Int J Performability Eng ›› 2019, Vol. 15 ›› Issue (2): 623-629.doi: 10.23940/ijpe.19.02.p26.623629

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Applying Creative Computing in the Analysis of Smart Tourism Research in China

Gongpeng Zhangab, Yuncai Ninga, Chi Zhangb*(), Zhaogang Wanga, and Beu Leec   

  1. a School of Management, China University of Mining and Technology, Beijing, 100083, China
    b Collaborative Innovation Center of eTourism,Beijing Union University,Beijing, 100101,China
    c College of Business,Texas A&M University, San Antonio,Texas, 78224, USA
  • Revised on ; Accepted on
  • Contact: Zhang Chi E-mail:tibuuzc@163.com
  • About author:Gongpeng Zhang is a Ph.D. student in the School of Management at China University of Mining & Technology. His research interests include management science and engineering and smart tourism. E-mail: gongpeng@buu.edu.cn.|Yuncai Ning is a deputy dean, professor, and doctoral tutor in the School of Management at China University of Mining & Technology. His research interests include technical and economic evaluation and project management.|Chi Zhang is a deputy dean and associate professor in the Tourism College at Beijing Union University. His research interests include tourism economics and tourism information. E-mail: tibuuzc@163.com.|Zhaogang Wang is a Ph.D. student in the School of Management at China University of Mining & Technology. His research interests include management science and engineering and text mining.|Beu Lee is an assistant professor in the College of Business at Texas A&M University. Email: eve.lee@tamusa.edu.

Abstract:

Understanding the contents of smart tourism comprehensively can provide abundant guidance and reference for the practices of smart tourism. It also helps to identify and overcome the shortcomings of smart tourism research. Based on the core ideas of creative computing, this paper constructs a word frequency matrix and performs cluster analysis by using keywords from smart tourism research. Then, the relevant keywords are extracted by using chi-squared statistics to interpret the cluster results. The results show that many creative articles focus on tourism information, the status quo and countermeasures of smart tourism, tourism information technology, and smart tourism scenic area management, which are the hot topics of domestic smart tourism research. Furthermore, tourism big data, tourism service supply chain, Internet+ tourism, and tourism experience have recently attracted increasing attention. The impact of tourism industry policy and the application of new information technology have always been an important source of creativity in smart tourism research.

Key words: smart tourism, creative computing, cluster, chi-squared statistics