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Robotic arms’ interactions with the external environment are growing more intricate, demanding higher control precision. This study aims to enhance control precision by establishing a dynamic model through the identification of the dynamic parameters of a self-designed robotic arm.

This study proposes an improved particle swarm optimization (IPSO) method for parameter identification, which comprehensively improves particle initialization diversity, dynamic adjustment of inertia weight, dynamic adjustment of local and global learning factors and global search capabilities. To reduce the number of particles and improve identification accuracy, a step-by-step dynamic parameter identification method was also proposed. Simultaneously, to fully unleash the dynamic characteristics of a robotic arm, and satisfy boundary conditions, a combination of high-order differentiable natural exponential functions and traditional Fourier series is used to develop an excitation trajectory. Finally, an arbitrary verification trajectory was planned using the IPSO to verify the accuracy of the dynamical parameter identification.

Experiments conducted on a self-designed robotic arm validate the proposed parameter identification method. By comparing it with IPSO1, IPSO2, IPSOd and least-square algorithms using the criteria of torque error and root mean square for each joint, the superiority of the IPSO algorithm in parameter identification becomes evident. In this case, the dynamic parameter results of each link are significantly improved.

A new parameter identification model was proposed and validated. Based on the experimental results, the stability of the identification results was improved, providing more accurate parameter identification for further applications.

This study aims to examine the potential guest perception of green hotel attributes (GHAs) and the underlying mechanism through which GHA perception influences attitude toward green hotels, intention to stay at green hotels and willingness to pay a premium. It also investigates the moderating roles of personal norms and social norms in the influence of GHA perception on identification and trust toward green hotels.

A two-stage survey was used to collect data via Prolific Academic. The authors tested the hypotheses on 521 valid responses using the partial least squares method.

The results show that identification and trust mediate the effect of GHA perception on attitude, intention to stay and willingness to pay a premium for green hotels. The authors found a positive interaction effect between GHA perception and personal norms on identification and trust and a negative interaction effect between social norms and GHA perception on trust. The interaction effect of GHA perception and social norms on identification is not significant.

This study presents an integrated framework for green hotel adoption by examining the potential guest perception of GHAs and explores how it fosters positive guest responses. Findings show that GHA perception positively influences potential guest responses through identification (the personal route) and trust (the social route). This study also simultaneously considers personal norms and social norms, together with the effects of their interactions with GHA perception on identification and trust.

Spherical robot plays an essential role in the field of mobile robot because of its unique shape and omni-directional mobility, especially in the application of planet detection. Although spherical robot has many advantages over leg robot, its obstacle climbing performance is still not satisfactory, that is exactly the motivation of this paper. The purpose of this paper is to propose a high-performance hopping mechanism for spherical robot, which can adapt to different terrain and effectively cross obstacles.

The hopping system uses torque spring as part of the energy storage mechanism, and converts the kinetic energy of rotation into elastic potential energy with a particularly designed turntable. Moreover, the track of the turntable, based on the Archimedes spiral principle, has the attributes of equidistance and equivelocity that enable better stability of energy storage process.

Experiments show that the proposed hopping mechanism can make a 250 g spherical robot jump up to 58 cm with the take-off angle of 60°. Finally, the influence of friction and take-off angle on the hopping height and distance of the robot is also analyzed, which provides a prior guidance for optimizing its jumping process.

This paper shows how to easily design a lightweight, compact and embedded spring hopping structure so that a spherical hopping robot with detection ability can be developed.

COVID-19 is currently the most serious crisis facing the world, and scholars in the medical and social sciences are working to save lives and mitigate the societal effects of the pandemic. This global public health emergency requires interdisciplinary work to provide comprehensive insight into a rapidly changing situation. However, attempts to integrate the medical and social sciences have met several barriers. This paper aims to identify feasible research opportunities for interdisciplinary studies across tourism and public health regarding COVID-19.

This paper presents a critical review of the literature and generates corresponding conceptual and theoretical frameworks to provide an in-depth discussion.

Tourism-related issues of destination management policies and capital are addressed from an interdisciplinary perspective. The conclusions encourage interdisciplinary research into global health problems, which will promote tourism’s renaissance and sustainable development while enhancing social welfare.

This study focuses on integrating tourism and public health to offer stakeholders recommendations regarding destination management and tourism industry recovery amid COVID-19.

This paper represents a frontier study, critically uncovering a host of innovative interdisciplinary research directions and tourism-focused collaboration opportunities related to COVID-19.

新冠疫情是当今世界面对的最严重的危机, 医学和社会科学领域的学者们在共同努力, 拯救生命, 减轻疫情的社会影响。基于快速变化的形势, 这项全球突发的公共卫生事件亟需跨学科工作来进行全面的调查, 但目前医学和社会科学的融合存在一些阻碍因素。为了应对新冠疫情的爆发, 本文旨在探讨旅游与公共卫生跨学科合作的可行性和研究机会, 并总结潜在的研究主题和未来的研究议程。

本研究对文献进行了批判性的回顾, 并生成了相应的概念和理论框架, 以提供一个全面的, 深入的主题讨论。

研究结果从跨学科的角度讨论了旅游产业中的目的地管理、政策和资本问题。我们的结论鼓励对全球健康问题进行跨学科研究, 这将促进旅游业的复兴和可持续发展, 同时提高社会福利。

目前的研究重点是旅游研究和公共卫生的融合, 为利益攸关方提供关于在危机中目的地管理和旅游业复苏的建议。

本文是一项前沿研究, 批判性地、全面地确定了一系列与新冠疫情相关的旅游领域的跨学科研究方向和合作机会。

关键词：医学, 社会科学, 公共健康, 旅游管理, 跨学科研究, 新冠肺炎

文章类型： 研究型论文

Este trabajo presenta una revisión crítica de la literatura y genera los correspondientes marcos conceptuales y teóricos para proporcionar una discusión en profundidad.

El COVID-19 es actualmente la crisis más grave a la que se enfrenta el mundo, y los especialistas en ciencias médicas y sociales están trabajando para salvar vidas y mitigar los efectos sociales de la pandemia. Esta emergencia de salud pública mundial requiere un trabajo interdisciplinario para proporcionar una visión completa de una situación que cambia rápidamente. Sin embargo, los intentos de integrar las ciencias médicas y sociales han encontrado varios obstáculos. El objetivo de este artículo es identificar las oportunidades de investigación viables para los estudios interdisciplinares entre el turismo y la salud pública en relación con la COVID-19.

Las cuestiones relacionadas con el turismo en materia de gestión de destinos, políticas y capital se abordan desde una perspectiva interdisciplinar. Nuestras conclusiones alientan la investigación interdisciplinaria de los problemas de salud global, lo que promoverá el renacimiento del turismo y el desarrollo sostenible, al tiempo que aumentará el bienestar social.

Este estudio se centra en la integración del turismo y la salud pública para ofrecer a las partes interesadas recomendaciones relativas a la gestión de los destinos y la recuperación de la industria turística en medio de COVID-19.

Este trabajo representa un estudio de frontera, que descubre de forma crítica una serie de direcciones innovadoras de investigación interdisciplinaria y oportunidades de colaboración centradas en el turismo en relación con COVID-19.

Palabras clave Ciencias médicas, ciencias sociales, salud pública, gestión del turismo, investigación interdisciplinaria, COVID-19

Investigación

This paper aims to discuss the effects of COVID-19 on hotel marketing and management practices and outlines a three-pronged research agenda to stimulate knowledge development in the hotel sector.

This paper is based on an overview of the relevant literature on hotel marketing and management and the hotel guest behavior. The authors also investigated hospitality service trends to propose a research agenda.

This paper presents a research agenda from three dimensions – artificial intelligence (AI) and robotics, hygiene and cleanliness and health and health care. First, different types of AI (mechanical, thinking and feeling) might open up distinct research streams at the intersection of health crises and hotel management, in light of the COVID-19 pandemic. Additionally, this paper recommends that researchers move beyond typical perspectives on the antecedents and outcomes of hotel hygiene and cleanliness to delve into guests’ perceptions of the cleanliness of specific hotel surfaces. Furthermore, a more in-depth analysis is warranted about the evolving relationship between hotels and the health-care sector.

The recommended research areas are intended to advance the knowledge base to help hotels recover from the COVID-19 pandemic. The suggested research streams are expected to provide actionable insights to promote the development and sustainability of the hotel sector.

This paper appears to be a frontier study, critically examining possible effects of the COVID-19 pandemic on hotel marketing and management practices and how hoteliers may respond to such challenges to recover after this pandemic.

This study aims to examine the effectiveness of sustainability communication on social media. More specifically, the effects of message appeal (sensual vs guilt) and message source (hotel vs social media influencer [SMI]) on perceived environmental corporate social responsibility and the intention to stay at the eco-friendly hotel were examined.

Three studies using the experimental design were carried out. Study 1 examined the relationship between message appeal (sensual vs guilt), perceived environmental social corporate responsibility and the intention to stay at the eco-friendly hotel when the hotel posts sustainability messages on social media. Study 2 replicated Study 1 findings when the SMI posts sustainability messages. Study 3 examined the moderating role of message source (hotel vs influencer) in the effects of message appeal (sensual vs guilt) on behavioral intentions.

Sustainability messages with the sensual (vs guilt) appeal are more persuasive when the eco-friendly hotel (vs SMI) posts it on social media. Furthermore, the traveler’s perception of the hotel’s environmental corporate social responsibility mediates this relationship.

This study extends the literature on sustainability communication by demonstrating the role of message source and message appeal in influencing the traveler’s perceptions and intentions toward eco-friendly hotels.

According to the study findings, eco-friendly hotels can motivate travelers to make pro-sustainable choices by accurately matching the message appeal with the message source in the sustainability communication on social media.

This study is one of the earliest studies that examine the congruency effect of message appeal and message source for sustainability communication on social media in the hospitality realm. The findings offer novel insights for eco-friendly hotels to develop effective sustainability communication on social media.

This study aims to examine the role of message appeals (concrete vs abstract) posted by greenfluencers in determining their behavioral intention toward the sponsored sustainable product. This study examined the underlying mechanism of message authenticity and product sustainability image in this relationship. This study also investigated the boundary condition of product type (utilitarian vs hedonic) in the effect of sustainability message appeal on purchase intention.

Four studies were carried out. One field experiment on Facebook and three scenario-based online experiments were conducted to test the proposed relationships.

This study found that a concrete message appeal results in a higher purchase intention of the promoted product than an abstract message appeal. This effect is a result of message authenticity and product sustainability image. Furthermore, product type moderates the impact of message appeal on behavioral intention via message authenticity and product sustainability image.

This study contributes to the literature on influencer marketing, sustainability communication and the persuasion process.

This study’s findings provide insights for greenfluencers and firms that leverage greenfluencers to promote their sustainable products on social media. Specifically, it lays out how the sustainability message should be framed to be persuasive.

This study findings offer novel insights for greenfluencers and firms in developing effective message strategies to promote sustainable products on social media.

Most poverty research has explored monetary poverty. This chapter presents and analyzes the global multidimensional poverty index (MPI) estimations for China. Using China Family Panel Studies (CFPS), we find China’s global MPI was 0.035 in 2010 and decreased significantly to 0.017 in 2014. The dimensional composition of MPI suggests that nutrition, education, safe drinking water, and cooking fuel contribute most to overall non-monetary poverty in China. Such analysis is also applied to subgroups, including geographic areas (rural/urban, east/central/west, provinces), as well as social characteristics such as gender of the household heads, age, education level, marital status, household size, migration status, ethnicity, and religion. We find the level and composition of poverty differs significantly across certain subgroups. We also find high levels of mismatch between monetary and multidimensional poverty at the household level, which highlights the importance of using both complementary measures to track progress in eradicating poverty.

This paper aims to propose a method to quickly set the heating zone temperatures and conveyor speed of the reflow oven. This novel approach intensely eases the trial and error in reflow profiling and is especially helpful when reflowing thick printed circuit boards (PCBs) with bulky components. Machine learning (ML) models can reduce the time required for profiling from at least half a day of trial and error to just 1 h.

A highly compact computational fluid dynamics (CFD) model was used to simulate the reflow process, exhibiting an error rate of less than 1.5%. Validated models were used to generate data for training regression models. By leveraging a set of experiment results, the unknown input factors (i.e. the heat capacities of the bulkiest component and PCB) can be determined inversely. The trained Gaussian process regression models are then used to perform virtual reflow optimization while allowing a 4°C tolerance for peak temperatures. Upon ensuring that the profiles are inside the safe zone, the corresponding reflow recipes can be implemented to set up the reflow oven.

ML algorithms can be used to interpolate sparse data and provide speedy responses to simulate the reflow profile. This proposed approach can effectively address optimization problems involving multiple factors.

The methodology used in this study can considerably reduce labor costs and time consumption associated with reflow profiling, which presently relies heavily on individual experience and skill. With the user interface and regression models used in this approach, reflow profiles can be swiftly simulated, facilitating iterative experiments and numerical modeling with great effectiveness. Smart reflow profiling has the potential to enhance quality control and increase throughput.

In this study, the employment of the ultimate compact CFD model eliminates the constraint of components’ configuration, as effective heat capacities are able to determine the temperature profiles of the component and PCB. The temperature profiles generated by the regression models are time-sequenced and in the same format as the CFD results. This approach considerably reduces the cost associated with training data, which is often a major challenge in the development of ML models.

Many academic studies in international business empirically test the determinants of Chinese outward (O)FDI. A weakness with these studies is the limited critical evaluation given to the way in which Chinese OFDI data is collected and used. Chinese multinational enterprises (C)MNEs frequently establish special purpose entities in tax havens to transit FDI via intermediary jurisdictions. The purpose of this paper is to develop an alternative approach for measuring CMNE OFDI and subsequently explore how the results of previous studies may have been confounded use of tax havens by MNEs. The authors address the latter question by replicating widely cited quantitative studies.

Replication approach.

Through the replication of several studies, this paper finds high levels of discrepancies in general sign and significance between global ultimate ownership modeling results and those using officially recorded FDI data. More specifically, the main areas impacted by using official data rather than data which accounts for the use of tax havens are cultural proximity, geographic distance and natural resource seeking.

This paper looks at studies, which use official FDI data to understand CMNE behavior. It is important to note, however, that there are many hundreds, if not thousands, of studies that use other national-level FDI data to draw similar types of inferences about MNE activity. In this sense, the authors’ critical evaluation of CMNE work holds a much broader and, arguably, more important question: How reliable, in general, are studies, which use officially recorded FDI data? The results from this paper have already caused reflection on the impact of tax haven use on official FDI collection organizations, such as the OECD.

The social implications of companies using tax havens to route FDI is immense. The use of tax havens not only aids in tax minimization for companies, but also obscures the true providence and identity of companies. This is problematic in a society, which increasingly desires to understand where, how and by whom a product or service was created prior to consumption.

This paper argues that the tendency for Chinese MNEs to establish offshore holding companies in tax havens has given rise to significant biases in official FDI statistics. Through the use of global ultimate ownership data, the authors have put forward an alternate approach to measure genuine CMNEs’ OFDI activity, one which confronts and deals with their pervasive engagement with tax havens. Through the replication of several Chinese OFDI location choice studies, it was possible to understand how methodological issues stemming from the use of official FDI data may influence prior econometric results. In doing so, the authors hope to have sparked a debate which may lead to a re-evaluation of earlier received wisdom regarding Chinese MNE investment strategy and behaviors. This in turn should foster improved theorizing regarding the Chinese MNE and its outward investment activities.