Since the outbreak of COVID-19,tourists have been increasingly concerned over various risks of international travel,while knowledge of the pandemic appears to vary significantly.In addition,as travel restrictions cont...Since the outbreak of COVID-19,tourists have been increasingly concerned over various risks of international travel,while knowledge of the pandemic appears to vary significantly.In addition,as travel restrictions continue to impact adversely on international tourism,tourism efforts should be placed more on the domestic markets.Via structural equation modeling,this study unearthed different risk factors impacting Korean travelers’choices of alternative local destinations in the post-pandemic era.In addition,this study extended the goal-directed behavior framework with the acquisition of perceived risk and knowledge of COVID-19,which was proven to hold a sig-nificantly superior explanatory power of tourists’decisions of local alternatives over foreign countries during the COVID-19 pandemic.Furthermore,desire was found to play an imminent mediating role in the conceptual mod-el,maximizing the impact of perceived risk on travel intentions.Henceforth,this research offers meaningful the-oretical implication as thefirst empirical study to deepen the goal-directed behaviour framework with perceived risk and knowledge in the context of post-COVID-19 era.It also serves as insightful knowledge for Korean tour-ism authorities and practitioners to understand local tourists’decision-making processes and tailor effective recovery strategy for domestic tourism.展开更多
绿色出行的引导效果受政策及出行者选择偏好影响,需要考虑不同类型的低碳引导政策和出行者的异质性。为定量分析政策和出行者异质性对出行行为的影响,将政策分为三种:经济、便利和公共信息政策感知,基于521份绿色出行问卷调查数据,采用K...绿色出行的引导效果受政策及出行者选择偏好影响,需要考虑不同类型的低碳引导政策和出行者的异质性。为定量分析政策和出行者异质性对出行行为的影响,将政策分为三种:经济、便利和公共信息政策感知,基于521份绿色出行问卷调查数据,采用K-means聚类将出行者划分为享乐型组(60.7%)和实用型组(39.3%)。偏最小二乘法结构方程模型(partial least square method of structural equation model, PLS-SEM)的结果表明:在出行者绿色出行行为中,若不考虑出行者的异质性,可能高估或低估政策对出行者绿色出行意向的影响;享乐型组的绿色出行意向受公共信息政策感知的影响大于实用型组,受经济政策感知的影响小于实用型组;公共信息政策是引导享乐型组和实用型组绿色出行最重要的政策措施。展开更多
构建了基于BERT的双向连接模式BERT-based Bi-directional Association Model(BBAM)以实现在意图识别和槽位填充之间建立双向关系的目标,来实现意图识别与槽位填充的双向关联,融合两个任务的上下文信息,对意图识别与槽位填充两个任务之...构建了基于BERT的双向连接模式BERT-based Bi-directional Association Model(BBAM)以实现在意图识别和槽位填充之间建立双向关系的目标,来实现意图识别与槽位填充的双向关联,融合两个任务的上下文信息,对意图识别与槽位填充两个任务之间的联系进行深度挖掘,从而优化问句理解的整体性能.为了验证模型在旅游领域中的实用性和有效性,通过远程监督和人工校验构建了旅游领域问句数据集TFQD(Tourism Field Question Dataset),BBAM模型在此数据集上的槽填充任务F 1值得分为95.21%,意图分类准确率(A)为96.71%,整体识别准确率(A_(sentence))高达89.62%,显著优于多种基准模型.所提出的模型在ATIS和Snips两个公开数据集上与主流联合模型进行对比实验后,结果表明其具备一定的泛化能力.展开更多
Determining the travel intention of residents with shared electric vehicles(EVs)is significant for promoting the development of low-carbon transportation,considering that common problems such as high idle rate and lac...Determining the travel intention of residents with shared electric vehicles(EVs)is significant for promoting the development of low-carbon transportation,considering that common problems such as high idle rate and lack of attractiveness still exist.To this end,a structural equation model(SEM)based on the theory of multiple motivations is proposed in this paper.First,the influencing motivations for EV sharing are divided into three categories:consumer-driven,program-driven,and enterprise-driven motivations.Then,the intentions of residents in Shanghai to travel with shared EVs are obtained through a survey questionnaire.Finally,an SEM is constructed to analyze quantitatively the impact of different motivations on the travel intention.The results show that consumer-driven motivations with impact weights from 0.14 to 0.63 have the overwhelming impact on travel intention,compared to program-driven motivations with impact weights from−0.14 to 0.15 and enterprise-driven motivations with impact weights from 0.02 to 0.06.In terms of consumer-driven motivations,the weight of green travel awareness is the highest.The implications of these results on the policy to enable large-scale implementation of shared EVs are discussed from the perspectives of the resident,enterprise,and government.展开更多
基金supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(NRF-2020S1A5A2A01046684).
文摘Since the outbreak of COVID-19,tourists have been increasingly concerned over various risks of international travel,while knowledge of the pandemic appears to vary significantly.In addition,as travel restrictions continue to impact adversely on international tourism,tourism efforts should be placed more on the domestic markets.Via structural equation modeling,this study unearthed different risk factors impacting Korean travelers’choices of alternative local destinations in the post-pandemic era.In addition,this study extended the goal-directed behavior framework with the acquisition of perceived risk and knowledge of COVID-19,which was proven to hold a sig-nificantly superior explanatory power of tourists’decisions of local alternatives over foreign countries during the COVID-19 pandemic.Furthermore,desire was found to play an imminent mediating role in the conceptual mod-el,maximizing the impact of perceived risk on travel intentions.Henceforth,this research offers meaningful the-oretical implication as thefirst empirical study to deepen the goal-directed behaviour framework with perceived risk and knowledge in the context of post-COVID-19 era.It also serves as insightful knowledge for Korean tour-ism authorities and practitioners to understand local tourists’decision-making processes and tailor effective recovery strategy for domestic tourism.
文摘绿色出行的引导效果受政策及出行者选择偏好影响,需要考虑不同类型的低碳引导政策和出行者的异质性。为定量分析政策和出行者异质性对出行行为的影响,将政策分为三种:经济、便利和公共信息政策感知,基于521份绿色出行问卷调查数据,采用K-means聚类将出行者划分为享乐型组(60.7%)和实用型组(39.3%)。偏最小二乘法结构方程模型(partial least square method of structural equation model, PLS-SEM)的结果表明:在出行者绿色出行行为中,若不考虑出行者的异质性,可能高估或低估政策对出行者绿色出行意向的影响;享乐型组的绿色出行意向受公共信息政策感知的影响大于实用型组,受经济政策感知的影响小于实用型组;公共信息政策是引导享乐型组和实用型组绿色出行最重要的政策措施。
文摘构建了基于BERT的双向连接模式BERT-based Bi-directional Association Model(BBAM)以实现在意图识别和槽位填充之间建立双向关系的目标,来实现意图识别与槽位填充的双向关联,融合两个任务的上下文信息,对意图识别与槽位填充两个任务之间的联系进行深度挖掘,从而优化问句理解的整体性能.为了验证模型在旅游领域中的实用性和有效性,通过远程监督和人工校验构建了旅游领域问句数据集TFQD(Tourism Field Question Dataset),BBAM模型在此数据集上的槽填充任务F 1值得分为95.21%,意图分类准确率(A)为96.71%,整体识别准确率(A_(sentence))高达89.62%,显著优于多种基准模型.所提出的模型在ATIS和Snips两个公开数据集上与主流联合模型进行对比实验后,结果表明其具备一定的泛化能力.
基金the National Natural Science Founda-tion of China(Nos.71971139 and 72201172)。
文摘Determining the travel intention of residents with shared electric vehicles(EVs)is significant for promoting the development of low-carbon transportation,considering that common problems such as high idle rate and lack of attractiveness still exist.To this end,a structural equation model(SEM)based on the theory of multiple motivations is proposed in this paper.First,the influencing motivations for EV sharing are divided into three categories:consumer-driven,program-driven,and enterprise-driven motivations.Then,the intentions of residents in Shanghai to travel with shared EVs are obtained through a survey questionnaire.Finally,an SEM is constructed to analyze quantitatively the impact of different motivations on the travel intention.The results show that consumer-driven motivations with impact weights from 0.14 to 0.63 have the overwhelming impact on travel intention,compared to program-driven motivations with impact weights from−0.14 to 0.15 and enterprise-driven motivations with impact weights from 0.02 to 0.06.In terms of consumer-driven motivations,the weight of green travel awareness is the highest.The implications of these results on the policy to enable large-scale implementation of shared EVs are discussed from the perspectives of the resident,enterprise,and government.
