Using Cyber-enabled Transaction Data to Study Productivity and Innovation in Organizations
Abstract
This paper draws on recent research in a wide variety of disciplines to identify the key elements necessary to build an empirical infrastructure that will advance research on one of the key building blocks of science and innovation policy: organizations. We argue that cyber-tools and new data will permit researchers to examine the innovation process – both successes and failures – and explore business performance and business dynamics at the level of the appropriate economic entity.
We develop a roadmap that outlines how the new data can be developed, from harvesting the web to direct observation from deep within companies. The paper identifies a set of research questions and an approach whose pursuit could be used to develop a national research data infrastructure for the study of innovation and organizational performance. One key element of the approach is to identify and study innovation processes within organizations by collecting data on inputs and outcomes of innovation projects (or initiatives) within organizations. Another is the collection of representative data by business function/processes across firms, a proven statistical and economic approach (Sturgeon et al. 2006, Brown 2008, Lewin et al 2008).
Finally, we argue that the work to develop new data from deep within firms should involve the participation of computer and information scientists. Opportunities for quasi experimental approaches to data collection, and noninvasive techniques to harvest data from within firms (i.e., auto-populating of researcher databases) need to be explored. More generally, the bringing together of scientists to consider business microdata privacy/access and data collection from organizations is itself significant, with potential for creating opportunities in a broad range of applications.
