A NEW WORKPLACE SERVICE PROVISION MODEL FOR THE KNOWLEDGE WORKERS

Date

2024-1-10

Author

SARI, RAMAZAN

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Office workplaces are specialized environments presenting proper workable ambiance and social and communal services for the knowledge workers. The interior architectural parameters are targeted to improve the knowledge workers' productivity, comfort, and well-being. There is a growing demand for personalization and customization in the workplace environment, together with a high level of flexibility regarding where and when to work the knowledge worker. The current workplace services practices were not successful in meeting these growing demands. The study envisions that each knowledge worker can be matched with a temporary/dynamic workspace that suits their personal choices and task requirements through an intelligent matching/bidding system. The proposed system aims to outsource new office workplace service provision by integrating semantic web applications, smart contracts, and ambient intelligence. The new paradigm cannot only meet the participants' emerging demands but also improve occupancy satisfaction and decrease the operation costs of the organizations. The model was formalized and evaluated by web ontology models. The validation of the model was accomplished by use of literature and in-field based studies. Firstly, the validity of the arguments was investigated in a survey, and a simple test for user interface demo for workplace configuration was executed with the knowledge workers in a co-working office. Then, the applicability of the model in the real world was investigated by interviewing facility managers. The facility managers expressed application-based concerns for the new model and addressed practical handicaps and challenges. However, the model was applicable and presented many advantages for the industry stakeholders.

Subject Keywords

Workplace Service Provisions, Workplace Comfort & Wellbeing Parameters, Smart Contract, Web Ontology Models, Office Workplace Facility Management

URI

https://hdl.handle.net/11511/108277

Collections

Graduate School of Natural and Applied Sciences, Thesis