Analyzing air cargo flows of international routes: an empirical study of Taiwan Taoyuan International Airport

Air cargo demand is an important aspect of the operation and planning of private and public agencies responsible for airports. While most existing studies in this field include only geo-economic characteristics of airports and their hinterlands as explanatory variables, this study develops a gravity model of air cargo flows by trying to incorporate more factors that might influence international air cargo flows of an airport. The model is developed based on the panel data of air cargo services on scheduled routes at Taiwan Taoyuan International Airport during the years 2004-2007. The results indicate that population, air freight rate and three dummy variables, including the regional economic bloc of the “Chinese Circle”(an informal partnership between Hong Kong, Macao, Taiwan and mainland China), the Open Sky Agreements and long established colonial links, are key determinants of international air cargo flows from/to Taiwan. These results suggest a wider array of factors needs to be considered in policy.     

The application of stochastic frontier panel models in economic regulation: Experience from the European rail sector

This paper shows how stochastic frontier panel techniques can be used by economic regulators to benchmark regulated firms against international best practice. We utilise a unique, panel dataset of European rail infrastructure managers (1996-2006). A time-varying inefficiency model, with firm-specific time paths for inefficiency, is adopted. The results were used in the 2008 regulatory review of the British infrastructure manager, Network Rail, and showed that the company faced an efficiency gap of around 40% against European best practice - in line with engineering-based evidence. More widely, the paper highlights the advantages of the inefficiency specification adopted for use in economic regulation.     

A passenger demand model for air transportation in a hub-and-spoke network

This paper develops an air passenger model that deals with city-pair demand generation and demand assignment in a single framework. Using publicly available and regularly collected panel data, the model captures both time series and cross-sectional variation of air travel demand. The empirical analysis finds that pattern of correlations among alternatives can be described by a three-level nested logit model. Fare, frequency, flight time, direct routing, on-time performance, income, and market distance have significantly effects on air demand. Correcting for the problem of endogenous air fares using instrumental variables yields more plausible estimates of price sensitivity and value of time.     

Transportation mode selection with positive manufacturing lead time

In this paper we present a dual supply model taking into account that in many industries the replenishment cycle does not only involve the physical distribution of goods, but also the manufacturing of products. Further, we suggest postponing the transportation mode decision until the products are available for shipping. We investigate a class of order-up-to policies and show how to compute the optimal policy parameters. Our model enables us to quantify the value of the postponement of the transportation decision and the value of using an additional slow mode instead of only using the existing fast mode. In a numerical study the influence of various model parameters is investigated and it is shown that the use of a slow mode can be economically beneficial, especially for low value items.     

Can public slow charging accelerate plug-in electric vehicle sales? A simulation of charging infrastructure usage and its impact on plug-in electric vehicle sales for Germany

Alternative fuel vehicles face the lack of refueling infrastructure as one obstacle to market diffusion and potential operators of refueling stations await significant market shares before constructing a dense refueling network. The resulting lock-in effect or chicken-egg-problem has scarcely been analyzed for plug-in electric vehicles (PEVs) up to now. The research question of this article is How much public charging infrastructure for PEVs is needed and is there mutual interaction in the diffusion of public charging infrastructure and electric vehicles?

Here, we present an agent-based market diffusion model for PEVs and their charging infrastructure that is based on a large number of individual driving profiles for private and commercial car holders in Germany. Our results demonstrate the possibility of a market diffusion in Germany without any slow public charging infrastructure until 2030. Although a charging point at home is obligatory for early adopters, the second-best option for an infrastructure set-up is at work where the majority of vehicles is parked for a long time during the day, the installation is not costly and users profit more than from public facilities. Public slow charging facilities do not increase PEV market shares and they need to be subsidized for a long time.     

Terrorism and tourism demand: a case study of Lebanon,Turkey and Israel

Using a seemingly unrelated regression (SUR) model, this paper examines the impact of domestic and transnational terrorism on tourism demand (as measured by visitor arrivals) to Lebanon, Turkey and Israel. The distinguishing feature of this paper is that we use a dynamic framework that takes into account (i) the intensity of terrorism and (ii) the associated spillover effects. The empirical results, based on monthly data from 1995 to 2007, reveal that terrorism in one country affects visitor arrivals not only to that country but also to other countries. We find that tourists view Lebanese and Turkish tourism markets as substitutes. Terrorism in Israel, of all types (i.e. domestic or transnational) and intensities, affects visitor arrivals to Lebanon and Turkey. In overall terms, terrorism has a much larger negative impact on visitor arrivals to Lebanon.