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Leiva, V., Santos-Neto, M., Cysneiros, F. J. A., & Barros, M. (2016). A methodology for stochastic inventory models based on a zero-adjusted Birnbaum-Saunders distribution. Appl. Stoch. Models. Bus. Ind., 32(1), 74–89.
Abstract: The Birnbaum-Saunders (BS) distribution is receiving considerable attention. We propose a methodology for inventory logistics that allows demand data with zeros to be modeled by means of a new discrete-continuous mixture distribution, which is constructed by using a probability mass at zero and a continuous component related to the BS distribution. We obtain some properties of the new mixture distribution and conduct a simulation study to evaluate the performance of the estimators of its parameters. The methodology for stochastic inventory models considers also financial indicators. We illustrate the proposed methodology with two real-world demand data sets. It shows its potential, highlighting the convenience of using it by improving the contribution margins of a Chilean food industry. Copyright (c) 2015 John Wiley & Sons, Ltd.
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O'Ryan, R., & Pereira, M. (2015). Participatory indicators of sustainability for the salmon industry: The case of Chile. Mar. Pol., 51, 322–330.
Abstract: In this paper a methodological approach is proposed and applied to undertake a participatory process to obtain sustainable development indicators for the salmon sector in Chile including a common vision of sustainability for this industry. The selected indicators are a mix of bottom-up and top-down approaches, which capture the specific needs and perceptions of the different stakeholders related to salmon farming while allowing a high degree of international comparability. A detailed step by step description of the methodology allows understanding how to obtain acceptable social, economic and environmental indicators, a result that can be replicated in other natural resource based productive sectors that are common in developing contexts. (C) 2014 Elsevier Ltd. All rights reserved.
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