University of Phoenix School of Advanced Studies
Doctoral Candidate: Ed Jennings
Committee Members:
Jaclyn Krause, PhD, Chair
Kenneth Cromer, PhD, Committee Member
Connie Greiner, EdD, Committee Member
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Researcher’s Background
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Topic Background
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Key Terms
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Problem Statement
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Significance of the Study
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Research Questions
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Theoretical Framework
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Methodology
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Population
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Results
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Significance of the Study to Leadership
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Recommendations for Future Research
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Next Steps
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References
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Thank You
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Questions and Answers
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Saturation of cell
phones
41% of the food
budget was spent on
meals outside of the
home
The first coupon
was introduced in
1894
Restaurant
Promotions
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Performance Expectancy (PE): The degree to which mobile coupons assist individuals in
completing their goal of dining out while saving money.

Effort Expectancy (EE):
The level of ease or difficulty in using a new technology.

Social Influence (SI):
The belief that others who are important to them believe
they should be using mobile coupons.
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Opting-In (OI):
A permission-based marketing tactic that asks users for
permission to send something of value.
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Fear of Spam (FS):
Concern regarding Intrusive advertising delivered to a
user’s cell phone.
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Behavioral Intention (BI):
The degree to which an individual plans to perform a
behavior.
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General Problem:
Less than one percent of traditional printed coupons are redeemed and little
research exists on the behavioral intentions of consumers to use mobile coupons
for restaurant purchases.
Specific Problem Studied
The behavioral intention of young adults to use mobile coupons for casual
restaurant dining.
Performance
Expectancy
Fear of Spam
Opt-In
Effort
Expectancy
Social
Influence
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This study is significant at the organizational
and academic levels.
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RQ1: What is the relationship between performance expectancy and the behavioral intention to
redeem mobile coupons in a casual dining restaurant environment?
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Ho1: There is no relationship between performance expectancy and the behavioral intention to use
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Ha1: There is a relationship between performance expectancy and the behavioral intention to use
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mobile coupons in a casual dining restaurant environment.
mobile coupons in a casual dining restaurant environment.
RQ2: What is the relationship between effort expectancy and the behavioral intention to redeem
mobile coupons in a casual dining restaurant environment?
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Ho1: There is no relationship between performance expectancy and the behavioral intention to use
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Ha1: There is a relationship between performance expectancy and the behavioral intention to use
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mobile coupons in a casual dining restaurant environment.
mobile coupons in a casual dining restaurant environment.
RQ3: What is the relationship between social influence and the behavioral intention to redeem mobile
coupons in a casual dining restaurant environment?
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Ho3: There is no relationship between social influence and the behavioral intention to use mobile

Ha3: There is a relationship between social influence and the behavioral intention to use mobile
coupons in a casual dining restaurant environment.
coupons in a casual dining restaurant environment.
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RQ4: What is the relationship between opting-in and the behavioral intention to redeem mobile
coupons in a casual dining restaurant environment?
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Ho4: There is no relationship between opting-in and the behavioral intention to use mobile coupons in
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Ha4: There is a relationship between opting-in and the behavioral intention to use mobile coupons in
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the casual dining restaurant environment.
the casual dining restaurant environment.
RQ5: What is the relationship between the fear of spam and the behavioral intention to redeem mobile
coupons in a casual dining restaurant environment?
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Ho5: There is no relationship between the fear of spam and the behavioral intention to use mobile

Ha5: There is a relationship between the fear of spam and the behavioral intention to use mobile
coupons in the casual dining restaurant environment.
coupons in the casual dining restaurant environment.
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Theory of Reasoned
Action
Social Cognition
Theory
Technology
Acceptance Model
Theory of Planned
Behavior
Ajzen & Fishbein,
1980
Bandura, 1982
F. Davis, 1989
Ajzen, 1991
Model of Personal
Computer
Utilization
Innovation
Diffusion Theory
Motivational Model
Intrusive
Advertising
Thompson,
Higgins, & Howell,
1991
Rogers, 1995
Ballerand, 1997
Edwards, Li & Lee,
2002
Unified Theory of
Acceptance and Use
Technology
Permission Based
Marketing
Permission to
Interact in the
Mobile Space
Fear of Spam in
Wireless Coupons
Venkatesh, Morris,
Davis, & Davis,
2003
Jayawardhena, et
al.,
2009
Rohm & Sultan,
2006
Dickinger &
Kleijnen,
2008
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Quantitative Cross Correlational
study Measuring the Potential
Relationships Between Five
Antecedents and Behavioral
Intention
The Questionnaire Consisted of
Tools From: Unified Theory of
Acceptance and Use
Technology, Opt-In and SPAM
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Have You Previously Received a Text Message Coupon?
•Yes = 42.07%
•No = 57.93%
Have You Previously Redeemed a Text Message Coupon?
•Yes = 27.44%
•No = 72.56%
Do You Currently Use Text Messaging?
•Yes = 98.17%
•No = 1.83%
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Independent Variable Correlations with Behavioral Intention from Kendall Tau-b, Spearman, and Gamma tests
Independent Variable
Kendall tau-b
Spearman
Gamma
PE
.547**
.674**
.615**
EE
.478**
.589**
.538**
SI
.409**
.532**
.461**
Opt-In
.522**
.658**
.582**
Fear
.048
.063
.054
--
P = .237
P = .256
P = .265
Note. ** Correlation is significant at the .001 level. n = 328.
Note 2: The probability value was compared to the alpha value established at .05 to
determine whether the null hypothesis was accepted or rejected
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Independent Variable Correlations with Behavioral Intention from Pearson and Spearman tests
Independent Variable
Pearson
Spearman
PE
.682**
.674**
EE
.611**
.589**
SI
.512**
.532**
Opt-In
.680**
.658**
Fear
.040
.063
--
p = .459
p = .256
Note. ** Correlation is significant at the .001 level. n = 328.
Note 2: The probability value was compared to the alpha value established at .05 to
determine whether the null hypothesis was accepted or rejected
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The results using Spearman, Gamma and Kendall tau-b were consistent and compared
to Pearson’s Correlation
Tests were selected and appropriate for non-normalized data
The Spearman Correlation was used to determine whether a relationship existed and the
strength of the relationship between the independent variable and dependent variable
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A significant positive relationship exists between performance expectancy and
behavioral intention
A significant positive relationship exists between effort expectancy and behavioral
intention
A significant positive relationship exists between social influence and behavioral
intention

A significant positive relationship exists between Opt-In and behavioral intention

No relationship existed between fear of spam an behavioral intention
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Marketing Strategy
Creativity
Customer Loyalty
To Groupon or Not to
Groupon?
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Testing More Age Groups
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Institutional Trust
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Location, Time of Day and Search Based Coupons
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Applied Research to a Corporate Chain
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Creative Value Propositions
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Publish
Continue Teaching
Starting a Business – Be so good they can’t avoid you.
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Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
Retrieved from http://people.umass.edu/aizen/tpb.html
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice Hall.
Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122-147. doi:10.1037/0003066X.37.2.122
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS
Quarterly, 13(3), 319-339. doi:10.2307/249008
Dickinger, A., & Kleijnen, M. (2008). Coupons going wireless: Determinants of consumer intentions to redeem mobile
coupons. Journal of Interactive Marketing, 22(3), 23-39. doi:10.1002/dir.20115
Edwards, S., Li, H., & Lee, J. (2002). Forced exposure and psychological reactance: Antecedents and consequences of the
perceived intrusiveness of pop-up ads. Journal of Advertising, 31(3), 83-95.
doi:10.1080/00913367.2002.10673678
Jayawardhena, C., Kuckertz, A., Karjaluoto, H., & Kautonen, T. (2009). Antecedents to permission based mobile marketing:
An initial examination. European Journal of Marketing, 43(3/4), 473-499. doi:10.1108/03090560910935541
Rogers, E. (1995). Diffusion of innovations. New York, NY: Free Press.
Rohm, A., & Sultan, F. (2006). An exploratory cross-market study of mobile marketing acceptance. International Journal of
Mobile Marketing, 1(1), 2-10. Retrieved from http://www.mmaglobal.com/resources/international-journalmobile-marketing
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS
Quarterly, 15(1), 124-143. Retrieved from http://www.misq.org
Tsang, M., Ho, S., & Liang, T. (2004). Consumer attitudes toward mobile advertising: An empirical study. International J
ournal of Electronic Commerce, 8(3), 65-78. Retrieved from http://www.ijec-web.org/
Vallerand, R. J. (1997). Toward a hierarchical model of intrinsic and extrinsic motivation. Advances in Experimental Social
Psychology, 29(1), 271-360. doi:10.1016/S0065-2601(08)60019-2
Venkatesh, V., Morris, M., Davis, G., & Davis, F. (2003). User acceptance of information technology: Toward a unified view.
MIS Quarterly, 27(3), 425-478. Retrieved from http://www.misq.org
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