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游客接受手机APP的因素有哪些? 以延伸整合型科技接受模式(UTAUT2) 为框架的研讨 摘要

Purpose – This paper investigates cancellations and no-shows in hotel reservations using granular transaction data from a property management system. The aim is to identify typical behavioural patterns of guests who cancel their stays or fail to attend. Methodology/Design/Approach – A dataset of 33,263 reservations was analysed using the CHAID decision tree model. Classification included various nominal and continuous variables: reservation status, number of guests, length of stay, distribution channel, gross rate, rate type, lead time, and number of rooms. Findings – The analysis revealed that cancellations are more likely for reservations with long lead times and flexible cancellation policies. No-shows are more frequently associated with bookings at lower gross rates. Reservations made via intermediaries such as OTAs and wholesalers show higher cancellation and no-show rates compared to other channels. Originality of the research – The study’s originality stems from the use of detailed user transaction data, offering empirical evidence of customer behaviour in the hotel booking process. By analysing real operational data, the study contributes to a deeper understanding of cancellation and no-show behaviour, supporting more accurate forecasting and revenue management strategies in the hospitality industry.

Court-related fines and fees are widely levied on criminal defendants who are frequently poor and have little capacity to pay. Such financial obligations may produce a criminalization of poverty, where later court involvement results not from crime but from an inability to meet the financial burdens of the legal process. We test this hypothesis using a randomized controlled trial of court-related fee relief for misdemeanor defendants in Oklahoma County, Oklahoma. We find that relief from fees does not affect new criminal charges, convictions, or jail bookings after 12 months. However, control respondents were subject to debt collection efforts at significantly higher rates that involved new warrants, additional court debt, tax refund garnishment, and referral to a private debt collector. Despite significant efforts at debt collection among those in the control group, payments to the court totaled less than 5 percent of outstanding debt. The evidence indicates that court debt charged to indigent defendants neither caused nor deterred new crime, and the government obtained little financial benefit. Yet, fines and fees contributed to a criminalization of low-income defendants, placing them at risk of ongoing court involvement through new warrants and debt collection.

PurposeThis paper aims to explore how relative advantages, compatibility, perceived ease of use and perceived usefulness affect hotel room self-directed booking (SDB) behavior, specifically focusing on the mediating role of trust.Design/methodology/approachThe research utilized the responses of 432 hotel guests, applying an extended technology acceptance model (TAM)− innovation diffusion theory (IDT)−trust framework and using partial least squares structural equation modeling to conduct both direct and indirect path analyses to confirm the study hypotheses.FindingsResults show that perceived relative advantages, compatibility, usefulness and ease of use of the online booking platform significantly impact guests’ SDB behavior, with trust significantly mediating each of the proposed relationships, highlighting its crucial role in promoting online booking behavior.Research limitations/implicationsThis study underscores the importance of SDB providers’ showcasing the benefits and efficiency of online booking systems in influencing consumer decisions, offering new insights into how technological advancements affect SDB behavior in the hotel industry.Originality/valueBy integrating TAM, IDT and trust into an integrated framework, this study provides a comprehensive understanding of the diverse factors influencing hotel guest engagement with SDB, offering practical insights to enhance guest satisfaction with the SDB platform.

Seaports, the nodal and bottleneck points in the global supply chain network, have been making effort to encourage shipping companies to book berths before ships arrive at the ports. The information and communication technology (ICT) system is essential for the success of this effort. We propose an appointment mechanism with a refund policy for the berth booking ICT system to mitigate port congestion. Two refund policies are investigated: cash refund policy and coupon refund policy. We develop a bi-level model that considers the interests of the port and shipping companies, with which the cash refund policy determines its optimal booking fee and the returned cash, and the coupon refund policy determines its optimal booking fee, the value of the coupon, and the shelf life of the coupon. Numerical experiments are conducted to analyze the two refund policies, the reactions of shipping companies with different characteristics, and how the port takes advantage of the characteristics of shipping companies to maximize profit. The proposed appointment mechanism achieves a win-win performance for the port and shipping companies as it increases the income of the port and reduces the delay cost of shipping companies. This study innovatively investigates the refund policy for the berth booking system and helps understand the mechanism of the system, thereby providing theoretical support for applying the berth booking system in the maritime industry. Moreover, this study contributes to alleviating port congestion and to environmental sustainability by reducing ship emissions caused by waiting at port and inappropriate sailing speed.

The tourism industry has undergone significant transformation with the rise of digital technologies, particularly online booking systems. E-booking platforms have revolutionised how customers plan and book their travel, offering convenience, cost-efficiency, and the ability to access real-time information through smartphones and other digital devices. These systems not only streamline administrative and operational tasks for businesses but also provide valuable insights by analysing customer data to tailor services and predict trends. This study explores the critical role of e-booking in the digital era of tourism, employing cluster analysis to group countries by their adoption and performance of e-booking services. The findings highlight the growing global reliance on e-booking platforms and their potential to enhance the customer experience and optimise business operations.

With the rapid development of information technology in hotel booking context, it is no doubt that many hotels consequently enhance the needs of integrating information technologies into their overall business operations. In this study, we developed a research model which consists of perceived value, trust toward a third party online booking site, and trust toward hotels, and tested it by using partial least square techniques. Survey data were collected from 307 individuals who have prior experiences on making a reservation using third-party online booking sites. Based upon our findings, we found that the perceived value, which was affected by both price and quality, was positively related to individuals’ intention to book. We also found that both trust toward third-party online booking sites and trust toward hotels, which was influenced by online review, have positive impacts on individuals’ intention to book. The implications of these findings for both research and practice are discussed.

Within the fast paced digital transformation of the tourism and hospitality sector, the modalities of booking a tourist accommodation have been radically transformed by the uptake of digital business models and digital platforms. This study examines the underlying mechanisms and key specificities of digital business models for two of the sector’s sub-segments—hotel accommodation bookings and yacht charter accommodation bookings. Based on the literature review findings, the case study method was applied in relation to key digital business models relevant for hotel bookings. On the other end, in relation to the yacht charter segment and its digital business models, an empirical research was conducted, encompassing a final sample of 162 yacht charter agencies from 42 countries worldwide. The analyzed digital business models have multiple similarities, while there are specific differences between the two hospitality segments. Even though digital business models are highly important in both segments, they are generally more developed and sophisticated in the hotel segment, which is related to the segment’s sheer size, in comparison with the younger and smaller yacht charter segment. The novelty is reflected in shedding more light on the characteristics of digital business models in the fast-developing yacht charter segment, including through an empirical study.

As people feel more comfortable using the Internet, online hotel bookings has become popular in recent years. Understanding the drivers of online booking intention and behavior can help hotel managers to apply corresponding strategies to increase hotel booking rates. Thus the purpose of this study is to investigate the factors influencing the use intention and behavioral intention of online hotel booking. The proposed model has assimilated factors from the extended Unified theory of Acceptance and use of Technology (UTAUT2) along with age, gender, and experience as moderators. Data were collected by conducting a field survey questionnaire completed by 488 participants. The results showed that behavioral intention is significantly and positively influenced by performance expectancy, social influence, facilitating condition, hedonic motivation, price value, and habit behavior. Use behavior is positively influenced by facilitating condition and hedonic motivation. As for moderators, gender moderates the relationships between performance expectancy, social influence, and behavioral intention. Age moderates the relationships between effort expectancy, social influence, hedonic motivation, and behavioral intention. Experience moderates the relationships between social influence, price value, and behavioral intention and between habit behavior and use behavior. Based on the results, recommendations for hotel managers are proposed. Furthermore, research limitations and future directions are discussed.

It is now well understood that social media plays an increasingly important role in consumers’ decision making. However, an overload of social media content in product search engines can hinder consumers from efficiently seeking information. We propose a structural econometric model to understand consumers’ preferences and costs on search engines to improve user experience under unstructured social media. Our model combines an optimal stopping framework with an individual-level random utility choice model and analyzes click behavior in conjunction with purchase choices. Our model accounts for three major constraints in a consumer’s decision-making process: (1) interdependency in decision making for different alternatives, (2) sequential arrival of information revealed by click-throughs, and (3) nonnegligible search cost. Our approach allows us to jointly estimate consumers’ heterogeneous preferences and search costs under the interplay of social media and search engines, and to predict search and purchase behavior for each consumer. We validate the model using an individual session-level data set of approximately seven million observations resulting in room bookings in 2,117 U.S. hotels. Interestingly, our analysis allows us to quantify the trade-off between consumers’ benefits and cognitive costs from using large-scale unstructured social media information during decision making. Our policy experiments show that providing a carefully curated digest of social media content during the earlier stages of consumer search (i.e., on the search results summary page) can lead to a 12.01% increase in the overall search engine revenue. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2991 . This paper was accepted by Anandhi Bharadwaj, information systems.