A method for effective use of enterprise modelling techniques in complex dynamic decision making

Effective organisational decision-making requires information pertaining to various organisational aspects, precise analysis capabilities, and a systematic method to capture and interpret the required information. The existing Enterprise Modelling (EM) and actor technologies together seem suitable for the specification and analysis needs of decision making. However, in absence of a method to capture required information and perform analyses, the decision-making remains a complex endeavour. This paper presents a method that captures required information in the form of models and performs what-if calculations in a systematic manner

A wide-spectrum approach to modelling and analysis of organisation for machine-assisted decision-making

This paper describes a modeling approach that helps to represent necessary aspects of complex socio-technical systems, such as organization, in an integrated form and provides a simulation technique for analyzing these organisations. An actor-based language is introduced and compared to a conventional simulation approach (Stock-and-Flow) by simulating aspects of a software services company

On the Dynamics of the Deployment of Renewable Energy Production Capacities

This chapter falls within the context of modeling the deployment of renewable en-ergy production capacities in the scope of the energy transition. This problem is addressed from an energy point of view, i.e. the deployment of technologies is seen as an energy investment under the constraint that an initial budget of non-renewable energy is provided. Using the Energy Return on Energy Investment (ERoEI) characteristics of technologies, we propose MODERN, a discrete-time formalization of the deployment of renewable energy production capacities. Be-sides showing the influence of the ERoEI parameter, the model also underlines the potential benefits of designing control strategies for optimizing the deployment of production capacities, and the necessity to increase energy efficiency.Peer reviewe

Jay Forrester

Jay Wright Forrester was an American engineer and management thinker. He founded System Dynamics, an approach based on computer modelling which arguably has done more than any other method to provide a practical and realistic analysis of change processes in systems. System Dynamics (SD) has been taken up across the world, initially by Forrester’s students and colleagues, but increasingly by a much wider community. It has had profound and influential applications in a range of fields, most prominently organisational management, urban planning and environmental policy. Forrester summed up his concerns and his understanding of SD in an ‘elevator pitch’ (a statement short enough to be spoken in an elevator ride) on an email list: System dynamics deals with how things change through time, which includes most of what most people find important. It uses computer simulation to take the knowledge we already have about details in the world around us and to show why our social and physical systems behave the way they do. System dynamics demonstrates how most of our own decision-making policies are the cause of the problems that we usually blame on others, and how to identify policies we can follow to improve our situation. (Forrester JW. System dynamics in the elevator. System-dynamics email list. https://www.ventanasystems.co.uk/forum/viewtopic.php?t=1787#p1964. Accessed 25 Sept 2019, 1997

A model based approach for complex dynamic decision-making

Current state-of-the-practice and state-of-the-art of decision-making aids are inadequate for modern organisations that deal with significant uncertainty and business dynamism. This paper highlights the limitations of prevalent decision-making aids and proposes a model-based approach that advances the modelling abstraction and analysis machinery for complex dynamic decision-making. In particular, this paper proposes a meta-model to comprehensively represent organisation, establishes the relevance of model-based simulation technique as analysis means, introduces the advancements over actor technology to address analysis needs, and proposes a method to utilise proposed modelling abstraction, analysis technique, and analysis machinery in an effective and convenient manner. The proposed approach is illustrated using a near real-life case-study from a business process outsourcing organisation

Future Logistics: What to Expect, How to Adapt

As a result of global societal and economic as well as technological developments logistics and supply chains face unprecedented challenges. Climate change, the need for more sustainable products and processes, major political changes, the advance of “Industry 4.0” and cyber-physical system are some of the challenges that require radical solutions, but also present major opportunities. The authors argue that logistics has to reinvent itself, not only to address these chal-lenges but also to cope with mass individualization on the one hand while exploit-ing broad-fielded business applications of artificial intelligence on the other hand. An essential challenge will be to find a compromise between these two develop-ments – in line and in combination with the known triple-bottom line for sustaina-bility – that will define supply chains and logistics concepts of the future

"Open Innovation" and "Triple Helix" Models of Innovation: Can Synergy in Innovation Systems Be Measured?

The model of "Open Innovations" (OI) can be compared with the "Triple Helix of University-Industry-Government Relations" (TH) as attempts to find surplus value in bringing industrial innovation closer to public R&D. Whereas the firm is central in the model of OI, the TH adds multi-centeredness: in addition to firms, universities and (e.g., regional) governments can take leading roles in innovation eco-systems. In addition to the (transversal) technology transfer at each moment of time, one can focus on the dynamics in the feedback loops. Under specifiable conditions, feedback loops can be turned into feedforward ones that drive innovation eco-systems towards self-organization and the auto-catalytic generation of new options. The generation of options can be more important than historical realizations ("best practices") for the longer-term viability of knowledge-based innovation systems. A system without sufficient options, for example, is locked-in. The generation of redundancy -- the Triple Helix indicator -- can be used as a measure of unrealized but technologically feasible options given a historical configuration. Different coordination mechanisms (markets, policies, knowledge) provide different perspectives on the same information and thus generate redundancy. Increased redundancy not only stimulates innovation in an eco-system by reducing the prevailing uncertainty; it also enhances the synergy in and innovativeness of an innovation system.Comment: Journal of Open Innovations: Technology, Market and Complexity, 2(1) (2016) 1-12; doi:10.1186/s40852-016-0039-

Integrating Integrated Water Management

© 2014, Thomas Telford Services Ltd. All rights reserved. The water cycle is a contiguous system interconnected with human activities. Management has tended to be fragmented across anthropocentrically defined disciplines, potentially generating unintended negative consequences. The ecosystem approach and the ecosystem services framework emphasise interlinked, albeit often overlooked, benefits that the natural environment provides for people. This enables recognition and avoidance of potential ‘negative externalities’, identification of solutions optimising benefits across multiple services, and participation of wider constituencies of stakeholders. Systemic, outcome-based approaches are inherently economically efficient, yielding greater cumulative benefits for lower transaction costs by working with natural processes. The ecosystem approach establishes geographical and socio-economic contexts for management ecosystem service outcomes, providing a broader context in which to nest established water resource management methods. The ecosystem approach can also be applied at different scales and to diverse societal activities, internalising into them the value of natural processes. It is amenable to integration into catchment-scale considerations, yet does not present these activities as subsidiary to river basin planning. The addition of ecosystem services for options appraisal in preexisting decision-support tools adapts them to better address multi-benefit goals. Shifts are required in the policy and economic environment, but engineers have an important role in promoting, applying and innovating multibenefit solutions