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The 21st century is witnessing an influence of social media on consumer behaviour, and social media now has a significant impact on the variety of consumer’s aspects, such as awareness of products, purchase behavior, opinions, and evaluation of products (Mangold & Faulds, 2009). After most businesses started selling their products or doing advertisement online, most of consumers focused on online reviews before purchasing products (Suresh, Roohi, Eirinaki, & Varlamis, 2014). Also, many companies are providing peer-to-peer reviews on their webpages. For instance, Amazon encourages consumers to engage with online reviews, and recommendations of either same or different products. One of the main benefits of these reviews is that consumers may inform others about their experiences (Parikh, Behnke, Vorvoreanu, Almanza, & Nelson, 2014). In addition, online research and bookings have affected consumer purchasing behaviours for hospitality services (Ong, 2012). Hospitality companies have been adopting to opportunities of online reviews on social media websites. Consequently, consumers’ previous experience might have influenced other users (Kwok & Yu, 2012).
Restaurant firms have taken advantage of social media by collecting consumers’ feedback about their brands and using it for advertising (Zhang, Ye, Law, & Li, 2010). Also, restaurateurs need to be aware of the opportunities of user generated restaurant reviews. User generated restaurant review sites contain restaurant experiences from the consumer’s perspective (Parikh et al., 2014). Online restaurant reviews provide massive data that include consumer feedback, consumer rating, price level, and type of food and locations (Jurafsky, Chahuneau, Routledge, & Smith, 2014). Previous study measured the review quantity by the number of online reviews of a product. They concluded that the review quantity may have been represented as a product popularity, and a high number of online reviews mainly leads consumers to purchase (Park, Lee, & Han, 2007). Restaurant consumers’ experiences were studied in online reviews platform in London and the author mentioned that repeated six aspects may influence restaurant consumers’ decision process. Also, six of aspects were stated respectively; food, service, atmosphere, price, menu and design (Chaves, Laurel, Sacramento, & Pedron, 2014). Overall food quality and service quality are the most critical factor influencing consumers’ repurchasing in restaurant (Harrington, Ottenbacher, & Kendall, 2011).
Consumer review websites, such as Yelp, TripAdvisor and Angie’s List, have been increasing in popularity, and they offer reviews for almost every product and service. Yelp.com was founded in 2004, and is a functional review platform for consumers. It is helping consumers to select local organizations, such as restaurants, bars, etc. (Luca & Zervas, 2016). Yelp.com has 142 million visitors in 2015 and it has 2.1 million various of organizations which have been registered (Prasad, Ganguly, Mukherjee, Kumari, & Kumar, 2016). Approximately 30 countries have been using Yelp.com world-wide (Alasmary et al., 2015).
Furthermore, restaurant industry has observed that the different types of consumers’ attributes may express in restaurant online reviews and restaurateurs can evaluate which qualifications make consumers’ to revisit (Chaves et al., 2014). The group of expectations were mentioned in previous study and they can influence the consumer’s revisit decisions at a restaurant and it was listed respectively, service quality, food quality, atmosphere and food price value (Soriano, Domingo, 2002). In this work, this study addresses four aspects of restaurant services in the industry using previous researchers’ works. Four aspects will be estimate in online platform and restaurant consumers’ may be aware of restaurant overall qualities before making decision. Also, the number of online reviews and rating scale … (Actullay Professor, my main thought is that number of reviews and rating scale. How these items influence consumers’ decision? I couldn’t find the place insert these subjects).
Alasmary, M., Bedell, L., Erickson, T., Ferge, J., Graham, T., Kashpazha, A., … Phillips, C. (2015). Projects in geospatial data analysis: Spring 2015. Computer Science Technical Reports. Retrieved from http://scholar.colorado.edu/csci_techreports/1035
Chaves, M. S., Laurel, A., Sacramento, N., & Pedron, C. D. (2014). Fine-grained analysis of aspects, sentiments and types of attitudes in restaurant reviews. Tourism & Management Studies, 10(1), 66–72.
Harrington, R. J., Ottenbacher, M. C., & Kendall, K. W. (2011). Fine-dining restaurant selection: Direct and moderating effects of customer attributes. Journal of Foodservice Business Research, 14(3), 272–289. http://doi.org/10.1080/15378020.2011.594388
Jurafsky, D., Chahuneau, V., Routledge, B. R., & Smith, N. A. (2014). Narrative framing of consumer sentiment in online restaurant reviews. First Monday, 19(4). Retrieved from http://uncommonculture.org/ojs/index.php/fm/article/view/4944
Kwok, L., & Yu, B. (2012). Spreading social media messages on facebook: An analysis of restaurant business-to-consumer communications. Cornell Hospitality Quarterly, 1938965512458360. http://doi.org/10.1177/1938965512458360
Luca, M., & Zervas, G. (2016). Fake it till you make it: Reputation, competition, and Yelp review fraud. Management Science. http://doi.org/10.1287/mnsc.2015.2304
Mangold, W. G., & Faulds, D. J. (2009). Social media: The new hybrid element of the promotion mix. Business Horizons, 52(4), 357–365.
Ong, B. S. (2012). The perceived influence of user reviews in the hospitality industry. Journal of Hospitality Marketing & Management, 21(5), 463–485. http://doi.org/10.1080/19368623.2012.626743
Parikh, A., Behnke, C., Vorvoreanu, M., Almanza, B., & Nelson, D. (2014). Motives for reading and articulating user-generated restaurant reviews on Yelp. com. Journal of Hospitality and Tourism Technology, 5(2), 160–176.
Park, D.-H., Lee, J., & Han, I. (2007). The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement. International Journal of Electronic Commerce, 11(4), 125–148. http://doi.org/10.2753/JEC1086-4415110405
Prasad, U., Ganguly, N., Mukherjee, A., Kumari, N., & Kumar, M. (2016). The role of outsiders in consensus formation: A case study of Yelp. In Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work and Social Computing Companion (pp. 425–428). New York, NY, USA: ACM. http://doi.org/10.1145/2818052.2869090
Soriano, Domingo. (2002). Customers’ expectations factors in restaurants: The situation in Spain. International Journal of Quality & Reliability Management, 19(8/9), 1055–1067. http://doi.org/10.1108/02656710210438122
Suresh, V., Roohi, S., Eirinaki, M., & Varlamis, I. (2014). Using social data for personalizing review rankings. In RSWeb@ RecSys. Retrieved from https://pdfs.semanticscholar.org/654f/dac05adf0bf4765efdcc9a1b9720a2707465.pdf
Zhang, Z., Ye, Q., Law, R., & Li, Y. (2010). The impact of e-word-of-mouth on the online popularity of restaurants: A comparison of consumer reviews and editor reviews. International Journal of Hospitality Management, 29(4), 694–700. http://doi.org/10.1016/j.ijhm.2010.02.002ss in restaurant online reviews and restaurateurs can evaluate which qualifications make consumers’ to revisit (Chaves et al., 2014). The group of expectations were mentioned in previous study and they can influence the consumer’s revisit decisions at a restaurant and it was listed respectively, service quality, food quality, atmosphere and food price value (Soriano, Domingo, 2002). In this work, this study addresses four aspects of restaurant services in the industry using previous researchers’ works. Four aspects will be estimate in online platform and restaurant consumers’ may be aware of restaurant overall qualities before making decision. Also, the number of online reviews and rating scale … (Actullay Professor, my main thought is that number of reviews and rating scale. How these items influence consumers’ decision? I