Indonesia’s stock market has seen an increase in investment due to the ease of investing and the availability of information about stocks on different social media platforms. This research uses a social network approach to analyze overconfidence behavior in millennial stock investors. This research uses a descriptive quantitative method. The population used in this study are capital market investors in the Greater Solo area who are millennials (<30 years). The number of stock investors in the Greater Solo area is 60,542 investors. The sampling technique in this study was non-probability sampling using purposive sampling. This research uses the AMOS SEM (Structural Equation Model) analysis tool. The conclusion of this study is that millennial investors’ overconfidence behavior increases influenced by financial literacy. investor skills. family ties and friendship ties. The contribution of this research can be applied to understand and educate millennial investors in order to overcome overconfidence behavior so that they can anticipate the losses received. This research may have implications for improving Behavioral Finance Integration Incorporating insights from behavioral finance into investment strategies can help mitigate the negative effects of overconfidence. The limitation in this study is that the scope used in the study is only in the greater solo area.

The Trans Sumatra Toll Road (TSTR) is a mega toll road project with an assignment State-Owned Enterprise (SOE) scheme in Indonesia. In its development, TSTR has several limitations, including funding, low investment feasibility and the un-optimum implementation of land value capture (LVC). This has the impact of delaying the completion of project development, decreasing the performance of toll road developer companies and even causing bankruptcy. LVC is an alternative funding scheme proven successful in other countries such as Hongkong, England and Vietnam. Several transportation projects based on transit-oriented development have successfully achieved profits using the LVC method. With a low project feasibility, the implementation of the Road Plus Property Developer (RPPD) business model is expected to be a solution to improve investment performance in the TSTR project. RPPD is defined as an assignment scheme toll road business model based on LVC implementation. This research aims to develop policies for implementing the RPPD business model on toll road SOE-assigned schemes. The data was collected by in-depth interviews with experts in two stages. The data analysis method used is Soft System Methodology (SSM). This research produces two recommended actions: ratification of the Presidential Regulation regarding the implementation of LVC and institutional transformation of regionally owned business entities in the property sector. It is hoped that implementing the RPPD policy will become a priority in completing the TSTR project.

Unmanned Aerial Vehicles (UAVs) have gained spotlighted attention in the recent past and has experienced exponential advancements. This research focuses on UAV-based data acquisition and processing to generate highly accurate outputs pertaining to orthomosaic imagery, elevation, surface and terrain models. The study addresses the challenges inherent in the generation and analysis of orthomosaic images, particularly the critical need for correction and enhancement to ensure precise application in fields like detailed mapping and continuous monitoring. To achieve superior image quality and precision, the study applies advanced image processing techniques encompassing Fuzzy Logic and edge-detection techniques. The study emphasizes on the necessity of an approach for countering the loss of information while mapping the UAV deliverables. By offering insights into both the challenges and solutions related to orthomosaic image processing, this research lays the groundwork for future applications that promise to further increase the efficiency and effectiveness of UAV-based methods in geomatics, as well as in broader fields such as engineering and environmental management.

Blockchain technology has increasingly attracted the attention of the financial service sector, customers, and investors because of its distinctive characteristics, such as transparency, security, reliability, and traceability. The paper is based on a Systematic Literature Review (SLR). The study comprehended the literature and the theories. It deployed the technology-organization-environment (TOE) model to consider technological, organizational, and environmental factors as antecedents of blockchain adoption intention. The paper contributes to blockchain literature by providing new insights into the factors that affect the intention to adopt blockchain technology. A theoretical model incorporates antecedents of blockchain adoption intention to direct an agenda for further investigations. Researchers can use the model proposed in this study to test the antecedents of blockchain adoption intention empirically.

The development of the maize agribusiness system is highly dependent on the role of social capital in facilitating interaction among actors in the chain of activities ranging from the provision of farm supplies to marketing. Therefore, this research aimed to characterize the key elements of social capital specifically bonding, bridging, and linking, as well as to demonstrate their respective roles. Data were collected from farmers and non-farmers actors engaged in various activities in the maize agribusiness system. The data obtained were processed using ATLAS Ti, applying open, axial, and selective coding techniques. The results showed the roles played by bonding, bridging, and linking social capital in the interaction between farmers and multiple actors in activities such as providing farm supplies, farming production, harvesting, post-harvest, and marketing. The combination of these social capital forms acted as the glue and wires that facilitated access to resources, collective decision-making, and reduced transaction costs. These results have theoretical implications, suggesting that bonding, bridging, and linking should be combined with the appropriate role composition for each activity in the agribusiness system.

This study aims to develop and validate a strategic model tailored to the unique challenges and contexts faced by micro, small, and medium-sized enterprises (MSMEs) in Ecuador, enhancing their operational efficiency and access to financing. Employing a quantitative approach, the research utilized a non-experimental, cross-sectional design to gather data from a sample of 358 companies. The study revealed that MSMEs are significantly hindered by limited access to financing, lack of managerial skills, and technological gaps. Despite these challenges, MSMEs demonstrated considerable adaptability and resilience, underscoring their critical role in the local economy. The strategic model proposed leverages Porter’s Diamond Model to identify and address the specific competitive and operational challenges encountered by these enterprises. Key findings include the necessity for enhanced financial literacy, simplified regulatory frameworks, and the integration of digital technologies to improve competitiveness. The proposed model focuses on strategic training, fostering innovation, and creating a more supportive financing environment. The implications of this study are profound, suggesting that policymakers and practitioners should streamline regulatory processes, enhance financial and technological support frameworks, and provide tailored training programs. These strategies are intended to bolster the sustainability and growth of MSMEs, contributing to broader economic development. This research contributes to the academic literature by providing empirical evidence on the challenges faced by MSMEs in developing economies and proposing a contextually adapted strategic model to mitigate these challenges, thereby enhancing their economic impact and sustainability.