نشریه مدیریت فردا
پیاپی 33 (زمستان 1391)

Employees are critical factors for organization survival Therefore, empowering of them can play an important role in increasing the competitiveness of organizations. Studies show that five dimensions are effective in empowering which includes: "work meaning", "competence", "self-determination", "impact" and "trust". Knowledge management is one of the issues connected to human resource management and employee empowerment and various tools are used in processes related to knowledge management in organizations. The aim of this study is evaluation of knowledge management tools in employee empowerment. Therefore, seven knowledge management tools were selected by asking experts’ point of views. The statistical population of this study was considered the Knowledge-based companies located in science and technology parks and ultimately 43 questionnaires were studied. In this study Fuzzy AHP were used in order to ranking of seven tools of knowledge management. Results shows that among of seven tools “by asking experts’ point of view” and “In-service training” have greatest effect on employee empowerment and “Job Rotation” and “impact” have minimal effect on employee empowerment.

Successful implementation of e-government in each country requires the model that depends on the objectives, requirements and conditions of the country. The lack of proper planning and adoption will lead to the ignorance of necessities and fail in implementation. Since the different dimensions of government are related to each other, the creation and development of e-government is possible only with balanced development in all aspects. Review of the literature in this area suggests that the e-government maturity models, development models and strategic models, all have seen the evolution of e-government from one dimension; and in the field of stakeholders of e-government services, the focus has been only on the supply side of stakeholders. In this paper by reviewing existing models and stakeholder theories, with a systematic approach that will be adapted from Zachman framework, systematic Framework will be presented for the implementation of integrated e-government system. This systematic framework provides five main dimensions along with its components in five developmental stages for the implementation of e-government. These dimensions are: 1) strategies, values and programs (why and when), 2) partnerships and development of stakeholders (who), 3) data and information (what), and 4) infrastructure (What or where), 5) process (how). Finally, dimensions of the model will be analyzed using a questionnaire, survey of experts and statistical tests.

Social Network Analysis (SNA) is associated with the mapping and measuring of relationships and flows between people, groups, organizations, etc. Centrality measures in this context are defined to identify the most important actors in social network. One of the main centrality measures is closeness centrality; in this measure a node is more "central" if it is closer to many more nodes than any other node. In this paper, we develop a conceptual framework for defining centrality measures in complex networks. It is to be noted that one of the major limitations of determining centrality measures is concerning with the structure and effects of relations among people, groups or organizations in principle, and largely ignoring psychological attributes of the individuals. Therefore the proposed framework is based on the combination of two approaches: social network analysis and traditional social science approach by considering both structure of relations and individual characteristics. Detecting communities in complex networks is of considerable importance for understanding both the structure and function of the networks and it is necessary to interpret radial centrality measures. Therefore, we propose spectral clustering by determining the best number of communities as a prerequisite stage before finding closeness measures of centrality. Based on the proposed framework, an algorithm to compute the closeness centrality in complex networks is developed. We test the proposed algorithm on Zachary’s karate club network which is considerably used as a benchmark for community detection in a network. Experimental results indicate that the new algorithm is efficient at detecting both good inter-cluster closeness centrality and the appropriate number of clusters.

Competitive benefit for every service organization in current economic world is cognition of customers, needs and demands and their changes. With good recognition and knowledge of what customers want, organization can meet their expectations and demands and create greater value. this effort increases perceived value behalf of customers and will has positive effect on success organization.