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Author Spotlight: Understanding Riverine Nitrogen Impacts and Primary Productivity for Effective Nutrient Management
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Assessing the Visualization-Based Decision Support System for Environmental Impact Assessments.

Seo-Young Lee1, Sanghee Shin2, Hakjoon Kim2

  • 1College of Human Ecology, Cornell University, Ithaca, NY 14853, USA.

International Journal of Environmental Research and Public Health
|February 15, 2022
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Summary

This study introduces a decision support system (DSS) to make environmental impact assessments (EIAs) more accessible. The system enhances public understanding and communication between stakeholders, particularly benefiting those with environmental expertise.

Keywords:
Likert scaleenvironmental literacygraphicssustainabilityusability test

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Area of Science:

  • Environmental Science
  • Human-Computer Interaction
  • Decision Support Systems

Background:

  • Environmental Impact Assessments (EIAs) are crucial for decision-making but often inaccessible to the public due to complex data formats.
  • Lack of public understanding hinders effective participation in environmental decision-making processes.
  • Existing EIA communication methods often fail to bridge the gap between experts and the general public.

Purpose of the Study:

  • To develop and evaluate a decision support system (DSS) designed to enhance public comprehension of EIAs.
  • To improve communication and understanding between stakeholders, including the public and experts, during the EIA process.
  • To assess the usability of the DSS and the influence of user characteristics on its perception.

Main Methods:

  • A novel decision support system (DSS) was developed, incorporating data visualization for key environmental elements.
  • Usability testing was conducted with 107 participants to evaluate the system's effectiveness.
  • Individual differences, including environmental expertise and computer self-efficacy, were analyzed for their impact on user perception.

Main Results:

  • The proposed DSS demonstrated high usability among participants.
  • Users with higher computer self-efficacy and environmental expertise reported greater satisfaction and perceived higher usability.
  • The system effectively improved the visualization of environmental data, aiding user comprehension.

Conclusions:

  • The developed DSS significantly enhances the accessibility and understandability of EIAs for the public.
  • The system has the potential to improve communication during public hearings and boost environmental literacy.
  • Tailoring system design or user support based on individual expertise may further optimize usability and impact.