Search results

The purpose of this study is to investigate the influence of institutional dynamics on road accidents and whether this relationship is moderated by information and communication technology (ICT).

The study adopted a quantitative approach with 133 respondents. Research hypotheses were tested in AMOS version 21. In addition, moderated regression analysis was used to test the moderating role of ICT on the relationship between institutional dynamics and road accidents.

The results show that vehicle maintenance, policy enforcement, safety culture, driver training and driver management positively influence road accidents. Moreover, the study established that ICT moderates the relationship between institutional dynamics and road accidents.

The results of this study serve as a practical guideline for policymakers in the road haulage sector. Managers may gain insights on how to design effective interventions to reduce road accidents.

This research contributes to the existing body of knowledge by exploring previously unexplored moderating paths in the relationship between institutional dynamics and road accidents. By highlighting the moderating role of ICT, the study sheds new light on the institutional dynamics that influence road accidents in the context of road haulage companies.

Although risk culture is a key determinant for an effective risk management, identifying the risk culture of a firm can be challenging due to the abstract concept of culture. This paper proposes a novel approach that uses unsupervised machine learning techniques to identify significant features needed to assess and differentiate between different forms of risk culture.

To convert the unstructured text in our sample of banks' 10K reports into structured data, a two-dimensional dictionary for text mining is built to capture risk culture characteristics and the bank's attitude towards the risk culture characteristics. A principal component analysis (PCA) reduction technique is applied to extract the significant features that define risk culture, before using a K-means unsupervised learning to cluster the reports into distinct risk culture groups.

The PCA identifies uncertainty, litigious and constraining sentiments among risk culture features to be significant in defining the risk culture of banks. Cluster analysis on the PCA factors proposes three distinct risk culture clusters: good, fair and poor. Consistent with regulatory expectations, a good or fair risk culture in banks is characterized by high profitability ratios, bank stability, lower default risk and good governance.

The relationship between culture and risk management can be difficult to study given that it is hard to measure culture from traditional data sources that are messy and diverse. This study offers a better understanding of risk culture using an unsupervised machine learning approach.

The novel coronavirus (COVID-19) has caused financial stress and limited their lending agility, resulting in more non-performing loans (NPLs) and lower performance during the II wave of the coronavirus crisis. Therefore, it is essential to identify the risky factors influencing the financial performance of Indian banks spanning 2018–2022.

Our sample consists of a balanced panel dataset of 75 scheduled commercial banks from three different ownership groups, including public, private and foreign banks, that were actively engaged in their operations during 2018–2022. Factor identification is performed via a fixed-effects model (FEM) that solves the issue of heterogeneity across different with banks over time. Additionally, to ensure the robustness of our findings, we also identify the risky drivers of the financial performance of Indian banks using an alternative measure, the pooled ordinary least squares (OLS) model.

Empirical evidence indicates that default risk, solvency risk and COVAR reduce financial performance in India. However, high liquidity, Z-score and the COVID-19 crisis enhance the financial performance of Indian banks. Unsystematic risk and systemic risk factors play an important role in determining the prognosis of COVID-19. The study supports the “bad-management,” “moral hazard” and “tail risk spillover of a single bank to the system” hypotheses. Public sector banks (PSBs) have considerable potential to achieve financial performance while controlling unsystematic risk and exogenous shocks relative to their peer group. Finally, robustness check estimates confirm the coefficients of the main model.

This study contributes to the knowledge in the banking literature by identifying risk factors that may affect financial performance during a crisis nexus and providing information about preventive measures. These insights are valuable to bankers, academics, managers and regulators for policy formulation. The findings of this paper provide important insights by considering all the risk factors that may be responsible for reducing the probability of financial performance in the banking system of an emerging market economy.

The empirical analysis has been done with a fresh perspective to consider unsystematic risk, systemic risk and exogenous risk (COVID-19) with the financial performance of Indian banks. Furthermore, none of the existing banking literature explicitly explores the drivers of the I and II waves of COVID-19 while considering COVID-19 as a dependent variable. Therefore, the aim of the present study is to make efforts in this direction.

The proliferation of ride-hailing businesses brings significant considerations for improving the driver's operational performance. Informed by the literature on sharing economy, general deterrence theory and protection motivation theory this research investigates the behavioral factors impacting ride-hailing drivers' operational performance.

The authors empirically test the antecedents impacting a ride-hailing driver's operational performance using an online survey dataset comprising 513 ride-hailing drivers working for Uber and Lyft in the United States.

Ride-hailing drivers' intention to comply with the ride-hailing company guidelines results in better operational performance for the driver. Moreover, drivers believe that ride-hailing companies have effective penalties to deter drivers from violating company guidelines. However, drivers also believe that the chances of being caught while ignoring the company guidelines are low.

The results of this research support the decision-making processes of ride-hailing company managers and offer insights on how managers can enhance the operational performance of their drivers.

This study provides unique contributions to emerging research at the intersection of peer-to-peer asset sharing, behavioral studies and technology management. This research is one of the first to explore the role of behavioral factors such as coping mechanisms on the operational performance of sharing economy workers.

This study aims to identify the publication phase, performance and scientific contributions of research papers related to enterprise risk management (ERM) and to visualise the emerging themes in addressing volatility, uncertainty, complexity and ambiguity (VUCA).

The biblioshiny technique based on the bibliometrix R package was used to draw journal papers’ performance and scientific contributions by displaying distinctive features from the bibliometric method used in prior studies. The data was extracted from the Web of Science (WOS) and Scopus databases.

Since the 1990s, ERM publication has gained momentum, and it is generally categorised into four main themes. Studies by Miller (1992) and Bromiley et al. (2015) scored the highest in global and local citations, respectively. However, the Economic Outlook ranked first in quality of publications while the Journal of Risk and Insurance topped in quantity of publications. Collaborative research mainly exists between two authors, and the dynamic number of collaborative networks is evident in the USA.

This study is limited by the filtered keywords used to generate the search on journal papers’ in WOS and Scopus. It is imperative to have more comprehensive and rigorous analytics on ERM research to enable a direction for future research. Finally, ERM implementation better equips firms to mitigate risk in a VUCA environment.

This study attempts to fill a vacuum of ERM literature, specifically in business economics, in addressing VUCA. Moreover, it covers a comprehensive predetermined period of from its inception in 1983 until 2022.

This paper aims to develop an algorithm to pretest an industrial portfolio on a new scale. Portfolios include complex and uncertain projects at the front-end phase. The study, therefore, proposes a procedure that helps decision-makers to handle various complex projects and defines a common scale applicable to various kinds of industrial projects.

Decision-makers can employ the preference algorithm to reach a common understanding. To this end, the current paper posits the organization of criteria in various project sets. A sexagesimal scale is developed based on project complexity and its ability to achieve broad impact, both these factors being gauged on a five-point scale of user-friendly numberings.

The proposed algorithm shows the equivalence of industrial projects in different fields. Also, the algorithm articulates the status in terms of uncertainty, complexity, risk, and value of projects. The connections between decision-makers and criteria operate on the basis of the foreseen complexity, risk, and value. It can be said that this study exemplifies and visualizes the portfolio and criteria relationship.

The procedure covers contingency exercises at the front-end phase of a portfolio and supports decisions. However, updated information can change support positions.

The paper presents original scoring guidance for portfolio complexity on a new scale. The scaling and scoring are adjustable and calibrated using the proposed sexagesimal system. It presents an original classification of project risk and value. The main contribution is the presented algorithm which can be used to pretest industrial portfolios composed of projects that vary in both size and context.

The global financial crisis of 2008 has put greater doubt on the bank risk-management effectiveness around the world. As a part of the response to such doubt, the Gulf Cooperation Council (GCC) region is formulating some feasible approaches to manage bank risk. In this regard, an understanding of the role of the region’s culture and economic freedom will provide immense input into this risk management approach. This study examines the impact of national culture and economic freedom on bank risk-taking behavior.

Data on bank risk measures, culture and economic freedom are obtained from the FitchConnect, World Bank database, Hofstede’s insights and Heritage Foundation. Generalized least squares and two step-system generalized method of moments are then used to examine the risk-taking behavior of the region.

Banks of the GCC region operating in the low power distance, high collectivism, masculine and low uncertainty avoidance cultures are susceptible to assuming more operational and insolvency risks. Furthermore, banks’ overall risk-taking inclination is positively increased once the region has considerable business and monetary freedom.

The governments and bank regulatory bodies may benefit from the study findings by developing the best economic freedom index and national culture that enriches risk management practices and curves excessive risk-taking inclination.

To the best of the authors’ knowledge, this study is the first attempt to address the interplay among culture, economic freedom and bank risk to ensure constructive risk-taking behavior for the GCC banking industry.

Businesses are increasingly vulnerable and exposed to physical climate change risks, which can cascade through local, national and international supply chains. Currently, few methodologies can capture how physical risks impact businesses via the supply chains, yet outside the business literature, methodologies such as sustainability assessments can assess cascading impacts.

Adopting a scoping review framework by Arksey and O'Malley (2005) and the PRISMA extension for scoping reviews (PRISMA-ScR), this paper reviews 27 articles that assess climate risk in supply chains.

The literature on supply chain risks of climate change using quantitative techniques is limited. Our review confirms that no research adopts sustainability assessment methods to assess climate risk at a business-level.

Alongside the need to quantify physical risks to businesses is the growing awareness that climate change impacts traverse global supply chains. We review the state of the literature on methodological approaches and identify the opportunities for researchers to use sustainability assessment methods to assess climate risk in the supply chains of an individual business.

This study examines whether green buildings enjoy more favorable financing terms compared to their non-green counterparts, exploring the presence of a green discount in commercial real estate lending. Despite the extensive research on green premiums on the equity side, lending has received limited attention in the existing literature, even as regulations have increased and ambitious net-zero targets have been set in the banking sector.

In this study, the authors leverage a unique dataset comprising European commercial loan data spanning from 2018 to 2023, with a total loan value exceeding €30 billion. Hedonic regression analysis is used to isolate a potential green discount. Specifically, the authors rely on property assessments conducted by lenders to investigate whether green properties exhibit lower interest rate spreads and higher loan-to-value (LTV) ratios.

The findings reveal the existence of a green discount in European commercial real estate lending, with green buildings enjoying a 5.35% lower contracted loan spread and a 3.92% lower target spread compared to their non-green counterparts. However, this analysis does not indicate any distinct advantage in terms of LTV ratios for green buildings.

This research contributes to a deeper understanding of the interaction between green properties and commercial real estate lending, offering valuable insights for both lenders and investors.

This study, to the best of the authors’ knowledge, represents the first of its kind in a European context and provides empirical evidence for the presence of a green discount.

This study aims to investigate the relationship between boardroom gender diversity (BoGD) and risk-taking by property-liability (P-L) stock insurers from an analytical framework that control for organizational form and ownership structure. It relies on the behavioral agency model, the resource dependency theory and the concept of socioemotional wealth (SEW).

This study builds on an unbalanced panel of 2,285 firm-year observations from 232 European and US P-L stock insurers covering the period 2010–2019 and measure risk-taking by using four proxies: total risk (TR), upside risk (UpR), downside risk (DwR) and default risk (DR). Reverse causality and endogeneity concerns are treated by applying different approaches.

Findings suggest that BoGD mitigates the TR, DwR and DR but does not interfere with the UpR, which conceptualizes firm expectations to enhance patrimony and safeguard SEW for heirs, especially in family-owned insurers. The findings hold in various robustness checks including endogeneity and alternative specifications of BoGD and risk-taking.

This study contributes to practice by contrasting the role of female directors’ bevahior when assuming risk, which seems significantly different depending on the risk-taking specification and the organizational form. The author advises policyholders and policymakers to look at closely on BoGD and ownership structure as they affect insurance company risk-taking.

This study takes a more direct approach to highlight the BoGD’s effect on corporate risk-taking by focusing on the insurance sector which is characterized by risk and uncertainty bearing. To the best of the author’s knowledge, this is the first study to consider the full range of the stock organizational forms and the degree of family control in displaying this effect in both widely traded and closely traded insurers and to assess risk-taking from both market-based and accounting-based aspects.