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Artificial Intelligence for Sustainability—A Systematic Review of Information Systems Literature 面向可持续发展的人工智能——信息系统文献综述
Q2 Computer Science Pub Date : 2023-01-01 DOI: 10.17705/1cais.05209
Thorsten Schoormann, Gero Strobel, Frederik Möller, Dimitri Petrik, Patrick Zschech
The booming adoption of Artificial Intelligence (AI) likewise poses benefits and challenges. In this paper, we particularly focus on the bright side of AI and its promising potential to face our society’s grand challenges. Given this potential, different studies have already conducted valuable work by conceptualizing specific facets of AI and sustainability, including reviews on AI and Information Systems (IS) research or AI and business values. Nonetheless, there is still little holistic knowledge at the intersection of IS, AI, and sustainability. This is problematic because the IS discipline, with its socio-technical nature, has the ability to integrate perspectives beyond the currently dominant technological one as well as can advance both theory and the development of purposeful artifacts. To bridge this gap, we disclose how IS research currently makes use of AI to boost sustainable development. Based on a systematically collected corpus of 95 articles, we examine sustainability goals, data inputs, technologies and algorithms, and evaluation approaches that define the current state of the art within the IS discipline. This comprehensive overview enables us to make more informed investments (e.g., policy and practice) as well as to discuss blind spots and possible directions for future research.
人工智能(AI)的蓬勃发展同样带来了好处和挑战。在本文中,我们特别关注人工智能的光明一面及其面对我们社会重大挑战的巨大潜力。鉴于这种潜力,不同的研究已经通过概念化人工智能和可持续性的具体方面进行了有价值的工作,包括对人工智能和信息系统(IS)研究或人工智能和商业价值的审查。尽管如此,在信息系统、人工智能和可持续性的交叉点上,仍然很少有整体性的知识。这是有问题的,因为具有社会技术性质的信息系统学科有能力整合超越当前占主导地位的技术的观点,并且可以推进理论和有目的的人工制品的发展。为了弥补这一差距,我们披露了信息系统研究目前如何利用人工智能促进可持续发展。基于系统收集的95篇文章的语料库,我们研究了可持续性目标、数据输入、技术和算法,以及定义IS学科当前状态的评估方法。这种全面的概述使我们能够做出更明智的投资(例如,政策和实践),并讨论盲点和未来研究的可能方向。
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引用次数: 6
A Guide for Stakeholder Analysis in IS/IT Management and Research: The Case of Broadband Availability in Rural North Carolina IS/IT管理和研究中的利益相关者分析指南:北卡罗来纳州农村宽带可用性案例
Q2 Computer Science Pub Date : 2023-01-01 DOI: 10.17705/1cais.05326
Judith Gebauer, Minoo Modaresnezhad, Christopher Sibona, Kevin Matthews
Stakeholder analysis is a methodology that can provide valuable insights about a phenomenon. Information systems and information technology researchers have utilized stakeholder analysis to understand and learn from successes, failures, and other aspects of IS/IT initiatives. In this tutorial, we provide guidelines for conducting a stakeholder analysis currently missing in the IS/IT discipline despite being repeatedly called for. We reviewed studies on stakeholder analysis within IS/IT first, but found that there was not sufficient coverage. Then we went outside the discipline and found relevant studies in the areas of organizational and strategic management and public policy. Our analysis, then, consists of a review and a combination of the findings of studies from within the IS/IT discipline and studies in organizational and strategic management and public policy. Our guidelines start with determining who the stakeholders are related to a phenomenon and what key concerns these stakeholders have about the phenomenon. In the next step, we relate stakeholders to one another and across the key concerns and point out how to identify possible coalitions. Last, we describe how to apply these findings to determine strategies for managing stakeholders or building theory around a phenomenon and its concerns. These final steps can be used to make policy recommendations, provide guidance for IS/IT-related initiatives, or present constructs and relationships that can be tested by future researchers. We demonstrate the applicability of our guidelines with a case study about broadband availability in rural North Carolina.
利益相关者分析是一种方法,可以提供有关现象的有价值的见解。信息系统和信息技术研究人员利用利益相关者分析来理解和学习成功、失败和其他方面的信息系统/IT计划。在本教程中,我们提供了指导方针,用于执行目前在IS/IT规程中缺失的涉众分析,尽管它被反复呼吁。我们首先回顾了IS/IT内部利益相关者分析的研究,但发现没有足够的覆盖。然后我们走出学科,在组织和战略管理以及公共政策领域找到了相关的研究。因此,我们的分析包括对IS/IT学科研究结果的回顾和结合,以及对组织和战略管理以及公共政策的研究结果。我们的指导方针从确定谁是与某个现象相关的涉众以及这些涉众对该现象的主要关注点开始。在下一步中,我们将利益相关者彼此联系起来,并跨越关键问题,并指出如何确定可能的联盟。最后,我们描述了如何应用这些发现来确定管理利益相关者的策略或围绕一种现象及其关注点建立理论。这些最后的步骤可以用来制定政策建议,为与信息技术相关的计划提供指导,或者为未来的研究人员提供可以测试的结构和关系。我们通过一个关于北卡罗莱纳州农村宽带可用性的案例研究来证明我们的指导方针的适用性。
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引用次数: 0
Blending Modalities, Pedagogies, and Technologies: Redesigning an Information Systems Course to Encourage Engagement 混合模式、教学法和技术:重新设计信息系统课程以鼓励参与
Q2 Computer Science Pub Date : 2023-01-01 DOI: 10.17705/1cais.05313
Cathal Doyle, Yi-Te Chiu
Having realized that the traditional approach to teaching our IS course on Business and Systems Analysis was not engaging students enough, we decided we needed to redesign our learning environment. The goal was to develop a course that encourages student participation, allows them to practice the different techniques we introduce them to, and empowers students to take control of their learning. To achieve this, we blended modalities (online and in-person), pedagogies (constructivist and collaborative approaches), and technologies (student-centered technologies). This resulted in a redesign that included replacing the lecture with learning resources of a digestible size and an activity-based discussion, the workshop focusing on a project for authentic problems, sense-making via doing and reflection, hybrid participation in a steady and sustainable pace, and learning communities to enable more interaction. In this paper, we share our experience and lessons that we have learned through a journey toward a student-centered approach to learning.
我们意识到,传统的IS商业与系统分析课程教学方法无法吸引学生,于是我们决定需要重新设计学习环境。我们的目标是开发一门鼓励学生参与的课程,让他们练习我们介绍给他们的不同技术,并使学生能够控制自己的学习。为了实现这一目标,我们混合了模式(在线和面对面)、教学法(建构主义和协作方法)和技术(以学生为中心的技术)。这导致了重新设计,包括用易于理解的学习资源和基于活动的讨论取代讲座,研讨会专注于真实问题的项目,通过实践和反思来实现意义,以稳定和可持续的速度混合参与,以及学习社区以实现更多的互动。在本文中,我们分享了我们在以学生为中心的学习方法的过程中所学到的经验和教训。
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引用次数: 0
AgriMitr: Digitalizing the Agricultural Landscape with Satellite Imaging AgriMitr:利用卫星成像技术数字化农业景观
Q2 Computer Science Pub Date : 2023-01-01 DOI: 10.17705/1cais.05251
Amol S. Dhaigude, Riju Ghosh
AgriMitr was a tech-savvy start-up situated in Bengaluru, the Silicon Valley of India. It was a subsidiary of KnowThyData (KTD), a Data Science and Analytics firm, a leading data science firm providing myriad solutions to many clients. AgriMitr was established by the founder and CEO of KTD, Dr. Jishu Bose, to develop products using satellite imagery and data science. AgriMitr developed a mobile and web application that helped farmers and other key stakeholders understand crop health, soil fertility and other critical factors related to agriculture by machine learning algorithms using satellite images. The app was a major leap of innovation in the Indian Agri-Tech space. The app was to be used majorly by farmers based in rural India, and thus the major challenge lay in spreading awareness, adoption, and usage of the app. The app, if appropriately deployed, would be an imminent milestone in sustainable food production and consumption and can aid in taking a step forward in solving the world hunger problem, an SDG of the UN. Dr. Bose was planning the strategy for AgriMitr’s mass adoption and implementation with the help of Mr. Madhav A. Ram. The much-awaited meeting with investors and key stakeholders was just one week away. Madhav, under the guidance of Dr. Bose, had to prepare a roadmap and his game plan for the next year to bring this wave of change and large-scale digital adoption among the farmers of India.
AgriMitr是一家技术娴熟的初创公司,位于印度硅谷班加罗尔。它是KnowThyData (KTD)的子公司,KnowThyData是一家数据科学和分析公司,是一家领先的数据科学公司,为许多客户提供无数解决方案。AgriMitr由KTD的创始人兼首席执行官Jishu Bose博士成立,旨在开发使用卫星图像和数据科学的产品。AgriMitr开发了一个移动和网络应用程序,通过使用卫星图像的机器学习算法,帮助农民和其他关键利益相关者了解作物健康、土壤肥力和其他与农业相关的关键因素。这款应用是印度农业科技领域创新的一次重大飞跃。这款应用程序的主要用户是印度农村的农民,因此主要的挑战在于传播这款应用程序的意识、采用和使用。如果应用程序得到适当部署,它将成为可持续粮食生产和消费的一个即将到来的里程碑,并有助于在解决世界饥饿问题方面向前迈进一步,这是联合国的可持续发展目标。Bose博士在Madhav A. Ram先生的帮助下为AgriMitr的大规模采用和实施制定了战略。与投资者和主要利益相关者期待已久的会议只有一周的时间了。在Bose博士的指导下,Madhav必须为下一年准备一个路线图和他的游戏计划,以便在印度农民中带来这一波变革和大规模的数字应用。
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引用次数: 0
Extraordinary Claims Require Extraordinary Evidence: A Comment on “Recent Developments in PLS” 特殊的索赔需要特殊的证据:评“PLS的最新发展”
Q2 Computer Science Pub Date : 2023-01-01 DOI: 10.17705/1cais.05234
Pratyush N. Sharma, Benjamin D. Liengaard, Marko Sarstedt, Joseph F. Hair, Christian M. Ringle
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引用次数: 8
Institutional Work for Enterprise Architecture 企业架构的机构工作
Q2 Computer Science Pub Date : 2023-01-01 DOI: 10.17705/1cais.05311
Anne Kristin S. Ajer, Eli Hustad, Dag H. Olsen, Polyxeni Vassilakopoulou
Enterprise architecture (EA) is a systematic approach used for designing and implementing changes in technological systems and processes to improve organizational performance and align technology with business. This paper unpacks the process through which EA moves from strategic-level endorsement to diffusion across organizations. The insights provided are based on a longitudinal case study within the Norwegian hospital sector. An institutional work lens is adopted to analyze the purposeful activities carried out to introduce EA in Norwegian hospitals providing a granular view on diffusion. The paper provides a rich description of the institutional work employed by the key actors involved mapping them to different turns in EA’s trajectory. Drawing from this analysis, we contribute to Information Systems literature with a conceptual model that illustrates how institutional work can mitigate the challenges of moving from the strategic-level endorsement of novelty to its diffusion and institutionalization smoothing downturns along the way. The findings indicate ways to facilitate the introduction of EA within complex organizations, providing insights for practitioners involved in EA initiatives, and advancing extant EA research through an institutional perspective.
企业架构(EA)是一种系统的方法,用于设计和实现技术系统和过程中的变更,以改进组织性能并使技术与业务保持一致。本文揭示了EA从战略级别的认可到跨组织的扩散的过程。所提供的见解是基于挪威医院部门的纵向案例研究。采用机构工作视角来分析为在挪威医院引入EA而开展的有目的的活动,提供了扩散的细粒度视图。本文提供了对关键参与者所采用的制度工作的丰富描述,这些参与者将它们映射到EA轨迹中的不同转折。根据这一分析,我们为信息系统文献贡献了一个概念模型,该模型说明了制度工作如何能够减轻从战略层面对新颖性的认可到其传播和制度化的挑战,并在此过程中平滑衰退。这些发现指出了促进在复杂组织中引入EA的方法,为参与EA计划的实践者提供了见解,并通过制度的视角推进了现有的EA研究。
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引用次数: 0
MaCuDE IS Task Force Phase II Report: Views of Industry Leaders on Big Data Analytics and AI MaCuDE IS工作组第二阶段报告:行业领导者对大数据分析和人工智能的看法
IF 2 Q2 Computer Science Pub Date : 2023-01-01 DOI: 10.17705/1cais.05217
K. Lyytinen, H. Topi, Jing Tang
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引用次数: 0
Learner Engagement with YouTube Videos in Informal Online Learning: An Investigation of the Effects of Segmenting, Signaling, and Weeding 非正式在线学习中学习者对YouTube视频的参与:对分割、信号和剔除效果的调查
Q2 Computer Science Pub Date : 2023-01-01 DOI: 10.17705/1cais.05314
Zixing Shen
Millions of educational videos available on YouTube offer unprecedented opportunities for online learning. As it invites open-ended and self-paced exploration of almost any topic, YouTube has emerged as an important platform for informal online learning that occurs outside the formal classroom. A considerable number of studies have been directed toward YouTube educational videos. However, research on learner engagement with YouTube educational videos is limited, despite the central role of engagement in learning and the increasing popularity of YouTube videos in informal online learning. This paper addresses this research gap. We adopt the conceptualization that learner engagement has three dimensions – behavioral, emotional, and cognitive - and investigate how the features of segmenting, signaling, and weeding (SSW), the three multimedia learning principles, in YouTube educational video presentations collectively affect learner engagement in informal online learning. Our analysis shows that different SSW features have various associations with the three dimensions of learner engagement. These findings substantiate the empirical knowledge of learner engagement with YouTube educational videos. Our study corroborates extant video engagement research and extends its relevance to informal learning on social media. It also informs video designers and developers on adding video presentation features to optimize video engagement on social media.
YouTube上数以百万计的教育视频为在线学习提供了前所未有的机会。由于它邀请人们对几乎任何主题进行开放式和自定义的探索,YouTube已经成为正式课堂之外非正式在线学习的重要平台。相当多的研究都针对YouTube的教育视频。然而,尽管参与在学习中的核心作用和YouTube视频在非正式在线学习中的日益普及,但关于学习者参与YouTube教育视频的研究是有限的。本文解决了这一研究空白。我们采用学习者参与有三个维度的概念——行为、情感和认知——并研究了YouTube教育视频演示中的分割、信号和除法(SSW)这三种多媒体学习原则的特征如何共同影响学习者在非正式在线学习中的参与。我们的分析表明,不同的SSW特征与学习者投入的三个维度有不同的关联。这些发现证实了学习者参与YouTube教育视频的经验知识。我们的研究证实了现有的视频参与研究,并将其扩展到社交媒体上的非正式学习。它还告知视频设计师和开发人员如何添加视频演示功能,以优化社交媒体上的视频参与度。
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引用次数: 0
Children’s E-Learning Interactions and Perceived Outcomes with Educational Key Opinion Leaders in China 中国儿童与教育关键意见领袖的网络学习互动与感知结果
Q2 Computer Science Pub Date : 2023-01-01 DOI: 10.17705/1cais.05317
Susan Zhang, Jun Shen, Jun Yan
Classroom teaching has been undergoing a digital transformation in the last decade and is now being amplified by Educational Key Opinion Leaders (Edu-KOLs). This research aims to investigate the relationship between learners’ perceived outcomes, motivation, and the selection preferences of Edu-KOLs. This paper presents insights gained from a two-phase study. We conducted research in the first phase through an online questionnaire completed by 186 parents in China whose children are studying or have recently studied online. In the second phase, we interviewed parents to deep dive into their thinking process behind their choices of Edu-KOLs. By utilizing the PLS-SEM method, this research has proposed and verified six hypotheses asserting that e-learning platforms, student engagement scores, and perceived outcomes strongly correlate with the perception of Edu-KOLs. However, parents’ educational level or occupation has less impact on the choices of Edu-KOLs. There are also positive relationships among Edu-KOLs, customer advocacy, and future purchase intention.
在过去十年中,课堂教学经历了数字化转型,现在教育关键意见领袖(edukol)正在扩大课堂教学。本研究旨在探讨学习者感知结果、动机与教育kol选择偏好之间的关系。本文介绍了从两阶段研究中获得的见解。我们在第一阶段通过一份在线问卷进行了研究,问卷由186名中国家长填写,他们的孩子正在或最近在网上学习。在第二阶段,我们采访了家长,深入了解他们选择edukol背后的思考过程。通过使用PLS-SEM方法,本研究提出并验证了六个假设,断言电子学习平台、学生参与分数和感知结果与edui - kol的感知密切相关。而父母的受教育程度和职业对家长意见领袖选择的影响较小。用户意见领袖、顾客拥护和未来购买意愿之间也存在正相关关系。
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引用次数: 0
Navigating Workload Compatibility Between a Recommender System and a NoSQL Database: An Interactive Tutorial 在推荐系统和NoSQL数据库之间导航工作负载兼容性:一个交互式教程
Q2 Computer Science Pub Date : 2023-01-01 DOI: 10.17705/1cais.05327
Varol O. Kayhan, Donald J. Berndt
In this tutorial, the issue of compatibility between a big data storage technology and an analytic workload is explored using a fictitious streaming company as an example. The tutorial offers an interactive approach to help students understand the importance of considering workload compatibility when adopting new technologies. We provide instructors with the following: two Jupyter Notebooks that analyze compatibility, a detailed instructor guide on how to execute these notebooks, lessons learned, and appendices containing solutions and explanations. This tutorial provides a valuable resource for instructors teaching courses in database systems, big data, and analytic concepts, helping students develop practical skills to navigate effectively the complexities of big data technologies.
在本教程中,将以一个虚构的流媒体公司为例,探讨大数据存储技术和分析工作负载之间的兼容性问题。本教程提供了一种交互式方法,帮助学生理解在采用新技术时考虑工作负载兼容性的重要性。我们为教师提供以下内容:两本分析兼容性的Jupyter笔记本,关于如何执行这些笔记本的详细指导,经验教训,以及包含解决方案和解释的附录。本教程为教授数据库系统、大数据和分析概念课程的教师提供了宝贵的资源,帮助学生培养有效驾驭大数据技术复杂性的实用技能。
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引用次数: 0
期刊
Communications of the Association for Information Systems
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