Claim Missing Document
Check
Articles

Found 2 Documents
Search

AI Framework for Synthesizing Qualitative User Feedback A Literature Review Santa Lusianna Sitorus; Ratih Komala Dewi; Vika Febrian; Muhammad Faris Ariq; Ramiro Santiago Ikhsan
CORISINTA Vol 3 No 1 (2026): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/r1yewe47

Abstract

The increasing reliance on user-centered design in digital product development has intensified the need for systematic approaches to transforming qualitative user feedback into actionable insights for UX and UI decision-making. Although qualitative feedback provides rich understanding of user motivations, frustrations, and contextual behaviors, product teams often face challenges such as data ambiguity, interpretive bias, information overload, and weak alignment between research outcomes and product strategy. This literature review aims to synthesize existing academic research and industry practices to propose a structured framework that bridges qualitative analysis and technology-driven product decisions. Using a qualitative research design based on framework analysis, this study reviews established methods including user interviews, usability testing, open-ended surveys, thematic analysis, and affinity-based synthesis. These approaches are integrated into a four-step framework consisting of feedback coding, theme identification, alignment with product objectives, and formulation of actionable insights. The findings of this review suggest that applying a structured synthesis process enhances analytical clarity, improves traceability between user feedback and design actions, and supports more consistent prioritization in UX/UI practices. Illustrative applications drawn from prior studies demonstrate how the framework can translate qualitative insights into concrete design recommendations without relying on empirical experimentation. This study concludes that qualitative user feedback delivers meaningful value only when processed through a systematic synthesis mechanism that connects user narratives with strategic and operational product decisions, providing a conceptual foundation for data-driven and AI-supported UX/UI design environments.
Enhancing Digital Fashionpreneurship Through Innovation Capability and Market Sensing Santa Lusianna Sitorus; Asep Hermawan; Anton Wachidin Widjaja; Margaretha Pink Berlianto
Aptisi Transactions On Technopreneurship (ATT) Vol 8 No 2 (2026): July
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v8i2.721

Abstract

This study aims to examine the influence of intellectual capital and Market Sensing Capability (MSC) on business performance, with innovation capability serving as a mediating variable. This research examines fashion brand enterprises that function online in Indonesia. The conceptual framework employed is a novel model derived from previous research, highlighting the role of intellectual capital and MSC in enhancing business performance via the strategic mediation of innovation capability. This study utilizes a quantitative methodology employing the PLS-SEM technique to examine the causal links among latent constructs. Data were collected by the dissemination of closed questionnaires to online fashion brand enterprises represented by owners, directors, or managers. Through purposive sampling, 124 respondents were acquired and deemed valid for analysis. This study has seven hypotheses to evaluate the direct and indirect impacts of the constructs on organizational performance. The results affirm that innovation capability significantly mediates the relationship between intellectual capital and firm performance, as well as between MSC and firm performance. This study enhances the academic discourse on organizational capabilities and provides pragmatic insights for the management of strategic resources within the digital marketplace, specifically in the fashion sector.