This paper explores corporate digital responsibility and its implications for sharing economy platforms, suggesting tensions in accountability and value creation.
Purpose The purpose of this paper is to develop a conceptual framework of corporate digital responsibility (CDR) in the sharing economy (SE) by mobilizing and refining the established value-balance-accountability (VBA) framework. Design/methodology/approach The authors conceptually extend and interpret the VBA framework by considering the position of CDR in the conflicting realm of sharing platforms’ responsibilities and irresponsibilities and associated tensions. Through an integrative perspective, they combine top-down and bottom-up approaches by critically examining and linking together research on the SE, CDR and its dark side, using Airbnb and Uber as illustrative cases. Findings CDR of SE platforms can be subsumed into three distinct categories, that is, value, balance and accountability. Value demonstrates how economic, social and environmental value is created in the digital domain. Balance is manifested in different mechanisms, that is, algorithmic management, dynamic policy alignment and mediating mechanisms, that contribute to aligning the interests of different stakeholders on the platform. Accountability considers the importance of transparency, trustworthiness, equality and privacy in the digital sphere. Because of the multifaceted nature of each dimension, tensions inevitably arise among them. Moreover, the irresponsibility of SE platforms is demonstrated in value destruction, imbalances and unaccountability. Practical implications The framework serves as a practical guide for SE platforms, consumer protection agencies and policymakers. Originality/value The original contributions of this paper are fourfold: exploring the nuances of CDR in the SE setting; providing a comprehensive conceptual framework based on the VBA model that explains how organizations behave digitally (ir)responsibly; extending the VBA framework with the irresponsibilities to capture the dark side; and detecting the tensions that arise because of the multifaceted nature of each dimension of CDR.
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Richthofen et al. (2025) studied this question.
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