تحلیل موانع زنجیره عرضه زعفران در معیشت روستاییان شهرستان قاینات؛ کاربرد تکنیک تحلیل خاکستری (GRA) (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
زعفران یکی از اقلام مهم صادراتی ایران است که در سال های اخیر علی رغم افزایش سطح زیرکشت و تولید، میزان صادرات آن رشد چشمگیری نداشته است ایران به دلیل شرایط اقلیمی مناسب، عنوان بزرگترین تولید کننده و صادرکننده زعفران در دنیا است، اما نتوانسته از پتانسیل های خود بخوبی استفاده کند. در این راستا جهت شناسایی مشکلات موجود در تولید، در پژوهش حاضر واکاوی چالش های زنجیره عرضه زعفران در شهرستان قائن با استفاده از روش تحلیل خاکستری (GRA) انجام شده است. این مطالعه با روش پیمایشی و با استفاده از پرسشنامه و مصاحبه با 40 نفر از خبرگان و کارشناسان انجام شده است. نتایج نشان می دهد که محدودیت های زنجیره تأمین زعفران به ترتیب اولویت و رتبه بندی در منطقه عبارتند از چالش های گزینه توزیع کننده با وزن نهایی 68/0 در اولویت نسبت به سایر عوامل قرار دارد و عوامل تولید کننده، مشتری نهایی و تأمین کنندگان با وزن نهایی به ترتیب 63/0، 55/0 و 39/0 در اولویت های دوم تا چهارم قرار دارند. بنابراین پیشنهاد می گردد که سیاست های دولت در راستای برطرف نمودن مشکلات قیمت گذاری، نوآوری، بسته بندی، کیفیت مواد اولیه، بازاریابی و رقبا باشد.Analysis of Obstacles in the Supply Chain of Saffron in the Livelihood of Villagers in Qaynat County; Application of Gray Analysis Technique (GRA)
IntroductionThe production of saffron in Iran has a long history and its cultivation has been customary in the central plateau of Iran for a long time. Iran is currently the largest producer and exporter of saffron in the world, but it does not play a role in determining global prices and its consumption market. Although the relative profitability of saffron production has increased the area under cultivation and its production in recent years, but the increase in production costs and the stability of the domestic and international price of Iranian saffron, which is under the control of domestic and foreign intermediaries, practically discourage domestic producers. This commodity has lost its profitable trade.Agriculture is one of the most important and influential sectors in Iran's economy, which plays an important role and place in the political and economic independence of the country. One of the most important policies of the agricultural sector in order to develop it and rural development is to emphasize on strategic products suitable for the region and regional conditions. Because the cultivation of such products can not only provide a stable economy for farmers and villagers, but also create a special economic and political position for the country.Due to the significant development of saffron cultivation in the past decades in South Khorasan province and the weakness in managing the production and supply of saffron in this province in order to achieve the goals and answer the questions mentioned below, Qaynat County, which is the hub of saffron production in South Khorasan province. It will be studied as the selected city of this province. Therefore, the purpose of the current study is to analyze the challenges of the saffron supply chain in the livelihood of the villagers of Qaynat city using gray analysis method (GRA). MethodologyThe gray system is described by gray numbers, gray equations and gray matrices. Meanwhile, gray numbers are like atoms and cells of this system. Gray number is able to define a number with uncertainty. For example, the ranking of criteria in a decision-making process is presented as linguistic variables that can be expressed with numerical intervals, which will include uncertain information. One of the important advantages of the gray system theory is that it can produce good results for relatively small amounts of data with many variables, which are obtained by increasing the regularity between the data with an appropriate method and operation. Explaining the steps of using gray systems theory:First step: Determining the weight of the effective componentsThe second step: including the use of linguistic variables (such as very little, little, medium and very much) to specify the amount of components.Step 3: Create a gray decision matrixThe fourth step: determining the normalization of the gray decision matrixFifth step: creating the normalized weighted decision matrixThe sixth step: choosing the best optionThe seventh step: calculating the degree of gray possibilityEighth step: Ranking different options. FindingsIn this section, the approach of gray relational analysis has been used to determine the livelihood level of the households of the studied villagers in Qaynat city. After the relevant validity and reliability, a questionnaire was prepared and given to 40 agricultural Jihad experts in South Khorasan province and Qayinat city, and four options of final customer, producer, distributor and supplier were given according to 40 criteria. It has been scored and the final scores of the questionnaires have been presented. The final weight of the criteria of the quality of raw materials and agricultural inputs, wrong forecast, seasonality and the shortness of the agricultural product's life period and the change in the price of the product is superior to other criteria. Results and discussionBased on the results of gray analysis to investigate the obstacles of the saffron supply chain in Qayinat city, among the ranking of the criteria according to the challenges of the final customer, supplier, distributor and producer, the rank of the gray relationship is observed. It can be, the challenge of suppliers in the criteria of return of materials, the quality of raw materials, environmental problems and environmental factors (disease, environmental problems, etc.), the challenge of the producer in the quality criteria of raw materials and Product price change, the distributor's challenge in not being able to fulfill the demands (due to wrong forecasting, seasonality and short product life period) and the product price change and finally the final customer's challenge in the product inventory compared to other indicators. are superior. As can be seen, the distributor challenge option with a final weight of 0.68 is in priority over other factors, and the producer challenge factors, the final customer challenge, and the supplier challenge with a final weight of 0.63 respectively. 0.55 and 0.39 are in the second to fourth priorities.
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