Empirical agent-based modelling of everyday pro-environmental behaviours at work

We report on agent-based modelling work in the LOCAW project (Low Carbon at Work: Modelling Agents and Organisations to Achieve Transition to a Low Carbon Europe). The project explored the effectiveness of various backcasting scenarios conducted with case study organisations in bringing about pro-environmental change in the workforce in the domains of transport, energy use and waste. The model used qualitative representations of workspaces in formalising each scenario, and decision trees learned from questionnaire responses to represent decision-making. We describe the process by which the decision trees were constructed, noting that the use of decision trees in agent-based models requires particular considerations owing to the potential use of explanatory variables in model dynamics. The results of the modelling in various scenarios emphasise the importance of structural environmental changes in facilitating everyday pro-environmental behaviour, but also show there is a role for psychological variables such as norms, values and efficacy. As such, the topology of social interactions is a potentially important driver, raising the interesting prospect that both workplace geography and organisational hierarchy have a role to play in influencing workplace pro-environmental behaviours

Using agent based simulation to empirically examine complexity in carbon footprint business process

Through the critical analysis of the extant literature, it is observed that Simulation is widely used as a research method in Natural Sciences, Engineering and Social Sciences, in addition to argumentation and formalisation as the third way of carrying out research. Simulation is not so widely used in Business and Management research as it ought to have been, though this is changing for the better with the technological advances in computers and their computational power. These technological advances enhance the capability of theoretical research models, in defining a problem and their use in empirically examining a solution to the problem in simulated reality, like never before. Management journal searches for “Simulation and Complexity Theory” returned nil or zero returns, which explain that this combination is not popular in management research, though they are used individually more often. The major objective of this paper is to analyse some of the conceptual (or theoretical) and methodological (or empirical) contributions that Agent Based Simulation and Complexity Theory can make to the business and management community in their business process related research In view of this, some basic ideas are discussed of using Agent Based Simulation as a method in Business and Management Studies research and how an Agent Based Model can be applied to a business process as complex as Carbon Footprint. It is in this context that the use of Complexity as the base theory to empirically examine a business process is discussed. Throughout this article, our research on complex adaptive systems (e.g., Accounting Information System) in continuously changing organisations managing complex business processes (e.g., Carbon Footprint business process) is considered as the basis for illustrating some of the concepts. Through this article, avenues for further management research using these tools and methodology are suggested

Theory of deferred action: Agent-based simulation model for designing complex adaptive systems

Deferred action is the axiom that agents act in emergent organisation to achieve predetermined goals. Enabling deferred action in designed artificial complex adaptive systems like business organisations and IS is problematical. Emergence is an intractable problem for designers because it cannot be predicted. We develop proof-of-concept, conceptual proto-agent model, of emergent organisation and emergent IS to understand better design principles to enable deferred action as a mechanism for coping with emergence in artefacts. We focus on understanding the effect of emergence when designing artificial complex adaptive systems by developing an exploratory proto-agent model and evaluate its suitability for implementation as agent-based simulation

Modelling Socially Intelligent Agents

The perspective of modelling agents rather than using them for a specificed purpose entails a difference in approach. In particular an emphasis on veracity as opposed to efficiency. An approach using evolving populations of mental models is described that goes some way to meet these concerns. It is then argued that social intelligence is not merely intelligence plus interaction but should allow for individual relationships to develop between agents. This means that, at least, agents must be able to distinguish, identify, model and address other agents, either individually or in groups. In other words that purely homogeneous interaction is insufficient. Two example models are described that illustrate these concerns, the second in detail where agents act and communicate socially, where this is determined by the evolution of their mental models. Finally some problems that arise in the interpretation of such simulations is discussed

Responsibility modelling for civil emergency planning

This paper presents a new approach to analysing and understanding civil emergency planning based on the notion of responsibility modelling combined with HAZOPS-style analysis of information requirements. Our goal is to represent complex contingency plans so that they can be more readily understood, so that inconsistencies can be highlighted and vulnerabilities discovered. In this paper, we outline the framework for contingency planning in the United Kingdom and introduce the notion of responsibility models as a means of representing the key features of contingency plans. Using a case study of a flooding emergency, we illustrate our approach to responsibility modelling and suggest how it adds value to current textual contingency plans

A Generic Agent Organisation Framework For Autonomic Systems

Autonomic computing is being advocated as a tool for managing large, complex computing systems. Specifically, self-organisation provides a suitable approach for developing such autonomic systems by incorporating self-management and adaptation properties into large-scale distributed systems. To aid in this development, this paper details a generic problem-solving agent organisation framework that can act as a modelling and simulation platform for autonomic systems. Our framework describes a set of service-providing agents accomplishing tasks through social interactions in dynamically changing organisations. We particularly focus on the organisational structure as it can be used as the basis for the design, development and evaluation of generic algorithms for self-organisation and other approaches towards autonomic systems

Emergence of District-Heating Networks; Barriers and Enablers in the Development Process

Infrastructure provision business models that promise resource efficiencies and additional benefits, such as job creation, community cohesion and crime reduction exist at sub-national scales. These local business models, however, exist only as isolated cases of good practice and their expansion and wider adoption has been limited in the context of many centralised systems that are currently the norm. In this contribution, we present a conceptual agent based model for analysing the potential for different actors to implement local infrastructure provision business models. The model is based on agents’ ability to overcome barriers that occur throughout the development (i.e. feasibility, business case, procurement, and construction), and operation and maintenance of alternative business models. This presents a novel approach insofar as previous models have concentrated on the acceptance of alternative value provision models rather than the emergence of underlying business models. We implement the model for the case study of district heating networks in the UK, which have the potential to significantly contribute to carbon emission reductions, but remain under-developed compared with other European countries