Journal Articles
Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915
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Item From scientific models to decisions: exploring uncertainty communication gaps between scientists and decision-makers(Springer Science+Business Media, LLC, 2025-09-01) Dhungana A; Doyle EEH; Prasanna R; McDonald GEffective communication of uncertainty relies on transparent exchanges between scientists and decision-makers. However, significant gaps often exist between how scientists and decision-makers perceive, understand, and communicate uncertainty. This study examines the dynamics of uncertainty communication between scientists and decision-makers, employing a reflective thematic analysis of 32 interview datasets, comprising 17 scientists and 15 decision-makers. Our results show that Scientists typically approach uncertainty through methodological rigour, employing technical vocabulary and probabilistic language, which aligns with their scientific training but often complicates comprehension for decision-makers. Conversely, decision-makers prioritise actionable insights and practical implications, requiring uncertainty to be communicated in a way that supports decision-making processes across diverse contexts. The study further highlights the need for tailored communication strategies that bridge the complexities of uncertainty with the practical needs of decision-makers, emphasising collaboration and user-focused uncertainty visualisations as pathways to enhance uncertainty communication between scientists and decision-makers for the uptake of uncertainty information into decision-making.Item Navigating scientific modelling and uncertainty: Insights from hazard, risk, and impact scientists in disaster risk management (DRM)(Elsevier Ltd, 2025-02-15) Dhungana A; Hudson Doyle E; McDonald G; Prasanna RScientific models have long been used as an important tool in assisting in decision-making in Disaster Risk Management (DRM). However, it is commonly understood that uncertainty in these models significantly influences the integration of model outputs into decision-making processes, presenting a challenge for effective uncertainty communication. This paper explores how scientists in DRM approach modelling and uncertainty. We conducted seventeen in-depth qualitative interviews in Aotearoa, New Zealand, with scientists working on DRM. We provided an overview of the varied approaches and key factors influencing their processes for model characterisation and communicating uncertainties. We used Reflective Thematic Analysis to construct key themes, including (a) model development and characterisation, (b) accountability and opinion, (c) communication approach and challenges, and (d) collaboration for effective uncertainty communication. We found that different DRM scientists have different disciplinary and experiential training, experience, and interaction with decision-makers. These factors greatly influence their choices regarding scientific modelling and communication of uncertainty. The lack of a generally accepted guideline for a best practice approach to uncertainty communication is a key barrier to successfully incorporating uncertainties into DRM decision-making. We suggest that a better collaboration between scientists and decision-makers throughout the lifecycle of the model development process is a way forward for effective communication of uncertainty in DRM decision-making.Item Rapid and Resilient LoRa Leap: A Novel Multi-Hop Architecture for Decentralised Earthquake Early Warning Systems(MDPI (Basel, Switzerland), 2024-09-13) Ranasinghe V; Udara N; Mathotaarachchi M; Thenuwara T; Dias D; Prasanna R; Edirisinghe S; Gayan S; Holden C; Punchihewa A; Stephens M; Drummond P; Galmés S; Atakan BWe introduce a novel LoRa-based multi-hop communication architecture as an alternative to the public internet for earthquake early warning (EEW). We examine its effectiveness in generating a meaningful warning window for the New Zealand-based decentralised EEW sensor network implemented by the CRISiSLab operating with the adapted Propagation of Local Undamped Motion (PLUM)-based earthquake detection and node-level data processing. LoRa, popular for low-power, long-range applications, has the disadvantage of long transmission time for time-critical tasks like EEW. Our network overcomes this limitation by broadcasting EEWs via multiple short hops with a low spreading factor (SF). The network includes end nodes that generate warnings and relay nodes that broadcast them. Benchmarking with simulations against CRISiSLab's EEW system performance with internet connectivity shows that an SF of 8 can disseminate warnings across all the sensors in a 30 km urban area within 2.4 s. This approach is also resilient, with the availability of multiple routes for a message to travel. Our LoRa-based system achieves a 1-6 s warning window, slightly behind the 1.5-6.75 s of the internet-based performance of CRISiSLab's system. Nevertheless, our novel network is effective for timely mental preparation, simple protective actions, and automation. Experiments with Lilygo LoRa32 prototype devices are presented as a practical demonstration.Item Nurturing partnerships to support data access for impact forecasts and warnings: Theoretical integration and synthesis(Elsevier B.V., 2024-04-15) Harrison SE; Potter SH; Prasanna R; Doyle EEH; Johnston DThis paper presents a synthesis and theoretical integration of findings from a research project that explored the data needs and sources for implementing impact forecasts and warnings for hydrometeorological hazards. Impact forecasts and warnings (IFW) have received global attention in recent years as they offer a novel way of improving the communication of hazards and risks. The fundamental idea behind IFWs is to enable warning services to meaningfully communicate the anticipated outcomes, consequences, or impacts of the hazard interacting with society or the environment by incorporating knowledge about the underlying and dynamic exposure and vulnerability of people and assets. One key question for IFW implementation is about data needs and sources to inform IFWs.Using the Grounded Theory Methodology, we address the question “How can partnerships and collaboration better facilitate the collection, creation, and access to hazard, impact, vulnerability, and exposure data for IFWs?” Our findings point to partnerships and collaboration as a necessary strategy for implementing IFWs. Implementation requires accessing various types and sources of hazard, impact, vulnerability, and exposure data to assess and communicate the potential impacts of hydrometeorological hazards. Partnerships and collaboration facilitate the sharing of and access to required data and knowledge. Based on our findings, we provide recommendations to increase interagency communication and partnerships for IFWs and disaster risk reduction, such as making cohabitation arrangements between agencies, running joint training scenarios, and encouraging meteorological services and emergency responders to co-define tailored warning thresholds.Item Online learning adoption by Chinese university students during the Covid-19 pandemic(School of Psychology, Massey University, 2022-12-01) Huggins TJ; Tan ML; Kuo Y-L; Prasanna R; Rea DDThe 2019 Novel Coronavirus Pandemic has severely challenged the continuity of post-secondary education around the world. Online learning platforms have been put to the test, in a context where student engagement will not occur as a simple matter of course. To identify the factors supporting online learning under pandemic conditions, a questionnaire based on the Unified Theory of Acceptance and Use of Technology was adapted and administered to a sample of 704 Chinese university students. Structural equation modelling was applied to the resulting data, to identify the most relevant theoretical components. Effort expectancy, social influence, and information quality all significantly predicted both students’ performance expectancies and the overall adoption of their university’s Moodle-based system. Performance expectancy mediated the effects of effort expectancy, social influence, and information quality on symbolic adoption. Internet speed and reliability had no clear impact on adoption, and neither did gender. The direct impact of information quality on symbolic adoption represents a particularly robust and relatively novel result; one that is not usually examined by comparable research. As outlined, this is one of three key factors that have predicted online learning engagement, and the viability of educational continuity, during the Coronavirus pandemic. The same factors can be leveraged through user-focused development and implementation, to help ensure tertiary education continuity during a range of crisesItem ‘End to end’ linkage structure for integrated impact assessment of infrastructure networks under natural hazards(New Zealand National Society for Earthquake Engineering, 2021-06-01) Imtiaz SY; Uma SR; Prasanna R; Wotherspoon LMAn infrastructure impact assessment process relies on the analysis of multiple types of models, the performance of individual infrastructure networks and the interdependencies between multiple infrastructure networks. Several models are developed for their specific purposes and there is a need to link these models for the assessment of natural hazard impacts on distributed infrastructures to deliver the desired outcomes on network functionality and disruption levels that are suitable to assess socio-economic impact. In this paper, an ‘end-to-end’ linkage structure is proposed to link different models by which various features, data standards, parameters and structures are linked in a transparent and consistent manner. The framework has adopted a dedicated knowledge discovery and data analysis process to acquire information around input and output parameters for each of these models developed by various researchers and used in risk assessment tools. The framework is illustrated by applying the step-by-step procedure towards integrated impact assessments of electricity, potable water and road networks and their interdependencies.Item The role of data and information quality during disaster response decision-making(Elsevier Ltd, 2021-12) Jayawardene V; Huggins TJ; Prasanna R; Fakhruddin BMassive amounts of data and information are exchanged during the response phase of disaster management. A large body of contemporary research has indicated that most of these data and information have severe quality related concerns, meaning that they may not be suitable for critical decision-making. The current paper addresses these issues by identifying how certain features of data and information quality function, to support specific, naturalistic decision-making processes during disaster response. These functions are used to revise and consolidate pre-existing definitions of data and information quality, for use in further disaster response research.Item Micro-theory on knowledge transfer to foster disaster resilience: A grounded theory approach(Elsevier Ltd, 2021-11) Ahangama N; Prasanna RAlthough recent literature suggested that knowledge generation and dissemination in social networks influence resilience, research in knowledge transfer and social capital domains have shown a low tendency to integrate into theoretical frameworks. This paper discusses the process of building a micro-theory, which explains the dynamics of knowledge transfer in social networks of disaster responders in Sri Lanka. The proposed theory suggests the association among knowledge transfer, dimensions of social capital, and resilience in a disaster context. This study employs an interpretive case study research design, with an exploratory approach and uses grounded theory driven constant comparison method for data analysis. The transcriptions from 21 semi-structured interviews and participant observations of two disaster drill exercises used as the primary data source for the data analysis. The analysis of this study generates a coding pattern with six categories of concepts and proposes the theory of KTinSSC with the theoretical consensus from the two case studies. The proposed theory explains the knowledge transfer among responders who are focused mostly on the immediate survival and discusses the effect of knowledge transfer interactions on their normative beliefs. The study also suggests ways to attain higher levels of resilience among such survival-focused social groups.Item ‘Sharing is caring’: A socio-technical analysis of the sharing and governing of hydrometeorological hazard, impact, vulnerability, and exposure data in Aotearoa New Zealand(Elsevier Ltd, 2022-01) Harrison SE; Potter SH; Prasanna R; Doyle EEH; Johnston DThere has been a growing recognition of the need to collect disaster and risk data over the last two decades. Accordingly, better collection and management of disaster data was identified as a priority of the Sendai Framework for Disaster Risk Reduction. The introduction and implementation of Impact Forecasts and Warnings (IFWs) have further highlighted this need to collect and access hazard, impact, vulnerability, and exposure (HIVE) data. However, challenges have been met with reporting and using disaster data, which have resulted in an identified need to establish principles for data collection, recording, reporting, exchange/sharing, and comparability. This introduces the concept of data governance and management for disaster data, particularly with regards to data custodianship, stewardship, and sharing. Using Grounded Theory, a series of interviews were conducted with users and creators of HIVE data to develop further understanding around managing and accessing it for severe weather hazards in New Zealand. A socio-technical lens guided the analysis to identify the organisational and technical intervening conditions and action/interaction strategies for accessing and sharing HIVE data in NZ. Findings indicated that there is a need to establish data governance principles for HIVE data in New Zealand. An additional need was identified for nurturing partnerships to continue building trust between stakeholders for sharing data. Furthermore, integration challenges continue to interfere with the use of various sources of HIVE data for effective risk and impact assessments for IFWs and beyond. Systematic and standardised data collection approaches using GIS-based tools can support integration.Item Volunteered Geographic Information for people-centred severe weather early warning: A literature review(Massey University, 2020-06-01) Harrison S; Potter S; Prasanna R; Doyle EEH; Johnston DEarly warning systems (EWSs) can prevent loss of life and reduce the impacts of hazards. Yet, recent severe weather events indicate that many EWSs continue to fail at adequately communicating the risk of the hazard, resulting in significant life and property loss. Given these shortcomings, there has been a shift towards people centred EWSs to engage with audiences of warnings to understand their needs and capabilities. One example of engaging with warning audiences is through the collection and co-creation of volunteered geographic information (VGI). Much of the research in the past has primarily focused on using VGI in disaster response, with less exploration of the role of VGI for EWSs. This review uses a scoping methodology to identify and analyse 29 research papers on EWSs for severe weather hazards. Results show that VGI is useful in all components of an EWS, but some platforms are more useful for specific components than are others. Furthermore, the different types of VGI have implications for supporting people-centred EWSs. Future research should explore the characteristics of the VGI produced for these EWS components and determine how VGI can support a new EWS model for which the World Meteorological Organization is advocating: that of impact-based forecasting and warning systems.
