陈文平论文外文翻译

陈文平论文外文翻译 ?.外文翻译 目录? 外文原稿 1..............................................................................2 中文译文 1..............................................................................8 外文原稿 2..............................................................................12 中文译文 2..............................................................................1 7 外文翻译之一 Competition and Cooperation in Industrial Cluster: The Implication for Public Policy David Newlands English European Planning Studies, Vol.11, No.5(2003) 2. Industrial Clusters: A Critical Reading of Different Theories 2.1Standard Agglomeration Theory, From Marshall Onwards Marshall, in his writings on Sheffield, Lancashire and other British regions, viewed the main source of external economies as the 'commons', the infrastructure and other services from which each individual firm in an industrial district might draw (Marshall, 1921). Examples include, in modern terminology, improved job search and job matching, more favorable access to capital finance and inter-firm labor migration. The availability of such common resources to a number of firms then enhances their size and diversity as both capital and labor are attracted to such areas to exploit the larger markets for their services. This in turn leads to reductions in factor prices and/or increases in factor productivities. These are the ways in which the external benefit to firms of a location in the industrial district manifests itself. Unit production costs will be lower within the industrial district than out with it. Parallel to his studies of industrial organization, in the various editions of his Principles of Economics, Marshall (1890, 1920) helped develop what was to become standard agglomeration theory. This was then built upon subsequently by a number of writers. For example, Scitovsky (1954) identified a further category of 'pecuniary external economies', Perroux (1955) contributed his famous theory of growth poles, and Chinitz (1961) applied the notion of agglomeration economies to the economic development of New York and Pittsburgh. More recently, Krugman (1991, 1995) has emphasized the importance of increasing returns as a favorable condition for the development of external economies. Porter (1990) can also be understood as belonging to this lineage in the sense that external economies make up many of the key relationships within his famous 'diamond'. Standard agglomeration theory provides an explanation of why firms might cluster together, sharing a 'commons' of business services and a diversified labour force, and forming extensive local linkages with other firms. However, it conforms to neo-classical theory in that local economies are viewed as collections of atomistic businesses, aware of one another solely through the intermediation of price/cost signals. Firms continue to compete with each other although Marshall was keen to warn of the risks that firms' collaboration, in the development of shared inputs, risked blunting competitive forces. 2.2 Transaction Costs: The 'Californian School' In the writings of the 'Californian school', the disintegration of productive systems leads to an increase in firms' transaction costs (Scott & Storper, 1986; Scott, 1988; Storper, 1989). Changes in market and technological conditions have led to increased uncertainty and greater risks of over capacity (of labour and capital) and of being locked into redundant technologies. The response of deepening the organizational division of labour leads to an increase in the number of formal market transactions external to the firm. There may also be an increase in the unpredictability and complexity of transactions. The costs of carrying out certain types of transaction-especially those where tacit knowledge is important or trust is required and thus complete contracting is impossible-varies systematically with distance. Thus, agglomeration is the result of the minimization of these types of transactions costs in a situation where such minimization outweighs other production cost differentials. The Californian school sought to explain observed agglomerations of economic activity. The argument centered on the localization of traded interdependencies-or simple input-output relations-but this is at best only a partial explanation, not least in being unable to distinguish convincingly between 'good' and 'bad' agglomerations. Agglomerations have been found in high wage, technologically advanced industries and low wage technologically stagnant ones alike while there are technologically dynamic agglomerations which lack the dense inter-firm linkages and coordinating institutions of a 'new industrial district'. Nor is it clear whether markets will succeed in coordinating transactions within clusters (Cooke & Morgan, 1993). The management of traded interdependencies is exactly what we think of as the business of markets but there may nevertheless be market failure. Thus, certain "transactions-in labor markets, in inter-firm relations, in innovation and knowledge development-tended to have points of failure in the absence of appropriate institutions" (Storper,1995, p. 199). With this concern for the institutional arrangements within clusters, the 'Californian school' came to share certain of the arguments of the flexible specialization theorists who are discussed next and the institutional and evolutionary economists who are considered shortly. 2.3 Flexible Specialization, Trust and Untraded Interdependencies While neo-classical economics views firms as atomistic businesses, aware of one another only through formal market signals, modern industrial district theory emphasizes the interdependence of firms, flexible firm boundaries, and the importance of trust in creating and sustaining collaboration between economic actors within the districts. These themes arose first in the literature on flexible specialization in the 'Third Italy'(Brusco, 1982) but was later extended to Baden-Wu?rtemberg and other regions (Piore & Sabel, 1984). The sources of flexibility lay in collaborative networks of (mostly) small firms and supporting institutions. These networks permitted the establishment of trust between actors, a crucial argument within most contemporary approaches to clusters. The reasoning is that firms within networks of trust benefit from the reciprocal exchange of information-particularly tacit information that cannot be codified-but are simultaneously bound by ties of obligation which regulate behavior. Trust thus reinforces mutually beneficial relationships between firms. The implicit assumption is that trust is more likely to be sustained in geographically concentrated networks than more dispersed ones (Belussi, 1996). Firms may cooperate in seeking to get new work and may bid together on large projects. They may form consortia to access cheaper finance. They may jointly purchase materials and conduct or commission joint research. They may plan together and receive technical, financial and other services from the 'commons'. However, despite all these examples of cooperative relationships, founded on or reinforced by trust, because they remain privately owned businesses, firms within clusters continue to compete, with one another and with other firms, often more on quality than price. The embedding of economic relations into a wider social framework appears to be most common where business activity is conditioned by local politics, religion and close kinship and friendship relationships. Thus, "it is probably not a coincidence that the most successful districts have tended to be the most racially and culturally homogeneous" (Harrison, 1992, p. 479). Equally, national (or other broader) economic, legal and policy traditions are relevant. The development of inter-firm cooperation is more likely in some countries, such as Italy, than in others, such as the UK, because of differences in the operation of labor markets and competition policy. According to theorists such as Granovetter (1985), trust arises from the 'digestion' of experience. Trust accumulates from repeated interactions between firms and other actors in which they contract and recontract, formally and informally, strike deals, and help each other out at times of crisis. Trust results from a process of learning through experience which actors can be relied upon. Personal contact facilitates such repeated interactions and this in turn is likely to depend on proximity. This focus on untraded interdependencies is very different to the transactions costs approach to agglomeration. The latter concerns the cost minimization of traded relations while untraded interdependencies point to wider processes of the optimization of non-market or non-contract exchanges (Raco, 1999). Finally, it is important to note that untraded interdependencies can not only facilitate effective collective learning and action but also impede it. Especially where familiar conventions become well established, 'sclerosis' can set in. Areas can become locked into outdated and inferior technologies and institutions. 2.4 Innovative Milieux: The GREMI Group There have been various schools of thought on the relationship between innovation, high technology industry and regional development. One line of enquiry has focused on the conditions for the establishment and growth of such high technology complexes as Silicon Valley and Route 128. While many factors have been identified, the most discussed is the role of local research intensive universities, Stanford in the case of Silicon Valley and MIT in the case of Route 128. A large literature on the relationship between innovation, research universities and regional development has been spawned (Saxenian, 1985; Castells & Hall, 1994; Storper, 1993). Another direction of research has been in pursuit of the notion of an innovative milieu, the key theoretical concept of the GREMI (Groupement Europe′en des Milieux Innovateurs) group of regional economists (Aydalot & Keeble, 1988; Camagni, 1995). Clustering enables firms to benefit from a 'collective learning process', operating "through skilled labor mobility within the local labor market, customer-supplier technical and organizational interchange, imitation processes ... and informal 'cafeteria' effects" (Camagni, 1991, p. 130). This process draws upon "an intricate network of mainly informal contacts among local actors ... made up of personal face-to-face encounters, casual information flows, customer-supplier cooperation and the like" (Camagni, 1991, p. 131). However, there is a certain ambiguity as to what precisely milieux are. By some readings, a milieu is a set of institutions, practices and rules which provide a framework for development which guides and coordinates the activities of innovators. By other readings, a milieu is a network, of firms, research institutes and policy-makers, which provides the necessary coordination for successful innovation. These different interpretations, together with the very intangibility of milieux, are the sources of major intellectual problems. Thus, the GREMI group "has never been able to identify the economic logic by which a milieu fosters innovation. There is circularity: innovation occurs because of a milieu, and a milieu is what exists in regions where there is innovation ... they do not specify the potential mechanisms and processes by which such milieux function" (Storper, 1995, p. 203). 2.5 Institutional and Evolutionary Economics A further approach derives from institutional and evolutionary economics (Nelson & Winter, 1982; Amin & Thrift, 1992; Amin, 1999). Technological change is seen as path dependent since it involves sequenced, and not simultaneous, choices which are often irreversible. There is a spatial dimension to such choices with interdependencies between organizations being both traded and untraded. The latter include rules and conventions which shape the development and communication of knowledge between local actors. Given that there are strong irreversibilities, observed clusters are to some extent accidents of history, reflecting the impact of past choices, although their development is also influenced by the appearance and growth of reinforcing institutions. This approach is potentially very fruitful in understanding the nature of competition in contemporary capitalism (Dosi et al., 1987). Standard economic theory conceptualizes competition as the location on a production possibility frontier that maximizes a firm's comparative advantage given an existing set of factor prices. Competition is a state, characterized by the absence or minimization of monopoly rents (Nickell, 1996). In contrast, drawing upon an Austrian perspective, institutional and evolutionary economics views competition as a process of economic change, spurred by constant technological change. Thus, if innovation is the driver of competition, a firm (or locality) may possess technologies which are superior to those of others regardless of the level of factor prices. This distinction has come to be known as that between 'weak' competition and 'strong' or Schumpeterian competition (Hudson, 1999). Weak competition involves the search for lower cost means of producing existing goods with existing technologies. Strong competition is a strategy which involves the creation of new goods or of new technologies to produce existing goods. 产业集群中的竞争和合作:应用于公共政策 David Newlands 英国 《欧洲策略研究》，2003年第11期 2.产业集群:对不同理论的批判性解读 2.1 标准 excel标准偏差excel标准偏差函数exl标准差函数国标检验抽样标准表免费下载红头文件格式标准下载 的集聚理论--从马歇尔(Marshall)开始 马歇尔在他关于Sheffield, Lancashire等其他英国地区的著作中认为外部经济的主要来源是共同的，即个体企业在一个产业地区可能享有的基础设施和其他服务等(Marshall, 1921)。用现代术语来阐述，例如增加的工作寻找和匹配机会，更加便捷的融资渠道和企业之间的劳动力转移。因为被吸引到这些地区的资本和劳动力开拓了更广阔的市场，所以对大量的企业而言，这些共享资源的可获得性提高了企业的规模和多样性。这些反而导致了要素价格的减少或者要素生产效率的增加。这就是在一个地区产业集群内，企业获得外部利益的方式。单位生产成本在一个产业区内将低于在产业区之外。 与他的产业组织理论类似的，马歇尔在他的各种版本的《经济学原理》书中，发展了标准的集聚理论。之后的很多理论发展都是基于这个标准集聚理论。例如，Scitovsky(1954)进一步认证了无偿劳动的外部经济的种类，Perroux(1955)发表了著名的增长极理论，Chinitz(1961)将集聚经济设想应用于了纽约和匹兹堡的经济发展中。更近地，Krugman(1991, 1995)开始强调增加收益的重要性--外部经济发展的有利条件。Porter(1990)也被理解在其著名的钻石理论中，认为外部经济占有极其重要的位置。 标准的集聚理论试图解释为什么企业会集聚在一起，分享共同的商业服务和多样化的劳动力，与当地企业建立广泛联系。然而，与新古典主义一致的是， 二者都认为当地经济只是由很多微型商业所组成的集合体，彼此之间通过价格或成本信号为媒介机制来观察。尽管马歇尔已经预警在投入共享的发展过程中，企业合作将面临日益钝化的竞争力风险，但是企业之间还是不断地进行竞争，在发展共同投入时，风险将减弱竞争的力量。 2.2交易成本--加州学派 在加州学派的著作中，生产力系统的分散性导致了企业交易成本的提高(Scott & Storper, 1986; Scott, 1988; Storper, 1989)。市场和技术条件的变化增加了不确定性，加大了劳动力和资本过剩以及被过剩技术锁定的风险。对深化劳动力组织分散的反映导致企业外正常市场交易数量的增加，甚至会增加交易的不确定性和复杂性。实施特定交易类型--特别是那些需要默契或相互信赖，因此完全 合同 劳动合同范本免费下载装修合同范本免费下载租赁合同免费下载房屋买卖合同下载劳务合同范本下载 又是不可能的交易成本，会随着距离不同而出现系统性差异。因此集聚是最小化此类交易成本的产物，因为此类最小化超过了其它生产成本的差异。所以，在交易成本的最小化超过其它生产成本差异时，集聚就是最小化这些交易成本类型的结果。 加州学派试图对现存的经济集聚活动寻求解释。他们争论的焦点集中于贸易依赖(或者仅仅是投入和产出关系)的本地根植性，但最多也只是部分解释，至少能很信服地给出好和坏集群之间的区别。有高工资、技术先进的产业，低工资且技术停滞的产业，同时也存在技术上很有活力但却缺乏新产业区应有的企业间联系和协调机构的产业。 然而市场是否会在协调集群内交易方面获得成功，仍然是不明显的(Cooke & Morgan, 1993)。交易依赖性管理正如我们所看到的市场商业一样，也存在着市场失灵。因此在缺乏适当的机构的情况下，交易在劳动力市场、在企业内部关系、在创新和知识发展方面的将倾向于出现失灵(Storper,1995, p.1995)。出于对集群内机构安排的担忧，加州学派与提倡灵活专业化的专家， 制度 关于办公室下班关闭电源制度矿山事故隐患举报和奖励制度制度下载人事管理制度doc盘点制度下载 和演化经济学家在某些观点上具有相似之处，这两个学派在接下来将会被谈到。 2.3 灵活专业化，信赖和非贸易相互依赖性 新古典学派视企业为微型商业体，企业间仅仅通过正常的市场信号来观察彼此，现代产业区域理论强调企业间的相互依赖性，灵活的企业边界和信任在创造和维系区域内经济主体 之间合作的重要作用。 这个议 题 快递公司问题件快递公司问题件货款处理关于圆的周长面积重点题型关于解方程组的题及答案关于南海问题 的文字记载最早出现在"第三意大利"(Brusco,1982)的灵活专业化理论中，但是之后在Baden-Wurtemberg和其它地方得到拓展(Piore&Sabel,1984)。灵活性来源于小企业和协助机构的合作网络。这些网络允许主体之间信任感的建立，而这个信任感恰恰是通向集群的现代途径的争论焦点。这其中的推理过程是这样的，在相互信任网络内，企业得益于信息的相互交换，特别是那些不能制宪的默契信息，但是同时又受到规范企业行为的义务约束。信任因此加强了企业间的利益关系。其中的隐含假设是信任更有可能发生在地域上集中而不是分散的网络上(Belussi，1996)。 企业间可能会为寻找新项目而进行合作或者由一个大的工程项目建立联系。他们可能会合伙以获得更便宜的融资方式，相互合作购买原料或主导共同研究，一起 计划 项目进度计划表范例计划下载计划下载计划下载课程教学计划下载 并取得来自于公共物品上的技术上、财务上等的服务。然而，尽管有这么多由信任建立或者加强企业间合作关系的例子，但是因为这些企业仍然是私有企业，集群内的企业间仍然存在着彼此之间的竞争，这种竞争更关注于质量而不是价格。 在商业活动以地方政策、地域和亲密的亲戚和朋友关系为条件的地区，经济关系逐渐牢固以致发展成为更广阔的社会框架的现象是最普遍的。因此，"最成功的区域往往是那些在民族和文化上和谐的区域往往不是偶然(Harrison, 1992,p. 479)。同样的，民族(非其它边界)经济，法律和政策传统是相关的。由于劳动力市场运行机制和竞争政策的差异，企业间的相互合作更有可能发生在在意大利这类的国家而不是英国等国家。 根据Granovetter (1985)等的看法，信任源于对经验的消化。信任积累于企业和其它经济主体之间重复的相互作用，他们不断的重复签订合同，正式或非正式的，进行交易，相互帮助渡过危机。信任源于经济主体对可信经验的学习过程。私人接触加速了重复的相互合作，而这反之也是依赖于时间和空间上的接近性。 这种关注于非贸易的相互依赖性形成集群，与通过交易成本形成集群的方法是不同的。后者关注于贸易关系的成本最小化，而前者则更广泛地指向非市场或者非合同交易更广泛的优化过程 (Raco, 1999)。 最后，值得一提的，非贸易相互依赖性虽然可以加强有效的集体学习和行动，但同时也会造成阻碍。特别是当熟悉的传统建立之后，组织僵化就有可能乘虚而入。区域就有陷入过时、并且低效的技术和机构困境中。 2.4 创新环境:创新环境小组(GREMI Group) 在关于创新、高科技产业和区域发展三者的关系上存在很多的流派争议。其中一个派系关注于建立和发展类似于硅谷和128公路这样的高科技企业集群所需要的条件。很多的因素都已经被确定，争议最多的则是当地以研究性为主导的大学在其中所扮演的角色，如在硅谷案例中的斯坦福，在128公路中的麻省理工。因此发起了一场关于创新、研究性大学和区域经济发展之间关系的学术探讨(Saxenian,1985; Castells & Hall,1994; Storper,1993)。 另外一个研究方向则致力于创新环境设想，既以区域经济学家(Aydalot & Keeble,1988;Camagni,1995)为代表的欧洲创新环境小组GREMI (Groupement Europe'en des Milieux Innovateurs)的核心理论概念。集群使企业从"集体学习"过程中受益，通过"有技能劳动力在当地劳动力市场的流动，消费者--供给者在技术和组织上的相互交换、模仿过程等和非正式的咖啡店效应"(Camagni,1991, p.130)。这个过程依赖于内在的当地经济主体间的非正式接触......组成了私人的面对面的相遇、随机信息流，消费者-供给者合作等(Camagni,1991, p.131)。 然而，对环境的精确定义至今存在一定的模糊性。一些著作认为环境即是一系列的机构、操作和指导、协调创新活动发展框架的法律法规。另一些专著则认为，环境是企业、研究机构和政策制定机构组成的，为成功的创新提供必要协调的网络。 这些不同的阐释，同抽象的环境定义一起，是主要的问题来源。因此，欧洲创新环境小 组"总是不能确认环境促进创新的经济逻辑"，反之陷入了一个循环:创新由于环境发生，而 环境则存在于有创新行为的区域......他们并没有具体阐述这种环境运行的潜在机制和过程 (Storper,1995, p. 203)。 2.5 制度和演化经济学 一个更进一步的方法是来自于制度和演化经济学(Nelson & Winter,1982; Amin & Thrift, 1992; Amin,1999)。技术变化被视为路径依赖因为其涉及到连续的但不是同时的，而且通常 是不可逆转的抉择。关于贸易和非贸易机构间的相互依赖选择存在多维空间。后者包括促使 当地经济主体之间知识发展和交流形成的法规和传统。考虑到存在很强的不可逆性，被观察 到的集群在一定程度上产生于历史的偶然，反映了过去抉择对现在的影响，尽管它们的发展 受到了压力机构出现和成长的影响。 这种方法在理解现代资本主义竞争性质方面取得了很多潜在成果(Dosi et al.1987)。 标准的经济理论将竞争定义为在既定的一系列要素价格条件下，最大化公司比较优势的生产 可能性边界上的位置。竞争是一种最小化或缺少垄断租的状态(Nickell,1996)。相反的，以 奥地利学派的观点为依托，制度和演化经济学认为竞争是由一贯的技术变化所促进的经济变 化过程。因此，如果创新是竞争的动力，一个企业可能拥有比其它企业更先进的技术而不用 考虑要素价格水平。 这种差别以弱竞争和强竞争或者熊彼特竞争而著称(Hudson,1999)。弱竞争涉及到在现 有技术条件下，生产现有产品寻求更低的成本。而强竞争则是一种试图创造新的产品或开发 新技术去生产现有商品的战略。 外文翻译之二 The Software industry and India's economic development Asish Arora Suma Athreye American Indian Information Economics and Policy, Vol.1(2001) 4. The growth of software and human capital formation: public and private investments in training and the rewards to an engineering education Though India has one of the largest numbers of scientists and engineers it also has some of the lowest rates of literacy in the world with 52% of the total working population that cannot read or write. As Table 3 showed, despite the large total numbers of engineers, the numbers of engineers per million of population was smaller in India compared to several other countries. There is correspondingly an over-reliance on the existing stock of trained but underemployed engineers, for whose services a slowly growing and protected economy could not generate adequate demand. A very large fraction of the employees of Indian software firms are graduates of engineering college. Most of the Indian software firms interviewed by Arora et al. (2000) reported hiring only engineers. Data from a sample of nearly 60 software firms indicates that over 80% of their employees had an engineering degree. Only 13% were non-engineers trained in software development.14 In interviews, many firms categorically stated that they hired only engineers. This preference for engineers was unremarkable, and of little consequence, at the start of the industry, when its demand was small relative to the annual supply. India graduates over 160,000 engineers of all varieties. The sharp and sustained growth of the Indian industry has meant that by 1998-99, the number of employees has climbed to nearly 250,000, and estimates suggest that this may have crossed 400,000 in 2000-2001. If the industry continued to grow at 50% per year, then even allowing for increases in productivity, it appears that the software industry is going to run out of engineers to hire. (See Arora, Asundi and Fernandes, 2000 for more details.) These projections are consistent with other evidence. Wages in the software industry have grown at over 20% per annum and attrition rates are high. When asked in 1998-99 to list the top 3 problems they faced, more than half of all firms (out of a sample of over 100 firms) irrespective of age, size or market orientations (either export or import) selected manpower shortage and employee attrition as the most serious problem affecting them (Arora, et. al, 2000). Despite paying substantially above Indian standards, virtually all firms find it difficult to attract and retain talented software developers. The public policy response has been to emphasize increased investments in engineering colleges, increased emphasis on information technology in engineering curricula and the creation of institutes of information technology (IIIT) along the lines of the better known Indian Institutes of Technology. Though superficially reasonable, this is not the answer. These investments are unlikely to have a significant affect on supply in the short run. Moreover, expanding such capacity faces the problem that the growth of the software industry has tended to siphon off engineering masters and PhD students. A recent report on graduate engineering education in India noted that the number of engineering PhDs produced has fallen from 675 in 1987 to 375 in 1995. Concurrently, the number of engineers with postgraduate training has also risen only slowly, from a little over 12,000 in 1987-89 to a little over 17,000 in 1990-92. Surveys of India's premier technological institutions-the Indian Institutes of Technology (IITs) show that a very large fraction of postgraduates from those institutions enter the Information Technology (IT) sector, in some cases as many as 90%! Moreover, Table 6 below shows that the bulk of the Indian engineering capacity is located in just a few states - Maharashtra, Karnataka, Tamil Nadu and Andhra Pradesh. Further, the table also shows that the bulk of the capacity here is accounted for by "self financed" colleges, where students receive a much smaller subsidy, if at all, compared with the state financed colleges. An interesting and hitherto unexplored question is the reason that the organizational innovation of self- financing colleges has not diffused to other parts of the country. We can only speculate that this has to do partly with cultural and political factors, and partly with the lower returns to investments in human capital in other parts of the country. Not coincidentally, the south and west are also economically more advanced. We believe that although investments in engineering education are necessary, a bigger part of the solution lies in a more efficient use of existing human capital resources. Implicit in the discussion thus far is that only engineering graduates are well suited to perform the tasks required. This assumption appears to have shaky foundations. First, the bulk of the engineers working in the industry are not, in fact, trained in software engineering, computer science or related disciplines. Further, a very significant fraction of the work involves developing and refining business applications, databases and the like. Indeed, initially a great of the work involved porting applications from one computing platform, typically a mainframe, to another platform such as a Unix platform. This work requires familiarity with software development tools. It does not require a deep knowledge of computer architecture or operating systems. Finally, much of the work has tended to consist of small projects, with fairly low levels of technical complexity. Arora et al (2000) report that the median size of the "most important export project" of the firms they surveyed was only 150 man months, with an average of 510. This suggests that the typical export project is even smaller. Moreover, about half of the work was carried out in India; the rest was onsite, in the US. When pressed, most of the managers agreed that they did not require engineers: Bright graduates from any field could, with proper training, do what was needed. It seems that the preference for engineers is in some cases a way of signaling quality to customers. As one CEO put it "Take somebody from a good college (any of the top 20 colleges in India), give him 3 months of orientation and they are ready to take up a programming assignment. I don't need all these engineers.... But I don't want to be branded by my customers as a guy who hires NIIT graduates." (Emphases added.) (From Sloan Report, Arora et al 1999) This is a clear instance of a "race to the top". With limited market power, Indian software exporters try to distinguish themselves from the competition by pointing to the quality of their processes and people, and when possible, their experience. Firms also have quality concerns. Some managers we interviewed believe that an engineering education imparts a set of problem solving skills, methods of thinking logically and learning tools that help quick adaptation to changes in technology, domains and tasks. Since Indian firms provide services across a range of platforms and domains, this is an important asset. Another important consideration has to do the quality signaling in the labor market. The Indian education system is such that competition for an engineering education is intense, and as a result, graduating with an engineering degree is a signal of qualities such as intelligence and willingness to work hard. Software firms may prize these qualities more than the specific substantive knowledge of engineering. If so, this is certainly an inefficient allocation of resources.17 Indeed; the software industry has been growing in part by drawing away engineers from other industries. In our interviews we came across a number of instances of engineers with highly specialized training (such as VLSI design or satellite systems) working on tasks such as database design or development of business application software. Quite a few senior level engineers were drawn from a variety of public sector research and development institutions. Such a transfer of resources is entirely in line with the presumed comparative advantage in software development. Of course, there are a variety of distortions in the Indian economy, which imply caution in interpreting the market signals.18 In addition to changing the composition of economic activity, the increasingly tight market for engineers and managers is also likely to affect the organization of economic activity. As we discuss in greater detail in section 6, the increasing demand for trained engineers and managers is also affecting the balance between capital and labor (or more precisely, between capital and human capital), resulting in organizational innovations. The clearly increasing payoffs to human capital are also inducing greater investment in human capital. The Indian middle class has always relied upon education, particularly professional education such as engineering or medicine as means of economic advance. However, with a slowly growing economy, the returns to such investments have not been very high. The precarious state of public finances has limited the ability of the central and state governments to expand tertiary education. The rapid growth of the software sector has however, marked a watershed. One of the most rapidly growing sectors within the software industry is for private training. Private training institutions train individuals specifically for work in software development. NASSCOM sources estimated that there were 3800 such training firms in 1998, in what was then a $300 million market, although together NIIT and Aptech are believed to have 70% of the software training market. Private training institutes are also important for helping existing software developers acquire new skills. Many engineers also undertake further training in software development on their own from private training institutes. The growing presence of private training institutes in cities in India is increasingly making it possible for software developers to obtain certificates and diplomas from such institutes. It is also noteworthy that this is a private sector response to a market opportunity, namely the demand for training in specialized skills. In the US and elsewhere, for profit firms compete with a variety of public institutions, such as state and community colleges in the US. In India, the rapid growth of private training institutes testifies to the changed economic climate and the channeling of entrepreneurship into economically productive areas away from mere rent-seeking. This change, too, owes at least indirectly to the rapid growth of the software industry. To sum up the foregoing, we believe the evidence indicates that until recently, an excess supply of trained engineering talent was a significant source of competitive advantage for Indian firms. By the same token, it provided few incentives for firms to economize on the use of skilled engineering talent. Instead, the growth of the industry and high salaries have attracted not only newly graduating engineers but also engineers, managers and other professionals from other industrial sectors. Despite this, the explosive growth in the software industry has lead to a stage where firms recognize that skilled engineers, software professionals and good managers are a scarce resource. Moreover, faced with a number of attractive options including a move overseas, these talented engineers and managers are looking for more money and a more professional and rewarding work environment. In turn, this entails a variety of organizational changes we discuss below. 软件产业和印度的经济发展 Asish Arora Suma Athreye 美国 印度 《信息经济学和政策》，2001年第一期 4、软件行业的发展和人力资本的形成:在教育方面的私人和公共投资和工程教育回报 尽管印度拥有世界上最多的科学家和工程师，但是其由于52%的工作人员无法读写，而 同时成为世界上识字率最低的国家。正如表3所示，尽管有大量的工程师，但是印度每百万 人口里工程师的数量还是低于其他一些国家。由于缓慢增长的干预型经济不能产生对工程师 的足够需求，相应的就有对现存但未被雇用的工程师的过度依赖。 大部分的印度软件公司的职员都毕业于工程学院。根据Arora et al. (2000)的报告， 大部分被访企业只雇用工程师。60家软件公司的调查数据显示，超过80%的公司雇员有工程 师学位，只有13%是在软件发展中被培训起来的非工程师。在采访中，很多公司明确表示他 们只雇用工程师。 在软件行业发展的初期，由于需求远远小于每年的供给量，这种对工程师的偏好并不明 显或者不导致什么后果。印度总共有160，000各种各样工程类毕业生。印度产业稳定而快速 的发展意味着在1998年和1999年间，被雇佣者的数量将会累计到近250.000，预计将会在 2000到2001年间突破400，000。即使软件产业每年以50%的增长率增长，甚至假设生产力 提高，软件产业似乎还是会将出现工程师供不应求的局面。(参考 Arora, Asundi 和 Fernandes,《2000年细节》。) 这些预言得到证据支持。软件产业的工资率每年以20%的增长率在增长，同时人员损耗 率也是相当的高。当在1998年至1999年间，当软件产业被问及列举他们发展所面临的三大 问题时，超过一半的公司(以超过100的公司为样本)，不考虑公司的时间、规模和市场导向 (出口或者进口)，都不约而同的选择了人员紧缺和人员损耗作为他们所面临的最严重的问题。 尽管愿意偿付远远高于印度标准水平的工资, 很多企业最终还是发现难以吸引并且留住优秀 的软件开发人才。 公共政策对此做出的反应是加强在工程学院上的投资，重视工程课程上的信息技术，和 信息技术机构(IIIT)以及更有名的印度技术机构的创建等。尽管从表面上来看这些举措是 合理的，但是实际上这并不能解决问题。这些投资根本不可能在短期内能显著改善工程人员 供给。同时，如此大规模扩容导致软件产业发展趋向于抽调工程硕士和博士。一份最近对印 度工程研究生教育的调查显示，工程博士的数量已经从1987年的675位下降到1995年的375 位。同时，拥有硕士头衔的工程师的数量也只是缓慢增长，从1987-89年间的12，000位增 长到了1990-92年间的17，000位。对印度技术机构理工学校的调查显示，大量的该校毕业 生进入信息技术部门工作，有时甚至高达90%。 另外，表6显示印度大部分工程学校集中在少部分的几个州--Maharashtra, Karnataka, Tamil Nadu and Andhra Pradesh。同时其中大部分都是私立大学，在这些学校的学生收到的补助远远小于就读于州立大学的学生。但是，私立学院并未能在国家的其它部分扩散开来是一个有趣而费解的现象。我们只能大概的估计这部分归因于文化和政治因素，部分取决于在其它州人力资本投资的低收益率。并非巧合的，南部和西北在经济上确实是更发达。 我们认为，尽管在工程教育方面的投资是必需的，但是解决问题的更有效的办法应该是依赖于对现有人力资源的合理利用。在这场争论中的隐含假设是只有工程类毕业生才能胜任软件开发任务。这个假设技术显然是不合理的。首先,大部分现在软件产业工作的工程师事实上都是没有接受过在软件工程、电脑科学或者相关领域等的训练。其次，很大一部分工作是涉及到商业应用，数据库等。事实上，最初大量的工作涉及到从一个运行平台(通常如维护)到另一个运行平台(如Unix平台)的运用。这些工作只要求对软件开发工具相当熟悉，但并不要求对电脑结构和运行系统具有很深的认识。最后，大部分的工作其实都是由一个个具有较低技术复杂性的小工程组成的。Arora et al(2000)在他们调查中发现，公司最重要的出口工程的中等规模是150个人，但平均有510人。这表明典型的出口工程甚至更小。更有甚者，大约一半的工作在印度国内执行，剩下的则在美国。 当迫于无奈，很多经理也表示他们并不需要工程师:聪明的毕业生只要经过适当的培训，是能很快胜任何工作的。但是似乎对工程师的偏好是出于对顾客传递产品质量信号的考虑。正如某一CEO所说，"雇佣任何一个优秀学府的毕业生(印度排名前20的大学中的任何一所)，给他们三个月的培训，他们就能够胜任项目任务。事实上，我并不是完全需要这些工程师......但是我却不想在我的顾客中以雇佣非技术工程大学的毕业生而出名。"(来自《斯隆报告》，Arora et al 1999)。 这是一个"竞赛至上"的最好例子。受限于市场影响力，印度软件出口商们总是试图通过人才和生产过程质量，甚至可能的话，人才经验等方面来使自己在竞争中脱颖而出。 企业也有出于质量方面的考虑。一些被采访的经理表示受过工程类专门教育涉及到一系列问题解决技巧、逻辑思考的方法和学习工具，这些都有助于(雇员)快速适应在技术、领域和任务方面的变化。由于印度公司提供的是跨领域和平台的一系列服务，因此这些能力是很重要的资本。另外一个重要的考虑是工程教育背景是劳动力质量的信号指示。印度工程类教育体系是非常严格的，因而成功获得工程类学位的毕业生至少显示了智力和勤奋能力。软件公司可能因此更看重的是这些素质而不是具体大量的工程类知识。 如果事实如此，那么劳动力市场的分配必定是缺乏效率的。事实上，软件产业的发展部分是通过吸引来自别的产业的人才来实现的。在我们的采访中，我们遇到大量的具有高度专业背景(如VLSI 设计和卫星系统)的人从事诸如数据库设计和商业应用软件的开发。甚至有些高级工程师是来自政府研究和发展机构。这样一种资源转换是同我们先前假设的软件发展在印度所具有的相对优势所吻合的。当然，印度经济存在很多扭曲的地方，这些都是在解读市场信号时所应该警惕的。除了上述提到的改变经济活动的组成，市场对工程师和经理人日益增加的需求也将影响经济活动的组织。正如我们在第六部分以更多笔墨讨论的那样，对受训过的工程师和管理人员的需求增加也将影响资本和劳动力(或者更确切的说物质资本和人力资本)之间的平衡，从而引发组织革新。 对人力资本更多的回报也引发了对其更多的投资。印度的中产阶级，总是依赖于教育，特别是诸如工程师和医生的职业教育，作为改善经济状况的一种手段。然而印度经济的缓慢增长，使这类投资的回报率显得并不很高。政府公共财政的谨慎状态也限制了中央和州政府扩张第三方教育的能力。然而，快速增长的软件部门迅速分散。在软件产业内发展最迅速的部门之一既是私人培训。 私人培训机构对个体在软件开发工作方面进行专门培训。NASSCOM 估计，在1998年，有3800家类似于的培训机构，而市场潜力却是有30，000，000美元，尽管其中的70%相信被NIIT和Aptech所占领。私人培训机构在帮助在职软件开发员获得新的技术上也是非常重要的。很多工程师也参加私人培训机构进修。私人培训机构在印度城市的出现，使软件开发人员获得这些机构的认证和证书的变得更加可能。 同时值得一提的是，这是私人部门对市场机会--对特殊技能训练需求的反应。在美国和其它的国家，公司为了利益会和各种各样的公共机构(如公立大学)进行竞争。在印度，私人培训机构的快速成长，表明经济环境的变化和企业家行为从纯粹的寻租向经济效率性领域转轨。这种转变至少间接上是归因于软件产业的快速发展。 综上所述，我们认为，直到现在，证据显示受过训练的工程类人才的过度供给是印度公司一个巨大的竞争优势。同样的，这种过度供给也将导致公司缺乏人尽其用的激励。甚至，产业发展和高工资不断不仅吸引着新毕业的工程师，还吸引了包括工程师、经理和来自其它产业部门的专家。 尽管如此，软件产业的爆炸性成长使很多公司认识到技术型的工程师、软件专业人士和优秀的经理是一种稀缺资源。另外，面临着更诱人的选择(如移民海外)，那些很有天赋的工程师和经理也在寻找更高的回报率和更专业化的工作环境。因此，这引出了我们接下来对各种组织结构转变的讨论。 ?-1