Category Archives: Innovation

Measuring Originality in Science

Source: Springer, Nov 2019

We conceptualise originality as the degree to which a scientific discovery provides subsequent studies with unique knowledge that is not available from previous studies.

Specifically, we measure the originality of a paper based on the directed citation network between its references and the subsequent papers citing it. We demonstrate the validity of this measure using survey information. In particular, we find that the proposed measure is positively correlated with the self-assessed theoretical originality but not with the methodological originality.

We consider originality to be rooted in a set of information included in a focal scientific paper. However, we argue that the value of the paper is realised through its reuse by other scientists, and that its originality is established through its interaction with other scientists and follow-on research (Latour and Woolgar 1979; Merton 1973; Whitley 1984).

Base measure

We propose to measure the originality of an individual scientific papers based on its cited papers (i.e., references) and citing papers (i.e. follow-on research). We draw on subsequent papers that cite the focal paper to evaluate whether the authors of these subsequent citing papers perceive the focal paper as an original source of knowledge (Fig. 1A).

Suppose that the focal paper X cites a set of prior papers (reference set R) and is cited by a set of subsequent papers (citing set C). If X serves as a more original source of knowledge, then the citing papers (i.e., papers in citing set C) are less likely to rely on papers that are cited by X (i.e., papers in reference set R). In contrast, if X is not original but an extension of R, then C will probably also cite R together with X. In other words, we exploit the evaluation by the authors of follow-on research to measure the originality of the focal paper.

In conclusion, this study proposes a new bibliometric measure of originality. Although originality is a core value in science (Dasgupta and David ; Merton ; Stephan ; Storer ), measuring originality in a large scale has been a formidable challenge. Our proposed measure builds on the network betweenness centrality concept (Borgatti and Everett ; Freeman ) and demonstrates several favourable features as discussed above. 

Progress Studies

Source: AIER, Aug 2019

My work has argued that nations that are open to risk-taking, trial-and-error experimentation, and technological dynamism (i.e., “permissionless innovation”) are more likely to enjoy sustained economic growth and prosperity than those rooted in precautionary principle thinking and policies (i.e., prior restraints on innovative activities).

Collison and Cowen suggest that “there can be ecosystems that are better at generating progress than others, perhaps by orders of magnitude. But what do they have in common? Just how productive can a cultural ecosystem be?” Beyond gaining a better understanding of how innovation ecosystems work, they also want to nurture them. “Can we deliberately engineer the conditions most hospitable to this kind of advancement or effectively tweak the systems that surround us today?” they ask.

Mokyr has argued that technological innovation and economic progress can be viewed as “a fragile and vulnerable plant, whose flourishing is not only dependent on the appropriate surroundings and climate, but whose life is almost always short. It is highly sensitive to the social and economic environment and can easily be arrested by relatively small external changes.” McCloskey’s work has shown that cultural attitudes, social norms, and political pronouncements have had a profound and underappreciated influence on opportunities for entrepreneurialism, innovation, and long-term economic growth

Many scholars have surveyed the elements that contribute to a successful innovation culture and their lists typically include:

  • trust in the individual / openness to individual achievements;
  • positive attitudes towards competition and wealth-creation (especially religious openness toward commercial activity and profit-making);
  • support for hard work, timeliness, and efficiency;
  • willingness to take risks and accept change (including failure);
  • a long-term outlook;
  • openness to new information / tolerance of alternative viewpoints;
  • freedom of movement and travel for individuals and organizations (including flexible immigration and worker mobility policies);
  • positive attitudes towards science and development;
  • advanced education systems;
  • support for property rights and contracts;
  • reasonable regulations and taxes;
  • impartial administration of justice and the respect for the rule of law; and,
  • stable government institutions and transfers of power.

 

Innovation Dispersion

Source: MIT Technology Review,  Jan 2017

The rate at which innovations appear and disappear has been carefully measured. It follows a set of well-characterized patterns that scientists observe in many different circumstances. And yet, nobody has been able to explain how this pattern arises or why it governs innovation.

The notion that innovation arises from the interplay between the actual and the possible was first formalized by the complexity theorist Stuart Kauffmann. In 2002, Kauffmann introduced the idea of the “adjacent possible” as a way of thinking about biological evolution.

The adjacent possible is all those things—ideas, words, songs, molecules, genomes, technologies and so on—that are one step away from what actually exists. It connects the actual realization of a particular phenomenon and the space of unexplored possibilities.

But this idea is hard to model for an important reason. The space of unexplored possibilities includes all kinds of things that are easily imagined and expected but it also includes things that are entirely unexpected and hard to imagine. And while the former is tricky to model, the latter has appeared close to impossible.

What’s more, each innovation changes the landscape of future possibilities. So at every instant, the space of unexplored possibilities—the adjacent possible—is changing.

“Though the creative power of the adjacent possible is widely appreciated at an anecdotal level, its importance in the scientific literature is, in our opinion, underestimated,” say Loreto and co.

Nevertheless, even with all this complexity, innovation seems to follow predictable and easily measured patterns that have become known as “laws” because of their ubiquity. One of these is Heaps’ law, which states that the number of new things increases at a rate that is sublinear. In other words, it is governed by a power law of the form V(n) = knβ where β is between 0 and 1.

Words are often thought of as a kind of innovation, and language is constantly evolving as new words appear and old words die out.

This evolution follows Heaps’ law. Given a corpus of words of size n, the number of distinct words V(n) is proportional to n raised to the β power. In collections of real words, β turns out to be between 0.4 and 0.6.

Another well-known statistical pattern in innovation is Zipf’s law, which describes how the frequency of an innovation is related to its popularity. For example, in a corpus of words, the most frequent word occurs about twice as often as the second most frequent word, three times as frequently as the third most frequent word, and so on. In English, the most frequent word is “the” which accounts for about 7 percent of all words, followed by “of” which accounts for about 3.5 percent of all words, followed by “and,” and so on.

This frequency distribution is Zipf’s law and it crops up in a wide range of circumstances, such as the way edits appear on Wikipedia, how we listen to new songs online, and so on.

these systems involve two different forms of discovery. On the one hand, there are things that already exist but are new to the individual who finds them, such as online songs; and on the other are things that never existed before and are entirely new to the world, such as edits on Wikipedia.

Loreto and co call the former novelties—they are new to an individual—and the latter innovations—they are new to the world.

Curiously, the same model accounts for both phenomenon. It seems that the pattern behind the way we discover novelties—new songs, books, etc.—is the same as the pattern behind the way innovations emerge from the adjacent possible.

That raises some interesting questions, not least of which is why this should be. But it also opens an entirely new way to think about innovation and the triggering events that lead to new things. “These results provide a starting point for a deeper understanding of the adjacent possible and the different nature of triggering events that are likely to be important in the investigation of biological, linguistic, cultural, and technological evolution,” say Loreto and co.

Instilling Innovation via Words

Source: The Baffler, 2019

innovation in its most dominant form today is a kind of spirit, a way of being, an attitude.

Drucker said that what distinguished an “‘underdeveloped country’—and keeps it underdeveloped—is not so much a shortage of capital as it is shortage of innovation.”

3,000 Raw Ideas = 1 Commercial Success

Source: Winovations.com, date indeterminate

Research Reference:

Greg Stevens and James Burley, 3,00 Raw Ideas = 1 Commercial Success, Research Technology Management, 40(3), May-June 1997, 16-27.

Paul Romer – interviewed by Tyler Cowen

Source: Medium, Dec 2018

My number-one recommendation is to invest in people. Humans that are well trained are the inputs into this discovery process. And there’s big opportunities still, I think, to do a better job of investing in people.

I think it’d be very helpful if there were a lot more students looking at the far future, saying, “Where are the big opportunities? What do I really want to learn about to have an exciting career?” If those students controlled tuition resources that universities were competing for, the universities would be more responsive to the changing landscape.

’ve always been a little bit more inclined to take risks or maybe to sample a lot more ideas. I sometimes make fun of myself by saying, “I’m just a random idea generator.” And then what’s neat is, others who can filter out the bad ones — then on average I could be helpful.

COWEN: And you also think we should simplify the English language. Right?

ROMER: [laughs] Well, there’s two parts to that. One is, in writing and communication, there should be a very high priority on clarity.

Democracy Supports Innovation

Source: Wiley Online Library, Oct 2018

we propose a new institutional theory that identifies democracy’s unique advantage in prompting economic growth.

We contend that the channel of liberty‐to‐innovation is the most critical channel in which democracy holds a unique advantage over autocracy in promoting growth, especially during the stage of growth via innovation.

Our theory thus predicts that democracy holds a positive but indirect effect upon growth via the channel of liberty‐to‐innovation, conditioned by the level of economic development. We then present quantitative evidence for our theory. To our best knowledge, we are the first to propose such an indirect and conditional effect of democracy upon economic development and provide systematic evidence.

Our study promises to integrate and reconcile many seemingly unrelated and often contradictory theories and evidence regarding regime and growth, including providing a possible explanation for the inconclusive results from regressing overall regime score against the rate of economic growth or change in level of GDP per capita.