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Training activities organized by maker-spaces have become the most important channel through which makers acquire new external knowledge related to problem solving and thus contribute significantly to makers' innovation performance. Is it true that the more training activities in which makers participate, the better their innovation performance? Following the logic of process analyses, this paper empirically verifies the effects of the scope and frequency of makers' participation in training activities on their innovation performance.

Based on a survey of 134 makers in China, this paper employed the procedure recommended by Preacher and Hayes (2008) to empirically test the total effects, direct effects and indirect effects of the scope and frequency of participation in training activities on makers' innovation performance via their ability to exploit new knowledge.

The research findings show that the scope (frequency) of participation in training activities has a positive (negative) effect on makers' innovation performance via the mediating effect of the makers' ability to exploit new knowledge. Time pressure acts as a negative moderator.

This paper sheds light on a considerably overlooked research area by investigating the effects of the scope and frequency of makers' participation in training activities on their innovation performance. The authors further identify and empirically test the theoretical mechanism by considering the mediating effect of makers' ability to exploit new knowledge. The research findings also provide a managerial training activity arrangement strategy for makerspaces and government.

Research on makers and innovation has been equivocal regarding whether maker innovation is driven by internal motivation or external incentives. The motivation view favors the intrinsic motives of makers, whereas the incentive view supports external economic incentives. The authors combine both views to explore how innovation tournaments promote the product innovation outcomes of different creative and entrepreneurial makers, using economic incentives (money) or social incentives (love).

The authors interviewed 42 makers and collected a panel dataset of 29,823 makers from the largest digital maker community in China using a Python crawling program. The authors analyzed the data using multiple methods, including cluster analysis, discriminant analysis, factor analysis and negative binomial regression.

Compared with entrepreneurial makers, the product productivity of creative makers is inferior, but their product popularity is greater. The social incentive of innovation tournaments promotes the product productivity and popularity of creative makers compared with that of entrepreneurial makers, but the economic incentive is contradictory. In addition, social and economic incentives interact to generate inconsistent influences.

The study identifies creative and entrepreneurial makers and contributes to user innovation and innovation tournaments by integrating motivation and incentive views.

This research empirically investigates how service employees' ratings of technology readiness (TRI), negative attitudes towards robots (NARS), Big Five personality traits (BFI) and emotional demands (ED) affect their willingness to work with service robots (WTW).

One set of data is collected from 410 service employees expected to work with service robots in Study 1. Another set of field data is collected from 102 employees working with service robots in Study 2. Hierarchical regression is used to test hypotheses about the impact of technology readiness, negative attitudes towards robots and Big Five personality traits on WTW. Additionally, the interactions of emotional demands in the workplace are analysed.

TRI-optimism and TRI-insecurity significantly affect WTW in Study 2 but are nonsignificant in Study 1. The impacts of NARS-emotions in interaction with robots and NARS-interaction with robots situations on WTW are significant in Study 1 but nonsignificant in Study 2. Moreover, BFI-neuroticism negatively affected WTW in Study 1, while these effects were nonsignificant in Study 2. Finally, emotional demands significantly interact with three of eleven dimensions of IVs in Study 1, but all interactions are nonsignificant in Study 2.

This research provides a guiding framework for service companies to screen employees expected to cowork with service robots, to enhance newly hired employees' WTW and to improve existing employees' WTW.

Integrating the characteristics of service employees, service robots and jobs into a theoretical framework, this research is the first to empirically examine the effects of service employees' several critical characteristics (technology readiness, negative attitudes towards robots and Big Five personality) on WTW and the moderation of job characteristics (emotional demands).

This study explores whether and how four main factors of short-branded video content (content matching, information relevance, storytelling and emotionality) facilitate consumer engagement (likes, comments and shares), as well as the moderating effect of the release time (morning, afternoon and evening) in such relationships.

This study uses Python to write programs to crawl relevant data information, such as consumer engagement and short video release time. It combines coding methods to empirically analyze the impact of short-branded video content characteristics on consumer engagement. A total of 10,240 Weibo short videos (total duration: 238.645 h) from 122 well-known brands are utilized as research objects.

Empirical results show that the content characteristics of short videos significantly affected consumer engagement. Furthermore, the release time of videos significantly moderated the relationship between the emotionality of short videos and consumer engagement. Content released in the morning enhanced the positive impact of warmth, excitement and joy on consumer engagement, compared to that released in the afternoon.

The findings provide new insights for the dissemination of products and brand culture through short videos. The authors suggest that enterprises that use brand videos consider content matching, information relevance, storytelling and emotionality in their design.

From a broader perspective, this study constructs a new method for comprehensively evaluating short-branded video content, based on four dimensions (content matching, information relevance, storytelling and emotionality) and explores the value of these dimensions for creating social media marketing success, such as via consumer engagement.

The aerodynamic differences between the head car (HC) and tail car (TC) of a high-speed maglev train are significant, resulting in control difficulties and safety challenges in operation. The arch structure has a significant effect on the improvement of the aerodynamic lift of the HC and TC of the maglev train. Therefore, this study aims to investigate the effect of a streamlined arch structure on the aerodynamic performance of a 600 km/h maglev train.

Three typical streamlined arch structures for maglev trains are selected, i.e. single-arch, double-arch and triple-arch maglev trains. The vortex structure, pressure of train surface, boundary layer, slipstream and aerodynamic forces of the maglev trains with different arch structures are compared by adopting improved delayed detached eddy simulation numerical calculation method. The effects of the arch structures on the aerodynamic performance of the maglev train are analyzed.

The dynamic topological structure of the wake flow shows that a change in arch structure can reduce the vortex size in the wake region; the vortex size with double-arch and triple-arch maglev trains is reduced by 15.9% and 23%, respectively, compared with a single-arch maglev train. The peak slipstream decreases with an increase in arch structures; double-arch and triple-arch maglev trains reduce it by 8.89% and 16.67%, respectively, compared with a single-arch maglev train. The aerodynamic force indicates that arch structures improve the lift imbalance between the HC and TC of a maglev train; double-arch and triple-arch maglev trains improve it by 22.4% and 36.8%, respectively, compared to a single-arch maglev train.

This study compares the effects of a streamlined arch structure on a maglev train and its surrounding flow field. The results of the study provide data support for the design and safe operation of high-speed maglev trains.

Makerspaces, which serve as fertile grounds for makers' innovation activities, are rapidly increasing in emerging markets to help unleash a massive wave of bottom-up innovation and encourage broader participation in entrepreneurial activities. Makers' motivations to innovate are key antecedents of their subsequent innovative behavior. The paper aims to investigate the impact of makers' innovation motivations (both economic and social motivations) on their exploration and exploitation activities in makerspaces and the moderating role of the makerspace climate for innovation.

A survey was conducted for 139 individual makers from five makerspaces in China to test the research hypotheses.

Economic motivation positively affected the degree of exploitative innovation and was negatively related to the degree of exploratory innovation. In contrast, social motivation negatively affected the degree of exploitative innovation and was positively related to the degree of exploratory innovation. The makerspace climate for innovation strengthened the relationship between social motivation and exploratory innovation and exacerbated the negative effect of economic motivation on exploration.

The results offer managers a better understanding of how makers' motivation to participate in makerspaces affects their innovative behavior. Such information can guide makerspaces in designing their incentive policies and recruiting makers in line with their values to amplify makers' creative potential.

The empirical results reveal the impacts of economic and social motivations on makers' exploration and exploitation activities in makerspaces. They thus provide new insights into how different motivations give rise to different innovative behaviors and imply how makers' innovation activities can be managed effectively.

As a common form of failure in industry, corrosion causes huge economic losses. At present, with the development of computational techniques, artificial intelligence (AI) is playing a more and more important role in the field of scientific research. This paper aims to review the application of AI in corrosion protection research.

In this paper, the role of AI in corrosion protection is systematically described in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction.

With efficient and in-depth data processing methods, AI can rapidly advance the research process in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction and save on costs.

This paper summarizes the application of AI in corrosion protection research and provides the basis for corrosion engineers to quickly and comprehensively understand the role of AI and improve production processes.

The highly uncertain and turbulent environments nowadays intensify the paradoxical effects of supply base concentration (SBC) on improving cost efficiency while increasing idiosyncratic risk (IR). Digitalization is regarded as a remedy for this paradox, yet digitization's potentially curative effect has not been empirically tested. Leveraging the lenses of paradox theory and information processing theory (IPT), this study explores how two distinct dimensions of digitalization, i.e. digitalization intensity (DI) and digitalization breadth (DB), reconcile the paradoxical effects of SBC.

Using a panel dataset of 1,238 Chinese manufacturing firms in the period of 2012–2020, this study utilizes fixed-effects regression models to test the proposed hypotheses.

The authors discover that SBC enhances a firm's cost efficiency but induces greater IR. More importantly, there is evidence that DI restrains the amplifying effect of SBC on IR. However, DB weakens the enhancing effect of SBC on cost efficiency and aggravates the SBC's exacerbating effect on IR.

This study advances the understanding of the paradoxical effects of SBC on cost efficiency and IR from a paradox theory perspective. More importantly, to the best of the authors' knowledge, the authors' study is the first to untangle the differential roles of DI and DB in reconciling the paradox of SBC. This study also provides practitioners with nuanced insights into how the practitioners should use appropriate tactics to deploy digital technologies effectively.

Although supply chain collaboration (SCC) theoretically boosts the adoption of supply chain finance (SCF) through information sharing and cost savings, many companies with good supply chain partnerships still hesitate to engage in SCF. To disentangle this puzzle, this study aims to explore how two dimensions of information transparency (i.e. information quantity and information quality) and two types of transaction dependence (i.e. dependence on suppliers and dependence on customers) influence the relationship between SCC and SCF adoption.

This study uses secondary survey data from a Chinese bank, including 464 Chinese companies that have adopted SCF to varying degrees. This study then performs the logistic regression analysis to test the hypotheses.

This study empirically confirms that SCC shows a positive relationship with SCF adoption. More interestingly, information quantity negatively moderates this positive relationship, whereas information quality positively moderates this positive relationship. Most surprisingly, dependence on customers rather than dependence on suppliers strengthens this positive relationship.

This study makes theoretical contributions to the SCF literature by demonstrating the distinct moderating mechanisms regarding the relationship between SCC and SCF adoption. The findings also help companies reexamine their interactions with supply chain members.

This study investigates the impact of supply chain governance (SCG, which includes relational governance and contractual governance) on supply chain resilience (SCR) using the information processing theory. Moreover, the study also examines the mediating role of information processing capability and the moderating role of digital technology (DT) deployment.

A total of 288 questionnaires were collected from the Chinese manufacturing industry, and hierarchical regression was used to empirically test the proposed model.

This study reveals that SCG positively impacts SCR. Moreover, information processing capability plays a mediating role between SCG and SCR. Furthermore, the breadth of DT deployment positively moderates the effect of relational governance on information processing capability, and the depth of DT deployment positively moderates the effects of both relational governance and contractual governance on information processing capability.

This study offers a novel perspective that helps to understand the importance of the supply chain-wide information acquired by SCG in respect of improving SCR. Furthermore, this article extends the application of information processing theory by providing empirical evidence of the mediating role of information processing capability and elucidating the moderating role of DT deployment.