Relevant bibliographies by topics / Technology acceptance

Academic literature on the topic 'Technology acceptance'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 June 2023

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Journal articles on the topic "Technology acceptance"

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Greenfield, Geoffrey, and Fiona H. Rohde. "Technology Acceptance." International Journal of Information Systems and Social Change 2, no. 2 (April 2011): 26–36. http://dx.doi.org/10.4018/jissc.2011040102.

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During the past decade there has been an increasing interest in research within Not-for-Profit (NFP) organisations. Research has indicated that there are a number of characteristics that make NFPs different from other organisations. This paper considers whether workers within the NFP sector have different attitudes to technology and whether such differences affect the measures used within technology acceptance models. An exploratory study of workers within two NFPs indicated that workers within the service delivery functions of NFPs have different attitudes to technology than workers within the standard business functions of a NFP organisation e.g., marketing. These attitudes affected their perceptions of the use of and ease of technology.
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Harz, Mario, and Anton Vesper. "Acceptance of Technology?" Energy Procedia 40 (2013): 312–19. http://dx.doi.org/10.1016/j.egypro.2013.08.036.

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Momani, Alaa M., Mamoun M. Jamous, and Shadi M. S. Hilles. "Technology Acceptance Theories." International Journal of Cyber Behavior, Psychology and Learning 7, no. 2 (April 2017): 1–14. http://dx.doi.org/10.4018/ijcbpl.2017040101.

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Studying the acceptance and usage of technologies has become one of the most significant fields in software engineering domain. In order to explain the individuals' usage behavior towards technologies, many theories and models have been proposed over the years. This research paper focuses on reviewing a group of ten technology acceptance theories and models by studying their structure, evolution stages, and their strengths and weaknesses points. These theories were analyzed and classified into two main types depending on their development method and scientific field which they were developed in. This study reveals that these theories are almost similar in their structure, but different in explaining the behavioral intentions of technology. It considers that the best theory should be comprehensive and less complexity according to the number of the constructs and moderators which represent their structure. This will make the theory more understandable and applicable especially for studying the acceptance behavior for any new technology.
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Hu, Paul J., Patrick Y. K. Chau, Olivia R. Liu Sheng, and Kar Yan Tam. "Examining the Technology Acceptance Model Using Physician Acceptance of Telemedicine Technology." Journal of Management Information Systems 16, no. 2 (September 1999): 91–112. http://dx.doi.org/10.1080/07421222.1999.11518247.

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Khoi, Bui Huy. "Technology Acceptance Model in the Managing Information System." Journal of Advanced Research in Dynamical and Control Systems 12, SP7 (July 25, 2020): 869–76. http://dx.doi.org/10.5373/jardcs/v12sp7/20202177.

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Falco, Enzo, Constantinos Stylianou, Gilberto Martinez, Reinout Kleinhans, Sara Basso-Moro, and Haris Neophytou. "User Acceptance of Technology." International Journal of Electronic Government Research 16, no. 3 (July 2020): 85–104. http://dx.doi.org/10.4018/ijegr.2020070105.

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This article investigates how training public officials from two municipalities in Spain and Cyprus with new technologies affects three dependent variables: level of understanding of the technological innovation being introduced, its perceived usefulness, and its perceived ease-of-use. The tests to determine the impact of training were carried out by means of a self-constructed questionnaire within a repeated measure experimental design. The results demonstrate that the three variables are indeed positively affected by the training sessions to users from both municipalities. Consequently, training plays a vital role in encouraging government employees and administrators to accept, adopt and utilize e-government technologies.
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Ma, Qingxiong, and Liping Liu. "The Technology Acceptance Model." Journal of Organizational and End User Computing 16, no. 1 (January 2004): 59–72. http://dx.doi.org/10.4018/joeuc.2004010104.

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Nagadeepa C., Sibi Shaji, and B. Rose Kavitha. "Technology Acceptance of HRIS." International Journal of Information Communication Technologies and Human Development 11, no. 4 (October 2019): 35–45. http://dx.doi.org/10.4018/ijicthd.2019100103.

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In the digital era, people are shifting from human involvement to digital involvement. They expect everything do be done in single touch. In this fast world, digital technology has grown so much that people use the information technology in all their activities. This article focuses on the digital technology used for human resource management in B-Schools. It is understood that there are plenty of HRIS tools that are available to be used in the educational institutions. For the current study, the researchers focused the study towards the B-Schools in India. The respondents were employees of various B-Schools in Bangalore. This study considered 120 employees (low, middle and upper level) from various B-Schools. The study was to understand the effectiveness of the human resource information system tools in B-Schools using SEM.
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Marshall, Thomas E., Terry A. Byrd, Lorraine R. Gardiner, and R. Kelly Rainer Jr. "Technology Acceptance and Performance." Information Resources Management Journal 13, no. 3 (July 2000): 33–45. http://dx.doi.org/10.4018/irmj.2000070104.

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Yarbrough, Amy K., and Todd B. Smith. "Technology Acceptance among Physicians." Medical Care Research and Review 64, no. 6 (September 5, 2007): 650–72. http://dx.doi.org/10.1177/1077558707305942.

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Dissertations / Theses on the topic "Technology acceptance"

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Kowitlawakul, Yanika. "Technology acceptance model predicting nurses' acceptance of telemedicine technology (eICU®) /." Fairfax, VA : George Mason University, 2008. http://hdl.handle.net/1920/3058.

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Thesis (Ph.D.)--George Mason University, 2008.
Vita: p. 116. Thesis director: Jean Burley Moore. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Nursing. Title from PDF t.p. (viewed July 3, 2008). Includes bibliographical references (p. 108-115). Also issued in print.
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Hillmer, Ute. "Technology acceptance in mechatronics the influence of identity on technology acceptance." Wiesbaden Gabler, 2009. http://d-nb.info/995466742/04.

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Yousif, Wael K. "Examining engineering & technology students' acceptance of network virtualization technology using the technology acceptance model." Orlando, Fla. : University of Central Florida, 2010. http://purl.fcla.edu/fcla/etd/CFE0003071.

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Yousif, Wael K. Yousif. "EXAMINING ENGINEERING & TECHNOLOGY STUDENTS ACCEPTANCE OF NETWORK VIRTUALIZATION TECHNOLOGY USING THE TECHNOLOGY ACCEPTANCE MODE." Doctoral diss., University of Central Florida, 2010. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3039.

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This causal and correlational study was designed to extend the Technology Acceptance Model (TAM) and to test its applicability to Valencia Community College (VCC) Engineering and Technology students as the target user group when investigating the factors influencing their decision to adopt and to utilize VMware as the target technology. In addition to the primary three indigenous factors: perceived ease of use, perceived usefulness, and intention toward utilization, the model was also extended with enjoyment, external control, and computer self-efficacy as antecedents to perceived ease of use. In an attempt to further increase the explanatory power of the model, the Task-Technology Fit constructs (TTF) were included as antecedents to perceived usefulness. The model was also expanded with subjective norms and voluntariness to assess the degree to which social influences affect students decision for adoption and utilization. This study was conducted during the fall term of 2009, using 11 instruments: (1) VMware Tools Functions Instrument; (2) Computer Networking Tasks Characteristics Instrument; (3) Perceived Usefulness Instrument; (4) Voluntariness Instrument; (5) Subjective Norms Instrument; (6) Perceived Enjoyment Instrument; (7) Computer Self-Efficacy Instrument; (8) Perception of External Control Instrument; (9) Perceived Ease of Use Instrument; (10) Intention Instrument; and (11) a Utilization Instrument. The 11 instruments collectively contained 58 items. Additionally, a demographics instrument of six items was included to investigate the influence of age, prior experience with the technology, prior experience in computer networking, academic enrollment status, and employment status on student intentions and behavior with regard to VMware as a network virtualization technology. Data were analyzed using path analysis, regressions, and univariate analysis of variance in SPSS and AMOS for Windows. The results suggest that perceived ease of use was found to be the strongest determinant of student intention. The analysis also suggested that external control, measuring the facilitating conditions (knowledge, resources, etc) necessary for adoption was the highest predictor of perceived ease of use. Consistent with previous studies, perceived ease of use was found to be the strongest predictor of perceived usefulness followed by subjective norms as students continued to use the technology. Even though the integration of the task-technology fit construct was not helpful in explaining the variance in student perceived usefulness of the target technology, it was statistically significant in predicting student perception of ease of use. The study concluded with recommendations to investigate other factors (such as service quality and ease of implementation) that might contribute to explaining the variance in perceived ease of use as the primary driving force in influencing student decision for adoption. A recommendation was also made to modify the task-technology fit construct instruments to improve the articulation and the specificity of the task. The need for further examination of the influence of the instructor on student decision for adoption of a target technology was also emphasized.
Ed.D.
Department of Educational Research, Technology and Leadership
Education
Education EdD
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Joyce, Trevor. "Improving manufacturing technology acceptance." Thesis, Cranfield University, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.409585.

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Stewart, Laurie. "Technology acceptance in organizations." Thesis, Kansas State University, 2013. http://hdl.handle.net/2097/15322.

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Master of Arts
Department of Communication Studies
Sarah Riforgiate
New technology has changed how people do business. With rapid development of technology, it has been difficult for businesses and organizations to successfully implement technology advancements. This problem has spurred research in the area of technology acceptance. The Technology Acceptance Model (Davis, 1989) is a dominant theory used to explain technology use. Although many researchers have copied, expanded, and altered this model through quantitative research, making it robust, this study will further the model by using qualitative methods to explore how members understand and classify technology use. This study adds to the existing knowledge of computer-mediated communication and technology acceptance by exploring information technology use within a volunteer or not-for-profit organization (NPO). In order to offer a unique perspective to exploring how organizational members understand and adopt new technology, this study employs qualitative methodology to a topic traditionally explored through quantitative surveys and measurements. Research questions specifically consider why organizational members accept or reject new technology and how organizational membership affects technology acceptance. Using the third iteration of the technology acceptance model (TAM 3), data confirm perceived usefulness and perceived ease as determinants of technology acceptance. The influencing factors of perceived usefulness and perceived ease of use were also confirmed. Two new influencing factors of perceived usefulness emerged in this study: appropriateness and information overload. Also, insight into the role of age and technology adoption calls into question stereotypical misconceptions of technology use and acceptance. Overall, this study confirms and expands on research in the area of technology acceptance.
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Blue, Jon T. "Rebuilding Theories of Technology Acceptance: A Qualitative Case Study of Physicians' Acceptance of Technology." VCU Scholars Compass, 2006. http://hdl.handle.net/10156/1543.

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Dillon, Andrew. "User acceptance of information technology." London: Taylor and Francis, 2001. http://hdl.handle.net/10150/105880.

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This item is not the definitive copy. Please use the following citation when referencing this material: Dillon, A. (2001) User Acceptance of Information Technology. In: W. Karwowski (ed). Encyclopedia of Human Factors and Ergonomics. London: Taylor and Francis. Introduction: Despite significant investments in information technology in developed nations over recent decades, concern exists over the extent to which such expenditures have produced the intended benefits. At least part of this concern is based around the issue of whether any information technology is accepted by its intended users. Human factors professionals are interested in understanding the determinants of acceptance and ensuring new designs are built and implemented so as to minimize resistance. This concern has extended the traditional ergonomic concern with usability, or ability to use, to cover acceptance, or willingness to use.
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Fung, Suk-Yee Tammy, and 馮淑誼. "Effect of parents' technology perception on children's technology acceptance." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B29394752.

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Keeling, Kathleen A. "Customer acceptance of electronic service delivery : : extending the technology acceptance model." Thesis, University of Manchester, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.488161.

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Books on the topic "Technology acceptance"

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Hillmer, Ute. Technology Acceptance in Mechatronics. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8375-6.

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Teo, Timothy, ed. Technology Acceptance in Education. Rotterdam: SensePublishers, 2011. http://dx.doi.org/10.1007/978-94-6091-487-4.

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Wartburg, Walter P. von. Gene technology and social acceptance. Lanham, Md: University Press of America, 1999.

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Ursavaş, Ömer Faruk. Conducting Technology Acceptance Research in Education. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-10846-4.

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Technology acceptance in education: Research and issues. Rotterdam: Sense, 2011.

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Al-Emran, Mostafa, and Khaled Shaalan, eds. Recent Advances in Technology Acceptance Models and Theories. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-64987-6.

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Ramamurthy, V. S. Perception and acceptance of public risks. Bangalore: National Institute of Advanced Studies, 2012.

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L, Meiselman Herbert, and MacFie H. J. H, eds. Food choice, acceptance and consumption. London: Blackie Academic & Professional, 1996.

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Hiraoka, Clemens. Technology Acceptance of Connected Services in the Automotive Industry. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8309-1.

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Ortiz, Michael. Loss of Control and Technology Acceptance in (Digital) Transformation. Wiesbaden: Springer Fachmedien Wiesbaden, 2023. http://dx.doi.org/10.1007/978-3-658-39661-9.

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Book chapters on the topic "Technology acceptance"

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Andriessen, J. H. Erik. "Technology Acceptance." In Computer Supported Cooperative Work, 55–74. London: Springer London, 2003. http://dx.doi.org/10.1007/978-1-4471-0067-6_4.

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Iyamu, Tiko. "Technology acceptance model." In Applying Theories for Information Systems Research, 143–54. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003184119-9.

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Itaoka, Kenshi, Aya Saito, and Kazunari Sasaki. "Public Acceptance." In Green Energy and Technology, 561–79. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-56042-5_42.

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Wang, Lu, Chunwen Yan, and Junyu Xu. "Engineering Acceptance." In Technology Standard of Pipe Rehabilitation, 97–105. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4984-1_18.

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Hillmer, Ute. "Existing Theories Considering Technology Adoption." In Technology Acceptance in Mechatronics, 9–28. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8375-6_3.

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Teo, Timothy. "Technology Acceptance Research in Education." In Technology Acceptance in Education, 1–5. Rotterdam: SensePublishers, 2011. http://dx.doi.org/10.1007/978-94-6091-487-4_1.

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Smarkola, Claudia. "A Mixed-Methodological Technology Adoption Study." In Technology Acceptance in Education, 9–41. Rotterdam: SensePublishers, 2011. http://dx.doi.org/10.1007/978-94-6091-487-4_2.

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Luan, Wong Su, and Timothy Teo. "Student Teachers’ Acceptance of Computer Technology." In Technology Acceptance in Education, 43–61. Rotterdam: SensePublishers, 2011. http://dx.doi.org/10.1007/978-94-6091-487-4_3.

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Teo, Timothy. "Modeling Technology Acceptance Among Pre-Service Teachers." In Technology Acceptance in Education, 79–99. Rotterdam: SensePublishers, 2011. http://dx.doi.org/10.1007/978-94-6091-487-4_5.

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Hillmer, Ute. "Abstract." In Technology Acceptance in Mechatronics, 1–2. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8375-6_1.

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Conference papers on the topic "Technology acceptance"

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Michel, Christine, Marc-Eric Bobillier-Chaumon, and Philippe Sarnin. "Technology acceptance model." In the 2014 Ergonomie et Informatique Avancée Conference - Design, Ergonomie et IHM: quelle articulation pour la co-conception de l'interaction. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2671470.2671489.

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Daneshy, A. Ali, and Michael S. Bahorich. "Accelerating Technology Acceptance: Overview." In SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers, 2005. http://dx.doi.org/10.2118/98553-ms.

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Wang, Xinli, and Mostafa El-Said. "Technology Acceptance Model Revisited." In SIGITE '19: The 20th Annual Conference on Information Technology Education. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3349266.3351379.

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Mustafa, A'dillah Bt, Norasiah Hj Harun, and Mohd Zailan Endin. "Understanding e-book acceptance through Technology Acceptance Model (TAM Model)." In 2014 2nd International Conference on Information and Communication Technology (ICoICT). IEEE, 2014. http://dx.doi.org/10.1109/icoict.2014.6914052.

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Santoso, Cahyono Budy, Wayan Suparta, Edi Abdurachman, and Agung Trisetyarso. "Jakarta Government Official Portal Acceptance Based On Technology Acceptance Model." In 2020 International Conference on Information Technology Systems and Innovation (ICITSI). IEEE, 2020. http://dx.doi.org/10.1109/icitsi50517.2020.9264916.

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Shah, Maimunah Mohd, Roshidi Hassan, and Roslani Embi. "Technology acceptance and computer anxiety." In 2012 International Conference on Innovation Management and Technology Research (ICIMTR). IEEE, 2012. http://dx.doi.org/10.1109/icimtr.2012.6236408.

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Huldtgren, Alina, Gabriela Ascencio San Pedro, Anna Pohlmeyer, and Natalia Romero Herrera. "AAL-Technology Acceptance through Experience." In 8th International Conference on Pervasive Computing Technologies for Healthcare. ICST, 2014. http://dx.doi.org/10.4108/icst.pervasivehealth.2014.254934.

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Hannink, Ryan, Reiner Kuhr, and Tony Morris. "Public Acceptance of HTGR Technology." In Fourth International Topical Meeting on High Temperature Reactor Technology. ASMEDC, 2008. http://dx.doi.org/10.1115/htr2008-58218.

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Nuclear energy projects continue to evoke strong emotional responses from the general public throughout the world. High Temperature Gas-Cooled Reactor (HTGR) technology offers improved safety and performance characteristics that should enhance public acceptance but is burdened with demonstrating a different set of safety principles. This paper summarizes key issues impacting public acceptance and discusses the importance of openly engaging the public in the early stages of new HTGR projects. The public gets information about new technologies through schools and universities, news and entertainment media, the internet, and other forms of information exchange. Development of open public forums, access to information in understandable formats, participation of universities in preparing and distributing educational materials, and other measures will be needed to support widespread public confidence in the improved safety and performance characteristics of HTGR technology. This confidence will become more important as real projects evolve and participants from outside the nuclear industry begin to evaluate the real and perceived risks, including potential impacts on public relations, branding, and shareholder value when projects are announced. Public acceptance and support will rely on an informed understanding of the issues and benefits associated with HTGR technology. Major issues of public concern include nuclear safety, avoidance of greenhouse gas emissions, depletion of natural gas resources, energy security, nuclear waste management, local employment and economic development, energy prices, and nuclear proliferation. Universities, the media, private industry, government entities, and other organizations will all have roles that impact public acceptance, which will likely play a critical role in the future markets, siting, and permitting of HTGR projects.
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Safeena, Rahmath, and Abdullah Kammani. "Evaluation of E-Technology acceptance." In the 50th annual conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2214091.2214114.

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Vinodh, K., and Saji K. Mathew. "Web personalization in technology acceptance." In 2012 4th International Conference on Intelligent Human Computer Interaction (IHCI). IEEE, 2012. http://dx.doi.org/10.1109/ihci.2012.6481794.

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Reports on the topic "Technology acceptance"

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Christina B. Behr-Andres, Ph.D., P.E. EERC-DOE ENVIRONMENTAL TECHNOLOGY ACCEPTANCE. Office of Scientific and Technical Information (OSTI), April 2002. http://dx.doi.org/10.2172/794330.

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Hwang, Chanmi. Consumers' acceptance of wearable technology: Antecedents in a technology acceptance model (MS - 2nd place). Ames: Iowa State University, Digital Repository, November 2015. http://dx.doi.org/10.31274/itaa_proceedings-180814-1125.

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Rahman, Mohammad. Exploring the Factors Influencing Big Data Technology Acceptance. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.7389.

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Gottlieb, Isabel, Taber Allison, Cris Hein, and Pat Field. Technology Acceptance Workshop: Meeting Proceedings, 20-29 April 2022. Office of Scientific and Technical Information (OSTI), March 2023. http://dx.doi.org/10.2172/1963407.

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Ma, Yoon Jin, Hae Jin Gam, and Jennifer Banning. Acceptance of a Socially Responsible Label Model for Apparel Products: Application of the Technology Acceptance Model. Ames: Iowa State University, Digital Repository, 2013. http://dx.doi.org/10.31274/itaa_proceedings-180814-842.

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Huber, J. H. Enraf Series 854 advanced technology gauge (ATG) acceptance test procedure. Office of Scientific and Technical Information (OSTI), September 1996. http://dx.doi.org/10.2172/325908.

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HUBER, J. H. ENRAF Series 854 Advanced Technology Gauge (ATG) Acceptance Test Procedure. Office of Scientific and Technical Information (OSTI), August 1999. http://dx.doi.org/10.2172/797765.

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Barnes, G. A. Enraf series 854 Advanced Technology Gauge (ATG) acceptance test procedure. Revision 3. Office of Scientific and Technical Information (OSTI), May 1995. http://dx.doi.org/10.2172/71569.

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Dowell, J. L., and V. R. Enderlin. Acceptance Test Report for the 241-AN-107 Enraf Advanced Technology Gauges. Office of Scientific and Technical Information (OSTI), June 1995. http://dx.doi.org/10.2172/273661.

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Barnes, G. A. Enraf Series 854 advanced technology gauge (ATG) acceptance test procedure. Revision 2. Office of Scientific and Technical Information (OSTI), January 1995. http://dx.doi.org/10.2172/10118741.

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