Logistics Systems Dynamics Group

We aim to achieve world class research and education excellence in the advancement of management theory and practice.

The Logistics Systems Dynamics Group (LSDG) is a collaborative and collegial team interested in understanding the dynamic behaviour of logistical, or supply chain, business systems.

We bring together control theory, good operations management and industrial engineering practice, business process engineering and system dynamics simulation to form an integrated approach to logistics systems dynamics problem solving. We produce high quality and influential research within the Public Value ethos of Cardiff Business School, such as EPSRC research on remanufacturing systems and sustainable supply chain management. Our research on the dynamic behaviour of organisations has a positive impact on our members and collaborators. We add value to the careers of our members, enhance the research reputation of the University, and improve the performance of our collaborators.

The group was established by Professor Denis Towill, a long-serving and distinguished Cardiff University academic. He made a significant contribution to the Business School and the wider University across 50 years and will be remembered for his personal and professional achievements. Professor Towill passed away in August 2015.

In July 2017 we held our first Alumni Conference. Dr Peter McCullen from Brighton University, a long term collaborator with the LSDG, gave The Denis Towill Memorial Lecture, more details can be found on Peter's Blog.

Logistics Systems Dynamics Group alumni conference.

Collaborative research

Academics from the LSDG also participate in Advanced Sustainable Manufacturing Technologies (ASTUTE)

Selected publications

Rostami-Tabar, B. and Ziel, F. 2022. Anticipating special events in emergency department forecasting. International Journal of Forecasting 38 (3), pp.1197-1213. (10.1016/j.ijforecast.2020.01.001)
Chen, C. , Demir, E. and Huang, Y. 2021. An adaptive large neighborhood search heuristic for the vehicle routing problem with time windows and delivery robots. European Journal of Operational Research 294 (3), pp.1164-1180. (10.1016/j.ejor.2021.02.027)
Demir, E. , Eyers, D. and Huang, Y. 2021. Competing through the last mile: strategic 3D printing in a city logistics context. Computers and Operations Research 131 105248. (10.1016/j.cor.2021.105248)
Thürer, M. , Huang, Y. and Stevenson, M. 2021. Workload control in additive manufacturing shops where post-processing is a constraint: an assessment by simulation. International Journal of Production Research 59 (14), pp.4268-4286. (10.1080/00207543.2020.1761038)
Lin, M. S. , Potter, A. and Pettit, S. 2021. Relationship heterogeneity in Taiwanese maritime logistics service supply chains. Supply Chain Management 26 (3), pp.385-401. (10.1108/SCM-03-2019-0116)
Purvis, L. et al. 2021. Distributed manufacturing as an opportunity for service growth in logistics firms. Supply Chain Management 26 (3), pp.307-322. (10.1108/SCM-03-2019-0096)
Zepeng, W. , Mohammed, A. and Harris, I. 2021. Food waste management in the catering industry: enablers and interrelationship. Industrial Marketing Management 94 , pp.1-18. (10.1016/j.indmarman.2021.01.019)
Wang, Y. , Chen, C. H. and Zghari-Sales, A. 2021. Designing a blockchain enabled supply chain. International Journal of Production Research 59 (5), pp.1450-1475. (10.1080/00207543.2020.1824086)
Babai, M. Z. et al., 2021. A compound-Poisson Bayesian approach for spare parts inventory forecasting. International Journal of Production Economics 232 107954. (10.1016/j.ijpe.2020.107954)
Chen, C. et al., 2021. The adoption of self-driving delivery robots in last mile logistics. Transportation Research Part E: Logistics and Transportation Review 146 102214. (10.1016/j.tre.2020.102214)
Guo, Y. et al., 2021. Drivers of green cooperation between Chinese manufacturers and their customers: an empirical analysis. Industrial Marketing Management 93 , pp.137-136. (10.1016/j.indmarman.2021.01.004)
Eyers, D. et al. 2021. The impact of additive manufacturing on the product-process matrix. Production Planning and Control (10.1080/09537287.2021.1876940)
Wang, Y. , Skeete, J. and Owusu, G. 2021. Understanding the implications of artificial intelligence on field service operations: a case study of BT. Production Planning and Control (10.1080/09537287.2021.1882694)
Mohammed, A. et al. 2021. Gresilient supplier assessment and order allocation planning. Annals of Operations Research 296 , pp.335-362. (10.1007/s10479-020-03611-x)
Disney, S. M. , Ponte, B. and Wang, X. 2021. Exploring the nonlinear dynamics of the lost-sales order-up-to policy. International Journal of Production Research 59 (19), pp.5809-5830. (10.1080/00207543.2020.1790687)
Cannas, V. et al., 2020. Determinants for order-fulfilment strategies in engineer-to-order companies: Insights from the machinery industry. International Journal of Production Economics 228 107743. (10.1016/j.ijpe.2020.107743)
Delic, M. and Eyers, D. R. 2020. The effect of additive manufacturing adoption on supply chain flexibility and performance: An empirical analysis from the automotive industry. International Journal of Production Economics 228 107689. (10.1016/j.ijpe.2020.107689)
Cigolini, R. et al., 2020. Supply chain management in construction and engineer-to-order industries. Production Planning and Control (10.1080/09537287.2020.1837981)
Liu, H. et al. 2020. Developing logistics value propositions: drawing Insights from a distributed manufacturing solution. Industrial Marketing Management 89 , pp.517-527. (10.1016/j.indmarman.2020.03.011)
Zhang, M. et al., 2020. The double-edged sword effect of service recovery awareness of frontline employees: from a job demands-resources perspective. International Journal of Hospitality Management 88 102536. (10.1016/j.ijhm.2020.102536)
Lin, J. , Naim, M. M. and Spiegler, V. L. 2020. Delivery time dynamics in an assemble-to-order inventory and order based production control system. International Journal of Production Economics 223 107531. (10.1016/j.ijpe.2019.107531)
Chen, C. et al. 2020. Predictive maintenance using cox proportional hazard deep learning. Advanced Engineering Informatics 44 101054. (10.1016/j.aei.2020.101054)
Flynn, A. and Walker, H. 2020. Corporate responses to modern slavery risks: An institutional theory perspective. European Business Review 33 (2), pp.295-315. (10.1108/EBR-05-2019-0092)
Potter, A. T. , Towill, D. and Gosling, J. 2020. On the versatility of Little’s Law in operations management: a review and classification using vignettes. Production Planning and Control 31 (6), pp.437-452. (10.1080/09537287.2019.1647363)
Hedenstierna, C. P. T. et al. 2019. Economies of collaboration in build-to-model operations. Journal of Operations Management 65 (8), pp.753-773. (10.1002/joom.1014)
Lin, J. and Naim, M. M. 2019. Why do nonlinearities matter? The repercussions of linear assumptions on the dynamic behaviour of assemble-to-order systems. International Journal of Production Research 57 (20), pp.6424-6451. (10.1080/00207543.2019.1566669)
Flynn, A. 2019. Determinants of corporate compliance with modern slavery reporting. Supply Chain Management 25 (1), pp.1-16. (10.1108/SCM-10-2018-0369)
Rostami-Tabar, B. et al. 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)
Lotfi, M. 2019. Which practices are lean, agile and resilient Literature review and practitioners' perspective. International Journal of Advanced Operations Management 11 (1/2), pp.142-170. (10.1504/IJAOM.2019.098522)
Lotfi, M. , Akram, Y. and Jafari, S. 2018. The effect of emerging green market on green entrepreneurship and sustainable development in knowledge-based companies. Sustainability 10 (7) 2308. (10.3390/su10072308)
Li, Q. and Disney, S. M. 2017. Revisiting rescheduling: MRP nervousness and the bullwhip effect. International Journal of Production Research 55 (7), pp.1992-2002. (10.1080/00207543.2016.1261196)

Some of the projects currently being worked on by members of this group:

Advanced Sustainable Manufacturing Technologies (ASTUTE 2020)

Designed to stimulate growth in West Wales and the Valleys by applying advanced engineering technologies to manufacturing challenges, driving cutting-edge research development and innovation

Find out more about the ASTUTE 2020 project.

Recently completed projects:

Yeo Valley research project

5 January 2018 to 5 January 2020
Industry sponsored project
Led by Dr. Laura Purvis and Prof. Stephen Disney
Project aim: To aide Yeo Valley in increasing the flexibility of their production systems by implementing the most advanced inventory and capacity management techniques
Award type: Research

Find out more about the Yeo Valley research project.

Resilient Remanufacturing Networks: Forecasting, Informatics and Holons

1 October 2016 to 30 September 2018
Sponsored by Engineering and Physical Sciences Research Council (EPSRC)
Led by Professor Aris Syntetos with Professor Mohamed Naim, Dr Ying Liu (Cardiff School of Engineering)
Award type: Research

To develop and apply a novel inventory control decision support system for closed loop supply chains found in the remanufacturing environment

15 February 2016 to 14 February 2018
Sponsored by Technology Board, Engineering and Physical Sciences Research Council (EPSRC) and Qioptiq Ltd
Led by Professor Aris Syntetos
Award type: Knowledge Transfer Partnership

To combine advanced supply chain and 3D Printing solutions

13 January 2016 to 31 January 2018
Sponsored by Technology Board, Engineering and Physical Sciences Research Council (EPSRC) and Panalpina World Transport Ltd
Led by Professor Aris Syntetos
Award type: Knowledge Transfer Partnership

Engaged Manufacturing

1 January 2016 to 31 January 2017
Sponsored by Cardiff Business School
Led by Dr Andrew Potter with Dr Daniel Eyers, Dr Jonathan Gosling, Dr Laura Purvis and Dr Michael Ryan
Award type: Research