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ABSTRACT Most real-life decisions are made with less than perfect information and there is often some opportunity to acquire additional information to increase the quality of the decision. In this article, we define and study the sequential information acquisition process of a rational decision maker (DM) when allowed to acquire any finite amount of information from a set of products defined by vectors of characteristics. The information acquisition process of the DM depends both on the values of the characteristics observed previously and the number and potential realizations of the remaining characteristics. Each time an observation is acquired, the DM modifies the probability of improving upon the products already observed with the number of observations available. We construct two real-valued functions whose crossing points determine the decision of how to allocate each available piece of information. We provide several numerical simulations to illustrate the information acquisition incentives defining the behavior of the DM. Applications to knowledge management and decision support systems follow immediately from our results, particularly when considering the introduction and acceptance of new technological products and when formalizing online search environments. [ABSTRACT FROM AUTHOR]

This paper illustrates how wholly owned entry modes of multinational companies ( MNCs) are jointly determined by both the strategic objectives of the MNC and the local firms' assets in the creation of value. In particular, the entry mode chosen is based on the potential reciprocal technological spillovers between local firms and MNC subsidiaries. M& As are preferred when host countries exhibit a certain level of development in their local systems of innovation, especially for technologically leading MNCs. Otherwise, for technological laggard MNCs, greenfield investments prevail and M& As may be carried out for meeting demand motives in developing local systems of innovation. [ABSTRACT FROM AUTHOR]

The quality of its players is one of the most significant features determining the failure or success of a sports team. The wide array of factors contributing to the performance of the players together with the inherent financial limitations of the clubs have transformed the selection of players into a complex problem. The current paper presents an integrated approach that combines multiple‐criteria decision‐making analysis and mathematical programming to support the decision maker through the building process of a soccer team. First, the fuzzy analytic network process is applied to evaluate the significance of the different performance criteria for each position in the field. The score attained by the different players in each potential position is computed using PROMETHEE II. A biobjective integer programming model has been designed to evaluate the transfer status of the players. Finally, data envelopment analysis is used to identify the most efficient Pareto solution determining the status of each player. In order to demonstrate the applicability of the proposed approach, the position in the field and transfer status of 60 players being considered by a real soccer team have been determined. [ABSTRACT FROM AUTHOR]