Dynamic Pricing of Tropical Fruits in Hainan Based on Internet of Things Technol

时间：2024-08-31

Huiyuan WANG, Huafen ZOU, Chun WANG, Hailiang LI

1. Institute of Scientific and Technical Information, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China; 2. South Asian Tropical Crops Research Institute, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang 524091, China

Abstract In recent years, the Internet of Things (IoT) technology has been widely used in the production and sales of tropical fruits, with strong practicability and wide application prospects. The tropical fruit dynamic pricing model based on the IoT technology can promote the healthy development of the tropical fruit industry in Hainan and ensure the income of fruit farmers. Based on IoT technology, the quality grade of tropical fruits in Hainan is obtained. According to the dynamic pricing strategy of revenue management, a dynamic pricing model based on the quality of tropical fruits and a dynamic pricing model based on consumer segmentation are established to study the dynamic pricing problem under the condition of maximum profit for tropical fruit sellers. The research results show that for different fruit quality and consumer groups, different pricing models are required for pricing, in order to get the maximum profit from tropical fruit sales. Sellers must flexibly adopt different dynamic pricing models to price tropical fruits to enhance the competitiveness of the tropical fruit industry.

Key words Internet of Things, Hainan, Tropical fruit, Dynamic pricing, Pricing model

1 Introduction

Since the founding of New China, it has gone through the social development stages of poverty, adequate food and clothing, and moderate prosperity. After entering the 21century, the material living standards of the people have improved significantly. The food consumption structure of Chinese residents continues to upgrade and presents the characteristic of diversified development. Initially, the residents’ fruit consumption demand was simple, with a single variety. But with the continuous improvement of living standards, the demand of Chinese residents for fruits, especially tropical fruits, is gradually increasing. In 2017, China’s domestic fruit production reached 295.02 million t. According to customs statistics, in 2017, the fruit imports of China were 4.56 million t, the export volume was about 3.61 million t, and domestic consumption was about 295.97 million t. In 2009, the sales market scale of China’s fruit industry was about 0.098 billion yuan, and in 2017, the sales market scale of China’s fruit industry reached 2 trillion yuan.

At present, as a new technology born in the Internet era, the Internet of Things (IoT) technology is widely used in all walks of life, and its impact on the lives of Chinese residents and the economy and society is gradually increasing. The use of IoT technology for the fine management of agriculture is its main application feature, favorably promoting the healthy and benign development of agriculture. IoT applies QR code technology to the whole process of agricultural production, realizing the traceability and monitoring of the whole process from the production, processing, transportation and sales links of crops, significantly improving the quality of agricultural products and the income of farmers. In recent years, the trend of applying IoT technology in the fruit trade field is becoming more and more obvious. With the development of IoT technology, information about the production, transportation and sales of fruits can be obtained through the IoT technology. The IoT technology provides a means for the reference and decision-making of fruit pricing and sales strategies.

The production and sales of tropical fruits in Hainan, as a unique tropical region in China, have distinct characteristics, and an important impact on the dynamics of China’s fruit market. This research aims to explore the application and innovation of the IoT technology in the field of tropical fruit sales in Hainan, and to realize the pricing research of fruit retail based on the information technology of IoT. In this article, the development of IoT technology in China is illustrated, the impact mechanism of IoT technology on the transportation and sales of tropical fruits is analyzed, and the dynamic pricing of fruit sales in the IoT era is explored theoretically, in order to point out the relationship between IoT and tropical fruit dynamic pricing and provide theoretical reference for the pricing of tropical fruits in Hainan.

2 Research status

IoT is an information network formed by combining information sensing equipment with the Internet. In 1998, Kevin Ashton of the Massachusetts Institute of Technology first proposed the concept of IoT. In 2008, the European Commission said that IoT merges the physical and digital worlds, and every physical entity is represented by a number; and objects can perceive the external world and communicate with each other. IoT can immediately react to physical events and send instant messages.

In terms of domestic dynamic pricing research based on consumer behavior, Jiang Danused factor analysis and auxiliary structural equation models to study the dynamic pricing strategies and models of safe agricultural products supermarket sales, constructed a dynamic pricing model of agricultural products based on different consumer characteristics, and provided the optimal price path of supermarket agricultural products. Li Hao

al.

established a dynamic pricing model for two retailers when supply exceeds demand, described the conditions that the equilibrium price satisfies, and discussed the characteristics of equilibrium price in some special circumstances. Based on consumer behavior strategies, the competitive strategies of two sellers in a competitive environment were studied. Ji Weiweistudied consumer behavior and its impact on the pricing and revenue of perishable products, used consumer functions to model consumer behavior, derive demand functions and derive the optimal pricing strategy, explored the impact of market competition on the pricing and revenue of perishable products, and constructed a product dynamic pricing model under the consumer behavior strategy. Based on the different characteristics of strategic and short-sighted consumers, Chen Ziwei

al.

constructed a consumer utility function combining three factors, including willingness to pay, risk preference, and reference price, and studied the dynamic pricing by retailers of perishable products under the heterogeneous effect of consumer behavior. Yang Hui

al.

studied the impact on pricing and profits of corporates in a market where strategic consumers and short-sighted consumers coexist when strategic consumers were not affected by the reference price, established a two-stage dynamic pricing model, and explored the impact of different factors on corporate pricing.In terms of application of IoT technology in retrospective research on agricultural products, taking Jinyou

Citrus

maxima

as an example, Peng Hongxing

al.

studied the QR code and global positioning system (GPS) technology that may be used in the agricultural product traceability information model and system, and designed and developed a fruit traceability mobile internet system. They believed that the IoT technology can realize the traceability of fruit cultivation, processing, production, and transportation, and can improve the traceability of fruit quality and safety. Using the hazard analysis critical control point (HACCP), failure mode effects and criticality analysis (FMECA) and other technical methods, Meng Meng

al.

put forward the key factors affecting the quality and safety of tropical fruits, built a tropical fruit quality and safety traceability system based on QR code technology, and believed that fruit production enterprises should adopt such systems to improve the safety production level of tropical fruits and ensure the industrialized management and standardized management of tropical fruits. Xu Longqinused the production batch of subtropical fruit product as an "identity card", performed traceability coding with UCC/EAN-128 coding method combined with process coding, radio frequency identification (RFID) and QR code technology, and established a quality tracking and tracing system for the whole process of subtropical fruit production and processing with multi-level and multi-user authority dynamic management. Liu Yijian

al.

believed that the RFID core technology of the Internet of Things can improve the efficiency of the agricultural product supply chain, and help realize the traceability of agricultural products to ensure the quality and safety of agricultural products. They discussed the application of RDID technology, the necessity of its promotion in the supply chain of fresh agricultural products, and its application in the supply chain of agricultural products. Zhao Xianghao

al.

adopted the process traceability concept of the whole industry chain and constructed a quality and safety traceability system for the entire industrial chain of characteristic agricultural products in Xinjiang based on IoT.

3 Overview of production and prices of tropical fruits in China and Hainan Province

Hainan Province has a land area of 3 540 000 km. Tropical fruits such as banana, pineapple, lychee, longan, mango, and coconut are mainly grown. In the 30 years since Hainan was established as a province, the tropical fruit industry has developed rapidly, and the planting area and output are increasing year by year. The tropical fruit industry is one of the most distinctive hot crop industries in Hainan Province. As Hainan’s construction of an international tourist island has become a national strategy, the state clearly requires Hainan Province to give full play to its geographical resource advantages and vigorously develop modern agriculture, making Hainan Province an important fruit basket in China.

3.1 Overview of production and prices of tropical fruits in China

3.1.1

Overview of production of tropical fruits in China. The tropical fruits produced in China include banana, pineapple, longan, lychee, guava, carambola and wax apple.

In 2017, the planting area of tropical fruits in China was 1.89 million ha with total output of 26.44 million t and total output value of 94.90 billion yuan. The planting area of banana was 382 400 ha, and the total output was 12.89 million t, ranking 6and 1in the world, respectively. The yield of banana was 36 333.15 kg/ha. The planting area of lychee was 559 700 ha, and the total output was 2.39 million t, both ranking first in the world. The yield of lychee was 4 284.45 kg/ha. The planting area of longan was 358 300 ha, and the total output was 2.02 million t, both ranking first in the world. The yield of longan was 6 530.1 kg/ha. The planting area of mango was 257 700 ha, and the total output was 2.05 million t, both ranking 7in the world. The yield of mango was 12 664.35 kg/ha.

2018 was a high-yield year for Guangdong Province, Guangxi Zhuang Autonomous Region, Fujian Province, and Yunnan Province, the main producing areas of lychee, mango and pineapple in China. The planting area of lychee in the main producing areas of Guangdong Province, Guangxi Zhuang Autonomous Region, Yunnan Province and Fujian Province was 272 666, 203 333, 22 666 and 3 133 ha, respectively, and the total output was expected to be 1 246 000, 667 000, 182 000 and 28 000 t, respectively. The planting area of mango was 18 333, 43 466, 800 and 30 000 ha, respectively, and the total output was expected to be 224 000, 584 000, 11 000 and 409 000 t, respectively. The planting area of pineapple was 31 466, 2 333, 2 266 and 2 800 ha, respectively, and the total output was 1 034 000, 34 000, 43 000 and 73 000 t, respectively. Lychees from Guangdong Province are listed successively at the end of May. Mangoes from Guangxi Zhuang Autonomous Region will start to be picked on June, 2 and will be sold in large quantities, which is expected to have a greater impact on the later mango sales in Hainan Province.

The pineapples from Zhanjiang, Guangdong Province go on the market in March, and the sales are almost over. In addition, mangoes and pineapples from Southeast Asia have also entered China for sale, producing a certain impact on the sales of mangoes and pineapples in Hainan Province.

3.1.2

Overview of prices of tropical fruits in China. From the perspective of annual average price, the wholesale price of banana in China showed a fluctuating increase from 2008 to 2017, 2.88, 3.35, 3.56, 4.21, 3.57, 3.80, 5.45, 3.75, 3.94 and 4.21 yuan/kg, respectively. The highest prices appeared in May, June and September, and the lowest values appeared in January and July. It can be judged that the wholesale price of banana has the characteristic of seasonal fluctuation. Overall, the wholesale price of banana continued to rise from January to February each year. The main reason is that China’s seasonal fruits had not been put into market, and as the New Year’s Day and the Spring Festival approached, the market demand increased, so the price of bananas rose. The wholesale price of bananas decreased from March to April every year. Affected by the successive listings of daily fruits to occupy the market, the market supply increased, so the price of bananas fell. May is the peak time for pineapples to be listed nationwide. The national average wholesale price of pineapples was 2.42 yuan/kg, a decrease of 28.11% month-on-month, and a decrease of 46.24% year-on-year. At present, most of the pineapples sold in the market come from Guangdong and Hainan provinces, dominated by Yellow Mauritius cultivar. Most pineapples in the producing areas were unsalable, and the market price dropped sharply. It was expected that the price would continue to fall in early June, but would rise in mid to late June. June is the national intensive listing period of lychees. Affected by the national high yield and the concentration of the listing period, it is difficult to sell in the later stage, so the price of lychees was expected to drop slightly in the later stage. Lychees from Guangdong and Guangxi will gradually go on the market in late May. After lychees of Feizixiao from many places in Guangxi went into market, the local price was 8.0-9.0 yuan/kg. In May, the sales of lychees in the main sales markets across China gradually increased. From early to mid-May, the wholesale price of Feizixiao in the sales market was 20-50 yuan/kg, and that of Baitangying was 24-56 yuan/kg, and the market basically remained stable. In late May, the wholesale price of Feizixiao in the land market fell to 8-18 yuan/kg, and that of Baitangying fell to 8-14 yuan/kg. In May, 2018, the average purchase price of Tainong mangoes was 4.32 yuan/kg, decreased by 1.30 yuan/kg month-on-month; the average purchase price of Guifei was 64.98 yuan/kg, decreased by 1.68 yuan/kg month-on-month; and the average purchase price of Jinhuang was 6.52 yuan/kg, decreased by 1.58 yuan/kg month-on-month. The mangoes in Hainan entered the final stage of picking, and there were many defective fruits; but mangoes from Guangdong and Guangxi had begun to go on the market in large quantities, and the market supply was sufficient. The bumper harvest of lychees in 2018 caused a sharp drop in the price of mangoes. In May, the price of fresh longan was 15.84 yuan/kg, with a month-on-month increase of 1.54% and a year-on-year decrease of 5.38%. The price of fresh longan in China had risen slightly for two consecutive months. The fresh longan in the main domestic producing areas had not yet entered the market period, so the consumption of fresh longan mainly depended on imports. Driven by consumer demand during the May Day Holiday, the price of fresh longan continued to rise. It was expected that the price of fresh longan would decrease in the later period.

3.2 Overview of production and prices of tropical fruits in Hainan Province

3.2.1

Overview of production of tropical fruits in Hainan Province. Hainan Province is located at the southernmost tip of China, and its unique climatic conditions and geographical location make it the hometown of tropical fruits in China. Tropical fruits are competitive agricultural products in Hainan Province, and are also an important part of the agricultural product export industry in Hainan Province. Tropical fruits in Hainan Province can be divided into 53 genera and 29 families. The main tropical fruits in Hainan include banana, mango, lychee, pineapple and longan. The production profiles of tropical fruits in Hainan are obtained by consulting the annual data of Hainan Province (Table 1).

Table 1 Production of major tropical fruits in Hainan Province in 2010-2018

3.2.2

Overview of prices of tropical fruits in Hainan Province. In 2018, the sales of tropical fruits in Hainan Province faced the problem of low prices. The main reason is that the planting area of new varieties was small and the supply of old varieties exceeded demand; and due to weather, the fruits’ listing was delayed for 10-45 d, making them encounter the fruits from Guangdong, Yunnan and Fujian. Lower purchase prices had led to labor shortage and insufficient transportation capacity. Insufficient purchasing capacity and lack of organized dislocation production due to poor information made domestic fruits encounter in the market, and even worse, the impact of imported fruits from Southeast Asia had produced more serious consequences.

In May, mangoes from Hainan went on the market, and their prices dropped significantly. The purchase price of bagged Guifei mangoes was only about 8 yuan/kg, and that of non-bagged fruits was only about 4 yuan/kg. Lychees in Hainan had a good harvest this year. The price of Nuomizi lychees was about 20 yuan/kg. In May, the amount of lychees on the market gradually increased, and the purchase prices of Hainan Feizixiao and Baitangying showed a downward trend. By the end of May, the purchase price of Baitangying fell to 3.30 yuan/kg, and that of Feizixiao fell to 3.90 yuan/kg, 6.0-7.0 yuan/kg lower than that of the same period last year. Affected by the weather, Hainan’s banana shipments had been affected to a certain extent, so the prices had risen. Extreme weather also had a certain impact on the quality and fleshiness of bananas. The price was mostly between 6.6 and 8.0 yuan/kg. Regarding the price of pineapple, the highest market price in Hainan was 8.0 yuan/kg, and it was expected that the price would fluctuate and rise in the future. In May, a large amount of Hainan lychees were put into market. As a result, the wholesale price of mangoes fell sharply, and their sales in certain areas were slow.

4 Dynamic pricing model for tropical fruits

4.1 Dynamic pricing model based on quality differences of tropical fruits

To maximize the sales revenue of tropical fruits based on quality grade, it needs to write the specific expression of the sales revenue function, and give strict constraints.

where

is revenue;

and

are prices;

and

are quality;

is quality difference threshold;

is unit cost of fruit; and

and

are meant to show that the degree of mutual influence between fruits of two quality grades is different, and the size of the difference is characterized with different values of the two. For tropical fruits, the quality is not a step function, and instead, it is a gradual corruption process. Here, if the residual value of the unsold fruit is considered to be 0, then

=0, and

≤

.As mentioned earlier, different quality grades

and

of two kinds of fruits and their corresponding prices

and

are the decision variables of the non-linear programming. According to the accurate fruit quality level obtained by the Internet of Things and the description of the pricing strategy, the restriction conditions of the decision variables on the objective function are obtained as follows:

According to the non-linear programming MATLAB solution method, the second formula of the restriction conditions can be divided into one inequality constraint, and other constraints are variable constraints.

Assuming that tropical fruits arrive at the retailer through traceability of the origin and monitoring of logistics distribution, after calculation, two quality grades

and

of the same fruit are obtained, and it is considered that the quality difference threshold u exists between them. According to the quality difference threshold, the quality of the delivered fruits can be divided, without loss of generality. Assuming

=500 kg,

=800 kg,

=4.0 yuan,

=6.0 yuan,

=4.6 yuan,

=2,

=0.6,

=0.6 and

=0, calculation is performed after removing the dimension of the parameters and substituting them into the model. According to the calculation method of non-linear programming, the best prices of two kinds of tropical fruits are obtained:

=2.66 yuan,

=4.66 yuan; and the quality of the two kinds of fruits are

=0.6 and

=1.0.

First, the impact of quality on revenue is analyzed. Quality is initially considered to affect the probability function of fruit sales, so under the condition of the same customer arrival rate, the better the quality, the higher the revenue. The best prices selected here remain unchanged, and using the quality of two tropical fruits of different quality grades as parameters, a three-dimensional surface is drawn to show the impact of quality differences on sales revenue (Fig.1).

Fig.1 Effect of quality difference on sales revenue of tropical fruits

There is a linear increasing relationship between the income of two-quality grade fruits and the difference in the quality of the two. That is, the quality changes of the two fruits and the final income constitute a plane in the three-dimensional space. The maximum revenue corresponds to the optimal value of quality, which corresponds to a corner on the plane. This point is

=0.6 and

=1.0.

4.2 Dynamic pricing model based on consumer segmentation

Dynamic pricing has attracted more and more attention from manufacturers and retailers. At the same time, consumers are becoming more and more rational in the process of buying fruits. In most parts of China, tropical fruits are shipped from other places, and their freshness can no longer be compared with local fruits. Some consumers will consider buying after the fruit retailers implement a price reduction operation. This reflects the rationality of consumers when facing products. They are generally called strategic consumers in economics. Other consumers who have no strategy to purchase goods are called short-sighted consumers.

4.2.1

Conditional assumptions. A distinguishing characteristic of tropical fruits is their perishability. As tropical fruits are placed on shelves over time, the quality of the tropical fruits gradually decreases until they are completely rotten and have no sales value. Before constructing the model, the following assumptions are made. (i) The shelf life of fruits is divided into 2 segments, in which the selling prices are

and

(

). (ii) Strategic consumers account for a certain proportion of the total number of consumers. The total number of consumers is supposed to be

, and the proportion of strategic consumers is supposed to be

. (iii) The unit cost of fruit is

, and consumers’ reservation prices are evenly distributed within a certain price range. (iv) The purchase intentions of strategic consumers reflected in different price ranges have obvious differences with those of short-sighted consumers. This is dealt with in the form of discount factor, represented by the proportion of purchases in the first price segment.

4.2.2

Model construction. The reservation price for short-sighted consumers is

, then the number of people who choose to buy in the first price segment is expressed as (1-

)

·(

)

. For strategic consumers, they may not purchase when their reservation price is higher than

. This is equivalent to that when looking at commodity price, strategic consumers subjectively raise the psychological price of goods, which is at least higher than

. Since there has been so far no full description on the psychological price, it could be supposed to be

, and its value range is [

]. Thus, the number of strategic consumers who perform purchase behavior is

αN

·(

)

. If the fruit inventory is

and the loss rate is

, the profit of the retailer in the first segment,

, is expressed as:

Among consumers in the second price segment, the highest psychological price of short-sighted consumers is

. But due to the deterioration of fruit quality, the occurrence probability of actual purchase behavior is less than the difference between the psychological price and the price in the second segment. This probability reduction is expressed in the form of the product of the proportional coefficient and the highest reservation price, and called the quality decline factor

. The number of short-sighted consumers is (1-

)

·(

δp

)

. The goal of strategic consumers is to abandon the purchase in the first price segment and move to the second price segment for purchase, so

cannot be used as the highest reservation price. But there will also be a proportional decline in purchase intention due to the decline in fruit quality, and therefore, the number of consumers who choose the strategy of buying fruits in the second price segment is

αN

·(

δF

)

. According to the number of purchasers in the second price segment, the profit obtained in the second price segment is:

The profit of the dynamic pricing decision of the fruit retailers is expressed as:

To get the optimal profit for the entire sales cycle, it is necessary to start the analysis from the second price segment, that is, to satisfy:

The optimal profit conditions are obtained:

The purchase of short-sighted consumers in the first price segment is only related to the price

. As strategic consumers have relatively less purchases in the first price segment, the number of strategic consumers in the second price segment will be increased. That is, the purchase decision in the first price segment can be considered to be related to the price

in the second price segment, and the correlation factor (

) is introduced:

(

)

For strategic consumers, when the equation holds and when fruits are purchased in the first and second price segments, consumer surplus is considered to be equal psychologically. That is, this formula shows a dynamic pricing that has no effect on strategic consumers. The following formula is available:

After the income of the second price segment is also introduced into the correlation factor, the final profit based on strategic consumers and tropical fruit corruption is obtained:

ρLu

If fruit sellers want to maximize profits, it is necessary to substitute the expression of

into the expression of total profit, and make.

The optimal price strategy of fruit retailers can be solved as follows:

The parameters are as follows:

=(2-2

δαρ

)

-4

-(10-22

αρ

)

+(13-26

αδ

+10

δα

)

-(5-7

αδ

-8

)

=12-4

-(21-16

αδ

)

+(11-21

αδ

+16

δα

)

-(3-8

)

4.2.3

Analysis of calculation examples.Taking the carambola that went on the market from January to March as an example, assuming that the cost price of carambola after being shipped to the north is 6 yuan/kg, the highest reservation price among consumers can reach 20 yuan/kg, and the inventory volume in a single period exceeds the purchase volume of consumers, that is, there is no need to consider the problem of insufficient supply, the pricing strategy in this case can use the consumer segmentation strategy. Assuming that the number of consumers is 1 000, and the carambola inventory is 1 100 kg; due to the short shelf life of carambola, it is sold in 2 price segments during the sales cycle, and there is a 10% loss of inventory in the second price segment while no loss in the first price segment; consumers’ purchase intentions are reduced by 10% as a result of losses, and for strategic consumers, the impact factor of the second-segment price on the first-segment price is 0.6; according to the parameters in the formula,

=20,

=6.0,

=0.6.

=0.1,

=0.90,

=1 000 and

=1 100.Assuming that strategic consumers account for 40% of consumers (

=0.4), and the optimal price formulas are solved using MATLAB method:

1=12

1=16

2=9

That is, the optimal price for the first segment of winter carambola is 12.42 yuan/kg. In the psychology of strategic consumers, it is believed that the first-segment carambola will be reduced in price in the second segment, so they will be less willing to buy than short-sighted consumers. That is, the purchase intention of strategic consumer at the price of 12.42 yuan/kg is equal to that of short-sighted consumers at the price of 16.94 yuan/kg. In the second price segment, the best price for retail and supermarkets is 9.40 yuan/kg. To obtain the total income of the two segments, the above parameters are substituted into the total profit formula:

ρLu

=1 803.7 yuan

Then the profit of carambola is 1 803.7 yuan.

5 Conclusions

On the basis of researching the Internet of Things, all the elements of tropical fruits in their production and circulation are analyzed. Using the Internet of Things coding structure of electronic product code (EPC) and the RFID technology, the key elements that affect the quality and safety of tropical fruits are put forward, and a tropical fruit quality and safety traceability system based on the IoT technology is constructed, in order to ensure the transparency of the tropical fruit production and circulation process and safeguard consumers’ right to know, thereby further improving the sales level of tropical fruits. Based on the grading of quality, a dynamic pricing strategy is adopted to dynamically price the fruit sales under different quality grades and different proportions of strategic consumers, and the revenue is calculated. This provides reference and technical support for the traceability and sales model of tropical fruit production and circulation in China.

Tropical fruit quality traceability based on IoT technology is combined with dynamic pricing model and strategy. Decay and loss has always been a problem that has not been solved well in the sales of tropical fruits. Quality traceability based on IoT technology is very important in fruit quality control. Grading fruit quality can promote the continuous improvement of tropical fruit trade,

i.e.

, improve the efficiency of the industry and increase the profit of fruit sales. Based on this key point, the dynamic pricing strategy based on revenue management is combined with the quality traceability of tropical fruits based on the IoT technology in this paper to achieve innovative application. Aiming at the perishable characteristic of tropical fruits, a quality traceability system related to quality is established. The quality monitoring of tropical fruits must be strengthened from origin, logistics and distribution, and sales and inventory. Tropical fruits have unique properties compared with other products, so the quality traceability design for them must have certain uniqueness. Dynamic pricing is based on the grading of quality and the proportion of strategic consumers. By describing the relevant information of consumer purchases after the quality is graded, retailers are encouraged to price dynamically in the sale of fruits of different quality grades to get the maximum benefit; or according to the different proportion of strategic consumers, fruits are priced differently in the two price segments to get the maximum benefit.