Septhia Charenda Putri, Ali Ibrahim, Yadi Utama, Endang Lestari Ruskan, Fathoni Fathoni

Evaluating Pinterest User Experience and Usability Using AttrakDiff and PLS-SEM

Introduction

Evaluating pinterest user experience and usability using attrakdiff and pls-sem. Evaluate Pinterest UX & usability with AttrakDiff and PLS-SEM. This research shows functional usability is key to attractiveness, supported by hedonic qualities on visual platforms.

Abstract

The rapid development of visual platforms such as Pinterest necessitates a comprehensive understanding of how functional and emotional aspects jointly influence users’ perception and engagement. This research addresses the gap in user experience (UX) evaluation of visually rich applications by examining the effects of Pragmatic Quality, Hedonic Quality-Stimulation, and Hedonic Quality Identity on the perceived Attractiveness of the Pinterest application. A quantitative approach was employed using the 28-item AttrakDiff instrument, based on data collected from a final sample of 524 valid respondents, predominantly aged 18–25 years, and using Pinterest several times a week. The data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) with the aid of SmartPLS to examine the relationships among latent variables. The findings demonstrate that the structural model exhibits a high level of explanatory capability, with an R² value of 0.684. With all three UX dimensions exerting positive and statistically significant effects on Attractiveness. PQ shows the strongest influence (path coefficient = 0.457), followed by HQS (0.391) and HQI (0.112). These findings confirm that functional usability remains the primary driver of attractiveness on Pinterest, while hedonic qualities play a complementary role in enhancing user experience. Practically, this research suggests that designers and developers of visual platforms should prioritize efficient functionality while maintaining stimulating and identity-supporting elements to improve overall user appeal.

Review

This paper presents a well-structured investigation into the user experience and usability of Pinterest, a prominent visual platform. Addressing a notable gap in the literature regarding UX evaluation in visually rich applications, the research adeptly employs the AttrakDiff instrument and PLS-SEM to dissect the influence of Pragmatic Quality, Hedonic Quality-Stimulation, and Hedonic Quality-Identity on perceived Attractiveness. The study's clear objective, robust methodology, and significant findings contribute valuable insights into the interplay of functional and emotional aspects that shape user perception and engagement, offering a foundational understanding for future UX research and design. A key strength of this study lies in its rigorous methodological application. The utilization of the validated 28-item AttrakDiff instrument provides a comprehensive and standardized framework for measuring UX dimensions, which is particularly suitable for a complex platform like Pinterest. The substantial sample size of 524 valid respondents, carefully targeted within the 18-25 age group and frequent users, enhances the statistical power and external validity of the findings for this critical demographic. Furthermore, the high explanatory capability of the structural model (R² = 0.684) and the statistically significant positive effects of all three UX dimensions on Attractiveness, with Pragmatic Quality exerting the strongest influence, offer compelling empirical evidence that designers should prioritize efficient functionality alongside stimulating and identity-supporting elements. While commendably thorough, the study’s focus on a predominantly young adult demographic (18–25 years) suggests a potential area for future exploration. Investigating how UX perceptions and the relative importance of pragmatic versus hedonic qualities might vary across a wider age spectrum could yield richer, more nuanced insights. Additionally, while "Attractiveness" is a critical outcome, expanding the model to incorporate other user behavioral metrics such as continued usage intention, word-of-mouth, or content creation could provide a more comprehensive understanding of long-term engagement and platform success. Future research might also consider a mixed-methods approach to complement these quantitative findings with qualitative data, offering deeper contextual understanding into the 'why' behind user preferences.

Full Text

Comments

You need to be logged in to post a comment.