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    Influencing subjective well-being for business and sustainable development using big data and predictive regression analysis

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    Weerakkody_et_al_Journal_of_Business_Research.pdf (1.070Mb)
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    Publication date
    2020
    Author
    Weerakkody, Vishanth J.P.
    Sivarajah, Uthayasankar
    Mahroof, Kamran
    Maruyama, Takao
    Lu, Shan
    Keyword
    Big data
    Regression
    Well-being
    UN SDG goals
    Public sector
    Rights
    Crown Copyright © 2020 Published by Elsevier Inc. This is an Open Access article distributed under the Creative Commons CC-BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    Business leaders and policymakers within service economies are placing greater emphasis on well-being, given the role of workers in such settings. Whilst people’s well-being can lead to economic growth, it can also have the opposite effect if overlooked. Therefore, enhancing subjective well-being (SWB) is pertinent for all organisations for the sustainable development of an economy. While health conditions were previously deemed the most reliable predictors, the availability of data on people’s personal lifestyles now offers a new dimension into well-being for organisations. Using open data available from the national Annual Population Survey in the UK, which measures SWB, this research uncovered that among several independent variables to predict varying levels of people's perceived well-being, long-term health conditions, one's marital status, and age played a key role in SWB. The proposed model provides the key indicators of measuring SWB for organisations using big data.
    URI
    http://hdl.handle.net/10454/18006
    Version
    Published version
    Citation
    Weerakkody VJP, Sivarajah U, Mahroof K et al (2020) Influencing subjective well-being for business and sustainable development using big data and predictive regression analysis. Journal of Business Research. Accepted for publication.
    Link to publisher’s version
    https://doi.org/10.1016/j.jbusres.2020.07.038
    Type
    Article
    Collections
    Management and Law Publications

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