Abstract: While improving the management efficiency of gig platforms, algorithmic management has also brought challenges to gig workers. An increasing number of gig workers endure long working hours, tight schedules, and blurred work-family boundaries. How to balance work and family has become a common concern of both platform managers and gig workers. Current literature lacks an integrated framework to analyze the impact of algorithmic management on the work-family interface. Moreover, previous research on algorithmic management has overlooked the dissipative structural characteristics of the human brain and the individual. Grounded in the dual-process model and dissipative structure theory, this study constructs moderated mediation models of the impact of algorithmic management on work-family facilitation and work-family conflict, providing an integrated theoretical perspective for analyzing the impact of algorithmic management on the work-family interface. Specifically, Study 1 relies on the dissipative structural characteristics of the human brain and constructs a linear impact model of algorithmic management on work-family facilitation from the perspective of System 1; Study 2 draws on the dissipative structural characteristics of the individual and constructs a nonlinear impact model of algorithmic management on work-family conflict from the perspective of System 2.
This study has three innovative points. First, this study combines the dual-process model and dissipative structure theory, enriching the theoretical perspective of algorithmic management, expanding the outcome variable network of algorithmic management as well as the antecedent variable network of the work-family interface. Existing research on algorithmic management mainly analyzes its impact on gig workers from the perspectives of the job demands-resources model, self-determination theory, and cognitive appraisal theory. It has not yet incorporated the theoretical perspective of the dual-process model and dissipative structure theory. This study identifies the dissipative structural characteristics of the human brain and the individual, and regards algorithmic management as a key factor triggering fluctuations within the individual cognitive system. Integrating the processing pathways of System 1 and System 2 in the dual-process model, this study analyzes the complex impact of algorithmic management on work-family facilitation and work-family conflict, further enriching the theoretical perspective of algorithmic management. In addition, previous studies have paid limited attention to the relationship between algorithmic management and the work-family interface. This study introduces the work-family interface into the outcome network of algorithmic management, thereby expanding the research boundaries in this field.
Second, this study uses the dissipative structural characteristics of the human brain to construct a moderated mediation model of the linear impact of algorithmic management on work-family facilitation. Previous studies have lacked an exploration of the mechanism through which algorithmic management affects work-family facilitation, as well as an examination of variables related to individual attention. Based on dissipative structure theory, this study considers the dissipative structural characteristics of the human brain, analyzes the pathway through which algorithmic management enhances work-family facilitation by improving gig workers’ work concentration and work goal progress, and uses gig workers’ familiarity with platform algorithms as a moderator to identify the boundary conditions under which algorithmic management exerts a positive effect on work-family facilitation among gig workers.
Third, this study uses the individual’s own dissipative structural characteristics to construct a moderated mediation model of the nonlinear impact of algorithmic management on work-family conflict. Previous research on algorithmic management has not paid attention to the dissipative structural characteristics of gig workers themselves. Based on the dual-process model, this study uses the individual’s own dissipative structural characteristics to analyze the pathway through which algorithmic management nonlinearly affects work-family conflict via psychological entropy and uncertainty perception, and combines gig workers’ self-management level to explain the conditions under which algorithmic management’s nonlinear impact on work-family conflict operates. This study helps to reveal the complex impact of algorithmic management on gig workers and can also help to fill the gap left by previous studies that neglected the dissipative structural characteristics of gig workers themselves.
In addition to the above three innovations, this study applies the dual-process model to research on algorithmic management, thereby enriching the application scenarios of the theory in the digital economy era. The findings also offer practical implications for society, enterprises, and gig workers to help them adapt to the algorithmic society and better balance the relationship between work and family.

Key words: gig economy, algorithmic management, work-family interface, dual-process model, dissipative structure theory