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A fundamental problem for intelligent manufacturing is to equip the agents with the ability to automatically make judgments and decisions. This paper aims to introduce the basic principle for intelligent crowds in an attempt to show that crowd wisdom could help in making accurate judgments and proper decisions. This further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.

Efforts to support the critical role of crowd wisdom in intelligent manufacturing involve theoretical explanation, including a discussion of several prevailing concepts, such as consumer-to-business (C2B), crowdfunding and an interpretation of the contemporary Big Data mania. In addition, an empirical study with three business cases was conducted to prove the conclusion that our ideas could well explain the current business phenomena and guide the future of manufacturing.

This paper shows that crowd wisdom could help make accurate judgments and proper decisions. It further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.

The paper highlights the importance of crowd wisdom in manufacturing with sufficient theoretical and empirical analysis, potentially providing a guideline for future industry.

Live streaming commerce, a new form of social commerce where firms integrate with broadcasters, community members and customers in live chat rooms for real-time interaction to help sell products, has become increasingly popular. However, factors that impact the success of live streaming commerce are not fully explored. The purpose of this study is to examine these factors by exploring the relationships among customer trust (i.e., trust in broadcasters, community members, and products) and customer engagement, and the mediating role of swift guanxi.

The authors surveyed 422 customers who have watched Taobao Live, one of the largest live streaming commerce sites in China, and used their questionnaires to test the research model employing partial least squares modeling.

The authors’ results indicate that trust in broadcasters has a positive effect on trust in products and community members, which positively influences trust in products. Additionally, swift guanxi has a fully mediating effect on the relationship between customers' trust in broadcasters and customer engagement.

First, from the theoretical perspective, this study comprehensively identifies three types of trust, explores the transfer relationships among trust in broadcasters, community members, and products based on Trust Transfer Theory. In addition, this study examines the mediating influence of swift guanxi on the relationship between customer trust and engagement. Second, from the managerial perspective, the study provides insights to help broadcasters and practitioners use live streaming to facilitate shopping.

This study aims to investigate the effect of post-treatment on anti-corrosion performance of Al coating on the surface of Ti-6Al-4V (TC4) fastener.

The Al coatings with different layer structures were prepared on TC4 by middle-frequency and direct-current combined magnetron sputtering. The cross-sectional morphology and surface roughness of coatings were characterized by scanning electron microscope and atomic force microscope. The corrosion resistance was evaluated by electrochemical method. The monolayer coating was post-treated by Alodine chemical conversion, Ar⁺ bombardment and a combination of two methods above.

The results show that the interfaces in bilayer and trilayer coatings reduce the defects. Ar⁺ bombardment reduces the corrosion current density, and Alodine chemical conversion leads to a higher pitting corrosion potential. The combined post-treatment has the highest polarization resistance.

The corrosion resistance of the Al coating is enhanced as the layer quantity increases. The combination of two post-treatments, Ar⁺ bombardment and Alodine chemical conversion, could achieve an overall improvement in corrosion resistance of Al coating.

This study/paper aims to understand the public perceptions of AI through mass media discourse. In the past few years, significant progress has been made in the field of artificial intelligence (AI). The benefits of AI are obvious, but there is still huge uncertainty and controversy over the public perception of AI. How does the mass media conceptualize AI?

In this paper, the authors analyze the evolution of AI covered by five major news media outlets in the past 30 years from 7 dimensions: scientific subject, keyword, country, institution, people, topic and opinion polarity.

First of all, different subjects are competing for and dividing up the right to speak of AI, leading to the gradual fragmentation of the concept of AI. Second, reporting on AI often includes reference to commercial institutions and scientists, showing a successful integration of science and business. Moreover, the result of topic modeling shows that news media mainly defines AI from three perspectives: an imagination, a commercial product and a field of scientific research. Finally, negative reports have focused on various issues relating to AI ethics.

The results can help bridge various conversations surrounding AI and promote richer discussions, increase the participation of scientists, businesses, governments and the public and provide more perspectives on the functions, prospects and pitfalls of AI.

This paper considers the brand awareness and anchor influence on consumers' live-streaming purchases, and explores the existence of “free-riding” behavior, the comparison of brand promotion effect and active live-streaming effect and the optimal strategic combination between the brand and the anchor. The authors investigate the evolutionary stabilization strategies of the bounded rational brand and anchor, and explore the conditions for the realization of the optimal strategy. Management suggestions for the development of live streaming commerce can be provided in this paper.

Two significant models are used in this paper. The Stackelberg model is used to study the “free-riding” behavior, the comparison of brand promotion effect and active live-streaming effect and the optimal strategic combination between the brand and the anchor. Using evolutionary game theory to get the evolutionary stable equilibrium strategies and analyze the binary equilibrium strategy of the bounded rational brand and anchor. In addition, relevant simulation analysis is conducted using realistic data to verify the conclusions and for further analysis, making the conclusions of the paper have realistic significance.

The study shows that “free-riding” behavior exists and the positive effect of brand promotion is greater than that of active live-streaming. The brand and the anchor take active actions as the optimal strategy. As the sensitivity coefficient of consumers to live-streaming effort and the sensitivity coefficient of consumers to brand promotion change, various evolutionary stabilization strategies will appear. When the two sensitivity coefficients are below a certain threshold, the game sides will reach the optimal strategic combination to obtain the maximum benefits. When they rise above this threshold, it is counterproductive instead. The system achieves the optimal strategic combination when the difference factor between effort cost and promotion cost must be higher than a certain value, but when it takes the smallest possible value, the game sides tend to take active actions. This study can provide management suggestions for the sustainable development of the live-streaming model.

This paper shows that under certain conditions, the brand and the anchor can evolve into the optimal strategy to maximize the profits of both parties, which has certain practical significance for the prosperous development of live streaming commerce. In future research, the authors will consider the regulatory role of the government and construct a more realistic game model to provide constructive suggestions for the sustainable prosperity of live streaming commerce. Meanwhile, there are also games between multiple brands and multiple anchors, as well as games among brands-anchors-the live streaming platforms, and the authors will conduct more in-depth research in the future.

So far, the co-impact of anchor influence and brand awareness has not been considered simultaneously in published articles. This paper provides theoretical guidance for the behavioral choices of the brand and the anchor under the live streaming commerce, which is conducive to the prosperous development of live streaming commerce.

Based on the JD-R model and process-focused HRM perspective, this research paper aims to investigate the processes underlying the relationship between AI-enabled HR analytics and employee well-being outcomes (resilience) that received less attention in the AI-driven HRM literature. Specifically, this study aims to examine the indirect effect between AI-enabled HR analytics and employee resilience via job crafting, moderated by HRM system strength to highlight the contextual stimulus of AI-enabled HR analytics.

The authors adopted a time-lagged research design (one-month interval) to test the proposed hypotheses. The authors used two-wave surveys to collect data from 175 full-time hotel employees in China.

The findings indicated that employees' perceptions of AI-enabled HR analytics enhance their resilience. This study also found the mediation role of job crafting in the mentioned relationship. Moreover, the positive effects of AI-enabled HR analytics on employee resilience amplify in the presence of a strong HRM system.

Organizations that aim to utilize AI-enabled HR analytics to achieve organizational missions should also dedicate attention to its associated employee well-being outcomes.

This study enriched the literature with regard to AI-driven HRM in that it identifies the mediating role of job crafting and the moderating role of HRM system strength in the relationship between AI-enabled HR analytics and employee resilience.

This paper reviews the pros and cons of different parametric modeling methods, which can provide a theoretical reference for parametric reconstruction of 3D human body models for virtual fitting.

In this study, we briefly analyze the mainstream datasets of models of the human body used in the area to provide a foundation for parametric methods of such reconstruction. We then analyze and compare parametric methods of reconstruction based on their use of the following forms of input data: point cloud data, image contours, sizes of features and points representing the joints. Finally, we summarize the advantages and problems of each method as well as the current challenges to the use of parametric modeling in virtual fitting and the opportunities provided by it.

Considering the aspects of integrity and accurate of representations of the shape and posture of the body, and the efficiency of the calculation of the requisite parameters, the reconstruction method of human body by integrating orthogonal image contour morphological features, multifeature size constraints and joint point positioning can better represent human body shape, posture and personalized feature size and has higher research value.

This article obtains a research thinking for reconstructing a 3D model for virtual fitting that is based on three kinds of data, which is helpful for establishing personalized and high-precision human body models.

E-commerce live streaming (ELS) has become a new and important shopping channel. Although previous studies have provided insightful findings on how to engage consumers in ELS, limited effort has been made to explore the role of factors of live streaming rooms. Based on the literature on space perception and the retail environment, this study aims to develop a theoretical model to examine how perceived distance and perceived depth affect consumers' affective and cognitive perceptions and then further impact product attitude in ELS.

This study collected 414 valid survey responses to test the proposed research model. Survey data were analyzed using partial least squares (PLS)-structural equation modeling. The PLS Multi-Group analysis (PLS-MGA) was used to test the consistency of the research model across different product types and watching durations.

The results suggest that environmental factors of a live streaming room (i.e. perceived distance and perceived depth) can impact consumers' attitudes toward the product in the live streaming via both cognitive and affective routes. These effects keep consistent across different product types and watching durations.

The paper focuses on the environmental perspective, which is unexplored in previous literature on ELS. It highlights the importance of the space design of live streaming rooms.

This paper aims to determine the demand category and level of government and investors in public–private partnership (PPP) projects. It emphasizes the importance of meeting the demands of stakeholders and controlling the unreasonable demands. This study aims to improve the demand management of stakeholders in the PPP project and lay a foundation for the research on behavior based on the motivation theory.

This paper opted for a questionnaire survey to collect data based on indicators identified through literature. The participants come from the government and private sector (investors, contractors, operators, etc.) in China PPP Lecture Hall. The reliability, validity and variance analyses are used to test the reliability of data. Factor analysis and entropy method are used to determine demand categories and weights.

The government’s 14 demands are divided into four groups: satisfy public activities, self-interest, responsibility and relief financial pressure; 6 investor's demands are divided into development ability and satisfy social activities. The self-interest of government is higher than that of the publicity in PPP projects; investor's social reputation is most important, it is a foundation for obtaining external resources and achieving enterprise development.

Because of the chosen research approach, the demand indexes cannot be exhausted. Therefore, researchers are encouraged to enrich relevant contents further.

This paper includes implications for a targeted demand control mechanism and for managing the unreasonable demand.

This paper comprehensively identifies the demand hierarchy of the government and investors, and provides the theoretical basis for the target management of stakeholders.

Although the importance and variety of emotions have been emphasized in existing literature, studies on discrete emotions remain limited. This study aims to propose a method for more precise recognition and calculation of emotions in massive amounts of online data on attraction visitor experiences and behaviour, by using discrete emotion theory.

Using HowNet’s word similarity calculation technique, this study integrated multiple generic dictionaries, including the sentiment vocabulary ontology database of the Dalian University of Technology, the National Taiwan University Sentiment Dictionary and the Boson Dictionary. Word2vec algorithm filters emotion words unique to hospitality and tourism in 1,596,398 texts from Sogou News, Wikipedia and Ctrip reviews about attractions, and 1,765,691 reviews about attractions in China.

The discrete sentiment dictionary developed in this study outperformed the original dictionary in identifying and calculating emotions, with a total vocabulary extension of 12.07%, demonstrating its applicability to tourism.

The developed new dictionary can be used by researchers and managers alike to quickly and accurately evaluate products and services based on online visitor reviews.

To the best of the authors’ knowledge, this study is the first to construct a sentiment dictionary based on discrete emotion theory applicable to hospitality and tourism in the Chinese context. This study extended the applicability of affective psychology to hospitality and tourism using discrete emotion theory. Moreover, the study offers a methodological framework for developing a domain-specific sentiment dictionary, potentially applicable to other domains in hospitality.