Diffusion of Innovations (5th Edition) PDF

FREE PRESS A Division of Simon & Schuster, Inc. 1230 Avenue of the Americas New York, NY 10020 Copyright © 1995, 2003 by Everett M. Rogers Copyright © 1962, 1971, 1983 by The Free Press, A Division of Simon & Schuster, Inc. All rights reserved, including the right of reproduction in whole or in part in any form. FREE PRESS and colophon are trademarks of Simon & Schuster, Inc. The first edition of this book, by Everett M. Rogers, was published as Diffusion of Innovations; the second edition, by Everett M. Rogers with F. Floyd Shoemaker, was published as Communication of Innovations: A Cross-Cultural Approach; the third edition, by Everett M. Rogers, was published as Diffusion of Innovations, as was the fourth edition. Designed by Nancy Singer Olaguera Library of Congress Cataloging-in-Publication Data Rogers, Everett M. Diffusion of innovations / Everett M. Rogers—5th ed. p. cm. 1. Diffusion of innovations. 2. Diffusion of innovations—Study and teaching—History. I. Title. HM621.R57 2003 303.48’4—dc21 2003049022 ISBN 0-7432-5823-1 Visit us on the World Wide Web: http://www. SimonSays.com Dedicated to Bob Wallace, longtime editor of Free Press, who had faith in five editions of this book Contents Preface Chapter 1: Elements of Diffusion Water Boiling in a Peruvian Village: Diffusion That Failed What Is Diffusion? Controlling Scurvy in the British Navy Nondiffusion of the Dvorak Keyboard Four Main Elements in the Diffusion of Innovations 1. The Innovation 2. Communication Channels 3. Time 4. A Social System Diffusion of Hybrid Corn in Iowa Summary Chapter 2: A History of Diffusion Research The Beginnings of Diffusion Research in Europe Gabriel Tarde and Imitation Georg Simmel’s Stranger The British and German-Austrian Diffusionists The Rise of Diffusion Research Traditions Paradigms and Invisible Colleges The Anthropology Research Tradition Miracle Rice in Bali: the Goddess and the Computer Early Sociology Rural Sociology The Diffusion of Modern Math in Pittsburgh Worldwide Diffusion of the Kindergarten Public Health and Medical Sociology The Columbia University Drug Diffusion Study The Taichung Field Experiment STOP AIDS in San Francisco Communication Diffusion of News of the September 11 Terrorist Attacks Marketing Opinion Leaders and Mavens in the Diffusion of Electric Cars Geography General Sociology Networks in Recruitment to Freedom Summer Trends by Diffusion Research Traditions A Typology of Diffusion Research Summary Chapter 3: Contributions and Criticisms of Diffusion Research The Status of Diffusion Research Today Criticisms of Diffusion Research The Pro-Innovation Bias of Diffusion Research Pure Drinking Water in Egyptian Villages Preference for Sons in India and China The Individual-Blame Bias in Diffusion Research The Recall Problem in Diffusion Research The Issue of Equality in the Diffusion of Innovations Summary Chapter 4: the Generation of Innovations The Innovation-Development Process 1. Recognizing a Problem or Need 2. Basic and Applied Research Birth of the Laptop Computer at Toshiba 3. Development How the Refrigerator Got Its Hum Classifying the Segway 4. Commercialization Fumbling the Future at Xerox PARC 5. Diffusion and Adoption 6. Consequences Serendipity in the Discovery of Warfarin Socioeconomic Status, Equality, and Innovation Development Hard Tomatoes in California Tracing the Innovation-Development Process The Shortcomings of Tracer Studies Future Research on the Innovation-Development Process The Agricultural Extension Model Summary Chapter 5: The Innovation-Decision Process A Model of the Innovation-Decision Process The Knowledge Stage Which Comes First, Needs or Awareness of an Innovation? Three Types of Knowledge About an Innovation Early Versus Late Knowers of Innovations The Persuasion Stage The Decision Stage The Implementation Stage Re-Invention How Much Re-Invention Occurs? Re-Invention Is Not Necessarily Bad Why Does Re-Invention Occur? Re-Invention of Horse Culture by the Plains Indians The Confirmation Stage Dissonance Discontinuance The Discontinuance of Smoking Forced Discontinuance and the Rise of Organic Farming Are There Stages in the Innovation-Decision Process? Process Versus Variance Research Evidence of Stages The Hierarchy-of-Effects Stages-of-Change Communication Channels in the Innovation-Decision Process for Tetracycline Communication Channels by Stages in the Innovation-Decision Process Categorizing Communication Channels Mass Media Versus Interpersonal Channels Cosmopolite Versus Localite Channels The Bass Forecasting Model Communication Channels by Adopter Categories The Innovation-Decision Period The Rate of Awareness-Knowledge and Rate of Adoption The Length of the Innovation-Decision Period by Adopter Category How the Internet Is Changing the Innovation-Decision Process Summary Chapter 6: Attributes of Innovations and Their Rate of Adoption Black Music in White America: Rap Rate of Adoption Research on the Attributes of Innovations Measuring the Attributes of Innovations Organizations as the Units of Adoption Postdiction Versus Prediction An Agricultural Innovation That Failed Relative Advantage Economic Factors and Rate of Adoption Status Aspects of Innovations Overadoption Relative Advantage and Rate of Adoption Preventive Innovations The Effects of Incentives Mandates for Adoption Compatibility Compatibility with Values and Beliefs Compatibility with Previously Introduced Ideas Compatibility with Needs Photovoltaics on a Million Roofs The Daughter-in-Law Who Doesn’t Speak Compatibility and Rate of Adoption Technology Clusters Naming an Innovation Positioning an Innovation Acceptability Research Indigenous Knowledge Systems Complexity Trialability Observability Cellular Telephones and the Lifestyle Revolution Summary Chapter 7: Innovativeness and Adopter Categories Diffusion of Farm Innovations in a Colombian Village in the Andes Classifying Adopter Categories on the Basis of Innovativeness The S-Shaped Curve of Adoption and Normality Measuring Organizational Innovativeness Who Adopts? Adopter Categorization Adopter Categories as Ideal Types Innovators: Venturesome Early Adopters: Respect Early Majority: Deliberate Late Majority: Skeptical Laggards: Traditional People Who Said No to Innovation: The Old Order Amish Characteristics of Adopter Categories Socioeconomic Characteristics Personality Variables Communication Behavior Audience Segmentation and Adopter Categories Cell Phone Laggards in Hong Kong The Innovativeness/Needs Paradox and the Strategy of Least Resistance Network Influences on Innovativeness Summary Chapter 8: Diffusion Networks Opinion Leadership in the Diffusion of Modern Math Models of Communication Flows The Hypodermic Needle Model The Two-Step Flow Model Homophily and Heterophily in Communication Networks Homophily and Heterophily Homophily as a Barrier to Diffusion Measuring Opinion Leadership and Network Links The Role of Alpha Pups in the Viral Marketing of a Cool Electronics Game Monomorphic and Polymorphic Opinion Leadership Paul Revere’s Ride Characteristics of Opinion Leaders External Communication Accessibility Socioeconomic Status Innovativeness Innovativeness, Opinion Leadership, and System Norms Opinion Leader Organizations Do Opinion Leaders Matter? Networks in the Diffusion of a Medical Drug Diffusion Networks Building a Network for the Diffusion of Photovoltaics in the Dominican Republic Cluster Studies Dr. John Snow and the Cholera Epidemic in London Communication Network Analysis The Strength-of-Weak-Ties Theory Who Is Linked to Whom in Networks? Social Learning Theory The Critical Mass in the Diffusion of Interactive Innovations The Critical Mass in the Diffusion of Fax Diffusion of the Internet The Concept of Critical Mass Watching While Being Watched The Sleeper Individual Thresholds for Adoption Why Do Individuals Adopt Prior to the Critical Mass? Networks and the Turbocharger Effect Strategies for Getting to Critical Mass Summary Chapter 9: The Change Agent Targeting Change Agents as Linkers The Sequence of Change Agent Roles Coercion in Norplant Diffusion Safaris in Indonesia Factors in Change Agent Success Change Agent Efforts Client Orientation Compatibility with Clients’ Needs Sustainability: “Chicken” Davis in Nigeria Change Agent Empathy Communication Campaigns The ORT Campaign in Egypt Homophily and Change Agent Contact Change Agents’ Contact with Lower-Status Clients Para-Professional Aides Change Agent Credibility Inauthentic Professionalization of Aides The Baltimore Needle-Exchange Project The Use of Opinion Leaders The Role of Demonstrations Clients’ Evaluative Ability The Agricultural Extension Service Centralized and Decentralized Diffusion Systems Advantages and Disadvantages of Decentralized Diffusion Summary Chapter 10: Innovation in Organizations Types of Innovation-Decisions Organizations Virtual Organizations Organizational Innovativeness Size and Organizational Innovativeness Structural Characteristics and Organizational Innovativeness The Role of Champions The Innovation Process in Organizations Adoption of New Communication Technologies Stages in the Innovation Process 1. Agenda-Setting 2. Matching 3. Redefining/Restructuring 4. Clarifying 5. Routinizing The Santa Monica Freeway Diamond Lane Experiment: Implementation Failure New Communication Technologies in Organizations Summary Chapter 11: Consequences of Innovations Snowmobile Revolution in the Arctic Studying Consequences Classifications of Consequences Desirable Versus Undesirable Consequences Direct Versus Indirect Consequences ORT: The Consequences of Consequences Anticipated Versus Unanticipated Consequences Steel Axes for Stone-Age Aborigines Form, Function, and Meaning of an Innovation The Irish Potato Famine Achieving a Dynamic Equilibrium The Mosquito Killer Equality in the Consequences of Innovations The Communication Effects Gap Gap-Widening Consequences of the Diffusion of Innovations Social Structure and the Equality of Consequences Strategies for Narrowing Gaps Wider Gaps Are Not Inevitable The Digital Divide Summary Glossary Bibliography Name Index Subject Index Preface This volume, the fifth edition of my book Diffusion of Innovations, builds on its predecessors by retaining the same basic diffusion model that originally appeared in the first edition in 1962. Over the past four decades, this general model of the diffusion of innovations has been modified somewhat and expanded, based on further research and on theoretical developments. What is new in the present edition of Diffusion of Innovations is (1) changes in the contributions of various diffusion traditions, with marketing, public health, and communication coming on particularly strong in recent years, (2) many studies of the diffusion of new communication technologies like the Internet and cellular telephones, (3) expanded understanding of diffusion networks through such concepts as the critical mass and individual thresholds, and (4) the use of field experiments (in addition to surveys) to test the effects of such diffusion interventions as using opinion leaders. Many of the case illustrations, and the figures that accompany certain of them, are new to this edition. My introduction to research on the diffusion of innovations happened in the following manner. I became interested in the diffusion of agricultural innovations by observing farmers in my home community near Carroll, Iowa, who delayed for several years in adopting new ideas that could have been profitable for them. This behavior was puzzling—and frustrating—to me. Why didn’t farmers adopt innovations? Factors other than just economic explanations must have been at work. I had graduated from Iowa State University with a bachelor’s degree in agriculture in 1952 and then served as an Air Force officer during the Korean War, when I learned the skills of applied social science research. After my discharge from military service, I returned to Iowa State for graduate work in rural sociology, to study the diffusion of agricultural innovations. At that time, Iowa State was one of the centers of diffusion research as a result of the hybrid seed corn study by Bryce Ryan and Neal C. Gross (1943). In 1954, Professor George Beal at Iowa State University was initiating a diffusion project in one community, Collins, Iowa, located about twenty miles from Ames. This project was supported by the Iowa Agricultural Experiment Station, the research unit at Iowa State that had funded research to develop hybrid seed corn and other agricultural innovations. I joined Beal’s diffusion project in spring, 1954, and within about a week of my discharge from the Air Force, I was participating in a graduate seminar on diffusion, taught by Beal. I read the Ryan and Gross (1943) paper about the diffusion of hybrid seed corn in two Iowa communities. Shortly thereafter, I began interviewing some of the 148 farmers in Collins about their adoption of 2, 4-D weed spray and other agricultural innovations. Thus I became a diffusion scholar. My doctoral dissertation in 1957 was an analysis of the diffusion of several agricultural innovations in the rural community of Collins. While reviewing literature for my dissertation, I encountered studies of the diffusion of kindergartens and of driver training among schools (Mort, 1953), as well as the spread of an antibiotic drug (tetracycline) among medical doctors (Menzel and Katz, 1955). The main findings were strikingly similar to the agricultural diffusion studies in which I was involved: an S-shaped rate of adoption over time, different sources or channels at different stages in the innovation- decision process for an individual, and a tendency for innovators (the first individuals in a system to adopt an innovation) to travel and read widely and to have a cosmopolite orientation. The review of literature chapter in my dissertation argued that diffusion was a general process, not bound by the type of innovation studied, who the adopters were, or by place or culture. I was convinced that the diffusion of innovations was a kind of universal process of social change. Certainly one event that encouraged this type of thinking was a presentation on the diffusion of agricultural innovations by Professors George Beal and Joe Bohlen to the staff of the Iowa Extension Service in December 1954 in Ames. This dramatic presentation had grown out of the graduate seminar on diffusion in which I had enrolled the previous spring at Iowa State and focused (1) on the sources or channels of communication used at stages in the individual-level innovation-decision process, and (2) on characteristics of farmers who adopted relatively earlier and relatively later in the diffusion process. These were important steps toward generalizing a model of diffusion, although the Beal/Bohlen conceptualization was mainly oriented to farm innovations. Soon, however, Beal and Bohlen were being asked to give their presentation to audiences interested in civil defense (where the innovation of interest was building household bomb shelters) and household consumer products. Clearly, a more general diffusion model was being discussed. After completing graduate work at Iowa State in 1957, I joined the rural sociology faculty at Ohio State University, where I conducted research on the diffusion of agricultural innovations among Ohio farmers. My argument for a generalized diffusion model led me to write the first edition of Diffusion of Innovations, which was published in 1962. This book summarized diffusion research findings to date, organized around a general diffusion model, and argued for more standardized ways of adopter categorization and for conceptualizing the diffusion process. In 1963–1964, I taught and conducted research on the diffusion process in peasant communities in Colombia as a Fulbright lecturer. This experience allowed me to test the universality of the diffusion model, such as whether the diffusion of innovations also characterized peasant villages in developing countries, where the mass media were rare and where social change was often just getting under way. On my return to the United States, I accepted a faculty appointment in the Department of Communication at Michigan State University, then the seed institution for communication study in the United States (Rogers, 2001). This academic change fit with my vision for diffusion research: it would be more generalized, involving various disciplines, but with a firm grounding in communication theory. So my interest in a general diffusion model helped move me out of rural sociology (and the study of agricultural innovations) into the field of communication. I began to study the diffusion of health and family planning innovations in India and the diffusion of educational innovations among government secondary schools in Thailand. Eventually, the study of agricultural innovations by rural sociologists became somewhat passé in the face of farm surpluses (although it has made somewhat of a resurgence in recent years). But the diffusion model spread to many other academic fields. This book is about regularities in the diffusion of innovations, patterns that have been found across cultures, innovations, and the people who adopt them. The diffusion of innovations explains social change, one of the most fundamental of human processes. The four editions of my diffusion book (published in 1962, 1971, 1983, and 1995), each about a decade apart, mark turning points in the growth of the diffusion field. At the time the first edition of this book, Diffusion of Innovations, was published in 1962, there were 405 publications about this topic. The second edition (and revision), Communication of Innovations: A Cross-Cultural Approach (coauthored with F. Floyd Shoemaker), was published in 1971, nine years later. By then the number of diffusion publications had quadrupled, to about 1,500. Twelve years later, in 1983, when the third edition of Diffusion of Innovations appeared, the total number of diffusion publications had more than doubled again, to 3,085. The number of diffusion publications approached 4,000 when the fourth edition of Diffusion of Innovations was published in 1995. Today I estimate this number to be more than 5,200, and the field of diffusion continues to grow (at about the same rate of 120 diffusion publications per year that characterized the past four decades). No other field of behavior science research represents more effort by more scholars in more disciplines in more nations. The present book is based upon a yet broader foundation of diffusion research than the four earlier editions. I believe that the widespread diffusion of the Internet since about 1990 has changed the nature of the diffusion process in certain important ways, which are discussed in the present volume. This book is both (1) a revision of the theoretical framework and the research evidence supporting this updated model of diffusion and (2) a new intellectual venture, in that certain new concepts and new theoretical viewpoints are introduced. The stream of diffusion scholarship over the past sixty years represents both similarities and differences, continuities and discontinuities, and so does this book. By no means, however, do I seek only to synthesize the important findings from past research; I also strive to criticize this work (including my own) and to suggest directions for the future that are different from those of the past. I have once again titled this book Diffusion of Innovations to identify it with the forty-year sequential tradition of diffusion studies marked by my 1962 book of the same title. Most diffusion studies prior to 1962 were conducted in the United States and Europe. In the period between the first and second editions of my diffusion book, during the 1960s, an explosion occurred in the number of diffusion investigations that were being conducted in the developing countries of Latin America, Africa, and Asia. The classical diffusion model was usefully applied to the process of development that was a priority for these developing nations. The diffusion approach was a natural framework in which to evaluate the impacts of development programs in agriculture, family planning, public health, and nutrition. In studying the diffusion of innovations in developing nations, I (and others) gradually realized that certain limitations existed in the diffusion framework. In some cases, development programs outran the diffusion model on which they had originally been based. Certain modifications to the classical diffusion model were thus made. This book reflects a more critical stance than its original ancestor. During the past forty years or so, diffusion research has grown to be widely recognized, applied, and admired, but it has also been subjected to 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. Once diffusion researchers formed an “invisible college” (defined as an informal network of researchers who form around an intellectual paradigm to study a common topic), they began to limit unnecessarily the ways in which they went about studying the diffusion of innovations. Such standardization of approaches constrains the intellectual progress of diffusion research. Social changes and the social problems facing the world, of course, affect the diffusion of innovations. Examples are the Internet, the AIDS epidemic, and world terrorism. The Internet has spread more rapidly than any other technological innovation in the history of humankind. The diffusion of the Internet exemplifies certain concepts, such as that of critical mass. The term digital divide indicates those individuals who are advantaged versus those who are relatively disadvantaged by the Internet and helps illuminate our understanding of inequality in the consequences of innovation. We draw on illustrations of Internet diffusion throughout this book. We suggest that such interactive communication technologies may be changing the diffusion process in certain fundamental ways, such as by removing, or at least greatly diminishing, the role of spatial distance in who talks to whom about a new idea. The AIDS epidemic was first recognized in the United States in 1981, although we now know that it had antecedents going back several decades. The first HIV/AIDS prevention program to successfully halt the spread of the epidemic, STOP AIDS, was organized by gay men in San Francisco in the mid-1980s and was based directly on the diffusion model. We analyze the STOP AIDS intervention in Chapter 2, along with the thousands of other HIV prevention programs around the world, all based to some degree on the San Francisco model. The AIDS epidemic today is concentrated in the developing world of Latin America, Africa, and Asia, where 95 percent of the 40 million people living with HIV/AIDS are located (Singhal and Rogers, 2003). The epidemic represents one of the world’s gravest social problems, and we discuss here how the diffusion model has been, and could be, utilized to slow rates of infection (see Chapter 9). World terrorism, culminating in the September 11, 2001, attacks on the World Trade Center and Pentagon, poses another challenge to society. This event has focused attention in gaining improved understanding of how Al Qaeda and similar terrorist networks function. We discuss the unique qualities of networks in Chapter 8. In certain important respects, the architects of the United States’ antiterrorist efforts have not completely realized that a war on international terrorism is quite different from wars of the past, which were against nations. The present book makes use of the important concepts of uncertainty and information. Uncertainty is the degree to which a number of alternatives are perceived with respect to the occurrence of an event and the relative probabilities of these alternatives. Uncertainty motivates individuals to seek information, as it is an uncomfortable state. Information is a difference in matter-energy that affects uncertainty in a situation where a choice exists among a set of alternatives (Rogers and Kincaid, 1981). One kind of uncertainty is generated by an innovation, defined as an idea, practice, or object that is perceived as new by an individual or another unit of adoption. An innovation presents an individual or an organization with a new alternative or alternatives, as well as new means of solving problems. However, the probability that the new idea is superior to previous practice is not initially known with certainty by individual problem solvers. Thus, individuals are motivated to seek further information about the innovation in order to cope with the uncertainty that it creates. Information about an innovation is often sought from peers, especially information about their subjective evaluations of the innovation. This information exchange about a new idea occurs through a convergence process involving interpersonal networks. The diffusion of innovations is essentially a social process in which subjectively perceived information about a new idea is communicated from person to person. The meaning of an innovation is thus gradually worked out through a process of social construction. My thinking and writing about the diffusion of innovations have benefited a great deal in recent years from my collaboration with other diffusion scholars. Some are “rookies” in the diffusion field. My daily e-mail messages often contain a query from a young scholar or student asking for advice about a diffusion investigation that he or she is conducting. I learn from these exchanges, as I do from the undergraduate/ graduate course on the diffusion of innovations that I teach at the University of New Mexico. This volume benefits from such fresh questioning of an established framework, which helps advance it. The help of several old pros in diffusion research and teaching are also acknowledged. Jim Dearing of Michigan State University, Pete Korsching of Iowa State University, Gary Meyer at Marquette University, Todd Shimoda at Colorado State University, Arvind Singhal at Ohio University, and Tom Valente at the University of Southern California. I stay in touch with this network of scholars, exchanging course outlines and publications. I also thank Andrew Rubey of the University of New Mexico for certain of the graphics in this book, and Everett Rogers-King for making the indexes. Throughout this book, I seek to represent a healthily critical stance. We do not need more-of-the-same diffusion research. The challenge for diffusion scholars of the future is to move beyond the proven methods and models of the past, to recognize their shortcomings and limitations, and to broaden their conceptions of the diffusion of innovations. We offer this fifth edition as one step toward this important goal. Everett M. Rogers Albuquerque, New Mexico Elements of Diffusion There is nothing more difficult to plan, more doubtful of success, nor more dangerous to manage than the creation of a new order of things…. Whenever his enemies have the ability to attack the innovator, they do so with the passion of partisans, while the others defend him sluggishly, so that the innovator and his party alike are vulnerable. Niccolò Machiavelli, The Prince (1513) Getting a new idea adopted, even when it has obvious advantages, is difficult. Many innovations require a lengthy period of many years from the time when they become available to the time when they are widely adopted. Therefore, a common problem for many individuals and organizations is how to speed up the rate of diffusion of an innovation. The following case illustration provides insight into some common difficulties facing diffusion campaigns. Water Boiling in a Peruvian Village: Diffusion That Failed* The public health service in Peru attempts to introduce innovations to villagers to improve their health and lengthen their lives. This change agency encourages people to install latrines, burn garbage daily, control house flies, report cases of infectious diseases, and boil drinking water. These innova tions involve major changes in thinking and behavior for Peruvian villagers, who do not understand the relationship of sanitation to illness. Water boiling is an especially important health practice for Peruvian villagers. Unless they boil their drinking water, patients who are cured of an infectious disease in a medical clinic often return within a short time to be treated again for the same disease. A two-year water-boiling campaign conducted in Los Molinas, a peasant village of two hundred families in the coastal region of Peru, persuaded only eleven housewives to boil water. From the viewpoint of the public health agency, the local health worker, Nelida, had a simple task: to persuade the housewives of Los Molinas to add water boiling to their pattern of daily behavior. Even with the aid of a medical doctor, who gave public talks on water boiling, and fifteen village housewives who were already boiling water, Nelida’s diffusion campaign failed. To understand why, we need to take a closer look at the culture, the local environment, and the individuals in Los Molinas. Most residents of Los Molinas are peasants who work as field hands on local plantations. Water is carried by can, pail, gourd, or cask. The three sources of water in Los Molinas include a seasonal irrigation ditch close to the village, a spring more than a mile away from the village, and a public well whose water most villagers dislike. All three sources are subject to pollution at all times and show contamination whenever tested. Of the three sources, the irrigation ditch is the most commonly used. It is closer to most homes, and the villagers like the taste of its water. Although it is not feasible for the village to install a sanitary water system, the incidence of typhoid and other waterborne diseases could be greatly reduced by boiling water before it is consumed. During her two-year campaign in Los Molinas, Nelida made several visits to every home in the village and devoted especially intensive efforts to twenty-one families. She visited each of the selected families between fifteen and twenty-five times; eleven of these families now boil their water regularly. What kinds of people do these numbers represent? We describe three village housewives: one who boils water to obey custom, one who was persuaded to boil water by the health worker, and one of the many who rejected the innovation. Mrs. A: Custom-Oriented Adopter Mrs. A is about forty and suffers from a sinus infection. The Los Molinas villagers call her the “sickly one.” Each morning, Mrs. A boils a potful of water, which she uses throughout the day. She has no understanding of germ theory, as explained by Nelida. Her motivation for boiling water is a complex local custom of “hot” and “cold” distinctions. The basic principle of this belief system is that all foods, liquids, medicines, and other objects are inherently hot or cold, quite apart from their actual temperature. In essence, the hot-cold distinction serves as a series of avoidances and approaches in such behavior as pregnancy, child rearing, and the health-illness system. Boiled water and illness are closely linked in the norms of Los Molinas. By custom, only the ill use cooked, or “hot” water. If an individual becomes ill, it is unthinkable to eat pork (very cold) or drink brandy (very hot). Extremes of hot and cold must be avoided by the sick; therefore, raw water, which is perceived to be very cold, must be boiled to make it appropriate. Villagers learn from early childhood to dislike boiled water. Most can tolerate cooked water only if a flavoring, such as sugar, lemon, or herbs, is added. Mrs. A likes a dash of cinnamon in her drinking water. The village belief system does not involve the notion of bacteriological contamination of water. By tradition, boiling is aimed at eliminating the “cold” quality of unboiled water, not the harmful bacteria. Mrs. A drinks boiled water in obedience to local norms, because she perceives herself as ill. She adopted the innovation, but for the wrong reason. Mrs. B: Persuaded Adopter The B family came to Los Molinas a generation ago, but they are still strongly oriented toward their birthplace in the high Andes. Mrs. B worries about lowland diseases that she feels infest the village. It is partly because of this anxiety that the public health worker, Nelida, was able to convince Mrs. B to boil water. To Mrs. B, Nelida is a friendly authority (rather than a “dirt inspector,” as she is seen by other housewives) who imparts useful knowledge and brings protection from uncertain threats. Mrs. B not only boils water but has also installed a latrine and sent her youngest child to the health center for a checkup. Mrs. B is marked as an outsider in the community by her highland hairdo and stumbling Spanish. She will never achieve more than marginal social acceptance in the village. Because the community is not an important reference group to her, Mrs. B can deviate from the village norms on health innovations. With nothing to lose socially, Mrs. B gains in personal security by heeding Nelida’s advice. Mrs. B’s practice of boiling water has no effect in improving or damaging her marginal status. She is grateful to Nelida for teaching her how to neutralize the danger of contaminated water, which she perceives as a lowland peril. Mrs. C: Rejector This housewife represents the majority of Los Molinas families who were not persuaded by the efforts of the change agent during the two-year water- boiling campaign. In spite of Nelida’s repeated explanations, Mrs. C does not understand germ theory. How, she argues, can microbes survive in water that would drown people? Are they fish? If germs are so small that they cannot be seen or felt, how can they hurt a grown person? There are enough real threats in the world to worry about—poverty and hunger—without bothering about tiny animals that one cannot see, hear, touch, or smell. Mrs. C’s allegiance to traditional village norms is at odds with the boiling of water. A firm believer in the hot-cold superstition, she feels that only the sick should drink boiled water. Why Did the Diffusion of Water Boiling Fail? This intensive two-year campaign by a public health worker in a Peruvian village of two hundred families, aimed at persuading housewives to boil drinking water, was largely unsuccessful. Nelida was able to encourage only about 5 percent of the population, eleven families, to adopt the innovation. The diffusion campaign in Los Molinas failed because the innovation was perceived as culturally inappropriate by the villagers. Local tradition links hot foods with illness. Boiling water makes water less “cold” and hence appropriate only for the sick. If a person is not ill, he or she is prohibited by village norms from drinking boiled water. Only individuals who are not integrated into local networks risk defying the community norm on water boiling. An important factor regarding the adoption rate of an innovation is its compatibility with the values, beliefs, and past experiences of individuals in the social system. Nelida and her superiors in the public health agency should have understood the hot-cold belief system, as it is found throughout Peru (and in most nations of Latin America, Africa, and Asia). The indigenous knowledge system caused the failure of the diffusion effort for water boiling in Los Molinas. Nelida’s failure demonstrates the importance of interpersonal networks in the adoption or rejection of an innovation. Socially an outsider, Mrs. B was marginal to the Los Molinas community, although she lived there for several years. Nelida was a more important referent for Mrs. B than were her neighbors, who shunned her. Anxious to win reflected social prestige from the higher-status Nelida, Mrs. B adopted water boiling, not because she understood the correct health reasons but because she wanted to obtain Nelida’s approval. Thus we see that the diffusion of innovations is a social process, even more than a technical matter. Nelida worked with the wrong housewives if she wanted to launch a self- generating diffusion process in Los Molinas. She concentrated her efforts on village women such as Mrs. A and Mrs. B. Unfortunately, they were perceived as a sickly one and a social outsider, respectively, and were not perceived as social models of water-boiling behavior by the other women. The village opinion leaders, who could have activated local networks to spread the innovation, were ignored by Nelida. As a result, the rate of adoption of the innovation did not reach a critical mass, after which the diffusion process would have become self-sustaining. How potential adopters view a change agent affects their willingness to adopt new ideas. In Los Molinas, Nelida was perceived differently by lower- and middle-status housewives. Most poor families saw the health worker as a “snooper” sent to Los Molinas to pry for dirt and to press already harassed housewives into keeping cleaner homes. Because the lower-status housewives had less free time, they were unlikely to talk with Nelida about water boiling. Their contacts outside the community were limited, and as a result, they saw the technically proficient Nelida with eyes bound by the traditional beliefs of Los Molinas. They distrusted this outsider, whom they perceived as a social stranger. Nelida, who was middle class by Los Molinas standards, was able to secure more positive results from housewives whose socioeconomic status and cultural background were more similar to hers. This tendency for more effective communication to occur with those who are more similar to a change agent occurs in most diffusion campaigns. Unfortunately, those individuals who most need the help provided by the change agent are least likely to accept it. Nelida was “innovation-oriented” rather than “client-oriented.” She was unable to put herself in the role of the village housewives, and thus her attempts at persuasion failed to reach her clients because the message did not suit their needs. Nelida talked to villagers about germ theory, which they could not (and did not need to) understand. These factors produced the diffusion failure in Los Molinas. Once the remainder of the book has been read, it will be easier to understand the water-boiling case. What Is Diffusion? Diffusion is the process in which an innovation is communicated through certain channels over time among the members of a social system. It is a special type of communication, in that the messages are concerned with new ideas. Communication is a process in which participants create and share information with one another in order to reach a mutual understanding. This definition implies that communication is a process of con vergence (or divergence) as two or more individuals exchange information in order to move toward each other (or apart) in the meanings that they give to certain events. We think of communication as a two-way process of convergence, rather than as a one-way, linear act in which one individual seeks to transfer a message to another in order to achieve certain effects (Rogers and Kincaid, 1981). A linear conception of human communication may accurately describe certain communication acts involved in diffusion, such as when a change agent seeks to persuade a client to adopt an innovation. But when we look at what came before such an event and at what followed, we often realize that the event is only one part of a total process in which information is exchanged between the two individuals. For example, a client may go to a change agent with a specific problem, and the innovation may be recommended as a possible solution to this problem. The change agent–client interaction may continue through several cycles, as a process of information exchange. Diffusion is a special type of communication in which the messages are about a new idea. This newness of the idea in the message content gives diffusion its special character. The newness means that some degree of uncertainty is involved in diffusion. Uncertainty is the degree to which a number of alternatives are perceived with respect to the occurrence of an event and the relative probability of these alternatives. Uncertainty implies a lack of predictability, of structure, of information. Information is a means of reducing uncertainty. Information is a difference in matter-energy that affects uncertainty in a situation where a choice exists among a set of alternatives (Rogers and Kincaid, 1981). A technological innovation embodies information and thus reduces uncertainty about cause-effect relationships in problem solving. Diffusion is a kind of social change, defined as the process by which alteration occurs in the structure and function of a social system. When new ideas are invented, diffused, and adopted or rejected, leading to certain consequences, social change occurs. Of course, such change can happen in other ways, too; for example, a political revolution, a natural event such as a drought or an earthquake, or a government policy. Some authors restrict the term “diffusion” to the spontaneous, unplanned spread of new ideas and use the concept of “dissemination” for diffusion that is directed and managed. In this book we use the word “diffusion” to include both the planned and the spontaneous spread of new ideas. Controlling Scurvy in the British Navy * Many technologists believe that advantageous innovations will sell themselves, that the obvious benefits of a new idea will be widely realized by potential adopters, and that the innovation will diffuse rapidly. Seldom is this the case. Most innovations, in fact, diffuse at a disappointingly slow rate, at least in the eyes of the inventors and technologists who create the innovations and promote them to others. Scurvy control illustrates how slowly an obviously beneficial innovation spreads. In the early days of long sea voyages, scurvy killed more sailors than did warfare, accidents, and other causes. For instance, of Vasco da Gama’s crew of 160 men who sailed with him around the Cape of Good Hope in 1497, 100 died of scurvy. In 1601, an English sea captain, James Lancaster, conducted an experiment to evaluate the effectiveness of lemon juice in preventing scurvy. Captain Lancaster commanded four ships that sailed from England on a voyage to India. He served three teaspoonfuls of lemon juice every day to the sailors in one of his four ships. These men stayed healthy. The other three ships constituted Lancaster’s “control group,” as their sailors were not given any lemon juice. On the other three ships, by the halfway point in the journey, 110 out of 278 sailors had died from scurvy. So many of these sailors got scurvy that Lancaster had to transfer men from his “treatment” ship in order to staff the three other ships for the remainder of the voyage. These results were so clear that one would have expected the British Navy to promptly adopt citrus juice for scurvy prevention on all ships. Not until 1747, about 150 years later, did James Lind, a British Navy physician who knew of Lancaster’s results, carry out another experiment on the HMS Salisbury. To each scurvy patient on this ship, Lind prescribed either two oranges and one lemon or one of five other supplements: a half pint of sea water, six spoonfuls of vinegar, a quart of cider, nutmeg, or seventy-five drops of vitriol elixir. The scurvy patients who got the citrus fruits were cured in a few days and were able to help Dr. Lind care for the other patients. Unfortunately, the supply of oranges and lemons was exhausted in six days. Certainly, with this further solid evidence of the ability of citrus fruits to combat scurvy, one would expect the British Navy to have adopted this innovation for all ship’s crews on long sea voyages. In fact, it did so, but not until 1795, forty-eight years later, when scurvy was immediately wiped out. After only seventy more years, in 1865, the British Board of Trade adopted a similar policy and eradicated scurvy in the merchant marine. Why were the authorities so slow to adopt the idea of citrus for scurvy prevention? Other, competing remedies for scurvy were also being proposed, and each such cure had its champions. For example, Captain Cook’s reports from his voyages in the Pacific did not provide support for curing scurvy with citrus fruits. Further, Dr. Lind was not a prominent figure in the field of naval medicine, and so his experimental findings did not get much attention. While scurvy prevention was generally resisted for years by the British Navy, other innovations, such as new ships and new guns, were readily accepted. So the Admiralty did not resist all innovations. Obviously, more than just the relative advantages of an innovation, even when its benefits are clearly demonstrated, is necessary for its diffusion and adoption. The reader may think that such slow diffusion could only have happened in the distant past, before the contemporary era of scientific, experimental evaluations of innovations. On the contrary; consider the present-day case of the nondiffusion of the Dvorak keyboard. Nondiffusion of the Dvorak Keyboard * Most individuals who write on a computer do not realize that their fingers tap out words on a keyboard that is known as “QWERTY,” named after the first six keys on the upper row of letters. The QWERTY keyboard is intentionally inefficient and awkward. This keyboard takes twice as long to learn as it should and makes us work about twenty times harder than necessary. But QWERTY has persisted since 1873, and today unsuspecting individuals are taught to use the QWERTY keyboard, unaware that a much more efficient keyboard is available. In recent years of talking about the QWERTY keyboard with hundreds of large audiences, the present author has never encountered anyone who uses an alternative. Where did QWERTY come from? Why does it persist in the face of much more efficient alternative keyboard designs? QWERTY was invented by Christopher Latham Sholes, who designed this keyboard to slow down typists. In his day, the type bars on a typewriter hung down in a sort of bas ket and pivoted up to strike the paper; then they fell back into place by gravity. When two adjoining keys were struck rapidly in succession, they jammed. Sholes rearranged the keys on a typewriter keyboard to minimize such jamming; he “anti-engineered” the letter arrangement in order to make the most commonly used letter sequences awkward. By thus making it difficult for a typist to operate the machine and slowing down typing speed, Sholes’s QWERTY keyboard allowed early typewriters to operate with a minimum of jamming. His design was then used in the manufacture of all typewriters. Early typewriter salesmen could impress customers by pecking out “TYPEWRITER” as all of the letters necessary to spell this word were found in the top row (QWERTYUIOP) of the machine. Prior to 1900, most typists used the two-finger, hunt-and-peck system. Later, as touch typing became popular, dissatisfaction with the QWERTY typewriter began to grow. Typewriters became mechanically more efficient, and the QWERTY keyboard design was no longer necessary to prevent jamming. The search for an improved design was led by Professor August Dvorak at the University of Washington, who in 1932 used time-and-motion studies to create a much more efficient keyboard arrangement. Dvorak filmed people while they were typing and spent a decade analyzing which operations slowed them down. The Dvorak keyboard has the letters A, O, E, U, I, D, H, T, N, and S across the home row of the typewriter (Figure 1–1). Less frequently used letters were placed on the upper and lower rows of keys. About 70 percent of typing is done on the home row, 22 percent on the upper row, and 8 percent on the lower row. On the Dvorak keyboard, the amount of work assigned to each finger is proportionate to its skill and strength. Further, Professor Dvorak engineered his keyboard so that successive keystrokes fell on alternative hands; thus, while a finger on one hand is stroking a key, a finger on the other hand can be moving into position to hit the next key. Typing rhythm is thus facilitated; this hand alternation was achieved by putting the vowels (which represent 40 percent of all letters typed) on the left- hand side and the major consonants that usually accompany these vowels on the right-hand side of the keyboard. Professor Dvorak was thus able to avoid the typing inefficiencies of the QWERTY keyboard. For instance, QWERTY overloads the left hand, which must type 57 percent of ordinary copy. The Dvorak keyboard shifts this emphasis to 56 percent on the stronger right hand and 44 percent on the weaker left hand (for a right-hander, as are 90 percent of the public). Only 32 percent of typing is done on the home row with the QWERTY system, compared to 70 percent with the Dvorak keyboard. The newer arrangement requires less jumping back and forth from row to row. With the QWERTY keyboard, an efficient typist’s fingertips travel more than twelve miles a day, jumping from row to row. These unnecessary, intricate movements cause mental tension and carpal tunnel syndrome and lead to more typographical errors. Typists typing on the Dvorak keyboard have broken all speed records. Figure 1-1. Layout of the QWERTY and the Dvorak Keyboards. The Dvorak keyboard is much more efficient for typists than the QWERTY keyboard, which was designed more than a century ago to slow down typists so as to prevent the jamming of keys on early typewriters. Yet almost no one has adopted the Dvorak keyboard. Superior technological innovations do not necessarily diffuse themselves. One might expect, on the basis of its overwhelming advantages, that the Dvorak keyboard would have completely replaced the inferior QWERTY keyboard. On the contrary, after more than seventy years, almost all typists still use the inefficient QWERTY keyboard. Even though the American National Standards Institute and the Equipment Manufacturers Association have approved the Dvorak keyboard as an alternate design, it is still almost impossible to find a typewriter or a computer keyboard that is arranged in the more efficient layout. Vested interests are involved in hewing to the old design: manufacturers, sales outlets, typing teachers, and typ ists themselves. Unbeknown to most computer users, their machine that comes equipped with a QWERTY keyboard can easily be switched to a Dvorak keyboard. Nevertheless, a considerable effort, estimated at about a week’s training, is required for someone accustomed to the QWERTY design to become proficient on a Dvorak keyboard. Here we see that technological innovations are not always diffused and adopted rapidly, even when the innovation has obvious advantages. As the reader may have guessed by now, the present book was typed on a QWERTY keyboard. Four Main Elements in the Diffusion of Innovations Previously we defined diffusion as the process by which (1) an innovation (2) is communicated through certain channels (3) over time (4) among the members of a social system. The four main elements are the innovation, communication channels, time, and the social system (Figure 1–2). These elements are identifiable in every diffusion research study and in every diffusion campaign or program (such as the attempted diffusion of water boiling in a Peruvian village). Figure 1-2. The Diffusion Process Diffusion is the process by which (1) an innovation (2) is communicated through certain channels (3) over time (4) among the members of a social system. The following description of these four elements in diffusion constitutes an overview of the main concepts that will then be detailed in Chapters 2 through 11. 1. The Innovation An innovation is an idea, practice, or object that is perceived as new by an individual or other unit of adoption. It matters little, so far as human behavior is concerned, whether or not an idea is “objectively” new as measured by the lapse of time since its first use or discovery. The perceived newness of the idea for the individual determines his or her reaction to it. If an idea seems new to the individual, it is an innovation. Newness in an innovation need not just involve new knowledge. Someone may have known about an innovation for some time but not yet developed a favorable or unfavorable attitude toward it, nor have adopted or rejected it. “Newness” of an innovation may be expressed in terms of knowledge, persuasion, or a decision to adopt. Among the important research questions addressed by diffusion scholars are (1) how earlier adopters differ from later adopters of an innovation (see Chapter 7), (2) how the perceived attributes of an innovation, such as its relative advantage, compatibility, and so on, affect its rate of adoption, whether relatively rapidly or more slowly, as is detailed in Chapter 6, and (3) why the S-shaped diffusion curve “takes off” at about 10 to 20 percent adoption, when interpersonal networks become activated so that a critical mass of adopters begin using an innovation (see Chapter 8). It should not be assumed that the diffusion and adoption of all innovations are necessarily desirable. Some harmful and uneconomical innovations are not desirable for either an individual or the social system. Further, the same innovation may be desirable for one adopter in one situation but undesirable for another potential adopter whose situation differs. For example, mechanical tomato pickers were adopted rapidly by large commercial farmers in California, but these machines were too expensive for small-sized tomato growers, and thousands of farmers were thus forced out of tomato production (see Chapter 4). Similarly, at present about half of U.S. households own a personal computer. The half who do not perceive that they have little use for a computer, or else they use a computer at work or in a cybercafé. TECHNOLOGICAL INNOVATIONS, INFORMATION, AND UNCERTAINTY Most of the new ideas whose diffusion has been analyzed are technologi cal innovations, and we often use the word “innovation” and “technology” as synonyms. A technology is a design for instrumental action that reduces the uncertainty in the cause-effect relationships involved in achieving a desired outcome. A technology usually has two components: (1) a hardware aspect, consisting of the tool that embodies the technology as a material or physical object, and (2) a software aspect, consisting of the information base for the tool. For example, we often speak of (1) “computer hardware,” consisting of semiconductors, transistors, electrical connections, and a frame that protects these electronic components, and (2) “computer software,” consisting of the coded commands, instructions, manuals, and other information aspects of this tool that allow us to use it for certain tasks. This example illustrates the close relationship between hardware and software, between a tool and the way it is used. We often think of technology mainly in terms of hardware. Indeed, sometimes the hardware side of a technology is dominant. But in other cases, a technology may be almost entirely composed of information; examples are a political philosophy such as Marxism, a religious idea such as Christianity, a news event, and a policy such as a municipal no-smoking ordinance. The diffusion of such software innovations has been investigated, although a methodological problem in such studies is that their adoption cannot be so easily traced or observed. Such idea-only innovations have a relatively lower degree of observability and thus a slower rate of adoption. A number of new products involve both a hardware component and a software component, with the hardware purchased first so that the software component can then be utilized. Examples are VCRs and videotapes, compact disc players and CDs, and personal computers and computer software programs. Often a company will sell a hardware product at a relatively low price in order to capture market share and then sell its software at a relatively high price in order to recover profits. An example is video game players; these are sold at a fairly low price, but the video games to be played on them are sold at a relatively high price. This “shaver-and-blades” strategy is commonly used to speed the diffusion of consumer electronics innovations. Even though the software component of a technology is often not so apparent, we should not forget that a technology almost always represents a mixture of hardware and software. According to our definition, technology is a means of uncertainty reduction that is made possible by information about the cause-effect relationships on which the technology is based. This information often results from the scientific R&D activities that devel oped the technology. A technological innovation usually has at least some degree of benefit for its potential adopters, but this advantage is not always clear cut to those intended adopters. They are seldom certain that an innovation represents a superior alternative to the previous practice that it would replace, at least when they initially learn about it. Knowing of a technological innovation creates uncertainty about its consequences in the mind of potential adopters. Will the innovation solve an individual’s perceived problem? The potential advantage of a new idea impels an individual to exert effort to learn more about the innovation. Once such information-seeking activities reduce uncertainty about the innovation’s expected consequences to a tolerable level, a decision concerning adoption or rejection can be made. If a new idea is then used, further evaluative information about its effects is obtained. Thus, the innovation-decision process is essentially an information-seeking and information-processing activity in which an individual is motivated to reduce uncertainty about the advantages and disadvantages of the innovation (see Chapter 5). The main questions that an individual typically asks about a new idea include “What is the innovation?” “How does it work?” “Why does it work?” “What are the innovation’s consequences?” and “What will its advantages and disadvantages be in my situation?” TECHNOLOGY CLUSTERS An important conceptual and methodological issue is how to determine the boundaries around a technological innovation. The problem is how to determine where one innovation stops and another begins. If an innovation is defined as an idea that is perceived as new, the boundary question ought to be answered by the potential adopters who do the perceiving. In fact, this approach is used by diffusion scholars and by market researchers in “positioning” studies (described in Chapter 6). For example, some U.S. households that recycle paper also recycle bottles and cans, although many families recycle only paper. Presumably the two recycling behaviors represent two innovations that are part of an interrelated cluster of several recycling ideas. A technology cluster consists of one or more distinguishable elements of technology that are perceived as being closely interrelated. Some change agencies promote a “package” of innovations because they find that the innovations are thus adopted more rapidly. An example of a technology cluster was the package of rice-or wheat-growing innovations that led to the Green Revolution in the Third World countries of Latin America, Africa, and Asia. In addition to the so-called miracle varieties of rice or wheat, the cluster included chemical fertilizers, pesticides, and thicker planting of seeds. If the entire cluster were adopted by a farmer, crop yields approximately tripled. Past diffusion research generally investigated each innovation as if it were independent from other innovations. This oversimplification represents a dubious assumption, in that an adopter’s experience with one innovation obviously influences that individual’s perception of the next innovation to diffuse through the individual’s system. In reality, the innovations diffusing at about the same time in a system are interdependent. While it is much simpler for diffusion scholars to investigate the spread of each innovation as an independent event, this is a distortion of reality. More scholarly attention should be paid to technology clusters. PERCEIVED ATTRIBUTES OF INNOVATIONS It should not be assumed, as it sometimes has been in the past, that all innovations are equivalent units of analysis. This assumption is a gross oversimplification. While consumer innovations such as cellular telephones and VCR’s required only a few years to reach widespread adoption in the United States, other new ideas, such as using the metric system or seat belts in cars, require decades to reach complete use. The characteristics of innovations, as perceived by individuals, help to explain their different rates of adoption. 1. Relative advantage is the degree to which an innovation is perceived as better than the idea it supersedes. The degree of relative advantage may be measured in economic terms, but social prestige factors, convenience, and satisfaction are also important factors. It does not matter so much whether an innovation has a great deal of “objective” advantage. What does matter is whether an individual perceives the innovation as advantageous. The greater the perceived relative advantage of an innovation, the more rapid its rate of adoption will be. 2. Compatibility is the degree to which an innovation is perceived as being consistent with the existing values, past experiences, and needs of potential adopters. An idea that is incompatible with the values and norms of a social system will not be adopted as rapidly as an innovation that is compatible. The adoption of an incompatible innovation often requires the prior adoption of a new value system, which is a relatively slow process. An example of an incompatible innovation is the use of contraceptive methods in countries where religious beliefs discourage use of family planning, as in certain Muslim and Catholic nations. Previously in this chapter, we saw how the innovation of water boiling was incompatible with the hot-cold belief system in the Peruvian village of Los Molinas. 3. Complexity is the degree to which an innovation is perceived as difficult to understand and use. Some innovations are readily comprehended by most members of a social system; others are more complicated and are adopted more slowly. For example, the villagers in Los Molinas did not understand germ theory, which the health worker tried to explain to them as a reason for boiling their drinking water. New ideas that are simpler to understand are adopted more rapidly than innovations that require the adopter to develop new skills and understandings, such as the Dvorak keyboard. 4. Trialability is the degree to which an innovation may be experimented with on a limited basis. New ideas that can be tried on the installment plan will generally be adopted more quickly than innovations that are not divisible. Ryan and Gross (1943) found that every one of their Iowa farmer respondents adopted hybrid seed corn by first trying it on a partial basis. If the new seed could not have been sampled experimentally, its rate of adoption would have been much slower. Even then, many years of trial occurred before the typical Iowa farmer planted 100 percent of his corn acreage in hybrid seed. An innovation that is trialable represents less uncertainty to the individual who is considering it for adoption, as it is possible to learn by doing. 5. Observability is the degree to which the results of an innovation are visible to others. The easier it is for individuals to see the results of an innovation, the more likely they are to adopt. Such visibility stimulates peer discussion of a new idea, as the friends and neighbors of an adopter often request innovation evaluation information about it. Solar water- heating adopters, for example, are often found in neighborhood clusters in California, with three or four adopters located on the same block. Many other city blocks have no solar flat-plate collectors. The clustering of visible innovations is one evidence for the importance of observbility (and peer-to-peer networks). Other consumer innovations, such as home computers, are relatively low in observability and thus diffuse more slowly. Innovations that are perceived by individuals as having greater relative advantage, compatibility, trialability, and observability and less complexity will be adopted more rapidly than other innovations. Past research indicates that these five qualities are the most important char acteristics of innovations in explaining the rate of adoption. The first two attributes, relative advantage and compatability, are particularly important in explaining an innovation’s rate of adoption. RE-INVENTION For the first several decades of diffusion research, it was assumed that an innovation was an invariant quality that did not change as it diffused. I remember interviewing an Iowa farmer during my Ph.D. dissertation research at Iowa State University in 1954. I inquired about his adoption of 2, 4-D weed spray. The farmer described in some detail the particular and unusual ways in which he used the weed spray on his farm. At the end of his lengthy remarks, I simply checked “adopter” on my interview questionnaire. The concept of re-invention was not yet in my theoretical repertoire, so I condensed the farmer’s experience into my existing categories. In the 1970s, diffusion scholars began to study the concept of re- invention, defined as the degree to which an innovation is changed or modified by a user in the process of adoption and implementation. Some researchers measure re-invention as the degree to which an individual’s use of a new idea departs from the core or “mainline” version of the innovation promoted by a change agency (Eveland et al., 1977). Once scholars became aware of the concept of re-invention and began to measure it, they began to find that a considerable degree of re-invention had occurred for many innovations. Some innovations are difficult or impossible to re-invent; for example, hybrid seed corn does not allow a farmer much freedom to re- invent, as the hybrid vigor is genetically locked into the seed for only the first generation. Similarly, genetically modified (GM) corn seeds were sold in the early 2000s with a “killer gene” that destroys insects (such as European corn borers, an important pest, but also, unfortunately, many monarch butterfly caterpillars) when they eat the corn leaves. The second generation of this seed will not germinate, forcing the farmer to purchase new GM seed corn each year. Certain other innovations are more flexible in nature, and they are re- invented by many adopters who implement them in a wide variety of different ways. An innovation is not necessarily invariant during the process of its diffusion. And adopting an innovation is not necessarily a passive role of just implementing a standard template of the new idea. Many adopters want to participate actively in customizing an innovation to fit their unique situation. Later in this book, we show that an innovation diffuses more rapidly when it can be re-invented and that its adoption is more likely to be sustained. Given that an innovation exists, communication must take place if the innovation is to spread. We now turn our attention to this second element in the diffusion process. 2. Communication Channels Previously we defined communication as the process by which participants create and share information with one another in order to reach a mutual understanding. Diffusion is a particular type of communication in which the message content that is exchanged is concerned with a new idea. The essence of the diffusion process is the information exchange through which one individual communicates a new idea to one or several others. At its most elementary form, the process involves (1) an innovation, (2) an individual or other unit of adoption that has knowledge of, or has experienced using, the innovation, (3) another individual or other unit that does not yet have knowledge of, or experience with, the innovation, and (4) a communication channel connecting the two units. A communication channel is the means by which messages get from one individual to another. The nature of the information exchange relationship between a pair of individuals determines the conditions under which a source will or will not transmit the innovation to the receiver and the effect of such a transfer. Mass media channels are usually the most rapid and efficient means of informing an audience of potential adopters about the existence of an innovation—that is, to create awareness-knowledge. Mass media channels are all those means of transmitting messages that involve a mass medium, such as radio, television, newspapers, and so on, which enable one or a few individuals to reach an audience of many. On the other hand, interpersonal channels are more effective in persuading an individual to accept a new idea, especially if the interpersonal channel links two or more individuals who are similar in socioeconomic status, education, or other important ways. Interpersonal channels involve a face-to-face exchange between two or more individuals. In addition to mass media and interpersonal communication channels, interactive communication via the Internet has become more important for the diffusion of certain innovations in recent decades. Diffusion investigations show that most individuals do not evaluate an innovation on the basis of scientific studies of its consequences, although such objective evaluations are not entirely irrelevant, especially to the very first individuals who adopt. Instead, most people depend mainly upon a subjective evaluation of an innovation that is conveyed to them from other individuals like themselves who have already adopted the innovation. This dependence on the experience of near peers suggests that the heart of the diffusion process consists of the modeling and imitation by potential adopters of their network partners who have previously adopted. Diffusion is a very social process that involves interpersonal communication relationships (see Chapter 8). HETEROPHILY AND DIFFUSION An obvious principle of human communication is that the transfer of ideas occurs most frequently between two individuals who are similar, or homophilous. Homophily is the degree to which two or more individuals who interact are similar in certain attributes, such as beliefs, education, socioeconomic status, and the like. In a free-choice situation, when an individual can interact with any one of a number of other individuals, the tendency is to select someone who is very similar. Heterophily, the opposite of homophily, is defined as the degree to which two or more individuals who interact are different in certain attributes. Homophily occurs when similar individuals belong to the same groups, live or work near each other, and share similar interests. Physical and social propinquity makes homophilous communication more likely to occur than heterophilous communication. Such communication is also more likely to be effective and thus to be rewarding to the participants. More effective communication occurs when two or more individuals are homophilous. When they share common meanings and a mutual subcultural language, and are alike in personal and social characteristics, the communication of new ideas is likely to have greater effects in terms of knowledge gain, attitude formation and change, and overt behavior change. When homophily is present, communication is therefore likely to be rewarding to both participants. One of the most distinctive problems in the diffusion of innovations is that the participants are usually quite heterophilous. A change agent, for instance, is more technically competent than his or her clients. This difference frequently leads to ineffective communication as the two individuals do not speak the same language. However, when two individuals are identical regarding their technical grasp of an innovation, diffusion cannot occur as there is no new information to exchange. The nature of diffusion demands that at least some degree of heterophily be present between the two participants in the communication process. Ideally, the individuals would be homophilous on all other variables (education, socioeconomic status, and the like) even though they are heterophilous regarding the innovation. Usually, however, the two indi viduals are heterophilous on all of these variables because knowledge of, and experience with, an innovation are highly related to socioeconomic status, education, and so forth. 3. Time Time is a third element in the diffusion process. Much other behavioral science research is timeless in the sense that the time dimension is simply ignored or does not matter. The inclusion of time as a variable in diffusion research is one of its strengths, but the measurement of the time dimension (often by means of the respondents’ recall) can be criticized (see Chapter 3). The time dimension is involved in diffusion in (1) the innovation-decision process by which an individual passes from first knowledge of an innovation through its adoption or rejection, (2) the innovativeness of an individual or other unit of adoption (that is, the relative earliness/lateness with which an innovation is adopted) compared with other members of a system, and (3) an innovation’s rate of adoption in a system, usually measured as the number of members of the system who adopt the innovation in a given time period. THE INNOVATION-DECISION PROCESS The innovation-decision process is the process through which an individual (or other decision-making unit) passes from first knowledge of an innovation, to the formation of an attitude toward the innovation, to a decision to adopt or reject, to implementation and use of the new idea, and to confirmation of this decision. We conceptualize five main steps in the innovation-decision process: (1) knowledge, (2) persuasion, (3) decision, (4) implementation, and (5) confirmation. Knowledge is gained when an individual (or other decision-making unit) learns of the innovation’s existence and gains some understanding of how it functions. Persuasion takes place when an individual forms a favorable or unfavorable attitude toward the innovation. Decision occurs when an individual engages in activities that lead to a choice to adopt or reject the innovation. Implementation takes place when an individual puts an innovation into use. Re-invention is especially likely to occur at the implementation stage. Confirmation occurs when an individual seeks reinforcement of an innovation-decision that has already been made, but he or she may reverse this previous decision if exposed to conflicting messages about the innovation. The innovation-decision process is an information-seeking and information-processing activity in which an individual obtains information in order to gradually decrease uncertainty about the innovation. At the knowledge stage, an individual mainly seeks software information that is embodied in the technological innovation, information that reduces uncertainty about the cause-effect relationships that are involved in the innovation’s capacity to solve a problem. At this stage the individual wants to know what the innovation is and how and why it works. Mass media channels can effectively transmit such software information. But increasingly at the persuasion stage, and especially at the decision stage, an individual seeks innovation-evaluation information in order to reduce uncertainty about an innovation’s expected consequences. Here an individual wants to know the innovation’s advantages and disadvantages for his or her own particular situation. Interpersonal communication networks with near peers are particularly likely to convey such evaluative information about an innovation. Mass media channels are not very important at this stage because their messages are general in nature, and an individual deciding to adopt wants to know specific information: Will the innovation be beneficial to me in my particular situation? Subjective evaluations of a new idea by other individuals are especially likely to influence an individual at the decision stage, and perhaps at the confirmation stage. The innovation-decision process can lead to either adoption, a decision to make full use of an innovation as the best course of action available, or rejection, a decision not to adopt an innovation. Such decisions can be reversed at a later point. For example, discontinuance is a decision to reject an innovation after it has previously been adopted. Discontinuance may occur because an individual becomes dissatisfied with an innovation or because the innovation is replaced with an improved idea. It is also possible for an individual to adopt an innovation after a previous decision to reject it. Such later adoption and discontinuance occur during the confirmation stage of the innovation-decision process. The innovation-decision process involves time in the sense that the five steps usually occur in a time-ordered sequence of (1) knowledge,(2) persuasion, (3) decision, (4) implementation, and (5) confirmation. Exceptions to the usual sequence of these five stages may occur for some individuals under some conditions, such as when the decision stage precedes the persuasion stage (perhaps an individual was ordered to adopt by some authority figure). The innovation-decision period is the length of time required to pass through the innovation-decision process. Individuals vary in this innovation- decision period, with some people requiring many years to adopt an innovation, while other people move rapidly from knowledge to implementation. The present discussion of the innovation-decision process is mainly at the level of a single individual and of individual-optional innovation-decisions. But many innovation-decisions are made by organizations, communities, or other types of adopting units, rather than by individuals. For example, an organization may decide to implement an e-mail system on the basis of a staff decision or an official’s authority decision. An individual employee in the organization may have little or no say in this innovation-decision. When an innovation-decision is made by a system, rather than by an individual, the decision process is more complicated because a number of individuals are involved (see Chapter 10). So time is an important dimension in the innovation-decision process. INNOVATIVENESS AND ADOPTER CATEGORIES Innovativeness is the degree to which an individual or other unit of adoption is relatively earlier in adopting new ideas than the other members of a system. Rather than describing an individual as “less innovative than the average member of a social system,” it is more efficient to refer to the individual as being in the “late majority” or in some other adopter category. This shorthand notation saves words and contributes to clearer understanding. Diffusion research shows that members of each of the adopter categories have a great deal in common. If the individual is like most others in the late majority category, he or she is of relatively lower socioeconomic status, makes little use of mass media channels, and learns about most new ideas from peers via interpersonal communication channels. Adopter categories, the classifications of members of a social system on the basis of innovativeness, include: (1) innovators, (2) early adopters, (3) early majority, (4) late majority, and (5) laggards. Innovators are active information seekers about new ideas. They have a high degree of mass media exposure, and their interpersonal networks extend over a wide area, reaching outside their local system. Innovators are able to cope with higher levels of uncertainty about an innovation than are other adopter categories. As the first to adopt a new idea, they cannot depend upon the subjective evaluations of the innovation from other members of their system. We shall present a concise word picture of each of the adopter categories in Chapter 7. The measure of innovativeness and the classification of a system’s members into adopter categories are based upon the relative time at which an innovation is adopted. RATE OF ADOPTION A third way in which the time dimension is involved in the diffusion of innovations concerns the rate of adoption, defined as the relative speed with which an innovation is adopted by members of a social system. When the number of individuals adopting a new idea is plotted on a cumulative frequency basis over time, the resulting distribution is an S-shaped curve. At first, only a few individuals adopt the innovation in each time period (a year or a month, for example); these are the innovators. Soon the diffusion curve begins to climb, as more and more individuals adopt in each succeeding time period. Eventually, the trajectory of the rate of adoption begins to level off, as fewer and fewer individuals remain who have not yet adopted the innovation. Finally, the S-shaped curve reaches its asymptote, and the diffusion process is finished. Most innovations have an S-shaped rate of adoption. But there is variation in the slope of the “S” from innovation to innovation; some new ideas diffuse relatively rapidly, and the S-curve is quite steep. Other innovations have a slower rate of adoption, and the S-curve is more gradual, with a slope that is relatively lazy. One issue addressed by diffusion research is why some innovations have a rapid rate of adoption, while others are adopted more slowly (see Chapter 6). The rate of adoption is usually measured by the length of time required for a certain percentage of the members of a system to adopt an innovation. Therefore, we see that the rate of adoption is measured for an innovation in a system, rather than for an individual as the unit of analysis (this variable is innovativeness). The system may be a community, an organization, or some other structure. Innovations that are perceived by individuals as possessing greater relative advantage, compatibility, and the like, have a more rapid rate of adoption, as discussed previously. There are also differences in the rate of adoption for the same innovation in different social systems. Many aspects of diffusion cannot be explained by just individual behavior. The system has a direct effect on diffusion through its norms and other system-level qualities, as well as an indirect influence through the behavior of its individual members. 4. A Social System A social system is defined as a set of interrelated units that are engaged in joint problem solving to accomplish a common goal. The members or units of a social system may be individuals, informal groups, organizations, and/or subsystems. The system analyzed in a diffusion study may consist of all the peasant families in a Peruvian village, medical doctors in a hospital, or all the consumers in the United States. Each unit in a social system can be distinguished from other units. All members cooperate at least to the extent of seeking to solve a common problem in order to reach a mutual goal. This sharing of a common objective binds the system together. Diffusion occurs within a social system. The social structure of the system affects the innovation’s diffusion in several ways. The social system constitutes a boundary within which an innovation diffuses. Here we deal with how the system’s social structure affects diffusion, the effect of norms on diffusion, the roles of opinion leaders and change agents, types of innovation- decisions, and the consequences of innovation. Each of these issues involves relationships between the social system and the diffusion process that occurs within it. SOCIAL STRUCTURE AND DIFFUSION To the extent that the units in a social system are not all identical in their behavior, structure exists in a system. We define structure as the patterned arrangements of the units in a system. This structure gives regularity and stability to human behavior in a system; it allows one to predict behavior with some degree of accuracy. Thus, structure represents a type of information, in that it decreases uncertainty. An illustration of this predictability is provided by structure in a bureaucratic organization such as a government agency. The well-developed social structure in such a system consists of hierarchial positions, giving individuals in higher-ranked positions the right to issue orders to individuals of lower rank. Their orders are expected to be carried out. Such patterned social relationships among the members of a system constitute social structure, one type of structure. In addition to this formal structure among the units in a social system, an informal structure also exists in the interpersonal networks linking a system’s members, tracing who interacts with whom and under what circumstances. We define such communication structure as the differentiated elements that can be recognized in the patterned communication flows in a system. Previously we defined homophily as the degree to which two or more individuals in a system talk with others who are similar to them. A communication structure is thus often created in a system in which homophilous sets of individuals are grouped together in cliques. A complete lack of communication structure in a system would be represented by a situation in which each individual talked with equal probability to each other member of the system. This situation might occur when complete strangers first come together. However, regular patterns soon begin to occur in the communication network of the system. These aspects of communication structure predict, in part, the behavior of individual members of the social system, including when they adopt an innovation. The structure of a social system can facilitate or impede the diffusion of innovations. The impact of the social structure on diffusion is of special interest to sociologists and social psychologists, and the way in which the communication structure of a system affects diffusion is a particularly interesting topic for communication scholars. Katz (1961) remarked, “It is as unthinkable to study diffusion without some knowledge of the social structures in which potential adopters are located as it is to study blood circulation without adequate knowledge of the veins and arteries.” Compared to other aspects of diffusion research, however, there have been relatively few studies of how the social or communication structure affects the diffusion and adoption of innovations in a system. It is a rather complicated matter to untangle the effects of a system’s structure on diffusion, independent from the effects of the characteristics of individuals that make up the system. Consider an illustration of system effects, the influences of the structure and/or composition of a system on the behavior of the members of the system. Rogers and Kincaid (1981) identified two Korean women in their study of the diffusion of family planning in Korea. Both women are illiterate, are married, have two children, and are twenty-nine years of age. The husbands of both women are high school graduates; each operates a farm of five acres. One might expect that both women would be about equally likely, or unlikely, to adopt a new contraceptive method. But the women are different in one crucial respect: they live in different villages, one in Village A and one in Village B. Family-planning methods have been adopted by 57 percent of the eligible couples in Village A and by only 26 percent in Village B. The social and communication structures of these two villages are quite different regarding the diffusion of contraceptives, even though contraceptives were promoted equally in both villages by the national family-planning program. We predict that the woman in Village A will be more likely to adopt a contraceptive method than her counterpart in Village B because of system effects: Mrs. A’s friends and neighbors are more likely to encourage her to adopt since they themselves have adopted, and the village leaders in Village A are especially committed to family planning, while in Village B they are not. This example shows how a system’s structure can affect the diffusion and adoption of innovations, over and above the effect of such variables as the individual characteristics of the members of the system. Individual innovativeness is affected both by an individual’s characteristics and by the nature of the social system in which the individual is a member. SYSTEM NORMS AND DIFFUSION The Korean investigation by Rogers and Kincaid (1981) also illustrates the importance of village norms in affecting the rate of adoption of innovations. For example, their study of twenty-four Korean villages found large differences from village to village, both in the level of adoption of family-planning and in the adoption of particular types of family-planning methods. One village had 51 percent adoption of the intrauterine device (IUD) and only one vasectomy adopter, while another village had 23 percent adoption of vasectomy. Yet another was a “pill village” in which all the adopters of family planning decided to use contraceptive pills. These differences were not due to the nature of the national family-planning program in Korea, which had promoted the same “cafeteria” of contraceptive methods in all villages for ten years prior to our data gathering. The main explanation for the different contraceptive behavior from village to village was these systems’ norms. Norms are the established behavior patterns for the members of a social system. Norms define a range of tolerable behavior and serve as a guide or standard for the behavior of members of a social system. The norms of a system tell individuals what behavior they are expected to perform. A system’s norms can be a barrier to change, as in the previous example of water boiling in a Peruvian community. Such resistance to new ideas is often found in norms on food habits. In India, for example, sacred cows roam the countryside while millions of people are mal-nourished. Pork is not consumed by Muslims and Jews. Polished white rice is eaten in most of Asia and the United States, even though whole rice is much more nutritious. These are examples of cultural and religious norms. Norms can operate at the level of a nation, a religious community, an organization, or a local system such as a village. OPINION LEADERS AND CHANGE AGENTS The most innovative member of a system is very often perceived as a deviant from the social system and is accorded a status of low credibility by the average members of the system. This individual’s role in diffusion (especially in persuading others to adopt the innovation) is therefore very limited. Certain other members of the system function as opinion leaders. They provide information and advice about innovations to many other individuals in the system. Opinion leadership is the degree to which an individual is able to influence other individuals’ attitudes or overt behavior informally in a desired way with relative frequency. This informal leadership is not a function of the individual’s formal position or status in the system. Opinion leadership is earned and maintained by the individual’s technical competence, social accessibility, and conformity to the system’s norms. When the social system is oriented to change, the opinion leaders are more innovative; but when the system’s norms are opposed to change, the behavior of the leaders also reflects this norm. Through their conformity to the system’s norms, opinion leaders serve as a model for the innovation behavior of their followers. Opinion leaders thus exemplify and express the system’s structure. Many systems have both innovative opinion leaders and leaders who oppose change. Influential persons can lead in the spread of new ideas, or they can head an active opposition. When opinion leaders are compared with their followers, they (1) are more exposed to all forms of external communication and thus are somewhat more cosmopolite, (2) have somewhat higher socioeconomic status, and (3) are more innovative (although their degree of innovativeness depends, in part, on the system’s norms). The most striking characteristic of opinion leaders is their unique and influential position in their system’s communication structure: they are at the center of interpersonal communication networks. A communication network consists of interconnected individuals who are linked by patterned flows of information. An opinion leader’s interpersonal networks allow him or her to serve as a social model whose innovative behavior is imitated by many other members of the system. The respect with which the opinion leader is held can be lost, however, if an opinion leader deviates too far from the norms of the system. Opinion leaders can be “worn out” by change agents who overuse them in diffusion activities. Opinion leaders may begin to be perceived by their peers as too much like professional change agents and therefore lose their credibility with their former followers. Opinion leaders are members of the social system in which they exert their influence. A different kind of individual with influence in the system is professionals who represent change agencies external to the system. A change agent is an individual who influences clients’ innovation-decisions in a direction deemed desirable by a change agency. The change agent usually seeks to obtain the adoption of new ideas but may also attempt to slow down diffusion and prevent the adoption of undesirable innovations. Change agents often use opinion leaders in a social system as their lieutenants in diffusion activities. Change agents are usually professionals with a university degree in a technical field. This professional training, and the social status that goes with it, usually means that change agents are heterophilous from their typical clients, thus posing problems for effective communication about the innovations they are promoting. Many change agencies employ change agent aides. An aide is a less than fully professional change agent who intensively contacts clients to influence their innovation-decisions. Aides are usually homophilous with the average client and thus provide one means of bridging the heterophily gap between professional change agents and their client audience. TYPES OF INNOVATION-DECISIONS The social system has yet another important influence in the diffusion of new ideas. Innovations can be adopted or rejected (1) by an individual member of a system or (2) by the entire social system, which can decide to adopt an innovation by a collective or an authority decision. 1. Optional innovation-decisions are choices to adopt or reject an innovation that are made by an individual independent of the decisions of the other members of the system. Even in this case, the individual’s decision may be influenced by the norms of the system and by communication through interpersonal networks. The decision of an individual housewife in Los Molinas to adopt or reject boiling water was an optional innovation-decision, although this choice was influenced by community-level factors, such as norms on the hot-cold complex. The distinctive aspect of optional innovation-decisions is that the individual is the main unit of decision making, rather than the social system. The classical diffusion model evolved out of early diffusion investigations of optional innovation-decisions: the diffusion of hybrid corn among Iowa farmers, the spread of a new antibiotic drug among medical doctors, and the like. In more recent decades, however, the scope of the diffusion paradigm has included collective and authority innovation-decisions. Collective innovation-decisions are choices to adopt or reject an innovation that are made by consensus among the members of a system. All units in the system usually must conform to the system’s decision once it is made. Authority innovation-decisions are choices to adopt or reject an innovation that are made by a relatively few individuals in a system who possess power, status, or technical expertise. An individual member of the system has little or no influence in the authority innovation-decision; he or she simply implements the decision once it is made by an authority. For instance, some years ago the president of a large U.S. computer corporation decided that all male employees should wear a white shirt, a conservative necktie, and a dark suit; this authority decision had to be followed by every man who worked for the computer company. These three types of innovation-decisions range on a continuum from optional decisions (where the adopting individual has almost complete responsibility for the decision), through collective decisions (where the individual has a say in the decision), to authority decisions (where the adopting individual has no influence in the innovation-decision). Collective and authority decisions are more common than optional decisions in most organizations, such as factories, schools, or government organizations, in comparison with other fields such as agriculture and consumer behavior, where most innovation-decisions by farmers and consumers are optional. Generally, the fastest rate of adoption of innovations stem

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