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This study aims to examine various factors influencing the inclination of students toward Green Entrepreneurial Intention (GEI), including University Support (USP), Family Support (FSP), Religiosity (REL), Commitment to Environment (CEN) and Green Entrepreneurial Motivation (GEM), as well as Attitude towards Green Entrepreneurship (AGM).

Data were collected through an online survey of Muslim students at Indonesian Islamic universities. A five-point Likert scale was used in the online questionnaire, with 419 processed data. Partial least squares structural equation modeling was used to analyze the data and test the relationship between the variables.

The results showed that AGM, CEN and REL impacted GEM. AGM was influenced by FSP but not by USP while GEI was significantly influenced by AGM, FSP and USP.

The limitation of the study is the composition of the sample, consisting solely of Islamic university students. Another limitation is the variables used. Future studies should analyze other factors, such as role models, green knowledge or family background.

This study provided fresh perspectives by empirically establishing a framework for assessing GEI, considering REL variables, an unexplored area conceptually. Practically, it helped to advance sustainable entrepreneurship education, particularly in Islamic universities. Accordingly, it provided several practical contributions for universities to develop curricula that better support green entrepreneurship among students.

This study represented the first investigation into the influence of REL on GEI, specifically among university students. Furthermore, Stimuli, Organism and Response theory was used as a foundation for the development of the diverse variables under investigation.

This study aims to explore the factors influencing the evolution of emerging technology innovation network (ETIN) in combination with the key attributes and life cycle of emerging technologies, particularly the impact of multiple knowledge attributes and technology life cycle on the ETIN evolution.

This study collects 5G patent data and their citation information from the Derwent Innovations Index to construct a 5G technology innovation network (5GIN) as a sample network and conducts an empirical analysis of the 5GIN using the temporal exponential random graph model (TERGM).

The results indicate that during the 5GIN evolution, the network scale continues to expand and exhibits increasingly significant core-periphery structure, scale-free characteristic, small-world characteristic and community structure. Furthermore, the findings suggest that the multiple knowledge attributes based on the key attributes of emerging technologies, including knowledge novelty, coherence, growth and impact, have a significant positive influence on the ETIN evolution. Meanwhile, the temporal evolution of ETIN is also found to be correlated with the life cycle of emerging technologies.

This study extends the exploration of emerging technology research from a complex network perspective, providing a more realistic explanatory framework for the factors influencing ETIN evolution. It further highlights the important role that multiple knowledge attributes and the technology life cycle play within this framework.

This paper aims to provide a full introduction, new classification, comparison and investigation of the challenges as well as applications of layerless 3D printing, which is one of the industry 4.0 pioneers.

Given the significance and novelty of uniform 3D printing, more than 250 publications were collected and reviewed in an unbiased and clear manner.

As a result, the majority of uniform parts printed in polymer form are known up to this point. In a novel division for better researchers’ comprehension, uniform printing systems were classified into three categories: oxygen inhibition (OI), liquid lubrication (LL) and photon penetration (PP), and each was thoroughly investigated. Furthermore, these three approaches were evaluated in terms of printing speed, precision and accuracy, manufacturing scale and cost.

The parameters of each approach were compared independently, and then a practical comparison was conducted among these three approaches. Finally, a variety of technologies, opportunities, challenges and advantages of each significant method, as well as a future outlook for layerless rapid prototyping, are presented.