The Impact of Social Media Influencers Raffi Ahmad and Nagita Slavina on Tourism Visit Intentions across Millennials and Zoomers Using a Hierarchical Likelihood Structural Equation Model

Rezzy Eko Caraka, Maengseok Noh, Youngjo Lee, Toni Toharudin, Yusra, Avia Enggar Tyasti, Achlan Fahlevi Royanow, Dimas Purnama Dewata, Prana Ugiana Gio, Mohammad Basyuni and Bens Pardamean
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Rezzy Eko Caraka: Lab Hierarchical Likelihood, Department of Statistics, College of Natural Science, Seoul National University, Seoul 08826, Korea
Maengseok Noh: Department of Statistics, Pukyong National University, Nam-gu, Busan 608-737, Korea
Youngjo Lee: Lab Hierarchical Likelihood, Department of Statistics, College of Natural Science, Seoul National University, Seoul 08826, Korea
Toni Toharudin: Department of Statistics, Padjadjaran University, Bandung 45363, Indonesia
Yusra: Sekolah Tinggi Ilmu Ekonomi (STIE) Sabang, Banda Aceh 24415, Indonesia
Avia Enggar Tyasti: International Trade of ASEAN and RRT Region, Polytechnic of APP, DKI Jakarta 12630, Indonesia
Achlan Fahlevi Royanow: Tourism Polytechnic of Lombok, Lombok 83521, Indonesia
Dimas Purnama Dewata: Tourism Polytechnic of Lombok, Lombok 83521, Indonesia
Prana Ugiana Gio: Department of Mathematics, Universitas Sumatera Utara, Medan 20155, Indonesia
Mohammad Basyuni: Department of Forestry, Faculty of Forestry, Universitas Sumatera Utara, Medan 20155, Indonesia
Bens Pardamean: Computer Science Department, Bina Nusantara University, DKI Jakarta 11480, Indonesia

Sustainability, 2022, vol. 14, issue 1, 1-28

Abstract: Background: In this paper, we examine how social media influencers can influence visit intention, especially in the case of Raffi Ahmad and Nagita Slavina, a top influencer who by 2 September 2021 had reached 21.3 M subscribers on YouTube and 54.9 m followers on Instagram with an engagement rate of 0.42%. The focus of this study is Generation Y or Millennials (born 1981–1996) and Generation Z (born 1997–2012). Design/methodology/approach: Snowball sampling was performed to arrive at a representative group of Millennials. Data analysis was performed using hierarchical likelihood via structural equation modeling. Findings: The study results are helpful for a comprehensive understanding of factors affecting visit intention. Effects of the study results summary, tourists from Generations Y and Z are thriving within the internet of things and the digital age, an era in which information can be accessed via various forms of technology across multiple platforms. Practical implications: We discuss and identify the relative importance of each factor through the use of logistics with variational approximation and structural equation models using hierarchical likelihood. Originality: The technique we use is an integrated and extended version of the structural equation model with hierarchical likelihood estimation and features selection using logistics variational approximation.

Keywords: social media influencer; tourism; structural equation modeling; visit intention; h-likelihood (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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