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

Bing-Bing Cao; Zhi-Ping Fan; Tian-Hui You

doi:10.3934/jimo.2018090

Article Contents

2019, Volume 15, Issue 3: 1153-1184. Doi: 10.3934/jimo.2018090

This issue Previous Article Optimality conditions and duality for minimax fractional programming problems with data uncertainty Next Article Maritime inventory routing problem with multiple time windows

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
* Corresponding author: ZHI-PING FAN

Received: April 2017

Revised: January 2018

Early access: June 2018

Published: April 2019

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

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Abstract

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.

Keywords:

Joint decisions,
newsvendor model,
pricing,
temperature sensitive products (HTSPs, MTSPs, LTSPs and HLTSPs),
temperature effects.

Mathematics Subject Classification: Primary: 90B05, 68W27; Secondary: 68W40.

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Figure 1. The curves of temperature sensitive functions for HTSPs, MTSPs, LTSPs and HLTSPs

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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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