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The technology acceptance model (TAM) is an information systems theory that models how users come to accept and use a technology. The model suggests that when users are presented with a new technology, a number of factors influence their decision about how and when they will use it, notably:
Perceived usefulness (PU) - This was defined by Fred Davis as "the degree to which a person believes that using a particular system would enhance his or her job performance".
Perceived ease-of-use (PEOU) - Davis defined this as "the degree to which a person believes that using a particular system would be free from effort" (Davis 1989).
TAM is one of the most influential extensions of Ajzen and Fishbein's theory of reasoned action (TRA) in the literature. Davis's technology acceptance model (Davis, 1989; Davis, Bagozzi, & Warshaw, 1989)
is the most widely applied model of users' acceptance and usage of technology
(Venkatesh, 2000). It was developed by Fred Davis and Richard Bagozzi (Davis 1989, Bagozzi, Davis & Warshaw 1992). TAM replaces many of TRA's attitude measures with the two technology acceptance measures—ease of use, and usefulness. TRA and TAM, both of which have strong behavioural elements, assume that when someone forms an intention to act, that they will be free to act without limitation. In the real world there will be many constraints, such as limited freedom to act (Bagozzi, Davis & Warshaw 1992).
Bagozzi, Davis and Warshaw say:
Because new technologies such as personal computers are complex and an element of uncertainty exists in the minds of decision makers with respect to the successful adoption of them, people form attitudes and intentions toward trying to learn to use the new technology prior to initiating efforts directed at using. Attitudes towards usage and intentions to use may be ill-formed or lacking in conviction or else may occur only after preliminary strivings to learn to use the technology evolve. Thus, actual usage may not be a direct or immediate consequence of such attitudes and intentions. (Bagozzi, Davis & Warshaw 1992)
Earlier research on the diffusion of innovations also suggested a prominent role for perceived ease of use. Tornatzky and Klein (Tornatzky & Klein 1982) analysed the adoption, finding that compatibility, relative advantage, and complexity had the most significant relationships with adoption across a broad range of innovation types. Eason studied perceived usefulness in terms of a fit between systems, tasks and job profiles, using the terms "task fit" to describe the metric (quoted in Stewart 1986) Legris, Ingham & Collerette 2003 suggest that TAM must be extended to include variables that account for change processes and that this could be achieved through adoption of the innovation model into TAM.
Several researchers have replicated Davis's original study (Davis 1989) to provide empirical evidence on the relationships that exist between usefulness, ease of use and system use (Adams, Nelson & Todd 1992; Davis 1989; Hendrickson, Massey & Cronan 1993; Segars & Grover 1993; Subramanian 1994; Szajna 1994). Much attention has focused on testing the robustness and validity of the questionnaire instrument used by Davis. Adams et al. (Adams 1992) replicated the work of Davis (Davis 1989) to demonstrate the validity and reliability of his instrument and his measurement scales. They also extended it to different settings and, using two different samples, they demonstrated the internal consistency and replication reliability of the two scales. Hendrickson et al. (Hendrickson, Massey & Cronan 1993) found high reliability and good test-retest reliability. Szajna (Szajna 1994) found that the instrument had predictive validity for intent to use, self-reported usage and attitude toward use. The sum of this research has confirmed the validity of the Davis instrument, and to support its use with different populations of users and different software choices.
Segars and Grover (Segars & Grover 1993) re-examined Adams et al.'s (Adams, Nelson & Todd 1992) replication of the Davis work. They were critical of the measurement model used, and postulated a different model based on three constructs: usefulness, effectiveness, and ease-of-use. These findings do not yet seem to have been replicated. However, some aspects of these findings were tested and supported by Workman (Workman 2007) by separating the dependent variable into information use versus technology use.
Mark Keil and his colleagues have developed (or, perhaps rendered more popularisable) Davis's model into what they call the Usefulness/EOU Grid, which is a 2×2 grid where each quadrant represents a different combination of the two attributes. In the context of software use, this provides a mechanism for discussing the current mix of usefulness and EOU for particular software packages, and for plotting a different course if a different mix is desired, such as the introduction of even more powerful software (Keil, Beranek & Konsynski 1995).
The TAM model has been used in most technological and geographic contexts. One of these contexts is health care, which is growing rapidly 
Venkatesh and Davis extended the original TAM model to explain perceived usefulness and usage intentions in terms of social influence (subjective norms, voluntariness, image) and cognitive instrumental processes (job relevance, output quality, result demonstrability, perceived ease of use). The extended model, referred to as TAM2, was tested in both voluntary and mandatory settings. The results strongly supported TAM2 (Venkatesh & Davis 2000).
The MPT model: Independent of TAM, Scherer (Scherer 1986) developed the matching person and technology model in 1986 as part of her National Science Foundation-funded dissertation research. The MPT model is fully described in her 1993 text (Scherer 2005, 1st ed. 1993), "Living in the State of Stuck", now in its 4th edition. The MPT model has accompanying assessment measures used in technology selection and decision-making, as well as outcomes research on differences among technology users, non-users, avoiders, and reluctant users.
The HMSAM: TAM has been effective for explaining many kinds of systems use (i.e. e-learning, learning management systems, webportals, etc.) (Fathema, Sutton, 2013, Fathema, Shannon, Ross, 2015, Fathema, Ross, Witte, 2014). However, TAM is not ideally suited to explain adoption of purely intrinsic or hedonic systems (e.g., online games, music, learning for pleasure). Thus, an alternative model to TAM, called the hedonic-motivation system adoption model (HMSAM) was proposed for these kinds of systems by Lowry et al. (Lowry et al.). HMSAM is designed to improve the understanding of hedonic-motivation systems (HMS) adoption. HMS are systems used primarily to fulfill users' intrinsic motivations, such for online gaming, virtual worlds, online shopping, learning/education, online dating, digital music repositories, social networking, only pornography, gamified systems, and for general gamification. Instead of a minor TAM extension, HMSAM is an HMS-specific system acceptance model based on an alternative theoretical perspective, which is in turn grounded in flow-based cognitive absorption (CA). HMSAM may be especially useful in understanding gamification elements of systems use.
Extended TAM: Several studies proposed extension of original TAM (Davis, 1989) by adding external variables in it with an aim of exploring the effects of external factors on users' attitude, behavioral intention and actual use of technology. Several factors have been examined so far. For example, perceived self-efficacy, facilitating conditions, and systems quality (Fathema, Shannon, Ross, 2015, Fathema, Ross, Witte, 2014). This model has also been applied in the acceptance of health care technologies.
TAM has been widely criticised, despite its frequent use, leading the original proposers to attempt to redefine it several times. Criticisms of TAM as a "theory" include its questionable heuristic value, limited explanatory and predictive power, triviality, and lack of any practical value (Chuttur 2009). Benbasat and Barki suggest that TAM "has diverted researchers' attention away from other
important research issues and has created an illusion of progress in knowledge accumulation. Furthermore, the
independent attempts by several researchers to expand TAM in order to adapt it to the constantly changing IT environments has lead [sic] to a state of theoretical chaos and confusion" (Benbasat & Barki 2007). In general, TAM focuses on the individual 'user' of a computer, with the concept of 'perceived usefulness', with extension to bring in more and more factors to explain how a user 'perceives' 'usefulness', and ignores the essentially social processes of IS development and implementation, without question where more technology is actually better, and the social consequences of IS use. Lunceford argues that the framework of perceived usefulness and ease of use overlooks other issues, such as cost and structural imperatives that force users into adopting the technology. For a recent analysis and critique of TAM, see Bagozzi (Bagozzi 2007).
Legris et al. claim that, together, TAM and TAM2 account for only 40% of a technological system's use.
A study conducted by Okafor, D. J., Nico, M. & Azman, B. B. (2016) discovered that perceived ease of use doesn't have any influence on the adoption of multimedia online technologies for Malaysian SMEs. The answers from the participants in this study suggest that, for them, perceived ease of use was not indicative of their behavioural intention to adopt multimedia online technologies (MOT) in the future. Instead of not adopting MOT, if they are complicated some participants said they are willing to learn it or practice more.
^Muhammad Sharif Abbasi; Ali Tarhini; Tariq Elyas; Farwa Shah (2015-10-09). "Impact of individualism and collectivism over the individual's technology acceptance behaviour: A multi-group analysis between Pakistan and Turkey". Journal of Enterprise Information Management. 28 (6): 747-768. doi:10.1108/JEIM-12-2014-0124. ISSN1741-0398.
Czaja, S. J.; Hammond, K; Blascovich, J. J.; Swede, H (1986), "Learning to use a word processing system as a function of training strategy", Behaviour and Information Technology, 5 (3): 203-216, doi:10.1080/01449298608914514
Davis, F. D. (1989), "Perceived usefulness, perceived ease of use, and user acceptance of information technology", MIS Quarterly, 13 (3): 319-340, doi:10.2307/249008, JSTOR249008
Davis, F. D.; Bagozzi, R. P.; Warshaw, P. R. (1989), "User acceptance of computer technology: A comparison of two theoretical models", Management Science, 35 (8): 982-1003, doi:10.1287/mnsc.35.8.982
Fathema, N., Sutton, K. (2013). Factors influencing faculty members' Learning Management Systems adoption behavior: An analysis using the Technology Acceptance Model. International Journal of Trends in Economics Management & Technology, Vol. II(vi), pg20-28
Fathema, N., Shannon, D., & Ross, M., (2015). Expanding the Technology Acceptance Model (TAM) to examine faculty use of Learning Management Systems (LMS). Journal of Online Learning and Teaching.11(2),210-233.
Fathema, N., Ross, M., Witte, M., (2014). Student acceptance of university web portals: A quantitative study. International Journal of Web Portals. 6(2).42-58.
Hendrickson, A. R.; Massey, P. D.; Cronan, T. P. (1993), "On the test-retest reliability of perceived usefulness and perceived ease of use scales", MIS Quarterly, 17 (2): 227-230, doi:10.2307/249803, JSTOR249803
Hu, P. J.; Chau, P. Y. K.; Sheng, O. R. L. (1999), "Examining the tehnoogy acceptance model using physician acceptance of telemedicine technology.", Journal of Management Information Systems, 16 (2): 91-112
Keil, M.; Beranek, P. M.; Konsynski, B. R. (1995), "Usefulness and ease of use: field study evidence regarding task considerations", Decision Support Systems, 13 (1): 75-91, doi:10.1016/0167-9236(94)e0032-m
King, W. R.; He, J. (2006), "A meta-analysis of the technology acceptance model", Information & Management, 43 (6): 740-755, doi:10.1016/j.im.2006.05.003
Legris, P.; Ingham, J.; Collerette, P. (2003), "Why do people use information technology? A critical review of the technology acceptance model", Information & Management, 40 (3): 191-204, doi:10.1016/s0378-7206(01)00143-4
Lowry, Paul Benjamin; Gaskin, James; Twyman, Nathan W.; Hammer, Bryan; Roberts, Tom L. (2013), "Taking fun and games seriously: Proposing the hedonic-motivation system adoption model (HMSAM)", Journal of the Association for Information Systems (JAIS), 14 (11): 617-671, SSRN2177442
Pikkarainen, T.; Pikkarainen, K.; Karjaluoto, H. (2004), "Consumer acceptance of online banking: An extension of the Technology Acceptance Model.", Internet Research-Electronic Networking Applications and Policy, 14 (3): 224-235, doi:10.1108/10662240410542652
Scherer, M. J. (2005), Living in the State of Stuck, Fourth Edition, Cambridge, MA: Brookline Books.
Scherer, M. J. (2004), Connecting to Learn: Educational and Assistive Technology for People with Disabilities, Washington, DC: American Psychological Association (APA) Books, doi:10.1037/10629-000, ISBN978-1-55798-982-6
Scherer, M. J. (2002), Assistive Technology: Matching Device and Consumer for Successful Rehabilitation, Washington, DC: APA Books.
Stewart, T. (1986), Task fit, ease-of-use and computer facilities, Norwood, NJ: Ablex, pp. 63-76 In N. Bjørn-Andersen, K. Eason, & D. Robey (Eds.), Managing computer impact: An international study of management and organizations
Subramanian, G. H. (1994), "A replication of perceived usefulness and perceived ease of use measurement", Decision Sciences, 25 (5/6): 863-873
Szajna, B. (1994), "Software evaluation and choice: predictive evaluation of the Technology Acceptance Instrument", MIS Quarterly, 18 (3): 319-324, doi:10.2307/249621, JSTOR249621
Tornatzky, L. G.; Klein, R. J. (1982), "Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings", IEEE Transactions on Engineering Management, EM-29: 28-45, doi:10.1109/tem.1982.6447463
Venkatesh, V.; Davis, F. D. (2000), "A theoretical extension of the technology acceptance model: Four longitudinal field studies", Management Science, 46 (2): 186-204, doi:10.1287/mnsc.22.214.171.12426
Venkatesh, V. (2000), "Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model", Information Systems Research, 11 (4), pp. 342-365
Workman, M. (2007), "Advancements in technology: New opportunities to investigate factors contributing to differential technology and information use.", International Journal of Management and Decision Making, 8 (2): 318-342, doi:10.1504/ijmdm.2007.012727
Wu, J. H.; Wang, S C. (2005), "What drives mobile commerce? An empirical evaluation of the revised technology acceptance model.", Information and Management, 42 (5): 719-729
Okafor, D. J., Nico, M. & Azman, B. B. (2016). The influence of perceived ease of use and perceived usefulness on the intention to use a suggested online advertising workflow. Canadian International Journal of Science and Technology, 6 (14), 162-174.
Document from the year 2014 in the subject Engineering - Communication Technology, grade: 1,3, Friedrich-Alexander University Erlangen-Nuremberg, course: Managing Information Technology, language: English, abstract: The Technology Acceptance Model (TAM) is an information systems theory. This model was developed by Fred Davis in his dissertation which was published in 1989. Since then, this model has spread to one of the most cited models in the context of technology diffusion (Kotrik). User acceptance of technology has been a vital area of studies for two decades now. Many models do predict the diffusion of a system but the Technology Acceptance model is the only model which focuses mainly on Information Systems (Chuttur). With a growing demand for technology in the 1970's the increasing failure of adapting systems within enterprises became a new area of research. Fred Davis, a doctoral student at the MIT Sloan School of Management, proposed the Technology acceptance model in 1985. He explained that the use of a system is a response to user's motivation. User's motivation on the other hand depends on system features and capabilities. (Chuttur) [...]
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Ein gut funktionierendes betriebliches Vorschlagswesen ist ein Instrument zur wirtschaftlichen und menschengerechten BetriebsfÃ¼hrung und kann demnach sowohl zur Erreichung der Unternehmensziele als auch zur Erreichung der individuellen Ziele der Mitarbeiter und Mitarbeiterinnen im Unternehmen beitragen. Gerade in einer unbestÃ¤ndigen Zeit wie dieser, kÃ¶nnen die Mitarbeiter durch ihr kreatives Potenzial zu guten Ideenlieferanten werden, welche zu Verbesserungen der allgemeinen wirtschaftlichen Situation und nicht zuletzt auch zu notwendigen Einsparungen fÃ¼hren kÃ¶nnen und sollen. Die Praxis zeigt aber recht hÃ¤ufig, dass solche Innovationen nicht den erwarteten Nutzen und Erfolg bringen, nicht zuletzt deshalb, weil sie von den Organisationsmitgliedern nicht entsprechend angenommen bzw. akzeptiert werden. Der Erfolg eines jeden Ideenmanagement hÃ¤ngt vom Mitwirken der beteiligten Personen ab. Nicht nur Mitarbeiter mÃ¼ssen sich engagieren und VorschlÃ¤ge einreichen, auch Vorgesetzte mÃ¼ssen sich mit den eingereichten Ideen bzw. VorschlÃ¤gen auseinandersetzen und sie bei Bedarf in die RealitÃ¤t umsetzen. Durch das Vorschlagswesen, welches zu den Wert bildenden Unternehmensbestandteilen gehÃ¶rt, kann ein Unternehmen direkt am Wissen seiner Mitarbeiter teilhaben. Es trÃ¤gt zur UnternehmensidentitÃ¤t bei, zeigt auf wie Ziele erreicht werden kÃ¶nnen und vertritt ein Menschenbild welches beweist, dass der Mitarbeiter, sein Wissen und seine Leistungen von groÃer Bedeutung sind. Zudem zeigt das Vorschlagswesen auf, dass jeder Mitarbeiter Ã¼ber seine TÃ¤tigkeit hinaus Interesse an seiner Arbeit, seinem Arbeitsplatz und seinem Unternehmen haben kann.
This case covers the introduction and diffusion of retail banking in Egypt and the development in electronic delivery channels and payment systems in its marketplace, using the Technology Acceptance Model as a starting point. The case represents a model for the application of advanced information and communication technology in the context of a developing nation, specifically, and explores the difficulties and unique challenges of information technology management in developing countries, generally.
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PresentsÂ informationÂ to create a trade-off analysis framework for use in government and commercial acquisition environments
This book presents a decision management process based on decision theory and cost analysis best practices aligned with the ISO/IEC 15288, the Systems Engineering Handbook, and the Systems Engineering Body of Knowledge. It provides a sound trade-off analysis framework to generate the tradespace and evaluate value and risk to support system decision-making throughout the life cycle. Trade-off analysis and risk analysis techniques are examined. The authors present an integrated value trade-off and risk analysis framework based on decision theory. These trade-off analysis concepts are illustrated in the different life cycle stages using multiple examples from defense and commercial domains.
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Dr. Renyan Jiang is a professor at theÂ Faculty of Automotive and Mechanical Engineering, Changsha University of Science and Technology, China.
Statistical Aspects of the Microbiological Examination of Foods, Third Edition, updates some important statistical procedures following intensive collaborative work by many experts in microbiology and statistics, and corrects typographic and other errors present in the previous edition. Following a brief introduction to the subject, basic statistical concepts and procedures are described including both theoretical and actual frequency distributions that are associated with the occurrence of microorganisms in foods. This leads into a discussion of the methods for examination of foods and the sources of statistical and practical errors associated with the methods. Such errors are important in understanding the principles of measurement uncertainty as applied to microbiological data and the approaches to determination of uncertainty.
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Includes additional figures and tables together with many worked examples to illustrate the use of specific procedures in the analysis of data obtained in the microbiological examination of foods
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Corrects typographic and other errors present in the previous edition
Genetically Modified Organisms in FoodÂ focuses on scientific evaluation of published research relating to GMO food products to assert their safety as well as potential health risks. This book is a solid reference for researchers and professionals needing information on the safety of GMO and non-GMO food production, the economic benefits of both GMO and non-GMO foods, and includes in-depth coverage of the surrounding issues of genetic engineering in foods. This is a timely publication written by a team of scientific experts in the field who present research results to help further more evidence based research to educate scientists, academics, government professionals about the safety of the global food supply.
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Paperback. Pub Date :2013-01-01 Pages: 230 Language: Chinese Publisher: Jiangxi People's Publishing House for the search engine technology acceptance model. according to the status of Internet search engine development and evaluation studies. combined with search engine technology for acceptance model. through questionnaires. data analysis. concluded: user perceived subjective norms. related tasks. the quality of the user's information. IT proficient and pleasure that affect their perception of the search engines and acceptance. which has a search engine to make recommendations to improve the quality. improve the quality of the user's own information and information technology proficiency levels in two ways. Contents: Preface Chapter 1 raised the issue of 1.2 Introduction 1.1 Overview of Search Engine 2.1 in Chapter 2. the theoretical basis of the technology acceptance model...