Complementarities in the Implementation of Advanced Manufacturing Technologies

• Main Author: Percival, Jennifer
• Format: Others
• Language: en
• Published: University of Waterloo 2006
• Subjects: Management; Complementarity; Advanced Manufacturing Technologies; Lattice; Substitutes
• Online Access: http://hdl.handle.net/10012/843

Within the last decade, the importance of flexibility and efficiency has increased in the manufacturing sector. The rising level of uncertainty in consumer preferences has caused many organizations to aggressively search for cost reductions and other sources of competitive advantage. This fact has resulted in an increased implementation of advanced manufacturing technologies (AMT). A number of studies propose that the implementation of AMT must be accompanied by a shift in supporting organizational practices to realize the greatest performance enhancement. As yet, the complementarities between organizational policies and AMT have not been determined. Using assumptions about complementarities in manufacturing made by Milgrom and Roberts (1995) in conjunction with a comprehensive AMT survey (Survey of Advanced Technology in Canadian Manufacturing-1998) a model of manufacturing plant productivity was developed. Constrained regression analysis reveals that the use of AMT, as well as various organizational policies, depends both on the size of the plant as well as the industry in which it operates. Factor analysis of the over 70 variables found that regardless of the nature of the variable (business strategy, source of implementation support, AMT, etc. ), all design elements factored together. The factor analysis also shows that large firms who use AMT also have many design technologies. This result differs for smaller firms where the use of AMT is highly correlated with perceived benefits of the technology and a large number of sources of implementation support. The analysis also supports the distinction of high technology (highly innovative) industries and low technology (low levels of innovation) industries since electronics, chemicals and automotive have a large percentage of plants with all of the model factors whereas the textile, non-metal and lumber industries have very few plants with all of the model factors. The results show that there are important differences that should be considered when creating policies to encourage innovation and the use of AMT for the various manufacturing industries and plant sizes.