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Detecting customers knowledge from social media big data: toward an integrated methodological framework based on netnography and business analytics

Del Vecchio, Pasquale ; Mele, Gioconda ; Passiante, Giuseppina ; Vrontis, Demetris ; Fanuli, Cosimo

Journal of knowledge management, 2020-05, Vol.24 (4), p.799-821 [Periódico revisado por pares]

Kempston: Emerald Publishing Limited

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  • Título:
    Detecting customers knowledge from social media big data: toward an integrated methodological framework based on netnography and business analytics
  • Autor: Del Vecchio, Pasquale ; Mele, Gioconda ; Passiante, Giuseppina ; Vrontis, Demetris ; Fanuli, Cosimo
  • Assuntos: Analytics ; Big Data ; Business ; Business analytics ; Competition ; Competitive advantage ; Customer relationship management ; Customer satisfaction ; Customers ; Data collection ; Digital media ; Economic development ; Innovations ; Internet ; Knowledge management ; Market strategy ; Marketing ; Mathematical analysis ; Netnography ; Qualitative research ; Social networks ; Strategic management
  • É parte de: Journal of knowledge management, 2020-05, Vol.24 (4), p.799-821
  • Descrição: Purpose 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). Design/methodology/approach 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. Findings 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. Research limitations/implications 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 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. Originality/value 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.
  • Editor: Kempston: Emerald Publishing Limited
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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