Data mining of the declining US fashion industry: macroenvironmental shifts in the new economic reality
Hyojung Kim
Abstract
Purpose Drawing on the literature on corporate crises and failures, this study aims to examine how macroeconomic shifts impacted the U.S. fashion industry from 2008 to 2023. Design/methodology/approach This study employs data mining techniques to analyze 15,873 news articles, exploring media portrayals of fashion companies during major macroeconomic events, including the 2008 global financial crisis, the COVID-19 pandemic and recent geopolitical disruptions. The dynamic topic modeling approach identifies 20 key topics categorized into five themes: profit optimization in financial distress management, digital transformation, abrupt socioeconomic strain, leadership-driven reforms and the emergence of lifestyle stores. Findings The results reveal varied industry responses across three distinct subperiods. From 2008 to 2013, fashion companies implemented sustainability initiatives amid declining sales. Between 2014 and 2019, firms responded to the economic recovery by pursuing strategic adaptations, including mergers and store downsizing. The latest phase (2020–2023) was characterized by inflationary pressures, supply chain disruptions and leadership transitions exacerbated by the pandemic and geopolitical tensions. Originality/value These insights highlight the necessity of evaluating the financial viability of U.S. fashion companies and the significance of governmental support systems in an industry experiencing extended economic declines.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.