IDEAS home Printed from https://ideas.repec.org/a/ahd/journl/v3y2022i7p62-72.html
   My bibliography  Save this article

The Impact of Data Analytics on High Efficiency Supply Chain Management

Author

Listed:
  • Sakila Akter JAHAN

    (Independent University, Bangladesh, Dhaka, Bangladesh)

  • Mesbaul Haque SAZU

    (Case Western Reserve University, Cleveland, USA)

Abstract

Change is inevitable, so when supply chain (SC) managers strategize for future years, they must deal with challenges of the global supply chain management (SCM) issues. Leading trends over the last couple of years tend to be the increasing value of big data and analyzing the information through analytics. The information has tremendous value; businesses must capitalize on the assortment of information by proper and in-depth evaluation with the usage of big data analytics (BDA). This article seeks to spotlight the changing dynamics of the SC managing atmosphere, to recognize the way the two leading trends will influence SCM in future, to demonstrate the advantages which may be derived, and to generate suggestions for providing SC managers if BDA is adopted. The process of deriving value from the large quantities of information within the SCM is defined. It is demonstrated, through examples, the way SCM location might be influenced by these brand-new developments and trends. Within the examples, BDA have been adopted, utilized and applied effectively. Big data and analytics to draw out value coming from the information can create a big influence. It is clearly suggested that chain administrators pay attention to these two trends, since better usage of BDA can ensure they keep abreast with innovations modifications, which could help improve company competitiveness.

Suggested Citation

  • Sakila Akter JAHAN & Mesbaul Haque SAZU, 2022. "The Impact of Data Analytics on High Efficiency Supply Chain Management," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), vol. 3(7), pages 62-72, July.
    • Handle: RePEc:ahd:journl:v:3:y:2022:i:7:p:62-72
    DOI: 10.37945/cbr.2022.07.07
    as

    Download full text from publisher

    File URL: https://www.ceccarbusinessreview.ro/the-impact-of-data-analytics-on-high-efficiency-supply-chain-management-a238d/download-PDF/
    Download Restriction: no
    File URL: https://www.ceccarbusinessreview.ro/the-impact-of-data-analytics-on-high-efficiency-supply-chain-management-a238a/abstract/
    Download Restriction: no
    File URL: https://libkey.io/10.37945/cbr.2022.07.07?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
    ---><---

    References listed on IDEAS

    as
    1. Bresciani, Stefano & Ciampi, Francesco & Meli, Francesco & Ferraris, Alberto, 2021. "Using big data for co-innovation processes: Mapping the field of data-driven innovation, proposing theoretical developments and providing a research agenda," International Journal of Information Management, Elsevier, vol. 60(C).
    2. Ghasemaghaei, Maryam & Calic, Goran, 2020. "Assessing the impact of big data on firm innovation performance: Big data is not always better data," Journal of Business Research, Elsevier, vol. 108(C), pages 147-162.
    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. JAHAN Sakila Akter & SAZU Mesbaul Haque, 2022. "Innovation Management: Is Big Data Necessarily Better Data?," Management of Sustainable Development, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 14(2), pages 27-33, December.
    2. Hongyi Mao & Jiang Lu, 2023. "Big Data Management Capabilities and Green Innovation: A Dynamic Capabilities View," Sustainability, MDPI, vol. 15(19), pages 1-27, October.
    3. Li, Lixu & Ye, Fei & Zhan, Yuanzhu & Kumar, Ajay & Schiavone, Francesco & Li, Yina, 2022. "Unraveling the performance puzzle of digitalization: Evidence from manufacturing firms," Journal of Business Research, Elsevier, vol. 149(C), pages 54-64.
    4. Mariani, Marcello M. & Fosso Wamba, Samuel, 2020. "Exploring how consumer goods companies innovate in the digital age: The role of big data analytics companies," Journal of Business Research, Elsevier, vol. 121(C), pages 338-352.
    5. Long Xue & Qianyu Zhang & Xuemang Zhang & Chengyu Li, 2022. "Can Digital Transformation Promote Green Technology Innovation?," Sustainability, MDPI, vol. 14(12), pages 1-20, June.
    6. Linxuan Yu & Jing Xu & Xiang Yuan, 2024. "Sustainable Digital Shifts in Chinese Transport and Logistics: Exploring Green Innovations and Their ESG Implications," Sustainability, MDPI, vol. 16(5), pages 1-21, February.
    7. Pan, Qiaohong & Luo, Wenping & Fu, Yi, 2022. "A csQCA study of value creation in logistics collaboration by big data: A perspective from companies in China," Technology in Society, Elsevier, vol. 71(C).
    8. Rampersad, Giselle, 2020. "Robot will take your job: Innovation for an era of artificial intelligence," Journal of Business Research, Elsevier, vol. 116(C), pages 68-74.
    9. Behl, Abhishek & Gaur, Jighyasu & Pereira, Vijay & Yadav, Rambalak & Laker, Benjamin, 2022. "Role of big data analytics capabilities to improve sustainable competitive advantage of MSME service firms during COVID-19 – A multi-theoretical approach," Journal of Business Research, Elsevier, vol. 148(C), pages 378-389.
    10. Chengwei Ge & Wendong Lv & Junli Wang, 2023. "The Impact of Digital Technology Innovation Network Embedding on Firms’ Innovation Performance: The Role of Knowledge Acquisition and Digital Transformation," Sustainability, MDPI, vol. 15(8), pages 1-21, April.
    11. Li, Lei & Lin, Jiabao & Ouyang, Ye & Luo, Xin (Robert), 2022. "Evaluating the impact of big data analytics usage on the decision-making quality of organizations," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    12. Bargoni, Augusto & Santoro, Gabriele & Messeni Petruzzelli, Antonio & Ferraris, Alberto, 2024. "Growth hacking: A critical review to clarify its meaning and guide its practical application," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    13. Jiangying Wei & Xiuwu Zhang, 2023. "The Role of Big Data in Promoting Green Development: Based on the Quasi-Natural Experiment of the Big Data Experimental Zone," IJERPH, MDPI, vol. 20(5), pages 1-18, February.
    14. Singh, Anjali & Lim, Weng Marc & Jha, Sumi & Kumar, Satish & Ciasullo, Maria Vincenza, 2023. "The state of the art of strategic leadership," Journal of Business Research, Elsevier, vol. 158(C).
    15. Liu, Jingling & Chen, Yanying & Liang, Feng Helen, 2023. "The effects of digital economy on breakthrough innovations: Evidence from Chinese listed companies," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    16. Oesterreich, Thuy Duong & Anton, Eduard & Teuteberg, Frank & Dwivedi, Yogesh K, 2022. "The role of the social and technical factors in creating business value from big data analytics: A meta-analysis," Journal of Business Research, Elsevier, vol. 153(C), pages 128-149.
    17. Muhammad Adeel Munir & Amjad Hussain & Muhammad Farooq & Muhammad Salman Habib & Muhammad Faisal Shahzad, 2023. "Data-Driven Transformation: The Role of Ambidexterity and Analytics Capability in Building Dynamic and Sustainable Supply Chains," Sustainability, MDPI, vol. 15(14), pages 1-37, July.
    18. Sergi, Bruno S. & Ključnikov, Aleksandr & Popkova, Elena G. & Bogoviz, Aleksei V. & Lobova, Svetlana V., 2022. "Creative abilities and digital competencies to transitioning to Business 4.0," Journal of Business Research, Elsevier, vol. 153(C), pages 401-411.
    19. Hou, Tingting & Luo, Xin (Robert) & Ke, Dan & Cheng, Xusen, 2022. "Exploring different appraisals in deviant sharing behaviors: A mixed-methods study," Journal of Business Research, Elsevier, vol. 139(C), pages 496-509.
    20. Benny Lianto, 2023. "Identifying Key Assessment Factors for a Company’s Innovation Capability Based on Intellectual Capital: An Application of the Fuzzy Delphi Method," Sustainability, MDPI, vol. 15(7), pages 1-21, March.

    More about this item

    Keywords

    supply chain management; big data analytics;

    JEL classification:

    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics

    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:ahd:journl:v:3:y:2022:i:7:p:62-72. 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: Radu CIOBANU (email available below). General contact details of provider: .

    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.