The social side of spatial decision support systems

Investigating knowledge integration and learning

Research output: Contribution to journalArticleAcademicpeer-review

13 Citations (Scopus)

Abstract

Spatial decision support systems (SDSS) represent a step forward in efforts to account for the spatial dimension in environmental decision-making. The aim of SDSS is to help policymakers and practitioners access, interpret and understand information from data, analyses and models, and guide them in identifying possible actions during a decision-making process. Researchers, however, report difficulties in up-take of SDSS by the intended users. Some suggest that this field would benefit from investigation of the social aspects involved in SDSS design, development, testing and use. Borrowing insights from the literature on science-policy interactions, we explore two key social processes: knowledge integration and learning. Using a sample of 36 scientific papers concerning SDSS in relation to environmental issues, we surveyed whether and how the selected papers reported on knowledge integration and learning. We found that while many of the papers mentioned communication and collaboration with prospective user groups or stakeholders, this was seldom underpinned by a coherent methodology for enabling knowledge integration and learning to surface. This appears to have hindered SDSS development and later adoption by intended users.
Original languageEnglish
Pages (from-to)177-184
JournalEnvironmental Science & Policy
Volume76
DOIs
Publication statusPublished - 2017

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learning
knowledge
decision making
science policy
system development
social process
environmental issue
decision-making process
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Cite this

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title = "The social side of spatial decision support systems: Investigating knowledge integration and learning",
abstract = "Spatial decision support systems (SDSS) represent a step forward in efforts to account for the spatial dimension in environmental decision-making. The aim of SDSS is to help policymakers and practitioners access, interpret and understand information from data, analyses and models, and guide them in identifying possible actions during a decision-making process. Researchers, however, report difficulties in up-take of SDSS by the intended users. Some suggest that this field would benefit from investigation of the social aspects involved in SDSS design, development, testing and use. Borrowing insights from the literature on science-policy interactions, we explore two key social processes: knowledge integration and learning. Using a sample of 36 scientific papers concerning SDSS in relation to environmental issues, we surveyed whether and how the selected papers reported on knowledge integration and learning. We found that while many of the papers mentioned communication and collaboration with prospective user groups or stakeholders, this was seldom underpinned by a coherent methodology for enabling knowledge integration and learning to surface. This appears to have hindered SDSS development and later adoption by intended users.",
author = "Romina Rodela and Bregt, {Arnold K.} and Arend Ligtenberg and Marta P{\'e}rez-Soba and Peter Verweij",
year = "2017",
doi = "10.1016/j.envsci.2017.06.015",
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volume = "76",
pages = "177--184",
journal = "Environmental Science & Policy",
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The social side of spatial decision support systems : Investigating knowledge integration and learning. / Rodela, Romina; Bregt, Arnold K.; Ligtenberg, Arend; Pérez-Soba, Marta; Verweij, Peter.

In: Environmental Science & Policy, Vol. 76, 2017, p. 177-184.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - The social side of spatial decision support systems

T2 - Investigating knowledge integration and learning

AU - Rodela, Romina

AU - Bregt, Arnold K.

AU - Ligtenberg, Arend

AU - Pérez-Soba, Marta

AU - Verweij, Peter

PY - 2017

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AB - Spatial decision support systems (SDSS) represent a step forward in efforts to account for the spatial dimension in environmental decision-making. The aim of SDSS is to help policymakers and practitioners access, interpret and understand information from data, analyses and models, and guide them in identifying possible actions during a decision-making process. Researchers, however, report difficulties in up-take of SDSS by the intended users. Some suggest that this field would benefit from investigation of the social aspects involved in SDSS design, development, testing and use. Borrowing insights from the literature on science-policy interactions, we explore two key social processes: knowledge integration and learning. Using a sample of 36 scientific papers concerning SDSS in relation to environmental issues, we surveyed whether and how the selected papers reported on knowledge integration and learning. We found that while many of the papers mentioned communication and collaboration with prospective user groups or stakeholders, this was seldom underpinned by a coherent methodology for enabling knowledge integration and learning to surface. This appears to have hindered SDSS development and later adoption by intended users.

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