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The impact of COVID-19 measures on airport performance is obvious, and there have been numerous studies on this topic. However, most of these studies discuss prevention measures, the effects on airport operations, forecasts of economic impacts, changes in service quality, etc. There is a lack of research on the effects of various prevention measures on airport operations and the interrelationships between these measures. This study focuses on addressing this gap. In this study, an integrated approach is devised that combines the decision-making trial and evaluation laboratory (DEMATEL) method and interpretive structural modeling (ISM). This integrated method is useful for exploring the relationship between pandemic measures and airport performance as well as the complex relationship between them, and the combination of methods improves upon the shortcomings of the original models. This study reveals that mandating vaccination certificates for entry into a country is the most significant measure affecting airport performance. Additionally, aircraft movement at the airport has the greatest overall impact and can be considered the most crucial factor influencing airport performance from an operational standpoint. The findings show that both factors directly influence financial performance, as reflected in the net income. Some management implications are provided to mitigate the consequences of the measures taken to counter the pandemic crisis. This integrated approach should also assist authorities and policy-makers in planning cautious action for future crises. [ABSTRACT FROM AUTHOR]

Improving people's willingness to ride bicycles has become the main green transportation policy of the government in the world. Bikeability is an important factor affecting the willingness to ride. Since the urban riding environment is more complex than the suburbs, it is necessary to establish a complete urban bikeability evaluation framework. This study applies Bayesian BWM (Best Worst Method) and modified VIKOR to develop an urban bikeability evaluation framework. First, this study collects criteria affecting urban bikeability through literature review and experts' surveys to develop a novel evaluation framework. Second, the Bayesian BWM was used to evaluate the relative weights of criteria and dimensions. Finally, the modified VIKOR was used to evaluate the riding environment of urban bicycle systems. The modified VIKOR replaces the relatively good concept as the aspiration level, which can effectively reflect the real situation. This study used two cities of Taiwan as case studies to demonstrate the usefulness and effectiveness of the proposed model. The results show that "completeness of facilities" is the most important dimension and "maintenance of bicycle pavements", "width of bicycle lanes", and "separation of bicycle lanes and car lanes" are the critical criteria. Based on the findings, some management implications and improving strategies are provided. [ABSTRACT FROM AUTHOR]

Abstract Cycling as a mode of transportation brings certain benefits to the user, such as improving health and saving money. It can provide a significant improvement in the quality of city life with minimal ecological impact. Thus, public bike-sharing systems have been adopted as a modal choice in many cities world-wide. However, there are some problems that must be addressed when designing a bike-sharing system, one of which is how to improve service quality and attract more users. This study proposes a hybrid model, combining the Decision-Making Trial and Evaluation Laboratory (DEMATAL) method with the Analytical Network Process (ANP) approach (called DANP), which addresses the dependent relationships between the various criteria for the quality of service for bike-sharing systems to better reflect the real-world situation. After building a complex evaluation system, a modified VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method is applied to explore the weighted-gap to the aspiration levels. Furthermore, given the vagaries of human judgments and ratings, preferences cannot be assigned an exact numerical value, which can make it difficult to evaluate the performance or make comparisons. One way to improve upon this uncertainty is to apply Grey Theory. The proposed method is then applied using data for Taipei's Youbike and Obike systems. The analytical results and the resultant managerial applications for improving the service quality of both bike-sharing systems are also discussed with particular attention to the current policies of Taipei City. Highlights • We propose a model to evaluate and improve the service quality of public bike-sharing systems. • The model addresses the dependent relationships among various criteria and information uncertainty. • Our results indicated the infrastructure is the causal factor and safety has the largest gap for improvement. • Results are discussed with regards to the current policies of Taipei City. [ABSTRACT FROM AUTHOR]

There are several factors that need to be considered in fleet management when it is necessary to resolve disturbances which necessitate aircraft re-assignment due to flight cancellations, making this a multiple-criteria decision-making problem. A change in the type of aircraft assigned can lead to additional alterations as well as directly affecting connecting flights and interconnected schedules serving specific flight segments. Decision-making is crucial and involves the consideration of complex cost effects, with possible disruptive actions evaluated according to the priorities of airline management and the available resources. Airline managers require a practical and flexible tool to help them make appropriate decisions in a rapidly changing and highly competitive environment. Differing from prior studies using mathematical programming, we propose a hybrid model based on the decision-making trial and evaluation laboratory method and the concepts of analytic network process (DANP) to aid in the decision-making process. We also recommend using the VIKOR method to select the most appropriate alternatives, with the corresponding weights obtained using the DANP method. The efficiency and effectiveness of the proposed method is demonstrated by testing it on a real-world flight cancellation case and in consultation with experts. The results show that this hybrid model is an effective resource that airline managers can use to address and resolve aircraft re-assignment irregularities. [ABSTRACT FROM AUTHOR]

This study differs from previous studies by applying multivariate statistical analysis and multi-criterion decision-making methods to the improvement of service quality. We use the rough set theory (RST) with a flow graph approach to determine customer attitudes regarding service quality, which can assist managers in developing strategies to improve service quality and thus satisfy the needs of customers. A set of rules is derived from a large sample of airline customers, and its predictive ability is evaluated. The flow graph and the cause-and-effect relationship of the decision rules are heavily exploited in service quality characteristics. As compared with the results of other data-mining analyses, our results are encouraging. This study demonstrates that the combination of the RST model and flow graphs assists in identifying the needs of customers, determining their characteristics, and facilitating the development of an improvement strategy. [ABSTRACT FROM PUBLISHER]

This is a forward-looking approach that uses a multiple-criteria decision analysis (MCDA) model as an assessment tool for risk identification. This study proposes an indifference threshold-based attribute ratio analysis and technique for order preference by similarity to an ideal solution (ITARA-TOPSIS)-based assessment model to identify critical failure modes in products and systems. The improved indifference threshold-based attribute ratio analysis (ITARA) method can generate more reliable weights for risk factors. In addition, the modified technique for order preference by similarity to an ideal solution (TOPSIS) is used to obtain the risk levels of the failure modes. The gray correlation coefficient is applied to replace the conventional Euclidean distance, and a new index is used to determine the priority of failure modes. The determination of risk factors is based on the failure mode and effect analysis (FMEA) theory, including severity, occurrence, and detection. An important indicator, the expected cost, is also included in the framework. The case of a steam turbine for a nuclear power plant is used to demonstrate the approach, and the analysis results show that the proposed model is practical and effective. Moreover, the advantages of our integrated model are illustrated through model comparisons and sensitivity analysis. This paper can help decision-makers, risk engineers, and related researchers to better understand how a systematic risk assessment can be conducted. [ABSTRACT FROM AUTHOR]