Volume 3, Issue 2 (2013)
ORMR 2013, 3(2): 131-151 |
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Nemati S, Khaeef elahi A A, Momeni N. Designing Compensation System in Knowledge-Based Organization (KBO) by Interpretive Structural Modeling(ISM) Approach. ORMR 2013; 3 (2) :131-151
URL: http://ormr.modares.ac.ir/article-28-2943-en.html
URL: http://ormr.modares.ac.ir/article-28-2943-en.html
1- PhD Student in Human Resource (HR) Management, Tarbiat Modares University, Tehran, Iran
2- Associate Professor, Management and Economics Faculty, Tarbiat Modares University, Tehran, Iran
3- PhD in Organizational Behavior (OB) Management
2- Associate Professor, Management and Economics Faculty, Tarbiat Modares University, Tehran, Iran
3- PhD in Organizational Behavior (OB) Management
Abstract: (13003 Views)
Accepting differences between knowledge-based organizations and other organizations with respect to the philosophy of existence, nature of the activities and their differentiated employees, we intend to present a proper model with surveying existing models. The presented model should be applicable in the compensation system in knowledge based organizations. Components Influencing compensation systems identified and classified into two main groups of financial and non-financial and four sub-division categories through studying existing models. According to the experts, 8 main effective components in compensation of these organizations were identified. Finally, based on 8 selected components and with the exploiting of the experts opinion and using of Interpretive Structural Modeling (ISM) technique, a prioritizing and leveling model for compensation system of knowledge-based organizations was developed. In this designed model, nonfinancial factors such as job-related factors (job challenge and growth opportunities) and factors related to the job environment (having a floating work hours and workplace conditions) have higher priority. This means that these Factors in compensation system are more important and have more influence.
Keywords: Compensation, Knowledge-Based Organization (KBO), Interpretive Structural Modeling(ISM), Clustering
Received: 2013/06/11 | Accepted: 2014/04/21 | Published: 2014/08/23
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