Industrial manufacturing is a core component of a nation’s economic wealth. It is driven by technology, and its paradigm has shifted from craft production to mass production to lean production to mass customisation (MC). We identify how emerging technologies offer a new way to shift MC research focusing on the scientific communities that have been driving MC research, changes in MC throughout the years, and the technological advances that influence future research trends of MC. We then identify MC paradigms. We analyse 1,947 MC papers from 1992 to 2019 and discover the research attention changes from the perspectives of the communities and themes using topic modelling. Our result indicates that MC was explained in terms of the business and marketing strategy (BMS) and the operations management (OM), in accordance with technological development. In BMS, MC topics moved from demand uncertainty to industry transformation. In OM, topics changed from assembly line for product differentiation to additive manufacturing. We discuss the future research agenda according to the technological advances in computer-aided design, additive manufacturing, machine learning, identification technologies, virtual reality, and human–robot collaboration. Not only researchers but practitioners and policymakers can utilise our approach to analyse and formulate MC strategies considering new technologies.

The photovoltaic (PV) generation system has been widely used since the late 1990s. Considering its lifespan of 20 to 30 years, many end-of-life systems will emerge in the near future. This is why recycling PV systems will be beneficial (and may even be detrimental) to both the environment and the economy. Through the recycling process, hazardous by-product substances such as cadmium and lead can be treated properly. Moreover, valuable materials including indium, gallium, and tellurium can be extracted and reused for manufacturing purposes. Even though many studies have dealt with issues related to the PV system and its recycling policy, they lack significant factors regarding the recycling policy. This study analyzes and compares three real cases of manufacturer’s recycling policy, including Deutsche Solar, First Solar, and PV Cycle, from the perspective of a closed-loop supply chain. Two mathematical models are developed to help PV system manufacturers establish supply chain planning and choose suitable recycling policies in consideration of different circumstances. Furthermore, an experimental example of these models will be used to validate and conclude the significance of the models. The results from this study will show that recycling CdTe PV systems is much more efficient than recycling c-Si PV systems and that, in the case of c-Si, it is better to outsource recycling end-of-life systems and dispose of all manufacturing scrap.

Rare metals (RMs) are becoming increasingly important in high-tech industries associated with the Fourth Industrial Revolution, such as the electric vehicle (EV) and 3D printer industries. As the growth of these industries accelerates in the near future, manufacturers will also face greater RM supply risks. For this reason, many countries are putting considerable effort into securing the RM supply. For example, countries including Japan, Korea, and the USA have adopted two major policies: the stockpile system and Extended Producer Responsibility (EPR). Therefore, it is necessary for the manufacturers with RMs to establish a suitable supply chain plan that reflects this situation. In this study, the RM classification matrix is created based on the stockpile and recycling level in Korea. Accordingly, three different types of supply chain are designed in order to develop the closed-loop supply chain (CLSC) planning model of RM, and the CLSC planning models of RM are validated through experimental analysis. The results show that the stockpiling and the EPR recycling obligation increase the amount of recycled flow and reduce the total cost of the part manufacturing, which means that these two factors are significant for obtaining sustainability of the RMs’ CLSC. In addition, the government needs to set an appropriate sharing cost for promoting the manufacturer’s recycling. Also, from the manufacturer’s perspective, it is better to increase the return rate by making a contract with the collectors to guarantee the collection of used products.

This study explores the evolving trends and research issues in the field of drone-assisted multimodal logistics over the past two decades. By employing various text-mining techniques on related research publications, we identify the most frequently investigated topics and research issues within this domain. Specifically, we utilize titles, abstracts, and keywords from the collected studies to perform both Latent Dirichlet Allocation techniques and Term Frequency-Inverse Document Frequency analysis, which help in identifying latent topics and the core research themes within the field. Our analysis focuses on three primary categories of drone-assisted logistics: drone–truck, drone–ship, and drone–robot systems. The study aims to uncover which latent topics have been predominantly emphasized in each category and to highlight the distinct differences in research focuses among them. Our findings reveal specific trends and gaps in the existing literature, providing a clear roadmap for future research directions in drone-assisted multimodal logistics. This targeted analysis not only enhances our understanding of the current state of the field but also identifies critical areas that require further investigation to advance the application of drones in logistics.

Mental health problems are prevalent issues in modern society. While psychological counseling has been a traditional solution, it faces such barriers as negative societal perceptions and limited accessibility. To overcome these, researchers have explored remote counseling via video/voice calls. Despite its advantages of accessibility, convenience, and anonymity, the lack of personal interaction continues to be a drawback. This study investigates the feasibility of using an augmented reality (AR) mask in remote counseling and whether it could increase the level of self-disclosure-which is often used to measure the effectiveness of counseling-while maintaining anonymity. We conducted a controlled experiment and a qualitative user study to assess the effects of AR masks on counselees' level of self-disclosure during remote counseling. The results suggest that AR masks can increase this level more effectively for people with a low disposition for self-disclosure.