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Amaç: Bu çalışmanın amacı, OECD ülkelerinin 2019 yılı tarımsal etkinliğini ölçmek ve kurgulanan senaryolar üzerinden parçalı elastiklik analizleri gerçekleştirerek ülkelerin kısmi ölçeğe göre getiri karakterizasyonlarını ortaya koymaktır.Yöntem: Etkinlik ve elastiklik ölçümleri için Veri Zarflama Analizi (VZA) ve VZA tabanlı yöntemler kullanılmıştır.Bulgular: OECD ülkelerinin %43’ünün etkin bir şekilde faaliyet gösterdiği tespit edilmiş ve ortalama tarımsal etkinliğin 0,87 olduğu saptanmıştır. Elastiklik analizi bulgularına göre seçmeli radyal etkinlik varsayımını sağlayan OECD ülkelerinin büyük bir bölümü için kısa vadede tarımsal büyümenin gerçekleşmesinin beklenmediği, üretim faktörlerinde yaşanabilecek marjinal artışlar karşısında tarımsal çıktıların çoğunlukla azalan veya sabit oranda artış eğiliminde olduğu belirlenmiştir.Özgünlük: Çalışma, ülke bazında parçalı elastiklik ölçüm modellerinin ilk uygulaması olması ve OECD ülkelerinin tarımsal performanslarına dair bütünleyici bir perspektif sunması açısından önemlidir.

Amaç: Yükseköğretimde artan küresel rekabet dolayısıyla kurumlar ölçülebilir hedefler koymak amacıyla stratejik yönetim araçlarından Dengeli Puan Kartı (DPK) uygulamalarına yer vermekte ve literatürde konuyla ilgili birçok araştırma bulunmaktadır. Çalışmada, yükseköğretim kurumlarında DPK uygulamalarına derinlemesine bir bakış sunularak, üniversite performans değerlendirmesinde kullanılan kriterlerin derlenmesi amaçlanmaktadır. Yöntem: Çalışma kapsamında, uluslararası literatürde 2003 yılından itibaren yayınlanmış araştırma makaleleri incelenmiş ve üniversite performansının ölçümünde kullanılan kriterler gruplanarak derlenmiştir. Bulgular: Yapılan araştırma, yükseköğretim kurumları için ortaya konan DPK’ların hem kriterler hem de kriterlerin yer aldığı alt boyutlar açısından oldukça farklılaştığını ortaya koymaktadır. Çalışmada, incelenen çalışmalarda yer alan 540 kriter, 104 başlıkta incelenmiş ve bu başlıklar belli temalara göre gruplanarak her bir başlıkta yer alan kriterler detaylı bir biçimde sunulmuştur. Özgünlük: Çalışmanın yükseköğretimde performans değerlendirmesi ve stratejik planlama üzerine çalışacak gelecek araştırmalara bir kriter havuzu vasıtasıyla yol gösterici olması beklenmektedir.

This research addresses the utilization of user-defined and web-based data for decision-making in recreational activities, focusing on the case of scuba diving, a globally significant recreational pursuit. While a wealth of user-generated information is available on the internet for various leisure activities, harnessing this data involves extensive data collection and organization efforts. Our proposed methodology involves the collection and organization of user reviews, both in verbal and quantitative forms, to create a pertinent dataset for applying multiple criteria decision methodologies to classify diving sites worldwide. An initial dataset containing over 14,000 diving sites worldwide is aggregated into 721 regions and these regions are classified using UTADIS methodology. The research showcases how user-generated review data can be transformed into valuable information, applying classification algorithms of multiple criteria decision analysis within the context of scuba diving. Furthermore, the proposed approach in this research holds the potential to serve as a model for leveraging user-generated data in decision-making processes across various service sectors such as hospitality and leisure that highly rely on customer experience by providing new insights on how more data-driven approaches can be utilized.

IntroductionHealth expenditures are a factor that reflects the government's public health policy and contributes to the protection of national health. Therefore, this study focuses on measuring the effectiveness of health expenditures in order to evaluate and improve the public health system and policy during the pandemic period.MethodIn order to examine the effectiveness of health expenditures, the behaviors of the pandemic process were analyzed in two stages. The number of daily cases is analyzed in the first stage by dividing it into waves and phases according to the transmission coefficient (R). For this classification, the discrete cumulative Fourier function estimation is used. In the second stage, the unit root test method was used to estimate the stationarity of the number of cases in order to examine whether the countries made effective health expenditures according to waves and phases. The series being stationary indicates that the cases are predictable and that health expenditure is efficient. Data consists of daily cases from February 2020 to November 2021 for 5 OECD countries.ConclusionThe general results are shown that cases cannot be predicted, especially in the first stage of the pandemic. In the relaxation phase and at the beginning of the second wave, the countries that were seriously affected by the epidemic started to control the number of cas es by taking adequate measures, thus increasing the efficiency of their health systems. The common feature of all the countries we examined is that phase 1, which represents the beginning of the waves, is not stationary. After the waves fade, it can be concluded that the stationary number of health cases cannot be sustainable in preventing new waves' formation. It is seen that countries cannot make effective health expenditures for each wave and stage. According to these findings, the periods in which countries made effective health expenditures during the pandemic are shown.DiscussionThe study aims to help countries make effective short- and long-term decisions about pandemics. The research provides a view of the effectiveness of health expenditures on the number of cases per day in 5 OECD countries during the COVID-19 Pandemic.

This research aims to measure the change of provincial development levels of Turkey’s 81 provinces through banking sector data. The applied methodology is the Malmquist Total Factor Productivity Index (MTFPI). We perform the analysis based on two models. The main difference between models relies on handling the factor associated with ‘loans’. The first approach sees the loans as an output factor, which is based on the idea that loans indicate investment and therefore development. In the second model, we take the loans as an input factor, which represents the idea that loans indicate debt and therefore they should be minimized. We evaluate the findings with respect to geographical classification and the province development index.

Quality Assurance is one of the core elements of the Bologna Process in European Higher Education and the Bologna Process data of the programs can serve as a rich resource for assessing program quality and benchmarking since the data follow a standardized framework for any program. Despite the standardized framework, the data of each program require an organization in order to come up with comprehensive measures so that such measures can become comparable between programs. This paper aims to propose an analytical approach for academic program quality assessment utilizing the Bologna declarations of the programs. First, we propose a methodology on data organization. Second, the organized data are used for assessments at program and subdivision levels via Data Envelopment Analysis. We illustrate our proposed methodology in an application to Business bachelor degree programs in Turkish universities. We discuss the implications to various stakeholders of higher education from policy makers to students.

In this paper, we propose an extension of the standard UTADIS methodology, an approach that originates from multicriteria decision aid (MCDA) for sorting problems, such that it can handle more than one classification criteria simultaneously which possibly involves different predefined classes for alternatives. Moreover, we test the classification ability of the standard UTADIS methodology using the out-of-classification criterion approach, a new variant of the studies comprising out-of-time and out-of-sample testing methodologies. Results obtained in out-of-classification criterion testing are then compared with the classification ability of the Multiple Classification Criteria UTADIS (MCC UTADIS). Finally, an application to country risk evaluation is performed. In this application, classifications of two credit rating agencies, Standard & Poor's and Moody's, are taken as two different classification criteria. Moreover, robustness of MCC UTADIS method is tested through using several data sets. Results indicate that MCC UTADIS involving more than one classification criteria performs very close to standard UTADIS with single classification criterion and performs better than the out-of-classification criterion tests. These results emphasize both the sensitivity of UTADIS models to the classification criteria and the importance of using a multiple classification criteria approach.

Multiple Criteria Decision Analysis (MCDA) techniques are particularly suitable for Energy and Environment (E&E) decisions due to multiple criteria nature of these types of problems and they have been widely applied in this area. Main points that can be taken into consideration when examining the MCDA literature related to E&E are the selection of appropriate method, selection of criteria to be used and the widely distributed application areas. The motivation behind this study is designing such a Decision Support System (DSS) that enables the energy decision makers to perform analysis using different methods of MCDA and different criteria from various application areas and test the applicability of the system through an application in Turkish Energy Sector. The system includes several methods of MCDA and common parameters from previous studies in order to provide different approaches of evaluating decision problems. With this feature, the system stands on the intersection of MCDA and E&E fields. Moreover, an application of MCDA in Turkish Energy Sector has been performed to test the applicability of the system and some conclusions about electricity distribution in Turkey are put forth. Santrauka Daugiakriterinės sprendimų analizės (DKSA) metodai yra ypač tinkami energetikos ir aplinkos (E ir A) sprendimams priimti dėl daugiakriterinio problemų pobūdžio ir šioje srityje metodai buvo plačiai naudojami. Svarbiausi punktai, į kuriuos gali būti atsižvelgta nagrinėjant DKSA literatūrą, susijusą su E ir A, yra tinkamo metodo parinkimas, galimų rodiklių parinkimas ir plačiai paplitusios taikymo sritys. Šio mokslinio straipsnio motyvas yra suformuoti tokias sprendimų paramos sistemas (SPS), kurios leidžia energetikos sprendimus priimantiems asmenims atlikti analizę naudojant įvairius DKSA metodus ir skirtingus rodiklius iš įvairių taikymo sričių bei bandyti pritaikyti šią sistemą remiantis Turkijos energetikos sektoriumi. Sistema apima kelis DKSA metodus ir bendrus parametrus, iš ankstesnių mokslinių straipsnių, siekiant užtikrinti skirtingų požiūrių buvimą vertinant sprendimų priėmimo problemas. Šiame straipsnyje sprendimų sistema yra sankirtoje tarp DKSA bei E ir A. Be to, buvo atliktas DKSA pritaikymas Turkijos energetikos sektoriuje siekiant patikrinti sistemos pritaikomumą bei yra pateikti keli pasiūlymai dėl elektros paskirstymo Turkijoje. Reikšminiai žodžiai: Daugiakriterinė sprendimų analizė, energetika ir aplinka, sprendimų paramos sistemos, ELECTRE, PROMETHEE, duomenų apėmimo analizė