分享经济下竞争市场双边网约车平台定价策略

针对用户与司机在单归属环境下网约车平台进行交易过程,运用Salop模型确定用户与司机在双边市场中的分布,构建两个网约车平台的Stackelberg博弈模型,研究网约车平台定价策略、市场竞争强度和平台成本对网约车平台利润、消费者剩余和生产者剩余的影响规律。研究表明,平台成本增加导致占优平台与劣势平台的服务价格均提高,从而引致自身平台双边用户减少,竞争平台的双边用户数量增加,且对劣势平台的影响更大。市场竞争强度小时,劣势平台应效仿占优平台进行中等定价,此时利润取得最大值;当竞争强度适中时,劣势平台应采取低价策略,占据低价敏感用户的细分市场;当市场竞争强度十分激烈时,劣势平台应该提升自身服务质量,针对市场中高水平的用户进行服务,实现最优利润。此外,劣势平台可以通过控制平台运营成本提高利润并实现消费者剩余与生产者剩余的最大化。     

聚合模式下网约车市场的定价策略研究

针对聚合模式给网约车市场带来的收益分配和价格竞争问题,引入平台抽成和出行服务商服务差异刻画聚合模式下网约车市场的特征,构建了聚合平台和两服务商的斯坦伯格博弈模型,探讨了在聚合模式下网约车市场的定价均衡。随后引入平台补贴定价策略,分析了补贴策略对市场均衡定价以及聚合平台、出行服务商期望收益的影响。研究表明：聚合模式下出行服务商服务差异是影响平台抽成比例和网约车市场服务定价的重要因素,对聚合平台和出行服务商的期望收益有双向影响;平台对出行者的价格补贴提高了补贴前网约车市场的服务定价,导致平台抽成增加;采用合理的补贴定价策略可以有效提升出行服务商和聚合平台的收益,同时改进社会福利。     

需求波动下考虑乘运供应能力的网约车平台动态定价

“共享经济”理念下的网约车平台需求具有随机发生和波动变化的特点.针对乘车需求波动导致不同供需状态下的网约车平台定价问题,运用最优控制方法,以平台期望收益最大化为目标,构建乘运供应能力下的平台动态定价模型,并基于庞特里亚金极大值原理及模型推导,求得最优动态价格解以及平台乘运供应率和需求率的变化轨迹.研究表明:网约车平台的最优价格动态影响乘运供应,且随着市场乘车需求的波动而动态变化;尤其是乘车高峰需求时,最优动态价格将显著减少乘车需求订单的延误.最后,通过数值仿真验证模型结论并进一步探讨平台服务质量和市场乘车需求变化系数对最优价格和期望收益的影响.     

加强电信管制实现有效竞争

电信管制的主要内容:市场准入管制;互联互通管制;普遍服务管制;资费管制;资源管制;服务质量管制;技术标准管制。 独立管制机构是既独立于企业又相对独立于政府的管制机构,决策独立和财务独立是其重要特征,独立管制机构的经费主要来自许可证费和资源使用费等。国外管制机构的管制领域一般既包括传统电信,也包括有线电视,我国目前的情况是两者分离,不适应三网融合的趋势 国外引入竞争时,一般是立法在先,大多数发达国家均制定了新的电信法规。我国应尽快出台“电信法”。 不对称管制是从垄断向竞争转变的过渡性手段,依据是不对称竞争,即存在市场支配或主导力量。中国电信二次分拆后,原有不对称管制受到质疑,有人认为从收入市场份额计,目前没有主导经营者,应取消不对称管制。鉴于竞争的不对称程度有所减弱,因而有必要放松不对称管制。如:取消对他们的业务领域限制而改为业务帐务独立要求;对于长途通信,可以考虑取消不对称管制。     

我国电信管制改革七大悬念

当市场竞争达到一定程度以后,很难保证电信管制的有效性,最终只能放松资费的管制。 对中国电信和中国网通进行的新一轮拆分和重组,旨在促进市话竞争。但根据国际经验,可以预见这种改革很难达到预期的目的,不应该对新一轮电信拆分带给本地竞争的影响有过高的期望。 由于市场竞争尤其是替代竞争的发展,非对称管制有可能演变为阻碍竞争的因素。 从根本上解决互联互通问题,需要进一步进行资费平衡、增加基于网络的竞争、确定更合理的结算定价原则、确定成本的补偿原则。 我国3G通信系统的发展需尽快解决的重大问题:标准的选择问题;3G牌照或频谱的发放问题;未来管制方式问题。 下一步改革需要首先颁布普遍服务管理条例,明确普遍服务政策的目标、职能、融资机制、成本补偿办法以及管理体制。 实现政监分离的制度,建立独立的政府管制机构,将现有的电信管制职能进行整合。     

竞争环境下两个B2C服务共享平台的均衡决策

针对服务共享中某个时段内可能出现供小于需或供大于需的情形(即情形S或情形G),研究竞争环境下两个B2C服务共享平台的最优定价与服务水平决策.首先,构建每种情形下两个平台的Nash博弈模型,并通过求解模型得到均衡结果,包括服务价格、服务水平、实际需求和平台利润.进一步地,分析不同情形下共享产品投放量对均衡结果的影响.研究结果表明:若两个平台总的共享产品投放量小于一个阈值,则情形S下一个平台的最优服务价格与共享服务水平均大于情形G下该平台的最优服务价格与服务水平.若两个平台总的共享产品投放量满足一定条件,则情形S下一个平台的利润大于情形G下该平台的利润.当消费者针对共享产品的平均使用量较大时,情形S下的社会福利大于情形G下的社会福利.     

网约车任务分配系统优化

网约车是一种广泛应用的共享移动应用, 其核心问题是将出租车请求分配给具有不同目标的司机, 尽管对网约车的任务分配进行了广泛的研究, 但在很大程度上忽视了司机之间收入的公平性, 由于优化视角的短视和分配技术的耗时, 先行者对网约车公平任务分配的研究在公平性、效用性方面还存在不足. 在本文中, 提出了公平分配学习(LAF)方法, 它既优化了效用又优化了公平性的高效任务分配方案, 采用强化学习以整体的方式进行分配, 并提出一套加速技术, 以实现大规模数据的快速公平分配. 实验结果表明, 公平分配学习方法在公平性、效用性和效率方面分别比现有水平高出86.7%、29.1%和797%.     

基于深度强化学习的智联网汽车感知任务分配

随着智能/辅助/自动驾驶以及电动汽车技术的飞速发展,当前智联网汽车配备越来越多的传感器,拥有越来越强大的计算、存储和通信能力.作为智联网汽车中重要一类,出租车、滴滴等网约车(Mobility-on-demand vehicles)具有城市覆盖规模大和粒度细,以及空闲时间充足的优点.因此,利用这些智联网汽车现有的移动感知...     

具有网络外部效应的三度价格歧视研究

通过建立两厂商和两子市场的两阶段博弈模型,分析具有网络外部效应的寡头竞争市场厂商实施三度歧视定价的产出、价格和社会福利问题,研究结果表明:厂商通过歧视定价提高了强市场的价格,相应降低了弱市场的价格,虽然总产出没有改变,但却减少了社会总福利.     

基于深度强化学习的网约车动态路径规划

随着移动互联网的快速发展,许多利用手机App打车的网约车平台也应运而生.这些网约车平台大大减少了网约车的空驶时间和乘客等待时间,从而提高了交通效率.作为平台核心模块,网约车路径规划问题致力于调度空闲的网约车以服务潜在的乘客,从而提升平台的运营效率,近年来受到广泛关注.现有研究主要采用基于值函数的深度强化学习算法(如deep Q-network,DQN)来解决这一问题.然而,由于基于值函数的方法存在局限,无法应用到高维和连续的动作空间.提出了一种具有动作采样策略的执行者-评论者(actor-critic with action sampling policy,AS-AC)算法来学习最优的空驶网约车调度策略,该方法能够感知路网中的供需分布,并根据供需不匹配度来确定最终的调度位置.在纽约市和海口市的网约车订单数据集上的实验表明,该算法取得了比对比算法更低的请求拒绝率.     

A method for real-time trajectory monitoring to improve taxi service using GPS big data

As taxi service is supervised by certain electronic equipment (e.g., global positioning system (GPS) equipment) and network technique (e.g., cab reservation through Uber in USA or DIDI in China), taxi business is a typical electronic commerce mode. For a long time, taxi service is facing a typical challenge, that is, passengers may be detoured and overcharged by some unethical taxi drivers, especially when traveling in unfamiliar cities. As a result, it is important to detect taxi drivers’ misbehavior through taxi’s GPS big data analysis in a real-time manner for enhancing the quality of taxi services. In view of this challenge, an online anomalous trajectory detection method, named OnATrade (pronounced “on a trade,” which means activities in a taxi trade on the fly), is investigated in this paper for improving taxi service using GPS big data. The method mainly consists of two steps: route recommendation and online detection. In the first step, route candidates are generated by using a route recommendation algorithm. In the second step, an online anomalous trajectory detection approach is presented to find taxis that have driving anomalies. Experiments evaluate the validity of our method on large-scale, real-world taxi GPS trajectories. Finally, several value-added applications benefiting from big data analysis over taxi’s GPS data sets are discussed for potential commercial applications.     

MTO型供应链的价格/交货期协商支持模型

针对MTO(make-to-order)供应链环境下制造商与供应商的多个订单的价格/交货期协商问题，基于供应链伙伴间关系是竞争性合作的特点，提出一种新的两阶段协商议程．在合作性协商阶段，中介者利用模拟退火算法帮助制造商和供应商寻找最小化供应链总成本的交货期预协议点；制造商和供应商在此基础上基于整合效用的思想调整价格议题的保留值和期望值．在竞争性协商阶段双方逐步让步，就价格达成协议．实验表明，该协商议程能够获得近似最优的社会福利，达成对协商人双赢的方案．该协商议程能够有效应用于供应链协调和B2B在线市场．     

Analysing complaint intentions in online shopping: the antecedents of justice and technology use and the mediator of customer satisfaction

Complaint behaviours are the key to the competition in an online market when service quality is a major concern of consumers. An understanding of complaint intentions can provide insight into a negative service experience and in turn, effectively redress consumer's problems. It is our purpose to examine the determinants of complaint intentions in the online shopping. When online consumers essentially involve the purchase of products/services and the use of web-based technologies, two major issues particularly arise in this context, exchange behaviour and technology use. This study thus integrates justice perception and expectation–confirmation model (ECM) of information system continuance to understand customer satisfaction and in turn, complaint intentions. Data were collected for online consumers with negative service experiences. The results of testing the structural model indicated that distributive and interactional justices significantly contribute to customer satisfaction and complaint intentions, but procedural justice does not. ECM-based features, such as perceived usefulness, are all important in determining customer satisfaction and complaint intentions. The implications for managers and scholars are further discussed.     

Pricing and brokering services over interconnected IP networks

In this paper we consider an IP-based communication platform, characterized by a novel architectural model where barrier-free business and market interactions can be performed. We assume that the network is able to deliver application services which need of network service performance guarantees. In this scenario, we present the concept of the network commodity that is traded in the marketplace among network service providers, application service providers and customers. Moreover, we use this concept to define a new usage-based tariff model. Then, we especially focus on the activity of the so-called Network Resource Brokers, which have the goal of finding the end-to-end inter-domain path to deliver an application service that maximizes the users' benefit, in terms of price and perceived service level. In this regard, we present a QoS-and-price based inter-domain routing algorithm, analyze its computational complexity, and show its effectiveness in a selected simulation scenario.     

Managing feature interactions between distributed SIP call control services

The Session Initiation Protocol (SIP) is widely used as a call control protocol for Voice over IP (VoIP), and indeed commercial implementations are readily available off-the-shelf. SIP supports flexible service provisioning not only through third parties, but also end-users. Laboratory experience shows that as these services are interworking they are subject to the feature interaction problem. Feature interactions may considerably delay service deployment and hence are a threat to rapid service provisioning.This paper investigates the feature interaction problem in SIP-based services and investigates the application of a pragmatic approach. This runtime approach does not require any detailed information about the services and hence can be applied in a competitive market. Furthermore, the technique is particularly strong in handling interactions between distributed services – a key characteristic of SIP-based services. Moreover, the approach is fully distributed without any centralised components, and includes detection and resolution of feature interactions.     

Getting closer and experiencing together: Antecedents and consequences of psychological distance in social media-enhanced real-time streaming video

Social media services such as YouTube and Flickr have become online necessities for millions of users worldwide. Social media are online services that enable users to share contents, opinions, and perspectives that support communication with other users. Social media places an emphasis on the shared experience between users, which we call co-experience. However, the online characteristics of social media increase psychological distance between users, which, in turn, results in a decrease in the quality of co-experience. Hence, as the goal of this study, we theoretically modeled and empirically verified the antecedents and user experience-based consequences of psychological distance in a social media-enhanced real-time streaming video service. In order to reduce psychological distance, we introduced two system elements: inhabited space (the degree of being situated in context and in a meaningful place) and isomorph effects (the degree of preserving the structure of a user’s actions). We constructed a social media-enhanced real-time streaming video service prototype and conducted a field experiment with actual social media users. The prototype, which streamed a live baseball game, enabled users to simultaneously view the game from remote locations and to interact with each other through cheering tools. The results indicate that inhabited space and isomorph effects reduce psychological distance between users, and this, in turn, enhances co-experience. This paper ends with theoretical as well as practical implications of the study.     

Electric Power Network Oligopoly as a Dynamic Stackelberg Game

Over the last two decades, the electricity industry has shifted from regulation of monopolistic and centralized utilities towards deregulation and promoted competition. With increased competition in electric power markets, system operators are recognizing their pivotal role in ensuring the efficient operation of the electric grid and the maximization of social welfare. In this article, we propose a hypothetical new market of dynamic spatial network equilibrium among consumers, system operators and electricity generators as solution of a dynamic Stackelberg game. In that game, generators form an oligopoly and act as Cournot-Nash competitors who non-cooperatively maximize their own profits. The market monitor attempts to increase social welfare by intelligently employing equilibrium congestion pricing anticipating the actions of generators. The market monitor influences the generators by charging network access fees that influence power flows towards a perfectly competitive scenario. Our approach anticipates uncompetitive behavior and minimizes the impacts upon society. The resulting game is modeled as a Mathematical Program with Equilibrium Constraints (MPEC). We present an illustrative example as well as a stylized 15-node network of the Western European electric grid.