Dr Kathy Kotiadis is a Reader in Management Science/Operational Research and is an expert in developing quantitative and qualitative modelling approaches to support stakeholder engagement, primarily in Health Care.
Dr Kotiadis is the co-founder of PartiSim, which stands for Participatory Simulation, an approach to support stakeholder involvement in the discrete event simulation modelling process. She has held academic positions previously at Canterbury Christ Church Business School where she was the Director of Research and Knowledge Exchange. Prior to that she held Daphne Jackson Fellowship at the School of Computing (UoK) and was an Assistant Professor at the Warwick Business School.
Research InterestsDr Kathy Kotiadis research interests revolve around the following key terms: discrete-event simulation; conceptual modelling; health care modelling; systems thinking; problem structuring methods; soft systems methodology; facilitation; multiparadigm multimethodology.
Dr Kotiadis is primarily interested in developing OR approaches that support the engagement of stakeholders in the modelling process. She is the recipient of the UK OR society K. D. Tocher medal (Journal of Simulation) 2007-8. She was awarded the prestigious Daphne Jackson (STEMM) Fellowship (2014). She was also awarded an Engineering and Physical Research Sciences Research Council (EPSRC) (UK) grant EP/E045871/1 in 2007.
She was rated outstanding reviewer in 2016 for EJOR (4 star ABS). Additionally she reviews for JORS (3 star ABS); Systems, Man and Cybernetics: Systems; Production Planning and Control; Journal of Simulation; Operational Research in Healthcare, Health Systems etc.
Dr Kotiadis has designed and taught modules at UG, PG and executive level education on Simulation, Statistics, the process of Operational Research, Problem Structuring Methods and Project Management.
Dr Kathy Kotiadis has supervised the following PhD students:
Stavrianna Dimitriou - The impact of prices on boundedly rational decision makers in supply chains (with Prof S Robinson). Oct 2010
Tom Monks - Comparing model reuse with model building: an empirical study of learning from simulation (with Prof S Robinson). Apr 2011
She has also successfully supervised a large number of postgraduate students in their MBA and Master's dissertations.
Dr Kotiadis welcomes applications in the areas of simulation modelling, developing facilitated OR approaches and health care modelling.
Dr Kathy Kotiadis has undertaken research and consultancy projects in contexts such as health and social care as well as local government. She is a reviewer for RCUK and has been an EPSRC peer review college member since 2016. She is on the editorial board of the Journal of Simulation (since 2010).
Dr Kotiadis has been extensively involved in conference organisation. She was Programme Chair of the 2008 Operational Research Society 4th Simulation Workshop (SW08); Programme committee for SW10; SW12; SW14; SW16; SW18 and was the simulation stream co-organiser for OR59 for September 2017. Organised streams and presented research and at national and international conferences (e.g. IFORS, EURO (International) and WSC (USA), The UK Operational Research Society Conference) as well been invited speaker to institutions such as London School of Hygiene and Tropical Medicine (2018), LSE, Southampton and the Department of Health. She was the keynote Speaker for simulation stream at YOR20 in April 2017. Dr Kotiadis was the co-chair of the UK (OR society) simulation study group from 2006-2011 organising a number workshops/events. Dr Kotiadis is a member of the UK OR society.
Also view these in the Kent Academic Repository
Kotiadis, K. and Tako, A. (2018). Facilitated post-model coding in discrete event simulation (DES): A case study in healthcare. European Journal of Operational Research [Online] 266:1120-1133. Available at: http://dx.doi.org/https://doi.org/10.1016/j.ejor.2017.10.047.Research on facilitated discrete event simulation (DES) is gathering pace but there is still a need to put forward real examples to explain the process to newcomers. This paper is part of a line of research on the methodology of facilitated DES. In this paper we explain in more detail the facilitation process and the tools used to support the experimentation and implementation stages in a DES study involving workshops with a group of stakeholders, after an initial simulation model has been coded on the computer. A real case study is used to describe the process followed and the interactions at the workshops. Extracts from the transcripts are also included, with the view to providing evidence of the stakeholders' involvement and their mood during the workshops. We conclude with a discussion on the process and tools used to support the facilitation process. Future research directions are also put forward. © 2017 Elsevier B.V.
Robinson, S., Dimitriou, S. and Kotiadis, K. (2017). Addressing the sample size problem in behavioural operational research: Simulating the newsvendor problem. Journal of the Operational Research Society [Online] 68:253-268. Available at: http://dx.doi.org/10.1057/s41274-016-0016-3.Laboratory-based experimental studies with human participants are beneficial for testing hypotheses in behavioural operational research. However, such experiments are not without their problems. One specific problem is obtaining a sufficient sample size, not only in terms of the number of participants but also the time they are willing to devote to an experiment. In this paper, we explore how agent-based simulation (ABS) can be used to address the sample size problem and demonstrate the approach in the newsvendor setting. The decision-making strategies of a small sample of individual decision-makers are determined through laboratory experiments. The interactions of these suppliers and retailers are then simulated using an ABS to generate a large sample set of decisions. With only a small number of participants, we demonstrate that it is possible to produce similar results to previous experimental studies that involved much larger sample sizes. We conclude that ABS provides the potential to extend the scope of experimental research in behavioural operational research. © 2016 The Operational Research Society.
Tako, A. and Kotiadis, K. (2015). PartiSim: A multi-methodology framework to support facilitated simulation modelling in healthcare. European Journal of Operational Research [Online] 244:555-564. Available at: http://www.sciencedirect.com/science/article/pii/S0377221715000661.Discrete event simulation (DES) studies in healthcare are thought to benefit from stakeholder participation during the study lifecycle. This paper reports on a multi-methodology framework, called PartiSim that is intended to support participative simulation studies. PartiSim combines DES, a traditionally hard OR approach, with soft systems methodology (SSM) in order to incorporate stakeholder involvement in the study lifecycle. The framework consists of a number of prescribed activities and outputs as part of the stages involved in the simulation lifecycle, which include study initiation, finding out about the problem, defining a conceptual model, model coding, experimentation and implementation. In PartiSim four of these stages involve facilitated workshops with a group of stakeholders. We explain the organisation of workshops, the key roles assigned to analysts and stakeholders, and how facilitation is embedded in the framework. We discuss our experience of using the framework, provide guidance on when to use it and conclude with future research directions.
Monks, T., Robinson, S. and Kotiadis, K. (2015). Can involving clients in simulation studies help them solve their future problems? A transfer of learning experiment. Euorpean Journal of Operational Research [Online] 249:919-930. Available at: http://dx.doi.org/10.1016/j.ejor.2015.08.037.It is often stated that involving the client in operational research studies increases conceptual learning about a system which can then be applied repeatedly to other, similar, systems. Our study provides a novel measurement approach for behavioural OR studies that aim to analyse the impact of modelling in long term problem solving and decision making. In particular, our approach is the first to operationalise the measurement of transfer of learning from modelling using the concepts of close and far transfer, and overconfidence. We investigate learning in discrete-event simulation (DES) projects through an experimental study. Participants were trained to manage queuing problems by varying the degree to which they were involved in building and using a DES model of a hospital emergency department. They were then asked to transfer learning to a set of analogous problems. Findings demonstrate that transfer of learning from a simulation study is difficult, but possible. However, this learning is only accessible when sufficient time is provided for clients to process the structural behaviour of the model. Overconfidence is also an issue when the clients who were involved in model building attempt to transfer their learning without the aid of a new model. Behavioural OR studies that aim to understand learning from modelling can ultimately improve our modelling interactions with clients; helping to ensure the benefits for a longer term; and enabling modelling efforts to become more sustainable.
Tako, A., Kotiadis, K., Vasilakis, C., Miras, A. and Le Roux, C. (2014). Improving patient waiting times: a simulation study of an obesity care service. Improving patient waiting times: a simulation study of an obesity care service [Online] 23:373-381. Available at: http://qualitysafety.bmj.com/content/23/5/373.full.pdf+html?sid=263781bc-affb-4216-9c69-981c7cc8fa3e.Background Obesity care services are often faced with the need to adapt their resources to rising levels of demand. The main focus of thisstudy was to help prioritise planned investments in new capacity allowing the service to improve patient experience and meet future anticipated demand. Methods We developed computer models of patient flows in an obesity service in an Academic Health Science Centre that provides lifestyle, pharmacotherapy and surgery treatment options for the UK's National Health Service. Using these models we experiment with different scenarios to investigate the likely impact of alternative resource configurations on patient waiting times. Results Simulation results show that the timing and combination of adding extra resources (eg, surgeons and physicians) to the service are important. For example, increasing the capacity of the pharmacotherapy clinics equivalent to adding one physician reduced the relevant waiting list size and waiting times, but it then led to increased waiting times for surgical patients. Better service levels were achieved when the service operates with the resource capacity of two physicians and three surgeons. The results obtained from this study had an impact on the planning and organisation of the obesity service. Conclusions Resource configuration combined with demand management (reduction in referral rates) along the care service can help improve patient waiting time targets for obesity services, such as the 18 week target of UK's National Health Service. The use of simulation models can help stakeholders understand the interconnectedness of the multiple microsystems (eg, clinics) comprising a complex clinical service for the same patient population, therefore, making stakeholders aware of the likely impact of resourcing decisions on the different microsystems.
Monks, T., Robinson, S. and Kotiadis, K. (2014). Learning from discrete-event simulation: Exploring the high involvement hypothesis. European Journal of Operational Research [Online] 235:195-205. Available at: http://www.sciencedirect.com/science/article/pii/S0377221713008047.Discussion of learning from discrete-event simulation often takes the form of a hypothesis stating that involving clients in model building provides much of the learning necessary to aid their decisions. Whilst practitioners of simulation may intuitively agree with this hypothesis they are simultaneously motivated to reduce the model building effort through model reuse. As simulation projects are typically limited by time, model reuse offers an alternative learning route for clients as the time saved can be used to conduct more experimentation. We detail a laboratory experiment to test the high involvement hypothesis empirically, identify mechanisms that explain how involvement in model building or model reuse affect learning and explore the factors that inhibit learning from models. Measurement of learning focuses on the management of resource utilisation in a case study of a hospital emergency department and through the choice of scenarios during experimentation. Participants who reused a model benefitted from the increased experimentation time available when learning about resource utilisation. However, participants who were involved in model building simulated a greater variety of scenarios including more validation type scenarios early on. These results suggest that there may be a learning trade-off between model reuse and model building when simulation projects have a fixed budget of time. Further work evaluating client learning in practice should track the origin and choice of variables used in experimentation; studies should also record the methods modellers find most effective in communicating the impact of resource utilisation on queuing.
Kotiadis, K., Tako, A. and Vasilakis, C. (2014). A participative and facilitative conceptual modelling framework for discrete event simulation studies in healthcare. Journal of the Operation Research Society [Online] 65:197-213. Available at: http://www.palgrave-journals.com/jors/journal/v65/n2/abs/jors2012176a.html.Existing approaches to conceptual modelling (CM) in discrete-event simulation do not formally support the participation of a group of stakeholders. Simulation in healthcare can benefit from stakeholder participation as it makes possible to share multiple views and tacit knowledge from different parts of the system. We put forward a framework tailored to healthcare that supports the interaction of simulation modellers with a group of stakeholders to arrive at a common conceptual model. The framework incorporates two facilitated workshops. It consists of a package including: three key stages and sub-stages; activities and guidance; tools and prescribed outputs. The CM framework is tested in a real case study of an obesity system. The benefits of using this framework in healthcare studies and more widely in simulation are discussed. The paper also considers how the framework meets the CM requirements.
Kotiadis, K. (2017). Soft Systems Methodology. In: De Savigny, D., Blanchet, K. and Adam, T. eds. Applied Systems Thinking for Health Systems Research: A Methodological Handbook. Open University Press.
Kotiadis, K. and Mingers, J. (2014). Combining Problem Structuring Methods with Simulation: The Philosophical and Practical Xhallenges. In: Brailsford, S., Churilov, L. and Dangerfield, B. eds. Discrete Event Simulation and System Dynamics for Management Decision Making. Chichester: John Wiley, pp. 52-75.Combinations of problem structuring methods with hard OR methodologies are seldom described in the literature. This chapter reflects on the barriers to such combinations that can be seen at the philosophical level - paradigm incommensurability - and cognitive level - type of personality and difficulty of switching paradigm. The chapter examines the combination of soft systems methodology and discrete-event simulation within an intermediate care case study.
Conference or workshop item
Tako, A. and Kotiadis, K. (2018). Participative Simulation (Partisim): A Facilitated Simulation Approach for Stakeholder Engagement. In: 2018 Winter Simulation Conference (WSC). IEEE, pp. 192-206. Available at: http://dx.doi.org/10.1109/WSC.2018.8632434.Facilitated discrete event simulation offers an alternative mode of engagement with stakeholders (clients) in simulation projects. It is particularly beneficial when modeling systems with complex behavior, involving many stakeholders with plurality of opinions and objectives. PartiSim - short for Participative Simulation - is a facilitated modeling approach developed to support simulation projects through a framework, stakeholder-oriented tools, and manuals in facilitated workshops. This tutorial describes the PartiSim approach, available for analysts and simulation modelers to use. A PartiSim study includes six stages, four of which involve facilitated workshops. PartiSim has been developed and tested through working with health care organizations. It can, however, be applied to analyze operational problems in any other context within the services and manufacturing domains. This tutorial introduces PartiSim by describing the PartiSim framework and tools, some applications and example tools, a roadmap to adopting it and concludes with some tips for potential users.
Kotiadis, K. (2016). Towards Self-Adaptive Discrete Event Simulation (SADES). In: 8th Simulation Workshop. UK OR Society, pp. 1-11.Systems that benefit from the ongoing use of simulation, often require considerable input by the modeller(s) to update and maintain the models. This paper proposes automating the evolution of the modelling process for discrete event simulation (DES) and therefore limiting the majority of the human modeller's input to the development of the model. This mode of practice could be named Self-Adaptive Discrete Event Simulation (SADES). The research is driven from ideas emerging from simulation model reuse, automations in the modelling process, real time simulation, dynamic data driven application systems, autonomic computing and self-adaptive software systems. This paper explores some of the areas that could inform the development of SADES and proposes a modified version of the MAPE-K feedback control loop as a potential process. The expected outcome from developing SADES would be a simulation environment that is self-managing and more responsive to the analytical needs of real systems.
Kotiadis, K. and Tako, A. (2016). A Facilitation Workshop for the Implementation Stage: A Case Study in health care. In: 8th Simulation Workshop. pp. 165-174.Research on facilitation in discrete event simulation (DES) is gathering pace but there is still a need to put forward real examples to explain the process to newcomers. Most of the research has focussed on facilitation in the initial stages of the simulation modelling process. In this paper we focus on one of the postmodel coding stages. More specifically we focus on the implementation stage, the final stage in the modelling process. The primary contributions of this paper are the description of the process followed and the introduction of tools that can be used during this stage to support workshop activities. A real case study is provided describing the sequence of the interactions undertaken in the workshop. Extracts from the transcripts are also included, with the view to bringing evidence of the stakeholders' involvement and their mood during the workshop. The paper concludes with a discussion on the process followed and the importance of using tools in this stage.