Name (Last, First) _________________________________Practice Fi.docx

Name (Last, First): _________________________________
Practice Final Exam
ChE 2002 Introduction to Chemical Engineering Computing
Part 1 Circle all answers that are correct; there can be 0 to 5
correct answers.
1. (5 points) Which of the statements below is true?
a) A subroutine cannot open a message box
b) A subroutine can only return ONE value to an open
spreadsheet
c) A subroutine can insert a new spreadsheet
d) A subroutine cannot use a function
e) A subroutine can use either a function and/or another
subroutine
2. (5 points) Which of the statements below is false regarding
Macro Recording?
a) The macro recorder creates a subroutine that can format a
table
b) The macro recorder creates a function that generates a plot in
an open worksheet
c) The macro recorder creates VBA code that can calculate a
formula by using values from a spreadsheet
d) The macro recorder creates VBA code for a user-defined
function within a subroutine
e) The macro recorder creates a subroutine that assigns a
variable type in a message box
3. (10 points) If the VBA code below was complete, what is the
value of TodaysValue assuming ? Show the calculation the
computer would do.
Dim Values(1 To 10, 1 To 10) As Single
For i = 1 To 10

For j = 1 To 10
Values(i, j) = (i+50) / (k * j)
Next j
Next i
TodaysValue = Values(3, 2)
After the code has executed what is the value of the variable
TodaysValue?
TodaysValue = __________
Part 2 Programming Exercises
Note: Prepare all of your programming solutions in ONE Excel
workbook. Put EACH PROBLEM on a SEPARATE
WORKSHEET. Save the workbook with your name, for example
Last First Final Exam.xlsm. Submit your Excel workbook on
D2L in the electronic drop box designated for the Final Exam.
Problem 1 (20 points)
Using Sheet1 of your Excel workbook, write a user defined
function with an statement to evaluate the following function,:
Use your user defined function to plot fromto .
On Sheet2 of your workbook, find the number of real roots of
the following polynomial using a user defined function:
Remembering that the number of real roots equals the number of
times the polynomial crosses the x-axis, find the roots by
plotting the polynomial on the interval . List the number and
approximate value of the roots you find:
1. Number of real roots = _________________________
2. Approximate value of roots =
______________________________________________

The Maclaurin series for the inverse hyperbolic tangent is given
by
Using Sheet3 of your workbook, create a UserForm that allows
the user to
1. Choose the option to write the nth term of the series on the
worksheet
2. Choose the option to write the sum of the first n-terms on the
worksheet
3. Make the OK CommandButton and the OptionButton for the
sum of the n-terms as the default buttons
4. Create a button on the spreadsheet that starts the UserForm
For use your program on Sheet3 to calculate:
1. The value of the 10th term in the series:
____________________
2. The sum of the first 10 terms in the series:
___________________
79© 2007 Palgrave Macmillan Ltd 0967-3237 $30.00 Vol. 15, 2,
79–92 Journal of Targeting, Measurement and Analysis for
Marketing
www.palgrave-journals.com/jt
INTRODUCTION
According to the 2004 Voluntary Support of
Education Report, contributions to colleges and
universities in the United States increased from
$ 19.5bn in 2000 to $ 24.4bn. 1 From this amount,
48.8 per cent came directly from individual
donors (alumni and nonalumni) 2 which seem to
play an important role in total giving. Several
models of giving behaviour have been developed

in the fundraising literature 3 – 6 in order to explain
how, when, where and why people make
donations.
Giving to athletic programmes presented the
greatest percentage increase in universities the last
few decades. 7,8 Athletic programmes constitute a
means by which people can identify with an
institution and enhance the emotional ties with
their alma mater. 9 To gain a better understanding
of why some people make donations to
intercollegiate athletic programmes, motives for
athletic giving have been investigated. A plethora
of donation motives have been identifi ed in the
literature such as: tax deductions, priority seating,
professional and social contacts, special parking,
attendance of athletic events, the quality of the
university ’ s academic and athletic programmes,
complimentary programmes, license plates,
membership plaques, decals, hospitality rooms,
trips, priority on tickets for away games and bowl
games and a successful football team. 10 – 14
Although several motivation factors have been
identifi ed in the athletic fundraising literature, no
Correspondence: Rodoula Tsiotsou,
Department of Commerce & Advertising,
School of Business & Economics,
Higher Technological Educational Institution,
N. Plastira 57 Lykovrisi,
Athens TK 14123, Greece.
Tel: 0030-210-2849584;
Fax: 0030-210-2849584;
E-mail: [email protected]
An empirically based typology of

intercollegiate athletic donors:
High and low motivation scenarios
Received (in revised form): 2nd March, 2007
Rodoula Tsiotsou
received her PhD from Florida State University and is currently
an assistant professor of Marketing at the Department of
Commerce and
Advertising, School of Business and Economics, Higher
Technological Educational Institution, Crete, Greece. Her
primary research interests are
marketing nonprofi t organisations, leisure services marketing
(sport, tourism and arts), product promotion (sponsorship-
advertising) and consumer
segmentation.
Keywords donor segmentation , motives , non-profi
t marketing , involvement , values ,
athletic donors
Abstract The purpose of this research is to study the donors
of athletic programmes in order to
delve deeper into their motives, to gain a better understanding
of this market and to improve
marketing of nonprofi t athletic programmes. Specifi cally, the
objectives of the study were: (a) to
develop a measurement instrument on athletic donors ’
motivation, (b) to segment athletic donors
based on their motives, (c) to better profi le donor motivation
segments by using sociodemographic,
psychographic and behavioural data. The results of the study
provide several theoretical and practical
implications in identifying homogeneous athletic donor
segments, in predicting and enhancing
motivation, in increasing marketing effectiveness and boosting
donations to athletic programmes.

Journal of Targeting, Measurement and Analysis for Marketing
(2007) 15, 79 – 92. doi: 10.1057/palgrave.jt.5750037
Tsiotsou
Vol. 15, 2, 79–92 © 2007 Palgrave Macmillan Ltd 0967-3237
$30.0080
serious attempts to develop an instrument for
measuring donors ’ motivation have been made.
One goal of the current study is to fi ll this gap in
the literature. Moreover, no much data exists in
identifying homogeneous groups of donors of the
same cause but usually donors are categorised
according to the type of donation (eg money,
bequests), 15 their gender (males vs females) 16 or
cause they support (eg religious organisations,
universities, hospitals). 17 Furthermore, this study
contributes to the donor segmentation literature
by proposing the consolidation of
sociodemographics, behavioural variables and
psychographics in order to better identify and
profi le donors of athletic programmes. Previous
segmentation studies combined either
sociodemographics with behavioural variables, or
sociodemographics with psychographics, or
behavioural variables with psychographics. No
previous research has been identifi ed to
incorporate these three elements into a single
donor segmentation study.
The purpose of this research is to study the
donors of athletic programmes in order to delve

deeper into their motives, to gain a better
understanding of this market and to improve
marketing of nonprofi t athletic programmes.
Specifi cally, the objectives of the study are: (a) to
develop a measurement instrument on athletic
donors ’ motivation, (b) to segment athletic
donors based on their underlying motives, (c) to
better profi le donor motivation segments by
synthesising sociodemographic, psychographic and
behavioural data.
The paper is organised in fi ve parts. First, the
conceptual framework of the study is presented
followed by the methodology employed. Then,
the results are reported and discussed along with
their theoretical and practical implications. Finally,
the paper concludes with the limitations of the
study and future research recommendations.
CONCEPTUAL FRAMEWORK
As donations become an integral part for the
existence and operation of nonprofi t organisations,
various schools of thoughts emerged over the last
few decades. These notions come from scientifi c
fi elds such as economics, marketing, sociology and
social psychology, and attempt to explain why and
how people decide to contribute to different
causes. Charitable, econometric, marketing and
combined models have been introduced with the
fi rst two addressing only certain aspects of giving
behaviour. Charitable theories posit that donors
are motivated by philanthropic and empathy –
altruistic feelings 18,19 where people make
donations to help the needy and deprived
regardless of the benefi ts that come to them in

return. The econometric models suggest that
giving is a function of variables such as income,
tax deductions, age and gender. 20 – 23 Sargeant 24
introduced a model of donor behaviour by
incorporating theories from a variety of
disciplines such as marketing, social psychology,
economics, anthropology and sociology, whereas
Brittingham and Pezzulo 25 combined econometric
and charitable models to develop the ‘ impure
altruism ’ model.
Marketing theories, however, provide a more
comprehensive explanation of giving behaviour
than charitable and econometric approaches.
Marketing models are based on exchange /
relationship marketing theories 26 – 29 where
donation behaviour is perceived as an exchange
relationship between donors and nonprofi t
organisations. Although giving to a nonprofi t
organisation ‘ may appear to be a one-way action
with the donor giving his money but receiving
nothing in return, … … donors may receive other
returns for their gifts ’ . 30 An exchange relationship
between nonprofi t organisations and their donors
exists where a party offers a value to other in
exchange for value. 31 As Bagozzi stated ‘ all
exchanges involve a transfer of something
tangible or intangible, actual or symbolic, between
two or more social actors … . thing or things
exchanged may be physical (e.g., goods, money),
psychic (e.g., affect), or social (e.g., status) ’ . 32
Similarly, when donors offer value(s) (eg money,
time, gifts in kind), they expect to receive
value(s) for their donations (eg recognition,
prestige, social contacts, a seat in a football
game). Exchange is a theoretical area of much

relevance and importance to donation behaviour
that deserves as much attention as can be
engendered.
Empirically based typology of intercollegiate athletic donors
Marketing
Segmenting the donor market
Owing to fi erce competition in the nonprofi t
arena, donor segmentation can be proposed as
a strategic marketing weapon to effi cient use
of resources by categorising donors into
homogeneous groups and targeting the most
profi table segments. Segmentation is an
appropriate marketing strategy for charities in
contrast to mass (undifferentiated) marketing
because it saves costs and provides information for
effective fundraising. Because nonprofi t
organisations have limited resources (eg fi nancial,
personnel), donors are very sceptical when a large
portion of their contributions are spent on
fundraising and administrative activities instead on
the cause itself. 33 – 35 Thus, the increasing diversity
of appeals used by hundreds of thousands of
nonprofi ts soliciting support in combination with
donors ’ gradual metamorphosis into sophisticated,
selective and discriminating individuals, make
donor segmentation an imperative strategy for
effective non-profi t marketing.
Various segmentation criteria such as

sociodemographics, behavioural and
psychographics have been employed in the
literature in order to identify distinct donor
groups. 36,37 Sociodemographics such as age,
gender, income, residency, religion and education
have been considered important determinants of
giving behaviour, 38,39 though some scholars argue
that age and gender do not discriminate between
donor segments. 40 Research results on the effect
of gender on donation behaviour are inconsistent.
Some scholars have shown that female donors
differ from their male counterparts in the amount
of donation, 41,42 the types of nonprofi ts
supported, 43,44 their motivations 45,46 and
frequency of giving, whereas others report no
differences. 47,48 Age infl uences the amount and
frequency of giving as well as the type of
donations and charity organisations. 49 Income
determines frequency of giving, 50 amount of
donation 51 – 53 and type of nonprofi t organisations
supported. 54
Behavioural segmentation provides information
on the donation behaviour (donors vs nondonors),
donation level (actual amount or gift donated),
frequency of giving and types of nonprofi t
organisations supported. Usually,
sociodemographics are studied in relation to
behavioural segmentation criteria for identifying
the most profi table segments and for prediction
purposes. 55 – 57 Very often, however, actual donation
behaviour is diffi cult to measure because either
nonprofi t organisations are reluctant to release
such information or in self reporting donation
behaviour, social desirability bias is detected.

Psychographic segmentation criteria are
employed to understand why donations are made
and often refer to donors ’ perceived benefi ts and
motives. 58,59 Psychographics are postulated in
Sargeant ’ s 60 model of charity giving as intrinsic
determinants encompassing need for self-esteem,
guilt, pity, social justice, empathy, fear and
sympathy. Owing to conceptualisation and
operationalisation diffi culties associated with the
above motives, the author, however, recommends
the use of extrinsic determinants (eg age, gender,
income) as segmentation criteria. Based on social
exchange theory and its cost – benefi t notion,
Barnes and McCarville 61 tested a structural
equation model of donor behaviour and found
that incentives are associated with charitable
giving. Incentives in their study were material
(tangible rewards with an associated monetary
value), solidary (rewards related to a sense of
group membership) and purposive (feelings of
contributing to an important cause or assisting to
achieve a worthwhile goal).
Odendahl 62 based on motivations and donor
characteristics distinguished major donors into
four categories: ‘ the dynasty and philanthropy ’ , the
‘ fi rst generation man ’ , ‘ the lady bountiful ’ and ‘ the
elite Jewish giving ’ . Cermak et al . 63 also identifi ed
distinct benefi t segments of major donors named
‘ affi liators ’ (motivated by social ties and
humanitarian factors), ‘ pragmatists ’ (motivated by
tax advantages), ‘ dynasts ’ (motivated by family
tradition) and ‘ repayers ’ (benefi ted directly or
indirectly from the nonprofi t), using family
tradition, being a benefi ciary, social affi liation,

orientation of nonprofi t, humanitarianism, tax
advantages, communitarianism and being needed
as motivating factors.
Motivation and benefi t-based segmentation
have been recognised in the literature as more
Tsiotsou
$30.0082
powerful approaches in identifying distinct donor
groups than sociodemographics, 64,65 though the
former encompass several theoretical and practical
constraints. 66
Research on motives of athletic
donors
The large defi cits under which most athletic
programmes operate resulted in acquisitions for
funds from alumni and nonalumni in the form of
donations. Suggs 67 found that the average defi cit
for half of the Division I athletic departments has
reached $ 3.3m, while Fulks 68 reports that athletic
fundraising accounts for 18 per cent of the total
revenue generated by NCAA Division I-A
athletic departments. Collegiate athletics constitute
an expensive component of higher education
creating disputes between two camps of thought
regarding their role and importance. Some argue
that though athletic fundraising brings new
donors to an institution, such recruitment is

coming at a price to academic programmes
giving. 69,70 Others, however, believe that athletic
programmes (especially the successful ones)
provide universities with a ‘ brand name ’ , 71 a mean
for attracting nonalumni contributions 72 and may
assist in increasing giving to academic
programmes. 73
Plethora factors that motivate giving to
intercollegiate athletics have been reported in the
literature. To improve the quality of the athletic
programme, to promote the image of the
university and the state, to provide an educational
opportunity for young people, priority seating in
athletic events, special parking, priority on tickets
for away games and bowl games, decals,
hospitality rooms, license plates and membership
plaques are some of the underlying motives of
athletic donations. 74,75 Billing et al . 76 identifi ed
four potential motives for contributing to
athletics: social (to attend sport events with
friends and family), success (of the athletic
programme), benefi ts (priority in tickets, parking)
and philanthropic (for student scholarships).
The effect of successful athletic programmes
(mainly football and basketball) on charitable
contributions constitutes the most controversial
issue in the athletic fundraising literature
attracting much attention. Some scholars argue
that success or failure of the football and
basketball teams are associated with fl uctuations in
alumni giving, 77 whereas others do not support
this notion. 78,79 The majority of available
literature substantiates a direct positive effect of

winning athletic programmes on charitable
contributions to educational institutions. 80,81
Much emphasis has been given to tangible
motives for giving to athletics, whereas intangible
motives have not attracted equal attention.
Motives such as identifi cation and emotional
attachment with the institution or the athletic
programme should also be considered 82 when
studying athletic donations. People with strong
positive feelings toward an institution and / or
programme are motivated to support them
fi nancially. 83 Feelings of identifi cation 84 and
empathy 85 are also positively related with alumni
involvement and charitable giving. Thus,
intangible motives require further research and
their role in athletic giving needs to be examined.
Although the above studies provide valuable
insights, they convey several limitations, usually
not mentioned in the literature, justifying further
investigation. Common limitations often
mentioned in athletic fundraising studies refer to
the use of samples coming from only one
nonprofi t organisation and to not measuring
actual donation behaviour (real amount of money
donated). It, however, became apparent during
this course of literature review that many studies
on athletic giving lack a sound and clear
theoretical framework (theories or models), a
main weakness of this stream of research
disregarded by athletic fundraising scholars so far.
Most studies are confi ning their ‘ conceptual
framework ’ to reviews of historical facts and
reports on research fi ndings often leading to weak
conceptualisations and operationalisations of

constructs and contradictory results. In addition,
the extant literature on athletic giving postulates
the lack (a) of an instrument to measure the
underlying motives of athletic donors, and (b) of
a common consensus as to what motivates giving
to athletic programmes.
This research attempts to fi ll this gap and
overcome some of the previous studies limitations
Marketing
by proposing exchange theory as the underlying
rational for explaining athletic giving and to
explore various motives in order to create a
reliable motivation measurement instrument.
Motives are defi ned here as factors that prompt
people to initiate athletic giving, infl uence their
choice of giving and make them persist in
athletic giving over time. The aim of this research
is to derive some fundamental theoretical
dimensions that might assist in increasing our
understanding of athletic giving and to employ a
more sophisticated segmentation approach.
METHODOLOGY
This study utilised the survey research method to
explore athletic donors ’ motivation. An
anonymous questionnaire was sent by mail to 800
athletic donors of a large eastern university in the

United States. The questionnaires were coded and
mailed to the donor through the Foundation
offi ce ( n = 400) and the Boosters offi ce ( n = 400)
after receiving approval by the Human Subjects
Committee of the university. Donors of the
Foundation offi ce donated to both academic and
athletic programmes, whereas the Boosters
subsample consisted of people who donated only
to the athletic programme. Simple random
sampling techniques were used to gather
information. From the 387 returned
questionnaires, 383 valid questionnaires were used
in the study (47.8 per cent response rate). The
code of the received questionnaire assisted in
identifying the amount of annual donation of
each respondent through the Foundation ’ s and
Boosters ’ fi nancial records while securing donors ’
anonymity.
Instrumentation
The questionnaire used to gather the data of the
study consisted of fi ve parts. Part I measured
motivation (15 items, 5-point scale,
1 = unimportant, 5 = important). Part II gathered
demographic data, Part III measured involvement
with the athletic programme, Part IV measured
donors ’ values and Part V gathered data on giving.
The revised version of the Personal Involvement
Inventory 86 was used to measure involvement
ten items, 7-point bipolar scale), whereas the list
of values (LOV) developed by Kahle 87 was
employed to measure donors ’ values (nine items,
9-point scale, 1 = not at all important,
9 = extremely important).

RESULTS
Demographic profi le
A preliminary analysis of the demographic
characteristics of the sample showed that 70 per
cent of the respondents were males, whereas 30
per cent were females. In terms of their
education, most of the respondents held a
graduate degree (48.1 per cent), many completed
college (45.2 per cent) and few had some college
education (4.4 per cent). Regarding household
income, 39.8 per cent of athletic donors had an
income between $ 50,000 and $ 99,999, 18.6 per
cent had an income between $ 100,000 and
$ 149,999 and 17.9 per cent had an income larger
than $ 200,000. In terms of giving, the sample
under investigation donated to the athletic
programme from $ 20 to $ 10,800 annually. The
majority of respondents (28 per cent) donated
$ 50, 18.7 per cent gave $ 25 and 16.9 per cent
contributed $ 1,000 per year.
Factor analysis
An exploratory factor analysis was used to
identify the underlying structure of the 15 items
refl ecting various aspects of motivation. The
Kaiser – Meyer – Olkin test measuring the adequacy
of sampling produced a value of 0.865 larger than
the cut-off point of 0.60 and provided evidence
that the sample used for the study was adequate.
Moreover, the results of the Bartlett test of
sphericity ( p = 0.000) indicated that the factor
model is appropriate for the data set. Based on
Kaiser ’ s rule of selection (eigenvalues larger to 1),
four factors were extracted (explained variance
56.2 per cent; p -value for fi t test = 0.000; chi-

square statistic = 2698.768, 11 residuals (10 per
cent)) ( Table 1 ).
An oblique rotation (delta = 0) was chosen
because of the theoretical expectation that the
resulting factors would in reality be correlated.
The factors were labelled as belongingness , trusting ,
social-practical motivation and prestige . Construct
Tsiotsou
$30.0084
reliability of the motivation factors was tested
using the Cronbach alpha. The alpha values,
ranged from 0.722 to 0.899, indicating that the
measures of each dimension are reliable. The
correlations between the factors ranged
from − 0.436 to 0.575.
Cluster analysis (K-Means)
To segment donors of athletic programmes,
cluster analysis (K-Means) was used on the four
motivation factors. Two segments were extracted
from the analysis. Based on their mean in the
four motivation factors, the two segments were
named as low motivation and high motivation.
The low motivation segment represented 32.11
per cent of the sample, whereas the high
motivation segment represented 67.89 per cent of
the sample. To validate the two-cluster solution,
cluster membership was related (one-way

ANOVA and Duncan multiple-range test) to the
original four motivation factors. Between groups
and within groups differences were tested using
one-way ANOVAs ( Table 2 ). Cluster means were
found signifi cantly different on all four factors at
the 0.05 level.
Multivariate analysis of variance
As it has been recommended, the best way to test
the cluster solution is to validate the clustering
solution on a set of external variables different
from those used to produce the clusters. 88 By
doing so, the external validity is demonstrated
while the segments can be better profi led. Thus,
to assess the validity of the two motivation
segments identifi ed, multivariate analysis of
variance (MANOVA) was employed. Amount
being donated, amount intended to be donated
the next year, values, involvement with the
athletic programme and household income were
the dependent variables of the MANOVA analysis
( Table 3 ). A MANOVA was conducted with
follow-up ANOVAs. The overall multivariate null
Table 1 : Factor loadings for motivation
Factor 1 Factor 2 Factor 3 Factor 4
Factor 1:
Belongingness
Being associated with the school 0.930
Identify with the university 0.774
Being affi liated with the university 0.754
Being loyal to the school 0.541
Being part of a successful athletic programme 0.430

Keep up with the tradition 0.422
Factor 2:
Trusting
Believing in the vision of the institution − 0.836
Believing in the leadership of the university − 0.728
Factor 3:
Social-practical motivation
Social contacts 0.838
Professional contacts 0.746
Meeting friends 0.558
Priority seating in football games 0.416
Tax deductions 0.380
Factor 4:
Prestige
Increasing the prestige of the university through
a quality athletic program
0.880
Supporting a high prestige institution 0.539
Eigenvalue 5.740 2.174 1.178 0.945
Variance (%) 33.108 9.711 9.765 3.660
Cumulative variance (%) 33.108 42.819 52.584 56.244
Cronbach’s alpha 0.858 0.899 0.722 0.787
Number of items (total=15) 6 2 5 2

Marketing
hypothesis (H 0 : population mean vectors are
equal), tested to determine if any differences
existed within the groups in the dependent
variables, was rejected (Wilks � = 0.850, p = 0.000;
Hotellings test = 0.176, p = 0.000).
Thus, it was concluded that the two motivation
segments differed in relation to the dependent
variables. Univariate F -tests were run for all sets
of groups on the dependent variables to
determine where the differences existed.
Signifi cant differences between groups on three
out of the fi ve dependent variables were detected
( Table 2 ). Amount donated, donor values and
involvement with the athletic programme were
signifi cantly different in the two motivation
segments. A further analysis on the LOV indicated
that the two motivation segments did not differ
in values such as fun and enjoyment of life
( F = 2.675, p = 0.104), security ( F = 0.626,
p = 0.430) and warm relationships with others
( F = 0.545, p = 0.461). The low motivation
segment, however, differed from the high
motivation segment and scored lower in values
such as sense of belonging ( F = 14.369, p = 0.000),
excitement ( F = 8.897, p = 0.003), self-fulfi llment
( F = 5.417, p = 0.021), being well respected
( F = 5.152, p = 0.025), self-respect ( F = 4.907,
p = 0.028) and a sense of accomplishment
( F = 4.628, p = 0.033).
DISCUSSION
Theoretical implications

The purpose of the present study was to gain a
better understanding of athletic donors in order
to improve fundraising strategies. In general, the
results of the study are signifi cant for theoretical
and practical reasons. The study takes a useful
approach that could assist athletic fundraisers in
identifying valuable segments effectively by using
motivation as the main segmentation criterion.
The results of the study provide evidence that
motivation is a key criterion in identifying
distinct donor segments of the same cause
(athletic programmes). A useful measurement
instrument of athletic donors ’ motivation has
been developed that could assist in identifying
homogeneous athletic donors segments and
predicting different motivation levels. The
consolidation of various types of variables to
profi le athletic donors segments, the use of an
adequate sample size ( n = 383) and the use of
objective data (actual amount being donated) to
reduce the amount of same-source bias benefi ted
this study. The combination of sociodemographics,
psychographics and behavioural variables proved
to be a powerful tool to identify and better
describe donor segments justifying future
replications. Moreover, the study provides several
Table 2 : Cluster analysis results ( N =383)
Factor Low motivation
segment (32.11%)
High motivation
segment (67.89%)
F Signifi cance

Belongingness 3.34 4.28 191.750 0.000
Trusting 2.43 4.21 468.673 0.000
Social-practical motivation 2.40 3.08 45.935 0.000
Prestige 3.04 4.43 312.209 0.000
Table 3 : Descriptive statistics and ANOVA results on the
dependent variables
Dependent variable Low motivation segment High
motivation segment F Signifi cance
Mean Standard
deviation
Mean Standard
deviation
Amount donated 720.7 1235.6 1266.9 1968.6 6.426 0.012*
Amount to be donated 974.59 1738.2 2187.6 7254.2 2.668
0.103
Values 7.349 0.809 7.797 0.693 25.581 0.000*
Involvement 5.404 0.991 5.995 0.777 33.051 0.000*
Household income 3.666 1.268 3.823 1.394 0.864 0.353
*Signifi cant at the 0.05 level.
Tsiotsou
$30.0086

and important new insights into the relationship
between athletic donors ’ motivation and amount
of donation, future donation intentions, values,
involvement with the athletic programme of the
university and household income.
The instrument developed to measure athletic
donors ’ motivation extracted four factors and
produced satisfactory results. The motivation
factors were named: belongingness , trusting , social and
practical motivation and prestige . Belongingness refers
to motives related to identifi cation, loyalty to and
association with the university, and explained
most of the variance (33 per cent) in motivation.
Donors (alumni and nonalumni) make
contributions because they identify themselves
with the institution (identity salience) and aim at
keeping their bonds or building relationships with
it (commitment). Thus, donations might serve as a
vehicle to accomplish these goals and a mean to
declare their association and commitment to the
university.
Trusting is related to donors ’ trust on the
leadership and vision of the university explaining
9.7 per cent of the variance. Trusting indicates that
donors need to be confi dent about the reliability,
credibility and integrity of the university
(leadership of the institution) in order to provide
support. Moreover, the trusting factor might
represent shared values between donors and
institutions (believing in the vision of the
institution).
To support and increase the Prestige of the
university through athletics is the fourth

motivation factor explaining the least of the
variance in motivation (3.6 per cent). The small
variance explained by this factor can be
interpreted by its role associated with
organisational success and identifi cation, items
loaded in the belongingness factor. The correlation
between the two factors verifi es this assertion
(0.575). Prestige is an indicator of organisational
success, 89 and is associated with organisational
identifi cation defi ned as a sense of
belongingness 90 and identity salience. 91
Association with prestigious institutions assists in
bolstering self-esteem 92 justifying donors ’ attempts
to relate themselves to successful athletic
programmes and institutions.
The social and practical motivation factor consists
mainly of utilitarian, tangible motives (eg tax
deductions, priority seating), whereas the factors,
belongingness, trusting and prestige refer to intrinsic,
intangible motives (eg identify with the university,
increase prestige) and explain 46.3 per cent of the
variance in motivation. Thus, contrary to previous
fi ndings, the intangible dimensions of motivation
seem to play a dominant role in athletic giving
compared to its tangible aspects. The four-factor
solution, however, explained only some of the
variance of the construct (56.2 per cent)
indicating that other important attributes are
missing and improvements are necessary to
increase predictability and explain more of the
variance of motivation.
Although the four motivation factors explained
only 56.2 per cent of the variance, they were able
to provide distinct motivation groups and

predictability. Cluster analysis produced two
segments: athletic donors highly motivated and
donors less motivated. The hypothesis that
motivation will classify athletic donors was
confi rmed verifying the existence of different
motivation levels between donors of the same
cause. Highly motivated athletic donors scored
higher on all four aspects of motivation, whereas
less motivated donors scored lower. The results
showed that the largest segment (67.89 per cent)
consists of highly motivated athletic donors, and
less motivated donors constitute a minority in the
sample. Moreover, the mean scores of the
motivation factors manifested that the biggest
difference between the two motivation segments
exist in the second factor, trusting followed by the
fourth factor, prestige . Less motivated donors seem
to question the vision and leadership of the
university, lack trust and do not believe that their
fi nancial contributions to athletic programmes
would increase the prestige of the university.
Statistically signifi cant differences were found
between the means of the two motivation
segments in relation to the amount donated,
donors ’ values and involvement with the athletic
programme. The group means of the dependent
variables show that highly motivated athletic
donors donated larger amounts of money and
scored higher in the LOV than less motivated

Marketing
donors. Moreover, highly motivated donors were
more involved in the athletic programme than
less motivated athletic donors. This result confi rms
previous fi ndings on the importance of
involvement with university activities on giving
behaviour. 93 The largest differences between the
two segments were identifi ed in involvement with
the athletic programme followed by values. Thus,
involvement with university athletics (cause)
constitutes a signifi cant factor in motivating
giving confi rming previous fi ndings about the
relationship between involvement with a cause
and donation behaviour. 94 The fi ndings also
indicate that different motivation segments have
different values. Values such as sense of belonging,
excitement, self-fulfi lment, being well respected,
self-respect and a sense of accomplishment are
not as important to the low motivation segment
as they are to the high motivation segment. The
two motivation groups, however, perceive values
such as fun and enjoyment of life, security and
warm relationships with others equally important.
Because motives may reveal a person ’ s values, 95
similar values between the two segments might
explain donations to the same cause (athletic
programme), while different values might
represent differences in motivation. Donor values
are refl ected on their motives to give, infl uence
the strength of motivation and guide donation
behaviour.
Furthermore, this investigation revealed that
household income and future intentions to give

are not signifi cantly different in the two segments
manifesting the important role of motivation in
giving. Athletic donors of the study do not differ
signifi cantly in their capacity to give (household
income) but in their motivation to give. Thus,
motivation might be a more reliable predictor of
athletic giving at the low and medium donation
level than income.
The two motivation-based segments produced
from the study could be profi led as follow. The
low motivation segment consists of donors who
make smaller donations, are less involved in the
athletic programme of the university and score
less in the values instrument. The high motivation
segment consists of donors who contribute larger
amounts, are more involved with athletics and
appreciate more values such as sense of belonging,
excitement, self-fulfi lment, being well respected,
self-respect and a sense of accomplishment.
Alumni and nonalumni of the study did not
differ in their motivation, values, involvement
with athletics, household income and amount of
donation. Small differences were detected only in
the belongingness factor with alumni exhibiting
higher motivation than nonalumni. Owing to
large size inequality between the two groups
(non alumni represented only 8.7 per cent of the
total sample), these results should, however, be
considered with caution.
Practical implications
The practical implications of the study are several.
Fundraisers, usually confi ned to sociodemographic

information, can segment better their donor
market in order to increase their motivation and
plan more effective positioning strategies.
Motivation-based donor segmentation can benefi t
fundraisers in four ways: (a) provides the base for
target fundraising; (b) assists in developing more
effective marketing mixes in order to motivate
specifi c donor segments; (c) facilitates cause
differentiation; (d) targets marketing strategies
toward specifi c motivation groups; (e) shape
fundraising tactics to optimise results and (f)
provides easier identifi cation of fundraising
opportunities and threats. Identifying
opportunities for developing new products,
designing more effective fundraising strategies and
better allocation of resources could be some of
the benefi ts of targeting well-defi ned motivation
segments of athletic donors.
Moreover, the results of the study postulate
the need for employing relationship marketing
in athletic fundraising to build and maintain
long-term relationships with donors. To
accomplish longitudinal bonds, athletic fundraising
marketers need to keep donors motivated, built
trust, enhance their loyalty and increase
involvement with the athletic programmes of the
university.
Athletic fundraisers should base their
development activities and marketing strategies on
the motivations of the market segments that best
suit their institutional goals and values. The

Tsiotsou
$30.0088
proposed segmentation approach and the resultant
donor profi les are suggestive in substantiating and
enriching current athletic fundraising approaches.
The produced profi les of each motivation
segment can readily be used by fundraising
marketers to discriminate between donors, shape
up their relationships with athletic donors
accordingly and boost donations. Specifi cally,
marketing strategies should be designed to target
athletic donors highly motivated, donors of
academic programmes and those very involved in
the athletic programme of the university. Motives
such as belongingness , trusting , social and practical
motives and prestige should be emphasised in
fundraising appeals to attract prospects and retain
current donors. Because the need to be associated
and identify with the university is an important
motive, fundraisers should employ tools to
strengthen the ties between athletic donors and
the institution. Organising social events on a
regular basis where representatives of the
university (eg president, deans, athletic director)
will participate and interact with donors could
assist in this direction. During these events,
speeches should be given by the leadership of the
university presenting the vision of the institution
and clarifying administrative issues to assure
donors about their trustworthiness and integrity.
Because athletic donors are involved with
athletics, athletic events (eg golf tours or

basketball tournaments) where donors, university
athletes and / or coaches participate are also
recommended as a bonding tool. In addition to
events, web pages, e-mails, newsletters or
newspapers mailed regularly would keep donors
informed, increase their involvement with the
athletic programme and reassure them that they
constitute an integral part of the institution.
To increase motivation of the less motivated
segment, fundraisers need to provide this group
with more information about the leadership and
vision of the university and the athletic
programme. Information on institution ’ s vision
and leadership will increase donors ’ trust and
understanding, increase motivation and
involvement and consequently support. Because
the low motivation segment exhibits low
involvement with the athletic programme,
fundraisers should try to increase involvement in
this group by organising events, providing more
information about athletics and engaging them in
activities of the athletic department. For example,
to boost involvement, this group might be
allowed to attend football or basketball or baseball
practices once a month. Moreover, fundraisers
should not disregard different aspects of
motivation so they emphasise those during donor
recruitment and in all communication material
(eg website and pamphlets). Tangible and
intangible benefi ts derived from athletic donations
should be communicated to both motivation
segments and to all donor types (boosters and
foundation donors). Values (fun and enjoyment of
life, security and warm relationships with others)

equally appreciated by both motivation segments
could be conveyed in promotional fundraising
materials.
Athletic fundraisers need to address their
appeals to donors of the academic programmes
because this group might be more profi table
(higher income, larger donations). This group is,
however, motivated by prestige and might be
more demanding in relation to the quality and
integrity of the institution. To keep foundation
donors motivated, increasing the university ’ s
prestige should be presented as one of the main
aims of the fundraising campaigns. Prestige
increases the salience of a donors ’ university
identity which affects supportive behaviour
expressed as promotion of the university to others
and giving. 96 Because prestige is related
(indirectly) to giving, various actions should be
taken to enhance the prestige of the university
and its athletic programme. Obeying NCAA rules
and regulations so that the fame and image of the
university and its athletic programme are not hurt
by probations or fi nes is a way to assure donors
of the quality and high standards of the
institution. Communication of good athletic
records (eg number of athletic scholarships,
winning records, graduation rates of athletes),
success stories of student-athletes and alumni of
the university (eg current famous NBA or NFL
players) might also assist in increasing prestige.
Another tactic would be to enhance donors ’
perceived prestige of the university and its athletic

Marketing
programme by eliciting the support of celebrities,
especially of alumni celebrities.
Because boosters are motivated to give and are
involved with athletics but do not have the
capacity (income), a recommended strategy would
be to ask from them to offer time in addition to
money. Boosters could be asked to volunteer in
fundraising campaigns by offering time and work
to organise events or by communicating with and
cultivating prospect and / or existing donors.
Research has shown that ‘ motives for
discretionary collaborative behaviour are not
altruistic, but are rather utilitarian in nature ’ . 97
Thus, tangible (eg paraphernalia, football
coach autograph) and / or intangible (eg
acknowledgments during campaign celebrations)
rewards should be used to increase boosters ’
motivation to carry out volunteer work. The
application of a point system associated with
specifi c benefi ts (eg by raising $ 1,000 a donor
receives 10 points and deserves free parking in
basketball games, by raising $ 10,000 a donor
receives 100 points and deserves free parking in
football games) might also be a very effi cient way
not only to raise funds but to transform boosters
into effective (volunteer) fundraisers. Such tactics
will increase boosters ’ involvement with the
athletic programme and keep them motivated
since they become part of the fundraising process.

Athletic fundraising is expected to continue to
grow due to lack of state fi nancial support and
the enormous operational expenses of the athletic
departments. Competition will be intensifi ed in
the nonprofi t sector and effective marketing
strategies will become increasingly important.
Athletic fundraising organisations should
continuously improve their services in order to
maintain or increase donors ’ motivation and to
attract new ones. As a result, sound marketing
research is necessary as the nonprofi t sector
continues to grow and becomes more
competitive.
FUTURE RESEARCH
RECOMMENDATIONS / LIMITATIONS
Future research on athletic donors should focus
on longitudinal approaches in measuring
motivation changes and the relationship between
motivation and other variables (eg values, giving
and demographics). A better instrument
measuring athletic donor motivation needs to be
developed to explain more of the variance in the
construct by taking into account the unique
aspects of this donor market. So far, the intrinsic-
intangible dimensions of motivation have
been disregarded in the athletic fundraising
literature and did not attract much of researchers ’
attention. This research revealed the signifi cant
role of intrinsic-intangible motives justifying
further explorations. Moreover, a replication
of this study with a larger sample size and using
data from more than one university is
recommended.

It is conceivable that due to the complexity of
the giving pattern, donation models are diffi cult
to be built. Two different research methodologies
have been employed in the literature to explain
donation behaviour. Donation models are either
focused and tested only on one type of nonprofi t
organisations (eg religious organisations or
hospitals or athletic programmes) or take a more
integrative approach by synthesising various
criteria such as type of nonprofi ts (eg religious
organisations, hospitals, museums), donation
behaviour factors (eg amount of donation),
internal determinants (eg values, motives,
involvement with a cause) and external
determinants (eg age, income) in order to explain
giving in all kinds of situations. The fi rst approach
is widely used in the fundraising literature,
whereas the second one has not been embraced
by the majority of the academia due to
theoretical and practical constraints. The lack of a
general donation model justifi es future
investigations.
Particularly, in the athletic fundraising literature,
sound theoretical frameworks need to be
employed before testing hypotheses, and attention
should be given to construct conceptualisation
and operationalisation issues. Moreover, integrative
donation models are needed in order to explain
giving to athletic programmes. Athletic fundraising
literature indicates that research on the area is
limited to few selective factors and does not
create a complete picture for explaining athletic
giving. An evaluation and synthesis of previous

Tsiotsou
$30.0090
research fi ndings could lead to the development
of a comprehensive athletic giving model.
Theoretical value and practical relevance could
be derived from the fi ndings of this study, though
some limitations need to be mentioned. Social
desirability bias, a common phenomenon
associated with self-reports on sensitive issues such
as giving behaviour, is possible. In addition,
attempting to measure motives constitutes a
diffi cult task because motives are not primarily
cognitive and a person can have a motive to
behave ‘ without necessarily being aware of it ’ . 98
The sample frame employed in the study, athletic
donors of one educational institution, also raises
the question of generalisability of the fi ndings.
Thus, the results of the study refl ect only the
athletic donors studied, whereas interpretations
and generalisations should be made with caution.
Until these results are cross-validated in other
samples, it would be prudent to consider them as
exploratory. This study was intended to produce
meaningful data that would provide a tool and
data source on which quality marketing efforts
could be based.
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intrinsic motivation: The
theory of 16 basic desires ’ , Review of General Psychology
, Vol. 8 ,

No. 3 , pp. 179 – 193 .
cit .
op. cit., p. 108 .
98 Reiss ( 2004 ) op. cit., p. 79 .
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