Motivation and Labor Productivity in the Age of Automation

This study presents an experimental investigation into the preferences of specialists when choosing job offers in the digital economy. Using conjoint analysis and regression models, the relative importance of key offer parameters is evaluated: salary level, schedule flexibility, workload, contract structure, and the share of tasks involving artificial intelligence. The study relies on online survey data, which enables identification of preference heterogeneity by gender, work experience, current employment conditions, and intensity of AI use. The results demonstrate that, for most respondents, salary size and schedule flexibility remain the decisive factors, while attitudes toward AI and contract structure vary significantly depending on the worker’s profile. Special attention is paid to the calculation of the trade-off (monetary compensation) for changes in each offer parameter, as well as to the analysis of the relative importance of attributes. The findings have practical implications for companies shaping HR strategies in the era of automation, and suggest individualized approaches to the design of job offers.