R.1 Understanding SV 99: SV and Measurement Tools
SV 99 refers to China’s 99 listed companies selected from CSI 300 constituents, and the Discovering “SV 99” in China project involves the launch of a ranking list of these companies along with an assessment report on their SV performance. In China, where thousands or tens of thousands of rankings are released every year, the SV 99 Ranking may seem to be a drop in the ocean. The publication of the Chinese edition of Discovering “SV 99” in China-A-share Listed Company SV Assessment Report (2017) on 15 December 2017, however, soon grabbed the headlines of over 100 major media outlets, such as Securities Times, Xinhua Net, CBN, Hexun.com, Financial Times and South China Morning Post; three weeks after the publication of its English edition in Geneva, a team of more than 40 fund managers and financial analysts from the global fund management company Fidelity International made a visit to Shenzhen to learn more about the SV 99 project; during the 73rd United Nations General Assembly in September 2018, the China Alliance of Social Value Investment (CASVI), invited by the United Nations Development Programme (UNDP), was present at the meeting “How the Private Sector Can Align to the SDGs”, introducing to international delegates the philosophies and practices of SV 99.
How could this trivial endeavour arouse extensive interests? What is the rationale, vision and value of the SV 99 initiative?
As an initiative originated by civil society in China, the SV 99 strives to measure the total value of a target company based on its economic, social and environmental contributions by leveraging the SV Assessment Model. It aims to help advance sustainable development, and is guided by the UN SDGs[1] and CDV[2]. As a result of 14-months of collective efforts by 68 experts from 42 institutions home and abroad in pro-bono capacity under the coordination of CASVI, the project has achieved “four world’s firsts”-the first SV assessment system (SV 99 Assessment Model); the first SV assessment of listed companies (SV 99 Ranking); the first SV stock index (SV 99 Index); and the first released SV performance credit rating of listed companies (published in the Wind Financial Terminal). Now, CASVI is working with leading fund management companies in China to launch actively managed funds and exchange-traded funds (ETFs).
More importantly, statistics show that during the 24 months of market back-test and tracking from 23 November 2016 up to the date of this report, the SV 99 Index developed from the SV 99 Ranking outperformed mainstream A-Share indices, including SSE 50, CSI 300, CSI 800, Shanghai Composite Index, ChiNext Index and SCI, with a higher ROE than virtually all of its peers.
Is the SV assessment, along with its application products, simply a grasp at luck, or a “seed” of a vision blooming into reality? To better understand the SV 99 community, we need to first clarify the implications of SV and the structure of the assessment models.
1.1 The Concept of SV
SV in this report is referred to as DW & DG, which specifically means the comprehensive economic, social and environmental contributions created by organisations through innovative technologies for production, business operation models and management systems for the purpose of building a better future with improved quality, efficiency, justice and sustainability.
The proposition of SV is composed of three aspects (3A): AIM (to build a better future with improved quality, efficiency, justice and sustainability), APPROACH (innovative technologies for production, business operation models and management systems), and ACTION (comprehensive economic, social and environmental contributions). To evaluate an organisation’s SV, the assessment focuses on the following 3 forces: Driving Force (What has enabled the organisation to survive?), Innovation Force (What has enabled the organisation to be sustainable?), and Transformation Force (What value has the organisation created?). Therefore, SV is also referred to as the “3A-3 Force” value proposition.
1.1.1 Rationale
The concept of SV has been discussed by a number of Western philosophers, economists and sociologists, including Max Weber, a German philosopher, who coined the terms of “instrumental-rationality” and “value-rationality” in The Protestant Ethic and the Spirit of Capitalism[3], Arthur C. Pigou, a British economist, who put forward “externalities” in The Economics of Welfare[4], and John Rawls, an American political philosopher, who proposed “justice as fairness” in A Theory of Justice[5]. In the 21st century, William Clark, a professor at Harvard University, and some other scholars developed the new sustainability science based on multidisciplinary research on the interactions between economic, social and ecological systems focusing on the Earth’s carrying capacity. Herman E. Daly, a professor at the School of Public Policy of University of Maryland, proposed in his book Beyond Growth: The Economics of Sustainable Development[6] a more enlightening idea that “growth is quantitative increase in physical scale while development is qualitative improvement”. Sustainable development is a combination of environmental, social and economic benefits, requiring that the “growth-oriented” quantitative development concept be replaced with the “welfare-oriented” qualitative development concept. All the above theories have nurtured the evolution of SV.
In addition to drawing on the theoretical contributions above, the concept of SV in this report is derived from two lines of thinking.
First, it follows the traditional Chinese thinking of encouraging both DW & DG, which epitomises the oriental systematic thinking, different from Western linear thinking developed from formal logic. As early as 2,500 years ago, the Chinese classic Book of Changes made it clear that DW & DG are mutually transformable. In essence, they are the two sides of one coin. While DW guarantees a successful start, DG determines how far it will go. The Confucian, Taoist, Mohist and Legalist schools, although weighing the importance of DW and DG differently, all agree that the harmony between DW and DG and between man and nature is the fundamental principle of mankind. SV is a modern interpretation of DW & DG in a new era.
Second, it is consistent with the UN SDGs adopted on 25 September 2015 by 193 member states at the UN Summit on Sustainable Development held at the UN Headquarters in New York, which aim to substantially address the world’s systemic economic, social, and environmental challenges by 2030. Aligned with the SDGs, the SV proposition is dedicated to promoting the transformation from one-dimensional (economic) growth to three-dimensional (economic, social and environmental) development.
As a cross-disciplinary, cross-sector and cross-border collaboration in innovation, the concept of SV brings back the focus on the core essence of value to promote sustainable development. It is aligned with the market principles of value creation, delivery and realisation, and encapsulates the bright ideal of encouraging microeconomic entities to contribute to economy, society and environment.
1.1.2 Logic Framework
Drawing on the rationale in developing information technologies, a three-layer structure, which consists of Infrastructures, Tools and Applications, is developed to visualise the logic framework of the SV Assessment System. The Infrastructures layer concerns “logic”, with a focus on aligning the sustainable development concepts with the prevailing mainstream value systems including public policies, academic theories and the far-reaching cultural heritages. The Applications layer examines “demand”, placing emphasis on applying SV to government governance, business operation and daily life. The Tools layer deals with what has been most urgently needed in a well-coordinated development of government, market and society-a set of applicable tools, especially the tools that are logically self-consistent and can be universally used.
Figure 1.1 SV Assessment Model
1.2 Measurement Tools
Having outlined the framework of the SV Assessment System, we need to have a closer look at how the assessment models are developed, verified and applied.
1.2.1 Development of Assessment Models
Sampling on the CSI 300 A-share listed companies and building on the methods of classification tree and logistic regression, the SV Assessment Model is developed with distinct value propositions to evaluate the overall economic, social and environmental contributions made by the assessed companies, using the “3A-3 Force” logical framework matrix: AIM|Driving Force, APPROACH|Innovation Force, and ACTION|Transformation Force.
The SV Assessment Model for Listed Companies is composed of Sub-model for Screening and Sub-model for Scoring as shown in the Figure 2. The Sub-model for Screening (See AppendixⅡ) is an assessment tool that comes up with a negative list for SV assessment. It makes “yes or no” judgements on the subjects drawing on 18 indicators from 6 aspects (Industrial Issues, Sector Issues, Financial Issues, Major Negative Accidents, Violation of Laws and Regulations, and Special Treatments). If any of the indicators is applicable to a company, the company will lose its eligibility for further quantitative rating. The Sub-model for Scoring (See Appendix Ⅲ) is used to quantify the SV they have created. It encompasses 3 tier-one indicators (AIM, APPROACH and ACTION), 9 tier-two indicators, 27 tier-three indicators and 55 tier-four indicators.
Details on the explanatory version of the assessment models are provided in the Discovering “SV 99”-A-share Listed Company SV Assessment Report (2017), covering indicators, model versions, rationale of the indicators, attribute tags, value weighting and assignment, evaluation criteria, and weight adjustment principles (See Figure 1.3). The operational version, which was granted IPR protection on 13 November 2017, specifies the approaches and rules of value weighting and assignment, definition and rationale of the indicators, selection of focused areas, multi-dimensional attribute tags, definition of assessment targets, principles of scoring and their interpretation, operating rules for scoring, scoring samples, standard procedures of production, criteria of data completeness and semantic analysis, and guides of data analysis, indexing and model optimisation. Some of the content in the operational manual for assessment models, which is under continuous optimisation, has been disclosed to contracting partners including rating, indexing and academic organisations, and foundations.
Figure 1.2 SV Assessment Model
To leverage the SV assessment tool to build the ecosystem of SDGs, CASVI has sought partnerships with:
Big-data service providers to handle the selection of social and environmental focused issues, indicator adjustment, and value weighting and assignment in the manner of “outsourcing + experts” instead of the expert-reliant pattern;
Academic institutions to build subdivided models to quantify the indicators of SV-driven product and service innovation, customer satisfaction, and supply chain management for the purpose of measuring SV in a more scientific way;
Policy makers to develop the assessment models into a supporting decision-making tool for market supervision and meso-economic regulation;
Financial partners to work jointly on the development and application of funds, bonds, trust and asset management products;
● International organisations to gradually conduct assessment and rating of overseas-listed China Concepts Stocks and foreign shares, and develop internationally applicable assessment criteria;
● Technological players specialised in big data and AI to optimise algorithms and realise automatic semantic analysis.
1.2.2 Assessment Models Governance
To ensure that assessment models are developed and applied in an open, just, impartial and fair manner, a three-layer governance structure comprised of discussion, decision and execution has been established and continuously improved.
At the discussion level, the Advisory Committee on Standards of SV Assessment (“the Advisory Committee”) provides comments and suggestions on the components and functioning of the models (such as core basis, topic selection, index development, data sources, and assessment results), while the Expert Committee on Standards of SV Assessment (“the Expert Committee”) reviews major issues, including the reorientation of the models and the launch/cancellation of projects.
Figure 1.3 SV Assessment Model
Figure 1.4 Joint Modelling by Stakeholders
At the decision level, the Working Committee on Standards of SV Assessment (“the Working Committee”) is in charge of making decisions on daily issues such as adjusting model components and optimising functioning rules. The Working Committee is comprised of four working groups, each responsible for preliminary reviews of agenda respectively related to the models, assessment monitoring, product application and data. Led by the Working Committee, these working groups are open to eligible external experts. Decisions are made by majority vote through a process convened by the head of the Working Committee, and are effectively disclosed to the public.
Figure 1.5 SV Assessment Governance Structure & Principle of Work
At the execution level, the Project Team of SV Assessment (“the Project Team”) is responsible for project implementation specifically in four aspects: i) providing and collecting feedbacks on comments or suggestions raised by the Advisory Committee; ii) preparing relevant information on major issues for the Expert Committee to review; iii) implementing resolutions of the Working Committee; and iv) performing assessment jointly with data and technology service providers.
As of 31 October 2018, there were 84 members in the Advisory Committee, including 15 foreign nationals; 33 members in the Expert Committee, including 3 foreign nationals; and 11 members in the Working Committee, including 2 foreign nationals. All of them provide pro bono services as think tank members under the Code of Honour emphasising public good and professional expertise and the Confidentiality Agreement prohibiting conduct for personal gains or disruption of the market, which they all signed before their membership comes into effect. The Project Team keeps a record of the amount of time they have contributed and the value they have created in a time bank-based administration system.
1.2.3 Validation of Assessment Models
As Confucius said, “Great tools make good work.” To make the SV Assessment Model a great tool, we need more than a precise value proposition, rigorous logic framework and strict working process. Given that even economics is excluded from the realm of science by Karl Popper’s Falsification Principle and that the measurement of economic value remains controversial, any quantification of social well-being and environmental value can hardly be broadly accepted. Empirical cases from China and elsewhere (such as the Chinese time-honoured brands, the American Nifty Fifty constituents, and the globally prevailing sharing economy) and statistical analyses (research findings provided by professors of Oxford University or the University of Pennsylvania)-however many are made available-are inadequate to convince people that the mutually reinforcing DW & DG is a positive sum game.
Therefore, we have shifted our perspective to the assumption that “SV is a positive sum game”, based on which the SV of listed companies is assessed, to identify from a market perspective how investors have converted their “capital votes” into SV. Then, data mining technologies are used to examine the effectiveness of these assessment models through three-dimensional, clustering, correlational and regression analyses.
Figure 1.6 Back-testing on SV 99 Index and Important News on Capital Market
1.2.3.1 Market Back-testing
With the support and guidance of the Advisory Committee, the Expert Committee and the Working Committee, the Project Team completed in August 2018 the assessment of the SV of selected companies over the past five years, SV 99 indexing and the back-testing of the Index.
As the world’s first index on SV, the SV 99 Index is a total return index measuring the performance of SV 99 companies (See Chapter V). We have back-tested the Index over a five-year period by setting a base point of 1,000 points started from 16 December 2013. As shown by the back-testing results, the Index has been on the rise over the 5 years and hit its climax of 2,492.75 points on 23 January 2018. In particular, the Index outperformed the ChiNext Index on 23 November 2016, and has since then been running higher than all the mainstream A-share indices for 8 consecutive quarters.
To examine how investors’ capital votes are converted into SV, the SV 99 Index is analysed through the following four comparisons.
According to the benchmark comparison, the SV 99 Index shows a higher growth than CSI 300 in 15 of the 19 quarters, an indication that the SV Assessment Model can perform stably in selecting the best among the best.
According to the horizontal comparison, the SV 99 Index outperforms mainstream A-share indices such as SSE 50, CSI 300, CSI 800, Shanghai Composite Index, ChiNext and SCI with increasingly larger margins, showing that the SV Assessment Model is strong in identifying value. The comparison accurately reflects the tendency towards tightened financial risk management, contained speculation and a return to value-based investment.
According to the internal comparison of the SV 99 Index with the Middle 99 and Bottom 99 simulated indices, each comprised of 99 CSI 300 companies categorised by their SV scores, the results suggest a stable monotonicity of the three indices and a distinction among them since February 2016, validating the effectiveness of the SV Assessment Model.
According to the decomposition analysis of the SV Assessment Model on indicators categorised into the SV 99 Economic Index, the SV 99 Transformation Force Index and the SV 99 Driving Force + Innovation Force Index, the SV 99 Index comprised of all indicators demonstrates the highest growth rate, indicating that capital investment and stock prices are not only determined by the listed company’s economic performance, but also by its contributions to social well-being and environmental protection, as well as its innovation capabilities and value proposition.
In addition to the comparative analyses, the SV 99 Index is also studied in the context of major incidents on the capital market. The results show that the SV 99 Index has maintained a steady growth despite new rules on directional add-issuances, pledges and asset regulation in concern of risk management, and significant benefits such as the RMB’s inclusion in the SDR basket and the partial inclusion of A shares in MSCI Emerging Markets Index, suggesting that the SV 99 companies have achieved robust growth no matter they are in a bearish or bullish trend in the short term.
The performance of the capital market during the back-testing period reflects that the SV concept, aiming at sustainable development and marked by DW & DG, is gradually accepted and practiced by more investors through increase of stock share purchase.
1.2.3.2 Data Analysis
Under the guidance of the Advisory Committee, the Project Team completed the SV Data Analysis Report in May 2018 to verify the effectiveness of the models using 3D distribution, focus analysis, relevant indicator analysis and regression analysis.
According to the 3D spatial distribution analysis, the companies scoring high on AIM (Driving Force) often score high on both APPROACH (Innovation Force) and ACTION (Transformation Force), which means, specifically, the companies that show strong driving forces, namely, with a clear-cutting value system, long-term strategic planning, and appropriate business positioning, often show strong innovation and transformation forces as well; and those scoring high on ACTION (Transformation Force) often score high on APPROACH (Innovation Force) as well, meaning, specifically, the companies that show strong transformation forces, namely, with remarkable comprehensive economic, social and environmental contributions, are often strong players in innovation as well.
In general, the analysis shows the significance of AIM, APPROACH and ACTION as integral indicators in examining the performance of listed companies. In other words, a company is less likely to achieve sustainable development if its value system, innovation mechanism, and action capability are separate from or even inconsistent with each other.
According to the clustering analysis where the CSI 300 companies are ranked by their SV scoring, the top 79 companies in the ranking as a group record an average SV scoring of 60.48, those ranking from 80 to 181 as a group record an average of 48.90, and the rest 39.82. The analysis shows scoring groups that are close to those of the SV 99, the Middle 99, and the Bottom 99, verifying in a way the validity and effectiveness of the scoring groupings of the 99 listed companies, which are beneficial to investors’ portfolio management.
According to the analysis of indicator relevance, the total market value, net asset and total amount of tax payment are indicators showing relevance percentages greater than 50%, while the other 52 indicators show lower relevance, suggesting that indicators are selected in a comprehensive and balanced way. As the CSI 300 listed companies represent large-cap stocks (Intretech, which is ranked with the lowest market value, has a market value of RMB 14.7 billion), they are all strong in economic performance, and score high in relevance of economic indicators. Given that the models will be applied to China’s A-share listed companies which differ greatly in economic performance, the economic indicators that show relevance percentages greater than 50% remain unchanged.
According to the regression analysis where the SV score is an independent variable, and the yearly rate of return is a dependent variable, the two variables have been positively correlated over the past three years. That is, for every 1 score increase in SV performance, the yearly return rate of “SV 99” increased by 1.66% in 2016, 0.43% in 2017, and 0.66% in 2018, showing that the companies with stronger ability to create SV are better able to liquidate through stocks.
Despite the stock market seems to be unpredictable in the short-term, the SV and stock returns keep growing in tandem according to the fundamental analysis of a company’s long-term economic, social and environmental value creation capabilities. The assumption that “SV is a positive sum game” has been verified through market back-testing and data analysis, showing that DW & DG are not only a global consensus and a national strategy in China, but also the way of doing business and making investment.
1.2.4 Application of Assessment Models
As a measurement tool of comprehensive value and also the carrier of sustainable development as a concept, the assessment models are developed from practical applications for the purpose of serving practical needs, providing a basis for delivering the SV performance rating, the SV 99 Index, and the SV 99 Ranking.
Figure 1.7 A-share Listed Companies SV Rating
1.2.4.1 SV Credit Rating
To enable institutional investors to incorporate SV into their investment decisions, increase the awareness of listed companies about the idea of DG and DW, and provide regulators with insights into how national policies are implemented, CASVI, in cooperation with Wind, China’s leading financial data and analysis service provider, released on 17 September 2018 the world’s first rating of SV performance of A-share listed companies.
The SV performance rating comprises 10 basic categories at four levels, or AAA, AA, A, BBB, BB, B, CCC, CC, C, and D, and 10 subdivided categories marked with the symbols of + and-, or AA+, AA-, A+, A-, BBB+, BBB-, BB+, BB-, B+, and B-, for specifying slightly better or worse performance based on the broad categories.
In the rating, the highest rated SCI 300 listed company in 2018 is China State Construction Engineering (CSCE) at AA+ (no company in A-share has been rated AAA so far). The number of listed companies rated AA or above (high SV rating) has increased from 2 in 2016 to 22 in 2018; the number of companies rated BBB or above (SV investment rating) has increased from 94 in 2016, and 104 in 2017 (up 10.64% year-on-year) to 167 in 2018 (up 60.58% year-on-year). In 2017 and 2018, the companies in the SV 99 Ranking are all rated at or above BBB.
It is noteworthy, however, that the number of D-rated listed companies removed from the SV Assessment Model for Listed Companies has increased from 3 in 2017 to 25 in 2018, indicating a growing gap in SV performance among CSI 300 listed companies.
Table 1.1 CSI 300 Listed Company SV Credit Rating
Table 1.1 CSI 300 Listed Company SV Credit Rating-Continued
Figure 1.8 SV 99 Index on the Wind Financial Terminals
1.2.4.2 SV 99 Index
To enable institutional investors to make informed investment decisions on portfolio management, CASVI and Wind jointly launched the SV 99 Index (CI003004) on the Wind Financial Terminal on 6 November 2018 to show the dynamic relationship between the SV creation capability and the stock prices of companies listed in SSE and SZE. Detailed information about the calculation method, updating frequency, back-up sample and candidate enterprise list of the Index is provided in Appendix Ⅷ.
The SV 99 Index not only provides an indicator to monitor the correlationship between SV performance and stock price, but also acts as a financial tool for index-related ETF development.
1.3 SV 99
SV 99 is an annual ranking of China’s A-share listed companies in terms of their SV performance or contributions to sustainable development. The ranking is based on an assessment of CSI 300 constituent companies using the SV Assessment Model and drawing on publicly accessible information and cross-validated data. Initiated by CASVI, it is a cross-sectors and cross-disciplinary collaboration among pro-bono experts from home and abroad, data and technology service providers, and the Project Team.
Why are CSI 300 constituents selected as the first batch for SV measurement? What are the overall features of SV 99 companies? The explaination can be found in the following sections.
1.3.1 Universe Selection
The sample group as the basis for assessment modelling is selected by the following criteria: i) data availability; ii) measurability of results; and iii) model verifiability and optimisability.
Data availability. In the quantified assessment of SV, data unavailability, especially non-financial information insufficiency or absence, is a worldwide challenge. According to the database monitoring from the Project Team, among the 3,467 A-share listed companies by the end of 2017, only 841 (24%), have published their non-financial information reports (including reports on CSR, SV, sustainable development, ESG, etc.). If all A-share companies are quantitatively assessed in terms of their SV performance, only 14% of them are above the 80% threshold level of data completeness. In comparison, 243 (81%) CSI 300 companies have published specific reports on their non-financial information. This results in a data completeness of 80% among all CSI 300 companies.
Measurability of results. On the updated list of the CSI 300 companies as of June 2018, 186 companies are listed in SSE and 114 in SZE, with 234 on the main board, 50 on SME board, and 16 ChiNext. According to the CSI classification, 13 companies are from the energy sector, 37 from materials, 60 from industry, 38 from consumer discretionary, 13 from consumer staples, 22 health care, 56 finance, 15 real estates, 29 IT, 6 telecommunication services, and 11 utilities, covering all economic sectors. CSI 300 companies account for up to 55.71% of the total market value of all A-share listed companies.
According to the assessment model, financial indicators, such as the Operating Profit Margin and Total Tax Paid, need to be scored through peer and category comparisons. Representing all sectors and categories of business, CSI 300 companies provide a good basis for quantitative scoring.
Model verifiability and modification. As a leading index in the A-share market, CSI 300 is highly mature and stable. This guarantees reliable methods and data for the market back-testing and technical analysis, which lay a solid foundation for effective validation and optimisation of the assessment model.
In addition to the sample qualifications for modelling, the CSI 300 constituents are selected more importantly in terms of its “head effect”. According to the 80/20 principle discovered in the late 19th century by the Italian economist Vifredo Pareto, it is advisable to focus “limited resources” on the “key minority” at the initial stage of any product going from zero to one. CSI 300 companies are the exact “key minority” in this sense.
As shown in the above figure, calculated by output value, China’s GDP in 2017 was RMB 82.17 trillion. In the same year, the total revenue generated by all A-share listed companies was RMB 38.97 trillion (47.12% of GDP)[7], among which 25.01 trillion was from CSI 300 companies (30.24% of GDP), and RMB 17.74 trillion was from SV 99 companies (21.45% of GDP). That is, the combined revenues of the SV 99 listed companies contributed to 1/5 of the national GDP. For more accurate comparison and analysis, the value added calculated using the income approach created by all A-share listed companies in the same year reached RMB 10.00 trillion (12.08% of GDP), among which RMB 7.36 trillion was from CSI 300 companies (8.90% of GDP), and RMB 5.51 trillion was from SV 99 companies (6.66% of GDP).
Figure 1.9 China Domestic Economy and SV 99 Listed Companies
The statistics clearly show the strong “head effect” of CSI 300 companies in the national economy. Starting from this, a closed-loop validation of the SV assessment is completed in four steps.
Step 1: Find out the “head” contributors to the national economy (CSI 300) using available data and methods;
Step 2: Measure the comprehensive economic, social and environmental contributions made by the head companies according to the assessment models;
Step 3: Select the highest-rated group (“SV 99”) based on the quantitative SV assessment;
Step 4: Analyse the approach to SV creation and sustainable development by looking into the features of SV 99, the market back-testing results and the macro policy environment.
1.3.2 Group Features
On 15 December 2017, the first SV 99 ranking was launched by CASVI; on 17 September 2018, the 2018 annual ranking was unveiled. To conduct the market back-testing and verify the effectiveness of the assessment model, the Project Team completed in the first half of 2018 the annual rankings for the years of 2014, 2015 and 2018, making available the SV 99 rankings for 5 consecutive years from 2014 to 2018. The group features of SV 99 companies are outlined in this Part, and a detailed analysis is presented in Part II from four dimensions: basic profile, benchmarks, industry and index.
1.3.2.1 Total SV and its Structure
In 2018, both SV 99 and CSI 300 companies recorded a significant increase in their total SV score over 2017, with CSI 300 companies at a sharper rate than SV 99 companies. As shown in Table 1.2, SV 99 companies score 6,544 in total, 556.31 higher than the previous year, with an average score of 66.10, 5.62 higher than 2017, up 9.29%. CSI 300 companies score 16,699.89 in total, 1,781.72 higher than the previous year, with an average score of 55.67 points, 5.94 higher than 2017, up 11.94%. This indicates strengthened overall capabilities of China’s “head”, or leading, listed companies in creating SV.
From the perspectives of the model structure, in terms of AIM (Driving Force), SV 99 companies score 659.17 points, 183.47 higher than the previous year, up 38.57%; while CSI 300 companies score 1,761.50, 614.61 higher than the previous year, up 53.59%. In terms of APPROACH (Innovation Force), SV 99 companies score 1,943.73 points, 168.63 higher than the previous year, up 9.50%; while CSI 300 companies score 4,939.42, 572.26 higher than the previous year, up 13.10%. In terms of ACTION (Transformation Force), SV 99 companies score 3,941.10 points, 204.21 higher than the previous year, up 5.46%; while CSI 300 companies score 9,998.97, 594.84 higher than the previous year, up 6.33%. It is clearly found that in 2018, SV 99 companies have made significant progress in the 3 Forces. The most significant improvement is observed in terms of the value system of the companies, that is, the SV 99 companies score 3,941.10 points, 204.21 higher than the previous year.
1.3.2.2 Coefficient of Consistency and Variation
To identify whether an assessed company has practiced DW & DG consistently throughout its corporate structure from the upper (mission, vision & values), through the middle (technologies, products & services) to the lower (organisation, talent & performance) layers, the coefficient of consistency and variation between its scores on AIM (Driving Force), APPROACH (Innovation Force) and ACTION (Transformation Force) is calculated to reveal the level of consistency and synergic effects within the company.
Statistics show that the average consistency coefficient of SV 99 companies in 2018 rises by 8.53 percentage points over last year to 87.53%, compared to 83.19% among CSI 300 companies, which is up by 8.33 percentage points. Among SV 99 companies, Chongqing Changan Automobile (000625.SZ) and Zhejiang Huayou Cobalt (603799.SH) record the highest consistency coefficient at 99%, while Anhui Conch Cement (600585.SH) and Haitong Securities (600837.SH) represent the lowest at 71%. Overall, the consistency coefficients of all SV 99 companies are within a reasonable variance range, with 4.34 percentage points higher on average than those of CSI 300 constituents; and the top 10 SV 99 companies show an average consistency coefficient of 93.30%, 10.11 percentage points higher than their CSI 300 counterparts.
Table 1.2 Comparison of SV Performance
This suggests that with greater consistency between AIM, APPROACH and ACTION, a company is more likely to achieve synergies among 3 Forces, which translate to stronger capabilities for SV creation, and ultimately, more substantial contributions in comprehensive economic, social and environmental terms.
Table 1.3 Consistency Coefficient Comparison
From 2014 to 2018, 41 listed companies have ranked consecutively on the annual SV 99 list. Of them, 31 are state-owned enterprises (SOEs), 6 are privately-owned enterprises (POEs) and 4 with other ownership structures. In particular, CSCE has topped the list for 5 years in a row. It is also noteworthy that, despite the market turbulences and fierce competitions, six POEs-Shanghai Fosun Pharma, China Ping An, Ping An Bank, Suning.com, TBEA and Midea Group-have remained on the list in each of the past 5 years.
In terms of leadership, among the 41 companies that have made the list all 5 years, 20 have their chairpersons of the board serving successive terms, including Wang Dongsheng at BOE, Liu Qitao at China Communications Construction Company (CCCC), Tan Xuguang at Weichai Power, Nie Kai at China Gezhouba Group and Chen Qiyu at Shanghai Fosun Pharma. Generally, the sustainable development of a company needs to be guided by a visionary leader who thinks big, stays strategically focused, and is able to serve long terms.
Compared to the previous year, 31 companies have moved up in the 2018 SV 99 Ranking (See Table 2.1), while 36 have moved down, and 30 are new entrants, presenting a fairly balanced situation. CSCE (601668.SH) tops the ranking list for the 5th consecutive year, with its SV score rising by 4.06 points over last year to 80.61. Among the companies on the 2018 ranking, 64 (64.65%) are SOEs, an increase by 5 over 2017, while the number of POEs remains at 25 (25.25%). The fact that SOEs account for nearly two thirds of all ranked companies relates to the composition of the CSI 300 community in the same year, where SOEs represent 53.66% of all constituent companies.
1.3.2.3 Performance in DW & DG
To unveil the SV 99’s features in DW and DG, these companies are categorised into four groups according to the assessment of their performance in terms of economy, society and environment: i) Companies excel in pursuit of both DW & DG; ii) Companies register outstanding DW performance; iii) Companies stand out in DG performance; iv) Companies feature balanced performance in DW & DG.
As shown in the 2018 SV 99 List (See Figures 2.1 and 2.2), 23 companies excel in pursuit of both DW & DG, including CSCE, Agricultural Bank of China (ABC) and Lomon Billions, up by 16 over last year. They record higher market value and lower PE ratios compared to other CSI 300 and A-share companies.
Meanwhile, 28 companies register outstanding DW performance, including China Merchants Shekou Industrial Zone Holdings (CMSK), Qingdao Haier and Shanghai International Port Group (SIPG), down by 20 over last year; 27 companies stand out in DG performance, including BOE, CCCC and China Unicom, up by 15 over the previous year; and 21 companies feature balanced performance in DW & DG, including PetroChina, PowerChina and Beijing OriginWater Technology, down by 11 over last year. On the whole, the ranked companies are moving from “balanced performance in DW & DG performance” to “excellence in both DW & DG”, with a more significant improvement in terms of DG performance.
Ever since the concepts of responsible investment and impact investment were introduced in early 21st century, the relations among revenue, impact and risk have been discussed globally among the industry, academic communities and governments. In this context, the 2018 SV 99 community is analysed from 3 perspectives: DW performance (economic benefits), DG performance (social & environmental contribution), and risks (risk management).
DW Performance
In terms of economic contribution, the average revenue of SV 99 in 2018 reaches RMB 179.19 billion, which is 2.13 and 15.94 times that of CSI 300 companies and all A-share companies respectively, and represents a year-on-year increase of 4.52%, compared to a 17.48% increase recorded by CSI 300 constituents and 12.23% by all A-share companies.
The average net profit of SV 99 is RMB 21.05 billion, which is 2.22 and 20.36 times that of CSI 300 and A-share companies respectively, and represents a 4.62% year-on-year increase from last year, compared to an 18.19% increase recorded by CSI 300 constituents and 20.79% by all A-share companies.
The average market value of SV 99 stands at RMB 215.79 billion, which is 1.84 and 12.17 times that of CSI 300 and A-share companies respectively, and represents a 2.42% year-on-year rise, compared to a 9.05% increase recorded by CSI 300 companies, and a 4.44% drop by all A-share companies.
The average PE ratio of SV 99 registers 13.47, which is 78% and 54% that of CSI 300 and A-share companies respectively, and represents a year-on-year increase of 25.07%, compared to a 22.97% increase recorded by CSI 300 companies and a 1.54% fall by all A-share companies.
The average dividend yield ratio of SV 99 is 2.66%, which is 1.23 and 1.60 times that of CSI 300 and A-share companies respectively, and represents a year-on-year decline of 0.2 percentage points, compared to a 0.26 percentage point decrease recorded by CSI 300 companies and a 0.01 percentage point rise by A-share companies.
Table 1.4 DW Comparison
In terms of average revenue and net profit, SV 99 companies outperform CSI 300 companies by over 2 times and A-share companies by 15 to 20 times, demonstrating their strong capabilities to achieve financial returns, despite a year-on-year growth rate lower than CSI 300 companies.
In terms of average PE ratio, SV 99 companies trade at 13.47 times earnings, 3.82 lower than CSI 300 companies, yet at a 2.1 percentage point higher annual growth rate.
The results indicate that SV 99 companies are major economic contributors, sharing the benefits with investors directly through dividends. While most blue chip companies record a substantial increase in their valuation, SV 99 companies-as the best among the best-generally demonstrate a sharper growth rate in valuation than CSI 300 companies.
DG Performance
The DG performance of SV 99 is analysed from the perspective of their social and environmental contributions. Specifically, “social contribution” are evaluated in terms of Value to Customers & Users, Employee’s Rights and Interests, Operation Safety, Business Partnership and Contribution to Public Good; while “environmental contribution” are measured in Environmental Management, Green Growth and Pollution Prevention & Control.
In terms of social contributions, as measured by percentile ranking, SV 99 companies in 2018 score the highest in Operation Safety (85.19%), followed by Contribution to Public Good (73.57%), Employee’s Rights and Interests (73.00%), Value to Customers & Users (71.97%) and Business Partnership (68.35%), averaged at 74.41%. This suggests that Operation Safety is most emphasised in SV 99 companies, as evidenced by the fact that strict management mechanisms for safe production are generally in place to effectively prevent serious safety incidents. The results reveal a balanced performance in Contribution to Public Good, Employee’s Rights and Interests, and Value to Customers & Users; while performance in Business Partnership, with “supply chain management” and “fair operation” at the core, falls short of excellence.
With respect to performance improvement, their percentile rankings in descending order are: Contribution to Public Good (21.83%), Business Partnership (15.38%), Value to Customers & Users (2.97%), Operation Safety (2.25%) and Employee’s Rights and Interests (0.44%). The results display an unbalanced improvement in the five aspects, with the most significant in Contribution to Public Good and the least in Employee’s Rights and Interests. This reflects, to some extent, that these head companies have proactively responded to policies yet failed to integrate such actions into the core of their value creation.
Table 1.5 DG Comparison
In terms of environmental contributions, SV 99 companies in 2018 record the highest percentile ranking in Pollution Prevention & Control (64.35%), followed by Environmental Management (58.55%) and Green Growth (50.08%), averaged at 58.29%, 16.12 percentage points lower than the average in social welfare contributions, indicating a significant variance in the level of maturity in the 2 perspectives on the DG dimension.
With respect to performance improvement, their percentile rankings in descending order are: Environmental Management (18.48%), Pollution Prevention & Control (3.32%) and Green Growth (-0.80%). According to the results, under the three major incentives-institutional (management system and procurement policy), financial (environmental input, etc.), and compliance (environmental penalties, etc.), these head companies have made great efforts to improve their “weak hand” in Environmental Management. In terms of Pollution Prevention & Control, indicators show that the head companies focus most of their environmental efforts on the management of waste water, waste gas and solid waste, as well as greenhouse gas emission control and climate change adaptation as defined in the Paris Agreement. The lowest score is observed in Green Growth, where a negative growth is recorded, revealing a general lack of awareness in integrated energy consumption management, water resources and material consumption management and green office, especially in areas such as how to create green opportunities in major business operations.
For listed companies, making environmental contributions is a gradual process increasing in difficulty. From the practical point of view, pollution prevention & control involves the most direct actions; when it comes to environmental management, companies need to improve their institutional systems and incorporate such activities into budget programmes, which may cause difficulties; and the implementation of green growth requires strategic adjustment and even re-organisation of product and service systems, which are especially challenging for mature companies. Despite these challenges, however, both SV 99 and CSI 300 companies have demonstrated varying degrees of positive improvements.
The analysis shows that in both economic terms and the contributions to social welfare and environmental protection, SV 99 companies outperform CSI 300 companies, and are far ahead of all A-share companies.
Risk Prevention & Control
Risk-related indicators from the Sub-model for Scoring are selected to measure the risk prevention and control capabilities of SV 99 companies.
In terms of the risk management mechanism, the assessment is focused on examining the listed companies performance in their internal governance and emergency management. SV 99 companies score 82.07% in 2018, 9.13 percentage points higher than CSI 300 companies, despite a slight decrease from the previous year. In terms of solvency, the liquidity, leverage ratio and net asset of listed companies are what measurement is focused on. SV 99 companies score 66.02% in 2018, 3.55 percentage points higher than CSI 300 companies, despite a small drop from last year.
In view of the dramatically increasing risks related to the pledging of shares, a comparison among SV 99, CSI 300 and all A-share companies is made in terms of their practice of share pledging, using available data from the China Securities Depository and Clearing Corporation Limited. Up to 95 of the SV 99 companies have pledged their shares, with the only exceptions being China CITIC Bank (CNCB) (601998.SH), PetroChina (601857.SH), Red Star Macalline (601828.SH) and Intretech (002925.SZ), representing a 96% coverage, compared to 97% among CSI 300 companies, and 98% among all A-share companies. This validates a conclusion that in the A-share Market “virtually all listed companies have their shares pledged”.
The proportion of shares pledged by SV 99 companies averages 6.37%, 4.12 percentage points lower than CSI 300 companies, and 1.41 percentage points higher compared to the previous year. The figure among SOEs in the SV 99 community is 1.28%, 1.62 percentage points lower than that in the CSI 300 community and 0.52 percentage points lower compared to the previous year; the figure among POEs in the SV 99 community is 17.44%, 3.05 percentage points lower than that in the CSI 300 community and 5.84 percentage points higher compared to last year. It can be seen that although SV 99 companies have pledged their shares to raise loans, the proportion is lower than that of CSI 300 companies and far below that of all A-share companies, with no risk incidents triggering margin calls or forced liquidations.
The comprehensive analysis of financial return, risk and performance shows that SV 99 companies outperform CSI 300 companies and are far ahead of A-share companies in financial returns, risk management and external effect, where a strong positive correlation is calculable. Yet, additional time is needed for data accumulation and tracking research to identify whether there is a reciprocal causation among the three factors.
Table 1.6 Comparison of Risk Control Performance
1.4 Summary
The year 2018 marks the 40th anniversary of China’s reform and opening up. During 40 years of sweeping changes, China’s GDP calculated at constant prices has grown by 33.5 times, doubling every 8 years, and it has risen as the world’s second largest economy after overtaking the UK in 2006 and Japan in 2010. In the same period, the gross national income (GNI) per capita in China has increased by 44.0 times from USD 200 to USD 8,805; while its poor population (living on less than $1.25/day) has dropped sharply from 770 million to 30.46 million, and affluent Chinese travelers are increasingly seen as big spenders across the world. Despite some controversies, no one can deny the fact that in the 40 years of breathtaking changes, the market economy has liberated productivity, and fast-paced economic growth has led to the country’s development in every field.
However, while China celebrates its “40 years of growth”, it should not be forgotten that as a country with 5,000 years of civilisation, it still has many 40 years to go in the future. Unlike its one-way growing economy, the planet we live on is a resource-limited, physically closed ecosystem. For the well-being of future generations, it is imperative that we take the path of qualitative improvement instead of quantitative expansion.
Discovering China’s SV 99, in this sense, is to find a group of leading market players going beyond growth and driving sustainable development.
[1] SDGs refers to Sustainable Development Goals adopted on 25 September 2015 by 193 member states at the UN Summit on Sustainable Development held at the UN Headquarters in New York, which aim to substantially address the world’s systemic economic, social, and environmental challenges from 2015 to 2030.
[2] CDV refers to China’s Five-Pronged Development Vision, which was proposed at the 5th Plenary Session of the 18th CPC Central Committee. As stressed by the plenary, China should highlight and implement the concepts of innovation-driven development, balanced development, green development, open development and development for all, in order to fulfill the goals of the 13th five-year period, overcoming obstacles and sharpening its edge in development.
[3] The Protestant Ethic and the Spirit of Capitalism (German: Die protestantische Ethik und der Geist des Kapitalismus) is a book in the social sciences written by Max Weber, a German philosopher. Begun as a series of essays, the original German text was composed in 1904 and 1905, and was later included in The Sociology of Religion.
[4] Arthur C. Pigou was known as the father of welfare economics. As a rewritten and revised edition of his Wealth and Welfare published in 1912, The Economics of Welfare aims to “study certain important groups of causes that affect economic welfare in actual modern societies”.
[5] A Theory of Justice is a work of political philosophy and ethics by John Rawls, a professor at Harvard University. It has rich content and requires in-depth philosophical thinking. The book not only reflects the major controversial issue in the Western academic circles in the 20 years, but also deeply manifests the contradictions in Western society, providing a reference for readers to think about justice.
[6] Beyond Growth: The Economics of Sustainable Development is a masterpiece of the famous American eco-economist Herman E. Daly in theory of environmental economy and sustainable development, playing an important role in the environmental protection and development since the 1990s.
[7] Some of the data in the report may differ slightly from the figures obtained directly using the four fundamental rules of arithmetics, and the errors are due to rounding-off.