Literature DB >> 34393315

Tourist trip design with heterogeneous preferences, transport mode selection and environmental considerations.

José Ruiz-Meza1, Jairo R Montoya-Torres1.   

Abstract

Tourism is one of the fastest-growing sectors in the world with a shift from mass tourism to personalized travel. Nevertheless, it generates significant environmental impacts. The current events associated with quarantine measures generated by COVID-19 represent, however, a risk for this sector. It is hence necessary to create strategies that allow efficient decision-making for all echelons and actors for a rapid recovery. Tourists are key actors, which makes necessary to facilitate tourism trip planning according to tourists' preferences as a complex process. In this paper, we propose a novel model of tourist trip planning for heterogeneous preferences in a tourist group and selection of transport modes, in the first instance, while a second step seeks at minimizing the level of CO2 emissions. A comparison of the two models is made considering the objectives associated with individual tourist benefits and group profit equity, in contrast to the inclusion of the cost of CO2 emissions. A numerical comparison is carried out with a total of 546 data sets. Results illustrate the conflict between those objectives by generating an inverse relationship between the individual and group profit equity of tourists, in addition to individual benefit and emission minimization.
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.

Entities:  

Keywords:  Carbon emissions; Heterogeneous preferences; Mathematical modeling; Post-COVID; Tourist trip design problem; Transport mode selection

Year:  2021        PMID: 34393315      PMCID: PMC8344399          DOI: 10.1007/s10479-021-04209-7

Source DB:  PubMed          Journal:  Ann Oper Res        ISSN: 0254-5330            Impact factor:   4.854


  1 in total

1.  TriPlan: an interactive visual analytics approach for better tourism route planning.

Authors:  Xinyi Zhang; Xiao Pang; XiaoLin Wen; Fengjie Wang; Changlin Li; Min Zhu
Journal:  J Vis (Tokyo)       Date:  2022-08-16       Impact factor: 1.974

  1 in total

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