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This study in the hospitality industry aims to explore the underlying mechanisms through which socially responsible human resource management (SRHRM) affects frontline employees’ knowledge sharing, as well as the moderating effects of role conflict and role ambiguity.

Two data waves have been collected from one of the largest restaurant chains in China. Using Mplus 7.0, a structural equation modeling model is empirically tested to investigate the hypothesized moderated mediation model.

First, SRHRM appears to foster frontline employees’ perceived respect and organizational trust and further stimulates their knowledge sharing. Second, role conflict is found to weaken the relationship between SRHRM and organizational trust, while role ambiguity seems to weaken the strength of the linkage between SRHRM and perceived respect.

Managers should make SRHRM policies more visible and implement appropriate SRHRM practices to facilitate employees proactively to share knowledge at work. Furthermore, managers should realize the dark side effects of role conflict and role ambiguity, as they might hinder the positive impact of SRHRM on knowledge sharing.

This study uncovers the meditating roles of perceived respect and organizational trust through which SRHRM impacts on employees’ knowledge sharing. By incorporating the possible moderating roles of role conflict and role ambiguity, this scholarly work also increases the understanding of possible hindrances in this regard.

The purpose of this article is to provide an assessment of business educational reform requirements in China, in the light of current employability needs.

After introducing the problem the paper discusses labour market demands for business graduates. The paper continues with a thorough conceptualisation of the concept of employability and current notions on career development, and concludes with proposals for reforming the business education curriculum.

Employability enhancement should be an integrated activity that is undertaken in close collaboration between different parties, and to eliminate recruitment bottlenecks, policies that affect both graduates' suitability and labour requirements are needed.

The paper is a useful source of information and advice for educators, employers, and business education students planning to invest in their future employability. The paper is meant to evoke discussion and to stimulate curriculum reform efforts.

This paper focuses on current labour market demands and offers insights for educational institutions engaged in optimizing curricula.

The aim of this paper is to learn the views of law, business and philosophy students in China on the ethics of tax evasion.

This paper begins with a review of the literature and identifies the main issues and summarizes the three main viewpoints that have emerged over the centuries. It then reports on the results of a survey of Chinese law, business and philosophy students who were asked their opinions on the ethics of tax evasion. The survey consisted of 15 statements, representing the 15 issues and three viewpoints that have emerged over the centuries. Participants were asked to signify the extent of their agreement with each statement by placing a number from 1 to 7 in the space provided. About 256 usable responses were received. The data were then analyzed to determine which of the three viewpoints was dominant among the sample population. The three groups were compared to determine whether their responses were different. Male scores were also compared to female scores to determine if the responses differed by gender.

There was widespread approval for tax evasion on ethical grounds, although some arguments to support tax evasion were stronger than others. Males and females were equally opposed to tax evasion. Business and economics students were more favorably disposed to tax evasion than were law and philosophy students.

The sample was limited to students in just three majors in one Chinese city. Sampling students in other majors and in other Chinese cities might have yielded different results. Sampling Chinese business people, Chinese lawyers and accountants might have also yielded different results. No comparison based on age was made because the sample consisted of people from the same age group. Choosing a sample consisting of different ages might have revealed differences in opinion based on age.

If the government of China wants to reduce the extent of tax evasion, the first step is to determine why people evade taxes. The second step is to take measures to remove the reasons why people evade taxes. The present study ranks the reasons why people think tax evasion is morally acceptable. Corruption, waste and unfairness were the three strongest reasons for justifying tax evasion. Thus, three things government can do to reduce the extent of tax evasion is to become less corrupt, less wasteful and less unfair. This study has widespread implications for other countries, since the same arguments have been used in the literature for the past 500 years to justify tax evasion. The findings for China might be applied to any number of other countries.

This paper is the first to rank the reasons that have traditionally been given to justify tax evasion for a city in central China and it is one of only a few to rank reasons justifying tax evasion for any country.

In this study, a highly sensitive and quantitative analysis method using surface-enhanced Raman scattering (SERS)-labeled immunoassay is adopted for bisphenol A bisphenol A (BPA) detection in water samples.

Primarily, an excellent SERS immuno-nanoprobe is prepared, which relays on Au/Ag core-shell nanoparticles tagged 4-mercaptobenzoic acid (4MBA) and labeled with specific antibody against BPA. Second, the coating antigen of 4,4-Bis(4-hydroxyphenol) valeric acid (BVA) coupling poly-L-lysine (PLL) conjugate (BVA-PLL) is fastened on the substrate. Based on competitive immunoassay, the antibody labeled on SERS immuno-nanoprobe will bind with the free BPA and BVA-PLL competitively.

A calibration curve was obtained by plotting the intensity of SERS signal of 4MBA at 1007 cm⁻¹ versus the concentration of BPA. The results indicated that the limit of detection (LOD) for BPA is 1 ng/mL and present a great capacity for higher sensitivity. Furthermore, the method was able to quantitatively detect BPA in water samples, which was validated by high performance liquid chromatography (HPLC).

The method was developed based on competitive immunoassay, and the conjugate (BVA-PLL) was chosen as the coating antigen. Au/Ag core-shell nanoparticles played as the SERS active substrate and were labeled with Raman reporter. The value of this paper is supplying a wide potential for analysis of target analytes in the environmental monitoring and food safety.

As a transition economy, China is interested in allocating its limited innovation resources economically, reasonably and efficiently to produce as many outputs as possible with its limited financial and human resources. Nonetheless, what is the efficiency of the allocation of innovative resources for civil–military integration enterprises, and what factors hinder its efficiency improvement? The purpose of this paper is to explore these problems.

The improved two-stage network data envelopment analysis (DEA) method is used to measure the overall efficiency and stage efficiency of the innovation resource allocation of 58 Chinese civil–military integration listed companies from 2010 to 2016. Tobit model is used to analyze the influencing factors of resource allocation efficiency.

The results indicate that the overall efficiency and stage efficiency of innovation resource allocation fluctuate in varying degrees during the period. The optimization of overall efficiency is restricted by lower efficiency of innovation achievement transformation. Enterprise scale was found to have a significant negative impact on both overall and two-stage efficiencies. Proportion of research and development (R&D) personnel had a positive effect on the overall and two-stage efficiency. Government support had a significant positive effect on the stage of innovation resource development and overall efficiency.

Previous research studies have used either the DEA or stochastic frontier analysis method to measure the efficiency of innovation activities as a whole and ignored the stage of initial investment to final output in innovation activities. That is, the process in which initial input of R&D resources becomes innovation output, and then becomes economic benefits. Therefore, this paper studies the efficiency of innovation resource allocation of civil–military integration listed companies. The improved two-stage chain network DEA method and Tobit model were used.

Consumers have pervasively relied on mobile reviews in digital economy. However, little knowledge exists regarding how customers adopt several mobile reviews to make purchasing decisions. With the assistance of reader-response theory, this study investigates how the consistency of product reviews, in terms of their adherence to both other reviews and the prior experience of the customer, affect perceived quality, confirmation of the customer's expectations, the customer's level of trust in the seller and the consequent purchase intention.

Based on a scenario simulation and an online experiment to collect data, the authors employed AMOS to test the proposed hypotheses using survey data collected from 314 customers in Study 1 and 420 consumers in Study 2.

The results indicate that global consistency positively and significantly contributes to confirmation, perceived quality and trust in sellers while sequential inconsistency positively and significantly influences perceived quality. Meanwhile, purchase intention is positively and significantly promoted by confirmation, perceived quality and trust in sellers, and initial valence has some moderating effects on these relationships.

This study contributes to the understanding of how customers apply product reviews to make purchasing decisions from a new angle. It also elucidates the way in which the perceived consistency of product reviews affects how reviewers are perceived and the consequent effect of these perceptions on a customer's purchase intentions.

When the mobile manipulator is traveling on an unconstructed terrain, the external disturbance is generated. The load on the end of the mobile manipulator will be affected strictly by the disturbance. The purpose of this paper is to reject the disturbance and keep the end effector in a stable pose all the time, a control method is proposed for the onboard manipulator.

In this paper, the kinematics and dynamics models of the end pose stability control system for the tracked robot are built. Through the guidance of this model information, the control framework based on active disturbance rejection control (ADRC) is designed, which keeps the attitude of the end of the manipulator stable in the pitch, roll and yaw direction. Meanwhile, the control algorithm is operated with cloud computing because the research object, the rescue robot, aims to be lightweight and execute work with remote manipulation.

The challenging simulation experiments demonstrate that the methodology can achieve valid stability control performance in the challenging terrain road in terms of robustness and real-time.

This research facilitates the stable posture control of the end-effector of the mobile manipulator and maintains it in a suitable stable operating environment. The entire system can normally work even in dynamic disturbance scenarios and uncertain nonlinear modeling. Furthermore, an example is given to guide the parameter tuning of ADRC by using model information and estimate the unknown internal modeling uncertainty, which is difficult to be modeled or identified.

Intelligence level of a crowd network is defined as the expected reward of the network when completing the latest tasks (e.g. last N tasks). The purpose of this paper is to improve the intelligence level of a crowd network by optimizing the profession distribution of the crowd network.

Based on the concept of information entropy, this paper introduces the concept of business entropy and puts forward several factors affecting business entropy to analyze the relationship between the intelligence level and the profession distribution of the crowd network. This paper introduced Profession Distribution Deviation and Subject Interaction Pattern as the two factors which affect business entropy. By quantifying and combining the two factors, a Multi-Factor Business Entropy Quantitative (MFBEQ) model is proposed to calculate the business entropy of a crowd network. Finally, the differential evolution model and k-means clustering are applied to crowd intelligence network, and the species distribution of intelligent subjects is found, so as to achieve quantitative analysis of business entropy.

By establishing the MFBEQ model, this paper found that when the profession distribution of a crowd network is deviate less to the expected distribution, the intelligence level of a crowd network will be higher. Moreover, when subjects within the crowd network interact with each other more actively, the intelligence level of a crowd network becomes higher.

This paper aims to build the MFBEQ model according to factors that are related to business entropy and then uses the model to evaluate the intelligence level of a number of crowd networks.

This paper aims to optimize and evaluating the performance of the crowd networks through analyzing their information sharing patterns. That is, in a crowd network, the qualities of accomplishing tasks are highly dependent on the effective information sharing among intelligent subjects within the networks. Hence, proposing an adaptive information-sharing approach can help improve the performance of crowd networks on accomplishing tasks that are assigned to them.

This paper first introduces the factors that affect effectiveness of information-sharing pattern: the network topology, the resources owned by intelligent subjects and the degree of information demand. By analyzing the correlation between these factors and the performance of crowd networks, an Adaptive Information Sharing Approach for Crowd Networks (AISCN approach) is proposed. By referring to information needed for accomplishing the historical tasks that are assigned to a crowd network, the AISCN approach can explore the optimized information-sharing pattern based on the predefined composite objective function. The authors implement their approach on two crowd networks including bee colony and supply chain, to prove the effectiveness of the approach.

The shared information among intelligent subjects affects the efficiency of task completion in the crowd network. The factors that can be used to describe the effectiveness of information-sharing patterns include the network topology, the resources owned by intelligent subjects and the degree of information demand. The AISCN approach used heuristic algorithm to solve a composite objective function which takes all these factors into consideration, so that the optimized information-sharing pattern can be obtained.

This paper introduces a set of factors that can be used to describe the correlation between information-sharing pattern and performance of crowd network. By quantifying such correlation based on these factors, this paper proposes an adaptive information-sharing approach which can explore the optimized information-sharing pattern for a variety of crowd networks. As the approach is a data-driven approach that explores the information-sharing pattern based on the network’s performance on historical tasks and network’s characteristics, it is adaptive to the dynamic change (change of incoming tasks, change of network characteristics) of the target crowd network. To ensure the commonality of the information-sharing approach, the proposed approach is not designed for a specific optimization algorithm. In this way, during the implementation of the proposed approach, heuristic algorithms can be chosen according to the complexity of the target crowd network.