产业融合与黑龙江省冰雪旅游产业竞争力提升

近年来,随着国内外市场竞争日益激烈,黑龙江冰雪旅游产业受到严重的挑战。如何通过创新,不断提高黑龙江冰雪旅游产业的竞争力,在激烈的市场竞争中继续保持领先地位,是黑龙江冰雪旅游产业急需解决的问题。本文从产业融合的视角,利用波特的钻石理论模型,分析得出,通过推动冰雪旅游产业与相关产业的融合,有利于提升冰雪旅游产业的竞争力,并提出了放松政府管制、促进生产要素融合、加强需求引导、构建产业集群以及培育旅游企业集团等促进冰雪旅游产业融合、提升黑龙江省冰雪旅游产业竞争力的对策。     

文化视角下哈尔滨市冰雪旅游产业发展策略

为贯彻习近平总书记在2016年两次对龙江重要讲话中指出的"两山理论",哈尔滨市正积极优化冰雪旅游产业。哈尔滨拥有丰富的冰雪自然资源和浓厚的冰雪文化资源,为发展冰雪旅游产业提供得天独厚的优势。通过利用旅游产业集群的相关理论,分析哈尔滨市冰雪旅游产业的优势和存在问题,提出优化核心层、加强要素供应层衔接度、完善相关辅助层建设、建立冰雪文化基地的哈尔滨冰雪旅游产业的发展策略。     

基于“互联网+全域旅游”融合模式研究——江西省旅游产业融合模式剖析

"互联网+"代表着一种新的经济形态,它是依托互联网信息技术实现互联网与传统产业的联合,以优化各产业要素、更新业务体系、重新构建新的商务模式来完成经济转型和升级。全域旅游突破了以景区为核心的"景点旅游"制约,把旅游目的地城市变成一个不收门票的大景区,丰富了旅游的内涵,打通了旅游产业发展瓶颈,创造了新的经济增长模式。"互联网+全域旅游"则是利用互联网、移动电子商务等高新技术,应用于旅游产业而形成的一种崭新的产业经济融合模式,已成为一种全新的旅游业态和新的经济增长点。推进"互联网+全域旅游"融合模式是我国新阶段旅游产业发展战略的再定位,对"互联网+全域旅游"融合模式的研究更是具有深远意义。     

“互联网+”下的时代的旅游产业融合探讨

随着当前科学技术发展以及社会经济的飞速发展,互联网技术得到较为迅猛的发展,互联网时代到来,同时对于生产生活多个领域产生重大的影响,互联网时代到来对于当前旅游行业而言,一方面提供了更大发展空间以及更大的发展机遇;另一方面也带来了严峻的挑战,本文主要是关于互联网+时代旅游产业融合研究和探讨,以供相关专业人士进行参考和借鉴。     

促进龙江冰雪旅游产业发展对策研究

目前,冰雪旅游产业是黑龙江省重点发展的文化产业之一,在推动黑龙江省经济发展,促进冰雪产业间相互融合,树立黑龙江省品牌效应方面都起到了无可替代的作用。针对黑龙江省冰雪旅游产业发展中存在的不足,提出应加大财税政策支持力度,加快产业融合,加强人才培养,强化金融支持,加大宣传力度。     

假日经济与体育冰雪旅游产业发展对策研究

以我国目前假日经济为研究背景,阐述了体育冰雪旅游产业发展的可能性和必要性,揭示了体育冰雪旅游产业发展现存的主要问题,提出了相应的对策。旨在丰富我国体育冰雪旅游产业的理论研究,并为体育冰雪旅游产业发展提供思路。     

新发展理念视角下黑龙江省冰雪旅游产业发展对策研究

依托全国冰雪旅游发展黄金时代的大背景,结合四个理念,通过文献分析、实际调研,对黑龙江省冰雪旅游产业进行深入分析。面对冬奥会的冲击、新兴冰雪势力的崛起,以及黑龙江省冰雪旅游长久以来不能有实质性进展,从优势、劣势、机遇、挑战四个方面对黑龙江省冰雪旅游产业进行全面剖析,并从创新、协调、绿色、开放、共享角度提出提升竞争力的对策建议。     

沈阳市“冰雪旅游”发展现状及对策分析

冰雪旅游是一项集观光、娱乐、休闲于一体的旅游产品。沈阳丰富的冰雪资源和优越的地理位置,成为沈阳发展冰雪旅游业的基础。沈阳市的冰雪旅游虽然起步较晚,但是发展速度快,过快的发展速度势必存在一定的隐患,在现在的发展过程中沈阳市的冰雪旅游市场存在的问题日益显露出来。在未来的发展过程中,沈阳市应结合现在发现的问题,明确目标,确定发展方向。为此,对沈阳市冰雪旅游的发展现状及存在的问题做出简单分析,并提出相应对策,旨在使沈阳冰雪旅游市场逐渐完善。     

体育消费视域下冰雪体育旅游产业发展问题研究

随着社会经济的快速发展和居民生活水平的提升,大众对消费需求的满足已从"物质层面"转向到"精神层面",体育消费在满足大众健康需求中起着重要作用,在冬奥会成功申办的影响下冰雪体育旅游受到更多人的关注。本文从分析体育消费影响因素入手,剖析了黑龙江省冰雪体育旅游产业的现状,提出了为满足消费者需求的黑龙江冰雪体育旅游产业发展方式。     

一种数据链集成架构

目前数据链集成需要统一的解决方案。通过对美军数据链集成发展现状的分析,给出了一种基于统一的软/硬件接口标准,通过构建通用信息处理服务、通用多数据链平台接口和通用数据链端机接口来实现的一种集成框架,并给出了典型平台集成应用,提出了实现该架构的关键技术,可以有效解决数据链平台集成和多链集成应用问题。     

大数据在海基测控联合信息环境中的应用构想

针对海基测控领域存在的信息化烟囱、数据孤岛、信息安全等问题,开展了大数据在海基测控领域的应用研究,提出了基于大数据构建海基测控联合信息环境的系统架构和运行模式,对构建联合信息环境的相关技术进行了探索分析,应用大数据技术实现广域分布式环境下数据、信息和信息技术服务共享,将数据优势转换为信息优势,进而发挥决策优势。     

Cross-national differences in big data analytics adoption in the retail industry

Big data analytics (BDA) has emerged as a significant area of research for both researchers and practitioners in the retail industry, indicating the importance and influence of solving data-related problems in contemporary business organization. The present study utilised a quantitative-methods approach to investigate factors affecting retailers' adoption of BDA across three countries. A survey questionnaire was used to collect data from managers and decision-makers in the retail industry. Data of 2278 respondents were analysed through structural equation modelling. The findings revealed that security concerns, external support, top management support, and rational decision making culture have a greater effect on BDA adoption in developed countries UK than in UAE and Egypt. However, competition intensity and firm size have a greater effect on BDA adoption in UAE and Egypt than in UK. Finally, human variables (competence of information system's staff and staff's information system knowledge) have a greater effect on BDA adoption in Egypt than UK and UAE. The findings indicate that a “one-size-fits-all” approach is insufficient in capturing the heterogeneity of managers across countries. Implications for practice and theory were demonstrated.     

基于多维大数据的江西投资景气预警体系构建研究

为了提高江西省经济高质量发展下投资景气预警指数预警的科学性和精确性,基于与投资相关的多维大数据,结合宏观经济数据的经济预警分析方法,构建了投资景气预警指数体系。利用时差相关分析法与K-L信息量法选择指标,通过合成指数与预警指数构建了江西省投资景气预警指数及红绿灯号,进而对结果进行实证分析。     

Uncovering the message from the mess of big data

User-generated content, such as online product reviews, is a valuable source of consumer insight. Such unstructured big data is generated in real-time, is easily accessed, and contains messages consumers want managers to hear. Analyzing such data has potential to revolutionize market research and competitive analysis, but how can the messages be extracted? How can the vast amount of data be condensed into insights to help steer businesses’ strategy? We describe a non-proprietary technique that can be applied by anyone with statistical training. Latent Dirichlet Allocation (LDA) can analyze huge amounts of text and describe the content as focusing on unseen attributes in a specific weighting. For example, a review of a graphic novel might be analyzed to focus 70% on the storyline and 30% on the graphics. Aggregating the content from numerous consumers allows us to understand what is, collectively, on consumers’ minds, and from this we can infer what consumers care about. We can even highlight which attributes are seen positively or negatively. The value of this technique extends well beyond the CMO's office as LDA can map the relative strategic positions of competitors where they matter most: in the minds of consumers.     

Social media user behavior analysis applied to the fashion and apparel industry in the big data era

With the rapid development of the Internet and new media, the enormous data from social media and other public platforms have attracted increasing attention to user behavior research. Fashion is a hot topic for both the general public and the social economy, so there is great potential for exploring and manipulating social media data for the development of the fashion industry in the current era. This paper aims to explore the current status of social media user behavior analysis applied to the fashion and apparel industry for advanced product development, branding strategy planning and the resolution of other decision-making problems in the big data context. First, articles were retrieved from the database "Web of Science". With the assistance of experts, 201 articles were determined for further study. Next, the evolution of hot topics within the domain was visualized and discussed through bibliometric analysis. Then, the application of social media data in the fashion domain was investigated, and common data mining methods were discussed. Finally, the paper summarized the development status of social media user behavior analysis (SMUBA) applied to the fashion and apparel industry and put forward the future prospect under the framework of mass customization in the big data era.     

大型节事与地方旅游业可持续发展的机制研究

从大型节事和地方旅游业互动现状、现实意义和存在问题入手,系统地分析了影响节事旅游可持续发展的吸力、推力和支持力等要因,并构建了大型节事和地方旅游业可持续发展的机制框架系统模型来表明可持续发展系统中各因素的相互作用,以及推进节事旅游可持续发展的多元机制,提出了公众参与、政府支持、市场机制完善等实施保障。     

The intermediating role of big data analytics capability between responsive and proactive market orientations and firm performance in the retail industry

Big data analytics capability (BDAC) is the key resource for competitive advantage in the drastically changing market. Although some studies have investigated the impacts on firm performance, there is limited understanding of how firms enhance their BDAC. This study draws on organisational culture and investigates the effects of responsive and proactive market orientations on BDAC and firm performance. The results show that both responsive and proactive market orientations increase BDAC. Further, BDAC fully mediates the relationship between these two market orientations and firm performance. Our findings suggest that BDAC researchers should focus on market orientations that enhance BDAC.     

构建新发展格局下物流业与制造业深度融合发展研究

物流业与制造业深度融合发展是构建新发展格局的必然要求,近年来一些地方进行了积极实践,探索了多种深度融合发展模式。两业融合发展不仅有助于推动制造业的转型升级和创新业态模式的融合,而且有助于物流业与制造业的降本增效,提升经济社会整体效益。在构建新发展格局的背景下,应加强物流业与制造业深度融合发展的规划、加强物流业与制造业深度融合发展的要素保障、加快物流业与制造业供应链综合服务商的培育、注重制造业供应链体系全球化专业化水平的提升,不断推动物流业与制造业深度融合发展。