Index of Paper Presentations for the Parallel Sessions - Academy of ...

customer satisfaction (Bolton 1998, Mittal et al. 1999), and intention to purchase (LaBarbera and Mazursky, 1983,Mittal et al., 1999).The preceding discussion leads us to believe that user evaluations will undergo the same sequential updatingmechanisms as do consumer evaluations. To provide richer insights into how user evaluations unfold over time,therefore, it is essential to incorporate the theory of belief updating into the TAM framework. When applied in thecontext of continued use, the theory of belief updating suggests that for TAM: PEOU, PU, and INT at T = 1 willserve as anchors for future evaluations at T= 2 which will be updated with new adjustments. More specifically, INT (T = 2) is formed based onINT (T= 1), ATT (T= 2), and PU (T= 2); ATT (T= 2) is in turn determined by ATT (T= 1), PU (T= 2) and PEOU(T= 2); PU (T=2 is determined by PU (T= 1) and PEOU (T=2), finally, PEOU (T= 2) is also a function of PEOU (T=1) and other factors outside the boundary of this study (Figure 1).As opposed to common prejudice that individual behavior is mostly led by beliefs and attitudes; Melone (1990)found that much research in social psychology have been theorized on a reversed causal relationship from behaviorto beliefs and attitudes. However, most research to date in the IS domain has focused on the influence of userevaluations on user behavior rather than in the opposite direction (Kim and Malhotra, 2005). Abundant evidenceattests to the role of past behavior in the formation of judgments and intention. In a meta-analysis based on 64independent studies, Ouellette and Wood (1998) also showed that past behavior was significantly related to attitudes,subjective norms, perceived behavioral control, and intention. More specifically, the theory posits that (1) whencarrying out a routine task, the person will use rules of thumb as a way to save cognitive capacity but (2) forperforming an unfamiliar task, the individual will carefully process relevant information to arrive at a judgment. Thepreceding discussion suggests that whereas the sequential updating mechanism prevails among novice/light users(digital immigrants); the feedback mechanism is likely to occur mainly among experienced/heavy users (digitalnatives). Because both decision-making strategies are plausible in the context of continued use, we propose that EXPwill have a positiveeffect on respective determinants of each CTM at each time period (as shown in Figure 1).From the perspective of cognitive psychology, habit is made possible by a cognitive representation that links asituational cue and an action (Verplanken et al., 1997). This mental linkage is established as a result of repeatedperformances of the same behavior. That is, it is the well-learned mental structure that consistently instigates aroutinized behavior (e.g., visiting a favorite news Web site) given a situational cue (e.g., before beginning work inthe morning) without requiring deliberate decision making. Given the established cognitive structure, then thefrequency with which the behavior of interest is performed (i.e., the number of actions) is almost the same as thenumber of opportunities (i.e., the number of cues) to perform the behavior. In a stable context, furthermore, theoccurrence of opportunities in the past will be similar to the number of occurrences in the future.Consequently, future behavior, which is a function of future opportunities, tends to correlate with pastbehavior. Therefore, along with conscious intention, past use may be able to explain the variance in future use. Notethat we do not expect an individual user to follow both conscious (INT) and automatic processes past use/habit(EXP) simultaneously. I anticipate that both processes will coexist among various types of users (ranging fromoccasional to heavy users) within the context of continued use. To sum up, we propose the final hypothesis that USEat t = 1 will influence EXP at t = 2.