involvement product categories. Secondly, the question should be answered how some product knowledge can accumulate if only very little processing capacity is allocated to the information. And last but not least it should be clear how frequency of exposure has an effect on the resulting memory trace.

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