99 research outputs found
The Role Of Flow In Creating E-loyalty: The Case Of Online Hotel Booking Websites
This dissertation aims to examine the concept of ―online customer experience‖, ―flow‖, and its role in influencing online customers‘ loyalty to a hotel booking website. To achieve this aim, a model was developed, which proposed that online flow is generated by both hedonic and utilitarian website features. A model was developed based on literature review to measure the relationships between the constructs. To initiate this research, a survey approach was taken. After conducting a pilot study, a marketing company was contacted to distribute the link for the online questionnaire. Five hundred and eleven (511) questionnaires were completed by guests who booked a hotel room online. Participants completed the self-administered online questionnaire by answering questions related to their last hotel booking experience. Study results found that hedonic and utilitarian website features affect the flow experience positively. Results highlight that hedonic website features has a stronger effect on the flow experience compared to utilitarian ones. In addition, the results revealed that hedonic features positively impact brand equity and utilitarian features impact trust towards the hotel booking website. Further, both trust and brand equity have significant and positive relationship with e-loyalty. However, according to study results, flow experience does not have a direct significant effect on e-loyalty. The study findings suggest that consumers who are able to achieve a state of flow while shopping online will perceive higher brand equity and trust. Therefore, their perceptions of the brand are improved. With enhanced levels of trust and brand equity, consumers are more likely to build bonds and stay loyal to the hotel booking website. It is important to note that iv enhancing the brand equity and trust via hedonic and utilitarian website features is important to increase loyalty because flow experience does not directly influence loyalty. This study contributes to existing research on flow experience in several ways. Firstly, it developed and tested a model with precursors of flow experience in ecommerce by establishing a link between website features and flow experience. Antecedents and consequences of flow experience can help researchers understand when this experience occurs and what to expect from this optimal experience in online environments. Thus, this study makes a contribution to the existing literature by examining the effects of features of the website on flow experience. It is worth noting that in the model, hedonic website features had the largest impact on flow experience. This is particularly an important contribution, considering that precious related research examined variables such as attractiveness, novelty, playfulness, personal innovativeness, content of the website, interactivity, teleperesence and perceived ease of use as the precursors of flow experience, but they have not examined the website characteristics that derives from shopping orientations. Study results can give hotel booking website designers and marketers a better understanding of the online consumer experiences and loyalt
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Agent-based Modeling of Destination-Tourist Interactive Evolution
Given the pressing need to understand the macro-level tourist-destination interaction dynamics within the context of fast growing eWOM influences, the current study employs Agent-Based Modeling and simulates the tourist-destination interactive evolvement through the mediator of eWOMs. The visual and graphical outputs generated are global patterns that are otherwise not observable or hardly analyzable given the data inaccessibility for the scope of problem. Consequently, possible marketing or management strategies are experimented with simulation and proposed to facilitate tourist travel decisions and destination development
Online Hotel Booking Experience: Flow Theory, Measuring Online Customer Experience and Managerial Implications
The past decade has perceived a significant development of various Internet technologies including HTML5, Ajax, landing pages, CSS3, social media and SEO to name a few. New web technologies provide opportunities for e-commerce companies to enhance the shopping experiences of their customers. This article focuses the phenomenon of online experiences from a services marketing aspect by concentrating online hotel booking. Successful lodging management strategies have been associated with the creation of experience, which in turn leads to fruitful performance outcomes such as superior financial performance, enhanced brand image, customer loyalty, positive word of mouth and customer satisfaction. E-commerce researchers and practitioners also focus on the phenomenon of online customer experiences. Plentiful of previous studies investigated the precursors and consequences of positive online customer experiences by utilizing various marketing and Information Systems theories, and it was found that online customer experience has numerous positive outcomes for e-commerce companies. This study analyses the previous studies on customer experiences by utilizing flow theory and develops a conceptual framework of customer experiences. Later it proposes and tests a measurement model for online customer experiences. Our findings indicate that for successful e-commerce practices, online shoppers need to reach a state of mind where they engage with the website with total involvement, concentration and enjoyment. The traditional approaches to attract customers in brick-and-mortar commerce are not applicable in online contexts. Therefore, interaction, participation, co-creation, immersion, engagement and emotional hooks are important in e-commerce. Managerial and theoretical implications of positive online customer experiences were discussed
Importance-Performance Analysis of Guest Entertainment Technology Amenities in the Lodging Industry
An assessment of how hotel guests view in-room entertainment-technology amenities was conducted to compare the importance of these technologies to how they performed. In-room entertainment technology continues to evolve in the hotel industry. However, given the multitude of entertainment products available in the marketplace today, hoteliers have little understanding of guests’ expectations and of which in-room entertainment-technology amenities will drive guest satisfaction and increase loyalty to the hotel brand. Given that technology is integral to a hotel stay, this study seeks to evaluate the importance and performance of in-room entertainment-technology amenities. Findings indicate that free-to-guest television (FTG TV) and high-speed Internet access were the two most important inroom entertainment-technology amenities when it comes to the selection of a hotel for both leisure and business travelers. The Importance/Satisfaction Matrix presented in the current study showed that many of the in-room entertainment-technology amenities are currently a low priority for guests. Keywords: importance-performance analysis, hotel, in-room entertainment technologie
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Inner- versus Social-driven Travel Motivations among People with Mobility Challenges: Extending the Travel Motivation Interpretation with a New Horizon
Employing Self-determination Theory to explore travel motivational patterns among People with Mobility Challenges, this study extends the travel motivation conceptualization with a distinction of driving forces underlying travel motivations. The revealed variations in travel-facilitating effects and motivation-cultivating mechanisms across a spectrum of differentially driven motivations support the distinction. The cross-context reliability of the distinction was also checked through a challenge-level experimental manipulation. Specifically, the inner-driven self-determined motivations better facilitate PwMC’s travel pursuits when travel challenges are significant, whereas social-driven controlled motivations dominate travel facilitation at low-challenge levels. The support of autonomy, competence, and relatedness is found to facilitate both self-determined and controlled travel motivations, but setting self-determined pursuits apart from controlled pursuits at high-challenge levels. Moreover, this study introduces promising statistical approaches for competitively accurate and efficient comparison of correlated effects, useful for future applications in the tourism field
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Barriers to Information Technology Change Project in Hotels
The purpose of this study is to investigate the barriers and the sources of resistance to information technology (IT) change projects in hotel firms and evaluate strategies adopted in seeking to overcome these barriers. Based on an in-depth literature review, the authors developed an interview protocol. The authors will start collecting empirical data soon from the Information Technology Managers and the Hotel General managers in hotels in Orlando, FL. Based on the authors’ knowledge, this is one of the first research projects in the field that will provide empirical evidence on barriers to IT change projects and appropriate strategies in hotel companies
Research Note: Biometric Technology Applications and Trends in Hotels
The purpose of this study is to investigate the biometrics technologies adopted by hotels and the perception of hotel managers toward biometric technology applications. A descriptive, cross sectional survey was developed based on extensive review of literature and expert opinions. The population for this survey was property level executive managers in the U.S. hotels. Members of American Hotel and Lodging Association (AHLA) were selected as the target population for this study. The most frequent use of biometric technology is by hotel employees in the form of fingerprint scanning. Cost still seems to be one of the major barriers to adoption of biometric technology applications. The findings of this study showed that there definitely is a future in using biometric technology applications in hotels in the future, however, according to hoteliers; neither guests nor hoteliers are ready for it fully
A quantitative study exploring the difference between gaming genre preferences
Abstract Although gaming technologies have been in use for more than thirty years, there is a lack of academic research in this area. Specifically, the purpose of this study is to identify the difference between age and gender in gaming genre preferences. A cross sectional online survey was administered with a sample size of 408. It was found that there is a statistical difference between age groups and their gaming preferences with the older generation focusing more on strategic gaming offerings while the younger generation tended to side more with action games. The findings of this study provide insights for game developers
Combined artificial bee colony algorithm and machine learning techniques for prediction of online consumer repurchase intention
A novel paradigm in the service sector i.e. services through the web is a progressive mechanism for rendering offerings over diverse environments. Internet provides huge opportunities for companies to provide personalized online services to their customers. But prompt novel web services introduction may unfavorably affect the quality and user gratification. Subsequently, prediction of the consumer intention is of supreme importance in selecting the web services for an application. The aim of study is to predict online consumer repurchase intention and to achieve this objective a hybrid approach which a combination of machine learning techniques and Artificial Bee Colony (ABC) algorithm has been used. The study is divided into three phases. Initially, shopping mall and consumer characteristic’s for repurchase intention has been identified through extensive literature review. Secondly, ABC has been used to determine the feature selection of consumers’ characteristics and shopping malls’ attributes (with > 0.1 threshold value) for the prediction model. Finally, validation using K-fold cross has been employed to measure the best classification model robustness. The classification models viz., Decision Trees (C5.0), AdaBoost, Random Forest (RF), Support Vector Machine (SVM) and Neural Network (NN), are utilized for prediction of consumer purchase intention. Performance evaluation of identified models on training-testing partitions (70-30%) of the data set, shows that AdaBoost method outperforms other classification models with sensitivity and accuracy of 0.95 and 97.58% respectively, on testing data set. This study is a revolutionary attempt that considers both, shopping mall and consumer characteristics in examine the consumer purchase intention.N/
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