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The paper aims to develop a framework to facilitate the evaluation of the complexities of working in multi-level governance and partnership and to assess the extent to which collaboration adds value in terms of both process and outcomes.

The paper applies the fuzzy analysis hierarchy process (FAHP) to the design of an evaluation framework for partnerships and uses data from a questionnaire survey in Wuhan, China, to validate the framework.

The paper finds that the effectiveness of multi-level governance and partnerships is primarily determined by such factors as clarity of framework for partnership, consensus on mission statement of strategic partnership, mechanisms for joint initiation and implementation of projects and removal of barriers to flow of resources.

The paper shows that policymakers need to adopt an evaluation approach to improve the effectiveness of multi-level governance and partnerships.

The paper provides a framework for building multi-level governance and partnerships in the Chinese context.

As two essential styles of firm decision-making, the relationships among effectuation logic, causation logic and firm performance are unclear. It is helpful to deepen the understanding of reasoning theory and the process of decision-making. The purpose of this paper is to explore the relationship between effectuation logic, causation logic and firm performance.

Based on 31 independent empirical studies (including 11,600 samples) published by predecessors, meta-analysis is used to systematically integrate the impact of two decision-making styles on firm performance and explore the potential factors affecting their relationship.

The results show a positive correlation between two decision-making styles and firm performance and the influence of effectuation decision-making style in firm performance is slightly stronger. However, the application environment is different: in the emerging market, the causation decision-making style is more effective for firm performance management. When the firm chooses the effectuation decision-making style, it is more effective for performance management in the emerging market. In addition, the industry type, firm performance evaluation tools, national development level and firm scale and firm age can significantly moderate the impact of two decision-making styles on firm performance.

Both decision-making logics are possible ways for firm to success. Still, the future needs to dig deeper into the black box that can unlock the decision-making styles to achieve firm performance or competitive advantage based on other factors of the decision-behavior-outcome business model, more longitudinal data and experiments.

To the best of the authors’ knowledge, this is the first study to explore the impact of decision-making styles (effectuation logic and causation logic) on firm performance using a meta-analysis.

Risk perception is an essential factor affecting how individuals evaluate risk, make decisions and behave. The impact of risk perception on customer purchase behavior has been widely studied; however, the association has been debated. Therefore, the purpose of this paper is to examine the relationship between risk perception and customer purchase behavior and to examine factors that could moderate it.

This study conducted a meta-analysis of this relationship and examined factors that could moderate it. Six databases were comprehensively searched. Two reviewers independently selected the studies for inclusion, extracted data and assessed quality. Pearson's r was used as the effect estimate. A total of 33 studies were included in the meta-analysis.

The results revealed a negative relationship between risk perception and customer purchase behavior. The geographical region, purchase channel and country development level affected the relationship. The correlation between perceived risk and purchase behavior in European consumers was the highest, followed by the correlation in American consumers; the weakest correlation was found in Asian consumers. For consumers in developed countries, perceived risk had a stronger negative influence on customer purchase behavior than that for consumers in developing countries. The perceived risk of online purchase channels had a stronger negative impact on customer purchase behavior than that of offline purchase channels.

Risk perception is a useful context in which to explain barriers to customer purchase behavior. In addition, reducing consumers’ risk perception and perfecting the market transaction process with respect to buying behavior should be further studied.

The findings of this review indicate a direct negative relationship between risk perception and customer purchase behavior. To the best of the authors’ knowledge, this review is the first to meta-analytically summarize the impact of risk perception on customer purchase behavior in social sciences research, and it also illuminates new perspectives for future studies.

With the development of the service sector and network communication technology, customers are involved in business activities through virtual communities and demonstrating the ability to create personalized products or services with companies. This paper systematically studied the driving factors of customer participation in service innovation. Based on related literature research achievements and a better development of virtual brand communities in China-XiaoMi community, this paper empirically analyzed the different factors. The results showed that self-efficacy and trust have a significant positive impact on knowledge sharing and co-production, while the perceived risk and helpfulness have a significant positive impact on knowledge sharing. Finally, effective strategies and recommendations are proposed on how companies encourage and manage customers to effectively participate in service innovation of virtual brand communities based on the conclusions of analysis.

The teenager community is the most affected community by cybercrime in the COVID-19 era. Increasing social networks and facilitating teenager access to the Internet have increased the probability of cybercrimes. On the other hand, entertainment such as mobile and computer games is top-rated among teenagers. Teenagers' tendency to cybercrime may be influenced by individual, parent, social, economic and political factors. Studying the impact of social networks, mobile games and parents' religious attitudes on teenagers' tendency to cybercrimes in the COVID-19 era is the primary goal of this paper.

The outbreak of COVID-19 caused a considerable change in the world and the lifestyle of all people. Information and Communication Technology (ICT) was also affected by the special conditions of this virus. Changes in ICT and rapid access to it have empowered individuals and organizations, and people have increased civic participation and interaction through ICT. However, the outbreak of COVID-19 has created new challenges for the government and citizens and may cause new crimes. Cybercrime is a type of crime that occurs in a cyber environment. These crimes range from invasions of privacy to crimes in which the offender vaguely paralyzes the macroeconomic. In this research, 265 students of high schools and universities are used for collecting data by utilizing a survey. Measuring actions have been done in all surveys employing a Likert scale. The causal pattern is assessed through a constructional equation modeling procedure to study the scheme's validity and reliability.

The outcomes have indicated that social networks have no significant relationship with teenagers' tendency to cybercrimes in the COVID-19 era. Mobile games have a mild effect on teenagers' tendency to cybercrimes in the COVID-19 era, and parents' religious attitudes significantly impact teenagers' tendency to cybercrimes in the COVID-19 era.

Current research also has some restrictions that must be noticed in assessing the outcomes. First, sample research was selected from high schools and universities in one city. So, the size of the model is small, and the generalization of results is limited. Second, this research may have ignored other variables that affect the tendency of teenagers' to cybercrime. Future researchers intend to investigate the parents' upbringing system's impact on teenager's trend to cybercrime in the COVID-19 era. Future research can also examine practical factors such as parental upbringing, attitudes toward technology development and virtual addiction in the COVID-19 era.

In this study, teenagers' tendency to cybercrimes in the COVID-19 era is investigated, and a procedure is applied depending on a practical occasion. This article's offered sample provides a perfect framework for influencing parents' social networks, mobile games and religious attitudes on teenagers' tendency to cybercrimes in the COVID-19 era.

Based on social cognitive theory, this study aims to explore the influence of supervisor bottom-line mentality (SBLM) on employee knowledge behavior (knowledge territorial behavior and knowledge sabotage behavior). The study first investigates the role of an ethical decision-making mechanism (moral disengagement) in mediating this relationship. In addition, it considers the possible boundary conditions to supplement research on the influence of SBLM in the knowledge management field.

The authors collected 256 data points from employees across three stages using convenience sampling. The authors then tested the proposed hypothesis using hierarchical regression and bootstrap methods.

The results demonstrated that SBLM promotes employees’ moral disengagement, leading to more knowledge territorial behavior and knowledge sabotage behavior. Furthermore, high power distance orientation among employees exacerbates the ill effects of SBLM according to the first stage of a moderated mediation model. Employees with such an orientation are more likely to respond to a SBLM by exhibiting a higher level of moral disengagement, thus increasing their knowledge territorial behavior and knowledge sabotage behavior.

Research on the influence of SBLM in the knowledge management field is limited. This study not only clarifies the relationships between SBLM and two types of knowledge behavior (knowledge territorial behavior and knowledge sabotage behavior) but also enriches the research on the antecedents of these two types of knowledge behavior.

The purpose of this paper is to design an exoskeleton robot and present a corresponding rehabilitation training method for patients in different rehabilitation stages.

This paper presents a lightweight seven-degrees-of-freedom (DOF) cable-driven exoskeleton robot that is wearable and adjustable. After decoupling joint movement caused by a cable-driven mechanism, active rehabilitation training mode and passive rehabilitation training mode are proposed to improve the effect of rehabilitation training.

Simulations and experiments have been carried out, and the results validated the feasibility of the proposed mechanism and methods by a fine rehabilitative effect with different persons.

This paper designed a 7-DOF cable-driven exoskeleton robot that is suitable for patients of different body measurements and proposed the active rehabilitation training mode and passive rehabilitation training mode based on the cable-driven exoskeleton robot.

Dielectric barrier discharge (DBD) is widely used in the treatment of skin disease, surface modification of material and other fields of electronics. The purpose of this paper is to design a high-performance power supply with a compact structure for excimer lamps in electronics application.

To design a high-performance power supply with a compact structure remains a challenge for excimer lamps in electronics application, a current-source type power supply in a single stage with power factor correction (PFC) is proposed. It consists of an excitation voltage generation unit and a PFC unit. By planning the modes of the excitation voltage generation unit, a bipolar pulse excitation voltage with a high rising and falling rate is generated. And a high power factor (PF) on the AC side is achieved by the interaction of a non-controlled rectifier and two inductors.

The experimental results show that not only a high-frequency and high-voltage bipolar pulse excitation voltage with a high average rising and falling rate (7.51GV/s) is generated, but also a high PF (0.992) and a low total harmonic distortion (5.54%) is obtained. Besides, the soft-switching of all power switches is realized. Compared with the sinusoidal excitation power supply and the current-source power supply, the proposed power supply in this paper can take advantage of the potential of excimer lamps.

A new high-performance power supply with a compact structure for DBD type excimer lamps is proposed. The proposed power supply can work stably in a wide range of frequencies, and the smooth regulation of the discharge power of the excimer lamp can be achieved by changing the switching frequency. The ideal excitation can be generated, and the soft switching can be realized. These features make this power supply a key player in the outstanding performance of the DBD excimer lamps application.

Current reinforcement learning (RL) algorithms are facing issues such as low learning efficiency and poor generalization performance, which significantly limit their practical application in real robots. This paper aims to adopt a hybrid model-based and model-free policy search method with multi-timescale value function tuning, aiming to allow robots to learn complex motion planning skills in multi-goal and multi-constraint environments with a few interactions.

A goal-conditioned model-based and model-free search method with multi-timescale value function tuning is proposed in this paper. First, the authors construct a multi-goal, multi-constrained policy optimization approach that fuses model-based policy optimization with goal-conditioned, model-free learning. Soft constraints on states and controls are applied to ensure fast and stable policy iteration. Second, an uncertainty-aware multi-timescale value function learning method is proposed, which constructs a multi-timescale value function network and adaptively chooses the value function planning timescales according to the value prediction uncertainty. It implicitly reduces the value representation complexity and improves the generalization performance of the policy.

The algorithm enables physical robots to learn generalized skills in real-world environments through a handful of trials. The simulation and experimental results show that the algorithm outperforms other relevant model-based and model-free RL algorithms.

This paper combines goal-conditioned RL and the model predictive path integral method into a unified model-based policy search framework, which improves the learning efficiency and policy optimality of motor skill learning in multi-goal and multi-constrained environments. An uncertainty-aware multi-timescale value function learning and selection method is proposed to overcome long horizon problems, improve optimal policy resolution and therefore enhance the generalization ability of goal-conditioned RL.