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Performance Measurement of Logistics Firms with Multi-Criteria Decision Making Methods

Year 2013, Volume: 13 Issue: 4, 449 - 460, 01.11.2013

Abstract

In today’s competitive environment firms that have to use their resources optimally, should regularly carry out performance measurement in order to see the degree of achieving their goals. A strategic performance measurement necessitates inter-comparison of the firms operating in the same industry. Accordingly, the aim of this study is to conduct the performance measurement of 10 logistics firms taking place among the best 500 firms the Journal of FORTUNE Turkey explained for the year 2011 via Multi-Criteria Decision Making (MCDM) techniques. In the first stage of the three-stage study, the weights of the criteria that were determined considering the literature and data availability calculated using the CRITIC (Criteria Importance Through Intercritera Correlation) method, an objective MCDM technique. In the second stage, by performing SAW (Simple Additive Weighting), TOPSIS (The Technique for Order Preference by Similarity to Ideal Solution) and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) methods with the help of the weights obtained, firms are ranked with respect to their performances. In the third stage, a combined ranking is obtained by utilizing the three rankings of the mentioned methods via the Borda Count method, a data fusion technique. As a result of the application, it is revealed that the combined method used in the study is a convenient method for performance measurement and yields satisfactory results. Another study applying the integrated method used in this study is not met in the literature

References

  • Alfaro, J., Ortiz, A. ve Poler, R. (2007) “Performance Measurement System for Business Processes” Production Planning Control, 18(8): 641-654.
  • Borda, J.C. (1784)Memoire Sur Les Elections Au Scrutin. Paris, Histoire de I’Academie Royaledes Sciences.
  • Chamodrakas, I.,Leftheriotis, I. ve Martakos, D. (2011) “In-Depth Analysis and Simulation Study of an Innovati ve Fuzzy Approach for Ranking Alternatives in Multiple Attribute Decision Making Problems Based on TOPSIS”Applied Soft Computing, 11(1):900-907.
  • Charnes, A., Cooper, W.W. ve Rhodes, E. (1978) “Measuring the Efficiency of Decision Making Units” European Journal of Operational Research, 2:429-444.
  • Choo, E.U. ve Wedley, W.C. (1985) “Optimal CriterionWeights in Repetitive Multicriteria Decision- Making” Journal of Operational Research Society, 36
  • Chu, A.W., Kalaba, R.E. ve Spingarn, K. (1979) “A Comparison of Two Methodsfor Determining The Weights of Belonging to Fuzzy Sets” Journal of Optimization Theoryand Applications, 27(4):531-538.
  • Churchman, C.W. ve Ackoff, R.L. (1954) “An Approximate Measure of Value” Journal of Operations Research Society of America, 2(1):172-87.
  • Deng, H., Yeh, C.H. ve Willis, R.J.(2000) “Inter- Company Comparison Using Modified TOPSIS with Objective Weights” Computers & Operations Research 27:963-973.
  • Diakoulaki D., Mavrotas G. ve Papayannakis, L. (1995) “Determining Objective Weights in Multiple Criteria Problems: The Critic Method” Computers& Operations Research, 22:763-770. IN
  • Ellinger, A.E., Ketchen, D.J., Hult, G.M., Elmadağ, A.B. ve Richey, R.G. (2008) “Market Orientation, Employee Development Practices, and Performance in Logistics Service Provider Firms”Industrial Marketing Management, 37:353-366.
  • Fan, Z.P., Ma, J. ve Zhang, Q. (2002) “An Approachto Multiple Attribute Decision Making Based on FuzzyPreference Information on Alternatives”Fuzzy Sets and Systems, 131:101-106.
  • Fishburn, P.C. (1967) Additive Utilities with Incomplete Product Set: Applications to Priorities and Assignments, Baltimore, MD ORSA Publication.
  • Hamdan, A. ve Rogers, K.J. (2007) “Evaluating the Efficiency of 3PL Logistics Operations” International Journal of Production Economics, 113(1):235-244.
  • Hwang, C.L. ve Yoon, K. (1981)Multiple Attribute Decision Making: Methodsand Applications, A State-of-the- Art Survey, New York, Springer-Verlag.
  • Hwang, C.L., ve Lin, M.J. (1987) Group Decision Making Under Multiple Criteria: Methods and Application, New York, Springer-Verlag.
  • Jahan, A., Mustapha, F., Sapuan, S.M., Ismail, Y. ve Bahraminasab, M. (2012) “A Framework ForWeighting of Criteria in Ranking Stage of Material Selection Process”International Journal of Advanced ManufacturingTechnology, 58:411-420.
  • Jahanshahloo, G.R., Lotfi, F.H. ve Izadikhah, M.(2006) “An Algorithmic Method to Extend TOPSIS for Decision-Making Problems with Interval Data” Applied Mathematics and Computation, 175(2):1375- 1384.
  • Lamboray, C. (2007) “A Comparison Between the Prudent Order and the Ranking Obtained with Borda’s, Copeland’s, Slater’sand Kemeny’s Rules” Mathematical Social Sciences, 54(1):1-16.
  • Liu, C.H. ve Lyons, A.C.(2011) “An Analysis of Third-Party Logistics Performance and Service Provision” Transportation Research Part E, 47:547-570.
  • Ma, J., Fan, Z.P. ve Huang, L.H. (1999) “A Subjective And Objective Integrated Approach to Determine Attribute Weights, European Journal of Operational Research,112:397-404.
  • Nuray, R. ve Can F. (2006) “Automatic Ranking of Information Retrieval Systems Using Data Fusion”Information Processingand Management: an International Journal, 42(3):595-614.
  • Min, H. ve Joo, S.J. (2006) “Benchmarking the Operational Efficiency of Third Party Logistics Providers Using Data Envelopment Analysis” Supply Chain Management: An International Journal, 11(3):259-265.
  • Min, H. ve Joo, S.J. (2009) “Benchmarking Third- PartyLogistics Providers Using Data Envelopment Analysis: An Update” Benchmarking: An International Journal, 16(5):572-587.
  • O’Neill, J.C. (2004) “Tie-Breaking with the Single Transferable Vote” Voting Matters, 18(14):14-17.
  • Opricovic, S. (1998) Multicriteria Optimization of Civil Engineering Systems, Belgrade, Faculty of Civil Engineering.
  • Opricovic, S. ve Tzeng, G.H. (2003) “Defuzzification with in a Multicriteria Decision Model” International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 11(5):635-652.
  • Opricovic, S. ve Tzeng, G.H. (2004) “Compromise Solution by MCDM Methods: A Comparative Analysis of VIKOR and TOPSIS” European Journal of Operational Research, 156(2):445-455.
  • Opricovic, S. ve Tzeng, G.H. (2007) “Extended VIKOR Method in Comparison with Outranking Methods” European Journal of Operational Research, 178:514-529.
  • Saaty, T.L. (1980)The Analytic Hierarchy Process, New York, McGraw-Hill.
  • Sherman, D.H.(1984) “Hospital Efficiency Measurementand Evaluation: Empirical Test of New Technique”Medical Care, 22(10):922-938.
  • Shannon, C.E.(1948) “A Mathematical Theory of Communication” Bell Systems and Technology Journal, 27: 379-423.
  • Srinivasan, V. ve Shocker, A.D. (1973) “ A Composite Criterion Using Pairwise Judgments” Psychometrika,
  • Stewart, TJ. (1996) “Relationships Between Data Envelopment Analysis and Multi-criteria Decision Analysis” Journal of Operational Research Society, 47(5):654-665.
  • Tzeng, G.H. ve Huang, J.J. (2011) Multiple Attribute Decision Making: Methods and Applications, CRC Press, Taylor & Francis Group, A Chapman&Hall.
  • Wang, Y.M. ve Parkan, C. (2006) “A General Multiple Attribute Decision-Making Approach For Integrating Subjective Preferences and Objective Information” Fuzzy Sets and Systems, 157:1333-1345.
  • Wang, Y.M. ve Luo, Y. (2010) “Integration of Correlations with Standard Deviationsfor Determining Attribute Weights in Multiple Attribute Decision Making” Mathematical and Computer Modeling, 51(1- 2):1-12.
  • Wanke, P.F. (2009)“Determinants of Scale Efficiencyin the Brazilian 3PL Industry: A 10-Year Analysis” International Journal of Production Research,50(9):2012.
  • Yeh, C.H. (2003) “The Selection of Multi-attribute Decision Making Methods for Scholarship Student Selection” International Journal of Selection and Assessment, 11(4):289-296.
  • Yousefi, A. ve Hadi-Vencheh, A. (2010) “An Integrated Group Decision Making Model and Its Evaluation by DEA for Automobile Industry“ Expert Systems with Applications, 37: 8543-556.
  • Yu, P.L. (1973) “A Class of Solutions for Group Decision Problems” Management Science 19(8):936-946.
  • Zeleny, M.(1982) Multiple Criteria Decision Making, New York,Mc Graw-Hill.
  • Zhou, G., Min H., Xu, C. ve Cao, Z. (2008) “Evaluating the Comparative Efficiency of Chinese Third-Party Logistics Providers Using Data Envelopment Analysis” International Journal of Physical Distribution & Logistics Management, 38(4):262-279.

Çok Kriterli Karar Verme Teknikleriyle Lojistik Firmalarında Performans Ölçümü

Year 2013, Volume: 13 Issue: 4, 449 - 460, 01.11.2013

Abstract

Günümüz yoğun rekabet ortamında kaynaklarını optimal şekilde kullanmak zorunda olan işletmeler belirledikleri hedeflere ulaşma derecelerini görebilmek için düzenli olarak performans ölçümü yapmalıdır. Stratejik bir performans ölçümü ise aynı endüstri dalında faaliyet gösteren işletmelerin birbirleriyle karşılaştırılmasını gerektirir. Bu doğrultuda çalışmanın amacı, literatürde yaygın olarak kullanılan Çok Kriterli Karar Verme (ÇKKV) teknikleri yardımıyla 2011 yılı için “FORTUNE Türkiye” dergisinin açıkladığı ilk 500 firma listesinde yer alan 10 lojistik firmasının performans ölçümünü gerçekleştirmektir. Üç aşamada gerçekleştirilen uygulamanın ilk aşamasında literatür ve veri elverişliliği dikkate alınarak belirlenen değerlendirme kriterlerinin önem ağırlıkları objektif bir ÇKKV tekniği olan CRITIC (Criteria Importance Through Intercritera Correlation) yöntemiyle hesaplanmıştır. Elde edilen ağırlıklar yardımıyla ikinci aşamada SAW (Simple Additive Weighting), TOPSIS (The Technique for Order Preference by Similarity to Ideal Solution) ve VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) yöntemleri kullanılarak firmalar performanslarına göre sıralanmıştır. Üçüncü aşamada ise bir veri birleştirme (data fusion) tekniği olan Borda Sayım (Borda Count) yöntemiyle söz konusu üç yöntemle elde edilen sıralamalardan yararlanılarak bütünleşik tek bir sıralama elde edilmiştir. Uygulama sonucunda çalışmada kullanılan bütünleşik modelin performans ölçümü amacıyla kullanılabilecek uygun bir yöntem olduğu ve uygulayıcılara tatminkâr sonuçlar verdiği ortaya çıkmıştır. Bu çalışmada kullanılan bütünleşik yöntemle ilgili literatürde başka bir çalışmaya rastlanmamıştır

References

  • Alfaro, J., Ortiz, A. ve Poler, R. (2007) “Performance Measurement System for Business Processes” Production Planning Control, 18(8): 641-654.
  • Borda, J.C. (1784)Memoire Sur Les Elections Au Scrutin. Paris, Histoire de I’Academie Royaledes Sciences.
  • Chamodrakas, I.,Leftheriotis, I. ve Martakos, D. (2011) “In-Depth Analysis and Simulation Study of an Innovati ve Fuzzy Approach for Ranking Alternatives in Multiple Attribute Decision Making Problems Based on TOPSIS”Applied Soft Computing, 11(1):900-907.
  • Charnes, A., Cooper, W.W. ve Rhodes, E. (1978) “Measuring the Efficiency of Decision Making Units” European Journal of Operational Research, 2:429-444.
  • Choo, E.U. ve Wedley, W.C. (1985) “Optimal CriterionWeights in Repetitive Multicriteria Decision- Making” Journal of Operational Research Society, 36
  • Chu, A.W., Kalaba, R.E. ve Spingarn, K. (1979) “A Comparison of Two Methodsfor Determining The Weights of Belonging to Fuzzy Sets” Journal of Optimization Theoryand Applications, 27(4):531-538.
  • Churchman, C.W. ve Ackoff, R.L. (1954) “An Approximate Measure of Value” Journal of Operations Research Society of America, 2(1):172-87.
  • Deng, H., Yeh, C.H. ve Willis, R.J.(2000) “Inter- Company Comparison Using Modified TOPSIS with Objective Weights” Computers & Operations Research 27:963-973.
  • Diakoulaki D., Mavrotas G. ve Papayannakis, L. (1995) “Determining Objective Weights in Multiple Criteria Problems: The Critic Method” Computers& Operations Research, 22:763-770. IN
  • Ellinger, A.E., Ketchen, D.J., Hult, G.M., Elmadağ, A.B. ve Richey, R.G. (2008) “Market Orientation, Employee Development Practices, and Performance in Logistics Service Provider Firms”Industrial Marketing Management, 37:353-366.
  • Fan, Z.P., Ma, J. ve Zhang, Q. (2002) “An Approachto Multiple Attribute Decision Making Based on FuzzyPreference Information on Alternatives”Fuzzy Sets and Systems, 131:101-106.
  • Fishburn, P.C. (1967) Additive Utilities with Incomplete Product Set: Applications to Priorities and Assignments, Baltimore, MD ORSA Publication.
  • Hamdan, A. ve Rogers, K.J. (2007) “Evaluating the Efficiency of 3PL Logistics Operations” International Journal of Production Economics, 113(1):235-244.
  • Hwang, C.L. ve Yoon, K. (1981)Multiple Attribute Decision Making: Methodsand Applications, A State-of-the- Art Survey, New York, Springer-Verlag.
  • Hwang, C.L., ve Lin, M.J. (1987) Group Decision Making Under Multiple Criteria: Methods and Application, New York, Springer-Verlag.
  • Jahan, A., Mustapha, F., Sapuan, S.M., Ismail, Y. ve Bahraminasab, M. (2012) “A Framework ForWeighting of Criteria in Ranking Stage of Material Selection Process”International Journal of Advanced ManufacturingTechnology, 58:411-420.
  • Jahanshahloo, G.R., Lotfi, F.H. ve Izadikhah, M.(2006) “An Algorithmic Method to Extend TOPSIS for Decision-Making Problems with Interval Data” Applied Mathematics and Computation, 175(2):1375- 1384.
  • Lamboray, C. (2007) “A Comparison Between the Prudent Order and the Ranking Obtained with Borda’s, Copeland’s, Slater’sand Kemeny’s Rules” Mathematical Social Sciences, 54(1):1-16.
  • Liu, C.H. ve Lyons, A.C.(2011) “An Analysis of Third-Party Logistics Performance and Service Provision” Transportation Research Part E, 47:547-570.
  • Ma, J., Fan, Z.P. ve Huang, L.H. (1999) “A Subjective And Objective Integrated Approach to Determine Attribute Weights, European Journal of Operational Research,112:397-404.
  • Nuray, R. ve Can F. (2006) “Automatic Ranking of Information Retrieval Systems Using Data Fusion”Information Processingand Management: an International Journal, 42(3):595-614.
  • Min, H. ve Joo, S.J. (2006) “Benchmarking the Operational Efficiency of Third Party Logistics Providers Using Data Envelopment Analysis” Supply Chain Management: An International Journal, 11(3):259-265.
  • Min, H. ve Joo, S.J. (2009) “Benchmarking Third- PartyLogistics Providers Using Data Envelopment Analysis: An Update” Benchmarking: An International Journal, 16(5):572-587.
  • O’Neill, J.C. (2004) “Tie-Breaking with the Single Transferable Vote” Voting Matters, 18(14):14-17.
  • Opricovic, S. (1998) Multicriteria Optimization of Civil Engineering Systems, Belgrade, Faculty of Civil Engineering.
  • Opricovic, S. ve Tzeng, G.H. (2003) “Defuzzification with in a Multicriteria Decision Model” International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 11(5):635-652.
  • Opricovic, S. ve Tzeng, G.H. (2004) “Compromise Solution by MCDM Methods: A Comparative Analysis of VIKOR and TOPSIS” European Journal of Operational Research, 156(2):445-455.
  • Opricovic, S. ve Tzeng, G.H. (2007) “Extended VIKOR Method in Comparison with Outranking Methods” European Journal of Operational Research, 178:514-529.
  • Saaty, T.L. (1980)The Analytic Hierarchy Process, New York, McGraw-Hill.
  • Sherman, D.H.(1984) “Hospital Efficiency Measurementand Evaluation: Empirical Test of New Technique”Medical Care, 22(10):922-938.
  • Shannon, C.E.(1948) “A Mathematical Theory of Communication” Bell Systems and Technology Journal, 27: 379-423.
  • Srinivasan, V. ve Shocker, A.D. (1973) “ A Composite Criterion Using Pairwise Judgments” Psychometrika,
  • Stewart, TJ. (1996) “Relationships Between Data Envelopment Analysis and Multi-criteria Decision Analysis” Journal of Operational Research Society, 47(5):654-665.
  • Tzeng, G.H. ve Huang, J.J. (2011) Multiple Attribute Decision Making: Methods and Applications, CRC Press, Taylor & Francis Group, A Chapman&Hall.
  • Wang, Y.M. ve Parkan, C. (2006) “A General Multiple Attribute Decision-Making Approach For Integrating Subjective Preferences and Objective Information” Fuzzy Sets and Systems, 157:1333-1345.
  • Wang, Y.M. ve Luo, Y. (2010) “Integration of Correlations with Standard Deviationsfor Determining Attribute Weights in Multiple Attribute Decision Making” Mathematical and Computer Modeling, 51(1- 2):1-12.
  • Wanke, P.F. (2009)“Determinants of Scale Efficiencyin the Brazilian 3PL Industry: A 10-Year Analysis” International Journal of Production Research,50(9):2012.
  • Yeh, C.H. (2003) “The Selection of Multi-attribute Decision Making Methods for Scholarship Student Selection” International Journal of Selection and Assessment, 11(4):289-296.
  • Yousefi, A. ve Hadi-Vencheh, A. (2010) “An Integrated Group Decision Making Model and Its Evaluation by DEA for Automobile Industry“ Expert Systems with Applications, 37: 8543-556.
  • Yu, P.L. (1973) “A Class of Solutions for Group Decision Problems” Management Science 19(8):936-946.
  • Zeleny, M.(1982) Multiple Criteria Decision Making, New York,Mc Graw-Hill.
  • Zhou, G., Min H., Xu, C. ve Cao, Z. (2008) “Evaluating the Comparative Efficiency of Chinese Third-Party Logistics Providers Using Data Envelopment Analysis” International Journal of Physical Distribution & Logistics Management, 38(4):262-279.
There are 42 citations in total.

Details

Other ID JA22MS74SP
Journal Section Research Article
Authors

Süleyman Çakır This is me

Selçuk Perçin This is me

Publication Date November 1, 2013
Published in Issue Year 2013 Volume: 13 Issue: 4

Cite

APA Çakır, S., & Perçin, S. (2013). Performance Measurement of Logistics Firms with Multi-Criteria Decision Making Methods. Ege Academic Review, 13(4), 449-460.
AMA Çakır S, Perçin S. Performance Measurement of Logistics Firms with Multi-Criteria Decision Making Methods. ear. November 2013;13(4):449-460.
Chicago Çakır, Süleyman, and Selçuk Perçin. “Performance Measurement of Logistics Firms With Multi-Criteria Decision Making Methods”. Ege Academic Review 13, no. 4 (November 2013): 449-60.
EndNote Çakır S, Perçin S (November 1, 2013) Performance Measurement of Logistics Firms with Multi-Criteria Decision Making Methods. Ege Academic Review 13 4 449–460.
IEEE S. Çakır and S. Perçin, “Performance Measurement of Logistics Firms with Multi-Criteria Decision Making Methods”, ear, vol. 13, no. 4, pp. 449–460, 2013.
ISNAD Çakır, Süleyman - Perçin, Selçuk. “Performance Measurement of Logistics Firms With Multi-Criteria Decision Making Methods”. Ege Academic Review 13/4 (November 2013), 449-460.
JAMA Çakır S, Perçin S. Performance Measurement of Logistics Firms with Multi-Criteria Decision Making Methods. ear. 2013;13:449–460.
MLA Çakır, Süleyman and Selçuk Perçin. “Performance Measurement of Logistics Firms With Multi-Criteria Decision Making Methods”. Ege Academic Review, vol. 13, no. 4, 2013, pp. 449-60.
Vancouver Çakır S, Perçin S. Performance Measurement of Logistics Firms with Multi-Criteria Decision Making Methods. ear. 2013;13(4):449-60.