Building intellectual structure of knowledge sharing

Examining the research taxonomy of artificial intelligence, deep learning & machine learning in the financial sphere-a bibliometric analysis

This paper surveys the extant literature on machine learning, artificial intelligence, and deep learning mechanisms within the financial sphere using bibliometric methods. We considered the conceptual and social structure of publications in ML, AI, and DL in finance to better understand the research's status, development, and growth. The study finds an upsurge in publication trends within this research arena, with a bit of concentration around the financial domain. The institutional contributions from USA and China constitute much of the literature on applying ML and AI in finance. Our analysis identifies emerging research themes, with the most futuristic being ESG scoring using ML and AI. However, we find there is a lack of empirical academic research with a critical appraisal of these algorithmic-based advanced automated financial technologies. There are severe pitfalls in the prediction process using ML and AI due to algorithmic biases, mostly in the areas of insurance, credit scoring and mortgages. Thus, this study indicates the next evolution of ML and DL archetypes in the economic sphere and the need for a strategic turnaround in academics regarding these forces of disruption and innovation that are shaping the future of finance.

Virtual Reality Aided Therapy towards Health 4.0: A Two-Decade Bibliometric Analysis

Health 4.0 aligns with Industry 4.0 and encourages the application of the latest technologies to healthcare. Virtual reality (VR) is a potentially significant component of the Health 4.0 vision. Though VR in health care is a popular topic, there is little knowledge of VR-aided therapy from a macro perspective. Therefore, this paper was aimed to explore the research of VR in aiding therapy, thus providing a potential guideline for futures application of therapeutic VR in healthcare towards Health 4.0. A mixed research method was adopted for this research, which comprised the use of a bibliometric analysis (a quantitative method) to conduct a macro overview of VR-aided therapy, the identification of significant research structures and topics, and a qualitative review of the literature to reveal deeper insights. Four major research areas of VR-aided therapy were identified and investigated, i.e., post-traumatic stress disorder (PTSD), anxiety and fear related disorder (A&F), diseases of the nervous system (DNS), and pain management, including related medical conditions, therapies, methods, and outcomes. This study is the first to use VOSviewer, a commonly used software tool for constructing and visualizing bibliometric networks and developed by Center for Science and Technology Studies, Leiden University, the Netherlands, to conduct bibliometric analyses on VR-aided therapy from the perspective of Web of Science core collection (WoSc), which objectively and visually shows research structures and topics, therefore offering instructive insights for health care stakeholders (particularly researchers and service providers) such as including integrating more innovative therapies, emphasizing psychological benefits, using game elements, and introducing design research. The results of this paper facilitate with achieving the vision of Health 4.0 and illustrating a two-decade (2000 to year 2020) map of pre-life of the Health Metaverse.

Influence of national culture on knowledge management process: literature review and research agenda

Purpose

The purpose of this study is to explore, understand and investigate the relationship between national culture and knowledge management (KM) process.

Design/methodology/approach

This study is based on systematically and objectively capturing the contents of extant research papers published by researchers in this area by using the literature review methodology.

Findings

The study demonstrates significant relationship between national culture and KM process. Further, it also provides directions for future research.

Practical implications

The study will help top management to understand and appreciate the impact of national culture on KM process in organization, where people from different nations are working together. The management may apply appropriate organizational interventions to manage people of different national cultures in effective manner and effective utilization of knowledge of the organization through KM process. This paper will be considered as a quick reference and resource for anyone interested in this area.

Originality/value

This study is a comprehensive literature review of influence of national culture on KM process. Further, it also sets the research agenda for future researchers.

An Extensive Knowledge Mapping Review of Measurement and Validity in Language Assessment and SLA Research

This study set out to investigate intellectual domains as well as the use of measurement and validation methods in language assessment research and second language acquisition (SLA) published in English in peer-reviewed journals. Using Scopus, we created two datasets: (i) a dataset of core journals consisting of 1,561 articles published in four language assessment journals, and (ii) a dataset of general journals consisting of 3,175 articles on language assessment published in the top journals of SLA and applied linguistics. We applied document co-citation analysis to detect thematically distinct research clusters. Next, we coded citing papers in each cluster based on an analytical framework for measurement and validation. We found that the focus of the core journals was more exclusively on reading and listening comprehension assessment (primary), facets of speaking and writing performance such as raters and validation (secondary), as well as feedback, corpus linguistics, and washback (tertiary). By contrast, the primary focus of assessment research in the general journals was on vocabulary, oral proficiency, essay writing, grammar, and reading. The secondary focus was on affective schemata, awareness, memory, language proficiency, explicit vs. implicit language knowledge, language or semantic awareness, and semantic complexity. With the exception of language proficiency, this second area of focus was absent in the core journals. It was further found that the majority of citing publications in the two datasets did not carry out inference-based validation on their instruments before using them. More research is needed to determine what motivates authors to select and investigate a topic, how thoroughly they cite past research, and what internal (within a field) and external (between fields) factors lead to the sustainability of a Research Topic in language assessment.