独创性
引用
中心性
系统回顾
计算机科学
数据科学
社会网络分析
模块化(生物学)
网络分析
知识管理
定性研究
社会学
万维网
工程类
社会化媒体
社会科学
组合数学
生物
电气工程
法学
遗传学
数学
梅德林
政治学
作者
Syed Asif Raza,Srikrishna Madhumohan Govindaluri
出处
期刊:Benchmarking: An International Journal
[Emerald (MCB UP)]
日期:2021-02-23
卷期号:28 (9): 2605-2635
被引量:22
标识
DOI:10.1108/bij-10-2020-0547
摘要
Purpose The purpose of this paper is to conduct a structured literature review using advanced bibliometric tools to understand the existing knowledge base, understand the trends in omni-channel (OC) research and identify emerging research topics. Design/methodology/approach More than 500 articles selected through a keyword combination search from reputed databases of peer-reviewed academic sources from period 2009–19 are analyzed for the purposes of this study. The study first presents an exploratory analysis to determine influential authors, sources and regions, among other key aspects. Second, several network analyses including co-citation and dynamic co-citation network analyses are conducted to identify themes. These allow identifying research clusters and emerging research topics algorithmically. Both centrality and modularity-based clustering are employed. A content analysis of the most influential groups within OC literature for each cluster is included. Findings The findings of this paper make unique contributions by using advanced tools from network analysis along with the standard bibliometric analysis tools to explore the current status of OC research, identify existing themes and the guidance for potential areas of future research interest in OC. Practical implications This research provides a comprehensive view of the range of topics of importance that have been discussed in the literature of OC management. These research trends can serve as a quick guide to researchers and practitioners to improve decision making and also develop strategies. Originality/value The paper employs advanced tools for the first time to review the literature of OC retailing. The sophisticated tools include co-citation and dynamic co-citation network analysis.
科研通智能强力驱动
Strongly Powered by AbleSci AI