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This study aims to develop a model based on the financial variables for better accuracy of financial distress prediction on the sample of private French, Spanish and Italian firms. Thus, firms in financial difficulties could timely request for troubled debt restructuring (TDR) to continue business.

This study used a sample of 312 distressed and 312 non-distressed firms. It includes 60 French, 21 Spanish and 231 Italian firms in both distressed and non-distressed groups. The data are extracted from the ORBIS database. First, the authors develop a new model by replacing a ratio in the original Z”-Score model specifically for financial distress prediction and estimate its coefficients based on linear discriminant analysis (LDA). Second, using the modified Z”-Score model, the authors develop a firm TDR probability index for distressed and non-distressed firms based on the logistic regression model.

The new model (modified Z”-Score), specifically for financial distress prediction, represents higher prediction accuracy. Moreover, the firm TDR probability index accurately depicts the probabilities trend for both groups of distressed and non-distressed firms.

The findings of this study are conclusive. However, the sample size is small. Therefore, further studies could extend the application of the prediction model developed in this study to all the EU countries.

This study has important practical implications. This study responds to the EU directive call by developing the financial distress prediction model to allow debtors to do timely debt restructuring and thus continue their businesses. Therefore, this study could be useful for practitioners and firm stakeholders, such as banks and other creditors, and investors.

This study significantly contributes to the literature in several ways. First, this study develops a model for predicting financial distress based on the argument that corporate bankruptcy and financial distress are distinct events. However, the original Z”-Score model is intended for failure prediction. Moreover, the recent literature suggests modifying and extending the prediction models. Second, the new model is tested using a sample of firms from three countries that share similarities in their TDR laws.

This study aims to determine how cognitive diversity at the workplace influences team creativity. In this regard, the authors examined knowledge sharing and team-focused inclusion through which team members’ cognitive diversity was expected to elevate their positive work outcomes.

A quantitative method is used to accumulate the data. The authors surveyed workers and their respective managers at a single China-based food company. The supervisors rated the outcome variables (creativity and team effectiveness) regarding their employees, whereas employees were asked to rate the cognitive diversity, inclusion and knowledge sharing within the workgroup. The final valid sample size (n = 391) consisted of 137 workgroups with an adequate response rate (62.3%).

Cognitive diversity is related to team effectiveness but not creativity. The research found that cognitive diversity can increase creativity only through enhanced inclusion and knowledge sharing. Inclusion, likewise, explained the impact of cognitive diversity on effectiveness.

The originality of the current research lies in its contemporary exploration of inclusion and cognitive diversity and their pathways to team creativity and effectiveness. The social capital theory was applied to explain the proposed relationships.

This study aims to examine the relationship between entrepreneurial leadership (EL) and new product development performance (NPDP) at the firm level (level 2) of analysis and employee’s creativity (EC) at the cross level (level 1) of analysis. It also examines the serial mediations of (1) intrinsic motivation (IM)-EC and (2) creative self-efficacy (CSE)-EC on the relationship between EL and NPDP.

A systematic random sampling technique was used to collect data through self-administered surveys from leaders and employees of small and medium-sized enterprises (SMEs) in Pakistan’s IT sector. Analysis was conducted on net responses from 114 leaders and 476 employees.

The results revealed significant positive associations between EL and NPDP at the firm level of analysis and EC at the cross level of analysis. The results of the cross-level serial mediations show that (1) IM and EC, and (2) CSE and EC serially mediate the relationship between EL and NPDP.

This study is among the few to use the Coleman bathtub model to show top-down and bottom-up relationships. The study extends and complements the multilevel perspective on leadership and new product development research by simultaneously examining the relationships between EL and NPDP at the individual and firm levels.

Although total quality management (TQM) is an innovative management philosophy, how it connects innovative behaviour (INB) to innovation performance (INP) has gone unnoticed. Also, the external factors (technological turbulence [TUR], competitive intensity [CMP], market dynamism [MKD] and government regulation [GOV]) under which the INB–TQM connection may grow are yet to be understood. In spite of the various evolutions that have occurred in the banking industry, there remains a necessity to enhance the quality of service offered to clients. This paper aims to address these issues in the total quality management literature.

This study constructs and analyses a research framework by analysing the replies of 260 executives in senior and intermediate positions across 21 quality-certified universal banks in Ghana, using the Smart PLS methodology.

TQM played a partial mediating role between INB and INP (variance accounted for = 46.85%, p = 0.000). TUR (β = 0.023, p = 0.000), CMP (β = 0.043, p = 0.000), MKD (β = 0.056, p = 0.000) and GOV (β = 0.068, p = 0.000) positively and significantly moderated the INB–TQM connection.

Future research may examine the proposed framework in various environments and sectors.

Practical insights for industry players in the sector are discussed.

To the best of the authors’ knowledge, this study is the first to show how innovation serves both as an antecedent and consequence of TQM. It is also the first to explicate the boundary conditions under which the INB–TQM relationship may flourish.

In this research, we seek to understand the effects of artificial intelligence (AI) and knowledge management (KM) processes in enhancing proactive green innovation (PGI) within oil and gas organizations. It also aims to investigate the moderator role of trust and sustainability in these relationships.

This paper employs a quantitative analysis. Surveys have been gathered from the middle-line managers of twenty-four oil and gas government organizations to evaluate the perceptions of the managers towards AI, KM processes, trust, sustainability measures and proactive measures toward green innovation. Analytical and statistical tools that were employed in this study, including structural equation modeling with SmartPLSv3.9, have been used to analyze the data and to examine the measurement and structural models of this study.

The study results reveal a significant and positive impact of AI utilization, KM processes and PGI within oil and gas organizations. Furthermore, trust and sustainability turn out to be viable moderators affecting, and influencing the strength and direction of AI, KM and PGI relationships. In particular, higher levels of trust and more substantial sustainability commitments enhance the positive impact of AI and KM on green innovation outcomes.

Understanding the impact of AI, KM, trust and sustainability offers valuable insights for organizational leaders and policymakers seeking to promote proactive green innovation within the oil and gas industry. Thus, organizations can increase the efficiency of sustainable product development, process improvement and environmental management by using robust AI technologies and effective KM systems. Furthermore, fostering trust among stakeholders and embedding sustainability principles into organizational culture can amplify the effectiveness of AI and KM initiatives in driving green innovation outcomes.

This study extends the current knowledge by assessing the effect of AI and KM on proactive green innovation while accounting for trust and sustainability as moderators. Utilizing quantitative methods offers a nuanced understanding of the complex interactions between these variables, thereby advancing theoretical knowledge in the fields of innovation management, sustainability and organizational behavior. Additionally, the identification of specific mechanisms and contextual factors enriches practical insights for organizational practitioners striving for a practical understanding of the dynamics of the complexities of sustainable innovation in an AI-driven era.

Recent literature in environmental management suggests that fostering employees’ innovative behaviour in green service is vital for enhancing the environmental sustainability of hospitality organizations. Despite this, few efforts have been made to understand how green entrepreneurial leadership (GEL) relates to green service innovative behaviour (GSIB). This study aims to examine whether GEL can promote GSIB among hospitality employees through the serial mediation of green learning orientation (GLO) and green knowledge acquisition (GKA) using the conservation of resources theory. The authors expect environmental dynamism to strengthen the relationship between GEL and employees’ GSIB, leveraging the resource-based view theory.

This study collected data through a multi-wave survey (four waves, two weeks apart) from 341 employees working in three-to-five-star hotels in Pakistan’s major cities. The authors used partial least squares structural equation modelling to evaluate the hypotheses proposed in the theoretical model.

The study revealed a significant relationship between GEL and employee GSIB, mediated by GLO and GKA. In addition, environmental dynamism strengthened the relationship of GEL with employee GSIB.

The research advances the literature on GEL in the hospitality sector by providing insights into the mediating and moderating processes that translate GEL into GSIB among hospitality employees. Moreover, the research provides important implications for hotels investing in green initiatives and looking for ways to foster employees’ GSIB.

The objective of this article is to study the factors influencing the leverage and debt maturity of 48 Public Entities and 297 Private Entities, in the health sector in Portugal, in the period between 2015 and 2021, including the pandemic crisis, coronavirus disease 2019.

To test the proposed hypotheses, the panel data methodology was used, considering the GMM (Generalized Method of Moments) system estimation method.

Our findings suggest that in times of crisis, both public and private entities resort to long-term loans to finance additional expenses and guarantee the continuity of health services. Also, there is a strong dependence on short-term debt (short leverage [SLEV]), especially in the public sector, suggesting some financial imbalance in current management, with no margin of financial security. In private hospitals, a more considered strategic definition is demonstrated, without current management risks.

As far as the authors are aware, this article is original and covers an important gap in the literature when considering the determinants of debt maturity in public and private hospitals in Portugal, a country where the debate about the essence of the National Health System, it’s in the news every day.

This study aimed to investigate the relationship between exploitative leadership (EL) and employee green innovative behavior (GIB) in the hospitality sector organizations of Pakistan. The relationship between EL and GIB is mediated by emotional exhaustion (EE). Perceived organizational support (POS) is used as a moderator between EL and EE.

The study used convenience and purposive sampling techniques from the population, and the data collected on the structured questionnaire were analyzed through structural equation modeling (SEM) using SmartPLS. The data analysis involved the assessment of the measurement model and structural model.

The results of the data analysis show that EL has a significant and negative influence on employee GIB, and EE mediates the relationship, meaning EE caused by EL lowers GIB. The moderating effect of perceived organization support between EL and EE also lowers the effects of EL and diminishes EE leading to increased GIB.

The findings of the study suggest that organizations in the hospitality sector like hotels and resorts need to focus on the POS to curb EE in employees due to EL to accelerate positive attitudes at work. Investments of resources in this avenue can enhance employee engagement and improve organizational performance while contributing to environmentally sustainable goals.

The originality of the study lies in the findings that in the presence of higher perceived organization support, the negative effects of EL are mitigated, and this leads to the replenishment of the emotional resources of employees, which allows them to engage in GIBs. GIB is a term that is being researched by the scholars in the hospitality industry of Pakistan. Conservation of natural resources is only possible through individual efforts, especially the efforts of individuals whose livelihoods depend on environmentally related industries, such as hospitality.

This study aims to analyze the two-dimensional ferrofluid flow in porous media. The effects of changes in parameters such as permeability parameter, buoyancy parameter, Reynolds and Prandtl numbers, radiation parameter, velocity slip parameter, energy dissipation parameter and viscosity parameter on the velocity and temperature profile are displayed numerically and graphically.

By using simplification, nonlinear differential equations are converted into ordinary nonlinear equations. Modeling is done in the Cartesian coordinate system. The finite element method (FEM) and the Akbari-Ganji method (AGM) are used to solve the present problem. The finite element model determines each parameter’s effect on the fluid’s velocity and temperature.

The results show that if the viscosity parameter increases, the temperature of the fluid increases, but the velocity of the fluid decreases. As can be seen in the figures, by increasing the permeability parameter, a reduction in velocity and an enhancement in fluid temperature are observed. When the Reynolds number increases, an increase in fluid velocity and temperature is observed. If the speed slip parameter increases, the speed decreases, and as the energy dissipation parameter increases, the temperature also increases.

When considering factors like thermal conductivity and variable viscosity in this context, they can significantly impact velocity slippage conditions. The primary objective of the present study is to assess the influence of thermal conductivity parameters and variable viscosity within a porous medium on ferrofluid behavior. This particular flow configuration is chosen due to the essential role of ferrofluids and their extensive use in engineering, industry and medicine.