The Willingness to Recommend a Visit to the Azores: A Hierarchical Ordered Probit Model with Application to Scandinavian Tourists

被引:2
|
作者
Santos, Carlos M. [1 ]
Vieira, Jose Cabral [1 ]
Sarmento, Manuela [2 ]
机构
[1] Univ Azores, Econ & Business Management Dept, PT-9501801 Ponta Delgada, Azores, Portugal
[2] Univ Lusiada Lisbon, Fac Econ & Business Sci, Lisbon, Portugal
关键词
Scandinavian tourists; Azores; willingness to recommend; hierarchical ordered probit model; LOCAL ECONOMIC-IMPACTS; LENGTH-OF-STAY; DESTINATION; SEGMENTATION; DETERMINANTS;
D O I
10.1080/15022250.2014.960133
中图分类号
F [经济];
学科分类号
02 ;
摘要
Tourism is a growing activity around the world and tourism destinations compete fiercely in order to attract tourists. It is usually recognized that the satisfaction that tourists have with the destination is an important way of attracting an increasing number of tourists in the future. Such a process of spreading the recommendation to visit the destination is very important for regions such as the Azores where tourism is still at a very early stage of development. The main goal of this paper is to analyze this topic in the case of the Azores. For this purpose, we use representative data in order to examine to what extent those who visited that region would recommend it to other people. The answer is then conditioned on a set of variables such as the characteristics of the individual and his overall level of satisfaction with the trip using a hierarchical ordered probit model.
引用
收藏
页码:73 / 83
页数:11
相关论文
共 24 条
  • [1] An extended hierarchical ordered probit model robust to heteroskedastic vignette perceptions with an application to functional limitation assessment
    Huang, Zhiyong
    Wang, Haoxian
    Zheng, Wenyuan
    PLOS ONE, 2021, 16 (03):
  • [2] Is the front passenger seat always the "death seat"? An application of a hierarchical ordered probit model for occupant injury severity
    Zhai, Guocong
    Yang, Hongtai
    Liu, Jun
    INTERNATIONAL JOURNAL OF INJURY CONTROL AND SAFETY PROMOTION, 2020, 27 (04) : 438 - 446
  • [3] Factors influencing pedestrian injury severity in Chile: A hierarchical probit ordered model approach
    Gutierrez, Margareth
    Ramos, Raul
    Soto, Jose J.
    Cordova, Felisa
    JOURNAL OF SAFETY RESEARCH, 2025, 92 : 272 - 282
  • [4] An Analysis on the Influencing Factors on College Students' On-Line Payment Willingness Based on the Ordered Probit Model
    Chen, Juan
    2013 INTERNATIONAL CONFERENCE ON MANAGEMENT (ICM 2013), 2013, : 1 - 9
  • [5] An autoregressive ordered probit model with application to high-frequency financial data
    Müller, G
    Czado, C
    JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 2005, 14 (02) : 320 - 338
  • [6] A spatial rank-ordered probit model with an application to travel mode choice
    Mondal A.
    Bhat C.R.
    Transportation Research Part B: Methodological, 2022, 155 : 374 - 393
  • [7] Bayesian inference for an adaptive Ordered Probit model: An application to Brain Computer Interfacing
    Yoon, Ji Won
    Roberts, Stephen J.
    Dyson, Mathew
    Gan, John Q.
    NEURAL NETWORKS, 2011, 24 (07) : 726 - 734
  • [8] A zero-inflated ordered probit model, with an application to modelling tobacco consumption
    Harris, Mark N.
    Zhao, Xueyan
    JOURNAL OF ECONOMETRICS, 2007, 141 (02) : 1073 - 1099
  • [9] A spatial rank-ordered probit model with an application to travel mode choice
    Mondal, Aupal
    Bhat, Chandra R.
    TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2022, 155 : 374 - 393
  • [10] Application of Dynamic Spatial Ordered Probit Model Patterns of Ozone Concentration in Austin, Texas
    Wang, Xiaokun
    Kockelman, Kara M.
    TRANSPORTATION RESEARCH RECORD, 2009, (2136) : 45 - 56