This study examines the relationship between job satisfaction and employee performance among engineering professionals in the infrastructure construction sector. The construction industry is fast-paced and demanding, making it important to understand how job satisfaction impacts worker performance. A structured questionnaire was used to collect data from 98 participants, selected using Cochran’s formula. The survey focused on key factors such as work environment, salary and benefits, career growth, work-life balance, relationships with supervisors, and recognition. Data were analyzed using SPSS version 27, applying descriptive statistics, correlation, and regression analysis. The findings show that compensation, recognition, and work-life balance have a strong positive influence on performance. In contrast, factors like career development and work environment had a positive but less significant effect. The regression analysis confirmed compensation and recognition as the strongest predictors of performance. These results suggest that practical, immediate job satisfaction factors have a greater impact on performance than long-term ones. Construction companies can use these insights to develop better policies that improve employee satisfaction and, in turn, project success.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Job Satisfaction and Employee Performance in Infrastructure Construction—A Case Study in South India

  • Hendry Poulose,
  • Nincy Jose

摘要

This study examines the relationship between job satisfaction and employee performance among engineering professionals in the infrastructure construction sector. The construction industry is fast-paced and demanding, making it important to understand how job satisfaction impacts worker performance. A structured questionnaire was used to collect data from 98 participants, selected using Cochran’s formula. The survey focused on key factors such as work environment, salary and benefits, career growth, work-life balance, relationships with supervisors, and recognition. Data were analyzed using SPSS version 27, applying descriptive statistics, correlation, and regression analysis. The findings show that compensation, recognition, and work-life balance have a strong positive influence on performance. In contrast, factors like career development and work environment had a positive but less significant effect. The regression analysis confirmed compensation and recognition as the strongest predictors of performance. These results suggest that practical, immediate job satisfaction factors have a greater impact on performance than long-term ones. Construction companies can use these insights to develop better policies that improve employee satisfaction and, in turn, project success.