Planned fashion obsolescence in the light of supply chain uncertainty

Title

Planned fashion obsolescence in the light of supply chain uncertainty

Creator

Philip R.S.; Anian A.M.; Raja A.S.M.

Description

Fast fashion has popularised the phenomenon of perceived obsolescence whereby customers try to stay in line with the current fashion trends in the market even though the apparel they own are in perfect condition. This has ultimately led the fashion industry to become the second largest polluter in the world. The primary objective of this research paper is to comprehend how the media manoeuvres customers to indulge in fast fashion and how that in turn leads to uncertainty in the supply chain. To understand this, a maximum variation sampling method was adopted which consisted of customers, supply chain partners and marketers. In order to draw a parallel between the variables researched in the past and the present day scenario, an interview schedule was employed. Through the variables selected with the help of Dedoose, a model was created to identify the hurdles faced by suppliers as well as the customer in the fast fashion cycle. The results found that the power to break the fast fashion phenomenon lay in the hands of the media as it is through them that customers' perception can be altered. The importance of artificial intelligence in SCM and the modern tools used in industry 4.0 have also been discussed. 2020 Allied Business Academies.

Source

Academy of Strategic Management Journal, Vol-19, No. 1, pp. 1-17.

Date

2020-01-01

Publisher

Allied Business Academies

Subject

Artificial intelligence; Circular economy; Fast fashion; Media; Supply Chain uncertainty

Coverage

Philip R.S., CHRIST (Deemed to be University), India; Anian A.M., CHRIST (Deemed to be University), India; Raja A.S.M., CHRIST (Deemed to be University), India

Rights

Restricted Access

Relation

ISSN: 15441458

Format

Online

Language

English

Type

Article

Identifier

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087300254&partnerID=40&md5=6eeec8f682696985cf98e8a5fc753de4