Measurement of organizational happiness

Eyal Eckhaus

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Personal well-being studies have reported a strong positive relationship between happiness and productivity, determining the need of the Human Resource (HR) function to regularly monitor and maintain employee happiness and satisfaction. However, lack of scientific precision in defining the term ‘happiness’ and inconsistency in its measurement have made this research area more challenging. The study proposes an automated detection technique that uses Natural Language Processing (NLP), to offer the HR function an easy means of implementing a technique that enables constant monitoring of happiness levels, and leverages the data into a tool for evaluating the effectiveness of programs, policies, and practices. A case study is presented to demonstrate the framework’s effectiveness.

Original languageEnglish
Title of host publicationAdvances in Human Factors, Business Management and Leadership - Proceedings of the AHFE 2017 International Conferences on Human Factors in Management and Leadership, and Business Management and Society
EditorsTibor Barath, Jussi Ilari Kantola, Salman Nazir
Pages266-278
Number of pages13
DOIs
StatePublished - 2018
EventAHFE 2017 International Conferences on Human Factors in Management and Leadership, and Business Management and Society, 2017 - Los Angeles, United States
Duration: 17 Jul 201721 Jul 2017

Publication series

NameAdvances in Intelligent Systems and Computing
Volume594
ISSN (Print)2194-5357

Conference

ConferenceAHFE 2017 International Conferences on Human Factors in Management and Leadership, and Business Management and Society, 2017
Country/TerritoryUnited States
CityLos Angeles
Period17/07/1721/07/17

Keywords

  • Email sentiments
  • HR metrics
  • Happiness
  • Natural language processing

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