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This study aims to investigate the response of green investments of emerging countries to own-market uncertainty, oil-market uncertainty and COVID-19 effect/geo-political risks (GPRs), using the tail risks of corresponding markets as measures of uncertainty.

This study employs Westerlund and Narayan (2015) (WN)-type distributed lag model that simultaneously accounts for persistence, endogeneity and conditional heteroscedasticity, within a single model framework. The tail risks are obtained using conditional standard deviation of the residuals from an asymmetric autoregressive moving average – ARMA(1,1) – generalized autoregressive conditional heteroscedasticity – GARCH(1,1) model framework with Gaussian innovation. For out-of-sample forecast evaluation, the study employs root mean square error (RMSE), and Clark and West (2007) (CW) test for pairwise comparison of nested models, under three forecast horizons; providing statistical justification for incorporating oil tail risks and COVID-19 effects or GPRs in the predictive model.

Green returns responds significantly to own-market uncertainty (mostly positively), oil-market uncertainty (mostly positively) as well as the COVID-19 effect (mostly negatively), with some evidence of hedging potential against uncertainties that are external to the green investments market. Also, incorporating external uncertainties improves the in-sample predictability and out-of-sample forecasts, and yields some economic gains.

This study contributes originally to the green market-uncertainty literature in four ways. First, it generates daily tail risks (a more realistic measure of uncertainty) for emerging countries’ green returns and global oil prices. Second, it employs WN-type distributed lag model that is well suited to account for conditional heteroscedasticity, endogeneity and persistence effects; which characterizes financial series. Third, it presents both in-sample predictability and out-of-sample forecast performances. Fourth, it provides the economic gains of incorporating own-market, oil-market and COVID-19 uncertainty.

This paper aims to present an iterative path-following method with joint limits to solve the problem of large computation cost, movement exceeding joint limits and poor path-following accuracy for the path planning of hyper-redundant snake-like manipulator.

When a desired path is given, new configuration of the snake-like manipulator is obtained through a geometrical approach, then the joints are repositioned through iterations until all the rotation angles satisfy the imposed joint limits. Finally, a new arrangement is obtained through the analytic solution of the inverse kinematics of hyper-redundant manipulator. Finally, simulations and experiments are carried out to analyze the performance of the proposed path-following method.

Simulation results show that the average computation time is 0.1 ms per step for a hyper-redundant manipulator with 12 degrees of freedom, and the deviation in tip position can be kept below 0.02 mm. Experiments show that all the rotation angles are within joint limits.

Currently , the manipulator is working in open-loop, the elasticity of the driving cable will cause positioning error. In future, close-loop control based on real-time attitude detection will be used in in combination with the path-following method to achieve high-precision trajectory tracking.

Through a series of iterative processes, the proposed method can make the manipulator approach the desired path as much as possible within the joint constraints with high precision and less computation time.

The purpose of this article is based on the unit patent license fee model in the closed-loop supply chain.

This paper analyzes the impact of the bundling strategy of the retailer selling new products and remanufactured products on the closed-loop supply chain under the condition that the original manufacturer produces new products and the remanufacturer produces remanufacturing products.

The results show that alternative products can be bundled, and in many cases, the bundling of remanufactured products and new products is better than selling alone.

If the retailer chooses bundling, for the remanufacturer, when certain conditions are met, the benefits of bundling are greater than the separate sales at that time; for the original manufacturer, when the recycling price sensitivity coefficient is high, the bundling is better than separate sales.

The purpose of this study is to analyze the robot trends of the next generation.

This paper is divided into two sections: the key modern technology on which Europe's robotics industry has built its foundation is described. Then, the next key megatrends were analyzed.

Artificial intelligence (AI) and robotics are technologies of major importance for the development of humanity. This time is mature for the evolution of industrial and service robots. The perception of robot use has changed from threading to aiding. The cost of mass production of technological devices is decreasing, while a rich set of enabling technologies is under development. Soft mechanisms, 5G and AI have enabled us to address a wide range of new problems. Ethics should guide human behavior in addressing this newly available powerful technology in the right direction.

The paper describes the impact of new technology, such as AI and soft robotics. The world of work must react quickly to these epochal changes to enjoy their full benefits.

This study evaluates the moderating role of work-based social supports (i.e. supervisor support and co-worker support) in the relationship between job insecurity and job burnout among hospitality employees in Malaysia. Besides, the direct effect between job insecurity and job burnout is examined.

The cross-sectional data of this study were based on a total of 220 self-administered questionnaires that have been completed by hospitality employees from three different states in Malaysia. Respondents were recruited based on a snowball sampling approach. The data were collected during the COVID-19 pandemic, which was from October 2020 to January 2021.

Partial least square-structural equation modeling (PLS-SEM) was performed via SmartPLS software. The finding confirmed that job insecurity significantly intensifies employees' job burnout. Supervisor support and co-worker support were found to moderate the link between job insecurity and burnout. As anticipated, the relationship between job insecurity and job burnout increased when supervisor support is low. But high co-worker support was found to strengthen the impact of job insecurity on job burnout instead of the reverse.

This study supplements the existing literature by clarifying which sources of work-based social support (i.e. co-worker support or supervisor) is more salient in alleviating the adverse impact of job insecurity on job burnout during the COVID-19 pandemic among hospitality employees in Malaysia.

The objectives of this paper are to estimate the annual Malmquist TFP(total factor productivity) index of Korea and China’s road freight transport with DEA(data envelope analysis) and to decompose the index into technical efficiency change and technology change. In the process of the estimation, we used labor, capital, and fuel as input factors and ton-km of road freight transport as output factor. The panel data of Korea and China’s road freight transport industry from 1985 to 2004 are used. The results of the analysis show several points. First, there was no significant improvement in China’s TFP growth before 1997, but there was continuous growth in TFP since 1997 because of constantly increasing domestic freight transport demand. Second, there was downward trend in Korea’s TFP, especially there was a large reduction of productivity in 1998 because of the huge reduction of road freight transport demand during the period of the economic crisis. Third, the technology improvements play a significant role in the TFP growth and the technical efficiency had negative effects on the TFP growth of Korea. However, the technology improvements as well as the technical efficiency had positive effects on the TFP growth of China’s road freight transport industry.

In the presence of coronavirus disease 2019 (COVID-19), due to the social distance restriction, consumers' regular consumption behaviors and patterns have been changing fundamentally. Thereafter, an innovative group buying model has emerged and developed explosively with a specific focus on consumer's location, known as community-based group buying (CGB). The purpose of this paper is to investigate the transfer mechanism of user's trust in dyadic contexts of social and commercial role-playing in the CGB program.

This study adopts an empirical research method, with an online and offline questionnaire survey, a total of 382 responses have been obtained. Then, both descriptive analysis and hierarchical regression analysis are conducted to explore the dual roles of group leader and its corresponding effects on consumers' trust (i.e. emotional trust and behavioral trust) and engagement actions (i.e. purchase and share) in the CGB program.

Results indicate that resident's trust and their perception of group leader's friend role can positively enhance their engagement actions in the CGB programs. Meanwhile, for the purpose of profit maximization, the group leader is more willing to play a friend role in transactions no matter whether the role conflict exists.

Research findings provide some managerial insights for CGB platform on the selection and training of group leaders and the incentive mechanism design.

The purpose of this study is to address a significant gap in the understanding of entrepreneurship at the microfoundation level. It focuses on how individual entrepreneurs, specifically Hongbang entrepreneurs in China from 1896 to 1949, shape and transform their contexts. The aim is to provide a deeper understanding of the mechanisms that facilitate entrepreneurial success.

The study adopts a microhistorical approach, investigating the case of Hongbang entrepreneurs in China during 1896-1949. It involves an in-depth examination of historical records to explore the strategic interactions between these entrepreneurs and core stakeholders such as consumers, financial intermediaries, government regulators, and human resources. The research methodology emphasizes a process-oriented view, examining the evolution of personalized networks into extensive connections.

The research reveals that Hongbang entrepreneurs successfully reshaped their unfavorable embedded contexts by strategically collaborating with key stakeholders. They influenced consumer tastes, allied with financial intermediaries, negotiated with governments on regulation policies, and developed human resource stocks. The transformation was facilitated by the evolution of their networks from personalized to extensive connections. These findings highlight the localized strategies such as cronyism in resource acquisition within China’s private property development industry.

This study contributes to the field by offering insights into entrepreneurial contextualization and networking. It sheds light on the complex interplay between entrepreneurs and their contexts, providing a nuanced understanding of localized strategies in the Chinese context. The findings add value to the discourse on entrepreneurship by elucidating the strategic and processual acts through which entrepreneurs engage with stakeholders and reshape their environments.

This study aims to use regression Least-Square Support Vector Machine (LS-SVM) as a probabilistic model to determine the factor of safety (FS) and probability of failure (PF) of anisotropic soil slopes.

This research uses machine learning (ML) techniques to predict soil slope failure. Due to the lack of analytical solutions for measuring FS and PF, it is more convenient to use surrogate models like probabilistic modeling, which is suitable for performing repetitive calculations to compute the effect of uncertainty on the anisotropic soil slope stability. The study first uses the Limit Equilibrium Method (LEM) based on a probabilistic evaluation over the Latin Hypercube Sampling (LHS) technique for two anisotropic soil slope profiles to assess FS and PF. Then, using one of the supervised methods of ML named LS-SVM, the outcomes (FS and PF) were compared to evaluate the efficiency of the LS-SVM method in predicting the stability of such complex soil slope profiles.

This method increases the computational performance of low-probability analysis significantly. The compared results by FS-PF plots show that the proposed method is valuable for analyzing complex slopes under different probabilistic distributions. Accordingly, to obtain a precise estimate of slope stability, all layers must be included in the probabilistic modeling in the LS-SVM method.

Combining LS-SVM and LEM offers a unique and innovative approach to address the anisotropic behavior of soil slope stability analysis. The initiative part of this paper is to evaluate the stability of an anisotropic soil slope based on one ML method, the Least-Square Support Vector Machine (LS-SVM). The soil slope is defined as complex because there are uncertainties in the slope profile characteristics transformed to LS-SVM. Consequently, several input parameters are effective in finding FS and PF as output parameters.

Drawing on the theory of memory-dominant logic, this study aims to examine how the substantive staging of the servicescape, experience co-creation, experiential satisfaction and experience intensification affect experience memorability and hedonic well-being in the case of unmanned smart hotels.

An online survey was used, with the target respondents being hotel guests people aged 18 years and older who had been recent guests of the FlyZoo Hotel in Hangzhou, China. Data were collected online from 429 guests who had stayed in the hotel between April and June 2023. Data analysis was undertaken using structural equation modelling.

The results suggest that all the proposed four constructs are positive drivers of a memorable unmanned smart hotel experience. The relationship between the memorability of the hotel experience and hedonic well-being was found to be significant and positive.

Unmanned smart hotels should ensure that all smart technologies function effectively and dependably and offer highly personalised services to guests, allowing them to co-create their experiences. This will lead to the guest receiving a satisfying and memorable experience. To enable experience co-creation using smart technologies, unmanned smart hotels could provide short instructional videos for guests, as well as work closely with manufacturers and suppliers to ensure that smart technology systems are regularly updated.

This study investigates the antecedents and outcomes of a novel phenomenon and extends the concept of memorable tourism experiences to the context of unmanned smart hotels.