A Study on the Utilization Factors and Effects of Big Data in SMEs
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Abstract
Background/Objectives: The purpose of this study was to derive major utilization factors that can increase the practical data utilization ability of SMEs by utilizing big data, and examine the utilization methods and effects.
Methods/Statistical analysis: This study derives the utilization factors and effects of organizational, technical, environmental, and policy aspects so that SMEs can increase their data utilization capabilities. The target was for SME managers or members. Frequency analysis was conducted to understand the distribution by demographic characteristics, and the relationship between factors and effects was measured through factor analysis, correlation analysis, and regression analysis for the measured variables.
Findings: Perform regression to analyze the impact, utilization, and impact of independent variables on technology, organizational gender, environment, and policy performance as dependent variables
Durbin-Watson's index was below 2.1 and self-relevant and had the power to explain the impact of independent variables such as organizational gender, technology, environment, and policy on utilization. In terms of application, it was found that the use of big data had an effect on education and human resource development rather than the perception of managers and members. Therefore, it was found that education related to big data and in-house experts were recognized as necessary. On the effective side, it was found that the perception of managers and employees influenced. It was found that corporate members thought that when promoting big data, promoting it with the strong will of the manager is an effective aspect for using big data.
Improvements/Applications: If you possess the infrastructure and knowledge in the company, and improve the system with the support of members, it will be an opportunity to increase the utilization of it
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