International Joint Polish-Swedish Publication Service

The Impact of Software renovation on Identity: A Social Approach According to the Rules of Science and Technology

Henning Blomgren, Carl Isaksson, Thorsten Sörensen

Abstract

In the recent decades, it has been detected that innovation rules have a decisive role in the process of technological development. According to the existence of dynamic relations between rules and innovation, having a comprehensive outlook in analyzing technological processes seems to be necessary. According to the growing trend of application and the effect of technology in the society especially organizations, Social-cultural studies in the field of Science and Technology is of great importance. With a sociological outlook on the field of information technology, this research has been evaluated to investigate a range of software renovation impacts of traditional trends in the system of Telecommunication subscriber affairs on components of identity. The present research explained the intended relationships through emphasizing the Antony Giddens' theories, correlation method and the questionnaire's technique on 222 of workers who were selected by Stratified sampling. All analyzes were done with the aid of software package for social sciences. The results show that there are two direct and significant relationships between the variable of Software renovation of traditional trends and the variable of users' fundamental trust (P<0.001) and between the variable of Software renovation of traditional trends and the variable of users' values and attitudes (P<0.001). Also, there are two other direct and significant relationships between the variable of users' values and attitudes and the variable of users' personal identity (P<0.02) and the variable of users' fundamental trust with the variable of users' personal identity (P<0.02) and the variable of users' fundamental trust with the variable of users' personal identity (P<0.001). The variable of users' fundamental trust (β =0.26, P< 0.001) predicts the variable of users' personal identity.

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