Simultaneous coordination of capacity building and price decisions in a decentralized supply chain

International audienceAbstract

Sustainable Value Generation Through Post-retail Initiatives : An Exploratory Study of Slow and Fast Fashion Businesses

The dialogue between slow and fast fashion has gained great prominence in recent years particularly in terms of sustainability. In the forward value chain, fast fashion companies are most often considered to be unsustainable whereas the slow fashion brands are comparatively more planet-friendly. However, the discussionon the trade-off between sustainability and “speed of fashion” (classified into slow and fast fashions) in the post-retail segment is still limited. A deeper understanding, however, would not only contribute towards conceptualizing the post-retail initiatives, but would also shed light on how these are differentially undertaken by various types of fashion businesses in terms of generating sustainable value. This study proposes sustainable value generation in terms of closing the material and responsibility loops. It further reveals that the trade-off in post-retail is not as rigid as itis in the forward value chain. However, fast fashion offers the lowest potential todisplace the purchase of new clothes to close the material loop whereas the redesign brands offer the highest; moreover fast fashion is less liable to take extended responsibilities compared to the slow fashion brands. It can be concluded that fast fashion is somewhat “stuck in the middle” in comparison to the slow and redesign brands in terms of generating value through closing the loop activities

A Comparative Study on Fashion Demand Forecasting Models with Multiple Sources of Uncertainty

Fast fashion is a timely, influential and well observed business strategy in the fashion retail industry. An effective fast fashion supply chain relies on quick and competent forecasts of highly volatile demand that involves multiple stock keeping units. However, there are multiple sources of uncertainty, such as market situation and rapid changes of the fashion trends, which makes demand forecasting more challenging. Therefore, it is crucial for the fast fashion companies to carefully select the right forecasting models to thrive and to succeed in this ever changing business environment. In this study, we first review a selected set of computational models which can be applied for fast fashion demand forecasting. We then perform a real sale data based computation analysis and discuss the strengths and weaknesses of these versatile models. Finally, we conduct a survey to learn about the perceived importance of different demand forecasting systems’ features from the fashion industry. Finally, we rank the fast fashion demand forecasting systems using the AHP analysis and supplement with important insights on the preferences on the demand forecasting systems of different groups of fashion industry experts and supply chain practitioners