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This paper explores the association between directors’ and officers’ liability insurance (D&O insurance) and management tone manipulation.

This study uses data from A-share listed non-financial companies from 2009 to 2021 as its sample for empirical tests. In addition, the study relies on text analysis and the construction of models to investigate the relationship between D&O insurance and management tone manipulation.

The authors find that the purchase of D&O insurance will lead to management tone manipulation in the “management discussion and analysis” part of companies’ annual reports, and operating risk and agent cost are the two paths for the effect. Further analysis shows that having a male CEO and employing high-quality auditors can weaken the positive impact of D&O insurance on tone manipulation.

This paper provides a new approach for studying the literature related to D&O insurance and management behavior, and the findings enrich our understanding of the influencing factors and the mechanism of management tone manipulation, thus revealing policy implications for further standardization of the terms and system of D&O insurance in China.

This study aims to explore Augmented Language Models (ALMs) for synthetic data generation in services marketing and research. It evaluates ALMs' potential in mirroring human responses and behaviors in service scenarios through comparative analysis with five empirical studies.

The study uses ALM-based agents to conduct a comparative analysis, leveraging SurveyLM (Bickley et al., 2023) to generate synthetic responses to the scenario-based experiment in Söderlund and Oikarinen (2018) and four more recent studies from the Journal of Services Marketing. The main focus was to assess the alignment of ALM responses with original study manipulations and hypotheses.

Overall, our comparative analysis reveals both strengths and limitations of using synthetic agents to mimic human-based participants in services research. Specifically, the model struggled with scenarios requiring high levels of visual context, such as those involving images or physical settings, as in the Dootson et al. (2023) and Srivastava et al. (2022) studies. Conversely, studies like Tariq et al. (2023) showed better alignment, highlighting the model's effectiveness in more textually driven scenarios.

To the best of the authors’ knowledge, this research is among the first to systematically use ALMs in services marketing, providing new methods and insights for using synthetic data in service research. It underscores the challenges and potential of interpreting ALM versus human responses, marking a significant step in exploring AI capabilities in empirical research.

There is a dearth of research in the field of social marketing that attempts to understand why consumers prefer to use plastic packages when using online food delivery services. In addressing this issue, this study aims to investigate the role of moral disengagement, myopia and environmental apathy in the young generations' intentions to use plastic bags while ordering food online. It also examines the mediating role of moral disengagement and the moderating role of guilt in the context of the online food delivery service industry in China.

An online survey was designed to collect data, which yielded 256 usable responses. The partial least squares structural equation modelling (PLS-SEM) technique (SmartPLS 4.0) was used to test the study hypotheses.

The results indicate that environmental apathy, myopia and moral disengagement exert significant negative effects on consumer intention to use plastic. In addition, moral disengagement was able to mediate the links between “environmental apathy”, “myopia” and “plastic usage intention”. Lastly, consumers’ guilt was found to be a significant moderator in the link between moral disengagement and plastic usage intention.

This research holds significant importance for social marketers in the online food delivery service industry. Particularly, by understanding consumers' negative behavioural aspects, social marketers can implement marketing strategies that emphasise green practices for environmental well-being.

This is a pioneer study that focuses on the negative aspects of consumer behaviour, such as myopia, environmental apathy and moral disengagement, to understand what drives young consumers to use plastic. Additionally, this study investigates several new relationships in the social marketing field, such as the mediating effect of moral disengagement between myopia, environmental apathy and plastic usage intention. It also tests the moderating effect of guilt on the link between moral disengagement and use intention.

This study examines the digital accessibility of information services for students with disabilities at the University of Jordan. Despite advancements in disability rights and technology, academic libraries often lag in providing fully accessible digital services.

The mixed-methods research involved quantitative surveys from 173 students with disabilities and a qualitative interview with the head of the information application department, in addition to a focus group interview with 10 students with disabilities. Quantitative analysis included means, standard deviations and four-way ANOVA to identify significant differences in perceptions. Qualitative insights highlighted specific issues and recurring themes, revealing significant gaps in digital accessibility.

The results revealed a weak level of digital accessibility of students with disabilities to information services in academic libraries in Jordan is very low. The findings indicate a need for improvements in library infrastructure, staff training and policy development. The study also offers insights into challenges in a developing country context and provides recommendations for enhancing library inclusivity and support structures, emphasizing the importance of aligning services with international accessibility standards.

The findings will primarily be beneficial for library managers to understand their library’s deficiencies and responsibility towards the local community and the enhancement of digital inclusion. This understanding will aid in planning training programs and workshops for employees on supporting students with disabilities. Additionally, it serves as a valuable resource for collaboration between libraries and educators to organize educational sessions for academic librarians in Jordan and other developing nations.

It serves as a valuable resource for collaboration between libraries and educators to organize educational sessions for academic librarians in Jordan and other developing nations. This research adds value to existing literature by highlighting the context in one developing country.

The key to preventing employees from engaging in deceptive knowledge hiding is fostering a responsible environment. Drawing on social cognitive theory, this study aims to explore the factors that inhibit deceptive knowledge hiding and to construct potential pathways for enhancing individual moral cognition. This study further analyzes the moderating effect of leader–follower value congruence on these relationships.

Using data from 341 full-time employees in various service industries in China, this study conducted path analysis, the product-of-coefficients method and bootstrapping to test the hypotheses through a three-stage, time-lagged survey.

The empirical results show that responsible leadership is negatively associated with employees’ deceptive knowledge hiding. Employee moral reflectiveness mediates this relationship, whereas leader–follower value congruence moderates the indirect effect of responsible leadership on deceptive knowledge hiding through moral reflectiveness.

First, this study extends field research by introducing positive leadership factors to reduce deceptive knowledge hiding, whereas prior studies focused mainly on negative leadership antecedents. Second, this study sheds light on the underlying moral cognitive mechanisms and explains how responsible leadership can prevent implicit unethical behavior. Third, it reveals how leader–follower value congruence can enhance the impact of responsible leadership on moral reflectiveness, offering novel insights into the role of value-based fit in reducing deceptive knowledge hiding.

The main purpose of this research study is to investigate and examine the factors that might influence the intention to adopt and use mobile payment and their relationships during the COVID-19 pandemic.

This research study used both mobile payment adoption literature, The Technology Adoption Model and Unified Theory of Acceptance and Use of Technology, to propose a conceptual framework for mobile payment adoption. Quantitative method is used in which 306 participants responded to an online survey to validate the proposed conceptual framework.

The introduced integrated model embraced perceived risk, transaction transparency, mobile payment usefulness, social influence, performance expectation as independent variables and usage continuation intention to adopt mobile payment as the dependent variable. The results from data analysis have statistically revealed significant relationships and a positive impact of perceived risk, mobile payment usefulness, social influence and performance expectation. Also, the results identified a negative impact for the transaction transparency factor. As this research study is conducted at a later stage of the COVID-19 pandemic, it adds value to the existing literature by providing insights to business managers on the factors influencing mobile payment usage and other implications related to increasing the market potential for businesses in the new normality of the coronavirus pandemic.

This paper offers a combination conceptual framework of mobile payment adoption based on a literature review on mobile payment adoption from information systems perspective. It adapts integrated model to establish a more comprehensive innovation adoption framework for mobile payment.

This study aims to identify which types of information quality influence purchase intentions the most in live streaming commerce and to examine the role of network size in this context.

We propose a model to investigate the correlation among the quality of different information in live streaming commerce, consumer trust, network size and purchase intention. An empirical analysis of 505 questionnaires was conducted by constructing a structural equation model.

The empirical findings indicate that information quality can directly enhance purchase intention and exert an indirect influence through the mediating factors of trust in products and streamers. Perceived network size positively moderates the relationship between information quality and trust in products. Of the five types of information, the quality of bullet-screen comments information is most important to consumers.

This study represents the first systematic analysis of how the quality of multiple types of information in live streaming commerce influences consumer trust and purchase intention, integrated within a unified framework. It uniquely introduces network size as a moderating variable, offering both theoretical insights and practical guidance for balancing information quality with network size in live streaming commerce environments.

This study proposes a framework that demonstrates how the perceived value of augmented reality (AR) shopping influences the formation of psychological ownership of product and technology. The mediating role of flow experience and the moderating role of perceived control are identified.

An online survey study recruiting 480 participants who experienced AR shopping was conducted to test the hypotheses.

Functional value is negatively related to psychological ownership of product and technology whereas emotional value shows opposite effects. Flow experience mediates the relationships between functional/emotional value and psychological ownership of product and technology. Perceived control moderates the relationship between emotional value and flow experience, as well as the relationship between functional/emotional value and psychological ownership of product and technology.

The findings suggest the importance of AR’s functional and emotional values in developing psychological ownership of product and technology. To mitigate the negative effect of functional value, AR designers should focus on creating emotionally engaging apps that induce a flow experience, thereby enhancing psychological ownership. Furthermore, AR apps should be designed to empower users with a sense of control in the AR experience.

This research contributes to the AR and psychological ownership literature. It introduces a model that can explain both the formation of psychological ownership of product and psychological ownership of technology, thereby expanding the current understanding. By adding perceived values as antecedents of psychological ownership, it enriches the psychological ownership literature. Moreover, it enhances the flow experience literature by demonstrating the role of flow experience in the formation of psychological ownership of product and technology.

Compared to traditional (domestic) e-commerce consumers, cross-border electronic commerce (CBEC) consumers may face greater information asymmetry in the CBEC purchase process. Given this background, however, the literature has paid limited attention to the informational antecedents that influence consumers' perceptions of transaction costs and their CBEC purchase intentions. To fill this gap, this study integrates the elaboration likelihood model (ELM) and transaction cost theory (TCT) to develop a model for exploring how product (website informativeness, product diagnosticity and website interactivity as the central route) and external (country brand, website policy and vendor reputation as the peripheral route) informational antecedents affect consumers’ evaluations of transaction costs in terms of uncertainty and asset specificity and their CBEC purchase intentions.

This study employs a survey approach to validate the model with 766 Generation Z CBEC consumers based on judgment sampling. The partial least squares (PLS) technique is adopted for data analysis.

The results show that all the proposed central and peripheral informational antecedents reduce consumers’ perceptions of uncertainty and asset specificity, which in turn negatively influences their CBEC purchase intentions.

Through this investigation, this study increases our understanding of how product and external informational antecedents affect consumers’ evaluations of transaction costs, which subsequently determine their CBEC purchase decisions. This study offers theoretical contributions to existing CBEC research and has practical implications for CBEC organizations and managers.

The diagnosis and prediction methods used for estimating the health conditions of the bearing are of great significance in modern petrochemical industries. This paper aims to discuss the accuracy and stability of improved empirical mode decomposition (EMD) algorithm in bearing fault diagnosis.

This paper adopts the improved adaptive complementary ensemble empirical mode decomposition (ICEEMD) to process the nonlinear and nonstationary signals. Two data sets including a multistage centrifugal fan data set from the laboratory and a motor bearing data set from the Case Western Reserve University are used to perform experiments. Furthermore, the proposed fault diagnosis method, combined with intelligent methods, is evaluated by using two data sets. The proposed method achieved accuracies of 99.62% and 99.17%. Through the experiment of two data, it can be seen that the proposed algorithm has excellent performance in the accuracy and stability of diagnosis.

According to the review papers, as one of the effective decomposition methods to deal with nonlinear nonstationary signals, the method based on EMD has been widely used in bearing fault diagnosis. However, EMD is often used to figure out the nonlinear nonstationarity of fault data, but the traditional EMD is prone to modal confusion, and the white noise in signal reconstruction is difficult to eliminate.

In this paper only the top three optimal intrinsic mode functions (IMFs) are selected, but IMFs with less correlation cannot completely deny their value. Considering the actual working conditions of petrochemical units, the feasibility of this method in compound fault diagnosis needs to be studied.

Different from traditional methods, ICEEMD not only does not need human intervention and setting but also improves the extraction efficiency of feature information. Then, it is combined with a data-driven approach to complete the data preprocessing, and further carries out the fault identification and classification with the optimized convolutional neural network.