Dr Bahman Rostami-Tabar

Reader in Management Science

: rostami-tabarb@cardiff.ac.uk
: +44 (0)29 2087 0723
: C08, Adeilad Aberconwy, Rhodfa Colum, Cathays, Caerdydd, CF10 3EU

: Ar gael fel goruchwyliwr ôl-raddedig

Bahman is lecturer (Assistant Professor) in Logistics and Operations Management at Cardiff Business School, Cardiff University.

Bahman's life objective is to help the world becoming a better place by freely offering his skills and developing free resources.

Bahman holds a Ph.D. in Industrial Engineering from the University of Bordeaux. He earned his B.Sc. in Industrial Engineering from K.N.Toosi University of Technology, Tehran, Iran, and his M.Sc. in Industrial Engineering from Tarbiat Modares University, Tehran.

His research goals are directed toward the use of Operations Research (OR) techniques to improve decision making in supply chains and operations management (SCOM), and as such positively contribute to both industrial and societal advancements.

Qualifications

2016 - Postgraduate Certificate in Learning and Teaching in Higher Education, Coventry University, UK
2013 - Ph.D., Industrial Engineering. Thesis entitled 'ARIMA Demand Forecasting by Aggregation', University of Bordeaux, France
2010 - M.Sc., Information Systems, ECE Paris, France
2009 - Proficiency in French Language, Université de Poitiers , France
2008 - M.Sc., Industrial Engineering, Tarbiat Modares University, Tehran, Iran
2002 - B.Sc., Industrial Engineering, K.N.Toosi Uni. Of Technology, Tehran, Iran (4 years).

Anrhydeddau a Dyfarniadau

2009 - 2013 Campus France Scholarship award
2013 MIM best paper award (IFAC)
2017 International Symposium on Industrial Engineering and Operations Management, Best Track Paper Award, Bristol, UK

Safleoedd academaidd blaenorol

2015 - 2016: Lecturer in Supply Chain Management, School of Strategy and Leadership, Coventry University, UK.
2013 - 2015: Postdoctoral Research Fellowship, Industrial Engineering Lab, Ecole Centrale Paris, France.

2022

Abolghasemi, M., Rostami-Tabar, B. and Syntetos, A. 2022. The value of point of sales information in upstream supply chain forecasting: an empirical investigation. International Journal of Production Research (10.1080/00207543.2022.2063086)
Petropoulos, F. et al. 2022. Forecasting: theory and practice. International Journal of Forecasting (10.1016/j.ijforecast.2021.11.001)
Mircetic, D., Rostami-Tabar, B., Nikolicic, S. and Maslaric, M. 2022. Forecasting hierarchical time series in supply chains: an empirical investigation. International Journal of Production Research 60(8), pp. 2514-2533. (10.1080/00207543.2021.1896817)
Babai, M. Z., Boylan, J. E. and Rostami-Tabar, B. 2022. Demand forecasting in supply chains: a review of aggregation and hierarchical approaches. International Journal of Production Research 60(1), pp. 324-348. (10.1080/00207543.2021.2005268)
Wang, Z., Rostami-Tabar, B., Haider, J. J. and Naim, M. 2022. A systematic literature review of trauma networks and systems: from operations management perspectives. Presented at: 12th European Decision Sciences Conference, Dublin, Ireland, 29 May – 1 June 2022.

2021

Rostami-Tabar, B. 2021. Business forecasting in developing countries. In: Gilliland, M., Tashman, L. and Sglavo, U. eds. Business forecasting : the emerging role of artificial intelligence and machine learning. Wiley and SAS Business Series
Rostami-Tabar, B. and Rendon-Sanchez, J. F. 2021. Forecasting COVID-19 daily cases using phone call data. Applied Soft Computing 100, article number: 106932. (10.1016/j.asoc.2020.106932)
Rostami-Tabar, B., Ali, M. M., Hong, T., Hyndman, R. J., Porter, M. D. and Syntetos, A. 2021. Forecasting for social good. International Journal of Forecasting (10.1016/j.ijforecast.2021.02.010)

2020

Rostami-Tabar, B. and Ziel, F. 2020. Anticipating special events in emergency department forecasting. International Journal of Forecasting (10.1016/j.ijforecast.2020.01.001)

2019

Rostami-Tabar, B., Babai, M. Z., Ali, M. and Boylan, J. E. 2019. The impact of temporal aggregation on supply chains with ARMA(1,1) demand processes. European Journal of Operational Research 273(3), pp. 920-932. (10.1016/j.ejor.2018.09.010)

2017

Kourentzes, N., Rostami-Tabar, B. and Barrow, D. K. 2017. Demand forecasting by temporal aggregation: Using optimal or multiple aggregation levels?. Journal of Business Research 78 (10.1016/j.jbusres.2017.04.016)
Rostami-Tabar, B. and Disney, S. M. 2017. The bullwhip effect under count time series: The case of first order integer auto-regressive demand processes. Presented at: International Symposium on Industrial Engineering and Operations Management, Bristol, UK, 25-26 July 2017.
Rostami-Tabar, B. and Disney, S. M. 2017. The impact of temporal aggregation on production and inventory costs. Presented at: OR59 Annual Conference, Loughborough, United Kingdom, 12-14 September 2017.

2016

Emrouznejad, A., Rostami-Tabar, B. and Petridis, K. 2016. A novel ranking procedure for forecasting approaches using data envelopment analysis. Technological Forecasting and Social Change 111, pp. 235-243. (10.1016/j.techfore.2016.07.004)

2015

Rostami-Tabar, B., Babai, M. Z., Ducq, Y. and Syntetos, A. 2015. Non-stationary demand forecasting by cross-sectional aggregation. International Journal of Production Economics 170(Part A), pp. 297-309. (10.1016/j.ijpe.2015.10.001)

2014

Rostami-Tabar, B., Babai, M. Z., Syntetos, A. and Ducq, Y. 2014. A note on the forecast performance of temporal aggregation. Naval Research Logistics 61(7), pp. 489-500. (10.1002/nav.21598)

2013

Rostami-Tabar, B., Babai, M. Z., Syntetos, A. and Ducq, Y. 2013. Demand forecasting by temporal aggregation. Naval Research Logistics 60(6), pp. 479-498. (10.1002/nav.21546)

2008

Amin-Naseri, M. and Rostami-Tabar, B. 2008. Neural network approach to lumpy demand forecasting for spare parts in process industries. Presented at: International Conference on Computer and Communication Engineering, 13-15 May 20082008 International Conference on Computer and Communication Engineering Proceedings. IEEE pp. -., (10.1109/ICCCE.2008.4580831)
Nasiri Pour, A., Rostami-Tabar, B. and Rahimzadeh, A. 2008. A hybrid neural network and traditional approach for forecasting lumpy demand. Proceedings of the World Academy of Science, Engineering and Technology 2(4)

Teaching commitments

Operations Analytics
Strategic Supply Chain Management

Research

I am interested in research on time series forecasting, supply chain forecasting and forecasting for social good. In my research, I have examined how a data transformation apparoach (Temporal Aggregation) can improve forecast accuracy and supply chain utilities. I am currently working on projects which are concerned with the social impact of forecasting.

Primary research interests

Statistical supply chain forecasting
Forecasting by aggregation
Forecasting for social good (health, Humanitarian, enviroment, education,...)
The interface between forecasting and decision making

PhD Supervision

I welcome enquiries from potential PhD students in the areas of supply chain forecasting and forecasting for social good(health, humanitarian, disaster, enviromental, education, ...) and Forecasting by aggregation.