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Using Decision Support System to Enable Crowd Identify Neighborhood Issues and Its Solutions for Policy Makers: An Online Experiment at Kabul Municipal Level

Author

Listed:
  • Jawad Haqbeen

    (Department of Computer Science, Nagoya Institute of Technology, Nagoya 466-8555, Japan)

  • Sofia Sahab

    (Department of Social Informatics, Kyoto University, Kyoto 606-8501, Japan)

  • Takayuki Ito

    (Department of Social Informatics, Kyoto University, Kyoto 606-8501, Japan)

  • Paola Rizzi

    (Department of Architecture, Design and Urban Planning, University of Sassari, 07100 Sassari, Italy)

Abstract

Planning a city is a systematic process that includes time, space, and groups of people who must communicate. However, due to security problems in such war-ravaged countries as Afghanistan, the traditional forms of public participation in the planning process are untenable. In particular, due to gathering space difficulties and culture issues in Afghanistan, women and religious minorities are restricted from joining male-dominated powerholders’ face-to-face meetings which are nearly always held in fixed places called masjids (religious buildings). Furthermore, conducting such discussions with human facilitation biases the generation of citizen decisions that stimulates an atmosphere of confrontation, causing another decision problem for urban policy-making institutions. Therefore, it is critical to find approaches that not only securely revolutionize participative processes but also provide meaningful and equal public consultation to support interactions among stakeholders to solve their shared problems together. Toward this end, we propose a joint research program, namely, crowd-based communicative and deliberative e-planning (CCDP), a blended approach, which is a mixture of using an artificial-intelligence-led technology, decision-support system called D-Agree and experimental participatory planning in Kabul, Afghanistan. For the sake of real-world implementation, Nagoya Institute of Technology (Japan) and Kabul Municipality (Afghanistan) have formed a novel developed and developing world partnership by using our proposed methodology as an emerging-deliberation mechanism to reframe public participation in urban planning processes. In the proposed program, Kabul municipality agreed to use our methodology when Kabul city needs to make a plan with people. This digital field study presents the first practical example of using online decision support systems in the context of the neighborhood functions of Gozars, which are Kabul’s social and spatial urban units. The main objective was to harness the wisdom of the crowd to innovative suggestions for helping policymakers making strategic development plans for Gozars using open call ideas, and for responding to equal participation and consultation needs, specifically for women and minorities. This article presents valuable insights into the benefits of this combined approach as blended experience for societies and cities that are suffering long-term distress. This initiative has influenced other local Afghan governments, including the cities of Kandahar and Herat as well as the country’s central government’s ministry of urban planning and land, which has officially expressed its intention to collaborate with us.

Suggested Citation

  • Jawad Haqbeen & Sofia Sahab & Takayuki Ito & Paola Rizzi, 2021. "Using Decision Support System to Enable Crowd Identify Neighborhood Issues and Its Solutions for Policy Makers: An Online Experiment at Kabul Municipal Level," Sustainability, MDPI, vol. 13(10), pages 1-34, May.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:10:p:5453-:d:553817
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    References listed on IDEAS

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    1. Beath, Andrew & Christia, Fotini & Enikolopov, Ruben, 2012. "Empowering women : evidence from a field experiment in Afghanistan," Policy Research Working Paper Series 6269, The World Bank.
    2. David Rios Insua & Gregory E. Kersten & Jesus Rios & Carlos Grima, 2008. "Towards Decision Support for Participatory Democracy," International Handbooks on Information Systems, in: Handbook on Decision Support Systems 2, chapter 66, pages 651-685, Springer.
    3. Thomas W. Malone & Mark Klein, 2007. "Harnessing Collective Intelligence to Address Global Climate Change," Innovations: Technology, Governance, Globalization, MIT Press, vol. 2(3), pages 15-26, July.
    4. Eduardo Medeiros & Arno van der Zwet, 2020. "Sustainable and Integrated Urban Planning and Governance in Metropolitan and Medium-Sized Cities," Sustainability, MDPI, vol. 12(15), pages 1-20, July.
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    Cited by:

    1. Dorota Kamrowska-Załuska, 2021. "Impact of AI-Based Tools and Urban Big Data Analytics on the Design and Planning of Cities," Land, MDPI, vol. 10(11), pages 1-19, November.

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