Embed Size (px)
Citation preview
Decision Analytics, Mobile Services, and Service Science
The DA/MS/SS Track focuses on emerging managerial and organizational decision-‐making strategies, processes, tools, technologies, services and solutions in the Digital Age. This track has four interrelated themes. Analytics focuses on decision making processes, models, tools and technologies. Mobile Services work with the development and delivery of data, information and services with mobile technology platforms. Challenges and issues of emerging service industries, and service orientation and -‐transformation of strategies, processes, organizations, systems and technologies are covered in Service Science. In this track, we also discuss innovative approaches of decision making for/with Critical and Emerging Solutions in a number of high-‐impact areas. Minitracks:
• Addressing Grand Challenges with Systems Sciences • Analytics, Information Systems and Decision Technologies for Sustainability • Big Data and Analytics: Concepts, Methods, Techniques and Applications • Business Value of the Internet of Things • Data, Text and Web Mining for Business Analytics • Decision Support for Smart City and E-‐Society Services • Digital and ICT Enabled Services • Digital Service Innovations based on "Open" Phenomena and Practices • Gamification: Motivations, Effects, and Analytics • Humanitarian Operations Research -‐ Decision Analytics for Crisis and Disaster Management • Intelligent Decision Support for Logistics and Supply Chain Management • Interactive Visual Decision Analytics • Mobile Value Services • Multi-‐criteria Decision Analysis and Support Systems • Service Analytics • Service Science • Smart Service Systems: Analytics, Cognition and Innovation • Soft Computing • Streaming Data Analytics and Applications • Systemic Financial Risk Analytics • Wearables and Quantified Self
Track Chairs: Christer Carlsson Institute for Advanced Management Systems Research ICT House A4053 Abo Akademi University 20520 Turku, Finland Tel: +358-‐2-‐215-‐4196 Fax: +358-‐2-‐251-‐9912 Email: [email protected]
Haluk Demirkan Milgard School of Business University of Washington – Tacoma 1900 Commerce Street Box 358420 Tacoma, WA 98402-‐3100 Tel: (253) 692-‐5751 Fax: (253) 692-‐4523 Email: [email protected]
Addressing Grand Challenges with Systems Sciences
This minitrack provides a forum for the discussion of the world’s most important or challenging problems, and the role that system science can play in resolving those problems. In contrast to papers which focus on a narrow problem domain, this minitrack seeks submissions which address big, important issues, the resolution of which would be widely beneficial to mankind. Papers that propose innovative, ambitious, or unusual system science-‐based solutions to humanity’s greatest problems are particularly encouraged. Papers which leverage the system sciences to address any of the world’s most important or challenging problems are welcome. Problem domains of interest include, but are not limited to:
• Biodiversity • Climate change and other environmental issues • Economic stability and prosperity • Education • Energy • Geopolitical stability • Global development • Health, disease, and other medical issues • Human rights • Hunger, poverty, and clean drinking water • Natural disasters • Sustainability • Women's rights
Minitrack Chair: Daniel Soper California State University, Fullerton Tel: (657) 278-‐7270 Email: [email protected]
Analytics, Information Systems and Decision Technologies for Sustainability The minitrack welcomes research articles and practitioner reports exploring technical and organizational issues pertaining to innovative ways for leveraging information systems and technologies for addressing sustainability issues, and research to mitigate the impact of economic development and information technologies on the environment. The minitrack encompasses environmental informatics and analytics, sustainable computing, and Green IT. Theoretically founded papers that illustrate the application of advanced communication and decision technologies in are particularly welcomed. Possible topics include, but are not limited to:
• Analytics and decision technologies • Collective awareness platforms • Environmental sustainability and decision making • Environmental knowledge acquisition and management • Environmental Management Information Systems (EMIS), Environmental Decision Support
Systems (EDSS), and Green Information Systems (IS) • Green IT • Environmental cyberinfrastructure • Environmental communication • Energy Informatics • Technologies for decision support systems development and environmental applications
(e.g., GIS, computational intelligence, service-‐oriented computing, web services, semantic web, artificial intelligence, agent-‐based computing, and multiple criteria decision making)
Minitrack Co-‐Chairs: Omar El-‐Gayar (Primary Contact) College of Business and Information Systems Dakota State University Tel: (605) 256-‐5799 Email: Omar.El-‐[email protected] Arno Scharl Department of New Media Technology MODUL University Vienna Email: [email protected] PingSun Leung Department of Natural Resources and Environmental Management University of Hawaii at Manoa Email: [email protected]
Big Data and Analytics: Concepts, Methods, Techniques and Applications This minitrack solicits paper submissions that: advance our knowledge of Big Data storage and structure; help us learn about effective processes and approaches to effectively manage Big Data and the associated business analytics; begin to identify ways to measure the organizational benefits derived from using and analyzing Big Data; present case studies of Big Data implementation and use; and address the organizational and business aspects of big data and analytics. Papers will be solicited in several areas, including, but not limited to the following: • Challenges in managing big data repositories and projects • Graph analytics -‐ both syntactic and semantic -‐ that play a big role in the exploitation of social
media data • Advanced analytics, -‐ emphasizing visual analytics and non-‐numeric analysis models and their
implementation as applied to complex problems in different domains • Scalable semantic annotation and reasoning across big data stores • Metrics for assessing the impact of big data in business, scientific, and governmental decision-‐
making • Organizational and business aspects of big data, analytics and data science • Crowdsourcing as a distributed, complex analytic tool. Minitrack Co-‐Chairs: Stephen Kaisler (Primary Contact) SHK & Associates 8822 Cardinal Forest Circle Laurel, MD 20723 Tel: (301) 498-‐4244 Email: [email protected] Frank Armour Kogod School of Business American University 4400 Massachusetts Avenue, NW Washington, DC 20016 Tel: (202) 251-‐3554 Email: [email protected] Alberto Espinosa Kogod School of Business American University 4400 Massachusetts Avenue, NW Washington, DC 20016 Tel: (202) 885-‐1958 Email: [email protected]
Business Value of the Internet of Things This minitrack addresses managerial and organizational issues organizations face as they seek to create and realize business value from incorporating the emerging Internet of Things into their organizational infrastructure, their electronic business partner relationships, and the products and services they offer to customers. We encourage authors to share new and interesting theoretical and methodological perspectives on topics relevant to both academic researchers and practitioners. We welcome work-‐in-‐progress that examines existing and extended theory using the IoT combined with wireless sensor networks, RFID, and big data analytics as the technologies of focus and case studies of organizations implementing the IoT inside and outside their span of control. We give special consideration to research submissions when the author(s) commit to include an industry partner in their presentation. We welcome research that reflects a range of current research methods including case studies, analytical models, econometrics, and frameworks. Minitrack Co-‐Chairs: Fred Riggins (Primary Contact) North Dakota State University Tel: (651) 335-‐8417 Email: [email protected] Matthias Dehmer Bundeswehr University Munich, Germany Email: [email protected]
Samuel Fosso Wamba NEOMA Business School, France Email: samuel.fosso.wamba@neoma-‐bs.fr
Data, Text and Web Mining for Business Analytics Data mining is the process of discovering valid, novel, potentially useful, and ultimately understandable patterns (i.e., nuggets of knowledge) in data stored in structured databases, where the data is organized in records populated by categorical, ordinal and continuous variables. Text mining, on the other hand, refers to the very same discovery process as it applies to unstructured data sources including business documents, customer comments, Web pages, and XML files. This minitrack focuses on decision support aspects of advanced analytics, with emphasis on data, text and Web mining. Topic areas covered in this minitrack include, but are not limited to: • New methods and algorithms of data/text/Web mining • The process and new methodologies of conducting data/text/Web mining • Ethical and privacy issues in data/text/Web mining • Novel, interesting applications of data/text/Web mining for better decision making • Data pre-‐processing related aspect of data/text/Web mining, such as data characterization,
data cleaning, data integration, data sampling, data reduction, data visualization. Minitrack Co-‐Chairs: Dursun Delen Oklahoma State University Tel: (918) 594-‐8283 Email: [email protected]
Decision Support for Smart City and E-‐Society Services Developing smart city and enhancing e-‐society services are the critical important to urbanization process for improving the effectiveness and efficiency of traditional cities. With the massive applications of Internet of things (IoT), mobile networks, and social networks, unprecedentedly large amount of various heterogeneous data can be gathered and processed in terms of advanced analytics to support smart applications and e-‐society services. Furthermore, decision support tools and soft computing models can be employed to speed up the whole process. This minitrack addresses issues that focus on the applications of various decision support tools, such as big data analytics, decision analysis, and soft computing, to develop smart city applications and e-‐society services. We also encourage papers to report on system level research and case studies related to smart city and e-‐society. Topics of interest include, but are not limited to:
• Advanced analytics for smart city planning and e-‐society services • Case study and best practices for smart cities and e-‐society services • Decision support models and tools for smart city and e-‐society services • Design and implementation of intelligent systems for smart city applications • Innovative applications in smart cities, such as smart finance, smart health, smart research,
and smart travel • Novel applications in e-‐society services, such as information recommendation, social media
analytics, and crowdsourcing applications • Soft computing for smart city and e-‐society services
Minitrack Co-‐Chairs: Wei Xu (Primary Contact) School of Information Renmin University of China Tel: + 86-‐10-‐8250-‐0904 Email: [email protected] Jian Ma Department of Information Systems City University of Hong Kong Tel: + 852-‐2788-‐8514
Digital and ICT Enabled Services The purpose of the minitrack is to draw researchers’ attention to the innovation, design, development, management, and use of Digital and ICT Enabled Services for both Consumers and Enterprises. It will provide a discussion forum for researchers interested in fostering analytics-‐based and service-‐based approaches to theoretical and practical problems related to such services [1-‐6]. In a broad sense, ICT enabled services can be defined as [1] : ‘..systems that enable value co-‐creation through the development and implementation of information and communication technology enabled processes that integrate system value propositions with customer value drivers.’ These services meld the worlds of bits and atoms and promise to transform the transportation, energy, and other sectors like the media industries before them. Examples of such ICT enabled services are, e.g., NFC enabled Air New Zealand frequent flyer cards that facilitate check-‐in and identity verification, mobile ticketing services for public transport, digital services for music festival participants to interact and co-‐create with each other before, during, after the event, smart television services and content, tablet-‐based services for ordering food and drinks at a casino or restaurant, etc. Likewise, there are substantial opportunities for ICT-‐driven service innovation in business-‐to-‐business settings. These opportunities exist particularly in manufacturing in which innovation activities increase the digitization of products and production processes. We see that the global awareness of the power of the manufacturing industry will be linked to horizontal cyber-‐physical systems that enable value co-‐creation in the networked business environment. The cyber-‐aspects of such systems are ICT infrastructure, computer hardware, software, and different kind of sensors and actors. These components turn cyber-‐physical systems into platforms for designing and operating service. The data on products and processes gained through networked CPS and the ability to act on this data through control systems and actors enables novel ways of co-‐creating service in industrial contexts. This emerging area of research raises interesting questions. For example, traditional development approaches focus on improving the efficiency and effectiveness of organizational processes. The design of ICT enabled services may, however, require an emphasis on the socio-‐psychological aspects, such as the value-‐in-‐use and user/consumer/co-‐creator experiences. Similarly, we consider that the design and development of digital services is an important topic and we see that there are different continuums of ICT enables services. One of these continuums is the level of digitalization. Another is likely to be related to cyber-‐physical aspects of services and how the service is linked to the physical world through sensors and/or people’s interactions. Discussion Topics: The shift of consumer and enterprise personnel from users to co-‐creators of value, calls for a significant re-‐appraisal of our current design and development approaches. Relevant topics for this minitrack include (but are not limited to): • ICT enabled services, mobile services, and consumer information systems
o Discovery, fuzzy-‐front end, and innovation processes o Design, and development processes and methodologies o Analytics supported innovation, design, development, and management o Socio-‐psychological aspects of ICT enabled service use
o Temporo-‐spatial relevance, e.g., wearable device, such as iWatch or Google Glasses, enabled services
• Consumer and enterprise user aspects o Service ecosystems o Social networking o Location and/or sensor aware services o Hedonic ICT enabled services o Understanding social and cultural contexts o Consumerization of enterprise services
• Cyber-‐Physical systems and services o Cyber-‐Physical systems and services from different disciplinary perspectives, such as,
information systems, operations research, software engineering, service science, and service research
o Service innovation based on cyber-‐physical systems and services o Service ecosystems, platforms and novel architecture related cyber-‐physical systems
and services o Theoretical aspects of cyber-‐physical systems and services research o Cyber-‐physical systems and services as artifacts o Use and adoption of cyber-‐physical systems and services
References [1] T. Tuunanen, M. Myers, and H. Cassab, "A Conceptual Framework for Consumer Information Systems Development," Pacific Asia Journal of the Association for Information Systems, vol. 2, pp. 47-‐66, 2010. [2] S. L. Vargo and R. F. Lusch, "Evolving to a New Dominant Logic for Marketing," Journal of Marketing, vol. 68, pp. 1-‐17, 2004. [3] V. K. Tuunainen and T. Tuunanen, "IISIn-‐A model for analyzing ICT Intensive Service Innovations in n-‐sided Markets," 2011, pp. 1-‐10. [4] K. N. Lemon and M. H. Huang, "IT-‐Related Service: A Multidisciplinary Perspective," Journal of Service Research, vol. 14, p. 251, August 2011. [5] I. R. Bardhan, H. Demirkan, P. Kannan, and R. J. Kauffman, "Special Issue: Information Systems in Services," Journal of Management Information Systems, vol. 26, pp. 5-‐12, 2010. [6] T. Tuunanen, J. Bragge, J. Häivälä, W. Hui, and V. H. Virtanen, "A Method for Recruitment of Lead users from Virtual Communities to Innovate IT Enabled Services for Consumers in Global Markets," Pacific Asia Journal of the Association for Information Systems, vol. 3, p. 3, 2011.
Minitrack Co-‐Chairs: Tuure Tuunanen (Primary Contact) University of Jyväskylä Department of Computer Science and Information Systems P.O. Box 35 FIN-‐40014 Tel: +358 40 036260 Email: [email protected] Tilo Böhmann University of Hamburg Department of Informatics Vogt-‐Kölln-‐Str. 30 D-‐22527 Hamburg Germany Tel: +49 40 428 83-‐2299 Email:tilo.boehmann@uni-‐hamburg.de
Ola Henfridsson University of Warrick Business School Coventry CV4 7AL, United Kingdom Email: [email protected]
Digital Service Innovations based on "Open" Phenomena and Practices
Value produced by digital service innovation is disrupting established markets as well as generating entirely new ones. The innovations come from many different sources: traditional R&D, cross-‐industry initiatives, new entrants that displace incumbents in traditional industries and more and more from open development processes or crowdsourcing of new ideas from consumers as existing or potential customers. This minitrack focuses on those open phenomena and practices. Examples new kind of development openness include, for example: the opening of the vast data resources collected by authorities and different governmental units, the increasing availability of new open sensor data (for example, from mobile devices), and innovation contests. We seek novel research describing innovative services or service systems that are created. The submissions can be research papers, case studies, or practitioner reports related new service development and their implications. Relevant topics for this minitrack include (but are not limited to):
• Novel approaches to crowdsourcing new digital service ideas • Novel approaches to development of new digital services • Business value of digital service innovations • Business model destruction/creation caused by digital service innovations • Open data service ecosystems • Applications and models utilizing ‘quantified self’ data • Mydata/Midata and similar personal data management approaches • Location and sensor data based digital services • Open data infrastructures • Privacy issues related to open data and open data services
Minitrack Co-‐Chairs:
Juho Lindman (Primary Contact) Hansen School of Economics Email: [email protected] Virpi Tuunainen Aalto University School of Business Email: [email protected]
Matti Rossi Aalto University School of Business Email: [email protected]
Gamification: Motivations, Effects, and Analytics Cutting edge research on gamification, the increased convergence of games and everyday life. A wide array of contributions relating to the employment of the power of psychological and behavioral mechanisms classically attributed to homo ludens in and into systems meant for homo oeconomicus are welcomed. Studies incorporating related mechanisms such as status reports, top lists, level advancement, acknowledgements of user status, points and other instant rewards and virtual assets are welcomed and the wide variety of research outcomes can include business benefits, hedonic pleasure, conversion and click-‐through, satisfaction, enjoyment, fun or flow. Relevant topics for this minitrack include (but not limited to):
• Impact of games and gamification: o User behavior o User psychological states o Organizational impacts o Societal impacts
• Recent developments in game and gamification applications: o Emerging mobile and web applications o Gamification-‐related development features in enterprise systems and decision
support systems • Game/gamification design:
o Classical gamification mechanisms o Emerging ideas, features and mechanisms for gamification o Fun and games based system design philosophies o Theoretical contributions of motivating system use and technology adoption
• Player and user motivations: o Why do people play/adopt/use different games o What needs games satisfy
• Outcomes of gamification: o Business benefits, hedonic pleasure, conversion and click-‐through, satisfaction,
enjoyment, fun and flow.
Minitrack Co-‐Chairs: Juho Hamari (Primary Contact) University of Tampere Tel: +358 50 318 6861 Email: [email protected] Petri Parvinen Aalto University School of Science, Finland Tel: +358 50 312 0905 Email: [email protected]
Humanitarian Operations Research -‐ Decision Analytics for Crisis and Disaster Management
The aim of this minitrack is to provide a forum for discussion on methodologies, solutions, and issues related to decision analytics in humanitarian operations research. We invite submissions on the general area of providing analytical capabilities for decision support. General topics include, but are not limited to:
• Prediction and forecasting • Data analytics • Optimization under uncertainty and multi-‐objective optimization (w.r.t. the general topic) • Simulation approaches • Routing in wireless local networks • Humanitarian supply chains • Evacuation models • Vehicle routing • Facility location • Early warning systems • Decision support systems • Mobile solutions and services • Communications systems
Minitrack Co-‐Chairs: Erik Kropat (Primary Contact) University of the Bundeswehr Munich Email: [email protected]
Silja Meyer-‐Nieberg University of the Bundeswehr Munich Email: silja.meyer-‐[email protected]
Intelligent Decision Support for Logistics and Supply Chain Management This minitrack aims at organizing a minitrack consisting of two sessions depending on the number of high quality submissions. We seek papers dealing with decision technologies which contribute to intelligent decision support in the whole field of logistics and in particular in all categories of SCM. This includes but is not restricted to simulation, optimization, heuristics, metaheuristics, agent technologies, decision analytics, descriptive models, and data mining. We are especially interested in real-‐world applications and in software solutions which assist in solving decision problems. This is extended towards, e.g., computational logistics, advanced planning systems and the intelligent use of ERP systems. Also conceptual ideas, reports on projects in progress, and case studies are welcome. Moreover, teaching cases both at the university as well as the executive level may be of interest. Minitrack Co-‐Chairs: Stefan Voß (Primary Contact) University of Hamburg, Germany Tel: +49-‐40-‐42838-‐3062 Email: stefan.voss@uni-‐hamburg.de Hans-‐Jürgen Sebastian RWTH Aachen University, Germany Tel: +49-‐24-‐1809-‐6185 Email: [email protected]‐aachen.de Email: [email protected]
Interactive Visual Decision Analytics Interactive Visual Decision Analytics supports human decision making through interaction with data and statistical and machine learning processes. IVDA applies in broad range of situations where human expertise must be brought to bear on problems characterized by massive datasets and data that are uncertain in fact, relevance, location in space and position in time. Current applications include environmental science and technologies, natural resources and energy, health and related life sciences, precision medicine, safety and security and business processes. We also encourage submissions that extend the areas of use to new analytic tasks in science and technology, public health, business intelligence, financial analysis, and other domains. Submissions may include studies of visual analytics and decision support in the context of an organization (e.g., communication between analysts and policy-‐makers), perceptual and cognitive aspects of the analytic task, Interactive Machine Learning, and collaborative analysis using visual information systems. This proposal builds upon our successful HICSS-‐47 and HICSS 48 minitracks on visual analytics for decision support and our earlier minitracks on visual analytics, mobile computing, and digital media at scale. It seeks to define analytical methods and technologies that use interactive visualization to meet challenges posed by data, platforms, and applications for decision making and risk-‐based decision making:
• Visualization and Analysis of datasets of varying size and complexity from archives and real-‐time streams
• Collaborative visual analysis and operational coordination within and across organizations. • Interactive and Visual Risk-‐based decision making • Interactive Machine Learning methods • Cross-‐platform interoperability, from mobiles to data walls • Managing response time of complex analytical tasks • Effective deployment and case studies of success from deployed visualization and analytics
experiences • Visualization and analytics for data-‐driven policy making and decision support • Issues and Challenges of evaluation of visual decision making • Cognitive and social science aspects of visual decision making environments
For HICSS 2016, we encourage authors to address these themes from their own research perspectives. Authors are encouraged to bring the lens of their own background and expertise to focus on the analytics of the data itself and coordination of multiple levels of analysis, decision-‐making and operations to the design and evaluation of effective presentations for stakeholders. Both algorithmic ‘data sciences’ approaches and human-‐centered "visualization" and ‘visual analytics’ human-‐computer interface methods hold great promise for operationalizing massive datasets and streaming data in support of a broad range of human activities. Applications in basic scientific research, business analytics, health sciences, environmental science and engineering R&D explore the implications of these methods for advancement of knowledge and strategic planning. Applications in coordination, command and control of complex human activities such as crowd and
traffic management, disaster relief, law enforcement, and national and cyber security add the constraints of real-‐time performance and distribution of planning to the challenges faced. For this minitrack we invite computational, cognitive, and organizational perspectives on advanced data processing and interactive visualization across a range of human endeavors. We also invite participation from researchers who are looking at scaling issues and multiscale issues, whether these scales refer to the time of decision making, the form-‐factor and operational constraints of mobile devices, the number of decision makers or the more traditional notion of multiscale simulation and real world scales of data. We are particularly interested in approaches that combine computational and interactive analytics in ‘mixed initiative’ or Interactive Machine Learning systems, decision support in the context of an organization (e.g. communication between analysts and policy-‐makers), perceptual and cognitive aspects of the analytic task, and collaborative analysis using visual information systems. Minitrack Co-‐Chairs: David S. Ebert (Primary Contact) School of Electrical and Computer Engineering Purdue University Tel: (765) 494-‐9064 Email: [email protected] Brian Fisher School of Interactive Arts Simon Fraser University Tel: (778) 782-‐7474 Email: [email protected] Kelly Gaither Texas Advanced Computing Center University of Texas Tel: (512) 471-‐8957 Email: [email protected]
Mobile Value Services This minitrack covers different aspects of design, realization and implementation, use and effect of mobile value services within a business environment. We focus on business aspects, such as business models, business impacts of mobile information systems, use of mobile apps and platforms in a business environment as well as their effects on the one hand as well as more technology and design oriented aspects on the other hand. Mobile application development that is either native or is following a cross-‐platform approach is an important topic. As HICSS is addressing leading edge developments, we especially encourage submissions on is-‐sues as: adaptability and adaptivity of mobile services and platforms, on mobile cloud services, and on the role and relevance of reliability, privacy and security. For the business oriented part of the mini-‐track submissions on business models, platforms in relation with (open and closed) micro eco-‐systems within a business environment are invited. We welcome studies on use and effect of mobile applications and platforms in business environments. We seek mobile business research papers, case studies, and practitioner reports related to business aspects. Of special interest are conceptual and empirical papers analyzing business and business model aspects, including mobile services and application development and design that go beyond existing technologies and for instance look into cloud or sensor technologies. Such applications will contribute to the advancement of user-‐inspired and employee centric information systems design within this paradigm. We welcome studies with either qualitative or quantitative research methods as well as design research. Minitrack Co-‐Chairs: Pirkko Walden (Primary Contact) Åbo Akademi University Tel: +358-‐40-‐5409141 Email: [email protected] Tomi Dahlberg Åbo Akademi University Tel: +358 50 550 5718 Email: [email protected] Esko Penttinen Aalto University School of Business Tel: +358-‐40-‐5754520 Email: [email protected]
Multi-‐criteria Decision Analysis and Support Systems
Most decisions involve multiple objectives. A decision alternative is chosen based on a multitude of often-‐conflicting decision criteria, and a solution is sought that provides the best compromise with respect to these various desired objectives. Multi-‐criteria decision-‐making (MCDM), over the last forty years, has become an established field of research, with extensive theory, a wide choice of solution methods, and a number of available computer-‐based decision support packages. Many general software tools, such as linear programming packages and electronic spreadsheets that do not implement specific MCDM techniques, can also be used to analyze multi-‐criteria problems. Multi-‐criteria decision support (MCDSS) may focus on various stages of the decision making process, from problem exploration and structuring, to discovering the decision-‐maker’s preferences and the most preferred compromise solution. Possible topics for this minitrack may include:
• Success factors for MCDSS • The role of the decision-‐maker in effective multi-‐criteria decision support • Case studies of multi-‐criteria decision support • Design of technology for specific aspects or phases of multi-‐criteria decision support • Decision support for project selection • Decision support for specific applications domains (e.g. health care) • Classifications of decision problems and solution technology • Tools and techniques for multi-‐criteria portfolio selection • Solution approaches to special types of decision problems involving conflicting objectives • Quality and types of data in multi-‐criteria decision support
Minitrack Co-‐Chairs: Rakesh Sarin (Primary Contact) University of California Los Angeles Email: [email protected] Heinz-‐Roland Weistroffer Virginia Commonwealth University Email: [email protected]
Service Analytics Research topics addressed in this minitrack include the applicability of basic and advanced analytics to different service systems, the state-‐of-‐the-‐art of service analytics methodologies and tool-‐support, and the investigation of benefits resulting from the application of service analytics. This minitrack will serve as a forum for researchers and practitioners to share progress in the study of these and related themes. Submissions on, but not limited to, the following topics are encouraged:
• Web Usage Mining and Web Personalization • Data Mining • Machine Learning applied to Services • Recommender Systems for Services • Social Network Analytics applied to Services • Privacy Issues resulting from Service Analytics • Fraud Analytics for Service Systems • Analysis and Prediction of User Behavior in Mobile Phone Systems • Analysis and Prediction of Driver Behavior in Traffic Situations • Analysis and Exploitation of Floating Car Data • Electricity Consumption Analysis using Smart Meter Data • Analytics for Healthcare Services • Analysis and Prediction of IT Service Demand Patterns • Analysis of Service Problem Reports • Industrial Service Analytics and Optimization • Sports Analytics
Minitrack Co-‐Chairs: Hansjoerg Fromm (Primary Contact) Karlsruhe Institute of Technology (KIT) Tel: +49-‐171-‐5538591 Email: [email protected] Thomas Setzer Karlsruhe Institute of Technology (KIT) Tel:+49-‐721-‐9654866 Email: [email protected]
Gerhard Satzger IBM Germany Tel: +49-‐171-‐5504748 Email: [email protected]
Service Science Service science deals with the design, development, and managerial issues concerning ‘service systems,’ integrated, value-‐creating configurations of service providers, their clients, their partners, and others. The best-‐performing service systems are IT-‐enabled, customer-‐centered, relationship-‐focused, and knowledge-‐intensive -‐ yet span multiple formal and informal organizations. Because of this multidisciplinary context, researchers and practitioners in management, social sciences, and computer sciences are all working to increase service innovation. These multiple perspectives can be unified using the theoretical construct of the service system, in which entities (people, businesses, government agencies, etc.) interact to co-‐create value via value propositions that describe dynamic re-‐configurations of resources. The framework of value creation in complex service systems, which requires elaborating various stakeholder perspectives and understanding the broad context of use for specific cases to enable effective value creation especially given advanced and autonomous technology, has emerged as the central unifying framework across many papers and presentations. The Service Science minitrack will focus on papers that connect rigorous disciplinary research with the emerging interdisciplinary framework of value creation in service systems, focusing particularly on service design, innovation, and technology. Minitrack Co-‐Chairs: Paul Maglio (Primary Contact) University of California, Merced Tel: (831) 588-‐7354 Email: [email protected] Michael Shaw University of Illinois, Urbana-‐Champaign Email: [email protected]
Fu-‐ren Lin National Tsing Hua University, Taiwan Email: [email protected]
Smart Service Systems: Analytics, Cognition and Innovation Smart service systems can be characterized by: (1) the types of offerings to their customers and/or citizens, (2) the types of jobs or roles for people within them, and (3) the types of returns they offer investors interested in growth and development, through improved use of technology, talent, or organizational and governance forms, which create (dis)incentives that (re)shape behaviors. An important trend in smart service systems is the increasing availability of cognitive assistants (e.g., Siri, Watson, Jibo, Echo, etc.) to boost productivity and creativity of all the people inside them. There is a need to apply robust research findings in the appropriate management and organizational contexts related to innovation of smart service systems, service innovation, quality, architecture, design and delivery, and the resulting customer satisfaction and business value. In part, because of analytics and cognitive systems, smart service systems adapt to a constantly changing environment to benefit customers and providers. Using big data analytics, service providers try to compete for customers by (1) improving existing offerings to customers, (2) innovating new types of offerings, (3) evolving their portfolio of offerings and making better recommendations to customers, (4) changing their relationships to suppliers and others in the ecosystem in ways their customers perceive as more sustainable, fair, or responsible. The goal of this minitrack is to explore the challenges, issues and opportunities related to innovation of smart service systems that enable value co-‐creation with analytics, cognitive and human systems. We are interested in novel theories, approaches and applications for innovation of smart service systems. Possible topics of applied, field and empirical research include, but are not limited to:
• Theories, approaches and applications for innovation of smart service systems • Value co-‐creation processes, metrics and analytics for smart innovation processes • Methods scale the benefits of new knowledge globally, rapidly, and profitably • Service-‐oriented agile IT realization platform for smart service co-‐creation • Place of cognitive systems, computing, system engineering, cloud for smart service systems • Innovation ecosystems with internet and internet-‐of-‐things • Theories and approaches for integrating analytical and intuitive thinking processes • Open innovation and social responsibility • Planning, building and managing design and innovation infrastructures and platforms • Technology and organizational platforms support rapid scaling processes (smart phones,
franchises, etc.) • Smart service systems include the customer, provider, and other entities as sources of
capabilities, resources, demand, constraints, rights, responsibilities in value co-‐creation processes, and includes current applications of human and cognitive systems
• Analytics models, tools and engine for analytics support • Agile business development platform for operational enablement: business processes, rules,
real-‐time event management • The commoditization of business processes (e.g. out-‐tasking, ITIL, SCORE), software (e.g. the
software-‐as-‐service model, software oriented architecture, application service providers) and hardware (e.g., on-‐demand, utility computing, cloud computing, software oriented infrastructure with virtualized resources, infrastructure service providers for innovations
• Self-‐service and smart technologies & management for sustainable innovations
• Services implications to value chains, networks, constellations and shops • Collaborative innovation management in B2B and B2C e-‐commerce
Minitrack Co-‐Chairs: Haluk Demirkan (Primary Contact) University of Washington -‐ Tacoma Tel: (253) 692-‐5751 Email: [email protected] Ralph Badinelli Virginia Tech Tel: (540) 231-‐7688 Email: [email protected]
Jim Spohrer IBM Almaden Research Center Tel: (408) 927-‐1928 Email: [email protected]
Soft Computing Soft Computing refers to a collection of computational techniques (Neural Networks, Evolutionary Computing, Fuzzy Systems, Bayesian networks, etc.) which study, model, and analyze very complex phenomena: Those for which more conventional methods have not yielded low cost, analytic, and complete solutions. The purpose of this Mini-‐Track is to study Soft Computing methods in connection with building intelligent decision support systems (DSS) and information retrieval systems (IRS). They should support managers and knowledge workers in problem solving, planning and decision-‐making. Interpretability, due to its human-‐centric character, plays a key role in DSS and IRS modeling where there is a huge interaction with humans. Intelligent systems endowed with interpretability capabilities are likely to be trusted on by end-‐users, increasing the success rate of introducing intelligent systems into the market. This Minitrack provides a forum to discuss and disseminate recent and significant advances in Soft Computing regarding theory and technology transfer. It will provide a forum to discuss and disseminate recent and significant research efforts on the Soft Computing research along with the presentation of some challenging applications. The focus of the Mini-‐Track is to facilitate cross-‐fertilization between methodological and applied research. The topics of interest include but are not limited to:
• New Methods: o Fuzzy logic o Artificial neural networks, self-‐organizing maps o Probabilistic reasoning o Swarm intelligence, ant algorithms o Evolutionary computing o Optimization o Linguistic summarization o Computing with perceptions o Knowledge extraction, representation, modeling o Decomposable models o Interpretability issues
• Applications: o Information mining o Mining and representing temporal and spatial data o Mining and representing text and semi-‐structured data o Graph mining o Intelligent data analysis o Information retrieval techniques o Information retrieval models and applications o Information filtering models and systems o Information visualization and exploration o Interactive retrieval, user models and studies o Metadata extraction and generation
o Multimedia content-‐based information retrieval o Web and distributed information retrieval o Information extraction and integration o Information clustering and classification o Personalization and personal information management o Semantic Integration o Question answering o Decision support and innovations o Social networks o Sensory analysis o Robotics
Minitrack Co-‐Chairs: Rudolf Kruse (Primary Contact) Otto von Guericke University Magdeburg Tel: +49-‐39-‐1675-‐8706 Email: [email protected] Gabriella Pasi University of Milan Bicocca Tel: +39-‐02-‐6448-‐7847 Email: [email protected] José M. Alonso European Centre for Soft Computing Tel: +34-‐98-‐545-‐6545 Email: [email protected]
Streaming Data Analytics and Applications Both academia and organizations show great interest in streaming big data analytics -‐ the process of extracting knowledge structures from continuous, high volume and high velocity continuous flow of data in a myriad of formats from a variety of real-‐time data sources. The challenge for organizations lies in being able to transform this deluge of data into instantaneous intelligence that can enable faster, better business decisions. For academia, mining streaming data is still not a mature discipline which faces some unique theoretical and practical challenges. This minitrack aims to present and share new research in defining and highlighting the values of stream data analytics, including new theory, algorithms, innovation in methodologies, and benefits from variety applications. Topics include, but are not constrained only to:
• Data stream mining techniques and methodologies • Adaptive data mining • Distributed data stream models • Graph-‐based stream models • Concept drift in streaming data • Visualization for big data streams • Deep learning on stream data • Real-‐world applications using streaming data analytics in: • Health care • Banking • Industry • Social networks • Intelligence and cybersecurity • Smart power grid • Sensor networks • Internet of Things • Situation awareness
Minitrack Co-‐Chairs: Mehmed Kantardzic (Primary Contact) Computer Engineering and Computer Science Department J.B. Speed School of Engineering University of Louisville Tel: (502) 852-‐3703 Email: [email protected]
Jozef Zurada Computer Information Systems Department College of Business University of Louisville Tel: (502) 852-‐4681 Email: [email protected]
Systemic Financial Risk Analytics In the aftermath of the global financial crisis of 2007/2008, there is an acute interest in analytics for early identification and assessment of risks and vulnerabilities that eventually may lead to a systemic financial crisis. This minitrack brings together the most recent advances on computational tools for systemic financial risk identification and assessment, including early-‐warning indicators and models, stress-‐testing models, and contagion or spillover models. The key aim of the minitrack is to adopt methods and techniques from other disciplines, such as computer science, biology and physics, that make use of computer-‐intensive approaches, novel data sources, visual representations or interactive interfaces, among others. The minitrack also covers a range of other related topics, such as methods for the analysis of coinciding systemic financial stress and systemically important financial institutions. Hence, it solicits contributions on a wide range of topics on analytics related to systemic financial risk and financial stability. Minitrack Co-‐Chairs:
Peter Sarlin (Primary Contact) Hanken School of Economics Tel: +358-‐40-‐572-‐7670 Email: [email protected]
Tuomas Peltonen European Central Bank Email: [email protected]
Wearables and Quantified Self Information systems are getting closer to our bodies, and the boundary between the user and the machine is blurring. Wearable intelligence is the next chapter of the mobile revolution in emerging technologies. Wearables are not just a consumer phenomenon; they have the potential to change the way organizations conduct business. For example, data collected by wearable medical devices has the potential to disrupt many industries including healthcare and insurance. There is need for research to investigate this phenomenon. This minitrack will focus on the role of wearable technologies and the data collected through wearables. Areas of wearable computing research include user interface design, augmented reality, pattern recognition, and wireless and personal area network technologies. We encourage authors to submit conceptual, design and empirical work relevant to wearables and quantified self areas. We solicit papers in various topics, including, but not limited to the following:
• Theories regarding wearable intelligence and quantified self • Challenges in managing wearables and the data collected through them • New methods to analyze wearable intelligence • Analytical models for the wearables industry • Process-‐redesign for the wearable technologies • Case studies on wearables and quantified self • Quantified self and big-‐data analyses, analytical models, and simulations • System design, and application areas • Impact on user interface design, augmented reality, and wireless networks • Integrating wearables into larger systems (such as augmented reality systems, training
systems, and platforms for collaborative work) • Behavioral models • Management of wearable devices • Cultural and social implications of adopting wearable computing devices • Privacy, personal safety, and quality of life issues
Minitrack Co-‐Chairs: Tayfun Keskin (Primary Contact) University of Washington Bothell Tel: (425) 352-‐3381 Email: [email protected] Deanna Kennedy University of Washington Bothell Tel: (425) 352-‐5321 Email: [email protected]
Hugo Paredes University of Trás-‐os-‐Montes e Alto Douro (UTAD) Tel: (351) 259 350 332 Email: [email protected]
![Welcome! [shidler.hawaii.edu]shidler.hawaii.edu/sites/shidler.hawaii.edu/files/2019/...Make sure to bring photocopies of your passport, VISA, NTU acceptance and admission letters and](https://img.pdfslide.us/doc/110x75/5fb7c091b341447ca751d21b/welcome-make-sure-to-bring-photocopies-of-your-passport-visa-ntu-acceptance.jpg)
