Browsing by Subject "Decision making -- Data processing"
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Item A field study of organizational factors affecting DSS implementation(Texas Tech University, 1983-05) Sanders, George LawrenceNot availableItem A knowledge-based decision support system for managerial problem recognition and diagnosis(Texas Tech University, 1985-08) Ata Mohamed, Nassar HCurrent decision support systems lack in providing support for the early phases of decision making (i.e., problem finding and problem diagnosis). This research develops a conceptual model for managerial problem recognition and diagnosis, develops a system architecture, implements a prototype system based on a computer-based simulated management game, and tests the prototype with a set of problems. The conceptual model is based on Pounds' model of problem finding and Sage's model of cognitive processing. The conceptual model consists of a problem finding component (Monitor) that detects deviations in specified variables, and a problem processor. The problem processor supports routine diagnoses (that have occurred in the past) through the experiential knowledge base. New problem diagnosis is supported through several processes such as construction of causation trees, hypotheses generation, hypotheses evaluation, verification of diagnosis, and statistical verification of user's models. The elements of the full system architecture consist of a User Interface, Performance Monitor, Security System, Monitor for Problem Detection, Problem Processor, Structural Model Knowledge Base, System Dictionary, and a Process Controller. In the prototype implementation, the components Performance Monitor and Security System were not included; also the problem processor implementation did not include the component for statistical verification of the user's models. Structural modeling was used for knowledge representation since it allows representation of causal relations among variables, which is important in business problem domains. Results show the technical feasibility of the approach and confirm the view of some researchers that perhaps the domain of business problems requires more than one method of knowledge representation. Results also indicate that the quality of diagnosis depends on the quality of the model from which diagnosis is inferred. These results were discussed in relation to the type of models for which the approach is appropriate and new questions for future research were proposed.Item A model of the effects of change in communication technology on the sources of information for organizational decision making(Texas Tech University, 1985-08) Meile, Larry CarlThe technology supporting computer assisted communication (CAC) is becoming an increasingly significant factor affecting the decision-making process. Current models do not adequately represent this situation. A framework is synthesized from literature representing three fields of study: management information systems, communication, and decision making. The framework views all available decision-making information as either currently residing In the mind of the decision maker or being provided through communication sources. Furthermore, the communication sources are divided into a formal (system supplied) versus informal (non-system supplied) dichotomy. A conceptual model is then created, based on the framework, that is useful in qualitatively assessing the effects of installing or upgrading CAC on the decision-making information that is available to the decision maker. This model Is then used as a basis for analyzing some of the cost/benefit tradeoffs of employing CAC. The primary contribution of this research is a model that provides a tool for analyzing the effects of CAC technology on the source of decision-making information and on the cost of making decisions using CAC.Item Alternative report format effects of a decision support system(Texas Tech University, 1984-12) Dunikoski, Robert HenryThis dissertation examined the influence of report format on decision support system use and performance. The major independent variable, report format, was operationalized as either menu driven or fixed report. The major dependent variable was a qualitative measure of performance. The influence of cognitive style on decision making performance was a part of the study. A business simulation game and its accompanying interactive decision support system provided the experimental environment. Eighty-five undergraduate senior business majors enrolled in a capstone course participated in the study as a part of the course. Subjects were organized as teams making decisions in simulated industries. The subjects were exposed to two different industries of the game over a five week period. Subjects initially made four sets of "practice" decisions to acquaint themselves with the simulation and the decision support system. The analytic results of the dissertation were based on the subjects performance in seven subsequent "official" decisions. The primary subject motivation was the basing of a large portion of the student's course grade on performance in the simulation.Item An examination of an expectancy theory model of decision support system use(Texas Tech University, 1982-05) DeSanctis, Gerardine LThis dissertation developed a conceptual model of user behavior based on expectancy theory, a psychological theory of motivation. A portion of the proposed model was examined in a controlled laboratory study. The major independent variable in the study was predicted motivation, or ''force" to use a decision support system. Amount of DSS use was the dependent variable. A business simulation "game†and its accompanying interactive support program served as the research contexts Eighty-eight undergraduate business students participated in the study. The procedure required each subject to play the role of a manager in a competitive industry consisting of three firms: the student's firm and two phantom firms. Over a three-week period, the subject was required to make two "practice†decisions and five "real" decisions. Subjects were trained in the use of the DSS which accompanied the simulation, but they were not required to use the system beyond the practice decision period. The subjects received monetary and grade-based rewards which were contingent upon their level of performance in the simulation. Results of the study suggest some support for the hypothesized model of user behavior. The strength of the force - behavior relationship, as in previous expectancy theory research, was not strong. However, the presence of significant across-subjects correlations between activation to use a DSS and actual use of the system imply that expectancy theory constructs any offer some explanatory power in a comprehensive theory of user behavior. Tests for hypotheses of the influence of the two personality variables, locus of control and cognitive style, on components of the expectancy model yielded no significant findings. The results are discussed in terms of their implications for the expectancy theory literature, for the MIS literature, and for development of behavioral-science based theory within the field of MIS.Item An investigation into the factors that may affect the perceived utilization of computer-based decision support systems(Texas Tech University, 1979-08) Fuerst, William LeeNot availableItem Causal modeling as a basis for the design of an intelligent business problem formulation system(Texas Tech University, 1986-05) Paradice, David BryanPast research has shown that humans demonstrate many biases when they attempt to formulate the structure of a problem. These biases can be very detrimental to actually solving the problem at hand. In some cases, the problem formulation process may be so biased that the wrong problem is formulated entirely. Prior research has demonstrated that the process of building a model of the problem situation is beneficial to problem solution. Model construction in the domain of business problems is a very complex task, however, due to the large number of potentially relevant variables, the dynamic characteristics of business organizations, and the temporal nature of relationships in the problem domain. Much of the prior research in management information systems has assumed that any problem formulation involved has generated a correct formulation. This research explores a computer-based methodology aimed at assisting a manager in producing a correct formulation of his problem environment. A prototype system has been developed that allows a user (1) to access an organizational database of information, (2) to hypothesize and test relationships between items in the database, (3) to store relationships for use at a later session, (4) construct model based on these stored relationships, and (5) give advice regarding ways of manipulating variables in order to achieve goals. Furthermore, a rudimentary process for automatic discovery of relationships has been installed in the system. The prototype was evaluated by comparing its ability to determine relationships in the database with human subjects from a prior study. Since the database used was generated by a management simulation game, it was possible to determine the "true" relationships in the database by examining the program code for the game. The system and the student subjects agreed on approximately seventy per cent of the relationships identified. Of the remaining thirty per cent, the student subjects were correct one-third of the time, the system was correct one-third of the time, and the remainder were vaguely specified making it impossible to determine exactly which was "correct." The limitations of the methodology used herein is discussed, as well as areas for future research.Item Decision making in dynamic environments: the effects of instructions inducing an internal task representation, and of outcome feedback(Texas Tech University, 1985-12) Hurts, Carolus Marinus MariaHuman information processing in dynamic decision environments is relatively unexplored. These are environments where decisions are made continually and modified on the basis of feedback, as well as complicated by the occurrence of time lags. The present study formulates a general model of such decision making phrased in terms of Feedback, Filtering, Situation Assessment, Internal Model of the decision environment. Decision Planning, and Decision Implementation. The empirical part consisted of an experiment using a computerized management game which was played individually. Participants were expected to make nine sets of decisions over a series of nine decision rounds. Each set was fed into the simulation as a result of which a new, updated, decision environment was created for the participants. Independent variables were amount of instructions allowing the formation of an internal model of the decision environment (Extensive versus Normal Instructions), frequency of outcome feedback (every round versus every other round), and time-on-task (number of rounds played). Dependent variables were decision performance (measured by retained earnings), accuracy of the subjects' performance prediction, accuracy of the internal model (measured by a knowledge test), and the degree to which the eight decision variables were utilized (changed) by the subjects. Besides, several aspects of the subjects' query behavior were studied, including number of historic queries, number of redundant queries, and the number of query links corresponding to first-order Markov chains. It was hypothesized that with the more extensive instructions and with frequently presented outcome feedback subjects would show better decision performance, higher internal model accuracy, and higher prediction accuracy. Moreover, the number of historic queries was expected to decrease and the number of relevant queries and the number of first-order query links to increase under the same conditions. The same trends were predicted to take place over time. Finally, Extensive Instructions and Frequent Outcome Feedback were predicted to result in increased usage of the decision variables. Results showed that amount of instructions had a negative effect on performance and prediction accuracy (lower with Extensive Instructions), although the effect on prediction accuracy was nonsignificant. Internal model accuracy, on the other hand, was affected in the expected direction (higher accuracy with Extensive Instructions) by this independent variable. Frequency of outcome feedback had a negative effect on performance and prediction accuracy (lower with Frequent Outcome Feedback). For the performance data this effect was mainly due to subjects in the Infrequent Feedback group making higher earnings on rounds where outcome feedback was made available to them. On the alternate rounds there was no difference in earnings between the two Feedback groups. The effect of the feedback manipulations on internal model accuracy was nonsignificant. Of the query behavior measures the number of historic queries showed expected effects of both amount of instructions and frequency of outcome feedback. The effects on the other query behavior measures showed an inconsistent pattern. The extent to which the decision variables were used changed in the expected direction as a result of Extensive Instructions and Frequent Outcome Feedback, but only significantly so for two and one decision variables, respectively. Finally, learning effects were observed only for performance and prediction accuracy. The experimental design model of this study utilized four covariates to correct for experimental groups having different means on these covariates and to correct for correlations between these covariates and the dependent variables. These correlations were quite large, boosting the overall model R-squared value in some cases even as high as 0.60. This finding was taken as a sign of the importance of individual differences, i.e., background variables such as experience and age, in explanations of decision performance and behavior. An in-depth analysis of these individual differences also showed how background variables moderated the effects that were of primary interest to this study, namely, those of amount of instructions and frequency of outcome feedback. The discussion focused on the phenomena of cognitive overload and the stability of people's internal models (even if they are in error) as an explanation for some of the paradoxical findings of this study. The results were also discussed in relation to methodological problems that probably were inherent to this study and in relation to their implications for decision support and future research.Item Design of a decision support system facilitating model management and utilization(Texas Tech University, 1982-05) Minch, Robert PaulNot availableItem Design of an inquiry support system for managerial problem diagnosis(Texas Tech University, 1993-05) Chang, HwalsikProblem diagnosis, the process of discovering and constructing the causal structure of a problem, is one of the most critical aspects of decision making. Management information system (MIS) research, as a discipline concerned with improving managerial decision making, must provide adequate support for this critical and difficult decision process. The purpose of this research was to formulate a conceptual framework for developing problem diagnosis support systems (PDSS), design PDSS based on the framework, and validate the design based on prototype system implementation. The conceptual framework identified essential elements of PDSS, delineated logical steps in PDSS development, specified the individuals' roles, and discussed major issues to be addressed for PDSS development. The framework indicated that PDSS must combine user-driven and system-driven approaches to support semi-structured or unstructured problem diagnosis process. Thus, PDSS must have both cognitive and normative elements. Furthermore, PDSS must reduce, or at least attempt to reduce, the errors, biases, and uncertainties in conceptualizing a problem. The framework indicated that PDSS must structure complex causal relationships, support the entire problem diagnosis process, and maintain extensive interactions with the users. This research identified various activities inherent in, and essential for, successful problem diagnosis. Also identified are a variety of views necessary to support the problem diagnosis activities. This research integrated structural, statistical, and rule-based modeling for problem diagnosis support. The support functions are designed from both cognitive and normative perspective. This research incorporated the inquiry guaranteeing concepts into PDSS design. The framework and the conceptual design of PDSS provided a sound basis for developing more powerful, comprehensive, and cooperative PDSS. The prototype system, tested with two different diagnostic problems, demonstrated that it can overcome the limitations of previous PDSS by integrating structural, statistical, and rule-based modeling approaches, supporting the entire problem diagnosis process, and achieving a more cooperative inquiry. The key concepts synthesized in this research include the cooperative system concept, multiple causal modeling approaches, the process-oriented decision support approach, and the inquiry "guaranteeing" concepts.Item Determining the individual microeconomic demand for continuous online assurance given specific types of decisions(Texas Tech University, 2002-05) Daigle, Ronald JudeThe accounting profession is studying the viability of a new potential assurance service, continuous auditing (continuous online assurance [COA]). The ability to begin developing COA as a professional service is due to the proliferation of information technology, which has provided more timely information, as well as the potential for more timely assurance. The purpose of this study is to investigate the relative demand for COA by individual decision-makers given specific types of decision-making situations. This study provides a framework based on the information hypothesis and information microeconomics for explaining the demand for COA when making individual repetitive decisions. Using an experimental methodology, five decision aspects are studied: (1) the level of precision in the COA report, (2) choice versus judgment decisions, (3) the level of similarity or dissimilarity of options when making choice decisions, (4) the number of decision criteria and (5) the benefit/penalty to be earned/incurred from making decisions. Markets are developed and compared to determine which situations have relatively more significant and consistent demand for COA. Results indicate that (1) more precise COA reports are significantly demanded more than less precise COA reports when an equal economic benefit can be obtained from either option, (2) COA demand is significantly greater and more consistent for judgment decisions than choice decisions, (3) while no significant difference in COA demand is found for choice decisions based on the similarity/dissimilarity of options. COA purchase patterns differ with changes in the similarity/dissimilarity of options, (4) COA demand is significantly greater and more consistent with an increase in the number of decision criteria when making judgment decisions, but only more consistent when making choice decisions, (5) no significant difference is found in the level or consistency of COA demand with an increase in reward/penalty to be earned/incurred, whether the decisions are judgment or choice in nature. Based on the results, because judgment decisions are more indicative of internal decisions and choice decisions are more indicative of external decisions to an organization, the accounting profession should first develop COA towards meeting the needs of internal decision-makers.Item Determining the individual microeconomic demand for continuous online assurance given specific types of decisions(Texas Tech University, 2002-05) Daigle, Ronald JudeThe accounting profession is studying the viability of a new potential assurance service, continuous auditing (continuous online assurance [COA]). The ability to begin developing COA as a professional service is due to the proliferation of information technology, which has provided more timely information, as well as the potential for more timely assurance. The purpose of this study is to investigate the relative demand for COA by individual decision-makers given specific types of decision-making situations. This study provides a framework based on the information hypothesis and information microeconomics for explaining the demand for COA when making individual repetitive decisions. Using an experimental methodology, five decision aspects are studied: (1) the level of precision in the COA report, (2) choice versus judgment decisions, (3) the level of similarity or dissimilarity of options when making choice decisions, (4) the number of decision criteria and (5) the benefit/penalty to be earned/incurred from making decisions. Markets are developed and compared to determine which situations have relatively more significant and consistent demand for COA. Results indicate that (1) more precise COA reports are significantly demanded more than less precise COA reports when an equal economic benefit can be obtained from either option, (2) COA demand is significantly greater and more consistent for judgment decisions than choice decisions, (3) while no significant difference in COA demand is found for choice decisions based on the similarity/dissimilarity of options. COA purchase patterns differ with changes in the similarity/dissimilarity of options, (4) COA demand is significantly greater and more consistent with an increase in the number of decision criteria when making judgment decisions, but only more consistent when making choice decisions, (5) no significant difference is found in the level or consistency of COA demand with an increase in reward/penalty to be earned/incurred, whether the decisions are judgment or choice in nature. Based on the results, because judgment decisions are more indicative of internal decisions and choice decisions are more indicative of external decisions to an organization, the accounting profession should first develop COA towards meeting the needs of internal decision-makers.Item Formulation, design and implementation of the MAGIC/ROC decision support system generator(Texas Tech University, 1981-08) Wang, Michael Szu-yuanDecision Support Systems (DSS) , which may be briefly defined as man-computer systems for facilitating managers' decision-making processes in semi-structured and unstructured situations, have received much attention in the recent MIS literature. These systems use data and models to perform data extraction, data aggregation, data analysis, estimation, optimization, simulation, etc., to assist managers in decision making. Generalized software systems integrating these decision support and data management capabilities, which are known as DSS generators, are needed at the current stage of MIS/DSS development. No existing software system has been reported as a generalized, powerful and "friendly" system, which provides full-range capabilities for easily building specific DSS in any application area. The development of DSS generators is a complicated task. In order to cleverly integrate a variety of decision support and data management capabilities into a well-designed, orderly whole, a conceptual model must be created as a foundation for developing such software systems. The objectives of this dissertation are: (1) to formulate a comprehensive conceptual model for developing DSS generators; (2) to design a prototype DSS generator based on the conceptual model t o demonstrate the validity of the model; and (3) to implement an experimental version (selected portions) of the prototype DSS generator to validate the design. The conceptual model conveys a concept of "macro" to extend the conventional meaning of "model" in a CSS environment, and a concept of three - level knowledge bases to enhance organizational communication and sharing of corporate knowledge. Because of the structural similarity between matrices and relations, both of which represent data in tabular form, the conceptual model suggests the use of the relational data model to enhance the integration of the model base management subsystem (MBMS) and the data base management subsystem (DBMS). Components of the conceptual model are: • a model base management subsystem • a data base management subsystem • model/data dictionaries • the linkage between the MBMS and DBMS • the linkage between the DSS generator and the local computing environment • the skeleton of three-level knowledge bases • a security system • a performance monitor • a user-system interface • a language system The top-down design approach was employed to design the MAGIC/ROC* Decision support system Generator based on the conceptual model. The rationale was to include all features present in the conceptual model in a software system which is designed to be a DSS generator in order to achieve an orderly system. MAGIC/ROC advances software technology employed in MIS/DSS fields and sets up a framework of DSS generators for subsequent development. The experimental version of HAGIC/ROC was implemented via an existing software system, Statistical Analysis System (SAS). This "workable" DSS generator validates the design of MAGIC/ROC and the conceptual model formulated for developing DSS generators.Item Principles of design for a multiple viewpoint problem formulation support system(Texas Tech University, 1989-08) Baldwin, Dirk StevenThe world is filled with multiple views. There are multiple political philosophies, multiple economic models, multiple scientific theories and multiple management science models. This research explores the architecture of a computer system that creates, displays and manages multiple views. Three basic questions are answered: "What are the characteristics of a multiple viewpoint system?" "Can a multiple viewpoint computer system be constructed?" and "What design principles guide the development of a multiple viewpoint system?" The answers to these questions are discovered using two approaches. The analytic approach uses aspects of set theory and logic to specify system characteristics. This approach also leads to some general design principles, including the principle of viewpoint normalization. The second approach is system prototyping. In particular, a multiple viewpoint system, DOVE, is created which supports management problem formulation. This system is capable of creating and managing multidimensional financial models, causal models, Forrester flow models, goal hierarchy models, linear programming models and many other types of views. This second approach leads to more detailed design principles concerning the architecture of frames and rules. This dissertation develops the basic characteristics of a multiple viewpoint system, demonstrates that such a system can be constructed and illustrates principles which can guide the future development of a multiple viewpoint system. It contributes to the information systems field since past research has focused almost exclusively on the design of systems which promote a single point of view.