The purpose of this dissertation was to analyze the susceptibility of capital budgeting decisions to bias. Based on the political nature of many of these decisions, attribute framing effects were analyzed in a capital budgeting decision context. Specifically, two independent variables were analyzed: accounting data and attribute frames. This research proposed that attribute framing effects would be conditional on the nature of the accounting data being considered. When the accounting data elicited a positive or negative evaluative reaction, attribute frames were expected to be unobtrusive to capital budgeting decisions. However, when the accounting data was neutral, eliciting an ambiguous evaluative reaction, attribute frames were predicted to bias these decisions. An experiment was conducted that considered the issue across two types of capital budgeting decisions: accept/reject decisions (dichotomous decision) and strategic alliance judgments (monetary allocations). Experimental findings strongly support the predicted relationships. These results suggest that persuasive descriptions are not effective in capital budgeting contexts when accounting data provides a clear picture as to the investment's future success; however, these tactics may be vitally important when accounting information is unclear about the investment's future success. / Ph. D.

Les informations négatives sur les produits et les entreprises auxquelles les consommateurs ont accès ne sont pas toujours fiables et claires. Cette thèse étudie comment l'orientation régulatrice des consommateurs influe sur leur réaction par rapport aux informations négatives comme une fonction de l'ambiguïté des informations. Nous suggérons que lorsque les informations négatives sont ambigües, les consommateurs avec une orientation prévention, par rapport à ceux avec une orientation promotion, seront beaucoup plus influencés par les informations et susceptibles de changer en conséquence vers le bas leur attitude envers la marque. En revanche, lorsque les informations négatives sont claires, à la fois les consommateurs orientés promotion et ceux orientés prévention seront très influencés et susceptibles de revoir leur attitude à la baisse par rapport à la marque en question. De plus, nous alléguons que la diagnosticité perçue des informations exerce un rôle médiateur sur les effets proposés. Plus particulièrement, en présence des informations négatives ambiguës, l'orientation prévention (par rapport à l'orientation promotion) a tendance à amplifier la diagnosticité perçue des informations qui, en retour, accentue les effets que les informations négatives auront sur la révision de l'attitude. Quatre études expérimentales ont testé et confirmé ces hypothèses à travers trois scénarios ambigus différents : (1) quand les informations négatives proviennent d'une source dont la crédibilité est incertaine (étude 1), (2) quand la raison pour laquelle un produit défectueux est ambiguë (étude 2) et (3) quand les évaluations de produit sont très contradictoires (études 3a et 3b). / Negative information about products or companies that consumers encounter in the marketplace is not always certain and clear-cut. This dissertation explores how consumers' regulatory focus orientation affects their response to negative information as a function of information ambiguity. We propose that under the situations where ambiguity is present in the negative information, prevention-focused compared to promotion-focused consumers will be more strongly persuaded and exhibit a large downward revision of their attitude toward the brand. In contrast, under the situations where the negative information is unambiguous, both promotion and prevention-focused consumers will be strongly persuaded and revise accordingly their attitude toward the brand. Moreover, we argue that perceived diagnosticity of the information mediates the proposed effect. Specifically, in the presence of ambiguity in negative information, a prevention focus (vs. a promotion focus) leads to an inflated perceived information diagnosticity, which, in turn, accentuates the impact of negative information on judgment revision. Four experimental studies tested and confirmed these propositions in three different ambiguous scenarios: (1) when negative product information comes from a source with uncertain credibility(Study 1); (2) when the cause of a reported product failure is ambiguous(Study2), and (3) when product reviews are highly conflicting (Study 3a and Study 3b).

We are concerned with addressing the worst-case distributed source coding (DSC) problem in asymmetric and interactive communication scenarios and its application to data-gathering wireless sensor networks in enhancing their lifetime. First, we propose a unified canonical framework, obtained by considering different communication constraints and objectives, to address the variants of DSC problem. Second, as for the worst-case information-theoretic analysis, the notion of information entropy cannot be used, we propose information ambiguity, derive its various properties, and prove that it is a valid information measure. Third, for a few variants of our interest of DSC problem, we provide the communication protocols and prove their optimality. In a typical data-gathering sensor network, the base-station that wants to gather sensor data is often assumed to be much more resourceful with respect to energy, computation, and communication capabilities compared to sensor nodes. Therefore, we argue that in such networks, the base-station should bear the most of the burden of communication and computation in the network. Allowing the base-station and sensor nodes to interactively communicate with each other enables us to carry this out. Our definition of sensor network lifetime allows us to reduce the problem of maximizing the worst-case network lifetime to the problem of minimizing the number of bits communicated by the nodes in the worst-case, which is further reduced to the worst-case DSC problem in asymmetric and interactive communication scenarios, with the assumption that the base-station knows the support-set of sensor data. We demonstrate that the optimal solutions of the energy-oblivious DSC problem variants cannot be directly applied to the data-gathering sensor networks, as those may be inefficient in the energy-constrained sensor networks. We address a few energy-efficient variants of DSC problem and provide optimal communication protocols for the sensor networks, based on those variants. Finally, we combine distributed source coding with two other system level opportunities of channel coding and cooperative nature of the nodes to further enhance the lifetime of the sensor networks. We address various scenarios and demonstrate the dependence of the computational complexity of the network lifetime maximization problem on the complex interplay of above system-level opportunities.