Estimating the efficiency level of different tea farming systems in Rize Province Turkey

Abstract

The primary purpose of this study was to analyze the efficiency level of tea farms operated by owners and shareholders, and to explore the effect of different decisional, structural and management factors on efficiency. The data were collected from a stratified sample of 138 tea farmers operated in Rize province Turkey in 2017. The data envelopment analysis (DEA) program was used to estimate the efficiency scores. Tobit model was used to explore determinants of technical efficiency. Results disclosed that farmers can reduce their inputs use by 43% without compromising their yield level. However, they have low economic efficiency (0.41). Shareholder-operated farms were highly efficient (0.76) than the owner-operated farms. The factors such as old tea parcels, high land slope, and altitude were having a significant negative effect on farms’ efficiency. Applying fertilizer in the root zone or mixed with soil, terracing of farmland, and performing of soil test was positively and significantly contributing to efficiency. Generally, the efficiency of tea farmers is low, and mostly farm management and structure related factors were negatively affecting the farmer’s efficiency. The farmers should be aware of associated benefits with early replanting tea, fertilizer application in the root zone and terracing to control their production cost.

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

“…Focusing on data collection through personal interviews, a small part of them (12 papers) had a reference on how they collected their samples. More precisely, 4 referred to Random sampling technique formula (Raheli et al 2017 ; Ramezani et al 2022 ; Sherzod et al 2018 ; Sui et al 2022 ); another 4 to Cochran technique (Ashraf et al 2020 ; Esfahani et al 2017 ; Molinos-Senante et al 2016 ; Payandeh et al 2021 ); 2 to Yamane technique (Haq and Boz 2019 ; Ul Haq et al 2020 ); 1 to Stratified Sampling formula (Godoy-Durán et al 2017 ) and one to snowball sampling method (Mwambo et al 2021 ).…”

“…In other words, in many cases where only economic pillar was represented in a DEA methodological approach, authors embodied methodologies such as LCA (Beltrán-Esteve et al 2017 ; Gamboa et al 2020 ) or functions for the calculation of CO 2 emissions (Ashraf et al 2020 ; Basavalingaiah et al 2020 ; Ilahi et al 2019 ) or environmental cost benefit analysis (Mwambo et al 2020 ). Economic and social aspect increased as well, due to the fact that DEA outcomes were used as dependent variables in regression models such as Tobit (Haq and Boz 2019 ; Sherzod et al 2018 ) or truncated regression (Liu and Sun 2019 ; Martino et al 2016 ), to identify significant relations of socioeconomic variables to them. It is really positive the fact that the number of DEA papers contributing to all sustainability pillars increased from 13 to 24, representing almost 20% of the sample, thus the percentage remains low given the fact that examined papers have been retrieved through a structured search for sustainability in agriculture.…”

Composite effects of human, natural and social capitals on sustainable food-crop farming in Sub-Saharan Africa

“…Note that Nepal is a hilly region with rugged, mountainous areas lying between 900 to 3000m higher above the sea level (Grabowski, 1985), and coffee is cultivated at 800m altitude or higher (Poudel et al, 2017). In contrast, Haq and Boz (2019) showed that high land slope and high altitude have a significant and negative effect on farming efficiency. Similarly, Southavilay et al (2012) indicated that maize crops on low land (e.g., less than 360m) would be more efficient than on the high ground.…”

“…However, there is a handful of evidence on the impact of land elevation or altitude on farming efficiency. A few studies can be found in India (Ghosh et al, 2014), Turkey (Haq and Boz, 2019), and Laos (Southavilay et al, 2012). In their research, using the data in the area of the Ashti watershed of mid-hills of the northwest Himalayas regions from 2009 to 2011, the author indicated that the productivity of crops (e.g., wheat, maize, cowpea, soybean, and finger millet) are improved along with the increase in altitude from 600-1500m (Ghosh et al, 2014).…”

Analysis of Economic Efficiency and its Determinants in Millet Based Production Systems in the Derived Savanna Zone of Nigeria

“…More than ever, farmers will have to move closer to efficiency frontier: that is, produce determined output from a given combination of inputs or expend the lowest levels of inputs for a given level of output considering the rapid population growth and competing land use in Nigeria. Haq and Boz (2019) considered the efficiency level of diverse tea farming methods in Rize province, Turkey. DEA and Tobit models were used to appraise the efficiency grades and explore the determinants of technical efficiency (TE), respectively.…”