The aim of this study is to propose a framework model to capture the knowledge management (KM) process and KM enablers and their connection to improving learning and growth in creative industries. This study is a literature review that analyses several articles related to KM and creative industries. Field observations were conducted at two creative industries to verify the literature review results. This review explores several studies of KM enablers and KM processes to identify KM’s relationship with organizational performance. Organizational performance can be measured from several perspectives, one of which is the tangible perspective of learning and growth. The framework model comprises three interrelated concepts of KM and performance: KM enablers, KM processes, and learning and growth as an intangible type of performance. Further study is needed to identify the types of KM enablers and KM processes to obtain a better understanding of how to improve the performance of creative industries. This study is limited to knowledge management in creative industries. Studies of KM strategies in creative industries are limited, including in Indonesia. Previous studies identify the relationship between KM implementation and improving tangible performance measurements, such as financial and customer performance. This study contributes to our knowledge of implementing KM to improve intangible performance in creative industries.

The X and Y fields are among the oil fields in the Java basin, Indonesia. As oil production decreases due to exploitation activities in X and Y fields, it is necessary to carry out activities to increase production. To increase the yield of its oil production, Enhanced Oil Recovery (EOR) technology is needed. Enhanced oil recovery (EOR) technique screening analysis is needed to be carried out at the initial stage of the feasibility study in the EOR project. At present, there is no fully established method for identifying potential candidates for the EOR technique. The most common approach for selecting EOR techniques is conventional filtering, which is generally based on the "go-no go" trial and error, with a reduced chance of success. Besides, determining potential candidates for EOR techniques often uses a reservoirsimulation approach, but this is time-consuming and requires high costs in using the software license. EOR technique screening with a method that explains how to form a multi-criteria decision-making model with a combination of AHP and TOPSIS methods together as a systematic and measurable method to get the best EOR techniques in both X and Y fields. The research results found that the CO2Immiscible Technique was the most appropriate for EOR in fields X and Y because it has the highest preference value (0.676), is then followed by the Micellar technique (preference value 0.645) and HC Immiscible (preference value 0.517). With the multi-criteria decision-making technique, the best EOR technique results are obtained. Then the proposal can provide valuable recommendations for company management in both fields X and Y with a faster, accurate, and inexpensive method compared to the reservoir simulation method, which has a longer processing time and more expensive costs. This technique can support technology implementation decision-making in the early stages of EOR project development.