The current economic theory of innovation mainly analyses the technology factor and its impact on economic growth. In today's world, growth in information technology and knowledge of new ideas has altered the business paradigm dramatically. Modern economies have undergone a dynamic shift from material manufacturing to a new information technology model with research and development (R&D) and human capital. Through information and communications technology efficient information usage has achieved substantial productivity gains through learning by doing and incremental innovations. The present volume discusses this new paradigm in terms of both theory and industry applications, including Schumpeter in his innovation model and the emphasis on new innovations replacing the old. Growth of business networking and R&D consortium have dramatically helped the modern business to reduce their unit costs and improve efficiency. This volume presents some new models emphasizing knowledge sharing and R&D cooperation. Rapid growth in recent times in some south Asian countries have been cited as growth miracles are largely caused by knowledge spillover and learning by doing, and this volume also investigates the role of incremental innovations. With a strong focus and extension of the current theory of innovation and industry growth experiences of both the US and Asian countries, this book will be of interest to MBA and graduate students in economics, innovation management, and applied industrial economics.
With the increasingly complex and ubiquitous data available through modern technology, digital information is being utilized daily by academics and professionals of all disciplines and career paths. Information Seeking Behavior and Technology Adoption: Theories and Trends brings together the many theories and meta-theories that make information science relevant across different disciplines. Highlighting theories that had their base in the early days of text-based information and expanding to the digitization of the Internet, this book is an essential reference source for those involved in the education and training of the next-generation of information science professionals, as well as those who are currently working on the design and development of our current information products, systems, and services.
The contemporary economy is primarily understood through the rationalist and formalist lenses of economic theory and its accompanying (mainstream) theories of organization and management. In this corpus of work, the economy is commonly portrayed as emerging on the basis of the calculated and instrumental use of heterogeneous resources. Innovation - the capacity to produce new goods and services, being of key importance in a competitive capitalist economic regime - is a joint collaborative process embedded in social action, i.e., through forms of agency. In contrast to individualist, calculative, and utilitarian images of economic agency, sociologists, historians, anthropologists, and others have demonstrated that economic agency is determined in many cases by social and cultural conditions that extend beyond the narrow sphere of instrumental economic behavior. A Social Theory of Innovation makes a connection between innovation, economic agency, and three complementary perspectives - i.e. those of playfulness, reciprocity, and squandering (the conspicuous and symbolic waste of excess resources) - in terms of being three principles that underlie innovative and creative work. Rather than postulating the homo oeconomicus model of economic agency - prescribed by neoclassical economic theory - as the only possible and legitimate image of economic agency, alternative models exist which in various ways contribute to our understanding of how and why innovation is produced in contemporary society. The book draws on a diverse corpus of literature from management studies, economics, economic sociology, and the humanities to provide a less confined and narrow image of innovation and economic agency. This book is intended for undergraduate, graduate, and post-graduate business school curricula in both economic sociology and other educational programs addressing the organization of the economy and society at large.
'National Systems of Innovation' presents a new perspective on the dynamics of the national and the global economy. Its starting point is that the international competitiveness of nations is founded on innovation. Which role do different parts of the national system play in determining the long-term dynamics of the economy? What is happening to the coherence of national systems of innovation in an era characterised by far-reaching internationalisation and globalisation? These and other issues are addressed in this volume. Available for the first time in paperback, the book is an invaluable resource for scholars and policy-makers.
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.
Now in its fifth edition, Diffusion of Innovations is a classic work on the spread of new ideas. In this renowned book, Everett M. Rogers, professor and chair of the Department of Communication & Journalism at the University of New Mexico, explains how new ideas spread via communication channels over time. Such innovations are initially perceived as uncertain and even risky. To overcome this uncertainty, most people seek out others like themselves who have already adopted the new idea. Thus the diffusion process consists of a few individuals who first adopt an innovation, then spread the word among their circle of acquaintances—a process which typically takes months or years. But there are exceptions: use of the Internet in the 1990s, for example, may have spread more rapidly than any other innovation in the history of humankind. Furthermore, the Internet is changing the very nature of diffusion by decreasing the importance of physical distance between people. The fifth edition addresses the spread of the Internet, and how it has transformed the way human beings communicate and adopt new ideas.
Computer Aided Innovation (CAI) is a young domain, the goal of which is to support enterprises throughout the complete innovation process. This comprehensive book presents the most up-to-date research on CAI. It addresses the main motivations of the industrial sector regarding the engineering innovation activity with computer tools and methods. The book also discusses organizational, technological and cognitive aspects of the application of CAI methods and tools.
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.
This award-winning book brings together some of the world's best thinkers and researchers to offer insights on creativity, innovation, and entrepreneurship. The new edition features fully updated chapters, including expanded coverage of exciting topics such as group creativity, ethics, development, Makerspaces, and lessons from other fields.