Analysis of Linkages between Logistics Information Systems and Logistics Performance Management under Uncertainty

Logistics performance management has received more attention by government and organizations in recent years as it becomes the critical success factor of the supply chain. The study of logistics performance management in this paper aims to analyze dimensions and relevant factors of logistics information system (LIS) usage that affects logistics performance management under uncertainty. A survey was conducted on distribution activity and applied Technology Acceptance Model to extrapolate the intention to use LIS. Exploratory factor analysis and ANOVA were employed to examine the association among the dimensions that influent on LIS usage. A case study was taken from a large household product firm whose business survival depended on logistics performance. We analyzed various logistics activities to determine the associativity among these activities. As such, related linkages can be established for subsequent logistics performance monitor and improvement. Summary of findings and future work are reported. Keywords: Logistics information systems; Logistics performance management; Uncertainty management; Technology acceptance model

Innovative Logistics Management under Uncertainty using Markov Model

This paper proposes an innovative uncertainty management using a stochastic model to formulate logistics network starting from order processing, purchasing, inventory management, transportation, and reverse logistics activities. As this activity chain fits well with Markov process, we exploit the very principle to represent not only the transition among various activities, but also the inherent uncertainty that has plagued logistics activities across the board. The logistics network model is thus designed to support logistics management by retrieving and analyzing logistics performance in a timely and cost effective manner. The application of information technology entails this network to become a Markovian information model that is stochastically predictable and flexibly manageable. A case study is presented to highlight the significance of the model. Keywords: Logistics network; Markov process; Risk management; Uncertainty management

Effects of Recycled Polyethylene on Natural Rubber Composite Blends Filled with Aluminum Trihydroxide and Polyurethane Waste: Mechanical and Dynamic Mechanical Properties, Flammability

This research studies natural rubber (NR) composite blends prepared with recycled polyethylene (PE), polyurethane waste (PU), silica (SiO2), and aluminum trihydroxide (ATH) under the proper mixing conditions using an internal mixer and a two-roll mill. The mechanical, impact, dynamic mechanical, and thermal properties, together with flammability, were investigated. NR/PU composites filled with a specific SiO2/ATH concentration resulted in excellent flame-retardant properties without using PE. Adding PE causes poor flammability, while using PU and SiO2 prevents flame extensibility of the composites. In addition, SiO2 and ATH synergistically improved both mechanical and dynamical mechanical properties. This is attributed to the reinforcement of SiO2 particles inside the matrix, whereas the ATH releases water as a flame retardant. The V-0 composites tested with UL-94 showed acceptable heat resistance, strength, and durability, making them suitable for interior and exterior applications in buildings without the lightweight requirement