This study aims to develop a multi-dimensional night-time economy vitality index (NTEVI) to measure the vitality of night-time economic (NTE) activities in Zhejiang Province, China, covering its 11 cities and 90 counties. Comprising 44 supply and demand indicators of the NTE, the index was composed of an overall index and six major sub-indices that measured the vitality of six typical NTE subsectors, including catering, shopping, recreation, accommodation, touring, and fitness. The NTEVI was calculated using a unique multi-source dataset based on hourly online transaction data from a leading Chinese online-to-offline service platform, monthly night-time electricity consumption data, and official statistics from 2019 to 2020. Robustness and sensitivity analyses were conducted to ensure high credibility of the index results. The findings of this study suggested that the NTEVI was highly and significantly correlated with night light indices, economic indicators, and tourism demand measures. By identifying regional and temporal differences across several service sectors over time at the county, city, and provincial levels, the NTEVI serves as a powerful numerical and visual tool: it offers key information to guide policy formulation, resource allocation, and policy evaluation. In the context of COVID-19, the index analyses also reflect the NTE recovery process in Zhejiang Province. Our findings indicate that it is important for the Chinese government, regional authorities, and enterprises to encourage the NTE as a main driver of economic revitalization.
30 April 2024 in International Journal of Hospitality Management
Against the backdrop of the fourth industrial revolution and the COVID-19 pandemic, digital transformation (DT) in the day-to-day operations of micro and small enterprises (MSEs) comes with challenges. Existing maturity models generally focus on advanced levels and are inappropriate for relatively immature companies (e.g., most hospitality MSEs). This study used online documents and in-depth interviews as data sources to develop a customized maturity model framework for hospitality MSEs. Through coding analysis, the research identified four key dimensions that constitute the digital maturity of hotels: strategy and organization, digital technology, digital capabilities, and integrated business. These enterprises have progressed in their digital maturity, moving from an IT-enabled transformation to adopting a brand-oriented approach. The selection of a digital transformation strategy depends on strategic alignment. The proposed model provides a comprehensive understanding of the maturity levels of these companies, thereby facilitating their successful integration into the ongoing modern industrial revolution.