Harnessing the power of the general public for crowdsourced business intelligence: a survey

Bin Guo (1) , Yan Liu (1) , Yi Ouyang (1) , Vincent W. Zheng (2) , Daqing Zhang (3, 4, 5) , Zhiwen Yu (1)

1 NPU - Northwestern Polytechnical University [Xi'an]
2 Advanced Digital Sciences Center
3 TSP - RS2M - Département Réseaux et Services Multimédia Mobiles
4 ACMES-SAMOVAR - Architecture, Cloud continuum, formal Models, artificial intElligence and Services in distributed computing
5 CNRS - Centre National de la Recherche Scientifique

Crowdsourced business intelligence (CrowdBI), which leverages the crowdsourced user-generated data to extract useful knowledge about business and create marketing intelligence to excel in the business environment, has become a surging research topic in recent years. Compared with the traditional business intelligence that is based on the firm-owned data and survey data, CrowdBI faces numerous unique issues, such as customer behavior analysis, brand tracking, and product improvement, demand forecasting and trend analysis, competitive intelligence, business popularity analysis and site recommendation, and urban commercial analysis. This paper first characterizes the concept model and unique features and presents a generic framework for CrowdBI. It also investigates novel application areas as well as the key challenges and techniques of CrowdBI. Furthermore, we make discussions about the future research directions of CrowdBI.

Mots clés: Competitive intelligence; Commercial site recommendation; Crowdsourced business intelligence; Brand trending; Crowd intelligence; Consumer behaviors

Domaines: Informatique [cs]

Bin Guo, Yan Liu, Yi Ouyang, Vincent W. Zheng, Daqing Zhang, et al.. Harnessing the power of the general public for crowdsourced business intelligence: a survey. IEEE Access, 2019, 7, pp.26606-26630. ⟨10.1109/ACCESS.2019.2901027⟩. ⟨hal-02321021⟩