Rainfall interception by Santa Monica's municipal urban forest

Effects of urban forests on rainfall interception and runoff reduction have been conceptualized, but not well quantified. In this study rainfall interception by street and park trees in Santa Monica, California is simulated. A mass and energy balance rainfall interception model is used to simulate rainfall interception processes (e.g., gross precipitation, free throughfall, canopy drip, stemflow, and evaporation). Annual rainfall interception by the 29,299 street and park trees was 193,168 m³ (6.6 m³/tree), or 1.6% of total precipitation. The annual value of avoided stormwater treatment and flood control costs associated with reduced runoff was $110,890 ($3.60/tree). Interception rate varied with tree species and sizes. Rainfall interception ranged from 15.3% (0.8 m³/tree) for a small Jacaranda mimosifolia (3.5 cm diameter at breast height) to 66.5% (20.8 m³/tree) for a mature Tristania conferta (38.1 cm). In a 25-year storm, interception by all street and park trees was 12,139.5 m³ (0.4%), each tree yielding $0.60 (0.4 m³/tree) in avoided flood control costs. Rainfall interception varied seasonally, averaging 14.8% during a 21.7 mm winter storm and 79.5% during a 20.3 mm summer storm for a large, deciduous Platanus acerifolia tree. Effects of differences in temporal precipitation patterns, tree population traits, and pruning practices on interception in Santa Monica, Modesto, and Sacramento, California are described.     

THE BIAS OF COST CONTROL CHARTS TOWARD TYPE II ERRORS

Application of control charts has significantly improved process control by explicitly recognizing uncontrollable variation in the process. A dangerous misapplication of the technique involves the use of control charts with data produced by accounting systems. This paper points out the weaknesses inherent in using aggregated accounting data for inferences about cost control.     

AN EMPIRICAL EXAMINATION OF SOCIAL POWER IN TERMS OF DECISION THEORY1

The paper presents an extension of decision theory to the analysis of social power. The power of a person, A, over another person, B, is viewed in terms of the effect A has on B's decision. The analysis is based on the idea that B's decision regarding the performance of alternative behaviors is a function of 1) B's utility for the consequences of the behaviors and 2) B's subjective probabilities that the behaviors will lead to these consequences. In these terms, A's power over B lies in A's ability to mediate various consequences for B, contingent upon B's compliance or noncompliance. Subjects were asked to consider eight situations in which hypothetical individuals had to make a choice between two courses of action. In each situation another person (A) was attempting to induce the hypothetical individual (B) to choose one of the alternatives, while various situational factors were influencing B to choose the other alternative. The subjects were asked to consider B's utilities and subjective probabilities in each situation and to indicate whether or not B should comply with A and to make ratings of A's power. The decision theory analysis did well in predicting whether or not subjects would indicate that B should comply with A. Also, subjects generally were able to correctly specify whether A or the situational factors had more influence over B's decision. Finally, the subjects' ratings of A's power in the eight situations were highly related to the decision theoretic measure of power.     

A STRATEGY FOR INTEGRATING QUANTITATIVE TECHNIQUES INTO THE BUSINESS CURRICULUM*

Quantitative methods courses play an increasingly significant role in the programs of Schools of Business. However, maximum utilization of the concepts can occur only when these quantitative techniques have been integrated into the various functional areas via a faculty knowledgeable with such techniques and their applications. Lacking sufficient stimuli, this integrative process is observed to be one of an evolutionary nature. This article presents a strategy for stimulation of this process.     

EVALUATION OF MULTIATTRIBUTE ALTERNATIVES: ADDITIVE VERSUS CONFIGURAL UTILITY MEASUREMENT

A model for measuring subjective evaluations of multiple component alternatives is developed and tested in the context of business students' evaluations of professorial candidates for tenured positions. The model is based on a type of ANOVA formulation in which the response variable need only be rank ordered. That is, arbitrary monotonic functions of subjective responses can be made that optimize a well-defined badness of fit measure. Application of the model indicates that metric analysis of the response data can exhibit a large number of configural (interaction) effects that may be a reflection of how subjects use rating scales rather than anything more basic in their combination of multiple component cues. Implications of these findings for the modeling of multiple component choices are discussed.     

RESIDENTIAL MORTGAGE RISK CHARACTERISTICS*

This paper applies discriminant analysis to a relatively large sample of residential mortgages-some of which have defaulted or have been foreclosed and others of which have remained untroubled at least until the date of the last observation-in an attempt to derive a function which would allow mortgage lenders to increase their accuracy of predicting mortgage difficulty. From the data available for testing, no improvement in predictability is obtained, because it is thought that the data may already have been badly biased by the screening process of the loan officers which had already taken place and by the post-loan origination nature of the important variables in mortgage difficulty. The latter is confirmed by discriminant models of post-origination variables which are successful. It is concluded that changes in home value, changes in mortgagor income, mortgage assumption, and regional economic considerations are the major explanations of mortgage difficulty.     

THE DEVELOPMENT OF AN INTEGRATIVE CURRICULUM IN AN UNDERGRADUATE BUSINESS PROGRAM*

This paper describes how the core portion of the undergraduate business program at Indiana University was revised to facilitate integration of basic functionally oriented decision making skills and thus help students gain a deeper understanding of the interdependence of business decisions. It relates, in essence, why and how a single computer-oriented case study which demanded a solution to a large-scale, unified finance-marketing-production problem was used at Indiana University, mentions how we plan to accomplish further integration of functional material, and provides some insight into student reaction to what was, in fact, a massive project from both student and administrative points of view.