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风险投资与“孵化器”都是创业企业成长的要素，风险投资以资本的方式培育企业，而“孵化器”则注重构筑企业的基础和良好的环境，二者与创业企业建立的是多赢互利的关系。基于这种互补性和一致性，在国外，“孵化器”对风险投资表现出强有力的助推作用，并与风险投资呈现出一种结合融合的态势。而在我国，风险投资与“孵化器”在很大程度上还是相互分离，风险投资并没有在“孵化器”作用下迅猛发展，二者也没有形成良性的融合联动。 相似文献
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入孵创业企业的道德风险长期制约着科技企业孵化器的融资行为。针对科技企业孵化器与互联网金融有机结合的新形势,构建科技企业孵化器、创业企业、风险投资三者间的演化博弈模型,并分析三方合作的稳定性。研究结果表明,借助互联网金融能够有效缓解信息不对称问题,提高融资成功率:当创业企业违约罚金期望值大于违约后的额外净收益时,创业企业必将选择诚信策略;而且降低科技企业孵化器努力成本、降低创业企业的融资目标和提高风险投资的投资预期收益有助于提高融资成功率。而当科技企业孵化器无法对创业企业进行有效监督时,创业企业必定选择投机——创业企业投机风险存在的必然性。 相似文献
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孵化器与风险投资都是创业型企业成长的孵化要素。两者在对创业企业的投资方向、价值实现途径上有很强的一致性。但同时在参与企业成长的阶段、与企业的关系、承担的风险以及服务层面上都有一定差异。在新经济下,不论对于创业型企业还是孵化器和风险投资,它们结成了一种“双赢互利”的关系。因此,孵化器与风险投资的融合必然越来越紧密,两者必将由“融合”到“结合”。 相似文献
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孵化器与风险投资融合的原因探究 总被引：1，自引：0，他引：1
孵化器与风险投资都是高新技术企业成长的孵化要素.两者在对高新技术企业的投资方向、价值实现途径上有很强的一致性.在新经济下,高新技术企业,孵化器和风险投资,它们结成了一种"多赢互利"的关系.因此,对我国孵化器、风险投资和高新技术企业发展瓶颈问题进行分析,探讨孵化器与风险投资融合的原因,对于促进高新技术企业、风险投资和孵化器的共同发展具有一定的现实意义. 相似文献
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以企业孵化器为研究对象,在继承和借鉴国内外科技企业孵化器与风险投资融合发展的研究成果基础上,对孵化器开展风险投资业务的障碍进行了分析,提出了我国企业孵化器开展风险投资的三种模式及其资金来源渠道,并指出企业孵化器应着力打造孵化器品牌、引进复合型专业人才、发挥专业孵化器优势,建立风险分担与补偿机制以及退出渠道建设来提升开展风险投资的能力。希望通过上述研究,指导孵化器更有效地开展风险投资,实现其自身的可持续发展,更好地服务于在孵企业和科技创新。 相似文献
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在对科技企业孵化器发展风险投资功能的背景分析基础上,理论分析和合理推测相结合,探讨引入风险投资功能可能给科技企业孵化器以及在孵企业发展带来的正反两方面效应,提出科技企业孵化器发展风险投资应慎重、投资机制需创新的观点。 相似文献
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范围经济是生产过程中存在的一种典型经济规律,企业孵化器与风险投资的融合由于实现了信息、创业网络和退出通道等的资源共享,从而具有了范围经济性。 相似文献
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知识管理和商务智能关系研究 总被引：1，自引：0，他引：1
知识管理和商务智能是改善决策者所获得信息和知识质量的两项核心技术.在概述知识管理和商务智能的基础上,从技术、处理过程、企业文化、加工深度、处理结果等角度对二者的共同点和不同点做了对比分析.对于知识管理(KM)和商务智能(BI)的关系,学术界有三种观点:(1)KM是BI的子系统;(2)BI是KM的帮手;(3)KM和BI是功能互补的系统.为了充分发挥两个系统的优势,弥补各自功能的不足,应该集成知识管理和商务智能.对知识管理和商务智能的三种集成方式做了分析,最后构建了KM和BI并重的集成模型. 相似文献
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The development of artificial intelligence (AI) technology expands the boundary of business practice, inducing the emergence and application of business intelligence (BI) that has promoted the transformation of information techniques to optimize business decision and operation. However, there is a lack of theoretical consensus and measurement of the technology embedded in BI at present. This study exploratively develops the Sense-Transform-Drive (STD) conceptual model of BI based on dynamic capabilities theory and organizational evolutionary theory to explain the core BI capabilities. By using factoring analysis and structural equation modeling analysis, we extract the latent constructs and empirically verify the validity of the STD model and further examine the correlation and mode of interaction of the three core BI capabilities and the impact of BI application on firm performance in the real economy with a sample contextual to Chinese business practices. The study results show that there are direct and high-intensity cumulative positive effects among the structural components of the STD conceptual model and BI-related dynamic capabilities can enhance operating efficiency and firm performance. 相似文献
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《Information processing & management》2020,57(6):102279
Evidently, online voice of customers (VoC) expressed in social media has emerged as quality data for researchers who are willing to conduct customer-driven business intelligence (BI) research. Nevertheless, to the best of authors’ knowledge, there is still a dearth of studies that deal with such remarkable research stream and address various open data (e.g., social media, intellectual property) from a BI research perspective. Therefore, this study has attempted to evaluate the applicability of social media data in BI research and provide a systematic review on the primary research articles in the domain. This study compared social media data with the other open data (e.g., gray literature, public government data) in terms of data content, collection, updatability and structure, which are determined through a thorough discussion with experts. Next, this study selected 57 social media-based BI research articles from the Web of Science (WoS) database and analyzed them with three research questions about the data, methodologies, and results to understand this research domain. Our findings are expected to inform the existing researchers in the research domain about the future research directions, enable newcomers to understand the overall process of analyzing social media data, and provide the practitioners with social media analysis approaches suitable for their environment. 相似文献
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As healthcare organizations continue to be asked to do more with less, access to information is essential for sound evidence-based decision making. Business intelligence (BI) systems are designed to deliver decision-support information and have been repeatedly shown to provide value to organizations. Many healthcare organizations have yet to implement BI systems and no existing research provides a healthcare-specific framework to guide implementation. To address this research gap, we employ a case study in a Canadian Health Authority in order to address three questions: (1) what are the most significant adverse impacts to the organization's decision processes and outcomes attributable to a lack of decision-support capabilities? (2) what are the root causes of these impacts, and what workarounds do they necessitate? and (3) in light of the issues identified, what are the key considerations for healthcare organizations in the early stages of BI implementation? Using the concept of co-agency as a guide we identified significant decision-related adverse impacts and their root causes. We found strong management support, the right skill sets and an information-oriented culture to be key implementation considerations. Our major contribution is a framework for defining and prioritizing decision-support information needs in the context of healthcare-specific processes. 相似文献
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The business intelligence (BI) has been often touted as a game-changer especially during the pandemic crisis. Although most managers are familiar with BI and agree that, it should be operationalized across their organizations. The BI is not well assimilated throughout adopting organizations. Rooted in institutional and upper echelon theories, this study proposes a theoretical model aimed toward explaining BI assimilation. We surveyed 174 respondents occupying leadership positions from174 auto-components manufacturing firms in India to gather data. The findings suggest that normative and mimetic (but not coercive) factors significantly influence top leader’s commitment to the BI initiatives. We found that the commitment of the top leaders influences the assimilation of BI via acceptance and routinization. Our study is an attempt to address the previous research calls related to BI assimilation. The findings of the study inform the information management scholars via theory-based research on phenomena related to post-adoption BI diffusion during a pandemic crisis. Practitioners can utilize the results of our study to design their policies that help assimilate BI such that forecasted benefits can be fully realized during an uncertain time. 相似文献
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《International Journal of Information Management》2014,34(2):272-284
Company movements and market changes often are headlines of the news, providing managers with important business intelligence (BI). While existing corporate analyses are often based on numerical financial figures, relatively little work has been done to reveal from textual news articles factors that represent BI. In this research, we developed BizPro, an intelligent system for extracting and categorizing BI factors from news articles. BizPro consists of novel text mining procedures and BI factor modeling and categorization. Expert guidance and human knowledge (with high inter-rater reliability) were used to inform system development and profiling of BI factors. We conducted a case study of using the system to profile BI factors of four major IT companies based on 6859 sentences extracted from 231 news articles published in major news sources. The results show that the chosen techniques used in BizPro – Naïve Bayes (NB) and Logistic Regression (LR) – significantly outperformed a benchmark technique. NB was found to outperform LR in terms of precision, recall, F-measure, and area under ROC curve. This research contributes to developing a new system for profiling company BI factors from news articles, to providing new empirical findings to enhance understanding in BI factor extraction and categorization, and to addressing an important yet under-explored concern of BI analysis. 相似文献
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Extant research on technology acceptance has devoted considerable attention to the relationship between behavioral intention (BI) and system use (SU) over time. However, the empirical results have been mixed—studies have found BI to both influence and not influence SU. Studies that examined the BI→SU relationship have employed different research models and research designs. Prior research models have examined direct effects on SU, indirect effects on SU through BI, the moderator effects on BI→SU, and the mediating role of BI in BI→SU. Studies have employed different types of respondents, information technologies, geographic regions, voluntariness, and measurement designs. This study proposes that such differences in research models and designs contribute to the mixed results for BI→SU, and reports a meta-analysis of findings reported in 113 prior studies along with a critical review of the BI→SU relationship. While no significant differences were found in the results for the BI→SU relationship across various research design characteristics, this study finds that the measurement of SU has been conflated with future and current or past behavior, direct and indirect effects on SU impact BI→SU, BI is modeled to fully and partially mediate the effects of other variables on SU, and moderators for the BI→SU relationship may be necessary. This study identifies several directions for future research and underlines the need to rethink the link between BI and SU. 相似文献
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《Information processing & management》2023,60(4):103380
Business Intelligence (BI) seeks to increase the profitability of the organization by making intelligent and accurate decisions. Management accounting (MA) reports are the score-card of an operation manager's efficiency. The operational; tactical, and strategic decision types make the road to achieving the goals of a company. Further, Environmental factors may affect the supply chain or increase the costs of materials. This study aims to investigate the impact of the BI on the development of MA in industrial companies. Samples are 200 Managers of these companies. The researcher-made questionnaire was employed to collect the required data. Factor analysis by reliability and item content technique verified by 0.896 Cronbach's alpha. Results revealed that the impact of BI on the development of MA is meaningful. For the β-values, the highest and the lowest effect of variables on success of BI is for decision type and flexibility variables, respectively. However, For the t-values, it is for data quality and integration with other systems (IOS) variables, respectively. Managers in industrial companies, should pay attention to decision type and data quality more than flexibility and IOS. 相似文献