Search

The adoption rate of residential solar photovoltaic (PV) systems in the US has grown exponentially in the past two decades. However, from a human-centered design perspective, there is a lack of clear understanding of what current users need and want from solar PV systems and from the experience of installing solar. In this study, we interviewed 18 solar stakeholders and conducted surveys of 1,773 homeowners including both solar adopters and non-adopters in California and Massachusetts. We analyzed the data using discrete choice theory and showed that cost savings, solar system reliability, installer warranty, and reviewer ratings of the installer were the most important factors when these homeowners considered purchasing a solar system. Preference differences were discovered between adopters and non-adopters, and with state, age, and income. Via surveys of current solar adopters' experiences of installing residential solar panels, we found that solar owners ranked installer reliability as even more important than price. The findings are intended to inform designers, engineers, and manufacturers as they create more compelling residential solar PV systems and to inform installers in designing better installation services. The ultimate goal is to promote renewable energy technology and reduce global greenhouse gas emissions. • Savings, warranty, and rating are key factors for homeowners' choice of solar installers. • Savings and reliability are key when homeowners choose solar systems. • Affluent homeowners have stronger preference for new-tech, low-visibility panels. • Older homeowners have stronger preferences for long warranties and micro-inverters. • Solar owners rank installer reliability & responsiveness as more important than price. [ABSTRACT FROM AUTHOR]

We develop and estimate a statistical model of neighborhood choice that draws on insights from cognitive science and decision theory as well as qualitative studies of housing search. The model allows for a sequential decision process and the possibility that people consider a small and selective subset of all potential destinations. When combined with data from the Los Angeles Family and Neighborhood Survey, our model reveals that affordability constraints and households' tendency toward short-distance moves lead blacks and Hispanics to have racially stratified choice sets in which their own group is disproportionately represented. We use an agent-based model to assess how racially stratified choice sets contribute to segregation outcomes. Our results show that cognitive decision strategies can amplify patterns of segregation and inequality. [ABSTRACT FROM AUTHOR]

What factors explain stakeholder benefit-cost expectations for participating in a collaborative institution? This article examines this question by applying a version of the collective interest model. The case study includes original data from a mail-in questionnaire and in-person interviews of stakeholders' expectations before the start of a collaborative process to establish marine-protected areas in California. The results provide little support for the traditional variables in the collective interest model with null results for group and personal efficacy. Selective incentives, especially putting in your own time versus company time, are important in explaining stakeholders' benefit-cost expectations. The results show that ally efficacy is an important factor, suggesting that perceptions of allies compared to opponents shape initial expectations for a collaborative process. This article adds to the research on political participation in environmental management by presenting a rare exploration of ex ante beliefs before the start of a collaborative planning institution. [ABSTRACT FROM AUTHOR]

Numerous attempts have been made to incorporate Operations Research (OR) techniques in the management of health care facilities but, for various reasons, success has only been modest. This paper outlines the rationale utilized to develop an OR department at the VA Hospital in Brentwood, California, and describes two studies undertaken by the OR department. The discussion includes the types of projects that should be undertaken, and suggested ways to implement study recommendations. The overall progress of the OR department in improving organizational efficiency is evaluated at the end of the paper. [ABSTRACT FROM AUTHOR]

In a recent article in Management Science. W. F. Massy [2] outlines an interesting difference equation model of the Stanford University budget system. He proceeds then to solve for first and second order (i.e., short-term) balanced budget conditions. However. Massy's assertion that the balanced budget requirement cannot be modeled "effectively" for an extended time horizon is inaccurate. This note shows that such long-range solutions are readily available from the eigenstructure of his model. We derive simple sufficient conditions for maintaining balanced university budgets. Related issues of balanced budget attainability, empirical correspondence, and policy feasibility are also discussed. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to demonstrate the use of the set theoretic model of organizations developed by Mackenzie in the study of complex market organizations. Part one briefly outlines the mathematical development of Mackenzie's model. Part two describes the organization and structure of the wood products market in Los Angeles within the framework of this model. [ABSTRACT FROM AUTHOR]

The article relates a study on neurobiology, which investigates correlated brain activity in the efficiency and fairness of decision making. It mentions that Steven Quartz and colleagues of the California Institute of Technology in Pasadena, California, using functional magnetic resonance imaging, found that more efficient decisions correlated with more activity in a brain region called the putamen, whereas decisions that emphasized fairness correlated with more activity in the insula, which is involved with emotional processing.

Animals often select one item from a set of candidates, as when choosing a foraging site or mate, and are expected to possess accurate and efficient rules for acquiring information and making decisions. Little is known, however, about the decision rules animals use. We compare patterns of information sampling by western scrub-jays (Aphelocoma californica) when choosing a nut with three decision rules: best of n (BN), flexible threshold (FT), and comparative Bayes (CB). First, we use a null hypothesis testing approach and find that the CB decision rule, in which individuals use past experiences to make nonrandom assessment and choice decisions, produces patterns of behavior that more closely correspond to observed patterns of nut sampling in scrub-jays than the other two rules. This approach does not allow us to quantify how much better CB is at predicting scrub-jay behavior than the other decision rules. Second, we use a model selection approach that uses Akaike Information Criteria to quantify how well alternative models approximate observed data. We find that the CB rule is much more likely to produce the observed patterns of scrub-jay behavior than the other rules. This result provides some of the best empirical evidence of the use of Bayesian information updating by a nonhuman animal.

Health Systems Agencies (HSAs), the new regional health planning agencies established by the National Health Planning and Resources Development Act of 1974, have as their major goals quality, accessibility, continuity and cost containment. One of the tools for cost containment available to HSAs is their active participation in the statewide certificate-of-need (CON) program. To help anticipate how HSAs may play their CON roles, this article reviews the CON decisionmaking processes of two Comprehensive Health Planning (CHP) agencies, the predecessors of HSAs. While most CHPs lacked specific health plans and powers. the two California agencies examined have had both regional plans and roles in CON programs comparable to the present HSAs'. Our focus is on the decisionmaking process rather than the effectiveness of CON programs. A simple descriptive model is developed based on the assumptions that the planners seek satisfactory, rather than optimal solutions and that the data available are extremely limited. The cases analyzed suggest that, while most projects exceed the bed need standards, institutions were almost always able to demonstrate a need through various special circumstances. Once a need has been shown, the agency was able to deny an application only if a better alternative were available. This study suggests two approaches to improving regional health planning decisionmaking. First, identified needs can be better met either by increasing the agency's ability to generate alternatives or by encouraging health facilities to submit competing applications. Second, a regional health care budget would force the agency to make choices among competing needs.