Search results

There are many complex networks like World-Wide Web, internet and social networks have been reported to be scale-free. The major property of scale-free networks is their degree distributions are in power law form. Generally, the degree exponents of scale-free networks fall into the range of (2, 3). The purpose of this paper is to investigate other situations where the degree exponents may lie outside the range.

In this paper, analysis has been carried out by varying the degree exponents in the range of (0.5, 4.5). In total, 243 scenarios have been generated with varying network size of 1,000, 2,000 and 4,000, and degree exponents in the range of (0.5, 4.5) using interval of 0.05.

The following five indicators have been investigated: average density, average clustering coefficient, average path length, average diameter and average node degree. These indicators vary with the network size and degree exponent. If certain indicators do not satisfy with the user requirement using degree exponents of (2, 3), one can further increase or decrease the value with tradeoff. Results recommend that for degree exponents in (0.5, 2), 26 possible scale-free networks can be selected whereas for (3, 4.5), 41 possible scale-free networks can be selected, assuming a 100 percent deviation on the network parameters.

A tolerance analysis is given for the tradeoff and guideline is drawn to help better design of scale-free network for degree exponents in range of (0.5, 2) and (3, 4.5) using network size 1,000, 2,000 and 4,000. The methodology is applicable to any network size.

This research aims to comprehend the factors that impact the emerging inclination of consumers toward mobile finance technology (fintech) services over banking institutions. The study focuses on users' demographics and psychographics to delineate their unique segments and profiles.

The study proposes a segmentation and profiling framework that includes variance analysis, two-step cluster analysis and pairwise statistical tests. This framework is applied to a dataset of customers using a range of mobile fintech services, specifically robo-investment, peer-to-peer (P2P) payments, robo-advisory and digital savings. The analysis creates distinct customer profile clusters, which are later validated using pairwise statistical tests based on segmentation output.

Empirical results reveal that P2P payment service users exhibit a higher frequency of usage, proficiency and intention to continue using the service compared to users of robo-investment or digital savings platforms. In contrast, individuals utilizing robo-advisory services are identified to have a significantly greater familiarity and intention to sustain engagement with the service compared to digital savings users.

The findings provide financial institutions, especially traditional banks with actionable insights into their customer base. This information enables them to identify specific customer needs and preferences, thereby allowing them to tailor products and services accordingly. Ultimately, this understanding may strategically position traditional banks to maintain competitiveness amidst the increasing prominence of fintech enterprises.

This research provides an in-depth examination of customer segments and profiles within the mobile fintech services sphere, thus giving a nuanced understanding of customer behavior and preferences and generating practical recommendations for banks and other financial institutions. This study thereby sets the stage for further research and paves the way for developing personalized products and services in the evolving fintech landscape.

This study aims to provide a more complete picture of blockchain development by combining numerous methodologies with diverse data sources, such as academic papers and news articles. This study displays the developmental status of each subject based on the interrelationships of each topic cluster by analyzing high-frequency keywords extracted from the collected data. Moreover, applying above methodologies will help understanding top research topics, authors, venues, institutes and countries. The differences of blockchain research and new are identified.

To identify and find blockchain development linkages, researchers have used search terms such as co-occurrence, bibliographic coupling, co-citation and co-authorship to help us understand the top research topics, authors, venues, institutes and countries. This study also used text mining analysis to identify blockchain articles' primary concepts and semantic structures.

The findings show the fundamental topics based on each topic cluster's links. While “technology”, “transaction”, “privacy and security”, “environment” and “consensus” were most strongly associated with blockchain in research, “platform”, “big data and cloud”, “network”, “healthcare and business” and “authentication” were closely tied to blockchain news. This article classifies blockchain principles into five patterns: hardware and infrastructure, data, networking, applications and consensus. These statistics helped the authors comprehend the top research topics, authors, venues, publication institutes and countries.

Since Web of Science (WoS) and LexisNexis Academic data are used, the study has few sources. Others advise merging foreign datasets. WoS is one of the world's largest and most-used databases for assessing scientific papers.

This study has several uses and benefits. First, key concept discoveries can help academics understand blockchain research trends so they can prioritize research initiatives. Second, bibliographic coupling links academic papers on blockchain. It helps information seekers search and classify the material. Co-citation analysis results can help researchers identify potential partners and leaders in their field. The network's key organizations or countries should be proactive in discovering, proposing and creating new relationships with other organizations or countries, especially those from the journal network's border, to make the overall network more integrated and linked. Prominent members help recruit new authors to organizations or countries and link them to the co-authorship network. This study also used concept-linking analysis to identify blockchain articles' primary concepts and semantic structures. This may lead to new authors developing research ideas or subjects in primary disciplines of inquiry.

The purpose of this paper is to bibliometrically analyze the gerontology-related research articles for a comprehensive understanding of the gerontology literature.

This study employed the approach of visual analytics on 32 journals with a total of 99,204 articles published after 2000 to identify the main subfields, keywords, and growth trend. The investigated journals are either open access online or listed in the Social Sciences Citation Index. In addition, the 200 most frequently cited papers were analyzed through bibliographic coupling, co-word, and co-citation analysis.

The selected most cited papers were mostly published before 2007, and psychiatry and psychology were the top research subfields. Dementia, older adult, and Alzheimer’s disease were the three most frequently occurring keywords, both in Author Keywords and KeyWords Plus. While coupling analysis yielded 12 research groups, co-word analysis classified the most frequently used 20 Author Keywords into two categories. Four research clusters were identified by the co-citation analysis.

This research provides a comprehensive view of the gerontology research as well as an understanding of the subfields and their interrelations. It also provides government departments with directions for formulating and executing policies affecting older people not only in setting academic and professional priorities but also in understanding the key topics related to older people.

This study aims to provide researchers a holistic approach for comprehensive understanding of the Bitcoin-related research by discovering its trends, subjects, relations, keywords and concepts.

An integrated approach of bibliometric analysis, network analysis and concept linking analysis was proposed for exploring Bitcoin-related studies from 70 countries in the Scopus database.

The bibliometric analysis shows that electronic money and blockchain are the mainstream issues of Bitcoin, and the domain distribution of the literature is mainly in engineering-related fields. Through the network analysis of cocitations, co-occurrences and cowords, research clusters were discovered respectively from different perspectives. The authors also have mastered a multilevel concept linking diagram for six related major concepts.

The major contribution of this research is about providing an integrated and comprehensive approach to extract the mainstream issues that can help researchers conduct Bitcoin-relevant research. This study shows the development trend, context and clusters of Bitcoin-related studies from various perspectives networks and produces a visual concept linking diagram that will enable researchers to quickly understand the contextual relationship between Bitcoin keywords during literature analysis. In addition, the most crucial studies in the main topics are extracted to save the considerable time and labor that would be required to manually read all the literature and summarize the issues.

The purpose of this study was to explore the effect of innovative service mode of intelligent library on improving the service quality and a series of impacts on user behavior. With the rapid development of information technology, internet of things has become an important carrier of people’s “intelligent life”. The emergence of intelligent library will no longer be limited by space; it is affecting people’s lives and work imperceptibly. This new service mode was studied here, and the relationship between the service quality of intelligent library and users’ behavior was analyzed from the perspective of user acceptance and use behavior of intelligent library. Moreover, this study explores how to optimize the service quality to let users accept this technology and service mode and thus realize the original idea.

Through 800 questionnaires issued to the users in the Zhejiang Provincial AI Library, the authors obtained the study data. Among the received questionnaires, 676 copies are valid, and 124 responses are either incomplete or not answered, and so, the efficient rate is 84.5 per cent.

There is a significantly positive correlation between service innovation and service quality. There is a significantly positive correlation between service quality and behavioral intention. There is a significantly positive correlation between service innovation and behavioral intention.

From the point of view of innovative service, this paper analyzes the effect of innovative service mode of intelligent library on improving the service quality and a series of impacts on user behavior. This study confirms that intelligent library is a relatively new service innovation. Users’ curiosity and exploration will make them access some relevant information. As a result, a reasonably innovative service is an important factor in users’ acceptance behavior.

This chapter provides an overview of the social policy development and assessment in East Asia. Our study shows that social policy assessment in this region is still relying on objective indicators and interviews, even though most of the regional governments have implemented the Regulatory Impact Assessment for improving regulation quality. General approaches to measuring social value such as Cost–Benefit Analysis, Cost-Effectiveness Analysis and Social Return on Investment are not commonly used in the formulation of social policies. We compare the features of these approaches and provide suggestions about how to embed social value assessment tools into social policy and strategy development process.

A tension leg platform (TLP) is a vertically moored, floating structure which is normally used for offshore oil/gas production. However, these types of structures can be damaged by vibration responses that are too large. The purpose of this paper is to consider the influence of the external waves on oceanic structures.

A mathematical model of an ocean environment was constructed, in which wave‐induced flow fields cause structural surge motion, then solutions to the mathematical model were analytically derived.

The Takagi‐Sugeno (T‐S) fuzzy model is employed in the approximation of the oceanic structure. The stability analysis of the TLP system is carried out using the Lyapunov direct method.

The dependence of the wave‐induced flow field and its resonant frequency on the wave characteristics and the structural properties of the platform, which include width, thickness and mass, can be drawn using a parametric approach.

Mathematical modeling is applied to find the wave‐induced displacement due to the surge motion. The vibration of the mechanical motion of the platform structure caused by wave force is also discussed.

There has been considerable discussion of various aspects of the “Web 2.0” concept in the past several years. However, the Web 2.0 concept as a whole has not been analysed through the lens of the Web 1.0 metrics on which managers rely heavily for planning and evaluation. This paper aims to analyse the relationships among a site's audience metrics and its degree of Web 2.0‐ness.

Data collected from an online panel's clickstreams were aggregated to derive the web audience metrics. A web site's degree of Web 2.0‐ness was evaluated through a three‐step procedure by a series of binary criteria as to whether the site accommodates popular Web 2.0 applications. Pearson and Spearman correlations were conducted for the empirical analysis of data consisting of clickstreams gathered from an online panel coupled with expert scoring of web sites.

It was found that the size of a web site's visitor base is positively associated with the average number of page views per visitor. The average number of page views per visitor is in turn positively associated with the speed at which the visitors consume the site's content. Furthermore, a site's degree of Web 2.0‐ness is positively associated with the average number of page views per visitor and the speed of content consumption on the site.

First, the “double jeopardy” phenomenon of small brands found in the consumer package goods market is also observed for small sites in cyberspace in terms of audience metrics. Second, the accommodation of more Web 2.0 applications in a web site enhances the site's attractiveness so that its visitor base grows and its visitors will have a deeper relationship with the site.

This paper examines the Web 2.0 phenomenon through the Web 1.0 lens by exploring the relationships among web audience metrics and the degree of Web 2.0‐ness across web sites. It characterises the relationships among a web site's audience metrics and those between such metrics and the site's degree of Web 2.0‐ness. In addition this study fills an important gap in the literature and could serve as a stepping‐stone for further exploration of Web 2.0 issues from the market perspective.