Advertising Effects Under Different Combinations of Motivation, Capacity, and Opportunity to Process Information

ABSTRACT - Like the Elaboration Likelihood Model (Petty and Cacioppo 1986), the MOA (Motivation, Opportunity, and Ability) framework (Batra and Ray, 1986; MacInnis and Jaworski, 1989) refers to motivation and ability as general determinants of advertising processing. It differs from the ELM by its explicit distinction between ability and opportunity. A study is reported in which the effect of the three factors on advertising processing and effect measures is assessed. Results provide partial support for the hypotheses and for the relevance of a distinct opportunity factor. Implications for future advertising studies are discussed.


Theo B.C. Poiesz and Henry S.J. Robben (1996) ,"Advertising Effects Under Different Combinations of Motivation, Capacity, and Opportunity to Process Information", in NA - Advances in Consumer Research Volume 23, eds. Kim P. Corfman and John G. Lynch Jr., Provo, UT : Association for Consumer Research, Pages: 231-236.

Advances in Consumer Research Volume 23, 1996      Pages 231-236


Theo B.C. Poiesz, Tilburg University, the Netherlands

Henry S.J. Robben, Delft University of Technology, Delft, The Netherlands


Like the Elaboration Likelihood Model (Petty and Cacioppo 1986), the MOA (Motivation, Opportunity, and Ability) framework (Batra and Ray, 1986; MacInnis and Jaworski, 1989) refers to motivation and ability as general determinants of advertising processing. It differs from the ELM by its explicit distinction between ability and opportunity. A study is reported in which the effect of the three factors on advertising processing and effect measures is assessed. Results provide partial support for the hypotheses and for the relevance of a distinct opportunity factor. Implications for future advertising studies are discussed.


Commercial communication is becoming increasingly important as the result of general market, marketing, and product developments. Possible reasons relate to (perceptions of) the lack of market transparancy and to diminishing interbrand differences within many product categories (see, e.g., Foxman, Muehling, and Berger 1990; Foxman, Berger, and Cote 1992). These developments negatively affect brand differentiation possibilities.

In principle, a variety of marketing instruments may be used to distinguish a brand from its competitors. Marketers tend to be reluctant, however, to differentiate brands on the basis of price, and often lack the possibility to differentiate on the basis of distribution. This contrast between differentiation needs and limitations boosts the importance of the role of communication, which is reflected in the growing number and variety of media, messages, and communication attempts (Poiesz and Robben 1994).

The suggested developments directly affect three parties in the area of advertising. The growing number of advertising exposures require consumers, as the first group, to be increasingly selective, which limits or even prevents message processing. The second group, advertisers, are faced with the combination of increasing advertising costs and decreasing advertising effects. This problem needs to be solved by the third party, the producers of advertising - the media suppliers and advertising agencies. (By consequence, the latter party confronts a new phenomenon: 'accountability', referring to advertising performance justifications before rather than after media expenditures).

Academic and commercial advertising researchers form the party that is indirectly affected by these developments. The stronger call for accountability may be equated with a stronger need for 1. an adequate and applicable consumer behavior basis for advertising decisions, and 2. reliable and valid diagnostic instruments for the assessment of advertising quality. However, while the need for a behavioral foundation of advertising effectiveness seems to be increasing, the present body of knowledge often cannot be readily applied. There appears to be no single, generally applicable theoretical and methodological framework that may be easily applied to the diagnosis of the quality of a particular advertising message prior to exposure. The empirical evidence reported in the academic literature is not very helpful either. The evidence is acquired in individual studies that tend to address single aspects of advertising messages, styles of execution, media characteristics, or exposure situations. In sharp contrast, advertising decisions cannot relate to these isolated aspects, but need to refer to their particular, complex interactions.

In summary, market and marketing developments seem to result in the convergence of the interests of advertising practitioners and advertising researchers. Both parties are faced with the issue of accountability, and with the issue of validity as its academic counterpart. There is a need for a single and parsimonious approach for the judgment of the communication potential of individual advertising messages. Even though such an approach does not seem to be avaible, we will elaborate upon two general approaches that seem to provide a useful starting point.


In recent years several attempts have been made to introduce an overall theoretical framework for the explanation of advertising processing. The best known approach is that of the Elaboration Likelihood Model (ELM) by Petty and Cacioppo (1983, 1986), which specifies motivation and ability as the primary conditions for advertising processing and persuasion. If these conditions are favorable, argument-based processing is expected to take place. If either one or both of these conditions is/are unfavorable, processing is based on message execution aspects at best. While the ELM focuses upon motivation and ability, other approaches explicitly distinguish between motivation, ability, and opportunity to process an advertising message (the so-called MOA-framework, Andrews, 1988; Batra and Ray 1986; Curry and Moutinho 1993; MacInnis and Jaworski 1989; MacInnis et al. 1991). In the ELM, the concept of opportunity is subsumed under that of ability.

If we were to discard of opportunity-related elements in the ability concept, and would distinguish opportunity from ability, the latter concept would acquire a meaning that is more exclusively related to personal capacity, capability, or proficiency. With this conceptualization of ability, opportunity may be defined as the extent to which external conditions, unrelated to personal factors or characteristics, are favorable or unfavorable for message processing to take place.

There seem to be no a priori theoretical or meta-theoretical reasons why the two-factor approach (motivation/ ability) is more or less desirable than an approach employing three factors (motivation/ ability/ opportunity). Which would imply that the choice between the two approaches is basically a matter of emphasis by the individual researcher. Yet, we will present several arguments that seem to favor the explicit inclusion of a distinct opportunity factor next to motivation and ability.

The reasons why we prefer to use the three factor approach are the following:

- A distinct opportunity factor requires the researcher to focus upon differences between laboratory and actual advertising exposure situations. In the introduction it was argued that actual advertising exposure conditions are becoming increasingly unfavorable (also in terms of opportunity). The exposure conditions in research settings tend to be relatively favorable, however;

- The specification of a separate opportunity factor provides a better possibility for the distinction between person related and situation related influences;

- For advertising practitioners it is useful to know whether (suboptimal) message processing should be attributed to the recipient, to the message, and/or to the exposure situation. Depending upon the diagnosis, there is a substantial difference between the necessary correction measures. Explicit identification of possible determinants (e.g., ability vs. opportunity) is crucial for adequate diagnosis and intervention decisions.

In order to avoid confusion between ELM and MOA interpretations of the concept of ability, we will refer, in the following, to capacity (cf. Robben and Poiesz 1993). The conceptual and semantic meaning of capacity is more associated with personal rather than environmental characteristics.

Motivation, capacity, and opportunity may be interpreted in either an objective or subjective way. This is tantamount to saying that all three factors may be both externally manipulated (by advertisers or researchers) and subjectively assessed (by consumers or research participants). We assume that the inclination to process an advertising message is more dependent upon subjective assessments of motivation, capacity, and opportunity, than upon its objective counterparts. For example, even though the amount of time available for processing a particular ad can be judged as amply sufficient on 'objective grounds', processing may not take place if the consumer perceives the time as insufficient.

With regard to the operationalizations (manipulations and multi-item measurement scales) of the three general factors several observations may be made:

Generally, the emphasis is on motivation and ability/ capacity only; to our knowledge, the concept of subjective or perceived opportunity is generally ignored. Several possible reasons may be mentioned:

- Depending upon the level of the opportunity factor, its role may be trivial in the sense that common sense does not assume any effect if opportunity is absent or very low;

- Conceptually, opportunity has not been elaborated. Its dimensions are not clear, but are likely to include time, distance, and external distraction;

- To the extent that the role of opportunity is not trivial (when we speak of, for example, limited, sufficient, or ample time), it is not clear how it interacts with the other two main factors motivation and ability;

- At high levels of motivation, limitations with regard to opportunity may possibly be overcome by increasing capacity (e.g. attention);

- A possible reason why opportunity is relatively neglected is that it is easier to acquire data for publication purposes if research participants are provided with more opportunity to react to the stimulus. In this sense there may be a systematic bias in the methodology of advertising research in that the exposure conditions tend to be favorable relative to those in actual circumstances.

In summary, there are several reasons why the operationalization of opportunity lagged behind those of motivation and ability/ capacity. At the same time we must note that opportunity is a potentially important factor. Ad processing results that have been observed in the literature may be related to a particular (sufficient) level of opportunity only. The effects of motivation and ability/ capacity may differ depending on the level of available opportunity.

Another observation with regard to the operationalization of the three factors is that in some advertising studies, these factors are operationalized or manipulated merely in terms of some of its aspects or antecedents. For example, motivation has a tendency to be operationalized as product involvement or personal relevance (see, for instance, Zaichkowsky, 1985), ability/ capacity is often operationalized in terms of product knowledge or experience; and opportunity (if operationalized at all) is operationalized in terms of exposure time. Obviously, motivation as a general factor may not be dependent upon involvement or personal relevance only, but may depend upon the combination of executional and media characteristics as well. Similarly, the operationalization of ability/ capacity should not reflect product knowledge only, as knowledge is merely an aspect or antecedent, next to other possible aspects or antecedents (such as product and message familiarity, message comprehensibility, recipient intelligence, memory capacity, etc.). Finally, even though time to process is an aspect of opportunity, the overall concept and operationalization of opportunity should not limit itself to processing time, but should include, for example, external distractions and distance to the stimulus as well.

For the present purposes it does not suffice to identify some operationalization of motivation, capacity, and opportunity and to establish the effect of that operationalization on processing. Rather, we need operationalizations that may be assumed to fully cover the conceptual meanings of motivation, capacity, and opportunity to process. In the case of a particular advertising message we may simply not know which particular aspects of motivation, ability/ capacity or opportunity are at play. Then, more general operationalizations are preferred. In the present study we will attempt 1. To explicitly introduce opportunity as one of the factors to be considered; and 2. To use operationalizations of the three factors that are of a general nature so as to avoid the suggestion of an emphasis on a particular aspect or determinant.

The following hypotheses overlap with and partly add to the theoretical notions put forward by the ELM (Petty and Cacioppo 1983; 1986) and the MOA-framework (as elaborated by MacInnis and Jaworski 1989; MacInnis et al. 1991):

H1: Motivation, capacity, and opportunity are positively related to the advertising processing related measures: ad recognition (RECAD) and recall (RCLAD), and brand recognition (RECB) and recall (RECB);

H2a: Ad recognition and ad recall are positively related to the attitude toward the ad (AAD);

H2b: Brand recognition and brand recall are positively related to attitude toward the brand (AB);

H3: Attitude toward the ad is positively related to attitude toward the brand (AB);

H4a: Attitude toward the ad is positively related to Intention to act (IACT)

H4b: Attitude toward the brand is positively related to Intention to act (IACT).

These hypotheses can be summarized in the Figure 1:


Subjects and design

Hundred-and-twenty six female members of the Product Evaluation Laboratory Research Panel of Delft University of Technology participated in the study. Age varied between 25 and 83, with a median of 50 years. The data of four participants were not used in subsequent analyses because the presentation of one stimulus was flawed. All received a small monetary compensation for their efforts (about $6.00) and a small gift. Subjects were randomly assigned to one of the eight experimental cells. The design was a 2*2*2 factorial design with two levels ('high' and 'low') for each of the between-subjects factors motivation, capacity, and opportunity.




The stimuli were slides of mock-up car advertisements. The top half of the slide showed the car, the bottom half presented the body copy and the brand name, 'Tewikan.' This is a nonexistent brand name, for which it was established in a separate pilot study that it does not carry any negative or positive connotations in the Dutch language.

Independent variables

Opportunity to process the information contained in the ad was either low (slide presentation of 12 seconds) or high (20 seconds). A separate pilot study indicated that 12 seconds was barely enough to see the picture and read the text in the ad. Capacity to process the information was either facilitated by presenting the body copy in everyday language (high), or impeded by presenting the copy in technical jargon (low). Motivation was either enhanced by presenting a full-color picture with a relevant headline ('For your safety') (high) or diminished by presenting a black-and-white picture without the headline (low).

Dependent Measures

Six measures were included that represented early ad-processing effects in the hierarchy of advertising effects (affective, cognitive) and later effects (intentions to act).

Attitude toward the Ad (AAD). Three semantic differential-type items assessed subjects' evaluation of the ad on 7-point scales (a=.94). The anchor points were "very negative-very positive," "very unfavorable-very favorable," and "very bad-very good."

Attitude toward the Brand (AB). Similarly, subjects' evaluation of the brand was assessed (a=.97).

Brand Name Recall (RCLB). Subjects wrote down the name of the brand as they recalled it. This response was classified on a 3-point scale (incorrect, partially correct, fully correct).

Advertisement Recall (RCLAD). Subjects answered on a 7-point scale whether they could recall the advertisement very badly (1) or very well (7).

Brand Recognition (RECB). On a separate page, using a single 7-point scale ("Not sure at all-Very sure"), subjects indicated how sure they were that "TEWIKAN" was the brand name identified on the ad.

Advertisement Theme Recognition (RECAD). Similarly, they indicated whether safety was the product attribute stressed by the ad.

Intention to Act. On two separate 7-point scales (totally disagree-totally agree), subjects indicated the extent to which they wanted more information on the advertised car, and their wish for a test drive. The significant and positive correlation between both measures (r=.76, p<.0001) warranted the construction of a single intention to act measure, IACT.


The present study was embedded in a larger investigation involving different experiments by several investigators. This multistudy setting was familiar to the subjects as they all had cooperated previously with the research panel. The total investigation was presented as a set of product evaluation tests. All separate studies involved an evaluation of durable or fast-moving consumer goods.

For the present experiment, subjects sat in front of a projection screen. A research associate read the instructions aloud while the subjects read them simultaneously. A slide projector with an accurate timing device presented the advertisements for either 12 or 20 seconds. Immediately after the projection, subjects completed a scale assessing their subjectively experienced motivation, capacity, and opportunity to process the commercial information. They completed 16 motivation items (e.g., "This advertisement does not appeal to me" and "This advertisement captures my attention"), 12 capacity items (e.g., "I have trouble understanding this advertisement" and "It was immediately clear what this advertisement wanted to say"), and 14 opportunity items (e.g., "You need more time for this advertisement" and "I think the circumstances for watching this advertisement are ideal"). All responses were given on 7-point scales with a "1" indicating "totally disagree" and a "7" indicating "totally agree."



The items for the scales were obtained through qualitative and quantitative pretest studies. In one qualitative pretest, conducted by a professional market research agency, four group discussions involving six persons at a time, each produced statements on 38 different ads. Subsequently, these statements were evaluated with regard to two different ads (a transformational ad on beer and one informational ad on insurance) in survey with 686 respondents by the same agency.


Appropriateness of the Stimuli. To assess the extent to which the subjects typically avoid ads like the one shown in the study, they answered this statement on a 7-point scale (from "totally disagree" to "totally agree"). The mean score (X=5.79, SD=1.81) suggested that the subjects could relate to the ads in the experiment.

Principal Components Analysis. An initial principal components analysis of the items designed to measure the motivation, the capacity, and the opportunity to process the ad, yielded 13 factors accounting for 74.3% of the variance. Inspection of this solution showed that the large majority of these factors contained only items designed to measure either the motivation, the capacity, or the opportunity to process information. Therefore, in line with the theoretical model underlying this study, a three-factor solution was forced, yielding six items for each theoretically defined factor with factor loadings and communalities of .50 or greater, accounting for about 63% of the variance. The factor scores for each factor were used to represent subjective appraisals of the motivation, the capacity, and the opportunity to process the information contained in the experimental stimuli.

Manipulation Checks. The (regression-method) factor scores of the motivation, capacity, and opportunity factors were subjected to t-tests to estimate the extent to which they varied systematically given the respective manipulations. Table 1 presents the results of these tests. The results show that the independent variables induced the hypothesized subjective experiences in the subjects, i.e., that the manipulations worked as intended.

Test of the conceptual model.

Using LISREL 8 (J÷reskog and S÷rbom 1993) the conceptual model specified in Figure 1 was subjected to path analysis. The results showed that the specified covariance structure (see Figure 1) fitted the data poorly (c2=123.32, df=23, p=.000; goodness of fit index=.83). Inspection of the modification indices suggested several unexpected but theoretically interesting additional paths: from motivation to AAD and from capacity to AAD and AB. Also, an error covariance was suggested between RECAD and RECB.

Reestimation of the path model including these new paths resulted in a significant improvement over the first model although the final fit indices remained unsatisfactory (c2=51.43, df=20, p=.000; goodness of fit index=.92; Dc2=80.89, Ddf=3, p-<-.001).

The path analyses highlighted several aspects. First, that motivation, capacity, and opportunity have independent effects on a subset of the processing variables RECAD, RCLAD, RECB, and RCLB. Second, motivation and capacity also have independent and direct effects on the affective outcome variables AAD and AB. Third, the role of opportunity is limited to influencing the cognitive processing variables, and it does not affect processing outcomes later in the information processing hierarchy.

The intention to act upon the information contained in the advertisement either through asking for additional information or by wanting a test drive is marginally positively influenced through AAD; AAD also influenced AB. These relationships are consistent with general research on the role of AAD in advertising research although we also expected a positive influence of AB on IACT (see, e.g., Brown and Stayman 1992).

The results reported in Table 2 provide only partial support for the hypotheses. Motivation, capacity, and opportunity are not consistently related to advertising processing effects and more general advertising effects. Yet, individual relationships suggests that each one of these factors does have a function in the explanation of the variance in the dependent measures.


The main goal of the present study was to assess the relevance of the explicit distinction of an opportunity factor apart from motivation and capacity factors. Opportunity was found to have a significant impact on brand name recall and on brand name recognition. However, it did not affect the recall and the recognition of the advertisement.

Several characteristics of the present study may account for the observed findings. First of all, it should be noted that there are no well developed and standardized measurement scales for motivation, capacity, and opportunity. Second, the opportunity manipulation may have suffered from the complexities discussed in the introduction. Opportunity was manipulated by varying exposure time, and exposure times were set at 'barely enough to see the picture and read the text' and 'amply sufficient' (almost twice as much exposure time). This manipulation may have been experienced by subjects as being sufficient and more than sufficient. In other words, opportunity may have been manipulated in a positive region of the opportunity dimension, and may not have created opportunity differences as intended by the authors. The effect of opportunity on brand name related measures warrants more systematic attention to the opportunity variable in future studies. Here we want to repeat the suggestion that advertising research may be biased toward favorable opportunity or exposure time conditions.



Another characteristic of this study that may have affected the nature of its outcomes is the quality of the advertising stimuli. The stimuli were non-professional mock-up ads which led to relatively low evaluations by the subjects. As a result, the high motivation stimuli received in fact a neutral score on the evaluation dimension, and the low motivation stimuli received a very low score. This may imply a deviation from the types of advertising messages used in main stream advertising studies, and may provide an explanation for the unexpected negative (significant) relationship is observed between Motivation and RCLAD: -.46 (t=3.28, p<.01). A post hoc interpretation of this result is that remarkably unattractive ads were remembered better than the more professional looking ones.

It would be premature to point here at managerial implications of the results obtained with this study. However, some general observations can be made that point to the relevance of the present discussion for advertising practice. One of the most notable differences between advertising exposure in laboratory conditions and in real life is that in the former, the opportunity to process a message tends to be relatively favorable. Actual advertising situations, media characteristics or environmental factors strongly affect the opportunity to process a message. Actual exposure conditions rarely come close to the ideal viewing situation: either processing time is insufficient (fast ads, MTV-like productions) or distraction is too high (crying children in the living room). Although ads may have been perfectly executed to capture consumers' attention, to touch them personnally, and talk to them at the correct level of understanding, consumers need the opportunity to process these. To put it differently, the effects of motivation and capacity may very much depend upon the availability of sufficient opportunity to process. In future studies, effects of motivation and capacity should be studied under diffent opportunity conditions to approach external validity and contribute to the question of accountability.


Andrews, J. Craig (1988), "Motivation, ability, and opportunity to process information: Conceptual and experimental manipulation issues," Advances in Consumer Research, 15, 219-225.

Batra, Rajeev and Ray, Michael L. (1986), "Situational effects of advertising repetition: The moderating influence of motivation, ability, and opportunity to respond," Journal of Consumer Research, 12, 432-445.

Brown, Stephen and Stayman, Douglas M. (1992), "Antecedents and consequences of attitude toward the ad. Journal of Consumer Research, 19, 34-51.

Curry, Bruce and Moutinho, Luiz (1993), "Neural networks in marketing: Modelling consumer responses to advertising stimuli," European Journal of Marketing, 27, 5-20.

Foxman, E.R., P.W. Berger and J.A. Cote (1992), "Consumer brand confusion: A conceptual framework," Psychology and Marketing, 9, 123-141.

Foxman, E.R., Muehling, D.D. and Berger, P.W. (1990), "An investigation of factors contributing to consumer brand confusion," Journal of Consumer Affairs, 24, 170-189.

J÷reskog, Karl G. and S÷rbom, Dag (1993), LISREL 8. Chicago, Ill. Scientific Software International, Inc.

MacInnis, Deborah J. and Bernard J. Jaworski (1989), "Information processing from advertisements: Toward an integrative framework," Journal of Marketing, 53, 1-23.

MacInnis, Deborah J., Christine Moorman, and Bernard J. Jaworski (1991), "Enhancing and measuring consumers' motivation, opportunity, and ability to process brand information from ads," Journal of Marketing, 55, 32-53.

Petty, Richard E. and John T. Cacioppo (1983), "Central and peripheral routes to persuasion: application to advertising," in Advertising and Consumer Psychology, eds. Larry Percy and Arch G. Woodside. Lexington, MA: Lexington Books, 3-23.

Petty, Richard E. and John T. Cacioppo (1986), Central and Peripheral Routes to Attitude Change, New York: Springer-Verlag.

Poiesz, Theo B.C. and Henry S.J. Robben (1994), "Individual reactions to advertising; theoretical and methodological developments," International Journal of Advertising, 13, 25-53.

Robben, Henry S.J. and Theo B.C. Poiesz (1993), "The operationalization of motivation, capacity and opportunity to process an advertising message," European Advances in Consumer Research, 1, 160-167.

Zaichkowsky, Judith L. (1985), "Measuring the Involvement Construct," Journal of Consumer Research, 12, 341-352.



Theo B.C. Poiesz, Tilburg University, the Netherlands
Henry S.J. Robben, Delft University of Technology, Delft, The Netherlands


NA - Advances in Consumer Research Volume 23 | 1996

Share Proceeding

Featured papers

See More


Is Warm Always Trusting? The Effect of Seasonality on Trustworthiness

Gretchen Wilroy, Pennsylvania State University, USA
Margaret Meloy, Pennsylvania State University, USA
Simon Blanchard, Georgetown University, USA

Read More


H2. Influencing Consumer Response to Products with High Styling: The Role of Mindsets

Ying-Ching Lin, National Chengchi Uniersity, Taiwan
Angela Chang, Northeastern University, USA

Read More


Don’t Stop! Partitioning Increases Satiation to Food

Cammy Crolic, University of Oxford
Yang Yang, University of Florida, USA
Yangjie Gu, HEC Paris, France

Read More

Engage with Us

Becoming an Association for Consumer Research member is simple. Membership in ACR is relatively inexpensive, but brings significant benefits to its members.