The Dark Side of Sharing Economy under Algorithmic Management:Conceptual Framework and Agenda
With the rapid development and widespread application of digital technology and artificial intelligence(Al),economic models characterized by temporary transfer of usage rights have risen rapidly over the past two decades to form a new sharing econ-omy model.As sharing economy platforms elevate their demands for resource matching speed and quality control,more and more companies are introducing algorithmic management into sharing economy activities to replace the traditional manual scheduling model,using algorithms to achieve efficient matching between consumers,merchants,and digital laborers while controlling the qual-ity of transactions.On the one hand,algorithmic management brings the opportunity for platforms to reduce economic costs and im-prove transaction efficiency,consumer experience and employee welfare through efficient matching and control.On the other hand,algorithmic management has led to many negative outcomes in the sharing economy.For example,algorithmic management extends the privacy issues associated with information collection and use;algorithmic bias generates digital discrimination;the scheduling principle of on-demand work makes it difficult to protect the rights and interests of digital laborers;and algorithmic control under-mines the autonomy and self-efficacy of digital laborers'work,and exacerbates the power inequality among stakeholders.Algorith-mic management has led to the unprecedented development of the sharing economy,and while people enjoy the positive experiences brought by the sharing economy,the dark side of the sharing economy triggered by algorithmic management has also been empha-sized by both the practical and academic communities.The topic of the dark side of the sharing economy has triggered various discussions recently,and previous studies have mainly re-vealed the negative impacts of the sharing economy on consumers,service providers,or the society from the perspective of resource crowdsourcing,such as social inequality,impacts on traditional industries,and negative impacts on the ecological environment.How-ever,existing research still lacks a conceptual understanding of the dark side of the sharing economy under algorithmic management,and a systematic theoretical framework and in-depth theoretical exploration of the specific dark side arising from algorithmic man-agement on multiple stakeholders in the sharing economy have yet to be developed.Therefore,further research is needed to deepen the understanding of the sharing economy under algorithmic management and to provide theoretical basis and practical suggestions for the development of corresponding policy recommendations and solutions.In response to the above background,this research first discusses the connotation and characteristics of the dark side of the sharing economy from an algorithmic management perspective.Second,this research draws on Stefano Puntoni's theoretical framework of user experience journey in human-computer interaction,while also considering the diversity of interaction objects and the specificity of algorithmic functions in the sharing economy,and divides the activities of the sharing economy with algorithmic management at its core into four progressive themes:data acquisition,storage and analysis,behavioral agency,and social interaction.Then,this research explores the causes of the dark side of the sharing economy under the three core themes of data acquisition,behavioral agency,and social interaction under the three core themes of data acquisition,behavioral agency,and social interaction,and explores the causes of the sharing economy under algorithmic management from different theoretical perspectives,including seven perspectives on the above themes from the psychological ownership theory,the privacy concern theory,the labor process theory,the expectancy inconsis-tency theory,the digital discrimination,the psychological contract theory,and the organizational justice theory,as well as discusses the current state of the relevant research and the development direction.Finally,this research presents research contributions and management recommendations,and condenses and discusses future research directions based on the three core themes.This research makes the following major contributions in theory and practice:first,this research explores the definition and conno-tation of the dark side of the sharing economy from the perspective of algorithmic management,expanding and deepening the con-ceptual understanding of the dark side of the sharing economy.Second,by systematically combing the current research status of the dark side of the sharing economy from the perspective of algorithmic management and exploring the future development direction,this research provides rich research themes and directions for future theoretical research related to the sharing economy and algorith-mic management.Especially,this research discusses future research directions for the sharing economy under the three dimensions of data acquisition,agent behavior,and social interaction,covering topics such as user privacy issues in the sharing economy,user attitudes toward algorithms,and the dark side of the sharing economy from the perspective of multi-sided platforms.Finally,based on the findings,this research proposes relevant practical suggestions for management,including establishing reasonable rules for data collection and privacy protection,transforming digital laborers'perceptions of algorithm management,and encouraging other partici-pants to join in regulating the platforms,so as to promote the sustainable development of the sharing economy and social equity.
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