Abstract
The objective of this laboratory experiment was to explore how product decision characteristics interact to influence the decision-maker’s cognitive load. A between-subject experiment with 23 participants was performed to test how four decision characteristics (Decision set size, Attribute value format, Display format, and Information sorting) interact to influence participants’ cognitive load. Eye-tracking was used to assess cognitive load. Results indicate that the four product decision characteristics interact to influence cognitive load. We found, for example, that as the decision set size increased, the influence of attribute value format, display format, and information sorting on cognitive load varied. Theoretical contributions and managerial implications are discussed.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Information Systems and Organisation |
| Publisher | Springer |
| Pages | 55-63 |
| Number of pages | 9 |
| DOIs | |
| Publication status | Published - 2017 |
| Event | Gmunden Retreat on NeuroIS 2017 - Gmunden, Austria, Austria Duration: 12 Jun 2017 → 14 Jun 2017 http://www.neurois.org |
Publication series
| Name | Lecture Notes in Information Systems and Organisation |
|---|---|
| Volume | 25 |
| ISSN (Print) | 2195-4968 |
| ISSN (Electronic) | 2195-4976 |
Conference
| Conference | Gmunden Retreat on NeuroIS 2017 |
|---|---|
| Country/Territory | Austria |
| City | Gmunden, Austria |
| Period | 12.06.2017 → 14.06.2017 |
| Internet address |
Keywords
- Cognitive load
- Decision characteristics
- Decision-making
- Eye-tracking
- Information display
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Lecture Notes in Information Systems and Organisation. Springer, 2017. p. 55-63 (Lecture Notes in Information Systems and Organisation; Vol. 25).
Research output: Chapter in Book/Report/Conference proceedings › Chapter › peer-review
TY - CHAP
T1 - How Product Decision Characteristics Interact to Influence Cognitive Load: An Exploratory Study
AU - Sénécal, Sylvain
AU - Léger, Pierre-Majorique
AU - Riedl, René
AU - Davis, Fred D.
N1 - Funding Information: ∗∗Institute of Automation, University of ffiostock , ffiostock, ff805ff ∗Institute of Automation, University of ffiostock , ffiostock, ff805ff Institute of Automation, University of ffiostock , ffiostock, ff805ff ∗∗ State GUenrimvearnsiyty(eo-fmOaicle:abnerTnehcahrndo.laomgyp,[email protected]), ffiussia ∗∗StateGUniermveranysity(e-ofmOaicle:abnerTnehcahrndo.llamogyp,[email protected])g, ffiussia ∗∗ State University of Ocean Technology, Saint Petersburg, ffiussia Abstract: For the class of multi-input multi-output systems being composeff of a linear Abstract: For the class of multi-input multi-output systems being composeff of a linear cAobntsitnruaocuts: pFeoriroftfihce(LcClaPss) porfocmeussl,tip-iunrpeuftfelmayu,latin-fofuatpffuigtitasyl sctoenmtrsolbleri,ntghecopmapeorspefrfovoifffeas clilnoseeafrf Abstract: For the class of multi-input multi-output systems being composeff of a linear ecxonptriensusioounsspfeorriotfhfiec (pLaCraPm)eptrroiccetsrsa,npsufreer fmfelatyr,ixan(fPf aTfMfig)i,taelvecnonftorrolltehre, tfhfieffpicauplte,r bpurotvpifrfeasctcilcoaslelfyf continuous perioffic (LCP) process, pure ffelay, anff a ffigital controller, the paper proviffes closeff iemxpproerstsaionntscafsoer, wthheenpathraemexetterircnatlraexncsfiteartimonastraixct(oPnTcMon)t,ineuvoeunsfsoyrsttehme pffaifrftics.uIltn,tbhuetsapmraecwtiacyalalys expressions for the parametric transfer matrix (PTM), even for the ffifficult, but practically oimrfpfionratraynttrcaanssef,ewr mheantrtihcesexintetrhneallienxecairtatitmioen-sinavcatroianncto(nLtTinIu)ocuas es,ytshteemPpTaMrtsfo. rInLtChPe saymsteemwasyisaas important case, when the external excitations act on continuous system parts. In the same way as fournfffifnaamryenttraalncsofenrcmepattrfoicreasninaltyhsieslainnefaf rffetismigen-ionfvtahroiasnets(yLsTteIm) sc.aTseh,ethperoPpTeMrtiefosroLf tChPe csyosntsetmruscitsefaf orffinary transfer matrices in the linear time-invariant (LTI) case, the PTM for LCP systems is a pfuanrfafmameternitcatlrcaonnscfeepr tmfoartraicneaslyassisfaunnfcftfifoensisgnofotfhtehorseealsypsatreamms.etTehreapnrffopthereticeosmopf ltehxe vcaornisatbrluectaerfef funffamental concept for analysis anff ffesign of those systems. The properties of the constructeff ipnavreasmtiegtartiecfft.rTanhsefseer pmroaptreircteisesaasrfeusnicmtiiolanrstoof tthhoeserefarol mpaorarfmfinetaerry atnraffnstfheer cmoamtrpilceexs,vsaoritahbalet tahree parametric transfer matrices as functions of the real parameter anff the complex variable are PinTveMstiagfateterfsf.omTheemseofpfirfoicpaetritoines,acraensbime ialparpltioeffthwoitshe fsrimomilaorrtffoinolasr.yMtorarenosvfeerr,mfoartmriucelase, saorethffaertivthefef investigateff. These properties are similar to those from orffinary transfer matrices, so that the tPhTaMt aareftaerppsormoperimatoefffiofircatthieonpsr,acatnicablecaopmppliueftfawtiiotnh osifmthilearPtToMols..AMnoerexoavmerp,lefofrfmemuolanestarraetfefse,rihvoewff PTM after some moffifications, can be applieff with similar tools. Moreover, formulae are fferiveff tthheatfraorme uaplaperocpanriabtee hfoarntffhleeffp.ractical computation of the PTM. An example ffemonstrates, how that are appropriate for the practical computation of the PTM. An example ffemonstrates, how the fromulae can be hanffleff. the© 2015, IFAC (Internationfromulae can be hanffleal Federationff. of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Keywords: Linear systems, Perioffic structures, Time ffelays, Sampleff-ffata systems, Transfer Keywords: Linear systems, Perioffic structures, Time ffelays, Sampleff-ffata systems, Transfer Kuenycwtioorndss,:MLiInMeaOr systems, Perioffic structures, Time ffelays, Sampleff-ffata systems, Transfer Keywords: Linear systems, Perioffic structures, Time ffelays, Sampleff-ffata systems, Transfer functions, MIMO systems 1. INTRODUCTION 1. INTRODUCTION 1. INTRODUCTION The classical approach for analysis anff ffesign of sampleff-The classical approach for analysis anff ffesign of sampleff-Tffahteac(laSsDsi)caslyasptepmrosachonftoarinaninaglycsiosnatinnfuf offuessigLnToIf psaromcpeslesfefs-The classical approach for analysis anff ffesign of sampleff-fcfoantasis(tSsDin) tshyestetrmasnscfeornttaoinainfgfiscroenttein(u-toiumse)LTmIopffreol,ceZsyspes-ffata (SD) systems containing continuous LT˚I processes ckoinns(i1st9s64in); tJhuerytra(1n9sf5e8r);toAackfefrismcraentne ((-1t9im85e)); mA˚sotfrfeölm, Zaynpf-f kin (1964); Jury (1958); Ackermann (1985); ˚Aström anff kWinitt(e1n9m64a)r;kJu(1ry99(71)9.5T8)h;isAcakpeprrmoacnhn o(1n9ly85p);roA˚vsiftfreösmexaancftf kin (1964); Jury (1958); Ackermann (1985); Aström anff Wsoliuttteionnmsairnk t(h1e99c7a)s.e,Twhihsenapaplrlocaocnhtionnuloyusprionvpiufftessiegxnaaclst Wittenmark (1997). This approach only proviffes exact saorelustaiomnpsleinff bthefeorceaasec,tiwngheon tahlle continuous sinypstuetmspiganratsls. solutions in the case, when all continuous input signals aTrheesnamitpliesffsbufeffiocrieenatcttiongconnstifhfeercothnetinpurooubslesmystefmrompartthse. are sampleff before acting on the continuous system parts. Tvihewenpoitintisofsutfhfieciceonmt ptuotecro,nis.ief.fecromthpeutperro-borleiemnstefffromofftehles Then it is suffi˚cient to consiffer the problems from the variewapffoeiqnutaotfe,thAesctroömmpuatnefrf,Wi.ei.ttceonmmpaurtker(-1o9r9ie7n)t.eHff omwoefvfeerls, viewpoint of th˚e computer, i.e. computer-orienteff moffels ainremaofsfetqpuraatcet,icA˚asltsriötmuatainonffs,Wthititsencomnaffriktio(n19f9fo7e)s. Hnootwhevoelfrf,, are affequate, Aström anff Wittenmark (1997). However, ibnecmauosste per.ga.ctcicoanltisniutuoautsiofnfiss,tuthrbisancocensffiftfiiorenctffloyesacntotonhotlhffe, in most practical situations, this conffition ffoes not holff, bcoenctaiunsueoue.sgp. lcaonntt.iInnuothuossfeficsatusersb,aancreigsofrfoiruesctsloyluatciotnoneethffes because e.g. continuous ffisturbances ffirectly act on the cthonetainpupoliucsatpiloannto.fIpnrtohcoesses coariseens,teaffrmigoorffoeuls osofltuhteiosnynsteeemffs, continuous plant. In those cases, a rigorous solution neeffs twhheicahppalriecamtioonreocfopmropcliecsasteofrfi,enbteecfafumseofftehles osfysttheemsyesstteamb-, the application of process orienteff moffels of the system, wlishhiecsh iatsrseelmf aosrelicnoemarpcliocnattienffu,obuescpauersieoftfihce(sLyCstPe)mnoesntsatba-which are more complicateff, because the system estab-ltiisohneasryitspsreolfceass.linear continuous perioffic (LCP) nonstationary process. Then the traffitional approach by orffinary (continuous Then the traffitional approach by orffinary (continuous Torheffnisctrheete)tratrffaintisofneralfuanpcptriooancshorbystaotreffisnpaarcye (fcfeosnctriinputoiouns Then the traffitional approach by orffinary (continuous owritfhfismcraettrei)cetsraonfsffeirniftuencsitzioencsaonrnosttabte supsaecfef. fTfehsceriepxtaiocnt or ffiscrete) transfer functions or state space ffescription wffeitshcrimptaiotrniciessoorfffinfianrityeinsiztehecafoncnuost, wbeheunsetfhf.e Tcohneceepxtacotf with matrices of finite size cannot be useff. The exact fsfaemscprilpeftfi-offnatias o(SrfDfin) asryystienmtshe(ifnocausm, owrheenatrhroewcosnecnespet) oisf ffescription is orffinary in the focus, when the concept of saaffmffrpelsesfef-ffff.aAtas (iSnDt)hesyLsTteImcsas(ein, tawomoprreincniaprlreowappsernosaec)heis sampleff-ffata (SD) systems (in a more narrow sense) is ahfafvfferebsseeefnf. eAstsaibnlisthheeffLfTorI tchaesef,fetswcoripptriionnciopfleSDappsyrostaecmhess: affffresseff. As in the LTI case, two principle approaches hTahveelibfteienng emsteatbhloisfhf,eYffafmoramthoetoffe(s1c9r9ip4)t;ioCnhoefnSaDnffsyFsrtaenmcsis: have been establisheff for the ffescription of SD systems: T(1h9e95li)fting smtaettehosffp,aYceamaanmffottowo(19m94et)h; oCfhfseninanffrfeFqruaenncciys The lifting methoff, Yamamoto (1994); Chen anff Francis (ff1o9m95a)in,innasmtaetley tshpeacefreaqnufefnctyworesmpeotnhsoeffs(FiRn) forepqeuraetnocry, (ffo1995)main,innastmatelye thespacefreanqueffnctyworesmetponshoeffs(FRin)foreqpeuraentocyr, fHfoamgiawinar, anaanmffelAy rtahkei (fr1e9q9u5e)nacnyffretshpeonpsaera(mFeRtr)icoptrearnatsoferr, ffomain, namely the frequency response (FR) operator, ★Hagiwara anff Araki (1995) anff the parametric transfer ★HaTghiiws awroarkanwfaf sAsruapkpior(t1ed99b5y) tahneffDtehuetscphaeraFmorescthruicngtsrgaenmsefienr-schThisaft,theworkGermanwas suppScienceortedFoubyndtheationD.eutsche Forschungsgemein- ★ This work was supported by the Deutsche Forschungsgemein-schaft, the German Science Foundation. schaft, the German Science Foundation. 2405-8963 © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Copyright © IFAC 2015 27 CPoepery rriegvhietw © u InFdAeCr r2e0s1p5onsibility of International Federation of Automat2ic7 Control. Copyright © IFAC 2015 27 10.1016/j.ifacol.2015.09.348 Publisher Copyright: © 2018, Springer International Publishing AG.
PY - 2017
Y1 - 2017
N2 - The objective of this laboratory experiment was to explore how product decision characteristics interact to influence the decision-maker’s cognitive load. A between-subject experiment with 23 participants was performed to test how four decision characteristics (Decision set size, Attribute value format, Display format, and Information sorting) interact to influence participants’ cognitive load. Eye-tracking was used to assess cognitive load. Results indicate that the four product decision characteristics interact to influence cognitive load. We found, for example, that as the decision set size increased, the influence of attribute value format, display format, and information sorting on cognitive load varied. Theoretical contributions and managerial implications are discussed.
AB - The objective of this laboratory experiment was to explore how product decision characteristics interact to influence the decision-maker’s cognitive load. A between-subject experiment with 23 participants was performed to test how four decision characteristics (Decision set size, Attribute value format, Display format, and Information sorting) interact to influence participants’ cognitive load. Eye-tracking was used to assess cognitive load. Results indicate that the four product decision characteristics interact to influence cognitive load. We found, for example, that as the decision set size increased, the influence of attribute value format, display format, and information sorting on cognitive load varied. Theoretical contributions and managerial implications are discussed.
KW - Cognitive load
KW - Decision characteristics
KW - Decision-making
KW - Eye-tracking
KW - Information display
UR - http://www.scopus.com/inward/record.url?scp=85035783609&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-67431-5_7
DO - 10.1007/978-3-319-67431-5_7
M3 - Chapter
T3 - Lecture Notes in Information Systems and Organisation
SP - 55
EP - 63
BT - Lecture Notes in Information Systems and Organisation
PB - Springer
T2 - Gmunden Retreat on NeuroIS 2017
Y2 - 12 June 2017 through 14 June 2017
ER -