The bullwhip effect on inventory: a perspective on information quality

References

• Ali, M. M., and J. E. Boylan. 2011. “Feasibility Principles for Downstream Demand Inference in Supply Chains.” Journal of the Operational Research Society 62 (3): 474–482. doi:10.1057/jors.2010.82.
   Web of Science ®Google Scholar
• Aviv, Y. 2001. “The Effect of Collaborative Forecasting on Supply Chain Performance.” Management Science 47 (10): 1326–1343. doi:10.1287/mnsc.47.10.1326.10260.
   Web of Science ®Google Scholar
• Boute, R. N., and J. A. Van Mieghem. 2015. “Global Dual Sourcing and Order Smoothing: The Impact of Capacity and Lead Times.” Management Science 61 (9): 2080–2099. doi:10.1287/mnsc.2014.1992.
   Web of Science ®Google Scholar
• Bray, R. L., and H. Mendelson. 2015. “Production Smoothing and the Bullwhip Effect.” Manufacturing & Service Operations Management 17 (2): 208–220. doi:10.1287/msom.2014.0513.
   Web of Science ®Google Scholar
• Cachon, G. P., and M. Fisher. 2000. “Supply Chain Inventory Management and the Value of Shared Information.” Management Science 46 (8): 1032–1048. doi:10.1287/mnsc.46.8.1032.12029.
   Web of Science ®Google Scholar
• Cao, L., and H. Zhu. 2013. “Normal Accidents: Data Quality Problems in ERP-Enabled Manufacturing.” Journal of Data and Information Quality 4 (3): 1–26. doi:10.1145/2458517.
   Google Scholar
• Chae, B. K., C. Yang, D. Olson, and C. Sheu. 2014. “The Impact of Advanced Analytics and Data Accuracy on Operational Performance: A Contingent Resource Based Theory (RBT) Perspective.” Decision Support Systems 59: 119–126. doi:10.1016/j.dss.2013.10.012.
   Web of Science ®Google Scholar
• Chatfield, D. C., J. G. Kim, T. P. Harrison, and J. C. Hayya. 2004. “The Bullwhip Effect - Impact of Stochastic Lead Time, Information Quality, and Information Sharing: A Simulation Study.” Production and Operations Management 13 (4): 340–353. doi:10.1111/j.1937-5956.2004.tb00222.x.
   Web of Science ®Google Scholar
• Chen, F., Z. Drezner, J. K. Ryan, and D. Simchi-Levi. 2000. “Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and Information.” Management Science 46 (3): 436–443. doi:10.1287/mnsc.46.3.436.12069.
   Web of Science ®Google Scholar
• Chen, L., and H. L. Lee. 2009. “Information Sharing and Order Variability Control Under a Generalized Demand Model.” Management Science 55 (5): 781–797. doi:10.1287/mnsc.1080.0983.
   Web of Science ®Google Scholar
• Chen, L., and H. L. Lee. 2012. “Bullwhip Effect Measurement and its Implications.” Operations Research 60 (4): 771–784. doi:10.1287/opre.1120.1074.
   Web of Science ®Google Scholar
• Cohen, M. A., T. H. Ho, Z. J. Ren, and C. Terwiesch. 2003. “Measuring Imputed Cost in the Semiconductor Equipment Supply Chain.” Management Science 49 (12): 1653–1670. doi:10.1287/mnsc.49.12.1653.25115.
   Web of Science ®Google Scholar
• Croson, R., and K. Donohue. 2006. “Behavioral Causes of the Bullwhip Effect and the Observed Value of Inventory Information.” Management Science 52 (3): 323–336. doi:10.1287/mnsc.1050.0436.
   Web of Science ®Google Scholar
• Cui, R., G. Allon, A. Bassamboo, and J. A. Van Mieghem. 2015. “Information Sharing in Supply Chains: An Empirical and Theoretical Valuation.” Management Science 61 (11): 2803–2824. doi:10.1287/mnsc.2014.2132.
   Web of Science ®Google Scholar
• Dey, D., and S. Kumar. 2013. “Data Quality of Query Results with Generalized Selection Conditions.” Operations Research 61 (1): 17–31. doi:10.1287/opre.1120.1128.
   Web of Science ®Google Scholar
• Gaur, V., A. Giloni, and S. Seshadri. 2005. “Information Sharing in a Supply Chain under ARMA Demand.” Management Science 51 (6): 961–969. doi:10.1287/mnsc.1050.0385.
   Web of Science ®Google Scholar
• Ha, A. Y., and S. Tong. 2008. “Contracting and Information Sharing under Supply Chain Competition.” Management Science 54 (4): 701–715. doi:10.1287/mnsc.1070.0795.
   Web of Science ®Google Scholar
• Hazen, B. T., C. A. Boone, J. D. Ezell, and L. A. 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
• Hoberg, K., J. R. Bradley, and U. W. Thonemann. 2007. “Analyzing the Effect of the Inventory Policy on Order and Inventory Variability with Linear Control Theory.” European Journal of Operational Research 176 (3): 1620–1642. doi:10.1016/j.ejor.2005.10.040.
   Web of Science ®Google Scholar
• Huo, B., X. Zhao, and H. Zhou. 2014. “The Effects of Competitive Environment on Supply Chain Information Sharing and Performance: An Empirical Study in China.” Production and Operations Management 23 (4): 552–569. doi:10.1111/poms.2014.23.issue-4.
   Web of Science ®Google Scholar
• Kwak, J. K., and S. Gavirneni. 2015. “Impact of Information Errors on Supply Chain Performance.” Journal of the Operational Research Society 66 (2): 288–298. doi:10.1057/jors.2013.175.
   Web of Science ®Google Scholar
• Lee, H. L., K. C. So, and C. S. Tang. 2000. “The Value of Information Sharing in a Two-Level Supply Chain.” Management Science 46 (5): 626–643. doi:10.1287/mnsc.46.5.626.12047.
   Web of Science ®Google Scholar
• Leng, M., and M. Parlar. 2009. “Allocation of Cost Savings in a Three-Level Supply Chain with Demand Information Sharing: A Cooperative-Game Approach.” Operations Research 57 (1): 200–213. doi:10.1287/opre.1080.0528.
   Web of Science ®Google Scholar
• Li, S., and B. Lin. 2006. “Accessing Information Sharing and Information Quality in Supply Chain Management.” Decision Support Systems 42 (3): 1641–1656. doi:10.1016/j.dss.2006.02.011.
   Web of Science ®Google Scholar
• Li, S. H., S. S. Rao, T. S. Ragu-Nathan, and B. Ragu-Nathan. 2005. “Development and Validation of a Measurement Instrument for Studying Supply Chain Management Practices.” Journal of Operations Management 23 (6): 618–641. doi:10.1016/j.jom.2005.01.002.
   Web of Science ®Google Scholar
• Lukyanenko, R., J. Parsons, and Y. F. Wiersma. 2014. “The IQ of the Crowd: Understanding and Improving Information Quality in Structured User-Generated Content.” Information Systems Research 25 (4): 669–689. doi:10.1287/isre.2014.0537.
   Web of Science ®Google Scholar
• Ma, Y., N. Wang, A. Che, Y. Huang, and J. Xu. 2013a. “The Bullwhip Effect on Product Orders and Inventory: A Perspective of Demand Forecasting Techniques.” International Journal of Production Research 51 (1): 281–302. doi:10.1080/00207543.2012.676682.
   Web of Science ®Google Scholar
• Ma, Y., N. Wang, A. Che, Y. Huang, and J. Xu. 2013b. “The Bullwhip Effect Under Different Information-Sharing Settings: A Perspective on Price-Sensitive Demand that Incorporates Price Dynamics.” International Journal of Production Research 51 (10): 3085–3116. doi:10.1080/00207543.2012.754551.
   Web of Science ®Google Scholar
• Ma, Y., N. Wang, Z. He, J. Lu, and H. Liang. 2015. “Analysis of the Bullwhip Effect in Two Parallel Supply Chains with Interacting Price-Sensitive Demands.” European Journal of Operational Research 243 (3): 815–825. doi:10.1016/j.ejor.2014.12.043.
   Web of Science ®Google Scholar
• Özer, Ö., and W. Wei. 2006. “Strategic Commitments for an Optimal Capacity Decision Under Asymmetric Forecast Information.” Management Science 52 (8): 1238–1257. doi:10.1287/mnsc.1060.0521.
   Web of Science ®Google Scholar
• Parssian, A., S. Sarkar, and V. S. Jacob. 2004. “Assessing Data Quality for Information Products: Impact of Selection, Projection, and Cartesian Product.” Management Science 50 (7): 967–982. doi:10.1287/mnsc.1040.0237.
   Web of Science ®Google Scholar
• Raghunathan, S. 2001. “Information Sharing in A Supply Chain: A Note on Its Value When Demand Is Nonstationary.” Management Science 47 (4): 605–610. doi:10.1287/mnsc.47.4.605.9833.
   Web of Science ®Google Scholar
• Shan, J., S. Yang, S. Yang, and J. Zhang. 2014. “An Empirical Study of the Bullwhip Effect in China.” Production and Operations Management 23 (4): 537–551. doi:10.1111/poms.2014.23.issue-4.
   Web of Science ®Google Scholar
• Simchi-Levi, D., and Y. Zhao. 2003. “The Value of Information Sharing in a Two-Stage Supply Chain with Production Capacity Constraints.” Naval Research Logistics 50 (8): 888–916. doi:10.1002/(ISSN)1520-6750.
   Web of Science ®Google Scholar
• Taylor, T. A., and W. Xiao. 2010. “Does a Manufacturer Benefit from Selling to a Better-Forecasting Retailer?” Management Science 56 (9): 1584–1598. doi:10.1287/mnsc.1100.1204.
   Web of Science ®Google Scholar
• Wang, N., J. Lu, G. Feng, Y. Ma, and H. Liang. 2016. “The Bullwhip Effect on Inventory under Different Information Sharing Settings Based on Price-Sensitive Demand.” International Journal of Production Research 54 (13): 4043–4064. doi:10.1080/00207543.2016.1171418.
   Web of Science ®Google Scholar
• Wang, R. Y., and D. M. Strong. 1996. “Beyond Accuracy: What Data Quality Means to Data Consumers.” Journal of Management Information Systems 12 (4): 5–33. doi:10.1080/07421222.1996.11518099.
   Google Scholar
• Xu, H. J., J. H. Nord, N. Brown, and G. D. Nord. 2002. “Data Quality Issues in Implementing an ERP.” Industrial Management & Data Systems 102 (1): 47–58. doi:10.1108/02635570210414668.
   Web of Science ®Google Scholar
• Zhang, S. H., and K. L. Cheung. 2011. “The Impact of Information Sharing and Advance Order Information on a Supply Chain with Balanced Ordering.” Production and Operations Management 20 (2): 253–267. doi:10.1111/poms.2011.20.issue-2.
   Web of Science ®Google Scholar
• Zhou, H., Y. Shou, X. Zhai, L. Li, C. Wood, and X. Wu. 2014. “Supply Chain Practice and Information Quality: A Supply Chain Strategy Study.” International Journal of Production Economics 147 (SIC): 624–633. doi:10.1016/j.ijpe.2013.08.025.
   Web of Science ®Google Scholar