Best Alternative Models to Increase Local Product Consumption

Autor: Kenan Çiftçi, Püren Veziroğlu, Bülent Miran, Ömer Faruk Emeksiz, Ayça Nur Şahin
Rok vydání: 2017
Předmět:
Zdroj: Selcuk Journal of Agricultural and Food Sciences. 3:154-161
ISSN: 1309-0550
DOI: 10.15316/sjafs.2017.49
Popis: A local agricultural product which briefly defined as a product sold close to the area of produced have an important impact on local farmer’s welfare. Within the scope of the study, consumer profiles who prefers local food and motives to buy local food were analyzed. The data of the study have been obtained through face to face interviews with agricultural product consumers. In that context collected data are primary which consist 93 surveys. Consumers selected randomly from university students in Adana where is the fourth biggest city of Turkey and has a very high potential of agricultural production. Firstly, through local product preference model with the help of ANP (Analytical Network Process) the weights that consumers give to the various criteria and alternatives have been determined. Based on these weights the combinations of most suitable conditions that consumers will prefer were determined. By taking into consideration the combination of consumers’ three conditions with highest probability were examined. In determining the best design, the method of “the best combinations of alternatives”(BeCA) was employed. BeCA gives optimum homogeneous preference combinations with the aid of 0-1 integer programming. The best combinations that were obtained were analyzed by selected appropriate statistical tests. Considering the results of the study, firstly; 39 students over 93 are assigned to 3 best groups. Secondly, students preferred fruits which are produced with imported seed and local labour. Furthermore, students stated that they prefer organic and healthy foods –mostly fruits- and they want to reach that type of foods in their local food markets. Finally, students wanted to be informed about the foods by the TV broadcasts.
Databáze: OpenAIRE