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http://dx.doi.org/10.52255/smarttourism.2022.2.3.2

Attitude Change Towards Self-Service Technology Adoption Using Latent Growth Modeling  

Um, Taehyee (Conrad N. Hilton College of Hotel & Restaurant Management, University of Houston)
Chung, Namho (Smart Tourism Research Platform, Kyung Hee University)
Publication Information
Journal of Smart Tourism / v.2, no.3, 2022 , pp. 5-15 More about this Journal
Abstract
As the utilization of technology in the tourism field becomes familiar, it greatly impacts people's tourism activities. These changes could also affect the behavior of tourists during the pandemic. To investigate consumers' adaptation to the self-service technology (SST) environment during the coronavirus disease of 2019 (COVID-19) pandemic, we adopted a model of absorptive capacity as the main framework for empirical research. To track the social effects of COVID-19, consumers' behavioral intentions for four different points in time are collected. The analysis was conducted using latent growth and structural equation modeling. We set the organizational and environmental characteristics as the first step of the model, with assimilation and trust as a middle step. Intention to use a kiosk is placed at the final step as an exploit. Findings indicate that organizational characteristics and environmental characteristics positively influenced assimilation and trust, except for environmental characteristics. Consumers' assimilation in SST encourages immediate intention to use a kiosk. Consumers' trust in kiosks positively impacts both immediate and continuance intention to use a kiosk during COVID-19.
Keywords
self-service technology; kiosk; absorptive capacity; trust; COVID-19; latent growth model;
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1 Reinders, M. J., Dabholkar, P. A., & Frambach, R. T. (2008). Consequences of forcing consumers to use technology-based self-service. Journal of Service Research, 11(2), 107-123.   DOI
2 Salo, J., & Karjaluoto, H. (2007). A conceptual model of trust in the online environment. Online Information Review, 31(5), 604-621.   DOI
3 Shin, H., & Perdue, R. R. (2019). Self-Service Technology Research: A bibliometric co-citation visualization analysis. International Journal of Hospitality Management, 80, 101-112.   DOI
4 Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-903.   DOI
5 Tavera-Mesias, J. F., van Klyton, A., & Zun iga Collazos, A. (2022). Social stratification, self-image congruence, and mobile banking in Colombian cities. Journal of International Consumer Marketing, 34(3), 312-331.   DOI
6 Alt, R. (2021). Digital transformation in the restaurant industry: Current developments and implications. Journal of Smart Tourism, 1(1), 69-74.   DOI
7 The World Bank. (2020, June 8). The Global Economic Outlook During the COVID-19 Pandemic: A Changed World. Retrieved from www.worldbank.org/en/news/feature/2020/06/08/the-global-economic-outlookduring-the-covid-19-pandemic-a-changed-world
8 Todorova, G., & Durisin, B. (2007). Absorptive capacity: Valuing a reconceptualization. Academy of Management Review, 32(3), 774-786.   DOI
9 Tussyadiah, I. P., & Park, S. (2018). When guests trust hosts for their words: Host description and trust in sharing economy. Tourism Management, 67, 261-272.   DOI
10 Um, T., & Chung, N. (2021). Does smart tourism technology matter? Lessons from three smart tourism cities in South Korea. Asia Pacific Journal of Tourism Research, 26(4), 396-414.   DOI
11 Turner, T., & Shockley, J. (2014). Creating shopper value: Co-creation roles, in-store self-service technology use, and value differentiation. Journal of Promotion Management, 20(3), 311-327.   DOI
12 Assaker, G., Vinzi, V. E., & O'Connor, P. (2011). Examining the effect of novelty seeking, satisfaction, and destination image on tourists' return pattern: A two factor, non-linear latent growth model. Tourism Management, 32(4), 890-901.   DOI
13 Aurier, P., & N'Goala, G. (2010). The differing and mediating roles of trust and relationship commitment in service relationship maintenance and development. Journal of the Academy of Marketing Science, 38(3), 303-325.   DOI
14 Bae, S. Y., & Chang, P.-J. (2020). The effect of coronavirus disease-19 (COVID-19) risk perception on behavioural intention towards 'untact' tourism in South Korea during the first wave of the pandemic (March 2020). Current Issues in Tourism, 1-19.
15 Baumann, C., Hamin, H., & Chong, A. (2015). The role of brand exposure and experience on brand recall-Product durables vis-a -vis FMCG. Journal of Retailing and Consumer Services, 23, 21-31.   DOI
16 Beldad, A. D., & Hegner, S. M. (2018). Expanding the technology acceptance model with the inclusion of trust, social influence, and health valuation to determine the predictors of German users' willingness to continue using a fitness app: A structural equation modeling approach. International Journal of Human-Computer Interaction, 34(9), 882-893.   DOI
17 Chen, C.-J., Tsai, P.-H., & Tang, J.-W. (2022). How informational-based readiness and social influence affect usage intentions of self-service stores through different routes: An elaboration likelihood model perspective. Asia Pacific Business Review, 28(3), 380-409.   DOI
18 Collier, J. E., Moore, R. S., Horky, A., & Moore, M. L. (2015). Why the little things matter: Exploring situational influences on customers' selfservice technology decisions. Journal of Business Research, 68(3), 703-710.   DOI
19 Chang, Y.-S., Cheah, J.-H., Lim, X.-J., Morrison, A. M., & Kennell, J. S. (2022). Are unmanned smart hotels du jour or are they here forever? Experiential pathway analysis of antecedents of satisfaction and loyalty. International Journal of Hospitality Management, 104, 103249.
20 Lu, H. P., & Yu-Jen Su, P. Y. J. (2009). Factors affecting purchase intention on mobile shopping web sites. Internet Research, 19(4), 442-458.   DOI
21 Meuter, M. L., Ostrom, A. L., Roundtree, R. I., & Bitner, M. J. (2000). Selfservice technologies: Understanding customer satisfaction with technology-based service encounters. Journal of Marketing, 64(3), 50-64.
22 Meidute-Kavaliauskiene, I., Yildiz, B., Cig dem, S., & C inc ikaite , R. (2021). The effect of COVID-19 on airline transportation services: A study on service robot usage intention. Sustainability, 13(22), 12571.   DOI
23 Um, T., Chung, N., & Stienmetz, J. (2022). Factors affecting consumers' impulsive buying behavior in tourism Mobile commerce using SEM and fsQCA. Journal of Vacation Marketing, 13567667221090991.
24 Um, T., Kim, H., Kim, H., Lee, J., Koo, C., & Chung, N. (2022a). Travel Incheon as a Metaverse: Smart Tourism Cities Development Case in Korea. Paper presented at the ENTER22 e-Tourism Conference.
25 Um, T., Kim, H., Rhee, J., & Chung, N. (2022b). A mixed-method approach to explore the motivations and constraints of kiosks consumers. Asia Pacific Journal of Information Systems, 32(1), 92-124.   DOI
26 Um, T., Kim, T., & Chung, N. (2020). How does an intelligence chatbot affect customers compared with self-service technology for sustainable services? Sustainability, 12(12), 5119.   DOI
27 Volberda, H. W., Foss, N. J., & Lyles, M. A. (2010). Perspective-Absorbing the concept of absorptive capacity: How to realize its potential in the organization field. Organization Science, 21(4), 931-951.   DOI
28 Walker, W. R., Vogl, R. J., & Thompson, C. P. (1997). Autobiographical memory: Unpleasantness fades faster than pleasantness over time. Applied Cognitive Psychology, 11(5), 399-413.   DOI
29 Wei, W., Torres, E., & Hua, N. (2016). Improving consumer commitment through the integration of self-service technologies: A transcendent consumer experience perspective. International Journal of Hospitality Management, 59, 105-115.   DOI
30 Wilson, T. D., & Gilbert, D. T. (2008). Explaining away: A model of affective adaptation. Perspectives on Psychological Science, 3(5), 370-386.   DOI
31 Xie, Y., & Greenman, E. (2011). The social context of assimilation: Testing implications of segmented assimilation theory. Social Science Research, 40(3), 965-984.   DOI
32 Van Den Bosch, F. A., Van Wijk, R., & Volberda, H. W. (2003). Absorptive capacity: Antecedents, models and outcomes. ERIM Report Series Reference No. ERS-2003-035-STR, Available at SSRN: https://ssrn.com/abstract=411675.
33 Kokkinou, A., & Cranage, D. A. (2013). Using self-service technology to reduce customer waiting times. International Journal of Hospitality Management, 33, 435-445.   DOI
34 Laumer, S., Maier, C., & Eckhardt, A. (2010). Why do they resist? -An empirical analysis of an individual's personality trait resistance regarding the adoption of new information systems. ECIS 2010 Proceedings. 31.
35 Lee, H.-J., & Lyu, J. (2016). Personal values as determinants of intentions to use self-service technology in retailing. Computers in Human Behavior, 60, 322-332.   DOI
36 Lee, K., & Mirchandani, D. (2010). Dynamics of the importance of IS/IT skills. Journal of Computer Information Systems, 50(4), 67-78.
37 Lee, Y.-K., Park, J.-H., Chung, N., & Blakeney, A. (2012). A unified perspective on the factors influencing usage intention toward mobile financial services. Journal of Business Research, 65(11), 1590-1599.   DOI
38 Liang, H., Saraf, N., Hu, Q., & Xue, Y. (2007). Assimilation of enterprise systems: The effect of institutional pressures and the mediating role of top management. MIS Quarterly, 31(1), 59-87.   DOI
39 Lin, J.-S. C., & Hsieh, P.-L. (2007). The influence of technology readiness on satisfaction and behavioral intentions toward self-service technologies. Computers in Human Behavior, 23(3), 1597-1615.   DOI
40 Liu, S. (2012). The impact of forced use on customer adoption of selfservice technologies. Computers in Human Behavior, 28(4), 1194-1201.   DOI
41 Liu, Y., Li, H., & Hu, F. (2013). Website attributes in urging online impulse purchase: An empirical investigation on consumer perceptions. Decision Support Systems, 55(3), 829-837.   DOI
42 McMillen, J. C., Smith, E. M., & Fisher, R. H. (1997). Perceived benefit and mental health after three types of disaster. Journal of Consulting and Clinical Psychology, 65(5), 733-739.   DOI
43 DeWitt, T., Nguyen, D. T., & Marshall, R. (2008). Exploring customer loyalty following service recovery: The mediating effects of trust and emotions. Journal of Service Research, 10(3), 269-281.   DOI
44 Enkel, E., Heil, S., Hengstler, M., & Wirth, H. (2017). Exploratory and exploitative innovation: To what extent do the dimensions of individual level absorptive capacity contribute? Technovation, 60-61, 29-38.   DOI
45 Feng, W., Tu, R., Lu, T., & Zhou, Z. (2019). Understanding forced adoption of self-service technology: The impacts of users' psychological reactance. Behaviour and Information Technology, 38(8), 820-832.   DOI
46 Fischer, K. W. (1980). A theory of cognitive development: The control and construction of hierarchies of skills. Psychological Review, 87(6), 477-531.   DOI
47 Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.   DOI
48 Gupta, A. K., & Gupta, N. (2020). Effect of corporate environmental sustainability on dimensions of firm performance-Towards sustainable development: Evidence from India. Journal of Cleaner Production, 253, 119948.   DOI
49 Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152.   DOI
50 Harris, L. C., & Goode, M. M. H. (2010). Online servicescapes, trust, and purchase intentions. Journal of Services Marketing, 24(3), 230-243.   DOI
51 Kale, E., Aknar, A., & Basar, O . (2019). Absorptive capacity and firm performance: The mediating role of strategic agility. International Journal of Hospitality Management, 78, 276-283.   DOI
52 Cserdi, Z., & Kenesei, Z. (2021). Attitudes to forced adoption of new technologies in public transportation services. Research in Transportation Business and Management, 41, 100611.   DOI
53 Zhang, T., Tao, D., Qu, X., Zhang, X., Zeng, J., Zhu, H., & Zhu, H. (2020). Automated vehicle acceptance in China: Social influence and initial trust are key determinants. Transportation Research Part C, 112, 220-233.   DOI
54 Zhu, K., Kraemer, K. L., & Xu, S. (2006). The process of innovation assimilation by firms in different countries: A technology diffusion perspective on e-business. Management Science, 52(10), 1557-1576.   DOI
55 Zohar, D., Tzischinski, O., & Epstein, R. (2003). Effects of energy availability on immediate and delayed emotional reactions to work events. Journal of Applied Psychology, 88(6), 1082-1093.   DOI
56 Nelms, T. C., Maurer, B., Swartz, L., & Mainwaring, S. (2018). Social payments: Innovation, trust, Bitcoin, and the sharing economy. Theory, Culture and Society, 35(3), 13-33.   DOI
57 Nijssen, E. J., Schepers, J. J. L., & Belanche, D. (2016). Why did they do it? How customers' self-service technology introduction attributions affect the customer-provider relationship. Journal of Service Management, 27(3), 276-298.   DOI
58 Parasuraman, A. (2000). Technology Readiness Index (TRI): A multipleitem scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4), 307-320.   DOI
59 Patil, A., & Humbare, R. (2020, June). Interactive Kiosk Market Size, Share and Growth. Allied Market Research. https://www.alliedmarketresearch.com/interactive-kiosk-market
60 Petrick, J. F. (2004). Are loyal visitors desired visitors? Tourism Management, 25(4), 463-470.   DOI
61 Park, J.-H., Suh, H.-J., & Yang, H.-D. (2007). Perceived absorptive capacity of individual users in performance of Enterprise Resource Planning (ERP) usage: The case for Korean firms. Information and Management, 44(3), 300-312.   DOI
62 Garci a-Milon, A., Olarte-Pascual, C., & Juaneda-Ayensa, E. (2021). Assessing the moderating effect of COVID-19 on intention to use smartphones on the tourist shopping journey. Tourism Management, 87, 104361.   DOI
63 Kim, M. J., Lee, C.-K., Chung, N., & Kim, W. G. (2014). Factors affecting online tourism group buying and the moderating role of loyalty. Journal of Travel Research, 53(3), 380-394.   DOI
64 Park, S., & Tussyadiah, I. P. (2017). Multidimensional facets of perceived risk in mobile travel booking. Journal of Travel Research, 56(7), 854-867.   DOI
65 Wang, W., Liu, L., Feng, Y., & Wang, T. (2014). Innovation with IS usage: Individual absorptive capacity as a mediator. Industrial Management and Data Systems, 114(8), 1110-1130.   DOI
66 Zahra, S. A., & George, G. (2002). Absorptive capacity: A review, reconceptualization, and extension. Academy of Management Review, 27(2), 185-203.   DOI
67 Liao, S.-H., Chen, C.-C., Hu, D.-C., Chung, Y.-c., & Yang, M.-J. (2017). Developing a sustainable competitive advantage: Absorptive capacity, knowledge transfer and organizational learning. Journal of Technology Transfer, 42(6), 1431-1450.   DOI
68 Min, J., Yang, K., & Kim, J. (2022). The role of perceived vulnerability in restaurant customers' co-creation behavior and repatronage intention during the COVID-19 pandemic. Journal of Vacation Marketing, 28(1), 38-51.   DOI
69 Blut, M., Wang, C., & Schoefer, K. (2016). Factors influencing the acceptance of self-service technologies: A meta-analysis. Journal of Service Research, 19(4), 396-416.   DOI
70 Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128-152.   DOI
71 Shiwen, L., Kwon, J., & Ahn, J. (2022). Self-service technology in the hospitality and tourism settings: A critical review of the literature. Journal of Hospitality and Tourism Research, 46(6), 1220-1236.   DOI
72 Rowley, J. (2006). An analysis of the e-service literature: Towards a research agenda. Internet Research, 16(3), 339-359.   DOI
73 Prentice, C., Weaven, S., & Wong, I. A. (2020). Linking AI quality performance and customer engagement: The moderating effect of AI preference. International Journal of Hospitality Management, 90, 102629.   DOI
74 Pulkkinen, J., Jussila, J., Partanen, A., Trotskii, I., & Laiho, A. (2019). Smart mobility: Services, platforms and ecosystems. Technology Innovation Management Review, 9(9), 15-24.
75 Rau, P.-L. P., Gao, Q., & Wu, L.-M. (2008). Using mobile communication technology in high school education: Motivation, pressure, and learning performance. Computers and Education, 50(1), 1-22.   DOI
76 Reddy, R., Rhodes, J. E., & Mulhall, P. (2003). The influence of teacher support on student adjustment in the middle school years: A latent growth curve study. Development and Psychopathology, 15(1), 119-138.   DOI