بررسی عوامل مؤثر بر تمایلات رفتاری نسبت به استفاده از فناوری اطلاعات در کارکنان مدارس الکترونیکی
الموضوعات :زهره شکیبایی 1 , عذرا سمنانی 2 , مریم گلی‌توانا 3
1 - استادیار گروه مدیریت آموزشی، واحد تنکابن، دانشگاه آزاد اسلامی، تنکابن، ایران
2 - دانش آموخته کارشناسی ارشد مدیریت آموزشی، واحد تنکابن، دانشگاه آزاد اسلامی، تنکابن، ایران
3 - دانشجوی دکترای مدیریت آموزشی، واحد تنکابن، دانشگاه آزاد اسلامی، تنکابن، ایران
الکلمات المفتاحية: مدارس الکترونیکی, تمایل رفتاری نسبت به استفاده از فناوری اطلاعات, سازگاری ادراک شده, سودمندی ادراک شده, سهولت ادراک شده, تجربه نسبت به استفاده,
ملخص المقالة :
این پژوهش با هدف بررسی عوامل مؤثر بر تمایلات رفتاری نسبت به استفاده از فناوری اطلاعات در کارکنان مدارس الکترونیکی استان گیلان انجام شد. روش پژوهش توصیفی از نوع همبستگی بوده است. جامعه آماری، شامل کلیه کارکنان مدارس الکترونیکی استان گیلان به تعداد 2145 بود. حجم نمونه بر اساس فرمول کوکران 326 نفر برآورد گردید و از روش نمونه‌گیری غیراحتمالی در دسترس استفاده شد. ابزار پژوهش شامل پرسش‌نامه محقق ساخته برای اندازه‌گیری متغیرهای اثرگذار بر تمایلات رفتاری نسبت به استفاده از فناوری اطلاعات میباشد. جهت سنجش روایی ابزار از روش روایی صوری و روایی همگرا با استفاده از میانگین واریانس استخراج شده (AVE) که بالاتر از 0/5 برآورد گردید، استفاده شد و پایایی ابزار با استفاده از آلفای کرونباخ 0/85 و همچنین، با استفاده از اعتبار ترکیبی از طریق ضریب دیلون- گلدنشتاین بالای 0/7 محاسبه شد. تحلیل دادهها از طریق آمار استنباطی و تکنیک آماری مدل‌یابی معادلات ساختاری با رویکرد حداقل مربعات جزیی انجام شده است. نتایج حاکی از تأثیر هنجارهای ذهنی، سودمندی ادراک شده، سهولت ادراک شده، ریسک ادراک شده، تجربه نسبت به استفاده و انتظار بهبود عملکرد بر تمایل رفتاری نسبت به استفاده از فناوری اطلاعات دارد. همچنین، نتایج نشان داد، سازگاری ادراک شده در رابطه بین سودمندی ادراک شده و سهولت ادراک شده، ریسک ادراک شده، تجربه نسبت به استفاده، انتظار بهبود عملکرد و تمایلات رفتاری نسبت به استفاده از فناوری اطلاعات، نقش تعدیل‌کنندگی دارد.
Abdulwand, M. A. (2013). An investigation of the factors affecting the acceptance of internet banking by combining two models of technology acceptance and theory of planned behavior with consumer perceived risk and profit. Marketing Management, 15, 2-14. (in Persian).
Ahmadi Deh Ghotboddini, M., Meshkani, M., & Mohammad Khani, A. (2010). Effect of computer self-efficacy and computer anxiety on the structures of the davis technology acceptance model: New perspectives of social psychology. Psychological Research, 13(1), 51-72. (in Persian).
Ahmadi, A., & Jadidi, A. (2011). The relation between the complexity of the internet on the ease of use and perceived usefulness of the internet among school administrators. New Approach in Educational Management, 2(3), 106-89. (in Persian).
Akbar, F. (2013). What affects students’ acceptance and use of technology? Dietrich College of Humanities and Social Sciences. Dietrich College Honors Theses,Carnegie Mellon University. Retrieved from http://repository.cmu.edu/hsshonors
Akturan, U., & Tezcan, N. (2012). Mobile banking adoption of the youth market: Perceptions and intentions. Marketing Intelligence & Planning, 30(4), 444-459.
Alirezaie, A., Jabbarzadeh, H. Haji Akhundi, A., & Youshanlouie, H. (2014). Adoption of teleworking technology in tehran organizations: Explaining the Role of Social Influence, Motivation and Facilitating Conditions. Information Technology Management, 5(3), 105-122. (in Persian).
Atafar, A., Khazai Poul, J., & Pour Mustafa Khoshkrodi, M. (2013), Factors affecting acceptance of information technology in the tourism industry. Tourism Management, 7(18), 131-156. (in Persian).
Ayeh, J. (2015). Travellers’ acceptance of consumer-generated media: An integrated model of technology acceptance and source credibility theories. Computers in Human Behavior, 48, 173-180.
Baradaran, V. (2015). Factors affecting internet banking by legal persons based on the development of technology acceptance model (Case Study: New economy bank), Technology Development Management, 3(1), 99-122. (in Persian).
Bhatiasevi, V., & Yoopetch, C. (2015). The determinants of intention to use electronic booking among young users in Thailand. Hospitality and Tourism Management, 23, 1-15.
Cai, Z., Fan, X., & Du, J. (2017). Gender and attitudes toward technology use: A meta-analysis. International Journal of Computers & Education, 105, 1-13.
Chen, Shih-Chih., Jong, Din. & Lai, Min-Tsai. (2014). Assessing the relationship between technology readiness and continuance intention in an e-appointment system: Relationship quality as a mediator. Med Syst, 38, 1-12.
Cheung Chan, S., & Te Lu, D. M. (2004). Understanding internet banking adoption and use behavior: A Hong Kong perspective. Global Information Management, 12(3), ABI/INFORM Global pg. 21 2004.
Chien, S.-H., Chen, Y-H., & Hsu, C.-Y. (2012). Exploring the impact of trust and relational embeddedness in e-marketplaces: An empirical study in Taiwan. Industrial Marketing Management, 41(3), 460-468.
Chiou, Y. (2012). Perceived usefulness, perceive ease of use, computer attitude, and using experience of Web 2.0 applications as predictors of intent to use Web 2.0 by pre-service teachers for teaching. Dissertation Abstracts International Section A, 72, 4527. Retrieved from EBSCOhost
Chow, M., Herold, D. K., Choo, T. M., & Chan, K. (2012). Extending the technology acceptance model to explore the intention to use second life for enhancing healthcare education. Computers and Education, 59(4), 1136-1144.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
Dishaw, M. T., Strong, D. M., & Bandy, D. B. (2002). Extending the task-technology fit model with self-efficacy constructs. Retrieved from www.melody.syr.edu/hci/ amcis02_minitrack/RIP/Dishaw.pdf
Dutot, V. (2015). Factors influencing Near Field Communication (NFC) adoption: An extended TAM approach. High Technology Management Research, 26, 45-57.
Ertmer, P. A., Ottenbreit-Leftwich, A. T., Sadik, O., Sendurur, E., & Sendurur, P. (2012). Teacher beliefs and technology integration practices: A critical relationship. Computers and Education, 59(2), 423-435. Retrieved from http://dx. doi.org/10.1016/j.compedu.2012.02.001
Fazio, R. H., & Roskos-Ewoldsen, D. R. (2005). Acting as we feel: When and how attitudes guide behavior. In T. C. Brock, & M. C. Green (Eds.), Persuasion: Psychological insights and perspectives. Thousand Oaks, CA, US: Sage Publications, Inc.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Marketing Research, 18(1), 39-50.
Giovanis, A. N., Binioris, S., & Polychronopoulos, G. (2012). An extension of TAM model with IDT and security/privacy risk in the adoption of internet banking services in Greece. EuroMed Journal of Busines, 7(1), 24-53.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2012). PLS-SEM: Indeed a silver bullet. Marketing Theory and Practice, 19(2), 139-151.
Heidari, H., Alborzi, M., & Mosa Khani, M. (2016). Effective factors on encouraging students to use social networks as a virtual learning network. Human Interaction and Information, 3(2), 57-69. (in Persian).
Ho, S. M, Ocasio, M., & Booth, C. (2017). Trust or consequences? Causal effects of perceived risk and subjective norms on cloud technology adoption. Computers & Security. Retrieved from http://dx.doi.org/doi: 10.1016/j.cose.2017.08.004
Hosseini, S., Mirzaie Alavijeh, M., Ataei, M., Jalilian, F., Karami Matin, B., & Rastegar, L. (2015). Admission of e-learning from the perspective of faculty members of Kermanshah University of Medical Sciences and Health Services. Medical Education, 14(5), 447-437. (in Persian).
Hur, J. W., Shen, Y. W., Kale, U., & Cullen, T. (2015). An exploration of pre-service teachers' intention to use mobile devices for teaching. International Journal of Mobile and Blended Learning, 7(3), 1-18.
Imtiaz, M. A., & Maarop, N. (2014). A review of technology acceptance studies in the field of education. Teknologi, 69(2), 27e32.
Jalali., Z., Ashrafi Rizi., H., Soleimani, M., & Afshar, M. (2017). Factors affecting information technology acceptance by isfahan university librarians based on TAM Model. Health Consequence, 11(4), 400-410. (in Persian).
Kafashan, M. (2010). Application of technology acceptance theories in the evaluation of information technology libraries: A textual analysis approach. Library and Information Science, 13(4), 193-218. (in Persian).
Kale, U. (2018). Technology valued? Observation and review activities to enhance future teachers’ utility value toward technology integration. International Journal of Computers & Education, 117, 160-174.
Khedmatgozar, H.R, Hanafizadeh, P., & Kianpour, R. (2011). The role of perceived risk dimensions of banking customers in Internet banking acceptance in Iran. Management Sciences of Iran, 5(20), 49-68. (in Persian).
Khodadad Hosseini, H., Nouri, A., & Zabihi, M. (2013). Admission of e-learning in higher education: Application of stream theory, technology acceptance model and quality of services. Research and Planning in Higher Education, 19(1), 111-136. (in Persian).
Koutromanos, G., Styliaras, G., & Christodoulou, S. (2015). Student and in-service teachers' acceptance of spatial hypermedia in their teaching: The case of hypersea. Education and Information Technologies, 20(3), 559-578.
Kurkinen, E. (2012). On the exploration of mobile technology acceptance among law enforcement officers using Structural Equation Modelling (SEM): A multi-group analysis of the Finnish Police Force. Jyväskylä: University of Jyväskylä, 2012, 159 P. (Jyväskylä Studies in Computing. ISSN 1456-5390; 159).
Lazgian, M., Haddadian, A., Kafashan, M., & Aseman Darre, Y. (2013). Student perceptions of electronic services in academic libraries: A research based on the theory of planned behavior of Ajzen. Information Processing and Management, 29(2), 333-350. (in Persian).
Lazgian, M., Mortazavi, S., & Rajabzadeh, M. (2011). The effect of factors affecting the acceptance of electronic government services by users using the UTAUT Pattern. Management and Development Process, 87, 4-20. (in Persian).
Lee, D. Y., & Lehto, M. R. (2013). User acceptance of YouTube for procedural learning: An extension of the Technology Acceptance Model. International Journal of Computers & Education, 61, 193-208.
Lee, M. C. (2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electron. Commerce Res. Applic., 8: 130-141. DOI: 10.1016/j.elerap.2008.11.006.
Lee, S., Kang H., & Shin G. (2015). Head flexion angle while using a smartphone. Ergonomics, 58(2), 220-226.
Littler, D., & Melanthiou, D. (2006). Consumer perceptions of risk and uncertainty and the implications for behavior towards innovative retail services: The case of internet banking. J. Retail. Consumer Services, 13, 431-443. DOI: 10.1016/j. jretconser.2006.02.006
Maleki Najafdar, A. R, Rasulli Shemirani, R., & Rousta, M. (2012). Investigating the effect of factors affecting the adoption and application of information technology based on the Davis Model (Case Study of tax officers of southern Province of Tehran), Journal of Research Institute of Taxation, 4(62), 167-136. (in Persian).
Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 91-173.
McCarthy, J., & Wright, P. (2004). Technology as experience. Cambridge MA: MIT Press.
Montazeri, M, Mirzai, A, Pasandbury, N., & Kharazmi, M. (2014). The role of technology acceptance model, theory of planned behavior and trust component in internet banking acceptance (Case study: Customers of the National Bank of Sirjan City). Monetary and Banking Management Development Quarterly, 2(4), 2-18. (in Persian).
Naderi Bani, M., Delshad, A., Mohammadi, F., & Adibzadeh, M. (2014). Factors affecting information technology acceptance in Shiraz Hotels. Tourism Management Studies, 10(29), 69-93. (in Persian).
Najmul Islam, A. (2016). E-learning system use and its outcomes: Moderating role of perceived compatibility. Telematics and Informatics, 8, 92-106.
Nakhaie, A., & Kheiri, B. (2012). Investigating selected effects on Internet to purchase green products. Marketing Management, 15, 130-105. (in Persian).
OECD. (2016). PISA 2015 results: Excellence and equity in education (Vol. I). Paris: OECD Publishing.
Ozturk, A. B. (2016). Customer acceptance of cashless payment systems in the hospitality industry. International Journal of Contemporary Hospitality Management, 28(4). In press.
Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning. In Educational Technology & Society, 12(3), 150-162.
Partala, S., & Saari, T. (2015). Understanding the most influential user experiences in successful and unsuccessful technology adoptions. Computers in Human Behavior, 53, 381-395.
Rasouli M., R. (2015). The structural model of the relationship between cultural values and cognitive beliefs with the level of internet use between undergraduate students at Allameh University. Culture and Communication Studies, 15(28), 78-105. (in Persian).
Renny, G. Suryo., & Siringoringo, H. (2013). Perceived usefulness, ease of use, and attitude towards online shopping usefulness towards online airlines ticket purchase. Procedia - Social and Behavioral Sciences, 81, 212-216.
Sadaf, A., Newby, T., & Ertmer, P. (2016). An investigation of the factors that influence preservice teachers' intentions and integration of Web 2.0 tools. Educational Technology Research & Development, 64(1), 37-64. Retrieved From http://dx.doi. org/10.1007/s11423-015-9410-9
Sarlak, M, Golpaygani, Z., & Yamani, M. (2014). Investigating the factors affecting the adoption of e-government by referents to tehran’s judiciary based on the dtpb model (Case Study: Case management system of Shahid Beheshti Complex). Development Management Process, 27(1), 54-27. (in Persian).
Schepers, J., & Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44, 90-103.
Scherer, R., Tondeur, J., Siddiq, F., & Baran, E. (2018). The importance of attitudes toward technology for pre-service teachers' technological, pedagogical, and content knowledge: Comparing structural equation modeling approaches. Computers in Human Behavior, 80, 67-80.
Šebjan, U., & Tominc, P. (2015). Impact of support of teacher and compatibility with needs of study on usefulness of SPSS by students. Computers in Human Behavior, 53, 354-365
Seif, M. H. (2016). Presentation of the causal model of behavioral ethics in the use of information technology in medical students of medical sciences of shiraz. Medical Ethics, 10 (35), 198-177.
Sepehri, M. M., Abdolvand N., & Baradaran, V. (2013). Developing strategic alignment model of business strategies and information technology. Strategic Management Studies, 14, 143-125.
Shah, M. u., Fatimee, S., & Sajjad, M. (2014). Mobile commerce adoption: An empirical analysis of the factors affecting consumer intention to use mobile commerce. Journal of Basic and Applied Scientific Research, 4, 80-88.
Sheikh Shoaee, F. (2007). Technology acceptance model: Application and concepts. Information Management Quarterly, 1(6), 35-46.
Shoham S., & Gonen A. (2008). Intentions of hospital nurses to work with computers. CIN, 26(2), 106-116.
Siddiq, F., Hatlevik, O. E., Olsen, R. V., Throndsen, I., & Scherer, R. (2016). Taking a future perspective by learning from the past e a systematic review of assessment instruments that aim to measure primary and secondary school students' ICT literacy. Educational Research Review, 19, 58e84. Retrieved From https://doi.org/ 10.1016/ j.edurev.2016.05.002
Srite, M., & Karahanna, E. (2006). The role of espoused national cultural values in technology acceptance. MIS Quarterly, 30(3), 679-704.
Teo, T., Milutinovi, C. V., Zhou, M., & Bankovi, C. D. (2016). Traditional vs. innovative uses of computers among mathematics pre-service teachers in Serbia. Interactive Learning Environments, 1e17. Retrieved from https://doi.org/10.1080/ 10494820.2016. 1189943.
Van Laar, E., van Deursen, A. J. A. M., van Dijk, J. A. G. M., & de Haan, J. (2017). The relation between 21st-century skills and digital skills: A systematic literature review. Computers in Human Behavior, 72, 577e588. Retrieved from https://doi.org/10.1016/ j.chb.2017.03.010
Venkatesh, V., & Bala, H. (2008).Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39, 273-315.
Venkatesh, V., Morris, M., Davis, G., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
Walter, N, Ortbach, K., & Niehaves, B. (2015). Designing electronic feedback-Analyzing the effects of social presence on perceived feedback usefulness. Int. J. Human-Computer Studies, 76, 1-11.
Wetzels, M., Odekerken-Schroder, G., Oppen, C. (2009). Using PLS path modelling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Quarterly, 33, (1), 177-195.
Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information & Management, 42(5), 719-729.
Wu, W., & Ke, C. C. (2015). An online shopping behavior model integrating personality traits, perceived risk, and technology acceptance. Social Behavior and Personality, 43(1), 85-98.
Yiu, C. S., Grant, Y. K., & Edgar, D. (2007). Factors affecting the adoption of internet banking in Hong Kong: Implications for the banking sector. International Journal of Information Management, 2, 336-351.
Yu, C-S. (2012). Factors affecting individuals to adopt mobile banking: Empirical evidence from the UTAUT Model. Electronic Commerce Research, 13(2), 104-121.
Yusop, F. D. (2015). A data set of factors that influence preservice teachers' intentions to use web 2.0 technologies in future teaching practices. British Journal of Educational Technology, 46(5), 1075-1080.
Zhao, A. L., Koenig-Lewis, N., Hanmer-Lloyd, S., & Ward, P. (2010). Adoption of internet banking services in China: Is it all about trust. International Journal of Bank Marketing, 28(1), 7-26.
Zint, M. (2002). Comparing three attitude-behavior theories for predicting science teachers’ intentions. Research in Science Teaching, 39(9), 819-844.
Zogheib, B., Rabaa’i, A., Zogheib, S., & Elsaheli, A. (2015). University student perceptions of tech-neology use in mathematics learning. Information Technology Education: Research, 14, 417-438.
_||_Abdulwand, M. A. (2013). An investigation of the factors affecting the acceptance of internet banking by combining two models of technology acceptance and theory of planned behavior with consumer perceived risk and profit. Marketing Management, 15, 2-14. (in Persian).
Ahmadi Deh Ghotboddini, M., Meshkani, M., & Mohammad Khani, A. (2010). Effect of computer self-efficacy and computer anxiety on the structures of the davis technology acceptance model: New perspectives of social psychology. Psychological Research, 13(1), 51-72. (in Persian).
Ahmadi, A., & Jadidi, A. (2011). The relation between the complexity of the internet on the ease of use and perceived usefulness of the internet among school administrators. New Approach in Educational Management, 2(3), 106-89. (in Persian).
Akbar, F. (2013). What affects students’ acceptance and use of technology? Dietrich College of Humanities and Social Sciences. Dietrich College Honors Theses,Carnegie Mellon University. Retrieved from http://repository.cmu.edu/hsshonors
Akturan, U., & Tezcan, N. (2012). Mobile banking adoption of the youth market: Perceptions and intentions. Marketing Intelligence & Planning, 30(4), 444-459.
Alirezaie, A., Jabbarzadeh, H. Haji Akhundi, A., & Youshanlouie, H. (2014). Adoption of teleworking technology in tehran organizations: Explaining the Role of Social Influence, Motivation and Facilitating Conditions. Information Technology Management, 5(3), 105-122. (in Persian).
Atafar, A., Khazai Poul, J., & Pour Mustafa Khoshkrodi, M. (2013), Factors affecting acceptance of information technology in the tourism industry. Tourism Management, 7(18), 131-156. (in Persian).
Ayeh, J. (2015). Travellers’ acceptance of consumer-generated media: An integrated model of technology acceptance and source credibility theories. Computers in Human Behavior, 48, 173-180.
Baradaran, V. (2015). Factors affecting internet banking by legal persons based on the development of technology acceptance model (Case Study: New economy bank), Technology Development Management, 3(1), 99-122. (in Persian).
Bhatiasevi, V., & Yoopetch, C. (2015). The determinants of intention to use electronic booking among young users in Thailand. Hospitality and Tourism Management, 23, 1-15.
Cai, Z., Fan, X., & Du, J. (2017). Gender and attitudes toward technology use: A meta-analysis. International Journal of Computers & Education, 105, 1-13.
Chen, Shih-Chih., Jong, Din. & Lai, Min-Tsai. (2014). Assessing the relationship between technology readiness and continuance intention in an e-appointment system: Relationship quality as a mediator. Med Syst, 38, 1-12.
Cheung Chan, S., & Te Lu, D. M. (2004). Understanding internet banking adoption and use behavior: A Hong Kong perspective. Global Information Management, 12(3), ABI/INFORM Global pg. 21 2004.
Chien, S.-H., Chen, Y-H., & Hsu, C.-Y. (2012). Exploring the impact of trust and relational embeddedness in e-marketplaces: An empirical study in Taiwan. Industrial Marketing Management, 41(3), 460-468.
Chiou, Y. (2012). Perceived usefulness, perceive ease of use, computer attitude, and using experience of Web 2.0 applications as predictors of intent to use Web 2.0 by pre-service teachers for teaching. Dissertation Abstracts International Section A, 72, 4527. Retrieved from EBSCOhost
Chow, M., Herold, D. K., Choo, T. M., & Chan, K. (2012). Extending the technology acceptance model to explore the intention to use second life for enhancing healthcare education. Computers and Education, 59(4), 1136-1144.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
Dishaw, M. T., Strong, D. M., & Bandy, D. B. (2002). Extending the task-technology fit model with self-efficacy constructs. Retrieved from www.melody.syr.edu/hci/ amcis02_minitrack/RIP/Dishaw.pdf
Dutot, V. (2015). Factors influencing Near Field Communication (NFC) adoption: An extended TAM approach. High Technology Management Research, 26, 45-57.
Ertmer, P. A., Ottenbreit-Leftwich, A. T., Sadik, O., Sendurur, E., & Sendurur, P. (2012). Teacher beliefs and technology integration practices: A critical relationship. Computers and Education, 59(2), 423-435. Retrieved from http://dx. doi.org/10.1016/j.compedu.2012.02.001
Fazio, R. H., & Roskos-Ewoldsen, D. R. (2005). Acting as we feel: When and how attitudes guide behavior. In T. C. Brock, & M. C. Green (Eds.), Persuasion: Psychological insights and perspectives. Thousand Oaks, CA, US: Sage Publications, Inc.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Marketing Research, 18(1), 39-50.
Giovanis, A. N., Binioris, S., & Polychronopoulos, G. (2012). An extension of TAM model with IDT and security/privacy risk in the adoption of internet banking services in Greece. EuroMed Journal of Busines, 7(1), 24-53.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2012). PLS-SEM: Indeed a silver bullet. Marketing Theory and Practice, 19(2), 139-151.
Heidari, H., Alborzi, M., & Mosa Khani, M. (2016). Effective factors on encouraging students to use social networks as a virtual learning network. Human Interaction and Information, 3(2), 57-69. (in Persian).
Ho, S. M, Ocasio, M., & Booth, C. (2017). Trust or consequences? Causal effects of perceived risk and subjective norms on cloud technology adoption. Computers & Security. Retrieved from http://dx.doi.org/doi: 10.1016/j.cose.2017.08.004
Hosseini, S., Mirzaie Alavijeh, M., Ataei, M., Jalilian, F., Karami Matin, B., & Rastegar, L. (2015). Admission of e-learning from the perspective of faculty members of Kermanshah University of Medical Sciences and Health Services. Medical Education, 14(5), 447-437. (in Persian).
Hur, J. W., Shen, Y. W., Kale, U., & Cullen, T. (2015). An exploration of pre-service teachers' intention to use mobile devices for teaching. International Journal of Mobile and Blended Learning, 7(3), 1-18.
Imtiaz, M. A., & Maarop, N. (2014). A review of technology acceptance studies in the field of education. Teknologi, 69(2), 27e32.
Jalali., Z., Ashrafi Rizi., H., Soleimani, M., & Afshar, M. (2017). Factors affecting information technology acceptance by isfahan university librarians based on TAM Model. Health Consequence, 11(4), 400-410. (in Persian).
Kafashan, M. (2010). Application of technology acceptance theories in the evaluation of information technology libraries: A textual analysis approach. Library and Information Science, 13(4), 193-218. (in Persian).
Kale, U. (2018). Technology valued? Observation and review activities to enhance future teachers’ utility value toward technology integration. International Journal of Computers & Education, 117, 160-174.
Khedmatgozar, H.R, Hanafizadeh, P., & Kianpour, R. (2011). The role of perceived risk dimensions of banking customers in Internet banking acceptance in Iran. Management Sciences of Iran, 5(20), 49-68. (in Persian).
Khodadad Hosseini, H., Nouri, A., & Zabihi, M. (2013). Admission of e-learning in higher education: Application of stream theory, technology acceptance model and quality of services. Research and Planning in Higher Education, 19(1), 111-136. (in Persian).
Koutromanos, G., Styliaras, G., & Christodoulou, S. (2015). Student and in-service teachers' acceptance of spatial hypermedia in their teaching: The case of hypersea. Education and Information Technologies, 20(3), 559-578.
Kurkinen, E. (2012). On the exploration of mobile technology acceptance among law enforcement officers using Structural Equation Modelling (SEM): A multi-group analysis of the Finnish Police Force. Jyväskylä: University of Jyväskylä, 2012, 159 P. (Jyväskylä Studies in Computing. ISSN 1456-5390; 159).
Lazgian, M., Haddadian, A., Kafashan, M., & Aseman Darre, Y. (2013). Student perceptions of electronic services in academic libraries: A research based on the theory of planned behavior of Ajzen. Information Processing and Management, 29(2), 333-350. (in Persian).
Lazgian, M., Mortazavi, S., & Rajabzadeh, M. (2011). The effect of factors affecting the acceptance of electronic government services by users using the UTAUT Pattern. Management and Development Process, 87, 4-20. (in Persian).
Lee, D. Y., & Lehto, M. R. (2013). User acceptance of YouTube for procedural learning: An extension of the Technology Acceptance Model. International Journal of Computers & Education, 61, 193-208.
Lee, M. C. (2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electron. Commerce Res. Applic., 8: 130-141. DOI: 10.1016/j.elerap.2008.11.006.
Lee, S., Kang H., & Shin G. (2015). Head flexion angle while using a smartphone. Ergonomics, 58(2), 220-226.
Littler, D., & Melanthiou, D. (2006). Consumer perceptions of risk and uncertainty and the implications for behavior towards innovative retail services: The case of internet banking. J. Retail. Consumer Services, 13, 431-443. DOI: 10.1016/j. jretconser.2006.02.006
Maleki Najafdar, A. R, Rasulli Shemirani, R., & Rousta, M. (2012). Investigating the effect of factors affecting the adoption and application of information technology based on the Davis Model (Case Study of tax officers of southern Province of Tehran), Journal of Research Institute of Taxation, 4(62), 167-136. (in Persian).
Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 91-173.
McCarthy, J., & Wright, P. (2004). Technology as experience. Cambridge MA: MIT Press.
Montazeri, M, Mirzai, A, Pasandbury, N., & Kharazmi, M. (2014). The role of technology acceptance model, theory of planned behavior and trust component in internet banking acceptance (Case study: Customers of the National Bank of Sirjan City). Monetary and Banking Management Development Quarterly, 2(4), 2-18. (in Persian).
Naderi Bani, M., Delshad, A., Mohammadi, F., & Adibzadeh, M. (2014). Factors affecting information technology acceptance in Shiraz Hotels. Tourism Management Studies, 10(29), 69-93. (in Persian).
Najmul Islam, A. (2016). E-learning system use and its outcomes: Moderating role of perceived compatibility. Telematics and Informatics, 8, 92-106.
Nakhaie, A., & Kheiri, B. (2012). Investigating selected effects on Internet to purchase green products. Marketing Management, 15, 130-105. (in Persian).
OECD. (2016). PISA 2015 results: Excellence and equity in education (Vol. I). Paris: OECD Publishing.
Ozturk, A. B. (2016). Customer acceptance of cashless payment systems in the hospitality industry. International Journal of Contemporary Hospitality Management, 28(4). In press.
Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning. In Educational Technology & Society, 12(3), 150-162.
Partala, S., & Saari, T. (2015). Understanding the most influential user experiences in successful and unsuccessful technology adoptions. Computers in Human Behavior, 53, 381-395.
Rasouli M., R. (2015). The structural model of the relationship between cultural values and cognitive beliefs with the level of internet use between undergraduate students at Allameh University. Culture and Communication Studies, 15(28), 78-105. (in Persian).
Renny, G. Suryo., & Siringoringo, H. (2013). Perceived usefulness, ease of use, and attitude towards online shopping usefulness towards online airlines ticket purchase. Procedia - Social and Behavioral Sciences, 81, 212-216.
Sadaf, A., Newby, T., & Ertmer, P. (2016). An investigation of the factors that influence preservice teachers' intentions and integration of Web 2.0 tools. Educational Technology Research & Development, 64(1), 37-64. Retrieved From http://dx.doi. org/10.1007/s11423-015-9410-9
Sarlak, M, Golpaygani, Z., & Yamani, M. (2014). Investigating the factors affecting the adoption of e-government by referents to tehran’s judiciary based on the dtpb model (Case Study: Case management system of Shahid Beheshti Complex). Development Management Process, 27(1), 54-27. (in Persian).
Schepers, J., & Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44, 90-103.
Scherer, R., Tondeur, J., Siddiq, F., & Baran, E. (2018). The importance of attitudes toward technology for pre-service teachers' technological, pedagogical, and content knowledge: Comparing structural equation modeling approaches. Computers in Human Behavior, 80, 67-80.
Šebjan, U., & Tominc, P. (2015). Impact of support of teacher and compatibility with needs of study on usefulness of SPSS by students. Computers in Human Behavior, 53, 354-365
Seif, M. H. (2016). Presentation of the causal model of behavioral ethics in the use of information technology in medical students of medical sciences of shiraz. Medical Ethics, 10 (35), 198-177.
Sepehri, M. M., Abdolvand N., & Baradaran, V. (2013). Developing strategic alignment model of business strategies and information technology. Strategic Management Studies, 14, 143-125.
Shah, M. u., Fatimee, S., & Sajjad, M. (2014). Mobile commerce adoption: An empirical analysis of the factors affecting consumer intention to use mobile commerce. Journal of Basic and Applied Scientific Research, 4, 80-88.
Sheikh Shoaee, F. (2007). Technology acceptance model: Application and concepts. Information Management Quarterly, 1(6), 35-46.
Shoham S., & Gonen A. (2008). Intentions of hospital nurses to work with computers. CIN, 26(2), 106-116.
Siddiq, F., Hatlevik, O. E., Olsen, R. V., Throndsen, I., & Scherer, R. (2016). Taking a future perspective by learning from the past e a systematic review of assessment instruments that aim to measure primary and secondary school students' ICT literacy. Educational Research Review, 19, 58e84. Retrieved From https://doi.org/ 10.1016/ j.edurev.2016.05.002
Srite, M., & Karahanna, E. (2006). The role of espoused national cultural values in technology acceptance. MIS Quarterly, 30(3), 679-704.
Teo, T., Milutinovi, C. V., Zhou, M., & Bankovi, C. D. (2016). Traditional vs. innovative uses of computers among mathematics pre-service teachers in Serbia. Interactive Learning Environments, 1e17. Retrieved from https://doi.org/10.1080/ 10494820.2016. 1189943.
Van Laar, E., van Deursen, A. J. A. M., van Dijk, J. A. G. M., & de Haan, J. (2017). The relation between 21st-century skills and digital skills: A systematic literature review. Computers in Human Behavior, 72, 577e588. Retrieved from https://doi.org/10.1016/ j.chb.2017.03.010
Venkatesh, V., & Bala, H. (2008).Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39, 273-315.
Venkatesh, V., Morris, M., Davis, G., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
Walter, N, Ortbach, K., & Niehaves, B. (2015). Designing electronic feedback-Analyzing the effects of social presence on perceived feedback usefulness. Int. J. Human-Computer Studies, 76, 1-11.
Wetzels, M., Odekerken-Schroder, G., Oppen, C. (2009). Using PLS path modelling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Quarterly, 33, (1), 177-195.
Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information & Management, 42(5), 719-729.
Wu, W., & Ke, C. C. (2015). An online shopping behavior model integrating personality traits, perceived risk, and technology acceptance. Social Behavior and Personality, 43(1), 85-98.
Yiu, C. S., Grant, Y. K., & Edgar, D. (2007). Factors affecting the adoption of internet banking in Hong Kong: Implications for the banking sector. International Journal of Information Management, 2, 336-351.
Yu, C-S. (2012). Factors affecting individuals to adopt mobile banking: Empirical evidence from the UTAUT Model. Electronic Commerce Research, 13(2), 104-121.
Yusop, F. D. (2015). A data set of factors that influence preservice teachers' intentions to use web 2.0 technologies in future teaching practices. British Journal of Educational Technology, 46(5), 1075-1080.
Zhao, A. L., Koenig-Lewis, N., Hanmer-Lloyd, S., & Ward, P. (2010). Adoption of internet banking services in China: Is it all about trust. International Journal of Bank Marketing, 28(1), 7-26.
Zint, M. (2002). Comparing three attitude-behavior theories for predicting science teachers’ intentions. Research in Science Teaching, 39(9), 819-844.
Zogheib, B., Rabaa’i, A., Zogheib, S., & Elsaheli, A. (2015). University student perceptions of tech-neology use in mathematics learning. Information Technology Education: Research, 14, 417-438.
