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Evaluation across and within collaborative manufacturing networks: a comparison of manufacturers’ interactions and attributes

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  • Jiewu Leng
  • Pingyu Jiang

Abstract

Evaluation on collaborative manufacturing network (CMN) structure characteristics has important implications for network operations such as production decision-making, product recovery, creating consensus. Several recent studies suggest that augmenting network structure with nodes’ attributes can provide a more fine-grained understanding of the network. However, there have been few studies to provide a systematic understanding of these effects in a CMN at scale. This gap is bridged using an industrial printing machinery CMN data-set collected on a web-based producing and outsourcing service platform. Novel phenomena with respect to both interaction and attribute metrics across and within the CMNs are observed. Moreover, although many studies employ either interaction or attribute data to study the relative roles of manufacturers in a CMN, relatively little is known about the relationship between these two types of data. This study explores this relationship by comparing two defined metrics (i.e. relational capability and node capability), which evaluate the manufacturers’ interactions and attributes, respectively. We examine to what extent the two metrics of manufacturers correlate with each other, and how possible dissimilarities and similarities can be explained based on the collected industrial CMN data-set. The insights thereby provide a better basis for efficient operations decision-making in CMN.

Suggested Citation

  • Jiewu Leng & Pingyu Jiang, 2018. "Evaluation across and within collaborative manufacturing networks: a comparison of manufacturers’ interactions and attributes," International Journal of Production Research, Taylor & Francis Journals, vol. 56(15), pages 5131-5146, August.
  • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:15:p:5131-5146
    DOI: 10.1080/00207543.2018.1430903
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    Cited by:

    1. Christian Weckenborg & Karsten Kieckhäfer & Christoph Müller & Martin Grunewald & Thomas S. Spengler, 2020. "Balancing of assembly lines with collaborative robots," Business Research, Springer;German Academic Association for Business Research, vol. 13(1), pages 93-132, April.
    2. Leng, Jiewu & Ruan, Guolei & Jiang, Pingyu & Xu, Kailin & Liu, Qiang & Zhou, Xueliang & Liu, Chao, 2020. "Blockchain-empowered sustainable manufacturing and product lifecycle management in industry 4.0: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    3. Chiara Freichel & Nicolas Neis & Axel Winkelmann, 2021. "A Taxonomy For Interorganizational Production Networks," Business Logistics in Modern Management, Josip Juraj Strossmayer University of Osijek, Faculty of Economics, Croatia, vol. 21, pages 167-187.
    4. Mehmet Ali Soytaş & Damla Durak Uşar & Meltem Denizel, 2022. "Estimation of the static corporate sustainability interactions," International Journal of Production Research, Taylor & Francis Journals, vol. 60(4), pages 1245-1264, February.
    5. Gansterer, Margaretha & Födermayr, Patrick & Hartl, Richard F., 2021. "The capacitated multi-level lot-sizing problem with distributed agents," International Journal of Production Economics, Elsevier, vol. 235(C).

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