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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    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. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Wang, Juite & Shu, Yun-Feng, 2007. "A possibilistic decision model for new product supply chain design," European Journal of Operational Research, Elsevier, vol. 177(2), pages 1044-1061, March.
    12. Deniz Preil & Michael Krapp, 2022. "Artificial intelligence-based inventory management: a Monte Carlo tree search approach," Annals of Operations Research, Springer, vol. 308(1), pages 415-439, January.
    13. Hareer Fatima Ahmed & Amin Hosseinian-Far & Dilshad Sarwar & Rasoul Khandan, 2024. "Supply Chain Complexity and Its Impact on Knowledge Transfer: Incorporating Sustainable Supply Chain Practices in Food Supply Chain Networks," Logistics, MDPI, vol. 8(1), pages 1-24, January.
    14. Jain, Vipul & Deshmukh, S.G., 2009. "Dynamic supply chain modeling using a new fuzzy hybrid negotiation mechanism," International Journal of Production Economics, Elsevier, vol. 122(1), pages 319-328, November.
    15. Hua Ke & Yong Wu & Hu Huang, 2018. "Competitive Pricing and Remanufacturing Problem in an Uncertain Closed-Loop Supply Chain with Risk-Sensitive Retailers," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(01), pages 1-21, February.
    16. Handfield, Robert & Warsing, Don & Wu, Xinmin, 2009. "(Q,r) Inventory policies in a fuzzy uncertain supply chain environment," European Journal of Operational Research, Elsevier, vol. 197(2), pages 609-619, September.
    17. Petrovic, Dobrila, 2001. "Simulation of supply chain behaviour and performance in an uncertain environment," International Journal of Production Economics, Elsevier, vol. 71(1-3), pages 429-438, May.
    18. Левнер Е.В. & Птускин А.С., 2014. "О Выборе Направлений Модернизации Предприятий На Основе Информационно-Энтропийной Модели Хозяйственного Риска," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 50(2), pages 111-126, апрель.
    19. M J Schniederjans & A M Schniederjans & D G Schniederjans, 2009. "Operations research methodology life cycle trend phases as recorded in journal articles," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(7), pages 881-894, July.
    20. Roozbeh Nia, Ali & Hemmati Far, Mohammad & Akhavan Niaki, Seyed Taghi, 2014. "A fuzzy vendor managed inventory of multi-item economic order quantity model under shortage: An ant colony optimization algorithm," International Journal of Production Economics, Elsevier, vol. 155(C), pages 259-271.

    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.