Big Data and Service Science

Big data is about handling huge and/or complex datasets that conventional technologies cannot handle or handle well. Big data is currently receiving tremendous attention from both industry and academia as there is much more data around us than ever before. This chapter addresses the relationship between big data and service science, especially how big data can contribute to the process of co-creation of service value. In particular, the value co-creation in terms of customer relationship management is mentioned. The chapter starts with brief descriptions of big data, machine learning and data mining methods, service science and its model of value co-creation, and then addresses the key idea of how big data can contribute to co-create service value.

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Big Data and Service Science

Advances in Marketing, Customer Relationship Management, and E-Services - Progressive Trends in Knowledge and System-Based Science for Service Innovation ◽

10.4018/978-1-4666-4663-6.ch007 ◽

2014 ◽

pp. 128-144 ◽

Cited By ~ 2

Author(s):

Tu-Bao Ho ◽

Siriwon Taewijit ◽

Quang-Bach Ho ◽

Hieu-Chi Dam

Keyword(s):

Machine Learning ◽

Data Mining ◽

Big Data ◽

Customer Relationship Management ◽

Relationship Management ◽

Service Science ◽

Customer Relationship ◽

Service Value ◽

Mining Methods ◽

The Relationship

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ENTERPRISE CUSTOMER RELATIONSHIP MANAGEMENT BASED ON BIG DATA MINING

Latin American Applied Research - An international journal ◽

10.52292/j.laar.2018.220 ◽

2018 ◽

Vol 48 (3) ◽

pp. 163-168

Author(s):

X. T. LI ◽

F. FENG

Keyword(s):

Data Mining ◽

Big Data ◽

Customer Relationship Management ◽

Relationship Management ◽

Customer Relationship ◽

Potential Core ◽

Big Data Mining ◽

Customer Classification ◽

Classification Index

Based on the customer relationship management in the context of big data, focusing on B2C e-commerce companies, this paper constructs a customer classification index system, uses a factor analysis and Bagging model to study the sales data of an e-commerce business, and demonstrates the specific operation of customer relationship management under the background of big data. This paper finds that through the classification of past consumer behavior data, managers can distinguish between potential, core, and lost customers. The bagging model can predict the type of customer and guide the administrator to perform differentiated customer relationship management.

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Customer Relationship Management and Big Data Mining

Studies in Big Data - Information Granularity, Big Data, and Computational Intelligence ◽

10.1007/978-3-319-08254-7_16 ◽

2014 ◽

pp. 349-360

Author(s):

Yi Hui Liang

Keyword(s):

Data Mining ◽

Big Data ◽

Customer Relationship Management ◽

Relationship Management ◽

Customer Relationship ◽

Big Data Mining

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The customer relationship management based on data mining

Advances in Industrial Engineering, Information and Water Resources ◽

10.2495/aie120341 ◽

2012 ◽

Author(s):

Haiying Ma ◽

Dong Gang

Keyword(s):

Data Mining ◽

Customer Relationship Management ◽

Relationship Management ◽

Customer Relationship

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Relationship Ending in the Concept of Customer Relationship Management

Olsztyn Economic Journal ◽

10.31648/oej.3138 ◽

2015 ◽

Vol 10 (2) ◽

pp. 103-113

Author(s):

Ewa Hajduk-Kasprowicz ◽

Lech Nieżurawski

Keyword(s):

Customer Relationship Management ◽

Relationship Management ◽

Professional Services ◽

Customer Relationship ◽

Modern Literature ◽

Relationship Dissolution ◽

Business Relationships ◽

Efficient Management ◽

The Future ◽

The Relationship

The paper discusses the problems of fading and ending of business relationships in the sphere of professional services i.e. the phase of a relationship dissolution resulting from a client's or a firm's decision to end it. This phase includes, among others, determining the causes of the relationship dissolution and drawing conclusions for the future in order to prevent losing the most lucrative clients. Both in theory and in practice, relationship ending is perceived as something stretched in time i.e. consisting of numerous stages and influenced by numerous factors and events.The aim of the present paper is an analysis of the modern literature on the causes and mechanisms of business relationships termination in the sphere of professional services as well as indicating some possibilities of a more effective and efficient management of these relations.

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