管理评论 ›› 2023, Vol. 35 ›› Issue (1): 97-107.

• 经济与金融管理 • 上一篇    下一篇

中国旅游产业融合的趋势和模式变化——基于非结构化数据

宋红娟   

  1. 海南热带海洋学院旅游学院, 三亚 572022
  • 收稿日期:2020-08-26 出版日期:2023-01-28 发布日期:2023-02-27
  • 作者简介:宋红娟,海南热带海洋学院旅游学院副教授,硕士生导师,博士。
  • 基金资助:
    海岛旅游资源数据挖掘与监测预警技术文化和旅游部重点实验室建设项目(KLITRDMM 2021-02)。

The Trends and Patterns of Tourism Industry Convergence in China: Based on Unstructured Data

Song Hongjuan   

  1. School of Tourism Management, Hainan Tropical Ocean University, Sanya 572022
  • Received:2020-08-26 Online:2023-01-28 Published:2023-02-27

摘要: 产业融合已成为中国旅游业转型升级的一种途径,但这种现象在中国旅游业中是否持续稳定,还有待进一步研究。本文抓取大量的旅游产业融合的非结构化数据,经过数据清洗,对新闻报道的关键词进行了共现分析,并使用归一化点互信息指数(Pointwise Mutual Information,PMI)作为测量旅游产业融合度的指标,分析了中国旅游业的融合现象,重点关注其趋势和模式。结果发现:第一,中国旅游产业融合整体上呈现日益增长的趋势;第二,旅游产业与服务型产业呈现叠加的融合关系(线性),而旅游产业与非服务型产业呈现产业重组的融合关系(非线性);第三,旅游产业的融合模式是异质的,其中旅游和体育、健康、生态、工业等产业呈现了演化融合趋势,而旅游和乡村、节庆和婚庆等产业呈现平稳融合趋势。这些发现表明,旅游经济正在发生重大转变,产业的融合模式模糊边界逐渐扩大。另外,本研究为预测中国产业融合的未来方向提供了一种方法。

关键词: 旅游产业融合, 共现分析法, 点互信息指数, 非结构化数据

Abstract: Industry convergence has become a way of China’s tourism industry’s transformation and upgrading. However, whether this phenomenon continues to be stable in China’s tourism industry remains to be further studied. In this paper we collect a large number of unstructured data on tourism industry convergence and after data cleaning, carry out a co-occurrence analysis of keywords in news coverage and use the Pointwise Mutual Information Index (PMI) as an index of tourism industry convergence to analyze the Convergence of China’s tourism industry, with a focus on its trends and patterns. The results are as follows. Firstly, the convergence of tourism industry in China presents a growing trend as a whole. Secondly, the tourism industry and the service-oriented industry show superposition patterns (linear), while the tourism industry and the non-service industry show industrial restructuring patterns (non-linear). Thirdly, the convergence patterns of tourism industry are heterogeneous, in which “tourism+sports”, “ tourism+health” and“ tourism+ecology” industries have shown evolutionary convergence, while “tourism+rural”, “tourism +event” and “tourism+wedding” industries have shown stationary convergence. These findings show that the tourism economy is undergoing major changes and the fuzzy boundary of the industrial convergence mode gradually expands. In addition, this study provides a way to predict the future direction of China’s industrial convergence.

Key words: tourism industry convergence, co-occurrence analysis method, point mutual information index, unstructured data