Şirket özelliklerinin işletme sermayesi yönetimine etkisi: BİST'te işlem gören şirketler  üzerine sayısal bir araştırma
Effect of campanies' characteristics on working capital:  A study of Turkish listed companies
Yazar: MOHAMMAD AKBAR FARHANG
Danışman: PROF. DR. MEHMET ARSLAN
Gazi Üniversitesi / Sosyal Bilimler Enstitüsü / İşletme Ana Bilim Dalı
Derece: Doktora, 2018
Konu: İşletme = Business Administration
Dizin: Borsa İstanbul = İstanbul Stock Exchange ; Firmalar = Firms ; Nakit döngüsü = Cash conversion cycle ; Sektörel analiz = Sectoral analysis ; İşletme sermayesi = Working capital ; İşletme sermayesi yönetimi = Working capital management

Özet:
Araştırmanın amacı, şirket özelliklerinin işletme sermayesi üzerine etkisini; şirket büyüklüğü, aktif kârlılığı, hisse senedi fiyatı, toplam borç oranı, faaliyet kârlılığı, net kâr marjı gibi faktörler bağımsız değişkenler olarak dikkate alınarak test etmektir. Nakit döngüsü (CCC)  ve faaliyet döngüsü bağımlı değişkenler olarak ele alınmıştır. Bu amaçla,   imalat sektörü, perakende sektörü ve teknoloji sektörü  2008-2016 yıllarına ilişkin KAP'tan derlenen  üçer aylık mali veriler kullanılarak hipotezler test edilmiştir. Araştırma hipotezlerini test etmek üzere, çoklu doğrusal regresyon analizi ve ilgili istatistiksel analizler kullanılmıştır. Analiz sonuçlarına göre; imalat sanayinde hesaplanan oranlar istatistiksel olarak normal dağılım göstermiş ve karlılığın negatif çarpıklığa sahip olduğu tespit edilmiştir. Regresyon analizinin de (P=0,000) düzeyinde anlamlı olduğu tespit edilmiştir. Faaliyet karı, büyüklük ve net kar marjı carı oran (işletme sermayesi) düzeyinin üzerinde etkisinin anlamlı olduğu (P< 0,07). Nakit döngüsü R2 değeri  0,512 olarak tespit edilmiştir. Perakende sektörü açısından ise; işletmelerin nakit döngüsü -99,3509 olarak tespit edilmiştir. Nakit döngüsünün işletme sermayesini belirleme gücü R2 değeri 0,601 olarak tespit edilmiştir ve modelin anlamlılık düzeyi de (P=0,000) olmuştur. İlginç olarak bu sektörde işletme büyüklüğünün nakit döngüsünü etkilemediği ortaya çıkmıştır. Teknoloji sektöründe ise;  ortalama tahsilat süresi 180 gün ve faaliyet döngüsü 309 gün; nakit döngüsü 173 gün olarak çok uzun bir süre tespit edilmiş ve 0,97 düzeyinde pozitif çarpıklığa sahip stokta kalma süresi bulunmuştur.  Son olarak, sektörel karşılaştırma analizinde tek yönlü ANOVA'nın sonucuna göre, sektörlerin finansal göstergeler açısından farklı olduğunu göstermiştir.

Abstract:
The objective of this research is to determine and test the effects of company characteristics including, company size, return on assets, return on equity, total debt ratio, operating profit and net profit margin that are considered as independent variables. Cash conversion cycle (CCC), operating cycles and current ratio are used as dependent  variabls.Companies' characteristics consist of company size, return on assets (ROA), stock price, total debt ratio, operating profit, net profit margin and some other factors are considered as a variable on this study For this purpose, Totally 29 large segmented firms from three main sector of Istanbul Stock Exchange (IES) listed companies (16 companies from manufacturing, 7 companies from technology and 6 companies from retial sector) has taken as sample size to this research. Companies' balance sheets, income statements and other required financialThe related financial data of these sectors; manufacturing, retail  and technology, data are extracted from KAP (public disclosure platform) on a quarterly basis for the period of year 2008 to 2016.  , Istanbul Stock Exchange (IES) Data Store, Turkish Share Markets and companies related websites.  Company characteristics like; company size, return on assets (ROA), return on equity (ROE), total debt ratio, operating profit and net profit margin are considered as predictive variables. Cash conversion cycle (CCC) which is used as a measure of working capital management (WCM) is taken as outcome variable. The multiple linear regression analysis and other relevant statistical analysis are used to test the hypothesis of the study. According to the test of normality of the variables  used in the analysis states that,found to be standard division of interest rate coverage ratio is almost (+1) which indicate a normally distributed. Findings of the analysis showed that, for the manufacturing sector, financial ratios are normally distributed and sector, as a whole, had a negatively skewed profitability ratios. The average current ratio and asset test ratio are 2,25 and 1,56 respectively in production sector. The multiple linear regression model found to be statistically significant (P = 0,000)  which (P) value is P< 0,05 with  the Cash Conversion cycle's . The adjusted R^2 value of  0,512demonst..  By considering the (P) value of predicted variables separately, its found that total debt ratio, operating profit and return on equity have the (P) value P< 0,05 and have significant relation with CCC.   Operating profit, size and  net profit margin found to have effect on  current ratio (proxy for working capital) with (p<0,07) statistical significance. Cash conversion cycle for the retail sector found to be -99,35 days.,  
	The result from descriptive statistical analyze on retail sector has found that average current ratio and asset test ratio are; 1,3486 and 0,9715 respectively. Based on this analysis average account receivable period is 23 days, average operating cycle period is 39 days and cash conversion cycle (CCC) period is determined -99,3509. 
The results of result from regression statistical analysis of  proved that, the model is statistically  significant as a whole (P=0,000). And CCC  found to heve effects on working capital levels with the adjusted  R^2  value of  0,601. Interestingly,  the firms' size found not have any impact on  the  level of CCC.  By looking the (P) values of predictive variables of the model separately, its found that only net profit margin and return on assets (ROA) are statistically significant and the remaining independent variables (total debt ratio, operating profit, equity price and company size) are not statistically significant. The result from descriptive statistical analyze on companies which is doing businesses in technology sector has found, average account receivable period and operating cycle period 180 days and 309 days respectively. And the CCC period indicated 173 days. Another interesting result is that the, inventory period 0,97 is positively skewed, means that firms in technology businesses are required to invest up to certain level on their inventories. Apart from that, interest coverage ratio is also positively skewed (0,78). Finally the result from regression analysis table onof analysis  on technology sector found to have  average collection period is 180 days, operating cycle of 309 days and CCC of 173 days wich is very long duration and with 0,97 value of positively skewed inventory period. Finally, one-way ANOVA methodology used   to test if sectoral differences exist   on the basis of selected financial measures and all three sectors found to have differentiated from each other.