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.
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References
Quayle, M.: A study of supply chain management practice in UK industrial SMEs. Supply Chain. Manag.: Int. J. 8(1), 79–86 (2003)
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)
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)
Stevens, G.C.: Integrating the supply chain. Int. J. Phys. Distrib. Mater. Manag. 19(8), 3–8 (1989)
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)
Christopher, M.: Logistics & Supply Chain Management, 4ª edn. Pearson, UK (2011)
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)
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
Halaweh, M., Massry, A.E.: Conceptual model for successful implementation of big data in organizations. J. Int. Technol. Inf. Manag. 24(2), 2 (2015)
Loshin, D.: Big Data Analytics: From Strategic Planning To Enterprise Integration With Tools, Techniques, NoSQL, and Graph. Elsevier, Amsterdam (2013)
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)
Porter, M.E., Heppelmann, J.E.: How smart, connected products are transforming competition. Harv. Bus. Rev. 92(11), 64–88 (2014)
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)
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)
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
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/
Davenport, T.: Big Data at Work: Dispelling the Myths, Uncovering the Opportunities. Harvard Business Review Press, Boston (2014)
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
Wu, X., Zhu, X., Wu, G.Q., Ding, W.: Data mining with big data. IEEE Trans. Knowl. Data Eng. 26(1), 97–107 (2014)
DHL Trend Research: Logistics Trend Radar: Delivering Insight Today. Creating Value Tomorrow! (DHL Trend Research, Germany) (2016)
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
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)
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
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
Stamford, C.: Gartner Predicts Business Intelligence and Analytics Will Remain Top Focus for CIOs Through 2017 (2013). www.gartner.com/newsroom/id/2637615
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)
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)
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
IAPMEI: PME Líder e PME Excelência 2017 (2018).https://www.iapmei.pt/PRODUTOS-E-SERVICOS/Qualificacao-Certificacao/PME-Lider.aspx
Hill, M., Hill, A.: Investigação por questionário. Edições Sílabo, Lisboa (2005)
Thong, J.Y.: Resource constraints and information systems implementation in Singaporean small businesses. Omega 29(2), 143–156 (2001)
Swaminathan, S.: The Effects of Big Data on the Logistics (2012). http://www.oracle.com/us/corporate/profit/archives/opinion/021512-sswaminathan-1523937.html
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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
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