The way we interact with the physical world around us is being changed rapidly by advances in technology. These new technologies are very helpful for developing smart cities with the goal of improving the quality of life considering sustainability. Technology is also at the core of the circular city vision, and we need to use the new technologies and act in a smarter way in smart cities to support the achievement of economic, environmental, and social targets that are important for sustainable development and circular economy (CE) implementation. The metaverse (which is the combination of the prefix “meta” with the word “universe”) is a new concept that is known as transcending hypothetical synthetic environment linked to the physical world. In this chapter, the proposed concept will be introduced in more detail, and then the authors discuss how smart cities can use the metaverse platforms for improving themselves in five main aspects including governance, environment, mobility, economy, and quality of life dimensions.

Background: This study investigates how firms can enhance the functionality of their circular supply chains (CSCs) by adopting a portfolio of sustainable practices as well as digital technologies to increase performance. It analyzes the benefits that firms can obtain when investing in specific technologies to boost the impact of technologies and sustainable practices on CSCs, and further increase performance. Methods: We test several hypotheses by using structural equation modeling as well as multi-group analysis to verify whether CSCs can be achieved through sustainable practices and technologies and improve the firms’ performance. Results: The empirical results partially support the research hypotheses. While the main research hypotheses are fully supported, the analysis of single digital technologies reveals that only a few solutions can contribute to both the management and the improvement of the CSC. Conclusions: Our findings demonstrate that the identification of green suppliers and ad hoc environmental regulations, combined with attention to the origin and provenance of raw materials, can promote a CSC. Moreover, transportation management systems (TMS) and the internet of things (IoT) are efficient technologies for managing transportation and product flow in the CSC. Furthermore, machine learning (ML) is effective in making positive green decisions, and 3D printing can extend product life.

This paper is an extension of Hsu and Hsu (Int J Ind Eng Comput 3(5):939-948, 2012) aiming to determine the optimal order quantity of product batches that contain defective items with percentage nonconforming following a known probability density function. The orders are subject to 100 % screening process at a rate higher than the demand rate. Shortage is backordered, and defective items in each ordering cycle are stored in a warehouse to be returned to the supplier when a new order is received. Although the retailer does not sell defective items at a lower price and only trades perfect items (to avoid loss), a higher holding cost incurs to store defective items. Using the renewalreward theorem, the optimal order and shortage quantities are determined. Some numerical examples are solved at the end to clarify the applicability of the proposed model and to compare the new policy to an existing one. The results show that the new policy provides better expected profit per time.

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