In the last two decades technology companies engaging in surveillance capitalism (gathering data, creating predictive products, implementing behavioural modification) have reaped exorbitant profits. Using big data and machine learning algorithmic recommender systems are able to accurately predict future behaviour of users. However, other aspects than accuracy should be considered for the success of such systems. From a company perspective, Netflix has been successfully engaging in surveillance capitalism in video streaming. Claiming to be a user-centric company, personalised recommendations are the basis of Netflix’s success, while it ventures into new strategic directions with original content. Using the technology acceptance model to adopt a user-perspective, this paper examines the utility of users of the Netflix recommender system. The effects of transparency and curation as features of the Netflix platform together with user’s level of trust towards the system are examined for their impact on the perceived usefulness and ease of use of the recommender system, in order to determineuser’s behavioural intent to use the system and actual system usage. Additionally, the potential effects of user interaction as a potential future feature are explored. Using structural equation modelling on data collected from survey respondents, the paper finds that curation and trust in fact impact behavioural intent and usage while transparency fails to impact perceived factors. User interaction does not significantly improve the utility of users. The outcome suggests that Netflix should focus on curation and trust-building features as differentiating characteristics of their platform to sustain competitive advantage.
Date of Award | 29 Jun 2021 |
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Original language | English |
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Awarding Institution | - Universidade Católica Portuguesa
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Supervisor | Boris Durisin (Supervisor) |
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- Technology acceptance model
- Recommender system
- Utility
- Algorithm
- Streaming
- Surveillance capitalism
- Platform
- Netflix
- Mestrado em Gestão e Administração de Empresas
Does the Netflix recommender system produce customer utility?: an analysis of the technology acceptance of the algorithmic-prediction-based Netflix recommender system and its drivers
Lengyel, D. (Student). 29 Jun 2021
Student thesis: Master's Thesis