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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.

The research objective starts from the argument that small-scale multinational corporations’ (SMNCs’) managerial behavior toward auditing decisions is influenced by their personal value, especially when the auditing process is not mandatory. This study aims to examine how national culture-religiosity affects that decision. The authors further examine how foreign-owned MNCs might behave differently from local MNCs, although the host country’s cultural-religiosity value might influence that decision.

This study obtains the data from three sources: Hofstede Framework, Pew Research Center and World Bank Enterprise Survey in cross-sectional mode. The final sample consists of 8,590 SMNCs from 45 countries as the observations. This study uses robust regression analysis to test the effects of culture, religiosity and controlling shareholders on the audited financial statements decision.

The regression results support the hypothesis, whereas cultural-religiosity values are associated with the audited financial report. The findings confirm stakeholder theory and institutional theory.

This study fills a gap in the literature by providing empirical evidence on the cultural and religiosity effects on the accounting decision of SMNCs. The results can be used as the foundation for future research related to MNCs’ managerial behavior toward accounting policies, especially with the psychosocial factors.

This study examines the effects of financial literacy and financial risk tolerance on investor behavior by introducing social stigma as a mediator and emotional intelligence as a moderating factor.

Data is collected from 761 financially independent individual investors, with a minimum age of 25 years, a minimum of five years of stock market experience and residing in five selected major Indian cities. The collected data is subsequently analyzed using SmartPLS. Homogeneous purposive sampling followed by snowball sampling was employed.

The findings of the study demonstrate a strong and noteworthy impact of financial literacy on investor behavior. The research reveals that social stigma acts as a partial mediator and emotional intelligence plays a significant moderator with direct effects and indirect effects between financial literacy, financial risk tolerance, social stigma and investor behavior.

Exploring emotional intelligence in financial decisions enriches academic programs by integrating it into financial education. Collaboration between academia and financial institutions yields practical tools, infusing emotional intelligence into services. This prompts systemic shifts, reshaping education and societal discourse, fostering inclusive, emotionally intelligent financial landscapes, aiming to redefine both academic teachings and real-world financial practices.

Integrating emotional intelligence into government-led financial literacy programs can transform societal perspectives on financial decision-making. Customized services, destigmatizing workshops and collaborative efforts with academia foster an emotionally intelligent financial landscape, reshaping traditional paradigms.

Promoting open societal discussions about finances combats stigma, fostering a supportive space for risk-taking. Emphasizing emotional intelligence in awareness campaigns cultivates inclusivity and confidence. Normalizing financial talks empowers individuals, enhancing their well-being. Elevating both financial literacy and emotional intelligence enhances overall financial health, nurturing a community adept at navigating financial journeys.

This study marks a notable contribution to behavioral finance and social stigma theory by examining their intersection with emotional intelligence. It uniquely introduces social stigma as a mediator and emotional intelligence as a moderator, unexplored in this context. This novelty underscores the research’s significance, offering practical insights into financial well-being.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2023-0626

Millennials are a vital generational cohort of the Indian population, and understanding their motivation to participate in the stock market is crucial. This study aims to understand the investment decision-making behavior among millennials in the Indian Stock Market.

Using a cross-sectional research design that entails in-depth personal interviews, this study aims to understand the equity investment behavior of millennials. Verbatim texts from interview transcripts were used to analyze the content and arrive at themes.

The study investigated the motivation to enter the stock market and gained insights into how individuals make equity investment decisions considering economic and behavioral dimensions. The basis for stock selection was predominantly on the self-analysis of investors. Multiple stock selection priorities are also discussed. In addition, informants ensured asset diversification and exercised various strategies to overcome emotions. Furthermore, they suffered from various behavioral biases.

Individual investors are the least informed and most impacted stakeholders in the stock markets; therefore, this study contributes fresh insights to enhance their financial security. The paper also examines some noticeable behavioral tendencies retail investors exhibit and gathers helpful strategies for mitigating behavioral biases.

The uniqueness of the research lies in its adoption of a qualitative methodology that uses the investment experience of millennial investors to reveal the components of decision-making behavior and investor psychology. The findings are thereby unique and have significant managerial implications.

This study examines the Robo-Advisors (RA) based on Artificial Intelligence (AI), a new service that digitises and automates investment decisions in the financial and banking industries to provide low-cost and personalised financial advice. The RAs use objective algorithms to select portfolios, reduce behavioural biases, and improve transactions. They are inexpensive, accessible, and transparent platforms. Objective algorithms improve the believability of portfolio selection.

This study adopts a qualitative approach consisting of an exploratory examination of seven different RA case studies and analyses the RA platforms used in the banking industry.

The findings provide two different approaches to running a business that are appropriate for either fully automated or hybrid RAs through the realisation of two platform model frameworks. The research reveals that relying solely on algorithms and not including any services involving human interaction in a company model is inadequate to meet the requirements of customers in decision-making.

This study emphasises key robo-advisory features, such as investor profiling, asset allocation, investment strategies, portfolio rebalancing, and performance evaluation. These features provide managers and practitioners with new information on enhancing client satisfaction, improving services, and adjusting to dynamic market demands.

This study fills the research gap related to the analysis of RA platform models by providing a meticulous analysis of two different types of RAs, namely, fully automated and hybrid, which have not received adequate attention in the literature.

This paper aims to review the literature extensively by analysing recent work and providing a guide for models, data sets and research findings.

This paper reviews the literature extensively by analysing recent work and providing a guide for models, data sets and research findings within the context of capital market imperfections. The authors further break down the literature into closer-in-nature categories for reader’s convenience and comprehension. Finally, the authors address gaps in the existing literature and propose government policies that can tone down the potential effect of credit rationing on employment.

This paper provides a map of the literature so as to help future researchers in the relevant literature and give a short insight of what has been explored so far.

This paper is original and is the result of a thorough review of an extensive literature.

Since conducting agile strategies provides sustainable passenger satisfaction and revenue by replacing applied policies with more profitable ones rapidly, the focus of this study is to evaluate agile attributes for managing low-cost carriers (LCCs) operations by means of resources and competences based on dynamic capabilities built on resource-based view (RBV) theory and to achieve sustainable competitive advantage in a volatile and dynamic air transport environment. LCCs in Turkey are also evaluated in this study since the competition among LCCs is high to gain market share and they can adapt quickly to all kinds of circumstances.

Two well-known Multi-Criteria Decision-Making Methods (MCDM) named as the Stepwise Weight Assessment Ratio Analysis (SWARA) and multi-attributive border approximation area comparison (MABAC) methods by employing Picture fuzzy sets (PiFS) are employed to determine weight of agile attributes and superiority of LCCs based on agile attributes in the market, respectively. To check the consistency and robustness of the results for the proposed approach, comparative and sensitivity analysis are performed at the end of the study.

While the ranking orders of agile attributes are Strategic Responsiveness (AG1), Financial Management (AG4), Quality (AG2), Digital integration (AG3) and Reliability (AG5), respectively, LCC2 is selected as the best agile airline company in Turkey with respect to agile attributes. SWARA and MABAC method based on PiFS is appropriate and effective method to evaluate agile attributes that has important reference value for the airline companies in aviation industry.

The findings of this study will support managers in the airline industry to conduct airline operations more flexibly and effectively to take sustainable competitive advantage in unexpected and dynamic environment.

To the author' best knowledge, this study is the first developed to identify the attributes necessary to increase agility in LCCs. Thus, as a systematic tool, a framework is developed for the implementation of agile attributes to achieve sustainable competitive advantage in the airline industry and presented a roadmap for airline managers to deal with crises and challenging situations by satisfying customer and increasing competitiveness.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.

The purpose of this paper is to engage in a systematic examination of previous scholarship on the relationship between Sharia governance (SG), which is represented by the Sharia Supervisory Board (SSB), and the Internal Sharia Review (ISR), to determine whether the ISR can minimize financing risk in Islamic banking.

The literature search consisted of two steps: a randomized and systematic literature review. The methodology adopted in this article is a systematic literature review.

To reduce the risk of financing in Islamic banking, SG must be implemented optimally by making rules regarding the role of the SSB in supervising customer financing. In addition, it is a necessary to establish an entity that assists the SSB in the implementation of SG, namely, the ISR section, but there is still very little research on the role of the SSB and ISR in minimizing financing risk.

Establishing an ISR to assist the SSB in carrying out its duties has direct practical implications for Islamic banking: minimizing financing risks and compliance with Islamic Sharia principles. In addition, new rules regarding the role of SSBs and the ISR in reducing credit risk include monitoring customers to ensure that they fulfill their financing commitments on time. This new form of regulation and review can be used as a reference by the Otoritas Jasa Keuangan or Finance Service Authority to create new policies or regulations regarding SG, especially in Indonesia.

Subsequent research may introduce other more relevant variables, such as empirically testing the competence, independence or integrity of SSB and the ISR team as it attempts to minimize the risk of financing in Islamic banks. In addition, further research is expected to examine whether the SSB or the ISR team has a positive or negative influence on the risk of financing Islamic banks with secondary data.

This study aims to develop a comprehensive framework for Islamic social entrepreneurship (ISE) by synthesizing Islamic principles and social entrepreneurship concepts, bridging the gap between theory and practice.

Using a systematic literature review, this study focuses on scholarly works published from 1992 to 2023, uses thematic analysis and engages with subject experts to craft a framework for ISE.

The study identified 39 sub-dimensions grouped into 13 core dimensions. These findings highlight the multifaceted impact on ISE, emphasizing its commitment to ethical, socially responsible practices and achieving lasting social impact through collaborative, innovative approaches guided by Islamic principles.

Limitations include regional focus, lack of longitudinal data and absence of quantitative testing for the framework. Future research should expand scope, use quantitative analysis and explore gender dynamics, policy implications and standardized impact metrics to enhance the framework’s robustness.

The study’s comprehensive framework aids ISE practitioners in aligning their ventures with Islamic ethics and social impact. As interest in ISE grows, particularly in Muslim-majority contexts, this research facilitates the integration of Islamic values into social entrepreneurship, addressing pressing societal challenges.

This study contributes to the field of ISE by proposing a meticulously crafted framework that synthesizes Islamic principles and social entrepreneurship concepts. It stands out as a unique endeavor that bridges the gap between theory and practice in ISE, offering practical guidance while enriching the scholarly discourse on the subject.