Creativity=recombination, Jedi edition

Where do great ideas come from? A popular notion among creativity experts is that recombination of preexisting ideas in a new context is the form that most if not all creativity takes. One more datum: Courtesy of my lovely wife, it seems that George Lucas may have been voguing, so to speak, when he came up with one of his most iconic images. 


Neuroeconomic imperialism?

I just saw a recent article in the Chronicle of Higher Education on the emerging field of neuroeconomics. Unlike behavioral economics, where ideas from psychology have been ported over to economics to explain various individual “anomalies” in choice behavior, in neuroeconomics much of the intellectual traffic has gone in the other direction–economic modeling tools are helpful in understanding psychological processes (including where those processes deviate from classic economic theory). The axiomatic approach to choice makes it a lot easier to parse out how the brain’s actual mechanisms do or don’t obey these axioms.

An important guy to watch in this area is Paul Glimcher, who mostly stays out of the popular press but is a hardcore pioneer in trying to create a unified (or “consilient”) science encompassing neuroscience, psychology, and economics. I’ve learned a lot from reading his Foundations of Neuroeonomics (2010) and Decisions, Uncertainty, and the Brain (2004): why reference points (as in prospect theory) are physiologically required; how evolutionary theory makes a functionalist and optimizing account of brain behavior more plausible than a purely mechanical, piecemeal, reflex-type theory; why complementarity of consumption goods presents a difficult puzzle for neuroscience; and much more.

Read the rest of this entry »


Motivation Trumps IQ. What now?

An article recently posted in Slate reviews research showing that a significant portion of the variation in IQ tests is attributable to motivation rather than ability. In one striking study researchers measured the children’s IQ and split them into High, Average, and Low groups. They reran the test offering the low group an M&M for every correct answer. As a result of this simple incentive, the low group’s score went from 79 to 97 – on par with the average group.

Ok, so incentives work. Perhaps not a big surprise on many levels.

On the other hand, there is a large OB/HRM literature invested in the conclusion that performance increases are associated with hiring employees with a higher IQ. The assumption there is that IQ measures ability as opposed to motivation.

This raises a critical question for strategy scholars. Is motivation an immutable attribute of human capital Read the rest of this entry »


A Fly in the Ointment…

An article in today’s New York Times highlights a dramatic increase in the price of generic ointments over the last few years — generics have gone up 6 to 7 times their 2008 prices. Here is a chart showing the climb in prices for a few products. Before you say, this is clearly fallout from the new healthcare law, the article doesn’t point to any change in legislation covering ointments. In fact, there is a certain amount of puzzlement over why prices have gone up so much.

They note that doctors are not price sensitive when they write prescriptions and patients do what doctors recommend — that’s nothing new.

It turns out that regulation for generic skin treatments is more stringent than other generics because they must demonstrate that products are absorbed as well as the original treatments. This, more costly process creates higher entry barriers for generic ointments Read the rest of this entry »


Entrepreneurship: Exploring (or Building) Adjacencies

Because I write and teach about innovation and strategy, friends and students often ask me to evaluate their new business ideas. A relatively large percentage of these business ideas are about a product the individual somehow identifies with, but in an area in which the individual has no work experience. The mythology of entrepreneurship is that it’s all about great ideas. The reality is that great ideas are a dime a dozen; successful entrepreneurship is much more closely linked to the ability to execute. How do people learn to execute? In general, it’s through having deep experience somewhere in the value chain. In other words, most successful entrepreneurship is accomplished through exploring (or building) something adjacent to where you already are or have been. If, for example, you have worked for an interior design firm for several years, and you travel to South Africa and see beautiful and unusual textiles you would like to be able to use in your practice, but no one is importing these textiles, you are in a much better position to create such an import business (and to know what it’s worth, and how to reach the target market) than another tourist who sees the beautiful textiles and wonders why the interior designer she has hired hasn’t shown her anything so unique.

Adjacent positions give you insight into the value chain of your target area (Who are the likely suppliers? What is their cost structure like? Who are the buyers? How are they used to being presented with goods to choose from? How big is the market? How are the logistics typically handled?). Adjacent positions can also help you identify valuable problems to solve (What aspects of the currently available products or business model are inefficient or irritating? What new innovation would exceed customer expectations, and how much more would they pay for it?). Perhaps most importantly, occupying an adjacent position means you are more likely to have valuable network contacts to lubricate your entry – for example, already having a relationship and credibility with distributors will usually have a big impact on the rate at which you can enter a market.

What if you love an idea, and are motivated to execute on it, but aren’t in an adjacent position? Build one. Consider working (or interning) for a firm that is either upstream or downstream in the value chain you will be entering. If you can offer up your effort at a low cost (preferably free) for at least a few hours a day, you can usually edge your way into just about any business. You could also consider working for someone who will ultimately be your competitor, but working for someone who will be your supplier or your customer is more likely to engender goodwill in the value chain, and help you accrue valuable contacts that you will use in your new business.

A case in point: My good friend, Rick Alden, founded a company called Skullcandy in 2003 that makes, primarily, headphones with an edgy, extreme sports aesthetic.  I was initially skeptical of his idea to enter headphones – to me it was a commoditized product category dominated by companies that operate in countries with significantly lower production costs. Rick, however, was deeply embedded in an adjacent industry – snowboarding. He had founded National Snowboarding Incorporated in the 1980s (which promoted the sport of snowboarding and offered lessons and competitions), and had designed and patented the first ever step-in snowboard boot and binding system. His brother Dave was a pro-snowboarder for Burton, and his father Paul Alden had been one of the founders of the North American Snowboard Association which helped to create guidelines for teaching snowboarding and developed the snowboarding World Cup. In short, Rick knew snowboarders – he knew their aesthetic, and he knew their habits. He knew most of the major snowboarding manufacturers, snowboard shops, and snowboard pro-riders. So when Rick launched Skullcandy, he was not only in a great position to evaluate what design features snowboarders would respond to, he was also able to get endorsements from the most famous snowboarders, and get on the shelves of the best snowboard shops. Once he had captured that market, the mass market (Best Buy, college bookstores, etc.) eagerly demanded product. Within two years Skullcandy had surpassed a million in sales, and by 201 1 Skullcandy’s sales had reached $231 million.

Had Rick started by developing a mass market product and approached Best Buy, it is unlikely the story would have turned out the same. It is equally unlikely that someone outside of the extreme sports industry could have replicated what Rick did. It was Rick’s adjacent position that gave him the knowledge, the contacts, and the credibility to enter and succeed in this market.


Individual Bias and Collective Truth?

Freek’s latest post on confirmation bias notes that intellectual commitments can bias which research findings one believes. The tone of the post is that we would all be better off if such biases didn’t exist, but there is definitely a tradeoff here. Greater objectivity tends to go with lower intensity of interest in a subject. (Disinterested and uninterested are correlated, for those old-timers who remember when those words had different definitions.) That’s why you often find that those with strong views on controversial topics–including those with minority or even widely ridiculed opinions–often know more about the topic, the evidence, and the arguments pro and con than “objective” people who can’t be bothered to dig into the matter. Other than partisanship, the only thing that will get people interested enough to seriously assess competing claims is a personal stake in the truth of the matter. (And in all cases, Feynman’s admonition that the easiest person to fool is yourself should be borne in mind.)

Historians of science of all stripes, from romanticists like Paul de Kruif (author of the classic The Microbe Hunters) to sophisticated evolutionists like David Hull in Science as a Process, have reported that intellectual partisanship motivates a great deal of path-breaking research. “I’ll show him!” has spawned a lot of clever experiments. Burning curiosity and bland objectivity are hard to combine.

But how can such partisanship ever lead to intellectual progress? Partisans have committed to high-profile public bets on one or another side of a controversy; their long-term career and immediate emotional payoffs depend not directly on the truth, but on whether or not they “win” in the court of relevant opinion. The key to having science advance is for qualified non-partisan spectators of these disputes be able to act as independent judges to sort out which ideas are better.

Ideally, these adjacent skilled observers would have some skin in the game by virtue of having to bet their own research programs on what they think the truth is. If they choose to believe the wrong side of a dispute, their future research will fail, to their own detriment. That’s the critical form of incentive compatibility for making scientific judgments objective, well-described in Michael Polanyi’s “Republic of Science” article. If, for most observers, decisions about what to believe are closely connected to their own future productivity and scientific reputation, then the partisanship of theory advocates is mostly a positive, motivating exhaustive search for the strengths and weaknesses of the various competing theories. Self-interested observers will sort out the disputes as best they can, properly internalizing the social gains from propounding the truth.

The problem for this system comes when 1) the only scientific interest in a dispute lies among the partisans themselves, or 2) observers’ control over money, public policy, or status flows directly from choosing to believe one side or another regardless of the truth of their findings. Then, if a false consensus forms the only way for it come unstuck is for new researchers to benefit purely from the novelty of their revisionist findings–i.e., enough boredom and disquiet with the consensus sets in that some people are willing to entertain new ideas.


Fungibility v. Fetishes

For an economist studying business strategy, an interesting puzzle is why businesspeople, analysts, and regulators often don’t seem to perceive the fungibility of payments. Especially in dealing with bargaining issues, a persistent “optical illusion” causes them to fetishize particular transaction components without recognizing that the share of total gain accruing to a party is the sum of these components, regardless of the mix. Proponents of the “value-based” approach to strategy, which stresses unrestricted bargaining and the core solution concept, ought to be particularly exercised about this behavior, but even the less hard-edged V-P-C framework finds it difficult to accommodate.

Some examples:

  • There’s been some noise lately about U.S. telecom providers cutting back on the subsidies they offer users who buy smartphones. None of the articles address the question of whether the telecom firms can thereby force some combination of a) Apple and Samsung cutting their wholesale prices and b) end users coughing up more dough for (smartphone + service). The possibility that competition among wireless providers fixes the share of surplus that they can collect, so that cutting the phone subsidy will also require them to cut their monthly service rates, is never raised explicitly. There is a pervasive confusion between the form of payments and the total size of payments.

Read the rest of this entry »


A Causally Ambiguous Research Stream

I’m reporting from another great ACAC conference. This conference featured retrospectives marking the 30 year anniversaries for Nelson and Winter’s book and Lippman and Rumelt’s article. Kudos to Bill and the organizing committee for putting it together.

A starting similarity in the two is that they were both directly intended to influence conversations in economics and both missed their marks. For example, about 1% of the cites for Lippman and Rumelt were in top Econ journals – despite the fact that the article appeared in the Bell Journal of Economics. Lippman & Rumelt recorded a video specifically for the occasion Read the rest of this entry »


In the mail: Guitar Zero: A Neuroscientist Debunks the Myth of “Music Instinct”

When you read this, you realize just how little we really know about learning. Major implications for the study of strategy, of course. But, also, a glimmer of hope that I may one day pursue that long-abandoned rock career. Article here: Guitar Zero: A Neuroscientist Debunks the Myth of “Music Instinct” | Brain Pickings. Book here.


How much rationality is enough?

Last week I had the great good fortune to attend the Max Planck Institute at Leipzig’s first conference on Rigorous Theories of Business Strategies in a World of Evolving Knowledge. The conference spanned and intense four days of presentations, exploration, and discussion on formal approaches to business strategy. Participants were terrific and covered the scholarly spectrum: philosophers, psychologists, game theorists, mathematicians, and physicists. Topics included cooperative game theory, unawareness games, psychological micro-foundations of decision making, and information theory. It was heartening to see growth in the community of formal theorists interested in strategy and my guess is that the event will spawn interesting new research projects and productive coauthoring partnerships. (Thanks to our hosts, Jurgen Jost and Timo Ehrig for organizing and sponsoring the conference!)

If one had to pick a single, overarching theme, it would have to be the exploration of formal approaches to modeling agents with bounded rationality. For example, I presented on subjective equilibrium in repeated games and its application to strategy. Others discussed heuristic-based decision making, unawareness, ambiguity, NK-complexity, memory capacity constraints, the interaction of language and cognition, and dynamic information transmission.

Over the course of the conference, it struck me just how offensive so many of my colleagues find the rationality assumptions so commonly used in economic theory. Of course, rational expectations models are the most demanding of their agents and, as such, seem to generate the greatest outrage. What I mean to convey is the sense that displeasure with these kinds of modeling choices go beyond dispassionate, objective criticism and into indignation and even anger. If you are a management scholar, you know what I mean.

Thus, at a conference such as this, we spend a lot of time reminding ourselves of all the research that points to all the limitations of human cognition. We detail how humans suffer from decision processes that are emotional, memory constrained, short-sighted, logically inconsistent, biased, bad at even rudimentary probability assessment, and so on. Then, we explore ways to build formal models in which our agents are endowed with “more realistic” cognitive abilities.

Perhaps contrary to your intuition, this is heady stuff from a modeler’s point-of-view: formalizing stylized facts about real cognition is seen as a worthy challenge … and discovering where the new assumptions lead is always amusing. From the perspective of many management scholars, such theories are more realistic, better able to explain observations of shockingly stupid decisions by business practitioners and, hence, superior to the silly, overly simplistic models that employ a false level rationality.

I am not mocking the sentiment. In fact, I agree with it. Indeed, none of the economists I know dispute the fact that human cognition is quite limited or that perfect rationality is an extreme and unrealistic assumption. (This isn’t to say there aren’t those who believe otherwise but, if there are, they are not acquaintances of mine.) On the contrary, careers have been made in game theory by finding clever ways to model some observed form of irrationality and using it to explain some observed form of decision failure. If this is the research agenda then, surely, we have hardly scratched the surface.

Yet, as I thought about it during the MPI conference last week, it dawned on me that our great preoccupation with irrational agents is misdirected. That animals as cognitively limited as us often, if not typically, fail to achieve rational consistency in our endeavors is no puzzle. What else would you expect? Rather, the deep mystery is how agents so limited in rational thought invent democracy, create the internet, land on the moon, and run purposeful organizations that succeed in a free market. Casual empiricism suggests that the pattern of objective-oriented progress in the history of mankind is too pervasive to ascribe to dumb luck. Even at the individual level, in spite of their many cognitive failings, the majority of people lead purposeful, productive lives.

This leads me to remind readers that economists invented the rational expectations model precisely because it was the only option that came anywhere close to explaining observed patterns in economy-level reactions to changes in government policies. This, even though the perfect rationality assumption is axiomatically false. There you have it.

Which leaves open the challenge of identifying which features of human cognition lead to persistent patterns of success in highly unstable environments. I conjecture that our refined pattern recognition abilities play a role in this apparent miracle. Other candidates include our determination to see causality everywhere we look as well as our incredible mental flexibility. Social factors and institutions must be involved — and, somewhere in there, a modicum of rationality and logic. After all, we did invent math.


The case against interview-based research (and a plea for facts)

I’ll admit it; I am rapidly becoming a skeptic when it comes to interview-based data. And the reason is that people (interviewees) just don’t know their business – although, of course, they think they do. 

For example, in an intriguing research project with my (rather exceptional) PhD student Amandine Ody, we asked lots of people in the Champagne industry whether different Champagne houses paid different prices for a kilogram of their raw material: grapes. The answer was unanimously and unambiguously “no”; everybody pays more or less the same price. But when we looked at the actual data (which are opaque at first sight and pretty hard to get), the price differences appeared huge: some paid 6 euros for a kilogram, others 8, and yet other 10 or even 12. Thinking it might be the (poor) quality of the data, we obtained a large sample of similar data from a different source: supplier contracts. Which showed exactly the same thing. But the people within the business really did not know; they thought everybody was paying about the same price. They were wrong. 

Then Amandine asked them which houses supplied Champagne for supermarket brands (a practice many in the industry thoroughly detest, but it is very difficult to observe who is hiding behind those supermarket labels). They mentioned a bunch of houses, both in terms of the type of houses and specific named ones, who they “were sure were behind it”. And they quite invariably were completely wrong. Using a clever but painstaking method, Amandine deduced who was really supplying the Champagne to the supermarkets, and she found out it was not the usual suspects. In fact, the houses that did it were exactly the ones no-one suspected, and the houses everyone thought were doing it were as innocent as a newborn baby. They were – again – dead wrong.

And this is not the only context and project where I have had such experiences, i.e. it is not just a French thing. With a colleague at University College London – Mihaela Stan – we analyzed the British IVF industry. One prominent practice in this industry is the role of a so-called integrator; one medical professional who is always “the face” towards the patient, i.e. a patient is always dealing with one and the same doctor or nurse, and not a different one very time the treatment is in a different stage. All interviewees told us that this really had no substance; it was just a way of comforting the patient. However, when we analyzed the practice’s actual influence – together with my good friend and colleague Phanish Puranam – we quickly discovered that the use of such an integrator had a very real impact on the efficacy of the IVF process; women simply had a substantially higher probability of getting pregnant when such an integrator, who coordinates across the various stages of the IVF cycle, was used. But the interviewees had no clue about the actual effects of the practice.* 

My examples are just conjectures, but there is also some serious research on the topic. Olav Sorenson and David Waguespack published a study on film distributors in which they showed that these distributors’ beliefs about what would make a film a success were plain wrong (they just made them come true by assigning them more resources based on this belief). John Mezias and Bill Starbuck published several articles in which they showed how people do not even know basic facts about their own companies, such as the sales of their own business unit, error rates, or quality indicators. People more often than not were several hundreds of percentages of the mark, when asked to report a number.

Of course interviews can sometimes be interesting; you can ask people about their perceptions, why they think they are doing something, and how they think things work. Just don’t make the mistake of believing them. 

Much the same is true for the use of questionnaires. They are often used to ask for basic facts and assessments: e.g. “how big is your company”, “how good are you at practice X”, and so on. Sheer nonsense is the most likely result. People do not know their business, both in terms of the simple facts and in terms of the complex processes that lead to success or failure. Therefore, do yourself (and us) a favor: don’t ask; get the facts.

 

* Although this was not necessarily a “direct effect”; the impact of the practice is more subtle than that.


Reinventing discovery: the promise of open science

I’ve been skimming/reading through Michael Nielsen’s (pioneer in quantum computing) new (2012) book Reinventing discovery: the new era of networked science, Princeton University Press.  The book chronicles the various open science and open innovation initiatives from the past and present: Torvalds and Linux, Tim Gowers’ polymath project (see his post: is massively collaborative mathematics possible), the failed quantum wiki (qwiki) effort, Galaxy Zoo, collaborative fictionSloan Digital Sky Survey (SDSS)Open Architecture Network, Foldit, SPIRESPaul Ginsbarg’s arXiv, the Public Library of Science (PLoS), of course Innocentive, etc, etc.

My quick take on the book – it is a nice review of the existing forms that open innovation and open science are taking.  I’ve read or followed most of the above projects over the years so the book doesn’t cover too much new territory from that perspective.  The language in the book isn’t too precise –e.g., “network” isn’t very specific (I suppose in this case it simply means internet, broadly, and more general openness). But then again, this isn’t really an academic book (lots of great footnotes though).  But the book is a great review of some of the existing efforts in open innovation and open science.

But beyond detailing the many instances of increased openness in science, the book touches more generally on the possibilities of “citizen science” (David Kirsch posted about citizen science on orgtheory.net, see here).  I think there are lots of interesting possibilities: funding, tapping into cognitive ‘surplus,’ perhaps gamification, and many other forms of collaboration.  And the book leaves off with some important problems for and questions about open science.  How do you get the incentives right for openness?  Who should be the gatekeepers?  What institutions are needed to support openness?  Etc.

Here’s the author speaking at Google a few weeks ago:


Thinking fast and slow about terrorism insurance

This morning, my colleague Josh Gans and I sat in on a general audience talk by Daniel Kahneman about his new book Thinking Fast and Slow. It was interesting to see how the research agenda has progressed and evolved over the past couple of decades. This idea explored in this book, and in the talk, is that cognition can be broken into two “systems” — one that responds instantly and without effort and another that responds with will and effort. The example given to distinguish between the two was being asked to answer the following questions: (a) what is  2 + 2? and, (b) what is 17 x 24? The first comes unbidden and effortlessly to mind. The second requires conscious effort (which has several physiological traits associated with it, such as significant pupil dilation).

Kahneman is a terrific speaker and these issues are inherently fascinating. One of the examples raised a puzzle in Josh’s mind. The example is asking air travelers whether they want to buy insurance. When asked how much they are willing to pay for $100,000 worth of life insurance for an upcoming flight covering death due to any reason, subjects report a number. When asked how much they are willing to pay for $100,000 worth of insurance for death due to a terrorist attack (only), they report a substantially higher number. The reason given for this is that the “fast” system associates terrorism with fear and fear motivates higher willingness to pay for insurance.

The puzzle is: why do insurance companies specifically exclude terrorist acts from life insurance policies? Presumably, a”slow” thinking group of insurance executives could cash in on the “fast” thinking bias of travelers by inducing impulse purchases of terrorist insurance at ticket kiosks at the time of check-in. Yet they don’t. Having recently had some problematic insurance company dealings, Josh’s “fast” thinking answer was that insurance company execs are not very skilled decision makers. I am open to a more rational reason, though I cannot think of what it would be.


Turing Test and Artificial Intelligence

The Turing Test is a key test of artificial intelligence: can robots fool humans into thinking they are intelligent?  Despite optimistic projections for AI (e.g., Herbert Simon made some wild predictions),AI still underwhelms.  Well, in some areas (in chess, for example, computers beat humans).

Perhaps the Turing test isn’t the right measure of ‘intelligence.’  But chatbots have yet to fool humans that they actually are human.  The yearly Loebner prize puts this to the test, here’s the 2010 winner Suzette,  or the 2011 winner Rosette. Chat with either of the bots, or any other for that matter, and you’ll quickly see the problems.  Over at orgtheory.net we have ‘tested’ the winning chatbots several times – and inevitably they fail.

The clip below is a game show with some AI bots (ol’ Eliza versus Deep Blue versus an evolutionary algorithm – ok, it’s not the actual bots).

The best clip still is the chatbot v chatbot discussion at Cornell.

Here’s Ray Kurzweil a few weeks ago (at the 2011 Singularity Summit) talking about “from Eliza to Watson to passing the Turing Test.”


Innovator’s DNA

Since Jeff is my colleague – I better plug his recent (2011) book The Innovator’s DNA: Mastering the Five Skills of Disruptive Innovators, Harvard University Press.  The book is co-authored with Hal Gregersen (Insead) and Clayton Christensen (Harvard).

I just talked to Jeff about the book – interesting to learn about the intricacies of publishing a practitioner book.  The book is doing very well.  (I was at O’Hare airport a few weeks ago and it’s hard to miss the separate showcase that the book has at various bookstores.)

Jeff, Hal and Clay have also published a few articles related to the book in 2009:

Entrepreneur behaviors, opportunity recognition, and the origins of innovative ventures.  Strategic Entrepreneurship Journal. 

The Innovator’s DNA. Harvard Business Review.  

Be sure to check the book and articles out!


Psyched Out Strategy: What is a firm?

Glenn Hoetker recently gave me the opportunity to consider what new contributions the field of psychology could offer to the strategy literature (see the description here). The video illustrates how behavior often depends more on perception than on reality — does it matter if the steering wheel is attached or not if the other driver acts as if it is? Often, researchers are interested in organizational outcomes and theorize that the underlying behaviors are driven by objective reality. What research opportunities are highlighted as we take seriously the subjective nature of our most central constructs?

In this installment, we explore the question, “what is a firm?” This is so taken for granted in the field that most of you will probably stop reading here. Read the rest of this entry »


Time-critical social mobilization

The most recent issue of Science has a very practical and interesting piece on time-critical social mobilization (here’s the non-gated arXiv version).

The article recounts the winning team’s strategy in the DARPA network challenge – a challenge where 10 red weather balloons were placed in locations throughout the US.   The winning MIT team found them all in less than 9 hours: check out their use of the web, tweets, the use of incentives ($40,000), etc.

In terms of incentives, the MIT team used the promised prize money as the incentive — $4,000 for each of the 10 balloons.  $2000 per balloon was promised to the first person sending the balloon coordinates, $1000 to the person who recruited the finder onto the team, $500 to whoever invited the inviter, $250 to whoever invited that person, etc.

Here are some of the other strategies:

  • The second team, from Georgia Tech, used an altruism-based approach (the money would be donated to the Red Cross) – they found nine of the ten balloons.
  • George Hotz, a Twitter celebrity, recruited his followers – he found eight of the ten balloons.

Check out the paper for additional details (lots of cool stuff on networks, recruitment, etc).

Here’s the abstract:

The World Wide Web is commonly seen as a platform that can harness the collective abilities of large numbers of people to accomplish tasks with unprecedented speed, accuracy, and scale. To explore the Web’s ability for social mobilization, the Defense Advanced Research Projects Agency (DARPA) held the DARPA Network Challenge, in which competing teams were asked to locate 10 red weather balloons placed at locations around the continental United States. Using a recursive incentive mechanism that both spread information about the task and incentivized individuals to act, our team was able to find all 10 balloons in less than 9 hours, thus winning the Challenge. We analyzed the theoretical and practical properties of this mechanism and compared it with other approaches.

Here’s where the balloons were located:


Reality distortion field and strategy

I’ve been reading the new Steve Jobs biography and I find the possibilities of the “reality distortion field” quite promising for strategy (well, we do have lots of research on “framing” that indeed relates).  When I worked in venture capital, I saw lots of entrepreneurs try to distort reality, some successfully, many not.  Perhaps more on the RDF concept once I’ve finished the 571-page book.

Here’s Dilbert poking fun (click below).  The use of superlatives (particularly by Jobs) in Apple product launches was simply ridiculous – but, in the end, his spell seems to have worked on many (including me: I use a lot of Apple products). Read the rest of this entry »


Cognition and strategy

I was recently reading up on the latest and greatest in cognition and strategy and ran into Sarah Kaplan’s overview piece (2011) “Research in cognition and strategy: reflections on two decades of progress and a look to the future” Journal of Management Studies.

In the article she pulls together a list of key words for 226 cognition-related articles that cite Porac et al. (1989).  As you can see from the table, there is quite a bit of conceptual proliferation in the area of cognition.


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