Search results

This paper aims to explore the mechanism and boundary conditions of authoritarian leadership that influence employee innovation behavior (EIB) in Chinese culture based on the leader–member exchange theory and state–trait theory.

The authors used Mplus and SPSS to test the proposed model with data from 286 leader–employee dyads in Chinese companies. In this study, questionnaires were collected through commission and field investigation.

The results indicate that authoritarian leadership can positively influence perceived insider status and EIB within a certain range in Chinese organizational culture, although this is counterintuitive. In addition, perceived insider status has a high level of explanatory power on EIB and can mediate the relationship between authoritarian leadership and EIB. Furthermore, proactive personality can moderate the positive influence of authoritarian leadership on perceived insider status.

Innovation management is inseparable from the specific organizational cultural context. This paper argues that the relationship between authoritarian leadership and EIB in the context of organizational culture in China may differ from that in the west. This study constructs a unique research model and offers new insights into when and how EIB can be influenced by authoritarian leadership.

The purpose of this paper is to explore the combined influence of exchange quality (i.e. leader-member exchange or LMX, and coworker exchange or CWX) and organizational identity on the relationship between authoritarian leadership and employee innovation based on social cognition theory and social exchange theory.

The authors used mediation analysis, moderation analysis and bootstrapping method to test the proposed model with data from 286 supervisor-subordinate dyads in China, covering manufacturing and Internet companies. This study also used the time-lag design, and the questionnaires were collected by means of multi-source and multiphase.

The results indicate that authoritarian leadership can positively influence employee innovation behavior, and organizational identity mediates this relationship. Both LMX and CWX can significantly moderate the relationship between authoritarian leadership and organizational identity, while the moderating effect is the opposite. To be specific, CWX has appositive effect, while LMX has a negative effect. Furthermore, the indirect effect of authoritarian leadership on employee innovation behavior via organizational identity is also moderated by LMX.

At present, scholars have not yet reached a consensus on the relationship between authoritarian leadership and employee innovation behavior. Based on social cognition theory and social exchange theory, this study incorporates organizational identity and exchange quality into the research model to explore this lack of consensus. By verifying the research model, this study offers original views on when and how authoritarian leadership and exchange quality affect employee innovation behavior, which enriches the current research on employee innovation and the effectiveness of authoritarian leadership in different cultural contexts.

The purpose of this paper is to explore the mechanism and boundary condition of the effect of managers' negotiable fate belief (NFB) on enterprise incremental and radical innovation based on social cognition theory and social network theory.

The authors used Mplus and SPSS (Statistical Product and Service Solutions) to test the proposed model with data from 278 enterprises that have established national or municipal enterprise technology centers. In this study, questionnaires were collected through commission and field investigation.

The results indicate that managers' NFB has a significant positive impact on local and cross-border knowledge search and on the incremental and radical innovation of enterprises. Knowledge search is positively correlated with enterprise innovation and can play a mediating role between the managers' NFB and enterprise innovation. Network capability can positively moderate the relationship between managers' NFB and cross-border knowledge search but has no significant impact on the relationship between managers' NFB and local knowledge search.

Although there have been many studies of managers' cognition, little is known about how managers' NFB influences enterprise behavior and enterprise innovation. This study incorporates managers' NFB and knowledge search into the research model and examines the moderating effect of network capability between managers' NFB and knowledge search from an interactive perspective. By verifying the research model, this study offers original views on whether and how managers' NFB and knowledge search affect enterprise innovation.

This paper seeks to explore the fiber orientation distribution and rheological properties of turbulent fiber suspensions flowing through a contraction.

The Reynolds averaged Navier‐Stokes equation was solved with the Reynolds stress model to get the mean fluid velocity and the turbulent kinetic energy in the turbulent flow of a contraction with rectangular cross‐section. The turbulent velocity fluctuations were represented as a Fourier series with random coefficients. Then the slender‐body theory was used to predict the fiber orientation distribution, orientation tensor, additional shear stress and first normal stress difference of suspensions in the flow.

It is found that the longer fibers tend to align the streamline easily. Increased contraction ratio results in higher fiber alignment in the direction of flow. The fibers are weakly and strongly aligned in the direction of flow in the region near the inlet and the exit, respectively. Fibers are significantly more aligned in the plane of the contraction than in the x‐z plane. Contraction ratio and fiber length were shown to strongly and weakly affect the distributions of additional shear stress and first normal stress difference.

It is the first time that the fiber orientation distribution and rheological properties of turbulent fiber suspensions flowing through a contraction have been computed numerically. The computational approach and results are valuable to the design and operation of contraction used in the industrial processes.

This paper aims to propose a new method to solve the two problems in fabric defect detection. Current state-of-the-art industrial products defect detectors are deep learning-based, which incurs some additional problems: (1) The model is difficult to train due to too few fabric datasets for the difficulty of collecting pictures; (2) The detection accuracy of existing methods is insufficient to implement in the industrial field. This study intends to propose a new method which can be applied to fabric defect detection in the industrial field.

To cope with exist fabric defect detection problems, the article proposes a novel fabric defect detection method based on multi-source feature fusion. In the training process, both layer features and source model information are fused to enhance robustness and accuracy. Additionally, a novel training model called multi-source feature fusion (MSFF) is proposed to tackle the limited samples and demand to obtain fleet and precise quantification automatically.

The paper provides a novel fabric defect detection method, experimental results demonstrate that the proposed method achieves an AP of 93.9 and 98.8% when applied to the TILDA(a public dataset) and ZYFD datasets (a real-shot dataset), respectively, and outperforms 5.9% than fine-tuned SSD (single shot multi-box detector).

Our proposed algorithm can provide a promising tool for fabric defect detection.

The paper includes implications for the development of a powerful brand image, the development of “brand ambassadors” and for managing the balance between stability and change.

This work provides technical support for real-time detection on industrial sites, advances the process of intelligent manual detection of fabric defects and provides a technical reference for object detection on other industrial

Therefore, our proposed algorithm can provide a promising tool for fabric defect detection.

This paper aims to examine the blockchain introduction and altruistic preference decisions of the supplier in agricultural food supply chains and discuss how the supplier decisions are influenced by blockchain technology and altruistic preference levels.

The author considers a single period two-level supply chain model to describe the supplier’s decisions. The supplier, as the leader of the game, decides whether to introduce blockchain technology and his own level of altruistic preferences. Consumers have environmental awareness and heterogeneity in green trust. Supply chain members determine their own product pricing and green effort level under Stackelberg game.

The results reveal the negative impact of unit verification cost in the technology introduction process on the supply chain. In addition, the supplier can adjust their profits by adjusting their altruistic preferences after introducing blockchain to offset the impact of blockchain through the influence of altruistic preferences as discussed by the author.

This paper investigates how the profits and green efforts of supply chain members are influenced by blockchain technology and altruistic preferences.

The paper aims to present the novel design approach for a low power LC-voltage-controlled oscillators (VCO) design with low phase noise that too targeted at the most sought band of Bluetooth applications. Owing to their crucial role in a wide variety of modern applications, VCO and phase-locked loop (PLL) frequency synthesizers have been the subject of extensive research in recent years. In fact, VCO is one of the key components being used in a modern PLL to provide local frequency signal since a few decades. The complicated synthesizer requirements imposed by cellular phone applications have been a key driver for PLL research.

This paper first opted to present the recent developments on implemented techniques of LC-VCO designs in popular RF bands. An LC-VCO with a differential (cross-coupled) MOS structure is then presented which has aimed to compensate the losses of an on-chip inductor implemented in UMC’s 130 nm RF-CMOS process. The LC-VCO is finally targeted to embed onto the synthesizer chip, to address the narrowband (S-Band) applications where Bluetooth has been the most sought one. The stacked inductor topology has been adopted to get the benefit of its on-chip compatibility and low noise. The active differential architecture, which basically is a cross-coupled NMOS structure, has been then envisaged for the gain which counters the losses completely. Three major areas of LC-VCO design are considered and worked upon for the optimum design parameters, which includes Bluetooth coverage range of 2.410 GHz to 2.490 GHz, better linearity and high sensitivity and finally the most sought phase noise performance for an LC-VCO.

The work provides the complete design aspect of a novel LC-VCO design for low phase noise narrowband applications such as Bluetooth. Using tuned MOS varactor, in 130 nm-RF CMOS process, a high gain sensitivity of 194 MHz/Volt was obtained. Thus, the entire frequency range of 2415-2500 MHz for Bluetooth applications, supporting multiple standards from 3G to 5G, was covered by voltage tuning of 0.7-1.0 V. To achieve the low power dissipation, low bias (1.2 V) cross-coupled differential structure was adopted, which completely paid for the losses occurred in the LC resonator. The power dissipation comes out to be 8.56 mW which is a remarkably small value for such a high gain and low noise VCO. For the VCO frequencies in the presented LO-plan, the tank inductor was allowed to have a moderate value of inductance (8 nH), while maintaining a very high Q factor. The LC-VCO of the proposed LO-generator achieved extremely low phase noise of −140 dBc/Hz @ 1 MHz, as compared to the contemporary designs.

Though a professional tool for inductor and circuit design (ADS-by Keysight Technologies) has been chosen, actual inductor and circuit implementation on silicon may still lead to various parasitic evolutions; therefore, one must have that margin pre-considered while finalizing the design and testing it.

The proposed LC-VCO architecture presented in this work shows low phase noise and wide tuning range with high gain sensitivity in S-Band, low power dissipation and narrowband nature of wireless applications.

The on-chip stacked inductor has uniquely been designed with the provided dimensions and other parameters. Though active design is in a conventional manner, its sizing and bias current selection are unique. The pool of results obtained completely preserves the originally to the full extent.