Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Customer engagement with tourism social media brands
2016557 citationsPaul Harrigan, Uwana Evers et al.profile →
Customer engagement and the relationship between involvement, engagement, self-brand connection and brand usage intent
2017374 citationsPaul Harrigan, Uwana Evers et al.Journal of Business Researchprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Uwana Evers's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Uwana Evers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Uwana Evers more than expected).
This network shows the impact of papers produced by Uwana Evers. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Uwana Evers. The network helps show where Uwana Evers may publish in the future.
Co-authorship network of co-authors of Uwana Evers
This figure shows the co-authorship network connecting the top 25 collaborators of Uwana Evers.
A scholar is included among the top collaborators of Uwana Evers based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Uwana Evers. Uwana Evers is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Harrigan, Paul, Timothy M. Daly, Kristof Coussement, et al.. (2020). Identifying influencers on social media. International Journal of Information Management. 56. 102246–102246.145 indexed citations
8.
Lee, Julie, et al.. (2019). What do we value?: How our values influence everyday behaviours. UWA Profiles and Research Repository (University of Western Australia).7 indexed citations
Harrigan, Paul, et al.. (2017). Customer engagement and the relationship between involvement, engagement, self-brand connection and brand usage intent. Journal of Business Research. 88. 388–396.374 indexed citations breakdown →
13.
Evers, Uwana, Paul Harrigan, & Timothy M. Daly. (2015). Consumer Brand Engagement with Tourism Organisations on Social Media. UWA Profiles and Research Repository (University of Western Australia). 1–7.1 indexed citations
14.
Evers, Uwana, Sandra C. Jones, Peter Caputi, & Don Iverson. (2013). Promoting Asthma Awareness to Older Adults. UWA Profiles and Research Repository (University of Western Australia). 4(2). 77–84.9 indexed citations
Evers, Uwana, Sandra C. Jones, Peter Caputi, & Don Iverson. (2013). Asthma in Older Adults. UWA Profiles and Research Repository (UWA). 4(4). 183–190.4 indexed citations
18.
Jones, Sandra C., et al.. (2012). Breathlessness is not a normal part of aging: Development and testing of asthma awareness messages for older Australians. Research Bank (Australian Catholic University). 110.1 indexed citations
Evers, Uwana, Sandra C. Jones, Peter Caputi, & Donald C. Iverson. (2011). Combining the health belief model and social marketing to develop a community-level campaign about asthma for older adults. Research Online (University of Wollongong). 117–125.1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.