Does Criticism Overcome the Praises of Journal Impact Factor?

Journal impact factor (IF) as a gauge of influence and impact of a particular journal comparing with other journals in the same area of research, reports the mean number of citations to the published articles in particular journal. Although, IF attracts more attention and being used more frequently than other measures, it has been subjected to criticisms, which overcome the advantages of IF. Critically, extensive use of IF may result in destroying editorial and researchers’ behaviour, which could compromise the quality of scientific articles. Therefore, it is the time of the timeliness and importance of a new invention of journal ranking techniques beyond the journal impact factor

A Comparison between Two Main Academic Literature Collections: Web of Science and Scopus Databases

Nowadays, the world’s scientific community has been publishing an enormous number of papers in different scientific fields. In such environment, it is essential to know which databases are equally efficient and objective for literature searches. It seems that two most extensive databases are Web of Science and Scopus. Besides searching the literature, these two databases used to rank journals in terms of their productivity and the total citations received to indicate the journals impact, prestige or influence. This article attempts to provide a comprehensive comparison of these databases to answer frequent questions which researchers ask, such as: How Web of Science and Scopus are different? In which aspects these two databases are similar? Or, if the researchers are forced to choose one of them, which one should they prefer? For answering these questions, these two databases will be compared based on their qualitative and quantitative characteristics

Global ICT developments, 1998–2009.

<p>Source: ITU World Telecommunication/ICT Indicators database.</p

Estimation Results using GMM Estimator based on different income levels.

<p>The dependent variable is the Ln(GDP) and all variables are in Logarithm form.</p><p>Figures in parentheses refer to standard errors.</p><p>***, ** and * denote statistically significant at 1%, 5% and 10%, respectively.</p><p>GDP (-t) and ICT (-t), t = 1, 2, 3, 4 are lagged variables of GDP and ICT respectively.</p

Information and Communication Technology Use and Economic Growth

<div><p>In recent years, progress in information and communication technology (ICT) has caused many structural changes such as reorganizing of economics, globalization, and trade extension, which leads to capital flows and enhancing information availability. Moreover, ICT plays a significant role in development of each economic sector, especially during liberalization process. Growth economists predict that economic growth is driven by investments in ICT. However, empirical studies on this issue have produced mixed results, regarding to different research methodology and geographical configuration of the study. This paper examines the impact of Information and Communication Technology (ICT) use on economic growth using the Generalized Method of Moments (GMM) estimator within the framework of a dynamic panel data approach and applies it to 159 countries over the period 2000 to 2009. The results indicate that there is a positive relationship between growth rate of real GDP per capita and ICT use index (as measured by the number of internet users, fixed broadband internet subscribers and the number of mobile subscription per 100 inhabitants). We also find that the effect of ICT use on economic growth is higher in high income group rather than other groups. This implies that if these countries seek to enhance their economic growth, they need to implement specific policies that facilitate ICT use.</p> </div

Estimation Results using GMM Estimator.

<p>***, ** and * denote statistically significant at 1%, 5% and 10%, respectively.</p><p>The dependent variable is the first-difference of the Ln(GDP) per capita and all variables are in Logarithm form.</p><p>GDP (-t) and ICT (-t), t = 1, 2, 3, 4 are lagged variables of GDP and ICT use index respectively.</p

ICT use index, 2000–2009.

<p>ICT use index, 2000–2009.</p