Research on Influencing Factors of Repurchase Rate of Hainan Cross-border E-commerce Platform Based on User Experience

doi:10.21203/rs.3.rs-3909641/v1

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Research on Influencing Factors of Repurchase Rate of Hainan Cross-border E-commerce Platform Based on User Experience

https://doi.org/10.21203/rs.3.rs-3909641/v1

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The conventional analysis method of influencing factors on the repurchase rate of cross-border e-commerce platforms mainly uses SPSS17.0 to obtain the influencing factors, which is vulnerable to the impact of customer experience competition, leading to the high variance between the influencing factor analysis groups. Therefore, an effective analysis method of influencing factors on the repurchase rate of cross-border e-commerce platforms in Hainan needs to be designed based on user experience. That is to say, the preference index of Hainan cross-border e-commerce platform repurchase is selected based on the repurchase impact variables of Hainan cross-border e-commerce platform, and then the contribution value of the variables is calculated using the stepwise regression analysis method, and the regression model of factors affecting the repurchase rate of Hainan cross-border e-commerce platform is constructed, thus realizing the analysis of factors affecting the repurchase rate of Hainan cross-border e-commerce platform. The case analysis results show that the inter group variance of the designed analysis method of factors affecting the repurchase rate of Hainan cross-border e-commerce platform based on user experience is small, which proves that the designed analysis method of factors affecting the repurchase rate is effective, accurate, and has certain application value, and has made certain contributions to improving the comprehensive sales profit of Hainan cross-border e-commerce platform.

User experience

Hainan

Cross-border e-commerce

Platform

Repurchase rate

Influencing factors

Research

In the era of rapid economic development, the way of information dissemination in China is changing, and people's shopping mode is gradually changing from the original offline shopping mode to online shopping mode^[1–4]. Under the above background, China's e-commerce platforms have risen rapidly, and the term cross-border e-commerce has also come into being. The earliest cross-border e-commerce in China was established in 2005. After more than a decade of development, the scale of cross-border e-commerce in China has expanded several times. Research shows that China has launched a number of representative cross-border e-commerce platforms. At present, e-commerce economy has become an important part of China's economy.

The improvement and progress of e-commerce platform has also promoted the development of China's logistics industry^[5–8], and various logistics companies have emerged as the times require, resulting in a new logistics model. In order to improve their comprehensive competitiveness, we need to use big data technology to extract personalized data from users, and predict consumers' subsequent consumption demand.

There is a big gap between cross-border e-commerce transactions and traditional trade^[9–12]. The number of transaction batches is large, and the amount of transactions is small, which can effectively reduce the risks in the trade process and solve many problems in the trade process. Therefore, most manufacturers are starting to transform to cross-border e-commerce. In fact, there are also obvious differences between online transactions and offline transactions. Online consumers have certain preferences in their consumption behavior, and can predict and push according to consumers' consumption data to increase total sales.Repurchase rate refers to the repurchase rate of a product purchased by consumers, which is closely related to the user's experience. The higher the repurchase rate of commodities, the higher the satisfaction of users with commodities^[13–16]. It can be seen that the repurchase rate is an important indicator affecting the platforms, created an impact model for the repurchase rate through the simulation method, and predicted the actual repurchase effect. However, the conventional analysis method for the factors affecting the repurchase rate mainly uses SPSS17.0 to obtain the influencing factors, which is vulnerable to the impact of customer experience competition^[17–19], leading to high variance between the analysis groups of influencing factors,It does not meet the current analysis needs. Therefore, this paper designs a new analysis method of factors affecting the repurchase rate of Hainan cross-border e-commerce platform based on user experience.

1.1 Select Hainan cross-border e-commerce platform repurchase preference index

In order to solve the problem of high inter group variance caused by the competitive effect of customer experience when SPSS17.0 obtains the impact factors of repurchase rate, this paper obtained the influencing factor variable^[20]in advance. Information preference is an overall reflection indicator related to the consumption habits of regional consumers. Information preference is often related to the average consumption dimension P and consumption proportion Q^[21–23]. According to the demand relationship of e-commerce platforms, a relationship diagram of repurchase preference indicators can be constructed, as shown in Fig. 1 below.

It can be seen from Fig. 1 that with the increase of consumption proportion, the average consumption dimension of users is getting higher and higher, so there is a positive relationship between the two.

This paper diversified the cross-border e-commerce platform repurchase preference indicators according to the different needs of consumption, judged the distribution of consumption in different countries, and made a preliminary assumption^[24]. At this time, a class of national average consumption preference indicators${W_P}$as shown in (1) below.

$${W_P}=\frac{{{S_D} - {S_B} \times Q - f}}{{{N_D}}}$$

In formula (1),${S_D}$represent the logistics expenses of countries/regions,${S_B}$represents the weight of the commodity,represents the quality of goods,on behalf of commodity packaging charges,${N_D}$based on the basic charges of representative commodities, further analysis combined with the above formula shows that the charging standards of different countries also have an important impact on the repurchase rate^[25]. At this time, we can calculate the average consumption preference index of the second category of countries${W_Z}$, as shown in (2) below.

$${W_Z}=\frac{{{S_D} - {S_a} \times Q}}{{{N_D}}}$$

In formula (2),${S_a}$representing the loss weight, combined with the above formula, the basic average calculation can be carried out to obtain the comprehensive repurchase preference index of e-commerce platform${T_i}$, as shown in (3) below.

$${T_i}=\frac{{{W_P}+{W_Z}}}{{{N_D}+{N_C}}}$$

In formula (3),${N_C}$representing the proportion of logistics consumption, using the above comprehensive repurchasing preference index of e-commerce platform can effectively calculate the parameters of the subsequent regression model, analyze the factors affecting the repurchasing rate from different perspectives, and improve the accuracy of the analysis.

1.2 Based on user experience, build an analysis regression model of factors affecting the repurchase rate of Hainan cross-border e-commerce platform

User experience refers to the clearly defined feeling of users in the process of using products, which has some connection with the commonness of products. Based on user experience, the factors affecting the repurchase rate can be divided into three types: commodity attribute, logistics attribute, and consumer location attribute. At this time, the comprehensive contribution value function of the three factors$U(X,Q)$as shown in (4) below.

$$U(X,Q)=a\left( {\frac{X}{{{P_2}}}} \right)Q+k{T_i}$$

In formula (4),represents the commodity attribute coefficient,represents the logistics attribute coefficient,${P_2}$represents the attribute coefficient of consumers,represents the weight of commodity influence,represents the weight of logistics impact,${T_i}$represent the influence weight of consumers. Combining the contribution value calculated above, we can arrange the independent variables of influencing factors and build a regression model for influencing factor analysis, as shown in (5) below.

$$h=\frac{{\Delta B}}{{\Delta R}}\cdot A{\left( {\frac{1}{{{P_2}}}} \right)^2}$$

In formula (5),$\Delta B$represent the repurchase effect of consumers,$\Delta R$represents incremental value,represents the elasticity coefficient of repurchase. Combining the above influencing factor analysis regression model, dynamic analysis can be carried out to determine the trend of each variable and improve the accuracy of influencing factor analysis to the greatest extent.

In order to study the analysis effect of the analysis method of influencing factors on the repurchase rate of Hainan cross-border e-commerce platforms based on user experience designed in this paper, this paper takes a cross-border e-commerce platform as an example, and conducts an example analysis, as follows.

2.1 Overview and preparation

B the cross-border e-commerce platform is a large cross-border e-commerce platform, which has strong dynamic novelty. The platform involves more than 20 national consumption channels, and the overall operating cost is high. At present, the platform is divided into several different operation modes, including self built operation, agency operation, platform operation, etc. However, due to the impact of economic fluctuations, the platform currently has problems in logistics, payment, credit and other aspects to varying degrees, and its core competitiveness is gradually declining. The repurchase rate of cross-border e-commerce platforms is related to the consumer experience of users. Therefore, the repurchase rate of cross-border e-commerce platforms can be further studied according to the consumer structure and consumption relationship of users.

Combined with the requirements of case analysis, this paper selects SOR model as the analysis model, analyzes the psychological changes of the human body in combination with the stimulus relationship between the external scene and the human body, and determines the human body are positively correlated. Therefore, in the process of case analysis, the SOR shopping experience research model should be constructed according to the principle of analogical reasoning. In order to improve the effectiveness of case analysis, selects case analysis variables, and the generated case analysis research framework is shown in Fig. 2 below.

It can be seen from Fig. 2 that, in combination with the above case analysis research framework, case analysis assumptions can be made, that is, the impact factors of the repurchase rate can be selected according to the intermediary variables and dependent variables that affect the repurchase rate of cross-border e-commerce platforms, as shown in Fig. 3 below.

It can be seen from Fig. 3 that the influencing factors of cross-border e-commerce platform repurchase rate include platform experience significant influencing trust factor, product experience significant influencing trust factor, and interactive experience significant influencing trust factor. During the instance process, there is a certain conversion relationship between different influencing factors. Therefore, the associated experience coefficient can be obtained according to the conversion correlation between influencing factors, so as to complete the case analysis hypothesis.

In the case analysis process, affected by the virtual shopping environment of the cross-border e-commerce platform, it is difficult for consumers to really feel the goods, so there is a high uncertainty in the factors affecting the repurchase rate of the cross-border e-commerce platform. In view of the above problems, this paper adds intermediary effects in the case analysis process, and puts forward different assumptions. The summary table is shown in Table 1 below.

Table 1

Summary of Case Analysis Assumptions
suppose		Assumption Content
H1	H1a	Platform experience significantly affects trust
	H1b	Product experience significantly affects trust
	H1c	Interactive experience significantly affects trust
	H1d	Relevance experience significantly affects trust
	H1e	Logistics experience significantly affects trust
H2	H2	Trust significantly affects repeat purchase intention
H3	H3a	Platform experience significantly affects repeat purchase intention
	H3b	Product experience significantly affects repeat purchase intention
	H3c	Interactive experience significantly affects repeat purchase intention
	H3d	Relevance experience significantly affects repeat purchase intention
	H3e	Logistics experience significantly affects repeat purchase intention
H4	H4a	Trust has a mesomeric effect in the process of the impact of platform experience on repurchase intention
	H4a	There is a mesomeric effect of trust in the process of the impact of product experience on repurchase intention
	H4a	Trust has a mesomeric effect in the process of interaction experience's impact on repurchase intention
	H4a	There is a mesomeric effect effect of trust in the process of the impact of connected experience on repurchase intention
	H4a	Trust has a mesomeric effect in the process of the impact of logistics experience on repurchase intention

It can be seen from Table 1 that, combined with the above generated hypothesis summary, the case analysis and research model obtained is shown in Fig. 4 below.

It can be seen from Fig. 4 that combining the above example analysis and research model, we can obtain the analysis dimensions of factors affecting the repurchase rate of cross-border e-commerce platforms, generate user experience dimension measurement options, and obtain the user repurchase measurement table, as shown in Table 2 below.

Table 2

Measurement of overall re purchase of users
dimension	Measurement item
Platform Experience	A1. The platform is easy to operate and can be learned to use with minimal time
	A2. This platform provides a sound transaction maintenance mechanism, which can comprehensively prevent the leakage of important personal information and transaction data
	A3. The payment method provided by this platform is very secure, which can effectively protect my account and fund security
	A4. The platform provides a wide range of products that can meet most of my consumption preferences
Product Experience	A5. The quality of the platform's products is good
	A6. The physical product provided by the website is highly consistent with the online description
	A7. I am very concerned about the post purchase experience sharing and communication interaction of other consumers
Interactive experience	A8. Before making a purchase, I will carefully review other buyers' evaluations of the product and service
	A9. The sharing experience with other customers is very important to me
	A10. The platform remembers my shopping habits and will recommend suitable product information to me through various methods (such as text messages, emails, etc.)
Related Experience	A11. The website will issue vouchers or give away points during holidays or event days, which will stimulate me to repeat purchases
Related Experience	A12. If I were a member of this platform, I could enjoy various discounts, but turning to other platforms would result in me losing a lot of benefits
Logistics Services	A13. The platform will provide timely information on ordering and delivery progress through chat boxes or text messages, and I can monitor the delivery status in real-time
	A14. The platform provides multiple logistics modes that I can freely choose from
	A15. The platform can deliver products to me in a relatively short time

It can be seen from Table 2 that the above overall user repurchasing measurement table can be used for statistical description of factors affecting the repurchasing rate, which is the basis for subsequent case analysis.

2.2 Application effect and discussion

In combination with the above overview and preparations, we can conduct an example analysis of the factors affecting the repurchase rate of Hainan cross-border e-commerce platforms. That is, on the basis of the above analysis model of factors affecting the repurchase rate of Hainan cross-border e-commerce platforms, we use the analysis method of factors affecting the repurchase rate of Hainan cross-border e-commerce platforms based on user experience designed in this paper and the conventional analysis method of factors affecting the repurchase rate of cross-border e-commerce platforms. The inter group variance obtained by the two methods is shown in Table 3 below.

Table 3

Application Effect
dependent variable	sexual distinction	age	occupation	income
this text
The platform price is lower than that of physical stores	0.151	0.335	0.141	0.348
Providing physical stores with difficult to purchase products	0.223	0.256	0.356	0.254
Fast logistics speed	0.185	0.241	0.254	0.221
Logistics price discounts	0.241	0.345	0.187	0.148
All day online service	0.159	0.121	0.241	0.284
The platform design is aesthetically pleasing	0.189	0.378	0.115	0.361
Multiple international payment methods	0.245	0.256	0.289	0.174
convention
The platform price is lower than that of physical stores	1.541	2.546	1.216	2.265
Providing physical stores with difficult to purchase products	2.585	3.565	2.582	2.545
Fast logistics speed	1.656	4.546	3.781	3.453
Logistics price discounts	3.884	2.028	2.563	3.189
All day online service	2.989	3.546	3.874	3.255
The platform design is aesthetically pleasing	1.156	2.887	1.285	2.125
Multiple international payment methods	3.654	3.564	4.216	2.151

It can be seen from Table 3 that the inter group variance of the analysis method for influencing factors of the repurchase rate of Hainan cross-border e-commerce platform designed in this paper based on user experience is small under the analysis of different factors of dependent variables, while the inter group variance of the analysis method for influencing factors of the repurchase rate of Hainan cross-border e-commerce platform is large under the analysis of different factors of dependent variables. The above experimental results prove that the analysis method of factors affecting the repurchase rate of Hainan cross-border e-commerce platform based on user experience designed in this paper is effective, reliable and has certain application value.

As early as 2013, China's cross-border e-commerce has achieved initial development. In 2020, China's total export transactions reached a new high, breaking through trillion yuan. In this context, China's cross-border e-commerce has serious competition problems. In order to improve its competitive strength, this paper conducts in-depth analysis on the repurchase rate of users, and designs an effective analysis method of factors affecting the repurchase rate of Hainan cross-border e-commerce platform. The results of case analysis show that the analysis method of factors affecting the repurchase rate of Hainan cross-border e-commerce platform designed has good analysis effect, small variance between groups, reliability and certain application value, and has made certain contributions to promoting the follow-up development of China's cross-border e-commerce.

Ethics Approval and Consent to Participate:

No participation of humans takes place in this implementation process

Human and Animal Rights:

No violation of Human and Animal Rights is involved.

Funding:

No funding is involved in this work.

Data availability statement:

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study

Conflict of Interest:

Conflict of Interest is not applicable in this work.

Authorship contributions:

All authors are contributed equally to this work

ACKNOWLEDGEMENT

1. This work was supported by Project No.721RC1049 Research on factors influencing the repurchase rate of Hainan cross-border e-commerce platform based on user experience

2.This work was supported by Project No. HNKY2021-16 Hainan Provincial Education Department, project-based exploration of web design curriculum based on cross-border e-commerce platform

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Research on Influencing Factors of Repurchase Rate of Hainan Cross-border E-commerce Platform Based on User Experience

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Abstract

Figures

Introduction

Analysis method of influencing factors of repurchase rate of Hainan cross-border e-commerce platform based on user experience

1.1 Select Hainan cross-border e-commerce platform repurchase preference index

Example analysis

2.1 Overview and preparation

2.2 Application effect and discussion

Conclusion

Declarations

References

Additional Declarations

Status:

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