We Eat First with Our (Digital) Eyes: Enhancing Mental Simulation of Eating Experiences via Visual-Enabling Technologies

This research examines how consumers’ intentions to purchase food change depending on the visualisation mode (3D vs. AR) and product format (served vs. packaged). In three studies, we demonstrate that mental simulation of eating experiences (process and outcome) mediate these effects. Study 1 shows that AR visualisation of a served food improves simulation of the eating process over 3D visualisation, with a positive effect on purchase intention. Study 2 reveals that 3D visualisation improves purchase intention for packaged products (high instrumental properties) over served products (low instrumental properties) while the opposite is true for AR visualisation. In addition, interactivity and immersion mediate the effects of 3D (vs. AR) on mental simulation of the eating process for packaged products. Study 3 extends these results by showing that 3D increases purchase intention by eliciting mental simulation of the eating outcome, when the food is visible due to transparent (vs. opaque) packaging (displaying both sensory and instrumental properties), but that no such differences emerge for AR. This research highlights the importance of using different visualisation modes to promote food depending on the product format. The findings have important implications for both offline and online retailers.     

Auction theory adaptations for real life applications

We develop extensions to auction theory results that are useful in real life scenarios.1. Since valuations are generally positive we first develop approximations using the log-normal distribution. This would be useful for many finance related auction settings since asset prices are usually non-negative.2. We formulate a positive symmetric discrete distribution, which is likely to be followed by the total number of auction participants, and incorporate this into auction theory results.3. We develop extensions when the valuations of the bidders are interdependent and incorporate all the results developed into a final combined realistic setting.4. Our methods can be a practical tool for bidders and auction sellers to maximize their profits. The models developed here could be potentially useful for inventory estimation and for wholesale procurement of financial instruments and also non-financial commodities.All the propositions are new results and they refer to existing results which are stated as Lemmas.     

Analysis of the effect of charging infrastructure design on electric taxi driving profiles: A case study approach on the example of Singapore

Replacing conventional vehicle taxis with electric vehicles would be an efficient measure to reduce greenhouse gas emissions. Due to the limited range and long charging times of current battery electric vehicles, it is of utmost importance to provide sufficient charging facilities. This article analyses the impact of the placement and charging power of charging stations on potential mileage and revenue of electric taxis on the example of Singapore. Therefore, we developed an agent-based electric taxi simulation model to investigate electric taxis’ driving profiles with respect to different vehicle types and charging infrastructure designs. This model is also capable of simulating conventional taxi driving profiles. The validation of these simulation results with real taxi data showed that the model is reproducing taxi driving profiles with high accuracy in great detail. We found out that electric taxis could reach the same mileage and revenue as conventional taxis if charging with a power of 160?kW is possible. Furthermore, we discovered that waiting times for available charging stations have a stronger effect on revenue than the length of detours to reach charging stations. Based on these findings, we concluded that it is more important to reduce waiting times by placing sufficient numbers of charging stations at each location before expanding the charging network by installing small numbers of charging stations at many locations.     

An explainable machine learning approach to improve take-off time predictions

Accurate aircraft trajectory predictions are necessary to compute exact traffic demand figures, which are crucial for an efficient and effective air traffic flow and capacity management. At present, the uncertainty of the take-off time is one of the major contributions to the loss of trajectory predictability. In the EUROCONTROL Maastricht Upper Area Control Centre, the predicted take-off time for each individual flight relies on the information received from the Enhanced Traffic Flow Management System. However, aircraft do not always take-off at the times reported by this system due to several factors, which effects and interactions are too complex to be expressed with hard-coded rules. Previous work proposed a machine learning model that, based on historical data, was able to predict the take-off time of individual flights from a set of input features that effectively captures some of these elements. The model demonstrated to reduce by 30% the take-off time prediction errors of the current system one hour before the time that flight is scheduled to depart from the parking position. This paper presents an extension of the model, which overcomes this look-ahead time constraint and allows to improve take-off time predictions as early as the initial flight plan is received. In addition, a subset of the original set of input features has been meticulously selected to facilitate the implementation of the solution in an operational air traffic flow and capacity management system, while minimising the loss of predictive power. Finally, the importance and interactions of the input features are thoroughly analysed with additive feature attribution methods.     

基于GM(1,1)模型的造纸业上市公司财务研究——以冠豪高新为例

财务风险是企业调整发展战略、提升管理水平的重要参考指标之一。财务风险预测模型的建立能够预测企业在中短期内的财务风险,为企业敲响警钟。以造纸业上市公司冠豪高新为例,选取近五年财务杠杆系数为风险指标,建立GM(1,1)风险预测模型,结果显示该公司短期内财务风险呈下降趋势,调查发现这主要得益于产品成本的降低以及营销策略的改变。     

The mechanism of credit risk contagion among internet P2P lending platforms based on a SEIR model with time-lag

The credit risk contagion of Internet peer-to-peer (P2P) lending platforms is an important part of Internet financial risk management and supervision. This study analyzes the contagion path of credit risk in Internet P2P lending. Based on complex network theory and the theory of infectious disease dynamics, the characteristics of Internet P2P lending development are combined to construct a SEIR model of credit risk transmission among Internet P2P lending platforms with time lag, and the robustness of the model is analyzed and proven. The influence of platform correlations, the susceptible immune rate, the platform elimination rate, contagion latency, the saturation coefficient, and the susceptibility input rate on credit risk contagion behavior among Internet P2P lending platforms is analyzed, using the equilibrium point and threshold value. The impact of each variable is analyzed by simulation. Corresponding countermeasures and suggestions are proposed to prevent and control credit risk contagion among these platforms.     

黑龙江森工林区林业产业结构演变趋势及优势产业选择

采用灰色预测方法对黑龙江森工林区2018—2027年林业三次产业产值进行预测,并在此基础上利用动态偏离-份额分析方法对此阶段黑龙江森工林区的林业优势产业进行选择。结果表明:2019年黑龙江森工林区林业产业结构将演变为"三、一、二"模式;林业第一产业中的林木育种和育苗、经济林产品的种植和采集业可作为优势产业进行重点发展和管理。因此,提出优化黑龙江森工林区林业产业结构的相关建议:继续巩固发展林木育种和育苗、经济林产品的种植和采集这两个优势产业;推动加工制造业向深加工、精加工的方向转变;加强林业旅游与休闲服务业的竞争力。     

Bayesian forecasting of UEFA Champions League under alternative seeding regimes

The evaluation of seeding rules requires the use of probabilistic forecasting models both for individual matches and for the tournament. Prior papers have employed a match-level forecasting model and then used a Monte Carlo simulation of the tournament for estimating outcome probabilities, thus allowing an outcome uncertainty measure to be attached to each proposed seeding regime, for example. However, this approach does not take into account the uncertainty that may surround parameter estimates in the underlying match-level forecasting model. We propose a Bayesian approach for addressing this problem, and illustrate it by simulating the UEFA Champions League under alternative seeding regimes. We find that changes in 2015 tended to increase the uncertainty over progression to the knock-out stage, but made limited difference to which clubs would contest the final.     

基于多软件平台的机电液一体化虚拟试验方法

提出一种针对复杂机电液系统的虚拟仿真试验方法,分别在ADAMS、AMESim、MATLAB/Simulink软件中建立机械子系统、液压子系统和控制子系统模型,并基于软件间接口技术,建立动态数据共享通道,实现系统的全面仿真分析,为系统设计与优化、控制策略选择等提供依据.该方法对于复杂机电液系统仿真分析具有普遍适用性,对缩短产品开发周期、降低产品研发成本、减轻仿真工作复杂性具有重要意义.     

Exploring the impact of the physical conditions of mannequin displays on mental simulation: An embodied cognition theory perspective

This study examines how mannequins' physical conditions of display height and distance are related to consumers’ shopping motivations in generating mental simulation resulting in purchase intention. A 2 × 2 x 2 between-subjects lab experiment (n = 249) was conducted to address this question. The results reveal a significant three-way interaction effect of display height, distance, and shopping motivation. Specifically, it is found that for those with a dominant hedonic shopping motivation, a mannequin displayed up high generates greater mental simulation than one displayed down low, but for those with a dominant utilitarian shopping motivation, a mannequin displayed high and close to consumers generates greater mental simulation than one displayed low and close to them. This study also reveals that mental simulation mediates the influence of the interaction effect of “display height x distance,” moderated by shopping motivation, on purchase intention. Important theoretical and practical implications for retail managers are discussed.