Online Traveling Research Articles

"Net" value co-creation: The effect of interactions on consumer citizenship behavior in online travel communities.

Online traveling community is initiated by companies, but its survival is inextricably linked to consumer citizenship behavior (e.g., out-group recommendation, in-group helping, and inward response). The majority of researches have investigated consumer behavior of brand community such as consumer satisfaction, brand loyalty, and purchase intention. A few scholars try to explore consumer behaviors beyond the purchase, like participation, which was concerned as the value co-creation. However, the value co-creation of the community should depend on consumers’ citizenship behaviors instead of their pure participation. Therefore, this study empirically examines the effect of consumer interaction on consumer psychology and citizenship behaviors of the online travel community. The findings demonstrated that consumer interaction facilitated participants’ self-identity and their perceived social support, which enhanced their community identification and thus their citizenship behaviors. Furthermore, the motivation of participation plays a moderator in this process. Specifically, symbolic motivation moderates the relationship between consumer interaction and their self-identity, while utilitarian motivation moderates the effect of consumer interaction on their perceived social support. These findings contributed to the intervention of consumer citizenship behavior in online traveling community and provide insights into the management of the online travel community from the perspective of the value co-creation.

A decision-making algorithm combining the aspect-based sentiment analysis and intuitionistic fuzzy-VIKOR for online hotel reservation.

In the process of hotel reservation on online traveling platforms, online reviews, as a fundamental source where the actual information of a product can be had access to, have been attached with high importance by customers when they have difficulty making a decision on which hotel to pick. However, with enormous amount of online reviews distributed in diverse online traveling platforms, customers tend to have few patience or time to manually read all these reviews and get the exact information they want. Inspired by the widespread application of aspect-based sentiment analysis in the field of data mining, a bidirectional long short-term memory (Bi-LSTM) and attention mechanism based model to predict multiple attributes of a product from online review texts is proposed. Experimental result shows that such Bi-LSTM with attention mechanism model apparently improves the accuracy of the prediction, compared with single LSTM model. Meanwhile, based on the output of the prediction, we analyze and transfer it into a statistical matrix. With an intuitionistic fuzzy compromise decision-making method VIKOR applied, an overall ranking, according to multiple product attributes can be made, in which way to help customers make decisions. To prove the rationality of the algorithm, online hotel reviews from three stream online travelling platforms are crawled as a case.

Behavioral intention of traveling in the period of COVID-19: an application of the theory of planned behavior (TPB) and perceived risk

PurposeThis paper aims to examine travelers’ behavioral intention of traveling in the period of coronavirus by using the theory of planned behavior. The framework incorporates attitude, subjective norms, perceived behavioral control and a very crucial construct, i.e. perceived risk, as per the current critical scenario of COVID-19.Design/methodology/approachData was collected using a survey instrument on the internet by posting the questionnaire link over social network web pages of online traveling websites. The data was analyzed using structural equations modeling with AMOS 22.0 and SPSS software and the proposed hypotheses were statistically tested. The sample under consideration constitutes 417 responses.FindingsEmpirical findings suggest that attitude, perceived behavioral control and perceived risk are significant for predicting behavioral intention while subjective norms do not. Then, these variables explained about 35% of the variance in the behavioral intention of traveling in the period of coronavirus.Research limitations/implicationsThis study can benefit travelers, the tourism and hospitality industry, governments, the aviation industry and other relevant organizations as this paper offers the latest updates and essential information regarding traveler’s intention of traveling in the period of coronavirus. The study mainly focuses on India, so the generalizations of results to other countries are unwanted.Originality/valueThe primary value of this paper is that it tested the theory of planned behavior by incorporating perceived risk in the context of COVID-19. To the best of the authors’ knowledge, in the Indian context, there is no study, which has tested the TPB by adding perceived risk in explaining the Indian citizens’ behavioral intention of traveling in the period of Coronavirus.

An Investigation of Purchase Intention of Using Mobile Apps for Online Traveling and Booking Service

An Investigation of Purchase Intention of Using Mobile Apps for Online Traveling and Booking Service

Commitment to Online Community and Continuance Intention: Issue Involvement, Interactivity, and Social Interaction

The purpose of this study is to investigate how issue involvement, online interactivity, and social interaction influence consumer commitment to online travel community and intention to continue participating in the community. An online traveling forum was examined as the issues being observed in this study are highly relevant to the forum. Based on 135 valid responses from active members of the forum obtained through distributing online questionnaire in the forum, structural equation modeling was employed to examine the research model. The results show that issue involvement and social interaction affect commitment to the community; while surprisingly social interaction does not have a significant influence on the commitment. Moreover, commitment to the community leads consumers to continue their participation in the community. Managerial contributions and limitations of the study are discussed.

On the power of lookahead in on-line server routing problems

We study the usefulness of lookahead in on-line server routing problems: if an on-line algorithm is not only informed about the requests released so far, but also has a limited ability to foresee future requests, what is the improvement that can be achieved in terms of the competitive ratio? We consider several on-line server routing problems in this setting, such as the on-line traveling salesman and the on-line traveling repairman problem. We show that the influence of lookahead can change considerably depending on the particular objective function and metric space considered.

A FLEXIBLE TRANSACTION FRAMEWORK FOR DYNAMIC COLLABORATION OF AGENTS–WITH AN ONLINE TRAVEL APPLICATION

The advancement of Internet-based commerce has created a turbulent market environment by allowing easier introduction of new products, services, and suppliers. For this dynamic environment, information systems need to be designed in a flexible way to meet the changing requirements. This paper proposes a flexible transaction framework for multi-agent systems so that agent systems can adapt to various types of changes in the dynamic electronic market environment. The flexible transaction framework consists of a flexible conversation model (FCM) for agents and an ontology meta-model called TOO (Task-Oriented Ontology) for the specific requirements of FCM. FCM permits agents to use newly acquired conversation policies that are induced by the frequent changes in transaction methods. Since FCM requires agents to be aware of a broader set of ontology entities, TOO is used to reduce the complexity of the ontology design and implementation for FCM. The flexible transaction framework is illustrated with an online traveling system developed for Korean domestic transportation services. The prospective synergy between the present work and Web services is discussed in the discussion section.

Successful Factors For A Travel Web Site: Perceptions Of On-Line Purchasers In Hong Kong

With the increasing popularity of on-line traveling, many studies have been stating numerous competitive advantages for setting up a travel Web site. However, the number of published articles that scrutinize the view of on-line travel purchasers on the factors for a successful travel Web site appears to be very limited. This research note reports on a study about investigating how on-line travel purchasers in Hong Kong view these successful factors. Empirical evidence from a large-scale omnibus survey indicates that 22.5% of the Hong Kong participants had visited one or more travel Web sites and that 6.54% of these e-travelers were also on-line travel purchasers. In general, e-buyers consider “secure payment methods” and “specifically designed for travelers in Asia Pacific” as the most and least important factors, respectively, for a successful travel Web site.

News from the online traveling repairman

In the traveling repairman problem (Trp), a tour must be found through every one of a set of points (cities) in some metric space such that the weighted sum of completion times of the cities is minimized. Given a tour, the completion time of a city is the time traveled on the tour before the city is reached. In the online traveling repairman problem (OLTrp) requests for visits to cities arrive online while the repairman is traveling. We analyze the performance of algorithms for the online problem using competitive analysis, where the cost of an online algorithm is compared to that of an optimal offline algorithm.We show how to use techniques from online-scheduling to obtain a deterministic algorithm with a competitive ratio of (1+2)2<5.8285 for the OlTrp in general metric spaces. We also present a randomized algorithm which achieves a competitive ratio of 4/ln3<3.6410 against an oblivious adversary. Our results extend to the “dial-a-ride” generalization L-OlDarp of the OlTrp, where objects have to be picked up and delivered by a server. This improves upon the previously best competitive ratio of 9 for the OlTrp on the real line and, moreover, the results are valid for any metric space. For the case of the L-OlDarp our algorithms are the first competitive algorithms.We also derive the first lower bounds for the competitive ratio of randomized algorithms for the OlTrp and the L-OlDarp against an oblivious adversary. Our lower bounds are (ln16+1)/(ln16−1)>2.1282 for the L-OlDarp on the line, (4e−5)/(2e−3)>2.41041 for the L-OlDarp on general metric spaces, 2 for the OlTrp on the line, and 73 for the OlTrp on general metric spaces.