The Knowledge Mapping of Mobile Commerce Research: A Visual Analysis Based on I-Model

Shan Du · Hua Li

35 citations0/0 files storedSustainability

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

scientometrics and bibliometrics research Technology Adoption and User Behaviour E-commerce and Technology Innovations

Abstract

With the advance of 5G communication technologies and Internet+ strategy, mobile commerce has experienced rapid growth and needs urgent attention from researchers. It is the aim of this article to analyze the literature on mobile commerce to address the following question: With the wide application of artificial intelligence and big data, what are the latest technology, models and problems in the background of the new era that researchers and practitioners need to understand in order to grasp the research frontier in this field quickly? Therefore, to achieve these objectives, this paper reviews 1130 m-commerce articles with 25,502 associated references from the SCI-EXPANDED, SSCI, CPCI-S, CPCI-SSH database and develops a framework of m-commerce value by analyzing the most influential authors, institutions, countries, journals and keywords in m-commerce. We apply three types of knowledge mapping to our study—cluster view, timezone view and timeline view. Frequency statistics, clustering coefficient as well as centrality calculation are employed to analyze by CiteSpace. We use the strength of citation bursts to analyze keywords and put result into the I-Modelwhich provide an important framework for classifying m-commerce activities and theories. In this study, we explore the knowledge structure, development and the future trend of mobile commerce for researchers. We identify the main technology and models to improve customer satisfaction and adoption behavior in the background of the new era which provide decision support for practitioners. Compared with the existing literature reviews of mobile commerce, we make a set of knowledge maps to show the future trend of mobile commerce and analyze visual results based on I-model. It is the first study to present the major clusters to reveal their associated intellectual bases and research fronts.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 35 citations exist upstream.

References

2003Trust and TAM in Online Shopping: An Integrated Model1 2005CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature 1986Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control 2000Measuring the Customer Experience in Online Environments: A Structural Modeling Approach 2004What drives mobile commerce?2003Why do people play on-line games? An extended TAM with social influences and flow experience 2016Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology 2009An empirical examination of factors influencing the intention to use mobile payment

Cited by

2021Application of Revised Importance–Performance Analysis to Investigate Critical Service Quality of Hotel Online Booking 2022Mapping the evolution of e-commerce research through co-word analysis: 2001–2020 2022Impact of Perceived Influence, Virtual Interactivity on Consumer Purchase Intentions Through the Path of Brand Image and Brand Expected Value 2023Deciphering the resistance behaviours towards mobile commerce applications: A Mobile Commerce Applications Resistance Theory (MOCART)

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.