Cfp October 2020

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Fwd: [AISWorld] JAIS Special Issue on Data Science for Social Good - Second CFP with updates on Editorial Board
by Gustaf Neumann 20 Oct '20

20 Oct '20

-------- Forwarded Message -------- Subject: [AISWorld] JAIS Special Issue on Data Science for Social Good - Second CFP with updates on Editorial Board Date: Mon, 19 Oct 2020 18:06:07 -0400 From: Jennifer Xu <jiexu2(a)gmail.com> To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org> Dear Colleagues, We cordially invite you to submit your research to the special issue on *Data Science for Social Good *at the Journal of Association for Information Systems (JAIS). *Submission deadline*: *February 15, 2021* * Special Issue Co-Editors* - Ahmed Abbasi, University of Notre Dame (aabbasi(a)nd.edu) - Roger H.L. Chiang, University of Cincinnati (roger.chiang(a)uc.edu) - Jennifer Xu, Bentley University (jxu(a)bently.edu) * Scope and Focus of the Special Issue* Data science is an interdisciplinary field that applies mathematics, statistics, machine learning, and data visualization techniques to extract insights and knowledge from data that are normally big and encompass both structured and unstructured formats. Jim Gray, a 1998 Turing Award winner, promoted data science as a new, fourth paradigm for scientific discovery in response to the large amounts of data generated by scientific experiments in many disciplines (Hey et al., 2009). In this vein, data science complements experimental, theoretical, and computational science as an emerging research paradigm for understanding nature and society (Bell et al., 2009). The inherently interdisciplinary nature of data science, and the fact that it is a catalyst for business transformation and technology disruption, presents many research opportunities for a diverse discipline such as Information Systems (IS). This has spurred a call for greater IS research on business data science (Saar-Tsechansky 2015). Similarly, there is a need for IS research on the development and evaluation of data science artifacts (e.g., models, methods, and systems) that address broader societal challenges. A lingering question remains: what societal challenges can IS-oriented data science research contribute towards - and how can we conduct such research to maximize impact and relevance? It is generally accepted that the primary goal of scientific discovery and technological innovation are to improve the human condition and the overall well-being of society. As the world deals with unprecedented pandemics and grapples with painful centuries-old social justice inequities, the importance of data science for social good has once again come front and center. For example, the U.S. National Institute for Health's data science resource page lists many available datasets and computational resources ( https://datascience.nih.gov/covid-19-open-access-resources). This data is being used to develop models and methods to diagnose likelihood of infection, detect outbreak hot spots, and forecast intensive care unit bed capacities. Similarly, social justice projects are attempting to democratize data science in key contexts such as crime analytics. However, it must be pointed out that data science for social good (DSSG) is not merely about applying data science techniques to data sets of societal importance. As a recent McKinsey report noted, data science/AI work exploring social good use cases cannot rely solely on a "social-first" or "tech-first" approach, but rather, must consider the amalgamation of these two perspectives (Chui et al., 2018). The IS field has noted the importance of taking a more holistic approach to such research that encompasses a socio-technical lens (Abbasi et al., 2016) spanning context, people, process, and technology. Accordingly, for this special issue, some of the major themes include: * Novel Data Science Artifacts for Social Good* IT artifacts include constructs, models, methods, and instantiations (Hevner et al., 2004). Novelty lies at the intersection of artifact design as well as its application (Gregor and Hevner 2013). Whereas application domains like health and the environment have received some attention, many key areas remain underexplored (Chui et al., 2018). Examples include education, economic empowerment, security and justice, crises response, infrastructure, and hunger. For DSSG, the novel data science artifacts include new models, methods, and systems applied to interesting and timely social good use cases that enhance our knowledge and understanding of the state-of-the-art in meaningful ways. * Measuring Social Impact* Data science artifacts are often evaluated and validated based on how well they perform across a set of well-established performance metrics (e.g., accuracy and sensitivity). The importance of such metrics has been further amplified in recent years with the rise of data analytics competitions, crowd-sourcing platforms, and leaderboards. While such metrics are important, and in some respects, they constitute the "price of admission" for artifact design, they often fail to consider key downstream implications - humanistic outcomes and societal impact. This is what some IS scholars have described as "going the last research mile...using scientific knowledge and methods to address important unsolved classes of problems for real people with real stakes in the outcomes" (Nunamaker et al., 2015, p. 11). Research geared towards measuring social impact might include (but is not limited to) new methods, constructs, or case studies that enhance our understanding of how to quantify and assess the social impact of data science artifacts. * Data Science Ethics and Governance Considerations* Important data science considerations related to trust, explainability, bias, fairness, privacy, and ethical use are beginning to garner a fair amount of attention from policy makers, academia, and the business community - and for good reason. However, much work has taken a univariate tunnel-vision perspective that fails to consider the interplay between these factors. As one example, through immersive longitudinal field research, we know that DSSG projects examining the efficacy of interventions geared towards health disparate populations should consider the intersections between factors such as trust, bias, privacy, and fairness (Abbasi et al., 2018; Taylor et al., 2018). We welcome research that explores the complexity of ethical challenges and governance considerations related to the application of data science in interesting societally impactful contexts. * Topics of Interest* The DSSG follows a tradition of IS research that examines how the advancement of information technology and systems address societal challenges such as digital divide and social inclusion. Data science has a great potential to provide tremendous social benefits in the future. This special issue advocates the need for more IS research in studying DSSG, and encourages the creation and evaluation of data science artifacts to examine and address societal challenges in a variety of contexts and domains. In addition, this special issue seeks to promote collaborations between IS researchers that are technically focused and those with more of a social/people focus. Our hope is that this special issue sparks in-depth examination about where data science capabilities can be applied to address societal challenges in ways that are unique, thought-provoking, and impactful. This JAIS special issue welcomes original research for addressing societal challenges in various domains and areas, including, but not limited to, the following: - Crises response - Healthcare and welfare - Public transportation and safety - Education and employment - Security and law enforcement - Urban planning and development - Environmental protection, clean energy, and sustainability - Not-for-profit organizations and government agencies' services - Ethnical and social biases embedded in datasets and analytics methods - Social justice, disparities, inequality and poverty * Submission Process and Timelines* In the extended abstract and full paper submission, authors should clearly justify the novelty and significance of their work. We encourage prospective authors to read the recent JAIS editorial on "What's in a Contribution?" to justify their research's significant and novel contributions to the IS discipline regarding Data Science for Social Good (Leidner 2020). All submissions must be original and not be published or under review elsewhere. Papers should be submitted following the standard JAIS submission procedure (http://aisel.aisnet.org/jais/). All JAIS submission guidelines must be met. Although optional, authors are strongly encouraged to contact the co-editors with a 1-3 page extended abstract by November 15, 2020 to evaluate research fit with the special issue. The co-editors also plan to organize an online paper development workshop in the summer of 2021. Authors of invited to submit a revision for a second round of review will have an opportunity to present their work at this workshop. The exact date and format of this online workshop will be determined after the first round of review. November 15, 2020: 1-3 page extended abstract submission February 15, 2021: Full paper submission June 15, 2021: Notification of first round review October 15, 2021: Revised manuscript submission January 15, 2022: Notification of second round review April 15, 2022: Second revision submission July 15, 2022: Notification of final decision *Special Issue Editorial Board * Alan Abrahams, Virginia Tech Victor Benjamin, Arizona State University Michael Chau, University of Hong Kong Maria De'Arteaga, University of Texas at Austin Monica Garfield, Bentley University Tomer Geva, Tel-Aviv University Steven Johnson, University of Virginia Brent Kitchens, University of Virginia John Lalor, University of Notre Dame Karl Lang, Baruch University Raymond Lau, City University of Hong Kong Yang Lee, Northeastern University Xiaobai (Bob) Li, University of Massachusetts at Lowell Ee-Peng Lim, Singapore Management University Xiao Liu, Arizona State University Asil Oztekin, University of Massachusetts at Lowell Jeff Proudfoot, Bentley University Shawn Qu, University of Notre Dame Sagar Samtani, Indiana University Alan Wang, Virginia Tech Chih-Ping Wei, National Taiwan University Kang Zhao, University of Iowa Wenjun Zhou, University of Tennessee * References* Abbasi, A., Sarker, S., & Chiang, R. H. (2016). "Big Data Research in Information Systems: Toward an Inclusive Research Agenda," Journal of the Association for Information Systems, 17(2), i-xxxii. Abbasi, A., Li, J., Clifford, G., & Taylor, H. (2018). "Make "Fairness by Design" Part of Machine Learning," Harvard Business Review. Bell, G., Hey, T., & Szalay, A. (2009). "Beyond the Data Deluge," Science. (323:5919), 1297-1298. Chui M. et al. (2018). "Notes from the AI Frontier: Applying AI for Social Good," McKinsey Global Institute. Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). "Design Science in Information Systems Research," MIS Quarterly, 28(1), 75-105. Hey, T, Tansley, S., & Tolle, K. (2009). The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research. Leidner, D. E. (2020). "What's in a Contributions?," Journal of the Association for Information Systems, 21(1), 238-245. Nunamaker Jr, J. F., Briggs, R. O., Derrick, D. C., & Schwabe, G. (2015). "The Last Research Mile: Achieving both Rigor and Relevance in Information Systems Research," Journal of Management Information Systems, 32(3), 10-47. Saar-Tsechansky, M. (2015). "Editor's comments: The Business of Business Data Science in IS journals," MIS Quarterly, 39(4), iii-vi. Taylor, H. A., Henderson, F., Abbasi, A., & Clifford, G. (2018). "Cardiovascular Disease in African Americans: Innovative Community Engagement for Research Recruitment and Impact," American Journal of Kidney Diseases, 72(5), S43-S46. Jennifer Jie Xu, Professor Computer Information Systems Bentley University Waltham, MA 02452 Tel: 781-891-2711

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Fwd: [AISWorld] [AJIS] New Article: An Integrated Search Framework for Leveraging the Knowledge-Based Web Ecosystem
by Gustaf Neumann 20 Oct '20

20 Oct '20

-------- Forwarded Message -------- Subject: [AISWorld] [AJIS] New Article: An Integrated Search Framework for Leveraging the Knowledge-Based Web Ecosystem Date: Tue, 20 Oct 2020 13:11:10 +1100 From: Ajis Editor <ajis.eic(a)gmail.com> To: ISHoDs <IS-hods(a)list.utas.edu.au>, ISWorld <aisworld(a)lists.aisnet.org>, ISAus <IS-Aus(a)list.utas.edu.au> Hi, The *Australasian Journal of In*formation Systems has just published its latest article. *An Integrated Search Framework for Leveraging the Knowledge-Based Web EcosystemZhu, Nimmagadda, Reiners & Rudrahttps://doi.org/10.3127/ajis.v24i0.2331 <https://doi.org/10.3127/ajis.v24i0.2331>* *Abstract* The explosion of information constrains the judgement of search terms associated with Knowledge-Based Web Ecosystem (KBWE), making the retrieval of relevant information and its knowledge management challenging. The existing information retrieval (IR) tools and their fusion in a framework need attention, in which search results can effectively be managed. In this article, we demonstrate the effective use of information retrieval services by a variety of users and agents in various KBWE scenarios. An innovative Integrated Search Framework (ISF) is proposed, which utilises crawling strategies, web search technologies and traditional database search methods. Besides, ISF offers comprehensive, dynamic, personalized, and organization-oriented information retrieval services, ranging from the Internet, extranet, intranet, to personal desktop. In this empirical research, experiments are carried out demonstrating the improvements in the search process, as discerned in the conceptual ISF. The experimental results show improved precision compared with other popular search engines. #IntegratedSearchFramework #InformationRetrieval #SearchEngine #textClassification #DigitalEcosystem #InformationManagement #Crawler -=-=-=- *Call for Papers* AJIS publishes high quality contributions to the global Information Systems (IS) discipline with an emphasis on theory and practice on the Australasian context. Topics cover core IS theory development and application (the nature of data, information and knowledge; formal representations of the world, the interaction of people, organisations and information technologies; the analysis, design and deployment of information systems; the impacts of information systems on individuals, organisations and society), IS domains (e-business, e-government, e-learning, e-law, etc) and IS research approaches. Research and conceptual development based in a very wide range of epistemological methods are welcomed. All manuscripts undergo double blind reviewing by at least 2 well qualified reviewers. Their task is to provide constructive, fair, and timely advice to authors and editor. AJIS welcomes research and conceptual development of the IS discipline based in a very wide range of epistemologies. Different types of research paper need to be judged by different criteria. Here are some assessment criteria that may be applied: • Relevance - topic or focus is part of the IS discipline. • Effectiveness - paper makes a significant contribution to the IS body of knowledge. • Impact - paper will be used for further research and/or practice. • Uniqueness - paper is innovative, original & unique. • Conceptual soundness - theory, model or framework made explicit. • Argument - design of the research or investigation is sound; methods appropriate. • Clarity - Topic is clearly stated; illustrations, charts & examples support content. • Reliability - data available; replication possible. • References - sound, used appropriately, and sufficient – appropriate AJIS articles referenced • Style - appropriate language, manuscript flows. This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. AJIS has been published since 1993 and appears in the Index of Information Systems Journals, is ranked "A" by both the Australian Council of Professors and Heads of Information Systems and the Australian Business Deans' Council. In addition to web distribution, AJIS is distributed by EBSCO, it is listed in Cabell's International Directory and is indexed by EBSCO, Elsevier, Scopus and the Directory of Open Access Journals. Thanks for the continuing interest in our work, Cheers Associate Professor John Lamp Editor-in-Chief, Australasian Journal of Information Systems http://journal.acs.org.au/index.php/ajis/ _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [AISWorld] CFP Special Issue of the Drake Management Review on FinTech Research
by Gustaf Neumann 20 Oct '20

20 Oct '20

-------- Forwarded Message -------- Subject: [AISWorld] CFP Special Issue of the Drake Management Review on FinTech Research Date: Tue, 20 Oct 2020 02:22:14 +0000 From: Troy Strader <troy.strader(a)drake.edu> To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org> Call for Papers Special Issue of the Drake Management Review on Financial Technology (FinTech) Research Special issue Co-Editors: Troy Strader and Yu-Hsiang (John) Huang, Drake University Special Issue Description and Article Submission We invite submissions from any financial technology (FinTech) related research area. We broadly define FinTech as any research addressing issues involving information technology use and impact on financial processes, financial decision-making, financial markets, and the global economy. Financial areas may include banking, payments, corporate finance, investment, insurance or real estate. We invite submissions that are original, unpublished, and not currently under review at another publication. Submission guidelines and format are available at http://faculty.cbpa.drake.edu/dmr/Submission_Guidelines.pdf. All submissions will be reviewed by at least two editorial review board members. Articles are double-blind peer-reviewed and final accept/reject decisions are made based on recommendations from reviewers and the editors. Studies may use any research methodology including, but not limited to, conceptual, empirical, quantitative, qualitative, or case study. Please share this call for papers with your colleagues in finance or other FinTech related disciplines. Special Issue Deadlines Initial paper submission January 4, 2021 Initial review and decision February 23, 2021 Revised paper submission March 29, 2021 Issue publication April 2021 Articles may be submitted by e-mail to: Dr. Troy Strader, Editor-in-Chief Drake Management Review troy.strader(a)drake.edu The Drake Management Review (DMR) is an online publication of the Drake University College of Business and Public Administration and has been published online since 2011 The journal is available without subscription at http://faculty.cbpa.drake.edu/dmr/ _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [WI] ECIS 2021 Call for Papers - Track Business Analytics and Big Data
by Gustaf Neumann 16 Oct '20

16 Oct '20

-------- Forwarded Message -------- Subject: [WI] ECIS 2021 Call for Papers - Track Business Analytics and Big Data Date: Fri, 16 Oct 2020 14:09:35 +0000 From: Barbara Dinter <barbara.dinter(a)wirtschaft.tu-chemnitz.de> Reply-To: Barbara Dinter <barbara.dinter(a)wirtschaft.tu-chemnitz.de> To: wi(a)lists.kit.edu <wi(a)lists.kit.edu> * Bitte entschuldigen Sie etwaige Mehrfachzustellungen * === CALL FOR PAPERS === 29th European Conference on Information Systems (ECIS 2021) June 14 – 16, 2021 - Marrakesh, Morocco Track: Business Analytics and Big Data (http://ecis2021.ma/tracks-description) *Track Description* Technological advancements have contributed to the generation of massive amounts of data that unleash huge opportunities not only for organizations but also for society. The application of business analytics, business intelligence, and big data approaches enables us to integrate, analyse, visualize, and ultimately understand and improve the complex processes that make up our digitized world. Such approaches are enablers for knowledge discovery transforming societies and organizations. Over the past few years, there has been enthusiasm around business analytics as organizations explore how they can leverage their data to create and maintain a competitive advantage. Improved communication, more sustainable processes, as well as new business models are examples for the innovative use of disparate data sources (such as mobile, the Internet of Things, streaming data or social media data). In addition to the potential of transforming businesses, business analytics, business intelligence and big data can contribute to better human health and well-being, improved public services, and better support of environmental and climate causes. The datafication of our society can help the drive towards solutions that safeguard and promote human values by creating empowered societies through the use of data, building digital bridges, and maintaining sustainable and inclusive societies among others. Motivated by the explosion of interest in these emerging fields, the present track aims to promote multidisciplinary contributions dealing with socio-economic, organizational, technological, cultural, and societal perspectives. We call for submissions based on quantitative and qualitative work, theoretical research, design research, action research, or behavioral research. Furthermore, we encourage papers with outcomes that demonstrate the organizational impact of business analytics and big data in terms of competitive performance, innovativeness, increased agility, and market capitalizing competence. In particular, we welcome papers that discuss and expand our understanding of how the use of business analytics and big data is impacting fundamental human values and society at a larger scale. Please note that papers solely dealing with AI and machine learning algorithms are not the focus of this track. Suggested topics include, but are not limited to: * The role of business intelligence, business analytics, and big data for new horizons in digitally united societies * Individual and societal empowerment through business analytics and big data * Emerging and changing concepts and methodologies for business analytics and big data * Strategic and change management issues stemming from business analytics and big data * Business value of business analytics and big data * Adoption, routinization, maturity, use, and innovative applications of business analytics and big data * Data privacy, data quality, and data governance * Opportunities and challenges of sharing data and of open data * Data-driven business model innovation and the digital ecosystem big data * Data visualization, visual analytics * Business analytics in the cloud, business analytics as a service * Data, text and social media analytics for business analytics * Process mining and the benefits of robotic process automation * Digital manufacturing and the Internet of Things * Operational, real-time, or event-driven business analytics *Track Chairs* Olgerta Tona (contact), University of Gothenburg, Sweden, olgerta.tona(a)ait.gu.se <mailto:olgerta.tona@ait.gu.se> Barbara Dinter, Chemnitz University of Technology, Germany, barbara.dinter(a)wirtschaft.tu-chemnitz.de <mailto:barbara.dinter@wirtschaft.tu-chemnitz.de> Christian Janiesch, University of Würzburg, Germany, christian.janiesch(a)uni-wuerzburg.de <mailto:christian.janiesch@uni-wuerzburg.de> Patrick Mikalef, Norwegian University of Science and Technology, Norway, patrick.mikalef(a)ntnu.no <mailto:patrick.mikalef@ntnu.no> *Important Dates* 18 November 2020: Submission deadline 03 March 2021: Notification of conditional acceptance 14 -16 June 2021: ECIS 2021 conference We are looking forward to your submissions and seeing you in Marrakesh! Kind regards Olgerta, Barbara, Christian, and Patrick --- Univ.-Prof. Dr. Barbara Dinter Technische Universität Chemnitz Professur Wirtschaftsinformatik - Geschäftsprozess- und Informationsmanagement Thüringer Weg 7, 09126 Chemnitz Tel.: 0371 531 39228 Mail: Barbara.Dinter(a)wirtschaft.tu-chemnitz.de <mailto:Barbara.Dinter@wirtschaft.tu-chemnitz.de> Info: http://www.tu-chemnitz.de/wirtschaft/wi1 <http://www.tu-chemnitz.de/wirtschaft/wi1> -- Mailing-Liste: wi(a)lists.kit.edu Administrator: wi-request(a)lists.kit.edu Konfiguration: https://www.lists.kit.edu/wws/info/wi

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Fwd: [AISWorld] CFP: ISCRAM - Disaster Public Health & Healthcare Informatics in the Pandemic
by Gustaf Neumann 16 Oct '20

16 Oct '20

-------- Forwarded Message -------- Subject: [AISWorld] CFP: ISCRAM - Disaster Public Health & Healthcare Informatics in the Pandemic Date: Fri, 16 Oct 2020 09:14:42 -0500 From: Nick Lalone <nick.lalone(a)gmail.com> To: AISWorld(a)lists.aisnet.org Hi all, The Conference Information Systems for Crisis Response and Management (ISCRAM) is in Blacksburg, Virginia USA - May 23rd- 26th, 2021. https://www.drrm.fralinlifesci.vt.edu/iscram2021/call-papers.php - General Page https://www.drrm.fralinlifesci.vt.edu/iscram2021/files/CFP/ISCRAM2021-Track… - CFP in PDF We are seeking papers for our track focused on: *Disaster Public Health & Healthcare Informatics in the Pandemic. * *Description Below: * The COVID-19 pandemic places renewed focus on informatics-based approaches for healthcare systems responding to crises. The domain of disaster healthcare informatics is unique in that it involves multiple medical subdisciplines ranging from global/emergency medicine to primary care. Public health infrastructure, from community engagement to laboratory services also play a pivotal role in responding to major health crises. Health systems also must interface effectively with joint emergency operations centers often at multiple levels of government. These systems rely heavily on physicians, nurses, and EMT practitioners, and concern both population level and individual patient level data. Given these factors, data fusion/integration, data security and privacy, and the legal and ethical implications of information systems designed to support healthcare systems in crisis are of particular importance. Areas of significant innovation in disaster health informatics are occurring in part because of the complexity of the current pandemic, but also more broadly in the field. Areas of particular interest for the track include computational epidemiology, hotspotting, community situated case management, contact tracing, automated/autonomous/robotic clinical systems, human-machine collaboration, and disaster mortuary. Possible topics of interest for this track include the following: - Pandemic data management, analysis and visualization - Computational epidemiology - Digital contact tracing strategies - Autonomous/robotic clinical systems - Virtual / eVisits in healthcare - Healthcare worker’s experiences with technology supported work - Healthcare/public health data fusion in crisis events - Public health laboratories - Sentinel events and superspreaders - Simulation of healthcare processes, Covid-19 spread and responses - Hotspot detection - Disaster eHealth - eTriage - Health related mapping and geographical information - Disaster mortuary - Healthcare transformation through crisis learning - Human-machine collaborative systems for crisis If you have any questions, please feel free to contact me at nlalone(a)unomaha.edu Thanks! Nick LaLone *Assistant Professor* *Department of Information Systems & Quantitative Analysis* College of Information Sciences and Technology *University of Nebraska at Omaha* www.nicklalone.com _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [AISWorld] Call for Papers - Business Analytics and Big Data at European Conference on Information Systems (ECIS 2021)
by Gustaf Neumann 16 Oct '20

16 Oct '20

-------- Forwarded Message -------- Subject: [AISWorld] Call for Papers - Business Analytics and Big Data at European Conference on Information Systems (ECIS 2021) Date: Fri, 16 Oct 2020 09:01:06 +0000 From: Olgerta Tona <olgerta.tona(a)ait.gu.se> To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org> 29th European Conference on Information Systems (ECIS 2021) June 14 – 16, 2021 - Marrakesh, Morocco Track: Business Analytics and Big Data (http://www.ecis2021.com/tracks-description) *Track Description* Technological advancements have contributed to the generation of massive amounts of data that unleash huge opportunities not only for organizations but also for society. The application of business analytics, business intelligence, and big data approaches enables us to integrate, analyse, visualize, and ultimately understand and improve the complex processes that make up our digitized world. Such approaches are enablers for knowledge discovery transforming societies and organizations. Over the past few years, there has been enthusiasm around business analytics as organizations explore how they can leverage their data to create and maintain a competitive advantage. Improved communication, more sustainable processes, as well as new business models are examples for the innovative use of disparate data sources (such as mobile, the Internet of Things, streaming data or social media data). In addition to the potential of transforming businesses, business analytics, business intelligence and big data can contribute to better human health and well-being, improved public services, and better support of environmental and climate causes. The datafication of our society can help the drive towards solutions that safeguard and promote human values by creating empowered societies through the use of data, building digital bridges, and maintaining sustainable and inclusive societies among others. Motivated by the explosion of interest in these emerging fields, the present track aims to promote multidisciplinary contributions dealing with socio-economic, organizational, technological, cultural, and societal perspectives. We call for submissions based on quantitative and qualitative work, theoretical research, design research, action research, or behavioral research. Furthermore, we encourage papers with outcomes that demonstrate the organizational impact of business analytics and big data in terms of competitive performance, innovativeness, increased agility, and market capitalizing competence. In particular, we welcome papers that discuss and expand our understanding of how the use of business analytics and big data is impacting fundamental human values and society at a larger scale. Please note that papers solely dealing with AI and machine learning algorithms are not the focus of this track. Suggested topics include, but are not limited to: * The role of business intelligence, business analytics, and big data for new horizons in digitally united societies * Individual and societal empowerment through business analytics and big data * Emerging and changing concepts and methodologies for business analytics and big data * Strategic and change management issues stemming from business analytics and big data * Business value of business analytics and big data * Adoption, routinization, maturity, use, and innovative applications of business analytics and big data * Data privacy, data quality, and data governance * Opportunities and challenges of sharing data and of open data * Data-driven business model innovation and the digital ecosystem big data * Data visualization, visual analytics * Business analytics in the cloud, business analytics as a service * Data, text and social media analytics for business analytics * Process mining and the benefits of robotic process automation * Digital manufacturing and the Internet of Things * Operational, real-time, or event-driven business analytics *Track Chairs* Olgerta Tona, (contact) University of Gothenburg, Sweden, olgerta.tona(a)ait.gu.se Barbara Dinter, Chemnitz University of Technology, Germany, barbara.dinter(a)wirtschaft.tu-chemnitz.de Christian Janiesch, University of Würzburg, Germany, christian.janiesch(a)uni-wuerzburg.de Patrick Mikalef, Norwegian University of Science and Technology, Norway, patrick.mikalef(a)ntnu.no *Important Dates* 18 November 2020: Submission deadline 03 March 2021: Notification of conditional acceptance 14 -16 June 2021: ECIS 2021 conference We are looking forward to your submissions and seeing you in Marrakesh! Regards Barbara, Christian, Olgerta, and Patrick _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [AISWorld] Call for Short Papers (International FinTech, InsurTech & Blockchain Forum 2020 | Nov. 13th | Zurich & Online) -- Submission Deadline: October 30, 2020.
by Gustaf Neumann 16 Oct '20

16 Oct '20

-------- Forwarded Message -------- Subject: [AISWorld] Call for Short Papers (International FinTech, InsurTech & Blockchain Forum 2020 | Nov. 13th | Zurich & Online) -- Submission Deadline: October 30, 2020. Date: Fri, 16 Oct 2020 11:41:23 +0200 From: Thomas Puschmann <thomas.puschmann(a)uzh.ch> To: aisworld(a)lists.aisnet.org ** Call for Short Papers: International FinTech, InsurTech & Blockchain Forum** ** Website: www.fintech-forum.org <http://www.fintech-forum.org/>** ** Submission Deadline: October 30th, 2020** ** Location: Zurich, Switzerland & Online; Date: Nov. 13, 2020 ** The "International FinTech, InsurTech and Blockchain Forum" invites short papers for submission. All submissions should be formatted as five-page extended abstracts (up to 4 pages for content and 1 page for literature). As we want to foster a diversity of innovative ideas from a broad variety of disciplines and research fields, submissions may refer to work that is recently published, is currently under review elsewhere, or in preparation, and may link to content of one publicly accessible paper. However, each submission will be evaluated solely on the submitted abstract, which must therefore comprise an entirely self-contained description of the work. Topics of interest include, but are not limited to: Theories of fintech, insurtech, blockchain and the internet of value Reference models for fintech, insurtech, blockchain and the internet of value Architectures for fintech, insurtech, blockchain and the internet of value Fintech, insurtech and blockchain technologies and standards Applications for fintech, insurtech, blockchain and the internet of value techfin / bigtech Cryptocurrencies, digital currencies, central bank digital currencies Token economy Novel ways of asset and investment management Smart contracts Financial peer-to-peer markets Digital identity and data privacy Regulatory technology Digital client relationships in financial services Social and robo advisory models Fintech-enabled business models Financial inclusion Future financial services ecosystems Future financial market infrastructures Green fintech, sustainable digital finance Important dates: October 30th: Submission Deadline November 6th: Paper Acceptance Information November 13th: Conference and Paper Session (Online and Onsite) More information can be found here: https://www.fintech-forum.org/submissions <https://www.fintech-forum.org/submissions> On behalf of the Program Committee: Thomas Puschmann (University of Zurich) Douglas Arner (University of Hong Kong) Markus K. Brunnermeier (Princeton University) Damir Filipovic (EPFL) Urs Gasser (Harvard University) Kay Giesecke (Stanford University) Terrence Hendershott (University of California at Berkeley) Thorsten Hens (University of Zurich) Michael G. Jacobides (London Business School) William J. Knottenbelt (Imperial College) Alex (Sandy) Pentland (MIT) Raghavendra Rau (University of Cambridge) Burkhard Stiller (University of Zurich) Nir Vulkan (University of Oxford) Rolf H. Weber (University of Zurich) David L. Yermack (NYU Stern School of Business) J. Leon Zhao (City University of Hong Kong) _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [WI] LATA 2020 & 2021: extended submission deadline October 26
by Gustaf Neumann 16 Oct '20

16 Oct '20

-------- Forwarded Message -------- Subject: [WI] LATA 2020 & 2021: extended submission deadline October 26 Date: Fri, 16 Oct 2020 02:44:20 +0200 From: IRDTA <irdta(a)irdta.eu> Reply-To: IRDTA <irdta(a)irdta.eu> To: wi(a)lists.kit.edu LATA 2020 & 2021: extended submission deadline October 26 *To be removed from our mailing list, please respond to this message with UNSUBSCRIBE in the subject line* ******************************************************************************* *14^th -15^th INTERNATIONAL CONFERENCE ON LANGUAGE AND AUTOMATA THEORY AND APPLICATIONS* *LATA 2020 & 2021* *Milan, Italy* *March 1-5, 2021* Co-organized by: Department of Informatics, Systems and Communication University of Milano-Bicocca and Institute for Research Development, Training and Advice Brussels/London https://irdta.eu/lata2020-2021/ ******************************************************************************* _* Extended submission deadline: October 26 *_ *AIMS:* LATA is a conference series on theoretical computer science and its applications. LATA 2020 & 2021 will reserve significant room for young scholars at the beginning of their career. It will aim at attracting contributions from classical theory fields as well as application areas. LATA 2020 & 2021 will merge the scheduled program for LATA 2020, which could not take place because of the Covid-19 crisis, with a new series of papers submitted on this occasion. *VENUE:* LATA 2020 & 2021 will be held in Milan, the third largest economy among European cities and one of the Four Motors for Europe. The venue will be: University of Milano-Bicocca Viale Piero e Alberto Pirelli 22 Building U6 Aula Mario Martini (Aula U6-04) Milan *SCOPE:* Topics of either theoretical or applied interest include, but are not limited to: algebraic language theory algorithms for semi-structured data mining algorithms on automata and words automata and logic automata for system analysis and programme verification automata networks automatic structures codes combinatorics on words computational complexity concurrency and Petri nets data and image compression descriptional complexity foundations of finite state technology foundations of XML grammars (Chomsky hierarchy, contextual, unification, categorial, etc.) grammatical inference, inductive inference and algorithmic learning graphs and graph transformation language varieties and semigroups language-based cryptography mathematical and logical foundations of programming methodologies parallel and regulated rewriting parsing patterns power series string processing algorithms symbolic dynamics term rewriting transducers trees, tree languages and tree automata weighted automata *STRUCTURE:* LATA 2020 & 2021 will consist of: invited talks peer-reviewed contributions *KEYNOTE SPEAKERS:* Eric Allender (Rutgers University), The New Complexity Landscape around Circuit Minimization Laure Daviaud (City, University of London), About Decision Problems for Weighted Automata Christoph Haase (University College London), Approaching Arithmetic Theories with Finite-state Automata Artur Jeż (University of Wrocław), Recompression: Technique for Word Equations and Compressed Data Jean-Éric Pin (CNRS), How to Prove that a Language Is Regular or Star-free? Thomas Place (University of Bordeaux), Deciding Classes of Regular Languages: A Language Theoretic Point of View *PROGRAMME COMMITTEE:* Jorge Almeida (University of Porto, PT) Franz Baader (Technical University of Dresden, DE) Alessandro Barenghi (Polytechnic University of Milan, IT) Marie-Pierre Béal (University of Paris-Est, FR) Djamal Belazzougui (CERIST, DZ) Marcello Bonsangue (Leiden University, NL) Flavio Corradini (University of Camerino, IT) Bruno Courcelle (University of Bordeaux, FR) Laurent Doyen (ENS Paris-Saclay, FR) Manfred Droste (Leipzig University, DE) Rudolf Freund (Technical University of Vienna, AT) Paweł Gawrychowski (University of Wrocław, PL) Amélie Gheerbrant (Paris Diderot University, FR) Tero Harju (University of Turku, FI) Lane A. Hemaspaandra (University of Rochester, US) Jarkko Kari (University of Turku, FI) Dexter Kozen (Cornell University, US) Markus Lohrey (University of Siegen, DE) Parthasarathy Madhusudan (University of Illinois, Urbana-Champaign, US) Sebastian Maneth (University of Bremen, DE) Nicolas Markey (IRISA, Rennes, FR) Carlos Martín-Vide (Rovira i Virgili University, ES, chair) Giancarlo Mauri (University of Milano-Bicocca, IT) Victor Mitrana (University of Bucharest, RO) Paliath Narendran (University at Albany, US) Gennaro Parlato (University of Molise, IT) Dominique Perrin (University of Paris-Est, FR) Nir Piterman (Chalmers University of Technology, SE) Sanguthevar Rajasekaran (University of Connecticut, US) Antonio Restivo (University of Palermo, IT) Wojciech Rytter (University of Warsaw, PL) Kai Salomaa (Queen’s University, CA) Helmut Seidl (Technical University of Munich, DE) William F. Smyth (McMaster University, CA) Jiří Srba (Aalborg University, DK) Edward Stabler (University of California, Los Angeles, US) Benjamin Steinberg (City University of New York, US) Frank Stephan (National University of Singapore, SG) Jan van Leeuwen (Utrecht University, NL) Margus Veanes (Microsoft Research, US) Mikhail Volkov (Ural Federal University, RU) *ORGANIZING COMMITTEE:* Alberto Leporati (Milan, co-chair) Sara Morales (Brussels) Manuel Parra-Royón (Granada) Rafael Peñaloza Nyssen (Milan) Dana Shapira (Ariel) David Silva (London, co-chair) Bianca Truthe (Giessen) Claudio Zandron (Milan, co-chair) *SUBMISSIONS:* Authors are invited to submit non-anonymized papers in English presenting original and unpublished research. Papers should not exceed 12 single-spaced pages (all included) and should be prepared according to the standard format for Springer Verlag's LNCS series (see http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0). If necessary, exceptionally authors are allowed to provide missing proofs in a clearly marked appendix. Upload submissions to: https://easychair.org/conferences/?conf=lata20202021 *PUBLICATIONS:* A volume of proceedings published by Springer in the LNCS series will be available by the time of the conference. A special issue of Information and Computation (Elsevier, 2019 JCR impact factor: 0.872) will be later published containing peer-reviewed substantially extended versions of some of the papers contributed to the conference. Submissions to it will be by invitation. *REGISTRATION:* The registration form can be found at: https://irdta.eu/lata2020-2021/registration/ *DEADLINES *(all at 23:59 CET)*:* Paper submission: October 26, 2020 – EXTENDED - Notification of paper acceptance or rejection: November 23, 2020 Final version of the paper for the LNCS proceedings: November 30, 2020 Early registration: November 30, 2020 Late registration: February 15, 2021 Submission to the journal special issue: June 5, 2021 *QUESTIONS AND FURTHER INFORMATION:* david (at) irdta.eu *ACKNOWLEDGMENTS:* Università degli Studi di Milano-Bicocca IRDTA – Institute for Research Development, Training and Advice, Brussels/London -- Mailing-Liste: wi(a)lists.kit.edu Administrator: wi-request(a)lists.kit.edu Konfiguration: https://www.lists.kit.edu/wws/info/wi

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Fwd: [AISWorld] *New Issue* ACM Transactions on Human-Robot Interaction 9(4) October 2020
by Gustaf Neumann 16 Oct '20

16 Oct '20

-------- Forwarded Message -------- Subject: [AISWorld] *New Issue* ACM Transactions on Human-Robot Interaction 9(4) October 2020 Date: 15 Oct 2020 13:26:10 -0500 From: young(a)cs.umanitoba.ca To: aisworld(a)lists.aisnet.org ============================================ ACM Transactions on Human-Robot Interaction ============================================ We are pleased to announce the publication of Volume 9, Issue 4, October 2020. https://dl.acm.org/toc/thri/2020/9/4 ============================================ October 2020 ============================================ Destruction, Catharsis, and Emotional Release in Human-Robot Interaction Michal Luria, Ophir Sheriff, Marian Boo, Jodi Forlizzi, Amit Zoran Abstract: The intersection between social, technical, and economic factors biases new product development to focus on utilitarian value. However, objects that serve alternative goals, behaviors and emotions have accompanied humankind for millennia. This article ... DOI: https://doi.org/10.1145/3385007. Where Do You Think You're Going?: Characterizing Spatial Mental Models from Planned Routes Brandon S. Perelman, Arthur W. Evans III, Kristin E. Schaefer Abstract: Route planning is a critical behavior for human-intelligent agent (H-IA) team mobility. The scientific community has made major advances in improving route planner optimality and speed. However, human factors, such as the ability to predict and ... DOI: https://doi.org/10.1145/3385008. Measuring the Perceived Social Intelligence of Robots Kimberly A. Barchard, Leiszle Lapping-Carr, R. Shane Westfall, Andrea Fink-Armold, Santosh Balajee Banisetty, David Feil-Seifer Abstract: Robotic social intelligence is increasingly important. However, measures of human social intelligence omit basic skills, and robot-specific scales do not focus on social intelligence. We combined human robot interaction concepts of beliefs, desires, and ... DOI: https://doi.org/10.1145/3415139. Towards Effective Interface Designs for Collaborative HRI in Manufacturing: Metrics and Measures Jeremy A. Marvel, Shelly Bagchi, Megan Zimmerman, Brian Antonishek Abstract: We present a comprehensive framework and test methodology for the evaluation of human-machine interfaces (HMI) and human-robot interactions (HRI) in collaborative manufacturing applications. An overview of the challenges that face current- and next-... DOI: https://doi.org/10.1145/3385009. Human Perception of Social Robot’s Emotional States via Facial and Thermal Expressions Denis Peña, Fumihide Tanaka Abstract: Facial and thermal expressions can be used by humans to interpret emotions. While facial expressions can be a voluntary reaction, the change of temperature in the body is often not. Thus, a facial expression may not always be consistent with the ... DOI: https://doi.org/10.1145/3388469. The Influence of Robot Number on Robot Group Perception—A Call for Action Ricarda Wullenkord, Friederike Eyssel Abstract: Research on robot groups has often applied psychological principles underlying group processes between humans to interactions with and between robots. However, such research has failed to test empirically whether these principles indeed apply to the ... DOI: https://doi.org/10.1145/3394899. Embodiment, Presence, and Their Intersections: Teleoperation and Beyond Nicolas Nostadt, David A. Abbink, Oliver Christ, Philipp Beckerle Abstract: Subjective experience of human control over remote, artificial, or virtual limbs has traditionally been investigated from two separate angles: presence research originates from teleoperation, aiming to capture to what extent the user feels like actually ... DOI: https://doi.org/10.1145/3389210. ============================================ ACM THRI welcomes contributions from across HRI and Robotics. For details on the journal, information for authors, and upcoming Special Issues, please visit the ACM THRI website: http://thri.acm.org Odest Chadwicke Jenkins Selma Sabanovic ACM THRI Editors-in-Chief James Young, University of Manitoba ACM THRI Managing Editor _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [AISWorld] Last Call For Book Chapters: Handbook of Research on Intelligent Analytics with Multi-Industry Applications
by Gustaf Neumann 16 Oct '20

16 Oct '20

-------- Forwarded Message -------- Subject: [AISWorld] Last Call For Book Chapters: Handbook of Research on Intelligent Analytics with Multi-Industry Applications Date: Fri, 16 Oct 2020 13:41:05 +1000 From: Zhaohao Sun <zhaohao.sun(a)gmail.com> To: aisworld(a)lists.aisnet.org BOOK: Handbook of Research on Intelligent Analytics with Multi-Industry Applications EDITED BY PROF. DR. ZHAOHAO SUN TO BE PUBLISHED BY IGI Global, USA https://www.igi-global.com/publish/call-for-papers/call-details/4539 or http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=96711 or https://www.researchgate.net/project/Intelligent-Analytics-with-Applications Introduction Intelligent analytics is an emerging scientific paradigm that integrates big data/information/knowledge/wisdom, analytics and artificial intelligence (AI) to provide smart services to our work, business, life, industry and society. From a fundamental perspective, intelligent analytics at least includes intelligent big data analytics, intelligent big information analytics, intelligent big knowledge analytics, intelligent big wisdom analytics. Intelligent analytics has been revolutionizing our work, life, business, management, organization and industry. It becomes disruptive technology for healthcare, web services, service computing, cloud computing, 5G development, blockchain and social networking computing. However, many fundamental, technological and managerial issues in developing and applying intelligent analytics with multi-industry applications remain open. For example, what is the foundation of intelligent analytics? what are the elements of intelligent analytics? What are the real big characteristics of intelligent analytics? How can apply intelligent analytics to improve healthcare, mobile commerce, web services, cloud services, blockchain, 5G development, digital transformation and industries? What is the effect of intelligent analytics on business, management, the Internet of things, cloud computing, blockchain, service and society? This book will address these issues by exploring the cutting-edge theory, technologies and methodologies of intelligent analytics with multi-industry applications and emphasize integration of AI, business intelligence, big data/information/knowledge/wisdom, and analytics from a perspective of computing, service and management. This book also provides applications of the proposed theory, technologies and methodologies of intelligent analytics to e-SMACS (electronic, social, mobile, analytics, cloud and service) commerce and services, healthcare, the Internet of things, sharing economy, cloud computing, blockchain, and Industry 4.0 in the real world. This book titled “Intelligent Analytics with Multi-industry Applications” is the first book to reveal the cutting-edge theory, technologies, methodologies of intelligent analytics with applications. This is also the first book demonstrating that intelligent analytics is an important enabler for developing cloud computing, 5G, blockchains, digital transformation, business, management, governance and services in multi-industry applications. The proposed approaches will facilitate research, development and applications of intelligent analytics, big data/information/knowledge/wisdom analytics, data science, digital transformation, e-business and web service, service computing, cloud computing and social computing. Aims, Scope and Target Audience This book’s primary aim is to convey the foundations, technologies, thoughts, and methods of intelligent analytics with multi-industry applications to scientists, engineers, educators and university students, business, service and management professionals, policy makers and decision makers and others who have interest in big data, big information, big knowledge and big intelligence and wisdom, intelligent analytics, AI, cloud computing, the Internet of things (IoT), digital transformation, SMACS intelligence and computing, commerce and service as well as data science, information science, and knowledge science. Primary audiences for this book are undergraduate, postgraduate students and variety of professionals in the fields of big data, data science, information science and technology, knowledge technology and engineering, intelligence science, analytics, AI, computing, commerce, business, services, management and government. The variety of readers in the fields of government, consulting, marketing, business and trade as well as the readers from all the social strata can also be benefited from this book to improve understanding of the cutting-edge theory, technologies, methodologies and applications of intelligent analytics with applications. Papers as book chapters of all theoretical and technological approaches, and applications of intelligent analytics are welcome. Submissions that cross multiple disciplines such as management, service, business, artificial intelligence, intelligent systems, data science, optimization, statistics, information systems, decision sciences, and industries to develop theory and provide technologies and applications that could move theory and practice forward in intelligent analytics, are especially encouraged. Topics Topics of contributions to this book include four parts: foundations, technologies, applications and emerging technologies and applications of intelligent analytics as follows. Part I. Foundations of intelligent analytics Topics: fundamental concepts, models/architectures, frameworks/schemes or foundations for developing, operating, evaluating, managing intelligent analytics. The following topics might also include, but not limited to. • Intelligent analytics as a Science and Technology (IAaaST) • Big Data science • Big Data intelligence • Intelligent Analytics for big data, information, knowledge, intelligence and wisdom • Intelligent analytics in business ecosystems • Decision science for intelligent analytics • Computing and foundations of intelligent analytics • New computational models for Big Data • Mathematical fundamentals of intelligent Big Data analytics • Fuzzy logic approach to intelligent analytics • Graph theory for intelligent analytics • ICT fundamentals for analytics • Intelligent visualization techniques for analytics • Statistical modelling for intelligent analytics • Machine learning for intelligent analytics • Optimization techniques for intelligent analytics • Data mining for intelligent analytics • Business models for intelligent analytics • Real-time algorithms for intelligent analytics • Computing thinking for intelligent analytics Part II. Technologies for intelligent analytics Topics: Technologies for developing intelligent analytics might also include the following topics, but not limited to. * Intelligent Analytics as a System (IAaaSy) * Intelligent Analytics as a Service (IAaaSe) * Intelligent Analytics as a Management (IAaaM) * Intelligent Analytics as a Business (IAaaB) * Rule-based systems, * Machine learning, * Multi-agent systems, * Neural networks systems, * Fuzzy logic, * Cased-based reasoning, * Genetic algorithms, * Data mining algorithms, * Intelligent agents, * Intelligent user interfaces * Web technologies, * Intelligent big data/information/knowledge technologies, * Intelligent service technologies, * Social networking technologies, * Intelligent decision technologies, * Intelligent management technologies and business technologies. * Machine-to-machine communication Part III. Multi-industry Applications of intelligent analytics Topics: cases for using foundations and technologies in Part I, II in multi-industry applications and various domains such as digital transformation, blockchain, 5G, SMACS computing, commerce and services, financial services, legal services, healthcare services, educational services, and military services taking into account intelligent diagnostic, descriptive, predictive and prescriptive analytics. The following topics might also include, but not limited to. * Intelligent Analytics as an application * Intelligent analytics with applications * Intelligent analytics-based innovation and entrepreneurship * Intelligent analytics in business ecosystems * Intelligent analytics with public and open data * Intelligent analytics and markets * Intelligent analytics for e-commerce * Intelligent analytics for cloud computing * Intelligent analytics for IoT * Intelligent analytics for blockchain * Intelligent analytics for 5G applications * Intelligent analytics in business decision making * Intelligent analytics in healthcare * Marketing Analytics * Intelligent analytics in banking industry * Intelligent analytics in social networking services * Intelligent analytics for Big Data, information, knowledge and intelligence * Cybersecurity and privacy issues in Intelligent analytics. * Intelligent analytics for management * Intelligent analytics for risk management * Organization analytics Part IV. Emerging technologies and applications for intelligent analytics Topics: Emerging technologies, methodologies, and applications for intelligent analytics. The following topics might also include, but not limited to * Emergent AI-based technologies * Emergent intelligent analytics technologies * Challenges for intelligent big data analytics * Challenges for intelligent big information analytics * Challenges for intelligent big knowledge analytics * Challenges for intelligent analytics research * Challenges for intelligent analytics applications * Challenges for intelligent analytics tools Submission Procedure Please submit a brief summary (abstract) consisting of title and round 150-200 words for the proposed chapter clearly identifying the main objectives of your contribution online by clicking “propose a chapter” at https://www.igi-global.com/publish/call-for-papers/call-details/4539 or to the editor at zhaohao.sun(a)gmail.com assp. Authors of the accepted proposals will be notified and provided with detailed guidelines. Full chapters are to be submitted based on the communication with the editor. Submission Format and Evaluation This book will be developed using the eEditorial Discovery™ online submission manager. Therefore, all manuscripts of book chapter must be submitted online using https://www.igi-global.com/submission/submit-chapter/?projectid=8480e8ad-d6… Every book chapter submission should consist of 8,000-12,000 words, and be structured into sections including Abstract, Introduction, background (or related work), main sections, future research directions, conclusion, references. Every book chapter must be submitted in Microsoft® Word, and be typewritten in English in APA style based on “manage source” and “insert citation” function. Every book chapter submission is original. Only ORIGINAL articles will be accepted for publication by IGI-Global. Upon acceptance of your article, you will be required to sign a warranty that your article is original and has NOT been submitted for publication or published elsewhere. All chapter submissions undergo a double-blind peer-review using the eEditorial Discovery™ online submission manager. Conditioned chapters will have an additional opportunity for being improved and evaluated. In the second evaluation, a definitive editorial decision among: accepted or rejected will be reported. All of the accepted chapters must be submitted according to the Editorial publishing format rules timely. Instructions for authors can be downloaded at: http://www.igi-global.com/Files/AuthorEditor/guidelinessubmission.pdf. The final chapters are copy edited/proofed by the authors prior to submission, following the IGI Global chapter formatting and submission guidelines. Important Dates *October 30, 2020*: Proposal Submission Deadline * October 30, 2020:* Full Chapter Submission *November 18, 2020:* Review Results Returned * November 19, 2020:* Final Acceptance Notification * November 20, 2020:* Final Chapter Submission December 2020: estimated publishing period. This is the last chance for scholars who have interest to contribute to this book. Editor Information Prof. Dr. Zhaohao Sun, Ph.D. Editor of Handbook of Research on Intelligent Analytics with Multi-Industry Applications Research Centre of Big Data Analytics and Intelligent Systems (BAIS) Department of Business Studies PNG University of Technology Morobe, PNG _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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