Task-technology fit and adoption behaviors of mobile business systems

Ace p.

Order the writing of a tailor-made Computer science Essay

Free quote online

Essay Format .pdf

Task-technology fit and adoption behaviors of mobile business systems

Download

Read an extract

Reader
Abstract
Contents
Extract

Abstract

In this paper, a combined task–technology fit (TTF) and UTAUT model is proposed to explore the adoption of mobile technologies in the real estate and insurance industry. The research results indicate: (1) five constructs: data quality, authorization, timeliness, reliability, and relationship with users extract from TTF theory are the dominant factors in measuring the task-technology fit of using mobile business systems; (2) performance expectancy and effort expectancy mediate the influence of TTF on intention to continuing using mobile business systems; (3) data quality and relationship with users in TTF are the two factors that affect performance expectancy in using mobile commerce systems; and (4) relationship with users in TTF is the only factor that affects the effort expectancy in using mobile commerce systems.

In order to help employees improving task performance, many corporations have developed mobile business systems for their employees. Therefore, understanding the degree to which systems characteristics satisfy employees' task needs and what factors will influence the intention to continue using mobile business systems are critical in the implementation of mobile business system.

Keywords: Adoption, Continue Using, Mobile Business, Task-Technology Fit Theory, UTAUT Theory.

Abstract
Introduction
Literature review
1. Unified theory of Acceptance and Use of technology (UTAUT)
2. Task-technology fit model (TTF)
The cases of mobile business system
1. Case 1: Mobile Dr. insurance system
2. Case 2: The top agent PDA system
Research model and hypotheses
1. Research model
2. Research hypotheses
Research methodology
1. Research samples
2. Measurement methodology
3. Reliability and validity of research instrument
Research results
Discussion
Conclusion
References

Get this table of contents for free after login.

Extract

[...] L.; Development and Measurement Validity of a Task-Technology Fit Instrument for User Evaluations of Information Systems, Decision science pp.105-137. [10]. Goodhue, D. L.; Understanding User Evaluations of Information Systems, Management Science (41:12) pp.1827-1844. [11]. Goodhue, D. L., and Thompson, R. L.; Task-Technology Fit and Individual Performance, MIS Quarterly pp.189-211. [12]. Melone, N. P.; A Theoretic Assessment of User-Satisfication Construct in Information System Research, Management Science pp. 76-91. [13]. Moore, G. C., and Benbasat, I.; Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation, Information Systems Research pp. [...]

[...] Eight general factors were developed to measure the task-technology fit: data quality, locatability, authorization, compatibility, production timeliness, systems reliability, ease of use/training, and relationship with users (Goodhue and Thompson, 1995) The Cases of Mobile Business System Users of two mobile business systems, Mobile Dr. Insurance system and Top Agent PDA system, are the subjects of this study Case Mobile Dr. Insurance System The Mobile Dr. Insurance system is the most popular mobile insurance system which is developed by company G and is adopted by more than twelve life insurance corporations in Taiwan for more than three years. [...]

[...] Hypothesis The agents' Evaluation of Task-technology fit of using Mobile Business System will impact the Performance Expectancy and Effort Expectancy. TTF of mobile business are used to measure the degree of systems features match user task needs. When agents perceived mobile systems with high TTT, they will have higher performance expectancy and effort expectancy on their task. Hence, we postulate the agents' evaluation of TTF of using mobile business system will impact the performance 3 expectancy and effort expectancy. TTF of MBS Task Performance TTF Performance Expectancy Intention to Continue Effort Expectancy Using MBS Social Influence UTAUT Facilitating Condition Use Behavior Fig Research Model Hypothesis The Performance Expectancy and Effort Expectancy mediates the relationship of Task-Technology fit (TTF) and Intention to Continue Using (UCI) on using Mobile Business System. [...]

[...] Therefore, Hypothesis 1 that the agents' evaluation of task-technology fit of using Mobile Business System will impact the performance expectancy and effort expectancy is supported Table 3 Regression Analysis of TTF on PE and EE β Coefficient TTF Adjusted R-Square p-value [...]

[...] In practice, two successful mobile business systems are reported and the use behaviors of the systems are studied. The experiences and insights of the implementation results and using behaviors can help other corporations and industries in adopting mobile technologies. As with all research, this study has certain limitations. The sample of this study is limited to two mobile business systems users in Taiwan real estate and life insurance industry. As such, the research needs to be replicated to examine the robustness of findings across a wide range of industries and areas. [...]

pdf