International Journal of Fuzzy Systems

, Volume 18, Issue 3, pp 523–536 | Cite as

Critical Success Factors for the Iron and Steel Industry in Turkey: A Fuzzy DEMATEL Approach

  • Özgür KabakEmail author
  • Füsun Ülengin
  • Bora Çekyay
  • Şule Önsel
  • Özay Özaydın


The attempt to improve the efficiency and competitiveness of an industrial sector is aided by the determination of critical success factors (CSFs) which focus efforts in those areas that really affect the whole industry, thereby conserving limited resources. In this paper, a three-stage methodology is proposed to find CSFs for an industrial sector. The methodology specifies the interrelations between factors that shape the global competitiveness of a country as a whole and those that shape the competitiveness of the particular industry in question. It integrates a Web-based survey, a Delphi-type workshop, and a fuzzy decision making trial and evaluation laboratory model to highlight those CSFs upon which policymakers should especially concentrate in order to increase the competitiveness of a given industry. This methodology is then applied to a case study, identifying the CSFs of the iron and steel industry in Turkey. The results show that the burden of custom procedures, total tax rate, scope and impact of taxation, and solidity of banks are the CSFs for the competitiveness of the Turkish iron and steel industry.


Critical success factors Decision making trial and evaluation laboratory (DEMATEL) Fuzzy set theory Delphi method Iron and steel industry 



This research was supported by SEDEFED (Turkish Federation of Industrial Associations) and REF (TÜSİAD-Sabancı University Competitiveness Forum). The authors are also very grateful to all the experts who contributed to the surveys and to the anonymous referees for their invaluable suggestions.


  1. 1.
    World Economic Forum: The Global Competitiveness Report 2012–2013. World Economic Forum, Cologny/Geneva (2012)Google Scholar
  2. 2.
    Leidecker, J.K., Bruno, A.V.: CSF analysis and the strategy development process. In: Taylor, B. (ed.) Strategic Planning and Management Handbook. pp. 333–351. Van Nostrand Reinhold, New York (1987)Google Scholar
  3. 3.
    Rockart, J.F.: Chief executives define their own data needs. Harv. Bus. Rev. 57, 81–93 (1979)Google Scholar
  4. 4.
    Ülengin, F., Önsel, Ş., Aktas, E., Kabak, Ö., Özaydın, Ö.: A decision support methodology to enhance the competitiveness of the Turkish automotive industry. Eur. J. Oper. Res. 234, 789–801 (2014)CrossRefGoogle Scholar
  5. 5.
    Kabak, Ö., Ülengin, F., Önsel, Ş., Özaydin, Ö., Aktaş, E.: Cumulative belief degrees approach for analyzing the competitiveness of the automotive industry. Knowl.-Based Syst. 70, 15–25 (2014)CrossRefGoogle Scholar
  6. 6.
    Porter, M.E.: Competitive Advantage of Nations Creating and Sustaining Superior Performance. Free Press, New York (2014)Google Scholar
  7. 7.
    United Nations Comtrade database. (2013). Accessed 25 Dec 2013
  8. 8.
    Ülengin, F., Önsel, Ş., Çekyay, B., Özaydın, Ö., Aktaş, E., Kabak, Ö.: Iron and Steel Industry—Competitiveness Report. REF-SEDEFED, Istanbul (2011)Google Scholar
  9. 9.
    Choi, S.H., Jeon, B.N.: The impact of the macroeconomic environment on merger activity: evidence from US time-series data. Appl. Financ. Econ. 21, 233–249 (2011)CrossRefGoogle Scholar
  10. 10.
    Wu, J.-N., Zhong, W.-J.: Application capability of e-business and enterprise competitiveness: a case study of the iron and steel industry in China. Technol. Soc. 31, 198–206 (2009)CrossRefGoogle Scholar
  11. 11.
    Ohashi, H.: Learning by doing, export subsidies, and industry growth: Japanese steel in the 1950s and 1960s. J. Int. Econ. 66, 297–323 (2005)CrossRefGoogle Scholar
  12. 12.
    Hourcade, J., Quirion, P.: Does the CO2 emission trading directive threaten the competitiveness of European industry? Quantification and comparison to exchange rates fluctuations. Presented at the EAERE conference, Budapest, Hungary, June (2004)Google Scholar
  13. 13.
    Anger, N., Oberndorfer, U.: Firm performance and employment in the EU emissions trading scheme: an empirical assessment for Germany. Energy Policy 36, 12–22 (2008)CrossRefGoogle Scholar
  14. 14.
    Smale, R., Hartley, M., Hepburn, C., Ward, J., Grubb, M.: The impact of CO2 emissions trading on firm profits and market prices. Clim. Policy 6, 31–48 (2006)CrossRefGoogle Scholar
  15. 15.
    Demailly, D., Quirion, P.: European emission trading scheme and competitiveness: a case study on the iron and steel industry. Energy Econ. 30, 2009–2027 (2008)CrossRefGoogle Scholar
  16. 16.
    Singh, R.K., Murty, H.R., Gupta, S.K., Dikshit, A.K.: Development of composite sustainability performance index for steel industry. Ecol. Indic. 7, 565–588 (2007)CrossRefGoogle Scholar
  17. 17.
    Bullen, C.V., Rockart, J.F.: A Primer on Critical Success Factors. Massachusetts Institute of Technology, Sloan School of Management, Boston (1981)Google Scholar
  18. 18.
    Sun, C.-C.: Identifying critical success factors in EDA industry using DEMATEL method. Int. J. Comput. Intell. Syst. 8, 208–218 (2015)CrossRefGoogle Scholar
  19. 19.
    Belassi, W., Tukel, O.I.: A new framework for determining critical success/failure factors in projects. Int. J. Proj. Manag. 14, 141–151 (1996)CrossRefGoogle Scholar
  20. 20.
    Chan, A.P.C., Scott, D., Chan, A.P.L.: Factors affecting the success of a construction project. J. Constr. Eng. Manag. 130, 153–155 (2004)CrossRefGoogle Scholar
  21. 21.
    Karlsen, J.T., Andersen, J., Birkely, L.S., Odegard, E.: An empirical study of critical success factors in IT projects. Int. J. Manag. Enterp. Dev. 3, 297–311 (2006)CrossRefGoogle Scholar
  22. 22.
    King, S.F., Burgess, T.F.: Understanding success and failure in customer relationship management. Ind. Mark. Manag. 37, 421–431 (2008)CrossRefGoogle Scholar
  23. 23.
    Getz, D., Brown, G.: Critical success factors for wine tourism regions: a demand analysis. Tour. Manag. 27, 146–158 (2006)CrossRefGoogle Scholar
  24. 24.
    Hong, K.-K., Kim, Y.-G.: The critical success factors for ERP implementation: an organizational fit perspective. Inf. Manag. 40, 25–40 (2002)CrossRefGoogle Scholar
  25. 25.
    Pettit, S., Beresford, A.: Critical success factors in the context of humanitarian aid supply chains. Int. J. Phys. Distrib. Logist. Manag. 39, 450–468 (2009)CrossRefGoogle Scholar
  26. 26.
    Ragatz, G.L., Handfield, R.B., Scannell, T.V.: Success factors for integrating suppliers into new product development. J. Prod. Innov. Manag. 14, 190–202 (2003)CrossRefGoogle Scholar
  27. 27.
    Trkman, P.: The critical success factors of business process management. Int. J. Inf. Manag. 30, 125–134 (2010)CrossRefGoogle Scholar
  28. 28.
    YewWong, K.: Critical success factors for implementing knowledge management in small and medium enterprises. Ind. Manag. Data Syst. 105, 261–279 (2005)CrossRefGoogle Scholar
  29. 29.
    Hsu, C.-C.: Evaluation criteria for blog design and analysis of causal relationships using factor analysis and DEMATEL. Expert Syst. Appl. 39, 187–193 (2012)CrossRefGoogle Scholar
  30. 30.
    Zhou, Q., Huang, W., Zhang, Y.: Identifying critical success factors in emergency management using a fuzzy DEMATEL method. Saf. Sci. 49, 243–252 (2011)CrossRefGoogle Scholar
  31. 31.
    Gabus, A., Fontela, E.: World Problems, an Invitation to Further Thought Within the Framework of DEMATEL. Battelle Geneva Research Center, Geneva (1972)Google Scholar
  32. 32.
    Gabus, A., Fontela, E.: Perceptions of the World Problematique: Communication Procedure, Communicating with Those Bearing Collective Responsibility. Battelle Geneva Research Center, Geneva (1973)Google Scholar
  33. 33.
    Herrera, F., Herrera-Viedma, E., Martínez, L.: A fusion approach for managing multi-granularity linguistic term sets in decision making. Fuzzy Sets Syst. 114, 43–58 (2000)CrossRefzbMATHGoogle Scholar
  34. 34.
    Wang, R.-C., Chuu, S.-J.: Group decision-making using a fuzzy linguistic approach for evaluating the flexibility in a manufacturing system. Eur. J. Oper. Res. 154, 563–572 (2004)CrossRefzbMATHGoogle Scholar
  35. 35.
    Liou, J.J.H., Tzeng, G.-H., Chang, H.-C.: Airline safety measurement using a hybrid model. J. Air Transp. Manag. 13, 243–249 (2007)CrossRefGoogle Scholar
  36. 36.
    Liou, J.J.H.: Developing an integrated model for the selection of strategic alliance partners in the airline industry. Knowl.-Based Syst. 28, 59–67 (2012)CrossRefGoogle Scholar
  37. 37.
    Wu, W.-W.: Segmenting critical factors for successful knowledge management implementation using the fuzzy DEMATEL method. Appl. Soft Comput. 12, 527–535 (2012)CrossRefGoogle Scholar
  38. 38.
    Wu, H.-H., Chang, S.-Y.: A case study of using DEMATEL method to identify critical factors in green supply chain management. Appl. Math. Comput. 256, 394–403 (2015)MathSciNetGoogle Scholar
  39. 39.
    Govindan, K., Khodaverdi, R., Vafadarnikjoo, A.: Intuitionistic fuzzy based DEMATEL method for developing green practices and performances in a green supply chain. Expert Syst. Appl. 42, 7207–7220 (2015)CrossRefGoogle Scholar
  40. 40.
    Jeng, D.J.-F.: Generating a causal model of supply chain collaboration using the fuzzy DEMATEL technique. Comput. Ind. Eng. 87, 283–295 (2015)CrossRefGoogle Scholar
  41. 41.
    Sangari, M.S., Razmi, J., Zolfaghari, S.: Developing a practical evaluation framework for identifying critical factors to achieve supply chain agility. Measurement 62, 205–214 (2015)CrossRefGoogle Scholar
  42. 42.
    Zadeh, L.A.: Is there a need for fuzzy logic? Inf. Sci. 178, 2751–2779 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  43. 43.
    Wu, W.-W., Lee, Y.-T.: Developing global managers’ competencies using the fuzzy DEMATEL method. Expert Syst. Appl. 32, 499–507 (2007)CrossRefGoogle Scholar
  44. 44.
    Tseng, M.-L.: A causal and effect decision making model of service quality expectation using grey-fuzzy DEMATEL approach. Expert Syst. Appl. 36, 7738–7748 (2009)CrossRefGoogle Scholar
  45. 45.
    Linstone, H.A., Turoff, M. (eds.): The delphi method: techniques and applications. Online book (2002). Accessed 5 Dec 2013
  46. 46.
    Herrera, F., Martinez, L.: A model based on linguistic 2-tuples for dealing with multigranular hierarchical linguistic contexts in multi-expert decision-making. IEEE Trans. Syst. Man Cybern. Part B 31, 227–234 (2001)CrossRefGoogle Scholar
  47. 47.
    Opricovic, S., Tzeng, G.-H.: Defuzzification within a multi-criteria decision model. Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 11, 635–652 (2003)MathSciNetCrossRefzbMATHGoogle Scholar
  48. 48.
    Abdullah, L., Zulkifli, N.: Integration of fuzzy AHP and interval type-2 fuzzy DEMATEL: an application to human resource management. Expert Syst. Appl. 42, 4397–4409 (2015)CrossRefGoogle Scholar
  49. 49.
    Huang, C.-Y., Shyu, J.Z., Tzeng, G.-H.: Reconfiguring the innovation policy portfolios for Taiwan’s SIP Mall industry. Technovation 27, 744–765 (2007)CrossRefGoogle Scholar
  50. 50.
    Tzeng, G., Chiang, C., Li, C.: Evaluating intertwined effects in e-learning programs: a novel hybrid MCDM model based on factor analysis and DEMATEL. Expert Syst. Appl. 32, 1028–1044 (2007)CrossRefGoogle Scholar
  51. 51.
    Bai, C., Sarkis, J.: A grey-based DEMATEL model for evaluating business process management critical success factors. Int. J. Prod. Econ. 146, 281–292 (2013)CrossRefGoogle Scholar
  52. 52.
    Li, Y., Hu, Y., Zhang, X., Deng, Y., Mahadevan, S.: An evidential DEMATEL method to identify critical success factors in emergency management. Appl. Soft Comput. 22, 504–510 (2014)CrossRefGoogle Scholar
  53. 53.
    Turkish Industrial Strategy Document 2011–2014 (Towards EU Membership). (2010)
  54. 54.
    2003 Strategy Report. Turkish exporters assembly, Istanbul, Turkey (2003)Google Scholar
  55. 55.
    Wei, P.-L., Huang, J.-H., Tzeng, G.-H., Wu, S.-I.: Causal modeling of web-advertising effects by improving SEM based on DEMATEL technique. Int. J. Inf. Technol. Decis. Mak. 09, 799–829 (2010)CrossRefzbMATHGoogle Scholar
  56. 56.
    Yu, M.-C., Keng, I., Chen, H.-X.: Measuring service quality via a fuzzy analytical approach. Int. J. Fuzzy Syst. 17, 292–302 (2015)CrossRefGoogle Scholar
  57. 57.
    Keikha, A., Mishmast Nehi, H.: Fuzzified choquet integral and its applications in MADM: a review and a new method. Int. J. Fuzzy Syst. 17, 337–352 (2015)CrossRefGoogle Scholar

Copyright information

© Taiwan Fuzzy Systems Association and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Industrial Engineering DepartmentIstanbul Technical UniversityIstanbulTurkey
  2. 2.School of ManagementSabancı UniversityIstanbulTurkey
  3. 3.Industrial Engineering DepartmentDogus UniversityIstanbulTurkey

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