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Journal of Education for Business
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Effects of Professional Experience and Group
Interaction on Information Requested in Analyzing
IT Cases
Constance M. Lehmann & Cynthia D. Heagy
To cite this article: Constance M. Lehmann & Cynthia D. Heagy (2008) Effects of Professional Experience and Group Interaction on Information Requested in Analyzing IT Cases, Journal of Education for Business, 83:6, 347-354, DOI: 10.3200/JOEB.83.6.347-354
To link to this article: http://dx.doi.org/10.3200/JOEB.83.6.347-354
Published online: 07 Aug 2010.
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hepurposeofthepresentstudywas to determine whether membership in certain types of groups can enhance the quality of information requests by novices analyzing realistic business casesinvolvingunstructuredinformation systemsdesignandimplementation.We analyzedwhetherparticipants(noviceor experienced) benefited from interaction in established groups as opposed to ad hocgroupspriortoanalyzingtheexperi-mentalcaseindividually.
Wefoundthatwithincreasinglevels of professional experience, the num-ber of information requests that match the information requests of a master panel(matchedanswers)alsoincreases. This is consistent with prior evidence thatmoreexperiencedprofessionalsare better at information gathering (e.g., Lehmann & Norman, 2005; Schmidt, Norman, & Boshuizen, 1990; Stevens, Lopo,&Wang,1996).Inanextension ofthispreviousresearch,wefoundthat novicesinestablishedgroupshadhigh-ermatchedinformationscoresthandid novicesinadhocgroupswhencomplet-ing the experimental case individually afterextendedgroupinteraction.
Theresultsofourstudyhaveeduca-tional and training implications. First, ifresearchersandeducatorscanunder- standhowprofessionalsevaluateasitu-ationandrequestinformation,educators willbeinabetterpositiontostructure the college classroom experience and
the corporate training environment to enhance learning. Bonner, Libby, and Nelson (1997) suggested that under-standing the particular aspects of knowledgethatauditorsneedisneces-sary before educators and firms can determinethebestwaystoorganizethe instruction of auditors. We expect the sameistrueofinformationtechnology (IT)professionals.
Second, if established groups are found to be an effective way to help new graduates and new professionals to learn critical problem-solving skills inunstructuredenvironments,thisfind-ingwouldleadtorecommendationson the use of group interaction to educate and train new professionals to practice addressing these types of issues with theirclients.
BackgroundandHypothesis Development
EffectsofExperienceLevels
Many researchers analyzing differ-ences in problem-solving strategies have examined the differences in per-formancebetweenexpertsandnovices. Schmidtetal.(1990)suggestedthatone phenomenonthatcouldnotbeexplained in the medical expertise literature was that experts gathered less, rather than more, data.The authors suggested that becauseexpertsrapidlyassessacasein termsofpreviouscases,theycanfocus
EffectsofProfessionalExperience
andGroupInteractiononInformation
RequestedinAnalyzingITCases
CONSTANCEM.LEHMANN CYNTHIAD.HEAGY
UNIVERSITYOFHOUSTON–CLEARLAKE HOUSTON,TEXAS
T
ABSTRACT. Theauthorsinvestigatedtheeffectsofprofessionalexperienceand groupinteractionontheinformationthat informationtechnologyprofessionalsand graduateaccountinginformationsystem (AIS)studentsrequestwhenanalyzing businesscasesrelatedtoinformationsys- temsdesignandimplementation.Under-standingtheseeffectscancontributeto thesuccessofthecollegeclassroomand corporatetraininglearningenvironments. Theresultssuggestthatastheamountof professionalexperienceincreases,thenum-berofinformationrequeststhatmatchthe informationrequestsdeterminedbyamas-terpanel(matchedanswers)alsoincrease. Inaddition,highernumbersofmatched answersbynoviceswereassociatedwith beinginestablishedgroupspriortocom-pletingtheexperimentalcaseindividually.
Keywords:AISstudents,groupinteraction, informationrequested,informationsys- temsdesignandimplementation,unstruc-turedcases
Copyright©2008HeldrefPublications
ontheinformationneededforconfirma-tion of their diagnosis, whereas nov-icesprogressstep-by-steptodiagnosea case.Inthesameway,ITprofessionals must diagnose the problem presented bytheiremployerorclientanddevelop recommendationstosolvetheproblem. Muchasinthemedicalprofession,these unstructured problems often require additionalinformationtoidentifywhat issues need to be addressed to provide recommendations.
Stevens et al. (1996) confirmed that students requested additional tests and information seldom used by experts. Their requests reflected those recom- mendedintextbooksorlabs.Research- erswouldexpectthataccountinginfor-mationsystem(AIS)graduatestudents would similarly use their textbook knowledge to develop their additional information requests to confirm their diagnosisofanITproblem.ITprofes-and Norman (2005) found that experts requested less information and fewer tests to confirm audit judgments than didintermediate-levelpersonnelandthat intermediate-level personnel requested lessthandidnovices.Abdolmohammadi andWright(1987)foundsimilarresults byusingastructuredtaskforauditors.
On the basis of these studies, in the presentstudy,wedevelopedthefollow-inghypotheses(Hn):
H1 :Higherlevelsofprofessionalexpe-rience will be associated with fewer additional information requests to confirmdecisions.
H2 :Higherlevelsofprofessionalexpe-riencewillbeassociatedwithhigher information-requested scores (i.e., requests that more closely match thoseofthemasterpanel).
EffectsofGroupInteraction
Researchers have studied knowl-edgetransferonsubsequenttasks(e.g., Beane & Lemke, 1971; Hollingshead, 1998, 2000; Laughlin & Barth, 1981; Laughlin & Sweeney, 1977; Lehm-ann, Heagy, & Willson, 2006, Olivera & Straus, 2004). Lehmann et al.
sug-gested that novices show performance improvementinproblemrepresentation afterinteractionwithestablishedgroups. Noviceswhohadworkedinestablished groupsperformedaswellastheexperi-encedprofessionals.LaughlinandBarth found evidence of individual learning afterpracticingtheMastermindtaskas a group, and Olivera and Straus found thattraininginagrouporevenobserv-ingthegroupprocessresultedinbetter subsequent individual performance on brain teasers. Even 10 min of group collaborationcanaffectstudentperfor-Lemke and Hollingshead (2000) sug-gested that having groups with either different levels of ability or an expert facilitatestransfer.
Basedonthesestudies,wetestedthe followinghypothesis:
H3: Novice and experienced participants who had group interaction in estab- lishedgroupswillhavehigherinforma-tion-requested scores than will those whohadadhocgroupinteraction.
METHOD
Sample
Wedrewparticipantsfromaregional publicaccountingfirm(n=7),achapter of the Information Systems Audit and ControlAssociation (ISACA;n = 23), andthreegraduateaccountinginforma-tioncoursesectionsinamedium-sized, upper-leveluniversityintheSouthwest (n=62).ISACA’smembershipincludes professionals with accounting training, as well as professionals in the design, development,implementation,auditing, and security of accounting information systems. The cases used in the experi-mentweresimilartothetypesofcases usedintheAISclasses.Wefeltthatthe graduate AIS students were qualified to participate because they had been exposedtotextbookmaterialsneededto respondtothecases.
We visited the regional accounting firm participants in their offices. The
managing partner (an alumnus of the university)encouragedthemtopartici- pate.TheISACAparticipantscomplet-edthecaseduringamonthlytechnical meetingaspartofatrainingsessionon working with groups. After they com-pleted the individual case and turned in their responses, we led a discussion of the recommended answers. Of the participants, 6 received gift cards in a random drawing, and all participants received1hrofcontinuingprofessional educationcredit.
Of the participating ISACA mem-bers, 2 had no previous experience in the IT field. Of the 62 students who participated,18hadITexperience.The students completed the experiment in theclassroomandearnedextracredit.
Most participants listed accounting (n =41),managementinformationsys-tems(MIS;n=8),oraccounting/MIS (n = 4) as their majors. The sample included 52 men and 40 women. Of those who reported certifications, 26 hadeitherthecertifiedpublicaccoun- tantcertificationorthecertifiedinfor-mation systems auditor certification (seeTable1).
ProcedureandTask
Our experimental task consisted of a series of three unstructured, open-endedcasesthatwehaddeveloped(see AppendixA). Time limits for working each case were established for all par-ticipants as follows: 15 min for each individualcaseand20minforthegroup case. During the semester, undergrad- uatestudentswereabletofinishsimilar cases in 15–20 min (when working in groups).Priorresearchhasfoundmixed resultswithrespecttotheeffectoftime constraints on performance. Therefore, we cannot rule out the possibility that the time constraint may have affected ourresults.
We assembled a master panel to developanswerstoourcases.Thispanel comprisedhighlyexperiencedindividu-als: an independent IT consultant with morethan32yearsofprofessionalexpe-rienceinretail,energy,andtechnology; an IT auditor from a Big-Four public accountingfirmwithmorethan18years of professional auditing experience; and a systems implementation expert,
whose more than 7 years of employ-ment with an independent risk consult-ing firm included an extensive range of IT experience in various industries andareasofpractice.Weinstructedour panelmemberstorespondtothefollow-ing questions listed inAppendixA for allthreecases:
1.Summarize the situation confronted bytheclient(company).
2.Indicate your solution to the prob- lem.
3.Indicateotherinformationyouwould requesttojustifyyoursolution. The initial agreement among our panel members was better than 80%. Weadjustedthecasematerialsandcon-tinueddiscussionswithpanelmembers until a final consensus on the answers wasreached(seeAppendixB).
Two independent coders who were graduate research assistants coded responses to Question 3. These coders wereneitherawareofthehypothesesnor providedwithanydemographicinforma-tion about the participants. The coders hadhighagreement(≥ 74%).Wheredis-crepanciesoccurred,thecodersdiscussed these and reached 100% agreement. A thirdindependentcoderalsogradedthe participants’ answers for the question againstthecompositeanswersdeveloped by the master panel. No partial credit was given, although the wording of the
requested information did not have to be exact (e.g., a participant’s response “indicate location and customer bases of each store” was considered a match to the master panel’s response “collect demographicsofeachstore”).Appendix Bshowssomeexamplesofmatchedand notmatchedresponses.
DependentVariables
The dependent variables were relat-ed to the participants’ responses to the third question for the video case. We counted the number of information itemsrequested(rawvideoinfo)totest H1.Theitemsofinformationrequested were graded against the response from ourmasterpanel(gradedvideoinfo)to testH2andH3.
IndependentVariables
TheindependentvariableforH1and H2 was months of experience (novice vs. experienced). Type of group inter-action (ad hoc vs. established type of group [GRP]) was used with experi-ence (novice vs. experienced partici-pants [EXPGRP]) to testH3 (factor: EXP×GRP).Thegroupswereformed on the basis of a quick survey that asked for their names and the num-berofyearsofITexperiencethatthey had. We then formed groups based on experience levels. These quick surveys
were administered to the professionals astheyenteredthemeetingareaandto the students during the semester. The established groups were either (a) stu-dents who worked in the same group fortheentiresemesterandwhohadIT experienceor(b)professionalswhohad worked together on their work teams prior to this study. The ad hoc groups wereformedrandomly,andthestudents and professionals in these groups had neverworkedtogetherbefore.
As shown in Tables 1 and 2, the Experience×Groupinteractiongroups werethefollowing:
Adhocnovicegroups(n=19).These weregraduatestudents(17)andISACA members (2) with no professional experience in systems. They had not worked together in groups prior to the experiment. They completed a sample case individually as practice (hospital case),thenacase(aeronauticscase)in groupsof3–5,andfinallyacase(video case) individually. Steiner (1972) indi-catedthatwithadiscretionarytask(i.e., one in which members can solve the problem however they desire and with no specific requirements to take into account as to which members’ conclu-sions are preferred), group size is not related to the ability of the group to beproductive.However,processlosses increasewithincreasesinthesizeofthe group.Withadifficulttask,productivity TABLE1.DescriptiveStatisticsofParticipants
Adhoc Established
Variable Fullsample Novice Experienced Novice Experienced
Gender n=92 n=19 n=28 n=28 n=17
Male 52 6 20 11 15
Female 40 13 8 17 2
Major(reported) n=91 n=19 n=28 n=27 n=17
Accounting 41 14 15 7 5
MIS 8 1 4 2 1
Accounting/MIS 4 2 1 1 0
Othera 38 2 8 17 11
Certification(reported) n=91 n=3 n=27b n=28 n=17
CPA 10 0 8 0 2
CISA 16 0 16 0 0
Otherc 18 0 15 1 2
None/notreportedd 59 19 0 27 13
Note .Onlyoneoftheestablishednoviceshadacertification.Forthetwoexperiencedgroups,thiscategoryindicatesthosewhodidnothavethecerti-ficationslistedatthetimeoftheexperiment.
aOthermajor(e.g.,computerscience,finance,generalbusiness).bTwelveoftheadhocexperiencedparticipantshadmorethanonecertification.cOther certification(e.g.,CISSP,software-specificcertification).dNone/notreported:Theadhocnoviceswerenotaskedaboutcertifications.
isafunctionofgroupsizeuptoapoint. Butonceacertaingroupsizeisreached, thereareneitherproductivitygainsnor achangeintheprobabilitythatatleast one person in the group can solve the problem.Onthebasisofourexperience with work groups and student groups, we tried to keep group membership to 4 individuals per group to maximize efficiency given the nature of the task andthetimelimitations.Becauseofour
Adhocexperiencedgroups(n=28). Of the participants in ad hoc groups that included members with IT experi-ence,21wereISACAchaptermembers (M professional experience = 171.43 months).Also,7weregraduatestudents with MIS experience (M MIS expe-rience = 64.29 months) who had not worked in groups prior to the experi-ment. These participants followed the sameexperimentalproceduresasthose oftheadhocnovices.
Establishednovicegroups(n=28). The 28 novices in established groups were graduate students who had worked on cases similar to those in the experiment throughout a semes-ter.Thesestudentsworkedthehospital andaeronauticscasesindividuallyafter completing the video case. Analysis ofvariance(ANOVA)determinedthat there were no order effects (i.e., the order of completion of the cases was
not significantly associated with the dependentvariables).
The groups were established at the beginningofthesemesteronthebasisof randomassignmentwithoutregardtothe resourcesofeachgroupmember.Mem-bers worked 14 similar unstructured, open-endedcasesduringthesemesterin theirgroups.Thevideocasewasthefirst casethattheyworkedonindividually.
Established experienced groups (n = 17).Of the established experienced groups’ participants (M professional experience = 119.14 months), 7 were membersofaregionalinformationsys-tems design and implementation firm who had worked in teams prior to the experiment.Aftertheexperiment,feed-back from these participants indicated that the cases in the experiment were very similar to situations that their teamsregularlyfacedwhendeveloping newsystemsforclients.
The 7 members of these groups workedthethreeexperimentalcasesin thesameorderasdidtheadhocgroups. Theother10participantsweregraduate students (M professional experience = 39.10 months) who had IT experience and had worked in established student groupsoverasemester.
RESULTS
H1andH2
Because of the two dependent vari-ables(rawvideoinfoandgradedvideo info)we used a multiple analysis of
variance(MANOVA)totestH1andH2. RegressionwasalsousedtoanalyzeH2. Inthesetests,experiencewasusedasa continuousvariable(covariate)andnot asagroupingvariable.
AsshowninTable3,theMANOVA resultssuggestthattherawnumberof items requested (H1) did not differ as a function of the number of months of experience (p= .62). However, there were significant differences in thegradedinformationrequested(H2) with months of experience (p= .00). Theresultsofaregressiononthegrad-ed video info (see Table 4) indicatTheresultsofaregressiononthegrad-ed that with more professional experi-ence, the graded information-request- edscorewashigher;thatis,thepartic-ipants’requestsmorecloselymatched those of the master panel. Although we expected to find that higher lev-els of professional experience were associatedwithfewerrawinformation requests,wefoundnosupportforthat hypothesis (H1). However, there was support forH2 (higher levels of pro-fessional experience associated with higherinformation-requestedscores).
H3
To testH3, we performed a priori contrasts on the one-way ANOVA. Participants were placed into one of fourgroupsthatwedescribedearlier: ad hoc novice, ad hoc experienced, establishednovice,establishedexperi-enced(fixedfactor:EXP×GRP).The ANOVAresultswiththegradedscore TABLE2.DescriptiveStatisticsofInformationRequested
Adhoc Established
Fullsample Novice Experienced Novice Experienced
(n=92) (n=19) (n=28) (n=28) (n=17)
Variable M SD M SD M SD M SD M SD
Rawvideoinfo 2.33 1.61 2.21 1.75 2.18 1.61 2.32 1.25 2.76 2.02 Gradedvideoinfo 0.64 0.86 0.21 0.42 0.79 0.99 0.82 0.67 0.59 1.12 Monthsexperience 57.35 88.19 0.00 0.00 144.64 105.33 0.04 0.19a 72.06 47.94
Note.Rawvideoinfo=numberofpiecesofinformationrequested;gradedvideoinfo=numberofpiecesofinformationrequestedthatmatchthecase answers;adhocnovice=participantswithnoprofessionalexperiencewhointeractedinadhocgroupsformedsolelytoperformtheexperiment;adhoc experienced=participantswithprofessionalexperiencewhointeractedinadhocgroupsformedsolelytoperformtheexperiment;establishednovice= participantswithnoprofessionalexperiencewhointeractedinestablishedgroupsforatleast4monthspriortotheexperiment;establishedexperienced= participantswithprofessionalexperiencewhointeractedinestablishedgroupsforatleast4monthspriortotheexperiment.
aOnestudenthadcompleteda1-semesterinternship.
as the dependent variable showed a significantassociationbetweengraded information scores and the combina-tionofexperience(p≤.00)andgroup (p≤.02),showingsupportforH3(see Table5).Whenwecontrastedthetwo ad hoc groups with the two estab-lished groups, the estabestab-lished groups were no different from the ad hoc groups(p<.26;resultsnotshownin Table5).Wesuspectthatthisfinding wasduetothefactthattheregression resultsshowedthatprofessionalexpe-rience and the graded information- requestedscoreswerepositivelyrelat- ed.Weexpectthetypeofgroupinter-action (where 0 = established group and1=adhocgroup)tobeinversely related to graded information scores. Consequently,wesuggestthatcertain combinations of the type of group interaction and the experience level affectthegradedscore.
Toinvestigatethisfurther,wecom-pared the two novice groups (ad hoc vs. established—Contrast 1) and the established novice group to each of thetwoexperiencedgroups(adhoc— Contrast 2; established—Contrast 3). As shown in Table 6, there were no significant differences between the established novice group’s grad-ed information-requestgrad-ed score and those of the two experienced groups (Contrasts2and3).Furthermore,the established novice group had signifi-cantly higher (p< .02) graded video infoscoresthandidtheadhocnovice group(Contrast1).Theseresultssup-portH3 for the novices but not for experiencedprofessionals.
DISCUSSION
Working with established groups could help novices to learn the infor-mation-gathering techniques of more experiencedprofessionals.Thismethod could enable educators and trainers to betterpreparestudentstotacklethechal-lengesofunstructureddecisionmaking by enhancing critical-thinking skills in working through these cases over a period of time while in the protected environment of the classroom.Also, it mightbehelpfultoassignnewhiresto a stable group situation in a protected training environment to learn the
pro-cess of information gathering to aid in thedevelopmentofsolutions.Wehope that this type of practice would make suchnewgraduatesandnewprofession-als more valuable to their employers morequickly.
As expected, we found that greater professional experience was associated
withhigherinformation-gatheringscores. However,wealsoanalyzedtheinteraction of experience level (novice vs. experi-enced) with group interaction type (ad hoc vs. established) and found that nov-iceswhointeractedforatleast4months with their established groups that were workingonsimilarcasesdidnotdifferin TABLE3.MultipleAnalysisofVarianceResultsforTestsofHypothesis1 andHypothesis2
Dependent Sumof
Source variable errors df M F p
Correctedmodel Rawvideo 0.64 1 0.64 0.24 .62 Gradedvideo 7.95 1 7.95 12.08 .00 Intercept Rawvideo 368.62 1 368.62 140.63 .00 Gradedvideo 13.00 1 13.00 19.76 .00 Experience Rawvideo 0.64 1 0.64 0.24 .62 Gradedvideo 7.95 1 7.95 12.08 .00 Error Rawvideoinfo 235.91 90 2.62 Gradedvideo 59.22 90 0.66 Total Rawvideoinfo 739.00 92 Gradedvideo 105.00 92 Correctedtotal Rawvideo 236.55 91 Gradedvideo 67.16 91
Note.Rawvideo=numberofpiecesofinformationrequested;gradedvideo=numberofpieces ofinformationrequestedthatmatchthecaseanswers;experience=numberofmonthsofprofes-sionalITexperience.
TABLE4.RegressionResultsforTestsofHypothesis2
Unstandardizedcoefficients Standardizedcoefficients
Variable B SE β t p
Constant 2.392 .202 — 11.859 .000 Experience –0.001 .002 –.052 –0.495 .622
Note.Dependentvariable=gradedinformationrequested;independentvariable=experience (numberofmonthsofprofessionalITexperience).
TABLE5.AnalysisofVarianceResultsforTestsofHypothesis3
Source Sumoferrors df M F p
Correctedmodel 11.64 2 5.82 9.33 .00 Intercept 10.36 1 10.36 16.61 .00 Experience 10.89 1 10.89 17.46 .00
GRP 3.69 1 3.69 5.92 .02
Error 55.52 89 0.62
Total 105.00 92
Correctedtotal 67.16 91
Note.Dependentvariable=gradedvideoinfo(numberofpiecesofinformationrequestedthat matchthecaseanswers);independentvariables=experience(numberofmonthsofprofessional ITexperience)andGRP(typeofgroupinteraction[adhoc=1,established=0]).
their information-requested scores from eitheroftheexperiencedgroups(adhoc vs. established). Furthermore, the nov-ices in established groups outperformed the novices in ad hoc groups. Research-ers of transactive knowledge have dem-onstrated this superior performance by novices in established groups (e.g., Hol-lingshead,2000;Lewis,Lange,&Gillis, 2005; Liang, Morland, &Argote, 1995; Wegner, 1986, 1995; Wegner, Erber, & Raymond,1991).Transactiveknowledge isenhancedbytheknowledgeoftheindi-vidual members and an understanding of who knows what within the team’s informationbase.Researchershavecom-paredthesememorysystemstocomputer networks(Wegner,1995)andfoundevi-denceforthesesystemsinstudents(Liang et al.), personal relationships (Wegner et al., 1991), top management teams (Rau, 2006), and organizational groups (Bran- don&Hollingshead,2004).Inthepres-ent research, we showed that a similar system can be developed even in estab-lished groups consisting of individuals with no experience in solving complex andunstructuredITcases,reinforcingthe
importanceofusingrealisticcasesinthe classroomandprofessionaltraining.
Contrary to our expectations, we did not find a decrease in the raw number of information requests with more experience.We suspect that this result might be because our novices in established groups acted more like the expert-like novices described by Stevens et al. (1996), as indicated by thenovicesinestablishedgroupshav-results of a quasi-experiment beyond similar types of individuals and tasks islimited(Shadish,Cook,&Campbell, 2002).Althoughincludingprofessionals added richness to the present sample, wewererequiredtoperformtheexperi-mentinlocationsoutsidethelaboratory environment.Inaddition,thecodingof written protocol is labor-intensive and maynotbetotallyobjective.
The time limitations set for response tothecasesconstrainedtheabilityofthe participants to generate ideas other than thosethatcameimmediatelytomind,and thisconstraintmayhavehadaneffecton theabilityofparticipantstofullydevelop their recommendations or to access their entire knowledge base.An informal sur-veyofsomeparticipantsrevealedthatthey did not feel rushed but, in fact, focused morequicklyondevelopingtheirrespons-esbecausetheyknewtheyhadalimited amountoftime.Futureresearchersmight address the issues of the time limitation andhowitaffectsagroup’sinteraction.
Wedidnotstudytheprocessofgroup interaction or the process of transac-tive memory (e.g., seeing if the groups identified the expertise of the group members; observing the allocation of information or tasks among the group members).Becauseofthesmallnumbers ofrequestedinformationitemsineachof thegroups,wecouldnotperformstatisti-calanalysissuchaschi-squaretoreview patternsofinformationgatheringamong the different experience levels. Future researcherscouldfurtherinvestigatehow groups communicate and gather infor-mation, how they come to agreement, and whether all members participate to enhancetheirlearning.(Forareviewof group-processing research since 1989, see Kerr & Tindale, 2004. For exam-ples of such experiments, see Hollings-head, 2001; Laughlin, Zander, Knievel, & Tan, 2003; Marxen, 1990; Watson, Michaelsen,&Sharp,1991.)
NOTES
ConstanceM.Lehmann,PhD,isanassociate professor of accounting and teaches IT auditing, accounting information systems, and financial accounting.
CynthiaD.Heagy,DBA,CPA,isaprofessor ofaccountingandteachesaccountinginformation systemsandmanagerialaccounting.
Correspondence concerning this article should beaddressedtoCynthiaD.Heagy,Universityof examination of the effects of experience and task complexity on audit judgments. Account-ingReview,62(1),1–13.
Beane, W. E., & Lemke, E. A. (1971). Group variablesinfluencingthetransferofconceptual behavior.Journal of Educational Psychology, 62,215–218.
TABLE6.ContrastResultsforTestsofHypothesis3
Adhoc Established
Contrast Novice Experienced Novice Experienced
1 1 0 –1 0
2 0 1 –1 0
3 0 0 1 –1
Contrastresults
Valueof
Gradedvideoinfo Contrast contrast SE t df p
Assumeequal
variances 1 –0.61 .26 –2.45 88 .02
2 0.00 .22 –0.16 88 .87
3 0.23 .26 0.90 88 .37
Notassume
equalvariances 1 –0.61 .16 –3.85 45 .00
2 0.00 .23 –0.16 47 .88
3 0.22 .30 0.78 23 .45
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attheannualmeetingoftheAmericanEduca-Some problems had to be overcome. Polk Memorial Children’s Hospital and the 20–30 largest vendors already had the necessary computerhardwareresourcestoimplementtheEDIsystemandprovencommercialsoftwarewasavailableforimmediateinstallation.But
APPENDIXA(cont.)
EDIhasbeensuccessfullyimplemented,allowingPaperMoontoexpanditscustomerbasetoincludeBowingCorporationandLock-weedMartianAerospace.BothfirmsarelargeaerospacecontractorswhocertifyhardwareforNASA’sspacestationandspaceshuttle programs.BecauseofPaperMoon’sexpertiseinthedevelopmentandmanufactureoflabequipment,otherinternationalpartnersinthe spacestationhaveexpressedinterestinworkingwithPaperMoontodevelopresearchtoolsforuseonthespacestation.
Asaresultofthecompany’sgrowth,PaperMoondesperatelyneedsanewaccountingsystem.Ratherthanpaythehighcostofhiring anoutsideconsultantorconsultingfirm,theCEOhasaskedyoutomakerecommendationstoexecutivemanagementforanewsystem. Thegoalofthesystemistoreducethelabor-intensiveactivitiessuchasmanuallyprintingcheckstopayvendors,manuallyprinting invoicestocustomers,keepingtrackofemployeebenefits,taxes,etc.TheCEOrequeststhatabudgetforthenewsystembeapartof yourrecommendations.
BayAreaVideoCase
AndreaClarkfoundedBayAreaVideoseveralyearsago.Thesinglestoreprosperedandshenowownsthreelocalstores.Eachhasa full-timemanagerwhohiresstudentsandotherstoworkonapart-timebasis.EveryweekAndreaforwardsadvancenoticesofforthcom-ingvideostoeachstoremanager.StoremanagerssubmitpurchaserequeststoAndrea,whoconsolidatesthemandplacestheorders.As managersperceivethedesirabilityofaddingtotheexistinginventoryofparticularlypopularfilms,theseareaddedtotheweeklypurchase requestsandAndreaplacesaconsolidatedpurchaseorder.Whenstoremanagersnoticethatfilmsarenolongerbeingrented,thosefilms areplacedonsale.
Whenherfirststoreopened,Andreaselectedacertifiedpublicaccountant(CPA)tomaintainheraccountingrecordsandhandleall payrollandbillpaying.ShegetsamonthlyincomestatementfromtheCPAaroundthe10thofeachmonththatshowstotalsalesbroken downbytypeandadetailedbalancesheet.AlthoughthesereportsareusefultogaugeherprogressandAndreahasnocriticismofthe accountingreports,shehasafeelingthatsheisunabletomonitorindividualstoreoperationsascloselyaswaspossiblewhenshehad onlyone.Also,storemanagersarehavingdifficultymonitoringtheirinventory.
APPENDIXB
ExamplesofMatchedandNotMatchedResponsestotheCaseQuestionPortionofthe GradingSheetUsedtoRecordMatchedResponsestoCaseQuestion3
Question3:Additionalinformationandtestingyouwouldrequest(checkallthatapply)
• Demographicsofeachstore(toreviewdemanddrivenbydemographics). _____________
• Datacurrentlybeingcaptured. _____________
• Currentaccountingsoftware’sreportingcapabilities. _____________
• Controlscurrentlyinplace. _____________
• Detailsofinformationthatneedstobecapturedateachstore. _____________
• Timingofrequiredreports. _____________
• Reviewofpastdecisionstoseeifthey’dchangewithup-to-dateinformation. _____________ • Exploretechnologyalternatives,includingpoint-of-saleorothermethods,tocollectandreportnecessary
informationtotherightpeople. _____________
Totaladditionalinformationitemsrequested _____________
Examplesofresponsesthatdidnotmatchthemasterpanel’sresponses
“Lotsoftraininginformation”
“Trackpayrollandhoursforeachstoreemployee” “Howmuchwouldthesoftwarecost?”
“Cost/benefitofkeepingtheCPA” “Istheownerwantingtosellthebusiness?” “Fulldescriptionofentiretransaction/businessflow” “Estimateofshrinkageloss”
“Howtotrackinventorytheft/unreturnedvideos”
