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

Vundla, S 2012, Statistical models and techniques applied to the International Manufacturing Strategy Survey (IMSS) database , PhD thesis, University of Salford.

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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 the fourth round of the IMSS (2005/06) database, which was the latest available release at the time when the main report was compiled. The data set contained in that release was the one analysed throughout this thesis. The research had two broad aims: (a) To contribute towards management insight, by uncovering those factors that affect business performance, as evidenced from the IMSS data set. The IMSS data set is an important source of information about manufacturing companies. (b) To provide a detailed discussion of statistical models which can be used to analyse ordinal 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 this can create a useful body of knowledge for similar studies, based on this data set or other similar data sets. The statistical models which were examined include latent variable models (latent class analysis and latent trait models), ordinal logistic regression, multiple linear regression and structural equation modelling. Thus, for example, with regards to the latent variable models, the latent trait and latent class analysis models were fitted to the IMSS database in an attempt to establish whether the latent variable is better modelled as a continuous or discrete variable. It was concluded that the latent trait model provides a marginally better fit to the data compared to the latent class analysis model, which suggests that the latent variable(s) is better modelled as a continuous variable. A further aim of the research work was to contribute to the existing literature on manufacturing strategy. Through examining and linking operations strategy, such as manufacturing and competitive strategies, to business performance, the research has uncovered a better understanding and insight into the various relationships. It has thus contributed towards managerial knowledge in this domain. A primary intention was to demonstrate that to achieve and maintain core competencies, and also as a pre-requisite to being able to formulate viable long-term strategies, managers should better understand the links 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 highly significant to business performance indicators compared to the competitive strategy variables. The fact that competitive strategy variables have a less dominant influence on business performance could be due to the fact that the manufacturing firms who responded to the survey are driven by market conditions and customer needs. The results imply that companies are using competitive strategies to compete against their rivals, while their performances relative to the past are more affected by market conditions. Furthermore, two main explanatory variables have been identified as consistently significant across all the performance measures, and these are 'market dynamics' and 'product design and quality'. These results affirm the importance of quality (as represented by product design and quality) among manufacturing firms, and the importance of responding (by firms) to the dynamics of their environment. The 'market dynamics' in which a firm operates have an important 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 specific implications". Therefore, the main contribution of the research is testing and explaining the relationships among manufacturing strategy, competitive strategy, market characteristics and business performance. Since the thesis is based on the analysis of a large database, we argue that the results from this research provide a basis for further studies in the area and note that these results are easily generalisable to other similar studies. However, owing to the fact that the questionnaires which were used to conduct the surveys differed from one collection phase to another, this study is a cross-sectional rather than a longitudinal one. Because some of the relationships investigated were concerned with strategies for improving performance the cross-sectional approach rules out the possibility of unearthing actual improvements in respondents' performance over time. Such issues are thus limitations of the research. Finally, we note that studying both market characteristics and competitive strategies and their relative impact on overall business performance is a new feature of this research and this adds to the literature on the use and analysis of the IMSS data. Relationship studies based on this data set have, in the past, tended to concentrate on the impact on manufacturing performance only.

Item Type: Thesis (PhD)
Contributors: Dangerfield, B (Supervisor) and Wang, W (Supervisor)
Schools: Schools > Salford Business School
Depositing User: Institutional Repository
Date Deposited: 12 Aug 2021 14:56
Last Modified: 27 Aug 2021 21:57

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