Economics of technical efficiency in white honey production: Using stochastic frontier production function

Alropy, Eman T.; Desouki, Noha E.; Alnafissa, Mohamad

doi:10.1016/j.sjbs.2019.09.029

Cited by 15 publications

(9 citation statements)

References 11 publications

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“…Efficiency can be achieved by maximising honey production and minimising the cost of inputs. There is a paucity of research on the economic efficiency of honey bee farming in the world (Alropy et al, 2019;Ritten et al, 2018), and none on the economic efficiency of honey bee or stingless beekeeping in Malaysia. Hence, the purpose of this research is to evaluate the performance of commercial stingless beekeepers in Peninsular Malaysia via an economic efficiency assessment, and thence to identify the underlying factors in farm management responsible for any shortcomings.…”

Section: Introductionmentioning

confidence: 99%

Economic Efficiency of Stingless Bee Farms in Peninsular Malaysia Estimated by Data Envelopment Analysis (DEA)

Soh¹,

Samsuddin²,

Ismail³

2021

JSSH

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The commercial stingless beekeeping industry has good economic growth potential in Malaysia, which is a tropical country rich in flora that serves as food sources for stingless bees. Local consumption of honey is increasing and its production locally can be raised to meet the demand by sustainable stingless beekeeping. An important indicator that measures the success of the industry is the economic efficiency of the farm. This study hence examined the cost efficiency (CE), technical efficiency (TE), and allocative efficiency (AE) of commercial stingless beekeeping farms in the East Coast and Northern regions of Peninsular Malaysia using Cost Data Envelopment Analysis (DEA) under the assumption of Constant Return to Scale (CRS). Interviews with 47 respondents in the East Coast region and 28 respondents in the Northern region showed that the average CE scores for the two regions were 0.291 and 0.172, respectively. TE for the East Coast region and Northern region were 0.656 and 0.385 while mean AE scores of 0.445 and 0.404 were obtained. Factors that influenced the efficiency of the farms included farmers’ years of schooling and extension officer visits. In conclusion, CE, TE, and AE of commercial stingless bee honey production in Peninsular Malaysia were fairly low, and the determinants responsible for this low efficiency is of concern. Economic efficiency in stingless beekeeping needs to be further elevated to optimise productivity.

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Section: Introductionmentioning

confidence: 99%

Economic Efficiency of Stingless Bee Farms in Peninsular Malaysia Estimated by Data Envelopment Analysis (DEA)

Soh¹,

Samsuddin²,

Ismail³

2021

JSSH

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“…We need to multiply marginal productivity by the output market price to obtain the monetary value of non‐marketed input (Grammatikopoulou et al, 2019). The general form of production function is defined as follows:

Y = f ((),, X_{j}, β) + ɛ_{i},

where Y is the production amount of the agriculture commodity, X j is use of production input j , β is function parameters and ɛ i is coefficient of random error (Alropy et al, 2019). There are 20 functional forms of Leontief, Linear, Quadratic, Cubic, Generalized Leontief, Square root, Logarithmic, Mitscherlich, Spillman, Cobb‐Douglas, Generalized Cobb‐Douglas, Trascendental, Resistance, Modified Resistance, CES, Translog, Generalized Quadratic, Generalized Power, Generalized Box‐Cox and Augmented Fourier.…”

Section: Methodsmentioning

confidence: 99%

A comparison of Zayandehrood River water values for agriculture and the environment

Karami

Yazdani

Saleh

et al. 2020

River Research & Apps

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River water management is challenging not only since they are open systems with changing physical structures, but also because the water values are mostly unknown over varied sectors. If policymakers grasp water values, water management will be more efficient. This research intends to examine the values of water in agriculture, which receives the most substantial portion of water resources, with the values of water in the environment in Isfahan located in the Zayandehrood River basin of Iran. The consequences of contingent valuation and production function methods revealed that per cubic metre value of water is 13 times higher in the environment than agriculture. The government should reconsider the higher value of the environment despite it is a non‐market value. The contingent valuation model additionally proved that women exhibited 21% more willingness to pay than men in order to protect the environment; however, they are paid less by 36%.

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“…In the future, we believe Ethiopia's honey industry will be a sustainable source of income, helping families escape poverty and promoting ecosystem balance and land restoration for the beneft of present and future generations [9]. Average total, net return, and return on investment all increase with increased production capacity [10]. Agro-chemical poisoning, a shortage of bee food, a lack of rainfall, pests and predators, absconding, and a lack of honey storage facilities were other factors that restricted the latent potential of beekeeping [11].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Determinants of Economic Efficiency in Honey Production in Horo Guduru Zone, Ethiopia: Stochastic Dual Cost Frontier Model Approach

Tesema

Adugna

2023

Advances in Agriculture

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Honey production is generating employment and source of income in the rural area of Ethiopia. However, its productivity was low. The objective of this study was to measure the economic efficiency of honey production in Ethiopia’s Horo Guduru Wollega Zone and their limiting factors. To achieve the above-mentioned objective, the study employed a survey methodology using a structured questionnaire tool, and the data were collected from 396 households. Both descriptive and econometric data analysis methods are employed. Dual cost was used to measure the levels of economic efficiency and the Tobit model to identify the determinants of economic efficiency in the study area. In this regard, the analysis relied on a cross-sectional data collected from 396 sample farm households. The mean economic efficiency was 44%. This demonstrates that the farmers in the study area have to decrease production cost by 56% to achieve 100% economic efficiency level. From the determinants of economic efficiency family size, extension services, training, beekeeping experience, and family size are significant technical efficiency variables for honey producers. The study suggests policies to address economic inefficiencies by increasing the number of hives, extending the best performers’ experience by increasing the frequency of extension contacts on honey production, facilitating and expanding credit service in the study area, making bee forage access simple, and increasing forest coverage on the land area in line with the current policy of Ethiopia. Additionally, since farmers in the study area spend their time guarding the honey from damage by ants and monkeys, labor that utilizes technology must be made available in the study area.

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Economics of technical efficiency in white honey production: Using stochastic frontier production function

Cited by 15 publications

References 11 publications

Economic Efficiency of Stingless Bee Farms in Peninsular Malaysia Estimated by Data Envelopment Analysis (DEA)

Economic Efficiency of Stingless Bee Farms in Peninsular Malaysia Estimated by Data Envelopment Analysis (DEA)

A comparison of Zayandehrood River water values for agriculture and the environment

Analysis of Determinants of Economic Efficiency in Honey Production in Horo Guduru Zone, Ethiopia: Stochastic Dual Cost Frontier Model Approach

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