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Hotels are fundamental elements of tourism industry and provide various services for tourists. Moreover, hotels development has an important impact on tourism industry development. Therefore, an understanding of hotels relative efficiency performance, over a period of time, is important for practitioners, analysts, and policymakers alike. The main objective of this paper is to measure the efficiency of the four and five stars hotels in Tehran. A Data Envelopment Analysis (DEA) is employed to investigate the technical efficiency of eight hotels using the data over the period 1380 - 1384. DEA analysis is a methodology for analyzing the relative efficiency of units having the same multiple inputs and multiple outputs. In this study, the input variables comprise employee, rooms, restaurants and land and the output variables include hotel income and occupancy rate. The results show that technical and scale efficiency scores in all periods are relatively higher but there is no a regular trend over the period under study. Since 1380 to 1384; 75, 62.5, 75, 62.5, and 50 percent of the selected hotels were respectively efficient under the constant and variable to scale assumptions. Moreover, the findings confirm that more scale efficiency (0.997) refers to 1380 and less scale efficiency (0.894) refers to 1381 and 1382. The results also show that more technical efficiency, on average, under variable to scale assumption (0.964) refers to 1380 and less technical efficiency (0.894) refers to 1384. Finally, the efficiency of the five stars hotels is more than the four stars hotels implying the priority of the five stars hotel’s development in Tehran. Overall, the findings indicate that the particular problem is mismanagement in the Tehran’s hotels. Consequently, it caused the average scale efficiency to be more than the average technical efficiency. Since management plays a vital role in the efficiency improvement of hotels, this paper suggests the improvements of managerial systems in the hotels. More specifically, education, employment and Customer Reservation Systems (CRS) are the main factors influencing the efficiency.

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In the present study an attempt has been made to use a non-parametric method Data Envelopment Analysis (DEA) for assessing source-wise and operation-wise the Technical Efficiency (TE) and Return-to-Scale (RTS) for paddy production in four zones of the state of Punjab, India. The results were then compared to corresponding ones already obtained from a parametric method (Cobb-Douglas production function). The data from farmers growing rice in four zones including labor-h, machine-h, power source, horse power and hours used, kind of machinery used, physical inputs such as seed, fertilizers and pesticides (as inputs) and the yield (as output) were transformed into energy terms (MJ ha-1). The results revealed that farmers in zone 2 with a source-wise TE of 0.91, have consumed energy from more efficient sources, followed by zone 4 (0.90) and then zones 3 and 5 (0.85). No significant correlation could be established between the parametric and non-parametric TE for source-wise energy inputs. According to the DEA results, it was observed that 55.6% and 64.1% of inefficient farmers had an increasing RTS for operation-wise and source-wise energy inputs, respectively. However, a constant RTS had been reported by the parametric frontier function.

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Estimates of technical inefficiency in agricultural production are suspect so long as variations exist in production technology among the sampled farmers. Traditional methods of dealing with these technological differences risk attributing "technology gaps" to technical inefficiency between farms, pointing to the need to undertake a metafrontier analysis that allows technology gaps to be distinguished from technical inefficiency. Using farm-level data on the production of three different varieties of pistachio trees in Iran, we outline two criteria to justify its use: an inability in farmers to switch between production technologies except in the long term, and satisfaction of statistical tests on metafrontier coefficients. The application of metafrontier analysis enabled technical efficiency scores to be corrected for differences in production capacity imposed by tree variety. Results reveal that there is very little difference in technical efficiency between farms growing the different tree varieties. But they show that ignoring the production constraints imposed by variety choice could overstate the scope for farmers to improve their technical performance by adopting better farming practices. The results also indicate that it is misleading to compare the performance of different tree varieties on the basis of yield per hectare alone.

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Banks play substantial role in the national economy and its growth and prosperity. In this regard, recent researches have focused on performance evaluation of banks using “data envelopment analysis” (DEA). However, most of these studies has paid less attention to the selection of input and output variables. Obviously, the change in the variables set makes the efficiency scores and assessments of the decision-making units very different. Hence, in this paper, a logistic regression model is used in order to select the input and output variables. Applying this method indicates that the main variables of model are main source of financing as "input variable" and the bank facilities, resource absorption rate and number of bills as "output variables". These are of the greatest impact on forecasting of units efficiency (inefficiency). Then, we dealt with this set of variables to determine technical, allocative, and overall efficiency of 15 branches of Sepah Bank in Tehran during 2011. The results show that only 27 percent of units are 100% efficient, 20% of the units are 100% inefficient, 20% of units are allocatively inefficient and 34% of them are technically inefficient.

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Due to increasing concerns on environmental problems in current era, this study assesses the eco-efficiency of oil refineries. The oil refineries play essential role in the national economy in one hand, and cause environmental pollution due to high fossil fuel consumption and Co2 emissions in the other hand. Eco-efficiency is calculated using Windeap software, DEA output-oriented method, and inclusion of undesirable outputs. The results suggest that Bandar Abbas Oil Refining Company is the most efficient refinery over the 2003-2009, and growth rates of refineries eco-efficiency are positive. The results of Tobit regression show that fuel oil and gasoil have negative effects on the eco-efficiency, however natural gas, refinery gases, and liquefied petroleum gas (LPG) have positive effects on the eco-efficiency. On the other hand, if a refinery refines crude oil slightly more than nominal capacity rate, refinery eco-efficiency will be further decreased. 

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In the present study, an attempt has been made to use Data Envelopment Analysis (DEA) for assessing the technical efficiency and return-to-scale for greenhouse cucumber production in Iran. For this purpose, the data from greenhouses in Esfahan province, during one period of plant cultivation in one year including spring plants were randomly collected. The results indicated that total input energy, total output energy and energy ratio were 436,824 MJ ha^-1, 128,532 MJ ha^-1 and 0.29, respectively. DEA can be used to optimize the performance of any cucumber greenhouse. Based on input-oriented CRS and VRS models of DEA, the average values of pure technical efficiency, technical efficiency and scale efficiency were found to be 0.95, 0.83 and 0.88, respectively. Also the results revealed that, on average, about 30.27% of the total input energy could be saved without reducing the cucumber yield from its present level by adopting the recommendations based on the present study.

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This paper, based on the stochastic frontier approach (SFA), measures the technical efficiency (TE) of Iranian manufacturing industries under the estimation of Translog production function used by the maximum likelihood technique. The findings indicated that out of 140 evaluated industries in this study, 5 industries including the refined primary copper products, cleaning and grading, packing pistachios, manufacture of motor vehicles, manufacture of plastics in primary forms and  manufacture of plastics in primary forms, and of synthetic rubber have had the highest efficiency in 2009. The results also demonstrated that 4 industries; manufacture of food and beverages,  manufacture of tobacco, manufacture of plastic except the footwear, and finally, Manufacture of lifting and handling equipment have experienced the greatest change for efficiency during the period 1995-2009 among the industries.    

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Ratoon Rice (RR) has been proposed to be an effective alternative rice system to increase productivity growth and reduce the environmental impact, but data on the economic performance of RR for farmers are limited. A survey of paddy farms was conducted to assess the impact of the adoption of RR in Hubei, China. Endogenous switching regression framework was used to account for observed and unobserved heterogeneity. We analyzed the effect of yield, income, and technical efficiency of RR adoption. Results show that adoption of RR has great impact on yield, income, and technical efficiency. Increase in rice yield (by 5.12%) and rice income (3.74%) was found for RR farmers; increases of yield, income and technical efficiency was also significant if farmers cultivating single rice shifted to RR. Technical efficiency showed a large difference when RR was adopted by farmers cultivating single rice. Small farms and large farms benefit from the adoption of RR. Large farms benefit more yield and income than small farmer, while small farms are more efficient than large farms. Our findings provide meaningful and timely implications for future national programs and policies to promote the implementation of RR in China that aim to promote more sustainable practices and lower environmental impact in agriculture.

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The sugar industry has many backward and forward linkages in the supply chain. In this industry, a chain of agricultural, industrial, oil, transportation, and commerce sectors is engaged to transform raw materials into product and shipping it to consumers. In this research, the efficiency of decision-making units in Iran's sugar supply chain is evaluated using network and simple Data Envelopment Analysis methods. Results of the first level of decentralized sugar supply chain in Iran (extraction of sugar from sugar beets) indicate that the average technical efficiency in terms of a constant return to scale and the allocation, economic, and scale efficiency are not at appropriate levels. In the second level of supply chain, weakness was observed in allocative and economic efficiency. The results showed that the Provinces of West Azerbaijan and Khorasan-e Razavi offer desirable conditions for sugar beet production in terms of efficiency. Supply chain management has been used as a tool for timely delivery of the product to market at a lower cost to increase the efficiency of the entire sugar supply chain. A move toward vertical integration in sugar production is also proposed to benefit integration.

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The purposes of the study were: (i) To comparatively estimate the economic performance and productive efficiency of owner and sharecroppers in Kaş District of Antalya Province in Turkey, (ii) To find out the factors affecting the profitability of owner operators and sharecroppers, and (iii) To formulate the policy options in the light of findings. Research data were collected from randomly selected 58 owner operators and 45 sharecroppers by using questionnaire. Cluster analysis was performed to select similar sharecropper and owner operator in terms of farmers’ profile, farm income, and land size. Data envelopment analysis (DEA) was used to estimate the efficiency measures. Research result showed that labor cost of sample farm had largest share in total farm expenses. The tomato and pepper yield of sharecroppers were higher than that of owners. Net farm income of owner operator and sharecroppers per hectare were $44518.3 and $51248.8, respectively. The mean technical, allocative and economic efficiency of owner operators were 0.724, 0.729 and 0.528, respectively, while that of sharecroppers was 0.851, 0.598 and 0.509, respectively. Sharecroppers had higher technical efficiency score compared to owners, but reverse was the case for allocative and cost efficiency scores. According to the research findings, farmers can increase their technical competence, if both owner operator and sharecropper improved their skills by participating in training and extension programs. Implementing performance-based earning systems may accelerate improving farmers’ technical capability. Reorganizing of farm and controlling marketing cost may also be beneficial for increasing economic efficiency in the research area.

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Agricultural production is very important in terms of both energy production and consumption. The main purpose of this study was to calculate the energy values, productivity, and energy efficiency of inputs used in sunflower production in Konya. The sample volume was calculated as 51 by using the Neyman Method of the Stratified Random Sampling Method. In the energy balance analysis of enterprises, the energy equations of all outputs and inputs used in sunflower production were acquired by multiplying with conversion coefficients. Energy output and input equations were calculated for unit sunflower production (MJ kg^-1). In conclusion, it was ascertained that 25.26% of the total energy input per hectare comprised direct energy and 74.74% consisted of indirect energy. Energy use efficiency in the research area was 4.94, while the specific energy value was 5.06 MJ kg^-1. In other words, 5.06 MJ kg^-1 of energy was consumed for 1 kg of sunflower production. The price of 1 kg of sunflower is USD 0.60. The average Technical Efficiency (TE) of the enterprises in the research area was 0.874, and 29.41% of the enterprises producing sunflowers were efficient in energy use per production, whereas 70.58% were less efficient enterprises. Saving energy in sunflower production will have a positive economic impact on the business.

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The purpose of this research was to investigate whether the European Union's high amounts of construction and technology grants provided to dairy farms under The Instrument for Pre-accession Assistance for Rural Development (IPARD) program make a real contribution in terms of energy use and efficiency. The primary data of the study were obtained from Dairy Farms Supported (SDF) and Non-Supported (NSDF) by the IPARD program by using a questionnaire filled during the face-to-face interviews. The full count method was used to determine the 50 SDF while the Neyman allocation sampling method was used to determine the 100 NSDF. Energy indicators were used to evaluate the efficiency of input energy transformation into output and data envelopment analysis was used to calculate technical efficiency and pure technical efficiency. Unlike other studies in the literature, we analyzed energy efficiency of dairy farms in terms of the contribution of the EU supports. The results showed that SDF were more energy-efficient dairy farms with much better energy indicators and efficiency scores than NSDF. Productivity, benefit/cost ratios, and energy scores clearly show that EU grants given to dairy farms contribute to the efficient use of resources, including energy, increasing the competitiveness of dairy farms, and contributing to the rural area through energy efficiency and economic performance.

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Participatory Irrigation Management (PIM) has emerged as a significant intervention in which farmers are given more control over irrigation management. The primary goal of this study was to identify the factors that influence farmers' participation in PIM activities and compare the economic viability of participation levels. A multi-stage random sampling technique was used to collect the data from 240 farmers of Nasrana and Maduana distributaries located at the tail end of the Lower Chenab Canal (LCC) west circle in district Faisalabad, Punjab, Pakistan, using a structured questionnaire. The factors influencing farmers' participation in PIM activities were identified using an ordered Probit Regression model. The findings revealed that education level (β= 0.12; P=0.00), village leadership (β= 0.97; P= 0.00), and being a beneficiary of a water user association (β=1.20; P= 0.00) all had a significant positive influence on farmers' participation in PIM activities. On the other hand, family size (β= -0.05 P= 0.04), land ownership (β= -0.44; P= 0.05), and off-farm income (β= -0.52; P= 0.01) were found to have a significant negative impact on farmers' participation. Farmers with a high level of participation had higher farm technical efficiency and crop productivity. For these reasons, farming communities must be encouraged to participate in PIM activities in order to achieve a sustainable irrigation system.

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The purpose of this work was to analyse the energy productivity and efficiency of agricultural enterprises growing poppy. The number of enterprises investigated in the study was determined from a stratified random sample of 87, the data is from 2019, and the study was conducted in Turkey. All inputs and outputs used in poppy production were obtained by multiplying energy equations with conversion coefficients in determining the energy use of the enterprises. Data Envelopment Analysis (DEA) method was employed to calculate the technical, pure-technical, and scale efficiency of poppy-producing enterprises. Poppy energy inputs consisted of the use of human labour, machinery, fertilizer, pesticides, seeds, water, and fuel. The poppy capsule yield per unit area was regarded as the energy output. In the end, 40.23% of the total energy input in poppy production consisted of direct and 59.77% indirect energy. Non-renewable energy consumption (88.70%) was found to be rather high in the research area. Therefore, the use of chemical fertilizers and fuels, which are non-renewable energy sources, must be lessened for poppy plant production. The energy efficiency was found to be 0.08 in poppy production. According to this result, the production systems of the enterprises producing poppy are sufficient and energy is used efficiently. The specific energy value in the enterprises was calculated as 11.95 MJ kg^-1 and the Technical Efficiency (TE) was calculated as 0.683. Producers produce at the same level with 68.3% of their capital, and 31.7 % saving.

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A survey was conducted to assess the technical and allocative efficiency of tomato (Solanum lycopersicum L.) production under the plastic house in metropolitan city of Pokhara, Nepal. From the total tomato growers, 80 farmers were selected through multistage sampling. Stochastic frontier approach is applied to the obtained survey data and analyzed to study the technical and allocative efficiency of tomato production. This research is essential for enhancing tomato yields without incurring additional input expenses. Our results find the mean technical efficiency of 78.19%, which shows the great opportunity of improvement of tomato production in Pokhara. Technical efficiency is positively influenced by education level and training availability and negatively affected by farmers' ages. Subsidy has non-significant effect on technical efficiency in the study area. The allocative efficiency ratio of plastic house area, seed, and di-ammonium phosphate shows its underutilization with a score above 1. On the contrary, farmyard manure, urea and muriate of potash application are overutilized with a score of less than 1. The efficiency in tomato production can be improved by optimal allocation of resources, encouraging young farmers in farming, increasing access to education and training to farmers, and change in current subsidy mechanism. Through corrective measures, policies, and practices, an efficient frontier could be achieved by the tomato-growing farmers of the study area, which ultimately will maximize profit without necessarily increasing input level.

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This study aimed to determine the efficiency levels of beef cattle farms in Izmir Province and identify the factors that affect their efficiency by means of Bootstrap Data Envelopment Analysis (BDEA). The study covers 62 farms engaged in beef cattle farming in five different districts of Izmir. The BDEA for beef cattle farming provided the result that the analysis should be conducted with the Constant Return to Scale (CRS) assumption. The average corrected input-oriented CRS efficiency after bootstrapping was found to be 0.90. According to the results of truncated regression analysis, a positive relationship was found between adjusted input-oriented efficiency scores and the number of fattening periods per year. On the other hand, it was determined that union membership had a statistically significant negative effect on efficiency. In addition, big farms had lower efficiency than smaller farms, farms in Buca District had lower efficiency than those in Odemis District, and those who fatten old cattle had lower efficiency than those who fatten young cattle. As a result, farms that fatten cattle for shorter periods of time, farms that do not increase the number of animals much, and farms that fatten young cattle achieve higher output per unit of input used, indicating higher technical efficiency.