The Impact of Big Five Personality Traits and Positive Psychological Strengths towards Job Satisfaction: a Review

Human resource can be a dynamic asset or a debilitating liability depending upon how well it is harnessed. Many progressive organizations around the world have begun to internalize this reality and keeping the human resource satisfied is considered one of the key factors for the success of any organization. Dispositional base of job satisfaction has gained renewed interest since job satisfaction is a mixture of beliefs and feelings. With an eye toward research and practice, the current study consolidates various literatures and examines the relationship between Big Five Personality, Positive psychological strengths towards job satisfaction. The study also takes into consideration the demographic impact towards job satisfaction. It provides acumen and a different magnitude for predicting job satisfaction apart from conventional variables like work itself, pay, promotion, supervision, co-workers

A Dispositional Approach to Examine the Impact towards Students Stressors in Indian Context

The current study explored the relationship between big five personality factors and various stressors of the students who are undergraduate, postgraduate and research scholars from nine colleges in North Chennai. The study is based on quantitative data with descriptive research design. The 20-item personality inventory developed by Donnellen et al. (2006) was used to analyse their personality and the stressors was measured using MSSQ (Medical Student Stressor Questionnaire) scale developed by Yusoff (2011). A total of 250 students were selected as respondents using cluster random sampling technique. It revealed a significant positive relationship with neuroticism and three types of stressors (academic, inter and intra personal and social). It also throws light on the personality trait, namely openness to experience played a major role in predicting the academic performance (CGPA). Through regression, it can be concluded that personality has a significant positive relationship with both academic and social stressors. The findings will provide appropriate measures for educators by realizing the importance of personality the student possesses and applying suitable strategies for them to improve their academic performance. The dispersal of the study’s findings will significantly help students and the educators in the region

The viability of neural network for modeling the impact of individual job satisfiers on work commitment in Indian manufacturing unit

This paper provides an exposition about application of neural networks in the context of research to find out the contribution of individual job satisfiers towards work commitment. The purpose of the current study is to build a predictive model to estimate the normalized importance of individual job satisfiers towards work commitment of employees working in TVS Group, an Indian automobile company. The study is based on the tool developed by Spector (1985) and Sue Hayday (2003).The input variable of the study consists of nine independent individual job satisfiers which includes Pay, Promotion, Supervision, Benefits, Rewards, Operating procedures, Co-workers, Work-itself and Communication of Spector (1985) and dependent variable as work commitment of Sue Hayday (2003).The primary data has been collected using a closed-ended questionnaire based on simple random sampling approach. This study employed the multilayer Perceptron neural network model to envisage the level of job satisfiers towards work commitment. The result from the multilayer Perceptron neural network model displayed with four hidden layer with correct classification rate of 70% and 30% for training and testing data set. The normalized importance shows high value for coworkers, superior satisfaction and communication and which acts as most significant attributes of job satisfiers that predicts the overall work commitment of employees

The viability of neural network for modeling the impact of individual job satisfiers on work commitment in Indian manufacturing unit

This paper provides an exposition about application of neural networks in the context of research to find out the contribution of individual job satisfiers towards work commitment. The purpose of the current study is to build a predictive model to estimate the normalized importance of individual job satisfiers towards work commitment of employees working in TVS Group, an Indian automobile company. The study is based on the tool developed by Spector (1985) and Sue Hayday (2003).The input variable of the study consists of nine independent individual job satisfiers which includes Pay, Promotion, Supervision, Benefits, Rewards, Operating procedures, Co-workers, Work-itself and Communication of Spector (1985) and dependent variable as work commitment of Sue Hayday (2003).The primary data has been collected using a closed-ended questionnaire based on simple random sampling approach. This study employed the multilayer Perceptron neural network model to envisage the level of job satisfiers towards work commitment. The result from the multilayer Perceptron neural network model displayed with four hidden layer with correct classification rate of 70% and 30% for training and testing data set. The normalized importance shows high value for coworkers, superior satisfaction and communication and which acts as most significant attributes of job satisfiers that predicts the overall work commitment of employees