scholarly journals Sustainability assessment of entire forest value chains: Integrating stakeholder perspectives and indicators in decision support tools

2010 ◽  
Vol 221 (18) ◽  
pp. 2206-2214 ◽  
Author(s):  
Justus von Geibler ◽  
Kora Kristof ◽  
Katrin Bienge
Keyword(s):  
Decision Support ◽  
Sustainability Assessment ◽  
Value Chains ◽  
Decision Support Tools ◽  
Stakeholder Perspectives ◽  
Support Tools

A framework synthesis of stakeholder perspectives on clinical decision support tools to inform clinical AI implementation: a qualitative evidence synthesis protocol (Preprint)

2021 ◽  
Author(s):  
Mohaimen Al-Zubaidy ◽  
H.D. Jeffry Hogg ◽  
Gregory Maniatopoulos ◽  
S. James Talks ◽  
M. Dawn Teare ◽  
...  
Keyword(s):  
Decision Support ◽  
Evidence Synthesis ◽  
Clinical Decision ◽  
Qualitative Evidence Synthesis ◽  
Decision Support Tools ◽  
Patient Benefit ◽  
Stakeholder Perspectives ◽  
Qualitative Evidence ◽  
Support Tools ◽  
Clinical Decision Support Tools

BACKGROUND Quantitative systematic reviews have identified clinical artificial intelligence (AI) enabled tools with adequate performance for real-world implementation. To our knowledge, no published report or protocol synthesizes the full breadth of stakeholder perspectives. The absence of such a rigorous foundation perpetuates the ‘AI chasm’ which continues to delay patient benefit. OBJECTIVE To synthesize stakeholder perspectives of computerized clinical decision support tools (CCDST) in any healthcare setting. Synthesized findings will inform future research and the implementation of AI into healthcare services. METHODS The search strategy will use MEDLINE (Ovid), Scopus, CINAHL (EBSCO), ACM Digital Library and Science Citation Index (Web of Science). Following deduplication, title, abstract and full text screening will be performed by two independent reviewers with a third topic expert arbitrating. The quality of included studies will be appraised to support interpretation. Best-fit framework synthesis will be performed, with line-by-line coding completed by two independent reviewers. Where appropriate, these findings will be assigned to one of 22 a-priori themes defined by the Non-Adoption, Abandonment, Scale-Up, Spread and Sustainability (NASSS) framework. New domains will be inductively generated for outlying findings. The placement of findings within themes will be reviewed iteratively by a study advisory group including patient and lay representatives. RESULTS Study registration was obtained from PROSPERO (ID 248025) in May 2021. Final searches were executed in April and screening is ongoing at the time of writing. Full text data analysis is due to be completed in October 2021. We anticipate that the study will be submitted for open-access publication in late 2021 . CONCLUSIONS This paper describes the protocol for a qualitative evidence synthesis aiming to define barriers and facilitators to the implementation of CCDSTs from all relevant stakeholders. The results of this study are intended to expedite the delivery of patient benefit from AI enabled clinical tools. CLINICALTRIAL PROSPERO ID 248025

scholarly journals A Review of Waste Management Decision Support Tools and Their Ability to Assess Circular Biowaste Management Systems

2018 ◽  
Vol 10 (10) ◽  
pp. 3720 ◽  
Author(s):  
Eldbjørg Blikra Vea ◽  
Veronica Martinez-Sanchez ◽  
Marianne Thomsen
Keyword(s):  
Decision Support ◽  
Waste Management ◽  
New Technologies ◽  
Sustainability Assessment ◽  
Resource Scarcity ◽  
Environmental Benefits ◽  
Management Systems ◽  
Management Decision ◽  
Decision Support Tools ◽  
Support Tools

The circular economy concept offers a number of solutions to increasing amounts of biowaste and resource scarcity by valorising biowaste. However, it is necessary to consistently address the environmental benefits and impacts of circular biowaste management systems (CBWMS). Various decision support tools (DST) for environmental assessment of waste management systems (WMS) exist. This study provides a review of life cycle assessment based WMS-DSTs. Twenty-five WMS-DSTs were identified and analysed through a shortlisting procedure. Eight tools were shortlisted for the assessment of their applicability to deliver sustainability assessment of CBWMS. It was found that six tools model key properties that are necessary for assessing the environmental sustainability of CBWMSs, including waste-specific modelling of gaseous emissions, biogas generation or bioproduct composition. However, only two tools consider both waste-specific heavy metals content in bioproducts and the associated implications when applied on soil. Most of the shortlisted tools are flexible to simulate new technologies involved in CBWMS. Nevertheless, only two tools allow importing directly new background data, which is important when modelling substitution of new bioproducts developed in emerging biowaste refineries.

Environmental sustainability assessment of rice management practices using decision support tools

2021 ◽  
pp. 128135
Author(s):  
Beatriz Moreno-García ◽  
Eric Coronel ◽  
Colby W. Reavis ◽  
Kosana Suvočarev ◽  
Benjamin R.K. Runkle
Keyword(s):  
Decision Support ◽  
Environmental Sustainability ◽  
Management Practices ◽  
Sustainability Assessment ◽  
Decision Support Tools ◽  
Support Tools

Decision Support Tools For Assessing Petroleum Upstream Investments

2020 ◽  
pp. 323
Author(s):  
Nour Elislam Djedaa ◽  
Abderrezak Moulay Lakhdar
Keyword(s):  
Decision Support ◽  
Decision Support Tools ◽  
Support Tools

Elicitation of expert knowledge to develop decision support tools for use in water demand management planning

2007 ◽  
Vol 7 (5-6) ◽  
pp. 53-60
Author(s):  
D. Inman ◽  
D. Simidchiev ◽  
P. Jeffrey
Keyword(s):  
Decision Support ◽  
Water Demand ◽  
Expert Knowledge ◽  
Demand Management ◽  
Decision Processes ◽  
Conservation Strategy ◽  
Influence Diagrams ◽  
Decision Support Tools ◽  
Water Demand Management ◽  
Support Tools

This paper examines the use of influence diagrams (IDs) in water demand management (WDM) strategy planning with the specific objective of exploring how IDs can be used in developing computer-based decision support tools (DSTs) to complement and support existing WDM decision processes. We report the results of an expert consultation carried out in collaboration with water industry specialists in Sofia, Bulgaria. The elicited information is presented as influence diagrams and the discussion looks at their usefulness in WDM strategy design and the specification of suitable modelling techniques. The paper concludes that IDs themselves are useful in developing model structures for use in evidence-based reasoning models such as Bayesian Networks, and this is in keeping with the objectives set out in the introduction of integrating DSTs into existing decision processes. The paper will be of interest to modellers, decision-makers and scientists involved in designing tools to support resource conservation strategy implementation.

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