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Academic research and findings on an aspect of contract provisions – extensions and termination rights

Academics conduct research that makes me envious. Consider a detailed study of contracts described in the Acad. Mgt. Rev., Feb. 2011 at 182. Three professors studied 385 contracts Compustar had entered into with buyers of its IT services. (Of interest to me was the statement that lawyers negotiated none of the contracts; “lawyers conducted a final-stage review of the contracts” (at 200).) The article focuses on extendability and early termination provisions in the contracts. To research their effect, the authors coded a number of variables regarding the contractual arrangement and the contracting party. They then conducted regressions to find answers to their hypotheses.

My point here has only a little to do with what this particular empirical research can tell law department managers about contracting activities. My main point is that the methodology of data collection and analysis can uncover what is going on in the world far more insightfully and convincingly than the anecdotal sense of even the most experienced lawyer. Once you count it, analysis it, and run regressions coupled with causal relationships, you reach a much deeper understanding of whatever you study. Academics can do this and they publish their findings. This article illustrates the power of that approach.

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One response to “Academic research and findings on an aspect of contract provisions – extensions and termination rights”

  1. Bill Wilson says:

    Sometimes. Over the years, I have seen as much drivel come from quantitative sources as anecdotal evidence. While I recognize that there are methods for assigning values to “things” of all sorts, I also think the quantitative approach understates dramatically the inherent bias of the evaluator or lack of complete understanding of what is being measured. If I spend 90 minutes teaching engineers the fundamentals of product liability law, exactly how does one quantify the value add in that activity? You can look at how loss experience drops, but the correlation/causation is difficult to establish. I almost feel sometimes that Excel is the worst program ever invented, because it gave the quants a tool on their desktop to drive an overwhelming need to measure and create data, most of which in the final analysis is not very informative, and no better than anecdotal data. I am not naive enough to believe that it can’t be done, because I have seen instances where it has been done well, but my experience tells me it’s not done well often enough.