Acta Geographica Sinica ›› 2017, Vol. 72 ›› Issue (10): 1886-1903.doi: 10.11821/dlxb201710012

• Tourism Geography • Previous Articles     Next Articles

Urban tourism destination personality and its cultural landscape representation via machine learning: A case study of Nanjing

Chen ZHANG1,2(), Zhenfang HUANG1,2(), Jie ZHANG3, Junlian GE1,2   

  1. 1. School of Geography Science, Nanjing Normal University, Nanjing 210023, China
    2. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
    3. Department of Land Resources and Tourism Sciences, Nanjing University, Nanjing 210093, China
  • Received:2016-10-16 Revised:2017-02-17 Online:2017-11-10 Published:2017-11-06
  • Supported by:
    National Natural Science Foundation of China, No.41301145, No.41671137;Tourism Young Expert Training Program, No.TYETP201526;Priority Academic Program Development of Jiangsu Higher Education Institutions


Tourism destination has both material and spiritual attributes. Compared to the material attributes of place, the spiritual attributes are more abstract, which leads to the difficulty in description and measurement for scholars. This may be the main reason for the scarcity of research in this direction. Ekinci and Hosany proposed the concept of 'tourism destination personality' and used Aaker's brand personality scale to measure destination personalities that can be viewed as a pioneering work for investigating spiritual aspects of tourism destination. However, as a new direction, most research on tourism destination personality has followed the way of brand personality research, and moreover, it has not touched some in-depth questions such as the representation and its mechanism referring to tourism destination personality. In view of this, taking urban tourism destination as an example, this paper aims to design a personality scale for urban tourism destination, and to find urban tourism destination personality traits and their landscape representation mechanism. Nanjing is selected as the case in this study. A questionnaire survey was conducted in 2015, and 789 valid questionnaires were finally collected. Machine learning, as an intelligent data analysis tool, is used in this study. By analyzing the collected data, it can be concluded that: (1) Urban tourism destination personalities can be divided into four dimensions, such as 'attitude', 'glamour', 'disposition' and 'capability'. (2) Urban cultural landscapes are important in representing urban destination personalities, and can be divided into five dimensions, i.e., 'modern space landscape', 'traditional space landscape', 'ecological landscape', 'social landscape' and 'landscape for living'. (3) The effects of urban cultural landscapes in representing urban tourism personalities are quite different. This study provides a conceptual framework and method for tourism destination personality research. The findings provide new insights for human-environment interaction from the spiritual perspectives.

Key words: spiritual attribute of place, urban tourism destination personality, cultural landscape representation, machine learning, Nanjing