Resource Matching Hypothesis – RM

On the premise that human cognition has limited resources and at a given time, only a portion of the available resources will be allocated to process message, Anand and Sternthal (1989) proposed the Resource-Matching Hypothesis to explain the relationship between message persuasion/effectiveness and resource utilisation. As with Lang’s model, this theory also used the principles of memory to some extent and mentioned that message effectiveness is determined by cognitive resources which act as internal inputs for processing (Anand & Sternthal, 1989). In this theory, there are

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two situations that would undermine the effectiveness of a message: first, when the demand for cognitive resources by particular stimuli is less than what is allocated by the person at that time to process the message and second, when the demand for cognitive resources exceed that of available. The first leads to an abundance of resources while the second leads to cognitive overload. Hence, the effectiveness of the message would be superior in the resource matching condition. The theory does not suggest allocating all the cognitive resources available at a given time but rather suggests that one will allocate a certain amount of resources to process a message and whether the message’s demand for resources matches with that of allocated. As a result, the persuasion of the message will follow a Wundt (inverted “U”) curve.

With Scarcity of Resources

Resources will be limited in situations where the recipient fails to allocate enough resources. This may be mainly due to motivational issues. In other words, motivated recipients tend to allocate more resources to the pool of resources for processing the message than their unmotivated counterparts. The personal relevance of the message is also a part of the motivation factor. The other reason is the inherent complexity of the message to be processed that can be caused by several factors. Syntactic structure (see Section 2.4.4.1 for more information), quantitative vs. qualitative messages (e.g.

Viswanathan & Narayanan, 1994; Yalch & Elmore-Yalch, 1984), amount of factual data in a message (e.g. Chang, 2007), and the characteristics of the stimuli bundle with the message are some of these factors (e.g. Meyers-Levy & Peracchio, 1995).

Inadequacy of resources can be dealt with by either increasing the available resources in the pool of resources for processing the message or by reducing the demand for resources (Anand & Sternthal, 1989; Meyers-Levy & Peracchio, 1995). According to the hypothesis, the former can be achieved by increasing message incongruity, personal relevance of the message, and exposure to the message. Message incongruity is described in relation to the knowledge / expectations the recipients already possess.

Some factors like Need for Cognition also contribute to the motivation factor by increasing the invested resources to process the contents (Chang, 2007; Martin et al., 2005). Based on the notion that people will be motivated to acquire new knowledge that would not match with their expectations, more of the cognitive resources will be allocated to process the message (Anand & Sternthal, 1989). However, expertise makes

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it an exception in a manner that little knowledge would not trigger resource allocation while personal relevance will. Experts, on the other hand, will be motivated to allocate more resources to process the contents that are personally relevant but incongruent (Hahn & Hwang, 1999; Heckler & Childers, 1992). In the original script Anand and Sternthal noted that in the case of cognitive overload, recipients tend to rely on heuristics or peripheral cue-related evaluations. This could be because of two things.

One is that the lack of motivation makes the capacity of the resource pool small and the other is that modal specific resources may be utilised to evaluate the message. The former was supported in a research where picture and description layouts in an advertisement copy were tested against differently motivated recipients (Meyers-Levy

& Peracchio, 1995). They found that the hypothesis appeared to be true for the motivated but not for the unmotivated users.

Multiple exposures to the message will make more resources available for processing the parts of the message in subsequent occurrences. However, too much repetition will eventually undermine persuasion (e.g. Cacioppo & Petty, 1989; Claypool, Mackie, Garcia-Marques, McIntosh, & Udall, 2004) due to the abundance of resource (e.g.

Anand & Sternthal, 1990). This is common for exposure time as well and such a claim could be further supported by the type of media used. For instance, self-paced media like print may enable recipients to allocate more resources for processing due to active involvement and the ability to revisit the parts of the message (see Section 2.4.2 for more description).

With Abundance of Resources

The theory suggests that when available cognitive resources are higher than those required, persuasion/effectiveness will be undermined due to elaboration of idiosyncratic associations while having less elaboration of message content. Such idiosyncratic associations are message-related except that it is not messaging content.

They are the other related memory activated due to the message (Anand & Sternthal, 1989).

Thus, as a solution, it is suggested that the resources demanded by the message / advertisement be increased or that the pool of resources available for processing the message be trimmed. Anand and Sternthal suggest several strategies to reduce resource

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availability such as increasing the message presentation rate and introducing a distraction prior to and during the presentation of the message. The rate of message appeared to demand more of the resources mainly due to increased complexity. For instance, inclusion of diagnostic information in an advertisement will increase involvement and brand evaluation; however, further inclusion of such will attenuate brand evaluation (e.g. Chang, 2007; Peracchio & Meyers‐Levy, 1997). Based on their prior research and the other related research, Anand and Sternthal suggest that the introduced distraction would use the abundant resources preventing elaboration of idiosyncratic associations (e.g. Hahn & Hwang, 1999). However, improved effects are subject to maintaining such techniques at the optimum level as over or under doing will cause a reduction of message effectiveness.

Some of the conflicting findings in the literature can be explained from the resource matching perspective. Especially such findings are significantly positive, negative, or not significant. (Keller & Block, 1997) put such conflicts to the test with the objective of finding answers from the resource matching perspective. They manipulated vividness of information presented on health-related issues in accordance with demand for cognitive resources to process each and found that it was not the vividness per se, but the extent to which each message met the resource-matching condition determines the level of persuasion. Nonetheless, these researchers mostly manipulated one or two stimuli to maintain the “moderate” level of resource utilisation without giving due emphasis to the innate resource pressure perceived by a consumer.

2.5.3.3 LC4MP vs.RM Hypothesis

Both LC4MP and RM Hypothesis have considered cognitive resources from the available vs. allocated perspective though it is addressed differently in their respective theoretical contexts. The major difference between the two models presented here is that LC4MP is predominantly based on the theories of memory and it tries to explain the effect of memory as a result of three sub-processors and resource allocation for each by two mechanisms. It goes by the notion “when resources are allocated for processing” while the Resource Matching Theory tries to address the notion of “when resources are not fully demanded or over demanded.” Thus, the effects of the latter can be somewhat generally applicable while the former is more specific.

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The explanation for some of the findings referring to Lang’s model was not complete either. For instance, low brand recall found in high involving-experienced players in M.

Lee and Faber (2007)’s study can be considered. An alternative argument for such findings could be that involvement could allocate more resources when experienced consumers allocate less of them and thereon high recall scores, which was not the finding. A possible reason for such ambiguity is that Lang’s model could be most applicable to explaining the utilisation of resources between the sub-processors of a considered task. It does not fully explain the possible influence of the remaining resources considering the total pool of cognitive resources available, an explanation of which can be drawn from the RM Hypothesis. Furthermore, some of the findings (e.g.

M. Lee & Faber, 2007; Sundar & Kalyanaraman, 2004) explained in LC4MP could have drawn a more complete explanation had such researchers used the Resource-Matching Hypothesis as well. Accordingly, it appears that these models are more complementary in explaining the effects and thus, both are considered in explaining the respective effects of this research.

2.5.4 Summary

Cognitive load is the cognitive pressure exerted by a task to be performed on the performer’s cognitive system. It is a construct commonly considered in the domain of educational psychology and commonly applied in instructional designing. There are various methods already used by researchers to measure it. For instance, in addition to the physiological mechanisms like skin conductance, pupil dilation, and EEG, subjective measurement techniques like NASA-TLX and SWAT have also been used.

Most of the research in the field of consumer behaviour has administered secondary tasks to truncate the available working memory for processing as a means of generating the cognitive load. Two bases can be used to explain resource utilisation and its effects based on the premise that cognitive load is a reflection of resource pressure. These are the Limited Capacity Model and the Resource Matching Theory. The former tries to capture the memory effects as a result of resource allocation between sub-processors while the latter tries to capture the overarching effects of a particular message’s demand for cognitive resources vs. available resources for processing.

70 2.6 ATTITUDE

The construct of attitude has been of central importance in studies of social psychology since the beginning of the 20^th century (Crano, Cooper, & Forgas, 2010; Eagly &

Chaiken, 1993) and it can be considered as one of the most commonly addressed constructs in consumer behaviour research. It is fundamental to behaviour since it helps people to decide what to approach and what to avoid (Sweldens, Corneille, &

Yzerbyt, 2014). People evaluate information presented to them externally by sources such as the media or from their own experience (Crano et al., 2010) in order to make judgments on themselves and their surrounding environment (Albarracin, Johnson, Zanna, & Kumkale, 2005). Based on these evaluations, either favourable or unfavourable dispositions, called attitudes, are generated (Eagly & Chaiken, 1993).

Despite a number of definitions of attitude in the literature (see Allport, 1967), they all contain the notion of evaluating information and linking the subsequently generated psychological state to an object or an event. For instance, Eagly and Chaiken (1993) define attitude as “..a psychological tendency that is expressed by evaluating a particular entity with some degree of favour or disfavour” (p. 1) whereas an early definition by Allport (1967) states that “attitude is a mental and neural state of readiness, organised through experiences, exerting a directive or dynamic influence upon the individual’s response to all objects and situations to which it is related” (p. 8).

Thus, it is apparent that attitude will not be generated until an evaluation of information occurs and a link is created between such evaluation and the object concerned.

Accordingly, attitude as the “overall degree of favourability” (p. 29) towards the attitude object (Ajzen, 2001) is used as the definition in this research context.

Attitudes are stored in the memory and when the same object or a related cue is presented, these memories will get activated (Eagly & Chaiken, 1993). Hence, it gives rise to the subsequent question of whether attitude is persistent over time. Based on a review of the literature, Kruglanski and Stroebe (2005) noted that some attitudes were persistent while others were not based on the availability and/or accessibility of judgments related to such attitude object. This could even be on the same attitude object in a situation where attitudes take on ambivalence or “evaluative dissimilarity” (p. 123);

hence, it could be context-dependent as well (Eagly & Chaiken, 1993). All in all, it is

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accepted in the present day that attitude is a function of cognitive and affective experience on an attitude object and will be represented as a “summary” of such experience (Crano & Prislin, 2006).