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This study aims to analyze the influence of farmers’ degree of participation in collective action on their adoption decisions and waiting time regarding soil and water conservation (SWC) measures.

The Probit model and Generalized Propensity Score Match method are used to assess the effect of the degree of participation in collective action on farmers’ adoption decisions and waiting time for implementing SWC measures.

The findings reveal that farmers’ engagement in collective action positively influences the decision-making process regarding terrace construction, water-saving irrigation and afforestation measures. However, it does not significantly impact the decision-making process for plastic film and ridge-furrow tillage practices. Notably, collective action has the strongest influence on farmers’ adoption decisions regarding water-saving irrigation technology, with a relatively smaller influence on the adoption of afforestation and terrace measures. Moreover, the results suggest that participating in collective action effectively reduces the waiting time for terrace construction and expedites the adoption of afforestation and water-saving irrigation technology. Specifically, collective action has a significantly negative effect on the waiting time for terrace construction, followed by water-saving irrigation technology and afforestation measures.

The results of this study underscore the significance of fostering mutual assistance and cooperation mechanisms among farmers, as they can pave the way for raising funds and labor, cultivating elite farmers, attracting skilled labor to rural areas, enhancing the adoption rate and expediting the implementation of terraces, water-saving irrigation technology and afforestation measures.

Drawing on an evaluation of farmers’ degree of participation in collective action, this paper investigates the effect of participation on their SWC adoption decisions and waiting times, thereby offering theoretical and practical insights into soil erosion control in the Loess Plateau.

This study aims to explore the eye movement behavior of preadolescent children accessing and diagnosing information.

The researchers tracked the eye movements of 30 children with an eye-tracking apparatus. Using the kit of factor-referenced cognitive tests to measure perceptual speed and associative memory, they measured information-searching behavior with screen recordings, the data of which were analyzed by IBM SPSS Statistics 26.

Regarding information accessibility, there was a correlation between the child’s age, associative memory and the number of round-trip choices, and there were differences in the total fixation area among children of different age groups. Regarding diagnosticity, perceptual speed was positively correlated with the total fixation area, and the number of round-trip choices was negatively correlated with fixation duration.

Empirical evidence suggests that during information encoding, perceptual speed is the most important influencing factor. Extensive research indicates that children predominantly rely on recall and familiarity when searching for new information, both of which play roles in associative memory. Through an examination of the psychological and behavioral indicators of children, the study elucidated the cognitive processes involved in information processing and how children engage with information at both visual and cognitive levels.

Aiming to investigate the direct and indirect effects of community involvement on residents’ life satisfaction, this study builds a conceptual framework through the mediation effect of perceived impacts and trust in government based on social exchange theory. The moderating effect of place attachment among these variables is proposed and empirically examined.

The conceptual model and causal relationships were estimated by adopting structural equation modeling, a serial mediation and moderation analysis. A total of 362 valid questionnaire data from residents in five rural tourism communities of China were collected and used for data analysis.

The results indicate that residents’ community involvement directly influences their life satisfaction and indirectly through perceived benefits and trust in government. Place attachment is also found to moderate the effect of community involvement on residents’ life satisfaction.

This study tests the effect of community involvement on residents’ life satisfaction that evolves from linking community involvement to perceived tourism impacts and trust in government to increase life satisfaction within the rural tourism context. It simultaneously detects place attachment as a moderating variable. The findings of this study can provide valuable insights for rural tourism managers to improve residents’ life satisfaction.

为了探究社区参与对居民生活满意度的直接和间接影响, 本研究基于社会交换理论构建了通过感知影响和政府信任作为中介效应的理论模型。同时, 提出并实证检验了地方依恋在这些变量关系中的调节作用。

采用结构方程模型和一系列的中介和调节分析来估计概念模型和变量之间的因果关系。从中国五个乡村旅游社区收集了362份有效问卷并进行数据分析。

结果显示, 居民的社区参与不仅直接影响他们的生活满意度, 并且通过感知收益和政府信任对他们的生活满意度产生间接影响。研究还发现,地方依恋可以调节社区参与对居民生活满意度的影响关系。

本研究探讨了乡村旅游可持续发展中社区参与对生活满意度的影响, 这种影响从链接社区参与与旅游感知效应到政府信任, 从而提高生活满意度,同时检验了地方依恋的调节作用。本研究能够为乡村旅游管理者提高居民生活满意度提供有价值的建议。

Con el objetivo de investigar los efectos directos e indirectos de la participación de la comunidad en la satisfacción con la vida de los residentes, este estudio construye un marco conceptual a través del efecto mediador de los impactos percibidos y la confianza en el gobierno basado en la teoría del intercambio social. Se propone y examina empíricamente el efecto moderador del apego local entre estas variables.

La relación causal entre el modelo conceptual y la estructura se estima a través del modelo de ecuación estructural, y se lleva a cabo una serie de análisis de mediación y regulación. Los datos fueron recolectados de 362 cuestionarios válidos de cinco comunidades de turismo rural en China.

Los resultados muestran que la participación comunitaria de los residentes influye directamente en su satisfacción con la vida, e indirectamente a través de sus ingresos percibidos y la confianza en el Gobierno. El estudio también encontró que el apego local puede regular la participación de la comunidad en la satisfacción de los residentes con la vida.

Este estudio explora el impacto de la participación comunitaria en la satisfacción con la vida en el desarrollo sostenible del turismo rural, que va desde la vinculación de la participación comunitaria y la percepción turística hasta la confianza del Gobierno, mejorando así la satisfacción con la vida. Al mismo tiempo, se examina la función reguladora del apego local. Los resultados de este estudio proporcionan información de referencia valiosa para que los administradores del turismo rural mejoren la satisfacción de los residentes con la vida.

Recently, Internet of Things (IoT) devices and sensors are rapidly increasing in the word. They are connecting to the internet and are generating vast packets in the network. Thus, the networks could be congested, and the performance will degrade. For this reason, it is important to decrease the number of transmitted packets. Agile is a technique to develop the software and manage the work efficiently. Kanban is a method to support Agile development. The purpose of this paper is to propose an IoT sensors management system considering Agile–Kanban and show its application for weather measurement and electric wheelchair management.

The authors present the design and implementation of two systems and show the measurement device, data communication failure and experimental results.

The proposed Agile–Kanban system can manage a large amount of IoT sensors and can decrease the IoT sensor’s consumption power thus increasing the IoT sensor lifetime.

By experimental results, the authors have shown that the proposed systems have good performance and can control the IoT devices efficiently.

The purpose of this paper is to accomplish robust actuator fault isolation and identification for microsatellite attitude control systems (ACSs) subject to a series of space disturbance torques and gyro drifts.

For the satellite attitude dynamics with Lipschitz constraint, a multi-objective nonlinear unknown input observer (NUIO) is explored to accomplish robust actuator fault isolation based on a synthesis of H_inf techniques and regional pole assignment technique. Subsequently, a novel disturbance-decoupling learning observer (D²LO) is proposed to identify the isolated actuator fault accurately. Additionally, the design of the NUIO and the D²LO are reformulated into convex optimization problems involving linear matrix inequalities (LMIs), which can be readily solved using standard LMI tools.

The simulation studies on a microsatellite example are performed to prove the effectiveness and applicability of the proposed robust actuator fault isolation and identification methodologies.

This research includes implications for the enhancement of reliability and safety of on-orbit microsatellites.

This study proposes novel NUIO-based robust fault isolation and D²LO-based robust fault identification methodologies for spacecraft ACSs subject to a series of space disturbance torques and gyro drifts.

The purpose of this paper is to improve the mechanical and tribological properties of Si₃N₄ ceramics and to make the application of Si₃N₄ ceramics as tribological materials more extensive.

Si₃N₄-based composite ceramics (SN-2L) containing nitrogen-doped graphene quantum dots (N-GQDs) were prepared by hot press sintering process through adding 2 Wt.% nanolignin as precursor to the Si₃N₄ matrix, and the dry friction and wear behaviors of Si₃N₄-based composite against TC4 disc were performed at the different loads by using pin-on-disc tester.

The friction coefficients and wear rates of SN-2L composite against TC4 were significantly lower than those of the single-phase Si₃N₄ against TC4 at the load range from 15 to 45 N. At higher load of 45 N, SN-2L/TC4 pair presented the lowest friction coefficient of 0.25, and the wear rates of the pins and discs were as low as 1.76 × 10⁻⁶ and 2.59 × 10⁻⁴mm³/N·m. The low friction and wear behavior could be attributed to the detachment of N-GQDs from the ceramic matrix to the worn surface at the load of 30 N or higher, and then an effective lubricating film containing N-GQDs, SiO₂, TiO₂ and Al₂SiO₅ formed in the worn surface. While, at the same test condition, the friction coefficient of the single-phase Si₃N₄ against TC4 was at a range from 0.45 to 0.58. The spalling and cracking morphology formed on the worn surface of single-phase Si3N4, and the wear mechanism was mainly dominated by adhesive and abrasive wear.

Overall, a high-performance green ceramic composite was prepared, and the composite had a good potential for application in engineering tribology fields (such as aerospace bearings).

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0161/

Abundant studies of outpatient visits apply traditional recurrent neural network (RNN) approaches; more recent methods, such as the deep long short-term memory (DLSTM) model, have yet to be implemented in efforts to forecast key hospital data. Therefore, the current study aims to reports on an application of the DLSTM model to forecast multiple streams of healthcare data.

As the most advanced machine learning (ML) method, static and dynamic DLSTM models aim to forecast time-series data, such as daily patient visits. With a comparative analysis conducted in a high-level, urban Chinese hospital, this study tests the proposed DLSTM model against several widely used time-series analyses as reference models.

The empirical results show that the static DLSTM approach outperforms seasonal autoregressive integrated moving averages (SARIMA), single and multiple RNN, deep gated recurrent units (DGRU), traditional long short-term memory (LSTM) and dynamic DLSTM, with smaller mean absolute, root mean square, mean absolute percentage and root mean square percentage errors (RMSPE). In particular, static DLSTM outperforms all other models for predicting daily patient visits, the number of daily medical examinations and prescriptions.

With these results, hospitals can achieve more precise predictions of outpatient visits, medical examinations and prescriptions, which can inform hospitals' construction plans and increase the efficiency with which the hospitals manage relevant information.

To address a persistent gap in smart hospital and ML literature, this study offers evidence of the best forecasting models with a comparative analysis. The study extends predictive methods for forecasting patient visits, medical examinations and prescriptions and advances insights into smart hospitals by testing a state-of-the-art, deep learning neural network method.

This research aims to find out the reasons why Chinese people prefer domestic products. The authors examine the effect of consumer ethnocentrism (CE), social norms (SNs) and national identity (NI) on willingness to buy (WTB) domestic products in two time points and test the product category differences and age group differences.

Two survey studies (n₁ = 314; n₂ = 346) were conducted in China in 2021 and 2022, respectively. The authors measured CE, SNs, NI and WTB domestic products in both studies and WTB four categories of products in study 2. Multiple hierarchical linear regression was conducted to test the hypotheses.

In study 1, the authors found that SNs and NI significantly predicted WTB domestic products, but CE did not. In study 2, the authors found that all three indicators significantly predicted WTB domestic products. CE played a significant and consistent role in different product categories, while SNs and NI had inconsistent effects. NI predicted WTB domestic products for younger people but not for older people.

This research is the first to examine CE, SNs and NI in the same study and the first to explore the role of SNs and NI in WTB domestic products in China. It promotes the understanding of CE and other related factors, increases the knowledge of Chinese consumers’ purchasing behavior and indicates the power of the situation. Practical implications are also discussed.

The purpose of this study is to examine the differential association of family supportive supervisor behavior on promotive voice under different gender. Further, while employees’ self-concept factors have received considerable attention in the research on the triggering mechanism of employee voice, the authors’ knowledge about how and when family factors affect employee voice remains underdeveloped.

According to the resource conservation theory and gender role theory, the authors constructed a research model to investigate the influence and boundary of family supportive supervisor behavior on employee promotive voice and tested their research model using a paired data of 332 married employees and their direct supervisors of enterprises in China.

The findings suggest that family supportive supervisor behavior has a positive effect on employee promotive voice. Family supportive supervisor behavior can strengthen employee promotive voice by improving work-to-family enrichment and reducing work–family conflict, yet no significant mediation effect was found regarding family-to-work enrichment and conflict. Furthermore, family supportive supervisor behavior is more likely to improve female employee work–family enrichment and assuage male employee work–family conflict and thus enhance employee promotive voice.

This study sheds light on the different influential paths of family supportive supervisor behavior on promotive voice of employees of different genders and provides references for enterprises to motivate employees’ promotive voice.