A logistics service company in Batam faces challenges related to warehouse load fulfillment and sorting inaccuracies. This study aims to identify proposed efficiency improvements to the goods distribution system using the cross-docking method. The research method chosen is cross-docking, a technique that eliminates the storage process in the warehouse, thus saving time and cost. The research findings show significant benefits, especially in achieving zero inventory efficiency. Data processing and discussion revealed that efficiencies were apparent by increasing the sorting tables from 1 to 6, with an output of 90,000 kg during aircraft loading and unloading (compared to approximately 77,000 kilograms). This efficiency arises from the larger output of the sorting tables compared to the input, eliminating the need for warehousing and adding ten trucks. As a result, the shipment can be completed in one trip, with no goods stored in the warehouse. The analysis shows that implementing cross-docking in the company increases efficiency in distributing goods to forwarding partners.

This research examines the interplay between human dignity and the pursuit of knowledge within Islamic thought, using insights from the Quran. It explores how Islamic epistemology emphasizes the harmonious integration of divine revelation and human reason, underscoring the importance of knowledge as a key factor in both intellectual and spiritual development. By analyzing the contributions of classical Islamic scholars, such as Al-Farabi, Ibn Sina, and Al-Ghazali, alongside Western epistemological traditions, the study highlights complementary and contrasting approaches to understanding knowledge and its role in shaping ethics and governance. Furthermore, the research draws on contemporary case studies, such as the Marrakesh Declaration and Masdar City, to illustrate how Quranic principles of cooperation, justice, and environmental stewardship can inform modern societal frameworks. Ultimately, the study argues for the continued relevance of Islamic thought in addressing contemporary global challenges, emphasizing that the pursuit of knowledge not only advances scientific discovery but also promotes human dignity, justice, and societal well-being.

Given the issues of urban-rural educational inequality and difficulties for children from poor families to succeed, this study explores the impact mechanism of internet usage on rural educational investment in China within the context of the digital divide. Using data from the 2019 China Household Finance Survey (CHFS), this study analyzed the educational investment decisions of 2064 rural households. Results indicate that in the Eastern region, a high level of educational investment is primarily influenced by the per capita income of the family, with social capital and internet usage also playing supportive roles. In the Northeastern region, the key factor is the diversity of internet usage, specifically using both a smartphone and a computer. In the Central region, factors such as the diversity of internet usage, subjective risk attitudes, the appropriate age of the household head, and per capita income of the family contribute to higher levels of educational investment. In the Western region, the dominant factors are the diversity of internet usage, subjective usage and per capita income of the family. These factors enhance expected returns on the high level of educational investment and boost farmers’ confidence. High internet usage rates significantly promote diverse and stable educational investment decisions, providing evidence for policymakers to bridge the urban-rural education gap.

This research aims to delineate the ecocity indicators from the local perspectives in urban communities in the Northeast of Thailand. The research was quantitative survey research. Data was collected from a sample of 400 people who live in Khon Kaen Municipality and Udon Thani Municipality using a questionnaire. Data was analyzed by descriptive statistics and factor analysis. We found that the eco-city indicators from the perspective of people in the urban communities in the Northeast of Thailand were divided into three main criteria: a) economic perspectives; b) social perspectives; and c) environmental perspectives. When considering each aspect, it was found that the economic perspective had a total of 9 issues with an average of 3.06 out of 5.00, the social perspective had a total of 16 issues with an average of 3.76 out of 5.00, and the environmental perspective had a total of 14 issues with an average at 3.00 out of 5.00.

To address the escalating online romance scams within telecom fraud, we developed an Adaptive Random Forest Light Gradient Boosting (ARFLGB)-XGBoost early warning system. Our method involves compiling detailed Online Romance Scams (ORS) incident data into a 24-variable dataset, categorized to analyze feature importance with Random Forest and LightGBM models. An innovative adaptive algorithm, the Adaptive Random Forest Light Gradient Boosting, optimizes these features for integration with XGBoost, enhancing early Online romance scams threat detection. Our model showed significant performance improvements over traditional models, with accuracy gains of 3.9%, a 12.5% increase in precision, recall improvement by 5%, an F1 score increase by 5.6%, and a 5.2% increase in Area Under the Curve (AUC). This research highlights the essential role of advanced fraud detection in preserving communication network integrity, contributing to a stable economy and public safety, with implications for policymakers and industry in advancing secure communication infrastructure.

This research seeks to identify the value of a few common factors determining the speed of economic growth in Baltic states and analyzes their impact in detail on Latvia’s lagging. Latvia’s economic starting point after regaining independence because of the collapse of the Soviet Union was at least comparable to its neighbors. Still, after the implementation of liberal reforms towards a free market’ economy and 20 years of operation as an EU full member, Latvia is lagging in growth, prosperity, and innovation. Within the analysis, this scientific paper pays special attention to the three less discussed factors, namely, the impact of post-Soviet mind-set effects as a part of local innovation culture, lasting since regaining independence in 1991; the importance of the availability of talent pull, its density, diversity, and accessibility; and readiness and capability to capture external knowledge and technology adoption. The overall approach is the systemic assessment of the national innovation system and/or innovation ecosystem, trying to understand the differences between these two models. Research is performed by analysis of the performance of the local innovation ecosystem in connection with export- and Foreign Direct Investment (FDI) policies. The authors present a novel method for visually representing economic growth and its application in analyzing process development within transitional economic nations. The study uses an analytical and synthetical literature review. It offers a new GDP data visualization method useful for monitoring economic development and forecasting potential economic crises—the outcomes from aggregative literature analysis in a consolidated concept are provided for required talent policy proposals. The post-Soviet mindset is seen as a heritage and devious underdog that has left incredibly diverse consequences on today’s society, power structures, economic growth potential, and the emergence of healthy, well-managed, and sustainable innovation ecosystems. The post-Soviet mindset is a seemingly hidden and, at the same time, an intriguing factor that has a significant impact on the desire to make and implement the right decisions related to innovation, education, and other policies promoting business development. The key outcome of the article is that sociocultural aspects and differences in innovation culture led to a slow-down of Latvia’s economic growth compared to Estonia’s and Lithuania’s slightly more successful economic reforms.

Within the last four years, Lithuania has faced different foreign policy challenges due to geopolitical situations such as the Ukraine-Russia war, the migration crisis on the border with Belarus, and the conflict with China. After opening a Taiwanese representative office in Vilnius, China downgraded diplomatic relations with Lithuania. The purpose of the article is to assess the impact of the changes on international economic relations between Lithuania and China. The paper employs descriptive statistics, correlation-regression, sensitivity analysis, and agglomerative hierarchical cluster analysis. The research is based on the impact of international economic relations on international trade by analyzing separately imports and exports. Our research fills a gap in international relations and globalization theory by focusing on international collaboration between small and large countries, while the large country implements economic sanctions. In the context of Lithuania, exports to China and imports from China comprise a small percentage in the structure of international trade. Lithuania’s GDP level reacts sensitively to changes in export and import data only if they change drastically (over 50%).

Global trade is based on coordinated factors, that means labor and products are moved from their point of origin to the point of use. Strategies have a significant impact on global trade because they enable the effective development of goods across international borders. The decision making is an important task for the development of Logistics Supply Chain (LSC) infrastructure and process. Decisions on supplier selection, production schedule, transportation routes, inventory levels, pricing strategies, and other issues need to be made. These decisions may have a big influence on customer service, profitability, operational efficiency, and overall competitiveness. The Artificial Intelligence (AI) approach of Fuzzy Preference Ranking Organization Method for Enrichment Evaluation (Fuzzy-Promethee-2) is used to assess the priority selection of the factors associated with the LSC and evaluate the importance in global trade. The role of AI is very useful compare to statistical analysis in terms of decision making. The computational analysis placed promotion of exports as the most important priority out of five selected attributes in LSC, with infrastructure development. The result suggests that LSC depends heavily on export promotion as the most significant attribute. Infrastructural development also appeared another factor influencing LSC. The foreign investment was ranked the lowest. The evaluated results are useful for the policy makers, supply chain managers and the logistics professionals associated with the supply chain management.