PALMETTO REVIEW
2006
Published by the University of South Carolina Upstate
From the Editor
Quality is… .......................................................................................................... 1
Lilly Lancaster, University of South Carolina Upstate
Issues in Regional Development
The South Carolina Education Lottery: Determinants of Revenue ..................... 2
Robert T. Barrett & Robert E. Pugh, Francis Marion University
Business Education
The Role of Self-Monitoring in Job Search Success: A Field Study ................. 12
Kimberly A. Freeman, Winston-Salem State University
Management as A Liberal Art ............................................................................ 19
George S. Lowry & Edward D. Showalter, Randolph-Macon College
Factors Impacting One’s Desire to Telecommute:
An Investigation of Student Perspectives .......................................................... 25
Beth Clenney & Thomas E. Gainey, University of West Georgia
Accounting Practice
A Brief Review of the Sarbanes-Oxley Act of 2002 .......................................... 31
Gloria Clark, Winston-Salem State University
Wendy Meyers, Nova Southeastern University
Quality Initiatives ............................................................................. 37
USC Upstate is a member institution
of the University of South Carolina
PALMETTO REVIEW
Edited by
Lilly M. Lancaster, Ph.D.
William S. Moore Palmetto Professor in Quality Studies
School of Business Administration and Economics
University of South Carolina Upstate
Spartanburg, South Carolina
Volume 9
2006
PALMETTO REVIEW
Journal Audience and Readership
Palmetto Review is targeted toward both academicians and business professionals. The academic audience is interested in applied business-related research to use as a tool to enhance teaching and classroom
experiences for students. The professional/ practitioner audience is interested in sharing experiences about
a broad range of business-related topics. Topics for publication may be drawn from a variety of areas including manufacturing, service, government, health care and education. A section of the journal is devoted
to chronicling quality initiatives.
Journal Mission
Palmetto Review supports communication and applied research about business-related topics among
professionals and academicians in South Carolina and the Southeast.
Journal Content
Published annually by the University of South Carolina Upstate, the journal contains peer-reviewed
papers. All papers accepted are blind reviewed by at least two individuals. Letters to the editor and book
reviews may also be published.
Authors are discouraged from submitting manuscripts with highly statistical analyses and/or strong
theoretical orientation. Simple statistical analyses, tables, graphs and illustrations are encouraged. Please
see the “Guidelines for Authors” on the inside of the back cover of this journal.
Comments on published material and on how the journal can better serve its readers are solicited.
Contact:
Lilly M. Lancaster, Ph.D., Editor, Palmetto Review
William S. Moore Palmetto Professor in Quality Studies
School of Business Administration and Economics, University of South Carolina Upstate,
800 University Way, Spartanburg, S.C. 29303
Tel: 864/503-5597, Fax: 864/503-5583, E-mail: llancaster@uscupstate.edu
2006 REVIEW BOARD
School of Business Administration
and Economics
Jerome Bennett, Accounting
Richard Gregory, Finance
Faruk Tanyel, Marketing
Sarah P. Rook, Economics
Frank Rudisill, Management
University of Massachusetts
Joseph L. Balintfy, Professor Emeritus
PALMETTO REVIEW
Table of Contents
From the Editor
Quality is… ..........................................................................................................................1
Lilly Lancaster, University of South Carolina Upstate
Issues in Regional Development
The South Carolina Education Lottery: Determinants of Revenue .....................................2
Robert T. Barrett & Robert E. Pugh, Francis Marion University
Business Education
The Role of Self-Monitoring in Job Search Success: A Field Study .................................12
Kimberly A. Freeman, Winston-Salem State University
Management as A Liberal Art ............................................................................................19
George S. Lowry & Edward D. Showalter, Randolph-Macon College
Factors Impacting One’s Desire to Telecommute:
An Investigation of Student Perspectives ..........................................................................25
Beth Clenney & Thomas E. Gainey, University of West Georgia
Accounting Practice
A Brief Review of the Sarbanes-Oxley Act of 2002 ..........................................................31
Gloria Clark, Winston-Salem State University
Wendy Meyers, Nova Southeastern University
Quality Initiatives ........................................................................................................37
PALMETTO REVIEW
From the Editor
Quality is . . .
Variety. The ninth issue of Palmetto Review contains an impressive selection of articles on a variety of topics. As
I was reviewing the journal for publication, I became more and more interested, and absorbed in several of them.
First of all, the article about the South Carolina State Lottery by colleagues, Bob Barrett and Robert Pugh at Francis
Marion University, is most informative about the lottery, how it began and predictions for the future. Anyone who
lives in South Carolina is affected by the lottery. This article provides much insight into the process. Its currency
is validated by an article that appeared this last week in many State papers highlighting the impact that the North
Carolina State Lottery, as well as increasing gas prices, may have on South Carolina lottery ticket sales.
There are also three excellent articles related to business education. The discussion of self-monitoring behavior
and its impact on young graduates as they enter the job market is thought provoking. It gives us all an additional
dimension to consider as we work with our students preparing them for job interviews.
In the business education section, I particularly enjoyed the paper about management as a liberal art. This paper
discusses ways to bridge the gap between what we do in a business school and what are colleagues in the liberal
arts are doing. It is so important for us to work with colleagues campus wide. I look forward to sharing this paper
with my colleagues across campus.
Lastly, the article in the business education section about telecommuting had some results that were surprising
to me. I had assumed that individuals either wanted to telecommute or work in the office. From this preliminary
research, it appears that a more blended approach is desirable. Most of the respondents preferred to telecommute
approximately twenty hours per week if possible.
With a number of business schools currently in the process of recruiting accounting faculty, the article about the Sarbanes-Oxley Act of 2002 is also timely. As the article states, Sarbanes-Oxley is often called the ‘“CPA Employment
Act of 2002.”’ Many universities are feeling the pressure to enhance their accounting programs to satisfy student
demand while, at the same time, it appears that there are fewer and fewer qualified accounting faculty available on
the market. The next few years will prove interesting in accounting recruitment, partially due to the Sarbanes-Oxley
Act.
I hope that you will find the variety of topics in the 2006 issue of Palmetto Review of interest, also. Best wishes for
a successful 2006-2007 academic year!
Sincerely,
William S. Moore Palmetto Professor in Quality Studies
Volume 9, 2006
1
Palmetto Review
THE SOUTH CAROLINA EDUCATION LOTTERY:
DETERMINANTS OF REVENUE
Robert T. Barrett
Robert E. Pugh
Francis Marion University
ABSTRACT
The South Carolina Education Lottery, started in 2002, has been a big success for the state. Most of the
proceeds from the lottery, as was required by the legislation establishing the lottery, has gone to fund college scholarships. Technology and other educational needs have also been funded. This paper uses regression analysis to
examine the determinants of lottery revenues and related issues.
INTRODUCTION
ies continued, and by 2003, 39 states plus the District
of Columbia had established lotteries. This expansion
of state lotteries was greatly facilitated by advances in
information processing and communications technology,
which made lotteries more exciting for participants and
provided a high degree of control of lottery processing
to guard against corruption (Hills, 2005).
Six of the seven southeastern states established
lotteries during this period. In 1988, Virginia and Florida
started state lotteries, and, in 1993, Georgia started its
lottery. These three states held state-wide referendums
to gain the necessary approval for establishing their
lotteries. In 1998, Alabama held a state referendum on
establishing a lottery, but it failed. Two years later, in
2000, South Carolina voters gave approval for a state
lottery. More recently, in 2002, Tennessee held a referendum on a state lottery, and it was approved. In North
Carolina in 2005, legislation to establish a lottery was
passed.
As the South Carolina Education Lottery nears
the end of its third year, it is appropriate to analyze the
Lottery experience. In the first section of this paper,
some of the public concerns are reviewed. Secondly, a
brief look at the results from the first three years is presented. Then the study develops a statistical analysis of
the South Carolina lottery to identify the demographic
and economic factors that determine lottery revenues.
Lastly, this statistical analysis leads to an improved understanding of lottery revenue sources and serves as the
basis for examining policy issues related to the South
Carolina Education Lottery.
Lotteries are prominent throughout history.
The Great Wall of China was partly financed by a lottery. India, Greece, and Japan also had lotteries during
ancient times. Lotteries were used throughout the 1400s
and 1500s to finance various public works. In 1753 the
British Museum was funded by a lottery (Hills, 2005).
Lotteries have a mixed history in the United
States. In colonial times lotteries were used to finance
public works such as bridges, roads, and public buildings. The earliest of the colonial lotteries, authorized
by the English in 1612, helped fund the Jamestown,
Virginia, settlement. During the American Revolution,
lottery proceeds financed colonial troops. Lotteries lost
popularity in the period before the Civil War due to
corruption, such as fraud and rigged drawings. Many
states discontinued their lotteries. By 1860 only three
states—Missouri, Kentucky, and Delaware—continued
to maintain lotteries. Following the Civil War several
states again legalized lotteries, but again scandal and corruption undermined the public confidence. As a result,
by 1894 lotteries were prohibited in all states; and 35
states, including South Carolina, developed constitutional
provisions forbidding lottery operations (Hills, 2005).
During the early twentieth century Americans
gradually became more tolerant of gambling. Las
Vegas became the gambling capital of the country and
a number of states legalized race horse gambling. In
1964, New Hampshire began a new trend by legalizing
a state lottery. New York and New Jersey followed New
Hampshire’s lead by establishing state lotteries in 1967
and 1970, respectively. This expansion of state lotterVolume 9, 2006
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Palmetto Review
The South Carolina Education Lottery: Determinants of Revenue
PUBLIC CONCERNS
REGARDING THE LOTTERY
play. Citizens with less than $50,000 income are three
times as likely to play as those with higher incomes.
There are many concerns about the lottery
including opposition to gambling, fiscal dependency
on lottery revenues, and regressive effects of lottery
participation. Here the concerns about the lottery are
discussed in terms of two areas: (1) the possible effects of
the lottery on other public policies and (2) the effects on
the poor and less educated segment of the population.
SOUTH CAROLINA LOTTERY PROCEEDS
DISTRIBUTION
THE FIRST THREE YEARS SCHOLARSHIPS AND OTHER RECIPIENTS
In March of 2002, the House and Senate passed
spending plans for the lottery proceeds that were vastly
different. Some labeled the House plan as one that ignored the poor (who would most likely be the ones who
would buy the most tickets) in favor of students who
could better afford college anyway (Sheinin, 2002).
One of the primary beneficiaries of the lottery
proceeds in the approved spending plan is the college
scholarship fund. There are four primary scholarships
available to graduates of South Carolina high school. The
Palmetto Fellow and LIFE scholarships were established
before the lottery was in existence. Lottery proceeds have
helped to expand these programs. The HOPE scholarship was initially funded with lottery proceeds, as was
the tuition assistance program for students attending
technical colleges (Edwards, 2002). Stated goals of these
scholarships include: “greater access to higher education;
bright, college-bound students choosing in-state schools,
rather than elite schools elsewhere; and bright college
graduates staying home, rather than adding to the brain
drain” (Brinson, 2002).
In addition to scholarships, lottery funds have
supported other public entities. Funds have been made
available to colleges and universities in the state for
technology upgrades. Endowed professorships have
been funded at the research universities. Lottery funds
have been used to purchase much needed school buses.
Local libraries have received funds along with the state’s
gambling addiction programs.
The plan approved by the Legislature also considered distribution of the revenues, which include ticket
sales, permit fees, retailer telephone fees ands other additional costs. Revenues are distributed as follows: 58
percent to prizes; 7 percent to retailer commissions; 6
percent to operating expenses; and 29 percent transferred
to the Education Lottery Account for disbursement.
Clearly the Education Lottery Account is for merit based
scholarships, with no regard for the family’s ability to
pay tuition. Some legislators and the State’s Commission on Higher Education have argued that more of the
dollars should go for needs based programs (Strensland,
2002).
For the fiscal year ending June 30, 2004, lottery
revenues totaled $950 million. After payouts and other
Effects on Public Policy
Purchasing lottery tickets is sometimes perceived
as the poor person’s version of gambling. A 1996 article
by Joseph P. Shapiro (Shapiro 1996), speaking mainly
of gambling in casinos, asks a number of pertinent questions: Is there economic benefit to gambling? Does
gambling create economic development? What are the
social costs? Does gambling lead to crime?
Another general concern with gambling is that
up to 30 percent of youth participate in gambling in some
form (Crary, 2003). Still, another concern is presented in
the Wall Street Journal (Wall Street Journal, 2004). The
Journal editorial chastises legislatures who use money
irresponsibly when they count on lottery/gambling proceeds to fund ongoing programs. Some actually see these
revenues as means to expand programs.
With interstate and international business becoming more and more electronic, gambling is following suit.
The 1961 Federal Wire Act made betting on sports on
the telephone or on the Internet illegal in the U.S. This
form of gambling, however, is not illegal in many other
countries and gambling has become big business overseas. An estimated $5.7 billion in revenues was earned
world-wide from online gambling in 2003. The majority
of the gamblers demographically were American (Angwin, 2004).
Effects on the Poor and Less Educated
Opponents of the South Carolina lottery voiced
their opposition early on stating that these types of revenue generators for state programs create exploitation of
the poor. A December 24, 2002, editorial in The State
(Editorial, The State, 2002) referenced a study conducted
by the lottery commission that indicated that lottery players are “disproportionately poor and black and not highly
educated.” Blacks play at a rate 50 percent higher than
whites. Households with incomes less than $40,000 play
more than households with higher incomes (proportionately). Fewer college graduates play when compared
with those with no college education. The numbers are
even more pronounced when looking at the intensity of
Volume 9, 2006
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Palmetto Review
Robert T. Barrett, Robert E. Pugh
expenses, about $270 million was used to fund college
scholarships. Officials had originally estimated about
$250 million for the year. Much of the increase was
attributed to excitement, and subsequent heavy ticket
sales, surrounding the large Powerball jackpots (AP
Report, 2004). From the first sales in January 2002
through October 14, 2005, over $664 million has been
transferred from the lottery revenues to the Education
Lottery Account (AP Report, 2004, www.sceducationlottery.com).
This reflects the fact, observed by others, that higher income people spend a smaller proportion of their income
on the lottery than lower income people.
The third explanatory variable in the model is
accommodation tax. This tax is on motel/hotel rooms
and is a measure of the flow of people overnighting in a
county, including both tourist and business travelers. In
2002 South Carolina collected nearly $33.5 million in
accommodation taxes, but the tax collections are very
unevenly distributed among the state’s 46 counties with
two counties collecting almost no taxes and one county,
Horry, collecting $12.2 million or almost one-third of
the State’s total. Referring to the regression model for
year 2002, the accommodation tax variable, AT02, has
a coefficient of +.00121 indicating that, on average, for
a county a $1000 increase in accommodation tax collections would be associated with an increase of $.00121
million or $1,210 in lottery sales. Table 1 provides
accommodations tax collections and associated lottery
sales for 2002 for the top five counties in accommodation tax collections. These five counties account for
approximately 95.5 percent of South Carolina 2002 accommodation tax collections.
The remaining two variables in the model are
NCAP, North Carolina accessible population, and GAB,
Georgia counties that border on South Carolina (0-1
variable). These variables are described fully in the
Model-Based Analysis section, evaluating the effects
of counties in North Carolina and Georgia on South
Carolina’s lottery revenues.
A STATISTICAL ANALYSIS OF
THE SOUTH CAROLINA
EDUCATION LOTTERY
To develop an understanding of the factors
related to lottery sales or revenue, statistical models are
developed of lottery revenue as a function of economic,
demographic, and geographic variables. Five models are
developed, one for each calendar quarter of 2002 and one
for the year 2002. The complete statistical description
of the five models developed is found in the Appendix.
All the models are strong statistically with the R-square
values ranging from .96 to .91 indicating that statistically
each model explains more than 90 percent of the variation
in the dependent variable, lottery revenue.
An Example of Findings Particular to South Carolina
Examining the model for the year 2002, the
population variable, POP, and per capita income variable, PCI are the first two explanatory variables involved.
Note that the population variable, POP, is an explanatory
variable both acting alone and acting in combination
with per capita income, PCI. This part of the regression
model has the form:
TABLE 1
Estimated Impact of Visitors on Lottery Sales Based
on Accommodation Tax Collections for the
Top Five Counties in Accommodation Tax
.200POP - .00314POPxPCI.
County
The POPxPCI variable, the product of population and
per capita income, represents the purchasing power of
the resident population of the county. One implication
is that for a county with a specified population, lottery
sales decrease as the per capita income of the county
increases.
The hypothetical examples below illustrate the
contribution to lottery revenue for two counties with
80,000 residents but with different levels for PCI:
Population
80,000
80,000
Volume 9, 2006
PCI
$15,000
$20,000
Horry
Charleston
Beaufort
Richland
Greenville
Accommodation Tax
Collections in 2002
(million$)
Lottery Sales in 2002
Associated with
Accommodation Tax
Collections ($)
12.22
6.72
4.28
1.62
1.60
14,786
8,131
5,179
1,960
1,936
MODEL-BASED ANALYSES
Border Effects
The state of Georgia has had a lottery for a number of years. Has the introduction of the South Carolina
Education Lottery had any impact in lottery sales for the
Georgia counties that border South Carolina? Lottery
Contribution to Lottery Sales
$12.232 million
$10.976 million
4
Palmetto Review
The South Carolina Education Lottery: Determinants of Revenue
summarized in Table 3. In the second column of Table
3 the proportion of each North Carolina county that is
directly across the border from the corresponding South
Carolina county is shown in parentheses. For example,
for Cherokee County, 100 percent of Cleveland County
and 60 percent of Rutherford County are directly across
from Cherokee County. Therefore the NCAP variable
for Cherokee County includes all of Cleveland County’s
population plus 60 percent of Rutherford County’s population.
One question of particular interest is: When
North Carolina implements its lottery, in 2006, will this
reduce the South Carolina lottery sales? Our modelbased estimates for 2002 are that South Carolina lottery
sales to North Carolina residents were $43.28 million;
and since the total 2002 sales were $626.9 million, sales
to North Carolinians were 6.9 percent of the total. In
fiscal year 2004, South Carolina lottery sales were $950
million. If the same 6.9 percent held, this means that
for 2004 sales to North Carolina residents were about
$65.5million. With the advent of North Carolina’s lottery South Carolina might lose a significant part of these
sales. In addition, South Carolina residents will purchase
lottery products in North Carolina to some extent. A
rough estimate of South Carolina’s annual sales loss is
$80-$90 million in 2004 prices. This is significantly
lower than the $150 million a year loss in South Carolina
sales predicted by a number of South Carolina lottery
officials. South Carolina, of course, may be able to
mitigate its loss in sales in the early years of the North
Carolina lottery because of South Carolina’s ability to
rollout fresh games and by offering the very profitable
and popular Powerball drawings (Strensland, 2002).
However, in the longer term the two state lotteries will
probably be roughly equal in attractiveness to purchasers. At that point, North Carolina may have a slight
advantage mainly because of the large South Carolina
population that resides and works in the Charlotte, NC,
metropolitan area. Thus, the long term rough estimate
of South Carolina’s annual net revenue loss of $80-$90
million, in 2004 prices, reflects North Carolina capturing the estimated $65.5 million that South Carolina was
selling to North Carolina residents plus sales to South
Carolinians residing in the Charlotte metropolitan area.
The remaining variable in the year 2002 model
is the Georgia boundary (GAB) variable. This is a binary variable with a “1” for each South Carolina county
that borders on Georgia and a “0” for all other counties.
In the model this variable has a coefficient of –2.613,
indicating that for counties bordering Georgia there is
an associated reduction in lottery revenue. This loss is
expected because of the competition in these counties
sales for all counties of Georgia over the period from
2000 through 2003 show an overall increase. Lottery
sales declined from 2000 to 2001. Georgia experienced
about a 12 percent increase in 2002 compared with 2001
sales. Lottery sales in 2003 were about 6.3 percent more
than in 2002 statewide.
Table 2 shows the percentage changes in lottery
sales from year to year for the Georgia counties bordering South Carolina, all other Georgia counties, and the
total State. While the State experienced a healthy 6.31
percent increase in lottery sales from 2002 to 2003, the
counties on the South Carolina border showed an almost
2 percent decrease in sales. Over this 2002-2003 period,
six of the 13 border counties experienced declines in
sales, two were virtually flat, two others experienced
less than 3 percent increases, and one other a 5.3 percent
increase. This clearly indicates that South Carolina’s
lottery has dampened Georgia’s lottery sales in those
counties bordering South Carolina.
TABLE 2
Increases (Decreases) in Lottery Sales for the
13 Georgia Counties That Border South Carolina, the Other
Georgia Counties, and All Counties in Georgia
From
To
Border Counties
(%)
2000
2001
2002
2001
2002
2003
(3.87)
6.78
(1.87)
Other
Counties
(%)
Total Sales
(%)
(5.55)
12.76
7.38
(5.35)
12.03
6.31
The variable measuring the North Carolina assessable population, NCAP, for South Carolina counties
that border North Carolina has a coefficient of +.0250
in the model for the year 2002, indicating a positive
contribution of the North Carolina counties to South
Carolina lottery sales. The NCAP variable measures
the market in North Carolina for cross-border sales.
For example, Roberson County, North Carolina, with
a population of 123,300, is directly across the state line
from Dillon, South Carolina. The Dillon County NCAP
is 123.3. Therefore the lottery sales in Dillon County
associated with this particular North Carolina population is (.0250)(123.3) = $3.08 million per year. In like
manner, the 11 South Carolina counties bordering North
Carolina have increased lottery sales due to cross-border
sales. Based on the regression model York County has
the largest cross-border sales; since its NCAP = 885.9,
the model estimates York County’s annual sales to the
North Carolina market at (.0250)(885.9) or $22.15 million. Estimated impacts of the North Carolina Accessible
Population on the South Carolina border counties are
Volume 9, 2006
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Palmetto Review
Robert T. Barrett, Robert E. Pugh
from the more well-established Georgia lottery. From the
model, on average each of the 11 South Carolina counties
bordering Georgia is associated with lost sales of $2.613
million per year. Thus, without the cross-border sales to
Georgia in its initial year, the sales of the South Carolina
lottery would have been an additional $28.743 million
or 4.6 percent higher.
TABLE 4
Sales for 2002 in Millions of Dollars.
TABLE 3
SC
Counties
Cherokee
Chesterfield
Dillon
Greenville
Horry
Lancaster
Marlboro
Oconee
Pickens
Spartanburg
York
Total
Bordering NC
Counties
Cleveland (1.00)
Rutherford (0.60)
Arson (1.00)
Union (0.27)
Roberson(1.00)
Polk (0.15)
Henderson (1.00)
Transylvania (0.40)
Brunswick (1.00)
Columbus (1.00)
Union (0.73)
Scotland (1.00)
Richmond (1.00)
Transylvania (0.30)
Jackson (1.00)
Transylvania (0.30)
Rutherford (0.40)
Polk (0.85)
Mecklenburg (1.00)
Gaston (1.00)
Estimated
Effect on
Lottery
Sales
($1,000,000)
134.0
3.35
58.7
1.47
123.3
103.6
3.08
2.59
127.8
3.20
123.7
82.6
3.09
2.06
42.0
1.05
8.9
40.8
0.22
1.02
885.9
22.15
Quarter
3
Quarter
4
Total
Sales
$185
$134
$115
$192
$626
Quarterly
index
1.18
0.86
0.73
1.23
Determinants of Lottery Sales
The regression models presented in the Appendix provide additional insight into the relative strength
of the statistical determinants of South Carolina lottery
sales. Table 5 summarizes the relative strength of the
determinants under four general factors: Residents, Visitors, Border Effects, and Other. “Residents” represent
sales to each county’s resident population, and hence
relates directly to the model variables population (POP),
per capita income (PCI), and the product of these two
variables, with this product representing the personal
income of a county. “Visitors” represent lottery sales to
those visiting the county on either business or pleasure.
This factor is measured in our model by the accommodations tax (AT) variable. “Border Effects” represent the
influence of the North Carolina and Georgia counties
bordering South Carolina. This factor is measured by
the North Carolina accessible population (NCAP) and
Georgia border counties (GAB) variables. “Others”
represent primarily the lottery sales unexplained by the
model plus the model constant term. For example, in the
model for the first quarter of 2002, the R-square value
is .96 indicating that .04, or four percent, of the lottery
sales for that quarter are not explained by the model.
This unexplained sales along with the constant term of
.276 constitute the “Others” factor shown in Table 5.
Table 5 was developed by applying each model
to the 46 counties of South Carolina and summarizing the
results. For example, for the year 2002, or first row of the
table, the year 2002 model is applied to each county and
the results for each term of the model are retained separately. Then the results for the 46 counties are added for
the POP, population, and POPxPCI, product of population and per capita income, terms to obtain the Residents’
contribution to sales. In like manner, the contribution to
sales for Visitors and Border Effects are each computed.
The “Others” contribution is the remainder of the sales
not accounted for by the other three determinants. To
illustrate, in 2002 total lottery sales were $626 million,
and from the model application as just described, $498
43.28
Seasonal Pattern of Sales
The models for the four quarters of 2002 presented in the Appendix have a structure similar to the
model for the year 2002. The quarterly distribution of
lottery sales in 2002, the first year of operation, shows a
definite seasonal pattern. For that year lottery sales for
the first and fourth quarters were high and sales for the
other two quarters were relatively low. Table 4 shows
quarterly sales levels for 2002 along with the quarterly
index values. This pattern is shown clearly by the quarterly seasonal indices for lottery sales in 2002. South
Carolina lottery officials have indicated that this seasonal
pattern of sales is expected to be typical for other years,
with lighter sales in the warmer, vacation-period of the
year (Davenport, 2002).
Volume 9, 2006
Quarter
2
(millions)
Estimated Impact of North Carolina Accessible Population
on the South Carolina Border Counties
NC
Accessible
Population
(1000)
Quarter
1
Year
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Palmetto Review
The South Carolina Education Lottery: Determinants of Revenue
TABLE 5
Proportion of South Carolina Lottery Sales Explained By Specified Determinants in 2002 and Quarters of Year 2002
Statistical Determinants
Residents:
Time Period
Year 2002
Quarter 1
Quarter 2
Quarter 3
Quarter 4
Visitors:
Unexplained
Population and
Per Capital Income
Border Effects:
Accommodations Tax
0.80
0.85
0.81
0.77
0.74
0.07
0.06
0.08
0.07
0.09
million were associated with Residents, $41 million with
Visitors, $14 million with Border Effects, and $73 million
with “Others.” The proportions are then computed for
these four types of contributions in the first line of Table
5. The proportions are computed for each quarter of 2002
utilizing the respective models for the four quarters.
As Table 5 shows, lottery sales associated with
Residents account for a large portion of sales, 80 percent for year 2002 and between 74 and 85 percent for
the quarters of that year. Thus, eight out of every ten
dollars of lottery sales are associated with the resident
population, their number and income level. Visitors are
associated with seven percent of lottery sales for 2002,
with the quarterly level varying from six to nine percent.
The Border Effects include two forces. First, on the
North Carolina border there are sales associated with
the over-the-border North Carolina population. Second,
on the South Carolina-Georgia border there are sales to
Georgia residents by South Carolina and sales to South
Carolina residents by Georgia, since each state has its
own lottery. Note in the table that for the year 2002,
two percent of lottery sales are associated with Border
Effects. However, in the second and third quarters the
South Carolina Lottery experienced a loss in sales, two
percent in the second quarter and one percent in the third.
This means that in those quarters purchases by South
Carolina residents from the Georgia lottery exceeded the
sales to North Carolina residents from the South Carolina
lottery.
Lottery Sales
0.02
0.03
-0.02
-0.01
0.07
0.11
0.05
0.13
0.17
0.01
typically academically more advanced) families.
This argument can be addressed in an approximate way by using the regression model for 2002
presented in Table A1. As mentioned in a previous
discussion, the residents’ lottery spending, called RLOS
here, is described statistically by the population (POP)
and per capita income (PCI) variables as structured in
the first two terms of the model. That is:
RLOS = .200POP - .00314POPxPCI.
Let’s assume that we have a hypothetical county with
a population equal to the median population of South
Carolina’s 46 counties, 52,500 (POP = 52.5). For this
hypothetical county we can compare lottery spending
by residents for a lower income county, say with a per
capita income of $20,000 (PCI = 20), with the spending
of a higher income county, say with a per capita income
of $30,000 (PCI = 30). Using the population of 52,500
we have:
RLOS = .200(52.5) - .00314(52.5)PCI or
RLOS = 10.5 - .165PCI.
Then for a per capita income of $20,000:
RLOS = 10.5 - .165(20) = 7.2,
And for a per capita income of $30,000:
Regressive Impact of Lottery
A general policy concern with state lotteries is
that the lower income groups spend a larger proportion
of their income on the lottery than higher income groups.
South Carolina residents exhibit this typical behavior in
their lottery spending. This in effect means that lottery
spending acts as a regressive state tax. This bolsters the
argument that lower income residents are paying for tuition scholarships for students from higher income (and
Volume 9, 2006
NC Accessible
Population and
GA Border
Others:
RLOS = 10.5 - .165(30) = 5.0.
From this it is seen that the $20,000 per capita income
group spending is about $137 ($7,200,000/52.5 = $137)
per person, whereas for the $30,000 per capita income
group the per capita lottery spending is about $95
($5,000,000/52.5 = $95). This means that the $20,000
per capita income group spends about .07 percent
($137/$20,000 = .007 or .07 percent) of their income
7
Palmetto Review
Robert T. Barrett, Robert E. Pugh
on the lottery compared with .03 percent ($95/$30,000
= .003 or .03 percent) for the $30,000 per capita income
group. This is put in perspective by noting that the per
capita lottery spending by residents in the entire State
in 2002 was about $125, this from the lottery spending
by residents in 2002 of $498 million, discussed previously, divided by the South Carolina population of four
million.
It should be understood that these lottery spending estimates for per capita income groups are rough estimates. This is because the models of the determinants of
lottery spending use the average per capita income levels,
whereas our interpretations are made for subpopulations
that have specified per capita income levels. While these
interpretations may result in estimates with some bias,
the results are seen as reasonable as to direction, in that
lower income groups spend a larger proportion of their
incomes on the lottery, and reasonable as to magnitude
compared to the $125 per capita lottery spending, which
is determined independently of the regression model.
findings are:
• In its initial year of operation, the sales of South
Carolina’s lottery were distributed in the following way: Residents—90 percent, Visitors—seven
percent, Cross-border—two percent. This leaves
1 percent of the sales unexplained by the statistical model.
• Lottery sales are regressive relative to income.
Those with lower incomes spend a larger proportion of their income on the lottery. For example,
it is estimated that with a $20,000 annual income,
seven percent of the income is spent on the lottery
whereas those with $30,000 in income spend only
three percent.
• In its first year, the South Carolina lottery had
significant cross-border sales with North Carolina
and with Georgia. North Carolina did not have
a lottery in the initial year of the South Carolina
lottery, and cross-border sales to North Carolina
residents were $43.28 million or 6.9 percent of
total sales. Georgia, with its well-established
lottery, drew $28.73 million in net sales from
South Carolina, reducing South Carolina’s sales
by 4.6 percent.
• South Carolina Lottery sales were seasonal in
its initial year with a quarterly index pattern of
1.18, 0.86, 0.73, and 1.23, respectively. This is a
typical pattern for lottery sales, light in the springsummer and heavy in the fall-winter period.
While these findings are based in the initial year of lottery
operations, it is reasonable to assume that similar patterns
of results hold for subsequent years of the lottery.
Although it appears that the South Carolina Educational Lottery has operated without either corruption
or malfeasance since 2002, a number of proposals for
change have been made. These changes relate primarily
to two areas: (1) the administration of lottery operations
and (2) the allocation of the lottery generated funds
among educational programs. In lottery operations, The
South Carolina Legislative Audit Council recommended
that cost cutting should be made, such as reducing the
number of cellular phones used and re-evaluating the use
of vehicles. Another administrative change suggested is
cutting the seven percent fee paid retailers on lottery sales
to six percent (www.scgovernor.com
www.scgovernor.com 2003). Governor
Mark Sanford made this recommendation several times,
including the Fiscal Year 2006-07 Executive Budget in
which this saving was estimated at $8.4 million (Sanford
2006).
In the area of allocation of educational support
funds from the lottery, two proposals of interest have been
made. First, it has been proposed that lottery sales be
CONCLUSION
Since the first ticket was sold in January 2002,
the SC Education Lottery has been successful, exceeding
expectations of the most optimistic supporters. By the
end of the third complete fiscal year, ticket sales totaled
just under $3 billion (fiscal year ending June 30, 2005).
Ticket sales in the first three fiscal years were $724.3
million (2003), $950.0 million (2004), and $956.0 million (2005) (www.sceducationlottery.com).
As stated in current SC Education Lottery legislation, “proceeds of lottery games must be used to support
improvements and enhancements for educational purposes and programs as provided by the General Assembly
and that the net proceeds must be used to supplement,
not supplant, existing resources for educational purposes
and programs” (www.sceducationlottery.com). By the
end of the 2005 calendar year, including distributions
made in 2002 (a partial fiscal year), funds distributed to
the SC Education Lottery Account exceeded $1 billion.
Over 460,000 scholarships for students attending colleges
and universities and technical colleges were funded by
the lottery account. Over $330 million was provided to
K-12 public schools, in addition to 400 buses, and $28
million for textbooks (www.sceducationlottery.com).
In this study the focus is on understanding the
economic and demographic consequences of lottery sales
by the South Carolina Education Lottery. The methodology employed is regression modeling that represents
lottery sales in South Carolina’s 46 counties as a function
of economic and demographic variables. The principal
Volume 9, 2006
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The South Carolina Education Lottery: Determinants of Revenue
subject to the state income tax (Calhoun, 2003). The Lottery Commission has opposed this idea, but this idea may
well be raised again (Sheinin, 2002). A second example
of changes in the allocation of educational support funds
is to direct more funds to K-12 or early childhood education rather than to college scholarships. The interest in
this change was sparked by the recent court decision in
the “minimally adequate” school funding lawsuit verdict
(www.sceducationlottery.com 2006).
12. Eichel, Henry, (2002) “Stores near the Borders
Lead Lottery Sales,” The State, Columbia, S.C, March
17, 2002, B 1.
13. “Five Key Issues in 2006,” (2006) The State, Columbia, S.C., January 8, 2006, D1.
REFERENCES
14. “Greenville News Editorializes in Support of Gov.
Sanford’s Lottery Retailer Cut,” (2003) State of South
Carolina, Office of the Governor, www.scgovernor.com,
December 5, 2003.
1. Angwin, Julia, (2004) “Could U.S. Bid to Curb
Gambling on the Web Go Way of Prohibition?” The Wall
Street Journal, August 2, 2004, B1.
15. Hills, Chad, (2005) “A History of the Lottery,”
Focus on Social Issues, www.family.prg/cforum/foci/
gambling/lottery/10026528.cfm. December 27, 2005.
2. AP Report, (2004) “S.C. Lottery Brings in Almost
$1 Billion,” Morning News, Florence, SC, August 9,
2004, A 7.
16. Monk, John, (2000) “Hodges put Machine to Work
for Lottery,” The State, Columbia, S.C., November 9,
2000, B1-B2.
3. Barrett, Robert T., and Pugh, Robert E., (2003)
“Success of the South Carolina Education Lottery – Six
Month Report,” Southeast Decision Sciences Institute
Proceedings, February 2003, pp. 313-315.
17. News Article, (2004) “More than Half a Billion
Transferred to Education,” www.sceducationlottery.com.
May 13, 2004.
18. Sanford, Mark, Governor of South Carolina, (2006)
Executive Budget, State of South Carolina, www.scgovernor.com, January 4, 2006.
4. Brinson, Claudia Smith, (2002) “Merit-based Scholarships are Misguided, Largely Ineffective,” The State,
Columbia, S.C, July 28, 2002, D 1, 5.
19. Scoppe, Cindi Ross, (2004) “Lottery Opponents
Would Love to See Rules Spelled Out Before Vote,” The
State, Columbia, S.C., May 4, 2000, A14.
5. Calhoun, Cecil, (2003) “Budget Debate Leaves Public Ed Funding,” www.thescea.org, March 14, 2003.
20. Shapiro, Joseph P., (1996) “America’s Gambling
Fever: The nation’s favorite pastime comes under fire
from those who fear it won’t help communities and
families in the long run,” U.S. News & World Report,
January 15, 1996, pp. 52-60.
6. Crary, David, (2003) “Experts Say Gambling Problems on the Rise among American Youth,” Morning News
(Florence, SC), July 14, 2003, A1, 5.
7. Davenport, Jim, (2002) “Lottery Revenue Slower
than Expected in July,” Morning News, Florence, S.C.,
August 30, 2002, A5.
21. Sheinin, Aaron, (2002) “Bill Clears House, is
Branded Elitist,” The State, Columbia, SC, March 15,
2002, A 1, 9.
8. Edgar, Amy Geier, (2004) “S.C. lottery, USC form
Unique Partnership,” Morning News, Florence, SC,
August 9, 2004, A 7.
Editorial, (2002) The State, December 24, 2002, A8.
22. Sheinin, Aaron Gould, (2003) “Proposed Lottery
Sales Tax Opposed,” The State, Columbia, SC, December
3, 2003, B 1.
10. Editorial, (2004) “Political Gambling,” Wall Street
Journal, July 19, 2004, A 10.
23. Strensland, Jeff, (2002) “Lottery Fuels Scholarship
Debate,” The State (Columbia, S.C), July 28, 2002, D 1, 6.
11. Edwards, Laura, (2002) “Gambling on their Future,”
Morning News, Florence, S.C., June 6, 2002, A1, 8.
24. Strensland, Jeff, (2005) “S.C. Games has Means to
Compete with N.C.” The State, Columbia, SC, www.
thestate.com, May 9, 2005.
9.
Volume 9, 2006
9
Palmetto Review
Robert T. Barrett, Robert E. Pugh
25. “Who Went to the Polls in South Carolina,” (2000)
The State, Columbia, S.C., November 8, 2000, A16.
26. www.sceducationlottery.com.
APPENDIX
REGRESSION MODELS EXPLAINING
LOTTERY SALES
The model statistics provided in the lower
rows of Table A1 provide overall measures of the statistical reliability of the models. The F-ratios provide
a statistical test of the significance of the overall model
relationship between the dependent variable and the set
of independent variables. For all five of these models
the F-ratios indicate the overall model relationship is
strong, significant at the 99 percent confidence level or
higher. Thus, each model represents a relationship that
is highly significant statistically. The R-square values
represent another overall measure of model statistical
strength, measuring the proportion of the variation in
the dependent variable that is explained by the set of
independent variables in the model. In these models the
R-square values range from .96 to .91 indicating that each
model statistically explains more than 90 percent of the
variation in the dependent variable, lottery revenue.
Another important measure of model reliability
is the t-scores that measure the statistical reliability of the
individual independent or explanatory variables included
in the model. The coefficients of the explanatory variables
in the regression model for year 2002, for example, are
significant at the 97 percent level or higher. The t-scores
are given in parentheses below each model coefficient.
Note that the same independent variables are included
in each of the five models to provide easy comparison in
the interpretation of the models. This causes three of the
coefficients of explanatory variables, two in the model
for the third quarter and one in the model for the fourth
quarter to be of lower level of significance than .97.
An interesting aspect of the structure of these
models is that the population variable, POP, appears in
the models both acting alone and acting in combination
with per capita income, PCI. The combination variable,
POPxPCI, is called an interaction variable or crossproduct variable, and in this situation the cross-product
variable substantively represents the spending power of a
county’s population. Such variables are often important
in representing a nonlinear relationship among variables,
and in these models there is a nonlinear relationship
between the POP and PCI variables acting together and
the dependent variable, lottery revenue. In this study the
interaction variable provides the basis for an increased
understanding between per capita income and lottery
spending.
The methodology employed in this study
involved the development of regression models that
represented lottery revenues from sales as a function of
economic, demographic, and geographic variables. The
observations on the variables used to estimate the models
were taken from the 46 counties of South Carolina. Five
models are developed, one for each calendar quarter of
2002 and one for the year 2002. The interpretation of
these models was a primary basis in the study for providing an improved understanding of the factors related to
lottery sales revenues. The model for the year 2002 is:
LR02 = 1.61 + .20 POP – 0.00314 POPxPCI +0.00121
AT02 + 0.025 NCAP – 2.61 GAB
where:
LR02-Lottery sales revenue for each county in
2002 in millions of dollars
POP-Population of county in 2000 in thousands
PCI- Per capita income of county in 2000 in
thousands of dollars
AT02-Accommodation taxes collected in county
in 2002 in thousands of dollars
NCAP-North Carolina population accessible to
South Carolina counties
on the South Carolina-North Carolina border in
2000 in thousands
GAB-South Carolina counties that border on
Georgia (0-1 variable)
The complete statistical description of the five
models developed is provided in Table A1. These five
models all include the same dependent and independent
variables, except that the dependent variable and one of
the independent variables are represented on a quarterly
basis in the four quarterly models. Lottery revenue, the
dependent variable, is represented for each quarter of
2002 as LRQ1, LRQ2, LRQ3, and LRQ4, respectively.
Likewise, the independent accommodations tax variables
are represented by quarter as ATQ1, ATQ2, ATQ3, and
ATQ4, respectively.
Volume 9, 2006
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The South Carolina Education Lottery: Determinants of Revenue
TABLE A1
Regression Models Representing Lottery Sales Revenue as a Function of County Characteristics
VARIABLE/
STATISTIC
Dependent Variable:
Lottery Revenue
($1,000,000)
Constant Term
QUARTER
1 MODEL
QUARTER QUARTER 3 QUARTER
2 MODEL
MODEL
4 MODEL
YEAR
2002
MODEL
LRQ1
LRQ2
LRQ3
LRQ4
LR02
0.276
0.355
0.451
0.404
1.61
POP
.0654
(6.15)
POP
.0453
(4.96)
POP
.0330
(3.56)
POP
.0643
(4.41)
POP
.200
(5.09)
POPxPCI
-.00109
(2.89)
POPxPCI
-.00758
(2.38)
POPxPCI
-.000458
(1.43)
POPxPCI
-.00118
(2.33)
POPxPCI
-.00314
(2.30)
Accommodation
Tax ($1000)
ATQ1
.00286
(3.25)
ATQ2
.00108
(4.69)
ATQ3
.000551
(5.21)
ATQ4
.00273
(4.87)
AT02
.00121
(5.02)
North Carolina Accessible
Population (1000)
NCAP
.00873
(9.58)
NCAP
.00343
(4.36)
NCAP
.00250
(5.21)
NCAP
.0104
(8.26)
NCAP
.0250
(7.38)
Georgia Boundary (0 or 1)
GAB
-.810
(2.77)
GAB
-.567
(2.24)
GAB
-.482
(1.89)
GAB
-.450
(1.12)
GAB
-2.61
(2.40)
0.96
220.4
0.94
133.3
0.91
90.9
0.93
115.3
0.95
165
Independent Variables:
Population (1000)
Population (1000) x
Per Capita income ($1000)
Model Statistics:
R-Square
F-Ratio
ABOUT THE AUTHORS
Robert T. Barrett is Professor of Management
and Associate Dean in the School of Business at Francis
Marion University. Dr. Barrett teaches and researches
in management science, statistics, and operations management. His latest research has focused on supply
chain management and regional economic development
including projects studying the influences of highways,
influences of communicable diseases, and influences
of the state-run lottery on the regional economy. He
has published scholarly papers in journals including the
Southern Business Review, the International Journal of
Computers and Operations Research, the Production
and Inventory Management Journal, Simulation, and
the Journal of Travel and Tourism Management. He is
a regular contributor as reviewer for Decision Sciences
and the International Journal of Computers and Opera-
Volume 9, 2006
tions Research and a regular participant in regional and
national professional meetings.
Robert E. Pugh is Professor of Management
and the Eugene A. Fallon, Jr. Professor of Production
Management in the School of Business at Francis Marion University. Dr. Pugh teaches and researches in management science, operations management, and statistical
model building. His recent research focuses on the effects of existing and proposed highways, tourism, and retirement migration on regional economic development.
He has published scholarly papers in Coastal Business
Review, Journal of Policy Analysis and Management,
Mathematical Programming, Southern Business Review,
and other journals. He participates in professional meetings as a reviewer, discussant and presenter.
11
Palmetto Review
THE ROLE OF SELF-MONITORING
IN JOB SEARCH SUCCESS: A FIELD STUDY
Kimberly A. Freeman
Winston-Salem State University
ABSTRACT
Students nearing graduation are often quite concerned with securing job offers that will launch their careers. This study investigates whether getting second interviews, receiving job offers, and accepting a job prior to
graduation from an MBA program is more likely for those individuals who are high on self-monitoring compared
to those who are low on self-monitoring. The results of hierarchical regression analyses support these hypotheses
by demonstrating that the prospects on these outcomes are positive for students who report to be high (rather than
low) on self-monitoring behavior. Implications of these results are discussed, as are directions for future research.
INTRODUCTION
Unckless, & Hiller, 2002; Gangestad & Snyder, 2000;
Turnley & Bolino, 2001).
A recent study of employed Executive MBA
students revealed a relationship between self-monitoring and the Big Five personality traits. Barrick, Parks,
& Mount (2005) found that when self-monitoring was
high, the relationships between three of the Big Five
personality traits (Extroversion, Emotional Stability, and
Openness to Experience) and supervisory ratings of interpersonal performance were attenuated. The interpersonal
performance factor included interpersonal skills, rapport
in relationships, cooperation, communication, listening,
and other aspects. Self-monitoring did not, however,
moderate the relationships between supervisory or peer
ratings of task performance and personality traits (Barrick, et al, 2005).
Another study found that people who were more
demographically different (e.g., citizenship, race, etc.)
from their coworkers created more negative impressions
than did more similar coworkers, but “these impressions
were more positive “when they were either high SMs or
more extroverted (Flynn, Chatman, & Spatero, 2001).
In a cross-cultural study of college students, Goodwin
& Pang Yew Soon (1994) found the British subjects
were higher SMs than their Chinese counterparts which
supported their hypothesis that Western students would
be significantly higher SMs than those from Eastern
cultures, as hade been found by Gudykunst, Yang &
Nishida (1987). Zweigenhaft & Cody (1993) reported
that black students scored significantly lower on Snyder’s
self-monitoring scale than their white colleagues on a
predominantly white college campus.
Job search success may depend upon a number of
factors. Organizations typically gather basic information
about the job applicants through the application process
and resume in order to decide whom will receive an initial
interview. Candidates who are successful in the first interview are often required to engage in a second interview
prior to the hiring decision. The interview is generally
regarded as a useful way to discern whether or not the
candidate is a good fit or “match” for the organization.
Considerable research on interview techniques and dynamics has been conducted. However, few researchers
have studied the effect of a personality trait identified as
self-monitoring behavior on hiring decisions.
LITERATURE REVIEW
Self-monitoring has been studied extensively
across a wide variety of social interaction circumstances. In their comprehensive review of published
literature, Gangestad & Snyder (2000) summarize that
“high self-monitors may be highly responsive to social
and interpersonal cues of situationally appropriate
performances,” whereas “for those low self-monitors,
expressive behaviors are not controlled by deliberate attempts to appear situationally appropriate; instead, their
expressive behavior functionally reflects their own inner
attitudes, emotions, and dispositions.” In other words,
high self-monitors (SMs) are willing and able to display
behaviors to impress other people in contrast to low
SMs who resist or are unable to do so (Day, Schleicher,
Volume 9, 2006
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The Role of Self-Monitoring in Job Search Success: A Field Study
Leadership and self-monitoring behavior research has revealed several relationships of self-monitoring with leadership emergence and leader flexibility.
Compared with low SMs, high SMs initiated structure
more often and emerged as leaders more often indirectly
through initiating structure (Dobbins, Long, Dedrick, &
Clemons., 1990). In another study, high SM was associated with leadership capabilities of social perceptiveness
and behavioral flexibility requirements incorporating
both trait and situational elements of leadership and
respond accordingly (Zaccaro, Foti, & Kenny, 1991).
High SMs are also more likely to hold more leadership
positions (Day, et al., 2002; Zaccaro, et al., 1991).
Since high SMs appear more effective socially
by reading and responding to interaction cues, researchers
hypothesized in a study of emotional intelligence (Goleman, 1995) that SM is a moderator of conscientiousness
and performance and should be controlled as a variable
due to the overlap of the emotional intelligence constructs
(Douglas, Frink, & Ferris, 2004). Douglas, Frink, and
Ferris (2004) also found high SM was positively correlated with rating of performance and negatively related
to age, though not with conscientiousness or emotional
intelligence.
Mehra, Kilduff, and Brass (2001) found a direct
relationship between high SM and performance. In
research involving performance appraisal from various
sources (self, peer, and supervisors), both in student work
groups and in a study of project teams in corporations,
high SMs rated themselves significantly higher than low
SMs; only in student groups did low SMs ratings reflect
their greater consistency of behavior which supported
their hypotheses (Miller & Cardy, 2000). In other situations, high SMs received higher supervisory performance
appraisals from supervisors than low SMs in boundary
spanning roles (Caldwell & O’Reilly, 1982) and low
SMs showed behavioral consistency and received higher
performance ratings from their supervisors (Caliguri &
Day, 2000).
In a study of turnover intentions, self-monitoring
accounted for previously unexplained variance beyond
traditional predictors of satisfaction and commitment:
degree of job satisfaction was a better indicator of intent
to leave for high SMs and commitment was a better for
low SMs (Jenkins, 1993).
Kilduff and Day (1994) tracked MBA graduates
over five years and found that high SMs were more likely
to change employers, move to different geographic locations, and achieve cross-company promotions than low
SMs. The high SMs who stayed with an organization got
more promotions than low SMs during that same period.
They concluded that high SMs pursue more successful
Volume 9, 2006
managerial career strategies than low SMs by being able
to adapt to circumstances and opportunities (Kilduff &
Day, 1994).
Particularly with regard to personnel selection,
there is a reliance on appearance and personality (Snyder, Berscheid, & Matwychuk, 1988). Tasks involving
selection decisions from an evaluator’s viewpoint showed
that interviewers who are high SMs focus more on job
candidates’ appearances and low self-monitoring interviewers focused more on the job candidates’ personalities
(Snyder et. al. 1988). Dobbins, Farh, & Werber (1993)
found a self-monitoring effect on the job search process,
with high SMs more likely than low SMs to portray
themselves as best suited to workplace situations (Miller
& Cardy, 2000).
HYPOTHESIS DEVELOPMENT
The interview is perhaps the most widely used
selection approach in organizations and provides a
forum in which applicants have only a brief time to
present themselves as a prospective employee. Impressions made during this critical face-to-face time period
have immediate and lasting consequences. With the
high SM’s tendency to develop their self-presentation
behaviors, they seem more likely to make a stronger
impression during in an interview situation than low
SMs. The advantage of this personality tendency may
be relatively pronounced if all job candidates are similar on other factors (e.g., education, background, work
experience, etc.).
High SMs seem to have a number of advantages
in an organizational environment. This leads one to
hypothesize that receiving the opportunity to use that
personality trait may begin with the selection process
itself. As long as interviews are used, high SMs could
present themselves as a better fit or job match than low
SMs, which may result in more favorable outcomes.
Three hypotheses were tested in this study:
(1) First, it was hypothesized that self-monitoring accounts for significant incremental
variance in the number of second interviews granted to the job seekers beyond
the variance due to demographic and
background variables, with self-monitors
receiving more second interview opportunities.
(2) The second hypothesis was that selfmonitoring would account for a significant
amount of variance in the number of job
offers extended to candidates, beyond
that accounted for by demographic and
13
Palmetto Review
Kimberly Freeman
(3)
background variables.
Thirdly, it was hypothesized that selfmonitoring would explain a significant
amount of variance over demographic and
background variables for the early job acceptance measure of job search success.
search success: (1) the number of second interview opportunities the student had received, (2) the number of job
offers extended, and (3) whether the subject had accepted
a job offer at least two weeks before graduation.
RESULTS
METHOD
Descriptive Statistics
Table 1 presents the means, standard deviations
and intercorrelations matrix for the demographic and
background variables used in the study.
Subjects
Ninety-seven second-year MBA students in a
private southeastern university participated in the study.
A total of 40 subjects completed usable questionnaires,
resulting in a response rate of 41.2%. Among those who
responded, 35% were women, the average age was 26.5,
and the average months of work experience was 36.2.
All forty subjects were seeking employment through the
MBA placement office.
TABLE 1
Means, Standard Deviations, and Intercorrelations for
Demographic and Background Variables, and
Self-Monitoring scale
Measures
Demographics and background. Data on
gender, age, months of work experience (MWE), undergraduate grade point average (UGPA), a standardized
test score (GMAT), and graduate-level grade point average after three semesters (GPA3) were made available
by the administration for use as predictor variables. It
should be noted that undergraduate GPA was based on
the traditional 4.0 scale, while the graduate-level GPA
was scaled from 0.0 to 8.0.
Self-Monitoring Scale. The subjects completed
a 25-item self-report measure of true-false questions on
self-monitoring behavior and scores could range from 0
to 25. The self-monitoring scale (SMS) was developed
by Snyder (1974) and has been used extensively (Gangestad & Snyder, 2000; Snyder & Gangestad, 1982). High
test-retest reliability, internal consistency, reliability, and
validity of the SMS scale have been well established
(Snyder & Gangestad, 1986; Snyder, 1987). Examples
of SMS scale questions that reflect high self-monitors
include “Even if I am not enjoying myself, I often pretend to be having a good time”; “In different situations
and with different people, I often act like very different
persons”; and “I’m not always the person I appear to be.”
Low self-monitors would tend to respond positively to
“I find it hard to imitate the behavior of other people”;
“I have trouble changing my behavior to suit different
people and different situations”; and “My behavior is
usually an expression of my true inner feelings, attitudes,
and beliefs.”
Job Search Success measures. Two weeks
prior to graduation, the MBA placement office provided
the information for the three dependent measures of job
Volume 9, 2006
Measure
M
SD
2
1.
2.
3.
4.
5.
6.
26.5
36.2
2.92
594
6.42
12.83
4.02
40.21
0.36
41.91
0.46
4.13
.94*** -.33*
--.36*
--
Age
MWE
UGPA
GMAT
GPA3
SMS
3
4
5
6
-0.22
-0.16
0.25
--
-0.23
0.21
0.14
0.1
--
0.06
0.1
-0.2
-0.13
0.1
--
N=40.
Note: MWE is Months Work Experience, UGPA is Undergraduate Grade
Point Average. GMAT is Graduate Management Aptitude Test, GPA3 is
Grade Point Average after 3 semesters in the MBA program; and SMS is the
Self-monitoring scale.
* p < .05.
** p < .01.
*** < .001.
***p
Relationships among Demographic and Background
Variables and Self-monitoring
There were no gender differences on any of the
variables, thus gender was not included in the analysis.
As would be expected, age was strongly related to months
of work experience. Undergraduate GPA was negatively
correlated with both age and MWE, as would also be
predicted. Neither GMAT nor graduate-level GPA was
significantly correlated with any of the other variables in
the study. Age ranged from 22 to 40 years old, months of
work experience (MWE) ranged from 0 to 152 months,
undergraduate GPA for the students ranged from 2.1
to 3.7 (based upon a 4.0 scale), GMAT scores ranged
from 510 to 700, and GPA after three semesters in the
MBA program ranged from 5.63 to 7.58 (based upon
an 8.0 scale). Scores on the SMS ranged from 5 to 24
and were not correlated with any of the demographic or
background variables.
Relationships among Self-monitoring and Job
Search Success Measures
The three measures of job search success were
14
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The Role of Self-Monitoring in Job Search Success: A Field Study
highly intercorrelated. The number of second interviews
was strongly related to both number of offers and early
job acceptances. As would be expected, whether one had
accepted a job offer by two weeks prior to graduate was
strongly related to the number of offers received by the
subject. Table 2 shows these correlations.
On step two, the self-monitoring variable was
entered into the regression equations to assess the incremental variance it explained in the dependent measures
beyond those entered into the equation on the first step.
The hierarchical regression results are presented in Table
3. Results for the number of second interviews are given
first. As shown, self-monitoring accounted for significant
variance in the number of second interviews beyond that
accounted for by variable entered in the first step (Delta
R-squared = .39), F
F(6,33) = 22.91, p < .0001.
TABLE 2
Means, Standard Deviations, and Intercorrelations for Self
Monitoring and Dependent Variables
Measure
1. SMS
2. Second Int.
3. Offers
4. Accept
M
12.83
2.15
0.98
0.58
SD
4.13
1.27
0.86
0.5
2
.63***
--
3
.43**
.56***
--
4
.36**
.47**
.75***
--
TABLE 3
Hierarchical Regression Analysis controlling for
Demographic and Background Variables with Main Effect
(Self-Monitoring) entered in Step 2 for Prediction of
Second Interviews, Job Offers, and Early Job Acceptance
N=40.
Note: SMS is Self-Monitoring Score, Second Int. is for number of second
interviews, Offers is for number of job offers, and Accept is for early job
acceptances.
* p < .05.
** p < .01.
*** p < .001.
Job Search Success Measures
Second
Job Offers
Interviews
Betas
Betas
Step 1:
Control
variables
Age
MWE
UGPA
GMAT
GPA3
R-squared
Relations among Self-Monitoring and Other Variables
Self-monitoring was related to all three of the job
search success measures. Self-monitoring was strongly
correlated with number of second interviews (r = .63, p
<.001) and with the number of offers extended (r = .43,
p < .01), and moderately correlated with early job acceptance (r = .36, p <.05).
Step 2:
SMS
R-squared
Delta
R-squared
Tests of the Hypotheses
The hypotheses were tested by examining the
incremental variance explained by self-monitoring over
the demographic and background variables. Two-step hierarchical regression analyses were conducted using each
of the job search success measures as the criterion.
On the first step, the demographic and background variables entered simultaneously were: age,
MWE, UGPA, GMAT, and GPA3. It was expected that
age, grades, test scores, and work experience would
explain some of the variance in the job search success
measures for several reasons. Since past performance is a
good predictor of future performance, it would seem that
high grades and test scores would be important indicators
of job search success as indicators of ability, perseverance, and/or a willingness to work hard. Further, age and
work experience would likely indicate a higher level of
maturity and experience in assimilating into the work
environment. Thus, it was felt that these variables should
be controlled prior to entering the variable relevant to the
hypotheses: self-monitoring. However, the demographic
and background variables which were entered at step 1
did not account for a significant amount of variance for
any of the three dependent variables.
Volume 9, 2006
-0.11
0.01
0.58
0
0.2
Early Job
Acceptance
Betas
-0.07
0
-0.22
0
-0.1
0.06
0.2
-0.04
0
-0.14
0
0.02
0.09
0.09
0.13
0.04
.45*
0.27
0.25
.39***
.18**
.12*
N=40.
Note: MWE is Months Work Experience, UGPA is Undergraduate Grade
Point Average. GMAT is Graduate Management Aptitude Test, GPA3 is
Grade Point Average after 3 semesters in the MBA program, and SMS is
Self-monitoring Scale.
Note: Beta values are for full model.
* p < .05.
** p < .01.
*** p < .001.
Results for offers extended were similar to those
for second interviews. Self-monitoring accounted for a
significant amount of variance beyond the demographic
and background variables alone (Delta R-squared = .18),
F(6,33) = 8.33, p < .01.
F
The results with regard to early job acceptance,
the third measure of job search success, were also
significant ((F
F(6,33)
F
(6,33) = 5.52, p < .01). Self-monitoring
accounted for an additional 12% of variance beyond the
demographic and background variables alone.
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Kimberly Freeman
DISCUSSION
Graf & Harland (2005) used MBA students in
a study of effective screening and selection of expatriates and found that interpersonal competence measures,
which included a communication skills component,
predicted intercultural decision quality in an intercultural
organizational scenario.
One of the top recommendations by Bernthal
and Wellins (2006) was to base selection and promotion decisions for leaders on interpersonal skills and
personal qualities. The lack of these skills and qualities
being the two most common reasons for failure of leaders despite being promoted based on the leader’s ability
to get results.
Although McFarland, Ryan, and Krista (2002)
did not directly evaluate self-monitoring behavior, they
found that an applicant’s use of soft influence tactics
(e.g., ingratiation, rational persuasion) indeed positively
influences interviewer perceptions and ratings. They
recommended that interviewers be explicitly trained
to recognize applicant influence tactics to increase the
usefulness of interviews so that more accurate selection
decisions can be made.
If we can assume that self-monitoring is linked
to one’s success in a job search, then recruiters must
be aware of the effect that this factor may have on
organizational outcomes. Based on the current study,
organizations tend to disproportionately offer a second
interview, extend offers to, and hire individuals who
can adapt to situations and present themselves favorably to others as needed. This may offer a competitive
advantage such that the workforce of an organization
is flexible, malleable, and can respond to change. This
finding might be relevant for organizations when examining or evaluation their selection criteria. Perhaps
more explicit consideration of the personality aspect is
warranted. If self-monitoring is not a valid criterion to
use for selection into a particular position, however, its
presence may unduly influence those involved in the
selection decision.
In view of this argument, recruitment and selection methods and processes may help determine the
prevalence of hiring high self-monitors. If the recruiting procedures are poorly designed (e.g., interviews are
unstructured, no work sample or performance testing is
conducted) then recruiters and organizational decision
makers are likely to be influenced more heavily by high
self-monitors due to more opportunities for impression
management associated with subjective assessment.
However, a well-designed recruitment and selection
process that includes work sample tests, structured interviews, and behavioral simulation tests, for example, is
likely to increase objectivity in the selection process and
The results strongly support the role of selfmonitoring behavior in three phases of job search success.
It was hypothesized that a person’s score on self-monitoring accounts for significant variance in three job search
success measures beyond that explained by age, months
of work experience, undergraduate GPA, a standardized
test score (the GMAT) and grade point average after three
semesters of graduate school. The incremental change in
the percentage of variance explained in all three measures
of job search success when the self-monitoring predictor
was added to the demographic and background variables
confirmed the three hypotheses posed in this study.
The magnitudes of the zero-order correlations
show that one’s self-monitoring is strongly related to all
three aspects of job search success: 0.63 with number
of second interviews, 0.43 with number of job offers,
and 0.36 with early job acceptance. Further, none of the
zero-order correlations between the demographic and
background variables with any of the three job search
success measures were significant, with the sole exception of a negative relationship between age and early job
acceptance ((p <.05).
Taken together, these results emphasize the
relative importance of self-monitoring in job search outcomes. The higher a person scores on self-monitoring,
the more likely he/she is to receive second interviews, job
offers, and to make an early decision to accept a job.
There are several plausible explanations for these
findings. First, job candidates high on self-monitoring
may influence the perceptions of recruiters, and others
involved in the selection process, of their goodness of
“fit” with the job sought. Because of a relative lack of detailed information regarding the job candidate’s technical
job competence, perhaps recruiters relied upon subject’s
ability to portray themselves as good potential job
candidates and employees who are a good match for the
position.
A second reason that the effects of GPA, MWE,
GMAT and other likely predictors of job search success are not as strong as self-monitoring may lie in the
recruiter’s perception that all MBAs have a sound technical background and thus look to other variables (e.g.,
adaptability, flexibility) upon which to base decisions.
Earlier research on MBA recruitment (e.g., Kane, 1993)
provides support for this possibility. Kane (1993) found
that recruiters reported interpersonal skills, communication skills, and teamwork skills were more important
criteria than technical skills or work experience for any
category of positions (i.e., general management, functional specialty areas, and commissioned sales).
Volume 9, 2006
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The Role of Self-Monitoring in Job Search Success: A Field Study
decrease the effects of self-monitoring behavior.
As with any study involving the use of self-report
measures, this investigation has its limitations that may
be overcome in future research. Additional personality variables that may be factors in job search success
(e.g., extroversion, conscientiousness) can be included
to determine the relative importance of self-monitoring
behavior. Further, the sample size is rather small (n= 40)
and involves a narrow range of job candidates in terms
of age and other background variables such as race or
cultural orientation. Interview criteria used by recruiters
was also unknown. Finally, it would be useful to add
a time dimension to track subsequent job success (e.g.,
the number and timing of promotions, salary increases,
job tenure).
2. Bernthal, P. and Wellins, R. (2006). Growing leaders. Leadership Excellence, Vol. 23, No. 3, p. 8.
3. Caldwell, D.F., and O’Reilly, C.A., III (1982).
Responses to failure: The effects of choice and responsibility on impression management. Academy of Management Journal, Vol. 25, pp. 121-136.
4. Caligiuri, P.M., and Day, D.V. (2000). Effects of
self-monitoring on technical, context, and assignmentspecific performance. Group & Organizational Management, Vol. 25, pp. 154-174.
5. Day, D.V., Schleicher, D.J., Unkless, A.L., and
Hiller, N. J. (2002). Self-monitoring personality at
work: A meta-analytic investigation of construct validity. Journal of Applied Psychology, Vol. 87, No. 2, pp.
390-401.
CONCLUSION
In this study, self-monitoring behavior by job
seekers is shown to be a predictor of job search success
during each of the three phases of the process: second
interviews, offers extended, and early job acceptances.
The subsequent effects of this phenomenon for the organization should be recognized. For example, initial
evidence from this study indicates that recruiters and
others involved in the selection process are susceptible to
a candidates’ adeptness at presenting himself or herself in
a favorable light in no way reflects the person’s technical
competence or work experience, which could be critical
factors for subsequent job success.
6. Dobbins, G.H., Fahr, J., and Werber, J.D. (1993).
The influence of self-monitoring on inflation of gradepoint averages for research and selection purposes.
Journal of Applied Social Psychology, Vol. 23, No. 4,
pp. 321-334.
7. Dobbins, G.H., Long, W. S., Dedrick, E. J., and
Clemons, T. C. (1990). The role of self-monitoring and
gender on leader emergence: A laboratory and field study.
Journal of Management, Vol. 16, No. 3, pp. 609-618.
8. Douglas, C., Frink, D. D., and Ferris, G. R. (2004).
Emotional intelligence as a moderator of the relationship
between conscientiousness and performance. Journal of
Leadership and Organizational Studies, Vol. 10, No. 3,
pp. 2-14.
Implications for Educators
By increasing students’ awareness that learning as much as they can about an organization’s culture
and environment prior to engaging in a job interview
may help them to discern the right fit or match for them,
faculty members perform a positive service for students.
Students who are low SMs might also be aware that if
the match isn’t compatible that they can potentially be
at a disadvantage relative to high SM job candidates
who are more naturally adept at portraying themselves
as the best person for job. Long term consequences such
as performance, promotions, and career mobility can be
effected.
9. Flynn, F.J., Chatman, J.A., and Spataro, S.E. (2001).
Getting to know you: The influence of personality on
impressions and performance of demographically different people in organizations. Administrative Science
Quarterly, Vol. 46, No. 3, pp. 414-446.
10. Gangestad, S. W., and Snyder, M. (2000). Selfmonitoring: Appraisal and re-appraisal. Psychological
Bulletin, Vol. 126, No. 4, pp. 530-555.
REFERENCES
11. Goleman, D. (1995). Emotional Intelligence. New
York: Bantam Books.
1. Barrick, M.R., Parks, L., and Mount, M.K. (2005).
Self-monitoring as a moderator of the relationships
between personality traits and performance. Personnel
Psychology, Vol. 58, No. 3, pp. 745-768.
Volume 9, 2006
12. Goodwin, R. & Pang Yew Soon, A. (1994). Self-monitoring and relationship adjustment: A cross-cultural analyses.
The Journal of Social Psychology, Vol. 134, No. 1, pp. 35.
17
Palmetto Review
Kimberly Freeman
13. Graf, A. and Harland, L.K. (2005). Expatriate
selection: Evaluating the discriminant, convergent, and
predictive validity of five measures of interpersonal
and intercultural competence. Journal of Leadership &
Organizational Studies, Vol. 11, No. 2, pp. 46-63.
23. Snyder, M., Berscheid, E., & Matwychuk, A. (1988).
Orientations toward personnel selection: Differential
reliance on appearance and personality. Journal of Personality and Social Psychology, Vol. 54, pp. 972-979.
24. Snyder, M., and Gangestad, S. (1982). Choosing
social situations: Two investigations of self-monitoring
processes. Journal of Personality and Social Psychology,
Vol. 43, pp. 123-135.
14. Gudykunst, W., Yang, S., & Nishida, T. (1987).
Cultural differences in self-consciousness and self-monitoring. Communication Research, Vol. 4, pp. 7-34.
15. Jenkins, J.M. (1993). Self-monitoring and turnover:
The impact of personality on intent to leave. Journal of
Organizational Behavior, Vol. 14, No. 1, pp. 83-91.
25. Snyder, M., and Gangestad, S. (1986). On the nature
of self-monitoring: Matters of assessment, matters of
validity. Journal of Personality and Social Psychology,
Vol. 51, pp. 125-139.
16. Kane, K.F. (1993). MBAs: A recruiter’s-eye view.
Business Horizons, Jan.-Feb., pp. 65-71.
26. Turnley, W.H. and Bolino, M.C. (2001). Achieving desired images while avoiding undesired images:
Exploring the role of self-monitoring in impression
management. Journal of Applied Psychology, Vol. 86,
No. 2, pp. 351-360.
17. Kilduff, M., and Day, D. (1994). Do chameleons
get ahead? The effects of self-monitoring on managerial
careers. Academy of Management Journal, Vol. 37, No.
4, pp. 1047-1061.
18. McFarland, L.A., Ryan, A.M., and Krista, S.D.
(2002). Field study investigation of applicant use of
influence tactics in a selection interview. The Journal
of Psychology, Vol. 136, No. 4, pp. 383-399.
27. Zaccaro, S.J., Foti, R.J., and Kenny, D.A. (1991).
Self-monitoring and trait-based variance in leadership:
An investigation of leader flexibility across multiple
group situations. Journal of Applied Psychology, Vol.
76, No. 2, pp. 308-315.
19. Mehra, A., Kilduff, M., and Brass, D.J. (2001). The
social networks of high and low self-monitors: Implications for workplace performance. Administrative Science
Quarterly, Vol. 46, pp. 121-146.
28. Zweigenhaft, R. L., and Cody, M. L. (1993). The
self-monitoring of black students on a predominantly
white campus. The Journal of Social Psychology, Vol.
133, No. 1, pp. 5.
20. Miller, J. S., and Cardy, R. L. (2000). Self-monitoring and performance appraisal: Rating outcomes in
project teams. Journal of Organizational Behavior, Vol.
21, No. 6, pp. 609-626.
ABOUT THE AUTHOR
Kimberly A. Freeman is a visiting professor at Winston-Salem State University in the School
of Business and Economics. She previously taught at
Wake Forest University’s Babcock Graduate School of
Management and holds an MBA and Ph.D. from Indiana
University—Bloomington. She has published articles
in Journal of Management, Human Resource Management Review, Small Group Research, The International
Executive, Journal of Management Systems, Business
Horizons, and elsewhere.
21. Snyder, M. (1974). The self-monitoring of expressive behavior. Journal of Personality and Social
Psychology, Vol. 30, pp. 526-537.
22. Snyder, M. (1987). Public appearances/private
realities: The psychology of self-monitoring. San Francisco: Freeman.
Volume 9, 2006
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Palmetto Review
MANAGEMENT AS A LIBERAL ART
George S. Lowry
Edward D. Showalter
Randolph-Macon College
ABSTRACT
This paper explores the connection of traditional content in principles of management courses with the liberal
arts. While not initially obvious, the topics covered in the general “principles” course represent a tremendous breadth
of fields of study, not unlike that found in a liberal arts curriculum. Recognition of this connection can facilitate a
depth of appreciation with applicability to management courses beyond the principles level. To that end, this paper
provides a functional description of the field of management, a brief overview of the liberal arts, and finally makes
connections between the core content of traditional principles of management courses and the liberal arts.
INTRODUCTION
The curriculum of collegiate academic institutions is influenced by two major forces; the traditions
of higher education (i.e. the liberal arts) and the market.
And while the business curriculum continues to attract
significant student interest (which helps maintain enrollments for the schools), its enrollment dominance does
not come without some level of disdain by those in other
fields, particularly those in the liberal arts. This paper
explores the basis of a liberal arts education, then shows
an obvious connection between the topical presentation
of traditional principles of management concepts and
the liberal arts. Before addressing these two, however,
a simplifying framework of management is needed.
emphasizes the functional activities of all organizations
while over-laying the traditional process of management
(e.g. planning, organizing, leading, controlling).
Production, marketing, and finance form the basic functional structure of all organizations. Production
is concerned with the entire transformation process, from
acquisition of resources to final distribution of finished
goods (and waste). Marketing is broadly defined as
communications. The marketing function communicates information about the organization to the outside
world (advertising, promotion, public relations, etc.) and
gathers information from the outside for distribution and
use inside (sales orders, focus groups, environmental
scanning, etc.). Finance is concerned with tracking the
flow of resources through the organization and includes
everything from fund-raising/capital acquisition through
bookkeeping/auditing to process control. Generally, all
activities within an organization fall into one of these
basic “business” functions. All organizations, whether
for-profit or not-for-profit, utilize all three. Obviously,
some organizations rely on some functions more than
others, and the degree of sophistication varies greatly
with size and scope of the organization.
Using business function as the reference point,
the management process (i.e. planning, organizing, leading, and controlling) more clearly becomes a means to an
end. Often, students see the process as the end in itself,
never connecting the process to the practice of management. And while this is not uncommon in a survey
course such as the principles of management course, the
challenge is to shift the emphasis to encourage critical
thinking and deeper learning.
A FRAMEWORK FOR MANAGEMENT
As a discipline, management is complex. Often
the detail of its study overshadows the general precept,
suggesting that functions dominate practice. A simplifying construct redirects the emphasis, which supports
a means-oriented approach to conceptualizing the field
and thus to teaching the subject. This construct presents
“management” as a process, present at all levels of an
organization. It coordinates, directs, and facilitates the
activities of the organization. And, as a field of inquiry,
management finds application in all three of the basic
functions common to all organizations, profit or notfor-profit: Production, Marketing, and Finance. That
is to say, management is not an end in itself, but rather
is present in all of the specific areas of operation within
the organization. Using this framework can help reduce
the compartmentalizing of learning fostered by the traditional textbook approaches. In particular, this framework
Volume 9, 2006
19
Palmetto Review
George S. Lowry, Edward D. Showalter
THE LIBERAL ARTS
“Until recently, the shifting sands of practitioner
judgment were the major if not the only source
of knowledge about how to organize and run
an enterprise. Now research on leadership,
management, and organization, undertaken by
social scientists, provides a more stable body of
knowledge than has been available in the past.”
(Likert, 1967, 1).
Academics today are influenced by the educational traditions of the past and are inextricably connected to the liberal arts. However, the liberal arts have
evolved from their origins in the middle ages as artes
liberales; a normative educational system. Encouraged
by a desire for deeper understanding of religious texts,
language and grammar (along with literature), history,
moral instruction, and the art of rhetoric (with logic as
an adjunct) emerged. Mathematics and the sciences
were necessary foundations for factual knowledge, and
music was studied as a practical matter. Specialization
in any area was eschewed, its pursuit tantamount to selfindulgence. Philosophia became the catch-all phrase,
naming the entire field of learning. Over the centuries,
debate about the true definition of the liberal arts continued. Consistent themes exist today, however. Under its
tradition, the liberal arts broaden the mind of the student
by exposing them to a variety of theories and ideas. The
process of learning is one of assimilation, then critical
analysis. Some suggest the only true foundation lies in
classical texts, while others see the path illuminated by
“free thinking.”
In reality, the explicit dimensions of a liberal
arts education often are the result of negotiated political
interests embodied in academic disciplines within the
academy, both individually and generally. A non-specific
accumulation of knowledge (i.e. truth) evident in the past
has given way to core curricula and general education
programs which encourage the very specialization denounced in the classical model. And, to the displeasure of
the proponents of the liberal arts tradition (however modified over time), these areas of specialization (often referred
to as majors or minors) consume increasing proportions of
the student’s undergraduate (liberal arts) studies.
A dedication to the liberal arts—to broaden the
minds of students, to open them to truth, discipline, and
critical evaluation—may not be lost in the pursuit of
specialty. The bane of the liberal arts enthusiast (the
business curriculum) may indeed contain the very seeds
needed for enlightened inquiry.
Obviously, any academic discipline finds its origins in pure empiricism, and this is true of management.
However, the field of management has been a cohesive
discipline worthy of inclusion not only in schools of business but also in the liberal arts for quite some time.
Connections in the Standards
The content areas embraced by the liberal arts
community appear to be supported by The Association
to Advance Collegiate Schools of Business (AACSB)
in their general guidelines for general management
programs and in the common contents of standard Principles of Management texts. This section helps clarify
these connections by more closely examining the topics
covered in current Principles textbooks, delineating the
connections of the AACSB guidelines to the chapter topics, and finally showing connections between the chapter
topics and fields in the liberal arts.
By analyzing the chapter coverage of several
Principles textbooks from different publishers, a common content list was developed (Table 1). Seventy-six
chapters in four texts (Robbins, 2005; Krietner, 2004;
Daft, 2003; Jones, 2003) cover 19 distinct content areas
(including introductory chapters). Of these 19 areas, only
4 appear in less than three of the four texts, and those
topics are covered to a greater or lesser extent elsewhere
in the texts.
TABLE 1
Principles of Management Test Topics
Principles of Management
Text Topics
Communications
Control
Culture, Corporate Culture
Decision Making, Decision Theory
Diversity
Entrepreneurship/Small Business
Ethics, Social Responsibility
Groups and Teams
Historical Perspectives
Human Resources
Information Systems
International Perspective
Introduction
Leadership/Motivation/OB
Negotiations
Operations
Organizational Theory
Planning and Goal Setting
The Changing Environment
Total Chapters in 4 texts
PRINCIPLES OF MANAGEMENT AND THE
LIBERAL ARTS
The perception exists in some minds that the
field of management is based primarily on the intuitive
expertise of practicing managers. While early in the development of the field, this may have been partially true
(e.g. Barnard, 1938; Fayol, 1949), the reality changed
long ago even if the perception did not. Likert stated
in 1967,
Volume 9, 2006
20
Number of
Chapters
4
4
3
4
2
2
3
4
4
4
2
4
4
10
2
3
5
8
4
76
(not in Kreitner)
(Not in Kreitner or Robbins)
(Not in Kreitner or Robbins)
(not in Jones and George)
(Not in Kreitner or Robbins)
(not in Daft or Robbins)
(not in Kreitner)
Palmetto Review
Management As A Liberal Art
While the AACSB does not prescribe specific courses in
the curriculum, it does suggest areas of coverage, all of
which are included in the listing in Table 2. The second
column of Table 2 indicates the connections between
the text topics and the AACSB guidelines.
TABLE 3
Topics (other than Introductory Chapters) covered in at least
three Texts and Related Liberal Arts Fields
Principles of Management Text Topics
Communications
Control
Culture, Corporate Culture
TABLE 2
Principles of Management Text topics as they relate to
AACSB Area Coverage
AACSB Topics List
(adapted from AACSB, 2004, 67)
Global, environmental, political,
economic, legal, and regulatory
context for business.
Individual ethical behavior and
community responsibilities in
organizations and society.
Management responsiveness to ethnic, cultural, and gender diversity.
Statistical data analysis and management science as they support
decision-making processes throughout an organization.
Information acquisition, management, and reporting for business
(including information management
and decision support systems for
accounting, production, distribution, and human resources).
Creation of value through the integrated production and distribution
of goods, services, and information (from acquisition of materials
through production to distribution
of products, services, and information).
Group and individual dynamics in
organizations.
Human resource management and
development.
Finance theories and methods;
financial reporting, analysis, and
markets.
Strategic management and decision-making in an integrative
organizational environment.
Other management-specific knowledge and skills as identified by the
school.
Decision Making, Decision Theory
Ethics, Social Responsibility
Principles of Management Text Topics
Groups and Teams
Culture, Corporate Culture; Diversity; International Perspective; Introduction; The Changing
Environment
Historical Perspectives
Human Resources
Culture, Corporate Culture; Diversity; Ethics,
Social Responsibility
International Perspective
Culture, Corporate Culture; Diversity
Leadership/Motivation/OB
Operations
Control; Decision Making, Decision Theory
Organizational Theory
Planning and Goal Setting
Control; Decision Making, Decision Theory;
Information Systems
The Changing Environment
CONNECTIONS IN THE LITERATURE
Control; Operations
Another method for establishing the connection between the management field and the liberal arts
is to look at intersections in the literature. While, again,
not an exhaustive list, several references are offered to
show the connections between the liberal arts to management. As a simplifying framework, the three traditional divisions of the liberal arts are used and include
the Humanities, Social Sciences and Natural Sciences/
Mathematics. Many more examples exist and it is clear
that a greater representation exists in some of the three,
and to a lesser extent in others.
Communications; Control; Diversity; Groups
and Teams; Leadership/Motivation/OB
Diversity; Human Resources
Control; Negotiations
Culture, Corporate Culture; Decision Making,
Decision Theory; Planning and Goal Setting;
The Changing Environment
Historical Perspectives; International Perspective; Organizational Theory
Humanities
Connections to the humanities are inescapable.
History, composition & grammar, languages/communications, philosophy, religion, and other fields are obviously linked to the study of management. Of most
recent interest is the study of ethics and morality. Lawrence Kohlberg (1976) connects ethics to the development of moral development and then to specific organizations. His focus was on individual development, but
with implications to groups.
Other forms of connection are apparent. The
Academy of Management Annual Meetings have for
several years now included competitive tracks in “Man-
(adapted from AACSB, 2004, 67)
Table 3 presents 14 areas of coverage (non-introduction topics covered explicitly in three or more of
the texts) and a set of possible connections between the
management content areas and related liberal arts fields.
This set of connections is not meant to be exhaustive,
but suggestive of potential connections between management and the liberal arts.
Volume 9, 2006
Related Liberal Arts Fields
Communication Studies,
English/Language, Rhetoric
Systems Theory, Entropy,
Biology, Physics, Mathematics,
Economics
Sociology, Anthropology,
Psychology
Sociology, Statistics, Mathematics, Philosophy, Psychology
Religion, Economics, Law
Philosophy
Sociology, Psychology, Political
Science
History
Economics, Psychology,
Education
International Studies, Sociology,
Political Science, Economics
Psychology, Sociology
Mathematics, Physics,
Chemistry, Biology
Sociology
Mathematics, Sociology,
Economics, Psychology,
Political Science
Sociology
21
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George S. Lowry, Edward D. Showalter
agement, Spirituality, and Religion”, “Management History”, “Organizations and the Natural Environment”,
as well as an “Academy Arts” division which accepts
paintings and sculptures as well as poetry and literature.
In addition, The Hartwick Humanities in Management
Institute publishes a series of management cases based
on classic literature and film, and other examples of using classic literature are found throughout case books
and management texts. Sage publications announced in
2005 that one of the most downloaded articles from The
Journal of Management Education was Jim McCambridge’s (2003) study on 12 Angry Men.
discuss his work without venturing into an exploration
of the liberal arts. In his best-selling “Images of Organization” he discusses the importance and application of metaphor (rhetoric and literature) and then uses
metaphor to explore management as represented by:
biological science (natural selection, variety of species,
population ecology), brains (psychology), cultures (sociology and anthropology), political systems, psychic
prisons (philosophy using Plato’s Cave metaphor), logics of change (mathematics – chaos theory), and instruments of domination (sociology) (Morgan, 1997).
Natural Sciences/Mathematics
Behling (1980) makes the case that despite arguments against using the natural science approach to
study social organizations, none of the problems the approach generates are insurmountable, and the approach
is the best tool available.
Herbert Simon (1957) made many contributions to the discipline, but in a variety of sub-fields, including decision theory and artificial intelligence. His
reflections on his choice of educational direction show
the multidisciplinary foundation that shaped his contributions.
Social Sciences
Irving Janis states that his work is multidisciplinary. In his Preface to “Victims” he states “A final
note for scholars: This book obviously is at the intersection of three disciplines – social psychology, political
science, and history” (Janis, 1972, vi). Nowhere in his
preface does he refer to or suggest that his is a management work, however his work is cited in three of the
four management textbooks reviewed in this present
study.
When Likert published his work, he was the
Director for the Institute for Social Research and Professor of Psychology and Sociology at the University of
Michigan. The following paragraph clearly establishes
management as a social science.
By the time I was ready to enter the University of Chicago, in 1933, I had a general sense
of direction. The social sciences, I thought,
needed the same kind of rigor and the same
mathematical underpinnings that had made
the “hard” sciences so brilliantly successful. I
would prepare myself to become a mathematical social scientist. By a combination of formal
training and self study, the latter continuing
systematically well into the 1940s, I was able to
gain a broad base of knowledge in economics
and political science, together with reasonable
skills in advanced mathematics, symbolic logic,
and mathematical statistics (Simon in Linbeck,
1992).
“The art of management can be based on verifiable information derived from rigorous, quantitative research. Independent investigators can
repeat the research and test the validity of the
findings. Not only is the body if knowledge more
stable and accurate, but it is likely to grow continuously as the results of additional research
on management are accumulated. Quantitative
research anywhere in the world can add to this
body of knowledge. Its rate of growth can be
accelerated by increasing the expenditures for
social science research focused on organizations” (Likert, 1967, 1-2).
Norbert Wiener combined his training and interests in mathematics and engineering into a multiplicity of theoretical and applied models contributing
to probability theory, decision theory, communications,
and organizational control.
Abraham Maslow’s hierarchy (1943) is presented in all four management texts (and many others)
as the introduction to the discussion of needs based motivation. All the texts move on from there with numerous other motivation theories – more or less directly related to business management – but the starting point of
Maslow clearly connects the discipline to psychology.
While Gareth Morgan’s background is primarily from the field of management, it is impossible to
Volume 9, 2006
…these [experimental and mathematical] concepts have combined with the engineering preoccupations of a professor of the Mathematical
Institute of Technology to lead me to make both
theoretical and practical advances in the theory
22
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Management As A Liberal Art
of communication, and ultimately to found the
discipline of cybernetics, which is in essence a
statistical approach to the theory of communication (Weiner, 1948).
provide opportunities for extensions. First, the fundamental definition of the liberal arts is not universally
agreed. Using this paper’s narrow approach may be
insufficient or lead to illogical conclusions. Next, it is
assumed that the Principles of Management is generally
taught using a text similar to the four referenced in this
paper. It may be the case that such a course follows
another text or framework. In such a case, the claim of
a liberal arts connection may not exist. Finally, there
is always the question of completeness. Arbitrarily
setting limits on examples opens the door to criticism.
There are likely more and better examples of seminal
works, authors, contributors, and connections to the liberal arts. This paper is a first attempt at addressing the
concept of management as a liberal art.
Ludwig von Bertalanffy makes clear the difficulties of separate disciplinary pursuit, thus calling for
a unified approach to theory development; a general
systems theory. His clarion call is for integration, not
isolation.
“Modern science is characterized by its everincreasing specialization, necessitated by the
enormous amount of data, the complexity of
techniques and of theoretical structures within
every field. Thus science is split into innumerable disciplines continually generating new subdisciplines. In consequence, the physicist, the
biologist, the psychologist and the social scientist are, so to speak, encapusulated in their
private universes, and it is difficult to get word
from one cocoon to the other...”
REFERENCES
1. AACSB International. (2004). The Association
to Advance Collegiate Schools of Business Eligibility
Procedures and Accreditation Standards for Business
Accreditation. Adopted: April 25, 2003 Revised: January 01, 2004
“These considerations lead to the postulate of a
new scientific discipline which we call general
system theory. It’s subject matter is formulation
of principles that are valid for “systems” in
general, whatever the nature of the component
elements and the relations or “forces” between
them...”
2. Barnard, C. (1938). The Functions of the Executive. Cambridge, MA: Harvard University Press.
3. Behling, O. (1980). The Case for the Natural Science Model for Research in Organizational Behavior
and Organization Theory. Academy of Management
Review. 5(4), 483-490.
“It seems, therefore, that a general theory of
systems would be a useful tool and providing on
the one hand, models that can be used in, and
transferred to, different fields, and safeguarding, on the other hand, from vague analogies
which often have marred the progress in these
fields” (von Bertalanffy, 1951).
4. Boyer, Ernest L. (1991). Scholarship Reconsidered: Priorities of the Professorate. Princeton, NJ: The
Carnegie Foundation for the Advancement of Teaching.
5. Daft, R. (2003). Management, 6th ed. Mason, OH:
Thompson/South-Western.
CONCLUSION
6. Fayol, H. (1949). “General and Industrial Administration”. Sir Isaac Pitman & Sons: London.
This paper connects the study of management
to the liberal arts. Intended as a survey, the Principles
level course provides a broad representation of the field
of management, both in theory and in practice. The
theory supporting the discipline is based on the work
founded in other fields; those constituting the traditional
liberal arts. Because management, at least as portrayed
at the Principles level, represents such a broad range of
fields, it can be considered a liberal art in itself.
Several limitations are present in this paper and
Volume 9, 2006
7. Janis Irving L. (1972). Victims of Groupthink Boston, MA: Houghton Mifflin.
8. Janis, I. L. (1971, November) Groupthink. Psychology Today Magazine, 43-46.
9. Jones, G. & George, J. (2003). Contemporary
Management, 3rd ed. Boston: McGraw-Hill/Irwin.
23
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George S. Lowry, Edward D. Showalter
ABOUT THE AUTHORS
10. Kimball, Bruce A. (1995). “A Typology of Contemporary Discussion” in Orators and Philosophers: A
History of the Idea of Liberal Education. The College
Board. pp. 205-241.
George S. Lowry is Professor of Business at
Randolph-Macon College, teaching management and
finance. He has numerous publications covering a diverse field of interest, including innovative teaching and
applied finance and has served as an officer in both the
Southeast Decision Sciences Institute and Southeastern
Institute for Management Science and Operations Research. Additionally, George is active with the Society
for the Advancement for Management (SAM), serves
on the editorial review board of the Coastal Business
Journal and is co-managing editor of the Virginia Economic Journal. He earned his Ph.D. in Management
from Virginia Commonwealth University.
11. Kohlberg, Lawrence. (1976). Moral development
and Behavior: Theory, Research, and Social Issues.
Issues T.
Lickona, ed. New York: Holt, Rienehart, and Winston.
12. Krietner, R. (2004). Management, 9th ed. Boston:
Houghton-Mifflin.
13. Likert, R. (1967). The Human Organization: Its
Management and Value. McGraw-Hill: New York.
14. Lilienthal, David E. (1966). Management: A Humanist Art. New York: Columbia University Press.
Edward D. Showalter is an assistant professor
at Randolph-Macon College where he teaches courses
in Management and Organizational Behavior. He has
presented papers at the Southeastern Chapter of the
Institute for Management Science and Operations Research, the Southeastern Chapter of the Decision Sciences Institute, and the National Meetings of the Academy of Management. He has published in the Journal
of Distance Learning Administration, and serves on
the editorial board of the SAM Advanced Management
Journal. He received both his MBA and Ph.D. in Management from Virginia Commonwealth University.
15. Maslow, A. H. (1943). A Theory of Human Motivation. Psychological Review, 50, 370-396.
16. McCambridge, J. (2003) 12 Angry Men: A Study
in Dialogue Journal of Management Education, 27(3),
384-401.
17. Morgan, Gareth (1997). Images of Organization
(New Edition) Thousand Oaks, CA:Sage.
18. Naughton, Michael J. and Bausch, Thomas A.
(1996). “The Integrity of a Catholic Management Education.” California Management Review. Summer, v38,
n4, p. 118 (23).
19. Robbins S. & Coulter, M. (2005). Management,
8th ed. Upper Saddle River, NJ: Pearson/Prentice Hall.
20. Simon, Herbert. (1992). Nobel Lectures, Economics 1969-1980. Assar Lindbeck, ed. World Scientific
Publishing Company, Singapore.
Volume 9, 2006
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FACTORS IMPACTING ONE’S DESIRE TO TELECOMMUTE:
AN INVESTIGATION OF STUDENT PERSPECTIVES
Beth Clenney
Thomas E. Gainey
University of West Georgia
ABSTRACT
Telecommuting assists individuals in balancing the demands in their personal and professional lives. And,
employers increasingly offer telecommuting programs as a benefit. Yet, our study reveals that individuals have very
different perspectives when it comes to this work alternative. Results of our student survey indicate that many of
these differences are attributable to perceptual, demographic, and work experience factors.
ing home. Thus, the time normally spent in daily traffic
is used more productively, and employees save on gas
and parking expenses. Further, there is evidence that
spending less time commuting each day can significantly
reduce stress (Tan-Solano & Kleiner, 2001). Therefore,
employees feel better, are more satisfied, and produce
better quality work.
There are potential benefits for employers who
offer telecommuting programs as well. Specifically,
previous studies have revealed that telecommuting significantly reduces both absenteeism and turnover (Wells,
2001). Additionally, research has shown that telecommuting has resulted in a 20 to 40 percent increase in
productivity (Manochehri & Pinkerton, 2003; McLarty,
2004). Further, many employers find that by offering
telecommuting options, they are able to open up new
labor pools and recruit more highly talented employees
(Wells, 2001). In fact, as broadband Internet connections become more accessible and individuals become
more comfortable with the idea of working remotely,
more employers are beginning to offer telecommuting as
a perk to recruit top executives (Armour, 2004; Maher,
2004).
However, despite the many benefits of telecommuting for both the employee and the employer, there is
evidence that not all individuals embrace this work alternative (Harpaz, 2002). Although the majority of Fortune
1000 firms offer telecommuting, more than half say that
only between 1 and 5 percent of employees participate in
these programs (Wells, 2001). Thus, this study examines
individual perceptions of telecommuting and identifies
some factors that might influence these perceptions.
INTRODUCTION
Increasingly, today’s employees seek a balance
between work activities and their personal lives (Kimberly & Lowe, 2003). Additionally, employers continue
to look for ways to recruit and retain top talent in their
firms (HR Focus, 2004). Telecommuting may offer a
reasonable solution for both workers and employers to
realize these goals.
The International Telework Association &
Council (ITAC) defines telecommuters as employees
who work from home at least one day per month (Smith,
2004). And, based on recent studies, telecommuting is
an increasingly popular work alternative. For instance,
a five-year Society for Human Resource Management
(SHRM) benefits survey of 754 human resource (HR)
professionals revealed that 37 percent of employers offered telecommuting in 2001 -- a 17 percent increase
from 1997 (Wells, 2001). Additionally, the number of
telecommuters in the U.S. rose from 23.5 million in
2003 to about 24.1 million in 2004 and, according to
the Dieringer Research Group, the number of workers
telecommuting on a full-time basis increased from 8.8
million in 2003 to 12.4 million in 2004 (Maher, 2004).
Telecommuting offers a number of potential
benefits to organizations and their employees. From the
employee’s perspective, telecommuting offers a way to
achieve a better balance between work and family life.
And, according to a 2003 survey, about 85 percent of
employees reported that achieving this balance was a
top priority (Amour, 2004). Additionally, telecommuting reduces, or often eliminates, long commutes. With
the use of computer and communication technologies,
many employees complete their duties without ever leavVolume 9, 2006
25
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Beth Clenney, Thomas E. Gainey
And, almost another third reported that they would
telecommute 10 hours or less per week if given the opportunity. Only, about 30 percent expressed a desire to
work from home more than 20 hours per week. And, only
9 percent noted that they would telecommute on a fulltime basis. Thus, about 70 percent of our respondents
opted to telecommute 20 hours or less during a typical
work week.
SAMPLE AND RESULTS
Respondent Profile
The sample for this study included 242 management students. Intuitively, it may seem that using a
student sample in this context is inappropriate. However,
we believe that it is reasonable, and even preferable, for
three fundamental reasons. First, a majority of the individuals surveyed are non-traditional students who have
work experience. Specifically, of the 242 individuals
surveyed, 68 percent indicated that they were currently
working full-time or part-time, while 98 percent reported
that they had either current or previous work experience.
Of those currently working, results showed that, on average, they worked approximately 17 hours per week and
had over two years of full-time work experience.
Second, we wanted to survey a diverse sample of
individuals who had worked in a variety of occupations
and had differing levels of work experience. If we limited our sample to full-time workers from one company, it
is possible that the influence of the organization’s culture
would impact the results, thus limiting both the ability to
find statistical differences and the external validity of the
results. Additionally, without including some individuals
in the sample with either no work experience or limited
experience, we would not be able to test the impact that
work experience plays on individual perceptions.
Third, we felt it was important to examine how
future employees view this work alternative. Previous
studies have focused exclusively on individuals already
into their careers, yet employers are increasingly offering telecommuting as a benefit to attract talented new
employees. Thus, it is important to understand to what
extent this work option will be embraced.
As anticipated, survey results revealed not only a
significant difference in work experience, but also a very
diverse group of individuals in terms of demographics.
For instance, the age of those surveyed ranged from 19
to 55 years. Fifty-seven percent of the sample was male
and 43 percent were female. Sixty-nine percent of the
respondents were white, 23 percent African-American,
and 8 percent were other.
TABLE 1
Hours Per Week Respondents
Would Prefer to Work From Home
Hours
Percentage of
Respondents
0
15
6.4%
1-5
7
3.0%
6-10
48
20.5%
11-15
23
9.8%
16-20
74
31.6%
21-25
13
5.6%
26-30
24
10.3%
31-35
9
3.8%
36-40
21
9.0%
Given the popularity of telecommuting and the
trend for individuals to seek more of a balance between
work and home life, we next examined a number of
factors that might impact the decision to telecommute.
Specifically, we looked at the extent to which certain
perceptual factors, demographic differences, and previous work experience were associated with one’s desire
to work from home.
Perceptual Indicators
In our survey, we asked respondents about how
working from home might impact one’s career and the
ability of managers to do their jobs. As Table 2 shows,
we asked about how distractions at home might impact
one’s ability to be productive. To determine the extent to
which individuals viewed telecommuting as potentially
harmful, we asked respondents to respond to two similar
Likert-type items. First, we asked if being physically
located in the office was important to career advancement. Second, we asked if working from home impaired
one’s ability to be promoted. There was a statistically
significant difference in the number of hours respondents
would work from home based on their perception of the
importance of being physically located in the workplace.
Respondents who agreed or strongly agreed that being
physically present in the workplace was important to
Desire to Telecommute
In the survey, we asked individuals how many
hours they would work from home in a typical 40-hour
week, if given the opportunity. Results were unexpected.
Despite the numerous benefits typically associated with
telecommuting, Table 1 shows that not everyone has the
same desire to work from home. Almost a third of the
respondents indicated that they would telecommute only
between 16 -20 hours in a typical 40-hour workweek.
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Number of
Respondents
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Factors Impacting One’s Desire to Relecommute: An Investigation of Stuent Perspectives
one’s career, desired to work from home, on average, just
more than 15 hours per week. Alternatively, respondents
who did not view being physically present in the workplace as important wanted to telecommute about 20 to
23 hours each week.
It is likely that those who wanted to work from
home less often may have felt that being “out of sight”
may lead to being “out of mind” when it comes to promotions. By telecommuting more than half the week, our
respondents may believe that they are alienated from the
social and task networks that can strongly impact career
advancement.
believe that managers give up an element of control when
they allow employees to telecommute. Therefore, they
may question how managers can truly be certain that
their employees are actually doing their work. While
there are certainly ways to monitor productivity outside
of the workplace, it is possible that those subscribing to
a Theory X philosophy may have trouble adjusting to
telecommuting as a legitimate work alternative.
Finally, in examining perceptions, we asked
about how distractions at home might impact one’s desire
to telecommute. Our results showed that respondents
who felt they had too many distractions at home to work
effectively wanted to telecommute significantly less than
those who did not believe that working out of the home
would present a problem. For instance, those who agreed
that there were too many distractions to work from home
reported that they would only telecommute 12.6 hours per
week. Alternatively, respondents who did not believe
they would experience disruptions at home indicated
they would telecommute over 25 hours per week. It is
unclear why some employees felt that their home would
be a distraction. However, we can speculate that having
others living at home, neighbors and friends that are frequent visitors and even one’s personality would impact
the perceptions of our respondent group.
TABLE 2
Perceptual Indicators 1,2
Disagree
or Strongly
Disagree
Neutral
Agree or
Strongly
Agree
Being physically located in the office is important to career
advancement.
23.8 a
20.6 a
15.5
Working from home impairs one’s ability to be considered
for promotions.
21.8 a
19.6 a
15.4
Employees need to be able to meet face-to-face, on a frequent
basis, with their managers to do their jobs. properly.
24.3
18.6 a
15.3 a
Managers can be more effective when they have their
employees close by.
25.5
20.3
15.4
There are too many distractions at my home for me to try to
work there.
25.2
19.4
12.6
Allowing employees to work from their home would likely
result in lower productivity.
22.9
17.7 a
14.6 a
IMPACT ON CAREER
ABILITY TO MANAGE
DISTRACTIONS AT HOME
1
Means represent the average number of hours that respondents would
work from home (out of a 40-hour week) if given the opportunity.
2
In ANOVA comparisons, means with the same letter are not significantly
different.
Demographic Differences
Table 3 reports differences in the hours our
respondents would telecommute based on age, gender,
marital status, race, and number of dependents. Clearly,
the age of our respondents was an important factor. Older
respondents expressed a desire for significantly more
telecommuting hours each week than younger respondents. This was not unexpected. It is likely that individuals who are younger, and who may not have established
the friendship networks of their older counterparts, may
view the workplace as being crucial to developing social
interactions. Thus, the isolation from working at home
may not be particularly appealing. Further, younger
workers, who may have limited experience in the workplace, may feel that being physically present in the office
is crucial to career advancement.
Marital status proved to be another significant
indicator of one’s desire to work from home. Those
respondents who were single reported they would telecommute only 18.4 hours per week if given the opportunity, compared to married respondents who desired, on
average, to telecommute 25.1 hours. Again, this is not
unexpected. Those individuals who are married likely
view telecommuting as an alternative that allows them
more time to spend with their spouse. Conversely, our
single respondents may view the workplace as a plausible
As shown in Table 2, respondents also desired
less work from home when they believed that having
employees and managers in close proximity to each
other was essential to making sure jobs were completed
correctly. In fact, there was almost a 10-hour difference
between the respondents who believed telecommuting
affected one’s ability to manage and those that did not
see a problem. The specific managerial issues that were
important to the respondents are not entirely clear. However, there are two likely sources. First, despite advances
in communication technology, the information richness
associated with face-to-face communication may be a
source of concern. When individuals communicate in
“less rich” ways, the nonverbal cues and instant feedback
opportunities are not available. Thus, while it is likely
dependent on the context, the inability to be in close
proximity to employees may very well present some
managerial challenges. Second, some individuals may
Volume 9, 2006
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Beth Clenney, Thomas E. Gainey
opportunity to meet their future spouse.
Table 3 shows that respondents with dependents
also viewed telecommuting more positively. Specifically,
the results indicate that individuals with dependents
would telecommute over 25 hours per week, while
those with no dependents would only work from home
about 18 hours per week. This significant difference is
most likely attributable to greater demands on personal
time for those with family obligations. Telecommuting
allows those with dependents and opportunity to better
balance work and family life. As indicated in Table 3,
neither gender, nor race, was a significant indicator of
one’s desire to telecommute.
time in organizations over the years or that are in the
workplace more each day may feel that time away from
work will not impact their careers in a negative manner.
In fact, those working less hours per week may feel that
they need to be in the office more because they are essentially part-time workers already. These workers may feel
that career mobility is hampered by their part-time status
and that telecommuting may further hinder advancement.
Second, for those who have worked longer, or are currently doing so, telecommuting provides an opportunity
to pursue personal interests outside of the workplace.
As time in the workplace continues to increase, these
individuals may be more receptive to work alternatives
that provide a measure of flexibility.
TABLE 3
TABLE 4
Demographic Differences 1,2
Work Experience 1,2
Average
Hours
Average
Hours
AGE
•
•
•
19-21
22-23
24-55
17.1 a
19.7 a,b
24.6 b
FULL-TIME WORK EXPERIENCE
GENDER
•
•
Female
Male
19.9
18.5 a
Single
Married
White American
Black American
Other
18.4
25.1
Yes
No
•
1 – 20 Hours
17.6
•
More Than 20 Hours
19.4
•
1 – 3 Days
16.9
•
4 – 7 Days
19.8
Means represent the average number of hours that respondents would work
from home (out of a 40-hour week) if given the opportunity.
1
25.3
18.3
1
Means represent the average number of hours that respondents would
work from home (out of a 40-hour week) if given the opportunity.
2
In t-tests and ANOVA comparisons, means with the same letter are not
significantly different.
In t-tests and ANOVA comparisons, means with the same letter are not
significantly different.
2
MANAGERIAL IMPLICATIONS
Despite the popularity and increased use of
telecommuting, our study revealed that this alternative
work schedule is not equally appealing to everyone.
Specifically, individuals indicated that they would telecommute over a wide range of hours each week, if given
the opportunity. Additionally, results show that these
differences were associated with a number of perceptual,
demographic, and work experience factors. Based on
this study, there are a number of useful recommenda-
Work Experience
While none of the three work experience factors
that we examined were statistically different, the means
reported in Table 4 do show some modest differences.
Specifically, those individuals who have more full-time
work experience and those working more hours and days
per week reported that they would telecommute more
if given the opportunity. This is not surprising for two
reasons. First, individuals who have spent either more
Volume 9, 2006
21.8
DAYS WORKED PER WEEK
19.3 a
18.8 a
15.3 a
DEPENDENTS
•
•
18.7
More Than 5 Years
HOURS WORKED PER WEEK
RACE
•
•
•
1 – 5 Years
•
a
MARITAL STATUS
•
•
•
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Factors Impacting One’s Desire to Relecommute: An Investigation of Stuent Perspectives
tions that can be offered. Five specific recommendations
conclude this paper:
well be that part-time workers look to the workplace as
an important outlet for social interactions. Additionally,
workers who work less hours, have more time to attend
to the personal demands on their time.
1. Begin Slowly
About 70 percent of our respondents indicated
they would prefer to telecommute 20 hours or less each
week. Thus, give employees time to adjust to this work
option and some flexibility in how they use the program.
Attempts to go “cold turkey” with telecommuting might
well be met with resistance. For instance, it might be
useful to gradually increase telecommuting hours until
employees reach an optimum level of comfort and production.
REFERENCES
1. Armour, S. (2004). More bosses getting into the
telecommuting biz. USA Today
Today, November 3, 2B.
2. Harpaz, I. (2002). Advantages and disadvantages
of telecommuting for the individual,organization, and
society. Work Study London, 52:2/3, 74-80.
2. Provide Extensive Feedback
Our results show that those individuals who feel
that telecommuting will negatively impact future promotional opportunities are less likely to take advantage
of this work alternative. It is critical for management to
provide extensive feedback on work performance and
take steps to keep telecommuters “in the loop.” Employees who feel isolated from the organization may be
less receptive to telecommuting.
3. HR Focus. (2004). Telework: The star of flexible
work options. HR Focus, 81:10, S2-S3.
4. Kimberly, F., & Lowe, J. (2003). An examination
of alternative work arrangements in private accounting
practice. Accounting Horizons, 17:2, 139.
5. Manochehri, G., & Pinkerton, T. (2003). Managing
telecommuters: Opportunities and challenges. American
Business Review, 21:1, 9-17.
3. Training is Essential
Individuals in our survey who perceived that
telecommuting inhibited a manager’s ability to do his or
her job or who felt that there were too many distractions
at home to work were less likely to express a desire to
work from home. Thus, training is crucial to both employees and managers. Employees can be instructed on
how to create a work environment at home that is free
of distractions. And, managers can be trained on how
to monitor and lead employees when they are no longer
physically present.
6. Mayer, K. (2004) Corner office shift: Telecommuting rises in executive ranks. Wall Street Journal,
September, 21, B1.
7. McLarty, S. (2004). Why doesn’t everyone telecommute? Communications of the ACM
ACM, 47:11, 12-13.
8. Smith, R.L. (2004). Work at home grows in past
year by 7.5% in U.S. Use of Broadband for work at home
grows by 84%. Retrieved April, 2005, from the
World Wide Web http://www.telecommute.org/news/
ttp://www.telecommute.org/news/
pr090204.htm.
pr090204.htm
4. Consider Your Employees
Demographic differences in the workforce may
well determine the success of a telecommuting program.
Our results show that older, married workers with dependents are more likely to telecommute on a regular basis.
Thus, if an organization is comprised of a younger, single
workforce, the social interaction afforded by the workplace may be an important aspect of the work experience.
Telecommuting programs may not be as attractive among
this group of workers.
9. Tal-Salano, M., & Kleiner, B. (2001). Effects of
telecommuting on organizational behavior. Management
Research News, 24, 123-126.
10. Wells, S. (2001). Making telecommuting work. HR
Magazine, 46:10, 34-45.
5. Examine Your Work Schedules
If your employees primarily work part-time,
telecommuting may not be the answer. In fact, our results indicate that interest in telecommuting was lower
as hours and days worked per week decreased. It may
Volume 9, 2006
29
Palmetto Review
Beth Clenney, Thomas E. Gainey
ABOUT THE AUTHORS
Beth Clenney is a lecturer at the University of
West Georgia. She received her MBA from Georgia
State University and her B.B.A. from the University of
West Georgia. Prior to joining the University of West
Georgia as a lecturer, Mrs. Clenney was employed as a
human resources generalist with a manufacturing firm.
She was also a graduate research assistant while attending
Georgia State University. Mrs. Clenney is a member of
Phi Kappa Phi National Honor Society and Beta Gamma
Sigma National Business Honor Society.
Volume 9, 2006
Thomas W. Gainey is Chairman of the Department of Management and Business Systems in the
Richards College of Business at the University of West
Georgia. He received a Ph.D. in management from the
University of South Carolina and an MBA from Wake
Forest University. His research interests include the
effects of HR outsourcing, employee discipline, and
alternative work systems. His research has appeared in
such journals as Personnel Psychology, Entrepreneurship
Theory and Practice, and Journal of Management.
30
Palmetto Review
A BRIEF REVIEW OF THE SARBANES-OXLEY ACT OF 2002
Gloria Clark
Winston-Salem State University
Wendy Meyers
Nova Southeastern University
ABSTRACT
Prior to 2002, the accounting profession was self-regulated. The American Institute of Certified Public
Accounting (AICPA) controlled and promulgated auditing standards and rules. Additionally, generally accepted accounting principles (GAAP) were primarily the responsibility of the Financial Accounting Standards Board (FASB).
While the Securities and Exchange Commission (SEC) had legal responsibility to set accounting and auditing standards, especially in regard to publicly listed corporations, it allowed the profession through the AICPA and FASB to
self-regulate.
Between 2000 and 2002, a number of events occurred leading to the passage of the Sarbanes-Oxley Act of
2002. The biggest and most public of those events was the 2002 Enron scandal. Other corporations identified with
questionable accounting practices during this time period included Global Crossing, Adelphia Communications,
WorldCom and Tyco. Furthermore, the accounting firm of Arthur Andersen dissolved as a direct result of the negative fallout from these corporate scandals.
On July 30, 2002, President Bush signed one of the most important acts of his presidency, the Sarbanes-Oxley
Act. This paper reviews the Sarbanes-Oxley Act of 2002 and its primary objectives.
IMPACT ON THE
ACCOUNTING PROFESSION
INTRODUCTION
The Sarbanes-Oxley Act of 2002 resulted from
public outcry. Investors, companies and vendors suffered
tremendous financial loss from entrusting their funds to
companies, who “cooked the books.” Investment decisions had been made based upon deceptive and fraudulent
financial statements. From this scandal, Sarbanes-Oxley
emerged.
A description of selected corporate scandals in
North America and Europe that occurred immediately
before the enactment of Sarbanes-Oxley is presented in
Table A1 (page 34). (Sylwia Gornik-Tomaszwewki &
McCarthy -Spring 2005).
The Sarbanes-Oxley Act mandated the following: (1) the creation of the Public Company Accounting
Oversight Board (PCAOB) (2) auditor independence (3)
corporate governance and responsibility (4) disclosure
requrements (5) penalities for fraud and other violations.
These reforms are summarized in Table A2 (page 35)
(Hall & Singleton 2005).
Volume 9, 2006
The accounting profession and industry have
been impacted in a number of significant ways from
Sarbanes-Oxley. Some of the implications include
progressively more positive public impressions of accountants, changes in reporting lines, changes in the roles
for auditors and audit committees, and accounting firm
size.
Reputation of the Accounting Profession
The accounting profession has suffered unfairly
in recent years due to the well publicized accounting
scandals. Those in the profession must work with
Sarbanes-Oxley to regain the public trust. According to
Couston, Leincke, Rexfdord and Ostrosky (2004), the
United States has an outstanding auditing and accounting profession, however, the message in not yet out. The
creation of a government public company accounting
oversight board to monitor and enforce the accounting
profession compliance with Sarbanes-Oxley has begun
to restore public confidence and trust in the profession.
31
Palmetto Review
Gloria Clark, Wendy Meyers
Changes in Reporting Lines
Sarbanes-Oxley changed the reporting lines
(audit committees), roles of the internal and external
auditors (auditor independence) and attestation rules,
which include internal controls over financial reporting. Sarbanes-Oxley created additional accounting
responsibilities and more business for accounting firms,
resulting in increased costs. According to Copeland
(2005), an auditor from Deloitte and Touche, to ensure
compliance, all participants in the financial reporting
“value chain” must share the responsibility of restoring
an appropriate level of trust and confidence in our capital
market system. The links in that system’s value chain
begin with company management. Therefore, the buck
may not stop with management, but certainly starts with
management and continues along the capital markets
value chain (Copeland 2005).
Accounting Firm Size
Accounting firms of all sizes have been impacted
by Sarbanes-Oxley. As a result of the increase in business and/or repositioning of firms to handle the influx
of clients, firms have become more discriminating. Additionally, there have been increases in registration fees
and the cost of professional liability insurance. Actually,
Sarbanes-Oxley is often called the “CPA Employment
Act of 2002” (Green 2005) since it has created a tremendous demand for accounting expertise. “That has resulted
in opportunities for small firms that can help companies
implement the accounting ongoing requirements, take
on engagements the company auditor may no longer
perform or pick up assignments that larger firms forgo
because they are too involved in Sarbanes-Oxley- related
engagements” (Dennis 2005). Effective 2006, all publicly traded companies are required to submit an annual
report of the effectiveness of internal accounting controls.
Therefore, due to the high demand of work by companies
implementing the Sarbanes-Oxley deadline, many firms
have repositioned themselves for the overload.
For example, some companies (Dennis, 2005):
(1) have gotten out of the business of auditing SEC companies (2) have chosen to shed audits because of their
added complexity (3) have shed benefit plan audits as
well as audits to midsize privately held companies – so
they can work on Sarbanes-Oxley related engagement.
(4)have received additional assignments through contacts with existing clients, bankers, lawyers, insurance
companies and benefit plan administrators.
Therefore, Sarbanes-Oxley created work for
everyone in the major market and created practice opportunities as well. Sarbanes-Oxley mandates that public
firm’s cannot work on audit engagements and perform
non-audit services for the same client. Therefore,
firms will have to choose which engagements they will
perform, thus allowing other firms the opportunities.
Consequently, the work is moving downstream at an
incredible rate, which is good for the smaller firms. Currently, the larger firms are networking with each other to
create alliances to receive or alleviate work or complete
full service work to a client, so everyone profits.
Roles for Auditors and Audit Committees
The role of auditors and audit committees
changed as a result of Sarbanes-Oxley in the following
ways:
1. Auditors report to audit committee: Now
auditors will report to and be overseen by a
company’s audit committee.
2. Audit committees must approve all services: Audit committees must pre-approve
all services, both audit/non-audit services
not specifically prohibited, provided by its
auditor.
3. Auditors must report new information to
audit committee: This information includes:
critical accounting policies and practices to
be used, alternative treatments of financial
information within GAAP that have been
discussed with management, accounting
disagreements between the auditor and management, and other relevant communications
between auditor and management.
4. Offering specified non-audit services prohibited: The new law statutorily prohibits
auditors from offering certain non-audit
services to audit clients. These services are
shown in Table A2.
5. Audit partner rotation: The lead audit partner and audit review partner must be rotated
every five years on public company engagements.
6. Employment implications: An accounting firm cannot provide audit services to a
public company if one of that company’s top
officials such as the chief executive officer,
Volume 9, 2006
controller or chief accounting officer, was
employed by the firm and worked on the
company’s audit during the previous year.
CONCLUSION
Sarbanes-Oxley provides a framework for both
accountants and the accounting profession to regain
32
Palmetto Review
ABrief Review of The Sarbanes-Oxley Act of 2002
public trust. Its principal reforms pertain to: (1) creation
of an accounting oversight board; (2) auditor’s independence; (3) corporate governance and responsibility;
(4) disclosure requirements and (5) penalties for fraud
and other violations. These reforms have impacted the
profession and its reputation positively. Reporting lines,
roles of auditors, audit committees, and accounting firm
size have been clarified. Although accounting firms and
its professionals are adhering and implementing these
reforms and the future is looking brighter, Sarbanes-Oxley and other laws will be needed to prevent and deter
further unethical and perhaps illegal activity.
7. Hall, J. and Singleton, T. (2005). Information
Technology Auditing and Assurance Introduction to
Business Ethics and Fraud. 2nd edition, p. 511-513.
8. Sylwia Gornik-Tomaszwewki, Irene McCarthy
(Spring 2005). Response to Corporate Fraud in the
United States and Europe: Towards a Consistent Approach in Regulation. Vol 26, 2, p. 15-23 Retrieved
November 19, 2005 from http://0-proquest.umi.comnovacat.nova.edu/pqweb?did=851740321&FMT=4&clie
ntId=17038&RQT=309&VName=PQD.
ntId=17038&RQT=309&VName=PQD
REFERENCES
1. Copeland, Jim (New York: Apr 1, 2003). Post-Enron Challenges for the Auditing Profession: Accountability. Vol 69, 12, p. 360-364. Retrieved November
19, 2005 from http://0-proquest.umi.comnovacat.nova.
edu/pqweb?did=851740321&FMT=4&clientId=17038
&RQT=309&VName=PQD.
&RQT=309&VName=PQD
2. Coustan, H., Leinicke, L., Rexroad, M., & Ostrosky, J (New York: Feb 2004). Sarbanes Oxley: What
it Means to the Marketplace. Vol 197, 2, p. 43-47)
Retrieved November 19, 2005 from http://0-proquest.
umi.comnovacat.nova.edu/pqweb?did=851740321&F
MT=4&clientId=17038&RQT=309&VName=PQD.
MT=4&clientId=17038&RQT=309&VName=PQD
3. Dennis, Anita (Sept 2005). Practice Management/
Small Firms. Vol 200, 3, pg. 61-66. Retrieved November 19, 2005 from http://0-proquest.umi.comnovacat.
nova.edu/pqweb?did=851740321&FMT=4&clientId=
17038&RQT=309&VName=PQD.
17038&RQT=309&VName=PQD
4. Dennis, Anita (June 2004). Small Firms: Think
Big! Journal of Accountancy. Retrieved November
19, 2005 from https:www.aicpa.org/pubs/jofa/jun2004/
dennis.htm.
5. Dennis, Anita (June 2004). Second CPA firm update: The Sarbanes Oxley cloud has a Silver Lining
– unzip it. Retrieved November 19, 2005 from https:
www.findarticles.com/p/articles/mi_m6280/is_3_200/
ai_n15400283/print.
ai_n15400283/print
6. Green, John W. (Nov 2005). On The Record. Retrieved November 19, 2005 from http://0-proquest.umi.
comnovacat.nova.edu/pqweb?did=851740321&FMT=
4&clientId=17038&RQT=309&VName=PQD.
4&clientId=17038&RQT=309&VName=PQD
Volume 9, 2006
33
Palmetto Review
Gloria Clark, Wendy Meyers
TABLE A1
RECENT MAJOR CORPORATE SCANDALS IN NORTH AMERICA AND EUROPE
Country of Incorporation
USA
USA
Auditor of
Company
Enron
WorldCom
Global
Crossing, Ltd.
ITALY
Parmalat
Finanziara,
SpA
Volume 9, 2006
Consolidated
Accounts
BERMUDA
NETHERLANDS
Industry
Royal Ahold
N.V.
Questionable Accounting
Practices
Arthur Anderson
Widespread use of off-balance
sheet financing in the reporting
of partnership transactions.
Enron was forced to restate its
profits from 1997 through 2000
– lowering its book value by
$1.25 billion.
Arthur Anderson
Reduction of operating expenses by: (1) improperly releasing
certain reserves held Services
against operating expenses,
and (2) re-characterizing certain expenses as capital assets.
Material overstatement of the
reported income by approximately $9 billion.
Telecommunications
Services
Arthur Anderson
Inflation of pro forma values
for cash revenue and adjusted
Earnings Before Interest, Taxes,
Depreciation and Amortization
by including amounts for which
cash was not received or where
there had been non-monetary
exchanged of capital capacity.
Dairy
Deloitte &
Touche (Grant
Thornton-individual accounts)
$3.95 billion in cash and securities supposedly contained in a
Cayman-based bank account
did not exist.
Deloitte &
Touche
Fraudulent inflation of promotional allowances at U.S.
Foodservice, Ahold’s wholly
service-owned subsidiary, the
improper consolidation of joint
ventures through fraudulent
side letters; and other accounting errors and irregularities
which amounted to $880 million.
Energy & Utilities
Telecommunications
Services
Retail Trade/Food
Service
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Palmetto Review
ABrief Review of The Sarbanes-Oxley Act of 2002
TABLE A2
A SUMMARY OF SARBANES-OXLEY REFORMS
Accounting Oversight Board:
The Public Company Accounting Oversight Board (PCAOB)
is empowered to set auditing standards, quality control, and
ethics standards, to inspect registered accounting firms, to
conduct investigations, and to take disciplinary actions.
Corporate Governance & Responsibility:
Committee members are independent; the committee is
required to hire and oversee external auditors.
•
Public companies are prohibited from making loans
to executive officers and directors; and
•
Attorneys are required to report evidence of a
material violation of securities laws or breaches
of fiduciary duty to the CEO, CFO, or PCAOB.
Auditor Independence:
More separation between a firm’s attestation and non-auditing
activities is created. This is intended to specify categories of
services that a public firm cannot perform for its clients, the
9 functions are:
•
Bookkeeping or other services related to the accounting
of records or financial statements
•
Financial information systems design and implementation.
•
Appraisals or valuation services, fairness opinions, or
contribution-in-kind reports.
•
Actuarial services.
•
Internal audit outsourcing services.
•
Management function or human resource.
•
Broker or dealer, investment adviser, or investment
banking services.
•
Legal services and expert services unrelated to the audit.
•
Any other service the PCOAB determines as impermissible.
Issuer & Management Disclosures:
New corporate disclosure requirements are:
•
•
•
Public companies must report all off-balancesheet transactions.
Annual reports filed with the SEC must now
include a statement by management asserting
that it is responsible for creating and maintaining
adequate internal controls and asserting to the effectiveness of those controls and asserting to the
effectiveness of those controls.
Officers must certify that the company’s accounts
“fairly present” the firm’s financial condition and
results of operations. Knowingly filing a false
certification is a criminal offense.
Fraud and Criminal Penalties:
The Sarbanes Oxley Act imposes a range of new criminal penalties for fraud and other wrongful acts. It also creates new
federal crimes relating to the destruction of documents or audit work papers, securities fraud, tampering with documents to
be used in an official proceedings, and actions against whistleblowers.
Volume 9, 2006
35
Palmetto Review
Gloria Clark, Wendy Meyers
ABOUT THE AUTHORS
Gloria M. Clark is an Associate Professor of
Accounting at Winston-Salem State University. She
holds an Ed.D. in Administration and Supervision with
a concentration in Leadership from Atlanta University.
She is a licensed Certified Public Accountant in the State
of North Carolina. In 2004, Dr. Clark received the Cedric Rodney Service Award. She received the 2003 NC
Board of Governors Excellence in Teaching Award. She
is also the recipient of the 2001 Wachovia Excellence
in Teaching Award, and 1997 Teaching and Excellence
Award from the 8th International Conference on College
Teaching and Learning. Her research interest areas are
instructional technology, entrepreneurship and not-forprofit organizations and more recently Sarbanes-Oxley
Act of 2002.
Volume 9, 2006
Wendy Myers is a graduate student at Nova
Southeastern University in accounting.
36
Palmetto Review
MILLIKEN MEDAL OF QUALITY
RECIPIENTS
1997
2004
Chairman and CEO
Milliken and Company
Professor
Clemson University
John G. Surak, Ph.D.
Roger Milliken
1998
2005
President and CEO
Asten, Incorporated
Senior Vice President and
Executive General Manager
Department of Energy
Wakenhut Services Incorporated
Lawrence Brede, Jr., D.P.A
William A. Finn
1999
Dan Hargett
Vice President
Microeletronics for Lockwood Greene
2000
Greg Frampton
Executive Administrator
South Carolina Department of Revenue
2000
Dr. Mary Thornley
President
Trident Technical College
2001
Thomas J. Malone, Ph.D.
President and CEO
Milliken and Company
2002
Robert L. Colones
Executive Vice President
McLeod Regional Medical Center
2003
Frank W. Fusco
South Carolina Budget and Control Board
Volume 9, 2006
37
Palmetto Review
SOUTH CAROLINA GOVERNOR’S
QUALITY AWARD WINNERS
1995
2001
1997
2002
 WIX Filtration Products Division, Dillion Plant
 MEMC Electronic Materials, Inc.
 Bridgestone/Firestone South Carolina, Aiken
Plant
 Chem-Nuclear Systems, LLC
1998
2003
 Saint Eugene Medical Center
 Robert Bosch Corporation
 Standard Corporation
1999
 AlliedSignal Greer Repair and Overhaul
2004
2000
 Wakenhut Services, Inc.-Savannah River Site
 McLeod Regional Medical Center of the Pee Dee, Inc.
*Awards not made in 1996 and 2005.
ACHIEVERS
1995
2000
Gold Achiever
 Preferred Billing and Management Services
 Dana Corporation, Spicer Driveshaft Division of Lugoff
1996






Silver Achievers
Chem-Nuclear Systems, Inc.
Dana Spicer Systems Assembly Division
The Ohio Casualty Insurance Group
Preferred Billing and Management Services
South Carolina Department of Revenue
Spartanburg Regional Healthcare System
 Dana Corporation, Spicer Driveshaft Division of Columbia
 Standard Corporation Integrated Logistics of Columbia
and Greenville
Bronze Achiever
 Dana Corporation, WIX Filtration Products of Dillon
1997




2001
Beattie Plant (Subsidiary of Delta Woodside Industries, Inc.)
Saint Eugene Community Hospital
Southern Division-Naval Facilities Engineering Command
South Carolina Department of Education
Explorer Process
 South Carolina Mentor
Silver Achiever
1998
 South Carolina Vocational Rehabilitation Department
Gold Achiever
2002
 Dana Corporation, Spicer Heavy Systems Assembly Division
 Wackenhut Services, Inc.
Bronze Achiever
 McLeod Home Health
Silver Achiever
 Pirelli Cables and Systems North America
2003
Bronze Achiever
 Eaton Cutler-Hammer
Gold Achiever
 Operations Associates
 Springs Industries Warehousing and Distribution Division
 Stevecoknit Fabrics Company, Rainsford Plant
Bronze Achiever
 South Carolina Mentor
1999
2004
 McDevitt Street Bovis
 Wackenhut Services, Inc., Savannah River Site
 South Carolina Vocational Rehabilitation Department
Silver Achiever
 GlayoSmithKline
Gold Achiever
Gold Achiever
Bronze Achiever
 Operations Associates
Explorer Process
 The Roche Carolina Inc. of Florence, SC
Bronze Achiever
 MUSC Medical Center
2005
Silver Achiever
 South Carolina Department of Mental Health
Volume 9, 2006
38
Palmetto Review
FACULTY
The School of Business Administration & Economics
Accredited by AACSB International
The Association to Advance Collegiate Schools of Business Internationally
Jerome V. Bennett
Professor, Accounting
Dr. Bennett received his Ph.D. from the University of South Carolina. He served as dean of the School of Business
and Economics from 1986 until 1998 and also as executive director of the John M. Rampey, Jr. Center for Quality and
Management Education. Bennett received a Bachelor of Textile Engineering Degree from Georgia Techical College and
an MBA from University of North Carolina-Chapel Hill. He is a certified management accountant and was a registered
professional engineer in Pennsylvania. He teaches cost accounting and accounting information systems. His corporate
career included controller positions with Uniroyal and Riegel Paper Corporation, Industrial Engineer with DuPont, and
director of Technology Utilization of the South Carolina Budget and Control Board. He is the author of Budgeting and
Forecasting Manual.
Stephen E. Berry
Associate Professor, Management
Dr. Berry teaches organizational management, operations management and statistics. He received his MBA and Ph.D.
degrees in Operations Research from the University of Georgia. His research interests are quality awards and quality
management practices. He has published in a number of scholarly journals including Production and Inventory Management,
Academy of Management Journal, Palmetto Review, and Southern Business Review.
Steven D. Caldwell
Assistant Professor, Management
Dr. Caldwell received his Ph.D. in Management from the Georgia Institute of Technology. He has taught at USC Upstate
since August 2004 in organizational behavior, human resources and statistics. He has presented his research at both national
and international conferences sponsored by organizations such as the Academy of Management, the Southern Academy of
Management, the Society of Industrial and Organizational Psychologists, and the International Journal of Business and
Economics, as well as published in Journal of Applied Psychology, Personnel Psychology, Encyclopedia of Industrial/
Organizational Psychologists, and Decision Sciences. Prior to his academic career, he was Founding President of Data
Ventures, LLC and served in executive positions in various other businesses within the consumer products industry.
Richard Gregory
Assistant Professor, Finance
Dr. Gregory joined the faculty in fall of 2002. He received his Ph.D. from Old Dominion University in 1996, and the M.A.
in Economics from Indiana University in 1990. From 2000-2002, he was Visiting Professor of Finance at Old Dominion
University. Before returning to teaching, Dr. Gregory worked for the Virginia Economic Development Partnership, a
private/public funded organization that led economic development activity for the government of the Commonwealth
of Virginia. His interests include international finance, investments and risk exposure. He is member of Beta Gamma
Sigma and Omicron Delta Epsilon. Dr. Gregory also consults with firms on employee retirement plans and on economic
damages.
Lilly M. Lancaster
William S. Moore Palmetto Professor in Quality Studies
Dr. Lancaster received her Ph.D. in Management Science from the University of Massachusetts. She has taught at USC
Upstate since 1987 in operations management and statistics. She has published in a number of scholarly journals including
European Journal of Operational Research, Interfaces, Socio-Economic Planning Sciences and Production and Inventory
Management. She is a member of the American Society for Quality and has served as the academic advisor for the Industrial
Crescent Chapter of the APICS - The Educational Society for Resource Management. She served as an examiner for the
South Carolina Governor’s Quality Award from 1997-2000.
Volume 9, 2006
39
Palmetto Review
James W. Reese
Associate Professor, Economics
Dr. Reese received his Ph.D. from the University of Tennessee. He teaches in the areas of economics and statistics and
has recently begun teaching management information systems courses. Dr. Reese’s research interests are in computers
and technology.
Sarah P. Rook
Professor, Economics
Dr. Rook received her M.E. and Ph.D. degrees in economics from North Carolina State University. She teaches
macroeconomics, microeconomics, and statistics. Her research interest is environmental economics.
Frank Rudisill
Associate Professor, Management
Dr. Rudisill received his Ph.D. in management science from Clemson University. He joined the USC Upstate faculty in
fall 2002. He teaches in the areas of management, operations management and statistics. He has 20 years experience in
industry as a statistician, operations research manager and statistical quality control consultant. His research interests focus
upon applying quality tools and techniques in solving industrial problems. He has published in Production and Inventory
Management and Quality Engineering. He is the co-author of a book, Quality Management and Measurement Systems.
Dr. Rudisill is a member of the American Society of Quality and holds APICS certification.
Stuart Shough
Senior Instructor, Accounting
Mr. Shough received his Masters of Accountancy degree from the University of South Carolina. He teaches a variety of
accounting courses.
Brian Smith
Instructor
Mr. Smith received his Master of Management Information Systems degree from Georgia College and State University.
A formal IT Manager and Certified Novell Engineer, he teaches Management Information Systems.
Richard W. Stolz
Professor, Economics
Dr. Stolz received his Ph.D. in Economics from Michigan State University. He teaches a variety of economics, finance
and statistics courses.
Faruk I. Tanyel
Professor, Marketing
Dr. Tanyel received his MBA from Syracuse University and his D.B.A. in Marketing from the University of Tennessee. He
teaches marketing, economics and business policy. He has served as the assistant dean and chair of the School of Business
Administration and Economics. Professor Tanyel’s research and consulting interests include management development,
export, import, and marketing. He has completed a faculty internship position with Remington Company, and was the
director of management training for the National Education Foundation.
Sonja Wilson
Assistant Professor, Law
Mrs. Wilson joined the faculty in fall 2000. She teaches business law and tax. She received the J.D. from the University
of South Carolina, the M.Tx from Georgia State University and a M.Ed. from the University of South Carolina. A
graduate of the University of South Carolina Upstate, she received the B.S. in Mathematics in 1990. She is a former high
school math teacher for Dorman and Byrnes High Schools. As a high school teacher, she wrote and received grants for
underprivileged math students and the multicultural camp at Furman University. She has also taught mathematics for area
businesses such as BMW and Dare Food Products. Her personal interests include the implementation and operation of
nonprofit corporations.
Volume 9, 2006
40
Palmetto Review
William R. Word
Professor, Economics
Dr. Word received his Ph.D. from the University of Tennessee. He has published in a number of scholarly journals including
the Monthly Labor Review, Public Personnel Management, and the Southern Business Review. During 1993-95, 199698, and 2001-03, he served as a member of the Business Accreditation Committee for AACSB International. He was the
principal consultant for AACSB accreditation to the University of Laval in Quebec City, ESSEC in Paris, the Rotterdam
School of Management, Queen’s University (Canada), the University of Mannheim (Germany) and the University of St.
Gallen (Switzerland). The University of Laval received AACSB accreditation in 1995; ESSEC was accredited in 1997;
the Rotterdam School of Management and Queen’s University received accreditation in 1998; the University of Mannheim
was accredited in 2000; and the University of St. Gallen was accredited in 2003; ESSEC was the first school in Europe
to be accredited by AACSB.
Donald Yates
Senior Instructor, Information Management
Mr. Yates received his MBA from Harvard Business School and spent 25 years in textiles and related industries. After
early retirement, he joined USC Upstate as an instructor in business information systems. He also teaches marketing and
business policy. He also serves as the financial manager for the owner of the Carolina Panthers. His research interests
are quality issues and diversity.
Publication of Palmetto Review is made possible through the generous support of the William S.
Moore Palmetto Professorship in Quality Studies.
Volume 9, 2006
41
Palmetto Review
GUIDELINES FOR AUTHORS
Submit three (3) copies with the text in MSWORD. When accepted for publication, you will be asked to
submit a disk copy. On the diskette, write the paper title and author(s). Diskettes will not be returned.
Follow format guidelines given below:
BASE FONT: Times New Roman 11 pt.
MARGINS: Indent paragraphs with a tab of five (5) spaces. Set the margins: left margin, right margin,
top margin: 1 inch, bottom margin: 1.25 inches.
SPACING: Single-space the body of the paper. Double-space before and after first- and second-level
headings. Triple-space between the title and before and after the author’s name.
PAGE NUMBERS: Do not type in page numbers; pencil in numbers on pages.
TITLE: Bold-faced and centered at the top of the first page.
AUTHORS and AFFILIATIONS: Centered, bold-faced, and single-spaced beginning on the third line
below the title. Do not use titles such as Dr., Assistant Professor, etc.
ABSTRACT: Begin the paper with an abstract of approximately 100 words. Type the word, ABSTRACT,
in all capital letters, bold-faced and centered on the third line following the author(s) and affiliation(s). The
text of the abstract is in italics.
HEADINGS: Show first-level headings centered, bold-faced, and in all capital letters. Show secondlevel headings flush with the left margin, bold-faced, upper and lower case letters.
BODY: Show single-spaced and following the abstract. Body is both left and right-justified.
FOOTNOTES: Do not use footnotes. Give references within the text with the last name and year of
publication.
REFERENCES: List references at the end of the paper in alphabetical order. Center the word,
REFERENCE, at the beginning of the listing. See journal articles for examples.
ABOUT THE AUTHOR: Immediately following the references, include a short paragraph about the
author(s).
TABLES: If tables are used, they may be placed within the text. In addition, submit tables in a separate
file.
Volume 9, 2006
42
Palmetto Review