Can involving clients in simulation studies help them solve their future problems? A transfer of learning experiment

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

Can we learn from wrong simulation models? A preliminary experimental study on user learning

A number of authors believe that wrong models can be useful, providing learning opportunities for their users. This paper details an experiment on model complexity, investigating differences in learning after using a simplified versus an adequate version of the same model. Undergraduate students were asked to solve a resource utilization task for an ambulance service. The treatment variables were defined as the model types used (complex, simple, and no model). Two questionnaires (before and after the process) and a presentation captured participants' attitudes towards the solution. Results suggest differences in learning were not significant, while simple model users demonstrated a better understanding of the problem. This paper consists of a preliminary behavioural operational research study that contributes towards identifying the value of wrong simulation models from the perspective of model users

Behavioural operational research: returning to the roots of the OR profession

We witness and welcome the resurgence of interest in the study of behavioural issues in the conduct of operational research (OR). The use of the term ‘resurgence’ is deliberate: the consideration of human factors in models and model-supported processes can be traced back to debates in the 1960s and 1970s (e.g. Ackoff, 1977; Churchman, 1970; Dutton & Walton, 1964). However, whilst the socially situated nature of OR in practice has long been recognised (e.g. Keys, 1997), it was not until the wave of recent activity triggered by Hamalainen et al.’s (2013) paper in this journal that the role and impact of behaviour in OR practice regained centrality in academic and practitioners circles alike

Techne and techniques for engaging in a socially complex world

This paper addresses the challenge for Operational Research (OR) in extending out from traditional forms of modelling towards a more relational form of modelling. The challenge comes from OR practice becoming more transformative in nature, which puts more emphasis on reflective practice, people and relationships. Staged Appreciation is proposed as an overall guiding framework and selected illustrative techniques are presented for engaging with social complexity; so-called “wicked” problems. Systems Thinking techniques, guided by Staged Appreciation add an insightful new dimension to knowledge sharing for understanding, and for reflecting upon the intricacies involved in socially complex situations. There are analytical advantages of standing apart from complexity. Staged Appreciation complements this analytical standpoint by asking analysts to take a more reflective view of their own working relationships, being more a part of the socially complex problem as well as standing apart from it. Staged Appreciation offers a reflective framework for working with Systems Thinking techniques and together they complement traditional practice. The proposal and suggestions aim to support analysts to adopt a more reflective and relational view of a complex problematic situation in order to see it “as a whole.” The paper draws lessons from holism, reflective practice and subjective analysis

Discrete event simulation in livestock management

The agricultural sector in the UK is facing unprecedented challenges as a result of changes in the macroeconomic environment and the future of the livestock sub-sector is particularly uncertain. Farmer's businesses and livelihoods are at risk with the planned removal of subsidy payments as a consequence of emerging agricultural policy change as a result of Brexit. Farmers are forced to seek adaptive strategies to survive because of changing socio-political circumstances. This study explores the potential of an analytical tool, Discrete Event Simulation (DES) applied within the agricultural sub-sector of livestock management. It utilises a multi methodological approach using both interviews with farmers and a simulation of a real case; Colclough livestock farm, located in Yorkshire, England. The findings show that DES can be used by livestock farmers, helping to simulate potential growth strategies and observe the impact in relation to existing farm processes. Barriers to the sector wide adoption of new farm technologies are presented. This research captures the current views of farmers regarding technology adoption, showing empirically that technologies and software exist which can improve economic performance of farming enterprises, however, contingent factors, such as age, attitudes, skillsets and broadband connectivity, limits successful adoption

Aplicação da simulação de eventos discretos como ferramenta computacional de análise e tomada de decisão em processos de automatização de ensaios químicos em laboratórios de análise mineral / Application of discrete events simulation as a computational tool for analysis and make a decision in chemical test automation processes in mineral analysis laboratories

 A queda de 70% do preço das commodities de minério de ferro entre os anos de 2011 e 2016 motivou as empresas do ramo a reverem seus processos produtivos, visando reduzir ao máximo o desperdício de capital. Uma das possíveis soluções seria a automatização robótica, porém, tal inovação necessitaria de um alto investimento financeiro. Este artigo tem como objetivo geral demonstrar as análises e propor melhorias para o fluxo de trabalho do laboratório de análise mineral em uma empresa mineradora de grande porte, por meio da simulação de um modelo de eventos discretos como auxilio à tomada de decisões quanto ao capital expanditure. O modelo desenvolvido foi simulado no software Arena®, inicialmente com a coleta dos dados históricos, como tempos e fluxos dos processos, quantidades de amostras, taxa de utilização de recursos, dentre outros. Posteriormente, validou-se o modelo desenvolvido simulando um cenário base, que representa a realidade do laboratório sem a automatização. Em seguida, foram simulados outros três cenários que consideraram o fluxo do processo com a implementação da automação diferenciando a disponibilidade de recursos planejados em relação ao projeto inicial. A análise do fluxo foi feita com base em três indicadores de desempenho: quantidade de análises de amostras realizadas, taxa de utilização dos funcionários e tempo médio de análise das amostras. Os resultados das simulações evidenciaram que a automatização do laboratório seria benéfica para a empresa, com melhoria expressiva dos indicadores quando estiver em conformidade com a capacidade produtiva planejada. O modelo de simulação desenvolvido neste artigo serve de referência para análise de processos de qualquer tipo de laboratório, independentemente de ser um laboratório de análise mineral, sendo uma importante ferramenta de auxílio aos gestores na tomada de decisão

Facilitated post-model coding in discrete event simulation (DES): a case study in healthcare

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