This paper aims to propose a new model in assessing individual performance on information technology adoption. The new model to assess individual performance was derived from two different theories: decomposed theory of planned behavior and task-technology fit theory. Although many researchers have tried to expand these theories, some of their efforts might lack of theoretical assumptions. To overcome this problem and enhance the coherence of the integration, I used a theory from social science literature, particularly from Blumer's theory of symbolic interactionism. This theory indicates, as Blumer himself noted, "The symbolic interactionist approach rests upon the premise that human action takes place always in a situation that confronts the actor and that the actor acts on the basis on defining this situation that confronts him." Symbolic interactionism may have theoretical strengths on the basis that reality is understood as a social production; interaction is symbolic; humans have the capacity to engage in self-reflexive behavior; interactionism regards society as ongoing process; and social and physical environments set limits on behavior, but do not determine behavior. In this essence, normally, humans use technologies not for the sake of technologies but for supporting their primary tasks, being job related or entertainment oriented. Thus, there is an interaction between human and his/her technology. In this paper, I suggest some propositions that can be tested later using experimental research design or longitudinal survey research.
KEYWORDS: Individual Performance, Human-technology Interaction, Decomposed Theory of Planned Behavior, Task-technology Fit Theory
The interaction between information technology and individual performance has been an ongoing concern in Information System (IS) research. Since information technology adoption is related with human, researchers use psychology theory to predict human behavior on that regard: Theory of Reasoned Action/TRA (Fishbein and Ajzen 1975), Theory of Planned Behavior/TPB (Ajzen 1985, 1991), Technology Acceptance Model/TAM (Davis, 1989), and recently, Decomposed Theory of Planned Behavior/DTPB (Taylor and Todd 1995, Hsu and Chiù 2004, Koeder et al. 201 1). As to predict individual performance, IS researcher uses the concept of "fit" to investigate the interaction of task and system characteristics and their effects on information system usage and task performance: Task-TechnologyFit/TTF theory (Goodhue and Thompson 1995, Dishaw et al. 2002, Klopping and McKinney 2004, McGill and Hobbs 2006, Usoro et al. 2010).
This paper proposes a new model of the linkage between information technology adoption and individual performance by drawing on insight from these two streams of research (user behavior as predictors of system usage and task-technology-fit as predictors of performance). The core content of this new model, called Human-Task-Technology Interaction and Performance Model (HTTIP), is the deposition that for information technology has a positive impact on individual performance, not only the technology must be accepted and used, but also the technology must be a good fit with the task it supports.
To develop a new model, I focus on the DTBP (Taylor and Todd 1995) and TTF (Goodhue and Thompson 1995). The DTBP has advantages over other acceptance models in that it identifies specific prominent beliefs that may influence information technology usage. The model has better predictive power compared to the initial TPB and ???. Likewise, the TTF theory defines a model that has been used to explain information system utilization. Goodhue and Thompson's (1995) research describes the relationship between the task requirements of the user and the functionality of the system and their impact on utilization. Performance impacts will occur when the technology meets the users' needs and provides features that support the fit of the requirements of the task. …