Changing innovation processes models: a chance to break out of path dependency for less developed regions

Transcription

1 Changing innovation processes models: a chance to break out of path dependency for less developed RSA Winter Conference 2013, London Gateway Empirical and conceptual understandings of how are mobilised Korneliusz Pylak, PhD Lecturer Department of Economics and Management of Economy Faculty of Management Lublin University of Technology POLAND

2 Presentation structure can we change? Research purpose what is next? Further research what can we do? where we are? Introduction is it possible? who can change? Main findings when and how? what did we measure? Methodology how did we measure? 2

3 The purpose of the research if and how less developed can change innovation processes models Used photo from: [RockefellerCenter] TO break out of path dependency [ and become rich]? 3

4 Source: own elaboration So, could it look like on this graph? 4

5 Source: Maddison, A., 2003, The World Economy: Historical Statistics, Paris, Organization for Economic Co-operation and Development. Allen, R. C., 2011, Global Economic History: A Very Short Introduction (Oxford University Press, New York) From the very beginning differences in prosperity were increasing dramatically The income gaps have expanded with only few exceptions The richest countries in 1820 have grown the most Differences in prosperity were very small Europe s GDP per capita was twice that much of the world Great Britain $1,706 USA, Canada $1,100-1,200 The rest of the world $ Africa $415 5

6 Growth factor, 1820 to 2008 Source: Allen, R. C., 2011, Global Economic History: A Very Short Introduction (Oxford University Press, New York), p. 4 The exceptions are Taiwan & South Korea Japan GDP per head in 1820 but also China 6

7 Source: Henning M., Stam E., Wenting R., 2013, Path Dependence Research in Regional Development: Cacophonyor Knowledge Accumulation?, Regional Studies 2013 Vol. 47, No. 8, p What is path dependency? continued behaviour similar to past behaviour, e v e n in settings where conditions of the business environment have changed dramatically a mechanism that drives one product to be dominant over others, SO: e v e n when a superior substitute is introduced at a later stage (i.e. QWERTY keyboard) initial conditions establish a trajectory REFERS TO: Product(s) Industry(ies) Region(s) Entire performance 7

8 But how locked-in can be unlocked? an event a shock coincidencies co-evolution in motion 8

9 Concept of co-evolution in motion process co-evolution Growth factor paths not taken new industries pool 9

10 Source: Wintjes, R. and H. Hollanders, 2010, The Regional Impact of Technological Change in 2020, Report to the European Commission, Directorate General for Regional Policy, on behalf of the network for European Techno-Economic Policy Support (ETEPS AISBL) Distribution of region groups due to the level of availability, absorption and diffusion of knowledge and technology Availability Low Medium High Absorption: Diffusion: low low Traditional Southern Skilled industrial Eastern EU Absorption: Diffusion: Absorption: Diffusion: medium medium high medium Knowledge absorbing Skilled technology Metropolitan knowledge intensive services Public knowledge centres Absorption: Diffusion: high high High-tech 10

11 Ability to exploit knowledge Level of absorption Source: own elaboration based on The World Bank, 2008, Global Economic Prospects. Technology Diffusion in the Developing World, Washington DC Concept of absorptive capacity of the region to fulfil the knowledge gaps Trade FDI Diaspora & other networks Existing technologies new to the market or to companies (technological frontier) Exposition Exposition Exposition Exposition Absorption Developing region Economies of scale Multiplier effects R e l a t e d v a r i e t y Absorption Absorptive capacity of the region Good governance and business climate Basic technological literacy The financing of innovative companies Pro-active policies Entrepreneurial discovery of specializations N e w t e c h n o l o g i e s Technological diversification process innovations N e w t e c h n o l o g i e s Technological hybridization Policies supporting competencies, infrastructure and innovation-friendly environment Policies supporting smart specializations radical product process radical innovations innovations innovations innovations P e r f o r m a n c e o f t h e r e g i o n 11

12 Public authorities Business Concept of co-evolution in regional innovation systems Favourable Environment Specializations Roles Roles Roles New business Part of the process models fostering of entrepreneurial radical innovations discovery S h a r e d c o m p e t e n c i e s Systemic impact S h a r e d c o m p e t e n c i e s Context s conditionalities Context s conditionalities Creativity Resource efficiency Discovery potential Science Civil society Roles Roles Roles 12

13 METHODOLOGY Research questions The subject of the research The phases of the research The method and techniques 13

14 Research questions Is path dependency imminent, or whether it is possible to implement the development paths in accordance with the evolutionary approach? in particular: 1. Is it possible to change the model of innovation processes taking place in a region (is it possible for a region to switch between models)? Is it possible for a region to break out of path dependency? 2. If so, what development paths can be identified in the period in the studied (what transitions between the groups are possible)? 14

15 Innovation process model definition OECD approach Gross Domestic Product (GDP) per capita (millions of USD PPP, current prices) Unemployment Rate (number of unemployed persons as a share of the labour force) Share of Employment in Manufacturing (Manufacturing, Mining and Quarrying, Electricity, Gas and Water Supply employees as a share of total employment) High and Medium-High Technology (HTM) Manufacturing as a % of Total Manufacturing (number of persons employed in high and medium-high technology manufacturing sectors as a percentage Gross Domestic Expenditure on R&D (GERD) as share of GDP (percentage points) Percentage of the Labour Force with Tertiary Education (persons with tertiary education ISCED 5 and 6 as a percentage of the total labour force) Business R&D Expenditure as a Share of Total R&D Expenditure (percentage points) Share of Employment in the Primary Sector (number of employees in Agriculture, Hunting, Forestry and Fishing as a share of total employment) Share of Employment in the Public Sector (number of employees in Public Administration and Defence, Compulsory Social Security, Education, Health, and Social Work, Other Community, Social and Personal Service Activities, and Private Households with Employed Persons as a share of total employment) Knowledge- Intensive Services (KIS) as a Percentage of Total Services (number of persons employed in knowledge-intensive service sectors PCT Patent Applications per Million Inh. (annual average over the last three years) Population Density of employment in the manufacturing as a percentage of employment in (persons per square km) 22/11/2013 sector) Changing the innovation service sector) processes models: 15

16 The subject of the study a set of 12 indicators (selected by OECD) that differentiate as per their innovation processes. The survey covered 240 (from 23 countries). The analysed period of time covered 17 years from 1995 to

17 The scientific approach The regional groupings 17 compilations (for each year separately) 1995 Unifying the groups same models (in each compilation) 1995 Analyse of the transitions 2011 of all development paths 22/11/2013 Changing innovation processes models: 17

18 The method and techniques For the regional groupings we used a hierarchical agglomeration method. In this case, the classification process of n objects began with the creation of n single-element cluster that in the next (n-1) steps were combined in another concentration, until one cluster containing all objects was achieved. The result of clustering could be represented by a dendrogram. Distances between the objects were measured using a Euclidean metric, and for creating clusters the Ward's method was used. It involves minimizing the variance of the intragroup and is recommended as a method to extract the most homogeneous concentration. The values of variables describing the have been standardized in order to compensate the classifying impact of each variable. 18

19 FINDINGS Innovation processes groups and models Transitions between models Conclusions Further research 19

20 Innovation processes groups and models KIS GROUP Knowledge intensive services-driven TNS GROUP Transition MAN GROUP Manufacturing-driven KIS.1 Knowledge-intensive city/capital districts KIS.2 Knowledge and technology hubs TNS.1 High education-driven transition TNS.2 Average performance MAN.1 High and Medium High Technology (HTM)- driven MAN.2 Primary-sector based manufacturing KIS.3 Knowledge and technology pretenders 20

21 Relative performance of the models MAN.1 Knowledge-intensive city/capital districts Knowledge-Intensive Services (KIS) as a Percentage of Total High and Medium-High Technology (HTM) Manuf. as % of Total PCT Patent Applications per Million Inhabitants Population Density Gross Domestic Product (GDP) per capita Gross Domestic Expenditure on R&D (GERD) as share of Business R&D Expenditure as a Share of Total R&D Share of Employment in Manufacturing Share of Employment in the Primary Sector Share of Employment in the Public Sector Percentage of the Labour Force with Tertiary Education Unemployment Rate 21

22 Relative performance of the models MAN.2 Knowledge and technology hubs High and Medium-High Technology (HTM) Manuf. as % of Total Manufacturing PCT Patent Applications per Million Inhabitants Knowledge-Intensive Services (KIS) as a Percentage of Total Services Population Density Gross Domestic Product (GDP) per capita Gross Domestic Expenditure on R&D (GERD) as share of GDP Business R&D Expenditure as a Share of Total R&D Expenditure Share of Employment in Manufacturing Unemployment Rate Share of Employment in the Primary Sector Share of Employment in the Public Sector Percentage of the Labour Force with Tertiary Education 22

23 Relative performance of the models MAN.3 Knowledge and technology pretenders Knowledge-Intensive Services (KIS) as a Percentage of Total Services High and Medium- High Technology (HTM) Manuf. as % of Total Manufacturing PCT Patent Applications per Million Inhabitants Population Density Gross Domestic Product (GDP) per capita Gross Domestic Expenditure on R&D (GERD) as share of GDP Business R&D Expenditure as a Share of Total R&D Expenditure Share of Employment in Manufacturing Unemployment Rate Share of Employment in the Primary Sector Share of Employment in the Public Sector Percentage of the Labour Force with Tertiary Education 23

24 Relative performance of the models TNS.1 High educated-driven transition Knowledge-Intensive Services (KIS) as a Percentage of Total Services High and Medium- High Technology (HTM) Manuf. as % of Total PCT Patent Applications per Million Inhabitants Population Density Gross Domestic Product (GDP) per capita Gross Domestic Expenditure on R&D (GERD) as share of GDP Business R&D Expenditure as a Share of Total R&D Expenditure Share of Employment in Manufacturing Unemployment Rate Share of Employment in the Primary Sector Share of Employment in the Public Sector Percentage of the Labour Force with Tertiary Education 24

25 Relative performance of the models TNS.2 Average performance Knowledge-Intensive Services (KIS) as a Percentage of Total Services High and Medium- High Technology (HTM) Manuf. as % of Total PCT Patent Applications per Million Inhabitants Population Density Gross Domestic Product (GDP) per capita Gross Domestic Expenditure on R&D (GERD) as share of GDP Business R&D Expenditure as a Share of Total R&D Expenditure Share of Employment in Manufacturing Unemployment Rate Share of Employment in the Primary Sector Share of Employment in the Public Sector Percentage of the Labour Force with Tertiary Education 25

26 Relative performance of the models MAN.1 High and Medium High Technology (HTM)- driven Knowledge-Intensive Services (KIS) as a Percentage of Total Services PCT Patent Applications per Million Inhabitants Population Density Gross Domestic Product (GDP) per capita Gross Domestic Expenditure on R&D (GERD) as share of GDP High and Medium- High Technology (HTM) Manuf. as % of Total Manufacturing Business R&D Expenditure as a Share of Total R&D Expenditure Share of Employment in Manufacturing Unemployment Rate Share of Employment in the Primary Sector Share of Employment in the Public Sector Percentage of the Labour Force with Tertiary Education 26

27 Relative performance of the models MAN.2 Primary-sector based manufacturing Knowledge-Intensive Services (KIS) as a Percentage of Total Services High and Medium- High Technology (HTM) Manuf. as % of Total PCT Patent Applications per Million Inhabitants Population Density Gross Domestic Product (GDP) per capita Gross Domestic Expenditure on R&D (GERD) as share of GDP Business R&D Expenditure as a Share of Total R&D Expenditure Share of Employment in Manufacturing Unemployment Rate Share of Employment in the Primary Sector Share of Employment in the Public Sector Percentage of the Labour Force with Tertiary Education 27

28 Regional innovation models changes existing development paths in Towards knowledge intensive services-driven models KIS Group Knowledge intensive services-driven TNS Group Transition TNS.2 Average performance TNS.1 High educationdriven transition KIS.3 Knowledge and technology pretenders 3 2 KIS.2 Knowledge and technology hubs KIS.1 Knowledge-intensive city/capital districts MAN Group Manufacturingdriven MAN.2 Primary-sector based manufacturing MAN.1 High and Medium High Technology (HTM)-driven Coloured numbers mean the number of the path changing cases 28

29 Regional innovation models changes existing development paths in Towards high and medium high technology-driven models KIS Group Knowledge intensive services-driven TNS Group Transition MAN Group Manufacturingdriven KIS.1 Knowledgeintensive city/capital districts TNS.2 Average performance KIS.2 Knowledge and technology hubs 3 KIS.3 Knowledge and technology pretenders TNS.1 High education-driven transition MAN.2 Primary-sector based manufacturing MAN.1 High and Medium High Technology (HTM)- driven 29

30 I n g o i n g r e g i o n s Percentage of in-coming and out-coming to/out the models from group KIS Percentage of all passing (to the given model) Given model Percentage of all outgoing (of the given model) [All passing to all the models = 100%] [All outgoing from all the models = 100%] KIS.3 Knowledge and technology pretenders TNS.1 High education-driven transition TNS.2 Average performance KIS.2 Knowledge and technology hubs 3% 3% 1% 6% TNS.1 High education-driven transition 16% TNS.2 Average performance 4% KIS.1 Knowledge-intensive city/capital districts KIS.2 Knowledge and technology hubs KIS.3 Knowledge and technology pretenders 6% 1% 3% 7% 6% KIS.3 Knowledge and technology pretenders TNS.1 High education-driven transition KIS.2 Knowledge and technology hubs TNS.1 High education-driven transition MAN.1 High and Medium High Technology-driven O u t g o i n g r e g i o n s Legend: Percentage of passing : 1% 2-5% 6-10% 11-16% Region groups: Knowledge intensive services (KIS)-driven Transition (TNS) Manufacturingdriven (MAN) MAN.1 High and Medium High Technology-driven 1% 5% MAN.2 Primary-sector based manufacturing 30

31 I n g o i n g r e g i o n s Percentage of in-coming and out-coming to/out the models from group TNS Percentage of all passing (to the given model) Given model Percentage of all outgoing (of the given model) [All passing to all the models = 100%] [All outgoing from all the models = 100%] KIS.2 Knowledge and technology hubs KIS.3 Knowledge and technology pretenders TNS.2 Average performance MAN.1 High and Medium High Technology-driven MAN.2 Primary-sector based manufacturing 1% 7% 9% 14% 3% TNS.1 High educationdriven transition TNS.2 Average performance 3% 16% 12% 1% 4% 9% 6% KIS.2 Knowledge and technology hubs KIS.3 Knowledge and technology pretenders MAN.2 Primary-sector based manufacturing KIS.2 Knowledge and technology hubs KIS.3 Knowledge and technology pretenders TNS.1 High education-driven transition O u t g o i n g r e g i o n s Legend: Percentage of passing : 1% 2-5% 6-10% 11-16% Region groups: Knowledge intensive services (KIS)-driven Transition (TNS) Manufacturingdriven (MAN) MAN.1 High and Medium High 1% Technology-driven MAN.2 Primary-sector based 22/11/2013 Changing innovation processes manufacturing models: 31

32 I n g o i n g r e g i o n s Percentage of in-coming and out-coming to/out the models from group MAN Percentage of all passing (to the given model) Given model Percentage of all outgoing (of the given model) [All passing to all the models = 100%] [All outgoing from all the models = 100%] KIS.3 Knowledge and technology pretenders TNS.2 Average performance MAN.2 Primary-sector based manufacturing KIS.3 Knowledge and technology pretenders TNS.1 High education-driven transition TNS.2 Average performance 6% 6% 1% 5% 12% 1% MAN.1 High and Medium High Technologydriven MAN.2 Primary-sector based manufacturing 1% 14% 2% 3% 1% KIS.3 Knowledge and technology pretenders TNS.1 High education-driven transition MAN.2 Primary-sector based manufacturing TNS.1 High education-driven transition MAN.1 High and Medium High 2% MAN.1 High and Medium High Technology-driven Technology-driven 32 O u t g o i n g r e g i o n s Legend: Percentage of passing : 1% 2-5% 6-10% 11-16% Region groups: Knowledge intensive services (KIS)-driven Transition (TNS) Manufacturingdriven (MAN)

33 Conclusions Results indicate that half of analysed experience path dependency break-throughs, which are both positive and negative the poorest have real problems to phase into better models, so it is really difficult to breakthrough a path dependency, but they still have a possibility (by tertiary education or high tech) While research indicates that the reasons for growth in the different models are different and hence there should be encouraged other factors in different stages of regional development the study also indicates that there might be an evolutionary staged process that might be worth researching further, especially when there is so much risk in the relevant conducting of the process. 33

34 Regional innovation models changes existing development paths in Towards knowledge intensive services-driven models KIS Group Knowledge intensive services-driven TNS Group Transition TNS.2 Average performance TNS.1 High educationdriven transition KIS.3 Knowledge and technology pretenders 3 2 KIS.2 Knowledge and technology hubs KIS.1 Knowledge-intensive city/capital districts MAN Group Manufacturingdriven MAN.2 Primary-sector based manufacturing MAN.1 High and Medium High Technology (HTM)-driven 34

35 Further research analyse separately policy for less developed (concepts developed for the growth of one region may not fit into other and even in the same region, but in a different period) discover a sparkle that initiated changes discover some macro and micro conditions that favoured changing the models identify key elements behind a successful policy oriented to change models analyse if and how specialisations influence changing the models analyse roles expected from each axe of the regional quadruple helix develop the context s conditionalities that have made possible new business models, especially regarding the role of regional public policy 35

36 Thank you for your attention! Korneliusz Pylak, PhD Lecturer Department of Economics and Management of Economy Faculty of Management Lublin University of Technology POLAND mob Contributed Ninetta Chaniotou, DEA Director for International Cooperation Projects Kainuun Etu Oy, FINLAND mob (0) /11/