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Aesthetic signals in organizational space: AI-driven visual contrast analysis of coworking and open-plan offices
The Australian National University, Australia.ORCID iD: 0000-0003-2905-6836
The Australian National University, Australia.ORCID iD: 0000-0002-0363-1460
Excelia Business School, CERIIM, France; Corvinus Institute for Advanced Studies (CIAS), Hungary.ORCID iD: 0000-0001-6649-6422
Deakin University, Australia.ORCID iD: 0000-0003-1583-641X
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2026 (English)In: Journal of Management and Organization, ISSN 1833-3672, E-ISSN 1839-3527, Vol. 32, no 1, p. 139-156Article in journal (Refereed) Published
Abstract [en]

This study explores the visual aesthetics of organizational space by contrasting coworking spaces with traditional open-plan offices. Drawing on signaling theory and symbolic interactionism, we examine how ambience communicates symbolic meaning. Employing an archaeological approach to retrieve large-scale online photo data from Coworker and Pinterest, we then apply AI-driven deep learning visual contrast analysis to reveal clear aesthetic distinctions in organizational space. Coworking spaces evoke a homely, dining-room-like ambiance, with artwork, plants, warmer color palettes, and a more homely and hospitable ambience. Traditional open-plan offices, by contrast, tend toward cooler colors and industrial design elements. Findings suggest that coworking spaces visually signal greater affective and sensory value, promoting belonging, creativity, and warmth. The study contributes to organizational space theory by theorizing how visual aesthetics act as symbolic cues that shape workplace experiences and by introducing a methodological framework that integrates AI-based analysis with interpretive meaning-making. 

Place, publisher, year, edition, pages
Cambridge University Press, 2026. Vol. 32, no 1, p. 139-156
Keywords [en]
organizational space, photo data, signaling theory, visual AI-based analytics
National Category
Other Social Sciences Business Administration
Research subject
Business Administration
Identifiers
URN: urn:nbn:se:kau:diva-107765DOI: 10.1017/jmo.2025.10061ISI: 001606003400001Scopus ID: 2-s2.0-105021246204OAI: oai:DiVA.org:kau-107765DiVA, id: diva2:2018506
Available from: 2025-12-03 Created: 2025-12-03 Last updated: 2026-03-25Bibliographically approved

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Karpen, Ingo Oswald

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