The micro-evidence of innovation: data and research applications. Micheline Goedhuys. UNU-MERIT, Maastricht, Netherlands
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1 The micro-evidence of innovation: data and research applications Micheline Goedhuys UNU-MERIT, Maastricht, Netherlands
2 Overview of lecture 1. The rise of survey methods 2. OECD Oslo manual and innovation surveys 3. Use of innovation survey data for research 4. World Bank enterprise surveys 5. Applications 6. Conclusion
3 1. The rise of survey methods End 1980s, 1990s rising interest to analyse innovation from an innovation system perspective investigating the black box of innovation at the firm or micro level Firms interact with clients, suppliers, other firms, research institutes and government Innovation results from multiple inputs, feedbacks and interactions This does not become clear from the traditional measures of science and technology in a linear view of innovation
4 Traditional measures R&D statistics Measures input Does not capture well innovative activity in small firms Externally developed technology improvements (software) do not show up in these statistics Patenting Records inventions Sector differences in patenting activity Intl. differences in criteria for granting patents Patent citations
5 1 The rise of innovation surveys Systemic nature of innovation calls for firm level information, as key agents of innovation Need to understand the innovation process in firms need for indicators capturing non-r&d activities and incremental change Surveys are important to stimulate research on innovative behavior of firms to feed into the policy process Monitoring and evaluation of policies
6 2. OECD Oslo manual and innovation surveys Harmonisation of survey efforts in the Oslo Manual, 1992, 1997, 2005 basis for consecutive rounds of Community Innovation Surveys (CIS-1, CIS-2, CIS-3, CIS-4, CIS-2006, CIS-2008, CIS-2010, CIS-2012). CIS 2010 conducted in EU Member States, plus Norway and in candidate states, Iceland, Serbia and Turkey. CIS 2010 responses from 818,816 enterprises (Innovation core NACE activities, B-M71_INN), 52.6% innovative Became standard for innovation data collection.
7 Increasing number of countries, sectors (services), types of innovation (product, process, mkt, organisational) Influenced design of innovation surveys in other countries, including Australia, Canada, China, Japan, New Zealand, Russia, Africa, Switzerland and the USA (Arundel and Smith, 2013).
8 Oslo Manual based Questionnaire: eg CIS-2012 General information about the enterprise: linkage with foreign groups, geographic markets Did your firm introduce any new or improved products or services/processes new to you? new to your market? %sales of innovative products
9 Innovation activities R&D intramural R&D extramural Acquisition of machinery Acquisition of external knowledge Training Market introduction Design YES/NO and expenditures Government support, policy or incentives affecting innovation
10 Sources of information for innovation Cooperation or collaboration for innovation (with competitors, customers, universities, government) Organisational innovation: new business practices (eg q management, supply chain management ), new methods for organising work responsibilities and decision making, new methods of organising external relations Marketing innovation: design, promotion, placement, pricing Goals and impact of innovations to reach goals Obstacles to reach goals Employment and sales evolution over 3 years % employees with tertiary education
11
12 Use of innovation survey data for research: CIS The CIS provides a rich data source for academic research. First data available to academics in 1994 and 1995 Since 2004, UNU-MERIT (Arundel, Bordoy, van Cruysen, Es-Sadki, Hollanders and Kanerva) has constructed and maintained a database of all published studies, in English, that use the CIS data. As of May 2014, MERIT has identified 663 studies that use data from CIS-1, CIS-2, CIS-3, CIS-4, CIS-2006, CIS or CIS-2010.
13 Papers using Community Innovation Survey data ( )
14 Number of studies Research themes over time, Who innovates Innovation strategies How much Effects on performance Who innovates: Main innovation activities Expenditures Characteristics of the firm 35 How much: Innovation sales shares Innovation strategies: Knowledge sourcing IPR and appropriation Effects on performance: Turnover Number of employees Modules (environmental inno, creativity and skills, Strategies and obstacles to growth) Publication year
15 Number of studies Papers using eco-module CIS 2008 data ( ) Annual count Cumulative Number Publication year
16 16 Africalics Academy Algiers 22-Oct-2013 Oslo Manual and innovation in developing economies Characteristics of innovation in developing countries: Less private and more informal RD Fragmented flows of information Market structure : Small firm size and informality, foreign and state ownership Barriers to innovation: uncertainty, infrastructure, lack of awareness, lack of government support instruments
17 17 Africalics Academy Algiers 22-Oct Oslo Manual and innovation in developing economies Importance of incremental innovation; Organisational and marketing innovation; Importance of innovation embodied in machinery and equipment (dissemination) Importance of agriculture; increased knowledge intensity in resource based sectors Need to measure capabilities, HC
18 Conclusion CIS and CIS-like surveys have stimulated innovation research at the micro level Academics continue to be interested in each version of the CIS, esp. in different questions included in each survey. The one-page particular topics increase academic use of CIS data. The narrow focus of innovation surveys has also limitations for research
19 2.2. Enterprise surveys countries, 130,000 firms Since 2002 (and earlier) cover a broad range of business environment topics Coverage: survey of firms that is meant to be representative of a country's non-agricultural economy. Separate manufacturing and services modules 5+ employees
20 2.2. Enterprise surveys Core Questionnaire 1. General information 2. Infrastructure and services 3. Sales and supplies, incl. exports 4. Competition and innovation 5. Capacity 6. Conflict resolution/legal environment 7. Crime 8. Business-government relations 9. Finance 10. Labor relations, incl. skills level, training 11. Investment climate constraints to the establishment 12. Productivity, incl. 3 year production, sales, expenses;
21 Enterprise surveys innovation module New effort to collect innovation data at micro level Data available for Bangladesh, DRC, Ethiopia, Ghana, India, Kenya, Malawi, Namibia, Nepal, Nigeria, Pakistan, Rwanda, South Sudan, Sudan, Tanzania, Uganda, Zambia, Zimbabwe, more upcoming As a follow up survey to the enterprise survey On a random subsample (eg 75% of the firms of the ES sample in Bangladesh) data can be merged with regular ES data
22 Product - process marketing organisational innovation For product innovation: #, % of sales For the main product and process innovation: qualitative description, goals, degree of novelty, origin of the idea, collaboration, effect on employment Organisational innovation: various questions on management practices, performance monitoring, target setting, incentives schemes
23 Expenditures on : Internal R&D External R&D Training Acquisition of machinery, equipment, software Purchase or licensing of a patent Government support Source of finance Source of ideas Use of ICT
24 Example 1: Analysis of Innovation strategies in Tanzania Strong correlation of innovation with R&D, ICT, skills, investment and collaboration, but different innovation strategies for local and foreign firms. Goedhuys, M., 2007, Learning, product innovation and firm heterogeneity in developing countries, evidence from Tanzania, Industrial and Corporate Change, 16,
25 Example 2:Innovation and firm growth in Brazil How do firms in Brazil innovate: technology make or buy or both? The buy and make and buy option proved most succesful. Does product or process innovation or a combination lead to firm growth? Product innovation far more succesful. Goedhuys, M., Veugelers, R., 2012, Innovation Strategies, Process and Product Innovations and Growth: Firm-Level Evidence from Brazil, Structural Change and Economic Dynamics, 23,
26 Example 3 : Innovation and productivity Explaining productivity with technological (innovation) variables and other more institutional variables Innovation and techno variables (product innovation, process innovation, R&D, technology licensing) failed to explain differences in productivity in Tanzania In contrast management HC, quality certification, membership of business association, health of workforce, administrative burden, credit constraints, Goedhuys, M., Janz, N., Mohnen, P., 2008, What drives productivity in Tanzanian manufacturing firms: technology or business environment?, European Journal of Development Research, 20,
27 27 Africalics Academy Algiers 22-Oct-2013 Example 4: Innovation and productivity Does level of development of the country influence the return on innovation efforts? Sectoral versus national systems of innovation Study on firm productivity in food, textiles and garments and leather, in Ecuador, Brazil, Tanzania, South Africa and Bangladesh Goedhuys, M., Janz, N., Mohnen, P., 2013, Knowledgebased productivity in low-tech industries: evidence from firms in developing countries, Industrial and Corporate Change.
28 Example 5: Innovation and productivity How important are national and institutional factors (research infrastructure, education, politics and governance, GDP/cap) in explaining TFP: Directly Indirectly by moderating the relationship between technological efforts and productivity Multilevel model, 42 countries, firms, micro and macro variables
29 Firm level model: TFP ij = 0j + 1j R&D ij + 2j TRN ij + 3j ISO ij + 4j FOR ij + 5j lnage ij + e ij Country level model: 0j = TECH j + 02 EDU j + 03 GOV j + 04 POL j + u 0j 1j = TECH j + 12 EDU j + 13 GOV j + 14 POL j + u 1j 2j = TECH j + 22 EDU j + 23 GOV j + 24 POL j + u 2j 3j = TECH j + 32 EDU j + 33 GOV j + 34 POL j + u 3j 4j = TECH j + 42 EDU j + 43 GOV j + 44 POL j + u 4j 5j = TECH j + 52 EDU j + 53 GOV j + 54 POL j + u 5j
30 Direct positive impact of education, research infrastructure, governance and policital stability on TFP Positive influence on firm R&D returns ISO, training of workers are more rewarding in LDCs and the foreign-local productivity gap is larger. Goedhuys, M., Srholec, M., Understanding multilevel interactions in economic development, UNU-MERIT WP Goedhuys, M., Srholec, M., Technological capabilities, institutions and firm productivity, EJDR, 2014.
31 Conclusion Survey data provide rich information on innovation in firms, the key actors in the innovation process From there interesting insight for the regional, national or sectoral or technological system of innovation can be derived Innovation surveys : survey standard, but narrow in scope limited for academic research data of enterprise performance are limited other factors influence the performance of firms (OVB)
32 Enterprise(+innovation) surveys: Broader scope; Available data Too many questions reduce data quality Limited samples and representativeness Conduct your own survey Tailored to your reseach question, population... Original approach or measure of innovation Costly
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