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This study proposes a novel method utilising a speech-word pair bipartite network to examine the correlation structure between members of parliament (MPs) in the context of the UK- China relationship.

We construct MP-word pair bipartite networks based on the co-occurrence relationship between MPs and words in their speech content. These networks are then mapped into monopartite MPs correlation networks. Additionally, the study calculates correlation network indicators and identifies MP communities and factions to determine the characteristics of MPs and their interrelation in the UK-China relationship. This includes insights into the distribution of key MPs, their correlation structure and the evolution and development trends of MP factions.

Analysis of the parliamentary speeches on China-related affairs in the British Parliament from 2011 to 2020 reveals that the distribution and interrelationship of MPs engaged in UK-China affairs are centralised and discrete, with a few core MPs playing an integral role in the UK-China relationship. Among them, MPs such as Lord Ahmad of Wimbledon, David Cameron, Lord Hunt of Chesterton and Lord Howell of Guildford formed factions with significant differences; however, the continuity of their evolution exhibits unstableness. The core MP factions, such as those led by Lord Ahmad of Wimbledon and David Cameron, have achieved a level of maturity and exert significant influence.

The research has several limitations that warrant acknowledgement. First, we mapped the MP-word pair bipartite network into the MP correlation network for analysis without directly analysing the structure of MPs based on the bipartite network. In future studies, we aim to explore various types of analysis based on the proposed bipartite networks to provide more comprehensive and accurate references for studying UK-China relations. In addition, we seek to incorporate semantic-level analyses, such as sentiment analysis of MPs, into the MP-word -pair bipartite networks for in-depth analysis. Second, the interpretations of MP structures in the UK-China relationship in this study are limited. Consequently, expertise in UK-China relations should be incorporated to enhance the study and provide more practical recommendations.

Firstly, the findings can contribute to an objective understanding of the characteristics and connotations of UK-China relations, thereby informing adjustments of focus accordingly. The identification of the main factions in the UK-China relationship emphasises the imperative for governments to pay greater attention to these MPs’ speeches and social relationships. Secondly, examining the evolution and development of MP factions aids in identifying a country’s diplomatic focus during different periods. This can assist governments in responding promptly to relevant issues and contribute to the formulation of effective foreign policies.

First, this study expands the research methodology of parliamentary debates analysis in previous studies. To the best of our knowledge, we are the first to study the UK-China relationship through the MP-word-pair bipartite network. This outcome inspires future researchers to apply various knowledge networks in the LIS field to elucidate deeper characteristics and connotations of UK-China relations. Second, this study provides a novel perspective for UK-China relationship analysis, which deepens the research object from keywords to MPs. This finding may offer important implications for researchers to further study the role of MPs in the UK-China relationship.

This study proposes a novel scheme for analysing the correlation structure between MPs based on bipartite networks. This approach offers insights into the development and evolving dynamics of MPs.

The anticorrosion coatings used in marine and atmospheric environment are subjected to many environmental factors. And the aging failure has been puzzling researchers. The purpose of this study is to find the correlation between the initial aging of epoxy coatings and the typical marine atmospheric environmental factors.

The epoxy coatings were subjected to a one-year exposure in three typical marine atmospheres. Meanwhile, principal component analysis, linear regression and Spearman and gray correlation analysis were applied to quantify the environmental characteristics and establish correlations with the coating aging.

The results indicate that the coating will undergo macroscopic fading and chalking upon exposure to the marine atmosphere, while microscopic examination reveals holes, cracks and partial peeling. The adhesion performance and electrochemical properties of the coating deteriorated with prolonged exposure, coating aging mainly occurs with the generation of O-H bonds and the breakage of molecular chains such as C-N and C-O-C. The coating was most deeply aged after exposure to the Xisha, followed by Zhoushan and finally Qingdao. Environmental factors affect the photooxidative aging and hydrolytic degradation processes of coatings and thus coating aging. To further demonstrate the correlation between environmental factors and coating aging, principal component analysis was used. The correlation model between environmental factors and coating aging was subsequently obtained. The correlation model between the rate of coating adhesion loss (E) and the comprehensive evaluation parameter of environmental factors (Z) is expressed as E = 0.142 + 0.028Z. Meanwhile, the Spearman correlation analysis and gray correlation method were used to investigate the impact of each environmental factor on coating aging. Solar irradiation, relative humidity and wetting time have the highest correlation with coating aging, which are all above 0.8 and have the greatest influence on coating aging; wind speed and temperature have the smallest correlation with coating aging, which are about 0.6 and have the least influence on coating aging.

This paper establishes a correlation between typical marine environmental factors and coating aging performance, which is crucial for predicting the service life of other coatings in diverse environments.

The relationships between integrated reporting quality (IRQ) and corporate governance characteristics have been studied extensively, but the results are still inconclusive and, sometimes, contradictory. The purpose of this paper is to systematize the results of previously published studies on the relationship between corporate governance and IRQ.

This paper uses several complementary theoretical perspectives (agency, stakeholder and signaling theory). The relevant aspects of the corporate governance system are the attributes and composition of the board, the existence of a social responsibility committee, the quality of the audit committee, integrated report assurance and ownership structures. The sample consisted of 61 papers published in top journals between 2015 and 2021. Meta-analytic procedures were applied on bivariate and partial correlations between IRQ and the identified corporate governance characteristics.

The results confirm that director independence, the existence of a social responsibility committee, institutional ownership and the hiring of a Big 4 auditor are significantly correlated with IRQ. On the other hand, board gender diversity, audit committee independence and dedicated assurance have a positive but nonsignificant impact on IRQ. Chairperson-chief executive officer duality does not seem to impact report quality, while ownership concentration has a negative but nonsignificant impact on IRQ.

Future research can improve the measurement of focal indicators by using a common set of variables for comparability, favoring disaggregate measures of corporate governance and updating the measurement of some indicators. Future research could also propose new indicators in the area of corporate governance and expand the theoretical domain of IRQ research.

The findings emphasize the need to explicitly consider the role of corporate governance structures and arrangements in improving IRQ. Through meta-analysis, the paper aims to provide a comprehensive and generalizable set of findings, suggesting that corporate governance indicators cannot be overlooked as predictors of integrated reporting.

The purpose of this paper is to measure the relationship of technology acceptance model (TAM) variables (PEOU and PU) with behavioral intention (BI) and attitude in mobile and digital libraries context. This study also examines the relationship of external variables (information quality and system quality) with TAM variables (PEOU and PU) in mobile and digital libraries context.

This meta-analysis was performed through PRISMA-P guidelines. Four databases (Google Scholar, Web of Science, Scopus and LISTA) were used for searching, and the search was conducted according to defined criteria.

Findings of this study revealed a large effect size of PU and PEOU with BI. There was also a large effect size of PU and PEOU with attitude. A medium effect size was found between SysQ → PU, InfoQ → PU and SysQ → PEOU. However, there was a small effect size between InfoQ and PEOU.

To the best of the authors’ knowledge, there was no study published till the time of conducting this meta-analysis. Hence, this study fills the literature gap. This study also confirms that TAM is a valid model in the acceptance and use of technology in mobile and digital libraries context. Thus, the findings of the present study are helpful for developers and designers in designing and developing mobile library apps. It will also be beneficial for library authorities and system librarians in designing and developing digital libraries in academic settings.

The purpose of this study is to assess the value of altmetrics or other indicators, showcasing the impact of academic output, which is seen too often correlated with the citation count.

This study considered three reputed journals of Library and Information Science (LIS) published by Elsevier. A total of 1,164 articles were found in these journals from 2016 to 2020 and the relationships between altmetric attention scores (AAS) and citations were examined. The analysis was extended to compare the grouped data set based on percentile ranks of AAS like top 50%, top 25%, top 10% and top 1%.

Using Spearman correlation analysis, the findings reveal a positive correlation between AAS and citations with different significant levels for all articles, and articles with AAS, as well as for normalized AAS in the top 50%, top 25%, top 10% and top 1% data set. For the three journals International Journal of Information Management (IJIM), Journal of Informetrics (JIF) and Library and Information Science Research (LISR), a significant positive correlation is observed across all data sets. But an unexpected result was observed: in the case of the top 50% of articles for the IJIM and JIF showed no significant correlation but the LISR journal showed a positive correlation for the whole data set. This journal though has fewer articles in comparison to the other two.

A source item that is highly cited may not be having high social media attention as reflected in the findings. This demarcates AAS with citations implying various factors on which these measurements are dependent. The study distinguishes these metrics lucidly. There is not a single guideline or uniformity in assessing the correlation found. But the problem is that the interpretation of the correlation strength affects the conclusion of the study. Moreover, this study will be a role model as a draft for librarians to select relevant journals for their libraries and will facilitate authors in the choice of the publication outlets for their papers, particularly concerning the journals that have both visibility and research impact.

The study reported devising a comprehensive tool to validate AAS as a measure of scholarly impact to include appropriate social media sources and verify its relationship with other metrics. To the best of the authors’ knowledge, this paper is the first attempt to discover the correlation between AAS and citations for the highly impactful LIS journal published by Elsevier. The empirical evidence lies in the citation and altmetric data extracted from the dimension database.

This study aims to establish a reliable index to identify interdisciplinary breakthrough innovation effectively. We constructed a new index, the D_Div index, for this purpose.

The D_Div index incorporates the degree of interdisciplinarity in the breakthrough index. To validate the index, a data set combining the publication records and citations of Nobel Prize laureates was divided into experimental and control groups. The validation methods included sensitivity analysis, correlation analysis and effectiveness analysis.

The sensitivity analysis demonstrated the D_Div index’s ability to differentiate interdisciplinary breakthrough papers from various categories of papers. This index not only retains the strengths of the existing index in identifying breakthrough innovation but also captures interdisciplinary characteristics. The correlation analysis revealed a significant correlation (correlation coefficient = 0.555) between the interdisciplinary attributes of scientific research and the occurrence of breakthrough innovation. The effectiveness analysis showed that the D_Div index reached the highest prediction accuracy of 0.8. Furthermore, the D_Div index outperforms the traditional DI index in terms of accuracy when it comes to identifying interdisciplinary breakthrough innovation.

This study proposed a practical and effective index that combines interdisciplinary and disruptive dimensions for detecting interdisciplinary breakthrough innovation. The identification and measurement of interdisciplinary breakthrough innovation play a crucial role in facilitating the integration of multidisciplinary knowledge, thereby accelerating the scientific breakthrough process.

Amid rapid technological progress, the construction industry is embracing Construction 4.0, redefining work practices through emerging technologies. However, the implications of Construction 4.0 technologies to enhancing well-being are still poorly understood. Particularly, the challenge lies in selecting technologies that critically contribute to well-being enhancement. Therefore, this study aims to evaluate the implications of Construction 4.0 technologies to enhancing well-being.

A list of Construction 4.0 technologies was identified from a national strategic plan on Construction 4.0, using Malaysia as a case study. Fourteen construction industry experts were selected to evaluate the implications of Construction 4.0 technologies on well-being using fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The expert judgment was measured using linguistic variables that were transformed into fuzzy values. Then, the collected data was analyzed using the following analyses: fuzzy TOPSIS, Pareto, normalization, sensitivity, ranking performance and correlation.

Six Construction 4.0 technologies are critical to enhancing well-being: cloud & real-time collaboration, big data & predictive analytics, Internet of Things, building information modeling, autonomous construction and augmented reality & virtualization. In addition, artificial intelligence and advanced building materials are recommended to be implemented simultaneously as a very strong correlation exists between them.

The novelty of this study lies in a comprehensive understanding of the implications of Construction 4.0 technologies to enhancing well-being. The findings can assist researchers, industry practitioners and policymakers in making well-informed decisions to select Construction 4.0 technologies when targeting the enhancement of the overall well-being of the local construction industry.

The climate change and related impacts are experienced around the world. There arise different triggering factors to climate change and impact. The purpose of this study is to figure out how changes in vegetation cover may or may not have an impact to climate change. The research will produce ideas for vegetation preservation and replant.

The investigation was probed for 34 years’ time period starting from the year 1981 to 2015. After testing and checking for serial autocorrelation in the vegetation data series, Mann–Kendal nonparametric statistical evaluation was carried out to investigate vegetation cover trends. Sen’s method was deployed to investigate the magnitude of vegetation cover change in natural differential vegetation index (NDVI) unit per year. Furthermore, the ArcGIS spatial analysis tools were used for the calculation of mean NDVI distribution and also for carrying out the spatial investigation of trends at each specific location within the study region.

The yearly mean NDVI during the study period was observed to have a decreasing trend. The mean NDVI value ranges between 0.32 and 0.98 NDVI unit, and hence, this means from less or poor vegetated zones to higher or healthier vegetated zones. The mean NDVI value was seen decreasing toward the highlands regions. The NDVI-rainfall correlation was observed to be stronger than the NDVI-temperature correlation. The % area coverage of NDVI-rainfall positive correlation was higher than the negative correlation. The % area coverage of NDVI-temperature negative correlation was higher than the positive correlation within the study region. Rainfall is seen as a highly influencing climatic factor for vegetation growth than the temperature within the study region.

This study in this country is a new approach for climate change monitoring and planning for the survival of the people of Papua New Guinea, especially for the farmer and those who is living in the coastal area.

This paper aims to empirically investigate time–frequency linkages between Euramerican mature and Asian emerging crude oil futures markets in terms of correlation and risk spillovers.

With daily data, the authors first undertake the MODWT method to decompose yield series into four different timescales, and then use the R-Vine Copula-CoVaR to analyze correlation and risk spillovers between Euramerican mature and Asian emerging crude oil futures markets.

The empirical results are as follows: (a) short-term trading is the primary driver of price volatility in crude oil futures markets. (b) The crude oil futures markets exhibit certain regional aggregation characteristics, with the Indian crude oil futures market playing an important role in connecting Euramerican mature and Asian emerging crude oil futures markets. What’s more, Oman crude oil serves as a bridge to link Asian emerging crude oil futures markets. (c) There are significant tail correlations among different futures markets, making them susceptible to “same fall but different rise” scenarios. The volatility behavior of the Indian and Euramerican markets is highly correlated in extreme incidents. (d) Those markets exhibit asymmetric bidirectional risk spillovers. Specifically, the Euramerican mature crude oil futures markets demonstrate significant risk spillovers in the extreme short term, with a relatively larger spillover effect observed on the Indian crude oil futures market. Compared with India and Japan in Asian emerging crude oil futures markets, China's crude oil futures market places more emphasis on changes in market fundamentals and prefers to hold long-term positions rather than short-term technical factors.

The MODWT model is utilized to capture the multiscale coordinated motion characteristics of the data in the time–frequency perspective. What’s more, compared to traditional methods, the R-Vine Copula model exhibits greater flexibility and higher measurement accuracy, enabling it to more accurately capture correlation structures among multiple markets. The proposed methodology can provide evidence for whether crude oil futures markets exhibit integration characteristics and can deepen our understanding of connections among crude oil futures prices.

The purpose of this study is to assess the correlations between the e-entrepreneurial intentions, attitude toward e-entrepreneurship, subjective norms, perceived behavior control, attitude toward risk and entrepreneurial knowledge of Jordanian business students to start an online business and the e-entrepreneurial intention.

A sample of 392 undergraduate business students from different Jordanian public and private universities participated in the study. Data were collected using an online survey-based questionnaire (i.e. Google Forms) using emails and social media platforms (i.e. WhatsApp, Facebook, etc.); reliability and validity tests were ensured. This study employs a 50-item questionnaire (distributed online via Google Forms and in two languages) to collect data, utilizing 5-point Likert scales; correlation analysis, linear regression analysis, and structural equation modeling are used to analyze the data.

The results showed that the e-entrepreneurship intentions of Jordanian business students are significantly predicted by their attitude toward e-entrepreneurship, subjective norms, perceived behavioral control, and entrepreneurial knowledge. One’s attitude toward risk does not influence the ambition to launch an Internet company much. Furthermore, their affiliation does not significantly impact the students' plans to pursue e-entrepreneurship.

The study has important real-world implications, particularly for Jordan. The country could create more jobs and boost the economy by encouraging students to start online businesses and helping small businesses grow. This is especially important in Jordan, where many people, particularly young adults, struggle to find work. Therefore, true need for interventions to foster e-entrepreneurship among business students in emerging economies like Jordan.

The goal of this research is to examine Jordanian business students' aspirations to launch Internet businesses in developing nations throughout the digital age. The results offer valuable information on the elements influencing the e-entrepreneurial intents of Jordanian business students. This information may be utilized to create programs and policies that effectively encourage e-entrepreneurship in Jordan.