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This research explores the appropriateness of using a digital learning system based on a multiplayer online animated game in firefighting education and training. Use of the game improved learning was effective. It can increase learners' understanding of the taught content and their willingness to learn.

The research applies digital learning based on a multiplayer online animated game coupled with 3D and virtual reality (VR) technology. To verify the effectiveness of this approach, participants were divided into two groups, an experimental group (using the game) and a control group (not using the game). T-tests were used to compare the learning of the two groups.

Firefighting knowledge was significantly better among the experimental group than the control group. Learning was explored in three different domains: basic firefighting knowledge, fire extinguisher operation and fire source identification; the latter two showed statistically significant differences. After learners acquired knowledge from multimedia, the addition of a VR exercise effectively helped them to remember what they learned and increased their understanding of the taught content.

The approach proposed in this study applies digital learning via a multiplayer online animated game to explore the appropriateness of such games in firefighting education and training. Use of the game improved learning and was effective. It can not only increase learners' understanding of the taught content, but also their willingness to learn.

This study examines why and when qualitative job insecurity (JI) leads to instigated workplace incivility.

The authors collected data from 227 Chinese full-time employees from multiple organizations at two time points. Structural equation modeling was used to test hypotheses.

Results show that qualitative JI is positively related to instigated workplace incivility through negative emotions; this indirect relationship is weaker among employees with higher self-compassion and stronger among employees with higher rumination.

The authors shift the predominant focus on the predictor of instigated workplace incivility from quantitative JI to qualitative JI. Based on the transactional model of stress and the stressor–emotion model of counterproductive work behavior (CWB), they provide new theoretical insights on why qualitative JI affects workplace incivility and identify new boundary conditions that affect employees' reactions to qualitative JI.

The purpose of this paper is to explore the relationship between demographic diversity on boards and employer/employee relationship (EER) and to test the moderating effect of contextual factors such as a firm’s financial situation.

This paper analyzes data from over 1,000 publicly listed US firms and uses hierarchical regression.

Demographic diversity on boards of a given firm, such as ethnic diversity and gender diversity, should have positive effects on EER, which can be considered as an important dimension of overall human resource management performance in a given firm. Contextual factors such as a firm’s financial situation should moderate the relationship between demographic diversity on boards and the EER.

First, this research contributes to the current literature by showing that EER can be influenced by demographic diversity on boards, which further helps to highlight the beneficial effect of demographic diversity in top management team. Second, this study uncovers the moderating role of some contextual factors such as a firm’ financial situation. Third, this study also contributes to the corporate governance literature by studying the link between demographic diversity on boards and EER.

This study aims to overcome the problem of traditional association rules relying almost entirely on expert experience to set relevant interest indexes in mining. Second, this project can effectively solve the problem of four types of rules being present in the database at the same time. The traditional association algorithm can only mine one or two types of rules and cannot fully explore the database knowledge in the decision-making process for library recommendation.

The authors proposed a Markov logic network method to reconstruct association rule-mining tasks for library recommendation and compared the method proposed in this paper to traditional Apriori, FP-Growth, Inverse, Sporadic and UserBasedCF algorithms on two history library data sets and the Chess and Accident data sets.

The method used in this project had two major advantages. First, the authors were able to mine four types of rules in an integrated manner without having to set interest measures. In addition, because it represents the relevance of mining in the network, decision-makers can use network visualization tools to fully understand the results of mining in library recommendation and data sets from other fields.

The time cost of the project is still high for large data sets. The authors will solve this problem by mapping books, items, or attributes to higher granularity to reduce the computational complexity in the future.

The authors believed that knowledge of complex real-world problems can be well captured from a network perspective. This study can help researchers to avoid setting interest metrics and to comprehensively extract frequent, rare, positive, and negative rules in an integrated manner.

In crises such as the coronavirus disease 2019 (COVID-19) pandemic, governments need to act in time to lead citizens toward rational reactions and disclose information effectively to the public. This paper aims to understand the content published by the government and identify how citizen engagement relates to content type and emotional valence.

The grounded theory approach was adopted and nine types of content posted by the government were observed. The data were obtained from “People's Daily”, an official Sina Weibo account representing the voice of the Chinese government, from January 3 to June 22 in 2020.

The analysis shows that information related to emotional support and social mobilization were the most reposted, while those mentioning immoral and illegal incidents were the most liked and commented. Also, it was found that positive posts tend to attract more likes, yet with fewer reposts than neutral posts.

The authors adopted thematic analysis and focused on the impact of post content and valence on user participation behavior. This study expands the existing literature. The government can improve crises management capability by learning about citizen engagement behaviors on social media.

This study aims to explore the relationship between managerial ownership and environmental innovation, particularly focusing on the impact of minority shareholder protection within the context of China’s A-share listed companies.

The study employs a fixed effect model over a decade-long sample, analysing secondary data from nonfinancial Chinese A-share firms. The two-stage least squares (2SLS) method is adopted to address endogeneity concerns.

The results demonstrate a significant positive influence of managerial ownership on environmental innovation, suggesting that top managers who have a say in the boardroom are inclined towards sustainable development. The presence of minority shareholders' protection positively moderates this relationship, underlining their roles in fostering environmentally friendly development. The subsample analysis showed that these relationships vary between state-owned enterprises (SOEs) and non-SOEs. It also differs between heavily and lightly polluting industries, which indicates that it is not enough to just have internal self-management, and more external pressure is necessary in heavily polluting industries.

Our study underscores the importance for managers to recognize the potential of aligning their ownership interests with environmental objectives. Companies can enhance their commitment to sustainability by fostering an internal environment that supports minority shareholder rights.

This study specifically focuses on the role of top managers and minority shareholders, providing new empirical evidence on how their influence can drive sustainable development initiatives. It is also among the few studies that differentiate between firm characteristics and pollution intensity, which provides valuable insights into how the impact of managerial ownership and minority shareholder protection varies across different contexts.

With the rapid development of fresh food e-commerce, sustaining customer loyalty is becoming critical for fresh food e-tailers (FFE) to be competitive. This study aims to investigate how to sustain customer loyalty of FFE in China.

A comprehensive literature review leads to the development of a conceptual model using the American customer satisfaction index (ACSI). This model is then tested and validated through structural equation modelling (SEM) of the survey data in China.

The study reveals that trust and perceived product risk significantly affect customer loyalty. It states that trust is significantly influenced by customer satisfaction and perceived product risk. Furthermore, the study shows that perceived risk of online shopping does not significantly influence customer trust and loyalty.

This study is the first in China for exploring how to sustain customer loyalty of FFE. The findings are significant for FFE to develop customer loyalty by formulating appropriate policies and strategies.

Online business can be an attractive career choice but bears gendered implications under China’s market economy. This study aims to examine how highly educated young women negotiate their career choice of online business, given their enhanced career ambitions and the persisting conservative views of their parents. It is to be examined how these factors interact in shaping women’s strategies and commitment to their nonconventional careers.

The study draws on 23 interviews with 18 women involved in online business. The interviews were coded by themes about how women perceive and make career choices to enter online business, the influence of various motivations (e.g., economic security, decency, autonomy and earning potential) and women’s interactions with their parents under gendered social expectations. The study analyzes and categorizes women’s varied strategies and levels of commitment in taking up online business, an attractive but suspicious career for highly educated young women.

The study finds that some women chose to conduct online business as a secondary job behind their stable and formal primary job; their compromise under parents’ preferences and social expectations as “compliant daughters,” willingly or forced, coexisted with their persisting interest in online entrepreneurship. Other women, or “self-determined daughters,” embraced online business as their primary job; some benefited from parents’ tolerant views, but others needed to handle the pressure of parental disapproval by hiding or proving their nonconventional career choices worthwhile.

This study speaks to the gendered opportunity-necessity framework of entrepreneurship by illustrating women’s multiple motivations in China’s market reforms and the rising online entrepreneurship dynamics. The findings contextualize women’s career choices in different family dynamics and suggest how social expectations and gender norms are imposed and transformed, with a focus on the shifting gendered concerns of opportunity, security and decency in an era of digital economy.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

Accounting for locational effects in determining price is of fundamental importance. The demise of the mainstream property market has culminated in increasing appetite and investment activity within the private rental sector. The primary purpose of this paper aims to analyse the local variation and spatial heterogeneity in residential rental prices in a large urban market in the UK using various geo-statistical approaches.

Applying achieved price data derived from a leading internet-based rental agency for Belfast Northern Ireland is analysed in a number of spatially based modelling frameworks encompassing more traditional approaches such as hedonic regressive models to more complex spatial filtering methods to estimate rental values as a function of the properties implicit characteristics and spatial measures.

The principal findings show the efficacy of the geographically weighted regression (GWR) technique as it provides increased accuracy in predicting marginal price estimates relative to other spatial techniques. The results reveal complex spatial non-stationarity across the Belfast metropole emphasizing the premise of location in determining and understanding rental market performance. A key finding emanating from the research is that the high level of segmentation across localised pockets of the Belfast market, as a consequence of socio-political conflict and ethno-religious territoriality segregation, requires further analytical insight and model specification in order to understand the exogenous spatial and societal effects/implications for rental value.

This study is one of only a few investigations of spatial residential rent price variation applying the GWR methodology, spatial filtering and other spatial techniques within the confines of a UK housing market. In the context of residential rent prices, the research highlights that a soft segmentation modelling approaches are essential for understanding rental gradients in a polarised ethnocratic city.