The Reality and the Effect on Organizational Commitment of Myanmar Workers’ Consciousness: A Case of Blue Collar Worker in Manufacturing Industry

2019 ◽  
Vol 10 (3) ◽  
pp. 17-35
Author(s):  
YeongSam Yun ◽  
HtetMyet Sandy Kyaw
Keyword(s):  
Organizational Commitment ◽  
Manufacturing Industry ◽  
Blue Collar ◽  
Blue Collar Worker

scholarly journals An Empirical Study on the Model of Self-Efficacy and Organizational Citizenship Behavior Transmitted through Employee Engagement, Organizational Commitment and Job Satisfaction in the Thai Automobile Parts Manufacturing Industry

2021 ◽  
Vol 7 (3) ◽  
pp. 170
Author(s):  
Khahan Na-Nan ◽  
Suteeluck Kanthong ◽  
Jamnean Joungtrakul
Keyword(s):  
Job Satisfaction ◽  
Organizational Commitment ◽  
Employee Engagement ◽  
Organizational Citizenship ◽  
Organizational Citizenship Behavior ◽  
Self Efficacy ◽  
Manufacturing Industry ◽  
Statistical Significance ◽  
Citizenship Behavior ◽  
Parts Manufacturing

This research aims to study the direct and indirect influence of self-efficacy on organizational citizenship behavior transmitted through employee engagement, organizational commitment and job satisfaction, and to examine employee engagement, organizational commitment and job satisfaction as partial or full mediators. The study samples were 400 employees in the automobile parts manufacturing industry. The study instruments used by previous researchers were applied and back translation was conducted on all questionnaire items. Content validity and reliability was then tested prior to using them for data collection. Direct and indirect influences and mediators were analyzed with the Hayes Model 81 using the PROCESS Program. Results revealed that self-efficacy had a direct influence on organizational citizenship behavior with statistical significance, with an indirect influence transmitted through employee engagement, organizational commitment and job satisfaction. Employee engagement, organizational commitment and job satisfaction functioned as partial mediators between self-efficacy and organizational citizenship behavior with statistical significance. The model was based on the theory of self-efficacy to express organizational citizenship behavior. However, the study results showed that employee engagement, organizational commitment and job satisfaction play roles as mediators in transmission of effective organizational citizenship behavior. Therefore, these mediators are important factors that can accurately explain organizational citizenship behavior.

scholarly journals A Case Study Exploration of Blue-Collar Worker Retirement Plan Investment Decisions

2016 ◽  
Vol 15 (1) ◽  
Author(s):  
Mark Griffin ◽  
Steven Tippins
Keyword(s):  
Investment Decisions ◽  
Blue Collar ◽  
Blue Collar Worker ◽  
Treasury Bonds ◽  
The Great Recession ◽  
Blue Collar Workers ◽  
New Family ◽  
Retirement Accounts ◽  
Participant Group ◽  
Retirement Investment

The finances of blue-collar workers were the most acutely impacted as these workers lost their jobs during the Great Recession of 2007 through 2009. The literature revealed a minimal understanding of how blue-collar workers allocated funds for their retirement, and what their investments might be when they invested. To address this problem, the current qualitative study addressed (a) how blue-collar workers chose to invest or not invest for retirement and (b) how blue-collar workers diversified their portfolio if they chose to invest. Theoretical foundations of the study were based on regret theory and prospect theory. A nonrandom purposeful sample of 10 blue-collar worker participants answered 19 open-ended questions. Data from these questions were analyzed inductively. Findings revealed that, as participants reached the age of 30, they started to consider investing for their retirement. Participants under the age of 30 were not as likely to invest. Only one person over the age of 30 did not invest for retirement. The factors that contributed to these blue-collar workers’ investment decisions for retirement were based on an employer-provided retirement accounts, the fear of running out of money later in life during retirement, and the addition of new family members. One of the most popular retirement investment products for the participant group, which included mechanics, laborers, and material movers, was the U.S. Treasury bonds. Other popular investments were mutual funds, 401(k)s, and IRAs. These findings may inform researchers who are conducting a study on the investment decisions of blue-collar workers. The findings can also be beneficial for other blue-collar workers by showing them that other blue-collar workers do invest, and by revealing their rationales in doing so.

On the Implications of Automation in the Manufacture Industry on United States Residing Blue-Collar Workers

2021 ◽  
Author(s):  
Raghav Sriram
Keyword(s):  
United States ◽  
Social Order ◽  
Manufacturing Industry ◽  
The United States ◽  
Industrial Robots ◽  
Blue Collar ◽  
United States Bureau ◽  
Blue Collar Workers ◽  
Robotic Devices ◽  
New Jobs

A study done by the United States Bureau of Labor Statistics found that of men ages 25 to 54, 13.2% were without work (Eberstadt). The British Broadcasting Company (BBC) believes this can be attributed to the increased use of robots—specifically in the manufacturing industry. Since 2000, industrial robots have replaced 1.7 million manufacturing jobs worldwide, and of these 1.7 million jobs, 260,000 were lost in the United States (Robots’ 'to replace up to 20 million factory jobs' by 2030) displaying the massive contribution automation has had on America’s unemployment crisis. According to Workism Is Making Americans Miserable, blue-collar jobs produce tangible products such as coal steel rods, and houses (Thompson) allowing manufacturers to easily replace them with more economically efficient robots. When 1,896 experts were asked the following question, “Will networked, automated, artificial intelligence (AI) applications and robotic devices have displaced more jobs than they have created by 2025?” Half responded that they envision a future in which robots and digital agents have displaced significant numbers of blue-collar workers with much-expressing concern that this will lead to vast increases in income inequality and a breakdown of social order. The other half believed technology will have not displaced more jobs than it creates by 2025 and predicted human ingenuity will create new jobs, industries, and ways of living to ensure jobs are created (Smith). This uncertainty for what lies ahead in the future makes it imperative to determine the extent automation in the manufacturing industry has impacted blue-collar workers in present society. While automation has led to the development and creation of many new jobs, most of these jobs are unattainable for the traditional blue-collar worker causing many to be replaced and without work. Manufacturing corporations must address this issue by improving the effectiveness of worker training programs and providing financial support for workers who have been displaced.

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