Agile supply chain analytic approach: a case study combining agile and CRISP-DM in an end-to-end supply chain

References

• Ageron, B., O. Bentahar, and A. Gunasekaran. 2020. “Digital Supply Chain: Challenges and Future Directions.” Supply Chain Forum 21 (3): 133–138. doi:10.1080/16258312.2020.1816361.
   Google Scholar
• Ahangama, S., and D. Poo. 2015. “Improving Health Analytic Process through Project, Communication, and Knowledge Management.” The International Conference on Information Systems (ICIS), Fort Worth, Texas, USA.
   Google Scholar
• Akter, S., S. F. Wamba, A. Gunasekaran, R. Dubey, and S. J. Childe. 2016. “How to Improve Firm Performance Using Big Data Analytics Capability and Business Strategy Alignment?” International Journal of Production Economics 182: 113–131. doi:10.1016/j.ijpe.2016.08.018.
   Web of Science ®Google Scholar
• Arnould, M., L. Morel, and M. Fournier. 2021. “Developing the Persona Method to Increase the Commitment of Non-Industrial Private Forest Owners in French Forest Policy Priorities.” Forest Policy and Economics 126 (May 2021): 102425. doi:10.1016/j.forpol.2021.102425.
   Google Scholar
• Arunachalam, D., N. Kumar, and J. P. Kawalek. 2018. “Understanding Big Data Analytics Capabilities in Supply Chain Management: Unravelling the Issues, Challenges and Implications for Practice.” Transportation Research Part E: Logistics and Transportation Review 114: 416–436. doi:10.1016/j.tre.2017.04.001.
   Web of Science ®Google Scholar
• Ayerbe, C., and A. Missonier. 2007. “Validité interne et validité externe de l’étude de cas: Principes et mise en œuvre pour un renforcement mutuel.” Revue Finance Contrôle Stratégie 10: 37–62.
   Google Scholar
• Baijens, J., R. Helms, and R. Kusters. 2020. “Data Analytics Project Methodologies: Which One to Choose?” Proceedings of the 2020 International Conference on Big Data in Management, Manchester, United Kingdom, 41–44.
   Google Scholar
• Baramichai, M., E. W. Zimmers, and C. Marangos. 2006. “Agile Supply Chain Transformation Matrix: A QFD-based Tool for Improving Enterprise Agility.” International Journal of Value Chain Management 1 (3): 281–303. doi:10.1504/IJVCM.2007.013305.
   Google Scholar
• Barriocanal, E. G., S. Sánchez-alonso, M.-A. Sicilia, and -J.-J. Cuadrado. 2018. “Agile Methods as Problem-based Learning Designs: Setting and Assessment.” Proceedings of the 6th International Conference on Technological Ecosystems for Enhancing Multiculturality, Salamanca, Spain. doi:10.1145/3284179.32842371.
   Google Scholar
• Bentahar, O., S. Benzidia, and R. Fabbri. 2016. “Traceability Project of a Blood Supply Chain.” Supply Chain Forum 17 (1): 15–25. doi:10.1080/16258312.2016.1177916.
   Google Scholar
• Braganza, A., L. Brooks, D. Nepelski, M. Ali, and R. Moro. 2017. “Resource Management in Big Data Initiatives: Processes and Dynamic Capabilities.” Journal of Business Researc 70: 328–337. doi:10.1016/j.jbusres.2016.08.006.
   Web of Science ®Google Scholar
• Brangier, E., C. Bornet, J. M. C. Bastien, G. Michel, and R. Vivian. 2011. “Effets des personas et contraintes fonctionnelles sur l’idéation dans la conception d’une bibliothèque numérique.” Le Travail Humain 75 (2): 121–145. doi:10.3917/th.752.0121.
   Google Scholar
• Brintrup, A., J. Pak, D. Ratiney, T. Pearce, P. Wichmann, P. Woodall, and D. Duncan Mcfarlane. 2020. “Supply Chain Data Analytics for Predicting Supplier Disruptions: A Case Study in Complex Asset Manufacturing.” International Journal of Production Research 58 (11): 3330–3341. doi:10.1080/00207543.2019.1685705.
   Web of Science ®Google Scholar
• Cagliano, A. C., G. Mangano, and C. Rafele. 2021. “Determinants of Digital Technology Adoption in Supply Chain. An Exploratory Analysis.” Supply Chain Forum 22 (2): 100–114. doi:10.1080/16258312.2021.1875789.
   Google Scholar
• Cao, L., K. Mohan, P. Xu, and B. Ramesh. 2009. “A Framework for Adapting Agile Development Methodologies.” European Journal of Information Systems 18 (4): 332–343. doi:10.1057/ejis.2009.26.
   Web of Science ®Google Scholar
• Chakroun, A., A. El Bouchti, and H. Abbar. 2019. “Logistics and Supply Chain Analytics: Benefits and Challenges.” Second World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4), London, United Kingdom. doi:10.1109/WorldS4.2018.8611623.
   Google Scholar
• Chaouch, S., A. Mejri, and S. A. Ghannouchi. 2019. “A Framework for Risk Management in Scrum Development Process.” Procedia Computer Science 164: 187–192. doi:10.1016/j.procs.2019.12.171.
   Google Scholar
• Chen, H., R. H. L. Chiang, and V. C. Storey. 2018. “Business Intelligence and Analytics: From Big Data to Big Impact.” MIS Quarterly 36 (4): 1165–1188. doi:10.2307/41703503.
   Google Scholar
• Ćirić, D., and D. Gračanin. 2017. “Agile Project Management beyond Software Industry.” In Proceedings of the XV International Scientific Conference on Industrial Systems, Novi Sad, Serbia, 332–337.
   Google Scholar
• Cohen, D., M. Lindvall, and P. Costa. 2004. “An Introduction to Agile Methods.” Advances in Computers 62 (C): 1–66.
   Google Scholar
• Cooper, A. 1999. “The Inmates are Running the Asylum: Why High-Tech Products Drive Us Crazy and How to Restore the Sanity”. New York: Macmillan.
   Google Scholar
• De Boer, E., Fritzen, S., Khanam, R., Lefort, F. 2020. “Preparing for the next normal via digital manufacturing’s scaling potential.” McKinsey Glob. https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/the-covid-19-recovery-will-be-digital-a-plan-for-the-first-90-days
   Google Scholar
• Drucker-Godard, C., S. Ehlinger, and C. Grenier. 1999. “Validité et fiabilité de la recherche.” book: Méthodes de recherche en management, Dunod, chap 10: 257–287.
   Google Scholar
• Ebneyamini, S., and M. R. Sadeghi Moghadam. 2018. “Toward Developing a Framework for Conducting Case Study Research.” The International Journal of Qualitative Methods 17 (1): 1–11. doi:10.1177/1609406918817954.
   Web of Science ®Google Scholar
• Espinoza, J., and F. Armour. 2016. “The Big Data Analytics Gold Rush: A Research Framework for Coordination and Governance.” In Proceedings of Hawaii International Conference on System Sciences, Koloa, Hawaii, United States, 1112–1121. doi: 10.1109/HICSS.2016.141.
   Google Scholar
• Fernandez, D. J., and J. D. Fernandez. 2008. “Agile Project Management-Agilism versus Traditional Approaches.” Journal of Computer Information Systems 49 (2): 10–17.
   Web of Science ®Google Scholar
• Grady, N., M. Underwood, A. Roy, and W. Chang. 2014. “Big Data: Challenges, Practices and Technologies: NIST Big Data Public Working Group Workshop.” In IEEE International Conference on Big Data, Washington, United States.
   Google Scholar
• Grover, V., R. H. L. Chiang, T. P. Liang, and D. Zhang. 2018. “Creating Strategic Business Value from Big Data Analytics: A Research Framework.” Journal of Management Information Systems 35 (2): 388–423. doi:10.1080/07421222.2018.1451951.
   Web of Science ®Google Scholar
• Gunasekaran, A., T. Papadopoulos, R. Dubey, S. F. Wamba, S. J. Childe, B. Hazen, and A. Shahriar. 2017. “Big Data and Predictive Analytics for Supply Chain and Organizational Performance.” Journal of Business Research 70: 308–317. doi:10.1016/j.jbusres.2016.08.004.
   Web of Science ®Google Scholar
• Hammad, M., and I. Inayat. 2019. “Integrating Risk Management in Scrum Framework.” Conference: Frontiers of Information Technology At: Islamabad Pakistan, pp. 158–163.
   Google Scholar
• Hidalgo, E. S. 2019. “Adapting the Scrum Framework for Agile Project Management in Science: Case Study of a Distributed Research Initiative.” Heliyon 5 (3): e01447. doi:10.1016/j.heliyon.2019.e01447.
   PubMed Web of Science ®Google Scholar
• Huber, S., H. Wiemer, D. Schneider, and S. Ihlenfeldt. 2019. “DMME: Data Mining Methodology for Engineering Applications - A Holistic Extension to the CRISP-DM Model.” Procedia CIRP 79: 403–408. doi:10.1016/j.procir.2019.02.106.
   Google Scholar
• Ismail, H. S., and H. Sharifi. 2006. “A Balanced Approach to Building Agile Supply Chains.” International Journal of Physical Distribution and Logistics Management 36 (6): 431–444. doi:10.1108/09600030610677384.
   Google Scholar
• Jagadish, H., J. Gehrke, A. Labrinidis, Y. Papakonstantinou, J. Patel, R. Ramakrishnan, and C. Shahabi. 2014. “Big Data and Its Technical Challenges.” Communications of the ACM 57 (7): 86–94. doi:10.1145/2611567.
   Web of Science ®Google Scholar
• Jensen, M. H., P. A. Nielsen, and J. S. Persson. 2020. “Managing Big Data Analytics Projects: The Challenges of Realizing Value.” Conference: 27th European Conference on Information Systems (ECIS), Stockholm, Sweden.
   Google Scholar
• Kaisler, S., F. Armour, J. A. Espinosa, and W. Money. 2013. “Big Data: Issues and Challenges Moving Forward.” Proceedings of the Hawaii International Conference on System Sciences, Wailea, Hawaii, United States, 995–1004.
   Google Scholar
• Karlesky, M., and M. Vander Voord. 2008. “Agile Project Management (Or, Burning Your Gantt Charts).” Embedded Systems Conference Boston ESC 247-267, Boston, Massachusetts, 1–16.
   Google Scholar
• Kusters, R. J., Y. Van de Leur, W. G. Rutten, and J. J. Trienekens. 2017. “When Agile Meets Waterfall-investigating Risks and Problems on the Interface between Agile and Traditional Software Development in a Hybrid Development Organisation.” In International Conference on Enterprise Information Systems, Porto, Portugal, 2: 271–278.
   Google Scholar
• Lemieux, N. 2013. “Création et adoption de pratiques pour la conduite du changement: Une démarche évolutive au sein d’une entreprise québecoise.” Question (S) de Management 2 (2): 67–79. doi:10.3917/qdm.132.0067.
   Google Scholar
• Leveling, J., M. Edelbrock, and B. Otto. 2014. “Big Data Analytics for Supply Chain Management.” IEEE International Conference on Industrial Engineering and Engineering Management, Selangor Darul Ehsan, Malaysia, 918–922.
   Google Scholar
• Lin, C. T., H. Chiu, and P. Y. Chu. 2006. “Agility Index in the Supply Chain.” International Journal of Production Economics 100 (2): 285–299. doi:10.1016/j.ijpe.2004.11.013.
   Web of Science ®Google Scholar
• Makris, D., Z. N. L. Hansen, and O. Khan. 2019. “Adapting to Supply Chain 4.0: An Explorative Study of Multinational Companies.” Supply Chain Forum 20 (2): 116–131. doi:10.1080/16258312.2019.1577114.
   Web of Science ®Google Scholar
• Marchand, D., and J. Peppard. 2013. “Why IT Fumbles Analytics.” Harvard Business Review, 91: 104–113.
   Web of Science ®Google Scholar
• Marshall, R., S. Cook, V. Mitchell, S. Summerskill, V. Haines, M. Maguire, R. Sims, D. Gyi, and K. Case. 2015. “Design and Evaluation: End Users, User Datasets and Personas.” Applied Ergonomics 46: 311–317. doi:10.1016/j.apergo.2013.03.008.
   PubMed Web of Science ®Google Scholar
• Martinez, I., E. Viles, and I. G. Olaizola. 2021. “Data Science Methodologies: Current Challenges and Future Approaches.” Big Data Research 24: 100183. doi:10.1016/j.bdr.2020.100183.
   Web of Science ®Google Scholar
• Mikalef, P., M. Boura, G. Lekakos, and J. Krogstie. 2019. “Big Data Analytics and Firm Performance: Findings from a Mixed-method Approach.” Journal of Business Research 98: 261–276. doi:10.1016/j.jbusres.2019.01.044.
   Web of Science ®Google Scholar
• Mishra, R., and R. Sharma. 2015. “Big Data: Opportunities and Challenges.” International Journal of Computer Science and Mobile Computing 46 (6): 27–35.
   Google Scholar
• Modgil, S., S. Gupta, R. Stekelorum, and I. Laguir. 2021. “AI Technologies and Their Impact on Supply Chain Resilience during −19.” International Journal of Physical Distribution and Logistics Management. doi:10.1108/IJPDLM-12-2020-0434.
   Web of Science ®Google Scholar
• Moran, A. 2015. Agile Project Management. Cham: Managing Agile, Springer. doi:10.1007/978-3-319-16262-1_4.
   Google Scholar
• Mousannif, H., H. Sabah, Y. Douiji, and Y. O. Sayad. 2014. “From Big Data to Big Projects: A Step-by-Step Roadmap.” International Conference on Future Internet of Things and Cloud, Barcelona, Spain, 373–378.
   Google Scholar
• Nielsen, L. 2004. “Personas – Communication or Process?” Proceedings of the Seventh Danish HCI Research Symposium, København, Denmark, 25–26.
   Google Scholar
• Oliveira-Dias, D., J. M. Maqueira-Marín, and J. Moyano-Fuentes. 2022. “The Link between Information and Digital Technologies of Industry 4.0 And Agile Supply Chain: Mapping Current Research and Establishing New Research Avenues.” Computers and Industrial Engineering 167: 108000. doi:10.1016/j.cie.2022.108000.
   Web of Science ®Google Scholar
• Oncioiu, I., O. C. Bunget, D. I. Topor, and A. S. Tamas. 2019. “The Impact of Big Data Analytics on Company Performance in Supply Chain Management.” Sustainability 11 (18): 4864. doi:10.3390/su11184864.
   Web of Science ®Google Scholar
• Peng, R. D., and E. Matsui. 2016. “The Art of Data Science: A Guide for Anyone Who Works with Data”, LuLu.com. 1365061469, 9781365061462.
   Google Scholar
• Pouly, M., S. Naciri, and S. Berthold. 2009. “Collaborative Manufacturing Management in Networked Supply Chains.” Leveraging Knowledge for Innovation in Collaborative Networks. PRO-VE 2009. IFIP Advances in Information and Communication Technology 307: 36–145. doi:10.1007/978-3-642-04568-4_15.
   Google Scholar
• Prenner, N., C. Unger‐Windeler, and K. Schneider. 2021. “Goals and Challenges in Hybrid Software Development Approaches.” Journal of Software: Evolution and Process 33 (11): e2382.
   Web of Science ®Google Scholar
• Raman, S., N. Patwa, I. Niranjan, U. Ranjan, K. Moorthy, and A. Mehta. 2018. “Impact of Big Data on Supply Chain Management.” International Journal of Logistics 21 (6): 579–596. doi:10.1080/13675567.2018.1459523.
   Web of Science ®Google Scholar
• Raut, R. D., S. K. Mangla, V. S. Narwane, M. Dora, and M. Liu. 2021. “Big Data Analytics as a Mediator in Lean, Agile, Resilient, and Green Practices Effects on Sustainable Supply Chains.” Transportation Research Part E: Logistics and Transportation Review 145: 102170. doi:10.1016/j.tre.2020.102170.
   Web of Science ®Google Scholar
• Rossi, R., and K. Hirama. 2015. “Characterizing Big Data Management.” Issues in Informing Science and Information Technology 12: 165–180. doi:10.28945/2204.
   Google Scholar
• Roßmann, B., A. Canzaniello, H. Von Der Gracht, and E. Hartmann. 2018. “The Future and Social Impact of Big Data Analytics in Supply Chain Management: Results from a Delphi Study.” Technological Forecasting and Social Change 130: 135–149. doi:10.1016/j.techfore.2017.10.005.
   Web of Science ®Google Scholar
• Saltz, J. S. 2015. “The Need for New Processes, Methodologies and Tools to Support Big Data Teams and Improve Big Data Project Effectiveness.” IEEE International Conference on Big Data, Santa Clara, United State, 2066–2071. doi: 10.1109/BigData.2015.7363988.
   Google Scholar
• Saltz, J. S., and I. Shamshurin. 2016. “Big Data Team Process Methodologies: A Literature Review and the Identification of Key Factors for A Project’s Success.” IEEE International Conference on Big Data, Washington, United States, 2872–2879. doi: 10.1109/BigData.2016.7840936.
   Google Scholar
• Saltz, J. S., I. Shamshurin, and C. Connors. 2017(a). “Predicting Data Science Sociotechnical Execution Challenges by Categorizing Data Science Projects.” Journal of the Association for Information Science and Technology 68 (12): 2720–2728. doi:10.1002/asi.23873.
   Web of Science ®Google Scholar
• Saltz, J. S., I. Shamshurin, and C. Connors. 2017(b). “A Framework for Describing Big Data projects”.Lecture Notes in Business Information Processing.” International Conference on Business Information Systems, Poznań, Poland, 263: 183–195. doi:10.1007/978-3-319-52464-1_17.
   Google Scholar
• Shamout, M. D. 2020. “Supply Chain Data Analytics and Supply Chain Agility: A Fuzzy Sets (Fsqca) Approach.” International Journal of Organizational Analysis 28 (5): 1055–1067. doi:10.1108/IJOA-05-2019-1759.
   Web of Science ®Google Scholar
• Sivarajah, U., M. M. Kamal, Z. Irani, and V. Weerakkody. 2017. “Critical Analytics of Big Data Challenges and Analytical Methods.” Journal of Business Research 70: 263–286. doi:10.1016/j.jbusres.2016.08.001.
   Web of Science ®Google Scholar
• Studer, S., T. B. Bui, C. Drescher, A. Hanuschkin, W. Ludwig, S. Peters, and K.-R. Mueller. 2020. “Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology.” Machine Learning and Knowledge Extraction 3 (2): 392–413. doi:10.3390/make3020020.
   Google Scholar
• Swafford, P. M., S. Ghosh, and N. Murthy. 2008. “Achieving Supply Chain Agility through IT Integration and Flexibility.” International Journal of Production Economics 116 (2): 288–297. doi:10.1016/j.ijpe.2008.09.002.
   Web of Science ®Google Scholar
• Tarafdar, M., and S. Qrunfleh. 2017. “Agile Supply Chain Strategy and Supply Chain Performance: Complementary Roles of Supply Chain Practices and Information Systems Capability for Agility.” International Journal of Production Research 55 (4): 925–938. doi:10.1080/00207543.2016.1203079.
   Web of Science ®Google Scholar
• Uikey, N., and U. Suman. 2015. “Risk Based Scrum Method: A Conceptual Framework.” International Conference on Computing for Sustainable Global Development, New Delhi, India, 4120–4125.
   Google Scholar
• Wang, G., A. Gunasekaran, E. W. T. Ngai, and T. Papadopoulos. 2016. “Big Data Analytics in Logistics and Supply Chain Management: Certain Investigations for Research and Applications.” International Journal of Production Economics 176: 98–110. doi:10.1016/j.ijpe.2016.03.014.
   Web of Science ®Google Scholar
• Wirth, R., and J. Hipp. 2000. “CRISP-DM: Towards a Standard Process Model for Data Mining.” Proceedings of the Fourth International Conference on the Practical Application of Knowledge Discovery and Data Mining, Manchester, United Kingdom,29–39.
   Google Scholar
• Xiang, L. Y., H. J. Hwang, H. K. Kim, M. Mahmood, and N. M. Dawi. 2021. “The Use of Big Data Analytics to Improve the Supply Chain Performance in Logistics Industry.” In Software Engineering in IoT, Big Data, Cloud and Mobile Computing. Studies in Computational Intelligence, 930: 17–31. doi:10.1007/978-3-030-64773-5_2.
   Google Scholar
• Yin, R. K. 2009. “Case Study Research: Design and Methods. 4th ed.)” ed. Thousand Oaks, CA: Sage.
   Google Scholar
• Zhou, Z., N. V. Chawla, Y. Jin, and G. J. Williams. 2014. “Big Data Opportunities and Challenges: Discussions from Data Analytics Perspectives [Discussion Forum].” IEEE Computational Intelligence Magazine 9 (4): 62–74. doi:10.1109/MCI.2014.2350953.
   Web of Science ®Google Scholar
• Zhu, S., J. Song, B. T. Hazen, K. Lee, and C. Cegielski. 2018. “How Supply Chain Analytics Enables Operational Supply Chain Transparency: An Organisational Information Processing Theory Perspective.” International Journal of Physical Distribution & Logistics Management 48 (1): 47–68. doi:10.1108/IJPDLM-11-2017-0341.
   Web of Science ®Google Scholar