This study investigates the direct and indirect influences of behavioral quality, social support, perceived system, emotional perception, and public expectation on user favorability regarding government chatbots in both government service and policy consultation contexts. The findings reveal that while behavioral quality, social support, and perceived system directly affect user favorability in both scenarios, public expectation uniquely impacts user favorability in policy consultation settings, but not in government service scenarios. Furthermore, the analysis indicates that social support, emotional perception, and public expectation all indirectly influence user favorability through their mediating effect on behavioral quality in both contexts. Notably, the significant distinction between the two scenarios is the presence of an indirect impact of perceived system on user favorability within policy consultation scenarios, which is absent in government service scenarios. This study sheds light on the intricate interplay of factors shaping user favorability with government chatbots, and provides valuable insights for improving user experiences and user favorability in different governmental service contexts.

This study focuses on the impact of technological changes, particularly the development of generative artificial intelligence, on government–citizen interactions in the context of government services. From a psychological perspective with an emphasis on technological governance theory and emotional contagion theory, it examines public perceptions of the simulated emotions of governmental chatbots and investigates the moderating role of age. Data were collected through a multi-stage stratified purposive sampling method, yielding 194 valid responses from an original distribution of 300 experimental questionnaires between 24 September and 13 October 2023. The findings reveal that public expectations significantly enhance the simulated emotional perception of chatbots, with this effect being stronger among older individuals. Age shows significant main and interaction effects, indicating that different age groups perceive the simulated emotional capabilities of chatbots differently. This study highlights the transformative impact of generative artificial intelligence on government–citizen interactions and the importance of integrating AI technology into government services. It calls for governments to pay attention to public perceptions of the simulated emotions of governmental chatbots to enhance public experience.

This paper introduces the Emotional Governance Theory for the first time and reveals the crucial role of emotional perception in the interaction between government chatbots and the public through an analysis of the relationship between public expectations, emotional perception, and public satisfaction with government chatbots. The research findings indicate a significant moderating effect of emotional perception at different levels on the relationship between public expectations and public satisfaction with government chatbots. At the average level, emotional perception positively influences this relationship. At high levels, emotional perception attenuates the positive association, while at low levels, emotional perception significantly enhances the positive relationship between public expectations and public satisfaction with government chatbots. Finally, the paper proposes a series of policy recommendations to foster more proactive and effective interaction between government chatbots and the public, thereby enhancing the quality of public services and public satisfaction.

Zanthoxylum piasezkii Maxim. is a widely distributed species of edible medicinal plant in China. It has been used for traditional spicy condiment and medicinal ingredients for quite a long time. In this study, the complete chloroplast genome sequence of Z. piasezkii was first reported and characterized from sequencing data. The complete chloroplast genome was determined to be 158,728 bp in length, consisting of a large single-copy (LSC) region (85,918 bp) and a small single copy (SSC) region (17,612 bp), which were separated by a pair of 27,599 bp inverted repeat (IR) regions. The chloroplast genome is predicted to contain 132 genes, including 87 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. The overall GC content of cpDNA is 38.4%. The phylogenetic analysis of 12 complete chloroplast genomes reveals that Z. piasezkii is mostly related to the congeneric Z. bungeanum.

In a comprehensive analysis of the voting behaviors of street-level bureaucrats, the study identified political identities and gender equality consciousness as positive drivers of voting inclination. Specifically, street-level bureaucrats with a favorable political identities and heightened awareness of gender equality are more likely to engage in voting. Conversely, birth year, social stratum, and economic status have been pinpointed as negatively influencing factors, with younger bureaucrats and those of higher social and economic standing often displaying reduced voting participation. However, elements such as ethnicity, internet usage, and social friend circles do not exhibit a significant impact on the voting intentions of street-level bureaucrats. These findings provide a novel insight into the political behaviors of street-level bureaucrats.