American Institute of Mathematical Sciences

doi: 10.3934/jimo.2018090

The optimal pricing and ordering policy for temperature sensitive products considering the effects of temperature on demand

 1 School of Management, Guangzhou University, Guangzhou 510006, China 2 Department of Information Management and Decision Sciences, School of Business Administration, Northeastern University, Shenyang 110167, China 3 State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China

* Corresponding author: ZHI-PING FAN

Received  April 2017 Revised  January 2018 Published  July 2018

Fund Project: The study is supported in part by the National Natural Science Foundation of China (Project No. 71571039) and the 111 Project (B16009)

Temperature sensitive products such as down jackets are commonly used in customers' daily life. The market demand for these products is directly related to the average temperature during the selling period. This study focuses on joint pricing and ordering decisions for temperature sensitive products. First, the four types of temperature sensitive products are considered: HTSPs, MTSPs, LTSPs and HLTSPs. By analyzing the demand characteristics of these types of products, four corresponding demand functions are constructed. Then, the four joint pricing and ordering decision models are constructed considering the temperature sensitive products. By solving the four constructed models, the retailer's optimal policy regarding price and order quantity for HTSPs, MTSPs, LTSPs and HLTSPs can be determined. Furthermore, the impacts of the average temperature and temperature sensitive parameter on retailer's optimal policy are analyzed for HTSPs, MTSPs, LTSPs and HLTSPs. The results show that both average temperature during the selling period and temperature sensitive parameter can affect retailer's optimal policy, but the trend and extent of the impacts differ for the four types of products.

Citation: 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, doi: 10.3934/jimo.2018090
References:
 [1] Y. Aviv and A. Pazgal, Optimal pricing of seasonal products in the presence of forward-looking consumers, M & Som-Manuf. Serv. Op., 10 (2008), 339-359. doi: 10.1287/msom.1070.0183. [2] S. Bhat and A. Krishnamurthy, Interactive effects of seasonal-demand characteristics on manufacturing systems, Int. J. Prod. Res., 54 (2016), 2951-2964. doi: 10.1080/00207543.2016.1138150. [3] B. B. Cao, Z. P. Fan, H. Li and T. H. You, Joint inventory, pricing and advertising decisions with surplus and out-stock loss aversions, Discrete Dyn. Nat. Soc. , 2016 (2016), Art. ID 1907680, 14 pp. doi: 10.1155/2016/1907680. [4] B. B. Cao, Z. P. Fan, H. Li and T. H. You, Inventory control and pricing for regret-averse newsvendor, Rairo-Oper. Res., 51 (2017), 1033-1054. doi: 10.1051/ro/2017005. [5] F. Caro and J. Gallien, Dynamic assortment with demand learning for seasonal consumer goods, Manage. Sci., 53 (2007), 276-292. doi: 10.1287/mnsc.1060.0613. [6] F. Y. Chen and C. A. Yano, Improving supply chain performance and managing risk under weather-related demand uncertainty, Manage. Sci., 56 (2010), 1380-1397. doi: 10.1287/mnsc.1100.1194. [7] J. Chen, Y. Zhou and Y. Zhong, A pricing/ordering model for a dyadic supply chain with buyback guarantee financing and fairness concerns, Int. J. Prod. Res., 55 (2017), 5287-5304. doi: 10.1080/00207543.2017.1308571. [8] O. C. Demirag, Performance of weather-conditional rebates under different risk preferences, Omega-Int. J. Manage. S., 41 (2013), 1053-1067. [9] L. Earnest, Same-store sales rise 2. 9 % in May, Los Angeles Times (June 3). Available from: http://articles.latimes.com/2005/jun/03/business/fi-retail3. [10] H. Fu, B. Dan and X. Sun, Joint optimal pricing and ordering decisions for seasonal products with weather-sensitive demand, Discrete Dyn. Nat. Soc. , 2014 (2014), Art. ID 105098, 8 pp. doi: 10.1155/2014/105098. [11] F. Gao, D. O. Caliskan and F. Y. Chen, Early sales of seasonal products with weather-conditional rebates, Prod. Oper. Manag., 21 (2012), 778-794. doi: 10.1111/j.1937-5956.2011.01298.x. [12] B. C. Giri and S. Sharma, Optimal ordering policy for an inventory system with linearly increasing demand and allowable shortages under two levels trade credit financing, Oper. Res., 16 (2016), 25-50. doi: 10.1007/s12351-015-0184-y. [13] B. C. Giri and B. R. Sarker, Coordinating a two-echelon supply chain under production disruption when retailers compete with price and service level, Oper. Res-Ger., 16 (2016), 71-88. doi: 10.1007/s12351-015-0187-8. [14] C. S. Grewal, S. T. Enns and P. Rogers, Dynamic reorder point replenishment strategies for a capacitated supply chain with seasonal demand, Comput. Ind. Eng., 80 (2015), 97-110. doi: 10.1016/j.cie.2014.11.009. [15] T. Y. Lin, M. T. Chen and K. L. Hou, An inventory model for items with imperfect quality and quantity discounts under adjusted screening rate and earned interest, J. Ind. Manag. Optim., 12 (2016), 1333-1347. doi: 10.3934/jimo.2016.12.1333. [16] C. H. Nagaraja, A. Thavaneswaran and S. S. Appadoo, Measuring the bullwhip effect for supply chains with seasonal demand components, Eur. J. Oper. Res., 242 (2015), 445-454. doi: 10.1016/j.ejor.2014.10.022. [17] T. H. Nguyen and M. Wright, Capacity and lead-time management when demand for service is seasonal and lead-time sensitive, Eur. J. Oper. Res., 247 (2015), 588-595. doi: 10.1016/j.ejor.2015.06.005. [18] N. C. Petruzzi and M. Dada, Pricing and the news vendor problem: A review with extensions, Oper. Res., 47 (1999), 183-194. [19] Y. Qin, R. Wang, A. J. Vakharia, Y. Chen and M. M. Seref, The newsvendor problem: Review and directions for future research, Eur. J. Oper. Res., 213 (2011), 361-374. doi: 10.1016/j.ejor.2010.11.024. [20] S. A. Raza and M. Turiac, Joint optimal determination of process mean, production quantity, pricing, and market segmentation with demand leakage, Eur. J. Oper. Res., 249 (2016), 312-326. doi: 10.1016/j.ejor.2015.08.032. [21] A. N. Sadigh, S. K. Chaharsooghi and M. Sheikhmohammady, A game theoretic approach to coordination of pricing, advertising, and inventory decisions in a competitive supply chain, J. Ind. Manag. Optim., 12 (2016), 337-355. doi: 10.3934/jimo.2016.12.337. [22] G. P. Soysal and L. Krishnamurthi, Demand dynamics in the seasonal goods industry: An empirical analysis, Market. Sci., 31 (2012), 293-316. doi: 10.1287/mksc.1110.0693. [23] A. A. Taleizadeh and S. S. Kalantari, Determining optimal price, replenishment lot size and number of shipments for an EPQ model with rework and multiple shipments, J. Ind. Manag. Optim., 11 (2015), 1059-1071. doi: 10.3934/jimo.2015.11.1059. [24] A. A. Taleizadeh and M. Noori-daryan, Pricing, inventory and production policies in a supply chain of pharmacological products with rework process: A game theoretic approach, Oper. Res-Ger., 16 (2016), 89-115. doi: 10.1007/s12351-015-0188-7. [25] A. A. Taleizadeh and M. Noori-daryan, Pricing, manufacturing and inventory policies for raw material in a three-level supply chain, Int. J. Syst. Sci., 47 (2016), 919-931. doi: 10.1080/00207721.2014.909544. [26] Y. C. Tsao, Q. Zhang, H. P. Fang and P. L. Lee, Two-tiered pricing and ordering for non-instantaneous deteriorating items under trade credit, Oper. Res-Ger., (2017), 1-20. doi: 10.1007/s12351-017-0306-9. [27] T. M. Whitin, Inventory control and price theory, Manage. Sci., 2 (1955), 61-68. doi: 10.1287/mnsc.2.1.61. [28] J. Zhou, Z. Tang, D. Zhou and T. Fang, A study on capacity allocation scheme with seasonal demand, Int. J. Prod. Res., 53 (2015), 4538-4552. doi: 10.1080/00207543.2014.991457.

show all references

References:
 [1] Y. Aviv and A. Pazgal, Optimal pricing of seasonal products in the presence of forward-looking consumers, M & Som-Manuf. Serv. Op., 10 (2008), 339-359. doi: 10.1287/msom.1070.0183. [2] S. Bhat and A. Krishnamurthy, Interactive effects of seasonal-demand characteristics on manufacturing systems, Int. J. Prod. Res., 54 (2016), 2951-2964. doi: 10.1080/00207543.2016.1138150. [3] B. B. Cao, Z. P. Fan, H. Li and T. H. You, Joint inventory, pricing and advertising decisions with surplus and out-stock loss aversions, Discrete Dyn. Nat. Soc. , 2016 (2016), Art. ID 1907680, 14 pp. doi: 10.1155/2016/1907680. [4] B. B. Cao, Z. P. Fan, H. Li and T. H. You, Inventory control and pricing for regret-averse newsvendor, Rairo-Oper. Res., 51 (2017), 1033-1054. doi: 10.1051/ro/2017005. [5] F. Caro and J. Gallien, Dynamic assortment with demand learning for seasonal consumer goods, Manage. Sci., 53 (2007), 276-292. doi: 10.1287/mnsc.1060.0613. [6] F. Y. Chen and C. A. Yano, Improving supply chain performance and managing risk under weather-related demand uncertainty, Manage. Sci., 56 (2010), 1380-1397. doi: 10.1287/mnsc.1100.1194. [7] J. Chen, Y. Zhou and Y. Zhong, A pricing/ordering model for a dyadic supply chain with buyback guarantee financing and fairness concerns, Int. J. Prod. Res., 55 (2017), 5287-5304. doi: 10.1080/00207543.2017.1308571. [8] O. C. Demirag, Performance of weather-conditional rebates under different risk preferences, Omega-Int. J. Manage. S., 41 (2013), 1053-1067. [9] L. Earnest, Same-store sales rise 2. 9 % in May, Los Angeles Times (June 3). Available from: http://articles.latimes.com/2005/jun/03/business/fi-retail3. [10] H. Fu, B. Dan and X. Sun, Joint optimal pricing and ordering decisions for seasonal products with weather-sensitive demand, Discrete Dyn. Nat. Soc. , 2014 (2014), Art. ID 105098, 8 pp. doi: 10.1155/2014/105098. [11] F. Gao, D. O. Caliskan and F. Y. Chen, Early sales of seasonal products with weather-conditional rebates, Prod. Oper. Manag., 21 (2012), 778-794. doi: 10.1111/j.1937-5956.2011.01298.x. [12] B. C. Giri and S. Sharma, Optimal ordering policy for an inventory system with linearly increasing demand and allowable shortages under two levels trade credit financing, Oper. Res., 16 (2016), 25-50. doi: 10.1007/s12351-015-0184-y. [13] B. C. Giri and B. R. Sarker, Coordinating a two-echelon supply chain under production disruption when retailers compete with price and service level, Oper. Res-Ger., 16 (2016), 71-88. doi: 10.1007/s12351-015-0187-8. [14] C. S. Grewal, S. T. Enns and P. Rogers, Dynamic reorder point replenishment strategies for a capacitated supply chain with seasonal demand, Comput. Ind. Eng., 80 (2015), 97-110. doi: 10.1016/j.cie.2014.11.009. [15] T. Y. Lin, M. T. Chen and K. L. Hou, An inventory model for items with imperfect quality and quantity discounts under adjusted screening rate and earned interest, J. Ind. Manag. Optim., 12 (2016), 1333-1347. doi: 10.3934/jimo.2016.12.1333. [16] C. H. Nagaraja, A. Thavaneswaran and S. S. Appadoo, Measuring the bullwhip effect for supply chains with seasonal demand components, Eur. J. Oper. Res., 242 (2015), 445-454. doi: 10.1016/j.ejor.2014.10.022. [17] T. H. Nguyen and M. Wright, Capacity and lead-time management when demand for service is seasonal and lead-time sensitive, Eur. J. Oper. Res., 247 (2015), 588-595. doi: 10.1016/j.ejor.2015.06.005. [18] N. C. Petruzzi and M. Dada, Pricing and the news vendor problem: A review with extensions, Oper. Res., 47 (1999), 183-194. [19] Y. Qin, R. Wang, A. J. Vakharia, Y. Chen and M. M. Seref, The newsvendor problem: Review and directions for future research, Eur. J. Oper. Res., 213 (2011), 361-374. doi: 10.1016/j.ejor.2010.11.024. [20] S. A. Raza and M. Turiac, Joint optimal determination of process mean, production quantity, pricing, and market segmentation with demand leakage, Eur. J. Oper. Res., 249 (2016), 312-326. doi: 10.1016/j.ejor.2015.08.032. [21] A. N. Sadigh, S. K. Chaharsooghi and M. Sheikhmohammady, A game theoretic approach to coordination of pricing, advertising, and inventory decisions in a competitive supply chain, J. Ind. Manag. Optim., 12 (2016), 337-355. doi: 10.3934/jimo.2016.12.337. [22] G. P. Soysal and L. Krishnamurthi, Demand dynamics in the seasonal goods industry: An empirical analysis, Market. Sci., 31 (2012), 293-316. doi: 10.1287/mksc.1110.0693. [23] A. A. Taleizadeh and S. S. Kalantari, Determining optimal price, replenishment lot size and number of shipments for an EPQ model with rework and multiple shipments, J. Ind. Manag. Optim., 11 (2015), 1059-1071. doi: 10.3934/jimo.2015.11.1059. [24] A. A. Taleizadeh and M. Noori-daryan, Pricing, inventory and production policies in a supply chain of pharmacological products with rework process: A game theoretic approach, Oper. Res-Ger., 16 (2016), 89-115. doi: 10.1007/s12351-015-0188-7. [25] A. A. Taleizadeh and M. Noori-daryan, Pricing, manufacturing and inventory policies for raw material in a three-level supply chain, Int. J. Syst. Sci., 47 (2016), 919-931. doi: 10.1080/00207721.2014.909544. [26] Y. C. Tsao, Q. Zhang, H. P. Fang and P. L. Lee, Two-tiered pricing and ordering for non-instantaneous deteriorating items under trade credit, Oper. Res-Ger., (2017), 1-20. doi: 10.1007/s12351-017-0306-9. [27] T. M. Whitin, Inventory control and price theory, Manage. Sci., 2 (1955), 61-68. doi: 10.1287/mnsc.2.1.61. [28] J. Zhou, Z. Tang, D. Zhou and T. Fang, A study on capacity allocation scheme with seasonal demand, Int. J. Prod. Res., 53 (2015), 4538-4552. doi: 10.1080/00207543.2014.991457.
The curves of temperature sensitive functions for HTSPs, MTSPs, LTSPs and HLTSPs
The curves of temperature sensitive functions for MTSPs and HLTSPs when $\bar{T} = {{\bar{T}}_{A}} = {{\bar{T}}_{B}}$
 [1] Lisha Wang, Huaming Song, Ding Zhang, Hui Yang. Pricing decisions for complementary products in a fuzzy dual-channel supply chain. Journal of Industrial & Management Optimization, 2018, 13 (5) : 1-22. doi: 10.3934/jimo.2018046 [2] Jing Zhao, Jie Wei, Yongjian Li. Pricing and remanufacturing decisions for two substitutable products with a common retailer. Journal of Industrial & Management Optimization, 2017, 13 (2) : 1125-1147. doi: 10.3934/jimo.2016065 [3] Lou Caccetta, Elham Mardaneh. Joint pricing and production planning for fixed priced multiple products with backorders. Journal of Industrial & Management Optimization, 2010, 6 (1) : 123-147. doi: 10.3934/jimo.2010.6.123 [4] Takeshi Fukao, Nobuyuki Kenmochi. A thermohydraulics model with temperature dependent constraint on velocity fields. Discrete & Continuous Dynamical Systems - S, 2014, 7 (1) : 17-34. doi: 10.3934/dcdss.2014.7.17 [5] Roberto Garra. Confinement of a hot temperature patch in the modified SQG model. Discrete & Continuous Dynamical Systems - B, 2017, 22 (11) : 1-10. doi: 10.3934/dcdsb.2018258 [6] Gongfa Li, Wei Miao, Guozhang Jiang, Yinfeng Fang, Zhaojie Ju, Honghai Liu. Intelligent control model and its simulation of flue temperature in coke oven. Discrete & Continuous Dynamical Systems - S, 2015, 8 (6) : 1223-1237. doi: 10.3934/dcdss.2015.8.1223 [7] Maryam Ghoreishi, Abolfazl Mirzazadeh, Gerhard-Wilhelm Weber, Isa Nakhai-Kamalabadi. Joint pricing and replenishment decisions for non-instantaneous deteriorating items with partial backlogging, inflation- and selling price-dependent demand and customer returns. Journal of Industrial & Management Optimization, 2015, 11 (3) : 933-949. doi: 10.3934/jimo.2015.11.933 [8] Shichen Zhang, Jianxiong Zhang, Jiang Shen, Wansheng Tang. A joint dynamic pricing and production model with asymmetric reference price effect. Journal of Industrial & Management Optimization, 2018, 13 (5) : 1-22. doi: 10.3934/jimo.2018064 [9] 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 [10] Feng Tao, Hao Shao, KinKeung Lai. Pricing and modularity decisions under competition. Journal of Industrial & Management Optimization, 2017, 13 (5) : 1-19. doi: 10.3934/jimo.2018152 [11] Toyohiko Aiki, Martijn Anthonissen, Adrian Muntean. On a one-dimensional shape-memory alloy model in its fast-temperature-activation limit. Discrete & Continuous Dynamical Systems - S, 2012, 5 (1) : 15-28. doi: 10.3934/dcdss.2012.5.15 [12] Seiji Ukai, Tong Yang, Huijiang Zhao. Exterior Problem of Boltzmann Equation with Temperature Difference. Communications on Pure & Applied Analysis, 2009, 8 (1) : 473-491. doi: 10.3934/cpaa.2009.8.473 [13] Jingzhi Li, Masahiro Yamamoto, Jun Zou. Conditional Stability and Numerical Reconstruction of Initial Temperature. Communications on Pure & Applied Analysis, 2009, 8 (1) : 361-382. doi: 10.3934/cpaa.2009.8.361 [14] Ming Chen, Meng Fan, Xing Yuan, Huaiping Zhu. Effect of seasonal changing temperature on the growth of phytoplankton. Mathematical Biosciences & Engineering, 2017, 14 (5&6) : 1091-1117. doi: 10.3934/mbe.2017057 [15] Naveen K. Vaidya, Xianping Li, Feng-Bin Wang. Impact of spatially heterogeneous temperature on the dynamics of dengue epidemics. Discrete & Continuous Dynamical Systems - B, 2019, 24 (1) : 321-349. doi: 10.3934/dcdsb.2018099 [16] Mehmet Önal, H. Edwin Romeijn. Two-echelon requirements planning with pricing decisions. Journal of Industrial & Management Optimization, 2009, 5 (4) : 767-781. doi: 10.3934/jimo.2009.5.767 [17] Xuguang Lu. Long time strong convergence to Bose-Einstein distribution for low temperature. Kinetic & Related Models, 2018, 11 (4) : 715-734. doi: 10.3934/krm.2018029 [18] Guangwei Yuan, Yanzhong Yao. Parallelization methods for solving three-temperature radiation-hydrodynamic problems. Discrete & Continuous Dynamical Systems - B, 2016, 21 (5) : 1651-1669. doi: 10.3934/dcdsb.2016016 [19] J. David Logan, William Wolesensky, Anthony Joern. Insect development under predation risk, variable temperature, and variable food quality. Mathematical Biosciences & Engineering, 2007, 4 (1) : 47-65. doi: 10.3934/mbe.2007.4.47 [20] Shuji Yoshikawa, Irena Pawłow, Wojciech M. Zajączkowski. A quasilinear thermoviscoelastic system for shape memory alloys with temperature dependent specific heat. Communications on Pure & Applied Analysis, 2009, 8 (3) : 1093-1115. doi: 10.3934/cpaa.2009.8.1093

2017 Impact Factor: 0.994

Metrics

• PDF downloads (16)
• HTML views (212)
• Cited by (0)

Other articlesby authors

• on AIMS
• on Google Scholar

[Back to Top]