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Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.

This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.

Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.

This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.

After the identification of a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at Wuhan, China, a pandemic was widely spread worldwide. In Italy, about 240,000 people were infected because of this virus including 34,721 deaths until the end of June 2020. To control this new pandemic, epidemiologists recommend the enforcement of serious mitigation measures like country lockdown, contact tracing or testing, social distancing and self-isolation.

This paper presents the most popular epidemic model of susceptible (S), exposed (E), infected (I) and recovered (R) collectively called SEIR to understand the virus spreading among the Italian population.

Developed SEIR model explains the infection growth across Italy and presents epidemic rates after and before country lockdown. The results demonstrated that follow-up of strict measures such that country lockdown along with high testing is making Italy practically a pandemic-free country.

These models largely help to estimate and understand how an infectious agent spreads in a particular country and how individual factors can affect the dynamics. Further studies like classical SEIR modeling can improve the quality of data and implementation of this modeling could represent a novelty of epidemic models.

Venture capital (VC) is an essential element in healthy entrepreneurial environments; therefore, many countries in developing entrepreneurial economies support the industry via direct or indirect government interventions. The purpose of this study is to examine through the example of the Hungarian market, whether direct or hybrid state involvement has contributed more to the growth of the invested enterprises. The findings are relevant in the design of government VC schemes and in the contracts mitigating the moral hazards inherent in government funding.

The basis of empirical research is a unique hand-collected database covering Hungarian government-backed VC (GVC) investments. Based on the financial data of investee firms, the authors investigate whether firms financed by hybrid VC involving market participants are able to outperform firms that receive pure public financing using panel regression.

Based on Hungarian evidence, hybrid VC-backed firms generated lower growth and employment than their purely government-backed peers. Both schemes showed meagre innovation activity. The conclusion is that because of the conflict of private and economic policy objectives in hybrid financing, the exposure of hybrid risk capital to moral hazard is higher than that of pure public financing. Private interests in hybrid funds can only improve investment efficiency if they are structured along the lines of market-based independent financial intermediation and the contracts imitate the ones existing amongst limited and general partners in private schemes.

The research covers the data of Hungarian government-backed firms by tracking the full range of 86 investments made in the purely government scheme and 340 firms that received funding in the hybrid scheme. The research focuses on two government initiatives, and the results are influenced by the specific regulation of the programs; therefore, the results cannot be generalized for all government agendas; they are indicative in the designs of the agendas.

There is a limited number of empirical studies investigating the impact of VC in developing markets, especially in the Central and Eastern Europe region. This firm-level research on the impact of public VC can help improve the effectiveness of development policies. By analysing the entirety of investments of a VC program that is near to its completion, the authors provide new insight into the efficiency and prospects of GVC schemes in the region.

The objective of this study is to investigate the barriers hindering the integration of lean manufacturing (LM) practices within the furniture industry of Bangladesh. The traditional operational paradigms in this sector have posed substantial challenges to the effective implementation of LM. In this study, the barriers of implementing LM in the furniture business are examined, aiming to provide a systematic understanding of the barriers that must be addressed for a successful transition.

The research reveals that “Fragmented Industry Structure,” “Resistance to Lean Practices” and “Inadequate Plant Layout and Maintenance”, emerged as the foremost barriers to LM implementation in the furniture industry. Additionally, “Insufficient Expert Management,” “Limited Technical Resources” and “Lack of Capital Investment” play significant roles.

The outcomes of this study provide valuable insights into the furniture industry, enabling the development of strategies for effective LM implementation. One notable challenge in lean implementation is the tendency to revert to established practices when confronted with barriers. Therefore, this transition necessitates informed guidance and leadership. In addition to addressing these internal challenges, the scope of lean implementation should be broadened.

This study represents one of the initial efforts to systematically identify and assess the barriers to LM implementation within the furniture industry of Bangladesh, contributing to the emerging body of knowledge in this area.

The current study aims to examine the impact of two black swan events on the performance of six stock markets in Gulf Cooperation Council (GCC) economies (Abu Dhabi, Bahrain, Dubai, Oman, Qatar and Saudi Arabia). The two selected black swan events are the US Mortgage and credit crisis (Global Financial Crisis of 2008) and the COVID-19 pandemic.

The performance of all the six stock markets are represented by their return and price volatility behavior, which has been measured by applying ARCH/GARCH model. The comparative analysis is done by employing mean difference models. The data is collected from Bloomberg on a daily frequency.

The response of two black swan events on the GCC stock markets has been heterogenous in nature. During the financial crisis, the impact was heavily felt on most of the stock markets in the GCC countries. It is revealed that the financial crisis had a negative significant impact on four of the six countries. Whereas during the COVID-19 crisis, it is revealed that there is no significant impact on four of the six selected stock markets. The positive significant impact is felt on two stock markets, namely, the Abu Dhabi stock market and the Saudi stock market.

The present investigation attempts to fill the gap in the literature on the intended topic because it is evident from the literature on the chosen subject that no study has been undertaken to evaluate and contrast the impact of the GFC crisis and COVID-19 on the GCC stock markets.

This work analyzes, through social-environmental reports, whether banks with higher transparency in social-environmental policies better safeguard financial stability in Brazil.

The analysis is carried out through a panel database analysis of the 42 largest Brazilian banks, representing 98% of the Brazilian financial system. Seeking to avoid spurious results, we followed rigorous methodological standards. Hence, we conducted an empirical analysis using a dynamic panel data model, we used the difference generalized method of moments (D-GMM) and the system generalized method of moments (S-GMM).

The results show that the higher the transparency of social-environmental policies, the lower the chance of possible stress on the financial stability of Brazilian banks. In sum, this study builds evidence that disclosing risks related to policies about sustainability can enhance financial stability. It is essential to highlight that social-environmental transparency does not have as direct objective financial stability.

The manuscript submitted represents an original work that analyzes whether banks with higher transparency in social-environmental policies better safeguard financial stability. Some countries, such as Brazil, have their potential for sustainable policies spotlighted due to their green territory and diverse natural ecosystems. Besides having green potential, Brazil is a developing country with a well-developed financial system. These characteristics make Brazil one of the best laboratories for studying the relationship between transparency in social-environmental policies and financial stability.

This study aims to validate the content of an instrument which identifies the organizational, sociocultural and technological characteristics that foster digital transformation (DT) in higher education institutions (HEIs) through the Delphi method.

The methodology is quantitative, non-experimental, and descriptive in scope. First, expert judges were selected; Second, Aiken's V coefficients were obtained. Nine experts were considered for the validation.

This study’s findings show that the instrument has content validity and there was strong consensus among the judges. The instrument consists of 29 questions; 13 items adjusted and 2 merged.

A novel instrument for measuring the DT at HEIs was designed and has content validity, evidenced by Aiken's V coefficients of 0.91 with a 0.05 significance, and consensus among judges evidenced by consensus coefficient of 0.81.

This paper aims to determine the impact of mentorship on the development of self-directedness among beginner teachers in their initial years of teaching.

The researcher adopted a positivist paradigm to explore the situation of concern. Quantitative research was conducted, involving the collection and analysis of numerical data. Two closed-ended structured questionnaires were utilised, derived from the 40-item self-directed learning readiness scale (SDLRS) developed by Fisher and King, and a pre-determined questionnaire by Glazerman focused on the first-year teaching experience, induction and mentoring of beginner teachers.

Beginner teachers merely relying on the knowledge obtained from their studies is insufficient to achieve a satisfactory level of self-directedness when starting a teaching career. Most beginner teachers faced significant challenges in their early years of teaching due to the absence of mentoring support. In addition, most indicated that they resume their teaching duties and rely on their district for general support, guidance and orientation. Finally, the results have shown that mentoring positively impacts beginner teachers’ self-directedness.

The first limitation was that this study was narrowed to one South Africa University part-time B.Ed honours students working as beginner teachers in different provinces at primary and secondary schools. As a result, the findings of this research might be interpreted by some critics as one-sided and not representative of the views of most beginner teachers in South Africa who are working. The second limitation of this study is the sample size. In this study, 222 responses were received. As a result, the findings of this research might be considered not representative of the target sample size.

The presence and effective implementation of mentoring programmes in schools can positively impact beginner teachers' professional development and retention during their first years of teaching.

We contend that our research holds significance for international readership as it aims to garner attention towards potential research endeavours in diverse settings concerning mentorship programs for beginner teachers, specifically promoting self-directed learning. Our research offers opportunities to compare our findings with studies conducted in more comprehensive, comparative contexts and foster research possibilities in broader, contrasting contexts.

Based on the findings of this research, the availability and effective use of mentoring programmes would significantly affect beginner teachers' self-directedness, improve their retention rate and alleviate their teaching challenges. This study was the first research on the perceptions of the influence of mentoring on the self-directedness of beginner teachers.

Although microfinancing is considered a key tool for fostering women's entrepreneurship development, there is growing concern regarding the impact of loan repayment strategies on the mental health of women entrepreneurs. This study seeks to unravel the implications of microfinance loans on the mental well-being of women entrepreneurs.

A carefully structured questionnaire was distributed to a purposive sample of one hundred women entrepreneurs in Lagos State using a mixed-method research approach. Also, interviews were conducted using an interview guide, which directly mirrored the questionnaire administered to five focus groups within Lagos State.

The study found that loan repayment and recovery strategies positively and significantly impact women entrepreneurs' mental well-being, with psychological distress serving as a measure for measuring mental well-being. Additionally, other factors such as the number of dependants and household headship trigger psychological distress, while age in business was associated with a reduction in psychological distress.

This study contributes to the existing literature by delving into the psychological implications of loan repayment strategies on the mental health of female entrepreneurs in Lagos State, Nigeria. Furthermore, it employs a triangulation research approach to validate questionnaire responses through focus group discussions.

This study aims to test the validity of the Rajan theory in South Africa and other selected emerging markets (Chile, Peru and Brazil) during the period 1975–2019.

In this study, the researchers used time-series data to estimate a Bayesian Vector Autoregression (BVAR) model with hierarchical priors. The BVAR technique has the advantage of being able to accommodate a wide cross-section of variables without running out of degrees of freedom. It is also able to deal with dense parameterization by imposing structure on model coefficients via prior information and optimal choice of the degree of formativeness.

The results for all countries except Peru confirmed the Rajan hypotheses, indicating that inequality contributes to high indebtedness, resulting in financial fragility. However, for Peru, this study finds it contradicts the theory. This study controlled for monetary policy shock and found the results differing country-specific.

The findings suggest that an escalating level of inequality leads to financial fragility, which implies that policymakers ought to be cautious of excessive inequality when endeavouring to contain the risk of financial fragility, by implementing sound structural reform policies that aim to attract investments consistent with job creation, development and growth in these countries. Policymakers should also be cautious when implementing policy tools (redistributive policies, a sound monetary policy), as they seem to increase the risk of excessive credit growth and financial fragility, and they need to treat income inequality as an important factor relevant to macroeconomic aggregates and financial fragility.