Incentive Issues in R&D Consortia: Insights from Applied Game Theory

Article excerpt


A. Aims and Premise

How can applied game theory help analysts understand Research and Development (R&D) consortia? Our basic premise is as follows. We view institutions such as R&D consortia as mechanisms for dealing with incentive problems that are obstacles to realizing the benefits of cooperation. These incentive problems involve strategic interaction. Hence, we need game theory to understand them. Yet, a full-blown game model the incorporates all relevant incentive issues is not feasible--the mathematics is too complex. Thus, we review a series of relevant insights--drawing upon several strands of more rigorous literature on incentive problems--and synthesize these insights into a single narrative or "logic." We use a case study of an R&D consortium, the Latin American Fund for Irrigated Rice (Spanish acronym: FLAR), to illustrate how the applied game-theoretic insights fit together and how they are relevant to a real-world institution like FLAR. (1) We introduce our proposed logic and FLAR in the present section.

Our principal aims are (1) to set out this logic step by step, (2) to persuade the reader of its relevance to R&D consortia, and (3) to suggest how insights from several strands of applied game theory can be applied to R&D consortia.

In the course of our argument, we introduce several concepts that are building blocks for our logic. These include in particular the notion that complexification should precede simplification (crucial to bridging the gap between applied game theory and real-world institutional analysis), the multidimensionality of subsidies, the coexistence of crowding in and reverse crowding out, a novel concept of leadership, and a "big-picture game" (i.e., one that abstracts from specific incentive issues) that is a repeated prisoners' dilemma (PD) with unknown horizon.

B. Approach and Overview

Olson (1965) elaborated a key insight from the literature on public goods (e.g., Samuelson, 1954, 1955)--namely that the existence of a group of players with a common interest does not automatically give rise to collective action or may result in collective action at a suboptimal level. At the core of Olson's logic is a simple mathematical model that yields several propositions, for example, those relating group size to the severity of the collective action problem. The decades since Olson (1965) have witnessed an explosion of applied game-theoretic models of a number of incentive problems that are relevant to collective action. Hence, we propose an updated, more conceptual, logic that can accommodate much of this subsequent literature and does more justice to the complexity of real-world institutions (Figure 1). We think of participants in an R&D consortium as players in a game, who have certain reasons for joining the consortium (Box A in Figure 1) but face incentive issues (Box B) that are obstacles to optimal cooperation. We analyze the resulting arrangement as a solution to those incentive issues, emphasizing the role of leadership (Box F).


Who are the players--individuals, or households, or organizations, or governments, etc.? This is a tricky and important question. We take a flexible approach. In the next subsection, we sketch FLAR and argue that its "representative organizations" (one for each country) are the relevant collective action players. However, a few individuals were instrumental in founding and designing FLAR (see bellow).

Why should a group of players form an R&D consortium? There are three key technical reasons for doing so (Box A). (2) First, R&D outputs are typically (imperfect) public goods: they are characterized by imperfect rivalry and imperfect (or costly) appropriability. This is the reason for collective action that Olson (1965) and the collective action literature generally focus on. A second key reason is the existence of complementary or synergistic assets--such as intellectual property (IP), genetic materials, and employees' expertise--that serve as inputs into the R&D process. …


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