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Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the most appropriate AM technology can be challenging. This study aims to propose a method to solve the complex process selection in 3D printing applications, especially by creating a new multicriteria decision-making tool that takes the direct certainty of each comparison to reflect the decision-maker’s desire effectively.

The methodology proposed includes five steps: defining the AM technology selection decision criteria and constraints, extracting available AM parameters from the database, evaluating the selected AM technology parameters based on the proposed decision-making methodology, improving the accuracy of the decision by adopting newly proposed weighting scheme and selecting optimal AM technologies by integrating information gathered from the whole decision-making process.

To demonstrate the feasibility and reliability of the proposed methodology, this case study describes a detailed industrial application in rapid investment casting that applies the weightings to a tailored AM technologies and materials database to determine the most suitable AM process. The results showed that the proposed methodology could solve complicated AM process selection problems at both the design and manufacturing stages.

This research proposes a unique multicriteria decision-making solution, which employs an exclusive weightings calculation algorithm that converts the decision-maker's subjective priority of the involved criteria into comparable values. The proposed framework can reduce decision-maker's comparison duty and potentially reduce errors in the pairwise comparisons used in other decision-making methodologies.

Given the importance of employee psychological well-being to job performance, this study aims to investigate the mediating role of affective commitment between psychological well-being and job performance while considering the moderating role of job insecurity on psychological well-being and affective commitment relationship.

The data were gathered from employees working in cellular companies of Pakistan using paper-and-pencil surveys. A total of 280 responses were received. Hypotheses were tested using structural equation modeling technique and Hayes’s Model 1.

Findings suggest that affective commitment mediates the association between psychological well-being (hedonic and eudaimonic) and employee job performance. In addition, perceived job insecurity buffers the association of psychological well-being (hedonic and eudaimonic) and affective commitment.

The study results suggest that fostering employee psychological well-being may be advantageous for the organization. However, if interventions aimed at ensuring job security are not made, it may result in adverse employee work-related attitudes and behaviors.

The study extends the current literature on employee well-being in two ways. First, by examining psychological well-being in terms of hedonic and eudaimonic well-being with employee work-related attitude and behavior. Second, by highlighting the prominent role played by perceived job insecurity in explaining some of these relationships.