PROCEDIMIENTOS EN CATALOGACIÓN

Given the limitations in the Theory of Reasoned Action, Ajzen (1991) has improved this model into the Theory of Planned Behavior. In this new model (see 3.2), he explains that apart from behavioral beliefs and normative beliefs, human behav-ior is also guided by control beliefs. The schematic model depicts that beliefs are antecedents to attitude, subjective norms, and perceived behavioral control. In ex-plaining the process of intention-behavior and its determinants relationship, he de-scribed that behavioral beliefs is more to do with beliefs about the likely conse-quences, or other attributes of the behavior and normative beliefs refers to some-one’s beliefs about the normative expectations of other people that she or he per-ceived is important, while the term of control beliefs is used to explain the presence of factors that may further or obstruct someone to perform the behavior.

Moreover, Ajzen (1991) defines that attitude (A) is a function of behavioral be-liefs (b), outcome evaluations of bebe-liefs (e), and the number of salient outcomes (n_b).

This function is expressed as shown in Equation 6.1. According to Mathieson (1991), behavioral belief refers to subjective probability that a person’s behavior will lead to a particular outcome, while an outcome evaluation expresses a rating of the de-sirability of the outcome. For the purpose of this study, I employ the function’s denotations that Mathieson (1991) adapted in his research in explaining the Theory of Planned Behavior.

bbi= behavioral belief i,

FIGURE3.2: The schematic representation of the theory of planned behavior

Source: Ajzen ( 2002a, p. 1)

oei = outcome evaluation of belief i, n_b = number of salient outcomes.

As mentioned by Ajzen (1991), subjective norms is a function of normative be-liefs (n) that reflect the likelihood that important referent individuals or groups suggest or not suggest of performing a given behavior and motivation to comply (m) across the number of salient others (no). The appropriate function of subjective norms is illustrated in Equation 3.2.

SN=

no

i

∑

nbimci (3.2)

SN = subjective norms,

nbi = normative beliefs about referent other i, mc_i= motivation to comply with referent other i, no = number of salient others.

According to Ajzen (1991), among the beliefs that ultimately determine intention and action, lie a set of presence or absence of requisite resources and opportunities.

This argument brings us to a term of perceived behavioral control, which is com-puted as a function of the control beliefs (c) and perceived power of the control factor (p) to facilitate or inhibit performance of the behavior across the nc salient control beliefs. Equation 3.3 exemplifies perceived behavioral control function.

PCB=

nc

i

∑

cb_ipf_i (3.3)

PCB = perceived behavioral control,

cbi= control belief about the availability of skill, resources, or opportunity i, pfi= perceived power of skill, resource or opportunity i,

no = number of salient skills, resources, or opportunities.

Furthermore, Ajzen (1991) also mentioned the importance of perceived behav-ioral control operationalization, which has to be distinguished into either as a global or as a belief-based measure. He described that if a global measure consists of a 2-to 4-item scale designed 2-to directly assess a person’s overall perception of control, while a belief-based measure includes a list of individual control beliefs that she or he considers salient. He believes that by inquiring a belief-based perceived behav-ioral control measure, the measurement can be expected to be more accurate as the measurement is based on more information, and on the other side, with a global measure, a person is expected to consider all possible factors of her or his perceived behavioral control. Eventually, he argues a general rule that if one perceives that she or he has more favorable attitude and subjective norms, and the greater perceived control over performing the behavior, the person is more likely to form strong in-tentions to perform the behavior.

During the past decade, the Theory of Planned Behavior has been employed to examine a wide variety of behaviors with considerable success. These behav-iors include examining the intention to recycling wastepaper, attitude and pro-environmental action, intention to softlifting or illegal duplicating the copyrighted software by individuals for personal use, trying to consume, risk perception and trust in food safety information, predicting user intentions towards new computer system (e.g., Mathieson, 1991), and also examining the intention to purchase organic foods and genetically modified food products (e.g., Cheung et al., 1999; Goles et al., 2008; Lobb et al., 2007; Bagozzi & Warshaw, 1990; Chen, 2007; Sparks et al., 1992;

Bredahl et al., 1998; Cook et al., 2002; and Townsend & Campbell, 2004). Although the findings offer considerable support for the robustness of the Theory Planned Behavior in explaining intention, however, there is some indication that the theory is more appropriate in well established markets that are characterized by clearly formulated behavioral patterns such as in UK consumers (Kalafatis et al., 1999).

Hoyer & Maclnnis (2007) provided a more comprehensive literature, in which he characterized that there are some factors that affect whether a consumer’s attitudes will influence his or her behavior:

• Level of involvement/elaboration. Attitudes are more likely to foresee be-havior when cognitive involvement is high and consumer elaborate or think

extensively about the information that gives rise to their attitudes.

• Knowledge and experience. Attitudes are more likely to be strongly held and predictive of behavior when the consumer is knowledgeable about or experi-enced with the object of the attitude.

• Analysis of reasons. Consumers’ analysis of reasons for brand preference in-creases the relation between attitude and behavior.

• Accessibility of attitudes. Attitudes are more strongly related to behavior when they are easily reached or ‘top of mind’. Conversely, if an attitude cannot be easily remembered, it will have little impact on behavior.

• Attitude confidence. Confidence is more likely to be stronger when the atti-tude is based on either a greater amount of trustworthy information.

• Specificity of attitudes. Attitudes have a propensity to be good predictors of behavior when it is very specific about the behavior that it tries to predict.

• Attitude-behavior relationship over time. It leads to the important needs to keep consumers’ attitude away from declining over time.

• Situational factors. Intervening situational factors can put off behavior from being performed and can thus weaken the attitude-behavior relationship. This reason gives us an example of a consumer that might have a very positive attitude toward a product, but he or she might not purchase it because of its unaffordable price.

• Normative factors. Normative factors refer to how other people in the social environment influence consumer behavior.

• Personality variables. Certain personality types are more likely to show stronger attitude-behavior relationships than are others.