Research on Constructing a Village Financial Management Model Based on Cloud Finance in the Context of Rural Revitalization Strategy

With the acceleration of China’s urbanization process and the transfer of rural population to cities, the rural economy is facing serious challenges. The implementation of the rural revitalization strategy can promote the development of the rural economy, raise the income level of farmers, narrow the gap between urban and rural areas, and realize the overall progress of rural society [1-4]. Rural revitalization strategy refers to a series of policies and measures formulated in the process of achieving rural modernization and promoting agricultural and rural development [5-6]. It aims to promote the take-off of rural economy and the improvement of farmers’ living standards through comprehensive initiatives in reform and innovation, industrial development, ecological protection, and infrastructure construction [7-9].

Cloud finance refers to the financial management system deployed in the cloud, through cloud computing technology to achieve financial data processing, storage and analysis. Compared with the traditional financial management, cloud finance has the characteristics of real-time, scalability, security, flexibility and so on [10-13], which is an important technology in today’s financial industry. Under the background of rural revitalization, cloud finance has an important role in village-level financial management, and it can realize real-time processing, analysis and management of financial data. And the village financial management department is one of the important departments of the village organization [14-17]. It is responsible for the preparation, implementation, supervision and management of the financial budget of the village-level collective economy, as well as the statistical analysis and summary reporting of the village-level collective income and expenditure. At the same time, the formulation, propaganda and training of financial management policies, regulations and systems for village-level organizations are also important tasks of village-level financial management departments [18-21].

With the help of cloud computing and mobile networking technology, this paper proposes a specific construction program for village-level financial management model, and designs the overall framework and functions of village-level cloud financial management platform, which mainly covers master data management, fund management, asset management and other contents. It improves the village financial management system and process, establishes a standardized accounting system, uses the advantages of cloud financial agency services and technological innovation, exerts the synergistic effect of village financial management and other platforms, reduces the cost and construction difficulty of rural financial management informationization, and enhances the value of financial management. In order to test the credibility of the method of this paper, the cloud financial management platform is modeled using complex networks, and its structural eigenvalues are calculated to evaluate the credibility of the village-level cloud financial management platform. Finally, the effects of the cloud financial management platform after its application by village-level organizations in City Z are analyzed.

2

Cloud-based village financial management model

Based on the research perspective of village financial management mechanism in the context of rural revitalization, through visiting and researching and data analysis, it is found that there are problems such as non-standard accounting operation institutions, low level of financial management of village accounting institutions, difficulties in financing of village collective economic organizations, unsound internal control system of village collective economy, limited mode of income of village collective economy, and non-positive and non-standard mechanism of village benefit distribution in the management of village projects and funds. For this reason, this paper proposes a cloud-based model for village financial management that provides reference and assistance for optimizing village financial management mechanisms in rural revitalization projects.

2.1

Overall framework of the village cloud financial management platform

The overall framework of the village-level financial management cloud platform is divided into three levels from bottom to top: infrastructure service layer (laaS), platform service layer (PaaS) and software service layer (SaaS) [22]. The platform service layer and infrastructure service layer are oriented towards the software service provider as application support, and the software service vendor is responsible for their use and management. The software service layer as the application platform is directly facing the users, and the government, the village committee, the agency bookkeeping company and the villagers can access the cloud computing half-table through the service terminals (computers, cell phones, etc.) and obtain the required services.

The overall framework of the cloud financial platform is shown in Figure 1. The main features and advantages of the village financial management system deployed as a Saas layer are mainly [23]:

1) Accelerates the progress of software deployment, avoids the risk of software deployment failure, and reduces the difficulty of promotion.

2) Greatly reduce the construction cost of village-level financial management informationization.

3) Possesses high security.

4) Has good scalability.

In practical applications, priority can be given to the use of existing mature fair platforms, such as government cloud, Ali cloud, Baidu cloud, etc., in order to reduce the difficulty and complexity of construction, reduce the cost of construction, and reduce the dependence on hardware, storage, network, security and other aspects. Put the core focus on the construction of the business platform for village-level financial management, that is, focus on the SaaS layer.

2.2

Village-level cloud financial management platform management functions

The functional framework of the village cloud financial management platform is shown in Figure 2, which is centered on the management of rural “three capitals”, starting from the management of funds, assets, resources, etc. By sorting out the business system and management process, it can conveniently, openly, transparently, and standardly record the financial management matters of the village. It establishes full-process management including information collection, process approval, business processing, report analysis, supervision, and early warning.The main construction content includes master data management, fund management, asset management, resource management, report analysis, supervision and early warning, village affairs disclosure, and other functions.

2.2.1

Master data management

Master data is the basic data used to describe the core business entity, and master data management mainly provides the maintenance of basic data, such as accounting entries, correspondent units, villagers’ representatives, and the nature of funds.

Due to the chaotic management of village-level financial master data, the accounting account system is not uniform, and there are problems such as redundancy of basic data between different townships in the same county, non-uniformity of coding, and inconvenience for users to query the data. The content of master data management is to integrate the most core and most necessary data to be shared in the centralized accounting business, which is centrally managed and maintained by the county, and timely distributed to each township according to the business needs of each township.

By using the master data management function, the following objectives can be achieved:

1) Effective centralized management of master data can distribute unified, accurate and perfect master data to each village in each township in a timely manner, which is convenient for their business operations and data analysis.

2) Analyzed from the perspective of information system construction, master data management can increase the flexibility of the system and more flexibly meet the changes in the business requirements of each tenant.

2.2.2

Funds management

The fund management business module mainly provides centralized management of all funds of rural collectives, and the construction includes bill management, budget management and account processing.

1)

Bills Management

In order to carry out unified management of different types of bills in village-level reporting, avoid the phenomenon of lost bills and incomplete reporting procedures, and standardize the bill management system by making bills electronic.

2)

Budget management

In the village-level financial reporting, all income and expenditure must be included in the account accounting, all expenses must comply with the system’s provisions, and there must be real bills as evidence.The use of collective funds within the village must be within the constraints of the system, and all expense categories must be controlled within the prescribed limits.

3)

Accounts processing

In account processing, accounting books in rural areas are standardized, and the accounting system is unified by the county as the standard tenant, including the establishment of standardized accounts, auxiliary accounting, and so on.

2.2.3

Asset management

Asset management business module mainly provides centralized management of collectively owned assets in rural areas, including rural collective housing, buildings, machinery, equipment and other fixed assets, water conservancy, transportation, culture, education and other basic public welfare facilities, as well as agricultural assets and other assets.

1)

Asset registration

Rural collective land and other resource assets management ownership is ill-defined, contracting is not standardized, registration is not clear, the existence of collective assets by the villagers at a low price contracted or uncompensated possession and use of the phenomenon. In order to solve this problem, asset management is carried out by means of an asset ledger, which registers in detail the asset category, quantity, value, use and other information of each asset, takes an inventory of the assets, and discloses the use of the assets to the villagers on a regular basis.

2)

Leasing and Lending of Assets

Contracting, leasing, lending, transferring, and other transactions related to rural collective assets must abide by the principles of openness, justice, and fairness.In accordance with the procedures for leasing and lending of assets, and strict registration and management, all villagers can be clear about the use of collective assets.

3)

Disposal of assets

Rural collective assets due to irresistible factors such as asset destruction, demolition and reconstruction, facilities and equipment scrapping, etc.It needs to be in accordance with the asset disposal procedures in the system for immediate registration.Through the asset disposal function, the management of rural collective assets is realized, so as to make the accounts consistent with the actual situation.

2.3

Optimized design of village financial management model

2.3.1

Management model optimization

The establishment of a cloud financial management platform at village level is the cornerstone for achieving budget management integration. Now, the budget integration system at the county level and above has been basically improved, which includes the basic information management module, the project library, the budget preparation, execution and general accounting modules, all of which have been functioning normally. In addition, the cloud financial management platform has also covered the entire budgeting, indicator, treasury payment, and accounting processes.The interconnection between the Government Procurement Agency and the Asset Business System has been accelerated to enhance overall operational efficiency. By adopting the cloud financial management platform, the standardization and standardization of financial operations in the province can be achieved, thus improving efficiency and quality.

Through precise financial supervision, budget application and execution can be supervised and controlled throughout the entire process, and every expenditure can be monitored in real-time through the system. By establishing the foundation of financial big data application, it realizes T+1 aggregation of budget data in the province, and utilizes the function of jurisdictional data query to supervise and manage the budget, execution, revenue and expenditure in the province.

Similarly, applying the cloud financial management platform to village-level organizations, the model is basically consistent with the township level and above, and the management model based on the village-level cloud financial management platform is shown in Figure 3. Among other things, the listed village-level organizations are responsible for managing basic information management and payment entry, while other modules are still executed and managed by the Village Accounts Office Records Centre on their behalf.

2.3.2

Management process evaluation

The use of cloud financial management platform is a new financial governance model for village-level organizations using big data and cloud computing, which is bound to bring unprecedented progress and development to the financial governance of village-level organizations. Now, combining the cloud platform design and the financial management design scheme of village-level organizations, the credibility evaluation system of the cloud financial management platform is constructed from the three dimensions of financial level enhancement, management work improvement, and the characteristics of the platform itself. The details are as follows:

1) Financial level improvement consists of three evaluation indexes: budget execution, centralized payment and unit accounting, which are determined by the main application modules of cloud financial management platform.

2) Improvement of management work consists of 2 evaluation indicators, namely, simplification of process and effective supervision, which mainly refers to the simplification of work content and the visualization of the supervision process at the upper level in the process of using.

3) The characteristics of the platform itself are composed of three evaluation indicators: security, reliability, and simplicity. As a software product, whether cloud financial management is safe, reliable, and practical will have an impact on the application of village-level organizations. Specific evaluation methods and indicators will be described in the next chapter.

3

Cloud financial management platform credibility evaluation model

Software trustworthiness is a concept used to express the quality of software. It refers to the comprehensive characteristics and guarantee methods of multiple quality attributes in the process of using software systems.In the case of cloud financial management platforms, trustworthiness refers to a series of trustworthy attributes, such as compliance, security, and integrity, that should be possessed during the process of using the platform.

Although the cloud financial management platform, which relies on cloud computing, provides technical support for the financial management and business decision-making work of organizations in the new era. However, if the degree of system trustworthiness cannot meet the needs of village-level organizations, and problems such as failures occur from time to time, villages will not only be unable to enjoy the convenience brought by accounting informatization, but will even suffer great losses. Therefore, only by providing users of cloud financial management platform with accurate credibility evaluation methods, so that they can effectively choose a safe and credible accounting informatization system, cloud finance can play its maximum utility, so that enterprises can really benefit from it. In this paper, complex network theory is used to model the cloud financial management platform as a complex network and calculate its structural eigenvalues. Subsequently, through the derived structural eigenvalues, the link between the structural eigenvalues of the cloud financial management platform and the trustworthiness attributes is established, thus realizing the trustworthiness evaluation of the financial management platform.

3.1

Complex Network Characterization and Metrics

Combining the characteristics of each network characteristic parameter and the research focus of this paper, four parameters, namely, degree and degree distribution value, standard structural entropy, average path length and tightness, are selected for the relevant research [24]. Each network characteristic parameter is described as follows:

1)

Node degree and degree distribution

In graph theory, the degree of a node is defined as the number of associated edges a node has, the in-degree of a node refers to the number of directed edges to that node, and the out-degree refers to the number of directed edges to other nodes. The degree distribution is calculated as: (1) $k_{i} = \sum_{e = E} δ_{e}^{i}$

Among them: (2) $δ_{e}^{i} = {\begin{matrix} 0, t h e e d g e e c o n t a i n s t h e n o d e \\ 1, e d g e e d o e s n o t c o n t a i n n o d e s \end{matrix}$

In order to better characterize the connectivity of each node in the whole network, the concept of degree distribution is introduced, which is essentially the probability distribution function of different degree values. For example, the node degree distribution function p(k) refers to the probability distribution function of the degree value of k in the whole network, and its calculation formula is as follows: (3) $p (k) = \sum_{k' = k}^{\infty} p (k^{'})$

2)

Standard structural entropy

Entropy is the short form of entropy value, which is initially used to describe the degree of stability and orderliness of molecular motion in thermodynamic problems. In network science, the network structure entropy is used to describe whether the whole complex network structure has the characteristic of orderliness, but in order to eliminate the influence of the changes of different complex networks, the standard structure entropy is derived from the normalization of the network structure, and accordingly to judge the degree of orderliness among different complex networks. The derivation of standard structural entropy is as follows:

First, the degree value of node i is compared to the total degree value of the whole network to find out the importance degree of that node as I_i, i.e.: (4) $I_{i} = k_{i} / \sum_{i = 1}^{N} k_{i}$

Then the network structure entropy E is: (5) $E = - \sum I_{i} \ln I_{i}$

At the same time, in order to eliminate the mutual influence between nodes and edges of networks of different sizes, the structure entropy E is normalized.

If the maximum value of network structural entropy E is denoted as E_max and the minimum value of network structural entropy is denoted as E_min, it can be concluded that the standard network structural entropy after network normalization is E_s: (6) $E_{s} = \frac{E - E_{\min}}{E_{\max} - E_{\min}}$

Therefore, the network structure entropy E is maximized when $I_{i} = \frac{1}{N}$ . The network is a uniform network at this point: (7) $E_{\max} = \ln N$

When E is the minimum value, the corresponding network structure is a star network, in this case: (8) $E_{\min} = \ln n - (\frac{n - 1}{n}) \ln (n - 1)$

Finally, the resulting E_max and E_min can be found by bringing them into the network standard structural entropy E_s equation: (9) $E_{s} = 1 - \frac{n [\sum_{k = 1}^{n} p (k) \ln p (k) + \ln n]}{(n - 1) \ln (n - 1)}$

3)

Average path length

The shortest path in a network is defined as the path with the least number of edges between two connected nodes i and j. And the distance d_ij between node i and node j is defined as the number of edges passed by the shortest path of these two connected nodes. The average path length L of the network is then the average of the distance d_ij between any two nodes i and j, i.e.: (10) $L = \frac{1}{\frac{1}{2} N (N - 1)} \sum_{i \geq j} d_{i j}$

4)

Compactness

For a network with N nodes, the tightness of a given node V is the product of the total number of nodes in the entire network minus 1 and the reciprocal of the shortest path cumulative value for that node and the remaining nodes in the network, which is calculated by the formula: (11) $C (v_{i}) = {[\sum_{j = 1}^{N} d_{i j}]}^{- 1} (N - 1)$

3.2

Complex network modeling

In this study, complex network theory will be used to measure the trustworthiness of financial management platform in cloud accounting environment. Firstly, based on the accounting collocations between the modules of the financial management platform in the cloud financial environment, it is abstracted into a complex network graph using Pajek, a complex network analysis software, where each sub-module is considered as a vertex. With Pajek, a large network can be decomposed into a number of smaller networks so that more effective methods can be used in subsequent processing, providing users with powerful visualization and manipulation tools to execute effective algorithms to analyze large-scale networks.

3.2.1

Model Vertex Settings

1)

General Ledger Sub-module Vertex Setting

General ledger sub-module vertex setting is shown in Table 1, which contains 58 (1~58) vertices in total. General ledger sub-module is an important part of accomplishing accounting work by acquiring, processing financial data and saving related information. The General Ledger sub-module is the most common module used in all financial management work and plays a crucial role in the entire financial management workflow, guaranteeing the accuracy and credibility of financial information output.The apex setting of this module has a significant impact on the evaluation of the credibility of financial management in the cloud financial environment.

Table 1.

Vertex Settings of the general ledger submodule

Vertex ID	Vertex name	Vertex ID	Vertex name
1	General ledger	30	Operating expenses
2	Account balance sheet	31	Itemized list of subjects
3	Calculate the project general ledger	32	Accounting project balance sheet
4	Summary of cost of goods sold	33	Summary of gross profit on sales
5	Summary of collection and settlement	34	Schedule of accounts receivable
6	Accounts receivable	35	Summary of accounts payable
7	Statement of accounts payable	36	Aging analysis sheet
8	Quantity and amount ledger	37	Transfer history information table
9	Accounting account	38	Certificate word
10	Document entry	39	Voucher amortization
11	Certificate query	40	Final closing
12	Summary of vouchers	41	Current statement
13	Breakdown of bad debts	42	Reverse closing
14	Cash flow inquiry	43	Subsidiary ledger
15	Financial statement	44	Certificate audit
16	Multi-column ledger	45	Voucher cancellation
17	Summary table of account items	46	Write-off management
18	Calculate the project ledger	47	Cash flow statement
19	Statement of cost of goods sold	48	Schedule item adjustment
20	Summary of accounts receivable	49	Voucher query during adjustment
21	Payment calculation schedule	50	Voucher accrual
22	Account payable warning form	51	Final transfer
23	Quantity and amount ledger	52	Automatic transfer
24	Adjustment period management	53	Report processing
25	Accounting item	54	Reverse Posting
26	Certificate processing	55	Profit and loss carried forward
27	Bad debt statistical analysis table	56	Current write-off
28	Schedule item	57	Bad loan entry
29	Document entry during adjustment	58	Detailed classification

As different cloud financial environment financial management service providers more or less always have some conceptual differences, the general ledger sub-module meets the basic accounting relationships at the same time, the sub-module’s internal data logic structure and vertex settings will be personalized according to the customer’s business structure and the different needs of enterprise management.

2)

Vertex setting of fund management sub-module

The vertex setting of fund management submodule is shown in Table 2, which contains 31 (59~89) vertices. Village-level organizations should use the fund management submodule to implement centralized and unified management of funds in the financial management system under the cloud financial environment.This module is responsible for managing fund flow, fund settlement, and operations management in the financial management platform under the cloud financial environment.The fund management sub-module is involved in the occurrence of business in the production and operation activities of the enterprise and generates interaction between accounting information. And it is an important module that should not be ignored when measuring the credibility of the financial management platform in the cloud financial environment.

Table 2.

Vertex Settings of the fund management submodule

Vertex ID	Vertex name	Vertex ID	Vertex name
59	Request for funds	75	Bank statement
60	Internal interest rate	76	Payment schedule
61	Borrowing interest	77	Financial position list
62	Credit list	78	Financial balance
63	Cash access	79	Electronic statement
64	Receipt order	80	Internal interest statistics
65	Notes receivable	81	Daily bank deposit statement
66	Bank account	82	A running bank account
67	Fund inquiry	83	Bank deposit flow journal
68	Bank payment	84	Bank transfer
69	Bank account	85	Fund allocation
70	Capital transfer	86	Cash journal
71	Subdivision of funds	87	Bill balance sheet
72	Draw on a bill	88	Fund distribution
73	Draw down a bill	89	Bank account balance
74	Cash count	-

3)

Fixed Assets Sub-module Vertex Setting

The fixed assets sub-module vertex settings are shown in Table 3, which contains a total of 30 (90~119) vertices. Good fixed asset sub-module vertex settings enable the financial management platform in the cloud financial environment to effectively count, manage and supervise the fixed assets with high unit price and dispersed range of roles that exist in the village-level organizations, and generate close information interaction with other sub-modules. The specific linkage is to pass the vouchers generated in the fixed assets sub-module to the general ledger sub-module for accounting processing, and to pass the accounting information related to depreciation expense to the cost management sub-module when calculating the cost of products. If the financial management platform in the cloud financial environment can complete the above financial management work in real time and efficiently, then it can be said that the cloud financial management platform has a high degree of credibility and the creation and expression of financial information is at a relatively credible level.

Table 3.

Vertex Settings of the fixed assets submodule

Vertex ID	Vertex name	Vertex ID	Vertex name
90	List of fixed assets	105	Asset purchase order
91	Statement of increase in fixed	106	Asset transfer order
92	Depreciation schedule of fixed	107	Asset attribute
93	Card entry	108	Provision for depreciation
94	Fixed assets inquiry	109	Inventory plan
95	Asset purchase plan	110	Statement of changes in fixed assets
96	Department transfer order	111	Summary of depreciation of fixed assets
97	Asset information	112	Fixed assets inventory form
98	Depreciation method	113	New increase in fixed assets
99	Change in original value	114	Liquidation of fixed assets
100	Schedule of fixed assets	115	Asset purchase status
101	New table of fixed assets	116	Asset transfer order
102	Depreciation expense allocation	117	Use condition
103	Fixed assets card	118	Depreciation adjustment
104	Changes in fixed assets	119	Balance sheet of fixed assets

3.2.2

Compliance testing

According to the functions of accounting and management, the financial management platform under cloud financial environment is divided into several sub-modules, and the logical structure of each module should be in line with the basic norms and collocation of financial work. Compliance is a basic credibility requirement for the financial management platform in the cloud financial environment. It requires the product to meet the relevant requirements for financial work.

The compliance of the financial management platform in the cloud financial environment requires that every sub-module in the system structure is capable of fulfilling its duties. Therefore, to measure the trustworthiness of the cloud financial platform, it must first be tested for compliance and meet the module setup compliance test.

3.3

Credibility level determination

In this paper, five language variables are used to describe the trustworthiness level of the cloud financial platform: “Untrustworthy (VL)”, “Very Poor (VB)”, “Low Confidence (L)”/“Bad (NG)”, “Medium Confidence (MT)”/“Medium (M)”, “High Confidence (H)”/“Good (G)”, and “Very Trustworthy (VH)”/“Very Good (VG)”. Each grade is represented by triangular fuzzy numbers in the range of 0~10, and the language variables represented by triangular fuzzy numbers are shown in Table 4.

Table 4.

Language variables represented by triangular fuzzy numbers

Linguistic variable	Triangular fuzzy number (1, m, u)
VL/VB	(0, 0, 3)
L/NG	(3, 4.5, 6)
MT/M	(6, 7.5, 8.5)
H/G	(8.5, 9, 9.5)
VH/ VG	(9.5, 10, 10)

Suppose there is m platform to be evaluated under S_i(i=1,2,⋯,m), n credible indicators TA_j(j=1,2,⋯,n), and r evaluation experts. Each expert describes the fuzzy evaluation of the trustworthiness of system S_i under indicator TA_j based on the experience of using cloud accounting AIS using triangular fuzzy language, and the specific fuzzy evaluation matrix is: (12) $T A_{1} T A_{2} \dots T A_{n}$ (13) $(W_{1}^{(*)} W_{2}^{(*)} \dots W_{n}^{(*)})$ (14) ${\tilde{E}}^{k} = \begin{matrix} A_{1} \\ A_{2} \\ ⋮ \\ A_{m} \end{matrix} [\begin{matrix} {\tilde{e}}_{11}^{k} & {\tilde{e}}_{12}^{k} & \dots & {\tilde{e}}_{1 n}^{k} \\ {\tilde{e}}_{21}^{k} & {\tilde{e}}_{22}^{k} & \dots & {\tilde{e}}_{2 n}^{k} \\ ⋮ & ⋮ & ⋱ & ⋮ \\ {\tilde{e}}_{m 1}^{k} & {\tilde{e}}_{m 2}^{k} & \dots & {\tilde{e}}_{m n}^{k} \end{matrix}], k = 1, 2, \dots, r$

Where, $w^{(*)} = (W_{1}^{(*)}, W_{2}^{(*)}, \dots, W_{n}^{(*)})$ is the weights of AIS credible indicators derived in the previous section, and $e_{i j}^{k}$ is the fuzzy judgment of system S_i credibility under credible indicators TA_j given by the krd expert. In this paper, we assume that the judgment result of each expert has equal importance, and synthesize the fuzzy evaluation matrix of r experts to get: (15) $\tilde{E} = {({\tilde{e}}_{i j})}_{m \times n}$

Satisfaction: (16) ${\tilde{e}}_{i j} = \frac{1}{r} \otimes ({\tilde{e}}_{i j}^{1} \oplus {\tilde{e}}_{i j}^{2} \oplus \dots \oplus {\tilde{e}}_{i j}^{r})$

Where, e_ij represents the average fuzzy judgment of system s_i ‘s credibility under index TA_j given by r experts, and the credibility grade e_i is obtained after defuzzification process, then the credibility evaluation value of the system is: (17) $E V S T = \sum_{i = 1}^{n} e_{i} * W_{i}^{(*)}$

4

Case studies

According to the design scheme of Chapter 2, the program of village-level financial management cloud platform has been carried out, and after half a year’s construction and operation, the business of village-level financial management platform in Z city has been running stably, and all the work has achieved better results, and the project acceptance has been obtained. At the same time as the first pilot in Z city, the pilot work has been completed simultaneously in other counties and other places in China, and Z city and other places have entered the stage of region-wide (county) promotion. This chapter uses the actual application of City Z as a study case to analyze the application’s effect and credibility after implementing the construction of a cloud financial management platform.

4.1

Calculation of credible indicators

4.1.1

Calculation of indicators of credible attributes

1)

Network density

The network density of the Village Financial Management Platform of City Z was calculated by Pajek Complex Network Software to be 0.01433215, which implies that only 1.433215% of all possible arcs are present in the network. In particular, the degree of aggregation between the general ledger module and other modules in the village-level financial management platform of City Z is high, while certain relatively independent asset modules are relatively loosely connected to other modules.

2)

Proximity Center Degree and Proximity Center Potential

Calculated by Pajek software, the results of the vertex proximity centrality of each module can be obtained as shown in Table 5. In this paper, we only list the top 20 vertices in terms of proximity centrality, and we can see that the range of values of proximity centrality of the top 20 vertices is between 0.2569 and 0.3624. The proximity centrality of vertex 25 is the largest, with the value of 0.3624. Therefore, the general ledger module is located in the middle of the network, but it is not the highest value that may appear in the same size network. Meanwhile, the proximity centrality of all vertices in the network does not differ much, for example, the values of 28 (Schedule item) and 48 (Schedule item adjustment) are both 0.2601. It can be seen that the average distance between vertex pairs in the network is 0.2056, which has a low variance, low centrality, and low integration. Therefore, the trustworthiness in terms of proximity centrality performance is poor.

Table 5.

Approach center degree of vertexes

Serial number	Centrality of proximity	Vertex ID	Serial number	Centrality of proximity	Vertex ID
1	0.3624084	25	11	02649053	16
2	0.3085332	87	12	0.2601793	28
3	0.2926833	66	13	0.2601599	48
4	0.2902201	51	14	0.2590461	8
5	0.2896347	87	15	0.2587355	24
6	0.2820019	101	16	0.3584587	22
7	0.2780760	45	17	0.2583265	5
8	0.2748823	83	18	0.2578806	111
9	0.2692896	75	19	0.2576658	19
10	0.2670845	51	20	0.2569053	20

3)

Intermediary centrality degree and central potential

The greater the variation of centrality degree among the vertices, the more centralized the network is, and it can also be said that the greater the variation of vertex centrality degree, the more centralized the network is, the better the integration is, and the higher the trustworthiness is. The calculated mediator centrality degrees are arranged in descending order and the nodes that rank in the top 20 are selected as shown in Table 6. As can be seen from the table, the maximum value of the mediator degree of the village-level financial management platform of City Z is 0.6366, with a large degree of variation, so the credibility performance in the mediator center degree is better. Moreover, the mediation centrality potential of the village financial management platform of City Z is 0.61889805, which is much higher than the proximity centrality degree.

Table 6.

Mediation center degree of vertexes

Serial number	Intermediate centrality	Vertex ID	Serial number	Intermediate centrality	Vertex ID
1	0.6366067	25	11	0.1205572	151
2	0.3514444	108	12	0.0856413	92
3	0.2861326	15	13	0.0785112	17
4	0.2552261	78	14	0.0716894	16
5	0.2114856	79	15	0.0653163	29
6	0.1739558	45	16	0.0610844	12
7	0.1591766	83	17	0.0580604	47
8	0.1477855	54	18	0.0568068	56
9	0.1432443	21	19	0.0479981	31
10	0.1270829	37	20	0.0407081	52

The result of the vertex intermediary centrality visualization of the village financial management platform in City Z is shown in Figure 4, where the vertex size represents the size of intermediary centrality. There are some vertices that are invisible because these vertices have intermediary centrality of 0, i.e., they do not act as intermediaries between other vertices. Obviously, the voucher processing module is located in the center of the network, which confirms the conformity of the village financial management platform in Z city from another perspective.

4.1.2

Average shortest path calculation

The Pajek software calculation of the average shortest path of the village financial management platform in City Z shows that the average shortest path is 4.87522, which means that any two modules should be connected to each other through at least 4 modules on average, indicating that the connection between modules is generally more stable and credible. It is also possible to calculate the distance between pairs of points (any two vertices, which may or may not be connected). The distances between two random vertices are shown in Table 7, with each point even corresponding to a distance value. For example, 515 point-evenings have a distance of 1. 2030 point-evenings have a distance of 2, and so on. From the table, it can be seen that the number of point evens with distances of 4 and 5 is the most, thus further indicating that any two modules in the cloud financial management platform are interconnected with each other at a distance roughly between 4 and 5. Therefore, the Village Financial Management Platform of City Z is relatively tightly structured and highly stable, with a low probability of error and a certain degree of credibility.

Table 7.

The distance between two vertexes

Distance	Dot even	Distance
1	515	7	4306
2	2030	8	1817
3	4560	9	650
4	7723	10	178
5	7205	11	35
6	6437	-	-

4.2

Trustworthiness analysis of village financial management platforms

Since the number of nodes in the village-level financial management platform of Z city is small and the network complexity is not high, the failure strategy of nodes is defined as the failure of nodes according to the high and low median in turn, and each time there is a node failure, the impact on it is recorded and analyzed, and the corresponding credibility coefficients are derived. It is used to observe the impact of key node failure on the trustworthiness of the financial management platform in the cloud financial environment, reflecting the level of trustworthiness of the Z village-level financial management platform.

In the case of no node failure, the “General Ledger” node has the highest mediator, which plays an obvious role in the network. After removing this node and the directed edges connected to it, the maximum weakly connected subgraph of the platform is derived to simulate the system condition after the failure of the “General Ledger” node, as shown in Fig. 5. Figure 5. Accordingly, when the “General Ledger” node fails, the 69, 77, and 59 vertices in the fund management sub-module have the highest node permittivity, which are 0.6034, 0.4432, and 0.3059, respectively, and the edges connected to them are removed from the network to observe the impact on the network. Remove the vertex “Bank Account (69)” with the highest permittivity and its connected edges and observe the effect on the network.

The maximum weakly connected subgraph of the network of trustworthiness impact relationships for the cloud financial management platform after removing the three vertices with the highest meshes 69, 77 as well as 59 is shown in Fig. 6. The impact on the meshes of each node after each node removal is recorded and the corresponding credibility coefficients are obtained. In this study, we choose the average point degree value, network density, average shortest path, close center potential and mediator center potential, which are five specific trustworthiness indexes used for the trustworthiness evaluation metrics of financial management platforms in cloud financial environment in the complex network model. Set the trustworthiness value of financial management platform in cloud financial environment as EVST for the trustworthiness metric: $E V S T = \sum_{i = 1}^{n} e_{i} * W_{i}^{(*)} = 8.65$

The result is EVST= 8.65, which is at the level of “Highly Reliable (H)”/“Good (G)”, i.e., the reliability of the Village Financial Management Platform of City Z is 8.65.

In summary, the results show that by applying the cloud financial management platform, the village-level organizations in City Z have effectively used each village-level organization and manager as a financial management terminal to achieve unified processing of budgeting, auditing, supervision and payment, including bookkeeping, payment, supervision, reporting and reconciliation functions. Through the unified business process, the transmission speed and accuracy of financial information has been substantially improved, which enables the back-office team to focus on financial analysis and reporting, thus providing more real-time and reliable data support for financial decision-making and budgeting in village-level organizations.

5

Conclusion

In the era of “Internet Plus,” the improvement of network infrastructure, the development of cloud computing technology, the increasing improvement of government cloud, and the advancement of financial management informatization have laid a good foundation for village-level financial management cloud platforms, and the conditions for building village-level financial management cloud platforms are gradually maturing. In view of the needs and current situation of village-level financial management in the context of the rural revitalization strategy, it is necessary to face up to the problems and gaps in village-level financial management, improve the ideological understanding of village-level financial management, and make full use of the advantages of the technological innovation of the Internet and the mobile Internet and the advantages of the professional services of financial agents. From the perspective of reducing the cost and construction difficulty of village-level financial management informatization and improving the management process and supervision system, the village-level financial management cloud platform is planned and designed to realize the improvement of village-level financial management. In actual implementation, it should be based on overall planning, business first, and system support to achieve the goals of accounting systemization, business standardization, process clarity, and real-time supervision. To achieve the long-term development of the village-level financial management model based on cloud finance, it is important to focus on data security issues and supplier management.

Langue:: Anglais

Périodicité:: 1 fois par an
Sujets de la revue:: Sciences de la vie, Sciences de la vie, autres, Mathématiques, Mathématiques appliquées, Mathématiques générales, Physique, Physique, autres

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Research on Constructing a Village Financial Management Model Based on Cloud Finance in the Context of Rural Revitalization Strategy

Junmei Li

Publié en ligne: 17 mars 2025

Reçu: 07 nov. 2024

Accepté: 19 févr. 2025

DOI: https://doi.org/10.2478/amns-2025-0267

Mots clésFinancial management platform, Cloud computing, Cloud finance, Complex network, Credibility evaluation

© 2025 Junmei Li, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Financial management platform, Cloud computing, Cloud finance, Complex network, Credibility evaluation