Exploring the Patterns of Job Satisfaction for Individuals Aged 50 and over from Three Historical Regions of Romania. An Inductive Approach with Respect to Triangulation, Cross-Validation and Support for Replication of Results

In this paper, we explore the determinants of being satisfied with a job, starting from a SHARE-ERIC dataset (Wave 7), including responses collected from Romania. To explore and discover reliable predictors in this large amount of data, mostly because of the staggeringly high number of dimensions, w...

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Main Authors: Daniel Homocianu, Aurelian-Petruș Plopeanu, Nelu Florea, Alin Marius Andrieș
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/10/7/2573
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spelling doaj-5ce3562a45fa4d3aafc31ec072eb9d852020-11-25T03:54:07ZengMDPI AGApplied Sciences2076-34172020-04-01102573257310.3390/app10072573Exploring the Patterns of Job Satisfaction for Individuals Aged 50 and over from Three Historical Regions of Romania. An Inductive Approach with Respect to Triangulation, Cross-Validation and Support for Replication of ResultsDaniel Homocianu0Aurelian-Petruș Plopeanu1Nelu Florea2Alin Marius Andrieș3Department of Accounting, Business Information Systems and Statistics, Faculty of Economics and Business Administration (FEAA), Alexandru Ioan Cuza University of Iași (UAIC), Carol I Boulevard, No.22, 700505 Iași, RomaniaInstitute of Interdisciplinary Research, Department of Social Sciences and Humanities, UAIC, Lascar Catargi Street, No.54, 700107 Iași, RomaniaDepartment of Management, Marketing and Business Administration, FEAA, UAIC, Carol I Boulevard, No.22, 700505 Iași, RomaniaDepartment of Finance, Currency and Public Administration, FEAA, UAIC, Carol I Boulevard, No.22, 700505 Iași, RomaniaIn this paper, we explore the determinants of being satisfied with a job, starting from a SHARE-ERIC dataset (Wave 7), including responses collected from Romania. To explore and discover reliable predictors in this large amount of data, mostly because of the staggeringly high number of dimensions, we considered the triangulation principle in science by using many different approaches, techniques and applications to study such a complex phenomenon. For merging the data, cleaning it and doing further derivations, we comparatively used many methods based on spreadsheets and their easy-to-use functions, custom filters and auto-fill options, DAX and Open Refine expressions, traditional SQL queries and also powerful 1:1 merge statements in Stata. For data mining, we used in three consecutive rounds: Microsoft SQL Server Analysis Services and SQL DMX queries on models built involving both decision trees and naive Bayes algorithms applied on raw and memory consuming text data, three LASSO variable selection techniques in Stata on recoded variables followed by logistic and Poisson regressions with average marginal effects and generation of corresponding prediction nomograms operating directly in probabilistic terms, and finally the WEKA tool for an additional validation. We obtained three Romanian regional models with an excellent accuracy of classification (AUROC > 0.9) and found several peculiarities in them. More, we discovered that a good atmosphere in the workplace and receiving recognition as deserved for work done are the top two most reliable predictors (dual-core) of career satisfaction, confirmed in this order of importance by many robustness checks. This type of meritocratic recognition has a more powerful influence on job satisfaction for male respondents rather than female ones and for married individuals rather unmarried ones. When testing the dual-core on respondents aged 50 and over from most of the European countries (more than 75,000 observations), the positive surprise was that it undoubtedly resisted, confirming most of our hypotheses and also the working principles of support for replication of results, triangulation and the golden rule of robustness using cross-validation.https://www.mdpi.com/2076-3417/10/7/2573job satisfactiondata mining (DM)decision treesnaive Bayes and LASSOlogistic and Poisson regressions with average marginal effectsprediction nomograms
collection DOAJ
language English
format Article
sources DOAJ
author Daniel Homocianu
Aurelian-Petruș Plopeanu
Nelu Florea
Alin Marius Andrieș
spellingShingle Daniel Homocianu
Aurelian-Petruș Plopeanu
Nelu Florea
Alin Marius Andrieș
Exploring the Patterns of Job Satisfaction for Individuals Aged 50 and over from Three Historical Regions of Romania. An Inductive Approach with Respect to Triangulation, Cross-Validation and Support for Replication of Results
Applied Sciences
job satisfaction
data mining (DM)
decision trees
naive Bayes and LASSO
logistic and Poisson regressions with average marginal effects
prediction nomograms
author_facet Daniel Homocianu
Aurelian-Petruș Plopeanu
Nelu Florea
Alin Marius Andrieș
author_sort Daniel Homocianu
title Exploring the Patterns of Job Satisfaction for Individuals Aged 50 and over from Three Historical Regions of Romania. An Inductive Approach with Respect to Triangulation, Cross-Validation and Support for Replication of Results
title_short Exploring the Patterns of Job Satisfaction for Individuals Aged 50 and over from Three Historical Regions of Romania. An Inductive Approach with Respect to Triangulation, Cross-Validation and Support for Replication of Results
title_full Exploring the Patterns of Job Satisfaction for Individuals Aged 50 and over from Three Historical Regions of Romania. An Inductive Approach with Respect to Triangulation, Cross-Validation and Support for Replication of Results
title_fullStr Exploring the Patterns of Job Satisfaction for Individuals Aged 50 and over from Three Historical Regions of Romania. An Inductive Approach with Respect to Triangulation, Cross-Validation and Support for Replication of Results
title_full_unstemmed Exploring the Patterns of Job Satisfaction for Individuals Aged 50 and over from Three Historical Regions of Romania. An Inductive Approach with Respect to Triangulation, Cross-Validation and Support for Replication of Results
title_sort exploring the patterns of job satisfaction for individuals aged 50 and over from three historical regions of romania. an inductive approach with respect to triangulation, cross-validation and support for replication of results
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2020-04-01
description In this paper, we explore the determinants of being satisfied with a job, starting from a SHARE-ERIC dataset (Wave 7), including responses collected from Romania. To explore and discover reliable predictors in this large amount of data, mostly because of the staggeringly high number of dimensions, we considered the triangulation principle in science by using many different approaches, techniques and applications to study such a complex phenomenon. For merging the data, cleaning it and doing further derivations, we comparatively used many methods based on spreadsheets and their easy-to-use functions, custom filters and auto-fill options, DAX and Open Refine expressions, traditional SQL queries and also powerful 1:1 merge statements in Stata. For data mining, we used in three consecutive rounds: Microsoft SQL Server Analysis Services and SQL DMX queries on models built involving both decision trees and naive Bayes algorithms applied on raw and memory consuming text data, three LASSO variable selection techniques in Stata on recoded variables followed by logistic and Poisson regressions with average marginal effects and generation of corresponding prediction nomograms operating directly in probabilistic terms, and finally the WEKA tool for an additional validation. We obtained three Romanian regional models with an excellent accuracy of classification (AUROC > 0.9) and found several peculiarities in them. More, we discovered that a good atmosphere in the workplace and receiving recognition as deserved for work done are the top two most reliable predictors (dual-core) of career satisfaction, confirmed in this order of importance by many robustness checks. This type of meritocratic recognition has a more powerful influence on job satisfaction for male respondents rather than female ones and for married individuals rather unmarried ones. When testing the dual-core on respondents aged 50 and over from most of the European countries (more than 75,000 observations), the positive surprise was that it undoubtedly resisted, confirming most of our hypotheses and also the working principles of support for replication of results, triangulation and the golden rule of robustness using cross-validation.
topic job satisfaction
data mining (DM)
decision trees
naive Bayes and LASSO
logistic and Poisson regressions with average marginal effects
prediction nomograms
url https://www.mdpi.com/2076-3417/10/7/2573
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