The Influence of Price Discrimination from Airports on the Route Development Behavior of Airlines

Given the prominence and magnitude of airport incentive schemes,it is surprising that literature hitherto remains silent as to their effectiveness.In this paper,the relationship between airport incentive schemes and the route development behavior of airlines is analyzed.Because of rare and often controversial findings in the extant literature regarding relevant influencing variables for attracting airlines at an airport,expert interviews are used as a complement to formulate testable hypotheses in this regard.A fixed effects regression model is used to test the hypotheses with a dataset that covers all seat capacity offered at the 22 largest German commercial airports in the week 46 from 2004 to 2011.It is found that incentives from primary choice,as well as secondary choice airports,have a significant influence on Low Cost Carriers.Furthermore,Low Cost Carriers,in general,do not leave any of both types of airports when the incentives cease.In the case of Network Carriers,no case is found where one joins a primary choice airport and receives an incentive.Insufficient data between Network Carriers and secondary choice airports in the time when incentives have ceased means that no statement can be given.

Feature Selection Method Based on Class Discriminative Degree for Intelligent Medical Diagnosis

By using efficient and timely medical diagnostic decision making,clinicians can positively impact the quality and cost of medical care.However,the high similarity of clinical manifestations between diseases and the limitation of clinicians’knowledge both bring much difficulty to decision making in diagnosis.Therefore,building a decision support system that can assist medical staff in diagnosing and treating diseases has lately received growing attentions in the medical domain.In this paper,we employ a multi-label classification framework to classify the Chinese electronic medical records to establish corresponding relation between the medical records and disease categories,and compare this method with the traditional medical expert system to verify the performance.To select the best subset of patient features,we propose a feature selection method based on the composition and distribution of symptoms in electronic medical records and compare it with the traditional feature selection methods such as chi-square test.We evaluate the feature selection methods and diagnostic models from two aspects,false negative rate(FNR)and accuracy.Extensive experiments have conducted on a real-world Chinese electronic medical record database.The evaluation results demonstrate that our proposed feature selection method can improve the accuracy and reduce the FNR compare to the traditional feature selection methods,and the multi-label classification framework have better accuracy and lower FNR than the traditional expert system.

Price Discrimination of Film Products and Building of Hierarchical Market under the Background of “Internet Plus”

Price Discrimination of film products is theoretically feasible and logically inevitable, and it has been used for a long time in film industry as well. However, there are practical paradoxes in the new environment due to market factors like popularization of Internet environment and Online to Offline(O2O) retailers between hierarchical markets. Compared with high-level markets, low-level markets are lack of conditions for differentiated lower price like cinema infrastructure, and environment for film consumption market, so that the consumption potential for market has not been motivated yet. Therefore, it is quite important to pay close attention to how to expand the market by clearer gradient pricing structures and Internet platform.

Gender-Based Price Discrimination: The Cost of Being a Woman

Women have been oppressed since the beginning of time;however,the past has earned women their rightful position in society.Despite that,there are still traces of sexism that we find in modern society–these traces can be shown through direct or indirect means.One of the major areas that women are still vigorously oppressed in is gender-based pricing.The pink tax is an old phenomenon that has only gained global attention recently.The pink tax segregates women and often causes life-threatening consequences.This paper will analyze the effects of the pink tax through commodities being sold in the world-famous city of New York in the States.The New York City government is the only government that took action to undergo comprehensive research on such an important topic.In addition to that,the paper will also compare the pink tax while making notations on the gender wage gap to fully highlight the injustice women face today.To conclude this paper,policies and solutions will be recommended to work towards the abolishment of the pink tax trend.

Price Discrimination in the Steel Industry:Evidence from Egypt

This paper studies and enlightens mainly price discrimination;which is simply selling products for differentiated prices.First,a literature framework is detailed with all the theories and types of price discrimination throughout the years.It is a strategy that is used worldwide by so many companies and firms,but this paper studies specifically the activity of the major player in the Egyptian steel industry;Ezz steel.The research resulted in;that there is no price discrimination,activities are implied in the industry currently by the companies due to the interference of the government.However,before that,the company applied some strategies that are illustrated in the paper in detail.

Using Big Data to Discriminate Charged Price in the Car Insurance Industry: Evidence from United States

The purpose of this paper is to examinethe gender-based discrimination in car insurance ratesand whether the reasons provided by the car insurancecompanies for the different rates are valid or not. Thepaper studies the average annual premiums paid bymen and women across different age groups from 16years old to over 56 years old along with the percentagedifferences. Additionally, the concept of big data andhow it is utilized by businesses to apply personalizeprice discrimination is investigated. The researchdesign is conclusive and secondary data is used in bothqualitative and quantitative forms. Qualitative data iscollected from articles for the literature review andas for the quantitative data it is in the form of reportsand surveys. The data shows that at lower age groupswomen pay less than men for car insurance but as theage increase men start paying less. The paper reaches aconclusion that gender is not necessarily a crucial riskfactoras the regular factors such as driving record canprovided accurate risk determinants.

Misclassification analysis of discriminant model

This paper extends the criterion of the misclassification ratio of discriminant model and presents a new selection method of discriminant model.For selecting the discriminant model,this method establishes the rule of misclassification degree ratio through misclassification ratio of the discriminant model and misclassification degree of the samples.To test the effect of this method,this work uses seven UCI data sets.Numerical experiments on these examples indicate that this method has certain rationality and has a better effect to select a discriminant model.

医疗服务领域中的价格歧视——以特需门诊为例

特需门诊是医院为了提高利润而采取的一种价格歧视策略。本文通过构建博弈模型,分析了医院对普通门诊和特需门诊的资源配置行为和特需门诊对不同类型患者福利的影响,并进一步分析了数量管制政策的效果。该博弈模型的子博弈精炼纳什均衡结果表明,如果政府没有采取任何管制政策,那么医院将把全部医疗资源配置到特需门诊,全体患者的福利受损。当政府采取数量管制政策时,价格歧视对患者福利的损害程度减轻,但是特需门诊患者和普通门诊患者的福利水平依旧是下降的。从保护患者福利的视角出发,政府应该进一步完善管制政策体系,限制特需门诊的发展。

大数据杀熟是否可以避免——基于演化博弈和仿真的分析

以节约公共资源和支持市场自由发展为出发点,建立平台与用户之间的演化博弈模型,探讨用户在可以自由切换平台的情境下,不同均衡点的形成条件及其稳定性。根据理论推导的条件,使用Octave进行数值仿真,以分析影响平台算法杀熟定价的因素,并确定不使用杀熟定价的理想状态所需满足的条件。同时,研究旨在探索除监管外,哪些措施可以帮助实现这一理想状态。研究结果表明,避免大数据杀熟并不一定需要依赖实时监控或罚款等手段,以市场化手段发展多个平台和鼓励平台竞争可能是最直接且可行的方法。

基于时变价格弹性矩阵的深谷电价多目标定价策略

随着碳中和、碳达峰目标的提出,构建高比例新能源的新型电力系统已成为未来能源电力的发展形态,由此导致的高比例新能源渗透使系统净负荷曲线呈现剧烈的波动性和显著的深谷特征,对电力系统安全运行以及供需平衡提出了新挑战。为此,提出了一种基于时变价格弹性矩阵的需求侧深谷电价多目标定价模型。首先,确立基于模糊隶属度的深谷时段划分方法,并利用贝叶斯判别法对时段划分结果进行合理性评估。其次,针对用户需求响应的动态性,建立具有时变特征的价格弹性矩阵模型衡量用户的响应程度。最后,以用户满意度和系统峰谷差作为待优化的两个目标,建立多目标混合整数规划的深谷电价定价模型,并用非支配排序遗传算法求解模型并得到其Pareto最优解。为了检验所提模型的有效性,将其应用于中国华东地区某省的实际场景进行仿真分析。结果表明,上述模型可在高比例新能源渗透情景下降低峰谷差,促进用户用电行为向深谷时段转移,缓解电力系统在深谷时段的运行压力。

大数据杀熟行为的反垄断法调整方法

大数据杀熟行为的反垄断法调整方法问题,是世界反垄断法研究中的热点问题。现有研究大多将其定性为价格歧视行为,这存在方向性的偏差。大数据杀熟行为本身并不排除、限制竞争,因此不符合价格歧视行为的构成要件和分析方法。本质上,大数据杀熟的主要损害是对消费者直接进行剥削,从每个消费者身上榨取每一分利润,而不是对竞争者进行排斥,因而属于过高定价行为。与此同时,大数据杀熟与传统的过高定价行为又存在一定差异,在其分析过程中必须根据这些特殊性,对传统反垄断法理论与规则进行必要的修正。采用反垄断法上关于过高定价行为的构成要件和分析方法认定大数据杀熟行为构成垄断行为的基本步骤是:其一,认定行为人拥有支配地位;其二,将杀熟行为认定为过高定价行为;其三,允许当事人提出合理的理由进行抗辩。其中在支配地位以及过高定价的认定上,大数据杀熟行为都具有一些传统产业中所没有的特点,需要依托反垄断法理与案例进行细致分析。

算法价格歧视下消费者感知背叛与应对策略分析

随着大数据的广泛应用,算法已经深入人们的日常生活中,但出现了较多针对消费者的算法价格歧视。基于归因理论与关系质量理论,通过实地调查的方式,检验分析算法价格歧视对消费者的感知背叛情况的影响机理。研究关系质量与价格敏感度的中介变量效应,来进一步探算法价格歧视和消费者感知背叛、蓄意归因的关系。研究显示,高算法价格歧视对消费者可以产生更强的蓄意归因,使消费者可以感受到更强的感知背叛,如果企业与消费者之间有着较高的关系质量,那么算法价格歧视将会引起消费者产生更强烈的感知背叛。

能力遮蔽、文凭排斥和身份符号:“第一学历现象”的社会学审思

当前,部分用人单位在招聘过程中注重考察求职者首次获得的高等教育文凭,并据此给予区别对待,这被称为“第一学历现象”。这一现象屡见不鲜且难以根除,说明其背后有深刻的社会根源,这就需要从社会学的角度对此现象的根源和危害进行深入剖析。在教育系统培养、分流与筛选过程中,高考作为重要的选拔机制,根据学生的学习能力,将他们分配到不同层次的高等院校接受本科教育。于是,“第一学历”成为了评判学生能力的重要指标。用人单位偏好名校本科“第一学历”,并将其作为职业门槛,形成了基于名校本科学历的文凭排斥。这使得“第一学历”在社会互动中逐步演变为一种社会身份符号。“第一学历现象”不仅造成就业歧视,还加剧基础教育阶段升学竞争,加深高校间的等级分化,制约个体奋斗从而削弱教育公平,固化学历“出身”的符号标签进而形成社会排斥,等等。消除“第一学历现象”,需要通过立法反对“第一学历”就业歧视,构建大学生综合素质评价档案系统,营造社会公正用人环境。

考虑混合补贴和消费者敏感的生鲜农产品供应链定价决策

在单个供应商和单个电商构成的生鲜农产品供应链系统中,引入消费者敏感系数、政府保鲜技术补贴额和电商绿色研发补贴率等参数,运用Stackelberg博弈对比分析了政府保鲜技术补贴、电商绿色研发补贴、混合补贴对供应链决策的影响。研究表明,在3种模式下,增加消费者对新鲜度或绿色度的敏感度有利于提高供应链成员利润和社会福利;在适度的消费者绿色度敏感下,政府或电商提供的补贴都有利于提升社会福利,且混合补贴最有利;混合补贴下的供应商投入保鲜努力、产品绿色度、产品需求以及供应商利润最高;在适度的电商绿色研发补贴率下,混合补贴对生鲜电商最有利,若绿色研发补贴率过高,则单一政府补贴更有利。

医疗服务价格改革与DRG付费改革相互关系研究——基于某三甲医院住院患者结算清单数据

目的:分析医疗服务价格改革与DRG付费改革的相互关系,探讨两者之间的共同作用,为政府决策和医院高质量发展提供参考。方法:基于2018—2022年样本医院610624例住院患者结算清单数据,采用结构变动度和灰色关联分析法对医院住院费用的结构变动度、结构变动度贡献率及关联度情况进行定量分析。结果:2018年以来,样本医院住院次均费用呈波动下降趋势,年均下降1.81%,其中药品费占比逐年下降,结构变动贡献率最高;治疗费、手术费相对上升,结构变动贡献率次之;但检验费、检查费占比相对上升,耗材费占比基本不变。结论:医疗服务价格改革联合DRG付费改革促进了医院医疗费用结构的优化,应进一步提升两者共同作用,加强两者互补关系,不断优化医院收入结构,助力医院高质量发展。

基于非刚性特征的发动机积碳程度判别模型

汽车发动机积碳的长期累积会引起发动机动力下降、油耗上升、排放性能降低等问题,对发动机及时的检测和清理可以有效缓解积碳造成的影响。本文提出了一种新的基于非刚性特征的模型,用于积碳程度的判别。首先,在模型中使用可变形卷积调整卷积核的偏移位置和偏移幅度,提高网络的有效感受野,提取非刚性特征信息;其次,根据核区域中像素的相关性,使用自适应指数度量池化核对神经元进行加权,以此捕获更好的细节特征信息;最后,添加基于自注意机制的特征增强模块,获取特征图的上下文信息。经过实验测试,本文方法的测试准确率为87.1%,各项指标相较原始模型平均提高2.5%,证明本文方法可以提取有效的积碳程度判别特征。

人工智能算法的法律问题与应对措施

随着人工智能技术的飞速发展,人工智能算法逐渐影响了人们的日常生活,但因算法黑箱、算法歧视、算法支配、算法垄断等法律问题使得算法在现实应用中直接影响立法决策的准确、司法决策的公正、行政监管的规范,也成为继个人信息保护和数据安全立法基本成形后,当前我国人工智能发展的主要风险防控与秩序信任议题。破解这些难题的路径在于明确算法立法的目的,完善算法立法的形式,构建算法立法的法律体系,从而更好应对人工智能算法风险。

算法价格歧视反垄断规制的逻辑与进路

算法价格歧视具有高度隐蔽性和技术性,具有损害消费者合法权益、遏制企业技术创新以及破坏市场竞争秩序三重威胁。对算法价格歧视行为施以反垄断规制具有正当性和必要性,但产生于传统商业模式下的反垄断法难以有效应对算法的异化风险,存在认定受限和监管失灵的现实问题。因此,需要转变规制思路,从立法和执法两个层面提出应对之策:立法方面,要拓宽行为主体的外延,改良损害后果的评估方法,明确正当理由的适用标准,从而解决算法价格歧视的反垄断认定难题;执法方面,可构建反垄断法和算法的二元监管体系,并同步探索消费者数据赋权的私人治理模式,多管齐下规制算法价格歧视,将其引向正确的轨道。

垄断势力视角下平台大数据杀熟的价格歧视机理

大数据杀熟问题近年来受到各界的广泛关注,政府出台了一系列有关大数据杀熟治理的政策文件。然而,诸多法规相互交叉、竞合,给监管执行造成了巨大的困难。大数据杀熟愈演愈烈,导致了消费者群体与涉事平台企业之间存在严重的信任危机。为了能更好地理解和治理大数据杀熟,本文深入分析了垄断势力视角下平台大数据杀熟的价格歧视机理。通过分析,揭示了大数据杀熟的经济逻辑为(:1)垄断势力是形成大数据杀熟的源泉(;2)大数据杀熟本质是不公平的高价价格歧视。在以上分析的基础上,本文对大数据杀熟的本质、认识误区和治理思路进行了分析,指出大数据杀熟治理的关键是反垄断和防欺诈。总之,本研究通过对大数据杀熟垄断势力下价格歧视机理的分析,厘清了大数据杀熟与价格歧视和精准营销的区别,从而为正确认识大数据杀熟和有效抑制大数据杀熟提供参考。

高速铁路客运票价最高限价调整机制研究

铁路客运票价市场化改革是铁路市场化运营的关键环节,建立健全高速铁路客运票价调整机制是铁路收益管理的核心要义。文章研究高速铁路客运票价最高限价调整机制,设计基于线路繁忙程度和区域经济发展水平的指标体系,利用Kmeans聚类算法、结合改进的通用匹配矩阵确立二者的匹配关系,并根据其在通用匹配矩阵中的所属区域,判断最高限价的调整方式,为高速铁路客运票价最高限价的合理化制定和调整提供理论依据。