Knowledge Strategies in Using Social Networks
AbstractKnowledge strategy selection is a multiple criteria decision-making (MCDM) problem, and requires adequate methods to solve it appropriately. Knowledge strategies are also intrinsically linked to individuals and their ability to comprehend the world and leverage their intellectual assets to respond e!ectively to a fast changing environment. the essential features of social networking sites include but are not limited to: blogging, grouping, networking and instant messaging. Since the social networks facilitate communication and interaction among users, there is a continuous need of researches to examine what are the motives that a!ect the acceptance of usage of the social networks. This study aims at examining the role of the knowledge strategies that individuals employ in using social networks with respect to the overall objective of increasing the knowledge level. For this purpose we have used the Analytic Hierarchy Process (AHP) mathematical model since it allows us a structuring of the overall objective on the main components. For the present research we considered a structure composed of three levels: L1 – the purpose of networking, L2 – strategies used to achieve that purpose, and L3 – activities needed for strategies implementation. At the upper level (L1), the main objective of a person in using social networks is to increase its knowledge level. To obtain the aforementioned objective we considered for the second level (L2) the following strategies: S1 – to learn from other persons; S2 – to make new friends; S3 – to increase the personal experience and visibility. the implementation of these strategies is realized through the following activities considered at the third hierarchy level (L3): A1– joining general social networks (e.g. Facebook, Google+, MySpace, Hi5 etc.); A2– joining professional social networks (e.g. LinkedIn etc.); A3– creating a personal blog (e.g. Blogster, Wordpress etc.); A4– joining online communities of practice. the study focused on students, as they hold very important percentage of the total users of social networks. A total of 700 questionnaires were distributed to 18-25 years old students and the rate of response was 42%. Based on the theory of eigenvalues, the AHP mathematical model provides the priority vectors for both the strategies and the activities levels, thus, underlining the main knowledge strategies employed in using social networks.
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