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Rural development in a Knowledge Economy

by James Macaskill on Oct 15, 2010

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Thank you to the organising committee for the invitation to speak to you today. Transfer of knowledge economy in sustainable development and environmental protection Bucharest 8 th and 9 th October 2010
In looking at a model for sustainable rural development I will cover these points. As you will see it is a diverse canter around some of the key elements that influence how you choose to put your model together. What I would like to do today is identify some of the steps in developing any model trying to address sustainable rural economic development be built around ? A knowledge economy is a factor of access and relevance of knowledge. Given today’s digital revolution filtering and processing this information and translating into knowledge is a key elements if an assumed one in the current presentation. In doing so I will call upon my experience of running a variety of projects from the mid 90’s until today. Most of my work has been associated with markets that are in transition or are indeed fractured that is to say there has been a single or a series of dramatic discontinuities that has caused the existing market to fail. The list contains some of the major pragmatic drivers for change and in responding to these changes. The hardest lesson I learnt was to ensure you get the right champion and the right team together or you can seriously burn resources and ultimately end up failing.
The pace of change towards knowledge economies and the migration of production economies eastwards can be seen from the FDI league table. If you look at the ratio of FDI projects across Europe and the numbers of jobs created it reflects this migration and the implied value of the jobs created. These large FDI decisions tend to be single supply chain investments that trigger the growth of small just-in-time suppliers to these large economic investments. However, significant and profitable as some of these investments are on the local and regional economies, they are only sustainable in a local economic sense provided they also trigger a diversification of skills and markets for the suppliers locally and regionally. Otherwise as the FDI move further East the absence of a skills or knowledge legacy will prevent a timely economic rebound. If this embryonic knowledge economy is overly dependent on a single supply chain and does not capture knowledge and the ability to market its new skills then the fate of the local and regional economy is determined by the corporate decisions made in other countries. Think about the EU / USA car industry.
The withdrawal of FDI can dramatic and lead to immediate social and human capital issues of retaining expertise, in decreasing disposable income that deflates the economy or in general high local unemployment.
Global market swings influence the choice of market and the risk associated with the investment. Fortunately and consistently over the last three years CEEC along with China have been at the top of the FDI list. However, the fragility and security of these investments is highlighted by the retained growth in more stable economies. These make beneficiary economies vulnerable if they do not develop higher level skills and diversified knowledge based economy. While China now delivers the vast majority of global manufactured products where can it expand to other than stimulate internal level of consumption. So against this backdrop it can be seen that there is going to be a growing dependency on human capital and the potential to re-invent competitiveness based on the impact of these changes. In advanced economies over 50% of GDP will come from knowledge based industries and over 70% of company value might be assigned to knowledge or skill based assets. Therefore, a model that can create vital, viable and vibrant rural economies must support the diffusion of knowledge with a more diversified and sustainable economy while minimising single supply chain dependences.
In moving towards a rurally based knowledge economy it is a good idea to establish sources for the knowledge you might require. A range of sources are available but there are definite communities of practice that can provide appropriate knowledge. This knowledge can be local or global relevant and networks or communities of practice need to be viewed similarly. Of course all knowledge is good but comparative knowledge for economic development should be part of a quest. Howells (2002) [1] defines knowledge as “a dynamic framework or structure from which information can be stored, processed and understood” (Howells,J.R.L (2002) Tacit knowledge, innovation and economic geography. Urban Studies 39(5/6), 871-94) It is important to appreciate in a knowledge economy, knowledge is a product, while in a knowledge-based economy, knowledge is a tool. Both are relevant to transition economies.
Stokes model provides a basis for shaping the quest as a factor of the ultimate use for the knowledge obtained. This proves valuable when beginning to understand the drivers for change and how to influence the participants and the sources of knowledge to lay the foundations for how businesses and universities can work together to provide solutions for the quest. Understanding the relationship between these components of a knowledge economy will determine the success or failure for any collaborative model of sustainable rural economic development. For knowledge economies to work efficiently they require “gatekeeper” to work across boundaries of knowledge and technology to ensure informal and formal diffusion of knowledge. This role can also act as a barrier where knowledge retained is seen as power or an opportunity to broker a deal. Therefore, it is important to establish trust and value chains in this diffusion process to ensure that it is not abused. The importance of implicit and explicit knowledge in creating comparable and competitive advantage at local and regional levels will be touched on later. But suffice to say that explicit knowledge without the tacit understanding of how to make it work will again prove an unsatisfactory model. Gaining access to both is critical and lays the foundations for creating opportunities to “learn by doing”.
Repeated cycles of boom and bust have dramatic impact on urbanisation promoting migration from, sometimes to, rural communities and the consequential deskilling and the aging of the populations. In my experience social capital migrations directly follow persecution, market liberalisation or fracture and the deskilling and age profiles are similar across all the EU regions. However, accession states whether from 1973 or 2007 have all benefited from access to the larger market opportunities presented by the EU but it has also brought broader exposure to greater political risk offered through EU membership. Nevertheless growth rates in GDP have been consistent and can be accelerated by accession to the EU knowledge economy provided the opportunity to build a diversified skills and knowledge based economy is grasped.
However, in contrast the consequence of these shifts has been a continued dramatic if complex resultant decline in the value of agriculture to the economy despite failures in local supply to meet consumption requirements that results in the importation of food. Thus any model for sustainable rural economic development must balance the diminishing contribution agriculture currently makes to the rural economy and supplant it with other added value products and services to build a vital, viable and vibrant rural economy through greater awareness of global market economies and the ability to access these markets and arbitrage opportunities.
To create economic growth, firms will seek knowledge and clusters of expertise can assist in sharing or accessing local and tacit knowledge making proximity an important driver in the ability to generate competitive advantage. By implication differences in GDP provide regional and local opportunities to exploit these differences to the benefit of rural economies by adding value to existing natural products, agri-tourism new product development or accessing markets more effectively and more cost competitively. Here you can see the effect on accession on the clustering of each accession group. It is obvious that there is no clear natural tendency for convergence in the near term at least on this index measure. Thus in terms of comparative advantage it would seem apparent that certain clusters of regions have existing clear advantages when compared to other regions and provided that within regions there are strong knowledge diffusion structures then these advantages can be clustered effectively and a significant competitive advantage can be delivered.
In promoting a knowledge based rural economy it will be the ability to leap frog conventional societal or technological progression with a dynamic innovative approach to the economy or market that will promote the development of competitive advantage. This has implications over how the convergence of regional economies manifests itself in the market and the ability of regions to capitalise on these differences.
From that series of slides there are indications for the gap between 1986 cluster of accession states being 7 to 10 years behind the 1970’s and 1995 cluster and the 2007 cluster being between 15 and 20 years behind this cluster offering enormous opportunities to develop competitive advantages within regions and across regions and leapfrog traditional approaches.
Convergence then is highly variable and wrapped up in the growth of urbanisation across the EU and through regional variations in the development of larger city states on the surrounding economy. Thus while the newer regions are growing faster from a lower base compared to the older EU members there is a wider disparity in growth across the newer states regions. This re-enforces the impact of regional diversity and the opportunity to build sustainable competitive advantages between and within member states. As knowledge based societies tend to migrate to the most developed nodes of this activity or expertise. Therefore local credible strengths can be developed as effective nodes of knowledge that can be exploited. Thus the holistic model developed from my experiential journey re-enforces these points and is self adapting. The benefits accrue to all parties equally and real changes to the ability to fully exploit social and human capital through tangible The be effective the Model must set out clear understanding of : Discontinuity or market fracture that exists Potential Quest in response Who the Partners and Champions will or need to be across multi-agency levels The shape of the initial cluster and determines gaps in the available or accessible information and knowledge Begin process of harnessing human and social capital towards quest Build trust and value within cluster and beyond cluster Facilitate access to knowledge and databases information so as to allow the development of business plans and generate collaborative outcomes satisfying quest
The holistic and simple model has proved reliable in creating sustainable business clusters in transition economies through its adaptability to any given discontinuity and flexibility in its response to the quest identified. In the Baltic States, United Kingdom, Romania and trans-national partnerships within a number of Interreg programmes the model has proved effective. The model both creates knowledge, tacit and explicit, and retains and exploits it within the group. Therefore. being better able to utilise it for competitive advantage. It successfully has successfully developed multi-agency approaches to providing sustainable programmes. Thus in Estonia partnerships were developed between food and beverage companies, state ministries, 6 regional and county administrations and with public and private learning including local agricultural colleges and development partners. A solution to the quest was successfully delivered for well over 10 years that provided improvements to the branded quality of food products, developed greater access to markets and awareness in regional and national markets and successfully launched 4 in-store supermarket outlets for the clusters products. Participants were able to share logistics chains, and packaging chains through collaborative structures that produced scales of economy and had access to a regional development fund to support their growth and expansion. A range of knowledge transfer activities ensured access to relevant knowledge for product development. The UK cluster provided business diversification support to farm businesses in England at risk of bankruptcy to tackle wide spread underperformance on farm business accounts. The multi-agency approach again included regional development agencies, trade associations, private and public training groups, local authorities, 6 regional agricultural colleges and supported through regional development funds and the ESF. The model successfully delivered a sustainable approach to business diversification and facilitated the transition of farm businesses by increasing non-farming income streams of greater than 50% of farm income to support their continued survival. In Romania the multi-agency approach, on this occasion including the Word bank, paralleled those above and successfully delivered the initial collaboration of over 100 farm businesses who were able to combine some 25,000 ha of land. This collaboration provided access to information and technology sharing to facilitate improved storage and production methods. These scales of economy savings were targeted at improving access to markets and in improving value chains. The collaboration was able to successfully access significant SAPARD funding to make further scales of economy savings, upgrade technology and support diversification and business integration. The success of the programme gave confidence to the partners to undertake the formation of a second collaborative partnership to share their knowledge with others. This cascade of knowledge further supports the sustainability of the programmes and demonstrates real value of developing knowledge based economies to support

Rural development in a Knowledge Economy Presentation Transcript

Sustainable Rural Economies in a Knowledge Economy A model for post-industrial sustainable rural economic development Dr James MacAskill Bucharest, October 2010
A sustainable rural economic model
- Avoiding FDI generated discontinuities
- Relevance of knowledge and accessing it
- Impact of urbanisation and knowledge clusters
- Harnessing human capital
- Trust and Value chain development
- Making it happen
Avoiding FDI discontinuities Trend Share 2008 2008 Share 2007 2007 Country -16% 100% 148,333 100% 176,551 Total -35% 10% 15,063 13% 23,032 Other -44% 2% 3,063 3% 5,484 Serbia -23% 2% 3,391 2% 4,379 Belgium -15% 2% 3,448 2% 4,045 Portugal -57% 2% 3,660 5% 8,479 Slovenia -31% 3% 5,038 4% 7,335 Spain -63% 4% 5,626 9% 15,102 Czech Republic 56% 4% 6,335 2% 4,052 Ireland 117% 5% 6,709 2% 3,096 Bulgaria 91% 8% 11,397 3% 5,972 Germany -9% 8% 11,403 7% 12,464 Romania 5% 8% 11,659 6% 11,104 Hungary -14% 9% 12,900 8% 14,934 Russia -11% 9% 12,933 8% 14,488 France -16% 10% 15,512 10% 18,399 Poland -16% 14% 20,196 14% 24,186 United Kingdom
Trend in FDI
Most attractive regions
Sources of knowledge Howells defines knowledge as “a dynamic framework or structure from which information can be stored, processed and understood”
Pasteur’s Quadrant
EU 27 GDP
Agricultural added value % GDP
Indexed GDP (1990)
EU Enlargement 0 10000 20000 30000 40000 50000 60000 1 5 9 13 17 21 25 29 33 37 1970 = 0yrs GMP per capita $ 1970 group 1973 group 1981 group 1986 group 1995 group 2004 group 2007 group Expon. (1986 group) Expon. (2004 group) Expon. (1995 group) Impact of accession
EU Enlargement 0 10000 20000 30000 40000 50000 60000 1 5 9 13 17 21 25 29 33 37 1970 = 0yrs GMP per capita $ 1970 group 1973 group 1981 group 1986 group 1995 group 2004 group 2007 group Expon. (1986 group) Expon. (2004 group) Expon. (1995 group) Impact of accession
Growth of GDP per head 20002004 and GDP per head 2004 Cited in REFORMING EU COHESION POLICYA reappraisal of the performance of theStructural Funds, John Bachtler and Grzegorz Gorzelak Policy Studies, Vol. 28, No 4, 2007
The model Quest Discontinuity
Thank You Currently: Dean, St James’s Business School St James’s House 23 King Street St James’s London SW1Y 6QY [email_address] www.bite.ac.uk/sbs

Rural development in a Knowledge Economy

by James Macaskill on Oct 15, 2010

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Rural development in a Knowledge Economy Presentation Transcript