Zhejiang Gongshang University

About: Zhejiang Gongshang University is a education organization based out in Hangzhou, China. It is known for research contribution in the topics: Computer science & Chemistry. The organization has 8258 authors who have published 7670 publications receiving 90296 citations. The organization is also known as: Zhèjiāng Gōngshāng Dàxué.

How transformational leadership influences follower helping behavior: The role of trust and prosocial motivation

Abstract: Summary We proposed and tested a moderated mediation model that jointly examines affect-based and cognition-based trust as the mediators and prosocial motivation as the moderator in relationships between transformational leadership and followers’ helping behavior towards coworkers. Data were collected from 348 sales and servicing employees and their supervisors in four private retail companies and five private manufacturing companies located in Southeast China. The results showed that both affect-based trust and cognition-based trust mediated the relationship between transformational leadership and followers’ helping behavior towards coworkers. Furthermore, moderated mediation analyses showed that affect-based trust mediated the relationship between transformational leadership and followers’ helping behavior towards coworkers only among employees with high prosocial motivation, whereas cognition-based trust mediated this relationship among only those with low prosocial motivation. Implications for the theory and practice of leadership are then discussed. Copyright © 2013 John Wiley & Sons, Ltd.

MTES: An Intelligent Trust Evaluation Scheme in Sensor-Cloud-Enabled Industrial Internet of Things

Abstract: As an enabler for smart industrial Internet of Things (IoT), sensor cloud facilitates data collection, processing, analysis, storage, and sharing on demand. However, compromised or malicious sensor nodes may cause the collected data to be invalid or even endanger the normal operation of an entire IoT system. Therefore, designing an effective mechanism to ensure the trustworthiness of sensor nodes is a critical issue. However, existing cloud computing models cannot provide direct and effective management for the sensor nodes. Meanwhile, the insufficient computation and storage ability of sensor nodes makes them incapable of performing complex intelligent algorithms. To this end, mobile edge nodes with relatively strong computation and storage ability are exploited to provide intelligent trust evaluation and management for sensor nodes. In this article, a mobile edge computing-based intelligent trust evaluation scheme is proposed to comprehensively evaluate the trustworthiness of sensor nodes using probabilistic graphical model. The proposed mechanism evaluates the trustworthiness of sensor nodes from data collection and communication behavior. Moreover, the moving path for the edge nodes is scheduled to improve the probability of direct trust evaluation and decrease the moving distance. An approximation algorithm with provable performance is designed. Extensive experiments validate that our method can effectively ensure the trustworthiness of sensor nodes and decrease the energy consumption.