Dataset for Spatiotemporal patterns and nonlinear correlates of digital economy and tourism ecological security coordination in Chinese cities

Description

This dataset contains the indicator data used to evaluate the coordinated development between the digital economy and tourism ecological security in Chinese cities from 2006 to 2023. The dataset covers panel data of 206 prefecture-level cities in China and includes digital economy indicators, tourism ecological security indicators, and socioeconomic driving factors. The dataset supports the analysis of the spatiotemporal evolution and nonlinear driving mechanisms of digital economy–tourism ecological security coupling coordination.

Steps to reproduce

The dataset was constructed using city-level panel data from 206 prefecture-level cities in China during 2006–2023. The data were collected mainly from official statistical yearbooks, government reports, and public databases, including the China Statistical Yearbook, China City Statistical Yearbook, China Tourism Statistical Yearbook, annual reports of communications administrations, and the China National Intellectual Property Administration database. The digital economy index was constructed using indicators related to digital infrastructure, digital industry development, and digital innovation capacity. The CRITIC method was applied to determine indicator weights and measure the digital economy development level. The tourism ecological security index was developed based on the DPSIR framework, including driving force, pressure, state, impact, and response dimensions. The entropy-weighted TOPSIS method was used to calculate tourism ecological security levels. Subsequently, the coupling coordination degree (CCD) model was employed to measure the coordinated development between the digital economy and tourism ecological security. Kernel Density Estimation and Jenks natural breaks classification were used to analyze spatiotemporal patterns. XGBoost combined with SHAP interpretation was applied to identify nonlinear driving mechanisms and interaction effects. Missing values in the original dataset were supplemented using linear interpolation when necessary.

Institutions

• Shandong Normal University

  Shandong, Jinan

Categories

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