DOeSMBNT RBSOMB
i© 276 816 CE 645 817
/ADfBOR Pligics, Rcbgccs M, ; And Others 1:1::
TITCE Towsrds an yadirstandinf of Army Bnlistment
: Hotivation PattSriis i Technical: Ri^ : :
IHSTITOTICHI AfBf Research Znsti for the Behavioral and Social
Sciences, Alexandria, Va.
REKOif ftO j^|-TR-702
^^re DATE tJan 86
jlOTB 45p.
PUB TYPE Reports - Research/Technical (143)
EBRS PRICE ^ei/Pe62 Plus Postage^ ^ -
OESSRIPT^S Adult Education; *Aniied Forces; Economic Factors;
*Enlisted Personnel; ^Motivation; Surveys
tOBMTXFZBRS *Army; *Military Bnlistment; Psychological
Influences
ABSTRACT _ -_ - i
_ _ As part ef_anongQing_8ttfvey effort^ new^
were silryeyed at United States An^ reception stations across the
eowtrf -during the spring and su^ of 1982 and 1983. in addition to
preMnting cross^tabttlated responses^ for survey questions on
reei^ita* reasons for enlistii!>j, principal cooiponents analyses were
eoapfited on these data. These vanalyses indicated that six distinct
fie^fs underlying recruits* eniiistment motivation could be
idifi|:i£ied* They were'L8e''f-f :;'.^rovement^ eeonemie advaneement^---i _
miliary servieei^ time but ^ travel^ and education moneys The analyses
suggested that recruits enlist in the Army for a variety of economic
and psychological reasons. Eighteen data tables are provided.
(TLB)
*******************************************
* Reproductions supplied 1^ BDRS are the best that can be made *
* from the original document. *
******************************
0
ERIC
Technical Report 702
uj Towards an Understanding of Army
Enlistment Motivation Patterns
Rebecca M. PHske, Timothy W. Ellg, ft Richard M. Johnson
PersGririel Utilization Technical Area
Manpower and Personnel Research Laboratory
i of Educatiorwl RMMich^nd lmprov#ment
AtldNAL AESdURGESHNFORMATION
CENTER (ERIC)
/lli&^-documinMwt^4^^ f«produc«d m
F rfc«l««d_ffDm th« p«raon or organization
oriQihatiho It
□ Minof^cMngM hivo b««n mado to improve
r«pfDdtictk> n QuaiWy.
• Pbl nta of viaw or opin^ stated in this donu-
mant do not naoanartty rapraiaht offidai
OERI position or pohcy.
U. S. Army
Research Institute for the Behavioral and Social Sciences
January 1986
Approv«d for public release; distribution unlimited.
y. i. ARMY RiSlARCN INSTiTUTE
FOR THE BEHAVIORAL AND SOCIAL SCIENCES
A Field Operating Agency under tfie Jurisdictidh of the
Deputy Chief of Staff for Personnel
WA. DARRYL HENDERSON
EDGAR M. JOHNSON OOL, IN
TKhtlical Db'eclor Q>jnnu_ndu^
Technical review by
David K. Horhe
Mary M, Weltin
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siFigo - J
^eCtf WItY CLASSiriCHTieN OF THtS PKOE fmmMMi mniim^
RiPdRf l)OCOItENTAtibN PAGE
1. REPORT NUMSCfl^
Report 702
2. OOVT ACCESSION NO
4. TITLE fan«Siifrim«>
a!OS9ARDS AN UNDERSTANDIilG OF AKMY ENLISTMENT
MOTIVAMON PATTERliS
7t AOTHORTiD
Rebecca M. Plisker Timothy W. Elig^ and
Richard M. Jbhhsdh
PERPORMiNO ORdANiZATION NAME AND AODRESS
U.S. ArwY Research Institute for the Behavioral
and Social Sciences
5001 Eise.lhcw^ er A^^hue ^ Alexandrian VA 22333-5600
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U.S. Army Research Institute for the Behavioral
and Social Sciences
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Approved for ptiblic release; distribution unlimited
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3. RECIPIENT'S CATALOG NUMGER
5. TYPE OF REPORT A PERIOD COVERED
Final Report
February 1^4 - November 198
6. PERFORMING ORG; REPORT NUMBER
a. CONTRACT OR GRANT NUMBERf*^
10. PROGRAM ELEMENT. PROJECT, TASK
AREA ft WORK UNIT NUMBERS
2gl62722A791
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«2. Report oate
J anuar y 1986
13. NUMBER OF PAGES
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15. SECURITY CLASS, fol thU r^et)
Unclassified
fS«. DECLASSIFICATION/OOWNGRAOING
SCHEDULE
17. DISTRIBUTION STATEMENT (ot Ow «b*(r«e( mttftmath Block SO, it dlU^rmt tnm Rmport)
Ift. SUPPLEMEWTART NOTES
It* KEY WORDS fCdiilifMi* on rovoroo midm itnmcmmmmrr md Idmntliy by biock numb^t)
Recruiting „.
Enlistment motivation
2& AiBSTyACt f T^ iii ffc ii ■ — oi* » tmemmmmtr mmAMmUifr kr blocft^ manftor/j i
^fP^^^.^^^'^^^izes inforM the ARI New Recziait Surveys for
1982 and 1983 related to enlistment inbtivatibns of new Army recruits. In addi-
tion to fresenting cross-tabulated responses for survey questions^ principal
coii(>oheht analyses (PCA) were cbn^leted oh recruits* responses to questions on
their rectsohs for enlistment. The PCA indicated that, recruits enlist for a
variety of ecdhbmic and psychblbgical. reasons^ such as self improvement^ eco-
hbmic advancement, military service, time but, travel^ and education money*
1473 cirniM OF tiibvisis
BTE
UNCLASSIFIED
ERIC
i SECURITY O:A»FtCATI0lt OF THIS PASIE fliliiR Data KiforoiO
Technical Report 702
Towards an Understanding of Army
Enlistment IWotlvatiori Patterns
Rebecca M„ Plleke, Timothy W. Ellg, & Richard M. Johnson
Persohhel Utilization Technicaj Area
Paul A. Gade, Chief
Manpower and Personnel Research Laboratory
Newell K. Eaton, Acting Director
us. ARMY RESEARCH INSTITUTE FOR THE BEHAVIORAL AND SOCIAL SCIENCES
5001 Eisenhower Avenae, Alexandria. Vfc-glnia 22333-5600
Office. Deputy Chief of Staff for Personnel
Department of the Army
Jahuary 1986
Manpower. Personnel and Training
Approved for public rej«ate; distribution unlimited,
iii 5
Army Project l^lumber
20ie2722A781
ARI Remn^ Repbrtt fritf^ arejmmded_for sponioit of
R&P tasks and for other reseat and mlMtary agencies. Any findings ready
for icriplemehtati^^ pre»shted in the last part
of the Brief* Upon cbmpieSpri of a rnifor phase of the task, formal recom*
mehdatiCMis tor offidiai action norrn:^iiy are conveyed to appropriate military
agencies by briefing or Di^Mitioh Form.
iv
8
FbREWORD-
This report sommrizes recent findings from survey efforts uhairtakeri by
ARi in support of the Office df__tfee Deputy Chief of Staff _ Tor Personnei and the
U*S. Army Recruiting Command. This study presents information on psychological
variables that influence young peoples* enlistment decis arid argues that
policy makers should use models of the enlistment decision process that include
both psychological and economic variables.
EDSfflRM. JOHNSON
Technical Director
TOWARDS AM UNDBRSTANDISG OF AfiMX EWLiSTMENT MOTIV^ITIOH PATTERSS
EXECUTIVE SUMMAitt
Requirement :
in order to attract high-quailty appiicants^ the Arajy spends a_ good deal
of money on economic incentives such as the Veterans V Educational Assistance
Program (VEAP). The military personhel^planhers who allocate the money for
these incentives need to consider the important psychological and economic
factors that underlie enlistment motivation patterns.
Procedure:
The data presented in this report_rfere_c611ected as part of an ongoing
survey effort conducted by the tJiS* Ariy Research Institute for the Behavibrai
and Social Sciences {ARlJi Sew. recruits were surveyed at U.S* Army reception
stations across the country during the spring and summer months of 1982 and
1983* in addition to presenting cross-tabulated responses for survey questions
on recruits* reasons for enlisting ^ principal components analyses were com-
pleted on these data.
Results:
.These analyses indicated that six disW factors underlying recruits'
enlistment motivation can be identified. They are ab follows: self improve^
raent, economic advancement, military service, time out ^travel, and education
money. The analyses suggest that recruits enlist in the Army for a variety of
economic and psychological reasons.
Utilization of Findings:
The information presented in this report will be used by military person-
nel planners who allocate mdn^ for various recruiting efforts^ These data
will also be added to a growing longitvadinal data base used for modeling indi-
vidual decision making and microeconomic forecast modeling.
vii
s
TOWABDS AN UNDERSTANDING OF ARMY ENLISTMENT MOTIVATION PATTERNS
CONTENTS
Page
SURVEY PROCEDUmS AND SAMPLE * i * • i i i • • 2
RESULTS , 4
F6rcedr>Ghbice Questions • • . • • i . . 4
Maitinoodal Importance Ratings • • • • ^ i ^ ^ . . . [ 10
Internal Validity Check ... ••iiii. 12
Principal Compbhents Analyses •••^•i. ....... 16
SUMMARY AND CONCLUSIONS . * . i ............ 3q
REFERENCES . * . i . . . 31
APPENDIX A ....... . ....... 32
LIST OF TABLES
Table 1* Survey and population demographics for non-prior service.
Regular Aimy recruits, 1982 and 1983 3
2. Con^arlsbn of most important reasons for enlistment
1979/1982/1983 .. ^ ^ . g
3. Percent of recruits responding to forced-choice questions
on nost in^ortant reason for enlisting by AFQT category
classification ......... J
4. Percent of recruits responding to forced-choice questions
on reason for enlisting by sex ....... 3
5. Percent of recSits responding to forced-choice questions
on most important reason for enlisting by educational
background of recruit 9
6. Percent of recruits responding to ^Itinoniai questions
on reasons for enlistment by AFQT category classification ... 11
7. Percent of recruits responding to multinomial questions
on reasons for enlistment by sex « ^ i i i . . . . . 13
8. Percent of recruits responding to^ltinomial questions
on reasons for enlistment by educational background ...... 14
eONTBIfS- 1 eoptittoed)
Page
Table 9- Percent of recruits responding to multinomial and
forced-choice questions oh reasons for enlistment 13
10. Percent of recruits responding to forced^hoice question
on most important reason for enlistment by their plans
after enlistment 17
11. Percent of recruits responding to the forced-choice
question on reasons for enlistment by their employment i
status when they enlisted • ^ ^ ^ • ^ t • i • « • » • i • « i • l8
12. Rotated factor loadings (oblique solution) ••••»•••«•• 20
13- Factor correlations for rotated factors 23
Ikk Rotated factor loadings for higher order factor analysis . • • . 2h
13. Comparison of factor loadings (oblique rotation) for 1982
and 1983 ^ 23
16. Hean factor scores by demographic variables 27
A-ii Rotated factor loadings from the orthogonal solution 32
A-2. Factor loadings (oblique rotation), number of factors
restricted to three 33
10
o
ERIC
TOWARDS AN UNDERSTANDING OF ARWY ENLISTMENT WOTIVATION PATTERNS
Our nation^ s Armed Services are faced with the continuing challenge of
attracting large numbers of qualified young men and women. Since the
introduction of the all volunteer force, the Armed Services have had to compete
with private sector employers and educational institutions for these young
people._ This competition promises to become even more intense in the near
future because the number of Service-eligible youth is declining while the
manpower needs of the Services are growing.
^ In order io attract high quality applicints, the iServices spend a good
deal of money^ on economic incentives such as increased levels of compensation
IvLVl ^^^^ ^ ^"^"^^^''-^^^ the Veterans' Educational Assistance Program
iVEAP). The military personnel planners who allocate the monies for these
recruiting efforts rely to a large extent oh economic jnodels of military
accessionSi_ A common procedure for examining ^e effects of enlistment
incentives on military assess ions is to use some type of econometric modeling.
A crucial assumption of such models is that the equations estimated are
properly specified," that is, that the equations include all variables that
may have a major influence on the outcome of interest. If important variables
are omitted from the equations, then the estimates of the effect of the
variables that are included may be seriously biased.
EcoSomic models of enlistment tend to focus on pecuniary factors such as
pay^ benefits, and bonuses that can be directly altered by policy makers and
generally include other ••economic" factors such as the unemployment rate,
mtnimum-wagelevels. and recruiting resourses. Recently, some economists have
begun^ to include "non^economic" variables in their models. For example, Dale
and Gilroy ^1984) have shown that a non-economic variable measuring recruiter
ettort had a significant effect oh the number of Army enlistments.
--Although economic models provide useful information to policy makers, we
agree with faris C19S4J who claims that purely economic models are insufficient
to account for military recruiting patterns. Paris reports data on the
probability of reenlistment intentions of ehlisted persohnel that indicate two
^on-economic variables are significant factors in the reenlistment decision.
One factor^refiected the individual's relative satisfaction with the "more
Immediate features of the military work role" and the other factor reflected
_attachment to the broader role of the military." Paris presents data th^t
lndicate^|hat non-economic factors are also important for the retention of
junior officers.
.^^ P^i^^ of this report is to summarize receht findinis from a survey
administered to new recruits entering the US Ariy that provides informatibh
about Army enlistment motivation patterns. We hypothesized that today's youth
are attracted to the military service for both economic and non-economic
reasons and our results generally support this hypothesis. In this report, we
i
111
present information on psychoibgical variables^ that influence young peoples'
enlistment decisions and we argue that policy makers should use models of the
enlistment decision process that include both psychological and economic
vairiables;.
The data presented in this report were collected as part of an ongoing
survey effort conducted by the US Army Research Institute for the Behavioral
and Social Sciences (ARI). In response to a request from the Departrouiit of the
Army^ ARI developed a Survey of Personnel Entering the Army to answer questions
concerning the demographics and enlistment motivation of new recruits* The
structure of the current survey is based in part on the 1979 Department of
Defense Survey of Personnel Entering Military Service (Doering, Grissmer, and
Horse, 1980a, 19805),
The ARI survey was first administered in the spring and summer of 1982.^ A
revised form of the ARI survey was administered in the_ spring and summer of
1983, The focus of this report will be on the 1983 survey data that address
the issue of why young people decide to enlist in the Army. Some comparisons
to relevant data collected in the 1982 survey will also be included. Elig
(1983) summarizes the survey design and sampling procedure^ provides general
technical information about the questionnaires, and describes the data bases in
detail. Only a brief summary of this information is provided below.
SURVEY PROCEDURES AND SAMPLE
New recruits were surveyed at US Army reception stations across the „
country during the spring andsummermohths of 1982 and 1983. An effort was
made to minimize sampling bias by sampling all recruits without prior military
service (NPS recruits). Although data was collected from recruits entering the
Army Reserves arid the Army National Guard, this report will- only present dafa
collected from recruits entering the Regular Army (RA recruits), individual
qnestiohnaireswere matched with accession records taken from the Military
Entrance Processing Station Reporting System (MEPRS) to provide important
demographic information suchas Armed Forces Qualification Test (AFQT) scores.
Matching MEPRS records were found for 6,318 MPS RA recruits in the 1982 sample
arid 8^605 NPS RA recruits in the 1983 sample. The actual number of cases for
some of the analyses presented in this report is smaller than_ the total sample
because some items did not appear in all of the alternate forms of the survey
questionnaire.
Table 1 presents demographic data on several variables that may influence
recruits' responses to survey questions for the 1982 and 1983 samples of new
recruits; data on the total population of new recruits are included for
compa risen purposes. The demographics frpm the ARI surveys indicate J:hat the
samples are fairly representative of the population of new Army recruits in
1982 and 1983. However, the 1982 and 1983 samples may be somewhat biased
because they were both administered during the last half of the fiscal year.
EKLC
2.
A.
12
Table 1
Survey and populati6h_demographics for non-prior service, Regular Army
recruits, 1982 and 1983;
o2
82
83
83
82
82
83
83
Sample
Pop,
*
Sample
Pop.
Sample
Pop.
SampJ.e
fop;
AFQT
Region
I&II
31. D
31.9
36.0
36;5
N£
20.9
22.3
20.1
22.2
IlIA
18.9
21;i
27;8
24.9
S£
25.1
23.7
21.0
22.3
IIIB
26.6
27.8
30.4
26.6
SW
15.2
13.3
16.4
27.3
XV
19.2
5.8
12.0
MW
26.3
26.1
27.4
13.6
West
12.5
14.6
15.1
14.6
Ethnic
fe^m of
Group
£nlls tmen E
White
65.9
71.0
73.8
74.0
2
8.5
6.0
7.7
6.9
Black
26.4
24.6
19.6
21.8
3
51.0
56.9
56.2
57;9
Other
7.7
4.4
6.S
4.2
4
40.5
37.1
36.1
35.2
Education
Sex
HSDG
91.9
86.0
83.9
87.6
Male
91.0
87.0
90.4
87.6
NHSG
8.1
14.0
16.1
12.4
Female
9.0
13.0
9.6
12.4
Age at
Contracting
17
33.1
9;8
39.9
8.2
18
25.4
32.4
22.4
32.3
19
13.0
19.4
12.4
20.4
20
8.8
11.3
7.4
11.7
21-23
12.4
16.5
11.0
16.9
24 Or
7.3
10.6
6.9
10.5
More
3
u
Id
ERIC
This pbtehtlal seaspaal : bias is attenuated by the fact that many of the
recruits have sighed enlistment contracts thrbughbut the preceeding year under
the Army's Delayed _Ehi:ry Program (DEP), The results of bur accession samples
are best interpreted as indicators of the relative strength of motivations for
enlistment rather than definitive percentages of accessions motivated In
specific ways.
New recruits' reasonsfor enlisting in the Army were assessed using twb
different types of question formats that we will refer to as the forced-choice
questions and the multinomial questions, the forced-choice questions asked
recruits to pick their most important reason for enlistment from a list of ten
alternative reasons. Although the forced-choice format has been the
traditional way of measuring reasons for enlistment and is useful for
crbss-year comparlsbhs^ it is psycbometrlcally weak. _ Fbr example^ Bbesei and
Richards. ( 1982) no ted how sensi tlve 1 1 is tb brder ef f ec ts . Fur thermbre ^ as
discussed by £iig 9 Johnson, Gade^ and Bertzbach_(1984), forced-choice questibhs
are inflexible because they cannot be changed to include other possible reasons
without destroying comparability. Forced-choice items are also insensitive to
the probable mixed nature of enlistment motives. Most recruits probably have
many reasbns fbr enlistment and are hot necessarily clear on exactly why they
enlisted.
the multinomial questions. introduced in_ the 1982 survey make enlistment
motivation amenable to the most powerful statistical tools* For_these^
questions, recruits were asked to make Importance ratings of iS different
reasons which may have caused them to enlist. The use of multinomial
importance ratings was expanded in the 1983 survey to Include up to 28
different reasbns in some fbrilis of the survey. Assessing recruits' reasons for
enlistment with alternative formats not only allbwir for a variety of
statistical analyses to be conducted, it also provides a check for the Internal
validity of the information obtained in the questionnaire.
Forced-Choice Questions
Tables 2^5 present the dar4 f rbm_ the f brced-chbice questlbhs pertaining tb
reasons for enlistments Recruits. were given two separate lisxs of reasons and
were asked "which of Sese reasbns is your MOST IMPORTANT REASON for enlisting"
from each list, the two lists were identical except that in tist 2 "chance to
better myself" replaced "I want to travel." The two alternative lists of
reasons were included fbr comparison purposes With similar forced-choice
questions used in previous surveys (e.g., Doerlng et al., 1980a, 1980b).
RESULTS
Results presented in table 2 show how reasons for enlistment have changed
since i979. As can be seen in columns one and_ two of Table 2, the biggest
changes in self-reports of motivation from 1979 to 1982 are decreases ip-
rootivatioa for a •'chance to better myself" and ••skill training^; and increases
in motivation for '•money to attend college ••and for •'escape from unemployment/*
••Chance to better myself " and "skili training" also decreased from 1982 to 1983
(columns two and three), while the only notable increase from 1982 to 1983 is
in motivation to earn more money.
^ Differences in recruits' responses to the forced-choice questions
observed for several different demographic variables. Tables 3-5 present the
data according to AFQT category classification, sex, and educational background
of the recruits^ The data in Table 3 indicate that although there is a
statis tically signifcantdifference In self-reports of motivation for
enlistment for recruits of different AFQT categories (p<. 01 ), there is a great
deal of similarly among the recruits. Not surprisingly, recruits with higher
AFQT scores (CAT Is and lis) report that the mbst_ important reason for their
enlistment was to obtain money to attend college more often than recruits in
the lower AFQT categories. Recruits from the lowest AFQT categories (CAT
IVA/IVB) were more likely to report that the most important reason for their
enlistment was that ttiey were unemployed as compared to recruits from the
higher AFQT categories.
Differences in recruits' responses according to sex are shown in Table 4,
It is important to note that the differences between the sexes shown in Table 4
may be confounded somewhat with other demographic factors because enliptijient
standards are more strict for females (no CAT IV females or female^ without a
high school educationwere admitted in 1983). However^ log linear analyses
including both sex and AFQT as categorical variables indicated that the 3-way
Interaction between sex J AFQT and response to the test question was not
statistically significant (£<.01)i but the sex differences are statistically
significant (£>.01). Females are more likely to report "chance to better
myself" and "money for college education" as their most important reason for
^nlistihg; whereas males are more likely to report "service to country" and
"unemployment" as their most important reasons.
- table 5 presents the data from the forced-choice questions according to
educational background of the recruits^ The differences shown in Table 5 are
statistically significant (£<i01). Recruits with some post-high school
education report ••money for college" as their most important reason for
enlisting more frequently than recruits with high school educations or non-high
school graduates. The data in Table 5 also indicate that recruits with some
post-high school education are less likely to report "service to coantry" as
the most important reason for enlistment as compared to recruits who do not
have any post-high school education.
is
Table 2
Cbmparisbn of most important reasons for enlistment 1979/i§82/i983.
Which one of these
reasons is your mOist
important reason for
ehlis ting?
1979 DoD
Survey of
April
Contracts
ARI Survey of New Recruits*
List i
1982 1983
List 2
1982 1983
Chance to better myself
(not measured in duly-Aug 82)
To get trained in a skill
Honey for a college education
To serve my country
I was unemployed
To prove that 1 can make it
To be away from home on my own
Earn more money
Travel (not measured in
May-JUne 82)
To ge t away from a
personal problem
Family tradition to serve
39
25
7
10
3
5
1
4
30
22
is
9
16
6
4
2
25
i$
16
9
9
7
5
7
35
20
10
10
9
5
4
30
17
12
10
10
7
6
4
100%
100% 100%
1 2
100% iOO%
^Regular Array, non-prior service enlistments only
16
ERIC
Table 3
Perceht of recruits responding to forced-choice questions on most important
reason for enlisting by AFQT category classification.
Reason for enllsf-mAn^
Ca tegory
List 1
X u Xx
XXXS
^ XiJJ
/ M— 1 ^ 1 C \
VN=1 JIj;
(N=292)
To iZGt trained tn a ^Icf^t
Z J • J
Z/ .Z
j4*4
28.8
Honey _ for college _ ed uca ti on
30.8
21 1
7
1 A a
lU . 0
To serve my country
11.6
12.4
10.7
9.6
1 was unemployed
9.5
9.6
12.5
22.3
To prove that I can make it
7.4
8.4
10.5
9.2
To be away from home oh my own
5.3
8.1
7.4
8.2
Earn more mnnpv
«5 'i
^ • J
/• 7
5.8
Travel
A 1
0 "7
5.2
3.4
To set auav frflltl niBl"cnrl^B1 nmKlAtn
1 A
1 . D
4 . J
i c
1.0
2.1
FamiXv tiradlt'fnn 1*0 c^tn/o
1 n
i - 6
I .jC
-1^0
100%
List 2
VN=294^
Chance to hetit'ei" mvQAl f
91 £
ip . >
25.3
24. 0
To Ket trained in a skill
1 a
^ V • P
1 Q (\
ly
Zl . 0
17.4
Honey for college education
27 ^
14-4
To serve my country
9.6
9.1
9.3
6.8
1 was unemployed
6.i
8.3
9.0
11.9
To prove that ! can make it
5.7
6.6
7.1
10.2
To be away from home on my own
4.7
6.1
5.0
6.8
Earn more money
5.7
8.4
7.3
7.1
to get away from personal problem
1.7
2.0
1.8
2.4
Family tradition to serve
.8
1^5
2^0
lOOZ
100%
lOOZ
lOOZ
7
Table 4
Percent of recruits responding to forced-choice questions on most important
reason for enlisting by sex.
Sex
Male -Female
IN=4857) (N=522)
Reasons for Enlistment
List 1
To get trained In a skill 29.2 30.5
Money. fbrcbllegeeducatibh i7 .1 24.9
To serve my country H.5 7.5
i was unemployed _ _ 12.2 5.4
To prove that I can make it 9.5 ii.7
To be away from home on my own 6.6 7.5
Earn more money 6.0 3.8
Travel 4.4 4.2
To get away from personal problem 1.9 4.2
Family tradition to serve 1.5 0«4
1002 100%
(N=4878) (N=524)
List 2
Chance to be t ter my self 23.6 30 . 5
TO get. trained in a skill 19.5 19.8
Honey for college education 16.6 26.4
To serve my country 9.3 5.9
1 was unemployed 8.3 4.0
To prove that 1 can make it 7.2 6.9
To be away from hoihe oh iny own 5.3 4.0
Earn more money 6.9 4.2
To get away from personal problem 1.9 3.6
Family tradition to serve 1.4 0«6
100% 100%
Table 5
Percent of recruits respbridlng to fprced-chbice questions on most important
reason for enlisting by educational background of recruit.
Reason for enlistment
List 1
To get trained in a skill
Honey_ for college education
To serve my country
1 was unemployed
To prove that I can make it
To be away from home on my own
Earii more money
Travel
Tb_get away from personal problem
Family tradition to serve
List 2
Chance to better myself
To get trained in a skill
Money for college education
To serve my country
I was unemployed
To prove that 1 can make it
To be_away_from home on my own
£arn_ more money
To get away from personal problem
Family tradition to serve
Post
High School
Educational Background
aigh_School
Son -High
Schooii^rad
vN=oo5;
24.2
29.8
32.8
27 5
-1 7 - Q
5.9
9.1
11.7
12.2
117
lU • J
1 C iC
15.6
1 L
Q
12.8
5.5
7 9
6 3
5.5
5.0
3 1
1 - Q
2.3
lOOZ
i N=i ni^ 1
(N=881 )
24.8
22.8
28.8
16.9
20.0
20.5
23.2
17.7
6.7
7.1
9.4
9.6
8.6
7.4
9.6
5.9
7.0
9.4
3.7
5.7
5.2
5.6
7.1
6.5
3.3
1.7
1.9
lid
1.3
1.6
100%
100%
100%
19
in general, the data froo the forced questions on the most- ^
important reason for enlistment indicate that recruits frequently report that ^
the most important reason for their enlistment_was "a chance to better myself."
Because "skill training" has declined with ••chance" over the years aild because
"skill tiraihihg" gets the biggest increase when "chance" is not asked (See
tables_2-5), ••chance to better myself" is often interpreted as economic _
self-improvement, .Support for this interpretation comes from order-effect ___
research that found that "skill training" is the most frequently selected item
when it is asked before ••chance" while '^chance to better myself" is the most
frequently selected item when asked before •!skill^! £Boesel and Richards, 1982).
Ah alternative explanation is that "chance to better myself is just a nebulous
phrase that sounds good and is all things to all people.- However* we^^
hypothesized a third alternative; we believe "chance to better myself" does
have an exact, hbn-econbmic meaning. By using the powerful analyses available
for our multinomialmeasureswe feel we are on: the track of finding that
meaning. However, before discussing these analyses^ '^/e will briefly summarize
the cross tabulations of responses to the multinomial questions and some
additional cross tabulations used to check the internal validity of our survey
data.
Sfaltlnomit I Importance Ratings
Recruits were asked to ra!:e_ the importance of 28 reasons for enlisting on
a four-point scale. For each reason^ they indicated whether this reason was
"hot at all important," "somewhat important,'/ "very important/* or "I would
not have enlisted except for this reason." The data for the reasons that
received the highest importance ratings are shown in Tables 6-r8._The numbers
in the tables were obtaihed by cbmbihihg the percent of respondents who. _
indicated that reasonwas "very important" with the percent who indicated "i
would not have enlisted exceptf or this reason." As with the forced-choice
questions, differences in responses werefound for different demographic
breakdowns of the data. There are so many subtle differences in the data that
discussion of all of them is impractical; some of the larger differences will
be summarized below.
Table 6 shows. the percent. of respondents according to AFQT category.
Although there appears to be a good deal of similarity in the ivispdnses of the
recruits from the different AFQT categories^ chi square tests indicated that
there are statistically significant differences for most of the reasons
t£<.01J, "Chance to better myself was rated as being very important by all
categories of recruits, but there is a slight tendency for the recruitsirom
the lower AFQT categories tb give higher importance ratings to this factor as
compared to recruits from the higher AFQT categories. Importance ratings of
••skill training opportunities" was also moderated by AFQT category; recruits
from the lower AFQT categories are more likely to rate skill training as being
very important than are recruits from the higher AFQT categories^ the recruits
from AFQT categories I c.nd 11 were more likely to indicate that money for _
college education was very important than recruits from lower AFQT categories.
20
Table 6
Percent of recruits responding to multinomial questions on reasons for etiiistmeiit
by AFQt category classification.
AFQt Category
111 A — IIIB IVA/IVB
Reasons for eh ltsPiient
70.7 (2063) 71.0 (456)
62.1 (2000) 62.3 (453)
36.7 (1998) 37.3 (451)
49.5 (1367) 50.8 (303)
45.5 (2005) 47.6 (454)
44.4 (1372 47.4 (304)
39.5 (2001) 43.5 (457)
36.0 (1359) 38.0 (303)
27.4 (1996) 32.3 (455)
28.0 (2001) 29.1 (450)
* p<.01.
Number in parentheses represents sample size.
11
Em:
^Chance to better myself
^Sklll training opportunity
*Md'4ey for college
edtica tloh
^bearn to be responsible
mature
*Serve my country
Become more self reliant
Physical training
*Prove I can make it
*Mbhey f or vo tech/business
education
^£am more money
67.5 (2226)'*" 69.6 (1461)
48.0 (2226) 56.2 (1453)
62.1 (2224) 55.4 (1458)
37.7 (1457) 43.2 (968)
44.3 (2224) 45.7 (1466)
39.7 (1456) 42.1 (966)
41.0 (2221) 41.0 (1467)
28.8 (1455) 33.9 (966)
34.9 (2225) 36.6 (1464)
20.5 (2218) 25.3 (1460)
The percent of recruits who Indicated these reasons were very important
are presented by sex iii Table 7. As with the forced-choice questions, the
reader should be call tlohed that other factors may contribute to the sex
differences presented in Table 7 beMuse recruits must have a high
school education and be classified as GatSB or aboveoh AFQT to be eligible
for enlistment. (However, separate log linear analyses^ one including both sex
and AFQT as categorical variables, and another including sexand educational
background^ indicated no statistically significant 3-way interactions, )- In
general^ although female rectUits rated all the reasons presented in table 7
as being mbre.impbrtaht than male recruits^ the relative iinportance of the
reasons is similar- for bbthmalesand females That is, "chance to better
myself" had the highest percent of recruits indicating this was a very
iffipor tan t reason for both males and females, and "skill training" has the next
highest percent. Chi square tests indicated that there are statistically
significant differences M>tween male and female recruits for all of the reasons
listed in Table 7 except "pl^sical training".
Tables presents the percent of recruits responding to these questions
based on edurationai background. Chi square tests indicated that there are
significant differences for ail of the rMsbns listed in table 8* '^Chance to
better myself" was rated as being very important by ail the recruits, but this
was especially true for high school graduates. "Skill training" appears to be
less Important for recruits with post high school education and "college money"
is less important for non-high school graduates.
Internal _ Val idi ty- Check
By asking essentially the same questions in alternative formats^ it is
possible to assess the internal validity of our survey data by doing some
simple cross tabulations. The data in Table 9 represent the percent of
recruitswhb responded "very impbrtaht" or "would hot have enlisted except for
this reason" when they we m asked tb make importance ratings of these reasons
tabulated according to their reipons to the forcedrcboice question on reasons
for enlistment (List 2)*; For example, column one presents da ta from those,
recruits who chose "chance to better myself" from the forced-choice list; 83.3%
indicated "chance to better myself" was "very impoirtant" ur "1 would not have
enlisted except for this reason" when asked to rate the importance of this
factbr when It was presented in the Jiultihbmial format; 73.7% bf the these
individuals rated skill training as "very Important" or "1 would not have
enlisted except for this reason"^ and sb on.^ The data along the diagonal in
Table 9 indicate there is a great deal of consistency in recruits ' responses
to the two types of question format. The other data presented in the table
illustrate that there are indeed multiple reasons underlying recruits*
motivation to enlist.
Tible 7
Percent of recruits responding to muitinoraiai questions bh reasons for enlistment
by sex.
Sex
Reasons for enlistment
iiaie-
Female
*
Chance to better myself
70.0
(7462)+
76.0
(799)
*
Skill training opportunities
55.7
(7445)
62.5
(798)
*
Money for college education
46.6
(7444)
63.3
(797)
*
Learn to be responsible
44.7
(4980)
55.7
(529)
*
Serve my country
45.9
(7454)
40.4
(799)
*
Become more self reliant
43.4
(4987)
56.0
(527)
Physical training
41.3
(7468)
42.4
(800)
*
Prove i can make it
33.0
(4969)
38.2
(529)
*
Honey for vo tech/business education
31.2
(7453)
38.8
(798)
Earn more money
24.3
(7436)
26.9
(800)
* p<.01
Number in parentheses represents sample size
" 23
ERIC
Table 8
Percent of recraits respond! to muitinomial questions on reasons for enlistment
by educational background.
Educational Background
Post High School Non-High
High School Diploma Grad School Grad
Reasons f o r E nlistment
*
Chance to better myself
68.2
(1655)"'"
70.3
(5398)
63.6
(1322)
it
50.2
(1655)
57.9
(5388)
55.7
(1319)
ir
Honey for college edncatton
6i.l
(1658)
49.0
(5381)
28.5
(1319)
Learti to be responsible mature
38.9
(1081)
47.0
(3613)
48.2
(891)
*
Serve my country
39.0
(1660)
46.4
(5401)
48.4
(1311)
it
Become more self reliant
41.9
(1083)
44.2
(3613)
48.0
(895)
Physical training
42.0
(1655)
40.7
(5403)
43.6
(1328)
Prove I can make it
28.8
(1082)
34.7
(3601)
32.7
(892)
*
Hooey for vo tech/business
educa Cion
36.3
(1658)
32.5
(5389)
124.3
(1319
★
Earn more money
23.6
(1649)
25.5
(5390)
22.3
(1313)
+
p<.01
Number in parentheses represents
sample
size
Table 9
Percent of recruits responding to multinomial and f orced--choice questions on
reasons for enlistment.
Multinomial format
Forced-choice format
BettEer Skill College Serve My
Myself training Money Country
Unemjployed
Better Mys-lf
83.3*
53,
.7
40
.0
46.2
20
.2
Skill Training
73.7
78.
,7
45
.0
40.5
24
.3
College Money
64.2
53.
,7
88
.1
35. i
33
,3
Serve By Country
70.9
34.
,7
34
.6
83.4
12
.3
Unemployed
50.4
54.
9
34,
.5
36.6
72
.8
^Numbers Id table reflect percent of recruits responding "I would not have
enlisted except for this reason** combined with the percent of recruits
responding "very important."
15
The survey, included many other questions in addition to the questions oh
reasons for enlistment. In a further attempt to validate our data, we
tabulated recruits* responses to the forced-choice: question on reasons for
enlistment with a question that. asked them about their plans af ter enlistment.
These results, which are shown in Table 16^ indicate that recruits •
seliE** reports of enlistment motivation are consistent with their self-report of
plans after enlistment. For example, 45.7 percent of the recruits who plan to
go on to college af teti their enlistment^ chose "money for college" as their
most important reason for enlistment. Interestingly, 17.1 percent of the
recruits who plan a career in the army^ chose "service to country" as the most
important reason for enlistingi It is important to note that 37 percent of the
respondents (n=2,038) indicated they "did not know" what their plans after
enlistment would be.
We also cross-tabulated the responses to the forced-^choice question on
reasons for enlistment with a question that asked recruits to report their
employment status when they enlisted. These data ar| shown in Table 11. As
expected, recruits wh6_ indicated they were u at the time of
enlis^ent, were much more likely to choose "1 was unemployed" as the most
important reason for enlistment as compared to recruits who were employed or
attending school at the time of enlistment. Interestingly, the pattern of
responses to the forced-choice question on reasons for enlistment for recruits
reporting they were employed full time is very similar to the pattern of
responses for recruits reporting they were attending school.
Principal Components- Analyses^
As discussed previously, recruits have multiple reasons for wanting to
eiilist in the Army and in order to assess the relative importance of these .
multiple reasons we asked the recruits to rate the importance of 28 different
reasbhsi Many of these reasons were similar in nature. For example^ recruits
were asked to rate "I enlisted to be come a and "I enlisted
to learn to be a responsible, mature person." Obtaining responses oh sets of
similar questions permits the use of sophisticated statistical techniques such
as principal components analysis (PCA) that can reveal a great deal about the
underlying processes that may have generated the observed responses to this set
of questions.
Recruits* importance ratings of the 28 reasohs„f or enlis tment were
analysed using PCA to reduce the 28 reasons to a smaller set^ Principal
components analysis groups similar reasons together into "factors" (or
cbmpphehts) according to the degree of correlation between the reasons. After
the factors are "extracted" from the correlations between the separate reasons,
the factors are "rotated" to improve the interpretabili ty ot the factors.
26
table id
Percent of recruits responding to forced-choice question on Sbit important
reason for enlistment by their plans after enlistment.
Plans After Enlistment
eiviiian _ Career Don't
Employmen t College Vo/ tech Reenlist ^^rmy Know
(686)* (1027) (243) (530) (977) (2038T
Reasoif or enlistment
Chance to better myself
17.8
18.3
14.4
29.2
30.2
26.0
to get trained in a skill
27.6
11.4
18.5
18.5
18.9
21 9
Money for college education
6.7
45.7
21.0
8.9
6.9
12.0
To serve my country
hii
4.5
7.8
10.9
17.1
7.8
I was unemployed
15.9
3.9
9.5
7.0
6.8
8.2
To prove that, i can make it
6.9
4.1
7.4
9-1
7.1
8.4
To be away from home
on my own
5i5
5.0
6.6
6.2
3.5
5.8
Earn more money
8.9
4.9
9.5
6.4
5.7
7.3
To get away from personal
problem
3.1
1.6
4.5
2.3
1.2
1.9
Family tradition to serve
1.2
100%
.8
100%
— .8
100%
1.5
100%
2.7
100%
1.0
100%
^Sample Size.
ERIC
17
27
Table 11
Percent of recruits respbridirig to the forced-choice question on reasons for
eniistroent by their employment status when they enlisted.
Employment Status
Full
Time
Part
Time
Laid
oil
Fired
Quit
Looking Attending
lit dob School
(518)*
(575)
(286)
(69)
(296)
(129)
(639)
Reason ^r enlis tmen t
Chance to better myself
24
25
24
29
26
21
22
To get trained in a skill
19
21
19
17
22
18
18
Money for college
education
18
17
15
12
14
. 12
21
To serve iny country
11
8
7
4
7
5
11
I was unemployed
4
4
16
13
11
23
7
To Drove that 1 can
make It
8
. 7
7
7
7
10
8
To be away from home
oh my own
7
8
3
1
4
3
4
Earn more money
6
7
7
6
5
6
7
To get away form personal
problems
2
1
1
7
3
2
2
Family tradition to serve
1
1
1
3
2
0
2
^Sample size.
_„ W€ were_particn^^ the Interpretabillty of the
"chance to better myself** reason* As indicated in the discussion of the
forced-choice and multinomial questions » recruits tend to pick this reason as
their most Important reason for enlisting. It is hot clears however^ whether
this reason refers to ecbhbmlc improvemeht suc^ as _ *J€^rn more money** and "get
trained in a skill'* or self improvement such as **become a better individual.**
By uslag PCA iire (3n detemine_ whether ^^^*^^ to better myself** combines with
economic reasons. such as **eam more money** or with self-improvement reasons
such as "become a responsible, mature individual.** Ue predicted that the
"chance to better myself** reason would combine with other hoh^cbhpmic reasons
to form a "self improvement** factor. Cbhfirmatioh of this hypothesis would
support bur Iqrpbthesis that recruits are motivated to join the Army fbr bbth
economic and hbh-ecbhomic reasons. Although we recognize that "economic"
factors such as "earn mbre money** or "get trained in a skill" could also be
considered as_ways to improve one's self, we believe these motivational factors
can be distingalshed from factors that are more directly related to personal
growth and maiturity, such as "become a responsible, mature individual."
The principal components analysis indicated that thereare six distinct
factors underlying the 28 reasbhs for enlistment rated in the survey. [We
restricted the elgehvaltaes to 1.0 or more to_ ensure the stability of the
factors. 1 Table 12 shows the results of rotating the factors and allowing the
factors to be correlated (a direct quartimip oblique solution). The numbers
presented under the factor columns in Table 12, called "factor IbadingSi"
indicate the strength of the relationship between the individual reasbhs listed
in the left most column and the factors. Reasons loading positively on the
same factor tend to be impbr tab t to the same people;, the larger the factor
loading^ the stronger the relationship be tween the individual reason and that
factor^ The individual reasons in fable 12 have been ordered according to the
size of liieir factor loadings. Reasons that load on more than one factor
appear towards the bottom of the table. Factor loadings smaller than .25 are
generally not interpreted and have been removed. The right most column of the
table, labeled "shared variance" Indicates how well all of the factors
considered together account. for the variability for that individual reason.
These numbers provide ah indication of how well the PCA **fits** the data. A
general rule of thumb is that the individual variables (reasons in our
analysis) should have a shared variance estimate of at least .30.
The results of the factor analysis are very Interesting.^ We have labeled
the first factor in the solution *JSelf improveraent"i it includes "chance to
better myself" ahdseveral other reason^ which are re to self improvement
such.as "learntb be a responsible, mature individual," "become more self
reliant," "become a better individual," "need for discipline," "leadership
training," and **physical training."
The second factor in the sblutibh is ah economic factor^ which we labeled
"Economic advancement." It Includes reasons such as "obtain a better job when
I get out," "I was unemployed," **eam more money," and "obtain skill training."
19
29
table 12
Rotated factor loadings (oblique soiiitibn)
factors
Reasons for Enllstinent
I:- 11 III lif V yJ-:
Self -jconomic Military Time _ im''^^^. Stared
Improveioent Advancement Service Out Travel Variance
6et away on my m
Travel
A ^ Variance accounted for:
ERIC
.5238
Learn to be responsible.. - „ „ „ .
Becooie tore. self, reliant 0.771 - „ ^
Seconie. better individual
Need for discipline
teadership training „ „ .
Obtain better job - 0.652 - > '
I was unemployed - 0.6OO - - ' q 5
Earn: more money - o.564 - - ^' ' c
S^iil training - 0.532 '
Retirement benefits ~ 0.306 0.656 -- ^ '5^72
Fringe benefits i- 0.412 0.528 -- - ^ '
. Join old friends ^ ^ 0,553 „ ^ ' ^
0 Escape personal.problems - - O-538 - ^700
Family tradition - ^ 0.287 0^536 - . 5
0.815
mm
—
AM
0.771
—
mm
0.765
—
^m
0.685
mm
0.301
0.550
0.283
mm
O.o32
mm
^
-
0.600
mm
mm
/-
0.564
mm
mm
mm
/•
mm
0.532
—
—
/•
8.306
0.656
/•
0.412
0.528
--
—
—
—
0.699
—
mm
0.538
—
—
0.287
0.536
mm
mm
mm
—
0.745
y
mm
—
—
mm
—
mm
0.693
y
mm
mm
mm
mm
0.393
mm
m^
0.333
-0.280
0.370
0,326
0.494
mm
*•
-0.390
mm
/
0.358
mm
/
0,355
0.332
0.286
/"
0.350
•0.293
0.491
/
0.482
mm
mm
mm
0.362
mm
mm
mm
0.269
0.378
mm
mm
WW
/
0.324
■0;254
0.473
6.013
2.112
1.930
1.484
1.304
m
.5960
Money for college - - I i! .^^3
Money for vot2ch/ ''^"^
business school - ~ ^. „ m ■■ -
P"ve myself 0.393 =^ 0333 '
^"^f , - -0.280 0.370 o;326 ^
ebance to better myself 0,494 - - -0390 / ^
Make new friends 0.358 - „ y .' | '
- 0,355 0.332 0.286 ^ ]
V'^^" ^'350 -0.293 0.491 - - /
Physical training . 0.482 - « „ / •
See what military is like 0,362 ~ q jaq / '
5«t respect o,378 - J / '
Serve ray country 0.324 -0;254 0.473 - « / '!
.4991
31
zj-z?^®!?^^'^^ factor, ehich we; have iabeied "Hilitary service i". consists Sf
reasons that genetaliy deal with the desirablity of miiitary life in general.
For example, it includes "retirement benefits," "fringe benefits," "be a
soldier," and "serve my cbuhtryi"
Factor Itf was^ most difficult factor to name because several different
typss of reasons loaded on this factor. We have labeled it "Time out" because
l±is is consistent with most of the reasons thai loaded on this factor that
include the "take time out to decide future plans" reason. Other reasons that
had high loadings include "join old friends," "escape personal problems," and
"family tradition to server" Interestingly, "chance to better myself" has a
fairly high negative loading on this factor.
_ The last too factors were readily ihterpretable. The fifth factor has
been labeled "Travel." It includes "chance to travel," ind "get away from
home on my own." The sixth factor has been labeled "education money;" it
includes "money for college education," and "money for votech or business
education."
The stability of the PGA solution was tested by splitting the total sample
of recruits who had made importance ratings of all 28 reasons into too samples
according to the last digit of their social security number (odd versus even)
and then conducting separate; PCAs. These solutions were almost identical to
the solution presented in Table 12. Another analysis was also done on the
total sample in which the factors were rotated such that they remained
uncbrrelated Can orthogonal, varlmax solution) and the results of this analysis
appear in fable A-i in Appendix A. Very similar results were obtained using
the two different rotation methods. The similarity of these different analyses
suggests that the factor pattern shown in Table 12 is quite stable.
Principal components analysis (P^ was used to reduce the 28 separate
reasons for enlistment to a smaller set of more general reasons. The PCA used
to produce the pattern of results shown in Table 12 allowed the factors to be
correlated with each other. Because several of these factors are rather narrow
in scope, such as "Mucation money" and "Travel,!^ it is possible that further
reduction of these factors into an even smaller number of more general factors
would be meaningful. To explore this possibility, the correlations between
these factors^ called 'Jfirst-order factors," were used as input into another
PCA to identify "higher-order" factors that are br»>ader in scope. If our
hypothesis that recruits enlist for both economic and non-economic reasons is
correct, then then the "higher-order" solution should contain separate factors
that reflect the economic and self Improvement motivations for enlistment.
The correlatldns between the first-order factors are shown in Table 13 and
the results of the ••higher-order" factor analysis are shown in table i4i the
factors in this PCA wire rotated such that they could be correlated (i.e. , an
oblique rotatioh was usedj. These results indicate that there are three broad
factors which underlie the importance ratings of _ the 28 reasons and the :
first-order factor analysis, the first hlgherrbrder factor includes both the
"Self improvement" factor and the "Military service" factor identified ih_^^^^
first-order PCA. The second higher-order factor is an "Economic" factor and it
includes the "Economic improvement" factor and the "Education money" factor
identified in the first-order PCA . The third higher-order factor includes the
"Time out" factor and_the_ "Travel" factor froiL the first-order PCA. Ndte^
however, that the first-order "travel" factor also loads oh the higher-order
factor we have labeled "Self improvement."
Thus the results of both the first-order and the higher-order principal
compbheht aoalyses cbhfinn our hyp^^ that there are both economic and
nonr^economic reasons tmderlylng recruits' decisions to enlist. In the
firstorder PCA ^ six separate factors are fbcmed that reflect a variety of both
economic and self-improvement reasons^^ Furthermbre^.even in the higher-order
factor analysis when we attempt to form very broad factors^^ J^^P^^^^^^^^"
does not combine with "Economic advancement" which suggests that these are very
distinct reasons influencing the enlistment decision.
_ The results of the_hlgher-order factor analysis are particularly
interesting when we compare the results of PCAs conducted on comparable sets of
questions from the 1982 and 1983 surveys^ The_1983 survey only included 15
multinomial questions about reasons for ealistment, in cQhtrast_to_the 28
questions included in the 1983 survey, to compare the results from the
different years additional PCAs were conducted for: the 15 reasons that appeared
in both surveys. Oblique and or thpgbnal rotations produced similar solutions.
The factor loadings for these analyses that appear in Table 15 are from the
oblique solutions. The pattern of results for the two years are quite similar;
four factors were identified for both the 198*1 and 1983 da ta^ and three of
chese factors correspond fairly well with the three higher-order factors
identified wheii the entire set of 28 reasons was used in analyzing the 1983
data.
The first factor presented in Table 15, for both the 1983 and 1982
samples, is the "Self -improvement" factor which includes "Be a soldier,"
"Service to country," "Physical training,'/ "Prove I can make It," and "Want
respect," in addition to "Chance to bettermyseif ." The second factor for both
years is the "Time Out" factor which includes "travel" and "Get away from
home ^" as well as "Take time but to decide life plans." the third factor, for
both the I983_ahd 1982 samples^ is the "Ecbhbmic" factor which includes "Skill
training," "Earn more moneys" and "Unemployment." The fourth factor for the
1983 data is labeled "College Money;" whereas, the fourth factor for the 1982
data is labeled "Escape."
33
Table 13
Factor correlations for rotated factors
Factor
Self Economic
improvement Advancement
Factor
Military
Service
Time Education
Out Travel Money
Self Improvement
1.060
Economic
Advancement
0.073
1.000
Military
Service
0.27i
0.033
1.000
Time out
0.085
0.056
0.045
1.000
Travel
0.313
0.095
0.157
0.208
l.ODD
Education
Honey
0.146
0.152
0.040
■0.028
0.093
ERIC
Si
Table 14
Rotated factor loadings for higher order factor analysis.
Higher Order Factors
Mrst order
Factors
Military Service
Self Improvement
Economic advance
Education money
Time out
Travel
Self
Improvement
.777
.742
.457
Economic
.761
.745
Time
Out
Variance accounted for: 1.649
1.094
.887
.512
1.019
Shared
Variance
.608
.619
.588
.777
.547
.623
S5
Table IS
Comparison of factor loadings (oblique roUtloiil for 1982 and 1983.
1983 Sanpie (N«5,381)
I II
Self Time
Improvement Gut
Factor
iii
Econoailc
IV
College
Money
Reasons for Enlistment
Be a soldier
Service to country
Phy sical_ training
Want respect
Chance to better myself
time to decide
Away from home
Escape personal problem
Travel
Bnemployment
Earn more money
Skill trainiiag
Money for college
Family tradition
Prove
Variance accounted for:
I
Self
Improvement
II
Time
Out
Factor
ill
Economic
IV
Escape
teasoii fdir enlistment
Be a soldier.
Service to country
Physical training
Want respect
Prove myself
Get away from home
Time to decide
travel.
Uneinplbyment
Earn more money
Escape personal problems
Skill training
Family tradition
Chance to better myself
College money
Variance accounted for: 3.071
Shared
Variance
0.806
0.751
0.647
—
.5459
.4815
0.555
.4451
0.536
0.441
.5205
0.686
.4515
0.623
.4537
0.526
-0.395
.4549
0.502
.3913
0.735
.5628
0.680
.4868
0.519
0.507
.5258
0.387
0.608
.4949
0.272
-0.474
.3504
0.473
0.265
.4253
3.046
1.646
1.371
1.170
1982
Sample (N=2,885)
Shared
Variance
0.797
.6334
0.785
.6005
0.614
.5021
0.586
.4720
0.542
0.264
.4498
0.599
.4219
0.582
.3868
0.523
.3812
0.800
.6366
0.699
.5051
0.358
0.621
.5497
0.421
-0.570
.5013
e.267
0.510
.3541
0.487
-0.463
.4950
0.481
-0.322
.3488
3.071
ii588
1.402
1.179
The simiiarity of these results with those of the higher-order PCA on the
i 983 data prompted as to conduct- one additional set bf-PCAs* Using. the data on
the is reasonis that vrere rated in both the 1982 and 1983 surveys^ we ran
another set of PCAs ^ut this _ time we restricted the number of factors to three;
The results of thi^bblique rotation solutions are shown in Table A-2 in ^
Appendix A. The three factors identified in these analyses are very similar to
those identified in the higher-order PCA of the 1983 data.
The results of the PCAs indicate that there are three broad factors
underlying the importance ratings of the reasons for enlistment and^_ that_when _
additional reasons are added to the set it is possible to identify six distinct
factors. These six factors include both economic and non-economic reasons that
motivate young people to enlist in the Army. The next question we address is
whether a particular factor is characteristic of a particular subgroup of the
population.
Factor scores were generated for each recruit in order. to relate the
factors to various d^amographic variables. For our data, factor scores indicate
the degree to which each individual factor explains the variabltty in rach
recruits •importance ratings of the reasons for enlistment. The factor scores
were generated frbm the brthdgoM PCA (shown in Appendix A) so the factor
scores would be independent^- Thesefactorscores were used as the dependent
variables iEor a series of analyses of variance (ANOVAs) that used various
demographic variables as independent variables. _ The results of these analyses
are summarized in Table 16.^ The numbers presented in Table 16 are mean factor
scores that are ipxerpretable in a relative sense. That is, larger positive
numbers indicate that this subgroup of recruits tended to iiave higher scores on
this factor and larger negative numbers Indicate that this subgroup of people
has lower scores on this factor.
The ANOVA on recruits* factors scores on the "Self improvement" factor
indicated that educational background, sexj AFQT category, region of the
country ,_ length of enlistment termi and ethnic grbupali had a significant
effect-(£<*G0ii on_recrults* factor scores for the "Self improvement'V factor.
Recruits have higher scores on this factor ifthey have any of the following
characteristics: non-high school graduates, female, AFQT categories IIIA and
below, are from the southern or western regions of the country, enlisted for a
3-year term^ and list their ethnicity as "other."
The ANOVA on recruits' factor scores for the "Economic advancement" factor
indicated that AFQT category^ region of the country^ age at signing the
enlistment contract, and tera of enlistment. had significant ef fee on factor
scores for this factor. Recruits have higher scores on this if they
have any of the following characteristics: AFQT category IIIB/IV, from the
southeastern or mldwestern states, were between 19 an^ 21 when they signed
their enlistment contract, and enlisted for a 3-year term.
37
2(S
Table 16
Mean factor scores by demographic variables.
Factor
Self - Economic Military Time
improvement Advancement Service Out
^di]ca4:ion
Travel
Education
Money
NoH'^high school grad
High school grad
Post-high school
Sex
Male
Female
AFQT
CAT X
CAT II
eAT iilA
CAT IIIB
CAT IV
Region
Northeast
Southeast
Sou thues t
Midwest
West
Age at conlracting
if
18
i9
20
21
24
13
8
5
0
—1 £
—Jo
i
-2
-i
"A
7
1
JL
-13
-32
-5
6
-11
28
-i
-1
3
3
-2
-3
is
6
-35
-28
20
29
-25
-52
=i
5
-5
38
-6
-13
-4
-8
-i
42
«
0
-2
-6
-3
3
7
13
4
8
4
-27
0
30
2
22
i
-28
-2
-a
-4
3
-3
5
5
1?
-2
-9
-3
9
-12
5
b
-6
1
-8
13
-8
4
5
-2
3
-7
-3
-3
7
13
3
-13
i
-i
8
2
2
-2
-7
9
10
-10
4
13
-lb
-2
10
3
4
17
-4
3
-12
10
-7
13
3
-5
-24
2
14
2
22
-19
-48
8
table 16 (continued)
Factor
Self
Ecbhbmic
Military
i'ime
Educa
Improvement
Advancement
Service
Out
Travel
Mone;
Enila tmen t -Term
z yea r s
—JO
1 /
3 years
5
7
-4
2
-2
-5
4 years
-2
-5
10
-5
0
-4
Etimic Group
If nx ce
1
DiaCK
"1 /
7
- /
Q
aispaaic
*
H
7
l^t
0 tner
t 1
11
C
D
1^
Rgral/Brbaa
Large city
2
-6
-5
3
-5
8
Large cit^ suburb
b
-i
2
3
6
8
Medium city
6
i
-3
-1
4
5
Medium city suburb
3
6
-8
11
6
2
Small city
-3
6
3
-6
-A
-1
Rural
-3
2
2
-3
-1
-15
Farm
-2
-4
7
-3
6
-8
26
39
_ The ANOVA on factor scores for _ "Sill tory service" indicated that sex,
region of the country^ ^ term of enH and ethnic group all had significant
effects on„ the factor scores for this factor. Recruits have higher scores oh
this factor if they have any of the following characteristics: male ^ from the
southeastern states, enlisted for a 4-year term^ and listed their ethnicity as
"white," or "hispanic."
_ The factor scores for the factor we have labeled "Time out" were
sighificantljf affected by_ the following demographic variables; educational
background^ sex, AFQf category and age at signing contract. Male recruits^
non-high school graduates and recruits with some post-high school education,
recruits from the I, IIIB and IV AFQT categories, and IS-year-old recruits
tend to have higher factor scores for this factor^
The ANOVA on the factor scores for the "Travel" factor indicated that
educational bacfeground^ M^ region of the country and age at signing contract
all had sighif leant effects. Recruits scored higher on this factor if they had
any of the following characteristics: high school diploma graduates, female,
from_l*e northeastern, midwes tern or western states, and age 19 or younger at
the time they signed their enlistment contract.
The AHOVA on the factor scores for the "Education money" factor indicated
that the follow IhgL demographic variables had significant effects on the factor
scores for this factor: educational background, sex, AFQT category, term of
enlistment, and whether the recruit came from a rural or urban area. Recruits
had higher scores on this factor if they had any of thef bllowihg
characteristics: post-high school educa tion, female^ higher AFQT categories
(especially categories I and 11), 2-year term of enlistment, and if the
recruit came from a medium or large city or a suburb of a medium or large city.
TSe information in Table 16 can also be used to assesis the relative
importanf:e of the six different factors for a particular category of
individuals. Consider, for example^ term of enlistment. Recruits who signed
up for a two-year term have large,_positive factor scores for the Travel and
Education money factors and large negative scores for the Self improyemeht,
Economic improvement^ and Military service factors. This suggests that
recruits who enlist for two years are motivated to enlist because of travel
opportunities and the opportunity to obtain money for ±helr future education.
The largest factor score for recruits who signed up for a four-year term is for
the Military service factor. This suggests that this group of individuals is
strongly motivated by patriotic reasons and a desire to be part of the military
service.
EKLC
29 40
SUMMARY AND GONCLUSiONS
The purpose of this report was to summarize recent tlndings from a survey
administered to new recruits entering the US Army that indicate young people
are Joining. the Army for both economic and non-economic reasons. Our results
indicate that there a re a variety of reasons underlying a recruit's enlistment
decisionand that different types of individuals (e.g.» high school graduates
vs. non-high school graduates, males vs. females, etc.) are motivated to a
certain extent by different reasons.
Future research that attempts to explain enlistment motivation should be
based oh models that consider both economic and hbh-ecohpmic variables. New
modeling techniques need to be developed that can directly assess the relative
trade-offs between these two types of factors. _Fpr example, would prospective
enlistees be willing to accept jobs that would provide le88_ educational money
for when they leave the service If the jobs offered them challenging
opportunities for personal growth and self Improvement while they are in the
service? Will these trade-offs be strongly affected by the longterm career
goals of the enlistee? Although the noh-ecbhbmic factors are less tangible and
thus much more difficult to measure tba the ecohbmic factors^ biir data
suggests. that. these non-economic factors can be measured and should be included
in future models to provide a more complete understanding of enlistment
motivation patterns.
30
REFERENCES
Boesel^ D,P,^ 5 Richards^ j.A. (1982) Enlistment motivatibh In the
All-Volunteer force environment: A review of major surveys- £roceedings of
the^Atfa A nnaa3.x:onfereHce of the Military Testing Aasociaiton . 188-193.
Dale, C.J & Gilroy, C. (1984) DetermiDants of enlistments: A microeconomic
time-series view. Armed Forces S^Society . IQ, 192-210.
boering, Z.D.^ Crissaeri D.W. , & Morse, J.S. (1980a) 1979 DbD Survey of
Personnel E n terl n g ^iiitary Service : Wave 1 user's manual and codph^
(Rand Note N-i605-MRAL). Santa Monica ^ CA: The Rand Corporation.
DoeriSg, Z.D., Srissmer, D.H., & Morse, J.S. (1980b) 1970 PoELSnrvey of
Personnel Entering Military Servicer Jteve 2 aser's manual and codebook
(Rand Note N-1606-MRAL) ^ Santa Monica, CA: The Rand Corporation.
Elig, T.B. il983) Tfae=1982 DA Survey of Personnel Entering the A^iyx
Baclcgroun< U^ser's^manual^ and codebook (POTA WP83-3). Alexandria, VA:
Army Research Institute for the Behavioral and Social Sciences.
Eltg, T.W., Johnson^ R.M.^ Cade, P.A. & Hertzbach, A. (1984) The Army
Enlistmen t Decisio n: A n overvlew-of ARI^Reccui t Surveys, 1982 and 1983
(Research Report 1371)* Alexandria, VA: Army Research Institute for the
Behavioral and Social Sciences.
Paris, J.H. (1984) Economic and nbh-ecbhomic factors of personnel recruitment
and retention in the All Volunteer Force. Armed F orces & Society. 10.
42
31
solution
II m tV V vi
Hilltary Economic Time Education Shared
Service Advancement Out Travel Money fiariance
-- — — .6489
-- — ~ — .6262
.5928
0.327 - ~ .5238
0.350
0.575
0.529
.4916
0.274 - - 0.258 - .4533
-0.355 - - .4838
0.620 0.390 - -- .5672
~ -- — — .6012
— .4991
0.677 — — — .5042
0.586 - - - .4155
0.566 — — ~ .3945
0.549 , - = .4385
- Q.680 ~ ~ .4897
0.569 — ~ .3780
0.342 -- 0.501 -- ~ .3750
0.729 — .5960
0.263 — - 0.644 - .5351
0.849 .7369
— 0.783 .6668
0.266 — .3822
0.444 - 0.340 0.276 — .4195
0.425 0.366 ~ .4174
0.355 ~ .3825
— — 0.294 ~ .3723
0.288 — — — Si .3589
0.496 0.494 — -- ~ .5387
2.111 1.930 1.484 i.303 1.056
Table A-2
Factor loadings (oblique rotation), number of fictors restricted to three.
1983 Sample (N«5381)
R e ason ^or enlistment
Be-a soldier
Serve my couti try
Physica:, training
CMnce to better myself
Van t_ respect
Escape personal problems
Time to decide
Be away from home
Skill training
College money
Prove myself
Unemployment
Family tradition
travel
Earn more money
Variance accoMnted for
ERIC
Reason^^orenlis tmen t
Be a soldier
Serve my country
Physical training
Prove my self
Wani respect
Chance to better myself
Escape personal problem
Skill training
Earn more money.
Fainlly tradition
Honey f or _ college
Unemployment
Travel
Be away from home
Time to decide
Variance accounted for:
Self
Improvement
9.783
6.74i
0.669
0.549
0.328
in
Economic
6.286
0.649
0.438
-0.259
33
45
Shared
Variance
.6207
.5406
.4801
.5200
.4023
0.554
.3149
0.547
.3944
0.765
.4918
6.563
.2588
0.475
0.335
.4189
0.387
6.256
.2667
6.401
-6.328
.3122
0. Jlo
0.277
.2688
0.360
6.416
.3365
_
3.046
1.646
1.371
1982
Sample (N«288S}
fact6r
i
ii
III
Self
Time
Shared
Improvemeni:
Pot-
Economic
Variance
0.753
-6.276
.6629
0.727
.5336
6.680
. ^925
0.579
.4498
0.568
6.273
.4456
0.565
0.366
.4924
6.743
.5449
0.681
.5613
6.274
0.544
.3964
0.449
-6.285
.3176
0.264
.6715
6.264
0.489
.3358
6.381
i2465
0.494
.3375
0.498
6.660
.3669
3.071 _
1.588
1.463
861106
