Learning, Innovation and Economic Growth: A Long-run Model of Industrial Dynamics

Silverberg, Gerald; Verspagen, Bart

doi:10.1093/icc/3.1.199

Cited by 93 publications

(52 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…As one of the early evolutionary models of technological change (Silverberg and Verspagen, 1994) puts it, requirements needed to genuinely model endogenous growth are (i) coexistence of many technologies and techniques of production at any given time period; (ii) no unique production function (coexistence of multiple techniques of production even at the frontier); (iii) dependence of the aggregate rate of technical change on diffusion of innovation, not simply on the instantaneous innovation rate; (iv) if the innovative effort is represented by a stochastic draw from probability distributions, the parameters of the distributions have to be unknown for firms.…”

Section: Innovation and Growthmentioning

confidence: 99%

In order to stand up you must keep cycling: Change and coordination in complex evolving economies

Dosi

Virgillito

2021

Structural Change and Economic Dynamics

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. In this work we discuss the main building blocks, achievements and challenges of an evolutionary interpretation of the relation between mechanisms of coordination and drivers of change in modern economies, seen as complex evolving systems. It is an evident stylised fact of modern economic systems that there are forces at work which keep them together and make them grow despite rapid and profound modifications of their industrial structures, social relations, techniques of production, patterns of consumption. We suggest that a fruitful interpretation of the two processes rests in what we call the "bicycle conjecture": in order to stand up you must keep cycling. However, changes and transformation are by nature "disequilibrating" forces. Thus there must be other factors which maintain relatively ordered configurations of the system and allow a broad consistency between the conditions of material reproduction (including income distributions, accumulation, available techniques) and the thread of social relations. Terms of use: Documents in

show abstract

Section: Innovation and Growthmentioning

confidence: 99%

In order to stand up you must keep cycling: Change and coordination in complex evolving economies

Dosi

Virgillito

2021

Structural Change and Economic Dynamics

View full text Add to dashboard Cite

show abstract

“…4 This approach parallels some of the work in evolutionary economics that stresses the positive effect of learning behaviour on company performance in a dynamic context. For instance, Verspagen (1994 and found that in a world of technological change firms do not necessarily demonstrate short-term optimal, efficient behaviour, instead a long-term, learning-oriented behaviour was found to generate higher returns. The analysis of Allen (1988) also shows that in a dynamic economic environment, learning through various contacts pays off as this behaviour can outperform short-term maximizing behaviour that concentrates on the efficiency in existing contacts.…”

Section: A Learning Perspective On Networkmentioning

confidence: 99%

Learning in Dynamic Inter-Firm Networks: The Efficacy of Multiple Contacts

Hagedoorn

Duysters

2002

Organization Studies

212

155

View full text Add to dashboard Cite

This paper examines the relevance of both an efficiency-based network strategy and a learningbased network strategy in the context of inter-firm partnering. The effect of these different forms of network behaviour on company performance is analysed for companies in the international computer industry. Strategies associated with learning through so-called exploratory networks appear to generate a greater impact on technological performance in a dynamic environment than efficiency strategies through exploitative networks.(Networks, learning, technological performance) 1 INTRODUCTIONThe objective of this paper is to evaluate different network strategies that can guide companies in setting up network-ties with other companies through which they gain access to information that enables them to achieve higher performance than other network players. This particular perspective follows some recent developments in academic work on networks (Burt 1992a and b;Freeman, 1979;Powell, Koput and Smith-Doerr, 1996;Walker, Kogut and Shan, 1997) where the attention paid to the strategic behaviour of network players coincides with a refocusing of research from the traditional laboratory setting or a purely theoretical approach to empirical research. This increase of empirical network analysis particularly affects the current management and organization literature that focuses on the effect of both intra-and intercompany networks on company performance. According to some, the practical and strategic implications of recent empirical network analysis might even go as far as offering $... a manual for those wishing to optimize their instrumental networks ...# (Andrews, 1995, p. 355) in a concrete business setting.In the following we will refer to two different network analytical approaches where either efficiency or learning is placed in the context of strategic players who are using networks in which they operate to improve their own performance vis à vis other players. The expected higher performance of strategic players, then, is linked to their ability to access information about rewarding opportunities, applying a network strategy that is based on either maximum efficiency in setting up network-ties or based on learning through multiple contacts with a number of companies. 1One of the practical implications of our critical evaluation of modern network analysis 2 is that we will qualify some of its instrumentalist and concrete suggestions. In our opinion, concrete advice based on applied network analysis in a market environment can easily lead to some misleading suggestions for the network strategies of companies, unless proper attention is paid to the environmental and behavioural conditions of networks. The main point we are making below is that in a dynamic environment, efficiency behaviour, which might pay off in a static environment, will lose its purpose. Strict maximizing rules for the efficiency of networks, for instance with a preference for so-called non-redundant contacts, might be rational in a static environment, but ...

show abstract

“…Contrarily, Unger argues that developing countries, due to needing new skills and also rare entrepreneurship resources, will be "on the edge of vain rotation". Institutional and social circumstances: Abramovitz argues that a country is able to develop rapidly in which backwardedness is not due to incompetency [4], [11] However, when the country is technologically back warded, but enjoys social advantage, the situation is provided for quick growth [12] Abramovitz considers such facilities as international technical communications channels, international trade circumstances, and direct foreign investment as significant in knowledge distribution [13][14][15]. Macro policy-making and development plan: Tunzelmann (1995) shows that in dynamism perception, the appropriate technology to choose is not the one that is compatible with our advantages and talents, rather the quality of talents increase for long term advantage is significant [14,16] He believes that in any case of successful quick access, it begins with focusing on the process.…”

Section: Domestic Structuresmentioning

confidence: 99%

A quantitative model of technological catch-up

Gholizadeh¹,

Naeini

Moini

2015

IJET

View full text Add to dashboard Cite

This article presents a quantitative model for the analysis of technological gap. The rates of development of technological leaders and followers in nanotechnology are expressed in terms of coupled equations. On the basis of this model (first step) comparative technological gap and rate of that will be studied. We can calculate the dynamics of the gap between leader and follower. In the Second step, we estimate the technology gap using the metafrontier approach. Then we test the relationship between the technology gap and the quality of dimensions of the Catch-up technology which were identified in previous step. The usefulness of this approach is then demonstrated in the analysis of the technological gap of nanotechnology in Iran, the leader in Middle East and the world. We shall present the behaviors of the technological leader and followers. At the end, analyzing Iran position will be identified and implying effective dimension of catch-up Suggestions will be offered which could be a fundamental for long-term policies of Iran.

show abstract

Learning, Innovation and Economic Growth: A Long-run Model of Industrial Dynamics

Cited by 93 publications

References 0 publications

In order to stand up you must keep cycling: Change and coordination in complex evolving economies

In order to stand up you must keep cycling: Change and coordination in complex evolving economies

Learning in Dynamic Inter-Firm Networks: The Efficacy of Multiple Contacts

A quantitative model of technological catch-up

Contact Info

Product

Resources

About