3D printing technology is suitable for application in advancing digitization in dentistry. However, the use of this technology in the dental field is not as widespread as expected. The study discusses the barriers to advancing 3D printing technology in dentistry. First, Fuzzy Delphi was used to conduct in-depth interviews with experts to explore what barriers prevent the advancement of 3D printing technology in dentistry. Second, the decision-making and trial assessment laboratory (DEMATEL) was used to identify the cause-and-effect relationship among barriers. Because DEMATEL relies on the expert decision-making system, experts often have different experiences and backgrounds, so judgment results are often uncertain and inconsistent. Therefore, this study proposes using a rough-Z-number to integrate opinions among experts, which can effectively overcome the problems of inconsistency and uncertainty. After analyzing the results, we found that “lack of standard infrastructure” is the most important barrier to the advancement of 3D printing in dentistry, and this study provides improvement strategies based on the results. The results put forward countermeasures for the barriers to the promotion of 3D printing technology in dentistry, which will make the development of dental digitization more effective.

Using green energy is an important way for businesses to achieve their ESG goals and ensure sustainable operations. Currently, however, green energy is not a stable source of power, and this instability poses certain risks to normal business operations and manufacturing processes. The installation of energy storage equipment has become an indispensable accompaniment to facilitating green energy use for an enterprise. However, businesses may encounter significant barriers during the process of installing energy storage equipment. This study aims to explore and discern the key barrier factors that influence the assessment and decision-making process of installing energy storage equipment. A hybrid approach combining the Decision-making and Trial Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) is developed to explore the causality relationships and degrees of influence among these key factors. The Z-number and Rough Dombi Weighted Geometric Averaging (RDWGA) methods are also utilized to integrate the experts’ varied opinions and uncertain judgements. Finally, recommendations are provided based on the results to assist businesses to make informed decisions while evaluating the installation of energy storage equipment, to ensure a stable and uninterrupted supply of green energy for use in normal operations.