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As entrepreneurial top management teams in multidivisional forms are typically treated in pertinent literature as the default organizational solutions for developing dynamic capabilities, the emerging innovative organizational forms tend to be overlooked, even though they could be a viable means of transforming established enterprises. The present case study examines how Haier's microenterprise and platforms influenced the firm's dynamic capabilities development.

The paper presents a qualitative case study of Haier Group Corporation in China.

The findings indicate that Haier employed a loosely coupled relationship between its headquarters and the microenterprises, developed quasi market-based exchange relationships and established peer-to-peer learning opportunities and coordination among its microenterprises. Data analyses further revealed that Haier has adopted three-step routines to capture market opportunities and enhance operational efficiency. This research extends the sensing-seizing-reconfiguration model typically recommended in the existing literature. It also demonstrates that organizational configuration is an important aspect of dynamic innovation. In summary, the study results showcase microdivisionalization as a new way for developing dynamic capabilities to better adapt to the ever-changing market environments.

In summary, our study showcased microdivisionalization as a new way for firms to change the organization structure and business strategies to better adapt to the ever-changing market environments.

With the popularity of high-rise buildings, wall inspection and cleaning are becoming more difficult and associated with danger. The best solution is to replace manual work with wall-climbing robots. Therefore, this paper proposes a design method for a rolling-adsorption wall-climbing robot (RWCR) based on vacuum negative pressure adsorption of the crawler. It can improve the operation efficiency while solving the safety problems.

The pulleys and tracks are used to form a dynamic sealing chamber to improve the dynamic adsorption effect and motion flexibility of the RWCR. The mapping relationship between the critical minimum adsorption force required for RWCR downward slip, longitudinal tipping and lateral overturning conditions for tipping and the wall inclination angle is calculated using the ultimate force method. The pressure and gas flow rate distribution of the negative pressure chamber under different slit heights of the negative pressure mechanism is analysed by the fluid dynamics software to derive the minimum negative pressure value that the fan needs to provide.

Simulation and test results show that the load capacity of the RWCR can reach up to 6.2 kg on the smooth glass wall, and the maximum load in the case of lateral movement is 4.2 kg, which verifies the rationality and effectiveness of the design.

This paper presents a new design method of a RWCR for different rough wall surfaces and analyses the ultimate force state and hydrodynamic characteristics.

This study explores how collaborative cost sharing between the buyer and the supplier in cold chain equipment and marketing and advertising affects the performance of a fresh agricultural produce supply chain (FAP-SC).

We use a contingency approach to modeling different scenarios and analyzing how fairness perception, interplaying with corporative–retailer cost sharing., influences the performance of fresh agricultural produce cold chains.

The findings of the research highlight the crucial role of the retailer's fairness concern. When the retailer's fairness concern is absent, cost sharing (in cold chain equipment and marketing and advertising) is found to help boost demand and enhance the profits of members of the supply chain; bilateral cost sharing is found to have a more significant impact than unilateral cost sharing. When the retailer's fairness concern is taken into account, however, cost sharing is found to reduce demand at a lower level of fairness coefficient but increases demand at a higher level of fairness coefficient; bilateral cost sharing boosts both demand and profit of the supply chain when the retailer is in a “high concern, high anger” state.

The findings of the research highlight the important role of the buyer's farness perception when supply chain partners adopt collaborative cost sharing programs. This study contributes significantly to research and practice in supply chain collaboration and agricultural cold chain performance.

The purpose of this work is to comprehensively reveal the spatial distribution and evolution features of a running-in attractor.

The friction coefficient signals extracted from wear experiments are reconstructed. A projected matrix is obtained based on the reconstructed matrix. Then the approach of three-dimensional (3D) histogram of phase points is proposed, which is used to intuitively characterize the complex properties of the running-in attractor.

The space occupied by the running-in attractor gradually contracts, then stabilizes and finally expands; the maximum of phase points number in a certain bin initially decreases, then keeps stable and finally increases rapidly; yet the percentage of bins number storing phase points shows an inverse variation tendency. Consequently, 3D histogram evolves from a nonuniform state to a uniform state then returns back to the nonuniform state, which indicates the evolution rule of “formation, stabilization and disappearance” of the running-in attractor.

Characterization on the features of the running-in attractor can provide valuable information about friction systems and their dynamic behaviors.

This study employs situated learning theory to elucidate the mechanisms of interorganizational collaboration by analyzing the relationships among absorptive capacity, institutional compensation, task cognitive integration and interorganizational collaboration in BIM-enabled construction projects.

An online questionnaire survey was conducted with managers and professionals involved in building information modeling (BIM-) enabled construction projects, and 220 valid responses were received. Data were analyzed by means of the linear regression models and bootstrap method.

The results show that (1) absorptive capacity, institutional compensation and task cognitive integration have a positive impact on interorganizational collaboration; (2) institutional compensation partially mediates the effect of absorptive capacity on interorganizational collaboration; (3) task cognitive integration fully mediates the effect of absorptive capacity on interorganizational collaboration; (4) institutional compensation and task cognitive integration serially and fully mediate the relationship between absorptive capacity and interorganizational collaboration and (5) the serial mediating model has a greater indirect effect than the other two models considered in this study.

This study contributes to the body of knowledge by demonstrating the way to break through the three types of organizational boundaries (i.e. syntactic, semantic and pragmatic organizational boundaries) and provide an internal collaborative mechanism from the perspective of situated learning theory. This study presents the critical effects of absorptive capacity, institutional compensation and task cognitive integration on interorganizational collaboration, selects the enhanced mediating model for explaining the effects of absorptive capacity on interorganizational collaboration and enables managers to update the traditional collaborative model in BIM-enabled construction projects.

The purpose of this paper is to explore the correction mechanism of resilient safety culture on new generation of construction workers (NGCWs)' unsafe behavior and test the multiple mediation effects of job crafting and perceived work meaningfulness based on the context of Chinese construction industry in order to find a new way to effectively correct the NGCWs' unsafe behavior.

A theoretical model of correction mechanism was established based on literature research and theoretical deduction. An empirical study was employed based on confirmatory factor analysis and regression analysis with a sample of 404 NGCWs in China.

The results indicated that resilient safety culture can effectively correct NGCWs' unsafe behavior through job crafting and perceived work meaningfulness. Job crafting and perceived work meaningfulness can play independent and serial mediating roles between resilient safety culture and unsafe behavior.

Research results only represent a short-term law about the correction mechanism of NGCWs' unsafe behavior based on a questionnaire study from China's construction industry. It is necessary to continue to implement a longitudinal study to test it in a relatively long period in future research. The findings also need to be verified based on the young construction workers in other countries.

This study provides a theoretical basis and feasible management reference for construction enterprises in China to correct NGCWs' unsafe behavior from the perspective of resilient safety culture. Furthermore, the construction of resilient safety culture in construction enterprises can help NGCWs better carry out job crafting and perceive the meaning of work.

This paper clarifies the correction mechanism of resilient safety culture on unsafe behavior of NGCWs, and further tests the independent mediating roles and a serial mediating role of job crafting and perceived work meaningfulness between resilient safety culture and unsafe behavior, which fills the research gap about the influence mechanism of resilient safety culture on young construction workers' unsafe behavior and enriches the theoretical system of unsafe behavior correction of construction workers.

New generation of construction workers (NGCWs) who were born in the 1980s and later have gradually become the main workforce of Chinese construction industry. They may behave differently when dealing with knowledge-related activities due to divergent characteristics caused by generational discrepancy. To provide a theoretical foundation for construction companies and safety managers to improve safety management, this research explores the factors and paths impacting the NGCWs' ability to share their safety knowledge.

Based on literature review, main factors that influence the safety knowledge sharing of the NGCWs were identified. Decision-Making Trial and Evaluation Laboratory and Interpretive Structural Modeling were applied to identify the hierarchical and contextual relations among the factors influencing the safety knowledge sharing of the NGCWs.

The results showed that sharing atmosphere ranked first in centrality and had a high degree of influence and being influenced, indicating itself an extremely important influencing factor of safety knowledge sharing of NGCWs. Six root influencing factors were identified, including individual characteristics, work pressure, sharing platform, incentive mechanism, leadership support and safety management system.

The number of influencing factors of safety knowledge sharing of the NGCWs identified in this study is limited, and the data obtained by the expert scoring method is subjective. In future studies, the model should be further developed and validated by incorporating experts from different fields to improve its integrity and applicability.

The influencing factors identified in this paper can provide a basis for construction companies and safety managers to improve productivity and safety management by taking relevant measures to promote safety knowledge sharing. The research contributes to the understanding knowledge management in the context of the emerging market. It helps to answer the question of how the market can maintain the economic growth success through effective knowledge management.

This paper investigates the influencing factors of NGCWs' safety knowledge sharing from the perspective of intergenerational differences, and the 13 influencing factor index system established expands the scope of research on factors influencing safety knowledge sharing among construction workers and fills the gap in safety knowledge sharing research on young construction workers. Furthermore, this paper establishes a multi-layer recursive structure model to clarify the influence path of the influencing factors and contributes to the understanding of safety knowledge sharing mechanism.

Accurately evaluating fluid flow behaviors and determining permeability for deforming porous media is time-consuming and remains challenging. This paper aims to propose a novel machine-learning method for the rapid estimation of permeability of porous media at different deformation stages constrained by hydro-mechanical coupling analysis.

A convolutional neural network (CNN) is proposed in this paper, which is guided by the results of finite element coupling analysis of equilibrium equation for mechanical deformation and Boltzmann equation for fluid dynamics during the hydro-mechanical coupling process [denoted as Finite element lattice Boltzmann model (FELBM) in this paper]. The FELBM ensures the Lattice Boltzmann analysis of coupled fluid flow with an unstructured mesh, which varies with the corresponding nodal displacement resulting from mechanical deformation. It provides reliable label data for permeability estimation at different stages using CNN.

The proposed CNN can rapidly and accurately estimate the permeability of deformable porous media, significantly reducing processing time. The application studies demonstrate high accuracy in predicting the permeability of deformable porous media for both the test and validation sets. The corresponding correlation coefficients (R²) is 0.93 for the validation set, and the R² for the test set A and test set B are 0.93 and 0.94, respectively.

This study proposes an innovative approach with the CNN to rapidly estimate permeability in porous media under dynamic deformations, guided by FELBM coupling analysis. The fast and accurate performance of CNN underscores its promising potential for future applications.

The assembly simulation in tolerance analysis is one of the most important steps for the tolerance design of mechanical products. However, most assembly simulation methods are based on the rigid body assumption, and those assembly simulation methods considering deformation have a poor efficiency. This paper aims to propose a novel efficient and precise tolerance analysis method based on stable contact to improve the efficiency and reliability of assembly deformation simulation.

The proposed method comprehensively considers the initial rigid assembly state, the assembly deformation and the stability examination of assembly simulation to improve the reliability of tolerance analysis results. The assembly deformation of mating surfaces was first calculated based on the boundary element method with optimal initial assembly state, then the stability of assembly simulation results was assessed by the density-based spatial clustering of applications with noise algorithm to improve the reliability of tolerance analysis. Finally, combining the small displacement torsor theory, the tolerance scheme was statistically analyzed based on sufficient samples.

A case study of a guide rail model demonstrated the efficiency and effectiveness of the proposed method.

The present study only considered the form error when generating the skin model shape, and the waviness and the roughness of the matching surface were not considered.

To the best of the authors’ knowledge, the proposed method is original in the assembly simulation considering stable contact, which can effectively ensure the reliability of the assembly simulation while taking into account the computational efficiency.

As complex analysis of contact models is required in the traditional assembly strategy, it is still a challenge for a robot to complete the multiple peg-in-hole assembly tasks autonomously. This paper aims to enable the robot to complete the assembly tasks autonomously and more efficiently, with the strategies learned by reinforcement learning (RL), a learning-accelerated deep deterministic policy gradient (LADDPG) algorithm is proposed.

The multiple peg-in-hole assembly strategy is designed in two modules: an advanced planning module and a bottom control module. The advanced module is completed by the LADDPG agent, which is used to derive advanced commands based on geometric and environmental constraints, that is, the desired contact force. The bottom-level control module will drive the robot to complete the compliant assembly task through the adaptive impedance algorithm according to the command set issued by the advanced module. In addition, a set of safety assurance mechanisms is developed to safely train a collaborative robot to complete autonomous learning.

The method can complete the assembly tasks well through RL, and it can realize satisfactory compliance of the robot to the environment. Compared with the original DDPG algorithm, the average values of the instantaneous maximum contact force and contact torque during the assembly process are reduced by approximately 38% and 74%, respectively.

The entire algorithm can also be applied to other robots and the assembly strategy can be applied in the field of the automatic assembly.

A compliant assembly strategy based on the LADDPG algorithm is proposed to complete the automated multiple peg-in-hole assembly tasks.