อิทธิพลส่งผ่านของการรับรู้ของบุคลากรในธุรกิจขนาดเล็กต่อแนวโน้มของ ความตั้งใจที่จะใช้เทคโนโลยีคลาวด์คอมพิวติ้งบนโมเดลสมการโครงสร้างเชิงเส้น
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ธ.ค. 26, 2019
คำสำคัญ:
ความตั้งใจที่จะใช้เทคโนโลยี คลาวด์คอมพิวติ้ง ธุรกิจขนาดเล็ก โมเดลสมการโครงสร้างเชิงเส้น อิทธิพลส่งผ่าน
Main Article Content
บทคัดย่อ
บทคัดย่อ
สิ่งสำคัญที่ส่งผลต่อความสำเร็จในการนำเทคโนโลยีใหม่มาใช้งานในองค์กรขนาดเล็ก คือ การยอมรับการใช้เทคโนโลยีของผู้ใช้งานภายในองค์กร งานวิจัยนี้จึงมุ่งศึกษาถึงความสัมพันธ์ของปัจจัยที่เกี่ยวข้องกับการยอมรับเทคโนโลยีคลาวด์คอมพิวติ้งที่ได้มาจากทฤษฎีการยอมรับนวัตกรรมและเทคโนโลยี (TAM) และทฤษฎีการแพร่กระจายนวัตกรรม (DoI) โดยเครื่องมือในการเก็บรวบรวมข้อมูล คือ แบบสอบถาม ซึ่งได้รับกลับคืนมา 447 ชุด ผลการทดสอบโดยใช้เทคนิคโมเดลสมการโครงสร้างเชิงเส้น (SEM) พบว่า ความง่ายในการใช้งานที่รับรู้ได้ส่งผลต่อแนวโน้มความตั้งใจที่จะใช้เทคโนโลยีคลาวด์คอมพิวติ้งของผู้ตอบแบบสอบถามสูงสุด สำหรับปัจจัยจากทฤษฎี DoI นั้น ความซับซ้อนในการใช้งานส่งอิทธิพล
เชิงลบต่อข้อได้เปรียบเชิงเปรียบเทียบ และยังส่งผ่านอิทธิพลเชิงลบผ่านข้อได้เปรียบเชิงเปรียบเทียบไปยังความตั้งใจที่จะใช้เทคโนโลยีคลาวด์คอมพิวติ้ง เช่นเดียวกับความสัมพันธ์ของความง่ายในการใช้งานที่รับรู้ได้และประโยชน์ที่รับรู้ได้จากทฤษฎี TAM อย่างไรก็ตาม เมื่อพิจารณาค่าอิทธิพลรวมของปัจจัยทั้งสองคู่นี้ ได้แก่ ความง่ายในการใช้งานที่รับรู้ได้กับความซับซ้อน
ในการใช้งาน และประโยชน์ที่รับรู้ได้กับข้อได้เปรียบเชิงเปรียบเทียบ จะเห็นว่ายังคงมีความแตกต่างกันบ้าง จึงยังไม่สามารถใช้แทนกันได้อย่างสมบูรณ์
คำสำคัญ: 1) ความตั้งใจที่จะใช้เทคโนโลยี 2) คลาวด์คอมพิวติ้ง 3) ธุรกิจขนาดเล็ก
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บทความวิจัย (Research article)
References
บรรณานุกรม (Bibliography)
Alkhater, N., Wills, G. and Walters, R. (speaker). (December 15-18, 2014). Factors influencing an organisation's intention to adopt cloud computing in Saudi Arabia. In IEEE 6th International Conference on Cloud Computing Technology and Science. (pp. 1040-1044). Singapore: IEEE Computer Society.
Alshamaila, Y., Papagiannidis, S. and Li, F. (2013). Cloud computing adoption by smes in the northeast of England: A multi-perspective framework. Journal of Enterprise Information Management, 26(3), 250-275.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.
Davis, F. D., Bangozzi, R. P., and Warshaw, P. R. (1989). User acceptance of computer technology:
A comparison of two theoretical models. Management Science, 35(8), 982-1003.
Davis, F. (1987). User acceptance of information systems: The technology acceptance model (TAM). Michigan: School of Business Administration, University of Michigan.
Gupta, P., Seetharaman, A. and Raj, J. R. (2013). The usage and adoption of cloud computing by small and medium businesses. International Journal of Information Management, 33(5), 861-874.
Hair, J., Blak, W. C., Barbin, B. J., Anderson, R. E. and Tatham, R. L. (2010). Multivariate data analysis (7th ed.). New Jersey: Prentice Hall.
Han, H. S., Lee, J. N., and Seo, Y. W. (2008). Analyzing the impact of a firm's capability on outsourcing success: A process perspective. Information and Management, 45(1), 31-42.
Hashim, H. S., Hassan Z. B. and Hashim A. S. (2015). Factors influence the adoption of cloud computing: A comprehensive review. International Journal of Education and Research, 3(7), 295-306.
Information Systems Audit and Control Association (ISACA). (2009). The risk IT framework escerpt. Retrieved October 23, 2017, from http://www.isaca.org
Keesookpun, C. and Mitomo, H. (speaker). (November 18-21, 2012). Cloud computing adoption and determining factors in different industries: A case study of Thailand. In 19th ITS Biennial Conference 2012 Moving Forward with Future Technologies: Opening a Platform for All. (pp. 125-132). Bangkok: International Telecommunications Society.
Lederer, A. L., Maupin, D. J., Sena, M. P. and Zhuang, Y. (2000). The technology acceptance model and the World Wide Web. Decision Support Systems, 29(3), 269-282.
Lee, Y. H., Hsieh, Y. C. and Hsu, C. N. (2011). Adding innovation diffusion theory to the technology acceptance model: Supporting employees’ intentions to use E-learning systems. Educational Technology and Society, 14(4), 124-137.
Lian, J. W., Yen, D. C. and Wang, Y. T. (2014). An exploratory study to understand the critical factors affecting the decision to adopt cloud computing in Taiwan hospital. International Journal of Information Management, 34(1), 28-36.
Lin, A. and Chen, N. C. (2012). Cloud computing as an innovation: Perception, attitude and adoption. International Journal of Information Management, 32, 533-540.
Lin, C., Shih, H. and Sher P. J. (2007). Integrating technology readiness into technology acceptance: The TRAM model. Psychology and Marketing, 24(7), 641-657.
Low, C., Chen, Y. and Wu, M. (2011). Understanding the determinants of cloud computing adoption. Industrial Management and Data Systems, 111(7), 1006-1023.
Moore, G. C. and Benbasat, I. (1991). Development of an instrument to measure the perception of adopting an information technology innovation. Information Systems Research, 2(3), 192-222.
Morgan, L. and Conboy, K. (speaker). (June 5-8, 2013). Factors affecting the adoption of cloud computing: An exploratory study. In Proceedings of the 21st European Conference on Information Systems. (pp. 125-134). Barcelona: Utrecht University.
National Statistical Office. (2016). A 2016 survey of the use of information and communication technology in workplaces. Retrieved November 12, 2017 from http://service.nso.go.th/nso/nso_center/project/search/result_by_department-th.jsp
Oliveira, T., Thomas, M. A. and Espadanal, M. (2014). Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Information and Management, 51(5), 497-510.
Opitz, N., Langkau, T. F., Schmidt, N. H. and Kolbe, L. M. (speaker). (January 4-7, 2012). Technology acceptance of cloud computing: Empirical evidence from German IT departments. In 45th Hawaii International Conference on System Sciences. (pp. 1593-1602). Hawaii: IEEE Computer Society.
Pandya, R. E. (2012). A framework for engaging diverse communities in citizen science in the US. Frontiers in Ecology and the Environment, 10(6), 314-317.
Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university Students behavioral intention to use e-Learning. Educational Technology and Society, 12(3), 150-162.
Park, E. and Kim K. J. (2014). An integrated adoption model of mobile cloud services: Exploration of key determinants and extension of technology acceptance model. Telematics and Informatics, 31(3), 376-385.
Pavlou, P. A. and Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly, 30(1), 115-143.
Rogers, E. M. (1995). Diffusion of innovations. New York: Free Press.
Sabi, H. M., Uzoka, F. M. E., Langmia, K. and Njeh, F. N. (2016). Conceptualizing a model for adoption of cloud computing in education. International Journal of Information Management, 36(2), 183-191.
Saini, S. L., Saini, D. K., Yousif, J. H. and Khandage, S. V. (July 6-8, 2011). Cloud computing and enterprise resource planning systems. In Proceedings of the World Congress on Engineering 2011. (pp. 681-684). London: International Association of Engineers.
Shi, Z. (2010). The role of IS architecture planning in enhancing IS outsourcing's impact on ISperformance: Its antecedents and an empirical test. Journal of Enterprise Information Management, 23(4), 439-465.
Sonnenwald, D. H., Maglaughlin, K. L. and Whitton, M. C. (speaker). (June 20-22, 2001). Using innovation diffusion theory to guide collaboration technology evaluation: Work in progress. In Proceedings of the IEEE 10th International Workshop on Enabling Technologies. (pp. 114-119). Cambridge: Infrastructure for Collaborative Enterprises.
Stieninger, M. and Nedbal, D. (January 6-9, 2014). Diffusion and acceptance of cloud computing in SMEs: Towards a valence model of relevant factors. In Proceedings of the 47th Hawaii International Conference on System Sciences. (pp. 3307-3316). Hawaii: IEEE Computer Society.
Tan, K. S., Chong, S. C., Lin, B. and Eze, U. C. (2009). Internet-based ICT adoption: Evidence from Malaysian SMEs. Industrial Management and Data Systems, 109(2), 224-244.
Taylor, S. and Todd, P. A. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly, 19(2), 561-570.
Udo, G. G. (2000). Using analytic hierarchy process to analyze the information technology outsourcing decision. Industrial Management and Data Systems, 100(9), 421-429.
Wu, W. W. (2011). Developing an explorative model for SaaS adoption. Expert Systems with Applications, 38(12), 15057-15064.
Yamane, T. (1973). Statistics: An Introductory Analysis (3rd ed.). New York: Harper and Row.
Yi, M. Y., Jackson, J. D., Park, J. S. and Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward an integrative view. Information and Management, 43(3), 350-363.
Alkhater, N., Wills, G. and Walters, R. (speaker). (December 15-18, 2014). Factors influencing an organisation's intention to adopt cloud computing in Saudi Arabia. In IEEE 6th International Conference on Cloud Computing Technology and Science. (pp. 1040-1044). Singapore: IEEE Computer Society.
Alshamaila, Y., Papagiannidis, S. and Li, F. (2013). Cloud computing adoption by smes in the northeast of England: A multi-perspective framework. Journal of Enterprise Information Management, 26(3), 250-275.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.
Davis, F. D., Bangozzi, R. P., and Warshaw, P. R. (1989). User acceptance of computer technology:
A comparison of two theoretical models. Management Science, 35(8), 982-1003.
Davis, F. (1987). User acceptance of information systems: The technology acceptance model (TAM). Michigan: School of Business Administration, University of Michigan.
Gupta, P., Seetharaman, A. and Raj, J. R. (2013). The usage and adoption of cloud computing by small and medium businesses. International Journal of Information Management, 33(5), 861-874.
Hair, J., Blak, W. C., Barbin, B. J., Anderson, R. E. and Tatham, R. L. (2010). Multivariate data analysis (7th ed.). New Jersey: Prentice Hall.
Han, H. S., Lee, J. N., and Seo, Y. W. (2008). Analyzing the impact of a firm's capability on outsourcing success: A process perspective. Information and Management, 45(1), 31-42.
Hashim, H. S., Hassan Z. B. and Hashim A. S. (2015). Factors influence the adoption of cloud computing: A comprehensive review. International Journal of Education and Research, 3(7), 295-306.
Information Systems Audit and Control Association (ISACA). (2009). The risk IT framework escerpt. Retrieved October 23, 2017, from http://www.isaca.org
Keesookpun, C. and Mitomo, H. (speaker). (November 18-21, 2012). Cloud computing adoption and determining factors in different industries: A case study of Thailand. In 19th ITS Biennial Conference 2012 Moving Forward with Future Technologies: Opening a Platform for All. (pp. 125-132). Bangkok: International Telecommunications Society.
Lederer, A. L., Maupin, D. J., Sena, M. P. and Zhuang, Y. (2000). The technology acceptance model and the World Wide Web. Decision Support Systems, 29(3), 269-282.
Lee, Y. H., Hsieh, Y. C. and Hsu, C. N. (2011). Adding innovation diffusion theory to the technology acceptance model: Supporting employees’ intentions to use E-learning systems. Educational Technology and Society, 14(4), 124-137.
Lian, J. W., Yen, D. C. and Wang, Y. T. (2014). An exploratory study to understand the critical factors affecting the decision to adopt cloud computing in Taiwan hospital. International Journal of Information Management, 34(1), 28-36.
Lin, A. and Chen, N. C. (2012). Cloud computing as an innovation: Perception, attitude and adoption. International Journal of Information Management, 32, 533-540.
Lin, C., Shih, H. and Sher P. J. (2007). Integrating technology readiness into technology acceptance: The TRAM model. Psychology and Marketing, 24(7), 641-657.
Low, C., Chen, Y. and Wu, M. (2011). Understanding the determinants of cloud computing adoption. Industrial Management and Data Systems, 111(7), 1006-1023.
Moore, G. C. and Benbasat, I. (1991). Development of an instrument to measure the perception of adopting an information technology innovation. Information Systems Research, 2(3), 192-222.
Morgan, L. and Conboy, K. (speaker). (June 5-8, 2013). Factors affecting the adoption of cloud computing: An exploratory study. In Proceedings of the 21st European Conference on Information Systems. (pp. 125-134). Barcelona: Utrecht University.
National Statistical Office. (2016). A 2016 survey of the use of information and communication technology in workplaces. Retrieved November 12, 2017 from http://service.nso.go.th/nso/nso_center/project/search/result_by_department-th.jsp
Oliveira, T., Thomas, M. A. and Espadanal, M. (2014). Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Information and Management, 51(5), 497-510.
Opitz, N., Langkau, T. F., Schmidt, N. H. and Kolbe, L. M. (speaker). (January 4-7, 2012). Technology acceptance of cloud computing: Empirical evidence from German IT departments. In 45th Hawaii International Conference on System Sciences. (pp. 1593-1602). Hawaii: IEEE Computer Society.
Pandya, R. E. (2012). A framework for engaging diverse communities in citizen science in the US. Frontiers in Ecology and the Environment, 10(6), 314-317.
Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university Students behavioral intention to use e-Learning. Educational Technology and Society, 12(3), 150-162.
Park, E. and Kim K. J. (2014). An integrated adoption model of mobile cloud services: Exploration of key determinants and extension of technology acceptance model. Telematics and Informatics, 31(3), 376-385.
Pavlou, P. A. and Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly, 30(1), 115-143.
Rogers, E. M. (1995). Diffusion of innovations. New York: Free Press.
Sabi, H. M., Uzoka, F. M. E., Langmia, K. and Njeh, F. N. (2016). Conceptualizing a model for adoption of cloud computing in education. International Journal of Information Management, 36(2), 183-191.
Saini, S. L., Saini, D. K., Yousif, J. H. and Khandage, S. V. (July 6-8, 2011). Cloud computing and enterprise resource planning systems. In Proceedings of the World Congress on Engineering 2011. (pp. 681-684). London: International Association of Engineers.
Shi, Z. (2010). The role of IS architecture planning in enhancing IS outsourcing's impact on ISperformance: Its antecedents and an empirical test. Journal of Enterprise Information Management, 23(4), 439-465.
Sonnenwald, D. H., Maglaughlin, K. L. and Whitton, M. C. (speaker). (June 20-22, 2001). Using innovation diffusion theory to guide collaboration technology evaluation: Work in progress. In Proceedings of the IEEE 10th International Workshop on Enabling Technologies. (pp. 114-119). Cambridge: Infrastructure for Collaborative Enterprises.
Stieninger, M. and Nedbal, D. (January 6-9, 2014). Diffusion and acceptance of cloud computing in SMEs: Towards a valence model of relevant factors. In Proceedings of the 47th Hawaii International Conference on System Sciences. (pp. 3307-3316). Hawaii: IEEE Computer Society.
Tan, K. S., Chong, S. C., Lin, B. and Eze, U. C. (2009). Internet-based ICT adoption: Evidence from Malaysian SMEs. Industrial Management and Data Systems, 109(2), 224-244.
Taylor, S. and Todd, P. A. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly, 19(2), 561-570.
Udo, G. G. (2000). Using analytic hierarchy process to analyze the information technology outsourcing decision. Industrial Management and Data Systems, 100(9), 421-429.
Wu, W. W. (2011). Developing an explorative model for SaaS adoption. Expert Systems with Applications, 38(12), 15057-15064.
Yamane, T. (1973). Statistics: An Introductory Analysis (3rd ed.). New York: Harper and Row.
Yi, M. Y., Jackson, J. D., Park, J. S. and Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward an integrative view. Information and Management, 43(3), 350-363.