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This study proposes a machine learning framework to predict customer complaints from production line tests in an automotive company's lot-release process, enhancing Quality 4.0. It aims to design and implement the framework, compare different machine learning (ML) models and evaluate a non-sampling threshold-moving approach for adjusting prediction capabilities based on product requirements.

This study applies the Cross-Industry Standard Process for Data Mining (CRISP-DM) and four ML models to predict customer complaints from automotive production tests. It employs cost-sensitive and threshold-moving techniques to address data imbalance, with the F1-Score and Matthews correlation coefficient assessing model performance.

The framework effectively predicts customer complaint-related tests. XGBoost outperformed the other models with an F1-Score of 72.4% and a Matthews correlation coefficient of 75%. It improves the lot-release process and cost efficiency over heuristic methods.

The framework has been tested on real-world data and shows promising results in improving lot-release decisions and reducing complaints and costs. It enables companies to adjust predictive models by changing only the threshold, eliminating the need for retraining.

To the best of our knowledge, there is limited literature on using ML to predict customer complaints for the lot-release process in an automotive company. Our proposed framework integrates ML with a non-sampling approach, demonstrating its effectiveness in predicting complaints and reducing costs, fostering Quality 4.0.

This paper explores the impact of multiple team membership (MTM) on the productivity of team members in engineering consulting firms. MTM refers to employees participating concurrently in multiple teams, a concept closely linked to projectification. Despite the fact that this concept can enhance collaboration, it also introduces coordination challenges that may negatively affect productivity.

Through an inductive approach involving 12 semi-structured interviews with engineering consulting professionals specializing in water and energy infrastructure projects, this paper examines the factors affecting team member productivity in an MTM setting. Following the interviews, a Delphi technique was employed, engaging 16 experts to rank the factors and sub-factors identified from the interview data. This two-stage approach ensured a comprehensive and validated assessment of productivity factors.

This study develops 8 factors process model grounded in structuration theory to explain the socio-technical mechanisms by which multiple team membership shapes productivity outcomes in engineering consulting firms specialized in water and energy infrastructure projects. Key findings surface micro-foundations, tensions in technology provisions, planning processes, and career development that inform theoretical advances and practical improvements.

This research contributes empirically insights into managing MTM in expert service contexts. Applying Giddens' structuration theory, this study reveals how agency and structures shape productivity across organizational, team, and individual levels. In practice, this study provides recommendations for improving productivity within projectified environments, mainly for team members working in an MTM environment in engineering consulting firms specializing in water and energy infrastructure projects.

Powder bed fusion-laser beam (PBF-LB) is a rapidly growing manufacturing technology for producing Al-Si alloys. This technology can be used to produce high-pressure die-casting (HPDC) prototypes. The purpose of this paper is to understand the similarities and differences in the microstructures and properties of PBF-LB and HPDC alloys.

PBF-LB AlSi10Mg and HPDC AlSi10Mn plates with different thicknesses were manufactured. Iso-thermal heat treatment was conducted on PBF-LB bending plates. A detailed meso-micro-nanostructure analysis was performed. Tensile, bending and microhardness tests were conducted on both alloys.

The PBF-LB skin was highly textured and softer than its core, opposite to what is observed in the HPDC alloy. Increasing sample thickness increased the bulk strength for the PBF-LB alloy, contrasting with the decrease for the HPDC alloy. In addition, the tolerance to fracture initiation during bending deformation is greater for the HPDC material, probably due to its stronger skin region.

This knowledge is crucial to understand how geometry of parts may affect the properties of PBF-LB components. In particular, understanding the role of geometry is important when using PBF-LB as a HPDC prototype.

This is the first comprehensive meso-micro-nanostructure comparison of both PBF-LB and HPDC alloys from the millimetre to nanometre scale reported to date that also considers variations in the skin versus core microstructure and mechanical properties.

The case is derived from secondary sources, including publicly available reports and information about all companies directly or indirectly engaged in the industry. No primary sources were available.

This teaching case is designed for students to demonstrate their mastery of industry-level analysis in the emerging space tourism industry. It allows students to understand what constitutes the industry within the broader space sector and to apply analytical tools such as PESTEL and Porter’s Five Forces, with the option to discuss strategic groups. Students gain insights into how the industry is evolving within its broader environment and how companies could respond or differentiate themselves. Information is also provided for students to consider the broader social impact of a relatively new industry from the perspective of sustainable development.

The case is written for undergraduate and graduate students enrolled in strategic management courses. The case placement is ideally in conjunction with industry-level analytical frameworks such as Porter’s Five Forces, PESTEL analysis, strategic groups (optional) and industry life cycle. Most strategic management textbooks cover these concepts in the first few chapters. For example, “Strategic Management, 14th edition” by Hill, Schilling and Jones (2023) covers these topics in chapter 2. Given that space tourism is an embryonic industry dependent on technological innovation, instructors might also use this case in innovation or entrepreneurship-related courses. This case could also be used to address critical issues, such as sustainability, in tourism management courses.

In light of the expanding prominence of work-integrated learning (WIL), the pedagogical model that integrates work experiences into an academic curriculum, this paper presents a systematic review that uncovers little-explored students’ reflections of quality (RoQ).

Drawing on the concept of wayfinding rocks and Bronfenbrenner’s (1979) ecological systems theory, the “students’ RoQ (pronounced [ROK]) WIL model” offers guidance for future research, policy development and educational interventions aimed at optimizing students' experiences of WIL.

This paper highlights RoQ WIL through student voice. The outcomes offer a model, contributing insights for institutions, employers and students involved in WIL experiences.

While the study addresses specific limitations such as the use of specific search terms and potential biases, future research is needed to explore cultural capital’s influence on WIL quality. A focus on broadening the scope of data collection to include a more comprehensive range of student perspectives is needed.

The paper suggests practical implications for institutions, employers and educators in designing WIL programs that prioritize student perspectives, ultimately enhancing the quality of WIL experiences.

By focusing on students' RoQ in WIL, this paper fills a significant gap in the literature and provides a foundation for future research and practice in optimizing WIL engagement and outcomes.