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The purpose of this paper is to explore the influence mechanism of job satisfaction and positive affect on knowledge sharing among project members in Chinese construction industry, and test the moderating role of organizational commitment between them in order to find a new approach from the perspective of psychology to improve the knowledge sharing performance within project management organizations in China constantly.

An empirical study was used based on confirmatory factor analysis and hierarchical regression analysis with a sample of 540 project members from 80 project management organizations in China.

Research results showed that job satisfaction and positive affect of project members both have a significant positive impact on knowledge sharing; organizational commitment could moderate the influence of job satisfaction and positive affect on knowledge sharing among project members partially within the Chinese context.

A questionnaire study from China only represents the relationship and regular pattern within a shorter time interval in the Chinese context. It is necessary to continue to implement a longitudinal study in a relatively long period in future research.

Knowledge sharing among project members can be enhanced through improving job satisfaction and positive affect, and strengthening project members’ organizational commitment can amplify the influence effect of job satisfaction and positive affect on knowledge sharing.

This paper clarifies the direct influence mechanism of project members’ job satisfaction and positive affect on explicit knowledge sharing (EKS) and tacit knowledge sharing (TKS), and further tests the partial moderating effect of organizational commitment on the influence relationship of job satisfaction and positive affect on EKS and TKS.

Understanding costumer requirements is a precondition for clothing design and manufacturing. A good shapewear designer should know women’s preferences for their buttock shapes before making patterns. The purpose of this paper is to figure out factors affecting the beauty of women’s buttock shapes and the effect of ethnic background to buttock shapes preference.

The approach utilized both 3D virtual models and 3D printed models to detect women’s preference for their buttock shapes. As a first stage, a two-step K-means cluster method was used to classify female buttock shapes into ten groups and these ten kinds of buttock shapes were output as 3D virtual models and printed out as 3D plastic models. In a subsequent stage, 51 Caucasians, 35 African-Americans and 49 Asians were selected to rank the models separately based on their preference and choose the factors which they thought could influence the beauty of buttock shapes. Kendall’s W coefficient was tested to help assessing the ranking results. Finally, a sample girdle was designed based on the buttock shape preferences of Asian females as an example, and was tested by a model.

Results showed some correlation between ethnicity and buttock shape preference. Both methods of presentation of the shapes were equally preferred by participants. Caucasian women preferred a full, round buttock shape, which was coordinated to other parts of the body. The attractive buttock shape as judged by Asian women was curvy, not drooping and not too big. African-American women choose buttock shapes that were very full with high buttock bumps as beautiful. A sample girdle was made based on the preferences of Asian females and it proved to perform well in creating the desired shape during the trial test.

Current research in the literature about women’s buttock beauty is based on plastic surgeons’ experiences. This study provides a novel method to analyze female’s preference for their buttock shapes; a method that can also be used for other body parts. The results can also be used as an indicator for underwear designers to improve shapewear pattern designs and for consumers to evaluate the shaping ability of shapewear.

An exact pattern prototype is a prerequisite for female girdle pattern-making. The purpose of this paper is to develop new ways to make girdle pattern prototypes based on 3D technology.

This paper presented two novel methods for creating girdle pattern prototypes. The first one was the girdle's parametric foundation pattern developing method based on 3D geometric modeling. In this method, considering the different characteristics of a female's lower body shape, several models were created to define the relationship between the female's lower body shape and the pattern, such as a side-waist curvature model, an interior-posterior waist-warping model, a buttocks' parametric model and an abdomen parametric model. Then, parameters of drawing the prototype were abstracted to facilitate transforming the 3D geometric model into the 2D pattern. Another method was implemented by 3D virtual modeling and unwrapping. The whole process included surface division, surface reconstruction and surface unwrapping.

The prototypes created by these two methods were tested using the 3D virtual trying-on examination. Trial tests showed that the patterns can be dressed in the right positions on the virtual model with little pressure. This means that the proportions and shapes of the pattern are correct. The prototypes obtained through the methods proposed in this paper have good effects and high precision. Both methods can be used for making the girdle's foundation pattern.

Two pragmatic approaches of girdle's prototype building have been put forward. The parametric prototype designing method has changed the unconstrained state of free modeling. The pattern structure can be controlled by parameter constraints. In the other method, with 3D scanning and surface modeling technology, personalized girdle's pattern is generated, and the segmentation lines of the girdle can be designed flexibly according to the requirements. These findings also can be used in other tight garments' prototype making.

Herringbone groove thrust bearings are typically used in high-speed, light-load applications, such as spindle motors for hard disk drives. In the past researches, the effect of shaft misalignment was little considered. This study aims to reveal effects of shaft misalignment on the microscopic flow regime in the water-lubricated herringbone groove thrust bearing.

The liquid film in a thrust herringbone groove bearing was investigated by computational fluid dynamics. The effects of micro-grooves on the flow field were carefully explored. Two-dimensional liquid films at four different sites were examined for obtaining the rich flow field properties.

The distributions of pressure, temperature and water vapor volume fraction were obtained, the micro hydrodynamic effects were formed by the herringbone grooves and the effects of the shaft misalignment on lubrication and sealing performance could be found.

The influence of misalignment on the herringbone groove thrust bearing performance was investigated in detail. The obtained results could give the reference guideline for the bearing design.

The purpose of this paper is to build a mathematical model of men’s wear prototype, so that the computer can draw men’s wear prototype automatically.

First, the bust line, front and back center line, waist line, side seam, front chest width and back width line in the coordinate system are expressed by equations. Then, a parabola is used to establish a neckline curve, a linear equation is used to establish a shoulder oblique line, and a double ellipse is superposed to construct the armhole arc. Finally, all the garment prototype curves are built mathematical models.

The result shows that every curve of garment prototype can be expressed approximately by mathematical model.

This research lays the foundation for the automation and intelligence of garment pattern-making.

The purpose of this paper is to propose a relatively simple and rapid method to create a digital human model (DHM) to serve clothing industry.

Human body’s point cloud is divided into hands, foots, head and torso. Then forward modeling method is used to model hands and foots, photo modeling method is used to model head and reverse modeling method is used to model torso. After that, hands, foots, head and torso are integrated together to get a static avatar. Next, virtual skeleton is bound to the avatar. Finally, a lifelike digital human body model is created by the mixed modeling method (MMM).

In allusion to the defect of the three-dimension original data of human body, this paper presented an MMM, with which we can get a realistic digital human body model with accurate body dimensions. The DHM can well meet the needs of fashion industry.

The DHM, which is got by the MMM, can be well applied in the field of virtual try on, virtual fashion design, virtual fashion show and so on.

The originality of the paper lies in the integration of forward modeling, reverse modeling and photo modeling to present a novel method of human body modeling.

Against the backdrop of the global reshaping of supply chains, supply chain ecosystems have emerged as a critical force in ensuring the high-quality development of enterprises and fostering stable economic growth. However, a systematic theoretical understanding of how to construct these supply chain ecosystems remains nascent. This study aims to explore the mechanism of the process of building supply chain ecosystems between digital innovation platform enterprises and digital trading platform enterprises from the perspective of dynamic capabilities.

An explanatory case study is conducted based on a theoretical framework grounded on dynamic capabilities view. Two preeminent digital platform enterprises in China (Haier and JD.com) are studied. The authors primarily conducted this research by collecting a large volume of these Chinese public materials.

First, the construction processes of supply chain ecosystems in both digital platform enterprises can be delineated into three stages: embryonic, development and maturity. Second, digital innovation platform enterprises’ construction process is primarily influenced by factors such as production and operational collaboration, consumer demand and research and development. This influence is exerted through interactions on digital platforms and within sub-ecosystems. Meanwhile, digital trading platform enterprises’ construction process is influenced by factors such as infrastructure development, consumer demand and financial support, driving dynamic capability formation through multi-party cooperation and ecological interactions based on conceptual identity.

In the establishment of supply chain ecosystems, digital platform enterprises should prioritize the cultivation of opportunity expansion, resource integration and symbiotic relationship capabilities. Furthermore, this study shows that digital platform enterprises need to actively adjust their interactive relationships with cooperating enterprises based on changes in the market, industry, policies and their own developmental stages.

This study addresses prior deficiencies in understanding the comprehensive construction of supply chain ecosystems and provides significant insights to enhance the theoretical foundation of supply chain ecosystem studies. Additionally, this paper uncovers the dynamic capability development behaviors and contextual features inherent in the construction process of supply chain ecosystems by digital platform enterprises.

The purpose of this paper is to achieve one garment with multiple uses, reduce waste and increase the fun of clothing design.

Through the comparison of the structural design of windbreaker with the structural design of suit and other coats, find out the similarities and differences between them in the structure then provide a reliable theoretical basis for the combination and transformation of the two; and then start with the structural theory of men's windbreaker, from the detail structure and the structure. The optimization design of the overall structure, the application of mathematical theory to establish a regular structure design method, so that it can be split through the zipper combination into men's suits or other coats. Finally, from the perspective of technology, the functional transformation from men's windbreaker to men's casual suit and other coats is completed in terms of style, structure and technology.

Through reasonable clothing structure design and invisible zipper layout, one type of clothing can be used as multiple types of clothing.

A new fashion design method is proposed to minimize the waste of fashion design process.

For comfort evaluation of underwear pressure, this paper proposes an improved GA algorithm to optimize the weight and threshold of BP neural network, namely PSO-GA-BP neural network prediction model.

The objective parameters of underwear, body shape data, skin deformation and other data are selected for simulation experiments to predict the objective pressure and subjective evaluation in dynamic and static state. Compared with the prediction results of BP neural network prediction model, GA-BP neural network prediction model and PSO-BP neural network prediction model, the performance of each prediction model is verified.

The results show that the BP neural network model optimized by PSO-GA algorithm can accelerate the convergence speed of the neural network and improve the prediction accuracy of underwear pressure.

PSO-GA-BP model provides data support for underwear design, production and processing and has guiding significance for consumers to choose underwear.

The purpose of this paper is to improve the prediction accuracy of the body shape prediction model and provide some reference value for the design of underwear.

The body size data of 250 male youths is measured to analyze the body shape of the lower body. And there is a total of 56 measurement items, which are clustered by GA-BP-K-means, K-means, optimal segmentation method for ordered samples, wavelet coefficient analysis, regression analysis and Naive Bayes Algorithm. Finally, a test male sample of an unknown body shape was clustered to verify the superiority of the GA-BP-K-means.

This paper presented the key factors for body shape clustering, and experimental results have shown that the GA-BP neural network model is higher in speed and precision than other algorithm prediction models.

It was clarified which is the key to body shape clustering. At the same time, the GA-BP-K-means algorithm can promote the popularization and application of the prediction model in body shape clustering.