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Models for Innovation Diffusion by Vijay Mahajan,Robert A. Peterson Pdf
Presents a powerful set of techniques for investigating the temporal diffusion process of any innovation. In addition, this volume outlines several widely used diffusion models and suggests their appropriate applications.
Models for Innovation Diffusion by Vijay Mahajan,Robert A. Peterson Pdf
Presents a powerful set of techniques for investigating the temporal diffusion process of any innovation. In addition, this volume outlines several widely used diffusion models and suggests their appropriate applications.
Network Models of the Diffusion of Innovations by Thomas W. Valente Pdf
This text presents a key to understanding how ideas, products and opinions take off and spread throughout society - referred to as the diffusion of innovation - and provides a means to estimate how fast or slow that spread occurs. The diffusion of innovations occurs among individuals in a social system, and the pattern of communications among these individuals is a social network. The network determines how quickly innovations diffuse and the timing of each individual's adoption. The book thus analyses how social networks structure the diffusion of innovation.
Getting an innovation adopted is difficult; a common problem is increasing the rate of its diffusion. Diffusion is the communication of an innovation through certain channels over time among members of a social system. It is a communication whose messages are concerned with new ideas; it is a process where participants create and share information to achieve a mutual understanding. Initial chapters of the book discuss the history of diffusion research, some major criticisms of diffusion research, and the meta-research procedures used in the book. This text is the third edition of this well-respected work. The first edition was published in 1962, and the fifth edition in 2003. The book's theoretical framework relies on the concepts of information and uncertainty. Uncertainty is the degree to which alternatives are perceived with respect to an event and the relative probabilities of these alternatives; uncertainty implies a lack of predictability and motivates an individual to seek information. A technological innovation embodies information, thus reducing uncertainty. Information affects uncertainty in a situation where a choice exists among alternatives; information about a technological innovation can be software information or innovation-evaluation information. An innovation is an idea, practice, or object that is perceived as new by an individual or an other unit of adoption; innovation presents an individual or organization with a new alternative(s) or new means of solving problems. Whether new alternatives are superior is not precisely known by problem solvers. Thus people seek new information. Information about new ideas is exchanged through a process of convergence involving interpersonal networks. Thus, diffusion of innovations is a social process that communicates perceived information about a new idea; it produces an alteration in the structure and function of a social system, producing social consequences. Diffusion has four elements: (1) an innovation that is perceived as new, (2) communication channels, (3) time, and (4) a social system (members jointly solving to accomplish a common goal). Diffusion systems can be centralized or decentralized. The innovation-development process has five steps passing from recognition of a need, through R&D, commercialization, diffusions and adoption, to consequences. Time enters the diffusion process in three ways: (1) innovation-decision process, (2) innovativeness, and (3) rate of the innovation's adoption. The innovation-decision process is an information-seeking and information-processing activity that motivates an individual to reduce uncertainty about the (dis)advantages of the innovation. There are five steps in the process: (1) knowledge for an adoption/rejection/implementation decision; (2) persuasion to form an attitude, (3) decision, (4) implementation, and (5) confirmation (reinforcement or rejection). Innovations can also be re-invented (changed or modified) by the user. The innovation-decision period is the time required to pass through the innovation-decision process. Rates of adoption of an innovation depend on (and can be predicted by) how its characteristics are perceived in terms of relative advantage, compatibility, complexity, trialability, and observability. The diffusion effect is the increasing, cumulative pressure from interpersonal networks to adopt (or reject) an innovation. Overadoption is an innovation's adoption when experts suggest its rejection. Diffusion networks convey innovation-evaluation information to decrease uncertainty about an idea's use. The heart of the diffusion process is the modeling and imitation by potential adopters of their network partners who have adopted already. Change agents influence innovation decisions in a direction deemed desirable. Opinion leadership is the degree individuals influence others' attitudes.
New-Product Diffusion Models by Vijay Mahajan,Eitan Muller,Yoram Wind Pdf
Product sales, especially for new products, are influenced by many factors. These factors are both internal and external to the selling organization, and are both controllable and uncontrollable. Due to the enormous complexity of such factors, it is not surprising that product failure rates are relatively high. Indeed, new product failure rates have variously been reported as between 40 and 90 percent. Despite this multitude of factors, marketing researchers have not been deterred from developing and designing techniques to predict or explain the levels of new product sales over time. The proliferation of the internet, the necessity or developing a road map to plan the launch and exit times of various generations of a product, and the shortening of product life cycles are challenging firms to investigate market penetration, or innovation diffusion, models. These models not only provide information on new product sales over time but also provide insight on the speed with which a new product is being accepted by various buying groups, such as those identified as innovators, early adopters, early majority, late majority, and laggards. New Product Diffusion Models aims to distill, synthesize, and integrate the best thinking that is currently available on the theory and practice of new product diffusion models. This state-of-the-art assessment includes contributions by individuals who have been at the forefront of developing and applying these models in industry. The book's twelve chapters are written by a combined total of thirty-two experts who together represent twenty-five different universities and other organizations in Australia, Europe, Hong Kong, Israel, and the United States. The book will be useful for researchers and students in marketing and technological forecasting, as well as those in other allied disciplines who study relevant aspects of innovation diffusion. Practitioners in high-tech and consumer durable industries should also gain new insights from New Product Diffusion Models. The book is divided into five parts: I. Overview; II. Strategic, Global, and Digital Environments for Diffusion Analysis; III. Diffusion Models; IV. Estimation and V. Applications and Software. The final section includes a PC-based software program developed by Gary L. Lilien and Arvind Rangaswamy (1998) to implement the Bass diffusion model. A case on high-definition television is included to illustrate the various features of the software. A free, 15-day trial access period for the updated software can be downloaded from http://www.mktgeng.com/diffusionbook. Among the book's many highlights are chapters addressing the implications posed by the internet, globalization, and production policies upon diffusion of new products and technologies in the population.
Innovation Diffusion Models by Mariangela Guidolin Pdf
Innovation Diffusion Models Understand innovation diffusion models and their role in business success Innovation diffusion models are statistical models that predict the medium- and long-term sales performance of new products on a market. They account for numerous factors that contribute to the life cycle of a new product and are subject to continuous reassessment as markets transform and the business world becomes more complex. In a modern market environment where product life cycles are becoming ever shorter, the latest innovation diffusion models are essential for businesses looking to perfect their decision-making processes. Innovation Diffusion Models: Theory and Practice provides a comprehensive and up-to-date guide to these models and their potential to impact product development. It focuses on the latest product diffusion models, which combine time series analysis with nonlinear regression techniques to create increasingly refined predictions. Its combination of mathematical theory and business practice makes it an indispensable tool across many sectors of industry and commerce. Innovation Diffusion Models readers will also find: Real-world examples demonstrating the kinds of data sets generated by new product growth models and their potential applications Discussion of the factors underlying the decision to select a given growth model for a particular product Clear, detailed explanation of each model’s explanatory ability Innovation Diffusion Models is an essential volume for practitioners in any field of industry or commerce, as well as for graduate students and researchers in business and finance.
Innovation Diffusion Models by Mariangela Guidolin Pdf
Innovation Diffusion Models Understand innovation diffusion models and their role in business success Innovation diffusion models are statistical models that predict the medium- and long-term sales performance of new products on a market. They account for numerous factors that contribute to the life cycle of a new product and are subject to continuous reassessment as markets transform and the business world becomes more complex. In a modern market environment where product life cycles are becoming ever shorter, the latest innovation diffusion models are essential for businesses looking to perfect their decision-making processes. Innovation Diffusion Models: Theory and Practice provides a comprehensive and up-to-date guide to these models and their potential to impact product development. It focuses on the latest product diffusion models, which combine time series analysis with nonlinear regression techniques to create increasingly refined predictions. Its combination of mathematical theory and business practice makes it an indispensable tool across many sectors of industry and commerce. Innovation Diffusion Models readers will also find: Real-world examples demonstrating the kinds of data sets generated by new product growth models and their potential applications Discussion of the factors underlying the decision to select a given growth model for a particular product Clear, detailed explanation of each model’s explanatory ability Innovation Diffusion Models is an essential volume for practitioners in any field of industry or commerce, as well as for graduate students and researchers in business and finance.
Benoît Godin is a Professor at the Institut national de la recherche scientifique, Montreal. Models abound in science, technology, and society (STS) studies and in science, technology, and innovation (STI) studies. They are continually being invented, with one author developing many versions of the same model over time. At the same time, models are regularly criticized. Such is the case with the most influential model in STS-STI: the linear model of innovation. In this book, Benoît Godin examines the emergence and diffusion of the three most important conceptual models of innovation from the early twentieth century to the late 1980s: stage models, linear models, and holistic models. Godin first traces the history of the models of innovation constructed during this period, considering why these particular models came into being and what use was made of them. He then rethinks and debunks the historical narratives of models developed by theorists of innovation. Godin documents a greater diversity of thinkers and schools than in the conventional account, tracing a genealogy of models beginning with anthropologists, industrialists, and practitioners in the first half of the twentieth century to their later formalization in STS-STI. Godin suggests that a model is a conceptualization, which could be narrative, or a set of conceptualizations, or a paradigmatic perspective, often in pictorial form and reduced discursively to a simplified representation of reality. Why are so many things called models? Godin claims that model has a rhetorical function. First, a model is a symbol of “scientificity.” Second, a model travels easily among scholars and policy makers. Calling a conceptualization or narrative or perspective a model facilitates its propagation.
Diffusion and Adoption of Information Technology by Karlheinz Kautz,Jan Pries-Heje Pdf
It. is well known that t.he introduction of a new technology in one organization not always produces the intended benefits (Levine, 1994). In many cases, either the receivers do not reach the intended level of use or simply the technology is rejected because it does not match with the expectations (true or false) and the accepted psychological effort to use it. The case of formal methods is a paradigmatic example of continual failures. The published cases with problems or failures only constitute the visible part of a large iceberg of adoption cases. It. is difficult to get companies to openly express the problems they had; however, from the experience of the author, failure cases are very common and they include any type of company. Many reasons to explain the failures (and in some cases the successes) could be postulated; however, the experiences are not structured enough and it is difficult to extract from them useful guidelines for avoiding future problems. Generally speaking, there is a trend to find the root of the problems in the technol ogy itself and in its adequacy with the preexistent technological context. Technocratic technology transfer models describe the problems in terms of these aspects. Although it is true that those factors limit the probability of success, there is another source of explanations linked to the individuals and working teams and how they perceive the technology.
Knowledge Diffusion and Innovation by Piergiuseppe Morone,Richard Taylor Pdf
The book uses state-of-the-art theorizing about a topic that has attracted a lot of attention in the past five years or so. It provides a very useful review of the literature, and is very well written and on a novel topic. I especially liked the methodological rigour in the exposition of the model, yet at the same time the text remains accessible to a wide readership. I highly recommend the book. Koen Frenken, Utrecht University, The Netherlands Modern economies are described as knowledge based . This book investigates the meaning of such a statement, assessing the relevance of knowledge and the channels through which knowledge is exchanged, both from a theoretical and an empirical perspective. Moving within the realm of complexity theory, the authors provide a methodological assessment of the knowledge diffusion debate as well as presenting theoretical and applied models of knowledge diffusion and innovation. They illustrate how geography plays a role in shaping innovative patterns and how dense networks generally result in more innovative environments. The book concludes that establishing the right connections within such dense networks appears to be more crucial than any other factor, thus highlighting the importance of linkages (or the effects of their absence) within innovation systems. Proposing a taxonomy of knowledge-sharing patterns, this book will be warmly welcomed by academics, researchers and postgraduate students in the areas of the economics of innovation, evolutionary economics and knowledge economics.
Diffusion of Innovations, 4th Edition by Everett M. Rogers Pdf
Since the first edition of this landmark book was published in 1962, Everett Rogers's name has become "virtually synonymous with the study of diffusion of innovations," according to Choice. The second and third editions of Diffusion of Innovations became the standard textbook and reference on diffusion studies. Now, in the fourth edition, Rogers presents the culmination of more than thirty years of research that will set a new standard for analysis and inquiry. The fourth edition is (1) a revision of the theoretical framework and the research evidence supporting this model of diffusion, and (2) a new intellectual venture, in that new concepts and new theoretical viewpoints are introduced. This edition differs from its predecessors in that it takes a much more critical stance in its review and synthesis of 5,000 diffusion publications. During the past thirty years or so, diffusion research has grown to be widely recognized, applied and admired, but it has also been subjected to both constructive and destructive criticism. This criticism is due in large part to the stereotyped and limited ways in which many diffusion scholars have defined the scope and method of their field of study. Rogers analyzes the limitations of previous diffusion studies, showing, for example, that the convergence model, by which participants create and share information to reach a mutual understanding, more accurately describes diffusion in most cases than the linear model. Rogers provides an entirely new set of case examples, from the Balinese Water Temple to Nintendo videogames, that beautifully illustrate his expansive research, as well as a completely revised bibliography covering all relevant diffusion scholarship in the past decade. Most important, he discusses recent research and current topics, including social marketing, forecasting the rate of adoption, technology transfer, and more. This all-inclusive work will be essential reading for scholars and students in the fields of communications, marketing, geography, economic development, political science, sociology, and other related fields for generations to come.
Diffusion, or the widespread adoption of innovations, is a critical yet under-researched topic. There is a wide gap between development and successful adoption of an innovation. Therefore, a better understanding of why and how an innovation is adopted can help develop realistic management and business plans. Most books on this topic use a single-discipline approach to explain the diffusion of innovations. This book adopts a multi-disciplinary and managerial process approach to understanding and promoting the adoption of innovations, based on the latest research and practice. It will be of interest to graduates and researchers in marketing, product development and innovation courses.
