Objective
The main objective of this study is to investigate the utilization of wearable smart sensors as a means to enhance employee well-being and performance within the workplace. This research proposal introduces a comprehensive approach, aiming to employ wearable smart sensors for the empirical examination of the factors that impact employees' well-being and productivity during operational tasks. The study will focus on specific sectors, such as manufacturing and services, utilizing data from these sensors to monitor individual actions, group behaviors, and environmental influences. In certain instances, the study will also consider the attitudes and behaviors of customers as relevant contributing factors. Overall, this research seeks to provide valuable insights into the potential of wearable technology in comprehending and improving the work-related factors affecting employees. This study adopts a qualitative case study design, specifically employing a multiple case study approach to explore and compare various strategies and approaches employed in assessing the well-being and productivity of workers. The significance of this research lies in its emphasis on often overlooked human factors that exert a substantial influence on employee well-being and productivity within the workplace. By harnessing the capabilities of wearable smart sensors, the study is poised to offer real-time data on individual attitudes, group dynamics, and environmental variables that shape employees' experiences while on the job. In essence, this study endeavors to contribute to workplace improvement by comprehensively understanding and addressing these pivotal human dimensions. The findings of this study will be disseminated through publication in reputable research journals, along with presentations at seminars, workshops, and the authoring of book chapters to facilitate the sharing of knowledge and its impact on the wider academic and professional community.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- social scienceseconomics and businesseconomicsproduction economicsproductivity
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
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Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European FellowshipsCoordinator
56126 Pisa
Italy