Person: Balkan, Dursun
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Doç. Dr.
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Balkan
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Dursun
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Dursun BALKAN
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Publication Environmental performance assessment of manufacturing sectors(Springer Science and Business Media LLC, 2020-06-13) Onder Belgin; Dursun Balkan; Balkan, DursunPublication Assessment of technical efficiency of public hospitals in Turkey(Oxford University Press (OUP), 2019-08-14) Aziz Küçük; Volkan Soner Özsoy; Dursun Balkan; Balkan, DursunAbstractBackgroundTurkish public hospitals have been subjected to health care reform because of increasing cost pressure, inequities in access to health care, poor quality of care and limited patient responsiveness in the last three decades. This study investigates the impact of recent hospital reforms on the efficiency of public hospitals.MethodsThe study provides a comprehensive evaluation of the efficiency of Turkish hospitals by using Data Envelopment Analysis (DEA). The estimation of efficiency of 669 public hospitals of Turkey is performed by an output-oriented model of DEA under the assumption of variable return-to-scale by using data collected from the Ministry of Health (MoH) over the period 2013–17.ResultsThe average efficiency score is equal to 0.83 for all MoH hospitals. Considering the hospital type, the efficiency scores of training and research hospitals are higher than those of the general and branch hospitals. In addition, considering the hospital size, huge-scale hospitals have the highest efficiency score in all years. Moreover, overcrowded regions such as Marmara and South-eastern Anatolia regions had higher efficiency scores than other geographical regions.ConclusionsThe results indicate that recent health reforms did not significantly enhance hospital efficiency. Thus, policymakers and managers should take the necessary precautions to increase hospital efficiency.Publication Smart manufacturing maturity assessment: a Turkish case study in glass balcony manufacturing enterprise(TAYLOR & FRANCIS LTD, 2024) Akyuez, Goeknur Arzu; Balkan, Dursun; Balkan, Dursun; Akyüz, Göknur Arzu; Turkish Aeronautical Association; Turk Hava Kurumu University; Turkish Aeronautical Association; Turk Hava Kurumu University; Turkish Aeronautical Association; Turk Hava Kurumu UniversitySmartness journey involves increasing knowledge availability and maturity in technological, organizational, managerial, and human dimensions for the transformation of an enterprise. This article implements a systematic methodology and multi-dimensional maturity assessment tool to measure the maturity in the mentioned dimensions by offering a Turkish case study. Contrary to frequent mention of sectors such as automotive in relation to smartness concept, this study offers a real-life application in an adverse sector: glass balcony manufacturing. The methodology calculates weighted maturity index, determines the maturity levels for each dimension, and aggregates them into an overall enterprise maturity assessment. While applying the methodology, ratings are obtained via case company interview, and weight set utilized are determined via academic experts having practical sectoral expertise. Based on the findings, specific suggestions are provided to the case company for smart manufacturing implementation in multiple dimensions for their smartness journey. The study is original in comprehensively handling all maturity dimensions; demonstrating how smartness maturity can be practically measured in a case company by a flexible and weighted approach; obtaining simple, easy-to-interpret measurements; and authenticity of the sector. [GRAPHICS]Publication Technological maturity of the OECD countries: A multi-criteria decision-making approach using PROMETHEE(Informa UK Limited, 2023-06-05) Dursun Balkan; Göknur Arzu Akyüz; Balkan, Dursun; Akyüz, Göknur ArzuPublication Tekstil Sektöründe Verimlilik Ölçümü ve Bir Uygulama(UCTEA Chamber of Textile Engineers, 2019-03-28) Dursun BALKAN; Balkan, DursunPublication LABOUR PRODUCTIVITY ANALYSIS OF MANUFACTURING SECTOR IN TURKEY AGAINST EU(Vilnius Gediminas Technical University, 2023-05-23) Dursun Balkan; Goknur Arzu Akyuz; Balkan, Dursun; Akyüz, Göknur ArzuThis study offers an in-depth analysis of labour productivity of manufacturing sector in Turkey and provides a comparison with EU27 and EA19 countries utilizing Eurostat time series data of 63 quarters covering 2005/first quarter-2020/third quarter time interval. Productivity trends are identified and interpreted by relating them with the key macroeconomic events and factors. Multiple linear and non-linear regression equations, and ARIMA model with different parameters are applied to the time series data considering the periods with and without covid effect. Future projections are made for the periods 2020–2023 for Turkey manufacturing sector based on the best fitting regression and ARIMA solutions and they are compared. Findings revealed that extreme covid conditions of even two quarters of data have significant impact on the forecasted values for Turkey, EU27 and EA19 countries. ARIMA analysis with 12 different parameter settings provided accurate results, supported by Thiel’s inequality coefficients and standard error measures. Analysis has shown consistent patterns between EA19 and EU27 countries. ARIMA results represent better compatibility with the regression results for Turkey. Study is valuable by providing comprehensive and comparative analysis, revealing future forecasts and covid effect and degree of recovery from the pandemic.Publication Logistics Sector Turnover: Forecasting for Turkey, EU27 and EA19 under Effects of COVID-19(MDPI AG, 2023-04-07) Dursun Balkan; Goknur Arzu Akyuz; Balkan, Dursun; Akyüz, Göknur ArzuBackground: The logistics sector is the backbone of today’s global trade, and is vital for the continuity of goods and services. The sector is gaining increased importance as logistics operate under the extreme conditions the world is passing through (COVID-19, earthquakes, wars). Methods: A comparative study is offered for Turkey and the EU27 and EA19 countries utilizing Eurostat database time series data for logistics turnover, based on regression analysis with and without COVID-19-affected data. General trends are identified regarding the logistics turnover and average turnover by different transportation modes in Turkey. Linear, exponential, logarithmic and polynomial regressions are fitted to the dataset to find the best fit. Afterwards, forecasting is performed based on the polynomial equation, which is identified as the best fit. A similar approach is repeated for the EU27 and EA19 countries to put forward the trends and forecasts as well as a detailed comparative discussion among countries. Results: Our study reveals the dramatic effect of COVID-19 on the turnover of different logistics modes and the radical shift that Turkey experienced from land transportation towards air transportation. Conclusions: Our study provides forecasting and a comparative picture for the logistics sector, shows the growth trends with respect to different transportation modes and reveals the effects of the pandemic on the logistics sector for Turkey and the EU27 and EA19 countries.Publication Comparative Study of Affiliated and Non-Affiliated Hospitals: DEA Based Analysis in Turkey(Science and Education Publishing Co., Ltd., 2021-05-10) Dursun BALKAN; Balkan, DursunPublication A novel approach for determining common weights in two division network DEA: a case study of Science and Technology Parks in Turkey(ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD, 2022) Ozsoy, Volkan Soner; Belgin, Onder; Balkan, Dursun; Balkan, Dursun; Aksaray University; Turk Hava Kurumu University; Turkish Aeronautical AssociationData Envelopment Analysis is a popular tool for assessing the relative efficiency of units, treated as a whole unit, without considering the internal structure of decision-making units. In contrast to the conventional models, Network DEA models consider the internal operations of units. In both models, the most favourable weights of the input-output factors for each unit are used. One of the main pitfalls of these models is that they require a set of n different vectors of these weights for the units, thus the factors may not have the same importance for each unit. To overcome this drawback and avoid ignoring some factors, several methods have been proposed to determine a common set of weights (CSWs) of the factors. However, none of the proposed approaches can determine the CSWs in network DEA models. This paper contributes to the existing literature by proposing a novel approach for determining the CSWs based on Entropy Method. Finally, the proposed approach is applied to demonstrate their applicability in both numerical and illustration examples. Moreover, a case of assessment of Science and Technology Parks in Turkey was used for the purpose of illustration.