Big Data Analytics and Forecasting in Fashion

A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).

Deadline for manuscript submissions: closed (30 November 2020) | Viewed by 1233

Special Issue Editors


E-Mail Website
Guest Editor
Centre for Fashion Business and Innovation Research, Fashion Business School, London College of Fashion, University of the Arts London. 272 High Holborn, London WC1V 7EY, UK
Interests: time series analysis and forecasting; applied statistics; quantitative methods

E-Mail Website
Guest Editor
1. International Institute for Applied Systems Analysis (IIASA), 2361 Laxenburg, Austria
2. Research Institute of Energy Management and Planning (RIEMP), University of Tehran, Tehran 1417466191, Iran
Interests: big data; AI; machine learning; statistics; digital twins; digital health; advanced technology
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Fashion Business School, London College of Fashion, University of the Arts London. 272 High Holborn, London WC1V 7EY, UK
Interests: fashion industry

Special Issue Information

Dear Colleagues,

In an age of fast fashion, high street retailers are struggling to remain competitive by maximising consumer insights through the exploitation of big data (Styles, 2019) and its potential for enhancing fashion analytics and forecasting. For an industry that has traditionally relied heavily on creativity and intuition for direction in designing, buying and merchandising, the time has come to get fashionable with (big) data (Silva et al., 2019a). In fact, Chinese e-commerce giant Alibaba used big data recently to predict fashion trends and had their collections built around these (Livni, 2019), whilst recent academic research has focused on the possibility of using Google Trends for predicting fashion consumer behaviour (Silva et al., 2019b). Whilst big data presents many opportunities for enhancing the status of sustainability, business operations and productivity within the fashion industry, it also has several challenges that hinder its wide application, from data privacy issues to a lack of data-savvy fashion graduates and slow academic research. Thus, this Special Issue will focus on the evolution of the fashion industry in an age of big data and rapid technological innovation and seek to promote and motivate more industry-relevant academic research into this subject area. Manuscripts are invited on topics that include but are not limited to the following:

  • The impact of big data on the entire fashion value chain from concept to consumption;
  • The influence of big data on the emergence of new business models;
  • How big data impacts supply chain and marketing;
  • How traditional fashion industry roles are changing through the leveraging of big data;
  • Big data analytics in fashion: applications, consumer attitudes and perceptions;
  • Big data opportunities and challenges in fashion;
  • Time series analysis and forecasting in fashion;
  • New insights on trend forecasting in an age of big data;
  • The future of blockchain technology in the fashion industry.

     

    References

    Livni, E. Alibaba designers used AI to shape New York Fashion Week looks. Available online: https://qz.com/quartzy/1704770/alibaba-designers-used-ai-for-new-york-fashion-week-looks/ (accessed on 18 September 2019).
    Silva, E. S., Hassani, H., and D. Ø. Madsen. Big data in fashion: Transforming the retail sector. J. Bus. Strategy 2019.DOI:10.1108/JBS-04-2019-0062.
    Silva, E. S., Hassani, H., D. Ø. Madsen, and Gee, L. Googling fashion: Forecasting fashion consumer behaviour using google trends. Soc. Sci. 2019, 8, 111.
    Styles, D. Data and the dress: what Christopher Wylie can teach fashion. Available online: https://www.theguardian.com/fashion/2019/aug/26/data-and-the-dress-what-christopher-wylie-can-teach-fashion (accessed on 18 September 2019).

Dr. Emmanuel Sirimal Silva
Prof. Dr. Hossein Hassani
Ms. Liz Gee
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Big Data and Cognitive Computing is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers

There is no accepted submissions to this special issue at this moment.
Back to TopTop