挑战还是阻断?平台算法压力对数字零工主动服务行为的影响机制

doi:10.3724/SP.J.1042.2024.01768

摘要/Abstract

摘要：

零工经济新业态依托在线服务平台迅速崛起, 成为创造就业机会与推动经济整体效率的重要引擎。平台在利用大数据算法提高运营效率的同时, 也在全景式动态追踪数字零工的劳动过程, 导致其在与算法系统和平台的互动中产生复杂多元的新型压力体验。然而, 现有研究并未清晰界定数字零工算法压力的概念, 且无法提供可靠的测量工具, 上述研究缺口成为探究数字零工压力反应及其对平台服务质量影响的障碍。因此, 本研究围绕“平台算法压力内涵及其对数字零工主动服务行为的差异化影响”的核心研究主题, 基于算法管理功能与零工算法互动过程, 创造性提出数字零工算法压力的新定义, 并通过开发科学的量表工具, 甄别算法压力的结构要素。在此基础上, 结合压力认知评估理论, 基于挑战性−阻断性压力认知评估框架揭示算法压力影响零工主动服务行为的增益路径和损耗路径, 以及双元路径发挥作用的边界条件。本研究不仅拓展了零工经济背景下平台算法研究的理论框架, 且能够为有效发挥在线服务平台算法的积极功能提供理论指引。

关键词: 算法压力, 主动服务行为, 零工经济, 压力认知评估理论, 数字零工

Abstract:

The burgeoning gig economy, underpinned by online service platforms, has become a critical source of employment and a catalyst for economic efficiency. Despite the benefits, the algorithmic management inherent in these platforms introduces a new type of stressor for digital gig workers, impacting their service behavior. However, there is a shortage of clarity and measurement tools regarding the concept of digital gigs' algorithmic stressors.

This study seeks to fill an important research gap by examining the implications of platform algorithmic stressors on the proactive service behavior of digital gig workers. Drawing from the gig economy context and existing research on algorithmic management, this study introduces the concept of "algorithmic stressors on digital gig workers." It first delves into the conceptual meanings and structural aspects of this concept, and then introduces the dual pathway of cognitive evaluation of challenge-hindrance stress to explore its impact and boundary conditions on proactive service behavior. The ultimate goal is to address fundamental scientific inquiries such as "What are the effects of algorithmic stressors on digital gig workers?" and "How do these stressors influence gig workers' proactive service behavior?"

This study proposes a research framework based on a mixed-methods approach, combining qualitative exploration and quantitative verification, resulting in three logically connected sub-studies. (1) Starting from the functional characteristics of algorithmic management in online service platforms and combining the interaction process between gig workers and algorithmic systems, this study employs both qualitative and quantitative research methods to define the concept of algorithmic stressors on digital gig workers, extract its subdimensions, analyze its connotations, and subsequently develop measurement tools. (2) Based on the theory of stress cognitive appraisal, this study explores the differentiated mechanisms through which the challenging-hindrance cognitive appraisal of algorithmic stressors on digital gig workers influences gig workers' proactive service behavior, providing a theoretical foundation for clarifying the impact of algorithmic stressors on gig workers' proactive service behavior. (3) Building on the dual pathways of gain and loss of algorithmic stressors on gig workers' proactive service behavior, this study further explores the cross-level moderating effects of platform algorithmic fairness and platform algorithmic support, aiming to elucidate how algorithmic characteristics at the organizational level function as boundary conditions in differentiated pressure impact pathways.

This study defines algorithmic stresses on digital gig workers as the stress experiences generated by digital gig workers in the process of interacting with algorithms under platform algorithm management, and the types of these stress experiences are related to the different functions of algorithm management. The findings indicate that algorithmic stressors on digital gig workers, when perceived as challenging, can positively influence problem-solving pondering and attentiveness, thereby promoting proactive service behavior. Conversely, when these stressors are appraised as hindrances, they can lead to work-related rumination and job anxiety, negatively affecting the propensity for proactive service behavior. When algorithms are perceived as fair, digital gig workers tend to challenge the evaluation of algorithm stressors; At the same time, the higher the level of platform algorithm support perceived by gig workers, the weaker the negative impact of hinderance cognitive appraisal.

This study constructs a theoretical model of the impact of algorithmic stressors on digital gig workers’ individual proactive service behavior, with the following three theoretical innovations. Firstly, based on the characteristics of algorithmic management in online service platforms and the human-computer interaction process between gig workers and algorithmic systems, this study proposes the concept of algorithmic stressors on digital gig workers. It effectively bridges the current research on algorithmic management work characteristics and gig worker stress experiences, providing a reliable measurement tool for subsequent related research. Second, based on the theory of stress cognitive appraisal, this study explores the dual pathways of challenging and hindrance stress cognitive appraisal through which algorithmic stressors influences gig workers' proactive service behavior, addressing the current research gap in neglecting the potential positive work stress brought by algorithmic management to digital gig workers. Third, this study clarifies the cross-level moderating effects of algorithmic management characteristics in online service platforms on the dual cognitive appraisal pathways of algorithmic pressure influencing gig workers' proactive service behavior. This not only supplements more theoretical details for revealing the interactive mechanisms between gig work environment characteristics and stress responses in online service platforms, but also provides more targeted references and insights for optimizing work resource allocation in platform organizations from a "humanistic" perspective in terms of management strategies and tools.

Key words: algorithmic stressor, proactive service behavior, gig economy, cognitive appraisal of stress theory, digital gig workers

中图分类号:

B849: C93

张振铎, 国佳宁, 李豪, 王宏蕾. (2024). 挑战还是阻断?平台算法压力对数字零工主动服务行为的影响机制. 心理科学进展 , 32(11), 1768-1785.

ZHANG Zhenduo, GUO Jianing, LI Hao, WANG Honglei. (2024). Challenge or hindrance? The impact of platform algorithmic stressor on digital gig workers’ proactive service behavior. Advances in Psychological Science, 32(11), 1768-1785.

图/表 5

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算法管理下的零工工作特征	影响效应	来源	研究对象	对应算法管理功能
传统工作压力视角
工作负荷	情绪耗竭(+) 满意度(−)	Shevchuk et al. (2018)	外卖骑手	目标设定绩效管理日程安排工作解雇
	睡眠不足(+) 健康(−)	Wood et al. (2019)	零工工人
	员工创造力(−)	马君, 赵爽 (2022)	零工工人
工作/生活不平衡工作环境	工作压力(+) 冒险态度(+)	Nguyen-Phuoc et al. (2022)	外卖骑手
传统工作资源视角
工作资源工作意义	员工创造力(+)	马君, 赵爽 (2022)	零工工人	绩效管理日程安排目标设定薪酬激励
工作资源工作意义	心理韧性(+) 幸福感(+)	Granger et al. (2022)	专业零工
社会支持反馈	工作压力(−) 冒险态度(+) 道路安全合规性(+)	Nguyen-Phuoc et al. (2022)	外卖骑手
工作灵活性	工作幸福感(+)	Tarafdar et al. (2019)	专业零工
算法控制视角
算法控制	服务绩效	裴嘉良等(2021)	外卖骑手	监控追踪绩效管理日程安排目标设定薪酬激励工作解雇
	自我损耗(∪) 安全绩效(∩)	范志灵等(2023)	网约车司机
	工作不安全感(+) 离职倾向(+)	玉胜贤等(2024)	外卖骑手
规范压力时间压力疏离压力身心压力	身心耗竭(+) 工作退缩行为(+)	高雪原等(2023)	外卖骑手
算法评估约束	过度劳动(+)	裴嘉良等(2024)	零工工人
算法评估约束	交互性心理紧张(+) 情绪劳动−浅层表演(+) 情绪劳动−深层表演(−)	张志朋等(2024)	外卖骑手

算法管理下的零工工作特征	影响效应	来源	研究对象	对应算法管理功能
传统工作压力视角
工作负荷	情绪耗竭(+) 满意度(−)	Shevchuk et al. (2018)	外卖骑手	目标设定绩效管理日程安排工作解雇
	睡眠不足(+) 健康(−)	Wood et al. (2019)	零工工人
	员工创造力(−)	马君, 赵爽 (2022)	零工工人
工作/生活不平衡工作环境	工作压力(+) 冒险态度(+)	Nguyen-Phuoc et al. (2022)	外卖骑手
传统工作资源视角
工作资源工作意义	员工创造力(+)	马君, 赵爽 (2022)	零工工人	绩效管理日程安排目标设定薪酬激励
工作资源工作意义	心理韧性(+) 幸福感(+)	Granger et al. (2022)	专业零工
社会支持反馈	工作压力(−) 冒险态度(+) 道路安全合规性(+)	Nguyen-Phuoc et al. (2022)	外卖骑手
工作灵活性	工作幸福感(+)	Tarafdar et al. (2019)	专业零工
算法控制视角
算法控制	服务绩效	裴嘉良等(2021)	外卖骑手	监控追踪绩效管理日程安排目标设定薪酬激励工作解雇
	自我损耗(∪) 安全绩效(∩)	范志灵等(2023)	网约车司机
	工作不安全感(+) 离职倾向(+)	玉胜贤等(2024)	外卖骑手
规范压力时间压力疏离压力身心压力	身心耗竭(+) 工作退缩行为(+)	高雪原等(2023)	外卖骑手
算法评估约束	过度劳动(+)	裴嘉良等(2024)	零工工人
算法评估约束	交互性心理紧张(+) 情绪劳动−浅层表演(+) 情绪劳动−深层表演(−)	张志朋等(2024)	外卖骑手