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This article aims to reveal the factors influencing the sustainable development of mobile e-commerce from both user and operational perspectives. It fills the gap in qualitative research on the sustainable development of artificial intelligence (AI) technology in mobile e-commerce based on the grounded theory. This study provides valuable insights and inspiration for sustainable development in this field and lays the theoretical foundation and research reference for future studies.

Based on the grounded theory (GT), interview method was used to conduct the study.

The impact of AI applications on mobile e-commerce is mainly reflected in three stages of the customer shopping process. They are pre-shopping, mid-shopping and after-shopping AI services and each of the three stages has its own separate dimensions that need attention. The study and its persistence aspects are discussed.

The results of this study can provide forward-looking suggestions and paths for the construction and optimization of future e-commerce platforms, contribute to the sustainable development of e-commerce and contribute to the sustainable and healthy growth of the social economy.

This study proposes sustainable development measures for the application of AI in mobile e-commerce, from operation to supervision, which is an important reference for promoting coordinated and rapid socio-economic development.

By analyzing the mechanisms by which rural infrastructure resilience (RIR) impacted population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.

This study considered 213 administrative villages in Longxi County in the Longzhong loess hilly region as the evaluation unit. Based on the construction of a multidimensional RIR evaluation system, the spatial spillover effect of RIR on population loss was determined using the spatial Durbin model (SDM).

The average resilience of each subsystem of rural infrastructure in Longxi County was low, and there were large differences in the spatial distribution. The mean RIR index value was 0.2258, with obvious spatial directivity and agglomeration characteristics. The population loss index of Longxi County had a value of 0.1759, with 26.29 of villages having a high loss level. The population loss was relatively serious and was correlated with the spatial distribution of RIR. The villages with larger RIR index values had lower population loss. The RIR had a significant spatial spillover effect on population loss. Productive infrastructure resilience and living infrastructure resilience (LIR) had negative spillover effects on population loss, and social service infrastructure resilience (SSIR) had a positive spillover effect on population loss.

By analyzing the mechanisms by which RIR impacted on population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.

The purpose of this article is to investigate the variables affecting heat transfer from the surfaces of a tall building and also the extent of the impact of each of them. Another purpose of this paper is to provide a suitable model for estimating the heat transfer coefficient of the external surfaces of the building according to the impact of variables.

In this study, the Taguchi's approach in the design of the experiments was used to reduce the number of experiments. Percent contributions factors into the overall and surface-averaged Nu of a square prism were obtained by the (ANOVA). The change in Nu by changing either of T, P, angle of attack and V were investigated by the (ANOM). The most significant factors affecting the value Nu were also identified to facilitate the design of thermal systems by eliminating the factors imposing no significant effect on the response in the molding phase. The set of conditions under which the air properties remained unchanged was identified. Five correlations were formulated to predict Nu.

Models used in BES, in which the effects of T, P, A and geometrical effects are not accounted for, are not reliable. The air pressure was found to impose no significant effect on the overall Nu of the considered square prism. Studied in the range of 274–303 K, the air temperature imposed a significant effect on the overall Nu. The results of ANOVA show the significant role of Re to predict Nu of tall buildings.

This article is taken from a doctoral dissertation.