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How Does Personality Matter? Relating the Five Factor Model to Technology Acceptance and Use
In this paper, the researchers expound on the Five Factor Model (FFM) of personality that has been used widely in management and psychology studies to forecast behavior, but has been overlooked in the information systems field. The authors explain how the FFM can be used in information systems research by using the FFM personality factors in the framework of technology acceptance. In addition, the authors propose a dispositional outlook to comprehend user attitudes and beliefs, and investigate the impact of user personality on both the supposed importance and of the subjective practices towards the acceptance and use of technology (Devaraj et al, 2008).
Basis for the Problem
The research problem investigated in the paper stems from the failure of previous research to incorporate qualitative methods in the study of information system aspects. Even though the future of IS research points to a movement beyond the technology acceptance model, the connection between the two elements has been concisely established, and this is the basis of the research.
Clarity and Completeness of Description of the Problem
The authors give a vivid description of the research problem. They first approach the topic from a historical perspective, referring to Hubers statements in 1983 that discouraged the study of cognitive techniques as a foundation for DSS design. They also refer to previous research in the field of personality and technology acceptance and present the hypotheses tested in these studies. The authors begin from early studies and research, then move step by step to recent studies on the same topic. They relate personality and FFM, arguing that the FFM is taken to be an all-inclusive and parsimonious representation of personality (Venkatesh and Davis, 2000). Next, they present a relation between personality and technology acceptance, this consequently leads to a relation between FFM and technology acceptance. These step by step processes lead to a concise understanding of the topic under study.
Design and Conducting of the Research Study
This research study employs a commercial collaborative system (which they call eproject) to collect data. The research system organizes team efforts around particular projects, offering numerous common social features such as announcements, discussions, document versions control and voting in addition to a number of project management features such as task assignment and issue management. !80 subjects were used for the study, comprising MBA (119) EMBA (61) students and. All subjects receive similar training on various aspects of information systems. After the training, the technology acceptance model (TAM), customer self-efficacy (CSE) and other related surveys were undertaken and this provided data for analysis. Control variables were used in the survey and these included the use of a different method to measure CSE. GMA and GPA scores of the subjects were also used to test whether a connection existed between these scores and survey results.
Infrastructuring: Toward an Integrated Perspective on the Design and Use of Information Technology
In this paper, the researchers investigate how the conclusions from a current debate on e-Infrastructures can be harnessed to improve the design of information technology systems in organizations. The authors mention that in the domain of computer systems, it is common to hear talks of infrastructure when explaining either the multitude or multiplicity of IT hardware, software, and standards that contemporary organizations use in their daily processes. In these perspectives, the term infrastructure receives inadequate definition, and it is not concise whether usage of the term means methods and perspectives apart from the use of the network or IT system. This is the research problem as the authors investigate how to improve the use of IS in a concise manner within an organization (Pipek and Wulf, 2009).
Basis for the Problem
Information systems experts have traditionally focused on designing individual products and attempting to integrate them into existing organizational systems. This strategy has a weakness since the developers miss numerous activities that need to be undertaken in the applications. Research on e-Infrastructures gives an opportunity for the developers to overcome the inefficiencies between IT design and IT adoption that have dogged the IS body for a long time. This approach allows one to appreciate the role of IT designers and innovators, and hence forms the basis of this research.
Clarity and Completeness of Description of the Problem
The authors give a comprehensive description of the research problem and begin by introducing the role of IT practices on organizational management. The authors next draw attention to the infrastructural aspects of IS that are relevant and the importance of such systems in assisting in the process of IT adoption. The explanation follows a systematic procedure and explains a number of features of e-Infrastructures and information systems, design challenges, and the development of a work infrastructure. The paper uses information from various peer-reviewed papers and this further provides a concise description of the problem at hand.
Design and Conducting of the Research Study
a detailed data analysis from numerous peer-reviewed papers. However, the paper undertakes a case study of an information system that was used by the government of a German state. This system connected the state government to the second chamber of the German legislature.
References
Devaraj, S., Easly, R. F., and Crant, J. M. (2008). How Does Personality Matter?
Relating the Five Factor Model to Technology Acceptance and Use. Information Systems Research, Vol. 19(1), 93-105.
Pipek, V., and Wulf, V. (2009). Infrastructuring: Toward an Integrated Perspective on.
The Design and Use of Information Technology. Journal of the Association for Information Systems, Volume 10, Special Issue, pp. 447-473.
Venkatesh, V. and Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science (46) 2, pp. 186-204.
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