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

被引:18
|
作者
Weerakkody, Vishanth [1 ]
Sivarajah, Uthayasankar [1 ]
Mahroof, Kamran [1 ]
Maruyama, Takao [1 ]
Lu, Shan [1 ]
机构
[1] Univ Bradford, Sch Management, Bradford, W Yorkshire, England
基金
欧盟地平线“2020”;
关键词
Big data; Regression; Well-being; UN SDG goals; Public sector; MULTINOMIAL LOGISTIC-REGRESSION; MENTAL-HEALTH; DATA ANALYTICS; CARE; RELIGION; INCOME; SATISFACTION; MODEL; INTELLIGENCE; PERFORMANCE;
D O I
10.1016/j.jbusres.2020.07.038
中图分类号
F [经济];
学科分类号
02 ;
摘要
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 wellbeing 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.
引用
收藏
页码:520 / 538
页数:19
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