Arzu Vuruskan, Turker Ince, Ender Bulgun and Cuneyt Guzelis
– The purpose of this paper is to develop an intelligent system for fashion style selection for non-standard female body shapes.
Abstract
Purpose
The purpose of this paper is to develop an intelligent system for fashion style selection for non-standard female body shapes.
Design/methodology/approach
With the goal of creating natural aesthetic relationship between the body shape and the shape of clothing, garments designed for the upper and lower body are combined to fit different female body shapes, which are classified as V, A, H and O-shapes. The proposed intelligent system combines genetic algorithm (GA) with a neural network classifier, which is trained using the particle swarm optimization (PSO). The former, called genetic search, is used to find the optimal design parameters corresponding to a best fit for the desired target, while the task of the latter, called neural classification, is to evaluate fitness (goodness) of each evolved new fashion style.
Findings
The experimental results are fashion styling recommendations for the four female body shapes, drawn from 260 possible combinations, based on variations from 15 attributes. These results are considered to be a strong indication of the potential benefits of the application of intelligent systems to fashion styling.
Originality/value
The proposed intelligent system combines the effective searching capabilities of two approaches. The first approach uses the GA for identifying best fits to the target shape of the body in the solution space. The second is the PSO for finding optimal (with respect to training mean-squared error) weight and threshold parameters of the neural classifier, which is able to evaluate the fitness of successively evolved fashion styles.
Details
Keywords
Cristina M. Ostermann, Leandro da Silva Nascimento, Fernanda Kalil Steinbruch and Daniela Callegaro-de-Menezes
This study aims to identify the drivers for adopting the circular economy (CE) in a born-sustainable business of the fashion sector.
Abstract
Purpose
This study aims to identify the drivers for adopting the circular economy (CE) in a born-sustainable business of the fashion sector.
Design/methodology/approach
An exploratory case study was carried out with a unique and relevant case: the only Brazilian company implementing circularity practices defined through a sectoral commitment, the 2020 Circular Fashion System Commitment.
Findings
From an analysis of the literature, a theoretical scheme composed of internal and external drivers is proposed. In the case studied, there is a prevalence of internal drivers that led the company to implement the CE. Most of the internal drivers described by the literature were identified in this research, except for two: profitability and available technology. Regarding the external drivers, of the 12 listed, only laws and regulations were identified. Thus, the results suggest that internal drivers are more numerous and may be more prominent than external ones for CE adoption in the born-sustainable business.
Research limitations/implications
Due to its exploratory design and unique case study, the research does not allow generalizations, suggesting replication with a larger number of companies and carrying out quantitative research with born-sustainable companies and incumbent companies, for comparison. Considering that there is a difference between companies that decide for sustainable practices and companies that were already born sustainable, it can be questioned if the drivers for implementing CE for both companies are also different.
Originality/value
This study proposes a theoretical scheme that indicates the main internal and external drivers for companies' CE implementation. Developed from a literature review and applied in an empirical case, this scheme is comprehensive and can be adopted to analyze companies of different sizes and industries. Hence, this paper generates new perspectives for CE literature.