Supply Chain Sustainability as a Mediator of Sustainable Performance in Indonesian Logistics SMEs

This study investigates supply chain sustainability as a mediating mechanism transforming organizational antecedents into sustainable performance outcomes among Indonesian logistics small and medium enterprises (SMEs). Drawing on stakeholder theory and resource-based view, we develop and test a mediation model using data from 284 Indonesian logistics SMEs across five geographic regions. Partial least squares structural equation modeling with 5,000 bootstrap resamples examines relationships between top management commitment, technology investment, human employee engagement, supply chain sustainability, and sustainable performance. Results reveal complete mediation patterns where supply chain sustainability fully mediates relationships between organizational antecedents and sustainable performance

Determinants of Parcel Locker Adoption in Last-Mile Delivery with Emphasis on Logistics Value, Consumer Orientation, Value Co-Creation, and Green Awareness

This study aims to identify the key factors that influence consumers' intention to adopt parcel locker services in last-mile delivery, using Service-Dominant Logic to explain how value is created between consumers and service providers. The research was conducted in Jakarta using a quantitative approach. Data were collected from 412 e-commerce users through a structured survey using stratified random sampling across five administrative cities. The Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with appropriate statistical software. The study concludes that consumer adoption of parcel lockers depends more on collaborative experiences and personalized interactions than on environmental concerns. Value Co-Creation plays a central role as the main pathway driving adoption

Assessing the Impact of Multilane Free Flow on Vehicle Operating Costs and Logistics Efficiency in Indonesia Using SWOT Analysis Approach

Indonesia’s logistics sector faces high costs and inefficiencies due to toll road congestion and delays. Multilane Free Flow (MLFF) offers a solution by enabling seamless toll transactions that can reduce delays and costs. Using a SWOT framework, with RBV and Institutional Theory, this study assesses MLFF’s impact. It highlights MLFF’s strengths in efficiency, lower VOC, safety, and environmental benefits. Challenges include technological accuracy, financial viability, user acceptance, and fragmented regulations. Public support offers opportunities for adoption, but implementation needs regulatory reform, infrastructure upgrades, and stakeholder collaboration. MLFF could reduce logistics costs and enhance competitiveness, but success depends on overcoming hurdles through coordinated efforts

Analysis of the Effect of Indonesia-Japan Economic Partnership Agreement (IJEPA) on the Trade in Service Sector in Indonesia

The Economic Partnership Agreement (EPA) is a trade agreement that aims to facilitate market access and considers aspects of economic cooperation and development initiatives between the two countries. The trade agreement between Indonesia and Japan is Indonesia's first bilateral trade agreement covering trade in goods, services, and investment, and entered into force in 2008. The development of the service sector is an important factor in supporting economic growth. This study uses panel data regression with the estimation method used by the gravity model with Difference in Difference (DiD) to see the impact of the IJEPA. The study results show that the interest variable is not significant to the dependent variable, illustrating that the existence of the IJEPA agreement is statistically unable to explain the relationship that occurs with the value of exports and imports of the Indonesian service sector. Implementing IJEPA in Indonesia still does not have an impact and has not provided benefits, especially for service trade

Supply Chain Optimization of Industrial Machinery Projects Based on Artificial Neural Networks for Multi-Product Demand Forecasting

Fluctuating demand and diverse products pose significant challenges for supply chain management in manufacturing, leading to production disruptions and increased costs. This study aims to optimize the supply chain of the industrial machinery sector through demand forecasting with artificial neural networks (ANN). Demand data covering 24 months for three products—water tanks, mixer machines, and conveyors—were analyzed using time series clustering based on autocorrelation and complete linkage. Stationarity was tested using the Augmented Dickey-Fuller (ADF) and Box-Cox transformation prior to modeling. The ANN was trained with a learning rate of 0.001, 20 hidden neurons, and PACF-based lag inputs. Results showed that cluster one achieved a MAPE below 30%, indicating strong predictive accuracy, while cluster two achieved a MAPE below 50%, considered acceptable. Predictions for the 25th month from cluster one are recommended for inventory planning. The study demonstrates that ANN-based forecasting effectively supports decision-making and enhances supply chain optimization in multi-product manufacturing

Improving Perfect Order Fulfillment in Textile SMEs with Open-Source ERP Odoo Implementation Based on the SCOR Model

SMEs often struggle with manufacturing efficiency and inventory management, hindering their ability to meet customer demands. ERP systems can integrate data to improve planning and decision-making but must align with SCOR principles to ensure holistic digital transformation. This study examines CV. PJ, a textile SME in Bandung operating across three locations to process yarn into raw material and then into dyed fabric. Problem identification was carried out using qualitative methods employing surveys and interviews and also quantitative methods to analyze sales data. A gap analysis revealed two primary issues that include plan and make. The plan component aims to enhance customer fulfillment planning accuracy through demand forecasting, while the make component focuses on production efficiency. To address these issues, the open-source ERP system Odoo, with modules for finance, manufacturing, inventory, sales, and purchasing, was implemented to streamline six main processes. The system effectively recorded data and generated reports, enabling SCOR-aligned decision-making. After six months, the implementation achieved an average perfect order fulfilment rate of 87.5%, categorized as excellent. This study highlights how SCOR-based ERP Odoo implementation enhances scheduling and product movement efficiency, significantly improving operational reliability and customer satisfaction

Optimization Disaster Logistics by Determining the Optimal Location and Number of Evacuation Centers

Indonesia, particularly Bandung Regency, faces significant flood risks that disrupt livelihoods and damage infrastructure. This study identifies the optimal locations and number of evacuation centers using the Set Covering Problem (SCP) model, integrating geographic data, population density, accessibility, and infrastructure capacity. The study applied constraints including a 1,000-meter maximum service distance, minimum road width of 6 meters for Class IIIB and IIIC access, shelter capacity limits, and full coverage of demand points. Using ArcGIS 10.2.1, candidate locations were evaluated by overlaying flood vulnerability maps with accessibility and facility data. Environmental sustainability was addressed by selecting sites with minimal ecological disruption, avoiding sensitive zones, and reusing existing structures to reduce land conversion. Results show that five centralized shelters in high-density, well-connected areas can cut evacuation travel time by up to 20% compared to dispersed locations. This integrated approach improves response efficiency, ensures access for vulnerable populations, and supports sustainable site planning. The findings contribute to disaster logistics theory and offer practical, replicable guidance for policy in other flood-prone regions

Enhancing MSME Competitiveness In The Creative Industry Through Human Resources Development In South Tangerang

This study aims to determine the strategy to increase the competitiveness of creative industry MSMEs in the digital era through human resource development in the creative industry, especially the Wood Processing Industry in South Tangerang. Findings reveal that HR development especially in digital skills training such as product design, online marketing, and online store management combined with the integration of technology into production processes, significantly improves efficiency, productivity, and market reach. Social media platforms, particularly WhatsApp, Instagram, and TikTok, are essential tools for marketing and customer engagement. The study contributes to the literature by providing an applied framework for enhancing MSME competitiveness through targeted HR capacity building and digital adaptation strategies. This study concludes that although there have been efforts to take advantage of digital opportunities, there is still room for further development in the use of technology and more effective online marketing strategies

An Empirical Analysis Of The Impact Of Human Resource Management, Logistic Warehouse, And Production Planning On Company Performance In The Manufacturing Industry

This study aims to analyze the Factors Affecting Company Performance Through Human Resource Management, Logistics Warehouse, and Production Planning in the Manufacturing Industry in Indonesia. Data were collected through a survey involving 150 employees from several manufacturing industry companies in Indonesia. The results of the study indicate that the Human Resource Management variable has a negative and significant effect on employee performance, Warehouse Logistics, and Production Planning has a positive and significant effect on company performance. The findings reveal that HRM has a negative and significant effect on employee performance, indicating potential issues in HR policies, practices, or implementation that may hinder workforce productivity. These results highlight the importance of reviewing HRM strategies while strengthening logistics and production systems to achieve sustainable performance in the manufacturing sector

The Impact Of International Trade On Human Resource Development In Indonesia

This study aims to analyze the impact of international trade on human resource development (HRD) in Indonesia by focusing on the variables of international trade (X1), trade openness (X2), HR quality (Y1), HR development (Y2), and the moderating variable of HR adaptability (Z). Data were collected from 200 respondents including business actors, workers, and stakeholders in the trade and HRD development sectors. The influence model between variables was tested using Smart PLS 3.0 to identify the relationship between international trade and trade openness on HR quality and development. The results of the study indicate that international trade (X1) and trade openness (X2) have a significant effect on the quality of human resources (Y1), but international trade does not affect human resource development (Y2). The variable of human resource adaptability (Z) is able to mediate These findings indicate that increasing international trade activities and trade openness policies can improve workforce competence through investment in education, training, and technology