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This paper aims to present an integrated system designed for quality control and inspection in additive manufacturing (AM) technologies.

The study undertakes a comprehensive examination of the process in three distinct stages. First, the quality of the feedstock material is inspected during the preprocessing step. Subsequently, the main research topic of the study is directed toward the 3D printing process itself with real-time monitoring procedures using computer vision methods. Finally, an evaluation of the 3D printed parts is conducted, using measuring methods and mechanical experiments.

The main results of this technical paper are the development and presentation of an integrated solution for quality control and inspection in AM processes.

The proposed solution entails the development of a promising tool for the optimization of the quality in 3D prints based on machine learning algorithms.

Particles bed binding by selective cement activation (SCA) method is a computer-aided manufacturing (CAM) technique used to produce cementitious elements. A computer-aided design file is sliced to generate G-codes before printing. This paper aims to study the effect of key input parameters for slicer software on the final properties of printed products.

The one factor at a time (OFAT) methodology is used to investigate the impact of selected parameters on the final properties of printed specimens, and the causes for the variations in outcomes of each variable are discussed.

Finer aggregates can generate a more compact layer, resulting in a denser product with higher strength. Fluid pressure is directly determined by voxel rate (r_V); however, high pressures enable better fluid penetration control for fortified products; for extreme r_Vs, residual voids in the interfaces between successive layers and single-line primitives impair mechanical strength. It was understood that printhead movement along the orientation of the parts in the powder bed improved the mechanical properties.

The design of experiment (DOE) method assesses the influence of process parameters on various input printing variables at the same time. As the resources are limited, a fractional factorial plan is carried out on a subset of a full factorial design; hence, providing physical interpretation behind changes in each factor is difficult. OFAT aids in analyzing the effect of a change in one factor on output while all other parameters are kept constant. The results assist engineers in properly considering the influence of variable variations for future DOE designs.

This study aims to identify and analyse critical barriers to cloud manufacturing (CM) adoption for achieving sustainability amongst manufacturing micro, small and medium-sized enterprises (MSMEs) in an emerging economy.

Initially, through a literature survey and expert inputs, this study identified and finalized 21 critical barriers to CM adoption, which were further analysed by employing a hybrid multiple criteria decision-making (MCDM) approach. In this approach, the best–worst method (BWM) was used to rank the identified barriers. However, to analyse the interrelation amongst these barriers and classify them into the cause-effect group, the decision-making trial and evaluation laboratory (DEMATEL) method was employed. Furthermore, the study recommended various strategies that can help overcome high-priority barriers and enhance CM adoption within firms.

The results of the study show that organizational, legal and economic barriers are the high-priority barriers that need to be addressed to enhance CM adoption.

The findings of the study will help managers and decision-makers in manufacturing MSMEs develop effective strategies and policies to enhance CM adoption.

Notably, this investigation is one of the preliminary research activities to explore the sustainability aspect of CM adoption amongst MSMEs in an emerging economy.

The number of universities offering Master of Translation and Interpreting (MTI) in China has increased to 316 in 15 years. This paper aims to take a closer look at the production patterns of experimental report theses in terms of total number, distribution across universities, supervision model and research content, reflects on the problems and suggests improvements, provides a reference for MTI education in China and beyond.

This paper presents a bibliometric analysis of the published final theses of experimental reports for the MTI in China between the years 2012 and 2022, the period during which this type of thesis was produced, to identify the production patterns of these theses.

The number of experimental reports published by the nine leading universities accounts for 80% of the total 296 papers. The uneven development is also reflected in the supervision model and research content. Most universities can structure the main content of theses according to the suggestions of the MTI Guidance Training Outline. However, there are still deficiencies in the areas of experimental design, experimental validity, research questions and academic standards.

This paper reflects on the problems of MTI theses of experimental reports. Also, suggestions are made for linking top-level design and university education, for joint progress in faculty development and talent training and for integrating industrial aspects and international visions, to provide a reference for MTI education in China and beyond.

Business schools play a significant role in providing individuals with the ability to adapt to constantly changing environments. Such agile organizations require deans who, as leaders, possess the knowledge and attributes of astute and responsible executives. In this regard, the measurement of the attributes of leadership paves the way for evaluating a leader’s options process. In this study, we measure the attributes of leadership to pave the way for evaluating a leader’s decision-making process.

The rich data included the opinions of 93 university professors from seven countries: Iran, India, China, France, the UK, Canada and the USA. In appraising the responses, the authors considered the nationality and the development level of each participant’s country and continent. In this study, the authors developed an online questionnaire based on the best-worst method (BWM). By performing a one-way analysis of variance (ANOVA), the authors also determined the significant statistical differences of the scientific communities through the lenses of authentic leadership, leader-member exchange and social identity and leadership.

The results provide evidence of transparency, measured as the most important criterion for leading a business school, i.e. knowledgeable deanship. Furthermore, the findings reveal a meaningful difference between developed and developing countries in the context of an authentic leadership pillar.

This paper contributed to the literature in five major ways as follows: The authors investigated the attitudes of scientific communities from different countries, business schools, BWM, dean selection and leadership evaluation.By means of the BWM, the authors measured the criteria culminating in the selection of a knowledgeable leader for a business school.The authors compared and contrasted the attitudes of scientific communities in developing countries vis-à-vis those in developed ones.The authors addressed the differences and similarities among countries in relation to the selection of a knowledgeable business school leader.The authors provided beneficial insights by addressing the different perspectives of researchers on the weights of the criteria involved in the selection procedure for a business school dean.

This study aims to examine the impact of some real variables such as real effective exchange rates, real mortgage rates, real money supply, real construction cost index and housing sales on the real housing prices.

This study uses a nonlinear autoregressive distributed lag (NARDL) model in the monthly period of 2010:1–2021:10.

The real effective exchange rate has a positive and symmetric effect. The decreasing effect of negative changes in real money supply on real housing prices is higher than the increasing effect of positive changes. Only positive changes in the real construction cost index have an increasing and statistically significant effect on real house prices, while only negative changes in housing sales have a small negative sign and a small increasing effect on housing prices. The fact that the positive and negative changes in real mortgage rates are negative and positive, respectively, indicates that both have a reducing effect on real housing prices.

This study suggests the first NARDL model that investigates the asymmetric effects on real housing prices instead of nominal housing prices for Turkey. In addition, the study is the first, to the best of the authors’ knowledge, to examine the effects of the five real variables on real housing prices.

The purpose of this study is to determine the competency characteristics required for the employment of master’s degree students in educational technology.

A combined qualitative and quantitative method was used to consult multiple experts through a modified Delphi method. Competency characteristics were extracted from Chinese recruitment apps, national recruitment websites and university training programs. Ten senior teacher experts who teach educational technology master’s students were consulted through a questionnaire consultation to validate the proposed competency model. The weights of competency characteristics were determined through a combination of the analytic hierarchy process and entropy method.

The results show that when recruiting educational technology master’s students, more emphasis is placed on operational skills. The majority of companies tend to assess practical abilities rather than theoretical knowledge. Relevant knowledge of educational technology, psychology, computer science and education is considered to be the basic knowledge components of educational technology master’s students, while professional skills are the core skills required for their positions. Therefore, universities need to focus on training, educational technology graduate students in these areas of competence. The study also found that professional qualities (such as physical and mental fitness) and personality traits (interpersonal communication and interaction) receive more attention from companies and are essential competencies for educational technology master’s students.

A competence model for educational technology master’s students is proposed, which includes aspects such as knowledge, personal skills/abilities, professional qualities and personality traits. The competence elements included in this model can serve as reference indicators for universities to cultivate the competence of educational technology master’s students, as well as reference points for recruiting units to help them select talents. This represents a new dimension in research related to the employment of educational technology master’s students. The study enriches the research objects and competence dictionary in the field of competence research.

The purpose of this study is to identify the risks that exist in halal meat supply chain activities and to carry out a risk assessment using the fuzzy best-worst method (FBWM) along with mitigating risks using the risk mitigation number (RMN).

The method used is to collect several literature reviews related to the halal meat supply chain, which has information relevant to the risks of the meat industry in Indonesia. Then, a focus group discussion was held with several experts who play a role in the meat industry in Indonesia, and 33 identified risks were identified in halal meat supply chain activities. The proposed methodology uses FBWM and RMN in conducting risk assessment and mitigation in the meat industry in Indonesia.

The analysis reveals that priority risk is obtained by using the global weight value on the FBWM, and then risk mitigation is carried out with RMN. Priority mitigation strategies can mitigate some of the risks to the meat industry in Indonesia. The proposed mitigation strategy is designed to be more effective and efficient in preventing risks that can interfere with product halalness in halal meat supply chain activities in the Indonesian meat industry.

The implications of this study highlight the need for collaboration among stakeholders, improved risk assessment methodologies and the expansion of research into other halal supply chains. By addressing these implications, the halal industry can enhance its integrity, consumer confidence and overall contribution to the global market.

This research provides an integrated approach to identifying, analyzing, assessing and mitigating risks to the meat industry in Indonesia.

The purpose of this paper is to identify and prioritise supply chain finance (SCF) adoption enablers and develop a novel comprehensive framework to select supplier firms based on their SCF adoption capability.

The study deploys a three-phase method to identify and prioritise SCF adoption enablers, followed by developing a model to select suppliers according to their SCF adoption capability. An extensive literature review, followed by a Delphi approach-based expert interview, has been used to finalise the enablers. Using the Best Worst Method and the VIsekriterijumsko KOmpromisno Rangiranje technique, a supplier selection model has been developed in the context of a case company.

The financial health and technological advancement variables received the top priority, followed by collaborative efficiency, whereas the human resources and organisational variables received the slightest significance. A supplier selection framework has also been developed by using the adoption capability of these factors by the supplier partners. In this study’s model, Supplier 4 exhibited better SCF adoption capability and received the top priority.

Manufacturing supply chains in a developing country are the scope of the current study. Extensive future studies are required to derive a global consensus.

The proposed framework of this study can be used to select supplier firms based on their SCF adoption capability. Policymakers can emphasise the most critical enablers of SCF adoption to assist small supplier firms to be a part of the advanced global supply chains.

The current study established a novel comprehensive framework for supplier selection based on the Supply Chain Finance adoption capability of MSME supplier firms.

The COVID-19 pandemic has caused significant disruptions to global supply chains (SCs), affecting the production, distribution, and transportation of goods and services. To mitigate these disruptions, it is essential to identify the barriers that have impeded the seamless operation of SCs. This study identifies these barriers and assesses their impact on supply chain network (SCN).

To determine the relative importance of different barriers and rank the affected industries, a hybrid approach was employed, combining the best-worst method (BWM) and the technique for order preference by similarity to an ideal solution (TOPSIS). To accommodate the inherent uncertainties associated with the pandemic, a triangular fuzzy TOPSIS was used to represent the linguistic variable ratings provided by decision-makers.

The study found that the airlines and hospitality industry was the most affected by the barriers, accounting for 46% of the total, followed by the healthcare industry (23%), the manufacturing industry (19%), and finally the consumer and retail industry (17%).

This study is limited to the four critical industries and nine identified barriers. Other industries and barriers may have different weights and rankings. Nevertheless, the findings offer valuable insights for decision-makers in SC management, aiding them in mitigating the impact of COVID-19 on their operations and enhancing their resilience against future disruptions.

This study enhances understanding of COVID-19’s impact on SCN and provides a framework for assessing disruptions using multi-criteria decision-making processes. The hybrid approach of BWM and TOPSIS in a fuzzy environment is unique and offers potential applicability in various evaluation contexts.