Statistical models and techniques applied to the International Manufacturing Strategy Survey (IMSS) database

The research explores statistical models and techniques which 'have been or might be used'to investigate relationships within the international manufacturing strategy survey (IMSS)database and other similar databases. The sample data for the research was taken from thefourth round of the IMSS (2005/06) database, which was the latest available release at thetime when the main report was compiled. The data set contained in that release was the oneanalysed throughout this thesis.The research had two broad aims:(a) To contribute towards management insight, by uncovering those factors that affectbusiness performance, as evidenced from the IMSS data set. The IMSS data set isan important source of information about manufacturing companies.(b) To provide a detailed discussion of statistical models which can be used to analyseordinal data, and employ data reduction techniques to generate generic measures.The models are investigated and tested on the IMSS data set. It is hoped that thiscan create a useful body of knowledge for similar studies, based on this data set orother similar data sets.The statistical models which were examined include latent variable models (latent classanalysis and latent trait models), ordinal logistic regression, multiple linear regression andstructural equation modelling. Thus, for example, with regards to the latent variablemodels, the latent trait and latent class analysis models were fitted to the IMSS database inan attempt to establish whether the latent variable is better modelled as a continuous ordiscrete variable. It was concluded that the latent trait model provides a marginally better fitto the data compared to the latent class analysis model, which suggests that the latentvariable(s) is better modelled as a continuous variable.A further aim of the research work was to contribute to the existing literature onmanufacturing strategy. Through examining and linking operations strategy, such as manufacturing and competitive strategies, to business performance, the research hasuncovered a better understanding and insight into the various relationships. It has thuscontributed towards managerial knowledge in this domain. A primary intention was todemonstrate that to achieve and maintain core competencies, and also as a pre-requisite tobeing able to formulate viable long-term strategies, managers should better understand thelinks between market characteristics, competitive strategies, manufacturing strategies,manufacturing performance and business performance.The results of the data analysis suggest that more market characteristics variables are highlysignificant to business performance indicators compared to the competitive strategyvariables. The fact that competitive strategy variables have a less dominant influence onbusiness performance could be due to the fact that the manufacturing firms who respondedto the survey are driven by market conditions and customer needs. The results imply thatcompanies are using competitive strategies to compete against their rivals, while theirperformances relative to the past are more affected by market conditions. Furthermore, twomain explanatory variables have been identified as consistently significant across all theperformance measures, and these are 'market dynamics' and 'product design and quality'.These results affirm the importance of quality (as represented by product design andquality) among manufacturing firms, and the importance of responding (by firms) to thedynamics of their environment. The 'market dynamics' in which a firm operates have animportant role to play on performance attainment and even survival of a business.This thesis could be regarded as "offering rich insight and the drawing of specificimplications". Therefore, the main contribution of the research is testing and explaining therelationships among manufacturing strategy, competitive strategy, market characteristicsand business performance. Since the thesis is based on the analysis of a large database, weargue that the results from this research provide a basis for further studies in the area andnote that these results are easily generalisable to other similar studies.However, owing to the fact that the questionnaires which were used to conduct the surveysdiffered from one collection phase to another, this study is a cross-sectional rather than alongitudinal one. Because some of the relationships investigated were concerned with strategies for improving performance the cross-sectional approach rules out the possibilityof unearthing actual improvements in respondents' performance over time. Such issues arethus limitations of the research.Finally, we note that studying both market characteristics and competitive strategies andtheir relative impact on overall business performance is a new feature of this research andthis adds to the literature on the use and analysis of the IMSS data. Relationship studiesbased on this data set have, in the past, tended to concentrate on the impact onmanufacturing performance only.

Level dc:type.qualificationlevel

Doctoral (Level 8)

Year dc:date.issued

2012

Author dc:creator

• Vundla, S

Language dc:language

en

Identifier

oai:salford-repository.worktribe.com:1337529

OAI identifier oai:identifier

oai:salford-repository.worktribe.com:1337529