A Consumer-Centric Framework for Measuring Product Obsolescence Using User-Generated Content and Large Language Models: Evidence From IoT Devices

Research output: Contribution to journalJournal Articlepeer-review

Abstract

Identifying product obsolescence factors is essential for guiding sustainable design and extending product longevity. Unlike prior studies, this research leverages online consumer reviews to explore product obsolescence factors. First, ChatGPT-4o, an advanced pretrained large language model, is utilized to identify these factors. User-generated content (UGC) time series-based product obsolescence indexes are then defined to quantify each factor's impact, offering a UGC-based complement to earlier methods that depended on expert judgment, supplier input, or survey data. By leveraging real-time customer insights, this approach aligns with Industry 4.0 principles, offering a UGC-based method that can support engineering managers to proactively address product obsolescence. It integrates factors' relative importance, determined through frequency–analytic hierarchy process (Freq-AHP), with their severity impact on consumers, assessed using the robustly optimized bidirectional encoder representations from transformers approach. This is further supported by a robustness check, where small perturbations were applied to sentiment intensities and all indices recalculated, confirming the aggregated obsolescence index remained stable across all product categories. This study focuses on consumer Internet of Things (IoT) devices, an area underexplored in existing literature, analyzing 47 695 online consumer reviews across nine product categories and selecting 4771 online obsolescence-related reviews for detailed analysis. Findings reveal 19 key factors and demonstrate a fundamental shift in obsolescence, indicating that product obsolescence of consumer IoT devices is increasingly driven by adaptability, interoperability, and digital resilience rather than physical durability. These insights demonstrate the potential of the proposed approach to inform product obsolescence mitigation strategies and guide more resilient, user-centered design in IoT ecosystems.

Original languageEnglish
Pages (from-to)448-466
Number of pages19
JournalIEEE Transactions on Engineering Management
Volume73
DOIs
Publication statusPublished - 2026

!!!Keywords

  • Internet-of-Things (IoT)
  • large language models (LLMS)
  • online consumer review
  • product obsolescence
  • user-generated content (UGC)

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