Linkages among automation, job displacement and reshoring: evidence from the Bangladeshi apparel industry

Abstract

Purpose This paper aims to evaluate the impact of automation on job displacement and reshoring in the apparel industry. It also compares with predictions on the same subject matter by the existing literature and, thus, provides future research agenda for further studies. Design/methodology/approach Primary data were collected through 27 semi-structured in-depth interviews. The grounded theory was used for thematic and network analyzes, which traced the drivers and barriers, as well as the impact of automation and reshoring. Findings Initially, automation decreases human interactions in any specific production section. However, it increases productivity, quality and cost advantages, which invoke growth and further employment in clothing firms. The employment of unskilled workers decreases in the long run when automation is well adopted in the system. Automation does not stimulate reshoring but may support relocation initiatives of production sites around the centers of global value chains (GVCs). This GVC-based relocation may create job displacement in apparel manufacturing nations in Asia while bringing employment opportunities to Sub-Saharan African countries, Europe and North America. Originality/value Little empirical research has been conducted on the impact of automation on the apparel industry. This study predicts that human interventions will dominate the sewing of fashionable and sophisticated apparel products while automation may replace many human workers for basic garment items in the foreseeable future.

Human resource development 4.0 (HRD 4.0) in the apparel industry of Bangladesh: a theoretical framework and future research directions

“…The involvement of 4IR is bringing some unexpected changes in the organizations especially in context to the digitalization of human resource development 4.0 (HRD 4.0), and its allied connection with other functionalities in the organization (Alexy et al, 2018;Ahmed et al, 2019;Bag et al, 2021). The increasing technology adoption causes anxiety and job insecurity in many sectors including the readymade garments (RMG) industry (Hoque et al, 2021b). Recently, the world economic forum (WEF) mentioned that globally one-third of the total jobs are likely to be disrupted due to automation by 2030 (Fleming, 2020).…”

“…The fear of technologyinduced job insecurity and unemployment have penetrated the policy response in both advanced and developing countries (Maloney and Molina, 2019;Valentino et al, 2020). Though, the labor market division is documented in some advanced countries (Kucera and Barcia de Mattos, 2019); however, there exists very little evidence about the impact of automation on different forms of displacement in developing countries (Park-Poaps et al, 2020;Hoque et al, 2021b).…”

“…Although the RMG supply chain is dispersed globally, most of the apparel production shifted to the low wages in Asian countries (Hoque et al, 2021b). A study conducted in early by ILO (2019a) shows that some Asian countries are probable to lose more than 80% of the apparel manufacturing jobs by 2041 due to the growing adoption of automation.…”

“…Given the above opinions, developing a set of skills is the only way to reach the target instead of allowing them to become the victim of automation (Park-Poaps et al, 2020). Automation has become the primary demand to reduce cost, expedite production volume to survive the market competition (Hoque et al, 2021b). The breakthrough of 4IR has badly affected the job market especially low skilled, semi-skilled or unskilled workers (Hoque et al, 2021b).…”

“…Automation has become the primary demand to reduce cost, expedite production volume to survive the market competition (Hoque et al, 2021b). The breakthrough of 4IR has badly affected the job market especially low skilled, semi-skilled or unskilled workers (Hoque et al, 2021b). According to an ILO report (ILO, 2019b), around 60% of the RMG workers (2.7 million) in Bangladesh are at risk of losing their job by 2041 due to technology adoption (ILO, 2019b).…”