Scott Rockart

Interdependency, Competition, and the Distribution of Firm and Industry Profits

Coordination of interdependencies among firms productive activities has been advanced as a promising explanation for sustained heterogeneity in capabilities among firms. In this paper, we extend this line of research to determine the industry structures and patterns of expected firm profits for the case when difficulty optimizing interdependent activities does, in fact, generate and sustain capability heterogeneity among firms. We combine a widely used agent-based model where firms search to discover sets of activities that complement one another (reducing overall costs or raising product quality) with traditional economic models of competition among profit-maximizing firms. The agent-based model produces a distribution of performance (interpreted as variable cost or product quality) among firms and the competition models determine resulting industry outcomes including patterns of entry, exit, and profits. The integration of economic models of competition among firms with an agent-based model of search for improvement by firms reveals a rich relationship between interdependencies in production functions and industry structure, firm profits, and industry average profitability.

Interdependency, Competition, and Industry Dynamics

Asystematic understanding of industry dynamics is critical to strategy research because individual firm performance dynamics both reflect and affect change at the industry level. Descriptive research on industry dynamics has identified a dominant pattern where prices fall, output rises, and the number of firms rises and then falls over time. Several models have been advanced to explain these patterns, with a particular focus on explaining why a shakeout in the number of firms occurs. In the most prominent models, shakeout is generated by rising realized heterogeneity among firms that either is assumed to be unrecognized but determined ex ante or is generated by stochastic innovation outcomes coupled with convex adjustment costs and scale advantages in innovation and learning. In this paper, we develop an alternative model where heterogeneity develops among firms over time (leading to a shakeout) because firms must make choices about highly interdependent productive activities where the ideal combinations cannot be easily deduced or imitated. By combining two established models (a Cournot model of competition with an NK model of interdependency in production activities), we are able to advance an alternative explanation for the observed patterns of industry behavior, including shakeout. We show that variation in the potential for interdependency in activities among industries is able to explain varying levels of shakeout as well as differing patterns of entry and exit among industries. Notably, the model generates several empirical predictions not apparent in past research and several that directly conflict with the results of prominent alternative models of industry dynamics. Specifically, we show that when the potential for interdependency within an industry is low, entry slows down and incumbent survival is all but assured, whereas in industries where the potential for interdependencies is high, shakeouts are severe and the rates of entry and exit remain high over longer time periods, with decreasing survival rates for incumbents.

Application description and policy model in collaborative environment for sharing of information on epidemiological and clinical research data sets.

Background Sharing of epidemiological and clinical data sets among researchers is poor at best, in detriment of science and community at large. The purpose of this paper is therefore to (1) describe a novel Web application designed to share information on study data sets focusing on epidemiological clinical research in a collaborative environment and (2) create a policy model placing this collaborative environment into the current scientific social context. Methodology The Database of Databases application was developed based on feedback from epidemiologists and clinical researchers requiring a Web-based platform that would allow for sharing of information about epidemiological and clinical study data sets in a collaborative environment. This platform should ensure that researchers can modify the information. A Model-based predictions of number of publications and funding resulting from combinations of different policy implementation strategies (for metadata and data sharing) were generated using System Dynamics modeling. Principal Findings The application allows researchers to easily upload information about clinical study data sets, which is searchable and modifiable by other users in a wiki environment. All modifications are filtered by the database principal investigator in order to maintain quality control. The application has been extensively tested and currently contains 130 clinical study data sets from the United States, Australia, China and Singapore. Model results indicated that any policy implementation would be better than the current strategy, that metadata sharing is better than data-sharing, and that combined policies achieve the best results in terms of publications. Conclusions Based on our empirical observations and resulting model, the social network environment surrounding the application can assist epidemiologists and clinical researchers contribute and search for metadata in a collaborative environment, thus potentially facilitating collaboration efforts among research communities distributed around the globe.