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This paper presents a Monotonic Unbounded Schemes Transformer (MUST) approach to bound/monotonize (remove undershoots and overshoots) unbounded spatial differencing schemes automatically, and naturally. Automatically means the approach (1) captures the critical cell Peclet number when an unbounded scheme starts to produce physically unrealistic solution automatically, and (2) removes the undershoots and overshoots as part of the formulation without requiring human interventions. Naturally implies, all the terms in the discretization equation of the unbounded spatial differencing scheme are retained.

The authors do not formulate new higher-order scheme. MUST transforms an unbounded higher-order scheme into a bounded higher-order scheme.

The solutions obtained with MUST are identical to those without MUST when the cell Peclet number is smaller than the critical cell Peclet number. For cell Peclet numbers larger than the critical cell Peclet numbers, MUST sets the nodal values to the limiter value which can be derived for the problem at-hand. The authors propose a way to derive the limiter value. The authors tested MUST on the central differencing scheme, the second-order upwind differencing scheme and the QUICK differencing scheme. In all cases tested, MUST is able to (1) capture the critical cell Peclet numbers; the exact locations when overshoots and undershoots occur, and (2) limit the nodal value to the value of the limiter values. These are achieved by retaining all the discretization terms of the respective differencing schemes naturally and accomplished automatically as part of the discretization process. The authors demonstrated MUST using one-dimensional problems. Results for a two-dimensional convection–diffusion problem are shown in Appendix to show generality of MUST.

The authors present an original approach to convert any unbounded scheme to bounded scheme while retaining all the terms in the original discretization equation.

The purpose of this paper is to develop a real-time trajectory planner with optimal maneuver for autonomous vehicles to deal with dynamic obstacles during parallel parking.

To deal with dynamic obstacles for autonomous vehicles during parking, a long- and short-term mixed trajectory planning algorithm is proposed in this paper. In long term, considering obstacle behavior, A-star algorithm was improved by RS curve and potential function via spatio-temporal map to obtain a safe and efficient initial trajectory. In short term, this paper proposes a nonlinear model predictive control trajectory optimizer to smooth and adjust the trajectory online based on the vehicle kinematic model. Moreover, the proposed method is simulated and verified in four common dynamic parking scenarios by ACADO Toolkit and QPOASE solver.

Compared with the spline optimization method, the results show that the proposed method can generate efficient obstacle avoidance strategies, safe parking trajectories and control parameters such as the front wheel angle and velocity in high-efficient central processing units.

It is aimed at improving the robustness of automatic parking system and providing a reference for decision-making in a dynamic environment.

The presentation of in-vehicle warnings information at risky driving scenarios is aimed to improve the collision avoidance ability of drivers. Existing studies have found that driver’s collision avoidance performance is affected by both warning information and driver’s workload. However, whether moderation and mediation effects exist among warning information, driver’s cognition, behavior and risky avoidance performance is unclear.

This purpose of this study is to examine whether the warning information type modifies the relationship between the forward collision risk and collision avoidance behavior. A driving simulator experiment was conducted with waring and command information.

Results of 30 participants indicated that command information improves collision avoidance behavior more than notification warning under the forward collision risky driving scenario. The primary reason for this is that collision avoidance behavior can be negatively affected by the forward collision risk. At the same time, command information can weaken this negative effect. Moreover, improved collision avoidance behavior can be achieved through increasing drivers’ mental workload.

The proposed model provides a comprehensive understanding of the factors influencing collision avoidance behavior, thus contributing to improved in-vehicle information system design.

The significant moderation effects evoke the fact that information types and mental workloads are critical in improving drivers’ collision avoidance ability. Through further calibration with larger sample size, the proposed structural model can be used to predict the effect of in-vehicle warnings in different risky driving scenarios.

The purpose of this study is to increase understanding about vertical coopetition from the perspective of interrelated conflict episodes on multiple levels.

The empirical part is based on a qualitative single case study of a coopetitive buyer-supplier relationship in the manufacturing sector.

Conflicts in vertical coopetition evolve from being merely functional and task-related to becoming dysfunctional and relationship-related, as the level of competition increases. The nature of conflict episodes influences the development of vertical coopetition, and therefore, the interrelatedness of conflict episodes is important to acknowledge.

Although a conflict is considered functional within a company, it may still be dysfunctional as far as the coopetitive relationship with the buyer or seller is concerned. Competition may trigger conflicts related to protecting own technology and knowledge, which may lead to termination of the cooperation, therefore coopetition should be managed in a way that balance sharing and protecting important knowledge to get advantages of coopetition.

The findings enhance prior research on vertical coopetition by offering new perspectives on causes of conflicts, their management, outcomes and types. The value of taking a multilevel approach lies in the ability to show how conflicts occur and influence other conflicts through the interrelatedness of conflict elements on different levels.

This paper claims to identify the behavioral and cultural features that push to use, or not, cryptocurrencies for electronic commerce. Indeed, despite the use of cryptocurrencies for electronic commerce spreading worldwide at a fast and growing pace, there are supporters and detractors among their users. The analysis of what distinguish these two groups of users is fundamental for understanding their different intention to use cryptocurrencies for electronic commerce.

A survey has been administered to 2,532 cryptocurrencies’ users across the USA and China, collecting data on their behavioral predispositions and cultural features. Results were then analyzed through structured equation modeling.

Results showed that while attitude, subjective norms, perceived behavioral control and herding behavior have a positive impact on the intention to use cryptocurrencies for electronic commerce, financial literacy has no influence. Cultural dimensions amplified or reduced the discovered relationships and caused different effects: positive for the USA and negative for China when considering illegal attitude and perceived risk.

Theory of planned behavior, financial behavior and cultural factors can, all together, represent a useful framework for envisioning the behavior of users in adopting cryptocurrencies for electronic commerce purposes through a test of all its elements. To the best of the authors’ knowledge, this is the first study considering behavior and cultural variables on the intention to use cryptocurrencies for electronic commerce as well as being the largest carried out, in terms of sample, on the cryptocurrency topic.

Although knowledge sharing in online communities has been studied for many years, little is known about the determinants for individuals' knowledge sharing in online health communities (OHCs) surrounding smoking cessation. Examining the determinants of knowledge sharing in such OHCs from the social capital perspective may prove particularly enlightening.

A questionnaire-based online user survey of two smoking cessation OHCs, one based in Finland and one based in China, was performed. Performing data analysis with partial least squares (SmartPLS 3.0), the authors developed a model conceptualizing the structural, cognitive and relational dimensions of social capital as drivers for knowledge sharing in smoking cessation OHCs, with users' stage in giving up smoking as a moderator.

The results show that structural capital (social ties) and relational capital (reciprocity) are important motivators behind knowledge sharing in smoking cessation OHCs, and the authors found a moderating effect of the stage in quitting on the antecedents' relationship with knowledge sharing in these OHCs.

The study enriches understanding of knowledge sharing in smoking cessation OHCs, contributing to theory and identifying practical implications for such groups' administration.

This study aimed to examine the impact of learning organization (LO) on job satisfaction and individual performance in Vietnamese enterprises. The study further explores the mediating effect of job satisfaction on the relationship between learning organization and employee performance.

Data were collected from 653 employees from various types of organizations in Vietnam. Structural equation modeling was implemented to test the hypotheses.

The results revealed that the proposed research model was supported. Results indicated that LOs positively influenced employees’ job satisfaction and the broader range of their individual performance. In addition, employees’ job satisfaction motivated them to achieve higher performance levels. The study also found a mediating effect of job satisfaction on the relationship between LO and employee performance. The results underscore the importance of implementing an LO culture for individual outcomes such as job satisfaction and employee performance in the Vietnamese cultural context, which is based on socialism and Confucianism.

To the best of the authors’ knowledge, this is the first study to examine the relationships among LO, job satisfaction and individual employee performance in the Vietnamese context. The results offer a deeper understanding of the LO concept in the Vietnamese cultural context and highlight the cultural impact on the LO concept and its effects. The results suggest how the LO concept is applied in the Vietnamese context.

This paper aims to research how technology transfer occurs, based on the Schumpeterian approach to innovation trilogy focusing on the interaction between the university and the company.

The methodology used for this study was the analysis of two cases with an exploratory and qualitative approach. The case study subjects were two Brazilian universities: University of Campinas (UNICAMP) and University of Vale do Rio dos Sinos (UNISINOS). Semi-structured interviews were used as the data collection technique, whereas content analysis was used as the analysis technique.

The main results showed the need of companies and universities to understand that working in collaborative technology research contributes to the transformation of applied research into technological innovations that can transform society.

The research’s limitations were the unfeasibility of studying the government helix, the lack of clear and established processes within universities so that a comparison between the cases would be possible and the lack of access to technology contracts, as they are considered confidential. In addition, the use of two cases is considered a limitation, as it is not possible to generalize the conclusions pointed out by the study.

With this research, the authors were able to conclude that the university–industry interaction process has been improving, but it still needs to advance in organizational aspects. Some of the aspects to be considered are the adjustments for the institutions’ internal policies, the existing negotiations, the researchers’ behavior regarding the dissemination of the innovation culture and the performance of the technological innovation centers, which gradually are being trained to work in the market as well as in the university. It is necessary that primarily companies and universities understand that they must join efforts in collaborative technological research, so that the financial resources invested are not only accepted as published articles in qualified journals but also turn into technological innovations accepted by the market. All this investment must return as new products, services and technologies that generate local, regional, national and even international impact, implementing new types of businesses and new markets and yielding an economic impact in the country, thus generating innovation and social well-being.

The proliferation of (big) data provides numerous opportunities for service advances in practice, yet research on using data to advance service is at a nascent stage in the literature. Many studies have discussed phenomenological benefits of data to service. However, limited research describes managerial issues behind such benefits, although a holistic understanding of the issues is essential in using data to advance service in practice and provides a basis for future research. The purpose of this paper is to address this research gap.

“Using data to advance service” is about change in organizations. Thus, this study uses action research methods of creating real change in organizations together with practitioners, thereby adding to scientific knowledge about practice. The authors participated in five service design projects with industry and government that used different data sets to design new services.

Drawing on lessons learned from the five projects, this study empirically identifies 11 managerial issues that should be considered in data-use for advancing service. In addition, by integrating the issues and relevant literature, this study offers theoretical implications for future research.

“Using data to advance service” is a research topic that emerged originally from practice. Action research or case studies on this topic are valuable in understanding practice and in identifying research priorities by discovering the gap between theory and practice. This study used action research over many years to observe real-world challenges and to make academic research relevant to the challenges. The authors believe that the empirical findings will help improve service practices of data-use and stimulate future research.

In the wake of the COVID-19 pandemics, the demand for innovative and effective methods of bacterial inactivation has become a critical area of research, providing the impetus for this study. The purpose of this research is to analyze the AuNPs-mediated photothermal inactivation of E. coli. Gold nanoparticles irradiated by laser represent a promising technique for combating bacterial infection that combines high-tech and scientific progress. The intermediate aim of the work was to present the calibration of the model with respect to the gold nanorods experiment. The purpose of this work is to study the effect of initial concentration of E. coli bacteria, the design of the chamber and the laser power on heat transfer and inactivation of E. coli bacteria.

Using the CFD simulation, the work combines three main concepts. 1. The conversion of laser light to heat has been described by a combination of three distinctive approximations: a- Discrete particle integration to take into account every nanoparticle within the system, b- Rayleigh-Drude approximation to determine the scattering and extinction coefficients and c- Lambert–Beer–Bourger law to describe the decrease in laser intensity across the AuNPs. 2. The contribution of the presence of E. coli bacteria to the thermal and fluid-dynamic fields in the microdevice was modeled by single-phase approach by determining the effective thermophysical properties of the water-bacteria mixture. 3. An approach based on a temperature threshold attained at which bacteria will be inactivated, has been used to predict bacterial response to temperature increases.

The comparison of the thermal fields and temporal temperature changes obtained by the CFD simulation with those obtained experimentally confirms the accuracy of the light-heat conversion model derived from the aforementioned approximations. The results show a linear relationship between maximum temperature and variation in laser power over the range studied, which is in line with previous experimental results. It was also found that the temperature inside the microchamber can exceed 55 °C only when a laser power higher than 0.8 W is used, so bacterial inactivation begins.

The experimental data allows to determinate the concentration of nanoparticles. This parameter is introduced into the mathematical model obtaining the same number of AuNPs. However, this assumption introduces a certain simplification, as in the mathematical model the distribution of nanoparticles is uniform.

This work is directly connected to the use of gold nanoparticles for energy conversion, as well as the field of bacterial inactivation in microfluidic systems such as lab-on-a-chip. Presented mathematical and numerical models can be extended to the entire spectrum of wavelengths with particular use of white light in the inactivation of bacteria.

This work represents a significant advancement in the field, as to the best of the authors’ knowledge, it is the first to employ a single-phase computational fluid dynamics (CFD) approach specifically combined with the thermal inactivation of bacteria. Moreover, this research pioneers the use of a numerical simulation to analyze the temperature threshold of photothermal inactivation of E. coli mediated by gold nanorods (AuNRs). The integration of these methodologies offers a new perspective on optimizing bacterial inactivation techniques, making this study a valuable contribution to both computational modeling and biomedical applications.