2023
DOI: 10.1016/j.ijhm.2023.103556
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Consumers' affective needs matter: Open innovation through mining luxury hotels' online reviews

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Cited by 14 publications
(14 citation statements)
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“…The nature of such data is thus sentimental and contextual based. Many previous studies have used online reviews and user-generated data as the main data source, particularly in studies related to destination branding and tourists' perceptions (Lee and Park, 2023;Qi et al, 2018;Wong and Qi, 2017;Wu et al, 2023). Those online reviews are believed to be individuals' self-disclosed inner feelings that are free of commercial meddling.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…The nature of such data is thus sentimental and contextual based. Many previous studies have used online reviews and user-generated data as the main data source, particularly in studies related to destination branding and tourists' perceptions (Lee and Park, 2023;Qi et al, 2018;Wong and Qi, 2017;Wu et al, 2023). Those online reviews are believed to be individuals' self-disclosed inner feelings that are free of commercial meddling.…”
Section: Methodsmentioning
confidence: 99%
“…The source is C-Trip.com (also known as Trip). Trip is currently the biggest online travel intermediary in China (Wu et al, 2023). Apart from the travel products that buyers can make bookings directly online, Trip also allows customers to share their experiences online, which makes Trip itself a renowned social media platform for travel tips.…”
Section: Data Collectionmentioning
confidence: 99%
“…These internal factors contribute to gaining competitive advantages by creating modern, innovative and personalised tourism services (Sheldon, 2020). On the other hand, they are also crucial in fostering positive internal emotions among consumers when they perceive first-hand their ease of use (Wu et al, 2023). The following research hypotheses are derived from these theoretical foundations: H3.…”
Section: Personal Factors (Pf)mentioning
confidence: 99%
“…In particular, online review mining involves analyzing reviews posted on ecommerce platforms with the aid of computer technology, potentially reducing subjective error. Wu et al (2023) collected online review data to identify service attributes that can enhance hotel innovation measures. Liu et al (2023) utilized online reviews from ecommerce platforms for smart phones and proposed Kansei engineering improvements.…”
Section: Kansei Engineeringmentioning
confidence: 99%