ABSTRACT
The construction industry has been experiencing many occupational accidents as working on construction sites is dangerous. To reduce the likelihood of accidents, construction companies share the latest construction health and safety news and information on social media. While research studies in recent years have explored the perceptions towards these companies' social media pages, there are no big data analytic studies conducted on Instagram about construction health and safety. This study aims to consolidate public perceptions of construction health and safety by analyzing Instagram posts. The study adopted a big data analytics approach involving visual, content, user, and sentiment analyses of Instagram posts (n = 17,835). The study adopted the Latent Dirichlet Allocation, a kind of machine learning approach for generative probabilistic topic extraction, and the five most mentioned topics were: (a) training service, (b) team management, (c) training organization, (d) workers' work and family, and (e) users' action. Besides, the Jaccard coefficient co-occurrence cluster analysis revealed: (a) the most mentioned collocations were ‘construction safety week', ‘safety first', and ‘construction team', (b) the largest clusters were ‘safety training', ‘occupational health and safety administration', and ‘health and safety environment', (c) the most active users were ‘Parallel Consultancy Ltd.', ‘Pike Consulting Group', and ‘Global Training Canada', and (d) positive sentiment accounted for an overwhelming figure of 85%. The findings inform the industry on public perceptions that help create awareness and develop preventative measures for increased health and safety and decreased incidents.
ABSTRACT
Tourism safety is essential for tourists and tourism practitioners. This study conducted a bibliometric analysis using VOSviewer and CiteSpace for 2018 articles indexed on the Web of Science (WoS). It also analysed 7293 Weibo posts between 1977 and 2022 using Python, MYSQL, AI sentiment, and Tableau. The first tourism safety publication on WoS appeared in 1977, while the first Weibo microblog dated was dated back to 2011. Compared to the information posted on Weibo, the annual publications about tourism safety on WoS recorded a stable increment. On Web of Science (WoS), the academic staff and universities produced the largest number of tourism safety posts. On the flip side, the most productive organisations on Weibo are government agencies in popular tourism destinations. "Accident", "medical tourism", "environment", "mediating role", and "hospitality" were important burst nodes in tourism safety on WoS. "Quality", "accident", and health-related words were the foci on both Weibo and WoS. On Web of Science, the top 10 most popular keywords of tourism safety-related articles could be classified into two groups: health ("Covid-19", "restoration", "pandemics", "Sars-Cov-2", "Sars", "mental health") and IT terminologies ("big data", "artificial intelligence"). It has been concluded that "artificial intelligence (AI)" is more likely to be included in the keywords on tourism researched by academia. In contrast, the public may not know about or use AI in the tourism industry. Besides, the top 10 most popular keywords on Weibo related to tourism risks and hazards were drowning and traffic risks and hazards, such as drowning and traffic risks. The digital divide may explain such a difference: the academic circle benefits more from the digital age than laypersons. It may also be the result of institutional differences and information asymmetry.
ABSTRACT
Due to hectic city lives and the growing health concerns in light of the global pandemic, mountain tourism has become increasingly popular worldwide, which has increased the related research. Based on traditional bibliometric laws, such as those authored by Price, Bradford, Lotka, and Zipf, this study acquired 1413 mountain tourism journal articles via bibliometric analysis and identified the most influential journal articles, researchers, and countries in mountain tourism research as indexed in the Web of Science (WoS) database during 2010–2020. The keyword analysis revealed mountain tourism’s emerging research topics, including climate change, sustainable development, sustainability, sustainable tourism, protected areas, rural tourism, and conservation. The most influential journal was Sustainability in the mountain tourism. The research results showed that China, the U.S., and Romania produced the most significant mountain tourism articles indexed in the WoS. Most developed countries in Europe had the highest average and average normalized citations, which indicated that they may have more influence in this field as compared to other countries. Some developing countries, such as India, Nepal, and China, had higher citations, average citations, and/or average normalized citations than other countries. The main research trend was the sustainable development aspect of mountain-based tourism during the COVID-19 pandemic. We identified the research gap in WoS;although there is some research shedding light on tourism via bibliometrics, mountain tourism bibliometric analysis and science mapping via VOSViewer is scarce. The paper summarizes the critical aspects of the current discussion of sustainable mountain tourism, such as transport and coopetition (i.e., combing with cooperation and competition) in mountain tourism areas. The results indicated that government agencies and destination managers need to strike a balance between sustainable mountain tourism development and environment and natural landscape conservation after COVID-19.
ABSTRACT
The rapid development of society and economy has imposed insurmountable pressure on the urban population, and many people suffer from sub-health conditions. Kangyang tourism (KT), which combines the concepts of health preservation, ecological resources, and tourism activities, has developed rapidly in China since the concept was first introduced. Although previous studies have examined the relationship among experience, satisfaction, and intention, there is a lack of study of experience value’s impact on Mountain Kangyang Tourim Spots’ Sustainability, that is, willingness to revisit and recommend to other potential tourists. Consequently, an “experience value (functional value, contextual value, emotional value, cognitive value, economic value), satisfaction and post-trip willingness to revisit and recommend” framework is suggested to examine mountain Kangyang tourism (MKT). Data were collected from 500 tourists after visiting five well-known MKT destinations in Panzhihua city. Using the structural equation modeling (SEM) technique, the results suggest that tourist satisfaction plays an important role in experience value as well as willingness to revisit and recommend the MKT spots after their revisits. Our research offers some practical suggestions for MKT destination operators when they design and provide MKT destinations. The results would be useful for governments and non-profit organizations which attempt to promote MKT.