Miroslav Nedeljković

Dr. Miroslav Nedeljković


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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20 January 2022 in Agriculture
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Journal Article
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Adis PuškaAdis Puška
Adis Puška
Miroslav NedeljkovićMiroslav Nedeljković
Miroslav Nedeljković
Radivoj Vasilj ProdanovićRadivoj Vasilj Prodanović
Radivoj Vasilj Prodanović
RVRadovan Vladisavljević
Radovan Vladisavljević
RSRadmila Suzić
Radmila Suzić
The research deals with the market assessment of pear varieties in Serbia. Market assessment represents the willingness of customers to consume a certain fruit or a certain variety. This research applies a market assessment of pear varieties based on expert decision making. Together with the experts, the criteria and varieties of pears used in the research are determined. Ten criteria and six varieties of pears that are mostly grown in Serbia are used. Experts evaluated pear varieties based on linguistic values according to selected criteria. Based on these values, and using fuzzy logic, the weights of the criteria are first determined using the fuzzy CRITIC method (criteria importance through intercriteria correlation), and pear varieties are ranked using the fuzzy CRADIS method (compromise ranking of alternatives from distance to ideal solution). The obtained results show that the highest rated varieties are Konferans and Viljamovka, while the lowest rated variety is Šampionka. Sensitivity analysis confirms these results. The obtained results will help cultivators and fruit vendors to choose those varieties that will achieve the best market results. This study is conducted to provide guidelines for the use of fuzzy methods in marketing assessment in fruit growing.

29 April 2021 in Symmetry
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Journal Article
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Adis PuškaAdis Puška
Adis Puška
Miroslav NedeljkovićMiroslav Nedeljković
Miroslav Nedeljković
Sarfaraz Hashemkhani ZolfaniSarfaraz Hashemkhani Zolfani
Sarfaraz Hashemkhani Zolfani
Dragan PamucarDragan Pamucar
Dragan Pamucar
The selection of sustainable suppliers (SSS) is the first step in applying a sustainable supply chain and sustainable production. Therefore, it is necessary to select the supplier that best meets the set sustainability criteria. However, the selection of suppliers cannot be done by applying symmetric information, because the company does not have complete information, so asymmetric information should be used when selecting suppliers. Since the SSS applies three main sustainability criteria, environmental, social, and economic criteria, this decision-making problem is solved by applying multi-criteria decision-making (MCDM). In order to solve the SSS for the needs of agricultural production, interval fuzzy logic was applied in this research, and six suppliers with whom agricultural pharmacies in Semberija work were taken into consideration. The application of interval fuzzy logic was performed using the methods PIPRECIA (Pivot pairwise relative criteria importance assessment) and MABAC (Multi-Attributive Border Approximation Area Comparison). Using the PIPRECIA method, the weights of criteria and sub-criteria were determined. Results of this method showed that the most significant are economic criteria, followed by the social criteria. The ecological criteria are the least important. The supplier ranking was performed using the MABAC method. The results showed that supplier A4 best meets the sustainability criteria, while supplier A6 is the worst. These results were confirmed using other MCDM methods, followed by the sensitivity analysis. According to the attained results, agricultural producers from Semberija should buy the most products from suppliers A4, in order to better apply sustainability in production. This paper showed how to decision make when there is asymmetric information about suppliers.

29 January 2022 in Sustainability
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Journal Article
Open access
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Miroslav NedeljkovićMiroslav Nedeljković
Miroslav Nedeljković
Adis PuškaAdis Puška
Adis Puška
RSRadmila Suzić
Radmila Suzić
AMAleksandar Maksimović
Aleksandar Maksimović
Bosnia and Herzegovina (abbreviated BiH) has great potential for fruit production. BiH has over 1.5 million hectares of agricultural land. In addition, there are excellent climatic conditions for growing fruit. However, although there is a long tradition of fruit production in BiH, this production must be improved. This paper provides guidance on making decisions in fruit growing when there are multiple criteria. All criteria are divided into two groups: economic and technical criteria. The economic criteria are further divided into three subcriteria, namely: marketing costs, orchard construction costs and processing and transport costs. Technical criteria are divided into four subcriteria, namely: fruit, variety resistance, production characteristics and processing and transport. According to these, a multicriteria decision-making model based on linguistic values was created. In order to take advantage of these values, a fuzzy approach was applied. Using this approach, decision-making process is easier because decision making is tailored to human thinking. For the example of raising a new orchard in the area of Semberija, an evaluation of seven different varieties of pears was performed. This problem is solved by applying the method of multicriteria analysis (MCDA). To solve this research problem, the MABAC (Multi-attributive border approximation area comparison) method was used. Using the fuzzy MABAC method, the obtained results show that the Šampionka variety has the best indicators among observed varieties. In addition, the Konferans variety achieved good results, and these two varieties are the first choice for raising a new orchard of pears. The paper validates the results and performs sensitivity analysis. The contribution of this research is to develop a new model of decision making by using a new methodology that facilitates decision making on variety selection. This model and methodology provide a flexible way of making decisions in fruit growing.