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Although many attempts to discover key segments of sport spectators have been extant, little segmentation effort has been made to reflect pandemic situations such as the COVID-19 pandemic. The purpose of this research is twofold: (1) to classify sport spectators into key segments based on perceived risks associated with a mass-gathered sporting event during the COVID-19 pandemic and (2) to identify each segment’s profiles.

Questionnaire surveys of spectators attending a Japanese rugby game during the COVID-19 pandemic (January–June 2021) were conducted (n = 1,410). A combination of hierarchical and non-hierarchical clustering methods was executed.

The results revealed the five-cluster solution as the optimal number of clusters representing the samples (i.e. spectators with extremely low-risk perception, those with low-risk perception, those with moderate-risk perception, those with high-risk perception and those with higher social risk perception). This five-cluster solution showed sufficient stability and validity. Moreover, each segment had different profiles regarding three background aspects – demographics, psychographics and behavioral variables.

This study is the first effort to segment sport spectators based on perceived risks associated with a mass-gathered sporting event in the pandemic situation. Despite extensive segmentation studies to explore sport fans, contribution reflecting the post-crisis situations is scant. Therefore, the findings provide insight into this realm by providing a new viewpoint for understanding sport spectators during a possible future pandemic era.

The purpose of this paper is to examine the 2015 Union Cycliste Internationale (UCI) Road World Cycling Championship in Richmond, Virginia.

An array of eclectic methods included in situ witness observations of several of the races, 21 semi-structured random interviews and multiple discussions with elements of UCI, the city of Richmond’s planners, residents and business owners during and after the championship in fall 2015.

This paper has uncovered five findings: First, the material investment was considerably smaller than that of other events (common good criterion CGC i – good governance); second, pre-planning was critical to successfully hosting the event; third, this event included not only two entities as one would expect at first glance, but many (common good criterion CGC ii – good management); fourth, a filière approach to community service and the exploitation of clustered thematic activities was of critical importance to successfully hosting the 2015 UCI Road World Cycling Championship; and fifth, this event enabled the opportunity to market other city and regional assets (common good criterion CGC iii – good outcomes).

Cities hoping to bid for events ought to consider hosting unique events such as road championships. Those cities will benefit from careful event pre-planning, responsible event hosting and post-event legacies in the form of socio-economic and mindscape memories.

Bidding and pre-event planning is increasingly seen as an opportunity to locate, create and develop support for common good urban projects, which will remain valuable after the event is over or which will need to be built in spite of the bid’s result.

This study fills an unresearched gap on the impact of events on a city’s future non-motorized sustainable transportation priorities.

The impact of various factors on how TV sports audiences perceive sport event sponsors’ billboards around sports facilities has been the subject of extensive research. Despite numerous factors that impact the effectiveness of sponsor signage at sporting events, there has been a lack of research regarding the language used for such signage around sports facilities’ billboards. Therefore, this study aims to investigate the effects of billboard advertisement language on TV sports audiences’ recognition, recall and search intention to sponsor signage.

This study employed an online experimental design. Participants (n = 925) were recruited from two linguistically different regions: Chinese and English. Participants were randomly assigned to one of two conditions: watching tennis video matches with billboard advertisements presented in either the Roman alphabet exclusively or in a combination of the Roman alphabet and Chinese characters.

This study revealed that although language cannot significantly impact audiences’ unaided recall of a brand, it does have a discernible effect on brand recognition and search intention among audiences. Additionally, people are more likely to search for brands in their native language. Participants from various regions tend to have different recognition rates and search intentions for sport sponsors.

This is the first manuscript examining the use of different languages in relation to audiences’ recognition and recall of sports sponsorship. It provides empirical evidence of the importance of carefully considering the language used in sponsor signage around stadium billboards to optimize the efficacy of sponsorships at sports events.

Sports tourism was strongly affected by the COVID-19 pandemic, but there is no consensus on what sports tourism should look like in the post-pandemic period. This study explores the future of sports tourism in light of the COVID-19 pandemic and provides an alternative paradigm model.

Data were collected by interviewing sports tourism experts. Data analysis was based on the continuous comparison method during three stages of open, axial and selective coding.

The findings point to the complexity of the future sports tourism industry. Post-COVID-19 sports tourism strongly depends on environmental forces and targeted support, with strategies focused on tourists’ safety and security, digitalization of the industry, and new employment opportunities.

This study contributes to the body of knowledge on sports tourism by providing answers to the current challenges, threats and opportunities associated with the pandemic. The proposed paradigm model could be a guideline for sports tourism practitioners and policymakers to accelerate recovery from COVID-19 in a sustainable and resilient manner.

The sudden COVID-19 epidemic in 2019 has frustrated China's overall economy, and the implementation and development of the National Fitness Program has encountered huge obstacles. At a new historical starting point, in order to realize the dream of becoming a powerful country in sports, it is necessary to transform the successful experience gained since the reform and opening up into regular understanding and systematic theories, so as to make a theoretical response to the new contradictions and challenges faced in development and give full play to the National Fitness has comprehensive values and multiple functions in improving people's health, promoting people's all-round development, promoting economic and social development and demonstrating the country's cultural soft power.

Taking the topic of national fitness as an example, this paper sets out from the three dimensions of knowledge input, knowledge output and knowledge production, using citation analysis, social network analysis, co-word analysis and cluster analysis, to measure the characteristics and knowledge structure of interdisciplinary knowledge exchange.

China's national fitness is still in the primary development stage, and the strong boost of the national top-level policy is the biggest driving force of its development, driven by the policy together with the settlement of many major events, constantly improving and enriching the wings. The main body of knowledge production on the topic of national fitness is mainly colleges and universities, with low participation of government and enterprises, high degree of cooperation among authors, obvious interdisciplinary characteristics and strong application of research themes.

This study provides a strong theoretical basis for the promotion of the Healthy China strategy. Especially under the influence of COVID-19, this paper can contribute to the comprehensive value and multimodal functions of national fitness in improving the health of people, promoting economic and social development and demonstrating the soft power of national culture.

The UAE is among the fastest-growing facilities management (FM) markets globally. Nevertheless, conclusive evidence on this market is scarce in the literature. Therefore, this paper aims to provide an in-depth insight into the FM market in the UAE.

Fourteen interviewees were purposively selected to provide insight into FM status through their field experiences. A SWOT analysis of their answers held place.

Interviewees revealed that the main trends of FM in the UAE include interests in sustainability, integration of technology, health and safety, outsourcing FM, switching to total facilities management (TFM), and performance management systems use. Besides, the quality of the service in the FM market is driven by the real-estate boom, services sophistication, the increasing awareness of FM and focus on the quality of services. Furthermore, the interviews found that the recruitment of poorly skilled labors can threaten the FM market to meet the allocated budget, misperception of FM, the value of money, the lack of continuous follow-up with recent advancements in technologies and the lack of performance measurement models.

This paper highlights the major trends, drivers and threats of the FM market in the UAE, and the implications of its findings can direct FM organizations and researchers in their practices.

The purpose of this paper was (1) to examine the underexplored intersection of sports betting and favorite team loyalty, and (2) to assess differences in gambling behavior among sport bettors by varying levels of team loyalty.

A total of 1,555 National Football League (NFL) bettors and non-betting NFL fans were surveyed to assess media consumption across a mix of team loyalty attitudes and betting behaviors.

Statistically significant differences were found between four types of NFL fans (casual, team loyalty-dominant, betting-dominant and hybrid) as it relates to media consumption in various forms. Most notably, the results suggested symbiosis between the activities.

The symbiosis finding, though preliminary, suggests the activity provides an additional platform for consumers to connect with spectator sport. Furthermore, the act of betting, like participation in fantasy sports, appears to spur consumption of the NFL product generally. The study, however, was limited to NFL fans, did not specify the method for sports betting, nor the intensity of gambling.

Teams should not worry that betting detracts from fan engagement with the team product. Also, leagues and media providers should continue to highlight betting content as participants consume at higher rates than non-participating sports fans.

Team fandom may potentially moderate problem behavior among bettors. The betting results indicate being a loyal team fan lowers one’s gambling spend per month and largest bet compared to non-loyal bettors. However, the hybrid fan showed significantly higher media consumption levels.

Sports fans have more opportunities to interact and engage with their favorite games than ever before. However, consumers have limited amounts of time and money, and this study is one of the first to examine differences in fan interests and behaviors related to sport betting and team loyalty and the resulting viewership and consumption behavior.

Earned value management (EVM)–based models for estimating project actual duration (AD) and cost at completion using various methods are continuously developed to improve the accuracy and actualization of predicted values. This study primarily aimed to examine natural gradient boosting (NGBoost-2020) with the classification and regression trees (CART) base model (base learner). To the best of the authors' knowledge, this concept has never been applied to EVM AD forecasting problem. Consequently, the authors compared this method to the single K-nearest neighbor (KNN) method, the ensemble method of extreme gradient boosting (XGBoost-2016) with the CART base model and the optimal equation of EVM, the earned schedule (ES) equation with the performance factor equal to 1 (ES1). The paper also sought to determine the extent to which the World Bank's two legal factors affect countries and how the two legal causes of delay (related to institutional flaws) influence AD prediction models.

In this paper, data from 30 construction projects of various building types in Iran, Pakistan, India, Turkey, Malaysia and Nigeria (due to the high number of delayed projects and the detrimental effects of these delays in these countries) were used to develop three models. The target variable of the models was a dimensionless output, the ratio of estimated duration to completion (ETC(t)) to planned duration (PD). Furthermore, 426 tracking periods were used to build the three models, with 353 samples and 23 projects in the training set, 73 patterns (17% of the total) and six projects (21% of the total) in the testing set. Furthermore, 17 dimensionless input variables were used, including ten variables based on the main variables and performance indices of EVM and several other variables detailed in the study. The three models were subsequently created using Python and several GitHub-hosted codes.

For the testing set of the optimal model (NGBoost), the better percentage mean (better%) of the prediction error (based on projects with a lower error percentage) of the NGBoost compared to two KNN and ES1 single models, as well as the total mean absolute percentage error (MAPE) and mean lags (MeLa) (indicating model stability) were 100, 83.33, 5.62 and 3.17%, respectively. Notably, the total MAPE and MeLa for the NGBoost model testing set, which had ten EVM-based input variables, were 6.74 and 5.20%, respectively. The ensemble artificial intelligence (AI) models exhibited a much lower MAPE than ES1. Additionally, ES1 was less stable in prediction than NGBoost. The possibility of excessive and unusual MAPE and MeLa values occurred only in the two single models. However, on some data sets, ES1 outperformed AI models. NGBoost also outperformed other models, especially single models for most developing countries, and was more accurate than previously presented optimized models. In addition, sensitivity analysis was conducted on the NGBoost predicted outputs of 30 projects using the SHapley Additive exPlanations (SHAP) method. All variables demonstrated an effect on ETC(t)/PD. The results revealed that the most influential input variables in order of importance were actual time (AT) to PD, regulatory quality (RQ), earned duration (ED) to PD, schedule cost index (SCI), planned complete percentage, rule of law (RL), actual complete percentage (ACP) and ETC(t) of the ES optimal equation to PD. The probabilistic hybrid model was selected based on the outputs predicted by the NGBoost and XGBoost models and the MAPE values from three AI models. The 95% prediction interval of the NGBoost–XGBoost model revealed that 96.10 and 98.60% of the actual output values of the testing and training sets are within this interval, respectively.

Due to the use of projects performed in different countries, it was not possible to distribute the questionnaire to the managers and stakeholders of 30 projects in six developing countries. Due to the low number of EVM-based projects in various references, it was unfeasible to utilize other types of projects. Future prospects include evaluating the accuracy and stability of NGBoost for timely and non-fluctuating projects (mostly in developed countries), considering a greater number of legal/institutional variables as input, using legal/institutional/internal/inflation inputs for complex projects with extremely high uncertainty (such as bridge and road construction) and integrating these inputs and NGBoost with new technologies (such as blockchain, radio frequency identification (RFID) systems, building information modeling (BIM) and Internet of things (IoT)).

The legal/intuitive recommendations made to governments are strict control of prices, adequate supervision, removal of additional rules, removal of unfair regulations, clarification of the future trend of a law change, strict monitoring of property rights, simplification of the processes for obtaining permits and elimination of unnecessary changes particularly in developing countries and at the onset of irregular projects with limited information and numerous uncertainties. Furthermore, the managers and stakeholders of this group of projects were informed of the significance of seven construction variables (institutional/legal external risks, internal factors and inflation) at an early stage, using time series (dynamic) models to predict AD, accurate calculation of progress percentage variables, the effectiveness of building type in non-residential projects, regular updating inflation during implementation, effectiveness of employer type in the early stage of public projects in addition to the late stage of private projects, and allocating reserve duration (buffer) in order to respond to institutional/legal risks.

Ensemble methods were optimized in 70% of references. To the authors' knowledge, NGBoost from the set of ensemble methods was not used to estimate construction project duration and delays. NGBoost is an effective method for considering uncertainties in irregular projects and is often implemented in developing countries. Furthermore, AD estimation models do fail to incorporate RQ and RL from the World Bank's worldwide governance indicators (WGI) as risk-based inputs. In addition, the various WGI, EVM and inflation variables are not combined with substantial degrees of delay institutional risks as inputs. Consequently, due to the existence of critical and complex risks in different countries, it is vital to consider legal and institutional factors. This is especially recommended if an in-depth, accurate and reality-based method like SHAP is used for analysis.

This study aims to develop an all-encompassing model to analyse various aspects of atmospherics, including components of the museum space and its physical surroundings. Moreover, it evaluates whether the identified attributes of the “museumscape” affect the positive word of mouth of museum visitors.

This exploratory study adopts a quantitative methodology. Data were collected through direct interviews with visitors at three Italian art museums and through a structured questionnaire. All dimensions were measured with multiple items on a five-point Likert scale. To assess the influence of the museumscape attributes on positive word of mouth, a structural equation model is performed adopting the two-stage testing procedure estimating the measurement model in the first stage and running a confirmatory factor analysis to assess reliability and demonstrate convergent and discriminant validity for all multi-item measures.

Six attributes of the museumscape are delineated (ambient conditions; facilities and convenience; signs and signage; staff behaviour; art gallery quality; exhibition space aesthetics). The latter three positively influence visitors' positive word of mouth.

The study expands frameworks from previous service museum marketing research in general and service museum research on atmospherics in particular. The framework developed here identifies the direct predictive power of museumscape cues on positive museum visitor's word of mouth, thus increasing knowledge of the customer service experience and service quality and atmospherics management.

The constructs discovered here may help museum managers to carefully design and manage the museumscape to enhance visitors' satisfaction and loyalty.

This study is the first application of servicescape theory in the museum context; previous applications focus on for-profit sectors.

This study consolidates insights on the role of virtual reality (VR) and augmented reality (AR) in tourism engagement (TE). In addition, it suggests new directions for research in tourism and hospitality.

A hybrid integrative review was used with bibliometric and theory-context-characteristics-method framework analyses of 236 peer-reviewed journal articles.

Computer science journals dominate TE in VR/AR research. Emotional and immersive attributes of VR/AR sustain TE. Exploring cultural theories can enrich TE perspectives in the context of VR/AR. This study offers fruitful directions by exploring virtual technology’s role in sustaining cultural heritage and studying TE intentions and perceptions on VR/AR tourism mobile applications.

To the best of the authors’ knowledge, this is the first study that uncovers the structure and intellectual rationale of existent research.

本研究整合了关于虚拟现实（VR）和增强现实（AR）在旅游参与（TE）中的作用的见解。此外, 本研究为旅游和酒店业的研究提供了新的方向。

本研究使用文献计量学和理论-背景-特征-方法（TCCM）框架分析, 采用混合综合审查方法, 分析了236篇同行评审的期刊文章

计算机科学期刊在VR/AR研究中主导了TE领域。VR/AR的情感和沉浸属性支持了TE。在VR/AR的背景下, 探索文化理论可以丰富TE的视角。本研究通过探讨虚拟技术在保护文化遗产方面的作用, 以及研究VR/AR旅游移动应用中的TE意图和感知, 提供了有益的研究方向。

这是第一项揭示现有研究结构和知识理论基础的研究。