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A Quantitative Approach for Identifying Adaptive Reuse Option for Industrial Buildings

In: Proceedings of the 19th International Symposium on Advancement of Construction Management and Real Estate

Author

Listed:
  • Yongtao Tan

    (The Hong Kong Polytechnic University)

  • Liyin Shen

    (Chongqing University)

  • Craig Langston

    (Bond University)

Abstract

With rapid economic development and restructuring, there are an increasing number of aged or obsolete buildings in large cities, such as Hong Kong. Adaptive reuse of these buildings provides an alternative for property stakeholders towards more sustainable practices instead of redevelopment or destruction. Adaptive reuse can also make great contributions to sustainable development by reducing construction waste and saving natural resources. As a result of industrial restructuring, manufacturing plants were migrated from Hong Kong to Mainland China during the 1980s and 1990s. Many industrial buildings then became vacant or under-utilized. Adaptive reuse of these industrial buildings is considered a viable way forward for all parties, including government, property stakeholders and the community. However, the problem is how to deal with multiple criteria to assess how these buildings can be reused for residential living, retail, training centers, or other purposes. Adaptive reuse of industrial buildings is discussed in this paper, and a fuzzy adaptive reuse selection model is developed for decision-making. A hypothetical example is used to demonstrate the application of the method and show its effectiveness.

Suggested Citation

  • Yongtao Tan & Liyin Shen & Craig Langston, 2015. "A Quantitative Approach for Identifying Adaptive Reuse Option for Industrial Buildings," Springer Books, in: Liyin Shen & Kunhui Ye & Chao Mao (ed.), Proceedings of the 19th International Symposium on Advancement of Construction Management and Real Estate, edition 127, chapter 0, pages 495-505, Springer.
    • Handle: RePEc:spr:sprchp:978-3-662-46994-1_41
    DOI: 10.1007/978-3-662-46994-1_41
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