Questionnaire & SEM PLS Results - Laugh, Engage, and Remember through Online Humor Advertising on Social Media

Research Abstract (Contextual Reference) This dataset originates from a quantitative cross-sectional study investigating how humorous advertising on social media influences brand recognition among Generation Z consumers in Indonesia.Data were collected from 297 respondents aged 19–27 years, all of whom are active users of Instagram, TikTok, and YouTube and have previously been exposed to humorous advertisements. The research examines causal pathways among: Humorous Advertising (HA) – independent variable Positive Electronic Word-of-Mouth (E-WOM) – mediating variable Brand Recognition (BR) – dependent variable Statistical analysis was conducted using Structural Equation Modeling (SEM-PLS) through SmartPLS 4 to evaluate the outer loadings, reliability, validity, and structural relationships among constructs. Variables and Analytical Focus Construct Description Example Indicators Humorous Advertising (HA) Measures perception of humor quality, attractiveness, and message clarity HA1–HA8 Positive E-WOM (EWOM) Captures audience engagement, message credibility, and information sharing IQ1–IQ6, IC1–IC6 Brand Recognition (BR) Assesses spontaneous and aided recall, brand identification, and awareness BI1–BI5, AA1–AA3, UA1–UA2 Dataset Overview Attribute Description Total Respondents 297 Sampling Method Non-probability purposive sampling Data Type Primary data, cross-sectional survey Instrument Type Structured questionnaire (Likert scale 1–5) Analysis Software SmartPLS 4 Output Metrics Outer Loadings, Reliability & Validity Indices, R² Values, Path Coefficients

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-04
DOI
https://doi.org/10.5281/zenodo.17264940
Primary Topic
Respiratory Support and Mechanisms
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Questionnaire & SEM PLS Results - Laugh, Engage, and Remember through Online Humor Advertising on Social Media

Zenodo (CERN European Organization for Nuclear Research)
Respiratory Support and Mechanisms
article

Questionnaire & SEM PLS Results - Laugh, Engage, and Remember through Online Humor Advertising on Social Media

article en

Abstract

Research Abstract (Contextual Reference) This dataset originates from a quantitative cross-sectional study investigating how humorous advertising on social media influences brand recognition among Generation Z consumers in Indonesia.Data were collected from 297 respondents aged 19–27 years, all of whom are active users of Instagram, TikTok, and YouTube and have previously been exposed to humorous advertisements. The research examines causal pathways among: Humorous Advertising (HA) – independent variable Positive Electronic Word-of-Mouth (E-WOM) – mediating variable Brand Recognition (BR) – dependent variable Statistical analysis was conducted using Structural Equation Modeling (SEM-PLS) through SmartPLS 4 to evaluate the outer loadings, reliability, validity, and structural relationships among constructs. Variables and Analytical Focus Construct Description Example Indicators Humorous Advertising (HA) Measures perception of humor quality, attractiveness, and message clarity HA1–HA8 Positive E-WOM (EWOM) Captures audience engagement, message credibility, and information sharing IQ1–IQ6, IC1–IC6 Brand Recognition (BR) Assesses spontaneous and aided recall, brand identification, and awareness BI1–BI5, AA1–AA3, UA1–UA2 Dataset Overview Attribute Description Total Respondents 297 Sampling Method Non-probability purposive sampling Data Type Primary data, cross-sectional survey Instrument Type Structured questionnaire (Likert scale 1–5) Analysis Software SmartPLS 4 Output Metrics Outer Loadings, Reliability & Validity Indices, R² Values, Path Coefficients

Zenodo (CERN European Organization for Nuclear Research)
Binus University (ID)
Openalex Percentile: Top 34%
Respiratory Support and Mechanisms
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.