Abstract
Based on the extended ECM-ISC continuous usage model and integration of the CAC model, a model that illustrates users’ continuous usage of online healthcare services is developed from the perspective of affect appeal by introducing satisfaction and worry variables. The factors influencing users’ continuous usage of online healthcare services in China are closely investigated in the paper. Based on the results of E-mail and Wen Juan Xing website online survey, the empirical analyses of the continuous usage of online healthcare services in China are conducted, utilizing SPSS and AMO. Through the screening of the questionnaires, 521 of the 600 questionnaires are valid. The main results of this study are as follows. Service quality, expectation confirmation degree, privacy concern, satisfaction degree, and continuous use intention are positively correlated with expectation confirmation degree, satisfaction degree, concern, and continuous use intention and continuous use behavior, respectively, while concern and continuous use intention are negatively correlated. It is found in this paper that both satisfaction and concern have a direct impact on users’ continuous use intention and continuous use behavior, and the effect of concern becomes increasingly prominent. Besides, service quality and privacy concern are the core variables affecting satisfaction degree and concern. Based on the above research results, this paper suggests to strengthen the security of user privacy information, and meanwhile, improve the quality of online doctors, which can promote users’continuous use intention and continuous use behavior, and thus further improve the efficiency of the use of health services online and quality medical resource allocation, as well as reduce hospital time and economic cost.
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References
Beaudry, A., & Pinsonneault, A. (2010). The other side of acceptance: studying the direct and indirect effects of emotions on information technology use[J]. MIS Quarterly, 34(4), 689–710.
Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation confirmation model[J]. MIS Quarterly, 25(3), 351–370.
Bulgurcu, B. (2010). Antecedents and outcomes of information privacy concerns in online social networking: a theoretical perspective[J].In Proceedings of JAIS Theory Development Workshop,
Chou, S. W., Lee, C. C., & Chang, Y. C. (2009). Understanding continuance intention of knowledge creation in online communities from a social-psychological perspective[C]. IEEE. Proceedings of the 42nd Hawaii International Conference on System Sciences.
Dadoa, J., Taborecka-Petrovicovaa, J., Sreten, C., & Rajicc, T. (2012). An empirical examination of the relationships between service quality, satisfaction and behavioral intentions in higher education setting[J]. Serbian Journal of Management, 7(2), 203–218.
Deng, L. (2016). Study on development and strategy of mobile medical health applications [J]. Modern Science & Technology of Telecommunications, 46(2), 38–42.
Deng, Z., & Hong, Z. (2017). An empirical study of patient-physician trust impact factors in online healthcare services. Journal of Management Science, 30(1), 43–52.
Deng, Z., Mo, X., & Liu, S. (2014). Comparison of the middle-aged and older users adoption of mobile health services in China[J]. International Journal of Medical Informatics, 83(3), 210–224.
Deng, Z., Liu, S., & Oliver, H. (2015). The health information seeking and usage behavior intention of Chinese consumers through mobile phones[J]. Information Technology and People, 28(2), 405–423.
Dinev, T., & Hart, P. (2006). Internet privacy concerns and social awareness as determinants of intention to transact[J]. International Journal of Electronic Commerce, 10(2), 7–29.
Fang, J., & Lu, Y. (2002). Modern medical statistics (pp. 247–251). Beijing: People's Medical Publishing House.
Gray, J. R., Braver, T. S., & Raichle, M. E. (2002). Integration of emotion and cognition in the lateral prefrontal cortex[J]. Proceedings of the National Academy of Sciences of the United States of America, 99(6), 15–20.
Han, C.-q., Yang, S.-q., & Cao, Y.-z. (2012). A synergistic model of “bile service users adoption”__an empirical investigation of mobile reading service[J]. Soft Science Journal, 26(3), 134–139.
Junglas, I. A., Johnson, N. A., & Spitzmuller, C. (2008). Personality traits and concern for privacy: an empirical study in the context of location-based services[J]. European Journal of Information Systems, 17(4), 387–402.
Kantar. 2016. 中国社交媒体影响研究[EB/OL]. http://cn.kantar.com.
Kathryn, M. C., & Kinshuk, J. L. (2014). Comparing the role of ICT literacy and anxiety in the adoption of mobile learning[J]. Computers in Human Behavior, 39, 8–19.
Kim, S., & Son, J.-Y. (2009). Out of dedication or constraint a dual model of post-adoption phenomena and its empirical test in the context of online services[J]. MIS Quarterly, 33(1), 49–70.
Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior[J]. Information Systems Research, 13(2), 205–223.
Larsen, T. J., & Sorebo, A. M. (2009). The role of task-technology fit as users motivation to continue information system use[J]. Computers in Human Behavior, 25(3), 778–784.
Lavidge, R. C., & Steiner, G. A. (1961). A Model for Pre- dictive Measurements of Advertising Effectiveness. Journal of Marketing, 25, 59–62.
Li, Y. (2015). Functions of domestic interrogation mobile medical APP[J]. Chinese Journal of Medical Library & Information Science, 24, 63–65.
Li, H., Sarathy, R., & Xu, H. (2011). The role of affect and cognition on online consumers decision to disclose personal information to unfamiliar online vendors [J]. Decision Support Systems, 51(3), 434–445.
Li, Y.-f., Luo, P., Cheng, L., Xia, E.-l., Zhang, J., Liao, J.-h., & Qin, J.-c. (2016). Research of the present mobile health care and the relevant APP application[J]. Modern Hospital Management, 14, 65–68.
Limayem, M., & Hirt, S. G. (2003). Force of habit and information systems usage: theory and initial validation[J].Journal of the association for. Information Systems, 4(1), 65–97.
Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How habit limits the predictive power of intention: the case of information systems continuance[J]. Management Information Systems Quarterly, 31(4), 705–737.
Liu, Q.-s., & Liang, Z. D. (2015). Research on Accept Behavior of APP Users for Mobile Health [J]. Journal of Shandong Youth University of Political Science, 31, 14–18.
Liu, L., & Sun, K. (2011). Extending ECM-ISC to Mobile Search Users’Continuance Usage: A Theoretical Model[J]. Library and Information Service, 55(20), 134–137.
Liu, Q., Zuo, M., & Liu, M. (2012). Analysis of continuance usage model for the elderly using Internet[J]. Management review journal, 24(5), 89–101.
Luo, X.-h., Yang, R.-q., & Zhou, S. (2014). An empirical study based on the willingness of issm mobile payment users to continue to use[J]. Journal of Economic History, (10), 49–51.
Merikivi, M. M. J. (2010). Investigating the drivers of the continuous use of social virtual worlds[C]. IEEE.Proceedings of the 43rd Hawaii International Conference on System Sciences.
Olive, R. L. (1980). A Cognitive model of the antecedents and consequences of satisfaction decisions[J]. Journal of Marketing Research, 17(4), 460–469.
Peng, X., Feng, Z., & Sun, Y. (2012). Theoretical model and empirical research on the intention of continuous use of Weibo users[J]. Modern Library and Information Technology, 11, 8–85.
Piaget, J., Brown, T. A., Kaegi, C. E. et al. (1981). Intelligence and affectivity: their relationship during child development[M]. Annual Reviews Inc.
Shi, N. (2010). The continuance of online social networks: How to keep people using facebook?. IEEE. Proceedings of the 43rd Hawaii International Conference on System Sciences.
Venkatesh, V., Morris, M. G., Davis, G. B., et al. (2003). User acceptance of information technology: toward a unified view[J]. MIS Quarterly, 27(3), 425–478.
Wang, B.-w., Zhao, L., Wang, Z.-y., et al. (2015). Function and application of hospital mhealth APP [J]. China Digital Medicine, 10(10), 30–32.
Westbrook, R. A., & Oliver, R. L. (1991). The dimensionality of consumption emotion patterns and consumer satisfaction[J]. Journal of Consumer Reasearch, 18(1), 84–91.
Wu, M. (2012). Structural Equation Model-AMOS Operation and Application. Chongqing University Press (pp 514–517).
Wu, H.-y., Ding, J., et al. (2019). Development of TCM job satisfaction scale based on confirmatory factor analysis[J]. Chinese Health Statistics, 2(1), 92–95.
Xia, Z., Xiaoli, W., & Wang, B. (2015). Research on factors that Influence the publics’ intention to use social media during disaster events.[J]. Journal of the China Society for Scientific and Technical Information, 34(3), 313–323.
Xu, Q., & Zhao, W.-l. (2015). Research status of mobile health care APP and implications[J]. Journal of Medical Informatics, 36, 8–13.
Xu, H., Teo, H. H., & Tan, B. C. (2009). The role of push-pull technology in privacy calculus: the case of location-baes services[J]. Journal of Management Information Systems, 26(3), 135–174.
Xu H., Gupta S., Rosson M.B.,et al. (2012). Measuring mobile users concerns for information privacy[c]. In proceedings of the 33rd International Conference on Information System, Orlando.
Yang, S., & Wang, K.-l. (2008). The measurement of online users7 privacy concern in China context[J]. Journal of Intelligence Magazine, 27(10), 3–7.
Ye, F., & Hu, Y. (2015). The empirical study of mobile reading teenagers’ user adoption behavior[J]. Journal of the China Society for Scientific and Technical Information, 34(8), 787–800.
Yin, G., & Yang, B. (2010). An Empirical study on usage continuance model of social network services[J]. China Journal of Information Systems, 4(1), 53–64.
Zhang, M., & Lu, Y. (2012). Balance of the motivators and inhibitors for consumers to continue using mobile services[J]. Library and Information Work Magazine, 56(14), 135–140.
Zhao, Y., & Fan, J. (2016). Influencing factors of the continued use of social media among college students:a comparative study via WeChat, Weibo and Renren Network Cases Zhao Ying[J]. Journal of Intelligence, 35(1), 188–195.
Zhao, Y., & Gao, T. (2015). An empirical research on influence factors of users’ continuance Usage of Mobile Library APP[J]. Information Sciences, 33(6), 95–100.
Zhao, Z., Du, X., & Chen, K. (2014). Research On the ‰如relying mechanism and solutions of online compulsive buying behavior[J]. Management Review, 26(4), 130–141.
Zhao, W.-j., Yi, M., & Wang, X.-d. (2017). Research on continued participation intention of social q&a platform users——based on the view of perceived value[J]. Information Science Journal, (32), 69–91.
Zhou, T., & Lu, Y. (2010). An empirical analysis of the impact of privacy concerns on the adoption behavior of mobile commerce users[J]. Journal of Management, (7), 1046–4051.
Zhou, T., Lu, Y. b., & Zhang, J. (2001). Research on the critical success factors of mobile commerce website[J]. Management Review Journal, 23(6), 61–67.
Zhou, T., Zhang, S. R., & Ji, B. Y. (2010). Exploring the effect of online banking service quality on users’ continuance usage[C]. IEEE. Proceedings of the 43rd Hawaii International Conference on System Sciences.
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National Natural Science Foundation of China (71571162)
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Ju, C., Zhang, S. Research on User’ Continuous Usage of Online Healthcare Services From the Perspective of Affect Appeal. J. technol. behav. sci. 5, 215–225 (2020). https://doi.org/10.1007/s41347-020-00128-9
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DOI: https://doi.org/10.1007/s41347-020-00128-9