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The importance of workers in labour-intensive industries, such as tourism, is undeniable. In this sense, it has been investigated for decades from various methodological approaches. However, in the academic literature on tourism, the partial least squares-structural equation modelling (PLS-SEM) technique has hardly been used.

Therefore, this work uses that technique to contrast which factors define the employees' wages in the Spanish tourism industry. Additionally, an importance-performance map analysis (IPMA) analysis is carried out, which provides informed decision-making.

Thus, the main results obtained are the verification and measurement of the relationships of Human Capital, Labour Conditions and Market with Wages, and the relation between Human Capital and Labour Conditions. Besides, the improvement points in each variable are identified. Especial emphasis is given to those related to Human Capital and, partially, to the Market.

However, there are certain limitations to this study. Mainly, as the indicators used are given by the 2018 Salary Structure Survey, they are stiff and so the design of the model turns to be more difficult.

Considering the turning point that the temporary cessation of the tourism industry activity due to the COVID-19 pandemic has been, it is essential to take advantage of it to identify and correct existing deficiencies. Therefore, this work aims to be a base document for the identification of these problems.

La importancia de los trabajadores de industrias intensivas en mano de obra, como el turismo, es innegable. En este sentido, se ha investigado durante décadas desde diferentes metodologías. Sin embargo, en la literatura académica en turismo, la técnica PLS-SEM path modelling apenas ha sido utilizada.

Por ello, este trabajo emplea esta técnica para contrastar los factores que definen los salarios de los empleados en la industria turística española. Además, se lleva a cabo un análisis IPMA, que permite la toma de decisiones informada.

Así, los principales resultados obtenidos son la verificación y medida de las relaciones del Capital Humano, Condiciones Laborales y Mercado con los Salarios, y la relación entre Capital Humano y Condiciones Laborales. Además, se identifican los puntos de mejora de cada variable. Se presta un interés especial a aquellos relacionados con el Capital Humano y, parcialmente, el Mercado.

Considerando el punto de inflexión que el cese de actividad temporal de la actividad de la industria turística ha supuesto a causa de la pandemia COVID-19, es esencial aprovechar para identificar y corregir las deficiencias existentes. Además, este trabajo pretende ser un documento base para la identificación de estos problemas.

No obstante, existen algunas limitaciones en este estudio. Principalmente los indicadores utilizados proceden de la Encuesta de Estructura Salarial de 2018, son fijos y, por ende, el diseño del modelo se torna más difícil.

Introduction: The insurance sector provides security to society by pooling resources to manage risks. Insurers’ improved ability to analyse risks by examining vast amounts of granular data has considerably refined this technique. Compiling and analysing the fine data sets is now transformed into the ‘Big Data’ technique. The introduction of big data analytics (BDA) is transforming the insurance industry and the role data plays in insurance.

Purpose: This chapter will attempt to examine the applications and role of big data in the insurance sector and how big data affects the different insurance segments like health insurance, property and casualty, and travel insurance. This chapter will also describe the disruptive impact of big data on the insurance market.

Methodology: Systematic research is carried out by analysing case studies and literature studies, emphasising how BDA is revolutionary for the insurance market. For this purpose, various articles and studies on BDA in the insurance market are selected and studied.

Findings: The execution of big data is continuously increasing in the insurance sector. The performance of big data in the insurance market results in cost reduction, better access to insurance services, and more fraud detection that benefits the customers and stakeholders. Therefore, big data has revolutionised the insurance market and assisted insurers in targeting customers more precisely.

Saudi Arabia is the main destination of religious tourism, as it has many spiritual places. With the passage of years, the figures for pilgrim visits are increasing, which is contributing to the economic growth of the Kingdom of Saudi Arabia (KSA). However, pilgrims’ visits can create strong opportunity costs in the form of environmental degradation. Owing to these notions, this study aims to discover the impact of religious tourism on the quality of the natural environment of Saudi Arabia.

This study develops the empirical relationship between the variables by sampling the data from 35 years ranging from 1986 to 2020. The regression among variables was checked by using fully modified ordinary least square and dynamic ordinary least square models.

This analysis proves that religious tourism has a direct impact on the environmental degradation of KSA. The unceasing visits of pilgrims accelerate various economic operations and activities, e.g. assimilation and digestion of industrial products, that necessarily hamper the environmental quality. In addition, this analysis indicates a negative impact on financial development, foreign investment and renewable energy consumption while the positive impact of fossil fuels assimilation and economic expansion on the secretion of CO₂. The statistical findings are robust and verify the pollution halo hypothesis while rejecting the Environmental Kuznets Curve model in this region.

This analysis recommends restructuring the policies on hajj and Umrah visits. KSA Government should ensure green consumption by pilgrims. The limitation on pilgrims’ visits and the introduction of quotas are alternative policies to impede the pollution in this region.

By controlling the routine determinants, this study offers innovative thoughts regarding the consequences of religious tourism on environmental quality.

通过抽样1986-2020年35年的数据来建立变量之间的实证关系。采用完全修正的普通最小二乘(FMOLS)和动态普通最小二乘(DOLS)模型检验变量间的回归关系

由于沙特阿拉伯有很多精神场所, 是宗教旅游的主要目的地。随着时间的推移, 朝圣访问数据不断增加, 这为沙特阿拉伯王国(KSA)的经济增长做出了贡献。然而, 朝圣访问也可能造成巨大的机会成本, 如环境退化。由于这些观念, 本研究试图揭露宗教旅游对沙特阿拉伯自然环境质量的影响。

研究表明, 宗教旅游对沙特阿拉伯的环境退化有直接影响。持续增长的朝圣来访加速了各种经济运作和活动, 如工业产品的吸收和分解等, 这必然会影响环境质量。此外, 分析表明, 金融发展、外国投资和可再生能源消费受到负面影响, 而化石燃料吸收和经济扩张对二氧化碳的排放产生积极影响。统计结果具有较强的可靠性, 验证了污染晕假说, 同时否定了该地区的环境库兹涅茨曲线(EKC)模型。

本研究建议重构大朝和小朝的政策。沙特阿拉伯政府应该确保朝圣者的绿色消费。朝圣访问的限制和引进配额是防止该地区污染的替代政策。

通过控制常规决定因素, 本研究为宗教旅游对环境质量的影响提供了创新思路。

Se desarrolla la relación empírica entre las variables mediante el muestreo de los datos de 35 años que van de 1986 a 2020. La regresión entre las variables se comprobó empleando modelos de mínimos cuadrados ordinarios totalmente modificados (FMOLS) y mínimos cuadrados ordinarios dinámicos (DOLS)

Arabia Saudí es el principal destino de turismo religioso porque cuenta con numerosos lugares espirituales. Con el paso de los años, las cifras de visitas de peregrinos están aumentando, lo que contribuye al crecimiento económico del Reino de Arabia Saudí (KSA). Sin embargo, las visitas de los peregrinos pueden crear fuertes costes de oportunidad en forma de degradación medioambiental. A partir de estos indicadores, este análisis busca descubrir el impacto del turismo religioso en la calidad del entorno natural de Arabia Saudí.

El análisis demuestra que el turismo religioso tiene un impacto directo en la degradación medioambiental de KSA. Las incesantes visitas de los peregrinos aceleran diversas operaciones y actividades económicas, como la adquisición y consumo de productos industriales, etc., que necesariamente dificultan la calidad medioambiental. Además, el análisis indica un impacto negativo en el desarrollo financiero, la inversión extranjera y el consumo de energías renovables, así como el impacto de la asimilación de combustibles fósiles y la expansión económica en la emisión de CO2. Los resultados estadísticos son robustos y verifican la hipótesis del efecto halo de la contaminación, al tiempo que rechazan el modelo de la curva de Kuznets ambiental (EKC) en esta región.

El análisis recomienda reestructurar las políticas sobre las visitas al hajj y la Umrah. El gobierno de KSA debería garantizar el consumo ecológico de los peregrinos. La limitación de las visitas de los peregrinos y la introducción de cuotas son políticas alternativas para impedir la contaminación en esta región.

Al controlar los determinantes frecuentes, este estudio ofrece reflexiones innovadoras sobre las consecuencias del turismo religioso en la calidad del medio ambiente.

The main purpose of the present research is to explore the possible effectiveness of information and communication technology (ICT), infrastructure development, exchange rate and governance on inbound tourism demand using time series data in India.

The stationarity of the variables is checked by using the ADF, PP and KPSS unit root tests. The paper uses the Bayer-Hanck and auto-regressive distributed lag (ARDL) bounds testing approach to cointegration to examine the existence of long-run relationships; the error-correction mechanism for the short-run dynamics and the vector error correction method (VECM) to test the direction of causality.

The findings of the research indicate the presence of cointegration among the variables. Further, long-run results indicate infrastructure development, word-of-mouth and ICT have a positive and significant linkage with international tourist arrivals in India. However, ICT has a positive and significant effect on tourist arrivals in the short run as well. The VECM results indicate long-run unidirectional causality from infrastructure, ICT, governance and exchange rate to tourist arrivals.

This study implies that inbound tourism demand in India can be augmented by improving infrastructure, governance quality and ICT penetration. For an emerging country like India, this may have far-reaching implications for sustaining and improving tourism sector growth.

This paper is the first of its kind to empirically examine the impact of ICT, infrastructure and governance quality in India using modern econometric techniques. Inbound tourism demand research aids government and policymakers in developing effective public policies that would reposition India to gain from a highly competitive global tourism industry.

This study aims to measure the relationship between demand and exchange rate shocks in the tourism industry.

A panel data set is constructed covering the period between 1995 and 2017, and the data set includes the top 26 countries that host 10 million tourists and above in the world as of 2017. The standard errors of the series are used as an indicator of shocks. First, the cross-sectional dependency, stationarity and the homogeneity of the series are examined; second, a panel cointegration analysis is implemented; third, long-term panel cointegration coefficients are analyzed with Dynamic Common Correlated Effects (DCCE) approach; and, finally, Dumitrescu and Hurlin’s (2012) Granger non-causality test is used to detect the causality.

The preliminary analyses show that the variables are cross-sectional dependent and heterogeneous and are stationary in their first difference; hence, the effects of the shocks are temporary. On the other hand, as a result of the panel cointegration analysis, it is found that both series are cointegrated over the long-term. However, the long-term coefficients estimated with the DCCE approach are found not to be statistically significant. Finally, as a result of the Dumitrescu and Hurlin’s (2012) Granger non-causality test, it is concluded that there is a causality running from exchange rate shocks to demand shocks.

To the best of the authors’ knowledge, the cointegration between the tourism demand shocks and exchange rates shocks has not been investigated before, and therefore, this study is considered to be a pioneering study that will contribute to the literature.

The purpose of this paper is to investigate the role of intersectoriality within the cultural, creative and tourism industries in Italian local development.

The research design builds on the literature on culture-led development and adapts the established body of empirical research on industrial districts to tourism and cultural development. The quantitative analysis of intersectoral specialization and the clustering of cultural, creative and tourism industries in Italian local labour systems (LLSs) combines specialization indexes with principal component analysis and cluster analysis.

About 50 per cent of Italian LLSs specialize in the economy of culture and tourism, mostly in material culture, although tourism has the highest level of specialization. There are three main patterns of agglomeration and clustering. The largest cluster is that of the cultural heritage and content and information industries, which coincides with the systems of medium-sized and large cities, followed by systems of tourism monoculture. The smallest is made up of material culture, typically made-in-Italy sectors. The tourism and material culture industries are monocultures – where tourism agglomerates, but material culture does not.

The analytical approach is quantitative and based on Istat’s Industry and Trade (2012) data set. Further studies are needed on the interaction between agglomerated specialized industries.

This paper contributes to the theoretical and political debate on the value generation and innovation potential of culture and creativity, and bridges the knowledge domains of local development and managerial studies. Novel statistical evidence on intersectoral specialization and the clustering of the cultural, creative and tourism sectors in Italy at the inter-municipal level is provided. This study helps to identify an Italian model of the economy of culture and tourism.

The study aims to analyze the effects of the Covid-19 pandemic on house prices.

The authors start by discussing the possibility that house price indexes may not fully incorporate the effects of the pandemic as of yet. Against the background of the pandemic, the authors then analyze economic and behavioral effects affecting house prices. The authors also discuss how the linkages between tourism and house prices have been affected. The authors further present evidence of an emerging shift in preferences from urban locations to more peripheral ones.

The authors report variance in the evolution of house prices across countries at the onset of the pandemic, with locations depending heavily on tourism showing slower price appreciation while appreciation has firmed in other places. The authors argue that the resilience of house prices is not only because of the low-interest rate environment and government efforts to support firms and households, but also behavioral factors. In some locations, the price of condominiums has declined relative to the price of detached houses. This could indicate that wealthier households are seeking more space and larger units as a result of the crisis. There is also evidence of a downward pressure on rents, leading to increased price–rent ratios in the USA.

By considering both economic and behavioral factors, this paper provides for a better understanding of the resilience and realignment of house prices at the onset of the Covid-19 pandemic.

Introduction: Tourism is one of the fastest growing industries in the world and an important source of income, taxes and jobs while being closely linked to social, economic and environmental well-being of many countries, especially of the developing countries. Sustainable tourism can be considered as an extension of the sustainability concept in the tourism sector, to meet the current needs of tourists, without compromising the possibilities of future generations to satisfy their own needs. The sustainable development of the tourism sector cannot be achieved if certain social groups will not be able to continue accessing tourism services and, at the same time, if the negative aspects of the environmental impact are neglected. The components of sustainable development actually form the core of social innovation activities. New business models, digital devices, user-generated content, big data and online commerce have positive effects on sustainable tourism. But the quality of the tourist product is influenced by the quality of the human factor. Activities that can be performed remotely will be based on new technologies, which require new skills and competencies for employees. It is necessary to reconfigure the implementation of the tourist services process, in which the human interaction is reduced and, at the same time, the client experience is stimulated. The COVID-19 crisis can be considered a catalytic moment to reconsider the growth trajectory of the tourism industry, in the sense that all activities can be reorganised so that the development of tourism is sustainable, with a less destructive impact on the social and environmental component.

Aim: The purpose of this chapter is to review the valences of sustainable tourism in the context of societal changes at the European level.

Method: An extensive literature review was carried out and then the authors discussed the critical issues affecting sustainable tourism. To achieve this, the authors incorporated findings from various researches into four categories. The result is a new perspective and a new potential framework for analysis.

Findings: The authors identified four critical factors that have the potential to influence the sustainable tourism development: social innovation, digitalisation, management of crisis situations and human capital development.

Originality of the Study: This chapter offers a new perspective on the factors that influence the sustainable tourism. These new factors offer potential for further in-depth analysis and refinement.

This study constructs the influence mechanism model of sustainable marketing activities (SMAs), event image, commemorative product perceived value and tourists’ behavioral intentions (TBIs) in the sports tourism context of the Beijing Winter Olympic Games. Additionally, the article discusses the role of event image and product perceived value in enhancing the SMAs’ effect on TBIs.

The research analyzed 315 valid questionnaires from tourists in the Chinese market by structural equation modeling.

The results indicate that SMAs positively impact sports tourism event image, tourists’ perceived commemorative product value and TBIs. Meanwhile, event image and product perceived value mediate the SMAs and TBIs relationship.

Considering SMAs as essential for sustainable development, this paper contributes to the strategic management discipline. Additionally, the research expands the analysis of event image and product perceived value in the brand theory and customer behavior research.

The article outlines the principal value of SMAs implementation in enhancing behavioral intentions. It also reveals that a favorable event image and good perceived value can enhance SMAs’ effectiveness toward positively influencing TBIs, especially purchase intentions. It provides a new vision for nonprofit organizations to prioritize SMAs’ implementation in marketing strategies.

It is pioneering work with a complex research framework for SMAs implementation in the sports tourism context.

This article intends to analyse the explanatory power of the Travel and Tourism Competitiveness Index (TTCI) and some of its constituent factors on national success metrics in managing the initial surge of the COVID-19 pandemic.

The authors study the outbreak control effectiveness of 132 countries during the first semester of 2020. The authors apply generalized linear regression models and weighted least squares models using 6 COVID-19-related dependent variables, 9 TTCI-related independent variables and 12 control variables.

The results suggest that countries with superior TTCI values and selected constituent factors have the highest daily averages of coronavirus infections and fatalities per million and the highest speed rates of COVID-19 spread. The authors also find that these countries have the shortest government response time, the lowest daily average of the social restrictions index and the shortest time from the first case reported in China to the first case reported nationally.

To the best of the authors' awareness, no previous study exists analysing the statistical relationship between the TTCIB and some of its constituent factors with the selected metrics of national success at managing the initial surge of the COVID-19 pandemic. This fact represents the primary evidence of this article's unique contribution.

本文擬分析旅行及觀光競爭力指數、以及其部份構成因素，如何影響有關國家在新型冠狀病毒肺炎大爆發初期控制病毒傳播方面的成功指標。

我們就132個國家於2020年上半年控制肺炎爆發方面的表現進行研究。我們以廣義線性回歸模型和加權最小平方法進行分析研究，當中使用了六個與新型冠狀病毒肺炎有關的因變數、九個與旅行及觀光競爭力指數有關的自變數、和12個控制變量。

研究結果暗示、在擁有優越的旅行及觀光競爭力指數值和選定的構成因素的國家，以百萬人來計算，每日冠狀病毒感染及死亡的平均數字是最高的; 而且，新型冠狀病毒肺炎的傳播速度也是最高的。研究結果亦顯示、在這些國家，政府反應所需的時間是最短的，社會限制指數的日均值是最低的，以及首宗在中國被報導的個案與首宗在有關的國家被全國性地報導的個案之間的時間距是最短的。

盡作者們所知，從前似沒有相關的研究、以國家在新型冠狀病毒肺炎大爆發初期成功控制病毒傳播的選定指數、來分析旅行及觀光競爭力指數與其部分構成因素之間的統計關係; 這正是本文所作獨特貢獻的基本證據。