Transitioning complex socioeconomic modeling to informed and visualized decision-making: A tightly coupled planning support system

Yoonshin Kwak, Si Chen, Brian Deal

Research output: Contribution to journalArticlepeer-review

Abstract

The integration of urban models into decision-making remains challenging, primarily attributed to the complex nature of urban mechanisms. This study develops a PSS with sufficient methodological complexity to examine socioeconomic dynamics while simultaneously delivering modeling results in a manner that is understandable to non-expert stakeholders for informed decision-making. This paper tests, applies and implements the system in a real-life case at a fine scale collaborating with Sangamon County Regional Planning Commissions. It explores regional socioeconomic mechanisms across economic sectors addressing multicollinearity, projects potential consequences of an investment plan, and develops a web-based PSS tool for their informed decision-making. Our results identify how each economic sector behaves differently concerning location choices for future developments impacted by the investment, necessitating the use of differentiated planning approaches tailored to each sector. Findings underscore the value of assessing the heterogeneity of dynamic land development with spatial explicitness for informed decisions. We advocate for the delivery of this modeling via an interactive PSS platform, fostering responsive and collaborative dialogues. This paper contributes not only to the development of an integrated modeling framework but also to the planning literature, bridging the gap between complexity and accessibility in decision-making.

Original languageEnglish (US)
Article number103332
JournalApplied Geography
Volume169
DOIs
StatePublished - Aug 2024

Keywords

  • Input-output model
  • Land use model
  • Planning support systems (PSS)
  • Socioeconomic complexity
  • Urban growth simulation

ASJC Scopus subject areas

  • Forestry
  • Geography, Planning and Development
  • General Environmental Science
  • Tourism, Leisure and Hospitality Management

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