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The purpose of this paper is to explore how an organization can combine different types of open innovations and what are the key factors that may influence the combination of different open innovations.

The basic methodology of this paper is the longitudinal inductive analysis within the conceptual framework of the open innovation proposed by Dahlander and Gann (2010). In this case study of Xiaomi Tech Inc., the open innovation combination is investigated through examining 25 new products created between August 2010 and December 2016 in terms of four general types: acquiring, sourcing, selling and revealing open innovation.

In practice, the combination of different types of open innovations can be realized. A firm may combine different open innovations at three levels: a single product level, a related product cluster level and a company level. In addition, different open innovations can be combined in diverse modes. The purpose of combining different types of open innovations is to overcome the disadvantages of each type and to exploit the advantages of all different types. Many factors may affect a firm’s option of how to combine open innovations. At different development stages, a firm may make and implement corresponding strategic direction based on its innovation capacity and internal resource. For a given strategy, the firm needs to create profits and manage intellectual property in the implementation of open innovations. These factors are interacted each other, rather than isolated.

The findings of this paper are helpful for better understanding how and why an organization can combine different types of open innovations. From a managerial point of view, an organization may combine different types of open innovations to leverage advantages and avoid disadvantages of each certain type of open innovation. An appropriate combination of different open innovations can effectively improve new product development.

It is a huge technical and engineering challenge to realize the precise assembly of thousands of large optics in high power solid-state laser system. Using the 400-mm aperture-sized transport mirror as a case, this paper aims to present an intelligent numerical computation methodology for mounting performance analysis and modeling of large optics in a high-power laser system for inertial confinement fusion (ICF).

Fundamental principles of modeling and analysis of the transport mirror surface distortion are proposed, and a genetic algorithm-based computation framework is proposed to evaluate and optimize the assembly and mounting performance of large laser optics.

The stringent specifications of large ICF optics place very tight constraints upon the transport mirror’s assembly and mounts. The operational requirements on surface distortion [peak-to-valley and root mean square (RMS)] can be met as it is appropriately assembled by the close loop of assembly-inspection-optimization-fastening. In the end, the experimental study validates the reliability and effectiveness of the transport mirror mounting method.

In the assembly design and mounting performance evaluation of large laser optics, the whole study has the advantages of accurate evaluation and intelligent optimization on nano-level optical surface distortion, which provides a fundamental methodology for precise assembly and mounting of large ICF optics.

This paper aims to describe a theoretical and experimental research concerning influence of recess shape on comprehensive lubrication performance of high speed and heavy load hydrostatic thrust bearing with a constant flow.

The lubrication performance of a hydrostatic thrust bearing with different recess shape under the working conditions of high speed and heavy load has been simulated by using computational fluid dynamics and finite volume method.

It is found that the comprehensive lubrication performance of a hydrostatic thrust bearing with circular recess is optimal. The results demonstrate that recess shape has a great influence on the lubrication performance of the hydrostatic thrust bearing.

The simulation results indicate that to get an improved performance from a hydrostatic thrust bearing with constant flow, a proper selection of the recess shape is essential.

Hydrostatic thrust bearing is a key component of the vertical CNC machining equipment, and often results in friction failure under the working condition of high speed and heavy load. The lubricating oil film becomes thin or breaks because of high speed and heavy load and it affects the high precision and stable operation of the vertical CNC machining equipment; hence, it is an effective way of avoiding friction failure for achieving the oil film shape prediction

For the hydrostatic thrust bearing with double rectangular cavities, researchers solve the deformation of the friction pairs in hydrostatic bearing by using the computation of hydrodynamics, elasticity theory, finite element method and fluid-thermal-mechanical coupled method. The deformation includes heat deformation and elasticity deformation, the shape of gap oil film is got according to the deformation of the friction pairs in hydrostatic bearing, and gets the shape of gap oil film, and determines the influencing factors and laws of the oil film shape, and achieves the prediction of oil film shape, and ascertains the mechanism of friction failure. An experimental verification is carried out.

Results show that the deformation of the rotational workbench is upturned along its radial direction under the working condition of high speed and heavy load. However, the deformation of the base is downturned along its radial direction and the deformation law of the gap oil film along the radius direction is estimated; the outer diameter is close but the inner diameter is divergent wedge.

The conclusion can provide a theoretical basis for the oil film control of hydrostatic thrust bearing and improve the stability of vertical CNC machining equipment.

Although prefabricated construction (PC) technology has attracted considerable attention worldwide because of its significant role in the global fight against COVID-19, market-driven adoption is still limited. The mechanisms for PC technology adoption have yet to be defined, which inhibits its diffusion in the construction market. This study aims to reveal the intrinsic motivation and action mechanism for PC technology adoption.

Drawing on the technology acceptance model (TAM), the study integrates characteristics from the diffusion of innovation theory to propose a multifaceted model for explaining practitioners’ PC technology adoption behavior from technology, organization and environment contexts. The proposed theoretical model was empirically examined via a survey of 234 professionals in mainland China using the partial least squares-structural equation modeling technique.

The outcomes indicated that relative advantage, corporate social responsibility and market demand are significantly positively related to practitioners’ perceived usefulness from PC technology. Regulatory support and trading partner support have noticeable positive effects on practitioners’ perceived ease of use from PC technology. Perceived ease of use is found to positively influence perceived usefulness, and both of them have a positive influence on the attitude toward adopting PC technology. Attitude is further confirmed as an important predictor of adoption intention, which would lead to actual PC technology adoption behavior.

To the best of the authors’ knowledge, this paper is the first attempt to explore industry perceptions toward PC technology adoption, providing valuable guidance for the effective diffusion of PC technology and laying a reliable foundation for research on other construction innovation adoption in post-COVID-19.

Lightweight apps such as WeChat mini programs (WMPs) are an emerging mobile channel (m-channel) touchpoint that have gained remarkable popularity among consumers. Despite the focus of migration research on traditional m-channel touchpoints (e.g. native apps and mobile websites), but few researchers have examined why consumers switch from native to lightweight apps. Drawing on the push-pull-mooring framework, this study aims to identify the key factors influencing consumers' switching related to lightweight apps.

The data were collected using a questionnaire survey of 416 WMP consumers and the proposed model was analyzed through structural equation modeling.

The results show that the push effect, specifically, high privacy concern, nudges consumers away from native apps, whereas the pull effects, including relative ease of use, convenience of access and exit and socially-oriented interaction, entice consumers to lightweight apps. Further, consumer switching intention is influenced by habit and perceived technology control, both of which reflect the mooring effects. Switching intention also stands as an important precedent of actual behavior.

This study is among the first theoretical explorations of consumer switching across m-channel touchpoints in the context of mobile commerce. For information system practice, these findings provide new insights for both incumbent providers and newcomers on how to retain existing shoppers as well as attract potential shoppers effectively.

The purpose of this study is to use role expectation theory to identify potential determinants of user voting avoidance on mobile social media.

Data were collected through a survey of 602 WeChat users, and the proposed model was analysed using structural equation modelling.

Results indicate that user voting avoidance was positively influenced by unfair competition, perceived inauthenticity, perceived information insecurity, over-consumption of renqing (a unique Chinese human relation) and organisation placement in the context of mobile social media.

This study illustrates mobile user voting avoidance from the perspective of role expectation theory and clarifies the importance of avoidance in current voting research.

Building on organizational support theory and social exchange theory, the purpose of this paper is to study the impact of organizational support on employee performance (EP) in the context of flexible manufacturing. In particular, the authors aimed to investigate the mediating role of employee attitude between organizational support and EP, and the moderating role of organizational justice (OJ).

A total of 180 participants from 36 work teams employed in 7 large automotive manufacturing enterprises in China were surveyed using a questionnaire designed by the authors. Multiple linear regressions were used to test the proposed hypotheses.

The results revealed four new performance indicators of frontline workers in the context of flexible manufacturing: continuous learning, teamwork, problem solving and active work. Organizational support can be divided into reinforcing support and inhibitive support. Reinforcing organizational support has a positive effect on new performance of frontline workers, and a sense of belonging plays a strong mediating role between them. Inhibitive organizational support plays an important role in the sense of awe (SA) of employees, but the SA has no influence on new performance of frontline workers. OJ plays a strong moderating role between organizational support and employee attitudes.

This study is one of the first attempts to explore the performance of frontline workers in the context of flexible manufacturing and contributes to the existing literature on the relationship between organizational support and EP.

The purpose of this paper is to attempt to establish the pattern of multi‐objective and multi‐dimensional grey fuzzy forecasting with feedback based on the theories of grey system and fuzzy recognition.

First, according to the given weights, the weighting integrated value of samples were computed. Second, the method of fuzzy recognition with single index was employed to calculate the fuzzy classification of the integrated value. According to the cause analysis, the fuzzy classification of the integrated value is used to compute the weights of indexes. In the same way, repeating the above processes, the weighting integrated value and fuzzy classification with given accuracy are retrieved at the same time. Finally, the authors calculate the correlation coefficient between the weighting integrated values and forecasting objects, according to the principle of maximal relativity, optimizing the weighting integrated value of samples, establishing the fuzzy forecasting pattern, and checking the model's precision. A numeric example is also computed in the last part of the paper.

The results are convincing: not only that the pattern of multi‐objective and multi‐dimensional grey fuzzy forecasting with feedback based is valid, but also the model's applied prediction accuracy is higher, where the test samples' mean forecast accuracy of groundwater dynamic levels is 96.50 percent.

The method exposed in the paper can be used to predict groundwater dynamic levels and even for other similar forecast problems.

The paper succeeds in realising both a prediction pattern and application of predicting groundwater dynamic levels by using the newest developed theories of grey system and fuzzy recognition.

Massively multiplayer online role-playing games (MMORPGs) create quasi-real social systems in which players can interact with one another, and quasi-real economic systems where players can consume and trade in-game items with virtual currency. The in-game currency price, an important indicator of a virtual economy, is highly contingent on players’ behavioral interaction in MMORPGs. The purpose of this paper is to adopt a network perspective to examine how topological characteristics of social networks in an MMORPG, namely, network externalities, density, and closure, would exert impacts on the in-game currency price.

Players’ behavioral data were collected from a popular MMORPG in China on a weekly basis for 52 weeks. With a time series analytical approach, the empirical model for the price function of in-game currency was estimated with vector autoregression.

The results show that the number of core avatars and network density are positively associated with in-game currency price, while network closure has a negative effect on in-game currency price. However, in-game currency price is found to have no significant relationship with the trade volume of the currency.

This study fills in an important research gap by investigating factors influencing the in-game currency price of MMORPGs from a network perspective, which contributes to the existing literature of network effects and advances our understanding about how players’ interaction will influence the dynamics of a virtual economy. The findings could offer useful insights for online game companies to better understand their players’ social interaction and consumption behavior.