Details

Autor(en) / Beteiligte

• Chen, Liwei
• Hsieh, J. J. Po-An
• Rai, Arun

Titel

How Does Intelligent System Knowledge Empowerment Yield Payoffs? Uncovering the Adaptation Mechanisms and Contingency Role of Work Experience

Ist Teil von

• Information systems research, 2022-09, Vol.33 (3), p.1042-1071

Ort / Verlag

Linthicum: INFORMS

Erscheinungsjahr

2022

Quelle

Informs

Beschreibungen/Notizen

• Intelligent systems—incorporating computational tools, learning algorithms, and statistical models—can generate knowledge to empower employees in how they conduct their work and increase their job performance. How can organizations realize this potential? Our in-depth study of transformation of work with intelligent systems in a technology maintenance service company provides managerial insights to this question. Although knowledge from intelligent systems can empower employees, employees will need to adapt how they work with intelligent systems to improve their job performance. Interestingly, they can leverage the empowerment to adapt in two ways: maximize benefits , where they use the system to its full potential in conducting work, and minimize disturbances, where they reduce role conflict with the system in conducting work. Although inexperienced employees leverage the empowerment to use the system to its full potential, experienced employees leverage the empowerment to minimize role conflict with the system. How empowered employees realize job performance gains requires understanding how employees channel their empowerment: maximize benefits through use of the system or minimize disturbances through role conflict with the system. Differentiating how inexperienced and experienced employees channel empowerment to increase job performance will enable managers to effectively manage the transformation of work for these two groups. Intelligent systems (IntelSys) are transforming the nature of work as humans and machines collectively perform tasks in novel ways. Although intelligent systems empower employees with algorithm-generated knowledge, they require employees to adapt how they work to enhance their job performance. We draw on the coping-adaptation framework as the overarching theoretical lens to explain how employees’ perceptions of IntelSys knowledge as an empowering external coping resource affect the mechanisms through which they adapt to IntelSys-induced changes to their work, as well as how their internal coping resources regulate their adaptation. Our coping-adaptation explanation of intelligence augmentation integrates (i) the empowering role of external coping resources, specifically IntelSys knowledge, captured as intelligent system knowledge empowerment (ISK-Emp); (ii) the benefit-maximizing adaptation mechanism (through infusion use enhancement) and the disturbance-minimizing adaptation mechanism (through role conflict reduction) that channel the impact of ISK-Emp on job performance; and (iii) the regulating role of internal resources, specifically, employees’ work experience, in influencing the importance of the adaptation mechanisms for the employee. We conduct studies in three distinct settings in which different intelligent systems were implemented to support employees’ knowledge work. Our findings show that ISK-Emp increases job performance through each of the two adaptation mechanisms. The benefit-maximization mechanism (via enhanced infusion use) plays a more important role for novice employees than for experienced employees, whereas the disturbance-minimization mechanism (via reduced role conflict) has higher importance for experienced employees than for novice employees. Our work provides insights into the critical role of adaptation mechanisms in linking ISK-Emp with performance outcomes and into the relative importance of the adaptation mechanisms through which job performance payoffs are realized by novice and experienced employees.