Abstract
Design/methodology/approach: This study applied sentiment analysis to determine the polarity of a given comment. Furthermore, content analysis was conducted based on the core attributes of the customer dining experiences.
Findings: Positive feelings towards the food and the service do not show a linear relationship, while the overall dining experiences increase in line with the positive feelings on food quality. Moreover, feelings towards the atmosphere of the restaurants are the most positive in peak season.
Practical implications: This study provides guidelines for restaurateurs regarding the aspects that need more attention in different seasons.
Originality/value: The paper contributes to the knowledge of customer feelings in local restaurants/gastronomy and the role seasonality plays in fostering such feelings. In addition, the novel methodological procedures provide insights for tourism research in discovering new dimensions in theories based on big data. © 2020, Emerald Publishing Limited.
| Original language | English |
|---|---|
| Pages (from-to) | 461-478 |
| Number of pages | 18 |
| Journal | J. Hosp. Tour. Technol. |
| Volume | 11 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 21 Sept 2020 |
Keywords
- Dining experience
- Local gastronomy
- Seasonality
- Sentiment analysis
- Service quality
- User-generated content
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In: J. Hosp. Tour. Technol., Vol. 11, No. 3, 21.09.2020, p. 461-478.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - The embedded feelings in local gastronomy: a sentiment analysis of online reviews
AU - Yu, C.-E.
AU - Zhang, X.
N1 - Cited By :27 Export Date: 14 December 2023 Correspondence Address: Yu, C.-E.; Department of Innovation and Management in Tourism, Austria; email: [email protected] Funding details: Cranfield University Funding text 1: The authors would like to express their deepest gratitude to Dr Edgar Jimenez Perez who is the Lecturer at Cranfield University in the UK for his patient and detailed proofreading. Moreover, the current study involves analyzing several languages and, thus required native speakers for translations. The authors would like to express their gratitude to Isabela Irimia (German and Italian), Kyoko Suzuki (Japanese), Arne Van den Winckel (Dutch), Laura Dulbecco (Spanish), Anna Chorna (Russian) and Tommy Kristoffer Nilsen (Swedish) from Salzburg University of Applied Sciences; Min Kyoung (Mimi) Kim (Korean) and Alexandre Abdollahi Khonacha (French) from Cranfield University; and Alicia Daniels Araújo Sousa (Portuguese) from Macao Institute for Tourism Studies. References: Alaei, A.R., Becken, S., Stantic, B., Sentiment analysis in tourism: capitalizing on big data (2017) Journal of Travel Research, 58 (2), pp. 175-191; Andaleeb, S., Conway, C., Customer satisfaction in the restaurant industry: an examination of the transaction‐specific model (2006) Journal of Services Marketing, 20 (1), pp. 3-11; Annamdevula, S., Bellamkonda, R.S., Effect of student perceived service quality on student satisfaction, loyalty and motivation in Indian universities (2016) Journal of Modelling in Management, 11 (2), pp. 488-517; Arora, R., Singer, J., Customer satisfaction and value as drivers of business success for fine dining restaurants (2006) Services Marketing Quarterly, 28 (1), pp. 89-102; Ayeh, J.K., Au, N., Law, R., Do we believe in TripAdvisor?” Examining credibility perceptions and online travelers’ attitude toward using user-generated content (2013) Journal of Travel Research, 52 (4), pp. 437-452; Becken, S., Alaei, A.R., Wang, Y., Benefits and pitfalls of using tweets to assess destination sentiment (2019) Journal of Hospitality and Tourism Technology, 11 (1); Bitner, M.J., Servicescapes: the impact of physical surroundings on customers and employees (1992) Journal of Marketing, 56 (2), pp. 57-71; Bogicevic, V., Yang, W., Bilgihan, A., Bujisic, M., Airport service quality drivers of passenger satisfaction (2013) Tourism Review, 68 (4), pp. 3-18; Boz, H., Arslan, A., Koc, E., Neuromarketing aspect of tourısm pricing psychology (2017) Tourism Management Perspectives, 23, pp. 119-128; Braun, V., Clarke, V., (2013) Successful Qualitative Research: A Practical Guide for Beginners, , Sage, Los Angeles; Bryman, A., (2016) Social Research Methods, , Oxford University Press, Oxford; Calheiros, A.C., Moro, S., Rita, P., Sentiment classification of consumer-generated online reviews using topic modeling (2017) Journal of Hospitality Marketing and Management, 26 (7), pp. 675-693; Carranza, R., Díaz, E., Martín-Consuegra, D., The influence of quality on satisfaction and customer loyalty with an importance-performance map analysis (2018) Journal of Hospitality and Tourism Technology, 9 (3), pp. 380-396; Cetin, G., Bilgihan, A., Components of cultural tourists’ experiences in destinations (2016) Current Issues in Tourism, 19 (2), pp. 137-154; Chang, S., Experience economy in hospitality and tourism: gain and loss values for service and experience (2018) Tourism Management, 64, pp. 55-63; Connell, J., Page, S.J., Meyer, D., Visitor attractions and events: responding to seasonality (2015) Tourism Management, 46, pp. 283-298; (2017) Inventory of intangible cultural heritage, , www.culturalheritage.mo/en/detail/2466/1, accessed 10 December 2018; Fereday, J., Muir-Cochrane, E., Demonstrating rigor using thematic analysis: a hybrid approach of inductive and deductive coding and theme development (2006) International Journal of Qualitative Methods, 5 (1), pp. 80-92; Fong, L.H.N., Lei, S.S.I., Law, R., Asymmetry of hotel ratings on TripAdvisor: evidence from single-versus dual-valence reviews (2017) Journal of Hospitality Marketing and Management, 26 (1), pp. 67-82; Gale, N.K., Heath, G., Cameron, E., Rashid, S., Redwood, S., Using the framework method for the analysis of qualitative data in multi-disciplinary health research (2013) Medical Research Methodology, 13 (117); Gaspar, R., Pedro, C., Panagiotopoulos, P., Seibt, B., Beyond positive or negative: qualitative sentiment analysis of social media reactions to unexpected stressful events (2016) Computers in Human Behavior, 56, pp. 179-191; Gomes, R.F., Casais, B., Feelings generated by threat appeals in social marketing: text and Emoji analysis of user reactions to anorexia nervosa campaigns in social media (2018) International Review on Public and Nonprofit Marketing, 15 (4), pp. 591-607; Ha, J., Jang, S., Effects of service quality and food quality: the moderating role of atmospherics in an ethnic restaurant segment (2010) International Journal of Hospitality Management, 29 (3), pp. 520-529; Han, H.J., Mankad, S., Gavirneni, N., Verma, R., What guests really think of your hotel: text analytics of online customer reviews (2016) Cornell Hospitality Report, 16 (2), pp. 3-17; Hsu, L.M., Field, R., Interrater agreement measures: comments on kappan, cohen’s kappa, scott’s π, and aickin's α (2003) Understanding Statistics, 2 (3), pp. 205-219; Hyun, S.S., Predictors of relationship quality and loyalty in the chain restaurant industry (2010) Cornell Hospitality Quarterly, 51 (2), pp. 251-267; Islam, M.R., Zibran, M.F., SentiStrength-SE: exploiting domain specificity for improved sentiment analysis in software engineering text (2018) Journal of Systems and Software, 145, pp. 125-146; Jiménez Beltrán, J., López-Guzmán, T., Santa-Cruz, F.G., Gastronomy and tourism: profile and motivation of international tourism in the city of Córdoba, Spain (2016) Journal of Culinary Science and Technology, 14 (4), pp. 347-362; Jin, N., Lee, S., Huffman, L., Impact of restaurant experience on brand image and customer loyalty: moderating role of dining motivation (2012) Journal of Travel and Tourism Marketing, 29 (6), pp. 532-551; Kandampully, J., The impact of demand fluctuation on the quality of service: a tourism industry example (2000) Managing Service Quality: An International Journal, 10 (1), pp. 10-19; Karson, K., Murphy, K.S., Attracting local guests to resort food and beverage operations: the case of the Orlando resort and spa (2013) Journal of Foodservice Business Research, 16 (4), pp. 391-406; Kim, J., Boo, S., Influencing factors on customers’ intention to complain in a franchise restaurant (2011) Journal of Hospitality Marketing and Management, 20 (2), pp. 217-237; Kim, W.G., Kim, H.-B., Measuring customer-based restaurant brand equity (2004) Cornell Hotel and Restaurant Administration Quarterly, 45 (2), pp. 115-131; Kim, Y., Hertzman, J., Hwang, J., College students and quick-service restaurants: how students perceive restaurant food and services (2010) Journal of Foodservice Business Research, 13 (4), pp. 346-359; Kim, I., Jeon, S.M., Hyun, S.S., The role of effective service provider communication style in the formation of restaurant patrons’ perceived relational benefits and loyalty (2011) Journal of Travel and Tourism Marketing, 28 (7), pp. 765-786; Knight, A.J., Worosz, M.R., Todd, E.C.D., Serving food safety: consumer perceptions of food safety at restaurants (2007) International Journal of Contemporary Hospitality Management, 19 (6), pp. 476-484; Kreeger, J.C., Parsa, H.G., Smith, S.J., Kubickova, M., Calendar effect and the role of seasonality in consumer comment behavior: a longitudinal study in the restaurant industry (2018) Journal of Foodservice Business Research, 21 (3), pp. 342-357; Lak, P., Turetken, O., Star ratings versus sentiment analysis – a comparison of explicit and implicit measures of opinions (2014) 47th HI International Conference on System Sciences, pp. 796-805. , IEEE; LeDoux, J.E., Hofmann, S.G., The subjective experience of emotion: a fearful view (2018) Current Opinion in Behavioral Sciences, 19, pp. 67-72; Lee, H., Jai, T.-M., Li, X., Guests’ perceptions of green hotel practices and management responses on TripAdvisor (2016) Journal of Hospitality and Tourism Technology, 7 (2), pp. 182-199; Lee, H.A., Law, R., Murphy, J., Helpful reviewers in TripAdvisor, an online travel community (2011) Journal of Travel and Tourism Marketing, 28 (7), pp. 675-688; Lei, S., Law, R., Content analysis of TripAdvisor reviews on restaurants: a case study of Macau (2015) Journal of Tourism, 16 (1), pp. 17-28; Leung, D., Law, R., van Hoof, H., Buhalis, D., Social media in tourism and hospitality: a literature review (2013) Journal of Travel and Tourism Marketing, 30 (1-2), pp. 3-22; Lin, L., Mao, P.C., Food for memories and culture – a content analysis study of food specialties and souvenirs (2015) Journal of Hospitality and Tourism Management, 22, pp. 19-29; López Barbosa, R.R., Sánchez-Alonso, S., Sicilia-Urban, M.A., Evaluating hotels rating prediction based on sentiment analysis services (2015) Aslib Journal of Information Management, 67 (4), pp. 392-407; Lu, Y., Chen, Z., Law, R., Mapping the progress of social media research in hospitality and tourism management from 2004 to 2014 (2018) Journal of Travel and Tourism Marketing, 35 (2), pp. 102-118; Meehan, K., Lunney, T., Curran, K., McCaughey, A., Aggregating social media data with temporal and environmental context for recommendation in a mobile tour guide system (2016) Journal of Hospitality and Tourism Technology, 7 (3), pp. 281-299; (2018) 2018 Macao year of gastronomy officially kicks off Forges ahead as a creative city of Gastronomy, , www.gov.mo/en, accessed 29 November 2018; (2018) Macanese cuisine and recipes, , http://en.macaotourism.gov.mo, accessed 10 December 2018; (2019) Restaurants, , www.macaotourism.gov.mo/en/dining/restaurant, accessed 2 August 2019; Moder, K., How to keep the Type I error rate in ANOVA if variances are heteroscedastic (2007) Austrian Journal of Statistics, 36 (3), pp. 179-188; Munezero, D., MonteroSutinen, M., Pajunen, J., Are they different? Affect, feeling, emotion, sentiment, and opinion detection in text (2014) IEEE Transactions on Affective Computing, 5 (2), pp. 101-111; Namkung, Y., Jang, S.C.S., Are highly satisfied restaurant customers really different? A quality perception perspective (2008) International Journal of Contemporary Hospitality Management, 20 (2), pp. 142-155; Narangajavana Kaosiri, Y., Callarisa Fiol, L.J., Moliner Tena, M.Á., Rodríguez Artola, R.M., Sánchez García, J., User-generated content sources in social media: a new approach to explore tourist satisfaction (2019) Journal of Travel Research, 58 (2), pp. 253-265; Neuhofer, B., Buhalis, D., Ladkin, A., Conceptualising technology enhanced destination experiences (2012) Journal of Destination Marketing and Management, 1 (1-2), pp. 36-46; O’Connor, P., (2008) User-generated content and travel: a case study on tripadvisor.com, , Information and communication technologiestourism; Oh, H., Diners' perceptions of quality, value, and satisfaction: a practical viewpoint (2000) Cornell Hotel and Restaurant Administration Quarterly, 41 (3), pp. 58-66; Okumus, B., Okumus, F., McKercher, B., Incorporating local and international cuisines in the marketing of tourism destinations: the cases of Hong Kong and Turkey (2007) Tourism Management, 28 (1), pp. 253-261; Oliveira, B., Casais, B., The importance of user-generated photos in restaurant selection (2019) Journal of Hospitality and Tourism Technology, 10 (1), pp. 2-14; Pang, B., Lee, L., (2008) Opinion Mining and Sentiment Analysis, 2. , Foundations and Trends®Information Retrieval, London; Park, E., Chae, B., Kwon, J., The structural topic model for online review analysis (2018) Journal of Hospitality and Tourism Technology, 11 (1), pp. 563-572; Park, S.B., Jang, J., Ok, C.M., Analyzing Twitter to explore perceptions of Asian restaurants (2016) Journal of Hospitality and Tourism Technology, 7 (4), pp. 405-422; Poria, S., Cambria, E., Howard, N., Huang, G.-B., Hussain, A., Fusing audio, visual and textual clues for sentiment analysis from multimodal content (2016) Neurocomputing, 174, pp. 50-59; Rambocas, M., Pacheco, B.G., Online sentiment analysis in marketing research: a review (2018) Journal of Research in Interactive Marketing, 12 (2), pp. 146-163; Rosselló, J., Sansó, A., Yearly, monthly and weekly seasonality of tourism demand: a decomposition analysis (2017) Tourism Management, 60, pp. 379-389; Saif, H., He, Y., Fernandez, M., Alani, H., Contextual semantics for sentiment analysis of Twitter (2016) Information Processing and Management, 52 (1), pp. 5-19; Schuckert, M., Liu, X., Law, R., Hospitality and tourism online reviews: recent trends and future directions (2015) Journal of Travel and Tourism Marketing, 32 (5), pp. 608-621; Simeon, M.I., Buonincontri, P., Cinquegrani, F., Martone, A., Exploring tourists’ cultural experiences in Naples through online reviews (2017) Journal of Hospitality and Tourism Technology, 8 (2), pp. 220-238; Sipe, L.J., Testa, M.R., From satisfied to memorable: an empirical study of service and experience dimensions on guest outcomes in the hospitality industry (2018) Journal of Hospitality Marketing and Management, 27 (2), pp. 178-195; Soriano, R.D., Customers’ expectations factors in restaurants (2002) International Journal of Quality and Reliability Management, 19 (8-9), pp. 1055-1067; Su, C., The role of service innovation and customer experience in ethnic restaurants (2011) The Service Industries Journal, 31 (3), pp. 425-440; Su, W.Y., Bowen, J.T., Restaurant customer complaint behavior (2000) Journal of Restaurant and Foodservice Marketing, 4 (2), pp. 35-65; Sukalakamala, P., Boyce, J.B., Customer perceptions for expectations and acceptance of an authentic dining experience in Thai restaurants (2007) Journal of Foodservice, 18 (2), pp. 69-75; Swain, J., A hybrid approach to thematic analysis in qualitative research: using a practical example (2018) Sage Research Methods, , Sage, New York, NY; Thelwall, M., The heart and soul of the web? Sentiment strength detection in the social web with SentiStrength (2017) Cyberemotions, pp. 119-134. , Springer, Cham; Thelwall, M., Buckley, K., Paltoglou, G., Sentiment strength detection for the social web (2012) Journal of the American Society for Information Science and Technology, 63 (1), pp. 163-173; Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., Kappas, A., Sentiment strength detection in short informal text (2010) Journal of the American Society for Information Science and Technology, 61 (12), pp. 2544-2558; Tiago, T., Amaral, F., Tiago, F., The good, the bad and the ugly: food quality in UGC (2015) Procedia - Social and Behavioral Sciences, 175, pp. 162-169; Tsai, C.T., Wang, Y.C., Experiential value in branding food tourism (2017) Journal of Destination Marketing and Management, 6 (1), pp. 56-65; (2017) 64 cities join the UNESCO creative cities network, , https://en.unesco.org, accessed 10 December 2018; Varkaris, E., Neuhofer, B., The influence of social media on the consumers’ hotel decision journey (2017) Journal of Hospitality and Tourism Technology, 8 (1), pp. 101-118; Vilares, D., Thelwall, M., Alonso, M.A., The megaphone of the people? Spanish SentiStrength for real-time analysis of political tweets (2015) Journal of Information Science, 41 (6), pp. 799-813; Vu, H.Q., Li, G., Law, R., Zhang, Y., Exploring tourist dining preferences based on restaurant reviews (2019) Journal of Travel Research, 58 (1), pp. 149-167; Wan, Y.K.P., Assessing the strengths and weaknesses of Macao as an attractive meeting and convention destination: perspectives of key informants (2011) Journal of Convention and Event Tourism, 12 (2), pp. 129-151; Wu, Y., Zhang, D.Z., Demand fluctuation and chaotic behaviour by interaction between customers and suppliers (2007) International Journal of Production Economics, 107 (1), pp. 250-259; Xiang, Z., Du, Q., Ma, Y., Fan, W., A comparative analysis of major online review platforms: implications for social media analytics in hospitality and tourism (2017) Tourism Management, 58, pp. 51-65; Xiang, Z., Schwartz, Z., Gerdes, J.H., Uysal, M., What can big data and text analytics tell us about hotel guest experience and satisfaction? (2015) International Journal of Hospitality Management, 44, pp. 120-130; Xie, K.L., Chen, C., Wu, S., Online consumer review factors affecting offline hotel popularity: evidence from tripadvisor (2016) Journal of Travel and Tourism Marketing, 33 (2), pp. 211-223; Yu, C.E., Sun, R., The role of instagram in the UNESCO’s creative city of gastronomy: a case study of Macau (2019) Tourism Management, 75, pp. 257-268; Yu, Y., Mu, Y., Ateniese, G., Recent advances in security and privacy in big data (2015) Journal of Universal Computer Science, 21 (3), pp. 365-368; Yüksel, A., Yüksel, F., Measurement of tourist satisfaction with restaurant services: a segment-based approach (2003) Journal of Vacation Marketing, 9 (1), pp. 52-68; Zhang, Y., Yu, X., Urban tourism and the politic of creative class: a study of the chefs in Macao (2018) International Journal of Tourism Sciences, 18 (2), pp. 139-151; Zhang, Z., Ye, Q., Law, R., Li, Y., The impact of e-word-of-mouth on the online popularity of restaurants: a comparison of consumer reviews and editor reviews (2010) International Journal of Hospitality Management, 29 (4), pp. 694-700; Kimes, S., Anderson, C.K., (2011) Hotel revenue management in an economic downturn
PY - 2020/9/21
Y1 - 2020/9/21
N2 - Purpose: This study aims to quantify the underlying feelings of online reviews and discover the role of seasonality in customer dining experiences. Design/methodology/approach: This study applied sentiment analysis to determine the polarity of a given comment. Furthermore, content analysis was conducted based on the core attributes of the customer dining experiences. Findings: Positive feelings towards the food and the service do not show a linear relationship, while the overall dining experiences increase in line with the positive feelings on food quality. Moreover, feelings towards the atmosphere of the restaurants are the most positive in peak season. Practical implications: This study provides guidelines for restaurateurs regarding the aspects that need more attention in different seasons. Originality/value: The paper contributes to the knowledge of customer feelings in local restaurants/gastronomy and the role seasonality plays in fostering such feelings. In addition, the novel methodological procedures provide insights for tourism research in discovering new dimensions in theories based on big data. © 2020, Emerald Publishing Limited.
AB - Purpose: This study aims to quantify the underlying feelings of online reviews and discover the role of seasonality in customer dining experiences. Design/methodology/approach: This study applied sentiment analysis to determine the polarity of a given comment. Furthermore, content analysis was conducted based on the core attributes of the customer dining experiences. Findings: Positive feelings towards the food and the service do not show a linear relationship, while the overall dining experiences increase in line with the positive feelings on food quality. Moreover, feelings towards the atmosphere of the restaurants are the most positive in peak season. Practical implications: This study provides guidelines for restaurateurs regarding the aspects that need more attention in different seasons. Originality/value: The paper contributes to the knowledge of customer feelings in local restaurants/gastronomy and the role seasonality plays in fostering such feelings. In addition, the novel methodological procedures provide insights for tourism research in discovering new dimensions in theories based on big data. © 2020, Emerald Publishing Limited.
KW - Dining experience
KW - Local gastronomy
KW - Seasonality
KW - Sentiment analysis
KW - Service quality
KW - User-generated content
UR - https://www.mendeley.com/catalogue/a6c8bf74-4404-3e3d-be5b-2701b03614bd/
U2 - 10.1108/jhtt-02-2019-0028
DO - 10.1108/jhtt-02-2019-0028
M3 - Article
SN - 1757-9880
VL - 11
SP - 461
EP - 478
JO - J. Hosp. Tour. Technol.
JF - J. Hosp. Tour. Technol.
IS - 3
ER -