Search results

The paper seeks to examine the use of Internet among the research scholars of the Central Science Library (CSL), University of Delhi, India. The prime objective is to find out the current trends in information search through Internet by the research scholars and type of problems faced by them in their research work.

Tools used for the study are questionnaire, observation and informal interview using stratified method. Content analysis is used to analyse open‐ended questions. Data were collected from the 51 research scholars in the CSL, University of Delhi. The questionnaire consists of 15 main questions with many of the main questions having a number of subsidiaries. The questions are designed for the research scholars to elicit their experience with the Internet use for their research work.

The study finds that Boolean logic, truncation and wildcards are the most often used search techniques, web directories, while subject gateways are least used navigational tools, and the researches are beset with the problems of inadequate computers with Internet facilities, slow Internet connection and lack of skills and training. The survey also reveals that 57 per cent of the respondents are facing retrieval problems. Some research scholars lack research techniques and training.

This is the first comprehensive study of the use of the Internet by the University of Delhi science research scholars. Its findings should help CSL, University of Delhi in its plans and programmes related to effective and efficient use of Internet to fulfill information requirements of the research scholars and also proposes proper Internet searching training to research scholars to keep up‐to‐date on harnessing the immense potential of the Internet as a source of information for their research work.

Sources of information and other opportunities available via the Internet are increasing exponentially. This comes with the steady increase in Internet use for education, marketing and commercial trading, and in government for communication of information to citizens. Using the action research cycle of planning, acting, recording and reflecting, this article introduces a model for an approach to Internet searching and use. The model is a conceptual framework for Internet searching that will help people to overcome the challenges of working within an environment that is subject to continuous change, both in the forms of technology used and in the content that is available through the Internet. Our model encourages the searcher to use action research principles to enlighten their searching, reflecting and learning about new techniques as the tools that they use change around them. Our model should prove valuable to educators, researchers and consultants to inform their own practice as well as for use in the educational environment.

This paper aims to estimate the impact of job search on the internet on the probability of re‐employment and the duration of unemployment spells.

The study uses national panel datasets from Germany (SOEP 2003‐2007) and South Korea (KLIPS 1996‐2006) to estimate probit and Hausman‐Taylor IV models of the impact of job search on the internet on the probability of re‐employment. The study also explores duration analysis with the aim of estimating the impact of internet job search on the duration of unemployment.

In Germany and South Korea job seekers who used the internet had a 7.1 and 12.7 percentage point higher probability, respectively, of being re‐employed in the next 12 months. Furthermore, job seekers who used the internet had a shorter duration of unemployment in both Germany and South Korea.

Over the past decade, internet penetration rates and use of the internet in job search have risen sharply across the world. The internet has significantly changed the job application process and improved the channels of communication between employers and job seekers. The findings of the research indicate that the internet is beneficial and should be a part of job search efforts.

The contribution of this study is twofold. It is the first study to use panel datasets to analyze the link between internet use and job search outcomes. Therefore, the results are robust to unobserved heterogeneity problems. The study also addresses the issue of endogeneity of job search on the internet by using the Hausman‐Taylor IV model.

Since 2000, there has been a dramatic increase in the number of individuals using the Internet, including for health purposes. Internet usage has increased from 46% of adults in 2000 to 79% in 2010. The purpose of this chapter is to examine changes in one type of Internet usage: online health searching. We examine the impact of traditional digital inequality factors on online health searching, and whether these patterns have changed over time.

Using data from five surveys ranging from 2002 to 2010 (n = 5,967 for all five surveys combined), we examine changing patterns of online health searching over the past decade.

Effects vary by inequality factor and time period examined. Despite the diffusion of the Internet, most of these gaps persist, and even strengthen, over time. Gender, age, and education gaps persist over time and appear to be increasing. An exception to this is the importance of broadband connection.

Since these data were collected, the use of mobile devices to access the Internet has increased. Research is needed on types of access and devices used for online health activities.

Larger scale inequalities play important roles in online health searching. Providing access and skills in evaluating online health information is needed for older and less educated groups. The results of this study have implications for the de-professionalization of medical knowledge.

This is the first study to examine digital inequality factors in online health information seeking over the breadth of this time period.

The Internet and related information services attract increasing interest from information retrieval researchers. A survey of recent publications show that frequent topics are the effectiveness of search engines, information validation and quality, user studies, design of user interfaces, data structures and metadata, classification and vocabulary based aids, and indexing and search agents. Current research in these areas is briefly discussed. The changing balance between CD‐ROM sources and traditional online searching is quite important and is noted.

The purpose of this paper is to analyze the relationship between new product diffusion and consumer internet search patterns using big data and to investigate whether such data can be used in forecasting new product diffusion.

This research proposes a new product diffusion model based on the Bass diffusion model by incorporating consumer internet search behavior. Actual data from search engine queries and new vehicle sales for each vehicle class and region are used to estimate the proposed model. Statistical analyses are used to interpret the estimated results, and the prediction performance of the proposed method is compared with other methods to validate the usefulness of data for internet search engine queries in forecasting new product diffusion.

The estimated coefficients of the proposed model provide a clear interpretation of the relationship between new product diffusion and internet search volume. In 83.62 percent of 218 cases, analyzing the internet search pattern data are significant to explain new product diffusion and that internet search volume helps to predict new product diffusion. Therefore, marketing that seeks to increase internet search volume could positively affect vehicle sales. In addition, the demand forecasting performance of the proposed diffusion model is superior to those of other models for both long-term and short-term predictions.

As search queries have only been available since 2004, comparisons with data from earlier years are not possible. The proposed model can be extended using other big data from additional sources.

This research directly demonstrates the relationship between new product diffusion and consumer internet search pattern and investigates whether internet search queries can be used to forecast new product diffusion by product type and region. Based on the estimated results, increasing internet search volume could positively affect vehicle sales across product types and regions. Because the proposed model had the best prediction power compared with the other considered models for all cases with large margins, it can be successfully utilized in forecasting demand for new products.

This study identifies whether the Internet search index can be used as effective enough data to identify agricultural and livestock product demand and compare the accuracy of the prediction of major agricultural and livestock products purchases between these prediction models using artificial neural network, linear regression and a decision tree.

Artificial neural network, linear regression and decision tree algorithms were used in this study to compare the accuracy of the prediction of major agricultural and livestock products purchases. The analysis data were studied using 10-fold cross validation.

First, the importance of the Internet search index among the 20 explanatory variables was found to be high for most items, so the Internet search index can be used as a variable to explain agricultural and livestock products purchases. Second, as a result of comparing the accuracy of the prediction of six agricultural and livestock purchases using three models, beef was the most predictable, followed by radishes, chicken, Chinese cabbage, garlic and dried peppers, and by model, a decision tree shows the highest accuracy of prediction, followed by linear regression and an artificial neural network.

This study is meaningful in that it analyzes the purchase of agricultural and livestock products using data from actual consumers' purchases of agricultural and livestock products. In addition, the use of data mining techniques and Internet search index in the analysis of agricultural and livestock purchases contributes to improving the accuracy and efficiency of agricultural and livestock purchase predictions.

This study aims to determine the antecedents and consequences of information source choice to support a purchase decision for services high in experience attributes.

The authors conduct two studies to test their propositions. Study 1 is a single-category application using data from a national survey of 974 consumers who recently made a hotel-stay purchase/reservation. Correspondence analysis was used to identify search patterns, and regression analysis was used to identify their antecedents and influence on search outcomes. Study 2 is a cross-category study using data from a survey of 422 MTurk respondents reporting on search processes across six different services contexts, including hotel reservations. In this study, the authors seek generalization of their results to other services categories.

The authors identify four dimensions that characterize what information sources consumers, on average, use together when purchasing services. It is found that loyalty program membership and consistency in service delivery across a brand’s outlets for the brands in a consumer’s evoked set are important determinants of search patterns. Search patterns partially mediate the impact of consumer characteristics, choice context and choice set characteristics on search effort and, ultimately, on price paid.

An understanding of the factors that are associated with consumers’ choices of information sources and whether these choices are systematically related to search outcomes has implications for market segmentation and for marketers’ initiatives with respect to what information content to emphasize across sources.

The contribution is an understanding of the antecedents and consequences of consumer search patterns – and what information sources consumers tend to use together, considering the diversity of both internet and non-internet sources. There are limited insights in the services literature regarding how the internet impacts information search processes.