Tourism Mobile Applets: Factors Affecting Tourists’ Behavioral Intention and Use Behavior in Shanghai, China
DOI:
https://doi.org/10.14456/shserj.2024.65Keywords:
Social Influence, Behavioral Intention, Use Behavior, Tourism Mobile App, ShanghaiAbstract
Purpose: This study aimed to investigate the factors influencing the behavioral intention and use behavior of Shanghai tourists towards Tourism Mobile Applets. The research framework focused on exploring the impact of trust, facilitating conditions, social influence, perceived ease of use, perceived usefulness, use behavior, and behavioral intention. Research design, data, and methodology: A quantitative research approach was employed, involving a sample of 500 tourists in the region. Non-probabilistic sampling techniques, including judgment sampling and quota sampling, were utilized. Prior to data collection, the project quality was assessed using the indicator of project purpose consistency. Additionally, the Cronbach's alpha coefficient values were calculated based on a preliminary test involving 30 participants. Statistical analysis, including validity, reliability, and goodness of fit tests, was conducted using Confirmatory Factor Analysis (CFA) and Structural Equation Model. Results: The study revealed that the most significant factors influencing the behavioral intention to use tourism mobile applets were facilitating conditions and trust. Moreover, social influence, perceived ease of use, and perceived usefulness were found to be important factors affecting the behavioral intention to use tourism mobile applets. Furthermore, behavioral intention emerged as a crucial factor impacting the use behavior of tourism mobile applets. Conclusions: Based on the findings, it is recommended that enterprises prioritize improving the facilitating conditions, trust, social influence, perceived ease of use, and usefulness of tourism mobile applets. Enhancing these factors can lead to an improvement in tourists' behavioral intention and utilization of such applets.
References
Agarwal, R., & Prasad, J. (1999). Are Individual Differences Germane to the Acceptance of New Information Technologies? Decision Sciences, 30(2), 361-391. https://doi.org/10.1111/j.1540-5915.1999.tb01614.x
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-t
Akbari, M., Ardekani, Z. F., Pino, G., & Maleksaeidi, H. (2019). An extended model of Theory of Planned Behavior to investigate highly-educated Iranian consumers’ intentions towards consuming genetically modified foods. Journal of Cleaner Production, 227, 784-793. https://doi.org/10.1016/j.jclepro.2019.04.246
Al-Mamary, Y. H., & Shamsuddin, A. (2015). Testing of the technology acceptance model in context of yemen. Mediterranean Journal of Social Sciences, 6(4), 268-273. https://doi.org/10.5901/mjss.2015.v6n4s1p268
Amin, M., Rezaei, S., & Abolghasemi, M. (2014). User satisfaction with a mobile website: The impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust. Nankai Business Review International, 5(3), 258-274.
Awang, Z. (2012). A Handbook on SEM Structural Equation Modelling: SEM Using AMOS Graphic (5th ed.). Kota Baru: Universiti Teknologi Mara Kelantan.
Awang, Z., Aziz, R. C., Yusoff, A. M., & Nawi, N. M. (2020). Grab Pay App: The Factors Influencing Tourists' Behavioral Intention-to-Use. Talent Development and Excellence, 12(3), 820-828. https://doi.org/10.9734/bpi/nicst/v7/1580c
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238-246.
https://doi.org/10.1037/0033-2909.107.2.238.
Chang, I.-C., Chou, P.-C., Yeh, R. K., & Tseng, H.-T. (2015). An Exploratory Study on Factors Influencing Chinese Tourists’ Intention to Use the Taiwan Medical Travel applets. Telematics, and Informatics, 33(2), 401-409.
http://dx.doi.org/10.1016/j.tele.2015.09.007
Chen, K., & Chan, A. H. S. (2014). Predictors of geotechnology acceptance by older Hong Kong Chinese. Technovation, 34(2), 126-135. https://doi.org/10.1016/j.technovation.2013.09.010
Chen, L. Y., & Wu, W. N. (2017). An exploration of the factors affecting users’ satisfaction with Mobile payments. International Journal of Computer Science & Information Technology (IJCSIT), 9(6), 97-105.
https://doi.org/10.5121/ijcsit.2017.9308
Chong, A. Y.-L. (2013). A two-staged SEM-neural network approach for understanding and predicting the determinants of m-commerce adoption. Expert Systems with Applications, 40(4). 1240-1247. https://doi.org/10.1016/j.eswa.2012.08.067.
Dasgupta, S., Paul, R., & Fuloria, S. (2011). Factors Affecting Behavioral Intentions towards Mobile Banking Usage: Empirical evidence from India. Romanian Journal of Marketing, 3(1), 6-28.
Dwivedi, Y. K., Shareef, M. A., Simintiras, A. C., Lal, B., & Weerakkody, V. (2016). A generalised adoption model for services: A cross-country comparison of mobile health (m-health). Government Information Quarterly, 33(1), 174-187. https://doi.org/10.1016/j.giq.2015.06.003
Ert, E., Fleischer, A., & Magen, N. (2016). Trust and reputation in the sharing economy: The role of personal photos in Airbnb. Tourism Management, 55, 62-73. https://doi.org/10.1016/j.tourman.2016.01.013
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Gifford, R., & Nilsson, A. (2014). Personal and social factors that influence pro-environmental concern and behavior: a review. International Journal of Psychology, 49(3), 141-157. https://doi.org/10.1002/ijop.12034
Guritno, S., & 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(1), 212-216.
https://doi.org/10.1016/j.sbspro.2013.06.415
Hooda, A., Gupta, P., Jeyaraj, A., Giannakis, M., & Dwivedi, Y. K. (2022). The effects of trust on behavioral intention and use behavior within e-government contexts. International Journal of Information Management, 67(12), 143-155. https://doi.org/10.1016/j.ijinfomgt.2022.102553.
Hu, W., Alam, M. Z., Hoque, M. R., & Kaium, M. A. (2019). Adoption intention and usage behavior of mHealth services in Bangladesh and China A cross-country analysis. International Journal of Pharmaceutical and Healthcare Marketing, 14(1), 37-60. DOI 10.1108/IJPHM-03-2019-0023
Huang, G., & Yuan, X. (2020). New edition Tutorial of Education Statistics and Measurement Evaluation. (1st ed.). East China Normal University Press.
Islam, J. U., Rahman, Z., & Hollebeek, L. D. (2018). Consumer engagement in online brand communities: a solicitation of congruity theory. Internet Research, 28(1), 23-45.
https://doi.org/10.1108/intr-09-2016-0279
Kaplan, H. E., & Gurbuz, E. (2021). An extended utaut2 perspective- determinants of mobile banking use intention and use behavior. Ömer Halisdemir Universitesi iktisadi ve idari Bilimler Fakültesi Dergisi,14(1), 1334-134.
Khan, R. A., & Qudrat-Ullah, H. (2021). Adoption of LMS in higher educational institutions of the Middle East (1st ed.). Springer.
Lavrakas, P. J. (2008). Encyclopedia of survey research methods (1st ed.). Sage Publications.
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. https://doi.org/10.1016/j.compedu.2012.10.001
Lin, W. R., Lin, C. Y., & Ding, Y. H. (2020). Factors Affecting the Behavioral Intention to Adopt Mobile Payment: An Empirical Study in Taiwan. Mathematics, 8(10), 1-19. https://doi.org/10.3390/math8101851
Mahardika, H., Thomas, D., Ewing, M. T., & Japutra, A. (2019). Experience and facilitating conditions a simple dements to consumers’ new technology adoption (Article). International Review of Retail Distribution and Consumer Research, 29(1), 79-98. https://doi.org/10.1080/09593969.2018.1556181.
Mahmood, M. A., Janice, M., & Leopoldo, A. (2000). Variables affecting information technology end-user satisfaction: a meta-analysis of the empirical literature. International Journal of Human-Computer Studies, 52(4), 751-771.
Miles, M. B., & Huberman, A. M. (1994). Qualitative Data Analysis: A Sourcebook of New Methods (2nd ed.). Sage.
Mohlmann, M. (2015). Collaborative consumption: Determinants of satisfaction and the likelihood of using a sharing economy option again. Journal of Consumer Behaviour, 14(3), 193-207.
Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theoryof relationship marketing. Journal of Marketing, 58(3), 20-38. https://doi.org/10.1177/002224299405800302
Murugesan, R., & Jayavelu, R. (2015). Testing the impact of entrepreneurship education on business, engineering and arts and science students using the theory of planned behavior: A comparative study. Journal of Entrepreneurship in Emerging Economies, 7(3), 256-275. https://doi.org/10.1108/jeee-12-2014-0053
Namahoot, K., & Laohavichien, T. (2015). An Analysis of Behavioral Intention to use Thai Internet Banking with Quality Management and Trust. Journal of Internet Banking and Commerce, 20(3), 119-130.
Neuman, W. R., Just, M. R., & Crigler, A. N. (1992). Common knowledge: news and the construction of political meaning (1st ed.). University of Chicago Press. https://doi.org/10.2307/2074663
Ong, H., & Lai, Y. (2006). Gender Differences in Perceptions and Relationships Among Dominants Of E-Learning Acceptance. Computers in Human Behavior, 22(5), 816-829. https://doi.org/10.1016/j.chb.2004.03.006
Palvia, P. C. (1996). A model and instrument for measuring small business user satisfaction with information technology. Information and Management, 31(3), 151-163. https://doi.org/10.1016/s0378-7206(96)01069-5
Pan, L. (2020). Fingers Open the New World: User adoption of tourism applets (1st ed.). Beijing: Travel Education Press.
Pedroso, R., Zanetello, L., Guimaraes, L., Pettenon, M., Goncalves, V., Scherer, J., Kessler, F., & Pechansky, F. (2016). Confirmatory factor analysis (CFA) of the crack use relapse scale (CURS). Archives of Clinical Psychiatry, 43(3), 37-40. https://doi.org/10.1590/0101-60830000000081
Perera, H. N. (2013). A novel approach to estimating and testing specific mediation effects in educational research: Explication and application of Macho and Ledermann’s (2011) phantom model approach. International Journal of Quantitative Research in Education, 1(1), 39-60. https://doi.org/10.1504/ijqre.2013.055640
Pham, T. T., Dang, L. A., Le, T. M., & Le, T. H. (2020). Factors affecting teachers’ behavioral intention of using information technology in lecturing-economic universities. Management Science Letters, 1(2), 2665-2672.
https://doi.org/10.5267/j.msl.2020.3.026
Rahimnia, F., & Hassanzadeh, J. F. (2013). The impact of website content dimension and e-trust on e-marketing effectiveness: the case of Iranian commercial saffron corporations. Information and Management, 50(5), 240-247.
https://doi.org/10.1016/j.im.2013.04.003
Rather, R. A., Tehseen, S., Itoo, M. H., & Parrey, S. H. (2019). Customer brand identification, affective commitment, customer satisfaction, and brand trust as antecedents of customer behavioral intention of loyalty: An empirical study in the hospitality sector. Journal of Global Scholars of Marketing Science, 29(2), 196-217.
https://doi.org/ 10.1080/21639159.2019.1577694.
Rovinelli, R., & Hambleton, R. (1977). On the use of content specialists in the assessment of criterion-referenced test item validity. Dutch Journal of Educational Research, 2, 49-60.
Septiani, R., Handayani, P. W., & Azzahro, F. (2017). An empirical examination of factors affecting the behavioral intention to use online transportation service: A case study of GRAB. International Conference on Advanced Computer Science and Information Systems, 17, 93-98. https://doi.org/10.1109/icacsis.2017.8355017
Sharma, G. P., Verma, R. C., & Pathare, P. (2005). Mathematical modeling of infrared radiation thin layer drying of onion slices. Journal of Food Engineering, 71(3), 282-286. https://doi.org/10.1016/j.jfoodeng.2005.02.010
Shelley, M. C. (2006). Structural Equation Modeling (1st ed.). Encyclopedia of Educational Leadership and Administration.
Sica, C., & Ghisi, M. (2007). The Italian versions of the Beck Anxiety Inventory and the Beck Depression Inventory-II: Psychometric properties and discriminant power. Nova.
Stocchi, L., Michaelidou, N., & Micevski, M. (2019). Drivers and outcomes of branded mobile applets usage intention. Journal of Product & Brand Management, 28(1), 28-49. https://doi.org/10.1108/JPBM-02-2017-1436
Suki, N. M., & Suki, N. M. (2019). Examination of peer influence as a moderator and predictor in explaining green purchase behavior in a developing country. J. Clean. Prod., 228, 833-844.
Sun, Y., Wang, N., Guo, X., & Peng, Z. (2013). Understanding the acceptance of mobile health services: a comparison and integration of alternative models. Journal of Electronic Commerce Research, 14(2), 183.
Tabachnick, B. G., & Fidell, L. S. (2007). Experimental designs using ANOVA (1st ed.). Duxbury Press.
Tarhini, A., Hone, K., & Liu, X. (2015). Factors affecting students’ acceptance of e-learning environments in developing countries: A structural equation modeling approach. International Journal of Information and Education Technology, 3(1), 54-59. https://doi.org/10.7763/ijiet.2013.v3.233
Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach's alpha. International journal of medical education, 2, 53-55.
Teo, T. (2009). Modeling technology acceptance in education: A study of preservice teachers. Computers & Education, 52(2), 302-312.
Teo, T. (2013). Handbook of Quantitative Methods for Educational Research. Sense Publishers.
Urvashi, T., Ravi, K., & Ash, N. S. (2016). Customer satisfaction using website functionality, perceived usability, and perceived usefulness towards online shopping in India. Information Development, 32(5), 1657-1673.
Velazquez, G., Kaplan, S., & Monzon, S. (2018). Ex-Ante and Ex-Post Evaluation of a New Transit Information applets: Modeling Use Intentions and Actual Use. Transportation Research Record, 2, 50-55.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
Visinescu, L. L., Sidorova, A., Jones, M. C., & Prybutok, V. R. (2015). The influence of website dimensionality on customer experiences, perceptions, and behavioral intentions: An exploration of 2D vs. 3D web design. Inf. Manag., 52, 1-17. https://doi.org/10.1016/j.im.2014.10.005
Visram, S., Smith, S., Connor, N., Greig, G., & Scorer, C. (2018). Examining associations between health, well-being, and social capital: findings from a survey developed and conducted using participatory action research. Journal of Public Mental Health, 17(3), 122-134. https://doi.org/10.1108/jpmh-09-2017-0035
Williams, B., Brown, T., & Onsman, A. (2010). Exploratory factor analysis: A five-step guide for novices. Australasian Journal of Paramedicine, 8(3), 1-13. https://doi.org/10.33151/ajp.8.3.93
Wu, J. H., & Wang, Y. M. (2006). Measuring KMS success: A respecification of the DeLone and McLean’s model. Information and Management, 43(6), 728-739. https://doi.org/10.1016/j.im.2006.05.002
Yang, K. (2010). Determinants of US consumer mobile shopping services adoption: implications for designing mobile shopping services. Journal of Consumer Marketing, 27(3), 262-270. https://doi.org/10.1108/07363761011038338
Yee, T. S., Seong, L. C., & Chin, W. S. (2019). Patient’s Intention to Use Mobile Health App. Journal of Management Research, 11(3), 18-20. https://doi.org/10.5296/jmr.v11i3.14776
Zahra, F., Hussain, A., & Mohd, H. (2017). Usability evaluation of mobile applications; where do we stand? AIP Conference Proceedings (1st ed.). Publishing.
Zhou, T., Lu, Y., & Wang, B. (2015). Integrating TTF and UTAUT to explain mobile banking user adoption. Computer Human Behavior, 26(4), 760-767. https://doi.org/10.1016/j.chb.2010.01.013
Zolkepli, I. A. (2016). Domination of mobile applets market: The effect of applets value on applets rating and applets costs in determining adoption. Proceedings of Penang International Symposium on Advanced in Social Sciences and Humanities, Royale Bintang, Penang, 1-12.
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