Emerging maritime cyber threats put Indonesia's marine technology-based systems at risk This study aims to determine the dimensions and analysis of risk assessment in maritime cyber security based on 3D models in the Indonesian sea area. A statistical descriptive qualitative method approach supported by the Analytical Hierarchy Process (AHP) and Technique for Order by Similarity to Ideal Solution (TOPSIS) methods were used in this study. Risk analysis in maritime cybersecurity has 3 (three) main criteria: Threat, Vulnerability, and consequence. Based on the results of 3D risk analysis, the six dimensions of MCS are identified as having a level of risk at Very Low and Low Risk. The highest risk value is obtained by the dimension of Cyber security-related company procedures (D2) (0.368) and the lowest risk value is Ship's systems readiness (D3) (0.048).

The world surrounded by plastics generates a lot of uncertainty and the first victims are sea animals, plastic in contact with the sun is able to disintegrate and generate toxins that are harmful to health. It is for this reason that this research in bibliographic review allows us to know the different solutions to counteract microplastics through the analysis of the Scopus database and the VOSviewer tool that allows us to analyze the data, considering the essential characteristics that are plants, animals, bacteria, algae and technologies that allow the disintegration, elimination and purification of microplastics, graphs and tables were obtained which allow us to recognize the analyzed data, the countries that carry out these investigations and the bibliometric maps worldwide. The results allow us to understand that the existence of microplastics generates many negative consequences for planet earth, however, there are different solutions which we can use and apply to counteract these microplastics, also considering that countries like Peru do not find published scientific research relevant to this matter. The purpose of this research is to allow us to make better decisions and not lose heart in the face of microplastics since it can be fought with the different solutions that we find on planet earth, technology and the other objective is to motivate readers to take action in the issue and allow generating change in the use of plastics.

In today's competitive business environment, the implementation of Customer Relationship Management (CRM) strategies is essential for firms to succeed. The purpose of this study is to investigate the relationship between CRM, customer satisfaction, and business profitability in the Jordanian logistics industry. Specifically, the study examines how customer satisfaction mediates the effect of three key CRM on business profitability. To achieve this, Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze data collected from 384 employees of logistics firms in Jordan. The results of the study suggest that CRM positively affects customer satisfaction, and that customer satisfaction has a significant mediating effect on the relationship between CRM and business profitability. The findings of this study have important implications for logistics firms seeking to improve their business profitability through the adoption of CRM. By focusing on the three key CRM (Customer Identification, Customer Acquisition, and Customer Analytics), firms can improve their customer satisfaction levels, which, in turn, can lead to improved business profitability. This study adds to the growing body of literature on CRM practices and their impact on business profitability, particularly in the context of the Jordanian logistics industry.

The current research addresses the inventory classification problem of community pharmacies, which have a dual role as both a vital component of the pharmaceutical supply chain and a typical retail store. Despite the existing literature indicating that pharmacists may lack knowledge on inventory management, it seems that the MCIC literature is weak in explaining how pharmacists can benefit from MCDA techniques in all aspects. To bridge this gap, the study aims to demonstrate that pharmacists can utilize MCDA techniques to gain deeper insights beyond mere classification in the context of inventory management. Real-world data from a community pharmacy in Turkey was classified using the EDAS method. Sensitivity analysis was performed for MCDA inputs, about which pharmacists may lack information. Scenario findings based on criterion weights and threshold values offer important managerial implications for pharmacists. This study provides a critical contribution to the literature on inventory management in community pharmacies by highlighting the potential of MCDA techniques to support decision-making beyond mere classification. The sensitivity analysis also sheds light on areas where pharmacists may lack knowledge and suggests ways to address these gaps. Overall, the study underscores the need for pharmacists to have a deeper understanding of inventory management and highlights the potential benefits of MCDA techniques in addressing this challenge.

The MEWMA chart is one of the traditional multivariate charts which are widely employed in inspecting the quality of manufacturing and services. This chart is created through monitoring the small shifts of mean vectors of variable quality characteristics. Often in practice, the measurement of a quality characteristic produces uncertain, incomplete values, so that ambiguous numbers are obtained. In this condition, a neutrosophic-based control chart can overcome the problem resulting from the ambiguous data. The paper’s objective is to construct a new multivariate monitoring scheme based on a neutrosophic chart, namely the neutrosophic Multivariate EWMA (NMEWMA). Furthermore, the performance of the new multivariate monitoring scheme is evaluated in detecting process shifts employing the Average Run Length (ARL) and Standard Deviation Run Length (SDRL). This control chart is an innovation in the quality monitoring of uncertain data. The research result obtained indicates that the NMEWMA chart performs better than the MEWMA in finding the small mean shifts as well as in the real case application.