An Empirical Assessment of Technology Adoption as a Choice between Alternatives (original) (raw)
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Expectation Confirmation in Information Systems Research: A Test of Six Competing Models
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Expectation confirmation research in general, and in information systems (IS) in particular, has produced conflicting results. In this paper, we discuss six different models of expectation confirmation: assimilation, contrast, generalized negativity, assimilation-contrast, experiences only, and expectations only. Relying on key constructs from the technology acceptance model (TAM), we test each of these six models that suggests different roles for expectations and experiences of the key predictor--here, perceived usefulness--and their impacts on key outcomes--here, behavioral intention, use, and satisfaction. Data were collected in a field study from 1,113 participants at two points in time. Using polynomial modeling and response surface analysis, we provide the analytical representations for each of the six models and empirically test them to demonstrate that the assimilation-contrast is the best existing model in terms of its ability to explain the relationships between expectations and experiences of perceived usefulness and important dependent variables--namely, behavioral intention, use, and satisfaction--in individual-level research on IS implementations.
Journal of the Association for Information Science and Technology, 2016
Research on information technology (IT) adoption and use, one of the most mature streams of research in the information science and information systems literature, is primarily based on the intentionality framework. Behavioral intention (BI) to use an IT is considered the sole proximal determinant of IT adoption and use. Recently, researchers have discussed the limitations of BI and argued that behavioral expectation (BE) would be a better predictor of IT use. However, without a theoretical and empirical understanding of the determinants of BE, we remain limited in our comprehension of what factors promote greater IT use in organizations. Using the unified theory of acceptance and use of technology as the theoretical framework, we develop a model that posits 2 determinants (i.e., social influence and facilitating conditions) of BE and 4 moderators (i.e., gender, age, experience, and voluntariness of use) of the relationship between BE and its determinants. We argue that the cognitions underlying the formation of BI and BE differ. We found strong support for the proposed model in a longitudinal field study of 321 users of a new IT. We offer theoretical and practical IT implications of our findings.
Factors affecting the adoption of new technologies
The study aims to identify how personal characteristics of bank employees influence the drivers of new information technologies adoption. Based on the theory of Technology Acceptance Model (TAM) the proposed methodology is investigating how employees’ demographic and psychographic variables affects their beliefs about their self-efficacy on using the new information technology, as well as about the technology’s ease of use and usefulness. The survey was conducted in a sample of 697 bank employees in several bank institutions in Greece using a dedicated research instrument. The results indicated that employees’ self-efficacy and perception about technology’s ease of use and usefulness are affected by their level of education, while employees’ age is related to employees’ self-efficacy and technology easiness and not to technology usefulness. As far as the employee’s psychographic variables are concerned, contrary to previous research efforts, mood has not revealed any impact on their beliefs about the technology characteristics. Finally, theoretical contributions and practical implications of the findings are discussed and suggestions for future research are presented.
Modeling Choice between Competing Technologies
Developing Business Strategies and Identifying Risk Factors in Modern Organizations, 2014
Even though there is a rich and extensive literature on the individual adoption of technologies, limited attention has been placed on the choice of one among competing alternatives, which the authors posit as an essential antecedent to the individual acceptance decision that has been considered in the past. In this chapter, they compare two levels at which the choice can be made—expectations and intentions—and then review and contrast four different comparison mechanisms that can integrate the evaluations made at each level as predictive of actual choice. These were investigated by asking business professionals to assess and evaluate technologies for potential adoption within their domain of expertise, and then a second study was conducted to further validate the results thus obtained. The authors also extensively discuss the implications of this research for future work on the processes leading to adoption of information technologies.
Previous research shows that selecting an appropriate theory or model has always remained a critical task for IS researchers. To the best of the authors' knowledge, there are few papers that review and compare the acceptance theories and models at the individual level. Hence, this article aims to overcome this problem by providing a critical review of eight of the most influential theories that have been used to predict and explain human behaviour towards adoption of various technologies at the individual level. This article also summarizes their evolution; highlight the key constructs, extensions, strengths, and criticisms from a selective list of published articles appeared in the literature related to IS. This review provides a holistic picture for future researchers in selecting appropriate single/multiple theoretical models/constructs based on their strengths and weaknesses and in terms of predictive power and path significance. It is concluded that a well-established theory should consider the personal, social, cultural, technological, organizational and environmental factors