Multivariate Linear Regression Method Based on STATA Analysis of Influencing Factors of Internal Control Quality
- DOI
- 10.2991/978-94-6463-056-5_49How to use a DOI?
- Keywords
- Multiple Linear Regression; STATA software; Interpersonal Trust; Internal Control Quality; Decision Power Allocation; Property Rights
- Abstract
In order to improve internal control quality of the business, this article explores this problem from culture which includes interpersonal trust. In this paper, the data of interpersonal trust, decision power allocation internal control and company financial performance from 2010 to 2019 are taken as samples, and the multivariate linear regression method is used to establish the model and observe the multivariate linear regression relationship by using STATA software. The results show that the linear model with interpersonal trust as the independent variable, decision power allocation as the moderator variable and internal control quality as the dependent variable has higher prediction accuracy, that is, interpersonal trust is significantly negatively correlated with the quality of internal control and decision power concentration has a negative moderating effect on the relationship between interpersonal trust and internal control quality.
- Copyright
- © 2023 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.
Cite this article
TY - CONF AU - Jingyu Liu PY - 2022 DA - 2022/12/29 TI - Multivariate Linear Regression Method Based on STATA Analysis of Influencing Factors of Internal Control Quality BT - Proceedings of the 2022 2nd International Conference on Management Science and Software Engineering (ICMSSE 2022) PB - Atlantis Press SP - 343 EP - 348 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-056-5_49 DO - 10.2991/978-94-6463-056-5_49 ID - Liu2022 ER -