Consumers form consideration sets by screening from all available alternatives. Consumers typically utilize one of two types of screening strategies: an exclusion screening strategy wherein alternatives not worthy of further consideration are rejected or an inclusion strategy wherein worthy alternatives are selected for further evaluation. Extant literature has documented the important role played by screening strategies in decision making. However, there is very limited understanding of when and why consumers may employ one screening strategy over the other as well the impact of the screening strategy for decision accuracy. This dissertation attempts to study the antecedent and consequence of screening strategies. Essay 1 in this dissertation, investigates the role of consumers' perceived uncertainty on the choice of screening strategy. Four studies in this essay show that when consumers are highly uncertain they are more likely to choose exclusion screening strategy; whereas when they are less uncertain they are more likely to use inclusion screening. Mediation analyses in Studies 1 and 2 show that the choice of screening strategy is primarily driven by perceived accuracy of the strategy. Study 3 demonstrates that the effect of uncertainty on the choice of screening strategy is moderated by consideration set size. When uncertain consumers form smaller sets they are more likely to use exclusion screening, but this relationship flips when they form larger consideration sets. Finally, external validity for the relationship between uncertainty and choice of screening strategy is demonstrated in Study 4 using the popular TV game show Who Wants to be a Millionaire? Essay two in this dissertation, investigates the role of perceived uncertainty and consideration set size on the relationship between screening strategy and objective accuracy of the decision. Utilizing an experimental study with an actual choice task, I demonstrate that perceived uncertainty moderates the screening strategy-decision accuracy relationship. Further, this interactive relationship is contingent on consideration set sizes. Whereas consumers with high perceived uncertainty make higher quality decisions with inclusion while forming smaller consideration sets, their decision quality is higher with exclusion when forming larger sets. Likewise, while consumers with low perceived uncertainty make more accurate decisions with exclusion when forming smaller sets, the accuracy of their decisions increases with inclusion when forming larger sets. This dissertation contributes to literature on screening strategies by explicating perceived uncertainty as a critical factor that leads to consumers preferring one screening strategy versus the other. Furthermore, it adds to our understanding of an important consequence of using screening strategies--decision accuracy.

This objectivist, experimental study investigated the influence of virtual expert systems (VES) on the decision accuracy of non-expert consultants within a technology consulting contact centre environment. Because of the overwhelming availability of conceptual information, non-expert consultants experience challenges in making accurate decisions, and would benefit from augmented technologies, such as VES. VES hold the ability to capture and scale large volumes of decision variables for consideration by human experts when making decisions. A total of 40 participants were randomly selected from contact centres in the Eastern Cape and Gauteng provinces of South Africa for this study. Human logic was captured and scaled into a technology fault finding virtual expert and administered as an experiment to group participants. The experimental and control group participants were randomly assigned to the respective groups of 20 participants each. The control group was exposed to the paper-based, fault-finding manual. The pre-test and post-test data were collected based on four decision accuracy measures, namely individual performance, average call handling time, first call resolution and customer service. The Clarify performance system of the participating technology consulting company was used as data collection tool to record the findings used for Chapter 5. Statistical data analyses were performed using ANOVA and two-tailed significance tests to test the relationship between VES and decision accuracy in the pre-test and post-test phases of the study. The study found that the participant scores on the decision accuracy measures were only statistically significant on the measure of first call resolution measure (significance score of a p value <.05). On the other (three) measures, the scores obtained from experimental group participants showed more improvement than that of the control group participants. Consequently, the hypothesis that the use of VES enhance decision accuracy amongst non-expert technology consultants was accepted and the alternative hypothesis rejected. Some limitations pertaining to the resultant Hawthorne effect (the effect when some employees work harder and perform better when they are participants in an experiment) was noted amongst participants. This effect resulted from the use of team leaders in monitoring performance during the experiment and the involvement of the technology consulting company in determining the performance norms of the identified measures. Another limitation of the study related to the size of the sample where only two provinces were included. The limitation may affect the generalisation of results to other future settings when such a study is repeated. It was recommended that future studies in this field should make provision for a larger population, inclusive of other provinces to avoid these limitations.

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This study investigates the relationship between three visual representations (two-dimensional, three-dimensional fixed, and three-dimensional rotatable) of multidimensional data, and the subjects' ability to make predictions based on the data. Output of a momentum accounting system was simulated and graphics were rendered based on that information. An interactive computer program was developed and used to administer the laboratory experiment and collect the results. Subjects made prediction decisions based on the graphics produced for four companies. The companies were stratified based on size (high or low) and growth patterns (high or low). Each subject made predictions for one type representation for each of the four companies. Because of inconsistencies of the sample distributions for the different representations, nonparametric analyses were used to examine the data. The subjects using the three-dimensional data that could be rotated were found to provide the most accurate predictions. No differences between the treatments were found based on the subject's visual acuity, as measured by the Visual Vividness Imagery Questionnaire (VVIQ). The subjects using the two-dimensional representations were found to take the least amount of time for their predictions. / Ph. D.

The purpose of this research is to study and improve decision accuracy in the real world. Spot price prediction of petroleum products, in a budgeting context, is the task chosen to study prediction accuracy. Prediction accuracy of executives in a multinational oil company is examined. The Brunswik Lens Model framework is used to evaluate prediction accuracy. Predictions of the individuals, the composite group (mathematical average of the individuals), the interacting group, and the environmental model were compared. Predictions of the individuals were obtained through a laboratory experiment in which experts were used as subjects. The subjects were required to make spot price predictions for two petroleum products. Eight predictor variables that were actually used by the subjects in real-world predictions were elicited through an interview process. Data for a 15 month period were used to construct 31 cases for each of the two products. Prediction accuracy was evaluated by comparing predictions with the actual spot prices. Predictions of the composite group were obtained by averaging the predictions of the individuals. Interacting group predictions were obtained ex post from the company's records. The study found the interacting group to be the least accurate. The implication of this finding is that even though an interacting group may be desirable for information synthesis, evaluation, or working toward group consensus, it is undesirable if prediction accuracy is critical. The accuracy of the environmental model was found to be the highest. This suggests that apart from random error, misweighting of cues by individuals and groups affects prediction accuracy. Another implication of this study is that the environmental model can also be used as an additional input in the prediction process to improve accuracy.

The primary goal of this study was to develop a new procedure for estimating decision consistency and accuracy indices using the bifactor and testlet response theory (TRT) models. This study is the first to investigate decision consistency and accuracy from a multidimensional perspective, and the results have shown that the bifactor model at least behaved in way that met the author's expectations and represents a potential useful procedure. The TRT model, on the other hand, did not meet the author's expectations and generally showed poor model performance. The multidimensional decision consistency and accuracy indices proposed in this study appear to provide good performance, at least for the bifactor model, in the case of a substantial testlet effect. For practitioners examining a test containing testlets for decision consistency and accuracy, a recommended first step is to check for dimensionality. If the testlets show a significant degree of multidimensionality, then the usage of the multidimensional indices proposed can be recommended as the simulation study showed an improved level of performance over unidimensional IRT models. However, if there is a not a significant degree of multidimensionality then the unidimensional IRT models and indices would perform as well, or even better, than the multidimensional models. Another goal of this study was to compare methods for numerical integration used in the calculation of decision consistency and accuracy indices. This study investigated a new method (M method) that sampled ability estimates through a Monte-Carlo approach. In summary, the M method seems to be just as accurate as the other commonly used methods for numerical integration. However, it has some practical advantages over the D and P methods. As previously mentioned, it is not as nearly as computationally intensive as the D method. Also, the P method requires large sample sizes. In addition, the P method has conceptual disadvantage in that the conditioning variable, in theory, should be the true theta, not an estimated theta. The M method avoids both of these issues and seems to provide equally accurate estimates of decision consistency and accuracy indices, which makes it a strong option particularly in multidimensional cases.

Regulatory focus theory encompasses promotion focus, seeking success and prevention focus, avoiding failure. These mutually exclusive focuses, when matched with the appropriate goal pursuit strategy, promotion with eager and prevention with vigilant, create a state of regulatory fit. This state of regulatory fit leads to different outcomes which the current study has grouped into fit sensitivity and performance. Fit sensitivity is the sensitivity to fit effects with an absence of correctness while performance outcomes are based in correctness. The goal of the current study was to examine both fit sensitivity and performance in the same task to demonstrate a difference in fit sensitivity effects between types of fit while showing equal performance between promotion and prevention fit. An applicant hiring simulation was implemented. 24 applicant profiles for the position of police officer were generated, six with high risk/ variable reward elements meant to align with individuals in a state of promotion fit, six with low-risk/consistent-reward elements meant to align with individuals in a state of prevention fit, and six applicant profiles with a high probability of succeeding and finally six applicant profiles meant to have a low probability of succeeding. Participants rated the applicant profiles on their suitability and recommended 12 applicants to be hired. Initial results did not support the hypotheses, however exploratory analysis did demonstrate fit sensitivity for prevention fit. Additional exploratory analyses are discussed and possible explanations for the lack of results are examined. / Master of Science / Regulatory focus theory includes two types of motivational orientations, promotion focus which centers on seeking success and prevention focus which centers on avoiding failure. If the way an individual’s pursues a goal (goal pursuit strategy) matches his or her regulatory focus orientation then he or she is considered to be in a state of regulatory fit. This state leads to various outcomes different than if an individual is in a state of non-fit. In the current study I have grouped these consequences into two types: fit sensitivity and performance. Essentially fit sensitivity is when the consequences seen do not have a correctness component and may be difference depending on the type of regulatory fit (promotion and prevention). Performance is when there is a correct or incorrect component to the outcome. The goal of the current study was to show that although fit sensitivity outcomes may be different for promotion fit and prevention fit, both fit states can lead to the same performance. With the initial analysis hypotheses were not supported but exploratory analysis did lend some support for prevention fit sensitivity. Discussion includes possible explanations for the lack of fit effects found.

M. Tech. (Department of Human Resource Development, Faculty of Management Sciences), Vaal University of Technology. / This objectivist, experimental study investigated the influence of virtual expert systems (VES) on the decision accuracy of non-expert consultants within a technology consulting contact centre environment. Because of the overwhelming availability of conceptual information, non-expert consultants experience challenges in making accurate decisions, and would benefit from augmented technologies, such as VES. VES hold the ability to capture and scale large volumes of decision variables for consideration by human experts when making decisions. A total of 40 participants were randomly selected from contact centres in the Eastern Cape and Gauteng provinces of South Africa for this study. Human logic was captured and scaled into a technology fault finding virtual expert and administered as an experiment to group participants. The experimental and control group participants were randomly assigned to the respective groups of 20 participants each. The control group was exposed to the paper-based, fault-finding manual. The pre-test and post-test data were collected based on four decision accuracy measures, namely individual performance, average call handling time, first call resolution and customer service. The Clarify performance system of the participating technology consulting company was used as data collection tool to record the findings used for Chapter 5. Statistical data analyses were performed using ANOVA and two-tailed significance tests to test the relationship between VES and decision accuracy in the pre-test and post-test phases of the study. The study found that the participant scores on the decision accuracy measures were only statistically significant on the measure of first call resolution measure (significance score of a p value <.05). On the other (three) measures, the scores obtained from experimental group participants showed more improvement than that of the control group participants. Consequently, the hypothesis that the use of VES enhance decision accuracy amongst non-expert technology consultants was accepted and the alternative hypothesis rejected. Some limitations pertaining to the resultant Hawthorne effect (the effect when some employees work harder and perform better when they are participants in an experiment) was noted amongst participants. This effect resulted from the use of team leaders in monitoring performance during the experiment and the involvement of the technology consulting company in determining the performance norms of the identified measures. Another limitation of the study related to the size of the sample where only two provinces were included. The limitation may affect the generalisation of results to other future settings when such a study is repeated. It was recommended that future studies in this field should make provision for a larger population, inclusive of other provinces to avoid these limitations.