IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v186y2017icp123-131.html
   My bibliography  Save this article

The negative impact of product variety: Forecast bias, inventory levels, and the role of vertical integration

Author

Listed:
  • Wan, Xiang
  • Sanders, Nadia R.

Abstract

Companies routinely increase product variety in order to enhance competitiveness and grow sales. Unfortunately, increasing product variety creates operational challenges and results in higher inventory levels. The large number SKUs deteriorate decision quality and can introduce forecast bias - the tendency to consistently over or under forecast – into the system, further exacerbating the inventory problem. In this study, we evaluate how firms can increase product variety while managing inventory levels. Using balanced panel data collected from 283 distribution centers over 26 continuous four-week periods, we empirically test the mediation relationship of forecast bias on inventory levels. We find support for this relationship and show that firms can mitigate the negative effect of product variety on inventory levels by using strategies to reduce forecast bias. We then explore this relationship pre and post vertical integration, allowing us to test the impact of organizational change. Vertical integration creates opportunities for information sharing, lowering the uncertainty that may contribute to forecast bias. We find that the relationship is indeed moderated by vertical integration, suggesting that many of the operational challenges of increasing product variety can be improved through information transparency and coordination with supply chain partners. Collectively these findings provide important guidelines on how firms can increase product variety while maintaining inventory levels.

Suggested Citation

  • Wan, Xiang & Sanders, Nadia R., 2017. "The negative impact of product variety: Forecast bias, inventory levels, and the role of vertical integration," International Journal of Production Economics, Elsevier, vol. 186(C), pages 123-131.
  • Handle: RePEc:eee:proeco:v:186:y:2017:i:c:p:123-131
    DOI: 10.1016/j.ijpe.2017.02.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527317300312
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2017.02.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gérard P. Cachon & Martin A. Lariviere, 2001. "Contracting to Assure Supply: How to Share Demand Forecasts in a Supply Chain," Management Science, INFORMS, vol. 47(5), pages 629-646, May.
    2. Eroglu, Cuneyt & Croxton, Keely L., 2010. "Biases in judgmental adjustments of statistical forecasts: The role of individual differences," International Journal of Forecasting, Elsevier, vol. 26(1), pages 116-133, January.
    3. Wesley David Sine & Scott Shane & Dante Di Gregorio, 2003. "The Halo Effect and Technology Licensing: The Influence of Institutional Prestige on the Licensing of University Inventions," Management Science, INFORMS, vol. 49(4), pages 478-496, April.
    4. Hau L. Lee & Kut C. So & Christopher S. Tang, 2000. "The Value of Information Sharing in a Two-Level Supply Chain," Management Science, INFORMS, vol. 46(5), pages 626-643, May.
    5. Williamson, Oliver E, 1979. "Transaction-Cost Economics: The Governance of Contractural Relations," Journal of Law and Economics, University of Chicago Press, vol. 22(2), pages 233-261, October.
    6. Dean W. Wichern & Benito E. Flores, 2005. "Evaluating forecasts: a look at aggregate bias and accuracy measures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(6), pages 433-451.
    7. Armstrong, J. Scott & Morwitz, Vicki G. & Kumar, V., 2000. "Sales forecasts for existing consumer products and services: Do purchase intentions contribute to accuracy?," International Journal of Forecasting, Elsevier, vol. 16(3), pages 383-397.
    8. Barry L. Bayus & William P. Putsis, Jr., 1999. "Product Proliferation: An Empirical Analysis of Product Line Determinants and Market Outcomes," Marketing Science, INFORMS, vol. 18(2), pages 137-153.
    9. Ellickson, Paul B., 2006. "Quality competition in retailing: A structural analysis," International Journal of Industrial Organization, Elsevier, vol. 24(3), pages 521-540, May.
    10. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
    11. Sunder Kekre & Kannan Srinivasan, 1990. "Broader Product Line: A Necessity to Achieve Success?," Management Science, INFORMS, vol. 36(10), pages 1216-1232, October.
    12. Lawrence, Michael & O'Connor, Marcus & Edmundson, Bob, 2000. "A field study of sales forecasting accuracy and processes," European Journal of Operational Research, Elsevier, vol. 122(1), pages 151-160, April.
    13. Syntetos, Aris A. & Nikolopoulos, Konstantinos & Boylan, John E., 2010. "Judging the judges through accuracy-implication metrics: The case of inventory forecasting," International Journal of Forecasting, Elsevier, vol. 26(1), pages 134-143, January.
    14. Fildes, Robert & Goodwin, Paul & Lawrence, Michael & Nikolopoulos, Konstantinos, 2009. "Effective forecasting and judgmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning," International Journal of Forecasting, Elsevier, vol. 25(1), pages 3-23.
    15. Robert Fildes & Paul Goodwin, 2007. "Against Your Better Judgment? How Organizations Can Improve Their Use of Management Judgment in Forecasting," Interfaces, INFORMS, vol. 37(6), pages 570-576, December.
    16. Nan Xia & S. Rajagopalan, 2009. "Standard vs. Custom Products: Variety, Lead Time, and Price Competition," Marketing Science, INFORMS, vol. 28(5), pages 887-900, 09-10.
    17. Li Chen & Hau L. Lee, 2009. "Information Sharing and Order Variability Control Under a Generalized Demand Model," Management Science, INFORMS, vol. 55(5), pages 781-797, May.
    18. Sampath Rajagopalan, 2013. "Impact of Variety and Distribution System Characteristics on Inventory Levels at U.S. Retailers," Manufacturing & Service Operations Management, INFORMS, vol. 15(2), pages 191-204, May.
    19. Albert Y. Ha & Shilu Tong & Hongtao Zhang, 2011. "Sharing Demand Information in Competing Supply Chains with Production Diseconomies," Management Science, INFORMS, vol. 57(3), pages 566-581, March.
    20. Sechan Oh & Özalp Özer, 2013. "Mechanism Design for Capacity Planning Under Dynamic Evolutions of Asymmetric Demand Forecasts," Management Science, INFORMS, vol. 59(4), pages 987-1007, April.
    21. Francine Lafontaine & Margaret Slade, 2007. "Vertical Integration and Firm Boundaries: The Evidence," Journal of Economic Literature, American Economic Association, vol. 45(3), pages 629-685, September.
    22. Syntetos, Aris A. & Nikolopoulos, Konstantinos & Boylan, John E. & Fildes, Robert & Goodwin, Paul, 2009. "The effects of integrating management judgement into intermittent demand forecasts," International Journal of Production Economics, Elsevier, vol. 118(1), pages 72-81, March.
    23. Gerard Cachon, 2001. "Managing a Retailer's Shelf Space, Inventory, and Transportation," Manufacturing & Service Operations Management, INFORMS, vol. 3(3), pages 211-229, July.
    24. Michael J. Brusco & Larry W. Jacobs, 2000. "Optimal Models for Meal-Break and Start-Time Flexibility in Continuous Tour Scheduling," Management Science, INFORMS, vol. 46(12), pages 1630-1641, December.
    25. Andrew King & Michael Lenox, 2002. "Exploring the Locus of Profitable Pollution Reduction," Management Science, INFORMS, vol. 48(2), pages 289-299, February.
    26. Pino G. Audia & Henrich R. Greve, 2006. "Less Likely to Fail: Low Performance, Firm Size, and Factory Expansion in the Shipbuilding Industry," Management Science, INFORMS, vol. 52(1), pages 83-94, January.
    27. Yossi Aviv, 2001. "The Effect of Collaborative Forecasting on Supply Chain Performance," Management Science, INFORMS, vol. 47(10), pages 1326-1343, October.
    28. Davydenko, Andrey & Fildes, Robert, 2013. "Measuring forecasting accuracy: The case of judgmental adjustments to SKU-level demand forecasts," International Journal of Forecasting, Elsevier, vol. 29(3), pages 510-522.
    29. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    30. Albert Y. Ha & Shilu Tong, 2008. "Contracting and Information Sharing Under Supply Chain Competition," Management Science, INFORMS, vol. 54(4), pages 701-715, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marissa Beck & Fiona Scott Morton, 2021. "Evaluating the Evidence on Vertical Mergers," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 59(2), pages 273-302, September.
    2. Chiang, Chung-Yean & Qian, Zhuang & Chuang, Chia-Hung & Tang, Xiao & Chou, Chia-Ching, 2023. "Examining demand and supply-chain antecedents of inventory dynamics: Evidence from automotive industry," International Journal of Production Economics, Elsevier, vol. 259(C).
    3. Song, Zhuzhu & Tang, Wansheng & Zhao, Ruiqing, 2020. "A simple game theoretical analysis for incentivizing multi-modal transportation in freight supply chains," European Journal of Operational Research, Elsevier, vol. 283(1), pages 152-165.
    4. Bichescu, Bogdan C. & Bradley, Randy V. & Smith, Antoinette L. & Wei, Wu, 2018. "Benefits and implications of competing on process excellence: Evidence from California hospitals," International Journal of Production Economics, Elsevier, vol. 202(C), pages 59-68.
    5. Yang, Jiaquan & Li, Kevin W. & Huang, Jun, 2023. "Manufacturer encroachment with a new product under network externalities," International Journal of Production Economics, Elsevier, vol. 263(C).
    6. Golrizgashti, Seyedehfatemeh & Hosseini, SeyedHossein & Zhu, Qingyun & Sarkis, Joseph, 2023. "Evaluating supply chain dynamics in the presence of product deletion," International Journal of Production Economics, Elsevier, vol. 255(C).
    7. Sali, Mustapha & Ghrab, Yahya & Chatras, Clément, 2023. "Optimal product aggregation for sales and operations planning in mass customisation context," International Journal of Production Economics, Elsevier, vol. 263(C).
    8. Wan, Xiang & Britto, Rodrigo & Zhou, Zenan, 2020. "In search of the negative relationship between product variety and inventory turnover," International Journal of Production Economics, Elsevier, vol. 222(C).
    9. Melek Akın Ateş & Robert Suurmond & Davide Luzzini & Daniel Krause, 2022. "Order from chaos: A meta‐analysis of supply chain complexity and firm performance," Journal of Supply Chain Management, Institute for Supply Management, vol. 58(1), pages 3-30, January.
    10. Mile Katic & Renu Agarwal, 2018. "The Flexibility Paradox: Achieving Ambidexterity in High-Variety, Low-Volume Manufacturing," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 19(1), pages 69-86, March.
    11. Lyons, Andrew Charles & Um, Juneho & Sharifi, Hossein, 2020. "Product variety, customisation and business process performance: A mixed-methods approach to understanding their relationships," International Journal of Production Economics, Elsevier, vol. 221(C).
    12. Menezes, Mozart B.C. & Pinto, Roberto, 2022. "Product proliferation, cannibalisation, and substitution: A first look into entailed risk and complexity," International Journal of Production Economics, Elsevier, vol. 243(C).
    13. Guenther, Miriam & Guenther, Peter, 2021. "The complex firm financial effects of customer satisfaction improvements," International Journal of Research in Marketing, Elsevier, vol. 38(3), pages 639-662.
    14. Menezes, Mozart B.C. & Ruiz-Hernández, Diego & Chen, Yen-Tsang, 2021. "On the validity and practical relevance of a measure for structural complexity," International Journal of Production Economics, Elsevier, vol. 240(C).
    15. Menezes, Mozart B.C. & Jalali, Hamed & Lamas, Alejandro, 2021. "One too many: Product proliferation and the financial performance in manufacturing," International Journal of Production Economics, Elsevier, vol. 242(C).
    16. Guo, Feng & Zou, Bo & Zhang, Xiaofei & Bo, Qingwen & Li, Kai, 2020. "Financial slack and firm performance of SMMEs in China: Moderating effects of government subsidies and market-supporting institutions," International Journal of Production Economics, Elsevier, vol. 223(C).
    17. Liu, Zhi & Li, Kevin W. & Li, Bang-Yi & Huang, Jun & Tang, Juan, 2019. "Impact of product-design strategies on the operations of a closed-loop supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 124(C), pages 75-91.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    2. Van den Broeke, Maud & De Baets, Shari & Vereecke, Ann & Baecke, Philippe & Vanderheyden, Karlien, 2019. "Judgmental forecast adjustments over different time horizons," Omega, Elsevier, vol. 87(C), pages 34-45.
    3. Eksoz, Can & Mansouri, S. Afshin & Bourlakis, Michael, 2014. "Collaborative forecasting in the food supply chain: A conceptual framework," International Journal of Production Economics, Elsevier, vol. 158(C), pages 120-135.
    4. Petropoulos, Fotios & Fildes, Robert & Goodwin, Paul, 2016. "Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 842-852.
    5. Baecke, Philippe & De Baets, Shari & Vanderheyden, Karlien, 2017. "Investigating the added value of integrating human judgement into statistical demand forecasting systems," International Journal of Production Economics, Elsevier, vol. 191(C), pages 85-96.
    6. Hyoduk Shin & Tunay I. Tunca, 2010. "Do Firms Invest in Forecasting Efficiently? The Effect of Competition on Demand Forecast Investments and Supply Chain Coordination," Operations Research, INFORMS, vol. 58(6), pages 1592-1610, December.
    7. Pennings, Clint L.P. & van Dalen, Jan & Rook, Laurens, 2019. "Coordinating judgmental forecasting: Coping with intentional biases," Omega, Elsevier, vol. 87(C), pages 46-56.
    8. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
    9. Sroginis, Anna & Fildes, Robert & Kourentzes, Nikolaos, 2023. "Use of contextual and model-based information in adjusting promotional forecasts," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1177-1191.
    10. Arvan, Meysam & Fahimnia, Behnam & Reisi, Mohsen & Siemsen, Enno, 2019. "Integrating human judgement into quantitative forecasting methods: A review," Omega, Elsevier, vol. 86(C), pages 237-252.
    11. Sechan Oh & Özalp Özer, 2013. "Mechanism Design for Capacity Planning Under Dynamic Evolutions of Asymmetric Demand Forecasts," Management Science, INFORMS, vol. 59(4), pages 987-1007, April.
    12. Bharadwaj Kadiyala & Özalp Özer & Alain Bensoussan, 2020. "A Mechanism Design Approach to Vendor Managed Inventory," Management Science, INFORMS, vol. 66(6), pages 2628-2652, June.
    13. Lu, Jizhou & Feng, Gengzhong & Shum, Stephen & Lai, Kin Keung, 2021. "On the value of information sharing in the presence of information errors," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1139-1152.
    14. Babai, Zied & Boylan, John E. & Kolassa, Stephan & Nikolopoulos, Konstantinos, 2016. "Supply chain forecasting: Theory, practice, their gap and the futureAuthor-Name: Syntetos, Aris A," European Journal of Operational Research, Elsevier, vol. 252(1), pages 1-26.
    15. A A Syntetos & N C Georgantzas & J E Boylan & B C Dangerfield, 2011. "Judgement and supply chain dynamics," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1138-1158, June.
    16. Noam Shamir & Hyoduk Shin, 2016. "Public Forecast Information Sharing in a Market with Competing Supply Chains," Management Science, INFORMS, vol. 62(10), pages 2994-3022, October.
    17. Liu, Hao & Jiang, Wei & Feng, Gengzhong & Chin, Kwai-Sang, 2020. "Information leakage and supply chain contracts," Omega, Elsevier, vol. 90(C).
    18. Fu, Ke & Wang, Ce & Xu, Jiayan, 2022. "The impact of trade credit on information sharing in a supply chain," Omega, Elsevier, vol. 110(C).
    19. Ma, Yungao & Wang, Nengmin & He, Zhengwen & Lu, Jizhou & Liang, Huigang, 2015. "Analysis of the bullwhip effect in two parallel supply chains with interacting price-sensitive demands," European Journal of Operational Research, Elsevier, vol. 243(3), pages 815-825.
    20. Fildes, Robert & Goodwin, Paul & Onkal, Dilek, 2015. "Information use in supply chain forecasting," MPRA Paper 66034, University Library of Munich, Germany.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:proeco:v:186:y:2017:i:c:p:123-131. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.