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The positive correlation between students’ internship and employability is well documented. However, there is no consensus on its relationship with academic performance. Previous studies investigated the Bachelor level: in the UK, the so-called sandwich placement is positively correlated; in the US, the results are mixed. This study aims to expand the scientific literature and focuses on Politecnico di Torino, Italy: the cases of the Industrial and Management Engineering Bachelor (BA) and Master of Science (MS) degree programs are examined.

The academic performance of 2,279 BA students and 2,560 MS students graduated between 2016 and 2021 is examined. Ordinary least square models are employed to test the relationship between grades and internship, controlling for ex ante academic scores, gender, age and geographical origin.

The results show a small robust negative correlation between internship and grades, especially at the bachelor level, where potentially a self-selection occurs. At the master level, the negative relationship is significant but very small and might be partially determined by the marks of the exams substituting the internship.

This study contributes to the empirical research on the relationship between students’ grade and internship and suggests the presence of complementarities in several ways: the Italian context, characterized by an optional internship is examined, both at the BA and MS level. Universities that intend to organize internship as overlapping with lectures and exams should be cautious, especially when considering the BA level students, whose maturity and skills are less developed than MS ones.

The purpose of this article is to prepare graphene/polyimide composite materials for use as bearing cage materials, improving the friction and wear performance of bearing cages.

The oil absorption and discharge tests were conducted to evaluate the oil content properties of the materials, while the mechanical properties were analyzed through cross-sectional morphology examination. Investigation into the tribological behavior and wear mechanisms encompassed characterization and analysis of wear trace morphology in PPI-based materials. Consequently, the influence of varied graphene nanoplatelets (GN) concentrations on the oil content, mechanical and tribological properties of PPI-based materials was elucidated.

The composites exhibit excellent oil-containing properties due to the increased porosity of PPI-GN composites. The robust formation of covalent bonds between GN and PPI amplifies the adhesive potency of the PPI-GN composites, thereby inducing a substantial enhancement in impact strength. Notably, the PPI-GN composites showed enhanced lubrication properties compared to PPI, which was particularly evident at a GN content of 0.5 Wt.%, as evidenced by the minimization of the average coefficient of friction and the width of the abrasion marks.

This paper includes implications for elucidating the wear mechanism of the polyimide composites under frictional wear conditions and then to guide the optimization of oil content and tribological properties of polyimide bearing cage materials.

In this paper, homogeneously dispersed PPI-GN composites were effectively synthesized by introducing GN into a polyimide matrix through in situ polymerization, and the lubrication mechanism of the PPI composites was compared with that of the PPI-GN composites to illustrate the composites’ superiority.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0415

We articulate cycles of creative storying and data analysis and the wonder that motivated the project by detailing our reading, thinking and writing processes to contribute to the conceptual and practical literature on collaborative writing as method.

This paper documents a process of collaborative writing as method that produced a co-written fictional narrative that evokes questions about schooling.

Our process began with world-building for our fictional future, creating characters to serve as a lens for analysis. From our discussions of the data, we crafted a plotline to present our themes in coherent story. As we explored and shared our readings, interdisciplinarity shaped our project in unique ways.

Throughout, our collaboration and fiction-writing opened spaces for wonder, interdisciplinarity and joy that may inspire other researchers to engage in collaborative and/or creative writing processes.

Adding to the rich literature of arts-based research methods, we contribute our reflections on the pragmatics of incorporating reading, writing and thinking for collaboration and creative writing as qualitative research methods for document analysis.

The present chapter discusses evolution, definitions, dimensions, capabilities, and the present state of the art of digital supply chain management (DSCM). The objective of the chapter is to offer a detailed understanding of DSCM, by shedding light on its historical development, exploring its multipronged definitions, and highlighting its core dimensions and capabilities in the contemporary business landscape. The evolution of DSCM appears as a central theme, rooted in the background of industrial revolutions. It starts by relooking at the First Industrial Revolution (IR) with its mechanization and steam power, progresses through the Second IR with electrification and mass production, and arrives at the Third IR, characterized by the rise of computers and the internet. The pivoting transition into the Fourth IR, also called Industry 4.0, marks the start of DSCM with its fusion of digital technologies (DTs) in the supply chain (SC) processes. Analysis of key definitions of DSCMs unveils their role as an enabler of SC collaboration, customer-centric nature, having overarching reliance on DTs. Moreover, the chapter explores the core dimensions of DSCM, exposing its ability to improve SC resilience, sustainability, visibility, efficiency, and agility. These capabilities stem from seamlessly woven DT developments into SC: artificial intelligence (AI), machine learning, the Internet of Things (IoT), and advanced analytics. The chapter concludes by highlighting the present state of the art in DSCM, reflecting its indispensable role in the contemporary turbulent business dynamics. In short, this chapter offers a synthesized view of DSCM's definitions, dimensions, evolution, capabilities, and present status within the larger context of supply chain management (SCM) literature.

This paper aims to investigate how and when visual referents in brand visual aesthetics (i.e. colours, shapes, patterns and materials) serve as design applications that enable consumer diasporic identity.

This paper uses an innovative methodology that triangulates 58 in-depth interviews with diasporic consumers, 9 interviews with brand managers and designers and a visual analysis of brands (food retailer, spices and nuts, skincare, hair and cosmetics, ice cream and wine) to provide a view of the phenomenon from multiple perspectives.

This study illustrates how and when particular applications and compositions of product and design referents support diasporic identity for Middle Eastern consumers living outside the Middle East. Specifically, it illustrates how the design applications of harmonising (applying separate ancestral homeland and culture of living product and design referents simultaneously), homaging (departing from the culture of living product and design referents with a subtle tribute to ancestral homeland culture) and heritaging (departing from the ancestral homeland culture product and design referents with slight updates to a culture of living style) can enable diasporic identity in particular social situations.

Although applied to the Middle Eastern diaspora, this research opens up interesting avenues for future research that assesses diasporic consumers’ responses to brands seeking to use visual design to engage with this market. Moreover, future research should explore these design applications in relation to issues of cultural appreciation and appropriation.

The hybrid design compositions identified in this study can provide brand managers with practical tools for navigating the design process when targeting a diasporic segment. The design applications and their consequences are discussed while visually demonstrating how they can be crafted.

While previous research mainly focused on how consumption from the ancestral homeland occurred, to the best of the authors’ knowledge, this study is the first to examine how hybrid design compositions that combine a diaspora’s ancestral homeland culture and their culture of living simultaneously and to varying degrees resonate with diasporic consumers.

The literature on communication in change processes, although fundamental, appears to still be very fragmented. The purpose of this study is to provide an explanatory and integrated framework for the communication process in organizational change processes.

The authors conducted 22 semi-structured interviews with employees from 21 companies and 13 different sectors in Germany. The four-step Gioia inductive coding approach was adopted as the methodological approach of the current study.

A final research model reveals that the organizational change communication (OCC) process is marked by specific change-restraining forces associated with the fear of the unknown, habits and convenience. Results also suggest the importance of communication timing and factors that help shape the OCC process, namely the scope, contents and channels of the communication process. Finally, the current research highlights contextual variables of the OCC process, such as credibility or the level of honesty.

The importance of OCC, in particular the understanding of the scope, contents of the message and the channels of communication adopted in the change management process, are important variables in the complexity of change. The paper illustrates the intricacy of communication in change and reinforces the internal and external variables that help shape the OCC process, with implications for change agents and scholars.

A significant number of criminal and deviant acts are investigated by nonpolice actors. These include private investigators who charge fees for their services, professional services firms such as firms of accountants who also charge fees, in-house investigators employed by private organisations and in-house investigators of public sector organisations who are not sworn police officers. Some of these investigators, such as private investigators, have been exposed in unethical activities such as illegal surveillance and blagging to name some. In this respect, this study aims to uncover the ethical orientations of investigators using cluster analysis.

This study is based upon an online survey of private investigators predominantly in the UK, i.e. investigators beyond the public police. An innovate statistical inferential analysis was used to investigate the sample which resulted in the development of three ethical orientations of such investigators.

Based upon a survey response from 331 of these types of investigators this study illustrates the extent they engage in unethical activities, showing a very small minority of largely private investigators who engage in such activities.

A unique feature of this study is the use of an innovative statistical approach using an unsupervised machine learning model, namely, TwoStep cluster analysis, to successfully group and classify respondents based on their ethical orientation. The model derived three types of ethical orientation: ethical, inbetweeners and risk takers.

The stress concentration factor (SCF) is commonly utilized to assess the fatigue life of a tubular T-joint in offshore structures. Parametric equations derived from experimental testing and finite element analysis (FEA) are utilized to estimate the SCF efficiently. The mathematical equations provide the SCF at the crown and saddle of tubular T-joints for various load scenarios. Offshore structures are subjected to a wide range of stresses from all directions, and the hotspot stress might occur anywhere along the brace. It is critical to incorporate stress distribution since using the single-point SCF equation can lead to inaccurate hotspot stress and fatigue life estimates. As far as we know, there are no equations available to determine the SCF around the axis of the brace.

A mathematical model based on the training weights and biases of artificial neural networks (ANNs) is presented to predict SCF. 625 FEA simulations were conducted to obtain SCF data to train the ANN.

Using real data, this ANN was used to create mathematical formulas for determining the SCF. The equations can calculate the SCF with a percentage error of less than 6%.

Engineers in practice can use the equations to compute the hotspot stress precisely and rapidly, thereby minimizing risks linked to fatigue failure of offshore structures and assuring their longevity and reliability. Our research contributes to enhancing the safety and reliability of offshore structures by facilitating more precise assessments of stress distribution.

Precisely determining the SCF for the fatigue life of offshore structures reduces the potential hazards associated with fatigue failure, thereby guaranteeing their longevity and reliability. The present study offers a systematic approach for using FEA and ANN to calculate the stress distribution along the weld toe and the SCF in T-joints since ANNs are better at approximating complex phenomena than standard data fitting techniques. Once a database of parametric equations is available, it can be used to rapidly approximate the SCF, unlike experimentation, which is costly and FEA, which is time consuming.

This study aimed to evaluate the potential of artificial intelligence (AI) as a tool for knowledge synthesis, the production of written content and the delivery of coaching conversations.

The research employed the use of experts to evaluate the outputs from ChatGPT's AI tool in blind tests to review the accuracy and value of outcomes for written content and for coaching conversations.

The results from these tasks indicate that there is a significant gap between comparative search tools such as Google Scholar, specialist online discovery tools (EBSCO and PsycNet) and GPT-4's performance. GPT-4 lacks the accuracy and detail which can be found through other tools, although the material produced has strong face validity. It argues organisations, academic institutions and training providers should put in place policies regarding the use of such tools, and professional bodies should amend ethical codes of practice to reduce the risks of false claims being used in published work.

This is the first research paper to evaluate the current potential of generative AI tools for research, knowledge curation and coaching conversations.

This article aims to investigate the status of and the trends in the intertwining of crowdfunding and innovation literature by identifying, evaluating and synthesizing the findings from previous research. This paper provides a bibliometric meta-analysis of the already substantial and growing literature on innovation and crowdfunding research.

Using a bibliometric approach, this research scrutinizes all articles that include terms related to “crowdfunding” and “innovation” (in their title, abstract or keywords) in Elsevier’s Scopus database. VosViewer and Bibliometrix package in R have been used to analyse 150 articles.

The results suggest that there are three main research clusters in the innovation and crowdfunding literature. The first cluster highlights the role of crowdfunding in fostering radical and incremental innovation. The second cluster focuses on the concept of openness and its effect on innovation in crowdfunding campaigns, while the third cluster explains the role of platforms’ innovation in crowdfunding success.

Taking a holistic perspective, this contribution advances new knowledge on the intertwining of crowdfunding and innovation research fields. It implies that crowdfunding is facilitating the flow of knowledge between different stakeholders, including project initiators and crowd investors, among others, as they all benefit from open innovation platforms.