Chapter XIII Contemporary Information Systems Alternative Models...

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Chapter XIIIContemporary Information

Systems Alternative Models to TAM:

A Theoretical Perspective

Ahmed Y. MahfouzPrairie View A&M University, Texas, USA

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

AbsTRAcT

Based on the theory of reasoned action, the technology acceptance model (TAM) has been one of the most widely used theories in management information systems research. This chapter proposes several alternative theories from the literature to TAM. Four theories are showcased that actually reveal a reverse relationship in contrast to the traditional attitude-behavior relationship in TAM. These four theories are theory of cognitive dissonance, social judgment theory, theory of passive learning, and self-perception theory. Other alternatives to TAM and other popular theories are flow theory, cognitive load theory, capacity information processing theory, and information processing theory. These theories are applicable in e-commerce, online consumer behavior, online shopping, immersive gaming, virtual social interactions, and cognitive research. Pragmatic examples are shown for the theories.

InTRODucTIOn AnD bAckgROunD

The technology acceptance model or TAM (Davis, 1989; Davis et al., 1989) has been one of the most popular theories utilized in IS research. TAM adoption has been in countless areas, beyond

the initial intended application of the theory, technology adoption in organizations. Over 700 citations have been made of the Davis’s et al. (1989) article (Bagozzi, 2007). An entire special issue of the Journal of the Association for Information Systems (JAIS) in April 2007 was dedicated to TAM, recounting the vast impact of the theory,

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Contemporary Information Systems Alternative Models to TAM

as well as its shortcomings, such as its simplic-ity (Bagozzi, 2007; Benbasat and Barki, 2007; Hirschheim, 2007).

This research proposes several alternative theories from the literature to TAM. Instead of the traditional attitude-behavior relationship in TAM, four theories are included to show how the reverse of the relationship, behavior-attitude, is possible: theory of cognitive dissonance, social judgment theory, theory of passive learning, and self-perception theory. TAM (Davis, 1989; Davis et al., 1989) is based on the theory of reasoned ac-tion or TRA (Fishbein, 1967; Fishbein and Ajzen, 1975), which was later extended to the theory of planned behavior or TPB (Ajzen, 1991). Table 1 shows a list of attitude-behavior link theories and their reverse link counterparts (Assael, 1998; Davis, 1989; Davis et al., 1989).

Other alternative theories to TAM are flow theory, cognitive load theory, capacity information processing theory, and information processing theory. These theories are relevant in multiple ar-eas in IS, including ecommerce, online consumer behavior, online shopping, immersive gaming, virtual social interactions, and cognitive research. Examples of implementations of the theories are also discussed.

Hence, the objectives of this paper are to provide the following:

• Suggest several alternative theories to TAM from the literature for IS research.

• Propose, specifically, theories that exhibit a reverse relationship to the traditional attitude-behavior link in TAM.

• Discuss more alternative theories, especially flow theory.

• Apply these theories with a discussion and examples.

TAm, TheORIes Of ReAsOneD AcTIOn, AnD plAnneD behAVIOR

TAM is based on TRA (Fishbein, 1967; Fishbein and Ajzen, 1975). TRA tries to explain the linkage between attitude and behavior. The influence of attitude towards an actual behavior happens as consciously intended (Davis et al., 1989) or rea-soned action through the mediating effect of be-havioral intention. This mediating effect between attitude and behavior is also called the sufficiency assumption (Bettman, 1986). It is more significant to consider users’ attitude towards purchasing or using a product than their attitude towards the object or brand itself in predicting their behavior of purchase intention (Fishbein, 1967; Fishbein and Ajzen, 1975). For example, a customer may have a favorable attitude towards a very powerful Dell computer system but an unfavorable attitude toward purchasing it due to cost. The theory was later modified to incorporate beliefs (evaluations of action) and social norms (Fishbein, 1967; Fish-bein and Ajzen, 1975). Evaluations of action are a person’s beliefs about perceived consequences of one’s actions. Social norms are a combination of normative beliefs (perceived expectations of one’s family and peers) and motivation to comply with these expectations (Fishbein, 1967; Fishbein and Ajzen, 1975).

Table 1. Attitude-behavior vs. behavior-attitude theories

Attitude-Behavior Theories Behavior-Attitude Theories

Theory of Reasoned Action Cognitive Dissonance Theory

Theory of Planned Behavior Social Judgment Theory

Technology Acceptance Model Theory of Passive Learning

Self-Perception Theory

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TRA was later extended to the theory of planned behavior (TPB) which includes perceived behavioral control as another determinant of intention and behavior (Ajzen, 1991). Mathieson (1991) compared TAM and TPB in predicting user intentions. TPB is shown in Figure 1. TRA is depicted graphically in Figure 2.

Based on TRA, TAM is a theory that explains user adoption of technology at the organizational level. It is one of the most widely used theories in IS literature. The theory establishes a chain of

causality of beliefs about the technology, attitudes towards using the technology, behavioral inten-tions of use of the system, and behaviors or actual usage of the technology (Heijden et al., 2003), as shown in Figure 3. According to Davis (1989) and Davis et al. (1989), two beliefs (perceived usefulness and perceived ease of use) predict at-titudes, which in turn influence intended use of a technology. This intention then consequently im-pacts behavior of actual system usage. Perceived usefulness is the degree to which a user thinks a

Figure 1. Theory of planned behavior

Figure 2. Theory of reasoned action

Figure 3. Technology acceptance model

Behavioral Intention

Behavior

Perceived Behavioral Control

Subjective Norm

Attitude Toward Act or Behavior

Social Norms

Attitude Towards Behavior

Intention to Act

Evaluations of Action

Actual Behavior

Perceived Ease of Use

Perceived Usefulness

Attitude Towards Using a Technology

Intention to Use a Technology

Behavior or Actual Usage of

a Technology

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technology would enhance performance or pro-ductivity in the workplace. Perceived ease of use is the degree of lack of effort required by the user in adopting a given technology. Perceived ease of use also affects perceived usefulness (Davis, 1989; Davis et al., 1989).

ReVeRse RelATIOnshIps TO TAm: AlTeRnATIVe TheORIes Of behAVIOR-ATTITuDe

This paper postulates four theories from the lit-erature that could provide alternatives to TAM, as well as explain a reverse relationship in contrast to the traditional attitude-behavior relationship in TAM or TRA. Explaining this reverse rela-tionship, these four theories show how behavior can affect subsequent attitude (such as online at-titude postpurchase): cognitive dissonance theory (Festinger, 1957), Sherif’s social judgment theory (Sherif et al. 1965), Krugman’s theory (1965) of passive learning, and Bem’s (1967, 1972) self-perception theory.

cognitive Dissonance

First, the theory of cognitive dissonance is an example of how behaviors can influence attitudes (Assael, 1998). According to cognitive dissonance theory (Festinger, 1957), a conflict occurs when an individual’s attitudes and behaviors are not congruent. The individual tries to reduce this conflict by changing one’s opinion to conform to the outcome of one’s behavior. For example, if consumers buy an Apple Macintosh computer instead of a PC, they may later have doubts about the purchase when they reevaluate the alternative platform. To reduce this dissonance in cognition or postpurchase conflict, they may extensively highlight the attributes of their current platform to reduce this discrepancy in belief or opinion. Hence, the behavior (purchase) is reinforced and results in more positive feelings (attitude) post-

purchase about the chosen decision. An example of implementing cognitive dissonance theory in systems development, Szajna and Scamell (1993) uncovered an association between realism of us-ers’ expectations and their perceptions, but not their actual performance, regarding an informa-tion system.

social Judgment Theory

Second, Sherif’s social judgment theory (Sherif et al., 1965) can explain how behavior can impact attitude (Assael, 1998). A recipient’s judgment on a persuasive message depends on one’s position on the topic. There are three categories of positions: latitude of acceptance (range of acceptable posi-tions), latitude of rejection (range of objectionable positions), and latitude of noncommitment (range of neutral positions). An assimilation effect occurs when recipients of a message exaggerate the degree of agreement between their beliefs and the mes-sage, since they agree with the message. However, a contrast effect occurs when the recipients of a message overstate the difference between their beliefs and the message, since they disagree with the message. Small to moderate discrepancies between the recipient’s beliefs and the message’s position (within the latitude of acceptance and noncommitment) will cause changes in attitude, but large discrepancies (within the latitude of rejection) will not. Simply put, individuals filter in and out messages they agree with or disagree with, respectively, and they will view a message they agree with more positively than it really is, and vice versa.

For example, when expectations regarding a decision or behavior are not met, dissatisfaction (or disconfirmation of expectations) regarding the behavior occurs (Assael, 1998). According to social judgment theory, when users of a web site are dissatisfied somewhat with relatively in-frequent but long download times, their attitudes will change slightly (attitude) to accommodate the new expectations (assimilation effect), since they

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still feel they made the right decision initially by visiting the site (behavior). This occurs since users are accepting and assimilating of the outcome. This only occurs with minor disappointments or changes in expectations. If the users are extremely disappointed for waiting a long time to access the site, a negative attitude forms, and it is likely they overstate this negative change in attitude (contrast effect). Therefore, behavior (visiting the site) results in a change in attitude (negatively, if site visitors are extremely annoyed).

Based on social judgment theory, Nah and Ben-basat (2004) examine expert-novice differences in group decision making in a knowledge-based support environment and find that the analyses and explanations provided by knowledge-based systems better support the decision making of novices than experts. Novices are more influenced by the system and find it more useful than experts do. Reagan-Cirincione (1994) suggests Group Decision Support Systems that combine facilita-tion, social judgment analysis, and information technology should be used to improve the accuracy of group judgment. Interacting groups outperform their most capable members on cognitive conflict tasks (Reagan-Cirincione, 1994).

passive learning

Third, Krugman’s (1965) theory of passive learn-ing sheds light on how behavior can affect attitude (Assael, 1998). Krugman (1965) realizes that tele-vision is a low-involvement, passive medium of learning and advertising since individuals do not actively participate in the communication process. TV viewers have high brand recall but change little in terms of brand attitude. In a low-involvement situation, changes in attitudes may not result in modifications to behavior (Assael, 1998). This is the case with low-involvement products, or items that require little search and decision making on part of the consumer, such as toilet paper. Most TV viewers may actually rate their purchases (behavior) favorably after postpurchase, resulting

in more favorable opinions (attitudes) towards the purchase decision or brand.

self-perception Theory

Fourth, Bem’s (1967, 1972) self-perception theory can be used to explain the reverse relationship of behavior on attitude. It is viewed as an alterna-tive to cognitive dissonance theory. One does not have to experience dissonance to have an attitude change. Instead, individuals have knowledge of their emotions and internal states and reach a certain attitude based on their own overt behavior and the situations in which these behaviors take place just as an outside observer or another person would. In essence, individuals develop their own attitude by observing themselves act in various circumstances. This is especially the case when internal cues are weak or ambiguous that the individual is like an outside observer, relying on external signals to infer an internal state.

mORe TheORIes As AlTeRnATIVes

Below are several theories that serve as additional alternatives to TAM. These theories are flow theory (Csikszentmihalyi, 1975, 1990, 2000), cognitive load theory (Sweller, 1988), limited capacity information processing theory (Lang 1995, 2000), and information processing theory (Miller, 1956). These theories apply to ecommerce, online consumer behavior, online shopping, im-mersive gaming, virtual social interactions, and cognitive research.

Optimal experience and flow

Csikszentmihalyi’s flow theory (1975, 1990, 2000) views flow as a state in which individuals are so engaged in an activity that they might be oblivious to the world around them and possibly lose track of time and even of self. Known as flow experience or

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state of flow, this state becomes an optimal experi-ence, another synonym for flow, when individuals feel they are in control of their actions and in a sense of enjoyment and exhilaration, when the levels of task challenges and their own skills are both equally high. For example, some athletes or people who exercise vigorously report they have entered the zone at a peak moment of their game or exercise routine, or are lost in the experience for computer-video gamers (Csikszentmihalyi, 1997). In order to facilitate a sense of flow, online sites need to be stimulating and responsive to users. Otherwise, boredom, anxiety, and apathy experiences materialize (Csikszentmihalyi, 1975, 2000). Boredom results when the interface or site is not challenging enough, while anxiety occurs if the system is too difficult to use. Apathy hap-pens when skills of users and challenges of sites are too low, while a flow experience takes place when both skills and challenges are congruent to one another (Csikszentmihalyi, 1975, 2000). In essence, flow is created when individuals achieve concentration effortlessly and sense joy while carrying out a specific set of objectives that need responses at the workplace, in leisure, or in social engagements (Csikszentmihalyi, 1997).

An important component of this optimal expe-rience is that it is an end in itself or a reward for its own sake, becoming what is called autotelic, from the Greek word auto or self and telos or goal (Csik-szentmihalyi, 2000). An autotelic experience is intrinsically interesting and involves establishing goals, becoming absorbed in the activity, paying attention and concentrating on what is happening, and learning to enjoy direct experience. Teaching kids to educate them is not autotelic, but teaching them because one likes to interact with children is autotelic (Csikszentmihalyi, 1990). Ultimately, the line between work and leisure is blurred as they become one whole, which is called life. The German word for experience, Erlebnis, is related to the verb to live (Schmitt, 1999). Flow experi-ence has been reported in many areas such as rock climbing, chess playing, dancing, surgery,

sports, arts, music compositions, and manage-ment, to name a few (Csikszentmihalyi, 1990, 2000). Table 2 lists studies that have utilized or dealt with flow theory in information systems (with a couple in marketing). The Webster and Martocchio (1992) and Agrawal and Karahanna (2000) articles have the distinction of being two of the top 100 cited articles published between 1990-2004 in a combination of MIS Quarterly, Information Systems Research, and the IS section of Management Science (Lowery et al., 2007). Similarly, Koufaris (2002) is one of the top 100 most cited articles published from 2000 to 2004 (Lowery et al., 2007).

After a flow experience, self becomes more complex in two ways: differentiation and integra-tion (Csikszentmihalyi, 1990). Differentiation is a sense of being unique and different from other people. On the contrary, integration is a union with others, ideas, and entities outside the individual. For example, customization and personalization of a web site shopping experience is an example of differentiation, but communication with online users in chat rooms and via egroups connected by a common interest is an example of integration.

The Internet facilitates a flow experience (Chen et al., 1999; Novak et al., 2000, 2003), and online activities resulting in flow can be classified as the virtual environment itself, newsgroup discussions, chat rooms, email, and computer games (Chen et al., 1999). User shopping experience, in such contexts as web surfing, online shopping, and playing online computer games, exhibit these characteristics. When users go online, they may have a clear goal, such as searching for informa-tion on a product or purchasing that item online, and receive feedback when the system responds to their search inquiry. They may also entertain themselves through leisurely browsing a site or playing a game with other users on the web. These tasks pose challenges and require Internet skills to complete them. In essence, users are carrying out those actions and concentrating on what they are doing. Higher challenge induces increased

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focused attention online (Novak et al., 2000). The users are in control of the interface and level of interactivity and manipulate various objects and controls, like buttons and vivid 3D simulations. Experiencing other interactivity features, they customize products to their liking and personalize the experience through user profiles. In interac-tive 3D games or product simulations, they feel so absorbed in their activities (Swartout and Van Lent, 2003) and may lose self-consciousness and lose track of time. While browsing and being in a virtual environment and undergoing this sensory, affective, and cognitive experience so far, users feel time distortion, enjoyment, and telepresence, and in turn experience flow (Skadberg and Kim-mel, 2003). Those feelings are a consequence of being transported into a virtual world of fantastic games or 3D dressing rooms with virtual models of users or virtual dressing rooms, such as the case

with landsend.com and eddiebauer.com. These experiences of online navigation and playing computer games (Jennings, 2002) become auto-telic when individuals carry out those activities for their own sake. Table 3 (Csikszentmihalyi and Rathunde, 1993) shows characteristics of such flow dimensions.

McMillan (2002) proposes models of classifica-tions of interactivity in terms of users, documents, and systems. One of those models deals with flow experiences. In the user-to-system interactivity models, as shown in Figure 4 (McMillan, 2002), there are two dimensions: center of control (human vs. computer) and interface (apparent vs. transpar-ent). She gives several examples to illustrate each model next. Computer-based interaction involves such things as users filling in online forms. Human-based interaction includes more user control, such as the case when individuals utilize

Table 2. Sample of studies dealing with flow experience

Relevant Findings Source

Web site complexity affects flow in online shopping. The study examines a complete model of flow with antecedents. Guo and Poole (in press)

Using cognitive fit and flow theories, a model and guidelines are developed for establishing a customer decision support system for customized products in online shopping. Kamis et al. (2008)

Interactivity and site attractiveness impact flow experience, which allows for greater user learning. Users report sensing time distortion, enjoyment, and telepresence while browsing. Skadberg and Kimmel (2003)

In entertainment and games, in this case an interactive science murder mystery, users achieve a state of flow. Jennings (2002)

Shopping enjoyment and perceived usefulness of a site are predictors of revisits. Koufaris (2002)

Cognitive absorption dimensions are temporal dissociation, focused immersion, heightened enjoy-ment, control, and curiosity. Agrawal and Karahanna (2000)

Revised model shows skill and control, challenge and arousal, focused attention, and interactivity and telepresence increase flow. Novak et al. (2000)

Flow is important in improving web site design. Flow includes challenges, control, and feelings of enjoyment. Chen et al. (1999)

Flow is relevant to sensory, affective, and cognitive experiences. Schmitt (1999, 2003)

They propose a model that is later revised into Hoffman and Novak’s (2000) Model of Flow. Hoffman and Novak (1996)

12-item flow scale, based on Trevino and Webster’s (1992) study, suggests 3 dimensions, combining curiosity and intrinsic interest into one dimension, cognitive enjoyment. Webster et al. (1993)

Four flow measures are control, attention focus, curiosity (sensory and cognitive), and intrinsic interest, as examined in work settings using email and voice mail. Trevino and Webster (1992)

Computer or cognitive playfulness, involving spontaneous and imaginative interactions with computers, is important in IS. Webster and Martocchio (1992)

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Table 3. Flow experience characteristics

Dimension Details

Clear goals Task at hand is clear and has immediate feedback.

Challenges = skills Opportunities to act are high, along with one’s perceived ability to act.

Merge of action and awareness One-pointedness of mind

Concentration on task- at-hand Extraneous input is ignored as worries and concerns are suspended for the time being.

Control There is a perceived sense of control.

Loss of self-consciousness Transcendent feelings of belonging to something of greater importance.

Altered sense of time Sense of time going by faster.

Autotelic experience When several of the prior conditions exist, the experience is worth the effort just for its own sake.

Figure 4. Four models of user-to-system interactivity (with flow)

Human-based Interaction

S R

Computer-based Interaction

S R

Adaptive Interaction

S R

Flow

PP

InterfaceApparent Transparent

Human

Center ofControl

Computer

S = sender; R = receiver; P = participant (sender/receiver roles are interchangeable)

tools setup by programmers, such as spreadsheets and databases. Adaptive communication occurs when the system changes to accommodate users’ skills or other characteristics, such as the case with educational systems and computer games (Jennings, 2002). Flow experience emerges when the users are actively interacting with the system, and its interface is virtually transparent since users are concentrating on the task at hand. This state of flow comes about during interactive computer games, online interactions, and virtual reality episodes (Jennings, 2002; Novak et al., 2003).

Webster et al. (1993) show that flow has both affective and cognitive components since users experience control, attention focus, curiosity, and intrinsic interest while interacting with comput-ers. They call the later two cognitive enjoyment. In terms of affective shopping experiences, flow includes challenges, control, and feelings of enjoyment (Chen et al., 1999). These feelings of enjoyment and concentration (characteristics of a flow experience) in shopping leads to an increased likelihood of return visits to a web site

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and changes in behavior, such as purchase inten-tions (Koufaris, 2002).

cognitive load, limited capacity and Information processing Theories

Cognitive load theory (Sweller, 1988) defines cognitive load as the amount of working memory needed to solve a problem. Working memory is short-term memory that stores current informa-tion being processed, comparable in function to random access memory (RAM) in computers. According to the theory, whenever individuals learn something new, they build schemata (sin-gular schema), or combinations of elements that combine several elements into a holistic experi-ence. This becomes essentially a knowledge-base from which to draw information. For example, experts are better than novices in solving problems because they have a schema bank over a lifetime of learning that allows them to recognize familiar patterns in problems and solve them quickly. This process of learning can be disrupted if working memory is overloaded failing to digest the new information for proper schema acquisition.

Likewise, limited capacity information pro-cessing theory (Lang, 1995, 2000) proposes that proper processing of information is necessary for encoding, storing, and ultimately retrieving this information. However, processing is disrupted either when the recipient allocates fewer resources to the message than necessary, or the message demands more resources than the recipient has to designate to the task.

Both theories draw from a seminal and foundational theory in cognitive psychology, information processing theory (Miller, 1956), which handles chunking and short-term memory capacity. According to the theory, short-term memory can handle only seven (or five to nine) pieces of information or chunks at one time. A chunk is a meaningful unit or single element of information.

fuTuRe TRenDs

A major area of future research would involve an integrated approach, drawing upon and combining complementary constructs from various relevant theories, in an attempt at unification. The attitude-intention-behavior relationship is a fundamental one that could be a source for this research. Hun-dreds of studies have utilized TAM, and a relatively newly developed aggregate theory, the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003) has recently surfaced to incorporate TRA and TAM, as well as six other prominent theories. This aggregation of theories is useful in examining interdisciplinary phenomenon. Combining TAM and flow theory, Koufaris (2003) draws from multiple theories to explain online consumer behavior and conclude that shopping enjoyment and perceived useful-ness of a site affect intention to revisit a web site. Skadberg and Kimmel (2004) determine that the indirect effect of flow on attitudinal and behavioral changes is mediated by increased learning about content of a site. These changes include positive attitudes towards the site, site revisits, and a higher propensity to gather more information about the site. Heijden et al. (2003) combine both TRA and TAM to investigate online purchase intentions and conclude that perceived risk and perceived ease of use directly affect attitude towards purchase. Moreover, empirical relationships can also be examined in light of the reverse relationships to TAM discussed above, as in the behavior-attitude vs. attitude-behavior links, based on cognitive dissonance, social judgment theory, theory of passive learning, and self-perception theory.

Furthermore, a significant avenue for future research is to investigate the relationships between attitude and intended or actual behavior, in terms of collaborative experiences in a very narrow context, such as virtual social interactions and immersive online gaming experiences, and how they affect player flow experiences and cogni-tive skills. Besides the use of flow theory, the

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cognitive analysis could be explained using the aforementioned theories: cognitive load theory, limited capacity information processing theory, and information processing theory. Combining another possible future research stream (with relational experience), a new study can examine how social norms, such as between peer groups in chat rooms or instant messaging sessions, impact user behavior (e.g. purchase of products online). Such a study can be even more parsimonious in its focus and instead utilize TAM to investigate the same relationships but in the context of infor-mation technology in the workplace.

cOnclusIOn

This research proposes several alternative theories from the literature to TAM. Instead of the traditional attitude-behavior relationship in TAM, four theories are included to show how the reverse of the relationship, behavior-attitude, are possible: theory of cognitive dissonance, social judgment theory, theory of passive learning, and self-perception theory. Other alternative theories are flow theory, cognitive load theory, capacity information processing theory, and information processing theory. These theories are applicable in many areas in IS: ecommerce, online consumer behavior, online shopping, immersive gaming, virtual social interactions, and cognitive research. Examples of implementations of the theories are also shown.

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key TeRms AnD DefInITIOns

Capacity Information Processing Theory: Proposes that proper processing of information is necessary for encoding, storing, and ultimately retrieving this information. However, processing is disrupted either when the recipient allocates fewer resources to the message than necessary, or the message demands more resources than the recipient has to designate to the task.

Cognitive Load Theory: Defines cognitive load as the amount of working memory needed to solve a problem. Working memory is short-term memory that stores current information being processed. Whenever individuals learn something new, they build schemata, or combinations of elements that combine several elements into a holistic experience. This process of learning can be disrupted if working memory is overloaded failing to digest the new information for proper schema acquisition.

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Flow Theory: Views flow as a state in which individuals are so engaged in an activity that they might be oblivious to the world around them and possibly lose track of time and even of self. Indi-viduals feel they are in control of their actions and in a sense of enjoyment and exhilaration, when the levels of task challenges and their own skills are both equally high. It is equated to entering the zone (for athletes) or being lost in the experience (for computer video gamers).

Information Processing Theory: Is a seminal and foundational theory in cognitive psychology. According to the theory, short-term memory can handle only seven (or five to nine) pieces of information or chunks at one time. A chunk is a meaningful unit or single element of information.

Self-Perception Theory: Indicates that in-dividuals have knowledge of their emotions and internal states and reach a certain attitude based on their own overt behavior and the situations in which these behaviors take place just as an outside observer or another person would. In essence, in-dividuals develop their own attitude by observing themselves act in various circumstances.

Social Judgment Theory: Proposes that a recipient’s judgment on a persuasive message depends on one’s position on the topic. There are three categories of positions: latitude of ac-ceptance, latitude of rejection, and latitude of noncommitment. An assimilation effect occurs

when recipients of a message exaggerate the degree of agreement between their beliefs and the message. However, a contrast effect occurs when the recipients of a message overstate the difference between their beliefs and the message. Small to moderate discrepancies between the recipient’s beliefs and the message’s position will cause changes in attitude, but large discrepancies will not.

Technology Acceptance Model (TAM): Is one of the most widely used theories in IS lit-erature. Two beliefs (perceived usefulness and perceived ease of use) predict attitudes, which in turn influence intended use of a technology. This intention then consequently impacts behavior of actual system usage. Perceived usefulness is the degree to which a user thinks a technology would enhance performance or productivity in the workplace. Perceived ease of use is the degree of lack of effort required by the user in adopting a given technology. Perceived ease of use also affects perceived usefulness.

Theory of Cognitive Dissonance: Suggests a conflict occurs when an individual’s attitudes and behaviors are not congruent. The individual tries to reduce this conflict by changing one’s opinion to conform to the outcome of one’s behavior.

Theory of Passive Learning: Implies that a medium, such as television, is a low-involvement, passive medium of learning and advertising since individuals do not actively participate in the com-munication process.

Chapter XIII Contemporary Information Systems Alternative Models...

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