Generating Value Through Open Source: Software Service Market Regulation and Licensing Policy

In the software industry, commercial open-source software vendors have recognized that providing services to help businesses derive greater value in the implementation of open source–based systems can be a profitable business model. Moreover, society may greatly benefit when software originators choose an open-source development strategy as their products become widely available, readily customizable, and open to community contributions. In this study, we present an economic model to study how software licensing attributes affect a software originator’s decisions, aiming to provide policy makers with insights into how welfare-improving, open-source outcomes can be incentivized. We show that when a competing contributor is apt at reaping the benefits of software development investment, a less restrictive open source license (e.g., Berkeley Software Distribution, or BSD style) can improve welfare. On the other hand, when the originator is better at leveraging investment and service costs are high, a more restrictive license (e.g., General Public License, or GPL style) can be best for social welfare even when a contributor can cost-efficiently develop the software. The online appendix is available at https://doi.org/10.1287/isre.2017.0726

Information Precision and Asymptotic Efficiency of Industrial Markets

Online market places have an unprecedented power of bringing together a large number of buyers and sellers and aggregating information. Despite its benefits, this scale of aggregation of private information may bring about adverse effects that can cause ine±ciencies, which can be ignored by conventional analysis. In this paper, I present a strategic model of a large industrial market with asymmetric information to examine (i) the validity of the conjecture of price-taking behavior in such markets as the number of agents becomes large; (ii) the effect of the rate that individual information precision decreases with increased number of agents on convergence to price-taking and e±ciency. I show that in an industrial market with downstream competition, increasing the number of sellers may make all participants price-takers in the limit, but increasing the number of buyers may not. When the total precision of information in the market is high, price taking and full social e±ciency is achieved in the limit with large numbers of buyers and sellers. However, if the total precision of information in the market is poor, large ine±ciencies, including full ine±ciency, can occur in the limiting outcome. The rate of decrease of individual information precision with increased number of agents determines the rate of convergence to efficiency, and the convergence is slower than that predicted by the single unit trading models in the literature

Information Precision and Asymptotic Efficiency of Industrial Markets

Online market places have an unprecedented power of bringing together a large number of buyers and sellers and aggregating information. Despite its benefits, this scale of aggregation of private information may bring about adverse effects that can cause ine±ciencies, which can be ignored by conventional analysis. In this paper, I present a strategic model of a large industrial market with asymmetric information to examine (i) the validity of the conjecture of price-taking behavior in such markets as the number of agents becomes large; (ii) the effect of the rate that individual information precision decreases with increased number of agents on convergence to price-taking and e±ciency. I show that in an industrial market with downstream competition, increasing the number of sellers may make all participants price-takers in the limit, but increasing the number of buyers may not. When the total precision of information in the market is high, price taking and full social e±ciency is achieved in the limit with large numbers of buyers and sellers. However, if the total precision of information in the market is poor, large ine±ciencies, including full ine±ciency, can occur in the limiting outcome. The rate of decrease of individual information precision with increased number of agents determines the rate of convergence to efficiency, and the convergence is slower than that predicted by the single unit trading models in the literature

Sourcing Flexibility, Spot Trading, and Procurement Contract Structure

We analyze the structure and pricing of option contracts for an industrial good in the presence of spot trading. We combine the analysis of spot trading and buyers' disparate private valuations for different suppliers' products, and we jointly endogenize the determination of three major dimensions in contract design: (i) sales contracts versus options contracts, (ii) flat-price versus volume-dependent contracts, and (iii) volume discounts versus volume premia. We build a model in which a supplier of an industrial good transacts with a manufacturer who uses the supplier's product to produce an end good with an uncertain demand. We show that, consistent with industry observations, volume-dependent optimal sales contracts always demonstrate volume discounts (i.e., involve concave pricing). However, options are more complex agreements, and optimal option contracts can involve both volume discounts and volume premia. Three major contract structures commonly emerge in optimality. First, if the seller has a high discount rate relative to the buyer and the seller's production costs or the production capacity is low, the optimal contracts tend to be flat-price sales contracts. Second, when the seller has a relatively high discount rate compared to the buyer but production costs or production capacity are high, the optimal contracts are sales contracts with volume discounts. Third, if the buyer's discount rate is high relative to the seller's, then the optimal contracts tend to be volume-dependent options contracts and can involve both volume discounts and volume premia. However, when the seller's production capacity is sufficiently low, it is possible to observe flat-price option contracts. Furthermore, we provide links between production and spot market characteristics, contract design, and efficiency.National Science Foundation (U.S.) (contract CMMI-0758069)National Science Foundation (U.S.) (contract DMI-0245352

Asymptotic Efficiency of Industrial Markets

, is a non-profit institution devoted to research on network industries, electronic commerce, telecommunications, the Internet, “virtual networks” comprised of computers that share the same technical standard or operating system, and on network issues in general

Information Precision and Asymptotic Efficiency of Industrial Markets

Online market places have an unprecedented power of bringing together a large number of buyers and sellers and aggregating information. Despite its benefits, this scale of aggregation of private information may bring about adverse effects that can cause inefficiencies, which can be ignored by conventional analysis. In this paper, I present a strategic model of a large industrial market with asymmetric information to examine (i) the validity of the conjecture of price-taking behavior in such markets as the number of agents becomes large; (ii) the effect of the rate that individual information precision decreases with increased number of agents on convergence to price-taking and efficiency. I show that in an industrial market with downstream competition, increasing the number of sellers may make all participants price-takers in the limit, but increasing the number of buyers may not. When the total precision of information in the market is high, price taking and full social efficiency is achieved in the limit with large numbers of buyers and sellers. However, if the total precision of information in the market is poor, large inefficiencies, including full inefficiency, can occur in the limiting outcome. The rate of decrease of individual information precision with increased number of agents determines the rate of convergence to efficiency, and the convergence is slower than that predicted by the single unit trading models in the literature.

Information precision and asymptotic efficiency of industrial markets

I present a strategic model of a bilateral oligopoly with asymmetric information to examine (i) the validity of the conjecture of price-taking behavior in such markets as the number of agents becomes large and (ii) the effect of the rate that individual information precision decreases with increased number of agents on convergence to price-taking and efficiency. I show that with downstream competition, increasing the number of sellers may make all participants price-takers in the limit, but increasing the number of buyers may not. When the total precision of information in the market is high, price-taking and full social efficiency is achieved in the limit with large numbers of buyers and sellers. However, if the total precision of information in the market is poor, price-taking conjecture may fail and large inefficiencies, including full inefficiency, can occur in the limiting outcome. The rate of decrease of individual information precision with increased number of agents determines the rate of convergence to efficiency, and the convergence is slower than that predicted by single-unit auction models in the literature. I also demonstrate that when the number of sellers or both the number of buyers and the sellers go to infinity, price-taking and information aggregation tend to go together. When the number of buyers goes to infinity, however, information can get aggregated when the agents do not become price-takers in the limit. Albeit, in the latter case, the aggregated information is masked by the noise in the sellers' signals and the cost variability.