Your browser doesn't support javascript.
Influencing subjective well-being for business and sustainable development using big data and predictive regression analysis.
Weerakkody, Vishanth; Sivarajah, Uthayasankar; Mahroof, Kamran; Maruyama, Takao; Lu, Shan.
  • Weerakkody V; School of Management, University of Bradford, United Kingdom.
  • Sivarajah U; School of Management, University of Bradford, United Kingdom.
  • Mahroof K; School of Management, University of Bradford, United Kingdom.
  • Maruyama T; School of Management, University of Bradford, United Kingdom.
  • Lu S; School of Management, University of Bradford, United Kingdom.
J Bus Res ; 2020 Aug 19.
Article in English | MEDLINE | ID: covidwho-720587
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.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Year: 2020 Document Type: Article Affiliation country: J.jbusres.2020.07.038

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Year: 2020 Document Type: Article Affiliation country: J.jbusres.2020.07.038