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A Sustainable Historic Waterfront Revitalization Decision Support Tool for Attracting Tourists

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  • Ali Keyvanfar

    (Facultad de Arquitectura y Urbanismo, Universidad Tecnológica Equinoccial, Calle Rumipamba s/n y Bourgeois, Quito 170508, Ecuador
    MIT-UTM MSCP Program, Institute Sultan Iskandar, Universiti Teknologi Malaysia, Skudai 81310, Malaysia
    Department of Landscape Architecture, Faculty of Built Environment, Universiti Teknologi Malaysia, Skudai 81310, Malaysia
    The School of Architecture and Environmental Design, Iran University of Science and Technology (IUST), Narmak Street, Tehran 1684613114, Iran)

  • Arezou Shafaghat

    (MIT-UTM MSCP Program, Institute Sultan Iskandar, Universiti Teknologi Malaysia, Skudai 81310, Malaysia
    Department of Landscape Architecture, Faculty of Built Environment, Universiti Teknologi Malaysia, Skudai 81310, Malaysia
    The School of Architecture and Environmental Design, Iran University of Science and Technology (IUST), Narmak Street, Tehran 1684613114, Iran)

  • Sapura Mohamad

    (Department of Landscape Architecture, Faculty of Built Environment, Universiti Teknologi Malaysia, Skudai 81310, Malaysia)

  • Mu’azu Mohammed Abdullahi

    (Civil Engineering Department, Jubail University College, Royal Commission of Jubail and Yanbu, Jubail 31961, Saudi Arabia)

  • Hamidah Ahmad

    (Department of Landscape Architecture, Faculty of Built Environment, Universiti Teknologi Malaysia, Skudai 81310, Malaysia)

  • Nurul Hidayah Mohd Derus

    (Department of Landscape Architecture, Faculty of Built Environment, Universiti Teknologi Malaysia, Skudai 81310, Malaysia)

  • Majid Khorami

    (Facultad de Arquitectura y Urbanismo, Universidad Tecnológica Equinoccial, Calle Rumipamba s/n y Bourgeois, Quito 170508, Ecuador)

Abstract

Waterfront revitalization would be an effective strategy to preserve heritages, conserve the contaminated or abandoned site and inspire the identity and authenticity. However, there is no decision support tool to quantify and evaluate the sustainability accreditation of waterfronts in tourism attraction. This research aimed to identify the most potential waterfront typology in tourism attraction and develop the waterfront sustainable revitalization (SWR) index assessment model. The SWR index can assist policy makers and urban developers to analyze the heritage waterfronts using Analytical Hierarchy Process (AHP) method. The research found out the historic waterfront has the highest potential in tourism attraction among other typologies. And, pollution moderator is mostly important sub-criterion in tourism absorption (W C2.2 = 0.1294); followed by Identity (W C1.2 = 0.1272) and Safety and well-being (W C1.3 = 0.1043). The SWR index can be applied in any waterfronts in heritage cities around the world, while this research implemented it as a case study in Bandar Maharani, Muar, Malaysia. It resulted Bandar Maharani was ranked as grade C; means, usable waterfront to which extent environmental, social and physical revitalization are needed. The SWR index can be coupled with other decision-making methods in future, to reduce its inconsistencies and increasing accuracy.

Suggested Citation

  • Ali Keyvanfar & Arezou Shafaghat & Sapura Mohamad & Mu’azu Mohammed Abdullahi & Hamidah Ahmad & Nurul Hidayah Mohd Derus & Majid Khorami, 2018. "A Sustainable Historic Waterfront Revitalization Decision Support Tool for Attracting Tourists," Sustainability, MDPI, vol. 10(2), pages 1-23, January.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:2:p:215-:d:128193
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    References listed on IDEAS

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    2. Gouxiong Yu & Jinwen (Jimmy) Tang & Junli Na & Tiancheng Ma, 2022. "Nighttime as Experiences: The Influence of Perceived Value on Urban Waterfront Night Cruise Loyalty," SAGE Open, , vol. 12(2), pages 21582440221, June.
    3. Min Gong & Mengyu Ren & Qin Dai & Xiaoyu Luo, 2019. "Aging-Suitability of Urban Waterfront Open Spaces in Gongchen Bridge Section of the Grand Canal," Sustainability, MDPI, vol. 11(21), pages 1-19, November.
    4. Marta Bottero & Chiara D’Alpaos & Alessia Marello, 2020. "An Application of the A’WOT Analysis for the Management of Cultural Heritage Assets: The Case of the Historical Farmhouses in the Aglié Castle (Turin)," Sustainability, MDPI, vol. 12(3), pages 1-17, February.
    5. Jinhyun Jun, 2023. "Towards Sustainable Urban Riverfront Redevelopment: Adaptability as a Design Strategy for the Hangang Riverfront in Seoul," Sustainability, MDPI, vol. 15(12), pages 1-22, June.
    6. Jing Wu & Changlong Ling & Xinzhuo Li, 2019. "Study on the Accessibility and Recreational Development Potential of Lakeside Areas Based on Bike-Sharing Big Data Taking Wuhan City as an Example," Sustainability, MDPI, vol. 12(1), pages 1-20, December.
    7. Aurora Skrame & Claudio Ciancio & Vincenzo Corvello & Roberto Musmanno, 2020. "A Quantitative Model Supporting Socially Responsible Public Investment Decisions for Sustainable Tourism," IJFS, MDPI, vol. 8(2), pages 1-9, June.
    8. Zydrune Morkunaite & Romualdas Bausys & Edmundas Kazimieras Zavadskas, 2019. "Contractor Selection for Sgraffito Decoration of Cultural Heritage Buildings Using the WASPAS-SVNS Method," Sustainability, MDPI, vol. 11(22), pages 1-25, November.
    9. Jing Wu & Jingwen Li & Yue Ma, 2019. "Exploring the Relationship between Potential and Actual of Urban Waterfront Spaces in Wuhan Based on Social Networks," Sustainability, MDPI, vol. 11(12), pages 1-18, June.
    10. Younghun Choi & Takuro Kobashi & Yoshiki Yamagata & Akito Murayama, 2021. "Assessment of waterfront office redevelopment plan on optimal building energy demand and rooftop photovoltaics for urban decarbonization," Papers 2108.09029, arXiv.org.
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    12. Younghun Choi & Takuro Kobashi & Yoshiki Yamagata & Akito Murayama, 2022. "Assessment of Waterfront Office Redevelopment Plan on Optimal Building Arrangements with Rooftop Photovoltaics: A Case Study for Shinagawa, Tokyo," Energies, MDPI, vol. 15(3), pages 1-15, January.
    13. Jing Wu & Xirui Chen & Shulin Chen, 2019. "Temporal Characteristics of Waterfronts in Wuhan City and People’s Behavioral Preferences Based on Social Media Data," Sustainability, MDPI, vol. 11(22), pages 1-37, November.

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