• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.83-90
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• 2023

This study aims to determine the direct effect of positive online reviews, negative online reviews, the usefulness of online reviews, reviewers' expertise, timeliness of online reviews, the volume of online reviews, and comprehensiveness of online reviews on accommodation booking intentions and also the indirect effect of positive online reviews on the intention of booking accommodations through trust as mediation. Research respondents are users of the accommodation booking application in Yogyakarta. Hypothesis testing was carried out using SEM (Partial Least Square). Data was collected by distributing questionnaires to 135 respondents. The results of this study indicate that the Usefulness of Online Reviews, Volume of Online Reviews, and Comprehensiveness of Online Reviews have a direct positive and significant influence on the accommodation booking Intention of booking application users in Yogyakarta. The variables of Negative Online Reviews and Timeliness of Online Reviews have negative and significant influences on the accommodation booking Intention of booking application users in Yogyakarta. Positive Online Reviews and Reviewer Expertise variables are not significant in this study. At the same time, the Trust variable has a full mediation relationship in an indirect relationship between the Positive Online Reviews variables and the accommodation booking Intention of booking application users in Yogyakarta.

• Journal of Distribution Science
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• v.16 no.4
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• pp.21-34
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• 2018

Purpose - The objective of this research is to a) examine the effects of online reviews, posted on online distribution channels, on the change of consumers' attitudes and booking intention by distinguishing three types of online review valence: positive, negative and neutral review valence, and b) to investigate the combined effect of the inclination of online review and perceived usefulness of reviews on consumers' attitude change. Research design, data, and methodology - An experimental design was used by creating a mimicked hotel company's website and online reviews extracted from several online distribution channels such as online travel agencies (OTAs). A total of 414 respondents were randomly assigned to a type of review valence. Results - The results showed that the valence of positive reviews has a significant effect on the positive change of attitude and booking intention. However, the effect of the valence of negative reviews on the change of booking intention was not statistically significant compared to that of the valence of neutral reviews. Conclusions - The results offer some insights into the effect of online reviews on consumers' decision making processes and have important managerial implications for companies that operate online distribution channels in terms of their online marketing and the distribution of service products.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.187-199
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• 2022

The purpose of this study was to offer a new conceptual framework based on a combination of the TPB model, the TAM model, and two additional constructs consisting of eWOM and pricing value called the E-P-TAM-TPB model, and to assess the model's implications on hotel selection behavior. This study empirically examines the E-P-TAM-TPB model to evaluate and validate domestic tourists' online hotel booking intentions by using the partial least squares structural equation modeling (PLS-SEM) approach. The data was collected from 355 domestic tourists who booked the room via the hotel website. The major findings of this study indicated that the E-P-TAM-TPB model has a positive significant influence on online hotel selection behavior. The results revealed that all proposed hypotheses were declared supported. Future studies should build on the framework by incorporating potential moderators to better understand how different groups of customers behave online in different segments of the hospitality industry. Managers must not only develop an easy booking process but also provide price value information to attract or impress clients. Tourists can compare room rates with other hotel websites and OTAs.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.519-529
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• 2022

Many consumers are opting for online booking over traditional booking systems. Customers can actively seek out information about hotels and lodging services, as well as book rooms, at any time and from any location. Customers also feel more supported when they interact with virtual assistants or professionals. Recognizing this issue, several hotels have focused on improving their websites by incorporating aspects that encourage customers to book directly through the hotel's website. The study's goal is to discover what factors impact people's decisions to book a hotel stay through the hotel's website. Therefore, hotel managers and owners can make decisions to improve the hotel website to attract residents to Can Tho City. The factors are website quality, affective commitment, social presence, and e-trust that affect customers' decision to book through the hotel website. The study uses quantitative methods to collect data from 180 residents living in Can Tho. Through data analysis on SPSS and Amos software, the research results show that three factors considered, namely website quality, affective commitment, and social presence, positively influence customers' booking decisions. This finding also suggests that e-trust is less critical to residents in Can Tho City, different from what the study had predicted.

• International Commerce and Information Review
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• v.8 no.2
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• pp.187-210
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• 2006

China continues to experience an expansion of its e-Commerce industry. This is true both for B2C and for B2B sectors. B2C websites are created by various players. B2C E-commerce is divided into three categories in China: online direct sale, online retail, and online booking services. Online retail remains the major form of B2C business, and online booking services and online direct sale also maintained rapid growth. The rapid growth of B2C E-commerce in China was due to three factors. Firstly, the number of Internet users is increasing, which expands E-commerce user base. Secondly, users' acceptance and recognition of E-commerce are gradually increasing. Lastly, improvement on payment, logistics and credit also provides a better and better industrial environment for B2C e-commerce. The B2C sector has seen a low transaction volume in spite of its large number of websites. The B2B sectors has seen a higher transaction volume and more stable growth than the B2C sector. There is a wide range of the total market size estimated by different sources. China's C2C market witnessed rapid growth in 2005, the market growth may slow down in 2006 and 2007, due to heavy market competition, challenges to the business model and slow corporate user growth. But there is the bottlenecks in E-commerce in China. The purpose of this paper is contribute to development E-commerce in China by finding the solutions of the bottlenecks in E-commerce in China.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.127-133
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• 2019

A callable product is one of service derivatives using options to generate demand and reduce risk. This paper compares two booking admission controls for callable products, the online and the batch admission controls. To this end, the paper computes the optimal booking policy by using the backward dynamic programming and the stochastic optimization method. Intuitively, the provider should outperform under the batch control by utilizing demand information. The contribution of the paper is to show that the two controls are equivalent in terms of the booking strategy and the expected profit, which enables the provider to keep its current control method. The paper develops the closed-form solutions for the three fare classes. The future work is to extend the result to the model with complicated fare structures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2609-2626
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• 2023

The hotel industry is an example of experiential services. As consumers cannot fully evaluate the online review content and quality of their services before booking, they must rely on several online reviews to reduce their perceived risks. However, individuals face information overload owing to the explosion of online reviews. Therefore, consumer cognitive fluency is an individual's subjective experience of the difficulty in processing information. Information complexity influences the receiver's attitude, behavior, and purchase decisions. Individuals who cannot process complex information rely on the peripheral route, whereas those who can process more information prefer the central route. This study further discusses the influence of the complexity of review information on hotel ratings using online attraction review data retrieved from TripAdvisor.com. This study conducts a two-level empirical analysis to explore the factors that affect review value. First, in the Peripheral Route model, we introduce a negative binomial regression model to examine the impact of intuitive and straightforward information on hotel ratings. In the Central Route model, we use a Tobit regression model with expert reviews as moderator variables to analyze the impact of complex information on hotel ratings. According to the analysis, five-star and budget hotels have different effects on hotel ratings. These findings have immediate implications for hotel managers in terms of better identifying potentially valuable reviews.

• Journal of Distribution Science
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• v.19 no.7
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• pp.113-121
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• 2021

Purpose: Technology induces the virtual distribution channel to exist, especially for booking a room online. This situation, indeed, provides an alternative for the customers to book based on their budget through digital platforms. One platform offering competitive prices is virtual hotel operators, such as Airbnb, OYO, RedDoorz, and Airy Rooms. Preferably, after using their platform, the user should be satisfied and loyal. Hence, this investigation aims to prove some associations. The first is between e-satisfaction and e-loyalty. The second is between website quality and e-satisfaction. The final is between website quality and e-loyalty. Research design, data, and methodology: This study is quantitatively designed with the sample of 350 users of the virtual hotel operator applications in Bandar Lampung: Airbnb, OYO, RedDoorz, and Airy, as the samples. Therefore, by denoting this sample size, the structural equation model based on covariance is utilized to examine the three hypotheses proposed. Also, to get the responses, this study uses a survey through a questionnaire. Result: This investigation demonstrates the positive relationship between e-satisfaction and e-loyalty. Additionally, website quality positively associates with e-satisfaction and e-loyalty. Conclusion: The virtual hotel operators must have the superiority on their website-based application to update the information based on the room availability and price, ensure online transaction safety, and facilitate its utilization to maintain long-term satisfaction and loyalty virtually.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.443-451
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• 2021

The classification standards for hotels in Vietnam are different from many other hotel classification standards in the world. This study aims to analyze customer reviews on the TripAdvisor website to develop a new algorithm for hotel rating that is independent of Vietnam's hotel classification standards. This method can be applied to individual hotels, or hotels of a region or the whole country, while online booking sites only rate individual hotels. Data was crawled from TripAdvisor with 22,287 reviews of 5 cities in Vietnam. This study used a statistical model to analyze the review dataset and build an algorithm to rate hotels according to aspects or hotel overall. The results have less rating deviation when compared to the TripAdvisor system. This study also supports hotel managers to regularly update the status of their hotels using data from customer reviews, from which, managers can strategize long-term solutions to improve the quality of the hotel in all aspects and attract more travelers to Vietnam. Moreover, this method can be developed into an automatic system to rate hotels and update the status of service quality more quickly, thus, saving time and costs.

• ETRI Journal
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• v.44 no.4
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• pp.624-640
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• 2022

Taxi-demand forecasting and hotspot prediction can be critical in reducing response times and designing a cost effective online taxi-booking model. Taxi demand in a region can be predicted by considering the past demand accumulated in that region over a span of time. However, other covariates-like neighborhood influence, sociodemographic parameters, and point-of-interest data-may also influence the spatiotemporal variation of demand. To study the effects of these covariates, in this paper, we propose three models that consider different covariates in order to select a set of independent variables. These models predict taxi demand in spatial units for a given temporal resolution using linear and ensemble regression. We eventually combine the characteristics (covariates) of each of these models to propose a robust forecasting framework which we call the combined covariates model (CCM). Experimental results show that the CCM performs better than the other models proposed in this paper.