@article{15dcdd08390f4bf2a9210547890012db,
title = "Transitioning complex socioeconomic modeling to informed and visualized decision-making: A tightly coupled planning support system",
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.",
keywords = "Input-output model, Land use model, Planning support systems (PSS), Socioeconomic complexity, Urban growth simulation",
author = "Yoonshin Kwak and Si Chen and Brian Deal",
note = "Anticipating the potential impact of socioeconomic plans is an arduous task due to complex interactions within urban systems (Deal et al., 2017; Klosterman, 2013). The uncertainty poses a significant challenge for decision-makers, as a multitude of interrelated factors evolve across both temporal and spatial dimensions, often resulting in unfavorable consequences, including urban fragmentation (Alberti, 2017; Yu et al., 2023). To tackle this challenge, substantial efforts have been devoted to developing coupled models for various urban components (Cong et al., 2022; Shahumyan & Moeckel, 2017), enabling real-time assessment of socioeconomic impact (Oddo et al., 2018), and incorporating scenario-based projections with stakeholder engagement (Pan et al., 2022). Notably, land-use change (LUC) models have been widely developed and refined, playing a critical role in these efforts. For decades, LUC models have proven valuable and useful in real-world planning, especially when combined with Planning Support Systems (PSS) that make complex models accessible to users (Pettit et al., 2020).Furthermore, our method can serve as an exemplar of an open and scalable planning support procedure that emphasizes collaborative efforts in urban system modeling. This approach not only streamlines the integration of various data sources but also fosters partnerships among stakeholders. Such collaborations enhance the pooling of resources, sharing of expertise, and alignment of objectives across different sectors, leading to more comprehensive and inclusive urban development strategies. Moreover, these collaborative frameworks ensure that planning processes are participatory and reflective of diverse community needs and perspectives, which is vital for tackling complex urban challenges effectively.This work was supported by Korea Environment Industry & Technology Institute (KEITI) through Climate Change R&D Project for New Climate Regime Program, funded by Korea Ministry of Environment (MOE) (RS-2023-00221110). This work was supported by Korea Environment Industry & Technology Institute(KEITI) through Climate Change R&D Project for New Climate Regime Program, funded by Korea Ministry of Environment(MOE)(RS-2023-00221110).",
year = "2024",
month = aug,
doi = "10.1016/j.apgeog.2024.103332",
language = "English (US)",
volume = "169",
journal = "Applied Geography",
issn = "0143-6228",
publisher = "Elsevier B.V.",
}