Browsing by Subject "Decision support"
Now showing items 1-4 of 4
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(2021)Human activities both depend upon and have consequences on the environment. Environmental risk assessment (ERA) is a process of estimating the probability and consequences of the adverse effects of human activities and other stressors on the environment. Bayesian networks (BNs) can synthesize different types of knowledge and explicitly account for the probabilities of different scenarios, therefore offering a useful tool for ERA. Their use in formal ERA practice has not been evaluated, however, despite their increasing popularity in environmental modeling. This paper reviews the use of BNs in ERA based on peer‐reviewed publications. Following a systematic mapping protocol, we identified studies in which BNs have been used in an environmental risk context and evaluated the scope, technical aspects, and use of the models and their results. The review shows that BNs have been applied in ERA, particularly in recent years, and that there is room to develop both the model implementation and participatory modeling practices. Based on this review and the authors’ experience, we outline general guidelines and development ideas for using BNs in ERA. Integr Environ Assess Manag 2021;17:62–78. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC)
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(2020)Machine learning platforms have emerged as a new promissory technology that some argue will revolutionize work practices across a broad range of professions, including medical care. During the past few years, IBM has been testing its Watson for Oncology platform at several oncology departments around the world. Published reports, news stories, as well as our own empirical research show that in some cases, the levels of concordance over recommended treatment protocols between the platform and human oncologists have been quite low. Other studies supported by IBM claim concordance rates as high as 96%. We use the Watson for Oncology case to examine the practice of using concordance levels between tumor boards and a machine learning decision-support system as a form of evidence. We address a challenge related to the epistemic authority between oncologists on tumor boards and the Watson Oncology platform by arguing that the use of concordance levels as a form of evidence of quality or trustworthiness is problematic. Although the platform provides links to the literature from which it draws its conclusion, it obfuscates the scoring criteria that it uses to value some studies over others. In other words, the platform "black boxes" the values that are coded into its scoring system.
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(2021)Abundance of information characterises decision-making about forest use. This challenges forest owners. Digitalisation and diverse e-services may enhance the delivery of forest resource information and decision support. However, little is known on how e-services engage forest owners. This study explores the Finnish state-funded Metsaan.fi e-service portal as a service innovation. We use web-based survey data about forest owners' views on aforementioned e-service (N = 5170) and register data about Finnish forest owners. The identified factors explain the respondents' activity in using the service. Theories of innovation diffusion and e-service quality framed the content analysis of the open-ended questions of the survey. According to the quantitative analysis, owners with timber production objectives and multi-objective owners were the most active users. Forest owners who were compliant with the service's recommendations of silviculture and harvesting operations, used the service actively. This implies that these forest owners had found the service useful. The qualitative analysis shows that independence from time and place and the ease-of-use make the service more inviting. The lack of forest inventory data or its perceived low quality detract forest owners from using it. Many forest owners expect the service to replace forest management plans as decision support tool but the information content there does not fully fulfil those expectations. The study produced knowledge for developing further the online platform and its services. Furthermore, it created understanding about e-government services in the management of natural resources. Specifically, the results argue for noticing attitudinal patterns of intended users when designing governmental e-services. Further research is suggested to integrate innovation adoption theory and service research theory to dig deeper into the value creation and service needs of different user groups.
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(2019)Mixed fisheries and the marine ecosystems that sustain them are complex entities and involve multiple and potentially conflicting management objectives and stakeholder interests. The presence of multiple trade-offs complicates the identification of strategies that satisfy various policy requirements while being acceptable to affected stakeholder groups. This creates a demand for tools and processes that support learning, cooperation and planning. We report on the application of decision support methodology used in combination with a co-creation approach to scenario based planning for the demersal fisheries of the West coast of Scotland. These fisheries face significant challenges, such as the depletion of key stocks and increased predation by seals. In collaboration with stakeholders we identified generic management alternatives and indicators to evaluate their performance in a structured evaluation using Multi Criteria Analysis. We identify the potential and limitations of this approach and suggest how it can contribute to Ecosystem Based Fisheries Management (EBFM). This approach does not provide tactical management advice, but stimulates learning and creates an opportunity for stakeholders to search for strategic and policy relevant solutions in an EBFM context.
