吸引力中心性： 用于旅游规划的新中心度公式

Year 2023, Volume: 8 Issue: 2, 203 - 208, 15.12.2023

Eren ERKILIÇ Ali AKAY Ibrahim CİFCİ

https://doi.org/10.31822/jomat.2023-8-2-203

Abstract

本研究旨在为有效旅游规划中的旅游目的地建立一个新的中心度公式。基于网络分析，研究结果提供了从我们的基本算法中得出的几种中心度测量公式，我们称之为有效旅游规划中的吸引力中心度。由于一些旅游热点的景点会对每个目的地的中心度得分产生影响，因此可以利用这些景点来根据空间模式进行更有效的旅行规划。有鉴于此，我们还讨论了对未来研究和目的地管理机构的若干启示。

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Attractiveness Centrality: A new centrality formula for travel planning

Abstract

This current study aims to establish a new centrality formula for tourism destinations in effective travel planning. Based on network analysis, the results provide several formulas for measuring centrality derived from our basic algorithm, which we call the attractiveness centrality for effective travel planning. Since the attractions at some tourist hup-points have an impact on the centrality scores of each destination, they can be utilised for more effective trip planning based on spatial patterns. With this in mind, several implications for future studies and destination authorities were also discussed.

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Keywords

Formula, attractiveness centrality, travel planning, destinations

References

• Asero, V., & Patti, S. (2009). Asymmetric Information, Tourist Satisfaction and Quality in Tourism. Annals of the University of Petrosani, Economics, 9, 12.
• Asero, V., Gozzo, S., & Tomaselli, V. (2016). Building Tourism Networks through Tourist Mobility. Journal of Travel Research, 55(6) 751–763
• Bizirgianni, I., & Dionysopoulou, P. (2013). The influence of tourist trends of youth tourism through social media (SM) & Information and Communication Technologies (ICTs). Procedia—Soc Behavior Sci, 73,652-660
• Bramwell, B. (1998). User satisfaction and product development in urban tourism. Tourism Management, 19(1), 35–47.
• Caldeira, A. M., & Kastenholz, E. (2018). Tourists' spatial behaviour in urban destinations: The effect of the prior destination experience. Journal of Vacation Marketing, 24(3), 247–260
• Chung, H. C., Chung, N., & Nam, Y. (2017). A social network analysis of tourist movement patterns in blogs: Korean backpackers in Europe. Sustainability, 9(12), 2251. https://doi.org/10.3390/su9122251
• Fotis, J., Buhalis, D., & Rossides, N. (2012). Social media use and impact during the holiday travel planning process. In Information and communication technologies in tourism 2012 (pp. 13-24). Springer, Vienna.
• Gretzel, U., & Yoo, K. H. (2008). Use and Impact of Online Travel Reviews. In O'Connor P., Höpken W., & Gretzel U. (Eds), Information and Communication Technologies in Tourism (pp. 35-46). Springer, Vienna
• Han, H., Kim, S., & Otoo, F. E. (2018). Spatial movement patterns among intra-destinations using social network analysis. Asia Pacific Journal of Tourism Research, 23(8), 806–822.
• Ho, G., & McKercher, B. (2014). A comparison of long-haul and short-haul business tourists of Hong Kong. Asia Pacific Journal of Tourism Research, 19(3), 342–355.
• Hwang, Y. H., & Fesenmaier, D. R. (2003). Multidestination pleasure travel patterns: Empirical evidence from the American Travel Survey. Journal of Travel Research, 42(2), 166–171.
• Hwang, Y. H., Gretzel, U., & Fesenmaier, D. R. (2006). Multicity Trip Patterns Tourists to the United States, Annals of Tourism Research, 33(4), 1057–1078
• Jeon, J. W., Duru, O., & Yeo, G. T. (2019). Cruise port centrality and spatial patterns of cruise shipping in the Asian market. Maritime Policy & Management, 46(3), 257-276.
• Jeuring, J. H. G., & Haartsen, T. (2017). The challenge of proximity: The (un) attractiveness of near-home tourism destinations. Tourism Geographies, 19(1), 118–141.
• Kang, S., Lee, G., Kim, J., & Park, D. (2018). Identifying the spatial structure of the tourist attraction system in South Korea using GIS and network analysis: An application of anchor-point theory. Journal of Destination Marketing & Management, 9, 358–370.
• Karakuş, Y. (2020). Introduction to Multi Criteria Decision Making Modelling (MCDM). In R. P. S. Kaurav, D. Gursoy, & N. Chowdhary (Eds.), An SPSS Guide for Tourism, Hospitality and Events Researchers (1st ed.). Routledge.
• Koo, T. T. R., Wu, C. L., & Dwyer, L. (2012). Dispersal of visitors within destinations: Descriptive measures and underlying drivers. Tourism Management, 33(5), 1209–1219.
• Law, R., Chan, I. C. C., & Wang, L. (2018). A comprehensive review of mobile technology use in hospitality and tourism, Journal of Hospitality Marketing & Management, 27(6), 626-648.
• Lee, S., Choi, J., Yoo, S., & Oh, Y. (2013). Evaluating spatial centrality for integrated tourism management in rural areas using GIS and network analysis. Tourism Management, 34, 14–24.
• Middleton, V. T. (1989). Tourism Marketing and Managemet Handbook. In S. F. Witt & L. Moutinho (Eds.), Tourist Product. Prentice Hall.
• Mosalev, A. I. (2020). Influence in the behavioral economy of the tourist industry. International Scientific Conference" Far East Con"(ISCFEC 2020), 726–732.
• Önder, I., Gunter, U., & Gindl, S. (2020). Utilizing Facebook statistics in tourism demand modeling and destination marketing. Journal of Travel Research, 59(2), 195–208.
• Park, D., Kim, J., Kim, W. G., & Park, H. (2019). Does distance matter? Examining the distance effect on tourists' multi-attraction travel behaviors. Journal of Travel & Tourism Marketing, 36(6), 692–709
• Pavlovich, K. (2003). The evolution and transformation of a tourism destination network: The Waitomo Caves, New Zealand. Tourism Management, 24, 203–216.
• Roy, J. R., & Thill, J. C. (2004). Spatial interaction modelling. Papers in Regional Science, 83(1), 339–361.
• Santos, G. E., Ramos, V., & Rey-Maquieira, J. (2012). Determinants of multi-destination tourism trips in Brazil. Tourism Economics, 18(6), 1331–1349.
• Šauer, M., & Bobkova, M. (2018). Tourist flows between central European metropolıses (In the context of metropolisation processes). Geographia Technica, 13(2), 125–137.
• Shih, H. Y. (2006). Network characteristics of drive tourism destinations: An application of network analysis in tourism, Tourism Management 27, 1029–1039.
• Sparks, B. A., & Browning, V. (2011). The impact of online reviews on hotel booking intentions and perception of trust. Tourism Management, 32(6), 1310–1323.
• Sredl, K., Soukup, A., & Severova, L. (2013). Models of Consumer’s choice/Modely volby spotrebitele. E+ M Ekonomie a Management, 16(2), 4–10.
• Vermeulen, I. E., & Seegers, D. (2009). Tried and tested: The impact of online hotel reviews on consumer consideration. Tourism Management, 30(1), 123–127.
• Wu, C. L., & Carson, D. (2008). Spatial and temporal tourist dispersal analysis in multiple destination travel. Journal of Travel Research, 46(3), 311–317.
• Wu, L., Zhang, J., & Fujiwara, A. (2011). A tourist's multi-destination choice model with future dependency. Asia Pacific Journal of Tourism Research, 17(2), 121–132.
• Xiang, Z., Magnini, V. P., & Fesenmaier, D. R. (2015). Information technology and consumer behavior in travel and tourism: Insights from travel planning using the internet. Journal of Retailing and Consumer Services, 22(0), 244–249.
• Yang, Y., Fik, T., & Zhang, J. (2013). Modeling Sequential Tourist Flows: Where Is The Next Destination? Annals of Tourism Research, 43, 297–320.