Economic Impacts of GO TO 2040

The economy of the Chicago metropolitan region has reached a critical juncture. On the one hand, Chicagoland is currently a highly successful global region with extraordinary assets and outputs. The region successfully made the transition in the 1980s and 1990s from a primarily industrial to a knowledge and service-based economy. It has high levels of human capital, with strong concentrations in information-sector industries and knowledge-based functional clusters -- a headquarters region with thriving finance, business services, law, IT and emerging bioscience, advanced manufacturing and similar high-growth sectors. It combines multiple deep areas of specialization, providing the resilience that comes from economic diversity. It is home to the abundant quality-of-life amenities that flow from business and household prosperity.On the other hand, beneath this static portrait of our strengths lie disturbing signs of a potential loss of momentum. Trends in the last decade reveal slowing rates, compared to other regions, of growth in productivity and gross metropolitan product. Trends in innovation, new firm creation and employment are comparably lagging. The region also faces emerging challenges with respect to both spatial efficiency and governance.In this context, the Chicago Metropolitan Agency for Planning (CMAP) has just released GO TO 2040, its comprehensive, long-term plan for the Chicago metropolitan area. The plan contains recommendations aimed at shaping a wide range of regional characteristics over the next 30 years, during which time more than 2 million new residents are anticipated. Among the chief goals of GO TO 2040 are increasing the region's long-term economic prosperity, sustaining a high quality of life for the region's current and future residents and making the most effective use of public investments. To this end, the plan addresses a broad scope of interrelated issues which, in aggregate, will shape the long-term physical, economic, institutional and social character of the region.This report by RW Ventures, LLC is an independent assessment of the plan from a purely economic perspective, addressing the impacts that GO TO 2040's recommendations can be expected to have on the future of the regional economy. The assessment begins by describing how implementation of GO TO 2040's recommendations would affect the economic landscape of the region; reviews economic research and practice about the factors that influence regional economic growth; and, given both of these, articulates and illustrates the likely economic impacts that will flow from implementation of the plan. In the course of reviewing the economic implications of the plan, the assessment also provides recommendations of further steps, as the plan is implemented, for increasing its positive impact on economic growth

Multi-objective model for optimizing railway infrastructure asset renewal

Trabalho inspirado num problema real da empresa Infraestruturas de Portugal, EP.A multi-objective model for managing railway infrastructure asset renewal is presented. The model aims to optimize three objectives, while respecting operational constraints: levelling investment throughout multiple years, minimizing total cost and minimizing work start postponements. Its output is an optimized intervention schedule. The model is based on a case study from a Portuguese infrastructure management company, which specified the objectives and constraints, and reflects management practice on railway infrastructure. The results show that investment levelling greatly influences the other objectives and that total cost fluctuations may range from insignificant to important, depending on the condition of the infrastructure. The results structure is argued to be general and suggests a practical methodology for analysing trade-offs and selecting a solution for implementation.info:eu-repo/semantics/publishedVersio

Nonprofit Strategies for 1- to 4-Unit REO Properties: An Analytical Framework

Real estate owned (REO) housing resulting from the recent foreclosure crisis threatens to destabilize low- and moderate-income neighborhoods across the country. Nonprofit organiza-tions seeking to redevelop these properties into affordable housing face weak market condi-tions and operate with limited resources and capacity. This study presents a framework through which nonprofits can analyze REO redevelopment opportunities for 1- to 4-unit properties within their communities. The paper specifies the conditions necessary for REO redevelopment and discusses how local market conditions, the geographic distribution and the physical characteristics of REOs, their ownership and legal status, internal organizational capacity, and public policies each affect nonprofit efforts to acquire, rehabilitate, sell and rent REO properties. Finally, this paper considers the unique difficulties of the current situation relative to past vacant-housing scenarios and concludes that many nonprofits may wish to pursue alternative, non-redevelopment strategies

Analyzing the solutions of DEA through information visualization and data mining techniques: SmartDEA framework

Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations, which is of vital practical importance in managerial decision making. DEA provides a significant amount of information from which analysts and managers derive insights and guidelines to promote their existing performances. Regarding to this fact, effective and methodologic analysis and interpretation of DEA solutions are very critical. The main objective of this study is then to develop a general decision support system (DSS) framework to analyze the solutions of basic DEA models. The paper formally shows how the solutions of DEA models should be structured so that these solutions can be examined and interpreted by analysts through information visualization and data mining techniques effectively. An innovative and convenient DEA solver, SmartDEA, is designed and developed in accordance with the proposed analysis framework. The developed software provides a DEA solution which is consistent with the framework and is ready-to-analyze with data mining tools, through a table-based structure. The developed framework is tested and applied in a real world project for benchmarking the vendors of a leading Turkish automotive company. The results show the effectiveness and the efficacy of the proposed framework

Life course building epidemiology: An alternative approach to the collection and analysis of carbon emission data

Developing policy for the reduction of the carbon emissions due to buildings requires models for energy usage that incorporate social, behavioural, and environmental factors in addition to the physical properties and technical specifications of the buildings. Marked parallels exist with some of the more intractable public health issues, such as rising levels of obesity. Recently, health researchers have recognized the importance of taking a broader life-course approach to epidemiology in order to examine the degree that long-term health outcomes are set in early life and the extent that these may be mediated or mitigated by subsequent growth and development, as well as by intervention strategies. Life course epidemiology as applied in building science, where energy usage is treated as analogous to poor health outcomes, provides an alternative approach for the construction of causal models that allow for complex interactions between social and technical factors as well as long term effects. It can provide a useful framework for the successful management and analysis of longitudinal studies and may prove particularly effective in identifying the type, timing, and targeting of intervention strategies to produce optimal outcomes in terms of absolute reductions of carbon emissions and resilience of building performance to external stresses, such as those imposed by climate change. An example based on a study in Milton Keynes (London), which is currently in progress, is used to illustrate the way causal models may help elucidate the complex interactions between factors that influence energy usage