| With the rapid development of information technology,algorithms gradually penetrate into various fields of people’s working life,and the development of the oddlabor economy has disrupted the conventional employment mode and employment pattern,making an increasing number of workers join the army of platform employment.Despite the increasing adoption of algorithms for management and monitoring by oddlabor platforms,the benefits or drawbacks of platform algorithmic control and how these correspond to platform workers’ attitudes toward work behavior are unclear.In the logistics sector,shared freight platforms are typical online odd-job platforms that use algorithms to regulate laborers.Due to the special nature of cargo transportation,labor conflicts are more prominent compared with similar platforms.At present,theoretical research on freight industry practitioners rarely involves platform laborers as a group,and at the same time,there is a lack of a unified conceptual definition and scientific and reliable measurement tools for platform laborers’ perception of algorithmic control.Therefore,the research related to the impact mechanism of algorithmic control of shared freight platforms on platform workers is a theoretical and practical problem that needs to be solved at present.To address the above issues,this study is based on the perspective of algorithmic control perception of freight platform workers.First,we conceptualize the connotation of platform algorithmic control,expand the dimensions and connotations of algorithmic control perceptions of workers on shared freight platforms,subdivide the conceptualization of algorithmic control perceptions hierarchically,and determine a three-dimensional model of algorithmic control perceptions,including mandatory standardization,tracking evaluation and behavioral constraint.This helps to reveal the mechanism of the influence of algorithmic control on the positive or negative psychology of workers on the shared freight platform,and lays a theoretical foundation for the subsequent exploration of the mechanism of the influence of perceived algorithmic control on work behavior.Second,unlike previous studies,which mostly focus on the macroscopic perspective and explore the operation mode of the platform organization and the social problems it brings,this paper focuses on the individual level and explores the psychological state of the shared freight platform workers at this microscopic level to see the problems faced by the platform enterprise management,breaking through the limitations of previous studies in terms of perspective.Finally,based on the framework of power dependency theory,this study distinguishes case studies or theoretical discussions that are mostly used in the theoretical field,constructs a research framework of "perceived algorithmic control-work autonomy/professional identity-job burnout" through empirical research,and systematically analyzes the effects and mechanisms of perceived algorithmic control on job burnout.The study was conducted with 350 valid questionnaires obtained online from workers on a shared freight platform,and the hypotheses were tested using SPSS and Smart PLS statistical analysis software.The main findings were that: perceived algorithmic control had a negative effect on work autonomy as well as occupational identity;work autonomy,as well as the professional identity,had a negative effect on job burnout;job autonomy as well as the professional identity between perceived algorithmic control and job burnout mediating role.This study provides theoretical support for better scientific guidance on the balance between algorithmic technical management and humane ethical management by dissecting the mechanism of platform algorithmic control on the formation of burnout among workers on shared freight platforms. |
