Measuring Leanness and Agility Status of Iranian Food Industries Supply Chains Using Data Envelopment Analysis

  • Pouyeh Rezazadeh
Part of the Communications in Computer and Information Science book series (CCIS, volume 245)


This research proposes a methodology to measure the overall leanness and agility of supply chains considering the most appropriate index of supply chains in food industry. Output and input of proposed model base in Data Envelopment analysis are identified from literature review and the level of them from a survey questionnaire accrued. Using the Data Envelopment Analysis technique, the leanness and agility measures delivers a self-contained, unit-invariant score of the whole supply chain system to support decision making on continuous improvement. And firms could adopt either a lean or an agile strategy or both, depending on the environment. This article provides a DEA method to measure two supply chain strategies and benchmarks their indexes to co-align competitive strategies with the environment to improve performance. This approach has been applied in case of some Iranian food industry supply chains to prove the applicability of the method.


Data Envelopment Analysis Lean Supply Chains Agile Supply Chains Iranian Food Industries 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Turner, K.: Modelling complexity in the automotive industry supply chain. Journal of Manufacturing Technology Management 16(4), 447–458 (2005)CrossRefGoogle Scholar
  2. 2.
    Agarwal, A., Shankar, R., Tiwari, M.K.: Modelling the metrics of lean, agile and leagile supply chain: an ANP-based approach. European Journal of Operational Research 173, 221–225 (2006)MathSciNetCrossRefMATHGoogle Scholar
  3. 3.
    Banker, R.D., Charnes, A., Cooper, W.W.: Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science 30(9), 1078–1092 (1984)CrossRefMATHGoogle Scholar
  4. 4.
    Baramichai, M., Zimmers Jr., E.W., Marangos, C.A.: Agile supply chain transformation matrix:an integrated tool for creating an agile enterprise. Supply Chain Management: An International Journal 12(5), 334–348 (2007)CrossRefGoogle Scholar
  5. 5.
    Bruce, M., Daly, L., Towers, M.: Lean or agile. A solution for supply chain management in the textiles and clothing industry. International Journal of Operations and Production Management 24(2), 151–170 (2004)CrossRefGoogle Scholar
  6. 6.
    Burgess, T., Hwarng, B., Shaw, N., De Mattos, C.: Enhancing value stream agility: the UK speciality chemical industry. European Management Journal 20(2), 199–212 (2002)CrossRefGoogle Scholar
  7. 7.
    Chen, C.-M.: Evaluation and Design of Supply-Chain Operations using DEA, PhD Thesis, Erasmus Research Institute of Management – ERIM Rotterdam School of Management (RSM), Erasmus School of Economics (ESE) (June 2009), Print: Haveka
  8. 8.
    Christopher, M.: The agile supply chain. Industrial Marketing Management 29, 37–44 (2000)CrossRefGoogle Scholar
  9. 9.
    Christopher, M., Peck, H., Towill, D.R.: A taxonomy for selecting global supply chain strategies. International Journal of Logistics Management 17(2), 277–287 (2006)CrossRefGoogle Scholar
  10. 10.
    Cox, A., Chicksand, D.: The limits of lean management thinking: multipleretailers and food and farming supply chains. European Management Journal 23(6), 648–662 (2005)CrossRefGoogle Scholar
  11. 11.
    de Treville, S., Shapiro, D., Hameri, A.-P.: From supply chain to demand chain: the role of lead time reduction in improving demand chain performance. Journal of Operations Management 21, 613–627 (2003)CrossRefGoogle Scholar
  12. 12.
    Eyong Michael, E.: Creating A Competitive Supply Chain: Evaluating The Impact Of Lean & Agile Supply Chain, School Of Innovation. Design & Product Development (Idt) Se – 721 23, Västerås/Eskilstuna, Sweden (2010)Google Scholar
  13. 13.
    Behrouzi, F., Wong, K.Y.: Lean performance evaluation of manufacturing systems: A dynamic and innovative approach. Procedia Computer Science 3, 388–395 (2011)CrossRefGoogle Scholar
  14. 14.
    Gil, N., Tommelein, I.D., Stout, A., Garrett, T.: Embodying product and process flexibility to cope with challenging project deliveries. Journal of Construction Engineering and Management 131(4), 439–448 (2005)CrossRefGoogle Scholar
  15. 15.
    Goldsby, T.J., Griffis, S.E., Roath, A.S.: Modelling lean, agile, and leagile supply chain strategies. Journal of Business Logistics 27(1), 57–79 (2006)CrossRefGoogle Scholar
  16. 16.
    Gunasekaran, A., Ngai, E.W.T.: Information systems in supply chain integration and management. European Journal of Operational Research 159, 269–295 (2004)MathSciNetCrossRefMATHGoogle Scholar
  17. 17.
    Khalili-Damghani, K., Taghavifard, M., Olfat, L., Feizi, K.: A hybrid approach based on fuzzy DEA and simulation to measure the effciency of agility in supply chain. International Journal of Management Science and Engineering Management 6(3), 163–172 (2011) ISSN 1750-9653Google Scholar
  18. 18.
    Krishnamurthy, R., Yauch, C.A.: Leagile manufacturing: a proposed corporate infrastructure. International Journal of Operations and Production Management 27(6), 588–604 (2007)CrossRefGoogle Scholar
  19. 19.
    Li, G., Lin, Y., Wang, S., Yan, H.: Enhancing agility by timely sharing of supply information. Supply Chain Management: An International Journal 11(5), 425–435 (2006)CrossRefGoogle Scholar
  20. 20.
    Mohammed, I.R., Shankar, R., Banwet, D.K.: Creating flex-lean-agile value chain by outsourcing, An ISM-based interventional roadmap. Business Process Management Journal 14(3), 338–389 (2008)CrossRefGoogle Scholar
  21. 21.
    Mason-Jones, R., Naylor, J.B., Towill, D.R.: Lean, agile or leagile? Matching your supply chain to the market place. International Journal of Production Research 38(17), 4061–4070 (2000)CrossRefGoogle Scholar
  22. 22.
    Mason-Jones, R., Towill, D.R.: Total cycle time compression and the agile supply chain. International Journal of Production Economics 62(1), 61–73 (1999)CrossRefGoogle Scholar
  23. 23.
    Narasimhan, R., Swink, M., Kim, S.W.: Disentangling leanness and agility: an empirical investigation. Journal of Operations Management 24, 440–457 (2006)CrossRefGoogle Scholar
  24. 24.
    Naylor, J.B., Naim, M.M., Berry, D.: Leagility: Integrating the lean and agile manufacturing paradigms in the total supply chain. International Journal of Production Economics 62, 107–118 (1999); formerly (1997) OccasionalPaper#47Google Scholar
  25. 25.
    Papadopoulou, T.C., Ozbayrak, M.: Leanness: experiences from the journey to date. Journal of Manufacturing Technology Management 16(7), 784–807 (2005)CrossRefGoogle Scholar
  26. 26.
    Pettersen, J.: Defining lean production: some conceptual and practical issues. TQM Journal 21(2), 127–142 (2009)CrossRefGoogle Scholar
  27. 27.
    Power, D.J., Sohal, A.S., Rahman, S.U.: Critical success factors in agile supply chain management: an empirical study. International Journal of Physical Distribution & Logistics Management 31(4), 247–265 (2001)CrossRefGoogle Scholar
  28. 28.
    Prince, J., Kay, J.M.: Combining lean and agile characteristics: creation of virtual groups by enhanced production flow analysis. International Journal of Production Economics 85, 305–318 (2003)CrossRefGoogle Scholar
  29. 29.
    Rickards, R.: Setting benchmarks and evaluating balanced scorecards with data envelopment analysis. Benchmarking: An International Journal 10(3), 226–245 (2003)CrossRefGoogle Scholar
  30. 30.
    Sanchez, L.M., Nagi, R.: A review of agile manufacturing systems. International Journal of Production Research 39(16), 3561–3600 (2001)CrossRefMATHGoogle Scholar
  31. 31.
    Seydel, J.: Data envelopment analysis for decision support. Industrial Management & Data Systems 106(1), 81–95 (2006)CrossRefGoogle Scholar
  32. 32.
    Shah, R., Ward, P.T.: Defining and developing measures of lean production. Journal of Operations Management 25, 785–805 (2007)CrossRefGoogle Scholar
  33. 33.
    Shaw, N.E., Burgess, T.F., de Mattos, C., Stecy: Supply chain agility: the influence of industry culture on asset capabilities within capital intensive industries. International Journal of Production Research 43(15), 3497–3516 (2005)CrossRefGoogle Scholar
  34. 34.
    Sherman, H.D., Ladino, G.: Managing bank productivity using data envelopment analysis (DEA). Interfaces 25(2), 60–73 (1995)CrossRefGoogle Scholar
  35. 35.
    Slack, N.: The flexibility of manufacturing systems. International Journal of Operations & Production Management 7(4), 35–45 (1987)CrossRefGoogle Scholar
  36. 36.
    Swafford, P.M., Ghosh, S., Murthy, N.N.: A framework for assessing value chain agility. International Journal of Operations and Production Management 26(2), 118–140 (2006)CrossRefGoogle Scholar
  37. 37.
    van der Vaart, T., van Donk, D.P.: Buyer focus: evaluation of a new conceptfor supply chain integration. International Journal of Production Economics 92, 21–30 (2004)CrossRefGoogle Scholar
  38. 38.
    van der Vorst, J.G.A.J., van Dijk, S.J., Beulens, A.J.M.: Supply chain design in the food industry. International Journal of Logistics Management 12(2), 73–85 (2001)CrossRefGoogle Scholar
  39. 39.
    van Hoek, R.I., Harrison, A., Christopher, M.: Measuring agile capabilities in the supply chain. International Journal of Operations and Production Management 21(1/2), 126–147 (2001)CrossRefGoogle Scholar
  40. 40.
    Wan, H.-D., Frank Chen, F.: A leanness measure of manufacturing systems for quantifying impacts of lean initiatives. International Journal of Production Research 46(23), 6567–6584 (2008), doi:10.1080/00207540802230058Google Scholar
  41. 41.
    Yang, B., Burns, N.: Implications of postponement for the supply chain. International Journal of Production Research 41(9), 2075–2090 (2003)CrossRefGoogle Scholar
  42. 42.
    Yang, B., Burns, N.D., Backhouse, C.J.: Postponement:are view and an integrated framework. International Journal of Operations and Production Management 24(5), 468–487 (2004)CrossRefGoogle Scholar
  43. 43.
    Zhu, J.: Multi-factor performance measure model with an application to Fortune 500 companies. European Journal of Operational Research 123(1), 105–124 (2000)CrossRefMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Pouyeh Rezazadeh
    • 1
  1. 1.Department of Industrial and System EngineeringSouth Tehran Branch, Islamic Azad UniversityTehranIran

Personalised recommendations