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Thursday, January 24, 2019

Greatness

From Wikipedia, the free encyclopedia

Krönung des Tugendhelden (c. 1612–1614) by Peter Paul Rubens
 
 
Greatness is a concept of a state of superiority affecting a person or object in a particular place or area. Greatness can also be attributed to individuals who possess a natural ability to be better than all others. The concept carries the implication that the particular person or object, when compared to others of a similar type, has clear advantage over others. As a descriptive term it is most often applied to a person or their work, and may be qualified or unqualified. An example of an expression of the concept in a qualified sense would be "Abraham Lincoln is the definition of greatness" or "Franklin D. Roosevelt was one of the greatest wartime leaders". In the unqualified sense it might be stated "George Washington achieved greatness within his own lifetime", thus implying that "greatness" is a definite and identifiable quality. Application of the terms "great" and "greatness" is dependent on the perspective and subjective judgements of those who apply them. Whereas in some cases the perceived greatness of a person, place or object might be agreed upon by many, this is not necessarily the case, and the perception of greatness may be both fiercely contested and highly individual.

Historically, in Europe, rulers were sometimes given the attribute "the Great", as in Alexander the Great, Frederick the Great, and Catherine the Great. Starting with the Roman consul and general Pompey, the Latin equivalent Magnus was also used, as in Pompeius Magnus, Albertus Magnus, and Carolus Magnus. The English language uses the Latin term magnum opus, (literally "great work") to describe certain works of art and literature. 

Since the publication of Francis Galton's Hereditary Genius in 1869, and especially with the accelerated development of intelligence tests in the early 1900s, there has been a vast amount of social scientific research published relative to the question of greatness. Much of this research does not actually use the term great in describing itself, preferring terms such as eminence, genius, exceptional achievement, etc. Historically the major intellectual battles over this topic have focused around the questions of nature versus nurture or person versus context. Today the importance of both dimensions is accepted by all, but disagreements over the relative importance of each are still reflected in variations in research emphases.

"Jesus teaches about greatness" (Matthew 18) by Julius Schnorr von Karolsfeld, 1860

Genetic approaches

The early research had a strong genetic emphasis and focused on intelligence as the driving force behind greatness.

Hereditary Genius – Galton (1869)

The earliest such research, Hereditary Genius by Francis Galton (1869), argued that people vary hugely in “natural ability” which is inherited biologically. Those at the very top end of the range, i.e., geniuses, become the leaders and great achievers of their generation. To prove this thesis Galton collected data showing that genius clusters in what he termed “Notable Family Lines”, such as those of Bernoulli, Cassini, Darwin, Herschel, and Jussieu in science, or Bach in music.

Galton then calculated the odds of eminent people having eminent relations, taking into account the closeness of the biological connection (e.g., son vs grandson), and the magnitude of achievement of the eminent parent. His findings were as anticipated: the more famous the parent (i.e., the greater level of presumed “natural ability”), the greater likelihood there would be illustrious relatives; and the closer the blood tie, the greater those odds.

Early Mental Traits of 300 Geniuses – Cox (1926)

Catharine Cox’s book on The Early Mental Traits of Three Hundred Geniuses (1926), was similar to Galton’s in its orientation. Using the method that her mentor, Stanford Psychology Professor Lewis Terman, had developed for differentiating children in terms of intelligence, Cox coded records of childhood and adolescent achievements of 301 historic eminent leaders and creators to estimate what their IQs would have been on the basis of intellectual level of such achievements relative to the age at which they were accomplished. For example, John Stuart Mill reportedly studied Greek at 3, read Plato at 7, and learned calculus at 11. As such, what he was doing at 5, the average person couldn’t do until 9 years, 6 months of age, giving Mill an estimated IQ of 190.

Cox found that the perceived eminence of those with the highest IQs was higher than that of those attaining lower IQ estimates, and that those with higher IQs also exhibited more versatility in their achievements. For example, da Vinci, Michelangelo, Descartes, Benjamin Franklin, Goethe, and others with IQs in the mid 160s or above were superior in their versatility to those attaining lower scores, such as George Washington, Palestrina, or Philip Sheridan.

Both Cox and Galton have been criticized for failing to take account of the role of nurture, or more specifically socio-economic and educational advantage, in the achievements of these historical greats.

Cultural approach

There was one major anthropological study of genius, and it was triggered specifically by the author’s contentions with Galton’s work.

Configurations of Cultural Growth – Kroeber (1944)

Alfred Kroeber’s Configurations of Cultural Growth (1944) looked at many of the same historic greats as did Galton and Cox, but from a completely different orientation. As a cultural anthropologist, Kroeber maintained that, in Simonton's words, “culture takes primacy over the individual in any account of human (behavior), and that historic geniuses are no exception…” 

To prove his thesis, Kroeber collected “long lists of notable figures from several nationalities and historic eras”, and then grouped them within a field and a shared cultural context, e.g., “Configuration for American Literature”. Then within these groupings he listed his notables in “strict chronological order”, identifying the most eminent figures by using capital letters for their surnames (e.g. EMERSON, LONGFELLOW, POE, WHITMAN, etc. in above configuration).

Kroeber found that genius never appeared in isolation, but rather, in Simonton's words, that “one genius cluster(ed) with others of greater and lesser fame in adjacent generations”. He also found that there were historical “crests” and “troughs” in every field. These fluctuations in the appearance of genius were much too rapid to be explained by the simple mechanism of genetic inheritance along family lines.

Kroeber argued, in Simonton's words, that his “configurations” were due to “emulations”: “Geniuses cluster in history because the key figures of one generation emulate those in the immediately preceding generations… (until) it attains a high point of perfection that stymies further growth”. At this point the “tradition degenerates into empty imitation, as most creative minds move on to greener pastures”.

Recent research is consistent with these explanations; but many aspects of the developmental process from birth to the attainment of greatness remain unaccounted for by Kroeber’s anthropological approach.

Developmental approaches

Retrospective studies, involving extensive interviews with individuals who have attained eminence, or at least exceptional levels of achievement, have added much to our understanding of the developmental process. Two studies in particular stand out.

Scientific Elite – Zuckerman (1977)

Harriet Zuckerman’s Scientific Elite: Nobel Laureates in the United States, is based on many sources of research evidence, including a series of forty-one extended interviews with American winners of the Nobel Prize for science. 

Zuckerman reported her results around two main topics: How the Prize is Awarded, and Career Development of the Scientific Elite.
 
In relation to the question of the career development of the scientific elite Zuckerman uses the phrase "accumulation of advantage" to describe her findings. In her words: “Scientists who show promise early in their careers (are) given greater opportunities in the way of research training and facilities. To the extent that these scientists are as competent as the rest or more so, they ultimately will do far better in terms of both role performance and reward… rewards (which) can be transformed into resources for further work.. (and hence over time) scientists who are initially advantaged gain even greater opportunities for further achievement and rewards.”

To see if ‘accumulation of advantage’ was operating in the career development of the scientific elite, Zuckerman compared the careers of future laureates with those of “members of the United States National Academy of Sciences and the scientific rank and file” along a number of dimensions including socioeconomic origins, status of undergraduate and graduate education, the process of moving into the scientific elite, and first jobs and professorships.

She also interviewed forty-one Nobel laureates extensively about their "apprenticeships" to "master" scientists while they were doing their doctoral research, and other aspects of their career development related to the above topics.

Zuckerman concluded that evidence of "accumulative of advantage" was clearly present over the course of development, with result that her research “… cast(s) considerable doubt on the conclusion that marked differences in performance between the ultra-elite and other scientists reflect equally marked differences in their initial capacities to do scientific work”.

Developing Talent in Young People – Bloom et al (1985)

Benjamin Bloom and five colleagues conducted extensive interviews with 120 “young men and women (as well as their parents and influential teachers)… who had reached the highest levels of accomplishment” in six fields – Olympic sprint swimmers, Top 10 rated professional tennis players, concert pianists, accomplished sculptors, exceptional mathematicians, and outstanding research neurologists.

They report many findings relevant to the “talent development process", including:
  • Development was tied throughout to the values, interests, resources, and personal investments of the family of origin. In most families “introduction to the field and initial… skill development occurred” because the “(p)arents (or other family members), in pursuing their own interests, created situations that intrigued, interested, or involved the child… The child’s interest was rewarded or encouraged…” and the parents then provided other ways to extend this interest.
  • The “work ethic” is central to talent development. It is developed by “the home environment” and “…directly related to learning and participation in the chosen talent field”.
  • “Each group of parents strongly encouraged their children’s development in a particularly highly approved talent field (related to the parents’ own “special interests”) and gave much less support to other possible talent fields and activities.”
  • “Families and teachers were crucial at every point along the way to excellence… what families and teachers do at different times and how they do it clearly sets the stage for exceptional learning in each talent field”.
  • “Few… (of the) individuals (included in this study) were regarded as child prodigies”; and, as a result, this research “raises (serious) questions about earlier views of special gifts and innate abilities as necessary prerequisites of talent development”.

Recent approaches

A 1995 book by Hans Eysenck argues that a “personality trait” called Psychoticism is central to becoming a creative genius; and a more recent book by Bill Dorris (2009) looks at the influence of “everything from genetics to cultural crises”, including chance, over the course of development of those who attain greatness. 

Hans Eysenck's book, Genius: The Natural History of Creativity (1995), "construct(s)... a model of genius and creativity" whose "novelty lies in (its) attempt to make personality differences central to the argument".

In particular Eysenck is interested in a personality trait called “psychoticism … chief among (whose) cognitive features is a tendency to over-inclusiveness, i.e., an inclination not to limit one's associations to relevant ideas, memories, images, etc."

He considers a massive range of experimental psychological research in order to establish the underlying genetic, neuro-chemical mechanisms which may be operating to influence levels of creativity associated with fluctuations in “the tendency towards over-inclusiveness indicative of psychoticism..."

Eysenck's assessment of his overall argument is as follows: "There is no hint that the theory is more than a suggestion of how many disparate facts and hypotheses can be pulled together into a causal chain, explaining… the apogee of human endeavor - genius. If the theory has one point in its favour it is that every step can be tested experimentally, and that many steps have already received positive support from such testing." 

The Arrival of The Fittest - Dorris (2009)

Bill Dorris's book, The Arrival of The Fittest: How The Great Become Great (2009), attempts to address a number of issues which remain unanswered on the subject. These include the role of chance over the course of development, the importance of the development of unique personal characteristics to achieving greatness, and the influence of changes in the wider worlds surrounding the person - from interpersonal to societal - on the course of an individual's development.

Dorris argues that those who attain ‘greatness’ are credited with solving a key generational problem in a field and/or society (e.g., Einstein resolving the conflict between Newton and Maxwell in physics at the outset of the 20th century; or Woody Guthrie providing a voice for the outcasts of the Great Depression of the 1930s).

Dorris’s core argument is that those who become ‘great’ start out with sufficient genetic potential and then are able, over two or more decades, to obtain matches/fits with “the right kind of problems” to extend the development of these genetic biases into what Dorris terms, “key characteristics”. These are the intellectual, personality, and self characteristics which eventually turn out to be required to solve a key generational problem in their field and/or society.

Dorris argues that there are four types of matching processes which occur over the course of such development. These refer to matches between the developmental needs of the person and the opportunities and resources essential to engaging in problem solving activities that stimulate further development of those aspects of intelligence, personality, and self which eventually become key characteristics.

Two of these matching processes are covered extensively in the existing research literature: continuous matching and cumulative matching.

The other two of the matching processes described by Dorris are completely new to this book: catalytic matching and chaotic matching. 

Dorris’s argument in relation to catalytic matching is that anyone who eventually becomes a ‘great’ will have experienced one or more sustained periods of exceptionally accelerated development of their key characteristics, accelerations which serve massively to differentiate them from their former peers in terms of both development and visibility within the field.

This acceleration occurs because the person becomes the focal point (star) of a self-reinforcing system of expertise and resources (catalytic system) which thrives off this person’s accelerated development and visibility.

Dorris's argument in relation to chaotic matching is that access to the resources and learning opportunities essential to the development of key characteristics of an eventual ‘great’ often occurs not due to the efforts/planning of the individual, but simply due to chance events in the interpersonal, institutional or societal worlds around the person, who (unlike perhaps millions of equally capable peers) becomes the beneficiary of these chance events – events which Dorris argues can change a person’s entire future in much the same way as a lottery jackpot or a Titanic ticket.

Dorris documents his theoretical arguments with extensive case studies of a wide range of individuals, including Einstein, Elvis, Monet, Mozart, da Vinci, Abraham Lincoln, Watson and Crick, basketball great Bill Russell, Louis Armstrong, Bill Gates, Alfred Hitchcock, Woody Guthrie, and Norma Jeane/Marilyn Monroe.

Innovation

From Wikipedia, the free encyclopedia
 
Innovation can be simply defined as a "new idea, creative thoughts, new imaginations in form of device or method". However, innovation is often also viewed as the application of better solutions that meet new requirements, unarticulated needs, or existing market needs. Such innovation takes place through the provision of more-effective products, processes, services, technologies, or business models that are made available to markets, governments and society. The term "innovation" can be defined as something original and more effective and, as a consequence, new, that "breaks into" the market or society. Innovation is related to, but not the same as, invention, as innovation is more apt to involve the practical implementation of an invention (i.e. new/improved ability) to make a meaningful impact in the market or society, and not all innovations require an invention. Innovation often manifests itself via the engineering process, when the problem being solved is of a technical or scientific nature. The opposite of innovation is exnovation.
 
While a novel device is often described as an innovation, in economics, management science, and other fields of practice and analysis, innovation is generally considered to be the result of a process that brings together various novel ideas in such a way that they affect society. In industrial economics, innovations are created and found empirically from services to meet growing consumer demand.

Definition

A 2014 survey of literature on innovation found over 40 definitions. In an industrial survey of how the software industry defined innovation, the following definition given by Crossan and Apaydin was considered to be the most complete, which builds on the Organization for Economic Co-operation and Development (OECD) manual's definition:
Innovation is production or adoption, assimilation, and exploitation of a value-added novelty in economic and social spheres; renewal and enlargement of products, services, and markets; development of new methods of production; and the establishment of new management systems. It is both a process and an outcome.
According to Kanter innovation includes original invention and creative use and defines innovation as a generation, admission and realization of new ideas, products, services and processes.

Two main dimensions of innovation were degree of novelty (patent) (i.e. whether an innovation is new to the firm, new to the market, new to the industry, or new to the world) and kind of innovation (i.e. whether it is processor product-service system innovation). In recent organizational scholarship, researchers of workplaces have also distinguished innovation to be separate from creativity, by providing an updated definition of these two related but distinct constructs:
Workplace creativity concerns the cognitive and behavioral processes applied when attempting to generate novel ideas. Workplace innovation concerns the processes applied when attempting to implement new ideas. Specifically, innovation involves some combination of problem/opportunity identification, the introduction, adoption or modification of new ideas germane to organizational needs, the promotion of these ideas, and the practical implementation of these ideas.

Inter-disciplinary views

Business and economics

In business and in economics, innovation can become a catalyst for growth. With rapid advancements in transportation and communications over the past few decades, the old-world concepts of factor endowments and comparative advantage which focused on an area's unique inputs are outmoded for today's global economy. Economist Joseph Schumpeter (1883–1950), who contributed greatly to the study of innovation economics, argued that industries must incessantly revolutionize the economic structure from within, that is innovate with better or more effective processes and products, as well as market distribution, such as the connection from the craft shop to factory. He famously asserted that "creative destruction is the essential fact about capitalism". Entrepreneurs continuously look for better ways to satisfy their consumer base with improved quality, durability, service and price which come to fruition in innovation with advanced technologies and organizational strategies.

A prime example of innovation involved the explosive boom of Silicon Valley startups out of the Stanford Industrial Park. In 1957, dissatisfied employees of Shockley Semiconductor, the company of Nobel laureate and co-inventor of the transistor William Shockley, left to form an independent firm, Fairchild Semiconductor. After several years, Fairchild developed into a formidable presence in the sector. Eventually, these founders left to start their own companies based on their own, unique, latest ideas, and then leading employees started their own firms. Over the next 20 years, this snowball process launched the momentous startup-company explosion of information-technology firms. Essentially, Silicon Valley began as 65 new enterprises born out of Shockley's eight former employees. Since then, hubs of innovation have sprung up globally with similar metonyms, including Silicon Alley encompassing New York City

Another example involves business incubators – a phenomenon nurtured by governments around the world, close to knowledge clusters (mostly research-based) like universities or other Government Excellence Centers – which aim primarily to channel generated knowledge to applied innovation outcomes in order to stimulate regional or national economic growth.

Organizations

In the organizational context, innovation may be linked to positive changes in efficiency, productivity, quality, competitiveness, and market share. However, recent research findings highlight the complementary role of organizational culture in enabling organizations to translate innovative activity into tangible performance improvements. Organizations can also improve profits and performance by providing work groups opportunities and resources to innovate, in addition to employee's core job tasks. Peter Drucker wrote:
Innovation is the specific function of entrepreneurship, whether in an existing business, a public service institution, or a new venture started by a lone individual in the family kitchen. It is the means by which the entrepreneur either creates new wealth-producing resources or endows existing resources with enhanced potential for creating wealth. –Drucker
According to Clayton Christensen, disruptive innovation is the key to future success in business. The organisation requires a proper structure in order to retain competitive advantage. It is necessary to create and nurture an environment of innovation. Executives and managers need to break away from traditional ways of thinking and use change to their advantage. It is a time of risk but even greater opportunity. The world of work is changing with the increase in the use of technology and both companies and businesses are becoming increasingly competitive. Companies will have to downsize and re-engineer their operations to remain competitive. This will affect employment as businesses will be forced to reduce the number of people employed while accomplishing the same amount of work if not more.

While disruptive innovation will typically "attack a traditional business model with a lower-cost solution and overtake incumbent firms quickly," foundational innovation is slower, and typically has the potential to create new foundations for global technology systems over the longer term. Foundational innovation tends to transform business operating models as entirely new business models emerge over many years, with gradual and steady adoption of the innovation leading to waves of technological and institutional change that gain momentum more slowly. The advent of the packet-switched communication protocol TCP/IP—originally introduced in 1972 to support a single use case for United States Department of Defense electronic communication (email), and which gained widespread adoption only in the mid-1990s with the advent of the World Wide Web—is a foundational technology.

All organizations can innovate, including for example hospitals, universities, and local governments. For instance, former Mayor Martin O’Malley pushed the City of Baltimore to use CitiStat, a performance-measurement data and management system that allows city officials to maintain statistics on several areas from crime trends to the conditions of potholes. This system aids in better evaluation of policies and procedures with accountability and efficiency in terms of time and money. In its first year, CitiStat saved the city $13.2 million. Even mass transit systems have innovated with hybrid bus fleets to real-time tracking at bus stands. In addition, the growing use of mobile data terminals in vehicles, that serve as communication hubs between vehicles and a control center, automatically send data on location, passenger counts, engine performance, mileage and other information. This tool helps to deliver and manage transportation systems.

Still other innovative strategies include hospitals digitizing medical information in electronic medical records. For example, the U.S. Department of Housing and Urban Development's HOPE VI initiatives turned severely distressed public housing in urban areas into revitalized, mixed-income environments; the Harlem Children’s Zone used a community-based approach to educate local area children; and the Environmental Protection Agency's brownfield grants facilitates turning over brownfields for environmental protection, green spaces, community and commercial development.

Sources

There are several sources of innovation. It can occur as a result of a focus effort by a range of different agents, by chance, or as a result of a major system failure. 

According to Peter F. Drucker, the general sources of innovations are different changes in industry structure, in market structure, in local and global demographics, in human perception, mood and meaning, in the amount of already available scientific knowledge, etc.

Original model of three phases of the process of Technological Change
 
In the simplest linear model of innovation the traditionally recognized source is manufacturer innovation. This is where an agent (person or business) innovates in order to sell the innovation. Specifically, R&D measurement is the commonly used input for innovation, in particular in the business sector, named Business Expenditure on R&D (BERD) that grew over the years on the expenses of the declining R&D invested by the public sector.

Another source of innovation, only now becoming widely recognized, is end-user innovation. This is where an agent (person or company) develops an innovation for their own (personal or in-house) use because existing products do not meet their needs. MIT economist Eric von Hippel has identified end-user innovation as, by far, the most important and critical in his classic book on the subject, The Sources of Innovation.

The robotics engineer Joseph F. Engelberger asserts that innovations require only three things:
  1. A recognized need,
  2. Competent people with relevant technology, and
  3. Financial support.
However, innovation processes usually involve: identifying customer needs, macro and meso trends, developing competences, and finding financial support.

The Kline chain-linked model of innovation places emphasis on potential market needs as drivers of the innovation process, and describes the complex and often iterative feedback loops between marketing, design, manufacturing, and R&D.

Innovation by businesses is achieved in many ways, with much attention now given to formal research and development (R&D) for "breakthrough innovations". R&D help spur on patents and other scientific innovations that leads to productive growth in such areas as industry, medicine, engineering, and government. Yet, innovations can be developed by less formal on-the-job modifications of practice, through exchange and combination of professional experience and by many other routes. Investigation of relationship between the concepts of innovation and technology transfer revealed overlap. The more radical and revolutionary innovations tend to emerge from R&D, while more incremental innovations may emerge from practice – but there are many exceptions to each of these trends.

Information technology and changing business processes and management style can produce a work climate favorable to innovation. For example, the software tool company Atlassian conducts quarterly "ShipIt Days" in which employees may work on anything related to the company's products. Google employees work on self-directed projects for 20% of their time. Both companies cite these bottom-up processes as major sources for new products and features.

An important innovation factor includes customers buying products or using services. As a result, firms may incorporate users in focus groups (user centred approach), work closely with so called lead users (lead user approach) or users might adapt their products themselves. The lead user method focuses on idea generation based on leading users to develop breakthrough innovations. U-STIR, a project to innovate Europe’s surface transportation system, employs such workshops. Regarding this user innovation, a great deal of innovation is done by those actually implementing and using technologies and products as part of their normal activities. Sometimes user-innovators may become entrepreneurs, selling their product, they may choose to trade their innovation in exchange for other innovations, or they may be adopted by their suppliers. Nowadays, they may also choose to freely reveal their innovations, using methods like open source. In such networks of innovation the users or communities of users can further develop technologies and reinvent their social meaning.

One technique for innovating a solution to an identified problem is to actually attempt an experiment with many possible solutions. This technique was famously used by Thomas Edison's laboratory to find a version of the incandescent light bulb economically viable for home use, which involved searching through thousands of possible filament designs before settling on carbonized bamboo.

This technique is sometimes used in pharmaceutical drug discovery. Thousands of chemical compounds are subjected to high-throughput screening to see if they have any activity against a target molecule which has been identified as biologically significant to a disease. Promising compounds can then be studied; modified to improve efficacy, reduce side effects, and reduce cost of manufacture; and if successful turned into treatments.

The related technique of A/B testing is often used to help optimize the design of web sites and mobile apps. This is used by major sites such as amazon.com, Facebook, Google, and Netflix. Procter & Gamble uses computer-simulated products and onlinen user panels to conduct larger numbers of experiments to guide the design, packaging, and shelf placement of consumer products. Capital One uses this technique to drive credit card marketing offers.

Goals and failures

Programs of organizational innovation are typically tightly linked to organizational goals and objectives, to the business plan, and to market competitive positioning. One driver for innovation programs in corporations is to achieve growth objectives. As Davila et al. (2006) notes, "Companies cannot grow through cost reduction and re-engineering alone... Innovation is the key element in providing aggressive top-line growth, and for increasing bottom-line results".

One survey across a large number of manufacturing and services organizations found, ranked in decreasing order of popularity, that systematic programs of organizational innovation are most frequently driven by: improved quality, creation of new markets, extension of the product range, reduced labor costs, improved production processes, reduced materials, reduced environmental damage, replacement of products/services, reduced energy consumption, conformance to regulations.

These goals vary between improvements to products, processes and services and dispel a popular myth that innovation deals mainly with new product development. Most of the goals could apply to any organization be it a manufacturing facility, marketing firm, hospital or local government. Whether innovation goals are successfully achieved or otherwise depends greatly on the environment prevailing in the firm.

Conversely, failure can develop in programs of innovations. The causes of failure have been widely researched and can vary considerably. Some causes will be external to the organization and outside its influence of control. Others will be internal and ultimately within the control of the organization. Internal causes of failure can be divided into causes associated with the cultural infrastructure and causes associated with the innovation process itself. Common causes of failure within the innovation process in most organizations can be distilled into five types: poor goal definition, poor alignment of actions to goals, poor participation in teams, poor monitoring of results, poor communication and access to information.

Diffusion

InnovationLifeCycle.jpg

Diffusion of innovation research was first started in 1903 by seminal researcher Gabriel Tarde, who first plotted the S-shaped diffusion curve. Tarde defined the innovation-decision process as a series of steps that includes:
  1. First knowledge
  2. Forming an attitude
  3. A decision to adopt or reject
  4. Implementation and use
  5. Confirmation of the decision
Once innovation occurs, innovations may be spread from the innovator to other individuals and groups. This process has been proposed that the life cycle of innovations can be described using the 's-curve' or diffusion curve. The s-curve maps growth of revenue or productivity against time. In the early stage of a particular innovation, growth is relatively slow as the new product establishes itself. At some point, customers begin to demand and the product growth increases more rapidly. New incremental innovations or changes to the product allow growth to continue. Towards the end of its lifecycle, growth slows and may even begin to decline. In the later stages, no amount of new investment in that product will yield a normal rate of return.

The s-curve derives from an assumption that new products are likely to have "product life" – i.e., a start-up phase, a rapid increase in revenue and eventual decline. In fact, the great majority of innovations never get off the bottom of the curve, and never produce normal returns. 

Innovative companies will typically be working on new innovations that will eventually replace older ones. Successive s-curves will come along to replace older ones and continue to drive growth upwards. In the figure above the first curve shows a current technology. The second shows an emerging technology that currently yields lower growth but will eventually overtake current technology and lead to even greater levels of growth. The length of life will depend on many factors.

Measures

Measuring innovation is inherently difficult as it implies commensurability so that comparisons can be made in quantitative terms. Innovation, however, is by definition novelty. Comparisons are thus often meaningless across products or service. Nevertheless, Edison et al. in their review of literature on innovation management found 232 innovation metrics. They categorized these measures along five dimensions i.e. inputs to the innovation process, output from the innovation process, effect of the innovation output, measures to access the activities in an innovation process and availability of factors that facilitate such a process.

There are two different types of measures for innovation: the organizational level and the political level.

Organizational level

The measure of innovation at the organizational level relates to individuals, team-level assessments, and private companies from the smallest to the largest company. Measure of innovation for organizations can be conducted by surveys, workshops, consultants, or internal bench marking. There is today no established general way to measure organizational innovation. Corporate measurements are generally structured around balanced scorecards which cover several aspects of innovation such as business measures related to finances, innovation process efficiency, employees' contribution and motivation, as well benefits for customers. Measured values will vary widely between businesses, covering for example new product revenue, spending in R&D, time to market, customer and employee perception & satisfaction, number of patents, additional sales resulting from past innovations.

Political level

For the political level, measures of innovation are more focused on a country or region competitive advantage through innovation. In this context, organizational capabilities can be evaluated through various evaluation frameworks, such as those of the European Foundation for Quality Management. The OECD Oslo Manual (1995) suggests standard guidelines on measuring technological product and process innovation. Some people consider the Oslo Manual complementary to the Frascati Manual from 1963. The new Oslo manual from 2005 takes a wider perspective to innovation, and includes marketing and organizational innovation. These standards are used for example in the European Community Innovation Surveys.

Other ways of measuring innovation have traditionally been expenditure, for example, investment in R&D (Research and Development) as percentage of GNP (Gross National Product). Whether this is a good measurement of innovation has been widely discussed and the Oslo Manual has incorporated some of the critique against earlier methods of measuring. The traditional methods of measuring still inform many policy decisions. The EU Lisbon Strategy has set as a goal that their average expenditure on R&D should be 3% of GDP.

Level Down of Innovation in Silicon Valley

Innovation is starting to decline due to the newly introduced immigration policies. The new immigration policies have effects on the economy because 25% of the companies were created by foreign entrepreneurs. 

Indicators

Many scholars claim that there is a great bias towards the "science and technology mode" (S&T-mode or STI-mode), while the "learning by doing, using and interacting mode" (DUI-mode) is ignored and measurements and research about it rarely done. For example, an institution may be high tech with the latest equipment, but lacks crucial doing, using and interacting tasks important for innovation.

A common industry view (unsupported by empirical evidence) is that comparative cost-effectiveness research is a form of price control which reduces returns to industry, and thus limits R&D expenditure, stifles future innovation and compromises new products access to markets. Some academics claim cost-effectiveness research is a valuable value-based measure of innovation which accords "truly significant" therapeutic advances (i.e. providing "health gain") higher prices than free market mechanisms. Such value-based pricing has been viewed as a means of indicating to industry the type of innovation that should be rewarded from the public purse.

An Australian academic developed the case that national comparative cost-effectiveness analysis systems should be viewed as measuring "health innovation" as an evidence-based policy concept for valuing innovation distinct from valuing through competitive markets, a method which requires strong anti-trust laws to be effective, on the basis that both methods of assessing pharmaceutical innovations are mentioned in annex 2C.1 of the Australia-United States Free Trade Agreement.

Indices

Several indices attempt to measure innovation and rank entities based on these measures, such as:

Rankings

Many research studies try to rank countries based on measures of innovation. Common areas of focus include: high-tech companies, manufacturing, patents, post secondary education, research and development, and research personnel. The left ranking of the top 10 countries below is based on the 2016 Bloomberg Innovation Index. However, studies may vary widely; for example the Global Innovation Index 2016 ranks Switzerland as number one wherein countries like South Korea and Japan do not even make the top ten.

Bloomberg Innovation Index 2016
Rank Country/Territory Index
1  South Korea 91.31
2  Germany 85.54
3  Sweden 85.21
4  Japan 85.07
5   Switzerland 84.96
6  Singapore 84.54
7  Finland 83.80
8  United States 82.84
9  Denmark 81.40
10  France 80.39
Global Innovation Index 2016
Rank Country/Territory Index
1   Switzerland 66.3
2  Sweden 63.6
3  United Kingdom 61.9
4  United States 61.4
5  Finland 59.9
6  Singapore 59.2
7  Ireland 59.0
8  Denmark 58.5
9  Netherlands 58.3
10  Germany 57.9

Future

In 2005 Jonathan Huebner, a physicist working at the Pentagon's Naval Air Warfare Center, argued on the basis of both U.S. patents and world technological breakthroughs, per capita, that the rate of human technological innovation peaked in 1873 and has been slowing ever since. In his article, he asked "Will the level of technology reach a maximum and then decline as in the Dark Ages?" In later comments to New Scientist magazine, Huebner clarified that while he believed that we will reach a rate of innovation in 2024 equivalent to that of the Dark Ages, he was not predicting the recurrence of the Dark Ages themselves.

John Smart criticized the claim and asserted that technological singularity researcher Ray Kurzweil and others showed a "clear trend of acceleration, not deceleration" when it came to innovations. The foundation replied to Huebner the journal his article was published in, citing Second Life and eHarmony as proof of accelerating innovation; to which Huebner replied. However, Huebner's findings were confirmed in 2010 with U.S. Patent Office data. and in a 2012 paper.

Innovation and development

The theme of innovation as a tool to disrupting patterns of poverty has gained momentum since the mid-2000s among major international development actors such as DFID, Gates Foundation's use of the Grand Challenge funding model, and USAID's Global Development Lab. Networks have been established to support innovation in development, such as D-Lab at MIT. Investment funds have been established to identify and catalyze innovations in developing countries, such as DFID's Global Innovation Fund, Human Development Innovation Fund, and (in partnership with USAID) the Global Development Innovation Ventures.

Government policies

Given the noticeable effects on efficiency, quality of life, and productive growth, innovation is a key factor in society and economy. Consequently, policymakers have long worked to develop environments that will foster innovation and its resulting positive benefits, from funding Research and Development to supporting regulatory change, funding the development of innovation clusters, and using public purchasing and standardization to 'pull' innovation through.

For instance, experts are advocating that the U.S. federal government launch a National Infrastructure Foundation, a nimble, collaborative strategic intervention organization that will house innovations programs from fragmented silos under one entity, inform federal officials on innovation performance metrics, strengthen industry-university partnerships, and support innovation economic development initiatives, especially to strengthen regional clusters. Because clusters are the geographic incubators of innovative products and processes, a cluster development grant program would also be targeted for implementation. By focusing on innovating in such areas as precision manufacturing, information technology, and clean energy, other areas of national concern would be tackled including government debt, carbon footprint, and oil dependence. The U.S. Economic Development Administration understand this reality in their continued Regional Innovation Clusters initiative. In addition, federal grants in R&D, a crucial driver of innovation and productive growth, should be expanded to levels similar to Japan, Finland, South Korea, and Switzerland in order to stay globally competitive. Also, such grants should be better procured to metropolitan areas, the essential engines of the American economy.

Many countries recognize the importance of research and development as well as innovation including Japan's Ministry of Education, Culture, Sports, Science and Technology (MEXT); Germany's Federal Ministry of Education and Research; and the Ministry of Science and Technology in the People's Republic of China. Furthermore, Russia's innovation program is the Medvedev modernisation programme which aims at creating a diversified economy based on high technology and innovation. Also, the Government of Western Australia has established a number of innovation incentives for government departments. Landgate was the first Western Australian government agency to establish its Innovation Program.

Regions have taken a more proactive role in supporting innovation. Many regional governments are setting up regional innovation agency to strengthen regional innovation capabilities. In Medellin, Colombia, the municipality of Medellin created in 2009 Ruta N to transform the city into a knowledge city.

Butane

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