FACTORS INFLUENCING THE INTENTION TO ADOPT BIG DATA TECHNOLOGY IN CONSTRUCTION COMPANIES IN INDONESIA

• Main Author: Abdurahman Faizi, Darda
• Format: Theses
• Language: Indonesia
• Subjects: Teknik sipil
• Online Access: https://digilib.itb.ac.id/gdl/view/84193
• Institution: Institut Teknologi Bandung

The rapid development of Big Data technology offers various benefits in data and information management, particularly in the construction industry, which is highly complex and requires efficient data management. Although the benefits of Big Data are widely recognized, its adoption in the construction industry in Indonesia remains relatively low. Therefore, this study focuses on identifying and analyzing the factors that influence the intention of construction companies to adopt Big Data technology. The purpose of this research is to develop a conceptual model that explains the relationship between various factors influencing the intention to adopt Big Data technology in the construction industry in Indonesia. The method used in this study is a survey using questionnaires distributed to managers and professionals in construction companies. The data obtained were then analyzed using descriptive and correlation analysis methods to identify significant factors. The research approach is based on the Technology-Organization-Environment (TOE) framework and the Diffusion of Innovation (DOI) theory. The TOE framework considers technological, organizational, and environmental factors as the main determinants of technology adoption, while the DOI theory provides insights into how technological innovations spread within organizations. The analysis results show that technological factors such as relative advantage and compatibility, organizational factors such as top management support and organization size, and environmental factors such as competitive pressure and regulations support have a significant influence on the intention to adopt Big Data technology. The dominant factors influencing intention are relative advantage, compatibility, and top management support. These findings are expected to help companies plan effective Big Data adoption strategies and provide insights for researchers and practitioners in developing a more comprehensive technology adoption model.