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The purpose of this study is to evaluate the performance of mutual funds during the COVID-19 pandemic with environmental, social and governance (ESG) criteria. The main research question is whether mutual fund performance differs with respect to the level of the mutual fund’s ESG score.

The data set contains global fund data, and mutual fund performance is analyzed using two types of data envelopment analysis (DEA) models: the DEA portfolio index (DPEI) and the range direction measure (RDM) DEA. Propensity score matching and logistic regression are also applied.

The results reveal that: nonequity mutual funds present significantly higher performance compared to the performance of equity mutual funds; mutual funds with high ESG scores are associated with significantly higher performance compared to those with low to medium ESG scores; funds with high ESG scores experience higher performance irrespective of their type; and efficiency scores derived from the RDM DEA are significantly higher than those derived from the DPEI model.

Investors, fund managers and market participants can benefit from the findings of this study and improve their investment decision-making process, including more sustainable funds in their portfolios. Regulators and policymakers should further promote or even require the inclusion of more sustainable investments in the financial products offered by institutional investors. The main limitation of the study is related to data availability regarding the ESG score of mutual funds.

To the best of the authors’ knowledge, this is the first study that provides robust evidence in support of a positive association between ESG scores and mutual fund performance during the pandemic-induced crisis applying a DEA methodology.

The design of a biomass supply chain is a problem where multiple stakeholders with often conflicting objectives are involved. To accommodate the aspects stakeholder, the supply chain design should incorporate multiple objectives. In addition to the supply chain design, the management of energy from biomass is a demanding task, as the operation of production of biomass products needs to be aligned with the rest of the operations of the biomass supply chain. The purpose of the paper is to propose a mathematical framework for the optimal design of biomass supply chain.

An integrated mathematical framework that models biomass production, transportation and warehousing throughout the nodes of a biomass supply chain is presented. Owing to conflicting objectives, weights are imposed on each aspect, and a 0-1 weighted goal programming mixed-integer linear programming (WGP MILP) programming model is formulated and used for all possible weight representations under environmental, economic and social criteria.

The results of the study show that emphasis on the environmental aspect, expressed with high values in the environmental criterion, significantly reduces the level of CO₂ emissions derived from the transportation of biomass through the various nodes of the supply chain. Environmental and economic criteria seem to be moving in the same direction for high weight values in the corresponding aspect. From the results, social criterion seems to move to the opposite direction from environmental and economic criteria.

An integrated mathematical framework is presented modeling biomass production, transportation and warehousing. To the best of the authors’ knowledge, such a model that integrates multiple objectives with supply chain design has not yet been published.