Annals of Operations Research最新文献

We investigate whether corporates’ environmental, social, and governance (ESG) performance affects their systemic risk. Based on 284 publicly-listed Chinese firms over the period 2011–2020, we construct a tail risk spillover network for measuring their connectedness and systemic risk and use a panel regression model to examine the influence of corporate ESG performance on systemic risk. Network connectedness is an essential channel for risk contagion, and the energy, industry, and finance sectors occupy a significant position in the system. The ESG performance has a significant negative impact on systemic risk, both in terms of systemic vulnerability and systemic risk contribution, i.e., the ESG performance can dampen the two-way transmission of shocks between individual firms and the system. The results are robust to proxy measures of systemic vulnerability and systemic risk contribution, as well as to winsorize all variables and lag the core explanatory variables. Our study provides a new angle from the ESG performance for regulating systemic risk.

The effective management of permissible payment delays and credit interest is a crucial aspect of financial inventory control. This research delves into payment policies such as acceptable credit terms, permissible payment delays, and interest rates on overdue payments in the context of managing perishable and non-perishable inventory items. The primary aim of our study is to formulate a total cost minimization problem with respect to optimal cycle time and ordering quantities, considering time-, price discount-, and advertisement-dependent demand patterns to simulate real-world scenarios. In today’s highly competitive market, determining optimal ordering policies and pricing strategies is paramount. Suppliers employ various tactics, including incentives for retailers and advertising, to boost sales. We specifically examine the impact of permissible payment delays within the framework of trade-credit policies, which can significantly benefit businesses. Additionally, our model incorporates practical elements such as partial backlogged shortages, lost sales, instantaneous replenishment, an infinite time horizon, and constant lead times. The objective of the current paper is to develop advanced inventory models that account for demand patterns influenced by time, price discounts, and advertisements, while incorporating trade-credit policies for both perishable and non-perishable items. By analyzing the objective functions, we derive optimal solutions for various scenarios within the inventory problem. An SGO (Swarm-based Global Optimization) algorithm is proposed to demonstrate the applicability of the developed models and to minimize the retailer’s total costs. Additionally, a comparative analysis of trade-credit policies for perishable and non-perishable items is conducted to highlight their respective impacts. We provide numerous numerical examples to validate our statistically independent processes and offer graphical analyses of the convexity of each nonlinear objective function. Our findings emphasize the substantial influence of each parameter on the optimal total cost within the proposed model. The findings indicate that as demand becomes increasingly sensitive to price, time, and advertisement, the benefits of coordination in inventory management are significantly enhanced, particularly in conjunction with trade-credit policies.

In response to the increasing demand for faster customer service and cost-effective solutions in competitive markets, many companies are exploring strategies and tools to streamline their services. One emerging approach involves the integration of drones with trucks, offering potential benefits such as reduced environmental impact and delivery time. This study focuses on the use of a single truck coordinating with multiple drones for postal package delivery. The drones are transported by the truck, and both vehicles are responsible for carrying out deliveries. To account for weather uncertainties, specifically wind direction and speed affecting drone travel time, a robust optimization model is developed to address the truck-drone routing problem. Additionally, a hybrid metaheuristic algorithm is proposed, combining Adaptive Large Neighborhood Search, Clarke and Wright Saving Algorithm, and Genetic Algorithm. The effectiveness of this algorithm is assessed through numerical experiments, including sensitivity analyses on key problem parameters. The findings demonstrate that the proposed model has practical applications in last-mile delivery services, while the algorithm provides near-optimal solutions within a reasonable timeframe (ALNS reaches the solutions 3500% faster than GAMS for small-sized problems in average). Also the results show that with the 100% increase in average distance between nodes in the network, the service time increases by more than 200%.

Religious norms, as one of the informal institutions, influence firms’ responsibility for protecting the natural environment and motivate them to invest in environmental innovation. Based on informal institution theory, we construct a model between religious norms and firms’ environmental innovation. To unlock their mechanism, we examined the mediating role of environmental ethics, as well as the moderating role of media attention and industrial competitiveness. The research sample selected 1066 listed Chinese firms from 2014 to 2022 involved in polluting industries. The results indicate that religious norms can positively affect firms’ environmental innovation, and environmental ethics play a mediating role between religious norms and firms’ environmental innovation. Media attention can strengthen the impact of religious norms on firms’ environmental ethics, while intense industrial competitiveness can weaken the incentive effect of environmental ethics on firms’ environmental innovation. This article provides key insights of relevance to the literature on informal institutions and communication studies. Moreover, the findings assist managers with religious beliefs in planning reasonable environmental innovation pathways.

This paper examines the spillover effects, connectedness and correlation among eco-friendly asset classes using robust estimation techniques such as rolling window wavelet correlation, multiscale quantile correlation coefficient and quantile VAR approaches. Specifically, the eco-friendly assets examined include the S&P Green Bond Select Index Price Index, the S&P Green Bond Index Price Index and the Dow Jones Sustainability Index World Price Index. Additional variables include the constituents of the MSCI Global Environment Price Index: Alternative Energy, Green Building, and Pollution Prevention or Clean Technology. We use daily returns from August 31, 2010, to January 13, 2022. Our results confirm that green bond indices offer opportunities for diversification across varying quantiles and time scales when paired with green stocks. Results confirm that investors can exploit the hedging and safe-haven potential of green bonds against green stocks in times of turbulent market.

Multicriteria aggregation methods typically require inputs from decision makers concerning the relative importance of the criteria. This work presents an approach to use qualitative information elicited from a panel, which can be applied to compensatory and non-compensatory multicriteria aggregation methods. In particular, it considers the additive multiattribute value function and ELECTRE, two classical methods with well-known differences in the meaning of the criteria weights. Moreover, the proposed protocol makes a distinction between the importance of improving the current situation and the importance of not worsening the current situation. The inputs from the panel are aggregated to define constraints on the importance-related parameters, which can then be used for robustness and stochastic analyses. As a real-world application, a comparison of Integrated Pest Management (IPM) is performed, considering the case of carrots cultivation in a French region. The comparisons are based on a sustainability assessment of the current practices and alternative IPM systems, using data from field trials, laboratory experiments and preferences from stakeholders. Results are robust to weighting choices, thus identifying which changes are recommended.

The need to obtain financial funds to pursue public utility investments implies the generation of Public-Private Partnership (PPP) projects. The PPP framework can involve risk-sharing mechanisms between public administration and private sector to encourage private investors to fund these projects. However, these risk-sharing mechanisms, such as Minimum Revenue Guarantee or Revenue Cap (RC), could generate opportunistic behaviors. For this reason, we can set this problem as a game in which government and private investors would act as players. This paper proposes a mathematical model to evaluate the PPP projects through a combination of Game Theory (GT) and Real Options Approach (ROA). The ROA is needed to price the uncertainty that affects PPP investments, and the GT captures the strategic interactions between public and private sectors. A case study on a wastewater treatment project is developed to apply the model we proposed.