The purpose of this study is to disclose farmers' awareness of environmental responsibility in terms of eco-efficiency and cleaner production in the post-soviet bloc. Theoretical modeling and survey methods were applied. Original empirical data were collected in Lithuanian farms in 2017. The results demonstrate that the patterns of farmers' environmental responsibility are diverse when taking into account farm's characteristics (e.g., size, years in operation, type of farming) and demographic farmer's characteristics (e.g., age, gender, education). The major share of Lithuanian farmers stated eco-efficiency and cleaner production characteristics being important factors regarding purchasing decisions of farm equipment and machinery. These factors appeared along with other environmental responsibility characteristics. At the same time, research elucidated the gaps of Lithuanian farmers' environmental responsibility and accordingly relevant policy implications are proposed.
Vilkė R.; Gedminaitė-Raudonė Ž.; Baležentis T.; Štreimikienė D. 2020. Farmers' awareness of ecoefficiency and cleaner production as environmental responsibility: Lithuanian case.Corp Soc Responsiby Environ Manag. 2021; 28:288–298; https://doi.org/10.1002/csr.2049; [ABI/INFORM Collection (ProQuest); Agricultural & Environmental Science Database (ProQuest); BIOBASE: Current Awareness in Biological Sciences (Elsevier); Business Premium Collection (ProQuest); Current Contents: Social & Behavioral Sciences (Clarivate Analytics); Environment Index (EBSCO Publishing); GeoArchive (Geosystems); Geotitles (Geosystems); Health Management Database (ProQuest); Health Research Premium Collection (ProQuest); Hospital Premium Collection (ProQuest); INSPEC (IET); Materials Science & Engineering Database (ProQuest); NATCHA: Natural & Cultural Heritage Africa (NISC South Africa); Natural Science Collection (ProQuest); Proquest Business Collection (ProQuest); ProQuest Central (ProQuest); RePEc: Research Papers in Economics; SciTech Premium Collection (ProQuest); SCOPUS (Elsevier); Social Sciences Citation Index (Clarivate Analytics); Technology Collection (ProQuest); WATERLIT (NISC South Africa); Web of Science (Clarivate Analytics)].