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Title: Managing big data from the crowd : strategic firm engagement with online social interactions
Author: Sheng, Jie
ISNI:       0000 0004 7432 7954
Awarding Body: University of Bristol
Current Institution: University of Bristol
Date of Award: 2018
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In today’s digital economy, information sharing has become common practice and significantly influences individuals’ behaviours and preferences. The interactive and participative environment fosters customer engagement in voicing and communicating in the virtual network. The sheer amount of user-generated content from online social interactions offers intriguing opportunities for businesses to develop sustainable competitive advantages; yet, how firms can create value by managing and capitalising on crowd voices remains an under-explored facet of big data research. This thesis discusses strategies for firms to engage in the online social interaction network so as to improve performance and achieve competitive advantages. The developed holistic framework for strategic firm engagement articulates three distinct but non-mutually exclusive roles of firms in the online communication network: observer, participant and strategic leader. Correspondingly, three studies are designed to examine business impacts of these firm engagement roles using a large-scale data set of over 800,000 online customer reviews and over 360,000 online managerial responses of London hotels. The first study investigates the observer role and validates an analytical strategy for mining customers’ textual reviews and exploiting the discovered knowledge to improve service quality. The second study considers the participant role and explores how firms respond to customer reviews and the efficacy of different response styles in future rating improvement. The third study examines the strategic leader role by testing the effects of firms being present and active online in stimulating customer engagement behaviour. Findings from the empirical studies demonstrate the strategic value of firm engagement in the online social interaction network. This thesis contributes to big data research, strategy and marketing literature in terms of strategising big data from the crowd by developing data-driven strategies. It also offers practical insights into strategic planning for businesses engaging in online social interactions.
Supervisor: Wang, Xiaojun Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available