How ecoefficient is European food consumption? A frontier‐based multiregional input–output analysis

Abstract

This paper presents an integrated approach combining the optimization‐based frontier model with a global multiregional input–output (MRIO) analysis for food consumption in Europe. The weighted and conventional data envelopment analysis models are coupled with production and consumption‐based environmental and economic footprint data obtained from the environmental footprint explorer database. Eco‐efficiency assessment is carried out using multiple undesirable environmental outputs such as carbon emission, total energy consumption, land use, material use, water use, and one desirable economic output, which is the gross value‐added (GVA). This assessment indicates an efficiency level of each economic activity associated with its environmental impacts and policies are made as a result of the efficiency level to propose an equilibrium between economic development and environmental impacts. Finally, a sensitivity analysis of each parameter, variability analysis between weighted and non‐weighted models, and performance improvement projections are presented. Based on the results, four countries become efficient when moving from production‐based accounting (PBA) to consumption‐based accounting (CBA). France, United Kingdom, Italy, and Sweden are efficient countries in both findings. Denmark caused the highest carbon emission from the production point of view. Germany is the largest importer in all environmental categories such as carbon emission, energy usage, material use, land use, and water use. Additionally, the weight‐restricted model indicated a noticeable difference concerning the eco‐efficiency scores under the PBA and CBA approach, where land use and material footprint categories were found to be the most sensitive parameters for eco‐efficiency scores. The authors believe that this integrated approach will aid in decision‐making and help build a composite eco‐efficiency score when comparing the performance of food consumption with multiple environmental and economic metrics.

Analysis of Environmental Priorities for Green Project Investments Using an Integrated q-Rung Orthopair Fuzzy Modeling

“…Third, q-ROFSs are developed and score functions are calculated. Fourth, 𝑠𝑠 𝑗𝑗 , 𝑘𝑘 𝑗𝑗 , 𝑞𝑞 𝑗𝑗 ,and 𝑤𝑤 𝑗𝑗 values are computed by Equations ( 18)- (20). Within this scope, 𝑘𝑘 𝑗𝑗 indicates coefficient, 𝑠𝑠 𝑗𝑗 represents comparative importance rate, 𝑤𝑤 𝑗𝑗 states the weights and 𝑞𝑞 𝑗𝑗 identifies the recalculated weight.…”

“…Another important subject regarding the environmental prioritization for green project investment is carbon emission problem. The carbon emission is one of the most critical problems of today [20]. The carbon emissions cause an increase in the problem of global warming.…”

Estimating the dynamic environmental footprints of the global finance and business sector towards sustainable development goals

“…The single‐regional input–output (SRIO) analysis, well‐known econometric method, was developed by the Nobel prize winner Wassily Leontief in 1970 to capture the interdependencies between different economic sectors or industries within a nation (Leontief, 1970). However, the multi‐regional input–output (MRIO) analysis technique, based on SRIO analysis, can characterize economic flows between different economic sectors of various regions and provide a global multinational environmental and socioeconomic impact model that satisfies the final demand of a given region (Bulak & Kucukvar, 2022; Chen et al, 2021). The environmental‐extended multi‐regional input–output (EE‐MRIO) analysis, a typical top‐down approach, measures EF by incorporating trade networks between regional sectors and their associated environmental impacts (Dejuán et al, 2022; Fry et al, 2022; Hu et al, 2021; Mi et al, 2020; Xing et al, 2022; Xu et al, 2022; Yang et al, 2020).…”

“…The singleregional input-output (SRIO) analysis, well-known econometric method, was developed by the Nobel prize winner Wassily Leontief in 1970 to capture the interdependencies between different economic sectors or industries within a nation (Leontief, 1970). However, the multi-regional input-output (MRIO) analysis technique, based on SRIO analysis, can characterize economic flows between different economic sectors of various regions and provide a global multinational environmental and socioeconomic impact model that satisfies the final demand of a given region (Bulak & Kucukvar, 2022;Chen et al, 2021).…”

Potential Energy and Environmental Footprint Savings from Reducing Food Loss and Waste in Europe: A Scenario-Based Multiregional Input–Output Analysis

“…A growing body of research deploys environmentally extended multiregional input–output (EE MRIO) models with trade-linked national IO tables to assess the environmental footprints of food systems on national, regional and global scales . These models differentiate production-, consumption-, and trade-related environmental pressures of different food industries/products and food-related services throughout the country/regional global supply chains .…”