AI Article Synopsis
Article Abstract
Since the introduction of a low-carbon economy, corporate performance is no longer limited to the evaluation of internal economic benefits but has become the performance of corporate sustainable development, adding environmental and social factors. Now, the whole world is paying attention to low consumption and low emission. As the main economic pillar of society, the enterprise undertakes the biggest low-carbon task. In order to develop the economy in the longer term and meet the needs of society, enterprises must combine green innovation to evaluate the performance of sustainable development. However, because the previous model's analysis of performance will produce distortion effects, the data error is also relatively large. Therefore, in order to solve these problems and make performance analysis more realistic, this paper deeply discusses the issue of green innovation and enterprise sustainable development performance. Using the method of the SBM-DEA model, it analyzes the performance comparison of enterprises without and with the expected output and conducts a comparison experiment. The result shows that in 2017, the efficiency of company A without unexpected output was 0.6943. The efficiency with undesired output is 0.6643. In 2018, the efficiency of the enterprise without undesired output is 1, and the efficiency with undesired output is 1. After applying the model, it is obvious that the efficiency of computing performance has been greatly improved. Therefore, in order to better study the sustainable development performance of enterprises, the SBM-DEA model should be focused on.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9448556 | PMC |
| http://dx.doi.org/10.1155/2022/3127899 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Assessing water status in rice plants in water-deficient environments using thermal imaging.
Bot Stud
January 2025
Crop Science Division, Taiwan Agricultural Research Institute, Ministry of Agriculture, Taichung, 413, Taiwan.
Background: Rice is a staple food for the global population. However, extreme weather events threaten the stability of the water supply for agriculture, posing a critical challenge to the stability of the food supply. The use of technology to assess the water status of rice plants enables the precise management of agricultural water resources.
View Article and Find Full Text PDFAssessment of geochemistry and irrigation suitability of the River Ganga, Varanasi, India: PCA reduction for water quality index and health risk evaluation.
Environ Sci Pollut Res Int
January 2025
Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, 221005, India.
Surface water chemistry of the River Ganga at Varanasi was analyzed at 10 locations over 3 years (2019-2021) across pre-monsoon, monsoon, and post-monsoon seasons. The study aimed to assess water parameters using principal component analysis (PCA), calculate the water quality index (WQI), determine processes governing water chemistry, evaluate irrigation suitability, and estimate non-carcinogenic health risks. The physical parameters measured included pH (8.
View Article and Find Full Text PDFLight and dark biofilm adaptation impacts larval settlement in diverse coral species.
Environ Microbiome
January 2025
Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, QLD, Australia.
Background: Recovery of degraded coral reefs is reliant upon the recruitment of coral larvae, yet the mechanisms behind coral larval settlement are not well understood, especially for non-acroporid species. Biofilms associated with reef substrates, such as coral rubble or crustose coralline algae, can induce coral larval settlement; however, the specific biochemical cues and the microorganisms that produce them remain largely unknown. Here, we assessed larval settlement responses in five non-acroporid broadcast-spawning coral species in the families Merulinidae, Lobophyllidae and Poritidae to biofilms developed in aquaria for either one or two months under light and dark treatments.
View Article and Find Full Text PDFPredicting land use and land cover changes for sustainable land management using CA-Markov modelling and GIS techniques.
Sci Rep
January 2025
Department of Wildlife Fisheries and Aquaculture, College of Forest Resources, Mississippi State University, Mississippi State, MS, 39762-9690, USA.
This study addresses the significant issue of rapid land use and land cover (LULC) changes in Lahore District, which is critical for supporting ecological management and sustainable land-use planning. Understanding these changes is crucial for mitigating adverse environmental impacts and promoting sustainable development. The main goal is to evaluate historical LULC changes from 1994 to 2024 and forecast future trends for 2034 and 2044 utilizing the CA-Markov hybrid model combined with GIS methodologies.
View Article and Find Full Text PDFAge group classification based on optical measurement of brain pulsation using machine learning.
Sci Rep
January 2025
Research Unit of Health Sciences and Technology, University of Oulu, Oulu, Finland.
Optical techniques, such as functional near-infrared spectroscopy (fNIRS), contain high potential for the development of non-invasive wearable systems for evaluating cerebral vascular condition in aging, due to their portability and ability to monitor real-time changes in cerebral hemodynamics. In this study, thirty-six healthy adults were measured by single channel fNIRS to explore differences between two age groups using machine learning (ML). The subjects, measured during functional magnetic resonance imaging (fMRI) at Oulu University Hospital, were divided into young (age ≤ 32) and elderly (age ≥ 57) groups.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!