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Measurement of Organizational Happiness

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Advances in Human Factors, Business Management and Leadership (AHFE 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 594))

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Abstract

Personal well-being studies have reported a strong positive relationship between happiness and productivity, determining the need of the Human Resource (HR) function to regularly monitor and maintain employee happiness and satisfaction. However, lack of scientific precision in defining the term ‘happiness’ and inconsistency in its measurement have made this research area more challenging. The study proposes an automated detection technique that uses Natural Language Processing (NLP), to offer the HR function an easy means of implementing a technique that enables constant monitoring of happiness levels, and leverages the data into a tool for evaluating the effectiveness of programs, policies, and practices. A case study is presented to demonstrate the framework’s effectiveness.

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Author information

Authors and Affiliations

  1. Ariel University, 40700, Ariel, Israel

    Eyal Eckhaus

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  1. Eyal Eckhaus
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Correspondence to Eyal Eckhaus .

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Editors and Affiliations

  1. Belgafik Oy, University of Vaasa, Vaasa, Finland

    Jussi Ilari Kantola

  2. University of Szeged, Szeged, Hungary

    Tibor Barath

  3. Institute of Maritime Operations, University College of Southeast Norway, Borre, Norway

    Salman Nazir

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Eckhaus, E. (2018). Measurement of Organizational Happiness. In: Kantola, J., Barath, T., Nazir, S. (eds) Advances in Human Factors, Business Management and Leadership. AHFE 2017. Advances in Intelligent Systems and Computing, vol 594. Springer, Cham. https://doi.org/10.1007/978-3-319-60372-8_26

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  • DOI: https://doi.org/10.1007/978-3-319-60372-8_26

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  • Online ISBN: 978-3-319-60372-8

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