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Analysis and construction of stress relief model for healthy indoor environments

Author

Listed:
  • Hsi-Chin Chen
  • Ching-Hsin Wang
  • Kuen-Suan Chen
  • Tsu-Liang Chang

    ()

Abstract

Currently, the average person spends 80–90 % of their workday in an airtight indoor environment. Under such conditions, the presence of organic chemical pollutants in the air can compromise the health of workers and undermine work efficiency. Many researchers have demonstrated that plants can be used to purify the air and relive stress, essential oils can promote positive emotions and eliminate negative thoughts, and music can relieve stress by calming nerves and relaxing muscles. All of these are positively related to the release of stress and the promotion of health. This study employed three factors to construct environment-related dimensions with an influence on stress relief. We employed analytic network process to identify the environmental factors that are essential to stress relief, in conjunction with Taguchi method to determine the best combination of parameters. A model based on statistical analysis was used to verify the different benefits resulting from these changes. The proposed system provides an effective means to enhance air quality in the promotion of a comfortable, clean, and healthy environment. Our findings provide a valuable reference for the implementation of environment improvements in medical facilities, retirement homes, and office spaces. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Hsi-Chin Chen & Ching-Hsin Wang & Kuen-Suan Chen & Tsu-Liang Chang, 2014. "Analysis and construction of stress relief model for healthy indoor environments," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 2053-2067, July.
  • Handle: RePEc:spr:qualqt:v:48:y:2014:i:4:p:2053-2067
    DOI: 10.1007/s11135-013-9879-4
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    File URL: http://hdl.handle.net/10.1007/s11135-013-9879-4
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    1. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
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