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.     

Sample bias in contingent valuation: A comparison of the correction methods

Abstract

This article compares various methods for correcting contingent valuation aggregate benefits when the sample is known to be biased. A sample is defined as the population, and response rates are simulated on the basis of a measure of salience. The simulated response rates suffer from nonresponse bias and selection bias. Coefficient and benefit estimates that result from weighting and self‐selection correction approaches are compared with the true coefficient and benefit estimates. Our results indicate that at both low and high response rates the standard approach leads to bias, and either correction approach will reduce the bias in coefficient and benefit estimates.     

城镇化进程中农村金融需求变化问题的调查解析--基于江苏农户的问卷调查

经济决定金融，金融必须努力服务于经济发展方式转变。基于农户微观视角，通过农户问卷调查，研究城镇化进程中农户金融需求变化及其行为特征问题，分析农村金融供给现状及差距，探讨和构建适合新时期农村金融服务工作的发展机制，对促进江苏农村经济发展、提高城镇化水平具有重要现实意义。     

A STRUCTURAL RISK‐NEUTRAL MODEL FOR PRICING AND HEDGING POWER DERIVATIVES

We develop a structural risk‐neutral model for energy market modifying along several directions the approach introduced in Aïd et al. In particular, a scarcity function is introduced to allow important deviations of the spot price from the marginal fuel price, producing price spikes. We focus on pricing and hedging electricity derivatives. The hedging instruments are forward contracts on fuels and electricity. The presence of production capacities and electricity demand makes such a market incomplete. We follow a local risk minimization approach to price and hedge energy derivatives. Despite the richness of information included in the spot model, we obtain closed‐form formulae for futures prices and semiexplicit formulae for spread options and European options on electricity forward contracts. An analysis of the electricity price risk premium is provided showing the contribution of demand and capacity to the futures prices. We show that when far from delivery, electricity futures behave like a basket of futures on fuels.     

An economic evaluation of market development programmes for US dairy products

‘This study measured the effectiveness of US dairy export promotion programmes on increasing foreign demand and enhancing producers’ revenues. An import demand equation based on panel data was used to test whether export promotion has a positive and significant impact on US dairy exports. The effects of various promotion scenarios on the dairy market were then simulated, and benefit–cost ratios (BCRs) for these programmes were estimated. There were three key findings. First, the combined effort of public and private dairy export promotion expenditures had a positive and statistically significant impact on demand for US dairy products in the world market. The findings indicated that export promotion stimulated total dairy exports by 4.14 billion pounds, on average, per year, which represented 55.8% of total exports. Second, US dairy export promotion has been highly profitable for the nation’s dairy farmers. The calculated BCRs, based on assumed elasticity of supply, ranged from a low of 8.54 for the most elastic assumption to a high of 30.12. Third, from an optimality standpoint, dairy farmers are underinvesting in export promotion. The marginal BCRs ranged from a low of 3.79 to a high of 15.22, which means that, at the margin, increasing export promotion expenditures would be profitable for dairy farmers.     

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.     

Minimum Wage Compliance and the Labor Demand Curve

Contrary to the traditional analysis of the employment effects of the minimum wage setting, the author shows that if compliance is contingent upon enforcement, complying with the minimum wage law involves a leftward shift of the labor demand curve rather than an upward movement along the curve. Furthermore, the labor demand curve will shift leftward with enforcement even if enforcement is insufficient to ensure compliance, becoming vertical when the options of compliance and noncompliance are equally attractive. Hence, it is not paying the statutory minimum wage that brings about a reduction in employment down to the full-compliance level but enforcement that, if sufficiently high, induces that same reduction in employment, even if the employer is still noncomplying with the minimum wage law.     

浅谈电子商务中的消费心理

在电子商务活动中人们是通过网上丰富的商品信息、完善的物流配送和方便安全的资金结算系统进行交易。面对崭新的交易方式,消费者的心理势必发生相应的变化。本文从对电子商务活动中消费者心理特征,变化和影响因素等方面进行分析,探讨网络消费者的心理。     

中国二手硬件市场分析

二手硬件市场作为一种新兴的市场,由于其价格低、入手易的特点越来越受到人们的关注,然而它的市场供求机制还不是很明确。论文对二手硬件市场供求平衡以及价格的形成做了系统的分析,在此基础上探讨了该市场目前出现的问题和解决的方法。