Productivity in agricultural enterprises is mainly achieved by increasing the productivity of seed, fertilizer, pesticide, labor and mechanization inputs. The aim of this study was to determine the productivity of the use of mechanization which has a significant share and limitation in production costs. For this purpose, in Karapınar, Çumra and Altınekin districts, which have 24% of the mechanization equipment used in the province of Konya, work was carried out. According to stratified random sampling method, 107 agricultural enterprises were interviewed. As a result of the surveys conducted with these enterprises, demographic and capital structures of the enterprises were examined, and annual activity results were calculated. According to the results of the annual activities, the land, labor and capital efficiency of the enterprises were calculated and the productivity of all three production factors increased in parallel with the growth of the enterprise scale. In order to determine the mechanization utilization productivity, which is the main purpose of the study, tractor draw force, working hours, age and usage costs were calculated. As a result of the analysis, it was determined that the mechanization productivity increased as the scale of the enterprise grew and the use of mechanization of the enterprises having land of 200 decares and above was in European standards. According to this result, it has been determined that the choice of tractor suitable for land and enterprise scale should be made. For this reason, a machine park model has been proposed to facilitate the utilization of new technologies.

Konya ilinin mekanizasyon düzeyini belirlemek için yapılan bu araştırmada; Konya ilindeki toplam alet-makine varlığının %24.73'ünü oluşturan Altınekin, Çumra, Karapınar ilçeleri araştırma alanı olarak belirlenmiştir. Çalışmada, örnek hacmi % 5 hata % 95 güven sınırları içerisinde 107 olarak belirlenmiş ve tarım işletmelerinden gönüllülük esasına göre anket tekniği kullanılarak veriler derlenmiştir. Tarımsal mekanizasyon düzeyi belirlenirken yararlanılan kriterler doğrultusun-da incelenen işletmelerde, işletme başına düşen traktör motor gücü 67.07 kW; ortalama traktör gücü 42.73 kW; traktör başına düşen alet-makine sayısı 7.05 adet; traktör başına düşen alet-makine ağırlığı 5.57 ton; birim alana düşen ortalama motor gücü 2.80 kW/ha; 1000 ha alana düşen traktör sayısı 65.72 adet; bir traktöre düşen işlenen alan 15.21 ha; 1000 ha alana düşen biçerdöver sayısı 0.39 adet olarak hesaplanmıştır. Conducted to determine the level of mechanization of Konya in this study; Konya, constituting 24.73 % of the total assets in the province Altınekin toolmaker, Çumra, Karapinar district have been identified as an area of research. In the study, the sample size was determined as 107 in a 5% error with 95% confidence limits, and data using the survey technique has been compiled on a voluntary basis in agricultural enterprises. The firms surveyed in accordance with the criteria used in determining the level of agricultural mechanization, falling 67.07 per farm tractor engine power kW; The average tractor power is 42.73 kW; The number of instrument-maker 7.05 per tractor units; 5.57 tons of weight per tractor per-machine tools; The average engine power per unit area of 2.80 kW / ha; The number of tractors to 1000 ha Total area 65.72; 15.21 ha of cultivated area falling on a tractor; The number of 1000 ha area was calculated as 0.39 units per harvester. This level of mechanization and the use of Konya in line with data obtained from average has been compared by value of Turkey in the light of figures and charts. As a result of the comparison, the enterprises surveyed had a value above average in Turkey.

Halal food has been studied in recent years in terms of both food safety and food security. Especially halal food products health, hygiene, quality, eco-friendly and so on. Considering the criteria, it is seen as an opportunity for entrepreneurs in the food sector. The rise in the demand for halal food products in the world evaluation of these opportunities is important in terms of Turkey. Indeed, Turkey is an important country as the potential for halal food products, consumers should investigation of attitudes and behavior towards halal food. Within the scope of the study, it was aimed to determine the willingness of consumers to pay for halal foods and for this purpose, 383 consumers were surveyed with a simple random sampling method in central districts of Konya. In the study, Willingness to Pay (WTP) method, which is one of the conditional evaluation methods, was used to determine the willingness of consumers to pay for halal foods. In this context, firstly, probit analysis was performed to determine the variables that best explain the willingness of consumers to pay. According to the probit analysis, it was found that willingness to pay for halal food products positively affected the gender, consumer age, marital status, consumer income, consumer occupation and education of the consumer. In addition, the marginal effects of variables used in the willingness to pay model for halal food for different payment options were calculated. According to the analysis, it was determined that the willingness to pay for marginal increases in the variables of the gender of the consumer, household width, consumer age, marital status, consumer monthly income, occupational status and consumer education. The level at which consumers are willing to pay for halal foods is WTP 10, a category where consumers can pay 100% or 2 times higher than normal price.

Günümüz koşullarında gerçekleştirilen sürdürülebilir kalkınma, üretimde kullanılan kaynakların sınırlı ve yenilenemez olmasından dolayı ekolojik dengeyi bozduğu sonucunu ortaya çıkarmaktadır. Özellikle gelişmiş ülkelerde toplumların mevcut fiziksel ve enerji tüketimleri göz önünde bulundurulduğunda Dünyanın mevcut tüketim düzeyinin sürdürülebilir olmadığı bilinmektedir. Sürdürülebilir ve ekolojik dengeyi gözeten bir üretim modeli için biyoekonomi, gelecek yıllar içerisinde önemini arttırarak devam edecektir. OECD (2012) raporlarına göre, biyoekonomik gelişmelerin temelinde, gelişen ülkelerde artan nüfus ve kişi başına düşen gelir yer almaktadır. Dünya nüfusu gelecek 10 yıl içerisinde 9 milyara ulaşacağı ve bu artışın %97’sinin gelişen ülkelerde meydana geleceği tahmin edilmektedir. Artan bu nüfus sonuç itibariyle gıda, yem, su kaynakları, enerji gibi kaynakların üzerinde baskı yaratacaktır. Ayrıca 2030 yılına kadar yine rapora göre GSYİH miktarının OECD ülkelerinde %2.3 ve gelişen ülkelerde %4.6 oranında artacağı öngörülmektedir. Raporda ayrıca biyokimyasal ürünlerin toplam kimyasal ürünler içerisindeki payının %35’e, biyoteknoloji ile üretilen ürünlerin oranının ise %50’ye ulaşılacağı tahmin edilmektedir. Bu nedenle biyoekonomi alanında bir yapılanmaya ihtiyaç duyulmakta ve biyoekonomi alanındaki ihtiyacın özel sektör girişimleri ile karşılanması gerekmektedir. Bu kapsamda, biyoekonomiye geçişin, girişimcilik anlayışı ile bu alandaki pazarlara ve iş fırsatlarına erişimin kolaylaşmasına yardımcı olacak çeşitli girişimci ilişkileri ve girişimleri incelenmiş olup, biyogirişimciliğin soyut kavramını geliştirmek, bileşenlerini kategorize etmek, Dünyada ve Türkiye’deki biyogirişimciliği incelemek çalışmanın temelini oluşturmaktadır. Ayrıca tarım sektöründeki biyoekonomi alanında yapılan faaliyetleri belirleyerek sektördeki yeni fırsatlar incelenmiş ve çalışma kapsamında tarımsal biyoekonomi alandaki gelişmeler ile ülkelerin kalkınmaları arasındaki ilişkiler ortaya konularak, tarımsal biyoekonomi girişimciliğinin yaygınlaştırılması gerekliliği ortaya çıkmıştır.

The aim of the study was to determine the factors affecting the decision of the entrepreneurship of the agricultural enterprises. For this purpose, a survey was conducted with 98 agricultural enterprises determined according to stratified random sampling method in the Ereğli district of Konya province and the factors affecting entrepreneurship were analyzed by multiple linear regression. In the study, entrepreneurial coefficients were taken as model dependent variables, and the amount of land, active capital, gross production value, MLU, producer age, agricultural insurance, net profit and formal education variables were included as independent variables. The description power of the model (R 2) was determined as 77.50%. All variables in the model were statistically significant according to t test. Based on the results obtained; The amount of active capital and age variables falling negative, land quantity, gross production value, EIB, insurance, net profit and education parameters were determined as positive according to the theory. As a result, it has been revealed that educational activities increase the level of entrepreneurship and young entrepreneurs have more entrepreneurial characteristics. Therefore, it is recommended to support young farmers such as training activities, small scale agricultural enterprises (SAME) and incentives.