Decision Analytics, Mobile Services, and Service Science

Transcription

1 Decisin Analytics, Mbile Services, and Service Science The DA/MS/SS Track fcuses n emerging managerial and rganizatinal decisin- making strategies, prcesses, tls, technlgies, services and slutins in the Digital Age. This track has fur interrelated themes. Analytics fcuses n decisin making prcesses, mdels, tls and technlgies. Mbile Services wrk with the develpment and delivery f data, infrmatin and services with mbile technlgy platfrms. Challenges and issues f emerging service industries, and service rientatin and - transfrmatin f strategies, prcesses, rganizatins, systems and technlgies are cvered in Service Science. In this track, we als discuss innvative appraches f decisin making fr/with Critical and Emerging Slutins in a number f high- impact areas. Minitracks: Addressing Grand Challenges with Systems Sciences Analytics, Infrmatin Systems and Decisin Technlgies fr Sustainability Big Data and Analytics: Cncepts, Methds, Techniques and Applicatins Business Value f the Internet f Things Data, Text and Web Mining fr Business Analytics Decisin Supprt fr Smart City and E- Sciety Services Digital and ICT Enabled Services Digital Service Innvatins based n "Open" Phenmena and Practices Gamificatin: Mtivatins, Effects, and Analytics Humanitarian Operatins Research - Decisin Analytics fr Crisis and Disaster Management Intelligent Decisin Supprt fr Lgistics and Supply Chain Management Interactive Visual Decisin Analytics Mbile Value Services Multi- criteria Decisin Analysis and Supprt Systems Service Analytics Service Science Smart Service Systems: Analytics, Cgnitin and Innvatin Sft Cmputing Streaming Data Analytics and Applicatins Systemic Financial Risk Analytics Wearables and Quantified Self

2 Track Chairs: Christer Carlssn Institute fr Advanced Management Systems Research ICT Huse A4053 Ab Akademi University Turku, Finland Tel: Fax: Haluk Demirkan Milgard Schl f Business University f Washingtn Tacma 1900 Cmmerce Street Bx Tacma, WA Tel: (253) Fax: (253) haluk@uw.edu

3 Addressing Grand Challenges with Systems Sciences This minitrack prvides a frum fr the discussin f the wrld s mst imprtant r challenging prblems, and the rle that system science can play in reslving thse prblems. In cntrast t papers which fcus n a narrw prblem dmain, this minitrack seeks submissins which address big, imprtant issues, the reslutin f which wuld be widely beneficial t mankind. Papers that prpse innvative, ambitius, r unusual system science- based slutins t humanity s greatest prblems are particularly encuraged. Papers which leverage the system sciences t address any f the wrld s mst imprtant r challenging prblems are welcme. Prblem dmains f interest include, but are nt limited t: Bidiversity Climate change and ther envirnmental issues Ecnmic stability and prsperity Educatin Energy Geplitical stability Glbal develpment Health, disease, and ther medical issues Human rights Hunger, pverty, and clean drinking water Natural disasters Sustainability Wmen's rights Minitrack Chair: Daniel Sper Califrnia State University, Fullertn Tel: (657) dsper@fullertn.edu

4 Analytics, Infrmatin Systems and Decisin Technlgies fr Sustainability The minitrack welcmes research articles and practitiner reprts explring technical and rganizatinal issues pertaining t innvative ways fr leveraging infrmatin systems and technlgies fr addressing sustainability issues, and research t mitigate the impact f ecnmic develpment and infrmatin technlgies n the envirnment. The minitrack encmpasses envirnmental infrmatics and analytics, sustainable cmputing, and Green IT. Theretically funded papers that illustrate the applicatin f advanced cmmunicatin and decisin technlgies in are particularly welcmed. Pssible tpics include, but are nt limited t: Analytics and decisin technlgies Cllective awareness platfrms Envirnmental sustainability and decisin making Envirnmental knwledge acquisitin and management Envirnmental Management Infrmatin Systems (EMIS), Envirnmental Decisin Supprt Systems (EDSS), and Green Infrmatin Systems (IS) Green IT Envirnmental cyberinfrastructure Envirnmental cmmunicatin Energy Infrmatics Technlgies fr decisin supprt systems develpment and envirnmental applicatins (e.g., GIS, cmputatinal intelligence, service- riented cmputing, web services, semantic web, artificial intelligence, agent- based cmputing, and multiple criteria decisin making) Omar El- Gayar (Primary Cntact) Cllege f Business and Infrmatin Systems Dakta State University Tel: (605) Omar.El- Gayar@dsu.edu Arn Scharl Department f New Media Technlgy MODUL University Vienna scharl@ecresearch.net PingSun Leung Department f Natural Resurces and Envirnmental Management University f Hawaii at Mana psleung@hawaii.edu

5 Big Data and Analytics: Cncepts, Methds, Techniques and Applicatins This minitrack slicits paper submissins that: advance ur knwledge f Big Data strage and structure; help us learn abut effective prcesses and appraches t effectively manage Big Data and the assciated business analytics; begin t identify ways t measure the rganizatinal benefits derived frm using and analyzing Big Data; present case studies f Big Data implementatin and use; and address the rganizatinal and business aspects f big data and analytics. Papers will be slicited in several areas, including, but nt limited t the fllwing: Challenges in managing big data repsitries and prjects Graph analytics - bth syntactic and semantic - that play a big rle in the explitatin f scial media data Advanced analytics, - emphasizing visual analytics and nn- numeric analysis mdels and their implementatin as applied t cmplex prblems in different dmains Scalable semantic anntatin and reasning acrss big data stres Metrics fr assessing the impact f big data in business, scientific, and gvernmental decisin- making Organizatinal and business aspects f big data, analytics and data science Crwdsurcing as a distributed, cmplex analytic tl. Stephen Kaisler (Primary Cntact) SHK & Assciates 8822 Cardinal Frest Circle Laurel, MD Tel: (301) skaisler1@cmcast.net Frank Armur Kgd Schl f Business American University 4400 Massachusetts Avenue, NW Washingtn, DC Tel: (202) fjarmur@gmail.cm Albert Espinsa Kgd Schl f Business American University 4400 Massachusetts Avenue, NW Washingtn, DC Tel: (202) albert@american.edu

6 Business Value f the Internet f Things This minitrack addresses managerial and rganizatinal issues rganizatins face as they seek t create and realize business value frm incrprating the emerging Internet f Things int their rganizatinal infrastructure, their electrnic business partner relatinships, and the prducts and services they ffer t custmers. We encurage authrs t share new and interesting theretical and methdlgical perspectives n tpics relevant t bth academic researchers and practitiners. We welcme wrk- in- prgress that examines existing and extended thery using the IT cmbined with wireless sensr netwrks, RFID, and big data analytics as the technlgies f fcus and case studies f rganizatins implementing the IT inside and utside their span f cntrl. We give special cnsideratin t research submissins when the authr(s) cmmit t include an industry partner in their presentatin. We welcme research that reflects a range f current research methds including case studies, analytical mdels, ecnmetrics, and framewrks. Fred Riggins (Primary Cntact) Nrth Dakta State University Tel: (651) fred.riggins@ndsu.edu Samuel Fss Wamba NEOMA Business Schl, France samuel.fss.wamba@nema- bs.fr Matthias Dehmer Bundeswehr University Munich, Germany Matthias.dehmer@unibw.de

7 Data, Text and Web Mining fr Business Analytics Data mining is the prcess f discvering valid, nvel, ptentially useful, and ultimately understandable patterns (i.e., nuggets f knwledge) in data stred in structured databases, where the data is rganized in recrds ppulated by categrical, rdinal and cntinuus variables. Text mining, n the ther hand, refers t the very same discvery prcess as it applies t unstructured data surces including business dcuments, custmer cmments, Web pages, and XML files. This minitrack fcuses n decisin supprt aspects f advanced analytics, with emphasis n data, text and Web mining. Tpic areas cvered in this minitrack include, but are nt limited t: New methds and algrithms f data/text/web mining The prcess and new methdlgies f cnducting data/text/web mining Ethical and privacy issues in data/text/web mining Nvel, interesting applicatins f data/text/web mining fr better decisin making Data pre- prcessing related aspect f data/text/web mining, such as data characterizatin, data cleaning, data integratin, data sampling, data reductin, data visualizatin. Dursun Delen Oklahma State University Tel: (918) dursun.delen@kstate.edu

8 Decisin Supprt fr Smart City and E- Sciety Services Develping smart city and enhancing e- sciety services are the critical imprtant t urbanizatin prcess fr imprving the effectiveness and efficiency f traditinal cities. With the massive applicatins f Internet f things (IT), mbile netwrks, and scial netwrks, unprecedentedly large amunt f varius hetergeneus data can be gathered and prcessed in terms f advanced analytics t supprt smart applicatins and e- sciety services. Furthermre, decisin supprt tls and sft cmputing mdels can be emplyed t speed up the whle prcess. This minitrack addresses issues that fcus n the applicatins f varius decisin supprt tls, such as big data analytics, decisin analysis, and sft cmputing, t develp smart city applicatins and e- sciety services. We als encurage papers t reprt n system level research and case studies related t smart city and e- sciety. Tpics f interest include, but are nt limited t: Advanced analytics fr smart city planning and e- sciety services Case study and best practices fr smart cities and e- sciety services Decisin supprt mdels and tls fr smart city and e- sciety services Design and implementatin f intelligent systems fr smart city applicatins Innvative applicatins in smart cities, such as smart finance, smart health, smart research, and smart travel Nvel applicatins in e- sciety services, such as infrmatin recmmendatin, scial media analytics, and crwdsurcing applicatins Sft cmputing fr smart city and e- sciety services Wei Xu (Primary Cntact) Schl f Infrmatin Renmin University f China Tel: weixu@ruc.edu.cn Jian Ma Department f Infrmatin Systems City University f Hng Kng Tel:

9 Digital and ICT Enabled Services The purpse f the minitrack is t draw researchers attentin t the innvatin, design, develpment, management, and use f Digital and ICT Enabled Services fr bth Cnsumers and Enterprises. It will prvide a discussin frum fr researchers interested in fstering analytics- based and service- based appraches t theretical and practical prblems related t such services [1-6]. In a brad sense, ICT enabled services can be defined as [1] :..systems that enable value c- creatin thrugh the develpment and implementatin f infrmatin and cmmunicatin technlgy enabled prcesses that integrate system value prpsitins with custmer value drivers. These services meld the wrlds f bits and atms and prmise t transfrm the transprtatin, energy, and ther sectrs like the media industries befre them. Examples f such ICT enabled services are, e.g., NFC enabled Air New Zealand frequent flyer cards that facilitate check- in and identity verificatin, mbile ticketing services fr public transprt, digital services fr music festival participants t interact and c- create with each ther befre, during, after the event, smart televisin services and cntent, tablet- based services fr rdering fd and drinks at a casin r restaurant, etc. Likewise, there are substantial pprtunities fr ICT- driven service innvatin in business- t- business settings. These pprtunities exist particularly in manufacturing in which innvatin activities increase the digitizatin f prducts and prductin prcesses. We see that the glbal awareness f the pwer f the manufacturing industry will be linked t hrizntal cyber- physical systems that enable value c- creatin in the netwrked business envirnment. The cyber- aspects f such systems are ICT infrastructure, cmputer hardware, sftware, and different kind f sensrs and actrs. These cmpnents turn cyber- physical systems int platfrms fr designing and perating service. The data n prducts and prcesses gained thrugh netwrked CPS and the ability t act n this data thrugh cntrl systems and actrs enables nvel ways f c- creating service in industrial cntexts. This emerging area f research raises interesting questins. Fr example, traditinal develpment appraches fcus n imprving the efficiency and effectiveness f rganizatinal prcesses. The design f ICT enabled services may, hwever, require an emphasis n the sci- psychlgical aspects, such as the value- in- use and user/cnsumer/c- creatr experiences. Similarly, we cnsider that the design and develpment f digital services is an imprtant tpic and we see that there are different cntinuums f ICT enables services. One f these cntinuums is the level f digitalizatin. Anther is likely t be related t cyber- physical aspects f services and hw the service is linked t the physical wrld thrugh sensrs and/r peple s interactins. Discussin Tpics: The shift f cnsumer and enterprise persnnel frm users t c- creatrs f value, calls fr a significant re- appraisal f ur current design and develpment appraches. Relevant tpics fr this minitrack include (but are nt limited t): ICT enabled services, mbile services, and cnsumer infrmatin systems Discvery, fuzzy- frnt end, and innvatin prcesses Design, and develpment prcesses and methdlgies Analytics supprted innvatin, design, develpment, and management Sci- psychlgical aspects f ICT enabled service use

10 Tempr- spatial relevance, e.g., wearable device, such as iwatch r Ggle Glasses, enabled services Cnsumer and enterprise user aspects Service ecsystems Scial netwrking Lcatin and/r sensr aware services Hednic ICT enabled services Understanding scial and cultural cntexts Cnsumerizatin f enterprise services Cyber- Physical systems and services Cyber- Physical systems and services frm different disciplinary perspectives, such as, infrmatin systems, peratins research, sftware engineering, service science, and service research Service innvatin based n cyber- physical systems and services Service ecsystems, platfrms and nvel architecture related cyber- physical systems and services Theretical aspects f cyber- physical systems and services research Cyber- physical systems and services as artifacts Use and adptin f cyber- physical systems and services References [1] T. Tuunanen, M. Myers, and H. Cassab, "A Cnceptual Framewrk fr Cnsumer Infrmatin Systems Develpment," Pacific Asia Jurnal f the Assciatin fr Infrmatin Systems, vl. 2, pp , [2] S. L. Varg and R. F. Lusch, "Evlving t a New Dminant Lgic fr Marketing," Jurnal f Marketing, vl. 68, pp. 1-17, [3] V. K. Tuunainen and T. Tuunanen, "IISIn- A mdel fr analyzing ICT Intensive Service Innvatins in n- sided Markets," 2011, pp [4] K. N. Lemn and M. H. Huang, "IT- Related Service: A Multidisciplinary Perspective," Jurnal f Service Research, vl. 14, p. 251, August [5] I. R. Bardhan, H. Demirkan, P. Kannan, and R. J. Kauffman, "Special Issue: Infrmatin Systems in Services," Jurnal f Management Infrmatin Systems, vl. 26, pp. 5-12, [6] T. Tuunanen, J. Bragge, J. Häivälä, W. Hui, and V. H. Virtanen, "A Methd fr Recruitment f Lead users frm Virtual Cmmunities t Innvate IT Enabled Services fr Cnsumers in Glbal Markets," Pacific Asia Jurnal f the Assciatin fr Infrmatin Systems, vl. 3, p. 3, 2011.

11 Tuure Tuunanen (Primary Cntact) University f Jyväskylä Department f Cmputer Science and Infrmatin Systems P.O. Bx 35 FIN Tel: tuure@tuunanen.fi Ola Henfridssn University f Warrick Business Schl Cventry CV4 7AL, United Kingdm Ola.Henfridssn@wbs.ac.uk Til Böhmann University f Hamburg Department f Infrmatics Vgt- Kölln- Str. 30 D Hamburg Germany Tel: til.behmann@uni- hamburg.de

12 Digital Service Innvatins based n "Open" Phenmena and Practices Value prduced by digital service innvatin is disrupting established markets as well as generating entirely new nes. The innvatins cme frm many different surces: traditinal R&D, crss- industry initiatives, new entrants that displace incumbents in traditinal industries and mre and mre frm pen develpment prcesses r crwdsurcing f new ideas frm cnsumers as existing r ptential custmers. This minitrack fcuses n thse pen phenmena and practices. Examples new kind f develpment penness include, fr example: the pening f the vast data resurces cllected by authrities and different gvernmental units, the increasing availability f new pen sensr data (fr example, frm mbile devices), and innvatin cntests. We seek nvel research describing innvative services r service systems that are created. The submissins can be research papers, case studies, r practitiner reprts related new service develpment and their implicatins. Relevant tpics fr this minitrack include (but are nt limited t): Nvel appraches t crwdsurcing new digital service ideas Nvel appraches t develpment f new digital services Business value f digital service innvatins Business mdel destructin/creatin caused by digital service innvatins Open data service ecsystems Applicatins and mdels utilizing quantified self data Mydata/Midata and similar persnal data management appraches Lcatin and sensr data based digital services Open data infrastructures Privacy issues related t pen data and pen data services Juh Lindman (Primary Cntact) Hansen Schl f Ecnmics juh.lindman@hanken.fi Matti Rssi Aalt University Schl f Business matti.rssi@aalt.fi Virpi Tuunainen Aalt University Schl f Business virpi.tuunainen@aalt.fi

13 Gamificatin: Mtivatins, Effects, and Analytics Cutting edge research n gamificatin, the increased cnvergence f games and everyday life. A wide array f cntributins relating t the emplyment f the pwer f psychlgical and behaviral mechanisms classically attributed t hm ludens in and int systems meant fr hm ecnmicus are welcmed. Studies incrprating related mechanisms such as status reprts, tp lists, level advancement, acknwledgements f user status, pints and ther instant rewards and virtual assets are welcmed and the wide variety f research utcmes can include business benefits, hednic pleasure, cnversin and click- thrugh, satisfactin, enjyment, fun r flw. Relevant tpics fr this minitrack include (but nt limited t): Impact f games and gamificatin: User behavir User psychlgical states Organizatinal impacts Scietal impacts Recent develpments in game and gamificatin applicatins: Emerging mbile and web applicatins Gamificatin- related develpment features in enterprise systems and decisin supprt systems Game/gamificatin design: Classical gamificatin mechanisms Emerging ideas, features and mechanisms fr gamificatin Fun and games based system design philsphies Theretical cntributins f mtivating system use and technlgy adptin Player and user mtivatins: What needs games satisfy Why d peple play/adpt/use different games Outcmes f gamificatin: Business benefits, hednic pleasure, cnversin and click- thrugh, satisfactin, enjyment, fun and flw. Juh Hamari (Primary Cntact) University f Tampere Tel: juh.hamari@uta.fi Petri Parvinen Aalt University Schl f Science, Finland Tel: petri.parvinen@aalt.fi

14 Humanitarian Operatins Research - Decisin Analytics fr Crisis and Disaster Management The aim f this minitrack is t prvide a frum fr discussin n methdlgies, slutins, and issues related t decisin analytics in humanitarian peratins research. We invite submissins n the general area f prviding analytical capabilities fr decisin supprt. General tpics include, but are nt limited t: Predictin and frecasting Data analytics Optimizatin under uncertainty and multi- bjective ptimizatin (w.r.t. the general tpic) Simulatin appraches Ruting in wireless lcal netwrks Humanitarian supply chains Evacuatin mdels Vehicle ruting Facility lcatin Early warning systems Decisin supprt systems Mbile slutins and services Cmmunicatins systems Erik Krpat (Primary Cntact) University f the Bundeswehr Munich erik.krpat@unibw.de Silja Meyer- Nieberg University f the Bundeswehr Munich silja.meyer- nieberg@unibw.de

15 Intelligent Decisin Supprt fr Lgistics and Supply Chain Management This minitrack aims at rganizing a minitrack cnsisting f tw sessins depending n the number f high quality submissins. We seek papers dealing with decisin technlgies which cntribute t intelligent decisin supprt in the whle field f lgistics and in particular in all categries f SCM. This includes but is nt restricted t simulatin, ptimizatin, heuristics, metaheuristics, agent technlgies, decisin analytics, descriptive mdels, and data mining. We are especially interested in real- wrld applicatins and in sftware slutins which assist in slving decisin prblems. This is extended twards, e.g., cmputatinal lgistics, advanced planning systems and the intelligent use f ERP systems. Als cnceptual ideas, reprts n prjects in prgress, and case studies are welcme. Mrever, teaching cases bth at the university as well as the executive level may be f interest. Stefan Vß (Primary Cntact) University f Hamburg, Germany Tel: stefan.vss@uni- hamburg.de Hans- Jürgen Sebastian RWTH Aachen University, Germany Tel: sebastian@r.rwth- aachen.de dimka@temple.edu

16 Interactive Visual Decisin Analytics Interactive Visual Decisin Analytics supprts human decisin making thrugh interactin with data and statistical and machine learning prcesses. IVDA applies in brad range f situatins where human expertise must be brught t bear n prblems characterized by massive datasets and data that are uncertain in fact, relevance, lcatin in space and psitin in time. Current applicatins include envirnmental science and technlgies, natural resurces and energy, health and related life sciences, precisin medicine, safety and security and business prcesses. We als encurage submissins that extend the areas f use t new analytic tasks in science and technlgy, public health, business intelligence, financial analysis, and ther dmains. Submissins may include studies f visual analytics and decisin supprt in the cntext f an rganizatin (e.g., cmmunicatin between analysts and plicy- makers), perceptual and cgnitive aspects f the analytic task, Interactive Machine Learning, and cllabrative analysis using visual infrmatin systems. This prpsal builds upn ur successful HICSS- 47 and HICSS 48 minitracks n visual analytics fr decisin supprt and ur earlier minitracks n visual analytics, mbile cmputing, and digital media at scale. It seeks t define analytical methds and technlgies that use interactive visualizatin t meet challenges psed by data, platfrms, and applicatins fr decisin making and risk- based decisin making: Visualizatin and Analysis f datasets f varying size and cmplexity frm archives and real- time streams Cllabrative visual analysis and peratinal crdinatin within and acrss rganizatins. Interactive and Visual Risk- based decisin making Interactive Machine Learning methds Crss- platfrm interperability, frm mbiles t data walls Managing respnse time f cmplex analytical tasks Effective deplyment and case studies f success frm deplyed visualizatin and analytics experiences Visualizatin and analytics fr data- driven plicy making and decisin supprt Issues and Challenges f evaluatin f visual decisin making Cgnitive and scial science aspects f visual decisin making envirnments Fr HICSS 2016, we encurage authrs t address these themes frm their wn research perspectives. Authrs are encuraged t bring the lens f their wn backgrund and expertise t fcus n the analytics f the data itself and crdinatin f multiple levels f analysis, decisin- making and peratins t the design and evaluatin f effective presentatins fr stakehlders. Bth algrithmic data sciences appraches and human- centered "visualizatin" and visual analytics human- cmputer interface methds hld great prmise fr peratinalizing massive datasets and streaming data in supprt f a brad range f human activities. Applicatins in basic scientific research, business analytics, health sciences, envirnmental science and engineering R&D explre the implicatins f these methds fr advancement f knwledge and strategic planning. Applicatins in crdinatin, cmmand and cntrl f cmplex human activities such as crwd and

17 traffic management, disaster relief, law enfrcement, and natinal and cyber security add the cnstraints f real- time perfrmance and distributin f planning t the challenges faced. Fr this minitrack we invite cmputatinal, cgnitive, and rganizatinal perspectives n advanced data prcessing and interactive visualizatin acrss a range f human endeavrs. We als invite participatin frm researchers wh are lking at scaling issues and multiscale issues, whether these scales refer t the time f decisin making, the frm- factr and peratinal cnstraints f mbile devices, the number f decisin makers r the mre traditinal ntin f multiscale simulatin and real wrld scales f data. We are particularly interested in appraches that cmbine cmputatinal and interactive analytics in mixed initiative r Interactive Machine Learning systems, decisin supprt in the cntext f an rganizatin (e.g. cmmunicatin between analysts and plicy- makers), perceptual and cgnitive aspects f the analytic task, and cllabrative analysis using visual infrmatin systems. David S. Ebert (Primary Cntact) Schl f Electrical and Cmputer Engineering Purdue University Tel: (765) ebertd@purdue.edu Brian Fisher Schl f Interactive Arts Simn Fraser University Tel: (778) bfisher@sfu.ca Kelly Gaither Texas Advanced Cmputing Center University f Texas Tel: (512) kelly@tacc.utexas.edu

18 Mbile Value Services This minitrack cvers different aspects f design, realizatin and implementatin, use and effect f mbile value services within a business envirnment. We fcus n business aspects, such as business mdels, business impacts f mbile infrmatin systems, use f mbile apps and platfrms in a business envirnment as well as their effects n the ne hand as well as mre technlgy and design riented aspects n the ther hand. Mbile applicatin develpment that is either native r is fllwing a crss- platfrm apprach is an imprtant tpic. As HICSS is addressing leading edge develpments, we especially encurage submissins n is- sues as: adaptability and adaptivity f mbile services and platfrms, n mbile clud services, and n the rle and relevance f reliability, privacy and security. Fr the business riented part f the mini- track submissins n business mdels, platfrms in relatin with (pen and clsed) micr ec- systems within a business envirnment are invited. We welcme studies n use and effect f mbile applicatins and platfrms in business envirnments. We seek mbile business research papers, case studies, and practitiner reprts related t business aspects. Of special interest are cnceptual and empirical papers analyzing business and business mdel aspects, including mbile services and applicatin develpment and design that g beynd existing technlgies and fr instance lk int clud r sensr technlgies. Such applicatins will cntribute t the advancement f user- inspired and emplyee centric infrmatin systems design within this paradigm. We welcme studies with either qualitative r quantitative research methds as well as design research. Pirkk Walden (Primary Cntact) Åb Akademi University Tel: pirkk.walden@ab.fi Tmi Dahlberg Åb Akademi University Tel: tmi.dahlberg@ab.fi Esk Penttinen Aalt University Schl f Business Tel: esk.penttinen@aalt.fi

19 Multi- criteria Decisin Analysis and Supprt Systems Mst decisins invlve multiple bjectives. A decisin alternative is chsen based n a multitude f ften- cnflicting decisin criteria, and a slutin is sught that prvides the best cmprmise with respect t these varius desired bjectives. Multi- criteria decisin- making (MCDM), ver the last frty years, has becme an established field f research, with extensive thery, a wide chice f slutin methds, and a number f available cmputer- based decisin supprt packages. Many general sftware tls, such as linear prgramming packages and electrnic spreadsheets that d nt implement specific MCDM techniques, can als be used t analyze multi- criteria prblems. Multi- criteria decisin supprt (MCDSS) may fcus n varius stages f the decisin making prcess, frm prblem explratin and structuring, t discvering the decisin- maker s preferences and the mst preferred cmprmise slutin. Pssible tpics fr this minitrack may include: Success factrs fr MCDSS The rle f the decisin- maker in effective multi- criteria decisin supprt Case studies f multi- criteria decisin supprt Design f technlgy fr specific aspects r phases f multi- criteria decisin supprt Decisin supprt fr prject selectin Decisin supprt fr specific applicatins dmains (e.g. health care) Classificatins f decisin prblems and slutin technlgy Tls and techniques fr multi- criteria prtfli selectin Slutin appraches t special types f decisin prblems invlving cnflicting bjectives Quality and types f data in multi- criteria decisin supprt Rakesh Sarin (Primary Cntact) University f Califrnia Ls Angeles rakesh.sarin@andersn.ucla.edu Heinz- Rland Weistrffer Virginia Cmmnwealth University hrweistr@vcu.edu

20 Service Analytics Research tpics addressed in this minitrack include the applicability f basic and advanced analytics t different service systems, the state- f- the- art f service analytics methdlgies and tl- supprt, and the investigatin f benefits resulting frm the applicatin f service analytics. This minitrack will serve as a frum fr researchers and practitiners t share prgress in the study f these and related themes. Submissins n, but nt limited t, the fllwing tpics are encuraged: Web Usage Mining and Web Persnalizatin Data Mining Machine Learning applied t Services Recmmender Systems fr Services Scial Netwrk Analytics applied t Services Privacy Issues resulting frm Service Analytics Fraud Analytics fr Service Systems Analysis and Predictin f User Behavir in Mbile Phne Systems Analysis and Predictin f Driver Behavir in Traffic Situatins Analysis and Explitatin f Flating Car Data Electricity Cnsumptin Analysis using Smart Meter Data Analytics fr Healthcare Services Analysis and Predictin f IT Service Demand Patterns Analysis f Service Prblem Reprts Industrial Service Analytics and Optimizatin Sprts Analytics Hansjerg Frmm (Primary Cntact) Karlsruhe Institute f Technlgy (KIT) Tel: hansjerg.frmm@kit.edu Gerhard Satzger IBM Germany Tel: satzger@de.ibm.cm Thmas Setzer Karlsruhe Institute f Technlgy (KIT) Tel: thmas.setzer@kit.edu

21 Service Science Service science deals with the design, develpment, and managerial issues cncerning service systems, integrated, value- creating cnfiguratins f service prviders, their clients, their partners, and thers. The best- perfrming service systems are IT- enabled, custmer- centered, relatinship- fcused, and knwledge- intensive - yet span multiple frmal and infrmal rganizatins. Because f this multidisciplinary cntext, researchers and practitiners in management, scial sciences, and cmputer sciences are all wrking t increase service innvatin. These multiple perspectives can be unified using the theretical cnstruct f the service system, in which entities (peple, businesses, gvernment agencies, etc.) interact t c- create value via value prpsitins that describe dynamic re- cnfiguratins f resurces. The framewrk f value creatin in cmplex service systems, which requires elabrating varius stakehlder perspectives and understanding the brad cntext f use fr specific cases t enable effective value creatin especially given advanced and autnmus technlgy, has emerged as the central unifying framewrk acrss many papers and presentatins. The Service Science minitrack will fcus n papers that cnnect rigrus disciplinary research with the emerging interdisciplinary framewrk f value creatin in service systems, fcusing particularly n service design, innvatin, and technlgy. Paul Magli (Primary Cntact) University f Califrnia, Merced Tel: (831) pmagli@ucmerced.edu Fu- ren Lin Natinal Tsing Hua University, Taiwan furen1963@gmail.cm Michael Shaw University f Illinis, Urbana- Champaign mjshaw@illinis.edu

22 Smart Service Systems: Analytics, Cgnitin and Innvatin Smart service systems can be characterized by: (1) the types f fferings t their custmers and/r citizens, (2) the types f jbs r rles fr peple within them, and (3) the types f returns they ffer investrs interested in grwth and develpment, thrugh imprved use f technlgy, talent, r rganizatinal and gvernance frms, which create (dis)incentives that (re)shape behavirs. An imprtant trend in smart service systems is the increasing availability f cgnitive assistants (e.g., Siri, Watsn, Jib, Ech, etc.) t bst prductivity and creativity f all the peple inside them. There is a need t apply rbust research findings in the apprpriate management and rganizatinal cntexts related t innvatin f smart service systems, service innvatin, quality, architecture, design and delivery, and the resulting custmer satisfactin and business value. In part, because f analytics and cgnitive systems, smart service systems adapt t a cnstantly changing envirnment t benefit custmers and prviders. Using big data analytics, service prviders try t cmpete fr custmers by (1) imprving existing fferings t custmers, (2) innvating new types f fferings, (3) evlving their prtfli f fferings and making better recmmendatins t custmers, (4) changing their relatinships t suppliers and thers in the ecsystem in ways their custmers perceive as mre sustainable, fair, r respnsible. The gal f this minitrack is t explre the challenges, issues and pprtunities related t innvatin f smart service systems that enable value c- creatin with analytics, cgnitive and human systems. We are interested in nvel theries, appraches and applicatins fr innvatin f smart service systems. Pssible tpics f applied, field and empirical research include, but are nt limited t: Theries, appraches and applicatins fr innvatin f smart service systems Value c- creatin prcesses, metrics and analytics fr smart innvatin prcesses Methds scale the benefits f new knwledge glbally, rapidly, and prfitably Service- riented agile IT realizatin platfrm fr smart service c- creatin Place f cgnitive systems, cmputing, system engineering, clud fr smart service systems Innvatin ecsystems with internet and internet- f- things Theries and appraches fr integrating analytical and intuitive thinking prcesses Open innvatin and scial respnsibility Planning, building and managing design and innvatin infrastructures and platfrms Technlgy and rganizatinal platfrms supprt rapid scaling prcesses (smart phnes, franchises, etc.) Smart service systems include the custmer, prvider, and ther entities as surces f capabilities, resurces, demand, cnstraints, rights, respnsibilities in value c- creatin prcesses, and includes current applicatins f human and cgnitive systems Analytics mdels, tls and engine fr analytics supprt Agile business develpment platfrm fr peratinal enablement: business prcesses, rules, real- time event management The cmmditizatin f business prcesses (e.g. ut- tasking, ITIL, SCORE), sftware (e.g. the sftware- as- service mdel, sftware riented architecture, applicatin service prviders) and hardware (e.g., n- demand, utility cmputing, clud cmputing, sftware riented infrastructure with virtualized resurces, infrastructure service prviders fr innvatins Self- service and smart technlgies & management fr sustainable innvatins

23 Services implicatins t value chains, netwrks, cnstellatins and shps Cllabrative innvatin management in B2B and B2C e- cmmerce Haluk Demirkan (Primary Cntact) University f Washingtn - Tacma Tel: (253) haluk@uw.edu Jim Sphrer IBM Almaden Research Center Tel: (408) sphrer@us.ibm.cm Ralph Badinelli Virginia Tech Tel: (540) ralphb@vt.edu

24 Sft Cmputing Sft Cmputing refers t a cllectin f cmputatinal techniques (Neural Netwrks, Evlutinary Cmputing, Fuzzy Systems, Bayesian netwrks, etc.) which study, mdel, and analyze very cmplex phenmena: Thse fr which mre cnventinal methds have nt yielded lw cst, analytic, and cmplete slutins. The purpse f this Mini- Track is t study Sft Cmputing methds in cnnectin with building intelligent decisin supprt systems (DSS) and infrmatin retrieval systems (IRS). They shuld supprt managers and knwledge wrkers in prblem slving, planning and decisin- making. Interpretability, due t its human- centric character, plays a key rle in DSS and IRS mdeling where there is a huge interactin with humans. Intelligent systems endwed with interpretability capabilities are likely t be trusted n by end- users, increasing the success rate f intrducing intelligent systems int the market. This Minitrack prvides a frum t discuss and disseminate recent and significant advances in Sft Cmputing regarding thery and technlgy transfer. It will prvide a frum t discuss and disseminate recent and significant research effrts n the Sft Cmputing research alng with the presentatin f sme challenging applicatins. The fcus f the Mini- Track is t facilitate crss- fertilizatin between methdlgical and applied research. The tpics f interest include but are nt limited t: New Methds: Fuzzy lgic Artificial neural netwrks, self- rganizing maps Prbabilistic reasning Swarm intelligence, ant algrithms Evlutinary cmputing Optimizatin Linguistic summarizatin Cmputing with perceptins Knwledge extractin, representatin, mdeling Decmpsable mdels Interpretability issues Applicatins: Infrmatin mining Mining and representing tempral and spatial data Mining and representing text and semi- structured data Graph mining Intelligent data analysis Infrmatin retrieval techniques Infrmatin retrieval mdels and applicatins Infrmatin filtering mdels and systems Infrmatin visualizatin and explratin Interactive retrieval, user mdels and studies Metadata extractin and generatin

25 Multimedia cntent- based infrmatin retrieval Web and distributed infrmatin retrieval Infrmatin extractin and integratin Infrmatin clustering and classificatin Persnalizatin and persnal infrmatin management Semantic Integratin Questin answering Decisin supprt and innvatins Scial netwrks Sensry analysis Rbtics Rudlf Kruse (Primary Cntact) Ott vn Guericke University Magdeburg Tel: Gabriella Pasi University f Milan Biccca Tel: pasi@disc.unimib.it Jsé M. Alns Eurpean Centre fr Sft Cmputing Tel: jse.alns@sftcmputing.es

26 Streaming Data Analytics and Applicatins Bth academia and rganizatins shw great interest in streaming big data analytics - the prcess f extracting knwledge structures frm cntinuus, high vlume and high velcity cntinuus flw f data in a myriad f frmats frm a variety f real- time data surces. The challenge fr rganizatins lies in being able t transfrm this deluge f data int instantaneus intelligence that can enable faster, better business decisins. Fr academia, mining streaming data is still nt a mature discipline which faces sme unique theretical and practical challenges. This minitrack aims t present and share new research in defining and highlighting the values f stream data analytics, including new thery, algrithms, innvatin in methdlgies, and benefits frm variety applicatins. Tpics include, but are nt cnstrained nly t: Data stream mining techniques and methdlgies Adaptive data mining Distributed data stream mdels Graph- based stream mdels Cncept drift in streaming data Visualizatin fr big data streams Deep learning n stream data Real- wrld applicatins using streaming data analytics in: Health care Banking Industry Scial netwrks Intelligence and cybersecurity Smart pwer grid Sensr netwrks Internet f Things Situatin awareness Mehmed Kantardzic (Primary Cntact) Cmputer Engineering and Cmputer Science Department J.B. Speed Schl f Engineering University f Luisville Tel: (502) mmkant01@exchange.luisville.edu Jzef Zurada Cmputer Infrmatin Systems Department Cllege f Business University f Luisville Tel: (502) jmzura01@luisville.edu

27 Systemic Financial Risk Analytics In the aftermath f the glbal financial crisis f 2007/2008, there is an acute interest in analytics fr early identificatin and assessment f risks and vulnerabilities that eventually may lead t a systemic financial crisis. This minitrack brings tgether the mst recent advances n cmputatinal tls fr systemic financial risk identificatin and assessment, including early- warning indicatrs and mdels, stress- testing mdels, and cntagin r spillver mdels. The key aim f the minitrack is t adpt methds and techniques frm ther disciplines, such as cmputer science, bilgy and physics, that make use f cmputer- intensive appraches, nvel data surces, visual representatins r interactive interfaces, amng thers. The minitrack als cvers a range f ther related tpics, such as methds fr the analysis f cinciding systemic financial stress and systemically imprtant financial institutins. Hence, it slicits cntributins n a wide range f tpics n analytics related t systemic financial risk and financial stability. Peter Sarlin (Primary Cntact) Hanken Schl f Ecnmics Tel: peter@risklab.fi Tumas Peltnen Eurpean Central Bank tumas.peltnen@ecb.int

28 Wearables and Quantified Self Infrmatin systems are getting clser t ur bdies, and the bundary between the user and the machine is blurring. Wearable intelligence is the next chapter f the mbile revlutin in emerging technlgies. Wearables are nt just a cnsumer phenmenn; they have the ptential t change the way rganizatins cnduct business. Fr example, data cllected by wearable medical devices has the ptential t disrupt many industries including healthcare and insurance. There is need fr research t investigate this phenmenn. This minitrack will fcus n the rle f wearable technlgies and the data cllected thrugh wearables. Areas f wearable cmputing research include user interface design, augmented reality, pattern recgnitin, and wireless and persnal area netwrk technlgies. We encurage authrs t submit cnceptual, design and empirical wrk relevant t wearables and quantified self areas. We slicit papers in varius tpics, including, but nt limited t the fllwing: Theries regarding wearable intelligence and quantified self Challenges in managing wearables and the data cllected thrugh them New methds t analyze wearable intelligence Analytical mdels fr the wearables industry Prcess- redesign fr the wearable technlgies Case studies n wearables and quantified self Quantified self and big- data analyses, analytical mdels, and simulatins System design, and applicatin areas Impact n user interface design, augmented reality, and wireless netwrks Integrating wearables int larger systems (such as augmented reality systems, training systems, and platfrms fr cllabrative wrk) Behaviral mdels Management f wearable devices Cultural and scial implicatins f adpting wearable cmputing devices Privacy, persnal safety, and quality f life issues Tayfun Keskin (Primary Cntact) University f Washingtn Bthell Tel: (425) keskin@uw.edu Deanna Kennedy University f Washingtn Bthell Tel: (425) deannak@uw.edu Hug Paredes University f Trás- s- Mntes e Alt Dur (UTAD) Tel: (351) hparedes@utad.pt