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Introduction: Financial failure is a concept that may arise from many internal and external factors such as operational, financial, and economic items and may incur serious losses. Over-indebtedness arising from managerial misjudgments may cause high financial distress, insufficiency, and bankruptcy. In this regard, determination of effects of capital structure decisions on financial failure risk is crucial.

Aim: The main purpose of this study is to explore the relationship between capital structure decisions and financial failure risk. For this purpose, data from Borsa İstanbul (BIST) for listed food and beverage companies for the period from 2004 to 2019 is used. Another purpose of this study is to compare the financial failure models considering capital structure theories.

Method: In the study, capital structure decisions are associated with five different financial ratios; while the financial failure risk is proxied by financial failure scores of Altman (1968), Springate (1978), Ohlson (1980), Taffler (1983), and Zmijewski (1984). Therefore, five different panel data models are used for testing these hypotheses.

Findings: The results of panel data analysis reveal that capital structure decisions have statistically significant effects on financial failure risk for all models; however, those effects vary from one financial failure model to another. Also, the results show that in the models in which financial failure risk is proxied by the Altman (1968) and Taffler (1983) scores, the aggressive financial policies increase the financial failure risk. However, regarding the models in which financial failure risk is proxied by the Springate (1978), Ohlson (1980), and Zmijewski (1984) scores, aggressive financial policies decrease the financial failure risk.

Originality of the Study: To the best of our knowledge, this chapter is original and important in terms of revealing the effects of capital structure decisions on the financial failure risk and comparing the financial failure models.

Implications: The results revealed that the risk of financial failure models represented by Altman (1968) and Taffler (1983) scores are found to be statistically stronger and more successful in meeting theoretical expectations compared to other models. Therefore, it would be more appropriate to refer Altman’s (1968) and Taffler’s (1983) financial failure models in financial failure risk measurements.

This study aims to research how the outbreak of coronavirus disease 2019 (COVID-19) impacts the selected sector price indices in Borsa Istanbul (BIST), Turkey.

The authors use the event study method because it is a useful method as stock prices and market instantly reflect the effect of such an unusual event. Data are retrieved from the https://www.investing.com/.

The authors find that selected sectors are impacted by the COVID-19 outbreak. The banking and transportation sectors, on the announcement of first death, were impacted negatively, while the telecommunication and food –beverage sectors were impacted positively. The transportation and banking sectors experience an obvious downturn after the spread of COVID-19, while the food–beverage and telecommunication sectors experience an obvious upturn after the spread of COVID-19. Besides, the most adversely impacted sector is banking.

This study bridges the research gap and adds significant insights to the existing literature. The main contribution of this study to the existing literature is the unexpected outbreak impacts on financial markets, especially on BIST. It is also expected that this study will make a significant contribution to analysts, researchers and policymakers.

This study aims to analyze corporate social responsibility (CSR) programs in tourism as a tool for sustainable development in the CSR program of a multinational enterprise in Turkey.

This study includes qualitative research on a single company, content analysis of company-originated documents, participant observations, questionnaires for tourism project coordinators and follow-up interviews with company directors and project managers.

The paper identifies immediate context variables, program management, the complementary nature of interests and the diverse capabilities of the partners and an ongoing evaluation process as the determining factors for creating shared value for CSR programs in tourism.

Despite the challenges of impact assessment and measurement of long-term effects, the study proposes a systematic framework for evaluating shared value creation generated by CSR activity.

The evaluation methodology introduced in this research will be of use to CSR program developers in interpreting and reporting on the anticipated outcomes and impacts of their interventions in sustainable tourism development.

A lack of outcome evaluation and impact assessment may affect accountability and, hence, the legitimacy of CSR programs. This study attempts to mitigate that limitation by introducing a novel methodology.

The value of CSR in tourism is a highly contested issue, despite its high potential for contributing to sustainable development. This longitudinal research goes beyond presenting immediate outputs of a CSR program in sustainable tourism; it discusses intermediate outcomes in the form of capitals, community well-being and shared value for society at large.

Introduction: Decision making is always based on several factors which may affect the possible outcomes, especially in financial markets. Instead of having many criteria which may be required for decision making, “Multiple Criteria Decision Making” (MCDM) models might be used as a tool to reduce all criteria into a single one.

Purpose: The aim of this study is to measure the financial performance of commercial banks listed on Borsa Istanbul (BIST) by the MCDM.

Method: To this end, data from 15 different financial ratios from 11 commercial banks were used between the periods of 2002 and 2018. Both TOPSIS and gray relational analysis (GRA) models were used, which are commonly used in the literature for detecting the financial performance of listed banks in BIST based on their consolidated financial statements.

Results: According to the TOPSIS method, while the best bank is QNB Finansbank, HALKB, a public bank, was determined as the best bank using the GRA method. There is no significant correlation between financial performance indicators and market returns obtained by either method, with exceptions. There is no generally significant correlation detected between financial ratios and market returns. Accordingly, it is concluded that the bank stock prices in the study are shaped by the influence of external factors and expectations. The study results include information that can be used for different purposes among bank managers, academics and financial investors.

Coronavirus disease (Covid-19) has created uncertainty in all countries around the world, resulting in enormous human suffering and global recession. Because the economic impact of this pandemic is still unknown, it would be intriguing to study the incorporation of the Covid-19 period into stock price prediction. The goal of this study is to use an improved extreme learning machine (ELM), whose parameters are optimized by four meta-heuristics: harmony search (HS), social spider algorithm (SSA), artificial bee colony algorithm (ABCA) and particle swarm optimization (PSO) for stock price prediction.

In this study, the activation functions and hidden layer neurons of the ELM were optimized using four different meta-heuristics. The proposed method is tested in five sectors. Analysis of variance (ANOVA) and Duncan's multiple range test were used to compare the prediction methods. First, ANOVA was applied to the test data for verification and validation of the proposed methods. Duncan's multiple range test was used to identify a suitable method based on the ANOVA results.

The main finding of this study is that the hybrid methodology can improve the prediction accuracy during the pre and post Covid-19 period for stock price prediction. The mean absolute percent error value of each method showed that the prediction errors of the proposed methods were all under 0.13106 in the worst case, which appears to be a remarkable outcome for such a difficult prediction task.

The novelty of this study is the use of four hybrid ELM methods to evaluate the automotive, technology, food, construction and energy sectors during the pre and post Covid-19 period. Additionally, an appropriate method was determined for each sector.

The purpose of this study is to investigate the association between environmental performance of firms and the level of voluntary environmental disclosure in emerging markets.

We used tobit regression OLS and t-test methods to reveal the association between environmental performance and the level of voluntary environmental disclosure.

We find a significant positive association between the level of discretionary environmental disclosures and corporate environmental performance. The result is in line with the arguments of economics disclosure theory that argues environmentally good performers disclose more.

Many of the environmentally good firms in Turkey are also listed in the “BIST Sustainability Index,” and this situation can be the result of the relative power of external regulations. Accordingly, it can be suggested to increase the community and governmental pressures for environmental reporting but also gives importance to increase intrinsic motivations for companies to engage in disclosure practices.

This study shed light on relation between environmental performance and environmental disclosure in an emerging market context. Also, it is revisited that the relation between environmental performance and the level of environmental disclosure by testing two different predictions on the level of environmental disclosures.

This study aims to investigate the effects of board characteristics on the cost of debt for non-financial companies in the Turkish capital markets.

Using a sample of 211 non-financial companies listed on Borsa Istanbul, this study examines how chairperson gender and board characteristics affect the cost of debt by using panel data analysis over the period of 2016–2020. A system generalized method of moments model is also applied to test the endogeneity issue.

The findings show that the presence of female chairperson and female directors on board reduces the cost of debt and the perceptions of default risk by fund providers, while board independence and board size do not have a significant impact on the cost of debt. The results provide insightful information for companies and policymakers. Companies can alter board composition through gender diversity, while policymakers can introduce new policies in encouraging the presence of female directors on boards.

This study primarily enriches the literature on the effect of board diversity on debt financing cost in a leading emerging market, enabling companies in emerging markets to better mitigate agency costs and finance their investment through effective board composition. Second, it provides evidence that financial institutions consider companies with chairwomen and women directors on the boards less risky and charge them less for debt financing than they do for companies with man chairperson. Finally, the results support policymakers to take actions to increase female presence on board.

The purpose of this paper is to explore the interrelationship between macroeconomic factors, firm characteristics and financial performance of quoted manufacturing firms in Nigeria. Specifically, the study investigates the effect of interest rate, inflation rate, exchange rate and the gross domestic product (GDP) growth rate, while the firm characteristics were size, leverage and liquidity. The dependent variable financial performance is measured as return on assets (ROA).

The study used the ex post facto research design. The population comprised all quoted manufacturing firms on the Nigerian Stock Exchange. The sample was restricted to companies in the consumer goods sector, selected using non-probability sampling method. The study used multiple linear regression as the method of validating the hypotheses.

The study finds no significant effect for interest rate and exchange rate, but a significant effect for inflation rate and GDP growth rate on ROA. Second, the firm characteristics showed that firm size, leverage and liquidity were significant.

The study has implications for regulators and policy makers in formulating policy decisions. In addition, managers may better understand the interplay between macroeconomic factors, firm characteristics and profitability of firms.

Few studies have addressed the interplay of macroeconomic factors and firm characteristics in determining the profitability of manufacturing firms in the country and developing countries in general.