The purpose of this research is to investigate the influence of green recruitment and selection, green training, and green intellectual capital on employee performance in Yogyakarta, Indonesia. The data collection method used in this research is to look for observation, interviews, and the distribution of questionnaires. Structural Equation Modeling is used to be an analysis method with SmartPLS assistance. Within the SEM model, this research predominantly employs the Partial Least Squares (PLS) technique, a component-based or variance-based structural equation modeling approach. PLS enables the testing of theories or theory development for predictive purposes based on experimental results. Based on the results of this study, green recruitment and selection have a significant and positive impact on employee performance. However, green training does not have any statistically significant positive effect on employee performance in the same region. On the other hand, green intellectual capital shows a significant and positive influence on employee performance. These results contribute to understanding the relationship between green human resource practices and employee performance.

Greenhouse gases (GHGs) have caused extreme temperature changes. In January 2023, temperatures were 0.1°C higher than the normal 30-year monthly average. Construction, especially high-rise offices, which occupy 42% of Jakarta, contributes significantly through energy con-Sumption. To reduce carbon emissions, Indonesia has started to implement green retrofits as part of the Net Zero Emission 2050. Due to high costs and lack of public education on new and existing green buildings, the implementation of green retrofits is inhibited, and owners prefer conventional buildings. This research aims to analyze the feasibility and investment risk of implementing green retrofits in high-rise office buildings using the life cycle cost method and the Minister of Public Works and Public Housing Regulation No. 21 of 2021 to generate a feasible and safe in-vestment. It has been proven with cost savings in energy and water consumption of up to 15% compared to conventional office buildings. Profits have also been achieved by providing 9 benefits to the building owner, building manager and building occupants. Therefore, this research has the potential to accelerate the green revolution through feasible and safe green retrofit investments in Jakarta's office buildings.

This study aims to develop a new data-driven methodology for identifying suitable influencers for a brand using data from social media. The increasing presence of such figures in these communication channels makes it challenging to select consistent and influential influencers for a specific audience. This paper introduces an innovative approach to defining these figures based on the analysis of relationships within the brand's network. Specifically, this methodology will be applied to the case study of a brand named “Anemonia”. The approach relies on the sequential application of various steps, including the use of tools such as Social Network Analysis (SNA) centrality, Sentiment Analysis (SA), and Analytical Hierarchical Process (AHP). Through the application of this methodology, the brand has been able to identify influencers consistent with its aesthetics and vision.

In the dynamic landscape of digital enterprises, cybersecurity has emerged as a critical determinant of organizational effectiveness. This study delves into the intricate realm of cybersecurity investment within ASEAN organizations, exploring the key facets that drive decision-making in this domain. Using a quantitative approach through structural equation modeling (SEM), we conducted an in-depth analysis based on a sample of 419 enterprises meeting cybersecurity criteria. Our findings reveal that cybersecurity strategy, financial considerations, and institutional and regulatory conditions are the primary factors influencing cybersecurity investments in the ASEAN region. In particular, financial resources emerged as the most critical determinant, underscoring the importance of adequate funding to address evolving cyber threats. Furthermore, our study highlights the crucial role of institutional and regulatory frameworks in shaping investment behavior, indicating a heightened awareness among firms regarding compliance with legal requirements. By unpacking these dynamics, our research provides deep insights into the intricate interplay of factors shaping cybersecurity investments in ASEAN organizations. This study contributes to the discourse by emphasizing the imperative nature of understanding the impact of risk aversion, organizational structures, and long-term practices on cybersecurity resilience. The implications of our findings extend to policy making, innovation, and future research directions in the cybersecurity domain, offering valuable insights to improve cybersecurity preparedness and resilience against evolving cyber threats.

This research presents a short review of Multiple Criteria Decision-Making (MCDM) methods and research in various fields, including marketing and business management. The academic literature shows that MCDM methods in the area of marketing are used by academics to solve problems related to the positioning of products and services, market segmentation, brand management, promotion and advertising strategies, product development and market entry strategies, customer relationship marketing and channel distribution. With regard to business and management domains they are used to prioritize various decision-making aspects, like project assessments, resource allocation, strategic planning, risk management, performance evaluation, supplier and vendor selection, human resource management and strategic investment decisions. We can claim that in both domains, MCDM brings a systematic and transparent approach to decision-making, helping marketing managers to make more informed and objective choices. In summary, the continual refinement of these methods and the integration of cutting-edge technologies hold promise for further enhancing the effectiveness and efficiency of decision-making processes in the dynamic landscape of business and management. Further, the analysis highlights emerging trends and challenges for the future of MCDM research.