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The Impact of Big Data Analytics on Company Performance in Supply Chain Management

Author

Listed:
  • Ionica Oncioiu

    (Faculty of Finance-Banking, Accounting and Business Administration, Titu Maiorescu University, 040051 Bucharest, Romania)

  • Ovidiu Constantin Bunget

    (Faculty of Economics and Business Administration, West University of Timisoara, 300223 Timisoara, Romania)

  • Mirela Cătălina Türkeș

    (Faculty of Finance, Banking and Accountancy, Dimitrie Cantemir Christian University, 040051 Bucharest, Romania)

  • Sorinel Căpușneanu

    (Faculty of Finance-Banking, Accounting and Business Administration, Titu Maiorescu University, 040051 Bucharest, Romania)

  • Dan Ioan Topor

    (Faculty of Economic Sciences, 1 Decembrie 1918 University, 510009 Alba-Iulia, Romania)

  • Attila Szora Tamaș

    (Faculty of Economic Sciences, 1 Decembrie 1918 University, 510009 Alba-Iulia, Romania)

  • Ileana-Sorina Rakoș

    (Faculty of Sciences, University of Petrosani, 20 Universitatii, 332006 Petrosani, Romania)

  • Mihaela Ștefan Hint

    (Faculty of Economic Sciences, 1 Decembrie 1918 University, 510009 Alba-Iulia, Romania)

Abstract

Big data analytics can add value and provide a new perspective by improving predictive analysis and modeling practices. This research is centered on supply-chain management and how big data analytics can help Romanian supply-chain companies assess their experience, strategies, and professional capabilities in successfully implementing big data analytics, as well as assessing the tools needed to achieve these goals, including the results of implementation and performance achievement based on them. The research method used in the quantitative study was a sampling survey, using a questionnaire as a data collection tool. It included closed questions, measured with nominal and ordinal scales. A total of 205 managers provided complete and useful answers for this research. The collected data were analyzed with the Statistical Package for the Social Sciences (SPSS) package using frequency tables, contingency tables, and main component analysis. The major contributions of this research highlight the fact that companies are concerned with identifying new statistical methods, tools, and approaches, such as cloud computing and security technologies, that need to be rigorously explored.

Suggested Citation

  • Ionica Oncioiu & Ovidiu Constantin Bunget & Mirela Cătălina Türkeș & Sorinel Căpușneanu & Dan Ioan Topor & Attila Szora Tamaș & Ileana-Sorina Rakoș & Mihaela Ștefan Hint, 2019. "The Impact of Big Data Analytics on Company Performance in Supply Chain Management," Sustainability, MDPI, vol. 11(18), pages 1-22, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:18:p:4864-:d:264609
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    References listed on IDEAS

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    Cited by:

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    2. Yuwei Yan & Xiaomeng Ma & Yi Song & Ajay Kumar & Ruixian Yang, 2023. "Exploring the interaction and choice behavior of organization and individuals in the crowd logistics," Annals of Operations Research, Springer, vol. 320(2), pages 1021-1040, January.
    3. Manish Shashi, 2023. "Sustainable Digitalization in Pharmaceutical Supply Chains Using Theory of Constraints: A Qualitative Study," Sustainability, MDPI, vol. 15(11), pages 1-18, May.
    4. Camelia Oprean-Stan & Ionica Oncioiu & Iulia Cristina Iuga & Sebastian Stan, 2020. "Impact of Sustainability Reporting and Inadequate Management of ESG Factors on Corporate Performance and Sustainable Growth," Sustainability, MDPI, vol. 12(20), pages 1-31, October.
    5. Govindan, Kannan & Kannan, Devika & Jørgensen, Thomas Ballegård & Nielsen, Tim Straarup, 2022. "Supply Chain 4.0 performance measurement: A systematic literature review, framework development, and empirical evidence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    6. Hafiz Wasim Akram & Samreen Akhtar & Alam Ahmad & Imran Anwar & Mohammad Ali Bait Ali Sulaiman, 2023. "Developing a Conceptual Framework Model for Effective Perishable Food Cold-Supply-Chain Management Based on Structured Literature Review," Sustainability, MDPI, vol. 15(6), pages 1-28, March.

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