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, USA, pp. 2410-2419. 4. Chuttur, M. Y. (2009), “Overview of the Technology Acceptance Model: Origins, Developments and Future Directions”, Sprouts: Working Papers on Information Systems, Vol. 9, No. 37, Indiana University, USA. 5. Costello, A. B., Osborne, J. W. (2005), “Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis”, Practical Assessment Research & Evaluation, Vol. 10, No. 7, pp. 1-9. 6. Croatian Bureau of Statistics (2017), “Census of Population, Households and Dwellings 2011”, available at: https

References 1. Acarli, D. S., & Sağlam, Y. (2015). Investigation of pre-service teachers’ intentions to use of social media in teaching activities within the framework of technology acceptance model. Procedia-Social and Behavioral Sciences, 176, 709-713. 2. Aktaş, S. (2007). An application on technology acceptance model and accountants’ use of information technology. (Unpublished master’s thesis). Gebze Institute of Technology, Turkey. 3. Attewell, J., Savill-Smith, C., Douch, R., & Parker, G. (2010). Modernising education and training: Mobilising technology for

R eferences 1. Adams, D. A., Nelson, R. R., Todd, P.A. (1992). Perceived Usefulness, Ease of Use, and Usage of Information Technology: A Replication. In: MIS Quarterly , Vol. 16, pp. 227 – 247. 2. Agarwal, R., Prasad, J. (1998). A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology. In: Information Systems Research , Vol. 9, No. 2, pp. 204 – 215. 3. Alshare, K., Grandon, E., Miller, D. (2004). Antecedents of Computer Technology Usage: Considerations of the Technology Acceptance Model in the Academic

determine if the Technology Acceptance Model (TAM) could provide an adequate explanation of adoption and use of IP by common beans’ farmers. An additional aim was to determine the extent to which some economic, social, technical, environmental, and market factors influence the decision making, TA and usage of the bean’s growers. For the purpose of the present study, the TAM was tested with IP understood as a bundle of technologies. 1.2 Factors that influence technology adoption (TA) in agriculture Several prior studies seek to understand the individual decision

References Al-Harbi. K.A, (2011). 'e-Learning in the Saudi tertiary education Potential and challenges" Applied Computing and Informatics, Vol.9, pp 31-46. Al-Adwan. A.M, Al-Adwan, A.H. and Smedley. J. (2013), 'Exploring students acceptance of e- learning using Technology Acceptance Model in Jordanian Universities', International Journal of Education and Development using Information and Communication Technology, Vol.9 Issue 2. pp.4-18 Al-Hujran, O., Al-Debei, M.M Chatfield and Migdadi. M. (2015). "The imperative of influencing citizen attitude toward e

Marketing. Reber, R., Schwarz, N., & Winkielman, P. (2004). “Processing fluency and aesthetic pleasure: Is beauty in the perceiver’s processing experience?” Personality and Social Psychology Review, Vol. 8, No. 4, pp. 364–382. Salonen, V., Karjaluoto, H. (2016). “Web personalization: the state of the art and future avenues for research and practice.” Telematics Inform. Vol. 33, No. 4, pp. 1088-1104. Salovaara, A., Tamminen, S. (2009). “Accept or appropriate? A design-oriented critique on technology acceptance models”, available at http://www.academia.edu/3314912

interviews with project managers and on-site workers on various building projects in Norway, where the “* Capture” snagging app ( RIB 2019 ) was deployed. The interview questions were guided by the technology acceptance model (TAM) ( Davis 1985 ), our chosen theoretical approach. Thus, we hope to disclose any barriers to the employment of a relatively new technology that might improve the quality of buildings under construction. An early version of this study has been presented at the Creative Construction Conference 2019, and the conference paper was published in the

area concentrate on explaining the success and failure drivers related to the implementation of different types of software in organisations, as well as on looking for determinants that facilitate or obstruct the IT adoption by organisations and individual users. In research, IT adoption is most often explained using the Technology Acceptance Model (TAM). It evolved from the Theory of Reasoned Action (TRA), which is used in many different fields of study to predict and explain human behaviours that are motivated by rational actions and the intention to control

References Al-Adwan, Am., Al-Adwan, Ah., & Smedley, J. (2013). Exploring students acceptance of e-learning using Technology Acceptance, Model in Jordanian universities. International Journal of Education and Development using Information and Communication Technology, (IJEDICT), 9(2), 4-18. Retrieved December 5, 2013 from http://ijedict.dec.uwi.edu/viewissue.php?id=35 Baloğlu, M. (2003). Individual differences in statistics anxiety among college students. Personality and Individual Differences, 34(5), 855-865, http://dx.doi.org/10.1016/S0191-8869(02)00076-4 Bisoux

adoption in organizations, and less to individual adoption. Sun (2013) constructed an adoption model for cloud storage based on technology acceptance model (TAM) and task-technology fit (TTF), and found that perceived usefulness, perceived ease of use, and TTF influenced adoption intentions significantly ( Sun, 2013 ). Cao and Bi (2014) added perceived fee, perceived risk, and personal innovativeness factors to the Unified Theory of Acceptance and Use of Technology (UTAUT) model ( Cao & Bi, 2014 ; Venkatesh et al., 2003), and then verified it through an empirical