Evaluation of Geothermal Energy Efficiency Factors by using Sem-pls for Citgöl Municipality
The fact that the global scale of energy resources is limited and the fact that they start to run out has increased the tendency towards renewable energy sources and has encouraged its use. One of there new able energy sources is geothermal energy. In Turkey geography, Kütahya region is one of the rich regions in terms of geothermal energy. Simav district, Çitgöl municipality, Naşa municipality Kütahya province is the are a using geothermal energy. While Çitgöl Municipality is using geothermal energy only for thermal springs until 2017, it started to use this energy for heating purposes in 2017. Regional heating system project has been commissioned in Çitgöl Municipality. As a result of our work in the context of energy efficient use of consumers; We identified energy efficiency, energy use, energy use information and physical environment factors. A face-to-face survey has been conducted in order to understand how effective the factors we determine are in increasing energy efficiency. Data collected from this questionnaire were tested using the partial least squares structural equation modeling (Smart PLS) approach.A common method to measure the reliability and internal consistency of the scale was Cronbach alfa. The Cronbach alpha values show the degree of internal consistency because it changes from 0,625 for energy efficiency to 0,889 for physical environment. Composite Reliability (CR) and Average Variance Extracted (AVE) tests were conducted to measure convergent validity. If the Cronbach alpha value for each structure is equal to or greater than 0.70, the reliability of the scale is generally accepted. CR value is between 0.841 and 0.944. However, it is recommended that the AVE must exceed 0.50 to ensure convergent validity. The value of AVE was between 0,579 and 0,894.This study consists of t-test, factor and regression analysis.
The results show administrative, theoretical and practical results for efficient use of the energies. This study presented International Congress On Afro - Eurasıan Research III October 19-21, 2017 / İstanbul .
Barclay J. M., Smith W. C. And Watts L.R. (1995), “The determinants of corporate leverage and dividend policies,” The Journal of Applied Corporate Finance, Vol.7, No.5, pp. 4-19, 1995.
Çalıkoğlu, E. (2004), “Enerji Verimliliği ve EİEİ Tarafından Yürütülen Çalışmalar”, 23. Ulusal Enerji Verimliliği Kongresi, EİEİ Genel Müdürlüğü (Enerji Tasarrufu Koordinasyon Kurulu) Yayını, Ankara.
Fornell, C., Larcker, D.F., 1981. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18 (1), 39–50.
Gaur, A. S., Gaur, S. S. (2006). Statistical methods for practice and research: A guide to data analysis using SPSS: Sage
Hair, Joe F., Marko Sarstedt, Christian M. Ringle, and Jeannette A. Mena. 2012a. "An Assessment of the Use of Partial Least Squares Structural Equation Modeling in Marketing Research." Journal of the Academy of Marketing Science 40 (3): 414-433.
İslatince H., Haydaroğu C. (2009), “Türk İmalat Sanayinde Enerji Verimliliği Ve Yoğunluğunun Analizi”, Dumlupınar Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. Sayı 24.
Kavak, K. (2005). “Dünyada ve Türkiye’de Enerji Verimliliği ve Türk Sanayinde Enerji Verimliliğinin İncelenmesi”, DPT Uzmanlık Tezi, Ankara
Önal, E. Ve Yarbay, R. Z. (2010). “Türkiye’de yenilenebilir enerji kaynakları potansiyeli ve geleceği”, İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, 9 (18), 77-96.
Özkaya M. G.,Variyenli H. İ., Yonar G., (2008). “Jeotermal Enerji İle Isıtılan Kütahya İli Simav İlçesindeki Isıtma Sisteminin Çevresel Etkilerinin Değerlendirilmesi ve Uygulanması Gereken Yenilikler”, C.Ü. Fen-Edebiyat Fakültesi Fen Bilimleri Dergisi, Cilt 29 Sayı 2.
Şener A. C. (2003). “Optimisation of Balçova Geothermal District Heating System”, Yüksek lisans tezi, İzmir Yüksek Teknoloji Enstitüsü Makina Mühendisliği Bölümü.
Tenenhaus, M., Esposito Vinzi, V. (2005). PLS regression, PLS path modeling and generalized procrustean analysis: a combined approach for PLS regression, PLS path modeling and generalized multiblock analysis. Journal of Chemometrics, 19, 145–153.
Wetzels M.,Odekerken-Schroder G.and Van Oppen, C. (2009). "Using PLS Path Modeling for Assessing Hierarchical Construct Models: Guidelines and Empirical Illustration," MIS Quarterly, (33: 1) pp.177-195.
Baysal M., Armağan K., Armağan C., Kıratlı N., Kitiş Ş., “Evaluation of Geothermal Energy Efficiency Factors by Using SEM (PLS) for Çitgöl Municipality “.
- There are currently no refbacks.