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The aim of this study is to examine the effects of innovativeness (INN), proactiveness, (PRC) and risk-taking (RIT) on the export performance of apparel small and medium-sized enterprises (SMEs) and the role of differentiation and low-cost leadership (LCL) strategies as mediating effects between entrepreneurial orientation (EO) dimensions and the performance of exporting firms. INN, RIT and PRC are considered EO dimensions.

A cross-sectional survey was carried out by providing a questionnaire to the owners, directors and senior managers of the apparel SMEs – the primary data of 550 treated by structural equation modeling (SEM) technique for final data analysis.

The study has revealed the positive dimensional effect of EO on export performance. For the mediation effects of differentiation and LCL, differentiation strategy (DS) positively mediates between INN, PRC and export performance. However, no mediation has been found between RIT and export performance. On the other hand, LCL has found positive effects between INN, RIT and export performance. However, the mediation effect was absent between PRC and export performance.

Limitations/implications- This study has been conducted on only Muslim owners, senior export managers and directors of apparel SMEs in Bangladesh. It has examined the two main competitive strategies as a mediator between EO dimensions and export performance. The findings of this study are based on one country data analysis.

EO, differentiation and low-cost leadership (LCL) strategy are resources and capabilities of an organization to create a competitive advantage to enhance performance. The factors of this research are helpful for SME practitioners.

The direct and indirect effects (differentiation and LCL strategy) of EO dimensions on export performance in an emerging country, i.e. the South-Asia region, is a pioneer study. Therefore, current research has theoretical and managerial implications for the international business and strategic management literature.

Although regulations to prevent financial wrongdoing exist in the USA, whistleblowing (WB) remains important in deterring unethical corporate behavior. The purpose of this study is to address the tension in the audit continuance literature by examining auditor resignations following a WB allegation.

WB allegation data is obtained from the US Occupational Safety and Health Administration and through manually collecting media-reported WB allegations. The authors use a difference-in-difference research design to examine auditor resignations around WB allegations. The test sample is compared against a propensity-score-matched (PSM) sample of control firms.

Auditors are significantly less likely to resign from an engagement following a WB allegation. Auditors prefer to increase their fees and continue with the engagement rather than resign, even when faced with the heightened risks posed by WB allegations. These findings suggest that auditors value the ability to earn a consistent stream of increased revenue from their clients, in agreement with the risk-spreading theory of audit continuance literature.

To the best of the authors’ knowledge, this is the first study that examines auditor resignations following a WB allegation. These findings contribute to the existing WB and auditing literature and add to the auditor acceptance/continuance literature. The findings are meaningful to shareholders, managers, researchers and especially to standard setters who are tasked with ensuring that auditors provide assurances about the accuracy of financial statements.

This study examines the relationship between internal control and corporate environmental responsibility.

Unlike US studies that concentrate solely on internal control over financial reporting, this study uses a comprehensive index that encompasses internal control over financial reporting, operations, and compliance. Corporate environmental responsibility is measured by environmental investments. Our research sample comprises Chinese listed firms from 2010 to 2018.

The results demonstrate a positive correlation between internal control and corporate environmental investments. Furthermore, we find that firms with high-quality internal control can improve their financial and environmental performance through environmental investments. After decomposing internal control into its five components, we show that the control environment, control activities, and information and communication components exhibit stronger effects on environmental investments than the risk assessment and monitoring components. Finally, the cross-sectional analyses reveal that the positive effect of internal control is more pronounced in private firms and in firms that are subject to weaker environmental regulation.

By focusing on the effect of a comprehensive internal mechanism on corporate environmental responsibility in China, this study contributes to the literature in developed-country settings that overwhelmingly focuses on the impact of external stakeholders and regulations.

This study aims to determine the impact of corporate digital transformation on the audit opinions of auditors in A-share nonfinancial listed companies in China. It also examines how corporate internal control and corporate social responsibility (CSR) disclosure levels moderate this effect. This study fills a gap in the literature by investigating the impact of digital transformation on business performance, especially in the Chinese context, where digital transformation is rapidly progressing. This study also offers practical guidance for practitioners on whether and how to undergo a digital transformation and enhance their internal governance and social responsibility practices.

This study uses a sample of 2,637 Chinese A-share nonfinancial listed companies from 2009–2022, after excluding firms with ST, ST* or PT status; negative revenue; and missing data for three or more consecutive years. Digital transformation index data is collected from firms’ annual reports, and the other microlevel data from the Wind and CSMAR databases. The authors winsorize the data at 1% for outliers, resulting in 17,305 firm-year observations. This study uses fixed-effects logistic regression with clustered robust standard errors to analyze the binary dependent variable. This study also performs various robustness checks, such as probit model, multilevel fixed effects model and IV 2SLS estimations, to confirm the validity of the results.

This study reveals that digital transformation leads to standard unqualified audit opinions, meaning that companies that invest more in digital technologies and capabilities has more tendency to receive standard unqualified audit opinions, which signify the reliability and credibility of their financial reporting. This study also finds that corporate internal control and CSR disclosure levels positively moderate the effect of digital transformation on audit opinions. This study further conducts heterogeneity analysis and shows that the positive effect is originated by the state-owned enterprises, firms audited by non-Big4 auditing firms, firms with high internal control levels and firms with low CSR disclosure levels. The results are robust to different econometric methods.

This study contributes to the literature by providing empirical evidence on how digital transformation influences audit quality and credibility and how internal governance and social responsibility practices strengthen this influence. This study also has practical implications for practitioners by providing advice on whether and how to pursue a digital transformation and improve their internal governance and social responsibility practices. This study demonstrates its originality by reviewing the existing literature from three theoretical perspectives: stakeholder, signaling and reputation, and identifying the research gap that the study addresses. This study also compares its findings with previous studies and discusses the implications and limitations of its research. This study also proposes directions for future research based on its findings.

Unverified information avoidance behavior refers to the conscious effort made by individuals to avoid consuming information that has not been verified by credible sources. This behavior is essential in preventing the spread of misinformation that can hinder effective public health responses. While previous studies have examined information avoidance behavior in general, there is a lack of research specifically focusing on the avoidance of unverified information during health crises. This study aims to fill this gap by exploring factors that lead to social media users’ unverified information avoidance behavior during health crises, providing novel insights into the determinants of this protective behavior.

We based our research model on the health belief model and validated it using data collected from 424 individuals who use social media. The proposed model was tested by using the partial least squares structural equation modeling (PLS-SEM) approach.

Our results indicate that individuals’ government social media participation (following accounts and joining groups) affects their health beliefs (perceived severity and benefits of information avoidance), which in turn trigger their unverified information avoidance behavior.

Our study contributes to the current literature of social media crisis management and information avoidance behavior. The implications of these findings for policymakers, social media platforms and theory are further discussed.

As more hotels adopt artificial intelligence (AI), it becomes inevitable for employees to rely on abilities enhanced by the use of AI to complete tasks. However, our understanding of how employees adapt to this shift in work design remains limited. Therefore, the purpose of this study is to explore hotel employees’ approach and avoidance behavioral reactions to dependence on AI.

A three-wave field study was conducted, collecting data from 303 hotel employees and analyzed using Mplus 8.3.

Dependence on AI can be construed as a positive stimulus, augmenting employees’ harmonious work passion and subsequently promoting approach job crafting. The promotion focus of employees positively moderates this process. On the other hand, dependence on AI also can be perceived as a negative stimulus, heightening employees’ feelings of AI threat and, consequently, fostering avoidance job crafting. In this case, the prevention focus of employees positively moderates the process.

This study provides theoretical foundations and decision-making references for management practice. Managers should implement measures to guide employees in developing a proper understanding of AI and provide them with emotional support and institutional safeguards.

This study unveils the consequences of dependence on AI for employees, offering new perspectives for AI research in the hotel industry. By differentiating job crafting, this study theorizes and tests a dual-path model of how dependence on AI may influence hotel employees’ approach and avoidance job crafting, thereby enriching the AI–job crafting literature.

This study disentangles the impact of consumers’ adoption of mini-program channels on social media on their purchase behavior in e-marketplaces from a multichannel retailer’s perspective and examines the moderating roles of two types of brand messages (informational and transformational messages).

Based on 2,204 transaction records from a Chinese multichannel retailer, this study used a Poisson regression model with fixed effects for empirical testing. The case of the WeChat mini-program in China was employed.

Adopting mini-program channels on social media reduces consumers’ purchase frequency but increases their purchase breadth in e-marketplaces. Moreover, informational messages worsen the negative effect of mini-program channel use on purchase frequency. In contrast, transformational messages reduce the negative effect of mini-program channel use on purchase frequency and amplify its positive effect on purchase breadth.

Managers can effectively leverage mini-programs to widen the range of consumers’ product purchases in e-marketplaces and the intensity of transformation messages posted within mini-programs to alleviate their negative impact on purchase frequency in e-marketplaces.

Previous studies only focus on the intrachannel impact of mini-program channels; however, this study highlights their cross-channel impact. Its findings underscore the dual role of mini-program channel use in e-marketplaces. Additionally, the nuanced moderating effects of informational and transformational messages enrich our understanding of mini-program channels on social media. Moreover, a substitution framework is utilized to understand the cross-channel effects generated by mini-program channels, demonstrating the applicability and generalizability of the framework in a new context.

This study aims to investigate the antecedents of corporate social responsibility (CSR) from the perspective of competitive dynamics and proposes a correlation of CSR between competing firms because rival firms’ engagement in CSR induces the focal firm’s catch-up to keep pace with them.

Using a sample of Chinese listed companies through the lens of firm dyads, and drawing on the awareness-motivation-capability (AMC) framework, a set of contingencies of firms’ competitive catch-up in CSR are examined, including the visibility of its competitors, the interdependence between the focal firm and its competitors and the focal firm’s resource slack.

The empirical results reveal that a focal firm’s CSR is in a positive relationship with that of its competitors, which is strengthened by the visibility of its competitors, the interdependence between the focal firm and its competitors, and is affected by the focal firm’s resource slack.

These findings uncover the interplay of CSR among competitors, enriching our understanding of its antecedents by extending the AMC framework to the CSR context.

This study investigates the role of environmental, social and governance (ESG) policies in enhancing the resilience of Chinese firms during the COVID-19 crisis. By analyzing data from over 3,069 publicly listed companies, the research aims to elucidate the impact of robust ESG practices on stock market performance and operational outcomes during economic disruptions.

Using a dataset comprising ESG scores and financial performance metrics of Chinese firms, we conduct an empirical analysis to assess the correlation between ESG practices and corporate resilience during the COVID-19 pandemic. The study focuses on evaluating the individual contributions of the social and governance components to overall firm performance.

The analysis reveals that firms with higher ESG scores, especially in social and governance aspects, exhibit superior stock market performance and operational outcomes during the pandemic. Companies with strong governance mechanisms demonstrate more pronounced benefits, including better long-term sales growth and return on equity (ROE). The findings highlight the critical role of ESG policies in ensuring corporate stability and competitive advantage during crises.

This article provides a comprehensive overview of the impact of corporate ESG ratings on corporate trust and offers a detailed discussion on the protective role of ESG/CSR on firm value during crises, thus providing an original literature contribution.

Fake news refers to intentionally fabricated or misleading information designed to deceive the public and manipulate opinions for personal, political or financial gain. Most existing detection methods primarily focus on capturing language features from news content. However, these methods neglect the varying importance of different news entities. Additionally, these methods tend to overlook the auxiliary role of external knowledge, resulting in an incomplete understanding of the entity. To address these issues, this paper aims to propose a Dual-layer Semantic Information Extraction Network with External Knowledge (DSEN-EK) for fake news detection.

This approach is proposed to comprise three parts: Dual-layer Semantic Information Extraction Network, Entity Integration Network with External Knowledge and Classifier. Specifically, Dual-layer Semantic Information Extraction Network is designed to enhance relationships between entities and the influence of important entity representations. The Entity Integration Network with External Knowledge is proposed to extract entity descriptions from external knowledge bases.

The DSEN-EK model performs well on the Liar, Constraint, Twitter15 and Twitter16 data sets, achieving accuracy of 98.02%, 94.61%, 90.09% and 93.65%, respectively. These results highlight its effectiveness in detecting fake news across different types of content.

The Dual-layer Semantic Information Extraction Network is proposed to capture the relationships between entities and enhance the continuous semantic information of the news. The Entity Integration Network with External Knowledge is designed to enrich entity descriptions, leading to a more comprehensive capture of semantic details.