Open AccessIndicators of Workers’ Satisfaction with Corporate Social Responsibility Initiatives in Construction Firms
Author(s) -
L. M. Amusan,
Maruosa Kathyrine Ehanire,
J. D Owolabi,
Rapheal A. Ojelabi
Publication year - 2021
Publication title -
xi'nan jiaotong daxue xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 21
ISSN - 0258-2724
DOI - 10.35741/issn.0258-2724.56.2.37
Subject(s) - likert scale , corporate social responsibility , data collection , descriptive statistics , sample (material) , scope (computer science) , job satisfaction , human resource management , scale (ratio) , consistency (knowledge bases) , business , marketing , population , human resources , psychology , knowledge management , public relations , computer science , management , political science , sociology , statistics , economics , mathematics , social psychology , geography , artificial intelligence , chemistry , developmental psychology , chromatography , programming language , demography , cartography
The concept of corporate social responsibility (CSR) is gradually becoming a universal phenomenon among industrialists in developing countries. Industrialists are progressively accepting it as a way of life in organizational development. Therefore, this research aimed at carrying out an exploratory study of the phenomenon, pointing out the relationship between CSR and employee job satisfaction. The study draws strength from fundamental underlying theories and relevant past work. Cohran’s and Slovin’s formulas were utilized to derive a population frame of 400. The authors used a sample size of 200 respondents. The essence of data collection guarantees that the research objectives can be appropriately organized and successfully achieved. A structured questionnaire calibrated in Likert Scale 1-5 was used as the data collection instrument. Content analysis was applied to process the collated questionnaires for consistency. The data were processed with the SPSS statistical tool using the descriptive statistics component. The scope of application of the research results includes Human resources management, Environmental policymaker, Industrial production management, industrial relation, and personnel management.