Validation of Literature-Derived Instagram Influencer Attributes for Smartphone Marketing: An Exploratory Factor Analysis among Teenagers in Rajkot, India

As Instagram influencer marketing has been growing in the promotion of smartphones, there is a lack of empirical studies validating the measurement of influencers' attributes in specific consumer contexts. The majority of studies have focused on the effect of the influencer attributes on consumer behaviour, while few studies have looked at the validity and reliability of the scales used in measuring the influencer. The aim of this study was thus, to validate the literature based attributes of the Instagram influencer for marketing the smartphones among teenagers in Rajkot, India. The data collection technique used was quantitative research using cross-sectional research design, with a questionnaire as the data collection tool and number of respondents 108 teenage Instagram users. The instrument for measurement was created by adapting the items from existing literature on influencer marketing. The dimensional structure of proposed attributes was analyzed by Exploratory Factor Analysis (EFA), the Kaiser–Meyer–Olkin (KMO) Measure of Sampling Adequacy, and Bartlett's Test of Sphericity were used to assess the reliability and suitability of the data. The Cronbach's alpha for the original 21 item measurement instrument was good, and was 0.888. After eliminating 5 weak performing items, the solution of 16 items obtained KMO value of 0.783 and the four factors extracted accounted for 76.90% of the total variance. These results offer exploratory evidence supporting the dimensional structure of Instagram influencer attributes in the case of smartphone marketing. The study adds to the existing body of knowledge on influencer marketing by presenting a context-specific and empirically validated framework to measure Instagram influencer attributes in smartphone marketing. The validated scale will be helpful for future academic studies and will give practitioners a tool to choose and assess Instagram influencers for their marketing strategies. The extracted dimensions can be structured criteria for initial influencer assessment and selection, but need to be further validated from a managerial decision making point of view regarding the effectiveness of these dimensions in marketing decision making from an operational point of view.

Authors

Institutions

Publication Details

Journal
Computer and decision making.
Published
2026-10-30
DOI
https://doi.org/10.1922/comdem.v3i6s.18821
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Validation of Literature-Derived Instagram Influencer Attributes for Smartphone Marketing: An Exploratory Factor Analysis among Teenagers in Rajkot, India

Vishal Khasgiwala, Rajeshwari B. Tapashetti, Sukanya Koti
Computer and decision making.
Digital Marketing and Social Media
article

Validation of Literature-Derived Instagram Influencer Attributes for Smartphone Marketing: An Exploratory Factor Analysis among Teenagers in Rajkot, India

Vishal Khasgiwala, Rajeshwari B. Tapashetti, Sukanya Koti
article en

Abstract

As Instagram influencer marketing has been growing in the promotion of smartphones, there is a lack of empirical studies validating the measurement of influencers' attributes in specific consumer contexts. The majority of studies have focused on the effect of the influencer attributes on consumer behaviour, while few studies have looked at the validity and reliability of the scales used in measuring the influencer. The aim of this study was thus, to validate the literature based attributes of the Instagram influencer for marketing the smartphones among teenagers in Rajkot, India. The data collection technique used was quantitative research using cross-sectional research design, with a questionnaire as the data collection tool and number of respondents 108 teenage Instagram users. The instrument for measurement was created by adapting the items from existing literature on influencer marketing. The dimensional structure of proposed attributes was analyzed by Exploratory Factor Analysis (EFA), the Kaiser–Meyer–Olkin (KMO) Measure of Sampling Adequacy, and Bartlett's Test of Sphericity were used to assess the reliability and suitability of the data. The Cronbach's alpha for the original 21 item measurement instrument was good, and was 0.888. After eliminating 5 weak performing items, the solution of 16 items obtained KMO value of 0.783 and the four factors extracted accounted for 76.90% of the total variance. These results offer exploratory evidence supporting the dimensional structure of Instagram influencer attributes in the case of smartphone marketing. The study adds to the existing body of knowledge on influencer marketing by presenting a context-specific and empirically validated framework to measure Instagram influencer attributes in smartphone marketing. The validated scale will be helpful for future academic studies and will give practitioners a tool to choose and assess Instagram influencers for their marketing strategies. The extracted dimensions can be structured criteria for initial influencer assessment and selection, but need to be further validated from a managerial decision making point of view regarding the effectiveness of these dimensions in marketing decision making from an operational point of view.

Computer and decision making.Vol. 3(6S)
Atmiya University (IN), Shri Vaishnav Vidyapeeth Vishwavidyalaya, Indore (IN)
Openalex Percentile: Top 5%
Digital Marketing and Social Media
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon