IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i19p14264-d1248644.html
   My bibliography  Save this article

A DPSIR Framework to Evaluate and Predict the Development of Prefabricated Buildings: A Case Study

Author

Listed:
  • Fanrong Ji

    (School of Management Engineering, Shandong Jianzhu University, Jinan 250101, China)

  • Zhaoyuan Luo

    (School of Management Engineering, Shandong Jianzhu University, Jinan 250101, China)

  • Xiancun Hu

    (School of Design and the Built Environment, University of Canberra, Canberra 2601, Australia)

  • Yunquan Nan

    (College of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China)

  • Aifang Wei

    (School of Design and the Built Environment, University of Canberra, Canberra 2601, Australia)

Abstract

Prefabricated building construction is an important method of enhancing construction productivity and promoting sustainable development in the construction industry. Evaluating and predicting the development performance of prefabricated buildings will contribute to identifying and implementing the most effective responses to promote prefabricated building technologies. Based on the Drives–Pressures–States–Impacts–Responses (DPSIR) framework, 14 evaluation indexes are determined to evaluate the development level of prefabricated buildings. The entropy weight method was used to determine the weight of the evaluation index, and the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method with improved grey correlation was applied to comprehensively evaluate the trend of the index. The grey model (GM(1,1)) was developed to predict the development trend of prefabricated buildings. The development of prefabricated buildings in Shandong province, China, is employed as a case to apply the developed method and investigate development experiences. The results demonstrate that the case has achieved significant progress and has great potential in promoting the use of prefabricated buildings. The development recommendations include developing a policy and regulation system, strengthening a prefabricated building talent pool, and enhancing the investment in technological innovation. This study innovatively formulated the evaluation and prediction system based on the DPSIR, TOPSIS and GM(1,1) models, which could be used for evaluating development performance between social and environmental factors among various cause-effect relationships.

Suggested Citation

  • Fanrong Ji & Zhaoyuan Luo & Xiancun Hu & Yunquan Nan & Aifang Wei, 2023. "A DPSIR Framework to Evaluate and Predict the Development of Prefabricated Buildings: A Case Study," Sustainability, MDPI, vol. 15(19), pages 1-17, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:19:p:14264-:d:1248644
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/19/14264/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/19/14264/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yinghui Song & Junwu Wang & Feng Guo & Jiequn Lu & Sen Liu, 2021. "Research on Supplier Selection of Prefabricated Building Elements from the Perspective of Sustainable Development," Sustainability, MDPI, vol. 13(11), pages 1-24, May.
    2. Chaofeng Shao & Xiaogang Tian & Yang Guan & Meiting Ju & Qiang Xie, 2013. "Development and Application of a New Grey Dynamic Hierarchy Analysis System (GDHAS) for Evaluating Urban Ecological Security," IJERPH, MDPI, vol. 10(5), pages 1-25, May.
    3. He Wang & Yinqi Zhang & Weijun Gao & Soichiro Kuroki, 2020. "Life Cycle Environmental and Cost Performance of Prefabricated Buildings," Sustainability, MDPI, vol. 12(7), pages 1-19, March.
    4. Shuyu Li & Rongrong Li, 2017. "Comparison of Forecasting Energy Consumption in Shandong, China Using the ARIMA Model, GM Model, and ARIMA-GM Model," Sustainability, MDPI, vol. 9(7), pages 1-19, July.
    5. Bartosz Radomski & Tomasz Mróz, 2021. "The Methodology for Designing Residential Buildings with a Positive Energy Balance—Case Study," Energies, MDPI, vol. 14(16), pages 1-19, August.
    6. Cavoli, Clemence, 2021. "Accelerating sustainable mobility and land-use transitions in rapidly growing cities: Identifying common patterns and enabling factors," Journal of Transport Geography, Elsevier, vol. 94(C).
    7. Bartosz Radomski & Tomasz Mróz, 2021. "The Methodology for Designing Residential Buildings with a Positive Energy Balance—General Approach," Energies, MDPI, vol. 14(15), pages 1-16, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dolores Ordóñez-Martínez & Joana M. Seguí-Pons & Maurici Ruiz-Pérez, 2023. "Conceptual Framework and Prospective Analysis of EU Tourism Data Spaces," Sustainability, MDPI, vol. 16(1), pages 1-35, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Łukasz Amanowicz, 2021. "Peak Power of Heat Source for Domestic Hot Water Preparation (DHW) for Residential Estate in Poland as a Representative Case Study for the Climate of Central Europe," Energies, MDPI, vol. 14(23), pages 1-15, December.
    2. Bartosz Radomski & Tomasz Mróz, 2023. "Application of the Hybrid MCDM Method for Energy Modernisation of an Existing Public Building—A Case Study," Energies, MDPI, vol. 16(8), pages 1-18, April.
    3. Anna Szymczak-Graczyk & Gabriela Gajewska & Ireneusz Laks & Wojciech Kostrzewski, 2022. "Influence of Variable Moisture Conditions on the Value of the Thermal Conductivity of Selected Insulation Materials Used in Passive Buildings," Energies, MDPI, vol. 15(7), pages 1-17, April.
    4. H.-Ping Tserng & Cheng-Mo Chou & Yun-Tsui Chang, 2021. "The Key Strategies to Implement Circular Economy in Building Projects—A Case Study of Taiwan," Sustainability, MDPI, vol. 13(2), pages 1-16, January.
    5. Pruethsan Sutthichaimethee & Boonton Dockthaisong, 2018. "A Relationship of Causal Factors in the Economic, Social, and Environmental Aspects Affecting the Implementation of Sustainability Policy in Thailand: Enriching the Path Analysis Based on a GMM Model," Resources, MDPI, vol. 7(4), pages 1-26, December.
    6. Qianqian Zhao & Junzhen Li & Roman Fediuk & Sergey Klyuev & Darya Nemova, 2021. "Benefit Evaluation Model of Prefabricated Buildings in Seasonally Frozen Regions," Energies, MDPI, vol. 14(21), pages 1-18, November.
    7. Wang, Qiang & Li, Shuyu & Li, Rongrong & Ma, Minglu, 2018. "Forecasting U.S. shale gas monthly production using a hybrid ARIMA and metabolic nonlinear grey model," Energy, Elsevier, vol. 160(C), pages 378-387.
    8. Bartosz Radomski & Tomasz Mróz, 2021. "The Methodology for Designing Residential Buildings with a Positive Energy Balance—Case Study," Energies, MDPI, vol. 14(16), pages 1-19, August.
    9. Sovacool, Benjamin K. & Daniels, Chux & AbdulRafiu, Abbas, 2022. "Transitioning to electrified, automated and shared mobility in an African context: A comparative review of Johannesburg, Kigali, Lagos and Nairobi," Journal of Transport Geography, Elsevier, vol. 98(C).
    10. Houchao Sun & Yuwei Fang & Minggan Yin & Feiting Shi, 2023. "Research on the Restrictive Factors of Vigorous Promotion of Prefabricated Buildings in Yancheng under the Background of “Double Carbon”," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    11. Weibo Zhao & Dongxiao Niu, 2017. "Prediction of CO 2 Emission in China’s Power Generation Industry with Gauss Optimized Cuckoo Search Algorithm and Wavelet Neural Network Based on STIRPAT model with Ridge Regression," Sustainability, MDPI, vol. 9(12), pages 1-15, December.
    12. Pruethsan Sutthichaimethee & Kuskana Kubaha, 2018. "The Efficiency of Long-Term Forecasting Model on Final Energy Consumption in Thailand’s Petroleum Industries Sector: Enriching the LT-ARIMAXS Model under a Sustainability Policy," Energies, MDPI, vol. 11(8), pages 1-18, August.
    13. Wang, Qiang & Li, Shuyu & Li, Rongrong, 2018. "China's dependency on foreign oil will exceed 80% by 2030: Developing a novel NMGM-ARIMA to forecast China's foreign oil dependence from two dimensions," Energy, Elsevier, vol. 163(C), pages 151-167.
    14. López-Guerrero, Rafael E. & Vera, Sergio & Carpio, Manuel, 2022. "A quantitative and qualitative evaluation of the sustainability of industrialised building systems: A bibliographic review and analysis of case studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    15. Jie Ma & Amos Oppong & Kingsley Nketia Acheampong & Lucille Aba Abruquah, 2018. "Forecasting Renewable Energy Consumption under Zero Assumptions," Sustainability, MDPI, vol. 10(3), pages 1-17, February.
    16. Muhammad Hamza & Rai Waqas Azfar & Khwaja Mateen Mazher & Basel Sultan & Ahsen Maqsoom & Shabir Hussain Khahro & Zubair Ahmed Memon, 2023. "Exploring Perceptions of the Adoption of Prefabricated Construction Technology in Pakistan Using the Technology Acceptance Model," Sustainability, MDPI, vol. 15(10), pages 1-25, May.
    17. Dittmer, Celina & Krümpel, Johannes & Lemmer, Andreas, 2021. "Power demand forecasting for demand-driven energy production with biogas plants," Renewable Energy, Elsevier, vol. 163(C), pages 1871-1877.
    18. Li Yang & Xue Wang & Junqi Zhu & Liyan Sun & Zhiyuan Qin, 2022. "Comprehensive Evaluation of Deep Coal Miners’ Unsafe Behavior Based on HFACS-CM-SEM-SD," IJERPH, MDPI, vol. 19(17), pages 1-29, August.
    19. Wang, Qiang & Song, Xiaoxin, 2019. "Forecasting China's oil consumption: A comparison of novel nonlinear-dynamic grey model (GM), linear GM, nonlinear GM and metabolism GM," Energy, Elsevier, vol. 183(C), pages 160-171.
    20. Shuyu Li & Xue Yang & Rongrong Li, 2018. "Forecasting China’s Coal Power Installed Capacity: A Comparison of MGM, ARIMA, GM-ARIMA, and NMGM Models," Sustainability, MDPI, vol. 10(2), pages 1-15, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:19:p:14264-:d:1248644. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.