Relevant bibliographies by topics / Technology Acceptance Model

Academic literature on the topic 'Technology Acceptance Model'

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Published: 4 June 2021
Last updated: 20 February 2023

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Journal articles on the topic "Technology Acceptance Model"

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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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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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KOWITLAWAKUL, YANIKA. "The Technology Acceptance Model." CIN: Computers, Informatics, Nursing 29, no. 7 (July 2011): 411–18. http://dx.doi.org/10.1097/ncn.0b013e3181f9dd4a.

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Hatami Kaleshtari, Mohammad, Ileana Ciobanu, Petre Lucian Seiciu, Andreea Georgiana Marin, and Mihai Berteanu. "Towards a Model of Rehabilitation Technology Acceptance and Usability." International Journal of Social Science and Humanity 6, no. 8 (August 2016): 612–16. http://dx.doi.org/10.7763/ijssh.2016.v6.720.

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Pierce, Tamra P., Christopher Willy, Robert Roncace, and John Bischoff. "Extending The Technology Acceptance Model: Policy Acceptance Model (PAM)." American Journal of Health Sciences (AJHS) 5, no. 2 (November 24, 2014): 129–44. http://dx.doi.org/10.19030/ajhs.v5i2.8963.

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Many have studied the process of acceptance and adoption of new ideas and technologies as they are introduced into society. While several models have been used to assess various influencing factors, the Technology Acceptance Model (TAM) is one that is most widely accepted. This model examines people’s acceptance of new technologies based on variables that directly correlate to how the end user views the product. This paper introduces the Policy Acceptance Model (PAM), an expansion of TAM, which is designed for the analysis and evaluation of acceptance of new policy implementation. PAM includes the traditional constructs of TAM and adds the variables of age and ethnicity. The model is experimentally assessed using a survey of people’s attitudes toward the upcoming health care reform from 72 survey respondents. The aim is that the theory behind this model can be used as a framework that will be applicable to studies looking at the introduction of any new or modified policies.
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Fuentes-Martínez, Ana. "From a Technology Acceptance Model to a Practice Acceptance Model." Ars Educandi 17, no. 17 (December 23, 2020): 61–66. http://dx.doi.org/10.26881/ae.2020.17.03.

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The paper delves into the problems of analyzing the introduction of programming in primary and secondary education from the perspective of the traditional Technology Acceptance Model. Instead, a Practice Acceptance model is suggested in which the focus is shifted from digital devices to the everyday practices of curriculum implementation.
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Fuentes-Martínez, Ana. "From a Technology Acceptance Model to a Practice Acceptance Model." Ars Educandi 17, no. 17 (December 23, 2020): 61–66. http://dx.doi.org/10.26881/ae.2020.17.03.

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The paper delves into the problems of analyzing the introduction of programming in primary and secondary education from the perspective of the traditional Technology Acceptance Model. Instead, a Practice Acceptance model is suggested in which the focus is shifted from digital devices to the everyday practices of curriculum implementation.
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Garcia Lirios, Cruz. "Exploratory Model of Technology Acceptance in The Covid-19 Era." Journal of Adolescent and Addiction Research 1, no. 1 (December 20, 2022): 01–04. http://dx.doi.org/10.58489/2836-2314/003.

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The intensive use of technologies, devices and electronic networks not only own differences between users and non - users, but also even among those who use one or the other same technology that eventually perfects and involves continuous learning abilities and knowledge processing and dissemination of information. The objective of the present study was to establish the reliability and validity of an instrument that measures the intention to search for information. From a non - experimental, exploratory and cross - sectional study with a non - probabilistic selection of 100 students at a public university, it is planned eight dimensions among navojoa.uson.mx which explain the information selectivity of 21% at full. Regarding the design limits of the study sample and the testing of the dimensions recommended in an investigation of major components in the analysis confirmatory factor.
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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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Teo, Timothy, and Pita Jarupunphol. "Dhammic Technology Acceptance Model (DTAM)." Journal of Educational Computing Research 52, no. 1 (March 2015): 136–51. http://dx.doi.org/10.1177/0735633114568859.

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Dissertations / Theses on the topic "Technology Acceptance Model"

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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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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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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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Mulero, Senikat Olumayowa. "Acceptance and impact of social networks marketing using extended technology acceptance model." Thesis, Cape Peninsula University of Technology, 2012. http://hdl.handle.net/20.500.11838/1385.

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Thesis (MTech (Information Technology)--)Cape Peninsula University of Technology, 2012
Includes bibliographical references (leaves 127)
In rapid advances in marketing strategies, Social Networks Marketing (SNM) is dramatically becoming an important aspect in promoting businesses. Social networks marketing has been found as one of the most effective tool used in businesses today, by most business owners in South Africa, to expand, and flourish their businesses. The explosion of Internet usage has drawn the attention of researchers towards social networks marketing. Research has shown that potential Internet users are doubtful, and indecisive to use, and accept SNM system in spite of their availability. Therefore, there is a need for researchers to identify some of the factors that determine user’s unwillingness to accept and use the system. According to the Technology Acceptance Model (TAM), Perceived Ease of Use (PEOU), and Perceived Usefulness (PU) are the two major constructs in determining the use and acceptance of various information systems. These beliefs may not fully explain the user’s behaviour towards newly introduced system, such as social networks marketing. Hence, this study had successfully implemented TAM to the newly proposed information system (social networks marketing system). Using TAM as a theoretical framework, the study added two new constructs “perceived credibility” and “awareness” as part of the factors influencing user’s acceptance of social networks marketing. The purpose of the study was to explore the impact of social networks marketing system by SMEs in South Africa, and perception of consumers. In addition, this research investigated factors that influence users’ acceptance of social networks marketing using TAM as the basis for the theoretical framework. Questionnaire-based study done in 2 groups; consumers and small and medium-scale enterprises (SMEs), in this work, represent the major users of social networks marketing in South Africa. The research model was tested using data collected from 143 questionnaires and analysed using linear regression. The results show that user’s intentions to use SNM are strongly and positively correlated with user acceptance. The empirical results confirmed that perceived credibility and perceived usefulness are the strongest determinant in predicting user’s intention to use SNM. In addition, many of the South African SMEs using SNM, have presumed that SNM has positively and negatively impacted their businesses.
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Gabbard, Ralph Barnhart. "Applying the technology acceptance model to online education." [Bloomington, Ind.] : Indiana University, 2004. http://wwwlib.umi.com/dissertations/fullcit/3162232.

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Thesis (Ph.D.)--Indiana University, 2004.
Source: Dissertation Abstracts International, Volume: 66-01, Section: A, page: 0011. Chair: Javed Mostafa. Title from dissertation home page (viewed Oct. 12, 2006).
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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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Vrablova, Adriana, and Stjepan Kalinic. "Technology acceptance of IKEA mobile application." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Företagsekonomi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-26676.

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In the past few years, rapid development of mobile technologies has been changing the way people approach purchasing. Using Technology Acceptance Model (Davis, 1986), the authors believe that IKEA’s furniture mobile application creates a certain value to its users. The study aims at examining the importance of perceived usefulness, perceived ease of use and compatibility dimensions of IKEA’s app and their impact on consumers’ behavioral intentions to see whether or not they lead to actual purchase.   The thesis findings reveal that IKEA mobile application is not widely used. The results should have been applicable for similar companies as IKEA especially those which promote in-store app usage. However, it is not possible since the thesis contradicts the assumption of broad usage of such mobile application.   The analysis of the surveys releaved gender having a role in IKEA mobile app perception as well as occupation. The analysis is also contributing by a realization that mobile technologies lead to faster decision-making, more information availability, and therefore, can create better marketing communication strategies.
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Ducey, Adam J. "Predicting Tablet Computer Use: An Extended Technology Acceptance Model." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4471.

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While information technology has rapidly changed work in the United States in the past 50 years, some businesses and industries have been slow to adopt new technologies. Healthcare is one industry that has lagged behind in information technology investment for a variety of reasons. Recent federal initiatives to encourage IT adoption in the healthcare industry provide an ideal context to study factors that influence technology acceptance. Data from 261 practicing pediatricians were collected to evaluate an extended Technology Acceptance Model. Results indicated that individual (i.e., perceived usefulness, perceived ease of use), organizational (i.e., subjective norm), and device (i.e., compatibility, reliability) characteristics collectively influence pediatricians' intention to adopt tablet computers in their medical practice. Theoretical and practical implications are discussed. Future research should examine additional variables that influence information technology adoption in organizations.
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Hur, Youngjin. "Determinants of sport website acceptance : an application and extension of the technology acceptance model." Online access for everyone, 2007. http://www.dissertations.wsu.edu/Dissertations/Summer2007/y_hur_072707.pdf.

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Books on the topic "Technology Acceptance Model"

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Kamel, Sherif. Assessing the introduction of electronic banking in Egypt using the technology acceptance model. Hershey, PA: Idea Group Pub., 2003.

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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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The Technology Acceptance Model: 30 Years of TAM. Springer, 2020.

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Ortiz, Michael. Loss of Control and Technology Acceptance in Transformation: Acceptance and Design Factors of a Heuristic Model. Springer Fachmedien Wiesbaden GmbH, 2023.

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Tan, Tio Boon. Technology Acceptance Model(TAM): A study of word processing usage in Singapore. 1996.

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An Evaluation of GeoBEST Contingency Beddown Planning Software Using the Technology Acceptance Model. Storming Media, 2002.

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Power, Performance, and Perception (P3): Integrating Usability Metrics and Technology Acceptance Determinants to Validate a New Model for Predicting System Usage. Storming Media, 1999.

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SINGH, Dr PREETI. INFORMATION TECHNOLOGY. KAAV PUBLICATIONS, DELHI, INDIA, 2022. http://dx.doi.org/10.52458/9789391842499.eb.

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The book offers a global platform for the academia to elevate their image as internationally acclaimed scholars, as it reaches the nook and the corner of the globe online. Researchers can also ripe the benefit of enriching their study by submitting manuscripts to the editorial board that comprises scholars with proven abilities and established research track record. All the articles submitted for publication are subjected to rigorous single blinded peer review to ensure its quality before it gets published. Authors’ scholarly work undergoes critical scrutiny by experts in the same subject to check for scientific validity, relevance and accuracy. Upon getting the final approval from the editorial board members, their decision on acceptance or rejection will be informed via E-mail. The Book supports open access publishing model to maximize the visibility of the published research. Authors can track the article status from the Editorial Manager System of the Book which allows authors to submit article, track status and respond to reviewers’ comments and revision requests.
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Winkelman, Warren Jay. The technological transformation of self-care: A patient-driven adaptation of the technology acceptance model for evaluation of patient-accessible electronic medical records. 2006.

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shaalan, khaled, and Mostafa Al-Emran. Recent Advances in Technology Acceptance Models and Theories. Springer International Publishing AG, 2021.

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Book chapters on the topic "Technology Acceptance Model"

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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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Jumaah, Fawaz, Sani Salisu, and Shahad Alfahad. "Technology Acceptance Model in Social Commerce." In Artificial Neural Networks and Structural Equation Modeling, 37–49. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-6509-8_3.

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Granić, Andrina. "Technology Acceptance and Adoption in Education." In Handbook of Open, Distance and Digital Education, 1–15. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0351-9_11-1.

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AbstractThe chapter provides a comprehensive and up-to-date insight into main research findings in the area of educational technology acceptance, adoption, and usage. Over the past decades, a variety of theoretical perspectives have been advanced to provide an understanding of the determinants of adoption of various technologies used to support the process of knowledge transfer and acquisition. Although some prominent theoretical approaches in educational contexts include Innovation Diffusion Theory (IDT), Unified Theory of Acceptance and Use of Technology (UTAUT), as well as Motivational Model (MM), research reveals the Technology Acceptance Model (TAM) as the most influential model and leading scientific paradigm in investigating acceptance of educational technology by students, teachers, and other stakeholders. Aiming to increase their predictive validity, in numerous empirical studies, models have been extended with different predictive factors, like the most often validated self-efficacy, subjective norm, perceived enjoyment, perceived playfulness, anxiety, social influence, system quality, and facilitating conditions. Research revealed electronic learning (e-learning) as the most common validated mode of delivery, followed by mobile learning (m-learning), learning management system (LMS), personal learning environment (PLE), and massive open online course (MOOC), along with different supportive facilitating technologies used in education such as social media platforms, teaching assistant robots, simulators, as well as virtual reality (VR) and augmented reality (AR) technologies. To enhance explanatory power, new developments in educational technology acceptance and adoption have suggested the need of integration of TAM and UTAUT with other contributing adoption and post-adoption theories and models, together with several established approaches from other fields.
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Granić, Andrina. "Technology Acceptance and Adoption in Education." In Handbook of Open, Distance and Digital Education, 183–97. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-2080-6_11.

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AbstractThe chapter provides a comprehensive and up-to-date insight into main research findings in the area of educational technology acceptance, adoption, and usage. Over the past decades, a variety of theoretical perspectives have been advanced to provide an understanding of the determinants of adoption of various technologies used to support the process of knowledge transfer and acquisition. Although some prominent theoretical approaches in educational contexts include Innovation Diffusion Theory (IDT), Unified Theory of Acceptance and Use of Technology (UTAUT), as well as Motivational Model (MM), research reveals the Technology Acceptance Model (TAM) as the most influential model and leading scientific paradigm in investigating acceptance of educational technology by students, teachers, and other stakeholders. Aiming to increase their predictive validity, in numerous empirical studies, models have been extended with different predictive factors, like the most often validated self-efficacy, subjective norm, perceived enjoyment, perceived playfulness, anxiety, social influence, system quality, and facilitating conditions. Research revealed electronic learning (e-learning) as the most common validated mode of delivery, followed by mobile learning (m-learning), learning management system (LMS), personal learning environment (PLE), and massive open online course (MOOC), along with different supportive facilitating technologies used in education such as social media platforms, teaching assistant robots, simulators, as well as virtual reality (VR) and augmented reality (AR) technologies. To enhance explanatory power, new developments in educational technology acceptance and adoption have suggested the need of integration of TAM and UTAUT with other contributing adoption and post-adoption theories and models, together with several established approaches from other fields.
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Ursavaş, Ömer Faruk. "Technology Acceptance Model: History, Theory, and Application." In Springer Texts in Education, 57–91. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-10846-4_4.

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Fernández Robin, Cristóbal, Scott McCoy, Luis Yáñez Sandivari, and Diego Yáñez Martínez. "Technology Acceptance Model: Worried about the Cultural Influence?" In Lecture Notes in Computer Science, 609–19. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07293-7_59.

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Eltayeb, Mohamed, and Maurice Dawson. "Understanding User’s Acceptance of Personal Cloud Computing: Using the Technology Acceptance Model." In Advances in Intelligent Systems and Computing, 3–12. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32467-8_1.

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Brangier, Éric, and Sonia Hammes-Adelé. "Beyond the Technology Acceptance Model: Elements to Validate the Human-Technology Symbiosis Model." In Ergonomics and Health Aspects of Work with Computers, 13–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21716-6_2.

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Mohmed Al-Sabaawi, Mohmed Y., and Halina Mohamed Dahlan. "Acceptance Model of Social Media for Informal Learning." In Recent Trends in Information and Communication Technology, 679–87. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59427-9_70.

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Rahman, Md Mahmudur, Shuchisnigdha Deb, Daniel Carruth, and Lesley Strawderman. "Using Technology Acceptance Model to Explain Driver Acceptance of Advanced Driver Assistance Systems." In Advances in Human Factors of Transportation, 44–56. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20503-4_5.

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Conference papers on the topic "Technology Acceptance Model"

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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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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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Busolo, Gilbert, Lawrence Nderu, and Kennedy Ogada. "A Multilevel Technology Acceptance Management Model." In 6th International Conference on Computer Science, Engineering And Applications (CSEA 2020). AIRCC Publishing Corporation, 2020. http://dx.doi.org/10.5121/csit.2020.101802.

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Knowledge is a strategic resource for successful data driven decision making in any organization. To harness this knowledge, successful adoption of a technological intervention is key. Institutions leverage on technology to drive knowledge management (KM) initiatives for quality service delivery and prudent data management. These initiatives provide the overall strategy for managing data resources. They make available knowledge organization tools and techniques while enabling regular updates. Derived benefits of positive deployment of a technological intervention are competency enhancement through gained knowledge, raised quality of service and promotion of healthy development of e-commerce. Successful and timely adoption of technological interventions through which knowledge management initiatives are deployed remains a key challenge to many organizations. This paper proposes a wholesome multilevel technology acceptance management model. The proposed model takes into account human, technological and organizational variables, which exist in a deployment environment. This model will be vital in driving early technology acceptance prediction and timely deployment of mitigation measures to deploy technological interventions successfully.
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Akbari, Elham. "Technology Acceptance Model and Mobile learning." In 2021 14th National and 8th International Conference on e-Learning and e-Teaching (ICELET). IEEE, 2021. http://dx.doi.org/10.1109/icelet202153025.2021.9712606.

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Gao, Shang, John Krogstie, and Per Anton Gransæther. "Mobile Services Acceptance Model." In 2008 International Conference on Convergence and Hybrid Information Technology. IEEE, 2008. http://dx.doi.org/10.1109/ichit.2008.252.

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Mohamad, Mohamad Amiruddin, Mohd Talmizie Amron, and Nur Hidayah Md Noh. "Assessing the Acceptance of E-Learning via Technology Acceptance Model (TAM)." In 2021 6th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE). IEEE, 2021. http://dx.doi.org/10.1109/icraie52900.2021.9704019.

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Sun, Jianjun, Qing Ke, and Ying Cheng. "Study of Consumer Acceptance in E-Commerce by Integrating Technology Acceptance Model with Task-Technology Fit Model." In 2007 International Conference on Wireless Communications, Networking and Mobile Computing. IEEE, 2007. http://dx.doi.org/10.1109/wicom.2007.895.

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Ismail, Irzan, Amirul ‘Aini, Nurazree Mahmud, and Helmy Abu Hasan. "Relationship between Information Technology (IT) Acceptance and Employee Performance using Technology Acceptance Model (TAM)." In 3rd International Conference on Economics, Business and Economic Education Science, ICE-BEES 2020, 22-23 July 2020, Semarang, Indonesia. EAI, 2021. http://dx.doi.org/10.4108/eai.22-7-2020.2307899.

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Reports on the topic "Technology Acceptance Model"

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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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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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Li, Ailin, and Yingjiao Xu. Chinese Consumers� Adoption Behaviors Toward Virtual Fitting Rooms: From the Perspective of Technology Acceptance Model. Ames (Iowa): Iowa State University. Library, January 2019. http://dx.doi.org/10.31274/itaa.8331.

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Contreras Salamanca, Luz Briyid, and Yon Garzón Ávila. Generational Lagging of Dignitaries, Main Cause of Technological Gaps in Community Leaders. Analysis of Generation X and Boomers from the Technology Acceptance Model. Universidad Nacional Abierta y a Distancia, May 2021. http://dx.doi.org/10.22490/ecacen.4709.

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Community and neighborhood organizations are in the process of renewing the organizational culture, considering technological environments in the way of training, and advancing communally, being competitive in adaptation and learning, creating new solutions, promoting change, and altering the status quo, based on the advancement of technology over the last few years, currently applied in most organizations. The decisive factor is the ability of true leaders to appropriate the Technological Acceptance Model –TAM– principles, participating in programs and projects, adopting new technologies from the different actors involved, contributing to the welfare of each community. There is, however, a relative resistance to the use of technology as support in community management, due to the generational differences in leaders and dignitaries, according to collected reports in this study, in relation to the age range of dignitaries –Generation X and Baby Boomers predominate–. They present a challenge to digital inclusion with difficulties related to age, cognitive, sensory, difficulty in developing skills, and abilities required in Digital Technologies, necessary to face new scenarios post-pandemic and, in general, the need to use technological facilities.
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Naim, Michael, Andrew Spielman, Shlomo Nir, and Ann Noble. Bitter Taste Transduction: Cellular Pathways, Inhibition and Implications for Human Acceptance of Agricultural Food Products. United States Department of Agriculture, February 2000. http://dx.doi.org/10.32747/2000.7695839.bard.

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Historically, the aversive response of humans and other mammals to bitter-taste substances has been useful for survival, since many toxic constituents taste bitter. Today, the range of foods available is more diverse. Many bitter foods are not only safe for consumption but contain bitter constituents that provide nutritional benefits. Despite this, these foods are often eliminated from our current diets because of their unacceptable bitterness. Extensive technology has been developed to remove or mask bitterness in foods, but a lack of understanding of the mechanisms of bitterness perception at the taste receptor level has prevented the development of inhibitors or efficient methods for reducing bitterness. In our original application we proposed to: (a) investigate the time course and effect of selected bitter tastants relevant to agricultural products on the formation of intracellular signal molecules (cAMP, IP3, Ca2+) in intact taste cells, in model cells and in membranes derived therefrom; (b) study the effect of specific bitter taste inhibitors on messenger formation and identify G-proteins that may be involved in tastant-induced bitter sensation; (c) investigate interactions and self-aggregation of bitter tastants within membranes; (d) study human sensory responses over time to these bitter-taste stimuli and inhibitors in order to validate the biochemical data. Quench-flow module (QFM) and fast pipetting system (FPS) allowed us to monitor fast release of the aforementioned signal molecules (cGMP, as a putative initial signal was substituted for Ca2+ ions) - using taste membranes and intact taste cells in a time range below 500 ms (real time of taste sensation) - in response to bitter-taste stimulation. Limonin (citrus) and catechin (wine) were found to reduce cellular cAMP and increase IP3 contents. Naringin (citrus) stimulated an IP3 increase whereas the cheese-derived bitter peptide cyclo(leu-Trp) reduced IP3 but significantly increased cAMP levels. Thus, specific transduction pathways were identified, the results support the notion of multiple transduction pathways for bitter taste and cross-talk between a few of those transduction pathways. Furthermore, amphipathic tastants permeate rapidly (within seconds) into liposomes and taste cells suggesting their availability for direct activation of signal transduction components by means of receptor-independent mechanisms within the time course of taste sensation. The activation of pigment movement and transduction pathways in frog melanophores by these tastants supports such mechanisms. Some bitter tastants, due to their amphipathic properties, permeated (or interacted with) into a bitter tastant inhibitor (specific phospholipid mixture) which apparently forms micelles. Thus, a mechanism via which this bitter taste inhibitor acts is proposed. Human sensory evaluation experiments humans performed according to their 6-n-propyl thiouracil (PROP) status (non-tasters, tasters, super-tasters), indicated differential perception of bitterness threshold and intensity of these bitter compounds by different individuals independent of PROP status. This suggests that natural products containing bitter compounds (e.g., naringin and limonin in citrus), are perceived very differently, and are in line with multiple transduction pathways suggested in the biochemical experiments. This project provides the first comprehensive effort to explore the molecular basis of bitter taste at the taste-cell level induced by economically important and agriculturally relevant food products. The findings, proposing a mechanism for bitter-taste inhibition by a bitter taste inhibitor (made up of food components) pave the way for the development of new, and perhaps more potent bitter-taste inhibitors which may eventually become economically relevant.
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Muelaner, Jody, ed. Unsettled Issues in Commercial Vehicle Platooning. SAE International, November 2021. http://dx.doi.org/10.4271/epr2021027.

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Platooning has the potential to reduce the energy consumption of commercial vehicles while improving safety; however, both advantages are currently difficult to quantify due to insufficient data and the wide range of variables affecting models. Platooning will significantly reduce the use of energy when compared to trucks driven alone, or at a safe distance for a driver without any automated assistance. Platooning will also reduce stopping distances—multiple states in the US have passed laws authorizing truck platoons to operate at shorter gaps than are authorized for normal, human-driven trucks. However, drivers typically do not currently leave the recommended gaps and, therefore, already gain much of the potential energy savings by drafting lead vehicles, albeit illegally. The automated systems associated with platooning cannot be programmed to flout safety recommendations in the way that human drivers routinely do. Therefore, actual energy savings may be minimal while safety may be greatly improved. More data will be needed to conclusively demonstrate a safety gain. Recommended safe gaps are currently highly generalized and must necessarily assume worst-case braking performance. Using a combination of condition monitoring and vehicle-to-vehicle communications, platooning systems will be able to account for the braking performance of other vehicles within the platoon. If all the vehicles in a platoon have a high level of braking performance, the platoon will be able to operate in a more efficient, tighter formation. Driver acceptance of platooning technology will increase as the systems become more effective and do not displace jobs. The increased loading of infrastructure must also be considered, and there may be requirements for upgrades on bridges or restrictions on platooning operation.
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Bonfil, David J., Daniel S. Long, and Yafit Cohen. Remote Sensing of Crop Physiological Parameters for Improved Nitrogen Management in Semi-Arid Wheat Production Systems. United States Department of Agriculture, January 2008. http://dx.doi.org/10.32747/2008.7696531.bard.

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To reduce financial risk and N losses to the environment, fertilization methods are needed that improve NUE and increase the quality of wheat. In the literature, ample attention is given to grid-based and zone-based soil testing to determine the soil N available early in the growing season. Plus, information is available on in-season N topdressing applications as a means of improving GPC. However, the vast majority of research has focused on wheat that is grown under N limiting conditions in sub-humid regions and irrigated fields. Less attention has been given to wheat in dryland that is water limited. The objectives of this study were to: (1) determine accuracy in determining GPC of HRSW in Israel and SWWW in Oregon using on-combine optical sensors under field conditions; (2) develop a quantitative relationship between image spectral reflectance and effective crop physiological parameters; (3) develop an operational precision N management procedure that combines variable-rate N recommendations at planting as derived from maps of grain yield, GPC, and test weight; and at mid-season as derived from quantitative relationships, remote sensing, and the DSS; and (4) address the economic and technology-transfer aspects of producers’ needs. Results from the research suggest that optical sensing and the DSS can be used for estimating the N status of dryland wheat and deciding whether additional N is needed to improve GPC. Significant findings include: 1. In-line NIR reflectance spectroscopy can be used to rapidly and accurately (SEP <5.0 mg g⁻¹) measure GPC of a grain stream conveyed by an auger. 2. On-combine NIR spectroscopy can be used to accurately estimate (R² < 0.88) grain test weight across fields. 3. Precision N management based on N removal increases GPC, grain yield, and profitability in rainfed wheat. 4. Hyperspectral SI and partial least squares (PLS) models have excellent potential for estimation of biomass, and water and N contents of wheat. 5. A novel heading index can be used to monitor spike emergence of wheat with classification accuracy between 53 and 83%. 6. Index MCARI/MTVI2 promises to improve remote sensing of wheat N status where water- not soil N fertility, is the main driver of plant growth. Important features include: (a) computable from commercial aerospace imagery that include the red edge waveband, (b) sensitive to Chl and resistant to variation in crop biomass, and (c) accommodates variation in soil reflectance. Findings #1 and #2 above enable growers to further implement an efficient, low cost PNM approach using commercially available on-combine optical sensors. Finding #3 suggests that profit opportunities may exist from PNM based on information from on-combine sensing and aerospace remote sensing. Finding #4, with its emphasis on data retrieval and accuracy, enhances the potential usefulness of a DSS as a tool for field crop management. Finding #5 enables land managers to use a DSS to ascertain at mid-season whether a wheat crop should be harvested for grain or forage. Finding #6a expands potential commercial opportunities of MS imagery and thus has special importance to a majority of aerospace imaging firms specializing in the acquisition and utilization of these data. Finding #6b on index MCARI/MVTI2 has great potential to expand use of ground-based sensing and in-season N management to millions of hectares of land in semiarid environments where water- not N, is the main determinant of grain yield. Finding #6c demonstrates that MCARI/MTVI2 may alleviate the requirement of multiple N-rich reference strips to account for soil differences within farm fields. This simplicity will be less demanding of grower resources, promising substantially greater acceptance of sensing technologies for in-season N management.
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Payment Systems Report - June of 2020. Banco de la República de Colombia, February 2021. http://dx.doi.org/10.32468/rept-sist-pag.eng.2020.

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With its annual Payment Systems Report, Banco de la República offers a complete overview of the infrastructure of Colombia’s financial market. Each edition of the report has four objectives: 1) to publicize a consolidated account of how the figures for payment infrastructures have evolved with respect to both financial assets and goods and services; 2) to summarize the issues that are being debated internationally and are of interest to the industry that provides payment clearing and settlement services; 3) to offer the public an explanation of the ideas and concepts behind retail-value payment processes and the trends in retail payments within the circuit of individuals and companies; and 4) to familiarize the public, the industry, and all other financial authorities with the methodological progress that has been achieved through applied research to analyze the stability of payment systems. This edition introduces changes that have been made in the structure of the report, which are intended to make it easier and more enjoyable to read. The initial sections in this edition, which is the eleventh, contain an analysis of the statistics on the evolution and performance of financial market infrastructures. These are understood as multilateral systems wherein the participating entities clear, settle and register payments, securities, derivatives and other financial assets. The large-value payment system (CUD) saw less momentum in 2019 than it did the year before, mainly because of a decline in the amount of secondary market operations for government bonds, both in cash and sell/buy-backs, which was offset by an increase in operations with collective investment funds (CIFs) and Banco de la República’s operations to increase the money supply (repos). Consequently, the Central Securities Depository (DCV) registered less activity, due to fewer negotiations on the secondary market for public debt. This trend was also observed in the private debt market, as evidenced by the decline in the average amounts cleared and settled through the Central Securities Depository of Colombia (Deceval) and in the value of operations with financial derivatives cleared and settled through the Central Counterparty of Colombia (CRCC). Section three offers a comprehensive look at the market for retail-value payments; that is, transactions made by individuals and companies. During 2019, electronic transfers increased, and payments made with debit and credit cards continued to trend upward. In contrast, payments by check continued to decline, although the average daily value was almost four times the value of debit and credit card purchases. The same section contains the results of the fourth survey on how the use of retail-value payment instruments (for usual payments) is perceived. Conducted at the end of 2019, the main purpose of the survey was to identify the availability of these payment instruments, the public’s preferences for them, and their acceptance by merchants. It is worth noting that cash continues to be the instrument most used by the population for usual monthly payments (88.1% with respect to the number of payments and 87.4% in value). However, its use in terms of value has declined, having registered 89.6% in the 2017 survey. In turn, the level of acceptance by merchants of payment instruments other than cash is 14.1% for debit cards, 13.4% for credit cards, 8.2% for electronic transfers of funds and 1.8% for checks. The main reason for the use of cash is the absence of point-of-sale terminals at commercial establishments. Considering that the retail-payment market worldwide is influenced by constant innovation in payment services, by the modernization of clearing and settlement systems, and by the efforts of regulators to redefine the payment industry for the future, these trends are addressed in the fourth section of the report. There is an account of how innovations in technology-based financial payment services have developed, and it shows that while this topic is not new, it has evolved, particularly in terms of origin and vocation. One of the boxes that accompanies the fourth section deals with certain payment aspects of open banking and international experience in that regard, which has given the customers of a financial entity sovereignty over their data, allowing them, under transparent and secure conditions, to authorize a third party, other than their financial entity, to request information on their accounts with financial entities, thus enabling the third party to offer various financial services or initiate payments. Innovation also has sparked interest among international organizations, central banks, and research groups concerning the creation of digital currencies. Accordingly, the last box deals with the recent international debate on issuance of central bank digital currencies. In terms of the methodological progress that has been made, it is important to underscore the work that has been done on the role of central counterparties (CCPs) in mitigating liquidity and counterparty risk. The fifth section of the report offers an explanation of a document in which the work of CCPs in financial markets is analyzed and corroborated through an exercise that was built around the Central Counterparty of Colombia (CRCC) in the Colombian market for non-delivery peso-dollar forward exchange transactions, using the methodology of network topology. The results provide empirical support for the different theoretical models developed to study the effect of CCPs on financial markets. Finally, the results of research using artificial intelligence with information from the large-value payment system are presented. Based on the payments made among financial institutions in the large-value payment system, a methodology is used to compare different payment networks, as well as to determine which ones can be considered abnormal. The methodology shows signs that indicate when a network moves away from its historical trend, so it can be studied and monitored. A methodology similar to the one applied to classify images is used to make this comparison, the idea being to extract the main characteristics of the networks and use them as a parameter for comparison. Juan José Echavarría Governor
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