The Effects of Modes of InformationPresentation on Decision-Makins :A Review and Meta-Analysis

A. R. MONTAZEMI and S. WANC

Ar-r R. Moxrnzeur is Assistant Professor of Infbrmation Systems at McMasterUniversiry. He received his M.Sc. in Management Science from University otSouthampton, England, and his Ph.D. from the University of Waterloo, Canada. Hisresearch interests include information requirements anaiysis, decision theory, andthe design of decision support systems. His papers on these topics have beenpublished in MIS Quarterlv, IEEE Transaction on rVan, S.ystems and Cybernetics,Journal of Operational Research Sociery, and INFOR. He is a member of ACM.CORS. DSI. and TIMS.

Suounoxc We,xc is a doctoral candidate in the Faculty of Business at McMasterUniversiry. His work experience includes manager of production at Hangdang Ironand Steel Co., and MIS lecrurer at the Tsinghua University, Beij ing, China. lvtr.Wang's research interests include modes of information presentation and informa-tion requirements analysis.

ABsrRAcr: This study investigates the impact of modes of intormation presentationon information dimensions. Twenty-four published studies were reviewed. Theresults of sixteen of these were cumulated by application of meta-analysis technique.The ensuing results demonstrate that the bar presentation format is slightly betterthan the tabular one in terms of intormation precision; however. the tace chart issuperior to the tabular format with respect to relevancy, and the multicolor presenta-tion is more relevant than the monocolor. In addition, two tactors of intluence(moderators) were venfied. First, personalitv, which is classified as t ' ieid-dependentand field-independent. acts as a moderator between color and intbrmation relevancv.Second, when comparing l ine graphical presentations with tabular. task environmenthas a moderate effect on both timesaving and precision.

KEy woRDs AND pHRAsES: lntbrmat ion media, graphics in informat i t ln svstems.

This research has been supported by a grant from the Natural Sciences and EngrneertnqCouncil of Canada.

102 A . R . MoNTAZEMT AND s . wANc

1. Introduction

R E c r N T L y , T H E R E H A s B E E N A N u p s u R c E o f i n t e r e s t i n t h e e f f e c t i v e n e s s o f

information presentation modes, and although the purpose of this type of research is

varied I l], the underlying philosophy remains the same. The major thrust is to

answer the question of how different modes of presenting information (i.e.. in

graphic, tabular, or textual form) can influence human behavior in terms of the

reception of information, its processing, and reaction to a decision environment.

Despite the presence of an extensive number of studies dealing with graphical and

other visual displays, the cognitive effects of different modes of presentation on the

process of decision-making are sti l l uncertain. Although DeSanctis [11] offered a

detailed descriptive comparison and a summary of the previous research, her review

is nonquantitative and fails to integrate statistically the results of individual research

efforts. A technique that allows the results of studies to be integrated statistically is

termed under the rubric of "meta-analysis. " In this article, it wil l be seen that this

type of analysis can correct disparit ies which arise from isolated investigations of

individual experiments and can reconcile conflicting outcomes of separate studies.

Thus. the meta-analysis technique is a fruitful tool that allows the pooling and the

cumulation of the results of previous experiments.

The purpose of this study is to survey the previous research. Our contention is that

our conclusion wil l be more substantive than previous ones. The article proceeds as

follows: Section 2 provides a general review of current research; unconventionally,

the review is a prelude to the meta-analysis method. Section 3 explains the meta-

analysis procedure as it relates to the intormation presentation issue. Section -1

provides the results of the analysis. Finally, the t-indings are discussed in section 5.

2. Presentation Modes of Information and Information Dimensions

2.1 . Relevant Research

Although it is recognized that well-designed modes of presentation enhance infor-

mation et-fectiveness by capturing the interest of the reader, by providing a clear and

economical message, and by stimulating analytical thought [33], l i tt le is known

about the actual uti l i ty of the different modes [11].The first thoughtful investigations of differing presentation formats were con-

ducted in the early 1900s. Washburne [39] asserted that different tormats were

preferable under different circumstances insothr as they related to the task. Since the

1960s, graphical presentations have become an inherent part of managerial decision-

making, mainly because of the development of computer-generated graphics. This

development in turn resulted in many new experiments that examined the effects of

information presentation. Yet. despite the large volume of research. no consensus

E F F E C T S O F I N F O R M A T I O N P R E S E N T A T I O N r03

about the uti l i ty and the impact of specific formats on decision-makins was obtained.

As a case in point. some studies, such as Zmud [-121, claimed that graphs were

preferred by managers. However, other studies. such as the one of Lucas 121.22),provided litt le support for these f,rndings. Sti l l others (e.9., Remus t29l) su*qgested

that, in some cases, the graph performed more poorly than the traditional tabular

presenrarion. DeSanctis [ 1], in a summary of twenty studies (with highly cont' l ict-

ing results) showed that the graphical mode was not necessarily more ef'fective than

the tabular in communicating information.

Further studies on graphical and tabular presentation modes wil l be conducted

and discussed in this paper. The objective is to attain more extensive and def-rnit ive

conclusions. However. to combine the previous studies into a cohesive analytical

framework, the various independent and dependent variables of the experiments wii l

be standardized.

2.2. The Independent Variables (Presentation lVlodes)

Identifying the independent variables of past experiments is simple. The two presen-

ution modes (or categories) are format and color. Obviously, when the eft'ect of

color is being studied. the format should be kept constant ["], 5, 6. l '2.31].Vlanv

different formats exist, the main classifications being tev, tabular. and graphicul.

The graphical can be further subdivided into the tollowing types. each havinq its

own advantages and disadvantages.

The most fami l iar graphicai format is that of the l ine 13, 4, 5 .7 , 12.2?.29, 391

This particular format presents the trend of data very well, especially in terms of

change rate, but the l ine is incapable of precisely identif ing the absolute value of each

point. Scatter plots, another graph tbrmat, have characteristics simiiar to those of

l ine plots [51. In addition, the bar format is very popuiar and particularly useful tor

comparing the magnitude of c lustered var iables [0, 12, 13. 14. 23, 37. 38. 39]. The

pie format [0, l4] l ike the bar tormat, is int'erior to the l ine format in capturine the

change rate of data. The unimated grtphics tormat, used most commoniv in the

f ie lds of educat ion and advert is ing [ l8. 30, 391, gives the reader a pictor ia l image;

and the recent development of rhe face tormat makes it possible to present tarrly

complex relations of multivariate data through the alteration of the emotions and

appearance of the faces t8,25, 351. However, th is technique requires great ski i l on

the part of the designer and user. Finally, the rhree-dirnensional tormat provides an

additional dimension of display through the use of a stereoscopic imaue []01 ()r the

plot of a three-dimensional perspective in a plane [ '101.

2.3. The Dependent Var iables ( Informat ion Dimensions)

Intormat ion c l imensions are those intormat ion at t r ibutes which contr tbute to deci-

s ion-making. To determine which intbrmat ion dimensions are at tected bv chances

l 04 A . R . MoNTAzEMI AND s . wANc

in the presentation modes. a two-stage procedure was conducted. First. a l ist of

factors for measuring information system satisfaction was extracted from the gener-

al l i terature. Next, a subset from this l ist was compiled by checking the measurement

factors against the "dependent variables" used in previous research. The purpose of

this procedure was not to adhere to specific terminology, but rather to explore the

nature of information dimensions and to avoid ambiguity. The tinal set of informa-

tion dimensions (or dependent variables) derived is discussed below.

Timesaving II9J:The time-effectiveness of decision-making when using the sysrem.

Timesaving is one of the most relevant dependent measures [1[, 19]. Usually, t ime

spent to solve the problem is the measured criterion [7,20, 38].

Precision (understandabilin) []J: The rariabiliry of the output informationfrom thot

which it purports to measure.

When measuring precision, the user is asked simple questions related to the interpre-

tation of information presented in a particular mode. The number of correct an-

swers, or the degree of departure from these, was used to judge if the presentation

allowed presentation of the true meaning.

Relevancy (usefulness) [ I ]: The degree of congruence between what the user wants or

requires and what is provided by the information products and services.

Unlike timesaving and precision. relevancy relates to decision quality. There are

three means to measure this. First, the absolute value of a management index (i.e.,

profit [21], cost [22,29| or forecasting accuracy [12]) can be used as the criterion

for a particular decision performance. Second, as considered by Benbasat et al. [3,

4, 5, 61, a normalized measure of the management index can be used. One example

is: [6]

(...,:':",i,",,, ) ( " . : : :: : , , , ' )

Decision quality :

/ Optimal

\

\ o. . i r ion , . rutrr , /( " : . : : :

: - : , , ' )

Third, the appropriateness of ajudgment [25, 35] can be used

tangible management index.

complex comparison [39] or of a management

to measure decision quality in the absence of a

EFFECTS OF INFOR} {AT ION PRESENTATION I05

Psvchological growrh [32J: The improv€ment of the users' cognirive Juncrittrt.

The latter includes two aspects as tollows:

Recall [a\J: The abiliry rc retieve the inforrnatiott supplierl by rhe informarion

system at an earlier time.

When examining recall abil ity, the user is exposed to a presentation for several

seconds. [:ter the user is asked to recall the information content of the presentation.

The interval between the presentation and the recall can be several seconds. several

hours, or even several weeks. The amount of information correctly remembered is

used to measure the recall abil ity.

Learning [21J: The rate of increase in perJormance.

When a user repears the same task over a period of t ime. generaily speaking' the

latter performances are better than the earlier ones. The improvement rate between

two performances is the criterion for measuring learning abil ity.

2.4. The Moderators

The relationship between the independent and dependent variables l isted above can

be detined as a probabil istic function, where g - fk): here,r represents the informa-

tion presentation morJe and y stands tor the intormation dimension. Horvever. as

mentioned earlier, inconsistent conclusions are apparent concerning presentetlon

effects. That is, the same presentation mode may produce different effects on the

same user's pertormance. Some researchers [3 , 12. ?2. 23] propose that there exist

certain iactors of intluence on the relationship between intbrmation presentatlon

modes and dimensions. tn other words, the probabil istic function should be

g = fl;y,) instead of g : f(.r), where : denotes variables other than presentation

modes. By det-init ion, these factors are known as moderator variables. this is be-

cause these factors moderate or alter the magnitude of a relationship betrveen two

orher var iables (see [31], p. l3) . In th is paper. : wi l l be det lned as a moderator

between presentation modes and intormation dimensions.

The moderator t jeterminarion procedure consists of three stases. First. ptltential

moderators are identif ied; second. the etfects of these potential moderators lrre

examined in independent experiments: and tlnally, i. l svstematic cumuiative anaiysts

of individual experiments is pertormed to verity the e.ristence of the moderator(s).

2.4.1. Potent ia l Nloderators

potential moderators originate from vanous sources. In I proptlsal tbr rcsearch tln

intormation systems. Mason and iv{itrofT [:1] stated that:

106 A . R . } I O N T A Z E M I A N D S . W A N G

An information system consists of. at least, one PERSON of a certain

PSYCHOLOGICAL TYPE who thces a PROBLEM within some OR-

GANIZATIONAL CONTEXT for which he needs EVIDENCE to arrive

at a solution where the evidence is made available through some MODE

OF PRESENTATION. (p. a75)

This statement indicates that an individual's psychological type, the characteris-

tics of the problem, or the organizational context may moderate between informa-

tion dimensions and presentation modes. lndeed, Lucas [22], Lusk and Kersnick

[23], and Benbasat and Dexter [3], suggested that the cognitive style (decision style

or personality type) can be a moderator. In addition, Dickson et al. [2] proposed

that task environment. which includes task content, task complexity, and degree

of task structure, may at'fect the impact of information presentation. Other po-

tential moderators may be established by examining the managerial environ-

ment. For example, Benbasat et al. [4], when observing managerial activity

and deciiion-making behavior, suggested that time constraint may be a mod-

erator.When defining moderators, measuring the moderator level is a major problem.

For some proposed moderators, unfortunately there is no agreement either on

definit ions or on what methodologies should be used to operationalize their levels.

The only way to quantify these kinds of moderators is through careful analysis and

by adhering to a consistent rule. For example, the level of task environment could be

established according to the number of variables processed at any one time to reach a

decision, the degree of knowledge required for the decision, and whether or not a

step-by-step procedure can be employed [I2].

2.4.2. Test of Potential Moderators in lndependent Experiments

Potentiai moderators may be tested by experiments that establish their statistical

s igni f icance [3, 4,5,12,22,23]. The at tached Appendix shows the ef fects of several

potential moderators identif ied from previous research. One example is the experi-

ment by Dickson et al. [12] which indicated that, in terms of relevancy of informa-

tion, no significant difference exists between the tabular and the graphical presenta-

tion when a simple, structured task is pertbrmed: however, the latter is better than

the tbrmer under a medium-complex task environment.

2.4.3. Cumulative Analysis of the Moderororc

A single experiment, howevet is insufficient to establish the e.\istence of a modera-

tor variable [l7]. If two or more experiments involve the same moderator. though,

their results may be cumulated to obtain a more definite conclusion. Betbre this

cumulative analysis of moderators is performed. the relationship between indepen-

dent and dependent variables must be investigated.

EFFECTS OF INFORIV1ATION PRESENT. \T ION

2.5. Reviewed Studies Summarized

r07

Twenty-four experimental (and quasi-experimental) studies were reviewed. A syn-

opsis of the relationship among presentation modes, intormation dimensions. and

moderators, is shown in Appendix. The independent and dependent variables were

categorized as discussed, and the adopted moderators used in the corresponding

studies. Experiments were also classified by task complexiry: this classification was

according to the recommendations made by Dickson et ai. [12].

The summanzed results reveai severai important facts. First. the topics of infor-

mation presentation et'fects are diversif ied. Consequently, the intersection of sets of

comparable research results is small. Second. two approaches can be used to evaiu-

ate the impact of presentation modes: the subjective evaiuation method (e.g.. [3.

42)), which involves measuring the information user's perception or t 'eeiins oi the

presentar ion value; and the object ive approach (e.g. , [3, .12]) , which involves f - re ld

experiments and management games (here the subject's performance is the mea-

sured criterion). Third. few consistent conclusions can be drawn with regard to the

effects of presentarion modes on intormation dimensions, although it does appear

that the multicolor presentation is always superior or at least.equivalent to the

monocolor mode. Finally, most of the studies supplied their own statistical data.

such as t-value, F-ratio, chi-square, etc.

Given these facts. it was necessary to cumulate the t ' indings of individuai studies

to obtain more substantial results. This was achieved through the appiication tlf

meta-analysis.

3. Meta-analysis

lNcoNSrsrENT RESULTS about the re la t ionsh ip be tween presenta t ion modes and

intbrmation dimensions makes the integration of research tlndings imperative.

Severai methods of achieving this integration are available. One is the narrattve

review method, which a.l lows broad, qualitative judgments I I I ]. However. this

method is nonquantitative and does not lend itself to statistical analysis. Although

many statistical integration methods exist [2], the meta-analysis method tormulated

by Hunter et a i . t17,341 provides the "state-ot- the-art" method, and thus was

selected fbr use here. This section wil l explain brietly the procedure and the pnmarv

properties of the meta-analysis method as required tor our purpose here.

3.1. Cr i t i ca l Prob lems

Betore proceeding with rhe discussion of the meta-analysis method. iactors that

cause spurious variation of results across studies must be isolated. One such t 'actor

consists of the art i tacts pecul iar to stat ist ics, which include sampl ing error. measure-

ment unrel iabi l i ty . d i f ferences in t reatment strensth across studies. computat ionai

r08 A . R . M O N T A Z E M I A N D S . W A N G

error, reporting error, etc. Another factor that can create inconsistency in results is

the effect of real moderators (see section 2.4). Therefore, to obtain consistent

conclusions based on the results of various studies, artifacts must be corrected and,

if there is "substantial" variance among correlated measures of association. then a

search for moderators is pursued.

3.2. Correction for Errors

3.2 .1 . Dpes o f Er ro rs

The different types of errors present in the reviewed studies are as follows:

I. Computational and rypographical errors.- Computational and typographical

errors are present in published literature and are caused inadvertently by the re-

searcher or his/her assistant. Examples of such errors are the failure to reverse the

sign of a variable when it was reverse-scored, and simple data-entry errors. Such

errors cannot be quantified and eliminated.

II. Measurement unreliabilim.- Variables are never perfectly measured, and since

no measurement reliability coefficients were reported in the reviewed studies, the

error caused by unreliable measurements cannot be corrected. However, the major

reason for the lack of reliability coefficients is that independent variables (i.e.,

presentation modes) are easy to measure and dependent variables (i.e., information

dimensions) are "hard" criterion measures.

ru. Variation in treatment strength across studies.- This type of artifact is best

explained by example. As shown in Figure l, some graphs employ grids when

presenting information (e.9., [7]) while others do not (e.g., [3]). Obviously, how the

same independent variable (i.e., line graph) is treated varies. This difference is

known as variation in treatment strength. Research indicates that this particular

variation is a source of artifact [71. Unfortunately, in the reviewed studies, the

treatment strength is not often reported. Even had this not been so, quantification of

these di f ferences is di f f icul t . Consequent ly, th is art i fact cannot be cor-

rected.

IV. Sampling error.- Sampling error tends to account for the greatest proportion

of variance among reported effect sizes across studies [ 171. At the level of the single

experiment, sampling error is random and thus impossible to correct. However, at

the level of meta-anaiysis, sampling error can be estimated and theretore corrected.

Thus, of the four types of artifacts discussed, oniy the last, sampling error, can be

corrected.

3.2.2 Correction of Sampling Error

Variations caused by sampling errors are corrected in the following way. First" a

basic statistic. called effect size d, is chosen. Effect size d is defined statistically as

1 n

EFFECTS OF INFORIV IATION PRESENTATION r09

5 1 0

A line graph without _end

< 1 nJ L W

A line graph with grid

Figure /. Variation in Treatment Strengrh.

the difference between the means of two experimental groups divided by the rvirhin-group standard deviation, that is

d : O t _ y t ) t ,

where yr and y2 are the means of two experimental groups and s is the within-groupstandard deviation.

Most studies reviewed employed the r-test when comparing the ef-fects of two

Presentat ion modes (e.9. , [12,22,291).Howeve( r-value is int luenced by samplesize. Therefore, in order to correct tbr this. the r-value should be transtormeci inro aneffect size d-value by means of the following fbrmula:

I : 2 ' r I J N .

For example, Dickson et al. [2] experimented with 154 subjecrs, and obtained a r-value of 0.49 when bar graphics were compared with tabular fbrmat in determininsinformation precision: thus the corresponding effect size r/-value is:

d = 2 ' 0 . 4 9 / J 1 5 4 = 0 . 0 7 9 .

Not all of the studies we reviewed provided the data necessary to caiculare rhe effectsize d-value. Thus, in order to cumulate the results of as many studies as possible.some perfect approximate conversion methods were adopted [3 I ]. For instance, ofl€experiment we reviewed was designed to examine the effects of presenration oninformation precision by means of several kinds of independent variables. includinethe use of color [371. The author, Tl.rl l is [37], reported the F-ratio in an ANOVA.However, the overall F-ratio of ANOVA is not sufficient to compure the effect size r/-value. Nevertheless, because the reported overall F-ratio indicared that the coioreffect was not significant and that the relative difference of the means pertormed bythecolor and monocolor t r ia l groups was as smal l as 0.01, i t can be concluded that

t 1 0 A. R . MONTAZEI I1 I AND S . WANG

the effect size d-value. in this case. is approximatelv zero.When calculating d-values, the tbllowing principle was tbllowed. If an experi-

ment employed different subject groups, each trial was considered ro be statisticallyindependent. However if the study was replicated by employing rhe same subjectgroup, the average effect size d-vaIue and the average sample size were used. As aresult. in this study a total of 38 independently observed effect size d-values, whichrepresented the relationship between information dimensions and presentationmodes, were produced.

Using the individual d-value and the sample size for each information dimensionand presentation mode pair, the frequency weighted mean and the variance of effectsize over studies was computed as follows:

(i.) The cumulated averase effect size:

c t = D [ t t i ' d i ] / I N d .

(i i.) The variance of the observed effect sizes over studies:

s 3 = E [ N i ' @ i - A 1 l ! N r .

(i i i .) Next, the variance due to sampling error was calculated as:

4 - ( r + 4 2 t 8 \ . K t N .

Where K represents the number of independent studies and ,V the total sample size.The variance of effect size corrected for sampling error (i.e., the residual vari-

ance) is:

t : t l - s 2 " -

Now, it becomes evident that, unlike the signiflcant level represented by the r-valueof a single experiment. the corrected effect size statistic expresses the actual distri-bution of the relationship between intbrmation dimensions and presentation modesacross observed studies. The 95 percent probabil ity confidence interval is:

a - 1 .96 s5 - d - J + 1 .96 s5

This gives an accurate picture of the degree of uncertainty for effect size d.To il lustrate the appropriateness of using the d-value statistic, we now present an

example where infbrmation precision is seen to vary as a ftrnction of presentationmode under a medium-complex task environment. When the l ine graphics formatwas compared to the tabular. as it was in Dickson et al. [2], the results indicated thatthe tabular format was slightly better than graphics. On the other hand. Lucas's [22]study showed that graphics were significantly superior to tabular presentations.

2s e :

EFFECTS OF INFORI I IAT ION PRESENTATION

Table I Stat is t ical Compar ison of Two Reported Invest isat ions

R e s e a r c h

D i c k s o n 1 9 8 5L u c a s 1 9 8 1

R e s u l c s

G < - T^ \ Tu 2 t

A v e r a g eS r m n l e c i - e N

320/+0

R . e p o r c e d

A v e r a g e C - C e s C

e f f e c c s i : e d S L u , n i f i c r n c e

_ v 4 e l . t v u J l S l r t ! l 9 d r l L

0 . 5 9 5 S i g n i f i c a n c

Table I shows the summarized data for these two studies.

As noted in Table l, the negative effect size d-value signifies that tabuiar data

presenration is superior to the graphical; a positive value indicates that the uraphicai

mode of presentation is superior to the tabuiar. Application of meta-an:rlvsis to thrs

example reveals that:

a - -o . rs3 , 0.070, s2" = 0.022. 0 . 0 4 8 . - 0 . 5 8 s d < 0 . : 3 .

Note that the two single r-test values suggest graphical intormation to be superior to

tabular. However, the cumulative analysis tells a different story. The negative aver-

age effect size d-value indicates that, from a statistical point of view. tabular presen-

tation should be better than linear graphical. The sampiing error is about one third of

the total variance of etfect size. The 95 percent probabil itv confldence interval tbr

ef fect s ize is -0.58 to 0.28, which impl ies that the tabular mode. in th is context . is

l ikely to be more ef-fective than the Iine graphical.

3.3. Detect ion of Moderators

After correct ing for sample error ( i .e. . r3) , i l the resi t iual var iancc oief f -ect s ize is

approximately zero, the population effect size d is estimated. Then a conclusion

about the relationship between the information dimension and the mode can be

drawn. However. if. after correction. the residual variance is not close to zero.

moderators may exist . Thus. a chi-square test to determine the srgni f icent residual

var iance of ef fect s ize is conducted: the fo i lowing tbrmuia is used:

x2vf - & - t ) l = $l t \z) 'K.

where K is the number of independent studies [11 . 2 ' ] ) .

A s igni f icant chi-square value indicates the necessi ty of searching f or moderators.

The search procedure entails breakrng the data into subsets. eech lccordinq to the

level of the potent ia i moderator. For each data group, the anaiyt icai pr<tcedure t i .e. .

correct ing for sampl ing error and pertorming a chi- test) must be repeated. I f larse

differences in the mean et'fect size between subsets or r reduction in variance rvrthin

subsets ( these are not independent events) exist . the ident i t led moderator mav be

u i

2t 6 =.,

S d :

t 1 2 A. R . MONTAZENTI AND S . WANG

confirmed. Otherwise. the existence of a moderator is not supportable. To i l lustratethis method. the effects of the l ine graphical format versus the tabular format oninformation relevancy must be considered. Ten effect size values are calculated. Themean effect size value and other statistics are as follows:

J : 0 . 3 0 8 , 1 3 : 0 . 3 7 5 . s 2 " = 0 . 0 3 4 , s 3 : 0 . 3 + 0 . x ' k t f - 9 ) : 1 0 9 .

The significant chi-square value (p < 0.005) indicates the possible existence of amoderator(s). The eight experiments are then separated into two subsets accordingto their task environment classification. Subset one is characterized by simple task

complexity and subset two characterized by medium to high task complexity. Theeffect size d-values are again calculated, along with the variance for each subset.After correcting for sampling error within each group we obtain:

Subset I2t : 0'462sfr 1 : 0.62

Note that the variance of et-fect size forsample. Hence, there is no support for

moderator.

Subset 2dz : 0 ' 175

' r -sf z : 0.06

subset I is larger than that of the originalthe hypothesis that task environment is a

4 . Resul ts

4.1. Meta-analysis Results

The intersection set of comparable research results is small. This is crucial here

because application of meta-analysis requires employing homogeneous statistical

data. Because of the insutficient data, only l6 of the 24 reported experimental studieswere selected for the meta-analysis. Table 2 shows a summary of the effects of

information presentation formats on various infbrmation dimensions according to

meta-analysis. In addition to the effect sizes for tabular versus specific graphical

formats (such as bar, l ine, and face), the etfect sizes tbr combined graphical versus

tabular format over each information dimension are also l isted. The studies used to

assess the effects of each pair are indicated by reference numbers.For each relationship, several statistics were computed. A positive J-value indi-

cates that, on average, the first (top) presentation mode is superior to the second(bottom) mode, whereas a negative d-value implies just the opposite. For example.when comparing the bar format to the tabular. in terms of information relevancy,

i : 0.336 indicates that the bar format is more effective than the tabular. When sfiis approximately zero. it can be said that the average effect size is the "true" size of

E F F E C T S O F I N F O R M A T I O N P R E S E N T A T I O N I 1 3

Table 2 Ef fect of Presentat ion Format on Intormat ion Dimension

I n f o r m -a c i o n

D i m e n s i o n

T ime

Sav ing

P r e c i s i o n

I d U U I d L

L U . \ L

. - ^ ^ 1 . i ^ ^u L d P t l r u r

T a b u l a r

r 1 1 1 q 1 7 1l r t t t - ) r J t )

a - o . e e qN - 2 5 0

a

o . - 0 . 7 82

a - 0 . 0 8 5

2o . - 0 . 7 0

L i n eV J

t d u u l d L

1 1 7 t It r r ' ) |

a - 0 . 0 5 5 |N - 8 6 I

) r

o . - O . i 4 |o ln l

o - 0 . L 4 |p t

B a r

T a b u l a r

1 ? lJ I T

d - 2 . 4 3 LN - 3 2

a - o . l aN - 8 7 3

I

d - 1 l qd:

a - 0 . 0 1 8e?

1 ,1 a" (- 2 . ( ) 1 < d s z . 3 6

2

.y: 23'2

T a b u i . r r

t / f j

d - 0 . 5 7 8N . L 3 2

a - o . 3 b| r - 2 5 9

?a , - 0 . 0 0

r12

o - I ) . { ) le?

O , - - t )L ]

)o " - 0 . 6 0

0

- 0 . 9 5 < d s 2 3 2 i - 1 . 4 6 < d s i . 5 82 . . |

2

X r - 1 . 6 I * , t 6

1 7 , L 2 , 2 2 , 3 6 ) 1 \ t , 1 2 , 2 2 ) Ia - - o r e i a - - 0 3 3 1N - 6 1 6 | N - 4 3 0 |

2 | o ' . - o . z 2 Io o - o . 2 o

| " Io ' - o . o 3 3 l o ' - o o 2 8 l

e l e la t r l

o r - o . L 7 | " u - 0 . l e i- 1 .00<ds0 . 62 |1 - I . l 9<ds0 . 5 l I

a t l l

X t - 3 1 I t r - 2 3 |

I r s , ] 8 1 l [ 3 , 4 , 5 , 1 2 , I s 1 [ 3 , 4 , s , 1 - 2 , I s l| 2 L , 2 2 , 2 3 , 2 5 | 2 L , 2 8 , 2 e , I1 2 8 , 2 9 , 3 4 , 3 8 1 1 3 8 i

R e l e . , a n c y l a - L . 2 8 i a - o . o 7 o

1 1 1 A l *! 4 r , J )

j - o . t - : zN - 1 8 6

a

a , - 0 . 0 1 4cz

a - 0 . 0 4 3e2

o ' ' Oo

[ ] . 2 , 2 2 , 3 8 1 l [ 2 5 , ] 4 i *

N - 5 1 8 | N - l e 3 l. t 2

o , - 0 . 0 4 4 | o , - 0 . 6 8d l o1 t 1. l

o - 0 0 f 9 l a - 0 . 0 1e l e. ' 2

o . - 0 . 0 2 6 | o " - 0 . 6 3d l 0

0 . 9 7 < d s l . 5 9 | - l . 4 9 < d s l . 6 3. t z

X r - / . 7 6 | l X r s - 3 2 ?- t

d - 0 . 3 0 8N - t l 7 5

1

o . - 0 . 3 7 5oa

o - 0 . 0 3 4e2

o . - 0 . 3 4 0U

- 0 . 8 4 < d s l . 4 5 i2 l

X s l o e I

Note: [ ] Ful l c l tat lons are* The averaqe etfect

given in the ret 'erence section.size is the "true" eifect sizc.

the populat ion. For example. the comparison of bar wi th tabular presentat lons rn

terms of informarion precis ion indicates that the average ef fect s lze, is 0. l i l . . rnd

the corrected variance of the elfect size is zero. Thus. we can say that the bar tbrmat

is definitely better than the tabular. However, if the corrected variance of the effect

size is greater than zero, the contidence interval and chi-square value of effect size

must be calculated. The contldence interval represents the eff 'ect size value distribu-

tion with a corrected standard cjeviation and a 95 percent probabil ity. The chi-square

value indicates the s ieni t ' icance level of the residual var iat ion across studies. Ft l r

l 1 4 M O N T A Z E } I I A N D S . W A N G

Table 3 Effects of Color on Intormation Dimension

L32

, x x2

0 . 7 1 5 2 . 2 1 0 . 1 3 2 . L 4 - 2 . l 5 < d < 3 . 5 8 x - 1 0

1 6 6 0 . 6 1 0 . 1 0 0 . l 0I J ' + l

Note: [ ] Full citations are given in the reference section.* The average effect size is the "true" effect size.

* * D < 0 .001

example, on examination of the effect of l ine graphical presentation versus tabular

on timesaving, a relatively large residual variance of 0.60 is obtained. The reported

interval of - I .46 < d < I .58 means that, based on the available data, the "true "

effect size probably ranges from - 1.46 to 1.58, and the chi-square of 16 (dJ': 2.

p < 0.001) indicates that the residual variance is significant. This wide confldence

interval and significant residual variance suggest that moderator searching is neces-

sary before definite conclusions can be drawn.

Table 3 shows the results of the effect of color on two intbrmation dimensions.

The notations used in Table 3 are the same as those used in Table 2.

After the init ial meta-analysis was completed, the tbllowing indicated statistically

insignificant amounts of residual variance:( i . ) In terms of precis ion, the bar chart fbrmat is s l ight ly better than the tabular

format (Table 2).(i i .) In terms of relevancy, the fhce chart is more ef'fective than the tabular t i lrmat

(Table 2).(i i i .) In terms of relevancy, the multicolor chart is more useful than monocolor

(Table 3).However, the remaining six effect size r/-values (other than those of combined

graphics versus tabular) when cumulated exhibit relatively wide contidence inter-

vals. Only the effect size of tabular modes versus textual tbr the relevancy dirnension

is sti l l positive. The other f-rve confidence intervals include the zero point and have

large chi-square values. which signify residual (unexplained) variance. The larqe

residual variance is caused by moderators and/or uncorrected errors, both of which

hide the "true" effect size [7]. These two factors wil l now be investigated.

iIl

S cudy I- l

I

M u l c i - c o l o r v s | l o n o - c o l o r

9 5 t

C o n f i d e n c e C h i -. t )

N d o ) o ^ o . I n C e r v a l s q u . r r eo e d

I o f o r m a c -^ l o nu l m e n s I o n

T imeSav ing

R e l e v a n c y

EFFECTS OF INFORIV{ATION PRESENTATION

1.2. Detection of lvloderators

As has been already noted. there are four proposed moderators: Task environment.

decision style, personality, and time constraint. Unfortunately, because of the pauci-

ty of comparable research, only task environment could be detected comprehensive-

ly across studies. Consequently, those studies that examined task environment were

divided into three subsets, using the criterion of Dickson et al. [2]. The first subset

is characterized by simple, structured, and common tasks; the second subset by

medium complex tasks: and the third by both complex and unstructured tasks.

Because in the experiment sample the graphics format is only seldom used to solve

complex and unstructured task. Table 4 shows the intormation tormat effects tor the

first and second task subsets oniy. Note that the obtained vaiues are compared with

those in the original set.

Table 4 indicates that when comparing l ine graphical with tabular modes. task

environment appears to be a moderator for dimensions of t imesaving and precision.

since the subsets'et-fect size variance is smaller than the original variance. However,

task environment does not appear to be a moderator tor intormation relevancy. The

probable reasons for this discrepancy are:

(i.) The signiticant uncorrected error caused by the differences in treetment

strength across studies 1we wil l return to this issue later).

(i i .) The influence of the task environment moderator on intormation relevancy is

complex. Simply classifying task environment into two or three categories is not

sufficient to ailow detection of the moderator. One possible solution is to separrte

out the individual effects of "task content." "task complexitv," and "task struc-

ture" t l2 l .(i i i .) The existence of other moderators may attenuate the task environment effect.

Thus, f i.uther subdivision of'the data is necessary to detect these other moderators.

However, since sutficient information is not currently availabie to subdivide the

present subsets. further investigation is prevented.

For the other potent ia l moderators already ident i f ied ( i .e. , decis ion sty le,

personality, and time constraint). meta-analysis across studies cannot be per-

formed as yet because of lack of required data. Nevertheless. meta-analvsts

within srudies can be conducted as long as independent trials are available reie-

vant to the moderator under examination tl7] For example, Benbasat and

Dexter [4] conducted two trials on color effects. The tlrst was conducted under

high time constraint and the other under low. Because different sub,;ect grouPs

were used, the two triais were statistically independent. : lnd thus their results

could be cumulated separately. Also, if the data set is sufficient to obtain an ef-

fec t s ize d-va lue fo r each t r ia l , the average e f fec t s ize o f the two t r ia ls

can be computed. along with the variance of effect size and the portion o.f the

variance due to sampiing error. In addition. a chi-test cxn be pertormed usins the

formula

r 15

x ' r K - l ) = t s 2 a i s l ) ' K . t K = 2 i n t h i s c a s e ) .

r 1 6 A . R . M O N T A Z E M I A N D S . W A N G

Table 4 The Meta-analysis Results of Information Format Effects When Task Environ-ment Is a Potential Moderator

Note: [ ] Full citations are given in the ref-erence section.* The averase effect size is the "true" effect size.

If the 12 value is significant, time constraint is a possible moderator. If 1t it not

significant, then no conclusions can be drawn, even if independent ,-tests indicated a

difference under the two conditions. [n the latter case, meta-analysis indicates that

capitalization on chance has occurred and that the variation in results is caused

simply by sampling error. By following the above procedure, meta-analysis within

the study was performed to detect other potential moderators. The results of this

analysis are shown in Table 5.

I n f o r r n a c i o n D i m e n s i o n

L i n e v s T a b u l a r

O r i g i n a l I S i m p l e T a s kS e c I S u b s e c

I

Med iumC o m p l e x T a s kS u b s e c

T i m e S a v i n g

S Eudy

a

N

2o .

o

2

X

l(

t 3 , 7 )

0 . 0 5 5

8 5

0 . 5 0

,I A

3

7 ) I t 3 l

IIII

IIIIII

)t

L . ] L

I 6

0

2

- o . 3 2

7 0

P r e c i s i o n

S Eudy

aN

2o .

0

,X

V

t 1l t t

1 2 ) ) 1- - l

- 0 . 3 3

/+30

0 . 1 9

t 1

t 7 la ^ t' L . L ' +

1 0

t 1 ) ) ) 1| . . - ' - - |- 0 . 1 5

3 5 0

0 . 0 4 8

6 . 4

2

Re levancy

S Eudy

aN

2o .

t

X

l\

[ 3 , 4 , 5 , L 2 , L s ,2 2 , 2 8 , 2 9 , 3 8 l

0 . 3 0 8

l r 7 5

0 . 3 4 0

1 0 9

L O

I r s , 2 8 , 3 8 ]

o . 6 6 2

0 . 6 r 9

[ 3 , 4 , s , L 2 , 2 2 ,2 8 , 2 e )

0 . 1 7 5

6 3 0

0 . 0 6

8 5

3

L 7

7

E F F E C T S O F I N F O R | V I A T I O N P R E S E N T A T I O N I T 7

Table 5 Resul ts of N1eta-anaiysis With in Study to Detect ! {oderare Ef fecrs

Note: [ ] Full citations are given in the ret-erence section.NS Not significant.* Approximately compured results.

The following conclusions can be drawn trom Table 5.(i.) When comparing multi- and monocolor effects on information relevancv.

personaliry, which is classified as treld-dependent and tield-independenr (see [i.4l]), appears to be a moderator.

(i i .) When comparing bar and tabular effects on information relevancy. personaliryas a moderator is not supportable.

(i i i .) When comparing the effects of the l ine graphical and the tabular tormar onthe information dimension of t imesaving, t ime constraint does not appexr to be emoderator.

4.3 . Conclusion

The results of this meta-ana.lysis can be summarized as toilows:(i.) Generaily speaking, l ine -eraphics have no general advantase over tabuiar

presentat ion intermsof t imesaving; that is , l inear is super ior to tabularonly when amedium-complex managerial task is performed: when a simpie task is to be per-formed, tabular is better than linear presenrarion.

(i i.) Line is l ikely to be less effective than tabular tor infbrmation precision.especially when a simple task is pertbrmed. However. bar charts are slightly better

P o c e n c i a l C h i - S i g n i -1 a

o d o " s q u a r e f i c a n c el { o d e r a c o r I S c u d y C o n C e x C .

t 4 l E f f e c c o fL i n e v s T a b u l a ro n T i m e - S a v i n g

o . 6 2 0 . 6 8 3 l . 8 2 : r s

T i m e | - - -C o n s c r a i n c *

0 . 1 3 0 . t 2 2 . 0 2 : r st 4 l C o I o r E f f e c c so n T i m e - S a v i n g

L r j C o l o r E f f e c c so n R e l e v a n c y

*L 4 . 4 0 . 3 7 7 8 p < 0 . 0 0 1

r ? ' t I( c r t E f f e c c o f

Bar vs Tabu la ron Re levancy

ta

0 . 0 0 . 0 5 0 . 0 N S

I 18 A. R. i l toNTAzEMI AND s. wANc

P r e s e n t a c i o nI tode s

R e s u l c s o f E h e m e t a - a n a l Y s i sI n fo rma c i onD i r n e n s i o n s

T i m e S a v i n g

P r e c i s i o n

R e I e v a n c y

Table 6 Summary of Meta-analysis Results

I i n o

vsT a b u l a r

L i n e i s s u p e r i o r E o c a b u l a r w h e n

p e r f o r m i n g a m e d i u m - c o m P l e xm a n a g e r i a l c a s k . B u E E a b u l a r i s

b e c c e r c h a n l i n e w h e n a s i m P l ec a s k i s p e r f o r m e d .

C o l o r N o s u p e r i o r e f f e c c s .

L inevsTabu la r

T a b u l a r i s l i k e l Y E o b e m o r ee f f e c t i v e c h a n l i n e ;a n d c h i s e f f e c c a p P e a r s s E r o n g e rw h e n p e r f o r m i n g a s i m P I e E a s k .

I B a r i s s l i g h c l y b e E t e r E h a n E a b u l a r '

Ba r vs Tabu la r II

F a c e v s

T a b u l a r

Face i s more use fu l Ehan cabu la r

L ine vsTabu la r

L i n e i s l i k e l y c o b e m o r e u s e f u l E h a n

c a b u l a r ; b u c E h e e f f e c c h a s a

r e l a E i v e l a r g e v a r i a E i o n .

C o l o rl , l u l c i - c o l o r i s m o r e u s e f u l E h a n

m o n o - c o l o r , e s p e c i a l l Y f o rt h e f i e l d - d e p e n d e n c P e r s o n .

than tabular forms in terms of information precision.

(i i i .) The face formar is more useful than the tabular in terms of information

relevancy. However, the effect of linear versus tabular on information relevancy

exhibits considerable variation.

(iv.) Color improves decision quality, especially for the information user with a

field-dependent personality. However, color has no superior effect on timesaving.

These findings are summarized in Table 6.

5. Discussion

UNoerec rED MoDERAT9RS MAy No r BE the so le cause o f t he l a rge res idua l

effect size variances of the results of the original meta-analysis. Uncorrected error

EFFECTS OF INFORI IAT ION PRESENTATION

sources mav contnbute to these residual variances. As noted in this studv, dirfer-ences in the treatment strength of independent variables is one such error source.

Benbasat and Dexter [4], ives [8], and Tufte [36] have stated that inadequaredesign of graphics could ruin the effects of a presentation mode. This suggesrs tharthe errors caused by differences in treatment strength are probably serious. Howev-er, as noted above, it seems impossible to correct this type of error. The major barrieris how to quantiry accurateiv this difference within the same presentation mode.

Pragmaticaily, the "best" designed format should be used when the effectivenessof several modes are compared. Hence, when conducting an experiment. a series ofpre-tests should ensure that the modes being compared are the "best. " As anaiternative, the modes being compared should be desiened accordinq to the samestandard (e.g. ,see [18. 33. 36]) . These opt ions are complemenrary and ideal l . ' - a l lowthe reduction of error caused by differences in treatment strengrh. This in turn wouidalso enhance ft:ture meta-analytical treatment of this subject.

Severai observations can be made trom this studv. First, moderator searching ,,vil l

become a dominant tactor in future research. Very few meaningful studies wil l fail tolink data to the moderator effect. Second, specif-rc design tearures should be system-atically manipulated or controlled when preparing experimenral graphical treat-ments. Poor graphical design and insufficient training in data presentarion wil l serveto contaminate any conclusions drawn. Finally, since the statisticai power of nreta-analysis l ies in sample size, it becomes clear that the number of effect sizes. the"true" population effect size, and the lack of comparabie experiments rather thanthe lack of analytical tools, created the major l imitation of this studv.

Appendix

An extensive summary table of different presentation modes. infbrmarron dimcn-sions, and potent ia l moderarors is given on pp. 120-125.

RepsRENces

l . Ba i iey , J . E. . and Pearson. S. W. Development o f a too l tbr rncasunns lnd lna lvzrngcomputer user satist 'act ion. ,Vunuqernent Science. 19. 5 (Nlav 1983), 5,10-5.1-5

2. Banger t -Drowns, R. L . Revtew of developments in meta-analvr rc methods. Pst t 'ho-l og i ca l Bu l l e r i n .99 . I (May 1986 ) , 388 -399 .

i . Benbasat . [ . , and Dexter . A. S. An cxper imenta l cva luat lon o i uraphice l lnd eo lor -cnhanced in tbrmatron repesentat ron. . l lunugement Sctence, l l . l l (Novcmber 1985) . l -1-18-t3&r.

-1 . Benbasat . [ . . and Dexter . A. S. An invest is l l t ion o f the e t t -ecr rveness ( ) t 'co l ( ) r endgraphical intbrmation presentation under varving t ime consrralnrs. .WIS r)uttrterl t ' . 10. I(Ma rch 1986 ) . 59 -83 .

5 . Benbasa t . I . : Dex te r . A . S . : l ndTodd . P . The i n t l uencco i co lo rand u raph rca i r n fb rma-t lon presentation in a manaqertai decision srmulatron. Hurrtun-Ct)mputer lnre'rt t t ' r tr tn. ). I(January 1986) , 65-92.

(continued ttn puge l26l

u 9

1 2 0 A . R . M o N T A z E M I A N D s . w A N G

Appendix

A Summary Table of the Relationship Between Information Presentation Modes.

Information Dimensions. and Potential Moderators

' . ' - R e i e v a n c r e s e a r c h . W T h e p o c e n c i a l n o d e r a c o r u a s e x a m i n e d i n c h e s a n e ; c : r t ' .) . 3 e : c e r : h a n .

A U T H O R , S B e n b a s a c e c a l

1 9 8 5

i

t _

III

l L n e s a v i n g ( 5 p e e d )

f r a n ' i < i n n I ' n r { p r . - - - / - F . i 1 i r . r \J g d l l u d u L L L r j , /

i l o n . c I . T t l- Y u I : . c l . C I> - l l o n . c I . C I

+ - - - -' : - l ' l u i ; . c l

I> l * T > c

l l o n o . c l I+ - - - -

$ u l c . c l > , t l

l t o n o . c l I Y u l c . c lR e l " e v a n c ' / ( U s e f u l n e s s ), k C > T l >

i - " . ; i i "? s v c h o l o g i c e l r - - - - " - - -

I I _ e a r n i n g

I

- + - - - -

I

I

I- - - + - - - - . - "

I 'J

- - - t - - - - - - -

l ' /- - - + - - - - - - -

i- - - + - - - - - - -

I- - - + - - - - - - -

I- - - t - - - - - - -

I- - - + - - - - - - -

l v- - - + - - - - - - -

I- - - + - - - - - . -

I

l l o n - L l n e a r L i n e / L i n e I v

C r a p h i c s3 a r

r L e

; . . ; -

O c h e r s

t - - - - -I C o l o r

: : : : : : : i : : . : : : t : : : . . . . . . . . . . . . . . . .H a r d C o p i e s v s C R T

I T a s k II E n v i r o n m e n c It lt lr - - - - - - - - - - - - lI I D e c i - l

I C o n g - | s i o n II n i c i - l S c y I e l

l v e l - - - - - - ll S c ; r L e I P e r - |

:rT:l: : :::::::::iHed lum

C o m p l e x & U n s c r u c c u r e d

; ; ; ; i ; . i ;A n a l y c i c

; i ; i ; . ; ; ; ; ; .F i e I d - i n d e o e n d e n c

. . - . . .

1:9: : :T: : :T:: : : I :Lo ' l T ime Cons c ra i .nc

V

| | s o n a -I I I i r . '| | L L r l

l - - - - -I T i m eI a - - - F - - i - >I v v r r J L r 4 r t l u

I

EFFECTS OF INFOR]V lAT ION PRESENTATION t2r

Appendix (continued)

\l

122 A. R. MoNTAzEt l t AND s. wANc

Appendix (continued)

A U T H O R . S

T i n e s a v i n g ( S p e e d )

I R e c a l I? s ; r c h o l o g i c a L i - - - - -6 r o w c h I

I L e a r n i n g

I

T e x c

T a b u l a r

D i c k s o n e c a i

: 1 8 6

E e l l s IL e 2 6 I

J

'J)

o O

= -

s 0 J

ti tr

c >

oqJli

P i e - B a r

I C > T

G r a p h i . c s

i lt li l

, , r 1 1- | - - - - - - - - +

r l

- - l - - - - " - - + - - + ' - - ' - - - '

I = o l . l

P r e c i s i o n ( U n d e r s c a n d a b i l i c y ) l

t - a I

T > - C I

I I I

| * = l o o l

R e l e v a n c y ( U s e f u l n e s s ) I : - C l C > T l

S l m p l e & S c r u c c u r e d

,a

q,

T a s kEnv i ronmenc

I D e c i -C o n g - | s i o nn l c i - | S c y I ev e l " - - "S c y l e I P e r -

I s o n a -

I r i c y

Medlum

C o o p l e x & U n s c r u c c u r e dt n I

H e u r i s c l c

A n a l y c l c

.f 1:li.i:r:1:::F l e l d - i n d e p e n d e n c

T i m eC o n s c r a i n c ::?:.1:T:.::::::::::

L o w T i m e C o n s c r a i n c

P a r c i a l s c a c i s c l c s w e r e a v a t l a b l e C o r l p I e ! e s c a c i s c r . c s C r a p h i c s

E F F E C T S O F I N F O R } I A T I O N P R E S E N T . \ T I O N I ? 3

Appendix (continued)

t 9 8 l

G > T

C R T . T I IT > G I I

P l o c C r a o h

r l rr t ' l- - | - - - + - - - - - r - - - - -

I

' t .

- + - . - -

i i ! s c c g r t r n - 1 r , , 1

v l v l. . . . i - - - +l l \ tI Ii ll - +r l- - - - 1 '

r r l

o c , S l o c k ) |t - . - - - - - -I

I v t l

T T a o u i a r l ' ( u I c . c l . - S u l c i - c o l o r . { o n o . c l . - X o n o - , : o i o r

I24 A. R. MoNTAzE:lrr AND s" wANG

Appendix (continued)

A U T H O R S

!r

= -

J t

= > .

li

T i m e s a ' r i n g S o e e d )

P r e c i s i o n ( U n d e r s c a n d a b i l i c Y )

t - - - - -II

I R e l e v a n c y ( U s e f u L n e s s )

c > T

G > T

I R e c a l lP s y c h o i o g i c a l l - - - - -C r o w c h

T e x c

iI L e a r n i n gI

T a b u l a r

E

q,

I N o n - I i n e a r L i - n e r / L i n e

l - - - - -I B a r

G r a p h i c s l - - - - -I P i e

I - - - - -I Facel - - - - -I O c h e r s

C o l o r

3 - D i . m e n s i . o n G r a p h i c s

H a r d C o p i e s v s C R T

I S i m p l e & S c r u c c u r e dT a s k | - - - - -Env i ronrnenc I Med iurn

l - - - - -I Conp lex & Unscruccured

t - - - - -I D e c i - I H e u r i . s c i c

C o n g - | s i o n | - - - - -n i c i - l S E y I e l A n a l y e i cv e l - - - - - - l - - - -S c y l e l P e r - | F l e l d - d e p e n d e n c

I s o n a - | - - - - -

I I i c y I F l e I d - i n d e p e n d e n c

t - - - - -T i m e I H i g h T i m e C o n s c r a l n CC o n s c r a i n c l - - - - -

I L o w T i m e C o n s c r a i n c

l D J - D i m e n s i o n G r a p h i c s . l l / R - w h l c e - B l a c k . 2 D - 2 - D l m e n s i o n G r a p h l c s .

EFFECTS OF INFORI I1ATION PRESENT. {T ION I :5

Appendix (continued)

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