A Model of Supply Chain Agility for Auto Part Manufacturer Companies by Using Interpretive – Structural Modeling Approach

Authors
yaqub ramazani
Gholamreza Esmailian
10.52547/jde.1.4.95
Abstract
Todays, organizations are faced with very high competition and uncertain environment and also intensify with innovations in technology and the changing needs of customers. Although the importance and urgency of supply chain agility, according to needs of acting quickly, respond to customers, increasing market changes and consumer needs and ... in many industries, both in scientific and empirical perspective, is clear, but automotive parts manufacturer companies paid little attention to these issues and agility in their supply chain. Clearly, being agile supply chain, flexible and responsive in automotive parts manufacturer companies, would be solved an important part of the problems that threats companies. The main issue of this study is that, how automotive parts manufacturer companies can agility in their supply chain. The main objective of this study is to provide a model for agile supply chain in auto part manufacturer companies.

Methodology: This study is descriptive-analytic and can be identified as developmental –functional on considering its aims. After surveying previous research literature and using experts’ opinions, we investigated final agile criteria and indicators of supply chain and then we used interpretive- structural modeling approach to determine the relation among criteria and indicators providing a model of supply chain agility in auto part manufacturer companies.

Findings: By reviewing the literature and using Delphi Technique, we identified 6 criteria (Competency, Celerity, Flexibility, Accountability, Market and Information Technology) and also Twenty two sub criteria for supply chain’s agility in auto part companies. Then the results were analyzed through interpretive-structural approach and relation of criteria and sub criteria and their results were achieved. These relations showed that Competency and Information Technology in criteria and Trust in Relationship and Quality in indicators are the basis of agility to achieve market in criteria and Customer Satisfaction in cub criteria. This research helps supply chain managers to have strategic planning to enhance agility in supply chain and find effective sub criteria and criteria to invest on.
Keywords
Agile supply chain
Delphi approach
Descriptive structural modeling
auto parts
Adeleye, E.O., Yusuf, Y.Y., (2006), Towards agile manufacturing: Models of competition and performance outcomes. International journal systems and management. 1(1), pp: 93-110.
Agarwal A., Shankar R., Tiwari M.K.; (2007), Modeling agility of supply chain; industrial marketing management, Vol.36, pp: 443-445.
Agarwal A., Shankar R., Tiwari M.K.; (2006), Modeling the metrics of lean, agile and leagile supply chain: An ANP- based approach, European journal of operation research, pp: 211-225.
Alvandi, M. Fazli, S. Memarzade, M. (2011). E-Supplier selection using Delphi, fuzzy AHP and SIR. European journal of scientific research. 66(4). pp: 481-509.102.
Baker P.; (2008), The design and operation of distribution centres within agile supply chain, international journal of production economics, Vol.111, pp: 27-41.
Carlson J., Yao A.,(2008)- Simulating an agile, synchronized manufacturing system-Int. J. Production Economics 112. pp: 714–722.
chee Yew Wong., Jan Stentoft Arlbjorn., Hans-Henrik Hvolby and John Johansen., (2006). Assessing responsiveness of a volatile and seasonal supply chain: A case study. International Journal of Operations & Production Management, vol. 104, issue 2, pp: 709-721.
Christopher, M. (2005). Logistics and Supply Chain Management. London: Prentice Hall, pp: 130-137.
Gunasekaran A., Lai K.H., Cheng T.C.; (2008), Responsive supply chain; Acompetitive strategy in a networked economy; omega 36, pp: 549-564.
Gunasekaran A., Patel C., Tirtiroglu E.; (2001), performance measure and metrics in a supply chain environment. International journal of operations & production management, Vol.21, No.1/2, pp: 71 – 87.
Gunasekaran, A., Patel, C., & McGaughey, R. (2004). A framework for supply chain performance measurement. International Journal of Production Economics, 87, pp: 333-347.
Jharkharia, S., Shankar R., (2005), IT enablement of supply chains: understanding the barriers, journal of information management, 18(1), pp: 11-27. 613
Lin CT., Chiu H., Tseng Y.H., (2006); “Agility Evaluation Using Fuzzy Logic”, International Journal of Production Economics, 101, pp: 353-368.
Radfar R.t Pilevari N., Aflaki S.; (2011), A model for evaluating and comparing the agility of supply chain case study: iran telecommunication company and iraancell company, American journal of scientific research, ISSN 1450- 223X Issue 33, pp:127-135.
Ramesh, g: Devadasan, S (2007). Literature Review on the agile manufacturing criteria, Journal of manufacturing technology management, vol.18, No. 2, pp: 182-201.
Swafford P. M., Ghosh S., (2006), Murthy M.; the antecedents of supply chain agility of a firm: scale development and model testing; Journal of operation management, Vol.24, pp: 170-188.
Swafford P. M., Ghosh S., Murthy nagesh.; (2008), Achieving supply chain agility through IT integration and flexibility; International journal of production economics, Vol.116, pp: 346-5137.
Swafford P. M., Soumen G.; (2005), The antecedents of supply chain agility of a firm: scale development and model testing; Journal of operation management, Vol.24, pp: 1-23.