Mohammad Turki Abdul-Abbas
Business Administration Department, Faculty
of Administration and Economics, University of Kerbala, Iraq.
ORCID: https://orcid.org/0009-0009-9129-0472
Email: muhammed.t@uokerbala.edu.iq
Safaa Abid Ali Abdulameer
Business Administration Department, Faculty
of Administration and Economics, University of Kerbala, Iraq.
ORCID: https://orcid.org/0009-0005-1701-2248
Email: safaa.a@uokerbala.edu.iq
Yasir Mahmood Fahad
Business Administration Department, Faculty
of Administration and Economics, University of Kerbala, Iraq.
ORCID: https://orcid.org/0009-0006-6569-0200
Email: yaser.m@s.uokerbala.edu.iq
Ahmed Abdullah Amanah*
Business Administration Department, Faculty
of Administration and Economics, University of Kerbala, Iraq.
ORCID: https://orcid.org/0000-0001-5092-391X
Email: ahmed.a@uokerbala.edu.iq
Correspondence: Email:
ahmed.a@uokerbala.edu.iq
This study seeks to examine how context influences the relationship between the cumulative manufacturing capabilities model and sustainable high-performance work systems at Erbil Summits Company – Al-Noura Factory in Holy Kerbala, Iraq. The study developed a theoretical framework to address the lack of information in existing scholarly works. The model was tested on a sample of 205 workers and analysed using statistical software programs SPSS v.23 and AMOS. The results indicate that the capabilities model aligns with increased emotional commitment and managerial confidence, supporting the incremental manufacturing capabilities hypothesis. The factors significantly improved employee performance. The research provides clear evidence that the unique circumstances of a corporation within a country have a significant impact on the relationship between manufacturing capabilities and achieving exceptional results. The findings indicate that Erbil Qimam Company-Al-Noura Factory in Holy Kerbala should allocate substantial resources towards implementing cumulative manufacturing capabilities. This will help improve employee attitudes, leading to higher performance levels. The proposed model for different production systems has the potential to make a significant contribution to scholarly studies on operations management.
