Управління складністю в університетському середовищі: контексти прийняття рішень за Cynefin

This paper considers some aspects of changes and transformations the contemporary university model undergoes. The paper suggests to use David Snowden’s Cynefin framework not only for providing the analysis of knowledge management or organizational learning but also for upgrading the University as such.У статті розглянуто деякі аспекти змін і трансформацій моделі сучасного універ- ситету. Пропонується використати теорію управління складністю Cynefin за Д. Сноуденом не лише для аналізу управління знаннями чи організаційного навчання, але й для вдосконалення моделі університету в цілому

Integrating multicriteria decision analysis and scenario planning : review and extension

Scenario planning and multiple criteria decision analysis (MCDA) are two key management science tools used in strategic planning. In this paper, we explore the integration of these two approaches in a coherent manner, recognizing that each adds value to the implementation of the other. Various approaches that have been adopted for such integration are reviewed, with a primary focus on the process of constructing preferences both within and between scenarios. Biases that may be introduced by inappropriate assumptions during such processes are identified, and used to motivate a framework for integrating MCDA and scenario thinking, based on applying MCDA concepts across a range of "metacriteria" (combinations of scenarios and primary criteria). Within this framework, preferences according to each primary criterion can be expressed in the context of different scenarios. The paper concludes with a hypothetical but non-trivial example of agricultural policy planning in a developing country

Communicating geographical risks in crisis management : the need for research

In any crisis, there is a great deal of uncertainty, often geographical uncertainty or, more precisely, spatiotemporal uncertainty. Examples include the spread of contamination from an industrial accident, drifting volcanic ash, and the path of a hurricane. Estimating spatiotemporal probabilities is usually a difficult task, but that is not our primary concern. Rather, we ask how analysts can communicate spatiotemporal uncertainty to those handling the crisis. We comment on the somewhat limited literature on the representation of spatial uncertainty on maps. We note that many cognitive issues arise and that the potential for confusion is high. We note that in the early stages of handling a crisis, the uncertainties involved may be deep, i.e., difficult or impossible to quantify in the time available. In such circumstance, we suggest the idea of presenting multiple scenarios

Communicating geographical risks in crisis management: The need for research

In any crisis, there is a great deal of uncertainty, often geographical uncertainty or, more precisely, spatio-temporal uncertainty. Examples include the spread of contamination from an industrial accident, drifting volcanic ash, and the path of a hurricane. Estimating spatio-temporal probabilities is usually a difficult task, but that is not our primary concern. Rather, we ask how analysts can communicate spatio-temporal uncertainty to those handling the crisis. We comment on the somewhat limited literature on the representation of spatial uncertainty on maps. We note that many cognitive issues arise and that the potential for confusion is high. We note that in the early stages of handling a crisis the uncertainties involved may be deep, i.e. difficult or impossible to quantify in the time available. In such circumstance, we suggest the idea of presenting multiple scenarios

Decision theory in sustainable supply chain management: a literature review

Purpose – This study aims to aid theory building, the use of decision theory (DT) concepts in sustainable supply chain management (SSCM) research is examined. Design/methodology/approach – An abductive approach considers two DT concepts, Snowden’s Cynefin framework for sense-making and Keeney’s value-focussed decision analysis, in a systematic literature review of 160 peer-reviewed papers in English. Findings – Around 60 per cent of the papers on decision-making in SSCM come from operational research (OR), which makes explicit use of DT. These are almost all normative and rationalist and focussed on structured decision contexts. Some exceptions seek to address unstructured decision contexts via Complex Adaptive Systems or Soft Systems Methodology. Meanwhile, a second set, around 16 per cent, comes from business ethics and are empirical, behavioural decision research. Although this set does not explicitly refer to DT, the empirical evidence here supports Keeney’s value-focussed analysis. Research limitations/implications – There is potential for theory building in SSCM using DT, but the research only addresses SSCM research (including corporate responsibility and ethics) and not DT in SCM or wider sustainable development research. Practical implications – Use of particular decision analysis methods for SSCM may be improved by better understanding different decision contexts. Social implications – The research shows potential synthesis with ethical DT absent from DT and SCM research. Originality/value – Empirical behavioural decision analysis for SSCM is considered alongside normative, rational analysis for the first time. Value-focussed DT appears useful for unstructured decision contexts found in SSCM. Originality/value – Empirical, behavioural decision analysis for SSCM is considered alongside normative rational analysis for the first time. Value-focussed DT appears useful for unstructured decision contexts found in SSCM

A decision theory perspective on complexity in performance measurement and management

Purpose – The purpose of this paper is to apply the aspects of decision theory to performance measurement and management (PMM), thereby enabling the theoretical elaboration of volatility, uncertainty, complexity and ambiguity in the business environment, which are identified as the barriers to effective PMM. Design/methodology/approach – A review of decision theory and PMM literature establishes the Cynefin framework as the basis for extending the performance alignment matrix. Case research with seven companies explores the relationship between two concepts underexamined in the performance alignment matrix – internal dominant logic (DL) as the attribute of organisational culture affecting decision making, and the external environment – in line with the concept of alignment or fit in PMM. A focus area is PMM related to sustainable operations and supply chain management. Findings – Alignment between DL, external environment and PMM is found, as are instances of misalignment. The Cynefin framework offers a deeper theoretical explanation about the nature of this alignment. Other findings consider the nature of organisational ownership on DL. Research limitations/implications – The cases are exploratory not exhaustive, and limited in number. Organisations showing contested logic were excluded. Practical implications – Some organisations have cultures of predictability and control; others have cultures that recognise their external environment as fundamentally unpredictable, and hence there is a need for responsive, decentralised PMM. Some have sought to change their culture and PMM. Being attentive to how cultural logic affects decision making can help reduce the misalignment in PMM. Originality/value – A novel contribution is made by applying decision theory to PMM, extending the theoretical depth of the subject

Eliciting Model Structures for Multivariate Probabilistic Risk Analysis

Notionally objective probabilistic risk models, built around ideas of cause and effect, are used to predict impacts and evaluate trade-offs. In this paper, we focus on the use of expert judgement to fill gaps left by insufficient data and understanding. Psychological and contextual phenomena such as anchoring, availability bias, confirmation bias and overconfidence are pervasive and have powerful effects on individual judgements. Research across a range of fields has found that groups have access to more diverse information and ways of thinking about problems, and routinely outperform credentialled individuals on judgement and prediction tasks. In structured group elicitation, individuals make initial independent judgements, opinions are respected, participants consider the judgements made by others, and they may have the opportunity to reconsider and revise their initial estimates. Estimates may be aggregated using behavioural, mathematical or combined approaches. In contrast, mathematical modelers have been slower to accept that the host of psychological frailties and contextual biases that afflict judgements about parameters and events may also influence model assumptions and structures. Few, if any, quantitative risk analyses embrace sources of uncertainty comprehensively. However, several recent innovations aim to anticipate behavioural and social biases in model construction and to mitigate their effects. In this paper, we outline approaches to eliciting and combining alternative ideas of cause and effect. We discuss the translation of ideas into equations and assumptions, assessing the potential for psychological and social factors to affect the construction of models. We outline the strengths and weaknesses of recent advances in structured, group-based model construction that may accommodate a variety of understandings about cause and effect

Final Preprint of paper published in Omega

Abstract Scenario planning and multiple criteria decision analysis (MCDA) are two key management science tools used in strategic planning. In this paper, we explore the integration of these two approaches in a coherent manner, recognizing that each adds value to the implementation of the other. Various approaches that have been adopted for such integration are reviewed, with a primary focus on the process of constructing preferences both within and between scenarios. Biases that may be introduced by inappropriate assumptions during such processes are identified, and used to motivate a framework for integrating MCDA and scenario thinking, based on applying MCDA concepts across a range of "metacriteria" (combinations of scearios and primary criteria). Within this framework, preferences according to each primary criterion can be expressed in the context of different scenarios. The paper concludes with a hypothetical but non-trivial example of agricultural policy planning in a developing country. Keywords: multicriteria decision analysis; scenario planning; decision making under uncertainty Background and Context Our initial motivation for this paper was a concern that many quantitative decision analytic models do not adequately deal with the many uncertainties and risks that arise in long term strategic decision making contexts. We are particularly concerned with the use of multi-criteria value models and, to some extent, decision trees and influence diagrams, but the same difficulties occur in using other quantitative models: we would contend all other quantitative models. French [1995] has written on the different forms of uncertainty that may arise in decision modelling and analysis and this paper to som