Remote Workers Predicative Analysis

This research delves into the prediction of factors impacting job satisfaction among remote workers in the UK by:

• Assessing the accuracy of two job satisfaction management theories in a new dataset: Hackman and Oldham's (1976) Job Characteristic Model (JCM) and Herzberg's (1976) Two-Factor Theory.
• Investigating the mediating role of motivation in the relationship between job satisfaction and key elements such as autonomy, feedback, and task significance.
• Scrutinising the influence of intrinsic factors (advancement, the nature of the work itself, growth opportunities, recognition, and career advancement) and extrinsic factors (interpersonal relationships, salary, supervision, working conditions, and job security) on job satisfaction.

A robust sample size of over 10,000 remote workers in the United Kingdom was examined using a secondary dataset obtained from the sixth European Working Conditions Survey in 2015. The findings were subjected to scrutiny through three distinct statistical methods and advanced machine learning tools: Linear Mediation Model, Least Absolute Shrinkage and Selection Operator (LASSO), and Multiple Linear Regression (MLR).

Research Aim

To conduct a predictive analysis on the factors that influence the job satisfaction of remote worker in the UK and to explore the mediating role of motivation in this context.

Research Objectives

• To assess and test the accuracy and assumptions of the proposed factors of the JCM theory in a unique dataset, examining their correlation with remote workers in the UK.
• Based on literature, propose, and identify the mediating role of motivation between the relationship of JCM Theory and job satisfaction.
• To identify additional factors that influence job satisfaction by leveraging Herzberg's (1966) Dual-Factor Theory (instrinsic and extrinsic factors).
• Using advanced machine learning tools LASSO and OLS multiple linear regression, to conduct a predictive analysis on the factors influencing job satisfaction, drawing on variables derived from both the JCM and Herzberg's Dual-Factor theories.

Result

The findings supports the statistical assumptions of Hackman and Oldham (1976). Herzberg (1976) theory, on the other hand, produced an inconsistent result as assumptions of intrinsic factors held true while untrue for extrinsic factors. Furthermore, the research indicated that remote workers are primarily influenced by psychological and motivational factors. The top three factors strongly associated with job satisfaction were identified as motivation, achievement, and advancement, while job security and supervision exhibited significant relevance to job dissatisfaction.

Theortical Framework

Hypothesis 1: Autonomy has positive relationship with motivation

Hypothesis 2: Autonomy has positive relationship with JS

Hypothesis 3: Feedback has a positive relationship with motivation

Hypothesis 4: Feedback has a positive relationship with JS

Hypothesis 5: Task significance has a positive relationship with motivation

Hypothesis 6: Task significance has a positive relationship with JS

Hypothesis 7: Motivation has a positive relationship with JS

Regression Result:

Regression of Outcome Variable (JS) on Explanatory Variables (Dual-factor) and Control Variables

Regression of Mediator Variable (Motivation) on Explanatory Variables (JCM) and Control Variables

Regression of Outcome Variable (JS) on Explanatory Variables (JCM), Meditating Variable and Control Variables

LASSO Regression Result and Level of Importance to the Outcome Variable Job Satisfation

LASSO Regression Result Chart