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This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

It is demonstrated how an analysis of airports’ cost structures and the calculation of long-run marginal costs (MCs) of serving passengers and airplanes can be used as a basis for setting airport charges according to the principles of welfare economics. Based on Norwegian data, the MC for an extra passenger (PAX) and extra air traffic movement (ATM) are used to set airport charges under the assumption that the charges should be equal for all airports in the country. When adjusting the estimates to meet revenue restrictions and comparing the estimates to current charges, we observe that PAX should be charged more and ATM less. This finding is in line with recommendations from the International Air Transport Association (IATA). When allowing charges to vary between airports, we demonstrate how a Ramsey pricing approach can be applied to set differentiated PAX and ATM charges, considering both the supply side (the competitive conditions between the airlines operating at the airports) and the demand side (the passengers’ price elasticity of demand).

In this chapter, an air cargo shipment planning problem is considered by including individual risk factors of any sub-contracted agents. Due to competitive market conditions, air cargo forwarders are advised to remain flexible in operations. A mixed integer linear programming formulation including the potential for divisible activities is developed to model the shipment planning problem. To solve this complicated problem, we employ an ant colony optimization (ACO) methodology. Numerical examples are generated using data from both the extant literature and from a global air cargo company, allowing investigation of the viability of the novel methodology. We find that the algorithm/methodology provides effective solutions for small problem sizes.

This paper explores dividend announcements based on information hypothesis. We explore in particular whether or not information signaling theory existed in Taiwan. We also explore the free cash flow hypothesis. In order to eliminate affecting factors, we target companies with irregular dividends as research samples, just like those with specially designated dividends (SDD). We examine whether or not those proceeds may be deemed as future earnings prospection. In this paper we study mainly dividend announcements made during stockholder’s meetings of the companies listed in the Taiwan Stock Exchange (TSE) or R.O.C. Over-the-Counter Securities Exchange (ROSE). We apply event study as means of analyzing abnormal returns of the companies. In addition we use the GARCH model with traditional ordinary least square to estimate the market model. The results indicate that SDDs are considered positive signals by the national exchange, TSE. In addition, we also show that the first-time SDD does transmit a positive signal to the market regarding the firm’s future cash flow, and that the SDD of no payment in the previous three years is negative. Furthermore, we prove that low Q firms have greater market reaction than high Q firms in announcement period. The free cash flow hypothesis and firm size effects could not be verified in Taiwan.

This chapter is an up-to-date survey of the state-of-the art in consumer demand analysis. We review (and evaluate) advances in a number of related areas, in the spirit of the recent survey paper by Barnett and Serletis (2008). In doing so, we only deal with consumer choice in a static framework, ignoring a number of important issues, such as, the effects of demographic or other variables that affect demand, welfare comparisons across households (equivalence scales), and the many issues concerning aggregation across consumers.

Although in principle prior information can significantly improve inference, incorporating incorrect prior information will bias the estimates of any inferential analysis. This fact deters many scientists from incorporating prior information into their inferential analyses. In the natural sciences, where experiments are more regularly conducted, and can be combined with other relevant information, prior information is often used in inferential analysis, despite it being sometimes nontrivial to specify what that information is and how to quantify that information. In the social sciences, however, prior information is often hard to come by and very hard to justify or validate. We review a number of ways to construct such information. This information emerges naturally, either from fundamental properties and characteristics of the systems studied or from logical reasoning about the problems being analyzed. Borrowing from concepts and philosophical reasoning used in the natural sciences, and within an info-metrics framework, we discuss three different, yet complimentary, approaches for constructing prior information, with an application to the social sciences.