IDEAS home Printed from https://ideas.repec.org/p/boh/wpaper/01_2011.html
   My bibliography  Save this paper

Fuzzy approach to supply chain management

Author

Listed:
  • Jaroslava Smolová

    (Department of Management, Faculty of Economics, University of South Bohemia In České Budějovice)

  • Martin Pech

    (Faculty of Economics, University of South Bohemia In České Budějovice)

Abstract

During recent years, the supply chain performance management has become a key strategic consideration. Many manufacturers seek to collaborate with their suppliers and customers in order to upgrade their competitiveness and management performance. Because of complexity, uncertainty and vagueness inherent in supply chains, performance measurement using fuzzy approach was also identified as a new research direction. The main aim of the paper is focused on evaluation of logistic dimensions (sets of logistic indicators) in supply chain, where the uncertainty arises from the inability to perform adequate measurement, and deals with application of fuzzy approach, that provides a formal method for modeling imprecise, vagueness or incomplete relationships inherent in supply chains. Gathered data from questionnaires are analyzed by cluster analysis. Afterwards fuzzy methods are used evaluations of basic five dimensions, which contain several numbers of logistic indicators. The new methodology adopted from Soyer, Kabak, & Asan (2007) research based on the intersection of fuzzy sets and fuzzy entropy method has been applied to evaluations in a case study. Results are afterwards modified by a applying of different membership functions, and changes of dimensions measures are analyzed. Finally supply chain modifying by adding new companies with capability of bind to supply chain are examined. New results of evaluation are compared according to new companies’ membership to different clusters.

Suggested Citation

  • Jaroslava Smolová & Martin Pech, 2011. "Fuzzy approach to supply chain management," Economics Working Papers 2011-01, University of South Bohemia in Ceske Budejovice, Faculty of Economics.
    • Handle: RePEc:boh:wpaper:01_2011
    as

    Download full text from publisher

    File URL: http://repec.ef.jcu.cz/RePEc/boh/wpaper/01_2011.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wu, Y. & Frizelle, G. & Efstathiou, J., 2007. "A study on the cost of operational complexity in customer-supplier systems," International Journal of Production Economics, Elsevier, vol. 106(1), pages 217-229, March.
    2. Martinez-Olvera, Cesar, 2008. "Entropy as an assessment tool of supply chain information sharing," European Journal of Operational Research, Elsevier, vol. 185(1), pages 405-417, February.
    3. Chang, Sheng-Lin & Wang, Reay-Chen & Wang, Shih-Yuan, 2006. "Applying fuzzy linguistic quantifier to select supply chain partners at different phases of product life cycle," International Journal of Production Economics, Elsevier, vol. 100(2), pages 348-359, April.
    4. Shuiabi, Eyas & Thomson, Vince & Bhuiyan, Nadia, 2005. "Entropy as a measure of operational flexibility," European Journal of Operational Research, Elsevier, vol. 165(3), pages 696-707, September.
    5. Petrovic, Dobrila & Roy, Rajat & Petrovic, Radivoj, 1999. "Supply chain modelling using fuzzy sets," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 443-453, March.
    6. Jaroslava Smolová, 2009. "Analysis of metrics used for storage process evaluation," Acta Universitatis Bohemiae Meridionales, University of South Bohemia in Ceske Budejovice, vol. 12(3), pages 111-118.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sivadasan, Suja & Smart, Janet & Huaccho Huatuco, Luisa & Calinescu, Anisoara, 2013. "Reducing schedule instability by identifying and omitting complexity-adding information flows at the supplier–customer interface," International Journal of Production Economics, Elsevier, vol. 145(1), pages 253-262.
    2. Jha, Pradeep K. & Jha, Rakhi & Datt, Rajul & Guha, Sujoy K., 2011. "Entropy in good manufacturing system: Tool for quality assurance," European Journal of Operational Research, Elsevier, vol. 211(3), pages 658-665, June.
    3. F. Jolai & J. Razmi & N. Rostami, 2011. "A fuzzy goal programming and meta heuristic algorithms for solving integrated production: distribution planning problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 19(4), pages 547-569, December.
    4. Preil, Deniz & Krapp, Michael, 2022. "Bandit-based inventory optimisation: Reinforcement learning in multi-echelon supply chains," International Journal of Production Economics, Elsevier, vol. 252(C).
    5. Seebacher, Gottfried & Winkler, Herwig, 2014. "Evaluating flexibility in discrete manufacturing based on performance and efficiency," International Journal of Production Economics, Elsevier, vol. 153(C), pages 340-351.
    6. Park, Kijung & Okudan Kremer, Gül E., 2015. "Assessment of static complexity in design and manufacturing of a product family and its impact on manufacturing performance," International Journal of Production Economics, Elsevier, vol. 169(C), pages 215-232.
    7. Taleizadeh, Ata Allah & Shokr, Iman & Konstantaras, Ioannis & VafaeiNejad, Mahyar, 2020. "Stock replenishment policies for a vendor-managed inventory in a retailing system," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
    8. Enrico Teich & Thorsten Claus, 2017. "Measurement of Load and Capacity Flexibility in Manufacturing," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(4), pages 291-302, December.
    9. Chang, Sheng-Lin & Wang, Reay-Chen & Wang, Shih-Yuan, 2007. "Applying a direct multi-granularity linguistic and strategy-oriented aggregation approach on the assessment of supply performance," European Journal of Operational Research, Elsevier, vol. 177(2), pages 1013-1025, March.
    10. Wang, Shih-Yuan & Chang, Sheng-Lin & Wang, Reay-Chen, 2009. "Assessment of supplier performance based on product-development strategy by applying multi-granularity linguistic term sets," Omega, Elsevier, vol. 37(1), pages 215-226, February.
    11. Keunho Choi & Gunwoo Kim & Yongmoo Suh & Donghee Yoo, 0. "Assignment of collaborators to multiple business problems using genetic algorithm," Information Systems and e-Business Management, Springer, vol. 0, pages 1-19.
    12. Ryu, Kwangyeol & Yücesan, Enver, 2010. "A fuzzy newsvendor approach to supply chain coordination," European Journal of Operational Research, Elsevier, vol. 200(2), pages 421-438, January.
    13. Peidro, David & Mula, Josefa & Jiménez, Mariano & del Mar Botella, Ma, 2010. "A fuzzy linear programming based approach for tactical supply chain planning in an uncertainty environment," European Journal of Operational Research, Elsevier, vol. 205(1), pages 65-80, August.
    14. Bottani, Eleonora & Rizzi, Antonio, 2008. "An adapted multi-criteria approach to suppliers and products selection--An application oriented to lead-time reduction," International Journal of Production Economics, Elsevier, vol. 111(2), pages 763-781, February.
    15. Zhengyin Zhou & Xiaoling Wang & Ruirui Sun & Xuefei Ao & Xiaopei Sun & Mingrui Song, 2014. "Study of the comprehensive risk analysis of dam-break flooding based on the numerical simulation of flood routing. Part II: Model application and results," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 72(2), pages 675-700, June.
    16. S Sivadasan & J Smart & L Huaccho Huatuco & A Calinescu, 2010. "Operational complexity and supplier–customer integration: case study insights and complexity rebound," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(12), pages 1709-1718, December.
    17. Kayakutlu, Gulgun & Buyukozkan, Gulcin, 2011. "Assessing performance factors for a 3PL in a value chain," International Journal of Production Economics, Elsevier, vol. 131(2), pages 441-452, June.
    18. Chen, Shun-Hsing & Yang, Ching-Chow & Lin, Wen-Tsann & Yeh, Tsu-Ming, 2008. "Performance evaluation for introducing statistical process control to the liquid crystal display industry," International Journal of Production Economics, Elsevier, vol. 111(1), pages 80-92, January.
    19. Wu, Chong & Barnes, David, 2010. "Formulating partner selection criteria for agile supply chains: A Dempster-Shafer belief acceptability optimisation approach," International Journal of Production Economics, Elsevier, vol. 125(2), pages 284-293, June.
    20. Lokesh Nagar & Pankaj Dutta & Karuna Jain, 2014. "An integrated supply chain model for new products with imprecise production and supply under scenario dependent fuzzy random demand," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(5), pages 873-887, May.

    More about this item

    Keywords

    Supply Chain; Fuzzy Sets; Fuzzy Measures; Fuzzy Entropy;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:boh:wpaper:01_2011. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Markéta Matějíčková (email available below). General contact details of provider: https://edirc.repec.org/data/efjcucz.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.