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Article
Publication date: 21 October 2023

Alex Rudniy, Olena Rudna and Arim Park

This paper seeks to demonstrate the value of using social media to capture fashion trends, including the popularity of specific features of clothing, in order to improve the speed…

Abstract

Purpose

This paper seeks to demonstrate the value of using social media to capture fashion trends, including the popularity of specific features of clothing, in order to improve the speed and accuracy of supply chain response in the era of fast fashion.

Design/methodology/approach

This study examines the role that text mining can play to improve trend recognition in the fashion industry. Researchers used n-gram analysis to design a social media trend detection tool referred to here as the Twitter Trend Tool (3Ts). This tool was applied to a Twitter dataset to identify trends whose validity was then checked against Google Trends.

Findings

The results suggest that Twitter data are trend representative and can be used to identify the apparel features that are most in demand in near real time.

Originality/value

The 3Ts introduced in this research contributes to the field of fashion analytics by offering a novel method for employing big data from social media to identify consumer preferences in fashion elements and analyzes consumer preferences to improve demand planning.

Practical implications

The 3Ts improves forecasting models and helps inform marketing campaigns in the apparel retail industry, especially in fast fashion.

Details

Journal of Fashion Marketing and Management: An International Journal, vol. 28 no. 3
Type: Research Article
ISSN: 1361-2026

Keywords

Open Access
Article
Publication date: 21 February 2024

Mehrgan Malekpour, Federica Caboni, Mohsen Nikzadask and Vincenzo Basile

This paper aims to identify the combination of innovation determinants driving the creation of innovative products amongst market leaders and market followers in food and beverage…

Abstract

Purpose

This paper aims to identify the combination of innovation determinants driving the creation of innovative products amongst market leaders and market followers in food and beverage (F&B) firms.

Design/methodology/approach

This research is based on the case study methodology by using two types of data sources: (1) semi-structured interviews with industry experts and (2) in-depth interviews with managers. In addition, a questionnaire adapted from prior research was used to consider market and firm types.

Findings

Suggesting an integrated theoretical framework based on firm-based factors and market-based factors, this study identified a combination of determinants significantly impacting innovative products in the market. Specifically, these determinants are competition intensity and innovation capability (a combination of research and development (R&D) investment and marketing capabilities). The study also examined how these determinants vary depending on whether the firms are market leaders or market followers.

Practical implications

This research provides practical insights for managers working in the F&B industry by using case studies and exploring the determinants of developing innovative products. In doing so, suitable strategies can be selected according to the market and firm situations.

Originality/value

The originality of the study is shown by focussing on how different combinations of market and firm factors could be applied in creating successful innovative products in the food sector.

Details

British Food Journal, vol. 126 no. 13
Type: Research Article
ISSN: 0007-070X

Keywords

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