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Occupant Behavior for Energy Conservation in Commercial Buildings: Lessons Learned from Competition at the Oak Ridge National Laboratory

Author

Listed:
  • Amanda Ahl

    (Department of Innovation Science, School of Environment and Society, Tokyo Institute of Technology, 3-3-6 Shibaura, Tokyo 105-0023, Japan)

  • Gina Accawi

    (Oak Ridge National Laboratory, Sustainable ORNL Program, 1 Bethel Valley Rd., Oak Ridge, TN 37830, USA)

  • Bryce Hudey

    (Oak Ridge National Laboratory, Sustainable ORNL Program, 1 Bethel Valley Rd., Oak Ridge, TN 37830, USA)

  • Melissa Lapsa

    (Oak Ridge National Laboratory, Sustainable ORNL Program, 1 Bethel Valley Rd., Oak Ridge, TN 37830, USA)

  • Teresa Nichols

    (Oak Ridge National Laboratory, Sustainable ORNL Program, 1 Bethel Valley Rd., Oak Ridge, TN 37830, USA)

Abstract

Accompanying efforts worldwide to deploy sustainable building technologies shows a pressing need for expanded research on occupant behavior. Discourse is lacking concerning drivers of occupant behavior for energy conservation, especially in the case of commercial buildings. This paper explores potential determinants of occupant behavior for energy conservation in commercial buildings. This is investigated in a case study of a two-month energy conservation competition involving eight office buildings at the Oak Ridge National Laboratory. Four buildings achieved energy savings based on the previous year’s baseline. Potential challenges and success factors of occupant behavior for energy conservation during the competition were explored based on an explanatory research design incorporating energy data, participant interviews, and surveys. The findings suggest that both social and technological aspects may be important drivers of energy conservation. The determinants of occupant behavior for energy conservation in commercial buildings suggested for further research include bottom-up involvement, stakeholder relationship management, targeted information, real-time energy visualization, and mobile social platforms. This paper presents initial implications, with a need for further research on these propositions and on their impacts on occupant behavior. This paper aims to contribute to both academia and practitioners in the arena of commercial building sustainability.

Suggested Citation

  • Amanda Ahl & Gina Accawi & Bryce Hudey & Melissa Lapsa & Teresa Nichols, 2019. "Occupant Behavior for Energy Conservation in Commercial Buildings: Lessons Learned from Competition at the Oak Ridge National Laboratory," Sustainability, MDPI, vol. 11(12), pages 1-18, June.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:12:p:3297-:d:240057
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    References listed on IDEAS

    as
    1. Delmas, Magali A. & Fischlein, Miriam & Asensio, Omar I., 2013. "Information strategies and energy conservation behavior: A meta-analysis of experimental studies from 1975 to 2012," Energy Policy, Elsevier, vol. 61(C), pages 729-739.
    2. Peeraya Inyim & Mostafa Batouli & Maria Presa Reyes & Triana Carmenate & Leonardo Bobadilla & Ali Mostafavi, 2018. "A Smartphone Application for Personalized and Multi-Method Interventions toward Energy Saving in Buildings," Sustainability, MDPI, vol. 10(6), pages 1-19, May.
    3. Cem Keskin & M. Pınar Mengüç, 2018. "On Occupant Behavior and Innovation Studies Towards High Performance Buildings: A Transdisciplinary Approach," Sustainability, MDPI, vol. 10(10), pages 1-33, October.
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    Cited by:

    1. Gómez, Patricia & Shaikh, Nazrul I. & Erkoc, Murat, 2024. "Continuous improvement in the efficient use of energy in office buildings through peers effects," Applied Energy, Elsevier, vol. 360(C).
    2. Jihan Muhaidat & Aiman Albatayneh & Mohammed N. Assaf & Adel Juaidi & Ramez Abdallah & Francisco Manzano-Agugliaro, 2021. "The Significance of Occupants’ Interaction with Their Environment on Reducing Cooling Loads and Dermatological Distresses in East Mediterranean Climates," IJERPH, MDPI, vol. 18(16), pages 1-13, August.
    3. Sun, Yannan & Hao, Weituo & Chen, Yan & Liu, Bing, 2020. "Data-driven occupant-behavior analytics for residential buildings," Energy, Elsevier, vol. 206(C).

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