JOURNAL OF NATURAL RESOURCES ›› 2021, Vol. 36 ›› Issue (7): 1647-1657.doi: 10.31497/zrzyxb.20210702

• Special Feature on "Innovation and Development of Red Tourism Resources of China" • Previous Articles     Next Articles

Research on the value co-creation mechanism of red tourism development from the perspective of tourists

LA Li-qing(), XU Fei-fei(), HE Yun-meng, HAN Lei   

  1. School of Humanities, Southeast University, Nanjing 210096, China
  • Received:2021-01-25 Revised:2021-04-14 Online:2021-07-28 Published:2021-09-28
  • Contact: XU Fei-fei E-mail:laliqing@seu.edu.cn;feifeixu@seu.edu.cn

Abstract:

Taking Jinggang Mountain Scenic Area as a case, this study collected and analyzed the travel notes of this scenic area from Mafengwo.com. We adopt big data analysis and qualitative text analysis methods and introduce the theory of value co-creation to explore the value co-creation mechanism of red tourism development from three dimensions (resources, practices and values). The results show that the value co-creation resources of red tourism scenic spots include historical and cultural heritages, natural landscape resources and iconic landscape symbols. Through practical activities including red culture experience, learning and training activities, and interpretation service experience, tourists gain knowledge of red history and culture, build an emotional connection with red culture and form the values of patriotism and identification with the country. This verifies the realization of the educational function of red tourism. On the other hand, the existing value co-creation practice of red tourist attractions is still limited. The value co-creation mechanism of red tourism development constructed in this study integrates the demand of tourists, the support service of scenic spots, and the possible value co-creation practice, which has practical significance for improving the participation of tourists and realizing the value co-creation of red tourist attractions.

Key words: red tourism, resource development, value co-creation, big data analysis, text analysis