To underscore the critical role of predictive capabilities in third-party logistics (3PL) companies for assortment planning, particularly within the rapidly evolving e-commerce sector and business to business (B2B) flows. This study employs a comprehensive literature review on the forecasting capabilities of 3PL firms, enriched by empirical research across nine logistics facilities. It leverages statistical tools and the ARIMA_PLUS algorithm to evaluate the precision and dependability of demand and supply forecasts generated by these companies. The research reveals that 3PLs possess the ability to generate accurate demand and supply forecasts utilizing advanced forecasting tools. The effectiveness of these forecasts is closely linked to the quality of data available, and the expertise of the personnel involved. Challenges arise in forecasting for smaller order volumes, which are more common in e-commerce flows. The study also highlights that technological advancements and investments in data analytics are pivotal in enhancing forecast accuracy. The investigation focuses on a select group of 3PL companies, potentially limiting the generalizability of the findings. Moreover, the study underscores the necessity for further exploration into how technological innovations impact forecasting capabilities. By emphasizing the significance of 3PL firms' predictive abilities, also for e-commerce assortment planning, this paper addresses a notable gap in existing research. Its insights are invaluable for businesses contemplating logistics outsourcing and for 3PL providers aiming to advance their forecasting proficiency. The findings stress the importance of integrating advanced forecasting models and analytics to stay competitive in the dynamic e-commerce landscape.

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.

Due to highly functionalized molecular structure, furfural has made a huge impact in renewable platforms. As there is a big need of producing renewable sources, this review reveals several attempts made by researchers distributed in every nook and corner of the world to produce furfural-based derivatives. As furfurals are converted to various forms, they reflect many applications both with respect to economy and environment friendly approach. In this review, a summarized detail of various reactions of furfural substrates are provided which includes Diels-Alder reactions, Oxidations, Hydrogenations, Hydrogenolysis, Conversions to C6 Carboxylic acids, Furfuryl amines, Cyclopentenones and other useful compounds. These compounds and their applications in various fields are mentioned systematically. The chemical as well as biocatalytic conversions are explained in detail which will help to know the future challenges and hurdles when design and optimization of furfural derivatives are concerned.

Antioxidant activity of a series of previously described 5-amino-N-(iododi(per)fluoroalkyl)-1H-1,2,3-triazole-4-carboxamides 3a-r, their synthetic precursors 5-amino-N-allyl-1,2,3-triazole-4-carboxamides 1a-g, and their deamination products N-(3-di(per)fluoroalkyl-2-iodo-n-propyl)-1,2,3-triazole-4-carboxamides 4a-e was investigated in vitro using DPPH test and ascorbic acid as a standard reference. It was established that compounds 3a-r inhibit DPPH free radicals in moderate to high values (50.9–97.6%). The effect of substituents in the position 1 of the 1,2,3-triazole nucleus, fluoroalkyl groups and amino groups on the level of antioxidant activity was studied in detail. Reactivity and electrostatic surface potential were evaluated for the most active carboxamides 3a,g,r using the DFT method, and molecular docking was studied in the NADPH oxidase protein model.

The correlation between coefficients from Dimroth equations and descriptors of global electron density transfer was explored based on the data available in the recent literature. We established that the obtained results should be very usable for the interpretation of the organic reactivity and molecular mechanisms.

Continuing the search for new antimicrobial agents with antibiofilm activity, bis-quaternary ammonium compounds based on natural (3,5-dibromo-4-hydroxyphenyl)acetic acid derivatives were synthesized. Antibacterial and antibiofilm activity of ammonium salts was evaluated in vitro against S. aureus, E. coli, and P. aeruginosa, including antibiotic-resistant strains. Bis-quaternary ammonium salts 1, 5, and 6 showed antibacterial activity with MIC values ranging from 25.0 to 200.0 μg/mL. Notably, these compounds demonstrated a high level of antibiofilm activity. Ammonium salts 1 and 6 reduced biofilm formation against S. aureus ATCC 25923, P. aeruginosa PA01, E. coli ATCC 25922, and antibiotic-resistant P. aeruginosa by 92 - 97% at a concentration of 100.0 μg/mL. In addition, compounds 1 and 6 inhibited the biofilm formation of antibiotic-resistant E. coli isolate by 60% and 63%, respectively.