Unit VII PP PFL

Research Article Construction of the Enterprise Human Resource Quality Evaluation System Based on the WICS Leadership Model

Na Zong

Huaxin College of Hebei Geo University, Hebei 050700, China

Correspondence should be addressed to Na Zong; [email protected]

Received 31 March 2022; Revised 23 April 2022; Accepted 6 May 2022; Published 7 June 2022

Academic Editor: Vijay Kumar

Copyright © 2022 Na Zong. ­is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

With the advancement of society and economy, the market competition among various businesses has become increasingly �erce. Nowadays, if businesses want to grow in the face of adversity, they must move forward boldly and make use of abundant human resources to fuel their growth. Human resource management is becoming increasingly important. As a result, this paper develops an enterprise human resource quality assessment system based on the WICS leadership model. ­e di�erences between the WICS model and the traditional management model are �rst compared in this paper. ­e requirements of the WICS model in human resource management are then described. Furthermore, this paper proposes a human resource evaluation algorithm that combines data-driven and WICS models to address the current human resource cost evaluation algorithm’s low accuracy and poor e�ect. ­e simulation results show that the proposed algorithm can re�ect changing human resource cost characteristics, improve human resource cost evaluation results, and obtain better results than other human resource cost evaluation models and has a wide range of applications.

1. Introduction

­e term “leadership” is increasingly being used as a new term in corporate human resource quality evaluations (EHRQA). A model with strong leadership can help busi- nesses attract talent, reduce internal con�ict at work, boost productivity, and foster a positive work environment. ­e corporate market is becoming increasingly competitive as the information age progresses [1–6]. ­ere is de�nitely a struggle for talent and resources going on behind the scenes of this matchup. ­e loss of enterprise talents has emerged as a signi�cant factor impeding the development of businesses. ­e factors that have contributed to this occurrence warrant careful investigation. ­e EHRQA technique, which is part of the leadership model, is being implemented progressively in order to alter the old talent management strategy. Comparing the leadership model to the typical EHRQA approach, the leadership model places a greater emphasis on the applicability of employees to the organization and pays more attention to the workability and performance of employees while at work [7–12]. Evaluating employees’

initiative, creativity capacity, and cooperation ability, among other traits, allows them to maximize their own initiative and maximize the value of their own abilities, thus enabling the �rm to enter a new stage of development [13, 14].

Davi-Mc Clelland, a Harvard University professor, was the �rst to introduce the concept of leadership, which was in 1973. According to any traits that can be consistently measured or counted, the notion of leadership refers to a sharp division between outstanding and ordinary people at work, which can be measured or tallied [15–17]. Examples of such divisions include work motivation, workplace attitude or values, personality traits and cognition as well as self- image, expertise in a speci�c subject, professional abilities, and so on. We must identify and separate outstanding performers from those who perform below average, reuse outstanding leaders, and scienti�cally cultivate ordinary ability workers, so that they can assume leadership roles. Currently, the concept of the leadership model is based on leadership, which means that enterprises place a strong emphasis on analyzing the leadership level of employees as well as job requirements, and the standards for human

Hindawi Mathematical Problems in Engineering Volume 2022, Article ID 3259403, 8 pages https://doi.org/10.1155/2022/3259403

resource employees are defined in terms of “quality” and measured in terms of “quantity.”

+e cost of human resources is a significant component of EHRQA [18, 19]. If the cost of human resources cannot be accurately estimated, it will result in a significant waste of human resources, a huge number of lost manpower op- portunities, and an increase in the operating costs of the organization as a result. +e cost of EHRQA is therefore directly tied to the survival of the organization, and the study in EHRQA is of significant importance [20–25].

Despite this, some businesses, particularly in China, fail to factor in human resource costs when making operational decisions. Due to the planned economy’s influence, many enterprises’ ideas and concepts have lagged behind tech- nological advancements, highlighting the EHRQA problem. Over the last decade, the EHRQA problem has garnered increasing attention from domestic research institutions and scholars, resulting in the development of a large number of EHRQA algorithms [26–31]. +e majority of EHRQA is completed manually, which is the most prevalent method. Because of the presence of human elements and the poor objectivity of the evaluation results, the EHRQA results are blind to a certain extent and it is difficult to acquire the ideal EHRQA results. With the existence of human factors and poor objectivity of the assessment findings, using EHRQA algorithms such as the gray model and neural network, some researchers have argued that by defining EHRQA indicators, collecting matching EHRQA data, and developing EHRQA models, they can get better outcomes than manual tech- niques in terms of EHRQA results. +e research has pro- gressed to the point where data on human resource costs has been amassed, and a considerable amount of EHRQA data has emerged, which serves as the foundation for data mining in the field of human resource cost assessment. Chaos theory is a data-driven strategy that may be used to extract the changing characteristics of situations from large amounts of data. It is also a new technology for EHRQA modeling that is being developed [32, 33].

+e continual appearance of quality difficulties in my country’s economic market has intensified people’s attention to quality management, resulting in the notion of overall quality management becoming more prevalent as the times have demanded it [34–37]. Personnel have a considerable impact on the output quality of enterprise products and services, and EHRQA has emerged as an important com- ponent of total quality management practice in the process. Due to the short time span in which comprehensive quality management has been implemented in human resource management, there are still some issues that need to be addressed. Because of this, it is critical to investigate the role of human resource management in the process of com- prehensive quality management [38–40].

+is paper proposes a data-driven EHRQA algorithm in order to improve EHRQA’s accuracy. +e results of this paper demonstrate that the algorithm can accurately capture the changing characteristics of human resource costs, im- prove the results of human resource cost assessment, and outperform existing human resource cost assessment models (DDW).

2. The Specific Application of the Leadership Model in EHRQA

Adopting the leadership model provides a new perspective and a solid foundation for the EHRQA’s work, clarifies the human resources departments’ fundamental responsibilities, and establishes a solid foundation for enterprise develop- ment. Meanwhile, it provides a solid foundation for the company’s personnel recruiting, job assignment, employee training and development, promotion and reward, and other activities, and it heralds the start of a new era in human resource development.

2.1. Employee Recruitment. When hiring personnel under the traditional paradigm, businesses place a greater emphasis on evaluating candidates’ academic qualifications as well as their expertise and abilities. As a result, such inspections have the disadvantage of not delving deeply into the char- acteristics of employees, which is negative, because both internal character qualities and employee characteristics are in the process of long-term development. Marketing social positions are tough to adapt to for people with avariety of personality types, such as quiet and sensitive personalities, who have received extensive long-term training in a timely manner. As a result, if deep-level features of employees are ignored, even long-term employee training and investment training may be ineffective in retaining personnel. +is is a significant waste of training resources for businesses. +e features of WICS talents, on the other hand, are taken into consideration throughout the selection process. Regarding employees, we thoroughly investigate their fundamental requirements and features, pay close attention to their fit for certain positions, ensure that employees can find their dream employment, and limit the waste of training resources caused by high employee turnover.

2.2. Work Assignment. +e traditional job assignment is based on a lack of available positions in the organization and is centered on affairs, whereas the employee job assignment under the guidance of the leadership model is centered on observing the components of the work, analyzing the characteristics of leadership, and evaluating the performance of employees, among other things. Leadership tasks are related to their positions in order to more effectively identify talent and develop appropriate career planning and com- pensation designs for employees.

2.3. Staff Training. Employee training in the traditional sense is primarily concerned with introducing employees to the job topic and improving their workability. In accordance with the new model, employee training is based on the principle of people-centeredness. +is company provides employees with specialized training that is based on their own quality conditions, as well as training that is tailored to their own personal development. It assists employees in enhancing their own deficiencies while simultaneously re- ducing training requirements. +e time-consuming steps of

2 Mathematical Problems in Engineering

the content, increased publicity and training of corporate culture, and instilling a strong feeling of professional belief and work confidence in new employees are all important goals.

2.4. Performance Appraisal. +e fundamental criterion of the leadership model is the ability to discriminate between the signs of exceptional talent and those of ordinary talent. One must establish performance appraisal indicators on the basis of this information, improve performance appraisal standards by making them more scientific and standardized, and implement systematic performance appraisal standards to more accurately reflect employees’ work performance, allowing outstanding employees to be recognized and rewarded in a timely manner, as well as being beneficial to employees and motivating and increasing the motivation of the employees.

2.5. Career Promotion. Achieving career advancement is something that every corporate employee hopes and expects to happen. It is the direct result of the employees’ efforts, and it signifies that the employees’ abilities and professional development have advanced to a new level. It is beneficial in inspiring people to enhance their work abilities, to actively work hard, and to contribute to the improvement of the overall competitiveness of the organization.

2.6. Future-Oriented EHRQA. Traditional EHRQA has the issue of being static and backward-looking, which makes it ineffective. It focuses on the historical job performance, as well as the performance of job seekers and employees in the future. One’s prior success, on the other hand, cannot be compared to his potential contribution to the organization in the future. Good performance in the previous year does not necessarily imply great ability nor does it imply that the employee will be able to adapt to the company’s future strategy and culture and continue producing and contrib- uting in the same manner in the future. It is vital to im- plement a future-oriented human resource assessment in order to increase the organization’s strategic flexibility.

Future-oriented personnel evaluation is not simply a reversal of traditional evaluation; rather, it is a transfor- mation of traditional evaluation. It necessitates not only the evaluation of past and present performance but also the evaluation of the behavior of obtaining performance and then the inference of the assessee’s ability to adapt to the future from the behavior performance of the assessee. Traditional techniques of personnel selection are concerned with determining the degree to which the candidate’s existing knowledge, ability, and experience matches the degree of knowledge, ability, and experience required by the target position, and using this information as the selection criteria. While there is nothing wrong with selecting talents in this manner in order to quickly adapt to job requirements when the external business environment is relatively stable, when the external business environment is constantly changing, or when the company is in a stage of rapid

development, it is possible to select talents in accordance with the requirements of existing positions. It will diminish the adaptability of the organization, which means that it will reduce the firm’s strategic flexibility as well.

Companies must consider the demand for talents for the role in the future when hiring, and they must select job applicants based on the talent requirements required for future opportunities in order to increase strategic flexibility. Nokia Corporation had hidden concerns about the unex- pected future instability of the industry at the beginning of this century in the consideration and strategic layout of talent selection, and it used this as a starting point. People who are adaptable to future development and change have been identified as the primary target of talent recruitment. Instead of focusing on the most competent talents available at the time, this strategy allows the company to make swift adjustments when faced with organizational changes and significant changes in the industrial environment, thereby avoiding the creation of a talent crisis in the first place.

How is a future-oriented human resource assessment conducted? By establishing standards, such as the Nokia’s “two-dimensional” model, the universal competency model based on future change and development, as well as industry and organizational characteristics, lays the groundwork for assessment. +e organization’s use of a professional com- petency model enables it to conduct a future-oriented hu- man resource evaluation. Human resource evaluation in the future requires enterprise managers to have strong strategic analysis capabilities. +ey can contribute actively to strategy formulation and analysis of the organizational environment. Businesses should focus on predicting the evaluation object’s ability and performance in future situations from a timely perspective when conducting talent evaluation activities such as recruitment, selection, and assessment, following the establishment of talent evaluation standards. Following the evaluation, it is critical to adjust the prediction level of the evaluation standard in accordance with actual employee performance in order to improve the forecast’s accuracy and thus the evaluation’s effectiveness.

2.7. 1e Importance of Establishing a Training System. Enterprises have largely recognized the necessity of training, but the majority of training sessions are conducted on an emergency basis, frequently in response to group difficulties in management or when performance has been slow for a lengthy period of time. Retraining is an after-the-fact remedy when it comes to increasing strategic flexibility, according to this approach. If a company wishes to achieve “longevity,” the concept of adapting to “cure” is a “disease- prevention” approach, which involves developing a forward- looking training system and strengthening the strategic flexibility of the company, resulting in a driving force for long-term development.

+e forward-looking training system is comprised of two components. +e first component is forward-looking training based on personal development, and the second component is forward-looking training based on organi- zational change. Employees’ knowledge of their own

Mathematical Problems in Engineering 3

personal development may increase, which may lead to a demand for training in the form of a work transfer, job promotion, or job skills enhancement as a result of this increased awareness. After comparing the existing work skills of employees with the potential future work skills requirements, businesses can �nally determine their training requirements. In some circumstances, even though the current work performance of employees is satisfactory to the �rm, there is still a gap between the requirements of the organization’s plan and the current work performance of employees, which must be addressed in advance through training.

Organizational change occurs as a result of a variety of factors, including competition and technological innovation, stagnation in industry development, strategic goal adjust- ment, the evolution of the enterprise life cycle, and natural and man-made disasters. Human resource managers can anticipate this transition to the greatest extent possible, enabling them to provide training support with a high degree of match during the strategic planning and pro- motion stages. Investing in this type of forward-thinking training bene�ts the organization by assisting and pro- moting the development and implementation of the overall plan. It contributes to employees’ long-term ability and competency development.

3. The DDW Model

­is paper proposes the DDW model for EHRQA. ­e model structure is shown in Figure 1.

EHRQA concerns are in�uenced by a variety of factors, including human resource introduction policies and in- centives, as well as the operational state of the business. ­e implicit change trend provides a credible foundation for human resource cost assessment modeling. Chaos theory is a widely used data-driven method. It is possible to invert the changing trend of human resource costs using phase space reconstruction technology, and a learning sample of human resource costs can be generated. As a result of the experi- ment, chaos theory is applied to human resource cost data in this work and a multidimensional human resource cost time series is created.

Let the historical EHRQA data of a certain enterprise be x(tj), j � 1,2, · · · ,n{ }, n represents the number of EHRQA samples, and the original EHRQA data is transformed into a more accurate EHRQA data by determining the delay time λ and the embedding dimension m of x(tj). Regular EHRQA cost data is as follows:

X(l) �[x(l),x(l + λ), · · · ,x(l +(m − 1)λ)], l � 1,2, · · · ,M.

(1)

According to the results of the analysis of (1), the values of the variables λ and m of x(tj) are extremely important for accurately estimating the cost of human resources, where λ represents the time interval between data points and m represents that multiple data points are related to the current human resource cost. ­e optimal value λ of human resource cost data should be determined using the CC method, and

the optimal value m of human resource cost should be determined using the CAO algorithm.

­e steps to determine λ are as follows:

(1) Setting two EHRQA data as X(i) � [x(i), x(i + λ), · · · ,x(i + (m − 1)λ)] and X(j) � [x(j), x(j + λ), · · · ,x(j + (m − 1)λ)], the distance between them is

rij �‖X(i) − X(j)‖. (2)

(2) When calculating the value of a human resource cost assessment, the critical radius r is used to de�ne its valid range, the data points within the critical radius are statistically sensitive, the logarithmic ratio of statistical data points by the associated integral is used, and the calculation formula is as follows:

C(m,N,r,λ) � 2

M(M − 1) ∑

1≤i≤j≤M H(r − ‖X(i) − X(j)‖), (3)

where H(r − ‖X(i) − X(j)‖) is

H(x) � 0,x≤0

1,x>0 { . (4)

In accordance with the critical radius, we divide the complete EHRQA data set into t subhuman resource cost assessment data sequences, with the following results:

S(m,r,λ) � 1 t ∑ L

l�1 Cl(m,r,λ) − Cl(m,r,λ)[ ]

m{ }. (5)

­e di�erence between the data is

ΔS(m,l) � max S m,rj,λ( )[ ] − min S m,rj,λ( )[ ]. (6)

­en,

Human resource cost data

Chaos Analysis

Training set

Extreme training set

Particle Swarm Optimization Algorithm

DDW

whether to quit

YES

NO

Figure 1: structure of our framework.

4 Mathematical Problems in Engineering

ΔS(l) � 1 4 ∑ k

m�1 ΔS(m,t). (7)

IfΔS(l) gets the �rst minimum value, it means that the λ value at this time is the optimal EHRQA data delay time.

­e steps to determine m are as follows: the ith reconstructed human resource cost assessment data is Xi(m + 1), and its nearest neighbor EHRQA data vector is Xn(i,m)(m + 1); then,

α(i,m) � Xi(m + 1) − Xn(i,m)(m + 1) ����

���� Xi(m) − Xn(i,m)(m) ����

���� ,

i � 1,2, · · · ,N − mλ.

(8)

­en,

E(m) � 1

N − mλ ∑ N− mλ

i�1 α(i,m). (9)

Suppose there are k EHRQA data in total, they form a data set Sk (xp,tp){ }

k

p�1, and the EHRQA data set after

chaotic processing is xp � xp,xp+1, · · ·xp+m− 1{ } T ,

wheretp � xp+m and m is the embedding dimension; we can get

min 1 2 βTk βk +

c

2 εTk ε( ),

s.t. tp � ∑ L

i�1 βkf αkxp + bk( ) − εkp � 1,2, · · ·k

  .

(10)

­en,

l w,ε,βk( ) � 1 2 βTk βk +

c

2 εTk ε − w Hkβk − Tk − ε( ),

s.t. tp � ∑ L

k�1 βkf αkxp + bk( ) − εkp � 1,2, · · · ,k

  .

(11)

l

β1 βi βL

oj Output Node

L Hidden Nodes

n Input Nodes

xj

(ai, bi) i

l n

L

Figure 2: ­e structure of ELM.

0 0 50 100 150 200

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Figure 3: Comparison of di�erent models.

Mathematical Problems in Engineering 5

Let the partial derivative of (11) be 0; then,

zL

zβL ⟶ βTk � wHk

zL

zε ⟶ cεT + w � 0

zL

zw ⟶Hkβk − T − ε � 0

 

. (12)

Let t and x be the input and output of EHRQA, re- spectively; then the extreme learning machine of EHRQA is

t � ∑ L

i�1 βkf αkx + bk( ). (13)

­e extreme learning machine is shown in Figure 2.

4. Results

For the purpose of evaluating the performance of the DDW algorithm, an EHRQA data set has been selected as the study object. ­ere are a total of 300 data points in this set, which have been normalized to the range of 0–1, as shown in Figure 3. As a validation set, we choose 100 data points.

Figure 3 illustrates how chaos theory was used to obtain the EHRQA data. ­is demonstrates that the EHRQA data exhibits a certain degree of temporal correlation, as indi- cated by the ideal EHRQA data with T�5 and m�5. The original EHRQA data is processed and normalized to the time interval T�5 and m�5. ­ere are EHRQA learning samples available.

Figure 4 and 5 illustrate EHRQA results obtained using the algorithm described in this article. As can be seen, the model presented in this research is capable of accurately predicting the changing trend in EHRQA and producing

0 1 9 17 25 33 41 49 57 65 73 81 89 97 10 5

11 3

12 1

12 9

13 7

14 5

15 3

16 1

16 9

17 7

18 5

19 3

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

TRUE Train predict

Figure 4: Train results.

0

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

TRUE Train predict

Figure 5: Test results.

6 Mathematical Problems in Engineering

near-perfect EHRQA results. ­e �ndings demonstrate that chaos theory and extreme learning can be integrated into EHRQA research and that the resulting human resource cost assessment is reliable.

As part of the e�ort to make the experimental �ndings of the human resource cost assessment algorithm in this study comparable, the BPNN, ARIMA, and SVM algo- rithms are utilized as comparison algorithms and the RMSE and MAPE algorithms are employed to evaluate EHRQA results, respectively. ­e comparison results are shown in Figure 6.

It can be seen that the DDW method outperforms the other methods on both metrics. Among the four methods, BPNN has the worst performance, followed by SVM, and ARIMA is slightly lower than the DDW model.

5. Conclusion

­e enterprise-wide human resource quality assessment (EHRQA) is a critical metric for determining an organi- zation’s human resource management e�ectiveness. Due to the fact that EHRQA is dependent on factors such as �- nancial resources, reputation, personnel age and degree structure, and other criteria, as well as the local human resources introduction policy, the EHRQA procedure is quite complex. To improve the accuracy of EHRQA, an algorithm based on the data-driven and WICS leadership model is developed and chaos theory is incorporated to analyze the original data for the human resource cost as- sessment and establish human resource costs. We evaluate the learning samples to ascertain the underlying charac- teristics of the data’s variance. In addition, the extreme learning machine is used to learn the data for the human resource cost evaluation, and as a result of this learning, the human resource cost evaluation algorithm is developed. ­is is the outcome of the cost-bene�t analysis of human resources.

Data Availability

­e data sets used to support the �ndings of this study are available from the author upon request.

Conflicts of Interest

­e author declares no con�icts of interest.

Acknowledgments

­e paper was supported by (1) Human Resources and Social Security Issues in the Hebei Province, the Research on the Optimization of Human Resource Management Professional Talent Training Model from the Perspective of the Big Data—Taking Huaxin College as a case study, under JRSHZ- 2021-01077, and (2) Human Resources and Social Security Issues in the Hebei Province, Discussion on the Path of Improving the Young Teachers Instructional Leadership in Colleges and Universities in the Hebei Province, under JRSHZ-2022-01065.\\S1HCIFS01\DEMData\16955\MYFILE- S\HINDAWI\MPE\3259403\PROOF\COPYEDITING\gs2

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