Analysis Of Interaction Fit Between Manufacturing Strategy And Technology Management And Its Impact On Performance

Purpose - Using the matching/difference perspective, the purpose of this paper is to examine the interaction fit between a set of managerial practices from manufacturing strategy (MS) and another set from technology management (TM) and the link of this fit to operational performance.Design/methodology/approach - The paper applies multiple statistical methods to a database of an international sample of plants in the auto supplier sector to explore (deviation score analysis/multiple linear regression) and confirm (correlation and variance subgroup analysis) whether a matching model presents organisational disequilibrium, where states of fit are related to effectively higher performance than states of misfit.Findings - Results from regression show that there were no states of misfit between the levels of both manufacturing practice sets/areas. This means that there are no significant differences in performance that may be tested for matching interaction. However, subgroup analysis provides greater detail on why there might not be any misfits (i.e. state of fit), by illustrating that when grouping by plant type (high/world class performer, HP, and standard performer, SP), the slight lack of significant difference in the correlation between MS and TM was in favour of HP. The implementation levels of MS-TM found were not significantly different, showing for HP slightly higher levels for both practices (+& +) than for SP, with slightly lower values in both cases (-&-). Therefore, it seems that both groups might perform equally well, due not to interaction but to the presence of a state of MS-TM fit alone. A state of fit such as this, known as selection or congruency, would be the reason for there being no significant matching interaction originally.Originality/value - Most of the interaction fit bibliography is from the accounting perspective. Therefore, the impact of the matching interaction fit between MS and TM (as well as its impact on performance) has not been well documented theoretically, and much less, empirically, in production and operations management.