基于电子商务平台的服务模式选择研究

随着电子商务的迅猛发展,提供优质的服务已成为电商企业获取竞争优势的主要手段。本文重点探究了电商平台与零售商之间服务模式的策略性选择问题。本文通过建立理论模型,量化比较四个服务模式即A模式(零售商承担服务)、B 模式(零售商将服务外包给第三方)、C模式(平台承担服务)和D模式(平台将服务外包给第三方)的特点得出最优决策。研究得到如下结论:在成本结构相同的情况下,C模式具有最高的服务水平和市场利润,而A模式和B模式能为顾客提供最低的市场价格。平台和供应商更倾向于自己来提供服务,分散的服务模式会降低服务水平,但当商家自身服务成本较高时,他们更愿意让另一方或较低服务成本的第三方作为服务提供方。另外,本文还发现在A模式和B模式下,平台收取的佣金比例随着需求对服务的敏感程度的增加而降低,而C模式和D模式则相反。     

基于排队系统的偏好差异性顾客服务策略分析

在服务商为不同偏好顾客提供差异性服务的排队系统中,其收益受到需求规模、顾客类型等因素影响,如何制定策略才能达到服务特定类型顾客并获取最大收益的目的？本文以服务时间与效果正相关的顾客密集型服务为背景,基于M/M/1模型对服务商为两种偏好顾客提供两种服务的情景进行研究,并将从偏好服务所获基准效用相对较低、较高的顾客分别定义为1类、2类顾客。结果表明,①随着潜在顾客规模的增加,最优策略所适用的3种基本策略依次为公平策略、优先服务2类顾客的策略以及仅服务2类顾客的排他性策略;②3种基本策略的适用范围仅与1类顾客的服务选择标准相关;③在优先服务某类顾客的策略中,有效到达速率及服务速度由另一类顾客的特征决定。     

Queueing models for appointment-driven systems

Many service systems are appointment-driven. In such systems, customers make an appointment and join an external queue (also referred to as the “waiting list”). At the appointed date, the customer arrives at the service facility, joins an internal queue and receives service during a service session. After service, the customer leaves the system. Important measures of interest include the size of the waiting list, the waiting time at the service facility and server overtime. These performance measures may support strategic decision making concerning server capacity (e.g. how often, when and for how long should a server be online). We develop a new model to assess these performance measures. The model is a combination of a vacation queueing system and an appointment system.     

To wait or not to wait: Strategic behaviors in an observable batch-service queueing system

This paper deals with an observable batch service queueing system in which customers rationally choose whether to form a batch with another customer or not, in addition to deciding whether or not to join the queue. When choosing whether to form a batch, a customer in an incomplete batch decides on an optimal waiting time for the next customer to arrive and share the service fee. When choosing whether to join the queue, customers follow a threshold strategy, which depends on the strategy identified in the former game.     

When should service firms provide free experience service?

By providing a free experience service, a service firm can attract more uninformed customers. However, it could reversely effect the delay-sensitive, informed customers’ decision. In this paper, we study a priority queueing system with free experience services. We study the customer behavior in equilibrium after we derive the expected customer waiting time. We then construct the service firm’s revenue function and obtain an optimal strategy for the service firm. Our results suggest that when the market size of informed customers is relatively small, the firm should consider providing free experience services for uninformed customers. Conversely, if the demand rate of potential informed customers is quite high, the firm should ignore uninformed customers.     

A multi-depot period vehicle routing problem arising in the utilities sector

This paper considers the resource planning problem of a utility company that provides preventive maintenance services to a set of customers using a fleet of depot-based mobile gangs. The problem is to determine the boundaries of the geographic areas served by each depot, the list of customers visited each day and the routes followed by the gangs. The objective is to provide improved customer service at minimum operating cost subject to constraints on frequency of visits, service time requirements, customer preferences for visiting on particular days and other routing constraints. The problem is solved as a Multi-Depot Period Vehicle Routing Problem (MDPVRP). The computational implementation of the complete planning model is described with reference to a pilot study and results are presented. The solution algorithm is used to construct cost-service trade-off curves for all depots so that management can evaluate the impact of different customer service levels on total routing costs.     

Estimating characteristics of queueing networks using transactional data

We are motivated by queueing networks in which queues are difficult to observe but services are easy to record. Our goal is to estimate the queues from service data. More specifically, we consider an open queueing network with Poisson external arrivals, multi‐server stations, general service times and Markovian switches of customers between stations. Customers' transitions between stations may be either immediate or of exponentially distributed durations. Each customer is supplied with an Identification Number (ID) upon entering the network. Operational data is collected which includes transaction times (starts and terminations of services) and ID's of served customers. Our objective is to estimate the evolution of the queues in the network, given the collected data. We cover estimation at both end of busy periods and in real time. The applicability of the theory is demonstrated by analyzing a service operation. This revised version was published online in June 2006 with corrections to the Cover Date.     

Customer equilibrium and optimal pricing in an M/G/1 queue with heterogeneous rewards and waiting cost rates

We consider an unobservable M/G/1 queue in which customers are allowed to join or balk upon arrival. The service provider charges the same admission fee to all joining customers. All joining customers receive a reward from completion of service and incur a waiting cost. The reward and waiting cost rate are random, however the customers know their own values upon arrival. We characterize the customer’s equilibrium strategy and the optimal prices associated with profit and social welfare maximization.     

考虑线下渠道时销售商在团购网站上的最优销售策略研究

基于团购网站和销售商的典型合作模式,考虑了团购网站和线下市场的相互影响,用非线性优化理论为基础以销售商制定团购上限和团购项目定价为决策变量,考虑团购价格和最低团购数量的约束条件,建立模型优化,求解出销售商推出团购项目的最优策略。考虑到团购网站下限和团购网站销售成本以及网上销售的广告效用,分析了销售商是否应该制定团购上限,如何结合团购项目定价制定团购上限。探讨了在线低价限量销售的优势,以及顾客转移购买率和团购下限对销售商策略选择的影响。通过和单一线下渠道的最优销售策略相比较,得出销售商推出团购项目的前提条件。同时为团购网站运营商如何引导销售商推出低价团购项目提供了管理启示。     

Consumer preference and service quality management with RFID

The importance of accurately measuring consumer preference for service quality management to firms in exceedingly competitive environments where customers have an increasing array of access to information cannot be overstated. There has been a resurgence of interest in consumer preference measurement and service quality management, specifically real-time service management, as more data about customer behavior and means to process these data to generate actionable policies become available. Recent years have also witnessed the incorporation of Radio-Frequency Identification (RFID) tags in a wide variety of applications where item-level information can be beneficially leveraged to provide competitive advantage. We propose a knowledge-based framework for real-time service management incorporating RFID-generated item-level identification data. We consider the economic motivations for adopting RFID solutions for customer service management through analysis of service quality, response speed and service dependability. We conclude by providing managerial insights on when and where managers should consider RFID-generated identification information to improve their customer services.     

The MAP/(PH/PH)/1 queue with self-generation of priorities and non-preemptive service

Customers arriving according to a Markovian arrival process are served at a single server facility. Waiting customers generate priority at a constant rate γ$\gamma$; such a customer waits in a waiting space of capacity 1 if this waiting space is not already occupied by a priority generated customer; else it leaves the system. A customer in service will be completely served before the priority generated customer is taken for service (non-preemptive service discipline). Only one priority generated customer can wait at a time and a customer generating into priority at that time will have to leave the system in search of emergency service elsewhere. The service times of ordinary and priority generated customers follow PH-distributions. The matrix analytic method is used to compute the steady state distribution. Performance measures such as the probability of n consecutive services of priority generated customers, the probability of the same for ordinary customers, and the mean waiting time of a tagged customer are found by approximating them by their corresponding values in a truncated system. All these results are supported numerically.     

Data-stories about (im)patient customers in tele-queues

Credible queueing models of human services acknowledge human characteristics. A prevalent one is the ability of humans to abandon their wait, for example while waiting to be answered by a telephone agent, waiting for a physician’s checkup at an emergency department, or waiting for the completion of an internet transaction. Abandonments can be very costly, to either the service provider (a forgone profit) or the customer (deteriorating health after leaving without being seen by a doctor), and often to both. Practically, models that ignore abandonment can lead to either over- or under-staffing; and in well-balanced systems (e.g., well-managed telephone call centers), the “fittest (needy) who survive” and reach service are rewarded with surprisingly short delays. Theoretically, the phenomenon of abandonment is interesting and challenging, in the context of Queueing Theory and Science as well as beyond (e.g., Psychology). Last, but not least, queueing models with abandonment are more robust and numerically stable, when compared against their abandonment-ignorant analogues. For our relatively narrow purpose here, abandonment of customers, while queueing for service, is the operational manifestation of customer patience, perhaps impatience, or (im)patience for short. This (im)patience is the focus of the present paper. It is characterized via the distribution of the time that a customer is willing to wait, and its dynamics are characterized by the hazard-rate of that distribution. We start with a framework for comprehending impatience, distinguishing the times that a customer expects to wait, is required to wait (offered wait), is willing to wait (patience time), actually waits and felt waiting. We describe statistical methods that are used to infer the (im)patience time and offered wait distributions. Then some useful queueing models, as well as their asymptotic approximations, are discussed. In the main part of the paper, we discuss several “data-based pictures” of impatience. Each “picture” is associated with an important phenomenon. Some theoretical and practical problems that arise from these phenomena, and existing models and methodologies that address these problems, are outlined. The problems discussed cover statistical estimation of impatience, behavior of overloaded systems, dependence between patience and service time, and validation of queueing models. We also illustrate how impatience changes across customers (e.g., VIP vs. regular customers), during waiting (e.g., in response to announcements) and through phases of service (e.g., after experiencing the answering machine over the phone). Our empirical analysis draws data from repositories at the Technion SEELab, and it utilizes SEEStat—its online Exploratory Data Analysis environment. SEEStat and most of our data are internet-accessible, which enables reproducibility of our research.     

OR and the management of electronic services

This review paper is meant to provide some insight to the relation between operations research and the management of electronic services. We use the term electronic services, within the broader e-business context, to refer to any service that is delivered to the customer via electronic means, mainly the Internet as a new channel to communicate with customers, but also through mobile and other digital communications. During the last years we have experienced an explosion in the development of electronic services, which is creating abundant opportunities for operations research (OR) applications, required to empower several types of technology-mediated interactions, exploit the large-scale digital data sources, and automate the recurring operational decisions. In this paper we summarise the various aspects in which operations research may support the management of electronic services, taking into account the different characteristics of alternative electronic media, such as the Internet, mobile communications, interactive television etc.     

Waiting-Time Asymptotics for the M/G/2 Queue with Heterogeneous Servers

In this paper, we consider a c-server queuing model in which customers arrive according to a batch Markovian arrival process (BMAP). These customers are served in groups of varying sizes ranging from a predetermined value L through a maximum size, K. The service times are exponentially distributed. Any customer not entering into service immediately orbit in an infinite space. These orbiting customers compete for service by sending out signals that are exponentially distributed with parameter . Under a full access policy freed servers offer services to orbiting customers in groups of varying sizes. This multi-server retrial queue under the full access policy is a QBD process and the steady state analysis of the model is performed by exploiting the structure of the coefficient matrices. Some interesting numerical examples are discussed.     

Staffing a service system with appointment-based customer arrivals

Appointment systems are widely used to facilitate customers’ access to services in many industries such as healthcare. A number of studies have taken a queueing approach to analyse service systems and facilitate managerial decisions on staffing requirements by assuming independent and stationary customer arrivals. This paper is motivated by the observation that the queueing-based method shows relatively poor performance when customers arrive according to their appointment times. Because customer arrivals are dependent on their appointment times, this study, unlike queueing-based methods, conducts a detailed analysis of appointment-based customer arrivals instead of making steady-state assumptions. We develop a new model that captures the characteristics of appointment-based customer arrivals and computes the probability of transient system states. Through the use of this model, which relaxes stationary and independent assumptions, we propose a heuristic algorithm that determines staffing requirements with aims to minimizing staff-hours while satisfying a target service level. The simulation results show that the proposed method outperforms the queueing-based method.     

带有负顾客且具有反馈的M/M/1/N工作休假排队

研究带反馈的且具有正、负两类顾客的M/M/1/N工作休假排队模型.工作休假策略为空竭服务多重工作休假.负顾客一对一抵消队首正在接受服务的正顾客(若有),若系统中无正顾客时,到达的负顾客自动消失,负顾客不接受服务.完成服务的正顾客以概率p(0相似文献   

Retrial queue with discipline of adaptive permanent pooling

A novel customer service discipline for a single-server retrial queue is proposed and analysed. Arriving customers are accumulated in a pool of finite capacity. Customers arriving when the pool is full go into orbit and attempt to access the service later. It is assumed that customers access the service as a group. The size of the group is defined by the number of customers in the pool at the instant the service commences. All customers within a group finish receiving the service simultaneously. If the pool is full at the point the service finishes, a new service begins immediately and all customers from the pool begin to be served. Otherwise, the customer admission period starts. The duration of this period is random and depends on the number of customers in the pool when the admission period begins. However, if the pool becomes full before the admission period expires, this period is terminated and a new service begins. The system behaviour is described by a multi-dimensional Markov chain. The generator and the condition of ergodicity of this Markov chain are derived, and an algorithm for computing the stationary probability distribution of the states of the Markov chain is given. Formulas for computing various performance measures of the system are presented, and the results of numerical experiments show that these measures essentially depend on the capacity of the pool and the distribution of the duration of the admission period. The advantages of the proposed customer service discipline over the classical discipline and the discipline in which customers cannot enter the pool during the service period are illustrated numerically.     

交货期敏感信息不对称下电子零售商的渠道决策

在顾客对产品的交货期敏感及敏感度信息私有的背景下,研究一个拥有网络零售平台电子零售商的一个产品渠道决策——自营(又称自主销售)或开放平台(又称外租平台给制造商直销)。求解了电子零售商自营时差别定价和统一定价策略下的最优激励策略(价格与交货期的设定),并分析了开放平台时收益分享比例对制造商定价及交货期策略的影响。通过比较自营和开放平台时电子零售商的最大收益,给出电子零售商最优的渠道决策流程图。研究结果表明,当产品采购成本高时,电子零售商将采取自营;当采购成本低且收益分享比例低时,电子零售商将开放平台。最后,借助数值实验分析了顾客类型和私有的延迟成本率对渠道决策的影响。     

有Bernoulli休假和可选服务的M/G/1重试反馈排队模型

考虑具有可选服务的M/G/1重试反馈排队模型,其中服务台有Bernoulli休假策略.系统外新到达的顾客服从参数为λ的泊松过程.重试区域只允许队首顾客重试,重试时间服从一般分布.所有的顾客都必须接受必选服务,然而只有其中部分接受可选服务.每个顾客每次被服务完成后可以离开系统或者返回到重试区域.服务台完成一次服务以后,可以休假也可以继续为顾客服务.通过嵌入马尔可夫链法证明了系统稳态的充要条件.利用补充变量的方法得到了稳态时系统和重试区域中队长分布.我们还得到了重试期间服务台处于空闲的概率,重试区域为空的概率以及其他各种指标.并证出在系统中服务员休假和服务台空闲的时间定义为广义休假情况下也具有随机分解特征.     

Analysis of MAP/PH1,PH2/1 queue with vacations and optional secondary services

In this paper we study a queueing model in which the customers arrive according to a Markovian arrival process (MAP). There is a single server who offers services on a first-come-first-served basis. With a certain probability a customer may require an optional secondary service. The secondary service is provided by the same server either immediately (if no one is waiting to receive service in the first stage) or waits until the number waiting for such services hits a pre-determined threshold. The model is studied as a QBD-process using matrix-analytic methods and some illustrative examples are discussed.