A Social Science of Architecture 

 After eight years of learning something about architecture (from  Harry Cobb  and his team) and extensive programmatic planning, the Institute for Quantitative Social Science this semester moves into the new Center for Government and International Studies buildings.  Our official address is the Third Floor of 1737 Cambridge Street (the design is vaguely reminiscent of the bridge of the Starship Enterprise), although we also occupy some of the other floors and some of the building across the street.  It is not really finished yet, but it is a terrific facility, with floor to ceiling windows in most offices, a wonderful seminar room for our Applied Statistics Workshop, and many other useful features.  Perhaps even more remarkably, everyone seems to love it (Congratulations Harry!). 

 One issue I learned during this long process was how the field of architecture has the best science, engineering, and art, but very little modern social scientific analysis.  Yet, social science, quantitative social science in particular, could greatly help architecture achieve its goals, I think.  Ultimately the goal of this particular $100M-plus building, and of most buildings built by universities, is not only to create beautiful surroundings but also to increase the amount of knowledge created, disseminated, and preserved (my summary of the purpose of modern research universities).  So do not limit yourself to asking how a building makes you feel, what architectural critics might think, how it fits in with the style of other buildings on campus, or whether your office is to your liking.  Ask instead, or in addition, whether the building increases the units of knowledge created, disseminated, and preserved more than some other building or some other potential use for the money.  This strikes me as the central question to be answered by those who decide what buildings to build, and yet the systematic scientific basis for this decision is almost nonexistent. 

 As such, some systematic data collection could have a considerable impact on this field.  Do corridors or suites make the faculty and students produce and learn more?  Does vertical circulation work as well as horizontal?  Should we put faculty in close proximity to others working on the same projects or should we maximize interdisciplinary adjacencies?  Which types of floor plans increase interaction?  Which types of interaction produce the most knowledge created, generated, and preserved?  Do we want to build buildings that encourage doors to be kept open, so as to make the faculty seem approachable or should we try to keep doors closed so that they can get work done?  In this field as in most others, a great deal can be learned by directly measuring the relevant outcome variable; in architecture, quite remarkably, this has only rarely been attempted. 

 Of course it is done all the time via qualitative judgments, but in almost every field of science where a sufficient fraction of information can be quantified, statistical analysis beats human judgment.  There is no reason to think that the same kind of statistical science wouldn't also create enormous advances here too. 

 I have heard of a couple of isolated academic works on this subject, but we're talking about some of the most important and expensive decisions universities make (and among the biggest decisions businesses, and many other institutions make too).  There should be an entire subfield devoted to the subject.  All it would take is some data collection and analysis.  Outcome measures could include, for example faculty citation rates, publications, awards, grants, and departmental rankings, along with student recruitment, retention, graduation, and placement rates.  The key treatment variables would include various information on the types of buildings and architectural design.  Random assignment seems infeasible, but relatively exogenous features might include departmental moves or city and town building restrictions.  Universities that allow faculty the choice of buildings could also provide useful revealed preference measures.  I would think that a few enterprising scholars on this path could have an enormous impact both in creating a new academic subfield and in improving a vitally important set of university (and societal) decisions. 

 In the interm, we'll enjoy the new buildings and hope they have a positive impact.