Item-level RFID for enhancement of customer shopping experience in apparel retail

In the customer-oriented apparel retail industry, providing satisfactory shopping experience for customers is a vital differentiator. However, traditional stores generally cannot fully satisfy customer needs because of difficulties in locating target products, out-of-stocks, a lack of professional assistance for product selection, and long waiting for payments. Therefore, this paper proposes an item-level RFID-enabled retail store management system for relatively high-end apparel products to provide customers with more leisure, interaction for product information, and automatic apparel collocation to promote sales during shopping. In this system, RFID hardware devices are installed to capture customer shopping behaviour and preferences, which would be especially useful for business decision-making and proactive individual marketing to enhance retail business. Intelligent fuzzy screening algorithms are then developed to promote apparel collocation based on the customer preferences, the design features of products, and the sales history accumulated in the database. It is expected that the proposed system, when fully implemented, can help promote retail business by enriching customers with intelligent and personalized services, and thus enhance the overall shopping experience. © 2015 Elsevier B.V.postprin

Apparel recommendation system evolution: an empirical review

Purpose: With the developments of e-commerce markets, novel recommendation technologies are becoming an essential part of many online retailers' economic models to help drive online sales. Initially, the purpose of this paper is to undertake an investigation of apparel recommendations in the commercial market in order to verify the research value and significance. Then, this paper reviews apparel recommendation techniques and systems through academic research, aiming to acquaint apparel recommendation context, summarize the pros and cons of various research methods, identify research gaps and eventually propose new research solutions to benefit apparel retailing market. Design/methodology/approach: This study utilizes empirical research drawing on 130 academic publications indexed from online databases. The authors introduce a three-layer descriptor for searching articles, and analyse retrieval results via distribution graphics of years, publications and keywords. Findings: This study classified high-tech integrated apparel systems into 3D CAD systems, personalised design systems and recommendation systems. The authors' research interest is focussed on recommendation system. Four types of models were found, namely clothes searching/retrieval, wardrobe recommendation, fashion coordination and intelligent recommendation systems. The forth type, smart systems, has raised more awareness in apparel research as it is equipped with advanced functions and application scenarios to satisfy customers. Despite various computational algorithms tested in system modelling, existing research is lacking in terms of apparel and users profiles research. Thus, from the review, the authors have identified and proposed a more complete set of key features for describing both apparel and users profiles in a recommendation system. Originality/value: Based on previous studies, this is the first review paper on this topic in this subject field. The summarised work and the proposed new research will inspire future researchers with various knowledge backgrounds, especially, from a design perspective

DAMPAK FAST FASHION DAN PERAN DESAINER DALAM MENCIPTAKAN SUSTAINABLE FASHION

Tujuan penelitian ini adalah (1) untuk mengetahui konsep fast fashion dan hubungannya dengan global fashionindustri, (2) untuk mengetahui dampak lingkungan akibat berkembangnya industri fast fashion, dan (3) untukmengeksplorasi peran desainer dalam menciptakan sustainable fahion. Fast fashion adalah model bisnis yangmenawarkan pakaian yang murah dan trendi, hasil kolaborasi produsen, pemasok, dan konsumen, yangperputarannya sangat cepat berganti untuk memenuhi dan menguasai pasar mode. Sebuah penekanan padakecepatan, kuantitas, dan ukuran mendorong budaya konsumsi dan industri, sehingga akan terjadi masalahterhadap kesejahteraan manusia, terutama polusi dan praktek perdagangan yang tidak adil. Industri fast fashiontelah tumbuh lebih cepat dari industri fashion lainnya, sehingga mendorong disposibilitas yang lebih besar.Industri fashion menjadi penyumbang tekstil limbah yang berakhir di tempat pembuangan sampah, sementarabahan sintetis tidak dapat terurai. Desainer merupakan salah satu aktor dalam membuat produk fashion,sehingga perannya dalam menciptakan fashion yang sustainable sangat bermanfaat dalam ikut menyelamatkanplanet bumi. Konsep yang diusulkan penulis yang bisa menjadi alternatif dalam menciptakan fashion yangsustainable antara lain: ethical fahion, eco label, quality & durability, timeless desain, local & traditional,recycling & upcycling, zero waste & modular structures

Fit evaluation of virtual garment try-on by learning from digital pressure data

Presently, garment fit evaluation mainly focuses on real try-on, and rarely deals with virtual try-on. With the rapid development of E-commerce, there is a profound growth of garment purchases through the internet. In this context, fit evaluation of virtual garment try-on is vital in the clothing industry. In this paper, we propose a Naive Bayes-based model to evaluate garment fit. The inputs of the proposed model are digital clothing pressures of different body parts, generated from a 3D garment CAD software; while the output is the predicted result of garment fit (fit or unfit). To construct and train the proposed model, data on digital clothing pressures and garment real fit was collected for input and output learning data respectively. By learning from these data, our proposed model can predict garment fit rapidly and automatically without any real try-on; therefore, it can be applied to remote garment fit evaluation in the context of e-shopping. Finally, the effectiveness of our proposed method was validated using a set of test samples. Test results showed that digital clothing pressure is a better index than ease allowance to evaluate garment fit, and machine learning-based garment fit evaluation methods have higher prediction accuracies

Model Fuzzy Expert System Berbasis Pemakai Pada PT. Batik Semar Cabang Medan

Model fuzzy expert system berbasis pemakai menggunakan metodeinferensi tsukamoto dirancang untuk memberikan rekomendasi pakaian batik yangsesuai untuk pemakai berdasarkan variabel usia, warna kulit, rencana kegiatanpemakai dan kemampuan beli (kisaran harga yang terjangkau oleh pemakai), yangdihasilkan dengan menggabungkan logika fuzzy dan sistem pakar. Aplikasi inidibangun dengan perangkat lunak Microsoft Visual Basic 6.0. Hasil logika fuzzydiperoleh dengan nilai kepentingan pemakai batik antara 50 sampai dengan 82dan hasil sistem pakar yang teridentifikasi dengan nilai kepentingan >=50 denganmelakukan penetapan warna batik, motif batik, bahan batik, proses pembuatanbatik, serta kisaran harga batik untuk setiap pemakai batik

Colour forecasting: an investigation into how its development and use impacts on accuracy

Colour forecasting is a sector of trend forecasting which is arguably the most important link in the product development process, yet little is known about it, the methodology behind its development or its accuracy. It is part of a global trend forecasting industry valued recently at $36bn, providing information which is developed commercially eighteen months to two years ahead of the season. Used throughout the garment supply chain, by the yarn and fibre manufacturers, the fabric mills, garment designers and retailers, it plays a pivotal role in the fashion and textile industry, but appears in many different forms. Colour forecasts were first commercially produced in 1917, but became more widely used during the 1970s, and in recent years digital versions of colour forecasts have become increasingly popular. The investigation aimed to establish the historical background of the industry, mindful of the considerable changes to fashion manufacturing and retailing in recent decades. For the purposes of the investigation, a period spanning 25 years was selected, from 1985 to 2010. In reviewing the available literature, and the methodologies currently used in developing forecasting information, it became clear that there was a view that the process is very intuitive, and thus a lack of in depth academic literature. This necessitated a considerable quantity of primary research in order to fill the gaps in the knowledge regarding the development, use and accuracy of colour forecasting. A mixed method approach to primary research was required to answer the aim of the thesis, namely to investigate how colour forecasts are compiled, and examine their use, influence and accuracy within the fashion and textiles industry, suggesting methods for developing more accurate forecasts in the future. Interviews were conducted with industry practitioners comprising forecasters, designers and retailers to better understand how colour was developed and used within industry. Two longitudinal studies were carried out with the two largest UK clothing retailers to map their development and use of colour palettes, and understand better how colour contributes to the critical path and supply chain. Two colour development meetings were observed, one with a commercial colour forecaster, the other with an industry association, and two colour archives were studied to establish whether or not any identifiable and predictable colour cycles existed. Data from the interviews and longitudinal studies were analysed using a grounded approach, and revealed some new insights into the influences upon the development of colour forecasts both commercially and from the retailer's perspective. The sell through rates of merchandise, EPOS analysis and range of practices between those interviewed and the two retailers studied provided an interesting insight into working practices and how colour forecasting information is changed when used by the retailers. It was found that a group of core colours existed, which were used season after season, and consistently demonstrated a high sell through rate, such as black, white, grey and navy. In order to establish whether or not colour cycles were consistently predictable in their repetition, two colour forecasting archives were assessed. If predictable colour cycles existed, they would be a useful tool in developing more accurate forecasts. Unfortunately this was not the case, as no clear colour cycles were found. However, the archive, together with evidence from the retailers demonstrated the 'lifecycle' of fashion colours was longer than expected, as they took time to phase in and out. It was concluded that in general the less fashion led brands used their own signature colours and were able to develop colour palettes far later in the product development timeline. This approach could be adopted more widely by retailers and designers as it was discovered that although accuracy rates for colour forecasts are generally accepted to be around 80%, the commercial forecasters provide colour update cards closer to the season where at least 40% of the colours are changed. Very early information, two years ahead of the season is no longer necessary in the contemporary fashion and textiles industry

23rd Recent Advances in Retailing & Services Science Conference, July 11-14, 2016, Edinburgh, Scotland:book of abstracts

This book includes the (edited) abstracts of the papers that will be presented at the 23rd Recent Advancesin Retailing and Services Science Conference, at the Carlton/Hilton hotel, Edinburgh, Scotland, July 11-16, 2016.The aim of the conference is to bring together an international and multidisciplinary audience working ondifferent topics in retailing and consumer behavior research. Both completed work and work in progresswill be presented. This is reflected in the kind of papers that have been accepted for presentation