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This paper aim to solve the problem of low assembly success rate for 3c assembly lines designed based on classical control algorithms due to inevitable random disturbances and other factors,by incorporating intelligent algorithms into the assembly line, the assembly process can be extended to uncertain assembly scenarios.

This work proposes a reinforcement learning framework based on digital twins. First, the authors used Unity3D to build a simulation environment that matches the real scene and achieved data synchronization between the real environment and the simulation environment through the robot operating system. Then, the authors trained the reinforcement learning model in the simulation environment. Finally, by creating a digital twin environment, the authors transferred the skill learned from the simulation to the real environment and achieved stable algorithm deployment in real-world scenarios.

In this work, the authors have completed the transfer of skill-learning algorithms from virtual to real environments by establishing a digital twin environment. On the one hand, the experiment proves the progressiveness of the algorithm and the feasibility of the application of digital twins in reinforcement learning transfer. On the other hand, the experimental results also provide reference for the application of digital twins in 3C assembly scenarios.

In this work, the authors designed a new encoder structure in the simulation environment to encode image information, which improved the model’s perception of the environment. At the same time, the authors used the fixed strategy combined with the reinforcement learning strategy to learn skills, which improved the rate of convergence and stability of skills learning. Finally, the authors transferred the learned skills to the physical platform through digital twin technology and realized the safe operation of the flexible printed circuit assembly task.

The purpose of this paper is to examine the impact of social media sharing on tourists’ willingness to pay more (WPM) at destinations. The moderating effects of tourists’ preferred route in decision-making or obtaining information (i.e. central or peripheral routes) were also examined.

A theoretical model was developed and tested using partial least squares structural equation modeling (PLS-SEM). Moderating effects of central and peripheral routes were tested using PLS multi-group analysis. Data were collected from 478 tourists in Antalya, Turkey, a sea, sun and sand tourist destination.

Findings indicate that importance attached to participant sharing (IPS) and importance attached to non-participant sharing (INPS) are significant antecedents of tourists’ WPM intentions. Moderating effects of tourists’ preferred route in decision-making reveal that the effect of IPS on WPM intention is more influential for those with high central route preferences than those with low central route preferences. While the effects of INPS and IPS on WPM intention is more determinative for those with higher peripheral route preferences.

Although it is known by the practitioners that consumer-generated contents are important, this research suggests and supports that these contents trigger tourists to pay higher prices.

How WPM is motivated by others’ social media sharing was not very clear in the literature. Therefore, this research gap was addressed in part by examining the social media sharing structure in terms of whether others posted on organization-related sites or on personal sites.

标题探索可能性路线在用户生成内容和支付意愿关系中的作用

本研究旨在探讨社交媒体分享对旅游者在目的地的支付意愿（WPM）的影响。还考察了旅游者在决策或获取信息时偏好路线（即中心或外围路线）的调节效应。

本文利用偏最小二乘结构方程模型（PLS-SEM）建立了理论模型并进行了验证, 使用PLS多组分析法检验了中心和外围路线的调节作用。从土耳其安塔利亚的478名游客中收集了数据。安塔利亚是一个拥有海洋、阳光和沙滩的旅游胜地。

结果表明, 游客对参与式分享（IPS）的重视程度和对非参与式分享（INPS）的重视程度是游客支付意愿 (WPM) 的显著前因。旅游者偏好路线在决策中的调节效应表明, IPS对WPM意图的影响, 对中心路线偏好高的游客比中心路线偏好低的游客更为显著。而INPS和IPS对WPM意图的影响对周边路线偏好较高者更具决定性。

尽管用户生成内容的重要性广为从业人员了解, 但本研究表明, 这些内容还能促使游客支付更高的价格。

在现有文献中, 他人的社交媒体分享是如何激励产生WPM的还不是很清楚。因此, 本文通过考察社交媒体分享的结构来填补这一研究空白, 即考察他人的内容是发布在组织相关的网站上还是个人网站上。

关键词: 社交媒体分享, 精化可能性模型, 中心路线, 外围路线, 支付意愿

研究论文

El papel de las rutas ELM (modelo de probabilidad de elección) en la relación entre el contenido generado por usuarios y la disposición a pagar

El propósito de esta investigación es examinar el impacto de la compartición en redes sociales con la disposición de los turistas a pagar más (willness pay more: WPM) en los destinos. También se examinaron los efectos moderadores de la ruta preferida de los turistas en la toma de decisiones u obtención de información (es decir, rutas centrales o periféricas).

Se desarrolló y probó un modelo teórico utilizando modelos de ecuaciones estructurales de mínimos cuadrados parciales (PLS-SEM). Los efectos moderadores de las rutas centrales y periféricas se probaron mediante análisis multigrupo de PLS. Se recopilaron datos de 478 turistas en Antalya, Turquía, un destino turístico de mar, sol y arena.

Los resultados indican que la importancia atribuida a la compartición de los participantes (importance participant sharing: IPS) y la importancia atribuida al la compartición de los no participantes (importance no participant saharing: INPS) son antecedentes importantes de las intenciones de los WPM de los turistas. Los efectos moderadores de la ruta preferida de los turistas en la toma de decisiones revelan que el efecto de IPS en la intención de WPM es más influyente para aquellos con altas preferencias de ruta central que aquellos con bajas preferencias de ruta central. Mientras que los efectos de INPS e IPS en la intención de WPM son más determinantes para aquellos con mayores preferencias de ruta periférica.

Aunque los profesionales saben que los contenidos generados por los consumidores son importantes, esta investigación sugiere y respalda que estos contenidos provocan que los turistas paguen precios más altos.

Al no estar clara en la literatura la relación de la WPM con la compartición en redes sociales y existir una brecha de investigación en este aspecto, este trabajo pretende abordar este tema, examinando la estructura de la compartición en redes sociales en términos de si otros publicaron en sitios relacionados con la organización o en sitios personales.

Compartición en redes sociales, Modelo de probabilidad de elección (ELM), Ruta Central, Ruta periférica, Disposición a pagar más

Trabajo de investigación

The purpose of this paper is to propose a whole set of methods for underwater target detection, because most underwater objects have small samples, low quality underwater images problems such as detail loss, low contrast and color distortion, and verify the feasibility of the proposed methods through experiments.

The improved RGHS algorithm to enhance the original underwater target image is proposed, and then the YOLOv4 deep learning network for underwater small sample targets detection is improved based on the combination of traditional data expansion method and Mosaic algorithm, expanding the feature extraction capability with SPP (Spatial Pyramid Pooling) module after each feature extraction layer to extract richer feature information.

The experimental results, using the official dataset, reveal a 3.5% increase in average detection accuracy for three types of underwater biological targets compared to the traditional YOLOv4 algorithm. In underwater robot application testing, the proposed method achieves an impressive 94.73% average detection accuracy for the three types of underwater biological targets.

Underwater target detection is an important task for underwater robot application. However, most underwater targets have the characteristics of small samples, and the detection of small sample targets is a comprehensive problem because it is affected by the quality of underwater images. This paper provides a whole set of methods to solve the problems, which is of great significance to the application of underwater robot.

The purpose of this paper is to examine the relationship between wine tourism experiences (i.e. winescape, winery service quality, winery brand differentiation and tourist motivation) and tourist behavioral intentions (satisfaction, loyalty and revisit intention) from both demand and supply perspectives in Ningxia, China, by using the SERVQUAL model and the self-determination theory.

The research comprises two studies with an exploratory sequential mixed-methods approach. Study 1 adopted semi-structured interviews with winery owners and managers to explore the factors related to wine tourism experiences that influence tourists’ tourism experience. The results from the Study 1 leads to Study 2, which used a survey to explore wine tourist experiences and their behavioral intentions

This study provided important information regarding the factors that influence wine tourists experience in Ningxia wine region from the perspectives of supply and demands sides. Frist, this study confirmed the various factors influence wine tourism experiences in Ningxia based on the results from Study 1 (supply perspectives). Second, by further investigation in the Study 1, this study integrates the SERVQUAL model and the self-determination theory as fundamental theoretical frameworks in Study 2 to analysis the tourist perspectives. Third, as results, the authors finally confirmed the theoretical frameworks of wine tourism in Ningxia based on dual supply-demand perspectives.

The integration of multiple research approaches enriches the research findings and provides a more robust understanding of the wine tourism experiences in Ningxia.

The purpose of this paper is to use the stimulus-organism-response (S-O-R) paradigm to understand how the source characteristics of the local and foreign food vloggers impact perceptions associated with the consumption setting of food vlogs (FVs), that is, experiential value and authentic value, cultivate the experiences of parasocial interaction (PSI) and how they are channelized into behavioral and attitudinal dispositions of food tourists.

Following a survey research design, a sample of 418 participants with an interest in food-related touristic journeys was analyzed. Both Pakistani and foreign FVs about Peshawar, a historic city situated on the ancient silk route, were selected for a common reference point.

The reception of Pakistani and foreign food vloggers differed significantly, implying that source characteristics, especially perceived similarity with the food vlogger, are an essential factor in the case of FVs. FVs’ authentic and experiential values significantly nurtured the experiences of PSI and positively influenced viewers’ evaluation of vlogs. The experiences of PSI cultivated visit intentions towards a destination. However, their relationship with the destination’s food image was not significantly related. The favorable reception of FVs was positively associated with the destination’s food image and visit intentions.

The findings provide tourism and hospitality managers with suggestions on how to appreciate and incorporate the marketability of FVs into their destination marketing campaigns.

This study opens up new avenues of scholarly debate by comparing the local and foreign food vloggers’ source effectiveness in cultivating PSI experiences and resultant attitudinal and behavioral changes. This study adds to the emergent research stream of understanding the food vlogger–viewer relationship through the S-O-R framework.

Wine tourism is gaining increasing popularity among Chinese tourists, making it necessary to thoroughly examine tourist behavior. While online reviews posted by wine tourists have been extensively studied from the perspectives of destinations and wineries, the perspective of the tourists themselves has been overlooked. To address this gap, this study aims to identify significant attributes intrinsic to the tourism experiences of Chinese wine tourists by adopting a text-mining approach from a tourist-centric perspective.

The authors use topic modeling to extract these attributes, calculate topic intensity to understand tourists’ attention distribution across these attributes and conduct topical sentiment analysis to evaluate tourists’ satisfaction levels with each attribute. The authors perform importance-performance analyses (IPAs) using topic intensity and sentiment scores. Furthermore, the authors conduct semistructured in-depth interviews with Chinese wine tourists to gain insights into the underlying reasons behind the key findings.

The study identifies eleven attributes for domestic wine tourists and seven attributes for outbound wine tourists. From the reviews of both domestic and outbound tourists, three common attributes have been identified: “scenic view”, “wine tasting and purchase” and “wine knowledge”.

According to the results of the IPAs, there is a pressing need for enhancements in the wine tasting and purchasing experience at domestic wine attractions. Additionally, managers of domestic wine attractions should continue to prioritize the positive aspects of the family trip experience and scenic views. On the other hand, for outbound wine attractions, it is crucial for managers to maintain their efforts in providing opportunities for wine knowledge acquisition, ensuring scenic views and upholding the reputation of wine regions.

First, this study breaks new ground by adopting a tourist-centric perspective to extract significant attributes from real wine tourism reviews. Second, the authors conduct a comparative analysis between Chinese wine tourists who travel domestically and those who travel abroad. The third novel aspect of this study is the application of IPA based on textual review data in the context of wine tourism. Fourth, by integrating topic modeling with qualitative interviews, the authors use a mixed-method approach to gain deeper insights into the experiences of Chinese wine tourists.

Tourism is one of the upcoming service industry in India with high potentials for future growth, particularly in rural areas. Many potential barriers are affecting the growth of tourism in rural India. Therefore, it is essential to explore and prioritize the barriers to tourism growth in rural India.

Qualitative and quantitative responses from “16” experts related to tourism and hospitality management from central India are collected for this study. An integrated Multi-Criteria Decision Making (MCDM) based framework is adopted to identify and relate significant barriers to tourism growth in India.

The result of the study identified many significant barriers and their importance to tourism growth in rural India.

The findings of this study add to the knowledge base of tourism research in line with the previous literature. This study offers an in-depth understanding of barriers focusing on rural tourism growth and devising both the plan of action and the suggestive measures in dealing with rural tourism.

The study provides a robust framework by integrating Interpretive Structural Modelling(ISM) and Decision Making Trial and Evaluation Laboratory (DEMATEL) to explore and prioritizing the critical barriers to rural tourism growth in India. The results of this study can help the decision-maker to fundamentally improve the economy of India through the growth of rural tourism.