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The paper aims to propose a virtual reality (VR) wisdom teaching model in open university English course from the perspective of “Metaverse”. The study aims to testify the stimulation for English learning and the effectiveness of English-expressing with VR tools for adult learners from the practice in a pilot reform project.

The paper opted for an exploratory study using ICARE Design Model as the framework, under the grounded theories of constructivism and multi-modal teaching. The study compared the evaluation data of one-semester English learning performance between the experimental class (67 students) with VR practice and the controlled class (67 students), including speaking test score, qualitative feedback and in-depth experience analysis. The data were complemented by reflection paper analysis, including manual evaluation (the criteria of semantics, pronunciation, fluency and completeness), questionnaire survey (in the form of five-point Likert scale) and semi-structured interview.

The paper provides empirical insights about the VR wisdom teaching model in English language teaching and learning in a Chinese Open University. The empirical results suggest that “3I” features of VR technology could make up for the shortcomings of traditional English classes in open universities in China, and VR resources designed with curriculum teaching materials could also be helpful for students’ command of knowledge points and language skills. What’s more, the sense of authentic experience in virtual could promote the teaching and learning effect in college English classes.

The present study focuses on a wisdom mode of foreign language teaching and learning for adult learners in open education, so the research results may lack generalizability. Therefore, researchers are encouraged to further explore the deep integration of VR/artificial intelligence in foreign language teaching and learning.

This paper fulfills an identified need to study how VR tools provide an engaging, fun and immersive language learning environment, to enhance autonomous learning and learning engagement.

When it comes to the high accuracy autonomous motion of the mobile robot, it is challenging to effectively control the robot to follow the desired trajectory and transport the payload simultaneously, especially for the cloud robot system. In this paper, a flexible trajectory tracking control scheme is developed via iterative learning control to manage a distributed cloud robot (BIT-6NAZA) under the payload delivery scenarios.

Considering the relationship of six-wheeled independent steering in the BIT-6NAZA robot, an iterative learning controller is implemented for reliable trajectory tracking with the payload transportation. Meanwhile, the stability analysis of the system ensures the effective convergence of the algorithm.

Finally, to evaluate the developed method, some demonstrations, including the different motion models and tracking control, are presented both in simulation and experiment. It can achieve flexible tracking performance of the designed composite algorithm.

This paper provides a feasible method for the trajectory tracking control in the cloud robot system and simultaneously promotes the robot application in practical engineering.

The flexible mode transitions, multiple power sources and system uncertainty lead to challenges for mode transition control of four-wheel-drive hybrid powertrain. Therefore, the purpose of this paper is to improve dynamic performance and fuel economy in mode transition process for four-wheel-drive hybrid electric vehicles (HEVs), overcoming the influence of system uncertainty.

First, operation modes and transitions are analyzed and then dynamic models during mode transition process are established. Second, a robust mode transition controller based on radial basis function neural network (RBFNN) is proposed. RBFNN is designed as an uncertainty estimator to approximate lumped model uncertainty due to modeling error. Based on this estimator, a sliding mode controller (SMC) is proposed in clutch slipping phase to achieve clutch speed synchronization, despite disturbance of engine torque error, engine resistant torque and clutch torque. Finally, simulations are carried out on MATLAB/Cruise co-platform.

Compared with routine control and SMC, the proposed robust controller can achieve better performance in clutch slipping time, engine torque error, vehicle jerk and slipping work either in nominal system or perturbed system.

The mode transition control of four-wheel-drive HEVs is investigated, and a robust controller based on RBFNN estimation is proposed. Compared results show that the proposed controller can improve dynamic performance and fuel economy effectively in spite of the existence of uncertainty.

As the quality of the environment decreases, enterprises and consumers' awareness of environmental protection is constantly improving. More and more enterprises begin to increase their investment in carbon emission reduction and attract environmentally friendly consumers to buy low-carbon products through advertising. The purpose of this paper is to utilize a realistic differential game model to provide dynamic carbon emission reduction strategies, advertising strategies and cooperation methods for complex supply chain members from a long-term perspective.

This paper uses the extend Vidale-Wolfe model (V-W model) to discuss the dynamic joint emission reduction strategy in the supply chain.

(1) When consumers' awareness of environmental protection increases, on the whole, carbon emission reduction and profit of products show an upward trend. (2) From a long-term perspective, the manufacturer's advertising subsidy to one of the retailers is the best choice. If the strength of the two retailers is unbalanced, the manufacturer will choose to cooperate with the dominant retailer. (3) Advertising, as a marketing means for retailers to promote low-carbon products, can alleviate the adverse effects of prisoner's dilemma in a semi-cooperative state, but it cannot achieve the Pareto optimization result.

This paper focuses on the analysis of the situation that when the manufacturer is the leader and thinks that consumers are active advocates of low-carbon products.

The results of this paper can provide theoretical basis for the joint emission strategy of supply chain members in low-carbon environment.

This conceptual paper focuses on a common observation in the implementation stage of reward-based crowdfunding (RBC) – entrepreneurs' failures and delays in delivery of rewards to investors, which, in turn, may be perceived as violations of reward delivery obligations.

Drawing on entrepreneurial personality theory and psychological contract theory, this paper develops propositions and identifies factors related to both entrepreneurs (overconfidence and narcissism) and factors related to investors (types of motivators and psychological contracts) that may explain the perceived violations of reward delivery obligations. Implications for theory and practice are also discussed.

The theoretical analysis, by wielding two independently developed literatures, has demonstrated that it is important to investigate factors that are related to both investors and entrepreneurs in understanding issues and challenges at different stages of the RBC model. The authors believe that the current analysis provides an integrated understanding and a solid foundation for researchers to further examine these issues by empirically testing these propositions.

The authors examined two previously understudied psychological factors in the context of RBC – entrepreneurial traits, mainly overconfidence and narcissism, and the type of psychological contracts formed between investors and entrepreneurs, both of which, according to McKenny et al. (2017), need greater attention from researchers studying crowdfunding.

This paper aims to explore whether nascent women entrepreneurs perceive more risks than men, and to determine how higher risk perceptions might limit start-up decisions by mediating the potential influence of passion and self-efficacy.

This study surveyed 103 participants in Sweden – both women and men – who, in the period 2008 through 2011, intended to start a business. ANOVA tests and binominal logistic regression models were conducted to test hypothesized framework.

The authors found that nascent women entrepreneurs perceive more risk than nascent male entrepreneurs, that risk perceptions influence start-up decisions and that risk preferences partial out the otherwise identified influence of passion on start-up decisions.

The authors reveal a consequence of gender socialization and how it impacts the start-up decisions of nascent women entrepreneurs. Support systems should consider developing activities that change the public’s perception of who is an entrepreneur and seek ways to balance risk perceptions between men and women.

The authors argue here that risk perceptions play a prominent role in start-up decisions. Specifically, they consider that nascent women entrepreneurs perceive more risks than men, and that their view of risk partials out any potential influence of their perceived passion and self-efficacy on their start-up decision.

The purpose of this paper is to identify the critical components of a complex system by using survival signature. First, a complex system is abstracted with varying scales and generates a multi-levels model. Then reliability evaluations can be conducted by survival signature from rough to fine for tracing and identifying them. Finally, the feasibility of the proposed approach is demonstrated by an actual production system.

The paper mainly applies a multi-level evaluating strategy for the reliability analysis of complex systems with components of multiple types. In addition, a multi-levels model of a complex system is constructed and survival signature also used for evaluation.

The proposed approach was demonstrated to be the feasibility by an actual production system that is used in the case study.

The case study was performed on a system with simple network structure, but the proposed approach could be applied to systems with complex ones. However, the approach to generate the digraphs of abstraction levels for complex system has to be developed.

So far the approach has been used for the reliability analysis of a machining system. The approach that is proposed for the identification of critical components also can be applied to make maintenance decision.

The multi-level evaluating strategy that was proposed for reliability analysis and the identification of critical components of complex systems was a novel method, and it also can be applied as index to make maintenance planning.

It has been believed that entrepreneurship involves a lot of risk nowadays, yet it is assumed that not being entrepreneurial can be a bigger risk. Enhancement in entrepreneurial behaviour can improve performance of the individual as well as that of the organization. This paper aims to propose a conceptual model that empirically examines the relationship of role satisfaction and its dimensions with entrepreneurial behaviour in an Indian context.

Three hundred and thirty three executives/managers from many organizations in India were approached. Cronbach's α, factor analysis, correlation and regression analyses were applied to check the research hypotheses.

It was found that most of the variables in the study were having significant relationship. All the hypotheses were supported. Furthermore, achievement, influence, control and affiliation were found to be important predictors of entrepreneurial behaviour.

This paper would help researchers and practitioners to work on these variables in some other cultures and nations also.

Improvement in role satisfaction will enhance the entrepreneurial behaviour among Indian business executives/managers which will improve the overall performance of the organization.

It is an innovative attempt to utilize role satisfaction to improve entrepreneurial behaviour in an Indian framework.

The purpose of this paper is to describe and analyze the benefits of the application of a requirements engineering framework to assist Enterprise Resource Planning (ERP) development. This framework combines the technology-driven and the process-driven approaches for requirements analysis and implementation. Specific business process modeling methods enhance the framework and assist the formulation of the functional specifications of the ERP system and the management of requirements.

A case study strategy was chosen as the most appropriate method to answer the research question and test the theoretical propositions. The case study’s unit of analysis is a Greek manufacturing company and its ERP implementation project. A requirements engineering framework enhanced with business process modeling methods was applied and the results were evaluated using metrics for ERP implementation success. Data were collected using multiple sources of evidences, including interviews with various stakeholders, structured questionnaires, direct observations, vendors’ functionality papers and company’s documentation.

This study proves that the configuration of ERP’s reference models together with the adjustments of organization’s processes, provided through a structured requirements engineering framework can lead to reliable functional specifications, a smooth transition to an ERP system and, eventually, to successful ERP implementation, concerning its alignment with requirements.

A single case study is conducted in a typical manufacturing company, providing opportunities for further research in other industries, testing in parallel well-defined requirements and other success factors for ERP implementation.

The paper fulfils the identified needs for applied methodologies and frameworks for requirements engineering which can assist successful ERP implementations.