Volume 2, Issue 7 (12-2018)                   2018, 2(7): 155-176 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

malekmohamadi M, najafifard M. Prioritizing Effective Factors in the Making Ethical Organizations by Using Combined Method of Interpretative Structural Modeling (ISM) and Principal Component Analysis (PCA). Journal title 2018; 2 (7) :155-176
URL: http://jde.khu.ac.ir/article-1-73-en.html
imam khomeini international university
Abstract:   (1601 Views)
Nowadays Organizations consider ethical principles in the business environment as an advantage and seek to strengthen it. This requires a coherent, interactive and cognitive understanding of the parts of internal and external environment of organization, which leads to the realization of the rights of the beneficiaries of the organization. The purpose of this paper is prioritize  the factors involved in the making of ethics in organizations in form of hierarchical model based on Interpretative Structural Modeling (ISM) and Principal Component Analysis (PCA). For this purpose, 88 experts and professors of the university based on survey method as a statistical society were questioned about relevant factors in the form of a questionnaire. With the analysis, it was found that the most important factors in the ethical organization are culture of organization, the organization's environment and the way employees perceive that these are strengthened by the style of managers and ethical infrastructures. Utilizing the proposed method, it leads to the reverse thinking, so can be explicitly attributed the present situation to its partial factors.
Full-Text [PDF 1069 kb]   (672 Downloads)    
Type of Study: Research | Subject: General
Received: 2017/09/2 | Accepted: 2018/10/3 | Published: 2018/12/3

Add your comments about this article : Your username or Email:
CAPTCHA

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Journal of Decision Engineering

Designed & Developed by : Yektaweb