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<p>Energy efficiency (EE) in the construction sector is crucial for sustainable development, particularly in emerging economies like Pakistan, where the industry accounts for a large share of energy consumption and environmental degradation. Despite its economic significance, Pakistan’s construction sector suffers from inefficiencies in energy use, with limited comprehensive assessments to guide improvements. This research introduces a novel, integrated approach combining Data Envelopment Analysis (DEA) and Tobit regression to evaluate and enhance EE in construction projects. DEA was applied to data from 120 construction firms, revealing an average technical efficiency (TE) of 84.4%, pure technical efficiency (PTE) of 93.2%, and scale efficiency (SE) of 90.4%, highlighting notable inefficiencies. The Tobit regression analysis identifies key factors influencing EE, including contractor training, access to loans, experience, and project site distance. This dual-method framework not only measures EE but also provides actionable insights to address inefficiencies, offering practical implications for policymakers and industry stakeholders. The findings emphasize the need for targeted interventions, such as government-supported financing and contractor training programs, to promote energy-efficient practices in Pakistan’s construction sector. This approach provides a replicable model for other developing economies seeking sustainable construction practices.</p>

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Energy efficiency evaluation of construction projects using data envelopment analysis and Tobit regression

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月3日

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  • Muzaffar Iqbal,
  • Junhai Ma,
  • Zulqarnain Mushtaq,
  • Naveed Ahmad,
  • Muhammad Zain Yousaf,
  • Bashar Tarawneh,
  • Wajid Khan,
  • Mukesh Pushkarna,
  • Ievgen Zaitsev

摘要

Energy efficiency (EE) in the construction sector is crucial for sustainable development, particularly in emerging economies like Pakistan, where the industry accounts for a large share of energy consumption and environmental degradation. Despite its economic significance, Pakistan’s construction sector suffers from inefficiencies in energy use, with limited comprehensive assessments to guide improvements. This research introduces a novel, integrated approach combining Data Envelopment Analysis (DEA) and Tobit regression to evaluate and enhance EE in construction projects. DEA was applied to data from 120 construction firms, revealing an average technical efficiency (TE) of 84.4%, pure technical efficiency (PTE) of 93.2%, and scale efficiency (SE) of 90.4%, highlighting notable inefficiencies. The Tobit regression analysis identifies key factors influencing EE, including contractor training, access to loans, experience, and project site distance. This dual-method framework not only measures EE but also provides actionable insights to address inefficiencies, offering practical implications for policymakers and industry stakeholders. The findings emphasize the need for targeted interventions, such as government-supported financing and contractor training programs, to promote energy-efficient practices in Pakistan’s construction sector. This approach provides a replicable model for other developing economies seeking sustainable construction practices.