فهرست مطالب saeed zohrabi

The purpose of this study is to present a comprehensive evaluation-based model for intelligent organizations.

The research was applied-developmental in terms of purpose, descriptive-exploratory in terms of method and quantitative-qualitative in terms of data collection approach. To determine the factors affecting intelligent organizations, the Fuzzy Delphi technique was applied. The statistical population of the study at this stage was consisted of all Iranian organizational managers as well as some academicians, from among of whom 27 individuals were selected by purposive sampling. At the next stage, the Social Security Organization was studied and the components of the intelligent organization were classified through exploratory factor analysis. Confirmatory factor analysis, analysis of variance and Bonferroni post hoc test were used to analyze the data.

The results of Fuzzy Delphi analysis revealed 40 factors, the most important of which are: intelligent foresight, intelligent management and intelligent technological infrastructure. The results of the second phase of the research revealed ten general categories which, according to their priority, are as follow: strategic intelligence, structural intelligence, technological intelligence, knowledge management, information technology, competitive intelligence, environmental intelligence, cultural intelligence, social intelligence and human intelligence.

Intelligent organization is an important part of the e-government strategic plan. The practical result of this research is a comprehensive model that can be used to evaluate similar organizations and to make intelligent decisions.

 Regarding the fact that strategic intelligence significantly affects other types of intelligence, taking it into special consideration is recommended. The role of technological intelligence is vital for the intelligent organization, unlike the traditional organization. With reference to the weight of structural intelligence, restructuring is of great importance at this age of information.

This research looking for design and explain a comprehensive model that can be used to evaluate organizations according to indicators of an intelligent organization.

Design/methodology/approach:

The research is an applied developmental one in terms of purpose, which follows descriptive survey method in terms of nature and methodology. The statistical population of Delphi panel is 20 experts in the field of management and the statistical population of the Case Study is the managers and senior experts of the Social Security Organization. data collection tool contains dimatel interviews that used Delphi technique in three stages to designing it. Data analysis was conducted through DANP (DEMATEL-ANP) technique to obtain cause and effect relationships and the weight of the indicators.

According to the results, technological intelligence (2 indicators) with a weight of 27.52, structural intelligence (4 indicators) 25.6, Intra-organizational intelligence (3 indicators) 23.81, Extra-organizational intelligence (3 indicators) 23.06, Also among 12 indicators, Knowledge management, information technology and systematic thinking were identified as the most important indicators of smart organization.

Limitations & Consequences:

 Due to the specialization of the components of the smart organization, there was a concern that the respondents would not have a uniform understanding of the concepts, so each of the concepts was explained.

Practical Consequences: 

the practical result of this research is a comprehensive model that can be used to evaluate organizations according to the dimensions and indicators of intelligent organization.

Innovation or value of the Article:

Intelligent organization is an important part of strategic integration and alignment in e-government. Also, in terms of the approach in the usual method using the Demetel method and ANP, many influences and relationships may be eliminated. In the DANP method using the total communication matrix to form the ANP supermatrix and calculate the weight of the criteria and sub-criteria.