ارزیابی کارایی تولید خرما به روش تحلیل پوششی داده های پنجره ای (مطالعه موردی: استان خوزستان)

استان خوزستان یکی از قطب­های اصلی تولید خرما در ایران است. تغییرات اقلیمی، افزایش دما، کاهش بارندگی، شور شدن تدریجی آب و خاک، تاثیرات منفی بسیاری بر روی عملکرد و کیفیت این محصول داشته است. به همین منظور، پژوهش حاضر به ارزیابی کارایی محصول خرما در استان خوزستان می­پردازد. از روش­های ارزیابی متداول، روش تحلیل پوششی داده­ها می­باشد. یکی از اشکالات روش تحلیل پوششی داده­ها در نظر نگرفتن عامل زمان در ارزیابی عملکرد است. در این راستا، روش تحلیل پوششی داده­های پنجره ای روشی است که امکان محاسبه کارایی در طول زمان را فراهم می­آورد. پژوهش حاضر، کارایی 8 تولید کننده خرما در استان خوزستان طی دوره زمانی 13961389 را با استفاده از روش تحلیل پوششی داده‌های پنجره­ای مورد ارزیابی قرار می­دهد. بدین منظور، داده­های مورد نیاز از دفتر طرح و برنامه جهاد کشاورزی تهیه شد که در برگیرنده اطلاعات مربوط به سطح اراضی، آب مصرفی، کود حیوانی، نیروی انسانی، کود شیمیایی، سموم آفات به عنوان متغیرهای ورودی   و عملکرد و سود ناخالص به عنوان متغیرهای خروجی می­باشد. نتایج پژوهش نشان داد هیچ کدام از تولید کننده­ها طی سال های 13911389 و 13961393دارای کارایی فنی کامل نبودند. در فاصله زمانی 13911389 کارایی تولید کننده­ها کم نوسان بوده و میانگین کارایی هر سال تولید کننده­ها در مقایسه با دوره زمانی 13961393، در سطح بسیار بالاتری قرار داشته است. بطوری‌که در فاصله زمانی 13911389، کمترین و بیشترین مقدار میانگین کارایی هر سال به ترتیب 820.0و973.0می­باشند. حال اینکه این مقادیر برای دوره زمانی 13961393 به ترتیب 610.0 و936.0 هستند. در سال 1392 دو تولید کننده در سطح کارایی فنی کامل قرار داشته اند.

Measuring the Efficiency of Date Crop by DEA (Data Envelopment Analysis) Window (Case Study: Khuzestan Province)

Introduction: Agriculture is the most important part of Iran economy. The agricultural sector always has an important role in supplying the essential elements of life and human wellbeing, so utilizing its capabilities is necessary to fulfill the development goals. Because of the growth population, the food supply is increasing and due to resource constraints, existing resources should be used efficiently to maximize possible production. Therefore, checking the efficiency of agricultural producers can be useful. Dates as one of the horticultural products due to its nutritional properties, and preservation of the environment have a special status in Iranian agriculture. Cultivating dates in Iran, especially in the southwestern regions (Abadan, Khoramshahr, Shadegan), date back to 6,000 years ago. According to the official statistics of the Food and Agriculture Organization (FAO) of United Nations, Iran has the world 's first position in terms of date’s cultivation. Iran is ranked in the second place after Egypt in terms of production and exports with 16.5% of the world 's exports. Khuzestan province with 37492 hectares of cultivation is one of the most important areas of production dates in the country. According to the official statistics, Khuzestan province by producing 15.2% of one million ton of country 's date has the highest production in the country. Unfortunately, in recent years, salinity of water and dust adversely affected the production and quality of dates in Khuzestan province. Evaluating the performance of this product in Khuzestan province due to its importance in terms of cultivation, production and employment is so significant for the economy of the country. The aim of this study is to determine the efficiency of 8 date’s producers in Khuzestan province during the agricultural period 20102017.;Materials  and Methods: Data Envelopment Analysis (DEA) is a management tool employed to estimate the efficiency of number of decision making units (DMU’s). DEA can be used to calculate the efficiency measures, and has a wide applicability in various service and industry sectors. The first model in DEA was presented in the CCR paper (after Charnes, Cooper and Rhodes1978) to produce the efficiency of DMUs under constant returns to scale (CRS) assumption. Subsequently, Banker et al. (1984) proposed a variable returns to scale version of the CCR model which was named BCC model. Since in real situations, variable returns to scale is more flexible so in this study BCC model is used. Suppose there is a set of n peer DMUs,  each using m inputs to produce s outputs and also assume  be the input and output vectors for DMUj, respectively, such that and . The inputoriented and outputoriented BCC models evaluate the efficiency of DMU0 by solving the following linear programs respectively:  ;  ;The choice of input or outputoriented models depends upon the production process characterizing the firm (i.e. minimize the use of inputs to produce a given level of output or maximize the level of output given levels of the inputs).  DEA window analysis is based on a dynamic perspective, regarding the same DMU in different period of time as entirely different DMUs. The benefit of this method is to describe the dynamic change of the efficiency of each DMU comprehensively, both horizontally and vertically. More importantly, the number of DMU is increased in this method; hence, it enhances the discriminating power by increasing the number of DMUs when a limited number of DMUs is available. Consider a set of DMUs in period of time. Every DMU has m kinds of input and s kinds of output. Let  denotes the level of input or output for DMU n in t period of time, then input vector and output vector will be presented as:Consider the window starts at the time point of, and the window width is, then input and output  matrix of each window will be presented as; The inputoriented BCC model of DEA window problem for is given by solving the following linear program:;Where .And the outputoriented BCC model is as follows:;Discussion of Results and Conclusion: Land area (ha); Water consumption (cubic meters); Animal manure (tons); Labor (persondays); Machinery (Hours); Fertilizer (kg) as well as pesticides (L) are used as indicators of inputs. Meanwhile, Performance (kg) and Gross profit (Rials) are regarded as two output indicators. Since beneficiaries have more control over the inputs than the outputs, the inputoriented DEA windows model is applied to evaluate the efficiencies of 8 date producers in Khozestan province during 20102017. By solving 144 models, the average performance of each window and the average annual provide a basis for measuring and comparing the performance of producers. Results showed that two producers were at full technical efficiency level in 2013, moreover none of the producers during 20102012 and 20142017 were full technically efficient. In period 20102012, efficiency of producers had small variation and the average annual efficiency of producers was much higher in comparison with period 20142017. Several factors cause the huge difference in performance over these two periods. Among these factors, one can mention dust in Khuzestan province, Dust particles reduce the harvest and the quality of the product. Another reason is the drought of the last two years. Reducing rivers water has made irreparable impacts on the agriculture of the region.