The Effect of Task Type and Information Format on Web Searching Performance

Web search engines have become a useful tool helping Web users seek required information. Such Web sites typically present searched results as a textual list that may include thousands of Web pages. Because of the unstructured content and format of information that searchers receive, they often feel the pressure of information overload, which will inevitably compromise the quality of decision-making. Although researchers as well as practitioners have developed various information visualization approaches to enhance information presentation on Web search engines, the benefits of using such technology are unknown. This study will investigate whether and under what circumstances visualization of search results enhances users’ search performance. Cognitive fit theory will be used as the theoretical foundation of this paper. The objectives of the paper are 1) to extent cognitive fit theory in the emergent domain of Web searching, 2) to understand the effects of the user interface on search performance, and 3) to guide search engine designers on how to best present results to support different search tasks

Understanding Consumer Decision Making for Complex Choices: The Effects of Individual and Contextual Factors

E-commerce consumers are facing increasingly complex purchasing decisions. Due to their cognitive capacity, however, consumers may not always achieve their goal of optimal product choice. Existing research has focused on providing aids to consumers to help them make rational and conscious information choices for complex purchasing decisions. Recently, a dual-process Unconscious Thought Theory (UTT) has suggested otherwise. It shows that due to the limited cognitive resources, unconscious information processing may outperform conscious information processing for complex decisions. Drawing on the UTT, the study proposes that strategically designed interventions would interact with other contextual and individual factors in consumer information processing, and ultimately lead to superior consumer choice under certain choice environment. An experiment was conducted to test the research model. Focusing on the unconscious information processing in online shopping, this study has important implications for Web-specific human-computer interaction research and e-commerce practitioners

Efecto de las comunicaciones word of mouth y electronic word of mouth en las intenciones de recompra de una marca colombiana

El objetivo del presente artículo consiste en analizar el efecto de las comunicaciones informales offline y online entre ellas mismas, y sobre las intenciones de recompra de la marca Totto por parte de los jóvenes universitarios. Para lograrlo, se utilizó una metodología cuantitativa cuya recolección de información se realizó a partir de la utilización de un cuestionario estructurado, aplicado a una muestra de 306 jóvenes de edades comprendidas entre los 16 y 24 años. Los resultados demuestran que los jóvenes son más propensos a repetir la compra cuando acuden a las recomendaciones o comentarios cuya fuente de información son los familiares, los amigos o los expertos, dejando a un lado las recomendaciones procedentes de las redes sociales o de Internet

Metodologías para el desarrollo de interfaces visuales de recuperación de información : análisis y comparación

Introduction. In recent years the volume of electronic information has grown exponentially. This phenomenon improves data exchange and communication but introduces new troubles in relation to information access and searching. Aim. This paper proposes an exhaustive review of the different models, methods and algorithms that can be used to develop Visual Interfaces for Information Retrieval. The methods are classified on the basis of the stage of the process in which they take part: data analysis and transformation, application of classification and visual distribution algorithms, and application of visual transformation techniques. Methodology. Based on the analysis, we compare the different methods that can be used in each stage of the production process. We also determine which combinations of methods and algorithms are most suitable at different stages. Results. In the first section, data analysis and transformation, we analyse content mining, structure mining and use mining. In the second section, visual classification algorithm, we shown the hierarchical, network, scattering and map representations. In the last section, visual transformation techniques, we present the distortion (Focus+Context) and non-distortion techniques. Conclusion. The results aim to become useful tools for other researchers when choosing a methodological combination for the development of specific proposals for visual interfaces for information retrieval, as well as suggest implications to be considered on the research of new visual transformation techniques

Designing Systems that Support the Blogosphere for Deliberative Discourse

Web 2.0 has great potential to serve as a public sphere (Habermas, 1974; Habermas, 1989) – a distributed arena of voices where all who want to do so can participate. A well-functioning public sphere is important for pluralistic decision-making at many levels, ranging from small organizations to society at large. In this paper, we analyze the capability of the blogosphere in its current form to support such a role. This analysis leads to the identification of the principal issues that prevent the blogosphere from realizing its full potential as a public sphere. Most significantly, we propose that the sheer volume of content overwhelms blog readers, forcing them to restrict themselves to only a small subset of valuable content. This ultimately reduces their level of informedness. Based on past research on managing discourse, we propose four design artifacts that would alleviate these issues: a communal repository, textual clustering, visual cues, and a participation facility for blog users. We present a prototype system, called FeedWiz, which implements several of these design artifacts. Based on this initial design, we formulate a research agenda for the creation of new tools that effectively harness the potential of the growing body of user-generated content in the blogosphere and beyond

The Impact of Sentiment Analysis Output on Decision Outcomes: An Empirical Evaluation

User-generated online content serves as a source of product- and service-related information that reduces the uncertainty in consumer decision making, yet the abundance of such content makes it prohibitively costly to use all relevant information. Dealing with this (big data) problem requires a consumer to decide what subset of information to focus on. Peer-generated star ratings are excellent tools for one to decide what subset of information to focus on as they indicate a review’s “tone”. However, star ratings are not available for all user-generated content and not detailed enough in other cases. Sentiment analysis, a text-analytic technique that automatically detects the polarity of text, provides sentiment scores that are comparable to, and potentially more refined than, star ratings. Despite its popularity as an active topic in analytics research, sentiment analysis outcomes have not been evaluated through rigorous user studies. We fill that gap by investigating the impact of sentiment scores on purchase decisions through a controlled experiment using 100 participants. The results suggest that, consistent with the effort-accuracy trade off and effort-minimization concepts, sentiment scores on review documents improve the efficiency (speed) of purchase decisions without significantly affecting decision effectiveness (confidence)

FURTHERING KNOWLEDGE MANAGEMENT RESEARCH THROUGH ETHICAL CONSIDERATIONS: A RESEARCH AGENDA

Noting the general paucity of ethical considerations in Knowledge Management (KM) research, this research commentary articulates the relevance of ethics to KM. Drawing from the classical ethical theories in philosophy, it revisits certain research focuses raised in Alavi and Leidner’s (2001) well-known paper on KM and generates corresponding ethically-informed research questions. The main aim of this paper is to further KM research through such ethically-informed research questions that can be investigated by future studies. Other contributions and implications are also discussed

Infusing Ethical Considerations in Knowledge Management Scholarship: Toward a Research Agenda

The authors of this paper believe that scholarly work on knowledge management (KM) has largely overlooked ethical considerations. As such, this paper argues for the infusion of ethical considerations into knowledge management (KM) research. Using the lens of the classical ethical theories in philosophy, this paper revisits key areas of KM—knowledge creation, storage and access, transfer, and application—and generates relevant research questions in each of these areas. The paper highlights the importance of examining ethical issues related to KM, and offers an illustrative set of ethically-informed research themes and questions that can potentially be investigated by future studies

Development Of A Fisheye-Based Information Search Processing Aid (FISPA) For Managing Information Overload In The Web Environment

Information technologies have proliferated at an unprecedented rate to provide access to information across geographical boundaries. However, this proliferation has led to an information overload. Information overload has adverse impacts on information use and decision quality. This research focuses on the overload problem resulting from a web search, and proposes a potential remedy. We develop the requirements of a system that makes use of clustering and visualization for browsing the results of a typical web search. Based on this model, we develop a prototype that visualizes search results by first organizing them into a hierarchy according to their individual contents. This system presents a visual overview of the groups in this hierarchy, and lets the users focus (zoom) on specific groups of interest. One general problem with zooming within hierarchical structures is the separation between the details and the context. To address this problem, we implement a fisheye zooming capability in our system. This paper describes a typology of the various components necessary for addressing the problem, and then the proposed solution based upon a fisheye view-based visualization. Next, the specific visualization algorithm and the system implementation are described. We conclude with research questions for further development of such interfaces for presentation of the results from web searches