Purpose: From the perspective of the institution and internationalization speed, the article discusses the internal mechanism of cross-border e-commerce selection mode, as well as the moderating role of social networks as the intangible resource, and expand the theoretical system of corporate internationalization.Design/methodology/approach: Based on the empirical data of 456 multinational e-commerce companies in five first-tier cities in China from 2016 to 2019, our research explores the selection mode of cross-border e-commerce.Findings: The results show that (1) the institutional distance of the host country leads to the exit from cross-border e-commerce platforms in the international expansion of enterprises. (2) The difference in internationalization speed online and offline has become a mediated mechanism for the exit of cross-border e-commerce platforms due to the institutional distance of the host country. (3) The diversity and scale of offline social networks can weaken the impact of differences in internationalization speed on the exit from cross-border e-commerce platforms. (4) The resistance of companies expanding to countries with a weak institutional environment is greater than that experienced when expanding to countries with a strong one.Originality/value: This study shows, for the first time, how to select expansion mode for cross-border e-commerce. And the paper also centers on the research of the impact of “social network”, a kind of intangible resource, on cross-border e-commerce platform adoption.

The emergence of Internet product sales platform has not only greatly enriched consumers’ choices and facilitated their purchasing behavior but also provided space for counterfeit products and relevant fraudulent signal strategies in China, which damage the consumer’s rights and interests and further disrupt the normal order of the e-commerce market. However, effective empirical study on the long-term and dynamic influence mechanism of fraudulent signals of counterfeit products and the seller incentive mechanism is still unavailable in academic circles, especially in the Chinese market, where government regulation is deemed to be lacking. For the purpose of this paper, an empirical study has been conducted by virtue of Internet e-commerce platform data based on data capture technology to analyze the dynamic performance effect mechanism of e-commerce fraudulent signals of counterfeit products under multiple game conditions. The study results show that selling of counterfeit products by using fraudulent signals can improve the current sales performance, but it will cause a long-term performance decline consequently. Additionally, from the perspective of the pricing mechanism, this paper analyzes the said seller incentive mechanism of counterfeit products. Finally, this paper puts forward relevant management suggestions based on the empirical study findings.

From the perspective of social network behavior, our paper discusses the relationship between agricultural entrepreneurial social network behavior and entrepreneurial financing performance in an Internet crowdfunding setting, and investigates the moderating role of entrepreneurial team size. In this paper, the data-mining method is used to capture and collate data regarding 7585 venture projects on an Internet crowdfunding platform between 2014 and 2017. Ordinary least squares (OLS) and Probit models are applied to the empirical test. The results show that first, compared with other industries, the effect of agricultural entrepreneurs’ quality information disclosure on entrepreneurship financing performance is lower, whereas the effect of their social network interaction is higher. Second, the entrepreneurial team size has a positive moderating role on the former and a negative moderating role on the latter. Our research is of significance for agricultural enterprises to raise their financial performance in Internet crowdfunding, especially for Chinese agricultural micro-enterprises.

In the context of worldwide internationalization, a new entrepreneurial financing mode has emerged and gained popularity, which has been improved and modified significantly in terms of both form and content. This study selects crowdfunding as its breakthrough point to explore and study the relationships between the backgrounds of initiators, experiences, and financing effects. Through data mining technology, this article introduces a database including 423 entrepreneurial financing projects and entrepreneurs’ information, and entrepreneurs’ locations covering 10 countries and regions. By using the multivariate least square model, we conclude that the entrepreneurs’ technical educational backgrounds, offline entrepreneurial experiences, and online entrepreneurial experiences all have positive effects on internet financing. The weaker the value that the uncertainty avoidance in the entrepreneurs’ host countries has, the stronger the facilitation and promotion from offline and online entrepreneurial experiences on internet financing. Furthermore, the level of uncertainty avoidance in the entrepreneurs’ countries has a moderating effect as well.

Urban Air Mobility (UAM) requires reliable communication and surveillance infrastructures to ensure safe Unmanned Aerial Vehicle (UAV) operations in dense metropolitan environments. However, urban infrastructure is inherently heterogeneous, leading to significant spatial variations in monitoring performance. This study proposes a unified framework that integrates infrastructure readiness assessment with Deep Reinforcement Learning (DRL)-based UAV path planning. Using Singapore as a representative case, we employ a data-driven methodology combining clustering analysis and in situ measurements to estimate the citywide distribution of surveillance quality. We then introduce an infrastructure-aware path planning algorithm based on a Double Deep Q-Network (DQN) with a convolutional architecture, which enables UAVs to learn efficient trajectories while avoiding surveillance blind zones. Extensive simulations demonstrate that the proposed approach significantly improves path success rates, reduces traversal through poorly monitored regions, and maintains high navigation efficiency. These results highlight the potential of combining infrastructure modeling with DRL to support performance-aware airspace operations and inform future UAM governance systems.