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The purpose of this research is to achieve multi-task autonomous driving by adjusting the network architecture of the model. Meanwhile, after achieving multi-task autonomous driving, the authors found that the trained neural network model performs poorly in untrained scenarios. Therefore, the authors proposed to improve the transfer efficiency of the model for new scenarios through transfer learning.

First, the authors achieved multi-task autonomous driving by training a model combining convolutional neural network and different structured long short-term memory (LSTM) layers. Second, the authors achieved fast transfer of neural network models in new scenarios by cross-model transfer learning. Finally, the authors combined data collection and data labeling to improve the efficiency of deep learning. Furthermore, the authors verified that the model has good robustness through light and shadow test.

This research achieved road tracking, real-time acceleration–deceleration, obstacle avoidance and left/right sign recognition. The model proposed by the authors (UniBiCLSTM) outperforms the existing models tested with model cars in terms of autonomous driving performance. Furthermore, the CMTL-UniBiCL-RL model trained by the authors through cross-model transfer learning improves the efficiency of model adaptation to new scenarios. Meanwhile, this research proposed an automatic data annotation method, which can save 1/4 of the time for deep learning.

This research provided novel solutions in the achievement of multi-task autonomous driving and neural network model scenario for transfer learning. The experiment was achieved on a single camera with an embedded chip and a scale model car, which is expected to simplify the hardware for autonomous driving.

The aim of this paper is to analyze the links between leaders' creation of knowledge in the setting of a leadership development program and the transfer of knowledge to their own organizations.

This is a case study of a leadership development program conducted during 2020–2022. The program was focused on how to lead and manage learning and knowledge processes in organizations, and offered a mix of theoretical perspectives and practical collaborative sessions. Data were collected through interviews and the participants' written reflections on their learning experiences. Total number of interviews was 13.

Overall the participants showed many examples of how they applied theories and practical tools that they had learned during the program in their own organizations. The participants experienced different types of challenges regarding knowledge transfer, but also potential meta-knowledge transfer through dialogue.

Pedagogical organizing of leadership development point to a need for supplementary dialogue between the leader of the development program and both the participating leader and manager.

This study shows that meta-knowledge transfer is not a simple matter of moving codified knowledge from the development program to new settings. Knowledge about others' knowledge requires and stimulates subject-to-subject relations between people through which new knowledge potential is created. These findings confirm and enhance previous studies that indicate the need for social support for soft-skill knowledge transfer.

The purpose of this paper is to examine the relationship among training design, trainee motivation and work environment on the transfer of learning for teachers enrolled in a continuing professional education (CPE) training program and the confirmation of potential positive, predictive relationships of trainee motivation, work environment and training design to transfer of learning. This study investigated the contribution of training efficiency and relevance as measured by the training design; work environment as measured by work autonomy, work complexity and work variability; and trainee’s motivation of training (learning- and job-oriented) to the transfer of knowledge and skills from the training program to their workplace. Both direct and indirect effects of mentioned components on the learning transfer were explored.

This study included 160 teachers working in high-needs schools with large numbers of English learners (ELs) Southwest USA. Teachers in this study primarily needed professional development to empower them and enhance their instructional capacity for ELs and economically challenged students. During the recruitment, participants completed a demographic information (e.g. gender, ethnicity, number of years teaching, age, educational background) survey.

A mediation model with training design as the mediating factor was developed and analyzed. The results revealed that training design fully mediated the relationship between trainees’ work environments and the transfer of knowledge, skills and attitude acquired from the training to their workplace. Furthermore, it partially mediated the relationship between learning-oriented motivation and the transfer of learning. These findings further amplify the significance of CPE program training design and foster important considerations for future research regarding the isolation of specific training design aspects that significantly contribute to the mediation of these relationships.

Considering the significance of learning transfer in developing professional knowledge and skills for target employees and trainees, confirming the mediating effects of training design on training transfer holds critical implications for future research. Specific and purposeful attention needs to be given to the design of CPE training. Investigations into the effects of training design and successful elements such as the training platform (online, hybrid or in-person), sample size, group structure, facilitation and participant demographics are warranted.

The finding of this research provides a preliminary guide for scholar-practitioners. Results of the study confirmed the role that learning-oriented motivation, job-oriented motivation, work variability or flexibility, work complexity and training design play in transfer of learning. In practice, training professionals will be more comfortable pinpointing the factors that lead to the transfer of learning or the lack of it.

Learning transfer has been found to be imperative for target employees and trainees to develop professional knowledge, skills and attitudes. Results of this study reveal variables that promote the positive transfer of learning to the workplace.

The present study used the job-demands and resources (JD-R) framework to understand how the training is transferred to an extreme working context through the analysis of job and personal resources (social support from the leader and colleagues and adaptability). Specifically, the authors tested the mediating role of motivation to transfer in the relationship (1) between the perceived support from the supervisor and colleagues and performance after training and (2) between adaptability and performance in an extreme context of the pandemic crisis – the first peak of COVID-19 in Portugal. Further, an inspection of the factors that predicted knowledge transfer and adaptability under an extreme context was carried out.

To do so, necessary training about the new safety rules regarding the pandemic crisis of COVID-19 was implemented in a healthcare institution as a strategy to help healthcare workers deal with the increasing uncertainty and complexity that was threatening their work. It consisted of three sessions (each with one hour of training) regarding procedures, rules and safety norms. The training occurred in May 2020. Overall, 291 healthcare workers participated in the study and answered one online questionnaire one week after training completion.

The results showed that the motivation to transfer had a significant indirect effect on the relationship between colleagues' and supervisors' support and performance and between adaptability and performance. Additionally, complementary analyses showed that the mediations depended on the levels of self-efficacy in such a way that the indirect relationships were stronger when self-efficacy was higher. Thus, adaptability and support, both from colleagues and the supervisor, are determining factors for knowledge transfer and resultant performance in extreme contexts, such as the COVID-19 pandemic crisis. Lastly, the results showed that the most significant predictors of transference were self-efficacy and the motivation to transfer the learned knowledge. On the other hand, self-efficacy, peer support and the opportunity to use the knowledge were the most significant predictors of adaptability.

These findings provide support for the role of employee motivation to transfer as a mechanism connecting both perceived support and adaptability to performance outcomes under extreme working contexts.

This study, conducted in the middle of the COVID-19 pandemic context – an extreme and uncertain working context – shows the relevance of both job and individual factors to predict employees' adaptability to such contexts.

This study aims to investigate the impact of technologies on the knowledge transfer process. In particular, the authors aim to analyze the topic of knowledge brokers and the relationship between broker and digital tools in the knowledge transfer process in the sport context. The study developed, therefore, aims to investigate the creating of this environment for knowledge transfer and knowledge sharing between man and machine, looking to improve the planning of technical sports projects of the clubs.

This paper presents a qualitative approach aimed at analyzing how platforms and the players’ agents can be useful tools in the knowledge transfer process. The research was conducted through a survey with a structured questionnaire via e-mail to 64 managers at the head of clubs playing in the Italian Series B basketball in the 2021–2022 championship. The total number of questions administered is 21.

The results demonstrate how sports directors, for the construction of a technical sports project, in addition to learning off the pitch by interactions with media, fans, pressure management, leadership skills, positive attitude, tolerance, understanding of other opinions, background and cultures, see the athletes’ agents as the main stakeholder of the managers. The research resulted, by the clubs’ managers, in both formal learning and informal-type learning. Informal learning, by far the most frequently used and most important in the general learning process of executives, is identified in the use that executives make of information available on digital platforms and of the fiduciary relationships that management has with players’ agents.

The results demonstrate the valuable opportunities for executives, coaches, managers and clubs to strategically manage learning and knowledge sharing. Improving and managing knowledge-sharing strategies would help increase knowledge, not only of the sports directors but also of the entire club, thus improving the absolute quality of the game within the Italian basketball divisions. The authors have developed an innovative framework regarding the construction of a “typed sports technical project”, and the authors have identified a series of crucial phases capable of determining the creation of a new roster of athletes.

This paper aims to conceptualize the role of leadership in organizational learning processes in multinational companies (MNCs). The authors present a model describing how managers in an MNC facilitated transitions between sub-processes of organizational learning at several organizational levels.

The authors collected data from the plants of a global process company in Norway, Brazil and China. Observation, in-depth interviews and archival material enabled one to reconstruct the organizational learning process over a period of 30 years as the company developed its own tailor-made improvement programme.

Based on the data, the authors describe the role of leadership in linking the sub-processes of organizational learning as orchestration, sponsoring and persistence. Orchestration included creating faith and optimism and designing the organization to allow close cooperation between operators and managers in the sub-process of experimenting. This eased transferring and institutionalizing in the global organization. Sponsoring included structural changes to support transferring and the demonstration of dedication to improvement programme values. These factors were important for institutionalizing. Persistence involved the continuous focus on adjustment of the improvement programme, which then facilitated further experimenting.

Firstly, this study suggests that activities and decisions in one sub-process have important implications for the following sub-processes. Secondly, this study indicates that leaders’ role in facilitating the transitions between sub-processes extend beyond their individual traits and behaviour, which previous research had focused on, and includes decisions concerning organizational structure and culture that help link social and organizational learning.

Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show more promising potential to cope with the challenges brought by increasingly complex tasks and environments, which have become the hot research topic in the field of robot skill learning. However, the contradiction between the difficulty of collecting robot–environment interaction data and the low data efficiency causes all these methods to face a serious data dilemma, which has become one of the key issues restricting their development. Therefore, this paper aims to comprehensively sort out and analyze the cause and solutions for the data dilemma in robot skill learning.

First, this review analyzes the causes of the data dilemma based on the classification and comparison of data-driven methods for robot skill learning; Then, the existing methods used to solve the data dilemma are introduced in detail. Finally, this review discusses the remaining open challenges and promising research topics for solving the data dilemma in the future.

This review shows that simulation–reality combination, state representation learning and knowledge sharing are crucial for overcoming the data dilemma of robot skill learning.

To the best of the authors’ knowledge, there are no surveys that systematically and comprehensively sort out and analyze the data dilemma in robot skill learning in the existing literature. It is hoped that this review can be helpful to better address the data dilemma in robot skill learning in the future.

Research has established that 38%, 56% and 66% of training is not transferred to work immediately, six months and 12 months after training, respectively. This has led scholars to advocate the continuous examination of factors that enhance training transfer to have a comprehensive understanding of the factors that enhance it. As a result, this study aims to examine transfer opportunity as a pretraining factor and its influence on assimilated training content (in-training factor); the influence of assimilated training content on motivation to transfer (post-training factor) and training transfer; the influence of motivation to transfer on training transfer; and the mediating role of motivation to transfer in the relationship between assimilated training content and training transfer.

A structural equation model is developed to test the five hypotheses formulated in this study using survey data obtained from 195 respondents who attended various training programs across different organizations. Following the assessment of the measurement model, the determination of the significance of the hypothesized paths is assessed based on the bias-corrected and accelerated confidence intervals obtained from the bootstrapping of 10,000 subsamples.

The findings of this study are that: transfer opportunity positively influences assimilated training content; assimilated training content positively influences motivation to transfer and training transfer; motivation to transfer positively influences training transfer; and motivation to transfer plays a complementary mediation role between assimilated training content and training transfer.

The nature of the work environment regarding the opportunity to transfer training influences trainees’ assimilation of the training content when they undergo training. Hence, organizations need to ensure that employees are always afforded the opportunity to transfer training content assimilated from previously attended training programs to assimilate the content of subsequent training programs. Furthermore, for training to culminate in training transfer, organizations and, more specifically, learning and development practitioners ought to pay attention to trainees’ assimilation of the content of training programs.

To the best of the authors’ knowledge, this is the first study to empirically consider transfer opportunity as a direct antecedent of assimilated training content. More so, it is one of few studies to empirically examine the influence of assimilated training content on training transfer.

This paper aim to solve the problem of low assembly success rate for 3c assembly lines designed based on classical control algorithms due to inevitable random disturbances and other factors,by incorporating intelligent algorithms into the assembly line, the assembly process can be extended to uncertain assembly scenarios.

This work proposes a reinforcement learning framework based on digital twins. First, the authors used Unity3D to build a simulation environment that matches the real scene and achieved data synchronization between the real environment and the simulation environment through the robot operating system. Then, the authors trained the reinforcement learning model in the simulation environment. Finally, by creating a digital twin environment, the authors transferred the skill learned from the simulation to the real environment and achieved stable algorithm deployment in real-world scenarios.

In this work, the authors have completed the transfer of skill-learning algorithms from virtual to real environments by establishing a digital twin environment. On the one hand, the experiment proves the progressiveness of the algorithm and the feasibility of the application of digital twins in reinforcement learning transfer. On the other hand, the experimental results also provide reference for the application of digital twins in 3C assembly scenarios.

In this work, the authors designed a new encoder structure in the simulation environment to encode image information, which improved the model’s perception of the environment. At the same time, the authors used the fixed strategy combined with the reinforcement learning strategy to learn skills, which improved the rate of convergence and stability of skills learning. Finally, the authors transferred the learned skills to the physical platform through digital twin technology and realized the safe operation of the flexible printed circuit assembly task.

This study explores the impact of Industry Revolution 4.0 (IR4.0) on learning factory implementation in Universiti Malaysia Pahang (UMP). A learning factory is an action-oriented approach to teaching with participants acquiring competencies through structured self-learning processes in a production–technological learning environment. It integrates different teaching methods with the main objective of moving traditional teaching methods to become closer to real industrial problems. However, there is still limited information that can be used to evaluate the impact of IR4.0 on its implementation in UMP. Therefore, this study focuses on exploring the challenges faced by UMP in developing their learning factory and examines the effectiveness of UMP Learning Factory as a new teaching and learning process to support Industry 4.0.

First of all, identifying a problem was done, and information regarding the topic was obtained via research from various sources. Example of sources is online journals, books, the Internet and others. It is essential to understand the rationale behind why the research should be carried out as well as the objectives of the study in relation to the topic of interest. After that, a survey of the relevant literature was carried out to compile more pertinent material and run it through the lens of the selected subject. It makes the process of establishing a theoretical framework easier, and it also improves one's knowledge of the research being done. The next step in the process involves selecting responders based on the research. In order to calculate the appropriate sample size for this study, we must identify the entire population so that we can ensure that the findings we obtain are reliable. The entire population are first filtered based on the purpose of the research, and only then is it possible to establish the size of the needed sample of respondents. This research study's data gathering techniques consisted of five steps; however, in this particular study, the researcher only employed two approaches, which focused on individual interviews and semi-structured interviews, respectively. In order to address both the study purpose and the research questions, the interview questions that were developed were meant to relate to one another. During this interview procedure, the interviewees will have the option to elaborate or supply an increasing amount of pertinent data and information. Participants in the interview who have accumulated a significant amount of experience in the relevant sector are better positioned to provide both their personal and professional perspectives. The researcher will utilize audio to gather the script from the responder so that they may collect the data for analysis. The researcher is able to find the precise data analysis from the responses with the assistance of this programme. As a result, the researcher's question to the responders can be considered credible and genuine. Each respondent may read a particular question in the questionnaire in the same manner. As a result, although the question may be trusted, this fact is mostly irrelevant given that it lacks internal validity and hence does not make it possible to answer the research topic. In conclusion, the findings of this study are analysed, and conclusions are drawn from them.

In order to explore and answer research questions that are tailored to research objectives, the purpose of this study is to investigate such questions. The primary purpose of this study is to evaluate the influence that Industry 4.0 will have on the instructional methodology that will be utilized at UMP. Regarding the second aim, the purpose is to investigate the difficulties that the Universiti Malaysia Pahang encounters in the process of creating the Learning Factory. The final goal is to investigate how well UMP Learning Factory performs as a novel approach to education and training that is intended to assist Industry 4.0. The University of Malaya in Penang (UMP), which is widely regarded as one of the premier educational institutions of its kind in Malaysia, has recently implemented a learning factory as one of its pedagogical approaches. The university's deployment of the learning factory is very recent, and as such, there is room for improvement to make the most of the potential offered by this instructional approach. However, the findings of this research indicate that there is a favourable influence on both learning and teaching. The influence of the implementation of Learning Factory, which is becoming one technique of educational reform, is one of the most important factors to consider. According to the study's findings, UMP has successfully developed a learning factory that has a major influence on the learning process and is extremely good at what it does. The student benefits from an enhanced teaching and learning experience as a direct result of the contribution made by the learning factory. When it comes to generating a learning component based on the result, several obstacles have been identified. If UMP or other institutions intend to create a new learning factory, the problems might be considered factors to consider. In the teaching and learning process context, it has been demonstrated that a learning factory is particularly successful. The learning factory approach is one of the teaching techniques that makes the students understand better and have the experience of handling and controlling the equipment. Because this method introduces the hands-on approach, it is one of the teaching methods. The learning factory method is one that, in its most fundamental form, may be particularly beneficial for students to prepare themselves for the arduous process of joining the workforce. The classroom setting will be quite similar to that of a factory, and the student will improve their general collaboration. In addition to this, they will be able to operate machines and have knowledge regarding the machines that are found in the learning factory. The learning factory makes a significant contribution to the knowledge transfer process in UMP by facilitating the development of a deeper comprehension of certain bodies of information. When compared to more traditional methods of transferring information, the student will have a much easier time comprehending the material that is taught to them through the use of the hands-on learning technique.

This study gained some information about the impact of IR4.0 towards educational transformation, which is expected to give positive results. Basically, this research will provide further explanation about IR4.0 and educational transformation in UMP focus on learning factory. Generally, the implementation of IR4.0 in education will produce a positive result and help the students in the future. The result from this case study will hopefully be beneficial to society. The finding from this research will be used as references to all, especially top management and technical staff of UMP, for further understanding of the impact of the implementation of the learning factory. While conducting this research, seven respondents were selected from the two faculty with their own learning factories, Faculty of Industrial Management (FIM) and Faculty of Technology (FTEK). The researcher targeted lecturers and technical staff as their respondents. The overall result from the interview session was analysed. All the result is based on the interview answer to the researcher's question