Access the full text.
Sign up today, get DeepDyve free for 14 days.
Deborah Compeau, C. Higgins (1995)Computer Self-Efficacy: Development of a Measure and Initial Test
MIS Q., 19
Gary Hackbarth, V. Grover, M. Yi (2003)Computer playfulness and anxiety: positive and negative mediators of the system experience effect on perceived ease of use
Inf. Manag., 40
S. Whitbourne (1986)Openness to experience, identity flexibility, and life change in adults.
Journal of personality and social psychology, 50 1
Usman Nasir, M. Niazi (2011)Cloud computing adoption assessment model (CAAM)
P. Aşkar, Aysun Umay (2001)Preservice Elementary Mathematics Teachers’ Computer Self-Efficacy, Attitudes towards Computers, and their Perceptions of Computer-Enriched Learning Environments
M. Jerusalem (1992)Self-efficacy as a resource factor in stress appraisal processes.
Általános tudományok (2010)Diffusion of Innovations
M. Fishbein, I. Ajzen (1977)Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research
Contemporary Sociology, 6
Namkee Park, R. Roman, Seungyoon Lee, J. Chung (2009)User acceptance of a digital library system in developing countries: An application of the Technology Acceptance Model
Int. J. Inf. Manag., 29
J. Blascovich (2008)Challenge and Threat
L. Vijayasarathy (2004)Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model
Inf. Manag., 41
Nimet Uray, Ayla Dedeoglu (1998)Identifying Fashion Clothing Innovators by Self-Report Method
Journal of Euromarketing, 6
P. Calvert (2013)Cloud Computing for Libraries
The Electronic Library, 31
P. Pavlou (2001)Consumer Intentions to Adopt Electronic Commerce - Incorporating Trust and Risk in the Technology Acceptance Model
V. Venkatesh, Michael Morris, P. Ackerman (2000)A Longitudinal Field Investigation of Gender Differences in Individual Technology Adoption Decision-Making Processes.
Organizational behavior and human decision processes, 83 1
A. Bandura (1977)Self-efficacy: toward a unifying theory of behavioral change.
Psychological review, 84 2
Kevin Gildea, T. Schneider, W. Shebilske (2007)Stress Appraisals and Training Performance on a Complex Laboratory Task
Human Factors: The Journal of Human Factors and Ergonomic Society, 49
Noa Aharony (2013)Librarians' attitudes towards mobile services
Aslib Proc., 65
J. Blascovich, J. Tomaka (1996)The Biopsychosocial Model of Arousal Regulation
Advances in Experimental Social Psychology, 28
Ritu Agarwal, J. Prasad (1998)A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology
Inf. Syst. Res., 9
V. Venkatesh, Michael Morris, G. Davis, Fred Davis (2003)User Acceptance of Information Technology: Toward a Unified View
Institutions & Transition Economics: Microeconomic Issues eJournal
Mark Seery, Max Weisbuch, M. Hetenyi, J. Blascovich (2010)Cardiovascular measures independently predict performance in a university course.
Psychophysiology, 47 3
Fred Davis, V. Venkatesh (1996)A critical assessment of potential measurement biases in the technology acceptance model: three experiments
Int. J. Hum. Comput. Stud., 45
Noa Aharony (2009)Web 2.0 use by librarians
Library & Information Science Research, 31
Qingxiong Ma, Liping Liu (2005)The Role of Internet Self-Efficacy in the Acceptance of Web-Based Electronic Medical Records
J. Organ. End User Comput., 17
M. Breeding (2012)Cloud Computing for Libraries
T. McGill, S. Bax (2007)From Beliefs to Success: Utilizing an Expanded TAM to Predict Web Page Development Success
Int. J. Technol. Hum. Interact., 3
R. Buyya, J. Broberg, A. Goscinski (2011)Cloud Computing Principles and Paradigms
M. Turner, B. Kitchenham, P. Brereton, S. Charters, D. Budgen (2010)Does the technology acceptance model predict actual use? A systematic literature review
Inf. Softw. Technol., 52
Fred Davis, R. Bagozzi, P. Warshaw (1989)User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
Management Science, 35
A. Serenko (2008)A model of user adoption of interface agents for email notification
Interact. Comput., 20
William King, Jun He (2006)A meta-analysis of the technology acceptance model
Inf. Manag., 43
G. Feuerlicht, Shyam Govardhan, W. Churchill (2010)Impact of Cloud Computing: Beyond a Technology Trend
R. Yeates (2013)Cloud Computing for Libraries
R. Sorrentino, C. Roney (2002)The Uncertain Mind: Individual Differences in Facing the Unknown
R. McCrae, P. Costa (1997)Conceptions and correlates of openness to experience.
Á. Crespo, Ignacio Rodríguez (2008)The effect of innovativeness on the adoption of B2C e-commerce: A model based on the Theory of Planned Behaviour
Comput. Hum. Behav., 24
Yong Liu, Hongxiu Li, C. Carlsson (2010)Factors driving the adoption of m-learning: An empirical study
Comput. Educ., 55
Fred Davis (1989)Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology
MIS Q., 13
Nae-Yang Jeong, Youngsang Yoo, Tae-young Heo (2009)Moderating effect of personal innovativeness on mobile-RFID services: Based on Warshaw's purchase intention model
Technological Forecasting and Social Change, 76
Robert O'Harrow (2005)No Place To Hide
M. Chow, David Herold, Tat-Ming Choo, Kitty Chan (2012)Extending the technology acceptance model to explore the intention to use Second Life for enhancing healthcare education
Comput. Educ., 59
Gordon Hodson, R. Sorrentino (1999)Uncertainty Orientation and the Big Five Personality Structure
Journal of Research in Personality, 33
G. Rose, D. Straub (1998)PREDICTING GENERAL IT USE : APPLYING TAM TO THE ARABIC WORLD
Journal of Global Information Management, 6
R. McCrae, P. Costa (2005)Personality in Adulthood: A Five-Factor Theory Perspective
Noa Aharony (2014)Library and Information Science students’ perceptions of m-learning
Journal of Librarianship and Information Science, 46
R. Stone, J. Henry (2003)The Roles of Computer Self-Efficacy and Outcome Expectancy in Influencing the Computer End-User's Organizational Commitment
J. Organ. End User Comput., 15
W. Mendes, J. Blascovich, S. Hunter, Brian Lickel, J. Jost (2007)Threatened by the unexpected: physiological responses during social interactions with expectancy-violating partners.
Journal of personality and social psychology, 92 4
R. McCrae (1996)Social consequences of experiential openness.
Psychological bulletin, 120 3
C. Looney, J. Valacich, A. Akbulut (2004)Online investment self-efficacy: development and initial test of an instrument to assess perceived online investing abilities
37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the
Said Al-gahtani (2001)The Applicability of TAM Outside North America: An Empirical Test in the United Kingdom
Inf. Resour. Manag. J., 14
P. Ellen, W. Bearden, Subhash Sharma (1991)Resistance to technological innovations: An examination of the role of self-efficacy and performance satisfaction
Journal of the Academy of Marketing Science, 19
Jairak Kallaya, P. Prasong, Mekhabunchakij Kittima (2009)An Acceptance of Mobile Learning for Higher Education Students in Thailand
Ji Park, Jun Yu, J. Zhou (2010)Consumer innovativeness and shopping styles
Journal of Consumer Marketing, 27
P. Pavlou (2003)Consumer Acceptance of Electronic Commerce: Integrating Trust and Risk with the Technology Acceptance Model
International Journal of Electronic Commerce, 7
R. Cheung, D. Vogel (2013)Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning
Comput. Educ., 63
Faisal Alshuwaier, Abdullah Alshwaier, Ali Areshey (2012)Applications of cloud computing in education
2012 8th International Conference on Computing and Networking Technology (INC, ICCIS and ICMIC)
Purpose – The purpose of this paper is to explore the extent to which the Technology Acceptance Model (TAM), and personal characteristics such as threat and challenge, self-efficacy and openness to experience, explain information professionals’ and educational technology experts’ perspectives about cloud computing. In addition, the study will investigate any differences between these two tech-savvy groups concerning cloud computing adoption. Design/methodology/approach – The research was conducted in Israel during the second semester of the 2013 academic year. Researchers used seven questionnaires to gather the data. Findings – The current study found that the behavioral intention to use cloud computing was impacted by perceived ease of use and personal innovativeness. Further, the study demonstrated that respondents’ intentions to use cloud computing are affected by personal characteristics such as threat and challenge, self-efficacy, and openness to experience. In addition, it seems that each group has a different perspective about technology. Originality/value – Findings reveal that newest technologies are not the main focus of information professionals. Therefore, if information organizations directors would like their employees to enhance their use of technological innovations, they should expose them to the latest technologies, emphasizing their usefulness, ease of use, and benefits.
Library Hi Tech – Emerald Publishing
Published: Nov 11, 2014
Access the full text.
Sign up today, get DeepDyve free for 14 days.