Other sections in Management Science:
An international centre of excellence working at the heart of research in management science and operational research.
The Department is a recognised centre of excellence in Management Science and related fields such as Operational Research, Operations Management, Information Systems and Business Analytics. We have a strong commitment to producing research of practical importance, capitalising on our tradition of collaborative research with industry. The Department takes the lead in two research centres: the Centre for Marketing Analytics and Forecasting and the Centre for Transport and Logistics. The Department is also a key partner in the EPSRC-funded Data Science Institute and STOR-i Centre for Doctoral Training.
Research in Management Science covers a wide range of topics in OR/MS, Business Analytics, Operations Management, Information Systems and Project Management. We have particular strengths in the following seven areas.
Forecasting and market analytics are important activities in organisations. With the pioneering Centre for Marketing Analytics and Forecasting we provide fundamental and applied research that leads to knowledge exchange between academia and business.
Our group advances the practice and research foundations of Marketing Analytics and Forecasting, by developing innovative approaches, and a programme of dissemination of best practices through the introduction of new methods, processes and systems. Research areas include promotional planning or defining omni-channel retail strategies. We support organisation to optimise their supply chain and improve their forecasting and planning process. For this we use the latest statistical methods but also focus on the behavioural aspect of decision making.
We are keen in collaborating with the industry on various projects. There is also a high demand for research academics in both these two fields and we are always looking for interested new PhD students.
Visit the Centre for Marketing Analytics and Forecasting for more information.
The Health Systems Research Group is a grouping of management scientists with a common interest in the development and application of Operational Research, Operations Management and Information Systems methods and theories, quantitative and qualitative, to important health systems issues.
Whilst the health systems research issues tackled are wide and varied, many of them relate to the general challenges of helping health systems to make better use of available resources, in terms of both improving efficiency and improving patient experiences. Much of it concerns elements of knowledge transfer, be it between researchers and practitioners, between industry and healthcare, or between the health systems of different countries.
Research is undertaken in a variety of modes including longer-term research via PhD, Research Council funded projects, and NHS R&D funded projects; and shorter-term research via Masters student projects and consultancy projects. This mix of research modes means that shorter term projects designed to meet fast-moving organisational timescales can be informed by ongoing research and expertise, whilst longer-term research can benefit from genuine experience of the real issues faced within health systems. Examples of MRes/PhD research and Masters projects can be accessed below.
A number of these people are also involved in collaborations with colleagues in other LUMS departments via the Centre for Sustainable Healthcare or in multi-disciplinary projects across the University via the Health Innovation Campus.
Interested PhD candidates would normally have some knowledge of health systems and strong knowledge of some area of management science. Research topics and methodology can then be tailored to meet the needs and interests of the candidate and the interests and expertise of potential supervisors, for example:
If you have any queries you wish to discuss, please contact Dr Dave Worthington and if you would like to apply for a PhD, please visit our PhD in Management Science.
Visit our Staff for further details.
The research of this group draws from socio-technical principles of design and use of information systems and technology (IST), and there is a strong inter-disciplinary focus to this group’s work. Within the department of Management Science, there are links with operations and supply chain management (through the study of intra- and inter-organisational co-ordination and networks), Systems/Soft OR (through problem structuring and methodology, and action research), and to the Health Systems Research group (through a focus on healthcare information systems).
Within the Management School, the group has complementary and teaching research interests with the Department of Organisation, Work and Technology. Across the wider University, there are links with the School of Computing and Communications and the School of Design, through the inter-disciplinary ESRC funded HighWire Doctoral Training Centre, which includes PhD supervision and Centre Co-directorships. The group also has links through its international work, especially the EU programmes, with the Lancaster Centre for Management in China.
Key projects by members of this research group include:
Key areas of research of this group are:
All of these areas draw from various social and technical theoretical perspectives in order to inform researchers and practitioners. Much of the work includes an international focus. The levels of analysis include individual, group and organisational. Specific topics and projects for individual faculty members are listed below.
The group has a strong PhD programme related to the strands outlined above. We welcome PhD and post-doctoral students in these areas. We are also open to other areas of research that fit our theoretical or methodological strengths - which include a broad range of qualitative and quantitative work. If you are interested in a topic not listed above you should write a brief description of the topic and why it may be of interest to a potential supervisor, sending it to our PhD Co-ordinator Monideepa Tarafdar.
We have one of the leading Supply Chain Management groups in Europe. Most of the research is empirical in nature, using a combination of case study, survey and simulation methods. The group works collaboratively with colleagues in the Department, across the School and in other faculties. Colleagues in Operational Research work on more quantitative aspects of operations, and the research covers five main areas:
There are particularly strong links with colleagues working on Information Systems, logistics, forecasting and supply chain modelling, industrial marketing, and service design.
There are several ongoing research projects that students may want to get involved in:
Visit our Staff for further details.
Optimisation is concerned with the maximisation or minimisation of functions of many variables. It is a multi-disciplinary field, having numerous applications in Management Science, Operational Research, Finance, Statistics, Computer Science, Engineering and the Physical Sciences. The Optimisation group in Lancaster is one of the largest in Europe, with over fifteen full-time faculty, in addition to post-docs and PhD students.
We have particular strengths in the following areas:
Members of the group have been on the editorial boards of journals such as Computational Optimization and Applications, Computers & Operations Research, Discrete Optimization, EURO Journal of Computational Optimization, Journal of Global Optimization, Mathematical Programming, Naval Research Logistics and Operations Research.
If you have any queries you wish to discuss, please contact Dr Guglielmo Lulli. If you would like to apply for a PhD, please see our PhD admissions page.
Visit our Staff and Publications for further details.
Simulation and Stochastic Modelling are very flexible modelling approaches, and are capable of incorporating uncertainty. Therefore, they are among the most widely used techniques in Operational Research and Management Science.
To gain insight into the behaviour of complex systems, and thereby improve decision-making, we can model individual components of the system, often incorporating randomness via probability distributions. Discrete event simulation, agent-based simulation and system dynamics link the components together in different ways to build models of the whole system. The overall behaviour of the system then emerges from the interactions between the elements, as the sum becomes more than its parts.
For some systems, insights can be gained through direct mathematical analysis without the need to resort to simulation, for example by using stochastic modelling techniques such as queueing theory, renewal theory, Markov chains and Markov processes.
The interplay between the modelling approaches is also very important. The development of simulation models can be guided by insights derived from stochastic models and the generality of stochastic models can be tested against simulated test cases. They can also be used in combination in multi-fidelity modelling, where a simulation model is often the high-fidelity but computationally expensive and stochastic modelling provides a less expensive low-fidelity model.
Collaborations with other departments and with industry are encouraged. For example, some recent and current PhD projects are part of the STOR-i Doctoral Training Centre which is a joint venture between the Department of Mathematics and Statistics, and the Department of Management Science. These projects usually have supervisors in both departments and an industrial partner.
If you have any queries you wish to discuss, please contact Dr Roger Brooks. If you would like to apply for a PhD, please see our PhD programme.
We have an excellent reputation for strong research impact in the field of transport and logistics through our dedicated Centre for Transport and Logistics (CENTRAL). This Centre explores an interdisciplinary approach to producing cutting-edge sustainable solutions to logistical and transportation issues. The research focuses on two main projects known as OR-MASTER and OptiFrame.