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The purpose of this paper is to bridge the gap between the existing theoretical and empirical studies by examining the asymmetric return–volume relationship. Indeed, the authors aim to shed light on the return–volume linkages for French-listed small and medium-sized enterprises (SMEs) compared to blue chips across different market regimes.

This study includes both large capitalizations included in the CAC 40 index and listed SMEs included in the Euronext Growth All Share index. The Markov-switching (MS) approach is applied to understand the asymmetric relationship between trading volume and stock returns. The study investigates also the causal impact between stock returns and trading volume using regime-dependent Granger causality tests.

Asymmetric contemporaneous and lagged relationships between stock returns and trading volume are found for both large capitalizations and listed SMEs. However, the causality investigation reveals some differences between large capitalizations and SMEs. Indeed, causal relationships depend on market conditions and the size of the market.

This paper explains the asymmetric return–volume relationship for both large capitalizations and listed SMEs by incorporating several psychological biases, such as the disposition effect, investor overconfidence and self-attribution bias. Future research needs to deepen the analysis especially for SMEs as most of the literature focuses on large capitalizations.

This empirical study has fundamental implications for portfolio management. The findings provide a deeper understanding of how trading activity impact current returns and vice versa. The authors’ results constitute an important input to build and control trading strategies.

This paper fills the literature gap on the asymmetric return–volume relationship across different regimes. To the best of the authors’ knowledge, the present study is the first empirical attempt to test the asymmetric return–volume relationship for listed SMEs by using an accurate MS framework.

The study explored various dimensions of overconfidence bias (OB) among retail investors in Indian financial markets. Further, these dimensions were validated through formative assessments for OB.

The study applied exploratory factor analysis (EFA) to 764 respondents to explore dimensions of OB. These were validated with formative assessments on 489 respondents by the partial least square path modeling (PLS-PM) approach in SmartPLS 4.0 software.

The major findings of EFA explored four dimensions for OB, i.e. accuracy, perceived control, positive illusions and past investment success. The formative assessments revealed that positive illusions followed by past investment success among retail investors played an instrumental role in orchestrating the OBs that affect investment decisions in financial markets.

The formative index of OB has several practical implications for registered financial and investment advisors, bank advisors, business media companies and portfolio managers, besides individual investors in the domain of behavioral finance.

This research provides a novel approach to provide a formative index of OB with four dimensions. This formative index can acts as an overview for upcoming researchers to investigate the OB of retail individual investors.

1. Overconfidence bias is an important predictor of retail investors' behavior

2. Formative dimensions of the overconfidence bias index.

3. Accuracy, perceived control, positive illusions and past investment success are important dimensions of overconfidence bias.

4. Modern portfolio theory and illusion of control theory support this study.

Overconfidence bias is an important predictor of retail investors' behavior

Formative dimensions of the overconfidence bias index.

Accuracy, perceived control, positive illusions and past investment success are important dimensions of overconfidence bias.

Modern portfolio theory and illusion of control theory support this study.

Grounded in the stakeholder theory and signaling theory, this study aims to broaden the research agenda on environmental, social and governance (ESG) investing by uncovering public sentiments and key themes using Twitter data spanning from 2009 to 2022.

Using various machine learning models for text tonality analysis and topic modeling, this research scrutinizes 1,842,985 Twitter texts to extract prevalent ESG investing trends and gauge their sentiment.

Gibbs Sampling Dirichlet Multinomial Mixture emerges as the optimal topic modeling method, unveiling significant topics such as “Physical risk of climate change,” “Employee Health, Safety and well-being” and “Water management and Scarcity.” RoBERTa, an attention-based model, outperforms other machine learning models in sentiment analysis, revealing a predominantly positive shift in public sentiment toward ESG investing over the past five years.

This study establishes a framework for sentiment analysis and topic modeling on alternative data, offering a foundation for future research. Prospective studies can enhance insights by incorporating data from additional social media platforms like LinkedIn and Facebook.

Leveraging unstructured data on ESG from platforms like Twitter provides a novel avenue to capture company-related information, supplementing traditional self-reported sustainability disclosures. This approach opens new possibilities for understanding a company’s ESG standing.

By shedding light on public perceptions of ESG investing, this research uncovers influential factors that often elude traditional corporate reporting. The findings empower both investors and the general public, aiding managers in refining ESG and management strategies.

This study marks a groundbreaking contribution to scholarly exploration, to the best of the authors’ knowledge, by being the first to analyze unstructured Twitter data in the context of ESG investing, offering unique insights and advancing the understanding of this emerging field.

Previous literature on sustainable supply chain management has largely adopted an instrumental view of stakeholder management and has focused on understanding the effect of powerful stakeholders who have a more decisive influence on an organization's supply chain decisions. Social enterprises have emerged as organizations that often aim to create impact by integrating marginalized stakeholders into their operations and supply chains. This study examines the trade-offs that social enterprises experience due to their moral stance toward stakeholder engagement, evidenced in their commitment to serving marginalized stakeholders, as well as the responses adopted to these trade-offs.

The study follows a theory elaboration approach through a multiple case study design. The authors draw on insights from stakeholder theory and use the empirical insights to expand current constructs and relationships in a novel empirical context. Based on an in-depth analysis of primary and secondary qualitative data on ten social enterprises, the authors examine how these organizations integrate marginalized stakeholders into various roles in their operations.

When integrating marginalized customers, suppliers and employees, social enterprises face affordability, reliability and efficiency trade-offs. Each trade-off represents conflicts between the organization's needs and the needs of marginalized stakeholders. In response to these trade-offs, social enterprises choose to internalize the costs through slack creation or vertical integration or externalize the costs to stakeholders. The ability to externalize is contingent on the growth orientation of the organization and the presence of like-minded B2B (Business-to-Business) customers. These responses reflect whether organizations accept the trade-offs at the expense of one or more stakeholders or if they avoid the trade-offs and find mutually beneficial solutions.

Building on the empirical insights, the authors elaborate on stakeholder theory with a focus on the integration of marginalized stakeholders by emphasizing a moral justification for stakeholder engagement, identifying the nature of the underlying trade-offs which can arise when various stakeholder needs are in conflict and examining the contingencies affecting organizational responses to these trade-offs.

This paper makes a conceptual contribution by intersecting two strands of literature (return to work following health issues and industrial relations) to facilitate our understanding of the potential role of social dialogue in supporting return to work (RTW) following the diagnosis of a chronic illness. It conceptualises the levels and channels through which various actors and their interactions may play a role in RTW facilitation within the actor-centred institutional framework.

The paper uses an exploratory design based mainly on desk research but is also informed by roundtable discussions done in six countries as part of a larger project.

The conceptual and analytical framework (CAF) is developed to explain how various actors interact together in ways shaped by the RTW policy framework and the industrial relations systems, resulting in a continuum of RTW facilitation situations.

There is limited research on return-to-work policies following diagnosis of chronic illness from a comprehensive actor-oriented perspective. The existing literature usually focusses on just one stakeholder, overlooking the role of social dialogue actors. By bridging the two streams of literature and incorporating all potential actors and their interactions in a unitary model, the proposed framework provides a valuable tool to further discuss how successful RTW after a diagnosis of chronic illness can be facilitated.

This paper aims to investigate the role of informational and relational mechanisms on equity crowdfunding investors' conformity behaviors by focusing on a relational culture of China.

The data of 108 financing projects and 7,688 investment records from a union of Chinese equity crowdfunding platforms are gathered. Lead investors' response to a campaign and follow-investors’ former links explain investors' conformity by social network analysis (SNA) and ordinary least squares (OLS) analysis.

The results show that informational and relational influences drive conformity in Chinese equity crowdfunding. Moreover, the informational influence weakens in a highly centralized structure of linked investors.

The results add new knowledge to follow-investors’ conformity behaviors in equity crowdfunding and enrich the literature on conformity theory by finding the contextual effect of information-influenced conformity and the adaption of conformity theory to cultural uniqueness. Besides, this preliminary work also suggests opportunities for future research.

The paper inspires new consideration on a strategical use of follow-investors’ conformity mentality to promote successfully financing and reminds platform managers to be alert to the interference of small groups formed based on informal relationships to the normal financing order.

This is the first study that discovers the non-informational influence and the limited influence of information on equity crowdfunding conformity through contextual concerns.

This study aims to guide firms in emerging markets on whether corporate social responsibility (CSR) engagement facilitates their access to debt with the moderation of asset structure and firm performance. Considering the moderating effect analysis, this study explores the substitutive or complementary effect of these two contingencies on CSR-oriented firms in accessing debt financing.

Drawing on data collected for 16 emerging markets between 2008 and 2019, this study runs country–industry–year fixed-effects regression.

This study finds that CSR performance and reporting facilitate access to debt in emerging markets. However, CSR performance does not have an inverted U-shaped influence on firms’ access to debt financing. The moderation analysis of this study shows that asset tangibility has a negative moderating effect on the link between CSR engagements (i.e. both CSR performance and reporting) and access to debt, confirming a substitutive relationship between asset tangibility and CSR engagements in accessing debt. In contrast, firm performance is positively moderating the nexus between CSR engagement proxies and access to debt, which confirms a complementary type of relationship between firm performance and CSR engagements in accessing debt.

The empirical evidence of this study implies that creditors critically consider CSR engagements of firms in the loan-granting decision process. Similarly, the inverted U-shaped relationship between CSR and access to debt implies that there is an optimal level of CSR engagement creditors might consider in their decision. Likewise, the moderating effects analysis highlights that asset tangibility and firm performance are two conditions under which CSR performance and reporting are linked to access to debt.

Emerging countries are a different set of countries than developed ones; they have high growth rates and hence need financing, have a weaker institutional environment and have weaker stakeholder power. These particularities motivated the authors to conduct a separate study focusing on CSR and debt financing links drawing on a wide range of emerging countries. Thus, this study adds to the ongoing debate by examining the conditions under which CSR-oriented firms can access debt financing in emerging economies.

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.

Online investment platforms offer an environment that may lead some traders into excessive behaviors akin to gambling. Over the last decade, gambling behaviors associated with the stock market have attracted the attention of many researchers but the literature on the subject remains scarce. This study aims to present the results of live interviews with a sample (N = 100) of retail investors trading online, and contrasts trading habits with gambling behaviors.

Participants are divided in three groups according to their score on an adapted version of the Problem Gambling Severity Index (referred to as the PGSI-Trading), and their trading habits and behaviors are compared.

The authors find that traders with higher PGSI-Trading scores are more likely to display gambling-related behaviors such as trading within a short timeframe, being motivated by making money quickly and experiencing high sensations when trading.

The sample is small but the authors proceeded this way in order to gather some qualitative data that would be helpful to clinicians in the Province of Quebec. The questionnaire used to classify traders at risk of being gamblers (PGSI-Trading) has not been validated.

The findings of this study will be helpful to clinicians who hwork with patients suffering from excessive online stock trading habits.

Clinicians observe an increasing number of patients who consult with excessive stock trading habits. This study has brought new information allowing clinicians to better understand how gambling manifests itself on the stock market.

To the authors’ knowledge, this study is the first to investigate the trading habits of individuals classified in terms of their score on an adapted PGSI questionnaire.

Blockchain for energy trading is a trending research area in the current context. However, a noticeable gap exists in the review articles focussing on solar energy trading with blockchain technology. Thus, this study aims to systematically examine and synthesise the existing research on implementing blockchain technology in sustainable solar energy trading.

The study pursued a systematic literature review to achieve its aim. The data extraction process focussed on the Scopus and Web of Science (WoS) databases, yielding an initial set of 129 articles. Subsequent screening and removal of duplicates led to 87 articles for bibliometric analysis, utilising VOSviewer software to discern evolutionary progress in the field. Following the establishment of inclusion and exclusion criteria, a manual content analysis was conducted on a subset of 19 articles.

The results indicated a rising interest in publications on solar energy trading with blockchain technology. Some studies are exploring the integration of new technologies like machine learning and artificial intelligence in this domain. However, challenges and limitations were identified, such as the absence of real-world solar energy trading projects.

This study offers a distinctive approach by integrating bibliometric and manual content analyses, a methodology seldom explored. It provides valuable recommendations for academia and industry, influencing future research and industry practices. Insights include integrating blockchain into solar energy trading and addressing knowledge gaps. These findings advance societal goals, such as transitioning to renewable energy sources (RES) and mitigating carbon emissions, fostering a sustainable future.