Browsing by Author "Varga, Liz"

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    Adaptive tension, self-organization and emergence : A complex system perspective of supply chain disruptions
    (Cranfield University, 2017-03) Tewari, Anurag; Varga, Liz
    The purpose of this thesis was to explore how microstate human interactions produce macro level self-organization and emergence in a supply disruption scenario, as well as discover factors and typical human behaviour that bring about disruptions. This study argues that the complex adaptive system’s view of complexity is most suited scholarly foundation for this research enquiry. Drawing on the dissipative structure based explanation of emergence and self-organization in a complex adaptive system, this thesis further argues that an energy gradient between the ongoing and designed system conditions, known as adaptive tension, causes supply chains to self-organize and emerge. This study adopts a critical realist ontology operationalized by a qualitative case research and grounded theory based analysis. The data was collected using repertory grid interviews of 22 supply chain executives from 21 firms. In all 167 cases of supply disruptions were investigated. Findings illustrate that agent behaviours like loss of trust, over ambitious pursuit, use of power and privilege, conspiring against best practices and heedless performance were contributing to disruption. Impacted by these behaviours, supply chains demonstrated impaired disruption management capabilities and increased disruption probability. It was also discovered that some of these system patterns and microstate agent behaviours pushed the supply chains to a zone of emergent complexity where these networks self-organized and emerged into new structures or embraced changes in prevailing processes or goals. A conceptual model was developed to explain the transition from micro agent behaviour to system level self-organization and emergence. The model described alternate pathways of a supply chain under adaptive tension. The research makes three primary research contributions. Firstly, based upon the theoretical model, this research presents a conceptualization of supply chain emergence and self-organization from dissipative structures and adaptive tension based view of complexity. Secondly, it formally introduces and validates the role of behavioural and cognitive element of human actions in a supply chain scenario. Lastly, it affirms the complex adaptive system based conceptualization of supply chain networks. These contributions succeed in providing organizations with an explanation for observed deviations in their operations performance using a behavioural aspect of human agents.
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    Aerospace Supply Chains as Evolutionary Networks of Activities: Innovation Via Risk-Sharing Partnerships
    (Blackwell Publishing Ltd, 2008-12-01T00:00:00Z) Rose-Anderssen, Christen; Baldwin, James S.; Ridgway, Keith; Allen, Peter M.; Varga, Liz
    In the aerospace industry competitive advantage is searched through product innovation. This paper sets out to explore the effects that relationship development in the commercial aerospace supply chains have on innovation and competitive advantage. A perspective of supply chains as complex activity networks is used for data analysis based on in-depth interviews in a global setting. Applying these concepts of supply chains as the interaction of multiple work activities assists in comprehending the forces of change. The processes of change are characterized by expansive learning processes of creating instruments for initializing, developing and sustaining these relationships. These processes take place in a terrain of complex power exercises. The long-term effects are totally dependent on nurturing the relationships. The findings may be useful to practitioners in understanding how implementation of successful supply chain changes may come about. It promotes risk-sharing partnerships as instruments for innovation. The paper provides evidence of changing relationships in commercial aerospace supply chains.
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    Agent based modeling of energy networks
    (Elsevier, 2014-04-03) Gonzalez de Durana, Jose Maria; Barambones, Oscar; Kremers, Enrique; Varga, Liz
    Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed.
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    An agent-based model for energy service companies
    (Elsevier Science B.V., Amsterdam., 2015-04-01T00:00:00Z) Robinson, Marguerite; Varga, Liz; Allen, Peter
    The residential housing sector is a major consumer of energy accounting for approximately one third of carbon emissions in the United Kingdom. Achieving a sustainable, low-carbon infrastructure necessitates a reduced and more efficient use of domestic energy supplies. Energy service companies offer an alternative to traditional providers, which supply a single utility product to satisfy the unconstrained demand of end users, and have been identified as a potentially important actor in sustainable future economies. An agent-based model is developed to examine the potential of energy service companies to contribute to the large scale upgrading of household energy efficiency, which would ultimately lead to a more sustainable and secure energy infrastructure. The migration of households towards energy service companies is described by an attractiveness array, through which potential customers can evaluate the future benefits, in terms of household energy costs, of changing provider. It is shown that self-financing is a limiting factor to the widespread upgrading of residential energy efficiency. Greater reductions in household energy costs could be achieved by committing to longer term contracts, allowing upgrade costs to be distributed over greater time intervals. A steadily increasing cost of future energy usage lends an element of stability to the market, with energy service companies displaying the ability to retain customers on contract expiration. The model highlights how a greater focus on the provision of energy services, as opposed to consumable products, presents a viable approach to reducing future energy costs and usage.
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    An agent-based model schema to understand how shocks to the household a ect energy consumption behaviour
    (Cranfield University, 2014-12) Wood, Katherine; Gu, Sai; Varga, Liz
    There are many factors which are understood to a ect domestic energy consumption, including: occupant demographics such as age, income and family type, occupant attitudes, peer networks and occupant-building interactions such as window opening, heating and lighting patterns. Both top-down and bottom-up modelling approaches have been used previously to represent these behavioural factors and other domestic energy usage variables such as dwelling construction. Top-down models were found to lack the granularity and exibility to accurately portray the UK domestic energy sector from the perspective of individual households. Conversely, bottom-up models were found to be more applicable to behavioural factors due to their ability to model individual entities and interactions. However, it was also identi ed that most current models only consider building construction or occupant behaviour, with few combining the two. This project aims to combine occupant behaviour and dwelling construction variables by suggesting an agent-based model implementation schema to provide insight into the domestic energy consumption system, with special interest in the e ects of life-stage changes on the household and the e ect of peer networks on the adoption of energy e ciency measures. Five `shock' groups are considered, namely, households a ected by a recent: retirement, unemployment, new child, house move or reduction in household size. A pilot survey was conducted in order to obtain results to inform model design decisions and the results are discussed.
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    Agent-based modeling of the energy network for hybrid cars
    (Elsevier, 2015-04-17) Gonzalez de Durana, Jose Maria; Barambones, Oscar; Kremers, Enrique; Varga, Liz
    Studies in complex energy networks devoted to the modeling of electrical power grids, were extended in previous work, where a computational multi-layered ontology, implemented using agent-based methods, was adopted. This structure is compatible with recently introduced Multiplex Networks which using Multi-linear Algebra generalize some of classical results for single-layer networks, to multilayer networks in steady state. Static results do not assist overly in understanding dynamic networks in which the values of the variables in the nodes and edges can change suddenly, driven by events, and even where new nodes or edges may appear or disappear, also because of other events. To address this gap, a computational agent-based model is developed to extend the multi-layer and multiplex approaches. In order to demonstrate the benefits of a dynamical extension, a model of the energy network in a hybrid car is presented as a case study.
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    Anaerobic digestion: a prime solution for water, energy and food nexus challenges
    (Elsevier, 2017-09-19) Haltas, Ismail; Suckling, James; Soutar, Iain; Druckman, Angela; Varga, Liz
    We solve the problem of identifying one or more optimal patterns of anaerobic digestion (AD) installation across the UK, by considering existing installations, the current feedstock potential and the project growth of the potential via population, demography and urbanization. We test several scenarios for the level of adoption of the AD operations in the community under varying amounts of feedstock supply, which may arise from change in food waste or energy crops generation via other policies and incentives. For the most resilient scales of solutions, we demonstrate for the UK the net energy production (bio-gas and electricity) from AD (and so the avoided emissions from grid energy), the mass of bio-waste processed (and avoided land-fill), and the quantum of digestate produced (as a proxy for avoided irrigation and fertilizer production). In order to simulate the AD innovation within WEF nexus we use agent based modelling (ABM) owing to its bottom-up approach and capability of modelling complex systems with relatively low level data and information.
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    The Coevolution Of The Firm And The Supply Network: A Complex Systems Perspective
    (Cranfield University, 2009-04) Varga, Liz; Allen, Peter M.
    A complex adaptive systems approach has been permeating organizational studies and the field of supply network management helping to describe and explain supply network dynamics and emergent inter-firm structures. This has improved our theoretical knowledge of the nature of supply networks transforming raw materials into products, within a constantly changing environment. From the early days of simple structures, describing bi-lateral, local arrangements between firms for the creation of relatively simple products, we are now in an environment of various supply network archetypes, describing different global sourcing regimes of highly integrated, sophisticated products within multi-tier networks. This thesis is a study of the coevolution of the firm and supply network in the commercial aerospace manufacturing sector producing jetliners of 100 or more seats. One of the contributions of this research is to demonstrate how the holistic approach of complexity science can be applied to describe, understand and gain new insight into the coevolution of the firm and the supply network. Based on the findings of multiple interviews and questionnaires in eight global aerospace firms across multiple supply chain tiers, this research finds high-performing clusters of inter-firm characteristics, plus the aspects of structure and integration which deliver the supply network performance. Practitioners can use these specific results to examine their own firms and the new coevolutionary conceptual framework developed in the thesis may aid future research studies of complex adaptive systems in practice. The simple survey design and analysis method used in the final research stage of this research, has the potential for use in other industries, markets and other complex adaptive systems generally to examine performance outcomes and the effects of having or adopting new inter-firm characteristics. Finally, implications for policy include the potential to legitimize supply networks in order to stimulate competition and innovation in the economy.
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    A collective mindfulness perspective of information sharing in the blood supply chain.
    (Cranfield University, 2018-11) Lusiantoro, Luluk; Yates, Nicky; Varga, Liz
    Purpose: This thesis aims to determine and unravel the underlying mechanisms of how inter-organisational information sharing influences blood safety and availability in the dyadic blood supply chain in normal, high tempo, and emergency conditions. Design/methodology/approach: Grounded in the critical realism paradigm and the perspective of high reliability theory particularly the collective mindfulness concept, this thesis uses an embedded multiple case study designed for theory elaboration. A combined retroductive-abductive and the basic qualitative description has been adopted as a research strategy. Two contrasting cases with three embedded cases for each main case are selected using convenient and context-based approaches, representing a centralised and tightly regulated blood supply chain in the UK as well as a decentralised and loosely regulated blood supply chain in Indonesia. The data are collected using the triangulation of semi- structured interviews, walkthroughs, and other supporting documents including artefacts and archives. Template analysis coupled with within-case and cross- case analyses are then used to analyse the data. Findings: This thesis finds that inter-organisational information sharing influences blood safety and availability through the dynamic enactments of collective mindfulness principles that reflect the inter-organisational information sharing behaviour across the operational conditions. It also finds that the blood supply chain actors in the centralised and tightly regulated context are collectively more mindful when sharing information than those in the decentralised and loosely regulated context, so that more positive changes in the blood safety and availability performance are observed in the former compared to that in the latter context. Interestingly, whilst the data reveal an emerging mechanism of heedful interrelating across a range of operational conditions, this thesis also reveals the fact that inter-organisational information sharing does not necessarily lead to positive changes in blood safety and availability. In fact, negatively enacted collective mindfulness principles can lead inter-organisational information sharing to unimproved and even potentially worse blood safety and availability performance. Originality/value: The primary contribution of this thesis lies in understanding the underlying mechanisms of how inter-organisational information sharing influences blood safety and availability in the dyadic blood supply chain across a range of operational conditions. Whilst offering practical and conceptually relevant knowledge to the blood supply chain literature, it informs the wider supply chain literature on the different collective mindfulness principles that make inter- organisational information sharing influence supply chain performance across a range of operational conditions. The use of the collective mindfulness concept offers a novel perspective that extends the current discussion on the effectiveness of that information sharing for supply chains.
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    A complex systems perspective on innovation, investment and regulation of evolving telecommunications networks
    (2017-09) Durmagambetov, Yerlan; Varga, Liz
    This thesis is a Doctoral Thesis of the International Executive Doctorate Programme (DBA) at the School of Management, Cranfield University, UK. The purpose of the study is to present the results of the research dedicated to the topic of Infrastructure Sharing, a common method to make use of the limited infrastructure resources of many stakeholders. The research aims to develop a decision support tool for a National Regulating Authority (NRA) on the basis of a software simulation representing infrastructure in use as complex systems consisting of agent and infrastructure networks. By applying a computational Agent-Based Modelling (ABM) approach to policy decisions, i.e. influence of Duct and Pole Access (DPA) to incumbent telecommunication infrastructures, the research investigates regulatory considerations that stimulate the development of alternative networks. The final deliverable of the research is a simulation tool that provides a solid foundation for simulating experiments, which allows analysis of demand for broadband services by different subgroups of users. The results of the study are of value for regulators, practitioners, representatives of telecommunication and other network industries, and scholars who deal with the topic of sustainable infrastructure development and recognise the value of a complex system perspective.
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    Control of supercritical organic Rankine cycle based waste heat recovery system using conventional and fuzzy self-tuned PID controllers
    (Springer, 2019-08-19) Chowdhury, Jahedul Islam; Thornhill, David; Soulatiantork, Payam; Hu, Yukun; Balta-Ozkan, Nazmiye; Varga, Liz; Nguyen, Bao Kha
    This research develops a supercritical organic Rankine cycle (ORC) based waste heat recovery (WHR) system for control system simulation. In supercritical ORC-WHR systems, the evaporator is a main contributor to the thermal inertia of the system, which is greatly affected by transient heat sources during operation. In order to capture the thermal inertia of the system and reduce the computation time in the simulation process, a fuzzy-based dynamic evaporator model was developed and integrated with other component models to provide a complete dynamic ORC-WHR model. This paper presents two control strategies for the ORC-WHR system: evaporator temperature control and expander output control, and two control algorithms: a conventional PID controller and a fuzzy-based self-tuning PID controller. The performances of the proposed controllers are tested for set point tracking and disturbance rejection ability in the presence of steady and transient thermal input conditions. The robustness of the proposed controllers is investigated with respect to various operating conditions. The results show that the fuzzy self-tuning PID controller outperformed the conventional PID controller in terms of set point tracking and disturbance rejection ability at all conditions encountered in the paper.
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    Data underpinning research article "Optimising Renewable Energy Integration in New Housing Developments with Low Carbon Technologies"
    (Cranfield University, 2021-02-09 00:33) Chowdhury, Jahedul; Ozkan, Nazmiye; Hart, Phil; Varga, Liz; Hu, Yukun
    This file includes data for energy demand and generation profile for different house types in the UK. It also contains data for daily average solar irradiance for typical UK weather conditions that were used for calculating PV outputs.
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    Data underpinning research article "Techno-environmental analysis of battery storage for grid level energy services"
    (Cranfield University, 2020-07-17 09:07) Chowdhury, Jahedul; Ozkan, Nazmiye; Goglio, Pietro; Hu, Yukun; Varga, Liz; McCabe, Leah
    This file includes data from the National Grid, UK for electricity supply and demand which was modified according to the research methodology laid out in the paper here (https://doi.org/10.1016/j.rser.2020.110018). Also, all the data needed for reproducing figures presented in the journal article are also included in the data file.
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    Economic evaluation of mental health effects of flooding using Bayesian networks
    (MDPI, 2021-07-13) Sedighi, Tabassom; Varga, Liz; Hosseinian-Far, Amin; Daneshkhah, Alireza
    The appraisal of appropriate levels of investment for devising flooding mitigation and to support recovery interventions is a complex and challenging task. Evaluation must account for social, political, environmental and other conditions, such as flood state expectations and local priorities. The evaluation method should be able to quickly identify evolving investment needs as the incidence and magnitude of flood events continue to grow. Quantification is essential and must consider multiple direct and indirect effects on flood related outcomes. The method proposed is this study is a Bayesian network, which may be used ex-post for evaluation, but also ex-ante for future assessment, and near real-time for the reallocation of investment into interventions. The particular case we study is the effect of flood interventions upon mental health, which is a gap in current investment analyses. Natural events such as floods expose people to negative mental health disorders including anxiety, distress and post-traumatic stress disorder. Such outcomes can be mitigated or exacerbated not only by state funded interventions, but by individual and community skills and experience. Success is also dampened when vulnerable and previously exposed victims are affected. Current measures evaluate solely the effectiveness of interventions to reduce physical damage to people and assets. This paper contributes a design for a Bayesian network that exposes causal pathways and conditional probabilities between interventions and mental health outcomes as well as providing a tool that can readily indicate the level of investment needed in alternative interventions based on desired mental health outcomes.
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    Energy and Complexity (Editorial)
    (Wiley, 2018-06-13) Lukszo, Zofia; Bompard, Ettore Bompard; Hines, Paul; Varga, Liz
    Sustainable energy systems are complex sociotechnical systems with a social network of many players that “together” develop, operate, and maintain the technical infrastructure. No single player controls the system, but their actions are coordinated through a range of institutions—informal and formal rules—and regulations. As the control is distributed among actors, the overall system behaviour (at different time scales) emerges from operating practices and characteristics, from (dis)investment decisions, and from other aspects of the players’ strategies.
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    Energy and complexity: new ways forward
    (Elsevier, 2015-01-15) Bale, Catherine S. E.; Varga, Liz; Foxton, Timothy J.
    The purpose of this paper is to review the application of complexity science methods in understanding energy systems and system change. The challenge of moving to sustainable energy systems which provide secure, affordable and low-carbon energy services requires the application of methods which recognise the complexity of energy systems in relation to social, technological, economic and environmental aspects. Energy systems consist of many actors, interacting through networks, leading to emergent properties and adaptive and learning processes. Insights on these type of phenomena have been investigated in other contexts by complex systems theory. However, these insights are only recently beginning to be applied to understanding energy systems and systems transitions. The paper discusses the aspects of energy systems (in terms of technologies, ecosystems, users, institutions, business models) that lend themselves to the application of complexity science and its characteristics of emergence and coevolution. Complex-systems modelling differs from standard (e.g. economic) modelling and offers capabilities beyond those of conventional models, yet these methods are only beginning to realize anything like their full potential to address the most critical energy challenges. In particular there is significant potential for progress in understanding those challenges that reside at the interface of technology and behaviour. Some of the computational methods that are currently available are reviewed: agent-based and network modelling. The advantages and limitations of these modelling techniques are discussed. Finally, the paper considers the emerging themes of transport, energy behaviour and physical infrastructure systems in recent research from complex-systems energy modelling. Although complexity science is not well understood by practitioners in the energy domain (and is often difficult to communicate), models can be used to aid decision-making at multiple levels e.g. national and local, and to aid understanding and allow decision making. The techniques and tools of complexity science, therefore, offer a powerful means of understanding the complex decision-making processes that are needed to realise a low-carbon energy system. We conclude with recommendations for future areas of research and application.
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    Engaging stakeholders in research to address water-energy-food (WEF) nexus challenges
    (Springer, 2018-04-04) Hoolohan, C.; Larkin, A.; McLachlan, C.; Falconer, R.; Soutar, I.; Suckling, J.; Varga, Liz; Haltas, Ismail; Druckman, A.; Lumbroso, D.; Scott, M.; Gilmour, D.; Ledbetter, R.; McGrane, S.; Mitchell, C.; Yu, D.
    The water–energy–food (WEF) nexus has become a popular, and potentially powerful, frame through which to analyse interactions and interdependencies between these three systems. Though the case for transdisciplinary research in this space has been made, the extent of stakeholder engagement in research remains limited with stakeholders most commonly incorporated in research as end-users. Yet, stakeholders interact with nexus issues in a variety of ways, consequently there is much that collaboration might offer to develop nexus research and enhance its application. This paper outlines four aspects of nexus research and considers the value and potential challenges for transdisciplinary research in each. We focus on assessing and visualising nexus systems; understanding governance and capacity building; the importance of scale; and the implications of future change. The paper then proceeds to describe a novel mixed-method study that deeply integrates stakeholder knowledge with insights from multiple disciplines. We argue that mixed-method research designs—in this case orientated around a number of cases studies—are best suited to understanding and addressing real-world nexus challenges, with their inevitable complex, non-linear system characteristics. Moreover, integrating multiple forms of knowledge in the manner described in this paper enables research to assess the potential for, and processes of, scaling-up innovations in the nexus space, to contribute insights to policy and decision making.
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    Engineering resilient complex systems: the necessary shift toward complexity science
    (IEEE, 2020-01-01) Punzo, Giuliano; Tewari, Anurag; Butans, Eugene; Vasile, Massimiliano; Purvis, Alan; Mayfield, Martin; Varga, Liz
    This position article addresses resilience in complex engineering and engineered systems (CES). It offers a synthesis of academic thinking with an empirical analysis of the challenge. This article puts forward argumentations and a conceptual framework in support of a new understanding of CES resilience as the product of continuous learning in between disruptive events. CES are in continuous evolution and with each generation they become more complex as they adapt to their environment. While this evolution takes place, new failure modes arise with the engineering of their resilience having to evolve in parallel to cope with them. Our position supports the role of an overarching complexity science framework to investigate the resilience of CES, including their temporal evolution, resilience features, the management and decision layers, and the transparency of boundaries between interconnected systems. The conclusion identifies the value of a complexity perspective to address CES resilience. Extending the latest understanding of resilience, we propose a circular framework where features of CES are related to a resilience event and complexity science explains the importance of interconnections with external systems, the increasingly fast system evolution and the stratification of heterogeneous layers.
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    Evaluating the bovine tuberculosis eradication mechanism and its risk factors in England’s cattle farms
    (MDPI, 2021-03-26) Sedighi, Tabassom; Varga, Liz
    Controlling bovine tuberculosis (bTB) disease in cattle farms in England is seen as a challenge for farmers, animal health, environment and policy-makers. The difficulty in diagnosis and controlling bTB comes from a variety of factors: the lack of an accurate diagnostic test which is higher in specificity than the currently available skin test; isolation periods for purchased cattle; and the density of active badgers, especially in high-risk areas. In this paper, to enable the complex evaluation of bTB disease, a dynamic Bayesian network (DBN) is designed with the help of domain experts and available historical data. A significant advantage of this approach is that it represents bTB as a dynamic process that evolves periodically, capturing the actual experience of testing and infection over time. Moreover, the model demonstrates the influence of particular risk factors upon the risk of bTB breakdown in cattle farms.
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    An evolutionary theory of systemic risk and its mitigation for the global financial system
    (Cranfield University, 2014-01) Ilin, Thomas; Nellis, Joe; Varga, Liz
    This thesis is the outcome of theory development research into an identified gap in knowledge about systemic risk of the global financial system. It takes a systems-theoretic approach, incorporating a simulation-constructivist orientation towards the meaning of theory and theory development, within a realist constructivism epistemology for knowledge generation about complex social phenomena. The specific purpose of which is to describe systemic risk of failure, and explain how it occurs in the global financial system, in order to diagnose and understand circumstances in which it arises, and offer insights into how that risk may be mitigated. An outline theory is developed, introducing a new operational definition of systemic risk of failure in which notions from evolutionary economics, finance and complexity science are combined with a general interpretation of entropy, to explain how catastrophic phenomena arise in that system. When a conceptual model incorporating the Icelandic financial system failure over the years 2003 – 2008 is constructed from this theory, and the results of simulation experiments using a verified computational representation of the model are validated with empirical data from that event, and corroborated by theoretical triangulation, a null-hypothesis about the theory is refuted. Furthermore, results show that interplay between a lack of diversity in system participation strategies and shared exposure to potential losses may be a key operational mechanism of catastrophic tensions arising in the supply and demand of financial services. These findings suggest new policy guidance for pre-emptive intervention calls for improved operational transparency from system participants, and prompt access to data about their operational behaviour, in order to prevent positive feedback inducing a failure of the system to operate within required parameters. The theory is then revised to reflect new insights exposed by simulation, and finally submitted as a new theory capable of unifying existing knowledge in this problem domain.