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The authors investigate the impact of governance on the leverage of East Asian firms in the financial crisis context, in order to understand the puzzle whether debt acts as a substitute for governance or an outcome of the governance mechanism.

The authors use 86,030 firm-years and the country-level governance data from eight East Asian countries over the period 1996–2017. The authors employ the fixed effects (FE) model, in the main analysis and the weighted least squares model, as a robustness check in order to compare the two competing hypotheses of agency theory, substitute and outcome models.

The authors’ results show that debt acts as a substitute for governance before the GFC, but during and after the GFC the picture changes. Namely, debt acts as an outcome of the governance mechanism during the GFC and its aftermath. Since during financial downturns both agency costs increase, and information asymmetry widens, firms in poor-governed countries may be reluctant to increase their leverage in order not to face financial distress and additional restrictions. Thus, the results imply that the use of debt as a tool to mitigate agency conflicts and a substitute for governance strongly depends on the environment that the firms operate and the general macroeconomic conditions, such as facing a financial crisis or not.

This study provides an interesting case of the firms' capacity to raise money during a crisis and that governance plays an important role in borrowing activities of firms. This will undoubtedly help motivating owners and policymakers for improving governance. The authors’ findings may be useful for policymakers to develop policies considering the adverse effects caused by exogenous shocks. This is crucial because the severity of GFC as a shock seems to change the macro and institutional environment that firms operate. While the authors properly address the research hypotheses using country governance data, future research may employ corporate governance data to attain firm-level results by testing two competing hypotheses.

There are several important areas where this study makes original contributions. First, while Tsoy and Heshmati (2019) focus on the dynamics of capital structure for only Korean firms, the authors extend the sample including eight East Asian countries considering the impact of country governance on capital structure policy. Specifically, this study is the first in using the robust country governance data, which differs by country and year, in the crisis context. Next, the authors investigate both the AFC and GFC to compare whether these two crises have different effects on capital structure policy of East Asian firms. Finally, the authors aim to understand whether leverage is used as a substitute for governance or an outcome of governance mechanism considering recessions.

Competence-Based Management (CBM) theory and research suggest that a firm’s competence building and leveraging processes are key factors influencing its competitive success. To achieve sustained competitive success, a firm’s competence building processes must continuously renew and extend the competences a firm has and can leverage. However, the ability of a firm to sustain strategically adequate levels of competence building – while also maintaining strategically successful competence leveraging – may be limited by various self-reinforcing managerial and organizational mechanisms that can arise from competence leveraging processes. In this paper we focus on certain managerial behaviors that may create path dependencies that lead an organization to become “locked-in” to its current competence leveraging processes and to neglect essential competence building, resulting in an inability to renew competences at a strategically adequate level and eventually in competitive failure.

In order to avoid such consequences, the management literature suggests that organizations must cultivate dynamic capabilities to overcome tendencies toward lock-in and to sustain ongoing competence building. This study investigates ways in which firms can maintain healthy competence building processes by avoiding lock-ins, especially those resulting from self-reinforcing managerial behaviors. A case study of successful competence-renewing processes in a home improvement retailing company helps to amplify the components of dynamic capabilities and to illustrate the insights that emerge from our study.

This study aims to investigate the effect of fear sentiment with a novel data set on Bitcoin’s (BTC) return, volatility and transaction volume. The authors divide the sample into two subperiods to capture the changing dynamics during the COVID-19 pandemic.

The authors retrieve the novel fear sentiment data from Thomson Reuters MarketPsych Indices (TRMI). The authors denote the subperiods as pre- and post-COVID-19 considering January 13, 2020, when the first COVID-19 confirmed case was reported outside China. The authors use bivariate vector autoregressive models given below with lag-length k, to investigate the dynamics between BTC variables and fear sentiment.

BTC market measures have dissimilar dynamics before and after the Coronavirus outbreak. The results reveal that due to the excessive uncertainty led by the outbreak, an increase in fear sentiment negatively affects the BTC returns more persistently and significantly. For the post-COVID-19 period, an increase in fear also results in more fluctuations in transaction volume while its initial and cumulative effects are both negative. Due to extreme uncertainty caused by the COVID-19 pandemic, investors may trade more aggressively in the initial phases of the shock.

The authors are convinced that the results in this paper have more far-reaching implications for other markets regulated by the states. BTC provides a natural benchmark to understand how fear sentiment drives and impacts the markets isolated from any interventions. Hence, the results show that in the absence of regulatory frameworks, market dynamics are likely to be more volatile and the fear sentiment has more persistent impacts. The authors also highlight the importance of using micro, asset-specific sentiment measures to capture market dynamics better.

BTC is not associated with any regulatory authority and is not produced by the governments and central banks. COVID-19 as a natural experiment provides an opportunity to explore the pure effects of market sentiment on BTC considering its decentralized and unregulated features. The paper has two main contributions. First, the authors use BTC-specific fear sentiment novel data set of TRMI instead of more general market sentiments used in the existing studies. Next, this is the first study to examine the association between fear and BTC before and after COVID-19.

The purpose of this paper is to explain how abstract space of the State – universally and specifically within the context of Middle Eastern cities – aims to homogenise the city and eliminate any anomaly that threatens its power structure.

Through a historical and discourse analysis of these policies and processes in the two case studies, this paper presents a contextualised reading of Lefebvre’s concept of abstract space and process of abstraction in relation to the alienation of political public spaces.

The paper proposes that regardless of these homogenising strategies being applied universally, they fail to respond to contextual particularities and therefore they – in a contradictory manner – may themselves produce a space of resistance and difference.

This paper focusses on Iran, the case of Tehran and Turkey, the case of Taksim Square and Gezi Park in Istanbul. Recent policies and strategies have been proposed and implemented to reduce, alienate and possibly neutralise the impacts of urban and political protests in these cities and socio-political contexts.

This study aims to compare the academic performance of female accounting students with their male counterparts and to assess the impact and association between gender and the academic performance of accounting students graduating from the College of Business Studies (CBS) in Kuwait.

The sample consisted of 141 accounting students, who graduated during 2015 from CBS. Independent samples test, correlation and linear least squares regression analyses tested the hypotheses.

The results indicate that there was a statistically significant association between gender and accounting students’ performance, which explained the superiority of the performance of the female students’ group over the performance of the male students’ group and explained the significant impact of gender on accounting students’ performance, with and without controls for other factors.

The findings have practical implications for how the administration of CBS and similar educational institutions should take action. The findings suggest that the administration of CBS should adopt policies that impose and encourage the acceptance of more female accounting students, as they perform well in accounting and their academic performance is better than their male counterparts.

The study makes significant contributions to the existing knowledge in the area of students’ performance by empirically supporting the theoretical expectation of the impact of gender on accounting students’ performance. It provides a foundation for future comparative studies, potentially leading to the harmonization of international accounting education. It also addresses some of the shortfalls in the existing regional accounting education literature resulting from the scarcity of prior studies, where little has been published.

The purpose of this paper is to examine the factors that influence farmers' preference for the use of Islamic banks in Turkey and to investigate their knowledge level and perception about Islamic finance.

Survey data used in this study is obtained by drawing a sample of 1902 farmers who are members of the Agricultural Credit Cooperatives Union (ACCU) from 37 provinces of Turkey. Pearson's Chi-square test is used to analyze the association between the demographic features of farmers, conventional bank usage and Islamic bank usage. Binary logistic regression model is used to estimate the factors influencing the preference for Islamic banks. Explanatory variables include knowledge on Islamic banking and finance, perception of compliance to religion, saving ability and cost concern along with the control variables of Islamic bank branch number in the region and age of respondent. Robustness check is conducted via alternative models using ordinary least squares (OLS) and logistic regression.

Less than 10% of the participant farmers use Islamic banks and 59% declare they know nothing about Islamic banking. Age, education level, income level, nonagricultural income level, saving ability, duration of working in agriculture, land size and region are significantly related to farmers' preference of using Islamic banks. Knowledge level, perception of religious compliance, saving ability and cost concern are statistically significant factors that influence the probability of using Islamic banks.

This study does not include the analysis of the relationship between being religious and using Islamic banks because questions related to the assessment of religious practice were excluded due to the ACCU's sensitivity to investigate personal beliefs. Therefore, future studies can expand the scope of this research by investigating religiousness. The sample is chosen from the ACCU members who are already benefiting from a formal source of credit; therefore, the results should not be attributed to all farmers.

Islamic banks and microfinance institutions' further engagement in the agricultural sector and ACCU's implementation of Islamic finance instruments.

Islamic banks' further diversification in the agricultural sector and ACCU's implementation of Islamic finance instruments.

To the best of the authors' knowledge, this paper is the first to investigate the farmers' perception and preference of Islamic banking in Turkey. The sample size of 1902 is much larger and geographically diversified compared to studies in agricultural finance. This study will be valuable for the agricultural finance empirical studies in Turkey as well as an important addition to the emerging literature on Islamic finance.

This study proposes a model that influences customer citizenship behavior during COVID-19, and empirically tests the effects of fast-food restaurant customers' perceptions of justice (price and procedural justice) on trust; trust on satisfaction and loyalty; and trust, satisfaction and loyalty on customer citizenship behavior. Furthermore, it was questioned whether there was a disparity between customer expectations based on the restaurant's image and consumption experience.

The data were gathered from customers of fast-food restaurants in the shopping centers in Turkey. The data set, which included 437 valid questionnaires, was subjected to CFA for validity and reliability, SEM analysis for hypothesis and paired sample t-Tests for the research questions.

The findings of the study indicate that perceived justice affects customer trust, which, consequently, affects customer loyalty and satisfaction during the COVID-19 period. Findings also demonstrate that, while customer loyalty and trust increase customer citizenship behavior, customer satisfaction alone is insufficient to increase customer citizenship behavior. The study also shows that during the COVID-19 period, fast-food restaurants should have raised awareness of employees’ fair behaviors toward the customers and provided additional services to differentiate themselves in the market. Also, it indicates that customer expectations related to price, cleanliness and professional appearance of staff are not met after taking service.

No research has been found in the literature focusing on the expectations, justice, trust, satisfaction, loyalty and citizenship behaviors of fast-food restaurant customers in the COVID-19 pandemic process. Therefore, the results can fill the gap in relevant literature by testing the relationships between justice, trust, satisfaction, loyalty and citizenship during the pandemic and provide inferences for fast-food business owners.

In the study, a five-dimensional-safety risk assessment model (5D-SRAM) is developed to improve the construction safety risk assessment approaches available in the literature. To that purpose, a hybrid multi-dimensional fuzzy-based model is proposed, which provides a comprehensive ranking system for the safety risks existing in a project by considering the contextualization of the construction-related activities resulting in an accident.

The developed 5D-SRAM is based on an amalgamation of different fuzzy-based techniques. Through the proposed fuzzy analytic hierarchy process (AHP) method, the importance weights of essential risk dimensions playing role in defining the magnitude of the construction-related risks are obtained, while a precise prioritized ranking system for the identified safety risks is acquired using the proposed fuzzy technique of order preference similarity to the ideal solution (FTOPSIS).

Through the application of the proposed 5D-SRAM to a real-life case study – which is the case of green building construction projects located in Hong Kong – contributions are realized as follows: (1) determination of a more complete range of risk dimensions, (2) calculation of importance weightings for each risk dimension and (3) obtainment of a precise and inclusive ranking system for safety risks. Additionally, the supremacy of the developed 5D-SRAM against the other safety assessment approaches that are commonly adopted in the construction industry is proved.

The developed 5D-SRAM provides the concerned safety decision-makers with not only all the crucial dimensions that play roles toward the magnitude of safety risks posing threats to the workers involved in construction activities, but also they are given hindsight regarding the importance weights of these dimensions. Additionally, the concerned parties are embellished with the final ranking of safety risks in a more comprehensive way than those of existing assessment methods, leading to sagacious adoption of future prudent strategies for dealing with such risks occurring on construction sites.

Numerous studies have documented the safety risks faced by construction workers including proposals for risk assessment models. However, the dimensions considered by such models are limited, generally constrained to risk event probability combined with risk impact severity. Overlooking other dimensions that are essential towards the calculation of safety risks' magnitude culminates in overshadowing the further adoption of fruitful mitigative actions. To overcome this shortcoming, this study proposes a novel 5D-SRAM.

With the rapid development of Internet technology, cybersecurity threats such as security loopholes, data leaks, network fraud, and ransomware have become increasingly prominent, and organized and purposeful cyberattacks have increased, posing more challenges to cybersecurity protection. Therefore, reliable network risk assessment methods and effective network security protection schemes are urgently needed.

Based on the dynamic behavior patterns of attackers and defenders, a Bayesian network attack graph is constructed, and a multitarget risk dynamic assessment model is proposed based on network availability, network utilization impact and vulnerability attack possibility. Then, the self-organizing multiobjective evolutionary algorithm based on grey wolf optimization is proposed. And the authors use this algorithm to solve the multiobjective risk assessment model, and a variety of different attack strategies are obtained.

The experimental results demonstrate that the method yields 29 distinct attack strategies, and then attacker's preferences can be obtained according to these attack strategies. Furthermore, the method efficiently addresses the security assessment problem involving multiple decision variables, thereby providing constructive guidance for the construction of security network, security reinforcement and active defense.

A method for network risk assessment methods is given. And this study proposed a multiobjective risk dynamic assessment model based on network availability, network utilization impact and the possibility of vulnerability attacks. The example demonstrates the effectiveness of the method in addressing network security risks.

The purpose of this study is proposing a novel neutrosophical stakeholders' analysis approach for sustainable fashion supply chain (SFSC), presenting a supply chain members and objectives in order to conduct a sustainable business, investigating the roles and positions of these stakeholders, determining the contribution levels of these stakeholders to the sustainability objectives, and accordingly identifying the convergence and divergence among the stakeholders in terms of realization of the objectives.

A novel neutrosophic set-based stakeholders' analysis Method of ACTors, Objectives, strength Reports (MACTOR) approach is proposed considering the uncertain and indeterminate opinions of decision-makers. In order to obtain the mutual opinions of decision-makers, Delphi technique is employed.

The analysis results of this research emphasizes that although the manufacturers can be thought as the foremost actor is SFSC by producing the main product, they have no superior power on conducting the business. Besides, the government, customer and fashion firms are the key players shaping the fashion industry. Retailers and distribution centers can be interpreted as an intermediary in between the other stakeholders. Moreover, the eco-friendly packaging providers have not gained an important role that they were supposed to in terms of the sustainability objectives.

The application phase of the research includes the possibility of subjective judgments of the participants as a limitation. Therefore, Delphi technique is applied to overcome this challenge by multiple rounds of interviews for panel of participants in order to combine the benefits with elements of the wisdom of people.

Examining a multi-echelon supply chain is a practical implication providing the mutual opinions of experts such as designers, stylists, journalists, consultants, procurement managers, entrepreneurs, activists etc. for sustainability in the fashion industry. One can derive from the findings to determine which sub-echelon requires more attention, or which business is more important to focus on most, or which branch of activity influences others most.

This is one of the few articles that focuses on the sustainability objective and highlights the active roles of all members of the supply chain. Besides, this is the first study deploying neutrosophic sets for MACTOR analysis.