Assessing Smartness of Automotive Industry: An Importance-Performance Analysis

Sahar Valipour Parkouhi (), Abdolhamid Safaei Ghadikolaei, Hamidreza Fallah Lajimi and Negin Salimi
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Sahar Valipour Parkouhi: University of Mazandaran
Abdolhamid Safaei Ghadikolaei: University of Mazandaran
Hamidreza Fallah Lajimi: University of Mazandaran
Negin Salimi: Wageningen University and Research

Chapter Chapter 8 in Advances in Best-Worst Method, 2023, pp 131-153 from Springer

Abstract: Abstract The automotive industry, like other industries, has been affected by the fourth industrial revolution. The intelligentization of manufacturing systems in the automotive industry is one of the achievements of this industrial revolution. Implementing a new manufacturing system requires continuous attention to the variables and conditions called Critical Success Factors (CSF). To successfully implement smart manufacturing, first, it is essential to assess the smartness level of an industry to have a better picture of that. To do this assessment, the importance of CSFs should be determined. Then the industry’s current performance should be evaluated based on CSFs. This assessment provides managers with a clear understanding of the condition of the industry, which can influence the effectiveness of their decisions. Therefore, this research aims to identify CSFs and evaluate the automotive industry’s performance. One approach to study this is using an importance-performance analysis (IPA). This approach is applied to the case of Iran’s two largest car manufacturers automotive industry. When studying importance, the Best-Worst Method is used. Due to incomplete information and uncertainty in the field of smart manufacturing, interval numbers have been used for more detailed analysis. Our results showed that although the two car manufacturers have performed relatively well in some factors, they have not performed well in important ones, such as customization and digitization of products and required technological infrastructure for using Industry 4.0. So, it seems these need to change the priority of these two care manufacturers’ attention to CSFs of smart manufacturing implementation. The results of this research can be suitable and useful for the managers of car manufacturers in Iran and other countries similar to Iran in terms of economic, political, and social conditions.

Keywords: Smart manufacturing; Critical success factors (CSFs); Interval importance-performance analysis (IIPA); Non-linear best-worst method; Interval analysis (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/978-3-031-40328-6_8

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