Ramifications of Monitoring Service Quality Through Passively Solicited Customer Feedback*

It is common for service providers to collect data from customers as part of efforts to monitor quality. Often, this data is passively collected, meaning (a) any solicitation of feedback is done without direct customer interaction, and (b) the customer initiates any response given. Examples include customer comment cards, toll-free telephone numbers, and comment links on World Wide Web pages. This article compares passive data collection with active methods (e.g., interviews and mail surveys). Passive methods generally have lower response rates and are inherently biased, but have cost and sample frame advantages when used to monitor quality on a continuous basis. Despite the biased nature of passive methods, this article describes the successful validation of a common customer-response model with passively collected empirical data. The model is expanded to consider the impact of complaint and compliment solicitation on customers' evaluation of the service provider. Results show that this impact is negative, and that customers who spontaneously register complaints generally record higher ratings of the service provider than customers who complain in response to a complaint solicitation. Discussion and conclusions are given.     

A Staged Service Innovation Model*

Drawing from the new product development (NPD) literature, service quality literature (SERVQUAL), and empirically grounded research with 53 service innovation decision makers, we develop a staged service innovation model (SIM) for decision makers. We tested the model using empirical data from 329 firms across five industries. The empirical results show that integrating prelaunch service quality training into new service development process leads to successful service innovation. The model developed in this article can be used as a decision support tool and diagnostic model for assessing service innovation ideas, evaluating performance of ongoing service innovations, allocating resources, and improving success rate of service innovations. Decision makers can use the measures developed in this study as a checklist to identify their strengths in delivering service quality to their own customers as well as areas of improvement. This article extends service innovation research by combining NPD and service quality development into a single study and opens the door to further work that could help improve the success rate of service innovations. The model can serve as a base model for future research extensions in service innovation research. A major takeaway for the academic reader is that the SIM demonstrates the value of using the SERVQUAL literature to understand how best to provide excellent quality that results in more fully satisfied customers and, ultimately, improved service performance.     

服务质量决定要因顾客满足和行动意图的影响--在中国服务产业的应用

为维持现有顾客和创造新顾客,服务企业必须知道怎样实施服务质量战略来增加顾客满足和行动意图,因为服务质量、顾客满足和顾客行动意图之间存在着因果关系.本研究把整体服务质量分解为相互作用质量、物理环境质量、结果质量三个决定要因,并对服务质量决定要因对顾客满足和行动意图的影响进行了研究,实证检验在中国服务产业中进行.对研究模型的验证结果支持本研究提出的所有因果假设,即构成整体服务质量的三个决定要因对顾客满足具有显著的正向影响,顾客满足对行动意图具有显著的正向影响.而且,对于中国顾客来说,服务质量决定要因对顾客满足的相对影响力依次为"结果质量"＞"相互作用质量"＞"物理环境质量".     

基于“云排队”的经济效益分析

随着各种云智能排队预约系统的推出，顾客“排队难”的问题得到了极大的缓解。其简便的操作方式，受到了大量商家与顾客的好评。本文基于当下热门服务行业的运营模式，建立排队博弈模型，从理论上分析了“云排队”平台对顾客以及服务商的影响。本文主要得到了以下几个结果：(1) 给出了两类顾客的纳什均衡策略(包括进队策略与最优到达间隔)；(2) 发现当前的预约机制能够提高“线上”顾客的效用，并刺激更多的线上顾客购买该产品，但同时也降低了“线下”顾客的进队意愿；(3) 发现在云排队机制下服务商的收益将大大提高，同时该机制将刺激服务商收取更高的服务费用。     

Increasing productivity in exponential queues by server-sharing

This paper sets out to investigate the effects of productivity improvements on the operation of queueing systems, the most noticeable effect being a change in the quality of the service that is provided to customers. A bulk-service queueing model is developed and solved, in which the average service time per batch is assumed to increase with the batch size, and the implications for service quality are discussed. The analysis shows that, under certain conditions, the benefits of group service over those of serving customers individually are quite substantial.     

基于SC-RS的我国工业电力用户价值画像模型研究

电力用户价值画像对于提升我国供电企业的营销服务资源配置效能,提高智慧营销管理水平,从而最大化撬动供电企业的综合效益具有重要的现实意义。现有工业电力用户价值画像模型评级指标体系未能反映国家最新能源政策对我国工业企业的发展要求、无法良好应对现实电力用户用电数据的稀疏性,以及对于新用户价值等级预测的准确性存在提高空间。针对以上问题,本文集成数据挖掘技术中的谱聚类算法(Spectral Clustering, SC)与智能算法中的粗糙集理论(Rough Set, RS),构建了一种优化的数据驱动型工业电力用户价值画像模型,简称SC-RS模型。新模型构造围绕“知识萃取-知识推理-知识服务”的逻辑脉络展开,首先,在“知识萃取”部分,结合我国“碳达峰”目标与“碳中和”愿景,构建优化的我国工业电力用户价值评级指标体系,此外,采用谱聚类技术,并联合网格搜索策略,提炼用户价值等级信息情报;然后,在“知识推理”部分,应用粗糙集理论,继承已有三维规则挖掘框架,构建基于ChiMerge离散法与变异系数的行约简、基于系统依赖度的列约简、基于对象确定性因子的格约简,以及基于规则强度的规则提取方案这一拓展的四维规则挖掘模型,生成用户价值等级规则库;最后,在“知识服务”部分,一方面运用用户价值等级信息情报,构造价值决策系统,以及描摹群体用户价值画像,另一方面运用规则库,呈现可理解的价值知识,以及构造价值等级规则软分类器,实现新用户价值等级预测与个体价值画像描摹。为了展示模型的应用路径与具体步骤,采用实际工业电力用户数据,对模型开展实证研究。结果表明,SC-RS模型构建的评级指标体系紧跟我国电力行业最新发展动态,具有较强先进性;模型能够兼容稀疏性数据,对数据要求低;构造的粗糙四维规则挖掘模型可行有效,且对新用户价值等级的预测准确性高。综上,SC-RS模型能够对电力用户大数据实现价值情报挖掘与利用,是为我国电力企业智慧营销管理赋能的有力工具。     

Customer service competencies: a global look

The purpose of the study was to identify competencies needed by those providing service to today's customers. A total of 460 service providers were interviewed from thirty-two different organizations in North America and twenty-six organizations in Asia and Europe. Based on 2.825 critical incidents, five major factors were identified to create the SERVE model: See the ‘big picture’ and how customer service fits into it; Establish an authentic human connection with each customer; Render timely, accurate and thorough service; Value and respond to unique customer needs; and Extend a hand to repair and strengthen relationships with customers who are upset or angry. Similarities and differences among the different geographic regions and among the different respondent types were noted. Implications for HRD practice and future research were discussed.     

基于体验的顾客满意度模型研究——针对团队旅游的实证研究

在服务业中,顾客亲自参与服务的生产与消费,服务就是一种顾客体验,服务的本质和特性决定了顾客体验对于服务估价产生重要影响。在文献回顾的基础上,建立了基于体验的顾客满意度模型,并通过对北京、天津、西安、南京、杭州5个城市共计976名团队旅游消费者群体的实证调研,验证了模型的合理性。最后,为旅游企业提出了建议。     

Capacity rationing in rental systems with two customer classes and batch arrivals

Service differentiation is an emerging method to improve profit and to better serve high-priority customers. Such an approach has recently been introduced by one of Europe's leading rail cargo companies. Under this approach, customers can choose between classic and premium services. Premium service is priced above classic service and premium customers receive a service guarantee which classic customers do not receive. The company has to decide under which conditions it should ration its fleet capacity to classic customers in order to increase service of premium customers. We model such a situation as a batch-arrival queuing loss system. We describe the model, solve it optimally, and derive quantities of interest such as service probabilities. We further analyze it by performing numerical experiments based on the data from the company that motivated our research. We show that the potential of capacity rationing can be substantial in situations like the one we analyzed. We also derive conditions under which rationing is especially beneficial, such as under high unit fleet holding costs or in the presence of batch arrivals compared to single arrivals.     

基于外部比较下的服务补救后顾客行为意向的探讨

本研究探讨了同一顾客在一家企业经历了服务失败和服务补救后与在另外一家企业从未遭遇过服务失败的比较下其行为意向,为服务补救的研究提供了新的视角。本研究考察了顾客归因对服务补救预期的影响,验证了顾客的补救预期越高则其满意度越低,满意度越高则其行为意向越积极,证明了顾客的行为意向不仅受到满意度的影响还受到顾客感知的服务失败严重程度的影响。     

A managerial assessment of the waiting-time performance for alternative service process designs

The paper develops an analytical model and, by applying it to a set of service process design alternatives, demonstrates the potential impact of process design on customer waiting-time performance. In doing so, it provides managers with some general tools and insights they can use in choosing the better service process design, adapting to changes in demand, and evaluating the impact of new technology application to the service process. It makes a case for flexibility in designing service processes by demonstrating that optimality of a design can depend on system parameter values. The various applications of this model and research findings can serve as guidelines for managers to use in designing their service processes so as to better serve their customers.     

Adoption of Mobile Telephony in Rural India: An Empirical Study

Mobile telephony has become one of the major factors driving the social and economic development of a country. The objective of this article is to identify factors affecting the adoption of mobile telephony in rural India and examine their impact on its adoption. An explanatory empirical methodology with sequential design was used for this purpose, and new factors that affect users’ decisions to adopt mobile telephony in rural India were identified. We extended the technology acceptance model by integrating new factors for a developing nation. This study found that ensuring service transparency and identifying opinion leaders in the local community are key requirements for increasing the speed of adoption in the rural India. The findings of this study will provide insights for service providers and policy makers to develop strategies and policies that will enhance mobile telephony adoption in rural India.     

基于异质性顾客心理期望等待时间的优先权服务定价研究

本文以非抢占式M/M/1排队系统为背景,以企业收益最大化为目标,基于顾客异质性(单位时间等待成本不同)将顾客分为两类,针对顾客的心理期望等待时间对服务提供商最优定价策略的影响进行研究。首先研究优先权顾客心理期望等待时间对企业收益的影响以及相应的优先权定价,然后研究优先权顾客和普通顾客同时存在心理期望等待时间对企业收益的影响和相应的优先权定价。研究表明:仅考虑优先权顾客的心理期望等待时间,企业应通过提高优先权定价来获得最优收益;当优先权顾客和普通顾客同时存在心理期望等待时间时,企业仍然采取提高优先权定价的策略,若普通顾客的价值大(获取服务的基本费用大),企业应对普通顾客提供一定的折扣来消除其心理期望等待时间增加企业收益;如果普通顾客的价值较小,企业应"有意"流失部分普通顾客,吸引更多顾客到优先权队列获取服务来获得更多收益。本文研究对于服务提供商在考虑顾客心理期望等待时间基础上设置最合理的队列机制有一定的指导意义和实际应用价值。     

考虑自取服务和门到门服务的电动汽车物流网络优化策略研究

在环境意识增长与政府政策支持的有利条件下,电动汽车在物流领域得以快速发展。为提高物流服务的效率,降低企业运营成本,文中研究了考虑顾客服务策略的电动物流汽车服务设施选址与配送路径问题。采取顾客自行取货与配送人员送货上门相结合的多样化服务策略,使得服务站点的建设成本、顾客点配送路径成本以及服务站点补货路径成本之和最小。建立了整数规划数学模型,允许配送车辆在服务过程中前往服务站点接受充电服务。其次,提出了基于改进节约算法和禁忌算法的混合启发式算法MCWSA-TS。随后,在小规模算例将CPLEX运算结果与MCWSA-TS进行对比,证明了算法的有效性。最后,采用多组算例探讨了顾客取货半径对运营成本的影响,并对分离配送策略与联合配送策略进行对比分析。实验结果表明,多样化服务策略有助于企业满足顾客取货时间和取货方式的个性化需求。同时,兼顾运营成本与顾客满意度,促进电动汽车参与的物流服务快速发展。     

Analysis of Effects of Operational Execution on Repeat Purchasing for Heterogeneous Customer Segments

Many retailers are increasingly turning to home delivery as a new arena of operational competition. This study controlled for industry by investigating the online home delivery grocery business, and an analysis of 1,919 customers of home delivery grocers identified four groups of online customers based on reasons for selecting this service. These four groups were next linked to operational execution in terms of service, product, and Internet quality, and found to vary in predicable ways. Subsequent to the initial data collection, five month's of post hoc longitudinal purchasing history was collected on the four groups of online customers to determine the relative profitability. Finally, as a follow‐on analysis, the study used regression to predict future consumer purchases based upon operational execution. Time savings and service quality emerged as the two most important independent variables in terms of future buying from such online home delivery services.     

THE MARKET SHARE IMPACT OF SERVICE FAILURES

This paper develops a simple but powerful model that relates service satisfaction/dissatisfaction to market share. The model is based on an intuitive service satisfaction framework that relates three service system parameters (service success rate, complaint rate, and service recovery rate) to the percent of satisfied customers. A dynamic model is then posited that relates the defection rate and the addition rate to market share changes. The service satisfaction/market share model yields useful insights into how market share is influenced by these service system parameters. The surprisingly simple model predicts changes in market share due to changes in customer satisfaction.     

Impact of customer loyalty and service operations on customer behaviour and firm performance: empirical evidence from UK retail sector

Abstract

Retail networks are striving to achieve competitive advantage by increasing value through loyalty and efficiency with a focus on service operations. As sales promotions have become an integral part of the retail supply chain planning, customer behavioural aspects based on loyalty and service operations have been challenged greatly. Subsequently, management capabilities, such as planning and timely replenishment, have become complicated tasks for many retail store managers. This study develops a model integrating retail network value and efficiencies with customer behaviour and performance. We validate the model using survey data from prominent U.K. retail store customers. Our data analysis shows that both loyalty and service operation attributes have positive significant impact on customer behaviour, while the service operation mediates the relationship between loyalty and customer behaviour. This result gives a new outlook to build managerial capability based on customer loyalty and service operations. Our results specifically show that the service operation attributes will indirectly influence the customers’ buying behaviour even in the presence of loyalty attribute such as promotion schemes. This result sends a strong signal to retail supply chain managers to offer customised promotions considering local community rather than having uniform sales promotion nationwide.     

基于应用扩展和网络论坛的领先用户识别方法研究

回顾了领先用户识别的电话网络法,分析了它的应用局限性。电话网络法只适合领先用户相对分散的情况下,企业需要找到部分领先用户为企业新产品概念开发贡献产品创意。但当领先用户的应用扩展到产品推广之后,为了使领先用户在市场中的领导地位能影响普通用户,并进一步带来更好的新产品绩效,需要找到目标群体中的全部领先用户。网络论坛的设立使得领先用户在产品开发论坛中相对集中,从而问卷法识别领先用户的效率能够得到保证。确立了识别领先用户的三大指标:市场或技术趋势、客户收益、信息复杂性。用统计学与概率论的方法建立了领先用户的识别模型。     

Dynamic capacity adjustments with reactive customers

In this paper we develop a behavioural model in which customers come and go based on their perception of waiting time (relative to other facilities) while managers gradually adjust the capacity of the facility based on their perception of demand. We explicitly account for the difference in access to information between existing and potential customers, which implies that the perception of potential customers lags the perception of current customers. We investigate the outcome of the interaction between these simultaneous dynamic decision processes, and in particular the impact of the lags created by the perception formation process and the time to implement desired changes in capacity. These multiple delays may result in customers and service provider being out of step: customers walk away just as the service provider manages to bring extra capacity online.     

Are Self‐Service Customers Satisfied or Stuck?

This paper investigates the impact of self‐service technology (SST) usage on customer satisfaction and retention. Specifically, we disentangle the distinct effects of satisfaction and switching costs as drivers of retention among self‐service customers. Our empirical analysis examines 26,924 multi‐channel customers of a nationwide retail bank. We track each customer's channel usage, overall satisfaction, and retention over a 1‐year period. We find that, relative to face‐to‐face service, customers who use self‐service channels for a greater proportion of their transactions are either no more satisfied, or less satisfied with the service they receive, depending on the channel. However, we also find that these same customers are predictably less likely to defect to a competitor if they are heavily reliant on self‐service channels characterized by high switching costs. Through a mediation model, we demonstrate that, when self‐service usage promotes retention, it does so in a way that is consistent with switching costs. As a robustness check, we examine the behavior of channel enthusiasts, who concentrate transactions among specific channels. Relative to more diversified customers, we find that self‐service enthusiasts in low switching cost channels defect with greater frequency, while self‐service enthusiasts in high switching cost channels are retained with greater frequency.