Determination of Economic Efficiency of Agricultural Enterprises in Turkey: A Dea Approach

Erdoğan, Güneş; Güldal, Hüseyin Tayyar

doi:10.30682/nm1904h

Cited by 9 publications

(9 citation statements)

References 21 publications

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“…They found that the efficiency of their production was low. The results obtained by Raheli et al [2] during their research applying the DEA method show that there were significant differences between efficient and inefficient farmers in the studied area. The main differences were in the use of chemical fertilizers, biocides and water for irrigation, i.e., better use of them would probably increase efficiency in the long term.…”

Section: Literature Reviewmentioning

confidence: 81%

Application of novel DEA-SWARA-WASPAS model for efficiency assessment of agricultural products

Zavadskas¹,

Đalić²,

Stević³

2021

JSEGC

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Aim:The aim of the research was to create an original model for assessing the efficiency of production lines for five agricultural products. The purpose was to determine, based on the developed model, which production lines are efficient and which are not efficient.Methods: An original integrated model was created that includes the Data Envelopment Analysis (DEA), Stepwise Weight Assessment Ratio Analysis (SWARA) and Weighted Aggregates Sum Product Assessment (WASPAS) methods. DEA was applied as a linear programming model to determine the efficiency of five agricultural products based on eight inputs and one output. After that, SWARA was applied to determine the weight values of criteria, and WASPAS was applied to the final ranking of alternatives. Results:The results show that 2 of the 5 production lines were not efficient, and they were further eliminated from the model. To determine the final ranking of production lines for other agricultural products, the SWARA-WASPAS model was implemented. The final results show that Alternative A2 (corn) is ranked as first, i.e., the most significant (0.933). Alternative A5 (seeds) is ranked second in terms of significance (0.874), while Alternative A1 (wheat) (0.769) is in third position.

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Section: Literature Reviewmentioning

confidence: 81%

Application of novel DEA-SWARA-WASPAS model for efficiency assessment of agricultural products

Zavadskas¹,

Đalić²,

Stević³

2021

JSEGC

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“…DEA-based models have primarily been used for efficiency evaluation methods [15]- [17]. They are more inclusive of both input and output indicators and can simultaneously evaluate the efficiency of decision-making units (DMUs) with multiple inputs and outputs.…”

Section: B Buildup Of Modelsmentioning

confidence: 99%

A Nonradial Super Efficiency DEA Framework Using a MCDM to Measure the Research Efficiency of Disciplines at Chinese Universities

Ding-xin

et al. 2020

IEEE Access

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Evaluating the efficiency of scientific research plays an important role in accelerating technological innovation and optimizing the allocation of research resources. Most studies have focused on measuring research efficiency from a macro perspective, ignoring differences within disciplines. Furthermore, existing methods have failed to discriminate between evaluation results and the fact that research has variable returns to scale. To address this, in this paper we propose a multiple-criteria decision-making (MCDM) nonradial super efficiency data envelopment analysis (NRSDEA) model, which uses an outputoriented nonradial SDEA method to manage nonsolution problems and integer decision variable constraints. In addition, we used a Malmquist index to decompose the productivity changes of statistics discipline's research efficiency at different universities in China. Finally, we verified the rationality and effectiveness of the proposed method. INDEX TERMS Discipline research efficiency, multiple-criteria decision-making, nonradial SDEA, Malmquist index.

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“…While scholars have investigated TIE at the firm level, such as new energy vehicle enterprises (Fang et al, 2020), lithium‐ion battery listed enterprises (Zhong et al, 2022), or renewable energy enterprises (Shen et al, 2022), they paid little attention to TIE of agribusiness firms. In addition, although recent literature on agribusiness firms discusses economic efficiency (Aydin & Unakitan, 2018; Gunes & Guldal, 2019), nontechnological innovations (Fuentes & Soto, 2015), and total factor productivity (Nilsson, 2017), we are not aware of any empirical studies on agribusiness management that examine the impact of AD on TIE. Therefore, this merits further attention and investigation.…”

Section: Introductionmentioning

confidence: 99%

Agribusiness diversification and technological innovation efficiency: A U‐shaped relationship

Zhang

Sun

et al. 2022

Agribusiness

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In recent years, agribusiness firms have increasingly diversified their product portfolio and expanded into new business areas through internal growth or acquisition, which can lead to the reallocation of innovation resources. This study examines the impact of agribusiness diversification (AD) on technological innovation efficiency (TIE) in China. Based on an 8‐year longitudinal dataset of 101 Chinese listed agribusiness firms from 2012 to 2019, this study applies the Tobit regression technique to reveal the underlying mechanism between AD and TIE. The empirical results show that: (1) the AD‐TIE relationship follows a U‐shaped pattern, that is, at low levels of AD, the AD‐TIE relationship is negative; at high levels of AD, the AD‐TIE relationship is positive. (2) government subsidies (GS) negatively moderate the U‐shaped relationship between AD and TIE, such that GS flattens the U‐shaped curve. Our findings have important implications for agribusiness managers and public policymakers. [EconLit citations: H25, L25, Q16].

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Determination of Economic Efficiency of Agricultural Enterprises in Turkey: A Dea Approach

Cited by 9 publications

References 21 publications

Application of novel DEA-SWARA-WASPAS model for efficiency assessment of agricultural products

Application of novel DEA-SWARA-WASPAS model for efficiency assessment of agricultural products

A Nonradial Super Efficiency DEA Framework Using a MCDM to Measure the Research Efficiency of Disciplines at Chinese Universities

Agribusiness diversification and technological innovation efficiency: A U‐shaped relationship

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