A Review of Supply Chain Data Mining Publications

  • David L. Olson University of Nebraska Lincoln


The use of data mining in supply chains is growing, and covers almost all aspects of supply chain management. A framework of supply chain analytics is used to classify data mining publications reported in supply chain management academic literature. Scholarly articles were identified using SCOPUS and EBSCO Business search engines. Articles were classified by supply chain function. Additional papers reflecting technology, to include RFID use and text analysis were separately reviewed. The paper concludes with discussion of potential research issues and outlook for future development.


Ayoub, N., Martins, R., Wang, K., Seki, H. and Naka, Y. (2007) 'Two levels decision system for efficient planning implementation of bioenergy production', Energy Conversion and Management, 48(3), 709-723.
Balasubramaniam, C.P. and Thigarasu, V. (2015) 'Agent-based modeling in supply chain management using improved C4-5', Research Journal of Applied Sciences, Engineering and Technology, 9(2), 91-97.
Banerjee, A., Bandyopadhyay, T. and Acharya, P. (2013) 'Data analytics: Hyped up aspirations or true potential?', Vikalpa: The Journal for Decision Makers, 38(4), 1-11.
Bhattacharya, A., Kumar, S.A., Tiwari, M.K. and Talluri, S. (2014) 'An intermodal freight transport system for optimal supply chain logistics', Transportation Research: Part C, 38, 73-84.
Brandau, A. and Tolujevs, J. (2013)'Modelling and analysis of logistical state data', Transport and Telecommunication, 14(2), 102-115.
Chae, B. (2015) 'Insights from hashtag #supplychain and Twitter analytics: Considering Twitter and Twitter data for supply chain practice and research', International Journal of Production Economics, 165(1), 247-259.
Chae, B., Olson, D. and Sheu, C. (2014) 'The impact of supply chain analytics on operational performance: A resource-based view', International Journal of Production Research, 52(16), 4695-4710.
Chen, M.C. and Wu, H.P. (2005) 'An association-based clustering approach to order batching considering customer demand patterns', Omega, 33(4), 333-343.
Chen, Y.S., Chen, C.H. and Lai, C.J. (2012) 'Extracting performance rules of suppliers in the manufacturing industry: An empirical study', Journal of Intelligent Manufacturing, 23(5), 2037-2045.
Choudhary, A.K., Harding, J.A., Lin, H.K., Tiwari, M.K. and Shankar, R. (2011) 'Knowledge discovery and data mining integrated (KOATING) Moderators for collaborative projects', International Journal of Production Research, 49(23), 7029-7057.
Collins, J.D., Worthington, W.J., Reyes, P.M.. and Romero, M. (2010) 'Knowledge management, supply chain technologies, and firm performance', Management Research Review, 33(10), 947-960.
Costa, G., Manco, G. and Masciari, E. (2014) 'Dealing with trajectory streams by clustering and mathematical transforms', Journal of Intelligent Information Systems, 42(1), 155-177.
Davenport, T. and O'Dwyer, J. (2011) 'Tap into the power of analytics', Supply Chain Quarterly, Fourth Quarter, 28-31.
Davis-Sramek, B., Germain, R. and Iyer, K. (2010) 'Supply chain technology: The role of environment in predicting performance', Journal of the Academy of Marketing Science, 38(1), 42-55.
Delen, D., Erraguntla, M., Mayer, R.J. and Wu, C.N. (2011) 'Better management of blood supply-chain with GIS-based analytics', Annals of Operations Research, 185(1), 181-193.
Demirkan, H. and Delen, D. (2012) 'Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud', Decision Support Systems, 55(1), 412-421.
Dobbs, R., Manyika, J. and Woetzel, J. (2015) No Ordinary Disruption: The Four Global Forces Breaking All the Trends. Philadelphia, PA, USA: PublicAffairs.
Faezy Razi, F. (2014) 'A supplier selection using a hybrid grey based hierarchical clustering and artificial bee colony', Decision Science Letters, 3(3), 259-268.
Forslund, H. and Jonsson, P. (2007) 'The impact of forecast information quality on supply chain performance', International Journal of Operations & Production Management, 27(1), 90-107.
Ghadge, A., Dani, S. and Kalawsky, R. (2012) 'Supply chain risk management: Present and future scope', International Journal of Logistics Management, 23(3), 313-339.
Gonzalez, H., Han, J., Cheng, H., Li, X., Klabjan, D. and Wu, T. (2010) 'Modeling massive RFID data sets: A gateway-based movement graph approach', IEEE Transactions on Knowledge & Data Engineering, 22(1), 90-104.
Ha, S.H. and Krishnan, R. (2008) 'A hybrid approach to supplier selection for the maintenance of a competitive supply chain', Expert Systems with Applications, 34(2), 1303-1311.
Hadighi, S.A., Sahebjamnia, N., Mahdavi, I. and Akbarpour Shirazi, M. (2013) 'A framework for strategy formulation based on clustering approach: A case study in a corporate organization', Knowledge-Based Systems, 49, 37-49.
Handfield, R. (2006) Supply Market Intelligence: A Managerial Handbook for Building Sourcing Strategies. New York: Taylor & Francis.
Handfield, R. and Nichols, E. (2004) 'Key issues in global supply base management', Industrial Marketing Management, 33(1), 29-35.
Ho, G.T.S., Lau, H.C.W., Kwok, S.K., Lee, C.K.M. and Ho, W. (2009) 'Development of a co-operative distributed process mining system for quality assurance', International Journal of Production Research, 47(4), 883-918.
Hong, G.H. and Ha, S.H. (2008) 'Evaluating supply partner’s capability for seasonal products using machine learning techniques', Computers and Industrial Engineering, 54(4), 721-736.
Ivanov, D. and Sokolov, B. (2012) 'The inter-disciplinary modelling of supply chains in the context of collaborative multi-structural cyber-physical networks', Journal of Manufacturing Technology Management, 23(8), 976-997.
Jain, R., Singh, A.R., Yadav, H.C. and Mishra, P.K. (2014) 'Using data mining synergies for evaluating criteria at pre-qualification stage of supplier selection', Journal of Intelligent Manufacturing, 25(1), 165-175.
Jain, V., Benyoucef, L. and Deshmukh, S.G. (2008) 'A new approach for evaluating agility in supply chains using fuzzy association rules mining', Engineering Applications of Artificial Intelligence, 21(3), 367-385.
Jain, V., Wadhwa, S. and Deshmukh, S.G. (2009) 'Select supplier-related issues in modelling a dynamic supply chain: Potential, challenges and direction for future research', International Journal of Production Research, 47(11), 3013-3039.
Ji, S.W., Tian, Y. and Gao, Y.H. (2013) 'Study on supply chain information control tower system', Information Technology Journal, 12(24), 8488-8493.
Kohli, R. and Grover, V. (2008) 'Business value of it: An essay on expanding research directions to keep up with the times', Journal of Association for Information Systems, 9(1), 23-39.
Kraus, C. and Valverde, R. (2014) 'A data warehouse design for the detection of fraud in the supply chain by using the Benford’s law', American Journal of Applied Sciences, 11(9), 1507-1518.
Lau, H.C.W., Ho, G.T.S., Zhao, Y. and Chung, N.S.H. (2009) 'Development of a process mining system for supporting knowledge discovery in a supply chain network', International Journal of Production Economics, 122(1), 176-187.
Lavalle, S., Lesser, E., Shockey, R.H., M and Kruschwitz, N. (2011) 'Big data, analytics and the path from insights to value', MIT Sloan Management Review, 52(2), 21-32.
Le, H.Q., Arch-Int., S., Nguyen, H.C. and Arch-Int., N. (2013) 'Association rule hiding in risk management for retail supply chain collaboration', Computers in Industry, 64(7), 776-784.
Lee, C.K.M., Lau, H.C.W., Kwok, S.K. and Ho, G.T.S. (2010) 'Design and development of supply chain knowledge discovery system for customer relationship management', International Journal of Services, Technology and Management, 14(1), 2-16.
Li, G.D., Yamaguchi, D. and Nagai, M. (2008) 'A grey-based rough decision-making approach to supplier selection', International Journal of Advanced Manufacturing Technology, 36(9-10), 1032-1040.
Li, Y., Kramer, M.R., Beulens, A.J.M. and van der Vorst, J.G.A.J. (2010) 'A framework for early warning and proactive control systems in food supply chain networks', Computers in Industry, 61(9), 852-862.
Liao, S.H., Chen, Y.N. and Tseng, Y.Y. (2009) 'Mining demand chain knowledge of life insurance market for new product development', Expert Systems with Applications, 36(5), 9422-9437.
Liao, S.H., Chen, C.M. and Wu, C.H. (2008a) 'Mining customer knowledge for product line and brand extension in retailing', Expert Systems with Applications, 34(3), 1763-1776.
Liao, S.H., Hsieh, C.L. and Huang, S.P. (2008b) 'Mining product maps for new product development', Expert Systems with Applications, 34(1), 50-62.
Liao, S.H. and Wen, C.H. (2009) 'Mining demand chain knowledge for new product development and marketing', IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, 39(2), 223-227
Liberatore, M. and Luo, W. (2010) 'The analytics movement', Interfaces, 40(4), 313-324.
Lin, R.H., Chuang, C.L., Liou, J.J.H. and Wu, G.D. (2009) 'An integrated method for finding key suppliers in SCM', Expert Systems with Applications, 36(3) part 2, 6461-6465.
Ludwig, S., de Ruyter, K., Friedman, M., Brűggen, E.C., Wetzels, M. and Pfann, G. (2013) 'More than words: The influence of affective content and linguistic style matches in online reviews on conversion rates', Journal of Marketing, 77(1), 87-103.
Masciari, E. (2012) 'SMART: Stream monitoring enterprise activities by RFID Tags', Information Sciences 195, 25-44.
Min, H. (2006) 'Developing the profiles of supermarket customers through data mining', Service Industries, 26(7), 747-763.
Mithas, S., Ramasubbu, N. and Sambamurthy, V. (2011) 'How information management capability influences firm performance', MIS Quarterly, 35(1), 237-256.
Morizumi, S., Chu, B., Cao, H. and Matsukawa, H. (2011) 'Supply chain risk driver extraction using text mining technique', Information, 14(6), 1935-1945.
Ni, M., Xu, X. and Deng, S. (2007) 'Extended QFD and data-mining-based methods for supplier selection in mass customization'. International Journal of Computer Integrated Manufacturing, 20(2-3), 280-291.
O'Dwyer, J. and Renner, R. (2011) 'The promise of advanced supply chain analytics', Supply Chain Management Review, 15, 32-37.
Oliva, R. and Watson, N. (2011) 'Cross functional alignment in supply chain planning: A case study of sales & operations planning', Journal of Operations Management, 29(5), 434-448.
Olson, D.L. and Shi, Y. (2006) Introduction to Business Data Mining. Irwin: McGraw-Hill.
Ordenes, F.V., Theodoulidis, B., Burton, J., Gruber, T. and Zaki, M. (2014) 'Analyzing customer experience feedback using text mining: A linguistics-based approach', Journal of Service Research, 17(3), 278-295.
Qin, L. and Zhao, X. (2012) 'Design and realization of information service platform of logistics parks based on cloud computing', Advances in Information Sciences and Service Sciences, 4(23), 112-120.
Parmar, D., Wu, T., Callarman, T., Fowler, J. and Wolfe, P. (2010) 'A clustering algorithm for supplier base management', International Journal of Production Research, 48(13), 3803-3821.
Peng, M., Peng, Y. and Chen, H. (2014) 'Post-seismic supply chain risk management: A system dynamics disruption analysis approach for inventory and logistics planning', Computers and Operations Research, 42, 14-24.
Pillutla, S., Yao, D.Q. and Li, X. (2014) 'Data mining the adoption intention of e-procurement system for Chinese companies', International Journal of Management & Decision Making, 13(2), 207-219.
Piramuthu, S. (2005) 'Knowledge-based framework for automated dynamic supply chain configuration', European Journal of Operational Research, 165(1), 219-230.
Ren, C., Liu, Y. and Guo, Y. (2014) 'Fuzzy evaluation on supply chain competitiveness based on membership degree transformation new algorithm', Journal of Chemical and Pharmaceutical Research, 6(2), 139-144.
Renaud-Gentié, C., Burgos, S. and Benoît, M. (2014) 'Choosing the most representative technical management routes within diverse management practices: Application to vineyards in the Loire Valley for environmental and quality assessment', European Journal of Agronomy, 56, 19-36.
Robinson, A., Levis, J. and Bennet, G. (2010) 'INFORMS to officially join analytics movement', OR/MS Today, 37(5), 59.
Sathi, A. (2012) Big Data Analytics: Disruptive Technologies for Changing the Game. Boise, ID: MC Press.
Schlegel, G.L. (2014/2015) 'Utilizing big data and predictive analytics to manage supply chain risk', Journal of Business Forecasting, 33(4), 11-17.
Schniederjans, D., Cao, E.S. and Schiederjans, M. (2013) 'Enhancing financial performance with social media: An impression management perspective', Decision Support Systems, 55(4), 911-918.
Schoenherr, T. and Speier-Pero, C. (2015) 'Data science, predictive analytics, and big data in supply chain management: Current state and future potential', Journal of Business Logistics, 36(1), 120-132.
Shao, C., Wang, L., Xiao, L. and Wu, J. (2010) 'Qualitative phase space reconstruction analysis of supply-chain inventory time series', South African Journal of Science, 106(11-12), 1-7.
Shih, S.C. (2007) 'A three-stage field service management model for effective post-sales service supply chain management', International Journal of Manufacturing Technology and Management, 12(4), 384-404.
Shukla, V., Naim, M.M. and Thornhill, N.F. (2012) 'Rogue seasonality detection in supply chains', International Journal of Production Economics, 138(2), 254-272.
Smith, A.D. (2011) 'Managing supply chain complexities and integration issues for competitive advantage: A comparative analysis', International Journal of Logistics Systems and Management, 9(3), 351-374.
Soeanu, A., Debbabi, M., Alhadidi, D., Makkawi, M., Allouche, M., Bélanger, M. and Léchevin, M. (2015) 'Transportation risk analysis using probabilistic model checking', Expert Systems with Applications, 42(9), 4410-4421.
Song, D.P. and Dinwoodie, J. (2008) 'Quantifying the effectiveness of VMI and integrated inventory management in a supply chain with uncertain lead-times and uncertain demands', Production Planning and Control, 19(6), 590-600.
Song, Z. and Kusiak, A. (2009) 'Optimising product configurations with a data-mining approach', International Journal of Production Research, 47(7), 1733-1751.
Srivihok, A. and Intrapairot, A. (2014) 'Model of inbound ASEAN economics community tourists in Thailand by using twining of feature selection and classification algorithms', Advanced Science Letters, 20(10-12), 2202-2205.
Stefanovic, N. (2014) 'Proactive supply chain performance management with predictive analytics', Scientific World Journal, 2014, 1-17.
Stefanovic, N. (2015) 'Collaborative predictive business intelligence model for spare parts inventory replenishment', Computer Science and Information Systems, 12(3), 911-930.
Thiesse, F., Floerkemeier, C., Harrison, M., Michahelles, F. and Roduner, C. (2009) 'Technology, standards, and real-world deployments of the EPC network', IEEE Internet Computing, 13(2), 36-43.
Thomassey, S. (2010) Sales forecasts in clothing industry: 'The key success factor of the supply chain management', International Journal of Production Economics, 128(2), 470-483.
Tien, J.M. (2006) 'Data mining requirements for customized goods and services', International Journal of Information technology & Decision Making, 5(4), 683-698.
Tien, J.M. (2012) 'The next industrial revolution: Integrated services and goods', Journal of Systems Science and Systems Engineering, 21(3), 257-296.
Ting, S.L., Tse, Y.K., Ho, G.T.S., Chung, S.H. and Pang, G. (2014) 'Mining logistics data to assure the quality in a sustainable food supply chain: A case in the red wine industry', International Journal of Production Economics, 152, 200-209.
Tirkel, I. (2013) 'Forecasting flow time in semiconductor manufacturing using knowledge discovery in databases', International Journal of Production Research, 51(18), 5536-5548.
Tsou, C.M. (2013) 'On the strategy of supply chain collaboration based on dynamic inventory target level management: A theory of constraint perspective', Applied Mathematical Modelling, 37(7), 5204-5214.
Wang, C., Luxhøj, J.T. and Johansen, J. (2004) 'Applying a knowledge management modeling tool for manufacturing vision (MV) development', Industrial Management & Data Systems, 104(9), 735-743.
Warkentin, M., Sugumaran, V. and Sainsbury, R. (2012) 'The role of intelligent agents and data mining in electronic partnership management', Expert Systems with Applications, 39(18), 13277-13288.
Wu, S. and Guo, J. (2012) 'The text mining and classification analyses on the relationship between green supply chain management and closed-loop supply chain research trends (2000-2010)', International Journal of Digital Content Technology and its Applications, 6(23), 281-288.
Xu, X. and Lin, J. (2009) 'An integrated method to discovering key suppliers in supplier chain management', Journal of Computational Information Systems, 5(3), 1445-1452.
Yi, L. (2014) 'A graphic-based data mining approach in RFID sensor networks', International Journal of Control and Automation, 7(2), 387-396.
Yűksel, M.E. and Yűksel, A.S. (2011) 'RFID technology in business systems and supply chain management', Journal of Economic & Social Studies, 1(1), 53-71.
Zhang, T., Yin, Y., Yue, D., Wang, X. and Yu, G. (2014) 'Research and implementation of an RFID simulation system supporting trajectory analysis', Journal of Software, 9(1), 162-168.
Zhao, K. and Yu, X. (2011) 'A case based reasoning approach on supplier selection in petroleum enterprises', Expert Systems with Applications, 38(6), 6839-6847.
Zhou, M., Dresner, M. and Windle, R.J. (2008) 'Online reputation systems: Design and strategic practices', Decision Support Systems, 44(4), 785-797.
Zhu, X. (2014) 'An algorithm for moving path discovery using frequent graphical mining approach', International Journal of Control and Automation, 7(10), 145-154.
Zou, Z., Tseng, T.L., Sohn, H., Song, G. and Gutierrez, R. (2011) 'A rough set based approach to distributor selection in supply chain management', Expert Systems with Applications, 38(1), 106-115.

Author Biography

David L. Olson, University of Nebraska Lincoln
Full Professor
How to Cite
OLSON, David L.. A Review of Supply Chain Data Mining Publications. Journal of Supply Chain Management Science, [S.l.], v. 1, n. 1-2, p. 15-26, june 2020. ISSN 2451-9901. Available at: <https://journals.open.tudelft.nl/jscms/article/view/955>. Date accessed: 12 july 2020. doi: https://doi.org/10.18757/jscms.2015.955.


Data mining, Supply Chain Management, Review paper