Platform playbook: a typology of consumer strategies against algorithmic control in digital platforms

ABSTRACT

Digital Platforms consist of algorithms and rules that shape consumer behaviour. When faced with these embodiments of the platform’s interests, how do consumers protect their own interests? Through multi-method, qualitative fieldwork focused on commuters using ride-hailing platforms in Metro Manila, this paper shows that consumers develop strategies to achieve better terms for themselves. This paper contributes to the literature on algorithmic control and user agency in two ways. First, it proposes a fine-grained typology of consumer strategies used in algorithmic digital platforms, consisting of 5 major types and 18 sub-types. Second, the typology sheds light on the distinct characteristics of consumer strategies and their implications. Future studies into user strategies, algorithmic systems, and digital platforms will benefit from the typology and implications laid out here.

KEYWORDS:

• Algorithms
• user agency
• digital platform
• user strategies
• consumer strategies

Acknowledgements

I wish to thank Prof. Vili Lehdonvirta, Prof. Eric T. Meyer, Prof. Jonathan Bright, Prof. Tom Lawrence, Dr. Alex Wood, Dr. Gretta Corporaal, Prof. Roberto Pedersini, the Oxford Internet Institute's iLabour Group, the members of Oxford's Platform Economy Interest Group (PEIG), the participants of the Society for the Advancement of Socio-Economics Conference 2020 (SASE), and two anonymous reviewers. Their comments helped sharpen the paper. I also wish to thank the Asian Center of the University of the Philippines for their help in data collection. All mistakes are mine.

Disclosure statement

No potential conflict of interest was reported by the author.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

The research for this paper was done under the support of the Oxford Clarendon Fund. The research was also partially funded by small grants from the Oxford Internet Institute and St. Edmund Hall University of Oxford.

Notes on contributors

Godofredo Ramizo

Godofredo Ramizo Jr is a DPhil candidate at the Oxford Internet Institute, University of Oxford. His research looks at firm strategy, government policymaking and user behaviour to understand the social implications of digital platforms, algorithms, and artificial intelligence. He holds an MA in Governance and Public Policy from the University of Queensland, and an MA in Development Management from the University of Westminster [email: [email protected]].