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Open AccessJournal ArticleDOI

Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model

TLDR
This work presents and tests an anchoring and adjustment-based theoretical model of the determinants of system-specific perceived ease of use, and proposes control, intrinsic motivation, and emotion as anchors that determine early perceptions about the ease ofuse of a new system.
Abstract
Much previous research has established that perceived ease of use is an important factor influencing user acceptance and usage behavior of information technologies. However, very little research has been conducted to understand how that perception forms and changes over time. The current work presents and tests an anchoring and adjustment-based theoretical model of the determinants of system-specific perceived ease of use. The model proposes control (internal and external--conceptualized as computer self-efficacy and facilitating conditions, respectively), intrinsic motivation (conceptualized as computer playfulness), and emotion (conceptualized as computer anxiety) as anchors that determine early perceptions about the ease of use of a new system. With increasing experience, it is expected that system-specific perceived ease of use, while still anchored to the general beliefs regarding computers and computer use, will adjust to reflect objective usability, perceptions of external control specific to the new system environment, and system-specific perceived enjoyment. The proposed model was tested in three different organizations among 246 employees using three measurements taken over a three-month period. The proposed model was strongly supported at all points of measurement, and explained up to 60% of the variance in system-specific perceived ease of use, which is twice as much as our current understanding. Important theoretical and practical implications of these findings are discussed.

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Journal ArticleDOI

The intellectual development of the technology acceptance model: A co-citation analysis

TL;DR: A visual mapping of intellectual structure in two-dimensions is presented and the subfields of the technology acceptance model through co-citation analysis are identified by using a sequence of statistical analyses including factor analysis, multidimensional scaling, and cluster analysis.
Journal ArticleDOI

The role of context in perceptions of the aesthetics of web pages over time

TL;DR: Estimating the congruence of perceptions of aesthetic value over time, including judgements after use of a web site, manipulating the aesthetic design of web pages and studying the relationship between usability and aesthetic value concludes that context is a pivotal factor influencing the stability of users' perceptions.
Journal ArticleDOI

An investigation of employees' use of e-learning systems: applying the technology acceptance model

TL;DR: Four factors are examined that are believed to influence employees' perceived usefulness, perceived ease of use, attitudes and intention to use e-learning systems in organisations.
Journal ArticleDOI

Exploring Factors That Affect Usefulness, Ease Of Use, Trust, And Purchase Intention In The Online Environment

Yoon C. Cho, +1 more
TL;DR: In this article, the authors apply the Technology Acceptance Model (TAM) to investigate factors that affect customers' online purchasing behavior, such as product information, price, convenience, and perceived product or service quality.
Journal Article

Internet Banking Adoption Among Young Intellectuals

TL;DR: In this paper, the authors developed a technology acceptance model for internet banking, a conceptual framework to explain the factors influencing undergraduate students' acceptance of internet banking and found that PU, PEOU, perceived ease of use (PEOU), perceived credibility (PC), and computer self-efficacy (CSE) had a significant relationship with behavioral intention.
References
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Journal ArticleDOI

The theory of planned behavior

TL;DR: Ajzen, 1985, 1987, this article reviewed the theory of planned behavior and some unresolved issues and concluded that the theory is well supported by empirical evidence and that intention to perform behaviors of different kinds can be predicted with high accuracy from attitudes toward the behavior, subjective norms, and perceived behavioral control; and these intentions, together with perceptions of behavioral control, account for considerable variance in actual behavior.

Perceived Usefulness, Perceived Ease of Use, and User

TL;DR: Regression analyses suggest that perceived ease of use may actually be a causal antecdent to perceived usefulness, as opposed to a parallel, direct determinant of system usage.
Journal ArticleDOI

Perceived usefulness, perceived ease of use, and user acceptance of information technology

TL;DR: In this article, the authors developed and validated new scales for two specific variables, perceived usefulness and perceived ease of use, which are hypothesized to be fundamental determinants of user acceptance.
Book

Judgment Under Uncertainty: Heuristics and Biases

TL;DR: The authors described three heuristics that are employed in making judgements under uncertainty: representativeness, availability of instances or scenarios, and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available.
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