Behind the screen: exploring the job resources and demands of digital content creation

Purpose Using the job demands-resources (JD-R) theory, our study aimed to examine the resources and demands of digital content creation (DCC), a growing occupation that remains underexplored from JD-R perspective. We focus on Indian YouTubers to offer contextually grounded insights into this emerging form of work. Design/methodology/approach Based on 21 semi-structured telephonic interviews with Indian YouTubers, this study examines the job demands and resources that define DCC, with a specific focus on the Indian context. Findings Drawing on JD-R theory, we identified the job resources and demands of the DCC occupation, which occurred at occupational, social, and digital ecosystem levels. The data analysis revealed several occupational, social, and digital ecosystem level resources and demands unique to this occupation (e.g. audience response uncertainty, and online hostility and trolling). The digital ecosystem level came up as a unique aspect of DCC, distinguishing it from other self-employed occupations. Under this level are resources such as “Digital platform capabilities” and demands such as “Navigating platform dynamics.” The findings show that the job resources and demands are interrelated and vary in their centrality. Research limitations/implications The grayscale diagram provides a nuanced understanding of the sources of the job resources and demands and their centrality, enabling both research and practice to accurately identify the areas to focus on for future research and effective interventions. Originality/value This study examines the job resources and demands of a growing but understudied occupational group. It extends the JD-R framework by developing a multi-level JD-R Grayscale Centrality Diagram, categorizing resources and demands into occupational, social, and digital ecosystem levels. The diagram reflects their centrality based on frequency and emphasis in participant accounts and captures their complex interrelations across levels, which are often oversimplified in existing research.