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Browsing by Subject "Sustainable development"
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Item Collaborative Leadership in Social Innovation: A Leadership Framework for Tackling Wicked Public Challenges(2023-11) Freije, Brenda Hacker; Haberski, Raymond J., Jr.; Blomquist, William A.; Craig, David M.; Hong, YoungbokIn today’s world, we regularly hear about and experience intractable, systemic social problems that seem to defy solutions. How do we engage in systems change to address them? What processes can help us deal more effectively with them? It is not enough to say we need to change their systems. We need to know how to change them and lead others in the work. This dissertation explores how leadership teams and organizations can tackle wicked public challenges by working collaboratively with stakeholders through a process of trying to understand the challenge and designing strategies to influence systems change. I offer a Leadership Framework for these efforts that puts the collaborative leader in the role of expert intermediary responsible for seven Core Functions within the Leadership Framework. As expert intermediary, the collaborative leader facilitates vision-informed and values-driven decision-making and draws on a range of leadership and problemsolving approaches with four priorities: (1) to provide a systems view and understanding of the challenge, (2) to facilitate collaborative engagement and learning from a wide range of stakeholders, (3) to consider in the design and implementation of strategies and solutions the interconnections between economic growth, social inclusion, and environmental protection in human flourishing, and (4) to recognize that values run through it all. I refer to the Leadership Framework and its process as Collaborative Leadership in Social Innovation. I lay out the Leadership Framework as a concept map showing the Core Functions arranged along a path with Key Actions for each Core Function and other foundational components to the path. Learning is the glue that holds the Leadership Framework together and a key output. The Leadership Framework is designed to improve decision-making about wicked public challenges by ensuring sufficient time is dedicated to the Core Functions that precede the design and implementation of strategies and solutions. Following the Leadership Framework reduces the chances that solutions will lead to unintended results, miss opportunities, or focus on solving smaller problems in siloes that get at symptoms but rarely the heart of a challenge.Item Public perception and response to extreme heat events(2014-01-03) Porter, Raymond E.; Johnson, Daniel P. (Daniel Patrick), 1971-; Wilson, Jeffrey S. (Jeffrey Scott), 1967-; Dwyer, Owen J.In the United States extreme heat events have grown in size and stature over the past 20 years. Urban Heat Islands exacerbate these extreme heat events leaving a sizable portion of people at risk for heat related fatalities. The evidence of this is seen in the Chicago heat wave of 1995 which killed 500 people over the course of a week and the European heat wave of 2003 which killed 7,000 people in the course of a month. The main guiding questions then become how government and the media can most effectively warn people about the occurrence of extreme heat events? Should extreme heat warnings be issued by T.V., newspaper or by radio? Even if warnings are issued will the population at large still change their behavior? Another possible question is whether people most vulnerable to extreme heat will change their behavior? A survey in 2010 by NASA will be the main basis for this analysis. This survey set out to see how well people in Phoenix, Philadelphia, and Dayton responded to extreme heat alerts by changing their behavior.Item User Modeling and Optimization for Environmental Planning System Design(2014) Singh, Vidya Bhushan; Mukhopadhyay, Snehasis; Tuceryan, Mihran; Xia, YuniEnvironmental planning is very cumbersome work for environmentalists, government agencies like USDA and NRCS, and farmers. There are a number of conflicts and issues involved in such a decision making process. This research is based on the work to provide a common platform for environmental planning called WRESTORE (Watershed Restoration using Spatio-Temporal Optimization of Resources). We have designed a system that can be used to provide the best management practices for environmental planning. A distributed system was designed to combine high performance computing power of clusters/supercomputers in running various environmental model simulations. The system is designed to be a multi-user system just like a multi-user operating system. A number of stakeholders can log-on and run environmental model simulations simultaneously, seamlessly collaborate, and make collective judgments by visualizing their landscapes. In the research, we identified challenges in running such a system and proposed various solutions. One challenge was the lack of fast optimization algorithm. In our research, several algorithms are utilized such as Genetic Algorithm (GA) and Learning Automaton (LA). However, the criticism is that LA has a slow rate of convergence and that both LA and GA have the problem of getting stuck in local optima. We tried to solve the multi-objective problems using LA in batch mode to make the learning faster and accurate. The problems where the evaluation of the fitness functions for optimization is a bottleneck, like running environmental model simulation, evaluation of a number of such models in parallel can give considerable speed-up. In the multi-objective LA, different weight pair solutions were evaluated independently. We created their parallel versions to make them practically faster in computation. Additionally, we extended the parallelism concept with the batch mode learning. Another challenge we faced was in User Modeling. There are a number of User Modeling techniques available. Selection of the best user modeling technique is a hard problem. In this research, we modeled user's preferences and search criteria using an ANN (Artificial Neural Network). Training an ANN with limited data is not always feasible. There are many situations where a simple modeling technique works better if the learning data set is small. We formulated ways to fine tune the ANN in case of limited data and also introduced the concept of Deep Learning in User Modeling for environmental planning system.