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Preference Functions for Spatial Risk Analysis.

L Robin Keller1, Jay Simon2

  • 1Paul Merage School of Business, University of California, Irvine, Irvine, CA, USA.

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|September 8, 2017
PubMed
Summary

This study introduces spatial measurable value and utility functions to analyze risks in geographic regions. These functions help assess spatial risk more effectively, using freshwater usage as an example.

Keywords:
Measurable valuepreferencesspatial risk analysisutility

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Area of Science:

  • Spatial analysis
  • Risk assessment
  • Decision theory

Background:

  • Traditional risk measures struggle with geographically defined outcomes.
  • A key challenge is developing preference functions that account for spatial data.

Purpose of the Study:

  • To explore preference conditions for spatial measurable value and utility functions.
  • To apply these functions to spatial risk analysis.
  • To demonstrate assessment and application using a freshwater usage example.

Main Methods:

  • Exploration of preference conditions.
  • Development of spatial measurable value and utility functions.
  • Application to spatial risk analysis with a case study.

Main Results:

  • Identified preference conditions enabling spatial measurable value and utility functions.
  • Demonstrated the utility of these functions in analyzing spatial risk.
  • Provided a practical example of assessing and applying spatial functions.

Conclusions:

  • Spatial measurable value and utility functions are crucial for complex spatial risk analysis.
  • These functions offer a more nuanced approach to understanding geographically distributed risks.
  • The methodology is applicable to various real-world scenarios involving spatial outcomes.