The increasing damages and losses bring requests to improve coping capacities for extreme conditions on the identification of and improvement to socioeconomic vulnerabilities. Disruptions to critical infrastructure (CI) influence the capacities for resilience and sustainable daily operations both directly and by causing failures in one system that in turn affects other systems. Among the transportation systems widely identified as national CI that should be protected, ports provide substantial employment, industrial activity, along with national and regional development. This study thus examines the vulnerability of port failures from an interdependency perspective. Fourteen vulnerable factors are developed by literatures as well as in-depth interviews. Four international commercial ports in Taiwan are employed as empirical cases to evaluate port vulnerability through semi-quantitatively systematic methods, including fuzzy cognitive maps and sensitivity model, while geographic information systems are used to clarify the spatial-functional interdependency. In addition to the underestimated vulnerability because of omitted interdependency, analytical results reveal that capacity and efficiency significantly affect port vulnerability. Increasing local cargo bases and co-opetition are suggested to improve the port vulnerability. The proposed assessment framework helps decision-makers understand the interdependent vulnerabilities and adopt appropriate strategies for the mitigation of losses.

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Purpose The increasing demand for high-quality logistics services has forced container shipping firms to decrease logistics service failure to retain the customers. This study thus aims to apply organizational information processing theory (OIPT) to construct a maritime supply chain collaborative decision-making model and examine its impact on logistics service performance. Design/methodology/approach In total, 142 usable questionnaires were collected from questionnaire survey. A two-step structural equation modeling approach including confirmatory factor analysis was subsequently performed to test the hypotheses. Findings The results show that internal information integration positively impacts external information integration, that external information integration positively impacts collaborative decision-making, and that collaborative decision-making positively impacts logistics service performance for container shipping firms. However, a relationship between internal information integration and collaborative decision-making was not found in this study. Research limitations/implications This study primarily examines collaborative decision-making from the view of container shipping firms. Future research including other supply chain members is needed to generalize the results and could also incorporate other factors such as relationship quality and culture, into the model to address this issue. Practical implications To decrease the occurrence of logistics failures and improve service quality in the maritime logistics process, it is suggested that container shipping firms apply information technology for acquiring and assimilating logistics information internally and externally across the supply chain to facilitate decision-making. Originality/value This study contributes to the knowledge about the antecedents and impacts of collaborative decision-making for container shipping firms in Taiwan. Particularly, in line with OITP, the findings indicate that container shipping firms can facilitate logistics decision-making and strategy formulation through information integration, which in turn enhances logistics service performance.

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Recently Web sites have been providing users with services in accordance with their preference data. In addition to such configuration services, notification services, which process jobs in response to events which occurred at a server in the users' absence, and asynchronous services, which perform jobs after users submit requests, are also available. An agent server architecture which manages users' agents on the server side is proposed for developing systems which provide such services. Such agent servers must be able to sustain high performance. In this paper, we demonstrate that the agent server approach can achieve higher performance than an existing approach which uses DBMS. Also, we describe the performance characteristics of the agent server.

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There are many studies on ABS and several frameworks for ABS have already been published. However, there are few frameworks that can enable agent-based simulation using large numbers of agents. We have been developing a Java-based platform for Massive Agent-Based Simulation (MABS) called "Zillions of Agents-based Simulation Environment" or ZASE. The purpose of ZASE is to develop MABS applications on multiple computers. ZASE is designed to host over millions of agents. We introduce ZASE in this paper. We evaluated ZASE for the agent-based auction simulation where the number of agents varied from ten to a million. The results indicate that the number of agents affects the final bid prices and their distributions. Performance measurement results on both an SMP computer environment and a multiple-computer environment are shown.