Gestão & Produção
https://gestaoeproducao.com/article/doi/10.1590/0104-530x5468-20
Gestão & Produção
SEÇÃO TEMÁTICA

An exploratory study on emerging technologies applied to logistics 4.0

Jobel Santos Corrêa; Mauro Sampaio; Rodrigo de Castro Barros

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Abstract

Abstract The concept of Logistics 4.0 works closely to that of Industry 4.0. While Industry 4.0 proposes a disruptive change in manufacturing, Logistics 4.0 advocates a transformation in the way organizations buy, manufacture, sell, and deliver products. The objective of this paper is to identify, in Brazilian companies, the degree of interest in the investment in six emerging technologies applicable to logistics, according to scientific literature, as well as to identify the current perception of data quality of these companies. To achieve these objectives, an online survey was conducted. The research showed that the technologies that most interest Brazilian companies are Internet of Things (IoT) and cloud computing, both with 82% of investment intention. The two technologies that least interested companies are crowdsourcing and 3D printing, both with 68% investment disinterest among respondents.

Keywords

Logistics 4.0, Industry 4.0, Investment, Emerging technologies

Referências

Bhoir H., Principal R. P. Cloud computing for supply chain management. International Journal of Innovations in Engineering Research and Technology. 2014;1(2):1-9.

Bocek T., Rodrigues B., Strasser T., Stiller B. Blockchains everywhere: a use-case of blockchains in the pharma supply-chain. 2017.

Carbone V., Rouquet A., Roussat C. The rise of crowd logistics: a new way to co‐create logistics value. Journal of Business Logistics. 2017;38(4):238-52.

Carbone V., Rouquet A., Roussat C. A typology of logistics at work in collaborative consumption. International Journal of Physical Distribution & Logistics Management. 2018;48(6):570-85.

Castillo V. E., Bell J. E., Rose W. J., Rodrigues A. M. Crowdsourcing last mile delivery: strategic implications and future research directions. Journal of Business Logistics. 2018;39(1):7-25.

Christidis K., Devetsikiotis M. Blockchains and smart contracts for the internet of things. IEEE Access: Practical Innovations, Open Solutions. 2016;4:2292-303.

CSCMP supply chain management definitions and glossary. 2017.

Dai H., Ge L., Zhou W. A design method for supply chain traceability systems with aligned interests. International Journal of Production Economics. 2015;170:14-24.

Dong Y., Carter C. R., Dresner M. E. JIT purchasing and performance: an exploratory analysis of buyer and supplier perspectives. Journal of Operations Management. 2001;19(4):471-83.

Drees J. Logistics 4.0: tailored solutions for the future. 2016.

Durach C. F., Kurpjuweit S., Wagner S. M. The impact of additive manufacturing on supply chains. International Journal of Physical Distribution & Logistics Management. 2017;47(10):954-71.

Goldsby T. J., Zinn W. Technology Innovation and New Business Models: can logistics and supply chain research accelerate the evolution?. Journal of Business Logistics. 2016;37(2):80-1.

Gubbi J., Buyya R., Marusic S., Palaniswami M. Internet of Things (IoT): a vision, architectural elements, and future directions. Future Generation Computer Systems. 2013;29(7):1645-60.

Hofmann E. Big data and supply chain decisions: the impact of volume, variety and velocity properties on the bullwhip effect. International Journal of Production Research. 2017;55(17):5108-26.

Hofmann E., Rüsch M. Industry 4.0 and the current status as well as future prospects on logistics. Computers in Industry. 2017;89:23-34.

Howe J. The rise of crowdsourcing. Wired Magazine.. 2006;14(6):1-5.

Contas nacionais trimestrais. 2018.

Kim S., Kim S. A multi-criteria approach toward discovering killer IoT application in Korea. Technological Forecasting and Social Change. 2016;102:143-55.

Kshetri N. 1 Blockchain’s roles in meeting key supply chain management objectives. International Journal of Information Management. 2018;39:80-9.

Kubáč L., Kodym O. The impact of 3D printing technology on supply chain. MATEC Web of Conferences. 2017;134:27-37.

Lambert D. M. The development of an inventory costing methodology: a study of the costs associated with holding enventory. 1975.

Lindner M., Galán F., Chapman C., Clayman S., Henriksson D., Elmroth E. The Cloud Supply Chain: a framework for information, monitoring, accounting and billing.. 2010.

Lu Y., Papagiannidis S., Alamanos E. Internet of things: a systematic review of the business literature from the user and organisational perspectives. Technological Rorecasting and Social Change.. 2018;136:285-97.

Parasuranan A., Grewal D., Krishnan R. Marketing research. 2006.

Pfohl H., Yahsi B., Kurnaz T. The impact of Industry 4.0 on the Supply Chain. 2015:32-58.

Richey Jr. R. G., Morgan T. R., Lindsey-Hall K., Adams F. G. A global exploration of Big Data in the supply chain. International Journal of Physical Distribution & Logistics Management. 2016;46(8):710-39.

Rogers H., Baricz N., Pawar K. S. 3D printing services: classification, supply chain implications and research agenda. International Journal of Physical Distribution & Logistics Management. 2016;46(10):886-907.

Rogers Z., Gooley T., Harrington L., Rogers D., Sharpe R., Kitajima T. Big data analytics in supply chain: tackling the tidal wave. 2017:1-6.

Rossmann B., Canzaniello A., Von der Gracht H., Hartmann E. The future and social impact of Big Data Analytics in Supply Chain Management: results from a Delphi study. Technological Forecasting and Social Change. 2018;130:135-49.

Sasson A., Johnson J. C. The 3D printing order: variability, supercenters and supply chain reconfigurations. International Journal of Physical Distribution & Logistics Management. 2016;46(1):82-94.

Strandhagen J. O., Vallandingham L. R., Fragapane G., Strandhagen J. W., Stangeland A. B. H., Sharma N. Logistics 4.0 and emerging sustainable business models. Advances in Manufacturing.. 2017;5(4):359-69.

Tiwari S., Wee H. M., Daryanto Y. Big Data Analytics in Supply Chain Management Between 2010 and 2016: insights to Industries. Computers & Industrial Engineering. 2018;115:319-30.

Tu M. An exploratory study of Internet of Things (IoT) adoption intention in logistics and supply chain management: a mixed research approach. International Journal of Logistics Management. 2018;29(1):131-51.

Varela Rozados I., Tjahjono B. Big data analytics in supply chain management: trends and related research. 2014.

Vazquez-Martinez G. A., Gonzalez-Compean J. L., Sosa-Sosa V. J., Morales-Sandoval M., Perez J. C. CloudChain: a novel distribution model for digital products based on supply chain principles. International Journal of Information Management. 2018;39:90-103.

Vilela L. O. Aplicação do ProKnow-C para seleção de um portifólio bibliográfico e análise bibliométrica sobre avaliação de desempenho da gestão do conhecimento. Revista Gestão Industrial.. 2012;8(1):76-92.

Waller M. A., Fawcett S. E. Data scientist: big data, predictive analytics, and theory development in the era of a maker movement supply chain. Journal of Business Logistics. 2013;34(4):249-52.

Waller M. A., Fawcett S. E. Print a maker movement supply chain: how invention and entrepreneurship will disrupt supply chain design. Journal of Business Logistics. 2014;35(2):99.

Wang K. Logistics 4.0 solution: new challenges and opportunities. 2016.

Zhong R. Y., Newman S. T., Huang G. Q., Lan S. Big data for supply chain management in the service and manufacturing sectors: challenges, opportunities, and future perspectives. Computers & Industrial Engineering. 2016;101:572-91.

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