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The reviews submitted by users are the foundation of user-generated content (UGC) platforms. However, the rapid growth of users brings the problems of information overload and spotty content, which makes it necessary for UGC platforms to screen out reviews that are really helpful to users. The authors put forward in this paper the factors influencing review helpfulness voting from the perspective of review characteristics and reviewer characteristics.

This study uses 8,953 reviews from 20 movies listed on Douban.com with variables focusing on review characteristics and reviewer characteristics that affect review helpfulness. To verify the six hypotheses proposed in the study, Stata 14 was used to perform tobit regression.

Findings show that review helpfulness is significantly influenced by the length, valence, timeliness and deviation rating of the reviews. The results also underlie that a review submitted by a reviewer who has more followers and experience is more affected by review characteristics.

Previous literature has discussed the factors that affect the helpfulness of reviews; however, the authors have established a new model that explores more comprehensive review characteristics and the moderating effect reviewer characteristics have on helpfulness. In this empirical research, the authors selected a UGC community in China as the research object. The UGC community may encourage users to write more helpful reviews by highlighting the characteristics of users. Users in return can use this to establish his/her image in the community. Future research can explore more variables related to users.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2020-0186.

The purpose of this paper is to study the ablative behavior of the silicone resin-coated carbon fabric (coated fabric) that will swell significantly during ablation.

The ablation experiments of three coated fabrics were conducted by quartz lamp radiant. Based on the experimental analysis, a numerical model was proposed for the coated fabrics to study the ablative process in term of the energy balance, mass conservation and thermal decomposition equations.

Results showed that the average relative errors between the simulated temperatures and experimental values of back surfaces of coated fabric 1, 2 and 3 were 10.01, 7.53 and 7.32%, respectively. The average density of silicone resin of coated fabric 1 was reduced by 47.96%, and the closer the distance from the heated surface was, the more the density decreased. The thermal conductivity and specific heat capacity of silicone resin of coated fabric 1 increased with time. Before 50 s, each decomposition rate curve showed an inflection point, at which the silicone resin decomposed most intensely.

Based on experimental observations, the ablative behavior of the material with fixed expansion layer was simulated. In the further research, the moving expansion layer could be considered.

This paper provides the theoretical basis to evaluate the effectiveness of thermal protection materials that will swell during ablation.

In crises such as the coronavirus disease 2019 (COVID-19) pandemic, governments need to act in time to lead citizens toward rational reactions and disclose information effectively to the public. This paper aims to understand the content published by the government and identify how citizen engagement relates to content type and emotional valence.

The grounded theory approach was adopted and nine types of content posted by the government were observed. The data were obtained from “People's Daily”, an official Sina Weibo account representing the voice of the Chinese government, from January 3 to June 22 in 2020.

The analysis shows that information related to emotional support and social mobilization were the most reposted, while those mentioning immoral and illegal incidents were the most liked and commented. Also, it was found that positive posts tend to attract more likes, yet with fewer reposts than neutral posts.

The authors adopted thematic analysis and focused on the impact of post content and valence on user participation behavior. This study expands the existing literature. The government can improve crises management capability by learning about citizen engagement behaviors on social media.

The purpose of this paper is to investigate the effects of structural parameters of fabric on thermal insulation properties of the coated fabric.

The authors established a numerical model for the ablation of silicone resin-coated fabric under high heat flow, and the simulation results have been validated by quartz lamp ablation experiment. The model was used to investigate the effects of structural parameters of glass fiber fabrics on the heat transfer process of the coated fabric.

The numerical values were in agreement with the experimental values. The thermal insulation of the coated glass fiber fabric was better than coated carbon fabric. Thermal insulation performance of the coated glass fiber fabrics was in order plain < 2/1 twill < 3/3 twill < 5/3 stain fabric. Increasing the warp density, from 100 to 180 ends/10 cm, the temperature of the back surface of the coated glass fiber fabric was reduced from 601°C to 553°C. Thermal insulation performance dramatically increased as yarn fineness went from 129 to 280 tex, and the temperature difference was 63°C.

In the ablation process, to simplify the calculation, the combustion reaction of silicone resin was ignored, which can be added in the future research.

This paper provides the ablation model of the silicon-coated fabric based on the 3D geometry model to explore the influence of the structural parameters of coated glass fiber fabric on its thermal protection performance.

The aim of this study is to determine the impact of different dimensions of consumer engagement in social media on firm performance in social media.

Beyond likes and comments, combined with the interactive behavior of consumer engagement with firms on social media, we proposed a set of metrics for consumer engagement on social media, namely personal engagement, user-interactive engagement, and fan-interactive engagement. We used the fixed-effect model and validated the impact of consumer engagement in different dimensions on firm performance.

The result shows that personal engagement and user-interactive engagement significantly correlate with firm performance; however, the same effect was not observed in fan-interactive engagement.

Prior researches on consumer engagement in social media are mainly about consumer engagement in firm-initiated social media page. In this study, we consider the consumer engagement behavior in firm-initiated and consumer-initiated social media pages, then validate the impact of different dimensions of consumer engagement on firm performance.

In the context of carbon peaking and neutrality, effectively controlling agricultural carbon emissions has gained academic attention. As an essential form of agricultural service scale management, this study investigates whether and how trusteeship affects the carbon emission behavior in planting production.

The authors established a theoretical framework to analyze the impact of agricultural production trusteeship on carbon emissions from planting. China's provincial panel data in the 2012–2021 period were selected to test the impact, mechanisms and heterogeneity of agricultural production trusteeship on carbon emissions from planting using the bidirectional fixed effect model and the panel correction standard error regression model.

The findings indicate that agricultural production trusteeship significantly inhibits carbon emissions from planting, especially in the dimensions of fertilizer input, pesticide application, agricultural film use and mechanical fuel. Agricultural production trusteeship primarily affects the intensity of these carbon emissions through contiguous farmland management and planting structure adjustment. Further examinations revealed that the influence of agricultural production trusteeship on carbon emissions from planting was heterogeneous with respect to geographical location, proportion of non-farming income and scale of agricultural production.

This study is the first to systematically evaluate the impact of agricultural production trusteeship on carbon emissions from planting.

A new direct blind equalization algorithm is presented in this paper. It relies on the auto‐correlation matrix of the channel, and adopts its eigenvector decomposition for designing an equalizer, which exploits the correlation characteristics of the channel. The proposed equalization is insensitive to the inaccuracy of the channel order estimation, and its data sequence length required for estimating the channel's correlation matrix is shorter than that of the other eigenvector decomposition methods that assumed that the channel order was known or had been estimated. Simulation results show that this algorithm is capable of acquiring a good performance under lower SNR in a communication system employing 16‐QAM modulation.

Large capacity current carrier printed circuit board (PCB) imposes strict control requirements on the hole wall roughness. The key factors are chip removal, drilling temperature and tool wear. This paper aims to find out a cryogenic drilling process to control the chip removal, chip morphology, tool wear and finally reduce the hole wall roughness.

The chip removal process, chip morphology, tool wear and hole wall roughness of glass fiber epoxy resin copper clad laminate (FR-4) drilling were observed and analyzed. The influence of cold air on the chip removal process, chip morphology, tool wear and hole wall roughness was also investigated. An optimization process of cold air auxiliary drilling was proposed to control the hole wall roughness of FR-4.

The results showed that the discharge time of copper foil chips with obvious characteristics can be used as the evaluation criterion for the smoothness of chip removal. The cold air can promote chip removal and reduce tool wear. In addition, the chip removal and cooling performance will be the best when using −4.7 °C cold air with the injection angle consisted with the angle of helical flute of the drill. The hole wall roughness of FR-4 could be controlled by drilling with −4.7°C cold air.

This paper was the first study of the effect of three kinds of cold air on PCB drilling. This provided a reference for the possibility that the cryogenic drilling methods apply to PCB drilling. A new cold air auxiliary drilling process was developed for large capacity current carrier FR-4 manufacturing.

The purpose of this paper is to present a novel n‐buried‐PSOI sandwiched radio frequencies (RF) power lateral diffused metal‐oxide semiconductor (LDMOS) and analyze its output characteristics.

The small‐signal equivalent circuit for RF power LDMOS method is used to analyze the proposed structure and the simulation and optimization are done using the computer‐aided design tools.

This improved structure is clearly decreasing drain‐substrate parasitic capacitance. At 1 dB compression point, its output power, the power‐added efficiency and the breakdown voltage are higher than that of the conventional LDMOS.

This paper puts forward a novel n‐buried‐PSOI sandwiched structure of RF power LDMOS. The analysis indicates that the output characteristics of this device are a great improvement on the conventional LDMOS and the n‐buried‐PSOI, RF power LDMOS proposed by earlier authors.

Drawing on the wisdom of ancient Chinese philosopher Xunzi, this paper aims to present a novel mechanism for governing opportunism, referred to as “cultivational governance.” By examining the role of artificial intelligence (AI) resources possessed by e-commerce platforms, the authors explore how these resources contribute to mitigating seller opportunism. The central hypothesis of this study posits that two distinct types of AI resources, namely, AI technology resources and AI human resources, serve as crucial factors in curbing seller opportunism. Furthermore, the authors propose that platform digital empowerment and value cocreation act as mediating variables linking AI resources to opportunism.

Based on the resource-based view and resource orchestration theory, the authors developed a framework and tested it using survey data from sellers. This framework encompasses five key variables: e-commerce platform’s AI technology resources, AI human resources, platform digital empowerment, value cocreation and seller opportunism. Regression analysis was used for data analysis.

The empirical results validate the effectiveness of cultivational governance mechanisms, as both AI resources effectively suppress seller opportunism through digital empowerment and value cocreation. Specifically, e-commerce platforms’ AI technology resources significantly promote value cocreation and platform digital empowerment, while AI human resources primarily contribute to platform digital empowerment. Although platform digital empowerment encourages value cocreation, its direct impact on reducing seller opportunism was not supported. Notably, value cocreation negatively affects seller opportunism.

The present research mainly contributes to the marketing channel governance literature by introducing a new approach to inhibit opportunism, namely, the cultivational governance mechanism.