Spatial–Temporal pattern and evolutionary trend of eco-efficiency of real estate development in the yangtze river economic belt

Fan, Zhenggen; Deng, Zhikang; Qi, Yanfei; Pan, JiaSen

doi:10.3389/fenvs.2022.996152

Cited by 3 publications

(1 citation statement)

References 59 publications

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“…Previous studies on EE have focused on the firm (industry), regional, and national levels. For example, at the firm (industry) level, Fan et al (2022) measured the EE of real estate development using the super-SBM model and showed that the overall efficiency of 108 cities in the Yangtze River Economic Belt improved from 2006 to 2020. Zhang, Yang, Wu, et al (2022) used a similar approach to measure the EE of China's tourism industry and showed that it is generally in a stage of dynamic equilibrium.…”

Section: Eco-efficiencymentioning

confidence: 99%

Using eco‐efficiency and eco‐wellbeing performance as indicators for urban sustainable development: A two‐stage network analysis

Zhang,

Cai,

Jiao

et al. 2023

Sustainable Development

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Sustainable development is one of the most significant issues of concern around the world today. Sustainable development goals cover natural resources, the environment, and human well‐being. It follows that eco‐efficiency (EE) and eco‐well‐being performance (EWP) are valid tools for measuring the level of different stages of sustainable development. This study uses a two‐stage super‐SBM model to gauge the EE and EWP of 281 cities in China from 2011 to 2019. The results show the following: (1) The national EE average is low, with M‐shaped “rising‐declining‐rising‐declining” fluctuation. The national EWP average is low, but there is a clear upward trend. (2) From a regional perspective, the best EE is in the eastern region, followed by the central and western regions, and the worst is in the northeastern region. The best EWP is in the western region, followed by the eastern and northeastern regions, and the worst is in the central region. (3) Among the 281 sample cities, approximately 12.8% are in the high EE‐high EWP development mode, 25.6% are in the high EE‐low EWP development mode, 18.2% are in the low EE‐high EWP development mode, and 43.4% are in the low EE‐low EWP development mode. Collectively, the three cities with the strongest sustainability are Shenzhen, Beijing, and Haikou, and the three weakest are Baise, Jinchang, and Baiyin. In addition, cities with larger populations tend to exhibit greater sustainability. These results provide the necessary reference for Chinese cities and cities worldwide in similar situations to formulate policies to improve sustainability.

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Section: Eco-efficiencymentioning

confidence: 99%

Using eco‐efficiency and eco‐wellbeing performance as indicators for urban sustainable development: A two‐stage network analysis

Zhang,

Cai,

Jiao

et al. 2023

Sustainable Development

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An analysis of production efficiency in China’s real estate industry based on a two-stage DEA model

Meng,

2024

PLoS ONE

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To examine the resource utilization in different phases such as development and sales within China’s real estate industry, this paper employs a two-stage Data Envelopment Analysis (DEA) model to measure the production efficiency of the real estate industry across 31 provinces, municipalities, and autonomous regions of China from 2014 to 2022. By examining both overall and phase-specific trends, the study utilizes a panel Tobit model to explore the factors affecting efficiency. Empirical results indicate that the leverage ratio of companies, per capita GDP of regions, and real estate regulatory policies significantly impact production efficiency. Further analysis of regional heterogeneity and its effect on production efficiency revealed that the per capita residential building area, which reflects the housing stock configuration in different regions, exhibits a significant single threshold effect. This not only objectively assesses the utilization of real estate resources in different areas but also delves deeper into the principal factors and their mechanisms affecting the production efficiency of the real estate industry, thus providing theoretical support and policy recommendations for effectively enhancing production efficiency.

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Dynamics, Risk and Management Performance of Urban Real Estate Inventory in Yangtze River Delta

Zhang

Chen²,

Zhao³

et al. 2022

Buildings

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(1) Background: Inventory management is a key point in the achievement of the virtuous cycle and sustainable development of the real estate industry. In response to the practical needs of city-based policies, this paper constructs a new research approach of “evolution dynamics—risk analysis—performance evaluation—policy design” of real estate inventory, and conducts a case study on the Yangtze River Delta. (2) Methods: This paper studies the change characteristics, trends and spatial patterns of real estate inventory changes in the Yangtze River Delta based on Geographic Information System software, and quantitatively evaluates the risk level and management performance of real estate inventory by introducing the Boston Consulting Group Matrix for corporate management and the Super- Data Envelopment Analysis Model for operations research, providing a basis for policy design. (3) Results: First, the “destocking” policy has gained results to some extent and diversified the inventory evolution, thus alleviating or curbing the negative trend in most cities. Second, the real estate inventory in the Yangtze River Delta is divided into high, low, potential and zero pressure zones by risk levels, and the proportion of cities with increased, decreased and unchanged risk levels is essentially the same. Third, the average real estate inventory management performance index has been steadily improving, but overall, it is still unsatisfactory, with cities in an effective state accounting for 40% and below for a long time. Fourth, real estate inventory and its management performance both show significant spatial effects, with cold and hot spot cities characterized by a “center-periphery” spatial pattern in geographical distribution, and the cities in the study area are classified into four types: super-efficiency, efficiency, inefficiency, and super-inefficiency. Fifth, the real estate inventory in most cities is continuing to grow positively, and a small number of cities have been in the high-risk zone for a long time or become new members of the high-risk zone, making the government and enterprises still faced up with great pressure and challenges in inventory management with the risk level further increased but management performance growing slowly. (4) Conclusions: The study area is divided into four types of policy areas, that is, red key area, yellow important area, green auxiliary area, and path-dependent area, and suggestions for optimization are made from the perspectives of risk control, performance improvement, benchmarking recommendation, and redundancy governance, providing a basis for the government’s real estate inventory management policy design and the enterprise’s high-quality development decision.

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Spatial–Temporal pattern and evolutionary trend of eco-efficiency of real estate development in the yangtze river economic belt

Cited by 3 publications

References 59 publications

Using eco‐efficiency and eco‐wellbeing performance as indicators for urban sustainable development: A two‐stage network analysis

Using eco‐efficiency and eco‐wellbeing performance as indicators for urban sustainable development: A two‐stage network analysis

An analysis of production efficiency in China’s real estate industry based on a two-stage DEA model

Dynamics, Risk and Management Performance of Urban Real Estate Inventory in Yangtze River Delta

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