Analyzing key influence factors of city logistics development using the fuzzy decision making trial and evaluation laboratory (DEMATEL) method

As the urban sprawl, the influence of city logistics on economy, society and environment is more and more remarkable, so city logistics receives increasingly attention recently. Since the city logistics system is a complex system affected by many factors, and these factors affect each other, it is difficult to improve all the influence factors at the same time to enhance the performance of city logistics. Therefore, there is need to find out the key influence factors of city logistics in order to improve them gradually. Considering the vagueness of human judgments, this paper pioneers in exploring the decision-making trial and evaluation laboratory (DEMATEL) method combining with fuzzy logic to identify the key influence factors of city logistics. According to analysis results, six key influence factors are identified,which are helpful to propose a comprehensive measure. As the implementation of this comprehensive measure, all other factors can be improved step by step. Finally the development level of city logistics might be improved.   Key words: City logistics, Key factor, fuzzy logic, decision-making trial and evaluation laboratory (DEMATEL) method

[1]  Shaohua Dong,et al.  Evaluation and Analysis: Development Trend of China’s Logistics Industry under Supply Chain Globalization Environments , 2009 .

[2]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning - II , 1975, Inf. Sci..

[3]  David J. A. V. Magalhães,et al.  Urban freight transport in a metropolitan context: The Belo Horizonte city case study , 2010 .

[4]  M. Figliozzi.  The impacts of congestion on time-definitive urban freight distribution networks CO2 emission levels: Results from a case study in Portland, Oregon , 2011 .

[5]  Julian Allen,et al.  BESTUFS good practice guide on urban freight transport , 2007 .

[6]  Jiuh-Biing Sheu,et al.  A novel dynamic resource allocation model for demand-responsive city logistics distribution operations , 2006 .

[7]  Tina Petersen.  Development of a city logistics concept , 2006 .

[8]  Chih-Hung Wu,et al.  Fuzzy DEMATEL method for developing supplier selection criteria , 2011, Expert Syst. Appl..

[9]  C. Busse.  A PROCEDURE FOR SECONDARY DATA ANALYSIS: INNOVATION BY LOGISTICS SERVICE PROVIDERS , 2010 .

[10]  Eduardo Betanzo-Quezada,et al.  An urban freight transport index , 2010 .

[11]  Gwo-Hshiung Tzeng,et al.  Defuzzification within a Multicriteria Decision Model , 2003, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[12]  Julian Allen,et al.  University of Westminster Eprints , 2006 .

[13]  F. Russo,et al.  A classification of city logistics measures and connected impacts , 2010 .

[14]  Luis Onieva,et al.  Solutions applicable by local administrations for urban logistics , 2005 .

[15]  Eiichi Taniguchi,et al.  EVALUATING CITY LOGISTICS MEASURES CONSIDERING THE BEHAVIOR OF SEVERAL STAKEHOLDERS , 2005 .

[16]  Quan Zhou,et al.  Identifying critical success factors in emergency management using a fuzzy DEMATEL method , 2011 .

[17]  Eiichi Taniguchi,et al.  Predicting the effects of city logistics schemes , 2003 .

[18]  Eiichi Taniguchi,et al.  Evaluating city logistics measures using a multi-agent model , 2010 .

[19]  Rong Li.  Fuzzy method in group decision making , 1999 .

[20]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[21]  Ronald R. Yager,et al.  Essentials of fuzzy modeling and control , 1994 .

[22]  Eiichi Taniguchi,et al.  An evaluation methodology for city logistics , 2000 .

[23]  Eiichi Taniguchi,et al.  Modeling City Logistics , 2002 .

[24]  S. M. Seyed Hosseini,et al.  Reprioritization of failures in a system failure mode and effects analysis by decision making trial and evaluation laboratory technique , 2006, Reliab. Eng. Syst. Saf..

[25]  Pavlos S. Kanaroglou,et al.  Logistics land use and the city: A spatial-temporal modeling approach , 2008 .

[26]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[27]  Eiichi Taniguchi,et al.  Incorporating risks in City Logistics , 2009 .

[28]  A. Gabus,et al.  Perceptions of the world problematique: communication procedure, communicating with those bearing collective responsibility , 1973 .

[29]  Hirohito Kuse,et al.  Logistics facility, road network and district planning: Establishing comprehensive planning for city logistics , 2010 .

[30]  Wei-Wen Wu,et al.  Developing global managers' competencies using the fuzzy DEMATEL method , 2007, Expert Syst. Appl..

[31]  Hans-Jürgen Zimmermann,et al.  Fuzzy Set Theory - and Its Applications , 1985 .

[32]  E. Karsak,et al.  Fuzzy multi-criteria decision-making procedure for evaluating advanced manufacturing system investments , 2001 .

[33]  Gwo-Hshiung Tzeng,et al.  Evaluating intertwined effects in e-learning programs: A novel hybrid MCDM model based on factor analysis and DEMATEL , 2007, Expert Syst. Appl..