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Service quality (SQ) is considered an organizational performance indicator that largely depends on employees’ attitudes and behaviors. Therefore, the purpose of this paper is to examine the mediating effect of employees’ citizenship behavior (OCB) on the relationship between affective commitment (AC) and SQ.

The current study has relied on two questionnaire surveys to gather cross-sectional data from 800 employees and 400 customers of telecommunications companies in Kuwait. Structural equation modeling via AMOS22 was used to build and test the hypothesized model.

The results show that OCB significantly and positively affects SQ dimensions except empathy which demonstrates insignificant association. Also, AC was found to be a strong predictor of OCB. More interestingly, the results show that AC does not show any effect on either responsiveness or empathy, while a partial mediation was found between AC and tangibles, reliability, and assurance.

The findings of the current study provide managers and practitioners with empirically validated model of how SQ can be achieved. The model indicates that managers need to increase the level of citizenship behavior through leveraging their employees’ AC, which in turn can result in a positive perception of SQ.

This study is considered among the first to investigate the causal effect of both OCB and AC on achieving high SQ. Also, the findings of this study further support the indirect relationship of AC and SQ. Moreover, this study is unique in its attempt to link both AC and OCB to the dimensions of SQ. Finally, this study is considered the first empirical investigation of SQ in the telecommunication sector in Kuwait.

This research paper aims to establish a comprehensive framework for the barriers to CER in the construction industry, assesses the barriers' relative degrees of hindrance and causal mechanisms.

Firstly, 26 carbon emission reduction (CER) barriers in the construction industry were identified based on a systematic literature review (SLR) and categorized into five dimensions: policy, economy, society, technology and organization (PEST + O model). Secondly, the Best–Worst Method (BWM) was used to clarify the degrees of hindrance of the CER barriers. Then, the Grey-Decision-Making Trial and Evaluation Laboratory (Grey-DEMATEL) was used to visualize the directional cause–result relationship network among prominent barriers. Finally, the Boston matrix model was used to propose differentiated strategies to address CER barriers in the construction industry.

The calculated centrality and causality of the prominent barriers indicated that the lack of relevant legal policies and normative guidelines, the poor binding force and enforcement of existing relevant policies, the lack of effective economic subsidies and incentives and the difficulty in the operation, transformation and upgrading of existing construction CER are the key barriers that CER needs to address first in the construction industry. Considering the order of priority and the optimal path, differentiated countermeasures are proposed to address key, driving, independent and effect barriers.

This study develops a BWM–Grey-DEMATEL integrated multi-criteria decision-making model. An innovative C-shaped strategic map for addressing CER barriers in the construction industry is proposed by integrating the dual dimensions of time and space. This will guide practitioners, policymakers and decision-makers in developing CER strategies.

The purpose of this study is to reveal the mechanism of humble leadership inducing abusive supervision from the low-status compensation perspective, examining the mediation role of leader perceived thread to status. Besides, the moderation effect of regulatory focus on the mediation path is discussed.

This study conducted a three-wave longitudinal survey. The data was collected from 438 leaders and their employees in five Chinese enterprises. This study used Mplus 7.4 and adopted a bootstrapping technique for data analysis.

Humble leadership has a positive effect on leader perceived threat to status. Leader perceived threat to status plays a mediation role between humble leadership and leader abusive supervision. Leader regulatory focus is the “gate valve” that humble leadership fosters leader abusive supervision. That is, when the leader promotion focus is high, leader perceived threat to status bred by humble leadership is low, resulting in less abusive supervision. When the leader prevention focus is high, humble leadership brings relatively more abusive supervision through perceived threat to status.

This study explores why humble leadership breeds abusive supervision behaviors and reveals the mechanism behind the negative effect of humble leadership based on low-status compensation theory. This study not only promotes the continuous development of the field of humble leadership research through empirical research but also provides guidance for effectively suppressing the negative effects of humble leadership, promoting strengths and avoiding weaknesses and suppressing inappropriate management behaviors in management practice.

Based on the Cognitive Appraisal Theory of Stress, this study aims to reveal the mechanism of peer abusive supervision on bystander proactive behavior through two different paths: bystander assertive impression management motivation and bystander defensive impression management motivation. Besides, the moderating effects of bystander uncertainty tolerance on the two paths are also explored.

In this study, 438 employees and their direct leaders from eight Chinese companies were surveyed in a paired survey at three time points, and the empirical data was analyzed using Mplus 7.4 software.

Peer abusive supervision leads bystanders to develop assertive impression management motivation and, thus, to exhibit more proactive behaviors. At the same time, peer abusive supervision also causes bystanders to develop defensive impression management motivation, which reduces the frequency of performing proactive behaviors. In addition, this study finds that bystander uncertainty tolerance plays a moderating role in influencing bystander assertive impression management motivation and bystander defensive impression management motivation in response to peer abusive supervision.

Starting from the bystander perspective, this study verifies the double-edged sword effect of peer abusive supervision on bystander proactive behavior as well as the mechanism of differentiated effects through cognitive appraisal, which broadens the scope of the research on abusive supervision, and deepens the academic understanding and development of the Cognitive Appraisal Theory of Stress. At the same time, it also provides new ideas for organizations to reduce the negative effects of workplace abusive behavior.

Incorporating dynamic spatial effects exhibits considerable potential in improving the accuracy of forecasting tourism demands. This study aims to propose an innovative deep learning model for capturing dynamic spatial effects.

A novel deep learning model founded on the transformer architecture, called the spatiotemporal transformer network, is presented. This model has three components: the temporal transformer, spatial transformer and spatiotemporal fusion modules. The dynamic temporal dependencies of each attraction are extracted efficiently by the temporal transformer module. The dynamic spatial correlations between attractions are extracted efficiently by the spatial transformer module. The extracted dynamic temporal and spatial features are fused in a learnable manner in the spatiotemporal fusion module. Convolutional operations are implemented to generate the final forecasts.

The results indicate that the proposed model performs better in forecasting accuracy than some popular benchmark models, demonstrating its significant forecasting performance. Incorporating dynamic spatiotemporal features is an effective strategy for improving forecasting. It can provide an important reference to related studies.

The proposed model leverages high-frequency data to achieve accurate predictions at the micro level by incorporating dynamic spatial effects. Destination managers should fully consider the dynamic spatial effects of attractions when planning and marketing to promote tourism resources.

This study incorporates dynamic spatial effects into tourism demand forecasting models by using a transformer neural network. It advances the development of methodologies in related fields.

纳入动态空间效应在提高旅游需求预测的准确性方面具有相当大的潜力。本研究提出了一种捕捉动态空间效应的创新型深度学习模型。

本研究提出了一种基于变压器架构的新型深度学习模型, 称为时空变压器网络。该模型由三个部分组成：时空转换器、空间转换器和时空融合模块。时空转换器模块可有效提取每个景点的动态时间依赖关系。空间转换器模块可有效提取景点之间的动态空间相关性。提取的动态时间和空间特征在时空融合模块中以可学习的方式进行融合。通过卷积运算生成最终预测结果。

结果表明, 与一些流行的基准模型相比, 所提出的模型在预测准确性方面表现更好, 证明了其显著的预测性能。纳入动态时空特征是改进预测的有效策略。它可为相关研究提供重要参考。

所提出的模型利用高频数据, 通过纳入动态空间效应, 在微观层面上实现了准确预测。旅游目的地管理者在规划和营销推广旅游资源时, 应充分考虑景点的动态空间效应。

本研究通过使用变压器神经网络, 将动态空间效应纳入旅游需求预测模型。它推动了相关领域方法论的发展。

La incorporación de efectos espaciales dinámicos ofrece un considerable potencial para mejorar la precisión de la previsión de la demanda turística. Este estudio propone un modelo innovador de aprendizaje profundo para capturar los efectos espaciales dinámicos.

Se presenta un novedoso modelo de aprendizaje profundo basado en la arquitectura transformadora, denominado red de transformador espaciotemporal. Este modelo tiene tres componentes: el transformador temporal, el transformador espacial y los módulos de fusión espaciotemporal. El módulo transformador temporal extrae de manera eficiente las dependencias temporales dinámicas de cada atracción. El módulo transformador espacial extrae eficientemente las correlaciones espaciales dinámicas entre las atracciones. Las características dinámicas temporales y espaciales extraídas se fusionan de manera que se puede aprender en el módulo de fusión espaciotemporal. Se aplican operaciones convolucionales para generar las previsiones finales.

Los resultados indican que el modelo propuesto obtiene mejores resultados en la precisión de las previsiones que algunos modelos de referencia conocidos, lo que demuestra su importante capacidad de previsión. La incorporación de características espaciotemporales dinámicas supone una estrategia eficaz para mejorar las previsiones. Esto puede proporcionar una referencia importante para estudios afines.

El modelo propuesto aprovecha los datos de alta frecuencia para lograr predicciones precisas a nivel micro incorporando efectos espaciales dinámicos. Los gestores de destinos deberían tener plenamente en cuenta los efectos espaciales dinámicos de las atracciones en la planificación y marketing para la promoción de los recursos turísticos.

Este estudio incorpora efectos espaciales dinámicos a los modelos de previsión de la demanda turística mediante el empleo de una red neuronal transformadora. Supone un avance en el desarrollo de metodologías en campos afines.

This paper aims to automatically obtain the implant parameter from the CBCT images to improve the outcome of implant planning.

This paper proposes automatic simulated dental implant positioning on CBCT images, which can significantly improve the efficiency of implant planning. The authors introduce the fusion point calculation method for the missing tooth's long axis and root axis based on the dental arch line used to obtain the optimal fusion position. In addition, the authors proposed a semi-interactive visualization method of implant parameters that be automatically simulated by the authors' method. If the plan does not meet the doctor's requirements, the final implant plan can be fine-tuned to achieve the optimal effect.

A series of experimental results show that the method proposed in this paper greatly improves the feasibility and accuracy of the implant planning scheme, and the visualization method of planting parameters improves the planning efficiency and the friendliness of system use.

The proposed method can be applied to dental implant planning software to improve the communication efficiency between doctors, patients and technicians.

The purpose of this paper is to deconstruct the multi-faceted dimensions of Chinese travellers’ image of boutique hotels with a large amount of online textual data from social media (53,427 reviews written from 2014 to 2018), reinforcing the value creation of user-generated content via social media.

With the aid of Python, a computer language, online textual reviews (53,427 reviews) of 86 high-end boutique hotels in seven cities (Beijing, Shanghai, Hangzhou, Nanjing, Chengdu, Qingdao and Sanya) were collected from the top-ranked online travel agency in China, Ctrip.com. Then, the overall perceived image of boutique hotels was revealed with the aid of Python.

The results showed multiple dimensions of the image of boutique hotels. The overall image can be grouped into eight dimensions (room, service, food, environment, entertainment, location, price and value, and uniqueness). An affective image based on eight dimensions was further developed in the Chinese boutique hotel context. It appears that online data from social media are beneficial for hotel managers to learn travellers’ overall perceptions of boutique hotels and help put more effective management strategies in place in the hospitality industry.

The relationship between cognitive image and affective image should be further investigated in future research. Theoretical implications are discussed from both cognitive image and affective image perspectives in the boutique hotel context. Managerial implications are highlighted to help industry managers understand the travellers’ perceptions of the hotels, via online data from social media, and put more effective hotel strategies in hospitality industry.

By using textual online data from social media, this paper deconstructs both the cognitive image and the affective image of boutique hotels. The dimensions of the most frequently mentioned concepts related to the Chinese boutique hotel industry are profoundly deconstructed, as is the uniqueness of the image of boutique hotels. The work is valuable for promoting effective marketing strategies in the hotel industry.

This study aims to explore the dimensions and sub-factors of Airbnb hosts’ affinity-seeking strategies. It also aims to build a conceptual framework of hosts’ affinity-seeking strategies and their impact on Airbnb guests’ feelings of affection toward their host and/or the homestay and their behavioral intentions.

Based on 150,161 Inside Airbnb online reviews in three major US cities, this study uses semantic analysis to explore processes through which hosts’ affinity-seeking strategies are constructed.

A conceptual framework is proposed to identify two dimensions (warmth and competency) and their sub-factors (“presenting friendly attitudes,” “showing personality traits,” “providing service and help” and “promoting social interaction and sharing”) of Airbnb homestay hosts’ affinity-seeking strategies. The framework shows a positive relationship between these strategies and guests’ affection and behavior in response.

The research findings provide valuable insights to hosts for improving their affinity and strengthening their competitive advantages. They also offer guidance to destination management organizations on how to build a positive destination image.

To the best of the authors’ knowledge, this study is the first to conceptualize Airbnb homestay hosts’ affinity-seeking strategies. It contributes to the literature by incorporating social cognition theory and service theory in the analysis of these strategies.

Drawing on Schumpeter’s theory of innovation and stereotype content model, this study aims to arrive at an integrated model that relates destination innovation type, destination innovativeness and revisit intention to uncover more about the drivers and outcomes of destination innovativeness from a consumer-centric perspective.

Three studies, including content analysis of news media, an onsite survey and an online survey in Chinese special featured towns, were conducted.

This study develops a consumer-centric destination innovation measure. The results reveal that input innovation and product innovation positively influence revisit intention through the serial mediation of destination innovativeness and perceived competence.

As the data was collected from tourists in China, any generalization of the results to other regions should be made with caution; accordingly, replication is needed to test the proposed model in different cultural contexts. Second, during the onsite data collection period, special featured town destinations were still recovering from the COVID-19 pandemic, which may have affected the perceptions of tourists. Third, the second round of data was collected using an online survey, which may have introduced bias due to a potential lack of representativeness. Fourth, some potential missing variables could also influence the links among innovation, destination innovativeness and revisit intention.

This study presents the first empirical test of the impact of innovation type and innovativeness on tourists’ response to tourism destinations. The results of this study could guide destinations to deliver more effective consumer-centric innovations to generate competitiveness.

本研究基于熊彼特的创新理论和刻板印象内容模型构建并且实证检验了目的地创新对游客重游意愿的中介影响机制, 旨在从消费者视角探究目的地创新性的驱动因素和影响结果。

本研究通过收集研究主题相关新闻稿件并进行内容分析获得高度情境化的测量问项, 并通过开展两轮问卷调查收集的数据对研究模型进行了检验。共回收有效问卷598份。

本研究开发了以消费者为中心的目的地创新量表。研究结果表明, 目的地投入创新和产品创新可能会影响游客对目的地创新性和感知能力的评价, 进而提升他们的重游意愿。并且, 研究发现目的地创新性和感知能力发挥了连续中介作用。

本研究从消费者感知角度出发, 揭示了目的地创新对游客重游意愿的影响作用及其内在机制, 为旅游目的地创新提供了启示。

Basándose en la teoría de la innovación de Schumpeter y en el modelo de contenido de los estereotipos, este estudio tiene como objetivo llegar a un modelo integrado que relacione el tipo de innovación del destino, capacidad de innovación del destino e intención de revisita del destino, para descubrir más acerca de los impulsores y resultados de la innovación desde una perspectiva centrada en el consumidor.

Se han llevado a cabo tres estudios entre los que se han incluido, el análisis del contenido de los medios de comunicación informativos, encuesta «in situ», además de una encuesta en línea en pueblos chinos que destacan por sus características especiales.

Esta investigación desarrolla una medición de la innovación del destino desde una perspectiva centrada en el consumidor. Los resultados revelan que la innovación en los recursos y la innovación del producto, influyen positivamente en la intención de revisitar a través de la mediación en serie de la innovación del destino y la competencia percibida.

Este trabajo presenta la primera prueba empírica del impacto del tipo de innovación, así como de innovaciones sobre la respuesta de los turistas a los destinos turísticos. Los resultados de este estudio podrían guiar a los gestores de los destinos en el ofrecimiento de innovaciones más efectivas centradas en el consumidor con el fin de generar competitividad.