The effects of attribute quality information and sources of information on consumers' perceptions and behavior: A model of Pre-purchase Information Utilization in Service Physical Environments

The search-experience-credence framework from economics of information, the human-environment relations models from environmental psychology, and the consumer evaluation process from services marketing provide a conceptual basis for testing the model of "Pre-purchase Information Utilization in Service Physical Environments." The model addresses the effects of informational signs, as a dimension of the service physical environment, on consumers' perceptions (perceived veracity and perceived performance risk), emotions (pleasure) and behavior (willingness to buy). The informational signs provide attribute quality information (search and experience) through non-personal sources of information (simulated word-of-mouth and non-personal advocate sources).^ This dissertation examines: (1) the hypothesized relationships addressed in the model of "Pre-purchase Information Utilization in Service Physical Environments" among informational signs, perceived veracity, perceived performance risk, pleasure, and willingness to buy, and (2) the effects of attribute quality information and sources of information on consumers' perceived veracity and perceived performance risk.^ This research is the first in-depth study about the role and effects of information in service physical environments. Using a 2 x 2 between subjects experimental research procedure, undergraduate students were exposed to the informational signs in a simulated service physical environment. The service physical environments were simulated through color photographic slides.^ The results of the study suggest that: (1) the relationship between informational signs and willingness to buy is mediated by perceived veracity, perceived performance risk and pleasure, (2) experience attribute information shows higher perceived veracity and lower perceived performance risk when compared to search attribute information, and (3) information provided through simulated word-of-mouth shows higher perceived veracity and lower perceived performance risk when compared to information provided through non-personal advocate sources. ^

Advertising effects on brand search and preference: Assessing the mediational role of *Aad and *Ab

Most advertising research has focussed at examining effects of advertising on attitudinal responses or brand preference and choice. However, in a natural environment, the time period between advertising exposure and purchase decision is filled with prepurchase search. Prepurchase external search refers to information search from sources other than memory, prior to making a purchase decision. Usually consumers access only a small subset of available information and base their choice decisions on it. Prepurchase search therefore acts as a filter and, the final choice depends critically on the small subset of potential inputs the consumer notes in the environment and integrates into the decision. Previous research has identified a variety of factors that affect consumers' prepurchase search behavior. However, there is little understanding of how specific advertisements designed by marketers impact consumers' prepurchase search. A marketer would like consumers to search information that reflects favorably on his/her brand. Hence, s/he would attempt to influence the brands and attributes on which consumers seek information prior to making a choice. The dissertation investigates the process by which a particular marketer's advertising influences consumers' search on available brands, i.e., the marketer's brand and other competing brands. The dissertation considers a situation where exposure to advertising occurs prior to seeking information from any other source. Hence, the impact of advertising on subsequent search behavior is the topic of interest. The dissertation develops a conceptual model of advertising effects on brand search and conducts two experiments to test the tenets of this model. Specifically, the dissertation demonstrates that attitudinal responses generated by advertising mediate advertising effects on search attitudes and behaviors. The dissertation goes on to examine how attitudinal responses generated by advertising and subsequent effects on search alter brand preference and choice. ^

The Influence of Psychological Predictors and Cognitive Behavioral Stress Management Intervention on Antiretroviral Therapy (ART) Adherence Among HIV-Positive Female Haitian Alcohol Users

Purpose: Over half the HIV-infected persons in the Caribbean, the second most HIV-impacted region in the world, live in Haiti. Using secondary data from a parent study, this research assessed the effects of psychological and social factors on antiretroviral therapy (ART) adherence among Haitian, HIV-positive, female alcohol users. Theoretical Foundation and Research Questions: Using the Theory of Planned Behavior/Reasoned Action and the Information, Motivation, Behavior skills model as guiding theoretical frameworks, the study examined the effectiveness of an adapted cognitive behavioral stress management (CBSM-A) intervention in improving ART adherence. The effect of psychological factors (depression, anxiety, beliefs about medicine, and social support), social factors (stigma, relationship status, and educational attainment), and alcohol on adherence to ART was assessed. Methods: The sample consisted of 116 female ART patients who were randomly assigned to the CBSM-A intervention or the wait-list control group. Participants completed intervention sessions as well as pre- and post-test assessments. Analyses of variance, t-tests, and point biserial correlations were used to test hypotheses. Results: Surprisingly, ART adherence rates significantly decreased for both groups combined [F (1, 108) = 8.79, p = .004]; there was no significant difference between the intervention and control groups with regard to the magnitude of change between baseline and post assessment. On average, depression decreased significantly among participants in the CBSM-A group only [(t (62) = 5.54, p < .001)]. For both groups combined, alcohol use significantly decreased between baseline and post-assessment [(F (1, 78) = 34.70, p < .001)]; there was no significant difference between the intervention and control groups with regard to the magnitude of change between baseline and post-assessment. None of the variables were significantly correlated with ART adherence. Discussion: Adherence to ART did not improve in this sample, nor were any of the variables significantly associated with adherence. The findings suggest that additional supportive and psychological services may be needed in order to promote higher adherence to ART among HIV-positive females. More research may be needed on this sample; a focus on mental health issues, partner conflict, family and sexual history may allow for better targeting and more successful interventions.

Efficient storage and domain-specific information discovery on semistructured documents

The increasing amount of available semistructured data demands efficient mechanisms to store, process, and search an enormous corpus of data to encourage its global adoption. Current techniques to store semistructured documents either map them to relational databases, or use a combination of flat files and indexes. These two approaches result in a mismatch between the tree-structure of semistructured data and the access characteristics of the underlying storage devices. Furthermore, the inefficiency of XML parsing methods has slowed down the large-scale adoption of XML into actual system implementations. The recent development of lazy parsing techniques is a major step towards improving this situation, but lazy parsers still have significant drawbacks that undermine the massive adoption of XML. ^ Once the processing (storage and parsing) issues for semistructured data have been addressed, another key challenge to leverage semistructured data is to perform effective information discovery on such data. Previous works have addressed this problem in a generic (i.e. domain independent) way, but this process can be improved if knowledge about the specific domain is taken into consideration. ^ This dissertation had two general goals: The first goal was to devise novel techniques to efficiently store and process semistructured documents. This goal had two specific aims: We proposed a method for storing semistructured documents that maps the physical characteristics of the documents to the geometrical layout of hard drives. We developed a Double-Lazy Parser for semistructured documents which introduces lazy behavior in both the pre-parsing and progressive parsing phases of the standard Document Object Model’s parsing mechanism. ^ The second goal was to construct a user-friendly and efficient engine for performing Information Discovery over domain-specific semistructured documents. This goal also had two aims: We presented a framework that exploits the domain-specific knowledge to improve the quality of the information discovery process by incorporating domain ontologies. We also proposed meaningful evaluation metrics to compare the results of search systems over semistructured documents. ^

Efficient Storage and Domain-Specific Information Discovery on Semistructured Documents

The increasing amount of available semistructured data demands efficient mechanisms to store, process, and search an enormous corpus of data to encourage its global adoption. Current techniques to store semistructured documents either map them to relational databases, or use a combination of flat files and indexes. These two approaches result in a mismatch between the tree-structure of semistructured data and the access characteristics of the underlying storage devices. Furthermore, the inefficiency of XML parsing methods has slowed down the large-scale adoption of XML into actual system implementations. The recent development of lazy parsing techniques is a major step towards improving this situation, but lazy parsers still have significant drawbacks that undermine the massive adoption of XML. Once the processing (storage and parsing) issues for semistructured data have been addressed, another key challenge to leverage semistructured data is to perform effective information discovery on such data. Previous works have addressed this problem in a generic (i.e. domain independent) way, but this process can be improved if knowledge about the specific domain is taken into consideration. This dissertation had two general goals: The first goal was to devise novel techniques to efficiently store and process semistructured documents. This goal had two specific aims: We proposed a method for storing semistructured documents that maps the physical characteristics of the documents to the geometrical layout of hard drives. We developed a Double-Lazy Parser for semistructured documents which introduces lazy behavior in both the pre-parsing and progressive parsing phases of the standard Document Object Model's parsing mechanism. The second goal was to construct a user-friendly and efficient engine for performing Information Discovery over domain-specific semistructured documents. This goal also had two aims: We presented a framework that exploits the domain-specific knowledge to improve the quality of the information discovery process by incorporating domain ontologies. We also proposed meaningful evaluation metrics to compare the results of search systems over semistructured documents.