ปัจจัยที่มีอิทธิพลต่อความตั้งใจใช้การบริการบอกตำแหน่ง บนเครือข่ายสังคมออนไลน์ของนักท่องเที่ยว
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มิ.ย. 5, 2018
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การบริการบอกตำแหน่ง ส่วนขยายทฤษฎีรวมการยอมรับการใช้เทคโนโยยีสารสนเทศ แบบจำลองสมการโครงสร้าง
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บทคัดย่อ
การวิจัยครั้งนี้มีวัตถุประสงค์เพื่อพัฒนาแบบจำลองสมการโครงสร้างของปัจจัยที่มีอิทธิพลต่อความตั้งใจใช้การบริการบอกตำแหน่ง (Location Based Service : LBS) บนเครือข่ายสังคมออนไลน์ของนักท่องเที่ยว เป็นการวิจัยเชิงสำรวจ กลุ่มตัวอย่างที่ใช้ในการวิจัย คือนักท่องเที่ยวชาวจีนจำนวน 363 คน โดยใช้แบบสอบถามทัศนคติ สถิติที่ใช้ในการวิเคราะห์ข้อมูลได้แก่ การวิเคราะห์องค์ประกอบเชิงยืนยัน และการวิเคราะห์แบบจำลองสมการโครงสร้าง ด้วยโปรแกรม SPSS AMOS 22.0 ผลการวิจัยพบว่า 1) แบบจำลองสมการโครงสร้างเชิงสมมติฐานที่กำหนดขึ้นมีความสอดคล้องกับข้อมูลเชิงประจักษ์ในระดับดี (2/df=2.265, GFI=0.899, AGFI=0.868, CFI=0.951, NFI=0.916, TLI=0.942, RMSEA=0.059) 2) แรงจูงใจด้านความบันเทิง อิทธิพลทางสังคม ความคาดหวังด้านสมรรถภาพ และมูลค่าตามราคา เป็นปัจจัยที่มีอิทธิพลทางตรงเชิงบวกต่อความตั้งใจใช้ LBS บนเครือข่ายสังคมออนไลน์อย่างมีนัยสำคัญทางสถิติ ในขณะเดียวกันความคาดหวังจากความพยายามและอิทธิพลทางสังคมเป็นปัจจัยที่มีอิทธิพลทางตรงเชิงบวกต่อความคาดหวังด้านสมรรถภาพอย่างมีนัยสำคัญทางสถิติ อีกทั้งยังพบว่าความคาดหวังจากความพยายามมีอิทธิพลทางตรงเชิงบวกต่อแรงจูงใจด้านความบันเทิงอย่างมีนัยสำคัญทางสถิติ
Article Details
รูปแบบการอ้างอิง
วิจิตรคุณากร ศ. (2018). ปัจจัยที่มีอิทธิพลต่อความตั้งใจใช้การบริการบอกตำแหน่ง บนเครือข่ายสังคมออนไลน์ของนักท่องเที่ยว. วารสารวิทยาการจัดการ มหาวิทยาลัยราชภัฏเชียงราย, 10(2), 62–84. สืบค้น จาก https://so03.tci-thaijo.org/index.php/jmscrru/article/view/127196
ประเภทบทความ
บทความวิจัย
ทัศนะและข้อคิดเห็นของบทความที่ปรากฏในวารสารฉบับนี้เป็นของผู้เขียนแต่ละท่าน ไม่ถือว่าเป็นทัศนะและความรับผิดชอบของกองบรรณาธิการ
เอกสารอ้างอิง
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Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models.Journal of the academy of marketing science, 16(1), 74-94.
Bansal, G., & Gefen, D. (2010). The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online. Decision Support Systems, 49(2), 138-150.
Bentler, P. M., & Chou, C. P. (1987). Practical issues in structural modeling.Sociological Methods & Research, 16(1), 78-117.
Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS quarterly, 399-426.
Bruner, G. C., & Kumar, A. (2005). Explaining consumer acceptance of handheld Internet devices. Journal of Business Research, 58(5), 553-558.
Chang, C. W., & Chen, G. M. (2014). College students’ disclosure of location-related information on Facebook. Computers in Human Behavior, 35, 33-38.
Chang, I. C., Hwang, H. G., Hung, W. F., & Li, Y. C. (2007). Physicians’ acceptance of pharmacokinetics-based clinical decision support systems.Expert Systems with Applications, 33(2), 296-303.
Chau, P. Y. (1996). An empirical assessment of a modified technology acceptance model. Journal of management information systems, 185-204.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50.
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Hu, B., & Ester, M. (2013, October). Spatial topic modeling in online social media for location recommendation. In Proceedings of the 7th ACM conference on Recommender systems ACM,25-32.
Humphreys, L., & Liao, T. (2011). Mobile geotagging: Reexamining our interactions with urban space. Journal of Computer‐Mediated Communication,16(3), 407-423.
Hung, C. C., Chang, C. W., & Peng, W. C. (2009, November). Mining trajectory profiles for discovering user communities. In Proceedings of the 2009 International Workshop on Location Based Social Networks ACM,1-8.
Kang, M., Liew, B. Y. T., Lim, H., Jang, J., & Lee, S. (2015). Investigating the Determinants of Mobile Learning Acceptance in Korea Using UTAUT2. In Emerging Issues in Smart Learning. Springer Berlin Heidelberg,209-216.
Kim, K. K., Shin, H. K., & Kim, B. (2011). The role of psychological traits and social factors in using new mobile communication services. Electronic Commerce Research and Applications, 10(4), 408-417.
Li, Y. (2011). Empirical studies on online information privacy concerns: literature review and an integrative framework. Communications of the Association for Information Systems, 28(1), 453-496.
Lindqvist, J., Cranshaw, J., Wiese, J., Hong, J., & Zimmerman, J. (2011). I'm the mayor of my house: examining why people use foursquare-a social-driven location sharing application. In Proceedings of the SIGCHI conference on human factors in computing systems ,2409-2418.
Lowry, P. B., Cao, J., & Everard, A. (2011). Privacy concerns versus desire for interpersonal awareness in driving the use of self-disclosure technologies: The case of instant messaging in two cultures. Journal of Management Information Systems, 27(4), 163-200.
Malhotra, N. K., Kim, S. S., & Agarwal, J. (2004). Internet users' information privacy concerns (IUIPC): The construct, the scale, and a causal model.Information Systems Research, 15(4), 336-355.
Mathieson, K. (1991). Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior.Information Systems Research, 2(3),173-191.
Noulas, A., Scellato, S., Mascolo, C., & Pontil, M. (2011). An Empirical Study of Geographic User Activity Patterns in Foursquare. ICwSM, 11, 70-573.
Riemenschneider, C. K., Hardgrave, B. C., & Davis, F. D. (2002). Explaining software developer acceptance of methodologies: a comparison of five theoretical models. Software Engineering, IEEE Transactions on, 28(12), 1135-1145.
Sadeh, N., Hong, J., Cranor, L., Fette, I., Kelley, P., Prabaker, M., & Rao, J. (2009). Understanding and capturing people's privacy policies in a mobile social networking application. Personal and Ubiquitous Computing, 13(6), 401-412.
Shen, A. X., Cheung, C. M., Lee, M. K., & Chen, H. (2011). How social influence affects we-intention to use instant messaging: The moderating effect of usage experience. Information Systems Frontiers, 13(2), 157-169.
Slade, E., Williams, M., & Dwivdei, Y. (2013). Extending UTAUT2 To Explore Consumer Adoption Of Mobile Payments. In Proceedings of the UK Academy for Information Systems Conference, March.
Smith, H. J., Milberg, S. J., & Burke, S. J. (1996). Information privacy: measuring individuals' concerns about organizational practices. MIS quarterly, 167-196.
Steiniger, S., Neun, M., & Edwardes, A. (2011). Foundations of Location Based Services Lesson 1 CartouCHe 1-Lecture Notes on LBS, V. 1.0.
Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model. Management Science, 42(1), 85-92.
Tsai, J. Y., Kelley, P. G., Cranor, L. F., & Sadeh, N. (2010). Location-sharing technologies: Privacy risks and controls. ISJLP, 6, 119.
Van der Heijden, H. (2004). User acceptance of hedonic information systems.MIS quarterly, 695-704.
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.
Vongjaturapat, S., & Chaveesuk, S. (2013, June). Mobile technology acceptance for library information service: A theoretical model. In Information Society (i-Society), 2013 International Conference IEEE,290-292.
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.
Zheng, Y., Zhang, L., Xie, X., & Ma, W. Y. (2009, April). Mining interesting locations and travel sequences from GPS trajectories. In Proceedings of the 18th international conference on World wide web,791-800.
Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760-767.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
Angst, C. M., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: the elaboration likelihood model and individual persuasion. MIS quarterly, 33(2), 339-370.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models.Journal of the academy of marketing science, 16(1), 74-94.
Bansal, G., & Gefen, D. (2010). The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online. Decision Support Systems, 49(2), 138-150.
Bentler, P. M., & Chou, C. P. (1987). Practical issues in structural modeling.Sociological Methods & Research, 16(1), 78-117.
Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS quarterly, 399-426.
Bruner, G. C., & Kumar, A. (2005). Explaining consumer acceptance of handheld Internet devices. Journal of Business Research, 58(5), 553-558.
Chang, C. W., & Chen, G. M. (2014). College students’ disclosure of location-related information on Facebook. Computers in Human Behavior, 35, 33-38.
Chang, I. C., Hwang, H. G., Hung, W. F., & Li, Y. C. (2007). Physicians’ acceptance of pharmacokinetics-based clinical decision support systems.Expert Systems with Applications, 33(2), 296-303.
Chau, P. Y. (1996). An empirical assessment of a modified technology acceptance model. Journal of management information systems, 185-204.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50.
Gefen, D., & Straub, D. W. (2000). The relative importance of perceived ease of use in IS adoption: a study of e-commerce adoption. Journal of the Association for Information Systems, 1(1), 8.
Gefen, D., Straub, D., & Boudreau, M. C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the association for information systems, 4(1), 7.
Hu, B., & Ester, M. (2013, October). Spatial topic modeling in online social media for location recommendation. In Proceedings of the 7th ACM conference on Recommender systems ACM,25-32.
Humphreys, L., & Liao, T. (2011). Mobile geotagging: Reexamining our interactions with urban space. Journal of Computer‐Mediated Communication,16(3), 407-423.
Hung, C. C., Chang, C. W., & Peng, W. C. (2009, November). Mining trajectory profiles for discovering user communities. In Proceedings of the 2009 International Workshop on Location Based Social Networks ACM,1-8.
Kang, M., Liew, B. Y. T., Lim, H., Jang, J., & Lee, S. (2015). Investigating the Determinants of Mobile Learning Acceptance in Korea Using UTAUT2. In Emerging Issues in Smart Learning. Springer Berlin Heidelberg,209-216.
Kim, K. K., Shin, H. K., & Kim, B. (2011). The role of psychological traits and social factors in using new mobile communication services. Electronic Commerce Research and Applications, 10(4), 408-417.
Li, Y. (2011). Empirical studies on online information privacy concerns: literature review and an integrative framework. Communications of the Association for Information Systems, 28(1), 453-496.
Lindqvist, J., Cranshaw, J., Wiese, J., Hong, J., & Zimmerman, J. (2011). I'm the mayor of my house: examining why people use foursquare-a social-driven location sharing application. In Proceedings of the SIGCHI conference on human factors in computing systems ,2409-2418.
Lowry, P. B., Cao, J., & Everard, A. (2011). Privacy concerns versus desire for interpersonal awareness in driving the use of self-disclosure technologies: The case of instant messaging in two cultures. Journal of Management Information Systems, 27(4), 163-200.
Malhotra, N. K., Kim, S. S., & Agarwal, J. (2004). Internet users' information privacy concerns (IUIPC): The construct, the scale, and a causal model.Information Systems Research, 15(4), 336-355.
Mathieson, K. (1991). Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior.Information Systems Research, 2(3),173-191.
Noulas, A., Scellato, S., Mascolo, C., & Pontil, M. (2011). An Empirical Study of Geographic User Activity Patterns in Foursquare. ICwSM, 11, 70-573.
Riemenschneider, C. K., Hardgrave, B. C., & Davis, F. D. (2002). Explaining software developer acceptance of methodologies: a comparison of five theoretical models. Software Engineering, IEEE Transactions on, 28(12), 1135-1145.
Sadeh, N., Hong, J., Cranor, L., Fette, I., Kelley, P., Prabaker, M., & Rao, J. (2009). Understanding and capturing people's privacy policies in a mobile social networking application. Personal and Ubiquitous Computing, 13(6), 401-412.
Shen, A. X., Cheung, C. M., Lee, M. K., & Chen, H. (2011). How social influence affects we-intention to use instant messaging: The moderating effect of usage experience. Information Systems Frontiers, 13(2), 157-169.
Slade, E., Williams, M., & Dwivdei, Y. (2013). Extending UTAUT2 To Explore Consumer Adoption Of Mobile Payments. In Proceedings of the UK Academy for Information Systems Conference, March.
Smith, H. J., Milberg, S. J., & Burke, S. J. (1996). Information privacy: measuring individuals' concerns about organizational practices. MIS quarterly, 167-196.
Steiniger, S., Neun, M., & Edwardes, A. (2011). Foundations of Location Based Services Lesson 1 CartouCHe 1-Lecture Notes on LBS, V. 1.0.
Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model. Management Science, 42(1), 85-92.
Tsai, J. Y., Kelley, P. G., Cranor, L. F., & Sadeh, N. (2010). Location-sharing technologies: Privacy risks and controls. ISJLP, 6, 119.
Van der Heijden, H. (2004). User acceptance of hedonic information systems.MIS quarterly, 695-704.
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.
Vongjaturapat, S., & Chaveesuk, S. (2013, June). Mobile technology acceptance for library information service: A theoretical model. In Information Society (i-Society), 2013 International Conference IEEE,290-292.
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.
Zheng, Y., Zhang, L., Xie, X., & Ma, W. Y. (2009, April). Mining interesting locations and travel sequences from GPS trajectories. In Proceedings of the 18th international conference on World wide web,791-800.
Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760-767.
