Smart support system of material procurement for waste reduction based on big data and predictive analytics

References

• Ahmed, Imran, Misbah Ahmad, Gwanggil Jeon, and Francesco Piccialli. 2021. “A Framework for Pandemic Prediction Using Big Data Analytics.” Big Data Research 25: 100190. doi:10.1016/j.bdr.2021.100190.
   Web of Science ®Google Scholar
• Atitallah, Safa Ben, Maha Driss, Wadii Boulila, and Henda Ben Ghézala. 2020. “Leveraging Deep Learning and IoT big Data Analytics to Support the Smart Cities Development: Review and Future Directions.” Computer Science Review 38: 100303. doi:10.1016/j.cosrev.2020.100303.
   Web of Science ®Google Scholar
• Bag, Surajit, Lincoln C. Wood, Sachin K. Mangla, and Sunil Luthra. 2020. “Procurement 4.0 and Its Implications on Business Process Performance in a Circular Economy.” Resources, Conservation and Recycling 152: 104502. doi:10.1016/j.resconrec.2019.104502.
   Web of Science ®Google Scholar
• Batini, Carlo, Cinzia Cappiello, Chiara Francalanci, and Andrea Maurino. 2009. “Methodologies for Data Quality Assessment and Improvement.” J ACM Comput. Surv. Article 16. doi:10.1145/1541880.1541883.
   Web of Science ®Google Scholar
• Belhadi, Amine, Karim Zkik, Anass Cherrafi, Sha'ri M. Yusof, and Said El Fezazi. 2019. “Understanding Big Data Analytics for Manufacturing Processes: Insights from Literature Review and Multiple Case Studies.” Computers & Industrial Engineering 137: 106099. doi:10.1016/j.cie.2019.106099.
   Web of Science ®Google Scholar
• Blake, Roger, and Paul Mangiameli. 2011. “The Effects and Interactions of Data Quality and Problem Complexity on Classification.” J. Data and Information Quality. Article 8. doi:10.1145/1891879.1891881.
   Google Scholar
• Bueno, Adauto, Moacir Godinho Filho, and Alejandro G. Frank. 2020. “Smart Production Planning and Control in the Industry 4.0 Context: A Systematic Literature Review.” Computers & Industrial Engineering 149: 106774. doi:10.1016/j.cie.2020.106774.
   Web of Science ®Google Scholar
• Çalı, Sedef, and Şebnem Yılmaz Balaman. 2019. “Improved Decisions for Marketing, Supply and Purchasing: Mining Big Data Through an Integration of Sentiment Analysis and Intuitionistic Fuzzy Multi Criteria Assessment.” Computers & Industrial Engineering 129: 315–332. doi:10.1016/j.cie.2019.01.051.
   Web of Science ®Google Scholar
• Cappiello, Cinzia, Chiara Francalanci, and Barbara Pernici. 2003. “Time-Related Factors of Data Quality in Multichannel Information Systems.” Journal of Management Information Systems 20 (3): 71–92. doi:10.1080/07421222.2003.11045769.
   Web of Science ®Google Scholar
• Chien, C.-F., M.-L. Tseng, R. R. Tan, K. Tan, and O. Velek. 2020. “Industry 3.5 for Sustainable Transition and Total Resource Management.” Resources, Conservation and Recycling 152: 104482. doi:10.1016/j.resconrec.2019.104482.
   Web of Science ®Google Scholar
• Chuang, Chia-Hung, and Yabing Zhao. 2019. “Demand Stimulation in Finished-Goods Inventory Management: Empirical Evidence from General Motors Dealerships.” International Journal of Production Economics 208: 208–220. doi:10.1016/j.ijpe.2018.11.013.
   Web of Science ®Google Scholar
• Dyson, R. G., and M. J. Foster. 1982. “The Relationship of Participation and Effectiveness in Strategic Planning.” Strategic Management Journal 3 (1): 77–88. doi:10.1002/smj.4250030107.
   Web of Science ®Google Scholar
• Gantz, J., and D. Reinsel. 2011. “Extracting Value from Chaos.” https://www.coursehero.com/file/27549522/Extracting-Value-from-Chaospdf/.
   Google Scholar
• Ghasemaghaei, Maryam, and Goran Calic. 2020. “Assessing the Impact of Big Data on Firm Innovation Performance: Big Data is Not Always Better Data.” Journal of Business Research 108: 147–162. doi:10.1016/j.jbusres.2019.09.062.
   Web of Science ®Google Scholar
• Ghobakhloo, Morteza. 2020. “Industry 4.0, Digitization, and Opportunities for Sustainability.” Journal of Cleaner Production 252: 119869. doi:10.1016/j.jclepro.2019.119869.
   Web of Science ®Google Scholar
• Güiza, Juan, Rafael Luque, Jennifer Murillo, Rodrigo Romero, David Barrera, and Héctor López-Ospina. 2021. “Integrating Pricing and Coordinated Inventory Decisions Between one Warehouse and Multiple Retailers.” Journal of Industrial and Production Engineering, 1–11. doi:10.1080/21681015.2021.1944342.
   Web of Science ®Google Scholar
• Haug, Anders, and Jan Stentoft Arlbjørn. 2011. “Barriers to Master Data Quality.” Journal of Enterprise Information Management 24 (3): 288–303. doi:10.1108/17410391111122862.
   Google Scholar
• Haug, Anders, Jan Stentoft Arlbjørn, and Anne Pedersen. 2009. “A Classification Model of ERP System Data Quality.” Industrial Management & Data Systems 109 (8): 1053–1068. doi:10.1108/02635570910991292.
   Web of Science ®Google Scholar
• Hazen, Benjamin T., Christopher A. Boone, Jeremy D. Ezell, and L. Allison Jones-Farmer. 2014. “Data Quality for Data Science, Predictive Analytics, and Big Data in Supply Chain Management: An Introduction to the Problem and Suggestions for Research and Applications.” International Journal of Production Economics 154: 72–80. doi:10.1016/j.ijpe.2014.04.018.
   Web of Science ®Google Scholar
• Jha, Aditya, Kiran Fernandes, Yu Xiong, Jiajia Nie, Neelesh Agarwal, and Manoj K. Tiwari. 2017. “Effects of Demand Forecast and Resource Sharing on Collaborative New Product Development in Supply Chain.” International Journal of Production Economics 193: 207–221. doi:10.1016/j.ijpe.2017.07.012.
   Web of Science ®Google Scholar
• Jolliffe, I. T. 2002. Principle Component Analysis. Springer.
   Google Scholar
• Kiraz, Alper, Onur Canpolat, Cem Özkurt, and Harun Taşkın. 2020. “Analysis of the Factors Affecting the Industry 4.0 Tendency with the Structural Equation Model and an Application.” Computers & Industrial Engineering 150: 106911. doi:10.1016/j.cie.2020.106911.
   Web of Science ®Google Scholar
• Ku, Chien-Chun, Chen-Fu Chien, and Kang-Ting Ma. 2020. “Digital Transformation to Empower Smart Production for Industry 3.5 and an Empirical Study for Textile Dyeing.” Computers & Industrial Engineering 142: 106297. doi:10.1016/j.cie.2020.106297.
   Web of Science ®Google Scholar
• Kuo, Tsai-Chi, Kuan Jui Chen, Wei-Jung Shiang, PoTsang B. Huang, Wilkistar Otieno, and Ming-Chuan Chiu. 2021. “A Collaborative Data-Driven Analytics of Material Resource Management in Smart Supply Chain by Using a Hybrid Industry 3.5 Strategy.” Resources, Conservation and Recycling 164: 105160. doi:10.1016/j.resconrec.2020.105160.
   Web of Science ®Google Scholar
• Kuo, Tsai-Chi, Ni-Ying Hsu, Tzu Yi Li, and Chin-Jung Chao. 2021. “Industry 4.0 Enabling Manufacturing Competitiveness: Delivery Performance Improvement Based on Theory of Constraints.” Journal of Manufacturing Systems 60: 152–161. doi:10.1016/j.jmsy.2021.05.009.
   Web of Science ®Google Scholar
• Liu, Qi, Gengzhong Feng, Xi Zhao, and Wenlong Wang. 2020. “Minimizing the Data Quality Problem of Information Systems: A Process-Based Method.” Decision Support Systems 137: 113381. doi:10.1016/j.dss.2020.113381.
   Web of Science ®Google Scholar
• Majeed, Arfan, Yingfeng Zhang, Shan Ren, Jingxiang Lv, Tao Peng, Saad Waqar, and Enhuai Yin. 2021. “A big Data-Driven Framework for Sustainable and Smart Additive Manufacturing.” Robotics and Computer-Integrated Manufacturing 67: 102026. doi:10.1016/j.rcim.2020.102026.
   Web of Science ®Google Scholar
• Mathai, Manu V., Cindy Isenhour, Dimitris Stevis, Philip Vergragt, Magnus Bengtsson, Sylvia Lorek, Lars Fogh Mortensen, et al. 2021. “The Political Economy of (Un)Sustainable Production and Consumption: A Multidisciplinary Synthesis for Research and Action.” Resources, Conservation and Recycling 167: 105265. doi:10.1016/j.resconrec.2020.105265.
   Web of Science ®Google Scholar
• Mcnulty, E. 2021. “Understand Big Data: the seven V’s.” Accessed February 13. https://dataconomy.com/2014/05/seven-vs-big-data/.
   Google Scholar
• Muir, Melanie, and Abubaker Haddud. 2018. “Additive Manufacturing in the Mechanical Engineering and Medical Industries Spare Parts Supply Chain.” Journal of Manufacturing Technology Management 29 (2): 372–397. doi:10.1108/JMTM-01-2017-0004.
   Web of Science ®Google Scholar
• Mungkung, Rattanawan, Kannika Sorakon, Saruda Sitthikitpanya, and Shabbir H. Gheewala. 2021. “Analysis of Green Product Procurement and Ecolabels towards Sustainable Consumption and Production in Thailand.” Sustainable Production and Consumption, doi:10.1016/j.spc.2021.03.024.
   Google Scholar
• Nagle, Tadhg, Tom Redman, and David Sammon. 2020. “Assessing Data Quality: A Managerial Call to Action.” Business Horizons 63 (3): 325–337. doi:10.1016/j.bushor.2020.01.006.
   Web of Science ®Google Scholar
• Nasiri, G. Reza, Mohammad Kalantari, and Behrooz Karimi. 2021. “Fast-Moving Consumer Goods Network Design with Pricing Policy in an Uncertain Environment with Correlated Demands.” Computers & Industrial Engineering 153: 106997. doi:10.1016/j.cie.2020.106997.
   Web of Science ®Google Scholar
• Ohlhorst, F. J. 2012. Big Data Analytics: Turning Big Data into Big Money. John Wiley & Sons. https://doi.org/10.1002/9781119205005.fmatter
   Google Scholar
• Okafor, Nwamaka U., Yahia Alghorani, and Declan T. Delaney. 2020. “Improving Data Quality of Low-Cost IoT Sensors in Environmental Monitoring Networks Using Data Fusion and Machine Learning Approach.” ICT Express 6 (3): 220–228. doi:10.1016/j.icte.2020.06.004.
   Web of Science ®Google Scholar
• Raguseo, Elisabetta, Claudio Vitari, and Federico Pigni. 2020. “Profiting from Big Data Analytics: The Moderating Roles of Industry Concentration and Firm Size.” International Journal of Production Economics 229: 107758. doi:10.1016/j.ijpe.2020.107758.
   Web of Science ®Google Scholar
• Ranjan, Jayanthi, and Cyril Foropon. 2021. “Big Data Analytics in Building the Competitive Intelligence of Organizations.” International Journal of Information Management 56: 102231. doi:10.1016/j.ijinfomgt.2020.102231.
   Web of Science ®Google Scholar
• Raut, Rakesh D., Sachin Kumar Mangla, Vaibhav S. Narwane, Manoj Dora, and Mengqi Liu. 2021. “Big Data Analytics as a Mediator in Lean, Agile, Resilient, and Green (LARG) 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
• Raut, Rakesh D., Vinay Surendra Yadav, Naoufel Cheikhrouhou, Vaibhav S. Narwane, and Balkrishna E. Narkhede. 2021. “Big Data Analytics: Implementation Challenges in Indian Manufacturing Supply Chains.” Computers in Industry 125: 103368. doi:10.1016/j.compind.2020.103368.
   Web of Science ®Google Scholar
• Research. November 9th. 2020. “What is predictive analytics?” Part Research. https://www.predictiveanalyticstoday.com/what-is-predictive-analytics/
   Google Scholar
• Sivarajah, Uthayasankar, Muhammad Mustafa Kamal, Zahir Irani, and Vishanth Weerakkody. 2017. “Critical Analysis 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
• Song, Zhuzhu, Wansheng Tang, Ruiqing Zhao, and Guoqing Zhang. 2021. “Inventory Strategy of the Risk Averse Supplier and Overconfident Manufacturer with Uncertain Demand.” International Journal of Production Economics 234: 108066. doi:10.1016/j.ijpe.2021.108066.
   Web of Science ®Google Scholar
• Sun, Weike, and Richard D. Braatz. 2021. “Smart Process Analytics for Predictive Modeling.” Computers & Chemical Engineering 144: 107134. doi:10.1016/j.compchemeng.2020.107134.
   Web of Science ®Google Scholar
• Wang, Xingzhi, Yuchen Wang, Fei Tao, and Ang Liu. 2021. “New Paradigm of Data-Driven Smart Customisation through Digital Twin.” Journal of Manufacturing Systems 58: 270–280. doi:10.1016/j.jmsy.2020.07.023.
   Web of Science ®Google Scholar
• Warth, J., G. Kaiser, and M. Kugler. 2011. “The Impact of Data Quality and Analytical Capabilities on Planning Performance: In: Insights from the Automotive Industry.” Paper presented at the Tenth International Conference on Wirtschaftsinformatik, Zuri, Switzerland.
   Google Scholar
• Watts, Stephanie, G. Shankaranarayanan, and Adir Even. 2009. “Data Quality Assessment in Context: A Cognitive Perspective.” Decision Support Systems 48 (1): 202–211. doi:10.1016/j.dss.2009.07.012.
   Web of Science ®Google Scholar
• Wijewardhana, Udani A., Denny Meyer, and Madawa Jayawardana. 2020. “Statistical Models for the Persistence of Threatened Birds Using Citizen Science Data: A Systematic Review.” Global Ecology and Conservation 21: e00821. doi:10.1016/j.gecco.2019.e00821.
   Web of Science ®Google Scholar
• Xu, Li Da, Eric L. Xu, and Ling Li. 2018. “Industry 4.0: State of the Art and Future Trends.” International Journal of Production Research 56 (8): 2941–2962. doi:10.1080/00207543.2018.1444806.
   Web of Science ®Google Scholar
• Yasmin, Mariam, Ekrem Tatoglu, Huseyin Selcuk Kilic, Selim Zaim, and Dursun Delen. 2020. “Big Data Analytics Capabilities and Firm Performance: An Integrated MCDM Approach.” Journal of Business Research 114: 1–15. doi:10.1016/j.jbusres.2020.03.028.
   Web of Science ®Google Scholar
• Zakaria, J. 2021. “A Step-by-Step Explanation of Principal Compoenent Analyssi (PCA).” Accessed May 27. https://builtin.com/data-science/step-step-explanation-principal-component-analysis.
   Google Scholar
• Zonta, Tiago, Cristiano André da Costa, Rodrigo da Rosa Righi, Miromar José de Lima, Eduardo Silveira da Trindade, and Guann Pyng Li. 2020. “Predictive Maintenance in the Industry 4.0: A Systematic Literature Review.” Computers & Industrial Engineering 150: 106889. doi:10.1016/j.cie.2020.106889.
   Web of Science ®Google Scholar