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From the perspectives of service-dominant logic and social identity theory, this study aims to assess social networking site (SNS) users’ likes as a form of social endorsement as well as its effects on like-clicking behavior, perceived brand value, customer-brand identification and purchase intention. Furthermore, the different effects of social endorsement on the perceived functional, hedonic, social and monetary brand value were investigated so as to support SNS users’ role as value cocreators.

An online survey was administered as a pretest of customer perceptions regarding brands that are liked on SNSs. Next, an experiment was conducted to verify the effects of social endorsement. A mixed-method approach including partial least squares (PLS) and fuzzy set qualitative comparative analysis (fsQCA) was adopted for the data analysis.

The results revealed that like-clicking behavior could be contagious because SNS users exposed to others’ likes were more likely to click the like button themselves. Like-clicking behavior positively influenced the perceived functional, hedonic, social and monetary value of the liked brand. Perceived brand value strengthened customer-brand identification, thereby increasing purchase intention.

Like-based social endorsements were confirmed as a type of value cocreation behavior that benefits the endorsed brand by spreading brand awareness, and increasing customer acquisition and retention. An fsQCA approach was developed to measure the moderating effect of users’ propensity to click the like button on perceived brand value, thus contributing to the advancement of fsQCA.

Drawing from social comparison theory, this study investigates the factors influencing benign or malicious envy toward influencers and the effects of envy on social media users' choice of endorsed or rival brands.

A sample of 453 social media users was obtained to examine the research model.

Homophily and symbolism positively affect both benign and malicious envy. Credibility affects benign envy positively but malicious envy negatively. Deservingness affects malicious envy negatively but exerts no effect on benign envy. Benign envy has a greater influence on choosing brands endorsed by influencers than it does on choosing rival brands; these effects are more substantial under conditions of high perceived control. By contrast, malicious envy significantly affects the choice of purchasing rival brands; however, this effect is not influenced by perceived control.

This study unveils a key aspect of the endorser–follower relationship by analyzing the effect of envy toward social media influencers on followers' intention to purchase endorsed or rival brands. This study identifies the differential effects of two types of envy on brand choice.

The purpose of this study is to investigate the influence of three sources of social representation (i.e. direct experience of an event, the media and social interaction) on tourists’ formation of event image; to examine the effect of event image, satisfaction and city image on tourists’ revisit intentions to the host city; and to explore the mediating role of city image.

This study used the 28th Qingdao International Beer Festival (QIBF) as the case for verifying the relationships in the proposed model. The survey was conducted in Qingdao and 366 valid observations were collected. Structural equation modeling was used to validate the research model.

Event image is found to be significantly and positively influenced by direct experience of an event and social interaction. City image and satisfaction are important predictors of revisit intention. The meaning of event image is transferred to city image. City image plays a pivotal role in mediating the effect of event image and satisfaction on revisit intention to the host city.

This study surveyed Chinese tourists attending QIBF in Qingdao and consequently the outcomes may lack generalizability. This research did not survey foreign tourists. Thus, the differences of attitudes and behaviors between Chinese and foreign tourists are not compared.

The outcomes provide insights into how a city manager can organize an event to enhance tourists’ intentions to revisit the city.

This study represents one of the few studies that use both social representation theory and the theory of brand image transfer in examining the influence of external social contexts on tourists’ formation of event image and investigates how the unique meaning of event activities is transferred to city image. In addition, the mediating role of city image is fully explored in this research.

本研究的目的包括（1）探究社会表征的三个来源（事件的直接体验, 媒体影响, 社会互动）对游客事件形象评价的影响；（2）验证事件形象、满意度、城市形象对游客重访举办地意愿的影响；（3）检验城市形象的中介作用。

本研究以第28届青岛国际啤酒节为案例研究对象, 来验证模型中的变量关系。调研在青岛进行, 共收集有效问卷366份。通过结构方程模型来验证研究假设。

事件形象评价受到直接体验和社会互动的显著积极影响。城市形象和满意度是游客重访意愿重要的影响因素, 事件形象的内涵转移到城市形象。城市形象在事件形象和满意度对重访意愿的影响作用中起到重要的中介作用。

本研究对参加青岛国际啤酒节的中国游客进行调研, 结果可能缺少普适性。本研究没有调研外国游客, 缺少中外游客的态度和行为差异的对比。

研究结论对于城市管理者如何更好的组织事件活动以提升游客重访城市的意愿提供了新的思路。

本研究将社会表征理论和品牌形象理论应用到事件营销当中, 解释了游客事件形象评价的形成过程中外部社会情境的影响, 以及事件活动的独特内涵向城市形象转移的过程。同时, 本研究验证了城市形象在事件形象和满意度对重访意愿的影响作用中的中介作用。

事件形象, 城市形象, 满意度, 重访意愿, 社会表征理论

研究论文

(1) explorar el impacto de tres fuentes de representación social (experiencia directa de eventos, influencia de los medios, interacción social) en la evaluación de la imagen del evento de los turistas; (2) Verificar el impacto de la imagen del evento, la satisfacción y la imagen de la ciudad en la voluntad de los turistas para volver a visitar el lugar; (3) verificar el papel mediador de la imagen de la ciudad.

Este estudio toma el 28° Festival Internacional de Cerveza de Qingdao como un objeto de estudio de caso para verificar la relación de las variables en el modelo. La encuesta se realizó en Qingdao y se recolectó un total de 366 cuestionarios válidos. El modelo de ecuación estructural se utiliza para verificar la hipótesis de investigación.

El estudio muestra que la experiencia directa de los eventos y la interacción social tienen un impacto positivo y significativo en la evaluación de la imagen del evento. La imagen de la ciudad y la satisfacción son factores importantes que influyen en la voluntad de los turistas a volver a visitar. Los resultados de la investigación muestran que la imagen de la ciudad desempeña un importante papel de mediación en el efecto de la imagen del evento y la satisfacción en la voluntad de volver a visitar.

este estudio encuestó a los turistas que participaron en el Festival Internacional de Cerveza de Qingdao, y los resultados pueden carecer de generalidad. Este estudio no investigó a los turistas extranjeros, solo a los turistas chinos, por eso careció de una comparación de las diferencias en actitudes y comportamientos entre los turistas chinos y extranjeros.

las conclusiones de la investigación proporcionan nuevas ideas sobre cómo los administradores de la ciudad pueden organizar mejor las actividades del evento para aumentar la voluntad de los turistas a visitar la ciudad nuevamente.

este estudio aplica la teoría de la representación social y la teoría de la imagen de marca al marketing de eventos, explicando el impacto de los contextos sociales externos en la formación de la evaluación de imágenes de eventos turísticos y el proceso de transferir la connotación única de las actividades de eventos a la imagen urbana. Al mismo tiempo, este estudio demuestra que el papel mediador de la imagen de la ciudad tiene un impacto de la imagen del evento y la satisfacción en la voluntad de volver a visitar.

FastSLAM is a popular method to solve the problem of simultaneous localization and mapping (SLAM). However, when the number of landmarks present in real environments increases, there are excessive comparisons of the measurement with all the existing landmarks in each particle. As a result, the execution speed will be too slow to achieve the objective of real-time navigation. Thus, this paper aims to improve the computational efficiency and estimation accuracy of conventional SLAM algorithms.

As an attempt to solve this problem, this paper presents a computationally efficient SLAM (CESLAM) algorithm, where odometer information is considered for updating the robot’s pose in particles. When a measurement has a maximum likelihood with the known landmark in the particle, the particle state is updated before updating the landmark estimates.

Simulation results show that the proposed CESLAM can overcome the problem of heavy computational burden while improving the accuracy of localization and mapping building. To practically evaluate the performance of the proposed method, a Pioneer 3-DX robot with a Kinect sensor is used to develop an RGB-D-based computationally efficient visual SLAM (CEVSLAM) based on Speeded-Up Robust Features (SURF). Experimental results confirm that the proposed CEVSLAM system is capable of successfully estimating the robot pose and building the map with satisfactory accuracy.

The proposed CESLAM algorithm overcomes the problem of the time-consuming process because of unnecessary comparisons in existing FastSLAM algorithms. Simulations show that accuracy of robot pose and landmark estimation is greatly improved by the CESLAM. Combining CESLAM and SURF, the authors establish a CEVSLAM to significantly improve the estimation accuracy and computational efficiency. Practical experiments by using a Kinect visual sensor show that the variance and average error by using the proposed CEVSLAM are smaller than those by using the other visual SLAM algorithms.

Based on laser-range-finder (LRF) sensing, the control design of location and orientation stabilization for the mobile robot is investigated. However, the practical limitation of the LRF sensing is usually ignored in the control design, which leads to incorrect localization and unexpected control results. The purpose of this study is to design the fuzzy controller subject to the practical limitation on the LRF-based localization for a differentially driven wheeled mobile robot.

First, the Takagi–Sugeno (T-S) fuzzy model is derived from the polar kinematic model of a differentially driven mobile robot. Then, the fuzzy controller is designed to the derived T-S fuzzy kinematic model in accordance with the Lyapunov stabilization theorem. The derived Lyapunov stabilization conditions for the fuzzy control design are expressed as the linear matrix inequality (LMI) form and effectively solved by LMI tools. The practical limitation on the LRF-based localization is also expressed as the LMI form and simultaneously solved with the control design.

The location and posture stabilization experiments are carried out on a mobile robot with LRF-based localization to prove the effectiveness of the proposed T-S fuzzy model-based control design. Furthermore, the ground truth experiment evaluates the accuracy of LRF-based localization.

The contribution of this study is to develop the fuzzy control law for a differentially driven wheeled mobile robot under the practical limitation on LRF-based localization. The proposed control design can be applied to other robots with practical limitations on the sensors.

High-tech industries play an important role in promoting economic and social development. The purpose of this paper is to accurately predict and analyze the output value of high-tech products in Guangdong Province, China, by using a multivariable grey model.

Based on the principle of fractional order accumulation, this study proposes a multivariable grey prediction model. To further enhance the prediction ability and accuracy of the model, an optimized model is established by reconstructing the background value. The optimal parameters are solved by minimizing the average relative error of the system characteristic sequence with the constraint of parameter relationships.

The results from the study show that the two proposed models exhibit better simulation and prediction performance than the traditional models, while the optimized model can significantly improve the modelling precision. In addition, it is predicted that the output value of high-tech products is 12,269.443bn yuan in 2021, which will approximately double from 2016 to 2021.

The two proposed models can be used to forecast the trend of the system and are grown as an effective extension and supplement of the traditional multivariable grey forecasting models.

The forecast and analysis of the development prospects of high-tech industries would be useful for the government departments of Guangdong Province and professional forecasters to grasp the future of high-tech industries and formulate decision planning.

A new multivariable grey prediction model based on fractional order accumulation and its optimized model obtained by reconstructing the background value, which can improve the modelling accuracy of the traditional model, is proposed in this paper.

With the development of economy, China’s OFDI constantly increase in recent year. Meanwhile, OFDI has spillover effect on economic development and technological development of home country. Thus, accurate OFDI prediction is a prerequisite for the effective development of international investment strategies. The purpose of this paper is to predict China’s OFDI accurately using a novel multivariable grey prediction model with Fourier series.

This paper applied a multivariable grey prediction model, GM(1,N), to forecast China’s OFDI. In order to improve the prediction accuracy and without changing local characteristics of grey model prediction, this paper proposed a novel grey prediction model to improve the performance of the traditional GM(1,N) model by combining with residual modification model using GM(1,1) model and Fourier series.

The coefficients indicate that the export and GDP have positive influence on China’s OFDI, and, according to the prediction result, China’s OFDI shows a growing trend in next five years.

This paper proposed an effective multivariable grey prediction model that combined the traditional GM(1,N) model with a residual modification model in order to predict China’s OFDI. Accurate forecasting of OFDI provides reference for the Chinese Government to implement international investment strategies.

The purpose of this paper is to develop a general mathematic approach to model the microstructures of porous structures produced by additive manufacturing (AM), which will result in fractal surface topography and higher roughness that have greater influence on the performance of porous structures.

The overall shapes of pores were modeled by triply periodic minimal surface (TPMS), and the micro-roughness details attached to the overall pore shapes were represented by Weierstrass–Mandelbrot (W-M) fractal representation, which was integrated with TPMS along its normal vectors. An index roughly reflecting the irregularity of fractal TPMS was proposed, based on which the influence of the fractal parameters on the fractal TPMS was qualitatively analyzed. Two complex samples of real porous structures were given to demonstrate the feasibility of the model.

The fractal surface topography should not be neglected at a micro-scale level. In addition, a decrease in the fractal dimension D_s may exponentially make the topography rougher; an increase in the height-scaling parameter G may linearly increase the roughness; and the number of the superposed ridges has no distinct influence on the topography. Furthermore, the synthesis method is general for all implicit surfaces.

The method provides an alternative way to shift the posteriori design paradigm of porous media to priori design mode through numeric simulation. Therefore, the optimization of AM process parameters, as well as the porous structure, can be potentially realized according to specific functional requirement.

The synthesis of TPMS and W-M fractal geometry was accomplished efficiently and was general for all implicit freeform surfaces, and the influence of the fractal parameters on the fractal TPMS was analyzed more systematically.

To build a persistent map with visual landmarks is one of the most important steps for implementing the visual simultaneous localization and mapping (SLAM). The corner detector is a common method utilized to detect visual landmarks for constructing a map of the environment. However, due to the scale-variant characteristic of corner detection, extensive computational cost is needed to recover the scale and orientation of corner features in SLAM tasks. The purpose of this paper is to build the map using a local invariant feature detector, namely speeded-up robust features (SURF), to detect scale- and orientation-invariant features as well as provide a robust representation of visual landmarks for SLAM.

SURF are scale- and orientation-invariant features which have higher repeatability than that obtained by other detection methods. Furthermore, SURF algorithms have better processing speed than other scale-invariant detection method. The procedures of detection, description and matching of regular SURF algorithms are modified in this paper in order to provide a robust representation of visual landmarks in SLAM. The sparse representation is also used to describe the environmental map and to reduce the computational complexity in state estimation using extended Kalman filter (EKF). Furthermore, the effective procedures of data association and map management for SURF features in SLAM are also designed to improve the accuracy of robot state estimation.

Experimental works were carried out on an actual system with binocular vision sensors to prove the feasibility and effectiveness of the proposed algorithms. EKF SLAM with the modified SURF algorithms was applied in the experiments including the evaluation of accurate state estimation as well as the implementation of large-area SLAM. The performance of the modified SURF algorithms was compared with those obtained by regular SURF algorithms. The results show that the SURF with less-dimensional descriptors is the most suitable representation of visual landmarks. Meanwhile, the integrated system is successfully validated to fulfill the capabilities of visual SLAM system.

The contribution of this paper is the novel approach to overcome the problem of recovering the scale and orientation of visual landmarks in SLAM tasks. This research also extends the usability of local invariant feature detectors in SLAM tasks by utilizing its robust representation of visual landmarks. Furthermore, data association and map management designed for SURF-based mapping in this paper also give another perspective for improving the robustness of SLAM systems.

The purpose of this paper is to solve the problem that the qualitative relative factors cannot be employed in traditional multivariate grey models.

First, a new model is constructed though introducing dummy drivers. Then, the parameters estimation method and recursive function of the model are discussed. Furthermore, dummy driver setting, pre and post test methods of dummy drivers are proposed. At last, the per capita income forecasting of rural residents in Henan province of China is solved with the proposed model.

The proposed model is the reasonable extension of original one. The accuracy of it is higher than former model. In the case study, the forecasting results of proposed model are compared with other grey forecasting models, and prove that proposed model has not only high accuracy, but also clear physical meaning.

The method proposed in the paper could be used in policy effect measure, marketing forecasting, etc., when the predictor variables are influenced by some qualitative variables.

It will promote the accuracy of multivariate grey forecasting model.