Como avaliar o impacto do blockchain sobre segurança e privacidade de dados na cadeia de suprimentos digital? Uma revisão do estado da arte

Autores

DOI:

https://doi.org/10.47456/bjpe.v10i2.44284

Palavras-chave:

Segurança, Privacidade de Dados, Cadeia de Suprimento Digital, Indicadores, Medidas

Resumo

As organizações e Cadeias de Suprimentos Digitais (CSD) da Indústria 4.0 são desafiadas a manter a privacidade e a segurança de dados em seus sistemas devido a violações cibernéticas, falta de gerenciamento e confiança entre seus membros, entre outras questões. Neste cenário, o Blockchain (BCK) surgiu como uma alternativa para manter informações descentralizadas, seguras e confiáveis aos participantes. Para verificar a efetividade da adoção do BCK, são apontados os requisitos-chave que sintetizam os critérios que devem ser considerados para mensurar diferentes aspectos que impactam na segurança e na privacidade de dados em CSD. Na sequência, mediante uma revisão sistemática da literatura publicada nos últimos 10 anos, apoiada pela metodologia PRISMA e pela técnica de amostragem snowball sampling, foram identificados os principais fatores que devem ser avaliados, como constructos e medidas, os quais são agrupados em elementos que representam o que deve ser medido de alguma forma pelas CSD. Assim, uma revisão do estado da arte sobre o desempenho do BCK em CSD é realizada e as principais dificuldades de medição e oportunidades de melhorias são discutidas.

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Biografia do Autor

Eliane Somavilla, Universidade Federal de Santa Catarina (UFSC)

Possui graduação em Sistemas de Informação pela Universidade Comunitária da Região de Chapecó - Unochapecó (2009), com especialização em Engenharia de Projetos de Software pela Universidade do Sul de Santa Catarina - Unisul (2013). Atualmente, aluna do mestrado de Engenharia de Produção na UFSC em fase de dissertação. Possui experiência no gerenciamento de demandas, planejamento estratégico, medição de indicadores para apoiar a tomada de decisão, gestão de projetos e produtos através de metodologia ágil por meio do framework SCRUM aliado a conceitos LEAN, gestão de pessoas e gestão de prazos e custos.

Gisele de Lorena Diniz Chaves, Universidade Federal de Santa Catarina (UFSC)

Professora Associada do Departamento de Engenharia de Produção e Sistemas - DEPS da Universidade Federal de Santa Catarina - UFSC. Pesquisadora do CNPq nível 2 desde 2016. Realizou seu pós-doutorado no Department of Environment and Civil Engineering da University of Central Flórida com financiamento FULBRIGHT. Possui doutorado em Engenharia de Produção pela Universidade Federal de São Carlos, com estágio sanduíche (um ano) no CRET-LOG, Grupo de Pesquisa em Logística da Université de la Mediterranée (Aix-Marseille II) na França, ambos com apoio CAPES. Graduada em Engenharia de Alimentos pela Universidade Federal de Viçosa (2003) e mestrado em Desenvolvimento Regional e Agronegócio pela Universidade Estadual do Oeste do Paraná (2005). Membro permanente do corpo docente do curso de Pós-graduação em Engenharia de Produção da UFSC desde 2022. Membro permanente do corpo docente do Programa de Pós-Graduação em Engenharia Sanitária e Ambiental desde 2022. Membro permanente do corpo docente do curso de Pós-graduação em Energia da UFES de 2011 a 2022.Atuou como docente na UFES por mais de 12 anos. Atuo principalmente nos seguintes temas: logística reversa, transportes, logística e gerenciamento de resíduos sólidos. Citações no google acadêmico: 1648 Fator H = 16; e Fator Google i10 =31.

Referências

Aljabhan, B. & Obaidat, M. A. (2023). Privacy-Preserving BCK Framework for Supply Chain Management: Perceptive Craving Game Search. Sustainability. 1-23. https://doi.org/10.3390/su15086905 DOI: https://doi.org/10.3390/su15086905

Aslam, J., Saleem, A., & Kim, Y. B. (2023). BCK-enabled supply chain management: integrated impact on firm performance and robustness capabilities. Business Process Management Journal, 29(6), 1680-1705. https://doi.org/10.1108/BPMJ-03-2023-0165 DOI: https://doi.org/10.1108/BPMJ-03-2023-0165

Balfaqih, H., Nopiah, Z. M., Saibani, N., & Al-Nory, M.T. (2026). Review of supply chain performance measurement systems: 1998-2015. Computers In Industry, 82, 135-150. https://doi.org/10.1016/j.compind.2016.07.002 DOI: https://doi.org/10.1016/j.compind.2016.07.002

Bhattacharya, R. & Bandyopadhyay, S. (2011). A review of the causes of bullwhip effect in a supply chain. The International Journal of Advanced Manufacturing Technology, 54(9-12), 1245-1261. https://doi.org/10.1007/s00170-010-2987-6 DOI: https://doi.org/10.1007/s00170-010-2987-6

Bigini, G. Freschi V., & Lattanzi, E. (2020). A Review on BCK for the Internet of Medical Things: definitions, challenges, applications, and vision. Future Internet, 12(12), 1-16. https://doi.org/10.3390/fi12120208 DOI: https://doi.org/10.3390/fi12120208

Budak, A. & Çoban, V. (2021). Evaluation of the impact of BCK technology on supply chain using cognitive maps. Expert Systems with Applications, 184, 115455. https://doi.org/10.1016/j.eswa.2021.115455 DOI: https://doi.org/10.1016/j.eswa.2021.115455

Buntak, K., Kovačić, M., & Mutavdžija M. (2021). Measuring Digital Transformation Maturity of Supply Chain. Tehni?Ki Glasnik, 15(2), 199-204. https://doi.org/10.31803/tg-20200414191933 DOI: https://doi.org/10.31803/tg-20200414191933

Chopra, S. & Meindl, P. (2011). Supply Chain Management: strategy, planning and operation. New York: Pearson Prentice Hall. 529 p.

Çikmak, S., Kantoglu, B., & Kirbaç, G. (2023). Evaluation of the effects of BCK technology characteristics on SCOR model supply chain perfor. International Journal of Logistics Research And Applications, 1-31. https://doi.org/10.1080/13675567.2023.2193736 DOI: https://doi.org/10.1080/13675567.2023.2193736

Dolgui, A., Ivanov, D., & Sokolov, B. (2017). Ripple effect in the supply chain: an analysis and recent literature. International Journal of Production Research, 56(1-2), 414-430. https://doi.org/10.1080/00207543.2017.1387680 DOI: https://doi.org/10.1080/00207543.2017.1387680

Eur-Lex, Access to European Union Law. Constituição (2016). General Data Protection Regulation. Brussels, 27 abr. 2016. Recuperado de https://eur-lex.europa.eu/eli/reg/2016/679/oj

Fares, N. & Lloret, J. (2023) Barriers to supply chain performance measurement during disruptions such as the COVID-19 pandemic. International Journal of Quality e Reliability Management, 40(5), 1316-1342. https://doi.org/10.1108/IJQRM-03-2022-0095 DOI: https://doi.org/10.1108/IJQRM-03-2022-0095

Frederico, G. F., Garza-Reyes, J. A., Anosike,A., & Kumar V. (2019). Supply Chain 4.0: concepts, maturity and research agenda. Supply Chain Management, 25(2), 262-282. https://doi.org/10.1108/SCM-09-2018-0339 DOI: https://doi.org/10.1108/SCM-09-2018-0339

Gökalp, E., Gökalp, M. O., & Çoban S. (2020). BCK-Based Supply Chain Management: understanding the determinants of adoption in the context of organizations. Information Systems Management, 39(2), 100-121. https://doi.org/10.1080/10580530.2020.1812014 DOI: https://doi.org/10.1080/10580530.2020.1812014

Govindan, K., kannan, D., Jorgensen, T. B., & Nielse, T. S. (2022). Supply Chain 4.0 performance measurement: a systematic literature review, framework development, and empirical evidence. Transportation Research Part e: Logistics and Transportation Review, 164, 102725. https://doi.org/10.1016/j.tre.2022.102725 DOI: https://doi.org/10.1016/j.tre.2022.102725

Hani, J. B. (2022). The influence of supply chain management practices on supply chain performance: the moderating role of information quality. Business, Management and Economics Engineering, 20(1), 152-171. https://doi.org/10.3846/bmee.2022.16597 DOI: https://doi.org/10.3846/bmee.2022.16597

Harding, K. (2014). Zotero. Journal of The Canadian Health Libraries Association / Journal de L'Association Des Bibliothèques de, 34(1), 41. https://doi.org/10.5596/c13-003. DOI: https://doi.org/10.5596/c13-003

Hellweg, F., Lechtenberg, S., Hellingrath, B., & Thomé, A. M. T. (2021). Literature Review on Maturity Models for Digital Supply Chains. Brazilian Journal of Operations e Production Management, 18(3), 1-12. https://doi.org/10.14488/BJOPM.2021.022 DOI: https://doi.org/10.14488/BJOPM.2021.022

Hong, L. & Hales, D. N. (2021). BCK performance in supply chain management: application in BCK integration companies. Industrial Management e Data Systems, 121(9), 1969-1996. https://doi.org/10.1108/IMDS-10-2020-0598 DOI: https://doi.org/10.1108/IMDS-10-2020-0598

Johnson, M. & Stevens, G. C. (2016) Integrating the Supply Chain... 25 years on. International Journal of Physical Distribution e Logistics Management. Online, p. 19-42. https://doi.org/10.1108/IJPDLM-07-2015-0175 DOI: https://doi.org/10.1108/IJPDLM-07-2015-0175

Joshi, A., Kale, S., Chandel, S., & Pal, D. K. (2015). Likert Scale: explored and explained. British Journal Of Applied Science e Technology, 7(4), 396-403. https://doi.org/10.9734/BJAST/2015/14975 DOI: https://doi.org/10.9734/BJAST/2015/14975

Jum’a, L. (2023). The role of BCK-enabled supply chain applications in improving supply chain performance: the case of jordanian manufacturing sector. Management Research Review, 46(10), 1315-1333. https://doi.org/10.1108/MRR-04-2022-0298 DOI: https://doi.org/10.1108/MRR-04-2022-0298

Kakhki, M. D. & Gargeya, V. B. (2019) Information systems for supply chain management: a systematic literature analysis. International Journal Of Production Research, v. 57, n. 15-16, p. 5318-5339. https://doi.org/10.1080/00207543.2019.1570376 DOI: https://doi.org/10.1080/00207543.2019.1570376

Kamble, S. S. & Gunasekaran, A. (2019). Big data-driven supply chain performance measurement system: a review and framework for implementation. International Journal of Production Research, 58(1), 65-86. https://doi.org/10.1080/00207543.2019.1630770. DOI: https://doi.org/10.1080/00207543.2019.1630770

Kim, J. S. & Shin, N. (2019). The Impact of BCK Technology Application on Supply Chain Partnership and Performance. Sustainability, 11(21), 6181.

https://doi.org/10.3390/su11216181 DOI: https://doi.org/10.3390/su11216181

Kopyto, M., Lechler, S., Gracht, H. A. V. D., & Hartmann, E. (2020). Potentials of BCK technology in supply chain management: long-term judgments of an international expert panel. Technological Forecasting And Social Change, 161, 120330.

https://doi.org/10.1016/j.techfore.2020.120330 DOI: https://doi.org/10.1016/j.techfore.2020.120330

Li, Z. P., Ceong, H. T., & Lee, S. J. (2021). The Effect of BCK Operation Capabilities on Competitive Performance in Supply Chain Management. Sustainability, 13(21), 12078. https://doi.org/10.1080/00207543.2015.1026614 DOI: https://doi.org/10.3390/su132112078

Maestrini, V., Luzzini, D., Caniato, F., Maccarrone, P. e Ronchi, S. (2018). Measuring supply chain performance: a lifecycle framework and a case study. International Journal of Operations e Production Management, 38(4), 934-956. https://doi.org/10.1108/IJOPM-07-2015-0455 DOI: https://doi.org/10.1108/IJOPM-07-2015-0455

Mahdiraji, H. A., Yaftiyan, F., Kamardi, A. A. A., Garza-Reyes, J. A., & Hajiagha, S. H. R (2022). The role of Industry 4.0 technologies on performance measurement systems of supply chains during global pandemics: an interval-valued intuitionistic hesitant fuzzy approach. International Journal of Quality e Reliability Management, 40(5), 1147-1171. https://doi.org/10.1108/IJQRM-03-2022-0094 DOI: https://doi.org/10.1108/IJQRM-03-2022-0094

Mangla, S. K., Kusi-Sarpong, S., Luthra, S., Bai, C., Jakhar, S. K., & Khan, S. A. (2020). Operational excellence for improving sustainable supply chain performance. Resources, Conservation and Recycling, 162, 105025. https://doi.org/10.1016/j.resconrec.2020.105025 DOI: https://doi.org/10.1016/j.resconrec.2020.105025

Marinagi, C., Reklitis, P., Trivellas, P., & Sakas D. (2023). The Impact of Industry 4.0 Technologies on Key Performance Indicators for a Resilient Supply Chain 4.0. Sustainability, 15(6), 5185. https://doi.org/10.3390/su15065185 DOI: https://doi.org/10.3390/su15065185

Melnyk, S. A., Schoenherr,T., Speier-Pero,C., Peters, C., Chang, J. F., & Friday, D. (2021). New challenges in supply chain management: cybersecurity across the supply chain. International Journal of Production Research, 60(1), 162-183. https://doi.org/10.1080/00207543.2021.1984606 DOI: https://doi.org/10.1080/00207543.2021.1984606

Merrad, Y., Habaebi, M. H., Elsheikh, E. A. A., Suliman, F. E. M., Islam, M. R., Gunawan, T. S., & Mesri, M. (2022). BCK: consensus algorithm key performance indicators, trade-offs, current trends, common drawbacks, and no. Mathematics, 10(15), 2754. https://doi.org/10.3390/math10152754 DOI: https://doi.org/10.3390/math10152754

Moher, D., Liberati, A., Tetzlaff, J., & Altman,D. G. (2010). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. International Journal of Surgery, 8, 336-341. https://doi.org/10.1371/journal.pmed.1000097 DOI: https://doi.org/10.1016/j.ijsu.2010.02.007

Naderifar, M., Goli, H., & Ghaljaie, F. (2017). Snowball Sampling: A Purposeful Method of Sampling in Qualitative Research. The Strides in Development Of Medical Education Journal, 14, 1-4. https://doi.org/10.5812/sdme.67670 DOI: https://doi.org/10.5812/sdme.67670

Oláh, J., Krisán, E., Kiss, A., Lakner, Z., & Popp J. (2020). PRISMA Statement for Reporting Literature Searches in Systematic Reviews of the Bioethanol Sector. Energies, 13(9), 2323. https://doi.org/10.3390/en13092323 DOI: https://doi.org/10.3390/en13092323

Patidar, A., Sharma, M., Agrawal, R., & Sangwan, K.S. (2022). Supply chain resilience and its key performance indicators: an evaluation under industry 4.0 and sustainability perspective. Management of Environmental Quality: An International Journal, 34(4), 962-980. https://doi.org/10.1108/MEQ-03-2022-0091 DOI: https://doi.org/10.1108/MEQ-03-2022-0091

Piurcosky, F. P., Calegário, C., Costa, M., & Frogeri, R. F. (2019). A lei geral de proteção de dados pessoais em empresas brasileiras: uma análise de múltiplos casos. Suma de Negocios, 10(23), 89-99. http://dx.doi.org/10.14349/sumneg/2019.V10.N23.A2 DOI: https://doi.org/10.14349/sumneg/2019.V10.N23.A2

Prisma Statement. (2023). Home. Recuperado de: http://www.prisma-statement.org/

Queiroz, M. M., Pereira, S. C. F., Telles, R., & Machado, M. C. (2019). Industry 4.0 and digital supply chain capabilities. Benchmarking: An International Journal, 28(5), 1761-1782. https://doi.org/10.1108/BIJ-12-2018-0435 DOI: https://doi.org/10.1108/BIJ-12-2018-0435

Roever, L. (2020). Guia prático de revisão sistemática e metanálise. Rio de Janeiro: Thieme Revinter. 86 p.

Ronaghi, M. H. (2022). Contextualizing the impact of BCK technology on the performance of new firms: the role of corporate governance as an intermediate outcome. The Journal of High Technology Management Research, 33(2), 100438-100451. https://doi.org/10.1016/j.hitech.2022.100438 DOI: https://doi.org/10.1016/j.hitech.2022.100438

Sammarco, G., Ruzza, D., Vishkaei, B. M., & De Giovanni, P. (2022). The Impact of Digital Technologies on Company Restoration Time Following the COVID-19 Pandemic. Sustainability, 14(22), 15266. https://doi.org/10.3390/su142215266 DOI: https://doi.org/10.3390/su142215266

Silvestre, B. S., Monteiro, M. S., Viana, F. L. E., & Filho, J. M. de S. (2018). Challenges for sustainable supply chain management: when stakeholder collaboration becomes conducive to corruption. Journal of Cleaner Production, 194, 766-776. https://doi.org/10.1016/j.jclepro.2018.05.127 DOI: https://doi.org/10.1016/j.jclepro.2018.05.127

Supply Chain Council – SCC. (2023). Supply Chain Operations Reference Model SCOR, 12. United States of America.

Tambaré, P., Meshram, C., Lee, C. C., Ramteke, R. J., & Imoize, A. L. (2021). Performance Measurement System and Quality Management in Data-Driven Industry 4.0: a review. Sensors, 22(1), 224-249. https://doi.org/10.3390/s22010224 DOI: https://doi.org/10.3390/s22010224

Tokkozhina, U., Martins, A. L., & Ferreira, J. C. (2020). Use of BCK Technology to Manage the Supply Chains: Comparison of Perspectives between Technol. Journal of Theoretical and Applied Electronic Commerce Research. 1616-1632. https://doi.org/10.3390/jtaer17040082 DOI: https://doi.org/10.3390/jtaer17040082

Weerabahu, W. M. S., K. Samaranayake, P., Nakandala, D., & Hurriyet, H. (2022). Digital supply chain research trends: a systematic review and a maturity model for adoption. Benchmarking, 29, 3040-3066. https://doi.org/10.1108/BIJ-12-2021-0782 DOI: https://doi.org/10.1108/BIJ-12-2021-0782

Publicado

08.05.2024

Como Citar

Somavilla, E., & Chaves, G. de L. D. (2024). Como avaliar o impacto do blockchain sobre segurança e privacidade de dados na cadeia de suprimentos digital? Uma revisão do estado da arte. Brazilian Journal of Production Engineering, 10(2), 196–224. https://doi.org/10.47456/bjpe.v10i2.44284

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ENGENHARIA ORGANIZACIONAL

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