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This research studies the development of the evolving dynamic system model and explores the important elements or factors and what detailed attributes are the main influences model in achieving the success of a business, industry and management. It also identifies the real and major differences between static and dynamic business management models and the detailed factors that influence them. Later, this research investigates the benefits/advantages and limitations/disadvantages of some research studies. The studies conducted in this research put more emphasis on the capabilities of system dynamics (SD) in modeling and the ability to measure, analyse and capture problems in business, industry, manufacturing etc.

The research presented in this work is a qualitative research based on a literature review. Publicly available research publications and reports have been used to create a research foundation, identify the research gaps and develop new analyses from the comparative studies. As the literature review progressed, the scope of the literature search was further narrowed down to the development of SD models. Often, references to certain selected literature have been examined to find other relevant literature. To do so, a supporting tool (that connects related articles) provided by Google Scholar, Scopus, and particular journals has been used.

The dynamic business and management model is very different from the static business model in complexity, formality, flexibility, capturing, relationships, advantages, innovation model, new goals, updated information, perspective and problem-solving abilities. The initial approach of a static system was applied in the canvas business model, but further developments can be continued with a dynamic system approach.

Based on this study, which shows that businesses are developing more towards digitalisation, wanting the ability to keep up with the era that is moving so fast and the desire to increase profits, an instrument is needed that can help describe the difficulties of the needs and developments of the future world. This instrument, or tool of SD, is also expected to assist in drawing future models and in building a business with complex variables that can be predicted from the beginning.

This study will contribute to the SD study for many business incubator research studies. Many practical in business incubator management to have a benefit how to achieve the business performance management (BPM) in SD review.

The significant differences between static and dynamics to be used for business research and strategic performance management. This comparative study analyses some SD models from many authors worldwide. Their goals behind their strategic business models and encounter for their respective progress.

Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and cooperative obstacle avoidance.

This study draws inspiration from the recurrent state-space model and recurrent models (RPM) to propose a simpler yet highly effective model called the unmanned aerial vehicles prediction model (UAVPM). The main objective is to assist in training the UAV representation model with a recurrent neural network, using the soft actor-critic algorithm.

This study proposes a generalized actor-critic framework consisting of three modules: representation, policy and value. This architecture serves as the foundation for training UAVPM. This study proposes the UAVPM, which is designed to aid in training the recurrent representation using the transition model, reward recovery model and observation recovery model. Unlike traditional approaches reliant solely on reward signals, RPM incorporates temporal information. In addition, it allows the inclusion of extra knowledge or information from virtual training environments. This study designs UAV target search and UAV cooperative obstacle avoidance tasks. The algorithm outperforms baselines in these two environments.

It is important to note that UAVPM does not play a role in the inference phase. This means that the representation model and policy remain independent of UAVPM. Consequently, this study can introduce additional “cheating” information from virtual training environments to guide the UAV representation without concerns about its real-world existence. By leveraging historical information more effectively, this study enhances UAVs’ decision-making abilities, thus improving the performance of both tasks at hand.

This paper presents a review of the state of the art on the application of blockchain and smart contracts to the peer-review process of scientific papers. The paper seeks to analyse how the main characteristics of the existing blockchain solutions in this field to detect opportunities for the improvement of future applications.

A systematic review of the literature on the subject was carried out in three databases recognized by the research community (IEEE Xplore, Scopus and Web of Science) and the Frontiers in Blockchain journal. A total of 1,967 articles were initially found, and after the exclusion process, the 26 remaining articles were classified according to the following dimensions: System Type, Open Access, Review Type, Reviewer Incentive, Token Economy, Blockchain Access, Blockchain Identification, Blockchain Used, Paper Storage, Anonymity and Maturity of the solution.

Results show that the solutions are normally concerned on offering incentives to the reviewers' work (often monetary). Other common general preferences among the solutions are the adoption of open reviews, the use of Ethereum, the implementation of publishing ecosystems and the use of InterPlanetary File System to the storage of the papers.

There are currently no studies covering the main aspects of blockchain solutions in the field of scientific peer review. The present study provides an overall review of the topic, summarizing important information on the current research and helping new adopters to develop solutions grounded on the existing literature.

The purpose of this empirical study is to enable a better understanding of the construct sustainability-oriented entrepreneurial intentions (SEI) and thereby promote sustainable entrepreneurship. It aims to examine the significance of work values (extrinsic rewards, intrinsic rewards and job security) as antecedents of SEI and to test the mediating effect of three constructs derived from the theory of planned behaviour – attitude towards sustainability, perceived entrepreneurial desirability and perceived entrepreneurial feasibility on the relationships between work values and SEI.

Confirmatory factor analysis and exploratory factor analysis were performed using analysis of moment structures v27 and statistical package for social science v28 on data obtained from the survey of young individuals of India. The respondents were students enrolled in higher education programmes.

All the identified antecedents (extrinsic rewards, intrinsic rewards, job security and theory of planned behaviour constructs) were found to be statistically significant. The partial mediating effect of the theory of planned behaviour constructs was also reported.

This empirical work leads to the theoretical advancement of the emerging construct, SEI, by presenting evidence of the significant individual-level antecedents of the construct. The results lead to recommendations for policymakers and educators to design strategies to strengthen SEI, thereby expanding the adoption of sustainable entrepreneurship.

The purpose of this paper is to study the following two issues regarding blockchain crowdsourcing. First, to design smart contracts with lower consumption to meet the needs of blockchain crowdsourcing services and also need to design better interaction modes to further reduce the cost of blockchain crowdsourcing services. Second, to design an effective privacy protection mechanism to protect user privacy while still providing high-quality crowdsourcing services for location-sensitive multiskilled mobile space crowdsourcing scenarios and blockchain exposure issues.

This paper proposes a blockchain-based privacy-preserving crowdsourcing model for multiskill mobile spaces. The model in this paper uses the zero-knowledge proof method to make the requester believe that the user is within a certain location without the user providing specific location information, thereby protecting the user’s location information and other privacy. In addition, through off-chain calculation and on-chain verification methods, gas consumption is also optimized.

This study deployed the model on Ethereum for testing. This study found that the privacy protection is feasible and the gas optimization is obvious.

This study designed a mobile space crowdsourcing based on a zero-knowledge proof privacy protection mechanism and optimized gas consumption.

Work environments are undergoing a transition and COVID-19 accelerated this change. Prior studies have associated various physical, digital and social work environment elements with occupational well-being. However, holistic approaches to the social work environment to compare the effects of the different elements have received less attention. The purpose of this study is to examine the relationship of various social work environment elements with hybrid worker well-being. The findings help organizations design their work environments and cultures for the post-COVID era.

The study builds on a quantitative survey with 1,057 respondents. The respondents were randomly selected, the answers were anonymous and the results were based on regression analysis.

The analysis indicated that working methods and practices, leadership and management practices, organizational communality and social interaction associate with hybrid worker well-being. Organizational values, reward systems and organizational structures yield no association with hybrid worker well-being.

The value of this paper is in that it investigates elements of the social work environment, presents a research model that examines the relationship of social work environment elements with hybrid worker well-being and provides new empirical data on their implications in a comparative manner.

This study is focused on achieving operational resilience through the practices of kaizen across the operational structure. The research is based on a case study of a commercial livestock farm in Nigeria. The study views the practice of kaizen from the perspective of the commitment of the members of the case study organisation who are directly involved with the operations of the organisation.

The study applies a qualitative approach to explore the topic, engaging members of the case study organisation in the research to gather relevant data on the implementation of kaizen practices and the drive to attain resilience in the case study organisation. Semi-structured personal interviews and workshops were used for data collection. The study adopts systems theory to explore the topic, identifying and engaging relevant stakeholders.

Parts of the findings relating to kaizen are the issues with the livestock production process, aggressive leadership and the issue of livestock mortality in the case study organisation. These were discussed based on extant literature. The study affirms the importance of organisational members' commitment and adequate leadership support to achieve sustainable kaizen practices. The study highlights the need to align kaizen practices with relevant organisational practices, such as reward systems and contextual requirements for its implementation in an operational process. The study suggests that further study can focus on the dynamics of the legal system on the implementation of kaizen, especially from a developing economic background like Nigeria, where this study was conducted.

The study projects learning about the spatial factors that can affect the practices of kaizen in critical sectors like livestock management.

The aim of this study is to empirically explore and analyze the concrete tasks of output measurement and the inherent challenges related to these tasks in a traditional and autonomous professional public work setting – the judicial system.

The analysis of the tasks is based on a categorization of general performance measurement motives (control-motivate-learn) and main stakeholder levels (society-organization-professionals). The analysis is exploratory and conducted as an empirical content analysis on materials and reports produced in two performance improvement projects conducted in European justice organizations.

The identified main tasks in the different categories are related to managing resources, controlling performance deviations, and encouraging improvement and development of performance. Based on the results, key improvement areas connected to output measurement in professional public organizations are connected to the improvement of objectivity and fairness in budgeting and work allocation practices, improvement of output measures' versatility and informativeness to highlight motivational and learning purposes, improvement of professional self-management in setting output targets and producing outputs, as well as improvement of organizational learning from the output measurement.

The paper presents empirically founded practical examples of challenges and improvement opportunities related to the tasks of output measurement in professional public organization.

This paper fulfils an identified need to study how general performance management motives realize as concrete tasks of output measurement in justice organizations.

Upon the premises of social exchange theory (SET), this study aimed at hypothesizing and examining a serial mediation model that investigated the underlying mechanism through which a high-performance work system (HPWS) affects individuals’ future time perspective (FTP).

The hypothesized relationships were examined using responses collected from 275 employees from 15 local private banks and 40 established branches through a proportionate stratified sampling technique. The statistical package for social sciences (SPSS) PROCESS macro 3.0 and analysis of moment’s structure (AMOS) 24.0 were employed for data analysis purposes.

The study revealed that HPWS is indirectly related to the individuals’ FTP through workplace social courage (WSC) and employee well-being (EWB) sequentially. Prescriptions for theoretical and managerial implications were discussed, and future research viewpoints with limitations were acknowledged.

This study illuminated the underlying mechanism and theoretical logic linking HPWS and individuals’ FTP by proposing the serial mediating effect of WSC and EWB.

This paper aims to study the agent learning from expert demonstration data while incorporating reinforcement learning (RL), which enables the agent to break through the limitations of expert demonstration data and reduces the dimensionality of the agent’s exploration space to speed up the training convergence rate.

Firstly, the decay weight function is set in the objective function of the agent’s training to combine both types of methods, and both RL and imitation learning (IL) are considered to guide the agent's behavior when updating the policy. Second, this study designs a coupling utilization method between the demonstration trajectory and the training experience, so that samples from both aspects can be combined during the agent’s learning process, and the utilization rate of the data and the agent’s learning speed can be improved.

The method is superior to other algorithms in terms of convergence speed and decision stability, avoiding training from scratch for reward values, and breaking through the restrictions brought by demonstration data.

The agent can adapt to dynamic scenes through exploration and trial-and-error mechanisms based on the experience of demonstrating trajectories. The demonstration data set used in IL and the experience samples obtained in the process of RL are coupled and used to improve the data utilization efficiency and the generalization ability of the agent.