City indicators : now to Nanjing

This paper provides the key elements to develop an integrated approach for measuring and monitoring city performance globally. The paper reviews the role of cities and why indicators are important. Then it discusses past approaches to city indicators and the systems developed to date, including the World Bank's initiatives. After identifying the strengths and weaknesses of past experiences, it discusses the characteristics of optimal indicators. The paper concludes with a proposed plan to develop standardized indicators that emphasize the importance of indicators that are measurable, replicable, potentially predictive, and most important, consistent and comparable over time and across cities. As an innovative characteristic, the paper includes subjective measures in city indicators, such as well-being, happy citizens, and trust.Cultural Policy,City Development Strategies,Cultural Heritage&Preservation,ICT Policy and Strategies,Housing&Human Habitats

Fuzzy cognitive mapping to support multi-agent decisions in development of urban policymaking

The awareness about environmental complexity involves real-time knowledge and demands urban planning initiatives. Knowledge is multiform, multi-agent and mirrors environmental complexity. Problems characterizing urban sustainability particularly claim non-expert knowledge, being informal, puzzling, uncertain, incomplete, hard to be handled, formalized, modelled. This study utilizes Fuzzy cognitive maps to explore such complexity and support multiagent decisions. It concerns the scenario-building process of the new plan of Taranto (Italy), a paradigmatic example of decaying industrial area, heavily characterized by social fragmentation and environment degradation. This approach aims at structuring environmental problems, modelling future strategies and contributing to build a multi-agent decision support system for complex urban planning contexts

The Participatory Potential of Fuzzy Cognitive Mapping in The Context of Harmful Algal Blooms in Peru

The involvement of non-academic actors in research has become a key characteristic of sustainability studies. As part of this trend, modellers increasingly turn to Participatory Modelling to incorporate stakeholders' knowledge, perceptions, norms, and values in the development of formalized, shared representations of social-ecological systems. While stakeholder participation has been shown to have many advantages, its limits are not adequately discussed in the contemporary Participatory Modeling literature. In particular, there is a lack of engagement with insights from fields that have a long participatory research tradition, such as development studies. To address this gap, the thesis employs Fuzzy Cognitive Mapping (FCM), a widely employed form of PM, in a case study in Peru, aiming to map the socio-ecological drivers, impacts, and related adaptation strategies in the context of Harmful Algal Blooms involving diverse groups of local stakeholders. Subsequently, the thesis critically reflects on the participatory knowledge production process, drawing on sociology and development studies literature. By identifying and discussing the limitations of the participatory approach within this specific case study, the thesis aims to contribute to the development of best practices specific to FCM

Situation Modeling of Regional Development in the Republic of Kazakhstan

The methodology of situation modeling was based on the application of fuzzy cognitive maps, indistinct regional data and indistinct time horizon. Based on indistinct number of involved concepts, the model enables users to create their own situations with fuzzy quantity of available concepts including both the existing and the added ones. The added concepts are characterized by the set properties and database related to no less than three fuzzy time horizons. The number of set impulses is fuzzy as well. Cognitive map training was based on the artificial intelligence element – the active Hebb learning rule. The impact of concepts was defined in the course of training. Fine adjustment of the fuzzy cognitive map was achieved by changing the training order using a rank scale and Saati’s sorting algorithm. The developed computer software was used in simulation modeling of regional socio-economic processes related to the project aiming at tourism development of the Alacol Lake in Almaty region. Research results are shown in the form of a fuzzy cognitive map reflecting internal and external relations within the region, graphs reflecting socio-economic development and the Bossel criterion. Simulation of allocations had a positive effect: GRP (Gross Regional Product) growth along with increase in employment and environmental improvement. The proposed approach provides a tool for forecasting of regional development and solution of different regional problems. This approach can be used with regard to any administrative-territorial entity, provided relevant statistical data

A structured participatory method to support policy option analysis in a social-ecological system

In this study we demonstrate how to support policy option analysis for a problematic Social-Ecological System (SES) with the help of stakeholder participation. SES sustainability problems 1) are highly complex, 2) may lack reliable data, 3) encompass conflicting interests and 4) may require contradictory management interventions. Our approach uses a structured participatory method combining the Driver-Pressure-State-Impact-Response (DPSIR) model together with Fuzzy Cognitive Mapping (FCM) to capture the complexity of the system and simplify its representation for simulation and policy option analysis. Using this novel mixed-method was useful in dealing with above-mentioned characteristics of the complex SES problems. The method was applied in a case study of water scarcity in Rafsanjan, Iran. FCMs were produced for 60 individual farmers and 40 individual researchers and policy makers. Our mixed-method analysis reveals similarities and differences of stakeholder knowledge and problem perception, and simulates the impacts of alternative policy options according to each group's perception. The final result of our case study indicates that farmers in Rafsanjan strongly believe in the impact of economic diversification on reducing water shortage, but they have a low level of trust in the ability of the government to regulate and control water usage, whereas the policy makers and researchers still believe in the role of government control and monitoring policies to deal with water scarcity in Rafsanjan

Situation Modeling of Regional Development in the Republic of Kazakhstan

The methodology of situation modeling was based on the application of fuzzy cognitive maps, indistinct regional data and indistinct time horizon. Based on indistinct number of involved concepts, the model enables users to create their own situations with fuzzy quantity of available concepts including both the existing and the added ones. The added concepts are characterized by the set properties and database related to no less than three fuzzy time horizons. The number of set impulses is fuzzy as well. Cognitive map training was based on the artificial intelligence element – the active Hebb learning rule. The impact of concepts was defined in the course of training. Fine adjustment of the fuzzy cognitive map was achieved by changing the training order using a rank scale and Saati’s sorting algorithm. The developed computer software was used in simulation modeling of regional socio-economic processes related to the project aiming at tourism development of the Alacol Lake in Almaty region. Research results are shown in the form of a fuzzy cognitive map reflecting internal and external relations within the region, graphs reflecting socio-economic development and the Bossel criterion. Simulation of allocations had a positive effect: GRP (Gross Regional Product) growth along with increase in employment and environmental improvement. The proposed approach provides a tool for forecasting of regional development and solution of different regional problems. This approach can be used with regard to any administrative-territorial entity, provided relevant statistical data

Tools and methods in participatory modeling: Selecting the right tool for the job

© 2018 Elsevier Ltd Various tools and methods are used in participatory modelling, at different stages of the process and for different purposes. The diversity of tools and methods can create challenges for stakeholders and modelers when selecting the ones most appropriate for their projects. We offer a systematic overview, assessment, and categorization of methods to assist modelers and stakeholders with their choices and decisions. Most available literature provides little justification or information on the reasons for the use of particular methods or tools in a given study. In most of the cases, it seems that the prior experience and skills of the modelers had a dominant effect on the selection of the methods used. While we have not found any real evidence of this approach being wrong, we do think that putting more thought into the method selection process and choosing the most appropriate method for the project can produce better results. Based on expert opinion and a survey of modelers engaged in participatory processes, we offer practical guidelines to improve decisions about method selection at different stages of the participatory modeling process

Testing management scenarios for the North Sea ecosystem using qualitative and quantitative models

The complexities of ecosystem-based management require stepwise approaches, ideally involving stakeholders, to scope key processes, pressures, and impact in relation to sustainability and management objectives. Use of qualitative methods like Fuzzy Cognitive Mapping (FCM) with a lower skill and data threshold than traditional quantitative models afford opportunity for even untrained stakeholders to evaluate the present and future status of the marine ecosystems under varying impacts. Here, we present the results applying FCM models for subregions of the North Sea. Models for the southern North Sea, Skagerrak, Kattegat, and the Norwegian Trench were developed with varying level of stakeholder involvement. Future scenarios of increased and decreased fishing, and increased seal biomass in the Kattegat, were compared with similar scenarios run on two quantitative ecosystem model. Correspondence in response by the models to the same scenarios was lowest in the southern North Sea, which had the simplest FCM model, and highest in Norwegian Trench. The results show the potential of combining FCM and quantitative modelling approaches in integrated ecosystem assessments (IEAs) and in future ecosystem-based management advice, but to facilitate such comparisons and allow them to complement and enhance our IEAs, it is important that their components are aligned and comparable

Testing management scenarios for the North Sea ecosystem using qualitative and quantitative models

The complexities of ecosystem-based management require stepwise approaches, ideally involving stakeholders, to scope key processes, pressures, and impact in relation to sustainability and management objectives. Use of qualitative methods like Fuzzy Cognitive Mapping (FCM) with a lower skill and data threshold than traditional quantitative models afford opportunity for even untrained stakeholders to evaluate the present and future status of the marine ecosystems under varying impacts. Here, we present the results applying FCM models for subregions of the North Sea. Models for the southern North Sea, Skagerrak, Kattegat, and the Norwegian Trench were developed with varying level of stakeholder involvement. Future scenarios of increased and decreased fishing, and increased seal biomass in the Kattegat, were compared with similar scenarios run on two quantitative ecosystem model. Correspondence in response by the models to the same scenarios was lowest in the southern North Sea, which had the simplest FCM model, and highest in Norwegian Trench. The results show the potential of combining FCM and quantitative modelling approaches in integrated ecosystem assessments (IEAs) and in future ecosystem-based management advice, but to facilitate such comparisons and allow them to complement and enhance our IEAs, it is important that their components are aligned and comparable