随着大数据和人工智能应用的发展,网络文本分析已成为旅游目的地形象感知的重要工具。该文以文本分析为脉络,从研究理论基础、国内外研究进展、技术发展与应用、研究发现与讨论等方面系统阐述了旅游目的地形象感知的内涵与特征、形成机...随着大数据和人工智能应用的发展,网络文本分析已成为旅游目的地形象感知的重要工具。该文以文本分析为脉络,从研究理论基础、国内外研究进展、技术发展与应用、研究发现与讨论等方面系统阐述了旅游目的地形象感知的内涵与特征、形成机制,得出了旅游目的地形象感知可以通过文本分析方法中的高频词提取、情感分析、语义网络构建等方法进行深入分析,挖掘出游客对目的地的认知、情感、形象感知特点;国内外学者在旅游目的地形象感知研究方面已有诸多探索,但存在跨文化旅游目的地形象感知研究不足、分析工具不够多模式整合应用等问题,未来应进一步加强技术与理论融合、加强旅游目的地形象感知研究的跨学科协作,为旅游目的地形象的优化和管理创造的创新提供支撑。With the development of big data and artificial intelligence applications, network text analysis has become an important tool for perceiving tourist destination images. This article takes text analysis as the main thread and systematically expounds on the connotation, characteristics, and formation mechanism of tourist destination image perception from aspects such as research theoretical basis, research progress at home and abroad, technology development and application, research findings and discussions. It is concluded that the perception of tourist destination images can be deeply analyzed through methods such as high-frequency word extraction, sentiment analysis, and semantic network construction in text analysis methods, so as to explore tourists’ cognitive, emotional, and image perception characteristics of the destination. Scholars at home and abroad have conducted many explorations in the research of tourist destination image perception. However, there are problems such as insufficient research on cross-cultural tourist destination image perception and insufficient multimodal integration and application of analysis tools. In the future, it is necessary to further strengthen the integration of technology and theory and interdisciplinary collaboration in the research of tourist destination image perception, so as to provide support for the optimization of tourist destination images and innovation in management.展开更多
随着环境保护意识的增强和绿色物流理念的推广,低碳发展逐渐成为各界关注的焦点。针对社区团购冷链产品的“网络中枢”中心仓选址优化问题,本文构建了以总成本最小化和碳排放强度最小化为双重目标的决策模型。在模型中引入碳排放强度等...随着环境保护意识的增强和绿色物流理念的推广,低碳发展逐渐成为各界关注的焦点。针对社区团购冷链产品的“网络中枢”中心仓选址优化问题,本文构建了以总成本最小化和碳排放强度最小化为双重目标的决策模型。在模型中引入碳排放强度等约束条件,通过加权处理兼顾成本与碳排放的优化需求,实现不同目标的单位和数量级差异消除,并提供动态调整的可能性。为求解该模型,本文采用遗传算法,最后结合实际数据对云南省某社区团购仓配网络体系进行优化分析。结果表明:(1) 在云南省设立昆明、曲靖、红河和大理四个中心仓库为最优方案;(2) 企业可依据低碳权重的不同设置,调整选址配置方案以更贴合社会发展的低碳导向。研究结论指出,该模型通过双目标优化兼顾碳排放和成本,能为社区团购网络体系的优化提供有效的借鉴。本文所建立的模型和设计的算法具有较好的实用性,可为不同区域的社区团购冷链产品提供低碳导向的选址优化决策支持。With the growing awareness of environmental protection and the promotion of green logistics concepts, low-carbon development has gradually become a focal point of attention across various sectors. Focusing on the optimization of the “network hub” central warehouse location for community group buying of cold chain products, this paper constructs a decision-making model with dual objectives of minimizing total costs and minimizing carbon emission intensity. The model incorporates constraints such as carbon emission intensity, and through weighted processing, it balances the optimization needs of cost and carbon emissions, eliminating the differences in units and magnitudes of different objectives, and providing the possibility for dynamic adjustments. To solve this model, this paper employs a genetic algorithm, and finally, it optimizes and analyzes the warehouse distribution network system of a community group buying in Yunnan Province using actual data. The results indicate that: (1) Establishing four central warehouses in Kunming, Qujing, Honghe, and Dali in Yunnan Province is the optimal solution;(2) Enterprises can adjust the location configuration plan according to different low-carbon weights to better align with the low-carbon orientation of social development. The research conclusion points out that the model, through dual-objective optimization, considers both carbon emissions and costs, and can provide effective reference for the optimization of community group buying network systems. The model established in this paper and the designed algorithm have good practicality and can provide decision support for low-carbon-oriented location optimization of cold chain products for community group buying in different regions.展开更多
本文研究中国A股上市物流企业ESG (环境、社会责任和公司治理)表现对绿色创新能力的影响,并考察数字化转型的调节作用。研究发现ESG表现正向影响绿色创新能力,其中社会责任的影响最为显著。数字化转型正向调节环境表现对绿色创新的影响...本文研究中国A股上市物流企业ESG (环境、社会责任和公司治理)表现对绿色创新能力的影响,并考察数字化转型的调节作用。研究发现ESG表现正向影响绿色创新能力,其中社会责任的影响最为显著。数字化转型正向调节环境表现对绿色创新的影响。此外,国有企业和东部地区物流企业在环境表现和社会责任方面对绿色创新的促进作用更明显。This paper examines the impact of ESG (environmental, social, and corporate governance) performance on the green innovation capability of A-share-listed logistics companies in China. It investigates the moderating effect of digital transformation. The study finds that ESG performance positively affects green innovation capability, with social responsibility having the most significant effect. Digital transformation positively moderates the impact of ESG performance on green innovation. In addition, state-owned enterprises (SOEs) and logistics companies in the eastern region have a more pronounced role in promoting green innovation regarding environmental performance and social responsibility.展开更多
近年来,供应链管理领域的数据量增长显著,将人工智能技术应用于供应链管理,对供应链的发展具有重要意义。为探究人工智能技术应用于供应链管理领域的研究热点和演化趋势,文章运用CiteSpace可视化分析软件,对Web of Science数据库核心合...近年来,供应链管理领域的数据量增长显著,将人工智能技术应用于供应链管理,对供应链的发展具有重要意义。为探究人工智能技术应用于供应链管理领域的研究热点和演化趋势,文章运用CiteSpace可视化分析软件,对Web of Science数据库核心合集中2013-2023年的518篇相关文献进行定量分析,分析内容包括发文时间、期刊分布、作者特征等,并通过构建高频关键词知识图谱、关键词频次统计等方法,揭示人工智能在供应链管理中的研究热点和前沿趋势。研究结果显示,该领域的研究热度呈上升趋势,预示着人工智能与供应链的结合仍有广阔的研究空间。展开更多
文摘随着大数据和人工智能应用的发展,网络文本分析已成为旅游目的地形象感知的重要工具。该文以文本分析为脉络,从研究理论基础、国内外研究进展、技术发展与应用、研究发现与讨论等方面系统阐述了旅游目的地形象感知的内涵与特征、形成机制,得出了旅游目的地形象感知可以通过文本分析方法中的高频词提取、情感分析、语义网络构建等方法进行深入分析,挖掘出游客对目的地的认知、情感、形象感知特点;国内外学者在旅游目的地形象感知研究方面已有诸多探索,但存在跨文化旅游目的地形象感知研究不足、分析工具不够多模式整合应用等问题,未来应进一步加强技术与理论融合、加强旅游目的地形象感知研究的跨学科协作,为旅游目的地形象的优化和管理创造的创新提供支撑。With the development of big data and artificial intelligence applications, network text analysis has become an important tool for perceiving tourist destination images. This article takes text analysis as the main thread and systematically expounds on the connotation, characteristics, and formation mechanism of tourist destination image perception from aspects such as research theoretical basis, research progress at home and abroad, technology development and application, research findings and discussions. It is concluded that the perception of tourist destination images can be deeply analyzed through methods such as high-frequency word extraction, sentiment analysis, and semantic network construction in text analysis methods, so as to explore tourists’ cognitive, emotional, and image perception characteristics of the destination. Scholars at home and abroad have conducted many explorations in the research of tourist destination image perception. However, there are problems such as insufficient research on cross-cultural tourist destination image perception and insufficient multimodal integration and application of analysis tools. In the future, it is necessary to further strengthen the integration of technology and theory and interdisciplinary collaboration in the research of tourist destination image perception, so as to provide support for the optimization of tourist destination images and innovation in management.
文摘随着环境保护意识的增强和绿色物流理念的推广,低碳发展逐渐成为各界关注的焦点。针对社区团购冷链产品的“网络中枢”中心仓选址优化问题,本文构建了以总成本最小化和碳排放强度最小化为双重目标的决策模型。在模型中引入碳排放强度等约束条件,通过加权处理兼顾成本与碳排放的优化需求,实现不同目标的单位和数量级差异消除,并提供动态调整的可能性。为求解该模型,本文采用遗传算法,最后结合实际数据对云南省某社区团购仓配网络体系进行优化分析。结果表明:(1) 在云南省设立昆明、曲靖、红河和大理四个中心仓库为最优方案;(2) 企业可依据低碳权重的不同设置,调整选址配置方案以更贴合社会发展的低碳导向。研究结论指出,该模型通过双目标优化兼顾碳排放和成本,能为社区团购网络体系的优化提供有效的借鉴。本文所建立的模型和设计的算法具有较好的实用性,可为不同区域的社区团购冷链产品提供低碳导向的选址优化决策支持。With the growing awareness of environmental protection and the promotion of green logistics concepts, low-carbon development has gradually become a focal point of attention across various sectors. Focusing on the optimization of the “network hub” central warehouse location for community group buying of cold chain products, this paper constructs a decision-making model with dual objectives of minimizing total costs and minimizing carbon emission intensity. The model incorporates constraints such as carbon emission intensity, and through weighted processing, it balances the optimization needs of cost and carbon emissions, eliminating the differences in units and magnitudes of different objectives, and providing the possibility for dynamic adjustments. To solve this model, this paper employs a genetic algorithm, and finally, it optimizes and analyzes the warehouse distribution network system of a community group buying in Yunnan Province using actual data. The results indicate that: (1) Establishing four central warehouses in Kunming, Qujing, Honghe, and Dali in Yunnan Province is the optimal solution;(2) Enterprises can adjust the location configuration plan according to different low-carbon weights to better align with the low-carbon orientation of social development. The research conclusion points out that the model, through dual-objective optimization, considers both carbon emissions and costs, and can provide effective reference for the optimization of community group buying network systems. The model established in this paper and the designed algorithm have good practicality and can provide decision support for low-carbon-oriented location optimization of cold chain products for community group buying in different regions.
文摘本文研究中国A股上市物流企业ESG (环境、社会责任和公司治理)表现对绿色创新能力的影响,并考察数字化转型的调节作用。研究发现ESG表现正向影响绿色创新能力,其中社会责任的影响最为显著。数字化转型正向调节环境表现对绿色创新的影响。此外,国有企业和东部地区物流企业在环境表现和社会责任方面对绿色创新的促进作用更明显。This paper examines the impact of ESG (environmental, social, and corporate governance) performance on the green innovation capability of A-share-listed logistics companies in China. It investigates the moderating effect of digital transformation. The study finds that ESG performance positively affects green innovation capability, with social responsibility having the most significant effect. Digital transformation positively moderates the impact of ESG performance on green innovation. In addition, state-owned enterprises (SOEs) and logistics companies in the eastern region have a more pronounced role in promoting green innovation regarding environmental performance and social responsibility.
文摘近年来,供应链管理领域的数据量增长显著,将人工智能技术应用于供应链管理,对供应链的发展具有重要意义。为探究人工智能技术应用于供应链管理领域的研究热点和演化趋势,文章运用CiteSpace可视化分析软件,对Web of Science数据库核心合集中2013-2023年的518篇相关文献进行定量分析,分析内容包括发文时间、期刊分布、作者特征等,并通过构建高频关键词知识图谱、关键词频次统计等方法,揭示人工智能在供应链管理中的研究热点和前沿趋势。研究结果显示,该领域的研究热度呈上升趋势,预示着人工智能与供应链的结合仍有广阔的研究空间。
