Effect of Transparency of Algorithmic Performance Management on Proactive Work Behavior: Role of Motivation to Improve Performance and Psychological Ownership

Introduction

The development and implementation of algorithmic management in organizations have created new opportunities to increase organizational productivity, improve employee work patterns, and so on. With the rise of digitalization, algorithms are increasingly central to business management (Janssen & Kuk, 2016). An algorithm is considered to be a computational formula that autonomously makes decisions based on statistical models or decision rules without explicit human intervention (Lee, 2018). Although algorithm management is often not seen as a manager, it can play a managerial role in the shaping of employee behavior (Stark & Pais, 2020). An increasing number of activities in organizations are being performed by algorithms (Meijerink & Bondarouk, 2023), taking on the role of a colleague or supervisor who transmits information: for example, managerial functions such as monitoring, goal setting, scheduling, performance management, payroll management, and job termination (Parent-Rocheleau & Parker, 2022). Algorithm transparency is a crucial factor in the pursuit of continuous improvement of employee performance in organizations. Enhancing algorithm transparency can boost individuals' trust and dependence on algorithm-assisted decision-making (You et al., 2022).

Specifically, the transparency of algorithmic performance management (TAPM) is defined as the level of awareness and understanding of how the system uses algorithmic evaluations and forms employee performance scores based on complex quantifiable data, which is typically generated in real-time (Bujold et al., 2022). Transparency refers to people's perception of the received information (Schnackenberg & Tomlinson, 2016) and broadly refers to the disclosure of algorithm operations, processes, and output results by users (Shin, 2021). The transparency of algorithms is related to the degree of disclosure of algorithm-related information (You et al., 2022). We live in an era where algorithms are used, and more and more organizations are using algorithmic performance management to measure and reward outstanding employees. Employees are increasingly concerned about how the system uses algorithms to evaluate and generate employee performance scores, the so-called transparency of algorithmic performance management.

Organizational disclosure of the transparency of algorithmic performance management contributes to the fairness, efficiency, and motivation of employees in their work. Previous studies have pointed out that the incomplete transparency and openness of algorithms provide employees with a certain degree of privacy and space. Without excessive monitoring, this allows them to work more confidently, encouraging them to demonstrate creativity more freely and promoting organizational innovation and improvement. The opacity of algorithm performance management can strip employees of their ability to fully understand and manage their work, limiting their voice and power maintenance (Duggan et al., 2020). This also reduces the willingness of employees to take proactive actions (Gal et al., 2020). Transparency can ensure fair outcomes in the performance management processes of organizations, reduce information asymmetries, ensure accountability, and enable individuals to take responsibility for their actions (Al-Sulaiti et al., 2023). At the same time, opacity can undermine employees' trust in algorithms and make it harder to determine responsibility, as they may withhold important information or behavior for fear of damaging their interests (Langer & König, 2023).