Shop for Technology acceptance model books. Get Technology Acceptance Model essential facts below. View Videos, Research or join the Technology Acceptance Model discussion. Add Technology Acceptance Model to your Like2do.com topic list for future reference or share this resource on social media.
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.
^Rahimi, Bahlol; Nadri, Hamed; Lotf nezhad afshar, Hadi; Timpka, Toomas (2018). "A Systematic Review of the Technology Acceptance Model in Health Informatics". Applied clinical informatics. 09 (03): 604. doi:10.1055/s-0038-1668091. PMID30112741.
^Nadri, Hamed; Rahimi, Bahlol; Lotf nezhad afshar, Hadi; Samadbeik, Mahnaz; Garavand, Ali (2018). "Factors Affecting Acceptance of Hospital Information Systems Based on Extended Technology Acceptance Model: A Case Study in Three Paraclinical Departments". Applied clinical informatics. 09 (02): 237. doi:10.1055/s-0038-1641595. PMID29618139.
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: 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
Davis, F. D.; Bagozzi, R. P.; Warshaw, P. R. (1989), "User acceptance of computer technology: A comparison of two theoretical models", Management Science, 35: 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: 227-230, doi:10.2307/249803
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
Scherer, M. J. (2002), Assistive Technology: Matching Device and Consumer for Successful Rehabilitation, Washington, DC: APA Books.
Segars, A. H.; Grover, V. (1993), "Re-examining perceived ease of use and usefulness: A confirmatory factor analysis", MIS Quarterly, 17: 517-525, doi:10.2307/249590
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
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.126.96.36.19926
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) [...]
To what extent does management recognize Technology acceptance model as a tool to increase the results? What are our Technology acceptance model Processes? Is Technology acceptance model currently on schedule according to the plan? Can we add value to the current Technology acceptance model decision-making process (largely qualitative) by incorporating uncertainty modeling (more quantitative)? What are the expected benefits of Technology acceptance model to the business?
This breakthrough Technology acceptance model self-assessment will make you the established Technology acceptance model domain auditor by revealing just what you need to know to be fluent and ready for any Technology acceptance model challenge.
How do I reduce the effort in the Technology acceptance model work to be done to get problems solved? How can I ensure that plans of action include every Technology acceptance model task and that every Technology acceptance model outcome is in place? How will I save time investigating strategic and tactical options and ensuring Technology acceptance model costs are low? How can I deliver tailored Technology acceptance model advice instantly with structured going-forward plans?
There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Technology acceptance model essentials are covered, from every angle: the Technology acceptance model self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Technology acceptance model outcomes are achieved.
Contains extensive criteria grounded in past and current successful projects and activities by experienced Technology acceptance model practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Technology acceptance model are maximized with professional results.
Your purchase includes access details to the Technology acceptance model self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria:
- The latest quick edition of the book in PDF
- The latest complete edition of the book in PDF, which criteria correspond to the criteria in...
- The Self-Assessment Excel Dashboard, and...
- Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation
...plus an extra, special, resource that helps you with project managing.
INCLUDES LIFETIME SELF ASSESSMENT UPDATES
Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
One of the most notable and momentary development recently has been the introduction of Internet banking as a means of transacting business. One of such approach is the application of technology acceptance model (TAM) that encourages customers to imbibe internet banking. However, considering the slow pace of adoption of Internet banking in CIMB customers despite the awareness of internet banking and its advantage. This study investigated the likely factors that determine and explain consumer behavioral intention to use in internet banking system. Adopting a quantitative approach through a survey method, a total of 400 questionnaires were distributed to Student and staff in Universiti Teknologi Malaysia and 375 properly completed questionnaires were returned giving a response rate of 94.5%. The theoretical frameworks of Technology Acceptance Model (TAM) has been utilized extensively as a predictor of user acceptance in this study, based on an individualâs determination of perceived usefulness (PU), perceived ease of use (PEU) and perceive credibility (PC) of a specific technology.
Seminar paper from the year 2015 in the subject Computer Science - Internet, New Technologies, grade: 1,3, Friedrich-Alexander University Erlangen-Nuremberg, language: English, abstract: The goal of this paper to find out factors that affect the acceptance of 3D printing toolkits. A hypothesized research model for 3D printing toolkits is proposed. Based on a survey of 30 participants this research model is analyzed and evaluated. The result is, that five of these seven proposed determinants have a strong influence on the Behavioral Intention to Use such a toolkit. Additive manufacturing, also known as 3D printing (3DP), is a technology which gained a lot of interest in recent years. The market is supposed to grow further with a new annual growth record of 35 % in 2013. However, the world leading market report for additive manufacturing, the Wohlers report, states that growth in the upcoming years is especially going to be driven by "3-D printers that cost less than $5,000, as well as the expanded use of the technology for the production of parts, especially metal, that go into final products."  Consequently, the following paper focuses on 3D printing for non-experts as more and more citizens can afford this technology and as there is not a lot of research in the field of information systems about 3D printing on the consumer level. Questions such as "What are the needs of consumers regarding 3D printing? Which are the top products the consumers want to produce? How do these non-experts deal with 3D printing design software?" have not been answered satisfactory yet. The goal of this paper to find out factors that affect the acceptance of 3D printing toolkits. A hypothesized research model for 3D printing toolkits is proposed. Based on a survey of 30 participants this research model is analyzed and evaluated. The result is, that five of these seven proposed determinants have a strong influence on the Behavioral Intention to Use such a toolkit. There are two diff
Facebook, Twitter, YouTube & Co. - Sie alle sind aus dem Privatleben von Jungen und Junggebliebenen nicht mehr wegzudenken. Doch auch im Beruf spielen Soziale Medien eine immer grÃ¶Ãere Rolle. In vielen Unternehmen ist Social Media lÃ¤ngst in der internen Kommunikation angekommen. Dennoch gibt es Firmen, die noch nicht auf den Zug der Neuen Medien aufgesprungen sind, oft auch, weil sich das Personal mit den neuen Technologien nicht auseinandersetzen kann oder will. Genau hier kann das Technology Acceptance Model (kurz: TAM) Abhilfe schaffen. Das TAM erklÃ¤rt auf wissenschaftlichem Wege, welche Voraussetzungen gegeben sein mÃ¼ssen, damit Ihre Mitarbeiter eine neue Technologie akzeptieren und mit ihr arbeiten. In diesem Buch erfolgt eine gewagte Neuinterpretation des TAM. Es wird nicht nur erklÃ¤rt, welche Kriterien zu einer Akzeptanz von Social Media in der internen Unternehmenskommunikation fÃ¼hren, sondern auch, wie man als Unternehmer aktiv zur ErfÃ¼llung dieser Kriterien beitragen kann. Abgerundet wird die Analyse mit einem Fallbeispiel zur EinfÃ¼hrung von Facebook in der internen Kommunikation. Dieses Buch basiert auf der gleichnamigen Bachelorarbeit des Autors und wurde in Kooperation mit dem "Web Literacy Lab" produziert.
GeoBEST (Base Engineer Survey Toolkit) is a software program built under contract with the USAF. It is designed to simplify the contingency beddown planning process through application of geographic information technology. The purpose of this thesis was to thoroughly evaluate GeoBEST using prospective GeoBEST users in a realistic beddown planning scenario. The Technology Acceptance Model (TAM) was applied, which measures a prospective user's perceptions of the technology's usefulness and ease-of- use and predicts their intentions to use the software in the future. The evaluation also included a qualitative evaluation of specific software features. The test group for this thesis was seventy-one Civil Engineering students attending contingency skills training at the Silver Flag training site, Tyndall AFB, FL. The students were given a one-hour interactive demonstration of GeoBEST after which they completed a survey. The students were given the option of using the program for preparation of their assigned beddown plan. Some Silver Flag instructors also completed a separate survey.The results from the TAM predict that the students were only slightly likely to use GeoBEST for beddown planning in the future. Throughout the course of the research, several features of GeoBEST were identified that limit the program's effectiveness. Some of these were minor irritants, while others were serious design flaws. Recommendations are made for implementation of GeoBEST and creation of training programs for prospective users.
Advances in grid technology in the past two decades have enabled some organizations to harness enormous computational power on demand. However, the prediction of widespread adoption of the grid technology has not materialized, while increasingly the cloud technology is becoming popular. In this book, the technology acceptance models were successfully tested and used to understand the factors that affect the acceptance or rejection of innovative grids and clouds. Using the online survey engine - Survey Monkey, data were collected from individuals (242 respondents) in schools, businesses and government in USA. The multiple regression technique was used to determine the relationship between the intent to adopt grids and these behavioral factors: perceived usefulness, perceived ease of use, attitude (competition from cloud computing technology) and trust (security). The research established a valuable model to predict acceptance or rejection of grids and clouds. The work sheds some light on the influential technology acceptance factors affecting grid and cloud technology, and should be especially useful to professionals in business, information technology and computer science.
Brand Newâs revolutionary innovation process is aproven road map you can put to work immediately tocreate successful new products, services, and business models.Written by leading innovation practitioners, and the coauthor ofthe bestseller Customers for Life, the authors of thistightly focused, highly entertaining book have nailed the issueperfectly when it comes to successfully introducing anything new.
Research shows people like new products and services.IndeedÂ they go out of their way to try to find them. Yetcompanies are truly terrible at providing new products and servicesthat meet these customersâ needs.
Why are companies so bad at giving customers what they want?Because they lack a simple proven process that makes sureinnovation occurs efficiently time after time.
No one knows this better than Mike Maddock and his team atMaddock Douglas, the Agency of Innovation,â¢ which has workedclosely with more than a quarter of Fortune 100.
To solve the innovation paradox, Maddock explains the processhis team has used to help the worldâs best companies andshows youÂ how to
Find needs and opportunity in the marketplace
Come up with significant market insights
Create compelling communication (using the actual words yourcustomers use) to convince people to try your new creation
What has worked for some of the worldâs most successfulcompanies, when it comes to innovation, will work for you. Startputting the lessons of Brand New to work foryouâ¦before the competition does.
Implementing computer systems is considered to be the most important phase in information systems development. New information systems can be subject to failure due to many reasons. One main reason is the rejection to use the new system. This relies on users? adoption of change. Studying how individuals accept new computer systems is one of the main issues in information systems research. Organisations need to develop and implement information and communication technology systems successfully. Successful implementation of any system depends on its acceptance and use by potential users. This study investigates how individuals make their decisions towards new information and communication technology systems. t The technology acceptance model (TAM), which includes new factors which have direct and indirect influence on managers? decisions to use new technology. The study pursues an answer for the research question ?what factors affect managers? decisions to accept or reject a new ICT system?? The results of this research is a new extension TAM to include more constructs which have evolved due to the fast developing technology.
This study will examine student perceptions ofcomputer-mediated communications (CMC) tools and howtheir perceptions may assist the institutionsdecisions to select and acquire those technologies. This study may help administrators make more informeddecisions regarding learning technology purchasesthat are more closely aligned with the organizationsstrategic direction and their student-centriccommitments. The value of investment in thesesystems can only be derived form the use they receiveby students? as well as faculty. The results of this study may be beneficial toadministrators at the university level when makingdecisions about technologies that may affect theteaching/learning process. Further, may help guidedecisions regarding where to commit resources(technology, monetary, labor, etc.) to implement andmaintain those systems. Moreover, it may encourageconcentrating the universities efforts on a smallernumber of technologies and training programs todevelop faculty and student skills in the use ofcomputer-mediated communication technologies withinthe university setting.