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Deregulation shaping the Electricity industry across the world is a systems challenge cutting across interdisciplinary fields of technology, economics, public policy, environment and sociology. Decision makers that shape tomorrow's policy and investors that invest in financial and technological developments in this industry need to rely on multiple decision models to make informed decisions. This thesis serves to provide one such decision model among many that could be used to understand the key dynamics shaping a highly complex industry. We employ "top-down" and "bottom-up" approaches to build system dynamics model in an attempt to distinguish between adoption and diffusion phenomenon, as a result benefiting from hybrid modeling techniques that combine structures from both models. The models are evaluated with wide range of scenarios to arrive at policy guidance and business model recommendations. The dynamic hypothesis arising from our system dynamics model points to declining marginal profits in a saturating market coupled with proliferation of competitors, over-estimation of demand and diminishing margins for Curtailment Service Providers (CSPs) in the long run. We propose recommendations to surmount these challenges. To tap the smaller commercial and residential markets, CSPs must extend its reach by partnering with composite channel partners, who in the long run could also play a vital role in demand generation. In the face of commoditization and disruptive innovations, CSPs would not be able to sustain their margins just by aggregating demand response (DR) capacity, they would need to reinvent themselves to become energy management firms providing integrated, automated turnkey energy services including energy efficiency services, risk management, planning, sourcing along with providing DR services. Taking a systems approach in evaluating demand-side technology, we further investigate environmental implications of DR by characterizing the carbon savings from DR. Our analyses revealed that the carbon savings from DR triggered load curtailment when calculated using system wide carbon intensities differ substantially from those calculated with locational carbon intensities. Locational carbon intensity captures the location and time-specific dynamics of electricity demand. We, therefore, recommend it is a better metric for evaluating total carbon savings from load curtailment, which could be used to devise carbon abatement policies and structure the electricity market design rules. Furthermore, adding a carbon price to the marginal cost equation could change the dispatch order of plants and thus align carbon abatement policies with load reduction schemes.
A how-to-guide to get others in your organization to accept new technologies, processes, regulations, management, etc.
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.
Here is the bestselling guide that created a new game plan for marketing in high-tech industries. Crossing the Chasm has become the bible for bringing cutting-edge products to progressively larger markets. This edition provides new insights into the realities of high-tech marketing, with special emphasis on the Internet. It's essential reading for anyone with a stake in the world's most exciting marketplace.
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 book tackles the latest research trends in technology acceptance models and theories. It presents high-quality empirical and review studies focusing on the main theoretical models and their applications across various technologies and contexts. It also provides insights into the theoretical and practical aspects of different technological innovations that assist decision-makers in formulating the required policies and procedures for adopting a specific technology.
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.
"This book discusses the emerging topics of information technology and the IT based solutions in global and multi-cultural environments"--Provided by publisher.
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.