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ItemBridging innovation system research and development studies: challenges and research opportunities(Georgia Institute of Technology, 2009-10-08) Lundvall, Bengt-Åke ; Vang, Jan ; Joseph, K. J. ; Chaminade, CristinaThis paper links innovation system analysis to economic development. Both fields are young and interdisciplinary. The origins of research on innovation systems goes back to the early 1980s (Freeman 1982, Lundvall 1985, Freeman 1987) although it links to several predecessors such as Babbage (1832, 3rd edition), List (1941) or Marshall (1965). Development economics, on the other hand, took off in the 1940s (Rosenstein-Rodan 1943) but, since then, it has been going through so many dramatic changes that yet cannot be characterised as a ‘mature’ field. In the recent years, particularly in the framework of Globelics, there has been a renewed interest on applying the innovation system concept in developing countries. However, some critical questions remained unanswered: Is innovation system a useful concept for understanding and explaining what goes on in a developing country? Can it be used as a tool and a framework for agents and agencies in charge of designing public policy and business innovation strategies? The assumption behind this paper is that we can answer a conditional ‘yes’ to both of these questions and in the first part of this paper we try to specify the conditions and we do so in a dialogue with critiques developed within the community of evolutionary and development scholars. Another important question is how the approach fits into the historical and current trends in development economics. In the second part of the paper we give a brief assessment of how development economics has evolved and we draw some lessons for a research strategy. We will argue that the crisis of the first generation of development economics that was represented by scholars such as Nurkse, Myrdal, Hirschman, Singer and Sen has left a void in development economics that cannot be filled neither by mainstream neoclassical economics nor by ‘new growth theory’. We see the innovation system approach as a serious candidate to fill this void. The paper is structured as follows. In the next section we review the concept of innovation system (in dialogue with other alternative concepts like national learning systems), the different forms of studying innovation systems and the critical dimensions to consider when studying innovation systems, particularly in developing countries. Section 3 reviews the recent evolution of Development Economics, pointing out to the main weakness of this discipline, particularly when it comes to the analysis of the factors underlying under-development. Section 4 proposes and discusses how innovation system research can contribute to development economics and vice-versa. The paper concludes highlighting the main research gaps in innovation systems and development and proposes a future research agenda in this topic.
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ItemInnovation policies for development: towards a systemic experimentation based approach(Georgia Institute of Technology, 2009-10-07) Chaminade, Cristina ; Lundvall, Bengt-Åke ; Vang-Lauridsen, Jan ; Joseph, K. J.This paper sheds light on how to address, conceptualize and design innovation policies taking into account the specific characteristics of innovation systems in developing countries. The main purpose is to reflect on the policy implications of adopting the innovation system perspective to the particularities of developing countries. It is only recently that the concept of innovation has entered the development discourse and subsequently the agenda of policy-makers in developing countries and international aid organizations (UNCTAD 2007, UNIDO 2007, Farley et al. 2007). Implementing innovation policies in developing countries has proved to be a challenging task. Academics, development practitioners and policy-makers are still struggling with understanding how to conceptualize innovation in developing countries, identifying who are the beneficiaries of innovation processes and more generally conceptualizing innovation system policies in the South (Lundvall et al, 2006; Borras et al, 2008; Intarakumnerd and Chaminade, 2007). Furthermore, in designing innovation policies, policy makers often lack tools for identifying problems in the system and for selecting policies supporting innovation and competence building to tackle them. Innovation systems in developing countries are very heterogeneous. Each system is embedded in a unique socio-economic institutional context and, in this sense, it is not possible to identify innovation policies that could be applied to all developing countries. Neither is this the purpose of this paper. However, the growing literature of innovation systems in developing countries suggests that innovation systems in developing countries differ from the mature innovation systems that we might find in the developed economies. Substantial differences in components and relationships indicate that just imitating innovation policies practiced in developed countries is unlikely to deliver the expected results. The purpose of this paper is to point out to the main differences between (most) innovation systems in developing countries and (most) innovation systems in developed countries and discuss the implications that these differences have for the identification of problems and opportunities. There are different analytical frameworks for the identification of these problems. As opposed to the market-failure model proposed by the neoclassical analysis (Arrow, 1962) scholars in the system of innovation approach, propose to focus on systemic failures (Smith, 2000, Woolthuis et al, 2005, Chaminade and Edquist, 2006). In this paper we investigate how far this framework is useful for designing innovation policies in developing countries. The reminder of this paper is structured as follows: First, we explain why innovation policy is relevant in developing countries. Then, we introduce what is meant by systemic problems, and apply the concept to developing countries. One of our main conclusions is the need to combine the concept of systemic failures with a pragmatic experimental approach. The main features of such experimental approach are presented in the last section of the paper.
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ItemIs there a need to develop new rules of the game at the global level to compensate development countries for brain-drain?(Georgia Institute of Technology, 2008-09) Joseph, K. J.
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ItemLeader in production but a laggard in consumption? Innovation System and IT Diffusion in India’s manufacturing sector(Georgia Institute of Technology, 2008-09) Abraham, Vinoj ; Joseph, K. J.It may be paradoxical that a developing country like India, while having only a negligible share in world trade, has been able to record remarkable export performance, mostly at the instance of domestic firms, in a knowledge intensive sector like IT software and services. and that has attracted world attention. While this achievement is highly laudable, the real return from a General Purpose Technology (GPT) like ICT is accrued when it is harnessed for enhancing the productivity and competitiveness of different sectors of the economy and welfare gains for different sections of the society. In the current era of globalization and intense international competition the ability to reap such returns could help ensure the survival of the developing countries and their catch up. The relevant question in case of India is its success with respect to harnessing the new technology for addressing various development problems. While, there are a number of studies on the use of ICT in agriculture and other service sectors including e-governance, the issue of IT diffusion in India’s manufacturing sector has not yet attracted the attention of researchers that it deserves. In this context the present study is an attempt at addressing this issue by making use of a unique dataset on the IT investment in India’s manufacturing sector furnished by the Annual Survey of Industries. Conventional approach towards analyzing the diffusion process involves estimation of diffusion curves which considers diffusion process analogous to the occurrence of an ‘epidemic disease’ within a population (Rogers 1962). Such analyses, cast mostly in the neoclassical framework involves analysis of the time path of the technology adoption process by estimating the sigmoid or S shaped curve. Most of the studies in this tradition (see Karshenhas and Stoneman 1995 for a survey) also indicate that inter-firm diffusion differs across industries and technologies and has highlighted a number of technology specific, adopter-specific and other factors like the environment in which the adopter operates that influence the diffusion process. Apart from the greater focus on demand side factors at the cost of supply side factors influencing diffusion process, it is also assumed that technology remain the same during the diffusion process. More importantly, these traditional analytical models fail to take care of the changes that take place in the environment wherein the diffusion process and those that occur at the original innovation itself (Freeman, 2003). In the evolutionary theory, that forms the theoretical foundation for the innovation systems approach, approach Nelson and Winter (1982) rejects the models that assume full information and classical rationality and instead postulates limited information and bounded rationality. They sustain that both the course and the rhythm of the diffusion process are not easily given, and are intertwined with a combination of elements such as: organizational routines, profitability expected by firms of the sector; consumers’ preferences and existing regulatory devices, as well as the imitation process. This paper follows the innovation system perspective to address the issue at hand.