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研究生: Praveen Vijaya Raj Pushpa Raj
Praveen Vijaya Raj Pushpa Raj
論文名稱: 考慮產品替代性與搶購行為的存貨模型
Inventory Models for Product Substitution under Panic Buying Behavior
指導教授: 曹譽鐘
Yu-Chung Tsao
口試委員: Yu-Chung Tsao
Yu-Chung Tsao
Kung-Jeng Wang
Kung-Jeng Wang
Vincent F. Yu
Vincent F. Yu
Shi-Woei Lin
Shi-Woei Lin
Yi-Kuei Lin
Yi-Kuei Lin
Kuo-Wei Su
Kuo-Wei Su
Tsung-Hui Chen
Tsung-Hui Chen
學位類別: 博士
Doctor
系所名稱: 管理學院 - 工業管理系
Department of Industrial Management
論文出版年: 2019
畢業學年度: 107
語文別: 英文
論文頁數: 91
中文關鍵詞: 存貨管理搶購消費產品替代顧客區隔混合整數規劃
外文關鍵詞: inventory management, panic buying, product substitution, customer segmentation, mixed-integer programming
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  • 在消費者的搶購狀況之下,以實際可用的產品去滿足這些需求是一個複雜的問題。而在現實情況中,大多數的零售商或是消費者在面臨搶購的狀況是能接受替代產品的。本研究考慮的模型具兩個時段,且考慮由公司帶動與消費者帶動的產品替代性情況。於所提出的模型中,搶購的消費行為發生在第一個時間區段,而供應的中斷則是發生在第二個時間區段。 在本文中我們討論三個問題。1. 為了讓批發商的利潤最大化,零售商被劃分為高指數(高價值)與低指數(低價值)顧客。在滿足低指數顧客的需求之前,批發商會先試圖滿足高指數客戶的搶購消費行為。此外,我們也考量一品牌公司生產多種產品下所帶動的替代產品狀況。2. 考量到顧客區隔與搶購行為時,我們考慮在公司帶動下不同的重量與品牌所產生的產品替代性情況且同時滿足批發商利潤最大化。3. 為了最大化零售商的利潤,我們考慮在消費者帶動下不同的重量與品牌所產生的產品替代性情況,並且考慮同時搶購消費行為與貨架的空間容量。針對各個問題,決策包括訂單和替代數量,以便在供應鏈中提供更好的分配。我們亦研究供應中斷的程度與搶購率對利潤和決策的影響,以獲得相關的管理意涵。最後,我們也進行具產品替代性與不具產品替代性的模型比較。


    Under conditions of consumer panic buying, satisfying demand with the available products is a complex problem. In reality, most retailers/customers accept alternative products during panic situations. This study considers the case of firm-driven and customer driven substitution of products over two time-periods. In the proposed model, panic behavior emerged in the first time-period and interruption in supply occurred in the second time period.
    In this dissertation, we discussed three problems. 1) To maximize the wholesaler’s total profit the retailers are segmented into the high (valuable) and low indexed (less valuable) customers. Before meeting the demand of low-index customers, wholesalers attempt to satiate high-index customer’s panic buying behavior. Also, we consider firm driven product substitution for a single brand with multiple products. 2) To maximize the wholesaler profit, we consider firm driven product substitution in different weights and brands considering customer segmentation and panic buying behavior. 3) To maximize the retailer profit, we consider brand and weight based customer-driven product substitution considering panic buying and shelf space capacity. For each problem, the decisions are to determine the order and substitution quantities to provide better distribution in the supply chain. To gain managerial insights, we also examined the influence of both the degree of interruption in supply and panic rate on profits and decisions. Finally, we compare the models with and without substitution.

    TABLE OF CONTENTS 摘要.................................................................................................................................................. I ABSTRACT ................................................................................................................................... I I ACKNOWLEDGEMENT .......................................................................................................... I I I TABLE OF CONTENTS .............................................................................................................. IV LIST OF FIGURES ................................................................................................................... V I I LIST OF TABLES ......................................................................................................................... X LIST OF ABBREVIATION ...................................................................................................... X I I CHAPTER 1 ................................................................................................................................... 1 INTRODUCTION .......................................................................................................................... 1 1.1. Background and Motivation ............................................................................................. 1 1.2. Research Objective ........................................................................................................... 3 1.3. Organization of Dissertation ............................................................................................. 4 CHAPTER 2 ................................................................................................................................... 6 LITERATURE REVIEW ............................................................................................................... 6 2.1. Panic buying and customer segmentation .............................................................................. 6 2.2. Product substitution ............................................................................................................. 7 CHAPTER 3 ................................................................................................................................. 10 PRODUCT SUBSTITUTION WITH CUSTOMER SEGMENTATION UNDER PANIC BUYING BEHAVIOR ................................................................................................................. 10 3.1. Problem definition and mathematical model .................................................................. 10 3.2. Numerical example ......................................................................................................... 16 3.3. Experimental Analysis .................................................................................................... 19 3.3.1. Impact of variation in interruption in supply …………...………………………19 3.3.1.1. Impact on total profit ………………………………………………………….20 3.3.1.2 Impact on percent of customer satisfaction obtained in HIS ………………….20 3.3.1.3 Impact on percentage of overall customer satisfaction obtained in retailers …21 3.3.1.4. Impact on inventory …………………………………………………………...22 V 3.3.2. Impact in constant interruption in supply for all products………………………23 3.3.3. Impact of variation in Rate of panic …………………………………………….24 3.3.3.1. Impact on total profit ………………………………………………………….24 3.3.3.2 Impact on percent of customer satisfaction obtained in high-index retailers .... 25 3.3.3.3 Impact on percentage of overall customer satisfaction obtained in retailers …26 3.3.3.4. Impact on inventory …………………………………………………………..27 3.4. Impact of price change ................................................................................................... 28 3.4.1. Impact on total profit ……………………………………………………………28 3.4.2 Impact on percent of customer satisfaction obtained in high-index retailers……28 . 3.4.3. Impact on percentage of overall customer satisfaction obtained in retailers …..30 3.4.4. Impact on inventory ……………………………………………………………...31 CHAPTER 4 ................................................................................................................................. 33 PRODUCT SUBSTITUTION IN DIFFERENT WEIGHTS AND BRANDS CONSIDERING CUSTOMER SEGMENTATION AND PANIC BUYING BEHAVIOR ................................ ... 33 4.1. Problem definition and mathematical model .................................................................. 33 4.2. Numerical example ......................................................................................................... 40 4.3. Numerical Analysis ........................................................................................................ 45 4.3.1. Instance 1 ............................................................................................................. 46 4.3.1.1 Influence on profit .............................................................................................. 46 4.3.1.2 Impact on the service level in high indexed stores ............................................. 47 4.3.1.3. Influence on the overall service level in stores ................................................. 47 4.3.1.4. Influence on inventory ....................................................................................... 48 4.3.2. Instance 2 ............................................................................................................. 49 4.3.2.1 Influence on profit .............................................................................................. 50 4.3.2.2 Impact on the service level in high indexed stores ............................................. 50 4.3.2.3. Influence on the overall service level in stores ................................................. 51 4.3.2.4. Influence on inventory ....................................................................................... 52 VI 4.3.3. Instance 3 ............................................................................................................. 53 4.3.3.1 Influence on profit .............................................................................................. 54 4.3.3.2. Influence on the overall service level in stores ................................................. 54 4.3.3.3. Influence on inventory ....................................................................................... 55 4.4. Impact of price change ................................................................................................... 56 4.4.1. Influence on profit ................................................................................................ 57 4.4.2. Influence on the overall service level in stores .................................................... 57 4.4.3. Influence on inventory .......................................................................................... 58 CHAPTER 5 ................................................................................................................................. 60 BRAND AND WEIGHT BASED PRODUCT SUBSTITUTION CONSIDERING PANIC BUYING AND SHELF SPACE CAPACITY 5.1. Problem Definition and Mathematical Model ................................................................ 60 5.2. Numerical example ......................................................................................................... 64 5.3. Numerical Analysis ........................................................................................................ 66 5.3.1. Instance 1 ............................................................................................................. 67 5.3.1.1 Influence on profit .............................................................................................. 67 5.3.1.2 Influence on inventory ........................................................................................ 67 5.3.1.3. Influence on additional units ............................................................................. 68 5.3.2. Instance 2 ............................................................................................................. 70 5.3.2.1 Influence on profit .............................................................................................. 70 5.3.2.2 Influence on inventory ........................................................................................ 70 5.3.2.3. Influence on additional units ............................................................................. 71 CHAPTER 6 ................................................................................................................................. 73 CONCLUSIONS AND FUTURE RESEARCH .......................................................................... 73 REFERENCES ............................................................................................................................. 75 COMPLETE LIST OF PUBLICATION ...................................................................................... 79

    REFERENCES
    1. Bassok Y., Anupindi. R., Akella R. 1999. “Single- period multiproduct inventory models with substitution”, Operations Research, 47, 632–642.
    2. Cheng C.H., Chen Y.S., 2009. “Classifying the segmentation of customer value via RFM model and RS theory”, Expert systems with Applications, 4176-4184.
    3. Chris Kitching. 2016. Hurricane Matthew sparks apocalyptic scenes in supermarkets as panicked shoppers stock up food and water. Mirror. http://www.mirror.co.uk/news/world-news/hurricane-matthew-sparks-apocalyptic-scenes-8989661, 07 October 2016.
    4. Chung-Lun Li, Panos Kouvelis. 1999. “Flexible and Risk-Sharing Supply Contracts Under Price Uncertainty”, Management Science, 45(10),1378-1398. 5. Corinne Purtill. 2017. “The economic case for price gouging.URL https://qz.com/1063188/hurricane-harvey-banning-price-gouging-is-bad-economics/”
    6. Desmet.P, Renaudin.V . 1998. “Estimation of product category sales responsiveness to allocated shelf space”, International Journal of Research in Marketing, 15, 443–457
    7. Dixit, A. K., R. S. Pindyck. 1994. “Investment under Uncertainty”, Princeton University Press, Princeton, NJ.
    8. Doyle Rice. 2016. “Super Typhoon Nepartak forecast to batter Taiwan. USA Today. http://www.usatoday.com/story/weather/2016/07/06/supertyphoon-nepartak-taiwan/86745634/” 06 July 2016.
    9. Dursun. A, Caber. M. 2016. “Using data mining techniques for profiling profitable hotel customers: An application of RFM analysis”, Tourism Management Perspectives 18 : 153–160.
    10. Dutta, P., Chakraborty, D. 2010. “Incorporating one-way substitution policy into the newsboy problem with imprecise customer demand”, European Journal of Operational Research, 200 (1), 99-110.
    11. Ervolina, T. Ettl, M. Lee, Y., and Peters, D. 2009. “Managing product availability in an assemble-to-order supply chain with multiple customer segments”, OR Spectrum, 31(1), 257–280.
    12. Fang, Y. and Shou, B. 2015. “Managing supply uncertainty under supply chain Cournot competition”, European Journal of Operational Research, 243, 156–176.
    13. Frontoni, E., Marinelli, F., Rosetti, R., Zingaretti, P. 2017. “Shelf space re-allocation for out of stock reduction”. Computers & Industrial Engineering, 106, 32-40.
    14. Gloy B. A., Akridge J. T., Preckel P. V.1997. “Customer lifetime value: An application in the rural petroleum market”. Agribusiness 13(3): 335–347. 15. Gümüs. M., Kaminsky. P.M., Mathur. S. 2016. “The Impact of Product Substitution and Retail Capacity on the Timing and Depth of Price Promotions: Theory and Evidence”. International Journal of Production Research, 54(7), 2108-2135
    76
    16. Hawkes, V. A., 2000. “The heart of the matter: The challenge of customer lifetime value”. CRM Forum Resources, 1–10.
    17. He, B. Huang, H., and Yuan, K. 2015. “The comparison of two procurement strategies in the presence of interruption in supply”, Computers & Industrial Engineering, 85, 296–305.
    18. Hosseini, S. M., Maleki, A.,Gholamian, M. R. 2010. “Cluster analysis using data mining approach to develop CRM methodology to assess the customer loyalty”, Expert Systems with Applications, 37: 5259–5264.
    19. Hsu, A., Bassok, Y. 1999. “Random Yield and Random Demand in a Production System with Downward Substitution”. Operations Research, 47 (2), 277-290.
    20. Hsu, V.N. Li C.-N., and Xiao W. 2005. “Dynamic lot size problems with one-way product substitution”, IIE Transactions, 37, 201-21.
    21. Huang, D., Zhao, Q. H., Fan, C.C. 2010. “Simulation-based Optimization of Inventory Model with Products Substitution”. International Handbooks on Information Systems, Part 3, 297-312.
    22. Hübner, A., Schaal, K. 2017. “An integrated assortment and shelf-space optimization model with demand substitution and space-elasticity effects”. European Journal of Operational Research, 261 (1), 302-316.
    23. Hughes, A. M.1994. “Strategic database marketing”. Chicago, USA: Probus Publishing Company
    24. Khajvand, M., Zolfaghar, K., Ashoori, S., Alizadeh, S. 2011. “Estimating customer lifetime value based on RFM analysis of customer purchase behavior: Case study”. Procedia Computer Science, 3, 57–63.
    25. Kotler, P. and Armstrong, G. 1996. “Principles of Marketing”, 7th ed., Englewood Cliffs, NJ: Prentice-Hall.
    26. Krishnan. H., Kapuscinski. R., David.A.Butz. 2004. “Coordinating Contracts for Decentralized Supply Chains”. Management Science 50, 1, 48–63.
    27. Lang J. C., 2010. “Production and inventory management with substitutions”. Berlin, Springer.
    28. Liu. Q., van Ryzin .G. 2011. “Strategic Capacity Rationing when Customers Learn”, Manufacturing & Service Operations Management, 13(1): 89–107. 29. Maclaughlin, S. “Japanese supermarket shelves are left completely empty as panic buying takes hold after deadly earthquake”, Daily mail Online, (2016). http://www.dailymail.co.uk/news/article-3545172/Japanese-locals-panic-buy-supplies-shelves-leaving-queue-food-water-two-deadly-earthquakes-kill-41-people.html. 18 April 2016. 30. Mac Slavo 2017 http://www.zerohedge.com/news/2017-01-19/empty-shelves-madness-america-minor-winter-storm-drove-people-panic-buying-food-and- . 19 January.
    77
    31. Mardan, E. Sadegh Amalnick, M. Rabbani, M., and Jolai, F. “A robust optimization approach for an inventory problem with emergency ordering and product substitution in an uncertain environment: A case study in pharmaceutical industry”, Scientia Iranica, Transactions E: Industrial Engineering, 24, 1533-1546 (2017).
    32. McGillivray. A.R., Silver E.A.. 1978. “Some concepts for inventory control under substitutable demands”. INFOR 16, 47–63.
    33. Miglautsch, J. R. 2000. “Thoughts on RFM scoring”. Journal of Database Marketing, 8(1), 67–72.
    34. Mishra, Raghunathan. 2004. “Retailer- vs. Vendor-Managed Inventory and Brand Competition”. Management Science 50, 4, 445–457.
    35. “Motorists resort to panic buying”, http://www.thehindu.com/news/national/andhra-pradesh/motorists-resort-to-panic-buying/article7710190.ece.1 October 2015. The Hindu, (2015).
    36. Nagarajan, S. and Rajagopalan, S. 2008. “Inventory Models for Substitutable Products: Optimal Policies and Heuristics”. Management Science 54, 1453–1466.
    37. Netessine, S. and Rudi, N. “Centralized and competitive inventory models with demand substitution”, Operations Research, 51( 2), 329–335 (2003).
    38. Nistorescu, T. and Silvia, P. 2009. “Marketing strategies used in crisis - case study”, MPRA Study 17743, University Library of Munich, Germany.
    39. “NOC dispatches fuel exceeding daily demand”, https://thehimalayan-times.com/nepal/noc-dispatches-fuel-exceeding-daily-demand/. The Himalayan Times, (2015).
    40. Ovchinnikov, A., J. M. Milner. 2012. “Revenue management with end-of-period discounts in the presence of customer learning”, Production and operations management, 21(1), 69-84.
    41. Pelin Bayindir. Z., Nesim. E, Refik. G. 2007. Assessing the benefits of remanufacturing option under one-way substitution and capacity constraint. Computers & Operations Research 34, 487–514.
    42. Pentico, D. W. 2008. “The assortment problem: A survey”, European Journal of Operational Research, 190, 295-309.
    43. Rajaram, K., Tang, C. S. 2001. “The impact of product substitution on retail merchandising, European Journal of Operational Research 135, 582–601.
    44. Rao, U. S. Swaminathan, J. M., and Zhang, J. “Multi-product inventory planning with downward substitution, stochastic demand and setup costs”, IIE Transactions, 36, 59–71 (2004).
    78
    45. Sang-Won Kim, Peter C. Bell. 2015. “A note on the optimal pricing and production decisions with price-driven substitution”, International Transactions in Operational Research.22 (6), 1097–1116.
    46. Smith, S. A., Agrawal, N. 2000. “Management of Multi-Item Retail Inventory Systems with Demand Substitution”, Operations Research, 48 (1), 50-64.
    47. Shah. J., Avittathur. B. 2007. “The retailer multi – item inventory problem with demand cannibalization and substitution”. International Journal of Production Economics 106, 104-114.
    48. Shen Z.M., Su X., 2007. “Customer Behavior Modeling in Revenue Management and Auctions: A Review and New Research Opportunities”, Production and Operations Management 16(6), 713–728.
    49. Shou, B. Xiong. H., and Shen, Z.M. 2016. “Consumer panic buying and quota policy under interruption in supply disruption”, working study.
    50. Stahl. Heinz K, Kurt Matzler, Hans H. Hinterhuber. 2003. “Linking customer lifetime value with shareholder value,” Industrial Marketing Management, 32,267 – 279. 51. The Economic Times. 2018. Delhi govt likely to announce policy to put a cap on hospitals' profits this week, URL https://economictimes.indiatimes.com/industry/healthcare/biotech/ healthcare/delhi-govt-likely-to-put-a-cap-on-hospital-profits-thisweek/articleshow/6404 7994.cms.
    52. Transchel, S. 2017. “Inventory management under price-based and stock out based substitution”, European Journal of Operational Research, 262, 996–1008.
    53. Wei, J. T., Lin, S. Y., & Wu, H. H. 2010. “A review of the application of RFM model”. African Journal of Business Management, 4(19), 4199–4206.
    54. Yannick Deflem, Nieuwenhuyse, I. Van. 2013. “Managing inventories with one-way substitution : A newsvendor analysis”. European Journal of Operational Research, 228(3), 484–493.
    55. Yglesias, Matthew., 2012. The case for price gouging. URL http://www.slate.com/articles/business/moneybox/2012/10/sandy_price_gouging_anti_gouging_laws_make_natural_disasters_worse.html.
    56. Yu, Y. Shou, B. Ni, Y., and Chen, L. 2016. “Optimal production, pricing, and substitution policies in continuous review production-inventory systems”, European Journal of Operational Research, 260, 631–649.
    57. Yucel, E. Karaesmen, F. Salman, F.S., and Turkay, M. 2009. “Optimizing product assortment under customer-driven demand substitution”, European Journal of Operational Research, 199, 759–768.

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