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The Journal of Academic Social Science Studies International Journal of Social Science Doi number:http://dx.doi.org/ /jasss1969 Volume 6 Issue 8, p , October 2013 İŞLETMELERİN GÖRECELİ ETKİNLİKLERİNİN

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The Journal of Academic Social Science Studies International Journal of Social Science Doi number:http://dx.doi.org/ /jasss1969 Volume 6 Issue 8, p , October 2013 İŞLETMELERİN GÖRECELİ ETKİNLİKLERİNİN VERİ ZARFLAMA ANALİZİ İLE ÖLÇÜLMESİ: İMALAT SANAYİNDE BİR UYGULAMA * EVALUATION OF RELATIVE EFFICIENCY OF BUSINESSES BY USING DATA ENVELOPMENT ANALYSIS: AN APPLICATION TO MANUFACTURING INDUSTRY Yrd. Doç. Dr. Ötüken SENGER Alper TAZEGÜL Ceyda YERDELEN KAYGIN Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Abstract In study, quarterly data of year 2012 gathered from financial reports of 26 businesses of which stocks being traded in Borsa İstanbul- operating through a sub-sector of manufacturing industry, namely Stone and Earth Industry was evaluated. Performance analysis of business is very vital on one hand for business owners or employers, managers, competitors and creditors and current and potential investors on the other. The aim of study is to evaluate performance of aforementioned businesses and make a comparison between their performance rates. In this context, Data Envelopment Analysis (DEA) is used to evaluate business efficiency, relative efficiency of input-output and determination of decision-making units. * Bu makale Crosscheck sistemi tarafından taranmış ve bu sistem sonuçlarına göre orijinal bir makale olduğu tespit edilmiştir. 528 Ötüken SENGER Alper TAZEGÜL Ceyda YERDELEN KAYGIN As Data Envelopment Analysis is relevant to input and output, input and output data included in study was collected in accordance with literature. Ratios such as current ratio, acid-test ratio, receivable turnover ratio, stock turnover ratio and total debt to total asset ratio were used as input data while ratios like net profit to total asset ratio, net profit to equity ratio and net profit to net sales ratio were used as output data. After analysis, full efficient firms were determined and necessary increase or decrease rates for input and output data were established in order to transform inefficient firms into efficient ones. In addition, it was shown that some firms were efficient during all periods while some others had varying levels of efficiency periodically. Key Words: Efficiency and Productivity, Performance Comparison, Data Envelopment Analysis Öz Çalışmada, Borsa İstanbul da işlem gören ve imalat sanayinin alt dallarından olan; Taş ve Toprağa Dayalı Sektör e ait 26 işletmenin 2012 yılına ait mali tablolarından veriler üçer aylık dönemler halinde incelenmiştir. İşletmelerin performansların analiz edilmesi, işletmenin sahipleri, yöneticileri, rakipleri ve kreditörleri açısından oldukça önemli olmasının yanı sıra mevcut ve potansiyel yatırımcılar için de önem arz etmektedir. Çalışmada söz konusu işletmelerin performanslarının ölçülmesi ve elde edilen performansların karşılaştırılması amaçlanmıştır. Bu amaçla işletmelerin etkinlikler, karar birimlerinin belirlenmesi ile girdi ve çıktıya yönelik göreceli etkinliklerinin ölçülmesine olanak tanıyan olanak tanıyan Veri Zarflama Analizi (VZA) yöntemi kullanılarak analiz edilmiştir. Veri Zarflama Analizi girdi ve çıktıya yönelik olduğu için araştırmada kullanılacak girdiler ve çıktılar literatürle uyumlu olarak belirlenmiştir. Cari oran, asit-test oranı, alacak devir hızı, stok devir hızı ve toplam borçlar / toplam aktifler oranı girdi olarak kullanılırken net kar/ toplam aktif oranı, net kar/ öz sermaye oranı ve net kar/ net satışlar oranı ise çıktı olarak kullanılmıştır. Analiz sonucunda tam etkin çalışan firmalar tespit edilmiş olup, etkin olmayan firmaları etkin hale dönüştürmek için referans alınan firmalar ile girdi ve çıktılarda yapılması gereken artırma veya azaltma oranları saptanmıştır. Ayrıca çalışma sonucunda, bazı firmaların incelenen tüm dönemlerde etkin olduğu, bazı firmaların ise etkinliğinin dönemsel olarak değiştiği tespit edilmiştir. Anahtar Kelimeler: Etkinlik ve Verimlilik, Performans Karşılaştırması, Veri Zarflama Analizi 1. INTRODUCTION As a result of globalization and rapid and continuous transformation process, businesses need to maintain their current competitive powers. To put it in a different way, they should have sustainable levels of competitive power. By meeting their İşletmelerin Göreceli Etkinliklerinin Veri Zarflama Analizi İle Ölçülmesi: İmalat 529 unlimited needs with limited resources and aiming to have sustainable levels competitive power, most businesses tend to focus on concepts like efficiency or to put it technically productivity. Today s competitive business environment forces firms to use their resources optimally or in the most efficient way. Firm managers periodically need evaluations and assessments in order to determine deviations from business plans and monitor both their own and competitors market positions (Yalama and Sayım, 2008: 89). Such evaluations and assessments are very vital for businesses stakeholders, potential investors, employees and credit agencies on one hand, and public and private researchers aiming to perform economic studies on the other. Performance is a qualitative and quantitative statement about an individual s, group s or enterprise s achievement and succeeding of a goal aimed at a specific business task (Kasnaklı, 2002: 131). A fundamental measure of performance, namely productivity (Dwyer and others, 2010: 275) is generally defined as the relation between an output created by a production or service system and input used in creation of that output (Prokopenko, 1987: 3). One may define productivity in a number of ways but most commonly and simply it can be defined as input / output ratio (McConnell, 1993: 93). Efficiency refers to the level of achieving a goal and the relation between intended and actual effect. While focusing on efficiency-related topics it is very important to make a sharp distinction between outputs and results. It is harder to evaluate and assess results than to evaluate and assess inputs and outputs (Gülcü and others, 2004: 91). Farrell (1957) groups a firm s efficiency into two: a- technical efficiency and b- allocative efficiency (Farrell, 1957: ). The former measures performance of a firm in producing maximum output by using given inputs and called as technical or production efficiency and the latter refers to the performance of a firm in choosing optimal inputs in terms of given input prices (Sengupta, 1999: 209). Allocative efficiency is selection of input components with minimum cost for producing desired output (Coelli and others, 2005: 5). Allocative efficiency and technical efficiency determine a firm s level of cost efficiency as an indicator of its production capabilities with minimum costs (Aktaş, 2001: 164). Efficiency evaluation enables a firm to monitor its market position in a competitive environment and refers to firm s level of performance in producing outputs by using given inputs (Yolalan, 1993: 6). Though it is thought that efficiency and productivity concepts are synonymous words, they in fact have different meanings. Eliminating this ambiguity plays an important role on evaluation of business s performance. Ratio analysis, one of the methods that are used for quantitative evaluation of business performance and analysis of its financial condition, measures financial power, 530 Ötüken SENGER Alper TAZEGÜL Ceyda YERDELEN KAYGIN efficiency and productivity level of business (Siddiqui and Siddiqui, 2005: ). In ratio analysis approach which is simply defined as ratio of one input to one output, each ratio evaluates only one of performance dimensions and thus this can be regarded as a weakness of ratio analysis. Another weakness of evaluations using ratios is that they need to be compared to different factors necessarily (Gülcü and others, 2004: 82). To put differently, unidimensionality of ratio analysis and parametric methods requiring data about functional structure between inputs and outputs limits the use of ratio analysis with parametric methods. For this reason, non-parametrical methods are widely used in evaluation of efficiency and productivity (Özer and others, 2010: 234). In study, we also used Data Envelopment Analysis, one of the non-parametric methods used in efficiency and productivity analysis of businesses. 2. LITERATURE REVIEW Soba and others (2012), by using financial ratios and applying Data Envelopment Analysis and TOPSIS method, evaluated efficiency and performance levels of 25 businesses from metal fabrication and machinery equipment sector and 26 businesses of which stocks being traded in Borsa Istanbul- from stone and earth sector between According to their results; they concluded that the number of efficient businesses in stone and earth sector was 14 in 2008, 8 in 2009 and finally 11 in The number of relatively efficient businesses in metal fabrication and macninery equipment sector in 2008 and 2009 was 9. In this sector, the number of efficient businesses was 11 in In their study, Soba et al. observed that data envelopment analysis was appropriate in measuring business efficiency while TOPSIS analysis could be used in evaluating firm performance. Altın (2010), by using financial ratios, tested finacial efficiencies of 142 companies registered in İMKB Industry Index. Research period covers balance as at december 31, Data Envelopment Analysis is based on assumption of constant returns to scale. In this context, efficiency consists of two stages; a-fundamental efficiency and b- super efficiency. According to study results, 44 out of 142 registered companies were found to be efficient during balance period. In their study, Kaya and others (2010), by using data collected from balance sheets and income statements of year 2008 (in the form of four quarters) of 25 companies operating through metal fabrication and machinery equipment sector, compared performance levels of these businesses by applying data envelopment analysis. According to their analysis results, they found that 5 businesses were efficient during all quarters of In their study, after determining efficient businesses through sector, they also offered some proposals for inefficient firms to improve themselves as they computed required recovery ratios. In their study, Ata and Yakut (2009), by using data envelopment analysis, evaluated efficiencies of firms operating through Turkish manufacturing sector between In addition, they also performed an efficiency analysis in terms of İşletmelerin Göreceli Etkinliklerinin Veri Zarflama Analizi İle Ölçülmesi: İmalat 531 pre-determined variables of input and output by using financial ratios. In their analysis, they computed an efficiency score for every sector and they also determined efficient and inefficient sectors. Finally, they made some proposals for inefficient firms to improve their efficiency capabilities. Yıldız (2007), by using financial ratios, evaluated scale efficiencies of businesses from manufacturing industry these businesses were registered to İMKB- and showed that in average these businesses had an efficiency level of nearly 70 %. In his study, Bakırcı (2006) evaluated efficiencies of 13 automotive firms that were ranked in top 500 firms in Turkey in 1994 and Data regarding these firms was fully accessible. In study, Bakırcı, by applying a comparative approach and using data envelopment analysis, measured efficiency levels of these firms. He found that 6 out of these 13 firms were inefficient in terms of input while small sized firms were more efficient. In their study, Yalçıner and others (2005), analysed stock yields of a number of companies by using semi-annual data (six sets of data in total) regarding period between December 2000 June In study, they performed a data envelopment analysis and a total factor productivity index analysis in order to determine efficiency levels of companies and variations among them. After determining the efficient companies by using data envelopment analysis, they concluded that there was a positive correlation between efficiency of company and stock yields of concerned period. Kayalıdere and Kargın (2004), by using data envelopment analysis, evaluated efficiency levels of a number of businesses registered to İMKB- that operate through textile and cement sectors. By using data regarding 2002, they performed 4 different types of analysis including 15 businesses from cement sector and 27 from textile sector. According to their results, 3 businesses in 1st analysis, 4 in 2nd, 5 in 3rd and 5 in 4th were found to be efficient while remaining businesses were found to be inefficient in terms of input-output values. 3. METHOD AND APPLICATION In this study, quarterly data of year 2012 gathered from financial reports of 26 businesses of which stocks being traded in Borsa İstanbul- operating through a subsector of manufacturing industry, namely Stone and Earth Industry was used. By using Frontier analysis program, these data were evalauted seperately as inputoriented and output-oriented. In study, a common instrument used by researchers, namely Data Envelopment Analysis (DEA) is used to evaluate business efficiency, relative efficiency of input-output and determination of decision-making units. In study, Ratios such as current ratio, acid-test ratio, receivable turnover ratio, stock turnover ratio and total debt to total asset ratio were used as input data while ratios 532 Ötüken SENGER Alper TAZEGÜL Ceyda YERDELEN KAYGIN like net profit to total asset ratio, net profit to equity ratio and net profit to net sales ratio were used as output data. The aim of study is to evaluate relative efficiency levels of businesses operating through aforementioned sector and to determine efficient and inefficient businesses. In addition, we also aim to determine the required levels of input/output ratio for inefficient businesses in order to improve themselves in comparison with efficient ones in sector Data Envelopment Analysis This analysis, known in literature as Data Envelopment Analysis (DEA), was first introduced by Farrell in 1957 in his study evaluating relative efficiency concept. Then in 1978, in their study, Charnes, Cooper and Rhodes applied this model (Charnes and others, 1978) for evaluating efficiency of decision-making units. For Data Envelopment Analysis to be applied, it is first required to choose decision-making units that have similar organizations and implement same decisions. To evaluate efficiency levels of decision-making units, one should determine input and output variables of these units (Atan, 2002: 61). Because, DEA method is applied to input and output variables (Charnes and others, 1981: 669). Input-oriented approach focuses on minimum amount of input for producing a specific output (input minimization) while output-oriented approach focuses on maximum output amount that can be produced by using a specific input (output maximization) (Keskin Benli, 2012: 371). Relative efficiency evaluation method of data envelopment analysis can be summarized as follows (Yolalan,1993: 27-28): i) to determine best observations (or decision-making units forming efficiency limit) from any observation set that produce maximum output combination by using minimum input combination. ii) to evaluate, by taking that limit as reference, distance (or efficiency levels) of inefficient decision-making units to this limit radially. Below mathematical equation shows output/input ratio that can be maximized for n number of organizational decision-making units that have m number of input and s number of output (Ulucan 2002): Productivity = Output /Input Maxh k = s r 1 s r 1 u v rk ik y x rj ij İşletmelerin Göreceli Etkinliklerinin Veri Zarflama Analizi İle Ölçülmesi: İmalat 533 in which x ij 0 parameter denotes output amount i used by decision-making unit j and y rj 0 parameter denotes output amount r used by decision-making unit j. Variables for this decision problem consist of weighted values of input and output determined by decision-making unit k. These variables are denoted as v ik and u rk in turn. Below inequation shows the limitation that prevents time efficiencies of other decision-making units exceeding %100 when weighted values of decision-making unit k are used by other decision-making units. s rk rj r 1 s r 1 u v ik y x ij 1; j = 1, n Finally, below equation shows the limitation that prevents input and output weights having a negative value. u rk 0 ; r =1,...,s v ik 0 ; i =1,...,m To transform these inequation sets into lineer programming form and solve them by using Simplex or similar algorithms, one should equalize denominator of objective function (in the form of maximization) to 1 and transform it into a limitation. Objective function; s Maxh k = u rk r=1 y ri m v ik x ik = 1 Limiting Conditions; i=1 s m u rk y ri v ik x ik 0 r=1 i=1 u rk, v ik 0 534 Ötüken SENGER Alper TAZEGÜL Ceyda YERDELEN KAYGIN h k = efficiency coefficient, h k is always smaller than 1 or equal to it. If h k 1, then decision-making unit is not relatively efficient. If h k = 1, then decision-making unit is relatively efficient. Aim of output-oriented CCR model ise to determine input and output weights that minimize actual input/actual output ratio in terms of target decision-making unit. These limitations lead to actual input/actual output ratio having a minimum value of 1 and all input and output weights taking positive values (Özer vd., 2010: 239). One of output factors, net profit for period, may sometimes have negative values for some businesses. Therfore, this condition violates positivity of variables assumption of DEA method, these values are transformed into positive ones by using normalization equation (Yıldız, 2005: 291). Xrj- Xj Min Xj Max - Xj Min Xrj= value of output r for decision-making unit j Xj Min = minimum r value Xj Max = maximum r value 3.2. Efficiency Analysis and Findings Table 1 shows pre-determined input and output variables for stone and earth sector which is a sub-sector of manufacturing industry and also registered to Borsa İstanbul. Table 1. Input and Output Variables Used in Study Inputs Current Ratio Acid-Test Ratio Receivables Turnover Ratio Outputs Net Profit/ Total Assets (Return on Assets) Net Profit/ Equity (Return on Equity) Net Profit/ Net Sales (Return on Sales) Stocks Turnover Ratio Total Debts / Total Assets Current Liabilities/Total Liabilities Table 2 shows codes and company names of 26 businesses registered to Borsa İstanbul- operating through stone and earth sector which is one of sub-sectors of manufacturing industry. İşletmelerin Göreceli Etkinliklerinin Veri Zarflama Analizi İle Ölçülmesi: İmalat 535 Table 2. Businesses Operating Through Stone and Earth Sector Included in Study No Kod Şirket Adı No Kod Şirket Adı 1 ADANA, ADANA ÇİMENTO 14 DOGUB DOĞUSAN ADBGR, ADNAC 2 AFYON AFYON ÇİMENTO 15 ECYAP ECZACIBAŞI YAPI 3 AKCNS AKÇANSA 16 EGSER EGE SERAMİK 4 ANACM ANADOLU CAM 17 GOLTS GÖLTAŞ ÇİMENTO 5 ASLAN ASLAN ÇİMENTO 18 HZNDR HAZNEDAR REFRAKTER 6 BOLUC BOLU ÇİMENTO 19 IZOCM İZOCAM 7 BSOKE BATISÖKE ÇİMENTO 20 KONYA KONYA ÇİMENTO 8 BTCIM BATI ÇİMENTO 21 KUTPO KÜTAHYA PORSELEN 9 BUCIM BURSA ÇİMENTO 22 MRDIN MARDİN ÇİMENTO 10 CIMSA ÇİMSA 23 NUHCM NUH ÇİMENTO 11 CMBTN ÇİMBETON 24 TRKCM TRAKYA CAM 12 CMENT ÇİMENTAŞ 25 UNYEC ÜNYE ÇİMENTO 13 DENCM DENİZLİ CAM 26 USAK UŞAK SERAMİK According to analysis results; firms having codes of ADANA, AKCNS, ASLAN, BSOKE, CIMSA, DENCM, ECYAP, HZNDR, MRDN and USAK were found to be fully efficient during all four study periods. In addition, it is also shown that firms having codes of ANACM, CMENT and KONYA increased their efficiency levels periodically and firm having code of KONYA began to work full efficiently since 3rd quarter. The e

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