Araştırma Makalesi
BibTex RIS Kaynak Göster

Risk Assessment Model in Turkish Agriculture with Multi Criteria Decision Making Analysis

Yıl 2019, Sayı: 17, 500 - 508, 31.12.2019
https://doi.org/10.31590/ejosat.613199

Öz

People have
learned and has been developing agriculture for years. The surrounding land has
become the best way to use as a result of years of observations. Over the
centuries, cities have grown significantly and observable changes in land usage
come up with the help of expanded and developing technology. Although Turkey
has a huge and suitable land for agriculture, agricultural activities are
gradually decreasing every year. The main reason why people of rural areas
migrate rapidly to the cities and why agricultural activities are decreasing
can be explained with the lack of adequate productivity in the production
layer; moreover, fertile soils are not used effectively. As a result of the low
level of productivity on agriculture, the production of agricultural products
does not meet domestic demand.

A significant amount of funding is planned for future
agriculture projects. Nevertheless, agricultural development in Turkey is
still facing major obstacles due to efficiency. Currently, significant inflation
rate increase in Turkey can be observed due to economical and geopolitical
events. One of the most important reasons for the serious increase in inflation
is the efficiency problems in agricultural items and activities. This study aims
to develop a detailed risk analysis model of the whole system to increase
productivity and efficiency with multi-criteria decision-making methods (MCDM).
The findings obtained are an analysis of in agricultural productivity in order
to make an improvement and it is important to be a preliminary study of the
steps to be taken for efficiency. At the end of the study proposed risk analysis model
aims to help all kinds of agricultural products to be planned and to be produced
with detailed scientific investigations

Kaynakça

  • Gul M and Guneri AF. (2016). A fuzzy multi-criteria risk assessment based on decision matrix technique: A case study for the aluminum industry. J Loss Prev Process Ind 40:89-100.
  • Miç, P. & Antmen, Z. F. (2019). A Healthcare Facility Location Selection Problem with Fuzzy TOPSIS Method for a Regional Hospital. Avrupa Bilim ve Teknoloji Dergisi, (16), 750-757.
  • Guneri AF, Gul M, and Ozgurler S. (2015). A fuzzy AHP methodology for selection of risk assessment.
  • Kılıçarslan, M. & Güçlü, A. (2019). İstanbul’da Bulunan Sağlık Bakanlığı Hastanelerinin Verimlilik Analizi. Avrupa Bilim ve Teknoloji Dergisi, (16), 552-558.
  • Gul M, Celik E, Aydin N, et al. (2016). A state of the art literature review of VIKOR and its fuzzy extensions on applications. Appl Soft Comput 46:60–89
  • Biswas, B., Lacey, J.R., Workman, J.P., and Siddoway, F.H. (1984). Profit Maximization as a Management Goal on Southeastern Montana Ranches. Western Journal of Agricultural Economics 9(1): 186-194.
  • Anvari, A., Zulkifli, N., & Arghish, O. (2013). Application of a modified VIKOR method for decision-making problems in lean tool selection. The International Journal of Advanced Manufacturing Technology, 71(5-8), 829–841.
  • Gul, M., & Ak, M. F. (2018). A comparative outline for quantifying risk ratings in occupational health and safety risk assessment. Journal of Cleaner Production, 196, 653-664.
  • “Faostat,” from http://www.fao.org/faostat/en/
  • Gul, M., Ak, M. F., & Guneri, A. F. (2016). Occupational health and safety risk assessment in hospitals: A case study using a two-stage fuzzy multi-criteria approach. Human and Ecological Risk Assessment: An International Journal, 23(2), 187–202.
  • “TUIK” from http://www.tuik.gov.tr/
  • Goker, N., Dursun, M., & Albayrak, Y. E. (2019). Agile Supplier Evaluation Using a Fuzzy Decision Making Procedure Based on Fuzzy Measure and Fuzzy Integral. Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making Advances in Intelligent Systems and Computing, 457–463.
  • Ksenija, M., Boris, D., Snezana, K., Sladjana, B. (2017). Analysis of the efficiency of insurance companies in Serbia using fuzzy AHP and TOPSIS methods. Economic Research 30(1), 550-565.
  • “OECD” from http://data.oecd.org/
  • Stavrou, D. I., Ventikos, N. P., & Siskos, Y. (2016). Locating Ship-to-Ship (STS) Transfer Operations via Multi-Criteria Decision Analysis (MCDA): A Case Study. Multiple Criteria Decision Making,137-163
  • Aragon_es-Beltr_an P, Mendoza-Roca JA, Bes-Pi_a A, et al. (2009). Application of multi-criteria decision analysis to jar-test results for chemicals selection in the physical-chemical treatment of textile wastewater. J Hazard Mater 164(1):288–95.
  • Ozdemir, Y., Basligil, H., & Ak, M. F. (2016). Airport Safety Risk Evaluation Based On Fuzzy Anp And Fuzzy Ahp. Uncertainty Modelling in Knowledge Engineering and Decision Making.
  • Ozdemir, Y., Basligil, H., & Ak, M. F. (2016). Airport Safety Risk Evaluation Based On Fuzzy Anp And Fuzzy Ahp. Uncertainty Modelling in Knowledge Engineering and Decision Making.
  • Zadeh, L. A. (1975). The Concept of a Linguistic Variable and its Application to Approximate Reasoning-I. Information sciences: 8: 199-249. Gul, M., & Ak, M. F. (2018). A comparative outline for quantifying risk ratings in occupational health and safety risk assessment. Journal of Cleaner Production, 196, 653-664.
  • Saaty TL. (1990). How to make a decision: The analytic hierarchy process. Eur J Oper Res 48(1):9–26 Tzeng GH and Huang JJ. 2011. Multiple Attribute Decision Making: Methods and Applications. CRC Press, Boca Raton, FL
  • Referans21 Yekta, T.S., Khazaei, M., Nabizadeh, R., Mahvi, A. H., Nasseri, S., Yari, A.R. (2015), Hierarchical distance-based fuzzy approach to evaluate urban water supply systems in a semi-arid region, Journal of Environmental Health Science and Engineering: 13(53): 1-12.
  • Kabir, G., & Sumi, R. S. (2012). Selection of Concrete Production Facility Location Integrating Fuzzy AHP with TOPSIS Method. International Journal of Productivity Management and Assessment Technologies, 1(1), 40–59.
  • Tzeng, G. H., & Huang, J.-J. (2011). Multiple attribute decision making: methods and applications. Boca Raton, FL: CRC Press.

Türk Tarımında Çok Kriterli Karar Verme Analizi ile Risk Değerlendirme Modeli

Yıl 2019, Sayı: 17, 500 - 508, 31.12.2019
https://doi.org/10.31590/ejosat.613199

Öz

İnsanlarca
yıllarca tarım öğrenildi ve geliştirilmeye devam etmektedir. İnsanları
çevreleyen yapılar yıllarca yapılan gözlemler sonucunda en iyi şekilde
kullanılmaya başlandı. Yüzyıllar boyunca, şehirler önemli ölçüde büyümüştür. Genişleyen
ve gelişen teknoloji sayesinde arazi kullanımında gözlenebilir değişiklikler
ortaya çıkmıştır. Türkiye'nin tarıma elverişli ve büyük alanları olmasına
rağmen, tarımsal faaliyetler her yıl giderek azalmaktadır. Kırsal alandaki
insanların şehirlere hızla göç etmelerinin ve tarımsal faaliyetlerin
azalmasının ana nedeni, üretim katmanında yeterli verim alınamaması ile
açıklanabilir; bunu yanı sıra, toprakların verimli kullanılmaması da buna sebep
teşkil etmektedir. Tarımda verim düşüklüğünün bir sonucu olarak da, tarımsal
ürünüretimi iç talebi karşılamayacak noktadadır.



Gelecek
yıllarda uygulanması planlanan tarım projeleri için önemli miktarda finansman ayrılması
hedeflenmektedir. Bununla birlikte, Türkiye'deki tarımsal gelişme, verimlilik
nedeniyle hala büyük sorunlarla karşı karşıya kalmaktadır. Günümüzde, ekonomik
ve jeopolitik olaylar nedeniyle, Türkiye'de önemli bir enflasyon artışı gözlemlenmektedir.
Enflasyondaki ciddi artışın en önemli sebeplerinden biri tarımsal ürün ve
faaliyetlerdeki verimlilik problemleridir. Bu çalışma, çok kriterli karar verme
yöntemleri (ÇKKV) ile üretkenlik ve verimliliği artırmak, tüm sistemin
ayrıntılı bir risk analiz modelini geliştirmeyi amaçlamaktadır. Elde edilen
bulgular, tarımsal verimliliğin artırılması ve iyileştirme amacıyla bir analiz
niteliğinde olup verimlilik için atılacak adımların ön incelemesi olması
noktasında önem arz etmektedir. Çalışmanın sonunda önerilen risk analiz modeli,
her türlü tarımsal ürünün planlanmasına ve detaylı bilimsel araştırmalarla
üretilmesine yardımcı olmayı amaçlamaktadır.

Kaynakça

  • Gul M and Guneri AF. (2016). A fuzzy multi-criteria risk assessment based on decision matrix technique: A case study for the aluminum industry. J Loss Prev Process Ind 40:89-100.
  • Miç, P. & Antmen, Z. F. (2019). A Healthcare Facility Location Selection Problem with Fuzzy TOPSIS Method for a Regional Hospital. Avrupa Bilim ve Teknoloji Dergisi, (16), 750-757.
  • Guneri AF, Gul M, and Ozgurler S. (2015). A fuzzy AHP methodology for selection of risk assessment.
  • Kılıçarslan, M. & Güçlü, A. (2019). İstanbul’da Bulunan Sağlık Bakanlığı Hastanelerinin Verimlilik Analizi. Avrupa Bilim ve Teknoloji Dergisi, (16), 552-558.
  • Gul M, Celik E, Aydin N, et al. (2016). A state of the art literature review of VIKOR and its fuzzy extensions on applications. Appl Soft Comput 46:60–89
  • Biswas, B., Lacey, J.R., Workman, J.P., and Siddoway, F.H. (1984). Profit Maximization as a Management Goal on Southeastern Montana Ranches. Western Journal of Agricultural Economics 9(1): 186-194.
  • Anvari, A., Zulkifli, N., & Arghish, O. (2013). Application of a modified VIKOR method for decision-making problems in lean tool selection. The International Journal of Advanced Manufacturing Technology, 71(5-8), 829–841.
  • Gul, M., & Ak, M. F. (2018). A comparative outline for quantifying risk ratings in occupational health and safety risk assessment. Journal of Cleaner Production, 196, 653-664.
  • “Faostat,” from http://www.fao.org/faostat/en/
  • Gul, M., Ak, M. F., & Guneri, A. F. (2016). Occupational health and safety risk assessment in hospitals: A case study using a two-stage fuzzy multi-criteria approach. Human and Ecological Risk Assessment: An International Journal, 23(2), 187–202.
  • “TUIK” from http://www.tuik.gov.tr/
  • Goker, N., Dursun, M., & Albayrak, Y. E. (2019). Agile Supplier Evaluation Using a Fuzzy Decision Making Procedure Based on Fuzzy Measure and Fuzzy Integral. Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making Advances in Intelligent Systems and Computing, 457–463.
  • Ksenija, M., Boris, D., Snezana, K., Sladjana, B. (2017). Analysis of the efficiency of insurance companies in Serbia using fuzzy AHP and TOPSIS methods. Economic Research 30(1), 550-565.
  • “OECD” from http://data.oecd.org/
  • Stavrou, D. I., Ventikos, N. P., & Siskos, Y. (2016). Locating Ship-to-Ship (STS) Transfer Operations via Multi-Criteria Decision Analysis (MCDA): A Case Study. Multiple Criteria Decision Making,137-163
  • Aragon_es-Beltr_an P, Mendoza-Roca JA, Bes-Pi_a A, et al. (2009). Application of multi-criteria decision analysis to jar-test results for chemicals selection in the physical-chemical treatment of textile wastewater. J Hazard Mater 164(1):288–95.
  • Ozdemir, Y., Basligil, H., & Ak, M. F. (2016). Airport Safety Risk Evaluation Based On Fuzzy Anp And Fuzzy Ahp. Uncertainty Modelling in Knowledge Engineering and Decision Making.
  • Ozdemir, Y., Basligil, H., & Ak, M. F. (2016). Airport Safety Risk Evaluation Based On Fuzzy Anp And Fuzzy Ahp. Uncertainty Modelling in Knowledge Engineering and Decision Making.
  • Zadeh, L. A. (1975). The Concept of a Linguistic Variable and its Application to Approximate Reasoning-I. Information sciences: 8: 199-249. Gul, M., & Ak, M. F. (2018). A comparative outline for quantifying risk ratings in occupational health and safety risk assessment. Journal of Cleaner Production, 196, 653-664.
  • Saaty TL. (1990). How to make a decision: The analytic hierarchy process. Eur J Oper Res 48(1):9–26 Tzeng GH and Huang JJ. 2011. Multiple Attribute Decision Making: Methods and Applications. CRC Press, Boca Raton, FL
  • Referans21 Yekta, T.S., Khazaei, M., Nabizadeh, R., Mahvi, A. H., Nasseri, S., Yari, A.R. (2015), Hierarchical distance-based fuzzy approach to evaluate urban water supply systems in a semi-arid region, Journal of Environmental Health Science and Engineering: 13(53): 1-12.
  • Kabir, G., & Sumi, R. S. (2012). Selection of Concrete Production Facility Location Integrating Fuzzy AHP with TOPSIS Method. International Journal of Productivity Management and Assessment Technologies, 1(1), 40–59.
  • Tzeng, G. H., & Huang, J.-J. (2011). Multiple attribute decision making: methods and applications. Boca Raton, FL: CRC Press.
Toplam 23 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Muhammet Fatih Ak 0000-0003-4342-296X

Yayımlanma Tarihi 31 Aralık 2019
Yayımlandığı Sayı Yıl 2019 Sayı: 17

Kaynak Göster

APA Ak, M. F. (2019). Risk Assessment Model in Turkish Agriculture with Multi Criteria Decision Making Analysis. Avrupa Bilim Ve Teknoloji Dergisi(17), 500-508. https://doi.org/10.31590/ejosat.613199