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1.
AI has received increased attention from the information systems (IS) research community in recent years. There is, however, a growing concern that research on AI could experience a lack of cumulative building of knowledge, which has overshadowed IS research previously. This study addresses this concern, by conducting a systematic literature review of AI research in IS between 2005 and 2020. The search strategy resulted in 1877 studies, of which 98 were identified as primary studies and a synthesise of key themes that are pertinent to this study is presented. In doing so, this study makes important contributions, namely (i) an identification of the current reported business value and contributions of AI, (ii) research and practical implications on the use of AI and (iii) opportunities for future AI research in the form of a research agenda. 相似文献
2.
As far back as the industrial revolution, significant development in technical innovation has succeeded in transforming numerous manual tasks and processes that had been in existence for decades where humans had reached the limits of physical capacity. Artificial Intelligence (AI) offers this same transformative potential for the augmentation and potential replacement of human tasks and activities within a wide range of industrial, intellectual and social applications. The pace of change for this new AI technological age is staggering, with new breakthroughs in algorithmic machine learning and autonomous decision-making, engendering new opportunities for continued innovation. The impact of AI could be significant, with industries ranging from: finance, healthcare, manufacturing, retail, supply chain, logistics and utilities, all potentially disrupted by the onset of AI technologies. The study brings together the collective insight from a number of leading expert contributors to highlight the significant opportunities, realistic assessment of impact, challenges and potential research agenda posed by the rapid emergence of AI within a number of domains: business and management, government, public sector, and science and technology. This research offers significant and timely insight to AI technology and its impact on the future of industry and society in general, whilst recognising the societal and industrial influence on pace and direction of AI development. 相似文献
3.
【目的/意义】人工智能的融入将推动图书馆在公共服务领域的业态革新,提升图书馆公共文化服务效能,
促进智慧图书馆建设过程中各领域的服务创新。【方法/过程】本文以SCI、SSCI、Scopus数据库为来源,通过对文献
进行内容分析和主题挖掘,呈现智慧图书馆研究的热点主题内容和热点应用场景、AI在智慧图书馆中的未来研究
趋势以及AI为智慧图书馆建设带来的机遇和挑战。【结果/结论】从热点主题内容上看,本文梳理了学者们的主要研
究兴趣;根据AI的技术优势以及智慧图书馆的业务需求,梳理出AI在智慧图书馆中的五大应用场景,并提出该领
域未来四个研究趋势;最后,结合AI技术未来最新的发展趋势,分析了AI为智慧图书馆带来的发展机遇,并提出AI
技术落地所面临的挑战。【创新/局限】本文分析了AI在智慧图书馆建设中的落地场景、未来研究趋势以及图书馆可
能面临的机遇与挑战;但研究的样本文献主要基于国外主流数据集,在未来研究中将进一步扩大样本文献。 相似文献
4.
Artificial intelligence (AI) will transform business practices and industries and has the potential to address major societal problems, including sustainability. Degradation of the natural environment and the climate crisis are exceedingly complex phenomena requiring the most advanced and innovative solutions. Aiming to spur groundbreaking research and practical solutions of AI for environmental sustainability, we argue that AI can support the derivation of culturally appropriate organizational processes and individual practices to reduce the natural resource and energy intensity of human activities. The true value of AI will not be in how it enables society to reduce its energy, water, and land use intensities, but rather, at a higher level, how it facilitates and fosters environmental governance. A comprehensive review of the literature indicates that research regarding AI for sustainability is challenged by (1) overreliance on historical data in machine learning models, (2) uncertain human behavioral responses to AI-based interventions, (3) increased cybersecurity risks, (4) adverse impacts of AI applications, and (5) difficulties in measuring effects of intervention strategies. The review indicates that future studies of AI for sustainability should incorporate (1) multilevel views, (2) systems dynamics approaches, (3) design thinking, (4) psychological and sociological considerations, and (5) economic value considerations to show how AI can deliver immediate solutions without introducing long-term threats to environmental sustainability. 相似文献
5.
Digital innovation has radically changed how organisations collaborate and compete. Coupled with this change are new collaborative value creation networks such as digital business ecosystems (DBEs). DBE is a socio-technical network of individuals, organisations and technologies that collectively co-create value. Since the emergence of DBE over a decade ago, there have been limited attempts to critically review and synthesise the body of knowledge presented over the years. Thus, the purpose of this paper is to fill this gap in DBE research by: (1) developing a comprehensive framework that synthesises and provides an overall direction of DBE research; (2) pointing out gaps in DBE literature; and (3) providing future research directions. To address this purpose, we systematically analysed 101 research articles on DBE. The findings provide insightful revelations to address some limitations in the current DBE research. As such, this study makes important contributions and serves as a useful resource for future DBE studies and practice. 相似文献
6.
《Information processing & management》2022,59(1):102759
The growing business evolution and the latest Artificial Intelligence (AI) make the different business practices to be enhanced by the ability to create new means of collaboration. Such growing technology helps to deliver brand services and even some new kinds of corporate interactions with customers and staff. AI digitization simultaneously emphasized businesses to focus on the existing strategies and regularly and early pursue new market opportunities. While digital technology research in the framework of business innovation is gaining greater interest and the privacy of data can be maintained by Blockchain technology. Therefore in this paper, Business Innovation based on artificial intelligence and Blockchain technology (BI-AIBT) has been proposed to enhance the business practices and maintain the secured interaction among the various clients. The collection of qualitative empirical data is made up of few primary respondents from two distinct business sectors. BI-AIBT has been evaluated by undertaking and exploring the difference and similarities between digitalization's impact on value development, proposal, and business capture. Besides, organizational capacities and staff skills interaction issues can be improved by BT. The experimental result suggests that digital transformation is usually regarded as essential and improves business innovation strategies. The numerical result proposed BI-AIBT improves the demand prediction ratio (97.1%), product quality ratio (98.3%), Business development ratio (98.9%), customer behavior analysis ratio (96.3%), and customer satisfaction ratio (97.2%). 相似文献
7.
价值共创作为一个新兴的、多学科融合的和极具发展前景的研究主题,已经成为当前理论和实践研究的前沿与重点。本文运用文献计量法对价值共创主题文献进行了系统梳理,整理并归纳出价值共创研究的发展脉络和规律以及内容框架。基于价值共创的前因-过程-结果,本文构建了价值共创研究的知识体系：价值共创的模式与过程、价值共创的驱动因素、顾客共创体验和价值共创的结果,并在分析现有研究不足的基础上指出了未来的研究方向,以期为国内价值共创领域的研究提供参考。 相似文献
8.
The explosive rise in technologies has revolutionised the way in which business operate, consumers buy, and the pace at which these activities take place. These advancements continue to have profound impact on business processes across the entire organisation. As such, Logistics and Supply Chain Management (LSCM) are also leveraging benefits from digitisation, allowing organisations to increase efficiency and productivity, whilst also providing greater transparency and accuracy in the movement of goods. While the warehouse is a key component within LSCM, warehousing research remains an understudied area within overall supply chain research, accounting for only a fraction of the overall research within this field. However, of the extant warehouse research, attention has largely been placed on warehouse design, performance and technology use, yet overlooking the determinants of Artificial Intelligence (AI) adoption within warehouses. Accordingly, through proposing an extension of the Technology–Organisation–Environment (TOE) framework, this research explores the barriers and opportunities of AI within the warehouse of a major retailer. The findings for this qualitative study reveal AI challenges resulting from a shortage of both skill and mind-set of operational management, while also uncovering the opportunities presented through existing IT infrastructure and pre-existing AI exposure of management. 相似文献
9.
Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts. 相似文献
10.
通过文献计量对创业机会领域的现状加以分析并对未来研究前景做出预判.目前,创业机会领域研究的热点和前沿等尚缺乏实证的支撑,在创业机会理论框架下对创业机会研究文献进行梳理,并采用文献计量方法及可视化技术进行分析.结果表明,创业机会研究的学术关注度逐年攀升,创业机会领域基本建立作者和机构的学术共同体,机会识别是创业机会研究的热点,社会资本是机会识别与开发的核心解释变量,创业学习是创业机会研究的前沿领域,围绕创业资源的研究是创业机会领域的重点主题.最后针对创业机会未来的研究进行展望. 相似文献
11.
[目的/意义]人工智能已成为推动新一轮科技革命和产业变革的重要技术力量,世界各国加紧出台了相关政策。通过对当前研究进行及时梳理,可为今后国内人工智能政策的理论推进及政策出台和完善等提供指导。[方法/过程]以国外SSCI和国内CSSCI期刊数据库收录的395篇研究论文为样本,采用文献计量分析和比较研究法对中外人工智能政策研究的高共被引文献、热点主题及演进趋势等进行深入探索。[结果/结论]与国外相比,国内研究起步较晚但势头迅猛;高共被引文献反映了人工智能领域存在的问题和风险、应用前景、技术革新及对社会的影响;国外研究热点涵盖了知识管理等十二类主题,而国内研究热点则包括国家治理背景下人工智能政策发展路径等三类主题;国外研究的演进特征体现在三个方面,而国内研究则体现在两个方面。最后,从加快形成和构建人工智能政策研究的理论框架体系等三个方面提出对国内研究的启示。 相似文献
12.
人工智能已经成为下一轮工业革命的核心内容,各国争先对其进行部署和发展。为了更好地了解我国人工智能领域的现状和发展,本文基于知识图谱的研究方法,以Web of Science和CNKI中人工智能相关文献作为样本数据,运用CiteSpace软件,通过双图叠加分析、共词分析和突现词分析等功能,从全球的视角对我国人工智能研究近十年来的发展面貌、特点和演化历程做出了可视化的分析。研究发现：人工智能的研究已经呈现出了多学科和学科融合发展的态势;我国在人工智能领域的发展已经取得成果,但距离顶尖还有差距;我国对人工智能应用的研究更为丰富,这与我国的丰富的数据资源和应用场景有关;未来我们应更注重人才的培养,对基础技术的长期支持和投入,同时期待人工智能技术能够带来更为深刻的变革。 相似文献
13.
Research on sustainable entrepreneurship increasingly recognizes the transformative potential of digital technologies to mitigate and counteract grand environmental and social challenges through entrepreneurial action. However, this emerging field of research, referred to as digital sustainable entrepreneurship, is currently dispersed and fragmented and lacks the consolidated foundation to progress further. This article further establishes this nascent stream by conducting a systematic literature review offering two main contributions. First, common themes are derived from the literature (i.e., enabling value for society and environment, stakeholder inclusion, venture viability, and entrepreneurial individuals) to unravel the field's current state. Second, previous work is discussed and integrated by applying a business model perspective. Specifically, the article offers a framework that contributes to the role of business models for merging sustainability and digital technologies, reconceptualizes digital technologies as business model actors, and further develops the entrepreneur-business model nexus. Based on this, we present a comprehensive and actionable research agenda and practical implications. 相似文献
14.
15.
《Information processing & management》2022,59(2):102821
People often search for information in order to learn something new. In recent years, the “search-as-learning” movement has argued that search systems should be better designed to support learning. Current search systems (especially Web search engines) are largely designed and optimized to fulfill simple look-up tasks (e.g., navigational or fact-finding search tasks). However, they provide less support for searchers working on complex tasks that involve learning. Search-as-learning studies have investigated a wide range of research questions. For example, studies have aimed to better understand how characteristics of the individual searcher, the type of search task, and interactive features provided by the system can influence learning outcomes. Learning assessment is a key component in search-as-learning studies. Assessment materials are used to both gauge prior knowledge and measure learning during or after one or more search sessions. In this paper, we provide a systematic review of different types of assessments used in search-as-learning studies to date. The paper makes the following three contributions. First, we review different types of assessments used and discuss their potential benefits and drawbacks. Second, we review assessments used outside of search-as-learning, which may provide insights and opportunities for future research. Third, we provide recommendations for future research. Importantly, we argue that future studies should clearly define learning objectives and develop assessment materials that reliably capture the intended type of learning. For example, assessment materials should test a participant’s ability to engage with specific cognitive processes, which may range from simple (e.g., memorization) to more complex (e.g., critical and creative thinking). Additionally, we argue that future studies should consider two dimensions that are understudied in search-as-learning: long-term retention (i.e., being able to use what was learned in the long term) and transfer of learning (i.e., being able to use what was learned in a novel context). 相似文献
16.
Recent research call for action on digital sustainability research could potentially contribute to achieving United Nations (UN) Sustainable Development Goals (SDG). In this opinion piece, we specifically focus on artificial intelligence (AI) as a technology that could help achieve digital sustainability. We identify six dimensions related to AI grounded in past literature: sensemaking, relationships among actors in the supply chain, green creativity skills, metrics, strategies, and AI tool improvement. We conceptualize several propositions for these six dimensions, highlighting the nuances associated with AI for digital sustainability to provide clear directions for future research. 相似文献
17.
Clinicians, healthcare providers-suppliers, policy makers and patients are experiencing exciting opportunities in light of new information deriving from the analysis of big data sets, a capability that has emerged in the last decades. Due to the rapid increase of publications in the healthcare industry, we have conducted a structured review regarding healthcare big data analytics. With reference to the resource-based view theory we focus on how big data resources are utilised to create organization values/capabilities, and through content analysis of the selected publications we discuss: the classification of big data types related to healthcare, the associate analysis techniques, the created value for stakeholders, the platforms and tools for handling big health data and future aspects in the field. We present a number of pragmatic examples to show how the advances in healthcare were made possible. We believe that the findings of this review are stimulating and provide valuable information to practitioners, policy makers and researchers while presenting them with certain paths for future research. 相似文献
18.
The blockchain is considered to be the potential driver of the digital economy. The Blockchain technology outweighs the challenges associated with the traditional transaction business governed and regulated by the third trusted party. There is a growth in the interest among the researchers, the industry, and the academia to study and leverage the potential of Blockchain. Blockchain provides a decentralized and distributed public ledger for all the participating parties. Though it seems that blockchain is a viable choice and solution for all the centralized governed and regulated transactions (in digital online space), it has potential challenges that need to be resolved; opportunities to be explored, and applications to be studied. This paper utilizes a systematic literature review to study several research endeavors made in the domain of blockchain. To further research on blockchain adoption, the paper theoretically constructs an integrated framework of the blockchain innovation adoption process in an organization considering organizational and user acceptance perspectives. This would facilitate its widespread adoption, thereby achieving sustained leadership solutions. The paper offers 23 propositions to information systems (IS)/information management (IM) scholars with respect to innovation characteristics, organizational characteristics, environmental characteristics, and user acceptance characteristics. Further, the paper explores several areas of future research and directions that can provide deep insights for overcoming challenges and for the adoption of blockchain technology. 相似文献
19.
The literature surrounding Intellectual Capital (IC) theory has grown substantially over the last 10 years with new models, frameworks and approaches introduced for how to manage IC. Yet, the practical implication of deploying IC methods in an organisation and its impact on a firm's business model innovation and decision-making process is relatively unexplored. This paper will review one tool, the IC Navigator approach and its effectiveness as a tool for resource deployment analysis and its impact on a firm's future value creation activities. The paper reports on research that involved five manufacturing firms who participated in an action learning workshop series and particularly the workshop dedicated to using the IC Navigator approach. The usefulness of this model as a tool to reconfiguring a firm's resources, as perceived by the five firms, is examined and findings are presented. 相似文献
20.
《Information processing & management》2023,60(1):103142
In sponsored search advertising (SSA), keywords serve as the basic unit of business model, linking three stakeholders: consumers, advertisers and search engines. This paper presents an overarching framework for keyword decisions that highlights the touchpoints in search advertising management, including four levels of keyword decisions, i.e., domain-specific keyword pool generation, keyword targeting, keyword assignment and grouping, and keyword adjustment. Using this framework, we review the state-of-the-art research literature on keyword decisions with respect to techniques, input features and evaluation metrics. Finally, we discuss evolving issues and identify potential gaps that exist in the literature and outline novel research perspectives for future exploration. 相似文献