To go or not to go? Exhibition attendees’ risk perception of COVID-19: Evidence from three Asian regions

References

• Aburumman, A. A. (2020). COVID-19 impact and survival strategy in business tourism market: The example of the UAE MICE industry. Humanities and Social Sciences Communications, 7(1), 1–11. doi:10.1057/s41599-020-00630-8
   Google Scholar
• Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), 888–918. doi:10.1037/0033-2909.84.5.888
   Web of Science ®Google Scholar
• Algarni, A. (2019). What message characteristics make social engineering successful on Facebook: The role of central route, peripheral route, and perceived risk. Information, 10(6), 211. doi:10.3390/info10060211
   Google Scholar
• Al-Gahtani, S. S., & King, M. (1999). Attitudes, satisfaction and usage: Factors contributing to each in the acceptance of information technology. Behaviour & Information Technology, 18(4), 277–297. doi:10.1080/014492999119020
   Web of Science ®Google Scholar
• Alshikhi, O. A., & Abdullah, B. M. (2018). Information quality: Definitions, measurement, dimensions, and relationship with decision making. European Journal of Business and Innovation Research, 6(5), 36–42.
   Google Scholar
• Anguera-Torrell, O., Aznar-Alarcón, J. P., & Vives-Perez, J. (2021). COVID-19: Hotel industry response to the pandemic evolution and to the public sector economic measures. Tourism Recreation Research, 46(2), 148–157. doi:10.1080/02508281.2020.1826225
   Web of Science ®Google Scholar
• Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94. doi:10.1007/BF02723327
   Google Scholar
• Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance: An elaboration likelihood model. MIS Quarterly, 30(4), 805–825. doi:10.2307/25148755
   Web of Science ®Google Scholar
• Bockarjova, M., & Steg, L. (2014). Can Protection Motivation Theory predict pro-environmental behavior? Explaining the adoption of electric vehicles in the Netherlands. Global Environmental Change, 28, 276–288. doi:10.1016/j.gloenvcha.2014.06.010
   Web of Science ®Google Scholar
• Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210–230. doi:10.1111/j.1083-6101.2007.00393.x
   Web of Science ®Google Scholar
• Casidy, R., & Wymer, W. (2016). A risk worth taking: Perceived risk as moderator of satisfaction, loyalty, and willingness-to-pay premium price. Journal of Retailing and Consumer Services, 32, 189–197. doi:10.1016/j.jretconser.2016.06.014
   Web of Science ®Google Scholar
• Chang, M. K., Cheung, W., & Lai, V. S. (2005). Literature derived reference models for the adoption of online shopping. Information & Management, 42(4), 543–559. doi:10.1016/S0378-7206(04)00051-5
   Web of Science ®Google Scholar
• Chang, Y. P., & Dong, X. B. (2016). Research on the impact of consumer interaction behaviour on purchase intention in an SNS environment: Evidence from China. Information Development, 32(3), 496–508. doi:10.1177/0266666914556821
   Web of Science ®Google Scholar
• Chang, Y. T., Yu, H., & Lu, H. P. (2015). Persuasive messages, popularity cohesion, and message diffusion in social media marketing. Journal of Business Research, 68(4), 777–782. doi:10.1016/j.jbusres.2014.11.027
   Web of Science ®Google Scholar
• Chen, C. W., Chen, W. C., & Chen, W. K. (2014). Understanding the effects of eWOM on cosmetic consumer behavioral intention. International Journal of Electronic Commerce Studies, 5(1), 97–102. doi:10.7903/ijecs.1030
   Google Scholar
• Cheng, Y., Fang, S., & Yin, J. (2022). The effects of community safety support on COVID-19 event strength perception, risk perception, and health tourism intention: The moderating role of risk communication. Managerial and Decision Economics : MDE, 43(2), 496–509. doi:10.1002/mde.3397
   PubMed Web of Science ®Google Scholar
• Choi, S. (2019). The roles of media capabilities of smartphone-based SNS in developing social capital. Behaviour & Information Technology, 38(6), 609–620. doi:10.1080/0144929X.2018.1546903
   Web of Science ®Google Scholar
• Cori, L., Bianchi, F., Cadum, E., & Anthonj, C. (2020). Risk perception and COVID-19. International Journal of Environmental Research and Public Health, 17(9), 3114. doi:10.3390/ijerph17093114
   PubMed Web of Science ®Google Scholar
• Cyr, D., Head, M., Lim, E., & Stibe, A. (2018). Using the elaboration likelihood model to examine online persuasion through website design. Information & Management, 55(7), 807–821. doi:10.1016/j.im.2018.03.009
   Web of Science ®Google Scholar
• Dryhurst, S., Schneider, C. R., Kerr, J., Freeman, A. L. J., Recchia, G., van der Bles, A. M., … van der Linden, S. (2020). Risk perceptions of COVID-19 around the world. Journal of Risk Research, 23(7-8), 994–1006. doi:10.1080/13669877.2020.1758193
   Web of Science ®Google Scholar
• Evans, J. R., & Lindsay, W. M. (2002). The management and control of quality (Vol. 5, pp. 115–128). Cincinnati, OH: South-western.
   Google Scholar
• Fenich, G. G., & Hashimoto, K. (2005). Casinos and conventions: Strange bedfellows. Journal of Convention & Event Tourism, 6(1–2), 63–79. doi:10.1300/J452v06n01_05
   Google Scholar
• 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:10.1177/002224378101800104
   Web of Science ®Google Scholar
• Friedman, S. A. (2002). Ten steps to a successful trade show. Marketing Health Services, 22(1), 31–32.
   PubMedGoogle Scholar
• Goodman, L. A. (1961). Snowball sampling. The Annals of Mathematical Statistics, 32(1), 148–170. doi:10.1214/aoms/1177705148
   Google Scholar
• Gupta, A., & Arora, N. (2017). Understanding determinants and barriers of mobile shopping adoption using behavioral reasoning theory. Journal of Retailing and Consumer Services, 36(1), 1–7. doi:10.1016/j.jretconser.2016.12.012
   Google Scholar
• Haugtvedt, C. P., Petty, R. E., & Cacioppo, J. T. (1992). Need for cognition and advertising: Understanding the role of personality variables in consumer behavior. Journal of Consumer Psychology, 1(3), 239–260. doi:10.1016/S1057-7408(08)80038-1
   Google Scholar
• Huang, K., Lee, Y., & Wang, R. (1999). Quality information and knowledge. Upper Saddle River, NJ: Prentice Hall.
   Google Scholar
• Ifinedo, P. (2012). Understanding information systems security policy compliance: An integration of the theory of planned behavior and the protection motivation theory. Computers & Security, 31(1), 83–95. doi:10.1016/j.cose.2011.10.007
   Web of Science ®Google Scholar
• Islam, M. A., & Daud, K. A. K. (2011). Factors that influence customers’ buying intention on shopping online. International Journal of Marketing Studies, 3(1), 128.
   Google Scholar
• IT & CMA. (2021). Top 12 MICE business events destinations in Asia to look out for in 2022. Retrieved from https://itcma.com/blog/mice-events-picks/top-12-mice-business-events-destinations-in-asia-to-look-out-for-in-2022/.
   Google Scholar
• Jin, B., & Kang, J. H. (2011). Purchase intention of Chinese consumers toward a US apparel brand: A test of a composite behavior intention model. Journal of Consumer Marketing, 28(3), 187–199. doi:10.1108/07363761111127617
   Google Scholar
• Jung, M. (2005). Determinants of exhibition service quality as perceived by attendees. Journal of Convention & Event Tourism, 7(3–4), 85–98. doi:10.1300/J452v07n03_05
   Google Scholar
• Juran, J. M. (1992). Juran on quality by design: The new steps for planning quality into goods and services. New York: Simon and Schuster.
   Google Scholar
• Kang, J. W., & Namkung, Y. (2019). The information quality and source credibility matter in customers’ evaluation toward food O2O commerce. International Journal of Hospitality Management, 78, 189–198. doi:10.1016/j.ijhm.2018.10.011
   Web of Science ®Google Scholar
• Kemp, S. (2022). Digital 2022: Global overview report - datareportal – global digital insights. DataReportal. Retrieved from https://datareportal.com/reports/digital-2022-global-overview-report.
   Google Scholar
• Kim, S. S., Chon, K., & Chung, K. Y. (2003). Convention industry in South Korea: An economic impact analysis. Tourism Management, 24(5), 533–541. doi:10.1016/S0261-5177(03)00006-2
   Web of Science ®Google Scholar
• Kim, M. J., Chung, N., Lee, C. K., & Preis, M. W. (2016). Dual-route of persuasive communications in mobile tourism shopping. Telematics and Informatics, 33(2), 293–308. doi:10.1016/j.tele.2015.08.009
   Web of Science ®Google Scholar
• Kim, E. E. K., Seo, K., & Choi, Y. (2022). Compensatory travel post COVID-19: Cognitive and emotional effects of risk perception. Journal of Travel Research, 61(8), 1895–1909. doi:10.1177/00472875211048930
   Web of Science ®Google Scholar
• Kim, S. S., Sun, H., & Ap, J. (2008). Is there competition in the exhibition market in Asia? Analysis of the positioning of major Asian exhibition host cities. Asia Pacific Journal of Tourism Research, 13(3), 205–227. doi:10.1080/10941660802280299
   Google Scholar
• Kock, F., Berbekova, A., & Assaf, A. G. (2021). Understanding and managing the threat of common method bias: Detection, prevention and control. Tourism Management, 86, 104330. doi:10.1016/j.tourman.2021.104330
   Web of Science ®Google Scholar
• Langford, I. H. (2002). An existential approach to risk perception. Risk Analysis : An Official Publication of the Society for Risk Analysis, 22(1), 101–120. doi:10.1111/0272-4332.t01-1-00009
   PubMed Web of Science ®Google Scholar
• Law, R. (2006). The perceived impact of risks on travel decisions. International Journal of Tourism Research, 8(4), 289–300. doi:10.1002/jtr.576
   Google Scholar
• Lee, C. K., Lee, M., & Yoon, S. H. (2013). Estimating the economic impact of convention and exhibition businesses, using a regional input–output model: A case study of the Daejeon Convention Center in South Korea. Asia Pacific Journal of Tourism Research, 18(4), 330–353. doi:10.1080/10941665.2012.658414
   Web of Science ®Google Scholar
• Lee, Y. W., Strong, D. M., Kahn, B. K., & Wang, R. Y. (2002). AIMQ: A methodology for information quality assessment. Information & Management, 40(2), 133–146. doi:10.1016/S0378-7206(02)00043-5
   Web of Science ®Google Scholar
• Lee, D. P., & Palakurthi, R. (2013). Marketing strategy to increase exhibition attendance through controlling and eliminating leisure constraints. Event Management, 17(4), 323–336. doi:10.3727/152599513X13708863378114
   Google Scholar
• Lee, Y., & Koo, J. (2016). Can a celebrity serve as an issue-relevant argument in the elaboration likelihood model? Psychology & Marketing, 33(3), 195–208. doi:10.1002/mar.20865
   Web of Science ®Google Scholar
• Lee, M. J., Yeung, S., & Dewald, B. (2010). An exploratory study examining the determinants of attendance motivations as perceived by attendees at Hong Kong exhibitions. Journal of Convention & Event Tourism, 11(3), 195–208. doi:10.1080/15470148.2010.507135
   Google Scholar
• Leong, A. M. W. (2007). Macau MICE tourism with a closer review of the Las Vegas and Atlantic City experiences. Journal of Macau University of Science and Technology, 1(2), 55–70.
   Google Scholar
• Li, C. Y. (2013). Persuasive messages on information system acceptance: A theoretical extension of elaboration likelihood model and social influence theory. Computers in Human Behavior, 29(1), 264–275. doi:10.1016/j.chb.2012.09.003
   Web of Science ®Google Scholar
• Lichtenstein, D. R., & Bearden, W. O. (1989). Contextual influences on perceptions of merchant-supplied reference prices. Journal of Consumer Research, 16(1), 55–66. doi:10.1086/209193
   Web of Science ®Google Scholar
• Lin, C. T., & Lin, C. W. (2013). Exhibitor perspectives of exhibition service quality. Journal of Convention & Event Tourism, 14(4), 293–308. doi:10.1080/15470148.2013.837020
   Google Scholar
• Liu, X., Seevers, R., Gu, Z., & Yang, X. (2020, December). Smart MICE: Definitions, foundations and development. 2020 7th International Conference on Information Science and Control Engineering (ICISCE) (pp. 1307–1311), Changsha, China.
   Google Scholar
• Lord, K. R., Lee, M. S., & Sauer, P. L. (1995). The combined influence hypothesis: Central and peripheral antecedents of attitude toward the ad. Journal of Advertising, 24(1), 73–85. doi:10.1080/00913367.1995.10673469
   Web of Science ®Google Scholar
• Mak, B., Schmitt, B. H., & Lyytinen, K. (1997). User participation in knowledge update of expert systems. Information & Management, 32(2), 55–63. doi:10.1016/S0378-7206(96)00010-9
   Web of Science ®Google Scholar
• Malaysiakini. (2022, April 24). Malaysiakini Covid-19 (April 23): 5,624 new cases, 9 deaths. Malaysiakini. Retrieved from https://www.malaysiakini.com/news/619054.
   Google Scholar
• McCartney, G. (2008). The CAT (casino tourism) and the MICE (meetings, incentives, conventions, exhibitions): Key development considerations for the convention and exhibition industry in Macao. Journal of Convention & Event Tourism, 9(4), 293–308. doi:10.1080/15470140802493380
   Google Scholar
• McClave, J., & Benson, P. (1992). A first course in business statistics (5th ed.). New York, NY: Macmillan.
   Google Scholar
• Meetings & Conventions Asia. (2020, January 3). Value of global mice industry projected to hit US$1.4 trillion in 2025. Retrieved from https://www.meetings-conventions-asia.com/News/Industry-Reports/Value-of-global-MICE-industry-projected-to-hit-US14-trillion-in-2025.
   Google Scholar
• Meng, B., & Choi, K. (2019). Tourists’ intention to use location-based services (LBS): Converging the theory of planned behavior (TPB) and the elaboration likelihood model (ELM). International Journal of Contemporary Hospitality Management, 31(8), 3097–3115. doi:10.1108/IJCHM-09-2018-0734
   Web of Science ®Google Scholar
• Mitchell, V. W. (1999). Consumer perceived risk: Conceptualisations and models. European Journal of Marketing, 33(1/2), 163–195. doi:10.1108/03090569910249229
   Google Scholar
• Morris, J. D., Woo, C., & Singh, A. J. (2005). Elaboration likelihood model: A missing intrinsic emotional implication. Journal of Targeting, Measurement and Analysis for Marketing, 14(1), 79–98. doi:10.1057/palgrave.jt.5740171
   Google Scholar
• Nehls, K. (2022). International visitors to Las Vegas: A 10-year economic and cultural analysis of high-growth markets. In Handbook of research on urban tourism, viral society, and the impact of the COVID-19 pandemic (pp. 144–162). Pennsylvania, United States: IGI Global. doi:10.4018/978-1-6684-3369-0.ch008
   Google Scholar
• Neuburger, L., & Egger, R. (2021). Travel risk perception and travel behaviour during the COVID-19 pandemic 2020: A case study of the DACH region. Current Issues in Tourism, 24(7), 1003–1016. doi:10.1080/13683500.2020.1803807
   Web of Science ®Google Scholar
• Nunnally. (1978). Psychometric theory. New York, NY: MacBraw-Hill.
   Google Scholar
• Ohanian, R. (1990). Construction and validation of a scale to measure celebrity endorsers’ perceived expertise, trustworthiness, and attractiveness. Journal of Advertising, 19(3), 39–52. doi:10.1080/00913367.1990.10673191
   Web of Science ®Google Scholar
• Pang, H. (2021). Identifying associations between mobile social media users’ perceived values, attitude, satisfaction, and eWOM engagement: The moderating role of affective factors. Telematics and Informatics, 59, 101561. doi:10.1016/j.tele.2020.101561
   Web of Science ®Google Scholar
• Parayitam, S., Kakumani, L., & Muddangala, N. B. (2020). Perceived risk as a moderator in the relationship between perception of celebrity endorsement and buying behavior: Evidence from rural consumers of India. Journal of Marketing Theory and Practice, 28(4), 521–540. doi:10.1080/10696679.2020.1795687
   Web of Science ®Google Scholar
• Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. In Communication and persuasion (pp. 1–24). New York, NY: Springer.
   Google Scholar
• Pritchett, B., Pritchett, T. K., & Kotler, P. (2003). Test item file [to accompany Philip Kotler], marketing management. Upper Saddle River, New Jersey, United States: Prentice Hall.
   Google Scholar
• Rahman, B. S. S. R. (2019). Malaysia aims to become a key MICE destination. Tourism – Gulf News. Retrieved from https://gulfnews.com/business/tourism/malaysia-aims-to-become-a-key-mice-destination-1.332954.
   Google Scholar
• Richard, M. O., Chebat, J. C., Yang, Z., & Putrevu, S. (2010). A proposed model of online consumer behavior: Assessing the role of gender. Journal of Business Research, 63(9–10), 926–934. doi:10.1016/j.jbusres.2009.02.027
   Web of Science ®Google Scholar
• Rittichainuwat, B., Laws, E., Maunchontham, R., Rattanaphinanchai, S., Muttamara, S., Mouton, K., … Suksai, C. (2020). Resilience to crises of Thai MICE stakeholders: A longitudinal study of the destination image of Thailand as a MICE destination. Tourism Management Perspectives, 35, 100704. doi:10.1016/j.tmp.2020.100704
   PubMed Web of Science ®Google Scholar
• Seraphin, H. (2021). COVID-19: An opportunity to review existing grounded theories in event studies. Journal of Convention & Event Tourism, 22(1), 3–35. doi:10.1080/15470148.2020.1776657
   Web of Science ®Google Scholar
• Scholtz, S. E. (2021). Sacrifice is a step beyond convenience: A review of convenience sampling in psychological research in Africa. SA Journal of Industrial Psychology, 47(0), a1837. doi:10.4102/sajip.v47i0.1837
   Google Scholar
• Singapore Business Review. (2021, June 3). Asia Pacific’s mice revenue hit $229B in 2018. Retrieved from https://sbr.com.sg/hotels-tourism/asia/asia-pacifics-mice-revenue-hit-229b-in-2018.
   Google Scholar
• Susmann, M. W., Xu, M., Clark, J. K., Wallace, L. E., Blankenship, K. L., Philipp-Muller, A. Z., … Petty, R. E. (2022). Persuasion amidst a pandemic: Insights from the Elaboration Likelihood Model. European Review of Social Psychology, 33(2), 323–359. doi:10.1080/10463283.2021.1964744
   Web of Science ®Google Scholar
• Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information Systems Research, 14(1), 47–65. doi:10.1287/isre.14.1.47.14767
   Web of Science ®Google Scholar
• Tien, D. H., Rivas, A. A. A., & Liao, Y. K. (2019). Examining the influence of customer-to-customer electronic word-of-mouth on purchase intention in social networking sites. Asia Pacific Management Review, 24(3), 238–249. doi:10.1016/j.apmrv.2018.06.003
   Web of Science ®Google Scholar
• Tseng, S. Y., & Wang, C. N. (2016). Perceived risk influence on dual-route information adoption processes on travel websites. Journal of Business Research, 69(6), 2289–2296. doi:10.1016/j.jbusres.2015.12.044
   Web of Science ®Google Scholar
• Ujang, U., & Azri, S. (2022). Individual mobility pattern in Malaysia during COVID-19 Recovery Movement Control Order partial lockdown. Geo : geography and Environment, 9(1), e00113. doi:10.1002/geo2.113
   PubMedGoogle Scholar
• Wang, P. (2015). Exploring the influence of electronic word-of-mouth on tourists’ visit intention: A dual process approach. Journal of Systems and Information Technology, 17(4), 381–395. doi:10.1108/JSIT-04-2015-0027
   Google Scholar
• Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 12(4), 5–33. doi:10.1080/07421222.1996.11518099
   Google Scholar
• Wu, H. C., Cheng, C. C., & Ai, C. H. (2016). A study of exhibition service quality, perceived value, emotion, satisfaction, and behavioral intentions. Event Management, 20(4), 565–591. doi:10.3727/152599516X14745497664514
   Google Scholar
• Xinhua. (2022, April 23). Retrieved from http://www.news.cn/politics/2022-04/24/c_1128589796.htm.
   Google Scholar
• Yang, S. M., & Kim, H. G. (2016). The influence of the direction of online word-of-mouth information on usefulness of information and purchase intention: Focusing on moderating effect involvement. In KODISA ICBE (International Conference on Business and Economics) (pp. 545–546).
   Google Scholar
• Yeo, V. C. S., Goh, S. K., & Rezaei, S. (2017). Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services. Journal of Retailing and Consumer Services, 35(2017), 150–162. doi:10.1016/j.jretconser.2016.12.013
   Google Scholar
• Yoo, J., & Weber, K. (2005). Progress in convention tourism research. Journal of Hospitality & Tourism Research, 29(2), 194–222. doi:10.1177/1096348004272177
   Google Scholar
• Yoo, C. W., Goo, J., Huang, C. D., Nam, K., & Woo, M. (2017). Improving travel decision support satisfaction with smart tourism technologies: A framework of tourist elaboration likelihood and self-efficacy. Technological Forecasting and Social Change, 123, 330–341. doi:10.1016/j.techfore.2016.10.071
   Web of Science ®Google Scholar
• Zheng, D., Luo, Q., & Ritchie, B. W. (2021). Afraid to travel after COVID-19? Self-protection, coping and resilience against pandemic ‘travel fear’. Tourism Management, 83, 104261. doi:10.1016/j.tourman.2020.104261
   Web of Science ®Google Scholar