Research on the Impact of Manufacturing Competence on Manufacturing Performance

Author(s):  
P. Li ◽  
J.x. Shi ◽  
Z.y. Qi ◽  
L. Zhang ◽  
Q. Jia
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alberto Bayo-Moriones ◽  
Alejandro Bello-Pindado

PurposeThe purpose of this paper is to analyse the impact on manufacturing performance of human resource management (HRM) practices across two job levels within manufacturing firms in Argentina and Uruguay: that of line managers and frontline workers. HRM practices are categorised into three bundles defined by the AMO theoretical framework: ability, motivation and opportunity.Design/methodology/approachThe article uses data from a survey to 301 manufacturing plants in Uruguay and Argentina. Given the characteristics of the dependent variable, linear regression models have been estimated in order to test the hypotheses.FindingsThe results show that the ability and opportunity bundles for line managers are positively associated with manufacturing performance. However, only the motivation bundle affects manufacturing performance for frontline workers.Research limitations/implicationsThe main limitations are the use of cross-sectional data, the focus on two specific countries and the analysis of two employee categories that are not completely homogenous. The paper extends the contingency perspective in HRM by examining the relevance of job level as a contingent factor in the HRM-performance relationship in the manufacturing industry.Practical implicationsThe results suggest that manufacturing companies should target HR investments more towards line managers than to frontline employees. More specifically, they should concentrate efforts on the ability and opportunity bundles.Originality/valueThe article contributes to the very limited empirical evidence on the impact of HRM differentiation on firm performance by analysing sub-dimensions in a context not previously analysed.


Author(s):  
Anna C. Thornton

Abstract Quality has been a rallying call in the design and manufacturing world for the last two decades. One way to improve quality is to reduce the impact of manufacturing variation. Variation risk mitigation is challenging especially when a product has multiple quality characteristics and complex production and assembly. It is common wisdom that companies should identify and mitigate the risk associated with variation throughout the design process. As yield problems are identified, they should be mitigated using the most cost effective approach. One approach to variation risk mitigation is variation reduction (VR). VR targets reduction of variation introduced by existing manufacturing processes using tools such as Design of Experiments (DOE) and robust design. Many companies have specialized groups that specialize in these methods. VR teams have the role of improving manufacturing performance; however, these teams are limited in their resources. In addition, no tools exist to quantitatively determine where a VR team’s efforts are most effectively deployed. This paper provides a mathematical and optimization model to best allocate VR resources in a complex product.


1997 ◽  
Vol 43 (9) ◽  
pp. 1246-1257 ◽  
Author(s):  
Sadao Sakakibara ◽  
Barbara B. Flynn ◽  
Roger G. Schroeder ◽  
William T. Morris

2016 ◽  
Author(s):  
Halim Mad Lazim ◽  
Che Azlan Taib ◽  
Hendrik Lamsali ◽  
Mohamed Najib Saleh ◽  
Chandrakantan Subramaniam

1990 ◽  
Vol 22 (1) ◽  
pp. 79-100 ◽  
Author(s):  
D L Rigby

In this paper the performance of the food and beverage industry in six regions of Canada between 1961 and 1984 is examined. The impact of spatial variations in commodity prices and techniques of production on the rate of profit are separated. Significant regional disparities in both production and market performance exist within the food sector and lend little support to the industry-mix thesis. Price variations are the principal cause of regional differences in manufacturing profitability. The rate of profit in the food industry declined in all regions, though at a slower rate than in manufacturing as a whole.


Significance While manufacturing is recovering after its sharp contraction during the first wave of shutdowns, the recovery is uneven by sector and region, reflecting the impact of COVID-19 on the structure of market demand, manufacturing capacity and global supply chains. Impacts The major industrial economies bar China have become more dependent on manufactured imports during 2020; this will ease gradually. Production is recovering but manufacturing employment is not, and this will continue; policies to support dislocated workers will be key. Geographic variations in the incidence of COVID-19 will accentuate the sectoral and regional differences in manufacturing performance.


Sign in / Sign up

Export Citation Format

Share Document