Impact mitigation or ecological restoration? Examining the environmental sustainability practices of multinational mining companies

This paper examines the environmental sustainability practices of multinational mining companies in addressing their impacts and promoting the sustainable development of local communities in Ghana. Although large-scale mining companies have embraced environmental sustainability, the drivers and the mechanisms for addressing their impacts throughout the mine life cycle is not fully understood because of the limited research in this area. The focus in this study involves an examination of the drivers for environmental sustainability in a weak and non-enabling institutional context and the mechanisms for addressing impacts on biodiversity, water quality and quantity, and ambient climate. The findings show that the environmental sustainability practices of multinational mining companies are determined by regulatory compliance and corporate environmental responsibility based on perceived ethical obligation. Additionally, we find gaps in mine closure planning and rehabilitation because of the limited requirement for biodiversity restoration in the domains of flora repopulation and active fauna reintroduction. This paper provides empirical and theoretical insights for academics and practitioners in industry and policymaking.     

Cluster Analysis for mixed data: An application to credit risk evaluation

Credit risk is one of the main risks faced by a bank to provide financial products and services to clients. To evaluate the financial performance of clients, several scoring methodologies have been proposed, which are based mostly on quantitative indicators. This paper highlights the relevance of both quantitative and qualitative features of applicants and proposes a new methodology based on mixed data clustering techniques. Indeed, cluster analysis may prove particularly useful in the estimation of credit risk. Traditionally, clustering concentrates only on quantitative or qualitative data at a time; however, since credit applicants are characterized by mixed personal features, a cluster analysis specific for mixed data can lead to discover particularly informative patterns, estimating the risk associated with credit granting.     

Dynamic management of aircraft stand allocation

This paper aimed to present an original approach for solving the aircraft stand allocation (SA) problem dynamically when due to operational disturbances, the planned allocation cannot be accomplished. The proposed Multiple-criteria Dynamic Stand Allocation (MDSA) method uses fuzzy logic to support decision-making under uncertainty. The MDSA method provides effective solutions in a short time, necessary for traffic management in case of delays, emergency, and untypical cases. It considers partially conflicting points of view of different airport users (airport managers, air traffic controllers, airlines, handling agents, and passengers) and may significantly support managers on the SA problem. The approach proposed can also be used for creating an initial SA plan for a considerable number of aircraft.     

Network structure,portfolio diversification and systemic risk

We investigate the effect of portfolio diversification on banking systemic risk, where the network effect is incorporated. We analyze three kinds of interbank networks, namely, random networks, small-world networks and scale-free networks. We show that the effect of portfolio diversification on banking systemic risk depends on interbank network structures and shock types. First, systemic risk increases first and then reduces with the increase of the level of portfolio diversification in the case of the individual shock. Second, in the case of the systemic shock, systemic risk reduces with the increases of the level of portfolio diversification. Third, banking systems with scale-free network structures are the most stable, and those with small-world network structures are the most vulnerable.     

Extinction accounting and accountability: Empirical evidence from the west European tissue industry

Recently, human activities are more and more invasive with respect to biodiversity. Several studies highlighted the key role played by accountants in contributing to the development of tools able to support company in assessing, reporting, and disseminating, as well as accomplishing, the preservation of natural species and ecosystems (King and Atkins, 2016). Corporate reporting of environmental information might increase the credibility of forest certifications, given that some scholars argued that certified forests are not often run, in a sustainable way. Moreover, certifications sometimes cover harmful forest practices (Elad, 2014) and do not ensure a good quality of environmental reporting and performance. The research question therefore intends to explore how extinction accounting and accountability (EAA) is able to reflect ex post the company's business strategy and, at the same time, influence ex ante its formulation by easing the prevention of deforestation risk and addressing the issue of credibility through specific actions. In more detail, the “Emancipatory Framework for Extinction Accounting and Accountability” (EFEAA) (Atkins and Maroun, 2018) was tested using content and interpretative analyses based on the reports inherent to top four companies working in West Europe in the tissue industry, where the preservation of forest heritage is a “compulsory route” for assuring the business sustainability, in terms of both raw material renewal and brand reputation. The findings highlighted the first attempt to carry out a qualitative research over the management of forest issues. In our study, companies tend to report advantages arising from the use of forest, but this kind of disclosure is too generic without providing evidence over the ecosystem services forests produce. Moreover, firm size affects the quantity and the quality of disclosure. At last, managerial implications and future research avenues are outlined and discussed.     

A study on factors affecting privacy risk tolerance to prevent the spread of COVID-19 in South Korea

South Korea has been evaluated as a country that is responding well to COVID-19. The Government of the Republic of Korea discloses where, when, and by which means of transportation people confirmed to have the virus have visited. Although disclosure of movement has contributed to flattening the curve and providing timely medical service, concerns about privacy infringement have also been raised. This article determines what factors influence privacy risk tolerance, looking specifically at threat severity, vulnerability, response efficacy, and response cost. We also provide implications for the preparation of better countermeasures for the government to implement.     

The mechanism of credit risk contagion among internet P2P lending platforms based on a SEIR model with time-lag

The credit risk contagion of Internet peer-to-peer (P2P) lending platforms is an important part of Internet financial risk management and supervision. This study analyzes the contagion path of credit risk in Internet P2P lending. Based on complex network theory and the theory of infectious disease dynamics, the characteristics of Internet P2P lending development are combined to construct a SEIR model of credit risk transmission among Internet P2P lending platforms with time lag, and the robustness of the model is analyzed and proven. The influence of platform correlations, the susceptible immune rate, the platform elimination rate, contagion latency, the saturation coefficient, and the susceptibility input rate on credit risk contagion behavior among Internet P2P lending platforms is analyzed, using the equilibrium point and threshold value. The impact of each variable is analyzed by simulation. Corresponding countermeasures and suggestions are proposed to prevent and control credit risk contagion among these platforms.     

The impact of COVID-19 on the stock market crash risk in China

This study investigates the impact of the COVID-19 pandemic on the stock market crash risk in China. For this purpose, we first estimated the conditional skewness of the return distribution from a GARCH with skewness (GARCH-S) model as the proxy for the equity market crash risk of the Shanghai Stock Exchange. We then constructed a fear index for COVID-19 using data from the Baidu Index. Based on the findings, conditional skewness reacts negatively to daily growth in total confirmed cases, indicating that the pandemic increases stock market crash risk. Moreover, the fear sentiment exacerbates such risk, especially with regard to the impact of COVID-19. In other words, when the fear sentiment is high, the stock market crash risk is more strongly affected by the pandemic. Our evidence is robust for the number of daily deaths and global cases.     

Relief aid stocking decisions under bilateral agency cooperation

We aim to quantify the benefits of cooperation between humanitarian relief agencies in terms of stocking decisions. We consider two agencies that stock the same type of relief item at different locations prone to individual disaster risks and agree to transship the shortage amount from available stocks in case of a disaster. We incorporate the disaster risk to the Newsvendor model by conditioning the stock quantity decisions on the event that a major disaster occurs within the lifetime of the stocked relief item. We optimize the stock quantity for each agency in response to the other's quantity and compute a Nash Equilibrium solution numerically. We apply this game theoretic approach to the case of earthquake preparedness in Istanbul to optimize the stocking decisions of an agency for shelter units in cooperation with another agency. We investigate the characteristics of the solutions under various parameter settings and identify cases in which cooperation may be beneficial to one or both of the agencies.     

Failure to learn from failure: The 2008 mortgage crisis as a déjà vu of the mortgage meltdown of 1994

This article traces the developments in the market for residential mortgage-backed securities (MBS) during the period 1970–2008. Drawing on an analysis of trade publications, business press, and interviews with practitioners, it shows that an MBS market meltdown in 1994 provided clear signals of problems with MBS. The market participants did not re-evaluate their use of risk management tools or adjust security design in response to the 1994 crisis, suggesting a lack of understanding of the implications of the crisis. The 1994 meltdown showed that MBS were vulnerable to systematic risks and that these risks could precipitate an MBS market crash. Furthermore, the 1994 meltdown demonstrated that large-scale investment in MBS could affect the primary mortgage market, thereby rendering the MBS risks unpredictable. After 1994, MBS investment shifted to MBS backed by mortgages with default risk – a development that led to the crash of 2008. By drawing parallels between the 1994 and 2008 crises, this article shows how the MBS market failed to self-correct. The results suggest that financial market participants do not always incorporate relevant information in their decision-making and that market participants have difficulties in both foreseeing the effect of financial innovations on markets and interpreting these effects.