A Monte-Carlo approach to estimating the effects of selected airport capacity options in London

The issue of future airport capacity in London is currently the subject of much political debate in the UK. Although realistic estimates of the effects of capacity enhancement may be desirable, such estimates are difficult. Through the use of Monte Carlo simulation, this paper quantifies and compares the relative capacity enhancements that may be afforded by the construction of a new hub airport in the Thames Estuary, additional runways at Heathrow, Gatwick and Stansted and changes to operating practices at Heathrow. The simulations show that a new hub airport would be the most effective way to increase capacity, although the reported financial and environmental costs of such a development indicate a comparatively poor rate of return. Proposed new runways at Heathrow, Gatwick and Stansted and the removal of runway alternation at Heathrow provide more modest increases in capacity.     

Managing security risks for inter-organisational information systems: a multiagent collaborative model

Information sharing across organisations is critical to effectively managing the security risks of inter-organisational information systems. Nevertheless, few previous studies on information systems security have focused on inter-organisational information sharing, and none have studied the sharing of inferred beliefs versus factual observations. In this article, a multiagent collaborative model (MACM) is proposed as a practical solution to assess the risk level of each allied organisation’s information system and support proactive security treatment by sharing beliefs on event probabilities as well as factual observations. In MACM, for each allied organisation’s information system, we design four types of agents: inspection agent, analysis agent, control agent, and communication agent. By sharing soft findings (beliefs) in addition to hard findings (factual observations) among the organisations, each organisation’s analysis agent is capable of dynamically predicting its security risk level using a Bayesian network. A real-world implementation illustrates how our model can be used to manage security risks in distributed information systems and that sharing soft findings leads to lower expected loss from security risks.     

面向能力培养的男装课程教学方法

本文以温州大学服装设计与工程专业为例,以温州大学人才培养模式创新实验区为依托,结合温州男装人才市场的实际需求,提出了面向能力培养的服装类院校男装课程体系教学改革方法。针对男装课程的具体特点和要求,在分析授课内容,总结实践教学经验的基础上,提出以课程项目为驱动,开展专项性与综合性相结合的教学设计,以此提升学生的学习兴趣,提升学生对男装的设计整合能力。     

Assessment of land use compatibility and noise pollution at Imam Khomeini International Airport

This study aimed to investigate land use planning around airports, by employing Remote Sensing (RS) and Geographic Information Systems (GIS), in conjunction with an optimization algorithm using an Integrated Noise Model (INM) software, to establish the potential effects of aircraft noise at Imam Khomeini International Airport (IKIA) in Tehran. We also checked for land use compatibility with the noise levels around IKIA and the residents' reaction to the noise. The research was carried out in three stages: a) the establishment of Strategic Noise Map (SNM) scenarios of the airport operation in the years 2011, 2020 and 2030 using the INM software; b) the assessment of the results with emphasis on the study area land uses and application of RS and GIS and the exposure of residents at different levels of environmental noise; and c) the assessment of the intensity of aircraft noise annoyance at various times of day and night. The results indicated that developing IKIA together with the residential development will increase airport noise. Hence proper management and control of noise at IKIA is essential.     

Design and development of inventory knowledge discovery system

Inventory management (IM) performance is affected by the forecasting accuracy of both demand and supply. In this paper, an inventory knowledge discovery system (IKDS) is designed and developed to forecast and acquire knowledge among variables for demand forecasting. In IKDS, the TREes PArroting Networks (TREPAN) algorithm is used to extract knowledge from trained networks in the form of decision trees which can be used to understand previously unknown relationships between the input variables so as to improve the forecasting performance for IM. The experimental results show that the forecasting accuracy using TREPAN is superior to traditional methods like moving average and autoregressive integrated moving average. In addition, the knowledge extracted from IKDS is represented in a comprehensible way and can be used to facilitate human decision-making.     

Has market concentration fostered on-time performance? A case study of seventy-two U.S. airports

The study compares a multivariate with a quantile regression model to determine whether utilized airport capacity, departure and airborne delays, departure and arrival demand, and market structure explained variations in on-time gate arrivals and arrival delays. In both models, airport departure delays, arrival and departure demand explained variations in the two response variables in prioritized and non-prioritized metroplexes, holding other variables constant. After 2008, the consolidation of the airline industry through mergers coincided with the implementation of NextGen programs, which may have contributed to improvements in on-time performance, especially at prioritized metroplexes where airspace was redesigned.     

Education Dashboards for Enhanced Learning: A Singapore Experience

Educators continue to utilize add-ons, extensions, or replacements to traditional Learning Management Systems (LMSs) to supplement capabilities and improve the classroom experience. This work resulted in the design and development of the Education Dashboards for Enhanced Learning (EDEL) template. The EDEL template enables faculty members to create dynamic web spaces called Knowledge Portals (KPortals). A semester-long introduction of KPortals proved to be positive and useful. Students tended to view the KPortal as a “go-to” webspace. The authors hope to refine the template in future studies and examine its usefulness in other countries.     

An estimation of returns to scale of airport airsides under multiple optimal solutions in DEA

The returns to scale (RTS) nature of 37 Chinese airport airsides are investigated in this paper. Multiple optimal solutions in DEA (Data Envelopment Analysis) models may lead to error RTS estimation. To address this problem, we use the (Zhu and Shen, 1995) RTS method. The empirical study shows that all those airsides with two runways operate under decreasing RTS and those airsides with only one runway either operate in the area of increasing RTS or in the area of constant RTS.     

The impact of IT-enabled customer service systems on service personalization,customer service perceptions,and hotel performance

Customer service is a critical element of a hotel's strategy and an important lever for differentiation of the hotel's offer. Over the last two decades, information systems have contributed to the transformation of customer interactions, enabling an unprecedented scale and scope of service personalization in the tourism industry. This paper reports the results of a mixed method study in a hotel that offers three contributions to the development and refinement of IT-enabled service personalization theory. It explores the role of signifiers in the design of customer service systems, showing that they significantly increase customer preference elicitation during the learning phase of the service personalization process. It then demonstrates that improved preference elicitation translates into higher customer service evaluations and value perceptions of the hotel. Finally, our study shows that IT-enabled service personalization creates financial benefits for the hotel via revenue share-shift from costly intermediated to direct distribution channels.