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This study examined the students' academic performance through psychological capital, academic engagement and academic persistence. It also investigated the function of psychological capital in mediating the relationship between academic engagement, persistence and performance.

The study utilized a quantitative method and structural equation modeling using PLS-SEM version 3. A total of 900 questionnaires were issued to Chinese university students, and 814 data were analyzed.

Findings suggest that academic engagement and persistence significantly and positively impact psychological capital. Psychological capital is also mediated between academic engagement, persistence and performance. Additionally, the study made several recommendations for upcoming researchers and industry professionals.

Analyzing the pupils' academic achievement after COVID-19 reopening as it indicates their attention and engagement in the study. Although previous studies explored students' academic performance regarding the post-COVID effect, the role of psychological capital and engagement in academia in the study has been studied in a post-COVID context.

The study aims to identify the central paradoxical tensions existing in developing resilience in organisations. The main thrust of this study is to develop a thorough understanding of diverse conflicting tensions in building resilience and develop the possible strategies to surmount these tensions.

Using the case study approach, the study applied theory-elaboration strategy as this study is based on well-established literature from both digitalisation and resilience. The study uses the paradox theory lens in a case study to reconcile both theories with contextual idiosyncrasies.

The paradox theory lens provides perspectives to understand tensions during resilience development and the role of digital transformation in this process. It assesses the potential solutions for surmounting tensions in resilient operations. The mapping of workable solutions with different paradoxes and propositions has been proposed for future empirical research.

The study suggests that practitioners should not consider resilience and sustainability as mutually exclusive; instead, managers must embrace ongoing tensions to bring solutions to address these two essential organisational priorities.

To the best of the authors' knowledge, this is the first empirical study that applies paradox theory to understand how an organisation can build resilience while confronting several paradoxes. The study findings support that resilience practices can move in tandem with environmental sustainability goals rather than being usually mutually exclusive.

This article aims to propose a model to support the assessment and prioritization of risk in manufacturing processes.

The model integrates the failure modes and effects analysis (FMEA) criteria with the evaluation procedures of a new hesitant fuzzy linguistic-technique for Order of Preference by Similarity to Ideal Solution (HFL-TOPSIS) variation. A case study evaluating failure risk in a wiring harness assembly process demonstrated the model's applicability. A sensitivity analysis was performed to verify the effect of the variation in the weights assigned to the decision-makers (DMs).

The failure mode (FM) ranking was FM4 > FM9 > FM17 > FM2>FM8>FM12 > FM16 > FM19 > FM11 > FM3>FM18 > FM15 > FM13 > FM10 > FM14 > FM7 > FM1 > FM5 > FM6. These outcomes suggest that “stripping length less than specified” was the top priority among the 19 FMs evaluated. Sensitivity tests demonstrated the effect of the DMs’ weights on the ranking of FMs. A comparison with FMEA and HFL-TOPSIS demonstrates the model's greater capacity to discriminate levels of risk priority, as it identifies a total of 19 risk levels compared with 9 levels in the other approaches.

The adoption of the proposed model can drive substantial improvements in risk management practices across industries, provided that the organization has a decision-making team experienced with FMEA. Therefore, this approach promotes the continuous improvement of operations and ensures that mitigation actions effectively address critical FMs.

This is the first study to propose a risk evaluation model that accounts for DMs' hesitation in defining criteria weights through linguistic expressions. Additionally, it addresses uncertainty when assessing weights for the DMs’ opinions and considers multiple factors that affect these weights in decision-making for risk prioritization.

The present research aims to explore the influence of enterprise social media (ESM) features on employee agility through knowledge sharing and hiding. ESM strain was taken as a moderator in the association among knowledge sharing, knowledge hiding and employee agility. Communication visibility theory is used to underpin the hypothesized research model.

Data is collected from 374 Chinese employees working in different companies. A structural equation modeling (SEM) is applied using AMOS software 21.0.

Findings illustrate that ESM features namely analysis, tracking and communication are significantly connected to knowledge sharing and negatively to knowledge hiding. Knowledge sharing is significantly related to employee agility while knowledge hiding is negatively linked to employee agility. Further, ESM strain strengthens the negative connection between knowledge hiding and employee agility. However, ESM strain has an insignificant moderating effect in the connection between knowledge sharing and employee agility.

The current research has practical implications for ESM users and ESM-enabled organizations. For individuals who use ESM to promote knowledge within an organization, this study highlights the important functioning of ESM features that include analysis, tracking and communication. For managers, this study suggests the use of ESM features to promote knowledge sharing and inhibit knowledge hiding.

The current research investigates how ESM features are associated with employee agility in the workplace. This study proposes that knowledge sharing and knowledge hiding are the mediators of the effect path between ESM features and employee agility. Moreover, the present study extends to ESM literature by highlighting the moderating role of ESM strain using communication visibility theory as a theoretical lens. Lastly, this study quantifies the benefits of ESM features to help organizations train agile employees.

This research is aimed to examine how environmental pollution affects consumers' preference for self-improvement products.

Through a series of three experimental studies, this research substantiates our hypotheses by employing various manipulations of environmental pollution and examining different types of self-improvement products.

The research demonstrates that environmental pollution enhances consumers' preference for self-improvement products via the mediation of perceived environmental responsibility. And the effect is negatively moderated by social equity sensitivity.

The recurrent incidence of environmental pollution has elicited significant concern among the general public and academic scholars. An overwhelming majority of research examining the impact of pollution on consumer behavior has concentrated on its influence on environmentally friendly and healthy consumption patterns. Nevertheless, the current research proposes that pollution fosters a preference for products associated with self-improvement, mediated by perceived environmental responsibility, with the effects being moderated by social equity sensitivity.

Monitoring of the quality of precast concrete (PC) components is crucial for the success of prefabricated construction projects. Currently, quality monitoring of PC components during the construction phase is predominantly done manually, resulting in low efficiency and hindering the progress of intelligent construction. This paper presents an intelligent inspection method for assessing the appearance quality of PC components, utilizing an enhanced you look only once (YOLO) model and multi-source data. The aim of this research is to achieve automated management of the appearance quality of precast components in the prefabricated construction process through digital means.

The paper begins by establishing an improved YOLO model and an image dataset for evaluating appearance quality. Through object detection in the images, a preliminary and efficient assessment of the precast components' appearance quality is achieved. Moreover, the detection results are mapped onto the point cloud for high-precision quality inspection. In the case of precast components with quality defects, precise quality inspection is conducted by combining the three-dimensional model data obtained from forward design conversion with the captured point cloud data through registration. Additionally, the paper proposes a framework for an automated inspection platform dedicated to assessing appearance quality in prefabricated buildings, encompassing the platform's hardware network.

The improved YOLO model achieved a best mean average precision of 85.02% on the VOC2007 dataset, surpassing the performance of most similar models. After targeted training, the model exhibits excellent recognition capabilities for the four common appearance quality defects. When mapped onto the point cloud, the accuracy of quality inspection based on point cloud data and forward design is within 0.1 mm. The appearance quality inspection platform enables feedback and optimization of quality issues.

The proposed method in this study enables high-precision, visualized and automated detection of the appearance quality of PC components. It effectively meets the demand for quality inspection of precast components on construction sites of prefabricated buildings, providing technological support for the development of intelligent construction. The design of the appearance quality inspection platform's logic and framework facilitates the integration of the method, laying the foundation for efficient quality management in the future.

The widespread use of artificial intelligence (AI) technology in the hospitality industry has triggered concerns among frontline service employees about their future careers, namely, AI awareness. This study aims to explore whether AI awareness influences frontline service employees’ silence through psychological contract breach and whether this process is contingent on frontline service employees’ moral identity, drawing on social exchange theory and moral identity theory.

The data were collected from 355 frontline service employees in Chinese hotels using a two-wave survey. SPSS macro PROCESS Model 58 was used to test the proposed hypotheses.

AI awareness increases frontline service employees’ silence by prompting psychological contract breach. This process is moderated by frontline service employees’ moral identity. Specifically, moral identity mitigates the effect of psychological contract breach on silence.

Organizations and managers should pay attention to the impact of AI on frontline service employees and take measures to help them better adapt to the rapidly changing work environment. In particular, it helps reduce frontline service employees’ silence by fostering positive attitudes toward AI, maintaining their psychological contracts and developing their moral identities.

This study enriches the research on the outcomes of AI awareness by directing our attention to frontline service employees’ silence. Moreover, this study not only explores the responses to AI awareness that frontline service employees make as “economic persons” but also examine whether they, as “moral persons,” regulate their responses contingent on their moral identity under the impact of AI. Exploring frontline service employees’ dual identities helps bring this research closer to the realities of managerial practice, thereby contributing to a better understanding and management of their complex responses to AI shocks.

The selfie phenomenon has significantly affected retail environments. This study aims to conceptualise this phenomenon and analyse its findings and implications for managers, researchers and policymakers in retail environments.

A literature review, an exploratory qualitative study and three experiments were conducted to examine the conceptualisation, findings and managerial implications of retail consumer selfie culture as a marketing tool across different age cohorts.

The concepts of the extended self in a digital world, sense of vision (sight), self-imagery and distance explain retail customer selfie culture and the findings that its impact varies significantly across different age cohorts in the retail environment from both vision (sight) and self-imagery perspectives.

This study proposes the retail consumer selfie theory (RCST). RCST can revolutionise retail advertising and branding and design more effective retail selfie campaigns specific to the target audience (different age cohorts) according to different products in various industries, offering new ways of performing product trials, evaluations, implementing retail strategies and public policy.

Drawing upon compensatory ethics theory, this study explored the underlying mechanisms through which gossipers engaged in helping behavior as a form of compensation after initiating negative workplace gossip.

Through a two-wave field study of 394 Chinese employees, this study tests theoretical hypotheses using path analysis and bootstrapping methods.

The findings suggested that negative workplace gossip positively influenced the gossipers’ helping behavior through moral self-image and guilt. Moreover, moral reflectiveness not only positively moderated the impacts of negative workplace gossip on moral self-image and guilt but also positively moderated the mediating effects of moral self-image and guilt in the relationship between negative workplace gossip and helping behavior.

These results enrich the theoretical research on negative workplace gossip, offer new perspectives for studying this phenomenon and provide a theoretical basis and decision-making reference for management practices.