Index system construction method based on cross-border e-commerce supply chain toughness evaluation

Abstract

The invention provides an index system construction method based on cross-border e-commerce supply chain toughness evaluation, which combines a rooting theory and a social network analysis method, constructs a cross-border e-commerce supply chain toughness evaluation index system by collecting cases and interview data and performing coding analysis by using the rooting theory, and screens indexes by means of the social network analysis method. And a comprehensive multi-dimensional evaluation system is formed. According to the method, the accuracy and reliability of evaluation are improved, the practicability and scientificity of an evaluation system are ensured through actual data, enterprises are helped to effectively identify potential risks of the supply chain, and the stability and competitiveness of the supply chain are improved.

Description

Technical Field

[0001] The present invention relates to the field of supply chain resilience assessment system construction, and in particular to a method for constructing an indicator system based on cross-border e-commerce supply chain resilience assessment. Background Art

[0002] With the increasing digitalization of global trade and the rapid development of cross-border e-commerce, the stability and resilience of the supply chain have become important factors affecting the competitiveness of enterprises. The cross-border e-commerce supply chain involves multiple countries and regions, facing challenges such as complex international trade environment, changing logistics conditions and unpredictable market demand. These challenges not only increase the risk of the supply chain, but may also lead to supply chain disruptions, which in turn affects the normal operation of enterprises and customer satisfaction.

[0003] The current research on the construction of supply chain resilience evaluation index system is very limited. The research methods used in most academic studies are often too single and lack comprehensive considerations. Supply chain resilience is a multi-dimensional concept that involves multiple links and levels of the supply chain. Therefore, a diversified approach is needed to build a comprehensive evaluation index system. In addition, existing research also has certain limitations in data collection and processing. Supply chain resilience assessment requires a large amount of real-time and accurate data support, but current data collection methods are often difficult to meet this demand. At the same time, data processing and analysis methods are not advanced enough, and it is difficult to fully explore the information and laws behind the data, which affects the accuracy and reliability of the evaluation results. Therefore, the present invention uses grounded theory and social network analysis to analyze the samples obtained from the literature, cases, and real interviews, and forms a complete cross-border e-commerce supply chain resilience evaluation index system through a combination of quantitative and qualitative methods. Summary of the invention

[0004] A method for constructing an indicator system based on cross-border e-commerce supply chain resilience assessment, characterized in that it specifically includes the following steps:

[0005] S1: Collect case data by entering keywords on the website and collect interview data through telephone interviews and corporate research interviews to obtain original data;

[0006] S2: Using grounded theory, extract information related to the research topic from the original data, and conceptualize and categorize the selected relevant sentences or paragraphs to obtain open coding;

[0007] S3: Using grounded theory, summarize and analyze the categories obtained from open coding to obtain the final main categories, thereby obtaining the main axis coding;

[0008] S4: Using grounded theory, on the basis of open coding and axial coding, through further induction and improvement, the core categories that can dominate other categories are identified, selective coding is obtained, and a cross-border e-commerce supply chain resilience assessment index system is preliminarily constructed;

[0009] S5: Search for papers on CNKI and Web of Science, organize the retrieved literature, and collect samples;

[0010] S6: Use social network analysis to analyze the collected samples. The specific steps are as follows:

[0011] S6-1: The evaluation indicators specified in the literature are regarded as nodes of the network, and the evaluation indicators of different scholars and their related research are regarded as connection points in the social network. Through these connections, a social relationship network of cross-border e-commerce supply chain resilience is formed;

[0012] S6-2: Convert the initial data matrix into a square matrix, perform centrality analysis, and obtain screening indicators;

[0013] S7: semantic clustering is performed on the indicators identified by the two methods. Words with high semantic similarity are merged or processed separately, otherwise they are processed separately, and the indicators are merged;

[0014] S8: Conduct a theoretical saturation test and finally obtain a cross-border e-commerce supply chain resilience assessment index system.

[0015] This paper constructs a comprehensive and multi-dimensional cross-border e-commerce supply chain resilience assessment index system by combining grounded theory and social network analysis, which not only improves the accuracy and reliability of the assessment, but also ensures the practicality and scientificity of the assessment system through the collection and analysis of actual data. This method innovatively combines qualitative research with quantitative analysis, can adapt to the complex and changing environment faced by the cross-border e-commerce supply chain, effectively identify potential risks and vulnerable links in the supply chain, thereby helping enterprises make more scientific and timely decisions, enhance the stability and competitiveness of the supply chain, and ultimately improve customer satisfaction and the market performance of enterprises.

[0016] The unique advantages, core objectives and significant features of the present invention will be presented one by one in the subsequent detailed description. Some details will become clear to professionals in this field after careful study of the specification, or a deeper understanding can be obtained through practical application of the present invention. By reading the specification, readers will be able to achieve the goals of the present invention and fully appreciate the many benefits it brings. In general, the pursuit of the present invention and the many benefits it brings will be fully realized and demonstrated through the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the purpose, technical solutions and significant advantages of the present invention, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, in which:

[0018] Figure 1 This is a schematic diagram of the overall process of a method for constructing an indicator system based on cross-border e-commerce supply chain resilience assessment;

[0019] Figure 2 Flowchart for Grounded Theory Analysis

[0020] Figure 3 Research Flowchart for Social Network Analysis

[0021] Figure 4 Social network analysis diagram for cross-border e-commerce supply chain resilience

[0022] Figure 5 Framework diagram of the cross-border e-commerce supply chain resilience assessment indicator system DETAILED DESCRIPTION

[0023] Through the following detailed specific examples, we will demonstrate the implementation method of the present invention, so that professionals in this field can easily grasp the core points of the present invention and the benefits it brings. It is worth noting that the essence and purpose of the present invention are open, and it allows it to be implemented through a variety of different implementation methods, and these methods will not deviate from the original intention of the present invention. Every detail disclosed in this specification can be appropriately adjusted and optimized according to different perspectives and application scenarios without violating the spirit of the present invention. Next, we will combine specific embodiments and drawings to further explain the technical solution of the present invention.

[0024] like Figure 1 As shown, the present invention proposes a method for constructing an index system based on cross-border e-commerce supply chain resilience assessment, and the specific steps are described as follows:

[0025] This paper uses grounded theory. In order to maximize the systematic and scientific nature of the case coding process, manual coding is mainly used in case coding. In addition, Nvivo11.0 is used as an auxiliary tool. Through continuous case collection, analysis and comparison, a cross-border e-commerce supply chain resilience evaluation index system is initially constructed. The process is as follows: Figure 2 shown.

[0026] Step 1: By entering keywords such as "cross-border e-commerce supply chain resilience", "supply chain management", and "factors affecting supply chain resilience" on websites such as Dianshubao, Netease, Hugo Cross-border, Ebrun, and iResearch, we collected industry reports and cases on cross-border e-commerce supply chain resilience and collected case materials; we interviewed experts from companies engaged in cross-border e-commerce supply chain related work through telephone interviews and corporate research interviews to collect interview materials. The interview results and case literature materials were collated and summarized, and a total of more than 35,000 words of original text materials were obtained.

[0027] Step 2: Using grounded theory, extract information related to the research topic from the original data, and conceptualize and categorize the selected relevant sentences or paragraphs to obtain open coding;

[0028] Step 2-1: Compile the text. Read the coded case materials carefully, find the key sentences and analyze them word by word, and number the selected sentences or paragraphs in the form of [An].

[0029] Step 2-2: Conceptualization. After a preliminary analysis of the original case material, any sentence that can be encoded is given a conceptualized label to form a free node, and the result of conceptualization is recorded as An.

[0030] Step 2-3: Categorization. Further compare and analyze the already formed concept nodes, gradually abstract and summarize them into multiple concept nodes, and cluster the initial concepts with the same or similar meanings into categories, represented by [Bn]. According to the above steps, the present invention screened and sorted out 232 sentences or paragraphs about the resilience of cross-border e-commerce supply chains from the original text materials, from which 45 concepts and 36 categories were excavated. Due to limited space, only the open coding process of part of the coded text is listed, see Table 1.

[0031]

[0032] Table 1 Open coding excerpt

[0033] Step 3: Using grounded theory, the 36 categories obtained by open coding were summarized and analyzed to obtain the final 15 main categories. The results are represented by [Cn]. As shown in Table 2, the results obtained by axial coding are: risk prediction capability, supply chain visibility, supply chain agility, dynamic adjustment capability, logistics service efficiency, cross-border payment capability, enterprise economic scale, cost management capability, social security level, collaborative cooperation capability, government support, information sharing capability, infrastructure construction, information management capability, and redundant design capability.

[0034]

[0035] Table 2

[0036]

[0037] Table 2 Overview of main categories and corresponding subcategories

[0038] Step 4: Analyze the 15 main categories and combine them with the cross-border e-commerce supply chain resilience management system, that is, respond to market changes, risks and uncertainties, and achieve efficient operation and sustainable growth of the supply chain. The following relationships are found: Risk prediction ability and supply chain visibility are the basis of supply chain management, involving accurate prediction and estimation of future demand changes, so "prediction ability" is considered as a core category. Supply chain agility, dynamic adjustment ability, logistics service efficiency, and cross-border payment ability are related to the ability to respond quickly to supply chain changes, so "response ability" is considered as a core category. Large economic scale and strong cost management ability of enterprises are conducive to improving the response and resistance of the supply chain, so "resistance" is considered as a core category. Enhanced social security, enhanced collaborative cooperation ability, and increased government support are conducive to supply chain emergency response and can have a positive impact on the resilience of the supply chain, so "resilience" is considered as a core category. Innovation sharing ability, infrastructure construction, information management ability, and redundant design ability enable cross-border e-commerce supply chains to better respond to market changes and adapt to different operating environments, so "adaptability" is considered as a core category. According to the above ideas, a preliminary cross-border e-commerce supply chain resilience assessment index system was constructed, as shown in Table 3.

[0039]

[0040] Table 3 Selective coding process

[0041] As a qualitative research method, grounded theory relies on the personal experience of the interviewees and has a certain degree of subjectivity in its analysis. Therefore, in order to enhance the objectivity of indicator construction, the present invention adopts a quantitative method to screen the indicators. Social network analysis conducts quantitative research by evaluating the relationships between network members. It focuses on the characteristics of network nodes and the connections between nodes, revealing the characteristics of network structure and the interactions between members. As one of the most commonly used tools in social network analysis, UCINET software can structure data into graphics for easy analysis and interpretation. The present invention uses UCINET software to process data, and combines existing indicator research results to apply social network analysis to construct an evaluation system for the resilience of cross-border e-commerce supply chains. Through social network analysis, we can explore the interaction patterns and laws of each participant in the network, as well as the centrality of the network structure, as a basis for selecting evaluation indicators. The specific ideas are as follows Figure 3 shown.

[0042] Step 5: Set the literature acquisition channels as CNKI and Web of Science. Because improving supply chain resilience is an important way to deal with supply chain risks, "cross-border e-commerce supply chain", "cross-border e-commerce supply chain risks", "cross-border e-commerce supply chain resilience influencing factors" are used as the main search fields, and the journal literature sources are set to core and above. "Title" or "Keywords" are used for advanced search, a total of 57 articles, and the statistical time is 2013-2024. The paper search conditions and search results are shown in Table 4.

[0043]

[0044] Table 4 Search conditions and search results

[0045] Step 6: Use social network analysis to analyze the collected samples. The specific steps are as follows:

[0046] Step 6-1: Consider the evaluation indicators specified in the literature as nodes of the network, and the evaluation indicators of different scholars and their related research as connection points in the social network. Through these connections, a social relationship network of cross-border e-commerce supply chain resilience is formed;

[0047] Step 6-2: In the original Excel matrix, the vertical coordinates are the indicators extracted from the literature, and the horizontal coordinates are the authors of the literature. The 0 and 1 in the matrix refer to whether the author mentioned the indicator in other research papers. If the author mentioned a specific indicator, the connection between them and the indicator is recorded as 1, otherwise it is 0. Based on the initial data matrix converted into a square matrix, the centrality analysis is performed, as shown in Table 5. The final results are shown in Figure 4 ;

[0048]

[0049] Table 5

[0050]

[0051] Table 5 Indicator screening results based on social network analysis

[0052] from Figure 4It can be seen from Table 5 that the centralities of supply chain agility, real-time supervision capability, infrastructure construction, strategic inventory capability, etc. are relatively high, all greater than the average value, indicating that they are the focus of the evaluation. However, the centralities of transportation service quality, inventory guarantee, etc. are lower than the average value, and are not highly representative, so they should be discarded. Based on the social network analysis method, the present invention obtains a total of 15 influencing factors of cross-border e-commerce supply chain resilience, namely, supply chain agility, information management capability, infrastructure construction, strategic inventory capability, risk prediction capability, cross-border payment capability, dynamic adjustment capability, regional collaboration capability, government support, logistics distribution method, real-time supervision capability, knowledge sharing capability, enterprise economic scale, cost control capability, and social security degree.

[0053] Step 7: semantically cluster the indicators identified by the two methods, merge or select one of the words with high semantic similarity, and process them separately. For example, cross-border logistics service capability includes logistics service efficiency and cross-border logistics distribution mode, so the present invention takes the cross-border logistics service capability as the indicator after merging; because the research object is the cross-border e-commerce supply chain, facing the international market, the collaborative cooperation capability and the regional collaboration capability are merged into the cross-regional collaboration capability to make the description more accurate.

[0054] The combined results are shown in Table 6.

[0055]

[0056] Table 6 Merge results

[0057] Step 8: Theoretical saturation refers to the inability to identify new concepts or discover new connections between categories when analyzing new data, indicating that the theory is close to completion. This concept is a key criterion for determining whether the analysis can be terminated. Therefore, in order to ensure the breadth of the research and the accuracy of the theoretical saturation assessment, the present invention coded the five newly added industry reports. The analysis shows that the concepts and categories in these new data are highly overlapping with the previous analysis, and fail to provide new category information or reveal unknown connections between categories. Based on these findings, the present invention believes that the previous coding analysis has reached the theoretical saturation point. Combined with the real-world background and expert interviews, the final indicator framework for evaluating the resilience of the cross-border e-commerce supply chain is obtained as follows: Figure 5 shown.

Claims

1. A method for constructing an index system based on cross-border e-commerce supply chain resilience assessment, characterized in that: The method comprises the following steps: S1: Collect case data by entering keywords on the website and collect interview data through telephone interviews and corporate research interviews to obtain original data; S2: Using grounded theory, extract information related to the research topic from the original data, and conceptualize and categorize the selected relevant sentences or paragraphs to obtain open coding; S3: Using grounded theory, summarize and analyze the categories obtained from open coding to obtain the final main categories, thereby obtaining the main axis coding; S4: Using grounded theory, on the basis of open coding and axial coding, through further induction and improvement, the core categories that can dominate other categories are identified, selective coding is obtained, and a cross-border e-commerce supply chain resilience assessment index system is preliminarily constructed; S5: Search for papers on CNKI and Web of Science, organize the retrieved literature, and collect samples; S6: Use social network analysis to analyze the collected samples. The specific steps are as follows: S6-1: The evaluation indicators specified in the literature are regarded as nodes of the network, and the evaluation indicators of different scholars and their related research are regarded as connection points in the social network. Through these connections, a social relationship network of cross-border e-commerce supply chain resilience is formed; S6-2: Convert the initial data matrix into a square matrix, perform centrality analysis, and obtain screening indicators; S7: semantic clustering is performed on the indicators identified by the two methods. Words with high semantic similarity are merged or processed separately, otherwise they are processed separately, and the indicators are merged; S8: Conduct a theoretical saturation test and finally obtain a cross-border e-commerce supply chain resilience assessment index system.

2. The method according to claim 1, characterized in that In S1, case data were searched by entering keywords in websites related to e-commerce and supply chain management, and interview data were collected through telephone interviews and enterprise research interviews.

3. The method according to claim 1, characterized in that: The grounded theory analysis steps included manual coding and the use of Nvivo11.0 as an auxiliary tool for continuous case collection, analysis, and comparison.

4. The method according to claim 1, characterized in that: The grounded theory analysis steps include: a. compiling the text, carefully reading the coded case materials, finding the key sentences and analyzing them word by word, and numbering the selected sentences or paragraphs in the form of [An]; b. conceptualization, after preliminary analysis of the original case materials, give any coded sentences a conceptual label to form a free node, and the result of conceptualization is recorded as An; c. categorization, further comparing and analyzing the already formed concept nodes, gradually abstracting and summarizing them into multiple concept nodes, and clustering and merging the initial concepts with the same or similar meanings into categories, represented by [Bn].

5. The method according to claim 1, characterized in that The steps of the social network analysis method include: a. using UCINET software to process data, and combining existing indicator research results, applying social network analysis to construct an evaluation system for cross-border e-commerce supply chain resilience; b. through social network analysis, exploring the interaction patterns and rules of each participant in the network, as well as the centrality of the network structure, as the basis for selecting evaluation indicators.

6. The method according to claim 1, characterized in that In S7, semantic clustering is performed on the indicators identified by the two methods, and words with high semantic similarity are merged or processed one of them, otherwise they are processed separately.

7. The method according to claim 1, characterized in that In order to ensure the breadth of the research and the accuracy of the theoretical saturation assessment, a theoretical saturation test was conducted in S8, and the newly added industry reports were coded. The concepts and categories in these new data were analyzed to see whether they were highly overlapped with the previous ones, whether they provided new category information or revealed unknown inter-category connections, so as to determine whether the theoretical saturation point had been reached.

8. A cross-border e-commerce supply chain resilience assessment index system, characterized by: The system is constructed based on the method described in any one of claims 1 to 7, and includes evaluation indicators in multiple dimensions such as supply chain agility, responsiveness, resistance, recovery, information management capability, collaborative cooperation capability, and government support.

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