Stochastic Common Learning

We present a general model in which agents learn by observing a stochastic process. We show that agents not only learn in such a model but also learn commonly. By this we mean that in the long run agents will form common beliefs concerning important facts and in particular they will commonly believe that their views regarding the future are similar. Journal of Economic Literature Classification Numbers: C72, C73, D82.     

Iterated Expectations and Common Priors

A necessary and sufficient condition for the existence of a common prior for several players is given in terms of the players' present beliefs only. A common prior exists iff for each random variable it is common knowledge that all its iterated expectations converge to the same value; this value is its expectation with respect to the common prior. The proof is based on the presentation of type functions as Markov matrices.Journal of Economic LiteratureClassification Numbers: C70, D82.     

Policy globalization and the “information society”: a view from Canada

The Canadian example suggests that recent shifts in communication policy frameworks should be understood as a transformation in how technology is organized politically, and not simply as a policy reaction to technological innovation. The process is tracked chronologically in three sections: institutional renewal (1993–1994); accelerated vertical slippage between national, regional and global policy levels (1995–1996); and horizontal dispersal of communication policy into new other sectors (1997). Across these stages, a series of convergences characterized by increased fluidity between territorial as well as sectoral jurisdictions are discussed; implications for the understanding of communication policy frameworks within the context of the “information society” project are identified.     

The least core, kernel and bargaining sets of large games

Summary. We study the least core, the kernel and bargaining sets of coalitional games with a countable set of players. We show that the least core of a continuous superadditive game with a countable set of players is a non-empty (norm-compact) subset of the space of all countably additive measures. Then we show that in such games the intersection of the prekernel and the least core is non-empty. Finally, we show that the Aumann-Maschler and the Mas-Colell bargaining sets contain the set of all countably additive payoff measures in the prekernel. Received: June 6, 1996; revised version: March 1, 1997     

The relative importance of project success dimensions

Traditionally, the success of a project is assessed using internal measures such as technical and operational goals, and meeting schedule and budget. More recently, it has been recognized that several other measures should be used to define project success. These measures reflect external effectiveness: the project's impact on its customers, and on the developing organization itself.
In our study of 110 defense projects performed by Israeli industry, we used a multidimensional approach to measure the success of defense projects. Based on previous studies, we defined four dimensions of success: meeting design goals ; benefits to the customer ; benefits to the developing organization ; and benefits to the defense and national infrastructure . For each project, we asked three different stakeholders (the customer, the developing organization, and the coordinating office within the Ministry of Defense) for their views on the relative importance of these dimensions of success. Analysis of the data revealed that the dimension benefits to the customer is by far the most important success dimension. The second in importance is meeting design goals . The other two dimensions are relatively unimportant.     

System modeling of the R&D domain through the object–process methodology: a practical tool to help R&D satisfy its customers' needs

Research and Development is an intricate process involving a host of challenging technological frontiers. This paper presents a practical tool to help R&D personnel satisfy the needs of customers by a systematic evaluation of R&D performance. To establish a sound methodology for R&D performance evaluation, we employ the object-process analysis (OPA) part of the object–process methodology. Using OPA, we gradually expose the constituents of the R&D system, its environment and the interaction between them. Through this systematic top-down refinement, we provide a comprehensive generic view of the R&D domain. The framework presented in the paper allows the user to describe, order, and inter-relate the issues that R&D managers should consider when managing, evaluating and planning R&D. As the approach addresses structure and behaviour in a unified, integrated manner, the analysis provides insights into both the static and dynamic aspects of the R&D domain and establishes a solid basis for its enterprise modeling.