Customer relationship management systems (CRMS) in the healthcare environment: A systematic literature review

Customer relationship management (CRM) is an innovative technology that seeks to improve customer satisfaction, loyalty, and profitability by acquiring, developing, and maintaining effective customer relationships and interactions with stakeholders. Numerous researches on CRM have made significant progress in several areas such as telecommunications, banking, and manufacturing, but research specific to the healthcare environment is very limited. This systematic review aims to categorise, summarise, synthesise, and appraise the research on CRM in the healthcare environment, considering the absence of coherent and comprehensive scholarship of disparate data on CRM. Various databases were used to conduct a comprehensive search of studies that examine CRM in the healthcare environment (including hospitals, clinics, medical centres, and nursing homes). Analysis and evaluation of 19 carefully selected studies revealed three main research categories: (i) social CRM ‘eCRM’; (ii) implementing CRMS; and (iii) adopting CRMS; with positive outcomes for CRM both in terms of patients relationship/communication with hospital, satisfaction, medical treatment/outcomes and empowerment and hospitals medical operation, productivity, cost, performance, efficiency and service quality. This is the first systematic review to comprehensively synthesise and summarise empirical evidence from disparate CRM research data (quantitative, qualitative, and mixed) in the healthcare environment. Our results revealed that substantial gaps exist in the knowledge of using CRM in the healthcare environment. Future research should focus on exploring: (i) other potential factors, such as patient characteristics, culture (of both the patient and hospital), knowledge management, trust, security, and privacy for implementing and adopting CRMS and (ii) other CRM categories, such as mobile CRM (mCRM) and data mining CRM.     

通信企业CRM中数据挖掘的应用研究

通信企业CRM的构建目标是为了使服务内容、服务方式、服务质量、经营管理以及服务意识不断提升与完善,赢得更多的客户并且提高客户的忠诚度和满意度,挖掘客户潜在价值以及降低销售和管理成本。本文通过通信CRM系统的框架结构、CRM中数据仓库的作用、通信CRM中数据挖掘的具体应用三个方面论述了详细论述了通信企业CRM中数据挖掘的应用。     

通信企业CRM中数据挖掘的应用研究

通信企业CRM的构建目标是为了使服务内容、服务方式、服务质量、经营管理以及服务意识不断提升与完善．赢得更多的客户并且提高客户的忠诚度和满意度，挖掘客户潜在价值以及降低销售和管理成本。本文通过通信CRM系统的框架结构、CRM中数据仓库的作用、通信CRM中数据挖掘的具体应用三个方面论述了详细论述了通信企业CRM中数据挖掘的应用。     

Intelligent customer complaint handling utilising principal component and data envelopment analysis (PDA)

In this study, we consider customer to be a company's crucial asset. In order to have a fast, efficient decision-making process, it is vital that a customer relationship management (CRM) decision-maker condenses and abstracts the existing information. A questionnaire survey was conducted among respondents in order to obtain the required data. The questionnaire contains nine categories of satisfaction variables. To perform the analysis, we used principal component analysis (PCA) and data envelopment analysis (DEA). PDA has been utilised as an abbreviation for the integration of these two methods. To effectively analyse the procedure, PCA was utilised to assign a number to each category of questions related to each satisfaction variable. To achieve optimal precision, DEA was applied to the three categories of customers (‘most important’, ‘important’ and ‘ordinary’ customers) in order to determine the strengths and weaknesses of customer services from these customers’ perspectives. Customers were clustered and then DEA was used to determine their viewpoints. Using DEA, we have optimised our recognition of customers’ complaints and then provided recommendations and remedial actions to resolve the current issues in logistics and transport industry in general, and at Fremantle port in particular.SignificanceThe current study integrates soft computing and optimisation technique in order to build the CRM recommender system. It demonstrates the hybrid soft computing strengthens in area of CRM as the relevance solution. The significance of the proposed algorithm is three fold. First, it integrates soft computing and optimisation technique in order to build the CRM recommender system. Second, it utilises the most standard CRM variables in its decision making process. Third, it is an optimising algorithm because it integrates DEA with PCA technique.     

神经网络算法在CRM中的应用

神经网络算法能通过对网络的训练,使客户关系管理系统中客户行为做出预测,便于企业更好为客户服务,改善客户关系,挽留客户.本文就神经网络算法的CRM应用做了相关的探讨.     

Study of the wireless/wire integration CRM Gateway for the effective application of Event CRM for small and medium sized enterprises

The CRM System, which maximizes business profits by pursuing a continuous relationship with customers, is based on an analytical CRM that sets up a marketing strategy by analyzing customer information. However, thanks to the technological development of the Internet and mobile phones, customer contact is being carried out through a variety of channels. Yet currently, the needs of customers are not being addressed in a timely manner due to a weak system that cannot immediately deal with customer requests and because of which customer information is not administered in a systematic manner.Therefore, rather than focusing on off-line-focused analytical CRM, it is necessary to concentrate on real time CRM that reflects the aspects of the operative or collaborative CRM. This study also develops an Event CRM solution that can bring satisfaction to customers when they want it by systematizing the contact points of customers, which constitute various institutions and channels.The CRM model that this study presents is the support of Event CRM services for all business types against the backdrop of a wireless/wire environment, and the support of small and medium sized companies, which are burdened by information management costs, to meet the demand for CRM.In order to present the wireless/wire integration CRM Gateway Model, the study focuses on insurance CRM services.When a customer event arises through various channels such as the Internet, SFA or CTI, the event data are transferred through a standardized form. Based on these data, the campaign and service is then extracted and analyzed with the Event CRM Gateway Engine. A match is immediately made between the saved rules and the campaign and services that best fit the customer. Finally, the information is provided to the customer via a mobile phone or website.     

数据挖掘技术在客户关系管理（CRM）中的应用及具体实现策略

人们普遍认识到,各种规模的企业需要学习效仿那些小型的、以服务为导向的商业模式,总是能做好建立一对一的客户关系。客户关系管理是广泛出现在很多书籍和会议上的议题。从铅跟踪软件到广告系列管理软件,再到呼叫中心软件。如今,在销售中一切都作为顾客关系管理工具。通过提高公司的能力和我们的顾客形成学习关系,数据挖掘可以在提升顾客关系管理。每一个行业中,高瞻远瞩的公司正在试图走向一对一的理解每一个客户,运用那种了解以方便客户做生意,而不是一个竞争者。同样,这些公司正在学习看终身价值的每一个客户,这样他们就能知道有哪些值得投资金钱和精力来坚持,哪些让下降。从大市场分割到个体消费者,这一关注的转变需要公司的改变,更重要的莫过于市场营销,销售和顾客的支持。     

数据挖掘技术在CRM中的应用

CRM（客户关系管理）是一种旨在改善企业与客户之间关系的新型管理机制。数据挖掘技术应用于CRM中，能够加强和改善客户关系管理，从而为企业带来更多的利润。该文对数据挖掘技术在CRM中的应用内容和过程进行了研究。     

支持CRM分析的数据仓库多维启动模型

CRM是一种整合了知识管理、数据挖掘及数据仓库技术的商业策略,旨在支持制定决策来保留长期有利的客户关系。分析了CRM中数据仓库的设计问题,提出一种支持CRM分析的强劲的多维启动模型。为验证此模型,用一些CRM的查询进行测试,并定义两个量:成功率和适配率来评估。实验结果表明,此启动模型具有很高的成功率和适配率,可用于客户收益分析、市场收益分析、产品收益分析、渠道收益分析等多种收益分析。     

IT alignment strategies for customer relationship management

Customer relationship management (CRM) is the overall process of building and maintaining profitable customer relationships by delivering superior customer value and satisfaction. A CRM strategy involves the entire enterprise and is employed on an ongoing basis. Despite the fact that CRM projects incur huge expenditures, a large percentage fails to achieve the stated objectives. Failure in CRM initiatives could be avoided if a firm's CRM strategies are intelligently linked with its employees, customers, channels, and IT infrastructure. In this paper, we focus on those linkages, particularly on the linkages between an organization's CRM strategies and its IT infrastructure. Even though the relationships between IT and business strategies have been extensively explored in the IT alignment literature, prior research has not addressed how a firm's CRM strategies are aligned with its IT infrastructure. In this paper, we investigate the issues relating to CRM-IT alignment based on an in-depth case study of a large, well-known Internet travel agency.     

An Integrated Model for Customer Relationship Management: An Analysis and Empirical Study

Ensuring customer satisfaction and maintaining long‐term relationships with customers have become essential for survival among competitive service industries. The present study addresses this need by proposing a conceptually integrated four‐phase model that incorporates elements of customer relationship management (CRM) and customer satisfaction (represented by the extended American Customer Satisfaction Index model). Then, this study formulates structural equation modeling to test various research hypotheses related to the effect of the CRM initiative. An empirical study of 143 leading Taiwanese service firms distributed among seven service industries was conducted. The implementation levels of various constructs, input (customer knowledge), service provision (customer interactions), output quality, perceived quality, perceived value, perception of customer satisfaction, customer loyalty, purchasing intention, and profits of CRM are assessed in a range of service industries by means of a questionnaire survey and in‐depth interviews. The results of the empirical study reveal statistically significant influences among various constructs of the CRM integrated model. These results also represent a useful reference for managers of service organizations that could be used to improve the profitability and implementation level of CRM. The present study represents an important investigation in the development of an integrated CRM implementation system for service industries. © 2012 Wiley Periodicals, Inc.     

数据挖掘技术在中国移动CRM中的应用

CRM是一种帮助企业向客户提供优质服务的工具,在CRM中利用数据挖掘技术不断的收集、分析客户资料,从而达到保有优质老客户、获取新顾客的目的,帮助企业制定有效的营销策略,提高企业的收益率。     

The state of CRM adoption by the financial services in the UK: an empirical investigation

In recent years, organisations have begun to realise the importance of knowing their customers better. Customer relationship management (CRM) is an approach to managing customer related knowledge of increasing strategic significance. The successful adoption of IT-enabled CRM redefines the traditional models of interaction between businesses and their customers, both nationally and globally. It is regarded as a source for competitive advantage because it enables organisations to explore and use knowledge of their customers and to foster profitable and long-lasting one-to-one relationships. This paper discusses the results of an exploratory survey conducted in the UK financial services sector; it discusses CRM practice and expectations, the motives for implementing it, and evaluates post-implementation experiences. It also investigates the CRM tools functionality in the strategic, process, communication, and business-to-customer (B2C) organisational context and reports the extent of their use. The results show that despite the anticipated potential, the benefits from such tools are rather small.     

Web数据挖掘在企业CRM中的应用

CRM的本质在于通过WWW的渠道,在营销、销售、服务和支持四个方面与客户建立良好的关系,从而提高企业收益。在电子商务中,提高客户忠诚度保持住客户,实现交叉销售等成为电子商务成败的一个关键问题。而Web数据挖掘能在电子商务中更好地运作CRM,建立良好客户关系的一种解决方法。该文研究了Web数据挖掘技术在CRM中的应用。     

Exploring the role of customer relationship management (CRM) systems in customer knowledge creation

This study explores how customer relationship management (CRM) systems support customer knowledge creation processes [48], including socialization, externalization, combination and internalization. CRM systems are categorized as collaborative, operational and analytical. An analysis of CRM applications in three organizations reveals that analytical systems strongly support the combination process. Collaborative systems provide the greatest support for externalization. Operational systems facilitate socialization with customers, while collaborative systems are used for socialization within an organization. Collaborative and analytical systems both support the internalization process by providing learning opportunities. Three-way interactions among CRM systems, types of customer knowledge, and knowledge creation processes are explored.     

Customer''s time-variant purchase behavior and corresponding marketing strategies: an online retailer''s case

The traditional customer relationship management (CRM) studies are mainly focused on CRM in a specific point of time. The static CRM and derived knowledge of customer behavior could help marketers to redirect marketing resources for profit gain at the given point in time. However, as time goes on, the static knowledge becomes obsolete. Therefore, application of CRM to an online retailer should be done dynamically in time. Though the concept of buying-behavior-based CRM was advanced several decades ago, virtually little application of the dynamic CRM has been reported to date.

In this paper, we propose a dynamic CRM model utilizing data mining and a monitoring agent system to extract longitudinal knowledge from the customer data and to analyze customer behavior patterns over time for the retailer. Furthermore, we show that longitudinal CRM could be usefully applied to solve several managerial problems, which any retailer may face.     

基于数据挖掘的CRM分析

进行客户关系管理系统建设,是企业争取竞争优势的重要手段,数据挖掘技术在CRM的实施中起着关键的作用。文章介绍了数据挖掘技术和CRM技术,具体介绍了在酒店CRM建设中用到的决策树和模糊聚类这两种数据挖掘的实现方法,并做出了实验分析。     

基于数据仓库的客户关系管理

数据仓库是数据管理信息领域近年来出现并发展迅速的一种新技术,它可以将各个渠道得来的数据,整理成全面、完善的客户信息库,通过数据挖掘和数据分析,来了解客户的需求,以保持良好的客户关系,维系客户忠诚,从而提高企业核心竞争力。论文介绍了数据仓库的基本概念及其技术特征,详细分析了数据仓库在客户关系管理中的作用。在此基础上,提出了客户关系管理数据仓库系统的具体设计方案。     

数据挖掘技术在民航CRM中的应用

进行客户关系管理系统建设,是当今各大航空公司争取竞争优势的重要手段。数据挖掘技术在CRM的实施中起着关键的作用。文章分别介绍了数据挖掘技术和CRM技术,具体介绍了在民航CRM建设中用到的决策树方法和模糊聚类方法这两种数据挖掘方法,并作了实验分析。最后对数据挖掘技术在民航中的应用作了展望。     

A model of customer relationship management and business intelligence systems for catalogue and online retailers

As more retailers evolve into customer-centric and segment-based business, business intelligence (BI) and customer relationship management (CRM) systems are playing a key role in achieving and maintaining competitive advantage. For the past ten years, the authors have had the rare opportunity of observing and interviewing employees and managers of three different management teams at three separate Fingerhut companies as they experimented with various ITs for their companies. When the first Fingerhut company peaked in 1998, as many as 200 analysts and 40 statisticians mined the database for insights that helped predict consumer shopping patterns and credit behaviour. Data mining and BI helped Fingerhut spot shopping patterns, bring product offerings to the right customers, and nurture customer relationships. By 1998, Fingerhut was the second largest catalogue retailer in the U.S. with revenues nearing $2 billion. However, after Federated acquired Fingerhut in 1999 and made it a subsidiary, Fingerhut Net, it suffered great losses and was eventually liquidated. Finally, a new company, Fingerhut Direct Marketing, was resurrected in 2002 under a new management team, and it once again became successful. What went right? What went wrong? The paper concludes with CRM and BI systems success factors and a discussion of lessons learned.