Examining Interrelationships between Tourist Travel Mode and Trip Chain Choices Using the Nested Logit Model

Cong Qi,Junlan Chen,Ruiying Lu,Xiucheng Guo,Zhenjun Zhu

doi:10.3390/su12187535

Abstract

As tourism grows, determining methods to ease traffic problems as a result of domestic tourism holidays has become a central issue in traffic planning and management. Trip chain and travel mode choices as well as their interplays are crucial in analysing and understanding the travel behaviour of tourists, which can help to address these problems. Therefore, this study explored the relationship between destination transportation modes and trip chain choices using nested logit models wherein two nest structures were used to analyse the decision processes of travellers. Empirical analysis confirmed the effectiveness of the rational model using survey data collected from 350 respondents in Nanjing, China in 2020. The results showed that tourists preferred deciding on the trip chain prior to the travel mode, and higher time and costs were acceptable when tourists selected a complex trip chain with tour activities. Moreover, non-local tourists owning a driver’s licence, travelling with companions, and staying for longer periods were more likely to use public transport with trip chains comprising tour activities; however, the relationship for trip chains with non-tour activities was the reverse. These findings are valuable for designing effective transport management strategies to ease traffic during holiday periods.

Highlights

As global tourism continues to grow rapidly, the increase in tourist transport has been influenced by various factors, such as the growing number of trips per person and the increasing number of tourists from emerging countries such as Brazil, Russia, India, China, and South Africa
Zhao [9] developed an nested logit (NL) model for analysing travel behaviour on holidays that explored the interrelationships between trip chains and travel mode choices; this model revealed the credibility of the structure with the trip chain above the transportation mode in evaluating travel behaviour during holiday periods
The findings may differ from those of Yang et al [3] in that the structure of the NL model used for analysing travel behaviour on holidays was the opposite of that used in this study

Summary

Introduction

As global tourism continues to grow rapidly, the increase in tourist transport has been influenced by various factors, such as the growing number of trips per person and the increasing number of tourists from emerging countries such as Brazil, Russia, India, China, and South Africa. In China, tourism has grown rapidly, with 6.0 bn domestic tourists in 2019 compared to 3.6 bn in 2014 [1]. Rising populations (especially in urban areas) and the resulting increased demand for leisure and tourism activities have led to traffic problems in many tourist destinations. Most policies that have been proposed promote the tourism demand on holidays but do not relieve traffic congestion. It is essential to conduct research on managing tourist traffic during the holidays

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Discussion

Conclusion