Management Science

System dynamics, systems thinking, and soft operations research (soft OR) all aspire to understanding and improvement of systems. In all, the first step interprets the real world into a description used in following stages. In system dynamics, description leads to equations of a model, simulation to understand dynamic behavior, evaluation of alternative policies, education and choice of a better policy, and implementation. Case studies, systems thinking, and soft OR usually lack the discipline of explicit model creation and simulation and so rely on subjective use of unreliable intuition for evaluating the complex structures that emerge from the initial description of the real system. Nevertheless, systems thinking and soft OR, with emphasis on eliciting information from real-world participants, should contribute useful insights to system dynamics. Conversely, the model creation and simulation stages of system dynamics should contribute rigor and clarity to systems thinking and soft OR. This paper discusses "systems thinking" and "soft operations research" (soft OR) as related to system dynamics. The next section briefly presents a system dynamics context within which to consider systems thinking and soft OR.

Abstract.  This paper offers an insight into the games software development process from a time perspective by drawing on an in-depth study in a games development organization. The wider market for computer games now exceeds the annual global revenues of cinema. We have, however, only a limited scholarly understanding of how games studios produce games. Games projects require particular attention because their context is unique. Drawing on a case study, the paper offers a theoretical conceptualization of the development process of creative software, such as games software. We found that the process, as constituted by the interactions of developers, oscillates between two modes of practice: routinized and improvised, which sediment and flux the working rhythms in the context. This paper argues that while we may predeterminately lay down the broad stages of creative software development, the activities that constitute each stage, and the transition criteria from one to the next, may be left to the actors in the moment, to the temporality of the situation as it emerges. If all development activities are predefined, as advocated in various process models, this may leave little room for opportunity and the creative fruits that flow from opportunity, such as enhanced features, aesthetics and learning.

There is little research into the emotional dimension of creative industry personnel, such as computer game designers, and how emotions relate to their creative practices and work-related events. Such socioemotional work is the focus of this chapter. There is a practice-centered relevance to this topic too-it is reported that there exists a poor quality of life in many global game studios. Given our deficient knowledge of emotions in computer game development, and the practical resonance of this topic, our key research question is: What emotions, creative practices and work-related events characterize emotional journeys in computer game design teams, and how do these characteristics inter-relate? To explore and answer this research question, we draw on an in-depth field study of a computer games studio in Singapore. The chapter offers a theory of emotion-mediated improvisation as a coping model for the tumultuous emotional journeys that game developers endure.

Most existing Intelligent Tutoring Systems (ITSs) are built around cognitive learning theories, such as Ohlsson’s theory of learning from performance errors and Anderson’s ACT theories of skill acquisition, which focus primarily on providing negative feedback, facilitating learning by correcting errors. Research into the behavior of expert tutors suggest that experienced tutors use positive feedback quite extensively and successfully. This paper investigates positive feedback; learning by capturing and responding to correct behavior, supported by cognitive learning theories. Our aim is to develop and implement a systematic approach to delivering positive feedback in ITSs. We report on an evaluation study done in the context of SQL-Tutor, in which the control group used the original version of the system giving only negative feedback, while the experimental group received both negative and positive feedback. Results show that the experimental group students needed significantly less time to solve the same number of problems, in fewer attempts compared to those in the control group. Students in the experimental group also learn approximately the same number of concepts as students in the control group, but in much less time. This indicates that positive feedback facilitates learning and improves the effectiveness of learning in ITSs.

Ensemble methods represent an approach to combine a set of models, each capable of solving a given task, but which together produce a composite global model whose accuracy and robustness exceeds that of the individual models. Ensembles of neural networks have traditionally been applied to machine learning and pattern recognition but more recently have been applied to forecasting of time series data. Several methods have been developed to produce neural network ensembles ranging from taking a simple average of individual model outputs to more complex methods such as bagging and boosting. Which ensemble method is best; what factors affect ensemble performance, under what data conditions are ensembles most useful and when is it beneficial to use ensembles over model selection are a few questions which remain unanswered. In this paper we present some initial findings using neural network ensembles based on the mean and median applied to forecast synthetic time series data. We vary factors such as the number of models included in the ensemble and how the models are selected, whether randomly or based on performance. We compare the performance of different ensembles to model selection and present the results.

Literature analysing reasons for Consumer Food Waste (CFW) revealed that it cannot be reduced to consumer behaviour alone. In fact, CFW should not be conceptualised as the problem but as a symptom of a food system that oversupplies and encourages consumerism. This research focuses on preventing CFW in the United Kingdom (UK), as a representative of a developed country, by improving the traditional food provisioning system to better integrate production and consumption. To achieve this, five stages are identified to design a sustainable product service system (PSS) capable of supporting consumers to better manage their food operations: (1) strategic analysis of current food provisioning system, (2) exploring system level innovations leading to minimisation of CFW, (3) refinement and selection of PSS, (4) designing the most promising PSS from an environmental, economic and social perspective, and (5) evaluating designed PSS. This paper considers the first of these stages, reviews reasons for and existing solutions to CFW, and provides a strategic analysis of the current food provisioning system to identify characteristics that could be exploited within a new PSS. Initial investigations reveal applicability of PSS concept to the food provisioning system and potential for reduction of CFW if core causes are addressed.

One of the most prominent challenges commonly acknowledged by modern manufacturing industries is “how to produce more with fewer resources?” Nowhere is this more true than in the food sector due to the recent concerns regarding the long-term availability and security of food products. The unique attributes of food products such as the need for fresh perishable ingredients, health risks associated with inappropriate production environment, stringent storage and distributions requirements together with relatively short post-production shelf-life makes their preparation, production and supply considerably different to other manufactured goods. Furthermore, the impacts of climate change on our ability to produce food, the rapidly increasing global population, as well as changes in demand and dietary behaviours both within developed and developing countries urgently demands a need to change the way we grow, manufacture and consume our food products. This paper discusses a number of key r...

In the age globalization, the concept of attractiveness is of crucial importance to territories that are involved in a fierce competition over attracting geographically mobile investments. Attractiveness is a new imperative for creating jobs, increasing investment in industry and services, accessing the global market, and developing new technologies. Attracting potential investors is therefore a major objective for all territories, and more specifically developing countries. The attractiveness of territories is based on a number of location advantages that are of fundamental importance, as companies only select the sites that enable them to reinforce their competitiveness. In this context, promoting and welcoming foreign investments is a multidimensional challenge in which the identification of perceived attractiveness to small and medium-sized enterprises occupies a prominent place. In this work, we discuss and explore the determinants on which foreign companies base their choice t...

A hybrid simulation model is a simulation model that is formed from at least two different simulation modelling methods (e.g. discrete event, system dynamics, agent-based). The use of different simulation modelling methods in one model requires modellers to specify additional model elements. This paper
discusses three elements, namely, the modules, module interfaces and updating rules. Each module may use a different simulation method. The interface between modules defines the information that will be passed between them (including aggregation and disaggregation). The updating rules define how the information sent by one module affects other modules. These three elements are explained using a case
study of a blood supply chain simulation model for low- and middle-income countries (LMIC) which has different characteristics and challenges in comparison to the typical blood supply chain in high-income countries (HIC).

In a simulation project, a good conceptual model representation is critical for communicating conceptual
models between stakeholders. A conceptual model describes the problem domain and model specifications. The description of the problem domain includes the objectives, inputs, outputs, content, assumptions and simplifications made in the model. The model specifications are used to specify the model’s behaviour.
This article focuses on the representation of the model content (structure, boundary and level of
detail) component of an agent-based simulation (ABS) model. For this, we propose the use of Business
Process Model and Notation (BPMN) from the Object Management Group. A Web-based visual modeling
tool has been developed using JavaScript to demonstrate how BPMN can be used to represent an ABS
conceptual model and how the tool translates the conceptual model into code ready for execution using
Repast HPC.

There seems to be paucity in the research into the collection of data for use in simulation. This is rather unfortunate since data quality and availability are two of the most challenging issues in many simulation projects. This paper discusses how simulation practitioners identify and collect data for simulation projects. The data was collected from ORH Ltd, a management consultancy company using participant observations method and an experiment using a mock case scenario. From the observation, we produce a generic data identification and collection method. The method is evaluated using a real project conducted for a UK Ambulance Service. The experiment reveals variations in the data identification process which are influenced by the role and the level of experience of modellers.

different stakeholders in the project, especially in the early stages. Good documentation or representation is essential for communicating conceptual models between stakeholders effectively. Despite the lack of a single accepted definition for a conceptual model, most definitions agree that a conceptual model contains a set of components, each of which specifies different aspects of a conceptual model. This paper advocates the use of a standard multi-faceted representation of conceptual models. A number of diagrams are proposed to represent each of the conceptual model components. Our intention is to initiate discussion and the development of a standard multi-faceted conceptual model representation that will benefit stakeholders involved in a simulation project. A case study in health-care is used to show how the proposed unified conceptual modelling representation can be applied in practice.

This paper advocates the use of a formal framework for analyzing simulation performance. Simulation performance is characterized based on the three simulation development process boundaries: physical system, simulation model, and simulator implementation. Firstly, we formalize simulation event ordering using partially ordered set theory. A simulator implements a simulation event ordering, and incurs implementation overheads when enforcing event ordering at runtime. Secondly, we apply our formalism to extract and formalize the simulation event orderings of both sequential and parallel simulations. Thirdly, we propose the relation stricter and a measure called strictness for comparing and quantifying the degree of event dependency of simulation event orderings respectively.

Research into the application of simulation modeling in healthcare is thriving. This is not the case for its step sister, social care, although it has long been recognized that the interface between healthcare and social care often causes problems that affect the performance at both sides. This paper presents a literature review of simulation modeling for the provision of social care services. It discusses the gap between findings from the literature and challenges in social care policies. Potential areas to which simulation modelers can contribute are highlighted. The literature shows that simulation modeling has contributed in areas such as demand, supply, service delivery methods (including the interface between care services and other services), and cost/financial modeling. However, a gap between the work reported in the literature and the challenges in social care policies exists. Hence, more work needs to be done to close the gap.