Theodoros Tsekeris

Prof. Dr. Theodoros Tsekeris

Centre for Planning and Economic Research, Athens, Attikí, Greece
orcid

Research Focus & Metrics

Academic Career Length

23Years (2004-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 April 2009 in NETNOMICS: Economic Research and Electronic Networking
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Theodoros TsekerisTheodoros Tsekeris
Theodoros Tsekeris
SVStefan Voß
Stefan Voß

13 June 2012 in European Transport Research Review
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Spyros NiavisSpyros Niavis
Spyros Niavis
Theodoros TsekerisTheodoros Tsekeris
Theodoros Tsekeris
This paper aims at benchmarking, measuring and identifying major determinants of the technical efficiency of container seaports in the region of South-Eastern Europe, including the Italian ports which directly affect competition in the wider region of East Mediterranean Sea. The study employs both non-parametric (standard and super-efficiency DEA) models and bootstrapped parametric techniques to provide a more holistic approach and useful insight into the given problem. The results indicate the relatively low (below 50 %) average total technical efficiency of the container ports in the study region, which can be attributed to both the lack of managerial skills and scale effects. The findings can help to determine sources of port inefficiency by geographical location and size and adopt best practices to improve the operational performance of container ports.

1 July 2010 in Journal of Transportation Engineering
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Journal Article
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Theodoros TsekerisTheodoros Tsekeris
Theodoros Tsekeris
ASAntony Stathopoulos
Antony Stathopoulos
This paper addresses the problem of modeling and predicting urban traffic flow variability, which involves considerable implications for the deployment of dynamic transportation management systems. Traffic variability is described in terms of a volatility metric, i.e., the conditional variance of traffic flow level, as a latent stochastic (low-order Markov) process. A discrete-time parametric stochastic model, referred to as stochastic volatility (SV) model is employed to provide short-term adaptive forecasts of traffic (speed) variability by using real-time detector measurements of volumes and occupancies in an urban arterial. The predictive performance of the SV model is compared to that of the generalized autoregressive conditional heteroscedasticity (GARCH) model, which has been recently used for the traffic variability forecasting, with regard to different measurement locations, forms of data input, lengths of forecasting horizon and performance measures. The results indicate the potential of the SV ...

19 December 2015 in Journal of Economic Interaction and Coordination
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Theodoros TsekerisTheodoros Tsekeris
Theodoros Tsekeris

1 January 2011 in Economic Research-Ekonomska Istraživanja
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Journal Article
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Theodoros TsekerisTheodoros Tsekeris
Theodoros Tsekeris
CTCharalambos Tsekeris
Charalambos Tsekeris
The main purpose of this paper is to comprehensively explore and productively overview the growing research field of demand forecasting in transport. In this analytic context, it seeks to describe, critically discuss and fruitfully elaborate on relevant mechanisms and models of demand forecasting, as well as on the particular development and implementation of systematic (or system-wide) approaches. The overview of various theoretical and methodological developments in current prediction models eventually advocates the use of consumer demand models (of dynamic character) to predict demand shares among alternative modes of transport.

1 April 2009 in NETNOMICS: Economic Research and Electronic Networking
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Journal Article
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LDLoukas Dimitriou
Loukas Dimitriou
Theodoros TsekerisTheodoros Tsekeris
Theodoros Tsekeris