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Week 4
Feb. 6th: Diffusion of Innovations
Chapter 1 in Rogers, Everett M. 1995. Diffusion of Innovations. New York, NY: Free Press.
Geroski, P.A. 2000. “Models of technology diffusion.” Research Policy 29:603-625.
Feb. 8th: Diffusion of Innovations II
Chapters 1-3 in Valente, Thomas. 1995. Network Models of the Diffusion of Innovations. Cresskill, NJ: Hampton Press.
January 2nd, 2007posted by:
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27 Comments Add your own
1. yliu | February 4th, 2007 at 6:32 pm
Rogers’ framework for analyzing the adoption of innovation is very insightful. In the ideal model of perfect information and rational individuals, it is difficult to conceive why innovations aren’t picked up immediately by those who stand to benefit from it. The diffusion of innovation model accounts for bounded rationality and social influences, and actually outlines 5 specific factors that influence adoption, which should be useful guidance to various marketers for innovation - whether they be international development workers out to educate on water-boiling, or the developers of the latest community-based Web-2.0 application seeking users.
What all 5 factors of adoption expresses in some way is the idea of risk, or rather, perception of risk on part of the potential adopter, and how best to minimize it. Adopting a new innovation is not only a calculation of what is to be gained, but also what of the status quo is at stake. Rogers touches upon this with the idea of reducing uncertainty, both on part of the innovation itself and its consequences, but I think this connection should be made explicit, and generalizations made more precise. A hypothetical educated, well-off technology enthusiast may be the classic definition of an early adopter, running all sorts of cutting-edge, innovative, fresh-from-the-source-repository software on his own workstation. At the same time, he might run his personal/hobbyist webservers with only release versions of software. For his dayjob as director of corporate IT, he might choose only proven stable versions and eschew the innovations introduced by later versions or alternative software packages - the risk of adoption outweighs the potential benefits. In this case, the person never changed, but due to the risk context, this individual is an early adopter in the first and late-majority/laggard in the second.
Geroski’s discussion probit models and using specific characteristics to assess adoption rates seems an intuitive thing to do, since we know that unlike communicable diseases, where contact implies infection, knowing an innovation exists does not necessarily imply adoption of that innovation. The language here focuses on corporate organizations, but expectations and costs are fairly applicable to individuals as well. I find interesting that firm size is raised as a characteristic for modeling, since as the author admits, firm size can be raised as both a reason for greater or lesser inclination to adopt innovations. Large firms can be good imitators, but I’d think they also can be poor imitators due to the structural rigidity of the organization and lack of agility. If such is the case, what is the explanatory power behind this characteristic?
February 4th, 2007 at 6:32 pm |WordPress database error: [Table 'i203.is203_users' doesn't exist]
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 12. Sean_Carey | February 6th, 2007 at 12:06 am
I found the first reading to be interesting, but long. The second reading felt dry with all the math involved. These dispersion methods discussed in the reading are actually important to marketing in the business world. There are always early adopters of technology, and sales tend to snowball as more people get onboard. However, with out proper explanation, technology won’t get dispersed into the general public. The Segway is a perfect example of technologies that don’t catch on. It would also make another great example for the Roger’s article. The inventor envisioned the Segway as a method for college students to get around, but the price point was too high, and people didn’t understand the real need for it. now overweight cops use it to get around. The innovator needs to explain in terms that the consumers can understand, or else the product will fail. I think that having consumers try out the product helps with dispersion. As the Roger’s article suggests, word of mouth is a very powerful tool when used correctly.
February 6th, 2007 at 12:06 am |WordPress database error: [Table 'i203.is203_users' doesn't exist]
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 13. Ken-ichi | February 6th, 2007 at 12:12 am
Response to Rogers
Seems a fairly structured approach to a fascinating topic. My main problems with all the case studies presented is incredibly small sample size and a failure to provide comparison to some kind of stochastic null model. Ryan and Gross’s hybrid corn study seems the most rigorous and they seem to have based their findings on more evidence than any other cases presented, but even their 259 farmers are all a part of a single community, one in which individuals can literally know and see each other. It’s nice that they observed an S-shaped curve, but a simultaneous study in a culturally similar but socially disconnected community would have been more convincing. The Korean village studies on contraception adoption got closer to this, but even that seemed like just a handful of villages. I guess studies on tens of communities are probably way outside the budgets of most sociologists. Ecologists have the same troubles.
But why no null models? If diffusion is a social process, why not show how the data differ from, say, simulated data from agent-based models wherein agents are whimsical and arbitrary?
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 14. karenhsu | February 7th, 2007 at 2:36 am
It’s not always clear why things take so long to happen. If it’s a good idea, why not simply adopt it? In my previous post for last week’s readings, I brought up the idea of technological momentum and how great (social or monetary) investment in a past technology directly influences the rate of adoption of a new one. This can be seen in Rogers’ QWERTY example, where the more efficient Dvorak keyboard was not widely accepted due to prior invested interests (by manufacturers, typists, pirates, teachers, etc.) in the old design. Other interesting factors in adoption rates that Rogers mentions include relative advantage and compatibility. Like momentum, these human-perceived characteristics of innovation pertain to the relationship between the new innovation and pre-existing societal values, ideas, and thus investments.
One more thing that I would like to mention from the Rogers paper is the relationship between the author’s notion of opinion leadership and heterophilly. In the paper, heterophilly is used to describe the effectiveness of communication channels between two or more individuals that share the same beliefs, education, social status, psychic ability, or whatever other attributes. It’s easy to see that opinion leaders can more easily influence those individuals who are more heterophilous.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 15. zgillen | February 8th, 2007 at 11:41 am
What I find fascinating, especially in the Rogers and Valente readings is this idea of the laggard. There were several examples in Rogers as to reasons why innovations do not diffuse (Water boiling in the Peruvian village, Scurvy and QWERTY examples). A breakdown in one of the four diffusion elements, proposed by Rogers, can prevent a certain innovation from achieving critical mass of dissemination. What about the remaining two to twenty percent who refuse adoption after diffusion occurs? What are the reasons that stop the laggard from technological adoption?
It appears you can classify ‘the laggard’ in two different categories that depend on the context of the innovation. There are those that encounter external barriers and others that make personal decisions that prevent adoption from reaching complete saturation. The idea of a ‘laggard’ implies that the majority of the population or innovation itself has overcome the main barriers of introduction. This could be economic restrictiveness of the innovation. For example, a new drug might be socially accepted into a certain population but the cost might be prohibitive. When a generic is introduced, this cost barrier is broken and diffusion occurs. The remaining laggards might be the poorest, or most socially isolated, or have some other barrier preventing them from what has become socially accepted. These barriers make sense when the innovation is something that has proven importance. An example is the diffusion of hybrid corn. If your crop yields twenty percent higher production, only something extremely prohibitive would prevent you from adoption.
Personal decision is separate and what I think is more interesting example of the laggard. An innovation like the compact disc is something that’s socially important, but not necessary for economic survival. The laggards who do not adopt this innovation are eventually making a personal decision not to adopt. Perhaps the sound quality is inferior, they don’t believe in the digitalization of sound or some other preference; however there is a decision not to adopt. Of course, what is a personal choice in the population of the Bay Area might be a restrictive economic barrier in a developing country. I think looking deeper at the social decisions made by the laggards would be really interesting!
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 16. srini | February 8th, 2007 at 12:26 pm
I would agree that social system and word of mouth play an important role in the diffusion of innovation. But I would like to point out there are certain other aspects other than the user or adaptor and the social system which affects the diffusion of innovation. In most of the technological innovations, they are either a radical concept/technology or an improvement of an existing technology with new ideas. For example telephone is a entirely new mode of communication, when it was introduced and hence people need some time to recognize and adopt it. Such radical innovation takes very long time as it tries to change the existing behavior. But we could see that the use of mobile phones, which is an improvement over the existing telephones are adopted relatively fast compared to the telephones. In all these cases, other factors such as cost, ease of use, relevance( for effective use of telephone , people whom i communicate with shoudl also have telephone) plays an important role in the diffusion of innovation. Though computers were invented before forty years, it found its great diffusion only in the past decade. Initially the cost of computers was very high, and it was useful only for a few people, and it was very complex to use. The diffusion started increasing exponentially once it becomes easily usable and affordable. Even if a innovation is well recognized it may not be adopted due to the above mentioned factors. For example, though Apple’s “Mac” exist in market for the past two decades, and it is highly appreciated for its innovation in graphics and design , it did not find its extensive diffusion due to factors such as cost and non-compatibility with other systems.
In case of social innovation, such as ‘boiling drinking water’, “family planning”, etc the communication channel should be properly selected with respect to the target audience. In a group of literate people this innovation can be explained with an awareness article or video. But when the audience are illiterate, the same message should be conveyed in a different way. For example if it is explained by their favorite celebrities, they may adopt it faster. In case of children the same message reaches easily through cartoons and animations. Hence the same innovation reaches different audience in different ways. And mass media and other social systems play an important role in such diffusion.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 17. megha | February 9th, 2007 at 2:42 pm
I liked the Roger’s reading and found it to be a powerful framework for understanding how some innovations take the world by storm while some others fail or remain dormant for years and years .The segmentation of the audience into 5 categories, based on their propensity to accept the new idea or behavior can probably applied to any innovation adoption.The bell-curve which represents this segmentation begins with visionaries, early adopters, early majorities, late majorities, with laggards holding out to the bitter end.I feel the people who fall in the “Late majority” and “Laggard” might be many times constrained due to different socio-economic factors rather than just driven by their personal decisions.Generally lot of the people in the society with a lower financial stand,waits for products to become cheap and picks them up only when they can afford it..Many innovations are widely adopted in few countries whereas major population in other countries take years to pick it up and thus fall into the category of “Late majority” or “laggard”. As for example - Internet seems to be adopted everywhere in USA, but it is only major cities and towns in India where you find internet connectivity.
In terms of communication channel, i feel that though mass media channels have a potential of reaching a broad audience, interpersonal channels definitely play a bigger role in the adoption of a technology by the people who falls in late majority category. No matter how many advertisements are shown everyday, we get mostly motivated to by something new when someone in our friend or family group had bought it and found it useful.
I wonder how similar or different is the model of diffusion when it comes to innovations which affect an organization and not a individual .For example - products like iPod are more targeted for individuals , whereas enterprise products like database are more targeted for organizations. Do they follow the same pattern of diffusion ?
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 18. elisa | February 9th, 2007 at 5:14 pm
I am finding very interesting the idea of social groups, and how different theories focus on different dynamics of interaction among individuals. SCOT emphasizes the importance of “relevant social groups,” and when we talked about The Social Life of Information we talked about core groups and ‘rings of hegemony.’ In looking at theories about the diffusion of innovation, we talked about early adopters and opinion leaders, homophilous vs heterophilous groups (but when Valente says that the more an individual’s network is heterogeneous, the faster will the innovation spread, does he mean that the individual is part of a heterophilous group? In this context, is heterophilous synonym with heterogeneous?) , and weak versus strong ties. These types of groups have many overlaps, and yet the distinction among them are very useful distinction when describing diffusion of innovation, because they allow the researcher to focus on a specific social aspect of the group s/he’s studying. In other words, if I want to study the diffusion of bicycles among women as a group, I can consider them as a homophilous group and contrast them with men, that would be their correspondent heterophilous group, and then I could look at the internal ties within a group of women and identify the early adopters, the leaders, etc. (I am not saying that this sort of theoretical mix-and-match would necessarily be methodologically sound, but it seems a plausible starting point). The trouble starts when one wants to make the leap from descriptive to predictive theories, because it becomes much harder to identify which “allegiance” will prevail in influencing the way an individual will react to an innovation. Who will prevail: an opinion leader with the same social status, or an opinion leader with a different social status, or peer-pressure? This seems the key issue that determines the viability of predictive diffusion theories in terms of practical applications (that is, marketing!), although there are so many variables to take into consideration that one wonders if it is really possible to model them all.
An interesting micro case-study: a friend works for an international fashion company that positions itself in the ‘entry luxury market’(translated into dollars, this means people who will spend $1500 to $2000 in a handbag, but not $3000). They had their UK market practically destroyed because the “chavs” (hmm, not sure what the American equivalent would be; wikipedia goes for “derogatory slang term in popular usage throughout the UK. It refers to a subculture stereotype of a person who is uneducated, uncultured and prone to antisocial or immoral behaviour. The label is typically, though not exclusively, applied to teenagers and young adults of white working-class or lower-middle class origin” and I think it’s fairly accurate) really liked their clothes, and began buying and wearing them (both the real thing and fakes), therefore destroying the appeal for the targeted socio-economical group (would this be “reverse opinion leaders” theory?). But then the company began a ‘celebrity campaign’ where they gave their new handbag to a celebrity, who wore it and was photographed in fashion magazines wearing it, and the sales have began to grow again (a clear case of early adopter/opinion maker convergence).
On an unrelated matter, I found the definition of technology used by Rogers quite bewildering. “A technology is a design for instrumental action that reduces the uncertainty in the cause-effect relationships involved in achieving a desired outcome.” I don’t think it influenced the rest of the article, so even adopting a more conventional definition of technology wouldn’t invalidate the thesis of the article, but I’d be interested in talking more about this ‘reduction of uncertainty in cause-effect relationships’.
February 9th, 2007 at 5:14 pm |WordPress database error: [Table 'i203.is203_users' doesn't exist]
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 19. cvolz | February 9th, 2007 at 6:30 pm
One of the first things I thought of while doing this week’s readings was the spread and adoption of gmail. Google, I think, gamed the system a little bit by incorporating some artificial scarcity and cachet — not only could you only receive entrance into gmail through an invitation but each person also only had a limited number of invitations. That said, I don’t think gmail would’ve spread as widely and as quickly as it had were it not also a genuine innovation in how web-based email systems work (or at least organize and display).
And while I don’t think the spread of innovation as a social process (I mean, how else would it spread? People, pretty obviously, pick up an innovation because they heard about it from someone), but I don’t think it’s a very interesting to think about the connections between people. Specifically, I found it very interesting that the most influential people in terms of proselytizing a new innovation do not necessarily have high social status. It seems to me that many innovations tend to start out with an initial fan base that advocates the innovation to their peers; who are almost always very similar to each other. But at some point the innovation breaks away from the initial small user-base and expands to the rest of the population. What I’m most curious about is this transition from the intial user base outward to the heterophilous general population. And while I know we’ve mostly been focused on interperosnal (ie- word of mouth and/or demonstration) influence, couldn’t it be argued that marketing and advertising are also social processes, or at least could be? Getting an innovation into the public’s consciousness and getting the endorsement of prominent members of the community are pretty key marketing objectives. So… how many innovations fail because they suck vs. how many fail because they were poorly advertised?
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 110. lawan | February 10th, 2007 at 2:19 am
An interesting point I agree in the Diffussion of Hybrid Corn study is that innovators are those people who owned larger-sized farms, higher incomes, and more years of formal education. This relates to Roger’s earlier point that not only innovations are created by means to reduce uncertainty, it also creates another kind of uncertainty (expected/unexpected) results.Combinding these two points, it implies that wealthier poeple are those tends to apply new innovation/technology since they have much more room for uncertainty in life, especially in term of economically. They can risk to try the new ideas, if it works they can adopt them. If it is not, they can just simply reject it without any impact financially. In contrast, normal people tends to seek for proven/trusted solutions that they know can be surely implemented and have direct benefit to them. So, they wait until the innovations/new ideas are proven by those innovator before they apply it into their situations/cases.
It is much clearer to me the reason why high-tech product / new technology always target high-end customer group. I believe not only that they have more money to spend, but by nature, they can be more risky in their decision than most people. So, that’s why they tends to try/buy new things that they think could be useful for them.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 111. jimmy | February 11th, 2007 at 2:28 am
For the four elements in the diffusion of innovations, I am particularly interested in Communication Channels. We certainly need various communication channels to deliver new technology and concepts to the masses. Different channels work under different circumstances. Although the mass media is very powerful that efficiently delivers information to every corner of the society, I think the most important channel is through the interpersonal networking. The mass adoption of new technology and innovation often results from the influence of peers with same belief, interests, language, religions, etc. When making decisions on whether or not to adopt new innovations, people tend to look for their friends’ suggestions. After a group of people have adopted a new concept, we can anticipate that more people will follow their steps and facilitate the diffusion of innovations.
However, as mentioned in the reading, one significant problem of the diffusion of innovations is that the participants are usually quite heterophilous. Because the change agents and early adopters often have the foresight which the masses don’t have, the bottleneck is the extent of diffusion from early adopters to the ordinary people. It may seem to be easy and straightforward to achieve this goal, but the truth might often lead to disappointments. For instance, we always see the bright side of doing business in China, but what we might ignor are the numerous failure cases each year. For western companies, trying to sell new products to developing countries with totally different cultures and customs needs further planning and adjustments. In other words, we need to strive for localization as a way to remove the obstacles of heterophily during the diffusion of innovations. I find it intriguing to relate the readings this week with the concept of globalization and localization.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 112. daniela | February 11th, 2007 at 9:28 am
I liked exploring the conflated definitions of risk and uncertainty in the context of diffusion and adoption. It seems reasonable to assume that both risk and uncertainty play a similarly critical role in the adoption process. Someone may not adopt an innovation, such as the electric toothbrush, due to the amount he or she does not know: does the brush run out of batteries often? Will the brush hurt my gums more than help my teeth? Likewise, someone may not adopt this technology if he or she deems the risk involved is too high: the chance of hurting my gums is too high to risk improving the hygiene of my teeth. In this case, risk is more subjectively determined by the individual than uncertainty. A person unfamiliar with other people’s adoption of the electric toothbrush cannot predict its many outcomes, the ostensibly objective unknowns. Yet, the amount of risk is clearly based on that which is more valuable to the individual: gums or their teeth. As Valente suggests, people are more likely to adopt a technology by viewing someone else adopting it first. The amount of risk that is involved in their decision is based on a mix of what they do and do not know, how certain they are of this knowledge, and the subjective relationship of this information to their own values and investments. The two concepts clearly apply to separate forces at work but relate to the same thing.
Free riders are another group that distinguish the effects of risk and uncertainty. Free riders probably associate little if no risk in their adoption of an innovation since no investment has been made. But uncertainty involved in their decision may still affect its outcome. I thought it was strange Valente assumed that free riders delay the critical mass of adoption. Let’s take Wikipedia. The site exemplifies the use of free riding in a context in which a community only built of contributors would have stymied the system. The free-riders in this sense do not impede the critical mass but actually enabled them. If we assume that Wikipedia is a tool for deriving encyclopedic knowledge, then the adoption of its use is of this nominal service and not the collaborative online platform it provides. In this case, most adopters would individually free ride in order to keep the system alive. I’m guessing the success of Wikipedia was not based on many other previously successful examples as much as on the marginal outlier who began the service and the opinion leaders who followed him or her up.
I also wanted to bring up Megha’s point regarding the three examples of adoption Valente explores: each study investigated the diffusion of a technology by an individual within a distinct group. No study we’ve looked into has explored the adoption of technologies by a group within a larger context. For example, how does a city adopt new transportation infrastructure like light-rail? I’m curious if any threshold or critical mass effects would still influence public opinion on this large a scale. How would you determine hierarchical equivalence of group adopters and group non-adopters? How would the concept of direct “contact” translate to a group? Enough questions. The point is that I think it’s no coincidence groups have been largely ignored by Rogers and Valente. It’s more difficult to operationalize group adoption practices than those of the individual. The Coleman, Katz and Menzel study of tetracycline illustrated that even for the individual there are difficulties in operationalizing the concept of adoption. They defined adoption as people’s first trial of the drug. Obviously, the first trial, unlike the continued use of the drug, could be easily and consistently measured. Still, in my mind, the results are ultimately inconclusive: they never measured the drug’s continued or discontinued use – namely, true “adoption.”
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 113. dondrea | February 11th, 2007 at 11:37 am
The reasons why any particular technology is adopted, whether by a person, group or on a larger societal scale are multi-faceted and can change over time. It is important to keep in mind that the mere existence of ’superior’ technology does not pre-determine its adoption, at least not immediately. Beta-max format was reported to be a superior technology to VHS yet it did not survive. Now both Beta-max and VHS have been replaced by the DVD format. So not all ‘superior’ technologies are inevitably adopted. The old Camera Phone idea that didn’t survive also provides an interesting example of this. As it was discussed in class, we’re asked why didn’t that technology catch on. There are any number of reasons.
Even when presented with ‘the facts’ of a superior technology, people don’t always make rational or logical decisions when it comes to purchases. They may purchase something based on appearance/style or prestige or the family/community tradition of buying a certain thing. Ineffective marketing, poor advertising, and social blocks are also possible reasons. Perhaps societal norms regarding public and private were a factor with regards to the video component of the phone. We’ve had around for years, email technology that allows us to see when a recipient has read our mail. Yet one wonders why it has not been more widely adopted. Poor user interface design is another possible reason. All the things that a product is designed to do vs. what people can use it to do may be two different things. Even the most simple design to the eye could be complicated to use in practice. In 213 we’ve read how some good technologies were released with poor interface design. Consumers could not use them which resulted in negative public opinion and product market failure. Even if they were redesigned, products like this aren’t reintroduced because of the power of public memory. No company will take the risk.
We can all think of examples of technologies that existed, launched and failed long before their ultimate mass adoption (Ex. the fax) mainly because several requirements have to be met for any technology to succeed. There has to be awareness of the technology and a need or perceived need for it. It has to be widely available and have an infrastructure to support it. And it must be affordable and usable to name a few. Who knows, in ten or twenty years maybe the ‘Camera Phone’ technology will be launched again, albeit with a different interface, in smart homes. So here we can see the time element involved in short term adoption. On a macro time scale however, “Is the adoption of superior technology in evitable?” remains an important question.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 114. bindiya | 327d February 11th, 2007 at 2:01 pm
I agree with the theory made my Roger that something more than just beneficial change is necessary for diffusion and adoption of innovation to occur. In today’s competitive market, the way a product is promoted and positioned in its initial phase is crucial. Take for example Apple’s I- Phone. Even before this “technological innovation” is available for purchase there is an enormous amount of hype around it. The early adoption phase for this innovation is going to be pretty easy. The way the product is marketed influences its initial sales greatly. Although the product might not be adopted by all sections of society, it definitely will take off more initially than a poorly advertised product.
What intrigues me is the question whether a better marketed product will eventually diffuse better into society than a product which is more beneficial but poorly advertised. My opinion is that although word of mouth is very powerful, it’s equally important to position and market the product well.
Back tracking a little into the development phase, I think it is important to identify un-met needs of customers and center the development around customers needs. It is unrealistic to just develop something without thinking of the target audience. One has to identify not only the primary market, but even the secondary market of the innovation. A lot of market segmentation and research has to be done before the development phase. Today “Usability Assessment” is a buzz word in almost all companies dealing with innovation. The “boiling water case” reinforces the theory that one should be “client- oriented” rather than “innovation-oriented” for the innovation to diffuse rapidly.
For example last fall, I was part of a team developing protective clothing against harmful pesticides for Farm workers in Central valley, California. We did a lot of on-field research, went to the farm- workers houses to observe them in their natural environment, heard stories from them and eventually came up with our prototype. Our strategy was to develop something which will fit easily into their lives and at the same time benefit them to a great extent. We decided not to come up with something that would seem alien to them since our research predicted that they would not end up using it. The switching costs would be very high for them to handle and it would prove very difficult to convince them to change certain routine ways of doing things. So we decided to model our product around their routine and fulfill un-met needs in their cycle. At the end of the project, although the projected cost was slightly higher than we thought they would be ready to pay for, the farm workers seemed very enthusiastic about the product although it would create potential budget problems. The reason for this was that we followed a client centric approach rather than a purely innovative approach. Another important reason for our success was that their leader endorsed and supported our project which created trust in their minds. I related greatly to this project while reading about opinion leaders being very influential when it comes to diffusion of innovation.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 115. johnson | February 11th, 2007 at 2:34 pm
The only diffusion I’m familiar with is the process found in chemistry. Looking at diffusion of innovation in society was a new and refreshing twist to the concept for me. The rate at which something is adopted has never been something I considered. But from what I’ve accrued, yes, I can see it is a slow process. Some things that are so useful to some can take ages to gain acceptance and that’s entirely understandable. I think many people are comfortable with their lives and frown upon change. Why change when you’re content with your life? The adoption and acclamation to the computer era is a perfect example. There are still those regions in our innovative society that refuse to use the computer. It not for monetary reason or complexity issues that serve as the deterrence but some just don’t care for it. The early adopters of an innovation differ greatly from the rest of society. Their thirst for novelty allows them to test out everything but unfortunately, they make up a small portion of the whole.
Rogers pointed out that the public health worker erred when she did not take into consideration the social network. As the reading states, “diffusion of innovation is a social process.” The Peruvian wives and boiling water example pointed out an aspect of society that caught my interest. Conformity influences adoption of innovation - that’s a concept I’m not familiar with, or at least have not stopped and wondered about. You’ve got to have guts to try out new things as it an attempt to go against the grain and hope that you change the grain for that matter. This gamble that people take can risk their social standing in a society and that’s really disheartening to grasp. In an ideal place, we wouldn’t be so judgmental and would willingly open ourselves to new ideas as there’s always room for improvement. As we can see from the four elements, diffusion can be treated as a science. This concept kept my interest as it discussed the different components of the science and clearly described the processes, principles, and subjects involved.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 116. nfultz | February 11th, 2007 at 2:36 pm
Read the stuff on diffusion, and I remembered Eric Sink’s old article on Marketing for Geeks. Same ideas, mostly, but written for people like me instead of for social scientists. I’d rather read about the diffusion of say, linux, than best practices among Brazilian farmers.
Anyway, I thought Valente (esp ch 3) was pretty good, but if you’re going to use graph theory, you might as well go all the way. Instead of using a similiarity matrix for the korean farmers, why not use a distance matrix (or is this the same as the geodesic calculations)? Math people like those more, although you can use the same techniques on either. And instead of assumming that all relationships are the same (and reciprocal), you could use a weighted directed graph. If you got the weights right (basing them on distance would be a good place to start, but weight them so they are probabilities), you could do some time-series stuff on the initial matrix and compare that against the actual adoption patterns. It sounded like this is what the flow matrix was for, but the discussion about what you could do with that was brief and felt tacked on, and they never used the phrase ‘time series’ and never compared the flow matrix model to the observations. Do they cover this stuff in later chapters?
It was also interesting that individual network density had a minimal correlation to innovativeness. That kinda goes against social causation, no? The community network density was strongly correlated to rate of adoption, although also not correlated to innovation. So diffusion in tight-knit communities is faster, but innovation is a constant.
Anyway, this weeks reading actually was a little relevant, because I’ve been messing with the Facebook Movie theatre problem.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 117. evynn | February 11th, 2007 at 4:14 pm
Though it seems counterintuitive at first glance, I did not find the dense-network aversion to technology innovations at all surprising when I began to think about a few examples. My first thought was of high school cliques, which are fairly exclusive in terms of membership, but then teenagers as a whole do pick up new trends pretty quickly, so they may not be the best group for thinking about the adoption of innovations question in this case. A readily available example of a group that innovations have an extremely hard time penetrating is the Amish. Though they do not reject all innovations conceived after the 17th century, they usually do not adopt them without a great deal of careful deliberation and qualifications on their use. There are telephones in Amish communities, for example, but they are not generally in people’s homes and they are only used in emergencies or as absolutely needed to contact outsiders.
But examples can be found closer to home as well. Academic departments, in some ways, can be extremely dense when it comes to some innovations. Case in point, I know some organizers from a union for academic student employees. A major hurdle to gaining new members can be the social ties within many departments– if someone in the department has had a bad experience with someone or something thing they perceive as being connected to the union, other students are more likely to trust that person’s assessment than the union organizer, the outsider. Even on a scholarly level, some departments can be wary of theoretical perspectives that are not compatible with those of the senior faculty (again, this is anecdotal, and in no way a critique of the iSchool). It’s not always simply a matter of the expertise of the faculty– it can affect hiring (limiting faculty to people who follow the same theoretical models) and how students’ independent research is critiqued in the advising context.
This brings up an interesting contrast. We think of university departments as breeding grounds for innovations: Why should they be averse to them in some cases? Of course, any network has cultural idiosyncrasies that make it more or less likely to adopt any particular innovation. To go back to the Amish example, they are actively trying to maintain a very specific interpretation of what it means to live a godly life, which involves simplicity, humility and modesty. But I think the aversion to innovation in some academic departments may actually stem from the same goals and qualities of their members that make them innovators in the first place. The progress of many areas of scholarship requires detailed, critical examination of new ideas and discoveries, and the work requires a great deal of communication with other people studying the same problems. The attitudes and behavior these factors engender surely reach beyond the narrow confines of the academic work. I’m not saying that academics are likely to be insular and hostile to outside innovations in general– both the examples I cite are, significantly, closely related to academic life and culture– but I think it’s worth being aware of the unique practices and mind-sets that affect which innovations a particular group adopts. Regardless of network density, these may be very important, even determining factors in some diffusion instances.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 118. k7lim | February 11th, 2007 at 4:47 pm
I feel that too much emphasis is placed on the “change agents,” namely they get too much credit for encouraging adoption, and the implication that they are asserting themselves on the social system doesn’t quite ring true to me.
A more interesting question to me is, who are the ideal change agents, who are the people who actually take it upon themselves to catalyze adoption, and then what is the disparity, and how can that be narrowed in the next iteration? A perfect case in narrowing of the disparity comes in the arc from no-name captain who cures scurvy to medical doctors to the way contemporary medical innovations are diffused by way of doctors who have more influence and qualification in making change-agent-style assertions.
Why is “agent” status only conferred on this exceeding minority? Surely, a social system acts upon its own set of potential change agents, as well as innovations?
In a way, laggards can act on change agents, signalling the end of life for a given innovation, and inciting those who are literally ahead of the curve to indeed be firmly planted on something new. I doubt that fashion is unique; to look at a cycle of adoption and decay is fundamentally useful to studying these things.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 119. jilblu | February 11th, 2007 at 5:05 pm
The diffusion of innovation readings this week remind me of a great Malcolm Gladwell article I read years ago called “The Coolhunt.” Here is the link to the article on Gladwell’s site: http://malcolmgladwell.com/1997/1997_03_17_a_cool.htm.
The article is about “coolhunters”, people who are hired by fashion companies to search the street for the latest trends. In one example, a coolhunter who works for Reebok drives around the streets of the Bronx and Harlem, looking for cool kids so that she can show them the latest sneaker prototypes and get their reactions.
According to the article, fashion used to be “trickle-down”: couture houses use to set the trends, and the market would follow. Sometime within the past few decades, fashion became “trickle-up”: designers now look to the street for the latest trends, and then design their products according. Fashion trends are now set by cool young people who always want to be on the cutting edge – they’re always looking in the thrift store bins for something different to wear. Since their definition of cool is something that no one else is doing, these people are impossible to market to. It is the coolhunter’s job to find these cool kids, figure out what they’re doing, what they like, and then report these results back to the fashion industry. From the article, “The paradox, of course, is that the better coolhunters become at bringing the mainstream close to the cutting edge, the more elusive the cutting edge becomes. This is the first rule of the cool: The quicker the chase, the quicker the flight.”
To tie this back to this week’s readings, these cool kids are innovators. They aren’t connected to group social norms; in fact, they actively seek not to conform. As mentioned in the readings, innovators and opinion leaders don’t usually have high social status. The cool kids in the article definitely don’t have (or want) social status; they’re black urban youths and other members of the cultural fringe. In fact, many fashion trends are inspired by society members who have the very LEAST status: low-hung, baggy pants came from teen-agers who were imitating the garb of prisoners, teen-age girls in LA imitate Mexican gangsters. And unlike in the innovation examples discussed in the readings (hybrid corn, birth control, medical technology), the innovators of fashion actually abandon their own innovations as soon as they are discovered by the early adopters.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 120. igorp | February 11th, 2007 at 9:08 pm
Looking at the total number of blog posts for this week, and typing this in myself a week late, I think it appropriate to analyze the phenomenon of blogging in light of this week’s reading. So, how is diffusion of blogging carrying on? As someone who is clearly completely out of the blogging loop, and not sorry about it, I can not claim to have my finger of the community pulse, only on my own, sometimes.
So, according to Valente, which would apply to blogging, diffusion or collective behavior? I thin it most neatly fits into the collective behavior category. In this class, for example, we “rely on some vague perception of normative behavior”. Specifically that blogging is an acceptable social technology. The risk of engaging is considerably lower than, for example, sinking money into a brand new wax tablet sold by Microsoft, and the outcome of engaging is pretty clear. However we shouldn’t forget there is a “network externality” forcing a students/blog relationship different than would exist under normal economic principles. Nonadoption is not a great option. Doubtless, many students new to the activity will be forced to adopt it at least for the semester and some will carry the contagion process beyond May. Still, some of us, with huge thresholds (myself included) will choose a path of discontinuance and proudly count ourselves in the (1 – (saturation)) percentage. In fact, some (ahem) believe that blog exhaltators are a somewhat limited group and their predictions that everyone will be using blogs are an example of pluralistic ignorance (some artistic license claims here). In fact, according to the spiral of silence theory, everybody will admit this as soon at the next doc com bubble bursts and Technoratti will go bust. Lack of current complaints is completely due to self indulging early adopters and collective conservatism. The decay process will be swift!
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 121. nfultz | February 11th, 2007 at 11:55 pm
Jill: Scott Westerfeld wrote a YA adventure novel about cool hunters: So Yesterday. It’s a quick fun read.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 122. eunkyoung | February 12th, 2007 at 9:31 am
In Roger’s book, he mainly used the term “innovation” as same as “technology”. However, I am thinking about adoption in a broader way. Why am I buying a toner that I have never used before? Why do I buy a book written by an author whom I’ve never heard of? Why am I going to a movie theater to watch a movie without knowing that I’ll like it or not?
In many cases, we refer to other people’s reviews. Many internet bookstore, movie ticket websites, and other internet shopping malls have their own review system closely interlocked with their shopping catalogue. People do care about other’s opinion, especially that are written by an “authorized reviewer”. To find a good book or movie of my taste, I’d better find authorized reviewers and read their writings. Today’s opinion leaders are bloggers, reviewers, commentators and journalists.
Speaking of adopting new things in these days, it seems that we cannot say anything without internet. I don’t consent to Valente’s idea - the relationship between “opinion leader” and “early adopter” that every opinion leader is early adopter (though reverse is not always the case). Opinion leader doesn’t have to be an early adopter. They can even turn 70s forgotten fads into today’s big hit. Today’s opinion leaders are those who can write and read, who can do the blogging and writing reviews. Everyone have influence upon everybody through blog, internet shopping mall and opinion section of a newspaper.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 123. jerryye | February 13th, 2007 at 3:00 am
Is there anything about diffusion of technology that didn’t seem apparent or just as easily deduced. People tend to fall into groups ranging from the more adventurous types to the more conservative. Younger people tend to fall into the earlier group and older people in the later. The phrase “old habits die hard” has meaning to it and real consequences. Adoption of a new technology depends on how much an individual or corporation has invested in it. If a company’s sole source of revenue relied on legacy software, you would hope that they thought twice about upgrading their infrastructure.
People tend to be social, we try to get our ideas across and see what others are up to. It’s only a matter of time before people know each other well enough to trust or distrust someone on certain matters. The likely scenario that would arise is that you would get groups that adopt technologies early, and have a fraction of those be complete idiots and not know what they are doing and have another fraction that utilizes the technology well and knows how to flaunt it. Opinion leaders will obviously arise and so the adoption phase begins until even grandma has an iPod.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 124. mcd | February 13th, 2007 at 11:35 am
Ack! I’m late, but if it’s not 12:30, it’s still last week, right?
I’ve been thinking about a problem with Valente’s theories that he acknowledges dismissively, namely that the theories only apply to successful innovations. This, of course, makes sense because of the vastly greater available data and the retroactive nature of the studies, but I think it’s interesting to question how the spaces of success, failure, early adopters, and opinion leaders overlap. Building on Elisa’s insightful proposition that we were only examining half of the problem space, I drew some diagrams:
Option 1 (Thanks, Elisa)
Option 2
Option 3
One conclusion I found particularly suspect was that all opinion leaders are early adopters. I think there is potential validity to options 2 and 3 where there are opinion leaders who do not adopt, thus influencing, in whole or in part, the success or failure of a particular innovation.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 125. jess | February 13th, 2007 at 12:10 pm
This week’s readings about diffusion mainly focused on the social processes behind the diffusion of an innovation. However, I think it’s important to also consider the monetary rationale for diffusion. Both the dust bowl and ecotourism are situations (like many other natural resource examples) where the involved parties require monetary incentives, rather than social processes to adopt new innovation.
The dust bowl is referred to the hardship experienced by farmers of the Great Plains in the 1930’s. These lands were originally grasslands that were converted to agriculture fields. And as a result of drought, heavy winds, and over-cultivation, crops were unable to grow. The innovation to improve the soil and general growing climate was for farmers to cease their plowing of the land. However, farmers could not realistically adopt such an innovation, without crops there was no mechanism for farmers to make money or produce their own food. Only when the federal government began rewarding farmers for sustainable farming practices could farmers actually cease plowing the land.
Ecotourism is a practice where landowners have the opportunity to preserve their land and encourage sustainable tourism. Instead of generating revenues through development of the land or extraction of natural resources (such as mining or logging), landowners can generate revenues from its tourists. In this case the innovation to protect natural resources is to not develop on or extract resources from the land. However, without the revenue generated by tourists, landowners would not have incentive to adopt this innovation.
In these situations there isn’t a social incentive to adopt innovations. Unlike luxury goods, such as the adoption of an iPod, farmers and landowners are concerned about whether the adoption of an innovation will prevent them from feeding their families. Only with monetary incentives, such as subsidies from the federal government and tourism revenue, will the above natural resource innovations actually be implemented.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 126. Bernt Wahl | February 22nd, 2007 at 1:31 pm
Considering a Technological Singularity
With the readings fresh in mind, I happened to cross the innovation diffusion notions with the idea of an approaching technological singularity. That is, the acceleration of innovation is so great that we’ll reach a point where the slope of growth will be so steep that many changes will happen in a very very short period of time. This idea has been made popular recently due to the release of Ray Kurzweil’s book, _The Singularity is Near_. Also, one of the original people to talk of singularity, Vernor Vinge, is giving a talk in San Francisco this Thursday evening.
Talk of singularity seems absurd in the light of Rogers et al… For a given innovation, there is so much between introduction and adoption. So how can we possibly talk of some mass adoption that occurs in very little time? Vinge thinks that the singularity will have to to with A.I. achieving some breakthrough, and Kurzweil talks about “spiritual machines.” Perhaps “bots” or “agents” will have something to do with the singularity? What do these programs that we assign trust and agency (not to mention human traits) have to do with the adoption curves?
How can we reconcile these two camps?
Vinge’s Talk:
http://upcoming.org/event/138377/
Add comment February 13th, 2007 posted by: k7lim
Newsgroups (Internet Discussion Groups)
In the early 1990’s Newsgroups (Internet Discussion Groups) played an integral part in the research collaboration. It was comprised for the most part of scientists or university students that had access to Internet communications. The bar consisted of gaining Internet access. There was a level of self-regulation observed by members enjoying the access of an almost utopia online society. If you did not fit in one there were hundreds and eventually thousands of others you could join. What kept it special was your peer group’s devotion to a specified topic; often leading players in a field would be members of their related group. I remember being a part of the ‘fractal’ group. If I had a challenging question there was usually someone who could point me in the right direction. It was a close group. Over time as the group grew it lost its focus and the academic elements became more watered down as more users started posting more general questions. Over time the value that the site provided for users waned and I was back to sending emails to my more intimate circle of fractal mathematician friends.
February 22nd, 2007 at 1:31 pm |If academic networks are to work, it is most likely in the context of a core of individuals that derive benefits of the association of its members. When that goes away the value diminishes.
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SELECT * FROM is203_users WHERE ID = '1' LIMIT 127. Bernt Wahl | February 22nd, 2007 at 1:34 pm
Additional Diffusion Models
Everett Rogers work, Diffusion of Innovations (1995) provides a structure on how information and knowledge is disseminated throughout a give body of potential adapters. In the derivative work, the book Crossing the Chasm by Geoffrey A. Moore (1991), the author builds on Everett Roger’s Diffusion Models by examining the diffusion of innovations through variable means. By adding the concept of a Chasm to Diffusion Models, potential barriers are put in place that can disrupt a cascading adoption to an expanded set of users. Built on Rogers and Moore works potential theories I would increase the distinct stages to: pre-chasm inventors (those who create or make contribution elements to the actual product), innovators (those who define its uses), initial adaptors (e.g. tech-heads who gravitate to new objects), and post-chasm crowd of: early adaptors, late adaptors and laggards. Rogers’ models are largely based on a simplistic epidemic diffusion model.
February 22nd, 2007 at 1:34 pm |In real life the epidemic diffusion model can prove to limited in the realm of prediction. The ‘classic’ epidemic prediction model has been revised and expanded to deal with resistance and immunity. This can be seen in two updated models Verhulst Equation and the Predator-Prey models. These models deal with changing parameters, limited penetration and saturation barriers. These diffusion models contend with issue of variability by introducing factors that cascade, pulsate and oscillate information/disease dissemination.
Historic Note: The Population Growth Model has its origins from work done by Belgian mathematician Pierre Verhulst (1804-1849) in which he describes models with restrictive growth. These models would in later decades be used by others to explain Gypsy Moth populations, Measles outbreaks, predator-prey models , along with various other models with contained growth. One main propose behind the Population Model is to pattern growth cycles found in real world systems, systems that can not continue unconstrained for an indefinite period. In nature eventually resources such as food or land get depleted to such an extent that competition for resources result in starvation or conflicts that reduces growth or even diminishes a population. These models have variations that fluctuate greatly, if they settle down to a single value we say that it is steady state system. If it splits into a transition of periodic points we say this process has bifurcated. When this bifurcation becomes indeterminable where the slightest change cause drastically different results, it is said to have reached its chaotic stage.
Reference:
Rogers, Everett M. 1995. Diffusion of Innovations. New York, NY: Free Press.
Geroski, P.A. 2000. ìModels of technology diffusion.î Research Policy 29:603-625.
Chapters 1-3 in Valente, Thomas. 1995. Network Models of the Diffusion of Innovations. Cresskill, NJ: Hampton Press.
Wahl, B. Exploring Fractals (1995) Addison-Wesley
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