Metamodern Strategy: A System Of Multi-Ontological Sense Making

Multi-ontological sense making in irreducible social systems requires the use of different worldviews to generate contextually appropriate understandings and insights for action in different systems states. While models exist for describing complex dynamics in social systems, no frameworks or aids exist to explain the system of worldviews. This dissertation developed a conceptual scheme that will aid in multi-ontological sense making in social systems. This conceptual scheme has both theoretical and practical implications for visualizing, understanding, and responding to social systems and ultimately to complexity. To develop this new conceptual scheme, a qualitative meta-synthesis approach was adopted to develop theory and to develop a framework for classifying management approaches, tools and techniques to corresponding worldviews for use in dynamic and complicated social systems. The research design was sequential, with four phases. In phase one a content analysis of 16 worldviews was conducted to develop a classification framework for worldviews. In phase two the worldview classification framework was then applied to 35 strategy consulting approaches to categorize the approaches to differing underlying worldviews and to understand the ontological mapping of the differing approaches. Phase three was analyzing the data, the results of which showed that strategy consulting engagements cast sense making in social systems primarily into three simplified quadrants: the simple, complex, and complicated. The results further showed that only the process consulting approaches adopted a multi-dimensional, worldview-driven approach to social systems, an approach that moved beyond the simplified states of the expert, doctor-patient, and emergent approaches to strategy consulting. In phase four a new theory of sense making was developed: the aspectus system. The aspectus system stresses the importance of segregating sense making activities in social systems into two distinct worldview-driven categories: (a) simplified sense making which informs and is followed by (b) metamodern sense making. In doing so, the Aspectus system separates worldview-driven sense making in social systems into a separate domain, emphasizing that social systems must be considered as both complex and complicated and also as distinct from other types of systems. The aspectus system application in shared sense making was then tested in a thought experiment to demonstrate how it should be applied in practice. The results indicate that a worldview-driven, metamodern approach to multi- ontological sense making in irreducible complex and complicated social systems generates contextually appropriate models for understanding, insights, and actions

Agent Based Modeling in Land-Use and Land-Cover Change Studies

Agent based models (ABM) for land use and cover change (LUCC) holds the promise to provide new insight into the processes and patterns of the human and biophysical interactions in ways that have never been explored. Advances in computer technology make it possible to run almost infinite numbers of simulations with multiple heterogeneously shaped actors that reciprocally interact via vertical and horizontal power lines on various levels. Based upon an extensive literature review the basic components for such exercises are explored and discussed. This resulted in a systematic representation of these components consisting of: (1) Spatial static input data, (2) Actor and Actor-group static input data, (3) Spatial dynamic input, (4) Actor and Actor-group dynamic input data, (5) the model with the rules describing the rules, (6) Spatial static output, (7) Actor and Actor-group static output, (8) Dynamic output of Actor behaviour changes, (9) Dynamic output of actor-group behavioural changes, (10) Dynamic output of spatial patterns, (11) Dynamic output of temporal patterns. This representation proves to be epistemologically useful in the analysis of the relationships between the ABM LUCC components. In this paper, this representation is also used to enumerate the strengths and limitations of agent based modelling in LUCC

Social representations of diagnosis in the consultation

Observations of physiotherapy consultations and qualitative interviews with patients were conducted to explore the clinical explanation for sciatic pain. We report three themes which illustrate the contested and negotiated order of the clinical explanation: anchoring, resistance and normalisation. We show using the theory of social representations how the social order in the physiotherapy consultation is maintained, contested and rearticulated. We highlight the importance of agency in patients’ ability to resist the clinical explanation and in turn shape the clinical discourse within the consultation. Social representations offer insights into how the world is viewed by different individuals, in our case physiotherapists and patients with sciatic pain symptoms. The negotiation about the diagnosis reveals the malleable and socially constructed nature of pain and the meaning making process underpinning it. The study has implications for understanding inequalities in the consultation and the key ingredients of consensus

Reducing ambiguity to close the science-policy gap

Scientists often worry that their evidence is not used properly in the policy-making process. Their main response is to change the supply of evidence to reduce policymaker uncertainty. They should focus more on ambiguity, combining evidence and persuasion to help policymakers define the policy problem. To do so, they need to understand the policy process in which they engage. They cannot do so alone. Policy scholars can help, by articulating the practical value of policy theories. To help most effectively, they need to state clearly the “causal mechanisms” of the policy process. For example, what causes policymakers to pay attention to an issue informed partly by evidence, or what rules guide their behavior most strongly when weighing up evidence with other factors? In this paper, we show that policy theories have informed this debate, but often without making explicit statements of causality. We draw on the social science causal mechanisms field to improve such analysis and suggest use qualitative methods to clarify and measure causal mechanisms to benefit policy scholars and the wider policy analysis community. A focus on mechanisms can inform policy scholarship, science community engagement and on-the-ground policy work

Bayesian participatory-based decision analysis : an evolutionary, adaptive formalism for integrated analysis of complex challenges to social-ecological system sustainability

Includes bibliographical references (pages. 379-400).This dissertation responds to the need for integration between researchers and decision-makers who are dealing with complex social-ecological system sustainability and decision-making challenges. To this end, we propose a new approach, called Bayesian Participatory-based Decision Analysis (BPDA), which makes use of graphical causal maps and Bayesian networks to facilitate integration at the appropriate scales and levels of descriptions. The BPDA approach is not a predictive approach, but rather, caters for a wide range of future scenarios in anticipation of the need to adapt to unforeseeable changes as they occur. We argue that the graphical causal models and Bayesian networks constitute an evolutionary, adaptive formalism for integrating research and decision-making for sustainable development. The approach was implemented in a number of different interdisciplinary case studies that were concerned with social-ecological system scale challenges and problems, culminating in a study where the approach was implemented with decision-makers in Government. This dissertation introduces the BPDA approach, and shows how the approach helps identify critical cross-scale and cross-sector linkages and sensitivities, and addresses critical requirements for understanding system resilience and adaptive capacity

An agent-based fuzzy cognitive map approach to the strategic marketing planning for industrial firms

This is the post-print version of the final paper published in Industrial Marketing Management. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Industrial marketing planning is a typical example of an unstructured decision making problem due to the large number of variables to consider and the uncertainty imposed on those variables. Although abundant studies identified barriers and facilitators of effective industrial marketing planning in practice, the literature still lacks practical tools and methods that marketing managers can use for the task. This paper applies fuzzy cognitive maps (FCM) to industrial marketing planning. In particular, agent based inference method is proposed to overcome dynamic relationships, time lags, and reusability issues of FCM evaluation. MACOM simulator also is developed to help marketing managers conduct what-if scenarios to see the impacts of possible changes on the variables defined in an FCM that represents industrial marketing planning problem. The simulator is applied to an industrial marketing planning problem for a global software service company in South Korea. This study has practical implication as it supports marketing managers for industrial marketing planning that has large number of variables and their cause–effect relationships. It also contributes to FCM theory by providing an agent based method for the inference of FCM. Finally, MACOM also provides academics in the industrial marketing management discipline with a tool for developing and pre-verifying a conceptual model based on qualitative knowledge of marketing practitioners.Ministry of Education, Science and Technology (Korea

Helping Business Schools Engage with Real Problems: The Contribution of Critical Realism and Systems Thinking

The world faces major problems, not least climate change and the financial crisis, and business schools have been criticised for their failure to help address these issues and, in the case of the financial meltdown, for being causally implicated in it. In this paper we begin by describing the extent of what has been called the rigour/relevance debate. We then diagnose the nature of the problem in terms of historical, structural and contextual mechanisms that initiated and now sustain an inability of business schools to engage with real-world issues. We then propose a combination of measures, which mutually reinforce each other, that are necessary to break into this vicious circle – critical realism as an underpinning philosophy that supports and embodies the next points; holism and transdisciplinarity; multimethodology (mixed-methods research); and a critical and ethical-committed stance. OR and management science have much to contribute in terms of both powerful analytical methods and problem structuring methods

A normal paranoia? The emergence of distrust between parents of autistic children and public officials

This paper explores the development of distrust and paranoia among parents and carers of autistic children in their interactions with public officials charged with such children’s diagnosis, education and care. The suspicion and distrust framework of Fein and Hilton (1994), and Kramer’s typology of organisational paranoia (1998, 2001) are used to show how distrust impacts on client experiences. Antecedents of distrust are identified, and the ‘normalcy’ of paranoia in this context is demonstrated. These findings should permit public sector staff dealing with parents and carers of autistic children to address such perceptions and build trust where little seems to exist