The global apparel industry experienced a 30% rise in new job postings related to social responsibility in Q3 2022 compared with the previous quarter, according to GlobalData’s whitepaper on Social Responsibility in Apparel – Hiring Activity in Q3 2022. This compares to a 203% increase versus Q3 2021.

Notably, Retail Salespersons jobs accounted for a 29% share of the global apparel industry’s social responsibility-related total new job postings in Q3 2022, up 25% over the prior quarter.

Retail Salespersons drive social responsibility-related hiring activity

Retail Salespersons, with a share of 29%, emerged as the top social responsibility-related job roles within the apparel industry in Q3 2022, with new job postings rising by 25% quarter-on-quarter. Cashiers came in second with a share of 7% in Q3 2022, with new job postings rising by 112% over the previous quarter.

The other prominent social responsibility roles include Fast Food and Counter Workers with a 6% share in Q3 2022, First-Line Supervisors of Sales Workers with a 3% share of new job postings.

Top five companies in apparel industry accounted for 38% of hiring activity

The top companies, in terms of number of new job postings tracked by GlobalData, as of Q3 2022 were TESCO, Target, Walmart and Kohl's. Together they accounted for a combined share of 38% of all social responsibility-related active jobs in the apparel industry.

TESCO posted 18,276 social responsibility-related new jobs in Q3 2022, Target 9,557 jobs, Walmart 6,596 jobs, and Kohl's 4,274 jobs, according to GlobalData’s Job Analytics.

Hiring activity was driven by the US with a 57% share of total active job postings, Q3 2022

The largest share of social responsibility-related new job postings in the apparel industry in Q3 2022 was in the US with 57% followed by the UK (34%) and Sweden (3%). The share represented by the US was two percentage points higher than the 55% share it accounted for in Q2 2022.

GlobalData

GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData’s Jobs Analytics uses machine learning to uncover key insights from tracking daily job postings for thousands of companies globally. Proprietary analysis is used to group jobs into key thematic areas and granular sectors across the world’s largest industries. classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.