A generic information framework for decision-making in a forest-based bio-economy

2021 ◽  
Vol 78 (4) ◽  
Author(s):  
Jean-Baptiste Pichancourt ◽  
Rodolphe Bauer ◽  
Antoine Billard ◽  
Maree Brennan ◽  
Sylvain Caurla ◽  
...  
2012 ◽  
pp. 808-822
Author(s):  
Ori Gudes ◽  
Elizabeth Kendall ◽  
Tan Yigitcanlar ◽  
Jung Hoon Han ◽  
Virendra Pathak

This chapter investigates the challenges and opportunities associated with planning for a competitive city. The chapter is based on the assumption that a healthy city is a fundamental prerequisite for a competitive city. Thus, it is critical to examine the local determinants of health and factor these into any planning efforts. The main focus of the chapter is on e-health planning by utilising Web-based geographic decision support systems. The proposed novel decision support system would provide a powerful and effective platform for stakeholders to access essential data for decision-making purposes. The chapter also highlights the need for a comprehensive information framework to guide the process of planning for healthy cities. Additionally, it discusses the prospects and constraints of such an approach. In summary, this chapter outlines the potential insights of using an information science-based framework and suggests practical planning methods as part of a broader e-health approach for improving the health characteristics of competitive cities.


Data Mining ◽  
2013 ◽  
pp. 1545-1558
Author(s):  
Ori Gudes ◽  
Elizabeth Kendall ◽  
Tan Yigitcanlar ◽  
Jung Hoon Han ◽  
Virendra Pathak

This chapter investigates the challenges and opportunities associated with planning for a competitive city. The chapter is based on the assumption that a healthy city is a fundamental prerequisite for a competitive city. Thus, it is critical to examine the local determinants of health and factor these into any planning efforts. The main focus of the chapter is on e-health planning by utilising Web-based geographic decision support systems. The proposed novel decision support system would provide a powerful and effective platform for stakeholders to access essential data for decision-making purposes. The chapter also highlights the need for a comprehensive information framework to guide the process of planning for healthy cities. Additionally, it discusses the prospects and constraints of such an approach. In summary, this chapter outlines the potential insights of using an information science-based framework and suggests practical planning methods as part of a broader e-health approach for improving the health characteristics of competitive cities.


Author(s):  
Ori Gudes ◽  
Elizabeth Kendall ◽  
Tan Yigitcanlar ◽  
Jung Hoon Han ◽  
Virendra Pathak

This chapter investigates the challenges and opportunities associated with planning for a competitive city. The chapter is based on the assumption that a healthy city is a fundamental prerequisite for a competitive city. Thus, it is critical to examine the local determinants of health and factor these into any planning efforts. The main focus of the chapter is on e-health planning by utilising Web-based geographic decision support systems. The proposed novel decision support system would provide a powerful and effective platform for stakeholders to access essential data for decision-making purposes. The chapter also highlights the need for a comprehensive information framework to guide the process of planning for healthy cities. Additionally, it discusses the prospects and constraints of such an approach. In summary, this chapter outlines the potential insights of using an information science-based framework and suggests practical planning methods as part of a broader e-health approach for improving the health characteristics of competitive cities.


2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.


2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.


2018 ◽  
Vol 41 ◽  
Author(s):  
Kevin Arceneaux

AbstractIntuitions guide decision-making, and looking to the evolutionary history of humans illuminates why some behavioral responses are more intuitive than others. Yet a place remains for cognitive processes to second-guess intuitive responses – that is, to be reflective – and individual differences abound in automatic, intuitive processing as well.


2014 ◽  
Vol 38 (01) ◽  
pp. 46
Author(s):  
David R. Shanks ◽  
Ben R. Newell

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