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As a strand in industrialization movement in architecture, engineering and construction (AEC) industry, prefabricated construction (PC) has gained widespread popularity due to high efficiency, energy saving, low environmental impacts, safety and other advantages of PC. Well-managed supply chain can further leverage the advantages of PC. However, there is a lack of more systematically overview of the prefabricated construction supply chain (PCSC). This paper aims to comb the current status and look into the future direction of PCSC by reviewing the existing research.

In total, 131 articles related to prefabricated construction supply chain management (PCSCM) from 2000 to 2022 have been collated to (1) conduct a bibliometric analysis by using VOSviewer, including the literature sources, keywords co-occurrence, co-authorships, authorship citation and country active in the field of PCSCM; (2) classify and summarize the status of research in PCSCM through qualitative discussion and (3) point out the future research directions.

In total, 131 articles are carried out for bibliometric analysis and in-depth qualitative discussion, the visualization maps and the main research themes in the field of PCSCM are obtained. The results show that supply chain intelligentization and informatization are hot topics. Finally, future research directions that should be paid attention to in the field of PCSCM are pointed out.

This study can help project managers understand the current status and problems of PCSC operations and provide a basis for future management decisions.

Compared with previous studies, this study adds the dimension of “article authorship” to the quantitative analysis and discusses the research themes in the field of PCSCM in a comprehensive manner. In addition, this paper deeply discusses the main research topics from both the specific contents and research methods adopted.

By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order decoupling point (CODP) positioning based on the mass customization service mode to provide customers with more diversified and personalized service content with lower total logistics service cost.

This paper addresses the general process of service composition optimization based on the mass customization mode in a cloud logistics service environment and constructs a joint decision model for service provider selection and CODP positioning. In the model, the two objective functions of minimum service cost and most satisfactory delivery time are considered, and the Pareto optimal solution of the model is obtained via the NSGA-II algorithm. Then, a numerical case is used to verify the superiority of the service composition scheme based on the mass customization mode over the general scheme and to verify the significant impact of the scale effect coefficient on the optimal CODP location.

(1) Under the cloud logistics mode, the implementation of the logistics service mode based on mass customization can not only reduce the total cost of logistics services by means of the scale effect of massive orders on the cloud platform but also make more efficient use of a large number of logistics service providers gathered on the cloud platform to provide customers with more customized and diversified service content. (2) The scale effect coefficient directly affects the total cost of logistics services and significantly affects the location of the CODP. Therefore, before implementing the mass customization logistics service mode, the most reasonable clustering of orders on the cloud logistics platform is very important for the follow-up service combination.

The originality of this paper includes two aspects. One is to introduce the mass customization mode in the cloud logistics service environment for the first time and summarize the operation process of implementing the mass customization mode in the cloud logistics environment. Second, in order to solve the joint decision optimization model of provider selection and CODP positioning, this paper designs a method for solving a mixed-integer nonlinear programming model using a multi-layer coding genetic algorithm.

Secret consumption refers to consumption of a product in a private situation, with the intent or behavior of hiding the consumption from others. This study contributes to the secret consumption literature by identifying the antecedents of secret consumption along with the explaining mechanism and boundary condition.

An online study with experiment design was conducted to examine the impact of extroversion/introversion, self-presentation and product scarcity on secrete consumption.

The results show that consumer extraverted disposition and the self-presentation motive negatively influence secret consumption intention and suggest this relationship is explained by the self-presentation need. The findings also revealed that perceived product scarcity attenuated the negative impact of extraversion and self-presentation on secret consumption intention.

The findings provide interesting insights into advertising and retailing. In recognizing that secret consumption is a prevalent phenomenon in consumer behavior that may improve actual consumer product evaluation and preference, retailers or brand managers may encourage consumers to consume secretly.

This empirical study is a first attempt to explore the antecedents, mediating mechanism and boundary condition of consumer intention to engage in secrete consumption. The findings of the study provide important implication to theoretical development and managerial applications in advertising and retailing.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

This study is aimed at making an inspection of the effects of collaborative innovation network characteristics on firm innovation performance, and the intermediary roles of knowledge transfer efficiency is taken into account.

This study used a convenient sampling method to obtain population and samples. Using data obtained by publishing online and paper questionnaires, and using on-site interviews in Anhui Province in the Yangtze River Delta region of China, descriptive analysis, regression analysis and correlation analysis are utilized to study the direct influence of collaborative innovation network characteristics on knowledge transfer efficiency as well as firm innovation performance, and the intermediary roles of knowledge transfer efficiency on firm innovation performance, respectively. In this study, 3,000 questionnaires were distributed to the employees of enterprises engaged in research and development (R&D) activities, of which 2,560 were valid. With the help of SPSS24.0 software, the reliability and validity of the questionnaire was analyzed.

The results are indicative of that network centrality and relationship strength positively affect knowledge transfer efficiency and firm innovation performance. Nevertheless, network scale has no significant correlation with knowledge transfer efficiency and enterprise innovation performance. In addition, knowledge transfer efficiency is an intermediary between collaborative innovation network characteristics and enterprise innovation performance, and positively affects enterprise innovation performance, which demonstrated that managers should take advantage of collaborative innovation network characteristics to elevate knowledge transfer efficiency because well-realized transferals of knowledge can help accelerate the coordination of resources in knowledge, and finally bring about the advancement of firm's innovation abilities and performance.

There are few previous studies that fully examined the relationships among collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. This paper developed previous researches on the relationships between collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. The mediation of knowledge transfer efficiency on the relationship between collaborative innovation network characteristics and firm innovation performance is analyzed. Further, studies on collaborative innovation network characteristics using data obtained from employees engaged in R&D activities are very limited in the literature. On account of that, the findings in this study may make sense to the innovation ability of innovative enterprise and expand the literature in the field of enterprise strategic management and knowledge management.

This analysis shows that collaborative innovation network characteristics have both positive and negative effects on firm innovation performance. Therefore, business managers should pay attention to their position in the collaborative innovation network and maintain the relationship strength with other innovation subjects. Special consideration should be given to the knowledge transfer of innovative enterprises, so as to improve firm innovation performance practically.

The study may provide additional understandings for researchers, government managers, universities and enterprises with regard to strategic management from the visual angle of innovation ecosystems. It is instrumental in the exploration of the mechanisms enabling firm innovation performance.

Industrial Revolution 4.0 (IR 4.0) has caused revolutionary changes in various industries of South Asia, including financial services. Financial inclusion has been recognized as an important driver of economic growth. The combination of financial inclusion and the industrial revolution offers exceptional opportunities for business. The present chapter delves into the significance of financial inclusion within the framework of IR 4.0 in Asia and its potential to stimulate growth, innovation, and societal influence. It includes the discourse regarding challenges and opportunities for business in a new era of financial inclusion and the industrial revolution. Based on a thorough discussion, we give practical insights and best practices for businesses aiming to maximize the opportunities offered by financial inclusion in the era of IR 4.0. This chapter provides an in-depth understanding of Asia’s expanding financial inclusion landscape and empowers companies with the information and tools needed to prosper in this dynamic market.

Purpose: This study aims to identify communication speech acts and transaction terms in online stores (Olshop) during live streaming on Facebook amid the COVID-19 pandemic and to understand communication patterns between sellers and buyers when shopping on Facebook live streaming in Indonesia.

The Need for Research: This research is motivated by the skill gap arising from increasing buying and selling transactions through live streaming on Facebook. Cultural and demographic shifts, along with the widespread availability of modern technologies and marketing 2.0 have resulted in the global population adopting social media at rates far beyond our use of the Internet, making a compelling case by example and analogy that social media has the potential to level the playing field and is effective in reaching their target market.

Methodology: The type of research is descriptive-qualitative using corpus data instruments. The data collection technique in this study was carried out by reading and observing the data and listening to speeches about buying and selling women’s equipment from various online stores on Facebook. Then select and sort the data designated as forms, strategies, and functions of speech acts in buying and selling transactions during live streaming on Facebook. The data analysis technique has three steps: (1) reducing the amount of data; (2) presenting the data; and (3) concluding.

Findings: The results show that there are four types of speech acts between sellers and buyers in the live-streaming online shop on Facebook, namely, assertive, directive, expressive, and commissive speech acts.

Rotating machinery is a crucial component of large equipment, and detecting faults in it accurately is critical for reliable operation. Although fault diagnosis methods based on deep learning have been significantly developed, the existing methods model spatial and temporal features separately and then weigh them, resulting in the decoupling of spatiotemporal features.

The authors propose a spatiotemporal long short-term memory (ST-LSTM) method for fault diagnosis of rotating machinery. The authors collected vibration signals from real rolling bearing and gearing test rigs for verification.

Through these two experiments, the authors demonstrate that machine learning methods still have advantages on small-scale data sets, but our proposed method exhibits a significant advantage due to the simultaneous modeling of the time domain and space domain. These results indicate the potential of the interactive spatiotemporal modeling method for fault diagnosis of rotating machinery.

The authors propose a ST-LSTM method for fault diagnosis of rotating machinery. The authors collected vibration signals from real rolling bearing and gearing test rigs for verification.

The combination of an Engineered Cementitious Composite (ECC) layer and steel plate to reinforce RC beams (ESRB) is a new strengthening method. The ESRB was proposed based on the steel plate at the bottom of RC beams, aiming to solve the problem of over-reinforced RC beams and improve the bearing capacity of RC beams without affecting their ductility.

In this paper, the finite element model of ESRB was established by ABAQUS. The results were compared with the experimental results of ESRB in previous studies and the reliability of the finite element model was verified. On this basis, parameters such as the width of the steel plate, thickness of the ECC layer, damage degree of the original beam and cross-sectional area of longitudinal tensile rebar were analyzed by the verified finite element model. Based on the load–deflection curve of ESRB, ESRB was discussed in terms of ultimate bearing capacity and ductility.

The results demonstrate that when the width of the steel plate increases, the ultimate load of ESRB increases to 133.22 kN by 11.58% as well as the ductility index increases to 2.39. With the increase of the damage degree of the original beam, the ultimate load of ESRB decreases by 23.7%–91.09 kN and the ductility index decreases to 1.90. With the enhancement of the cross-sectional area of longitudinal tensile rebar, the ultimate bearing capacity of ESRB increases to 126.75 kN by 6.2% and the ductility index elevates to 2.30. Finally, a calculation model for predicting the flexural capacity of ESRB is proposed. The calculated results of the model are in line with the experimental results.

Based on the comparative analysis of the test results and numerical simulation results of 11 test beams, this investigation verified the accuracy and reliability of the finite element simulation from the aspects of load–deflection curve, characteristic load and failure mode. Furthermore, based on load–deflection curve, the effects of steel plate width, ECC layer thickness, damage degree of the original beam and cross-sectional area of longitudinal tensile rebar on the ultimate bearing capacity and ductility of ESRB were discussed. Finally, a simplified method was put forward to further verify the effectiveness of ESRB through analytical calculation.