The Effective Business Model for Commercialization of ROV Products in Indonesia - Imam Sutrisno; Budianto; Yuning Widiarti; Mohammad Basuki Rahmat; Rini Indarti; Dinda Pramanta; Pranowo Sidi (CV. Creative Tugu Pena, 2025)
This research explores innovative business models for commercializing Remotely Operated Vehicles (ROVs) in the Indonesian market. By analyzing existing case studies and conducting interviews with industry experts, this study identifies potential business models such as ROV-as-a-Service, technology licensing, and joint ventures. The findings highlight the importance of tailoring business models to specific market segments and leveraging digital technologies to enhance operational efficiency and customer satisfaction. This research explores innovative business models for the commercialization of Remotely Operated Vehicles (ROVs) in the Indonesian market. Through case study analysis and interviews with industry experts, this research identifies and evaluates the potential of business models such as ROV-as-a-Service, technology licensing, and joint ventures. The research results show that the ROV-as-a-Service model has the most promising potential, with higher adoption rates among MSMEs due to the flexibility and cost efficiency it offers. In addition, this research also found that the integration of digital technology such as IoT and data analysis can increase ROV operational efficiency and provide added value for customers. These findings provide important implications for companies wishing to enter the ROV market in Indonesia, as well as for policy makers in supporting the development of the marine industry. The ideal number of case studies and interviews in a research depends on several factors, including: Depth of analysis: The deeper you want to dig into a phenomenon, the more cases need to be researched. Case variety: If you want to see a variety of business models or challenges faced by different ROV companies, you need to choose a variety of cases. Availability of resources: Time, cost, and accessibility to data will limit the number of case studies and interviews that can be conducted.