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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.

This study aims to examine the effects of green marketing tools on tourists’ behavioural intention to buy green products by measuring individuals’ subjective norms, attitudes and perceived behavioural control.

A total of 421 international tourists from several tourist attractions in Malaysia, selected through convenience sampling, participated in a survey.

The analysis results using partial least squares structural equation modelling suggest that behavioural intention of international tourists is firmly influenced by attitude, perceived behavioural control, subjective norms and green marketing tools. However, the subjective norm does not work as a mediator.

The relationships established in this study provide insight into hoteliers’ knowledge for further implementation of green marketing strategies (eco-label, eco-brand, environmental advertising), which can enhance green attitudes and behavioural intention of purchasing green products in the hospitality industry.

This study expands the theory of planned behaviour by including green marketing tools to measure international tourists’ green buying tendency in Malaysia.