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This study aims to examine consumer perception during COVID-19 and identifies cruise industry marketing strategies to fill a gap in crisis management and product pricing literature.

This study developed and validated two-factor measurement scales (vaccine perception and protective behavior), which predicted cruise intents well. This study revealed how geo-regional factors affect consumer psychology through spatial analysis.

This study recommended pricing 7-day cruises at $1,464 (the most preferred length). The results also showed that future price hikes would not affect demand and that coastal marketing would help retain customers.

This study contributed to the business, hospitality and tourism literature by identifying two new and unique factors (vaccine perception and protective behaviors), which were found to affect consumers’ intention to travel by cruise significantly. The result provided a better understanding of cruise tourists’ pricing preferences and the methods utilized could easily be applied to other cruise markets or tourism entities.

This study aims to evaluate Artificial Intelligence (AI) research in the hospitality industry based on the service AI framework (mechanical-thinking-feeling) and highlight prospective avenues for future inquiry in this growing domain.

This paper conceptualizes timely concepts supported by research spanning multiple domains.

This research introduces a novel classification for the domain of AI hospitality research. This classification encompasses prediction and pattern recognition, computer vision, NLP, behavioral research, and synthetic data generation. Based on this classification, this study identifies and elaborates upon five emerging research topics, each linked to a corresponding set of research questions. These focal points encompass the realms of interpretable AI, controllable AI, AI ethics, collaborative AI, and synthetic data generation.

This viewpoint provides a foundational framework and a directional compass for future research in AI within the hospitality industry. It pushes the industry forward with a balanced approach to leveraging AI to augment human potential and enrich customer experiences. Both the classification and the research agenda would contribute to the body of knowledge that will guide the industry toward a future where technology and human service coalesce to create unparalleled value for all stakeholders.

This study aims to extend the cognitive appraisal theory by developing and validating a conceptual framework to illustrate how travelers' behavioral intention is generated via a multi-stage evaluation of health-related variables.

SEM and moderator analysis were conducted to examine the theoretical framework (post-intervention event travel intention) and to investigate how the appraisal process differs across travelers with various attitudes toward vaccination.

This study found that cruise travel intention was positively influenced by the perceived hedonic value and perceived trustworthiness and negatively influenced by perceived infection risk. Furthermore, whereas perceived hedonic value, perceived trustworthiness and perceived risk of infection were all predicted by crisis management, the dimensions of crisis management operated differently. In addition, vaccination attitudes amplified the unfavorable effect of perceived risk on intention.

Drawing on the CAT, this study developed and validated a conceptual framework to integrate crisis management with customers' behavioral intentions. This study extends existing cruise travel intention theory by demonstrating how post-pandemic travelers' behavioral intention is generated via a multi-stage appraisal-reappraisal process based on the evaluations of infection risks and cruise line crisis management.

In a boundary layer ingestion (BLI) propulsion system, the fan operates continuously under distorted inflow conditions, leading to an increment of aerodynamic loss and in turn impacting the potential fuel burn reduction of the aircraft. Usually, in the preliminary design stage of a BLI propulsion system, it is essential to assess the impact of fuselage boundary layer fluids on fan aerodynamic performances under various flight conditions. However, the hub region flow loss is one of the major loss sources in a fan and would greatly influence the fan performances. Moreover, the inflow distortion also results in a complex and highly nonlinear mapping relation between loss and local physical parameters. It will diminish the prediction accuracy of the commonly used low-fidelity computational approaches which often incorporate traditional physics-based loss models, reducing the reliability of these approaches in evaluating fan performances. Meanwhile, the high-fidelity full-annulus unsteady Reynolds-averaged Navier–Stokes (URANS) approach, even though it can give rather accurate loss predictions, is extremely time-consuming. This study aims to develop a fast and accurate hub loss prediction method for a BLI fan under distorted inflow conditions.

This paper develops a data-driven hub loss prediction method for a BLI fan under distorted inflows. To improve the prediction accuracy and applicability, physical understandings of hub flow features are integrated into the modeling process. Then, the key physical parameters related to flow loss are screened by conducting a sensitivity analysis of influencing parameters. Next, a quasi-steady assumption of flow is made to generate a training sample database, reducing the computational time by acquiring one single sample from the highly time-consuming full-annulus URANS approach to a cost-efficient single-blade-passage approach. Finally, a radial basis function neural network is used to establish a surrogate model that correlates the input parameters and the output loss.

The data-driven hub loss model shows higher prediction accuracy than the traditional physics-based loss models. It can accurately capture the circumferentially and radially nonuniform variation trends of the losses and the associated absolute magnitudes in a BLI fan under different blade load, inlet distortion intensity and rotating speed conditions. Compared with the high-fidelity full-annulus URANS results, the averaged relative prediction errors of the data-driven hub loss model are kept less than 10%.

The originality of this paper lies in developing a new method for predicting flow loss in a BLI fan rotor blade hub region. This method offers higher prediction accuracy than the traditional loss models and lower computational time cost than the full-annulus URANS approach, which could realize fast evaluations of fan aerodynamic performances and provide technical support for designing high-performance BLI fans.

The purpose of this study is to identify the motivating factors that influence repeat participation among university student volunteers at a world-renowned food festival. The direct and indirection relationship (through attitude toward volunteering) was tested. Additionally, the moderating role of class standing between student volunteers' motivations, attitudes and repeat volunteer intention was assessed.

Researchers applied a quantitative methodology to data collected after the festival volunteering experience. The research team collected 205 useable surveys from university student volunteers at the Food Network and Cooking Channel South Beach Wine and Food Festival (SOBEWFF®). Structural equation modeling was used to test the relationships among volunteer motivations, attitude toward volunteering and intention to continue volunteering. Lastly, a multiple-group analysis was applied to test the moderating role of class standing.

The results showed the motivating factors purposive, personal enrichment and family traditions were significant in predicting attitude toward volunteering. These motivations did not significantly affect intention to continue volunteering; thus researchers found only an indirect relationship (through attitude toward volunteering) between volunteering motivations and intention to continue volunteering. Additionally, a positive attitude toward volunteering resulted in an intention to continue volunteering. Lastly, testing the moderating role of class standing revealed significant results on three pathways, indicating that students are motivated to volunteer differently based upon class standing (freshman through junior vs. senior, graduate).

The data were collected prior to COVID-19, and the ways in which COVID-19 has impacted the events industry and the scape of future events are yet to be determined.

Festival organizers and managers should appeal to different motivations of potential student volunteers depending on their class standing. For example, results of the moderator “class standing” indicated that the relationship between personal enrichment motivation and attitude toward volunteering was strongest and significant among freshmen, sophomores and juniors, but insignificant among seniors and graduate students. Thus, freshmen through juniors are more highly motivated to obtain practical experiences, and this motivation results in a positive attitude toward volunteering.

This study tests the moderating role of class standing to help predict intention to continue volunteering at a special event. The research is further unique by extending an understanding of the validity and reliability of the special events volunteer motivations scale.

For an axial-flow compressor rotor, the upstream inflow conditions will vary as the aircraft faces harsh flight conditions (such as taking off, landing or maneuvering) or the whole compressor operates at off-design conditions. With the increase of upstream boundary layer thickness, the rotor blade tip will be loaded and the increased blade load will deteriorate the shock/boundary layer interaction and tip leakage flows, resulting in high aerodynamic losses in the tip region. The purpose of this paper is to achieve a better flow control for tip secondary flows and provide a probable design strategy for high-load compressors to tolerate complex upstream inflow conditions.

This paper presents an analysis and application of shroud wall optimization to a typical transonic axial-flow compressor rotor by considering the inlet boundary layer (IBL). The design variables are selected to shape the shroud wall profile at the tip region with the purpose of controlling the tip leakage loss and the shock/boundary layer interaction loss. The objectives are to improve the compressor efficiency at the inlet-boundary-layer condition while keeping its aerodynamic performance at the uniform condition.

After the optimization of shroud wall contour, aerodynamic benefits are achieved mainly on two aspects. On the one hand, the shroud wall optimization has reduced the intensity of the tip leakage flow and the interaction between the leakage and main flows, thereby decreasing the leakage loss. On the other hand, the optimized shroud design changes the shock structure and redistributes the shock intensity in the spanwise direction, especially weakening the shock near the tip. In this situation, the shock/boundary layer interaction and the associated flow separations and wakes are also eliminated. On the whole, at the inlet-boundary-layer condition, the compressor with optimized shroud design has achieved a 0.8 per cent improvement of peak efficiency over that with baseline shroud design without sacrificing the total pressure ratio. Moreover, the re-designed compressor also maintains the aerodynamic performance at the uniform condition. The results indicate that the shroud wall profile has significant influences on the rotor tip losses and could be properly designed to enhance the compressor aerodynamic performance against the negative impacts of the IBL.

The originality of this paper lies in developing a shroud wall contour optimization design strategy to control the tip leakage loss and the shock/boundary layer interaction loss in a transonic compressor rotor. The obtained results could be beneficial for transonic compressors to tolerate the complex upstream inflow conditions.

The purpose of this research paper is to examine whether enduring involvement theory plays a role in predicting craft beer and food festival visitors' experience of the festivalscape. Though craft beer and brewing is a growing area of research, there has been limited studies and theory application in this area. Around the world, craft breweries are increasing in number and producing more unique styles of beer as the demand for craft beer increases. Craft beer consumers visit many of these breweries and are attracted to craft beer festivals in which they can sample multiple local, regional, national and international craft beers.

A quantitative methodology was used based on data collected at the site of the festival. Researchers collected 204 useable surveys from visitors attending the North Miami Brewfest in North Miami, Florida, USA. Structural equation modeling was employed to examine the relationships among enduring involvement, festivalscape, satisfaction, revisit intention and word-of-mouth.

The results revealed that enduring involvement is significant in predicting all four factors of festivalscape (food/beverage quality, convenience, facility and festival staff). The festivalscape factors facility, food quality and festival staff predicted festival attendee satisfaction which in turn predicted both revisit intention and word-of-mouth. However, the festivalscape factor convenience did not influence satisfaction.

The authors surveyed only one festival in one region in South Florida. Further studies can survey multiple festivals in multiple regions to increase the generalizability of the research model. Enduring involvement theory could be applied to other niche areas in hospitality and tourism in the future (in addition to craft beer tourism).

Craft beer festival organizers should appeal to craft beer clubs, breweries and publications to attract those with a commitment to the craft beer industry to their event. People with an enduring, lasting commitment to craft beer are more likely to have a positive experience of the festivalscape at the event. Lastly, festival organizers should focus on the festivalscape factors facility, festival staff and food and beverage quality to influence satisfaction at the event.

This project applies enduring involvement theory in a festival setting. The research is further unique by adding enduring involvement as a predictor of festivalscape experience.

This study aims to investigate the US cruise market by analyzing industry trends and consumer psychology. COVID-19 has coexisted with human beings for more than two years, and scientists claim that human beings will continuously live with the virus for a long time. Nowadays, cruise tourism and the COVID-19 pandemic studies are still popular in both academia and the industry, and cruise industry trends and market investigations are expected by consumers and investors. The purpose of this study is to investigate the US cruise market and provide a comprehensive market overview for 2022, especially regional comparisons of consumer perceptions. This study identified consumers' preferences, including cruise duration, cruise line, travel season, and travel experience. Regional impacts were assessed by comparing the Agreement scores, and the southern region's residents show higher intention and a more positive attitude toward cruise travel. Finally, theoretical and managerial implications, limitations, and future research directions are discussed.

With the increasing heat dissipation of electronic devices, the cooling demand of electronic products is increasing gradually. A water-cooled microchannel heat exchanger is an effective cooling technology for electronic equipment. The structure of a microchannel has great impact on the heat transfer performance of a microchannel heat exchanger. The purpose of this paper is to analyze and compare the fluid flow and heat transfer characteristic of a microchannel heat exchanger with different reentrant cavities.

The three-dimensional steady, laminar developing flow and conjugate heat transfer governing equations of a plate microchannel heat exchanger are solved using the finite volume method.

At the flow rate range studied in this paper, the microchannel heat exchangers with reentrant cavities present better heat transfer performance and smaller pressure drop. A microchannel heat exchanger with trapezoidal-shaped cavities has best heat transfer performance, and a microchannel heat exchanger with fan-shaped cavities has the smallest pressure drop.

The fluid is incompressible and the inlet temperature is constant.

It is an effective way to enhance heat transfer and reduce pressure drop by adding cavities in microchannels and the data will be helpful as guidelines in the selection of reentrant cavities.

This paper provides the pressure drop and heat transfer performance analysis of microchannel heat exchangers with various reentrant cavities, which can provide reference for heat transfer augmentation of an existing microchannel heat exchanger in a thermal design.