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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 investigates the effect of keyword portfolio characteristics on sales in paid search advertising. The authors propose two keyword portfolio characteristics (variety and disparity) and examine the effects of portfolio variety and portfolio disparity on direct and indirect sales in both PC and mobile environment.

By conducting a field study at a large e-commerce platform, the authors use a negative binomial model to develop empirical findings that provide insights into paid search advertising strategies.

For main effect, (1) portfolio variety has a negative effect on direct sales. However, (2) portfolio disparity has positive effects on both direct and indirect sales. Advertising channels influence the contribution of keyword portfolio to sales. (3) On mobile devices, portfolio variety positively affects both direct and indirect sales. However, portfolio disparity negatively affects both direct and indirect sales. (4) On PCs, portfolio variety negatively affects both direct and indirect sales. However, portfolio disparity positively affects both direct and indirect sales on PC.

The findings provide advertisers with insights into how to manage keyword portfolio between mobile devices and PCs.

The current study shifts the attention from keyword to keywords (keyword portfolio), which extends the paid search literature. Moreover, it also contributes to the literature by comparing the relative effectiveness of mobile and PC search advertising.

This paper aims to propose and test a moderated mediation model examining the relationships among ethical work climate, organizational identification, leader-member-exchange (LMX) and organizational citizenship behavior (OCB).

Numerous regression analyses were performed using PROCESS (version 2.13), a macro for SPSS developed by Hayes (2017) to test this moderated mediation model.

The analytical results showed that organizational identification mediates the positive relationship between an ethical work climate and OCB. The analytical results also showed that LMX moderates the direct effect of ethical work climate on organizational identification and that LMX also moderates the indirect effect of ethical work climate on OCB via organizational identification.

This study provides numerous valuable implications for hotels to develop effective strategies to promote employees’ OCB and improve their organizational identification.

This study was the first attempt to propose and test a moderated mediation model that explores the relationships among ethical work climate, organizational identification, leader-member-exchange (LMX) and OCB.

Projecting the population distribution in geographical regions is important for many applications such as launching marketing campaigns or enhancing the public safety in certain densely populated areas. Conventional studies require the collection of people’s trajectory data through offline means, which is limited in terms of cost and data availability. The wide use of online social network (OSN) apps over smartphones has provided the opportunities of devising a lightweight approach of conducting the study using the online data of smartphone apps. This paper aims to reveal the relationship between the online social networks and the offline communities, as well as to project the population distribution by modeling geo-homophily in the online social networks.

In this paper, the authors propose the concept of geo-homophily in OSNs to determine how much the data of an OSN can help project the population distribution in a given division of geographical regions. Specifically, the authors establish a three-layered theoretic framework that first maps the online message diffusion among friends in the OSN to the offline population distribution over a given division of regions via a Dirichlet process and then projects the floating population across the regions.

By experiments over large-scale OSN data sets, the authors show that the proposed prediction models have a high prediction accuracy in characterizing the process of how the population distribution forms and how the floating population changes over time.

This paper tries to project population distribution by modeling geo-homophily in OSNs.

The purpose of this paper is to investigate the heat and mass transport characteristics in microchannel reactors with non-uniform catalyst distributions.

A two-dimensional model is developed to study the heat and mass transport characteristics in microchannel reactors. The heat and mass transport processes in the microchannel reactors with non-uniform catalyst distribution in the catalytic combustion channel are also studied.

The simulated results are compared in terms of the distributions of species mole fraction, temperature and reaction rate for the conventional and new designed reactors. It is found that the chemical reaction, heat and mass transport processes are significantly affected and the maximum temperature in the reactor is also greatly reduced when a non-uniform catalyst distribution is applied in the combustion catalyst layer.

This study can improve the understanding of the transportation characteristics in microchannel reactors with non-uniform catalyst distributions and provide guidance for the design of microchannel reactors.

The design of microchannel reactors with non-uniform catalyst distributions can be used in methane steam reforming to reduce the maximum temperature inside the reactor.

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.

Which venture capital is more beneficial in the product innovation of entrepreneurial ventures? The authors study the drawbacks and different effects of corporate venture capital (CVC) and independent venture capital (IVC) on the effectiveness and efficiency of product innovation in entrepreneurial ventures to answer this question.

This study uses a panel dataset of 502 high-tech ventures and runs the Heckman model to correct potential endogeneity issues.

The authors find that CVC increases the product innovation effectiveness of entrepreneurial ventures, but decreases their efficiency. IVC reduces innovation effectiveness and enhances efficiency. However, CVC performs less positively, while IVC performs more positively in terms of innovation effectiveness and efficiency in the B2B market than in the B2C market.

This study provides insights into how to leverage venture capital to develop new products effectively and efficiently.

This study moves beyond the current understanding of the finance-marketing interface. It delineates the two faces of venture capital and reveals the joint effects of equity stakes and market stakes between different types of venture capital and transaction markets in product innovation.