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 effects of writing process instruction on the writing and reading performance of students with learning disabilities

The purpose of this study was to determine the efficacy of a writing process approach for the instruction of language arts with learning disabled elementary students. A nonequivalent control group design was used. The sample included 24 students with learning disabilities who were in second and third grade. All students were instructed in resource room settings for ninety minutes per day in language arts. The students in the treatment group received instruction using the writing process steps to create complete meaningful compositions on self-chosen topics. A literature-based reading program accompanied instruction in writing to provide examples of good writing and to provide a basis for topic selection. The students in the control group received instruction through the use of the county-adopted textbooks and accompanying worksheets. The teacher followed basic textbook and curriculum guide suggestions which consisted mainly of fill in the blank and matching type exercises. The treatment group consisted of 12 students: five second-graders and seven third-graders. The control group consisted of 12 students: four second-graders and eight third-graders. All students were pretested and posttested using the Woodcock-Johnson Tests of Achievement-Revised (WJ-R ACH) for writing samples and the Woodcock Reading Mastery Test (WRMT) for reading achievement. T-tests were also done to investigate the gain from pre to post for each reading or writing variable for each group separately. The results showed a highly significant difference from pretest to posttest for all writing and reading variables for both groups. Analysis of Covariance showed that the population mean posttest achievement scores for all variables adjusted for the pretest were higher for the treatment group than those for the control group.

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. ^

Ranked search on data graphs

Graph-structured databases are widely prevalent, and the problem of effective search and retrieval from such graphs has been receiving much attention recently. For example, the Web can be naturally viewed as a graph. Likewise, a relational database can be viewed as a graph where tuples are modeled as vertices connected via foreign-key relationships. Keyword search querying has emerged as one of the most effective paradigms for information discovery, especially over HTML documents in the World Wide Web. One of the key advantages of keyword search querying is its simplicity—users do not have to learn a complex query language, and can issue queries without any prior knowledge about the structure of the underlying data. The purpose of this dissertation was to develop techniques for user-friendly, high quality and efficient searching of graph structured databases. Several ranked search methods on data graphs have been studied in the recent years. Given a top-k keyword search query on a graph and some ranking criteria, a keyword proximity search finds the top-k answers where each answer is a substructure of the graph containing all query keywords, which illustrates the relationship between the keyword present in the graph. We applied keyword proximity search on the web and the page graph of web documents to find top-k answers that satisfy user’s information need and increase user satisfaction. Another effective ranking mechanism applied on data graphs is the authority flow based ranking mechanism. Given a top- k keyword search query on a graph, an authority-flow based search finds the top-k answers where each answer is a node in the graph ranked according to its relevance and importance to the query. We developed techniques that improved the authority flow based search on data graphs by creating a framework to explain and reformulate them taking in to consideration user preferences and feedback. We also applied the proposed graph search techniques for Information Discovery over biological databases. Our algorithms were experimentally evaluated for performance and quality. The quality of our method was compared to current approaches by using user surveys.

Framing infectious diseases and U.S. public opinion

The United States has been increasingly concerned with the transnational threat posed by infectious diseases. Effective policy implementation to contain the spread of these diseases requires active engagement and support of the American public. To influence American public opinion and enlist support for related domestic and foreign policies, both domestic agencies and international organizations have framed infectious diseases as security threats, human rights disasters, economic risks, and as medical dangers. This study investigates whether American attitudes and opinions about infectious diseases are influenced by how the issue is framed. It also asks which issue frame has been most influential in shaping public opinion about global infectious diseases when people are exposed to multiple frames. The impact of media frames on public perception of infectious diseases is examined through content analysis of newspaper reports. Stories on SARS, avian flu, and HIV/AIDS were sampled from coverage in The New York Times and The Washington Post between 1999 and 2007. Surveys of public opinion on infectious diseases in the same time period were also drawn from databases like Health Poll Search and iPoll. Statistical analysis tests the relationship between media framing of diseases and changes in public opinion. Results indicate that no one frame was persuasive across all diseases. The economic frame had a significant effect on public opinion about SARS, as did the biomedical frame in the case of avian flu. Both the security and human rights frames affected opinion and increased public support for policies intended to prevent or treat HIV/AIDS. The findings also address the debate on the role and importance of domestic public opinion as a factor in domestic and foreign policy decisions of governments in an increasingly interconnected world. The public is able to make reasonable evaluations of the frames and the domestic and foreign policy issues emphasized in the frames.

Next generation of recommender systems: Algorithms and applications

Personalized recommender systems aim to assist users in retrieving and accessing interesting items by automatically acquiring user preferences from the historical data and matching items with the preferences. In the last decade, recommendation services have gained great attention due to the problem of information overload. However, despite recent advances of personalization techniques, several critical issues in modern recommender systems have not been well studied. These issues include: (1) understanding the accessing patterns of users (i.e., how to effectively model users' accessing behaviors); (2) understanding the relations between users and other objects (i.e., how to comprehensively assess the complex correlations between users and entities in recommender systems); and (3) understanding the interest change of users (i.e., how to adaptively capture users' preference drift over time). To meet the needs of users in modern recommender systems, it is imperative to provide solutions to address the aforementioned issues and apply the solutions to real-world applications. ^ The major goal of this dissertation is to provide integrated recommendation approaches to tackle the challenges of the current generation of recommender systems. In particular, three user-oriented aspects of recommendation techniques were studied, including understanding accessing patterns, understanding complex relations and understanding temporal dynamics. To this end, we made three research contributions. First, we presented various personalized user profiling algorithms to capture click behaviors of users from both coarse- and fine-grained granularities; second, we proposed graph-based recommendation models to describe the complex correlations in a recommender system; third, we studied temporal recommendation approaches in order to capture the preference changes of users, by considering both long-term and short-term user profiles. In addition, a versatile recommendation framework was proposed, in which the proposed recommendation techniques were seamlessly integrated. Different evaluation criteria were implemented in this framework for evaluating recommendation techniques in real-world recommendation applications. ^ In summary, the frequent changes of user interests and item repository lead to a series of user-centric challenges that are not well addressed in the current generation of recommender systems. My work proposed reasonable solutions to these challenges and provided insights on how to address these challenges using a simple yet effective recommendation framework.^

Exploring Hidden Coherent Feature Groups and Temporal Semantics for Multimedia Big Data Analysis

Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e., IF-TMCA) approach is presented for effective event detection. Specifically, the HCFG algorithm is integrated with the Hierarchical Information Gain Analysis (HIGA) method to generate the Importance Factor (IF) for producing the initial detection results. Then, the TMCA algorithm is proposed to efficiently incorporate temporal semantics for re-ranking and improving the final performance. At last, a sampling-based ensemble learning mechanism is applied to further accommodate the imbalanced datasets. In addition to the multimedia semantic representation and class imbalance problems, lack of organization is another critical issue for multimedia big data analysis. In this framework, an affinity propagation-based summarization method is also proposed to transform the unorganized data into a better structure with clean and well-organized information. The whole framework has been thoroughly evaluated across multiple domains, such as soccer goal event detection and disaster information management.

Durability assessment of polymer trileaflet heart valves

The durability of a polymer trileaflet valve is dependent on leaflet stress concentrations, so valve designs that reduce stress can, hypothetically, increase durability. Design aspects that are believed to contribute to reduced leaflet stress include stent flexibility, parabolic coaptation curvature, and leaflet anisotropy. With this in mind, the purpose of this investigation was to elucidate what specific combinations of these parameters promote optimal acute and long-term valve function. A combination of four stent designs, seven leaflet reinforcement materials, and three coaptation geometries were evaluated through a combination of experimentation and modeling. Static tensile and Poisson’s ratio tests and dynamic tensile fatigue testing were used to evaluate the individual leaflet components; and hydrodynamic testing and accelerated valve fatigue was used to assess complete valve prototypes. The two most successful designs included a 0.40 mm thick knit-reinforced valve with a fatigue life of 10.35 years, and a 0.20 mm thick knit-reinforced valve with a 28.9 mmHg decrease in pressure drop over the former. A finite element model was incorporated to verify the impact of the above-mentioned parameters on leaflet stress concentrations. Leaflet anisotropy had a large impact on stress concentrations, and matching the circumferential modulus to that of the natural valve showed the greatest benefit. Varying the radial modulus had minimal impact. Varying coaptation geometry had no impact, but stent flexibility did have a marked effect on the stress at the top of the commissure, where a completely rigid stent resulted in a higher peak stress than a flexible stent (E = 385 MPa). In conclusion, stent flexibility and leaflet anisotropy do effect stress concentrations in the SIBS trileaflet valve, but coaptation geometry does not. Regions of high stress concentrations were linked to failure locations in vitro, so a fatigue prediction model was developed from the S/N curves generated during dynamic tensile testing of the 0.20 mm knit-reinforced leaflets. Failure was predicted at approximately 400 million cycles (10 years) at the top of the commissure. In vitro fatigue of this valve showed failure initiation after approximately 167 million cycles (4.18 years), but it was related to a design defect that is subsequently being changed.

Human Resource Development Practices in U.S. Enterprises in Russia: A Literature Review

This study investigated human resource development (HRD) in Russian enterprises, U.S. firms in Russia, or U.S.-Russian joint ventures. Thirty-three articles were selected through a database search and examined using content analysis. Emerging themes included workers’ knowledge and skills, training practices, organizational involvement, responsibility, and communication, and leadership styles.

The Specialist: Coming Soon To Your Local Hotel

In an article entitled - The Specialist: Coming Soon To Your Local Hotel - by Stan Bromley, Regional Vice President and General Manager, Four Seasons Clift Hotel, San Francisco, the author’s introduction states: “An experienced hotelier discusses the importance of the delivery of a high “quality-to-value” ratio consistently to guests, particularly as the hotel market becomes specialized and a distinction is drawn between a “property” and a “hotel.” The author’s primary intention is to make you, the reader, aware of changes in the hospitality/hotel marketplace. From the embryo to the contemporary, the hotel market has consistently evolved; this includes but is not limited to mission statement, marketing, management, facilities, and all the tangibles and intangibles of the total hotel experience. “Although we are knocking ourselves out trying to be everything to everyone, I don't think hotel consumers are as interested in “mixing and matching” as they were in the past,” Bromley says. “Today's hotel guest is looking for “specialized care,” and is increasingly skeptical of our industry-wide hotel ads and promises of greatness.” As an example Bromley makes an analogy using retail outlets such as Macy’s, Saks, and Sears, which cater to their own unique market segment. Hotels now follow the same outline, he allows. “In my view, two key factors will make a hotel a success,” advises Bromley. “First, know your specialty and market to that segment. Second, make sure you consistently offer a high quality-to-value ratio. That means every day.” To emphasize that second point, Bromley offers this bolstering thought, “The second factor that will make or break your business is your ability to deliver a high "quality/value" ratio-and to do so consistently.” The author evidently considers quality-to-value ratio to be an important element. Bromley emphasizes the importance of convention and trade show business to the hotel industry. That business element cannot be over-estimated in his opinion. This doesn’t mean an operator who can accommodate that type of business should exclude other client opportunities outside the target market. It does mean, however, these secondary opportunities should only be addressed after pursuing the primary target strategy. After all, the largest profit margin lies in the center of the target. To amplify the above statement, and in reference to his own experience, Bromley says, “Being in the luxury end of the business I, on the other hand, need to uncover and book individuals and small corporate meetings more than convention or association business.

Information Discovery on Electronic Health Records Using Authority Flow Techniques

Background As the use of electronic health records (EHRs) becomes more widespread, so does the need to search and provide effective information discovery within them. Querying by keyword has emerged as one of the most effective paradigms for searching. Most work in this area is based on traditional Information Retrieval (IR) techniques, where each document is compared individually against the query. We compare the effectiveness of two fundamentally different techniques for keyword search of EHRs. Methods We built two ranking systems. The traditional BM25 system exploits the EHRs' content without regard to association among entities within. The Clinical ObjectRank (CO) system exploits the entities' associations in EHRs using an authority-flow algorithm to discover the most relevant entities. BM25 and CO were deployed on an EHR dataset of the cardiovascular division of Miami Children's Hospital. Using sequences of keywords as queries, sensitivity and specificity were measured by two physicians for a set of 11 queries related to congenital cardiac disease. Results Our pilot evaluation showed that CO outperforms BM25 in terms of sensitivity (65% vs. 38%) by 71% on average, while maintaining the specificity (64% vs. 61%). The evaluation was done by two physicians. Conclusions Authority-flow techniques can greatly improve the detection of relevant information in EHRs and hence deserve further study.

Durability Assessment of Polymer Trileaflet Heart Valves

The durability of a polymer trileaflet valve is dependent on leaflet stress concentrations, so valve designs that reduce stress can, hypothetically, increase durability. Design aspects that are believed to contribute to reduced leaflet stress include stent flexibility, parabolic coaptation curvature, and leaflet anisotropy. With this in mind, the purpose of this investigation was to elucidate what specific combinations of these parameters promote optimal acute and long-term valve function. A combination of four stent designs, seven leaflet reinforcement materials, and three coaptation geometries were evaluated through a combination of experimentation and modeling. Static tensile and Poisson’s ratio tests and dynamic tensile fatigue testing were used to evaluate the individual leaflet components; and hydrodynamic testing and accelerated valve fatigue was used to assess complete valve prototypes. The two most successful designs included a 0.40 mm thick knit-reinforced valve with a fatigue life of 10.35 years, and a 0.20 mm thick knit-reinforced valve with a 28.9 mmHg decrease in pressure drop over the former. A finite element model was incorporated to verify the impact of the above-mentioned parameters on leaflet stress concentrations. Leaflet anisotropy had a large impact on stress concentrations, and matching the circumferential modulus to that of the natural valve showed the greatest benefit. Varying the radial modulus had minimal impact. Varying coaptation geometry had no impact, but stent flexibility did have a marked effect on the stress at the top of the commissure, where a completely rigid stent resulted in a higher peak stress than a flexible stent (E = 385 MPa). In conclusion, stent flexibility and leaflet anisotropy do effect stress concentrations in the SIBS trileaflet valve, but coaptation geometry does not. Regions of high stress concentrations were linked to failure locations in vitro, so a fatigue prediction model was developed from the S/N curves generated during dynamic tensile testing of the 0.20 mm knit-reinforced leaflets. Failure was predicted at approximately 400 million cycles (10 years) at the top of the commissure. In vitro fatigue of this valve showed failure initiation after approximately 167 million cycles (4.18 years), but it was related to a design defect that is subsequently being changed.

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