When we attend INFORMS, we usually we learn new things about what we already know, or experience new concepts for the first time. But I had an interesting experience in a TIMES session that made me think of another type of learning. Sometimes what we already know is not as well-defined or operationalized as we may have assumed.
As an example of well-defined, I was in SB03 , listening to a presentation by Sinan Erzurumlu that touched on entrepreneurs and big data. I realized that I’m not sure if there is yet a comprehensive theory of how entrepreneurs interact with big data. And this partly may be because many entrepreneurs are not large enough to have big data. But as analytics continue to become more important, that will change.
If big data is a resource, then one would argue that because entrepreneurs are generally resource-poor, they most likely do not have good access to big data. But big data may be more a source of competitive advantage for entrepreneurs, who due to their alertness in discovery or unique perspective may uncover new opportunities buried in the data. So how do entrepreneurs interact with big data? Perhaps that research has been done (and if so, please comment below), but a cursory search of Google Scholar seems to indicate that it has not yet.
As an example of operationalized, in the same session, Emre Guzelsu mentioned trying to measure time of commercialization in a data set of thousands of start-ups. Even non-TIMES researchers could give a decent-sounding definition of commercialization: it’s when a new product is launched or introduced to market. But suppose you are now creating a longitudinal study and need to record when start-ups have commercialized their first product. Is that the date of first viable prototype? Production? Launch? What about a product that is produced and made available for purchase, but no one buys it: has it truly been commercialized? Is success necessary for commercialization to have occurred?
While this uncertainty may be dismaying, these are also opportunities for research. So perhaps there are still significant opportunities in areas one would think had been well-studied. Which terms or concepts are you rethinking at this conference?