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Art return indices are usually estimated based only on a few means of artistic expression (mainly paintings and drawings). Other forms of expression (e.g. sculptures and installations) are generally ignored, in part because they are three-dimensional and, hence, more difficult to measure. We analyze the price determinants as well as the return and risk of three artistic expressions (paintings, drawings and sculptures) executed by Fernando Botero, the most expensive living Latin American artist, to analyze the degree to which their risk and return attributes differ throughout a 20-year period.

We analyzed all paintings, drawings and sculptures executed by Botero and sold at Sotheby’s and Christie’s between 2000 and 2020 (a total of 707 artworks). The data and the images of each artwork were obtained from the web pages of these two auction houses. A hedonic regression was run to explain the price of each artwork and use explanatory variables that are standard in the literature. Art price indices for paintings, drawings and sculptures were constructed using the year-dummy variables estimated in the regressions. We performed a similar analysis for another artist, Carlos Cruz-Diez, as a robustness to our results.

The performance of Botero’s sculptures through time differs markedly from that of his paintings and drawings. Our results suggest that it is possible that returns estimated in the literature could suffer from a bias, as they have usually ignored the performance of sculptures and other artistic expressions. Botero’s paintings provided a return that was comparable to those of his sculptures (3.36% and 3.20%, respectively), they were two times as high as those of his drawings (1.68%). On the other hand, whereas paintings and drawings had similar annual standard deviations (26% and 25.22%, respectively), sculptures had a much smaller standard deviation (16.96%).

A limitation of the hedonic regression method lies in the need to have a significant and diverse sample to identify the true effect of each variable on the price of a good. Another limitation is that we were only able to use art prices from auctions, as this is the only comprehensive source of art price data that is publicly available. These two limitations are shared by all the studies that use the hedonic pricing model.

Our results have practical applications for art collectors and investors, as well as for artists, galleries and, in general, for the whole art market ecosystem. The risk and return attributes of the various artistic expressions of an artist can be different, and thus it makes sense to analyze each one of them individually, as well as their correlations with the other artistic expressions and with traditional and other alternative investments.

The art market is part of what is known as the “orange economy” (also known as the Creative Economy). According to the World Bank, the economic value of the creative sector is not well known or appreciated, even though cultural, creative and artistic activities are vital for our sense of well-being.

To the best of our knowledge, this is the first paper that compares the financial performance of paintings, drawings and sculptures for the case of a specific artist. We chose Botero for three reasons. First, he is a Latin American living artist who has achieved the highest levels of international sales. Second, Botero has worked extensively on various artistic expressions (oil paintings, drawings on different materials and sculptures) throughout his life, a characteristic that is essential to be able to carry out our study. Third, there is a long record of auction sales for each of Botero’s artistic expressions.

Los índices de rentabilidad del arte generalmente se estiman basándose únicamente en unos pocos medios de expresión artística (principalmente pinturas y dibujos). Otras formas de expresión artística (por ejemplo, esculturas e instalaciones) generalmente se ignoran, en parte porque son tridimensionales y, por tanto, más difíciles de medir. Analizamos los determinantes del precio, así como el retorno y el riesgo de tres expresiones artísticas (pinturas, dibujos y esculturas) ejecutadas por Fernando Botero, el artista latinoamericano vivo más caro, para analizar en qué medida sus atributos de riesgo y retorno difieren a lo largo del tiempo, en un período de 20 años.

Analizamos todas las pinturas, dibujos y esculturas ejecutadas por Botero y vendidas en Sotheby’s y Christie’s entre 2000 y 2020 (un total de 707 obras de arte). Los datos y las imágenes de cada obra se obtuvieron de las páginas web de estas dos casas de subastas. Se realizó una regresión hedonante para explicar el precio de cada obra de arte y se utilizaron variables explicativas estándar en la literatura. Los índices de precios de arte para pinturas, dibujos y esculturas se construyeron utilizando variables ficticias anuales estimadas en las regresiones. Realizamos un análisis similar para otro artista, Carlos Cruz-Diez, como análisis de robustez de nuestros resultados.

El desempeño de las esculturas de Botero a través del tiempo difiere marcadamente del de sus pinturas y dibujos. Nuestros resultados sugieren que es posible que los retornos estimados en la literatura sufran un sesgo, ya que generalmente han ignorado el desempeño de esculturas y otras expresiones artísticas. Las pinturas de Botero proporcionaron un retorno comparable al de sus esculturas (3.36% y 3.20%, respectivamente), pero fueron dos veces superiores a los de sus dibujos (1.68%). Por otro lado, mientras que las pinturas y los dibujos tuvieron desviaciones estándar anuales similares (26% y 25.22%, respectivamente), las esculturas tuvieron una desviación estándar mucho menor (16.96%).

Una limitación del método de regresión hedónica radica en la necesidad de contar con una muestra significativa y diversa para identificar el verdadero efecto de cada variable sobre el precio de un bien. Otra limitación consiste en que solo pudimos utilizar precios de arte de subastas, ya que esta es la única fuente completa de datos sobre precios de arte que está disponible públicamente. Estas dos limitaciones son compartidas por todos los estudios que utilizan el modelo de precios hedónico.

Nuestros resultados tienen aplicaciones prácticas para coleccionistas e inversores de arte, así como también para artistas, galerías y, en general, para todo el ecosistema del mercado del arte. Los atributos de riesgo y retorno de las diversas expresiones de un artista pueden ser diferentes, por lo que tiene sentido analizar cada una de ellas individualmente, así como sus correlaciones con las otras expresiones artísticas y con las inversiones tradicionales y otras alternativas.

El mercado del arte forma parte de lo que se conoce como “economía naranja” (también conocida como Economía Creativa). Según el Banco Mundial, el valor económico del sector creativo no es bien conocido ni apreciado, a pesar de que las actividades culturales, creativas y artísticas son vitales para nuestra sensación de bienestar.

Hasta donde hemos podido comprobar, este es el primer artículo que compara el desempeño financiero de pinturas, dibujos y esculturas para el caso de un artista específico. Elegimos a Botero por tres razones. En primer lugar, es el artista vivo latinoamericano que ha alcanzado los mayores niveles de ventas internacionales. En segundo lugar, Botero ha trabajado extensamente en diversas expresiones artísticas (óleos, dibujos sobre distintos materiales y esculturas) a lo largo de su vida, característica que resulta fundamental para poder realizar nuestro estudio. En tercer lugar, existe un largo historial de ventas en subasta de cada una de las expresiones artísticas de Botero.

This study aims to explore the differences in the tourists’ perceived destination image on travel e-commerce platforms (e.g. Ctrip and Fliggy) and social media platforms (e.g. Xiaohongshu and Weibo).

The inclusion of esports as an official event in the Hangzhou Asian Games is an important step towards the institutionalisation of esports. The significance of this event marks that Asia once again takes a lead in the global esportisation. This chapter investigates a series of history events in the inclusion process of esports into the comprehensive Games in Asia using process sociology and actor network theory (ANT). This study will analyse the type characteristics of esports events in Hangzhou Asian Games, whilst examining how key stakeholders' interact and balance in the network composed of international sports organisations, host of the event, emerging esports organisations and esports game companies. The chapter also examines the functions of global game industrial economic geography, local cultural politics, esports geopolitics and Olympic values in esports sportization, aiming to reveal the implications of esports inclusion in the Asian Games on the debate of whether esports meets the criteria to be classified as a ‘sport’ and its enlightenment of digital strategy to the inclusion esports in the Olympics.

The paper aims to examine the digital economy's influence on China's regional innovation and development. It focuses on direct effects and spatial spillover across regions, and the mediating role of human capital. This analysis is vital for policy and strategic planning in the digital era.

This study uses panel data from 30 Chinese provinces (2004–2019) and uses the entropy method to quantify the digital economy's development. It investigates its impact on regional innovation using a dynamic spatial Durbin model (SDM) and mediation effect model, assessing direct effects, spatial spillover and human capital's mediating role. Various control variables are included for comprehensive analysis.

Findings show the digital economy significantly boosts regional innovation, acting as a growth driver. However, impacts vary regionally, with the central region gaining more than the eastern and western areas. Spatial spillover effects are mixed, showing negative short-term and positive long-term impacts under different weight matrices. Human capital is crucial for fostering innovation through the digital economy.

The paper offers unique insights into the spatial dynamics of the digital economy's impact on regional innovation in China. It advances understanding of the digital economy's role in regional development using innovative methods like the entropy method and dynamic SDM. Highlighting human capital as a key mediating factor enriches discussions on digital economy strategies for regional innovation.

The purpose of this study was to uncover representative emergent areas and to examine the research area of marketing, tourism and big data (BD) to assess how these thematic areas have developed over a 27-year time period from 1996 to 2022. This study analyzed 1,152 studies to identify the principal thematic areas and emergent topics, principal theories used, predominant forms of analysis and the most productive authors in terms of research.

The articles for this research were all selected from the Web of Science database. A systematic and quantitative literature review was performed. This study used SciMAT software to extract indicators. Specifically, this study analyzed productivity and produced a science map.

The findings suggest that interest in this area has increased gradually. The outputs also reveal the innovative effort of industry in new technologies for developing models for tourism marketing. Ten research areas were identified: “destination marketing,” “mobility patterns,” “co-creation,” “gastronomy,” “sustainability,” “tourist behavior,” “market segmentation,” “artificial neural networks,” “pricing” and “tourist satisfaction.”

This work is unique in proposing an agenda for future research into tourism marketing research with new technologies such as BD and artificial intelligence techniques. In addition, the results presented here fill the current gap in the research since while there have been literature reviews covering tourism with BD or marketing, these areas have not been studied as a whole.

El objetivo de esta investigación fue descubrir nichos representativos de áreas emergentes y examinar el área de Marketing, Turismo y Big Data, evaluando cómo han evolucionado estas áreas temáticas durante un período de 27 años desde 1996–2022. Analizamos 1.152 investigaciones para identificar las principales áreas temáticas y temas emergentes, las principales teorías utilizadas, las formas de análisis predominantes y los autores más productivos en términos de investigación.

Todos los artículos para esta investigación fueron seleccionados de la base de datos Web of Science. Realizamos una revisión sistemática y cuantitativa de la literatura. Utilizamos el software SciMAT para extraer indicadores. Específicamente, analizamos la productividad y elaboramos un mapeo científico.

Los hallazgos sugieren que el interés en esta área ha aumentado gradualmente. Los resultados también revelan el esfuerzo innovador de la industria en nuevas tecnologías para desarrollar modelos de marketing turístico. Se identificaron diez áreas de investigación (“marketing de destinos”, “patrones de movilidad”, “co-creación”, “gastronomía”, “sostenibilidad”, “comportamiento turístico”, “segmentación de mercado”, “redes neuronales artificiales”, “precios”, y “satisfacción del turista”).

Este trabajo es único al proponer una agenda para futuras investigaciones en investigación de Marketing Turístico con nuevas tecnologías como Big Data y técnicas de Inteligencia Artificial. Además, los resultados presentados aquí llenan el vacío actual en la investigación ya que si bien se han realizado revisiones de literatura que cubren Turismo con Big Data o Marketing, estas áreas no se han estudiado como un conjunto.

这一特定研究领域的目标是发现具有代表性的新兴领域, 并考察市场营销、旅游和大数据研究领域, 以评估这些主题领域在1996年至2022年的27年间是如何发展的。我们分析了1152项研究, 以确定主要专题领域和新兴主题、使用的主要理论、主要的分析形式以及在研究方面最有成效的作者。

本研究的文章都是从Web of Science数据库中选出的。我们进行了系统化的定量文献审查, 并使用SciMAT软件来提取指标。具体来说, 我们分析了生产力并制作了一个科学研究地图。

研究结果表明, 人们对这一领域的兴趣已经逐渐增加。本文也揭示了工业界在开发旅游营销模式的新技术方面的创新努力。研究确定了十个研究领域：“目的地营销”、“流动模式”、“共同创造”、“美食”、“可持续性”、“游客行为”、“市场细分”、“人工神经网络”、“定价 “和游客满意度”。

这项研究的独特之处在于提出了未来利用大数据和人工智能技术等新技术进行旅游营销研究的议程。此外, 本文的结果填补了目前的研究空白, 因为虽然有文献综述涉及旅游与大数据或市场营销, 但这些领域还没有被作为一个整体来研究。

The purpose of this paper is to have a deeper understanding of the nonlinear relationship between the impact of climate change on tourism development. Current studies on the effects of climate change on tourism development primarily rely on linear correlation assumptions.

Based on the New Institutional Economics theory, the institutional setting inherently motivates and ensures the growth of the tourism industry. For a precise evaluation of the nonlinear consequences of climate change on tourism, this paper concentrates on Chinese cities between 2011 and 2021, methodically analyzing the influence of climate change on tourism.

The study findings suggest that there is an “inverse U”-shaped nonlinear relationship between climate change and tourism development, initially strengthening and subsequently weakening. Based on these findings, the research further delves into how institutional contexts shape the nonlinear association between climate change and tourism growth. It was found that in a higher institutional backdrop, the “inverse U” curve tends to flatten and surpass the curve adjusted for a lesser institutional context. Upon deeper mechanism analysis, it was observed that cities with more advanced marketization, improved industrial restructuring and enhanced educational growth exhibit a more evident “inverse U”-shaped nonlinear connection between climate change and tourism evolution.

First, previous studies on climate change and tourism development largely rely on questionnaire data (Hu et al., 2022). In contrast to these studies, this paper uses dynamic panel data, which to some extent overcomes the subjectivity and difficulty of causality identification in questionnaire data, making our research conclusions more accurate and reliable. Second, this study breaks through the linear relationship hypothesis of previous literature regarding climate change and tourism development. By evaluating the nonlinear relationship of climate change to tourism development from the institutional pressure perspective, it more intricately delineates their interplay mechanism, expanding and supplementing the research literature on the relationship mechanism between climate change and tourism development. Thirdly, the conclusions of this study are beneficial for policymakers to better understand and assess the scope of climate change impacts. It also aids relevant departments in clarifying the direction of institutional environment optimization to elevate the level of tourism development when faced with adverse impacts brought about by climate change.

By focusing on Sustainable Development Goal 12 (SDG 12) and tourism automation, this perspective paper aims to investigate how tourism and automation will work to create a world in which tourism has more sustainable production and consumption patterns.

This perspective paper reviews the past developments of automation in tourism in the context of sustainable production and consumption patterns, the lessons learned from the COVID-19 pandemic and looks at the future of tourism and how automation will help it be more sustainable in terms of consumption and production patterns.

The insights from this analysis suggest that automation technologies will play a major role in both the supply and demand sides of the tourism and hospitality industry, encouraging increased tourism sustainability. While automation technologies will have the greatest impact on the supply side in the near future, as such technologies will be used to minimise waste and energy usage, creating large gains for environmental protection, the technologies will also benefit responsible consumption. Big data and analytical technologies will work in ways to ensure that consumers are nudged into consumer practices that are increasingly sustainable.

This perspective paper synthesises the literature on the subjects, namely, automation and SDG 12 in tourism, and points to important new future research agenda. This is one of the first papers in tourism to blend automation and SDG 12 literature to shed light on the use of automation in sustainable consumption and production in tourism.

通过聚焦于可持续发展目标12和旅游自动化, 本前瞻性文章旨在探讨旅游业和自动化如何共同创造一个让旅游产业拥有更可持续的生产和消费模式的世界。

本文回顾了旅游自动化在可持续生产和消费模式背景下的发展, 从COVID-19大流行中学到的教训, 并展望旅游业的未来以及自动化如何帮助其在消费和生产模式方面变得更加可持续。

根据分析, 自动化技术将在旅游和酒店业的供求两侧发挥重要作用, 促进旅游业的可持续性发展。虽然自动化技术在近期内将对供应侧产生最大影响, 因为这些技术将被用来最小化废物和能源使用, 为环境保护创造巨大收益, 但这些技术也将惠及负责任消费。大数据和分析技术将以确保消费者被引导向越来越可持续的消费实践。

本前瞻性论文综合了关于旅游中的自动化和可持续发展目标12的文献, 并指出了重要的新的未来研究议程。这是旅游业中第一批结合自动化和可持终发展目标12文献以阐明旅游中可持续消费和生产的自动化使用的论文之一。

Al centrarse en el ODS12 y la automatización del turismo, este artículo de perspectiva pretende investigar cómo el turismo y la automatización trabajarán para crear un mundo en el que el turismo tenga unos patrones de producción y consumo más sostenibles.

Este artículo de perspectiva revisa los desarrollos pasados de la automatización en el turismo en el contexto de los patrones de producción y consumo sostenibles, las lecciones aprendidas de la pandemia COVID-19, y examina el futuro del turismo y cómo la automatización le ayudará a ser más sostenible en términos de patrones de consumo y producción.

Las conclusiones de este análisis sugieren que las tecnologías de automatización desempeñarán un papel importante tanto en la oferta como en la demanda de la industria del turismo y la hotelería, fomentando una mayor sostenibilidad del turismo. Mientras que las tecnologías de automatización tendrán el mayor impacto en el lado de la oferta en un futuro próximo, ya que dichas tecnologías se utilizarán para minimizar los residuos y el uso de energía, creando grandes ganancias para la protección del medio ambiente, las tecnologías también beneficiarán al consumo responsable. Los macrodatos y las tecnologías analíticas funcionarán de manera que se incite a los consumidores a adoptar prácticas de consumo cada vez más sostenibles.

Este documento de perspectiva sintetiza la bibliografía sobre los temas, a saber, la automatización y el ODS12 en el turismo, y apunta a una nueva e importante agenda de investigación futura. Se trata de uno de los primeros trabajos sobre turismo que combina la literatura sobre automatización y ODS12 para arrojar luz sobre el uso de la automatización en el consumo y la producción sostenibles en el turismo.

This study aims to explore motives behind teachers' and students' use of translanguaging and how they use it in Tanzanian public secondary school classrooms.

Data were collected using interviews and non-participant observations.

The findings indicate that translanguaging was used to facilitate content comprehension, promote classroom interaction and increase students' motivation to learn. Translanguaging was implemented using three strategies: paraphrasing an English text into Kiswahili, translating an English text into its Kiswahili equivalent and word-level translanguaging.

By highlighting the motivations for translanguaging and corresponding strategies associated with translanguaging pedagogy in the Tanzanian context, this study has significant practical implications for teachers and students to showcase their linguistic and multimodal knowledge, while fostering a safe learning space that relates to students' daily experiences.

The study offers new insights into previous research on the role of language-supportive pedagogy appropriate for teachers and students working within bi-/multilingual education settings.

In the field of steel defect detection, the existing detection algorithms struggle to achieve a satisfactory balance between detection accuracy, computational cost and inference speed due to the interference from complex background information, the variety of defect types and significant variations in defect morphology. To solve this problem, this paper aims to propose an efficient detector based on multi-scale information extraction (MSI-YOLO), which uses YOLOv8s as the baseline model.

First, the authors introduce an efficient multi-scale convolution with different-sized convolution kernels, which enables the feature extraction network to accommodate significant variations in defect morphology. Furthermore, the authors introduce the channel prior convolutional attention mechanism, which allows the network to focus on defect areas and ignore complex background interference. Considering the lightweight design and accuracy improvement, the authors introduce a more lightweight feature fusion network (Slim-neck) to improve the fusion effect of feature maps.

MSI-YOLO achieves 79.9% mean average precision on the public data set Northeastern University (NEU)-DET, with a model size of only 19.0 MB and an frames per second of 62.5. Compared with other state-of-the-art detectors, MSI-YOLO greatly improves the recognition accuracy and has significant advantages in computational cost and inference speed. Additionally, the strong generalization ability of MSI-YOLO is verified on the collected industrial site steel data set.

This paper proposes an efficient steel defect detector with high accuracy, low computational cost, excellent detection speed and strong generalization ability, which is more valuable for practical applications in resource-limited industrial production.

Although the sharing economy improves comfort and convenience, it is yet unclear how it affects subjective well-being. This study aims to offer a conceptual model for understanding the linkages between the antecedents and consequences of subjective well-being in ridehailing services.

Using a non-probabilistic sampling method and a pre-tested survey instrument, 450 responses were collected from January to March 2020. The data were analysed using structural equation modelling.

Experience quality and perceived convenience are correlated with subjective well-being. Perceived value and personal innovativeness were not correlated with subjective well-being, as the former does not contribute to the latter’s development. Continuous usage intention significantly correlated with subjective well-being, followed by customer relationship proneness and advocacy. Regarding gender and age differences, men place higher value on customer relationship proneness than women, while women place higher value on subjective well-being than men. Older users value perceived convenience and customer relationship proneness in ridehailing services more than younger users.

Understanding key factors contributing to user well-being in ridehailing would promote a more affordable mobility sector globally. This understanding would enable ridehailing businesses to create more effective business and marketing plans while prioritising user well-being, thus enhancing user happiness and reducing turnover rates.

This research demonstrates how crucial it is for users’ well-being to have a positive experience and find the service convenient. It also highlights the importance of building strong customer relationships and examines how gender and age influence people’s adoption and use of these services.

Aunque la economía colaborativa mejora la comodidad y conveniencia, aún no está claro cómo afecta al bienestar subjetivo. Ofrecemos un modelo conceptual para comprender las conexiones entre los antecedentes y consecuencias del bienestar subjetivo en los servicios de transporte compartido.

Utilizando un método de muestreo no probabilístico y un instrumento de encuesta previamente probado, se recopilaron 450 respuestas entre enero y marzo de 2020. Los datos fueron analizados utilizando un modelo de ecuaciones estructurales.

La calidad de la experiencia y la percepción de conveniencia están correlacionadas con el bienestar subjetivo. El valor percibido y la innovación personal no se correlacionaron con el bienestar subjetivo, ya que el primero no contribuye al desarrollo del último. La intención de uso continuo se correlacionó significativamente con el bienestar subjetivo, seguida por la propensión a las relaciones con los clientes y la defensa de estos servicios. En cuanto a las diferencias de género y edad, los hombres valoran más la propensión a las relaciones con los clientes que las mujeres, mientras que las mujeres valoran más el bienestar subjetivo que los hombres. Los usuarios mayores valoran más la percepción de conveniencia y la propensión a las relaciones con los clientes en los servicios de transporte compartido que los usuarios más jóvenes.

Esta investigación demuestra lo crucial que es para el bienestar de los usuarios tener una experiencia positiva y encontrar el servicio conveniente. También resalta la importancia de construir relaciones sólidas con los clientes y examina cómo el género y la edad influyen en la adopción y uso de estos servicios.

Comprender los factores clave que contribuyen al bienestar de los usuarios en los servicios de transporte compartido promovería un sector de movilidad más asequible a nivel global. Esta comprensión permitiría a las empresas de transporte compartido crear planes de negocios y marketing más efectivos, priorizando el bienestar de los usuarios y mejorando así su felicidad y reduciendo las tasas de rotación.

尽管共享经济提高了舒适度和便利性, 但它如何影响主观幸福感尚不清楚。我们提供了一个概念模型, 用于理解乘车服务中主观幸福感的前因后果之间的联系。

采用非概率抽样方法和预先测试的调查工具, 在 2020 年 1 月至 3 月期间收集了 450 份回复。数据采用结构方程模型进行分析。

体验质量和感知便利性与主观幸福感相关。感知价值和个人创新性与主观幸福感不相关, 因为前者无助于后者的发展。持续使用意愿与主观幸福感密切相关, 其次是客户关系倾向和拥护。在性别和年龄差异方面, 男性比女性更重视客户关系倾向, 而女性比男性更重视主观幸福感。老年用户比年轻用户更重视乘车服务中的便利感和客户关系代言。

这项研究表明, 用户获得积极的体验和便捷的服务对他们的福祉至关重要。研究还强调了建立牢固的客户关系的重要性, 并探讨了性别和年龄如何影响人们采用和使用这些服务。

了解有助于提高乘车旅行用户幸福感的关键因素, 将在全球范围内推动建立一个更加经济实惠的移动出行行业。这种理解将使打车企业能够制定更有效的业务和营销计划, 同时优先考虑用户福祉, 从而提高用户幸福感并降低流失率。