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Money talks, happiness walks: dissecting the secrets of global bliss with machine learning

2023; Taylor & Francis; Volume: 22; Issue: 1 Linguagem: Inglês

10.1080/14765284.2023.2245277

1476-5292

Rachana Jaiswal, Shashank Gupta,

Psychological Well-being and Life Satisfaction

ABSTRACTThis study endeavors to construct a model for prognosticating happiness by integrating an encompassing theoretical framework and scrutinizing various happiness constructs. The findings reveal that the Random Forest outperforms its counterparts, exhibiting an astounding accuracy rate of 92.2709. Furthermore, the results uncover a conspicuous and pronounced divergence between joyful and despondent nations concerning their GDP per capita. The former exhibits a remarkable ascendency in this economic indicator relative to their less contented counterparts. The research posits far-reaching policy, managerial, and social implications. It underscores its significance in steering the realization of the United Nations' Sustainable Development Goals (SDGs), including Goals 3, 4, 8, and 10. The study recommends that SDG-driven efforts should be bolstered to hasten the attainment of happiness in developing countries while promoting the adoption of data-driven decision-making approaches in policy formulation and the development of efficacious policies.KEYWORDS: Happiness PredictionSustainable Development GoalsRandom ForestDeveloping NationsMachine Learning AcknowledgmentsThe author(s) express their deep appreciation to Prof. Wenxuan Hou MAE (Editor-in-Chief), Prof. Aviral Kumar Tiwari (Lead Guest Editor) and the anonymous reviewers for their exceptional guidance, constructive feedback, and unwavering support during the peer review process. Their insightful perspectives and illuminating comments were crucial in refining the paper, enhancing its quality, and upholding its high standard.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsRachana JaiswalRachana Jaiswal is an Assistant Professor in the Department of Business Management, School of Management, HNB Garhwal (A Central) University, Srinagar Uttarakhand, India. Before joining the HNB Garhwal University in 2012, she served as an Assistant Professor at Central University Jharkhand (CUJ) and the University of Pune. She is Ph.D. (2022), UGC-JRF (2011), MBA (2011) from Pune University, and M.Com (2008) from Banaras Hindu University (BHU) and currently pursuing CMA (Final). She has guided more than 60 PG students and currently supervising one Ph.D. scholar. In addition, she has authored over 25 research papers and 20 chapters in reputed journals, won nine awards for best papers, and presented 60 research papers at international/national conferences. Her thrust area lay at the intersection of finance, human capital, and applied machine learning.Shashank GuptaShashank Gupta is an impact-driven software professional in Data Science and Machine Learning with an IT experience of 15+ years in the Fintech industry. He aspires to solve real-world problems using state-of-the-art techniques like Machine Learning, Deep Learning, and Data Science and perform at his best level to showcase the potential in the workplace for collective betterment. He is working as Senior Manager with Morgan Stanley since 2019 and has prior experience working with Product based (Dell, Chegg, GlobalLogic) and Services based (UST Global, Syntel, RSystems) organizations. He holds Diploma in Artificial Intelligence and Machine Learning (DAIML) from the University of Hyderabad (UoH) Master of Computer Application (MCA) from GLA University. His interest lies in finance, machine learning, risk management, and compliance & governance.