Tourist Behavior and Sustainable Tourism Policy Planning in the COVID-19 Era: Insights from Thailand
Abstract
:1. Introduction
2. Literature Review
2.1. Components of Tourism Potential
- Accessibility is an essential component in facilitating the movement of tourists to their destinations. Journeys can be divided into land, waterway, and air modes of transportation, with a focus on linking tourist attractions with the movement of tourists, such as from airports, cities, train stations, bus stations, and highway networks [43,44,45];
- Accommodation is an essential component for tourists. Hotels may be available at a travel destination or as accommodation during a travel trip. There are different accommodation types to choose from, such as hotels, resorts, motels, hostels, homestays, lodges, and inns, depending on the purpose and budget of an individual’s trip [43,46];
- Attractions are places that attract tourists and influence their travel decisions. Attractions can be divided into natural and cultural resources. However, nowadays, many forms of tourism have emerged due to changing tourist behavior and unique travel needs, resulting in specific forms of tourism such as health tourism, creative tourism, community-based tourism, or event tourism [43,47];
- Activities relate to a traveler’s travel experience, depending on the purpose of the traveler’s trip. Experiences can be divided into two types: active and passive experiences [43];
2.2. The Concept of Tourism Logistics Efficiency
2.3. The Impact of the COVID-19 Pandemic on Travel and Tourism
3. Methodology
3.1. Data Collection
3.2. Participants
3.3. Descriptive Statistics
- Accessibility consists of three variables: P1, P2, and P3.
- Accommodation consists of two variables: P4 and P5.
- Attractions consists of three variables: P6, P7, and P8.
- Activities consists of two variables: P9 and P10.
- Amenities consists of two variables: P11 and P12.
- Physical flow consists of four variables: E1, E2, E3, and E4.
- Information flow consists of three variables: E5, E6, and E7.
- Financial flow consists of two variables: E8 and E9.
- COVID-19 effect on tourism potential consists of three variables: CP1, CP2, and CP3.
- COVID-19 effect on logistics efficiency consists of three variables: CE1, CE2, and CE3.
3.4. Pearson Correlation Coefficients
4. Results
- First-order confirmatory factor analysis as a measurement model;
- Second-order confirmatory factor analysis to find the overall relationship of each component;
- Path analysis to study whether the relationships between elements are relevant.
4.1. Measurement Model
4.2. Second-Order Confirmatory Factor Analysis
4.3. Indicator Reliability
4.4. Convergent Validity
4.5. Discriminant Validity
4.6. Model Fit Indices
4.7. Coefficients of Structural Paths
5. Conclusions and Policy implications
5.1. Conclusions
- Influence of Tourism Potential on Travel Decisions
- Influence of Tourism Logistics Efficiency on Travel Decisions
- Influence of COVID-19 effect on Tourism Potential on Travel Decisions
- Influence of COVID-19 effect on Logistics Efficiency on Travel Decisions
5.2. Policy Implications
5.3. Limitations and Future Research Directions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Wut, T.M.; Xu, J.; Wong, S.M. Crisis Management Research (1985–2020) in the Hospitality and Tourism Industry: A Review and Research Agenda. Tour. Manag. 2021, 85, 104307. [Google Scholar] [CrossRef] [PubMed]
- Yin, J.; Ni, Y. COVID-19 Event Strength, Psychological Safety, and Avoidance Coping Behaviors for Employees in the Tourism Industry. J. Hosp. Tour. Manag. 2021, 47, 431–442. [Google Scholar] [CrossRef]
- Mach, L.; Ponting, J. Establishing a Pre-COVID-19 Baseline for Surf Tourism: Trip Expenditure and Attitudes, Behaviors and Willingness to Pay for Sustainability. Ann. Tour. Res. Empir. Insights 2021, 2, 100011. [Google Scholar] [CrossRef]
- Wong, J.W.C.; Lai, I.K.W. The Mechanism Influencing the Residents’ Support of the Government Policy for Accelerating Tourism Recovery under COVID-19. J. Hosp. Tour. Manag. 2022, 52, 219. [Google Scholar] [CrossRef]
- Škare, M.; Soriano, D.R.; Porada-Rochoń, M. Impact of COVID-19 on the Travel and Tourism Industry. Technol. Forecast. Soc. Change 2021, 163, 120469. [Google Scholar] [CrossRef]
- Yang, Y.; Altschuler, B.; Liang, Z.; Li, X. (Robert) Monitoring the Global COVID-19 Impact on Tourism: The COVID-19 tourism Index. Ann. Tour. Res. 2021, 90, 103120. [Google Scholar] [CrossRef]
- Pardo, C.; Ladeiras, A. Covid-19 “Tourism in Flight Mode”: A Lost Opportunity to Rethink Tourism–towards a More Sustainable and Inclusive Society. Worldw. Hosp. Tour. Themes 2020, 12, 671–678. [Google Scholar] [CrossRef]
- Qiu, R.T.R.; Park, J.; Li, S.N.; Song, H. Social Costs of Tourism during the COVID-19 Pandemic. Ann. Tour. Res. 2020, 84, 102994. [Google Scholar] [CrossRef]
- Chowdhury, P.; Paul, S.K.; Kaisar, S.; Moktadir, M.A. COVID-19 Pandemic Related Supply Chain Studies: A Systematic Review. Transp. Res. Part E Logist. Transp. Rev. 2021, 148, 102271. [Google Scholar] [CrossRef]
- Butler, R. Tourism–Resilient but Vulnerable as “the Times They Are a Changing” in the “New Normality”. Worldw. Hosp. Tour. Themes 2020, 12, 663–670. [Google Scholar] [CrossRef]
- Sharma, G.D.; Thomas, A.; Paul, J. Reviving Tourism Industry Post-COVID-19: A Resilience-Based Framework. Tour. Manag. Perspect. 2021, 37, 100786. [Google Scholar] [CrossRef] [PubMed]
- Setthachotsombut, N.; Sua-iam, G. Tourism Value Chain Management and Tourism Logistics in Ubon Ratchathani Province, Northeast Thailand. African J. Hosp. Tour. Leis. 2020, 9, 1–12. [Google Scholar]
- Tiwari, P.; Chowdhary, N. Has COVID-19 Brought a Temporary Halt to Overtourism? Turyzm/Tourism 2021, 31, 89–93. [Google Scholar] [CrossRef]
- Eichelberger, S.; Heigl, M.; Peters, M.; Pikkemaat, B. Exploring the Role of Tourists: Responsible Behavior Triggered by the COVID-19 Pandemic. Sustainability 2021, 13, 5774. [Google Scholar] [CrossRef]
- Sumanapala, D.; Wolf, I.D. The Changing Face of Wildlife Tourism during the COVID-19 Pandemic: An Opportunity to Strive towards Sustainability? Curr. Issues Tour. 2021, 25, 357–362. [Google Scholar] [CrossRef]
- Patterson Edward, J.K.; Jayanthi, M.; Malleshappa, H.; Immaculate Jeyasanta, K.; Laju, R.L.; Patterson, J.; Diraviya Raj, K.; Mathews, G.; Marimuthu, A.S.; Grimsditch, G. COVID-19 Lockdown Improved the Health of Coastal Environment and Enhanced the Population of Reef-Fish. Mar. Pollut. Bull. 2021, 165, 112124. [Google Scholar] [CrossRef]
- Castanho, R.A.; Couto, G.; Sousa, Á.; Pimentel, P.; Batista, M.D.G. Assessing the Impacts of the COVID-19 Pandemic over the Azores Region’s Touristic Companies. Sustainability 2021, 13, 9647. [Google Scholar] [CrossRef]
- UNWTO 2020: Worst Year in Tourism History with 1 Billion Fewer International Arrivals. Available online: https://www.unwto.org/news/2020-worst-year-in-tourism-history-with-1-billion-fewer-international-arrivals (accessed on 25 February 2023).
- Marujo, N.; Borges, M.D.R.; Serra, J.; Coelho, R. Strategies for Creative Tourism Activities in Pandemic Contexts: The Case of the ‘Saídas de Mestre’ Project. Sustainability 2021, 13, 10654. [Google Scholar] [CrossRef]
- Gonçalves, A. What Is Staycation: Discover the Latest Trend in Sustainable Tourism. Available online: https://youmatter.world/en/staycation-definition-stay-vacations-sustainable/ (accessed on 25 February 2023).
- Wong, I.K.A.; Lin, Z.; Kou, I.T.E. Restoring Hope and Optimism through Staycation Programs: An Application of Psychological Capital Theory. J. Sustain. Tour. 2023, 31, 91–110. [Google Scholar] [CrossRef]
- Marome, W.; Shaw, R. COVID-19 Response in Thailand and Its Implications on Future Preparedness. Int. J. Environ. Res. Public Health 2021, 18, 1089. [Google Scholar] [CrossRef]
- Amar, M.Y.; Syariati, A.; Ridwan, R.; Parmitasari, R.D.A. Indonesian Hotels’ Dynamic Capability under the Risks of COVID-19. Risks 2021, 9, 194. [Google Scholar] [CrossRef]
- Srivastava, P.R.; Sengupta, K.; Kumar, A.; Biswas, B.; Ishizaka, A. Post-Epidemic Factors Influencing Customer’s Booking Intent for a Hotel or Leisure Spot: An Empirical Study. J. Enterp. Inf. Manag. 2021, 35, 78–99. [Google Scholar] [CrossRef]
- Sörensson, A.; von Friedrichs, Y. An Importance-Performance Analysis of Sustainable Tourism: A Comparison between International and National Tourists. J. Destin. Mark. Manag. 2013, 2, 14–21. [Google Scholar] [CrossRef]
- Du, J.; Rakha, H.A.; Filali, F.; Eldardiry, H. COVID-19 Pandemic Impacts on Traffic System Delay, Fuel Consumption and Emissions. Int. J. Transp. Sci. Technol. 2021, 10, 184–196. [Google Scholar] [CrossRef]
- Smith, L.V.; Tarui, N.; Yamagata, T. Assessing the Impact of COVID-19 on Global Fossil Fuel Consumption and CO2 Emissions. Energy Econ. 2021, 97, 105170. [Google Scholar] [CrossRef]
- TIME STAFF Tourists Force Closure of Thailand’s “Most Beautiful” Island|Time. Available online: https://time.com/4336737/thailand-island-koh-tachai-similan-phangnga-ranong-tourism-travelers/ (accessed on 4 March 2023).
- Archer, D. Thailand Shifts away from Mass Tourism|Destination Think. Available online: https://destinationthink.com/blog/thailand-shifts-away-mass-tourism/ (accessed on 4 March 2023).
- Chi, C.G.Q.; Qu, H. Examining the Structural Relationships of Destination Image, Tourist Satisfaction and Destination Loyalty: An Integrated Approach. Tour. Manag. 2008, 29, 624–636. [Google Scholar] [CrossRef]
- Kozak, M.; Rimmington, M. Measuring Tourist Destination Competitiveness: Conceptual Considerations and Empirical Findings. Int. J. Hosp. Manag. 1999, 18, 273–283. [Google Scholar] [CrossRef]
- Praditrod, C. Components of Tourist Attractions and Tourism Motivation Affecting to Working People’s Decision Making Travelling in Vicinity Areas; Bangkok University: Bangkok, Thailand, 2014. [Google Scholar]
- Kumplew, V.; Chartrungruang, B.; Tarapituxwong, S. Factors Affecting Decisions to Participate in Adventure Travel of Thai and Foreign Tourists. Phikanatesan 12AD 2020, 12, 140–148. [Google Scholar]
- Rattanaphan, P. Factors Affectinng the Decision of Tourists to Visit Songkhla. Prasit Ratt. 2016, 30, 168–180. [Google Scholar]
- Sittilert Khanapojs Logistic and Tourism in the Present. Lib. Arts Rev. 2011, 6, 1–14.
- Lumsdon, L.; Page, S. Progress in Transport and Tourism Research: Reformulating the Transport-Tourism Interface and Future Research Agendas; Routledge: Oxfordshire, UK, 2007; ISBN 9780080519401. [Google Scholar]
- Ketter, E.; Avraham, E. #StayHome Today so We Can #TravelTomorrow: Tourism Destinations’ Digital Marketing Strategies during the Covid-19 Pandemic. J. Travel Tour. Mark. 2021, 38, 819–832. [Google Scholar] [CrossRef]
- Suriya, K. Conceptual Framework of Tourism Logistics. Available online: http://www.sri.cmu.ac.th/~gms/tour-732ism/index.php?ge=topicdetall&webId=185 (accessed on 17 January 2023.).
- Aungthong, A. The Effects of Perceived Value from Tourist Attractions and Logistics Management on Satisfaction and Chiang Mai Tourism Loyalty. J. Manag. Sci. Ubon Ratchathani Univ. 2012, 1, 29–44. [Google Scholar]
- Chaichan, T. Tourism Logistics Management for Wang Nam Khiew District in Nakhon Ratchasima Province. Res. Rep. Suranaree Univ. Technol. 2012, 16, 17–33. [Google Scholar]
- Liang, N.; Corbitt, B.; Peszynski, K. Impacts of Logistics Service Performance through IT on Overall Tourist Satisfaction and Loyalty; Springer: Berlin/Heidelberg, Germany, 2008. [Google Scholar]
- Middleton, V.T.C.; Clarke, J.R. Marketing in Travel and Tourism; Routledge: Oxfordshire, UK, 2012; ISBN 9780080511108. [Google Scholar]
- Dickman, S. Tourism: An Introductory Text, 3rd ed.; Hodder Education: Rydalmere, Australia, 1997; ISBN 0733606776. [Google Scholar]
- Basuki Joewono, T.; Kubota, H.; Basuki Joewono, T.; Kubota, H. Paratransit Service in Indonesia: User Satisfaction and Future Choice. Transp. Plan. Technol. 2007, 31, 325–345. [Google Scholar] [CrossRef]
- Joewono, T.B.; Kubota, H. User Satisfaction with Paratransit in Competition with Motorization in Indonesia: Anticipation of Future Implications. Transportation 2007, 34, 337–354. [Google Scholar] [CrossRef]
- Murphy, P.; Pritchard, M.P.; Smith, B. The Destination Product and Its Impact on Traveller Perceptions. Tour. Manag. 2000, 21, 43–52. [Google Scholar] [CrossRef]
- Chansuk, C.; Arreeras, T.; Chiangboon, C.; Phonmakham, K.; Chotikool, N.; Buddee, R.; Pumjampa, S.; Yanasoi, T.; Arreeras, S. Using Factor Analyses to Understand the Post-Pandemic Travel Behavior in Domestic Tourism through a Questionnaire Survey. Transp. Res. Interdiscip. Perspect. 2022, 16, 100691. [Google Scholar] [CrossRef]
- Camilleri, M.A. The Tourism Industry: An Overview. In Tourism Economics and the Airline Product; Springer Nature: Berlin, Germany, 2018; pp. 3–27. [Google Scholar] [CrossRef]
- Ozturk, A.B.; Qu, H. The Impact of Destination Images on Tourists’ Perceived Value, Expectations, and Loyalty. J. Qual. Assur. Hosp. Tour. 2008, 9, 275–297. [Google Scholar] [CrossRef]
- Allan, G.; Connolly, K.; Figus, G.; Maurya, A. Economic Impacts of COVID-19 on Inbound and Domestic Tourism. Ann. Tour. Res. Empir. Insights 2022, 3, 100075. [Google Scholar] [CrossRef]
- de Haas, M.; Faber, R.; Hamersma, M. How COVID-19 and the Dutch “intelligent Lockdown” Change Activities, Work and Travel Behaviour: Evidence from Longitudinal Data in the Netherlands. Transp. Res. Interdiscip. Perspect. 2020, 6, 100150. [Google Scholar] [CrossRef]
- Mogaji, E. Impact of COVID-19 on Transportation in Lagos, Nigeria. Transp. Res. Interdiscip. Perspect. 2020, 6, 100154. [Google Scholar] [CrossRef]
- Fenichela, E.P.; Castillo-Chavezb, C.; Ceddiac, M.G.; Chowellb, G.; Gonzalez Parrae, P.A.; Hickling, G.J.; Holloway, G.; Horan, R.; Morin, B.; Perrings, C.; et al. Adaptive Human Behavior in Epidemiological Models. Proc. Natl. Acad. Sci. USA 2011, 108, 6306–6311. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sharangpani, R.; Boulton, K.E.; Wells, E.; Kim, C. Attitudes and Behaviors of International Air Travelers toward Pandemic Influenza. J. Travel Med. 2011, 18, 203–208. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Leggat, P.A.; Brown, L.H.; Aitken, P.; Speare, R. Level of Concern and Precaution Taking Among Australians Regarding Travel During Pandemic (H1N1) 2009: Results From the 2009 Queensland Social Survey. J. Travel Med. 2010, 17, 291–295. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hotle, S.; Murray-Tuite, P.; Singh, K. Influenza Risk Perception and Travel-Related Health Protection Behavior in the US: Insights for the Aftermath of the COVID-19 Outbreak. Transp. Res. Interdiscip. Perspect. 2020, 5, 100127. [Google Scholar] [CrossRef]
- Molloy, J.; Schatzmann, T.; Schoeman, B.; Tchervenkov, C.; Hintermann, B.; Axhausen, K.W. Observed Impacts of the COVID-19 First Wave on Travel Behaviour in Switzerland Based on a Large GPS Panel. Transp. Policy 2021, 104, 43–51. [Google Scholar] [CrossRef] [PubMed]
- Bucsky, P. Modal Share Changes Due to COVID-19: The Case of Budapest. Transp. Res. Interdiscip. Perspect. 2020, 8, 100141. [Google Scholar] [CrossRef] [PubMed]
- Hasselwander, M.; Tamagusko, T.; Bigotte, J.F.; Ferreira, A.; Mejia, A.; Ferranti, E.J.S. Building Back Better: The COVID-19 Pandemic and Transport Policy Implications for a Developing Megacity. Sustain. Cities Soc. 2021, 69. [Google Scholar] [CrossRef]
- Hara, Y.; Yamaguchi, H. Japanese Travel Behavior Trends and Change under COVID-19 State-of-Emergency Declaration: Nationwide Observation by Mobile Phone Location Data. Transp. Res. Interdiscip. Perspect. 2021, 9, 100288. [Google Scholar] [CrossRef]
- Kim, S.; Lee, S.; Ko, E.; Jang, K.; Yeo, J. Changes in Car and Bus Usage amid the COVID-19 Pandemic: Relationship with Land Use and Land Price. J. Transp. Geogr. 2021, 96, 103168. [Google Scholar] [CrossRef]
- Zhang, N.; Jia, W.; Wang, P.; Dung, C.H.; Zhao, P.; Leung, K.; Su, B.; Cheng, R.; Li, Y. Changes in Local Travel Behaviour before and during the COVID-19 Pandemic in Hong Kong. Cities 2021, 112, 103139. [Google Scholar] [CrossRef] [PubMed]
- Xin, M.; Shalaby, A.; Feng, S.; Zhao, H. Impacts of COVID-19 on Urban Rail Transit Ridership Using the Synthetic Control Method. Transp. Policy 2021, 111, 1–16. [Google Scholar] [CrossRef] [PubMed]
- Shang, W.L.; Chen, J.; Bi, H.; Sui, Y.; Chen, Y.; Yu, H. Impacts of COVID-19 Pandemic on User Behaviors and Environmental Benefits of Bike Sharing: A Big-Data Analysis. Appl. Energy 2021, 285, 116429. [Google Scholar] [CrossRef] [PubMed]
- Teixeira, J.F.; Lopes, M. The Link between Bike Sharing and Subway Use during the COVID-19 Pandemic: The Case-Study of New York’s Citi Bike. Transp. Res. Interdiscip. Perspect. 2020, 6, 100166. [Google Scholar] [CrossRef]
- Chang, H.H.; Lee, B.; Yang, F.A.; Liou, Y.Y. Does COVID-19 Affect Metro Use in Taipei? J. Transp. Geogr. 2021, 91, 102954. [Google Scholar] [CrossRef] [PubMed]
- Mützel, C.M.; Scheiner, J. Investigating Spatio-Temporal Mobility Patterns and Changes in Metro Usage under the Impact of COVID-19 Using Taipei Metro Smart Card Data. Public Transp. 2022, 14, 343–366. [Google Scholar] [CrossRef]
- Lee, C.C.; Chen, M.P. The Impact of COVID-19 on the Travel and Leisure Industry Returns: Some International Evidence. Tour. Econ. 2022, 28, 451–472. [Google Scholar] [CrossRef]
- Gutiérrez-Velasco, L.; Liébana-Presa, C.; Abella-Santos, E.; Villar-Suárez, V.; Fernández-Gutiérrez, R.; Fernández-Martínez, E. Access to Information and Degree of Community Awareness of Preventive Health Measures in the Face of COVID-19 in Spain. Healthcare 2021, 9, 104. [Google Scholar] [CrossRef]
- Shen, J.; Duan, H.; Zhang, B.; Wang, J.; Ji, J.S.; Wang, J.; Pan, L.; Wang, X.; Zhao, K.; Ying, B.; et al. Prevention and Control of COVID-19 in Public Transportation: Experience from China. Environ. Pollut. 2020, 266, 115291. [Google Scholar] [CrossRef]
- Ngonghala, C.N.; Iboi, E.; Eikenberry, S.; Scotch, M.; MacIntyre, C.R.; Bonds, M.H.; Gumel, A.B. Mathematical Assessment of the Impact of Non-Pharmaceutical Interventions on Curtailing the 2019 Novel Coronavirus. Math. Biosci. 2020, 325, 108364. [Google Scholar] [CrossRef]
- Abrahamse, W.; Steg, L.; Gifford, R.; Vlek, C. Factors Influencing Car Use for Commuting and the Intention to Reduce It: A Question of Self-Interest or Morality? Transp. Res. Part F Traffic Psychol. Behav. 2009, 12, 317–324. [Google Scholar] [CrossRef]
- Bamberg, S.; Hunecke, M.; Blöbaum, A. Social Context, Personal Norms and the Use of Public Transportation: Two Field Studies. J. Environ. Psychol. 2007, 27, 190–203. [Google Scholar] [CrossRef]
- Nordlund, A.M.; Garvill, J. Effects of Values, Problem Awareness, and Personal Norm on Willingness to Reduce Personal Car Use. J. Environ. Psychol. 2003, 23, 339–347. [Google Scholar] [CrossRef]
- De Groot, J.I.M.; Steg, L.; Poortinga, W. Values, Perceived Risks and Benefits, and Acceptability of Nuclear Energy. Risk Anal. 2013, 33, 307–317. [Google Scholar] [CrossRef] [PubMed]
- Mehdizadeh, M.; Mamdoohi, A.R.; Nordfjaern, T. Walking Time to School, Children’s Active School Travel and Their Related Factors. J. Transp. Health 2017, 6, 313–326. [Google Scholar] [CrossRef]
- Abdullah, M.; Dias, C.; Muley, D.; Shahin, M. Exploring the Impacts of COVID-19 on Travel Behavior and Mode Preferences. Transp. Res. Interdiscip. Perspect. 2020, 8, 100255. [Google Scholar] [CrossRef]
- Shamshiripour, A.; Rahimi, E.; Shabanpour, R.; Mohammadian, A. (Kouros) How Is COVID-19 Reshaping Activity-Travel Behavior? Evidence from a Comprehensive Survey in Chicago. Transp. Res. Interdiscip. Perspect. 2020, 7, 100216. [Google Scholar] [CrossRef] [PubMed]
- Zheng, D.; Luo, Q.; Ritchie, B.W. Afraid to Travel after COVID-19? Self-Protection, Coping and Resilience against Pandemic 716 “Travel Fear”. Tour. Manag. 2021, 83, 104261. [Google Scholar] [CrossRef]
- Iaquinto, B.L. Tourist as Vector: Viral Mobilities of COVID-19. Dialogues Hum. Geogr. 2020, 10, 174–177. [Google Scholar] [CrossRef]
- Das, P.; Singh, A.K.; Maitra, S. Effect of COVID-19 on Recreational Trips to Tourist Destination–An Indian Context. Asian Transp. Stud. 2022, 8, 100088. [Google Scholar] [CrossRef]
- Likert, R. A Technique for the Measurement of Attitudes. Archives of Psychology; Scientific Research: New York, NY, USA, 1985. [Google Scholar]
- Kline, R.B. Principles and Practice of Structural Equation Modeling, 4th ed.; The Guilford Press: New York, NY, USA, 2011; ISBN 9781462523351. [Google Scholar]
- George, D.; Mallery, P. SPPS for Windows Step by Step: A Simple Guide and Reference: 14.0 Update; Pearson A and B; SPPPS: Tokyo, Japan, 2007; ISBN 0205515851. [Google Scholar]
- Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E. Multivariate Data Analysis; Pearson College Div: New York, NY, USA, 2010; p. 785. [Google Scholar]
- Tabachnick, B.G.; Fidell, L.S. Using Multivariate Statistics, 6th ed.; New York Harper Row: New York, NY, USA, 2012; p. 1024. [Google Scholar]
- Friendly, M. Friendly Corrgrams: Exploratory Displays for Correlation Matrices. Am. Stat. 2002, 56, 316–324. [Google Scholar] [CrossRef]
- Ngeoywijit, S.; Kruasom, T.; Ugsornwongand, K.K.; Pitakaso, R.; Sirirak, W.; Nanthasamroeng, N.; Kotmongkol, T.; Srichok, T.; Khonjun, S.; Kaewta, C. Open Innovations for Tourism Logistics Design: A Case Study of a Smart Bus Route Design for the Medical Tourist in the City of Greater Mekong Subregion. J. Open Innov. Technol. Mark. Complex. 2022, 8, 173. [Google Scholar] [CrossRef]
- Taber, K.S. The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education. Res. Sci. Educ. 2018, 48, 1273–1296. [Google Scholar] [CrossRef] [Green Version]
- Fornell, C.; Larcker, D.F. Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics. J. Mark. Res. 1981, 18, 382. [Google Scholar] [CrossRef]
- Chou, S.F.; Horng, J.S.; Sam Liu, C.H.; Lin, J.Y. Identifying the Critical Factors of Customer Behavior: An Integration Perspective of Marketing Strategy and Components of Attitudes. J. Retail. Consum. Serv. 2020, 55, 102113. [Google Scholar] [CrossRef]
- Fan, X.; Lu, J.; Qiu, M.; Xiao, X. Changes in Travel Behaviors and Intentions during the COVID-19 Pandemic and Recovery Period: A Case Study of China. J. Outdoor Recreat. Tour. 2023, 41, 100522. [Google Scholar] [CrossRef]
- Lam, L.W. Impact of Competitiveness on Salespeople’s Commitment and Performance. J. Bus. Res. 2012, 65, 1328–1334. [Google Scholar] [CrossRef]
- Peterson, M.; Minton, E.A.; Liu, R.L.; Bartholomew, D.E. Sustainable Marketing and Consumer Support for Sustainable Businsses. Sustain. Prod. Consum. 2021, 27, 157–168. [Google Scholar] [CrossRef]
- Whittaker, T.A.; Schumacker, R.E. A Beginner’s Guide to Structural Equation Modeling; Routledge: Oxfordshire, UK, 2004; ISBN 9780367477967. [Google Scholar]
- Wheaton, B.; Muthen, B.; Alwin, D.F.; Summers, G.F. Assessing Reliability and Stability in Panel Models. Sociol. Methodol. 1977, 8, 84. [Google Scholar] [CrossRef]
- Steiger, J.H. Understanding the Limitations of Global Fit Assessment in Structural Equation Modeling. Pers. Individ. Dif. 2007, 42, 893–898. [Google Scholar] [CrossRef]
- Hu, L.T.; Bentler, P.M. Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria versus New Alternatives. Struct. Equ. Model. A Multidiscip. J. 1999, 6, 1–55. [Google Scholar] [CrossRef]
- Hooper, D.; Coughlan, J.; Mullen, M. Structural Equation Modeling: Guidelines for Determining Model Fit. Electron. J. Bus. Res. Methods 2007, 6, 11426–11436. [Google Scholar]
- Anwar, M.A.; Dhir, A.; Jabeen, F.; Zhang, Q.; Siddiquei, A.N. Unconventional Green Transport Innovations in the Post-COVID-19 Era. A Trade-off between Green Actions and Personal Health Protection. J. Bus. Res. 2023, 155, 113442. [Google Scholar] [CrossRef]
- Lambert, D.M.; Stock, J.R.; Ellram, L.M. Fundamentals of Logistics Management; New York Irwin: New York, NY, USA, 1998; Volume xvii, 892p. [Google Scholar]
- Wang, Y.; Gao, Y. Travel Satisfaction and Travel Well-Being: Which Is More Related to Travel Choice Behaviour in the Post COVID-19 Pandemic? Evidence from Public Transport Travellers in Xi’an, China. Transp. Res. Part A Policy Pract. 2022, 166, 218–233. [Google Scholar] [CrossRef]
- Raja, R. Impact of COVID-19 on the Logistics Supply Chain and Tourism Industry. In Effects of COVID-19 Pandemic; Redshine Publication: Lunawada, India, 2022; pp. 1–13. ISBN 978-93-95456-71-5. [Google Scholar]
- Li, X.; Gong, J.; Gao, B.; Yuan, P. Impacts of COVID-19 on Tourists’ Destination Preferences: Evidence from China. Ann. Tour. Res. 2021, 90, 103258. [Google Scholar] [CrossRef] [PubMed]
- Hüsser, A.P.; Ohnmacht, T. A Comparative Study of Eight COVID-19 Protective Measures and Their Impact on Swiss Tourists’ Travel Intentions. Tour. Manag. 2023, 97, 104734. [Google Scholar] [CrossRef] [PubMed]
- Chen, C.M.; Jih, C.Y.; Lin, Y.C.; Hung, W.H. The Impact of Border Control Policy on Tourists’ Behaviors in Taiwan during the COVID-19 Pandemic. J. Hosp. Tour. Manag. 2022, 53, 160–164. [Google Scholar] [CrossRef]
- Israngkura, A. Marine Resource Recovery in Southern Thailand during COVID-19 and Policy Recommendations. Mar. Policy 2022, 137, 104972. [Google Scholar] [CrossRef]
- Cai, G.; Xu, L.; Gao, W. The Green B&B Promotion Strategies for Tourist Loyalty: Surveying the Restart of Chinese National Holiday Travel after COVID-19. Int. J. Hosp. Manag. 2021, 94, 102704. [Google Scholar] [CrossRef]
Questionnaire | Descriptions | Frequency (n = 943) | Percentage (%) |
---|---|---|---|
Are you ever been infected with COVID-19 | No Yes | 509 434 | 54.0 46.0 |
During the COVID-19 pandemic, are you tend to travel to nearby provinces or take short-term travel, more or not. | No Yes | 267 676 | 28.3 71.7 |
During the COVID-19 pandemic, are you more likely to use a private car/taxi than public transport. | No Yes | 39 904 | 4.1 95.9 |
The main form of travel that you preferred to use before the outbreak of COVID-19. | Private car Paratransit Public transport | 158 583 202 | 16.8 61.8 21.4 |
The main form of travel that you preferred to use after the outbreak of COVID-19. | Private car Paratransit Public transport | 356 580 7 | 37.8 61.5 0.7 |
Variables | Description | |
---|---|---|
Accessibility | P1 | Many tourist attractions are easily accessible and convenient. |
P2 | Transportation infrastructures (roads, train stations, bus stations, ports, and airports) are ready to accommodate tourists. | |
P3 | Various transportation modes are ready to support tourists (private car, rental car, public transport). | |
Accommodation | P4 | Accommodation is sufficient and can meet the needs of all groups of tourists. |
P5 | The surrounding area of the main tourist attractions is large, and quality accommodation is available. | |
Attractions | P6 | Tourist attractions are famous and popular nationally. |
P7 | Tourist attractions are rich in natural attractions. | |
P8 | Tourist attractions with exciting history, traditions, and culture. | |
Activities | P9 | Tourism activities with the local community. |
P10 | Favorite tourist activities that are popular at the national level. | |
Amenities | P11 | Tourist information center with staff to give advice. |
P12 | An application to communicate travel information such as travel routes and times, and to recommend tourist attractions or present up-to-date information. | |
Physical flow | E1 | The tourist transportation system is high-quality and punctual. |
E2 | Transportation services for people with mobility, hearing, and visual disabilities. | |
E3 | Shuttle bus service to tourist attractions. | |
E4 | A tourist attraction that supports a variety of travel formats, both public transportation and private cars. | |
Information flow | E5 | A system to inform tourists about entrance fees, fares, travel schedules, and travel times. |
E6 | A clear and easily communicated bulletin board with information on attractions and routes. | |
E7 | Manages travel information via the Internet and social networking channels with up-to-date information (travel events, exciting activities, situations in the area). | |
Financial flow | E8 | Easily book and pay for goods, travel services, and tickets through electronic pay by scanning via a QR code for Thai and foreign banks. |
E9 | Pay for goods, travel services, and tickets via foreign credit cards and cash cards. | |
The impact of COVID-19 on tourism potential (CP) | CP1 | Measures to prevent the spread of COVID-19, such as vaccination background checks, have been enforced. Temperature screening, and ATK check before entering tourist attractions. |
CP2 | Strict measures to prevent the spread of COVID-19 have been enforced when entering and leaving an area. | |
CP3 | All hotel staff are fully vaccinated against COVID-19 as per standard. | |
The impact of COVID-19 on logistics efficiency (CE) | CE1 | Safe tourist transport system with sanitary standards. |
The impact of COVID-19 on logistics efficiency (CE) | CE2 | Intensive screening of passengers before using public transport. |
The impact of COVID-19 on logistics efficiency (CE) | CE3 | Improved booking process. Pay for travel goods and services to increase the convenience of cashless payments and reduce physical contact. |
Constructs | Item | Minimum | Maximum | Mean (SD) | Skewness | Kurtosis |
---|---|---|---|---|---|---|
Tourism potential (P) | P1 | 2 | 5 | 4.02 (0.767) | −0.338 | −0.484 |
P2 | 1 | 5 | 3.98 (0.796) | −0.451 | −0.046 | |
P3 | 1 | 5 | 3.93 (0.775) | −0.407 | 0.058 | |
P4 | 1 | 5 | 3.78 (0.950) | −0.388 | −0.467 | |
P5 | 1 | 5 | 3.76 (0.834) | −0.296 | −0.175 | |
P6 | 1 | 5 | 3.61 (0.992) | −0.633 | 0.339 | |
P7 | 1 | 5 | 3.75 (0.990) | −0.811 | 0.61 | |
P8 | 1 | 5 | 3.75 (0.980) | −0.793 | 0.643 | |
P9 | 1 | 5 | 3.83 (0.865) | −0.317 | −0.118 | |
P10 | 1 | 5 | 3.81 (0.791) | −0.35 | 0.308 | |
P11 | 1 | 5 | 3.92 (0.806) | −0.337 | −0.307 | |
P12 | 1 | 5 | 4.00 (0.761) | −0.355 | −0.251 | |
Logistics efficiency I | E1 | 1 | 5 | 4.21 (0.733) | −0.518 | −0.358 |
E2 | 2 | 5 | 4.12 (0.715) | −0.319 | −0.548 | |
E3 | 2 | 5 | 4.13 (0.741) | −0.392 | −0.521 | |
E4 | 1 | 5 | 4.09 (0.768) | −0.483 | −0.134 | |
E5 | 1 | 5 | 3.80 (0.965) | −0.538 | −0.004 | |
E6 | 1 | 5 | 3.80 (0.790) | −0.258 | −0.021 | |
E7 | 1 | 5 | 3.79 (0.862) | −0.286 | −0.295 | |
E8 | 1 | 5 | 4.14 (0.721) | −0.409 | −0.294 | |
E9 | 2 | 5 | 3.98 (0.688) | −0.132 | −0.442 | |
The impact of COVID-19 on tourism potential (CP) | CP1 | 1 | 5 | 3.84 (1.236) | −0.832 | −0.393 |
CP2 | 1 | 5 | 3.52 (1.077) | −0.789 | −0.039 | |
CP3 | 1 | 5 | 3.65 (1.110) | −0.616 | −0.282 | |
The impact of COVID-19 on logistics efficiency (CE) | CE1 | 2 | 5 | 4.18 (0.728) | −0.44 | −0.52 |
CE2 | 1 | 5 | 4.13 (0.729) | −0.44 | −0.205 | |
CE3 | 1 | 5 | 3.86 (0.856) | −0.55 | 0.38 |
Construct /Factor | Variable | Loading | Cronbach’s Alpha | CR | AVE |
---|---|---|---|---|---|
Accessibility (ACCE) | P1 | 0.561 | 0.674 | 0.977 | 0.414 |
P2 | 0.759 | ||||
P3 | 0.592 | ||||
Accommodation (ACCO) | P4 | 0.684 | 0.628 | 0.972 | 0.438 |
P5 | 0.639 | ||||
Attractions (ATTR) | P6 | 0.753 | 0.820 | 0.985 | 0.523 |
P7 | 0.716 | ||||
P8 | 0.699 | ||||
Activities (ACT) | P9 | 0.819 | 0.682 | 0.974 | 0.535 |
P10 | 0.632 | ||||
Amenities (AME) | P11 | 0.697 | 0.505 | 0.952 | 0.400 |
P12 | 0.476 | ||||
Physical flow (PF) | E1 | 0.620 | 0.760 | 0.983 | 0.409 |
E2 | 0.711 | ||||
E3 | 0.645 | ||||
E4 | 0.574 | ||||
Information flow (IF) | E5 | 0.689 | 0.755 | 0.986 | 0.511 |
E6 | 0.737 | ||||
E7 | 0.718 | ||||
Financial flow (FF) | E8 | 0.714 | 0.609 | 0.961 | 0.427 |
E9 | 0.587 | ||||
COVID-19 effect on tourism potential (CP) (Cronbach’s alpha = 0.881) | CP1 | 0.839 | 0.881 | 0.786 | 0.666 |
CP2 | 0.808 | ||||
CP3 | 0.801 | ||||
COVID-19 effect on logistics efficiency (CE) (Cronbach’s alpha = 0.665) | CE1 | 0.608 | 0.665 | 0.977 | 0.403 |
CE2 | 0.680 | ||||
CE3 | 0.615 |
√AVE | ACCE | ACCO | ATTR | ACT | AME | PF | IF | FF | CP | CE |
---|---|---|---|---|---|---|---|---|---|---|
ACCE | (0.643) | |||||||||
ACCO | 0.283 ** | (0.671) | ||||||||
ATTR | 0.260 ** | 0.567 ** | (0.723) | |||||||
ACT | 0.331 ** | 0.405 ** | 0.382 ** | (0.731) | ||||||
AME | 0.382 ** | 0.445 ** | 0.377 ** | 0.344 ** | (0.597) | |||||
PF | 0.428 ** | 0.227 ** | 0.122 ** | 0.384 ** | 0.318 ** | (0.640) | ||||
IF | 0.385 ** | 0.581 ** | 0.539 ** | 0.382 ** | 0.419 ** | 0.305 ** | (0.715) | |||
FF | 0.443 ** | 0.253 ** | 0.188 ** | 0.299 ** | 0.307 ** | 0.484 ** | 0.330 ** | (0.653) | ||
CP | 0.188 ** | 0.670 ** | 0.657 ** | 0.352 ** | 0.341 ** | 0.117 ** | 0.614 ** | 0.127 ** | (0.816) | |
CE | 0.394 ** | 0.281 ** | 0.124 ** | 0.340 ** | 0.314 ** | 0.565 ** | 0.336 ** | 0.430 ** | 0.179 ** | (0.635) |
Path Relationship | Standardized Estimate | Standard Error | t-Value | Result |
---|---|---|---|---|
Tourism Potential → CP | 0.743 ** | 0.022 | 33.773 | Supported |
Tourism Logistics Efficiency → CP | 0.056 ** | 0.005 | 11.200 | Supported |
Tourism Logistics Efficiency → CE | 0.692 ** | 0.038 | 18.211 | Supported |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Srisawat, P.; Zhang, W.; Sukpatch, K.; Wichitphongsa, W. Tourist Behavior and Sustainable Tourism Policy Planning in the COVID-19 Era: Insights from Thailand. Sustainability 2023, 15, 5724. https://doi.org/10.3390/su15075724
Srisawat P, Zhang W, Sukpatch K, Wichitphongsa W. Tourist Behavior and Sustainable Tourism Policy Planning in the COVID-19 Era: Insights from Thailand. Sustainability. 2023; 15(7):5724. https://doi.org/10.3390/su15075724
Chicago/Turabian StyleSrisawat, Purim, Wuyi Zhang, Kassara Sukpatch, and Wachira Wichitphongsa. 2023. "Tourist Behavior and Sustainable Tourism Policy Planning in the COVID-19 Era: Insights from Thailand" Sustainability 15, no. 7: 5724. https://doi.org/10.3390/su15075724