Optimization Analysis of Corporate Social Responsibility Innovation Paths Based on Bayesian Networks

DOI

10.2991/978-94-6463-598-0_42How to use a DOI?

Keywords

Bayesian networks; corporate social responsibility; path optimization

Abstract

To optimize corporate social responsibility (CSR) innovation paths, this study utilizes Bayesian networks to construct a dynamic decision-making model, analyzing the long-term effects of different strategies on environmental protection, social impact, and economic performance. The results show that Bayesian networks can effectively address complex uncertainties, enhance the scientific precision of CSR practices, and contribute to the improvement of sustainability and competitiveness.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yanbin Ni
PY  - 2024
DA  - 2024/12/19
TI  - Optimization Analysis of Corporate Social Responsibility Innovation Paths Based on Bayesian Networks
BT  - Proceedings of the 2024 3rd International Conference on Public Service, Economic Management and Sustainable Development (PESD 2024)
PB  - Atlantis Press
SP  - 406
EP  - 415
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-598-0_42
DO  - 10.2991/978-94-6463-598-0_42
ID  - Ni2024
ER  -