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Prefabricated construction is an innovative technique for decreasing carbon emissions in the construction industry. However, as the investors of housing projects, a majority of developers are unwilling to adopt prefabricated housing in practice. To promote prefabricated housing, this study aims to develop an integrated framework of fuzzy-decision making trial and evaluation laboratory (fuzzy-DEMATEL) and system dynamics (SD) to understand the underlying influencing mechanism of developers' willingness.

Through literature review, a total of 17 influencing factors were identified. Then, the interrelationships among the factors were evaluated by 10 experienced professionals, and the impacts given and received by each factor were further analyzed through fuzzy-DEMATEL. Based on the technology acceptance model (TAM), a SD model was developed to explore the influencing mechanism.

The major cause factors were identified, including mandatory implementation policies, economic incentive policies, environmental protection policies, component standardization and developers' economic strength. This group of factors was expected to be given priority attention in the case of limited resources. On the other hand, the results indicated that economic incentive policies and mandatory implementation policies could affect the developers' willingness via perceived usefulness, while the others mainly influenced perceived ease of use.

Little research has focused on the interrelationships among the influencing factors of developers' willingness to adopt prefabricated housing. This study contributed to understanding the mechanism of developers' willingness from a systematic view and providing the priority of influencing factors. Several strategies were proposed to improve the practical implementation of prefabricated housing development.

Because mobile phones offer a new, affordable and easy-to-use portal to reading material, mobile reading is emerging as the most ultra-modern reading approach. From the perspective of mobile reading service providers, knowledge of customer purchase, and consumption behaviour is critical for their survival and success. This paper aims to provide insights into the factors that influence the purchase e-books.

Following means-end chain theory, the prospect theory and elaboration likelihood model, a structural equation model is proposed to investigate and identify key factors that drive the purchase intention of experienced mobile readers. In the theoretical model, utilitarian value (UV) and hedonic value (HV) are supposed as formative second-order constructs formed by related payoff.

Both UV and HV are positively associated with readers’ purchase intention. However, there are no big differences between these two path coefficients. People seem to perceive relatively low payment risk although perceived risk could still negatively affect purchase intention. As a predictor of purchase intention, UV is less important when risk perception increases or when involvement (IV) decreases. Furthermore, this study illustrates that uniqueness and convenience (CV) are significant components of UV, whereas curiosity and flow are components of HV.

Mobile reading providers should highlight the professional and specificity of app such as beautiful cover, page setup that similar to real books and so on. Readers should be allowed to post real-time reviews and communicate with others to improve their sense of satisfaction, participation and belonging. The payment process should be concise and simple through which readers can save their purchase time and effort. Mobile reading service providers should provide trustworthy payment approaches, especially third-party platform and guarantee the CV and safety of payment activity.

By focusing on the impacts of relationships among UV, HV, perceived risk and IV to purchase intention, this paper not only provides a theoretical understanding of mobile reading purchase behaviour but also offers practical insights to reading material manufactures and app developers for promoting such a process.

This study aims to explore the gap between research and practice on supply chain risks due to COVID-19 by exploring the changes in global emphasis on supply chain risk research.

This work designed a research framework to compare the research of supply chain risks before and during the COVID-19 pandemic based on machining learning and text clustering and using the relevant publications of the web of science database.

The results show that scholars' attention to supply chain crisis has increased in the wake of the COVID-19 outbreak, but there are differences among countries. The United Kingdom, India, Australia, the USA and Italy have greatly increased their emphasis on risk research, while the supply chain risk research growth rate in other countries, including China, has been lower than the global level. Compared with the pre-pandemic period, the research of business finance, telecommunications, agricultural economics policy, business and public environmental occupational health increased significantly during the pandemic. The hotspots of supply chain risk research have changed significantly during the pandemic, focusing on routing problem, organizational performance, food supply chain, dual-channel supply chain, resilient supplier selection, medical service and machine learning.

This study has limitations in using a single database.

This work compared the changes in global and various countries' supply chain risk research before and during the pandemic. On the one hand, it helps to judge the degree of response of scholars to the global supply chain risk brought about by COVID-19. On the other hand, it is beneficial for supply chain practitioners and policymakers to gain an in-depth understanding of the relationship between the COVID-19 pandemic and supply chain risk, which might provide insights into not only addressing the supply chain risk but also the recovery of the supply chain.

The initial exploration of the changing extent of supply chain risk research in the context of COVID-19 provided in this paper is a unique and earlier attempt that extends the findings of the existing literature. Secondly, this research provides a feasible analysis strategy for supply chain risk research, which provides a direction and paradigm for exploring more effective supply chain research to meet the challenges of COVID-19.

The aim of this study is to undertake a systematic analysis of the supply chain literature to uncover the changes and patterns of international cooperation in the context of the COVID-19 pandemic.

In this study, the information on supply chain-related publications in the Web of Science (WOS) database is analyzed using statistical techniques and visual approaches. The focus is on the five countries with the highest number of supply chain publications, accounting for approximately 70% of global publications. This in-depth analysis aims to provide a clearer understanding of the cooperation patterns and their impact on the supply chain during the COVID-19 pandemic.

The results of the study reveal that the growth rate of international cooperation in supply chain research during the COVID-19 pandemic is higher compared to the 5-year and 10-year periods before the pandemic. This suggests that the pandemic has not hindered international cooperation in the field, but instead has increased collaboration. In terms of international cooperation patterns, the findings indicate that China and the USA have a strong partnership, with China being the largest partner for the USA and vice versa. The UK's largest partner is China, India's largest partner is the UK and Italy's largest partner is also the UK. This implies that trade, rather than the pandemic, is a determining factor in supply chain research.

This study examines the patterns of international cooperation in supply chain research during the COVID-19 pandemic, providing insights into the changes and mechanisms of international cooperation in this field. Moreover, the results of this study may offer practical benefits for supply chain operators and managers. By providing a deeper understanding of the international cooperation patterns in the field, this research could contribute to the recovery and growth of the global supply chain.

This study's analysis of the impact of crisis events, such as the COVID-19 pandemic, on international cooperation in supply chain research contributes to the theoretical development of the field. Additionally, by examining how academia responds to emergencies, it provides valuable insights for operations and supply chain managers in their pursuit of more effective supply chain management.

This study provides a preliminary examination of the international cooperation patterns of supply chain research in the context of the COVID-19 pandemic, representing a novel and early contribution to the existing literature, helping to expand upon current understanding in the field and provide a more comprehensive perspective. Furthermore, this study offers a practical analysis strategy for future supply chain research, fostering progress and growth in the field.

The purpose of this paper is to propose an improved proportional topology optimization (IPTO) algorithm for tackling the stress-constrained minimum volume optimization problem, which can meet the requirements that are to get rid of the problems of numerical derivation and sensitivity calculation involved in the process of obtaining sensitivity information and overcome the drawbacks of the original proportional topology optimization (PTO) algorithm.

The IPTO algorithm is designed by using the new target material volume update scheme and the new density variable update scheme and by introducing the improved density filter (considering the weighting function based on the Gaussian distribution) and Heaviside-type projection operator on the basis of the PTO algorithm. The effectiveness of the IPTO algorithm is demonstrated by solving the stress-constrained minimum volume optimization problems for two numerical examples and being compared with the PTO algorithm.

The results of this paper show that the uses of the proposed strategies contribute to improving the optimized results and the performance (such as the ability to obtain accurate solutions, robustness and convergence speed) of the IPTO algorithm. Compared with the PTO algorithm, the IPTO algorithm has the advantages of fast convergence speed, enhancing the ability to obtain accurate solutions and improving the optimized results.

This paper achieved the author’s intended purpose and provided a new idea for solving the stress-constrained optimization problem under the premise of avoiding obtaining sensitivity information.

This research widens the scope of the use of postponement by addressing how the generic supply chain structure and information sharing/relationship among supply chain actors affects the postponement decision, based on empirical data of Chinese manufacturers in the Pearl River Delta.

Case analysis, cross‐case comparisons, semi‐structured interviews.

A cross‐case analysis including study of the downstream structure, downstream relationship, upstream structure, upstream relationship, production method and inventory position produced a postponement classification into five categories: balanced structure without customer information; customer dominated; manufacturer dominated; balanced structure with loose suppliers, and finally virtual supply chain. Based on this classification, two propositions are postulated: when a supply chain has a balanced structure, it should use speculation or production postponement. When the supply chain has an unbalanced structure, it should use purchasing postponement or product development postponement.

This study is exploratory in nature, and more empirical data is needed to further validate the postulated results. Another limitation of the study is in its measurement of postponement, measured in this instance by the production method and inventory positions used. Other characteristics of postponement may be included in future research.

This research has extended the scope of the use of postponement by addressing how the generic supply chain structure and information sharing/relationship among supply chain actors affects the postponement decision.

Addresses postponement on the level of the supply chain, rather than company‐level. Addresses how the supply chain structure (balanced/unbalanced) and information sharing/relationship among supply chain actors affect the postponement decision.