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This paper aims to automatically plan sequence for complex assembly products and improve assembly efficiency.

An assembly sequence planning system for workpieces (ASPW) based on deep reinforcement learning is proposed in this paper. However, there exist enormous challenges for using DRL to this problem due to the sparse reward and the lack of training environment. In this paper, a novel ASPW-DQN algorithm is proposed and a training platform is built to overcome these challenges.

The system can get a good decision-making result and a generalized model suitable for other assembly problems. The experiments conducted in Gazebo show good results and great potential of this approach.

The proposed ASPW-DQN unites the curriculum learning and parameter transfer, which can avoid the explosive growth of assembly relations and improve system efficiency. It is combined with realistic physics simulation engine Gazebo to provide required training environment. Additionally with the effect of deep neural networks, the result can be easily applied to other similar tasks.

The problem of concurrent thermal and vibration loading has not been thoroughly studied even though it is common in electronic packaging applications. Here we attempt to address such a problem using a damage mechanics based constitutive model. Damage mechanics constitutive model for eutectic Pb/Sn solder alloys is used to simulate the damage effects of concurrent cyclic thermal loads and vibrations on Ball Grid Array (BGA) packages. The model is implemented into the commercial finite element code ABAQUS through its user defined material subroutine capability. For the integration algorithm we have used a return mapping scheme, which dramatically improves the convergency rate as compared to previous implementations of the same model. Results are examined in terms of accumulation of plastic strain within the solder connections. It is shown that the simplistic Miner’s rule can not accurately account for the combined effect of both loadings acting concurrently.

Using social exchange theory, this paper explores the relationship between supervisor perceived organizational support and supervisor developmental feedback. It verifies the mediating role of supervisor felt obligation to organization and the moderating role of supervisor core self-evaluation in this relationship.

A two-wave survey sampling method was applied to collect 247 pieces of paired data (supervisors-new employees) in organizations in China.

The results show that supervisor felt obligation to organization mediates the relationship between supervisor perceived organizational support and supervisor developmental feedback. The findings suggest that a high level of supervisor core self-evaluation strengthens the relationship between supervisor perceived organizational support and supervisor felt obligation to organization and then facilitates supervisor developmental feedback.

This study combines two perspectives, organizational factor and supervisor trait, to reveal the occurrence mechanism of supervisor developmental feedback and complements the research on the influencing factors of supervisor developmental feedback. In addition, it provides some theoretical guidance and practical insights into how organizations can motivate supervisors to provide developmental feedback to new employees.

Language styles of online reviews are becoming increasingly important in consumers’ purchase decisions. However, there are inconsistencies in research on the effects of literal and figurative language styles in online reviews on service consumption. Drawing upon construal level theory, this research explores the effects of literal and figurative online reviews on consumers’ word-of-mouth recommendations and their internal mechanisms in the context of service consumption. In addition, this research identifies service types (experience vs credence services) as boundary conditions under which online review language styles play a role.

Three studies are designed to verify the effect of language style in online reviews on consumer word-of-mouth recommendations. Study 1 (N = 195) tests the interaction between construal level and (literal vs figurative) language style on consumers’ word-of-mouth recommendations. Study 2 (N = 191) identifies the depth of information processing as an underlying mechanism. Study 3 (N = 466) examines the boundary condition due to service type. The main methods used are independent sample t-test, ANOVA and bootstrapping.

The results illustrate that (1) consumers at different construal levels prefer online reviews with different language styles, and this can influence their word-of-mouth recommendations: consumers with a low construal level prefer online reviews with a literal language style, while those with a high construal level prefer online reviews with a figurative language style; (2) the depth of information processing plays a mediating role in the above interaction effect and (3) service type serves as a boundary condition such that the preference for literal (vs figurative) language style among low- (vs high-) construal-level consumers holds only for experience services; for credence services, online reviews with a literal language style enhance word-of-mouth recommendations, regardless of consumers’ construal level. The findings shed light on the drivers of word-of-mouth recommendations and provide insights to promote more effective word-of-mouth recommendations.

Drawing upon the construal level theory, this research explores the factors that influence online review language styles on consumer word-of-mouth recommendations and their underlying mechanisms and discusses the moderating effects of different service types (i.e. experience services and trust services). It not only sheds light on the contradictions in the previous literature but also provides new insights for academics and business managers to deepen their understanding of facilitating word-of-mouth recommendations.

The purpose of this paper is to establish a dynamic model considering the actual operating conditions of the train and to study the dynamic performance and vibration characteristics of axle box bearings under different operating conditions.

In this paper, based on the internal contact characteristics of double-row tapered roller bearings, a dynamic model considering the actual operating conditions of the train is established. The correctness of the model is verified by the vibration test of the bearing. Comparative analysis was conducted on the effects of axial force, radial force and rotational speed on the angular velocity of the cage, slip rate and vibration acceleration level of the inner ring.

As the force increases, the slip rate of the cages on both sides decreases, and the vibration acceleration level of the inner ring increases. With the increase of rotational speed, the cage slip rate of the axle box bearing increases and the vibration acceleration level of the inner ring increases.

A dynamic model is established considering the actual operating conditions, and the dynamic performance and vibration characteristics of the axle box bearing under different operating conditions are analyzed by numerical method. The research content can provide reference for the parameter design of high-speed railway bearings.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0085/

The return behavior of customers has a great impact on the e-retail industry and has resulted in the emergence of return-freight insurance (RI). Additionally, customer loss aversion arising from returns affects e-retailers' decisions and manufacturers' profits. Therefore, the main purpose of the authors' study is to determine how e-retailers and manufacturers choose their RI strategy and pricing according to customers' loss aversion.

The authors propose three scenarios: no RI, customer purchase RI and free e-retail RI (FRI). Meanwhile, the authors also model a Stackelberg game between e-retailers and manufacturers for analysis. Then, according to customer return behavior and loss aversion, the authors study the optimal pricing decision and RI premium allocation scheme for e-retailers and manufacturers under different scenarios.

It was found that the loss sensitivity reduces customers' willingness to buy RI, which is not conducive to the development of e-retailers and manufacturers. Additionally, with higher loss sensitivity, e-retailers and manufacturers offer FRI to gain higher profits, which supports the implementation of the FRI strategy.

The authors introduce customers' loss aversion into RI to analyze the optimal pricing decisions and profits of e-retailers and manufacturers, enriching the application of loss aversion theory. In addition, this study analyzes the two-way cost-sharing mechanism between manufacturers and e-retailers to provide FRI, which provides a theoretical basis for RI premium sharing.

As an important engine of economic growth, the digital economy is bringing new opportunities for the promotion of entrepreneurship. However, key questions regarding the extent of the effect of the digital economy on entrepreneurship remain unanswered. This study examines how the digital economy influences entrepreneurship in China using provincial data from 2011–2020, applying convergence tests and spatial econometric models.

Based on theoretical analysis and using macro provincial data covering the period of 2011–2020, we adopt a diversified empirical analytical method and apply a combination of the convergence trend test, spatial auto correlation test, and spatial Durbin model to test the research hypotheses.

First, there is spatial correlation between the digital economy and entrepreneurship. Second, the overall trend of China’s digital economy shows s convergence, with the whole country and the eastern region showing absolute β convergence and the whole country as well as the central and western regions showing β conditional convergence. Third, the digital economy can significantly promote entrepreneurship and has spatial spillover effects. Moreover, higher education has a negative moderating effect on the process of digital economy empowering entrepreneurship.

Studying the spatially correlated impacts of the digital economy on entrepreneurship enhances our understanding of its contribution to economic growth. Policy-makers can use these findings to develop targeted digital infrastructure investments in lagging provinces, guide entrepreneurs to better grasp the opportunities of the digital economy, and provide support for innovation and entrepreneurship. The findings also could offer Chinese experience that can be used to guide developing countries in utilizing the digital economy to enable entrepreneurship.

This paper expands and enriches the analytical focus on digital economy-empowered entrepreneurship and complements the current theoretical research on the moderating effect of the digital economy in empowering entrepreneurship.

Based on resource dependence theory and transaction cost economics this study explores how green customer integration (GCI) affects financial performance via information sharing and opportunistic behavior, and the moderating effects of dependence and trust.

This study develops a theoretical model and tests it using data from two-waved survey data of 206 Chinese manufacturers. The hypotheses were tested using hierarchical linear regression analysis.

The results show that GCI has a significant and positive impact on information sharing, but its impact on opportunistic behavior is insignificant. Notably, information sharing has a significant and positive impact on financial performance, while opportunistic behavior has an insignificant impact on financial performance. In addition, dependence negatively moderates the impact of GCI on information sharing and positively moderates the impact of GCI on opportunistic behavior. Trust negatively moderates the impact of GCI on opportunistic behavior.

Although GCI has received widespread attention, how it affects a firm's performance remains unclear. Most previous studies have focused only on its bright side and ignored its dark side. This study highlights how GCI affects financial performance through information sharing and opportunistic behavior, and the moderating effects of dependence and trust. This enriches the understanding of how and under what conditions GCI affects a firm's performance.

Based on the idea of part standardisation and product differentiation in lean management, this paper answers the question when integrate firms should choose market foreclosure to maximise profits by studying a two-tier supply chain, which contains three types of firms: suppliers, manufacturers and integrated firms. Moreover, the effect of the substitutability between final products and the competition among firms in the supply chain would be investigated from the perspective of dynamic analysis.

Considering the decision order of integrated firms and manufacturers in the downstream of the supply chain, the authors build three competition models. In each model, integrated firms compete with manufacturers in Bertrand–Nash fashion. And, suppliers compete with each other in Cournot fashion, so do integrated firms and manufacturers. The authors further discuss how the competitive relationship between firms affect the equilibrium result.

Numerical analysis reveals that under other conditions unchanged, the increased competition between downstream firms leads to the rise in the willingness of selling parts for integrated firms, while the increase in the number of suppliers has the opposite effect. In addition, due to the market change before and after the vertical merger, it may lead to the transition from profitable to unprofitable for the vertical merger.

This paper provides a theoretical analysis and managerial implication for integrated firms' market foreclosure decision. From the perspective of dynamic analysis, this paper demonstrates the result of vertical mergers and provides an explanation for the failure of vertical mergers.

The purpose of this paper is to discuss motion planning about crossing obstacles and welding trajectory for a new-model mobile obstacle-crossing welding robot system. The robot can cross the obstacle in this way that one of the three adhesion mobile parts is pulled off the ground in turn. An optimal obstacle-crossing approach needs to be studied to improve the welding efficiency.

According to the characteristics of this mobile welding robot, two methods for crossing obstacles are compared. A special method is used for obstacle-crossing and welding. The kinematic model is established. By the optimization method, the optimum parameters for crossing obstacles are calculated. The welding speed when the robot is crossing the obstacle is very important, so its value must be in a certain range. Finally, the tracks of the wheels when the robot is crossing the obstacle are analyzed in order to observe the obstacle-crossing process.

According to the analysis, the maximum speed of the vehicle in the obstacle-crossing is determined. When crossing the obstacle, the robot can do welding simultaneously. The welding speed cannot exceed a certain value. In the obstacle-crossing process, the tracks of the wheels can reflect the process. According to the obtained conclusion, the obstacle-crossing experiments are successfully completed, and the welding effect is good. The results can prove that the proposed method is feasible.

The speed of obstacle-crossing is not very large. It has some relationships with the lifting speed of the wheels, which is determined by the quality of drive motor. More efficient robot must be developed to meet the needs of industrial robot.

Based on the excellent obstacle-crossing and welding capabilities, the robot with the new mechanism has a widely applying prospect in the field of welding and inspecting large equipment.

The obstacle-crossing approach has certain innovation. The way that the robot can maintain continuous welding when crossing the obstacle is of a great significance.