Hoarding symptoms are characterized by (1) a persistent difficulty discarding personal items (2) clutter that interferes with living areas and (3) clinically significant distress or impairment in functioning. Hoarding symptoms are common, affecting 2-6% of the general population and 20% to 56.7% of individuals with obsessive-compulsive disorder (OCD). Research suggests that individuals who hoard have impaired decision-making, particularly when it involve making decisions about personal possessions. This is thought to be a key deficit in hoarding resulting in an inability to discard unneeded possessions. Although the onset of hoarding symptoms is usually during childhood or adolescence (youth), little research has investigated hoarding symptoms in youth. The present study compared different aspects of decision-making processes between youth with OCD and youth with OCD and hoarding symptoms. Specifically, we assessed decision-making and the influence of ownership using the Balloon Analogue Risk Task (BART) and an endowment trading task, respectively. Additionally, we assessed cognitive flexibility, inhibitory control and delay discounting using the Wisconsin Card Sorting Task (WCST), the Stop Signal Task (SST) and Monetary Choice Questionnaire (MCQ), respectively. Participants included 52 youth (8-18 years old), all with a primary DSM-5 diagnosis of OCD. Parents completed the Child Saving Inventory to measure the presence of hoarding symptoms and to create hoarding severity groups. Youth with hoarding symptoms exhibited differences in ownership-based decision making; specifically, we found a larger endowment effect compared to the non-hoarding group. Compared to participants with OCD only, participants with hoarding exhibited significantly increased cognitive flexibility and lowered perseveration on the WCST. Performance of the hoarding and non-hoarding groups did not differ on other aspects of decision-making, including non-ownership decision-making, inhibitory control and delay discounting. Further regression analysis suggested that increased hoarding severity was associated with higher inattentive symptoms and improved performance on the WCST. These findings support the notion that hoarding is associated with specific differences in making decisions about personal items. / Thesis / Master of Science (MSc)

No description available.

Activity-Based Costing is presented in accounting text books as a costing system that can be used to make valuable managerial decisions. Accounting journals regularly report the successful implementations and benefits of activity-based costing systems for particular businesses. Little experimental or empirical evidence exists, however, that has demonstrated the benefits of activity-based costing under controlled conditions. Similarly, although case studies report conditions that may or may not favor activity-based costing decision making, controlled studies that measure the actual influence of those conditions on the usefulness of activity-based costing information are few. This study looked at the decision usefulness of activity-based costing information under controlled, laboratory settings. An interactive computer simulation tested the ability of 48 accounting majors to optimize profits with and without activity-based costing information and tested to see if presentation format or decision framing would influence their outcomes. The research showed that the activity-based costing information resulted in significantly better profitability decisions and required no additional time. Presentation in graphic (bar charts) or numeric (tabular reports) format did not influence profitability decisions but the graphs took longer for analysis and decision making. Decision framing influences were shown to beneficially affect profitability decisions but did not require additional time. Decision framing was especially helpful with the non-activity based costing information; it had no significant effect on activity-based costing performance. / Ph. D.

Cognitive processing has a primary role in decision making. In addition, metacognition, the regulation and knowledge of cognition, affects decision making in a consistent and predictable way. Novices explain situations in a simple way. Novices are more likely to make inappropriate decisions. Research suggests that training the novice on efficient use of metacognitive strategies can improve decision outcomes. The influence of metacognitive strategies on managerial decisions has received little attention. Two questions developed to guide this research. First, how do expert and novice managers differ on metacognitive awareness? And second, how does the level of metacognitive awareness influence successful hiring decisions? Subjects for this study were thirty-one hiring managers employed by a large national corporation. And two hundred eight-five hiring professionals from an association. Data collection involved four sources: (1) A hiring ratio used to report hiring outcomes, (2) Five hiring scenarios provided a measure of managers' ability to select the most appropriate candidate; (3) A 52-item instrument designed to assess metacognitive awareness in both knowledge of cognition and regulation of cognition; and (4) demographic data relating to expertise and experience in hiring. The results identified that metacognition has three underlying structures that influence hiring decision making. Expert and novice managers differ in a consistent way on metacognitive awareness. In exploring and testing the ill-defined mental process model of hiring decision making a methodological tool was established. And the results provided important implications for human resource development professionals with respect to the relevance of metacognitive awareness on managerial development and instructional design. / Ph. D.

This dissertation addresses the modeling and analysis of a strategic risk management problem via a novel decision tree optimization approach, as well as development of enhanced Reformulation-Linearization Technique (RLT)-based linear programming (LP) relaxations for solving nonconvex polynomial programming problems, through the generation of valid inequalities and reduced representations, along with the design and implementation of efficient algorithms. We first conduct a quantitative analysis for a strategic risk management problem that involves allocating certain available failure-mitigating and consequence-alleviating resources to reduce the failure probabilities of system safety components and subsequent losses, respectively, together with selecting optimal strategic decision alternatives, in order to minimize the risk or expected loss in the event of a hazardous occurrence. Using a novel decision tree optimization approach to represent the cascading sequences of probabilistic events as controlled by key decisions and investment alternatives, the problem is modeled as a nonconvex mixed-integer 0-1 factorable program. We develop a specialized branch-and-bound algorithm in which lower bounds are computed via tight linear relaxations of the original problem that are constructed by utilizing a polyhedral outer-approximation mechanism in concert with two alternative linearization schemes having different levels of tightness and complexity. We also suggest three alternative branching schemes, each of which is proven to guarantee convergence to a global optimum for the underlying problem. Extensive computational results and sensitivity analyses are presented to provide insights and to demonstrate the efficacy of the proposed algorithm. In particular, our methodology outperformed the commercial software BARON (Version 8.1.5), yielding a more robust performance along with an 89.9% savings in effort on average. Next, we enhance RLT-based LP relaxations for polynomial programming problems by developing two classes of valid inequalities: v-semidefinite cuts and bound-grid-factor constraints. The first of these uses concepts derived from semidefinite programming. Given an RLT relaxation, we impose positive semidefiniteness on suitable dyadic variable-product matrices, and correspondingly derive implied semidefinite cuts. In the case of polynomial programs, there are several possible variants for selecting such dyadic variable-product matrices for imposing positive semidefiniteness restrictions in order to derive implied valid inequalities, which leads to a new class of cutting planes that we call v-semidefinite cuts. We explore various strategies for generating such cuts within the context of an RLT-based branch-and-cut scheme, and exhibit their relative effectiveness towards tightening the RLT relaxations and solving the underlying polynomial programming problems, using a test-bed of randomly generated instances as well as standard problems from the literature. Our results demonstrate that these cutting planes achieve a significant tightening of the lower bound in contrast with using RLT as a stand-alone approach, thereby enabling an appreciable reduction in the overall computational effort, even in comparison with the commercial software BARON. Empirically, our proposed cut-enhanced algorithm reduced the computational effort required by the latter two approaches by 44% and 77%, respectively, over a test-bed of 60 polynomial programming problems. As a second cutting plane strategy, we introduce a new class of bound-grid-factor constraints that can be judiciously used to augment the basic RLT relaxations in order to improve the quality of lower bounds and enhance the performance of global branch-and-bound algorithms. Certain theoretical properties are established that shed light on the effect of these valid inequalities in driving the discrepancies between RLT variables and their associated nonlinear products to zero. To preserve computational expediency while promoting efficiency, we propose certain concurrent and sequential cut generation routines and various grid-factor selection rules. The results indicate a significant tightening of lower bounds, which yields an overall reduction in computational effort of 21% for solving a test-bed of 15 challenging polynomial programming problems to global optimality in comparison with the basic RLT procedure, and over a 100-fold speed-up in comparison with the commercial software BARON. Finally, we explore equivalent, reduced size RLT-based formulations for polynomial programming problems. Utilizing a basis partitioning scheme for an embedded linear equality subsystem, we show that a strict subset of RLT defining equalities imply the remaining ones. Applying this result, we derive significantly reduced RLT representations and develop certain coherent associated branching rules that assure convergence to a global optimum, along with static as well as dynamic basis selection strategies to implement the proposed procedure. In addition, we enhance the RLT relaxations with v-semidefinite cuts, which are empirically shown to further improve the relative performance of the reduced RLT method over the usual RLT approach. Computational results presented using a test-bed of 10 challenging polynomial programs to evaluate the different reduction strategies demonstrate that our superlative proposed approach achieved more than a four-fold improvement in computational effort in comparison with both the commercial software BARON and a recently developed open-source code, Couenne, for solving nonconvex mixed-integer nonlinear programming problems. Moreover, our approach robustly solved all the test cases to global optimality, whereas BARON and Couenne were jointly able to solve only a single instance to optimality within the set computational time limit, having an unresolved average optimality gap of 260% and 437%, respectively, for the other nine instances. This dissertation makes several broader contributions to the field of nonconvex optimization, including factorable, nonlinear mixed-integer programming problems. The proposed decision tree optimization framework can serve as a versatile management tool in the arenas of homeland security and health-care. Furthermore, we have advanced the frontier for tackling formidable nonconvex polynomial programming problems that arise in emerging fields such as signal processing, biomedical engineering, materials science, and risk management. An open-source software using the proposed reduced RLT representations, semidefinite cuts, bound-grid-factor constraints, and range reduction strategies, is currently under preparation. In addition, the different classes of challenging polynomial programming test problems that are utilized in the computational studies conducted in this dissertation have been made available for other researchers via the Web-page http://filebox.vt.edu/users/dalkiran/website/. It is our hope and belief that the modeling and methodological contributions made in this dissertation will serve society in a broader context through the myriad of widespread applications they support. / Ph. D.

Typescript (photocopy). / Digitized by Kansas Correctional Industries

Typescript (photocopy). / Digitized by Kansas Correctional Industries

Conduct an exploratory study on operationally focussed managers within a South African company, using both quantitative and qualitative analysis, to determine the correlation between the required and actual levels of complexity and time-span of control at specific hierarchical levels / Organisational design needs to be in line with capabilities of the individual-inrole. The structure of an organization directly impacts the overall effectiveness and ultimately the success of such an organization and the number of layers required in any given hierarchy is a product of the organization’s mission (Jaques, 1989). Stratified Systems Theory (Jaques, 1989) defines work in seven strata based on a basis of decision-making complexity. The research presented here identifies a specific organisation’s current level of work based on complexity and the time-span of decision-making. Research was done in one specific geographical region of a company operating in the Supply Chain and Logistics industry in South Africa. Qualitative data collection was done by means of interviews with a defined sample group that provided an adequate cross-section of the main functions of the business, however, the sampling technique used may not provide results representative of the entire population. ii The Brunel Institute for Organisation and Social Studies’ (BIOSS) Matrix of Working Relationships was used as main basis for reporting results. The research indicates that the organisation is presently, according to Jaques Stratified Systems Theory (Jaques, 1989), operating at one level below their intended level that will allow them to effectively meet their longterm strategic objectives. The report identifies shortcomings in terms of the current capabilities of the individual-in-role and the actual work requirements, setting a foundation for further analysis of individual capabilities for effective organisational design. / Graduate School of Business Leadership / MBL

AIMS OF THE RESEARCH: To explore the decision making processes of top management, CEO's and boards of directors - to gain ne~ insights into the causes of management decision failures, management risk and decision process weaknessess. To identify important factors that play a pivotal role in effective decision making in business situations. To draw up a frame~ork for effective decision making based on the correlations between decision theory and empirical findings amongst senior executives and board members. To find ways how management can minimize the risk of decision failure in complex problems, what questions they have to ask themselves about the way in which they make decisions, what decision risks they have to be aware of at each stage of the decision process and how they can gain from available decision theory. The aim is to improve the decision process to obtain better overall quality of decisions produced by kno~ledgeable senior managers and board members. This will provide a framework for effective third generation risk management. EXECUTIVE SUMMARY OF THE RESEARCH FINDINGS Board members and top executives rely on experience and personal knowledge to analyse complex problems and do not consciously involve concepts from decision theory (see section 8.5). They describe these phenomena in their organisations, but they have not formally done a decision process analysis to minimise decision risk. Current risk management practises in modern financial institutions focus mainly on risk classification techniques and structural mechanisms (see section 15) to control risks, with little or no attention to decision process dynamics. The Board of Directors and Top Management are generally very good at identifying corporate risks, economic risks and financial risks, but they have great difficulty in identifying internal decision process risks within the management hierarchy/system or amongst themselves. Introspective analysis of their own decision process dynamics can help to improve this. A step by step analysis of the decision process in the board and top management team as described in section 18.2 is proposed as a further contribution to improve the quality of decision making in financial institutions. Structural changes to boards like those introduced by Cadbury improved second generation risk management practices. This research proposes that further advances can be made by third generation risk management improvements in the decision process dynamics. We teach decision makers about economic and financial analysis and derivatives and risk management, but the fundamentals of decision science and the human decision process seem to be ignored. To prevent the financial failures that so often destroy shareholder value, we need to focus on decision science and financial decision process analysis Analysis of the decision process dynamics is proposed as a way to reduce the number of decision failures in large financial institutions and other organisations. By increasing the a~areness and kno~ledge of board members and top executives about the potential causes of decision failure, their own ability to identify and prevent these will be improved. New risk management structures and recent changes to board structures have contributed greatly to corporate governance but could not prevent many of the financial failures. Combining these structural improvements with an additional focus on decision process analysis can increase our ability to manage risk successfully. / Business Leadership / DBL

AIMS OF THE RESEARCH: To explore the decision making processes of top management, CEO's and boards of directors - to gain ne~ insights into the causes of management decision failures, management risk and decision process weaknessess. To identify important factors that play a pivotal role in effective decision making in business situations. To draw up a frame~ork for effective decision making based on the correlations between decision theory and empirical findings amongst senior executives and board members. To find ways how management can minimize the risk of decision failure in complex problems, what questions they have to ask themselves about the way in which they make decisions, what decision risks they have to be aware of at each stage of the decision process and how they can gain from available decision theory. The aim is to improve the decision process to obtain better overall quality of decisions produced by kno~ledgeable senior managers and board members. This will provide a framework for effective third generation risk management. EXECUTIVE SUMMARY OF THE RESEARCH FINDINGS Board members and top executives rely on experience and personal knowledge to analyse complex problems and do not consciously involve concepts from decision theory (see section 8.5). They describe these phenomena in their organisations, but they have not formally done a decision process analysis to minimise decision risk. Current risk management practises in modern financial institutions focus mainly on risk classification techniques and structural mechanisms (see section 15) to control risks, with little or no attention to decision process dynamics. The Board of Directors and Top Management are generally very good at identifying corporate risks, economic risks and financial risks, but they have great difficulty in identifying internal decision process risks within the management hierarchy/system or amongst themselves. Introspective analysis of their own decision process dynamics can help to improve this. A step by step analysis of the decision process in the board and top management team as described in section 18.2 is proposed as a further contribution to improve the quality of decision making in financial institutions. Structural changes to boards like those introduced by Cadbury improved second generation risk management practices. This research proposes that further advances can be made by third generation risk management improvements in the decision process dynamics. We teach decision makers about economic and financial analysis and derivatives and risk management, but the fundamentals of decision science and the human decision process seem to be ignored. To prevent the financial failures that so often destroy shareholder value, we need to focus on decision science and financial decision process analysis Analysis of the decision process dynamics is proposed as a way to reduce the number of decision failures in large financial institutions and other organisations. By increasing the a~areness and kno~ledge of board members and top executives about the potential causes of decision failure, their own ability to identify and prevent these will be improved. New risk management structures and recent changes to board structures have contributed greatly to corporate governance but could not prevent many of the financial failures. Combining these structural improvements with an additional focus on decision process analysis can increase our ability to manage risk successfully. / Business Leadership / DBL