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The purpose of this paper is to put forward the grey relational decision-making model of three-parameter interval grey number based on Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA), based on the previous study of grey relational decision-making model, and it considers the advantages of the decision-making schemes and the subjective preferences of decision makers.

First of all, through AHP, the preference of each index is analyzed and the index weight is determined. Second, the DEA model is adopted to obtain the index weight from the perspective of the most beneficial to each scheme and objectively reflect the advantages of different schemes. Then, assign the comprehensive weights to each index of the grey relational decision-making model of three-parameter interval grey number, and calculate the grey relation degree of each scheme to rank the schemes.

The effectiveness of the model is proved by an example of carrier aircraft selection.

The applicability of this model is analyzed by taking carrier aircraft selection as an example. In fact, this model can also be widely used in agriculture, industry, economy, society and other fields.

In this paper, the combination of AHP and DEA is used to determine the index weight. Based on which, the grey relation degree under the three-parameter interval grey number is calculated. It intended the application space of the grey relational decision-making model.

Pipeline maintenance technology using smart isolation tool is becoming more widely used in the global scope. This paper aims to investigate the effects of parameters on the frictional resistance between the slip and pipeline and the frictional characteristics under different lubrication films.

An experimental platform consisting of slip, pipeline and data acquisition system was developed, wherein the slip slips on the pipeline under different normal forces and velocities. In addition, three lubrication conditions, namely, dry wall, oil liquid and black powder on the wall, were investigated to study the effects of lubrications on the frictional coefficient and characteristics.

Research results indicate that the frictional force and coefficient were sensitive to normal force. The crude oil affected the frictional coefficient within a certain range of normal force, and the black powder enhanced the surface roughness in the natural gas pipeline. However, velocity had no effect on them. In addition, different contact behaviors could be observed from the frictional coefficient curves.

In this paper, the effects of normal force and velocity on frictional resistance of sliding slip during decelerating process in pipeline were investigated, and the effects of lubrication films on frictional characteristics were also revealed. The research results are of great value to improve the prediction accuracy of smart isolation tool, and also provide a guiding significance for the development of maintenance operation in pipelines.

The purpose of the present paper is to propose a full model‐based method for distance‐mapping calibration for the non‐SVP (non‐single viewpoint) catadioptric camera of the soccer robot. The method should be easy to operate, efficient, accurate, and scalable to fit larger field sizes.

The distance‐mapping model was first constructed based on the imaging principle. The authors then calibrated the internal parameters using the mirror boundary and used the mirror center to choose the correct pose from two possible solutions. The authors then proposed a three‐point method based on a unique solution case of the non‐SVP P3P (perspective‐three‐point) problem to solve the external parameters. Lastly, they built the distance mapping by back‐projection.

The simulation experimental results have shown that the authors' method is very accurate even when there is severe misalignment between the mirror and the camera and that all calibration operations, except the calibration of a standard camera, can be completed in 1 min. The result of the comparison with the traditional calibration method shows that the authors' method is superior to the traditional method in terms of accuracy and efficiency.

The proposed calibration method is scalable to larger fields because it only uses the boundary of the mirror and three feature points on the field, and does not need additional calibration objects. Additionally, an automatic calibration method that can be used during the game can be easily developed based on this method. Moreover, the proposed mirror‐pose‐selection method and a unique solution to the non‐SVP P3P problem are especially useful for a non‐SVP catadioptric camera.

Robot localization technology has been widely studied for decades and a lot of remarkable approaches have been developed. However, in practice, this technology has hardly been applied to common day-to-day deployment scenarios. The purpose of this paper is to present a novel approach that focuses on improving the localization robustness in complicated environment.

The localization robustness is improved by dynamically switching the localization components (such as the environmental camera, the laser range finder and the depth camera). As the components are highly heterogeneous, they are developed under the robotic technology component (RTC) framework. This simplifies the developing process by increasing the potential for reusability and future expansion. To realize this switching, the localization reliability for each component is modeled, and a configuration method for dynamically selecting dependable components at run-time is presented.

The experimental results show that this approach significantly decreases robot lost situation in the complicated environment. The robustness is further enhanced through the cooperation of heterogeneous localization components.

A multi-component automatic switching approach for robot localization system is developed and described in this paper. The reliability of this system is proved to be a substantial improvement over single-component localization techniques.

This study aims to investigate diners’ self-presentation mechanism as manifested in foodstagramming. Drawing upon the social cognitive and self-presentation theories, this study develops a conceptual model to examine the relationships among food experiential value (i.e. extrinsic value and intrinsic value), self-efficacy, strategic self-presentation and self-presentation outcomes.

The authors adopt a multi-study approach with two empirical studies (Study 1: tourists, n = 254; Study 2: residents, n = 252) and use partial least squares structural equation modeling to test the proposed model.

The results consistently show significant effects of extrinsic value, intrinsic value and self-efficacy on strategic self-presentation, which subsequently evokes perceived enjoyment and behavioral intention. The impact of food experiential value on self-efficacy varies between tourists and residents. The mediating effects of self-efficacy and strategic self-presentation are also confirmed.

Restaurant managers and destination marketers should acknowledge the importance of food experience as expressive capital and recognize self-presentation as a meaningful tool that links restaurant food experience with consumers’ personal branding. Businesses should strive to create a desired experiential setting shaped by food price, restaurant service, food aesthetics and consumers’ feelings, allowing diners to translate these stimuli into self-presentational resources.

This study dives into an important, yet under-examined, phenomenon of foodstagramming. To the best of the authors’ knowledge, this study is the first to theoretically link food experience to foodstagramming behavior via a self-presentation mechanism. Findings provide important theoretical and managerial implications.

Drawing on anthropomorphism and the stereotype content model, this study aims to explore the impacts of robot anthropomorphism on hotel guests’ word of mouth and continuous usage intention through perceived warmth and competence. This study also investigates the moderating effects of guests’ expertise.

A total of 524 valid data was collected with Chinese hotel guest through an online survey. Data were analyzed by using structural equation modeling.

The results indicate that robot anthropomorphism positively affects perceived warmth and competence. Perceived warmth positively affects guests’ word of mouth and continuous usage intention, while perceived competence only positively influences guests’ continuous usage intention. The findings further show that guest expertise weakens the positive relationship between robot anthropomorphism and perceived warmth and competence.

This study advances robot service literature by integrating the stereotype content model with robot anthropomorphism in exploring hotel guests’ perceptions on service robots. This study also discovers the vital boundary role of guest characteristics in human–robot interaction. This study provides valuable information for hoteliers to design and adopt better robots for optimal guest experiences.

基于拟人化和刻板印象内容模型, 本研究探讨了机器人拟人化通过感知温暖和感知能力对酒店客人的口碑和持续使用意向的影响。此外, 本研究也探讨了客人专业知识的调节作用。

通过在线调查问卷, 我们共收集了来自中国酒店客人的524份有效数据, 并采用结构方程模型对这些数据进行了分析。

研究结果表明, 机器人拟人化积极影响感知温暖和感知能力。感知温暖会对客人的口碑和持续使用意向产生积极影响, 而感知能力只对客人的持续使用意向产生积极影响。研究结果进一步表明, 客人的专业知识会削弱机器人拟人化与感知温暖和能力之间的积极关系。

为了探索酒店客人对服务机器人的感知（状况/情况）, 本研究将机器人拟人化因素整合到刻板印象内容模型中, 其结果推动了机器人服务研究的发展。本研究还发现了客人特征在人机互动中的重要边界作用。本研究为酒店经营者设计和采用更好的机器人以获得最佳的客人体验提供了有价值的参考。

Se recopiló datos válidos de un total de 524 clientes de hoteles chinos mediante una encuesta en línea. Los datos fueron analizados mediante un modelo de ecuaciones estructurales.

Basándose en el antropomorfismo y en el modelo de contenido estereotipado, este estudio explora el impacto del antropomorfismo de los robots en el boca a boca de los clientes del hotel y en la intención de uso continuado a través de la calidez y la competencia percibidas. El estudio investiga también los efectos moderadores de la experiencia de los huéspedes.

Los resultados indican que el antropomorfismo del robot afecta positivamente a la calidez y a la competencia percibidas. La calidez percibida influye positivamente en el boca a boca y en la intención de uso continuado de los huéspedes, mientras que la competencia percibida sólo influye positivamente en la intención de uso continuado de los huéspedes. Los resultados muestran, además, que la experiencia del cliente debilita la relación positiva entre el antropomorfismo del robot y la percepción de calidez y de competencia.

Este estudio supone un avance en la literatura sobre robots de servicio al integrar el modelo de contenido estereotipado con el antropomorfismo de los robots, en la exploración de las percepciones de los huéspedes de hoteles sobre los robots de servicio. Este estudio también muestra el papel vital que desempeñan las características de los huéspedes en la interacción humano-robot. El estudio proporciona información valiosa para que los hoteleros diseñen y adopten mejores robots para ofrecer experiencias óptimas a los huéspedes.

Building on theories of inter-organizational knowledge flows and social network, we explored how two types of collaboration network embeddedness (NE) (i.e. structural embeddedness (SE) and relational embeddedness (RE)) drive firms' inbound and outbound open innovation (OI) practices from a knowledge flow perspective, and further examined these relationships are to what extent contingent on network inertia (NI).

In this empirical research, the authors collected a sample of patents in the unmanned aerial vehicle (UAV) industry over the period of 2000–2018. Then the authors examined the direct roles of SE and RE in collaboration networks on firms' inbound and outbound OI practices from a knowledge flow perspective, and the moderating role of NI by using negative binomial regression.

Empirical results from our study of 96 firms showed that both bridging structural holes position in collaboration networks (i.e. SE) and having stronger tie strength (i.e. RE) would positively affects firms' inbound OI practices, whereas only having stronger tie strength in collaboration networks (i.e. RE) would facilitate outbound OI practices. In addition, NI strengthens the relationships between SE and firm OI practice, but weakens the positive roles of RE on firm OI practice.

This empirical research provides new insights into whether and how firms can grasp the benefits of collaboration NE to conduct OI activities by exploring NI contingencies. It further sheds lights on the scope of the NE–OI issue from a knowledge flow perspective by extending its research context to UAV industry.

The purpose is to explore the essential reasons for the differences between book awakening phenomena, to develop the critical factors in awakening the slumbering collections and to provide a reliable basis for maximizing book value and optimizing collection allocation.

The research employs the integrated learning algorithm XGBoost to measure driving factors. In the process of book circulation, the characteristics of collections and readers are worthy of attention. Therefore, this study also carries out feature selection and model construction from the two dimensions of books and readers.

The results show that reader features have a stronger impetus for the collection awakening phenomenon than collection features. Among reader features, education level, gender and major subject are the main factors, which are followed closely by the activity level; among collection features, publication date and price are the main driving factors. The indicators of book popularity are not significant, whose effect on the phenomenon of collection awakening is almost negligible.

This study aims to augment the theory of zero circulation from the theoretical level and, for the first time, seeks to define the phenomenon of collection awakening. This study attempts to present novel ideas for research in the field of libraries and to provide references for optimizing collection and maximizing the value of books.

The demanding nature of construction industry poses serious health risks to construction workers. In recent years, construction health management (CHM) has gained much attention to ensure a healthier and safer workplace. However, there is still lack of a systematic review to bring together the disaggregated studies and determine the development status of this research field. As essential for addressing health issues in construction industry, a bibliometric and content-based review on of previous CHM studies would be presented in this paper.

In total, 753 journal articles published in Web of Science core collection from 1990 to 2020 were examined using a systematic review. Bibliometric analysis concentrated on the analysis of publication and citation pattern of CHM research while content analysis was employed to identify main health hazards, levels of analysis and topical focuses.

The results indicated that the USA was the leading country in this research domain. Five health hazards together with 17 research topics at different levels of analysis were classified to allow researchers to track the structure and temporal evolution of the research field. Finally, three emerging trends and a set of research agenda were proposed to guide future research directions.

It is the first to highlight the issues of occupational health management from the perspective of construction workers. It contributes to the field of construction health management by clarifying the knowledge structure, emerging trends and future research directions. It offers valuable guidance and in-depth understanding to researchers, practitioners and policymakers to further promote construction workers' health performance.

The purpose of this paper is to analyze the inverted U-shaped relationship between external search in the collaboration network and firm innovation outcomes. It also seeks to explore whether these curvilinear relationships are moderated by the network centrality and structural holes in the knowledge network.

In this empirical research, the authors collected a sample of patents in the smartphone industry over the period of 2000-2017. Then the authors examined the direct roles of external search breadth and depth in the collaboration network and the moderating role of network embeddedness in the knowledge network by using negative binomial regression.

Results found that external search in the collaboration network contributes more to firm innovation outcomes when the breadth and depth of the external search are moderate rather than high or low. Furthermore, both network centrality and structural holes in the knowledge network have positive effects on the external search breadth – innovation outcomes and external search depth – innovation outcomes relationships.

The authors collected the patent data within the single industry and excluded other types of industries. This may limit the generalization of the findings.

The paper has practical implications for adopting appropriate search strategies in the collaboration network and developing a better understanding of the effect of network embeddedness in the knowledge network on firm innovation outcomes. The findings suggest future directions for technology-intensive industries to improve their innovation output.

This study adds value to open innovation literature by pointing out a curvilinear relationship (inverted U-shaped) between external search breadth/depth and innovation outcomes in collaboration networks, in contrast to studies focused on firms’ external collaboration strategies in a certain industry context. Furthermore, this study reinforces the key contingent role of embeddedness in knowledge networks. This study provides a valuable theoretical framework of innovation outcome determinants by connecting the network perspective of open innovation theory with an embeddedness view.