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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM66797

Impact of Workforce Training and Quality Management Practices on Production Performance

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM66797

Volume:

10 |

8 |

Aug 2026

Pages:

1-8

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM66797

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

MZR

Mohammed Zayan Raji

Management

Lovely Professional University

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NJTK

Narh Justice Tetteh Kwesi

Management

Lovely Professional University

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RM

Rafiatu Mustapha

Management

Lovely Professional University

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HI

Habibu Ibrahim

Management

Lovely Professional University

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AEK

Adjepong Edmund Kofi

Management

Lovely Professional University

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ST

Samuel Twum

Management

Lovely Professional University

FA

Francis Agyapong

Management

Lovely Professional University

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Mentors

DAS

Dr. Atul Sharma

Management

Lovely Professional University

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Abstract

Manufacturing performance depends on more than machinery and technology; it also reflects employee capability, disciplined quality practices, and the ability to improve production processes over time. This study examined the relationship of workforce training, quality management practices, and continuous improvement initiatives with production performance in a manufacturing context. A quantitative, descriptive design was used and primary data were collected through a structured questionnaire from 164 respondents associated with manufacturing-related work areas. Responses were analysed in SPSS using descriptive statistics, reliability testing, Pearson correlation, multiple regression, and ANOVA. The construct means were close to the neutral range, indicating moderate rather than strong agreement with the workplace practices measured. Workforce training (r = 0.586), quality management (r = 0.542), and continuous improvement (r = 0.514) were each positively associated with the reported Production Performance Score (p < .001). The regression model was significant, F = 102.091, p < .001, with R² = 0.657. Workforce training showed the largest standardized coefficient (β = 0.457). The findings suggest that manufacturing organisations should strengthen employee development, quality discipline, and systematic improvement activities while interpreting the results with attention to measurement limitations in the source study.

KEYWORDS

workforce training quality management practices continuous improvement production performance manufacturing industry employee productivity operational efficiency SPSS

Cite This Article

Mohammed Zayan Raji, Narh Justice Tetteh Kwesi, Rafiatu Mustapha, Habibu Ibrahim, Adjepong Edmund Kofi, Samuel Twum, Francis Agyapong, Dr. Atul Sharma, "Impact of Workforce Training and Quality Management Practices on Production Performance," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 8, pp. 1-8, Aug 2026. https://doi.org/10.55041/IJSREM66797

Full Article/Conclusion

This study examined workforce training, quality management practices, and continuous improvement initiatives in relation to production performance using questionnaire responses from 164 manufacturing-related respondents. The descriptive findings showed moderate, near-neutral assessments of the three practice areas. However, each predictor was positively and significantly associated with the reported Production Performance Score, and the combined regression model explained a substantial proportion of its reported variance within the sample. Workforce Training showed the largest standardized regression coefficient, followed by Continuous Improvement and Quality Management. The findings support the practical importance of employee capability, disciplined quality systems, and improvement-oriented work practices in manufacturing. They also reinforce the broader research view that technology and production systems depend on organisational capabilities and human participation for effective implementation. Because the study used convenience sampling and the source measurement contains issues requiring verification, the results should be interpreted cautiously. Even so, the study provides a useful basis for manufacturing organisations to consider training, quality discipline, and continuous improvement as connected components of production performance rather than isolated management practices.

References

·        Abbas, J. (2020). Impact of total quality management on corporate sustainability through the mediating effect of knowledge management. Journal of Cleaner Production, 244, 118806. https://doi.org/10.1016/j.jclepro.2019.118806 ·        Adel, A. (2022). Future of industry 5.0 in society: Human-centric solutions, challenges and prospective research areas. Journal of Cloud Computing, 11, Article 40. https://doi.org/10.1186/s13677-022-00314-5 ·        Bag, S., Gupta, S., Kumar, A., & Sivarajah, U. (2021). Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities. Technological Forecasting and Social Change, 163, 120420. https://doi.org/10.1016/j.techfore.2020.120420 ·        Bai, C., Dallasega, P., Orzes, G., & Sarkis, J. (2020). Industry 4.0 technologies assessment: A sustainability perspective. International Journal of Production Economics, 229, 107776. https://doi.org/10.1016/j.ijpe.2020.107776 ·        Culot, G., Orzes, G., Sartor, M., & Nassimbeni, G. (2020). Behind the definition of Industry 4.0: Analysis and open questions. International Journal of Production Economics, 226, 107617. https://doi.org/10.1016/j.ijpe.2020.107617 ·        Ghobakhloo, M. (2020). Industry 4.0, digitization, and opportunities for sustainability. Journal of Cleaner Production, 252, 119869. https://doi.org/10.1016/j.jclepro.2019.119869 ·        Javaid, M., Haleem, A., Singh, R. P., & Suman, R. (2021). Significance of Quality 4.0 towards comprehensive enhancement in manufacturing sector. Sensors International, 2, 100109. https://doi.org/10.1016/j.sintl.2021.100109 ·        Kamble, S. S., Gunasekaran, A., & Dhone, N. C. (2020). Industry 4.0 and lean manufacturing practices for sustainable organisational performance in Indian manufacturing companies. International Journal of Production Research, 58(5), 1319–1337. https://doi.org/10.1080/00207543.2019.1630772

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Publication Date

8/17/2026

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