Skip to main content

Full text of "ERIC ED276816: Towards an Understanding of Army Enlistment Motivation Patterns. Technical Report 702."

See other formats


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 



NOTICES 



PISTRiBUTION: Primary ^^^^^ has been made by ARI. Please addrns cdrre- 

. spondenos concerning distribution of reports to: U.S. Army Research Institute for the Behavioral 
5»nd Social Sciences, ATTN: PERI POT, 5001 Eisenhower Ave,, Alexandria. Virginia 22333<5600. 

FlNALzDISPOStTib^: Thjs report may be destroyed when it is no longer needed. Please do net 
return it to the U.S. Army Reseirch Institute for the Behavioral and Social Sciences. 



NOp: This report reflects the view of the author and does not represent official Army policy, 
position, or approwrl of its conclusions. 



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 



II. CONTROCtlNO OFFICE NAME AND J^OOR^S- 

U.S. Army Research Institute for the Behavioral 

and Social Sciences 

SOd J^Eisenhower ^^nue>^iiM:exandria, VA 22333-5600 



M. MONITORING AOENCY NAME ft ADORESSTIf mtmrmt fttm Controtting OUIcm) 



le. DISTRI8UTION STATEMENT (bt Ifif* JSepdrl) 

Approved for ptiblic release; distribution unlimited 



^BTORE COMPLETmO PORM- 



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 
221 



«2. Report oate 

J anuar y 1986 



13. NUMBER OF PAGES 

43 



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