mba 512 final presentation, hayes and rheam
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Do you think Money Grows on Trees?
SUSAN FORGETT RHEAM MARIE HAYES
EMPLOYEE THEFT SURVEY ANALYSISMBA 512
APRIL 28, 2010
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Topic Overview
• It is no secret that employees routinely steal from their employers.
• Thefts of:– Money– Time– Supplies– Merchandise– Company Property
Constitute use or misuse of an employer’s assets or resources without permission to do so.
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Employee Theft Information
• U.S. Chamber of Commerce reports:Thefts cost U.S. companies between an estimated
$20 and $40 billion each year.This translates into roughly $400 for every working
American.An estimated 75% of all employees steal at least
once, and that ½ of these steal again and again.One out of every three business failures are the
direct result of employee theft.
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Why this topic?
• January 5, 2010 DailyFinance.com article:Koss Corp. Fires Auditor as Alleged Fraud Loss Widens to
$31 Million• The 17 year CFO was highly trusted and given a lot
of autonomy in her function as head of the finance team.
“Anyone conducting alleged transfers of this size would have to be awfully confident that no one else was looking at the bank records, as transfers so large typically would be noticed.”
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Research Question
• Will enhanced monitoring discourage employee theft?
• Relevant factors:– Demographics– Employee theft– Perceptions of stealing– Awareness of employer monitoring– Sensitivity to employer monitoring
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Research Hypothesis
When employees know that their activities are carefully monitored, they are less likely to commit theft on the job.
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DATA COLLECTION & PREPARATION
• A 10 QUESTION SURVEY TO INVESTIGATE THE TOPIC WAS USED TO POLL RESPONDENTS
• A VARIETY OF QUESTION & ANSWER TYPES USED SUCH AS:• DEMOGRAPHIC- MULTIPLE CHOICE-SINGLE RESPONSE
& SIMPLE CATEGORY SCALE• BEHAVIORAL-SIMPLE CATEGORY SCALE, MULTIPLE
CHOICE-MULTIPLE RESPONSE & RATING RESPONSE STRATEGY
• OPINION- MULTIPLE CHOICE-SINGLE RESPONSE & MULTIPLE CHOICE-MULTIPLE RESPONSE
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SURVEY DESCRIPTION• FIRST-DEMOGRAPHIC QUESTIONS TO CONFIRM
THAT WE REACHED OUR TARGET AUDIENCE
• INCLUDED QUESTIONS ON:• AGE• GENDER• EMPLOYMENT STATUS –HOURLY, SALARIED, SELF, NOT
WORKING• POSITION-- ENTRY, MID, SUPERVISORY, SENIOR &
EXECUTIVE
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SURVEY DESCRIPTION• NEXT-BEHAVIORAL QUESTIONS TO GAUGE HOW
RESPONDENTS ACT IN CERTAIN SITUATIONS
• INCLUDED QUESTIONS DESIGNED TO GATHER INFORMATION:• ARE RESPONDENTS CURRENTLY BEING MONITORED AT
WORK?• WHAT ARE RESPONDENT’S REACTIONS TO CHANGES IN
MONITORING ACTIVITIES AT WORK?
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SURVEY DESCRIPTION• NEXT-OPINION QUESTIONS TO OBTAIN
INFORMATION ON RESPONDENT’S PERCEPTIONS OF THEFT AND MONITORING
• INCLUDED QUESTIONS DESIGNED TO GAUGE SENSITIVITY:• PERCEPTIONS ON WHAT CONSTITUTES STEALING FROM
AN EMPLOYER• COMFORT LEVELS WITH MONITORING• IMPACT OF INCREASED LEVELS OF MONITORING ON THEFT
PREVENTION
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DATA COLLECTION
TARGET AUDIENCE -PEOPLE OVER 18 WHO ARE (OR WERE) EMPLOYED• GOAL TO COLLECT SAMPLE OF GREATER THAN 50
RESPONDENTS
METHOD OF SURVEY ADMINISTRATIONSAMPLING PLAN USED:
• SNOWBALLING, RANDOM SAMPLING PLAN• ANONYMOUS = HONESTY
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DELIVERY METHOD
• PHYSICAL DISTRIBUTION OF PRINTED SURVEYS– SURVEYS HANDED TO PEOPLE WE KNEW– RECRUITING FROM ACQUAINTANCES TO REACH
ADDITIONAL RANDOM INDIVIDUALS• DISTRIBUTED 167 SURVEYS:
SELF-ADDRESSED STAMPED ENVELOPE TO A P.O. BOX
• GOAL TO COVER OUR GENERAL DEMOGRAPHIC AREA: WILKES BARRE - HAZLETON – BLOOMSBURG -
SELINSGOVE
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SUMMARY OF RESPONDENTS
• DETERMINE GEOGRAPHIC LOCATION BY POSTMARK ON RETURNED ENVELOPES
• POTENTIAL RESPONDENTS OUTSIDE OF TARGET AREA A RESULT OF USING SNOWBALL SAMPLING METHOD
• 66 RESPONDENTS OF 167 ≈ 39.5%**IF ALL 167 WERE DISTRIBUTED
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Geographic Location
Wilkes-Barre
Scranton
Harrisburg
Lehigh Valley
Syracuse
Reading
0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00
Number of Respondents
Post
mar
k
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Potential Sources of Error• FULL DISTRIBUTION OF SURVEYS BY
ACQUAINTANCES UNKNOWN• CERTAIN RESPONDENTS LEFT QUESTIONS
BLANK• WORDING OF CERTAIN QUESTIONS OR
QUESTION RESPONSE OPTIONS MAY HAVE BEEN CONFUSING TO RESPONDENTS
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Descriptive Statistical Analysis
• Demographics of respondents:– Gender and age– Employment status and position– Geographic location
• Behavior of respondents:– Admissions of theft
• Perceptions of respondents:– Theft considerations– Monitoring awareness and sensitivity
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Survey Respondents: 66 Total
32%
52%
17%
Gender
Male
Female
(Blank)
20%
12%
23%
23%
23%
AGE
18-26 yrs
27-35 yrs
36-43 yrs
44-52 yrs
52-up yrs
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Employment Status
Not currently working
Employee paid hourly
Salaried employee
Self-employed0
5
10
15
20
25
30
35
40
2
20
38
6
Num
ber o
f Res
pond
ents
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Position at Work
Entry level Mid-level Supervisory Senior mgmt Executive mgmt
0
5
10
15
20
25
30
Total 4Num
ber o
f Res
pond
ents
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Theft of Office Supplies
National survey of 2,137 employed adults reported 19% of workers stealing office supplies (May, 2008) Our survey respondent’s admission of taking home company office supplies for personal use: 15 / 66 = 23%
Entry-le
vel
Mid-le
vel
Supervi
sory
Senior m
gmt
Execu
tive m
gmt
0.00
0.10
0.20
0.30
0.40
0.50
0.60
Total 0.50
Employee Position
% o
f res
pond
ents
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Perceptions: Stealing?
Entry-le
vel
Mid-le
vel
Supervi
sory
Senior m
gmt
Execu
tive m
gmt
0%10%20%30%40%50%60%70%80%90%
Personal callsUse of softwareComputer fun workingComputer fun lunch
% o
f Res
pond
ents
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Monitoring Awareness & Sensitivity
No39%
Yes45%
Don't
know
15%
Are you currently being monitored at work?
Con-cerned
14% Don't care18%
Un-con-
cerned68%
Reaction to increased monitoring at work
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Respondent Interpretation
• 51% female, 32% male• Very equal cross-section of age categories• Majority salaried employees in mid-level positions• Geographic concentration in Central PA• 23% taken home company office supplies• Over 45% felt stealing included theft of time and
personal use of company software• 46% are currently being monitored at work• 68% unconcerned about increased monitoring
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Hypothesis Testing:Monitoring Concerns
• Are workers who are not currently monitored on the job as unconcerned about increased monitoring as workers who are already being monitored?
• Two-sample hypothesis test for the difference between proportions (sample size > 30):– NULL:p1 = p2– ALT: p1 <> p2
• Two-tail test
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HYPOTHESIS TESTx-value sample
1 26x-value
sample 2 22
sample size 1 30 sample size 2 26pooled proportion 0.857 proportion 1 0.8667 proportion 2 0.8462
std error 0.094
NULL: 1 = 2p pThere is no difference in perception of increased monitoring between monitored and unmonitored workers
ALTERNATIVE: 1 < > 2p pThere is a difference in perception of increased monitoring between monitored and unmonitored workers
one-tailed or two tailed? 2
test statistic (obs)
0.219 CONCLUSION
critical measure
1.960 Do not reject the Null Hypothesis
|obs| > critical?? NO
People who are not currently monitored at work are just as comfortable with the idea of increasedmonitoring as people who are currently monitored at work.p-value
0.827
a-level
0.050 p-value < a-level?? NO
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Hypothesis Testing:Personal Use of Work Computer
• Will most people stop using their company computer for personal fun during work time with increased monitoring?
• One-sample hypothesis test for the population proportion (sample size > 30):– NULL:p > = .5– ALT: p < .5
• One-tail test as direction implies
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HYPOTHESIS TESThypothesized
valuesample
proportion xsample
size std error
for the proportion 0.5 0.60606 40 66 0.061545745
NULL : > = .50pMost people will not stop using their work computer for personal fun with increased monitoring
ALTERNATIVE: < .50p
Most people will stop using their work computer for personal fun with increased monitoring
test statistic (obs)
1.723
critical measure
1.645
one-tailed or two-tailed? 1
|obs| > critical? YES
p-value 0.0424188 CONCLUSION
a-level
0.050 Reject the Null Hypothesis
p-value < a-level? YES
Most people will stop using their work computer for personal fun with increased monitoring
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Hypothesis Testing:More Frequent Monitoring
• Respondents asked what they thought the impact on theft prevention would be with more frequent monitoring of work activities:1. Have no impact on theft prevention2. Might help theft prevention3. Would greatly help theft prevention
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Hypothesis Testing:More Frequent Monitoring
• One-sample hypothesis test for the population proportion (sample size > 30):– NULL:p > = .5– ALT: p < .5
• One-tail test as direction implies
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HYPOTHESIS TESThypothesized
valuesample
proportion xsample
size std error
for the proportion 0.5 0.86364 57 66 0.061545745
NULL : > = .50pMost people feel frequent monitoring of work activities will not prevent theft
ALTERNATIVE: < .50pMost people feel frequent monitoring of work activities will prevent theft
test statistic (obs)
5.908
critical measure
1.645
one-tailed or two-tailed? 1
|obs| > critical? YES
p-value 0.0000000017 CONCLUSION
a-level
0.050 Reject the Null Hypothesis
Most people feel frequent monitoring of work activities will prevent theft
p-value < a-level? YES
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Summary of Hypothesis Testing
• Majority of workers are not resistant to increased monitoring:Even if they are not currently being monitored.
• 56% of respondents felt that using the company computer for personal fun during work time was stealing from an employer:Most people will stop using their work computer for
personal fun with increased monitoring.• Most people feel that frequent monitoring of work
activities would greatly help theft prevention.
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LINEAR REGRESSION ANALYSIS
GOAL IS TO FIND IF ANY RELATIONSHIPS EXIST BETWEEN VARIOUS THEFT VARIABLES VS. MONITORING OR CHECKING
The dependent variables in the following 3 scenarios are: #1 Theft of supplies-do they take home company supplies#2 Stop Theft-would they stop personal computer activity#3 During Lunch-would they only use the computer for personal
during lunch
The Independent variables used were:Checking-someone is checking work activitiesMonitoring-someone is monitoring work activities
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HYPOTHESIS
SCENARIO #1
• NULL: THEFT OF SUPPLIES IS NOT AFFECTED BY CHECKING
• ALT: THEFT OF SUPPLIES IS AFFECTED BY
CHECKING
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LINEAR REGRESSION-SCENARIO #1
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SCENARIO #1 INTERPRETATION
THE VARIABLE THAT IS SIGNIFICANT:CHECKING IS A SIGNIFICANT VARIABLE IN
RELATION TO THEFT OF SUPPLIES BECAUSE THE p-value .02 <α .05
HOW DOES THEFT BEHAVIOR CHANGE WITH EACH OF THE RELEVANT VARIABLES?
FOR EACH ADDITIONAL UNIT OF CHECKING; THEFT DECREASES
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SCENARIO #1 INTERPRETATION
RELEVANCE OF METHODS/DISCUSSION:
HOW RELIABLE IS YOUR MODEL? • IT IS 7.7% RELIABLE TO PREDICT DECREASE IN
THEFT
• MULTIPLE R: 0.277-Correlation Co-efficient Close to 1 =good
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HYPOTHESIS
SCENARIO #2 & #3#2 HO1
NULL: STOPPING PERSONAL USE IS NOT AFFECTED BY MONITORING
ALT: STOPPING PERSONAL USE IS AFFECTED BY MONITORING
#3 HO2
NULL: USING A COMPUTER FOR PERSONAL USE DURING LUNCH IS NOT AFFECTED BY MONITORING
ALT: USING A COMPUTER FOR PERSONAL USE DURING LUNCH IS AFFECTED BY MONITORING
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LINEAR REGRESSION-SCENARIO #2 & #3
SCENARIO #2 SCENARIO #3
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SCENARIO #2 & #3 INTERPRETATION
THE VARIABLE THAT IS SIGNIFICANT:
#2 HO1
MONITORING IS NOT A SIGNIFICANT VARIABLE IN RELATION TO STOPPING PERSONAL USE BECAUSE THE p-value .77262 is NOT <α .05
#3 HO2
MONITORING IS NOT A SIGNIFICANT VARIABLE IN RELATION TO USING A COMPUTER FOR PERSONAL USE DURING LUNCH BECAUSE THE p-value .4037 is NOT <α .05
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SCENARIO #2 & #3 INTERPRETATION
RELEVANCE OF METHODS/DISCUSSION:HOW RELIABLE IS YOUR MODEL?
#2 HO1
• IT IS 1.3% RELIABLE
#3 HO2
• IT IS 1.09% RELIABLE
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GRAPHICAL REPRESENTATION
-1.5 -1 -0.5 0 0.5 1 1.50
0.20.40.60.8
11.2
Monitoring (1,0,-1) Line Fit Plot
# Stop (1,0)Predicted # Stop (1,0)
Monitoring (1,0,-1)
# St
op (1
,0)
#3 HO2
-1.5 -1 -0.5 0 0.5 1 1.50
0.20.40.60.8
11.2
Monitoring (1,0,-1) Line Fit Plot
# Lunch (1,0)Predicted # Lunch (1,0)
Monitoring (1,0,-1)
# Lu
nch
(1,0
)
#2 HO1
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CONCLUSIONS
• RESPONDENTS WERE FAIRLY CONSISTENT IN THEIR PERCEPTIONS OF
WHAT CONSTITUTES THEFT
• MAJORITY OF WORKERS ARE NOT RESISTANT TO INCREASED
MONITORING
• USING A WORK COMPUTER FOR PERSONAL FUN IS EXPECTED TO DECLINE WITH INCREASED MONITORING
• FREQUENT MONITORING OF WORK ACTIVITIES APPEARS TO GREATLY
HELP THEFT PREVENTION
• THERE IS A RELATIONSHIP BETWEEN THEFT OF OFFICE SUPPLIES AND
SOMEONE CHECKING WORK ACTIVITIES
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CONCLUSIONS
• Our prediction about what we expected to happen in the study as stated in our research hypothesis is supported by the data collected and tested.
When employees know that their activities are carefully monitored, they are less likely to commit theft on the job.
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RECOMMENDATIONS
• REVISE SOME QUESTIONS TO BETTER ACHIEVE DATA COLLECTION FOR REGRESSION MODELS
• COLLECT MORE SPECIFIC DATA RELATED TO TIME THEFT• AMOUNT OF TIME SPENT ON PERSONAL CALLS,
FACEBOOK, ETC.
• EXPAND GEOGRAPHIC AREA BY DISTRIBUTING SURVEYS ONLINE
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REFLECTIONS
SAMPLING PLAN WAS EFFECTIVE FOR SURVEY
RESPONSE
SAMPLE COLLECTED WAS SUITABLE FOR OUR
PURPOSES
DATA COLLECTED WAS OF GOOD QUALITYTHERE ARE MANY MORE ISSUES RELATING TO
THIS TOPIC THAT CAN BE RESEARCHED
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The End
Questions?