Innovativeness, Work Flexibility, and Place Characteristics: A Spatial Econometric and Machine Learning Approach

This paper seeks to study work-related and geographical conditions under which innovativeness is stimulated through the analysis of individual regional data dating from just prior smartphone age. As a result, by using ISSP 2005 Work Orientations Survey, we are able examine role work flexibility, among other conditions, in relatively more traditional context that mostly excludes modern, smartphone-driven, remote-working practices. Our confirms freedom place, flexible hours, job security, living suburban areas, low stress, private business activity, ability take free time off important drivers innovation. In particular, spatial econometric model, identified an optimum level for weekly about 36 h, supported our findings tree-based ensemble models. The originality present particularly due its examination innovative output rather than general productivity integration person-level on addition novel methodological approach combines machine learning findings.