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This study aims to apply the predictive processing theory to examine the influence of artificial intelligence (AI)-driven robotic performers on audience emotions and the audience’s resulting electronic word-of-mouth (eWOM) behaviors during tourism service encounters.

Using a quantitative research methodology, survey responses from 339 regular customers of performing arts in tourism destinations were analyzed. The respondents were recruited through Prolific, a professional data collection platform. SPSS 23.0 was used for the preliminary analysis, from which a research model to achieve the aim was proposed. SmartPLS 3 was used for partial least squares structural equation modeling to test the model.

Interactive and novel robotic performances significantly encouraged the consumers to share their experiences online, thereby enhancing eWOM. However, melodic resonance had no significant impact on eWOM intentions. The consumers’ emotional responses fully mediated the relationship of the novelty and interactivity of the performances to the consumers’ eWOM intentions but did not mediate the relationship of the musical elements to their eWOM intentions.

This study enriches the understanding of how AI-driven performances impact consumers’ emotional engagement and sharing behaviors. It extends the application of the predictive processing theory to the domain of consumer behavior, offering valuable insights for enhancing audience engagement in performances through technological innovation.

本研究旨在运用预测处理理论, 考察人工智能（AI）驱动的机器人表演对观众情感及其在旅游服务接触中的电子口碑（eWOM）行为的影响。。

采用定量研究方法, 分析了339名经常观看旅游景点表演艺术的常客的调查问卷。受访者通过专业数据收集平台Prolific招募。初步分析使用SPSS 23.0进行, 从中提出了实现研究目标的研究模型。使用SmartPLS 3进行偏最小二乘结构方程模型测试该模型。

互动性和新颖性的机器人表演显著鼓励消费者在线分享他们的体验, 从而增强电子口碑。然而, 旋律共鸣对电子口碑意图没有显著影响。消费者的情感反应完全中介了表演的新颖性和互动性与消费者电子口碑意图之间的关系, 但没有中介音乐元素与电子口碑意图之间的关系。

本研究丰富了对AI驱动表演如何影响消费者情感参与和分享行为的理解。将预测处理理论的应用扩展到消费者行为领域, 为通过技术创新增强观众参与度提供了宝贵的见解。

This article investigates the mechanism of the direct and indirect effects of epidemics on agricultural production and projects the impact of COVID-19 on agricultural output in China.

This article first adopts a dynamic panel model and spatial Durbin model to estimate the direct and indirect effects, followed by a growth accounting method to identify the channels by which epidemics affect agriculture; finally, it projects the overall impact of COVID-19 on agriculture.

The incidence rate of epidemics in a province has a negative impact on that province's own agricultural productivity, but the increase in the input factors (land, fertilizer and machinery) can make up for the loss and thus lead to insignificant direct effects. However, this “input-offset-productivity” mechanism fails to radiate to the surrounding provinces and therefore leads to significant indirect/spillover effects. It is projected that COVID-19 will lower China's agricultural growth rate by 0.4%–2.0% in 2020 under different scenarios.

It is crucial to establish a timely disclosure and sharing system of epidemic information across provinces, improve the support and resilience of agricultural production in the short run and accelerate the process of agricultural modernization in the long run.

Considering the infectivity of epidemics, this article evaluates the mechanism of the direct and indirect effects by introducing a spatial dynamic model into the growth accounting framework. Moreover, besides the impact on input portfolio and productivity, this article also investigates whether epidemics reshape agricultural production processes due to panic effects and control measures.

Infrastructure financialization plays a critical role in infrastructure development and urban growth around the world. However, on the one hand, the existing research on the infrastructure financialization focuses on qualitative and lacks quantitative country-specific studies. On the other hand, the spatial heterogeneity and influencing factors of infrastructure financialization are ignored. This study takes China as a typical case to identify and analyze the spatial characteristics, development process and impact factors of infrastructure financialization.

To assess the development and characteristics of infrastructure financialization in China, this study constructs an evaluation index of infrastructure financialization based on the infrastructure financialization ratio (IFR). This study then analyzes the evolution process and spatial pattern of China's infrastructure financialization through the spatial analysis method. Furthermore, this study identifies and quantitatively analyzes the influencing factors of infrastructure financialization based on the spatial Dubin model. Finally, this study offers a policy suggestion as a governance response.

The results demonstrate that infrastructure financialization effectively promotes the development of infrastructure in China. Second, there are significant spatial differences in China’s infrastructure financialization. Third, many factors affect infrastructure financialization, with government participation having the greatest impact. In addition, over-financialization of infrastructure has the potential to lead to government debt risks, which is a critical challenge the Chinese Government must address. Finally, this study suggests that infrastructure financialization requires more detailed, tailored,and place-specific policy interventions by the government.

This study not only contributes to enriching the knowledge body of global financialization theory but also helps optimize infrastructure investment and financing policies in China and provides peer reference for other developing countries.

Cloud-based technologies are reliably improving Information Technology (IT) environment incorporating changes and modifications to the present business structure. Cloud computing enables small and medium-sized businesses (SMBs) to organize and exchange pertinent data and information in real time. This study checks out the influence of cloud-based services (IT infrastructure, expenses of cloud services, cloud data security and IT knowledge of human resources) on customers' satisfaction in SMBs.

Cloud computing offers a way to coordinate and share organizational and personal information and data. The adoption of cloud services is one of the most emerging technological advances in the current competitive business environment. Cloud-based services allow start-ups or SMBs to take advantage of technological advancements and respond more quickly to changing consumer demands. In the available literature, cloud computing has received a lot of attention. However, there is also a research gap in creating a paradigm that links the value development drivers in the electronic industry with the leveraging impact of cloud and intercloud computing resources for start-ups and SMBs. A hypothetical model was constructed based on a literature review, and the associations between the latent variables were investigated utilizing structural equations.

Findings from the study confirmed the validity of the proposed model for customer satisfaction assessment. Besides, the results showed that customer satisfaction is affected by cloud-based services in SMBs. The results illustrated that IT infrastructure influences customer satisfaction significantly and positively, with a T-value of 2.42. Also, the results confirmed that the cost of cloud services with a T-value of 2.68 affects customer satisfaction significantly and positively. Cloud data security also impacts customer satisfaction with a T-value of 5.20. The results also showed that the IT knowledge of human resources affects customer satisfaction with a T-value of 3.01.

The main originality of this research is proposing a new conceptual model to assess the impact of cloud-based services on the satisfaction of the customers in SMBs.

Although numerous studies have explored gamification, its effects on student intrinsic motivation and behavioral engagement remain ambiguous. This study aims to address this gap by investigating the impacts of exogenous and endogenous fantasies on students’ intrinsic motivation, behaviors and perception of learning in gamified, fully online courses.

Using a quasi-experimental design and mixed methods, this study involved two groups of postgraduate students: exogenous fantasy group (N = 23) and endogenous fantasy group (N = 23). Intrinsic motivation was assessed through surveys, while behavioral engagement was tracked over 10 weeks using online trace data. Semi-structured interviews gathered student insights on learning perceptions. The patterns of behavioral engagement in both fantasy groups were analyzed using epistemic network analysis.

Observed behavioral data indicated a significantly higher level of intrinsic motivation in the endogenous fantasy setting. The endogenous group was more engaged in pre-task analysis and post-task reflection, while the exogenous group focused more on quiz work and post-task reflection. Participants in the endogenous fantasy setting also reported increased cognitive engagement and a strong identification with their fictional characters.

Integrating endogenous fantasy into the curriculum can boost students’ intrinsic motivation, behavioral engagement and self-identification. Adopting a first-person perspective that allows students to embody the role of a virtual character is highly recommended. The use of interactive multimedia can greatly enrich the fantasy environment, resulting in a more immersive and engaging learning experience.

The study provides valuable insights into the impact of endogenous and exogenous fantasies on intrinsic motivation and behavioral engagement. It also stands out for its use of epistemic network analysis to assess and compare complex networks of learning task participation in two fantasy settings. Through analyzing these engagement patterns, researchers can obtain a more profound understanding of how each fantasy environment influences student engagement.

This remastered analysis focuses on the impact of entrepreneurial interventions in higher education institutions (HEI), particularly in social entrepreneurship. The study evaluated the effectiveness of such interventions through a pre-and post-test approach, examining various skill sets in students. The primary goal was to analyze the influence of entrepreneurial training programs on students' competencies in social entrepreneurship by analyzing changes in personal behavior, leadership, innovation, social value and management skills before and after the educational interventions.

The study employed a quasi-experimental design, analyzing pre-and post-test results in three distinct social entrepreneurship training experiences. The sample consisted of 304 participants, providing a comprehensive view of the impact of these interventions.

The main findings were: (1) Educational interventions in social entrepreneurship must emphasize strategies for self-awareness, emotional intelligence and personal development improvement. The analysis revealed significant improvements in these areas, indicating that targeted strategies in these domains are essential for enhancing the effectiveness of social entrepreneurship education. (2) The impact of educational interventions on these capabilities can be effectively evaluated using machine learning methods such as ordinary least squares (OLS) regression. This approach allows for the inclusion of variables such as gender, age or location, providing a comprehensive assessment of the interventions' impact. (3) The interventions were particularly effective in improving students' innovation and leadership competencies. The analysis demonstrated substantial enhancements in these areas, underscoring the success of the interventions in developing these critical skills. (4) The study highlighted the need for a more focused approach in future interventions, emphasizing the importance of management, social value and personal skills. Additionally, it pointed out the necessity of developing and utilizing appropriate tools to create and evaluate these interventions effectively.

The study provides insights into improving educational interventions in social entrepreneurship to better develop essential skills in students.

This research introduces a significant approach to educational interventions for educational communities and decision-makers by demonstrating the effectiveness of entrepreneurial training for competencies in innovation and leadership, which are crucial for societal and economic development.