The information resources utilization index: a case study in China

Abstract

Purpose – The purpose of this paper is to introduce a novel method for measuring the utilization of information resources (IRs) in order to provide a complementary index for existing information development indices and to reveal the links between the use of IRs and the readiness of ICT. Design/methodology/approach – This research mainly employs three types of research methodologies: literature study was conducted for defining the term of IRs and for finding the common features of the relevant indices; methods to construct composite indicators are used for developing a theoretical framework, selecting variables, imputation of missing data, normalization of data, weighting and aggregation of the novel index; a case study is carried out to provide a typical application for the index and to reveal the underlying links between the use of IRs and the readiness of ICT. Findings – This paper for the first time proposes a method to measure the utilization of IRs from a Chinese perspective and provides its theoretical foundations, conceptual frameworks, main steps and curial techniques. Further, correlations between the use of IRs and the readiness of ICT in China between 2009 and 2011 are also descried. Practical implications – Measuring the utilization of IRs provides the authorities with an alternative tool to monitor the evolutions a country toward information society. In addition, the novel index presented in this paper can also serve as a method to indentify the gaps among regions in deploying their IRs. Originality/value – This is the first paper to introduce a new measure for utilization of IRs and is also the first paper to reveal links between the use of IRs and the readiness of ICT as well as Gross Domestic Product in China.

Knowledge-based society and emerging disciplines: a correlation of academic performance

“…We used statistical analysis Spearman correlation for analyzing data using Statistical Package for Social Sciences to know the relationship between the pair of variables. This statistical analysis (non-parametric co-relations) is usually suitable for the smaller samples for ranking or ordinal data applied in analyzing the primary and secondary data (Borjigin et al , 2016; Ahmad et al , 2019). The Spearman’s correlation coefficient is based on rank values for each variable and not on the raw data.…”