World's Best Scientists 2026 revealed!

D-Index & Metrics

Business and Management

D-Index
41
Citations
6886
World Ranking
1593
National Ranking
254

Overview

Aris A. Syntetos is affiliated with Cardiff University in the United Kingdom. Their primary research spans multiple fields including Decision Sciences, Business, Management and Accounting, and Engineering. Within these areas, their work focuses notably on Management Science and Operations Research, Management Information Systems, Industrial and Manufacturing Engineering, as well as Statistics, Probability and Uncertainty, and Strategy and Management.

Their research topics cover a range of applied forecasting and operational challenges. Key areas include Forecasting Techniques and Applications, Supply Chain and Inventory Management, Advanced Statistical Process Monitoring, Energy Load and Power Forecasting, Stock Market Forecasting Methods, Reliability and Maintenance Optimization, and Vehicle Routing Optimization Methods.

Frequent publication venues for their work include:

  • European Journal of Operational Research
  • IMA Journal of Management Mathematics
  • International Journal of Forecasting
  • International Journal of Production Research
  • arXiv (Cornell University)

Among their recent published papers are:

  • Forecasting: theory and practice (2022, BOA - University of Milano-Bicocca)
  • Predictive maintenance using cox proportional hazard deep learning (2020, Advanced Engineering Informatics)
  • Inventory - forecasting: Mind the gap (2021, European Journal of Operational Research)
  • Last mile logistics: Research trends and needs (2022, IMA Journal of Management Mathematics)
  • Quality grading of returns and the dynamics of remanufacturing (2021, International Journal of Production Economics)

Aris A. Syntetos has also contributed to academic literature through book publications, including the title Intermittent Demand Forecasting - Context, methods and applications published in 2022 by Lancaster University.

Collaboration with other researchers is reflected in several frequent co-authors, who have contributed to multiple publications alongside them, such as M. Zied Babaï, Bahman Rostami-Tabar, John E. Boylan, Mohamed Mohamed Naim, and Ruud Teunter.

Best Publications

  • The accuracy of intermittent demand estimates

    Argyrios Syntetos;John E. Boylan

  • On the categorization of demand patterns.

    Aris A. Syntetos;John E. Boylan;J. D. Croston

  • Forecasting and operational research : a review

    Robert Fildes;Konstantinos Nikolopoulos;Sven F. Crone;Aris A. Syntetos

  • Supply chain forecasting: Theory, practice, their gap and the future

    Aris Syntetos;Zied Babai;John Edward Boylan;Stephan Kolassa

  • Intermittent demand: Linking forecasting to inventory obsolescence

    Ruud H. Teunter;Argyrios Syntetos;M. Zied Babai

  • ABC classification: service levels and inventory costs

    R.H. Teunter;M.Z. Babai;A.A. Syntetos

  • Classification for forecasting and stock control: a case study

    John E. Boylan;Aris A. Syntetos;G. C. Karakostas

  • On the stock control performance of intermittent demand estimators

    Argyrios Syntetos;John E. Boylan

  • Spare parts management : a review of forecasting research and extensions

    John E. Boylan;Aris A. Syntetos

  • Forecasting for inventory planning: a 50-year review

    Argyrios Syntetos;J. E. Boylan;Stephen Michael Disney

  • Demand categorisation in a European spare parts logistics network

    Argyrios Syntetos;M. Keyes;M. Z. Babai

  • Supply chain forecasting when information is not shared

    Mohammad Ali;Mohamed Zied Babai;John E. Boylan;Aris A. Syntetos

  • Forecasting and Inventory Performance in a Two-Stage Supply Chain with ARIMA(0,1,1) Demand: Theory and Empirical Analysis

    M. Z. Babai;Mohammad Mojiballah Ali;John Boylan;Aris A. Syntetos

  • On the demand distributions of spare parts

    Aris A Syntetos;Mohamed Zied Babai;Nezih Altay

  • Forecast errors and inventory performance under forecast information sharing

    Mohammad Mojiballah Ali;John Boylan;Aris A. Syntetos

  • Forecasting intermittent inventory demands: simple parametric methods vs. bootstrapping

    Unknown

  • On the calculation of safety stocks when demand is forecasted

    Dennis Prak;Ruud H. Teunter;Aris A. Syntetos

  • Determining order-up-to levels under periodic review for compound binomial (intermittent) demand

    R. H. Teunter;Argyrios Syntetos;M. Z. Babai

  • The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

    Thanos E. Goltsos;Borja Ponte;Shixuan Wang;Ying Liu

  • Demand forecasting by temporal aggregation

    Unknown

  • Economies of collaboration in build-to-model operations

    Carl Philip T. Hedenstierna;Stephen M. Disney;Daniel R. Eyers;Jan Holmström

  • Spare parts management: Linking distributional assumptions to demand classification

    D. Lengu;Argyrios Syntetos;M. Z. Babai

  • Intermittent demand forecasting: An empirical study on accuracy and the risk of obsolescence

    Mohamed Zied Babai;Argyrios Syntetos;Ruud Teunter

  • Forecasting for inventory management of service parts

    John E. Boylan;Aris A. Syntetos

  • Dynamic Re-order Point Inventory Control with Lead-Time Uncertainty: Analysis and Empirical Investigation

    Mohamed Zied Babai;Aris A Syntetos;Yves Dallery;Kostantinos Nikolopoulos

Frequent Co-Authors

M. Z. Babai
M. Z. Babai Kedge Business School
Ruud H. Teunter
Ruud H. Teunter University of Groningen
Mohamed Mohamed Naim
Mohamed Mohamed Naim Cardiff University
Paul Goodwin
Paul Goodwin University of Bath
Christoph H. Glock
Christoph H. Glock Technical University of Darmstadt
Rob J. Hyndman
Rob J. Hyndman Monash University
Robert L. Winkler
Robert L. Winkler Duke University
Spyros Makridakis
Spyros Makridakis University of Nicosia
Pierre Pinson
Pierre Pinson Technical University of Denmark
Sonia Leva
Sonia Leva Polytechnic University of Milan

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