E-Commerce Research Trend Forecasting: A Study of Bibliometric Methodology

姜國輝,; 蔡緒浩,; Tsai, Hsu-Hao; Chiang, Johannes K.

doi:10.4156/jdcta.vol5.issue1.12

Cited by 13 publications

(1 citation statement)

References 11 publications

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“…5. Moreover, some researchers used bibliometric methodologies to analyze the trends and forecasts in different domains, such as e-commerce, supply chain management and knowledge management (Tsai, 2011;Tsai & Chi, 2011;Tsai & Chiang, 2011). Using a bibliometric approach, (Tsai & Yang, 2010) analyzed data mining and CRM research trends from 1989 to 2009 by locating headings "data mining" and "customer relationship management" or "CRM" in topics in the SSCI database.…”

Section: The Hierarchical Distributed Dynamicmentioning

confidence: 99%

Research Trends with Cross Tabulation Search Engine

Yin

Hirokawa

Yau

et al. 2013

International Journal of Distance Education Technologies

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To help researchers in building a knowledge foundation of their research fields which could be a time-consuming process, the authors have developed a Cross Tabulation Search Engine (CTSE). Its purpose is to assist researchers in 1) conducting research surveys, 2) efficiently and effectively retrieving information (such as important researchers, research groups, keywords), and also 3) providing analytical information relating to past and current research trends in a particular field. Their CTSE system employs data-processing technologies and emphasizes the use of a “Learn by Searching” learning strategy to support students to analyze such research trends. To show the effectiveness of CTSE, a pilot experiment has been conducted, where participants were assigned to do research survey tasks and then answer a questionnaire regarding the effectiveness and usability of the system. The results showed that the system has been helpful to students in conducting research surveys, and the research trend transitions that our system presented were effective for producing research trend surveys. Moreover, the results showed that most students had favorable attitudes toward the usage and usability of the system, and those students were satisfied in gaining more know ledge in a particular research field in a short period.

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Section: The Hierarchical Distributed Dynamicmentioning

confidence: 99%

Research Trends with Cross Tabulation Search Engine

Yin

Hirokawa

Yau

et al. 2013

International Journal of Distance Education Technologies

View full text Add to dashboard Cite

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A “Milky Way Research Trend” System for Survey of Scientific Literature

Yin

Tabata

Hirokawa

2014

Lecture Notes in Computer Science

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Research trend survey is an essential preliminary step for any academic researches, but many beginning researchers have difficulty because they are still foreign to appropriate keywords in his/her research field. We constructed a support system for research trend surveys not only to accelerate the preliminary step but also to let students have a better grips of trend progresses and keyword transitions. Our system assumes a fair amount of data accumulation, for which we employed KAKEN database excerpts, but does not assume manual keyword registration or any other heuristic preprocesses: with an associative search module, it dynamically searches relevant words that are frequently used in the targeted academic field and gives users effective visualizations to understand trend transitions. Preliminary evaluations suggest that the trend transitions that our system presents are effective for trend surveys.

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Research trends analysis by comparing data mining and customer relationship management through bibliometric methodology

Tsai

2011

Scientometrics

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E-Commerce Research Trend Forecasting: A Study of Bibliometric Methodology

Cited by 13 publications

References 11 publications

Research Trends with Cross Tabulation Search Engine

Research Trends with Cross Tabulation Search Engine

A “Milky Way Research Trend” System for Survey of Scientific Literature

Research trends analysis by comparing data mining and customer relationship management through bibliometric methodology

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