外文翻译创新区域集群和Milieux.doc

外文翻译-创新区域集群和milieux 本科毕业论文外文翻译外文题目 innovative regionsclusters and milieux 出 处innovation system frontiers advances in spatial science 2009 33-58 作 者 brian wixted 原 文33 the geography of agglomerationcomparing how sub-national regional strengths evolve across time has beenvery difficult until quite recentlyin comparison to analysing national development trends due to data limitations there is a growing opportunity for improved analysis of regional activitiesadvantages and trends as national statistical agencies focus more of their effort on collecting data at various spatial scalesacross the european unionthere is multi-country structural pattern of uneven regional developmentcombes and overman 2003 identify a strong pattern of core and periphery5 regionswhen analysed for their proximity to markets gdpper capita regions in western germanynorthern france and south east england are revealed as the concentrated zone of value added gdp for europethe authors reveal that beyond this core there is a graduated drop in gdp per capita as distance increasesin these eu economiesregional income converged between countries in the period 1980 to 1999but regional income disparities within countries widened see le gallo and dallerba 2003 interestinglythe degree of industry concentration in the usa at state level and europes regions6 is not significantly differentbut in europethe trend has been towards greater regional concentration more rapidly than in the usa see andaluz et al2002 the underlying drivers of such trends are still hotly debatedthere are many arguments for the economic significance of regional concentrations but one of the more important ones is that knowledge generation is spatially agglomerated and knowledge diffuses poorly across distance see the next section on theories of proximity the cumulative nature of knowledge explored in chap2 and the link between the generation of knowledge and the ability to benefit economically is likely to be one set of characteristics that contribute to uneven developmentcom knowledge and innovation geographygdpnot the only characteristic of economies that is highly agglomeratedpatenting activity is as welleurostat 2002 has analysed the geographic dispersion of patent applications for the eu 15 group of countries across statistical regionstable 33 lists the top 15 regions for high technology7 patent applications per mill of labour force in 2000there were nearly 57500 applications to the european patent office epo for patents from all regions within the eus then 15 member statesthis included 10500 applications for patents in high-tech industriesthe geographic distribution of the patents is highly concentrated21 regions out of 211 accounted for more than half of all the patent applications filed with the epoand only 13 regions produced more than half of the high-tech applications eurostat 2002 in asimilar veinpaci and usai 2000 analysed innovation patents per million inhabitants labour productivity and industrial specialisation in 109 regions in europereporting that there is a tendency towards the formation in europe of highly specialized technological enclavesespecially in some sectorsmachinerytransport equipment and energymoreoverwe have documented how the spatial and sectoral specialization of innovative and productive activities is positively and significantly correlated p108 thereforethere is a link between the degree of specialisation in knowledge generationseen in patent applicationsand the pattern of industry specialisation howeverpatenting may not provide a good indicator of innovative behaviour because a few urban centres may be the base for the major corporate research and developme-nt facilities and thus be the sites for patent initiationthis would not indicate whetherinnovation is geographically agglomeratedby analysing data from the european co-mmunity innovation survey on businesses that identify them-selves as innovating and identifying them by regionevangelista et al 2002 reveal that there were only a limit-ed number of areas of italy which could be described as regional innovation system-sbeaudry and breschi add an important dimension to this findingthey report that firms are more likely to be innovative if they areco-located with other innovative firms and in thepresence of spillovers associated with a large accumulated stock of knowledge 2003p339 the converse is also truedisadvantages arise from the stro-ng presenceof non-innovative firms in a clusterbeaudry and breschi found for italybut not for the ukthat the presence of firms in related industries enhanced innovativ-enessthusthere are economies to innovativenessin thatregions that are innovatives-timulate more innovative activityfinallyconcentrations of entrepreneurial innovativ-eness revealed through new firm births had better employment growth prospects than places that have a higher reliance on large corporations in a comparison of 74 districts across west germany see audretsch and fritsch 2002 clearlythere is strong evidence that production and innovation clusters within part-icular locations in economies are relatedthere is also good evidence that there are st-rong dynamics that drive a tendency for knowledge to be localisedthese findings are not in dispute herewhat matters in this bookis not that clustering occursbut the imp-rtance the rolescale and spatial structure of external links whichit is argued here have not been thoroughly exploredto datea general tendency towards proximity for knowledge and industry is the not the sameas specifying how those agglomerations fit within multi-spatial innovations systemscom systems of systemscom supply architectureas innovation and production clustering appear relateddata on value chain interde-pendencies can provide useful descriptive informationmeasuring production interde-pendencies at both the national and regional levels has been used to locate clusters e-conomically and geographically and to describe the scope and density of relationsin-put-output i-o methodologies have been used widely see for example oecd 1999d and 2001c to map value chains because it can trace the flow of intermediate goods and servicessuch flows are the supply and use of industrial ingredients which are required for further processingat this pointto analyse value chains through a time dimension with i-o data is most easily conducted at the national scalemost regional analyses exist only as one off studies at the regional leveltrends business research 2001 utilised i-o and value added data to identify clusters in the united kingdomfeser and bergman 2000 used national input-output data and economic data for the american state of north carolina to create information on regional supply chain clustering patterns in that statethe benefit of their approach is that it identifies inter-industry linkages and thus vertical and horizontal linkages at the sub-national level rather than just relying upon location quotient approachesin researchthat could prove to be complimentary to existing approaches that map industry inter-linkageshoen 2002a has developed a methodology for calculating the importance of particular linkages to potential clusters and is thus able to determinest-atisticallylinkages that are within a particular cluster and those outsidenot only can i-o data beused to understand the web of industry relationships see haukness 1999 at a point in timeit can also be used to measure changes across timewixted 2005 has established that at the national levelbusiness to business relations intermediate input-output relations were relatively stable during a 20 year period 19701990 for 9 countriesthe charts reveal important changessuch as the growth of value chains based around service industries generallyand business services in partic-ularwith a view to the question behind the present researchthe charts provide some evidence that tempers the commonly held view that western economies lost significant amounts of manufacturing activity during this period supplies to manufa-cturing industriesoften from other manufacturing industries which are obviously not the same as goods for final consumption often grew at the same rate as the economy overall and thus remained surprisingly stable as a share of gdpa number of general characteristics appear from wixteds analysis of oecd econ-omies with matrices of 33 industries by 33 industriesthese includemostlyintra-industry connections for manufacturing could be seen as generally stable with the rate of growth of gdpwith declines of typically outside of some in japan at less than one per cent of gdp for the periodthe largest apparent decline was for intra-industry iron and steel supplies in japanthere was a widespread decline in textiles and clothing industry suppliesmo-stly to the textiles and clothing industryandsupplies growth in the service sector is clearly visible for most countriesparticularlyin industries such as business services input-output relationsthe structure of ingredients that it takes to make a given productlook to be much more resilient to dra-matic change when compared to other variables such as employment or an industrys overall share of gdptotal manufacturing employment declined in many oecd countries during the 1970s and 1980s see godbout 1993 manufacturings share of gdp for oecd countries8 has also been constantly decliningshifting from 291in 1960 to 28in 1968 to 216 in 1990 and then to 199in 1995thuswithin the space of 20 yearsmanufacturings share of gdp had declined by 229for the oecd a share that is representative of the decline in individual countriessee oecd 1999e67 the comparatively stable nature of inter-industry linkages is supported by verspagen who notes that for the us economythe linkage structure is rather sticky译 文创新区域集群和milieux33城市集群地理上的凝聚比较如何跨越时间来发展区域分国家优势已经非常困难直到最近比较国家发展趋势分析时由于数据的局限显得更加困难有一个区域活动优势趋势分析来提高国家统计机构着重于努力收集不同空间尺度的数据的机会整个欧洲联盟还有许多个国家的区域发展的结构模式是不平衡的combers和overman2003确定了在欧洲的一个强势格局的核心和周边5个地区法国北部和英格兰东南部作为在分析他们的邻近市场国内生产总值时揭示作为新增国内生产总值价值的集中区笔者发现超出这个核心根据远离核心距离的增加人均国内生产总值成累进程度的下降在1980年到1999年期间在这些欧盟国家经济中各地区收入和国家收入是趋于相同的但是国家内的各区域的收入差距却在扩大 see le gallo and dallerba 2003 有趣的是行业集中度的程度在美国国家级别和欧洲地区是不没有什么不同的但是在欧洲走向更大的区域集群的这一趋势的速度有超过美国 see andaluz et al2002 这种趋势的潜在动力依然存在激烈的辩论有很多集中区域经济意义的论点但更重要的是知识的产生使得空间形成区域块状知识的扩散使得距离的影响变小如同现在所说的地球有地球村的概念是一个道理 see the next section on theories of proximity 知识的累积性chap2探讨和知识的产生和经济获利能力之间的联系很可能是一个特点集有助于不平衡的发展com知识和创新国内生产总值不仅仅是只有经济高度凝聚的特点专利活动也是一样的欧盟统计局2000年分析了欧盟15个跨区域的国家统计组统计的分布在各地区的专利申请表33列出了前15个地区对高科技专利申请占劳动人口的百万分比表33欧盟地区的大多数高科技专利申请占劳动人口百万分比2000年会员国nut2地区高科技专利申请占劳动人口每百万分比高科技专利高科技专利占所有专利的百分比1德国oberbayern54091132372芬兰新地suuralue5304416523荷兰努尔德- brabant5242633404瑞典斯德哥尔摩4300416405瑞典sydsverige3363199356芬兰pohjois 312186547美国东英吉利亚2363265398芬兰etela2024188379德国mittelfranke国格洛斯特郡 威尔特郡北萨默塞特16961973911美国新罕布什尔州和怀特岛16901564312德国斯图加特16293151213瑞典over诺尔兰1605393514德国oberpfalz1596842015法国法国地幔155185425资料来源欧盟统计局2002年在2000年有将近有57500专利申请欧洲专利局epo这些都是在欧盟内部的15个会员国所有地区的专利其中包括了10500个在高新技术产业的专利申请专利的地理分布是高度集中的21个地区占211所占数量的比重超过了所有向欧洲专利局提交的专利申请的一半只有13个地区生产比高科技应用多一半以上欧盟统计局2002年本着相同的精神paci和usai2000年分析了创新每百万居民专利劳动生产率和109在欧洲地区的工业专业化在欧洲的飞地即在一国境内的外国领土有形成高度专业化技术的趋势特别是在一些行业比如说机械运输设备和能源此外我们已经证明创新和生产活动对空间和部门的专业化的作用是呈正相关的第108页因此知识的产生链接着专业化程度可以看到专利申请和专业化的产业格局但是不管怎么说专利并不能提供创新行为的良好指标因为一些城市的中心可能是各大公司的研究和开发设施基础是获得专利开始的地方这并不能说明创新是否是地理结块通过从企业的创新和识别标识为各地区evangelista et al等他们自己欧洲共同体创新调查的分析数据2000年显示只有意大利的数量有限的领域被描述为区域创新体系beaudry 和breschi在这一重要方面增加了一个重要发现他们的报告指出如果和其他创新型企业合作那么这个企业才更有可能创新和存在大量积累与股票相关的知识溢出效应2003年 第339页是一个道理反过来也是一样缺点来自于集群里存在着强大的非创新型企业beaudry和 breschi发现意大利的相关行业存在的企业创新能力在增强但是应该不是这样因此经济具有创新型那么这些区域就是创新区域集群这就更刺激了区域企业的更多创新活动最后通过集中的创业创新发现有比原来工作地方更好的就业前景的新公司这个新公司是在西德的74个地区里拥有更高的依赖的大企业 see audretsch and fritsch 2002 显然有强有力的证据证明生产和创新集群在经济里是相关的当它们处于自己特定的位置有强劲的动力驱使知识当地化这也是很好的证据这些发现在这样是没有争议的在这本书里对外部链接作用规模和空