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This study aims to build on social comparison theory to develop a theoretical model of leader–member exchange (LMX) relationship to workplace ostracism through perceived organizational status by coworkers and envy. This study further proposes that warmth and competence may potentially moderate these two indirect effects.

This study tested the hypotheses in a battery manufacturing company located in South China by a survey of 216 employees organized in 55 work teams, using different sources. Additionally, the authors conduct two online vignette experiments to test this study’s mediation, proving the causality.

The authors found that high-level LMX leads to both envy and perceived organizational status by coworkers, which results in a mixed blessing on workplace ostracism toward the employee with high-level LMX. The focal employee’s warmth and competence moderate these indirect relationships.

The authors use LMX to explore antecedents of workplace ostracism and explain how and when these focal employees suffer workplace ostracism from their coworkers. The authors extend the research on LMX by examining the interpersonal risk of being a focal employee. The authors discover two critical boundary conditions – warmth and competence.

This study suggests that it is important to balance the level of the differential LMX; appropriately endorsing other members is a good way to avoid eliciting envy and opposition. Meanwhile, person-oriented citizenship behaviors such as demonstrations of concern or help may shortly build up an employee’s warm impression on their coworkers.

By discovering the bright and dark sides of LMX, this paper has the potential to advance theories on LMX and workplace ostracism. Therefore, the authors believe the current research will have an important impact on relevant research in the future.

Current multi-source image fusion methods frequently overlook the issue of detailed features when employing deep learning technology, resulting in inadequate target feature information. In real-world mission scenarios, such as military information acquisition or medical image enhancement, the prominence of target feature information is of paramount importance. To address these challenges, this paper introduces a novel infrared-visible light fusion model.

Leveraging the foundational architecture of the traditional DenseFuse model, this paper optimizes the backbone network structure and incorporates a Unique Feature Encoder (UFE) to meticulously extract the distinctive features inherent in the two images. Furthermore, it integrates the Convolutional Block Attention Module (CBAM) and the Squeeze and Excitation Network (SE) to enhance and replace the original spatial and channel attention mechanisms.

Compared to other methods such as IFCNN, NestFuse, DenseFuse, etc., the values of entropy, standard deviation, and mutual information index of the method presented in this paper can reach 6.9985, 82.6652, and 13.6022, respectively, which are significantly improved compared with other methods.

This paper presents a UFEFusion framework that synergizes with the CBAM attention mechanism to markedly augment the extraction of detailed features relative to other methods. Moreover, the framework adeptly extracts and amplifies unique features from disparate images, thereby elevating the overall feature representation capability.

Political factors play a crucial role in China's initial public offering (IPO) market due to its distinctive institutional context (i.e. “economic decentralization” and “political centralization”). Given the significant level of IPO underpricing in China, we examine the impact of local political uncertainty (measured by prefecture-level city official turnover rate) on IPO underpricing.

Using 2,259 IPOs of A-share listed companies from 2001 to 2019, we employ a structural equation model (SEM) to examine the channel (voluntarily lower the issuance price vs aftermarket trading) through which political uncertainty affects IPO underpricing. We check the robustness of the results using bootstrap tests, adopting alternative proxies for political uncertainty and IPO underpricing and employing subsample analysis.

Local official turnover-induced political uncertainty increases IPO underpricing by IPO firms voluntarily reducing the issuance price rather than by affecting investor sentiment in aftermarket trading. These relations are stronger in firms with pre-IPO political connections. The effect of political uncertainty on IPO underpricing is also contingent upon the industry and the growth phase of an IPO firm, more pronounced in politically sensitive industries and firms listed on the growth enterprise market board.

Local government officials in China usually have a short tenure and Chinese firms witness significantly severe IPO underpricing. By introducing the SEM model in studying China IPO underpricing, this study identifies the channel through which local government official turnover to political uncertainty on IPO underpricing.

This paper proposes a new intra-layer partition adaptive slicing algorithm for FDM 3D printing, aiming to further improve forming efficiency based on the adaptive slicing algorithm while preserving the surface finish quality of the formed model.

This method initially applies a large layer thickness for primary slicing, then refines layer thickness in layer height ranges with significant cross-sectional contour changes. Refined layers are partitioned: the internal region uses the large layer thickness for efficiency, while the external region uses a smaller layer thickness for surface quality. A thickness ratio and transition zone between regions prevent overlaps and gaps in printing paths.

The experimental results show that, compared to traditional adaptive slicing algorithms, the intra-layer partition adaptive slicing algorithm can effectively improve forming efficiency for most models while ensuring the model’s surface finish, with minimal impact on the bonding strength of the model.

The intra-layer partition adaptive slicing algorithm is a novel algorithm improved upon the traditional adaptive slicing algorithm, enabling models to achieve higher printing efficiency while maintaining the surface finish provided by the conventional adaptive slicing algorithm. This algorithm is of significant importance to vendors and individual users who provide printing services for large-sized fused deposition modeling models, as it can greatly enhance their production efficiency.

This paper examines the moderating role of firms’ litigation environment on the association between gender diversity and financial reporting quality.

This study draws on a sample of US firms to examine the moderating role of firms’ litigation environment on the association between gender diversity and financial reporting quality. Firm-specific financial data come from Compustat. To measure the firms’ litigation environment, we use state-level datasets from the Lawsuit Climate Survey conducted for the US Chamber Institute for Legal Reform by the Harris Poll.

Findings suggest that firm litigation environment moderates gender diversity, as defined by female members on the board to subdue our first proxy for financial reporting quality (accruals-based earnings management), but our second proxy for financial reporting quality (real-activities manipulations) increases in a firm’s litigation environment. To the extent that our results hold after controlling for firms’ reputation indicates that female members on the board are sensitive to reputational loss and protect firms’ reputation in a litigation environment.

The study is based on a specific country, limiting the generalizability of the findings.

The findings provide support for promoters and advocates of gender diversity in corporate boards. Specifically, it shows the importance of gender diversity policies in business and society.

This study is the first to examine the moderating role of firms’ litigation environment on the association between gender diversity and financial reporting quality. The study provides novel evidence and shows that the litigation environment moderates gender diversity to improve financial reporting quality in the short-term (by decreasing accruals manipulation). In firms’ litigation environment, when female members on the board are restrained from engaging in accruals earnings management, they shift to value-destroying and costly real activities to maintain reputation and firm performance. To the extent that we control for the potential effects of firms’ reputation and financial performance, our findings suggest that ethical concerns are likely to drive female members on the board to produce high-quality financial reports.

This research examines the complex relationship between usage of Chat Generative Pre-Trained Transformer (ChatGPT) amongst student and their creativity, learning and assessment using empirical data collected from postgraduate students. In addition, the study explores the student’s intrinsic motivation for usage to understand student categories. This research seeks to provide further insights into this artificial intelligence tool in enhancing the educational ecosystem for all stakeholders concerned.

The target population of this research – the students of post-graduation in diverse fields of science and management. A five-point Likert scale-structured questionnaire adapted from earlier literature relevant to the research questions was adopted for data collection. The data were collected for two months, resulted in 403 usable responses. Ethical considerations of assurance of confidentiality to the participants were strictly adhered to. Structured equation modelling (SEM) was employed to explore the relationships between the constructs of the study for the assessment of latent relationships. SmartPLS 4 was used to explore these relationships.

Usage has a negative impact on a student’s creativity, but increased usage of ChatGPT encourages a student’s adoption due to its perceived usability. Pedagogical applications of ChatGPT aid students as a learning tool but require controlled usage under supervision.

This study is innovative in the context of postgraduate students, where very little evidence of creativity exists. Through this research, the authors illuminate how ChatGPT use affects academic performance, benefiting educators as a tool but for evaluation and assessment, policymakers and students. The findings of the study provide implications that help to create effective digital education strategies for stakeholders.

The effects of gendered views on employee voice are of great importance for knowledge sharing within public universities. Yet, they are still neglected by current human resource management and entrepreneurship literature. While strengthening themselves by reinforcing the strengths and opportunities, public universities can generate entrepreneurial opportunities through various knowledge-sharing mechanisms, including social networks and employee voice. This became a crucial lever for public universities to leverage competitive advantages and to support entrepreneurial activities through network knowledge-based sharing. For this purpose, this study aims to examine the various aspects of entrepreneurship via the voice of employees, emphasizing the moderating effect of gender and the mediating role of social networks on the link between employee voice and the entrepreneurial atmosphere of universities.

The authors collected survey data from a cross-sectional sample of 335 employees engaged in entrepreneurship activities within public universities in an emerging economy context and analyzed the data using partial least squares structural equation modeling (PLS-SEM) with the Smart-PLS software.

The PLS-SEM analysis found that different dimensions of the university entrepreneurial climate (communication, knowledge sharing and innovative climate) positively impact members’ voices within public universities. This effect is amplified by social networks, which are crucial for spreading knowledge among faculty, thereby fostering a more open and collaborative academic environment.

When acting, the university top management team should encourage the generation and dissemination of entrepreneurial ideas to nurture a dynamic entrepreneurial atmosphere and social involvement, ultimately supporting sustainable competitive advantages through a culture of strategic knowledge sharing. The results have practical implications for university managers, entrepreneurship education actors, administrators, policymakers and entrepreneurial ecosystem actors, by demonstrating how social networks can amplify the dissemination of ideas and entrepreneurial spirit.

This research explores how entrepreneurship and social networks can help faculty members have a stronger influence in academic settings. It also fills in the gaps in knowledge about how human resource management and entrepreneurship can work together to create a more communicative and innovative academic environment. Additionally, this study brings new ideas to existing literature by looking at how gender differences can affect employee voice, particularly emphasizing the importance of women in leadership roles at universities. This study is also the first to delve into how entrepreneurship and social networks, along with gender perceptions, play a role in shaping the voice of employees in a public university.

The purpose of this study is to assess the implications of auditor–client geographic proximity on audit fees, audit report lag and audit quality in the context of an emerging economy, Bangladesh.

The auditor–client proximity is gauged in kilometers and travel time, consistent with prior research to assess its association with audit fees, audit report lag and audit quality. Analyzing a data set of 469 firm-year observations from 2018 to 2021 through panel regression, the results are then interpreted in accordance with cluster theory and transaction cost theory.

The findings affirm a significant positive association of auditor–client proximity with audit fees and audit report lag. Distant auditors charge lower fees and maintain the timeliness of audit reports to capture and retain distant clients. In addition, the study uncovers a negative association between proximity and audit quality. Geographic proximity can create a familiarity threat between the management team of the client and the local auditor, which can decrease audit quality. These associations are more pronounced in low-risk clients than the high-risk ones.

These findings underscore the intricate interplay between geographic proximity, communication hurdles and their effects on diverse facets of the audit process that both auditor and client should consider in future audit engagement.

This research criticizes the existing literature linking auditor–client proximity with audit quality, fees and report lags and provides novel insight from an emerging economy context.

This paper investigates the mediated-moderation roles of adhocracy culture (ADC) and business ecosystem learning between user experience (UX) and continuous use of block-chain technologies (CUBT) among freight firms in Ghana.

A stratified sampling technique was used in the selection of 327 employees of freight firms. This paper employs regression analysis to examine the hypothesized paths.

The findings show that ADC moderates the partially mediated role of the business ecosystem between technology UX and CUBT.

Based on the cross-sectional design adopted, the study findings do not reflect the changing dynamics of employees of freight firms over a long period of time in Ghana.

This research is one of the first in maritime transport literature to explore the relevance of block-chain technologies among freight firms in an emerging economy.

The purpose of this paper is to empirically analyze the impact of directors’ and officers’ (D&O) liability insurance on enterprise strategic change. It also explores the mediating role of litigation risk, the moderating roles of enterprise science and technology level and precipitation organizational slack between them. In addition, it examines the joint moderating roles of the top management team (TMT) external social network and enterprise science and technology level, and enterprise scale and precipitation organizational slack.

Using the unbalanced panel data of A-share listed companies in the Shanghai and Shenzhen stock exchanges of China from 2002 to 2020 as the research sample, this paper uses the ordinary least square method and fixed-effect model to study the relationship between D&O liability insurance and enterprise strategic change. The study also focuses on the mediating mechanism and moderating mechanisms between them.

The authors find that D&O liability insurance has an “incentive effect,” which can significantly promote enterprise strategic change. Litigation risk plays a partial mediating role between D&O liability insurance and enterprise strategic change. Enterprise science and technology level and precipitation organizational slack negatively moderate the relationship between D&O liability insurance and enterprise strategic change. TMT external social network and enterprise science and technology level, and enterprise-scale and precipitation organizational slack have joint moderating effects on the relationship between D&O liability insurance and enterprise strategic change.

This paper confirms the “incentive effect hypothesis” of the impact of D&O liability insurance on enterprise strategic change, which not only broadens the research perspective of enterprise strategic management but also further expands the research scope of D&O liability insurance. Besides, this paper thoroughly explores the influencing mechanisms between D&O liability insurance and enterprise strategic change, providing incremental contributions to the research literature in the field of enterprise risk management and corporate governance. The findings have practical guiding significance for expanding the coverage of D&O liability insurance, promoting the implementation of strategic changes and improving the level of corporate governance of Chinese enterprises.