Search Results (5)

The European Green Deal indicates the renovation of both public and private buildings as a key element for the improvement of energy efficiency in the building stock, in order to reach the goals of the document itself. New incentives, also including density bonus, can significantly contribute to foster diffuse actions. In Italy, the density bonus is under testing: the current framework has produced profitability for regeneration in some areas and unprofitability in others. This has led to a non-diffuse renewal, widening differences in richness and quality throughout territories subjected to the same reward measure. A territory is characterized by a high degree of typological and qualitative fragmentation and dissimilarity. Thus, the aim of the present work is the construction of a model that allows for identifying the entity of the reward measure in terms of density bonus. Density bonus can determine the feasibility of renovation interventions—in economic-financial terms and in relation to urban impact—taking into account the characteristics of the context (or micro-context) where they are performed. The research model is based on a Balance Sheet Model and is applied to the city of Florence. The model suggests an innovative approach where urban, landscape and environmental impacts produced by the density bonus are evaluated according to the economic amount needed for their mitigation. The expected results in the application of the model consist in the definition of an iso-bonus map organized by areas. Full article

This article raises the issue of decision support system (DSS) development in enterprises concerning the compensation system (CS). The topic is relevant as the CS is one of the main components in human resource management in business. A key element of such DSSs is CS models that provide predictive analytics. Such models are able to give information about how a particular CS affects output, product quality, employee satisfaction, and wage fund. Thus, the main goal of this article is to obtain a CS statistical model and its formulas for determining the probability densities of resultant indicators. To achieve this goal, the authors conducted several blocks of research. Firstly, mathematical formalization of CS functionality was described. Secondly, a statistical model of CS was built. Thirdly, calculations of CS result indicators were made. Reliable scientific methods were used: black box modeling and statistical modeling. This article proposes a statistical and analytical model. As an example, a piecework-bonus system statistical model is demonstrated. The discussion derives formulas of integral estimations showing the probability density of the resulting CS indicators and the related statistical characteristics. These results can be used to predict the behavior of the workforce. This constitutes the scientific novelty of the study, which will establish significant advances in the development of DSSs in the field of labor economics and HR management. Full article

A central challenge in generative design is the exploration of vast number of solutions. In this work, we extend two major density-based structural topology optimization (STO) methods based on four classes of exploration algorithms of reinforcement learning (RL) to STO problems, which approaches generative design in a new way. The four methods are: first, using $\epsilon$ -greedy policy to disturb the search direction; second, using upper confidence bound (UCB) to add a bonus on sensitivity; last, using Thompson sampling (TS) as well as information-directed sampling (IDS) to direct the search, where the posterior function of reward is fitted by Beta distribution or Gaussian distribution. Those combined methods are evaluated on some structure compliance minimization tasks from 2D to 3D, including the variable thickness design problem of an atmospheric diving suit (ADS). We show that all methods can generate various acceptable design options by varying one or two parameters simply, except that IDS fails to reach the convergence for complex structures due to the limitation of computation ability. We also show that both Beta distribution and Gaussian distribution work well to describe the posterior probability. Full article

In the year 2017, about 89% of the total energy consumed in the US was produced using non-renewable energy sources, and about 43% of tenant households were cost burdened. Local governments are in a unique position to facilitate green affordable housing, that could reduce cost burdens, environmental degradation, and environmental injustice. Nonetheless, limited studies have made progress on the costs and benefits of green affordable housing, to guide decision-making, particularly in small communities. This study investigates density bonus options for green affordable housing by analyzing construction costs, transaction prices, and spillover effects of green certifications and affordable housing units. The authors employ pooled cross-sectional construction cost and price data from 422 Low-Income Housing Tax Credit (LIHTC) projects and 11,016 Multiple Listing Service (MLS) transactions in Virginia. Using hedonic regression analyses controlling for mediating factors, the study finds that the new construction of market-rate green certified houses is associated with small upfront costs, but large and statistically significant price premiums. In addition, the construction of market-rate green certified houses has large and statistically significant spillover effects on existing non-certified houses. Existing non-certified affordable housing units show small and often insignificant negative price impacts on the transaction prices of surrounding properties. The study concludes that the magnitude of social benefits associated with green building justifies the local provision of voluntary programs for green affordable housing, where housing is expensive relative to its basic cost of production. Full article