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This paper attributes the slow diffusion of innovations to an informational externality in the process of their adoption. When a new technology arrives its profitability is uncertain but each firm can learn progressively through observing the adoption experience of other firms. Given this prospect of social learning, every firm would prefer that other firms adopt before it does because this enables a better-informed adoption decision. In the absence of explicit coordination, the firms could end up in a sequence of waiting contests; this results in staggered adoptions even when all firms are ex-ante identical. The pace of diffusion is determined endogenously in this model and shown to depend on the characteristics of the innovation and of the learning process.
Wee felt it before in sense; but now wee know it by science. Edward Misselden (1623) The collective effort reported in this volume is the outcome of the diffusion of the idea of diffusion as a fundamental process in society. The considerable number of disciplines represented here indicates the weight of the problem area. The editors are to be congratulated for their initiative in drawing together present thinking at a vivid meeting, now also in print. An old timer in the business has not much to add. But maybe some things, bearing in mind that a Preface is a celebration and not a review. As always with ideas it is hard to identify those who first gave shape to the idea of diffusion. In a general sense it is probably an observation as old as human self-reflection that groups of populations exchange ideas and copy habits and implements from each other. Sometimes it has even been recommended, as a Chinese proverb suggested millenia ago, "If you want to become a good farmer, look at your neighbor" .
This article explores the mechanisms through which social learning mediates technology diffusion. We exploit an experiment on the dissemination of biochar, a soil amendment that can improve fertility on weathered and/or degraded soils. We find that social networks transmit information about the average benefits of adoption, but also its risk, and that observed variability inhibits uptake to a greater degree than positive average results engender it. Paradoxically, this relationship is stronger among networks that do not discuss farming, but disappears among farmer networks that do. This is resolved with a simple model of social learning about conditional, rather than unconditional benefit distributions. As farmers observe factors associated with outcomes in their networks, they constrain the distribution of their own potential outcomes. This conditional distribution diverges from the unconditional distribution that the econometrician observes. We conclude that social learning is characterized by implicit model-building by sophisticated decision makers, rather than simple herding towards observed good results.
This work explores the social processes involved in technological innovation, particularly in relation to the Information and Communications Technologies (ICTs).
The past few decades have witnessed a widening of the digital divide among countries in the world. Bridging this global digital divide has now become an important development policy of many governments in the developing world. Differing from previous studies that look at the Internet's popularity, this paper focuses on the speed of diffusion of such technologies over the period from 1997 to 2002 in order to highlight its role as a critical driving force in enhancing the social learning of a country. Our empirical results show that a country with better social learning can harmonize its heterogeneous populations, promote the sharing of knowledge as a result of using such technologies, and finally speed up the rate of information technology diffusion.
This title was first published in 2001. Offering a fascinating new perspective on the processes of technical and social change, this book complements contemporary innovation studies by adopting an integrative perspective on social learning as characterized by the introduction of educational multimedia. The contributors provide insights into policy making in the fields of education and multimedia, educational practices related to the use of multimedia and wider processes of technical change. Accessible in style, the book will appeal to researchers and policy makers alike and will be of particular relevance to those interested in education, media, science and technology.
Technological Learning in the Transition to a Low-Carbon Energy System: Conceptual Issues, Empirical Findings, and Use in Energy Modeling quantifies key trends and drivers of energy technologies deployed in the energy transition. It uses the experience curve tool to show how future cost reductions and cumulative deployment of these technologies may shape the future mix of the electricity, heat and transport sectors. The book explores experience curves in detail, including possible pitfalls, and demonstrates how to quantify the 'quality' of experience curves. It discusses how this tool is implemented in models and addresses methodological challenges and solutions. For each technology, current market trends, past cost reductions and underlying drivers, available experience curves, and future prospects are considered. Electricity, heat and transport sector models are explored in-depth to show how the future deployment of these technologies--and their associated costs--determine whether ambitious decarbonization climate targets can be reached - and at what costs. The book also addresses lessons and recommendations for policymakers, industry and academics, including key technologies requiring further policy support, and what scientific knowledge gaps remain for future research. Provides a comprehensive overview of trends and drivers for major energy technologies expected to play a role in the energy transition Delivers data on cost trends, helping readers gain insights on how competitive energy technologies may become, and why Reviews the use of learning curves in environmental impacts for lifecycle assessments and energy modeling Features social learning for cost modeling and technology diffusion, including where consumer preferences play a major role
How well suited are the institutions of a region, nation or international regime to the task of coping with the dramatic changes currently underway in the global economy? This volume examines this issue.
Technology intermediaries are seen as potent vehicles for addressing perennial problems in transferring technology from university to industry in developed and developing countries. This paper examines what constitutes effective user-end intermediation in a low technology, developing economy context, which is an under-researched topic. The social learning in technological innovation (SLTI) framework is extended using situated learning theory in a longitudinal instrumental case study of an exemplar technology intermediation programme. The paper documents the role that academic-related research and advisory centres can play as intermediaries in brokering, facilitating and configuring technology, against the backdrop of a group of small-scale pisciculture businesses in a rural area of Colombia. In doing so, it demonstrates how technology intermediation activities can be optimised in the domestication and innofusion of technology amongst end-users. The design components featured in this instrumental case of intermediation can inform policy making and practice relating to technology transfer from university to rural industry. Future research on this subject should consider the intermediation components put forward, as well as the impact of such interventions, in different countries and industrial sectors. Such research would allow for theoretical replication and help improve technology domestication and innofusion in different contexts, especially in less developed countries.
In recent decades, the world has witnessed, unprecedented in terms of speed and geographic coverage, diffusion of new information and communication technologies (ICT). The on-going digital revolution pervasively impacts and reshapes societies and economies and therefore deserves special attention and interest. This book provides extensive evidence on information and communication technologies development patterns and dynamics of this process across developed economies over the period 1980 to the present day. It adopts newly developed methodology to identification of the ‘critical mass’ and isolation of technological takeoff intervals, which are intimately related to the process of technology diffusion. The statistically robust analysis of country-specific data demonstrates the key economic, social and institutional prerequisites of ICT diffusion across examined countries, indicating what factors significantly foster or – reversely – hinder the process.