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Blockchain is the latest ‘disruptive innovation’ that has caught scholars’ attention. It is the underlying technology for Bitcoin and other digital currencies. Stakeholders like developers, entrepreneurs, and technology enthusiasts claim blockchain has the potential to reconfigure the contemporary economic, legal, political and cultural landscape. Skeptics claim the concept and its applications remain ambiguous and uncertain. Business scholars began publishing studies on the emergence and impact of blockchain, bitcoin, and related projects in 2014. In this study, we conduct a PRISMA guided systematic review of blockchain research in the business literature from 2014 to 2018. Our results show a rapid increase of studies over the five year period. The findings also convey key insights about the current state of scholarly investigation on blockchain, including its top benefits and challenges for business and society. We found that blockchain remains an early-stage domain of research in terms of theoretical grounding, methodological diversity, and empirically grounded work. We suggest research directions to improve our understanding of the state of blockchain and advance future research of this increasingly important and expansive area. 相似文献
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为探讨大数据的概念及全球的研究现状,以Web of Science TM核心集合作为数据源,对时间为2010—2016年期间有关大数据的经济管理类核心期刊进行文献梳理研究,利用知识图谱法、共词分析法和引文分析法对大数据研究领域的基础知识、知识演进以及研究热点及趋势展开分析和评述。基于文献计量软件Citespace绘制出时区视图、聚类图等,得出对大数据概念的多视角理解以及研究热点和研究趋势。 相似文献
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How do the effects of cognitive openness and structural openness on the research impact of business scholars vary over their careers? By analysing a longitudinal sample of 35,296 scholars who published in business and management journals, we show that the cognitive openness and the structural openness of business scholars have non-linear relationships with their research impact. In particular, we found that, whereas moderate levels of cognitive openness and structural openness are desirable for increasing young scholars’ citations, a high level of cognitive openness and a low level of structural openness contribute to senior scholars’ citations. This study contributes to our understanding of different search behaviour across business scholars’ career paths and its implications for scholars’ research impact. 相似文献
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Crowd science: The organization of scientific research in open collaborative projects 总被引：1，自引：0，他引：1
A growing amount of scientific research is done in an open collaborative fashion, in projects sometimes referred to as “crowd science”, “citizen science”, or “networked science”. This paper seeks to gain a more systematic understanding of crowd science and to provide scholars with a conceptual framework and an agenda for future research. First, we briefly present three case examples that span different fields of science and illustrate the heterogeneity concerning what crowd science projects do and how they are organized. Second, we identify two fundamental elements that characterize crowd science projects – open participation and open sharing of intermediate inputs – and distinguish crowd science from other knowledge production regimes such as innovation contests or traditional “Mertonian” science. Third, we explore potential knowledge-related and motivational benefits that crowd science offers over alternative organizational modes, and potential challenges it is likely to face. Drawing on prior research on the organization of problem solving, we also consider for what kinds of tasks particular benefits or challenges are likely to be most pronounced. We conclude by outlining an agenda for future research and by discussing implications for funding agencies and policy makers. 相似文献
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《Information processing & management》2019,56(6):102095
Big data adoption is a process through which businesses find innovative ways to enhance productivity and predict risk to satisfy customers need more efficiently. Despite the increase in demand and importance of big data adoption, there is still a lack of comprehensive review and classification of the existing studies in this area. This research aims to gain a comprehensive understanding of the current state-of-the-art by highlighting theoretical models, the influence factors, and the research challenges of big data adoption. By adopting a systematic selection process, twenty studies were identified in the domain of big data adoption and were reviewed in order to extract relevant information that answers a set of research questions. According to the findings, Technology–Organization–Environment and Diffusion of Innovations are the most popular theoretical models used for big data adoption in various domains. This research also revealed forty-two factors in technology, organization, environment, and innovation that have a significant influence on big data adoption. Finally, challenges found in the current research about big data adoption are represented, and future research directions are recommended. This study is helpful for researchers and stakeholders to take initiatives that will alleviate the challenges and facilitate big data adoption in various fields. 相似文献
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《Information processing & management》2023,60(5):103449
Due to the vast volumes of newly streamed data on the Internet and social media, the use of sentiment analysis (SA) to extract information and analyze people's opinions has become a trendy topic. Yet, the majority of research are attributed to the English language, despite the fact that other languages, such as Arabic, are among the most popular on the Internet. Considering the availability of numerous dialects of this language and how their data were annotated and processed, the absence of research in this field is evident. Understanding these initiatives merits a great deal of attention in Arabic SA research. To the best of our knowledge, this domain has not been considered before, and thus the aim of this study is to perform a systematic review with regard to SA and data annotations for Arabic dialects published between 2015 and 2023. The outcomes of this research offer a refined taxonomy of data annotation methods classified into three categories: (1) manual, (2) automatic, and (3) hybrid methods. In addition, a discussion of the research challenges, motivations, and recommendations is presented with detailed taxonomy analysis of current research trends, and from this, we identify new research gaps and propose new research implications and future directions that will encourage more scholars to contribute to Arabic SA research, facilitate more successful multilingual SA applications, and provide insights regarding Arabic SA in different contexts. 相似文献
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《Information processing & management》2022,59(2):102853
Predicting the probability that a user will click on a specific advertisement has been a prevalent issue in online advertising, attracting much research attention in the past decades. As a hot research frontier driven by industrial needs, recent years have witnessed more and more novel learning models employed to improve advertising CTR prediction. Although extant research provides necessary details on algorithmic design for addressing a variety of specific problems in advertising CTR prediction, the methodological evolution and connections between modeling frameworks are precluded. However, to the best of our knowledge, there are few comprehensive surveys on this topic. We make a systematic literature review on state-of-the-art and latest CTR prediction research, with a special focus on modeling frameworks. Specifically, we give a classification of state-of-the-art CTR prediction models in the extant literature, within which basic modeling frameworks and their extensions, advantages and disadvantages, and performance assessment for CTR prediction are presented. Moreover, we summarize CTR prediction models with respect to the complexity and the order of feature interactions, and performance comparisons on various datasets. Furthermore, we identify current research trends, main challenges and potential future directions worthy of further explorations. This review is expected to provide fundamental knowledge and efficient entry points for IS and marketing scholars who want to engage in this area. 相似文献
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“大数据”作为时下最火热的IT行业的词汇,数据中隐藏着大量有价值的模式和信息,它的商业价值的利用逐渐成为行业人士争相追捧的利润焦点。在本篇文章中,探讨了中小企业在迎接大数据时代应注意什么,应做些什么,最终使中小企业在大数据时代中把握先机。 相似文献
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While the use of big data tends to add value for business throughout the entire value chain, the integration of big data analytics (BDA) to the decision-making process remains a challenge. This study, based on a systematic literature review, thematic analysis and qualitative interview findings, proposes a set of six-steps to establish both rigor and relevance in the process of analytics-driven decision-making. Our findings illuminate the key steps in this decision process including problem definition, review of past findings, model development, data collection, data analysis as well as actions on insights in the context of service systems. Although findings have been discussed in a sequence of steps, the study identifies them as interdependent and iterative. The proposed six-step analytics-driven decision-making process, practical evidence from service systems, and future research agenda, provide altogether the foundation for future scholarly research and can serve as a step-wise guide for industry practitioners. 相似文献
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A longitudinal study of the actual value of big data and analytics: The role of industry environment
Despite the popularity of big data and analytics (BDA) in industry, research regarding the economic value of BDA is still at an early stage. Little attention has been paid to quantifying the longitudinal impact of organizational BDA implementation on firm performance. Grounded in organizational learning theory, this study empirically demonstrates the impact of BDA implementation on organizational performance and how industry environment characteristics moderate the BDA-performance relationships. Using secondary data regarding BDA implementation from 2010 to February 2020, we find that BDA implementation has a significant impact on two types of business value creation: operational efficiency and business growth. Furthermore, the impact of BDA on operational efficiency is amplified in less dynamic and complex environments, while the BDA-business growth relationship is more pronounced in more dynamic, complex, and munificent environments. Collectively, this study provides a theory-centric understanding of BDA’s economic benefits. The findings offer insights to firms about what actual benefits BDA implementation may generate and how firms may align the use of BDA with the industry environments they are operating in. 相似文献
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公司政治关联国外研究新进展 总被引：1，自引：0，他引：1
公司政治关联问题引起了战略管理学者的广泛关注,正成为一个前景广阔的热点研究领域.本文系统回顾了最近几年本领域国外研究的新进展,突出了针对转型经济体公司政治关联研究的新贡献.本文试图梳理如下问题:公司政治关联会产生哪些效应;在什么条件下存在政治关联;其作用的发挥受到哪些因素调节;以何种方式进行而发挥作用.在总结目前研究局限的基础上,提出了未来四个主要研究方向. 相似文献
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《International Journal of Information Management》2016,36(5):748-758
The expansion of big data and the evolution of Internet of Things (IoT) technologies have played an important role in the feasibility of smart city initiatives. Big data offer the potential for cities to obtain valuable insights from a large amount of data collected through various sources, and the IoT allows the integration of sensors, radio-frequency identification, and Bluetooth in the real-world environment using highly networked services. The combination of the IoT and big data is an unexplored research area that has brought new and interesting challenges for achieving the goal of future smart cities. These new challenges focus primarily on problems related to business and technology that enable cities to actualize the vision, principles, and requirements of the applications of smart cities by realizing the main smart environment characteristics. In this paper, we describe the state-of-the-art communication technologies and smart-based applications used within the context of smart cities. The visions of big data analytics to support smart cities are discussed by focusing on how big data can fundamentally change urban populations at different levels. Moreover, a future business model of big data for smart cities is proposed, and the business and technological research challenges are identified. This study can serve as a benchmark for researchers and industries for the future progress and development of smart cities in the context of big data. 相似文献
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The integration of products and services into a bundled product/service offering by manufacturing organisations is seen as a global trend in today’s competitive business environment. The shift of product-based manufacturers towards offering business solutions and value-added services to consumers is termed as ‘Servitization’. Contrary to the potential benefits expected by adding service activities to the offerings, advocates voice their concerns towards experiential problems and challenges in employing the servitization strategy – termed as ‘Servitization Paradox’. Nevertheless, the shift from product-based delivery to a service-based provision has the potential to significantly impact on developing sustainable and eco-friendly environment. To provide greater insights to the servitization phenomenon, this paper presents a comprehensive analysis of the servitization implementation in manufacturing organisations. In order to respond to the latter, we propose the following three research questions “Q1 – what are the different types of servitization strategies”, “Q2 – what are the different servitization definitions”, “Q3 – what are the potential benefits in selecting a servitization strategy?”, “Q4 – what are the challenges in transitioning towards servitization?”. A systematic literature review is carried out to understand the past trends and extant patterns/themes in the servitization strategy research area, evaluate contributions, summarise knowledge, thereby identifying limitations, implications and potential further research avenues. The key findings confirm servitization studies have contributed both conceptually and empirically to the development and accumulation of intellectual wealth to the manufacturing operations and supply chain discipline. Moreover, the findings clearly indicate the potential of servitization in transitioning manufacturing organisations (e.g. benefits) and utilising innovative technologies to generate business value. Nevertheless, some voices are backing further research/development in the area of servitization due to the several existing challenges. 相似文献
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Recently, patient safety and healthcare have gained high attention in professional and health policy-makers. This rapid growth causes generating a high amount of data, which is known as big data. Therefore, handling and processing of this data are attracted great attention. Cloud computing is one of the main choices for handling and processing of this type of data. But, as far as we know, the detailed review and deep discussion in this filed are very rare. Therefore, this paper reviews and discusses the recently introduced mechanisms in this field as well as providing a deep analysis of their applied mechanisms. Moreover, the drawbacks and benefits of the reviewed mechanisms have been discussed and the main challenges of these mechanisms are highlighted for developing more efficient healthcare big data processing techniques over cloud computing in the future. 相似文献
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Surabhi Verma Som Sekhar Bhattacharyya Saurav Kumar 《Information processing & management》2018,54(5):791-806
Research on the adoption of systems for big data analytics has drawn enormous attention in Information Systems research. This study extends big data analytics adoption research by examining the effects of system characteristics on the attitude of managers towards the usage of big data analytics systems. A research model has been proposed in this study based on an extensive review of literature pertaining to the Technology Acceptance Model, with further validation by a survey of 150 big data analytics users. Results of this survey confirm that characteristics of the big data analytics system have significant direct and indirect effects on belief in the benefits of big data analytics systems and perceived usefulness, attitude and adoption. Moreover, there are mediation effects that exist among the system characteristics, benefits of big data analytics systems, perceived usefulness and the attitude towards using big data analytics system. This study expands the existing body of knowledge on the adoption of big data analytics systems, and benefits big data analytics providers and vendors while helping in the formulation of their business models. 相似文献
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近年来,大数据引起了产业界、学术界以及政府部门的高度关注。高校作为我国科研创新的重要基地,科研信息化水平极大影响到高校创新事业的发展。目前我国高校科技管理信息化存在数据共享度比较低,科技产出数据零散不系统,数据的质量不理想,信息化数据的利用率低等问题。论文简要阐述了大数据的概念以及传统模式下的科研管理的挑战,并提出了基于大数据技术的科研管理信息化集成解决方案。 相似文献
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Srinivas Nidhra Muralidhar Yanamadala Wasif Afzal Richard Torkar 《International Journal of Information Management》2013