July  2019, 15(3): 1153-1184. 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, 2019, 15 (3) : 1153-1184. 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.  Google Scholar

[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.  Google Scholar

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B. B. CaoZ. P. FanH. 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.  Google Scholar

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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.  Google Scholar

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J. ChenY. 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.  Google Scholar

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O. C. Demirag, Performance of weather-conditional rebates under different risk preferences, Omega-Int. J. Manage. S., 41 (2013), 1053-1067.   Google Scholar

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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. Google Scholar

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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.  Google Scholar

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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.  Google Scholar

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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.  Google Scholar

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C. S. GrewalS. 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.  Google Scholar

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T. Y. LinM. 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.  Google Scholar

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C. H. NagarajaA. 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.  Google Scholar

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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.  Google Scholar

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N. C. Petruzzi and M. Dada, Pricing and the news vendor problem: A review with extensions, Oper. Res., 47 (1999), 183-194.   Google Scholar

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Y. QinR. WangA. J. VakhariaY. 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.  Google Scholar

[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.  Google Scholar

[21]

A. N. SadighS. 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.  Google Scholar

[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.  Google Scholar

[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.  Google Scholar

[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.  Google Scholar

[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.  Google Scholar

[26]

Y. C. TsaoQ. ZhangH. 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.  Google Scholar

[27]

T. M. Whitin, Inventory control and price theory, Manage. Sci., 2 (1955), 61-68.  doi: 10.1287/mnsc.2.1.61.  Google Scholar

[28]

J. ZhouZ. TangD. 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.  Google Scholar

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.  Google Scholar

[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.  Google Scholar

[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.  Google Scholar

[4]

B. B. CaoZ. P. FanH. 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.  Google Scholar

[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.  Google Scholar

[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.  Google Scholar

[7]

J. ChenY. 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.  Google Scholar

[8]

O. C. Demirag, Performance of weather-conditional rebates under different risk preferences, Omega-Int. J. Manage. S., 41 (2013), 1053-1067.   Google Scholar

[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. Google Scholar

[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.  Google Scholar

[11]

F. GaoD. 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.  Google Scholar

[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.  Google Scholar

[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.  Google Scholar

[14]

C. S. GrewalS. 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.  Google Scholar

[15]

T. Y. LinM. 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.  Google Scholar

[16]

C. H. NagarajaA. 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.  Google Scholar

[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.  Google Scholar

[18]

N. C. Petruzzi and M. Dada, Pricing and the news vendor problem: A review with extensions, Oper. Res., 47 (1999), 183-194.   Google Scholar

[19]

Y. QinR. WangA. J. VakhariaY. 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.  Google Scholar

[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.  Google Scholar

[21]

A. N. SadighS. 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.  Google Scholar

[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.  Google Scholar

[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.  Google Scholar

[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.  Google Scholar

[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.  Google Scholar

[26]

Y. C. TsaoQ. ZhangH. 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.  Google Scholar

[27]

T. M. Whitin, Inventory control and price theory, Manage. Sci., 2 (1955), 61-68.  doi: 10.1287/mnsc.2.1.61.  Google Scholar

[28]

J. ZhouZ. TangD. 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.  Google Scholar

Figure 1.  The curves of temperature sensitive functions for HTSPs, MTSPs, LTSPs and HLTSPs
Figure 2.  The curves of temperature sensitive functions for MTSPs and HLTSPs when $\bar{T} = {{\bar{T}}_{A}} = {{\bar{T}}_{B}}$
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