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Employee turnover expenses can cost businesses more than 100 per cent of a single employee’s annual wages and negatively affection an organization’s production and profits. High employee turnover also could affect community tax collections, social programs and physical and mental health issues. Therefore, understanding contributors to higher employee turnover remains essential for organizational managers from both a corporate and societal standpoint. This paper aims to provide an analysis of how job satisfaction and job embeddedness could predict employee turnover intent.

A randomly selected survey which consisted of Andrews and Withey’s (1976) job satisfaction questionnaire, a global job embeddedness scale (Crossley et al., 2007) and a three-item turnover intent questionnaire derived from a survey created by Mobley et al. (1978) using a Likert-type measurement to survey randomly selected individuals used within manufacturing plants located in the Southeastern USA.

The results of the multiple regression analysis showed a significant relationship between job satisfaction, job embeddedness and turnover intent; and that satisfied and committed employees are less likely to plan to leave their employment.

Limited current information is available on how job satisfaction and job embeddedness predict turnover intentions in US Southeast manufacturing. This study includes information that shows the importance of job satisfaction and job embeddedness on retaining employees in this region and industry. Given the importance of employee retention on corporate productivity, morale and profits along with the ability to improve the organization’s positive contribution to society, it is important for managers to understand these factors and their effect on employee turnover intent.

The purpose of this paper is to review possibilities of implementing ceramic additive manufacturing (AM) into electronic device production, which can enable great new possibilities.

A short introduction into additive techniques is included, as well as primary characterization of structuring capabilities, dielectric performance and applicability in the electronic manufacturing process.

Ceramic stereolithography (SLA) is suitable for microchannel manufacturing, even using a relatively inexpensive system. This method is suitable for implementation into the electronic manufacturing process; however, a search for better materials is desired, especially for improved dielectric parameters, lowered sintering temperature and decreased porosity.

Relatively inexpensive ceramic SLA, which is now available, could make ceramic electronics, currently restricted to specific applications, more available.

Ceramic AM is in the beginning phase of implementation in electronic technology, and only a few reports are currently available, the most significant of which is mentioned in this paper.

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 paper aims to explore if firms located in industrial districts (IDs) have different adoption paths concerning Industry 4.0 technologies and get different results with respect to other similar firms located outside IDs.

The study is based on a quantitative analysis related to an original data set of 206 Italian manufacturing firms specializing in made in Italy industries and adopting Industry 4.0 technologies. A case study of a district firm is also presented to explain the rationale of investment strategies and results obtained.

The analysis shows that there are differences between district and non-district firms when Industry 4.0 technology investments are concerned (higher investment rate in big data/cloud and augmented reality for district firms than non-district ones). In contrast to a breakthrough view of the fourth industrial revolution, the study suggests that 4.0 technologies emphasize the peculiarities and competitiveness factors typical of the district model in terms of customization and flexibility. There are differences in the motivations of adoption (product diversification for district firms vs productivity enhancement for non-district firms) and in the results achieved.

The paper is one of the first attempts to empirically explore the technological innovation paths related to Industry 4.0 within IDs, therefore, contributing to the debate on the possible evolution of the district model

The purpose of this paper is to analyse the production cycle of glazed porcelain stoneware, from the extraction of raw materials to the packaging of the finished product, with the aim of verifying the effects of integrating an environmental impact assessment into the decision-making process for managing the life cycle, to make it economically and ecologically sustainable, in a holistic approach along the supply-chain.

The research is performed using the life cycle assessment and life cycle costing methodologies, to identify environmental impacts and costs, that occur during extraction of raw materials, transportation, ceramic tiles production, material handling, distribution and end-of-life stages within a cradle to grave perspective.

Through the use of a comprehensive analysis of the environmental impact assessment and related externalities, three possible strategic options to improve the environmental performance and costs of ceramic tile production were formulated, leveraging sustainability as a competitive advantage.

This exploratory research opens future lines of investigation, the first of which is to confirm the technological feasibility and market responsiveness to the three strategic solutions hypothesised thanks to the use of an innovative eco-design technique.

The research has allowed testing and validating the tools of environmental impact assessment (life cycle assessment) and economic impact assessment (life cycle costing as structured methodologies in a life cycle management framework, to help companies implement competitive strategies based on sustainability.

The manufacturing industry is one of the most disrupted systems as a result of the global spread of the Covid-19 pandemic. Manufacturing firms are looking for strategies and policies to deal with the situation while also meeting customer demands. This study aims to discuss and analyze the barriers that have impacted manufacturing systems during this period.

The barriers and performance measures were extracted from the extant literature and further discussed with academic and industry experts. Based on the response of experts, a list of ten barriers and five performance measures were selected for further analysis. The interpretive ranking process (IRP) is applied to analyze the inter-relationship among the barriers with respect to performance variables. The cross-interaction matrices and the dominance profile are created to prioritize the barriers. Based on dominance value, an IRP-based manufacturing barrier evaluation model is developed for validation.

The impact of the pandemic on the manufacturing industry is analyzed through the list of barriers and a structured ranking model is proposed. The research findings of the study indicate that “Financial constraints” is the most influential barrier to manufacturing due to the outbreak of Covid-19, followed by “Government imposed restrictions” and “Setbacks in logistics services.”

The ranking of barriers and developed interpretive ranking process model would be helpful for practitioners and policymakers to formulate strategies for manufacturing organizations to deal with the pandemic situation. The finding can be beneficial as it promotes similar studies in other sectors.

This study contributes to the manufacturing sector by developing a contextual relationship among the set of identified barriers against various performance measures. As per the author's knowledge, this is the first study that provides a relationship and ranking of manufacturing barriers due to the outbreak of Covid-19.