Structure in creativity: An exploratory study to analyse the effects of structuring tools on scenario workshop results

Scenario projects increasingly combine quantitative models with qualitative, participatory products in order to make scenarios more coherent, relevant, credible and creative. A major advantage of adding participatory, qualitative scenarios is their ability to produce creative, innovative, non-linear products. Integrating participatory results with quantitative models, however, can lower their credibility of both products when they are not consistent. The low level of structure in most participatory output limits possibilities for linking them to quantitative models. More structure could be introduced, but this might hamper the creativity of the workshop results: outcomes (process) and outputs (storylines). This paper tests a new method to analyse the creativity of scenario storylines in order to analyse the effects of structuring tools on the creativity of workshop results. Both the perceptions of participants and the resulting storylines of nine case studies across Europe are used in the analysis. Results show that the use of structuring tools can have a negative effect on the creativity of the workshop, but the influence seems to vary between the different tools. The study shows the benefit of using indicators for the scenario quality criteria. More research is needed to develop indicators for other scenario quality criteria, to improve those developed here and to study the impact of structuring tools with a larger data set.     

Building scenarios with Fuzzy Cognitive Maps: An exploratory study of solar energy

In scenario planning, causal mapping has long been used as a means to elicit the worldviews of multiple experts, facilitate discussion, and challenge and improve mental models. Large and complex causal maps, however, are difficult to analyze. This paper proposes a novel method for scenario building, based on Fuzzy Cognitive Maps, that combines intuitive, cognitive mapping techniques with formal, quantitative analysis. The proposed method helps scenario planners to integrate the qualitative and partial knowledge of multiple individuals and overcome information processing limitations. The feasibility of the proposed approach is investigated with two scenario studies on solar photovoltaic panels.     

Multi-scale narratives from an IA perspective: Part I. European and Mediterranean scenario development

Desertification in the Northern Mediterranean region can be effectively managed only through an understanding of the principal ecological, socio-cultural and economic drivers. Scenarios can play an important role in the understanding of such a complex system. Following the fundamentals of Integrated Assessment, narrative storylines were developed that are qualitative, participatory, and highly integrated. Multi-scale long-term (2030) storylines were developed for Europe, the Northern Mediterranean, and for four local cases. This paper discusses the methodology and results of the process of developing European and Mediterranean scenarios. In Part II, the local scenario development by means of scenario workshops is elaborated upon. European and Mediterranean scenarios were based on a set of three existing European scenarios, that were adapted to fit the specific issues in the Mediterranean region, using the so-called Factor-Actor-Sector (FAS) framework. Resulting scenarios were Convulsive Change (disruptive climate change); Big is Beautiful (oversized EU and powerful multinationals); and Knowledge is King (technological development and mass migration). It proved possible to use and enrich a set of existing European scenarios and to translate them to fit the Mediterranean region. A possible use of this type of narrative storylines is further illustrated in Part II.     

Towards better participatory processes in technology foresight: How to link participatory foresight research to the methodological machinery of qualitative research and phenomenology?

Technological progress does not happen in a social vacuum. Shaping of tomorrow is not possible without qualitative analyses. Therefore, the social and psychological dimensions of reality form an important part of technology foresight. Qualitative research will be needed to understand superficial and deep structures of social realities. So called push and pull factors are always linked to social behaviour. People's relationship to the use of technologies and the utilization of technologies is a complex and not a one-dimensional or monological issue. Monological methodological approaches can be harmful and confusing in the field of participatory foresight. We can conclude that the cycles of deductive and inductive logic are needed in science and in participatory foresight studies. Experts of the FTA community must have a higher level of methodological know-how in this research field and they should use qualitative methods in multi-faceted (external and internal) ways in foresight studies. Still the qualitative parts of many studies are quite monological and these studies can be quite problematic, even confusing. More critical methodological approaches should be taken into serious consideration. As a methodological approach, the principle of triangulation should be used more in the fields of participatory foresight studies and technology foresight.The key focus of this article in the use of qualitative and phenomenological approaches in the fields of FTA and foresight. The aim of this theoretically oriented discussion is to promote the professional use of qualitative methods in foresight and FTA studies. The strength of qualitative analyses is linked to deeper understanding of social change and social patterns and structures. Actually people create and constitute the markets, networks, and crowds where technologies are applied and used.Internal systemic understanding of social realities is an important part of foresight activities, especially in participatory foresight studies. Internal and external analyses can be seen as complementary approaches, like qualitative and quantitative approaches. The use of qualitative methods is a conventional part of the research process in participatory foresight projects. A typical problem may be that the use of methods is not planned carefully enough and people are unaware of the underlying key assumptions of applied methods. Experimenting with phenomenology is not a simple task in foresight research. Therefore, the views and informative platforms expressed and presented in this article may be useful for foresight practitioners.     

Sustainability in the prospective scenarios methods: A case study of scenarios for biodiesel industry in Brazil,for 2030

In order to build prospective scenarios for biodiesel industry in Brazil, with a sustainable perspective, it was necessary to develop a cross-disciplinary work to include Sachs’ dimensions of sustainability into the scenarios method. This meant linking concepts from different disciplines, without transforming it in a new discipline. In order to support the proposition for the new method, a study case is presented, the framework for the biodiesel scenarios in Brazil, by 2030. An in-depth interview was used to test the proposition of having the sustainability dimensions as driving forces. The result was the identification of a critical uncertainty composed of various aspects related the response to climate change and environmental conservation. The scenario storylines that were developed based on the critical uncertainties showed that sustainable options for the future are possible if the mental maps are enlarged to see beyond the business as usual.The results show that the scenarios storylines go through social, environmental and economic aspects, supported by other aspects like the territorial and political. Also it showed that sustainable options are possible if the mental maps are enlarged to see beyond the business as usual.     

Stepping into futures: Exploring the potential of interactive media for participatory scenarios on social-ecological systems

In this paper, we present a strategy for the development of interactive media scenarios to help communicate uncertainties and complexities in coupled human and natural systems. Insights arising from Complex Adaptive Systems theory advocate the need for more adaptive perspectives on natural resources management. For the collaborative exploration of future complexities and uncertainties, participatory scenario development has proven to be a powerful approach. A range of communication strategies with benefits for conveying complexity, however, has not yet been adopted by scenario developers. We present a framework of criteria with which we structurally analyze the benefits of interactive media communication. First, we consider requirements of feasibility, flexibility and stakeholder contributions. Then, we synthesize criteria for the communication of Complex Adaptive Systems. Finally, we set criteria for communicatory clarity and engagement. Using this framework, we review several science communication fields, including landscape visualization, serious gaming and visual analytics. We then develop a strategy for interactive media communication in participatory scenario development, including two work-in-progress examples. This strategy employs mixed media, micro-games and accessible stakeholder contributions in a geo-web context, and is suitable for participatory work in live settings as well as on-line, from a local to a global scale.     

Past and future of backcasting: The shift to stakeholder participation and a proposal for a methodological framework

This paper deals with the past, present and future of backcasting. After having reviewed the origin and developments since the 1970s, it is concluded that several varieties can be distinguished and that a shift has been made to broad stakeholder participation and towards a focus on realising follow-up and implementation. A methodological framework for participatory backcasting is proposed consisting of five stages and four groups of tools and methods that can be applied and are necessary in such a framework, while different type of goals are possible. The paper reports on two cases in which participatory backcasting was applied, the Novel Protein Foods project at the Sustainable Technology Programme in the Netherlands and the Nutrition case study of the Sustainable Households (SusHouse) project. The paper concludes that these have resulted in broad stakeholder involvement, sustainable future visions, analyses and construction of follow-up agendas, but that follow-up and impacts are quite different. A research agenda is proposed to compare and evaluate backcasting studies and their impacts after a couple of years, while the future of participatory backcasting is also briefly discussed.     

Exploring techno-economic scenarios in an input-output model

The dynamic input-output model DIMITRI (Dynamic Input-output Model to study the Impacts of Technology Resulted Innovations) can be used for long-term scenario explorations on technology, demand and environmental effects. The model describes at a sectoral level the relations and dynamics between consumption, production and emissions. Technologies are introduced bottom-up at a sectoral level, through variations on the inputs from other sectors and by changes in the coefficients for capital, labour and emissions. This paper presents a methodology for future explorations of technologies in four scenarios, based on the International Panel on Climate Change (IPCC) scenario framework. Trend analysis combines detailed information on specific technologies. Differentiations are made between scenarios, based on their specific storylines. The adjustment of coefficients influences model outcomes such as production, balance of trade and emissions. This paper briefly outlines the methodology and presents the main outcomes for four scenarios for the period 2000-2030.     

Performance management in a milieu of customer participatory measurement: Beyond the ratings and rankings of Strictly Come Dancing

This research concerns the performance management practices that unfolded in Strictly Come Dancing, a television show whose viewers were promised that they could be its co-creators through Web 2.0-based customer participatory measurement systems that directed the development of the series mechanically. Analysing the performance management practice of the 2013 Danish version of the show, we find that an emotive, antagonistic competitive language game and an authoritative, calculative language game were operating in interaction. They facilitated an expectation of consumer democracy and made viewers engage fiercely with the show, while simultaneously controlling the drama so that it would unfold in a way that matched the voice of the television company. The study provides novel insights into our understanding of how companies might produce and use customer participatory measurement systems as an integrated part of their customer participatory logic of value co-creation. It also adds to the methodological apparatus for analysing, conceptualising, and understanding organisational practices of performance management.     

Bounding the future: The use of scenarios in assessing climate change impacts

This paper investigates the contribution of socio-economic scenarios to improve decisions and policies in climate assessments. We specifically looked at adaptation projects in the Dutch Climate changes Spatial Planning programme. Based on the four decision failure criteria neglect of internal information, bounded rationality, insufficient expansion of existing mental models and stickiness and lack of friction of information and knowledge, it was concluded that in these projects, socio-economic scenarios appear to generate useful data, but that their full potential to reduce decision failure is not likely to be exploited. Therefore adaptation options suggested by these studies may not be ‘future-proof’: they may be appropriate in some future societies, but fail in others. We believe similar results would be obtained in other contexts. Possible decision failures are caused by neglecting socio-economic developments, limiting the number of storylines generated by scenario studies to one or two, lack of stakeholder involvement in the scenario development and ignoring discontinuities.     

Robustifizierung des Chain-Ladder-Verfahrens über ein skalares Zustandsraummodell

Applications of state space models and the Kalman filter are comparatively underrepresented in stochastic claims reserving. This is usually caused by their high complexity due to matrix-based approaches, which complicate their applications. In order to facilitate the implementation of state space models in practice, we present a state space model for cumulative payments in the framework of a scalar-based approach. In addition to a comprehensive presentation of this scalar state space model, some empirical applications and comparisons with popular stochastic claims reserving methods are performed, which show the strengths of the scalar state space model in practical applications. This model is a robustified extension of the well-known Chain Ladder method under the assumption, that the observations in the upper triangle are based on unobservable states. Using Kalman-filter recursions for prediction, filtering and smoothing of cumulative payments, the entire unobservable lower and upper run-off triangles can be determined. Moreover, the model provides an easy way to find and smooth outliers and to interpolate gaps in the data. Thus, the problem of missing values in the upper triangle is also solved in a natural way.     

Future utility services’ (un)knowns framework: Knowledge existence and knowledge reach

This paper presents a framework for assessing risks and uncertainties in the domain of utility services in futures up to 100 years hence. A nine-step process framework is presented following a review of extant literature. The framework provides a way to quantitatively and qualitatively evaluate one or more vignettes (potential future utility infrastructure solutions) by examining: 1. Alternative scenario contexts; 2. User utility service requirements; 3. Technologies’ readiness; 4. Knowledge of each technology life cycle stage; 5. Criticality of technologies to user requirements; 6. Interdependencies between technologies. The framework is based on collecting multiple expert contributions in order to arrive at a comparative evaluation. We use the ‘city blood’ vignette, which represents an infrastructure system delivering hydrogen enriched water, to apply the framework to two radically different scenario contexts.     

SCENARIO GENERATION FOR OPERATIONAL RISK

Operational risk is an increasingly important area of risk management. Scenarios are an important modelling tool in operational risk management as alternative viable methods may not exist. This can be due to challenging modelling, data and implementation issues, and other methods fail to take into account expert information. The use of scenarios has been recommended by regulators; however, scenarios can be unreliable, unrealistic and fail to take into account quantitative data. These problems have also been identified by regulators such as Basel, and presently little literature exists on addressing the problem of generating scenarios for operational risk. In this paper we propose a method for generating operational risk scenarios. We employ the method of cluster analysis to generate scenarios that enable one to combine expert opinion scenarios with quantitative operational risk data. We show that this scenario generation method leads to significantly improved scenarios and significant advantages for operational risk applications. In particular for operational risk modelling, our method leads to resolving the key problem of combining two sources of information without eliminating the information content gained from expert opinions, tractable computational implementation for operational risk modelling, improved stress testing, what‐if analyses and the ability to apply our method to a wide range of quantitative operational risk data (including multivariate distributions). We conduct numerical experiments on our method to demonstrate and validate its performance and compare it against scenarios generated from statistical property matching for comparison. Copyright © 2013 John Wiley & Sons, Ltd.     

Connecting adaptation and strategy: The role of evolutionary theory in scenario planning

In this study, evolutionary theory is used to analyze and critique the strategic process of scenario planning. We argue that scenario planning can be strengthened as a theory- and practice-oriented process through the incorporation of evolutionary theory in the scenario narrative process, and in the subsequent implementation phases in response to environmental change. First, this paper addresses scenario planning in relation to theoretical perspectives on strategic planning and forecasting. Then, the concepts of variation, selection, retention, organizational learning and inertia are used to analyze scenario planning as a strategic process. This study argues that because scenario planning mirrors modes of variation and selection at the organizational level, evolutionary theory is a useful approach for assessing the plausibility of scenario narratives and strengthening the theoretical foundation of scenario planning as a process. By utilizing an evolutionary framework throughout the scenario planning process, this method has a better chance of encouraging exploratory strategic thinking without reinforcing non-blind variation or inertial practices. Concepts including inertia can also be used to better address bias and myopia in the scenario planning process. Additionally, evolutionary theory can be used to assess how entities learn from the outcomes of scenario planning as the environment changes over time.     

A systematic approach to multi-period stress testing of portfolio credit risk

We propose a new method for analysing multi-period stress scenarios for portfolio credit risk more systematically than in current macro stress tests. The plausibility of a scenario is quantified by its distance from an average scenario. For a given level of plausibility, we search systematically for the most adverse scenario. This ensures that no plausible scenario will be missed. We show how this method can be applied to some models already in use by practitioners. While worst case search requires numerical optimisation we show that we can work with reasonably good linear approximations to the portfolio loss function. This makes systematic multi-period stress testing computationally efficient and easy to implement. Applying our approach to data from the Spanish loan register we show that, compared to standard stress test procedures, our method identifies more harmful scenarios that are equally plausible.     

Analysis of ultra-high-frequency financial data using advanced Fourier transforms

This paper presents a novel application of advanced methods from Fourier analysis to the study of ultra-high-frequency financial data. The use of Lomb–Scargle Fourier transform, provides a robust framework to take into account the irregular spacing in time, minimising the computational effort. Likewise, it avoids complex model specifications (e.g. ACD or intensity models) or resorting to traditional methods, such as (linear or cubic) interpolation and regular resampling, which not only cause artifacts in the data and loss of information, but also lead to the generation and use of spurious information.     

Semi-Parametric Specification Tests for Discrete Probability Models

Loss functions play an important role in analyzing insurance portfolios. A fundamental issue in the study of loss functions involves the selection of probability models for claim frequencies. In this article, we propose a semi‐parametric approach based on the generalized method of moments (GMM) to solve the specification problems concerning claim frequency distributions. The GMM‐based testing procedure provides a general framework that encompasses many specification problems of interest in actuarial applications. As an alternative approach to the Pearson χ² and other goodness‐of‐fit tests, it is easy to implement and should be of practical use in applications involving selecting and validating probability models with complex characteristics.     

COS method for option pricing under a regime-switching model with time-changed Lévy processes

We extend the regime-switching model to the rich class of time-changed Lévy processes and use the Fourier cosine expansion (COS) method to price several options under the resulting models. The extension of the COS method to price under the regime-switching model is not straightforward because it requires the evaluation of the characteristic function which is based on a matrix exponentiation which is not an easy task. For a two-state economy, we give an analytical expression for computing this matrix exponential, and for more than two states, we use the Carathéodory–Fejér approximation to find the option prices efficiently. In the new framework developed here, it is possible to allow switches not only in the model parameters as is commonly done in literature, but we can also completely switch among various popular financial models under different regimes without any additional computational cost. Calibration of the different regime-switching models with real market data shows that the best models are the regime-switching time-changed Lévy models. As expected by the error analysis, the COS method converges exponentially and thus outperforms all other numerical methods that have been proposed so far.     

Pricing CDOs with state-dependent stochastic recovery rates

Up to the 2007 crisis, research within bottom-up CDO models mainly concentrated on the dependence between defaults. Since then, due to substantial increases in market prices of systemic credit risk protection, more attention has been paid to recovery rate assumptions. In this paper, we use stochastic orders theory to assess the impact of recovery on CDOs and show that, in a factor copula framework, a decrease of recovery rates leads to an increase of the expected loss on senior tranches, even though the expected loss on the portfolio is kept fixed. This result applies to a wide range of latent factor models and is not specific to the Gaussian copula model. We then suggest introducing stochastic recovery rates in such a way that the conditional on the factor expected loss (or, equivalently, the large portfolio approximation) is the same as in the recovery markdown case. However, granular portfolios behave differently. We show that a markdown is associated with riskier portfolios than when using the stochastic recovery rate framework. As a consequence, the expected loss on a senior tranche is larger in the former case, whatever the attachment point. We also deal with implementation and numerical issues related to the pricing of CDOs within the stochastic recovery rate framework. Due to differences across names regarding the conditional (on the factor) losses given default, the standard recursion approach becomes problematic. We suggest approximating the conditional on the factor loss distributions, through expansions around some base distribution. Finally, we show that the independence and comonotonic cases provide some easy to compute bounds on expected losses of senior or equity tranches.