Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome associated with COVID-19: An Emulated Target Trial Analysis.

RATIONALE: Whether COVID patients may benefit from extracorporeal membrane oxygenation (ECMO) compared with conventional invasive mechanical ventilation (IMV) remains unknown. OBJECTIVES: To estimate the effect of ECMO on 90-Day mortality vs IMV only Methods: Among 4,244 critically ill adult patients with COVID-19 included in a multicenter cohort study, we emulated a target trial comparing the treatment strategies of initiating ECMO vs. no ECMO within 7 days of IMV in patients with severe acute respiratory distress syndrome (PaO2/FiO2 <80 or PaCO2 ≥60 mmHg). We controlled for confounding using a multivariable Cox model based on predefined variables. MAIN RESULTS: 1,235 patients met the full eligibility criteria for the emulated trial, among whom 164 patients initiated ECMO. The ECMO strategy had a higher survival probability at Day-7 from the onset of eligibility criteria (87% vs 83%, risk difference: 4%, 95% CI 0;9%) which decreased during follow-up (survival at Day-90: 63% vs 65%, risk difference: -2%, 95% CI -10;5%). However, ECMO was associated with higher survival when performed in high-volume ECMO centers or in regions where a specific ECMO network organization was set up to handle high demand, and when initiated within the first 4 days of MV and in profoundly hypoxemic patients. CONCLUSIONS: In an emulated trial based on a nationwide COVID-19 cohort, we found differential survival over time of an ECMO compared with a no-ECMO strategy. However, ECMO was consistently associated with better outcomes when performed in high-volume centers and in regions with ECMO capacities specifically organized to handle high demand. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Assessment of the impact of progressive carbon taxation strategies on Supply Chain’s strategic decisions and performances

International audienceThe carbon tax legislation has been widely advocated as a cost-efficient law to push companies to reduce their carbon emission through their supply chain’s (SC) activities. Based on a carbon emission reduction’s target, different carbon taxation strategies have been implemented around the world. Generally, governments launch the carbon tax with a relatively low carbon price and plan to increase it incrementally over the years by adopting various strategies in a way to attend their emission reduction objective. The majority of developed mathematical models within the green supply chain design (GSCD) under carbon tax legislation have ignored the dynamic aspect of this legislation. Within this paper, we aim to contribute to the literature by studying the impact of the dynamic carbon tax legislations on the strategic decisions of a SC, its economic and environmental performances. Within this optic, we study the technology investment problem under different progressive strategies of carbon taxation, mainly a linear, a convex and a concave carbon taxes functions as well as a constant carbon tax law. Our objective is to assess and compare the efficiency of these progressive strategies for the purpose of assisting companies that are greening their SCs, in finding a compromise between reducing their carbon emissions and increasing their profits

The impact of dynamic carbon tax legislation on strategic supply chain decisions

International audienceAbstract. The carbon tax legislation has been widely advocated as a cost-efficient law to push companies to reduce their carbon emission through their supply chain’s (SC) activities. Based on a carbon emission reduction’s target, different carbon taxation strategies have been implemented around the world. Generally, governments launch the carbon tax with a relatively low carbon price and plan to increase it incrementally over years adopting various strategies in a way to attend their emission reduction objective. The majority of developed mathematical models within green supply chain design (GSCD) under carbon tax legislation have ignored the dynamic aspect of this legislation. We believe that companies when designing their SCs have to consider not only the actual applied carbon price but also the eventual evolution of this carbon price over years. We aim to contribute to literature by studying the impact of the dynamic carbon tax legislations on the strategic decisions of a SC mainly the technology investment decision. Our objective is to illustrate that the dynamic modeling approach is more appropriate to study such strategic problems than static modeling. We develop a dynamic model of technology selection under progressive carbon tax legislation. Through a numerical example, we solve the dynamic model and we compare it with the static model. To do so, this static model has been tested under three different values of the carbon taxes mainly the launch carbon tax value, the average carbon tax value and the final target carbon tax value. We compare the efficiency of the used modeling techniques to guarantee a more visibility for the company and provide it with performant decisions that allow greening their SCs and saving its profit

On The consideration of carbon emissions in modelling-based supply chain literature: the state of the art, relevant features and research gaps

International audienceThis review paper provides the operations management (OM) community with an exhaustive analysis of the mathematical models developed for the problem of low-carbon supply chain management (LCSCM). Our paper belongs to the green supply chain management (GSCM) reviews but is distinguished by its specific interest in analysing research works on supply chain (SC) management regarding the reduction of carbon emissions and its related constraints. To facilitate our benchmarking of the 83 selected papers, we adopt a literature classification based on the logistic decisions studied within the developed models. We distinguish three categories of logistic decisions: operational management, technology investment and SC design coordination. Companies are currently facing great external pressures from governments and their conscientious customers to reduce their overall emissions. We analyse how these environmental constraints, which we believe are key drivers for low-carbon emissions management, have been incorporated into mathematical models. Analysing these external pressures in terms of concern about carbon emissions constitutes our main contribution through this literature review. In addition, companies are facing a challenge to reduce their carbon emissions, which are mainly generated from production, transport and storage activities. Consequently, the modelling of carbon emissions remains a crucial task when addressing the LCSCM problem. We suggest analysing the techniques used thus far to approximate those carbon emissions. Furthermore, to illustrate our literature classification and the features of the LCSCM problem, we provide the framework on which we based our analysis of the selected literature. We discuss the modelling aspects of this problem to highlight the limits of the existing literature and consequently suggest recommendations for future research. We believe that this issue will continue to be one of the top concerns of the OM community within the GSCM field as it continues to gain importance among business leaders, and political and social actors

Assessment of the impact of progressive carbon taxation strategies on Supply Chain’s strategic decisions and performances

International audienceThe carbon tax legislation has been widely advocated as a cost-efficient law to push companies to reduce their carbon emission through their supply chain’s (SC) activities. Based on a carbon emission reduction’s target, different carbon taxation strategies have been implemented around the world. Generally, governments launch the carbon tax with a relatively low carbon price and plan to increase it incrementally over the years by adopting various strategies in a way to attend their emission reduction objective. The majority of developed mathematical models within the green supply chain design (GSCD) under carbon tax legislation have ignored the dynamic aspect of this legislation. Within this paper, we aim to contribute to the literature by studying the impact of the dynamic carbon tax legislations on the strategic decisions of a SC, its economic and environmental performances. Within this optic, we study the technology investment problem under different progressive strategies of carbon taxation, mainly a linear, a convex and a concave carbon taxes functions as well as a constant carbon tax law. Our objective is to assess and compare the efficiency of these progressive strategies for the purpose of assisting companies that are greening their SCs, in finding a compromise between reducing their carbon emissions and increasing their profits

A stochastic model for analyzing the combined effect of demand uncertainty and carbon tax within the context of Green Supply Chain Design

International audienceCarbon emission legislations are implemented for the purpose of pushing companies to pay more attention to their carbon emissions beyond Supply Chain (SC) activities and encouraging them to invest in cleaner technologies. Within this context, the present work studies the combined effect of carbon legislation and demand uncertainty on one of the strategic decisions related to green supply chain design (GSCD): the selection of production technologies. We consider a stochastic demand and we develop a stochastic newsvendor-based mathematical model for the problem of production planning and technology selection under carbon tax regulation. The majority of works that have studied this problem have developed deterministic models and studied the trade-off between emission reduction and cost increase under carbon legislations. Through a numerical example, we compare the economic and environmental performances of both deterministic and stochastic models. With this example, we show how the carbon legislations tend to push companies to invest in cleaner production technologies when demand uncertainty is considered. The obtained results also illustrate the robustness of the stochastic model to demand uncertainty over the deterministic model

A comparative study of progressive carbon taxation strategies: impact on firms’ economic and environmental performances

International audienceGovernments all over the world adopted different forms of progressive carbon taxation strategies (for example concave, convex and linear for respectively Swedish, French, and Canadian government). These progressive strategies provide companies with different degrees of flexibility to adapt their decisions to the new environmental regulations and reduce their carbon emissions without compromising their profit. However, no existing work has compared the impact of each progressive legislation on the optimal decisions of the supply chain, its profit, and its environmental performances. In this paper, we contribute to the literature by developing four multi-period technology selection models under different forms of progressive carbon taxes. We analytically determine the optimal strategic investment timing decision under each taxation strategy. We then develop a carbon tax assessment method using multi-criteria analysis techniques to compare the efficiency of each carbon taxation form in reducing carbon emission and maximising the Supply Chain (SC) profit. We prove that the earliest green investment decision and the decision of not investing in green depend on the target carbon tax rather than the taxation form. We show that government decision about the suitable taxation form should be based on the performance of the available green technologies

A dynamic stochastic model for technology investment decision under a progressive uncertain carbon tax legislation

International audienceAbstract: The carbon tax legislation is enacted in many countries to put pressures on companies to reduce their carbon emissions across their Supply chains (SC) and promote the green technology investment. The majority of countries, when applying such a legislation, adopt a progressive tax strategy. They launch the carbon tax with a relatively low carbon price and plan to increase it incrementally over the years in a way to attend their emission reduction objective. In our work, we aim to study the effect of such a carbon tax strategy on the strategic decisions of a SC. We consider a technology selection problem for a company facing a carbon tax legislation through a progressive and communicated strategy. We believe that due to changing social, economic and political circumstances, the carbon price is subject to uncertainty. Eventual alterations on the announced strategy may occur to adapt the carbon prices to changes and SC’s environment evolution. In our model, more than one scenario of the carbon tax implementation is considered. We contribute to the literature by developing a dynamic stochastic model of technology selection under a dynamic and uncertain carbon tax legislation using the scenario approach modeling technique. We solve this model through a numerical example derived from the textile industry and we assess the impact of the progressive carbon taxation strategy on strategic decisions of the company and its economic and environmental performances