American Institute of Mathematical Sciences

Advanced
doi: 10.3934/jimo.2018175

Optimal pricing and inventory strategies for introducing a new product based on demand substitution effects

Zhijie Sasha Dong 1, , Wei Chen 2, , Qing Zhao 3, and  Jingquan Li 2,,

1. 

Ingram School of Engineering, Texas State University, San Marcos, TX 78666, USA
2. 

School of Management and Engineering, Nanjing University, Nanjing, China 210093
3. 

Amazon, Seattle, WA 98109, USA

* Corresponding author: Jingquan Li

Received  July 2017 Revised  August 2018 Published  December 2018

This paper studies a single-period inventory-pricing problem with two substitutable products, which is very important in the area of Operations Management but has received little attention. The proposed problem focuses on determining the optimal price of the existing product and the inventory level of the new product. Inspired by practice, the problem considers various pricing strategies for the existing product as well as the cross elasticity of demand between existing and new products. A mathematical model has been developed for different pricing strategies to maximize the expected profit. It has been proven that the objective function is concave and there exists the unique optimal solution. Different sets of computational examples are conducted to show that the optimal pricing and inventory strategy generated by the model can increase profits.

Keywords: Inventory, pricing, optimal strategy, new product, demand substitution.
Mathematics Subject Classification: Primary: 90B05; Secondary: 91B24, 91B26.
Citation: Zhijie Sasha Dong, Wei Chen, Qing Zhao, Jingquan Li. Optimal pricing and inventory strategies for introducing a new product based on demand substitution effects. Journal of Industrial & Management Optimization, doi: 10.3934/jimo.2018175
References:
[1]

M. Akan, B. Ata and R. C. Savaskan-Ebert, Dynamic pricing of remanufacturable products under demand substitution: a product life cycle model, Annals of Operations Research, 211 (2013), 1-25.  doi: 10.1007/s10479-013-1409-1.  Google Scholar

[2]

G. Aydin and E. L. Porteus, Joint inventory and pricing decisions for an assortment, Operations Research, 56 (2008), 1247-1255.  doi: 10.1287/opre.1080.0562.  Google Scholar

[3]

D. Honhon, V. Gaur and S. Seshadri, Assortment planning and inventory decisions under stockout-based substitution, Operations Research, 58 (2010), 1364-1379.  doi: 10.1287/opre.1090.0805.  Google Scholar

[4]

C. C. Hsieh and C. H. Wu, Coordinated decisions for substitutable products in a common retailer supply chain, European Journal of Operational Research, 196 (2009), 273-288.  doi: 10.1016/j.ejor.2008.02.019.  Google Scholar

[5]

M. Karakul, Joint pricing and procurement of fashion products in the existence of clearance markets, International Journal of Production Economics, 114 (2008), 487-506.  doi: 10.1016/j.ijpe.2007.03.026.  Google Scholar

[6]

M. Karakul and L. M. A. Chan, Analytical and managerial implications of integrating product substitutability in the joint pricing and procurement problem, European Journal of Operational Research, 190 (2008), 179-204.  doi: 10.1016/j.ejor.2007.06.026.  Google Scholar

[7]

M. Karakul and L. M. A. Chan, Joint pricing and procurement of substitutable products with random demands - A technical note, European Journal of Operational Research, 201 (2010), 324-328.  doi: 10.1016/j.ejor.2009.03.030.  Google Scholar

[8]

M. Khouja, A. Mehrez and G. Rabinowitz, A two-item newsboy problem with substitutability, International Journal of Production Economics, 44 (1996), 267-275.  doi: 10.1016/0925-5273(96)80002-V.  Google Scholar

[9]

Y. Lan, Z. Liu and B. Niu, Pricing and design of after-sales service contract: The value of mining asymmetric sales cost information, Asia-Pacific Journal of Operational Research, 34 (2017), 1740002. doi: 10.1142/S0217595917400024.  Google Scholar

[10]

Y. Lan, R. Zhao and W. Tang, A fuzzy supply chain contract problem with pricing and warranty, Fuzzy Systems, 26 (2014), 1527-1538.  doi: 10.3233/IFS-130836.  Google Scholar

[11]

X. Li, G. Sun and Y. Li, A multi-period ordering and clearance pricing model considering the competition between new and out-of-season products, Annals of Operations Research, 242 (2016), 207-221.  doi: 10.1007/s10479-013-1498-x.  Google Scholar

[12]

S. Mou, D. J. Robb and N. DeHoratius, Retail store operations: Literature review and research directions, European Journal of Operational Research, 265 (2018), 399-422.  doi: 10.1016/j.ejor.2017.07.003.  Google Scholar

[13]

M. Nagarajan and S. Rajagopalan, Inventory models for substitutable products: Optimal policies and heuristics, Management Science, 54 (2008), 1453-1466.  doi: 10.1287/mnsc.1080.0871.  Google Scholar

[14]

X. A. Pan and D. Honhon, Assortment planning for vertically differentiated products, Production and Operations Management, 21 (2012), 253-275.  doi: 10.1111/j.1937-5956.2011.01259.x.  Google Scholar

[15]

A. Sainathan, Pricing and replenishment of competing perishable product variants under dynamic demand substitution, Production and Operations Management, 22 (2013), 1157-1181.  doi: 10.1111/poms.12004.  Google Scholar

[16]

Z. Sazvar, S. M. J. Mirzapour Al-e-hashem, K. Govindan and B. Bahli, A novel mathematical model for a multi-period, multi-product optimal ordering problem considering expiry dates in a FEFO system, Transportation Research Part E: Logistics and Transportation Review, 93 (2016), 232-261.  doi: 10.1016/j.tre.2016.04.011.  Google Scholar

[17]

H. Shin, S. Park, E. Lee and W. C. Benton, A classification of the literature on the planning of substitutable products, European Journal of Operational Research, 246 (2015), 686-699.  doi: 10.1016/j.ejor.2015.04.013.  Google Scholar

show all references

References:
[1]

M. Akan, B. Ata and R. C. Savaskan-Ebert, Dynamic pricing of remanufacturable products under demand substitution: a product life cycle model, Annals of Operations Research, 211 (2013), 1-25.  doi: 10.1007/s10479-013-1409-1.  Google Scholar

[2]

G. Aydin and E. L. Porteus, Joint inventory and pricing decisions for an assortment, Operations Research, 56 (2008), 1247-1255.  doi: 10.1287/opre.1080.0562.  Google Scholar

[3]

D. Honhon, V. Gaur and S. Seshadri, Assortment planning and inventory decisions under stockout-based substitution, Operations Research, 58 (2010), 1364-1379.  doi: 10.1287/opre.1090.0805.  Google Scholar

[4]

C. C. Hsieh and C. H. Wu, Coordinated decisions for substitutable products in a common retailer supply chain, European Journal of Operational Research, 196 (2009), 273-288.  doi: 10.1016/j.ejor.2008.02.019.  Google Scholar

[5]

M. Karakul, Joint pricing and procurement of fashion products in the existence of clearance markets, International Journal of Production Economics, 114 (2008), 487-506.  doi: 10.1016/j.ijpe.2007.03.026.  Google Scholar

[6]

M. Karakul and L. M. A. Chan, Analytical and managerial implications of integrating product substitutability in the joint pricing and procurement problem, European Journal of Operational Research, 190 (2008), 179-204.  doi: 10.1016/j.ejor.2007.06.026.  Google Scholar

[7]

M. Karakul and L. M. A. Chan, Joint pricing and procurement of substitutable products with random demands - A technical note, European Journal of Operational Research, 201 (2010), 324-328.  doi: 10.1016/j.ejor.2009.03.030.  Google Scholar

[8]

M. Khouja, A. Mehrez and G. Rabinowitz, A two-item newsboy problem with substitutability, International Journal of Production Economics, 44 (1996), 267-275.  doi: 10.1016/0925-5273(96)80002-V.  Google Scholar

[9]

Y. Lan, Z. Liu and B. Niu, Pricing and design of after-sales service contract: The value of mining asymmetric sales cost information, Asia-Pacific Journal of Operational Research, 34 (2017), 1740002. doi: 10.1142/S0217595917400024.  Google Scholar

[10]

Y. Lan, R. Zhao and W. Tang, A fuzzy supply chain contract problem with pricing and warranty, Fuzzy Systems, 26 (2014), 1527-1538.  doi: 10.3233/IFS-130836.  Google Scholar

[11]

X. Li, G. Sun and Y. Li, A multi-period ordering and clearance pricing model considering the competition between new and out-of-season products, Annals of Operations Research, 242 (2016), 207-221.  doi: 10.1007/s10479-013-1498-x.  Google Scholar

[12]

S. Mou, D. J. Robb and N. DeHoratius, Retail store operations: Literature review and research directions, European Journal of Operational Research, 265 (2018), 399-422.  doi: 10.1016/j.ejor.2017.07.003.  Google Scholar

[13]

M. Nagarajan and S. Rajagopalan, Inventory models for substitutable products: Optimal policies and heuristics, Management Science, 54 (2008), 1453-1466.  doi: 10.1287/mnsc.1080.0871.  Google Scholar

[14]

X. A. Pan and D. Honhon, Assortment planning for vertically differentiated products, Production and Operations Management, 21 (2012), 253-275.  doi: 10.1111/j.1937-5956.2011.01259.x.  Google Scholar

[15]

A. Sainathan, Pricing and replenishment of competing perishable product variants under dynamic demand substitution, Production and Operations Management, 22 (2013), 1157-1181.  doi: 10.1111/poms.12004.  Google Scholar

[16]

Z. Sazvar, S. M. J. Mirzapour Al-e-hashem, K. Govindan and B. Bahli, A novel mathematical model for a multi-period, multi-product optimal ordering problem considering expiry dates in a FEFO system, Transportation Research Part E: Logistics and Transportation Review, 93 (2016), 232-261.  doi: 10.1016/j.tre.2016.04.011.  Google Scholar

[17]

H. Shin, S. Park, E. Lee and W. C. Benton, A classification of the literature on the planning of substitutable products, European Journal of Operational Research, 246 (2015), 686-699.  doi: 10.1016/j.ejor.2015.04.013.  Google Scholar

Figure 1.  Effect of the extant product's price on the new product's order quantity
Figure Options

Download full-size image

Download as PowerPoint slide

Figure 2.  Effect of the extant product's price on the expected profit
Figure Options

Download full-size image

Download as PowerPoint slide

Table 1.  Effect of the inventory level of the existing product on the retailer's optimal policy and the expected profit
Strategy Variables Values
$ Q_1 $ 160 170 180 190 200 210 220 230 240 250
Unchanged $ Q_2 $ 840 830 820 810 800 800 800 800 800 800
$ s_1 (\$)$ 12 12 12 12 12 12 12 12 12 12
$ EP (\$)$ 5280 5360 5440 5520 5600 5600 5600 5600 5600 5600
$ RP (\$)$ 100.0 100.0 100.0 100.0 100.0 101.0 102.0 103.0 104.0 105.0
Decreased $ Q_2 $ 840 830 820 810 800 790 780 770 760 746.6
$ s_1 (\$)$ 12 12 12 12 12 11.7 11.4 11.1 10.8 10.5
$ EP (\$)$ 5280 5360 5440 5520 5600 5617 5628 5633 5632 5611.4
$ RP (\$)$ 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 99.7
Table Options

Download as excel

Strategy Variables Values
$ Q_1 $ 160 170 180 190 200 210 220 230 240 250
Unchanged $ Q_2 $ 840 830 820 810 800 800 800 800 800 800
$ s_1 (\$)$ 12 12 12 12 12 12 12 12 12 12
$ EP (\$)$ 5280 5360 5440 5520 5600 5600 5600 5600 5600 5600
$ RP (\$)$ 100.0 100.0 100.0 100.0 100.0 101.0 102.0 103.0 104.0 105.0
Decreased $ Q_2 $ 840 830 820 810 800 790 780 770 760 746.6
$ s_1 (\$)$ 12 12 12 12 12 11.7 11.4 11.1 10.8 10.5
$ EP (\$)$ 5280 5360 5440 5520 5600 5617 5628 5633 5632 5611.4
$ RP (\$)$ 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 99.7
Table 2.  Effect of the salvage value of the existing product on the retailer's optimal policy and the expected profit
Strategy Variables Values
$ h_1 $ -5 -4 -3 -2 -1 0 1 2 3 4
Unchanged $ Q_2 $ 800 800 800 800 800 800 800 800 800 800
$ s_1 (\$)$ 12 12 12 12 12 12 12 12 12 12
$ EP (\$)$ 5350 5400 5450 5500 5550 5600 5650 5700 5750 5800
$ RP (\$)$ 105.0 105.0 105.0 105.0 105.0 105.0 105.0 105.0 105.0 105.0
Decreased $ Q_2 $ 750 750 750 750 750 750 750 750 750 750
$ s_1 (\$)$ 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5
$ EP (\$)$ 5625 5625 5625 5625 5625 5625 5625 5625 5625 5625
$ RP (\$)$ 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Table Options

Download as excel

Strategy Variables Values
$ h_1 $ -5 -4 -3 -2 -1 0 1 2 3 4
Unchanged $ Q_2 $ 800 800 800 800 800 800 800 800 800 800
$ s_1 (\$)$ 12 12 12 12 12 12 12 12 12 12
$ EP (\$)$ 5350 5400 5450 5500 5550 5600 5650 5700 5750 5800
$ RP (\$)$ 105.0 105.0 105.0 105.0 105.0 105.0 105.0 105.0 105.0 105.0
Decreased $ Q_2 $ 750 750 750 750 750 750 750 750 750 750
$ s_1 (\$)$ 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5
$ EP (\$)$ 5625 5625 5625 5625 5625 5625 5625 5625 5625 5625
$ RP (\$)$ 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
[1]

Po-Chung Yang, Hui-Ming Wee, Shen-Lian Chung, Yong-Yan Huang. Pricing and replenishment strategy for a multi-market deteriorating product with time-varying and price-sensitive demand. Journal of Industrial & Management Optimization, 2013, 9 (4) : 769-787. doi: 10.3934/jimo.2013.9.769
[2]

Yanyi Xu, Arnab Bisi, Maqbool Dada. New structural properties of inventory models with Polya frequency distributed demand and fixed setup cost. Journal of Industrial & Management Optimization, 2017, 13 (2) : 931-945. doi: 10.3934/jimo.2016054
[3]

Yujing Wang, Changjun Yu, Kok Lay Teo. A new computational strategy for optimal control problem with a cost on changing control. Numerical Algebra, Control & Optimization, 2016, 6 (3) : 339-364. doi: 10.3934/naco.2016016
[4]

Xiaoming Yan, Ping Cao, Minghui Zhang, Ke Liu. The optimal production and sales policy for a new product with negative word-of-mouth. Journal of Industrial & Management Optimization, 2011, 7 (1) : 117-137. doi: 10.3934/jimo.2011.7.117
[5]

Bing-Bing Cao, Zhi-Ping Fan, Tian-Hui You. The optimal pricing and ordering policy for temperature sensitive products considering the effects of temperature on demand. Journal of Industrial & Management Optimization, 2019, 15 (3) : 1153-1184. doi: 10.3934/jimo.2018090
[6]

Ruopeng Wang, Jinting Wang, Chang Sun. Optimal pricing and inventory management for a loss averse firm when facing strategic customers. Journal of Industrial & Management Optimization, 2018, 14 (4) : 1521-1544. doi: 10.3934/jimo.2018019
[7]

Wai-Ki Ching, Tang Li, Sin-Man Choi, Issic K. C. Leung. A tandem queueing system with applications to pricing strategy. Journal of Industrial & Management Optimization, 2009, 5 (1) : 103-114. doi: 10.3934/jimo.2009.5.103
[8]

Ka Wo Lau, Yue Kuen Kwok. Optimal execution strategy of liquidation. Journal of Industrial & Management Optimization, 2006, 2 (2) : 135-144. doi: 10.3934/jimo.2006.2.135
[9]

Jia Shu, Zhengyi Li, Weijun Zhong. A market selection and inventory ordering problem under demand uncertainty. Journal of Industrial & Management Optimization, 2011, 7 (2) : 425-434. doi: 10.3934/jimo.2011.7.425
[10]

Fengjun Wang, Qingling Zhang, Bin Li, Wanquan Liu. Optimal investment strategy on advertisement in duopoly. Journal of Industrial & Management Optimization, 2016, 12 (2) : 625-636. doi: 10.3934/jimo.2016.12.625
[11]

Mitali Sarkar, Young Hae Lee. Optimum pricing strategy for complementary products with reservation price in a supply chain model. Journal of Industrial & Management Optimization, 2017, 13 (3) : 1553-1586. doi: 10.3934/jimo.2017007
[12]

Xiangyu Gao, Yong Sun. A new heuristic algorithm for laser antimissile strategy optimization. Journal of Industrial & Management Optimization, 2012, 8 (2) : 457-468. doi: 10.3934/jimo.2012.8.457
[13]

Li Deng, Wenjie Bi, Haiying Liu, Kok Lay Teo. A multi-stage method for joint pricing and inventory model with promotion constrains. Discrete & Continuous Dynamical Systems - S, 2018, 0 (0) : 0-0. doi: 10.3934/dcdss.2020097
[14]

Guibin Lu, Qiying Hu, Youying Zhou, Wuyi Yue. Optimal execution strategy with an endogenously determined sales period. Journal of Industrial & Management Optimization, 2005, 1 (3) : 289-304. doi: 10.3934/jimo.2005.1.289
[15]

Jianbin Li, Ruina Yang, Niu Yu. Optimal capacity reservation policy on innovative product. Journal of Industrial & Management Optimization, 2013, 9 (4) : 799-825. doi: 10.3934/jimo.2013.9.799
[16]

Konstantina Skouri, Ioannis Konstantaras. Two-warehouse inventory models for deteriorating products with ramp type demand rate. Journal of Industrial & Management Optimization, 2013, 9 (4) : 855-883. doi: 10.3934/jimo.2013.9.855
[17]

Wei Liu, Shiji Song, Cheng Wu. Single-period inventory model with discrete stochastic demand based on prospect theory. Journal of Industrial & Management Optimization, 2012, 8 (3) : 577-590. doi: 10.3934/jimo.2012.8.577
[18]

Magfura Pervin, Sankar Kumar Roy, Gerhard Wilhelm Weber. A two-echelon inventory model with stock-dependent demand and variable holding cost for deteriorating items. Numerical Algebra, Control & Optimization, 2017, 7 (1) : 21-50. doi: 10.3934/naco.2017002
[19]

Lizhao Yan, Fei Xu, Yongzeng Lai, Mingyong Lai. Stability strategies of manufacturing-inventory systems with unknown time-varying demand. Journal of Industrial & Management Optimization, 2017, 13 (4) : 2033-2047. doi: 10.3934/jimo.2017030
[20]

Katherinne Salas Navarro, Jaime Acevedo Chedid, Whady F. Florez, Holman Ospina Mateus, Leopoldo Eduardo Cárdenas-Barrón, Shib Sankar Sana. A collaborative EPQ inventory model for a three-echelon supply chain with multiple products considering the effect of marketing effort on demand. Journal of Industrial & Management Optimization, 2017, 13 (5) : 1-14. doi: 10.3934/jimo.2019020

2018 Impact Factor: 1.025

Tools

Metrics

  • PDF downloads (64)
  • HTML views (708)
  • Cited by (0)

Other articles
by authors

[Back to Top]

Copyright © 2019 American Institute of Mathematical Sciences