Information Search Behavior: Proposal of Study with Investors in the Stock Market

With the aim of analyzing the information search behavior of investors working in the stock market, this research sought to raise the aspects related to this behavior with focus on the cognitive and causal aspects which pervade the need for information of these investors. For that, the general pattern of informational behavior proposed by Wilson [10], and also the analysis of a report from an investor of the stock market area were used as basis for the analysis and reflection. The report of only one investor was used as basis for investigation, turning it impossible to extrapolate such result to a greater universe. The objective of this research was to investigate the need for information, the context and the intervenient variables which might interfere or not in the information search behavior of investors, in an attempt to get a deeper comprehension about the subject, as well as to propose the continuity of studies with basis on this study proposal.

Information Search Habits of First Year College Students

New technologies have transformed teaching processes and enabled new ways of study and learning. In these activities, it is suspected that the students don't make good use of new available technologies or, in the best case, they are underused. The analysis of this issue with the design of strategies to correct any defects found is the motivation that supports the development of this work and the main purpose of it. Evaluate information search habits used by the student and analyse their deduct synthesis and processing capabilities of the results found. The researchers of this study are university teachers of first year subjects, which allows them to know the information search performances by students.

Analysis and Coordination of Expert Statements in the Problems of Intellectual Information Search

* This work was financially supported by RFBF-04-01-00858.

Improving understandability in consumer health information search: Uevora @ 2016 fire chis

This paper presents our work at 2016 FIRE CHIS. Given a CHIS query and a document associated with that query, the task is to classify the sentences in the document as relevant to the query or not; and further classify the relevant sentences to be supporting, neutral or opposing to the claim made in the query. In this paper, we present two different approaches to do the classification. With the first approach, we implement two models to satisfy the task. We first implement an information retrieval model to retrieve the sentences that are relevant to the query; and then we use supervised learning method to train a classification model to classify the relevant sentences into support, oppose or neutral. With the second approach, we only use machine learning techniques to learn a model and classify the sentences into four classes (relevant & support, relevant & neutral, relevant & oppose, irrelevant & neutral). Our submission for CHIS uses the first approach.

THE INTERACTION BETWEEN INTERNAL AND EXTERNAL INFORMATION ON RELATIONAL DATA SEARCH

People often use tools to search for information. In order to improve the quality of an information search, it is important to understand how internal information, which is stored in user’s mind, and external information, represented by the interface of tools interact with each other. How information is distributed between internal and external representations significantly affects information search performance. However, few studies have examined the relationship between types of interface and types of search task in the context of information search. For a distributed information search task, how data are distributed, represented, and formatted significantly affects the user search performance in terms of response time and accuracy. Guided by UFuRT (User, Function, Representation, Task), a human-centered process, I propose a search model, task taxonomy. The model defines its relationship with other existing information models. The taxonomy clarifies the legitimate operations for each type of search task of relation data. Based on the model and taxonomy, I have also developed prototypes of interface for the search tasks of relational data. These prototypes were used for experiments. The experiments described in this study are of a within-subject design with a sample of 24 participants recruited from the graduate schools located in the Texas Medical Center. Participants performed one-dimensional nominal search tasks over nominal, ordinal, and ratio displays, and searched one-dimensional nominal, ordinal, interval, and ratio tasks over table and graph displays. Participants also performed the same task and display combination for twodimensional searches. Distributed cognition theory has been adopted as a theoretical framework for analyzing and predicting the search performance of relational data. It has been shown that the representation dimensions and data scales, as well as the search task types, are main factors in determining search efficiency and effectiveness. In particular, the more external representations used, the better search task performance, and the results suggest the ideal search performance occurs when the question type and corresponding data scale representation match. The implications of the study lie in contributing to the effective design of search interface for relational data, especially laboratory results, which are often used in healthcare activities.

Consumer Search Behavior in High Involvement Purchases

The aim of this study is to investigate the consumer search behavior in high involvement purchases. The results of this research provide the descriptive analysis of the information search phase which is a part of the decision-making process. The study focuses on customer’s choice of the information sources, motivation behind it and different factors that influence the search behavior. Particular attention is paid to the purchase categorization and the differences in information search between products and services. The qualitative research method is chosen for this study. The data is gathered through ten theme interviews. Each participant of the interview describes his/her own search behavior in a product and a service case. The results indicate that consumer search behavior vary according to the purchase categorization, demographic, individual and situational factors. Moreover, the above-mentioned factors influence the purpose and position of the information search phase in a five-step decision making model.

Backpacker 2.0 - Contemporary backpackers and their use of social media as an information and communication platform

Long-term independent budget travel to countries far away has become increasingly common over the last few decades, and backpacking has now entered the tourism mainstream. Nowadays, backpackers are a very important segment of the global travel market. Backpacking is a type of tourism that involves a lot of information search activities. The Internet has become a major source of information as well as a platform for tourism business transactions. It allows travelers to gain information very effortlessly and to learn about tourist destinations and products directly from other travelers in the form of electronic word-of-mouth (eWOM). Social media has penetrated and changed the backpacker market, as now modern travelers can stay connected to people at home, read online recommendations, and organize and book their trips very independently. In order to create a wider understanding on modern-day backpackers and their information search and share behavior in the Web 2.0 era, this thesis examined contemporary backpackers and their use of social media as an information and communication platform. In order to achieve this goal, three sub-objectives were identified: 1. to describe contemporary backpacker tourism 2. to examine contemporary backpackers’ travel information search and share behavior 3. to explore the impacts of new information and communications technologies and Web 2.0 on backpacker tourism The empirical data was gathered with an online survey, thus the method of analysis was mainly quantitative, and a qualitative method was used for a brief analysis of open questions. The research included both descriptive and analytical approaches, as the goal was to describe modern-day backpackers, and to examine possible interdependencies between information search and share behavior and background variables. The interdependencies were tested for statistical significance with the help of five research hypotheses. The results suggested that backpackers no longer fall under the original backpacker definitions described some decades ago. Now, they are mainly short-term travelers, whose trips resemble more those of mainstream tourists. They use communication technologies very actively, and particularly social media. Traditional information sources, mainly guide books and recommendations from friends, are of great importance to them but also eWOM sources are widely used in travel decision making. The use of each source varies according to the stage of the trip. All in all, Web 2.0 and new ICTs have transformed the backpacker tourism industry in many ways. Although the experience has become less authentic in some travelers’ eyes, the backpacker culture is still recognizable.

Is more information always good? : investigating the impact of website interface features on e-retailer's sales performance

A number of frameworks have been suggested for online retailing, but still there exists little consensus among researchers and practitioners regarding the appropriate amount of information critical and essential to the improvement of customers' satisfaction and their purchase intention. Against this backdrop, this study contributes to the current practical and theoretical discussions and conversations about how information search and perceived risk theories can be applied to the management of online retailer website features. This paper examines the moderating role of website personalization in studying the relationship between information content provided on the top US retailers' websites, and customer satisfaction and purchase intention. The study also explores the role played by customer satisfaction and purchase intention in studying the relationship between information that is personalized to the needs of individual customers and online retailers' sales performance. Results indicate that the extent of information content features presented to online customers alone is not enough for companies looking to satisfy and motivate customers to purchase. However, information that is targeted to an individual customer influences customer satisfaction and purchase intention, and customer satisfaction in tum serves as a driver to the retailer's online sales performance.

Information needs for a purchase of fairtrade coffee

This research investigates what information German Fairtrade coffee consumers search for during pre-purchase information seeking and to what extent information is retrieved. Furthermore, the sequence of the information search as well as the degree of cognitive involvement is highlighted. The role of labeling, the importance of additional ethical information and its quality in terms of concreteness as well as the importance of product price and organic origin are addressed. A set of information relevant to Fairtrade consumers was tested by means of the Information Display Matrix (IDM) method with 389 Fairtrade consumers. Results show that prior to purchase, information on product packages plays an important role and is retrieved rather extensively, but search strategies that reduce the information processing effort are applied as well. Furthermore, general information is preferred over specific information. Results of two regression analyses indicate that purchase decisions are related to search behavior variables rather than to socio-demographic variables and purchase motives. In order to match product information with consumers’ needs, marketers should offer information that is reduced to the central aspects of Fairtrade.

A grouped P2P network for scalable grid information services

Information services play a crucial role in grid environments in that the state information can be used to facilitate the discovery of resources and the services available to meet user requirements, and also to help tune the performance of a grid system. However, the large size and dynamic nature of the grid brings forth a number of challenges for information services. This paper presents PIndex, a grouped peer-to-peer network that can be used for scalable grid information services. PIndex builds on Globus MDS4, but introduces peer groups to dynamically split the large grid information search space into many small sections to enhance its scalability and resilience. PIndex is subsequently modeled with Colored Petri Nets for performance evaluation. The simulation results show that PIndex is scalable and resilient in dealing with a large number of peer nodes.