# “Internet + Artificial Intelligence” Human Resource Information Management System Construction Innovation and Research

Authors: Zhen Zeng; Longqi Qi
Journal: Mathematical Problems in Engineering
 (2021)

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## Abstract

Human resources are the cornerstone of operational operation. Good management of human resource information can enable businesses to operate effectively. However, for the time being, most enterprises still use traditional methods of allocating human resources, which are difficult to meet the development needs of enterprises. In order to find the optimal allocation of human resources in an enterprise, this article is based on “Internet + artificial intelligence,” using methods such as case analysis and literature analysis to collect data from databases such as CNKI, Wanfang Database, and SSCI, and uses fog computing to build a model for the optimal allocation of human resources which is proposed, and a large number of relevant literature studies are read and analyzed through the literature survey method. According to the research needs, through the research and summary of the content of the literature, the research structure found that there are many problems in the current human resource information management system. After the optimization of models and algorithms, the allocation of human resources has been greatly improved. The matching rate of personnel and job positions has increased by more than 50%. The operation efficiency index of the enterprise is above 0.8, an increase of about 30%. This shows that “Internet + artificial intelligence” can effectively optimize the enterprise human resource information management system, promote the greater use of its human resource value, bring higher economic returns to the enterprise, and provide assistance for the long-term stable and healthy development of the enterprise.


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## Body

## 1. Introduction

In today’s society, human resources, as science, play a vital role in socioeconomic development and scientific and technological progress. They are a very important social resource and can promote the development of other resources at the same time. The allocation of human resources is used as a link between people and material data. The organic chain together is a key link to whether human resources can play their full role [1]. At present, many jobs still retain the traditional human resource organization, facing a series of human resource problems such as the aging of the personnel structure and the relative lack of professional talents. With the development of time, this new management method will gradually be eliminated. Fog computing provides services to users locally. On the one hand, it can reduce business processing delays and improve work efficiency. On the other hand, it can reduce network and bandwidth requirements and save the system in general. Therefore, we have innovated and optimized the design of the human resources information management system based on the Internet + artificial intelligence, reasonably allocates human resources, quickly activates existing human resources, optimizes the actual allocation of human resources to maximize human resources, and strengthens the management of human resources information in order to better adapt to future market demands [2].In the modern enterprise management system, human capital pays more attention to the requirements of the enterprise management system, further formulates clear regulations, and refines the responsibilities of enterprise managers [3]. The optimized configuration of human resources based on the Internet + artificial intelligence can effectively revitalize human resources, and employees’ sense of responsibility and work initiative are significantly improved. The management level is reduced, and the enterprise entity is realized. The specific work is sinking. The matters that need to be reported at different levels are directly handled by each business department. Each business department directly participates in business management activities. The collaboration between departments is closer. The interaction is more efficient [4].Belizon et al. studied the differences in the use of international integration mechanisms in various human resource management (HRM) practices by multinational companies. Their findings indicate that personnel, information, and formal-based mechanisms are positively related to the use of centralized-based integration processes [5]. Liu and Yue use fog computing to create models and allocate resources. In his research, they found that fog computing is stable and meets the demand [6]. Leijun points out that, in today's rapid economic development, the traditional human resource allocation model is inconsistent with the current development trend, which makes it difficult for many enterprises that are still using traditional human resource allocation methods [7].Wang Wenxin believes that, in today’s rapid development of information, knowledge is the first contribution to the promotion of human society. How to arrange people with different roles in suitable positions, mobilize their enthusiasm for work, and develop their potential is the optimization of human resource management. The most important issue is the use of human resource-related theories, introducing the meaning of human resource allocation and the method of optimizing human resources and discussing the important role of human resource optimal allocation for social development [5]; Tang Linyu believes that fog computing can provide people with more services. Starting from the allocation of computing resources, they use fog computing to make models and allocate resources. In the research, it is found that fog computing is stable and demand matching. The results prove that the use of fog computing can make the allocation time relatively stable. The delay and accuracy of the calculation in the fog are better than the original calculation method [6]. Zhang Bo believes that the development and growth of enterprises cannot be separated from the optimal allocation of human resources. However, in today’s rapid economic development, the traditional human resource allocation model does not match the current development, which makes it difficult for many enterprises that still use traditional human resource allocation. In this regard, he emphatically introduced the methods of optimizing the allocation of human resources in the enterprise and cited relevant examples [7]. These studies have certain reference values for this article, but due to the narrow data cited in the research, the data industry is basically limited to individual industries and has no universal effect.This article applies the latest human resource allocation theory to fully mention the status quo of the human resource allocation of the enterprise, to seek to explore a specific plan for the establishment of a human resource information management system, and to provide a reference for relevant undertakings. Create an ecosystem structure model based on the “Internet + Artificial Intelligence” to carry out a thorough analysis of the current status of the new system management of human resources and make relevant countermeasures and proposals on the basis of the analytical conclusions to help similar companies build more competitive new human resource management system to better help the company to develop and develop.


## 2. Innovative Methods for the Construction of Human Resource Information Management System

### 2.1. Fog Calculation

Fog computing is a system-level architecture that provides computing, storage, control, and networking functions near the data generation source along the cloud to the continuum of things. The fog computing architecture is mainly divided into three layers: cloud computing layer, fog computing layer, and mobile terminal layer. The fog computing architecture brings the service closer to the end user, reduces latency, saves energy consumption, and enhances the user experience [8].The bottom layer of the architecture is the mobile terminal layer, which contains a large number of smart devices and sensors. Data collection, service requests, and so on all come from the bottom-end terminal equipment. Smart terminal equipment can preprocess and compress data to filter out some useless data [9]. At the same time, terminal equipment can also communicate through equipment such as base stations or routers to realize data sharing. The fog computing layer is located between the cloud computing layer and mobile terminal devices and is a bridge connecting cloud servers and terminal devices. Simple events and emergencies are detected at this layer, so that users can respond quickly.The delay of the fog computing layer includes the communication delay between fog devices and the calculation delay of fog devices. For communication delay, in the undirected graph composed of fog devices, the communication delay between fog nodes is used as the weight. As the amount of calculation increases, the calculation delay of the fog device increases accordingly; the more calculations increase and the more fog devices, the more calculation delay time [10]. Therefore, use the following function to describe the calculation delay of the fog device.(1)T=1wxaibi2.Among them,wx is the computing power of the fog device x, bi is the amount of tasks processed by the fog device, and ai is a preset real number. Therefore, the delay of the fog computing node is expressed as follows:(2)Tn=min∑i=1x1wxaibi2.The fog computing layer is composed of fog nodes deployed around IoT devices. The fog nodes are connected to devices such as base stations or routers, thereby reducing the transmission delay from device to device. In addition, a large number of fog nodes are deployed at the edge of the network, and even the same service is deployed on multiple fog nodes. This not only reduces the risk of service interruption caused by a failure of one fog node but also makes one fog node more than one. Equipment includes base stations or routers process data [11]. The fog node in the network can also be connected to the cloud data center. When the IoT device generates massive data that needs to be processed and the computing power of a single fog node cannot meet its needs, the fog node will forward the data to the cloud for processing. There will undoubtedly be a greater communication delay and reduce the efficiency of the service. In the calculation, because the self-correction function is added in each step of the calculation process, the maximum change of pressure and saturation allowed by each grid node in the two adjacent steps is limited [12]. Therefore, in the process of calculating the node penetration rate at time (n + 1), the following basic formula is used:(3)K=K0expap−p0.Here, we assume that the initial pressure of the reservoir is PP, the pressure value at timen is pn, and the pressure value at time n + 1 is pn + 1; then when pn + 1 < PP and PP = pn + 1,(4)Kn+1=K0e−a1p0−pn+1.Whenpn + 1 ≥ PP,(5)Kn+1=Kne−a2pn−pn+1.This paper uses immune optimization algorithm to study the energy consumption of data processing in fog computing. In the traditional three-layer network architecture, considering the long distance and high energy consumption when the cloud server caches data resources to the fog node, a four-layer network architecture model is proposed, that is, between the cloud computing layer and the fog computing layer. Add a layer of proxy fog server to make the cloud server cache data resources in advance and provide local services [13]. The specific process of addressing the proxy fog server through the optimal immune algorithm is described in detail, thereby reducing the energy consumption of the fog node to obtain data resources from the proxy fog server and also reducing the amount of precached resources by the cloud server to the fog node. Through theoretical analysis and simulation experiments, the effectiveness of the four-layer network architecture model in data processing energy consumption is proved.


### 2.2. New Human Resource Management System

Human resource management refers to a series of management activities based on the organization and mobilization of corporate human resources to promote the attraction of outstanding talents, enhance the enthusiasm of corporate talents, and promote the realization of corporate organizational goals [14]. Whether it is a matter of talent selection, employee incentives, or human resource management planning, training, performance, salary management, and so on, all activities’ management shall be implemented to achieve the organizational objectives of the undertaking. The sole purpose is to promote the implementation of the organizational objectives of the undertaking for the improvement of the undertaking. The enthusiasm of talent and the attraction of exceptional talent can be effective human resource management.The theory of human resource planning mainly includes two aspects. On the one hand, the theory believes that the viability of an enterprise comes from the structure and quantity of human resource management. On the other hand, the theory believes that the implementation of human resource planning by an enterprise can satisfy the development of the enterprise itself. To meet the development and interests of employees [15], human resource planning is a very important content in the human resource management system of an enterprise. As a key management activity, human resource planning is related to the rational, scientific, and comprehensive human resource management. Supported by human resource planning theory, the enterprise implementation that is reasonable human resource management strategy can not only improve the production and operation management level of the enterprise but also meet the strategic development needs of the enterprise [16].Management theory believes that, according to the close relationship between the scope of management and the level of management, there will be two forms of organizational structure: flat structure and straight structure. The so-called flat structure is a structure with few management levels and large management width. The case of the formula structure is the opposite [17]. Its structure is derived from the nonlinear partial differential equation of Taylor series expansion motion:(6)a2Rat2=bo21+ww′auad+⋯a2Rad2,where R is the displacement relative to time t and d is the distance of propagation; in this study, d is the length of the sample, the second- and third-order elastic constants and b02 is the velocity. Equations related to elastic constants of nonlinear parameters are as follows:(7)η2=−w″2w′.Variants of nonlinear motion equations are as follows:(8)a2Rat2=bo21−2η2auad+⋯a2Rad2.The solution of the equation is as follows:(9)R=R1cosqx−wd−14η2q2R2xsin2qx−wd+⋯.The relationship betweenR2 and R3 can be obtained:(10)R2=η24d2R12x.(11)R3=η228d4R13x2.When encountering obstacles,A1, A2, and A3, respectively, indicate operating efficiency(12)A2A12=η24d2x,(13)A3A13=η36d3x.According to the specific situation of the unit, to determine their ideal management width, the endogenous driving force of the flat management model of the enterprise lies in the continuous improvement of the manager’s personal ability [18]. Through flat design, scientific job distribution, and flat management of corporate managers to enrich front-line staff, revitalize existing human resources, solve the contradiction between redundancy and shortage, improve corporate executives’ sense of responsibility and work initiative, reduce risks, and improve the quality and efficiency of corporate collection and management, the promotion of modernization of corporate management systems is inevitable trends in corporate development [19].


### 2.3. Optimization and Innovation of the Human Resource System under Internet + Artificial Intelligence

In the Internet economic environment, the transformation of corporate business models has caused companies to face a new competitive situation. The traditional capital competition is constantly developing in the direction of intellectual resource competition. In this process, the importance of human resources will inevitably become more prominent. The decision-making choices of enterprise human resource management must also be changed [20]. In the context of the Internet economy, companies can only obtain strong development forces if they obtain strong human capital power. At the same time, they should effectively stimulate the capabilities and value of human resources through effective management and maximize their functions to meet the development needs of the company. This requires companies to pay attention to the transformation of the Internet model of human resource management [21]. Managers at all levels are in charge of affairs closely related to the various production, operation, and management activities of the enterprise. The development of the enterprise depends on the efficient completion of these basic tasks. Under the Internet thinking, due to the change of the status of human resources in enterprise management, as a result, the implementation methods of management functions at all levels have changed. The system management under the traditional model has not been able to adapt to the Internet thinking. Therefore, the functions of the managers at all levels will also undergo corresponding changes. Human resource management requires adaptation [22]. Calculate the similarity between the resources in the resource collection and the resources requested by the user:(14)cosmr,uq=α∗cosr,uq+1−α∗1m∑n=1mδij,where a represents the weight and the range is between [0, 1]. The simulation parameters are calculated as follows:(15)F=∑qrp,rpn−qrpmquq,uqn−quq∑n=1nqr−quq2∑quq,uqm−quq2.According to the humanistic characteristics of human resource management, it is very important to establish a unique cultural management model in the implementation of human resource management in an enterprise. Culture-led enterprises have more team cohesion and market competitiveness and can be more efficient in order to achieve the strategic development goals of the company; the current theoretical research on corporate management proposes a corporate culture management model. This is the most promising corporate management theory so far and the most practical value corporate management model [23].With the development of the Internet economy, the development of enterprises has become more dependent on talents, and Internet thinking is to study employees and enterprises as a whole. As the basic components of enterprises, employees must play a more important role in the Internet economy effect. Under the Internet thinking, the construction of human resource management mode in enterprises must fully consider the principle of people centeredness. Whether it is in the relationship between all members of the enterprise or the relationship between the enterprise and employees, the management, coordination, and combination of enterprise development can achieve significant results. This is one of the basic principles of the construction of a human-oriented Internet-thinking human resource management model [24].Incentive theory is the content of enterprise human management theory. In order to effectively stimulate employees’ working ability and enthusiasm, good results can be obtained through certain incentives. Incentive theory believes that the implementation of more powerful incentives for employees can promote the efficient realization of corporate goals. However, if the company’s incentive level is insufficient, employees’ enthusiasm for work cannot be exerted and the efficiency of achieving corporate goals will be low.Based on the relevant research on corporate human resource management under the domestic background, it can be seen that human resource management, as the core competitiveness of an enterprise, is related to the long-term strategic development of the enterprise under the background of the market economy. In order to enable enterprises to effectively use various resources in the context of the Internet and play an important role in human resource management, enterprises must innovate in human resource management from two aspects of technology and management, so that they can better conform to the development trend of the times, make enterprise management truly organically integrate with the Internet background, and meet the various needs of enterprise development in the new era [25].According to the viewpoint of the resource school, if the Internet is only used as technology and cannot spontaneously produce an effect, it must be transformed into a competitive advantage through a series of organizational management methods combined with changes in thinking. On the organizational level, the implementation of electronic human resource management as a process of management innovation may conflict with existing stakeholders. Since the human resource department is the main promoter of electronic human resource management innovation, its influence on the organization is crucial, that is, whether it can obtain the support of executives and parallel departments through its own influence.


## 2.1. Fog Calculation

Fog computing is a system-level architecture that provides computing, storage, control, and networking functions near the data generation source along the cloud to the continuum of things. The fog computing architecture is mainly divided into three layers: cloud computing layer, fog computing layer, and mobile terminal layer. The fog computing architecture brings the service closer to the end user, reduces latency, saves energy consumption, and enhances the user experience [8].The bottom layer of the architecture is the mobile terminal layer, which contains a large number of smart devices and sensors. Data collection, service requests, and so on all come from the bottom-end terminal equipment. Smart terminal equipment can preprocess and compress data to filter out some useless data [9]. At the same time, terminal equipment can also communicate through equipment such as base stations or routers to realize data sharing. The fog computing layer is located between the cloud computing layer and mobile terminal devices and is a bridge connecting cloud servers and terminal devices. Simple events and emergencies are detected at this layer, so that users can respond quickly.The delay of the fog computing layer includes the communication delay between fog devices and the calculation delay of fog devices. For communication delay, in the undirected graph composed of fog devices, the communication delay between fog nodes is used as the weight. As the amount of calculation increases, the calculation delay of the fog device increases accordingly; the more calculations increase and the more fog devices, the more calculation delay time [10]. Therefore, use the following function to describe the calculation delay of the fog device.(1)T=1wxaibi2.Among them,wx is the computing power of the fog device x, bi is the amount of tasks processed by the fog device, and ai is a preset real number. Therefore, the delay of the fog computing node is expressed as follows:(2)Tn=min∑i=1x1wxaibi2.The fog computing layer is composed of fog nodes deployed around IoT devices. The fog nodes are connected to devices such as base stations or routers, thereby reducing the transmission delay from device to device. In addition, a large number of fog nodes are deployed at the edge of the network, and even the same service is deployed on multiple fog nodes. This not only reduces the risk of service interruption caused by a failure of one fog node but also makes one fog node more than one. Equipment includes base stations or routers process data [11]. The fog node in the network can also be connected to the cloud data center. When the IoT device generates massive data that needs to be processed and the computing power of a single fog node cannot meet its needs, the fog node will forward the data to the cloud for processing. There will undoubtedly be a greater communication delay and reduce the efficiency of the service. In the calculation, because the self-correction function is added in each step of the calculation process, the maximum change of pressure and saturation allowed by each grid node in the two adjacent steps is limited [12]. Therefore, in the process of calculating the node penetration rate at time (n + 1), the following basic formula is used:(3)K=K0expap−p0.Here, we assume that the initial pressure of the reservoir is PP, the pressure value at timen is pn, and the pressure value at time n + 1 is pn + 1; then when pn + 1 < PP and PP = pn + 1,(4)Kn+1=K0e−a1p0−pn+1.Whenpn + 1 ≥ PP,(5)Kn+1=Kne−a2pn−pn+1.This paper uses immune optimization algorithm to study the energy consumption of data processing in fog computing. In the traditional three-layer network architecture, considering the long distance and high energy consumption when the cloud server caches data resources to the fog node, a four-layer network architecture model is proposed, that is, between the cloud computing layer and the fog computing layer. Add a layer of proxy fog server to make the cloud server cache data resources in advance and provide local services [13]. The specific process of addressing the proxy fog server through the optimal immune algorithm is described in detail, thereby reducing the energy consumption of the fog node to obtain data resources from the proxy fog server and also reducing the amount of precached resources by the cloud server to the fog node. Through theoretical analysis and simulation experiments, the effectiveness of the four-layer network architecture model in data processing energy consumption is proved.


## 2.2. New Human Resource Management System

Human resource management refers to a series of management activities based on the organization and mobilization of corporate human resources to promote the attraction of outstanding talents, enhance the enthusiasm of corporate talents, and promote the realization of corporate organizational goals [14]. Whether it is a matter of talent selection, employee incentives, or human resource management planning, training, performance, salary management, and so on, all activities’ management shall be implemented to achieve the organizational objectives of the undertaking. The sole purpose is to promote the implementation of the organizational objectives of the undertaking for the improvement of the undertaking. The enthusiasm of talent and the attraction of exceptional talent can be effective human resource management.The theory of human resource planning mainly includes two aspects. On the one hand, the theory believes that the viability of an enterprise comes from the structure and quantity of human resource management. On the other hand, the theory believes that the implementation of human resource planning by an enterprise can satisfy the development of the enterprise itself. To meet the development and interests of employees [15], human resource planning is a very important content in the human resource management system of an enterprise. As a key management activity, human resource planning is related to the rational, scientific, and comprehensive human resource management. Supported by human resource planning theory, the enterprise implementation that is reasonable human resource management strategy can not only improve the production and operation management level of the enterprise but also meet the strategic development needs of the enterprise [16].Management theory believes that, according to the close relationship between the scope of management and the level of management, there will be two forms of organizational structure: flat structure and straight structure. The so-called flat structure is a structure with few management levels and large management width. The case of the formula structure is the opposite [17]. Its structure is derived from the nonlinear partial differential equation of Taylor series expansion motion:(6)a2Rat2=bo21+ww′auad+⋯a2Rad2,where R is the displacement relative to time t and d is the distance of propagation; in this study, d is the length of the sample, the second- and third-order elastic constants and b02 is the velocity. Equations related to elastic constants of nonlinear parameters are as follows:(7)η2=−w″2w′.Variants of nonlinear motion equations are as follows:(8)a2Rat2=bo21−2η2auad+⋯a2Rad2.The solution of the equation is as follows:(9)R=R1cosqx−wd−14η2q2R2xsin2qx−wd+⋯.The relationship betweenR2 and R3 can be obtained:(10)R2=η24d2R12x.(11)R3=η228d4R13x2.When encountering obstacles,A1, A2, and A3, respectively, indicate operating efficiency(12)A2A12=η24d2x,(13)A3A13=η36d3x.According to the specific situation of the unit, to determine their ideal management width, the endogenous driving force of the flat management model of the enterprise lies in the continuous improvement of the manager’s personal ability [18]. Through flat design, scientific job distribution, and flat management of corporate managers to enrich front-line staff, revitalize existing human resources, solve the contradiction between redundancy and shortage, improve corporate executives’ sense of responsibility and work initiative, reduce risks, and improve the quality and efficiency of corporate collection and management, the promotion of modernization of corporate management systems is inevitable trends in corporate development [19].


## 2.3. Optimization and Innovation of the Human Resource System under Internet + Artificial Intelligence

In the Internet economic environment, the transformation of corporate business models has caused companies to face a new competitive situation. The traditional capital competition is constantly developing in the direction of intellectual resource competition. In this process, the importance of human resources will inevitably become more prominent. The decision-making choices of enterprise human resource management must also be changed [20]. In the context of the Internet economy, companies can only obtain strong development forces if they obtain strong human capital power. At the same time, they should effectively stimulate the capabilities and value of human resources through effective management and maximize their functions to meet the development needs of the company. This requires companies to pay attention to the transformation of the Internet model of human resource management [21]. Managers at all levels are in charge of affairs closely related to the various production, operation, and management activities of the enterprise. The development of the enterprise depends on the efficient completion of these basic tasks. Under the Internet thinking, due to the change of the status of human resources in enterprise management, as a result, the implementation methods of management functions at all levels have changed. The system management under the traditional model has not been able to adapt to the Internet thinking. Therefore, the functions of the managers at all levels will also undergo corresponding changes. Human resource management requires adaptation [22]. Calculate the similarity between the resources in the resource collection and the resources requested by the user:(14)cosmr,uq=α∗cosr,uq+1−α∗1m∑n=1mδij,where a represents the weight and the range is between [0, 1]. The simulation parameters are calculated as follows:(15)F=∑qrp,rpn−qrpmquq,uqn−quq∑n=1nqr−quq2∑quq,uqm−quq2.According to the humanistic characteristics of human resource management, it is very important to establish a unique cultural management model in the implementation of human resource management in an enterprise. Culture-led enterprises have more team cohesion and market competitiveness and can be more efficient in order to achieve the strategic development goals of the company; the current theoretical research on corporate management proposes a corporate culture management model. This is the most promising corporate management theory so far and the most practical value corporate management model [23].With the development of the Internet economy, the development of enterprises has become more dependent on talents, and Internet thinking is to study employees and enterprises as a whole. As the basic components of enterprises, employees must play a more important role in the Internet economy effect. Under the Internet thinking, the construction of human resource management mode in enterprises must fully consider the principle of people centeredness. Whether it is in the relationship between all members of the enterprise or the relationship between the enterprise and employees, the management, coordination, and combination of enterprise development can achieve significant results. This is one of the basic principles of the construction of a human-oriented Internet-thinking human resource management model [24].Incentive theory is the content of enterprise human management theory. In order to effectively stimulate employees’ working ability and enthusiasm, good results can be obtained through certain incentives. Incentive theory believes that the implementation of more powerful incentives for employees can promote the efficient realization of corporate goals. However, if the company’s incentive level is insufficient, employees’ enthusiasm for work cannot be exerted and the efficiency of achieving corporate goals will be low.Based on the relevant research on corporate human resource management under the domestic background, it can be seen that human resource management, as the core competitiveness of an enterprise, is related to the long-term strategic development of the enterprise under the background of the market economy. In order to enable enterprises to effectively use various resources in the context of the Internet and play an important role in human resource management, enterprises must innovate in human resource management from two aspects of technology and management, so that they can better conform to the development trend of the times, make enterprise management truly organically integrate with the Internet background, and meet the various needs of enterprise development in the new era [25].According to the viewpoint of the resource school, if the Internet is only used as technology and cannot spontaneously produce an effect, it must be transformed into a competitive advantage through a series of organizational management methods combined with changes in thinking. On the organizational level, the implementation of electronic human resource management as a process of management innovation may conflict with existing stakeholders. Since the human resource department is the main promoter of electronic human resource management innovation, its influence on the organization is crucial, that is, whether it can obtain the support of executives and parallel departments through its own influence.


## 3. Innovative Experiment of Human Resource Information Management System Construction

### 3.1. Experimental Purpose

This article makes full use of the research results in the field of human resource allocation under the Internet + still intelligence and takes the realization of the company’s sustainable development as the starting point. Through in-depth research on the company’s human resource allocation status and existing problems, it builds a system for the optimization of the company’s human resource allocation, and it puts forward feasibility and scientific opinions on advancing the optimization of human resource allocation, so as to help enterprises build a more competitive human resource system and promote the improvement of their market competitive position.


### 3.2. Establish a Model Evaluation Index System

Some conclusions can be drawn from the actual observation of the objects. Generally speaking, the system of an evaluation index includes three levels of evaluation indicators: it is the relationship between gradual decomposition and improvement. Among them, the first-level evaluation indicators and the second-level evaluation indicators are relatively abstract and cannot be used as a direct basis for the evaluation. The third-level evaluation indicators must be specific, measurable, and behavioral and can be used as a direct basis for assessing the teaching.Comprehensive quantitative and qualitative analysis methods: quantitative analysis is to analyze the data of the problem, using the intuition and clear essence of mathematics to reflect the existence of the problem; qualitative analysis is to collect, read, and organize relevant domestic and foreign research literature and systematically summarize the related theoretical results. The evaluation criteria of green supply chain performance are complex and diverse, including not only financial standards but also other nonfinancial standards. Some standards cannot be directly analyzed by quantitative methods but can only be evaluated by qualitative analysis methods. The green supply system performance evaluation standard system of the company is constructed using a model that combines quantitative and qualitative analysis methods. At the same time, it provides formulas for standard calculations and evaluation standards.


### 3.3. Determine the Reevaluation Weight

The index weight is a numerical index indicating the importance and function of the index. In the indicator system of the evaluation plan, the weight of each indicator is different. Even if the indicator level is the same, the weight is different. Index weight is also called weight and is usually represented bya. It is a number greater than zero but less than 1, and the sum of the weights of all the first-level indicators must be equal to 1; that is, satisfy conditions 0 < a < 1 and ∑a − 1.


### 3.4. Statistics

All data analysis in this paper uses SPSS19.0, statistical test uses double-sided test, the significance is defined as 0.05, andp<0.05 is considered significant. The statistical results are displayed as mean ± standard deviation (x ± SD). When the test data complies with the normal distribution, the double T-test is used for comparison within the group, and the independent sample T-test is used for comparison between the groups. If the regular distribution is insufficient, two independent samples and two related samples will be used for inspection.


## 3.1. Experimental Purpose

This article makes full use of the research results in the field of human resource allocation under the Internet + still intelligence and takes the realization of the company’s sustainable development as the starting point. Through in-depth research on the company’s human resource allocation status and existing problems, it builds a system for the optimization of the company’s human resource allocation, and it puts forward feasibility and scientific opinions on advancing the optimization of human resource allocation, so as to help enterprises build a more competitive human resource system and promote the improvement of their market competitive position.


## 3.2. Establish a Model Evaluation Index System

Some conclusions can be drawn from the actual observation of the objects. Generally speaking, the system of an evaluation index includes three levels of evaluation indicators: it is the relationship between gradual decomposition and improvement. Among them, the first-level evaluation indicators and the second-level evaluation indicators are relatively abstract and cannot be used as a direct basis for the evaluation. The third-level evaluation indicators must be specific, measurable, and behavioral and can be used as a direct basis for assessing the teaching.Comprehensive quantitative and qualitative analysis methods: quantitative analysis is to analyze the data of the problem, using the intuition and clear essence of mathematics to reflect the existence of the problem; qualitative analysis is to collect, read, and organize relevant domestic and foreign research literature and systematically summarize the related theoretical results. The evaluation criteria of green supply chain performance are complex and diverse, including not only financial standards but also other nonfinancial standards. Some standards cannot be directly analyzed by quantitative methods but can only be evaluated by qualitative analysis methods. The green supply system performance evaluation standard system of the company is constructed using a model that combines quantitative and qualitative analysis methods. At the same time, it provides formulas for standard calculations and evaluation standards.


## 3.3. Determine the Reevaluation Weight

The index weight is a numerical index indicating the importance and function of the index. In the indicator system of the evaluation plan, the weight of each indicator is different. Even if the indicator level is the same, the weight is different. Index weight is also called weight and is usually represented bya. It is a number greater than zero but less than 1, and the sum of the weights of all the first-level indicators must be equal to 1; that is, satisfy conditions 0 < a < 1 and ∑a − 1.


## 3.4. Statistics

All data analysis in this paper uses SPSS19.0, statistical test uses double-sided test, the significance is defined as 0.05, andp<0.05 is considered significant. The statistical results are displayed as mean ± standard deviation (x ± SD). When the test data complies with the normal distribution, the double T-test is used for comparison within the group, and the independent sample T-test is used for comparison between the groups. If the regular distribution is insufficient, two independent samples and two related samples will be used for inspection.


## 4. Innovative Experiment Analysis of Human Resource Information Management System Construction

### 4.1. Status of the Company

We have selected five companies to investigate the current status of their employees. We have selected the companies to be an information technology company in the city. Such companies are highly sensitive to staffing and their staffing is more reasonable. We survey employees and human resource systems and classify them by age, gender, and so on. The specific data are shown in Table1.Table 1
Distribution of employees.
The first companyThe second companyThe third companyThe fourth companyThe fifth company18–28273338293129–35252736243436–48332229173149–601917131617Male7566724969Female4045384742It can be seen from Figure1 that, in these five companies, the age and gender distribution of employees are not very different, and the main employees are between 18 and 35 years old. This is because people in this age group are generally receiving information quickly. The stage of strong learning ability is the main type of recruitment for information technology enterprises. The company’s male-female ratio is generally around 6.5 : 3.5, and the fourth company’s male-female ratio is 5 : 5. At the management level, the gap between age and gender is larger than that between employees. The specific data are shown in Table 2.Figure 1
Distribution of employees in different companies.Table 2
Distribution of leadership.
The first companyThe second companyThe third companyThe fourth companyThe fifth company18–282246329–35311671436–485171591249–6079181911Male1227193129Female51214711From Figure2, we can see that, at the company’s management level, the age is generally over 35 years, accounting for more than 60%. This is because leaders generally have more requirements, and they have high requirements for people’s skills and need people to constantly accumulate. In terms of gender, the leadership of these companies is mostly men, accounting for more than 65%, and the proportion of women is smaller than that of men.Figure 2
Distribution of employees in different companies.


### 4.2. Company Employees

Educational background is our most intuitive manifestation of personal abilities. Before we truly recognize a person, we can only judge a person’s abilities based on some external factors, such as human resources. Therefore, we have made relevant statistics on the academic qualifications of the employees and leaders of these five plus companies. The specific data are shown in Table3.Table 3
Employee education.
The first companyThe second companyThe third companyThe fourth companyThe fifth companyPrimary school54276Junior high school17139412High school2419132017University3329454755Master’s degree241719119Doctoral degree8615139It can be seen from Figure3 that, in enterprises, the educational background of employees is uneven, and so is the ability of employees. In statistics, we can clearly see that the employees with a college degree or below account for about 30%. The college degree is about 50%, and the college degree is only less than 20%. This is because the company we selected is of an information technology type. Generally, there are academic requirements for recruitment, which also requires us to do well in the human resources of our employees. Optimization: at the management level, the requirements for academic qualifications are more important. The academic qualifications of business leaders are basically university or higher, as shown in Table 4.Figure 3
Distribution of employees’ academic qualifications.Table 4
Distribution of leadership qualifications.
The first companyThe second companyThe third companyThe fourth companyThe fifth companyPrimary school13021Junior high school42212High school45731University121191612Master’s degree913171315Doctoral degree78587From Figure4, we can see that, at the management level of the company, the average education level is much higher than that of the employees. There are basically no graduates below high school. Most of them have a college degree or above, accounting for more than 70%. The master’s degree is about 20%, far higher than the average employee.Figure 4
Distribution of employees’ academic qualifications.


### 4.3. Operational Efficiency of the Enterprise

The purpose of optimizing the allocation of human resources is to improve the operating efficiency of the enterprise, so that employees can reach a reasonable state in the production, transportation, and profitability stages of the enterprise, so that the enterprise can be profitable and promote the development and growth of the enterprise. Therefore, we digitize the parameter utilization models of these five companies in daily production and life to make it more obvious. The details are shown in Table5.Table 5
Evaluation parameters.
Employee satisfactionEmployee motivationRedundant staffPerson-post matchingEmployee benefitsBusiness efficiencyThe first company0.4120.3842.30.4190.4330.412The second company0.4990.4213.70.4430.4970.424The third company0.5060.4723.80.5120.4760.533The fourth company0.5510.5913.60.510.4940.513The fifth company0.4570.4622.60.6220.6190.577It can be seen from Figure5 that, during the operation of the enterprise, the employee satisfaction and employee efficiency of these companies are around the passing line, which shows that the enterprise has not made the best use of the staff in the employment of employees. Giving full play to the enthusiasm of employees does not improve the operating efficiency of the company. After the test, the average score is about 0.5, and the redundancy rate of the company is about 4%. We also made statistics on management, as shown in Figure 6.Figure 5
Distribution of employees’ academic qualifications.Figure 6
Distribution of leadership operating efficiency.We can see from Figure6 that, in the leadership, satisfaction and enthusiasm have increased, with an average value of about 0.6, exceeding 0.5 of employees, and it is about to reach a good line. This is because the company’s emphasis on leadership makes it more powerful than ordinary employees. But at the leadership level, the redundancy rate has also reached about 3.5%. This shows that the company’s human resource allocation to the leadership still needs to be strengthened.


### 4.4. Comparison after the Introduction of Internet + Artificial Intelligence

Through the model we made, we input the enterprise’s human resource configuration parameters to obtain the human resource configuration adjusted by “Internet + artificial intelligence.” By comparing the differences between the two, we can obtain human resources based on “Internet + artificial intelligence” analysis to optimize the configuration effect, as shown in Table6.Table 6
Comparison after optimized allocation of human resources.
Employee satisfactionEmployee motivationRedundant staff (%)Person-post matchingEmployee benefitsBusiness efficiencyOriginal configuration0.4320.3922.70.4930.5140.521Configuration after optimization0.7230.6961.20.7840.8130.797The optimal value0.8370.8260.460.8720.8430.856From Figure7, we can see that, after the optimization of the human resource management information system by the Internet + artificial intelligence, the company’s various parameters have been qualitatively improved, which is very close to the optimal value, and the operational efficiency and employee satisfaction have been improved. Both exceed 50%, and the redundancy rate of enterprises has dropped by more than 40%. This shows that the Internet + artificial intelligence plays an extremely important role in the optimization of enterprise human resource information systems.Figure 7
Changes in enterprise parameters.


## 4.1. Status of the Company

We have selected five companies to investigate the current status of their employees. We have selected the companies to be an information technology company in the city. Such companies are highly sensitive to staffing and their staffing is more reasonable. We survey employees and human resource systems and classify them by age, gender, and so on. The specific data are shown in Table1.Table 1
Distribution of employees.
The first companyThe second companyThe third companyThe fourth companyThe fifth company18–28273338293129–35252736243436–48332229173149–601917131617Male7566724969Female4045384742It can be seen from Figure1 that, in these five companies, the age and gender distribution of employees are not very different, and the main employees are between 18 and 35 years old. This is because people in this age group are generally receiving information quickly. The stage of strong learning ability is the main type of recruitment for information technology enterprises. The company’s male-female ratio is generally around 6.5 : 3.5, and the fourth company’s male-female ratio is 5 : 5. At the management level, the gap between age and gender is larger than that between employees. The specific data are shown in Table 2.Figure 1
Distribution of employees in different companies.Table 2
Distribution of leadership.
The first companyThe second companyThe third companyThe fourth companyThe fifth company18–282246329–35311671436–485171591249–6079181911Male1227193129Female51214711From Figure2, we can see that, at the company’s management level, the age is generally over 35 years, accounting for more than 60%. This is because leaders generally have more requirements, and they have high requirements for people’s skills and need people to constantly accumulate. In terms of gender, the leadership of these companies is mostly men, accounting for more than 65%, and the proportion of women is smaller than that of men.Figure 2
Distribution of employees in different companies.


## 4.2. Company Employees

Educational background is our most intuitive manifestation of personal abilities. Before we truly recognize a person, we can only judge a person’s abilities based on some external factors, such as human resources. Therefore, we have made relevant statistics on the academic qualifications of the employees and leaders of these five plus companies. The specific data are shown in Table3.Table 3
Employee education.
The first companyThe second companyThe third companyThe fourth companyThe fifth companyPrimary school54276Junior high school17139412High school2419132017University3329454755Master’s degree241719119Doctoral degree8615139It can be seen from Figure3 that, in enterprises, the educational background of employees is uneven, and so is the ability of employees. In statistics, we can clearly see that the employees with a college degree or below account for about 30%. The college degree is about 50%, and the college degree is only less than 20%. This is because the company we selected is of an information technology type. Generally, there are academic requirements for recruitment, which also requires us to do well in the human resources of our employees. Optimization: at the management level, the requirements for academic qualifications are more important. The academic qualifications of business leaders are basically university or higher, as shown in Table 4.Figure 3
Distribution of employees’ academic qualifications.Table 4
Distribution of leadership qualifications.
The first companyThe second companyThe third companyThe fourth companyThe fifth companyPrimary school13021Junior high school42212High school45731University121191612Master’s degree913171315Doctoral degree78587From Figure4, we can see that, at the management level of the company, the average education level is much higher than that of the employees. There are basically no graduates below high school. Most of them have a college degree or above, accounting for more than 70%. The master’s degree is about 20%, far higher than the average employee.Figure 4
Distribution of employees’ academic qualifications.


## 4.3. Operational Efficiency of the Enterprise

The purpose of optimizing the allocation of human resources is to improve the operating efficiency of the enterprise, so that employees can reach a reasonable state in the production, transportation, and profitability stages of the enterprise, so that the enterprise can be profitable and promote the development and growth of the enterprise. Therefore, we digitize the parameter utilization models of these five companies in daily production and life to make it more obvious. The details are shown in Table5.Table 5
Evaluation parameters.
Employee satisfactionEmployee motivationRedundant staffPerson-post matchingEmployee benefitsBusiness efficiencyThe first company0.4120.3842.30.4190.4330.412The second company0.4990.4213.70.4430.4970.424The third company0.5060.4723.80.5120.4760.533The fourth company0.5510.5913.60.510.4940.513The fifth company0.4570.4622.60.6220.6190.577It can be seen from Figure5 that, during the operation of the enterprise, the employee satisfaction and employee efficiency of these companies are around the passing line, which shows that the enterprise has not made the best use of the staff in the employment of employees. Giving full play to the enthusiasm of employees does not improve the operating efficiency of the company. After the test, the average score is about 0.5, and the redundancy rate of the company is about 4%. We also made statistics on management, as shown in Figure 6.Figure 5
Distribution of employees’ academic qualifications.Figure 6
Distribution of leadership operating efficiency.We can see from Figure6 that, in the leadership, satisfaction and enthusiasm have increased, with an average value of about 0.6, exceeding 0.5 of employees, and it is about to reach a good line. This is because the company’s emphasis on leadership makes it more powerful than ordinary employees. But at the leadership level, the redundancy rate has also reached about 3.5%. This shows that the company’s human resource allocation to the leadership still needs to be strengthened.


## 4.4. Comparison after the Introduction of Internet + Artificial Intelligence

Through the model we made, we input the enterprise’s human resource configuration parameters to obtain the human resource configuration adjusted by “Internet + artificial intelligence.” By comparing the differences between the two, we can obtain human resources based on “Internet + artificial intelligence” analysis to optimize the configuration effect, as shown in Table6.Table 6
Comparison after optimized allocation of human resources.
Employee satisfactionEmployee motivationRedundant staff (%)Person-post matchingEmployee benefitsBusiness efficiencyOriginal configuration0.4320.3922.70.4930.5140.521Configuration after optimization0.7230.6961.20.7840.8130.797The optimal value0.8370.8260.460.8720.8430.856From Figure7, we can see that, after the optimization of the human resource management information system by the Internet + artificial intelligence, the company’s various parameters have been qualitatively improved, which is very close to the optimal value, and the operational efficiency and employee satisfaction have been improved. Both exceed 50%, and the redundancy rate of enterprises has dropped by more than 40%. This shows that the Internet + artificial intelligence plays an extremely important role in the optimization of enterprise human resource information systems.Figure 7
Changes in enterprise parameters.


## 5. Conclusions

With the continuous improvement of my country’s information technology level, its application in human resource management has also been continuously developed. The human resource management information system can reduce the level and time of information transmission and can also free human resource personnel from trivial administrative affairs, transform into the role of management to provide decision-making support and solutions, and change the service mode of the human resources department.Internet thinking is characterized by no boundaries, organizational forms are becoming more and more virtualized, and employees’ adhesion to the organization is decreasing. Flexible work and remote work have become normal work methods. Enterprises need to break the original relationship of power and responsibility and establish a new type of cooperative relationship with employees. Electronic human resource management is different from the previous human resource management model. It breaks through the limitations of one-way information communication in the past and pays more attention to the multichannel communication of information within the enterprise.In the research system of modern enterprise management mode, with the improvement of related theoretical research, after two management mode leaps, it is facing the outstanding demand of the third management mode leap. From traditional experience management to scientific management and then from scientific management to human-based management, every leap has brought about a huge change in enterprise human resource management, and the human resource management needs of enterprises under the background of the Internet have undergone tremendous changes and the trend of management model development towards cultural management has become increasingly prominent. This is an important reform direction of corporate management in the new century. The necessity of corporate management and cultural management under the Internet background has become more prominent.



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*Source: 5585753-2021-03-20.xml*