ISSN 2736-1721
Global Journal of Business Management ISSN 6731-4538 Vol. 5 (4), pp. 001-011, April, 2011. © International Scholars Journals
Full Length Research Paper
Modeling and evaluating the strategic effects of improvement programs on the manufacturing performance using neural networks
Mehdi Hajirezaie1, Seyyed Mohammad Moattar Husseini1*, Ahmad Abdollahzadeh Barfourosh2 and Behrooz Karimi1
1Department of Industrial Engineering, Amirkabir University of Technology, 424 Hafez Ave., Tehran, Iran.
2IT and Computer Engineering Faculty, Amirkabir University of Technology, 424 Hafez Ave., Tehran, Iran.
Accepted 23 February, 2019
Abstract
Selecting the most effective improvement programs is the main challenge of business managers to achieve superior operational performances. This paper, in an effort to develop new insights into practice-performance relationships, investigates improvement programs, strategic priorities, environmental factors, manufacturing performance dimensions and their interactions via a data mining approach. The results of implementing improvement programs in 91 Iranian small and medium sized companies were gathered by means of a questionnaire-based survey and an artificial neural network was trained to model the relationships between input and output variables. Using a series of regression analysis on the same data shows that the proposed model outperforms all estimated regression models. Also, to understand and evaluate the strength of strategic effects on performance dimensions, a sensitivity analysis method was conducted on the trained model which indicates that implementing a program may be supportive of some performance dimensions and simultaneously incompatible with the others. The results are aimed at providing guidance for decision makers using the prediction power of the proposed model to estimate performance changes before investment in implementing programs.
Key words: Operations strategy, neural network modeling, strategic decision-making, practice-performance relationships.