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The purpose of this paper is to propose a new grey prediction model, GOFHGM (1,1), which combines generalised fractal derivative and particle swarm optimisation algorithms. The aim is to address the limitations of traditional grey prediction models in order selection and improve prediction accuracy.

The paper introduces the concept of generalised fractal derivative and applies it to the order optimisation of grey prediction models. The particle swarm optimisation algorithm is also adopted to find the optimal combination of orders. Three cases are empirically studied to compare the performance of GOFHGM(1,1) with traditional grey prediction models.

The study finds that the GOFHGM(1,1) model outperforms traditional grey prediction models in terms of prediction accuracy. Evaluation indexes such as mean squared error (MSE) and mean absolute error (MAE) are used to evaluate the model.

The research study may have limitations in terms of the scope and generalisability of the findings. Further research is needed to explore the applicability of GOFHGM(1,1) in different fields and to improve the model’s performance.

The study contributes to the field by introducing a new grey prediction model that combines generalised fractal derivative and particle swarm optimisation algorithms. This integration enhances the accuracy and reliability of grey predictions and strengthens their applicability in various predictive applications.

Robots, as the crystallization of new artificial intelligence, are being applied in various fields, especially the hotel industry. They are seizing the opportunities, using technology to improve the overall quality and comprehensive competitiveness. However, they also cause many problems due to practical limitations. The purpose of this paper is to study customers' recognition and acceptance of hotel service robots to guide the successful promotion of this technology.

This paper proposed a comprehensive model based on the theory of planned behavior, the technology acceptance model and then the perceived value-based acceptance model. Exploratory factor analysis, confirmatory factor analysis, grouped regression analysis and path analysis was adopted to validate the impacts of each variable to obtain the final reliable model using data collected from hotel guests using a self-designed questionnaire.

The empirical research based on the theoretical model shows that the constructed conceptual model can thoroughly explain the influencing factors of hotel robot acceptance, enrich the acceptance theory and provide academic support for the use and popularization of hotel service robots. Among all variables, attitude, usefulness and perceived value are the factors that have the greatest impact on acceptance. They have significant differences in the effects of adjustment variables such as gender, educational level, whether hotel robots have been used, and whether other robot services have been experienced on different paths in the model.

This paper explored the customer acceptance of service robots in hotels, helped to understand the process of decision-making on service robot selection and contributed to the theoretical extension of the hospitality industry. The work guides hotel management to promote better-personalized products and services of robot technology in the hospitality industries.

The acceptance study on hotel service robots provides insight into the hotel industry to understand customers' attitudes and acceptance of emerging technology.

The purpose of this paper is to calculate the local guaranteed fiscal revenue with the local fiscal revenue of 31 provinces, and predict their guaranteed fiscal revenue in 2018 with the artificial neural network (ANN).

The principal components analysis (PCA), particle swarm optimization (PSO) and extreme learning machine (ELM) model was designed to produce the inputs of KMV model. Then the KMV model was used for obtaining the default probabilities under different issuance scales. Data were collected from Wind Database. MATLAB 2018b and SPSS 22 were used in the field of modeling and results analysis.

This study’s findings show that PCA–PSO–ELM proposed in this research has the highest accuracy in terms of the prediction compared with ELM, back propagation neural network and auto regression. And PCA–PSO–ELM–KMV model can calculate the secure issuance scale of local government bonds effectively.

The sustainability forecast in this study can help local governments effectively control the scale of debt issuance, strengthen the budget management of local debt and establish the corresponding risk warning mechanism, which could make local governments maintain good credit ratings.

This study sheds new light on helping local governments avoid financial risks effectively, and it is conducive to establish a debt repayment reserve system for local governments and the proper arrangement for stock debt.

This paper aims to clarify the effects of metallic nanoparticles (NPs) additives and room temperature ionic liquids (ILs) on the tribological performance of electric contacts.

Tribological properties of copper (Cu) and silver (Ag) NPs as lubricant additives in different lubricants of ILs or polyalphaolefin (PAO) oils under applied electric currents were investigated. After tribological tests, morphologies of worn surfaces were observed; meanwhile, lubrication and anti-wear properties were analyzed.

The mixture solution of the IL and Cu NPs showed desirable lubrication and anti-wear properties due to the reduction of electrocorrosion and the enhancement of rolling effects of particles in the contact region. The anti-wear performance of Cu NPs is better than that of Ag NPs due to the difference in the particle size. The PAO oil with the Cu NPs additives showed poor lubrication properties due to the low solubility of the particles in the oil. When the direction of applied current was changed, the friction of the lubricant with better conductivity was more stable in the variation trend.

This paper begins with a study of tribological properties of Cu and Ag NPs as lubricant additives in different lubricants of IL or PAO oils under applied electric currents. The authors then propose several methods and possible solutions which could be implemented to improve the tribological performance of electric contacts.

To meet the rising global needs, the humanitarian community has signed off on making a strategic change toward more localisation, which commonly refers to the empowerment of national and local actors in humanitarian assistance. However, to this date, actual initiatives for localisation are rare. To enhance understanding of the phenomenon, the authors explore localisation of logistics preparedness capacities and obstacles to its implementation. The authors particularly take the perspective of the international humanitarian organisation (IHO) community as they are expected to implement the localisation strategy.

A phenomenon-driven, exploratory and qualitative study was conducted. Data collection included in-depth interviews with 28 experienced humanitarian professionals.

The findings showed the ambiguity inherent in the localisation strategy with largely different views on four important dimensions. Particularly, the interviewees differ about strengthening external actors or internal national/local offices. The resulting framework visualises the gap between strategy formulation and implementation, which forms major obstacles to the localisation aims.

Further research is required to support the advancement of localisation of logistics preparedness capacities. Important aspects for future research include triangulation of results, other stakeholder perspectives and the influence of context.

The authors add to the important debate surrounding localisation by offering remedies to overcoming obstacles to strategy implementation. Further, the authors’ proposed framework offers a language to precisely describe the ways in which IHOs (should) view localisation of logistics preparedness capacities and its operationalisation.

To the best of authors’ knowledge, this paper is the first academic article on localisation within the humanitarian logistics context.

The provision of meals has long been regarded as an essential part of treatment of hospitalized patients complementing medical procedures and nursing management. Today, despite changes in the health-care landscape, which focused on improving the quality and efficiency of hospital care, malnutrition among inpatient was still a common worldwide concern.

This was a multi-centre, randomized study conducted in 21 study sites comprising 21 state and specialist government hospitals under the Ministry of Health, Malaysia. The sample size for this study was calculated with purposive sampling method, followed by proportionate sampling to determine the random sample size of each of the study sites. The total sample size required for this study was 2,759 subjects. A validated data collection form was used in the study.

Only 32.2 % and 37.6 % of subjects achieved adequate energy and protein intake, respectively, during their admission to medical ward. The study result showed that the overall mean energy and protein intake was 794.6 ± 487.8 kcal and 35.2 ± 24.3 g, respectively. The estimated energy (p = 0.001) and protein (p = 0.001) intake of all study sites was significantly lower compared to the adequacy value.

The adequacy intake in this study was only carried out in medical wards, thus reproducible result among other wards in different study sites could not be confirmed. Besides, this study assumed that the portion eaten by subjects during lunch and dinner was the same, and therefore, either one was recorded together with breakfast and either lunch or dinner to represent a subject’s daily intake.

This was the first nationwide study to report the adequacy of energy and protein intake of patients receiving therapeutic diets in the government hospital setting in Malaysia.

Existing tourism review articles have limited review topics and cover a relatively short period. This review paper aims to extend the coverage of the previous literature and enhances the completeness of tourism-related studies to provide comprehensive tourism-related literature from 1945 (World War II onward) to 2022. Specifically, this paper reveals the major research themes present in published tourism research during this time period and highlights the evolution of tourism research from the preliminary phase, the transversal phase, to the growth phase.

The present study visualizes tourism research through networks of coauthors and their countries and regions, cocitation analysis of keywords and explores the thematic evolution of tourism research after the World War II (i.e., 1945–2022) from Web of Science and Google Scholar through bibliometric analysis.

Findings reveal that the themes of tourism research in the past years can be divided into seven major research themes. The tourism research evolution from World War II to 2022 can be categorized into three stages: preliminary (1945–1970), transversal (1971–2004) and growth (2005–2022). In addition, the research themes of tourism are not static but evolve according to the dynamics of the society and the industry, and that seven main research themes have been formed, namely, “heritage tourism,” “medical tourism,” “adventure tourism,” “dark tourism,” “sustainable tourism,” “rural tourism” and “smart tourism.”

The present study expands and refines the comprehensive literature in tourism research, as well as reveals the trends and dynamics in tourism research through network analysis and thematic evolution research methods.

现有的旅游评论文章在审查主题方面有限, 并且涵盖的时间相对较短。本综述文章扩展了先前文献的涵盖范围, 增强了与旅游相关研究的完整性, 提供了从1945年（第二次世界大战之后）到2022年的全面旅游相关文献。具体而言, 本文揭示了此期间发表的旅游研究中的主要研究主题, 并突出了旅游研究从初步阶段、横向阶段到增长阶段的演变。

本研究通过共同作者及其国家的网络、关键词的共同引用分析, 将旅游研究可视化, 并探索二战后旅游研究的主题演变。本研究通过文献计量学分析, 将 Web of Science (WoS) 和 Google Scholar 中的旅游研究（即 1945–2022 年）可视化。

研究结果显示, 过去几年的旅游研究主题可分为七大研究主题。从第二次世界大战到 2022 年的旅游研究演变可分为三个阶段：初步阶段（1945–1970 年）、横向阶段（1971–2004 年）和成长阶段2005–2022 年）。此外, 旅游的研究主题并不是静态的, 而是根据社会和行业的动态而演变, 形成了七个主要研究主题, 即“遗产旅游”、“医疗旅游”、“冒险旅游”、“黑暗旅游”、“可持续旅游”、“乡村旅游”和“智慧旅游”。

本研究通过网络分析和主题演变研究方法扩展和完善了旅游研究方面的综合文献, 并揭示了旅游研究的趋势和动态。

Los artículos de revisión existentes sobre turismo tienen temas de revisión limitados y cubren un periodo relativamente corto. Este artículo de revisión amplía la cobertura de la bibliografía anterior y mejora la exhaustividad de los estudios relacionados con el turismo para ofrecer una bibliografía exhaustiva sobre el turismo desde 1945 (Segunda Guerra Mundial en adelante) hasta 2022. En concreto, este documento revela los principales temas de investigación presentes en la investigación turística publicada durante este periodo de tiempo y destaca la evolución de la investigación turística desde la fase preliminar, la fase transversal, hasta la fase de crecimiento.

El presente estudio visualiza la investigación turística a través de redes de coautores y sus países y regiones, análisis de co-citación de palabras clave, y explora la evolución temática de la investigación turística después de la Segunda Guerra Mundial (es decir, 1945–2022) a partir de Web of Science y Google Scholar mediante análisis bibliométricos.

Los resultados revelan que los temas de la investigación turística de los últimos años pueden dividirse en siete grandes temas de investigación. La evolución de la investigación turística desde la Segunda Guerra Mundial hasta 2022 puede clasificarse en tres etapas: preliminar (1945–1970), transversal (1971–2004) y de crecimiento (2005–2022). Además, los temas de investigación del turismo no son estáticos, sino que evolucionan según la dinámica de la sociedad y de la industria, y que se han formado siete temas principales de investigación, a saber: “turismo patrimonial”, “turismo médico”, “turismo de aventura”, “turismo oscuro”, “turismo sostenible”, “turismo rural” y “turismo inteligente”.

El presente estudio amplía y perfecciona la amplia bibliografía existente en el campo de la investigación turística, además de revelar las tendencias y la dinámica de la investigación turística mediante el análisis de redes y los métodos de investigación de evolución temática.

This paper aims to provide an understanding of how accounting systems have changed across four distinct periods of hegemonic leadership in China.

Using Gramsci's concept of hegemony, periods of leadership and accounting change throughout Chinese history are examined, including the Confucian tradition, the rise of the socialist system followed by the Cultural Revolution in the Maoist era, and the move towards the socialist‐market system in the Dengist era.

This paper shows how political leaders in these different time periods effectively achieved leadership by destroying an existing hegemony, creating a new ideology, and implanting this into people's daily lives in order to successfully mobilise their ideological systems. Consistent with changes in leadership, Chinese accounting systems are shown to have responded to hegemonic shifts across these periods.

This paper contributes to understandings of Gramsci's concept of hegemony, explanations of, and motivations for, accounting change, and provides an insight into the evolution of accounting systems throughout time in the context of China.

This study aims to investigate the consumer acceptance of robots in hotels before and after COVID-19, with a specific emphasis on whether COVID-19 had a significant effect on the acceptance of robots by hotel guests and whether guests had higher levels of acceptance of hotel robots since the initial COVID-19 outbreak was brought under control in China.

The sample for this research included Chinese hotel guests before and after COVID-19, with 247 responses obtained before its outbreak and a further 601 responses gathered after. Several hypotheses were developed and tested in a pseudo-experimental design.

The results showed that COVID-19 increased hotel guest acceptance of robots. After COVID-19, the perceived importance of the usefulness, social influence, attitude and value of robots increased, while the perceived importance of the ease of use and anthropomorphism of robots decreased. As a contactless service, the usefulness of robots was more valued by customers. This led customers to lower their requirements for the ease of use of robots. In addition, people were more concerned about the social influences on robot use.

Hotel guest attitudes and behavioral intentions toward robots and the services they can provide are changing. However, whether this change is purely ephemeral and motivated by a pragmatic stance triggered by COVID-19 remains to be established.

The hospitality industry is encouraged to create a new profile of guests in terms of their favorable or unfavorable disposition toward being served by robots. Hotels should consider the deployment of robots according to the demographic characteristics of customers (e.g. according to guest age levels).

This research demonstrated that major crises affect customer attitudes and behaviors toward new technologies. COVID-19 resulted in guests paying more attention to the advantages of services offered by hotel robots as a means of reducing the probability of contagion.

疫情前后酒店机器人非接触式服务的技术接受度对比研究

摘要

本研究调查了新冠疫情爆发前后酒店顾客对机器人接受程度的变化, 重点研究了新冠疫情是否对机器人的潜在接受程度有显著影响, 以及自疫情在中国得到控制以来, 顾客对酒店机器人的接受程度是否有所提高。

本研究的样本主要是新冠疫情爆发前后的中国酒店顾客, 在疫情爆发前收集了217份样本, 在疫情爆发后收集了601份样本。研究提出了若干假设, 并采用伪实验设计进行了检验。

结果显示, 新冠疫情的爆发提高了酒店顾客对机器人的潜在接受度。新冠疫情后, 机器人的有用性, 社会影响, 态度和价值的影响增加了, 而机器人的易用性和拟人化的影响降低了。由于机器人的无接触服务, 使得顾客更加关注有用性。这导致顾客对易用性的关注降低。此外, 顾客更加关注使用机器人的社会影响。

酒店顾客对机器人服务的态度和行为意图正在发生变化。然而, 这一变化是否是短暂的, 只是由新冠疫情驱动的, 仍有待确定。

我们鼓励酒店业根据客人对机器人的接受/不接受程度来创建一个新的客户档案。酒店也可以根据顾客的人口统计学特征（比如年龄）来部署机器人。

这项研究表明, 重大灾难会影响顾客对新技术的态度和行为。 COVID-19的爆发导致客人更加关注酒店机器人的服务优势（降低传染概率）。

Aceptación de la tecnología antes y después de la pandemia del COVID-19: Servicios ofrecidos por robots en hoteles

Resumen

Esta investigación analiza la aceptación por parte de clientes del uso de robots en hoteles antes y después del comienzo de la pandemia del COVID-19, prestando una atención especial a si dicha pandemia ha tenido un efecto significativo sobre los niveles de aceptación de robots por parte de clientes en hoteles en China a raíz de la pandemia del COVID-19.

La muestra de este estudio incluye clientes de hoteles en China encuestados antes y después del brote de COVID-19, con 247 cuestionarios recogidos antes del brote y otros 601 después del mismo. Este estudio incluye una serie de hipótesis puestas a prueba adoptando un diseño de investigación de carácter pseudo-experimental.

Los resultados de este estudio apuntan a que el brote de COVID en China conllevó un incremento en la proporción de los clientes de hoteles propensos a aceptar el uso de robots en este contexto. Después de la pandemia, hubo un incremento en la percepción de la importancia de su utilidad, influencia social, actitud y valor de los robots en este contexto, mientras que descendió la percepción de la importancia de la facilidad del use de robots y antropomorfismo descendió. Como servicio sin necesidad de contacto físico, la utilidad de los robots en hoteles fue más valorada por los clientes Esto produjo una disminución en los requisitos de los usuarios en lo referente a la facilidad del uso de robots en hoteles. Además, los participantes en esta encuesta se mostraron más propensos a valorar la influencia sobre la sociedad del uso de robots.

La actitud de clientes de hoteles y su aceptación del uso de robots en este contexto, así como los servicios que éstos proveen están cambiando rápidamente. No obstante, aún no se sabe con certeza hasta que punto estos cambios son meramente efímeros y motivados por una actitud pragmática hacia la crisis creada por la pandemia del COVID-19.

El sector de la hostelería debería intentar desarrollar un perfil de clientes nuevo en lo referente a su grado de aceptación de los robots como parte de los servicios ofrecidos. Los hoteles deberían considerar el uso de robots en los servicios ofrecidos dependiendo de las características demográficas de sus clientes (ejem. Nivel de estudios y formación).

Este estudio demuestra que las crisis de gran magnitud, como lo es la pandemia actual de COVID-19, pueden afectar las actitudes y comportamientos del consumidor en lo referente al uso de nuevas tecnologías. La pandemia del COVID-19 ha llevado a muchos clientes de hoteles a prestar una mayor atención a las ventajas de los servicios ofrecidos por robots como forma de reducir las posibilidades de contagio.

The massive adoption of virtual reality (VR) applications has started since the COVID-19 pandemic, and until now, VR applications are still being used. However, there is limited research that analyses the consumer's perspective on the adoption of VR applications. Thus, this study discovers the adoption of VR applications in the hospitality sector by integrating the value-based adoption model (VAM) and VR quality.

The data were gathered through a survey of 500 respondents and evaluated through the structural equation model-partial least squares (SEM-PLS).

Employing SEM-PLS and importance-performance map analysis (IPMA), the findings revealed that VR quality and perceived value are essential determinants in the adoption of VR applications in the hospitality industry.

Practically, this study encourages the hospitality industry to create and develop high-quality VR application technology to benefit visitors. Through this study, hospitality marketing managers, governments and others concerned with the hospitality industry’s future development can create effective ways to increase the adoption of VR applications in this industry.

This study offers novel perspectives into the theory and application of VR quality and VAM in the adoption of VR applications in the hospitality industry.