Analysis of the agility of the automotive industry supply chain in times of COVID-19: a case study

Keywords: Agility, assessment, attributes, enablers, competitive, fuzzy, automotive, corona, supply, chain

Abstract

In the early stages of the corona virus pandemic, business environment was changing rapidly. The Moroccan automotive industry was one of the export sectors most affected negatively by the corona crisis; it collapsed during the three months of confinement and the pandemic has created immense uncertainties in demand and disrupted global supply chains. Indeed, to save the automotive industry, Morocco relies on its competitiveness and challenges current supply models for supply chain agility in order to better prepare for future disruptions. Achieving a competitive edge requires aligning company with suppliers and customers as well as working together to achieve agility, organizationally, strategically and individually. However, agile supply chains are the most powerful competitive vehicles of the manufacturing companies. To help automakers deal with the many challenges associated with the pandemic, let’s present this research on the key enablers that will need to be monitored as the situation evolves. Thus, our article presents an original approach which, by linking the competitive priorities, agile supply chain attributes and enablers, aims at evaluates and enhances supply chain agility of a Moroccan automotive factory. Let’s adopt fuzzy quality function deployment (FQFD) approach and, in particular, the two houses of quality (HOQ) with a fuzzy scale in order to identify the most appropriate enablers to be implemented by the factory. This evaluation demonstrates that there are three enablers needing maximum attention: process compliance, logistics and distribution capabilities and supportive information technology. Then, the supply chain agility improvement should be based on these enablers

Downloads

Download data is not yet available.

Author Biographies

Fadoua Tamtam, Ibn Zohr University

Systems Engineering Laboratory and Decision Support

National School of Applied Sciences

Amina Tourabi, Ibn Zohr University

Systems Engineering Laboratory and Decision Support

National School of Applied Sciences

References

Haq, A. N., Boddu, V. (2014). Analysis of enablers for the implementation of leagile supply chain management using an integrated fuzzy QFD approach. Journal of Intelligent Manufacturing, 28 (1), 1–12. doi: https://doi.org/10.1007/s10845-014-0957-9

Lin, C.-T., Chiu, H., Chu, P.-Y. (2006). Agility index in the supply chain. International Journal of Production Economics, 100 (2), 285–299. doi: https://doi.org/10.1016/j.ijpe.2004.11.013

Al-Shboul, M. A. (2017). Infrastructure framework and manufacturing supply chain agility: the role of delivery dependability and time to market. Supply Chain Management: An International Journal, 22 (2), 172–185. doi: https://doi.org/10.1108/scm-09-2016-0335

Singh Patel, B., Samuel, C., Sharma, S. K. (2017). Evaluation of agility in supply chains: a case study of an Indian manufacturing organization. Journal of Manufacturing Technology Management, 28 (2), 212–231. doi: https://doi.org/10.1108/jmtm-09-2016-0125

Mehralian, G., Zarenezhad, F., Rajabzadeh Ghatari, A. (2015). Developing a model for an agile supply chain in pharmaceutical industry. International Journal of Pharmaceutical and Healthcare Marketing, 9 (1), 74–91. doi: https://doi.org/10.1108/ijphm-09-2013-0050

Abdoli Bidhandi, R., Valmohammadi, C. (2017). Effects of supply chain agility on profitability. Business Process Management Journal, 23 (5), 1064–1082. doi: https://doi.org/10.1108/bpmj-05-2016-0089

Gligor, D. M., Holcomb, M. C. (2012). Understanding the role of logistics capabilities in achieving supply chain agility: a systematic literature review. Supply Chain Management: An International Journal, 17 (4), 438–453. doi: https://doi.org/10.1108/13598541211246594

Bottani, E. (2009). A fuzzy QFD approach to achieve agility. International Journal of Production Economics, 119 (2), 380–391. doi: https://doi.org/10.1016/j.ijpe.2009.02.013

Aslam, H., Blome, C., Roscoe, S., Azhar, T. M. (2018). Dynamic supply chain capabilities: How market sensing, supply chain agility and adaptability affect supply chain ambidexterity. International Journal of Operations & Production Management, 38 (12), 2266–2285. doi: https://doi.org/10.1108/ijopm-09-2017-0555

I. van Hoek, R., Harrison, A., Christopher, M. (2001). Measuring agile capabilities in the supply chain. International Journal of Operations & Production Management, 21 (1/2), 126–148. doi: https://doi.org/10.1108/01443570110358495

Vinodh, S., Chintha, S. K. (2011). Application of fuzzy QFD for enabling agility in a manufacturing organization: A case study. The TQM Journal, 23 (3), 343–357. doi: https://doi.org/10.1108/17542731111124389

Shashi, Centobelli, P., Cerchione, R., Ertz, M. (2020). Agile supply chain management: where did it come from and where will it go in the era of digital transformation? Industrial Marketing Management, 90, 324–345. doi: https://doi.org/10.1016/j.indmarman.2020.07.011

Li, X., Goldsby, T. J., Holsapple, C. W. (2009). Supply chain agility: scale development. The International Journal of Logistics Management, 20 (3), 408–424. doi: https://doi.org/10.1108/09574090911002841

Irfan, M., Wang, M., Akhtar, N. (2019). Enabling supply chain agility through process integration and supply flexibility: Evidence from the fashion industry. Asia Pacific Journal of Marketing and Logistics, 32 (2), 519–547. doi: https://doi.org/10.1108/apjml-03-2019-0122

Jindal, A., Sharma, S. K., Sangwan, K. S., Gupta, G. (2021). Modelling Supply Chain Agility Antecedents Using Fuzzy DEMATEL. Procedia CIRP, 98, 436–441. doi: https://doi.org/10.1016/j.procir.2021.01.130

Qrunfleh, S., Tarafdar, M. (2013). Lean and agile supply chain strategies and supply chain responsiveness: the role of strategic supplier partnership and postponement. Supply Chain Management: An International Journal, 18 (6), 571–582. doi: https://doi.org/10.1108/scm-01-2013-0015

Prater, E., Biehl, M., Smith, M. A. (2001). International supply chain agility ‐ Tradeoffs between flexibility and uncertainty. International Journal of Operations & Production Management, 21 (5/6), 823–839. doi: https://doi.org/10.1108/01443570110390507

Yusuf, Y. Y., Sarhadi, M., Gunasekaran, A. (1999). Agile manufacturing: The drivers, concepts and attributes. International Journal of Production Economics, 62 (1-2), 33–43. doi: https://doi.org/10.1016/s0925-5273(98)00219-9

Dove, R. (1999). Knowledge management, response ability, and the agile enterprise. Journal of Knowledge Management, 3 (1), 18–35. doi: https://doi.org/10.1108/13673279910259367

Charles, A., Lauras, M., Van Wassenhove, L. (2010). A model to define and assess the agility of supply chains: building on humanitarian experience. International Journal of Physical Distribution & Logistics Management, 40 (8/9), 722–741. doi: https://doi.org/10.1108/09600031011079355

Kumar Sharma, S., Bhat, A. (2014). Modelling supply chain agility enablers using ISM. Journal of Modelling in Management, 9 (2), 200–214. doi: https://doi.org/10.1108/jm2-07-2012-0022

Pilevari, N., SeyedHosseini, S. M., Jassbi, J. (2008). Fuzzy logic Supply Chain Agility Assessment methodology. 2008 IEEE International Conference on Industrial Engineering and Engineering Management. doi: https://doi.org/10.1109/ieem.2008.4738043

Lin, C.-T., Chiu, H., Tseng, Y.-H. (2006). Agility evaluation using fuzzy logic. International Journal of Production Economics, 101 (2), 353–368. doi: https://doi.org/10.1016/j.ijpe.2005.01.011

Christopher, M., Lowson, R., Peck, H. (2004). Creating agile supply chains in the fashion industry. International Journal of Retail & Distribution Management, 32 (8), 367–376. doi: https://doi.org/10.1108/09590550410546188

Faisal, M. N., Banwet, D. K., Shankar, R. (2007). An approach to measure supply chain agility. International Journal of Industrial and Systems Engineering, 2 (1), 79. doi: https://doi.org/10.1504/ijise.2007.011438

Yusuf, Y. Y., Gunasekaran, A., Adeleye, E. O., Sivayoganathan, K. (2004). Agile supply chain capabilities: Determinants of competitive objectives. European Journal of Operational Research, 159 (2), 379–392. doi: https://doi.org/10.1016/j.ejor.2003.08.022

Al Humdan, E., Shi, Y., Behnia, M. (2020). Supply chain agility: a systematic review of definitions, enablers and performance implications. International Journal of Physical Distribution & Logistics Management, 50 (2), 287–312. doi: https://doi.org/10.1108/ijpdlm-06-2019-0192

Blome, C., Schoenherr, T., Rexhausen, D. (2013). Antecedents and enablers of supply chain agility and its effect on performance: a dynamic capabilities perspective. International Journal of Production Research, 51 (4), 1295–1318. doi: https://doi.org/10.1080/00207543.2012.728011

Pandey, V. C., Garg, S. (2009). Analysis of interaction among the enablers of agility in supply chain. Journal of Advances in Management Research, 6 (1), 99–114. doi: https://doi.org/10.1108/09727980910972190

Faisal, M. N., Banwet, D. K., Shankar, R. (2007). Supply chain agility: analysing the enablers. International Journal of Agile Systems and Management, 2 (1), 76. doi: https://doi.org/10.1504/ijasm.2007.015682

Li, X., Chung, C., Goldsby, T. J., Holsapple, C. W. (2008). A unified model of supply chain agility: the work‐design perspective. The International Journal of Logistics Management, 19 (3), 408–435. doi: https://doi.org/10.1108/09574090810919224

Mohanraj, R., Sakthivel, M., Vinodh, S., Vimal, K. E. K. (2015). A framework for VSM integrated with Fuzzy QFD. The TQM Journal, 27 (5), 616–632. doi: https://doi.org/10.1108/tqm-11-2012-0088

Chen, L.-H., Ko, W.-C. (2010). Fuzzy linear programming models for NPD using a four-phase QFD activity process based on the means-end chain concept. European Journal of Operational Research, 201 (2), 619–632. doi: https://doi.org/10.1016/j.ejor.2009.03.010

Vinodh, S., Rathod, G., Devadasan, S. R. (2011). Application of QFD for supplier selection in an Indian electronics switches manufacturing organisation. International Journal of Indian Culture and Business Management, 4 (2), 181. doi: https://doi.org/10.1504/ijicbm.2011.038916


👁 52
⬇ 50
Published
2021-11-18
How to Cite
Tamtam, F., & Tourabi, A. (2021). Analysis of the agility of the automotive industry supply chain in times of COVID-19: a case study. EUREKA: Physics and Engineering, (6), 112-120. https://doi.org/10.21303/2461-4262.2021.001949
Section
Mathematics