Browsing by Author "Law, Rob"

Now showing 1 - 7 of 7
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    Applying image recognition techniques to visual information mining in hospitality and tourism
    Liu, Xianwei; Nicolau, Juan Luis; Law, Rob; Li, Chunhong (Emerald, 2022-10-31)
    Purpose: This study aims to provide a critical reflection of the application of image recognition techniques in visual information mining in hospitality and tourism. Design/methodology/approach: This study begins by reviewing the progress of image recognition and advantages of convolutional neural network-based image recognition models. Next, this study explains and exemplifies the mechanisms and functions of two relevant image recognition applications: object recognition and facial recognition. This study concludes by providing theoretical and practical implications and potential directions for future research. Findings: After this study presents different potential applications and compares the use of image recognition with traditional manual methods, the main findings of this critical reflection revolve around the feasibility of the described techniques. Practical implications: Knowledge on how to extract valuable visual information from large-scale user-generated photos to infer the online behavior of consumers and service providers and its influence on purchase decisions and firm performance is crucial to business practices in hospitality and tourism. Originality/value: Visual information plays a crucial role in online travel agencies and peer-to-peer accommodation platforms from the side of sellers and buyers. However, extant studies relied heavily on traditional manual identification with small samples and subjective judgment. With the development of deep learning and computer vision techniques, current studies were able to extract various types of visual information from large-scale datasets with high accuracy and efficiency. To the best of the authors’ knowledge, this study is the first to offer an outlook of image recognition techniques for mining visual information in hospitality and tourism.
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    A demand-driven analysis of tourist accommodation price: A quantile regression of room bookings [Summary]
    Nicolau, Juan Luis; Masiero, Lorenzo; Law, Rob (Virginia Tech, 2015-09)
    Tourist accommodation expenditure is a widely investigated topic as it represents a major contribution to the total tourist expenditure. The identification of the determinant factors is commonly based on supply-driven applications while little research has been made on important travel characteristics. This paper proposes a demand-driven analysis of tourist accommodation price by focusing on data generated from room bookings. The investigation focuses on modeling the relationship between key travel characteristics and the price paid to book the accommodation.
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    Impact of hotel website quality on online booking intentions: eTrust as a mediator [Summary]
    Wang, Liang; Law, Rob; Guillet, Basak Denizci; Hung, Kam; Fong, Davis Ka Chio (Virginia Tech, 2015-05)
    Growing competitiveness in the marketplace pushes hoteliers to fully take advantage of their websites as a marketing tool. This study proposed that a trusting relationship with customers could be developed by investing in hotel website development. A research model that incorporates hotel website quality, eTrust, and online booking intentions was put forward. The software AMOS 20.0 was adopted to analyze the proposed inter-variable relationships. Statistical results demonstrated that hotel website quality is a strong predictor of eTrust which then also mediates the relationship between website quality and consumers’ online booking intentions.
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    The impact of online user reviews on hotel room sales [Summary]
    Ye, Qiang; Law, Rob; Gu, Bin (Virginia Tech, 2009)
    Despite hospitality and tourism researchers’ recent attempts at examining different aspects of online word-of-mouth [WOM], its impact on hotel sales remains largely unknown in the existing literature. To fill this void, we conduct a study to empirically investigate the impact of online consumer-generated reviews on hotel room sales. Utilizing data collected from the largest travel website in China, we develop a fixed effect log-linear regression model to assess the influence of online reviews on the number of hotel room bookings. Our results indicate a significant relationship between online consumer reviews and business performance of hotels
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    The impact of website quality on customer satisfaction and purchase intentions: Evidence from Chinese online visitors [Summary]
    Bai, Billy; Law, Rob; Wen, Ivan (Virginia Tech, 2008-09)
    With the increasing popularity of online shopping and being the most populated country in the world, China is one of the major online markets now and is likely to become the largest market in the future. In the academic literature, website quality has generally been recognized as a critical step to drive business online. As such, numerous studies have been devoted to website quality and evaluations. Research efforts are, however, in need of understanding the use of websites in regards to online customers’ behavior, especially Chinese customers. This study developed and empirically tested a conceptual model of the impact of website quality on customer satisfaction and purchase intentions. Results indicated that website quality has a direct and positive impact on customer satisfaction, and that customer satisfaction has a direct and positive impact on purchase intentions. While the influence of website quality on purchase intentions exists, customer satisfaction does significantly mediate this effect. Drawing on the empirical findings, managerial implications and recommendations for future research are offered.
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    The influence of online reviews to online hotel booking intentions [Summary]
    Zhao, Xinyuan (Roy); Wang, Liang; Guo, Xiao; Law, Rob (Virginia Tech, 2015)
    This study aims to investigate the impacts of online review and source features upon travelers’ online hotel booking intentions.
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    Repeat Customers and Satisfaction: Uncovering New Intricacies Through Restaurant Reviews
    Ji, Xiaoxian; Nicolau, Juan Luis; Law, Rob; Liu, Xianwei (Sage, 2022-12-14)
    Repeat customers are crucial for business success. Previous studies have mainly focused on those factors that affect repeat patronage but ignored how repeat customers reevaluate the same service provider after consumption. We obtained a dataset containing 637,748 reviews of restaurants in New York City and used a generalized difference-in-differences design to further explore the rating behavior of local repeat customers. The results of this study contribute to theories of customer satisfaction, repeat patronage, and customer location in the context of user-generated content as repeat customers are found to be sensitive to quality variations. Such sensitivity is even accentuated by local customers. Relevant practical implications for restaurant managers are also drawn from the results.