Recognised as one of the most prominent hindrances to the development of inclusive cities, urban violence is frequently described as a highly complex development challenge. Such descriptions are attributed to the recognised interrelatedness of the multiple drivers and dimensions associated with the prevalence of urban violence. Nonetheless, the application of complexity theories to the pragmatic planning and management approaches targeting urban violence prevention remain limited at best. In critically reflecting on the discourses surrounding complexity and the subsequently developed approaches to integrated violence prevention in South Africa, this paper calls in to question existing definitions of urban violence as a complex challenge and provides in-depth, context-oriented reflections on what truly makes urban violence a complex phenomenon. Furthermore, on the basis of merging existing theory with over a decade of practice experience, the paper argues an evidence-based need for a shift in focus towards how integrated violence prevention programmes may be more effectively managed, drawing most prominently on the concept of adaptive management. The assertion is thus that the achievement of broad-based violence prevention demands practices that take proactive cognizance of the functionality of complex systems, supported by institutional and governance structures that recognise and are thus positioned to cope with complexity.
Employers require well rounded work-ready graduates with the skills to adapt to a contemporary workplace. Australian universities are responding to these needs through the implementation of Work-integrated Learning (WIL) programs aimed at providing students with the necessary skills, knowledge and attributes employers seek. This paper describes a study of Work-integrated Learning programs in the Human Resource Management (HRM) discipline at a number of Australian business schools. Exploratory interviews were undertaken with a range of stakeholders and examined within a complexity theory lens. The findings suggest that WIL is viewed as a threat to the role of higher education rather than an opportunity. There is increased interdependence and vulnerability within universities and as universities struggle for resources to respond to uncertainties in their ecosystem, they are being forced into making short term changes rather than co-evolving with their environment. By looking at the connectedness and evolutionary properties of the universities involved in the study, a number of recommendations are suggested to encourage universities to move to the edge of chaos, where a university’s full potential can be realized. Complexity theory provides a new way for viewing the intricacies of higher education course development and provides an argument for universities to create enabling conditions to co-evolve with the ever changing and complex world we live in.
The paper explores the Darwinian idea of natural selection through the preservation of favorable variations and the rejection of injurious variations. This is shown through focus on the evolutionary processes of variation and selective retention. Variability is necessary is necessary for success in a rough and unpredictable environment. It is the micro-diversity that drives evolving, emerging organizational structures. The paper has tried to answer how manufacturers can make sense of variety and see opportunities for the future. Thus how can these processes be explained through the complexity of interactive entities. The methodology through which the evolutionary processes of variation and selective retention is explored is through cladistics and Linnaean classifications. The concept of evolutionary stable strategy is applied to these systems. This is demonstrated through the examples on the Varieties of Product Centered Genus. The paper then suggests a three level approach to variation, selection and retention, namely a genetic analogy where the phenotypic or interactor manifestation is taken, the concern about the fitness of the Variety within the external environment, and finally the implementation of a new manufacturing Variety through human action.
Many of societies’ most pressing social policy problems are wicked problems. While complex adaptive systems theory has been recognised as an appropriate way to address this type of problem, complexity-accepting strategies are difficult for public administrations because they are at odds with their current dominant logic. This paper describes the development and implementation of a diagnostic tool for tackling wicked problems that is underpinned by complex systems leadership theories and takes into account the current needs of government. The diagnostic tool was reasoned during a research project that investigated how best to increase the social impact of an active citizenship education program in the City of Onkaparinga, South Australia. The research project identified that while the program developed the active citizenship characteristics desired by the three levels of government in Australia, graduates from the program encountered systemic blocking factors when they attempted to put what they had learned during the program into practice. To increase the program’s impact, the diagnostic tool addresses these systemic blocking factors by focusing on nine leverage areas that enable systemic innovation and change to occur in communities.
This study was conducted to understand the various causalities and consequences of the hybrid structure and governance under public private partnerships (PPPs). Narrations pertaining to the central question of the research were collected from senior officials from PPPs in India, including executives from public agencies and private agencies. The grounded theory approach was used to analyze the narrations. Classical content analysis, selective coding and axial coding methods were used for data analysis.Complementary assets and capabilities among organizations, and inability to carry out project as a stand alone organization were the major casualties of the PPP structure. There were two dimensions of governance complexity, i.e. (i) Uninterpretable rules, policies, systems, and (ii) unexpected actions/decisions in uncertainty, in the PPP structure. The causalities in the complexity of the governance of the hybrid PPP structure were (i) organizational attributes, (ii) stakeholders’ expectations, (iii) power of control, (iv) institutional logic, (v) strategic decision making, and (vi) contract management. The attributes to the complex PPP governance system were, trust, ego, interpretation of complex operational phenomenon, mechanism to address risks and uncertainty and Interdependencies and reciprocity.
In transition times leaders should be aware of the hidden and intangible assets of their organizations or communities. While linear—analytical assessment tools face major difficulties in meeting this challenge, we suggest that the use of archetypal models as knowledge systems can be of help. A new tool, based on the use of geometrical patterns and aiming to reveal and assess a system’s capacity and maturity for change, is presented here.
The nature of China’s climate change dilemma is well-known: Climate change is exacerbating environmental devastation in China, but expanding mitigation efforts would pose new challenges to continuing economic development. National environmental measures often face strong resistance from sub-national authorities, which are incentivized by highly stable growth and development goals. This paper applies complexity theory to China’s climate change dilemma. Key insights of complexity theory—(i) the decisive role of systemic parameter settings (rule sets or minimum specifications) in shaping system behavior and (ii) the creative capacity of non-hierarchical organization—should encourage policy responses that reset incentives and harness creativity beyond government. Several instances are examined where incentive-focused, non-hierarchical initiatives have been effective in promoting climate-friendly behaviors. They include voluntary energy efficiency commitments undertaken by corporations, partnerships between local governments, clean-tech firms and international specialists, and ‘local issue-bundling’ to enlist public support for climate change mitigation.
This paper explores the question of whether people involved with a successful watershed policy initiative embraced and/or negated the complexity with which they worked. The setting was Lake Simcoe, in central Canada: an area important for fisheries, agriculture, tourism, recreation and citizens’ identities. Human activities had impacted water quality, and planned development posed further threats. Although government had supported considerable scientific data collection, citizens became frustrated by what they saw as a lack of regulatory and enforcement work. Citizens embarked on a range of creative pressure tactics for change. In early stages, citizens felt marginalized, but over time they were included in increasingly meaningful ways. This paper explores several complex system themes in interview transcripts, including initial starting conditions, attractors, and boundaries. A key finding is that citizens used scientific data as an attractor to enable their inclusion for a more complex range of agendas and benefits.
The concept of resilience has become popular in international development circles in recent years, but it is only one of many factors in a larger, integrated, empirical understanding of systemic health and development emerging from the study of energy-flow networks. This article explores how the Energy Network Sciences (ENS) can provide a robust theoretical foundation and effective quantitative measures for resilience and other characteristics that undergird systemic health and development in socio-economic networks. Einstein once said that “theory makes measurement possible.” We believe ENS can provide a more effective theory of economic health, which will open the door to surprisingly precise measures. Our goal is to outline the basic reasoning behind both theory and measures.
Utility–service provision is a process in which products are transformed by appropriate devices into services satisfying human needs and wants. Utility products required for these transformations are usually delivered to households via separate infrastructures, i.e., real-world networks such as, e.g., electricity grids and water distribution systems. However, provision of utility products in appropriate quantities does not itself guarantee that the required services will be delivered because the needs satisfaction task requires not only utility products but also fully functional devices. Utility infrastructures form complex networks and have been analysed as such using complex network theory. However, little research has been conducted to date on integration of utilities and associated services within one complex network. This paper attempts to fill this gap in knowledge by modelling utility–service provision within a household with a hypergraph in which products and services are represented with nodes whilst devices are hyperedges spanning between them. Since devices usually connect more than two nodes, a standard graph would not suffice to describe utility–service provision problem and therefore a hypergraph was chosen as a more appropriate representation of the system. This paper first aims to investigate the properties of hypergraphs, such as cardinality of nodes, betweenness, degree distribution, etc. Additionally, it shows how these properties can be used while solving and optimizing utility–service provision problem, i.e., constructing a so-called transformation graph. The transformation graph is a standard graph in which nodes represent the devices, storages for products, and services, while edges represent the product or service carriers. Construction of different transformation graphs to a defined utility–service provision problem is presented in the paper to show how the methodology is applied to generate possible solutions to provision of services to households under given local conditions, requirements and constraints.
Electrical power networks can be improved both technically and economically through the inclusion of distributed generator (DG) units, which may include renewable energy resources. This work uses multi-objective optimization by evolutionary computing, with power flow calculations and multi-dimensional results analysis, to investigate a method of defining optimal deployment of DG units. The results indicate that the method used is a feasible one for designing deployment of DG units in terms of type, number, and location.
Critical regimes are present in all socio-technical systems. Usually, man-made systems are designed to avoid these regimes completely, and stay in a stable steady state to avoid uncertainty. However, complexity theory postulates that the edge of chaos, between order and disorder, provides highly interesting phenomena, such as emergence, which are important for the evolution of the system. In this paper we explore the edge of chaos through a concrete example in electrical energy systems. The exploration is done through simulation, which provides a valuable mean to perform massive experiments on large scale systems. The complexity residing at the edge is discussed, and external, system relevant and internal factors which are likely to shift this edge or drive the systems trajectory towards or away from it are introduced.
The paper looks at the potential for multi-utility service providers to create business models that compete with traditional utility product providers whereby customers’ services increase and resource efficiency is improved. The objective in our modeling is to show the how Multi-Utility Service Companies (MUSCos) could invade the market, changing it from markets focused on selling, for example, energy to customers, to markets aimed at selling efficiency. The output of our modeling is the extent to which the resource efficiency of UK homes can be significantly improved, and we show this in 10 centile categories. The key difference between the two types of providers (Traditional and MUSCo) is that while households can switch traditional suppliers fairly rapidly (3 months), if a household signs up to get house improvements and utilities from a particular MUSCo, then the arrangement will be at least 5 years, and possibly longer. This means that households, once they sign up are no longer ‘on the market’ for utility supply. Although getting a contract signed may take much more time for a salesman than simply getting a normal utility order, the fruits and the income are guaranteed to the MUSCo for 5 or 10 years. Their sales force efforts can be switched to non-contracted households. So, essentially both utilities and MUSCos are trying to sell to the normal, non-contracted households. The real advantage that a MUSCo customer is that there is a discount on both the house improvements offered and the price of future supplies of energy and water. MUSCos are able to offer reduced cost of house insulation, appliances which reduce consumption and waste from multiple utilities, and can achieve marginal profits from financing of these appliances.
Attempts to model the present and future power networks face a huge challenge because it is a complex system, integrated by generation, distribution, storage and consumption subsystems, and using various control and automation computing systems. Moreover,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 electrical one, must be considered. In order to simulate those networks, a fully integrated agent-based model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is presented in this article. Moreover a way to try to extend it to cover infrastructure networks is outlined.
As half of the world’s population live in cities today, the topic of urbanization and urban energy systems shift continuously into society’s focus. It has become a common challenge for local governments to provide a so called “Master Plan”, outlining a long term vision for the city’s energy infrastructure, to which all planners and investors have to adhere. Being a top-down approach, these Master plans are first of all politically motivated documents, which focus on achieving given targets, such as CO2-emission reductions or higher shares of electric mobility. Originating from these targets, a set of milestones and measures is derived, e.g., the implementation of certain green technologies or refurbishments of buildings. The goal of this paper is to elaborate a model, which allows analysis of a Master Plan from a bottom-up perspective and thereby quantitatively assesses the plan with regards to its feasibility, while identifying possible bottlenecks in its implementation. The results can then serve the city planners to adapt their planning in order to avoid unforeseen problems, when putting the plan’s measures into practice. The approach pursued in this research is a combination of system dynamics and an agent-based simulation model of the city’s energy system, providing both a high spatial and temporal granularity. The model is developed with the multi-method modelling tool Anylogic and with Geographic Information System (GIS). The city itself is represented with its existing building and power infrastructure, which is then subject to the planned measures and developments. The core of the model implements on the one hand different energy generation technologies, both fossil fuels and renewables, reaching from big power plants to small local PV-installations on a private household’s roof. On the other hand, the heat and electricity consumers are represented through the buildings. The aim of the model is, at first, to provide a support system to analyze the short and long term effects of the Master Plan. Since its measures are usually not planned in detail concerning exact location or timing of the realization, the simulation results can provide references on these specific details. Secondly, the findings are used to identify the impact of single planned measures and their combinations which answers the questions of how, when and where local electricity and heat producers and the energy efficiency measures influence one another and if they have synergetic or competitive effects. Finally, a set of recommendations is derived from the analyses, which can help the city planners to transfer the strategic measures of the Master Plan into operative business.
The aims of this paper are to present and to discuss an agent-based model of population dynamics for the European regions at NUTS 3 level. It includes individuals that perform several activities with bounded rationality. The paper briefly discusses the latest novelties on this topic and then describes the processes to prepare a data base with the necessary information to feed and calibrate the model. Then it is presented the initialization module. It generates individual heterogeneity according to average and marginal aggregate distributions of the included variables that characterize the agents. In order to simulate the mechanisms of migration our model creates an artificial labor demand at regional level using simple but effective rules based on mainstream economic theory. The rest of the model is also presented: education, pairing, aging and deceases. A set of scenarios is defined and the regional aggregates are computed. Hence, the results are prepared to be visualized with tables, graphics and maps.
I present a model of ’engagement’ to explain how strategic decision makers use different concepts simultaneously to tame wicked problems in a modern business environment. Attention is placed on ’framing’ and ’reframing’ and how this can lead to the resolution of complex problems. I analyze a longitudinal case study of a transport logistics company, where a complex problem was framed through one set of concepts, reframed by another, and eventually tamed. I argue that strategic problem solving involves an engagement of different ideas and a process of reframing to tame wicked problems. Particular attention is paid to how the key actors interacted and how these interactions influenced ’engagement’. I conclude by relating this to modern European managers and the emergent problems they face.
In this paper, we extend the understanding of human interaction dynamics by examining three case studies of social-action-networks whose purpose was to achieve collective action on a complex social or environmental issue. Our research questions were “How do the organizing mechanisms of fine grained interactions construct emergent order?” and “Why do influencing strategies enable diffuse networks to emerge into discernible collective action?” The studies provided information about the fine-grained interactions as well as the coarse-grained properties that emerged. At the fine-grained level, there was a dynamic tension between structured and formalized organizing mechanisms aimed at organization and those that actively permitted (dis)organization. Network strategic intent was coherent at the coarse-grained level and varied between a clearly defined strategy and strategic ambiguity. We examine these empirical findings in relation to recent literature on constructing forces, strategic ambiguity and interpretive dominance.