Defining failure in the nonprofit organization: The case of four human service agencies

Private nonprofit human service organizations provide a spectrum of services that aim to resolve societal problems. Their failure may leave needed and desired services unprovided or not provided sufficiently to meet public demand. However, the concept of organizational failure has not been examined for the nonprofit organization. This research addresses the deficiency in the literatures of organization failure and nonprofit organizations.^ An eight category typology, developed from a review of the current literature and findings from expert interviews, is initially presented to define nonprofit organization failure. A multiple case study design is used to test the typology in four nonprofit human service delivery agencies. The case analysis reduces the typology to five types salient to nonprofit organization failure: input failure, legitimacy failure, adaptive failure, management failure and leadership failure.^ The resulting five category typology is useful to both theory builders and nonprofit practitioners. For theory development, the interaction of the failure types extends the literature and lays a foundation for a theory of nonprofit organization failure that diffuses management and leadership across all of the failure types, highlights management and leadership failure as collective functions shared by paid staff and the volunteer board of directors, and emphasizes the importance of organization legitimacy.^ From a practical perspective, the typology provides a tool for diagnosing failure in the nonprofit organization. Using the management indicators developed for the typology, a checklist of the warning signals of potential failure, emphasizing the key types of management and leadership, offers nonprofit decision makers a priori examination of an organization's propensity for failure. ^

Development and implementation of a tool to assess the micro/macro elements in an organization

This study examines the congruency of planning between organizational structure and process, through an evaluation and planning model known as the Micro/Macro Dynamic Planning Grid. The model compares day-to-day planning within an organization to planning imposed by organizational administration and accrediting agencies. A survey instrument was developed to assess the micro and macro sociological analysis elements utilized by an organization.^ The Micro/Macro Dynamic Planning Grid consists of four quadrants. Each quadrant contains characteristics that reflect the interaction between the micro and macro elements of planning, objectives and goals within an organization. The Over Macro/Over Micro, Quadrant 1, contains attributes that reflect a tremendous amount of action and ongoing adjustments, typical of an organization undergoing significant changes in either leadership, program and/or structure. Over Macro/Under Micro, Quadrant 2, reflects planning characteristics found in large, bureaucratic systems with little regard given to the workings of their component parts. Under Macro/Under Micro, Quadrant 3, reflects the uncooperative, uncoordinated organization, one that contains a multiplicity of viewpoints, language, objectives and goals. Under Macro/Under Micro, Quadrant 4 represents the worst case scenario for any organization. The attributes of this quadrant are very reactive, chaotic, non-productive and redundant.^ There were three phases to the study: development of the initial instrument, pilot testing the initial instrument and item revision, and administration and assessment of the refined instrument. The survey instrument was found to be valid and reliable for the purposes and audiences herein described.^ In order to expand the applicability of the instrument to other organizational settings, the survey was administered to three professional colleges within a university.^ The first three specific research questions collectively answered, in the affirmative, the basic research question: Can the Micro/Macro Dynamic Planning Grid be applied to an organization through an organizational development tool? The first specific question: Can an instrument be constructed that applies the Micro/Macro Dynamic Planning Grid? The second specific research question: Is the constructed instrument valid and reliable? The third specific research question: Does an instrument that applies the Micro/Macro Dynamic Planning Grid assess congruency of micro and macro planning, goals and objectives within an organization? The fourth specific research question: What are the differences in the responses based on roles and responsibilities within an organization? involved statistical analysis of the response data and comparisons obtained with the demographic data. (Abstract shortened by UMI.) ^

On the fundamentals of research and development (R&D) spillovers in competitive markets

Rivals may voluntarily share Research and Development (R&D) results even in the absence of any binding agreements or collusion. In a model where rival firms engage in non-cooperative independent R&D process, we used optimization and game theory analysis to study the equilibrium strategy of the firms. Our work showed that, while minimal spillover is always equilibrium, there may be another equilibrium where firms may reciprocally choose high, sometimes perfect, spillover rates. The incentive for sharing R&D output is based on firms' expectations of learning from their rivals' R&D progress in the future. This leads to strategic complementarities between the firms' choices of spillover rates and thus policy implication follows. ^ Public research agencies can contribute more to social welfare by providing research as public goods. In a non-cooperative public-private research relationship where parallel R&D is conducted, by making its R&D results accessible, the public research agency can stimulate private spillovers, even if there exists rivalry among the private firms who can benefit from such spillovers. ^

An analysis of teachers' perceptions of informal science professional development

Science professional development, which is fundamental to science education improvement, has been described as being weak and fragmentary. The purpose of this study was to investigate teachers' perceptions of informal science professional development to gain an in-depth understanding of the essence of the phenomenon and related science-teaching dispositions. Based on the frameworks of phenomenology, constructivism, and adult learning theory, the focus was on understanding how the phenomenon was experienced within the context of teachers' everyday world. ^ Data were collected from eight middle-school teachers purposefully selected because they had participated in informal programs during Project TRIPS (Teaching Revitalized Through Informal Programs in Science), a collaboration between the Miami-Dade school district, government agencies (including NASA), and non-profit organizations (including Audubon of Florida). In addition, the teachers experienced hands-on labs offered through universities (including the University of Arizona), field sites, and other agencies. ^ The study employed Seidman's (1991) three-interview series to collect the data. Several methods were used to enhance the credibility of the research, including using triangulation of the data. The interviews were transcribed, color-coded and organized into six themes that emerged from the data. The themes included: (a) internalized content knowledge, (b) correlated hands-on activities, (c) enhanced science-teaching disposition, (d) networking/camaraderie, (e) change of context, and (f) acknowledgment as professionals. The teachers identified supportive elements and constraints related to each theme. ^ The results indicated that informal programs offering experiential learning opportunities strengthened understanding of content knowledge. Teachers implemented hands-on activities that were explicitly correlated to their curriculum. Programs that were conducted in a relaxed context enhanced teachers' science-teaching dispositions. However, a lack of financial and administrative support, perceived safety risks, insufficient reflection time, and unclear itineraries impeded program implementation. The results illustrated how informal educators can use this cohesive model as they develop programs that address the supports and constraints to teachers' science instruction needs. This, in turn, can aid teachers as they strive to provide effective science instruction to students; notions embedded in reforms. Ultimately, this can affect how learners develop the ability to make informed science decisions that impact the quality of life on a global scale. ^

Development of risk based treatability and engineering measures for reducing exposure to lead contaminated media in the Miami inner city, Florida

A major consequence of contamination at the local level’s population as it relates to environmental health and environmental engineering is childhood lead poisoning. Environmental contamination is one of the pressing environmental concerns facing the world today. Current approaches often focus on large contaminated industrial size sites that are designated by regulatory agencies for site remediation. Prior to this study, there were no known published studies conducted at the local and smaller scale, such as neighborhoods, where often much of the contamination is present to remediate. An environmental health study of local lead-poisoning data in Liberty City, Little Haiti and eastern Little Havana in Miami-Dade County, Florida accounted for a disproportionately high number of the county’s reported childhood lead poisoning cases. An engineering system was developed and designed for a comprehensive risk management methodology that is distinctively applicable to the geographical and environmental conditions of Miami-Dade County, Florida. Furthermore, a scientific approach for interpreting environmental health concerns, while involving detailed environmental engineering control measures and methods for site remediation in contained media was developed for implementation. Test samples were obtained from residents and sites in those specific communities in Miami-Dade County, Florida (Gasana and Chamorro 2002). Currently lead does not have an Oral Assessment, Inhalation Assessment, and Oral Slope Factor; variables that are required to run a quantitative risk assessment. However, various institutional controls from federal agencies’ standards and regulation for contaminated lead in media yield adequate maximum concentration limits (MCLs). For this study an MCL of .0015 (mg/L) was used. A risk management approach concerning contaminated media involving lead demonstrates that the linkage of environmental health and environmental engineering can yield a feasible solution.

Left behind: A farmer's fate in the age of sustainable development

Globalization is eroding the livelihoods of small farmers, a significant and vulnerable class, particularly in the developing world. The cost-price squeeze stemming from trade liberalization places farmers in a race to the bottom that leads to displacement, poverty, and environmental degradation. Scholars and activists have proposed that alternative trade initiatives offer a unique opportunity to reverse this trend by harnessing the power of the markets to reward producers of goods with embedded superior cultural, environmental, and social values. Alternative trade via certification schemes have become a de facto prescription for any location where there is a need to conciliate economic interest with conservation imperatives. Partnerships among commodity production farmers, elite manufacturers and wealthy northern consumers/activists do not necessarily have win-win outcomes. Paradoxically, the partnerships of farmers with external agencies have unexpected results. These partnerships develop into dependent relationships that become unsustainable in the absence of further transfers of capital. The institutions born of these partnerships are fragile. When these fledging institutions fail, farmers are left in the same situation that they were before the partnership, with only minor improvements to show after spending considerable amounts of social and financial capital. I hypothesize that these failures are born out of a belief in a universal understanding of sustainability. A discursive emphasis on consensus, equity and mutual benefit hides the fact that what for consumers it is a matter of choice, for producers is a matter of survival. The growth in consumers’ demand for certified products creates a race for farmers to meet these standards. My findings suggest that this race generates economically perverse effects. First, producers enter into a certification treadmill. Second, the local need for economic sustainability is ignored. Third, commodity based alternative trade schemes increase the exposure of communities to global shocks. I conclude by calling for a careful reassessment of sustainable development projects that promote certification schemes. The designers and implementers of these programs must include farmers’ agenda in the planning of these programs.

Development of a dynamic headspace concentration technique for the non-contact sampling of human odor samples and the creation of canine training aids

Human scent and human remains detection canines are used to locate living or deceased humans under many circumstances. Human scent canines locate individual humans on the basis of their unique scent profile, while human remains detection canines locate the general scent of decomposing human remains. Scent evidence is often collected by law enforcement agencies using a Scent Transfer Unit, a dynamic headspace concentration device. The goals of this research were to evaluate the STU-100 for the collection of human scent samples, and to apply this method to the collection of living and deceased human samples, and to the creation of canine training aids. The airflow rate and collection material used with the STU-100 were evaluated using a novel scent delivery method. Controlled Odor Mimic Permeation Systems were created containing representative standard compounds delivered at known rates, improving the reproducibility of optimization experiments. Flow rates and collection materials were compared. Higher air flow rates usually yielded significantly less total volatile compounds due to compound breakthrough through the collection material. Collection from polymer and cellulose-based materials demonstrated that the molecular backbone of the material is a factor in the trapping and releasing of compounds. The weave of the material also affects compound collection, as those materials with a tighter weave demonstrated enhanced collection efficiencies. Using the optimized method, volatiles were efficiently collected from living and deceased humans. Replicates of the living human samples showed good reproducibility; however, the odor profiles from individuals were not always distinguishable from one another. Analysis of the human remains samples revealed similarity in the type and ratio of compounds. Two types of prototype training aids were developed utilizing combinations of pure compounds as well as volatiles from actual human samples concentrated onto sorbents, which were subsequently used in field tests. The pseudo scent aids had moderate success in field tests, and the Odor pad aids had significant success. This research demonstrates that the STU-100 is a valuable tool for dog handlers and as a field instrument; however, modifications are warranted in order to improve its performance as a method for instrumental detection.

Development of safety performance functions for SafetyAnalyst applications in Florida

In 2010, the American Association of State Highway and Transportation Officials (AASHTO) released a safety analysis software system known as SafetyAnalyst. SafetyAnalyst implements the empirical Bayes (EB) method, which requires the use of Safety Performance Functions (SPFs). The system is equipped with a set of national default SPFs, and the software calibrates the default SPFs to represent the agency's safety performance. However, it is recommended that agencies generate agency-specific SPFs whenever possible. Many investigators support the view that the agency-specific SPFs represent the agency data better than the national default SPFs calibrated to agency data. Furthermore, it is believed that the crash trends in Florida are different from the states whose data were used to develop the national default SPFs. In this dissertation, Florida-specific SPFs were developed using the 2008 Roadway Characteristics Inventory (RCI) data and crash and traffic data from 2007-2010 for both total and fatal and injury (FI) crashes. The data were randomly divided into two sets, one for calibration (70% of the data) and another for validation (30% of the data). The negative binomial (NB) model was used to develop the Florida-specific SPFs for each of the subtypes of roadway segments, intersections and ramps, using the calibration data. Statistical goodness-of-fit tests were performed on the calibrated models, which were then validated using the validation data set. The results were compared in order to assess the transferability of the Florida-specific SPF models. The default SafetyAnalyst SPFs were calibrated to Florida data by adjusting the national default SPFs with local calibration factors. The performance of the Florida-specific SPFs and SafetyAnalyst default SPFs calibrated to Florida data were then compared using a number of methods, including visual plots and statistical goodness-of-fit tests. The plots of SPFs against the observed crash data were used to compare the prediction performance of the two models. Three goodness-of-fit tests, represented by the mean absolute deviance (MAD), the mean square prediction error (MSPE), and Freeman-Tukey R2 (R2FT), were also used for comparison in order to identify the better-fitting model. The results showed that Florida-specific SPFs yielded better prediction performance than the national default SPFs calibrated to Florida data. The performance of Florida-specific SPFs was further compared with that of the full SPFs, which include both traffic and geometric variables, in two major applications of SPFs, i.e., crash prediction and identification of high crash locations. The results showed that both SPF models yielded very similar performance in both applications. These empirical results support the use of the flow-only SPF models adopted in SafetyAnalyst, which require much less effort to develop compared to full SPFs.

Development, validation and uncertainty analysis of quantitative structure and activity relationship models for Log P of disinfection by -products

Hydrophobicity as measured by Log P is an important molecular property related to toxicity and carcinogenicity. With increasing public health concerns for the effects of Disinfection By-Products (DBPs), there are considerable benefits in developing Quantitative Structure and Activity Relationship (QSAR) models capable of accurately predicting Log P. In this research, Log P values of 173 DBP compounds in 6 functional classes were used to develop QSAR models, by applying 3 molecular descriptors, namely, Energy of the Lowest Unoccupied Molecular Orbital (ELUMO), Number of Chlorine (NCl) and Number of Carbon (NC) by Multiple Linear Regression (MLR) analysis. The QSAR models developed were validated based on the Organization for Economic Co-operation and Development (OECD) principles. The model Applicability Domain (AD) and mechanistic interpretation were explored. Considering the very complex nature of DBPs, the established QSAR models performed very well with respect to goodness-of-fit, robustness and predictability. The predicted values of Log P of DBPs by the QSAR models were found to be significant with a correlation coefficient R2 from 81% to 98%. The Leverage Approach by Williams Plot was applied to detect and remove outliers, consequently increasing R 2 by approximately 2% to 13% for different DBP classes. The developed QSAR models were statistically validated for their predictive power by the Leave-One-Out (LOO) and Leave-Many-Out (LMO) cross validation methods. Finally, Monte Carlo simulation was used to assess the variations and inherent uncertainties in the QSAR models of Log P and determine the most influential parameters in connection with Log P prediction. The developed QSAR models in this dissertation will have a broad applicability domain because the research data set covered six out of eight common DBP classes, including halogenated alkane, halogenated alkene, halogenated aromatic, halogenated aldehyde, halogenated ketone, and halogenated carboxylic acid, which have been brought to the attention of regulatory agencies in recent years. Furthermore, the QSAR models are suitable to be used for prediction of similar DBP compounds within the same applicability domain. The selection and integration of various methodologies developed in this research may also benefit future research in similar fields.

Development of Safety Performance Functions for SafetyAnalyst Applications in Florida

In 2010, the American Association of State Highway and Transportation Officials (AASHTO) released a safety analysis software system known as SafetyAnalyst. SafetyAnalyst implements the empirical Bayes (EB) method, which requires the use of Safety Performance Functions (SPFs). The system is equipped with a set of national default SPFs, and the software calibrates the default SPFs to represent the agency’s safety performance. However, it is recommended that agencies generate agency-specific SPFs whenever possible. Many investigators support the view that the agency-specific SPFs represent the agency data better than the national default SPFs calibrated to agency data. Furthermore, it is believed that the crash trends in Florida are different from the states whose data were used to develop the national default SPFs. In this dissertation, Florida-specific SPFs were developed using the 2008 Roadway Characteristics Inventory (RCI) data and crash and traffic data from 2007-2010 for both total and fatal and injury (FI) crashes. The data were randomly divided into two sets, one for calibration (70% of the data) and another for validation (30% of the data). The negative binomial (NB) model was used to develop the Florida-specific SPFs for each of the subtypes of roadway segments, intersections and ramps, using the calibration data. Statistical goodness-of-fit tests were performed on the calibrated models, which were then validated using the validation data set. The results were compared in order to assess the transferability of the Florida-specific SPF models. The default SafetyAnalyst SPFs were calibrated to Florida data by adjusting the national default SPFs with local calibration factors. The performance of the Florida-specific SPFs and SafetyAnalyst default SPFs calibrated to Florida data were then compared using a number of methods, including visual plots and statistical goodness-of-fit tests. The plots of SPFs against the observed crash data were used to compare the prediction performance of the two models. Three goodness-of-fit tests, represented by the mean absolute deviance (MAD), the mean square prediction error (MSPE), and Freeman-Tukey R2 (R2FT), were also used for comparison in order to identify the better-fitting model. The results showed that Florida-specific SPFs yielded better prediction performance than the national default SPFs calibrated to Florida data. The performance of Florida-specific SPFs was further compared with that of the full SPFs, which include both traffic and geometric variables, in two major applications of SPFs, i.e., crash prediction and identification of high crash locations. The results showed that both SPF models yielded very similar performance in both applications. These empirical results support the use of the flow-only SPF models adopted in SafetyAnalyst, which require much less effort to develop compared to full SPFs.