Do sequels outperform or disappoint? Insights from an analysis of Amazon echo consumer reviews

• Main Authors: SHIM, Kyong Jin, LO, Siaw Ling, LIEW, Su Yee
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Data Analytics; Data Mining and Machine Learning for Social Media; Amazon Echo; consumer reviews; product sequels; smart home device; text mining; Databases and Information Systems; E-Commerce; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/6847; https://ink.library.smu.edu.sg/context/sis_research/article/7850/viewcontent/Sequels_outperform_0291_pvoa.pdf
• Institution: Singapore Management University

Rapid technological advances in recent years drastically transformed our world. Amidst modern technological inventions such as smart phones, smart watches and smart home devices, consumers of electronic digital devices experience greatly improved automation, productivity, and efficiency in conducting routine daily tasks, information searching, shopping as well as finding entertainment. In the last few years, the global smart speaker market has undergone significant growth. As technology continues to advance and smart speakers are equipped with innovative features, the adoption of smart speakers will increase and so will consumer expectations. This research paper presents an aspect-specific sentiment analysis of consumer reviews of the first three generations of Amazon Echo. Our text mining and aspect-specific sentiment analyses reveal that price, sound, smart home, connectivity, and comparison are outperforming aspects whereas voice, app, Q&A, companionship, and shelf life are disappointing and sunsetting aspects. Our study demonstrates a novel cross-generation visualization of directional changes in consumer sentiment using the Bollinger Bands and volume charts.