Green productivity and undesirable outputs in agriculture: a systematic review of DEA approach and policy recommendations

Abstract

Measuring efficiency in the presence of undesirable outputs could be difficult depending on how to treat these outputs; thus, undesirable outputs modelling has been an exciting subject of several studies in the Data envelopment analysis (DEA) literature in the last two decades. The present study aims to illustrate a thorough overlook of studies in which DEA has applied for measuring efficiency with undesirable outputs. Fifty-eight articles were published from 2000 to 2020 have been systematically reviewed through PRISMA protocol. The results indicated that "Journal of Cleaner Production" ranked first with six published articles, and Chinese scholars have the most contributions to this field, with twenty-third articles. Also, almost a quarter of the published articles' scope was related to agricultural pollution, and thirteen articles were published in 2016, the highest number of published articles annually. Taken together, the theoretical and empirical implications of research in the field of Green Productivity are discussed, and some policies were recommended.

A systematic literature review of data envelopment analysis implementation in agriculture under the prism of sustainability

“…Literature review shows that most researchers use CO 2 or GHG emissions to align their papers with the global effort for GHG emissions reduction. These outcomes are in accordance with Streimikis and Saraji’s ( 2021 ) review results. However, there is an increasing need for creating circular flows to eliminate the wasted energy, supporting this transition by an appropriate policy framework (Guo et al 2021 ).…”

“…Considering the idiosyncrasies of the agricultural sector, due to the interaction of multiple factors such as biotic and abiotic environment, cultivation protocols, and applied agricultural practices, including the incorporation of sustainability principles, a literature review of 120 papers was conducted, considering the year after SDGs’ release as a reference point for further promoting sustainability principles in the agricultural operational research society. Although Streimikis and Saraji ( 2021 ) have recently published a literature review for DEA in agriculture, focusing on the research gaps and main conclusions of each survey of undesirable outputs, the present review aims to contribute on the following questions:…”

Monitoring the Performance of Agricultural and Food Sector Companies Using Dea

“…Some challenges leading to inefficiencies and low productivity in the agriculture sector include high product costs, farm mismanagement, and sub-optimal production. An additional study complemented Otieno's findings regarding the inefficiencies in the agriculture sector Streimikis & Saraji (2021). pointed out that measuring efficiency in agriculture and food production is difficult, especially when the measurement is done in the presence of undesirable outcomes.…”

Input and output reconsidered in supplier selection DEA model

“…DEA is a well-known method to determine the relative efficiencies of a set of decision making units (DMUs) It is widely used to compare the efficiency of banks (Henriques et al 2020), healthcare (Sommersguter-Reichmann 2021), in education (Mojahedian et al 2020), in agriculture (Streimikis and Saraji 2021), in transportation (Mahmoudi et al 2020), in supply chain management (Soheilirad et al 2018) and in supplier selection (Dutta et al 2021, Vörösmarty andDobos 2020).…”