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As complex man-made systems that are home to the majority of the world population, cities have always faced a wide range of risks such as earthquakes. As the backbone of urban systems, physical components, including buildings, transportation networks, communication networks, and open and green spaces, are also vulnerable to disasters. To enhance the capacity to deal with disaster risks, enhancing urban resilience has recently become an essential priority for cities. This study aims to develop and pilot test a framework to evaluate urban physical resilience based on resilience characteristics and associated physical indicators. Interpretive Structural Modelling (ISM) was used to determine the relationships between physical indicators, and Multi-Criteria Decision-Making methods were applied to determine the relative importance of the characteristics. The results showed that the ‘Robustness of Building’, ‘Building Density’, ‘Aspect Ratio’, and ‘Street Width’ are the most important among the twenty physical indicators considered in the proposed framework. Subsequently, the proposed framework was applied to one of the districts of Kerman, a major city located in the southwest, earthquake-prone part of Iran. Overall results indicate low levels of physical resilience. The findings of this study can provide urban planners and decision-makers with more transparent and practical insights into the physical resilience of cities. Results can also be used to design and implement policies and programs to improve the current conditions.

General morphological analysis (GMA) is a method for structuring and investigating the total set of relationships contained in multidimensional, usually non-quantifiable, problem complexes. Pioneered by Fritz Zwicky at the California Institute of Technology in the 1930s and 1940s, it relies on a constructed parameter space, linked by way of logical relationships, rather than on causal relationships and a hierarchal structure. During the past 10 years, GMA has been computerized and extended for structuring and analysing complex policy spaces, developing futures scenarios and modelling strategy alternatives. This article gives a historical and theoretical background to GMA as a problem structuring method, compares it with a number of other 'soft-OR' methods, and presents a recent application in structuring a complex policy issue. The issue involves the development of an extended producer responsibility (EPR) system in Sweden.

Causal maps are widely employed in problem-structuring interventions. They permit a rich representation of ideas, through the modelling of complex chains of argument as networks. The last stage of a problem-structuring intervention is often to identify and agree to a set of potential strategic options. In some circumstances the preferred direction may emerge naturally from a process of negotiation; in others further, more-or-less formal, analysis to evaluate the options and to understand their impacts on the goals could be helpful. Such analysis may help to bring closure to the process. The main aim of this paper is to review systematically the approaches for evaluating options following from the use of a causal map for problem structuring; some directly using the map structure, others working with concepts extracted from, or an external model derived from, the map. Following a proposed taxonomy, each approach is presented, and its advantages and disadvantages are discussed.

To be able to exploit the future opportunities for Operational Research (OR), we need to prepare for them now. To conceptualize alternative futures for OR, we need to understand the potentialities of the present. To understand the present, we need to have a grasp of the past history that gave us the OR that we have, rather than some other analytic practice. OR was thrown up by a situation where traditional management methods were proving inadequate to handle the growing complexity of organizational arrangements. Problem structuring methods (PSMs) in turn were generated out of a sense that the trajectory of OR had led it away from important areas of social decision-making. PSMs have made great strides but are still encountering barriers to acceptance. This paper will explore the factors that presently constrain PSMs, and what developments could take them into new fields.

This paper discusses the challenges associated with the evaluation of problem-structuring methods (PSMs). PSMs are seen as complex interventions that seek wide-level change and action at many levels including individual and system. There is now a widespread acceptance that the traditional evaluation approaches are inappropriate for the evaluation of PSMs. The difficulty is compounded when PSMs are used in multi-agency settings. The paper proposes that evaluation, while pragmatic and situated, must be a theory-based exercise. Part of the challenge is to provide a narrative of the intervention as well as an agreed assessment.

Problem structuring methods (PSMs) are a family of participatory and interactive methods whose purpose is to assist groups of diverse composition tackle a complex problematic situation of common interest. This is achieved through modelling and facilitation, with a view to generating consensus on problem structure, and agreement on initial commitments. Despite the apparent success of PSMs reported in the literature, little progress has been made towards the development of theoretical models that integrate these experiences and guide PSM practitioners and academics in developing and implementing effective PSM interventions. In particular, no theoretical models have been presented concerning how conversational processes within a group are affected by PSMs. This paper develops a theoretical model of conversation intended to provide a means to identify a specific role for the analytical assistance provided through PSMs, and for evaluating their effectiveness. The hypothesis articulated from this model is that PSMs have the potential to improve the quality of the conversation in which actors participate. PSMs generate this effect through facilitating the structuring and sense-making activities embedded within a conversation. Improvement in the quality of conversation should tend to help actors engage in dialogue as a particular form of conversation, achieve shared understanding, and increase the actors' ownership of the commitments achieved during the conversation. The paper concludes with a discussion of the implications of the model for research and practice.

In this paper, we present the results of an empirical study that was conducted to demonstrate how the Structured MCDM methodology which is based on Nomology, the science of the laws of the mind, could be used to support problem structuring and improve rural community participation in a developing country in Africa. The results support the view that a model which is based on a generic structure is flexible and transferable to similar problem contexts and various situations across cultures and beyond national borders; and that it can easily support distributed participatory decision-making or be integrated into a Participatory Decision Support System.

Conventional approaches to change management tend to be prescriptive with the assumption that the specific course of action will lead to the intended outcome, with surprise when this does not materialise as expected. This possibly can be attributed to a failure to understand the context of change and thereby the failure to deal with conditions less than conducive to supporting the desired change. This paper presents Raul Espejo's Viplan Methodology as an appropriate framework to examine the context of change in an explicit and structured manner and thereby support the creation of conditions more conducive to change, thus increasing the likelihood of the desired outcomes. It draws upon the author's experience as a practitioner engaged in effecting operational change within UK small and medium-sized enterprises.

Decision workshops, sometimes called decision conferences, help a group of decision makers gain a shared understanding of a decision problem, analyse issues and commit to an action plan under the guidance of an experienced facilitator. This work seeks to identify best practice in the early stages of the facilitation of such workshops when the emphasis is placed on problem structuring and the main issues of a complex decision problem are identified and explored. Four decision workshops, based on the same hypothetical scenario but facilitated by a different person, were organized. Video material of the simulated workshops was analysed to compare and contrast the facilitated meetings including the problem structuring methods used. A framework for studying facilitation practices emerged. The effect of a facilitator on the structuring of the problem, the group decision process and the outcome of the workshop was studied. The results of the work indicate that a facilitator's style and approach to the workshop may have an impact on the action plan devised. Further research is required to generalize the findings of our work.

The design of buildings has become a complex and multidisciplinary problem involving multiple conflicting objectives as architects and designers address competing technical, economic, environmental, and societal concerns. This has been driving research in Architecture, Engineering, and Construction (AEC) toward rigorous multidisciplinary decision-making frameworks that generate and evaluate numerous design alternatives using multi-objective optimization in concert with simulation and analysis models of varying fidelity and computational expense. While such frameworks are well known and widely employed in the aerospace and systems engineering domains, efforts by design professionals and researchers in the AEC field are scattered at best. In this paper, we provide a detailed review of recent developments in optimization frameworks in the AEC field and subsequently highlight how such developments are largely compartmentalized into separate domains such as structural, energy, daylighting, and other performance factors. We further discuss the technical challenges involved in concurrent coupled multidisciplinary design optimization (MDO) in the AEC field such as interoperability issues between Building Information Modeling (BIM) environments, analysis/simulation tools, and optimization frameworks. We conclude by outlining research needed for more unified modeling and simulation-based optimization frameworks to aid in complex and multidisciplinary building design processes. We also highlight the need for the identification and development of multi-fidelity simulation tools for use across multiple design phases. As such, this paper contributes a novel roadmap to leverage aerospace and systems engineering research in MDO into the field of AEC, along with a call for researchers in the MDO community to seek collaborations in AEC field.