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Multi Actor Multi Criteria Analysis
Edited by Cathy Macharis and Gino Baudry
Professor Eve Mitleton-Kelly
Is it possible to effectively address complex problems when there are multiple and often conflicting interests, as well as multiple interacting causalities, within a constantly changing and complex environment? The analysis of such problems often results in an endless list of often contradictory factors and provides a picture with no linear causality and no overall coherent meaning, too random to help explain the complex interactions that led to the problem. Understanding not only the characteristics of organisations with their multiple interacting issues and causalities, but their co-evolutionary dynamics is the key here. This chapter provides detailed advice on how to use the complexity perspective in real life examples showing how the two parts of the EMK methodology were used in a challenging context. The first part was the identification of the multi-dimensional problem space and the co-evolutionary dynamics between the multiple dimensions, which provided a starting point for decision-making. The second part acknowledged that complex problems do not have single solutions, but need a broader enabling environment, capable of addressing the challenge over time as it changes and evolves.
Professor Michael E. Wolf-Branigin, Dr William G. Kennedy, Dr Emily S. Ihara and Dr Catherine J. Tompkins
Human services planners and evaluators require an increasing high level of flexibility and adaptability to remain effective in measuring the effectiveness of social interventions. Understanding the logic and assessing the impact behind the intervention can be difficult because commonly-used evaluative tools are based primarily on linear methods that assume that a set amount of input, throughput, and output will result in a set outcome. This chapter takes a complexity science approach and facilitates the use of agent-based modelling (ABM). It provides the requisite background for evaluators and researchers to frame their efforts as complex adaptive systems. These systems have several components that include agents having options, boundaries, self-organising behaviour, different options from which to choose, feedback to adapt, and an emergent behaviour. Complexity is viewed as a mathematical field where the relations between inputs and are better understood through simulations. Both qualitative and quantitative aspects of complexity are addressed through two applications of ABM that consider related social policy issues.
Associate Professor Benyamin Lichtenstein
Complexity science has been described as an amalgam of ‘models, methods, and metaphors’ for understanding dynamic systems. Methods most commonly associated with complexity are computational simulations. Although these have contributed greatly to organization, they represent just one category of complexity methods. A main goal of this chapter is to introduce what the author considers to be the 15 sciences of complexity, organized into three main paradigms or approaches: computational agent-based modelling; natural sciences and idiographic analogies; and, narrative and multi-method studies. The chapter presents a set of complexity methods and models that may be much broader than the norm. Researchers can use these to help identify the appropriate complexity methods to use to answer a specific research question. The value of this is underlined by many scholars who argue that the choice of a research method should be based on the kind of question being asked, rather than the method most familiar to the researcher.
Julian Burton and Sam Mockett
This chapter looks at the use of visual representations of organisational strategy in combination with facilitated dialogue (’Visual Dialogue’) as a complexity-inspired tool for culture change and organisational development. The process creates spaces for employees and leaders to come together to make sense of what is happening, what needs to change, and what actions are required. At the operational level, the process helps shift the way people talk about change and, as a result, enables the change process to become more meaningful, engaging and effective. We describe some of the cultural challenges of turning strategy into action and show how we have used the Visual Dialogue process as an Organisational Development intervention to address some of the key aspects of these challenges. Finally, we describe the component parts of Visual Dialogue and how each contributes to creating such enabling environments and supporting emergent change.
Professor Peter Allen
Perceived Benefits versus Unintended Consequences
Imad A. Moosa
Research output is evaluated by a combination of quantity (the number of research articles published) and quality, where quality is typically measured by the status of the journal in which the research is published. The citation-based approach (also called the citational approach and bibliometric method) has become the dominant method used to rank journals, reflecting in part the increasing availability of citation data. For all practical purposes, citation analysis began with the publication of the Science Citation Index (SCI) in 1961. Measuring journal quality by citation indices is questioned on the grounds that citations do not necessarily reflect impact. Although a long list of arguments can be presented against the use of citations, the citation approach is less subjective than other approaches to journal ranking.
Professor Pierpaolo Andriani and Professor Giuseppe Carignani
This chapter discusses the complex analogy between biological evolution and technological innovation, focusing in particular on the novel construct modular exaptation. After carefully defining exaptation – a biological concept whose technological analogue is useful in innovation studies – the chapter explores its epistemological bases, arguing that the etiological concept of function – a biological tenet – is valid also in the technological domain. The complex analogy extends to biological and technological functional modules, providing the main building block on which modular exaptation can be founded. Establishing a complex analogy enables the description of the two domains via the same relational structure. In turns this allows the transferability of knowledge from the base domain to the target domain, and vice-versa. The complex analogy can therefore be considered a methodological tool for understanding complex systems in general and technological innovation in particular, as discussed in the final section of the chapter.