Customer lifetime value is one of the most important tasks for enterprises to maintain customer relationships. However, due to the limitations of using a single data mining method, the measurement of customer lifetime value under the condition of noncontractual relationship has always been a research difficulty. This paper focuses on customer value measurement and customer segmentation based on customer lifecycle value theory, and carries out customer value measurement and customer segmentation research from the perspective of customer value, and constructs customer segmentation model. This paper first conducts feature engineering, such as data selection, data preprocessing, data transformation, and knowledge discovery, and then conducts customer value segmentation based on machine learning algorithms and customer relationship management analysis models and builds a customer value segmentation identification model under the condition of noncontractual relationship. Finally, empirical analysis is carried out with the real customer transaction data of the actual online shopping platform, which verifies the validity and applicability of the customer segmentation method and value calculation method proposed in this paper.

The COVID-19 epidemic has caused more than 6.4 million deaths to date and has become a hot topic of interest in different disciplines. According to bibliometric analysis, more than 340,000 articles have been published on the COVID-19 epidemic from the beginning of the epidemic until recently. Modeling infectious diseases can provide critical planning and analytical tools for outbreak control and public health research, especially from a spatio-temporal perspective. However, there has not been a comprehensive review of the developing process of spatio-temporal dynamic models. Therefore, the aim of this study is to provide a comprehensive review of these spatio-temporal dynamic models for dealing with COVID-19, focusing on the different model scales. We first summarized several data used in the spatio-temporal modeling of the COVID-19, and then, through literature review and summary, we found that the existing COVID-19 spatio-temporal models can be divided into two categories: macro-dynamic models and micro-dynamic models. Typical representatives of these two types of models are compartmental and metapopulation models, cellular automata (CA), and agent-based models (ABM). Our results show that the modeling results are not accurate enough due to the unavailability of the fine-grained dataset of COVID-19. Furthermore, although many models have been developed, many of them focus on short-term prediction of disease outbreaks and lack medium- and long-term predictions. Therefore, future research needs to integrate macroscopic and microscopic models to build adaptive spatio-temporal dynamic simulation models for the medium and long term (from months to years) and to make sound inferences and recommendations about epidemic development in the context of medical discoveries, which will be the next phase of new challenges and trends to be addressed. In addition, there is still a gap in research on collecting fine-grained spatial-temporal big data based on cloud platforms and crowdsourcing technologies to establishing world model to battle the epidemic.

Fostering students’ classroom engagement is a research hotspot in classroom teaching management. Enhancing classroom engagement requires consideration of the interactive effects of physical and interpersonal environments. Considering the characteristics of physical space, the teacher gives feedback on student engagement in terms of different seating positions. Further, near-seated peer group engagement has an impact, though previous research has found this to be inconsistent. The teacher and near-seated peer groups have different paths of influence on classroom engagement, and there is interplay between them. However, based on realistic classroom scenarios, it is difficult for traditional research methods to reveal how spatially heterogeneous and non-linear micro-interactions among teachers, students, and near-seated peer groups evolve into dynamic changes in macro-classroom engagement. Hence, this study utilized agent-based simulation to explore the non-linear dynamic mechanism underlying how teacher-student proximity, teacher feedback, and near-seated peer groups affect classroom engagement, thereby shedding light on the evolutionary features of classroom engagement. According to the results, the teacher’s positive feedback promoted an S-shaped increase in classroom engagement, and the closer a student sat to the teacher, the greater the increase was. The level and homogeneity of near-seated peer group engagement were predictors of changes in classroom engagement. Moreover, the proximity of students to the teacher, teacher feedback, and near-seated peer groups had a joint effect on student engagement. The compensation effect of the teacher’s positive feedback on the impact of low-engagement, near-seated peer groups was weaker than that of highly engaged, near-seated peer groups on the effects of the teacher’s negative feedback. This suggests that the model of teacher-student proximity and teacher feedback effects differed from that of near-seated peer group influence, and the two interacted and showed asymmetry.

Purpose: In the practice of inspiring employees’ innovative behavior (IB), managers often pay attention to the role of policies, capitals, incentive measures, equipment and other factors, while ignoring the role of the relationship between leaders and employees. Based on social exchange theory and conservation of resources theory, this paper is to examine the mediating role of job satisfaction (JS) and organizational commitment (OC) in the relationship between supervisor–subordinate guanxi (SSG) and employee IB, and the moderating role of psychological safety (PS) in the series mediation model between SSG and employee IB. Patients and Methods: Cross-sectional data came from 207 employees of Chinese scientific and technological enterprises. The participants completed the SSG scale, JS scale, OC scale, IB scale, and PS scale. SPSS PROCESS macro was used to test the research hypothesis. Results: SSG was positively associated with employee IB. SSG can not only influence IB through JS or OC (SSG→JS→IB; SSG→OC→IB) but also influence IB through JS and OC (SSG→JS→OC→IB). PS moderated the joint mediating effects between SSG and IB (SSG→JS→OC→IB). Conclusion: To stimulate employees’ IB within an enterprise can pay attention to the relationship between leaders and employees, improve employee JS, and strengthen employee OC. The lower the PS, the stronger the joint mediation effects between SSG and employee IB. Therefore, leaders should also pay attention to employees with high PS to avoid the counterproductive effect of cultivating SSG.

Purpose: Based on social information processing (SIP) model and conservation of resources (COR) theory, this paper is to examine the mediating and moderating roles of psychological safety (PS) in the relationship between work-related leader-member exchange (LMX)/non-work-related supervisor-subordinate guanxi (SSG) and employee affective commitment (AC). Participants and Methods: Cross-sectional data came from 213 enterprise employees in China. The participants completed the LMX scale, SSG scale, PS scale, and AC scale. SPSS PROCESS macro and RWA-Web were used to test the research hypothesis. Results: Both LMX and SSG were positively related to employee AC. LMX was more strongly associated with AC than SSG. PS partially mediated the influence of LMX/SSG on AC. PS negatively moderated the influence of LMX on AC, whereas it did not moderate the influence of SSG on AC. Conclusion: Different types of supervisor-subordinate relationships (SSR) were both beneficial to employee AC, and work-related LMX was more closely related to employee AC. Different types of SSR could both affect employee AC through PS. In addition, high PS also reduced the relationship between LMX and employee AC. Therefore, in the context of Chinese culture, enhancing employees’ AC within an enterprise can not only pay attention to the work-related LMX and non-work-related SSG but also the appropriate cultivation of employees’ PS.