Moscow January 21 2015 An overview of STI

Moscow January 21, 2015 An overview of STI statistics and indicators Giorgio Sirilli ISCr. ES - CNR

Outline of the presentation STI indicators STI policy The actors Models of innovation Manuals Uses and abuses of indicators Concluding remarks 2

Science, technology and innovation Science is the reasoned investigation or study of phenomena, aimed at discovering enduring principles among elements of the phenomenal world by employing formal techniques such as the scientific method Technology is the collection of tools, including machinery, modifications, arrangements and procedures used by humans Innovation is the process practical application of knowledge translating an idea or invention into a good or service that creates value or for which customers will pay 3

Indicators Statistic: A numerical fact or datum, i. e. one computed from a sample. Statistical data: Data from a survey or administrative source used to produce statistics. Statistical indicator: A statistic, or combinations of statistics, providing information on some aspect of the state of a system or of its change over time. (For example, gross domestic product (GDP) provides information on the level of value added in the economy, and its change overtime is an indicator of the economic state of the nation. ) 4

Indicators are a technology, a product, which - governs behaviour - is modified by users (outside of the producer community) - develops in response to user needs Data sources – Surveys, administrative data, private files, case studies – Data collection is informed by manuals Data populate statistics which can be indicators Decisions are taken on the basis of indicators 5

Science and technology indicators S&T indicators are defined as “a series of data which measures and reflects the science and technology endeavor of a country, demonstrates its strengths and weaknesses and follows its changing character notably with the aim of providing early warning of events and trends which might impair its capability to meet the country’s needs”. Indicators can help “to shape lines of argument and policy reasoning. They can serve as checks, they are only part of what is needed”. (OECD, 1976) 6

Lord Kelvin “If you can not measure it, you can not improve it. ” Lord Kelvin 7

Hariolf Grupp “If you can not measure it, don’t talk about it. ” Ariolf Grupp 8

The evolution of STI indicators The first attempt to measure S&T in 1957 Frascati Manual (1963) The Frascati manual “family” A continous process of broadening and deepening: from macro to micro, from public to private The role of international organisations The dialogue between producers and users 9

Science and technology policy A history which starts after WW 2 1940 s science 2010 s technology innovation jobs 10 competitiveness social needs

Science and technology policy Report “Science the Endless Frontier” 1945 (Vannevar Bush) 11

“Science the Endless Frontier” Concerns: Military security; Health Solution: Science policy “The Government is particularly fitted to perform certain functions, such as the coordination and support of broad programs on problems of great national importance” “Scientific progress on a broad front results from the play of free intellects, working on subjects of their own choice, in the manner dictated by their curiosity for exploration of the unknown. Freedom of inquiry must be preserved under any plan for Government support of science” 12

“Science the Endless Frontier” “Publicly and privately supported colleges and universities and the endowed research institutes must furnish both the new scientific knowledge and the trained research workers. It is chiefly in these institutions that scientists may work in an atmosphere which is relatively free from the adverse pressure of convention, prejudice, or commercial necessity. At their best they provide the scientific worker with a strong sense of solidarity and security, as well as a substantial degree of personal intellectual freedom. ” “Industry is generally inhibited by preconceived goals, by its own clearly defined standards, and by the constant pressure of commercial necessity. Satisfactory progress in basic science seldom occurs under conditions prevailing in the normal industry laboratory. ” 13

The triangle in STI policy making Policy makers design the future Analysts interpret today Data producers measure the past 14

Policy makers Luigi Einaudi Italian President “Conoscere per deliberare” Know first and then sanction 15

Policy makers President Roosevelt 16 Vannevar Bush Report “Science the Endless Frontier” 1945

Policy makers “Why shoud we pay the researchers if we make the best shoes in the world? ” Silvio Berlusconi “Culture does not provide food” (Con la cultura non si mangia) Giulio Tremonti 17

The relationship between producers and users After WWII the main issue in STI policy was the social responsibility of science. Now the attention is placed on the social return of investment on STI and, in particular, on innovation and social objectives Weak innovation theories do not allow a straighforward interpretation of indicators A tension: the simplification of policy makers (e. g. the 3% R&D/GDP ratio) versus deepening of analysts The time dimension: demand of indicators and analyses (quick and dirty) but …. the construction of indicators is a “heavy ship” (more than 10 years to build) 18

Producers of indicators OECD Group of ‘National Experts on Science and Technology Indicators’ - NESTI

NESTI: Working Party of National Experts on Science and Technology Indicators (1962) Mission: Produce methodologies, statistics and analyses Co-ordinating body Clearing house 20

International organisations active in STI indicators OECD and member countries Eurostat and the relevant Commission DGs and member states of the EU UNESCO United Nations Institute of Statistics RICYT and member countries NEPAD is moving in this direction 21

The role of OECD in the development of S&T measurement in the 1960 s In the 1960 s few countries collected data on S&T The OECD offered a ready-made model for those who had not yet developed the necessary instruments Standardisation was proposed by an international organisation and not by a specific country The Frascati Manual was introduced with a petits pas strategy - the first edition was an internal document only (1962) - the Manual was tested (1963 -1964) in many countries - it was revised in light of the experience gained from the surveys The Frascati Manual has never been an imperative document: countries are totally free to apply its conventions No harmonised questionnaire 22

United Nations Fundamental Principles of Official Statistics Official statistics provide an indispensable element in the information system of a democratic society. They need to be compiled and made available on an impartial basis by official agencies. To retain trust in official statistics, the statistical agencies need to decide according to strictly professional considerations on methods and procedures. To facilitate a correct interpretation of the data, the statistical agencies are to present information according to scientific standards on the sources, methods and procedures of the statistics. 23 Source: UN Statistical commission

United Nations Fundamental Principles of Official Statistics Data for statistical purposes may be drawn from all types of sources, be they statistical surveys or administrative records. Individual data collected by statistical agencies are to be strictly confidential and used exclusively for statistical purposes. The laws, regulations and measures under which the statistical systems operate are to be made public. Coordination among statistical agencies is essential. 24 Source: UN Statistical commission

The “dangerous” business of statisticians What matters is not how one fashions things, but what one does with them; not the weapon, but the battle (…). The making and the using of the tool are different things. O. Spenger, Man and Technics: A Contribution to a Philosophy of Life, 1932 25

Indicators community The members of the indicators community have to play the difficult game of finding a proper balance between data collection, analysis and policy making – preserving their intellectual integrity 26

Models of innovation Indicators make sense in the context of models Linear Chain-linked Triple helix Open innovation 27

The Linear model of innovation Research Development Design • Based on research • Sequential • Technocratic Engineering Production

The Chain-linked model of innovation Research • Ricerca Knowledge Potential • Mercato market • potenziale Invention/ Detailed • analytical Invenzione/ • Progettazione project • progettazione • dettagliata project & test e • analitica • test Re-design & production Distribution • Distribuzione & market • e mercato Based on design Interactive Research is not a pre-requisite for innovation

The Triple-helix model of innovation 30

The Triple-helix model of innovation Government-sponsored Research Institutes Research for public purposes Applied research Universities Supply scientists & engineers Curiosity-driven Basic research Firms Commercialisation Produce innovation 31 Development (R&D))

Open innovation 32

Open innovation 33

Open innovation 34 OECD Science, Technology and Industry Scoreboard, 2013

Open innovation 35 OECD Science, Technology and Industry Scoreboard, 2013

Open innovation 36 OECD Science, Technology and Industry Scoreboard, 2013

Relationship between research, develoment and innovation Overlapping area Commercialisation Basic research Experimental development R&D Intellectual property rights INNOVATION Technical assistance Applied research 37 Industralisation Distribution Production

What is a Manual? Manuals are codified knowledge They are guidelines for the collection and interpretation of data and for international comparisons of data, statistics and indicators. They are supported by an international infrastructure (ISIC, ISCED and ISCO) Manuals provide a language of discourse and they behave like a technology (our guiding assumption) 38

The OECD “Frascati Manual family” 1. The Measurement of Scientific and Technical Activities: Proposed Standard Practice for Surveys of Research and Development. Frascati Manual (2002) 2. Proposed Guidelines for Collecting and Interpreting Technological Innovation Data Oslo Manual (2005) 3. Patent Statistics Manual (1994) 4. Manual on the Measurement of Human Resources in Science and Technology Canberra Manual (1995) 5. Proposed Standard Practice for the Collection and Interpretation of Data on the Technological Balance of Payments (1992) ________________________ Bibliometrics Manual 39

The OECD “Frascati manual family” 40

Other related manuals and classifications System of National Accounts – SNA (CEC et al. , 1994) International Standard Industrial Classification – ISIC Rev. 3. 1 (UN, 2002) Statistical Classification of Economic Activities in the European Community – NACE Rev. 1. 1 – series 2 E. Nomenclature for the analysis and comparison of scientific programmes and budgets (NABS 2007) 41

The Frascati Manual 42

Freeman: the first edition of the Frascati Manual (1962) Freeman proposed standardised definitions, concepts, methodologies for conducting R&D surveys and measuring inputs, namely money devoted to R&D and S&T personnel. Four topics: - definition of research (basic, applied, development) - demarcation with other S&T activities (teaching, production, etc. ), - economic sectors (university, government, industry, pnp) - surveying methodology The underlying model: linear 43

The R&D data Money 1. Expenditure (GERD) 2. Budget appropriations (GBAORD) 44 People

Frascati Manual: The definition of R&D Research and experimental development (R&D) comprise creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of knowledge to devise new applications Basic research Applied research Experimental development 45

Frascati Manual: the definition of R&D personnel All persons employed directly on R&D should be counted, as well as those providing direct services such as R&D managers, administrators, and clerical staff Researchers Technicians and equivalent staff Other supporting staff 46

Oslo Manual Harmonised questionnaire 47

Types of innovation Product innovation (goods and services) Process innovation Marketing innovation Organisational innovation 48

Types of innovation A product innovation is the introduction of a good or service that is new or significantly improved with respect to its characteristics or intended uses. This includes significant improvements in technical specifications, components and materials, incorporated software, user friendliness or other functional characteristics. A process innovation is the implementation of a new or significantly improved production or delivery method. This includes significant changes in techniques, equipment and/or software A marketing innovation is the implementation of a new marketing method involving significant changes in product design or packaging, product placement, product promotion or pricing. An organisational innovation is the implementation of a new organisational method in the firm’s business practices, workplace organisation or external relations. 49

Types of innovation 50

Innovation: the system approach A systems approach Actors: Governments, education and health institutions, business, foreign institutions Activities: R&D, invention, innovation, diffusion of technologies and practices, HR development Linkages: Contracts, collaborations, co-publication, grants, monitoring Outcomes: Wealth, growth, jobs Impacts: Wellbeing, culture change, global influence The activity of innovation is dynamic, complex, non-linear and global 51

Use of indicators Monitoring Benchmarking Foresight Evaluation Research 52

Use of indicators Monitoring: Comparing the values of a set of indicators over time Some questions: • How much does the government spend on STI? • Where does it spend it (geography and industry)? • Why does it spend it (socio-economic objectives)? • What does the government get for spending this money? Some Publications: • European Innovation Scoreboard • OECD STI Scoreboard • OECD Science, Technology and Industry Outlook 53

Use of indicators Monitoring: Comparing the values of a set of indicators over time Indicators: • Innovation • R&D • Capital investment • Intellectual property rights • Learning • Education • Design 54

Use of indicators Benchmarking: 1. Decide upon a set of indicators which are relevant to policy objectives, and then decide about targets to be achieved 2. Agree on a set of indicators and then select another system which is performing better Examples: Ranking of countries and institutions The 3% Lisbon target and ensuing policies (focus the public debate) 55

R&D intensity in Italy: the Fata Morgana of 3% 3, 0% 1, 5% 1. 2% • 1960 56 • 1970 • 1980 • 1990 • 2000 • 2010 • 2020 • 2030 • Dagli anni 60 ad oggi il rapporto R&S/Pil è rimasto invariato, intorno all’ 1, 1%. Si può prevedere che nei prossimi anni rimarrà agli stessi livelli o che possa aumentare lievemente (l’ 1, 5% teoricamente possibile è rimasto una chimera). L’obiettivo di Lisbona e Barcellona è stato clamorosamente mancato non soltanto in Italia, ma anche in Europa, anche se è stato riconfermato dai capi di governo per il prossimo futuro.

Use of indicators Foresight: viewing the future involving a mix of quantitative and qualitative evaluation methods, including a set of a current set of indicators. Discern likely paths for emerging technologies, possible futures for an economic region, or alternative responses to a coming problem such as the country should function when the oil runs out. Indicators provide a background to the process but in general are too aggregated 57

The use of indicators Evaluation: concerns the effective and efficient use allocation of resources in order to achieve a set of objectives Various methods: Quantitative (bibliometric analysis, turnover from new products, audits, etc. ) and qualitative (peer review) Research Assessment Exercise in the UK (now Research Excellence Framework VEDERE) 58

Composite indicators 59

EU Summary Innovation Index Composite indicator (25 indicators) 3 25 60

The EU Summary Innovation Index 61

Summary Innovation Index The EU innovation performance indicator 62

Summary Innovation Index (ctd) 63

Summary Innovation Index for EU countries 64

Profile of Italy 65

Global innovation performance 66

Innovation performance of Russia 67

Innovation performance of Russia 68

The Stiglitz report In February 2008, the President of the French Republic, Nicholas Sarkozy, asked Joseph Stiglitz , Amartya Sen, and Jean Paul Fitoussi to create a Commission, subsequently called “The Commission on the Measurement of Economic Performance and Social Progress”. The Commission’s aim has been to identify the limits of GDP as an indicator of economic performance and social progress, including the problems with its measurement; to consider what additional information might be required for the production of more relevant indicators of social progress; to assess the feasibility of alternative measurement tools, and to discuss how to present the statistical information in an appropriate way.

"Gdp and beyond" Equitable and sustainable well-being 12 domains 1. Health 2. Education and training 3. Work and life balance 4. Economic well-being 5. Social relationships 6. Politics and Institutions 7. Security 8. Subjective well-being 9. Landscape and cultural heritage 10. Environment 11. Research and innovation 12. Quality of services

"Gdp and beyond" Equitable and sustainable well-being 1. 2. 3. 4. 5. 6. Features of the composite indicator Comparisons across space Comparison across time Non-substituability on elementary indicators Simplicity and transparency in calculation Immediate use and easy interpretation of results Robustness Methodology “Corrected MPI”, Mazziotta M. , Pareto A. (2013). A Noncompensatory Composite Index for Measuring Well-being over Time. Cogito. Multidisciplinary. Research Journal, vol. V, n. 4

Equitable and sustainable well-being 1. Intensity of research: Percentage of R&D expenditure on GDP. 2. Propensity to patent: Number of patent applications filed to the European Patent Office (EPO) per million of inhabitants. . 3. Impact of knowledge workers on employment: Percentage of persons employed with university education (ISCED 5 -6) in scientific-technological occupations (ISCO 2 -3) on total persons employed. 4. Innovation rate of the productive system: Percentage of firms that have introduced technological (product or process), organizational or marketing innovation in a three-year period on total number of firms with at least 10 number of persons employed.

Equitable and sustainable well-being (ctd) 5. Innovation rate of product/service of the national productive system: Percentage of firms that have introduced innovations of product/service in a three-years period on total number of firms with at least 10 number of persons employed. 6. Productive specialization in knowledge-intensive sectors: Percentage of persons employed in high-tech manufacturing sectors and those in knowledge-intensive services on total of persons employed. 7. Intensity of Internet use: Percentage of people aged 16 -74 years who have used internet at least once a week during the 12 months before the interview on total people aged 16 -74 years.

Ranking of universities Four major sources ARWU Shangai (Shangai, Jiao Tong University) QS World University Ranking THE University Ranking (Times Higher Education) US News e World Reports (Best Global Universities)

Academic Ranking of World Universities Shanghai Jiao Tong University “Starting from 2003, ARWU has been presenting the world Top 500 universities annually based on a set of objective indicators and third -party data. ARWU has been recognized as the precursor of global university rankings and the most trustworthy league table. ARWU adopts six objective indicators to rank world universities, including: -the number of alumni and staff winning Nobel Prizes and Fields Medals, -the number of Highly Cited Researchers, -the number of articles published in journals of Nature and Science, -the number of articles indexed in Science Citation Index Expanded and Social Sciences Citation Index, and -per capita performance. More than 1200 universities are actually ranked by ARWU every year and the best 500 universities are published. ”

Top UNIVERSITIES Worldwide university rankings, guides & events Criteria selected as the key pillars of what makes a world class university: Research Teaching Employability Internationalisation Facilities Social Responsibility Innovation Arts & Culture Inclusiveness Specialist Criteria

Top UNIVERSITIES Worldwide university rankings, guides & events Research Indicators considered here include assessments of research quality amongst academics, productivity (i. e. number of papers published), citations (i. e. how recognized and referred to those papers are by other academics) and awards (e. g. Nobel Prizes or Fields Medals). Teaching A key role of a university is the nurture of tomorrow's finest minds, inspiring the next generation of potential research academics. Typical indicators in teaching quality assessments are collation of student feedback through national student surveys, further study rate and student faculty ratio. Employability Graduate employability encompasses more than academic strength, focusing on ‘work-readiness’ - the ability to work effectively in a multi-cultural team, to deliver presentations, to manage people and projects. Common indicators in this area are surveys of employers, graduate employment rates and careers service support. Internationalisation Here, effective indicators could be the proportion of international students and staff, the numbers of exchange students arriving and departing, the number of nationalities represented in the student body, the number and strength of international partnerships with other universities and the presence of religious facilities. Facilities University infrastructure is an indicator which enables students to know what to expect from their university experience. Indicators such as sporting, IT, library and medical facilities, as well as the number of students societies are considered within this criterion. Online/Distance learning This category looks at various indicators such as student services and technology, track record, student faculty engagement, student interaction, commitment to online and reputation of the university. Social Responsibility Engagement measures how seriously a university takes its obligations to society by investing in the local community as well as in charity work and disaster relief. It also analyses the regional human capital development and environmentally awareness. Innovation, the output of the universities activities and findings to economy, society and culture, has become increasingly relevant for universities. Arts & Culture Effective indicators are the number of concerts and exhibitions organized by the institution, the number of credits and cultural awards and cultural investment. Inclusiveness This area looks at the accessibility of the university to students, particularly at scholarships and bursaries, disability access, gender balance and low -income outreach. Specialist Criteria Excellence in a narrow field is as valid a claim to world-class status as competence in the round. These criteria are designed to extend credit where it's due. This category looks at accreditations and discipline rankings.

Ranking of universities: the case of Italy ARWU Shangai (Shangai, Jiao Tong University) QS World University Ranking THE University Ranking (Times Higher Education) US News e World Reports (Best Global Universities) ARWU Shangai: Bologna 173, Milano 186, Padova 188, Pisa 190, Sapienza 191 QS World University Ranking: Bologna 182, Sapienza 202, Politecnico Milano 229 World University Ranking SA: Sapienza 95, Bologna 99, Pisa 184, Milano 193 US News e World Report: Sapienza 139, Bologna 146, Padova 146, Milano 155

OECD Science, Technology and Industry Outlook, 2008

OECD Science, Technology and Industry Outlook, 2008

OECD Science, Technology and Industry Scoreboard, 2013

OECD Science, Technology and Industry Outlook, 2008

OECD Science, Technology and Industry Scoreboard, 2013

OECD Science, Technology and Industry Outlook, 2008

OECD Science, Technology and Industry Scoreboard, 2013

OECD Science, Technology and Industry Outlook, 2008

OECD Science, Technology and Industry Scoreboard, 2013

OECD Science, Technology and Industry Scoreboard, 2013

OECD Science, Technology and Industry Scoreboard, 2013

Clusters 90

Use of indicators (Benoit Godin) As OECD admitted: “Monitoring and benchmarking are not coupled with policy evaluation (…). They are seldom used for evaluation purposes (…) but to analyse [counties’] position vis -à-vis competing countries and to motivate adaptation or more intense policy efforts (…). ” “Official statistics mainly served discourse purposes, and in this sense the accounting framework and the statistics presented within it were influential because they fit perfectly well with the policy discourse on rationality, efficiency and accountability: it aligns and frames the science system, by way of statistics, as goal-oriented and accountable. As it actually is, the accounting in official statistics on science is a metaphor, not an accounting exercise as such” 91

A rhetoric device: a plethora of figures and graphs “In the various studies on productivity and the New Economy the OECD constantly reminded the reader that the links between science, technology and productivity have not been demonstrated”. “A large series of graphs and figures could persuade the reader of the seriousness of the study. Although no statistics could be used to prove the emergence of the New Economy, graphs and figures nevertheless served the purpose of empiricism”. (Godin, 2004) 92

Use of indicators (Benoit Godin) The rhetoric of numbers Policy prescriptions based on shaking statistical evidence (New Economy) The “umbrella” concept, slogans, buzzwords, which shape new ways to arrange old indicators 93

A rhetoric device: a plethora of figures and graphs “Secure a quantitative statement of the critical elements in an official’s problem, draw it up in concise form, illuminate the tables with a chart or two, bind the memorandum in an attractive cover tied with a neat bow-knot (…). The data must be simple enough to be sent by telegraph and compiled overnight” (Mitchell, 1919) 94

The mystique of ranking GERD is used for target setting - from descriptive to prescriptive “The American GERD/GDP ratio of the early 1960 s, that is 3%, as mentioned in the first paragraphs of the first edition of the Frascati Manual, became the ideal to which member countries would aim, and which the OECD would implicitly promote” (Godin) Lisbona UE 3% (2% business, 1% public sector) 95

OECD Science, Technology and Industry Outlook, 2008

Keith Pavitt “One would think that the political agenda determines the collection and analysis of indicators. In reality it is the other way round: it is the availability of indicators which steers the political discourse. ” 97

Fred Gault “Policy analysts should be both literate and numerate, able to put a case using innovation indicators. Not only should the analysits have such a skill set, but they also require some knowledge of the subject. It is in this environment that monitoring, benchmarking and evaluation lead to policy learning and to more effective policies. ” 98

The policy advisor Advising has become the preserve of applied economists (no more physicists and sociologists) Advisors need to be – and to appear – experts who guarantee a competent and independent approach The compromise between engagement and integrity of analysts Frustration of advisors is part of the game The paradox: too many or too little indicators? The pressure of vested interests on official statisticians 99

Innovation expenditure. The Oslo Manual R&D = 55% 100 R&D = 38%

A dilemma for users • BERD (Frascati), Annual, all NACE industries, no size threshold • CIS (Oslo), selected NACE industries, 10 employees or more, sample • 80% • 60% • 40% • BERD-CIS R&D difference • (2010, manufacturing, • percentage) • 20% • P ol • C and ro • E ati st a on i • I a t • F aly • L ran it hu ce • R an om ia a • N • Ir nia et ela he n rl d a • F nd in s la n • S d pa • M in • D a en lta • B ma ul rk • S gar lo ia va • C ze • B ki ch elg a R ium ep • P ub or lic • H tug un al • S ga lo ry ve • C nia yp r • L us at vi a • 0% • -20% • -40% • -60% 101

Research Evaluation of what: research education “third mission” of universities and research agencies (consultancy, support to local authorities, etc. ) Evaluation by whom: experts, peers Evaluation of what: organisations (departments, universities, schools) programmes, projects individuals (professors, researchers, students) Evaluation when ex-ante in-itinere ex-post 102

Research Evaluation Indicators used - bibliometrics - R&D - peer review - students - graduates - patents - spin-offs - contracts and other funding - other 103

Evaluation in Italy New public management Accountability Value for money National Institute for the Evaluation of the Education and Training System 104

San Francisco Declaration on Research Assessment The Journal Impact Factor, as calculated by Thomson Reuters, was originally created as a tool to help librarians identify journals to purchase, not as a measure of the scientific quality of research in an article. With that in mind, it is critical to understand that the Journal Impact Factor has a number of well-documented deficiencies as a tool for research assessment. These limitations include: A) citation distributions within journals are highly skewed; B) the properties of the Journal Impact Factor are field-specific: it is a composite of multiple, highly diverse article types, including primary research papers and reviews; C) Journal Impact Factors can be manipulated (or “gamed”) by editorial policy; and D) data used to calculate the Journal Impact Factors are neither transparent nor openly available to the public. 105

San Francisco Declaration on Research Assessment General Recommendation Do not use journal-based metrics, such as Journal Impact Factors, as a surrogate measure of the quality of individual research articles, to assess an individual scientist’s contributions, or in hiring, promotion, or funding decisions. 106

Lessons from research evaluation Evaluation should enhance efficiency and effectiveness Evaluation is a difficult process Peer review vs bibliometrics NSE vs SSH Used to define financing and hiring/promoting staff League tables Pro-active evaluation vs punitive evaluation Competition vs cooperation of scientists Excellence Opportunistic behaviour and the split of the academic community Threat t othe equilibrium amongst the activities of the university Research Assessment Excercise (REF) in the UK

Concluding remarks After 50 years STI indicators are quite good International cooperation is key (the role of the OECD and EU) Support to non-OECD countries Further develop theoretical models and methodologies From macro to micro Keep the dialogue between actors alive More expertise: too many economists (philosophers, sociologists, other social scientists) Too many indicators? Resource constraints STI indicators are a public good, and the “owner” of statistics is the State The role of commercial data producers (e. g. bibliometrics) What to do with the misuse of indicators? Producers: stay creative, autonomous, and risk-taking 108

Thank you for your attention giorgio. sirilli@cnr. it