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Diffusion Of Innovations

Diffusion of innovations

The study of the diffusion of innovation is the study of how, why, and at what rate new ideas spread through cultures.

Theories of Innovation Diffusion

French sociologist Gabriel Tarde originally claimed that sociology was based on small psychological interactions among individuals, especially imitation and innovation. Diffusion of innovations theory was formalized by Everett Rogers in a 1962 book called Diffusion of Innovations. Rogers stated that adopters of any new innovation or idea could be categorized as innovators (2.5%), early adopters (13.5%), early majority (34%), late majority (34%) and laggards (16%), based on a bell curve. Each adopter's willingness and ability to adopt an innovation would depend on their awareness, interest, evaluation, trial, and adoption. Some of the characteristics of each category of adopter include:
- innovators - venturesome, educated, multiple info sources, greater propensity to take risk
- early adopters - social leaders, popular, educated
- early majority - deliberate, many informal social contacts
- late majority - skeptical, traditional, lower socio-economic status
- laggards - neighbours and friends are main info sources, fear of debt Rogers showed these innovations would spread through society in an S curve, as the early adopters select the technology first, followed by the majority, until a technology or innovation is common.

The S-Curve and technology adoption

S curve The speed of technology adoption is determined by two characteristics p, which is the speed at which adoption takes off, and q, the speed at which later growth occurs. A cheaper technology might have a higher p, for example, taking off more quickly, while a technology that has network effects (like a fax machine, where the value of the item increases as others get it) may have a higher q. As can be seen in the technology adoption chart, as time has gone on, both p and q seem to be increasing.

Caveats and Criticisms

A number of other phenomena can influence innovation adoption rates. One of these is that customers often adapt technology to their own needs, so the innovation may actually change in nature from the early adopters to the majority of users. A second is that disruptive technologies may radically change the diffusion patterns for established technology by starting a different competing S-curve. Finally, path dependence may lock certain technologies in place, as in the QWERTY keyboard.

External link

- [http://www.dallasfed.org/fed/annual/1999p/ar96.pdf Federal Reserve of Dallas 1996 Annual Report on Innovation]
- [http://www.teachers.ash.org.au/lindy/pencil/pencil.htm The Pencil Metaphor on diffusion of innovation particularly ICT in education] Category:Innovation Category:Diffusion Category:Marketing Category:Product management Category:Anthropology Category:Memetics

Imitation

Imitation is an advanced animal behaviour whereby an individual observes another's behaviour and replicates it itself. It has been argued by Susan Blackmore in The Meme Machine, that imitation is what makes humans unique among animals. Imitation might have been selected as fit by evolution because those who were good at it had a wider arsenal of learned cultural behavior at their disposal, such as tool making or even language. In anthropology, diffusion theories explain why cultures imitate the ideas or practices of other cultures. Some theories hold that all cultures imitate ideas from one or a few original cultures, the Adam of the Bible, or several cultural circles that overlap. Evolutionary diffusion theory holds that cultures are influenced by one another, but that similar ideas can be developed in isolation. In mid-20th century, social scientists began to study how and why people imitate ideas. Everett Rogers pioneered diffusion of innovations studies, using research to prove factors in adoption and profiles of adopters of ideas. Recent work in neuroscience has begun to reveal the mechanisms of imitation in the human brain. It seems that there is a system of mirror neurons which are active both when you see another person act and when you do the same thing yourself, and these may allow humans to learn by imitation. Category:Psychology

Everett Rogers

Everett M. Rogers (1931 in Carroll, Iowa - Albuquerque, New Mexico, 21 October 2004), communications scholar, pioneer of diffusion of innovations theory, writer, and teacher. He is best known for his 'diffusion of innovations' theory and introducing the term 'early adopter'.

Early life

He grew up on a farm in Iowa and had no plans to attend university until a school teacher drove him and some classmates to Ames to visit Iowa State University. Rogers decided to pursue a degree in agriculture there. He then served in the Korean War for two years. He returned to Iowa State University to earn a PhD in sociology and statistics in 1957.

Academic research

He published 30 books, translated into 15 languages, and more than 500 articles. In a 47-year academic career, Rogers taught at Ohio State University, National University of Colombia, Michigan State University, University of Michigan, Stanford University, Universite de Paris, University of Southern California, and the University of New Mexico. In total, he taught at six US universities and six universities in Europe, the Far East, and Latin America. He taught or conducted research in Colombia, Brazil, Ecuador, France, Germany, India, Korea, Mexico, Nigeria, Tanzania, and Thailand.

Diffusion of Innovations

Rogers achieved academic fame for his Diffusion of innovations theory; his book, Diffusion of Innovations, is now in its fifth edition. He proved that adopters of any new innovation or idea could be categorized as innovators (2.5%), early adopters (13.5%), early majority (34%), late majority (34%) and laggards (16%), based on Bell curve mathematic division. Each adopter's willingness and ability to adopt an innovation would depend on their awareness, interest, evaluation, trial, and adoption. People could fall into different categories for different innovations -- a farmer might be an early adopter of hybrid corn, but a late majority adopter of VCRs. Rogers showed these innovations would spread through society in an S curve. His research and work became widely accepted in communications and technology adoption studies, and also found its way into a variety of other social science studies. Geoffrey Moore's Crossing the Chasm drew from Rogers in explaining how and why technology companies succeed. Rogers was also able to relate his communications research to practical health problems, including hygiene, family planning, cancer prevention, and drunk driving.

Later life

In 1995, Rogers moved to the University of New Mexico, having become fond of Albuquerque while stationed at an airbase during the Korean War. He helped UNM launch a doctoral program in communication. Rogers suffered from kidney disease and retired from the University of New Mexico in the summer of 2004. He died just a few months later, survived by his wife, Corinne Shefner-Rogers, and two sons: David Rogers and Everett King.

External references

- [http://www.unm.edu/~market/cgi-bin/archives/000359.html#more Obituary from University of New Mexico]
- [http://www.technobility.com/docs/article032.htm The Danger of the "Early Adopter" Myth] Rogers, Everett Rogers Rogers, Everett Rogers Rogers, Everett Rogers, Everett

Disruptive technology

A disruptive technology is a new technological innovation, product, or service that eventually overturns the existing dominant technology in the market, despite the fact that the disruptive technology is both radically different from the leading technology and that it often initially performs worse than the leading technology according to existing measures of performance. A disruptive technology comes to dominate an existing market by either filling a role in a new market that the older technology could not fill (as more expensive, lower capacity but smaller-sized hard disks did for newly developed notebook computers in the 1980s) or by successively moving up-market through performance improvements until finally displacing the market incumbents (as digital photography has come to replace film photography). By contrast, sustaining technology refers to the successive incremental improvements to performance that market incumbents incorporate into their existing product. The term disruptive technology was coined by Clayton M. Christensen and described in his 1997 book The Innovator's Dilemma. In his sequel, The Innovator's Solution, Christensen replaced the term with the term disruptive innovation because he recognized that few technologies are intrinsically disruptive or sustaining in character. It is strategy that creates the disruptive impact.

The theory

Christensen distinguishes between low-end disruption which targets customers who do not need the full performance of the high end of the market and new-market disruption which targets customers who could previously not be served profitably by the incumbent. "Low-end disruption" occurs when the rate at which products improve exceeds the rate at which customers can learn and adopt the new performance. Therefore, at some point the performance of the product overshoots the needs of certain customer segments. At this point, a disruptive technology may enter the market and provide a product which has lower performance than the incumbent but which exceeds the requirements of certain segments, thereby gaining a foothold in the market. The Innovator's Solution In low-end disruption, the disruptive company will naturally aim to improve its margin (from low commodity level) and therefore will innovate to capture the next level of customer requirements. The incumbent will not want to engage in a price war with a simpler product with lower production costs and will move up-market and focus on its more attractive customers. After a number of iterations, the incumbent has been squeezed into successively smaller markets and when finally the disruptive technology meets the demands of its last segment the incumbent technology disappears. "New market disruption" occurs when a product that is inferior by most measures of performance fits a new or emerging market segment. In the disk drive industry, for example, new generations of smaller-sized disk drives were both more expensive and had less capacity than existing, larger-sized drives. Since size was not an important factor for the early computer market, these new drives seemed worse in every way. With the development of the minicomputer (or afterwards, the desktop computer, the notebook, and the personal music player), size became an important dimension, and these new drives quickly dominated the market. Not all disruptive technologies are of lower performance. There are a several examples where the disruptive technology outperforms the existing technology but is not adapted by existing majors in the market. These occur in industries with a high capitalization sunk into the older technology. To update, an existing player not only must invest in new technology but also must replace (and perhaps dispose of at high cost) the older infrastructure. It may simply be most cost effective for the existing player to "milk" the current investment during its decline - mostly by insufficient maintenance and lack of progressive improvement to maintain the long term utility of the existing facilities. A new player is not faced with such a balancing act. Some examples of high-performance disruption:
- The rise of containerization and the success of the Port of Oakland, California, while the port of San Francisco neglected modernization - perhaps wisely due to its inconvenient location at the end of a peninsula not oriented with the prevailing freight traffic. Rather than attempt to compete in the oceanic freight terminal business, the city's resources were directed elsewhere, primarily toward becoming the leading financial center on the west coast through the encouragement of the construction of high rise buildings for office space.
- "Mini mill" scrap feed steel product production facilities in the United States using integrated vertical casting methods feeding rolling mills in a single continuous process to produce specialty products such as reinforcing bars for concrete. This left the existing large steel producers with only the lower value commodity production which could not compete with lower cost production worldwide - largely due to the lower labor costs offshore.
- The deployment of utility-scale wind turbine "farms" to generate electricity. In the early 2000's, wind power became the lowest-cost form of new energy generation on earth, beating such traditional electricity stalwarts as coal- and natural gas-fired power plants on price. The cost advantages quickly translated to widespread adoption in Europe; by the year 2005, countries such as Denmark, Spain and Germany generated close to 20 percent of their national energy demand with wind turbines. But in America, political resistance - mostly from politically powerful incumbents in the coal industry - slowed the widespread adoption of wind power.

Examples of disruptive technologies

Not all technologies promoted as disruptive technologies have actually prospered as well as their proponents had hoped. However, some of these technologies have only been around for a few years, and their ultimate fate has not yet been determined. Unresolved examples of technologies promoted as 'disruptive technologies'
- Music downloads and file sharing vs. compact discs
- ebooks vs. paper books
- e-commerce vs. physical shops
- Open-source software vs. proprietary software (for example Linux versus Microsoft Windows, although Linux has already largely displaced proprietary Unix)
- Internet Video on Demand and IPTV vs. Advertising supported broadcast and cable television
- VoIP (and VoIP over 802.11) vs. traditional telephone and mobile phone service.
- portable mp3-players vs. the portable cassette player

Business implications

Disruptive technologies are not disruptive to customers, and often take a long time before they are significantly disruptive to other manufacturers, so they are often difficult to recognize. Indeed, as Christensen points out and studies have shown, it is often entirely rational for incumbent companies to ignore disruptive technologies, since they compare so badly to existing approaches, and the initial markets for a disruptive technology are often very small compared to the main existing market for the technology. Even if a disruptive technology is recognized, existing businesses are often reluctant to take advantage of it, since it would involve competing with their existing (and more profitable) technological approach. Christensen recommends that existing firms watch for these technologies, invest in small firms that might produce them, and continue to push technological demands in their core market so that performance stays above what disruptive technologies can achieve.

External links

- [http://c2.com/cgi/wiki?DisruptiveTechnology Disruptive Technology at c2.com]
- [http://economist.com/displayStory.cfm?Story_id=3307440 Disruptive Technology at The Economist: The blood of incumbents]
- [http://myst-technology.com/mysmartchannels/public/item/12485 RSS: Disruptive Technology Hiding in Plain Sight ]
- [http://www.pcmag.com/article2/0,1759,1628049,00.asp The Myth of Disruptive Technologies]. Note that Dvorak's definition of disruptive technology does not necessarily match the standard one described above. He complains about the overuse of the term and goes as far as claiming there are no disruptive technologies.
- [http://www2.warwick.ac.uk/fac/soc/law/elj/jilt/2001_1/mountain/] Could New Technologies Cause Great Law Firms to Fail?
- [http://technologybusiness.blogspot.com/ The Business of Technology - how disruptive technologies are changing the business landscape]

Books and papers

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- Tushman, M.L. & Anderson, P. (1986). Technological Discontinuities and Organizational Environments. Administrative Science Quarterly 31: 439-465. Category:Types of technology Category:Marketing Category:Product management category:Electronic commerce

Crossing the Chasm

Crossing the Chasm is a marketing book by Geoffrey A. Moore that focuses on the specifics of marketing high tech products. It was first published in 1991. Moore uses the diffusion of innovations theory from Everett Rogers, but argued that there is a chasm between the early adopters of the product (the technology enthusiasts and visionaries) and the early majority (the pragmatists). Moore argues that this is because visionaries and pragmatists have very different expectations. Moore attempts to explore those differences and builds from there to suggest techniques to successfully cross the "chasm", including choosing a target market, understanding the whole product concept, positioning the product, building a marketing strategy, choosing the most appropriate distribution channel and pricing. Moore's approach has been criticized from a strategic perspective because it deals with adoption and not profit. It is possible that in many cases "crossing the chasm" may not lead to profitability. Similarly, Moore places a large emphasis on being the first to cross the chasm, but there is substantial evidence that being a later mover in a given technology market may also be advantagous. Finally, Moore's theories may not be applicable in many non-technology markets. In 2002, 10 years after the first publication, more than 300,000 copies had been sold. Crossing the Chasm is available in several prints, one is ISBN 0060517123. pricing

Diffusion (business)

Diffusion is the process by which a new idea or new product is accepted by the market. The rate of diffusion is the speed that the new idea spreads from one consumer to the next. Adoption is similar to diffusion except that it deals with the psychological processes an individual goes through, rather than an aggregate market process.

Models of diffusion

There are several theories that proport to explain the mechanics of diffusion:
- 1) The two-step hypothesis - information and acceptance flows, via the media, first to opinion leaders, then to the general population
- 2) The trickle-down theory - products tend to be expensive at first, and therefore only accessible to the wealthy social strata - in time they become less expense and are diffussed to lower and lower strata
- 3) The Everett Rogers Diffusion of innovations theory - for any given product category, there are five categories of product adopters:
- innovators
- venturesome, educated, multiple info sources
- early adopters
- social leaders, popular, educated
- early majority
- deliberate, many informal social contacts
- late majority
- skeptical, traditional, lower socio-economic status
- laggards
- neighbours and friends are main info sources, fear of debt
- 4) Crossing the Chasm model developed by G. Moore - This is basically a modification of Everett Rogers' theory applied to technology markets and with a chasm added. According to Moore, the marketer should focus on one group of customers at a time, using each group as a base for marketing to the next group. The most difficult step is making the transition between visionaries (early adopters) and pragmatists (early majority). This is the chasm that he refers to. If successful a firm can create a bandwagon effect in which the momentum builds and the product becomes a defacto standard.
- 5) Technology driven models - These are particularly relevant to software diffusion. The rate of acceptance of technology is determined by factors such as ease of use and usefulness.

The rate of diffusion

Technology driven models According to Everett M. Rogers, the rate of diffusion is influenced by:
- the product's perceived advantage or benefit
- riskiness of purchase
- ease of product use - complexity of the product
- immediacy of benefits
- observability
- trialability
- price
- extent of behavioural changes required
- return on investment in the case of industrial products

Diffusion rate models

There are several types of diffusion rate models:
- 1) Penetration models - use test market data to develop acceptance equations of expected sales volume as a function of time - 3 examples of penetration models are:
- Bass trial only model
- Bass declining trial model
- Fourt and Woodlock model
- 2) Trial/Repeat models - number of repeat buyers is a function of the number of trial buyers
- 3) Deterministic models - assess number of buyers at various states of acceptance - later states are determined from calculations to previous states
- 4) Stochastic models - recognize that many elements of the diffusion process are unknown but explicitly incorporate probabilistic terms

References

- Bass, F. M. (1969). "A new product growth model for consumer durables". Management Science, 15, 215-227.
- Bass, F. M. (1986). "The adoption of a marketing model: Comments and observations". In V. Mahajan & Y. Wind (Eds.), Innovation Diffusion Models of New Product Acceptance. Cambridge, Mass.: Ballinger. Category:Marketing Category:Product management category:Management

Meme

The term meme ( in the IPA; rhymes with "dream"; from the Greek word mimema for 'something imitated') first came into popular use with the publication of the book The Selfish Gene by Richard Dawkins in 1976. The conceptual framework is borrowed from genes -- the unit of biological transmission. By analogy with genetics, a meme is passed from generation to generation, with occasional "mutations," but is passed via family and cultural traditions or training rather than sexual reproduction. Unlike genes, memes can typically be passed horizontally as well. Memes often occur in groups called "meme complexes," such as religious or political doctrine. Though Dawkins defined the meme as "a unit of cultural transmission, or a unit of imitation," memeticists vary in their definitions of meme. The lack of a consistent, rigorous and precise definition of a meme remains one of the principal criticisms leveled at memetics, the study of memes. The notion of a unit of social evolution, and a similar term (from Greek mneme, 'memory'), first appeared in 1904 in a work by the German evolutionary biologist Richard Semon: Die Mnemische Empfindungen in ihren Beziehungen zu den Originalenempfindungen, translated into English in 1921 as The Mneme. Different definitions of meme generally agree, very roughly, that a meme consists of some sort of a self-propagating unit of cultural evolution having a resemblance to the gene (the unit of genetics). Dawkins introduced the term after writing that evolution depended not on the particular chemical basis of genetics, but only on the existence of a self-replicating unit of transmission — in the case of biological evolution, the gene. For Dawkins, the meme exemplifies another self-replicating unit, and most importantly, one which he thought would prove useful in explaining human behavior and cultural evolution. In casual use, the term meme often refers to any piece of information passed from one mind to another. In this sense, it relates closely to the academic study of folklore, in that folkloristics deals with the informal communication of cultural information. This usage more closely resembles the analogy of "language as a virus" than Dawkins' analogy of memes as replicating units. This definition has come into popular use on the Internet to refer to phenomena such as Obey Giant, "All your base are belong to us", Blogebrity and Icy Hot Stuntaz.

Basic introduction

Though memeticists do not generally agree on a specific definition, one can roughly define 'meme' as any piece of information transferable from one mind to another. Examples might include thoughts, ideas, theories, practices, habits, songs, dances and moods. Memes supposedly have, as their fundamental property, evolution via natural selection in a way very similar to Charles Darwin's ideas concerning biological evolution, on the premise that replication, mutation, survival and competition influence them. For example, while one idea may become extinct, others will survive, spread and mutate — for better or worse — through modification. Note an important fact, however: not only the memes most beneficial to their hosts will necessarily survive; rather, memes supposedly spread best by functioning as the most effective replicators, which allows for the possibility that successful memes might prove detrimental to their hosts.

History of the concept of the meme

The concept of ideas that spread according to genetic rules predates the coining by Richard Dawkins in The Selfish Gene; for example William S. Burroughs asserted that "language is a virus." John Laurent in The Journal of Memetics has suggested that the term 'meme' itself may have derived from the work of the little-known German biologist Richard Semon. In 1904 Semon published Die Mneme (published in English as The Mneme in 1924). His book discussed the cultural transmission of experiences with insights parallel to those of Dawkins. Laurent found the use of the term mneme in The Soul of the White Ant (1927) by Maurice Maeterlinck and highlights its parallels to Dawkins's concept: :Maeterlinck, in discussing theories which attempt to explain 'memory' in termites as well as the other social insects (ants, bees etc.), uses the phrase "engrammata upon the individual mneme" (Maeterlinck, 1927, p.198). Webster's Collegiate dictionary defines an engram as "a memory trace; specif.: a protoplasmic change in neural tissue hypothesized to account for persistence of memory". Note that Maeterlinck explains that he obtained his phrase from the "German philosopher" Richard Semon. [http://jom-emit.cfpm.org/1999/vol3/laurent_j.html] Laurent suggests that the etymological roots of the term 'meme' may come from mimneskesthai, the Greek verb for 'to remember, to keep in mind' rather than from Dawkins' root of mimeisthai, "to imitate." Everett Rogers pioneered the "Diffusion of innovations" theory (formalised in 1962) which explains how and why people adopt new ideas. Rogers reflected some of the influence of Gabriel Tarde, who set out "laws of imitation" in his book of 1890 that explained how people decided whether to imitate behavior. Francis Heylighen of the Center Leo Apostel for Interdisciplinary Studies has come up with what he called memetic selection criteria. These criteria opened the way to a specialized field of applied memetics to find out if these selection criteria could stand the test of quantitative analyses. In 2003 Klaas Chielens carried out these tests in a Masters thesis project on the testability of the selection criteria.

"Ideas have a life of their own"

The old saying "Ideas have a life of their own" clearly encapsulates the "meme about memes". Keith Henson has traced this quote back to 1910 where an unknown interviewer of Gilbert Keith Chesterton used it - apparently as an old saying at that time. (Reported in alt.quotations [http://groups.google.ca/group/alt.quotations/msg/679859a365f8ad0d?hl=en&])

Memetics

Memetics, the study of memes, remains a controversial field among many scientists and skeptics. Memetics originated when Richard Dawkins reduced the process of biological genetic evolution to its most fundamental unit: the replicator (or gene). Dawkins, in a search for parallels and other things that he might classify as replicators, suggested that the information and ideas in brains — culture, for example — could function as replicators as well. Computer software may represent another form of replicator with which evolution may eventually build grand things, whether socially as in the open source movement, or through the use of evolutionary algorithms. Memetics takes concepts from the theory of evolution (especially population genetics) and applies them to human culture. Memetics also uses mathematical models to try to explain many very controversial subjects such as religion and political systems. Principal criticisms of memetics include the claim that memetics ignores established advances in the fields (such as sociology, cognitive psychology, social psychology, etc.) most relevant to the claims and methodologies of memetics. The term memetic association refers to the idea that memes herd. For example, a meme for blue jeans includes memes for trouser-flies, riveted clothing, blue dye, cotton clothing, belt-loops and double-sewn seams. In this way, groups of memes can operate symbiotically (to use a biological analogy) in the sense that they act for their mutual benefit/survival. The phrase memetic drift (formed by analogy to genetic drift) refers to the process of a meme changing as it replicates between one person to another. Memetic drift increases when meme transmission occurs in an awkward way. Very few memes show strong memetic inertia (the characteristic of a meme to manifest in the same way and to have the same impact regardless of who receives or transmits the meme). Memetic inertia increases when the meme transfers along with mnemonic devices, such as a rhyme, to preserve the memory of the meme prior to its transmission. See Murphy's law for one example of memetic drift. Memeticists generate much memetic terminology by prepending 'mem(e)-' to an existing, usually biological, term or by putting 'mem(e)' in place of 'gen(e)' in various terms. Examples include: meme pool, memotype, memetic engineer, meme-complex.

Memetic engineering

Memetic engineering consists of the process of developing memes, through meme-splicing and memetic synthesis, with the intent of altering the behavior of others. It consists of the process of creating and developing theories or ideologies based on an analytical study of societies, their ways of thinking and the evolution of the minds that comprise them. Memes in themselves appear morally neutral; not necessarily good or bad. However the application of memes can have moral implications, such as controlling the thinking of others in catastrophic ways. History furnishes many examples, such as the genocide that took place in Rwanda involving the Hutus and the Tutsis. Racism provides another example of a common meme: an ideology that has come to separate people. Once introduced into a culture, memes evolve and spread through society, sometimes becoming both harmful and attractive so that they spread like a virus. (Ref.: 1994 G. Burchett)

Memetic evolution

Memetic evolution, like genetic evolution, cannot happen without mutation. Mutation produces the essential variations, whereupon those variations that prove "better" at replication will become more common and therefore have a greater chance at replication again. However, unlike genetic evolution, memetic evolution seems to have no separate underlying genotype. If, for example, a mouse loses its tail or a bodybuilder lifts weights, the genetic information in their genotype, stored on their DNA, will remain unchanged, and when that genetic information replicates it will not pass on these acquired superficial characteristics. In memetics the phenotype apparently serves as the genotype, and therefore changes in the phenotype will accumulate and get passed on as they replicate. One could therefore think that memetics behaves in a Lamarckian manner, highlighting the apparent irony of a great deal of effort and debate devoted to proving that (genetic) evolution does not function in a Lamarckian manner. However, one can conceivably think of the set of memes in a person's mind as the genotype-analogue, with the phenotype as the actual deeds performed by that person. But gene mutations don't usually affect phenotypes directly and immediately, while meme mutations do. At any rate a change of phenotype (= different deeds) doesn't necessarily cause a mutation of memotype. In this sense memetic evolution is a sort of Darwinian evolution, not a Lamarckian one. Language most likely evolved by means of mutation from just a handful of primitive syllables (the original language phenotypes) into the modern wide array of dialects. Further mutations of language include writing, Braille, sign language, etc. Even the oft-cited "All your base are belong to us" meme produced variations such as "all your vote are belong to us". Other lines in the originating videogame's dialogue, such as "Someone set up us the bomb", have also replicated on the Internet, but with less success. Researchers may employ search engines as an imperfect tool in measuring the popularity of various memetic phrases.

Do cultures evolve?

Dawkins observed that cultures can evolve in much the same way that populations of organisms evolve. Various ideas pass from one generation to the next; such ideas may either enhance or detract from the survival of the people who obtain those ideas. This process affects which of those ideas will survive for passing on to future generations. For example, a certain culture may have unique designs and methods of tool-making that another culture may not have; therefore, the culture with the more effective methods may prosper more than the other culture, ceteris paribus. This leads to a higher proportion of the overall population adopting the more effective methods as time passes. Each tool design thus acts somewhat similarly to a biological gene in that some populations have it and others do not, and the meme's function directly affects the presence of the design in future generations.

Propagation of memes

Memes have as an important characteristic their propagation through imitation, a concept introduced by the French sociologist Gabriel Tarde. Imitation means to copy the observed behaviour of another individual. Typically imitators copy behaviour from observing other humans, but they may also copy from an inanimate source, such as from a book or from a musical score. When imitation first evolved in the animal ancestors of humans, it proved itself a valuable skill for learning, which increased an individual's ability to reproduce genetically. Some have speculated that sexual selection of the best imitators further drove a genetic increase in the ability of brains to imitate well. Memes propagate by imitation, direct or indirect, of one individual by another, and thus depend on brains sufficiently powerful to assess the key aspects of the imitated behavior (what to copy and why) as well as its potential benefits. Researchers have observed memetic copying in just a few species on Earth, including hominids, dolphins and birds which learn how to sing by imitating their parents. One could argue however that there exist examples of less complex memes in other species — for example, scientists have artificially induced imitative behavior in cephalopods and in rats. Zoopharmacognosy (the use of drugs by animals) may conceivably exemplify an animal meme. Observers have noticed that some species ingest non-foods, such as toxic plants or charcoal, to ward off parasitic infestation or poisoning, respectively (for an accessible description of several examples, see ). Both genes and memes can survive much longer than the individual organisms that carry them. A successful gene, such as a gene for powerful teeth in a population of lions, can remain unchanged in the gene pool for hundreds of thousands, or even millions of years. A successful meme can propagate itself from one individual to another long after the original form of the meme perished with its carrier. Interestingly, memetics suggests that memes have the potential for a much more lasting effect than genes. Most organisms pass their genes on to their offspring sexually, but with every generation the genetic contribution of a given ancestor halves - so that a person only has 1/4 of their grandfather's personal genes, for example (of course most genes are inherited in common). Susan Blackmore has poignantly evaluated the legacy of Socrates. Since the 5th century BC Socrates' genes have become thoroughly diluted (dispersed); however, his memes still have a profound effect on modern thought and on contemporary philosophical discourse.

Biological analogies

In much the same way that the selfish gene concept offers a fruitful way of understanding and reasoning about aspects of biological evolution, the meme concept allegedly can conceivably assist in the better understanding of some otherwise puzzling aspects of human culture (and learned behaviors of other animals as well). However, if one cannot test for "better" empirically, the question will remain whether or not the meme concept counts as a valid scientific theory. Memetics thus remains a science in its infancy, a protoscience (although critics sometimes label it a pseudoscience).

Thoughts as discrete units

Although memeticists speak of memes as discrete units, this need not imply that thoughts somehow become quantized or that "atomic" ideas exist which one cannot break down into smaller pieces. The meme as a unit simply provides a convenient way of discussing "a piece of thought copied from person to person", regardless of whether that thought contains others inside it, or forms part of a larger meme. A meme could consist of a single newly-coined word, or a meme could consist of the entire speech in which that word was first uttered. The "word itself" meme will most likely survive many more generations (after transmission alone or in other sentences) than the "speech in its entirety" meme will survive (due to errors of memory, abridged versions, etc.) This forms an analogy to the idea of a gene as a self-replicating set of code. The gene in this definition does not consist of a set number of nucleotides, but simply a collection of nucleotides (possibly in many different locations on the DNA) that replicate together and code for some set of behaviors or body parts.

Evolution of memes

Evolution requires not only inheritance and natural selection but also mutation, and memes also exhibit this property. Ideas may undergo changes in transmission which accumulate over time. Generations of hosts pass on these changes in the "phenotype" (the information in brains or retention systems). In other words, unlike genetic evolution, memetic evolution can show both Darwinian and Lamarckian traits. For example, folk tales and myths often become embellished in the retelling to make them more memorable or more appropriate and therefore more impressed listeners have a greater likelihood of retelling them, complete with embellishments. More modern examples appear in the various urban legends and hoaxes — such as the Goodtimes virus warning — that circulate on the Internet. A behavior, idea or usage distinguishes itself as a meme when some property of itself influences the likelihood of adoption. For example, tool designs affect the efficacy of a tool independently of the habits of the different people using them. Legends and myths often teach a moral lesson or explain a mystery, so they are more likely to be retold to serve different speakers' purposes than other similar stories without those elements.

Evolutionary forces affecting memes

A gene or a meme's success is determined only by the number of copies (and where the copies reside) that are extant. There is a strong (but not complete) correlation between genes that do well and genes that have a positive effect on the organism which contains those genes. And if we restrict attention to memes normally interpreted as statements of fact, then a correlation emerges between those memes that do well and those that reflect reality. However, some genes and memes do survive which owe their success to other factors. Similarly, a correlation exists between successful memes of a technological/ economic nature and those that help the economy. A gene's success in a body may stem from its attempt to bypass the normal sexual lottery by making itself present in more than 50% of zygotes in an organism. Some genes find other ways of having themselves transmitted between cells. Hence multiple factors influence the evolution of genes — not just the success of the species as a whole. Similarly the evolutionary pressures on memes include much more than just truth and economic success. Evolutionary pressures may include the following: #Experience: If a meme does not correlate with an individual's experience, then that individual has a reduced likelihood of remembering that meme #Happiness: If a meme makes people feel happier then they have a greater likelihood of remembering it #Fear: If a meme constitutes a threat then people may become frightened into believing it. The memes "if you do this you will burn in hell" and "do this and you will go to heaven" provide common examples. On the other hand, examples of memes which pass on the fear of a threat, of the likelihood or effectiveness of a threat, that "something will happen if you do such and such a thing", have a high likelihood of success, and may therefore replicate and remain in the meme pool. They may serve in this way for the survival of a thought, a theme or a philosophy within a community. #Censorship: If an organisation destroys any retention systems containing a particular meme or otherwise controls the usage of said meme, then that meme suffers a selective disadvantage. #Economics: If people or organisations with economic influence exhibit a particular meme, then the meme has a greater likelihood of benefitting from a greater audience. If a meme tends to increase the riches of an individual holding it, then that meme may spread because of imitation. Such memes might include "Hard work is good" and "Put number one first". #Distinction: If the meme enables hearers to recognize and respect tellers (as leaders, intelligent people, insightful, etc.), then the meme has a greater chance of spreading. The erstwhile receivers will want to become themselves tellers of the same meme (or an evolved/mutated version). Thus élite knowledge can provide a promotion to élite status. Memes, like genes, do not purposely do or want anything — they either get replicated or not. Some meme systems have negative effects on the host or on their host society, but we generally have a symbiotic relationship with these abstract entities. Memes don't mutate in an exclusively passive way. The brain inhabited by a meme system performs a sort of active modification of a meme. One could draw an analogy with a cell's error-correction systems, but they clearly function quite differently. In essence, people create and modify memes almost continuously. One can modify, manipulate, and create meme systems in thought, for instance through internal dialogue. As soon as one opens one's mouth and says something (or does something) that one has not copied (but that others can copy), one has unleashed a novel meme. Thus, one could conclude that we all perform the role of a memetic engineer to some degree (even if not consciously). This seems especially evident in modern society, more notably in the scientific and philosophical realms and in the entertainment industry. It has become standard practice for scientists and philosophers alike to assemble memetic systems and to question their philosophical and empirical integrity. On perceiving a flaw, one may seek philosophical (thought experiments/logic/analysis) or empirical (experimental/observational/[questionably] mathematical) resolution. This happens in large part due to the influence of some of the more "modern" philosophers of the past. Over the last few hundred (or thousand) years, a "philosophy" or paradigm has evolved and developed which benefits the societies in which many embrace it. That philosophy includes the ethical, moral, and scientific obligation to take nothing for granted and always to question any new information one perceives. People following this tradition have transformed the memetic base of modern science and philosophy. These people include (just to name a scant few) Socrates, Aristotle, Plato, Galileo, Newton, Darwin, Albert Einstein, Karl Marx, Benjamin Franklin and Karl Popper. Science accepts nothing as true unless empirical evidence and observation suggests such “truth” strongly and consistently. This entire procedure adheres to a meme system that has evolved to the point of rejecting almost any absolute truth. This meme system now includes such novel analytical paradigms as the scientific method and Dewey's Decision-Making model (among many other meme-based systems) to help distinguish useful (or truthful) meme systems from "bad" ones. Essentially, people modify and fabricate memes consciously, even intentionally (though some argue that the intention comes from the memes). This would help to explain how rapidly, extensively and usefully memetic evolution has functioned in and for culture. People apply many ever-evolving meme-based systems of analysis and error correction to all information flowing in and out. Just as genetic material has developed gene-based error-correction models, memetic systems have found it advantageous to associate with meme-based error-correction models. The entire process could appear as meme-based systemic complexes taking advantage (like a virus) of an extensive computational system (the human brain in this case), programming it to produce and modify memes, and thus to modify and expand the memotypic soup which largely dictates our thoughts and actions (and of course to build very useful - but still likely erroneous - memeplexes). In early social development, people and memes influence each other just as with developed individuals. People later may become aware of this influence and begin to consciously filter what influence the meme systems have on them as well as what influence they have on meme systems (likely in response to memeplex programming). In later, possibly somewhat esoteric stages, people become more acutely aware of the meme systems flooding their existence, and many people have begun to reach a more complete comprehension of these memes through a novel memeplex which evolves to explain its own kind (though one does not necessarily need to know of meme theory to realize that the situation exists). Eventually, many see the potential to fabricate or modify meme systems consciously to specific ends, based on conscious plans and logical foresight (all aided by interacting memeplexes which arguably constitute thought), such that the memesphere becomes a cluttered canvas of interconnected variables which everyone influences. Enlightened, the memeticist (or the meme artist) manifests in society to expand symbolic culture at an ever-accelerating rate. Many of the world's most successful religions (and arguably all religions) have become subject to conscious memetic modification over time. Judaism, Christianity, Mormonism and Islam (and their descendents) — just to name a few in that family — all arose (presumably) through variation, modification and memetic recombination from a common one or few ancestors. (Zoroastrianism appears to have functioned as an important and widely-shared memetic ancestor, contributing to Judaism, Christianity, Islam and their many derivative religions.) Those ancestors presumably resulted from extensive memetic engineering themselves, possibly more impressive than the modification of their descendants (as early religious meme systems had less to work with). Cultural materialism holds that the evolutionary pressures of economy and ecology explain many aspects of human culture. For example, the food taboos sometimes enshrined in religions - like the concepts of sacred cows, kosher and halal - would have prospered because they allowed the believing population to (say) live more hygienically and thus survive longer than non-believers in environments possibly more hostile to survival. A migration or a change of the economic infrastructure could render the taboo neutral or even adverse.

Memetic virus exchange?

One controversial application of this "selfish meme" parallel (cf. selfish gene) results in the idea that certain collections of memes can act as "memetic viruses": collections of ideas that behave as independent life forms which continue to get passed on — even at the expense of their hosts — simply because of their success at getting passed on. Some observers have suggested that evangelical religions and cults behave this way; so by including the act of passing on their beliefs as a moral virtue, other beliefs of the religion also get passed along even if they do not provide particular benefits to the believer. Others maintain that the wide prevalence of human adoption of religious ideas provides evidence to suggest that such ideas offer some ecological, sexual, ethical or moral value; otherwise memetic evolution would long ago have selected against such ideas. For example, most religions urge peace and cooperation among their followers ("Thou shalt not kill") which may possibly tend to promote the biological survival of the social groups that carry these memes. A tendency exists in memetics to disparage religious memes. However, some speculate that traditional religions act as mental immune systems to suppress new and potentially harmful memes. Interestingly, we can compare this scenario with the action of a virus (here a religion or a "bundle" of religious memes) proving ineffective and maladaptive if it kills its host(s). For example, popular Christianity forbids both murder and suicide (an idea from Augustine of Hippo's The City of God), and its precise definitions of heresy ensure that properly educated Christians cannot accept new religions which advocate such actions. One could make a case (as Susan Blackmore [http://www.susanblackmore.co.uk/Chapters/awaken.html has done]) that the study of Zen meditation in itself comprises a process of meme "pruning," i.e., a means to remove experiential clichés that reduce the value of life. This has not exempted Zen itself from serving as a source of highly mobile memes, such as "the sound of one hand clapping" koan or exclaiming "mu". It may surprise many memetics advocates to learn of meme-like concepts described long ago, and prevalent in Sufi teaching. Muwakkals rank as separate beings, elementals, that make up human thought (compare Leibniz's monads). (Note that the framing of this whole discussion may mislead. If humans, as seen rigorously from Richard Dawkins' perspective, comprise a collection of the extended effects of our various genes and memes, then the question of what counts as "valuable to the individual" cannot readily become separated from what benefits their genes and/or memes. Since one cannot easily determine the "ecological, sexual, ethical or moral value" of a meme outside of the context of the memes of the determiner, memeticists can easily misuse the idea of "meme" or of a "meme virus" to reject others' positions in a pseudo-scientific way. For example, insofar as you agree with me — i.e., we carry the same memes — I call your ideas "ideas"; insofar as I find your ideas wrong — i.e., you fail to transmit your memes to me — I can call them "memes" and brand you as "infected with a meme virus".) Dawkins notes that one can distinguish a biological virus from its host's normal genetic material by the fact that it can propagate alone, without the entire genetic corpus of the host being propagated — or half of it, in the case of diploid sexual reproduction; thus, a virus can "sabotage" the host's other genes. This applies to memes in the sense that a meme that requires the success of its hosts has a greater likelihood of favouring the interests of these hosts than does a meme capable of succeeding even if each host quickly dies. For example, the commonplace meme encouraging people to wash their hands after they use the toilet or before handling food, and to remind others to do the same, is not at all harmful. In contrast, a cultish meme telling people to [http://www.QuitYourJobDay.com quit their jobs], abandon their families, and run around spreading the meme seems quite virulent. Memetics offers maximum explanatory value in cases where one cannot demonstrate the truth of the contents of the meme. For example, one can readily show that washing hands helps to prevent illness, so the best explanation for the widespread popularity of this practice is that "it works," though memetics still helps explain the rate of spread, and details such as why the practice of washing hands before surgery took so long to catch on. Memetics though excels in explaining the spread of certain value judgements ("chastity is important"), preferences ("pork is repulsive"), superstitions ("black cats bring bad luck") and other scientifically unverifiable beliefs ("'X' is the one true God"), since one cannot easily account for any of these phenomena in terms of their truth-value. Calling someone's ideas/beliefs/action a "meme" therefore does not constitute an insult, but saying that it is "just a meme" does.

Non-natural selection

How "naturally" does this type of selection occur? Perhaps as naturally as sexual attraction or as ethical habits. The relationship of the meme to other ideas of evolution, e.g., those that separate ecological, sexual, ethical and moral factors and reserve no special or separate role for "culture" beyond these, seems to resemble that of a "pretender to the throne" — pretending to explain these more specific ideas of evolution and culture — but without any model to test. This causes some scientists and others to scoff at culture as any kind of factor in human life. A famous observation of this type came from Margaret Thatcher, who bluntly stated: "there is no such thing as society" — evidently she saw "it" as a set of survival, seduction and moral choice factors specific to individuals, couples and families, and not as a unified "culture" or "society" in any sense.

Reproductive isolation in meme "speciation"

In traditional population genetics the normal genetic variation, genetic selection, and genetic drift do not lead to formation of a new species without some form of "reproductive isolation"; i.e., in order to split a single species into two species, the two subpopulations of the original species must ultimately lose their ability to interbreed, which would normally maintain their heterogeneity. However, once separated, natural selection and/or just genetic drift acting on the normal genetic variation in the two subspecies will eventually change enough characteristics of the two subgroups that they can no longer interbreed, which by definition means that they will comprise two different species. Examples of reproductive isolation include geographical isolation, where a 'suddenly' appearing mountain range or river separates the two subgroups; temporal isolation (isolation by time), where one subgroup becomes entirely diurnal in its habits while the other becomes entirely nocturnal; or even just 'behavioral' isolation, as seen in wolves and domestic dogs: they could interbreed, biologically speaking, but normally they do not. A similar phenomenon can occur with memes. Normally, the population of individuals having a meme in their consciousness is heterogeneous and mixes enough to keep the meme intact although it covers a wide range of variations. Should that population become split, however, without sufficient contact for the two different subgroups of variations of the meme to equilibrate, eventually each group will evolve its own version of that meme, differing sufficiently from that of the other group to appear as a distinct entity. The Kellerman meme provides an example of this occurring on the Internet. A search of the web and/or Usenet for the word 'Kellerman' will turn up many citations, describing at great length the behavior of a 'Dr. Arthur Kellerman', who, with the willing assistance of the Centers for Disease Control and the public health lobby, purportedly fabricated studies in order to implicate firearms (and by extension their owners) as a menace to public safety, for the purposes of statist control of the population. The authors of these pages and postings describe purported machinations, "junk science," a subsequent recantation by Dr. 'Kellerman', and the use of his work by gun control proponents. In reality, no "Dr. Arthur Kellerman" exists, at least not in any connection with the above description. There is, however, a Dr. Arthur Kellermann (with double n), who has indeed published several papers estimating the overall impact on the public health of firearm availability and various aspects of firearm storage, as part of a career in public health and emergency and trauma medicine. As in any such series of studies, Kellermann's work has strengths and weaknesses, which pundits rigorously debate both in the literature and online. However, even after eliminating matters of opinion and statements which are not fully supported, the remaining verifiable facts of Kellermann's studies and career remain virtually unrecognizable in the negative descriptions of 'Kellerman.' The original meme of Kellermann and his work on gun-related violent injury has generated a new meme, "Dr. Kellerman is a evil lying gun-grabbing enemy of freedom," by the classic genetic phenomenon of a deletion mutation. The sub-population involved had strongly negative attitudes towards Kellermann's work as well as a lack of first-hand familiarity with his studies and career. Because of the "reproductive isolation" caused by the total non-intersection of the results of searches for "Kellerman" and "Kellermann," the 'Kellerman' meme drifted even further in the direction of negativity, unchecked by facts related to the real Kellermann. As this group encounters new individuals of similar general outlook, they introduce new recruits to the 'Kellerman' lore only, and go on to produce their own websites and postings furthering the rapid progress of this meme. This phenomenon also demonstrates two other features of memes — the "meme-complex" (memeplex), a set of mutually-assisting "co-memes" which have co-evolved a symbiotic relationship, and the [http://www.istop.com/~ggrant/memetics/memelex.html "Villain vs. Victim"] infection strategy.

Forms taken by memes in the brain

In 1981 biologists Charles J. Lumsden and Edward Osborne Wilson published a theory of gene-culture coevolution in the book Genes, Mind, and Culture: The Coevolutionary Process. They pointed out that the fundamental biological units of culture must correspond to neuronal networks that function as nodes of semantic memory. Wilson later adopted the term 'meme' as the best existing name for the fundamental unit of cultural inheritance and elaborated upon the fundamental role of memes in unifying the natural and social sciences in his book Consilience: The Unity of Knowledge.

The "be happy" and "make others happy" memes

Some spiritual practices such as Buddhism clearly promote ecological and moral goals recognizable to most people. For example, the Noble Eightfold Path emphasizes limited consumption, reduced cruelty, no delegation of violence or participation in violent systems, and a withdrawal from sexual and ethical processes that have no clear ecological or moral value to the practitioner — regardless of the value they may have to others. The Judeo-Christian-Islamic religions, however, focus more on devotion to a transcendent deity and to moral codes of behavior, including social and ethical codes affecting every aspect of life from public behavior to commerce to sexual expression. Such religions strongly encourage people to devote themselves to the needs of others. (The contrast between "be happy" and "make others happy", although not as stark in practice or theory as the traditional debate suggests, may satisfy constraints of different ecological or sexual norms in some non-obvious way.) On the other hand they also strongly encourage conversions and active (sometimes even violent, as History shows) proselytising. See below.

Religion

Some (such as Dawkins himself, see [http://www.simonyi.ox.ac.uk/dawkins/WorldOfDawkins-archive/Catalano/quotes.shtml]) consider religion itself a meme — or, more exactly, a memeplex or group of memes. For instance, one can observe that some fundamentalist evangelical movements act predominantly to add to their own numbers. The movements in question devote a large amount of time to evangelical activity, and therefore may seem to unsympathetic observers to serve no other function. This makes it possible to characterize them as self-serving if one does not accept their premises (such as postulating a Hell). On the other hand, for the meme to continue to propagate, it must provide some psychological benefit: catharsis, a release from worry and guilt, a sense of salvation, happiness, moral energy, or just a way out of the fear of death. The Religious Right in the United States of America has a unified message built around religious dogma. By attaching conservative political views to Christian religious evangelism (meme piggybacking), they have associated a particular set of political ideas/memeplexes with a separate set of religious ideas/memeplexes that have "replicated" very effectively for many centuries. Thus Christianity has won converts for centuries; now in many cases a religious conversion also becomes a political conversion. Compare cultural hegemony. Note, however, that Christianity makes some core-truth claims which have existed far longer than any single culture's political realities. In fact, much early persecution of Christianity resulted from its adherents' refusal to adopt an enforced political ritual/view ( Emperor-worship). Synergy between value-systems does not necessarily equal values expressed in the political arena. Note, contrariwise, that some perennial political issues have existed far longer than any single culture's religious system. Politico-religious memplexes form and re-form, evolve and decay.

Science

Similarly, the scientific method offers a body of social and experimental techniques which, given certain preconditions — a free press for the circulation of information, a large number of people predisposed to see the world as a mechanism subject to general rules which can be discovered through repeatable experiments — acts highly virulently, spreading quickly through an educated population. By demonstrating its success at making predictions, science as a practice can make itself more attractive to converts. Whether or not experimenters can necessarily verify them, ideas and attitudes which scientists tend to hold or which "feel" aesthetically pleasing in combination with scientific discoveries, can propagate themselves in societies where science has a high status by the same process of "meme piggybacking".

Meme resistance

Karl Popper advocated this in the strongest possible terms: "The survival value of intelligence is that it allows us to extinct a bad idea, before the idea extincts us." Resistance to science and technology has formed a common meme that can guide human cultural and cognitive evolution away from disastrous paths — for instance the U.S. and USSR stockpiled but did not use nuclear weapons in the Cold War period. Some cultures can consider ignorance a virtue — in particular, ignorance of certain temptations that the culture believes would prove disastrous if pursued by many individuals. The Internet, perhaps the ultimate meme-vector, seems to host both sides of this debate. Although it would seem to a naïve observer that no adult user of the Internet could oppose its use by other adults, that does in fact happen, based on any number of criteria: from ethics to intent to ability to resist hacking or pornography. The Principia Cybernetica project maintains a [http://pespmc1.vub.ac.be/MEMLEX.html lexicon of memetics concepts], comprising a list of different types of memes. It also refers to an essay by Jaron Lanier, [http://www.edge.org/3rd_culture/lanier/lanier_p1.html The ideology of cybernetic totalist intellectuals], which criticises very strongly "meme totalists" who assert memes over bodies.

Examples of memes

Crudely-stated versions of some common memes include:
- Technology: cars, paper-clips, etc. Technology clearly demonstrates mutation as well, which memetic (or genetic) progress requires. Many paper-clip designs have emerged throughout history, for example, with varying degrees of longevity, fecundity and copying fidelity (i.e., memetic "success"). An often-cited example of "technology as meme" involves the building of a fire.
- Jingles: advertising slogans set to an engaging melody
- Earworms: songs that one can't stop humming or thinking.
- Jokes: or at least those jokes popularly considered funny.
- Proverbs and aphorisms: for example: "You can't keep a good man down".
- Nursery rhymes: propagated from parent to child over many generations, sometimes with associated actions and movements.
- Children's culture: games, activities and taunts typical for different age groups.
- Epic poems: once important memes for preserving oral history; writing has largely superseded them.
- Chain letters: "You must send this message to five other people, or something bad will happen to you."
- Conspiracy theories
- Luck: "I am a lucky person. Here are some stories of my luck. If you believe in good luck, you can become lucky like me." (and its obverse)
- Fashions: especially clothing styles such as blue jeans.
- Medical and safety advice: "Don't swim for an hour after eating" or "Steer in the direction of a skid."
- Movies: very memetic given their mass replication, movies tend to cause people to replicate scenes or repeat popular catch phrases such as "You can't handle the truth!" from A Few Good Men or "Alllllllrighty then!" from Ace Ventura, even if they have not seen the movie themselves.
- Science: An empirical study shows that gene names, or more generally, concepts of genes a

Path dependence

__NOTOC__ Path-dependence exists when the outcome of a process depends on its past history, on the entire sequence of decisions made by agents and resulting outcomes, and not just on contemporary conditions. A closely related concept is hysteresis, a property of systems (usually physical systems) whose states depend on their immediate history. These principles tell us that "history matters" in understanding social and physical sciences. Consider as an example the technological development of videocassette recorders (VCRs) for home use. It is argued that management errors and minor design choices by Sony led to its Betamax format being defeated in market competition by VHS in the 1980s. Two mechanisms can explain why the small but early lead gained by VHS became larger over time. The first is the bandwagon of VCR manufacturers in favour of the VHS format in the U.S. and Europe, who switched because they expected VHS to win the standards battle. The second was a network externality: videocassette rental stores observed that more people had VHS players and stocked up on VHS tapes; this in turn led other people to buy VHS players, and so on until there was complete vendor lock-in to VHS. An alternative explanation, of course, is that VHS was better adapted to market demands and that path dependence had nothing to do with its success (note that Beta actually came to market first) and there is also some support for this latter claim. Positive feedback mechanisms like bandwagon and network effects are at the origin of path-dependence. They lead to a reinforcing pattern, in which industries 'tip' towards one or another product design. Uncoordinated standardisation can be observed in many other situations. A classic example is the rules of the road: whereas cars in most countries drive on the right and have steering wheels on the left side of the cars, cars in the U.K. and countries that were part of the British Empire continue to drive on the left, and to have the steering wheels on the right side. Technically, the two options are equivalent. The initial choice to drive on a particular side was accidental, but remains a legacy in these countries. Once this social convention emerged, though, it became permanent because of the huge switching costs involved in modifying it. Examples from economics, history, software, and biology are presented below.

Economics

Path dependency theory was originally developed by economists to explain technology adoption processes and industry evolution. The theoretical ideas have had a strong influence on evolutionary economics (e.g., Nelson & Winter 1982). There are many models and empirical cases where economic processes do not progress steadily toward some pre-determined and unique equilibrium, so that the nature of any equilibrium achieved depends partly on the process of getting there. The outcome of a path dependent process will often not converge towards a unique equilibrium but instead reach one of several equilibria (sometimes known as absorbing states). This dynamic vision of economic evolution is very different from the neo-classical economics tradition, which in its simplest form assumed that only a single outcome could possibly be reached, regardless of initial conditions or transitory events. With path dependence, both the starting point and 'accidental' events (noise) can have significant effects on the ultimate outcome. In each of the following examples it is possible to identify some random events that disrupted the ongoing course, with irreversible consequences:
- In the 1980s, the U.S. dollar exchange rate appreciated, lowering the world price of tradable goods below the cost of production in many (previously successful) US manufactures. Some of the factories which closed as a result could now be run at a (cash-flow) profit, because the dollar has declined. However, re-opening them is too expensive. This is an example of hysteresis and irreversiblity.
- In economic development, it is said (initially by Paul David in 1985) that a standard which is first-to-market can become entrenched (like the QWERTY layout in typewriters still used in computer keyboards). He called this "path dependence", and argued that inferior standards can persist simply because of the legacy they have built up. The case against QWERTY has been criticized (e.g. by The Fable of the Keys), but standards are clearly very important in modern economies, and the significance of path dependence in determining how they form is the subject of economic debate.
- Economists since Adam Smith have noted that businesses of a certain type tend to congregate geographically, attracting workers with skills in that business, which draw in more businesses looking for employees with experience. There may not have been any particular reason to prefer one place to another before the industry developed, but as it has become concentrated in one place any new entrants elsewhere are at a disadvantage, and will tend to move into the hub if possible, further increasing its relative efficiency. The mechanism at work is a network effect. New Trade Theory and Krugman's "New Economic Geography" are based partly on this story.
- If the economy follows adaptive expectations, future inflation is partly determined by past experience with inflation, since experience determines expected inflation and this is a major determinant of realized inflation.
- A transitory high rate of unemployment during a recession can lead to a permanently higher unemployment rate because of the skills loss (or skill obsolescence) by the unemployed along with a deterioration of work attitudes. In other words, cyclical unemployment may generate structural unemployment. The negative effects get reinforced by potential employers' negative view of the capacities of job-seekers who have been out of a job for a long time. This structural hysteresis model of the labour market differs from the prediction of a "natural" unemployment rate or NAIRU, around which 'cyclical' unemployment is said to move randomly. Since structural unemployment is endogenous, the NAIRU is also endogenous (see the article by Hargreaves Heap cited below). In technical terms, a path-dependence (stochastic system) can be defined as "one possessing an asymptotic distribution that evolves as a consequence (function of) the process's own history". This is also known as a "non-ergodic stochastic process". Confusingly, the use of "path dependent" to describe labour market hysteresis has the opposite sense to the term's meaning in the adaptive expectations model of inflation. In labour market economics, some "path dependent" models have unemployment following a driftless random walk, based solely on its previous level (a Markov process).

History and the Social Sciences

The history of humanity is almost by definition path-dependent. Accidental events such as the death at an early age of major historical figures like Napoleon or Hitler would surely have altered the political geography of Europe and even the languages spoken in different countries today. Recent methodological work in comparative politics and sociology has adapted the concept of path dependence into analyses of political and social phenomenon. Path dependence has primarily been used in comparative-historical analyses to analyze the development and persistence of institutions, whether they be social, political, or cultural. There are arguably two discernable types of path-dependent processes:
- One is the "critical juncture" framework, most notably utilized by Ruth and David Collier in political science. In the critical juncture framework, antecedent conditions define and delimit agential during a critical juncture in which actors make contingent choices that set a specific trajectory of [institutional]] development and consolidation that is difficult to reverse. This is akin to the concepts of lock-in or positive feedback derived from path dependence in economics. The critical juncture framework has been used to explain the development and persistence of welfare states, labor incorporation in Latin America, and the variations in economic development among countries, among others. An influential attempt to give some formal rigor to thinking about path dependence in political science is notably that of Paul Pierson. Pierson draws in particular on ideas from economics (see above). His efforts have been seriously challenged by Herman Schwartz, who argues that forces analogous to those identified in the economic literature are not pervasive in the political realm, where larger structural causes and the strategic exercise of power give rise to, maintain, and transform institutions. In perhaps a related vein, scholars such as Kathleen Thelen caution that the historical determinism embedded in path-dependent frameworks ignore the constant renegotiation of institutional configurations. She suggests that institutions undergo moments of institutional evolution wherein key actors renegotiate the configuration of said institutions.
- The other path-dependent process deals with "reactive sequences" where a primary event sets off a temporally-linked and causally-tight chain of events that is nearly uninterruptible. These reactive sequences have been used to link the death of Martin Luther King, Jr. with welfare expansion and the industrial revolution in England from the development of the steam engine.

Technology

In the computer and software markets, legacy systems indicate path dependence: customers' needs in the present market often include the ability to read data or run programs from past generations of products. Thus, for instance, a customer may need not merely the best available word processor but rather the best available word processor that can read Microsoft Word files. Such limitations in compatibility contribute to lock-in, and more subtly, to design compromises for independently developed products if they attempt to be compatible. It is not clear, however, that there is any inefficiency involved in the costs of remaining compatible with past decisions.

Biological evolution

Evolution is considered by some to be path-dependent: random mutations occurring in the past have had long-term effects on current life forms, some of which may no longer be adaptive to current conditions. For instance, there is a controversy about whether the panda's thumb is a leftover trait or not.

Physics

The process of Spontaneous_symmetry_breaking in physics is very similar to path dependence. For example, in materials that exhibit Ferromagnetism, magnetic domains form in otherwise completely homogenous materials.

References

- Douglas J. Puffert (2001), [http://www.vwl.uni-muenchen.de/ls_komlos/spatial1.pdf "Path Dependence in Spatial Networks: The Standardization of Railway Track Gauge"]
- Margolis and Liebowitz (2000), [http://www.utdallas.edu/~liebowit/palgrave/palpd.html "Path Dependence, Lock-In, and History"]
- Paul A. David (2000), [http://econwpa.wustl.edu/eps/eh/papers/0502/0502003.pdf "Path dependence, its critics and the quest for ‘historical economics’"], in P. Garrouste and S. Ioannides (eds), Evolution and Path Dependence in Economic Ideas: Past and Present, Edward Elgar Publishing, Cheltenham, England.
- Douglas J. Puffert (1999), "Path Dependence in Economic History"], based on the entry “Pfadabhängigkeit in der Wirtschaftsgeschichte,” in the Handbuch zur evolutorischen Ökonomik)
- 'S.J. Liebowitz and Stephen E. Margolis (1990), [http://www.utdallas.edu/~liebowit/keys1.html "The Fable of the Keys"], Journal of Law & Economics vol. XXXIII (April 1990)
- Nelson R. & Winter S. 1982. An evolutionary theory of economic change. Harvard University Press.
- Pierson, Paul. "Increasing Returns, Path Dependence, and the Study of Politics." American Political Science Review, June, 2000.
- Schwartz, Herman. "Down the Wrong Path: Path Dependence, Increasing Returns, and Historical Institutionalism." http://www.people.virginia.edu/~hms2f/Path.pdf

External links

- [http://eh.net/encyclopedia/article/puffert.path.dependence Article on Path Dependence from EH.NET's Encyclopedia]
- [http://cscs.umich.edu/~crshalizi/notebooks/qwerty.html "QWERTY, Lock-in, and Path Dependence"] Web page that argues that lock-in leads to market failure and provides a list of references although it short shrifts articles from those on the other side.
- Shawn Hargreaves Heap (1980), "Choosing the Wrong 'Natural' Rate: Accelerating Inflation or Decelerating Employment and Growth?" Economic Journal 90(359) (Sept): 611-20 (ISSN: 0013-0133) develops the idea that persistently high unemployment can cause the "natural" rate of unemployment to rise.
- [http://www.wiwiss.fu-berlin.de/w3/w3schrey/pfadkolleg/english/index.php "Doctoral Program Research on Organizational Paths"] Web page form the Freie Universitaet Berlin Faculty of Business Administration and Economic. ; Debate
- [http://forum.redlers.com/viewtopic.php?t=14 Forum Debate] a lively and informative ongoing debate over open vs. closed systems, standards, formats, vendor lock-in, and path dependence as a deliberate strategy by some businesses Category:Economics

Percolation

In chemistry and materials science, percolation proto-typically concerns the movement and filtering of fluids through porous materials. During the last three decades, percolation theory, an extensive mathematical model of percolation, has brought new understanding and techniques to a broad range of topics in physics and materials science.

Applications of percolation theory

Among the applications are the study of percolation of petroleum and natural gas through semi-porous rock; here the theory has helped predict and improve the productivity of natural gas and oil wells. In two dimensions, the percolation of water through a thin tissue (such as toilet paper) has the same mathematical underpinnings as the flow of electricity through two-dimensional random networks of resistors. In chemistry, chromotography can be understood with similar models. The propagation of a tear or rip in a sheet of paper, in a sheet of metal, or even the formation of a crack in ceramic bears broad mathematical resemblance to the flow of electricity through a random network of electrical fuses. Above a certain critical point, the electrical flow will cause a fuse to pop, possibly leading to a cascade of failures, resembling the propagation of a crack or tear. The study of percolation helps indicate how the flow of electricity will redistribute itself in the fuse network, thus modeling which fuses are most likely to pop next, and how fast they will pop, and what direction the crack may curve in. Examples can be found not only in physical phenomena, but also in biological and ecological ones (evolution), and also in economic and social ones (see diffusion of innovation). Percolation can be considered to be a branch of the study of dynamical systems or statistical mechanics. In particular, percolation networks exhibit a phase change around a critical threshold.

Technology lifecycle

Most new technologies follow a similar technology lifecycle. This is similar to a product life cycle, but applies to an entire technology, or a generation of a technology. There is usually technology hype at the introduction of any new technology, but only after some time has passed can it be judged as mere hype or justified true acclaim. Because of the logistic curve nature of technology adoption, it is difficult to see at in the early stages whether the hype is excessive. You can almost never believe the hype. The two errors commonly committed in the early stages of a technology's development are:
- fitting an exponential curve to the first part of the growth curve, and assuming eternal exponential growth
- fitting a linear curve to the first part of the growth curve, and assuming that takeup of the new technology is disappointing Similarly, in the later stages, the opposite mistakes can be made relating to the possibilities of technology maturity and market saturation. Technology adoption typically occurs in an S curve, as modelled in diffusion of innovations theory. This is because customers respond to new products in different ways. Diffusion of innovations theory, pioneered by Everett Rogers, posits that people have different levels of readiness for adopting new innovations and that the characteristics of a product affect overall adoption. From a layman's perspective, the technology life cycle can be broken down into five distinct stages. #Bleeding edge - any technology that shows high potential but hasn't demonstrated its value or settled down into any kind of consensus. Early adopters may win big, or may be stuck with a white elephant. #Leading edge - a technology that has proven itself in the marketplace but is still new enough that it may be difficult to find knowledgeable personnel to implement or support it. #State of the art - when everyone agrees that a particular technology is the right solution. #Dated - still useful, still sometimes implemented, but a replacement leading edge technology is readily available. #Obsolete - has been superseded by state-of-the-art technology, rarely implemented anymore.

Logistic function

The logistic function or logistic curve models the S-curve of growth of some set P. The initial stage of growth is approximately exponential; then, as competition arises, the growth slows, and at maturity, growth stops. As shown below, the untrammeled growth can be modelled as a rate term +rKP (a percentage of P). But then, as the population grows, some members of P (modelled as

-rP^2

) interfere with each other in competition for some critical resource (which can be called the bottleneck, modelled by K). This competition diminishes the growth rate, until the set P ceases to grow (this is called maturity).

The logistic function

As shown below The logistic function is defined by the mathematical formula: :

P(t) = a\frac \!

for real parameters a, m, n, and

\tau

. These functions find applications in a range of fields, from biology to economics. For example, in the development of a baby, a fertilized ovum splits, and the cell count grows: 1, 2, 4, 8, 16, 32, 64, etc. This is exponential growth. But the baby can grow only as large as the uterus can hold; thus other factors start slowing down the increase in the cell count, and the rate of growth slows (but the baby is still growing, of course). After a suitable time, the baby is born, and the child keeps growing. Ultimately, the cell count is stable; the person's height is constant; the growth has stopped, at maturity. In such examples, relationships between variables are modelled. In addition, an important logistic function is the Rasch model, which is a general stochastic measurement model. This model is used as a basis for measurement rather than for modelling relationships between variables for which measurements have already been obtained (as in the preceding example). In particular, the Rasch model forms a basis for maximum likelihood estimation of the locations of objects to be measured on a continuum, based on collections of categorical data. For example, the model can be applied in order to estimate the abilities of persons on a continuum based on assessment responses that have been categorized as correct and incorrect.

The Verhulst equation

A typical application of the logistic equation is a common model of population growth, which states that:
- the rate of reproduction is proportional to the existing population, all else being equal
- the rate of reproduction is proportional to the amount of available resources, all else being equal. Thus the second term models the competition for available resources, which tends to limit the population growth. Letting P represent population size (N is often used in ecology instead) and t represent time, this model is formalized by the differential equation: :

\frac=rP\left(1 - \frac\right) \qquad \mbox, \!

where the constant

r

defines the growth rate and

K

is the carrying capacity. The general solution to this equation is a logistic function. In ecology, species are sometimes referred to as r-strategist or K-strategist depending upon the selective processes that have shaped their life history strategies. The solution to the equation (with

P_0

being the initial population) is; :

P(t) = \frac

Where; :

\lim_ P(t) = K

Sigmoid function

The special case of the logistic function with

a=1, m=0, n=1, \tau=1

, namely :

P(t) = \frac\!

is called sigmoid function or sigmoid curve. The name is due to the sigmoid shape of its graph. This function is also called the standard logistic function and is often encountered in many technical domains, especially in artificial neural networks as a transfer function, probability, statistics, biomathematics,

Diffusion of innovations

Theories of Innovation Diffusion

The S-Curve and technology adoption

Caveats and Criticisms

See also

External link

Imitation

Everett Rogers

Early life

Academic research

Diffusion of Innovations

Later life

See also

External references

Disruptive technology

The theory

Examples of disruptive technologies

Business implications

External links

Books and papers

Crossing the Chasm

See also

Diffusion (business)

Models of diffusion

The rate of diffusion

Diffusion rate models

See also

References

Meme

Basic introduction

History of the concept of the meme

"Ideas have a life of their own"

Memetics

Memetic engineering

Memetic evolution

Do cultures evolve?

Propagation of memes

Biological analogies

Thoughts as discrete units

Evolution of memes

Evolutionary forces affecting memes

Memetic virus exchange?

Non-natural selection

Reproductive isolation in meme "speciation"

Forms taken by memes in the brain

The "be happy" and "make others happy" memes

Religion

Science

Meme resistance

Examples of memes

Path dependence

Economics

History and the Social Sciences

Technology

Biological evolution

Physics

References

External links

Percolation

Applications of percolation theory

See also

Technology lifecycle

See also

Logistic function

The logistic function

The Verhulst equation

Sigmoid function