54 Abstract During the COVID-19 pandemic, China has achieved high recovery efficiency. One of the most important reasons behind this is the effective poli- cies of promoting work resumption. Why can such policies maintain steady performance despite the high level of environmental uncertainties? This ques- tion can be answered from the perspective of policy resilience. This study employed a policy evaluation model for analyzing quantitative data of 342 poli- cies of promoting work resumption. We evaluate the policies through the Policy Modeling Consistency (PMC-index) model and text mining methods. The results show that: first, the contents and elements of all policies have consistent characteristics, including the combination of multiple policy tools, the combi- nation of support for work resumption and pandem- ic control, the incentives to support effective policy implementation, and the reasonable match between macro and micro policies as well as short-term and long-term policies. Second, among the nine policies that are randomly selected from the sample, one is rated excellent and the other eight are good, indicat- ing that China’s policies of promoting work resump- tion have good resilience. Keywords: COVID-19 pandemic, policy resilience, China’s policies of promoting work resumption, PMC-Index Model. A CASE STUDY ON CHINA’S POLICIES OF PROMOTING WORK RESUMPTION DURING THE COVID-19 PANDEMIC — PERSPECTIVE OF POLICY RESILIENCE*1 Qicheng LU Bin RONG Yijia LI Qicheng LU Professor, PhD, Business School of Yunnan University of Finance and Economics, Kunming, Yunnan, China E-mail: luqicheng@aliyun.com Bin RONG (corresponding author) MA candidate, Business School of Yunnan University of Finance and Economics, Kunming, Yunnan, China Tel.: 0086-199-1694.5502 E-mail: rbrongbin@aliyun.com Yijia LI Associate professor, Information School of Yunnan University of Finance and Economics, Kunming, Yunnan, China E-mail: tilburg@sohu.com * Acknowledgement: Supported by National Natural Science Foundation of China (no. 71872160, no. 71663057, no. 72064043), Key Program of Applied Basic Research Plan in Yunnan Province (no. 2019FA026), Graduate Innovation Fund Program of Yunnan University of Finance and Economics (no. 2021YUFEYC069). DOI: 10.24193/tras.SI2021.4 Published First Online: 12/15/2021 Transylvanian Review of Administrative Sciences, Special Issue 2021, pp. 54–76 55 1. Introduction Why could China overcome the COVID-19 pandemic peak and achieve rapid eco- nomic and social recovery? In recent decades, the losses caused by global crisis events have escalated (Abdulkareem, Elkadi and Breane, 2018, p. 176; Saja et al., 2018, pp. 862–863), and various new risks have emerged one after another. The economic devel- opment of a country is inevitably impacted or disturbed by factors such as economic recessions, technological innovation, natural disasters and even terrorism. Thus, the capacity of national crisis management is highly required. In particular, the outbreak of the COVID-19 pandemic has caused serious and lasting impact on the global economy and societies (Milani, 2020, pp. 1–2). It brings serious challenges of economic resilience, especially policy resilience. In 2020, the world’s total GDP decreased by 3.3% year-on- year, while China’s GDP increased by 3.1%, which is the only country with an increase of GDP among the top 15 countries. In fact, most of the emerging economies have been seriously troubled by the COVID-19 pandemic, and their economic development has stagnated or even declined. After analyzing the deeper reasons, we found that the Chinese government has designed and issued a series of policies to promote work re- sumption after the COVID-19 pandemic outbreak, so as to guide enterprises to effec- tively realize the resumption of work and production, and help enterprises overcome difficulties from the aspects of taxation, epidemic prevention, law, employment and so on. Under the circumstances of limited time and uncertain environment, the policies formulated by the Chinese government have shown strong resilience and effectively promoted the high-quality economic and social recovery. What is the nature of a policy with strong resilience is worth studying by scholars, and it is also an urgent problem to be solved through policy design. This study explores China’s policies of promoting work resumption from the perspective of resilience, aiming to promote the develop- ment of resilience theory, provide new thinking for policy-making, and have important value for the government to enhance its emergency management ability. Resilience, also known as elasticity and recovery, refers to the adaptability, recov- ery and sustainable development ability of various subjects when they encounter ex- ternal risks, pressures and damages (Walker et al., 2004, p. 2; Alexander, 2013). Resil- ience has originated from physics and is used to represent the property that an object recovers to its original state after being deformed by external forces (Bozza, Asprone and Manfredi, 2015, p. 1730). In the 1950s, psychology used resilience to denote the ability of individuals or families to actively face and adapt to adversity. In the 1970s, Holling (1973) introduced resilience into system ecology, indicating the ability of the ecosystem to maintain the operation of main functions and structures after being im- pacted by the outside environment. After that, human beings gradually extended re- silience from system ecology to social ecology for the purpose of maximizing social benefits and minimizing environmental impact (Berkes, Folke and Colding, 1998). With VUCA (Volatility, Uncertainty, Complexity and Ambiguity) becoming the pronoun of current environmental characteristics, economic resilience has increasingly become a strategic issue that countries all over the world must pay attention to in the pursuit of 56 economic development. It can ensure that economies can make rapid adjustment in the event of impact, and it is the basis for supporting the fine operation of economic and social systems (Martin and Sunley, 2015, p.13). Among them, policy resilience signifi- cantly helps to improve economic resilience and is the main driving force for healthy and high-quality development of economy and society after the outbreak of the crisis (Ma, Xiao and Yin, 2018, p. 247; Swanson et al., 2010, p. 924). It refers to the adaptive adjustment ability, reform ability and the vitality stimulated by the policy system when the economic and social system are impacted by the crisis (Capano and Woo, 2017). It resists and solves the consequences of the impact by adjusting policies and reallocat- ing resources, as well as restoring the original economic and social development. For example, after the outbreak of COVID-19 pandemic, more than 20% of the policies of China’s promoting work resumption stimulated the demand for electricity through phased measures such as reducing the price of electricity, subsidies for the use of elec- tricity, and no power failure after arrears. The year-on-year growth rate of power con- sumption in the second quarter of 2020 increased by 10.4% compared with the first quarter (People’s Daily, 2020), which is regarded as the ‘barometer’ of economic oper- ation. It reflects the good trend of China’s economic recovery (People’s Daily Overseas Edition, 2020), and reflects the remarkable effect of the policies of promoting work resumption. Policy design is a complex process, involving multiple actors and multi- ple interest demands. When facing VUCA situation, this puts forward stricter require- ments for policy-making. But the research on policy resilience can provide guidance for the government’s effective decision-making. Policy is an important way to improve economic resilience (Briguglio et al., 2006). However, gaps exist in the current field due to the lack of research on specific policies from the perspective of resilience. The deficiencies are as follows: first, no study has found a suitable perspective and method to analyze the radical advantages of China’s policies of promoting work resumption, the possible reasons for this are the limited empirical evidence, lack of policy evaluation tools and inadequate policy resilience the- ory. Second, as one of the three values of public administration, resilience often contra- dicts the bureaucratic norms and procedural principles of efficiency. The introduction of resilience theory needs to balance its relationship with other values (Hood, 1991, p. 11). However, the lack of research on the paradigm of policy resilience seriously re- stricts the consideration of resilience in policy design. Third, policy evaluation mainly focuses on the period or after policy implementation, such as Markov Analysis, Cost Benefit Analysis and Comparison Method. In these two stages of evaluation, policies often waste time and resources because of some inappropriate contents, and these play little role in a highly uncertain environment. Meanwhile, there are few policy evalua- tion methods before policy implementation, but the evaluation methods have the prob- lem of strong subjectivity, which cannot ensure the objectivity and scientificity of the evaluation results (Yi and Feiock, 2012; Suddaby, 2006; Baniya, Giurco and Kelly, 2021). In order to solve the limitations of the previous studies, from the perspective of policy resilience, this study analyzes China’s policies of promoting work resumption 57 by comprehensively using PMC-index model and text mining tools. The difference be- tween this model and the previous policy evaluation model is that it is based on the hypothesis of omnia mobilis as the guiding ideology, the main purpose of this model is that everything in the world is moving and connected. Therefore, any relevant vari- able should not be ignored or considered unimportant (Ruiz Estrada, Yap and Nagaraj, 2008, p. 188). When selecting variables, the scope of consideration is wider. The anal- ysis system based on this can effectively test the adaptability and stability of policies. Meanwhile, the model adopts the method of text mining, which can avoid the subjec- tivity of expert scoring and make the policy evaluation more objective and scientific. PMC-index model has been applied to new energy, cultivated land protection, science and technology and other fields for policy evaluation (Yang, Xing and Li, 2020; Kuang et al., 2020; Du, Yuan and Gao, 2019), showing good adaptability and scientificity. The novelty of this study includes three aspects: (1) Taking the COVID-19 pandemic as the research opportunity, this study analyzes the reasons for the steady performance of China’s policies of promoting work resumption from the perspective of policy resil- ience, which responds to recent calls (Dutt, 2016, p. 377). This provides practical value by suggestions on policy making of economic recovery for other countries, especially emerging economies; (2) Policy resilience is mainly reflected in the stability and adapt- ability of policies in an uncertain environment (Dutt, 2016, p. 375). Guided by these two characteristics, this study applies PMC-index model to analyze policy, which is a new attempt in the field of policy resilience research; (3) Before the implementation of the policy, we can comprehensively analyze its content and characteristics through text mining and quantitative evaluation of the policy text. It can enhance the objective fairness of the evaluation results and put forward scientific and comprehensive policy optimization paths to provide useful enlightenment for improving policy resilience. 2. Describing the case At the beginning of 2020, COVID-19 pandemic broke out all over the world, affect- ing the normal operation of economy and society. China was also seriously affected by it. The closure of cities began on January 23, and enterprises stopped production in a wide range, resulting in a year-on-year decrease of 6.8% in China’s GDP in the first quarter of 2020. However, it reversed the growth to 3.2% in the second quarter. China’s ‘Working arrangements for COVID-19 pandemic prevention and control and economic and social development’ conference was released in February 23, 2020, which has made strict arrangements for the next epidemic prevention and control and economic and so- cial development, and has begun the work of promoting work resumption. After that, China’s State Council, provinces, municipalities directly under the central government and autonomous regions have successively issued a series of policies on promoting work resumption in a short time, effectively helping enterprises to resume production smoothly and realizing the ‘V-shaped’ reversal of GDP during the epidemic. During this period, China helped the stagnant economic and social system revitalize through 58 policies that aimed at repairing the broken industrial chain, restore transportation, pro- vide financial and resource support, and restore personnel mobility. An example of such as policy is ‘Emergency notice on work resumption and dispatching arrangement of key material production enterprises for epidemic prevention and control’. Before the full work resumption, the Chinese government supported the survival of enterprises by maintaining and rebuilding the basic resources needed for enterprise operation. Especially for basic medical protection resources, the government was increasing the production subsidies and reserves, and directly provided them to employees return- ing to work, so as to prevent and control the epidemic and help enterprises solve the difficulties. In order to solve the major problem of enterprise employees maintaining realistic social distance (Radu, 2021, p. 128), the government issued ‘Special action plan for digital empowerment of small and medium-sized enterprises’ and other policies. Among these policies, the government has applied new mobile phone applications such as ‘Travel Track Card’ and ‘Health Code’ through information technology to sci- entifically and accurately track epidemic transmission paths. These policies also guide enterprises to realize online office, online financial management, and remote coop- eration and so on through digital tools. At the same time, these policies support and guide enterprises to build a supply chain system and sales network through digital operation, which combines online procurement and sales, offline optimal inventory and unmanned distribution, and intelligent logistics. Through a series of policies, the enterprise’s ability to deal with sudden crises and the stability of operation have been improved. Even if there is some structured evidence-based basis in the process of policy de- sign, the implementation effect is not ideal due to the deviation of decision makers’ subjective cognition of events or issues, the lack of knowledge, and the change of environment or issues. The governments of most countries have performed poorly in the face of COVID-19 pandemic, but the Chinese government has formulated a series of highly resilient policies for work resumption in a short time. In the face of severe uncertainty in the future, it has played a steady performance and played an important role in economic and social recovery. At the peak of the epidemic in the first half of 2020, China’s economy and society achieved a high-quality recovery, which provid- ed a rare opportunity to study policy resilience. Therefore, from the perspective of resilience, this study makes a detailed analysis of the content and characteristics of China’s policies of promoting work resumption. 3. Constructing the analysis model of policy This study analyzes policies of promoting work resumption through PMC-index model, which has several advantages. First, it can analyze the internal consistency of policy to reflect the degree of adaptability and stability of policy. Second, the advan- tages and disadvantages of individual policies can be analyzed. The overall evaluation of policies can be carried out through PMC index, and PMC surface intuitively and 59 vividly reflects the advantages and disadvantages of policies from a multi-dimension- al perspective in the images, which can be used as a basis to optimize policies and improve the resilience of policies. The application of PMC-index model includes the following four steps: (1) classification of variables and identification of parameters; (2) establishing multiple input-output tables; (3) measurement of PMC index; and (4) building PMC surfaces. 3.1 Samples and sorting of policies Policies of promoting work resumption studied in this paper come from the offi- cial websites of the central government of China and the governments of all provinc- es and municipalities directly under the central government. The time range of the selection is from January 1, 2020 to June 30, 2020. Irrelevant documents such as meet- ing minutes and receipts were filtered out, and 342 representative policy documents were selected. These included 7 policy documents issued by the State Council and the central government, 73 policy documents issued by national functional departments, and 262 policy documents issued by regional governments. These 342 documents are sorted out in detail according to policy types (see Table 1). Table 1: Types of policies for promoting work resumption Policy Types Details Quantity Proportion Restraint strength Operable strength Planning (160) Statute 1 0.3% Strong Weak Plan 2 0.6% Medium strong Weak Opinion 52 15.2% Medium strong Medium weak Measure 105 30.7% Medium strong Weak Implementing (182) Notice 180 52.6% Medium weak Medium strong Regulation 2 0.6% Medium strong Medium strong Total 342 100% - - Source: Authors’ elaboration 3.2 Comparative analysis of policy types From the perspective of policy implementation, this paper further divides pol- icy types into planning and implementing policies. Planning policy means that it only puts forward the ultimate goal and planning path, and lacks the implementable guidance of policies. The implementing policy elaborates the content of each mea- sure in the policy document, and specifies the specific implementation methods and principles of each measure (Du, Yuan and Gao, 2019, p. 102). By comparing the two main types of policies for resumption of work and production, we found that the im- plementing policies accounts for 53.2%, which are more operational and restrictive, reflecting the strong intervention of government in promoting work resumption. The government hoped to strengthen the guidance and control of work resumption by policies, so as to promote economic and social recovery. 60 3.3 Variables Before establishing the PMC-index model of policy, this paper first needs to de- termine the relevant variables of the policy. By sorting out 342 policies of promoting work resumption, we use text mining method, ROSTCM6.0 and UCINET tool to ex- tract key words, establish social network and calculate centrality. The detailed steps are shown in Figure 1. Policy text (Document set) Pretreatment (Segmentation word,Organize documents,Extracting feature words) Text mining analysis （Centrality analysis，Word frequency analysis，Keywords network analysis） Document intermediate form （Effective word frequency） Evaluation index of policy resilience Figure 1: The process of text mining Source: Authors’ elaboration 3.3.1 Word frequency analysis 342 policy texts are imported into the text mining database of ROSTCM6.0 soft- ware to form a document set for text word segmentation. Further, the word frequency statistics of the document set are carried out, and the results are sorted according to the frequency. Words like ‘support’, ‘development’ and ‘key’ that have no impact on the construction of evaluation indicators but have a high frequency were removed. Afterwards, we summarized effective high-frequency vocabulary. The top 60 words are listed in Table 2. Table 2: Effective words and quantities Words Quantity Words Quantity Words Quantity Enterprise 11791 SME 1084 Start a business 686 Pandemic 6529 Platform 1032 Demand 675 Service 4887 Security 1018 Guide 663 Policy 2546 Difficulty 1002 Science and technology 642 Work resumption 2206 Economics 1001 Emergency management 637 Guarantee 2184 Transport 908 Hygiene 618 Obtain employment 1842 Technology 894 Examine and approve 605 Staff 1732 Consumption 875 Human resources 604 61 Words Quantity Words Quantity Words Quantity Finance 1706 Guidance 852 Traffic 601 Project 1616 Supervise 848 Novel 586 Loan 1556 Healthy 840 Supply 565 Fund 1518 Subsidy 830 Informationize 527 Management 1397 Agriculture 801 Business 527 Sociology 1394 Industry 779 Travel 464 Insurance 1357 Apply 776 Logistics 454 Resources 1224 Innovate 766 Law 451 Material 1207 Mechanism 746 Passageway 432 Bank 1153 Pneumonia 739 Coronavirus 421 Financing 1125 Medical care 710 Graduate 400 Market 1108 Epidemic prevention 703 Green 390 3.3.2 Keywords network analysis In this study, the policy keywords are processed by ROSTCM6.0 software to get the policy keyword network (see Figure 2). The size of the circle in the figure indi- cates the frequency of keywords in the policies. The length of the line connecting keywords represents the tightness between keywords, reflects the text semantics and forms a social relationship network diagram. The social network diagram of the policy can visually reflect the core structure and radiation degree of the policy and provide a basis for determining the primary and secondary variables of PMC index. 3.3.3 Centrality analysis Through the Net-Degree function in UCINET software, the values of ‘Centrality’ and ‘Network Centralization’ of the keyword network of policies of promoting work resumption are obtained, and some effective words required to establish the evalua- tion system were selected, as shown in Table 3. Table 3: Some effective words and centrality Words Degree Words Degree Words Degree Enterprise 46537 Market 29029 Public 22834 Pandemic 46422 Meet an emergency 28743 Insurance 22797 Service 44115 Special 28539 Logistics 22594 Guarantee 43837 Apply 28421 Traffic 22476 Policy 42491 Perfect 28223 Hygiene 22108 Return to work 37889 Supervise 27699 Obtain employment 20855 Pneumonia 37594 Security 27258 Minor enterprises 20152 Management 35781 New type 27156 Informationize 20120 Continuation on page 63 62 Fi gu re 2 : K ey w or d ne tw or k So ur ce : A ut ho rs ’ e la bo ra tio n 63 Words Degree Words Degree Words Degree Capital 35463 Epidemic prevention 26807 Virus 20046 Personnel 34358 Innovate 26439 Coronal 19945 Platform 33738 Technology 26072 Industry 19255 Project 33359 Resources 25942 Investment 18873 Material 33111 Reduction 25875 Start a business 18636 Mechanism 32862 Green 25401 System 18242 Guide 31871 Finance 24728 Environment 17174 Healthy 31468 Medical care 24665 Unemployment 15991 Demand 30339 Examine and approve 24525 Support 15493 Sociology 29584 Novel coronavirus 23490 Operate 15124 Transport 29223 Economics 23347 Staff 14532 Finance 29136 Bank 22888 Science 14248 Note: network centralization = 23.42% Source: Authors’ elaboration The centrality value can represent the position of a keyword in the whole key- word network. The higher the centrality of a keyword, the higher its position in the network, and the more likely it is to become an indicator of research policy. For ex- ample, the word ‘pandemic’ ranks second in the overall centrality ranking, which is also the background of the research topic, so it is also in a more important position in the keyword table and keyword network diagram. 3.3.4 Classification of variables and identification of parameters Referring to the idea of constructing the index system by Ruiz Estrada (2011, p. 527), and combined with the analysis of high-frequency words and keywords, this paper combines the characteristics of the policies on promoting work resumption with the PMC- index model to construct the PMC evaluation index system. The indi- cator system includes 10 primary indicators and 50 secondary indicators (see Table 4). Table 4: Variable setting NO. Primary variable NO. Secondary variable NO. Secondary variable X1 Nature of policy X1:1 Forecast X1:2 Supervise X1:3 Proposal X1:4 Describe X1:5 Guide X2 Policy function X2:1 Market regulation X2:2 Business assistance X2:3 Promoting employment X2:4 Encourage entrepreneurship X2:5 Perfect mechanism X2:6 Strengthen supervision X2:7 Ensure safety X2:8 Epidemic prevention guidance Table 3 Continuation on page 64 64 NO. Primary variable NO. Secondary variable NO. Secondary variable X3 Policy perspective X3:1 Macroscopic X3:2 Microcosmic X4 Effective time X4:1 Temporary (t≤6 months) X4:2 Short-term (6 months 1 0. 00 0) P6 Po lic y s ug ge st io ns o n pr ev en tin g an d co nt ro lli ng C OV ID -1 9 pa nd em ic an d su pp or tin g sm al l a nd m ic ro e nt er pr is es to o ve rc om e di ffi cu lti es . Pr ov in ci al e pi de m ic p re ve nt io n an d co nt ro l ( 20 20 ) N o. 9 Zh ej ia ng p ro vin ce (1 .0 00 ≤ k ≤ 9 .9 99 ) P7 Op in io ns o n se ve ra l fi sc al a nd ta x po lic ie s on o ve ra ll su pp or t f or C OV ID -1 9 pa nd em ic p re ve nt io n an d co nt ro l a nd e nt er pr is es w or k re su m pt io n. He i C ai B an (2 02 0) N o. 9 He ilo ng jia ng p ro vin ce (5 00 ≤ k ≤ 9 99 ) P8 So m e m ea su re s on s up po rti ng th e de ve lo pm en t o f r ea l e co no m y. Yu n Zh en g Fa (2 02 0) N o. 1 1 Yu nn an p ro vin ce (1 00 ≤ k ≤ 49 9) P9 Si xt ee n m ea su re s to ta ck le th e CO VI D- 19 p an de m ic an d su pp or t S M E’s re su m pt io n of w or k an d he al th y d ev el op m en t. Xi n Zh en g Ba n Fa (2 02 0) N o. 7 Xi nj ia ng U yg ur Au to no m ou s Re gi on (1 0 ≤ k ≤ 99 ) No te : k = c um ul at ive n um be r o f c on fir m ed p at ie nt s So ur ce : A ut ho rs ’ e la bo ra tio n 68 Table 10: PMC index summary P1 P2 P3 P4 P5 P6 P7 P8 P9 Mean (X1) Nature of policy 0.6 0.4 0.4 0.6 0.8 0.8 0.6 0.4 0.6 0.578 (X2) Policy function 0.625 0.875 0.5 0.875 0.75 0.5 0.25 0.625 0.875 0.653 (X3) Policy perspective 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 (X4) Effective time 0.5 0.5 0.5 0.75 0.5 0.25 0.25 0.5 0.5 0.472 (X5) Issuing authority 0.4 0.4 0.2 0.4 0.2 0.2 0.2 0.2 0.2 0.267 (X6) Policy field 0.4 0.7 0.5 0.8 0.5 0.4 0.6 0.8 0.8 0.611 (X7) Guarantee incentive 0.429 0.714 0.571 1 0.857 0.429 0.429 1 0.714 0.683 (X8) Policy system 1 1 1 1 0.667 0.667 0.667 0.667 0.667 0.815 (X9) Policy receptor 0.6 0.8 0.8 0.8 0.6 0.8 0.8 0.8 0.6 0.733 (X10) Policy disclosure 1 1 1 1 1 1 1 1 1 1 PMC Index 6.054 6.889 5.971 7.725 6.374 5.545 5.296 6.492 6.456 6.311 Grade Good Good Good Excellent Good Good Good Good Good Figure 3: Depression index and PMC index Source: Authors’ elaboration This paper introduces the policy cobweb graph to compare with PMC surface (see Figure 4). The cobweb graph can intuitively display the scores of policy primary indicators, and can also compare policies horizontally. Although the cobweb graph is not three-dimensional and detailed as PMC surface, it provides another research idea for evaluation policy when only primary indicators need to be analyzed. However, compared with the policy cobweb graph, the surface graph can intuitively reflect the index advantages and disadvantages of a single policy and the depression degree of the policy, which is conducive to the in-depth analysis of a single policy. 69 Figure 4: Policy cobweb graph Source: Authors’ elaboration 4.3 Draw PMC surface graph According to the calculation results of PMC index, we gather 9 primary indicators into Matrix of 3×3, and then draw the PMC surface in the three-dimensional coor- dinate system according to the corresponding coordinate positions of each primary indicator. This article only shows the PMC surface diagram of policies P4 and P7 (see Figure 5 and Figure 6). On the PMC surface, the areas of each shading represent different values. The concave areas of the surface have relatively low scores, and the convex areas of the surface have relatively high scores. Figure 5: PMC surface of policy 4 70 Figure 6: PMC surface of policy 7 4.4 Analysis of policy evaluation results Based on the data results of the above policy analysis, we can analyze and evaluate the policies from two aspects. One is horizontal evaluation, it compares and evaluates various policies, or compares and analyzes the policies to be evaluated with the mean value. The other is vertical evaluation, it analyzes the advantages and disadvantages of individual policies with the help of depression degree and surface graph, and puts forward targeted suggestions. From the first point of view, the score ranking of PMC index is P4 > P2 > P8 > P9 > P5 > P1 > P3 > P6 > P7. As the policies of promoting work resumption are emergency management policies, it tends to be temporary and short-term in effective time, so scores are concentrated at 0.5. In the index policy nature X1, the scores of policies P1, P4, P5, P6, P7 and P9 are higher than the average, accounting for 66.7%, indicating that more attention is paid to the form of policy support. As for policy receptor X9, the scores of P2, P3, P4, P6, P7 and P8 are higher than the average level, indicating that the coverage objects of policy regulation are considered comprehensively in this kind of policy formulation, so as to expand the penetration impact of the policy, which is beneficial to ensure the stable effect of the policy in a highly uncertain environment. In the guarantee incentive X7, the scores of P2, P4, P5, P8 and P9 are higher than the average level, indicating the importance of incentive measures for promoting work resumption in policy formulation. In terms of policy function X2, issuing authority X5, policy field X6 and policy system X8, more than 50% of the policies scored lower than the mean value in these four primary indicators. Therefore, from the overall lev- el of policy evaluation, the policy of promoting work resumption can be improved in four aspects: policy function, issuing authority, policy field and policy system. Among them, the highest PMC index is P4, with a score of 7.725 as an excellent level policy, which fully shows that the hardest hit areas attach great importance to 71 the resumption of work and production. The lowest score of PMC index of P7 among the policies to be evaluated is 5.296, indicating that the resilience of the policy has a certain room for improvement. The scores of policy function X2, effective time X4 and guarantee incentive X7 are significantly lower than the average level, and the score gap is more than 0.2. The scores of some primary indicators are also lower than the means to varying degrees, accounting for 60%. In terms of policy function X2, P7 only involves promoting employment and ensuring security. The score of primary index X2 is 0.25 and less than the average score of 0.403. Therefore, attention should be paid to expanding the scope of policy support. In terms of effective time X4, it is found that the policy only involves the role within 6 months and has no long-term plan, so it is not specific and forward-looking. In terms of guarantee incentive X7, the policy only involves project support, tax preference and financial support. The guar- antee and incentive measures are not comprehensive enough. Policy makers should pay attention to the improvement of this aspect and ensure the effective implemen- tation of policies. Through the analysis of P6 policy, to improve the PMC index, we need to focus on the promotion in the order of X2-X7-X4, but there is a linkage effect between the indicators, so the order is not unique. The specific implementation pro- cess should be combined with the specific situation. According to the depression index of the policy and the PMC surface graph of the policy, we can also evaluate policies vertically. According to Figure 3, the depres- sion index can be divided into three levels: low depression index (0.1–3); acceptable depression index (3.1–4); high depression index (4.1–5). Among them, P4 is the low depression index, P1, P2, P5, P8 and P9 are the acceptable depression index, and P3, P6 and P7 are the high depression index. As shown in Figure 3, it can be observed that the depression index is inversely proportional to the PMC index. The order of depression degree of the nine policies from strong to weak is P7-P6-P3-P8-P1-P5-P9- P2-P4. Among the nine policies, P7 has the highest depression index. Combined with the PMC surface graph of P7 in figure 5, P7 has a high depression in four primary indicators: policy function X2, effective time X4, issuing authority X5 and guarantee incentive X7. It can be seen from the policy text that the policy function X2 only involves promoting employment and ensuring safety. Policy makers can consider expanding the function of the policy from market regulation, business assistance, encouraging entrepreneurship, perfect mechanism, strengthening supervision or ep- idemic prevention guidance, so as to achieve the ultimate goal of helping enterprises with epidemic prevention and normal operation. In terms of X4 effective time, only six months’ opinions are involved without long-term deployment. Therefore, some forward-looking opinions and suggestions can be put forward to make the policy play the role of long-term coherence. Since the policy is issued separately by the Heilongjiang Provincial Department of finance, the score of X5 is low. In order to give full play to the linkage effect of the policy, policies could be formulated jointly with other government functional departments. In terms of X7 guarantee incentive, it includes project support, tax preference and financial support. It aims to reduce 72 the operating pressure of enterprises by providing financial and tax support. It does not provide incentive and guarantee measures such as law, resources, approval and platform services. The government should comprehensively use incentive measures according to the actual situation to ensure that the policy has strong resilience in the implementation process. Therefore, taking P7 as an example, in order to improve pol- icy resilience, the policy optimization path is X5-X2-X4-X7, which is different from the first idea. The policy improvement path is not unique and should be determined in combination with the specific situation. 5. Conclusion and implications Based on the analysis of empirical data, several conclusions can be drawn. First, from the perspective of resilience, this paper deeply analyzes the content and element characteristics of China’s policies of promoting work resumption. (1) The policies not only considered the industries which were seriously affected by COVID-19 pandemic, but also paid close attention to the stable operation of medical treatment, insurance and other fields in supporting the work resumption. (2) The government has effectively combined various policy tools, using a variety of policy tools such as market regula- tion, business assistance and encouraging entrepreneurship to promote the resumption of work and production. This also helps to prevent the outbreak of the epidemic again by strengthening supervision and epidemic prevention guidance. The United States issued ‘Guidelines for opening up America’ on April 26, 2020, focusing on promoting work resumption by regions and stages. However, at this time, the COVID-19 pan- demic was not controlled, and there was no scientific protection, strict monitoring and management for the work resumption, resulting in repeated rebound of the COVID-19 pandemic and hindering the work resumption. (3) The government ensures the im- plementation of policies in terms of law, taxation, funds and services. For example, in order to solve the contradiction between the rework of employees across provinces and the inconsistency of pandemic prevention policies among provinces, the governments of Zhejiang Province and Fujian Province, through consultation, have cooperated to arrange special vehicles to pick up and transport employees in key positions to return to work. Similar to China, Singapore supports the effective implementation of poli- cies by means of employment training, issuing shopping vouchers, increasing com- munity development subsidies and providing one-time financial subsidies for public health prevention clinics. (4) The Chinese government not only makes policies from the macro and micro policy perspectives, but also combines short-term and long-term policies to provide comprehensive guidance for macro strategic planning and specific implementation. Secondly, the evaluation of 9 randomly selected policies shows that there are 1 ex- cellent grade policy and 8 good grade policies. The results show that China’s policies of promoting work resumption have good resilience. (1) The policies of promoting work resumption made by the superior government and the subordinate government exhibit 73 excellent consistency, which shows that the subordinate government strongly trusts and supports the superior government. Also, the subordinate government itself has excellent policy implementation ability. (2) The policies of promoting work resumption formulated by different regions have good consistency. In this way, governments can ensure the synchronous recovery of industrial chain and supply chain, and avoid con- flicts caused by different recovery processes between regions. This shows that when solving the same problem, the governments of different regions have made high re- silience policies through mutual learning and communication. The United States, Ita- ly, Sweden and other countries have highly decentralized their powers in promoting economic and social recovery, while the power of control and coordination has been weakened. Due to the imbalance in the severity of the COVID-19 pandemic, the level of economic development and the speed of work resumption among regions, the con- flicts between central and regional governments as well as between different regional governments have been intensified. Therefore, the macro-control policies issued by the state could not be implemented, which damaged the speed and effect of work resump- tion. Although China has many levels of government management, it implements uni- fied dispatching by the central government, and has set up joint prevention and control mechanisms at all levels to promote cross sectoral cooperation. South Korea and Singa- pore have adopted similar approaches to ensure strong policy resilience. South Korea has established a central disaster and security strategy headquarters led by the prime minister. They set up local disaster and security strategy headquarters in each region, which are mainly responsible for the local government. Singapore has set up an inter- departmental working group composed of eight government departments, with the deputy prime minister as the adviser and the ministers of health and National Devel- opment co-chairing the work. These cases show that the state’s unified leadership and rapid decision-making, and the regional governments’ mutual coordination and rapid action can help the national and regional governments make and implement strong resilient policies which promote very efficient resumption of work and production. The contribution of the research mainly includes three aspects. Firstly, from the perspective of resilience, this study deeply studies the content and characteristics of China’s policies of promoting work resumption during the COVID-19 pandemic. Sec- ondly, this study introduces the PMC-index model to analyze policies of promoting work resumption from the perspective of resilience for the first time, so as to pro- vide reference for future policy evaluation and resilience related research. Finally, this study puts forward a new perspective and method for the analysis of policies of work resumption. Before the implementation of the policy, through text mining and quan- titative analysis, it can save time and resources to the greatest extent, and make the evaluation results objective, scientific and traceable. Therefore, targeted, specific and objective suggestions are put forward to provide reference for policy makers to formu- late strong resilient policies in a short time and highly uncertain environment. Based on the research results and comprehensive analysis, this paper provides prac- tical implications. First, after the impact of the crisis, the market regulation mechanism 74 is slow and often needs government intervention. Governments should fully realize the important role of policy resilience in economic health, high-quality and sustain- able development, and strengthen the resilience thinking of policy design. Effective benign interaction mechanisms should be established between national and regional governments, between regions seriously and lightly affected by the epidemic, and be- tween regions with good and poor economic and social recovery. According to the characteristics of different tasks, the national system should shift or delegate the deci- sion-making power upward, and establish a coordination mechanism for resumption of work and production between governments at different levels. The state guides and supervises regional policies, and the region builds trust in the state and gives timely feedback. The governments further evaluate and revise policies according to the imple- mentation effect of policies and regional feedback. Avoiding conflict, mutual learning and guidance among regional governments can improve the government’s response speed, realize the coordinated development of the policies of work resumption, and enhance the policy resilience. Second, the policies issued by a single functional depart- ment are one-sided and limited, so multiple departments should be encouraged to co- operate to introduce the policies of work resumption. The severely divided functional departments need to establish institutionalized or procedural arrangements, make full use of the information technology platform, build a real-time interactive mechanism for the exchange and communication of work resumption policies, increase the linkage of policies, and finally form an efficient policy public service system. Third, the gov- ernment can improve policy resilience from two policy design perspectives: The first perspective is to increase the proportion of implementation policies, avoid the number of planning policies to exceed implementation policies, and ensure the enforceability of policies. The second perspective is the combination of long-term and short-term policies. The long-term policy can clarify the overall direction of efforts to stimulate and promote social recovery and ensure the stability of policy effect. The short-term policy can avoid falling into the trap of path dependence, which helps to continuously learn and improve the policy according to the monitored and feedback resumption process and the effect of policy implementation, so as to shape the flexibility of the policy. Finally, the government can improve policy resilience in the content of policy design. There are structural uncertainties in the resumption of work and high cognitive uncertainties of policy makers. In order to ensure high policy resilience, policymakers need to combine multiple policy tools to match the actual situation of the country or region. At the same time, policy makers should predict the difficulties that employees and enterprises may encounter in the process of work resumption, and formulate cor- responding support and incentive measures to ensure that the policies can be effective- ly implemented. The policy resilience measurement model constructed in this study takes China’s policies of work resumption as a sample, and does not involve other countries and different types of policies. Future research can conduct comparative research on more countries and types of policies. 75 References: 1. Abdulkareem, M., Elkadi, H. and Breane, M., ‘From Engineering to Evolutionary, an Overarching Approach in Identifying the Resilience of Urban Design to Flood’, 2018, International Journal of Disaster Risk Reduction, vol. 28, no. 1, pp. 176–190. 2. 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