Yaşar University

About: Yaşar University is a education organization based out in Izmir, Turkey. It is known for research contribution in the topics: Exergy & Job shop scheduling. The organization has 760 authors who have published 1436 publications receiving 20813 citations. The organization is also known as: Yaşar Üniversitesi.

Empirical examination of REITs in Turkey: an emerging market perspective

Abstract: Purpose – The aim of this paper is to investigate the risk‐return relationship of REITs listed on the Istanbul Stock Exchange (ISE) in order to assess the risk and to find some empirical results for investors within the framework of modern portfolio theory (MPT) using the standard version of the capital asset‐pricing model (CAPM) and the single index model (SIM) over the period January 2002‐June 2008.Design/methodology/approach – Time series, cross‐sectional regression and structural literature review are employed.Findings – Results indicate that linearity assumption for both the CAPM and the SIM are rejected. It should be emphasized that the econometrical specification exposed the weaknesses of t‐test methodology for testing coefficients of regression due to the non‐normality of residuals.Originality/value – Understanding of risk and its resultant impact on the returns and evaluation of risk‐return relationship is extremely important for investors. In this regard, real estate investment trusts (REITs) as...

The prioritisation of service dimensions in logistics centres: a fuzzy quality function deployment methodology

Abstract: This study takes a customer focus that prioritises the service-offering dimensions of logistics centres (LCs) by considering potential LC customer expectations. Applying a survey and a quality function deployment methodology to logistics service providers, the study explores, categorises and prioritises LC customer expectations and LC service characteristics. The results indicate that customer preferences mainly prioritise infrastructure, and warehouse and intermodal dimensions. However, when the cost dimension is included, higher utility values are delivered through soft service dimensions like value-added or standard services. LC investors or undertakers can use these results to guide their design of market offerings by using the same methodology to assess expectations in their target markets.

Heat transfer and pressure drop characteristics of a plate heat exchanger using water based Al 2 O 3 nanofluid for 30° and 60° chevron angles

Abstract: Nanofluid is a new class of engineering fluid that has good heat transfer characteristics which is essential to increase the heat transfer performance in various engineering applications such as heat exchangers and cooling of electronics. In this study, experiments were conducted to compare the heat transfer performance and pressure drop characteristics in a plate heat exchanger (PHE) for 30° and 60° chevron angles using water based Al2O3 nanofluid at the concentrations from 0 to 0.5 vol.% for different Reynolds numbers. The thermo-physical properties has been determined and presented in this paper. At 0.5 vol% concentration, the maximum heat transfer coefficient, the overall heat transfer coefficient and the heat transfer rate for 60° chevron angle have attained a higher percentage of 15.14%, 7.8% and 15.4%, respectively in comparison with the base fluid. Consequently, when the volume concentration or Reynolds number increases, the heat transfer coefficient and the overall heat transfer coefficient as well as the heat transfer rate of the PHE (Plate Heat Exchangers) increases respectively. Similarly, the pressure drop increases with the volume concentration. 60° chevron angle showed better performance in comparison with 30° chevron angle.

A discrete artificial bee colony algorithm for the traveling salesman problem with time windows

Abstract: This paper presents a discrete artificial bee colony algorithm (DABC) for solving the traveling salesman problem with time windows (TSPTW) in order to minimize the total travel cost of a given tour. TSPTW is a difficult optimization problem arising in both scheduling and logistic applications. The proposed DABC algorithm basically relies on the destruction and construction phases of iterated greedy algorithm to generate neighboring food sources in a framework of ABC algorithm. In addition, it also relies on a classical 1-opt local search algorithm to further enhance the solution quality. The performance of the algorithm was tested on a benchmark set from the literature. Experimental results show that the proposed DABC algorithm is very competitive to or even better than the best performing algorithms from the literature.