Effects of carbon emission reduction policies on transportation mode selections with stochastic demand

We are witnessing more frequent extreme weather events due to the global warming. There is an urgent need for governments, industries, general public, and academics to take coordinated actions in order to tackle the challenges imposed by the climate change. It is essential to incorporate the environmental objective in the transportation mode selection problem as transportation is a main contributor to carbon emissions. With this in mind, our paper studies the retailer’s ordering and transportation mode selection problem using stochastic customer demand and investigates the optimal ordering and transportation mode selection decisions under different carbon emission reduction policies. Our analytical results reveal that there are some important transportation mode shifting thresholds under different carbon emissions reduction policies. These findings do not only help firms to make optimal decisions under different carbon emission reduction policies but also support policy makers to develop effective policies on carbon emissions reduction.     

System dynamics modelling and forecasting health tourism demand: the case of Russian resorts

This article presents the results of the system dynamics modelling of the regional market of health tourism in the Krasnodar region of Russia. The research was based on various indicators characterizing the supply and demand for this type of tourism for years 2006–2012. The medium-term forecast made by constructed model shows a possible decrease in number of health tourists and income of sanatorium organizations. Price competition of inexpensive foreign resorts was a key factor influencing the market of tourist services; therefore ruble devaluation to US dollar may improve the prognostic indicators.     

The impact of Air Service Agreement liberalisation: The case of Nigeria

The positive impact of air transport liberalisation as suggested by economic theories and empirical studies has inspired many developing countries like Nigeria to liberalise some of its Air Service Agreements (ASAs). This paper seeks to examine the extent to which international air service liberalisation has impacted upon Nigeria ten years after it was introduced. The research developed a cross-sectional model with passenger traffic as the dependent variable, while macroeconomic factors (trade and GDP), historical links, distance and ASAs (a proxy for liberalisation) served as independent or predictor variables. The analysis revealed a set of ASA stages in the country's policy-making process (restricted Bilateral Air Service Agreement, Open Skies Agreement and Yamoussoukro Declaration). Further analysis showed that the predictor variables were all significant in explaining passenger demand. The model demonstrated that the liberalisation of market access to the Open Skies Agreement level could stimulate traffic growth by at least 65 percent. The findings can assist in guiding policy and industry stakeholders in future decisions relating to liberalisation and ASAs.     

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.     

外部因素对中国商品流通影响的长期性分析——以需求为例

改革开放以来,外部因素对我国国内需求以及商品流通都产生了深远影响,特别以东南亚金融危机以及本轮全球金融危机为最。外部因素对国内需求及商品流通的作用具有典型的阶段性特点,并随着开放经济的进一步发展呈现长期性。外部因素可经由数量、价格、全球化与国内市场互动以及渠道变革四个途径影响我国国内需求,进而影响商品流通的整个过程。鉴于外部因素作用于商品流通的长期性特点,在流通领域的理论和政策研究与实践中,需借助动态分析方法,从内生化层次讨论外部因素对我国商品流通的影响,按照外部因素内生化的基本观点,改进和丰富有关流通领域的贸易政策和产业政策。     

河北省农户储蓄与借贷需求分析

河北省农户金融活动除具有普通农户金融活动的特征外,还具有现金流量不稳定、资金用途难以区分、收入不平衡等特征。因此,需要构建新型农村金融体系,进行农村金融制度创新,为社会主义新农村建设提供资金支持。     

我国生产性服务业与制造业互动需求结构及发展态势

本研究采用投入产出法与比较分析方法,对典型国家(或地区)的生产性服务业与制造业的互动需求结构进行分析。研究发现,经济发展水平、服务业发展水平、生产性服务业性质、制造业性质四方面是影响生产性服务业与制造业需求结构的重要因素。本文从四要素发展特点总结了生产性服务业与制造业需求的国际发展态势,即随着经济发展水平与服务业发展水平的提高,生产性服务业由对制造业需求显著转为对自身需求显著,而生产性服务业内部由以非知识密集型服务业为主导逐步转向以知识密集型服务业为主导。结合我国现状,本文最后提出了推动我国两类产业互动发展的若干政策建议。     

The effects of learning and signaling on money demand: With an application to heterodox inflation stabilization programs

This paper develops a nonlinear vector autoregression of inflation and money growth subject to changes in regime. The regimes are fully characterized by the mean and variance of inflation and are conjectured to be the result of alternative government policies. Agents are unable to observe directly whether government actions are indeed consistent with the inflation rate targeted as part of a stabilization program. However, as part of their money demand decision, agents construct probability inferences regarding the regime. Government announcements are assumed to provide agents with additional, possibly truthful information regarding the regime.  This specification is estimated using data from the Israeli and Argentine high-inflation periods. Results indicate that the successful stabilization program implemented in Israel in July 1985 was more credible than either the earlier Israeli attempt in November 1984 or the Argentine programs. Government's signaling might simplify the agents' inference problem and increase the speed of their learning but, under certain conditions, it might also increase inflation volatility. Welfare gains from a temporary increase in real balances might be high enough to induce agents to raise their money demand in the short-term even if they are uncertain about the nature of government policy and the eventual outcome of the stabilization attempt. Statistically, the model restrictions cannot be rejected at the 1% significance level. First version received: August 1998/Final version received: January 1999     

Optimization approach to depot location and trip selection in one-way carsharing systems

In this paper, we present an optimization approach to depot location in one-way carsharing systems where vehicle stock imbalance issues are addressed under three trip selection schemes. The approach is based on mixed-integer programming models whose objective is to maximize the profits of a carsharing organization considering all the revenues and costs involved. The practical usefulness of the approach is illustrated with a case study involving the municipality of Lisbon, Portugal. The results we have obtained from this study provided a clear insight into the impact of depot location and trip selection schemes on the profitability of such systems.     

Analysis of travel behavior in Arab communities in Israel: a comparison of household surveys

This paper analyzes the main characteristics of travel behavior by the Arab minority community in Israel and discusses two issues related to household travel surveys: data collection among minorities and under-reporting of mid-day trips.Household travel surveys are generally designed and conducted for the majority population and, therefore, lack a proper accounting of minorities and miss many of their less-frequent trips. An alternative approach to conducting household surveys is presented, with the aim of improving data quality for transportation planning. The survey was designed for and conducted in three Arab towns in Israel. The main improvement of the survey involves better interaction between interviewer and interviewee, which should materialize into a relaxed environment that allows for obtaining detailed, reliable results within a reasonable amount of time.The results of the survey employing the alternative approach were compared to a sub-sample of the same towns taken from a regional survey conducted by the regional planning agency at the same time. The paper presents simple statistics on the main variables for each survey. Significant differences are found in the two data sets, mostly regarding the frequency of less frequent, non-home-based trips. A plausible explanation for these differences relates to the more detailed and improved data collected in the new survey.