Sustainable hub location under mixed uncertainty

This paper addresses a novel sustainable hub location problem (SHLP) in which two new environmental-based cost functions accounting for air and noise pollution of vehicles are incorporated. To cope with uncertain data incorporated in the model, a mixed possibilistic–stochastic programming approach is proposed to construct the crisp counterpart. A simulated annealing (SA) and an imperialist competitive algorithm (ICA) with a new solution representation are developed to solve real-sized instances whose performances are compared with a proposed lower bound. Finally, some computational experiments are provided to demonstrate the effectiveness of the proposed model and solution approaches.     

The veto mechanism in atomic differential information economies

We establish new characterizations of Walrasian expectations equilibria based on the veto mechanism in the framework of differential information economies with a complete finite measure space of agents. We show that it is enough to consider the veto power of a single coalition, consisting of the entire set of agents, to obtain the Aubin private core. Moreover, we investigate on the veto power of arbitrarily small and big coalitions, providing an extension to mixed markets of well known Schmeidler (1972) and Vind’s (1972) results in terms of Aubin private core allocations.     

Locating a Biorefinery in Northern Spain: Decision Making and Economic Consequences

Biofuels are emerging as a prominent renewable and sustainable energy sources in developed countries. In this sense, this paper presents a case study in which a biorefinery has to be sited in Northern Spain. Thus, the strategic decision of locating such a facility is deeply investigated through strategic policy evaluation. Then, tactical decisions ranging from purchasing and transportation policies to storage protocols are carried out. Only local and limited biomass can be harvested for supplying the biorefinery through a heterogeneous vehicle fleet. Moreover two different and mutually exclusive storage strategies are evaluated: direct supply from crops to biorefinery and using intermediate-collectors. Additionally, crop exploitation factors and biorefinery sizes are used to generate several scenarios in which the strategic decision of location as well as all the tactic decisions are made. Some mixed integer linear programming models are proposed to figure out all relevant decision problems.The results suggest that the Northwest study area as the best option to locate the biorefinery and recommend the intermediate-collector storage strategy. Moreover, the key information about critical biomass, crops and times are also provided.     

High-frequency credit spread information and macroeconomic forecast revision

We examine whether professional forecasters incorporate high-frequency information about credit conditions when revising their economic forecasts. Using a mixed data sampling regression approach, we find that daily credit spreads have significant predictive ability for monthly forecast revisions of output growth, at both the aggregate and individual forecast levels. The relationships are shown to be notably strong during ‘bad’ economic conditions, which suggests that forecasters anticipate more pronounced effects of credit tightening during economic downturns, indicating an amplification effect of financial developments on macroeconomic aggregates. The forecasts do not incorporate all financial information received in equal measures, implying the presence of information rigidities in the incorporation of credit spread information.     

Bridging the valuescape with digital technology: A mixed methods study on customers’ value creation process in the physical retail space

This mixed methods study investigated how value is created in the physical retail space and how the customer experience is influenced by digital technology. A cross-sectional survey, with both qualitative and quantitative components, was distributed across a heterogeneous sample of 832 customers. The results revealed an overarching model comprised of three interrelated clusters: customer, service provider, and digital technology. We propose that this model can be understood as a valuescape, where customers' specific goals, needs, and desires drive them to interact and co-create value with service providers in the physical retail space, with digital technology either enhancing or disrupting this value co-creation process. The results also show that the importance of aligning digital solutions with customers’ drives increases at the same pace as reliance on technology. The findings offer guidelines on how to utilize digitalization to leverage customer experiences and thus strengthen the attractiveness of physical retail spaces.     

Constructive deviance as a driver for performance in retail

A growing body of research is concerned with deviance in the workplace. While much research has explored negative forms of deviance, we examine constructive deviance: behaviour that deviates from salient norms and benefits the reference group. We empirically explore manifestations, determinants and performance outcomes of constructive deviance in standardised work processes. We do this through a mixed-methods study in bakery trading departments of an Australian retailer. We illustrate that constructive deviance occurs in these settings and show that some manifestations of constructive deviance improve organisational performance and pave the way for applying constructive deviance as a strategic tool in retail.     

Forecasting in a Mixed Up World: Nowcasting Hawaii Tourism

We evaluate the short term forecasting performance of methods that systematically incorporate high frequency information via covariates. Our study provides a thorough introduction of these methods to the tourism literature. We highlight the distinguishing features and limitations of each tool and evaluate their forecasting performance in two tourism-specific applications. The first uses monthly indicators to predict quarterly tourist arrivals to Hawaii; the second predicts quarterly labor income in the accommodations and food services sector. Our results indicate that compared to the exclusive use of low frequency aggregates, including timely intra-period data in the forecasting process results in significant gains in predictive accuracy. Anticipating growing popularity of these techniques among empirical analysts, we present practical implementation guidelines to facilitate their adoption.     

Willingness to pay for safety improvements in passenger air travel

The risk of being involved in an airplane accident is largely ignored in air passengers’ choice models. The reason presumably is that it is hard to operationalize, because objective safety indicators often involve extremely low probabilities that are hard to grasp and interpret by passengers. In this paper, we propose an operationalization that is based on the perception of safety, which is easy to understand and resonates that perceptions often influence decisions stronger than objective variables. We conceptualize that passengers form a safety perception score of a particular flight based on their perception of airline and route attributes and that this score in turn is traded-off against other flight attributes, such as ticket costs, to arrive at a flight choice. In line with this conceptualization, two stated preference experiments are conducted. In a first experiment, combinations of airline and route attributes are evaluated in terms of safety that is captured on a rating scale. In a second experiment, safety perception is treated as an attribute and traded-off against other flight attributes to arrive at a flight choice. The paper presents the results of a regression and a Panel Mixed Logit model estimated from responses obtained from a convenience sample of 161 air passengers recruited in the Netherlands. The results of both models are then combined to calculate the willingness to pay values for improvements made to a range of airline and route attributes, taking into account socio-demographic variables and psychological traits. As expected, the results indicate that the willingness to pay for improving safety decreases with higher initial safety levels.     

农业税改对东营农村经济影响分析

自实施农业税制改革以来,山东省东营市认真贯彻国家各项农业税制改革政策,于2005年全部免除农业税,大力加强财政支农和金融支农力度,有力地促进了社会主义新农村建设。本文从东营市入手深入调查研究了我国农业税制改革对该市农村经济所带来的积极影响与负面作用,并进一步分析了金融、财政在支持“三农”过程中所存在的问题,最后提出了对策、建议。     

中国通货膨胀预期及其影响因素分析——基于混频无套利Nelson-Siegel利率期限结构扩展模型

综合国债市场的利率期限结构信息以及不同频率的宏观信息,本文构建混频无套利Nelson-Siegel利率期限结构扩展模型,在对不同期限债券进行一致性定价理论约束下,提取了中国通货膨胀预期的期限结构并对其进行影响因素分析。研究结果表明,本文模型提取的通胀预期期限丰富、结果稳健,具有较好的参考价值。通胀预期水平和变动响应主要受货币增长率、通胀率及全球食品价格变动等国内外相关宏观变量的影响,与国债收益率因子之间的关系不显著;国债收益率因子对中长期通胀预期的方差波动具有较强解释力,表明国债定价反映了未来通胀的不确定性。本文研究有助于充分利用我国宏观与金融市场信息条件,有效发现和锚定通胀预期,一方面,研究结果可为政策制定者和市场投资者提供科学的决策参考,另一方面,研究方法对丰富宏观金融领域的分析框架具有参考价值。