IDEAS home Printed from https://ideas.repec.org/a/spr/opmare/v16y2023i2d10.1007_s12063-022-00337-w.html
   My bibliography  Save this article

Information sharing antecedents in the supply chain: a dynamic network perspective

Author

Listed:
  • Rasool Lavaei Adaryani

    (Agricultural Planning, Economic and Rural Development Research Institute (APERDRI))

  • Khalil Kalantari

    (University of Tehran)

  • Ali Asadi

    (University of Tehran)

  • Amir Alambeigi

    (University of Tehran)

  • Hesamedin Gholami

    (Agricultural Education and Extension Institute, Agricultural Research, Education and Extension Organization (AREEO))

  • Naser Seifollahi

    (University of Mohaghegh Ardabili)

Abstract

The primary purpose of this study is to empirically test the effects of trust, physical proximity, and network structure on the information-sharing ties across the Supply Chain Network (SCN) over time. Given a three-wave dataset, the Simulation Investigation for Empirical Network Analysis (SIENA) technique based on a Stochastic Actor-Oriented Model (SAOM) is employed to develop the research model. To do this, the two processes, including social selection (at the network level) and social influence (at the behavior level), are considered. The respondents of this study consisted of 91 chief executive officers from 32 Production Organizations (POs). The results revealed that information sharing was significantly the result of the social selection process. Physical proximity and network structure in the form of the social selection process affected information sharing. However, trust had no significant effect on information sharing. Indeed, trust may not directly predict information sharing rather indirectly explain it because of other phenomena such as physical proximity. Furthermore, the formation of information-sharing ties is not limited to the selection of a particular actor but is done with the aim of balancing the benefits and costs. The results provide managers with a set of useful mechanisms for enhancing information sharing across the supply chain.

Suggested Citation

  • Rasool Lavaei Adaryani & Khalil Kalantari & Ali Asadi & Amir Alambeigi & Hesamedin Gholami & Naser Seifollahi, 2023. "Information sharing antecedents in the supply chain: a dynamic network perspective," Operations Management Research, Springer, vol. 16(2), pages 887-903, June.
    • Handle: RePEc:spr:opmare:v:16:y:2023:i:2:d:10.1007_s12063-022-00337-w
    DOI: 10.1007/s12063-022-00337-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12063-022-00337-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12063-022-00337-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Andre Torre, 2008. "On the Role Played by Temporary Geographical Proximity in Knowledge Transmission," Regional Studies, Taylor & Francis Journals, vol. 42(6), pages 869-889.
    2. Xiao Fu & Guanghua Han, 2017. "Trust-Embedded Information Sharing among One Agent and Two Retailers in an Order Recommendation System," Sustainability, MDPI, vol. 9(5), pages 1-18, April.
    3. Kembro, Joakim & Näslund, Dag & Olhager, Jan, 2017. "Information sharing across multiple supply chain tiers: A Delphi study on antecedents," International Journal of Production Economics, Elsevier, vol. 193(C), pages 77-86.
    4. Wang, Qunzhi & Liu, Xinlin & Liu, Zijian & Xiang, Qin, 2020. "Option-based supply contracts with dynamic information sharing mechanism under the background of smart factory," International Journal of Production Economics, Elsevier, vol. 220(C).
    5. Hau L. Lee & Kut C. So & Christopher S. Tang, 2000. "The Value of Information Sharing in a Two-Level Supply Chain," Management Science, INFORMS, vol. 46(5), pages 626-643, May.
    6. Thokozani Patmond Mbhele, 2014. "Antecedents of Quality Information Sharing in the FMCG Industry," Journal of Economics and Behavioral Studies, AMH International, vol. 6(12), pages 986-1003.
    7. Hill, Alex & Doran, Des & Stratton, Roy, 2012. "How should you stabilise your supply chains?," International Journal of Production Economics, Elsevier, vol. 135(2), pages 870-881.
    8. Susan Cohen Kulp & Hau L. Lee & Elie Ofek, 2004. "Manufacturer Benefits from Information Integration with Retail Customers," Management Science, INFORMS, vol. 50(4), pages 431-444, April.
    9. Todo, Yasuyuki & Matous, Petr & Inoue, Hiroyasu, 2016. "The strength of long ties and the weakness of strong ties: Knowledge diffusion through supply chain networks," Research Policy, Elsevier, vol. 45(9), pages 1890-1906.
    10. Wu, Ing-Long & Chuang, Cheng-Hung & Hsu, Chien-Hua, 2014. "Information sharing and collaborative behaviors in enabling supply chain performance: A social exchange perspective," International Journal of Production Economics, Elsevier, vol. 148(C), pages 122-132.
    11. Paul F. Skilton & Ednilson Bernardes, 2015. "Competition network structure and product market entry," Strategic Management Journal, Wiley Blackwell, vol. 36(11), pages 1688-1696, November.
    12. Med Kechidi & Damien Talbot, 2010. "Institutions and coordination: what is the contribution of a proximity-based analysis? The case of Airbus and its relations with the subcontracting network," Post-Print hal-02354283, HAL.
    13. Shen, Jiayu, 2020. "An environmental supply chain network under uncertainty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    14. Li, Tian & Zhang, Hongtao, 2015. "Information sharing in a supply chain with a make-to-stock manufacturer," Omega, Elsevier, vol. 50(C), pages 115-125.
    15. T. Ramayah & Roaimah Omar, 2010. "Information Exchange And Supply Chain Performance," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 9(01), pages 35-52.
    16. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 1997. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 43(4), pages 546-558, April.
    17. Cheng, Jao-Hong, 2011. "Inter-organizational relationships and information sharing in supply chains," International Journal of Information Management, Elsevier, vol. 31(4), pages 374-384.
    18. Kao, Ta-Wei (Daniel) & Simpson, N.C. & Shao, Benjamin B.M. & Lin, Winston T., 2017. "Relating supply network structure to productive efficiency: A multi-stage empirical investigation," European Journal of Operational Research, Elsevier, vol. 259(2), pages 469-485.
    19. Banerjee, Mohua & Mishra, Manit, 2017. "Retail supply chain management practices in India: A business intelligence perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 34(C), pages 248-259.
    20. Lee, Hwee Khei & Fernando, Yudi, 2015. "The antecedents and outcomes of the medical tourism supply chain," Tourism Management, Elsevier, vol. 46(C), pages 148-157.
    21. Seiler, A. & Papanagnou, C. & Scarf, P., 2020. "On the relationship between financial performance and position of businesses in supply chain networks," International Journal of Production Economics, Elsevier, vol. 227(C).
    22. Mehmood Khan & Matloub Hussain & Avraam Papastathopoulos & Ioannis Manikas, 2018. "Trust, information sharing and uncertainty: An empirical investigation into their impact on sustainability in service supply chains in the United Arab Emirates," Sustainable Development, John Wiley & Sons, Ltd., vol. 26(6), pages 870-878, November.
    23. Özalp Özer & Yanchong Zheng & Kay-Yut Chen, 2011. "Trust in Forecast Information Sharing," Management Science, INFORMS, vol. 57(6), pages 1111-1137, June.
    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. Li, Xiaojing & Chen, Jing & Ai, Xingzheng, 2019. "Contract design in a cross-sales supply chain with demand information asymmetry," European Journal of Operational Research, Elsevier, vol. 275(3), pages 939-956.
    2. Lai, Kee-hung & Wong, Christina W.Y. & Lam, Jasmine Siu Lee, 2015. "Sharing environmental management information with supply chain partners and the performance contingencies on environmental munificence," International Journal of Production Economics, Elsevier, vol. 164(C), pages 445-453.
    3. Leon Yang Chu & Noam Shamir & Hyoduk Shin, 2017. "Strategic Communication for Capacity Alignment with Pricing in a Supply Chain," Management Science, INFORMS, vol. 63(12), pages 4366-4377, December.
    4. Babai, M.Z. & Boylan, J.E. & Syntetos, A.A. & Ali, M.M., 2016. "Reduction of the value of information sharing as demand becomes strongly auto-correlated," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 130-135.
    5. Hyun Jung Kim, 2017. "Information technology and firm performance: the role of supply chain integration," Operations Management Research, Springer, vol. 10(1), pages 1-9, June.
    6. Ding, Huiping & Guo, Baochun & Liu, Zhishuo, 2011. "Information sharing and profit allotment based on supply chain cooperation," International Journal of Production Economics, Elsevier, vol. 133(1), pages 70-79, September.
    7. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 2004. "Comments on "Information Distortion in a Supply Chain: The Bullwhip Effect"," Management Science, INFORMS, vol. 50(12_supple), pages 1887-1893, December.
    8. Abdurrezzak Sener & Mehmet Barut & Ali Dag & Mehmet Bayram Yildirim, 2021. "Impact of commitment, information sharing, and information usage on supplier performance: a Bayesian belief network approach," Annals of Operations Research, Springer, vol. 303(1), pages 125-158, August.
    9. Kefeng Xu & Yang Dong & Yu Xia, 2014. "‘Too Little’ or ‘Too Late’: The Timing of Supply Chain Demand Collaboration," Working Papers 0203mss, College of Business, University of Texas at San Antonio.
    10. Roberto Dominguez & Salvatore Cannella & Borja Ponte & Jose M. Framinan, 2022. "Information sharing in decentralised supply chains with partial collaboration," Flexible Services and Manufacturing Journal, Springer, vol. 34(2), pages 263-292, June.
    11. Özalp Özer & Yanchong Zheng & Yufei Ren, 2014. "Trust, Trustworthiness, and Information Sharing in Supply Chains Bridging China and the United States," Management Science, INFORMS, vol. 60(10), pages 2435-2460, October.
    12. Caridi, Maria & Moretto, Antonella & Perego, Alessandro & Tumino, Angela, 2014. "The benefits of supply chain visibility: A value assessment model," International Journal of Production Economics, Elsevier, vol. 151(C), pages 1-19.
    13. Li, Tian & Zhang, Hongtao, 2015. "Information sharing in a supply chain with a make-to-stock manufacturer," Omega, Elsevier, vol. 50(C), pages 115-125.
    14. Titah, Ryad & Shuraida, Shadi & Rekik, Yacine, 2016. "Integration breach: Investigating the effect of internal and external information sharing and coordination on firm profit," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 34-47.
    15. Ryu, Seung-Jin & Tsukishima, Takahiro & Onari, Hisashi, 2009. "A study on evaluation of demand information-sharing methods in supply chain," International Journal of Production Economics, Elsevier, vol. 120(1), pages 162-175, July.
    16. Caniato, Federico & Golini, Ruggero & Kalchschmidt, Matteo, 2013. "The effect of global supply chain configuration on the relationship between supply chain improvement programs and performance," International Journal of Production Economics, Elsevier, vol. 143(2), pages 285-293.
    17. Song, Yuyue, 2020. "Impact of untrue reporting in a two-echelon supply chain with asymmetric inventory information," International Journal of Production Economics, Elsevier, vol. 230(C).
    18. Zach Zhizhong Zhou & Kevin Xiaoguo Zhu, 2010. "The Effects of Information Transparency on Suppliers, Manufacturers, and Consumers in Online Markets," Marketing Science, INFORMS, vol. 29(6), pages 1125-1137, 11-12.
    19. Williams, Brent D. & Waller, Matthew A. & Ahire, Sanjay & Ferrier, Gary D., 2014. "Predicting retailer orders with POS and order data: The inventory balance effect," European Journal of Operational Research, Elsevier, vol. 232(3), pages 593-600.
    20. Simpson, N.C. & Tacheva, Zhasmina & Kao, Ta-Wei, 2023. "Semi-directedness: New network concepts for supply chain research," International Journal of Production Economics, Elsevier, vol. 256(C).

    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:spr:opmare:v:16:y:2023:i:2:d:10.1007_s12063-022-00337-w. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.