The Evolution Model of and Factors Influencing Digital Villages: Evidence from Guangxi, China

Abstract

(1) Background: Digitalization is the key to sustainable village development, posing a new challenge for village planning, construction, and governance in all countries. The construction of digital villages is currently in the stage of experimentation and exploration; China is the largest developing country and a pioneer in the digitization of villages. (2) Methods: Based on a combination of the Boston Consulting Group Matrix and GeoDetector, we conducted an empirical study on 70 counties in Guangxi, aiming to analyze the construction level, evolution model, and driving mechanism of digital villages and to provide a basis for decisions on government investment and social participation. (3) Results: First, Conspicuous disequilibrium in rural digitalization has manifested in Guangxi, and counties at different levels (leader, follower, and straggler) show significant clustering and correlation effects in their geographical distribution. Second, digital village construction in Guangxi has evolves in diversified modes (divided into four types: star, gazelle, cow, and dog), with hot and cold areas forming a center–periphery structure. Third, rural digitalization has a very complex driving mechanism, with high heterogeneity in the direct influencing factors, significant synergistic enhancement of factors, and nonlinear enhancement dominating the interaction’s relationship. (4) Conclusions: According to the results of analysis, we suggest highlighting the government-driven mechanism and regional linkage in the construction of digital villages, formulating differentiated management policies and development plans based on the combination of top-level design and grassroots innovation, establishing joint meetings or development associations and service alliances, and stimulating the enthusiasm of the whole of society, especially farmers and enterprises, in order to achieve rapid and sustainable rural digitalization.

Comprehensive evaluation of digital village development in the context of rural revitalization: A case study from Jiangxi Province of China

“…Mu et al created an index system of the digital economy in agriculture and rural areas from the industrial level on the basis of three components of digital economy formation [ 30 ]. Li Weiwei et al combined the Boston Consulting Group Matrix and GeoDetector to study the construction level and evolution pattern of digital villages in 70 counties in Guangxi [ 31 ]. Zhang Ping et al used geographic information systems (GIS) to evaluate the development of the digital countryside in Gansu Province and then formulated targeted development strategies according to the development level of each region [ 32 ].…”

Traditional Village Morphological Characteristics and Driving Mechanism from a Rural Sustainability Perspective: Evidence from Jiangsu Province

“…The application of new technologies and methods is increasing, including Space Syntax [26,27], machine learning [28,29], BIM technology [30,31], SD (system dynamics) technology [32,33], and CA (cellular automaton) technology [34,35]. These methods are applied in the fields of static and dynamic quantitative calculations for analyzing the spatial morphology of traditional villages [36], as well as their driving factors [37,38], and for simulating planning scenarios [39]. Representative results include the following.…”

Evolution Model and Driving Mechanism of Urban Logistics Land: Evidence from the Yangtze River Delta

“…β 0 is a constant term, (µ i , v i ) is the spatial coordinates of City i in the YRD (using the coordinate of the center of gravity point of the city polygon); β k (µ i ,v i ) is the regression coefficient of the independent variable of City i in the YRD, and ϵ i is the error in the regression equation. The geographical weighted regression coefficient is calculated as follows [59,60]:…”