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Influencing subjective well-being for business and sustainable development using big data and predictive regression analysis
Weerakkody, Vishanth J.P. Mahroof, Kamran Maruyama, Takao Lu, Shan
Weerakkody, Vishanth J.P.
Mahroof, Kamran
Maruyama, Takao
Lu, Shan
Publication Date
2020
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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/)
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Yes
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openAccess
Accepted for publication
27/07/2020
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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.
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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.
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Article