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This study aims to analyze the effect of cognitive load and social value orientation on managers’ preferences when they face with two types of restructuring choices in financially distressed firms: the first belonging to the family of organizational restructuring (massive layoffs) and the second to the family of financial restructuring (debt increases).

The authors investigate experimentally the impact of managers’ cognitive load and social value orientation on the decision to restructure leveraged buyout (LBO) firms in financial distress by using either massive layoffs or debt increases.

By investigating the impact of managers’ cognitive load and social value orientation on the restructuring decision of an LBO firm in financial distress, the research reveals that, on average, cognitively loaded managers prefer massive layoffs over increased debt levels. The massive layoffs seemingly provide a relatively easier way to avoid conflict with influential, residual claimants. In contrast, social value–oriented managers actively avoid massive layoffs and prefer to increase debt.

These results imply that the performance mechanisms emphasized to improve agency relations, for example, in LBOs, have their own limitations during periods of financial distress. This study shows that one of these limits is related to cognitive distortions and personality traits.

In this research, the originality lies in understanding how managers’ internal factors affect their restructuring decision-making, in the case of LBO firms in financial distress.

Pay-what-you-want (PWYW) is a pricing strategy implemented in a variety of settings like supermarkets and museums, in which consumers determine the price they are willing to pay for a product or service based on their perceived utility. The authors propose an analytical model to investigate the impact of PWYW delivery pricing on the online food delivery (OFD) platforms.

Using a game-theoretic model, the authors characterize the equilibrium as a function of the platform's average delivery cost and the consumer's social preferences parameters like fairness and reciprocity. The authors derive the parametric conditions under which PWYW generates higher profits for the platform compared to the traditional pay-as-asked delivery pricing.

For the PWYW strategy to be profitable, the average delivery cost to the platform should be low. Therefore, OFD platform managers should focus on reducing delivery costs. The authors also identify the feasible region in which the platform managers need to maintain the consumer's social preferences.

Under PWYW, the authors recommend that the platform managers impose a minimum delivery fee which consumers can use as a benchmark to minimize zero delivery fee payments and consumers' free-riding tendencies simultaneously. This allows OFD platforms to extract online orders from highly price-conscious consumers.

This is one of the first studies to explore the innovative application of PWYW to a particular segment of delivery pricing in OFD platforms. The authors establish that the overall consumer surplus and social welfare are higher under the PWYW strategy, forming a solid ground for its implementation in OFD platforms.

This study investigates the brand selfies that have the capability to help brands thrive through crises. The brand selfies spark a self-inferential process that makes customers feel connected to the brand and makes them biased toward a specific brand during an uncertain situation.

A total of 166 questionnaires were analyzed through structural equation modelling (Smart PLS) and a niche group of young millennials from Thailand was selected based on their luxury items usage, frequency of visits to leisure spas and hotels, expensive car showrooms, branded jewelry stores and luxury watch shops.

The study highlights the emergence of brand selfies during the crisis and the priority given by customers as compared to brand-generated content or promotional campaigns. The results indicated a positive influence of brand selfies on brand preferences directly and through the mediation of brand signature.

It is fascinating for brands that customers voluntarily include their products in their carefully crafted and staged selfies that deliver their image and massages as social signifiers during a chaotic situation.

The research classifies the impacts of brand selfies in the luxury, leisure and tourism market of Thailand and its assistance in thriving through crises. The study is one of the rare studies that present brand selfies as a hassle-free promotional tool for brand signature and a game-changing strategy to deal with crises.

There is emerging evidence in the accounting literature that investors react negatively to corporate greenwashing. But does that hold for all investors, or do different types of investors react differently? This paper aims to study retail investors’ responses to media reports on corporate greenwashing and how these responses depend upon the investors’ social value orientation. The authors argue that media reporting on corporate greenwashing negatively affects the rationale for allocating funds to firms engaging in greenwashing. The authors also expect this reaction to be stronger for prosocial investors compared to proself investors.

The authors conduct an online experiment with 229 participants representing retail investors in the German-speaking countries.

The results show that retail investors who received media reports on deceptive disclosure invest more funds in the company that does not engage in greenwashing (and less in the firm that engages in greenwashing) than investors who did not receive these reports. The authors’ results provide novel evidence that this effect primarily holds for investors with a prosocial value orientation. Finally, the authors’ data show that lower trust in the firm that engages in greenwashing partially mediates the effect of media reports on investor choices.

The authors provide unique evidence how different types of investors react to media reports on greenwashing. The authors find that moral motives, rather than risk-return considerations, drive investor responses to greenwashing. Overall, these findings support the important function of the media as an intermediary in stock market participation and highlight the pivotal role of individual traits in investors’ responses to greenwashing.

This study develops a computational method to investigate the predominant language styles in political discussions on Twitter and their connections with users' online characteristics.

This study gathers a large Twitter dataset comprising political discussions across various topics from general users. It utilizes an unsupervised machine learning algorithm with pre-defined language features to detect language styles in political discussions on Twitter. Furthermore, it employs a multinomial model to explore the relationships between language styles and users' online characteristics.

Through the analysis of over 700,000 political tweets, this study identifies six language styles: mobilizing, self-expressive, argumentative, narrative, analytic and informational. Furthermore, by investigating the covariation between language styles and users' online characteristics, such as social connections, expressive desires and gender, this study reveals a preference for an informational style and an aversion to an argumentative style in political discussions. It also uncovers gender differences in language styles, with women being more likely to belong to the mobilizing group but less likely to belong to the analytic and informational groups.

This study provides insights into the psychological mechanisms and social statuses of users who adopt particular language styles. It assists political communicators in understanding their audience and tailoring their language to suit specific contexts and communication objectives.

This study reveals gender differences in language styles, suggesting that women may have a heightened desire for social support in political discussions. It highlights that traditional gender disparities in politics might persist in online public spaces.

This study develops a computational methodology by combining cluster analysis with pre-defined linguistic features to categorize language styles. This approach integrates statistical algorithms with communication and linguistic theories, providing researchers with an unsupervised method for analyzing textual data. It focuses on detecting language styles rather than topics or themes in the text, complementing widely used text classification methods such as topic modeling. Additionally, this study explores the associations between language styles and the online characteristics of social media users in a political context.

Culture is considered a critical aspect of social media usage. The purpose of this paper is to explore how cultures and languages influence multilingual users' cross-cultural information sharing patterns.

This study used a crowdsourcing survey with Amazon Mechanical Turk to collect qualitative and quantitative data from 355 multilingual users who utilize two or more languages daily. A mixed-method approach combined statistical, and cluster analysis with thematic analysis was employed to analyze information sharing patterns among multilingual users in the Chinese cultural context.

It was found that most multilingual users surveyed preferred to share in their first and second language mainly because that is what others around them speak or use. Multilingual users have more diverse sharing characteristics and are more actively engaged in social media. The results also provide insights into what incentives make multilingual users engage in social media to share information related to Chinese culture with the MOA model. Finally, the ten motivation factors include learning, entertainment, empathy, personal gain, social engagement, altruism, self-expression, information, trust and sharing culture. One opportunity factor is identified, which is convenience. Three ability factors are recognized consist of self-efficacy, habit and personality.

The findings are conducive to promoting the active participation of multilingual users in online communities, increasing global resource sharing and information flow and promoting the consumption of digital cultural content.

This study aims to analyze the relationship between corporate social responsibility (CSR) and quality of accounting report, especially on earnings management (EM). In addition, potential moderators of this relationship are examined.

After a comprehensive study of potential mechanisms, the authors obtain plenty of empirical results to open the black box of the link between CSR and EM. Meta-analysis is applied on 51 studies from 35 papers. Further analysis is also carried out to determine the moderating effects, such as the cultural and sample selection differences in these papers.

CSR is negatively associated with EM. In addition, this effect is moderated by cultural difference, CSR measurement, and year of sample selection.

Two patterns of the hypothesis between CSR and EM are confirmed based on agency cost theory, a theoretical shift of corporate ethics based on organizational moral perspective. Several useful suggestions are also provided for future studies on the empirical model and sample selection. Further research is necessary to clarify the agency cost behind the two theoretical patterns.

CSR is not a tool for firms to market but rather a strategy to ensure their consistency with moral principles, indicating that management should pay more attention to the potential damage of the incongruence between CSR and accounting reporting quality. CSR reporting quality remains an important issue for legislature to guarantee continued firm operations.

To the best of the authors’ knowledge, this study is the first to analyze the CSR and EM link using a meta-analysis and to consider its underlying mechanism under the global environment. Previous method design and sample selection are reviewed to provide reference for future studies.

This study analyzes the role of cooperative behavior in facing the risk of encouraging innovative agricultural production projects by small-scale farmers in the context of farmers in developing countries.

A within-subjects field experiment was conducted with small-scale Colombian panela cane farmers. The authors used the collected data to run the regression analyses.

The results suggest that when small farmers can follow cooperative behavior by joining a group and pooling resources to face risk, they are more willing to invest in a novel and profitable alternative, albeit riskier. However, the possibility of cooperating with a group to invest in a novel production project depends on its expected risk level.

These results will help develop agricultural policies for sustainable development. Establishing informal networks for small-scale farmers to deal with unpredictable risks may aid in developing innovative systems.

Agriculture is highly vulnerable to climatic impacts, which, combined with the inherent risk of innovation, may reduce small farmers' willingness to adopt innovation. Cooperation appears to be a mechanism for pooling resources and facing risk.

Research has focused on experimentally testing the effect of cooperative behavior when facing risk. The authors contribute to the literature by demonstrating the impact of the ability of small-scale farmers in rural areas to collectively manage risk on investment in innovative projects.

This study aims to investigate the impact of financial and behavioural factors on investment decisions in the cryptocurrency market within the Gulf Cooperation Council (GCC).

The study uses the cross-sectional absolute deviation methodology developed by Chang et al. (2000) to determine the existence of herding behaviour during extreme conditions in the cryptocurrency market of four GCC countries: Bahrain, Saudi Arabia, Kuwait and UAE. In addition, a questionnaire survey was distributed to 322 investors from the GCC cryptocurrency markets to gather data on their investment decisions.

The study finds that the herding theory, prospect theory and heuristics theory account for 16.5% of the variance in investors' choices in the GCC cryptocurrency market. The regression analysis results show no multicollinearity problems, and a high F-statistic indicates the general model's acceptability in the results.

The study's findings suggest that behavioural and financial factors play a significant role in investors' choices in the GCC cryptocurrency market. The study's results can be used by investors to better understand the impact of these factors on their investment decisions and to develop more effective investment strategies. In addition, the study's findings can be used by policymakers to develop regulations that consider the impact of behavioural and financial factors on the GCC cryptocurrency market.

This study adds to the body of literature in two different ways. Initially, motivated by earlier research examining the impact of behaviour finance factors on investment decisions, the authors look at how the behaviour finance factors affect investment decisions of the GCC cryptocurrency market. To extend most of these studies, this study uses a regime-switching model that accounts for two different market states. Second, by considering the recent crisis and more recent periods involving more cryptocurrencies, the authors have contributed to several studies examining the impact of behavioural financial factors on investment decisions in cryptocurrency markets. In fact, very few studies have examined the impact of behavioural finance on cryptocurrency markets. Therefore, to the best of the authors’ knowledge, this study is the first of its kind to investigate how behavioural finance factors influence investment decisions in the GCC cryptocurrency market. This allows to better illuminate the factors driving herd behaviour in the GCC cryptocurrency market.

This study aims to explore the influence of risk preference and information acquisition on outdoor tourism safety decision-making.

Five hundred twenty outdoor tourists were surveyed, and data were analyzed using two-stage regression.

Risk preference positively affects tourists’ safety decisions for outdoor travel. The greater the risk preference is, the more likely the tourists are to make the risky decision of outdoor tourism. Information acquisition significantly negatively affects tourists’ safety decisions for outdoor tourism. Tourists who obtain information through social channels are more likely to make safer travel decisions than those who do not.

Risk preference and information acquisition are introduced into outdoor tourism safety research.