Abstract
In this paper, we investigate a new variant of the multi-commodity network flow problem, taking into consideration multiple transport lines and time windows. This variant arises in a city logistics environment, more specifically in a long-haul passenger transport system that is also used to transport urban freight. We propose two mixed integer programming models for two objective functions: minimization of network operational costs and minimization of travel times. Since the problems under study are NP-hard, we propose three size reduction heuristics. In order to assess the performance of the proposed algorithms, we carried out computational experiments on a set of synthetic problem instances. We use the relative percentage deviation as performance criterion. For the cost objective function, a LP-and-Fix algorithm outperforms other methods in most tested instances, but for the travel time, a hybrid method (size reduction with LP-and-Fix algorithm) is, in general, better than other approaches.

Abstract
Background: The multimedia capturing of live lectures has increased within higher education institutions, even in the pre-COVID-19 period. Despite student satisfaction, the video lecture capture (VLC) influence on students' attainment and achievement of intended learning outcomes is controversial. Methods: To explore the impact of VLC, a cross-sectional study across 2016/17 (n=209 students) and 2017/18 (n=206 students) was conducted in the course of Mechanistic Toxicology in Pharmaceutical Education. Results: The results showed that 73% and 90% of the assessed students entirely viewed the videos of theoretical (550 minutes) and practical/laboratory classes (250 minutes), respectively. VLC impacted student attainment and the achievement of intended learning outcomes on the capacity to understand the subjects and apply knowledge. Conclusion: The effectiveness of VLC is to be considered under the framework of constructive alignment and the specificities of the course.

Abstract
This study investigates the potential of dynamically adjusting WIP cap levels to maximize the throughput (TH) performance and minimize work in process (WIP), according to real-time system state arising from process variability associated with low volume and high-variety production systems. Using an innovative approach based on state-of-the-art deep reinforcement learning (proximal policy optimization algorithm), we attain WIP reductions of up to 50% and 30%, with practically no losses in throughput, against pure-push systems and the statistical throughput control method (STC), respectively. An exploratory study based on simulation experiments was performed to provide support to our research. The reinforcement learning agent's performance was shown to be robust to variability changes within the production systems.

Abstract
Paper aims: This study analyzes the comprehension of production engineering students about the influence of some key variables on the process performance measures in a service process, Originality: This paper points out the need for educators to re-evaluate their approaches to teaching the Operations Management (OM) principles related to process flow measures, Research method: This study used scenario-based role-playing experiments with 2×2×2 between-subject factorial design with three independent variables (variability of activities, capacity utilization, and resource pooling) and four dependent variables related to key internal process performance measures (Flow Time, Overall Quality of service, Quality of service employees, and Queue Size), The sample was composed of 178 undergraduate production engineering students from a large university in Brazil from various institution units, Main findings: These results show that students perceived the use of resource pooling as an impactful practice, However, the students did not correctly identify the effects of increasing resource utilization and the variability on flow time and queue size when activities are pooled, Implications for theory and practice: The teaching of basic concepts of OM requires the support of computational tools, Undergraduate courses that contemplate subjects in the field of OM should work more intensely on simulation-based learning.

Abstract
The support and influence of industrial business associations (IBAs) for the internationalisation process of small and medium-sized enterprises (SMEs) is questioned. This qualitative case study on the textile industry in Portugal illustrates how SMEs are influenced by their IBA. Findings suggest that it has a preponderant role in supporting the international expansion of associated SMEs. Particularly, the promotion and organisation of trade fairs seem to foster first entries and continuous international expansion in the same way the IBA seems to influence their foreign market selection. However, SMEs feel that the IBA’s work could still be improved by their facilitating more matchmaking processes, promoting collaborations, improving their seizing of available internationalisation opportunities, and providing more information about agents and distributors in foreign markets. Thus, we can say that, despite the internet and global opportunities that firms can directly benefit from, the role of IBAs is still relevant for SME’s internationalisation, and there is still room for improvement.

Abstract
The topic of digital transformation has become increasingly prevalent in recent decades. Its importance is justified by the fact that not only can it change the way companies operate, but also bring to light new business strategies. Indeed, companies have ramped up operational data collection opportunities and adopted digital practices to facilitate new flows of design information, allow teams to interoperate in different ways, or improve system performance. Given that a digital transformation occurs under certain sociotechnical contexts and with specific purposes, their success can critically depend on the ability to unambiguously describe this context and the intended transformation in the form of new operational scenarios. One of the challenges faced when attempting a digital transformation is that these efforts can be ad-hoc and poorly structured, which does not tie the transformation to strategic objectives and operational strengths and limitations. This paper aims at addressing this issue by leveraging an existing systems engineering analysis method called Concept of Operations to provide structure to the digital transformation process. Our work shows that this method has the potential to accelerate the sociotechnical system redesign cycle and generate actionable decisions aligned with strategic goals and operational strengths and limitations. © 2022 The authors and IOS Press.