Despite the rapid proliferation of generative AI, empirical understanding of how hotel managers integrate ChatGPT into their professional workflows remains limited. Adopting a constructivist grounded theory approach, this study develops a hotel manager-centered framework of ChatGPT usage benefits and challenges, explaining hotel managers’ utilization levels and continued use of ChatGPT. We identify five benefit domains—content creation and support, efficiency and productivity, well-being, enhanced communication, and knowledge enhancement—and three challenge domains: dependency, drawbacks, and capability requirements. By examining the interplay between these drivers and barriers, this study provides one of the first qualitative characterizations of professional ChatGPT engagement in hospitality. Theoretically, it extends technology adoption models by proposing a grounded framework explaining how benefits and challenges influence continuance use and utilization level. Practically, it offers a roadmap for hotel organizations to develop policies—and training that mitigate dependency risks while maximizing productivity gains from large language models.
The function of complex coacervates has always been closely related to their physical state and relaxation dynamics in multidisciplinary fields; however, how they affect the gelation kinetics of heat-set protein coacervate gels with condensed protein systems remained unknown. This study precisely regulated the relaxation dynamics of β-conglycinin/lysozyme heteroprotein complex coacervates via pH (6.0–8.0) and NaCl concentration (0 mM and 30 mM) and elucidated its impact on the gelation kinetics and multiscale structures of the resulting heat-set coacervate gels. Benefiting from the unique multivalent physical interaction network within the coacervates, the heat-set β-conglycinin/lysozyme coacervate gels exhibited a distinctive gelation mechanism characterized by thermal activation, denaturation, co-aggregation, microphase separation, and network formation. Faster relaxation dynamics, induced by lower pH or higher NaCl concentration, not only accelerated the characteristic thermal activation process of the coacervates but also enhanced their thermal stability, raising the temperatures for protein denaturation and aggregation. Furthermore, the tightly coupled β-conglycinin and lysozyme, bound via the multivalent physical interaction network, underwent unique co-aggregation and microphase separation phenomena after denaturation. The resulting microgels further cross-linked into a dense, uniform particulate gel network, increasing the hardness and compressive strength of coacervate gels at least ten-fold compared to the individual-protein gel with the same protein concentration. Additionally, accelerated relaxation dynamics promoted the formation of spherical multiscale structures in the coacervate gels. The mechanical strength of coacervate gels also increased with a higher degree of thermal activation.
While destinations increasingly leverage cultural capital for competitiveness, research predominantly focuses on top-down promotions of monument-centered heritage, neglecting the distinct social logic of gastronomic culture. Grounded in cultural capital theory, this study aims to examine how Hong Kong's tea restaurants food culture translates into residents' recommendation intentions toward culturally diverse individuals. It untangles the core inquiries: how everyday food culture fosters attachment; how this attachment subsequently shapes cultural identity and confidence; and how nostalgia and knowledge moderate these psychological pathways. Additionally, it identifies which specific tea restaurant's food culture dimensions serve as the primary drivers. Utilizing an empirical sample of 615 Hong Kong residents, this research adopts a PLS–SEM–ANN approach. The PLS–SEM analysis confirms that cultural identity and confidence act as pivotal mediators, while the complementary ANN analysis reveals that gastronomic identity, exceeding mere sensory flavour, is the predominant driving dimension. Empirically, nostalgia amplifies the culture–attachment link, and knowledge strengthens the attachment–confidence relationship. These findings advocate for a paradigm shift in destination marketing: beyond institutional campaigns, mobilizing residents as active cultural transmitters is crucial for gastronomic tourism, establishing a scalable mechanism for everyday cultural capital transmission.
To address the challenges of feature sparsity, geometric degradation, and motion distortion in unstructured agricultural environments, this paper proposes ALIW-IESEKF, a robust Wheel-LiDAR-IMU tightly-coupled Iterated Error State Extended Kalman Filter odometry algorithm. The core contributions are twofold. First, we derive a full-dimensional observation update equation that incorporates both linear and angular velocities from wheel odometry as hard constraints within the IESEKF framework, effectively reducing scale drift in LiDAR-only odometry under geometric degradation. Second, we integrate an adaptive voxel filtering strategy and a hash-octree-based nearest neighbor search mechanism, significantly enhancing map maintenance efficiency and query precision in complex agricultural settings.Experimental results on the public CitrusFarm dataset and real-world agricultural scenarios demonstrate that ALIW-IESEKF reduces the Absolute Trajectory Error (ATE RMSE) by 13.7% to 47.7% compared to state-of-the-art algorithms such as FAST-LIO2 and RSS-LIWOM. Quantitative analysis demonstrates that our system achieves superior map consistency with 2.694 bits average entropy (13.6% reduction from FAST-LIO2) in GPS-denied betel nut forests, while qualitative visual inspection confirms sharp boundary reconstruction and ghosting artifact mitigation in open fields, highlighting the framework’s significant practical value for autonomous agricultural robots.
This paper focuses on the singular value decomposition of third-order split quaternion tensors (St-SVD). Initially, the paper introduces a new multiplication operation (St-product) for the split quaternion tensors. To address the challenges arising from zero divisors and non-commutativity in split quaternions, a real representation method is proposed that successfully transforms the split quaternion tensor SVD problem into a real tensor SVD problem. Through this method, the paper establishes the existence of St-SVD. Furthermore, we extend the Moore-Penrose inverse to include split quaternion tensors and derives their specific form based on the St-SVD. Additionally, the paper provides general expressions for least-squares solutions and minimum norm least-squares solutions to the equation (A) over dot *(St) (X) over dot = (B) over dot. As applications, the paper proposes two algorithms for color video compression and deblurring. Experimental results demonstrate that the proposed methods outperform existing state-of-the-art approaches.
