Employees discrimination issues based on the statistical analysis using SPSS (Case of Georgia, Republic of)

Abstract

Every single person has right to work in a free and fair environment. But unfortunately, there are some cases all over the world which show that the situation in the workplaces is opposite. There are different types of discrimination of employees. That is why it is so much important to study the basis of all the types discrimination, find out the crucial problems in each one and work out the relevant solutions to facilitate the victims or potential victims for the improvement of their working conditions. The paper studies employee’s discrimination issues in the organization. For leading the management of the organization efficiently, it is of great importance to conduct a detailed study of the ongoing processes, analyze the results of the study and develop measures based on the information received as a result of the analysis for improving the management. The purpose of the present paper is to identify discrimination in the organization for further prevention of such facts. For this purpose, a special questionnaire was developed. The Methodology Statistical analysis of discrimination issues was made using the Statistical Package for the Social Sciences (SPSS). The questionnaire was filled out by 488 respondents living and working in Georgia. 5 hypotheses were determined in order to find out the correlation between some indicators and their impact level to discrimination in the workplace. Evaluation of the impact of those indicators was performed using Multiple Analysis of Variance (MANOVA) by using multivariate analysis.

Authors and Affiliations

Nino PARESASHVILI, Mzia TIKISHVILI, Teona EDZGVERADZE

Keywords

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  • EP ID EP695382
  • DOI 10.46656/access.2021.2.2(5)
  • Views 139
  • Downloads 0

How To Cite

Nino PARESASHVILI, Mzia TIKISHVILI, Teona EDZGVERADZE (2021). Employees discrimination issues based on the statistical analysis using SPSS (Case of Georgia, Republic of). ACCESS: Access to science, business, innovation in the digital economy, 2(2), -. https://europub.co.uk/articles/-A-695382