This study attempts to answer the question; does evolutionary theory provide a ‘good’ explanatory framework for examining the phenomenon of technological innovation? In doing so, the study critically examines mainstream marketing’s in-place explanatory frameworks, offers an explanation of ‘evolution’ based on new insights from a broad range of (sub)disciplines, and makes the practical proposition that this explanation is a ‘good’ analogous representation of the technological innovation process. As an alternative to the ‘scientific empiricist’ approach that dominates much of marketing’s research into technological innovation, the study develops a research methodology that is based within a postmodern philosophy, adopts an epistemology of transcendental realism, bases the research design on abduction and textual explanation, and brings together a research method based on the criteria of interesting, plausibility and acceptability. Familiarisation with mainstream marketing’s explanatory frameworks for research into technological innovation identified Diffusion theory, New Product Development theory and Network theory as dominant. It is concluded that these frameworks are based on problematic theoretical foundations, a situation considered as largely due to a pre-occupation with assumptions that are atomistic, reductionistic, deterministic, gradualistic and mechanistic in nature. It is argued, that in concert with the ‘socialised’ dominance of mathematical form over conceptual substance, mainstream marketing’s research into technological innovation is locked into a narrow range of ‘preordained axiomatics’. The explanation of ‘evolution’ offered within the study is based on a why, what, how, when and where format. The resultant explanation represents a significant departure from the (neo)Darwinian biological perspective that tends to dominate evolutionary explanations of socio-economic behaviour, in that the focus is on the principles (and associated conceptualizations) of ‘variation’, ‘selection’ and ‘preservation’ within the broader context of open and dissipative systems. The offered explanation presents a number of theoretical ideas, and in particular, that evolution can only occur in a ‘multidimensional space of possibilities’, denotes a process of ‘adaptive emergence’, and is essentially concerned with ‘on-going resilience through adaptability’. The practical proposition is made that the offered explanation of ‘evolution’ can be used in an ‘as if’ manner, that is, the principles of ‘variation’, ‘selection’, and ‘preservation’ (and the meanings ascribed to them through conceptualization) are analogically transferable to the technological innovation research area. The proposition is supported through reference to theoretical and empirical research, highlighting the similarity with respect to the generative mechanisms, structures and contingent conditions underpinning both ‘evolution’ and ‘technological innovation’.

This study attempts to answer the question; does evolutionary theory provide a ‘good’ explanatory framework for examining the phenomenon of technological innovation? In doing so, the study critically examines mainstream marketing’s in-place explanatory frameworks, offers an explanation of ‘evolution’ based on new insights from a broad range of (sub)disciplines, and makes the practical proposition that this explanation is a ‘good’ analogous representation of the technological innovation process. As an alternative to the ‘scientific empiricist’ approach that dominates much of marketing’s research into technological innovation, the study develops a research methodology that is based within a postmodern philosophy, adopts an epistemology of transcendental realism, bases the research design on abduction and textual explanation, and brings together a research method based on the criteria of interesting, plausibility and acceptability. Familiarisation with mainstream marketing’s explanatory frameworks for research into technological innovation identified Diffusion theory, New Product Development theory and Network theory as dominant. It is concluded that these frameworks are based on problematic theoretical foundations, a situation considered as largely due to a pre-occupation with assumptions that are atomistic, reductionistic, deterministic, gradualistic and mechanistic in nature. It is argued, that in concert with the ‘socialised’ dominance of mathematical form over conceptual substance, mainstream marketing’s research into technological innovation is locked into a narrow range of ‘preordained axiomatics’. The explanation of ‘evolution’ offered within the study is based on a why, what, how, when and where format. The resultant explanation represents a significant departure from the (neo)Darwinian biological perspective that tends to dominate evolutionary explanations of socio-economic behaviour, in that the focus is on the principles (and associated conceptualizations) of ‘variation’, ‘selection’ and ‘preservation’ within the broader context of open and dissipative systems. The offered explanation presents a number of theoretical ideas, and in particular, that evolution can only occur in a ‘multidimensional space of possibilities’, denotes a process of ‘adaptive emergence’, and is essentially concerned with ‘on-going resilience through adaptability’. The practical proposition is made that the offered explanation of ‘evolution’ can be used in an ‘as if’ manner, that is, the principles of ‘variation’, ‘selection’, and ‘preservation’ (and the meanings ascribed to them through conceptualization) are analogically transferable to the technological innovation research area. The proposition is supported through reference to theoretical and empirical research, highlighting the similarity with respect to the generative mechanisms, structures and contingent conditions underpinning both ‘evolution’ and ‘technological innovation’.

Work describes basic quantitative methods and their possible usage in IBM project management, it also substantiates the use of linear optimization software in real project

acase@tulane.edu / This dissertation research brings together disparate bodies of literature on environmental inequality, sociology of space, and feminist theories of intersectionality to bear on the location and distribution of environmental hazards in the form of landfills. Landfills pose a threat to both ecological sustainability as well as present risks to human health through contamination and pollution. While environmental inequality literatures have executed exceptional work into the dynamics of race and class with respect to the distribution of hazardous waste facilities, the literature is noticeably lacking with respect to identifying relationships between gender and environmental inequalities. Furthermore, many quantitative studies have exclusively focused on hazardous waste facilities as a singular measure of environmental inequality. This study advances the field in three major ways. First, through the inclusion of theorizations based on feminist intersectionality theories, this research empirically analyzes hypotheses derived from intersectionality theories to understand dynamics of gender-environment interactions. Second, this study extends analysis to all forms of waste containment—municipal, industrial, construction and demolition, and hazardous—to identify trends across the social fabric of the contiguous United States at the county level of analysis with respect to multiple forms of environmental hazards. Third, utilizing innovative analytic techniques, this research provides three unique and related strategies, geographic information systems, logistic binary regression, and structural equation modeling, to examine socio-environmental disparities. Findings from each analytic strategy inform the subsequent strategy. Findings suggest the importance of including gender indicators to account for the unique effect of gender and environmental inequality. Furthermore, results indicate the importance in applying intersectionality theories to environmental outcomes as well as empirically testing hypotheses derived from the largely theoretical and qualitatively backed field. Future research should focus on specific regional dynamics of identified socio-environmental interactions by including historical and qualitative data to triangulate quantitative findings. / 1 / Clare Cannon

Magister Pharmaceuticae - MPharm / Diabetes mellitus is a complex chronic condition and has become a major public health concern worldwide. Many diabetic patients are accessing primary health care (PHC) clinics for diabetes care. Diabetic patients who are considered stable are referred to chronic diseases of lifestyle club at the PHC facility. Effective management of this chronic condition requires a multidisciplinary team approach to diabetes care. Pharmacists are not often included in a multidisciplinary team and would consist of doctors, nurses and dieticians. Teams may be expanded and require specialist healthcare members’ expertise who can assist in the management of this disease, for example, ophthalmologists and podiatrists. Adherence to standard treatment guidelines (STGs) for the management of diabetes by healthcare professionals at a primary care level can improve glycemic control, decrease health costs and reduce the development of long-term diabetic complications.

This thesis has been partially OCRed. Please contact for further accessibility requests. / Several methods have been proposed and tested for calculating lower bounds on the objective function of facilities problems. These methods contribute to the efficiency of iterative solution methods by allowing the user to terminate the computation process when the objective function comes within a predetermined fraction of the optimal solution. Two of the existing bounding methods have been presented only for single facility location models with Euclidean (straight-line) distances. One of these methods uses the dual of the single facility location model to compute a lower bound. This thesis introduces a method for generating a feasible dual solution from any primal solution by means of a projection matrix. The projection matrix method is applied to single and multi-facility models. The second bounding method, which involves the solution of a rectilinear distance model to obtain a lower bound, is extended in this thesis to include a generalized, distance function and the multi-facility situation. Computation results for the two new bounding methods are compared with several existing bounding methods. These results should aid practitioners in selecting an appropriate bounding method for an iterative solution method to a facilities location problem. / Thesis / Doctor of Philosophy (PhD)

The analysis of big data points and the use of data analytics have proven successful in improving corporate business efficiencies, growing profits, and increasing competitive advantages. The theory of academic capitalism, which holds that institutions of higher education are becoming more like corporations due to declining operating funds and the need to become more efficient, transparent, and competitive, guided this study. Despite the positive outcomes that analytic tools may produce in advanced efficiencies and competitive growth, college academic administrators have not yet adopted these tools, due in part to barriers facing the administrators. The purpose of this phenomenological study was to explore the nature of those barriers in a community college. Ten academic managers in 6 community college divisions who reported accountability for criterion-based key performance indicators were interviewed on their perceived use of academic analytic tools and barriers in adopting these tools. The interviews were collected and analyzed through preliminary grouping, reducing and eliminating outliers, clustering descriptions into categories, and constructing themes. The managers' narratives suggested that there were 4 perceived barriers that prevented the adoption of tools such as organizational bureaucracy (climate), restricted organizational data (policy), training, and infrastructure. An important area for further research involves identifying the strategies managers could use to overcome these barriers. The findings of this study will assist college administrators in implementing analytic tools. Such tools will improve key performance indicators, resulting in a more cohesive and cost-effective academic experience for students, faculty, administrators, and the community.

Business survival requires that decision makers understand the critical knowledge resources that support the business' core competencies, while also facing the challenges of current labor trends. The purpose of this study was to explore the lived experiences of the management staff at a west Tennessee manufacturing facility about industrial technician skill losses. This phenomenological design included semistructured interviews of 20 managers, supervisors, and engineers and was an exploration of the potential losses from skilled worker attrition. The foundations of labor theory; knowledge management; and accounting measurements of intangible assets in advanced technology, communications, and economic systems provided the key elements of the conceptual framework. Interview data were sorted and grouped into 6 principle themes: attrition/succession planning, skills technology support, training requirements, economic benefits, support to lean operations, and skills alternative sources. These findings may enhance positive social change by informing manufacturing business leaders on the benefits of active learning organizations, collaboration with administrators of technical educational programs for improved training, replacement technologies, and utilization of the global economy for replacement workers. For skilled technical employees, the social impact of this study might ensure another generation of craft workers to help promote the prosperity of American industries and provide competitive paying worker jobs to the supportive employers, communities, and institutions.

Researchers have found that 90% of financial advisors leave the life insurance industry in first year, 68% in the second year, and 50% in the third year. Researchers have noted the importance of mentorship aimed at work attitudes, yet there is a lack of research concerning attrition and its effects on the industry. The purpose of this quantitative study was to examine managers' and financial advisors' perception of a mentoring program on advisors productivity and retention. Social learning theory was applied as the theoretical framework for this study. Data were collected from financial advisors and their managers across 13 branch offices from a major life insurance company. Data analysis included Pearson product moment, the independent t test, and analysis of variance. Specific quantitative findings indicated (a) a low but statistically significant positive correlation (r = .13) between advisors' number of years of working and mentoring scores, (b) low but statistically significant negative correlation coefficient ( r = -.19) between financial advisors' years of employment and productivity. The findings invite future research on the development of a mentoring program for advisors productivity and retention. The conclusion is that mentoring could be used to improve self-esteem and self-efficacy among advisors and a good applied recommendation would be that company leaders formulate policy to implement mentoring programs at all branches to improve job productivity and retention. Social change implications include opportunities for advisors to improve their job performance, thereby contributing revenue to the organization and the national economy.

Individuals who screen research grant applications often select candidates on the basis of a few key parameters; success or failure can be reduced to a series of peer-reviewed Likert scores on as little as four criteria: risk, relevance, return, and reasonableness. Despite the vital impact these assessments have upon the sponsors, researchers, and society in general as a benefactor of the research, there is little empirical research into the peer-review process. The purpose of this study was to investigate how reviewers evaluate reasonableness and how the process can be modeled in a decision support system. The research questions both address the relationship between an individual's estimates of reasonableness and the indicators of scope, resources, cost, and schedule as well as evaluate the performance of several cognitive models as predictors of reasonableness. Building upon Brunswik's theory of probabilistic functionalism, a survey methodology was used to implement a policy-capturing exercise that yielded a quantitative baseline of reasonableness estimates. The subsequent data analysis addressed the predictive performance of six cognitive models as measured by the mean-square-deviation between the models and the data. A novel mapping approach developed by von Helversen and Rieskamp, a fuzzy logic model, and an exemplar model were found to outperform classic linear regression. A neural network model and the QuickEst heuristic model did not perform as well as linear regression. This information can be used in a decision support system to improve the reliability and validity of future research assessments. The positive social impact of this work would be more efficient allocation and prioritization of increasingly scarce research funds in areas of science such as social, psychological, medical, pharmaceutical, and engineering.