Quantified photo-analysis for indoor and outdoor places of hybrid working. Location-specific approach

Purpose The purpose of this study is to support successful interdisciplinary research in understanding the leverage points between employee experience and the multitude of environmental factors. From a design knowledge perspective, the theoretical content is related to the environmental demands-resources model and Kaplan’s attention restoration theory. Gibson’s theory of affordances enlightens the latent action possibilities the environment offers individuals. The photo analysis originates from press photograph story analysis by Kedra and is customised to fit handling large quantities of photographs. Design/methodology/approach The increase in hybrid work has strengthened the trend towards using more flexible, space-efficient and non-territorial workplaces and other places not traditionally designed for work. Novel methods fitting interdisciplinary research are needed for analysing visual–spatial characteristics of the built work environment. This paper introduces a photo analysis method to advance understanding of workers’ use of indoor and outdoor physical surroundings. Findings The proposed quantified photo-analysis method provides similar structuring and rating for both indoor and outdoor built environments. The three main categories are nature elements (sky, ice or snow, water, greenery), static elements (built environment) and dynamic elements (people, furniture and vehicles) visually present at the same location as the worker or are seen through a window view. Originality/value The proposed photo-analysis provides method to study three-dimensional physical hybrid work environments at organisations’ properties and other places, which was not considered in earlier work environment research. The self-reported photos documenting workers’ views at their workstations are material for analysing the built environment’s affordances visually. Photo-analysis fits to machine vision analysis. The quantified visual data set is considered comparable or mergeable with the other quantified data sets produced by the participating disciplines to search for evidence of health – or well-being-related impacts.