Exploring customer online reviews for new product development: The case of identifying reinforcers in the cosmetic industry

被引:15
作者
Haddara, Moutaz [1 ]
Hsieh, Jenny [2 ]
Fagerstrom, Asle [1 ]
Eriksson, Niklas [3 ]
Sigurdsson, Valdimar [4 ]
机构
[1] Kristiania Univ Coll, Dept Technol, Sch Econ Innovat & Technol, Oslo, Norway
[2] TIAS Sch Business & Soc, Utrecht, Netherlands
[3] Arcada Univ Appl Sci, Dept Business Management & Analyt, Helsinki, Finland
[4] Reykjav Univ, Sch Business, Reykjavik, Iceland
关键词
MAJOR PLAYERS; ANTECEDENTS; BEHAVIOR; SYSTEMS; IMAGE; EWOM;
D O I
10.1002/mde.3078
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study analyzes online customer reviews in order to investigate customers' preferences regarding cosmetic products. Based on the marketing firm theory, this research explores the possibility of enhancing the bilateral contingent relationships between the customer and the marketing firm within the cosmetics domain. Hence, this study applies market-search concepts by extracting customer reviews and employing text analytics to identify reinforcers and factors in cosmetic products, which customers are expecting, and their sentiments towards them. Our results suggest that some reinforcers are shared among all customers, but some vary among the different customer segments based on their age and skin tone.
引用
收藏
页码:250 / 273
页数:24
相关论文
共 111 条
[81]   The effect of online reviews on product sales: A joint sentiment-topic analysis [J].
Li, Xiaolin ;
Wu, Chaojiang ;
Mai, Feng .
INFORMATION & MANAGEMENT, 2019, 56 (02) :172-184
[82]   Mining product maps for new product development [J].
Liao, Shu-Hsien ;
Hsieh, Chia-Lin ;
Huang, Sul-Ping .
EXPERT SYSTEMS WITH APPLICATIONS, 2008, 34 (01) :50-62
[83]  
Liu B., 2007, WEB DATA MINING EXPL
[84]  
Liu B, 2010, CH CRC MACH LEARN PA, P627
[85]  
Ma Y., 2018, INT J BUSINESS MANAG, V13, P211, DOI DOI 10.5539/IJBM.V13N3P211
[86]  
Matthies B., 2017, International Journal of Management, Knowledge and Learning, V6, P153
[87]   The role of ICT, eWOM and guest characteristics in loyalty [J].
Moliner-Velazquez, Beatriz ;
Fuentes-Blasco, Maria ;
Gil-Saura, Irene .
JOURNAL OF HOSPITALITY AND TOURISM TECHNOLOGY, 2019, 10 (02) :153-168
[88]  
Mudambi SM, 2010, MIS QUART, V34, P185
[89]   Thumbs up? Sentiment classification using machine learning techniques [J].
Pang, B ;
Lee, L ;
Vaithyanathan, S .
PROCEEDINGS OF THE 2002 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING, 2002, :79-86
[90]  
Patel F., 2012, International Journal of Advanced Computer Research, V2, P243