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Manufacturing companies still struggle to integrate additive manufacturing (AM) technologies with existing traditional manufacturing technologies. This paper explores AM technology integration into a global manufacturing company from an operational capability perspective.

The research was conducted using a single case study in collaboration with a global heavy-duty vehicle manufacturer. Data were collected through a focus group and interviews representing management and engineering roles. Additional data were collected from meetings, company documents, field notes and observations. Subsequently, the collected data were analyzed thematically.

The findings reveal that, despite the company embarking on its AM technology integration journey, it encountered challenges, including cognitive fixation, manufacturing fixation, situational awareness, ambiguous ownership and the make-or-buy dilemma. Furthermore, the findings showed that the company developed operational capabilities – such as developing proficiency in AM know-how, continuous use of AM technology, operational practices for AM technology, cross-collaboration for AM initiatives and business cases for AM technology – to address these challenges. A facilitation model was developed, outlining essential actions prioritized for the short-term, mid-term and long-term. These actions leverage the operational capabilities to address challenges in AM technology integration.

This paper offers an in-depth exploration of AM technology integration in a global heavy-duty vehicle manufacturer. It introduces a novel application of operational capability theory and proposes a facilitation model for managers and academics in pursuit of achieving AM technology integration.

This study aims to investigate the impact of brain drain on government AI readiness in EU member countries, considering the distinctive governance characteristics, macroeconomic conditions and varying levels of ICT specialists.

The research employs a dynamic panel data model using the System Generalized Method of Moments (GMM) to analyze the relationship between brain drain and government AI readiness from 2018 to 2022. The study incorporates various control variables such as GDP per capita growth, government expenditure growth, employed ICT specialists and several governance indicators.

The results indicate that brain drain negatively affects government AI readiness. Additionally, the presence of ICT specialists, robust governance structures and positive macroeconomic indicators such as GDP per capita growth and government expenditure growth positively influence AI readiness.

Major limitations include the focus on a specific region of countries and the relatively short period analyzed. Future research could extend the analysis with more comprehensive datasets and consider additional variables that might influence AI readiness, such as the integration of AI with emerging quantum computing technologies and the impact of governance reforms and international collaborations on AI readiness.

The theoretical value of this study lies in providing a nuanced understanding of how brain drain impacts government AI readiness, emphasizing the critical roles of skilled human capital, effective governance and macroeconomic factors in enhancing AI capabilities, thereby filling a significant gap in the existing literature.

This research fills a significant gap in the existing literature by providing a comprehensive analysis of the interaction between brain drain and government AI readiness. It uses control variables such as ICT specialists, governance structures and macroeconomic factors within the context of the European Union. It offers novel insights for policymakers to enhance AI readiness through targeted interventions addressing brain drain and fostering a supportive environment for AI innovation.

This study aims to investigate the effect of vibration on ceramic tools under dry cutting conditions and find the optimum cutting condition for the hardened steel machining process in a computer numerical control (CNC) lathe machine.

In this research, an integrated fuzzy TOPSIS-based Taguchi L9 optimization model has been applied for the multi-objective optimization (MOO) of the hard-turning responses. Additionally, the effect of vibration on the ceramic tool wear was investigated using Analysis of Variance (ANOVA) and Fast Fourier Transform (FFT).

The optimum cutting conditions for the multi-objective responses were obtained at 98 m/min cutting speed, 0.1 mm/rev feed rate and 0.2 mm depth of cut. According to the ANOVA of the input cutting parameters with respect to response variables, feed rate has the most significant impact (53.79%) on the control of response variables. From the vibration analysis, the feed rate, with a contribution of 34.74%, was shown to be the most significant process parameter influencing excessive vibration and consequent tool wear.

The MOO of response parameters at the optimum cutting parameter settings can significantly improve productivity in the dry turning of hardened steel and control over the input process parameters during machining.

Most studies on optimizing responses in dry hard-turning performed in CNC lathe machines are based on single-objective optimization. Additionally, the effect of vibration on the ceramic tool during MOO of hard-turning has not been studied yet.

This study aims to examine academic staff’s engagement with sustainable development goals (SDGs) in higher education institutions.

The triangulation, convergence model of the mixed methods research design was adopted as the strategy for inquiry. A total of 56 questionnaires and 25 interviews were used to collect the data, and this was buttressed by document review and use of secondary data obtained from Scival.

The results show moderate levels of engagement of academic staff with the SDGs. However, SDGs familiarisation is not correlated with the rate of localisation. The lack of funding deflated political will by university management, demotivated academia and shrinking government support are the leading impediments to SDGs localisation.

The results could be improved by using a larger sample size equally distributed across disciplines. Triangulation of academics’ views with those of students and non-academic staff could have improved the understanding of other dynamics involved in the localisation of SDGs by university teaching staff.

The results point towards the need for a university-based framework that interweaves national, institutional, thematic, structural and personal aspects into the SDGs implementation matrix. The underlying determinants of successful localisation of SDGs by academia need to be addressed through a bottom-up approach.

To the best of the authors’ knowledge, this paper is the first attempt in Zimbabwe to exclusively look at University teaching staff’s engagement with SDGs.

This paper aims to critically discuss the mounting role of social media (SM) or social networking sites (SNSs) on various human resource management (HRM) practices.

The paper is based on 87 published papers collected from the Web of Science Database particularly from 2010 to 2020 (up to June) using VOSviewer software. After reviewing those paper contents, the author briefly highlighted the findings.

According to most of the previous studies, the utilization of SM information for various HRM practices is rising although such utilization is mostly limited to talent search and recruitment & selection at present. Further, it was found that Facebook and LinkedIn are the two most accepted sites among the hiring professionals where the first one mostly provides behavioral information and the second one provides job-related information. Finally, it was revealed that organizations can develop a strong corporate branding through the presence in SM.

This review paper is expected to motivate further research initiatives regarding the role of social media into different HRM practices.

The author expects that based on the findings, the organizational policymakers can get some practical guidelines regarding the efficient utilization of such a platform.

Social media is a powerful platform for flourishing business entities, promoting products, branding, talent search and so many more purposes. An organization can well promote its existence through this popular platform. In particular, the media can be a well-established platform for searching competent employees and creating employer branding. Therefore, more and more research studies should be carried out focusing on this recent issue. This review paper can be a base for the upcoming researchers as it has accumulated the previous literature and their findings.

A direct correlation exists between waste disposal, disease spread and public health. This article systematically reviewed healthcare waste and its implication for public health. This review identified and described the associations and impact of waste disposal on public health.

This paper systematically reviewed the literature on waste disposal and its implications for public health by searching Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA), PubMed, Web of Science, Scopus and ScienceDirect databases. Of a total of 1,583 studies, 59 articles were selected and reviewed.

The review revealed the spread of infectious diseases and environmental degradation as the most typical implications of improper waste disposal to public health. The impact of waste includes infectious diseases such as cholera, Hepatitis B, respiratory problems, food and metal poisoning, skin infections, and bacteremia, and environmental degradation such as land, water, and air pollution, flooding, drainage obstruction, climate change, and harm to marine and wildlife.

Infectious diseases such as cholera, hepatitis B, respiratory problems, food and metal poisoning, skin infections, bacteremia and environmental degradation such as land, water, and air pollution, flooding, drainage obstruction, climate change, and harm to marine and wildlife are some of the public impacts of improper waste disposal.

Healthcare industry waste is a significant waste that can harm the environment and public health if not properly collected, stored, treated, managed and disposed of. There is a need for knowledge and skills applicable to proper healthcare waste disposal and management. Policies must be developed to implement appropriate waste management to prevent public health threats.

This study aims to offer a research overview of circular food waste management, covering key themes and trends. It analyses state-of-the-art research in this field and proposes an agenda to guide future research.

This study outlines bibliometric analysis from a sample of 349 articles with VOSviewer and SciMat software to identify research trend topics.

The findings reveal a substantial amount of interest in this field. The main research topics relate to the recovery processes and valorisation of food waste and its conversion into renewable and cleaner materials or energy sources, towards circularity. However, these processes require consideration of social aspects that facilitate their implementation, which are currently under-researched.

Companies can target their circular food waste management by considering three key aspects. Firstly, the establishment of closer and more sustainable relationships with various stakeholders; Secondly, a regulatory framework and the support of institutions are both required for the correct implementation of circularity. Finally, what is not measured does not exist. It is therefore necessary to establish indicators to measure both the level of development of circularity in waste management and the fulfilment of the established objective.

This bibliometric analysis looks at the application of circularity principles in food waste management from a holistic perspective, considering different areas of knowledge.

This study aims to investigate how sustainability and ethics are being addressed both by the literature and companies. Furthermore, it seeks to identify the specific strategies that these companies use to foster ethical behaviour and promote sustainability in their business operations.

The study entails a bibliometric analysis and a set of case studies from a sample of companies working in different industry sectors. Based on these tools, it analyses whether – and how – enterprises are placing an emphasis on sustainability and ethics as part of their businesses. In addition, the selected companies' unethical practices or socially irresponsible corporate activities were investigated and presented.

The findings suggest that using an ethics perspective can be a valuable tool in improving the accuracy and correctness of business decision-making. In addition, the paper has identified the fact that sustainability standards can be used to improve customer satisfaction as many important issues are addressed. Finally, the paper highlights the importance of ethical considerations when designing and implementing sustainability standards at enterprises and the need for regulatory guidance in this regard.

The paper addresses the need for studies on how sustainability and ethics are being discussed by both the literature and companies. The paper presents some elements that can be used as possible corporate indicators for a wider implementation of sustainability and ethics objectives in enterprises.

This paper presents an experimental investigation in establishing the relationship between FDM process parameters and tensile strength of polycarbonate (PC) samples using the I-Optimal design.

I-optimal design methodology is used to plan the experiments by means of Minitab-17.1 software. Samples are manufactured using Stratsys FDM 400mc and tested as per ISO standards. Additionally, an artificial neural network model was developed and compared to the regression model in order to select an appropriate model for optimisation. Finally, the genetic algorithm (GA) solver is executed for improvement of tensile strength of FDM built PC components.

This study demonstrates that the selected process parameters (raster angle, raster to raster air gap, build orientation about Y axis and the number of contours) had significant effect on tensile strength with raster angle being the most influential factor. Increasing the build orientation about Y axis produced specimens with compact structures that resulted in improved fracture resistance.

The fitted regression model has a p-value less than 0.05 which suggests that the model terms significantly represent the tensile strength of PC samples. Further, from the normal probability plot it was found that the residuals follow a straight line, thus the developed model provides adequate predictions. Furthermore, from the validation runs, a close agreement between the predicted and actual values was seen along the reference line which further supports satisfactory model predictions.

This study successfully investigated the effects of the selected process parameters - raster angle, raster to raster air gap, build orientation about Y axis and the number of contours - on tensile strength of PC samples utilising the I-optimal design and ANOVA. In addition, for prediction of the part strength, regression and ANN models were developed. The selected ANN model was optimised using the GA-solver for determination of optimal parameter settings.

The proposed ANN-GA approach is more appropriate to establish the non-linear relationship between the selected process parameters and tensile strength. Further, the proposed ANN-GA methodology can assist in manufacture of various industrial products with Nylon, polyethylene terephthalate glycol (PETG) and PET as new 3DP materials.

Since the COVID-19 pandemic had a significant impact on all facets of civilisation around the world, including food safety, this study aimed to determine and compare the pre-COVID and post-COVID food safety knowledge of Bangladeshi consumers and their association with sociodemographic variables.

The current study performed a cross-sectional survey of 503 consumers who prepared food at least 2–4 times per week through a validated questionnaire, selected through convenience sampling from two metropolitan cities and two rural districts in Bangladesh. The non-parametric Wilcoxon signed-rank test, Mann–Whitney U tests, Kruskal–Wallis H and binary logistic regression were used for statistical analysis.

Although an increased percentage of consumers showed a better level of overall food safety knowledge in the post-pandemic (38.2%) than the pre-pandemic (28.8%), there is a low level of awareness of the appropriate duration of handwashing, foodborne pathogens, consuming raw milk or eggs, safe storage and temperature control of food. University graduates, families with few children and urban consumers had a good understanding of food safety both pre- and post-pandemic.

This study compares consumers’ pre- and post-COVID-19 food safety knowledge previously unknown in Bangladesh. The findings have significantly contributed to existing food safety knowledge in Bangladesh to adopt policies and structure training programmes for consumers in the country.