Revealing the Structure of the Canadian Tourism Market: an Analysis based on Geographic Information Systems (GIS)

Tourism has become a significant component of the economy in Atlantic Canada, especially in Prince Edward Island (PEI). This study sheds light on the Canadian domestic tourism market by using geographic information systems (GIS) to analyze travel data collected from PEI. This study aims to (1) visualizing tourism demand: place of origin, and the amount of expenditure, and (2) examining the geographical distribution of tourist behavioral intention. The dataset contained 1,556 respondents who have had taken at least one overnight pleasure trip to PEI in 2016. ArcGIS 10.4 and SPSS 24.0 were employed for data analysis. Three maps were generated, including (1) a map displaying the location and distribution of current visitors across Canada, (2) a map showing the market segment based on each visitor’s average spending, and (3) a map delineating the customer post-consumption experience. Theoretical contributions and managerial implications were further discussed

The Effects of Motivation, Satisfaction and Perceived Value on Tourist Recommendation

Shuyue Huang is a PhD Candidate, school of hospitality, food & tourism management at University of Guelph. She got a BSc in Urban/Rural Planning & Management & Resources Environment in 2008, and an MSc in Human Geography in Sun Yat-Sen University, China. Her research interests include hospitality and tourism management, consumer behaviour, service management, and tourism planning. Ye Shen is a PhD student in the school of hospitality, food and tourism management, University of Guelph. She got a BBM at Southeast University and an MSc at Peking University, and participated in various tourism planning projects at China Academy of Urban Planning & Design. Her research interests include tourist behaviour and destination management. Dr. Hwan-Suk Chris Choi is a professor in the school of hospitality, food and tourism management (HFTM) at University of Guelph. His research focuses on three main specialties including destination management (e.g. monitoring system, planning, policy making and safety & security), tourist behaviour, and research methodology.</p

Examining the Role of Satisfaction and Brand Love in Generating Behavioral Intention

Behavioral intention has attracted much attention from both the industry and academia. As it is equated with customers\u27 conative loyalty, investigating behavioral intention can give implications for tourism businesses on how to raise consumers’ loyalty and thus lead to profitable development. To have a better understanding of the antecedents of behavioral intention, this study conducted 350 surveys and used structural equation modeling to test the relationships among perceived value, satisfaction, brand love, and behavioral intention. This study found that satisfaction and brand love have similar effects on intention to recommend while the effects of brand love on intention to revisit are much greater than that of satisfaction. Additionally, this study confirmed that perceived value can be used as a predictor of satisfaction and brand love

Development of City Destination Attractiveness Index: A China Case

This study aims to develop a comprehensive assessment model of city destination attractiveness index (CDAI), and to validate it by assessing the city destination attractiveness of the selected city destinations in China. The study result will complement the theoretical knowledge body of destination attractiveness evaluation. Besides, by measuring and matching the differences between a destination’s reality and a visitor’s perception, it can work as a decision-making instrument for DMOs, as well as improving tourists’ satisfaction

Does brand love matter to casual restaurants? A multi-group path analysis

Previous research indicates that just satisfying customers is insufficient for retaining loyalty. Therefore, this research explores how to inspire and retain loyalty by adding an important construct, brand love, to the value-satisfaction-loyalty chain. Data were collected from guests of casual dining restaurants. The measurement scales adopted in this research were derived from the previous literature and adapted to the restaurant context. A multi-group path analysis was conducted to investigate whether the effects of brand love varied with gender, age, and income groups. This research confirmed that brand love is the outcome of excellent perceived value and a high level of satisfaction, and brand love is more important than perceived value and satisfaction in inspiring revisit intentions. This investigation emphasizes the importance of brand love for certain segments: women, Generation Xers, and people with higher incomes. It fills a gap in the literature by including brand love in the value-satisfaction-loyalty framework

Plasma exchange treatment of a diabetic ketoacidosis child with hyperlipidemia to avoid pancreatitis: a case report

Type 1 diabetes mellitus (T1DM) is a metabolic disorder characterized by an absolute deficiency of insulin due to pancreatic failure. Diabetes ketoacidosis (DKA) has emerged as one of the most common complications of T1DM. Although exceedingly rare, the onset of T1DM with DKA may result in lipemia secondary to severe hypertriglyceridemia (HTG), accounting for several cases in the pediatric population. Along this line, plasma exchange treatment in children with DKA and severe hyperlipidemia has only been reported in some cases. In this case report, the diagnosis of an 11-year-old girl with diabetes ketoacidosis accompanied by severe HTG, along with subsequent plasma exchange treatment, is presented. Initially, the patient received initial management with crystalloid fluid bolus and intravenous insulin therapy. Despite rapid correction of acidosis, persistent HTG subsequently prompted the plasma exchange treatment. A total of three sessions were administered over 2 days, leading to a significant reduction in the triglyceride levels and corneal opacity resolution, indicating a successful therapeutic intervention

Latissimus dorsi flap – the main force in breast reconstruction for breast tumor in Chinese population

BackgroundThe latissimus dorsi flap (LDF) is the most commonly used autologous flap for breast reconstruction (BR) in China. We conducted this study to explore the current status of BR using LDF with/without implants.MethodsThis study was a single-center retrospective study that included breast tumor patients who underwent LDF breast reconstruction at Fudan University Shanghai Cancer Center (FUSCC) between 2000 and 2021.ResultsWe analyzed 4918 patients who underwent postmastectomy BR, including 1730 patients (35.2%) with autologous flaps. LDF was used for BR in 1093 (22.2%) patients, and an abdominal flap was used in 637 (13.0%) patients. The proportion of LDFs used in autologous BR patients decreased each year and dropped to approximately 65.0% after 2013 due to the increased use of abdominal flaps. Among these patients, 609 underwent extended LDF (ELDF) BR, 455 underwent LDF BR with implants, and 30 received a LDF as a salvage flap due to previous flap or implant failure. Patients who underwent ELDF reconstruction were older and had a higher BMI than those who received a LDF with implants. There was no significant difference in the mean postoperative hospital stay, neoadjuvant chemotherapy rates, or adjuvant radiotherapy rates between the two groups. Major complications requiring surgical intervention occurred in 25 patients (2.29%). There was no significant difference in the incidence of major complications between the two groups (P=0.542).ConclusionsLDF breast reconstruction is a well-developed and safe procedure. The duration of postoperative hospitalization nor the incidence of major complications was affected by implant use

Opportunistic Intermittent Control with Safety Guarantees for Autonomous Systems

Control schemes for autonomous systems are often designed in a way that anticipates the worst case in any situation. At runtime, however, there could exist opportunities to leverage the characteristics of specific environment and operation context for more efficient control. In this work, we develop an online intermittent-control framework that combines formal verification with model-based optimization and deep reinforcement learning to opportunistically skip certain control computation and actuation to save actuation energy and computational resources without compromising system safety. Experiments on an adaptive cruise control system demonstrate that our approach can achieve significant energy and computation savings

Kun: Answer Polishment for Chinese Self-Alignment with Instruction Back-Translation

In this paper, we introduce Kun, a novel approach for creating high-quality instruction-tuning datasets for large language models (LLMs) without relying on manual annotations. Adapting a self-training algorithm based on instruction back-translation and answer polishment, Kun leverages unlabelled data from diverse sources such as Wudao, Wanjuan, and SkyPile to generate a substantial dataset of over a million Chinese instructional data points. This approach significantly deviates from traditional methods by using a self-curation process to refine and select the most effective instruction-output pairs. Our experiments with the 6B-parameter Yi model across various benchmarks demonstrate Kun's robustness and scalability. Our method's core contributions lie in its algorithmic advancement, which enhances data retention and clarity, and its innovative data generation approach that substantially reduces the reliance on costly and time-consuming manual annotations. This methodology presents a scalable and efficient solution for improving the instruction-following capabilities of LLMs, with significant implications for their application across diverse fields. The code and dataset can be found at https://github.com/Zheng0428/COIG-KunComment: 12 pages, 12 figure