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The purpose of this study is to improve the magnetron quality in Company T by identifying the nonconforming defect, adjusting the factors affecting the leakage of the magnetron tube core, and determining the optimal parameter values of these factors.

A case study method is used to present the quality improvement of magnetron tube core. The define, measure, analyze, improve, and control framework is applied in the case study as well as several Six Sigma tools.

The results show that Ag–W thickness, Ag–W installation state and furnace entry interval are significant factors on the leakage of magnetron tube core, and the optimum settings for these factors are 0.055 mm, offset by 1 mm from the outer edge and 5 cm, respectively.

The main limitation of this study is that it was carried out on a small number of production processes. The authors would like to analyze more case studies on the improvements of after-sales quality and supplier quality.

This research could be used in magnetron manufacturing process as a tool for managers and engineers to improve product quality, which can also be extended to similar manufacturing systems.

In this case study, the Six Sigma approach has been applied for the first time to solve magnetron manufacturing problems by improving the quality of magnetron production process. It can help the quality engineers be more familiar with the deployment of Six Sigma and effective tools.

The purpose of this systematic literature review (SLR) is to examine the theoretical landscape of knowledge hiding (KH) research, identifies prevailing theories, the different ways KH is understood within these theories and the underlying assumptions that shape these views. Based on this, ideas for further research are derived to advance the theoretical basis of KH studies.

Using a theory-based SLR, the authors analysed 170 scientific papers from Scopus and Web of Science. This involved thematic analysis to categorise theories frequently applied in KH research and a detailed examination to link core assumptions to these theoretical perspectives.

The analysis revealed a reliance on 86 distinct theories, with a notable emphasis on social exchange theory and conservation of resources theory. KH is predominantly conceptualised as a negative, objective, reactive and relational behaviour rooted in social reciprocity and resource conservation. The review uncovers the multifaceted nature of KH, challenging the field to incorporate broader theoretical views that encompass positive aspects, subjective experiences, strategic intentions and non-relational determinants of KH.

To the best of the authors’ knowledge, this is the first study to systematically map and analyse the theoretical underpinnings of KH research. It offers a unique contribution by categorising the diverse theories applied in KH studies and explicitly linking these theories to their inherent assumptions about KH. This approach provides a comprehensive overview that not only identifies gaps in the current research landscape but also proposes alternative theoretical perspectives for exploring KH, thereby setting a new direction for future studies in this field.

Three-dimensional (3D) food printing is an innovative technology used to customize food products through the integration of digital technology and food ingredients. The purpose of this study is to assess the current state of research in the field of 3D food printing, identify trending topics and identify promising future research directions.

This bibliometric review systematically evaluates the field of 3D food printing using data from published literature in the Web of Science database. After reference screening, 812 articles were included in the analysis.

The result reveals that research in 3D food printing primarily focuses on the optimization and characterization of mechanical and rheological properties of food inks and that post-printing processing, such as laser treatment, has emerged recently as an important consideration in 3D food printing. However, extant works lack animal and human studies that demonstrate the functionality of 3D-printed food.

This sophisticated bibliometric analysis uncovered the most studied current research topics and the leading figures in the area of 3D food printing, providing promising future research directions.

Bullying knowledge hiding has been recently identified as a manifestation of knowledge hiding behavior. As a relatively new concept, it is still underexplored. Previous research has focused on the antecedents of bullying hiding. However, there is a lack of research on the negative consequences that bullying hiding may have on employees. This study aims to uncover the effects of supervisor bullying hiding on employees knowledge behavior. The study also aims to examine the moderating effect of power values and the mediating effect of job stress.

Data were gathered in two waves from 444 employees with higher education in Poland. Data collection was conducted in July and August 2022. A general linear model mediation analysis with jamovi Advanced Mediation Models software was used to examine the hypotheses.

The results indicate that bullying knowledge hiding by supervisors triggers subordinates’ job stress and aggression in the form of bullying knowledge hiding toward co-workers. Contrary to expectations, job stress does not mediate the relationship between supervisor bullying hiding and subordinate bullying hiding toward co-workers. Power-dominance values, contrary to power-resources values, moderate the above relationship.

As bullying hiding has significant potential to spread among organizational members, managers seeking to reduce it should check the personal values of job applicants and employees.

Based on the behavioral contagion and frustration–aggression–displacement theories, to the best of the author’s knowledge, this study is the first to investigate the relationships between supervisor bullying hiding, job stress, power values and subordinate bullying hiding toward co-workers.

This paper aims to investigate the impact of relationship quality among team members in the project team on knowledge transfer effectiveness and analyze the role of organizational structure in the influencing process.

The hypotheses are verified by the Structural Equation Modeling (SEM) analysis using Smart PLS 3 software with the data collected from 236 questionnaire samples in Chinese construction industry.

The results indicate that relationship quality has a direct impact on knowledge transfer in project teams and centralization has a negative impact on relationship quality. Moreover, relationship quality plays a mediating role between centralization and knowledge transfer effectiveness and formalization plays a negative moderating role in the effect of relationship quality on knowledge transfer effectiveness.

This paper studies intra-project knowledge transfer from the perspective of relationship quality of project teams and explores the antecedent and moderating role of organizational structure in the influence of relationship quality on knowledge transfer.

Companies should enhance their market position and competitiveness by improving staff effectiveness, skills, resource commitment, and applying relevant managerial methods. This study aims to examine the impact of knowledge management (KM) and total quality management (TQM) on employee effectiveness (EE) and supply chain performance (SCP) in emerging economies.

The used methodology consists on conducting a survey within Tunisian companies, where the authors gathered 206 responses. Collected data was analyzed using statistical package for the social sciences (SPSS) software, enabling the authors to establish a conceptual model. This model was further examined through structural equation modeling, using analysis of moment structures (AMOS) software for hypothesis validation. Additionally, the authors’ research aimed to enhance SCP and boost EE while minimizing costs through a nonlinear mathematical model and the quality function deployment method.

The results indicate that TQM and KM positively impact EE, and KM and EE positively impact SCP. However, the significance of employee performance on SCP varies depending on company location and industry sector studied.

This work emphasized the involvement of small- and medium-sized enterprise managers from emerging economies in the studied concepts and confirmed the effects of KM and TQM practices on EE and SCP.

A risk-based method is proposed to identify the dominant influencing factors of secondary lining cracking in an operating mountain tunnel with weak surrounding rock.

Based on the inspection data from a mountain tunnel in Southwest China, a lognormal proportional hazard model is established to describe the statistical distribution of secondary lining cracks. Then, the model parameters are obtained by using the Bayesian regression method, and the importance of influencing factors can be sorted based on the absolute values of the parameters.

The results show that the order of importance of the influencing factors of secondary lining cracks is as follows: location of the crack on the tunnel profile, rock mass grade of the surrounding rock, time to completion of the secondary lining, and void behind the secondary lining. Accordingly, the location of the crack on the tunnel profile and rock mass grade of the surrounding rock are the two most important influencing factors of secondary lining cracks in the investigated mountain tunnel, and appropriate maintenance measures should be focused on these two aspects.

This study provides a general and effective reference for identifying the dominant influencing factors of secondary lining cracks to guide the targeted maintenance in mountain tunnels.

This study aims to use geographical information on social media for public opinion risk identification during a crisis.

This study constructs a double-layer network that associates the online public opinion with geographical information. In the double-layer network, Gaussian process regression is used to train the prediction model for geographical locations. Second, cross-space information flow is described using local government data availability and regional internet development indicators. Finally, the structural characteristics and information flow of the double-layer network are explored to capture public opinion risks in a fine-grained manner. This study used the early stages of the COVID-19 outbreak for validation analyses, and it collected more than 90,000 pieces of public opinion data from microblogs.

In the early stages of the COVID-19 outbreak, the double-layer network exhibited a radiating state, and the information dissemination was more dependent on the nodes with higher in-degree. Moreover, the double-layer network structure showed geographical differences. The risk contagion was more significant in areas where information flow was prominent, but the influence of nodes was reduced.

Public opinion risk identification that incorporates geographical scenarios contributes to enhanced situational awareness. This study not only effectively extends geographical information on social media, but also provides valuable insights for accurately responding to public opinion.

Additive manufacturing (AM) is a layer-by-layer technique that helps to create physical objects from a three-dimensional data set. Fused deposition modeling is a widely used material extrusion (MEX)-based AM technique that melts thermoplastic filaments and selectively deposits them over a build platform. Despite its simplicity and affordability, it suffers from various printing defects, with partial warping being a prevalent issue. Warpage is a physical deformation caused by thermal strain incompatibility that results in the bending of the printed part away from the build platform. This study aims to investigate the warpage characteristics of printed parts based on geometrical parameters and build orientations to reduce the warpage extent.

Cuboidal samples of thermoplastic acrylonitrile butadiene styrene ranging from 5 to 80 mm were printed using a commercial MEX system. A Taguchi method-based design of experiment trial was performed to optimize the placement and orientation of the part for minimal warpage.

It was found that a lower value of the “in-plane” aspect ratio and a more prominent part thickness are favorable for minimal warpage. The part should always be placed near the region with the highest temperature (least thermal gradient) to minimize the warpage.

A novel dimensionless parameter (Y) is proposed that should be set to a minimum value to achieve minimal warpage. The results of this study can help improve the design and part placement for the MEX technique, thus elevating the print quality.

This study employs bibliometric analysis to map the research landscape of social media trending topics during the COVID-19 pandemic. The authors aim to offer a comprehensive review of the predominant research organisations and countries, key themes and favoured research methodologies pertinent to this subject.

The authors extracted data on social media trending topics from the Web of Science Core Collection database, spanning from 2009 to 2022. A total of 1,504 publications were subjected to bibliometric analysis, utilising the VOSviewer tool. The study analytical process encompassed co-occurrence, co-authorship, citation analysis, field mapping, bibliographic coupling and co-citation analysis.

Interest in social media research, particularly on trending topics during the COVID-19 pandemic, remains high despite signs of the pandemic stabilising globally. The study predominantly addresses misinformation and public health communication, with notable focus on interactions between governments and the public. Recent studies have concentrated on analysing Twitter user data through text mining, sentiment analysis and topic modelling. The authors also identify key leading organisations, countries and journals that are central to this research area.

Diverging from the narrow focus of previous literature reviews on social media, which are often confined to particular fields or sectors, this study offers a broad view of social media's role, emphasising trending topics. The authors demonstrate a significant link between social media trends and public events, such as the COVID-19 pandemic. The paper discusses research priorities that emerged during the pandemic and outlines potential methodologies for future studies, advocating for a greater emphasis on qualitative approaches.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2023-0194.