IDEAS home Printed from https://ideas.repec.org/a/ibn/assjnl/v21y2025i4p65.html

The Relationship of Omni-channel Retailing, Dynamic Capabilities and Firm Performance: Evidence from Chinese Cosmetics Industry

Author

Listed:
  • Yang Xiao
  • Raja Nerina Raja Yusof
  • Nor Azura Binti Adzharuddin

Abstract

There is an emerging trend in the retail industry known as omni-channel retailing. A major challenge for firms adapting to this environment is developing effective omni-channel retailing strategies. However, our understanding of the impact of omni-channel retailing on firm performance remains limited. This empirical study uses survey data from the Chinese cosmetics industry to test a model that measures the relationship between omni-channel retailing and firm performance. The results demonstrate that the omni-channel retailing environment significantly influences omni-channel integration, which in turn has a significant effect on firm performance. Furthermore, dynamic capability, influenced by the omni-channel retailing environment, not only positively affects omni-channel integration but also moderates the relationship between omni-channel integration and firm performance.

Suggested Citation

  • Yang Xiao & Raja Nerina Raja Yusof & Nor Azura Binti Adzharuddin, 2025. "The Relationship of Omni-channel Retailing, Dynamic Capabilities and Firm Performance: Evidence from Chinese Cosmetics Industry," Asian Social Science, Canadian Center of Science and Education, vol. 21(4), pages 1-65, August.
    • Handle: RePEc:ibn:assjnl:v:21:y:2025:i:4:p:65
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/ass/article/download/0/0/52019/56627
    Download Restriction: no
    File URL: https://ccsenet.org/journal/index.php/ass/article/view/0/52019
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pereira, Marina Meireles & Frazzon, Enzo Morosini, 2021. "A data-driven approach to adaptive synchronization of demand and supply in omni-channel retail supply chains," International Journal of Information Management, Elsevier, vol. 57(C).
    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. Jingxin Zhang & Jianxiong Zhang & Chunqiu Xu, 2024. "Contract design considering data driven marketing: with and without the cap and trade regulation," Annals of Operations Research, Springer, vol. 333(1), pages 157-199, February.
    2. Jirapan Liangrokapart & Sukanya Prakongwittaya, 2025. "Modelling Supply Chain Measurement in Omni-Channel Supply Chain," SN Operations Research Forum, Springer, vol. 6(3), pages 1-28, September.
    3. Fildes, Robert & Kolassa, Stephan & Ma, Shaohui, 2022. "Post-script—Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1319-1324.
    4. Kumar Detwal, Pankaj & Soni, Gunjan & Kumar Jakhar, Suresh & Kumar Srivastava, Deepak & Madaan, Jitender & Kayikci, Yasanur, 2023. "Machine learning-based technique for predicting vendor incoterm (contract) in global omnichannel pharmaceutical supply chain," Journal of Business Research, Elsevier, vol. 158(C).
    5. Vhatkar, Manjunath S. & Raut, Rakesh D. & Gokhale, Ravindra & Kumar, Mukesh & Akarte, Milind & Ghoshal, Sudishna, 2024. "Leveraging digital technology in retailing business: Unboxing synergy between omnichannel retail adoption and sustainable retail performance," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
    6. Chou, Yixuan & Tang, Wenjin, 2023. "Corporate advertising expense and share price synchronization," Finance Research Letters, Elsevier, vol. 56(C).
    7. Piyal Sarkar & Angappa Gunasekaran & Harshwardhan Kiran Patil, 2025. "Survivability of Supply Chains in the Era of Industry 4.0," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 26(1), pages 225-246, March.
    8. Xiaoxia Chen & Xiaofeng Su & Zhongbin Li & Jingjing Wu & Manhua Zheng & Anxin Xu, 2022. "RETRACTED ARTICLE: The impact of omni-channel collaborative marketing on customer loyalty to fresh retailers: the mediating effect of the omni-channel shopping experience," Operations Management Research, Springer, vol. 15(3), pages 983-997, December.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - 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:ibn:assjnl:v:21:y:2025:i:4:p:65. 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: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.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.