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As an important engine of economic growth, the digital economy is bringing new opportunities for the promotion of entrepreneurship. However, key questions regarding the extent of the effect of the digital economy on entrepreneurship remain unanswered. This study examines how the digital economy influences entrepreneurship in China using provincial data from 2011–2020, applying convergence tests and spatial econometric models.

Based on theoretical analysis and using macro provincial data covering the period of 2011–2020, we adopt a diversified empirical analytical method and apply a combination of the convergence trend test, spatial auto correlation test, and spatial Durbin model to test the research hypotheses.

First, there is spatial correlation between the digital economy and entrepreneurship. Second, the overall trend of China’s digital economy shows s convergence, with the whole country and the eastern region showing absolute β convergence and the whole country as well as the central and western regions showing β conditional convergence. Third, the digital economy can significantly promote entrepreneurship and has spatial spillover effects. Moreover, higher education has a negative moderating effect on the process of digital economy empowering entrepreneurship.

Studying the spatially correlated impacts of the digital economy on entrepreneurship enhances our understanding of its contribution to economic growth. Policy-makers can use these findings to develop targeted digital infrastructure investments in lagging provinces, guide entrepreneurs to better grasp the opportunities of the digital economy, and provide support for innovation and entrepreneurship. The findings also could offer Chinese experience that can be used to guide developing countries in utilizing the digital economy to enable entrepreneurship.

This paper expands and enriches the analytical focus on digital economy-empowered entrepreneurship and complements the current theoretical research on the moderating effect of the digital economy in empowering entrepreneurship.

Omnichannel sales have provided new impetus for the development of catering merchants. The authors thus focus on how catering merchants should manage capacities at the ordering, production and delivery stages to meet customers’ needs in different channels under third-party platform delivery and merchant self-delivery. This is of great significance for the development of the omnichannel catering industry.

This paper formulates the capacity decisions of omnichannel catering merchants under the third-party platform delivery and merchant self-delivery mode. The authors mainly use queuing theory to analyze the queuing behavior of online and offline customers, and the impact of waiting time on customer shopping behavior. In addition, the authors also characterize the merchant’s capacity by the rate in queuing model.

The authors find that capacities at ordering stage and food production stage are composed of base capacities and safety capacities, but the delivery capacities only have the latter. And in the self-delivery mode, merchants can develop higher safety capacities by charging delivery fees. The authors prove that regardless of the delivery mode, omnichannel sales can bring higher profits to merchants by integrating demand.

The authors focus on analyzing the capacity management of omnichannel catering merchants at the ordering, production and delivery stages. And the authors also add the delivery process into the omnichannel for analysis, so as to solve the problem of capacity decision-making under different delivery modes. The management of delivery capacity and its impact on other stages’ capacities are not covered in other literature studies, which is one of the main innovations of this paper.

This paper aims to solve the disadvantages of content-based domain ontology (CBDO) and metadata-based domain ontology (MDO) and improve organization and discovery efficiency of library resources by resource ontology (RO).

The paper constructed an RO model. Methods of informetrics are utilized to reveal semantic relationships among library resources. Methods of ontology, ontology-relational database mapping (O-R mapping) and relational database modelling are utilized to construct RO. Take author co-occurrence for example, the paper demonstrated the capability of RO model.

RO not only revealed the deep-level semantic relationships of metadata of library resources but also realized totally computer-automated processing. RO improved the efficiency of knowledge organization and discovery.

Semantic relationships revealed by RO are limited to simple metadata, which makes it difficult to reveal fine-grained semantic relationships. Ongoing research focuses on the revelation of semantic relationships based on the title and abstract.

The paper includes implications for utilizing methods of Informetrics to construct ontology.

This paper proposed a standardized process of ontology construction in library resources. It may be of potential interest for anyone who needs to effectively organize library resources.