Electronic word of mouth (eWOM) research – a comparative bibliometric analysis and future research insight

PurposeIn recent times, the growing use of electronic word of mouth (eWOM) has attracted consumers, organizations and marketers alike. The objective of this study is to summarize and compare the current mass of eWOM research published in leading hospitality and tourism journals with research published in the other fields of both business and management.Design/methodology/approachThis study uses multiple bibliometric analysis methods, including citation, co-citation, keyword and co-word analysis. It compares various assessments of eWOM research published in 399 selected business publications and 398 selected hospitality/tourism publications (ABDC A and above and ABS 3 and above) between 2003 and 2021.FindingsThe co-citation analysis identified three thematic areas under each of the domains, i.e. in the hospitality/tourism field, the three themes included eWOM and behavior; eWOM and social media; and eWOM as a marketing tool. Similarly, under the business field (encompasses remaining business and management subdisciplines), the three themes are eWOM and sales, eWOM quality and attributes; and eWOM, information and consumer. Additionally, the word and co-word analysis mapped the comparative evolution of research in these two fields. The study advocates more research focusing on less researched platforms using diverse data, recommender systems adoption and application of eWOM in the business to business (B2B) context.Research limitations/implicationsThis study summarizes the overall theoretical and conceptual structure of eWOM research in both business and hospitality/tourism fields; based upon which, several recommendations for future research are proposed.Originality/valueBy comparing the developments in the specialized hospitality/tourism sector with broader management literature using multiple, complementary techniques, this study brings out important insights for hospitality/tourism researchers.

Addressing Word Recognition Difficulties of Adolescents With Dyslexia

This chapter provides a comprehensive overview of evidence-based word analysis approaches for promoting accurate and fluent reading of complex words by adolescents with a specific reading disability (i.e., dyslexia). First, research has been reviewed to pinpoint the characteristics and causes of dyslexia as a specific learning disability. Specifically, two theories of dyslexia, the phonological theory of dyslexia and the magnocellular theory of dyslexia, have been discussed to ascertain the causal attributes of phonological awareness deficits and auditory and visual sequencing deficits to word recognition difficulties of adolescents with dyslexia. Next, two theories of word recognition, particularly the dual-route model of word recognition and connectionist model of word recognition, have been discussed to clarify the mechanism underlying the manifestation of dyslexia and resultant difficulties with word recognition. Finally, evidence-based word analysis programs have been described as approaches for improving word reading ability of adolescents with dyslexia.

Research trends in Educational Technology

The researchers of this study selected five journals in the field of education and conducted a series of analyses regarding publications dating from 2010 to 2019 to investigate the research trends and characteristics in the field of Educational Technology. By using the analytic tool Content Analysis Toolkit for Academic Research (CATAR), the researchers in this study conducted bibliometric analysis and breakdown analyses to summarize major contributing countries, educational institutions, most productive authors, and most cited papers; moreover, they used co-word analysis to reveal the representative items within each cluster. The findings in this study can provide implications and references for educators and researchers in the field of Educational Technology when selecting variables for their studies and technologies for their students.

Social Network Analysis on Tourists’ Perceived Image of Tropical Forest Park: Implications for Niche Tourism

Tourists’ perceived image is the core of destination marketing. As an important niche tourist destination, the analysis of tourists’ perceived image of tropical forest parks has great value. This study takes the Yalong Bay Tropical Paradise Forest Park as a case site and collects a total of 1,44,022 words from online travel reviews on Ctrip.com via the Python web crawler technology. Firstly, through high-frequency word analysis, we identified 77 core elements and a total of five image themes, which are attraction image, emotional image, service facility image, crowd image, and activity image. Secondly, building on Net Draw analysis, a network structure diagram of the tourist’ perceived image of the Yalong Bay Tropical Paradise Forest Park is constructed. Finally, the overall network and individual network of tourists’ perceived image are analyzed. The results indicate that low overall network density is in possession of core and periphery. Guojianglong Cable Bridge, battery car, and glass path enjoy both high degree centrality and betweenness centrality. They also show significant advantages of structural holes. Therefore, they are on the top of the network. The academic and practical value of tourism image projection and development in tropical forest park is discussed.

Mapping knowledge structure of artificial intelligence research in Bangladesh based on co-word analysis

Purpose: This article aims to map the knowledge structure of artificial intelligence (AI) in Bangladesh through detecting the interdisciplinarity and topic hotspots in the light of co-word analysis. Methodology: This study adopted bibliometric analysis of publications collected from the Web of Science (WoS) database. The WoS database was searched and 1557 publications were found. 1359 papers were selected for final analysis after eliminating duplicates. Co-occurrence words matrix, keyword clusters, hot topics were mapped using co-word analysis. The results were mapped, clustered and presented by VOSviewer.Results: The result showed a rapidly increasing publication trajectory with 12 sub-domain cluster under the AI knowledge domain in Bangladesh. It also identified that AI, machine learning, classification, neural network, deep learning, artificial neural network, convolutional neural network, support vector machine and data mining are hot topics during the period of studied time. However, the findings also suggest that many research areas in the research domain of AI of Bangladesh is still nascent.Limitation: VOSviewer often avoid having overlapping terms when multiple terms are positioned very close to each other. So, the overlapping terms remain invisible sometimes.Practical implications: This study may have potential usefulness in uncovering the AI research fields’ intellectual structure within a discipline and also to anticipate future innovation pathways of AI field in Bangladesh.Originality: Bibliometric methods to explore the research trend and growth of AI research field as a ‘knowledge base’ in Bangladesh is one of the first attempts.

MAPPING KNOWLEDGE MANAGEMENT RESEARCH: A BIBLIOMETRIC OVERVIEW

In recent years, knowledge management (KM) has consistently attained considerably growing research attention. Consequently, several literature reviews have been performed addressing different topic areas of KM. This paper seeks to present a comprehensive bibliometric and network analysis on KM to understand its development from the perspective of academic communities. Subsequently, it seeks to identify the structure of associations between prior and current themes, predict emerging trends and offer a longitudinal perspective on KM research. This study used web of science database and the initial sample was trimmed down by considering only the articles contributing to KM literature, and further 8,721 KM papers published in the last 30 years were systematically evaluated. The descriptive statistics and science mapping methods employing co-citation analysis were performed with VOSviewer software. In the descriptive analysis, we have analysed publication trends over time, geographical localization of the contributing institutions, journals, most prolific authors, top-performing institutions and most cited articles. Science mapping analysis is based on co-word analysis and co-citations analysis, namely articles’ co-citations and authors’ co-citations. The main findings of this paper will help researchers and academicians to develop knowledge in a specific sub-field by analysing the research outcomes of the papers included in the body of literature.