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This study examines the role of digital transformation intentions in enhancing the perceived resilience of firms, with a focus on China’s manufacturing sector. It investigates the mediating role of knowledge sharing and the moderating impact of transformational leadership.

A quantitative approach was employed, collecting data from 347 manufacturing firms. Participants included managers and MBA students involved in digital transformation projects. The study utilized statistical analysis to explore the relationships between digital transformation intentions, knowledge sharing, transformational leadership and perceived firm resilience.

The analysis reveals that knowledge sharing is a critical mediating factor between digital transformation intentions and perceived firm resilience. Additionally, transformational leadership significantly strengthens this relationship, highlighting its importance in the successful implementation of digital initiatives.

The study is geographically and sectorally limited to China’s manufacturing sector, which may affect the generalizability of the findings. Future research could explore other sectors and regions to validate and extend the results.

The findings underscore the necessity of integrating digital transformation initiatives with effective leadership and knowledge management practices. Firms that foster transformational leadership and facilitate knowledge sharing are better equipped to enhance their resilience in the face of global disruptions.

This research offers a deep understanding of how digital transformation intentions, mediated by knowledge sharing and supported by transformational leadership, contribute to perceived firm resilience. It provides valuable insights for both academic research and practical applications in the field of management.

In this paper a case study of mystery shopping is described, which was jointly conducted by a large apparel retailing company headquartered in Hong Kong and a management school in Shanghai. The program of mystery shopping in the stores of the company has been carried out for six years, and the scope of the activity covers some 30 cities in China. The reinforcement learning model is used to explain how mystery shopping can be employed as one strategy to improve service quality. The paper summarizes the main measures adopted by the company for continuous improvement. The whole processes of mystery shopping, the follow-up measures, and the evaluation sheet and work instruction are described as well. The paper also suggests the ways to select, train and control college students as mystery shoppers

The purpose of this paper is to provide the historical background of genealogical records and analyze the value of Chinese genealogical research through the study of names and genealogical resources.

The paper examines the historical evolution and value of Chinese genealogical records, with the focus on researching the Islamic Chinese names used by the people living in Guilin. The highlight of this paper includes the analysis and evolution of the Islamic Chinese names commonly adopted by the local people in Guilin. It concludes with the recommendations on emphasizing and making the best use of genealogical records to enhance the research value of Chinese overseas studies.

The paper covers the history of Islam and describes how the religion was introduced into China, as well as Muslims' ethnicity and identity. It also places focus on the importance of building a research collection in Asian history and Chinese genealogy.

This research study has a strong subject focus on Chinese genealogy, Asian history, and Islamic Chinese surnames. It is a narrow field that few researchers have delved into.

The results of this study will assist students, researchers, and the general public in tracing the origin of their surnames and developing their interest in the social and historical value of Chinese local history and genealogies.

The study of Chinese surnames is, by itself, a particular field for researching the social and political implications of contemporary Chinese society during the time the family members lived.

Very little research has been done in the area of Chinese local history and genealogy. The paper would be of value to researchers such as historians, sociologists, ethnologists and archaeologists, as well as students and anyone interested in researching a surname origin, its history and evolution.

Robots face fundamental challenges in achieving reliable and stable operations for complex home service scenarios. This is one of the crucial topics of robotics methods to imitate human beings’ advanced cognitive characteristics and apply them to solve complex tasks. The purpose of this study is to enable robots to have the ability to understand the scene and task process in complex scenes and to provide a reference method for robot task programming in complex scenes.

This paper constructs a task modeling method for robots in complex environments based on the characteristics of the perception-motor memory model of human cognition. In the aspect of episodic memory construction, the task execution process is included in the category of qualitative spatio-temporal calculus. The topology interaction of objects in a task scenario is used to define scene attributes. The task process can be regarded as changing scene attributes on a time scale. The qualitative spatio-temporal activity graphs are used to analyze the change process of the object state with time during the robot task execution. The tasks are divided according to the different values of scene attributes at different times during task execution. Based on this, in procedural memory, an object-centered motion model is developed by analyzing the changes in the relationship between objects in the scene episode by analyzing the scene changes before and after the robot performs the actions. Finally, the task execution process of the robot is constructed by alternately reconstructing episodic memory and procedural memory.

To verify the applicability of the proposed model, a scenario where the robot combines the object (one of the most common tasks in-home service) is set up. The proposed method can obtain the landscape of robot tasks in a complex environment.

The robot can achieve high-level task programming through the alternating interpretation of scenarios and actions. The proposed model differs from traditional methods based on geometric or physical feature information. However, it focuses on the spatial relationship of objects, which is more similar to the cognitive mechanism of human understanding of the environment.

The purpose of this study is to designed a robot odometry based on three dimensional (3D) laser point cloud data, inertial measurement unit (IMU) data and real-time kinematic (RTK) data in underground spatial features and gravity fluctuations environment. This method improves the mapping accuracy in two types of underground space: multi-layer space and large-scale scenarios.

An IMU–Laser–RTK fusion mapping algorithm based on Iterative Kalman Filter was proposed, and the observation equation and Jacobian matrix were derived. Aiming at the problem of inaccurate gravity estimation, the optimization of gravity is transformed into the optimization of SO(3), which avoids the problem of gravity over-parameterization.

Compared with the optimization method, the computational cost is reduced. Without relying on the wheel speed odometer, the robot synchronization localization and 3D environment modeling for multi-layer space are realized. The performance of the proposed algorithm is tested and compared in two types of underground space, and the robustness and accuracy in multi-layer space and large-scale scenarios are verified. The results show that the root mean square error of the proposed algorithm is 0.061 m, which achieves higher accuracy than other algorithms.

Based on the problem of large loop and low feature scale, this algorithm can better complete the map loop and self-positioning, and its root mean square error is more than double compared with other methods. The method proposed in this paper can better complete the autonomous positioning of the robot in the underground space with hierarchical feature degradation, and at the same time, an accurate 3D map can be constructed for subsequent research.

In order to find a way to combine traditional culture with modern living needs, taking “Chinese painting” as the breakthrough point, through the study of the development process and artistic characteristics of Chinese painting, four aspects of classical philosophy, natural landscape image, brush and ink composition artistic conception, and abstract aesthetic conception contained in Chinese painting are summed up. The results of the study provide enlightenment for contemporary residential landscape design, and summarize the methods of creating Chinese paintings in residential landscape design. Thus, a residential landscape model with the characteristics of “Chinese painting” is found out.

The purpose of this paper is to: summarize the major research that has been conducted regarding cross‐cultural issues in China; show the current practices on cross‐cultural management in Chinese organizations; and then identify future research needs on cross‐cultural management in China.

Meta‐analysis was carried out to summarize research of cross‐cultural management in China.

Empirical studies on cross‐cultural management in China have been conducted since the 1990s, and numerous empirical studies have been done in the past two decades across different level of constructs and practices (individual, group and organization). Among all the intercultural research concerning China, there are mainly two common types: the first type focuses on foreign managers and employees, center on their adjustment and performance in Chinese culture; and the second type of study examines Chinese who work with these foreigners in the multinational management setting. Furthermore, in recent years, emphases have been shifted from examining the effects of culture on single variables to examining the relationships among same and different level of variables.

Systematic conceptual model development and assessment of important topics are in great need. Although there is an increasing amount of comparative studies being done in China, very few studies have been conducted to study Chinese firms that are doing business abroad, which represents one of the most critical problems in the field of cross‐cultural management research in China. Most studies focus on cultural value identification and practical issues in Western global companies, which is concerned with comparison between Eastern and Western culture. Research should be conducted to study cultural differences among eastern countries, for example, countries in Asia.

Future cross‐culture management practices in China should follow several basic principles: be applicable, that is, build unique organizational culture that is embedded in the host country; be practical, since there is no well‐developed multinational culture in China, new culture should be concerned with both sides; be systematic, cross‐culture management practices should have supporting system; be equal, no single culture is better than another; cultural penetration, two different cultures have mutual impact; merit‐based appointment and promotion, use local personnel, not just talents from the home country. In Chinese settings, the most common cross‐cultural management interventions include: cross‐cultural training, cross‐cultural communication system and unified organizational culture.

This paper comprehensively reviews the research and practices on cross‐cultural management in China; identifies topics that have been studied in individual, group and organizational level. Implications on cross‐cultural selection, training are provided based research evidence.

Supply chain network design is an important strategic decision that firms make considering both the short‐ and long‐term consequences of the network's performance. The typical design approach implicitly assumes that, once designed, the facilities and the links will always operate as planned. In reality, however, facilities and the links connecting them, fail from time to time due to poor weather, natural or man‐made disasters, or a combination of any other factors. This work aims to propose a design framework that addresses the facility and link failures explicitly by accounting for their impact on a network's performance measures of efficiency and robustness.

The study incorporated a robustness metric for evaluating the resiliency of supply chains in the case of a network disruption. This robustness metric is based on expected losses incurred due to network failures. It defines efficiency and robustness in terms of operational cost and expected disruption cost (EDC), respectively. The EDC is defined in terms of loss of opportunity cost incurred due to not meeting demand on time after a disruption has occurred. The study used a scenario planning approach and formulated a mixed integer linear program model with the objective of maximizing both efficiency and robustness. It also evaluates the trade‐offs between efficiency and robustness.

The resulting supply chain is much more reliable in the long term since we have shown that a significant amount of robustness can be built into the system without compromising a lot on efficiency.

This work demonstrates a methodology which incorporates such disaster scenarios into the design of a supply chain network. This leads to a more reliable supply chain which would lead to higher profitability and lower disruption rates.

With the increasing number of institutions offering online degree programs, there is a growing need to understand the requirements for interactions and the challenges present in online learning environments. Consequently, this qualitative study aims to explore aspects of nontraditional students, typically defined as older than traditional college age, employed full-time or with family responsibilities.

This study employs a qualitative approach, conducting in-depth interviews with nine nontraditional students. Grounded in social presence theory, this study analyzed the experiences and viewpoints of nontraditional students in the online learning environment, utilizing thematic analysis.

Thematic analysis unveiled two major themes: interactions in online learning and challenges in online learning. Four sub-themes emerged from interactions in online learning (interaction with instructors, interaction with peers, content interaction and interface interaction). In addition, three sub-themes emerged from challenges in online learning (timing inflexibility, tools and technological barriers and diverse learning modes). The findings of this suggest that nontraditional students derived benefits from online learning, yet they faced limitations in peer interaction and experienced technological barriers.

This study is based on primary data collected from nontraditional students, offering valuable insights into the needs and challenges they face in higher education while engaged in online learning.

The purpose of this paper is to propose a new method based on three-dimensional (3D) vision technologies and human skill integrated deep learning to solve assembly positioning task such as peg-in-hole.

Hybrid camera configuration was used to provide the global and local views. Eye-in-hand mode guided the peg to be in contact with the hole plate using 3D vision in global view. When the peg was in contact with the workpiece surface, eye-to-hand mode provided the local view to accomplish peg-hole positioning based on trained CNN.

The results of assembly positioning experiments proved that the proposed method successfully distinguished the target hole from the other same size holes according to the CNN. The robot planned the motion according to the depth images and human skill guide line. The final positioning precision was good enough for the robot to carry out force controlled assembly.

The developed framework can have an important impact on robotic assembly positioning process, which combine with the existing force-guidance assembly technology as to build a whole set of autonomous assembly technology.

This paper proposed a new approach to the robotic assembly positioning based on 3D visual technologies and human skill integrated deep learning. Dual cameras swapping mode was used to provide visual feedback for the entire assembly motion planning process. The proposed workpiece positioning method provided an effective disturbance rejection, autonomous motion planning and increased overall performance with depth images feedback. The proposed peg-hole positioning method with human skill integrated provided the capability of target perceptual aliasing avoiding and successive motion decision for the robotic assembly manipulation.