Shi, Q and Wang, Z (2025) Spatial-temporal evaluation of total-factor energy efficiency in Chinese construction industry based on three-stage super-efficiency sbm-DEA model. Engineering, Construction and Architectural Management, 32(9), pp. 5716-5742. ISSN 0969-9988
Abstract
Purpose - The study aims to enhance energy efficiency within the high-energy consuming construction industry. It explores the spatial-temporal dynamics and distribution patterns of total factor energy efficiency (TFEE) across China’s construction industry, aiming to inform targeted emission reduction policies at provincial and city levels. Design/methodology/approach - Utilizing a three-stage super-efficiency SBM-DEA model that integrates carbon emissions, the TFEE in 30 Chinese provinces and cities from 2004 to 2019 is assessed. Through kernel density estimation and exploratory spatial data analysis, the dynamic evolution and spatial patterns of TFEE are examined. Findings - Analysis reveals that environmental investments positively impact TFEE, whereas Gross Regional Product (GRP) exerts a negative influence. R&D expenditure intensity and marketization show mixed effects. Excluding environmental and random factors, TFEE averages declined, aligning more closely with actual development trends, showing a gradual decrease from east to west. TFEE exhibited fluctuating growth with a trend moving from inefficient clusters to a more even distribution. Spatially, TFEE demonstrated aggregation effects and characteristics of space-time transition. Originality/value - This research employs the three-stage super-efficiency SBM-DEA model to measure the total factor energy efficiency of the construction industry, taking into account external environment, random disturbances, and multiple effective decision-making units. It also evaluates energy efficiency changes before and after removing disturbances and comprehensively examines regional and temporal differences from static and dynamic, overall and phased perspectives. Additionally, Moran scatter plots and LISA cluster maps are used to objectively analyze the spatial agglomeration and factors influencing energy efficiency.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | exploratory spatial data analysis; spatial agglomeration effect; spatial and temporal distribution; total-factor energy efficiency |
| Index terms: | maps, evolution, methodology, decision-making, China, efficiency, density, energy efficiency, carbon emission, estimation, dynamics, spatial data, construction industry |
| Subjects: | decision analysis, industry analysis, systems engineering, performance management, sustainability and energy, financial and cost management, research methods, spatial and geospatial analysis, Geography, environmental science, analytical methods, climate science |
| Topics: | Urban Studies, Cost Management, Research Practice, Quality Management, Geographical Context, Engineering Principles, Risk Management, Sustainability |
| Descriptive scope: | 3 PCT |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here