Search results

The effect of playfulness climate on employees in firms has been the subject of an increasing number of studies in recent years. Given the growing number of businesses that have incorporated playfulness into their operations, it is possible to enhance the task performance and innovative performance of the younger generation of workers by rationally managing playfulness, particularly when it comes to that aspect of the workplace. Based on the conservation of resources theory, this study aims to investigate how the playfulness climate in organizations influences the change self-efficacy of the millennial workers and how to enhance their task performance and innovation performance.

The authors used a quantitative approach to test the relationship between the hypotheses. The survey population for this study consisted of the millennial workers in the computer sector who are involved in research and development in China. Hierarchical regression analysis was used to test the built mediation model empirically over the course of the study's three rounds of data collection, each separated by one month. Through the collection of paired questions for leadership and their subordinates, 424 valid questionnaires were obtained.

The examination of the questionnaire results supports the study's theoretical hypothesis, which states that when millennial workers sense a more playfulness work environment, it will encourage them to develop a sense of change self-efficacy. Additionally, they will be better able to handle work-related responsibilities and come up with innovative ideas as a result of change self-efficacy, which would eventually enhance the task performance and innovation performance of millennial employees.

By introducing the mediation of change self-efficacy, this study expands on the application of the conservation of resources theory. The research on the performance of millennial employees is complemented and enhanced by investigating the relationship between the playfulness climate and employees' task performance and innovation performance from the perspective of their sense of change self-efficacy. This study also reveals that managers should foster a positive and playfulness environment in their workplaces in order to manage the performance of millennial employees.

Much of the research on overqualification has focused on the negative effects at the individual level. However, in the face of the increasing tendency to recruit overqualified employees, managing the perception of team overqualification can be effective in motivating team members in the current complex and changing business environment.

Based on the person–environment fit theory, this study examines how team overqualification affects employees' change self-efficacy and how it further motivates employees to engage in strategic scanning behavior toward proactive external information gathering and analysis. The data collection for this study was divided into two stages, spaced three months apart. The analysis of questionnaire data from 290 employees and 72 supervisors confirmed the theoretical hypothesis of this study.

When employees perceive a higher level of team overqualification, they will generate more strategic scanning behavior. And the change self-efficacy plays a mediating role between team overqualification and strategic scanning behavior and thus team members actively seek information from the external environment to develop future plans and work strategies. Meanwhile, transformational leadership positively moderates this process.

Firstly, this study extends the positive manifestations of overqualification at the team level. Secondly, this study verifies that change self-efficacy mediates the relationship between team overqualification and strategic scanning, enriching the research on the antecedent and outcome variables of change self-efficacy. Finally, this study verified that the interaction effect of transformational leadership and team overqualification had an impact on employee strategic scanning behavior through change self-efficacy.

This research is aimed to mainly be applicable to expediting engineering projects, uses the method of inverse optimization and the double-layer nested genetic algorithm combined with nonlinear programming algorithm, study how to schedule the number of labor in each process at the minimum cost to achieve an extremely short construction period goal.

The method of inverse optimization is mainly used in this study. In the first phase, establish a positive optimization model, according to the existing labor constraints, aiming at the shortest construction period. In the second phase, under the condition that the expected shortest construction period is known, on the basis of the positive optimization model, the inverse optimization method is used to establish the inverse optimization model aiming at the minimum change of the number of workers, and finally the optimal labor allocation scheme that meets the conditions is obtained. Finally, use algorithm to solve and prove with a case.

The case study shows that this method can effectively achieve the extremely short duration goal of the engineering project at the minimum cost, and provide the basis for the decision-making of the engineering project.

The contribution of this paper to the existing knowledge is to carry out a preliminary study on the relatively blank field of the current engineering project with a very short construction period, and provide a path for the vast number of engineering projects with strict requirements on the construction period to achieve a very short construction period, and apply the inverse optimization method to the engineering field. Furthermore, a double-nested genetic algorithm and nonlinear programming algorithm are designed. It can effectively solve various optimization problems.

Since China initiated its “go global” policy that promotes its overseas investment, China’s Outward Foreign Direct Investment (OFDI) has increased almost twenty times during the last 10 years, reaching $55.9 billion in 2008. The issue of internationalization of Chinese OFDI has attracted increasing attention of researchers from a business perspective. This article systematically reviews the previous studies on overseas investments by Chinese MNEs and discusses the characteristics of Chinese internationalization behavior at both firm level and country level. The internationalization of Chinese companies cannot be understood as a simple game of “catch up” with established MNEs, and more firm‐level empirical studies should be carried out on how these characteristics influence firms’ strategic decisions.

Student participation has been an important issue for information literacy (IL) teachings. The purpose of this paper is to promote active student participation in IL courses with Rain Classroom, an intelligent teaching tool.

Using mixed method research, the paper presents a practical case study of the author’s experiences with Rain Classroom to improve teaching and learning of IL.

The study shows that Rain Classroom helps implement problem-based learning, promote student participation in class interaction and optimize learning experience, which facilitates a shift of the IL course from passive to active learning.

It is known that university public courses have large class sizes (more than 50 students per class), and, therefore, class interaction is difficult to organize. So this is a big issue for the researchers to study.

The proposed Rain Classroom is a free teaching tool and can be used in other academic libraries to enhance active student participation in IL lessons.

The paper includes implications for improving interaction in large-size conference or trainings using Rain Classroom.

The existing literature has not traced the reports on using the Rain Classroom to enhance student participation in IL courses in academic libraries. This paper intends to fill this gap and share practical methods and experiences, deepening the application research of Rain Classroom.

Based on the weak seismic performance and low ductility of coupled shear walls, engineered cementitious composites (ECC) is utilized to strengthen it to solve the deformation problem in tall buildings more effectively and study its mechanical properties more deeply.

The properties of reinforced concrete coupled shear wall (RCCSW) and reinforced ECC coupled shear wall (RECSW) have been studied by numerical simulation, which is in good agreement with the experimental results. The reliability of the finite element model is verified. On this basis, a detailed parameter study is carried out, including the strength and reinforcement ratio of longitudinal rebar, the placement height of ECC in the wall limb and the position of ECC connecting beams. The study indexes include failure mode and the skeleton curve.

The results suggest that the bearing capacity of RECSW is significantly affected by the ratio of longitudinal rebar. When the ratio of longitudinal rebar increases from 0.47% to 3.35%, the bearing capacity of RECSW increases from 250 kN to 303 kN, an increase of 21%. The strength of longitudinal rebar has little influence on the bearing capacity of RECSW. When the strength of the longitudinal rebar increases, the bearing capacity of RECSW increases little. The failure mode of RECSW can be improved by lowering the casting height of the ECC beam in a certain range.

In this paper, ECC is used to strengthen the coupled shear wall, and the accuracy of the finite element model is verified from the failure mode and skeleton curve. On this basis, the casting height of the ECC casting wall limb, the strength and reinforcement ratio of longitudinal rebar and the position of the ECC beam are studied in detail.

The main purpose is to construct the mapping relationship between garment flat and pattern. Particle swarm optimization–least-squares support vector machine (PSO-LSSVM), the data-driven model, is proposed for predicting the pattern design dimensions based on small sample sizes by digitizing the experience of the patternmakers.

For this purpose, the sleeve components were automatically localized and segmented from the garment flat by the Mask R-CNN. The sleeve flat measurements were extracted by the Douglas–Peucker algorithm. Then, the PSO algorithm was used to optimize the LSSVM parameters. PSO-LSSVM was trained by utilizing the experience of patternmakers.

The experimental results demonstrated that the PSO-LSSVM model can effectively improve the generation ability and prediction accuracy in pattern design dimensions, even with small sample sizes. The mean square error could reach 1.057 ± 0.06. The fluctuation range of absolute error was smaller than the others such as pure LSSVM, backpropagation and radial basis function prediction models.

By constructing the mapping relationship between sleeve flat and pattern, the problems of the garment flat objective recognition and pattern design dimensions accurate prediction were solved. Meanwhile, the proposed method overcomes the problem that the parameters are determined by PSO rather than empirically. This framework could be extended to other garment components.

Not all apps can be favored on a smartphone. Users are bound to abandon some if they lose value. Analyzing the reasons behind this phenomenon can help develop strategies for avoiding app abandonment, which is the focus of this study.

This study conducted in-depth open interviews with 47 respondents who had abandoned or deleted mobile apps before and used the qualitative research method grounded theory to analyze the interview content, followed by open coding, axial coding and selective coding.

Seven main reasons are summarized after the relationship between every statement and concept is found and constructed, namely functional value, information expectation, emotional value, platform service, user trust, cost, and social influence.

Based on these findings, this study provided suggestions for mobile app developers to help them effectively improve the user experience and retain their customers.

This paper aims to introduce a series of experimental results which are the extension of our previous novel observations (Xie et al., Soft Matter, 2011), which could be helpful for revealing the lubrication failure mechanism in bearings when they are exposed to an electrical environment.

An experimental apparatus where a ball was in contact with a glass disk coated with a semi-reflective chromium layer. A small volume of oil droplet was put into the microgap of the ball-disk contact. Then, a potential was applied onto the oil micropool formed by the droplet surrounding the contact region.

It has been found that destabilization of the low-conducting oil micropool around the contact region could be induced after applying a potential. Thin oil films could be drained out of the oil pool and spread on the tribopair surfaces, resulting in the depletion of the oil pool. When the applied potential was increased, the occurrence of spreading would be easier and its development would be more obvious. In contrast, the electrospreading behavior would be suppressed when the oil viscosity, contact load and oil pool size were increased. Thermocapillary force due to thermal effect as a result of the current flow near the oil pool border has been proposed as the main driving force for the spreading behavior. The influences of the operating parameters have been ascribed to the change of the electric current near the oil pool border as well as the corresponding variations in the temperature rise and the surface tension of the oil pool.

This is the first study to directly observe that the lubricant oil micropool around the contact region could deplete after applying a potential, potentially resulting in oil starvation in the contact region.

Considering only two-dimensional (2D) ease allowance cannot fully reflect the three-dimensional (3D) relationship between the position of clothing and the human body. The purpose of this paper is to propose a method with a 3D space vector and corresponding distance ease to characterize fitting garments and then used to construct personalized clothing for similar shape body.

Firstly, a 3D scanner was used to obtain mannequin and fitted garment data, and 17 layers of cross-sections of the upper body were extracted. Then, 37 space vectors and corresponding space angles on each cross-section were obtained with the original point. Secondly, the detailed distance ease between the mannequin and garment was constructed due to the difference between garment vectors and body vectors. Thirdly, the distance ease mathematical models were achieved and used to calculate distance ease on a similar shape body. Additionally, the fit garment is constructed, and the garment pattern is altered by the geometric pattern alteration method.

The results show that 3D space vectors can explain the relationship between body skin and garment surface of the upper body properly. The distance ease is modeled by mathematic expressions and successfully used to make a new garment to fit a similar shape body.

The proposed method of constructing garments based on distance ease and 3D space vectors can create a fitted garment for a similar shape body effectively and accurately. It is useful for the personalized garment design and suitable for the manufacturing process.