Route churn: an analysis of low-cost carrier route continuity in Europe

Discontinuity of air routes is a subject that has been analysed in various ways. For example, the complex network approach focuses on network robustness and resilience due to route interruptions during a relatively short period. Also seasonal interruptions of air routes are a well-documented phenomenon in the context of demand variability. However, only recently discussions emerge on the more permanent cessation of air routes, the route churn. Today, European low-cost carriers frequently apply route churn in their networks. To enable early route churn detection in these networks, a regression model is developed in which route characteristics explain the churning likelihood of individual routes. The results of the econometric analysis show that churn rates are higher during an economic downturn, within the Eastern European market, between the Eastern and the Mediterranean market and between primary airports. In addition, we find that distance and the number of seats offered have a significant negative effect on the churn likelihood. The results also show significant effects of market share, seasonality and route age on the chance of cessation. To conclude, the paper demonstrates substantial differences in churn behaviour amongst specific low-cost carriers.     

基于Holt-Winter模型的铁路货运量预测研究

建立Holt-Winter预测模型，将具有线性趋势、季节变动和随机波动的时间序列进行分解研究，并与指数平滑法相结合，分别对长期趋势、趋势的增量和季节波动做出估计。介绍该模型的3个平滑方程和1个预测公式，以及初始值的计算和最优加权系数值的确定。通过实证分析，将预测结果与常用模型进行比较，说明该模型的预测精度较高。     

Responses of air cargo carriers to industrial changes

This study examines how product characteristics, values, inventory cost, shipping charges, shipping distance, and time affect an international firm's choice of air carrier. An individual choice model is constructed by assuming that the shipper in a specific industry chooses the optimal air cargo carrier with the minimal logistics cost. The study further aggregates air cargo demands on different routes for the carriers by considering the spatial distribution of the origin-destination pattern and any temporal changes in the industrial structure. A case study is used to illustrate the application of the proposed model using data from Taiwan Taoyuan International Airport and the industrial economics database in Taiwan. The results show that shippers with high product value and short delivery distance focus on the shipping charge and prefer choosing the air cargo carrier that offers more flights. Further a carrier may achieve a larger market share if its supply attributes match the industrial structure and the product characteristics of the market on the route. Finally, because dynamic changes in the industrial structure and product value have been captured, the results are more accurate than that from the Grey model.     

基于季节调整模型的我国铁路客运量波动分析

在研究TRAMO/SEATS季节调整模型计算方法的基础上,基于我国铁路2002年1月—2010年2月的客运量月度数据,应用Demetra软件,通过季节调整模型参数设置、模型的估计和检验,得到2010年3月—2012年2月的铁路客运量预测值,并对预测结果进行趋势性和季节性分析。研究结果表明,Tramo/Seats季节调整模型的预测精度较高。     

Air transportation demand forecast through Bagging Holt Winters methods

This paper expands the fields of application of combined Bootstrap aggregating (Bagging) and Holt Winters methods to the air transportation industry, a novelty in literature, in order to obtain more accurate demand forecasts. The methodology involves decomposing the time series into three adding components: trend, seasonal and remainder. New series are generated by resampling the Remainder component and adding back the trend and seasonal ones. The Holt Winters method is used to modelling each time series and the final forecast is obtained by aggregating the forecasts set. The approach is tested using data series from 14 countries and the results are compared with five methodology benchmarks (SARIMA, Holt Winters, ETS, Bagged.BLD.MBB.ETS and Seasonal Naive) using Symmetric Mean Absolute Percentage Error (sMAPE). The empirical results obtained with Bagging Holt Winters methods consistently outperform the benchmarks by providing forecasts that are more accurate.     

A neuro-fuzzy combination model based on singular spectrum analysis for air transport demand forecasting

Air transport demand forecasting is receiving increasing attention, especially because of intrinsic difficulties and practical applications. Total passengers are used as a proxy for air transport demand. However, the air passenger time series usually has a complex behavior due to their irregularity, high volatility and seasonality. This paper proposes a new hybrid approach, combining singular spectrum analysis (SSA), adaptive-network-based fuzzy inference system (ANFIS) and improved particle swarm optimization (IPSO), for short-term air passenger traffic prediction. The SSA is used for identifying and extracting the trend and seasonality of air transport demand and the artificial intelligence technologies, including ANFIS and IPSO, are utilized to deal with the irregularity and volatility of the demand. The HK air passenger data are collected to establish and validate the forecasting model. Empirical results clearly points to the enormous potential that the proposed approach possesses in air transport demand forecasting and can be considered as a viable alternative.     

Aircraft replacement scheduling: A dynamic programming approach

This study developed a stochastic dynamic programming model to optimize airline decisions regarding purchasing, leasing, or disposing of aircraft over time. Grey topological models with Markov-chain were employed to forecast passenger traffic and capture the randomness of the demand. The results show that severe demand fluctuations would drive the airline to lease rather than to purchase its aircrafts. This would allow greater flexibility in fleet management and allows for matching short-term variations in the demand. The results of this study provide a useful reference for airlines in their replacement decision-making procedure by taking into consideration the fluctuations in the market demand and the status of the aircraft.     

基于傅里叶级数的铁路客运量预测研究

基于傅里叶级数预测模型,以我国2004—2009年铁路客运量为数据基础,通过将时间序列划分为趋势性与季节性部分,分别采用最小二乘法与傅里叶级数法对两者进行拟合,应用Matlab软件编程,求出预测模型,并进行客运量预测。通过对预测结果的误差分析,结果表明:采用傅里叶级数预测法预测我国铁路客运量的效果较好。     

Short-term forecasting of air passenger by using hybrid seasonal decomposition and least squares support vector regression approaches

In this study, two hybrid approaches based on seasonal decomposition and least squares support vector regression (LSSVR) model are proposed for short-term forecasting of air passenger. In the formulation of the proposed hybrid approaches, the air passenger time series is first decomposed into three components: trend-cycle component, seasonal factor and irregular component. Then the LSSVR model is used to predict the components independently and these prediction results of the components are combined as an aggregated output. Empirical analysis shows that the proposed hybrid approaches are better than other time series models, indicating that they are promising tools to predict complex time series with high volatility and irregularity.     

Dynamic carbon emission performance of Chinese airlines: A global Malmquist index analysis

Monitoring the carbon emission performance of Chinese airlines helps inform targeted carbon-reduction policies. This paper proposes a global Malmquist carbon emission performance index (GMCPI), which can measure dynamic changes in total factor carbon emissions performance over time using a production frontier framework. The study then applied the proposed index to evaluate carbon emission performance of 12 Chinese airlines from 2007 to 2013; the study also proposed bootstrapping GMCPI to perform statistical inferences on the GMCPI results. The empirical study generated in three meaningful findings. First, the carbon emission performance of the airlines improved by 11.93%, mainly through technological progress. Second, there were carbon emission performance differences among three different airline types; there was also a convergence of carbon emission performance. Third, the most important factor influencing carbon emission performance was the air routes distribution. Chinese airlines should consider improving carbon emission performance further, by establishing an evaluation system, enhancing communication and coordination among different airlines, adjusting the scale of airline development, and optimizing the air routes distribution.     

建立铁路货运量季节性预测模型的研究

铁路货运量预测是编制运输方案的依据,目前采用的预测方法,难以全面、科学地反映数据的内在结构和复杂性,以年度为单位预测时,误差不大,但按月度预测时,则误差较大。为此利用三角函数周期性的特点,辅以线性趋势变动,建立适合不同预测期限、不同预测精度的季节性预测模型,经实例检测能够较为准确地预测月计划运输量。     

Seasonality patterns in dry bulk shipping spot and time charter freight rates

This paper investigates the nature of seasonality (deterministic and/or stochastic) in dry bulk freight rates, and measures and compares it across freight rates of different vessel sizes (Capesize, Panamax and Handysize), contract duration (spot, 1-year and 3-year time charters) and market conditions (peaks and troughs). Although, there is no evidence of stochastic seasonality, deterministic seasonality in freight rates is found to be varying from −18.2% to 15.3% in individual months within a year. Spot rates for larger vessels exhibit higher seasonal fluctuations compared to smaller vessels, although differences in seasonal fluctuations between sectors are eliminated as the contract duration increases. Also, for each vessel size, the seasonality declines as the contract duration rises. Asymmetries in seasonal fluctuations in freight rates over different market conditions are attributed to the high and low elasticities of supply expected under the respective market conditions. The results have implications for tactical shipping operations such as timing of dry-docking, chartering strategies and switching between freight markets.     

Study on China-EU container shipping network in the context of Northern Sea Route

The emerging Northern Sea Route (NSR) represents change to the existing liner network for China-EU container shipping. It is necessary to re-examine the container network in this context and assist liner companies in decision-making. This paper assesses the potential of the NSR based on designing a multi-port multi-trip liner service by establishing a two-stage optimization model. Based on the estimated data of NSR shipping, ship routing schemes on both the NSR and conventional routes are proposed. It is determined that container service along the NSR is largely influenced by ice-breaking charge, seasonality, and cargo volume, which makes NSR more likely to act as a supplementary line of the liner network in the short or medium term. The results also indicate that use of NSR may drive the redeployment of shipping network and hub ports in the long term. This study's conclusions may prove useful for strategic planning by liner companies, port authorities, and governments to assess the operation of liner service via the NSR.     

Distortional Bullwhip Effects on carriers

This paper analyzes the Bullwhip Effect (BWE) problem from the (carriers’) viewpoint. The analysis explores how retailer’s limited capability to forecast end-customer demand and their sub-optimal replenishment policies distort service demand signals to carriers. The consequent unnecessary increases in carriers’ capacity costs and operational instability are quantified for a context of pronounced seasonality. The paper finds that carriers unable to adjust transportation capacity to seasonal changes can incur costs of nearly five times what is possible with maximum forecasting capabilities and prudent replenishment policies. Another major finding is that replenishment policy is superior to forecasting capability in reducing BWE-related costs.     

Decomposing seasonality in an urban destination: the case of Milan

ABSTRACT

This paper analyses demand fluctuations in the field of urban destinations, decomposing Milan’s hotel seasonality. Four different seasonal periods are identified and two research questions are explored. The first aims to verify how seasonality evolved over the period 2004–2015 and the effectiveness of analysing tourism flow in an urban destination using daily data. The second aim explores the effects generated by the Milan Expo 2015 on seasonality. Using Smith Travel Research data, a longitudinal analysis (2004–2015) is carried out, decomposing the annual Theil index. Evidence is reported and discussed.     

A study on the temporal dynamics of tourism demand in the Asia Pacific Region

Using the monthly statistics of tourists from four different origins (America, Europe, Asia and Oceania) among seven places in the Asia Pacific region for a period from January 1991 to December 2005, we investigate these 28 time series using the Holt‐Winters method, artificial neural network and numerical graphical plots. Interesting comparisons on level fluctuations, trends and seasonal patterns of the time series among the Asia Pacific region are explored. These findings enable us to understand more about the temporal aspect of tourism demand in the Asia Pacific region. In sum, this paper lays out the importance of understanding the trend and seasonality indices in details. Copyright © 2009 John Wiley & Sons, Ltd.     

Persistence Characteristics of Tourism Arrivals to Australia

This paper examines the degree of persistence in international monthly arrivals to Australia by using data disaggregated by tourism‐source countries. We employ two competing models, which are very general in the sense that they include (seasonal and non‐seasonal) unit roots as particular cases of interest. The first model is based on a long‐memory process in the non‐seasonal part of the series along with a short‐memory autoregressive (AR) seasonal structure. The second model is based on a long‐memory process for the seasonal structure of the series, the short‐term evolution being described through a non‐seasonal AR(1) process. Results based on the residuals and forecasting assessment indicate that the second model is preferable in terms of fitting the data. We provide persistence ranking of all countries included in the study and discuss the managerial implications of the main findings. Copyright © 2011 John Wiley & Sons, Ltd.     

建立灰色关联评价模型科学评价铁路客运服务质量

通过对传统评价模型与灰色关联评价模型的论述,引入灰色关联评价模型,客观评价铁路客运服务质量的建模思路,并通过例证说明灰色关联评价模型的计算方法,使客运服务质量评价标准化,也促使铁路客运服务质量不断提高,成为制定铁路客运票价的重要因素。     

Analysis of an integrated maximum covering and patrol routing problem

In this paper, we address the problem of determining the patrol routes of state troopers for maximum coverage of highway spots with high frequencies of crashes (hot spots). We develop a specific mixed integer linear programming model for this problem under time feasibility and budget limitation. We solve this model using local and tabu-search based heuristics. Via extensive computational experiments using randomly generated data, we test the validity of our solution approaches. Furthermore, using real data from the state of Alabama, we provide recommendations for (i) critical levels of coverage; (ii) factors influencing the service measures; and (iii) dynamic changes in routes.     

运用转移函数模型预测铁路建设项目运营有关成本

运营成本是影响铁路建设项目后评价结论的重要基础数据。通过建立转移函数模型对铁路建设项目后评价时点后的运营有关成本进行预测，并对某铁路建设项目进行实证分析，说明采用转移函数模型的预测效果明显在回归模型的基础上有所改进，能较好地反映出有关成本的变化趋势，从而达到较好的预测效果。