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Too many or too few? On the optimal number of firms in the commons
No full textInternational audienceIn this paper, we consider common-pool non-renewable resource industries and study the socially optimal industry size. Our analysis is conducted in terms of an infinite-horizon differential game (with either open-loop or feedback strategies). We derive two main results. First, we show that there exists a unique state-independent efficiency-inducing industry size, ranging between 1 and infinity, if and only if the elasticity of the price-cost margin (capturing static market power) and the elasticity of the difference between social and private resource rents (capturing the tragedy of the commons) are the same. Second, allowing for entry/exit, we show that the regulator can set a license fee to be paid by firms to get access to the resource such that the endogenous number of firms in the equilibrium with regulated entry is socially optimal
Animal Behavior in Capital markets: Herding formation dynamics, trading volume, and the role of COVID-19 pandemic
No full textInternational audienceThis paper provides new evidence on herding behavior. Using daily frequency data for 336 US listed firms over a five-year period, we investigate three important elements of financial herding behavior. First, trading volume, representing market interest, as a significant variable in capital markets apart from stock prices. Second, herding dynamics since herding formation is a dynamic process. Third, the reaction of possible financial herding to exogenous events-threats, as we use the pandemic event in order to investigate a market under stress. Even though the benchmark herding model used does not provide evidence of herding behavior, our results verify the significance of the above herding elements. We also find that trading volume and positive changes in trading volume result in increased cross-sectional absolute deviation (CSAD). Most importantly, we find that herding behavior is evident during the COVID-19 pandemic confirming that investors tend to herd during major crisis periods
A machine learning study to improve the reliability of project cost estimates
No full textInternational audienceProject managers need reliable predictive analytics tools to make effective project intervention decisions throughout the project life cycle. This study uses Machine learning (ML) to enhance the reliability in project cost forecasting. A XGBoost forecasting model is developed and computational experiments are conducted using real data of 110 projects representing 1268 cost data points. The developed model performs better than some Earned value management (EVM), ML (Random forest, Support vector regression, LightGBM, and CatBoost), and non-linear growth (Gompertz and Logistic) models. The model produces more accurate estimates at the early, middle, and late stages of the project execution, allowing for early warning signals for more effective cost control. In addition, it shows more accurate estimates in most projects tested, suggesting consistency when repeatedly used in practice. Project forecasting studies mainly used ML to estimate the project duration; a few ML studies estimated the project cost at the project’s conceptual stage. This study uses real data and EVM metrics, proposing an effective XGBoost model for forecasting the cost throughout the project life cycle
A decentralized production–distribution scheduling problem: Solution and analysis
No full textInternational audienceIn modern production–distribution supply chains, decentralization has increased significantly, due to increasing production network efficiency. This study investigates a production scheduling and vehicle routing problem in a make-to-order context under a decentralized decision-making structure. Specifically, two different decision makers hierarchically decide the production and distribution schedules to minimize their incurred costs and we formulate the problem as a bi-level mixed-integer optimization model as a static Stackelberg game between manufacturer and distributor. At the upper level, the manufacturer decides its best scheduling under a flexible job-shop manufacturing system, and at the lower level, the distributor decides its distribution scheduling (routing) which influences the upper-level decisions. The model derives the best production–distribution scheduling scheme, with the objective of minimizing the cost of the manufacturer (leader) at the lowest possible cost for the distributor (follower). As the lower level represents a mixed-integer programming problem, it is challenging to solve the resulting bi-level model. Therefore, we extend an efficient decomposition algorithm based on Duplication Method and Column Generation. Finally, to discuss the decentralization value, the results of the presented bi-level model are compared with those of the centralized approach
The irreversible pollution game
No full textInternational audienceWe investigate the extent to which the irreversibility of pollution shapes the free-riding problems inherent in pollution (differential) games. To this end, we use two-country differential pollution games. Irreversibility is of a hard type: While strictly positive and concave below a certain threshold level of pollution, pollution decay drops to zero above this threshold. Assuming that the pollution damage function and preferences are quadratic, we first examine both the cooperative and non-cooperative versions of the game. We innovate in analytically demonstrating the existence of Markov perfect equilibria (MPE) and characterizing these. Second, we demonstrate that when players face the same pollution costs (symmetry), irreversible pollution regimes are more frequently reached than under cooperation, and we evaluate the irreversibility penalty stemming from the absence of cooperation. Incidentally, we prove that open-loop Nash equilibria lead to reach more frequently the irreversible regime than the MPE under our setting. Third, we study the implications of asymmetry in the pollution cost. We find that for equal total pollution costs, asymmetric equilibria produce a lower emission rate than the symmetric under some mild conditions, thereby driving the system to irreversibility less frequently than the latter. Finally, we prove that provided the irreversible regime is reached in both the symmetric and asymmetric cases, long-term pollution is greater in the symmetric case, reflecting more intensive free-riding under symmetry
Does corporate governance affect the performance and stability of Islamic banks?
No full textInternational audiencePurpose This paper aims to investigate the impact of corporate governance practices on cost efficiency and financial stability for a sample of Islamic and conventional banks. In the analysis, the author uses a set of corporate governance variables that include, the board size, board independence, director gender, board meetings, board attendance, board committees, chair independence and CEO characteristics. Design/methodology/approach The author uses corporate governance data of Islamic banks that is unique in this field. In the analysis, the author also uses stochastic frontier analysis and panel vector autoregression models to quantify long-run and short-run statistical relationships between the operational efficiency of Islamic Banks and corporate governance practices. Findings According to the results, Islamic and conventional banks exhibit important differences in the effects of corporate governance practices on cost efficiency and financial stability. Results show that with a blind general adoption of corporate governance practices, Islamic banks may suffer a loss in their value since the adoption of the third layer of binding practices, over and above the already existing ones, imposed by the Sharia Board and the Board of Directors, may lead to cumbersome business operations. This conclusion is of importance to Islamic Banks since they struggle to survive in a very competitive international environment. Practical implications The author believes that the results may be of a certain value to regulators, policymakers and managers of Islamic banks. Based on the results, the author postulate that Islamic banks should select carefully international corporate governance practices. Social implications Islamic banks should not adopt additional third layer of binding practices as that would result lower performance and instability that would be damaging for the economy Originality/value This study employs a unique sample of Islamic banks that includes corporate governance data hand collected. Our findings of the corporate governance impact on Islamic banks performance and stability are therefore unique in the literature
Integrating bloodmobiles and drones in a post-disaster blood collection problem considering blood groups
No full textInternational audienceProviding safe and adequate blood in an emergency to save many lives can be a challenge to the health system. In addition to managing blood collection in crises, delivering blood to the crisis site in a timely manner is another important problem in decision-making. Hence, in this study, we present a bi-objective mathematical model for determining the routing of bloodmobiles and drones to collect blood from various blood group donors and apply a cross-match strategy to supply adequate blood in critical situations. The first objective function is to maximize the amount of collected blood while the second objective function is to minimize the maximum arrival time of vehicles to the crisis-stricken city. We also introduce a function that determines the time required for bloodmobiles to stay in one place for the blood-collection process so as to bring the problem closer to real-world conditions. The problem is formulated as a two-stage stochastic problem by considering uncertainty in blood demands and the number of donors. To demonstrate the applicability and the efficiency of the proposed model, the model is tested on data from a real case study and implemented in various sizes via CPLEX and MOPSO. Finally, the sensitivity analysis is performed on certain parameters. The results show that by adding bloodmobiles, the staying time of bloodmobiles in stations decreases, and the demands are met more rapidly. Also, for each drone added to the system that is responsible for transporting the collected blood to the disaster-stricken area, the amount of collected blood increases by 12% while the arrival-time of the last vehicle decreases by 46%. Therefore, this model can benefit decision-makers in times of crisis and the collection and timely delivery of blood to the crisis area
Coordinating vessel recovery actions: Analysis of disruption management in a liner shipping service
No full textInternational audienceDisruptions often occur in liner shipping networks, and they are costly. When they occur, freight companies evaluate their effects on freightage in the pipeline and take the appropriate recovery actions by balancing customer service levels and increases in fuel consumption while accounting for environmental impact (greenhouse gas (GHG) emissions). The paper, therefore, develops an integrated mixed-integer programming problem (MIPP) that jointly minimizes the total voyage and transshipment costs and penalty charges for emitting GHG excess amounts beyond what is allowed. It does so by recovering a pre-established schedule of disrupted containerships. The solution to the MIPP suggests how to reconfigure the liner shipping network when skipping one or more call ports and determines the optimal velocity on assigned routes. The paper also develops and proposes a new and efficient algorithm based on the Crowd-Learning Particle Swarm Optimization (CLPSO) to solve this large-scale problem and shows the CLPSO to be superior to the potential ones in the literature. Computational experiments, based on data from a maritime shipping company, demonstrate the effectiveness of both the MIPP and CLPSO using several comparative metrics with suitable assumptions. The numerical results show that the developed MIPP has a potential application in practice
How uncertainty can determine corporate ESG performance?
No full textInternational audienceUsing Sino‐Securities Environmental, social, and governance (ESG) ratings data, we examine how environmental uncertainty affects the ESG performance of Chinese A‐share non‐financial listed firms from 2008 to 2020. Our findings show that environmental uncertainty harms corporate ESG performance. In particular, when environmental uncertainty increases, a firm's ESG score and ESG ratings decline due to factors such as financial constraints and industry competition. We argue that as the environmental risk premium rises, it increases the real options value of postponing sustainable investment for a firm. Consequently, the firms tend to cut down their ESG investment by weighing the long‐term benefits and short‐term direct costs. The value of real options changes with the investment opportunities available to the firms and the financing constraints and competitive pressure changes the size of investment opportunities. We argue that higher financing constraints and industry competition restrict available investment opportunities and dilute the negative impact of environmental uncertainty on corporate ESG performance. These results add to the existing literature investigating the impact of uncertainty on corporate ESG performance and offer insights to regulators and enterprise managers. These results are robust to alternate proxies of ESG performance and alternate regression techniques
Employee frustration with information systems: appraisals and resources
No full textInternational audienceFrustration experiences have important organizational and individual consequences, particularly in today's workplaces strongly reliant on information systems (IS). However, recent research has neglected the importance of this emotion in organizations. We propose a model of frustration with IS that considers its IS-related antecedents, consequences, and potential moderators. Drawing arguments from appraisal theory and conservation of resources theory, we propose a characterization of frustration through cognitive appraisals of IS in organizations. We suggest that both positive and negative responses to frustration can occur depending on its degree of activation, as well as individual and contextual factors, thus providing a holistic model of the IS frustration experience