Facilitating urban tourism governance with crowdsourced big data : a framework based on Shenzhen and Jiangmen, China

Abstract

The application of crowdsourced data holds transformative potential in reshaping decision-making processes. However, effectively harnessing the power of crowdsourced data within the complex landscape of urban tourism governance, especially in China marked by rapid growth and dynamic shifts in the tourism market, remains hindered by institutional constraints and capacity limitations. This study critically examines three pivotal challenges in urban tourism governance in China, stemming from the ever-evolving tourism demand dynamics: resource management, tourism promotion, and regional collaboration. In response to these challenges, we propose an innovative framework for tourism governance that capitalizes on crowdsourced data, comprising eight distinct analytical functions. To validate the efficacy of this novel approach grounded in crowdsourced information, empirical tests were conducted in Shenzhen and Jiangmen, China, using data sourced from Dianping.com, often dubbed the “Yelp of China.” The dataset encompassed 1,496 tourist attractions and 184,357 tourist reviews for Shenzhen, along with 559 attractions and 2,811 reviews for Jiangmen. By leveraging the proposed framework and its designated functions, we formulate policy recommendations for the advancement of tourism in Shenzhen and Jiangmen. Finally, we explore the potential advantages of adopting the crowdsourced information-based approach to tourism management, shedding light on its implications for both governmental and corporate entities.