由於科技進步與資訊爆炸，人類對科技產品之仰賴日深，也造就了科技產品的快速進步。在過去十年裡，各式各樣新穎的科技產品已經使人類的工作、生活型態發生了變化，例如行動通訊，早期的行動電話，主要是以行動通訊為主，讓使用者可以不用待在固定的地點，也可以撥打或接收電話，然而現今的行動電話，除了可以撥打電話外，更支援無線上網、攝影、拍照及遊戲功能，使用者僅需要一支行動電話，便可完成以往需要多樣設備才能達到的功能。加上體積小、方便攜帶的便利性，讓行動電話已經成為人們日常生活上重要的工具之一，也進而改變了人們的生活方式。加上行動通訊技術的進步，帶動上網速度變快，使得人們都透過行動裝置來連結世界，但卻削減了人與人之間的直接交流，導致在網路上可以暢所欲言，實際見面卻不知如何開口的窘境，進而影響人際關係。因此，了解技術變遷與行為影響是非常重要的。雖然已有不少文獻針對技術變遷與行為影響進行研究，但多是獨自論述技術變遷或行為影響，少以同時探討兩者之影響關係；為了要同時探討兩者的互相影響，本研究採用第2代整合型科技接受理論 (Unified Theory of Acceptance and Use of Technology 2, UTAUT2)為基礎，預測科技使用之行為；本研究首先利用決策實驗室分析法(Decision Making Trial and Evaluation Laboratory, DEMATEL)與、決策實驗室網路流程法(DEMATEL-based Network Process, DNP) 先行分析各構面和準則之間的關係，後以結構方程模式(Structural Equation Modeling, SEM)檢定前述DEMATEL推導之影響關係之假設顯著。最後，本研究以VR行動通訊技術對使用者技術之行為影響，實證分析架構之可行性，研究結果可作為學者專家定義解決行動通訊技術變遷造成負面衝擊策略之基礎。

By technology progressing and information explosion, more and more people rely on the technology products. In the past decade, many kinds of novel technologies have changed our life. For example, the mobile device is an epoch-making innovation. It makes people are able to communicate with someone without the restriction of locations. Nowadays, people can surf the net, take a picture, or play video games with a mobile device. The mobile device has become indispensable because easy to carry and exquisite. It has changed people’s life. In addition, the throughput of mobile network becomes higher and higher due to technology progressing. It makes people able to connect with world just use a mobile device. The technology brings us the convenience but reduces the chances of talking to each other, and then causes someone may be articulate on the net but embarrassed when talk face to face to affect the relationship. Therefore, it’s important to understand the relationship between technology transition and human behavior. There are many studies related technology transition and human behavior, but most of them focus on one topic, not both the mentioned topics. In order to study the interaction of technology transition and human behavior, the study is using Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) to examine behavioral intentions. And the relationships between each dimension will be analyzed by Decision Making Trial and Evaluation Laboratory (DEMATEL) and DEMATEL-based Network Process (DNP) in advance, and then Structural Equation Modeling (SEM) will test the hypothesis. At last, the study examines the feasibility of the structure in human behavior change with VR mobile communication technology. The result can be the foundation of the strategy making to overcome negative impact by mobile communication technology transition.

Aarts, H., Verplanken, B., & Knippenberg, A. (1998). Predicting behavior from actions in the past: Repeated decision making or a matter of habit? Journal of Applied Social Psychology, 28(15), 1355-1374.
Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.
Ajzen, I. (2012). Martin Fishbein’s legacy the reasoned action approach. The Annals of the American Academy of Political and Social Science, 640(1), 11-27.
Akaike, H. (1987). Factor analysis and AIC. Psychometrika, 52(3), 317-332.
Al-Gahtani, S. S., Hubona, G. S., & Wang, J. (2007). Information technology (IT) in Saudi Arabia: Culture and the acceptance and use of IT. Information & Management, 44(8), 681-691.
Amabile, T. M. (1997). Motivating creativity in organizations: On doing what you love and loving what you do. California management review, 40(1), 39-58.
Bagozzi, R. P., Davis, F. D., & Warshaw, P. R. (1992). Development and test of a theory of technological learning and usage. Human relations, 45(7), 659-686.
Bagozzi, R. P., & Yi, Y. (2012). Specification, evaluation, and interpretation of structural equation models. Journal of the academy of marketing science, 40(1), 8-34.
Bandura, A. (1982). Self-efficacy mechanism in human agency. American psychologist, 37(2), 122.
Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration. Technology studies, 2(2), 285-309.
Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological bulletin, 88(3), 588.
Boksberger, P. E., & Melsen, L. (2011). Perceived value: a critical examination of definitions, concepts and measures for the service industry. Journal of Services Marketing, 25(3), 229-240.
Boyle, R. P. (1970). Path analysis and ordinal data. American Journal of Sociology, 461-480.
Brooks, V. B. (1979). Control of intended limb movements by the lateral and intermediate cerebellum. Integration in the nervous system. Igaku-shoin, Tokyo New York, 321-356.
Burdea, G. C., & Coiffet, P. (2003). Virtual Reality Technology (Vol. 1): John Wiley & Sons.
Burke, R. R. (2002). Technology and the customer interface: what consumers want in the physical and virtual store. Journal of the academy of marketing science, 30(4), 411-432.
Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming: Routledge.
Casey, T., & Wilson-Evered, E. (2012). Predicting uptake of technology innovations in online family dispute resolution services: An application and extension of the UTAUT. Computers in Human Behavior, 28(6), 2034-2045.
Castells, M. (2011). The rise of the network society: The information age: Economy, society, and culture (Vol. 1): John Wiley & Sons.
Chang, E.-C., & Tseng, Y.-F. (2013). Research note: E-store image, perceived value and perceived risk. Journal of Business Research, 66(7), 864-870.
Chang, Y.-W., & Polonsky, M. J. (2012). The influence of multiple types of service convenience on behavioral intentions: The mediating role of consumer satisfaction in a Taiwanese leisure setting. International journal of hospitality management, 31(1), 107-118.
Chao, S.-C., Chang, C.-W., Yen, L.-F., Huang, H.-L., & Lu, Y.-T. (2012). The Influence of Excessive Use of Mobile Phone on College Students.
Chen, M. L. (2015). Development Trends and Business Opportunities for Next Generation on Mobile Communication Network. Industrial Technology Research Institute: IEK.
Chen, Y.-J. (2016). VR-Lab: Room-scale Immersive VR-Learning System with Customized DRM based on Unity3D. Taiwan: National Central University.
Chin, W. W. (2003). Issues and opinions on structural equation modeling.
Chong, A. Y.-L. (2013). Mobile commerce usage activities: The roles of demographic and motivation variables. Technological Forecasting and Social Change, 80(7), 1350-1359.
Chung, M. H. (2015). Prospects and Trends of Global Communication Industry in 2016. Industrial Technology Research Institute: IEK.
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied multiple regression/correlation analysis for the behavioral sciences: Routledge.
Costello, P. J. (1997). Health and safety issues associated with virtual reality: a review of current literature: Citeseer.
Csikszentmihalyi, M. (1992). A reponse to the Kimiecik & Stein and Jackson papers. Journal of Applied Sport Psychology, 4(2), 181-183.
Dalkey, N., & Helmer, O. (1963). An experimental application of the Delphi method to the use of experts. Management science, 9(3), 458-467.
Dalkey, N. C. (1972). Studies in the Quality of life; Delphi and decision-making.
Damnjanovic, A., Montojo, J., Wei, Y., Ji, T., Luo, T., Vajapeyam, M., . . . Malladi, D. (2011). A survey on 3GPP heterogeneous networks. IEEE Wireless Communications, 18(3), 10-21.
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Massachusetts Institute of Technology.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
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.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace1. Journal of applied social psychology, 22(14), 1111-1132.
Deaton, J. D., Irwin, R. E., & DaSilva, L. A. (2014). Dynamic spectrum access in LTE-advanced networks. Physical Communication, 10, 127-143.
Deschryvere, M. (2010). Conceptualising Mobility.
Dickel, N., & Bohner, G. (2012). Minority and majority influence on attitudes: INTECH Open Access Publisher.
Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers' product evaluations. Journal of marketing research, 307-319.
Escobar-Rodríguez, T., & Carvajal-Trujillo, E. (2013). Online drivers of consumer purchase of website airline tickets. Journal of Air Transport Management, 32, 58-64.
F. Hair Jr, J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. European Business Review, 26(2), 106-121.
Fishbein, M., & Ajzen, I. (1975). Belief. Attitude, Intention and Behavior: An Introduction to Theory and Research Reading, MA: Addison-Wesley, 6.
Fishbein, M., & Ajzen, I. (2011). Predicting and changing behavior: The reasoned action approach: Taylor & Francis.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50.
Gabus, A., & Fontela, E. (1972). World problems, an invitation to further thought within the framework of DEMATEL. Battelle Geneva Research Center, Geneva, Switzerland.
Gharbi, J.-E. (2008). Determinants and consequences of the website perceived value. Journal of Internet Banking and Commerce, 13(1).
Giovanis, A. N., Tomaras, P., & Zondiros, D. (2013). Suppliers logistics service quality performance and its effect on retailers’ behavioral intentions. Procedia-Social and Behavioral Sciences, 73, 302-309.
Govindan, K., Kannan, D., & Shankar, K. M. (2014). Evaluating the drivers of corporate social responsibility in the mining industry with multi-criteria approach: A multi-stakeholder perspective. Journal of Cleaner Production, 84, 214-232.
Green, K. C., Armstrong, J. S., & Graefe, A. (2007). Methods to elicit forecasts from groups: Delphi and prediction markets compared.
Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM): Sage Publications.
Hennigs, N., Wiedmann, K.-P., & Klarmann, C. (2013). Consumer value perception of luxury goods: a cross-cultural and cross-industry comparison Luxury Marketing (pp. 77-99): Springer.
Hong, F.-Y., Chiu, S.-I., & Huang, D.-H. (2012). A model of the relationship between psychological characteristics, mobile phone addiction and use of mobile phones by Taiwanese university female students. Computers in Human Behavior, 28(6), 2152-2159.
Hou, A. (2015). Wearable Device Trends Series : The latest development of VR. Industrial Technology Research Institute: IEK.
Houston, S., & Bolding Jr, J. (1974). Part, partial, and multiple correlation in commonality analysis of multiple regression models. Multiple Linear Regression Viewpoints, 5, 36-40.
Hsieh, K. (2016). Development Trend of Mobile VR Application. Industrial Technology Research Institute: IEK.
Hsu, C.-L., & Lu, H.-P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & management, 41(7), 853-868.
Hu, P. J., Chau, P. Y., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of management information systems, 16(2), 91-112.
Huang, C.-Y., Lin, Y.-F., & Tzeng, G.-H. (2011). A DEMATEL based network process for deriving factors influencing the acceptance of tablet personal computers Intelligent Decision Technologies (pp. 355-365): Springer.
Huang, C.-Y., Shyu, J. Z., & Tzeng, G.-H. (2007). Reconfiguring the innovation policy portfolios for Taiwan's SIP Mall industry. Technovation, 27(12), 744-765.
Huang, C.-Y., Tzeng, G.-H., & Ho, W.-R. J. (2011). System on chip design service e-business value maximization through a novel MCDM framework. Expert Systems with Applications, 38(7), 7947-7962.
Huang, C. Y., & Shyu, J. Z. (2006). Developing e-commerce business models for enabling silicon intellectual property transactions. International journal of information technology and management, 5(2), 114-133.
Huang, C. Y., Shyu, J. Z., & Tzeng, G. H. (2007). Reconfiguring the innovation policy portfolios for Taiwan's SIP Mall industry. Technovation, 27(12), 744-765.
Huang, C. Y., Tzeng, G. H., & Ho, W. R. J. (2011). System on chip design service e-business value maximization through a novel MCDM framework. Expert Systems with Applications, 38(7), 7947-7962.
Hung, H.-L., Altschuld, J. W., & Lee, Y.-F. (2008). Methodological and conceptual issues confronting a cross-country Delphi study of educational program evaluation. Evaluation and Program Planning, 31(2), 191-198.
Hung, S.-Y., Ku, Y.-C., & Chien, J.-C. (2012). Understanding physicians’ acceptance of the Medline system for practicing evidence-based medicine: A decomposed TPB model. International journal of medical informatics, 81(2), 130-142.
Jöreskog, K. G., & Sörbom, D. (1996). LISREL 8: User's reference guide: Scientific Software International.
Jeng, D. J.-F., & Tzeng, G.-H. (2012). Social influence on the use of clinical decision support systems: revisiting the unified theory of acceptance and use of technology by the fuzzy DEMATEL technique. Computers & Industrial Engineering, 62(3), 819-828.
Jia, P., Govindan, K., & Kannan, D. (2015). Identification and evaluation of influential criteria for the selection of an environmental shipping carrier using DEMATEL: a case from India. International Journal of Shipping and Transport Logistics, 7(6), 719-741.
Jones, J., & Hunter, D. (1995). Consensus methods for medical and health services research. BMJ: British Medical Journal, 311(7001), 376.
Jones, T. O., & Sasser, W. E. (1995). Jnr,“Why Satisfied Customers Defect”. Harvard Business Review, 73.
Judd, R. C. (1972). Forecasting to Consensus Gathering, Delphi Grows Up to College Needs. College and University Business.
Jun-Po, Y., & Hsiu-Hua, C. (2008). The Application of Critical Theory in Information Management
Kashdan, T. B., DeWall, C. N., Pond, R. S., Silvia, P. J., Lambert, N. M., Fincham, F. D., . . . Keller, P. S. (2013). Curiosity protects against interpersonal aggression: Cross‐sectional, daily process, and behavioral evidence. Journal of Personality, 81(1), 87-102.
Keller, H. H., McCullough, J., Davidson, B., Vesnaver, E., Laporte, M., Gramlich, L., . . . Jeejeebhoy, K. (2015). The Integrated Nutrition Pathway for Acute Care (INPAC): Building consensus with a modified Delphi. Nutrition journal, 14(1), 1.
Keller, K. L., Parameswaran, M., & Jacob, I. (2011). Strategic brand management: Building, measuring, and managing brand equity: Pearson Education India.
Kijsanayotin, B., Pannarunothai, S., & Speedie, S. M. (2009). Factors influencing health information technology adoption in Thailand's community health centers: Applying the UTAUT model. International journal of medical informatics, 78(6), 404-416.
Kim, H.-W., Chan, H. C., & Gupta, S. (2007). Value-based adoption of mobile internet: an empirical investigation. Decision Support Systems, 43(1), 111-126.
Kim, J.-O., & Mueller, C. W. (1978). Factor analysis: Statistical methods and practical issues (Vol. 14): Sage.
Kim, S., & Garrison, G. (2009). Investigating mobile wireless technology adoption: An extension of the technology acceptance model. Information Systems Frontiers, 11(3), 323-333.
Kim, S. S., & Malhotra, N. K. (2005). A longitudinal model of continued IS use: An integrative view of four mechanisms underlying postadoption phenomena. Management science, 51(5), 741-755.
Kohlenberger, J. (2015). Accelerating Next Generation Wireless Opportunities Everywhere. Washington, D.C.: Mobile Future.
Kotler, P., & Keller, K. L. (2013). Framework for Marketing Management: Global Edition: Pearson Higher Ed.
Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information systems research, 13(2), 205-223.
Kuo, Y.-F., Wu, C.-M., & Deng, W.-J. (2009). The relationships among service quality, perceived value, customer satisfaction, and post-purchase intention in mobile value-added services. Computers in Human Behavior, 25(4), 887-896.
Lee, C.-C., Lin, S.-P., Yang, S.-L., Tsou, M.-Y., & Chang, K.-Y. (2013). Evaluating the influence of perceived organizational learning capability on user acceptance of information technology among operating room nurse staff. Acta Anaesthesiologica Taiwanica, 51(1), 22-27.
Lee, D. Y., & Lehto, M. R. (2013). User acceptance of YouTube for procedural learning: An extension of the Technology Acceptance Model. Computers & Education, 61, 193-208.
Lee, Y., Kozar, K. A., & Larsen, K. R. (2003). The technology acceptance model: Past, present, and future. Communications of the Association for information systems, 12(1), 50.
Liao, S., Wu, M.-J., Huang, C.-Y., Kao, Y.-S., & Lee, T.-H. (2014). Evaluating and enhancing three-dimensional printing service providers for rapid prototyping using the DEMATEL based network process and VIKOR. Mathematical Problems in Engineering, 2014.
Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS quarterly, 705-737.
Linstone, H. A., & Turoff, M. (1975). The Delphi method: Techniques and applications (Vol. 29): Addison-Wesley Reading, MA.
Liu, C. H., Tzeng, G. H., & Lee, M. H. (2012). Improving tourism policy implementation–The use of hybrid MCDM models. Tourism Management, 33(2), 413-426.
Liu, Y.-H. (2016). The Past, Present and Future of VR Market: From Virtual to Reality. Industrial Technology Research Institute: IEK.
Long, J. S. (1983). Confirmatory factor analysis: A preface to LISREL (Vol. 33): Sage Publications.
Lu, A. (2016). Global Top 6 Smartphone Trends for 2016. Industrial Technology Research Institute: IEK.
Lu, Y., Zhou, T., & Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25(1), 29-39.
Luthra, S., Govindan, K., Kharb, R. K., & Mangla, S. K. (2016). Evaluating the enablers in solar power developments in the current scenario using fuzzy DEMATEL: An Indian perspective. Renewable and Sustainable Energy Reviews, 63, 379-397.
Lyons, M. (1971). Techniques for using ordinal measures in regression and path analysis. Sociological methodology, 3, 147-171.
MacCallum, R. C., & Austin, J. T. (2000). Applications of structural equation modeling in psychological research. Annual review of psychology, 51(1), 201-226.
Magni, M., Taylor, M. S., & Venkatesh, V. (2010). ‘To play or not to play’: A cross-temporal investigation using hedonic and instrumental perspectives to explain user intentions to explore a technology. International journal of human-computer studies, 68(9), 572-588.
Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1-13.
Mathieson, K. (1991). Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. Information systems research, 2(3), 173-191.
Miltgen, C. L., Popovič, A., & Oliveira, T. (2013). Determinants of end-user acceptance of biometrics: Integrating the “Big 3” of technology acceptance with privacy context. Decision Support Systems, 56, 103-114.
Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information systems research, 2(3), 192-222.
Murry, J. W., & Hammons, J. O. (1995). Delphi: A versatile methodology for conducting qualitative research. The Review of Higher Education, 18(4), 423.
Norman, D. A. (2013). The design of everyday things: Revised and expanded edition: Basic books.
Nunnally, J. (1978). Psychometric methods: New York: McGraw-Hill.
O'Rourke, N., & Hatcher, L. (2013). A step-by-step approach to using SAS for factor analysis and structural equation modeling: Sas Institute.
Olson, J. M., & Zanna, M. P. (1993). Attitudes and attitude change. Annual review of psychology, 44(1), 117-154.
Ott, R. L., & Longnecker, M. T. (2015). An introduction to statistical methods and data analysis: Nelson Education.
Pai, F.-Y., & Huang, K.-I. (2011). Applying the technology acceptance model to the introduction of healthcare information systems. Technological Forecasting and Social Change, 78(4), 650-660.
Pedhazur, E. J. (1982). Multiple regression in behavioral research: Explanation and prediction . Fort Worth, TX: Holt, Rinehart and Winston. Pedhazur2Multiple Regression in Behavioral Research: Explanation and Prediction1982.
Petrick, J. F. (2002). Development of a multi-dimensional scale for measuring the perceived value of a service. Journal of leisure research, 34(2), 119.
Phillips-Wren, G. (2010). Advances in Intelligent Decision Technologies: Proceedings of the Second KES International Symposium IDT 2010 (Vol. 4): Springer.
Pilke, E. M. (2004). Flow experiences in information technology use. International journal of human-computer studies, 61(3), 347-357.
Pu, J., & Chou, S. (2016). Virtual Reality Comes True. Industrial Technology Research Institute: IEK.
Rivera, J., & van der Meulen, R. (2013). Gartner says the internet of things installed base will grow to 26 billion units by 2020. Stamford, conn., December, 12.
Rogers, E. M. (2010). Diffusion of innovations: Simon and Schuster.
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American psychologist, 55(1), 68.
Saaty, T. L. (1990). Multicriteria Decision Making: The Analytic Hierarchy Process: Planning, Priority Setting. Resource Allocation, 2.
Schumacker, R., & Lomax, R. (1996). A Beginner's Guide to Structural Equation Modeling (Lawrence Erl baum Associates, Mahwah, New Jersey).
Sellin, N. (1995). Partial least square modeling in research on educational achievement. Reflections on educational achievement, 256-267.
Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of consumer research, 15(3), 325-343.
Shiau, W.-L., & Luo, M. M. (2012). Factors affecting online group buying intention and satisfaction: A social exchange theory perspective. Computers in Human Behavior, 28(6), 2431-2444.
Shieh, C. (2017). Global Virtual Reality Market Trend, Taiwan Challenges and its Opportunities. Industrial Technology Research Institute: IEK.
Shin, D.-H. (2009). Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior, 25(6), 1343-1354.
Snape, D., Kirkham, J., Preston, J., Popay, J., Britten, N., Collins, M., . . . Wyatt, K. (2014). Exploring areas of consensus and conflict around values underpinning public involvement in health and social care research: a modified Delphi study. BMJ open, 4(1), e004217.
Specht, D. A. (1975). On the evaluation of causal models. Social Science Research, 4(2), 113-133.
Stone, D. L., Deadrick, D. L., Lukaszewski, K. M., & Johnson, R. (2015). The influence of technology on the future of human resource management. Human Resource Management Review, 25(2), 216-231.
Suhr, D. D. (2006). Exploratory or confirmatory factor analysis? : SAS Institute Cary.
Sung, W. (2001). Application of Delphi method, a qualitative and quantitative analysis, to the healthcare management. Journal of Healthcare Management, 2(2), 11-19.
Swait, J., & Sweeney, J. C. (2000). Perceived value and its impact on choice behavior in a retail setting. Journal of Retailing and Consumer Services, 7(2), 77-88.
Tamura, M., Nagata, H., & Akazawa, K. (2002). Extraction and systems analysis of factors that prevent safety and security by structural models.
Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information systems research, 6(2), 144-176.
Teo, T. S., Lim, V. K., & Lai, R. Y. (1999). Intrinsic and extrinsic motivation in Internet usage. Omega, 27(1), 25-37.
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: toward a conceptual model of utilization. MIS quarterly, 125-143.
Triandis, H. C. (1979). Values, attitudes, and interpersonal behavior. Paper presented at the Nebraska symposium on motivation.
Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1-10.
Tzeng, G. H., & Huang, C. Y. (2012). Combined DEMATEL technique with hybrid MCDM methods for creating the aspired intelligent global manufacturing & logistics systems. Annals of Operations Research, 1-32.
Valaei, N., & Baroto, M. B. (2017). Modelling continuance intention of citizens in government Facebook page: A complementary PLS approach. Computers in Human Behavior, 73, 224-237.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision sciences, 39(2), 273-315.
Venkatesh, V., Bala, H., & Sykes, T. A. (2010). Impacts of Information and Communication Technology Implementations on Employees' Jobs in Service Organizations in India: A Multi‐Method Longitudinal Field Study. Production and Operations Management, 19(5), 591-613.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 36(1), 157-178.
Venkatesh, V., Zhang, X., & Sykes, T. A. (2011). “Doctors do too little technology”: A longitudinal field study of an electronic healthcare system implementation. Information systems research, 22(3), 523-546.
Walton, J. M. (1982). The effects of an artificial reef on resident flatfish populations. Marine Fisheries Review, 44(6), 45-48.
Wang, H.-Y., & Wang, S.-H. (2010). Predicting mobile hotel reservation adoption: Insight from a perceived value standpoint. International journal of hospitality management, 29(4), 598-608.
Webb, T. L., Sheeran, P., & Luszczynska, A. (2009). Planning to break unwanted habits: Habit strength moderates implementation intention effects on behaviour change. British Journal of Social Psychology, 48(3), 507-523.
Wei, P.-L., Huang, J.-H., Tzeng, G.-H., & Wu, S.-I. (2010). Causal modeling of web-advertising effects by improving SEM based on DEMATEL technique. International Journal of Information Technology & Decision Making, 9(05), 799-829.
Wei, R. (2008). Motivations for using the mobile phone for mass communications and entertainment. Telematics and Informatics, 25(1), 36-46.
Wolfe, L. M. (1977). An Introduction to Path Analysis. Multiple Linear Regression Viewpoints, 8(1), 36-61.
Wright, S. (1921). Correlation and causation. Journal of agricultural research, 20(7), 557-585.
Wright, S. (1934). The method of path coefficients. The annals of mathematical statistics, 5(3), 161-215.
Wright, S. (1960). Path coefficients and path regressions: alternative or complementary concepts? Biometrics, 16(2), 189-202.
Xu, X. (2014). Understanding users’ continued use of online games: An application of UTAUT2 in social network games. MMEDIA 2014.
Yang, Y.-P. O., Shieh, H.-M., Leu, J.-D., & Tzeng, G.-H. (2008). A novel hybrid MCDM model combined with DEMATEL and ANP with applications. International journal of operations research, 5(3), 160-168.
Yu, D., & Hang, C. C. (2010). A reflective review of disruptive innovation theory. International Journal of Management Reviews, 12(4), 435-452.
Yu, T.-K., Lu, L.-C., & Liu, T.-F. (2010). Exploring factors that influence knowledge sharing behavior via weblogs. Computers in Human Behavior, 26(1), 32-41.
Yuan, T.-H. (2014). The Negative Impacts of Over-Reliance on Mobile Phones. Industrial Technology Research Institute: IEK.
Zander, J., & Mähönen, P. (2013). Riding the data tsunami in the cloud: myths and challenges in future wireless access. IEEE Communications Magazine, 51(3), 145-151.
Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. The Journal of marketing, 2-22.
Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. the Journal of Marketing, 31-46.
Zhang, G. Q. (2012). Lecture notes in computer science.
Zhao, L., Lu, Y., Zhang, L., & Chau, P. Y. (2012). Assessing the effects of service quality and justice on customer satisfaction and the continuance intention of mobile value-added services: An empirical test of a multidimensional model. Decision Support Systems, 52(3), 645-656.
Zhou, T., & Lu, Y. (2011). Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience. Computers in Human Behavior, 27(2), 883-889.