Search results

Eco-innovation products, which means achieving more efficient and responsible use of resources and reducing the detrimental impact on the environment, can win a competitive advantage for the enterprises. But it is not easy to implement due to the high cost of eco-innovative technologies development, the uncertainty of market needs and return risk of investment. Many enterprises seek collaborations from their upstream suppliers to jointly carry out eco-innovation, such as Apple, IBM and Nike. A unique feature of collaboration is that efforts by one party enhance the marginal value of the other party's efforts. However, the collaboration will make the partner know the eco-innovation technology and prompt the partner to encroach the market to sell competitive products by herself. Motivated by this observation, this paper considers the optimal collaboration strategy on eco-innovation between upstream and downstream supply chain member and the optimal encroachment strategy of upstream supplier in a supply chain.

This paper models a supply chain wherein a supplier provides products or materials for her manufacturer and cooperates with her manufacturer in eco-innovation. Also, the supplier could encroach on the market to sell similar products by herself. Then this paper uses game theory and mathematical modeling to do relative analysis.

The analysis reveals several interesting insights. First, eco-innovation collaboration makes supplier encroachment no longer only rely on the encroachment cost. The delayed realized eco-innovation efficiency information also plays a vital role. Second, different from previous research, the authors find the manufacturer's preference for supplier encroachment depends on the uncertainty of eco-innovation efficiency and potential market demand. Third, both partial and full encroachment strategies of the supplier can effectively improve the eco-innovation level.

The paper is the first to take the interplay between collaboration and encroachment into account in a supply chain. The results caution enterprises and policymakers to take vertical collaboration and delayed realized information into account in the competitive supply chain before making any operational decisions. Furthermore, the authors propose that governmental intervention aimed at stimulating supplier encroachment in appropriate circumstances can contribute to the improved environmental performance of products.

This study aims to investigate the effect of perceived insider status to employees' innovative behavior, the mediating role of knowledge sharing and the moderating role of organizational innovation climate in the relationship between knowledge sharing and employees' innovative behavior.

This study adopted questionnaires to gather data. The sample of 341 employees working in diverse organizations in China was applied to examine the hypotheses.

The results indicate that perceived insider status is positively related to employees' innovative behavior and knowledge sharing mediates the relationship between perceived insider status and employees' innovative behavior. In addition, organizational innovation climate enhances the relationship of knowledge sharing and employees' innovative behavior.

This study builds a system from psychological aspect to behavior, which includes the mechanism of the influence of perceived insider status on employees' innovative behavior and a cross-level analysis of the influence of organizational innovation climate on employees' innovative behavior, breaking through the previous research paradigm of a single level of climate and employee behavior.

Realistic geometric description is essential for simulating physical properties of warp-knitted velvet fabrics, which are widely used for home-textiles and garments. The purpose of this paper is to provide an approach to the description of patterned piles and propose a customized simulation model to realize highly real-time simulation of warp-knitted velvet fabrics in three dimensions.

Based on knitting technology and structure features, a mathematical model to qualify forming possibility of piles is conducted by assessing underlaps of pattern bars and pile ground bars. When the pile areas and ground areas are classified, a three-dimensional (3D) space coordinate is built, of which the z-axis is divided into equal spaces to form certain multi-layer textured slices. Color and transparency of piles on each textured slice can be computed and generated by mapping to 3D geometrical grid layers with particular mapping relationship. Moreover, piles’ deflection and spatial collision are also taken into account to make sure high uniformity with real fabrics.

According to the models built, a simulator special for warp-knitted patterned velvet fabrics is programed via Visual C++ and the models are proven practical and easily implemented by comparing simulated effect of one sample with real fabric.

Because of present limited research, 3D simulation of patterned velvet fabrics knitted on double-needle bar Raschel machine as well as 3D shadow effect will be studied in the further research.

The paper includes implications for designing patterned velvet products and shows convenience to instantly see finished effect without sampling on machine.

This paper fulfills a featured simulation method for warp-knitted patterned velvet fabrics in 3D dimensions for the first time.

We make use of the Volunteered Geographic Information (VGI) data to extract the total extent of the roads using remote sensing images. VGI data is often provided only as vector data represented by lines and not as full extent. Also, high geolocation accuracy is not guaranteed and it is common to observe misalignment with the target road segments by several pixels on the images. In this work, we use the prior information provided by the VGI and extract the full road extent even if there is significant mis-registration between the VGI and the image. The method consists of image segmentation and traversal of multiple agents along available VGI information. First, we perform image segmentation, and then we traverse through the fragmented road segments using autonomous agents to obtain a complete road map in a semi-automatic way once the seed-points are defined. The road center-line in the VGI guides the process and allows us to discover and extract the full extent of the road network based on the image data. The results demonstrate the validity and good performance of the proposed method for road extraction that reflects the actual road width despite the presence of disturbances such as shadows, cars and trees which shows the efficiency of the fusion of the VGI and satellite images.

The purpose of this paper is to examine the relationship between ethical leadership and employee cross-team knowledge sharing via the differentiating mediating effects of cognitive and affective trust in colleagues.

Multi-source and multi-wave data were collected from 214 dyads of employees and their supervisors. Linear regression was employed to examine the hypotheses.

Ethical leadership positively predicts employee cross-team knowledge sharing. Affective trust in colleagues mediates the relationship between ethical leadership and employee cross-team knowledge sharing, whereas cognitive trust in colleagues does not. The hypothesis – the mediating effect of affective trust in colleagues between ethical leadership and cross-team knowledge sharing is greater than that of cognitive trust in colleagues – is not supported.

This study extends understanding of the influence of ethical leadership on cross-team knowledge sharing. It further differentiates cognitive and affective trust in colleagues between ethical leadership and cross-team knowledge sharing. These findings are valuable for improving the research of leadership practices and knowledge sharing.

Double-jacquard technique is referred as the most advanced technology for forming patterns on both layers of a 3D fabric knitted on a double-needle bar warp-knitting machine. In order to realize the computer-aided design and simulation of jacquard patterns, the purpose of this paper is to propose a mathematic model for representation of jacquard structures and an improved mass-spring model to improve the simulation of structural deformation behavior.

Primarily, it analyzes the jacquard patterning method and displacing principle to design jacquard structures on each layer and linking structures of two layers. Based on that, a loop geometry defined by six key points and segmental lines is built to transfer the jacquard bitmap and lapping movements into a fabric of loops and therefore realizing patterns visualization. Afterwards, an improved mass-spring model is built to simulate structural deformation, in which the fabric is simplified as a mesh of uniformly distributed mass particles. Each loop is treated as a massless particle while underlaps are referred as structural springs connecting loops particles. Elastic forces of these springs on each loop particle is calculated according to the Hook’s law and Newton’s second law, and then based on the explicit Euler’s equations, motion state of each particle is solved including the velocity and the shift.

Based on the above method, a simulator for double-layer jacquard fabrics is developed via Visual C++ language to visualize the patterned fabrics with pitting effects. With a jacquard shoe fabric as an example, this simulation model is proved to be practical and efficient by comparing the simulation result and real fabric.

Because of limited researches, 3D simulation modeling of this double-layer jacquard fabric will be studied in the further research.

The implement of this simulation method will offer the industries a time-saving and cost-saving approach for new fabrics development.

This approach can be used as a reference for simulating other knitted fabrics with jacquard patterns, such as jacquard garment fabrics and home textile fabrics.

Employee’s service innovative behavior lays the groundwork for bottom-up innovation and ongoing service improvement in service firms. Therefore, it is vital for service organizations to understand the antecedents of employees service innovative behavior. Drawing upon the social cognitive theory, this study aims to develop a research model that examines the effects of ethical and entrepreneurial leadership on service innovative behavior.

Data were collected from 178 managers and 415 employees working in 178 small- and medium-sized (SME) hotels in Vietnam.

The findings showed that ethical leadership has direct and indirect effects on service innovative behavior, while entrepreneurial leadership only influences service innovative behavior via intrinsic motivation. In addition, trust in leader moderates the effect of intrinsic motivation on service innovative behavior

The study advances current scholarly research on leadership by combining the two areas of entrepreneurial and ethical leadership into one theoretical model and examines how these leadership styles generate hospitality employees’ service innovative behavior through the mediating effect of intrinsic motivation and the moderating effect of trust in leader.

The findings of this research offer significant implications for SME hotels and their managers. In their recruitment processes, hotels should search for particular personality traits, which have been found to predict ethical and entrepreneurial leadership. Hospitality firms also need to encourage communication between leaders and co-workers to enhance employees’ intrinsic motivation.

There are calls for research to examine whether both entrepreneurial and ethical leadership styles can be integrated to enhance employees’ positive outcomes. Evidence about the mechanism linking entrepreneurial and ethical leadership to service innovative behavior is limited. With this stated, the current study makes significant contribution to leadership and innovation literature by filling in these voids.

The purpose of this paper is to analyze the implicit prices of hotel attributes in different time periods and different markets.

With data from the travel meta-search engine, this paper chose 3- to 5-star hotels in Beijing’s central business district and use hedonic price models.

The results suggest that the attributes with significant implicit prices differ in different time periods; the same attributes with different implicit prices in different time periods; the same attributes with different implicit prices in different market segments.

This study may help to explain the different findings on the relationship between the attributes and room rates of Chinese star-rated hotels in different time periods, and will be useful in both revenue optimization efforts and the design of new hotels projects.

This research aims to improve the performance of rail fastener defect inspection method for multi railways, to effectively ensure the safety of railway operation.

Firstly, a fastener region location method based on online learning strategy was proposed, which can locate fastener regions according to the prior knowledge of track image and template matching method. Online learning strategy is used to update the template library dynamically, so that the method not only can locate fastener regions in the track images of multi railways, but also can automatically collect and annotate fastener samples. Secondly, a fastener defect recognition method based on deep convolutional neural network was proposed. The structure of recognition network was designed according to the smaller size and the relatively single content of the fastener region. The data augmentation method based on the sample random sorting strategy is adopted to reduce the impact of the imbalance of sample size on recognition performance.

Test verification of the proposed method is conducted based on the rail fastener datasets of multi railways. Specifically, fastener location module has achieved an average detection rate of 99.36%, and fastener defect recognition module has achieved an average precision of 96.82%.

The proposed method can accurately locate fastener regions and identify fastener defect in the track images of different railways, which has high reliability and strong adaptability to multi railways.

The purpose of this paper is to describe the design and development of a novel series-parallel robot, which aims to climb on the transmission tower.

This study introduces a hybrid robot, which consists of adsorption and two 3-degree of freedom (DOF) translation parallel legs connected by a body linkage. The DOF of the legs ensures that the robot can move on the climbing plane, also contribute to a compact design of the robot. An electromagnet is used to adsorb onto the transmission tower, simplifying the overall structure. Based on the robot design, this paper further defines its climbing gait and adopt the 6th B-spline curves for climbing trajectory planning under different working environments.

The developed prototype that implements the design of the robot, which was used in simulation and experiments, showing that the robot is capable of climbing in the test environments with the planned climbing gait.

The hybrid robot is able to climb under varying degrees of inclinations and cross the obstacles, and the magnetic attraction can ensure stable climbing.