Corporate real estate analysis: evaluating telecom branch efficiency in Greece

This paper proposes productivity analysis for evaluating the relative efficiency in corporate real estate usage across decision-making units. Using data from the Greek Telecommunications Organization (GTO), we measure the productivity of 127 braches using the number of employees and the total area covered per building as inputs and the number of telephony access lines as outputs. We apply three non-parametric Data Envelopment Analysis (DEA) models assuming: constant returns to scale (CRS), variable returns to scale (VRS) and slacks-based measures (SBM), respectively. We discuss how the proposed approach can provide real estate managers and analysts a multi informational tool that allows the quantification of targets and may serve as a guide tool for the efficient employment of real estate assets

EVALUATING PUBLIC TRANSPORT EFFICIENCY WITH NEURAL NETWORK MODELS

This paper is concerned with measuring performance of public transport services based on the concept of productive efficiency. A new nonparametric approach is proposed based on multi-layer perception neural networks (MLPs). The advantages and limitations of this approach are discussed and compared with those of mathematical programming and econometric techniques. The MLP is used, along with data envelopment analysis (DEA) and corrected least squares (COLS), to set out comparative annual efficiency measures for the London Underground, for the period 1970 to 1994. It is argued that the MLP approach is superior to traditionally applied techniques since it is both nonparametric and stochastic and offers greater flexibility. Finally, it is demonstrated that the proposed MLP efficiency analysis has important practical implications for decision making

Seasonality in the Athens stock exchange

This paper studies calendar effects in the emerging Athens Stock Exchange. Rather than examining only basket indices, we analyse calendar effects for each of the constituent stocks of the Athens Stock Exchange General Index for the period from October 1986 to April 1997. In accordance with similar studies substantial evidence of 'day-of-the week', 'monthly', 'trading month' and 'holiday' effects are found. The intensity of these effects for various stocks on the basis of capitalization, beta coefficients and company type are examined. The results indicate that the calendar regularities vary significantly across the constituent shares of the General Index and that aggregation introduces a considerable bias in unravelling these regularities. Also, it is found that factors such as the beta coefficient and company type influence significantly the intensity of calendar effects.