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Detecting customers knowledge from social media big data: toward an integrated methodological framework based on netnography and business analytics
Journal of Knowledge Management ( IF 6.6 ) Pub Date : 2020-05-04 , DOI: 10.1108/jkm-11-2019-0637
Pasquale Del Vecchio , Gioconda Mele , Giuseppina Passiante , Demetris Vrontis , Cosimo Fanuli

This paper aims to demonstrate how the integration of netnography and business analytics can support companies in the process of value creation from social big data by leveraging on customer relationship management and customer knowledge management (CKM).,This paper adopts the methodology of a single case study by using desk analysis, netnography and business analytics. The context of analysis has been identified into the case of Aurora Company, a well-known producer of fountain pens.,The case demonstrates how the integration of big data analytics and netnography is relevant for the development of a customer relationship management strategy. The results obtained have been categorized according to the three main categories of customer knowledge, such as knowledge for, from and about customer.,This paper presents implications for the advancement of the theory on CKM by demonstrating, as the acquisition, storage and management of data generated by customers on social media require the adoption of a cross-disciplinary approach resulting from the integration of qualitative and quantitative approaches. The framework is structured as methodological tool to detect knowledge in virtual community.,Practical implications arise for managers and entrepreneurs in terms of value creation from knowledge assets generated on social big data through the management of the customers’ relationship and data-driven innovation patterns.,This paper offers an original contribution of integration of well-established research streams. The focus on the knowledge under the perspectives of information assets for, from and about customers in the debate on value creation and management of big data is an element of value offered by this study in addition to the comprehension of strategies of social customer relationship management as actual initiative embraced by a company in the leveraging of innovation and tradition.

中文翻译:

从社交媒体大数据中检测客户知识:建立基于网络志和业务分析的集成方法框架

本文旨在说明网络志和业务分析的集成如何通过利用客户关系管理和客户知识管理(CKM)来支持公司从社交大数据创造价值的过程中。使用案头分析,民族志和业务分析进行研究。分析的上下文已经在著名的钢笔生产商Aurora Company的案例中得以确定。该案例说明了大数据分析和网络技术的集成如何与客户关系管理策略的发展相关。所获得的结果已根据客户知识的三个主要类别进行了分类,例如有关客户的知识,来自客户的知识以及有关客户的知识。本文通过演示,说明了在社交媒体上客户生成,数据的获取,存储和管理需要采用定性和定量方法相结合的跨学科方法,这对CKM理论的发展提出了启示。该框架被构造为检测虚拟社区中知识的方法论工具。对于管理者和企业家而言,从通过管理客户关系和数据驱动的创新模式在社会大数据上产生的知识资产创造价值方面,产生了实际意义。 ,本文为整合完善的研究流提供了原创性的贡献。重点关注信息资产视角下的知识,
更新日期:2020-05-04
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