Comprehensive evaluation of urban talent development environment based on entropy weight-topsis method

Abstract

For urban, the quantity and quality of talent is often an important measure of their development potential. Based on the theory of talent and environment comfort degree and the theory of urban comfort degree, this paper constructs the Evaluation Index System of urban talent development environment. This paper selects 7 coastal urban in Shandong province as the research objects, and uses entropy Weight-TOPSIS and cluster analysis to measure the talent development environment. The research results show that: (1) The talent development environment of seven coastal urban presents the phenomenon of “siphoning” and “distinctness” of talents. On the whole, Qingdao, Weifang, and Yantai have certain advantages in the talent development environment. (2) Qingdao is the leading city, Weifang, Yantai, Weihai and Dongying are follow-up urban, and Binzhou and Rizhao are backward urban. (3) The environment of the eight first-level indicators forms a “magnetic field” for the development of talents. Only by fully releasing the “magnetic field effect” of the talent development environment can urban ensure that talents are “attracted, retained and used well". This paper puts forward some suggestions to optimize the talent de-velopment environment in coastal urban, which will help to stimulate the vitality and creativity of all kinds of talents in coastal urban.

Keywords

Coastal urban talent development environment measurement entropy weight-topsis method

1 Introduction

The report of the 18th National Congress of the Communist Party of China first put forward the idea of “Building a strong maritime country". The report of the 19th puts forward: “Stick to the overall planning of land and sea, accelerate the building of a strong maritime country.” According to the 2021 Statistical Bulletin of China’s marine economy, the country’s marine 2021 is worth 9,038.5 billion yuan. The marine industry has recovered strongly, showing its development potential and resilience. The talents of coastal urban play a vital role in the development of marine economy [1]. For coastal urban, the quantity and quality of talent has become an important measure of their development potential [2]. There is a steady stream of policies to attract talent in inland urban, and more and more talent will choose to stay in inland urban [3]. The scientific measurement of the talent development environment in the coastal urban and the suggestion of optimizing the talent development environment in the coastal urban are helpful to stimulate the vitality and creativity of all kinds of talents in the coastal urban.

In recent years, Shandong province will “Marine strong province” as one of the main development goals. Shandong Peninsula is the largest Chinese peninsula. The ocean is the greatest momentum, the greatest advantage and the greatest potential of Shandong’s development. In March 2020, Shandong province published on the implementation of the Talent Xinglu action to create a new era of talent gathering high land a number of measures. Shandong province proposes to build a highland for marine science and technology talents. Shandong has seven coastal urban in Qingdao, Yantai, Rizhao, Weihai, Weifang, Dongying and Binzhou. Seven coastal urban attach great importance to the construction of the talent environment, and constantly introduce new policies in optimizing the talent development environment. In order to systematically measure the talent development environment of 7 coastal urban in Shandong province, this paper constructs a set of scientific and reasonable evaluation index system of urban talent development environment. The entropy Weight-TOPSIS method is used to calculate the talent development environment of 7 coastal urban in Shandong province. The paper comprehensively and accurately evaluates the talent development environment con-struction level of 7 coastal urban in Shandong province, and makes an effective diagnosis to the talent development environment construction of 7 coastal urban in Shandong province.

The research on talent development environment mainly comes from the theory of population flow [4]. Population flow is a form of talent regulation, the study of talent flow begins with the outflow and inflow of employees [5]. The re-search on talent development environment mainly focuses on two aspects: talent flow and attracting factors, and talent development environment evaluation.

Talent flow is the dynamic expression of talent development environment [6]. The factors of urban talent flow have different manifestations in different periods of urban or regional development [7].The existing theories and related research results can be summarized in three aspects. First, it can provide the capacity for employment, such as economic factors, social factors [8], employment policy [9, 10], social security conditions [11, 12] and other factors. Second, it can provide opportunities for development factors, such as work stress, work-life balance, self-worth and other factors [13 –15]. Third, it can provide livable environmental factors, such as social environment [16], natural environment [17], cultural background [18], educational environment [19], housing environment [20] and other factors. Talent development environment is the key to talent attraction. Later, scholars began to study the problem of talent attraction. For example, the Internet development and governance research center of Tsinghua University School of Economics and Management and LinkedIn jointly release the Annual Report on Global Digital Talent Development and the report on the attractiveness of Chinese overseas returnees evergrande research institute and zhaopin.com jointly released the “ China city talent attraction ranking"; dongwu securities chief economist ren zeping team and zhaopin.com jointly published “China’s urban attractiveness rankings” and other [12].

The evaluation index system of talent development environment is constructed from different dimensions. Scholars have constructed the evaluation index system of talent development environment from the regional angle. Such as national level [13, 21], provincial level [10, 22], urban level [23]. Scholars have constructed the evaluation index system of talent development environment from the perspective of different types of talents. Such as academic talents, engineering talents, technical talents, skilled talents [24 –26].

Methods of environmental assessment of urban talent development mainly include analytic hierarchy process, fuzzy comprehensive evaluation, factor analysis, principal component analysis, Data envelopment analysis, entropy and so on [27, 28]. The evaluation methods are more and more diversified.

1.1 Research gaps based on literature review

Many academics have Exploratory research much about the flow and attraction of talent in urban and the environment in which it is developed. The research achievements are continuously abundant, but the research depth needs to be strengthened. Firstly, the study of urban talent development environment is mainly qualitative research, quantitative research is not rich enough. Secondly, there are many researches on the relationship between environmental factors and talent flow, but few on the evaluation of urban talent development environment. Generally, single city is chosen as the research object, while coastal urban are not often chosen as the empirical object [29, 30]. Thirdly, the evaluation index system of talent development environment is mostly based on the Maslow’s hierarchy of needs or the “Push-pull” theory, and the research difference is quite big [31, 32]. The evaluation index system based on the theory of individual-environment fit and urban comfort is few.

1.2 Research questions and intended contribution of the study

Based on the research gap described above, the study has realized the following research questions:

How to construct the Evaluation Index System of urban talent development environment based on the theory of personal environment adaptation and urban comfort?

How to evaluate urban talent development environment effectively and comprehensively?

How to put forward the countermeasures and suggestions to optimize urban talent development environment?

The expected contributions of the study are as follows: firstly, based on the theory of individual-environment fit and urban comfort, this paper constructs a set of evaluation index system of urban talent development environment, which is beneficial to the exertion of talent value and the activation of talent vitality. Secondly, this paper selects 7 coastal urban in Shandong province as the research objects, and uses entropy Weight-Topsis and cluster analysis to measure the talent development environment. The aim is to find out the difference of talent development environment in 7 coastal ur-ban of Shandong province. Thirdly, considering the time change and spatial distribution, the horizontal and vertical comparison of 7 coastal urban in Shandong province talent development environment. According to the evaluation results, the paper puts forward some suggestions to optimize the urban talent development environment.

1.3 Organization of the paper

The rest of the paper is organized as follows: Section 2 presents research design, including theoretical model, index system construction, data sources, method of measurement; Section 3 is measurement analysis; finally, the conclusions and Recommendations are presented in Section 4 along with limitations and future scope. The workflow of the paper is shown in Fig. 1.

Fig. 1

The workflow of the paper.

2 Research design

2.1 Theoretical model

Murray and Lewin put forward the theory of person-environment fit [33]. Ullman put forward the theory of urban comfort [34]. Urban should start from meeting the material needs, spiritual needs and value realization needs of talents, and create a “high-quality model” soft and hard environment for talent development. The urban talent development environment is a comprehensive system composed of many elements, a multi-level dynamic system. The combination of individual-environment matching theory and urban comfort theory can well explain the relationship between the environmental needs of urban talent development and environmental matching in different dimensions. The two theories link the city’s natural comfort, artificial comfort and atmospheric comfort with meeting the conditions for talent development. In addition, the evaluation model of urban talent development environment based on individual-environment matching theory and urban comfort theory is an evaluation model based on the perspective of systems theory, which can reflect the comprehensive impact of urban multi-factor environment on talent development, and can better explain the urban talent development environment. Changes in the combined effect of multiple factors. The model mechanism is shown in Fig. 2.

Fig. 2

The evaluation model for urban talent development environmental.

2.2 Index system construction

The author consults and draws on relevant literature [35 –37]. Based on the theory of talent and environmental comfort and the theory of urban comfort, an environmental evaluation index system for talent development in coastal urban is constructed. The evaluation index system includes both the “hard environment” for talent attraction and the” soft environment” for talent attraction. It includes 8 first-level indicators including economic development environment, natural environment, greening environment, living and living environment, innovation and development environment, cultural and humanistic environment, social security environment, and public safety environment. The specific evaluation index system (including index weights) is shown in Table 1.

Table 1
Evaluation index system (including index weights)

Primary Index Weight Secondary Index Indicator Weight

Direction

Economic development environment 0.1282 Per capita gross regional product + 0.0242

Secondary sector of the economy as a percentage of the region’s gross domestic product + 0.0156

Tertiary sector of the economy as a percentage of regional Gross Domestic Product + 0.0073

The growth rate of fixed asset investment + 0.0073

Foreign Direct Investment + 0.0431

General Public Budget Revenue + 0.0307

Natural environment 0.0765 Mean temperature in January + 0.0123

Mean temperature in July – 0.0106

Average precipitation + 0.0133

Annual Sunshine Hours + 0.0214

Total Water Resources + 0.0189

Green Environment 0.0729 Per capita green area of parks + 0.0176

Green Coverage area + 0.0341

Discharge of waste water – 0.0138

Sulfur dioxide emissions – 0.0074

Living environment 0.2592 Disposable income + 0.0118

Urban population density – 0.0162

Water supply penetration rate + 0.0619

Gas Penetration + 0.0040

Per capita urban road area + 0.0146

Number of civilian cars owned by the public + 0.0301

Household Deposits + 0.0268

Number of mobile phone subscribers + 0.0301

Number of fixed telephone subscribers + 0.0260

Broadband Internet access users + 0.0269

Number of computers used per 100 people + 0.0108

Innovative and development environment 0.1015 Number of patent applications granted + 0.0384

Research and test development personnel + 0.0322

R &D outlay + 0.0309

Cultural and humanistic environment 0.1280 Number of books in public libraries + 0.0199

Heritage business fee + 0.0272

Cultural Centre + 0.0494

Museum + 0.0315

Social security environment 0.2156 Registered urban unemployment rate – 0.0171

Retirement and retirement insurance benefits + 0.0213

Education expenditure + 0.0274

Social Security and employment expenditure + 0.0268

Health expenditure + 0.0243

Housing expenditure + 0.0150

Number of health and medical institutions + 0.0255

Average junior high school number + 0.0292

Average high school number + 0.0290

Public safety environment 0.0181 Number of traffic accidents – 0.0096

Number of fire accidents – 0.0085

Primary Index	Weight	Secondary Index	Indicator	Weight
Economic development environment	0.1282	Per capita gross regional product	+	0.0242
		Secondary sector of the economy as a percentage of the region’s gross domestic product	+	0.0156
		Tertiary sector of the economy as a percentage of regional Gross Domestic Product	+	0.0073
		The growth rate of fixed asset investment	+	0.0073
		Foreign Direct Investment	+	0.0431
		General Public Budget Revenue	+	0.0307
Natural environment	0.0765	Mean temperature in January	+	0.0123
		Mean temperature in July	–	0.0106
		Average precipitation	+	0.0133
		Annual Sunshine Hours	+	0.0214
		Total Water Resources	+	0.0189
Green Environment	0.0729	Per capita green area of parks	+	0.0176
		Green Coverage area	+	0.0341
		Discharge of waste water	–	0.0138
		Sulfur dioxide emissions	–	0.0074
Living environment	0.2592	Disposable income	+	0.0118
		Urban population density	–	0.0162
		Water supply penetration rate	+	0.0619
		Gas Penetration	+	0.0040
		Per capita urban road area	+	0.0146
		Number of civilian cars owned by the public	+	0.0301
		Household Deposits	+	0.0268
		Number of mobile phone subscribers	+	0.0301
		Number of fixed telephone subscribers	+	0.0260
		Broadband Internet access users	+	0.0269
		Number of computers used per 100 people	+	0.0108
Innovative and development environment	0.1015	Number of patent applications granted	+	0.0384
		Research and test development personnel	+	0.0322
		R &D outlay	+	0.0309
Cultural and humanistic environment	0.1280	Number of books in public libraries	+	0.0199
		Heritage business fee	+	0.0272
		Cultural Centre	+	0.0494
		Museum	+	0.0315
Social security environment	0.2156	Registered urban unemployment rate	–	0.0171
		Retirement and retirement insurance benefits	+	0.0213
		Education expenditure	+	0.0274
		Social Security and employment expenditure	+	0.0268
		Health expenditure	+	0.0243
		Housing expenditure	+	0.0150
		Number of health and medical institutions	+	0.0255
		Average junior high school number	+	0.0292
		Average high school number	+	0.0290
Public safety environment	0.0181	Number of traffic accidents	–	0.0096
		Number of fire accidents	–	0.0085

The construction logic of the eight first-level indicators is as follows:

Economic development environment: A coastal city with a higher level of economic development and a better urban construction level will be more attractive to talents.

Natural environment: The natural environment is the geographic location factor for talent attraction, aggregation, integration and growth.

Green environment: Green environment is the quality guarantee of a good life for talents.

Living and living environment: The living and living environment is the premise of talents’ performance.

Innovation and development environment: To stimulate the innovation and creativity of talents, it is necessary to create a good environment for innovation and development.

Cultural and humanistic environment: A harmonious and progressive cultural and humanistic environment can enhance talent’s sense of identity, pride and belonging to the city.

Social security environment: The social security environment is the fundamental guarantee for the performance of talents.

Public safety environment: The public security environment can enhance the happiness and security of talents. There are 44 second-level indicators under the eight first-level indicators.

2.3 Data sources

This paper selects seven coastal urban in Shandong Province from 2018 to 2020 as the object of empirical analysis. The sample data were obtained from the statistical bulletins of seven coastal urban in the 2021 Shandong Statistical Yearbook from 2019 to 2021.

2.4 Method of measurement

Entropy weight method is an objective method to determine the weight based on information entropy. The smaller the index entropy value is, the more information the index reflects, that is, the greater the weight; the larger the index entropy value is, the less information the index reflects, that is, the less the weight. The steps are as follows [38]:

Step 1. Standardization of indicators $Y_{ij} = {\begin{matrix} \frac{X_{ij} - min (X_{ij})}{max (X_{ij}) - min (X_{ij})}, X_{ij} is a positive indicator \\ \frac{max (X_{ij}) - X_{ij}}{max (X_{ij}) - min (X_{ij})}, X_{ij} is a negative indicator \end{matrix}$ (1)

In the above formula, i denotes the evaluation object, j denotes the measure index, X_ij denotes the original index value, Y_ij denotes the standardized index value, and max(X_ij) epsfboxG :/Tex/IOSPRESS/IFS/0 -222889/IF - 01 . epsmin(X_ij) denote the maximum and minimum values of X_ij, respectively.

Step 2. Calculate the proportion P_ij of the jth index of the ith evaluation object $P_{ij} = \frac{Y_{ij}}{\sum_{i = 1}^{n} Y_{ij}}$ (2)

In the above formula, n is the sample number of the research object.

Step 3. Calculate the entropy value e_j of the jth index $e_{j} = - k \times \sum_{i = 1}^{n} [p_{ij} \times log (p_{ij})]$ (3) $k = \frac{1}{ln n}$

Step 4. Calculate the difference coefficient E of the jth index $g_{i} = 1 - e_{j}$ (4)

Step 5. Calculate the weight w_j $w_{j} = \frac{g_{i}}{\sum_{j = 1}^{m} g_{j}}, j = 1, 2 \dots \dots m$ (5)

Among in, m is the index number.

The TOPSIS method quantifies the ranking by comparing the relative distances between each measurement object and the optimal and worst schemes, which has the advantages of simple calculation and reasonable results. Entropy method and TOPSIS method are suitable for urban talent development environment evaluation.

Step 1. Index weighted evaluation value matrix

Obtain the index weighted evaluation value matrix by standardizing the decision matrix Y = (y_ij) , (i = 1, 2 …… , m ; j = 1, 2 …… , n) and the index weight w_j. $γ = [\begin{matrix} w_{1} y_{11} & \dots & w_{j} y_{1 n} \\ ⋮ & ⋱ & ⋮ \\ w_{1} y_{m 1} & \dots & w j y_{mn} \end{matrix}] = [\begin{matrix} γ_{11} & \dots & γ_{1 n} \\ ⋮ & ⋱ & ⋮ \\ γ_{m 1} & \dots & γ_{mn} \end{matrix}]$ (6)

Step 2. Determine ideal solution and negative ideal solution $S_{j}^{+} = max (γ_{ij}), S_{j}^{-} = min (γ_{ij})$ $1 \leq i \leq m, 1 \leq j \leq n .$ (7)

Step 3. Calculate the distance between the optimal solution and the worst solution $D_{i}^{+} = \sqrt{\sum_{j = 1}^{n} S_{j}^{+} - γ_{ij})^{2}}$ (8) $D_{i}^{-} = \sqrt{\sum_{j = 1}^{n} S_{j}^{-} - γ_{ij})^{2}}$ (9)

Step 4. Calculates the closeness of the measure object to the ideal solution $C_{i} = \frac{D_{i}^{-}}{D_{i}^{+} + D_{i}^{-}}, C_{i} \in [0, 1]$ (10)

The C_i value is the comprehensive score of urban talent development environment, which is between 0 and 1. The higher the score, the more advantageous the urban is in talent development environment.

3 Measurement analysis

3.1 Comprehensive measurement of talent development environment in coastal urban

Figures 3 and 4 reflect the comprehensive scores and rankings of the talent development environment of the seven coastal urban, respectively. Figures 3 and 4 show that from 2018 to 2020, the comprehensive scores of the seven coastal urban’ talent development environment presented a “V"-shaped curve. Qingdao, Weifang, and Yantai rank among the top three in terms of comprehensive scores for talent development environment, and the rankings are very stable. Coastal urban pay great attention to attracting high-quality talents.

Fig. 3

Comprehensive score of talent development environment in seven coastal urban.

Fig. 4

Comprehensive ranking of talent development environment in seven coastal urban.

The F score of the talent development environment in coastal urban is between [0-1], and the higher the F score, the more obvious the advantages of the talent development environment in the coastal city. The talent development environment of coastal urban can be divided into three levels. Leading urban have an F-score between [0.5-1]; following urban have an F-score between [0-0.5); laggard urban have an F-score between 0-0.25).

By calculating the average score of talent development environment in seven coastal urban from 2018 to 2020, the author found that the talent development environment of seven coastal urban presents the phenomenon of talent “siphoning” and “distinction”. Qingdao is a leading city, and the average score of talent development environment is 0.60, between 0.5-1]. Weifang City, Yantai City, Weihai City and Dongying City are follow-up urban, and the average scores of talent development environment are 0.43, 0.40, 0.27, and 0.26, respectively, ranging from [0-0.5). Binzhou and Rizhao are backward urban rand the average scores of talent development environment are 0.24 and 0.21 respectively rranging from 0-0.25).

3.2 Sub-item measurement of talent development environment in coastal urban

Tables 2 r1 r2 r3 r4 r2019 rand 2020 rrespectively. The evaluation results show that from 2018 to 2020 rQingdao has obvious advantages in the dimensions of economic development environment rgreening environment rliving and living environment rinnovation and development environment rcultural and humanistic environment rand social security environment. The advantages allow Qingdao to form a talent gathering effect rwhich shows that Qingdao’s current talent development environment has obvious advantages rand the measures for talent development environment construction are relatively appropriate. From 2018 to 2019 rWeifang City has certain advantages in the dimension of natural environment. In 2020 rRizhao City and Qingdao City will surpass Weifang City. In 2018 rRizhao City has obvious advantages in the dimension of public safety environment. From 2019 to 2020 rWeihai City has certain advantages in the dimension of public safety environment. Average score and ranking of talent development environment in seven coastal urban from 2018 to 2020 is shown in Figs. 5 and 6. All in all rQingdao’s talent development environment has relatively obvious advantages and can play a good role in Qingdao’s radiating and leading role. The differences in the talent development environment of the seven coastal urban are mainly reflected in the details of the eight dimensions of the coastal city’s talent development environment.

Fig. 5

Average score of talent development environment in seven coastal urban from 2018 to 2020.

Fig. 6

Ranking of talent development environment in seven coastal urban from 2018 to 2020.

Table 2

The score of talent development environment in seven coastal urban in 2018

Coastal	Economic	Natural	Green	Living	Innovative	Cultural	Social	Public
urban	development	environment	environment	environment	and development	and humanistic	security	safety
	environment				environment	environment	environment	environment
Qingdao	0.76	0.51	0.59	0.66	0.54	0.44	0.73	0.51
Dongying	0.36	0.55	0.40	0.52	0.02	0.07	0.10	0.55
Yantai	0.37	0.52	0.23	0.48	0.22	0.27	0.48	0.50
Weifang	0.24	0.65	0.18	0.53	0.19	0.40	0.58	0.58
Weihai	0.26	0.49	0.39	0.47	0.07	0.18	0.23	0.74
Rizhao	0.15	0.55	0.27	0.38	0.00	0.06	0.20	0.93
Binzhou	0.11	0.47	0.20	0.44	0.04	0.06	0.22	0.85

4 Conclusions and recommendations

4.1 Conclusions

Based on the theory of talent and environmental comfort and the theory of urban comfort rthe author constructs an environmental evaluation index system for urban talent development. Taking seven coastal urban in Shandong Province as the empirical analysis objects rthe entropy weight-TOPSIS method is used to measure. The following conclusions are drawn: The talent development environment of seven coastal urban presents the phenomenon of “siphoning” and “distinctness” of talents. On the whole rQingdao rWeifang rand Yantai have certain advantages in the talent development environment. Qingdao is the leading city rWeifang rYantai rWeihai and Dongying are the following urban rand Binzhou and Rizhao are the backward urban. The environment of the eight first-level indicators forms a “magnetic field” for the development of talents. Only by fully releasing the “magnetic field effect” of the talent development environment can urban ensure that talents are “attracted rretained and used well”.

4.2 Recommendations

Firstly rcoastal urban use “policy temperature” to warm talents. Coastal urban should emancipate their minds rbroaden their thinking roptimize the talent attraction mechanism rand give full play to the guiding role of policies 39">0-0.5). Binzhou and Rizhao are backward urban, and the average scores of talent development environment are 0.24 and 0.21 respectively, ranging from 0-0.25).

Tables 2–4 reflect the scores of the eight dimensions of talent development environment in seven coastal urban in 2018, 2019, and 2020, respectively. The evaluation results show that from 2018 to 2020, Qingdao has obvious advantages in the dimensions of economic development environment, greening environment, living and living environment, innovation and development environment, cultural and humanistic environment, and social security environment. The advantages allow Qingdao to form a talent gathering effect, which shows that Qingdao’s current talent development environment has obvious advantages, and the measures for talent development environment construction are relatively appropriate. From 2018 to 2019, Weifang City has certain advantages in the dimension of natural environment. In 2020, Rizhao City and Qingdao City will surpass Weifang City. In 2018, Rizhao City has obvious advantages in the dimension of public safety environment. From 2019 to 2020, Weihai City has certain advantages in the dimension of public safety environment. Average score and ranking of talent development environment in seven coastal urban from 2018 to 2020 is shown in Figs. 5 and 6. All in all, Qingdao’s talent development environment has relatively obvious advantages and can play a good role in Qingdao’s radiating and leading role. The differences in the talent development environment of the seven coastal urban are mainly reflected in the details of the eight dimensions of the coastal city’s talent development environment.

Table 3
The score of talent development environment in seven coastal urban in 2019

Coastal Economic Natural Green Living Innovative Cultural Social Public

urban development environment environment environment and development and humanistic security safety

environment environment environment environment environment

Qingdao 0.65 0.46 0.61 0.48 0.79 0.44 0.76 0.45

Dongying 0.26 0.47 0.38 0.20 0.11 0.08 0.09 0.83

Yantai 0.30 0.47 0.24 0.33 0.26 0.32 0.52 0.79

Weifang 0.20 0.53 0.19 0.40 0.29 0.41 0.61 0.62

Weihai 0.18 0.48 0.39 0.18 0.13 0.13 0.23 0.94

Rizhao 0.10 0.47 0.26 0.07 0.09 0.04 0.22 0.88

Binzhou 0.10 0.48 0.22 0.16 0.11 0.06 0.29 0.94

Coastal	Economic	Natural	Green	Living	Innovative	Cultural	Social	Public
Qingdao	0.65	0.46	0.61	0.48	0.79	0.44	0.76	0.45
Dongying	0.26	0.47	0.38	0.20	0.11	0.08	0.09	0.83
Yantai	0.30	0.47	0.24	0.33	0.26	0.32	0.52	0.79
Weifang	0.20	0.53	0.19	0.40	0.29	0.41	0.61	0.62
Weihai	0.18	0.48	0.39	0.18	0.13	0.13	0.23	0.94
Rizhao	0.10	0.47	0.26	0.07	0.09	0.04	0.22	0.88
Binzhou	0.10	0.48	0.22	0.16	0.11	0.06	0.29	0.94

Table 4

The score of talent development environment in seven coastal urban in 2020

Coastal	Economic	Natural	Green	Living	Innovative	Cultural	Social	Public
urban	development	environment	environment	environment	and development	and humanistic	security	safety
	environment				environment	environment	environment	environment
Qingdao	0.64	0.44	0.70	0.50	0.98	0.82	0.79	0.02
Dongying	0.27	0.25	0.39	0.21	0.13	0.18	0.06	0.77
Yantai	0.33	0.36	0.46	0.35	0.37	0.68	0.50	0.48
Weifang	0.22	0.41	0.23	0.41	0.39	0.70	0.58	0.32
Weihai	0.20	0.40	0.41	0.21	0.15	0.34	0.15	0.78
Rizhao	0.12	0.50	0.27	0.09	0.10	0.23	0.18	0.77
Binzhou	0.12	0.23	0.29	0.19	0.17	0.38	0.24	0.59

5 Research prospect

First of all, the scientific nature of urban evaluation indicators needs further verification. The author obtains relevant indicator data from the statistical yearbook or annual report according to the principle of availability. The data are all second-hand data. In the next step, primary data indicators can be added, and the required primary data can be obtained by means of questionnaires, so as to further optimize the evaluation indicators.

Secondly, the future research can consider the spatial difference analysis of the talent attraction of coastal urban. Collect data on the talent development environment of 53 coastal urban in China, and use the spatial econometrics model to study the spatial difference of the talent development environment of coastal urban.

Funding

This research was s funded by Shandong Soft Science Project (2021RKY05097) and Jinan Philosophy and social science key project (JNSK21B48).

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