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Celebrity selection in social media ecosystems: a flexible and interactive framework

Shekhar Shukla (Information Management Area, S P Jain Institute of Management and Research, Mumbai, India)
Ashish Dubey (Marketing Area, IIM Lucknow, Lucknow, India)

Journal of Research in Interactive Marketing

ISSN: 2040-7122

Article publication date: 9 July 2021

Issue publication date: 10 May 2022

627

Abstract

Purpose

Quantitative objective studies on the problem of celebrity selection are lacking. Furthermore, existing research does not recognize the group decision-making nature and the possibility of customer involvement in celebrity or influencer selection for social media marketing. This study conceptualizes celebrity selection as a multi-attribute group decision-making problem while deriving the final ranking of celebrities/influencers using interactive and flexible criteria based on the value tradeoff approach. The article thus proposes and demonstrates a quantitative objective method of celebrity selection for a brand or campaign in an interactive manner incorporating customer's preferences as well.

Design/methodology/approach

Each decision-maker's preferences for celebrity selection criteria are objectively captured and converted into an overall group preference using a modified generalized fuzzy evaluation method (MGFEM). The final ranking of celebrities is then derived from an interactive and criteria-based value tradeoff approach using the flexible and interactive tradeoff method.

Findings

The approach gives a different ranking of celebrities for two campaigns based on group members' perceived importance of the selection criteria in different scenarios. This group includes decision-makers (DMs) from the brand, marketing communication agency and brand's customers. Further, each group member has an almost equal say in the decision-making based on fuzzy evaluation and an interactive and flexible value tradeoff approach to celebrity selection for receiving a rank order.

Research limitations/implications

The approach uses secondary data on celebrities and hypothetical scenarios. Comparison with other methods is difficult, as no other study proposes a multi-criteria group decision-making approach to celebrity selection especially in a social media context.

Practical implications

This approach can help DMs make more informed, objective and effective decisions on celebrity selection for their brands or campaigns. It recognizes that there are multiple stakeholders, including the end customers, each of whose views is objectively considered in the aspects of group decision-making through a fuzzy evaluation method. Further, this study provides a selection mechanism for a given context of endorsement by objectively and interactively encapsulating stakeholder preferences.

Originality/value

This robust and holistic approach to celebrity selection can help DMs objectively make consensual decisions with partial or complete information. This quantitative approach contributes to the literature on selection mechanisms of influencers, celebrities, social media opinion leaders etc. by providing a methodological aid that encompasses aspects of interactive group decision-making for a given context. Moreover, this method is useful to DMs and stakeholders in understanding and incorporating the effect of nature or context of the brand and the campaign type in the selection of a celebrity or an influencer.

Keywords

Acknowledgements

The authors want to thank the anonymous reviewers and the editorial team of the journal for their constructive feedback and suggestions that aided to shape and strengthen this research work. The authors also want to thank http://fitradeoff.org/ for providing their tool for FITradeoff based analysis.

Citation

Shukla, S. and Dubey, A. (2022), "Celebrity selection in social media ecosystems: a flexible and interactive framework", Journal of Research in Interactive Marketing, Vol. 16 No. 2, pp. 189-220. https://doi.org/10.1108/JRIM-04-2020-0074

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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