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Resource allocation.

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• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Resource allocation.

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• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Most organizations can't execute strategy. Complexity is their enemy. A shared model (vision) of the strategy is the best way to cut through complexity. Unfortunately, developing clear and compelling visions to guide organizations is an art mastered by very few leaders. Are we condemned to wander aimlessly until a great leader develops a vision? System dynamics can make a science of visioning. Managing from Clarity provides a roadmap for introducing systems thinking to your organization. Read it; it's a snapshot of how strategy will be managed in the 21st Century. (David P. Norton, President, Balanced Scorecard Collaborative, co-author of the best-selling The Balanced Scorecard and The Strategy-Focused Organization) If you're not a systems thinker, you're not a good business leader. A few born leaders do it through intuition. For all the rest, there's Managing from Clarity. The book will spell out for you how to build your strategic agenda and how to align your leadership team around it. (Francis Gouillart, CEO, Emergence Consulting, co-author of the best-selling Transforming the Organization) Since Jay Forrester published Industry Dynamics and single-handedly laid down the foundations of system dynamics, several of his disciples have conducted many powerful consulting interventions in corporations all over the world. Three decades later their practices are still transmitted mostly through apprenticeship, thus limiting the expansion of the discipline and the benefits it brings to the world. With this book, Jim and Hal turn the art of system dynamics interventions into science for the first time. For those of us who live the successes and the frustrations of organizations every day, this is a gift every bit as wonderful as Dr. Forrester's. (Jorge Rufat-Latre, Director, Strategos) This method really works! In 1999, the Strategic Decision Simulation Group applied the methodology described in this book to a pilot urban planning initiative in Honduras' capitol cit

Management. --- Resource allocation.

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We are currently experiencing a climate crisis that is associated with extreme weather events worldwide. Some of its most noticeable effects are increases in temperatures, droughts, and desertification. These effects are already making whole regions unsuitable for agriculture. Therefore, we urgently need global measures to mitigate the effects of climate breakdown as well as crop alternatives that are more stress-resilient. These crop alternatives can come from breeding new varieties of well-established crops, such as wheat and barley. They can also come from promoting underutilized crop species that are naturally tolerant to some stresses, such as quinoa. Either way, we need to gather more knowledge on how plants respond to stresses related to climate breakdown, such as heat, water-deficit, flooding high salinity, nitrogen, and heavy metal stress. This Special Issue provides a timely collection of recent advances in the understanding of plant responses to these stresses. This information will definitely be useful to the design of new strategies to prevent the loss of more cultivable land and to reclaim the land that has already been declared unsuitable.

Plant resource allocation.

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One-step efficient GMM estimation has been developed in the recent papers of Back and Brown (1990), Imbens (1993) and Qin and Lawless (1994). These papers emphasized methods that correspond to using Owen's (1988) method of empirical likelihood to reweight the data so that the reweighted sample obeys all the moment restrictions at the parameter estimates. In this paper we consider an alternative KLIC motivated weighting and show how it and similar discrete reweightings define a class of unconstrained optimization problems which includes GMM as a special case. Such KLIC-motivated reweightings introduce M auxiliary `tilting' parameters, where M is the number of moments; parameter and overidentification hypotheses can be recast in terms of these tilting parameters. Such tests, when appropriately conditioned on the estimates of the original parameters, are often startlingly more effective than their conventional counterparts. This is apparently due to the local ancillarity of the original parameters for the tilting parameters.

Resource allocation --- Mathematical models.