Search results

The traditional method to distinguish the serotype of influenza A virus was based on the antigen reaction of HA and NA with their antibodies. The antibody of specific subtype virus was difficult to get and the reaction was not easy to be done. To be a complementation to the traditional classification methods based on the serological reaction, aims to present a novel method for viral classification.

The similarity values of all subtype HA genes in vector space were considered and classified using a probabilistic neural network (PNN). The PNN model was trained by the 132 viral sequences in the training set and the classification quality was examined using 28 viral sequences in the testing set.

A novel technique for the serotype classification of influenza A virus isolated from human was proposed in the paper. The system achieved 100 per cent accuracy with all serotypes of human influenza A virus.

The time for the large‐scale calculations of the average similarity based on multisequence alignment is the main limitation.

This is a supplementation to the traditional virology research.

The novel classification method based on the similarity of viral nucleotide sequences and the PNN model would be useful for the epidemic supervision and prevention.

This paper aims to explore the direct effects of open innovation (OI) on firms’ innovative performance, and to examine the moderating effects of knowledge attributes, including knowledge distance, knowledge embeddedness and partner opportunism on this relationship.

Survey data of 247 samples from China were used to test the proposed model through hierarchical regression analysis.

The findings indicate that the dimensions of OI are positively related to innovative performance. The results also reveal that knowledge distance positively moderates the relationship between inbound OI and innovative performance, whereas knowledge embeddedness negatively affects that relationship. Knowledge embeddedness negatively affects the relationship between inbound OI and innovative performance, whereas knowledge distance positively moderates that relationship. Thus, a new finding is proposed that knowledge attributes could align effectively with specific OI type to achieve superior innovation outcomes. In addition, the empirical results suggest that partner opportunism plays a negative moderating role on the relationship between outbound OI and innovative performance.

The proposed view that a firm’s innovation outputs will be superior when its knowledge attributes effectively align with OI enriches studies of the OI context and expands the literature of both the resource-based view and the knowledge-based view. Furthermore, this study provides insights into how OI benefits can be influenced by external contexts from the perspective of partners’ opportunistic behaviour.

Building on the resource- and knowledge-based views, this paper aims to explore how coopetition affects radical innovation and the roles of knowledge structure and external knowledge integration in the relationship between coopetition and radical innovation.

This study proposes a research model to examine the mediating role of external knowledge integration on the coopetition-radical innovation link, where the mediation is moderated by the firm’s knowledge structure (including component knowledge and architectural knowledge). The authors use regression and bootstrapping to test the proposed model with survey data from 241 Chinese technology firms.

This study finds that coopetition positively affects radical innovation and the effect is fully mediated by external knowledge integration. Additionally, component knowledge negatively moderates the coopetition-external knowledge integration link and architectural knowledge positively moderates this relationship. Further, the mediating effect of external knowledge integration is also moderated by component knowledge and architectural knowledge.

Firms should engage in coopetition to promote radical innovation. Further, it is necessary for firms to appropriately manage coopetition according to their internal knowledge structure.

This study explains why scholars have different ideas about the relationship between coopetition and radical innovation by exploring the mediating role of external knowledge integration and the moderating effect of knowledge structure. Firms possess increased possibilities for knowledge leakage and partner opportunism with high levels of component knowledge, which will reduce the positive effect coopetition on external knowledge integration; thus, they are less likely to realize radical innovation. Instead, firms possess increased opportunities for resource sharing with high levels of architectural knowledge, thus improving the positive effect coopetition on external knowledge integration and they are more likely to achieve radical innovation.

The purpose of this paper is to examine the relationship between open innovation (OI) and innovative performance, and to explore the moderating effect of knowledge structure, including component knowledge and architectural knowledge, on this particular relationship.

The proposed model was tested with regression analysis of data collected through a questionnaire survey of 231 employees of Chinese manufacturing firms.

The findings indicate that inbound OI is positively related to innovative performance and that outbound OI has an inverted U-shaped effect on innovative performance. By presenting empirical evidence of the moderating effects of component and architectural knowledge, our analysis of results demonstrates that the strong alignment between knowledge structure and OI results in superior innovative performance.

This study addresses the controversial issues brought up by previous studies with findings of an inverted U-shaped effect of outbound OI on innovative performance. By exploring the moderating effect of knowledge structure, the authors provide insights into how internal contextual factors in relation to organizational knowledge can affect the efficacy of the inbound and outbound OI on innovative performance.

The purpose of this paper is to build a symbiotic evolution model to analyze the symbiotic modes and dynamic equilibrium of mobile internet platform innovation ecosystem (MIPIE) in order to explore its evolutionary path.

From a symbiosis theory perspective, the authors studied the dynamic evolution stages and symbiotic mode of MIPIE. By adopting logistic model, the symbiotic evolution model of MIPIE is established. After calculating the steady conditions and equilibrium point of this model, numerical simulation was done with MATLAB software to illustrate the impact of symbiotic parameters on evolution path in this ecosystem.

The symbiotic evolution mode of MIPIE experienced parasitism, commensalism to asymmetric mutualism, and symmetry mutualism or independence. In given conditions, the dynamic evolution of MIPIE eventually tends to a steady equilibrium point. The evolutionary consequence of innovative subjects is not only determined by the natural growth rate, but symbiotic modes can also affect the evolutionary path. Different symbiotic modes result in different evolutionary paths.

Improved understanding of symbiosis in MIPIE could help policy makers to promote value co-creation and dynamic interests balance while facilitating the cooperation of others for successful platform ecosystem management.

The logistic model introduced here bridge theory and practice while establishing a stronger link between symbiosis theory and platform ecosystem management.

The purpose of this study is to improve the dispersion of nanoserpentine modified with OA, KH550 and KH550/oleic acid in lubricating oil. The main aims are to analyze the influence of the dispersion and stability of nanoserpentine modified by different modifiers on the friction properties of lubricating oil.

The nanoserpentine particles obtained by ball-milling were modified by silane coupling agent KH550, OA and KH550/OA, respectively. The dispersity and stability of nanoserpentine in base lubricating oil were characterized by the absorbance value method, centrifuge precipitation rate method and static observation method. The MMU-5G screen display friction and wear tester was used to evaluate the tribological properties of C45E4/C45E4 friction pairs in corresponding lubricating oils. The surface morphology of the friction pairs was observed by scanning electron microscopy and energy dispersive spectroscopy.

The results showed that the dispersity and stability of nanoserpentine particles in lubricating oil were best modified by OA, followed by the KH550/OA and finally, the KH550. Nanoserpentine particles modified with oleic acid showed optimum tribological properties as lubricant additives.

This study can improve the dispersion stability of nanoserpentine particles in lubricating oil, increasing the antiwear and antifriction performance of lubricating oil, which has great significance in economic and military aspects.

The advanced technology enables retailers to develop customer profile analysis (CPA) to implement personalized pricing. However, considering the efficiency of developing CPA, the benefit to different retailers of implementing more precise personalized pricing remains unclear. Thus, this essay aimed to investigate the impact of efficiency on participants’ strategies and profits in the supply chain.

A two-stage game model was introduced in the presence of a manufacturer who sets his wholesale price and a retailer that decides her CPA strategy. The equilibrium results were generated by backward induction.

Most retailers are willing to develop the highest CPA to implement perfect personalized pricing, but those inefficient retailers with high production costs would like to determine a middle CPA to implement bounded personalized pricing. The retailers’ profits may decrease with the efficiency of developing CPA when the efficiency is middle. In this case, as the efficiency improves, the manufacturer increases the wholesale price, resulting in lower demand and thus lower profits. Moreover, define a Pareto Improvement (PI) strategy as one that benefits both manufacturers and retailers. Therefore, uniform pricing is a PI when the unit cost is high and the efficiency is low; personalized pricing is a PI when the unit cost is low and the efficiency is low or high; otherwise, there is no PI.

This study is the first that investigates how the retailer develops CPA to implement personalized pricing on a comprehensive spectrum, which can provide practical insights for retailers with different efficiencies.

Previously, the effect of pore-forming agents on the properties of pore size and morphology was studied. In this paper, we determine the optimal combination of parameters by tensile strength and perform tribological tests with optimal combination of parameters.

In this paper, porous polyimide (PI) materials were fabricated using vacuum hot molding technology. The orthogonal experiment was designed to test the mechanical properties of porous PI materials with the process parameters and the content of pore-forming agent as the changing factors. The porous PI oil-bearing materials were obtained by vacuum immersion, and tribological test were carried out.

The results showed that porous PI oil-bearing materials are suitable for low-speed and low-load conditions. The actual value of the friction coefficient basically match with the theoretical value of the regression analysis, and the errors of the friction coefficient are within 10% and 3%, respectively, which proves that the method used in the study is feasible for the friction coefficient prediction.

In this paper, we have produced a new porous oil-bearing material with good tribological properties. This study can effectively predict the friction coefficient of PI porous material.

Although much attention has been paid to understanding employee resistance to reform, little study has been done to explore the effect of employee resistance to public service units' (PSUs) reform in China. To address this need, this work aims to investigate the antecedents of employee resistance to PSUs' reform, especially from the perspective of the heterogeneity of the employees' age.

This study considers the PSUs in Harbin, China, as an example and uses survey questionnaires to analyze the factors influencing employees' resistance when PSUs reform. Besides, the authors developed a research model based on the status quo bias theory, the equity-implementation model.

According to the applied research model, employee resistance to PSU change is primarily influenced by perceived switching costs and benefits. According to their age, this survey also confirms how the employees responded to the reform implementation.

The results of this empirical study inform suggestions for the sustainable development of PSUs and organizational transformations. Overall, this work advances the theoretical understanding of employees' resistance to PSUs’ reform, thereby offering practical insights for managing employee resistance during organizational change.

Overall, given that employee resistance emotion exists in an organization, this study offers theoretical and practical implications for change management strategies.

Automatic guided vehicles (AGVs) are widely used in industrial fields. But most control strategies merely take the lateral force into consideration. This will reduce the accuracy, stability and robustness and will pay additional costs. Therefore, this paper aims to design a control strategy that initially considers lateral force. Thereby, it will improve the accuracy, stability and robustness and reduce the overall cost of AGV.

To achieve the goal of comprehensively improving AGV operating performance, this paper presents a new scheme, combining the dual-wheeled chassis model (DCM) using proportional–integral–differential (PID) control and a supporting quick response (QR) code navigation technology. DCM is the core, which analyzes the deviation caused by lateral force. Then, DCM with PID control by the control law is combined to suppress the errors. Meanwhile, QR code navigation technology provides effective data support for the control strategy.

Most AGV experiments are carried out in a standard environment. However, this study prepares unfavorable scenarios and operating conditions for the experiments that generate detailed data to demonstrate this study’s strategy, which can make an accurate, stable and robust operation process of AGV under various adverse environmental and mechanical factors.

This study proposed DCM, fully considering lateral force and converting the force into velocity. Subsequently, PID controls the speed of two wheels to reduce the error. QR code provides an efficient and low – cost way to obtain information. The three are cleverly combined as a novel industrial AGV control strategy, which can comprehensively improve the operating performance while reducing overall costs.