Comparing SMEs According to Industry 4.0 Adaptations for Mitigating the Bullwhip Effect

Babek Erdebilli*, Emine Nur Nacar, Mete Gundogan, Sujan Piya

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter


In supply chain management, the term “Industry 4.0” is gaining traction. Transparency across the supply chain and successful coordination between suppliers, manufacturers, distributors, wholesalers, retailers, and customers have been demonstrated to be critical. However, it is unavoidable that issues between supply chain firms would occur during the transfer of information from one stage to the next, resulting in negative effects for the whole chain. The issues emerging from the information flow between stakeholders result in improper planning, which makes it difficult to establish predictable systems and hence results in varying degrees of bullwhip effect. Industry 4.0 and its critical components, such as digitalization, system integration, big data analytics, and the Internet of Things (IoT), are critical for smart factories and hold the potential of resolving this issue. In this study, four suppliers which were selected from the automotive, food, furniture, and textile sectors were identified. Then, the potential of the data flow to reduce the bullwhip effect on a sectoral basis will be demonstrated. To evaluate these sectors, eleven criteria in four dimensions including capacity sharing and out-of-stock decisions, demand signal processing, price fluctuation, and order merge were selected.

Original languageEnglish
Title of host publicationMultiple Criteria Decision Making
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages16
Publication statusPublished - Jan 1 2022

Publication series

NameMultiple Criteria Decision Making
ISSN (Print)2366-0023
ISSN (Electronic)2366-0031


  • Bullwhip effect
  • Fuzzy
  • Industry 4.0
  • Supply chain
  • İntuitionistic

ASJC Scopus subject areas

  • Strategy and Management
  • Decision Sciences (miscellaneous)
  • Management Science and Operations Research

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