Skip to main content

Big Data Analysis in Supply Chain Management in Portuguese SMEs “Leader Excellence”

  • Conference paper
  • First Online:
New Knowledge in Information Systems and Technologies (WorldCIST'19 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 931))

Included in the following conference series:

Abstract

With the market becoming increasingly competitive, companies are looking for ways to differentiate themselves from competitors, thereby increasing the interest of organizations in analysing large data and their potential benefits to Supply Chain Management (SCM). The objective of this study is to understand the involvement of the Portuguese SMEs “Leader Excellence” with the Big Data theme and their analysis as a function of the SCM, as well as to understand if these companies are in the same line as the companies of worldwide reference, in what concerns to the topic in question. For this study, a survey was carried and applied to 80 SMEs distinguished as “SMEs Leader Excellence” certified by IAPMEI. With this random sample, from the analysis of the results, it was possible to verify that the Portuguese SMEs are not yet at the level of the big world companies with respect to the use of Big Data in the management of the supply chain. The analysis of the study results also concluded that the greatest benefit of the use of Big Data analysis it is in operations and customer service, that the SMEs recognize the benefits of the Big Data analysis and are aware of their importance in the SCM.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Quayle, M.: A study of supply chain management practice in UK industrial SMEs. Supply Chain. Manag.: Int. J. 8(1), 79–86 (2003)

    Article  Google Scholar 

  2. Waller, M.A., Fawcett, S.E.: Data science, predictive analytics, and big data: a revolution that will transform supply chain design and management. J. Bus. Logist. 34(2), 77–84 (2013)

    Article  Google Scholar 

  3. Cooper, M.C., Lambert, D.M., Pagh, J.D.: Supply chain management: more than a new name for logistics. Int. J. Logist. Manag. 8(1), 1–14 (1997)

    Article  Google Scholar 

  4. Stevens, G.C.: Integrating the supply chain. Int. J. Phys. Distrib. Mater. Manag. 19(8), 3–8 (1989)

    Google Scholar 

  5. Castro Melo, D., Alcântara, R.L.C.: A gestão da demanda em cadeias de suprimentos: uma abordagem além da previsão de vendas. Gestão & Produção 18(4), 809–824 (2012)

    Article  Google Scholar 

  6. Christopher, M.: Logistics & Supply Chain Management, 4ª edn. Pearson, UK (2011)

    Google Scholar 

  7. Kaminsky, P., Simchi-Levi, D., Simchi-Levi, E.: Designing and Managing the Supply Chain: Concepts, Strategies, and Case Studies, 3ª edn. McGraw-Hill, New York (2003)

    MATH  Google Scholar 

  8. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., Byers, A.: Big data: the next frontier for innovation, competition, and productivity (2011). https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/big-data-the-next-frontier-for-innovation

  9. Halaweh, M., Massry, A.E.: Conceptual model for successful implementation of big data in organizations. J. Int. Technol. Inf. Manag. 24(2), 2 (2015)

    Google Scholar 

  10. Loshin, D.: Big Data Analytics: From Strategic Planning To Enterprise Integration With Tools, Techniques, NoSQL, and Graph. Elsevier, ‎Amsterdam (2013)

    Chapter  MATH  Google Scholar 

  11. Turner, D., Schroeck, M., Shockley, R.: Analytics: the real-world use of big data in financial services. IBM Glob. Bus. Serv. 27, 1–12 (2013)

    Google Scholar 

  12. Porter, M.E., Heppelmann, J.E.: How smart, connected products are transforming competition. Harv. Bus. Rev. 92(11), 64–88 (2014)

    Google Scholar 

  13. Assunção, M.D., Calheiros, R.N., Bianchi, S., Netto, M.A., Buyya, R.: Big data computing and clouds: trends and future directions. J. Parallel Distrib. Comput. 79, 3–15 (2015)

    Article  Google Scholar 

  14. Bryson, S., Kenwright, D., Cox, M., Ellsworth, D., Haimes, R.: Visually exploring gigabyte data sets in real time. Commun. ACM 42(8), 82–90 (1999)

    Article  Google Scholar 

  15. Douglas, L.: 3D data management: controlling data volume, velocity and variety (2001). https://blogs.gartner.com/doug-laney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf

  16. Normandeau, K.: Beyond Volume, Variety and Velocity is the Issue of Big Data Veracity (2013). https://insidebigdata.com/2013/09/12/beyond-volume-variety-velocity-issue-big-data-veracity/

  17. Davenport, T.: Big Data at Work: Dispelling the Myths, Uncovering the Opportunities. Harvard Business Review Press, Boston (2014)

    Book  Google Scholar 

  18. Howie, T.: The Big Bang: How the Big Data Explosion Is Changing the World. Microsoft UK Enterprise Insights Blog (2013). http://blogs.msdn.com/b/microsoftenterpriseinsight/archive/2013/04/15/big-bang-how-the-big-data-explosion-is-changing-theworld.aspx

  19. Wu, X., Zhu, X., Wu, G.Q., Ding, W.: Data mining with big data. IEEE Trans. Knowl. Data Eng. 26(1), 97–107 (2014)

    Article  Google Scholar 

  20. DHL Trend Research: Logistics Trend Radar: Delivering Insight Today. Creating Value Tomorrow! (DHL Trend Research, Germany) (2016)

    Google Scholar 

  21. Ashton, K.: That ‘Internet of Things’ thing. In the real world, things matter more than ideas. RFID J. (2009). http://www.rfidjournal.com/articles/view?4986

  22. Chen, H., Chiang, R.H., Storey, V.C.: Business intelligence and analytics: from big data to big impact. MIS Q. 36(4), 1165–1188 (2012)

    Article  Google Scholar 

  23. KPMG Capital: Going Beyond the Data: achieving actionable insights with data and analytics (2014). https://assets.kpmg.com/content/dam/kpmg/pdf/2015/04/going-beyond-data-and-analytics-v4.pdf

  24. Rowe, S., Pournader, M.: Supply Chain Big Data Series Part 1 (2017). https://assets.kpmg.com/content/dam/kpmg/au/pdf/2017/big-data-analytics-supply-chain-performance.pdf

  25. Stamford, C.: Gartner Predicts Business Intelligence and Analytics Will Remain Top Focus for CIOs Through 2017 (2013). www.gartner.com/newsroom/id/2637615

  26. Jun, S.P., Park, D.H., Yeom, J.: The possibility of using search traffic information to explore consumer product attitudes and forecast consumer preference. Technol. Forecast. Soc. Change 86, 237–253 (2014)

    Article  Google Scholar 

  27. Sagaert, Y., Kourentzes, N., Aghezzaf, E. H., Desmet, B.: Sales forecasting with temporal big data: avoiding information overload for supply chain management. In: Informs International, Technology and Engineering conference, Hawaii, United States of America, 12–15 May (2016)

    Google Scholar 

  28. Instituto Nacional de Estatística: Empresas de Portugal 2016 (2018). https://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_publicacoes&PUBLICACOESpub_boui=318224733&PUBLICACOESmodo=2

  29. IAPMEI: PME Líder e PME Excelência 2017 (2018).https://www.iapmei.pt/PRODUTOS-E-SERVICOS/Qualificacao-Certificacao/PME-Lider.aspx

  30. Hill, M., Hill, A.: Investigação por questionário. Edições Sílabo, Lisboa (2005)

    Google Scholar 

  31. Thong, J.Y.: Resource constraints and information systems implementation in Singaporean small businesses. Omega 29(2), 143–156 (2001)

    Article  Google Scholar 

  32. Swaminathan, S.: The Effects of Big Data on the Logistics (2012). http://www.oracle.com/us/corporate/profit/archives/opinion/021512-sswaminathan-1523937.html

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to José Luís Reis .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Azevedo, F., Reis, J.L. (2019). Big Data Analysis in Supply Chain Management in Portuguese SMEs “Leader Excellence”. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S. (eds) New Knowledge in Information Systems and Technologies. WorldCIST'19 2019. Advances in Intelligent Systems and Computing, vol 931. Springer, Cham. https://doi.org/10.1007/978-3-030-16184-2_59

Download citation

Publish with us

Policies and ethics