考虑消费者损失规避行为的“互联网+”回收平台定价决策研究

Pricing decision for the‘Internet+’recycling platform considering consumer loss aversion

本文研究“互联网+”回收平台的最优定价决策,基于在线回收中回收价格的不确定性,考虑消费者损失规避特性对定价决策的影响。在消费者有无损失规避特性的情形下,分别构建了评级不匹配旧产品直接按照真实质量等级定价,不完全信息下评级不匹配旧产品的二次定价,完全信息下评级不匹配旧产品的二次定价三种情形下的定价模型,获取最优的定价策略。研究结果表明,“互联网+”回收平台对评级不匹配旧产品进行二次定价时有两种定价策略:直接认定为预估价或者重新定价为比真实质量等级更高的价格。其次,“互联网+”回收平台在评级不匹配旧产品直接按照真实质量等级定价的情形下获得最低的利润,在完全信息下评级不匹配旧产品的二次定价情形下会获得最高的利润。最后,消费者的损失规避特性对“互联网+”回收平台会产生不利影响,且当评级不匹配旧产品比例或者消费者损失规避系数较大时,消费者的损失规避特性不容忽视。

The amount of electronic waste,such as used mobile phones and computers,has been experiencing a sharp increase due to factors,including continuous product updates,short product life cycles and a large number of users.Determining ways to recycle and dispose of electronic waste effectively has become an important issue requiring worldwide attention.The rapid development of information and internet technology has brought new techniques to recycle electronic waste in recent years.Because of the advantages of being light in weight and easy to carry,electronic waste,such as used mobile phones and computers,can be recycled conveniently for customers through the‘Internet+’recycling platform.Therefore,the‘Internet+’platform is regarded as an effective way to increase the recycling rate of electronic waste.However,during the process of‘Internet+’recycling,the final recycling prices of used products are usually uncertain for customers.They worry that the recycling platform might use the lack of information transparency during the quality inspection process to deliberately decrease the recycling prices and then buy low and sell high to make a profit.In addition,the large deviation between final recycling prices and the platform′s estimated prices may be unacceptable for customers,resulting in a low recycling rate of electronic waste by the‘Internet+’recycling platform that is far below the desired level.Further,consumers with irrational behaviours may regard these estimated prices as references for recycling prices of used products.When the final recycling price of a used product is lower than its estimated price,a consumer might exhibit loss aversion characteristics.This study investigates the optimal pricing decision of the‘Internet+’recycling platform.Based on the uncertainty of the recycling price on the online recycling platform,this work considers the impact of consumer loss aversion characteristics on pricing decisions.By assuming the scenarios of consumers with or without loss aversion characteristics,three pricing models are constructed under the situations where the rating of used products′pricing with mismatched quality is based on the following factors:their real quality level,incomplete information and complete information.Furthermore,a comparison analysis of the constructed models in terms of the optimal pricing strategy and the profit of the‘Internet+’recycling platform is conducted.From the study,some meaningful results are as follows:first,when the‘Internet+’recycling platform re-prices used products with mismatched quality ratings,the following two pricing strategies can be adopted.If the differences among the residuals of used products with varying quality grades are not large,then used products with mismatched quality ratings should not be re-priced to avoid possible monetary losses.Conversely,re-pricing of used products with mismatched quality ratings should be done when the differences among the residuals of used products with varying quality grades are large.Second,considering the time-sensitivity of the used products price and loss in value of used products because of the disassembly operation of the recycling platform,this study suggested that the value loss factor of returning used products increases and the number of consumers returning used products decreases,increasing the profit of the recycling platform thereby.However,these models do not imply that the recycling platform can increase the recycling platform′s revenue by increasing the value loss of used products because the time lapsed from participating in online recycling to returning a used product is quite short.In addition,the loss of value of returning the used products results from the dismantling behaviour of the recycling platform.Because of this,consumers may lose their trust in the recycling platform and will no longer participate in online recycling.Third,regardless of whether consumers have loss aversion characteristics,the recycling platform gains the lowest profit in the model where used products with mismatched quality ratings are directly priced based on their true quality level.Conversely,the recycling platform gains the highest profit under the secondary pricing model,where the proportion of used products with mismatched quality ratings is predictable.Finally,consumer loss aversion characteristics negatively impact the‘Internet+’recycling platform.The higher the percentage of consumers holding low-value used products,the percentage of used products with mismatched quality ratings or the level of consumer loss aversion,the greater the positive impact of the complete information pricing decision model and the greater the negative impact of consumer loss aversion on the recycling platform.In practice,the recycling platform can increase its revenue in the following ways:First,it should reasonably set up the website′s price evaluation system.With reasonable strategies,such as reducing the proportion of used products with mismatched quality ratings,avoiding an excessively detailed classification of evaluation options to obscure consumers′choices or reducing the number of quality grade of used products to widen the gap among different quality levels of used products,the recycling platform may increase its revenue and alleviate the impacts of consumer loss aversion characteristics.Second,in the case of used products with mismatched quality ratings and consumer loss aversion characteristics,the recycling platform should collect historical data and estimate the proportion of used products with mismatched quality ratings.Thus,the recycling platform can increase its revenue and reduce the negative impact of consumer loss aversion characteristics using the pricing decision model under complete information.