How Does Web Advertising Affect Users' Information Seeking, Website Evaluation, and Source

Web advertising (ads) is currently a big issue for information seeking behavior on the Internet. Since websites are an important source of information in our daily lives, the websites have become popular media for advertising. The advertisers think that Web ads are the best way to get people to know quickly many things about a product or service [7]. However, from the viewers??? perspective, Web ads can be considered an obstacle to users??? information seeking on a website. Actually, Web ads received complains as being annoying or intruding, and it is considered to have negative effects such as affecting people???s task performance by many researchers [2, 5, 6]. The objective of this research is to know how Web advertising affects users??? information seeking, website evaluation, and source evaluation. Most previous studies have focused on the effectiveness of Web ads toward viewers. Not many studies researched on how Web ads affect users??? information seeking performance, website evaluation, and content evaluation of a website. According to visual attention theory, since people???s visual attention is limited, the more attention Web ads received from a viewer, the less amount of attention was available for the visual search task and the more damaging it was to the search task [5]. Therefore, Web ads will affect people???s information seeking performance, and consequently it will influence website evaluation and source evaluation of the website. My research question is: how do different types of Web advertising which attract people???s attention at differing levels affect users??? information seeking performance, website evaluation, and source evaluation? I will employ an empirical research design with various levels of attention grabbing Web ads and users??? information seeking performance, website evaluation, and source evaluation. I will use a total of 200 college students as the sample population in this research, and I will randomly assign the participants into four different groups (50 participants in each group): three experimental groups for low, medium, and high attention grabbing Web ads and one control group (a group with no Web ads). There would be no significant difference between groups in terms of years of computer experience, years of Internet experience, and gender

Institutional and Individual Influences on Scientists\u27 Data Sharing Behaviors

In modern research activities, scientific data sharing is essential, especially in terms of data-intensive science and scholarly communication. Scientific communities are making ongoing endeavors to promote scientific data sharing. Currently, however, data sharing is not always well-deployed throughout diverse science and engineering disciplines. Disciplinary traditions, organizational barriers, lack of technological infrastructure, and individual perceptions often contribute to limit scientists from sharing their data. Since scientists\u27 data sharing practices are embedded in their respective disciplinary contexts, it is necessary to examine institutional influences as well as individual motivations on scientists\u27 data sharing behaviors. The objective of this research is to investigate the institutional and individual factors which influence scientists\u27 data sharing behaviors in diverse scientific communities. Two theoretical perspectives, institutional theory and theory of planned behavior, are employed in developing a conceptual model, which shows the complementary nature of the institutional and individual factors influencing scientists\u27 data sharing behaviors. Institutional theory can explain the context in which individual scientists are acting; whereas the theory of planned behavior can explain the underlying motivations behind scientists\u27 data sharing behaviors in an institutional context. This research uses a mixed-method approach by combining qualitative and quantitative methods: (1) interviews with the scientists in diverse scientific disciplines to understand the extent to which they share their data with other researchers and explore institutional and individual factors affecting their data sharing behaviors; and (2) survey research to examine to what extent those institutional and individual factors influence scientists\u27 data sharing behaviors in diverse scientific disciplines. The interview study with 25 scientists shows three groups of data sharing factors, including institutional influences (i.e. regulative pressures by funding agencies and journals and normative pressure); individual motivations (i.e. perceived benefit, risk, effort and scholarly altruism); and institutional resources (i.e. metadata and data repositories). The national survey (with 1,317 scientists in 43 disciplines) shows that regulative pressure by journals; normative pressure at a discipline level; and perceived career benefit and scholarly altruism at an individual level have significant positive relationships with data sharing behaviors; and that perceived effort has a significant negative relationship. Regulative pressure by funding agencies and the availability of data repositories at a discipline level and perceived career risk at an individual level were not found to have any significant relationships with data sharing behavior

Social scientists’ data reuse behaviors: Exploring the roles of attitudinal beliefs, attitudes, norms, and data repositories.

Many disciplines within the social sciences have a dynamic culture of sharing and reusing data. Because social science data differ from data in the hard sciences, it is necessary to explicitly examine social science data reuse. This study explores the data reuse behaviors of social scientists in order to better understand both the factors that influence those social scientists' intentions to reuse data and the extent to which those factors influence actual data reuse. Using an integrated theoretical model developed from the theory of planned behavior (TPB) and the technology acceptance model (TAM), this study provides a broad explanation of the relationships among factors influencing social scientists' data reuse. A total of 292 survey responses were analyzed using structural equation modeling. Findings suggest that social scientists' data reuse intentions are directly influenced by the subjective norm of data reuse, attitudes toward data reuse, and perceived effort involved in data reuse. Attitude toward data reuse mediated social scientists' intentions to reuse data, leading to the indirect influence of the perceived usefulness and perceived concern of data reuse, as well as the indirect influence of the subjective norm of data reuse. Finally, the availability of a data repository indirectly influenced social scientists' intentions to reuse data by reducing the perceived effort involved

WEB ADVERTISING: WHAT DO WE KNOW ABOUT ITS ACCEPTANCE AND IMPACTS? - A META-ANALYSIS OF THE LITERATURE

Internet advertising market has grown rapidly over the past decade. Its annual revenue has reached around 21.1 billion in 2007, and more than half of Internet advertising is related to Web advertising. Web advertising affects the majority if not all web viewers who would encounter some Web ads at one time or the other when they are using the Web. With such a magnitude on investment and in influence, however, our understanding of Web ads is limited and fragmented. This study aims to provide a comprehensive picture of the state of research on Web advertising, especially its interaction with individual viewers. In this meta-analysis of more than sixty empirical research articles published from 1996 to 2007, we develop a framework of Web advertising research that can be used to demonstrate the research foci so far. Both dependent and independent variables can be classified with the framework. Our findings indicate that (1) empirical studies on Web advertising have considered features of four components and their interactions: viewer, Web Ad, ad host, and product/service being advertised. The impacts of Web ads have been found to be on viewers and viewers\u27 interactions with ads, hosts, and products/services. (2) The number of empirical research of Web advertising has increased gradually in different academic disciplines; however, the number is very insignificant compared to the growing Web advertising market and the broad influence of Web ads. (3) The study efforts are scattered and the findings are inconsistent and inconclusive. We conclude the existing studies and point out future research directions in this area

Scientists’ Data Reuse Behaviors: A Multilevel Analysis

This study explores the factors that influence the data reuse behaviors of scientists and identifies the generalized patterns that occur in data reuse across various disciplines. This research employed an integrated theoretical framework combining institutional theory and the theory of planned behavior. The combined theoretical framework can apply the institutional theory at the individual level and extend the theory of planned behavior by including relevant contexts. This study utilized a survey method to test the proposed research model and hypotheses. Study participants were recruited from the Community of Science’s (CoS) Scholar Database, and a total of 1,528 scientists responded to the survey. A multilevel analysis method was used to analyze the 1,237 qualified responses. This research showed that scientists’ data reuse intentions are influenced by both disciplinary level factors (availability of data repositories) and individual level factors (perceived usefulness, perceived concern, and the availability of internal resources). This study has practical implications for promoting data reuse practices. Three main areas that need to be improved are identified: Educating scientists, providing internal supports, and providing external resources and supports such as data repositories

Factors affecting psychologists’ adoption of an open data badge

The purpose of this research is to investigate the individual, normative and resource factors affecting psychologists’ adoption of an open data badge. The theory of planned behavior is employed as the theoretical framework to explain how these factors impact behavioral intention to adopt an open data badge. A national survey (n=341) of psychologists found that perceived benefits, norms of data sharing and attitude towards an open data badge had a significant positive relationship with attitude toward the open data badge, whereas perceived risk had a significant negative relationship. Perceived effort had a negative relationship to behavioral intention to adopt the open data badge, but had no relationship to attitude formation surrounding the open data badge adoption. The availability of a data repository and pressure from an open science journal did not have a significant relationship to behavioral intentions to adopt an open data badge. The implications for psychologists from a practical and theoretical perspective, and future directions for improving psychologists’ data sharing behaviors are discussed

Attitudinal, normative, and resource factors affecting psychologists’ intentions to adopt an open data badge: An empirical analysis

The purpose of this research is to investigate the attitudinal, normative, and resource factors affecting psychologists’ adoption of an open data badge. The theory of planned behavior was employed to demonstrate how these factors influence behavioral intentions to adopt an open data badge. This research used a survey method to examine to what extent those attitudinal, normative, resource factors influence psychologists’ behavioral intentions to adopt an open data badge, and therefore engage in data sharing behaviors. A national survey (n = 341) across the field of psychology showed that perceived benefit and perceived risk had significant positive and negative relationships with attitude toward the open data badge respectively. Furthermore, attitude toward open data badge and norm of data sharing had significant positive influences on psychologists’ behavioral intentions to adopt the open data badge. Perceived effort had a significant negative relationship with the behavioral intention to adopt the open data badge, but had no effect toward attitudes surrounding the badge. However, this research found that the availability of a data repository and pressure from an open science journal did not have any significant relationship with behavioral intention to adopt the open data badge. The discussion includes implications for psychologists from both practical and theoretical perspectives. Additionally, future directions for gauging psychologists’ adoption of the open data badge and increasing data sharing behaviors are discussed

To share or not to share?: a comparative analysis of data sharing factors by different academic positions

The significance of sharing research data has been critically discussed since data sharing is an essential matter in scientific research where the process needs to create and use the vast amount of data in data-intensive research environment. The institutional or disciplinary context is important to understand research practices and data re-use in scientific fields which encourages collaboration among researchers and promotes their research. However, there have been little studies on data sharing behaviors within institutional or disciplinary context. This study develops a research model based on the integration of institutional theory and the theory of planned behavior by focusing on the community norm of data sharing. This research investigates how essential data sharing factors including regulative pressure by journals, normative pressure, scholarly altruism, perceived career benefit and risk, and perceived effort differ across diverse academic positions such as graduate/post-doctoral researchers, and assistant, associate, and full professors. The survey was conducted with researchers in U.S. academic institutions in STEM disciplines, such as physical sciences, biological sciences, engineering, health sciences, and social sciences, and the total of 1,656 responses were collected. A Multivariate Analysis of Variance is employed to examine the hypothesized relationships between data sharing behaviors and academic positions in the research model. This research will provide theoretical and practical implications for encouraging data sharing in research communities and developing data sharing policies for funding agencies, journal publishers, and academic institutions

To share or not to share?: a comparative analysis of data sharing factors by different academic positions

The significance of sharing research data has been critically discussed since data sharing is an essential matter in scientific research where the process needs to create and use the vast amount of data in data-intensive research environment. The institutional or disciplinary context is important to understand research practices and data re-use in scientific fields which encourages collaboration among researchers and promotes their research. However, there have been little studies on data sharing behaviors within institutional or disciplinary context. This study develops a research model based on the integration of institutional theory and the theory of planned behavior by focusing on the community norm of data sharing. This research investigates how essential data sharing factors including regulative pressure by journals, normative pressure, scholarly altruism, perceived career benefit and risk, and perceived effort differ across diverse academic positions such as graduate/post-doctoral researchers, and assistant, associate, and full professors. The survey was conducted with researchers in U.S. academic institutions in STEM disciplines, such as physical sciences, biological sciences, engineering, health sciences, and social sciences, and the total of 1,656 responses were collected. A Multivariate Analysis of Variance is employed to examine the hypothesized relationships between data sharing behaviors and academic positions in the research model. This research will provide theoretical and practical implications for encouraging data sharing in research communities and developing data sharing policies for funding agencies, journal publishers, and academic institutions

Education for eScience Professionals: Integrating Data Curation and Cyberinfrastructure

Large, collaboratively managed datasets have become essential to many scientific and engineering endeavors, and their management has increased the need for "eScience professionals" who solve large scale information management problems for researchers and engineers. This paper considers the dimensions of work, worker, and workplace, including the knowledge, skills, and abilities needed for eScience professionals. We used focus groups and interviews to explore the needs of scientific researchers and how these needs may translate into curricular and program development choices. A cohort of five masters students also worked in targeted internship settings and completed internship logs. We organized this evidence into a job analysis that can be used for curriculum and program development at schools of library and information science