group dynamics: July 2009 Archives

Dr Linus Nyiwul's dissertation defense was conducted almost exclusively in the language of math, with very little generic English explanation for the non-resource management layperson. So I cannot write very much about it, except that it was obvious that his faculty members are excited about the potential of this framework Dr Nyiwul has created for government regulators to exploit market mechanisms by leveraging emissions standards against the needs of firms to attract investors.

There are a couple of premises that Dr Nyiwul builds upon, including a perception that investors would prefer to put their money into "green" companies, and evidence that companies who improve their own environmental management systems experience increases in stock value (e.g., Feldman 1996). Dr Nyiwul described a whole lot of complicated stuff that needs to be properly balanced:

• setting a standard,
  
• needing to monitor to ensure companies are meeting the standard,
  
• keeping the cost of monitoring low enough to be reasonable (for government) while
  
• making the threat of monitoring real enough that companies prefer to comply rather than risk being caught and having to pay the penalty.
  

Somehow all those things get crunched through some equations that calculate

1. "marginal damage" (whatever this means! it apparently refers wholistically to "society") and
2. monitoring costs (to the government) and
3. costs of compliance (for the firms)

.... now, where it gets real interesting is when the government establishes two emissions standards: a regular standard (the minimum to be deemed "in compliance" and avoid penalties) and an overcompliance standard - which would earn a special certification proving uber-greenness (or something en route to such glorified status). There is pilot project currently underway, the National Environmental Performance Track (NEPT), which has weaknesses but whose results - plugged into Dr Nyiwul's equations - demonstrates that TWO STANDARDS IS GOOD POLICY! Not to mention that firms which earn the overcompliance certification have a special marketing asset to appeal to investors. (They have to meet the minimum "regular" standard first, then apply and demonstrate accomplishment of the overcompliance standard.)

There was some fancy problem-framing, as Linus described one finding, saying that it came about in one way if you set the problem up this way, and comes about in another way if you set the problem up that way. (I love the fact that subjectivity can be found in math!) There are some issues with firms getting to self-report emissions (apparently without verification, unless the regulator goes to conduct the actual monitoring?) And there was quite a discussion about looking at the problem endogamously: with free entry into and out of the market. And output and size effects really matter (but cannot be reversed) in terms of the direct and indirect effects of enforcement costs. Yea, I don't really know what those sentences mean in "real" economic terms, but there may be other things in play at times which can lead to inconclusive results.

but.... drumroll please! Dr Linus Nyiwul concludes, and his faculty agree:

The challenges that issue forth from Dr Nyiwul's work include (in no particular order):

1. identifying which are the important uncertainties (given that anything could be uncertain except for whatever is under direct regulatory monitoring)


2. defining clearly what "overcompliance" means (if "compliance" means paying the right tax, i.e., reducing emissions in order to minimize tax.... does overcompliance move a firm into a "credit" situation?)


3. how to extend the framework from a single firm to an industry


4. identifying how the framework as it is fits within known policy issues and concerns, and


5. extending the frame beyond emissions to look at a lot of other policy issues.

For her final oral examination for a Ph.D in Resource Economics, Siny Joseph presented an analysis of Country of Origin Labeling (COOL) for seafood. I echo the words of the external member of her committee, who said,


Dr Siny Joseph's field is I.O. Economics - a term that I had to Google after the defense! My complete ignorance of the jargon in this field should alert you to the high probability that I have misconstrued or misunderstood major elements of her work. I will do my best to summarize and hope for correcting comments as needed.

Extrapolating from the wikipedia entry and my limited exposure to other disciplines, Industrial Organization explores the economic interaction between two dynamic forces:

1. the strategic behavior of firms (which I believe is the purview of my friends specializing in strategic management) and
2. the structures of markets (statistical analysis like I've never seen!)

Given my lowest-score-in-the-cohort competence in all things math, most of the substance of Siny's analysis and discussion with her Committee Members occurred in a language I cannot even pretend to understand: replete with "k-bars," and K's with subscript L's and H's, "thetas" and fixed parameter values composing profit maximization formulas... Go grrl go! Her findings, however, were described in comprehensible English - and they are fascinating.

Seventy percent of seafood purchased by consumers in the U.S. is imported; of these imports, 80% comes from less developed countries. COOL (Country of Origin Labeling) is legislation introduced in the 2002 Farm Bill, and implemented with seafood in 2005, with the idea that food quality and food safety are linked with where the food originates. Coincidentally, COOL is being extended to more foods this year with continuing debate over exemptions and on-going criticism of delays, making Dr Joseph's research findings immediately relevant. Regarding seafood, huge sectors are exempt: restaurants and other food service providers, specifically, and products deemed to be "processed." In general, then, COOL applies to the seafood you buy in a grocery store or market to cook at home.

It seems the first major task in an I.O. economic analysis is to define the boundary between what is included and what is excluded from the study. Siny focused on the US market, presumably because the boundaries could be readily established. (In a case study on shrimp, she explained the distinction between a "covered" and "uncovered" market, explaining she'd had to go with the former - specifically an undifferentiated market - because the mathematical expressions for the latter were unmanageable. Basically (I think!) this means using idealized equations rather than ones more representative of real life.) Generally, Americans will assume that seafood of domestic origin is of higher quality than seafood of foreign origin, and consumers are most willing to pay the costs of labeling during and immediately after food scares - so that they (we, smile) can make (at least) this basic differentiation.

But (I kept thinking to myself) - labeling after a scare doesn't do much to protect consumers during the scare and of course has no contribution to risk prevention whatsoever. So why isn't labeling just done, as a matter of business habit? "Because," Dr Joseph explained, "firms can masquerade low quality seafood as high quality when consumers don't have all the information, and that's where the profit comes from." She and her committee members debated nuances of the statistical measurements, recommending and justifying choices of particular statistical tools, but did not question Siny's basic finding that (now, with only three years of info available) the greatest profit comes under what's called "voluntary COOL" (which does occur with some seafood products), followed by partial implementation of COOL (the status quo), and drops the lowest under "total COOL" - an ideal she recommends because "real consumption is greatest when there is full implementation of COOL."

The rub for me during the whole presentation is the use of this indicator called WTP: Willingness to Pay. What I'd like to see is a complementary WTP2 (squared) equation: Willingness to Profit. Somehow the whole debate seems framed with WTP2 as an unquestionable given - companies have the inalienable right to maximize profit and consumers have to pay for safety. It just strikes me as wrong; at least out-of-balance. Firms can afford to pay much more than any individual can! Anyway, Siny's Committee engaged vigorously with her findings: "I like the story you're trying to tell," said a professor by speakerphone, wondering about pursuing the angle of diversion, and all of them wondering about policy recommendations based on these findings.

There was a measure of "Total Welfare" that supposedly mixes the best consumer outcome with the best business outcome.... and Dr Joseph did present some evidence that companies would label voluntarily under certain/specific conditions (of known/demonstrated consumer demand?), but for the most part companies are trying to duck this completely. For instance, shrimp traders are required to label unprocessed shrimp, so they would rather do something that qualifies as "processing" in order to avoid labeling. Doesn't it cost to do that, too? Honest - I get very confused! Why is one type of cost preferable to another? I think someone needs to institute an equation such that consumer WTP cannot exceed 1/2 the square root of the actual incurred cost apportioned over the entire volume in order to somehow link a decrease in the firm's WTP2 (willingness to profit) with the increase consumers are willing to pay. (Which is probably why I'm not an economist.)

Nonetheless, even if the current data is not totally amenable to a single clear and concise argumentative point, I definitely agree with Siny's committee member: "I like your plan of attack." I want to be able to argue convincingly that the government (through legislation) should be on the consumer's side - not only in the grocery store, but I would also like to be able to confirm the quality of seafood purchased in restaurants.

Keep it up, Dr Siny Joseph!

Only four sets of feet open this quiz...it was not a twelve pillow night, although there were more than a few direct hits!

The Innocent One displayed her growth by leaps and bounds. The (nearly always) Late One had his first shock when he saw that the jar was empty: no driving until that sucker was caught! (Not to be confused with the fictional movie, Man in a Car, although a conflation of Man&Snake in a Car might make decent competition with Snakes on a Plane.)

Warning: tea sharing customs vary, as does etiquette for surprise birthday parties. Age protects one not from the practical joke, but it sure helps the food preparation!

Personal favorite: "Someone called the lab and asked for my partner and I said he wasn't here. 'There's another guy,' he said, 'but I can't pronounce his name.'" (Me either.)

Rules:

• Five points each to the first person who correctly identifies all four sets of feet, and both pictured dishes, in order.
• One point each to the first person who answers the following questions.
• Five points for each speaker identified in any/all included references.
• Five points for each explanation of context for any/all included references.
• All responses must be posted as 'comments' to this post.
• No responses will be revealed for at least 24 hours from email notification.
• Points will be tallied and posted as a comment within 48 hours from the original email notification.
• The winner(s) will receive a home-cooked meal from yours truly.

Ready, Set, Go!

1. Who was even later than me and my erstwhile hosts to the famed Mumbai wedding?
2. Who's snores might bring down the house?
3. Which First Lady is shopping for a dog as spouse of the President of the Indian Student Association?
4. Whose birthday was it?
5. Who and what was the issue with that shirt's cut in the back?
6. Does someone really eat like a camel?
7. Who is the perfect stand-in for a working-class driver (in any country)?
8. Visa? Who needs a visa?

The forty-six "glance points" represented in this graph illustrate eye gaze tracking during driving. (Now!) Dr Anuj Pradhan has been crucial in co-developing the RAPT novice driver training in risk perception over the course of a six-year doctorate degree and four experiments. Risk Perception and Awareness Training combines simulation and field techniques for assessing new drivers' scope and skill in anticipating potential risks while driving.

Did you know?

• Car accidents are the leading cause of death for teens in US
• Teenagers, during the first six months of driving, have an eightfold increase in the risk of dying in a car crash
• Teenagers, in general, are four times more likely than older drivers to die in a car crash
• In numbers: teenagers are involved in 4.7% of the six million crashes annually in the US but compose 13% of the fatalities

Previous research has identified three main causes of teenage accidents, including failure to adjust speed appropriately to conditions (20.8%), failure to maintain attention to the task (23%), and - the biggest - failure to conduct an appropriate search of the driving environment (42.7%).

After his presentation, Dr Pradhan's Dissertation Committee gave him some grief about the distinction he wants to draw between "tactical scanning" and "strategic scanning." (They also asked him, right at the beginning, to take off his suit jacket and relax. This may have been the signal that they planned to heat up the room...!) The first question, however, came from one of the faculty during the presentation, and it involved clarifying the dependent variable of eye movement. Dr. Pradhan's first experiment established a correlation between the recognition of risk (seeing it) and the knowledge that risks may be present (use of eye gaze to scan in order to identify (i.e. see) them if they are present).

Two more experiments refined the technique for linking eye movement with perception and recognition of risk. Results from the three experiments indicate improvements in visual search behavior in all driving situations, from the benign - when no risks are present, to situations with a minimal possibility of risk, and on up to situations with obvious dangers.

In other words, the students and volunteer test subjects who participated in these experiments learned about the strategic need for constant maintenance of visual attention across the broad driving environment which might require the driver (i.e., me - or you!) to engage in specific tactical behaviors in order to reduce risk - or be able to implement evasive action should a risk materialize because one has seen it in time! My contribution came with the fourth experiment, I got to test out the version in development - my experience (as an "older driver," grin) may or may not have aided in refining the program, but it certainly reinforced for me that there is a purpose to where, when, and why I look and watch in the ways that I do while driving. (I learned that I could still do better!)

The need for this kind of training tool in driver's education programs everywhere is immediately and obviously apparent. I was also fascinated by the application of temporal and spatial algorithms to the eye movements captured by the Mobile Eye movement tracker. Time and space coordinates for every eye movement had to be combined and crossreferenced in a Fixation Identification Algorithm with prior and subsequent eye movements in order to define a glance. These glances are then superimposed on the objects in the driver's visual range, and categorized as on-road or off-road. In this way, the Mobile Eye Tracker pinpoints whether the driver's eye looked directly at the truck parked on the side of the road in front of a passenger crosswalk, when (from near or far), and for how long. Does the gaze return or simply pass on to other objects?

In other words, the direction of eye gaze can indicate the driver's perception of risk - or lack of it. Once a driver is informed of their own eye movement behavior, then their awareness of risk is enhanced (or should be, I think the larger research program of the Human Performance Lab is lacking a necessary qualitative element). In fact, after training in the tactics of using visual scanning to perceive the possibility of risk, Dr. Pradhan shows that drivers improve risk awareness in four significant ways:

1. Trained drivers maintain a wider horizontal range of vision
2. Trained drivers shift half their glances offroad, more trained looking to right - where more risks presumedly originate (compared with the untrained who look left & right more-or-less evenly)
3. Trained drivers glance off-road for slightly longer times (presumedly considering the extent to which the conditions in sight compose/obscure a risk or not)
4. Trained drivers learn not only to transfer recognition of risk types between similar scenarios, but also transfer the skill of tactical scanning to different scenarios than those they were exposed to during training

Throughout the presentation, I kept thinking, "if only" - if only I had had this knowledge five years ago -- the language of "visual scanning," "risk perception," and "risk awareness" -- then Hunju's driving practice might have gone more smoothly for both of us!

Anyway, Anuj's defense rolled along. Dr Krishnamurty pressed him on the relevance or distinction between top-down and perspective views, which Dr. Pradhan handled with aplomb: "I got you, excellent answer." No wonder Jeff calls Anuj, "my Yoda." The (self-named) Curmudgeon wouldn't let go of the tactical/strategic distinction but I wager this is merely ground for the next stage of hypothesis testing and theory building. The Committee Chair, Dr Fisher, supported Anuj throughout. They grilled him for a mere quarter of an hour after kicking out us observers (selected members of the fan club). And then they only made him wait for about that much longer (or less) before Dr Fisher came out and ushered him back in with a handshake and announcement: