Navigating the uncertainty path of virtual influencers: Empirical evidence through a cultural lens
Technological Forecasting and Social Change, ISSN: 0040-1625, Vol: 210, Page: 123896
2025
- 4Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures4
- Readers4
Article Description
The rise of artificial intelligence is changing the way companies interact with consumers. In the social media context, this has led to the spread of virtual influencers (i.e., influencers that may look human but are not). These new kinds of influencers are gaining popularity on social media, sponsoring renowned brands, and attracting new consumer segments. Despite this, it is still unclear how consumers with different cultural backgrounds may react to them. Based on Hofstede's cultural dimensions theory, we developed two studies showing how collectivistic countries with low uncertainty avoidance are more inclined to exhibit positive attitudes toward these new influencer types. Based on these findings, we provide a diagnostic tool that may orientate companies on how to develop successful collaboration with virtual influencers by limiting possible social concerns.
Bibliographic Details
Elsevier BV
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know