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• Algorithmic management uses digital platforms to oversee, control, and govern their crowd workforces through technologies. • A case study of an on-demand food delivery platform during the COVID-19 pandemic is conducted. • A process theoretical model that uncovers phases triggered by various contextual drivers and mechanisms essential for the shift from mechanistic algorithmic management to humanistic algorithmic management. • Humanistic algorithmic management explicates how human management should respond when algorithmic decisions are ineffective or deficient, and how to amplify the positives of both humans and algorithms with the underlying mechanisms. Unlike traditional employer-employee relationships, contemporary digital platforms use algorithms to control and regulate the crowd workforce. Although prior research has expressed concerns over dehumanization stemming from algorithmic management, limited scholarly attention has been dedicated to exploring how human management can complement algorithmic approaches to address these concerns. Leveraging a case study of an on-demand food delivery platform during the COVID-19 pandemic, we developed a process theoretical model that uncovers several drivers and mechanisms essential for the transition from mechanistic algorithmic management to humanistic algorithmic management. This model elucidates the dynamic substitution and complementarity of human and algorithmic management through four key mechanisms: replacing and dampening, compensating, enabling, and synergizing. It also delineates effective humanistic management actions in scenarios in which algorithmic decisions are insufficient, which contributes to both performance and humanistic outcomes. In the realm of contemporary crowd workforce management, where digital platforms employ algorithms, this research sheds light on the unique and timely insights into the role of human managers in enhancing the strategic and humanistic values of algorithmic technology. [ABSTRACT FROM AUTHOR]

Purpose: Online Peer-to-Peer (P2P) lending platforms are becoming increasingly popular globally in recent years. Our knowledge of how to develop and manage the digital platforms that make P2P lending possible, however, is limited. Through an in-depth examination of the strategies deployed and actions taken across the various stages of development of Tuodao, one of the most successful online P2P lending platforms in China, the purpose of this study is to develop a process model of P2P Lending Platform Development to address this knowledge gap. Design/methodology/approach: The case research method was adopted for this research, and a total of 16 informants were interviewed. The informants were composed of representatives of Tuodao'stop management, organizational IT functions as well as its various business units. Findings: Our study reveals that the development of a P2P lending platform can unfold in a specific sequence across three stages, and the development of a particular side of the platform should be emphasized in each stage (i.e. Partners, followed by Lenders, and then Borrowers). Each stage is also distinctive in terms of their strategies and platform configuration outcomes, which are elaborated on in our paper. Originality/value: Our process model contributes an in-depth view of how P2P lending platforms should be established and nurtured to complement the existing studies in this rapidly growing research area. In addition, our study also hints at the strategies that can facilitate the various stages. Our model can potentially serve as the foundation for formulating guidelines for the managers of P2P lending platforms, so that they are able to optimize the development of their platforms and extend the benefits of P2P lending to a broader base of customers. [ABSTRACT FROM AUTHOR]