In today's rapidly changing economic landscape, financial resilience has become increasingly important especially for public sector organizations. This study investigates the impact of e-government adoption and social support on individuals' financial resilience in Indonesia, with a focus on the mediating role of financial management skills. A quantitative research methodology was employed, and 348 complete and suitable questionnaires from individuals in the financial department in local government in Indonesia were analyzed using SmartPLS 4.0 software. The results indicate a significant relationship between e-government adoption and financial management skills, suggesting that digitizing government services contributes to improved financial resilience. Additionally, social support was found to have a positive impact on financial management skills, supporting the notion that social networks provide resources and support for financial well-being. Financial management skills were also found to be significantly associated with financial resilience, indicating that individuals with strong financial management skills are better equipped to adapt to changing circumstances. While the mediating effect of financial management skills between e-government adoption and financial resilience was not significant, it was significant in the relationship between social support and financial resilience. These findings provide insights into the factors that enhance financial resilience in an increasingly digitized society and inform strategies to promote financial well-being in Indonesia.

Several Multivariate Adaptive Regression Spline (MARS) approaches are available to model categorical and numerical (especially continuous) data. Currently, there are other numerical data types—discrete or count data—that call for specific consideration in modeling. Additionally, spatially correlated count data is frequently observed. This has been seen in the case of health data, for example, the number of newborn fatalities, tuberculosis patients, hospital visitors, etc. However, currently no structurally consistent nonparametric regression and MARS model for count data incorporating spatial lag autocorrelation. The SAR-MAGPRS estimator (Spatial Autoregressive - Multivariate Adaptive Generalized Poisson Regression Spline) is developed to fill this gap. Although it can be applied to different count distributions, the estimator was developed in this study under the assumption of a Generalized Poisson distribution. This paper provides an information-theoretic framework for incorporating knowledge of the spatial structure and non-parametric regression models, especially MARS for the count data types. Moreover, the proposed method can assist in modeling the number of diseases while health policies are being developed. The framework presents an application of the Penalized Least Square (PLS) method to estimate the SAR – MAGPRS model.

As a capital market investment, stocks have risks that must be managed. Therefore, investors should consider the returns and risks of investment products. This study aims to estimate the risk of insurance companies' loss when investing. The method used to estimate the level of risk is Value at Risk (VaR) based on Extreme Value Theory (EVT). The data used is secondary data in the form of daily stock closing prices from two insurance companies, AXA General Insurance and BRI Insurance, from January 2016 to January 2022. The data were used to estimate the risk value according to the EVT principle. As a result, Insurance AXA General Insurance, with 5.91% liquidity, has the lowest VaR value with a 99% confidence level, while BRI Insurance has 5.04%. We concluded from these results that AXA General Insurance has a lower investment risk. It means that each company has a different risk value. Therefore, investors should know these risk factors when choosing a company.

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 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.

In Indonesia, the success of coal extraction largely depends on the role of mining contractors. One of these successes is determined by proper asset management amidst uncertainty in the coal business, such as sustainability and digitalization issues. However, research that identifies the role of asset management in improving the performance of mining projects is still rare. Therefore, this research investigates the impact of Information technology capability, sustainability practices, and asset management on improving the performance of coal mining contractor projects in Indonesia. This research uses quantitative methods, with questionnaire data filled in by 128 project managers of mining contractor projects spread across Indonesia and analyzed by applying structural equation modeling (SEM). The findings indicate that Information technology capability and sustainability practices have a substantial and beneficial effect on improving asset management, which then enhances the performance of mining contractors. Interestingly, there is no direct impact of Information technology capability and sustainability practices on the operational performance of mining projects, so asset management is highly needed. The originality of this study is in the recognition of asset management as a valuable asset for firms that have integrated Information technologies & sustainability practices, as it promotes improved operational performance of projects, and there is still rarely any previous research that examines sustainability practices and asset management, especially mining projects. This research contributes to developing the resource-based view (RBV) theory and also contributes managerially to the practices that mining contractors must carry out when dealing with uncertain business situations.

Coal mining is a very important sector in Indonesia, but there has been a decline in the realization of coal production in recent years, so this can reduce state revenues. One of the big challenges in the mining sector is the uncertainty of the mining business, such as information technology and sustainability concerns, that affect the mining industry's supply chain procedure. The purpose of this examination is to identify and determine the performance of supply chain resilience in the face of business uncertainty by determining the function of IT capabilities and sustainability practices in coal mining contractors. This research was conducted using a quantitative research method approach that was carried out using a structured survey instrument. The methodology employed in this study is built on purposive sampling, which is a non-probability selection method. The researchers used the Structural Equation Model (SEM) to examine data that were gathered from a sample of 128 project managers of coal mining contractors in Indonesia. The findings of this study demonstrated that project operational performance was significantly and favorably impacted by supply chain resilience. Additionally, a major and advantageous mediating IT skill in the operational execution of projects is supply chain resilience. Furthermore, it was shown that the use of IT capacity and the implementation of sustainability practices had a noteworthy and favorable influence on enhancing the performance of mining contractor projects. This research also provides information that environmental dynamism does not significantly moderate supply chain resilience on mining project performance. The novelty of this research is the contribution of supply chain resilience as an important resource for organizations that are integrated with IT capabilities to encourage increased project operational performance, especially for coal mining contractors. Additionally, research is still rarely carried out in between sustainability practices and supply chain resilience in the mining sector. It is concluded that coal mining contractor projects need to build supply chain resilience at the site amidst the uncertainty of the coal mining business.

Slow fashion is a new movement in the textile industry, where slow production mode and more ethical business processes are highly considered. This movement is an alternative to buying fast fashion productsto achieve a sustainable pattern. The theory of planned behavior also includes attitudes, subjective norms, and perceived behavior control, which are commonly used to analyze the patterns of green attitudinal variables through other additional principles, namelythe willingness to pay a premium, consumer effectiveness, and environmental knowledge. Therefore, this study analyzed factors influencing purchase intention of slow-fashion products. In this analysis, a randomized questionnaire was implemented and distributed to 140 Generation Z people in West Java Province, Indonesia. Structural equation modelingwas also used to test the fit model and path analysis of attitudes mediating green products knowledge on the intensity of buying slow-fashion products. The results showed that the three main variables of TPB and other influential/significant expanding principles were observed, except consumers' perceived effectiveness did not affect purchase intention. The limitations also prioritized the need for more experimental loci capable of being developed at different points. Moreover, the results obtained were beneficial for both academic and managerial purposes. This proved that green product purchasing behavior analysis needs to be academically improved, specifically for slow-fashion in developing countries. Managerial suggestions also increased green knowledge of fashion products through descriptive analysis. These suggestions enhanced consumers' understanding of the effective reduction of textile waste by purchasing fashion products.

Manufacturing companies constantly strive to build sustainable performance to survive fierce business competition. Besides, the company should be committed to protecting the environment by paying attention to the role of supply chain members. Companies should collaborate with external partners, enabling them to fulfill customers' needs for environmentally friendly products. This study explores the effect of green supply chain management on operational performance with the mediating role of information technology infrastructure, internal integration, and external integration. This study surveyed manufacturing companies in Indonesia using structured questionnaires designed with a five-point Likert scale. The questionnaire is designed using Google Forms, and the links are distributed to respondents through email, WhatsApp, and other social media. As many as 245 responses were obtained and valid for analysis. The data processing used SmartPLS software version 4.0. The hypothesis test results found that green supply chain management influences information technology infrastructure, internal integration, external integration, and operational performance. Information technology infrastructure impacts improving internal integration, external integration, and operational performance. Internal integration has an impact on external integration and operational performance. External integration has an impact on improving operational performance. The research contributes to managerial practice by adopting the ISO 14001 standard in green supply chain management. for companies to make improvements. These findings also enrich the current research in supply chain management theories.

In the dynamic landscape of contemporary business, achieving entrepreneurial resilience is an important goal for organizations facing unprecedented challenges. This study investigates the complex interactions between ambidextrous leadership, entrepreneurial mindfulness, and the mediating mechanisms of business model innovation capacity in fostering entrepreneurial resilience. This research uses a quantitative approach with the population of the startup community in Indonesia. A sample of 340 startup actors was selected randomly. Data was collected via a Likert Scale questionnaire with a scale range of 1-6. Hypothesis testing was carried out using Structural Equation Modeling (SEM) Partial Least Squares (PLS) to overcome model complexity and small sample size. Findings support the relationship between entrepreneurial alertness, ambidextrous leadership, business model innovation capacity, and entrepreneurial resilience. The theoretical implications enrich the literature by introducing mediating variables and leading to the development of a more comprehensive theoretical model. The practical implications highlight the importance of leadership development and business innovation to improve adaptation and response to change. Policy implications emphasize the need for policy support to strengthen entrepreneurship and innovation in the national economy.