PurposeDrawing on social network and information diffusion theories, the authors study the impact of the structural characteristics of a seller’s local social network on her promotion effectiveness in social commerce.Design/methodology/approachThe authors define a local social network as one formed by a focal seller, her directly connected users and all links among these users. Using data from a large social commerce website in China, the authors build econometric models to investigate how the density, grouping and centralization of local social networks affect the number of likes received by products posted by sellers.FindingsLocal social networks with low density, grouping and centralization are associated with more likes on sellers’ posted products. The negative effects of grouping and centralization are reduced when density is high.Originality/valueThe paper deepens the understanding of the determinants of social commerce success from a network structure perspective. In particular, it draws attention to the role of sellers’ local social networks, forming a foundation for future research on social commerce.

Natural disasters can have devastating economic and financial consequences for those affected. This research note explores the potential of artificial intelligence (AI) in disaster relief through lending services. By collaborating with a credit-scoring company, we investigate how AI-empowered lenders can effectively reduce delinquency rates for borrowers in the aftermath of disasters. Our findings reveal that borrowers applying to lenders that utilize AI in their loan assessment process experience improved outcomes in terms of delinquency reduction, particularly for borrowers with lower credit scores. This research underscores the positive impact of AI in the lending context, benefiting both lenders and borrowers. Furthermore, we highlight that AI indirectly supports disaster relief efforts through financing, providing a compelling use case for AI fairness in lending. Our findings have significant implications for leveraging AI as a valuable tool in mitigating the financial impact of disasters and promoting fairness in lending practices.

PurposeLeveraging information technology (IT) to improve the treatment and support of patients is a widely studied topic in healthcare. For chronic diseases, such as diabetes, the use of information technology is even more important since its effect extends from a clinic environment to patients’ daily life. The purpose of this paper is to investigate the impacts of one widely adopted information technology, the mobile phone, on diabetes treatment, specifically on the complicated process of patients’ health, emotions and compliance.Design/methodology/approachWe leverage a unique longitudinal dataset on diabetes patients’ health status in rural areas of China to study the problem. We also cross-link the dataset with mobile carrier data to further differentiate mobile phone use to phone calls and network use. To address the endogeneity concerns, we apply PSM and a series of instrument variables.FindingsWe identify clear evidence that mobile phone use can significantly improve patients’ emotions and compliance, where the effect is generally larger on patients in worse health conditions. While mobile phone calls clearly benefit diabetes patients, we do notice that mobile phone network use has a negative moderating effect with patients’ health condition on improving compliance.Originality/valueThis study not only enriches our theoretical understanding of the role of mobile phones in diabetes management, it also shows the economic benefit of promoting patients’ use of mobile phones, which should be considered by medical care providers and medical policymakers.