Travelers’ food experience sharing on social network sites

Wang, Saerom; Kirillova, Ksenia; Lehto, Xinran

doi:10.1080/10548408.2016.1224751

Cited by 90 publications

(63 citation statements)

References 50 publications

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“…Many studies have been conducted by utilizing data mining gathered from online review platforms (Brochado & Brochado, 2019;Wang et al, 2017;Wu et al, 2014), and particularly speaking, Taecharungroj and Mathayomchan (2019) briefly mentioned local markets in Phuket as a tourist attraction among others. However, a more nuanced understanding of tourists' experiences at these individual markets in Phuket has yet to be offered and clarified, which is the gap addressed by this research.…”

Section: Discussionmentioning

confidence: 99%

“…Many scholars have also looked into various topics in the tourism and hospitality context by using online content and reviews as their source of data. For example, Wang et al (2017) studied Korean travelers' food experience, whilst Wu et al (2014) focused on tourists' shopping experiences in the Silk Market. Moreover, studies have examined complaints about hotels by means of online reviews (Au et al, 2014;Memarzadeh & Chang, 2015).…”

Section: Online Reviewsmentioning

confidence: 99%

“…Currently, many studies have used online reviews to examine tourists' experiences in various destinations (for instance, Brochado & Brochado, 2019;Wang et al, 2017;Wu et al, 2014), as online platforms have provided researchers with reliable and accessible sources to examine certain tourism phenomena (Kozinets, 2010;Yoo & Gretzel, 2008). Indeed, Taecharungroj and Mathayomchan (2019) have comprehensively examined tourist attractions, including markets, in Phuket by analyzing TripAdvisor reviews; however, the part on local markets failed to provide more detailed discussion and practical implications since the study covered many local attractions in Phuket.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Understanding Tourists’ Experiences at Local Markets in Phuket: An Analysis of TripAdvisor Reviews

Sangkaew

Zhu

2020

Journal of Quality Assurance in Hospitality & Tourism

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This research sets out to explore the tourists' experiences at local markets in Phuket by analyzing the online reviews from TripAdvisor. This research adopts a novel method by combining the KNIME Analytics Platform with the Naïve Bayes algorithm to undertake the sentiment analysis of 2,934 reviews from seven local markets in Phuket. According to the frequency, salience, and valence, this research has identified five positive and five negative terms to provide a comprehensive understanding of tourists' experiences at these local markets. Moreover, this research also provides a nuanced understanding of their experiences by highlighting the deviation for those positive terms that have negative valence at certain individual market(s) and vice versa. The findings of this research provide significant practical implications for tourism practitioners and local stakeholders.

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Section: Discussionmentioning

confidence: 99%

Section: Online Reviewsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Understanding Tourists’ Experiences at Local Markets in Phuket: An Analysis of TripAdvisor Reviews

Sangkaew

Zhu

2020

Journal of Quality Assurance in Hospitality & Tourism

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“…Since the ICT and social media revolution, tourists leave more and more digital footprints on different UGC platforms (Litvin et al, 2008;Munar & Jacobsen, 2014). Next to the fast-growing field of studies analysing topics and trends in UGC (O'Connor, 2008;Wang, Kirillova, & Lehto, 2017), analysing the digital footprint geographically can also give an indication on how tourists perceive, experience and use the destination (Ganzaroli et al, 2017;García-Palomares, Gutiérrez, & Mínguez, 2015;Girardin, Calabrese, Dal Fiore, Ratti, & Blat, 2008;Kádár, 2014;Koerbitz, Önder, & Hubmann-Haidvogel, 2013) and which experiences they communicate to their peers (Leung, Vu, Rong, & Miao, 2016).…”

Section: Theoretical Framework: Tourist Behaviour In Historic Citiesmentioning

confidence: 99%

Distribution of tourists within urban heritage destinations: a hot spot/cold spot analysis of TripAdvisor data as support for destination management

Zee

Bertocchi

Vanneste

2018

Current Issues in Tourism

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The emergence of social media and Web 2.0 has a notable impact upon the tasks of destination managers as these platforms have developed into influential mechanisms affecting tourist behaviour. This paper shows how Destination Management Organizations (DMOs) can reap the benefits of the Web 2.0 revolution as it serves as an important source of user-generated information, bringing novel opportunities for data-driven destination management. To test the applicability of user-generated content for destination management, this paper analyses restaurant reviews from five Flemish art cities which were retrieved from the Web 2.0 platform TripAdvisor. Getis-Ord hot spot analysis revealed spatial clusters of frequently ('hot spots') and rarely ('cold spots') reviewed restaurants in four out of the five art cities. By comparing these spatial patterns, the digital footprints of tourists were uncovered and discussed with DMO directors. Found patterns appeared to reflect local policies aimed either at concentrating tourism, as in Bruges, the city with the most prominent hot spot, or spreading tourism over time and space as seen in Antwerp and Ghent where less prominent hot spots were present. The visualization proved to be a valuable input when discussing tourism management and fuelled the sharing of knowledge between the destinations.

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“…Wang et al [40] proposed that tourists voluntarily and happily promote destinations and influence the decision-making of others by sharing their memorable experiences of destinations. Similarly, sharing dining experiences of landscape restaurants probably forms a subject norm and affects the behavioral intention of others.…”

Section: Practical Implicationsmentioning

confidence: 99%

Applying an Extended Theory of Planned Behavior for Sustaining a Landscape Restaurant

Liao

Fang

2019

Sustainability

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This paper extended the theory of planning behavior (ETPB) to examine the antecedents of consumer behavioral intention in order to explore the sustainable factors of a landscape restaurant. Following theory of planned behavior (TPB) and the related literature for landscape perception and preference, we initially developed a preliminary list of items, and after the expert review and pre-test, we employed a 33-item measure under a five-factor structure and collected a total of 395 valid questionnaires. The empirical results show that landscape perception and preference (LP&P), attitude (AT), subjective norm (SN), and perceived behavior control (PBC) have positive impacts, among which LP&P has the most significantly positive impact on consumer behavioral intention. Thus, ETPB helps contribute to the decision-making model of landscape restaurants. Lastly, we discuss managerial implications and future research directions.

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Travelers’ food experience sharing on social network sites

Cited by 90 publications

References 50 publications

Understanding Tourists’ Experiences at Local Markets in Phuket: An Analysis of TripAdvisor Reviews

Understanding Tourists’ Experiences at Local Markets in Phuket: An Analysis of TripAdvisor Reviews

Distribution of tourists within urban heritage destinations: a hot spot/cold spot analysis of TripAdvisor data as support for destination management

Applying an Extended Theory of Planned Behavior for Sustaining a Landscape Restaurant

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