Managing uncertainty: Principles for improved decision making

Kaye, P. H.; Smith, Andy; Strudwick, M. J.; White, Mark A.; Bird, Chloe E.; Aggarwal, Geeta; Durkin, T.; Marcuson, T. A. G.; Masters, T. R.; Regan, Natasha; Restrepo, Sebastián Arango; Toller, J. R.; White, S.; Wilkinson, Rob

doi:10.1017/s135732172000015x

Cited by 3 publications

(4 citation statements)

References 8 publications

(5 reference statements)

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“…Uncertainty refers to the state of mind to be unsure or doubtful about someone or something. It can be either about an outcome, any questions asked, the context of the issue or the dynamics of a problem and generally, its effect is considered as a negative phenomenon Kaye et al (2020). The results confirmed that uncertainty does not moderate any of the relationships hypothesized between four predictors of behavioral intention.…”

Section: Discussionmentioning

confidence: 55%

“…This scale was developed in accordance with the definition of uncertainty given in the literature review. It was difficult to adopt any previously studied scale as the dimensions of the variable change with the change in context and situation (Kaye et al , 2020). All of the constructs are measured on a five-point Likert scale from 1 (strongly disagree) to 5 (strongly agree) ranges.…”

Section: Methodsmentioning

confidence: 99%

“…It has been described as a feeling of incomplete, ambivalent and unreliable information, insufficient understanding and inconsistent alternatives (Lipshitz and Strauss, 1997). Furthermore, According to Kaye et al (2020) “uncertainty is a fact of life – and it is not outcomes that are uncertain. Often uncertainty is around the question being asked, the context of the issue being touched on and the dynamics of the problem at hand.” He has broadened the concept of uncertainty including uncertainty about any query, issue and problem faced, such as pandemic situation.…”

Section: Literature Review and Hypotheses Developmentmentioning

confidence: 99%

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Forced online experiment and its acceptance among the University students during pandemic in Pakistan

Abdullah

Parveen

Haq

2021

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Purpose This study aims to assess the acceptability of online classes among university students of Pakistan through the extension of the unified theory of acceptance and use of technology (UTAUT) model. Design/methodology/approach This study follows a quantitative research approach and data were collected from 662 university students of 10 different universities of Pakistan through a self-administrative Web survey. Structural equation modeling through SmartPLS was used to analyze the data. Findings Findings of the research show that performance expectancy, effort expectancy, social influence and facilitating conditions play a significant role in developing the intention to adopt online classes. Furthermore, facilitating conditions and intention to adopt online classes have further resulted in frequent use behavior. The authors also investigated the moderating role effect of active learning in relationship behavioral intention and use behavior. Findings show that active learning is an important component of online classes that interacts with the behavioral intention to develop the behavior of attending the online mode of learning by students. However, no significant moderation of uncertainty was found in the relationship between four components of acceptance of technology and behavioral intention to adopt the technology. Originality/value The authors have extended the UTUAT model by establishing the relationship between facilitating conditions and behavioral intention that supports e-learning. Furthermore, this study tests the moderating role of uncertainty and active learning on the UTUAT model.

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Section: Discussionmentioning

confidence: 55%

Section: Methodsmentioning

confidence: 99%

Section: Literature Review and Hypotheses Developmentmentioning

confidence: 99%

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Forced online experiment and its acceptance among the University students during pandemic in Pakistan

Abdullah

Parveen

Haq

2021

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“…Since ill-structured problems arise in all facets of life, this has led to many studies in different domains, for example in psychology (e.g. Frensch and Funke 1995;Stadler et al 2019), design thinking (Goel and Pirolli 1992;Buchanan 1992;Conklin 2006;Brown 2008;Kolko 2015;Micheli et al 2019), instructional design (Jonassen 1997(Jonassen , 2000 McDonald and Yanchar 2020), project management (Ahern et al 2014; Mikkelsen 2020), business decision-making (Snowden 2002;Kaye et al 2020) and engineering education (Dringenberg and Purzer 2018;Wolff 2020).…”

Section: Dealing With Problem Situationsmentioning

confidence: 99%

Introducing the VIPLAN Methodology (with VSM) for Handling Messy Situations – Nine Lessons

Harwood

2020

Syst Pract Action Res

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This paper examines the utility of a novel and relatively unknown approach to handling messy situations. This approach, developed by Raul Espejo, is the VIPLAN Methodology. It is presented as a heuristic and comprises a set of six activities which act as ‘pointers’ to guide thinking and actions. The methodology’s contribution rests upon its explicit focus upon the context within which messy situations are handled. This draws attention to the cybernetics of the situation (Cybernetic Loop), which can be made sense of using the Viable System Model. However, one of the challenges of the methodology is the perception that it is complex and difficult to use. A case-study is used to investigate how the methodology can be operationalised. This reveals a set of nine lessons, which are offered as guidelines to enhance our understanding of how to use the VIPLAN Methodology.

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Future-proofing the emergency recovery plan for freshwater biodiversity

et al. 2023

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Freshwater biodiversity loss is accelerating globally, but humanity can change this trajectory through actions that enable recovery. To be successful, these actions require coordination and planning at a global scale. The Emergency Recovery Plan for global freshwater biodiversity aims to reduce the risk for freshwater biodiversity loss through six priority actions: 1) accelerate implementation of environmental flows; 2) improve water quality to sustain aquatic life; 3) protect and restore critical habitats; 4) manage exploitation of freshwater species and riverine aggregates; 5) prevent and control nonnative species invasions in freshwater habitats; and 6) safeguard and restore freshwater connectivity. These actions can be implemented using future-proofing approaches that anticipate future risks (e.g., emerging pollutants, new invaders, synergistic effects) and minimize likely stressors to make conservation of freshwater biodiversity more resilient to climate change and other global environmental challenges. While uncertainty with respect to past observations is not a new concern for freshwater biodiversity, future-proofing has the distinction of accounting for the uncertainty of future conditions that have no historical baseline. The level of uncertainty with respect to future conditions is unprecedented. Future-proofing of the Emergency Recovery Plan for freshwater biodiversity will require anticipating future changes and developing and implementing actions to address those future changes. Here, we showcase future-proofing approaches likely to be successful using local case studies and examples. Ensuring that response options within the Emergency Recovery Plan are future-proofed will provide decision-makers with science-informed choices, even in the face of uncertain and potentially new future conditions. We are at an inflection point for global freshwater biodiversity loss; learning from defeats and successes can support improved actions towards a sustainable future.

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Managing uncertainty: Principles for improved decision making

Cited by 3 publications

References 8 publications

Forced online experiment and its acceptance among the University students during pandemic in Pakistan

Forced online experiment and its acceptance among the University students during pandemic in Pakistan

Introducing the VIPLAN Methodology (with VSM) for Handling Messy Situations – Nine Lessons

Future-proofing the emergency recovery plan for freshwater biodiversity

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