Author
Listed:
- Jialong Liu
- Xin Su
- Yang Wang
Abstract
The growing emphasis on sustainability in supply chain management has raised critical concerns about its implementation in complex ecosystems such as sports stadiums. This study investigates the economic and environmental dimensions of sustainable supply chains within sports complexes, employing the Method of Moments Quantile Regression (MMQR) technique to provide a nuanced analysis of key variables influencing sustainability outcomes from 2008 to 2022. By integrating Corporate Environmentalism (CE), Population Density (PD), Economic Complexity Ratio, and Workforce Readiness Ratio with Gross Domestic Product (GDP) differentiation metrics, the research identifies significant conditional and non-linear relationships. Results reveal that CE plays a pivotal role in driving GDP differentiation, particularly in lower quantiles, highlighting the potential of sustainability to contribute to balanced economic growth. Population Density consistently influences sustainability outcomes, underscoring the critical role of demographic factors. Additionally, the study exhibit strong macroeconomic and social implications, emphasizing the importance of inclusive strategies for sustainable development. Notably, higher GDP differentiation quantiles reveal trade-offs between economic and environmental goals, presenting challenges for achieving equilibrium. These findings suggest that policymakers and stakeholders should adopt tailored strategies to balance economic and environmental objectives, fostering sustainable practices in sports stadium ecosystems while mitigating disparities across different economic conditions.
Suggested Citation
Jialong Liu & Xin Su & Yang Wang, 2025.
"Evaluating sports complex sustainable supply chains: A prospective assessment technique method of moments quantile regression research,"
PLOS ONE, Public Library of Science, vol. 20(6), pages 1-17, June.
Handle:
RePEc:plo:pone00:0323054
DOI: 10.1371/journal.pone.0323054
Download full text from publisher
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:plo:pone00:0323054. 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.
We have no bibliographic references for this item. You can help adding them by using 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.