Factor Recognition Analysis on the Performance of Employees of Service companies in the Use of Big Data Information Technology

Abstract

The globalization of the market has intensified the field of competition for companies, companies are trying to increase or at least maintain their competitive advantages by using different resources and processes. Advances in information technology have enabled service companies to store large amounts of data about their customers and exploit it in their strategic marketing thinking. Hence, more knowledge of customers using big data information technology has been considered due to the large volume of seemingly unrelated data as well as the use of complex statistical software to analyze customer needs in recent decades in service companies. In this study, we identify the factors that affect the actual performance of Shuttle employees in the use of big data information technology that leads to the performance of the service company. The purpose of this research is applied and descriptive with the statistical population of the employees of the first mobile company in Alborz province. Statistical analyzes were performed using SPSS and Amos software and structural equations were used to test the hypotheses, which confirmed all but one of the two perceived risk hypotheses on performance prediction as well as perceived risk on behavioral intent. Findings show the effect of performance forecasting, effort forecasting and social factors on the performance of shuttle employees through behavioral intent, taking into account the perceived effect of risk, opportunity cost and resistance to the use of big data.

Keywords

• information technology
• big data
• employee behavior
• perceived risk
• technology resistance