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1、Howei Wu|Bin Xu|Feida Zhang|Ruoshi Li|Wei WuChina Europe International Business School CEIBS China and the World Research Area2023 China Business ReportOn Business Performance and Operations of Companies in China in the New Business EnvironmentHowei Wu Bin Xu Feida Zhang Ruoshi Li Wei Wu2023 China B

2、usiness ReportOn Business Performance and Operations of Companies in Chinain the New Business EnvironmentChina Europe International Business SchoolCEIBS China and the World Research AreaCopyright 2023 All Rights ReservedTHE RESEARCH TEAM 1ACKNOWLEDGEMENT 2SECTION 1:PREFACE 3 1.1.INTRODUCTION OF RESE

3、ARCH PROJECT 4 1.2.MACROECONOMIC BACKGROUND 6SECTION 2:DESCRIPTION OF SAMPLE ENTERPRISES 9 2.1.REGISTRATION TYPES 10 2.2.REVENUE CONTRIBUTION OF BUSINESS IN CHINA 12 2.3.INDUSTRY DISTRIBUTION 14 2.4.BUSINESS SIZES 18 2.5.PRODUCT/SERVICE POSITIONING 19 2.6.CLIENT TYPES IN CHINA 20SECTION 3:ANALYSIS O

4、F COMPANY FINANCIAL PERFORMANCE 21 3.1.OVERVIEW OF CORPORATE REVENUE 22 3.2.ANALYSIS OF COMPANIES WITH SIGNIFICANT DECLINES IN REVENUE 23 3.3.PANDEMIC PREVENTION AND REVENUE DECLINE 27 3.4.CONCLUSIONS AND RECOMMENDATIONS 36TABLE OF CONTENTSSECTION 4:ANALYSIS ON THE CONFIDENCE OF COMPANIES OPERATING

5、39 IN CHINA IN THE NEW BUSINESS ENVIRONMENT 4.1.TIME SERIES ANALYSIS OF CONFIDENCE INDEX 40 4.2.THE RELATIONSHIP BETWEEN REVENUE PERFORMANCE 42 AND CONFIDENCE INDEX 4.3.SHORT-TERM CONFIDENCE IN THE MANUFACTURING 43 AND SERVICE SECTORS 4.4.MEDIUM-TERM CONFIDENCE IN THE MANUFACTURING 45 AND SERVICE SE

6、CTORS 4.5.THE RELATIONSHIP BETWEEN FIRM SIZE AND CONFIDENCE INDEX 47 4.6.CONCLUSION 48SECTION 5:IMPLICATIONS FROM INNOVATION UNDER NEW BUSINESS ENVIRONMENT 51 5.1.BUSINESS AND INDUSTRIAL CHARACTERISTICS 54 5.2.RESOURCE CONSTRAINTS 55 5.3.FUTURE EXPECTATIONS 56 5.4.CONCLUSION 58SECTION 6:CONCLUSION 5

7、9APPENDIX:QUESTIONNAIRE 631Dr.Howei Wu is Assistant Professor of Economics at CEIBS.She received her B.A.and B.S.from Tsinghua University(Taiwan,China),and M.A.and Ph.D.from Stanford University.Dr.Wu does research in macroeconomics,monetary economics,innovation,and the Chinese economy.She has publis

8、hed at the Journal of Economics Dynamics and Control and others.Before joining CEIBS,Dr.Wu taught at Shanghai University of Finance and Economics and was a member of Chinas Macroeconomic Analysis and Forecast Project Team.Dr.Bin Xu is Professor of Economics and Finance,Wu Jinglian Chair Professor in

9、 Economics at CEIBS.He received his B.A.and M.A.from Fudan University,and Ph.D.from Columbia University.Dr.Xus research focuses on issues of the global and Chinese economy.He has published extensively in both international and Chinese journals,and is author of Applying Macroeconomics(2019)and Intern

10、ational Trade(2009).Dr.Xu has worked as a consultant for International Monetary Fund(IMF)and the World Bank.Dr.Feida Zhang is Associate Professor of Accounting at CEIBS.He received his M.Phil.in Accounting from Xiamen University and Ph.D.in Accounting from Hong Kong Baptist University.Dr.Zhangs rese

11、arch focuses on accounting information,corporate governance,capital markets,CSR and corporate finance.He has published on both Chinese and international top journals including Management World,Journal of International Business Studies,Journal of Financial and Quantitative Analysis,etc.Dr.Zhang held

12、appointments at leading universities,including The University of Queensland,Murdoch University and Sun Yat-Sen University.Ruoshi Li is Research Assistant of the Department of Economics and Decision Sciences at CEIBS.She received her bachelors degree from Boston University in 2017,with major in Econo

13、mics and minor in Business Administration,and her M.A.degree in Quantitative Economics and Econometrics from Boston University in 2019.Before joining CEIBS,Ruoshi worked as an analyst in a Chinese state-owned private equity investment fund.Wei Wu is Research Assistant of the Department of Finance an

14、d Accounting at CEIBS.He received his Bachelor of Commerce(Honors Class I)degree from The University of Queensland in 2019,with major in Accounting,and his Master of Commerce degree from The University of Queensland in 2021,with major in Applied Finance.Weis research paper is currently in the Revise

15、&Resubmit phase on the journal Advances in Accounting.THE RESEARCH TEAM2ACKNOWLEDGEMENTThe China Business Survey 2022 is supported by the active participation of many CEIBS alumni and current students,the support of the Alumni Relations Department,the Information Technology Department,the Marketing

16、and Communications Department,the various program departments(DBA,EMBA,FMBA,GEMBA,HEMBA,MBA and Executive Education Programs),and the funding of the Academys research grant(project no.AG20BIC),for which the research team is deeply grateful.The research results of this project belong to the China and

17、 the World research area of China Europe International Business School.The research team is fully responsible for the documentation.3SECTION 1Preface41.1.INTRODUCTION OF RESEARCH PROJECTThe China and Europe International Business School(CEIBS)Research Team with three professors and two research assi

18、stants conducted an online survey from November 18th to November 27th 2022,receiving 1,474 unique responses in total.1,181(80.2%)survey participants work for Chinese-owned firms or firms with 50%or more Chinese ownership,and 291(19.8%)participants work for foreign-owned firms in China or firms with

19、more than 50%foreign ownership.1 According to Figure 1.1,95%of participants are CEIBS alumni or students,and 55.6%are alumni or students of EMBA programme.Figure 1.2 shows that 42.1%of participants are principal decision makers(such as CEOs/GMs/Main Owners/Main Partners/Chief Representatives),35.5%a

20、re deputy decision makers(such as VPs/Vice GMs/Directors/Assistants of GM),and the other 18.3%are senior executives of their divisions.77.1%of the participants have at least 10 years of managing experience(Figure 1.3).Moreover,we have a gender-balanced survey with 31.82%female and 67.64%male.SECTION

21、 1:PREFACE1 Foreign-ownedfirmsincludeHongKong(China),Macao(China)andTaiwan(China)companies.Chinese-ownedfirmsrefertomainlandChinacompanies.Hereinafterwewillrefertothemas“foreign-ownedfirms”or“Chinese-ownedfirms”.FIGURE 1.1.CEIBS ALUMNI Open program or CSP DBA EMBA FMBA GEMBA HEMBA MBA Not yet5The pr

22、ofessional distributions show that the survey sample is not a typical sample of enterprises operating in China,but rather reflects the situation of the enterprises of the senior executives who have study experiences in CEIBS,especially that of enterprises of more than half of the EMBA alumni and stu

23、dents.According to the class profile of CEIBS EMBA programme,the average age of participants is 41,average years of working experience is 17,and their average years of managing experience is 12.More than 95%of the participants are senior managers.CEIBS has more than 20,000 alumni,including EMBA alum

24、ni who participated the most in this survey among all alumni or students.Based on the above information,we conclude that the survey result has reference value in the sense that it largely reflects how“head companies”(the leading companies and most active ones in their respective industries)in China

25、assessed and judged the impacts of business environment and innovation on business operations.This is also confirmed by the survey results of the reported market positioning of their products and services(in Section 2.5).SECTION 1:PREFACEFIGURE 1.2.POSITION IN THE COMPANYFIGURE 1.3.YEARS OF MANAGING

26、 EXPERIENCEPrincipal decision-making roleDeputy decision making roleProject Manager/Business Development Manager/Product ManagerMarketing/Sales ExecutiveOtherHR executiveFinance ExecutiveManufacturing,Operations,Logistics or Engineering ExecutiveR&D ExecutiveMore than 20 years10-19 years5-9 yearsles

27、s than 5 years61.2.MACROECONOMIC BACKGROUNDThe macroeconomic context of this survey can be summarized by the preliminary accounting results of the Chinese economy for the fourth quarter of 2022 released by the National Bureau of Statistics.Figure 1.4 shows the year-on-year growth rates of value adde

28、d and gross domestic product(GDP)of the Chinese economy by industries in the fourth quarter of 2022,measured using 2020 as the constant price base year,i.e.,the growth rate of the fourth quarter of 2022 values over the fourth quarter of 2021 values.The data shows that the Chinese economy was negativ

29、ely impacted to some extent by the restriction of movement of people and the shutdown of some industries due to the COVID-19 epidemic,with a year-over-year growth rate of only 2.9%.The Real Estate industry experienced the largest decline(-7.2%)due to both the epidemic and policy,with the sector havi

30、ng a significant increase of 21.4%in Q1 2021.The Accommodation and Restaurants industry had the next largest decline(-5.8%).The primary industry(Agriculture,Forestry,Animal Husbandry and Fishery)rose slightly,shows a year-on-year growth rate of 4.1%.Construction and Industrial sector in the secondar

31、y industry also showed the same trend of small growth,with year-on-year growth rates of 7.0%and 2.5%,respectively.The tertiary industry(service sector),which showed signs of rebound in 2021,experienced another winter of performance,with the Real Estate industry experiencing the largest decline,turni

32、ng negative from a 21.4%year-over-year growth rate in the first quarter of 2021.In the service sector,the year-on-year growth rates of the Accommodation&Restaurants industry and Transport,Storage and Post industry also turned from positive to negative,with growth rates of-5.8%and-3.9%,respectively.T

33、he Finance and Information Transmission,Software&Information Technology Services industries have continued to grow since the first quarter of 2020,with growth rates of 5.9%and 10.0%,respectively.SECTION 1:PREFACEFIGURE 1.4.INDUSTRY GROWTH RATE OF CHINESE ECONOMY IN 4TH QUATER OF 2022(Y-O-Y)Real Esta

34、teAccommodation&RestaurantsTransport,Storage&PostWholesale&Retail TradesManufacturingIndustrial SectorGross Domestic Product(GDP)Farming,Forestry,Animal Husbandry,and FisheryRenting,Leasing Activities&Business ServicesOthersFinanceConstructionInformation Transmission,Software&Information Technology7

35、It has been more than three years since the COVID-19 epidemic spread globally in early 2020,and the development of major economies around the world,including China,has been impacted in multiple dimensions.With the full liberalization of Chinas epidemic quarantine policy by the end of 2022,the overal

36、l recovery of the Chinese economy is expected to be imminent and international trade will continue to pick up,but the recovery trajectory is heterogeneous among different industries and firms,with small and medium-sized companies in service sector having a more difficult road to recovery.SECTION 1:P

37、REFACEDATA DISPLAY:THE PRELIMINARY ACCOUNTING RESULTS OF CHINAS 4TH QUARTER GDP RELEASED BY NATIONAL BUREAU OF STATISTICS(NBS)OF 2022IndustryShare of GDPBroad ClassificationCurrent Value(Trillion yuan)Share of GDPYear-on-Year ChangePrimary Industry13.9%Farming,Forestry,Animal Husbandry,and Fishery3.

38、5110.4%4.1%Secondary Industry44.9%Construction2.647.9%7.0%Industrial Sector(Include Manufacturing)10.6831.8%2.5%Tertiary Industry41.2%Accommodation&Restaurants0.521.6%-5.8%Wholesale&Retail Trades3.199.5%0.3%Transport,Storage&Post1.283.8%-3.9%Renting,Leasing Activities&Business Services1.193.5%5.6%Re

39、al Estate1.855.5%-7.2%Others5.1115.2%5.7%Finance2.387.1%5.9%Information Transmission,Software&Information Technology1.213.6%10.0%Total100.0%Gross Domestic Product(GDP)33.55100.0%2.90%SECTION 2Description of Sample Enterprises10SECTION 2:DESCRIPTION OF SAMPLE ENTERPRISES2.1.REGISTRATION TYPES The com

40、panies in our survey sample are divided into 8 categories according to their ownership structures(see Figure 2.1).More than half of companies,specifically 54.9%,are wholly private-owned Chinese enterprises.The second-largest number is wholly foreign-owned enterprise which accounts for 16.0%.Chinese

41、State-Owned Enterprises(SOEs),which is defined as majority state-owned enterprises plus wholly state-owned enterprises,account for 9.2%(135 firms)of the whole sample.Chinese private-owned enterprise,which contains wholly private-owned enterprises and majority private-owned companies,takes up 65.5%(9

42、66 firms).Foreign firms including wholly foreign-owned and majority foreign-owned joint ventures account for 19.7%(291 firms).Among the firms with foreign ownership,top 3 regions are European Union(29.7%),United States(28.6%),and Hong Kong China(19.3%).The exact ranking is reported in Figure 2.2.FIG

43、URE 2.1.SAMPLE BY REGISTRATION TYPEWholly Private-Owned Chinese EnterpriseWholly Foreign-Owned Enterprise Mixed-Owned Chinese Enterprise II(Majority Private-Owned)Foreign Joint Venture II(Minority Foreign-Owned)Wholly State-Owned Chinese EnterpriseMixed-owned Chinese Enterprise I(Majority Sate-Owned

44、)Foreign Joint Venture I(Majority Foreign-Owned)Other11SECTION 2:DESCRIPTION OF SAMPLE ENTERPRISESFIGURE 2.2.SOURCE OF BIGGEST OWNERSHIPEuropean UnionUSAHong Kong(China)OtherJapanASEANSouth KoreaTaiwan(China)Latin AmericaAfricaAustralia and New ZealandRussiaIndiaCentral AsiaDATA DISPLAY:REGISTRATION

45、 TYPESNumberPercentWholly Private-Owned Chinese Enterprise80954.90%Wholly Foreign-Owned Enterprise23616.00%Mixed-Owned Chinese Enterprise II(Majority Private-Owned)15710.70%Foreign Joint Venture II(Minority Foreign-Owned)805.40%Wholly State-Owned Chinese Enterprise704.80%Mixed-owned Chinese Enterpri

46、se I(Majority Sate-Owned)654.40%Foreign Joint Venture I(Majority Foreign-Owned)553.70%Other20.10%Total1,474100.0%12SECTION 2:DESCRIPTION OF SAMPLE ENTERPRISES2.2.REVENUE CONTRIBUTION OF BUSINESS IN CHINA Figure 2.3 presents the revenue contribution of business-in-China.1,149 firms report 50%or more

47、revenue from business-in-China(78%),we define them as“introverted”.Firms with 50%or more revenue from overseas business are defined as“extroverted”(323 firms with a share of 22%).Among extroverted firms,there are 24 extreme cases(1.6%)where those firms only have overseas businesses and receive zero

48、revenue from business-in-China.FIGURE 2.3.REVENUE CONTRIBUTION OF BUSINESS-IN-CHINADATA DISPLAY:REVENUE CONTRIBUTION OF BUSINESS-IN-CHINANumberPercentIntroverted:Business in China accounts for more than 50%of the total revenue(N=1,149;Share=78%)100%63242.9%75%-99%37325.3%50%-74%1449.8%Extroverted:Ov

49、erseas Business accounts for more than 50%of the total revenue(N=323;Share=22%)25%-49%986.7%1%-24%17912.2%0%241.6%Not sure221.5%Total1,472100.0%13SECTION 2:DESCRIPTION OF SAMPLE ENTERPRISESFIGURE 2.4.MAIN LOCATIONS OF BUSINESS-IN-CHINAShanghaiGuangdong ProvinceJiangsu ProvinceBeijingOtherZhejiang Pr

50、ovinceShenzhenTianjinDATA DISPLAY:MAIN LOCATIONS OF BUSINESS-IN-CHINANumberPercentShanghai85519.10%Guangdong Province61113.60%Jiangsu Province58513.10%Beijing57312.80%Other56712.70%Zhejiang Province56212.60%Shenzhen47310.60%Tianjin2525.60%Total4,478100%Figure 2.4 presents firm main locations of busi

51、ness-in-China.The top 3 locations are Shanghai(19.1%),Guangdong Province(13.6%)and Beijing(12.8%).Of the firms that chose the“other”option when they were asked about where the main locations of their business in China are,a large portion of firms(217 firms)reported that they operate nationwide,while

52、 another major portion of firms(123 firms)mainly operate in eastern China.14SECTION 2:DESCRIPTION OF SAMPLE ENTERPRISES2.3.INDUSTRY DISTRIBUTIONFigure 2.5 displays the companies in our survey sample divided into three categories based on the industries they operate in.Nearly half(49.6%or 742 compani

53、es)of our sample companies operate in the service industry,while 510 companies(34.1%of our total sample)operate in the manufacturing industry.The smallest group of companies(243 companies or 16.3%of our sample)operate in both the service and manufacturing industries.FIGURE 2.5.INDUSTRY DISTRIBUTION

54、Both services and manufacturing(N=243)Manufacturing(N=510)Services(N=742)Figure 2.6 illustrates the distribution of sub-industries within the service sector of our sample companies.We have categorized the entire service industry into 11 sub-industries.The top three sub-industries are Financial Servi

55、ces,Professional Services&Business Services,and Wholesale&Retail.Specifically,there are 176 Financial Services companies,representing 17.9%of our entire sample,followed closely by 175 Professional Services&Business Services companies,which make up 17.8%of our sample.In the Wholesale&Retail sub-indus

56、try,there are 115 companies accounting for 11.7%of our sample.The fewest companies in our sample(35 companies)belong to the Catering,Accommodation&Travel sub-industry,accounting for only 3.6%of the total companies in our sample.15SECTION 2:DESCRIPTION OF SAMPLE ENTERPRISESFIGURE 2.6.INDUSTRY DISTRIB

57、UTION OF SERVICE SECTORFinancial Services(N=176)Professional Services&Business Services(N=175)Wholesale&Retail(N=115)Other services(please specify):(N=110)Health Care,Medical&Sanitation(N=100)Telecommunications&Information Services(N=81)Real Estate Services(Note:Real estate construction belongs to m

58、anufacturing)(N=68)Logistics,Transportation&Storage(N=46)Culture,Entertainment&Recreation(N=43)Education(N=36)Catering,Accommodation&Travel(N=35)DATA DISPLAY:SERVICE SUB-INDUSTRY DISTRIBUTIONNumberPercentFinancial Services17617.9%Professional Services&Business Services17517.8%Wholesale&Retail11511.7

59、%Other services(please specify)11011.2%Health Care,Medical&Sanitation10010.2%Telecommunications&Information Services818.2%Real Estate Services(Note:Real estate construction belongs to manufacturing)686.9%Logistics,Transportation&Storage464.7%Culture,Entertainment&Recreation434.4%Education363.7%Cater

60、ing,Accommodation&Travel353.6%Total985100.0%16SECTION 2:DESCRIPTION OF SAMPLE ENTERPRISESFigure 2.7 illustrates the distribution of sub-industries within the manufacturing sector of the surveyed companies.There are 12 sub-industries in total in the manufacturing industry,with the top three sub-indus

61、tries being Pharmaceutical Products&Medical Devices,Machinery&Equipment,and Consumer Products.Specifically,there are 129 companies operating in the Pharmaceutical Products and Medical Devices sub-industry,representing 17.1%of our sample companies.The second largest group of manufacturing companies(1

62、05 companies)operate in the Machinery and Equipment sub-industry,accounting for 13.9%of our entire sample.A similar 13.7%of our surveyed companies are Consumer Products companies,with 103 of them.The fewest sample companies run their businesses in the Paper-making&Printing sub-industry,with only 8 o

63、f them,making up just 1.1%of our surveyed sample.FIGURE 2.7.INDUSTRY DISTRIBUTION OF MANUFACTURING SECTORPharmaceutical Products&Medical Devices(N=129)Machinery&Equipment(N-105)Consumer Products(N=103)Communications&Electronic Products(N=89)Civil Engineering and Construction(N=80)Chemical&Energy Pro

64、ducts(N=71)Automobile&Transportation Vehicles(N=59)Other manufacturing(please specify):(N=49)Agriculture,Forestry,Husbandry,Fishing&Mining(N=25)Metal&Non-Metallic Products(N=20)Public Utilities(such as water,electricity and gas supply)(N=15)Papermaking&Printing(N=8)17SECTION 2:DESCRIPTION OF SAMPLE

65、ENTERPRISESDATA DISPLAY:INDUSTRY DISTRIBUTION OF MANUFACTURING SECTORNumberPercentPharmaceutical Products&Medical Devices12917.1%Machinery&Equipment10513.9%Consumer Products10313.7%Communications&Electronic Products8911.8%Civil Engineering and Construction8010.6%Chemical&Energy Products719.4%Automob

66、ile&Transportation Vehicles597.8%Other manufacturing(please specify):496.5%Agriculture,Forestry,Husbandry,Fishing&Mining253.3%Metal&Non-Metallic Products202.7%Public Utilities(such as water,electricity and gas supply)152.0%Paper-making&Printing81.1%Total753100.0%18SECTION 2:DESCRIPTION OF SAMPLE ENT

67、ERPRISES2.4.BUSINESS SIZESFigure 2.8 presents the distribution of firm size.We measure firm size by number of employees in China,and divided firms into 9 subgroups.FIGURE 2.8.NUMBER OF EMPLOYEES IN CHINAGiantExtra-LargeLargeMedium-to-LargeMediumSmall-to-MediumSmallExtra-SmallMicroDATA DISPLAY:FIRM S

68、IZE(NUMBER OF EMPLOYEES IN CHINA)Number of EmployeesNumberPercentGiant50,000 or above714.8%Extra-Large10,000 to 49,9991459.8%Large5,000 to 9,9991107.5%Medium-to-Large2,000 to 4,9991459.8%Medium1,000 to 1,9991308.8%Small-to-Medium300 to 99933923.0%Small50 to 29935524.1%Extra-Small10 to 4914810.0%Micr

69、o0 to 9312.1%Total1,474100.0%19SECTION 2:DESCRIPTION OF SAMPLE ENTERPRISESFIGURE 2.9.TARGET POSITION DISTRIBUTIONBoth high-end&mid-end(N=503)High-end(N=380)All range from low,middle to high(N=291)Mid-end(N=173)Both mid-end&low-end(N=88)Not sure(N=44)Low-end(N=12)Both high-end&low-end(N=4)2.5.PRODUCT

70、/SERVICE POSITIONINGFigure 2.9 displays the distribution of our sample companies target positions.Our sample is distributed across 8 different types of target positions.The top three target positions are high-end&mid-end,high-end,and all ranges from low,middle to high target positions.Specifically,5

71、03 companies consider themselves targeting both high-end&mid-end markets,representing 33.6%of our surveyed sample.The next biggest group consists of 380 high-end companies,which represent 25.4%of our sample.291 companies position themselves in all market segments from low-,middle-to high-end markets

72、,accounting for 19.5%of our sample companies.DATA DISPLAY:TARGET POSITION DISTRIBUTIONNumberPercentBoth high-end&mid-end50333.60%High-end38025.40%All range from low,middle to high29119.50%Mid-end17311.60%Both mid-end&low-end885.90%Not sure442.90%Low-end120.80%Both high-end&low-end40.30%Total1,495100

73、.0%20SECTION 2:DESCRIPTION OF SAMPLE ENTERPRISES2.6.CLIENT TYPES IN CHINAFigure 2.10 presents the companies in our survey sample categorized into 5 groups based on the types of customers they serve.The top three customer types are companies/organizations(B2B),both individual(B2C)and companies/organi

74、zations(B2B),and individual(B2C)customers.Among our survey sample,790 companies,accounting for more than half(52.1%)of the sample,serve companies/organizations(B2B)customers.The second largest group of companies(486 companies,representing 32.0%of the entire sample)serve both individual(B2C)and compa

75、nies/organizations(B2B)customers.The third largest group(199 companies,about 13.1%of the sample)serve individual(B2C)customers.FIGURE 2.10.CUSTOMER TYPE DISTRIBUTIONCompanies/Organizations(B2B)(N=790)Both individuals(B2C)and companies/organizations(B2B)(N=486)Individuals(B2C)(N=199)No customers in C

76、hina(N=29)Other(please specify):(N=13)DATA DISPLAY:CUSTOMER TYPE DISTRIBUTIONNumberPercentCompanies/Organizations(B2B)79052.1%Both individuals(B2C)and companies/organizations(B2B)48632.0%Individuals(B2C)19913.1%No customers in China291.9%Other(please specify):130.9%Total1,517100.0%SECTION 3Analysis

77、of Company Financial PerformanceIn November 2022,China Europe International Business School(CEIBS)conducted an online survey regarding the performance and operation of companies in China under the new business environment.Most of our survey participants are CEIBS alumni working in different industri

78、es,and we received 1,474 valid responses.Hence,we believe that the results of this survey have valuable implications to the Chinese economy in 2023.This report is going to analyze the 2022 financial performance of our sample firms,with more attention paid to those experiencing significant revenue de

79、clines.22SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORMANCE3.1.OVERVIEW OF CORPORATE REVENUEThe revenue of a company paints a full picture of its production activities,market demand,and business environment during a year.Thus,using company revenue as a basis for analysis helps to conduct further in

80、vestigation.Figure 3.1 shows the respondents changes in revenue in 2022 compared with 2021.The strict COVID-19 pandemic prevention and control policies implemented in Q2 2022 gave rise to a widespread negative market sentiment in China,but our survey shows that this negativity did not spread to all

81、areas of the market.The proportion of companies with a revenue decrease is not overwhelmingly higher than that of those with a revenue increase(40.6%vs.35.8%).The proportion of respondents in each revenue-change range does not monotonically change with the range in either the revenue-increasing grou

82、p or the revenue-decreasing group.Therefore,we believe that the proportion of respondents in each range is random.In this survey,286 respondents(20.3%of the total)reported their companys revenue as unchanged from the previous year;230 respondents(16.3%of the total)reported a revenue decline of 10%-2

83、4%(the largest group of revenue-decreasing companies);and 190 respondents(13.5%of the total)reported a revenue increase of 10%-24%(the largest group of revenue-increasing companies).It is worth noting that a whopping 20%of companies experienced a revenue decline of 25%or more,and 7.2%reported a decl

84、ine of 50%or more.In view of public concerns about the risk of economic downturn and resilience,the following analyses will focus on the companies whose revenue has declined by 25%or more.FIGURE 3.1.CHANGES IN REVENUE IN 2022Decrease 50%or more7%Decrease 25%-49%13%Decrease 10%-24%16%Decrease 2%-9%6%

85、Basically unchanged(a change of less than 2%)20%Increase 2%-9%11%Increase 10%-24%14%Increase 25%or more13%23SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORMANCE3.2.ANALYSIS OF COMPANIES WITH SIGNIFICANT DECLINES IN REVENUEThis section focuses on the companies that reported a significant decline in re

86、venue.As revenue can be volatile,it is possible for a companys revenue to decline during a good economic year,which introduces bias to our analysis.To alleviate the impact of bias,we focus on the companies that report a significant decline in revenue,namely the companies whose revenue declined by 25

87、%or more from 2021 to 2022.These companies consist of those who chose“Fell by 25%-49%”or“Fell by 50%or more”when answering Q11 in the survey,which asked about their 2022 revenue compared with 2021.Figure 3.2 shows the proportion of companies with a significant revenue decline in each category.To fac

88、ilitate comparison,the five classification criteria(industry,ownership,product/service positioning,customer type,and corporate size)are shown on the horizontal axis,with a shared vertical axis.The companies are classified in terms of industry type(service,manufacturing,and dual-industry companies(th

89、ose involved in both service and manufacturing);ownership(foreign-owned,private,and state-owned companies);product/service positioning(high-end,mid-range,low-end,and mixed-strategy companies(those servicing high-end,mid-range,and low-end markets simultaneously);customer type(B2C companies(those serv

90、icing individual customers)and B2B companies(those servicing business customers);and size(small,medium-sized,and large companies).The number of companies in each category is indicated in parentheses(N=x).There are variations in the total numbers of companies across different categories because some

91、respondents chose“Other(please specify)”and“Not sure”options.The vertical axis displays the percentage of companies whose revenue declined by 25%or more,calculated by dividing the number of such companies in a category by the total number of companies in that category and multiplying the result by 1

92、00%.The largest proportion of companies in each group is marked in orange,the middle proportion in blue,and the smallest proportion in gray.In terms of industry type,the service industry has the highest proportion of companies with a significant decline in revenue(21.7%),followed by the dual-industr

93、y category(19.6%).The manufacturing industry has the lowest proportion(14.9%).If we consider all revenue change ranges(not just revenue decline ranges),the service industry shows negative revenue growth(-6.2%),while the manufacturing and dual-industry categories show positive growth,with manufacturi

94、ng exhibiting higher growth(2.6%)and the dual-industry category exhibiting lower growth(0.3%).This reflects the widespread impact of pandemic prevention and control policies on Chinas economy in Q2 2022,as the impact of the strict control measures in Shanghai spread gradually throughout East China a

95、nd thereafter throughout the entire economy.The restrictions on the movement of people crippled the service industry but had only limited impact on the manufacturing industry.The Shanghai Municipal Peoples Government promptly established a Work Resumption Whitelist system for the resumption of work

96、and production after SARS-CoV-2 was brought under control in Q2.The first batch of companies on the list were mostly manufacturers,comprising those involved in manufacturing integrated circuits,automobiles,and equipment.This stopped the revenue declines in the manufacturing industry and kickstarted

97、an early recovery.The recovery of the service industry came later,as it received less policy support.However,the decline in the revenue of service companies that are also involved in manufacturing may have been mitigated by the overall rebound in the revenues of manufacturing companies.24In terms of

98、 ownership structure,the proportion of companies with a significant revenue decline is the highest among private companies(21.5%),followed by state-owned companies who have a similar percentage(19.3%).Foreign-owned companies comprise the lowest proportion of revenue-declined companies(9.7%).Such pat

99、tern clearly presents foreign-owned companies resistance against the impact of COVID-19.Due to the scattered distribution of business throughout the world,foreign-owned enterprises managed to survive the pandemic smoothly.However,for the private and state-owned enterprises who mainly operate in the

100、domestic market,their reactions to the pandemic are more obvious.For state-owned companies,although the percentage of revenue-declined companies is in the middle across three types of companies,it is not significantly smaller than that of private companies(19.3%against 21.5%,respectively)2.As for ho

101、w well the three types of companies can recover in the post-pandemic era,further investigations are needed.In terms of service/product positioning,when companies target higher market segments,the proportion of revenue-declined companies is lower.That is,the higher a companys positioning,the lower th

102、e probability of a significant decline in revenue.Our data show that the biggest proportion of revenue-declined companies lies with low-end companies(30.1%);that of mid-range companies follows(20.4%);and the smallest proportion comes from high-end companies(16.0%).Among the companies executing the m

103、ixed-strategy,namely servicing high-end,mid-range and low-end markets simultaneously,the proportion of significant revenue-declined companies is 18.0%.This pattern is attention-worthy companies servicing mid-range and low-end customers were highly likely to experience revenue declines due to the pan

104、demic,whilst those servicing high-end customers were less likely to experience revenue declines.This trend is also identified in the average revenue of these three types of companies:companies servicing mid-range and low-end customers showed negative growth in their average revenue.The data show tha

105、t the companies servicing low-end and mid-range customers experienced negative average revenue growth of-5.9%and-3.4%,respectively.However,the companies servicing high-end customers achieved positive growth,with an average revenue increase of 3.2%.This reflects differences in the behaviors of high-e

106、nd,mid-range,and low-end consumers.In 2022,the lackluster economy impacted both the income and expectations of consumers in the mid-range and low-end markets,causing increasing numbers of them to spend less or even cease spending for a period.This intensified competition between companies servicing

107、these customers,adding to the downward pressure.Companies serving the high-end market,however,often have a smaller target audience but higher customer loyalty than those servicing the mid-range and low-end markets.Moreover,Veblen goods are part of the high-end market;these are highly conspicuous goo

108、d,such as luxury products and luxury cars,whose sales increase as their prices rise,in contradiction with the law of demand.For example,the 2022 spring/summer runway show of a luxury fashion brand broke records,with over 130 million livestream views.Another luxury brand witnessed strong growth in th

109、e Chinese market during Q3 2022.These examples highlight the stark differences between the high-end market and the mid-range to low-end market.Compared with companies servicing mid-range to low-end customers,those servicing high-end customers have a smaller and less diverse audience,so they can bett

110、er understand their customers preferences and make timely innovations.All these aspects contribute to the resilience of companies servicing high-end customers to shocks that pose greater challenges to companies servicing mid-range to low-end customers.SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORMA

111、NCE2 However,thedifferencebetweenstate-ownedandprivatecompaniesaveragerevenuesisrelativelymaterial.Itiscalculatedthatthechangeintheaveragerevenueofstate-ownedcompaniesis-1.9%,whileitis-8.5%forprivatecompanies.Suchdifferenceisalsosignificantfromastatisticalperspective(thep-valueofthestudentt-testis0.

112、000).25SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORMANCEIn terms of customer category,companies that serve individual customers(B2C companies)have a bigger percentage of companies with a significant decline in revenue(31.8%);companies that serve corporate/institutional customers(B2B companies),on

113、the other hand,have a smaller percentage of companies with a significant decline in revenue(15.1%).For companies that engage in both B2C and B2B operations(dual-customer companies),the proportion of companies with a significant decline in revenue is in between(21.7%).Meanwhile,the records of average

114、 revenue indicate a similar pattern B2C companies experienced more material negative growth,and the rate of negative growth is-11.0%.For dual-customer companies,although they also experienced negative growth,the rate of negative growth is smaller(-4.4%).In comparison,B2B companies obtained a minor g

115、rowth,and the growth rate is 1.6%.Such pattern verifies the situation of the pandemic control measures implemented in 2022 some economically developed regions imposed rigorous pandemic control policies and strictly prohibited travel,which greatly impacted the retail sector of the economy.Hence,many

116、B2C companies experienced a material economic shock.Local governments prioritized their attention and policy support on B2B companies both during and after pandemic control.For example,many local governments established production bubbles,in which factory employees were isolated from the outside wor

117、ld to prevent and curb infections,thereby enabling B2B companies to quickly resume operations when the pandemic situation improved slightly.In contrast,B2C companies had to wait until the pandemic was mostly under control to resume their operations.This resulted in performance differences between co

118、mpanies servicing different types of customers.In particular,the data show that when a B2C company also engaged in B2B business,the significant decline in their B2C business would be offset by the growth in the revenue of their B2B businesses.In terms of firm size,the proportion of significant reven

119、ue-declined companies is the biggest for small companies(26.8%),followed by medium companies(15.4%)and big companies(13.8%).Such pattern indicates that there is a negative relationship between firm size and revenue decline the bigger the firm is,the less likely it is that its revenue will decline,an

120、d vice versa.This pattern carries over to the average revenue perspective-small companies saw negative revenue growth.Medium and large-sized companies,however,witnessed positive growth,with no significant differences in their growth rates3.Specifically,the small companies average revenue declined by

121、 7.8%,while the medium and large-sized companies average revenue increased by 0.8%and 1.2%,respectively.Overall,the medium and large-sized enterprises had better revenue performance,while the small-sized enterprises faced greater challenges.Section 4.5 draws association between firm size and corpora

122、te confidence level,and it notes that corporate size is positively correlated with enterprise confidence in the short term.This is aligned with our analysis,i.e.,compared with small companies,large companies were less likely to experience a significant decline in revenue during the pandemic and had

123、higher confidence in the short term.Accordingly,we believe that companies are more resilient to unexpected risks and have a higher confidence index in the short term as they grow larger,and vice versa.This can be attributed to various factors,such as favorable government policies,lower financing cos

124、ts,and greater brand awareness enjoyed by large companies compared with smaller companies.In summary,a typical company with a significant revenue decline in 2022 is a small private company in the service sector that caters to individual customers in the low-end market.3 Thereisnostatisticallysignifi

125、cantdifferencebetweentheaveragerevenueofmedium-sizedandlargecompanies(p-valueis0.540inthestudentt-test).26SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORMANCEFIGURE 3.2.PROPORTION OF COMPANIES WITH A SIGNIFICANT REVENUE DECLINE IN EACH CATEGORYService(N=157)Manufacturing(N=76)Dual-industry(N=47)Forei

126、gn-owned companies(N=28)Private companies(N=225)State-owned companies(N=26)High-end companies(N=56)Middle-range companies(N=132)Low-end companies(N=28)Mixed strategy(N=50)Individual customers(B2C)(N=62)Business customers(B2B)(N=116)Individual and business customers(N=100)Small companies(0-299 employ

127、ees)(N=143)Medium-sized companies(300-1,999 employees)(N=72)Large companies(2,000 or more employees)(N=65)IndustryOwnershipCustomer TypeCorporate SizeProduct/ServicePositioning27SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORMANCE3.3.PANDEMIC PREVENTION AND REVENUE DECLINEThe pandemic prevention and

128、control policies implemented in Q2 2022 were one of the most significant factors influencing the Chinese economy and corporate revenue.To analyze whether the measures had an impact on the decline in the revenue of different types of business and,if so,to what extent,Q13 in our questionnaire asked re

129、spondents to indicate what percentage of their companys revenue decline in China in 2022 could be attributed to pandemic prevention and control policies.The options included 0%(indicating that the revenue decline had no relation to pandemic prevention and control policies),100%(indicating that the r

130、evenue decline was wholly due to pandemic prevention and control policies),and four ranges,namely,1%-24%,25%-49%,50%-74%,and 75%-99%.This is dedicated to describing whether and to what extent the pandemic prevention and control policies affected the decline in revenue of each type of business.In Fig

131、ures 3.33.7,the vertical axes indicate the percentage of revenue decline attributable to pandemic prevention and control policies(options in Q13),with the number of respondents who chose each option in Q13 shown in parentheses(N=x).The horizontal axes represent the percentage of companies within a c

132、ategory that selected the stated option in Q13.Across all of these figures,the bars for the“0%”option,indicating no correlation between revenue decline and pandemic prevention and control policies,are consistently the shortest.This indicates that very few companies,regardless of category,believe tha

133、t there was no correlation between revenue decline and pandemic prevention and control policies.That is,the majority of all types of companies attribute their revenue declines to pandemic prevention and control policies to some degree,ranging from 1%to 100%.Therefore,as this section focuses on the i

134、mpact of pandemic prevention and control policies on revenue,we only analyze the options other than“0%”,to ensure that we obtain an informative conclusion.28SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORMANCEFIGURE 3.3.PERCENTAGE OF REVENUE DECLINE ATTRIBUTED TO COVID-19 PANDEMIC PREVENTION AND CONT

135、ROL POLICIES(BY INDUSTRY)Figure 3.3 shows the percentage of revenue decline attributed to pandemic prevention and control policies across different industries.In the manufacturing industry,the majority of the companies(32.9%of the companies in this category)believe that pandemic prevention and contr

136、ol policies contributed to a revenue decline of 1%24%.As the percentage of revenue decline attributed to pandemic prevention and control policies increases,the proportion of companies in this range decreases monotonically,reaching the minimum when the percentage rises to 100%.Over half of the compan

137、ies(approximately 64.7%of the total)in the manufacturing industry attribute less than half of their revenue decline to pandemic prevention and control policies.Only approximately 4.0%of the manufacturing companies attribute their entire revenue decline to pandemic prevention and control policies.In

138、the service sector,24.7%of the companies attribute 25%49%of their revenue decline to pandemic prevention and control policies,and another 24.7%of the companies attribute 50%74%of their revenue decline to pandemic prevention and control policies.Moreover,20.55%of the companies attribute 75%99%of thei

139、r revenue decline to pandemic prevention and control policies,and 19.9%attribute 1%24%of their revenue decline to pandemic prevention and control policies.Only 9.0%of the service companies attribute their revenue decline in 2022 solely to pandemic prevention and control policies.The majority(29.5%)o

140、f the dual-industry companies believe that pandemic prevention and control policies caused 25%49%of their revenue decline,while 27.3%,18.2%,and 17.0%of the dual-industry companies believe that pandemic prevention and control policies caused 50%74%,75%99%,and 1%24%of their revenue decline,respectivel

141、y.Only approximately 8.0%of the dual-industry companies attribute their revenue decline solely to pandemic prevention and control policies.Overall,the service industry has the largest number of companies that consider pandemic prevention and control policies to be the predominant cause of their reve

142、nue decline(75%or more of the total),while the manufacturing industry has the smallest number of such companies.In contrast,the manufacturing industry has the greatest number of companies that believe pandemic prevention and control policies only caused a slight decline in their revenue(24%or less o

143、f the total),while the dual-industry has the smallest percentage of such companies.Dual-industry Manufacturing Service29SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORMANCEFigure 3.4 presents the rate of revenue decline that companies with different types of ownership attribute to pandemic prevention

144、 and control policies.Among state-owned companies,the biggest proportion of companies(32.7%)believe that pandemic prevention and control policies caused 1%-24%of revenue decline.This proportion decreases as the rate of decline caused by pandemic control increases,and it hits the bottom when the rate

145、 of decline caused by pandemic control reaches 100%.Only 4.0%state-owned companies completely attributed their revenue decline to pandemic prevention and control policies.As for private companies,the biggest proportion of them believe that the revenue decline caused by pandemic control takes up 25%-

146、49%(28.1%of private companies);next revenue decline range is 50%-74%,and the proportion of companies in this range is 24.7%.Another 21.3%private companies attribute 1%-24%revenue decline to pandemic control and prevention policies,and 17.7%private companies attribute 75%-99%of their revenue decline

147、to pandemic prevention and control policies.Around 7.9%private companies attribute their revenue decline entirely to pandemic control and prevention policies,which is the highest among the three different ownership types.Foreign-owned companies display a similar pattern as state-owned companies the

148、proportion of companies in the range decreases as the revenue decline range moves up.The biggest percentage of foreign-owned companies(27.2%)believe that 1%-24%of their revenue decline was attributable to pandemic control and prevention policies,whilst 26.2%,23.3%and 14.6%and 6.8%foreign-owned compa

149、nies believe that pandemic control and prevention policies resulted in 25%-29%,50%-74%,75%-99%and 100%of their revenue decline,respectively.In summary,most private companies believe pandemic control and prevention policies are the predominant cause of their revenue decline(causing 75%or more revenue

150、 decline),whereas fewest state-owned companies believe so.Among those who believe pandemic control and prevention policies are only the minor cause of their revenue decline(causing 25%or less revenue decline),state-owned companies are the most,whilst private companies are the fewest.FIGURE 3.4.PERCE

151、NTAGE OF REVENUE DECLINE ATTRIBUTED TO COVID-19 PANDEMICPREVENTION AND CONTROL POLICIES(BY OWNERSHIP STRUCTURE)State-owned Private Foreign-owned30SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORMANCEFigure 3.5 shows the percentage of revenue decline that companies servicing different markets attribute

152、 to pandemic prevention and control policies.Firstly,for the companies that target the low-end market,the highest proportion(36.4%)of companies attribute 50%-74%of their revenue decline to pandemic control and prevention policies.Around 25.0%companies attribute 1%-24%revenue decline to pandemic cont

153、rol.The smallest percentage of companies believe they should attribute 100%of their revenue decline to pandemic control(meaning that they entirely attribute the revenue decline to pandemic control and prevention policies),and this percentage is 6.8%.The second smallest group(9.1%of total low-end com

154、panies)attributes 75%-99%of their revenue decline to pandemic control and prevention policies.Next,for mid-range companies,most of them(26.1%of total mid-range companies)attribute 25%-49%of their revenue decline to pandemic control,while 24.0%of them attribute 1%-24%of the revenue decline to pandemi

155、c control.The smallest proportion(7.8%)of mid-range firms attribute 100%of their revenue decline to pandemic control,meaning that they entirely attribute their revenue decline to pandemic control and prevention policies.The second smallest group(19.1%of total mid-range companies)attributes 75%-99%of

156、 the total revenue decline to pandemic control and prevention policies.As for high-end companies,they present a similar pattern as mid-range companies in terms of the proportion of revenue decline caused by pandemic control and prevention policies.The biggest proportion(26.3%)of high-end companies a

157、ttribute 25%-49%revenue decline to pandemic control,while 24.6%of high-end companies attribute 1%-24%of their revenue decline to pandemic control and prevention policies.The smallest proportion(11.9%)of high-end companies attribute 100%of their revenue decline to pandemic control,meaning that they a

158、ttribute the entirety of their revenue decline to pandemic control),and the second smallest proportion(12.7%)of high-end companies attribute 75%-99%of their revenue decline to pandemic control.Lastly,for those companies that execute a mixed strategy(meaning that they simultaneously service high-end,

159、mid-range and low-end markets),32.1%of these companies attribute 25%-49%of their revenue decline to pandemic control,and this is the biggest group.24.8%of them attribute 50%-74%of their revenue decline to pandemic control.The smallest group(1.8%)of companies attribute 100%of their revenue decline to

160、 pandemic control(meaning that they attribute the entirety of the revenue decline to pandemic control).A 18.3%of these companies attribute 75%-99%of their revenue decline to pandemic control.Overall,among the companies who believe pandemic control to be the predominant cause of their revenue decline

161、(it causes 75%revenue decline or more),most are mid-range companies,and fewest are low-end companies.Among those who believe pandemic control to be only a minor cause of their revenue decline(causing 25%revenue decline or less),high-end companies are the most,and mix-strategy companies are the fewes

162、t.31SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORMANCEFIGURE 3.5.PERCENTAGE OF REVENUE DECLINE ATTRIBUTED TO COVID-19 PANDEMIC PREVENTION AND CONTROL POLICIES(BY MARKET)Mixed strategy Low-end Mid-range High-end32SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORMANCEFigure 3.6 shows the impact of pande

163、mic control and prevention policies on companies servicing different categories of customers.For B2B companies,the biggest percentage(26.5%)of them believe that the pandemic control caused 50%-74%of revenue decline,followed by 26.1%of them believing that the pandemic control caused 25%-49%of their r

164、evenue decline.Another 25.0%of companies believe pandemic control and prevention policies caused 1%-24%revenue decline.There are 6.0%of total B2B companies claiming that pandemic control and prevention policies resulted in all their revenue decline.For B2C companies,the biggest proportion(32.7%)of t

165、hem believe that pandemic control and prevention policies caused 25%-49%of their total revenue decline.The second biggest proportion(20.2%)of B2C companies attribute 50%-74%of their revenue decline to pandemic control,followed by 19.2%of B2C companies attributing 1%-24%of their revenue decline to pa

166、ndemic control,and 15.4%of B2C companies attributing 75%-99%revenue decline to pandemic control.Fewest B2C companies(11.5%of total B2C companies)attribute the entirety of their revenue decline to pandemic control.For dual-customer companies,their revenue decline distribution is similar to B2C compan

167、ies.The biggest proportion(26.7%)of dual-customer companies attribute 25%-49%of their revenue decline to pandemic control and prevention policies,whilst the smallest proportion(7.3%)of dual-customer companies attribute all of their revenue decline to pandemic control and prevention policies.In gener

168、al,among those companies who consider pandemic control and prevention policies to be the predominant cause of their revenue decline(causing 75%or more revenue decline),B2C companies are the most,and B2B companies are the fewest;among those companies that consider pandemic control and prevention poli

169、cies to be only a minor cause of their revenue decline(causing 25%or less revenue decline),B2B companies are the most,and B2C companies are the fewest.FIGURE 3.6.PERCENTAGE OF REVENUE DECLINE ATTRIBUTED TO COVID-19 PANDEMIC PREVENTION AND CONTROL POLICIES(BY CUSTOMER CATEGORY)Dual-customer B2B B2C33

170、SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORMANCEFIGURE 3.7.PERCENTAGE OF REVENUE DECLINE ATTRIBUTED TO COVID-19 PANDEMIC PREVENTION AND CONTROL POLICIES(BY COMPANY SIZE)Big companies Mid-sized companies Small companiesFigure 3.7 shows the impact of pandemic control and prevention policies on comp

171、anies of different sizes.Overall,in every size category,those who consider pandemic control irrelevant to revenue decline are the fewest(0.7%of total big companies,0.5%of total mid-sized companies and 1.3%of total small companies);and the second fewest groups are the companies that attribute the ent

172、irety of revenue decline to pandemic control and prevention policies(3.9%of total big companies,4.9%of total mid-sized companies and 11.4%of total small companies).In addition,the biggest proportion(30.9%)of big companies attribute 1%-24%of their revenue decline to pandemic control.28.0%of big compa

173、nies attribute 25%-49%of their revenue decline to pandemic control.Another 23.0%of big companies attribute 50%-74%of their revenue decline to pandemic control,followed by 12.5%of big companies attributing 75%-99%of their revenue decline to pandemic control.For mid-sized companies,the biggest proport

174、ion(30.8%)of companies believe that pandemic control and prevention policies resulted in 25%-49%revenue decline;the second biggest percentage(24.7%)of mid-sized companies consider that pandemic control caused 50%-74%revenue decline.Another 24.2%mid-sized companies attribute 1%-24%revenue decline to

175、pandemic control,and 14.8%of mid-sized companies attribute 75%-99%revenue decline to pandemic control.With small companies,the biggest percentage(24.2%)of them believe that pandemic control caused 25%-49%of their revenue decline,followed by 23.7%of small companies attributing 50%-74%of their revenue

176、 decline to pandemic control.21.6%of small companies believe that 75%-99%of their revenue decline are the result of pandemic control;and 17.8%of them believe that 1%-24%of revenue decline are caused by pandemic control.In a nutshell,among those who consider pandemic control and prevention policies a

177、re the predominant cause of their revenue decline(causing 75%or more revenue decline),small companies are the most,and big companies are the fewest;among those who consider pandemic control and prevention policies are only a minor cause of their revenue decline(causing 25%or less of their revenue de

178、cline),big companies are the most,and small companies are the fewest.34SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORMANCEAlthough the strict pandemic prevention and control policies were implemented in some regions in Q2 2022,no immediate impacts of such measures were observed.In fact,our results d

179、o not indicate significant revenue declines in any of the loss ranges.To further analyze the revenue declines,we examine the impact of pandemic prevention and control policies in each quarter,as shown in Figure 3.8.This figure has the same axes as Figures 3.33.7,but instead of different company type

180、s,the bars in Figure 3.8 represent different quarters.Figure 3.8 shows the percentage of corporate revenue declines in each quarter attributed to pandemic prevention and control policies.The shortest bars in each color appear for the 100%option,indicating that the lowest percentage of the companies

181、attribute their revenue decline solely to pandemic prevention and control policies in all four quarters(11.4%in Q1,9.9%in Q2,7.4%in Q3,and 7.0%in Q4).Most companies(29.3%)attribute 25%49%of their revenue decline in Q1 to pandemic prevention and control policies,while fewest companies(16.4%)attribute

182、 50%-74%of their revenue decline in Q1 to pandemic prevention and control policies.For Q2,the biggest percentage(26.7%)of companies attribute 25%-49%of their revenue decline to pandemic control,while the smallest percentage(18.6%)of companies attribute 75%-99%of their revenue decline to pandemic con

183、trol.As for Q3,the biggest proportion(28.6%)of companies attribute 25%-49%of their revenue decline to pandemic control,whereas the smallest proportion(16.7%)of companies attribute 75%-99%of their revenue decline to pandemic control.To Q4,the biggest group(31.5%)of companies attribute 50%-74%of their

184、 revenue decline to pandemic control,whilst the smallest group(16.1%)of companies attribute 75%-99%of their revenue decline to pandemic control.Looking at each revenue decline range,11.4%of the companies attribute 100%of their revenue decline in Q1 to pandemic prevention and control policies,which i

185、s the highest proportion that do so among all four quarters.In contrast,7.0%of the companies attribute 100%of their revenue decline in Q4 to pandemic prevention and control policies,which is the lowest proportion that do so among all four quarters.Companies in the range 75%99%believe that pandemic p

186、revention and control policies were the predominant cause for their revenue decline;this range was selected by 21.4%of companies for Q1,which is the highest proportion in this range across all four quarters,whereas it was selected by 16.1%of companies for Q4,which is the lowest proportion in this ra

187、nge across all four quarters.Companies in the revenue range 1%24%believe that pandemic prevention and control policies were a minor contributor to their revenue decline;this range was selected by 23.1%of the companies for Q4,which is the highest proportion that do so across all four quarters,whereas

188、 it was selected by only 20.0%of the companies for Q1,which is the lowest proportion that do so across all four quarters.Companies in the revenue decline ranges 25%49%and 50%74%believe that pandemic prevention and control policies were neither a predominant nor a minor contributor to their revenue d

189、ecline.The range 50%74%contained 31.5%of the companies for Q4,which is the highest proportion across all four quarters,whereas it contained only 16.4%of the companies for Q1,which is the lowest proportion across all four quarters.Moreover,29.3%of the companies attributed 25%49%of the decline in thei

190、r revenue in Q1 to pandemic prevention and control policies,indicating that these policies had a significant negative effect on revenue in this quarter,as this is the highest proportion of companies in this range across the four quarters.However,only 21%of the companies are in this range in Q4,which

191、 is the lowest proportion across the four quarters.35SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORMANCEFIGURE 3.8.PERCENTAGE OF REVENUE DECLINE ATTRIBUTED TO COVID-19 PANDEMIC PREVENTION AND CONTROL POLICIES(BY QUARTER)Q4 2022 Q3 2022 Q2 2022 Q1 202236SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORM

192、ANCE3.4.CONCLUSIONS AND RECOMMENDATIONSBased upon our analyses,we yield the following conclusions and recommendations.First,we can profile a typical enterprise that experienced a significant decline in revenue under pandemic prevention and control policies in 2022 as follows-a small private company

193、in the service sector that mainly targets individual customers in the low-end market.Companies such as this comprise a major part of the Chinese economy and rely heavily on a sound business environment.However,they did not receive adequate policy support amid the COVID-19 outbreaks.To facilitate the

194、ir recovery,the government should prioritize these companies and provide them with dedicated support.Second,the COVID-19 outbreaks in 2022 and the pandemic prevention and control policies posed a severe test for Chinas economy,as evidenced by general market pessimism.Surprisingly,our data do not sho

195、w a substantial gap between the percentage of companies facing declining revenues and that of companies enjoying revenue growth.For example,high-end enterprises in some niche markets exhibited great resilience and even increasing revenues amid the pandemic.This suggests that precision policies will

196、be more effective than one-size-fits-all policies to stimulate economic recovery in 2023.Third,enterprises that“put all of their eggs in one basket”are less resilient than more diversely oriented enterprise when a crisis strikes,as was especially evident during the COVID-19 outbreaks in 2022.Thus,co

197、mpared with manufacturing companies,service businesses faced more material revenue declines during the periods of tight restrictions on the populations movement.Therefore,investing or engaging in manufacturing would help service-based companies mitigate their losses.Although manufacturing companies

198、profited from their non-service business and avoided massive losses by not engaging in the service sector in 2022,they may benefit from a more diverse spread of business when facing other types of challenges that may arise in the future,such as shortages of raw materials and embargoes on spare parts

199、 caused by geopolitical conflicts.Fourth,section 4.5 notes that corporate size is positively correlated with enterprise confidence;i.e.,the bigger(smaller)a company is,the higher(lower)is its confidence.This research report draws a similar conclusion that is in favor of large companies from another

200、perspective:corporate size is negatively correlated with revenue decline,i.e.,the bigger(smaller)a company is,the less(more)likely it is that its revenue will decline.This shows that compared with small companies,big companies have more room to maneuver and thus are able to remain resilient when pan

201、demics or similar crises hit.Many factors contribute to this phenomenon,such as favorable government policies,lower financing costs,and higher brand awareness enjoyed by big companies compared with small companies.However,although the two conclusions above mentioned are consistent,we have not yet es

202、tablished any causal relationship between them.It remains unclear whether big companies short-term business confidence is a result of their resilience,or vice versa.More in-depth and targeted research is needed to determine the relationship between companies short-term business confidence and resili

203、ence.37SECTION 3:ANALYSIS OF COMPANY FINANCIAL PERFORMANCEFifth,the strict pandemic prevention and control policies implemented in Q2 2022 had an enormous negative impact on Chinas economy,and our data indicate that this impact was highly complex.First,the impact was not solely caused by the pandemi

204、c prevention and control policies,because most enterprises had already reported drastic revenue declines in Q1 2022.We believe that some underlying factors that emerged prior to 2022 contributed to the downward pressure on Chinas economy and that the pandemic prevention and control policies implemen

205、ted in Q2 2022 only worsened the situation.Second,the impact of the pandemic prevention and control policies implemented in Q2 2022 on corporate revenue was not immediate.Despite an overall pessimism about Chinas economic performance in Q2 2022,the market anticipated a rapid rebound fueled by reveng

206、e spending after the pandemic prevention and control policies were eased.Our data show a time lag between the pandemic prevention and control policies and revenue declines,as some groups of companies reported more significant revenue declines in Q3 and Q4 than in Q2.We believe similar time lags may

207、extend beyond quarters to years,such that the negative impact on the economy in 2022 is likely to manifest in the coming years.As of early February 2023,when this research report was produced,China had fully lifted its pandemic prevention and control policies,shifted the focus from infection prevent

208、ion to health protection,and downgraded COVID-19 to a Class B infectious disease,meaning that control policies have eased.This situation is strikingly similar to Q3 2022,when East China returned to business after the lifting of lockdowns.Based on our observations for Q2 2022,we posit that the antici

209、pated rapid and robust recovery in 2023 may not materialize immediately after the full lifting of pandemic prevention and control policies.Therefore,we recommend that enterprises take a conservative approach to business planning rather than being overly optimistic,such that they can effectively navi

210、gate a possible“darkest hour before the dawn”period.Moreover,although COVID-19 pandemic has been downgraded to a Class B infectious disease,we recommend that the government conduct a systematic analysis of economic performance in 2022,especially that during the lockdown period,and formulate correspo

211、nding policies.We also suggest that the government examine the economy over previous years to identify the underlying factors that may have inhibited business revenue growth.These factors may have existed before 2022 and been amplified in Q2,Q3,and Q4 of 2022.Further study is needed to determine the

212、se factors.SECTION 4Analysis on the Confidence of Companies Operating in China in the New Business EnvironmentThe China Europe International Business School(CEIBS)research team conducted an online survey on the performance and operations of companies in China in the new business environment between

213、November 18th and 27th,2022,and received a total of 1,474 valid questionnaires.This research report provides some preliminary analysis of the data collected from the survey on the short-term confidence(next 1 year)and medium-term confidence(next 5 years)of the sample companies in operating in China.

214、40SECTION 4:ANALYSIS ON THE CONFIDENCE OF COMPANIES OPERATING IN CHINA IN THE NEW BUSINESS ENVIRONMENT4.1.TIME SERIES ANALYSIS OF CONFIDENCE INDEXFirstly,we report the results of the time series analysis.The CEIBS Research teams survey on the business situation of companies in China started in 2011

215、and has been conducted for 12 years(all years reports are available for free download at https:/cn.ceibs.edu/faculty/research/research-reports/china-business-survey)Although the sample varies from year to year,the sample size is sufficiently large each year and the vast majority of the responses com

216、e from a highly homogeneous group of CEIBS students and alumni,so the sample means are comparable and it reflects the assessment of CEIBS student and alumni as a group on the business conditions of their companies.The surveys for these 12 years were done at the end of the year for all years except 2

217、020 and 2021.2020 and 2021 surveys were done in April because the Corona Virus epidemic hit the Chinese economy hard in the first quarter of 2020,so the survey for that year was brought forward to April in order to do a timely study of the impact of the epidemic shock.The 2021 survey is also placed

218、in April of the year,with the intention of making a comparison with the April 2020 survey results.The data for certain variables in both annual surveys,such as the confidence index,do not match the data for other years.In light of this,we have excluded two particular years,2020 and 2021,from the tim

219、e series study.FIGURE 4.1.SHORT-TERM CONFIDENCE OF COMPANIES TO OPERATE SUCCESSFULLY IN CHINA(NEXT 1 YEAR)Chinese FirmsForeign Firms2011 Survey(N=650)2012 Survey(N=346)2013 Survey(N=1205)2014 Survey(N=1009)2015 Survey(N=752)2016 Survey(N=772)2017 Survey(N=1197)2018 Survey(N=642)2019 Survey(N=986)202

220、2 Survey(N=1472)Figure 4.1 shows the short-term(next 1 year)confidence of companies to operate successfully in China.We observe a fluctuating trend in the short-term confidence index,with a downward trend in the 2011-2016 survey interval,following an upward trend in the 2016-2018 survey interval,and

221、 a downward trend again in the 2018-2022 survey interval.Except for the two years with the lowest short-term confidence indices(2016 and 2022),the short-term confidence of the sample foreign firms(foreign ownership 50%)is slightly higher than that of the sample Chinese firms(Chinese ownership 50%).2

222、011 survey shows that the confidence of the sample foreign firms in 2012 41SECTION 4:ANALYSIS ON THE CONFIDENCE OF COMPANIES OPERATING IN CHINA IN THE NEW BUSINESS ENVIRONMENTFIGURE 4.2.MEDIUM-TERM CONFIDENCE OF COMPANIES TO OPERATE SUCCESSFULLY IN CHINA(NEXT 5 YEARS)Chinese FirmsForeign Firms2011 S

223、urvey(N=650)2012 Survey(N=346)2013 Survey(N=1205)2014 Survey(N=1009)2015 Survey(N=752)2016 Survey(N=772)2017 Survey(N=1197)2018 Survey(N=642)2019 Survey(N=986)2022 Survey(N=1472)Figure 4.2 shows the medium-term(next 5 years)confidence of companies to operate successfully in China.We observe that the

224、 medium-term confidence index shows the same fluctuating trend as the short-term confidence index,but the first low of the medium-term confidence index appears in the 2015 survey,which is one year earlier than the first low of the short-term confidence index(2016 survey year).In almost all years,the

225、 value of the medium-term confidence index is higher than the value of the short-term confidence index,indicating that companies in China have a positive vision of successful business in China over a longer period of time,and are bullish on the prospects for the Chinese economy to rebound when it is

226、 at a low point.Figure 4.2 shows that the medium-term confidence of Chinese companies is more volatile,with two highs in 2012 and 2018(both at 7.20);while the medium-term confidence of foreign companies shows a one-sided downward trend,from 7.70 in 2011,to 7.00 in 2012 and 2013,then to 6.60 in 2019,

227、and to 6.56 in 2022.is as high as 7.20,which is significantly higher than the confidence of the sample Chinese firms in 2012s survey(7.00).Confidence indices from the 2016 survey bottomed out(6.20 for sample Chinese firms and 6.10 for sample foreign firms),which is consistent with Chinas economic gr

228、owth rate hitting a 26-year low of 6.7%in 2016.2017 saw Chinas economic growth rebound for the first time in seven years,although the official economic growth rate for 2017 was given as 6.8%,with most economists estimating GDP growth above 7%for the year.Reflecting this,the confidence index shown in

229、 the 2016-2018 surveys rebounded to a high level of 6.90(6.90 for both sample Chinese firms and sample foreign firms).Notably,COVID-19 epidemic has not yet occurred in China at the end of 2019,but the short-term confidence index of sample firms has fallen to a low point,slipping to a low of 6.10 and

230、 6.40 for sample Chinese firms and sample foreign firms respectively.This shows that the decline in confidence of companies in China to operate successfully was already evident in 2019,and the impact of the epidemic in 2020-2022 is further crystallizing this lack of confidence.424.2.THE RELATIONSHIP

231、 BETWEEN REVENUE PERFORMANCE AND CONFIDENCE INDEXFigure 4.3 shows the confidence index corresponding to the 2022 revenue performance in China of the sample companies.The horizontal axis of Figure 4.3 divides the revenue performance in China of the sample firms into nine groups,ranging from the worst

232、 performance(50%revenue decline in China in 2022)to the best performance(25%revenue growth in China in 2022).The sample size of each group shows a fairly even distribution of revenue growth rates in 2022,with a total of 598(42%)sample companies with negative revenue growth in China,527(37%)sample co

233、mpanies with positive growth,and 286(20%)sample companies with flat growth.Figure 4.3 shows that there is a positive relationship between confidence index and revenue performance,which is particularly evident in the short-term confidence index.101 companies with the worst revenue performance in Chin

234、a in 2022(decline rate 50%)have a short-term confidence index of only 4.32,while 185 companies with the best revenue performance in China in 2022(growth rate 25%)have a short-term confidence index of 7.37.Figure 4.3 shows that for all groups,the medium-term confidence indices are higher than the sho

235、rt-term confidence indices,and the extent to which it is higher is negatively correlated with revenue performance in China in 2022,indicating that the sample companies attribute their revenue performance in 2022 mainly to short-term factors,with the poorer performing companies believing there will b

236、e more room for upward movement in the medium term,while the better performing companies believe there is relatively limited room for upward movement in the medium term.Figure 4.3 shows that the 185 companies with the best revenue performance in China in 2022 have similar short-term confidence(7.37)

237、and medium-term confidence(7.48)in terms of value.SECTION 4:ANALYSIS ON THE CONFIDENCE OF COMPANIES OPERATING IN CHINA IN THE NEW BUSINESS ENVIRONMENTFIGURE 4.3.THE RELATIONSHIP BETWEEN REVENUE PERFORMANCE IN CHINA AND CONFIDENCE IN 2022Confidence Index to Next 5 Years(2023-2027)Confidence Index to

238、Next Year(2023)fell by 50%or more(N=101)fell by 25%to 49%(N=179)fell by 10%to 24%(N=230)fell by 2%to 9%(N=88)stayed about the same(within 2%up/down)(N=286)increased by 2%to 9%(N=152)Increased by 10%to 24%(N=190)increased by 25%or more(N=185)43SECTION 4:ANALYSIS ON THE CONFIDENCE OF COMPANIES OPERATI

239、NG IN CHINA IN THE NEW BUSINESS ENVIRONMENTFIGURE 4.4.SHORT-TERM(NEXT 1 YEAR)CONFIDENCE INDEX FOR THE MANUFACTURING SECTOR4.3.SHORT-TERM CONFIDENCE IN THE MANUFACTURING AND SERVICE SECTORSThe total sample of this survey is 1,474,of which the number of sample enterprises engaged in manufacturing sect

240、or is 749 and the number of sample enterprises engaged in service sector is 965,of which some enterprises are engaged in both manufacturing and service.After taking into account the overlap factors,the percentage of manufacturing sample enterprises is 44%and the percentage of service sample enterpri

241、ses is 56%.Figures 4.4 and 4.5 show the short-term(1 year ahead)confidence indices for the manufacturing and service sectors,respectively.The short-term confidence index for the whole sample of manufacturing sector is 6.38(Figure 4.4),which is higher than the short-term confidence index of 6.07(Figu

242、re 4.5)for the whole sample of service sector.Among the manufacturing industries,Civil Engineering and Construction(sample size 86,accounting for 11%of the total manufacturing sample)has the lowest short-term confidence index at 5.14.The next lowest short-term confidence index is in Consumer Product

243、s(sample size 112,accounting for 15%of the total manufacturing sample)at 5.90.Among the manufacturing industries,Paper-making and Printing(sample size 8,accounting for 1%of the total manufacturing sample)has the highest short-term confidence index at 7.38.The next highest is 6.97 for the Pharmaceuti

244、cal Products and Medical Devices industry(sample size 127,or 17%of the total manufacturing sample).The distribution of confidence in the manufacturing sector reflects its business opportunities in the context of the COVID-19 epidemic;not surprisingly,the Pharmaceutical Products and Medical Devices i

245、ndustry(as well as the Paper-making and Printing industry)has the highest short-term confidence index among manufacturing industries;while the real estate related industry has the lowest short-term confidence index among manufacturing industries due to the dual impacts of the epidemic and policies.C

246、ivilEngineering and Construction(N=86)Consumer Products(N=112)Other Manufacturing(N=5)Metal&Non-Metallic Products(N=23)Whole Sample(N=749)Communications&Electronic Products(N=93)Automobile&Transportation Vehicles(N=63)Machinery&Equipment(N=112)Chemical&Energy Products(N=79)Agriculture,Forestry,Husba

247、ndry,Fishing&Mining(N=25)Public Utilities(such as water,electricity and gas supply)(N=16)Pharmaceutical Products&Medical Devices(N=127)Papermaking&Printing(N=8)44SECTION 4:ANALYSIS ON THE CONFIDENCE OF COMPANIES OPERATING IN CHINA IN THE NEW BUSINESS ENVIRONMENTFIGURE 4.5.SHORT-TERM(NEXT 1 YEAR)CONF

248、IDENCE INDEX FOR THE SERVICE SECTORReal Estate Services(N=69)Telecommunications&Information Services(N=93)Logistics,Transportation&Storage(N=50)Culture,Entertainment&Recreation(N=51)Whole Sample(N=965)Catering,Accommodation&Travel(N=33)Education(N=36)Professional Services&Business Services(N=209)Hea

249、lth Care,Medical&Sanitation(N=102)Wholesale&Retail(N=132)Financial Services(N=173)Other Services(N=17)Among the service sector,Real Estate Services(sample size is 69,accounting for 7%of the total service sector sample)has the lowest short-term confidence index at 5.10,which is in line with the short

250、-term confidence index for Civil Engineering and Construction at 5.14,reflecting the perception of a sluggish outlook for the real estate sector.The service sector with the next lowest short-term confidence index is Culture,Entertainment and Recreation industry(sample size 51,5%of the total service

251、sector sample)at 5.41,followed by Education industry(sample size 36,4%of the total service sector sample)at 5.64.The Culture,Entertainment and Recreation industry and the Education industry are the hardest hit by the epidemic,and some of them are also deeply affected by the policy,so it is expected

252、that their short-term confidence is at a low level.Among the service industries,apart from“other services”,the Healthcare,Medical and Sanitation industry(sample size 102,accounting for 11%of the total service sector sample)has a relatively higher short-term confidence index(6.71),which is consistent

253、 with the short-term confidence index of the pharmaceutical products and medical devices industry(6.97),reflecting that medical-related industries are relatively favorable under the epidemic.45SECTION 4:ANALYSIS ON THE CONFIDENCE OF COMPANIES OPERATING IN CHINA IN THE NEW BUSINESS ENVIRONMENTFIGURE

254、4.6.MEDIUM-TERM(NEXT 5 YEARS)CONFIDENCE INDEX FOR THE MANUFACTURING SECTORCivilEngineering and Construction(N=86)Whole Sample(N=749)Communications&Electronic Products(N=93)Chemical&Energy Products(N=79)Other Manufacturing(N=5)Machinery&Equipment(N=112)Pharmaceutical Products&Medical Devices(N=127)Co

255、nsumer Products(N=112)Public Utilities(such as water,electricity and gas supply)(N=16)Agriculture,Forestry,Husbandry,Fishing&Mining(N=25)Automobile&Transportation Vehicles(N=63)Metal&Non-Metallic Products(N=23)Papermaking&Printing(N=8)4.4.MEDIUM-TERM CONFIDENCE IN THE MANUFACTURING AND SERVICE SECTO

256、RSFigures 4.6 and 4.7 show the medium-term(next 5 years)confidence indices for the manufacturing and service sectors,respectively.The medium-term confidence index for the whole sample of manufacturing sector is 6.93(Figure 4.6),which is higher than the medium-term confidence index of 6.61(Figure 4.7

257、)for the whole sample of service sector.Among manufacturing sector,Civil Engineering and Construction(sample size is 86,11%of the total manufacturing sample)has the lowest medium-term confidence index at 5.88.Excluding“other manufacturing”,which has only 5 samples,the next lowest medium-term confide

258、nce index is in Consumer Products(sample size is 112,15%of the total manufacturing sample)at 6.72.These two manufacturing industries with the lowest medium-term confidence indices are also the two industries with the lowest short-term confidence indices,which show that their low outlook is not mainl

259、y caused by short-term factors such as the epidemic,but by deeper reasons,which determine the lack of optimism about the medium-term outlook for the recovery of the real estate industry and the improvement of consumption momentum.Among the manufacturing industries,Paper-making and Printing(sample si

260、ze 8,accounting for 1%of the total manufacturing sample)and Agriculture,Forestry,Husbandry,Fishing and Mining(sample size 25,accounting for 3%of the total manufacturing sample)are the top two industries with the highest medium-term confidence indices,at 8.13 and 7.68 respectively.The Pharmaceutical

261、Products and Medical Devices industry(sample size 127,accounting for 17%of the total manufacturing sample)has the third highest medium-term confidence index,at 7.30.For all manufacturing industries,the medium-term confidence index is higher than the short-term confidence index;the industry distribut

262、ion of the medium-term confidence index basically continues the industry distribution of the short-term confidence index,indicating that the medium-term outlook of their manufacturing industries is relatively stable in the eyes of corporate executives.46SECTION 4:ANALYSIS ON THE CONFIDENCE OF COMPAN

263、IES OPERATING IN CHINA IN THE NEW BUSINESS ENVIRONMENTFIGURE 4.7.MEDIUM-TERM(NEXT 5 YEARS)CONFIDENCE INDEX FOR THE SERVICE SECTORReal Estate Services(N=69)Wholesale&Retail(N=132)Financial Services(N=173)Health Care,Medical&Sanitation(N=102)Culture,Entertainment&Recreation(N=51)Whole Sample(N=965)Log

264、istics,Transportation&Storage(N=50)Education(N=36)Professional Services&Business Services(N=209)Other Services(N=17)Telecommunications&Information Services(N=93)Catering,Accommodation&Travel(N=33)Among the service industries,the Real Estate Service industry(sample size 69,7%of the total service indu

265、stry sample)has the lowest medium-term confidence index at 5.80,which is in line with the medium-term confidence index for the Civil Engineering and Construction industry(5.88),reflecting the perception that the medium-term outlook for the real estate sector is not optimistic.The next lowest medium-

266、term confidence index is in the Culture,Entertainment and Recreation industry(sample size 51,5%of the total service sector sample)at 6.02,followed by the Education industry(sample size 36,4%of the total service sector sample)at 6.33.These figures reflect low confidence in the medium-term business ou

267、tlook for the Culture,Entertainment and Recreation industry and the Education industry in China.Among the service sector,the highest medium-term confidence index(7.55)was recorded in the Catering,Accommodation and Travel industry(sample size 33,accounting for 3%of the total service sector sample),in

268、dicating that the impact of the epidemic is a short-term shock to this industry and that the medium-term outlook is more optimistic.47SECTION 4:ANALYSIS ON THE CONFIDENCE OF COMPANIES OPERATING IN CHINA IN THE NEW BUSINESS ENVIRONMENT4.5.THE RELATIONSHIP BETWEEN FIRM SIZE AND CONFIDENCE INDEXBased o

269、n the answers to the question“How many employees in China does your company hire at present?”in the survey questionnaire,the size of the companies were divided into 9 categories as follows:(1)0 to 9(Micro);(2)10 to 49(Extra-Small);(3)50 to 299(Small);(4)300 to 999(Small-to-Medium);(5)1,000 to 1,999(

270、Medium);(6)2,000 to 4,999(Medium-to-Large);(7)5,000 to 9,999(Large);(8)10,000 to 49,999(Extra-Large);(9)50,000 or above(Giant).Figure 4.8 shows the relationship between firm size and confidence index.We find that in the range of micro to medium sized firms,both short-term and medium-term confidence

271、indices are positively correlated with firm size,i.e.,the larger the firm size,the higher the confidence;the short-term confidence index of micro enterprises is 5.77,while that of medium enterprises is 6.41;the medium-term confidence index of micro enterprises is 6.42,while that of medium enterprise

272、s is 7.03.In the range of medium to large sized firms,the short-term confidence index is relatively stable at around 6.40,while the medium-term confidence index is negatively correlated with the size of firms,i.e.,the larger the size of firms,the lower the confidence;the medium-term confidence index

273、 of medium-sized enterprises is 7.03,and the medium-term confidence index of large enterprises is 6.75.In the range of large to giant sized firms,the medium-term confidence index is positively correlated with firm size,i.e.the larger the firm size,the higher the confidence;the medium-term confidence

274、 index for large firms is 6.75 and for giant firms is 7.06.We also find that in the range of large to giant,the increase in short-term confidence index to medium-term confidence index is positively correlated with firm size,i.e.the larger the firm size,the greater the increase in short-term confiden

275、ce index to medium-term confidence index;the short-term confidence index of extra-large enterprises is 6.22 and medium-term confidence index is 6.78,an increase of 9%;the short-term confidence index of giant enterprises is 6.27 and medium-term confidence index is 7.06,an increase of 13%.As to why th

276、e relationship between enterprise size and confidence index is like this,further research is needed.FIGURE 4.8.THE RELATIONSHIP BETWEEN FIRM SIZE AND CONFIDENCE INDEXConfidence Index to Next 5 Years(2023-2027)Confidence Index to Next Year(2023)Micro(N=31)Extra-Small(N=148)Small(N=355)Small-to-Medium

277、(N=339)Medium(N=130)Medium-to-Large(N=145)Large(N=110)Extra-Large(N=145)Giant(N=71)48SECTION 4:ANALYSIS ON THE CONFIDENCE OF COMPANIES OPERATING IN CHINA IN THE NEW BUSINESS ENVIRONMENT4.6.CONCLUSIONIn late November 2022,the CEIBS research team conducted an online survey on the performance and opera

278、tions of companies in China in the new business environment,and received in total of 1,474 valid questionnaires.Since 2011,the CEIBS research team has conducted this online survey every year,thus accumulating 12 years of data.In all years,the questionnaires include the sample companies assessment of

279、 their short-term confidence(next 1 year)and medium-term confidence(next 5 years)in doing business in China.Based on these data,we have done some analysis of the short and medium term confidence indices and the results are as follows.First,in the two years with the lowest short-term confidence indic

280、es(2016 and 2022),the short-term confidence indices of the sample foreign firms are lower than those of the sample Chinese firms;in all other years,the short-term confidence indices of the sample foreign firms are slightly higher than those of the sample Chinese firms.It is thus inferred that the sh

281、ort-term outlook of the sample foreign firms is more positive than that of the sample Chinese firms,but their sensitivity to the short-term impact of negative shocks is higher than that of the sample Chinese firms,and the negative shocks have a greater impact on the short-term confidence of the samp

282、le foreign firms than that of the sample Chinese firms.Second,in all years,the medium-term confidence index is higher than the short-term confidence index,indicating that companies in China have a positive vision of successful business in China in the medium term and are bullish on the prospects of

283、rebounding when the Chinese economy is at a low point.The medium-term confidence index for Chinese companies is more volatile,with two highs in 2012 and 2018;while the medium-term confidence index for foreign companies shows a one-sided downward trend from 2011-2022.Third,in the survey at the end of

284、 2019,when the COVID-19 epidemic has not yet occurred,the short-term confidence indices of the sample Chinese firms and foreign firms have fallen to a low level of 6.10 and 6.40,which shows that the lack of confidence of companies in operating successfully in China has already begun to emerge in 201

285、9,and the epidemic shock in 2020-2022 is further curing this lack of confidence.Fourth,the confidence index values obtained from the 2022 survey are positively correlated with revenue performance in 2022,especially in the short-term confidence index.101 companies with the worst revenue performance i

286、n 2022 in China have a short-term confidence index of only 4.32,while 185 companies with the best revenue performance in 2022 have a short-term confidence index of 7.37.For all groups,the medium-term confidence index is higher than the short-term confidence index,but the degree of increase is negati

287、vely correlated with revenue performance in China in 2022,indicating that the sample companies attribute their revenue performance in China in 2022 mainly to short-term factors,with the poorer performing companies seeing more rising space in the medium term,while the better performing companies see

288、more limited space to ascend in the medium term.This is evident from the little difference between the short-term confidence index(7.37)and the medium-term confidence index(7.48)of the group with the best revenues.49Fifth,the short-term confidence index for the whole sample of manufacturing(6.38)is

289、higher than the short-term confidence index for the whole sample of services(6.07).Among manufacturing sector,Civil Engineering and Construction has the lowest short-term confidence index(5.14),and Consumer Products industry has the next lowest(5.90).Among the service sector,Real Estate Services has

290、 the lowest short-term confidence(5.10),followed by Culture,Entertainment and Recreation(5.41),and then Education(5.64).The low level of short-term confidence in these industries confirms that they are more affected by the epidemic and policies.Among the manufacturing industries,the Pharmaceutical P

291、roducts and Medical Devices sector has the highest short-term confidence index(6.97);among the service industries,the Healthcare,Medical and Sanitation industry has the highest short-term confidence index(6.71);this reflects the special period of the epidemic that favors the medical-related industri

292、es.Sixth,the medium-term confidence index for the whole sample of manufacturing industries(6.93)is higher than the medium-term confidence index for the whole sample of service industries(6.61).Among manufacturing sector,Civil Engineering and Construction has the lowest medium-term confidence index(5

293、.88);among service sector,Real Estate Services has the lowest medium-term confidence index(5.80);both reflect the perceived lack of optimism in the medium-term outlook for the real estate sector.The two manufacturing industries with the lowest medium-term confidence indices(Civil Engineering and Con

294、struction,and Consumer Products)are also the two manufacturing industries with the lowest short-term confidence indices;the service industries with low medium-term confidence indices(Culture,Entertainment and Recreation,and Education)are also the two service industries with low short-term confidence

295、 indices,suggesting that the sluggish outlook of these industries is not mainly caused by short-term factors such as the epidemic,but by deeper reasons.It is worth noting that the highest medium-term confidence index among service industries is in the Catering,Accommodation and Travel industry(7.55)

296、,suggesting that executives in this industry see the epidemic as a short-term impact and are optimistic about the medium-term outlook for the industry.Seventh,there is a non-linear relationship between firm size and confidence index.In the range of micro to medium sized firms,both short-term and med

297、ium-term confidence indices are positively correlated with firm size,i.e.,the larger the firm size,the higher the confidence.In the medium to large size range,the short-term confidence index is relatively stable,while the medium-term confidence index is negatively correlated with the size of enterpr

298、ises.In the range of large to giant,the medium-term confidence index returns to a positive relationship with firm size,i.e.,the larger the firm size,the higher the confidence.It is found that in the range of large to giant,the increase of short-term confidence index to medium-term confidence index i

299、s positively correlated with firm size;in other words,the larger the firm size is,the greater the increase from short-term confidence index to medium-term confidence index.Further research is needed to investigate why this relationship between firm size and confidence index is observed.SECTION 4:ANA

300、LYSIS ON THE CONFIDENCE OF COMPANIES OPERATING IN CHINA IN THE NEW BUSINESS ENVIRONMENTSECTION 5Implications From Innovation Under New Business Environment52SECTION 5:IMPLICATIONS FROM INNOVATION UNDER NEW BUSINESS ENVIRONMENTAs innovation,or research and development(R&D),is risky in nature,the comm

301、itment that firms are willing to engage its resources into nurturing innovation indicates the long-term outlook firms take.Their R&D efforts are indicative in understanding the future of Chinas innovation capacity and implications on long-term growth.We find that among the 1,474 survey responses,onl

302、y 5.4%reported a definite plan to decrease R&D investments for the coming three years compared to 2022,whereas a striking share of 26.5%reported a plan to not only increase future R&D,but at a magnitude of more than 10%(Figure 5.1).FIGURE 5.1.FUTURE R&D SPENDING OUTLOOK Increase by 10%or more Increa

303、se by 5%-10%(not including 10%)Increase by 2%-5%(not including 5%)The same Decrease Not sureNote:Summarized from responses of Q19 of the questionnaire:”In the coming 3 years(2023-2025),your companys R&D spending in China is expected to?”.There is usually high persistence in R&D spending decisions.We

304、 find that a major portion of the firms stick to the same investment decisions for 2022 and for the future 3 years(Figure 5.2).The remaining portion mainly adjust their investment decisions within the same direction(that is,increase or decrease at different magnitudes).However,we find that some firm

305、s that plan to increase future R&D by more than 10%held back on R&D investments recently(2.6%reported no R&D in both 2021 and 2022,and another 2.6%reported a decrease of more than 10%in 2022 compared to 2021).Likewise,many firms that plan to decrease future R&D had increased investments in 2022(15.2

306、%),while many of them have invested similar amounts in both 2021 and 2022(17.7%).53SECTION 5:IMPLICATIONS FROM INNOVATION UNDER NEW BUSINESS ENVIRONMENTFIGURE 5.2.FUTURE R&D SPENDING DECISION THE SAME AS R&D SPENDING DECISION IN 2022Note:Summarized from comparing responses of Q18(“Compared to 2021,w

307、hat is your companys estimated 2022 R&D spending in China?”)and Q19(”In the coming 3 years(2023-2025),your companys R&D spending in China is expected to?”).DecreaseThe sameIncrease by less than 10%Increase by 10%or moreFirms mainly have some form of internal R&D(84.1%)and reported collaboration with

308、 either business partners or academic institutions as a dual force.A small share of firms also purchase externally.The innovation activities that firms engage in range from relatively easier ones(such as providing technical training for employees)to harder ones(such as adding new features to existin

309、g products and reducing production costs)to the most challenging ones(such as introducing new products or services).Firms from the two spectrum of future R&D spending have both committed high share(above 10%)of their revenue in R&D account for 30.3%of firms that wish to increase R&D investments in t

310、he coming 3 years and 34.2%of firms that wish to decrease future R&D investments indicating the difficulty in R&D management,especially in a time of uncertainty.We are interested in the characteristics of those firms that are willing to increase their allocation of resources for R&D versus those tha

311、t plan to draw back under the new business environment.The majority of our respondents are decision makers that are alumni of CEIBS,thus they represent mainly leading companies of different industries,which indicate that there should be less heterogeneity among the profitability and management of th

312、ese firms.However,we observe versatile responses in future R&D expense.In the following sections,we explore the business and industrial characteristics firms belong to,resource constraint that firms face,and firms expectations about the future together shape the R&D spending decisions.54SECTION 5:IM

313、PLICATIONS FROM INNOVATION UNDER NEW BUSINESS ENVIRONMENT5.1.BUSINESS AND INDUSTRIAL CHARACTERISTICSNo matter how future R&D spending is planned,Chinese private enterprises are the majority.However,we do find that the firms that plan to hold R&D spending constant for future years have more foreign o

314、wnership involved.Small(50 to 299 employees)and Small-to-Medium(300 to 999 employees)are also the majority for all firms.Extra-Large firms(10,000 to 49,999 employees)have the tendency to either hold constant or shrink the magnitude of future R&D spending,most possibly due to more operating expenses

315、compared to smaller-sized firms.Firms that plan to increase future R&D by 10%or more mostly produce only high-end or both high-and-middle-end products,with no firms producing only low-end products.Firms that plan to decrease their future R&D spending also report no pure low-end products,however,a hi

316、gh share(6.3%compared to the whole sample mean of 3%)of these firms are not sure how the products they produced are positioned in the market.We find that“Professional Services&Business Services”and“Pharmaceutical Products&Medical Devices”are two industries with wide variations in future R&D planning

317、;a substantial share of firms among all categories of future R&D spending belong to these two industries.Other than that,the major industries for increased R&D spending are“Health Care,Medical&Sanitation”and“Machinery&Equipment”.Firms that belong to“Financial Services”and“Consumer Products”tend to h

318、old constant their future R&D expenditure,whereas firms in“Telecommunications&Information Services”and“Machinery&Equipment”report plans for future spending decline.FIGURE 5.3.MAIN BUSINESS LOCATIONS Increase by 10%or more Increase by less than 10%The same DecreaseBeijingTianjinShanghaiShenzhenJiangs

319、uProvinceZhejiangProvinceGuangdongProvinceNote:Summarized from responses of Q4 of the questionnaire:“What is the main location of your companys China business?(Multiple Answers Possible)”.We observe from the whole sample that the top three locations for business operations are Shanghai(18.3%),Guangd

320、ong province(13.1%),and Jiangsu province(12.5%).The distribution is slightly different according to different R&D expense outlooks.Most notably are firms that plan to decrease future R&D.Among them,we find that 21.4%reported that Shanghai is a main location for business operations,15.8%reported Guan

321、gdong province,and 13.7%reported Beijing(Figure 5.3).55SECTION 5:IMPLICATIONS FROM INNOVATION UNDER NEW BUSINESS ENVIRONMENT5.2.RESOURCE CONSTRAINTS Firms that plan to decrease future R&D rely heavily on business-in-China for their revenue and most face a smaller revenue increase.Firms that plan to

322、increase R&D spending not only have more diverse business operations,but also reported a higher share of revenue increase(both from operations in China and overseas operations).46.8%of firms with declining future R&D spending rely entirely on businesses in China,whereas only 40.7%for firms that plan

323、 to increase R&D spending.46.5%of the firms that plan to increase future R&D spending have reported an increase in revenue from business-in-China and while 73.4%of the firms that wish to decrease future R&D reported a decline in revenue from business-in-China.Firms that plan to increase future R&D r

324、ely more on innovation to generate their revenue.On average,80%of these firms reported that their past revenue benefited from innovation.Approximately half of all the firms(51.8%)receive no support from the government.The share of no government support is smaller among the firms that plan to increas

325、e future R&D spending(44.8%),whereas a higher share is observed among firms that plan to reduce future R&D(64.6%).In China,a lot of government support regarding R&D is related to the recognition of High-and-New-Technology-Enterprises(HNTE).This recognition is usually rewarded to firms that are compe

326、tent in their respective technological fields.Those that show potential are considered as part of the cultivation pool,which also enjoy some benefits.35.3%of the firms that plan to increase future R&D are either recognized as HNTE on the national or provincial level,or part of the national or provin

327、cial level cultivation pool.On the other hand,only 26.6%of the firms that are downsizing their R&D attained such a status in the past 3 years.56SECTION 5:IMPLICATIONS FROM INNOVATION UNDER NEW BUSINESS ENVIRONMENT5.3.FUTURE EXPECTATIONS Firms tend to have higher long-term confidence level(2023-2027)

328、compared to the near future(2023).Most quote the evolution of pandemic-related policies as the most important factor when forming their beliefs.Firms that plan to increase future R&D by 10%or more have the highest confidence level going forward,whereas those that wish to decrease their spending have

329、 a much lower confidence level(Figure 5.4).FIGURE 5.4.CONFIDENCE LEVEL 2023 2023-2027Note:Summarized from responses of Q25(“How confident are you that your companys business operations in China will be successful in the coming year(2023)?Please move the cursor or tap on the scale until the number yo

330、u want appears in the box on the left.”)and Q27(“How confident are you that your companys business operations in China will be successful in the next 5 years(2023-2027)?Please move the cursor or tap on the scale until the number you want appears in the box on the left.”)of the questionnaire.Increase

331、 by10%or moreIncrease byless than10%The sameDecreaseWholesample57SECTION 5:IMPLICATIONS FROM INNOVATION UNDER NEW BUSINESS ENVIRONMENTFIGURE 5.5.PERCEPTION OF BUSINESS OPERATIONS OVER THE PAST 5 YEARS Increase by 10%or more Increase by less than 10%The same DecreaseAs perceived risk(or uncertainty)i

332、s a crucial determinant in planning R&D,we find that firms that are more conservative going forward have faced a worsening of business environment both in the domestic market and the overseas market(Figure 5.5).We conjecture that the past experience and current revenue conditions together shaped the

333、 varying confidence levels among the firms we observe.Improvedsignificantly(domestic)Improvedsignificantly(international)Worsenedsignificantly(domestic)Worsenedsignificantly(international)Note:Summarized from responses of Q29(“Looking back,for the past 5 years(2018-2022),how would you describe Chinas domestic business environment for your companys operations in China?”)and Q30(“Looking back,for th