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In complex environments, a spherical robot has great application value. When the pendulum spherical robot is stopped or disturbed, there will be a periodic oscillation. This situation will seriously affect the stability of the spherical robot. Therefore, this paper aims to propose a control method based on backstepping and disturbance observers for oscillation suppression.

This paper analyzes the mechanism of oscillation. The oscillation model of the spherical robot is constructed and the relationship between the oscillation and the internal structure of the sphere is analyzed. Based on the oscillation model, the authors design the oscillation suppression control of the spherical robot using the backstepping method. At the same time, a disturbance observer is added to suppress the disturbance.

It is found that the control system based on backstepping and disturbance observer is simple and efficient for nonlinear models. Compared with the PID controller commonly used in engineering, this control method has a better control effect.

The proposed method can provide a reliable and effective stability scheme for spherical robots. The problem of instability in real motion is solved.

In this paper, the oscillation model of a spherical robot is innovatively constructed. Second, a new backstepping control method combined with a disturbance observer for the spherical robot is proposed to suppress the oscillation.

This study aims to investigate the impact of supply chain concentration (SCC) on corporate research and development (R&D) investment and determine the moderating roles of industry concentration and financing constraints on the relationship between SCC and R&D investment.

The study collected data from Chinese listed companies, used the fixed effects model to test the research hypotheses and further used the two-stage Heckman test and propensity score matching (PSM) to address potential endogeneity issues.

The result reveals a negative impact of SCC on corporate R&D investment. In addition, industry concentration mitigates the negative impact of SCC on corporate R&D investment, but financing constraints strengthen the negative impact.

This study introduces the concept of SCC and empirically tests its effect on R&D investment, further explaining the lack of corporate innovation. This study inspires companies to strengthen SC management and weigh the level of SCC with environmental factors.

In 2022, the new normal era began to experience an increase in the number of tourists visiting Bali. Even though spiritual tourism was optimistic in attracting foreign visitors, most tourists come from nearby nations like Australia, indicating that the visits had a brief duration in this new era. To sustain the income of spiritual tourism advocates, it is possible to overcome the brief visit. Therefore, this study aims to analyze the collaboration of digitalized spiritual tourism activities in 2022. Data were collected through literature study, observation and in-depth interviews to determine the spiritual tourism hybrid business. The result showed that the digitalization of spiritual tourism builds an on-off hybrid method in marketing and products, thus developing a theory of the characteristics. This on-off hybrid provides a touch of experience for tourists to visit directly. Therefore, digitalization builds the resilience of spiritual tourism in the new normal era through marketing and service of hybrid products.

The gap between word-of-mouth marketing habits, direct product service and the tendency to digitize creates adaptation problems that take time. These problems make a practical contribution to building marketing and spiritual tourism products. The theoretical contribution is to build integrated marketing and spiritual tourism digital product concepts. A qualitative research method was adopted because the population of spiritual tourism is very limited. Therefore, it needs to be explored through experienced and knowledgeable informants. Literature study, observation and in-depth interviews were used to collect data. The literature study technique collects data from written sources, namely books, articles and internet sources. Observations were made by analyzing non-participants by recording various marketing activities and services for spiritual tourism products. Additionally, in-depth interviews were conducted with informants about digitalization in the new normal era.

The result showed that the digitalization of spiritual tourism builds an on-off hybrid method in marketing and products, thus developing a theory of the characteristics. This on-off hybrid provides a touch of experience for tourists to visit directly. Therefore, digitalization builds the resilience of spiritual tourism in the new normal era through marketing and service of hybrid products.

The method has successfully built digital and direct visit products. Digital products share knowledge, while direct visit products serve to gain hands-on experience. These products provide income for spiritual tourism actors. However, direct visit products are more emphasized to spread income, such as hotels, restaurants and souvenirs. This development provides a theoretical implication that the characteristics of tourism products can be enjoyed at the service provider’s premises and the area of origin of tourists with digital technology. Therefore, digitalization has changed the theory of the characteristics of tourism products from having to be enjoyed by service providers (Yoeti, 1991).

Lean manufacturing (LM) concepts have been widely adopted in diverse industrial sectors. However, no literature review focusing on case studies describing LM implementation is available. Case studies represent the actual implementation and provide secondary data for further analysis. This study aims to review the same to understand the pathways of LM implementation. In addition, it aims to analyse other related review questions, such as how implementing LM impacts manufacturing capabilities and the maturity level of manufacturing organisations that implemented LM, to name a few.

A literature review of case studies that discuss the implementation of LM during the last decade (from 2010 to 2020) is carried out. These studies were synthesised, and content analyses were performed to reveal critical insights.

The implementation pattern of LM significantly varies across manufacturing organisations. The findings show simultaneous improvement in manufacturing capabilities. Towards the end of the last decade, organisations implemented LM with radio frequency identification, e-kanban, simulation, etc.

Reviewing the case studies documenting LM implementation to comprehend the various nuances is a novel attempt. Furthermore, potential future research directions are identified for advancing the research in the domain of LM.

This study aims to examine how the knowledge breadth and depth of a patent affect its likelihood of being pledged. It also seeks to explore whether these relationships change diversely in different technological environments.

A complementary log-log model with random effects was conducted to test the hypotheses using a unique data set consisting of 348,927 invention patents granted by the China National Intellectual Property Administration from 1985 to 2015 belonging to 74,996 firms.

The findings reveal that both knowledge breadth and depth of a patent positively affect its likelihood of being pledged. Furthermore, the knowledge breadth and depth entail different degrees of superiority in different technological environments.

This study focuses on the effect of an individual patent’s knowledge base on its likelihood of being selected as collateral. It does not consider the influence of the overall knowledge characteristics of the selected patent portfolio.

Managers need to pay attention to patents’ knowledge characteristics and the changes in technological environments to select the most suitable patents as collateral and thus improve the success rate of pledge financing.

This study explores the impact of multidimensional characteristics of knowledge base on patent pledge financing within a systematic theoretical framework and incorporates technological environments into this framework.

The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important issue to investors and policymakers. This study aims to examine neural networks (NNs) for office property price index forecasting from 10 major Chinese cities for July 2005–April 2021.

The authors aim at building simple and accurate NNs to contribute to pure technical forecasts of the Chinese office property market. To facilitate the analysis, the authors explore different model settings over algorithms, delays, hidden neurons and data-spitting ratios.

The authors reach a simple NN with three delays and three hidden neurons, which leads to stable performance of about 1.45% average relative root mean square error across the 10 cities for the training, validation and testing phases.

The results could be used on a standalone basis or combined with fundamental forecasts to form perspectives of office property price trends and conduct policy analysis.

Due to the miniaturization of electronic devices, the increased current density through solder joints leads to the occurrence of electromigration failure, thereby reducing the reliability of electronic devices. The purpose of this study is to propose a finite element-artificial neural network method for the prediction of temperature and current density of solder joints, and thus provide reference information for the reliability evaluation of solder joints.

The temperature distribution and current density distribution of the interconnect structure of electronic devices were investigated through finite element simulations. During the experimental process, the actual temperature of the solder joints was measured and was used to optimize the finite element model. A large amount of simulation data was obtained to analyze the neural network by varying the height of solder joints, the diameter of solder pads and the magnitude of current loads. The constructed neural network was trained, tested and optimized using this data.

Based on the finite element simulation results, the current is more concentrated in the corners of the solder joints, generating a significant amount of Joule heating, which leads to localized temperature rise. The constructed neural network is trained, tested and optimized using the simulation results. The ANN 1, used for predicting solder joint temperature, achieves a prediction accuracy of 96.9%, while the ANN 2, used for predicting solder joint current density, achieves a prediction accuracy of 93.4%.

The proposed method can effectively improve the estimation efficiency of temperature and current density in the packaging structure. This method prevails in the field of packaging, and other factors that affect the thermal, mechanical and electrical properties of the packaging structure can be introduced into the model.

This paper aims to present a set of processes for obtaining the global spraying trajectory of a cold spraying robot on a complex surface.

The complex workpiece surfaces in the project are first divided by triangular meshing. Then, the geodesic curve method is applied for local path planning. Finally, the subsurface trajectory combination optimization problem is modeled as a GTSP problem and solved by the ant colony algorithm, where the evaluation scores and the uniform design method are used to determine the optimal parameter combination of the algorithm. A global optimized spraying trajectory is thus obtained.

The simulation results show that the proposed processes can achieve the shortest global spraying trajectory. Moreover, the cold spraying experiment on the IRB4600 six-joint robot verifies that the spraying trajectory obtained by the processes can ensure a uniform coating thickness.

The proposed processes address the issue of different parameter combinations, leading to different results when using the ant colony algorithm. The two methods for obtaining the optimal parameter combinations can solve this problem quickly and effectively, and guarantee that the processes obtain the optimal global spraying trajectory.

Counterproductive work behavior (CWB) has grown into a significant problem in the tourism industry, for both individual employees and organizations. Employees who feel ostracized in their workplace often engage in negative and disruptive behaviors. The purpose of this study is to explore the psychological mechanism between workplace ostracism and CWB among tourism employees.

Drawing on psychological contract theory and social cognitive theory, the study proposed a research framework to explain tourism employees’ counterproductive behavior. Data were collected from 228 hotel employees at two time points in Huangshan, China. Hierarchical regression and SPSS-PROCESS Macro were used to test all the hypotheses.

Findings show that workplace ostracism significantly increases employee CWB, mediated by psychological contract violation. Workplace ostracism increases perceptions of psychological contract violation when employee self-esteem is higher. The mediating effect of psychological contract violation is also moderated by self-esteem.

Using the framework of psychological contract theory and social cognitive theory, the authors advance the organizational behavior literature in the tourism field. The authors contextualize the uniqueness of Chinese workplace behavior and highlight the need to understand “losing face (mianzi) view” in workplace relationships. This research contributes to better understanding the dark side of tourism workplace behavior by examining the effects of psychological contract violation and employee’s self-esteem on workplace ostracism and CWB.

旅游业中的反生产行为（CWB）已经成为一个重要问题, 反生产行为对员工和组织都会产生影响。在工作场所感到被排斥的员工往往会从事消极和破坏性的行为。本文的目的是研究旅游业员工工作场所排斥与反生产行为之间的心理机制。

基于心理契约理论和社会认知理论, 本研究提出了一个研究框架来解释旅游业员工的反生产行为发生机制。我们在中国黄山景区对228名酒店员工进行了两个时间点的问卷调查。采用分层回归和SPSS PROCESS Macro来测试所有假设。

结果表明 工作场所排斥显著增加员工反生产行为, 心理契约违背在其中起着中介作用。当员工自尊心较高时, 职场排斥对心理契约违反的感知影响更强。心理契约违背的中介效应也受到自尊心的调节。

我们运用心理契约理论和社会认知理论的框架, 推动了旅游领域的组织行为研究进展。我们讨论了中国情境下职场行为的独特性, 并强调在职场关系中需要考虑“面子观”。我们通过展示心理契约违背和员工自尊心对工作场所排斥和反生产行为（CWB）的影响, 有助于更好地理解旅游工作场所行为的负面影响。

El comportamiento laboral contraproducente (CLC) en la industria turística se ha convertido en un problema significativo tanto para los empleados individuales como para las organizaciones. Los empleados que se sienten marginados en su lugar de trabajo suelen participar en comportamientos negativos y disruptivos. El objetivo de este trabajo es examinar los efectos de la violación del contrato psicológico y la autoestima del empleado en el ostracismo en el lugar de trabajo y en el comportamiento laboral contraproducente CLC y agregar nuevos conocimientos para comprender mejor el lado oscuro del comportamiento laboral turístico.

Realizamos una encuesta de cuestionario a 228 empleados de hotel en dos momentos en Huangshan, China. Se utilizaron la regresión jerárquica y el SPSS PROCESS Macro para probar todas las hipótesis.

Los resultados muestran que 1) el ostracismo en el lugar de trabajo aumenta significativamente la CLC de los empleados. 2) La violación psicológica del contrato juega un papel mediador entre el ostracismo en el lugar de trabajo y CLC. 3) El ostracismo en el lugar de trabajo aumenta las percepciones de violación psicológica del contrato cuando la autoestima de los empleados es mayor. 4) El efecto mediador de la violación psicológica del contrato también es moderado por la autoestima.

Utilizando el marco de la teoría del contrato psicológico y la teoría cognitiva social, avanzamos en la literatura del comportamiento organizacional en el campo del turismo. Contextualizamos la singularidad del comportamiento en el lugar de trabajo chino y destacamos la necesidad de comprender la 'pérdida de la visión de la cara (mianzi)' en las relaciones laborales. Esta investigación contribuye con nuevos conocimientos para comprender mejor el lado oscuro del comportamiento turístico en el lugar de trabajo al examinar los efectos de la violación psicológica del contrato y la autoestima de los empleados en el ostracismo en el lugar de trabajo.

Based on signaling theory, this paper aims to explore the impact of supply chain transparency (SCT) on firms' bank loan (BL) and supply chain financing (SCF) in the context of voluntary disclosure of supplier and customer lists.

Based on panel data collected from Chinese-listed firms between 2012 and 2021, fixed-effect models and a series of robustness checks are used to test the predictions.

First, improving SCT by disclosing major suppliers and customers promotes BL but inhibits SCF. Specifically, customer transparency (CT) is more influential in SCF than supplier transparency (ST). Second, supplier concentration (SC) weakens SCT’s positive impact on BL while reducing its negative impact on SCF. Third, customer concentration (CC) strengthens the positive impact of SCT on BL but intensifies its negative impact on SCF. Last, these findings are basically more pronounced in highly competitive industries.

This study contributes to the SCT literature by investigating the under-explored practice of supply chain list disclosure and revealing its dual impact on firms' access to financing offerings (i.e. BL and SCF) based on signaling theory. Additionally, it expands the understanding of the boundary conditions affecting the relationship between SCT and firm financing, focusing on supply chain concentration. Moreover, it advances signaling theory by exploring how financing providers interpret the SCT signal and enriches the understanding of BL and SCF antecedents from a supply chain perspective.