DETERMINANTS THAT INFLUENCE COLLEGE STUDENTS IN
CONSIDERING HOSPITALITY BUSINESS
AS THEIR MAJOR: A NEW MODEL
By
Julie Longstreth Tkach

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Community, Agriculture, Recreation and Resource Studies – Doctor of Philosophy
2013

ABSTRACT
DETERMINANTS THAT INFLUENCE COLLEGE STUDENTS IN
CONSIDERING HOSPITALITY BUSINESS
AS THEIR MAJOR: A NEW MODEL
By
Julie Longstreth Tkach
In the vast and growing hospitality industry, the need for qualified supervisors, managers,
and owners is also continuing to grow. College-level hospitality business programs will
be an important source of qualified industry professionals. Therefore, the determinants
that freshman and sophomore students use to decide on hospitality business as an
academic major are of interest. This study extends Ajzen’s (1985) Theory of Planned
Behavior by adding constructs from Magolda’s (1999) Self-Authorship Theory to predict
how students choose Hospitality Business as an academic major. The contribution of this
study is the 19% increase in predictability of students choosing hospitality business
through the combination of Theory of Planned Behavior and Self-Authorship Theory
(66%) over employing the Theory of Planned Behavior alone (47%). Students perceive
the influence of others (parents, advisors, professors, friends, siblings, classmates, and
business people) as most important in deciding to major in hospitality business. Other
determinants are discussed and practical implications are presented.

Copyright by
JULIE LONGSTRETH TKACH
2013

DEDICATION
I would like to dedicate this dissertation to my husband, Thomas W. Tkach,
for his support of my love of teaching and care of our family while I worked,
to my precious daughters, Katharyn and Lauren,
for being the joy and blessings of my life,
to my mother, Barbara W. Longstreth, and grandmothers,
life-long educators who are watching over me from heaven,
to Mom and Dad Tkach, my sisters-in-law, brother, aunts, nephew and niece,
to my father, John K. Longstreth,
and to God, who made a way.

iv

ACKNOWLEDGEMENTS

I have been blessed by many people on this path and I am forever indebted to
them for their caring and kindness.
I am so thankful for Dr. Donald Holecek, committee chair, for taking me as his
advisee when his retirement was approaching. I have appreciated him staying involved in
the years since his retirement to see me through. His wise advice and careful guidance
was always there when my other responsibilities were mounting. I am also extremely
grateful for the smiles, laughs, motherly care, and occasional kick in the pants from my
dissertation director, Dr. Bonnie J. Knutson. She has always encouraged and calmed me,
helping me find a solution to every problem so in the end I could successfully finish. She
is a legend inside the classroom and out. I am honored she agreed to lead my dissertation
and stand beside me at graduation. I will always look up to her and hope I can have the
impact on others that she has experienced in her career.
My entire graduate school experience would not have been possible without the
generous support of Dr. Ronald F. Cichy, dissertation committee member and Director of
The School of Hospitality Business. His kindness and concern for me and my family will
always be remembered and the opportunities he gave me have forever shaped my career
path. Thank you to Shari L. Dann, my fourth committee member, for the unique
perspectives and great conversations on engaged learning. Your support, time, and
encouragement are appreciated.
I am eternally thankful for the generous gifts of time, talent, friendship, and
prayers by MiRan Kim, JaeMin Cha, SeungHyun Kim, and Praneet Randhawa. I could

v

not have done any of this without you. You were leading and encouraging me right up to
the very end. MiRan, you are my dear Korean sister. Our prayer to teach in close
proximity to each other was answered!
To all of The School of Hospitality Business faculty, staff, alumni, and students,
you are the reason that I wanted only to come back to MSU for graduate school. Your
kind assistance, caring actions, and unending support have never gone unnoticed. You
are my hospitality business family and I will miss working with you every day.
I deeply thank my husband, daughters, and our families for every kind and helpful
thing you did for me during this long journey. I love you and hope you feel the joy of
completion with me!
Thank God for making a way when there seemed to be no way. To God be the
glory, great things He has done!

vi

TABLE OF CONTENTS

LIST OF TABLES ............................................................................................................. ix
LIST OF FIGURES ........................................................................................................... xi
CHAPTER 1: INTRODUCTION ....................................................................................... 1
Introduction ........................................................................................................................ 1
Statement of the Problem .................................................................................................... 2
Purpose of the Study ........................................................................................................... 3
Significance of the Study ................................................................................................... 3
Research Questions ............................................................................................................. 4
Definition of Terms............................................................................................................. 4
Dissertation Organization .................................................................................................. 6
CHAPTER 2: LITERATURE REVIEW AND MODEL DEVELOPMENT..................... 7
Review of the Literature .................................................................................................... 7
Theoretical Background ..................................................................................................... 9
Theory of Planned Behavior ................................................................................ 9
Theory of Self-Authorship ................................................................................. 13
Proposed Conceptual Model ............................................................................................ 16
Hypotheses ....................................................................................................................... 18
CHAPTER 3: RESEARCH DESIGN AND METHODOLOGY .................................... 19
Design of the Study........................................................................................................... 19
Population and Sample ...................................................................................... 19
Data Collection Procedures ............................................................................... 20
Pretest ......................................................................................................... 20
Survey Administration ............................................................................... 20
Questionnaire Format ................................................................................. 21
Instrumentation ................................................................................................................ 22
Attitude ............................................................................................................ 23
Subjective Norms ............................................................................................. 24
Perceived Behavorial Control .......................................................................... 25
External Formulas ............................................................................................ 26
Crossroads ........................................................................................................ 27
Early Self-Authorship ...................................................................................... 27
Choose Hospitality Business ............................................................................ 28
Data Analyses ................................................................................................................... 33
Differential Perceptions ................................................................................... 33
Logistic Regression .......................................................................................... 34
Measurement Model ........................................................................................ 35
Model fit indices ...................................................................................... 35

vii

CHAPTER 4: RESULTS .................................................................................................. 36
Survey Response ............................................................................................................... 36
Data Collection ................................................................................................. 36
Characteristics of Survey Respondents ............................................................. 37
Study Subjects Selected from Survey Respondents ......................................... 38
Demographic Comparisons of Study Subjects to Other Subjects………… ..... 38
Testing the Measurement Model: Confirmatory Factor Analysis in AMOS .................. 43
Normality Test .................................................................................................. 43
Model Specification ......................................................................................... 45
Model Testing .................................................................................................. 46
Analyses ................................................................................................... 46
Reliability ................................................................................................. 46
Discriminant Validity ............................................................................... 50
Testing the Hypothesized Structural Model .................................................................... 51
Goodness-of-fit of the Structural Model .......................................................... 51
Path Coefficients and Hypothesis Testing ....................................................... 51
Effects on Choose Hospitality Business ........................................................... 55
CHAPTER 5: DISCUSSION, IMPLICATIONS, AND FUTURE RESEARCH…….….56
Summary Characteristics of Students who are Choosing their Majors ............................ 56
Results of Hypotheses Testing and Discussion of the Findings ...................................... 56
Implications....................................................................................................................... 62
Theoretical Implications ................................................................................... 62
Practical Implications........................................................................................ 63
Academic Process .................................................................................... 63
Educational Experience ............................................................................ 64
Hospitality Industry .................................................................................. 65
Limitations ....................................................................................................................... 66
Generalizability of Results ................................................................................ 66
TPB Construct of Intention was Removed ...................................................... 67
Freshmen and Sophomore Populations Changing Majors ................................ 68
Future Research ................................................................................................................ 68
APPENDICES .................................................................................................................. 70
Appendix A: Consent Form and Survey Tool ..................................................... 71
Appendix B: Example Calculation of Differential Perception- summary of
procedure............................................................................................................... 82
BIBLIOGRAPHY ............................................................................................................ 83

viii

LIST OF TABLES

Table 1. Four phases of the journey toward self-authorship ............................................ 15
Table 2. Description observed variables in the attitude construct of the proposed model
………………………………………………………………………… .......................... 24
Table 3. Description observed variables in the subjective norms construct of the proposed
model ................................................................................................................................ 25
Table 4. Description observed variables in the perceived behavior control construct of the
proposed model ................................................................................................................ 25
Table 5. Description observed variables in the external formulas construct of the
proposed model ................................................................................................................ 26
Table 6. Description observed variables in the crossroads construct of the proposed
model ................................................................................................................................ 27
Table 7. Description observed variables in the early self-authorship construct of the
proposed model ................................................................................................................ 28
Table 8. Description of factors and observed variables in the theory of planned behavior
(TPB) constructs of the proposed model .......................................................................... 29
Table 9. Description of factors and observed variables of the self-authorship (SA)
constructs in the proposed model ..................................................................................... 31
Table 10. Summary of data collection: total sample, returned sample, invalid sample, and
valid sample ..................................................................................................................... 37
Table 11. Survey respondents’ identified academic majors (n=893) .............................. 37
Table 12. No-preference survey respondents’ identified academic majors (n=91) ......... 38
Table 13. Comparison of demographic characteristics of sample ................................... 39
Table 14. Comparison of demographic characteristics of study subjects, Michigan State
University (MSU) students, and U.S. four-year college students .................................... 42
a

Table 15. Normality test results of items included in the proposed model presented in
Figure 2 ............................................................................................................................ 44
Table 16. Confirmatory factory analysis results for the measurement model ................. 47

ix

Table 17. Summary of means and mean difference test (t-test) results: hospitality
business choice vs. non-hospitality business choice for factors in the model ................. 50
Table 18. Correlations among constructs in the proposed model for examining
discriminant validity ......................................................................................................... 51
Table 19. Logit regression results .................................................................................... 53
Table 20. Comparison of explained variance in choice of hospitality business for 1) the
theory of planned behavior (TPB), 2) the TPB plus self-authorship (SA) ....................... 55

x

LIST OF FIGURES

Figure 1. Ajzen’s (1991) theory of planned behavior (TPB) ............................................ 12
Figure 2. Proposed model for this study .......................................................................... 17
Figure 3. Test results for the proposed structural model: standardized path coefficients
2
and Pseudo R ................................................................................................................... 54

xi

CHAPTER 1
INTRODUCTION

This chapter includes the following sections: (1) Introduction to the Study; (2) Statement
of the Problem; (3) Purpose of the Study; (4) Significance of the Study; (5) Research
Questions; (6) Definitions of Terms; and (7) Overview of the Dissertation Layout.

Introduction
College students have many decisions to make during their years at an institution
of higher education, but one of the most significant and impactful on their lives could be
which major they choose. In comparison with some academic majors, the field of
hospitality is one that is quite visible and accessible. Students have often worked in some
hospitality position during their high-school and early college years or at least have some
basis to have formed an internal image or impression of the field.
By one definition, the hospitality industry includes lodging, foodservice,
institutional settings, travel, and recreation facilities (Campbell, 1999). For purposes of
this study, the hospitality industry or field is the economic sector where host and guest
share in a service transaction away from their home, ranging from basic needs of food
and shelter, to entertainment, enrichment through travel, and spa relaxation and wellness.
According to the U.S. Bureau of Labor Statistics, in 2004, 21% of workers in food and
drinking establishments were aged 16-19, five times the proportion for all industries. As
of July 2011, 26 percent of employed youth worked in the leisure and hospitality sector
(U.S. Bureau of Labor Statistics, 2011). As this industry is projected to continue to grow,

1

so will the opportunities for qualified and passionate employees, managers, owners, and
operators. The primary focus of this study is to test a comprehensive model exploring
determinants in the choice of academic major, specifically hospitality business, within the
theoretical frameworks of the theory of planned behavior and self-authorship theory.

Statement of the Problem
A variety of theories have been used in research conducted on students and their
choice of major from fields such as home economics, sport management, and accounting
(Allen, 2004; Pittaoulis, 2012; Young and Johnson, 1986; Yu, 2011). The theory of
planned behavior model has been used in a variety of past studies (Mayhew, et al., 2009;
Phillips, 2009; Yu, 2011; Wu, 2008), but none in combination with the theory of selfauthorship. Most studies have focused on junior and senior level-students since they
have already gone through the process of choosing their major but this requires relying on
a hind-sight or historical perspective. Hindsight bias is a person’s belief that events that
happened were bound to have happened (Kunda, 1990) or, “having forgotten their initial
judgments, are forced to guess and, in the presence of outcome information, are likely to
use this information as an anchor” (Schwarz and Stahlberg, 2003). Because of this bias,
more studies are needed that investigate students in the midst of their decision-making
process.
The desire is to see if the combination of the theory of planned behavior and selfauthorship theory offers better prediction of student determinants in the decision-making
process for college freshmen and sophomores considering hospitality business as an
academic major than the theory of planned behavior alone.

2

Purpose of the Study
The purpose of this study is to empirically test a new theoretical model for
identifying determinants of freshman and sophomore students’ decision-making
processes of choosing hospitality business as their major. The secondary focus is
understanding which groups of these determinants are the strongest predictors of students
choosing hospitality business. Better understanding of these factors would help to guide
students to the major.

Significance of the Study
This study can contribute both theoretically and practically. This study was
conducted during fall semester 2012 and spring semester 2013, focusing on those
students who were taking selected hospitality business courses but not yet admitted to the
major, as this group was in the midst of making this important career decision.
This study contributes to the development of the body of knowledge about student
decision-making and choice of major studies. From an academic and industry
perspective, the insight provided into how freshmen and sophomore students weigh
perceived decision determinants can be used to design strategies to attract students who
are a good fit for a career in the hospitality business industry. Being able to understand
what determinants are perceived to be the most important to students when they are in the
process of making their choice of a major will offer information which can also be used
in The School of Hospitality Business recruitment materials, retention of admitted
students, curricula development, advising, and fundraising activities.

3

Research Questions
1.

Does the addition of the self-authorship constructs produce increased
understanding beyond the theory of planned behavior alone?

2.

Which of the constructs of the proposed conceptual model have the
strongest associations with choosing a major?

3.

What are the most common determinants that influence students’
decisions to select a major?

4.

How do the selected demographic variables (i.e. age, gender, ethnicity,
socio-economic status, and GPA) compare between hospitality business
and non-hospitality business majors in this sample?

Definition of Terms
The following terms are defined to clarify their use in this study:
Admitted major: the major program of study for which students have completed the
requirements for admission, applied, and been accepted into at or after junior-level status
has been obtained (Michigan State University Office of the Registrar, 2012).
Attitude toward the Behavior: The individual’s personal judgment about whether a
specific behavior is desirable or not, based on his/her pre-existing beliefs about the
desirability of different kinds of behaviors (Ajzen and Fishbein, 1980).
Behavioral Intention: The indications of how hard people are willing to try and of how
much of an effort they are planning to exert in order to perform the behavior (Ajzen,
1991).
Constructive-developmentalism: This theoretical perspective views people as active
constructors of meaning via their organizing and interpreting of their experience. It also
views these constructions as evolving in the context of increasingly complex assumptions
about how to construct meaning (Kegan, 1982).
Crossroads phase: the second of four phases that characterize the meaning making
assumptions employed by individuals in Magolda’s Journey toward Self-Authorship
study (Magolda, 2001).

4

Declared major: a major program chosen by students before junior-level status has been
reached. The students in this category must still apply to be an admitted major when
junior-level status has been reached (Michigan State University Office of the Registrar,
2012).
Early Self-Authorship: the third of four phases that characterize the meaning making
assumptions employed by individuals in Magolda’s Journey toward Self-authorship
study. This phase is noted for individuals making decisions with self-reliance (Magolda,
2001).
External Formulas: the first of four phases in Magolda’s Journey toward Self-authorship
study. Individuals’ decisions are strongly influenced by others (Magolda, 2001).
HB: an abbreviation for Hospitality Business used by the study university to code classes
(e.g., HB 100). (Michigan State University Office of the Registrar, 2012).
Hospitality Business Major: students who have applied for and been accepted into to the
hospitality business program after meeting the requirements for admission. (Michigan
State University Office of the Registrar, 2012).
Meaning-making: The complex ways of organizing experiences, or of making meaning,
to meet the demands of contemporary adult life (Magolda, 1998).
No-Preference: Students who are undecided about their fields of study may select the
No-Preference option at the time of admission or at a later time until junior-level status
has been reached (Michigan State University Office of the Registrar, 2012).
Perceived Behavioral Control: the individual’s perception of the ease (or difficulty) of
performing a specific behavior (Ajzen, 1991).
Self-Authorship: the ability to collect, interpret, and analyze information and reflect on
one’s own beliefs in order to form judgments. Self-authorship offers a theoretical lens to
understand the meaning-making processes that individuals use to make a wide range of
decisions (Magolda, 1998, 2004). It is comprised of three dimensions which are
interrelated (Creamer, Magolda, and Yue, 2010).
Epistemological or Cognitive dimension: Addresses the question of “How do I
know?” and encompasses epistemic assumptions about the nature, limits, and
certainty of knowledge (Creamer, Magolda, and Yue, 2010).
Interpersonal dimension: Addresses the question of “What relationships do I
want?” and refers to how one constructs relationships that are increasingly
characterized by interdependence and mutuality (Creamer, Magolda, and Yue,
2010).

5

Intrapersonal dimension: Addresses the broad question of “Who am I?” and
refers to a sense of self (Creamer, Magolda, and Yue, 2010).
Subjective Norms: The specific behavioral norms that an individual sets for him/herself;
what an individual believes that he/she should do (Ajzen and Fishbein, 1980).
Theory of Planned Behavior: An extension of the Theory of Reasoned Action. The theory
of Planned Behavior accounts for non-volitional control, or ‘actual control’, over the
behavior (Ajzen, 1985).
Theory of Reasoned Action: An expectancy-value model to predict and understand an
individual’s behavior. The theory assumes that human beings are rational and
motivation-based, thus a person’s behavior is determined by his/her intention to perform
the behavior and this intention, in turn, is a function of his/her attitude toward the
behavior and his/her subjective norm (Ajzen and Fishbein, 1980).

Dissertation Organization
The organization of this dissertation is as follows. Chapter 1 provides the general
background and justification for the study. Chapter 2 discusses theoretical and empirical
issues and deficiencies in the research on choosing an academic major, specifically
hospitality business. Two underlying theories upon which the research model is based
are also introduced. From the literature review, a new theoretical model is developed and
research hypotheses are then presented. Chapter 3 focuses on the research method
employed, how the sample was defined, how data were collected, and how constructs in
the research model were operationalized. Characteristics of sample statistics are also
described. Chapter 4 describes how measures are validated in the measurement model,
how research hypotheses were tested in the structural model, and provides data analyses
and results. Chapter 5 includes implications drawn from data analyses, presents research
limitations, and outlines future work to build on the results of this study.

6

CHAPTER 2
LITERATURE REVIEW AND MODEL DEVELOPMENT

This chapter includes the following sections: (1) Review of the Literature; (2) Theoretical
Background of Theory of Planned Behavior; (3) Theoretical Background of SelfAuthorship Theory; and (4) Proposed Conceptual Model.

Review of the Literature
The U.S. hospitality and tourism industry is vast in size and scope. In 2010, this
industry generated $1.8 trillion in economic impact in the United States with $759 billion
spent directly by domestic and international travelers, spurring an additional $1 trillion in
other industries (U.S. Travel Association, 2010). According to the American Hotel and
Lodging Association’s Lodging Industry Profile for 2011, tourism directly supports more
than 7.4 million travel and tourism jobs, and spending on travel and tourism in the United
States averaged $2 billion per day or $24,000 per second (American Hotel and Lodging
Association, 2011). It is estimated that the U.S. hospitality industry currently employs
over 8.8 million people, and it is expected that the industry will require more than 1.6
million new workers over the next decade if it is to keep pace with the anticipated
demand.
In addition to the increasing need for qualified supervisors and managers to fill
the opportunities for employment, the industry will need to rely on university graduates.
Therefore, hospitality programs will need to attract and enroll growing numbers of
students. Over the last 20 years, much research has been undertaken to understand

7

students’ perceptions of the hospitality industry related to careers and career choice in
hospitality and tourism (Barron and Maxwell, 1993; Bradford, 2005; Jenkins, 2001; Jiang
& Tribe, 2008; Lindsay, 2005; Scanlon, 2008; Walmsley, 2004). One way to attract and
retain students as future employees is to understand students’ attitudes and perceptions
towards the hospitality industry (Wan and Kong, 2012). Students who have positive
attitudes and perceptions towards the industry are more likely to enter and remain in the
industry after graduation (Richardson, 2009), and having a skilled and committed
workforce is vital to the success of firms in the hospitality industry (Kusluvan &
Kusluvan, 2000).
Earlier research on choosing a career (Kelly, 1989; Keys and Fernandes, 1993;
Keys et al., 1995; Foskett and Hesketh, 1995; Foskett and Hemsley-Brown, 1997) has
shown that initial occupations and career intentions are chosen during late
elementary/early middle school years (Foskett and Hemsley-Brown, 2001). However,
these choices may change as students gain more life experiences and be different for
students interested in hospitality. Recent studies by O’Mahoney, Whitelaw, and
McWilliams (2008) and Sciarini and Borchgrevink (2008) on students enrolled in
hospitality programs found that the majority of students had decided to major in
hospitality only after they were at college.
A variety of studies have been published on how or why students in various
schools choose their academic major (Beggs, Bantham, & Taylor, 2008; Bollman, 2009;
Bradford, 2005; Dahlstrand, 2010; Johnson & Mack, 1963; Pittaoulis, 2012; Schultz,
1997; Simmons, 2008; Snelling & Boruch, 1970; Young & Johnson, 1986; Yu, 2011).
Some studies intertwined the determinants in considering a major with those in choosing

8

an institution of higher education (Snelling and Boruch, 1970; O’Mahoney, et al., 2008;
Pittaoulis, 2012).
Numerous determinants have been attributed to the process of choosing of an
academic major. From a small portion of the studies, determinants include parental and
extended family involvement (Bradford, 2005; Simmons, 2008), salary, advancement
opportunities, and prestige (Shipp, 1999), and job security, professional recognition, and
leadership skills (Bradford, 2005).
In attempting to group or classify the characteristics which are important to the
decision making process for choosing a major for their study, Beggs, Bantham, and
Taylor (2008) ranked the following six domains in order of importance from their
research findings: Match with Interests, Job Characteristics, Major Attributes,
Psycho/Social Benefits, Financial Success, and Information Search. They speculated that
if information on majors was last on the list, “Is this a problem with the method for
delivering the information, the quality or the quantity of the information itself, or the
development level of the student?” (p. 390). However, the literature is sparse relative to
understanding the cognitive, social, and emotional developmental characteristics of
undergraduate students (typically 18-22 years of age) that influence them to choose
hospitality business for their academic major.

Theoretical Background
Theory of Planned Behavior
The theory of planned behavior (TPB), developed by Ajzen in 1985, has been
used frequently as a framework for predicting and explaining an individual’s behavior

9

and is an extension of the theory of reasoned action (TRA) (Fishbein & Ajzen, 1980).
The TRA was specifically designed to predict human behaviors under complete volitional
control. According to this theory, individuals are rational and motivation-based in their
decision-making processes and make a reasoned choice among various alternatives
(Fishbein and Ajzen, 1975). The TRA includes only the constructs of attitude and
subjective norms as the antecedents of behavioral intention which then leads to the
behavior. As an extension of TRA, an important assumption underlining the TBP is that
the strongest predictor of how we will behave is our intentions to act (Ajzen, 1987); both
social influences and personal factors as predictors of intention are included (Rivis &
Sheeran, 2003). Three major constructs of the theory describe influences on a person’s
intentions instead of just two constructs in TRA.
The first is “attitude toward the behavior” and refers to the degree to which a
person has a favorable or unfavorable evaluation or appraisal of the behavior in question.
The second antecedent of intention is “subjective norms” which is a social factor
referring to the perceived social pressure to perform or not to perform the behavior.
The third predictor is the degree of “perceived behavioral control” which refers to
the perceived ease or difficulty of performing the behavior. This construct reflects on past
experiences, as well as anticipated obstacles (Ajzen, 1991, p.188).
Intention is positioned as an immediate antecedent of behavior, and indicates an
individual’s readiness/willingness to engage in a particular behavior (Ajzen, 1985, 2009).
Whether individuals actually engage in the behavior is a function of their intention to do
so and the extent to which they have real control over situations which might otherwise
interfere with engaging in the behavior. In cases where a person’s perception of control

10

aligns with reality, perceived behavioral control may serve as a proxy for actual behavior
(Mayhew, Hubbard, Finelli, Harding, and Carpenter, 2009).
Behavior is the final step of the model and the anticipated action or outcome. The
relationship among the three constructs, intention, and behavior is illustrated in Figure 1.
Since the Theory of Planned Behavior was developed, it has been the theoretical
basis of numerous studies across various fields; in recent years it has been used in studies
focusing on casino motivation and gaming intention (Phillips, 2009), predicting student
cheating (Mayhew, et al., 2009), understanding the convenient use of credit cards
(Rutherford and DeVaney, 2009), Taiwanese high school students’ choice of sport
management as a major (Yu, 2011), determinants of participation in social support groups
for prostate cancer patients (Voerman, Visser, Fischer, Garssen, van Andel, and Bensing,
2007), predicting physical activity of first-year university students (Kwan, Bray, and
Ginis, 2009), and factors affecting students’ decisions to use online evaluation of
instruction (Wu, 2008).

11

Attitude toward
the Behavior

Subjective Norms

Intention

Behavior

Perceived
Behavioral
Control

Figure 1: Ajzen’s (1991) Theory of Planned Behavior (TPB)

According to Ajzen (1991) and Perugini and Bagozzi (2001), modifying the TPB
model by altering paths and including additional critical constructs in a certain context
often contribute to enhancing our understanding of the mechanisms within the theoretical
model and contribute to increasing the prediction power for individuals’
intention/behavior in that specific context. Broadening and deepening of the theory can
happen through such a process (Ajzen, 1991; Perugini and Bagozzi, 2001).
Cohen and Hanno (1993), in their study focusing on accounting majors, discussed
how, according to the theory of planned behavior, the antecedent of a behavior is the
intention to carry out the behavior. Since subjects in their study had already performed
the behavior of identifying a major, the intention of choosing a major was no longer an
immediate determinant of the action captured by the model. The absence of an
antecedent intention is a departure from the TPB and could limit the ability to draw

12

conclusions about the model’s applicability in this context. However, previous studies
have similarly modified the TPB model by removing the intention construct. Nijhof, ter
Hoeven, and de Jong’s (2008) study on the determinants of use of a diabetes risk test
used a modified model theorizing 11 independent variables preceding the dichotomous
dependent variable of using or not using the diabetes risk test. While the TPB model in
this study is extended with the addition of three theory of self-authorship constructs, the
TPB model is being modified by removing the intention construct.

Theory of Self-Authorship
Marcia Baxter Magolda (1998, 2001) has taken the concepts of “meaningmaking” and “constructive-developmentalism” and applied them to cognitive stages of
decision making through Self-Authorship Theory. Her notable longitudinal study (1999,
2001) of the identity development of college graduates followed individuals as they work
toward self-authorship. In the quest for self-authorship, people become better
independent decision makers and are more comfortable maintaining their sense of self
even as they work through situations of different or contradictory values and ideas while
being tolerant and accepting of such differences (Simmons, 2008).
Magolda based her research on the earlier work of Piaget (1950, 1957, 1971), and
Kegan (1994). Kegan (1994) first defined self-authorship and posited different orders of
mind through which individuals become more understanding and aware of external vs.
self-defined expectations.
Kegan explained, “liberating ourselves from that in which we are
embedded, making what was subject into object so that we can ‘have
it’ rather than being ‘had by it’ – this is the most powerful way I
know to conceptualize the growth of the mind.” Kegan stated that his

13

use of the word mind does not refer to cognition alone but rather to
the capacity of individuals to construct and organize meaning in their
thinking, feeling, and relating to self and others. (Baxter Magolda,
1999, p. 631)
The journey toward self-authorship has three dimensions and four phases that
characterize the perspective employed by individuals. As people mature and have more
and varied life-experiences, they move through the phases, shown in Table 1, at their own
speed. The first phase, following formulas or external formulas, is when young people
are operating according to the rules and expectations of authoritative figures in their lives,
e.g., parents and teachers. It is at the second phase, the crossroads phase, where people
struggle to move from following external norms to cultivating and relying on their own
internal authority. This is the typical phase college-aged students are in when they are
making decisions related to major and career. In this transition time, some people
recognize the need to make decisions for themselves, yet continue to rely on external
formulas (Magolda, 2004). Magolda notes that a student doesn’t tend to move on to early
self-authoring until after college, perhaps in his/her late 20s, depending on the person
(Magolda, 1999). Students in the early phases of self-authorship may be sensitive to
societal expectations that they make their own decisions even while they still rely heavily
on the advice of trusted others (Laughlin and Creamer, 2007). This is important because
college students are expected to make a decision, i.e. choosing a major, that will impact
the rest of their lives at a time when they may be dependent on what others expect them
to do and, perhaps, not able to think for themselves about what they really want and what
will make them the happiest.

14

For this study, the construct of self-authorship is defined as the capacity to operate
within the context of norms and expectations, whether defined as family, peers, or culture
in general, without being wholly defined by them.

Table 1: Four phases of the journey toward self-authorship
Phase 1:
Following
Formulas/External
Dimensions
Formulas
Epistemological Believe authority’s
plans; how “you”
dimension:
know
How do I
know?

Phase 2:
Phase 3:
Crossroads Early SelfAuthoring

Choose own Grounded
beliefs; how in internal
“I” know in belief
context of
system
external
knowledge
claims
Define self through Realize
Choose own Grounded
Intrapersonal
external others
dilemma of values;
in internal
dimension:
external
identity in
coherent
definition;
context of
sense of self
Who am I?
see need for external
internal
forces
identity
Act in relationships Realize
Act in
Grounded
Interpersonal
to acquire approval dilemma of relationships in mutuality
dimension:
focusing on to be true to
external
self,
What
approval;
mutually
relationships do
see need to negotiating
I have with
bring self to how needs
others?
relationship are met
Taken from Baxter Magolda, M.B. (2001), Making Their Own Way, Sterling,
VA: Stylus, p. 40.

15

Question
plans; see
need for
own vision

Phase 4:
Internal
Foundation

Proposed Conceptual Model
The proposed conceptual model incorporates the constructs of selfauthorship into the existing framework of the theory of planned behavior and removes the
behavioral intention construct as described earlier and shown in Figure 2. The proposed
model incorporates both individual behavioral factors (attitude, perceived behavioral
control, and subjective norms) and developmental factors (external formulas, crossroads,
and early self-authoring) as antecedents that influence a college student’s decision
regarding academic major. The main outcome variable is a dichotomous identifier of
choosing hospitality business (coded as 1) or choosing any other major (coded as 0).
Behavioral factors comprising the constructs of attitude, perceived behavioral
control, and subjective norms, and developmental factors comprising the constructs of
external formulas, crossroads, and early self-authorship influence a college student’s
choosing of a major positively and directly. I hypothesize that, as strong as TPB is
considered to be in its original form, adding the self-authorship constructs in terms of
capacity to operate as an individual will increase the strength of prediction of the TPB
model.

16

Attitude

H1: +
Subjective Norms

Perceived
Behavioral Control

H2: +

H3: +

Choose Hospitality
Business

H4: +
External Formulas
H5: +

Crossroads

H6: +

Early Self-Authorship

Figure 2: Proposed model for this study

17

Hypotheses
Based on the proposed conceptual model the following are the hypotheses for this
study:
H1: Attitude construct is expected to have a direct positive influence on Choose
Hospitality Business construct

H2: Subjective Norms construct is expected to have a direct positive influence on
Choose Hospitality Business construct

H3: Perceived Behavioral Control construct is expected to have a direct positive
influence on Choose Hospitality Business construct

H4: External Formulas construct is expected to have a direct positive influence on
Choose Hospitality Business construct

H5: Crossroads construct is expected to have a direct positive influence on
Choose Hospitality Business construct

H6: Early Self-Authorship construct is expected to have a direct positive influence
on Choose Hospitality Business construct

18

CHAPTER 3
RESEARCH DESIGN AND METHODOLOGY

The focus of this chapter is on: (1) the design of the study; (2) data collection;
(3) instrumentation; and (4) data analyses.

Design of the study
Population and Sample
Based on the guidelines of program admittance at junior-level standing, students
taking 100- and 200-level hospitality business classes at Michigan State University
(MSU), a Carnegie Land Grant Institution, in this study are usually “declared”
hospitality business majors or those exploring the major. The School of Hospitality
Business is an industry-specific School in The Broad College of Business at MSU.
Declared or exploring students in The Broad College of Business comprise a group of
freshmen and sophomores who are working on becoming eligible for admission to a
major. This group is taking hospitality business classes including and beyond the
introduction course for the purpose of delving deeper into the discipline areas of the
Hospitality Business program and also completing the classes needed to be admitted
when junior standing is reached.
The purpose of this study is to empirically test a new theoretical model of
determinants in freshman and sophomore students’ decision-making process of choosing
hospitality business as their academic major. Thus, the population is all MSU college

19

students in academic year 2012-2013 who had not been formally admitted to their
preferred major. The sample is a convenience sample using students enrolled in 100- and
200-level hospitality business courses at Michigan State University.

Data Collection Procedures
Pretest. Before data collection, a pilot study was conducted to confirm the face
validity of measures and scales. Thirty-six upper-level college students enrolled in two
upper-level hospitality business courses during the summer session 2012 agreed to
provide feedback regarding: 1) the on-line survey’s graphic design, 2) the clarity of the
questions asked, and 3) the amount of time required to complete the questionnaire. They
completed the questionnaire online at their convenience. The feedback collected from this
pretest on questions and/or problems concerning format and wording was used to refine
the survey instrument for the main survey. The above steps insured that the questionnaire
was satisfactory in terms of content and face validity.
Survey Administration. The cross-sectional survey was administered December 3
- 7, 2012 and January 27 – February 1, 2013 using the survey tool, Qualtrics. The
students in 100- and 200-level hospitality business courses (HB 100, 105, and 201 in fall
2012 and HB 100, 105, 201, 237, 265, and 267 in spring 2013) were sent an invitation
email containing the consent form and a link to follow to give consent, with the request
the survey be taken only one time. In some of the classes, the email with survey link was
distributed by the course instructor instead of by the researcher. As an incentive, all
participants were given the opportunity to enter a drawing to win one of two $50 gift
cards from a regional home and grocery store. Students who completed the survey and

20

chose to leave their contact information were entered into the drawing. A reminder email
was sent to the students and the professors half-way through the survey window.
Questionnaire Format. This study employs the quantitative survey research
method which is considered an appropriate method to address these research questions.
Specifically, a survey is a good method for examining relationships between factors
(Trochim, 2001). Quantitative methodology gave a large set of findings for this study by
obtaining responses from many people. Responses were gathered via an online survey
tool, Qualtrics. The instrument was administered online for ease of the students in
completing it and increased accuracy in compiling the data. All students at Michigan
State University have Internet connection available to them, and all students are required
to have their own computer, so there was no expected data collection bias.
The survey instrument consists of three main sections: [1] variables for measuring
factors of self-authorship (external formulas, crossroads, and early self-authorship), [2]
variables for measuring factors of attitude, subjective norms, and perceived behavioral
control, and [3] socio-demographics. A copy of the survey instrument is provided in
Appendix A.
The survey is comprised of three sections. The first section of questions is drawn
from a career decision making survey developed by members of a team called Women
and Information Technology. The subset of questions from that study was constructed to
measure the first three phases in the development of self-authorship consisting of 18
items, each using a 4-point Likert scale from 1(disagree) to 4 (agree). While low-count,
even-number item scales are not as popular as higher-count scales, scales of as few as
two or three points are sufficient to meet criteria of test-retest reliability, concurrent

21

validity, and predictive validity (Jacoby & Matell, 1971). This instrument was grouped
into dimensions; the items were then tested for reliability and validity in 2010 by
Creamer, Baxter Magolda, and Yue. Their initial data analysis involved Confirmatory
Factor Analysis (CFA) and the Multidimensional Random Coefficients Multinomial
Logit Model based on a generalized Item Response Theory (IRT). This modeling method
provided a statistical procedure for determining that the three-phase, three-dimension
factor structure was the most robust measure from among other configurations (Creamer,
Baxter Magolda, and Yue, 2010). Section One includes questions regarding how students
view their role in making education decisions, how advice is viewed, and how much
outside input is accepted. These questions pertain to the self-authorship constructs of
external formulas, crossroads, and early self-authorship.
Section Two of the survey is adapted from Allen’s (2004) and Cohen and
Hanno’s (1993) survey tools. The questions are asked in a 7-point Likert scale format.
Some studies suggest that seven response options are optimal (Cicchetti, Showalter, &
Tyrer, 1985). Using the theory of planned behavior as the theoretical framework, seven
additional items influencing choice of major were gathered from other studies (Bradford,
2005; Sibson, 2011; Yu, 2011) and adapted to focus on hospitality business
In Section Three, questions to assess any socio-demographic differences were
asked. These included age, gender, socio-economic status, GPA, and ethnicity.

Instrumentation
Constructs in the proposed conceptual model depicted in Figure 2 were derived
from the respondents’ self-reported perceptions in response to the question stimuli.

22

Factors for use in the proposed model were assessed using multiple item measures. All
scales were based on previous empirical studies using the theory of planned behavior and
the theory of self-authorship (Ajzen; 1991; Allen, 2004; Bradford, 2005; Cohen and
Hanno, 1993; Creamer, Baxter Magolda, and Yue, 2010; Yu, 2011). All items were
modified to reflect the context of choosing hospitality business as an academic major.
The proposed model includes seven constructs which were unobserved (i.e.
attitude, subjective norms, perceived behavioral control, external formulas, crossroads,
early self-authorship, and choose hospitality business). It also included forty-two
observed variables associated with those factors. These are listed in detail in Tables 8
and 9.
Attitude
Attitude toward choosing Hospitality Business as a major was measured with
thirteen 7-point Likert scale questions based upon items from Allen (2004) and Cohen
and Hanno (1993). First, using a scale of “very unimportant” to “very important”,
students responded to questions of how important the factor (outcome) identified in the
survey question is to the choice of academic major. For example, participants are asked to
rate the importance of the following question: “Choosing a major that prepares me for a
field with a number of job opportunities is….” Second, the participants assess the
likelihood that majoring in hospitality business and majoring in another major will result
in that same outcome using the seven-point Likert scale of “very unlikely” to “very
likely”. For example, “Choosing a major that prepares me for a field with a number of
opportunities will likely result if hospitality business is chosen as my major”, and
“Choosing a major that prepares me for a field with a number of opportunities will likely

23

result if a major other than hospitality business is chosen as my major.” The items in this
construct are listed in Table 2.
Table 2. Description observed variables in the attitude construct of the proposed model
Observed
Factor Variables
Survey Questions
Attitude A1
Thinking of a major or career for you, earning a good salary
initially is…
A2
Choosing a career with increasing salary and advancement
potential is…
A3
Entering a field that offers a chance to become an owner is…
A4
Choosing a career that provides social status is…
A5
Choosing an academic major that is not boring is…
A6
Choosing an academic major that is exciting is…
A7
Choosing a major with easy courses is…
A8
Choosing a major that prepares me for a field with a number
of job opportunities is…
A9
Choosing a major with the least cost of education is…
A10
Choosing a major that builds on previous or current
volunteer/employment experience is…
A11
Being a part of a department or school that is prestigious is…
A12
Having a degree with transferable skills and knowledge is…
A13
Being a part of a major that has social perks is…

Subjective Norms
Subjective norms were measured by seven items using 7-point rating scales from
Allen (2004), based on Ajzen (1991). These questions consisted of: “How much do you
care whether your parents approve or disapprove of your choice of an academic major?”
(1: very much to 7: not at all); “My advisors think I should major in hospitality business”
(1: very unlikely to 7: very likely); and “My professors think I should major in a field
other than hospitality business” (1:very unlikely to 7:very likely). The items in this
construct are listed in Table 3.

24

Table 3. Description observed variables in the subjective norms construct of the proposed
model
Observed
Factor
Variables
Survey Questions
Subjective SN3
How much do you care whether your parents approve or
Norms
disapprove of your choice of an academic major?
SN4
How much do you care whether your professors…
SN5
How much do you care whether your classmates…
SN6
How much do you care whether most business people…
SN7
How much do you care whether your siblings…
SN8
How much do you care whether your advisors…
SN9
How much do you care whether your friends…
Perceived Behavioral Control
Four items were measured with 7-point Likert scales from Allen (2004). These
questions consisted of: “The availability of job opportunities for hospitality business
graduates made it or would make it difficult for me to choose hospitality business as my
major” (1: strongly disagree to 7: strongly agree); “The statistics and math background
required in other majors’ courses made it or would make it difficult for me to choose a
major other than Hospitality Business as a major” (1: strongly disagree to 7: strongly
agree); and “It would be or was easy for me to choose Hospitality Business as my major”
(1: strongly disagree to 7: strongly agree). The items in this construct are listed in Table 4.
Table 4. Description observed variables in the perceived behavior control construct of the
proposed model
Observed
Factor
Variables
Survey Questions
Perceived PBC1
The statistics and math background required in
Behavior
Hospitality Business / a major other than Hospitality
Control
Business made or would make it difficult for me to
choose Hospitality Business / a major other than
Hospitality Business as my major.
PBC4
The availability of job opportunities for Hospitality
Business graduates…
PBC10
It would be or was easy for me to choose Hospitality
Business as my major / to choose a major other than
Hospitality Business.

25

Table 4 (cont’d)
Observed
Factor
Variables
Survey Questions
Perceived PBC11
My performance in other classes has been or would be
Behavior
hurt because of the workload of Hospitality Business
Control
courses/ courses in other majors.

External Formulas
This variable was measured with six items on 4-point Likert scales of 1: disagree
to 4: agree from Creamer, Magolda, and Yue (2010). Examples are “To make a good
choice about a career, I think the facts are the strongest basis for a good decision”; “The
most important role of an effective career counselor or advisor is to be an expert on a
variety of career options”; and “My primary role in making an education decision such as
choosing my major is to seek direction from informed experts.” The items in this
construct are listed in Table 5.
Table 5. Description observed variables in the external formulas construct of the
proposed model
Observed
Factor
Variables
Survey Questions
External ExF1
My primary role in making an education decision such as
Formulas
choosing my major is to acquire as much information as
possible.
ExF2
My primary role in making an education decision such as
choosing my major is to seek direction from informed experts.
ExF3
To make a good choice about a career, I think that facts are the
strongest basis for a good decision.
ExF4
To make a good career choice about a career, I think that
experts are in the best position to advise me about a good
choice.
ExF5
The most important role of an effective career counselor or
advisor is to be an expert on a variety of career options.
ExF6
The most important role of an effective career counselor or
advisor is to provide guidance about a choice that is appropriate
to me.

26

Crossroads
Measured by five items on 4-point Likert scales of 1: disagree to 4: agree from
Creamer, Magolda, and Yue (2010), this variable includes questions such as “To make a
good career choice about a career, I think that it is largely a matter of personal opinion”;
“The most important role of an effective career counselor or advisor is to help students
think through multiple options”; and “My primary role in making an education decision
such as choosing a major is to consider my own views.” The items in this construct are
listed in Table 6.
Table 6. Description observed variables in the crossroads construct of the proposed
model
Observed
Factor
Variables
Survey Questions
Crossroads CRS1
My primary role in making an education decision such as
choosing my major is to consider my own views.
CRS2
If a teacher or advisor recommended a career in a field that I
have never considered before, I would explain my point of
view.
CRS3
To make a good career choice about a career, I think that it is
largely a matter of personal opinion.
CRS4
The most important role of an effective career counselor or
advisor is to help students think through multiple options.
CRS5
When people have different interpretations of a book, I think
that some books are just that way. It is possible for all
interpretations to be correct.

Early Self-Authorship
Early self-authorship was measured by seven items using 4-point Likert scales of
1: disagree to 4: agree from Creamer, Magolda, and Yue (2010). Examples of these
questions are: “If a teacher or advisor recommended a career in a field that I have never
considered before, I would try to understand their point of view and figure out an option
that would best fit my needs and interests,”; “To make a good career choice about a

27

career, it is not a matter of facts or expert judgment, but a match between my values,
interests, and skills, and those of the job,”; and “My primary role in making an
educational decision in choosing my major is to make a decision considering all the
available information and my views.” The items in this construct are listed in Table 7.
Table 7. Description observed variables in the early self-authorship construct of the
proposed model
Observed
Factor
Variables
Survey Questions
Early Self- ESA1
My primary role in making an educational decision in
Authorship
choosing my major is to make a decision considering all the
available information and my views.
ESA2
If a teacher or advisor recommended a career in a field that I
have never considered before, I would try to understand their
point of view and figure out an option that would best fit my
needs and interests.
ESA3
To make a good career choice about a career, it is not a
matter of facts or expert judgment, but a match between my
values, interests, and skills and those of the job.
ESA4
In my opinion, the most important role of an effective
counselor or advisor is to direct students to information that
will help them to make a decision on their own.
ESA5
When people have different interpretations of a book, I think
that multiple interpretations are possible, but some are closer
to the truth than others.
ESA6
Experts are divided on some scientific issues, such as the
causes of global warming. In a situation like this, I would
have to look at the evidence to come to my own conclusion.
ESA7
Experts are divided on some scientific issues, such as the
causes of global warming. In a situation like this, I think it is
best to accept the uncertainty and try to understand the
principal arguments behind the different points of view.

Choose Hospitality Business
The questions, “What is your major today?” and “If you are no-preference, what
academic major would you pick if asked to choose one today?” were asked as openended questions. The participant’s behavior of choosing hospitality business or choosing

28

some other major was assessed using the responses to these two items. Since the
respondents gave a strong indication of what their choice of major would be, this variable
was used to determine the groups of choose hospitality business and choose other major
for subsequent analysis.
Table 8. Description of factors and observed variables in the theory of planned behavior
(TPB) constructs of the proposed model
Observed
Factors Variables
Survey Questions
Response Scale
a
A1
Thinking of a major or career for you, earning a
1:very unimportant
A
good salary initially is
to 7: very important
&1: very unlikely
to 7: very likely
A2
Choosing a career with increasing salary and
advancement potential is
A3
Entering a field that offers a chance to become
an owner is
A4
Choosing a career that provides social status is
A5
Choosing an academic major that is not boring is
A6
Choosing an academic major that is exciting is
A7
Choosing a major with easy courses is
A8
Choosing a major that prepares me for a field
with a number of job opportunities is
A9
Choosing a major with the least cost of
education is
A10
Choosing a major that builds on previous or
current volunteer/employment experience is
A11
Being a part of a department or school that is
prestigious is
A12
Having a degree with transferable skills and
knowledge is
A13
Being a part of a major that has social perks is
b
SN3
How much do you care whether you parents
1:very much to 7:
SN
approve/disapprove of your choice of academic
not at all & 1:very
major?
unlikely to 7: very
SN4
How much do you care whether your
likely
professors…
SN5
How much do you care whether your
classmates…
SN6
How much do you care whether most business
people…
SN7
How much do you care whether your siblings…

29

Table 8 (cont’d)
Observed
Factors Variables
Survey Questions
b
SN8
How much do you care whether your
SN
advisors…
SN9
How much do you care whether your
friends…
PBC1
The statistics and math background
c
PBC
required in Hospitality Business / a major
other than Hospitality Business made or
would make it difficult for me to choose
Hospitality Business / a major other than
Hospitality Business as my major.
The availability of job opportunities for
PBC4
Hospitality Business graduates…
It would be or was easy for me to choose
PBC10
Hospitality Business as my major / to
choose a major other than Hospitality
Business.
My performance in other classes has been
PBC11
or would be hurt because of the workload
of Hospitality Business courses/ courses
in other majors.

Response Scale
1:very much to 7: not
at all & 1:very unlikely
to 7: very likely

1:strongly disagree to
7: strongly agree

1:strongly disagree to
7: strongly agree
1:strongly disagree to
7: strongly agree

1:strongly disagree to
7: strongly agree

a

Note: Attitude: overall evaluative response of choosing hospitality business as a major;
b

Subjective Norms: the perceived social pressure in choosing hospitality business as a
c

major; Perceived Behavioral Control: perception of how easy or difficult it is to choose
hospitality business as a major.

30

Table 9. Description of factors and observed variables of the self-authorship (SA)
constructs in the proposed model
Observed
Factors Variables
Survey Questions
Response Scale
a
ExF1
My primary role in making an
1:disagree to 4: agree
ExF
education decision such as choosing
my major is to acquire as much
information as possible.
ExF2
My primary role in making an
1:disagree to 4: agree
education decision such as choosing
my major is to seek direction from
informed experts.
ExF3
To make a good choice about a career, 1:disagree to 4: agree
I think that facts are the strongest basis
for a good decision.
ExF4
To make a good career choice about a
1:disagree to 4: agree
career, I think that experts are in the
best position to advise me about a good
choice.
ExF5
The most important role of an effective 1:disagree to 4: agree
career counselor or advisor is to be an
expert on a variety of career options.
ExF6
The most important role of an effective 1:disagree to 4: agree
career counselor or advisor is to
provide guidance about a choice that is
appropriate to me.
b
CRS1
My primary role in making an
1:disagree to 4: agree
CRS
education decision such as choosing
my major is to consider my own views.
CRS2
If a teacher or advisor recommended a
1:disagree to 4: agree
career in a field that I have never
considered before, I would explain my
point of view.
CRS3
To make a good career choice about a
1:disagree to 4: agree
career, I think that it is largely a matter
of personal opinion.
CRS4
The most important role of an effective 1:disagree to 4: agree
career counselor or advisor is to help
students think through multiple options.
CRS5
When people have different
1:disagree to 4: agree
interpretations of a book, I think that
some books are just that way. It is
possible for all interpretations to be
correct.
c
ESA1
My primary role in making an
1:disagree to 4: agree
ESA
educational decision in choosing my

31

Table 9 (cont’d)
Observed
Factors Variables

ESA2

ESA3

ESA4

ESA5

ESA6

ESA7

Survey Questions
major is to make a decision considering
all the available information and my
views.
If a teacher or advisor recommended a
career in a field that I have never
considered before, I would try to
understand their point of view and
figure out an option that would best fit
my needs and interests.
To make a good career choice about a
career, it is not a matter of facts or
expert judgment, but a match between
my values, interests, and skills and
those of the job.
In my opinion, the most important role
of an effective counselor or advisor is
to direct students to information that
will help them to make a decision on
their own.
When people have different
interpretations of a book, I think that
multiple interpretations are possible,
but some are closer to the truth than
others.
Experts are divided on some scientific
issues, such as the causes of global
warming. In a situation like this, I
would have to look at the evidence to
come to my own conclusion.
Experts are divided on some scientific
issues, such as the causes of global
warming. In a situation like this, I
think it is best to accept the uncertainty
and try to understand the principal
arguments behind the different points
of view.

Response Scale

1:disagree to 4: agree

1:disagree to 4: agree

1:disagree to 4: agree

1:disagree to 4: agree

1:disagree to 4: agree

1:disagree to 4: agree

a

Note: External Formulas: the stage where individuals rely heavily on the influences of
b

others; Crossroads: the stage where individuals begin to practice their own decisionc

making; Early Self-Authorship: self-reliance and confidence in decision-making become
more common for individuals.

32

Data Analyses
Data were analyzed using AMOS and SPSS 20. A two-stage data analysis
procedure was used. In stage one, the descriptive analysis was used to compare the sociodemographics of the study participants. Stage two used Binary Logistic (Logit)
Regression to assess construct measures in the proposed model, in order to examine the
relationships between the constructs in the conceptual model. Following Anderson and
Gerbing’s (1988) two-step approach, a measurement model was estimated using
Confirmatory Factor Analysis (CFA) to ensure the adequacy of convergent and
discriminant validity. CFA was employed on items comprising the six constructs of the
full new model: attitude, subjective norms, perceived behavioral control, external
formulas, crossroads, and early self-authorship to show that the items measuring a given
construct can be considered indicators of the same latent variable. A model in which the
constructs’ items are treated as assessing separate constructs is superior to a model in
which all items are considered to measure the same underlying construct (Ajzen, 2009).

Differential Perceptions
In Section Two of the questionnaire, participants were asked to rate the
importance of items in the TPB constructs as well as the likelihood of that item occurring
by majoring in hospitality business and by majoring in a field other than hospitality
business. In total, students rated the importance of each factor to their academic major
decision. Next, following Allen (2004) and Cohen and Hanno (1993), the factors were
used to assess students’ perceptions toward each target behavior (choosing hospitality
business as a major) and non-target (choosing any other major) behavior, and then derive

33

a differential perception (i.e. target behavior minus non-target behavior) toward the
behavior. As noted by Ajzen and Fishbein (1980, p. 118), better prediction can be
obtained by considering the difference between the belief and their underlying
determinants than by considering each belief and its determinants individually. Finally,
the participant’s difference score is multiplied by the related outcome assessment. The
resulting products (per participant) are summed, and represent 1) the participant's
differential personal perception toward a major in hospitality business; 2) differential
perception of important referents toward a major in hospitality business; and 3) the
participant's differential perceived control over choosing a major in hospitality business.
See the Appendix B for a detailed calculation example.

Logistic Regression
Binary Logistic Regression (Logit) is a statistical technique which allows for a
regression-like analysis of the data in cases where the dependent variable is a qualitative
rather than a continuous interval-level variable (Walsh, 1987). In general, logistic
regression is a good choice for describing and testing hypotheses about relationships
between a categorical outcome variable and one or more categorical or continuous
predictor variables (Peng, Lee, and Ingersoll, 2002). In this study, the outcome is coded
as 1 if the student did or would choose hospitality business as his/her major and 0 if the
student did or would choose any other major. Logit also allows the researcher to analyze
the effects of a set of independent variables on a dichotomous dependent variable with
minimal statistical bias and loss of information (Walsh, 1987).

34

Measurement Model
The measurement model identifies how factors are measured in terms of the
observed variables, and factors describe the measurement qualities of the observed
variables. The measurement model was evaluated with Confirmatory Factor Analysis
(CFA). During measurement model testing, CFA estimates only relationships among
factors, not direct causal effects. In other words, causal relationships among factors in the
proposed structural model are not a product of the measurement model. The measurement
model including seven factors and 42 observed variables was tested and evaluated
through the model specification procedure suggested by Jöreskog and Sörbom (1993).
Model fit indices. The measurement model was specified based on previous
theoretical and empirical studies. The proposed model was tested and evaluated using
overall fit indices and parameters estimated using CFA. Multiple indices were used in
this study including the chi-square statistic adjusted for degrees of freedom (2/df), the
comparative fit index (CFI), the non-normed fit index (NNFI), and the root mean square
error of approximation (RMSEA) in assessing the model fit following suggestions by
Kline (1998). General rules of thumb for model fit are that CFI and NNFI should be
greater than .90 and RMSEA should not be larger than .05 (Kline, 1998).

35

CHAPTER 4
RESULTS

The focus of this chapter is on: (1) survey response information; (2) descriptive statistics;
(3) normality test results; (4) confirmatory factor analysis results; and (5) hypothesestesting results of the proposed conceptual model.

Survey Response
Data Collection
The survey was made available to college students enrolled in a 100- and 200level hospitality business course at Michigan State University during fall semester 2012
and spring semester 2013. In the fall semester, 684 surveys were received, of which 546
were completed surveys. In the spring semester, of the 971 surveys received, 720 were
completed. Next, the two collections were compared to check for multiple submissions
from students enrolled in 100- and 200- level classes for both semesters. Eighty-one (81)
students took the survey in both December and January, so those students’ January
surveys were removed. In the final step of cleaning, any students identifying themselves
as juniors or seniors were removed, equaling 149 in December and 137 in January. The
final number of useable surveys was 899 (December 397, January 502) as presented in
Table 10.

36

Table 10. Summary of data collection: total sample, returned sample, invalid sample, and
valid sample

Returned surveys
a
Invalid cases
Valid cases

December 2012
684
287

January 2013
971
466

Total
1655
753

397

505

899

a

Note: Invalid sample refers to respondents with incomplete or double responses, or

upper-level class standing.

Characteristics of Survey Respondents
As shown in Table 11, the distribution of the top three declared academic majors
of the participants taking introductory hospitality business courses is as follows: Business
(50.8%), Hospitality Business (27%), and No-Preference (10.2%). Social Science /
Education (4.5%), Liberal Arts / Communication (3.2%), and Natural Science / Medical
(3.1%) were the following three majors in frequency ranking.

Table 11. Survey respondents’ identified academic majors (n=893)
Category
Majors

Descriptions
Business (Finance, Accounting, Marketing)
Hospitality Business
Social Science / Education
Liberal Arts / Communication
Natural Science / Medical
Engineering
Agriculture / Environment / Natural Resources
Other
No-Preference

Frequency
454
241
40
29
28
6
5
5
91

Percent
50.8%
27.0%
4.5%
3.2%
3.1%
0.7%
0.6%
0.6%
10.2%

Of the respondents indicating No-Preference as their declared major, Business
(25.3%), Hospitality Business (23.1%), and Social Science/Education (13.2%) were the

37

three most frequently identified when asked to name a major he/she would choose if
required to do so today. The complete distribution is presented in Table 12.

Table 12. No-preference survey respondents’ identified academic majors (n=91)
Category
Majors

Descriptions
Business (General Business, Accounting, Finance)
Hospitality Business
Social Science / Education
Engineering
Natural Science / Medical
Liberal Arts / Communication
Other
Agriculture / Environment / Natural Resources
Unspecified

Frequency

Percent

23
21
12
6
5
5
4
3
12

25.3%
23.1%
13.2%
6.6%
5.5%
5.5%
4.4%
3.3%
13.2%

Study Subjects Selected from Survey Respondents
Survey respondents included not only freshmen and sophomores who have or
would choose Hospitality Business as their major, the targeted study population, but also
those who have or would choose any other major. The sample screening procedure
resulted in a final sample of 262 freshmen and sophomores who have declared, or would
choose, hospitality business as their major, representing 29.1% of the 899 survey
respondents.

Demographic Comparisons of Study Subjects to Other Subjects
Demographic characteristics of students choosing hospitality business (n=262)
were compared with the students in the study choosing any other major (n=637) to assess
similarities and differences. Subjects as a sample group were also compared to all
Michigan State University undergraduate students and U.S. four-year college students

38

based on US national education data to assess generalizability of the sample. Results of
these comparisons are presented in Tables 13 and 14.
As displayed in Table 13, the Hospitality Business majors are significantly
different from the non-hospitality business majors for each of the demographics except
academic year and family income. Hospitality business majors are more likely to be
female as compared with non-hospitality business students in this study (69.1%
hospitality business vs. 52.8% non-hospitality business), a younger group (74.0%
hospitality business vs. 61.2% non-hospitality business are 19 or younger) and more
likely to have a GPA below 3.0 (35% hospitality business vs. 25.4% non-hospitality
business). Ethnically, hospitality business majors more often identified as
White/Caucasian (65.9% hospitality business vs. 52.8% non-hospitality business) and
Hispanic/Latino (3.1% hospitality business vs. 1.0% non-hospitality business). There is
no significant difference between the family income levels of the two groups.

Table 13. Comparison of demographic characteristics of sample

Demographic
variables

Hospitality
Business
a
Majors
(n=262)

All
Descriptions

NonHospitality
Business
b
Majors
(n=637)

c

Test statistics


2

p

Gender
2

.000

2

Male
Female

.000

42.4%
57.6%

30.9%
69.1%

47.2%  =20.03
52.8%

65%
35%

74.0%
26.0%

61.2%  =13.41
38.8%

Age
19 or younger
20 or older

39

Table 13 (cont’d)
Demographic
variables

Hospitality
Business
a
Majors
(n=262)

All
Descriptions

NonHospitality
Business
b
Majors
(n=637)

c

Test statistics
p

 =0.54

.461

 =93.09

Academic
year

2

2

.000

2
 =8.75

.033



2

Freshman
Sophomore

50.4%
49.6%

48.5%
51.5%

51.2%
48.8%

White /
Caucasian

43.6%

65.9%

34.4%

Asian / Pacific
Islander

49.3%

25.3%

59.3%

Black / African
American

4.9%

5.7%

4.6%

Hispanic /
Latino

1.6%

3.1%

1.0%

Native
American

0.6%

0.8%

0.0%

Ethnicity

G.P.A.
3.5 or higher
3.0 to 3.49
2.5 to 2.99
2.49 or lower
Family
Income

31.4%
40.4%
19.1%
9.0%

28.0%
37.0%
24.5%
10.5%

32.8%
41.8%
17.0%
8.4%

$100,000 or
higher

46.9%

50.2%

45.5%

$75,000 to
$99,999

14.1%

16.3%

13.2%

$50,000 to
$74,999

15.3%

15.1%

15.3%

$49,999 or
lower

23.7%

2

 =6.42

40

18.3%

25.9%

.093

Table 13 (cont’d)
a

Note: Hospitality Business Majors refers to the respondents who have currently
b

declared or would declare hospitality business as their major. Non-Hospitality Business
Majors refers to respondents who have currently declared or would declare any major
c
other than Hospitality Business. p<.05.

Gender, age, and ethnicity are compared for participants in this study, MSU
undergrads, and undergrads from all U.S. 4-year colleges in Table 14. The data for only
freshmen and sophomores from the comparison groups could not be found for a better
comparison, so broader data for both MSU and U.S. college students were used for
comparison. Whereas the gender breakdown in this study is 42.4% male to 57.6%
female, the MSU student population is 49.8% male to 50.2% female and the U.S. college
population is 45% male to 55% female. The ages of all U.S. four-year college students
are distributed as follows: 19 or younger 28.6% and 20 or older 71.4%. MSU’s age
breakdown is age 19 or younger 39.1% and age 20 or older 60.9%. This is opposite of
the age breakdown of the study participants: age 19 or younger 65% and age 20 or older
35%. Regarding ethnic background, the majority of study subjects are Asian/Pacific
Islander (49.3%), followed by White/Caucasian (43.6%), Black (4.9%), Hispanic/Latino
(1.6%) and Native American (0.6%). Ethnic background for MSU undergrads and U.S.
college undergrads are White (79.5% and 64.6%, respectively), Black (7.9% and 14.6%,
respectively), Asian (4.8% and 6.5%, respectively), Hispanic (3.8% and 11.3%,
respectively) and Native American (.04% and .08%, respectively). The Native American
percentages are the only numbers similar across all three groups.

41

The subjects in this study that have or would choose hospitality business (N =
262) do not have overall demographic characteristics similar to those respondents who
have or would choose a major other than hospitality business (N = 637) and, as a whole
sample, are dissimilar to the total population of MSU and U.S. college students. This
creates the likelihood that generalizability of results to other hospitality programs could
likely be problematic based on the specificity of this study and its respondents. This
group of students may not think or act like groups of students elsewhere.
Table 14. Comparison of demographic characteristics of study subjects, Michigan State
University (MSU) students, and U.S. four-year college students
Demographic
variables

Descriptions

Study
a
subjects
(n=899)

MSU
undergrad
b
students
(n=33,044)

U.S. four year
c
college students
(n=10,563,055)

Gender
Male
Female

42.4 %
57.6 %

49.8%
50.2%

45%
55%

19 or younger
20 or older

65%
35%

39.1%*
60.9%*

28.6%
71.4%

White / Caucasian
Asian / Pacific
Islander
Black / African
American
Hispanic / Latino
Native American

43.6%

79.5%

64.6%

49.3%

4.8%

6.5%

4.9%
1.6%
0.6%

7.9%
3.8%
0.4%

14.6%
11.3%
0.8%

Age

Ethnicity

a

Note: Study subjects refer to respondents who are freshmen and sophomores taking
100- and 200-level hospitality business courses. This sample was used for main analyses,
b
testing the proposed model and developing a profile of students in this study. Source:
Undergraduate enrollment, Fall 2011, MSU Office of Planning and Budgets, Data Digest
c
2012. Source: four year undergraduate college students in Table 226 “Total fall
enrollment in degree-granting institutions, by level of enrollment, control and level of
institution, attendance status, and age of student: 2011”, Digest of Education Statistics,

42

National Center for Education Statistics. *MSU reports the ages of 19-20 as one group in
its printed reports. Here, 20 year-olds are included with the 19 and younger category.
Testing the Measurement Model: Confirmatory Factor Analysis in AMOS
This section concentrates on assessing the measurement model that represents
relationships between observed variables and factors. First, assumption tests measuring
normality of the data are discussed. Next, the measurement model is assessed through
confirmatory factor analysis (CFA). The discussions of reliability, convergent validity,
and discriminant validity for the measurement model are discussed.

Normality Test
The normality for each variable in the proposed model was examined to
determine if the data meet the normality assumption for the maximum likelihood
estimation (MLE) method. The normality test is an important preliminary analysis step
since test results must fall within acceptable standards for subsequent analyses to be
meaningful. Skewness and kurtosis tests were performed to evaluate normality. Data in
Table 15 show that the value for univariate skewness and kurtosis ranged from –2.36
(A1) to –0.28 (PBC2) and from –0.33 (SN3) to 8.0 (A1) respectively. Values of all
variables in the model for univariate skewness and kurtosis were found to fall within
conventional criteria of normality (-3 to 3 for skewness and –10 to 10 for kurtosis)
(Kline, 1998).

43

a

Table 15. Normality test results of items included in the proposed model presented in
Figure 2
b
c
Constructs and Items
Skewness
Kurtosis
(>│3│= extremely
skewed)

(>│10│:
extremely peaked)

Attitude (A)
A1
A2
A3
A4
A5
A6
A7
A8
A9
A10
A11
A12
A13

-2.26
-1.70
-1.95
-2.09
-2.14
-0.76
-1.18
-0.43
-0.62
-0.16
-0.28
-0.87
-0.79

7.00
4.29
4.66
5.86
6.95
-0.06
3.40
-0.33
0.00
0.14
-0.44
-4.04
-0.25

Subject norms (SN)
SN1
SN2
SN3
SN4
SN5
SN6
SN7

-1.06
-1.21
-1.06
-1.18
-1.37
-2.03
-1.68
-1.21

1.01
-1.81
0.67
1.70
2.46
2.58
1.96
1.42

Perceived behavioral control (PBC)
PBC1
PBC2
PBC3
PBC4

-1.84
-1.43
-1.60
-1.89
-1.57

1.50
0.76
3.34
4.43
2.85

-1.12
-2.36
-1.70
-1.95
-2.09
-2.14

0.65
6.88
4.19
4.66
5.46
3.95

Self-authorship (SA)
External Formulas (EXF)
EXF1
EXF2
EXF3
EXF4
EXF5
EXF6

44

Table 15 (cont’d)
b

Constructs and Items

c

Skewness
(>│3│= extremely
skewed)

-0.73
-0.62
-0.46
-0.28
-0.87
-0.79

Early Self-Authorship (ESA)
ESA1
ESA2
ESA3
ESA4
ESA5
ESA6
ESA7
a

-0.33
0.00
0.14
-0.44
-0.04
-0.25

-1.04
-1.21
-1.16
-1.18
-1.37
-2.36
-1.48

Crossroads (CRS)
CRS1
CRS2
CRS3
CRS4
CRS5

Kurtosis
(>│10│:
extremely peaked)

1.01
1.81
0.67
1.70
2.46
3.58
1.76
b

Note: Normality was examined in terms of skewness and kurtosis. Skewness refers to
the symmetry of the distribution. Skewness with a value above three is conventionally
c
considered as extremely skewed. Kurtosis indicates a relative excess of cases in the tails
of a distribution relative to a normal distribution. A kurtosis value of 10 is a conventional
criterion indicating normality distribution in terms of its peakedness. Values above 10 are
considered extremely peaked.

Model Specification
The proposed measurement model was specified for the relationships between
the observed variables and the factors through loadings of the observed variables and
their error term. All factors and observed variables were specified based on previous
empirical studies discussed in Chapter 3.
As shown in Figure 2, the proposed measurement model consisted of seven
factors and 42 observed variables. The attitude construct was specified by thirteen items,
the subjective norms construct was specified by seven items, and the perceived

45

behavioral control construct was specified by four observed variables. External formulas
construct included six observed variables, crossroads construct contained five items, and
early self-authorship construct was specified by seven items. All observed variables in
the proposed measurement model were presented earlier in Tables 8 and 9.

Model Testing

Analyses. Confirmatory Factor Analysis (CFA) was employed to assess construct
measures in the proposed model. The AMOS and SPSS 20.0 statistical program package
were used for CFA. To examine the causal relationships in the model, logit regression
was used via SPSS 20.
Reliability. In the first stage of model testing, confirmatory factor analysis was
employed to test measurement validity. CFA results established evidence of reliability,
convergent validity, and discriminant validity in the measurement model. Reliability of
measures was evaluated by estimating Cronbach’s alpha and composite construct
reliability (CCR). Reliability scores range from  = .70 to  = .96 which are equal to or
above the recommended .70 level. Observed variables should have a Cronbach’s alpha
of .7 or higher to be judged reliable measures (Nunnally, 1978). CCRs of all constructs
also exceed the level of 0.70. All scales demonstrate generally good reliability.
Convergent validity is used to determine if different observed variables used to measure
the same construct are highly correlated. Convergent validity can be assessed by
reviewing the t-test for factor loadings (Hatcher, 1994) and average variances extracted
(AVE) (Hair, Anderson, Tatham, and Black (1998). As presented in Table 16, all factor
loadings for the observed variables measuring the same construct are relatively high

46

(statistically significant at p<.05), ranging from .48 to .93 Additional testing shows that
AVEs in all constructs exceed the critical level of 0.50. Both are evidence of convergent
validity.

Table 16. Confirmatory factory analysis results for the measurement model
Constructs and Items
Standardized AVE CCR Item-to-total
loading*
correlation
Theory of Planned Behavior
Attitude (A)
.74
.89
A1
.87
.42
A2
.88
.62
A3
.62
.60
A4
.70
.58
A5
.67
.60
A6
.79
.64
A7
.71
.42
A8
.68
.65
A9
.59
.40
A10
.88
.60
A11
.81
.60
A12
.69
.63
A13
.86
.64
Subject norms (SN)
SN3
SN4
SN5
SN6
SN7
SN8
SN9
Perceived behavioral control
(PBC)
PBC1
PBC4
PBC10
PBC11

.78

.91

.86
.93
.88
.83
.83
.72
.90

Cronbach’s
α
.88

.96
.80
.87
.91
.85
.89
.89
.86

.50

.71

.58
.64
.68
.52

.70
.47
.56
.57
.53

Self-authorship (SA)
External Formulas
(EXF)

.69

47

.82

.74

Table 16 (cont’d)
Constructs and Items
EXF1
EXF2
EXF3
EXF4
EXF5
EXF6

Standardized
loading*
.54
.58
.61
.54
.55
.62

Crossroads
(CRS)
CRS1
CRS2
CRS3
CRS4
CRS5

.53
.69
.51
.65
.643

Early Self-Authorship
(ESA)
ESA1
ESA2
ESA3
ESA4
ESA5
ESA6
ESA7

.48
.60
.51
.54
.54
.50
.66

AVE

CCR

.51

Item-to-total
correlation
.55
.57
.40
.33
.46
.55

Cronbach’s
α

.72

.71
.61
.42
.54
.70
.52

.56

.73

.70
.58
.52
.55
.61
.53
.51
.47

Note: *Factor loadings were all significant at p < .05. Goodness-of- fit indices of full
2
2
measurement model: χ = 1224.08 (df = 428), χ /df = 2.86, NNFI =.920; CFI = .931;
RMSEA = .058. CCR: composite construct reliability, AVE: average variances extracted

The overall mean difference for the constructs in the model for hospitality
business majors and for non-hospitality business majors are presented in Table 17. The
differential personal perception (attitude) is positive (62.93) for hospitality business
majors, and positive (6.87) for non- hospitality business majors for a significant mean
difference of 56.07. The differential perception of the influence of important people
(subjective norms) is statistically significant at p < 0.05). Also, the mean response for

48

subjective norms is positive (86.69) for hospitality business majors and negative (-25.18)
for non-hospitality business majors. The negative sign on the differential perceived
control construct for non-hospitality business majors is predicted by the theory of planned
behavior (mean response = - 0.83). The means of external formulas, crossroads, and early
self-authorship for both hospitality business majors and non-hospitality business majors
are positive in nature and similar in number, yet, the mean difference is statistically
significant at p < 0.05.
The positive mean differences between the groups for the differential attitude,
differential subjective norms, and perceived behavioral control are statistically significant
(p < 0.05), suggesting that non-hospitality business majors perceive significantly less
importance in academic major characteristics, less influence of referents, and less control
over choosing a major in hospitality business than hospitality business majors. Overall,
the results show that hospitality business majors have a positive perception of a major in
hospitality business, while non-hospitality business majors have an unfavorable
perception of hospitality business as a major based on the positive versus negative means
for the two groups.

49

Table 17. Summary of means and mean difference test (t-test) results: hospitality
business choice vs. non-hospitality business choice for factors in the model

Number
of
variables
13

Hospitality
Business
(n=260)
62.93

NonHospitality
Business
(n=635)
6.87

Mean
Difference
56.07

t-value
11.26*

Subjective Norms

7

86.69

-25.18

111.87

20.39*

Perceived Behavioral
Control

4

1.95

-0.83

2.78

17.46*

External Formulas

6

19.83

19.13

.69

3.21*

Crossroads

5

17.00

16.15

.85

4.86*

Early Self-Authorship
7
Note: *significant at p < .05

23.58

23.53

1.05

5.04*

Factors
Attitude

Discriminant Validity. Discriminant validity was assessed in two ways. First,
correlations among constructs were inspected. As presented in Table 18, estimated
correlations between constructs were not excessively high, and none of the pairs for the
95% confidence interval approach 1.00, thus providing support for discriminant validity
(Anderson & Gerbing, 1988). The stronger discriminant validity test is also achieved if
the square root of the average variance extracted (AVE) is larger than correlation
coefficients (Fornell and Larcker, 1981). All the correlation coefficients met this
criterion, establishing discriminant validity among the constructs in the proposed model.

50

Table 18. Correlations among constructs in the proposed model for examining
discriminant validity
SQR
of
1
2
3
4
5
6
M
SD
AVE
1. A
1
24.16 66.87
.83
2. SN
.40
1
7.57 82.67
.81
3. PBC
.36
.61
1
-0.02
2.43
.70
4. EXF
.02
.01
.02
1
19.34
2.96
.86
5. CRS
.10
.09
.02
.67
1
16.39
2.49
.74
6. ESA
.05
.09
.05
.57
.61
1
20.85
1.59
.81
Note: SQR = square root; A: The differential personal perception of choosing a major in
hospitality business versus choosing a major other than hospitality business. SN: The
differential perception of important people about a major in hospitality business versus a
major other than hospitality business. PBC: The perceived differential control over
choosing a major in hospitality business versus choosing a major other than hospitality
business. EXF: The strong reliance on the influence of others when choosing a major.
CRS: Partial reliance on the influences of others when choosing a major. ESA: The selfreliance in choosing a major.

Testing the Hypothesized Structural Model
Goodness-of-fit of the Structural Model
When the proposed measurement model was tested, according to overall fit
2

indices, the proposed model produced a good fit with the data, χ (428)=1224.08, p<.05
2

2

(χ /df=2.86, CFI=.931, NNFI=.920, RMSEA=.058). Guidelines of χ /df smaller than
3.0, RMSEA smaller than .05, CFI and NNFI all greater than .90 are suggested by Kline
(1998).

Path Coefficients and Hypothesis Testing
Path coefficients estimated by SPSS and hypothesis testing results are presented
in Table 19, which shows the logit regression results for choosing an academic major.

51

The Chi Square statistic for goodness-of-fit is 477.30 with six degrees of freedom. The
2

Pseudo R from the logit regression is .66. The path coefficient from the attitude
construct to the choose hospitality business construct (differential personal perception)
was significant at the .05 level, indicating a strong and positive relationship (=.206,
t=11.26, p<.05). The path coefficients from the subjective norms construct to the choose
hospitality business construct (differential perception of important people) (=.526,
t=20.39, p<.05), and from the perceived behavioral control construct to the choose
hospitality business construct (perceived differential control) (=.408, t=17.46, p<.05)
were significant with strong and positive relationships. Further, path coefficients from the
external formulas construct to the choose hospitality business construct (strong reliance
on others) (=.255, t=3.21, p<.05) and from the early self-authorship construct to the
choose hospitality business construct (strong self-reliance) (=.192, t=5.04, p<.05) were
significant at .05 level with strong and positive relationships. The significant test results
for path coefficients support all hypotheses (H1, H2, H3, H4, and H6) except one (H5)
which is the crossroads construct (CRS) to the choose hospitality business construct
(partial reliance on others). The logistic regression analysis shows that students’
perceptions, along with high- and low-levels of reliance on others, directly influence their
choice of academic major.

52

Table 19. Logit regression results
Variables
Intercept
A
SN
PBC
EXF
CRS
ESA

Predicted
sign
+
+
+
+
+
+

Coefficient 
(standard error)
-5.173 (.989)
.206* (.002)
.526* (.003)
.408* (.072)
.255* (.059)
.091 (.071)
.192* (.104)

Wald
27.380
10.403
80.315
31.991
16.985
1.670
10.420

Hypotheses
testing results
Supported
Supported
Supported
Supported
Not supported
Supported

Note: *Coefficients were significant at p < .05; A=attitude; SN=subjective norms;
PBC=perceived behavioral control; EXF=external factors; CRS=crossroads; ESA=early
self-authorship. Chi-square goodness-of-fit=477.30, six degrees of freedom, p=.000, 2
2log likelihood=458.79, Pseudo R =.66

Based on the relative values of coefficients from the results, the subjective norms
construct (=.526) has the highest level of explanatory power for the choose hospitality
business construct when compared to the perceived behavioral control construct
(=.408), the external formulas construct (=.255), the attitude construct (=.206), and
2

the early self-authorship construct (=.192). These factors explain 66% (R =.66) of the
variance in the outcome variable of choose hospitality business, as shown in Figure 3.
The effect of the subjective norms construct on the choose hospitality business construct
is shown by its high level of explanatory power (=.526). Compared to the other factors,
the construct of crossroads is not significant in explaining the prediction of the choose
hospitality business construct (=.091) at p<.05.

53

Attitude

.026*
Subjective Norms

.526*

2

Perceived
Behavioral Control

R =.66
.408*

Choose Hospitality
Business

.255*
External Formulas

.091

Crossroads

.192*

Early Self-Authorship

*Significant at p<.05
Figure 3: Test results for the proposed structural model: standardized path
2
coefficients and Pseudo R .

54

Effects on Choose Hospitality Business
Indications of the contributions made by the self-authorship constructs of external
formulas, crossroads, and early self-authorship were evident in the comparison of
explained variances for the choose hospitality business construct between simply using
the theory of planned behavior and using the combination of TPB and SA constructs. A
summary of explained variance in the choose hospitality business construct is shown in
Table 14. The addition of the Self-Authorship constructs increases the explained variance
2

in Choose Hospitality Business by 19%. R increases from .47 to .66, when the selfauthorship constructs are added to the model of the theory of planned behavior model.
Based on the results, it is concluded that the proposed model is an improvement on the
model of the theory of planned behavior to explain choosing hospitality business as a
major.

Table 20. Comparison of explained variance in choice of hospitality business for 1) the
theory of planned behavior (TPB), 2) the TPB plus self-authorship (SA)
2
Model
Choose Hospitality Business (R )
Theory of planned behavior
.47
Theory of planned behavior plus SA
.66
Note: TPB=Theory of Planned Behavior; SA=Self-Authorship Theory

55

CHAPTER 5
DISCUSSION, IMPLICATIONS, AND FUTURE RESEARCH

The focus of this chapter is on: (1) results of hypotheses testing and discussion of the
findings; (2) theoretical and practical implications; (3) limitations; and (4) future
research.

Summary Characteristics of Students who are Choosing their Majors
The freshmen and sophomore students in this study who have chosen or would
choose hospitality business in this study are typically female (69.1%) and
White/Caucasian (65.9%), with a GPA in the 3.0 to 3.49 range (37%). The likely student
in this sample who has chosen or would choose a major other than hospitality business is
Asian (59.3%), female (52.8%), and also holds a GPA in the 3.0 to 3.49 range (41.8%).
Of important note, the College of Business is the academic home to more Chinese
international students than any other college on campus. This large Chinese population is
reflected in the demographics for non-hospitality majors.

Results of Hypotheses Testing and Discussion of the Findings
The purpose of this study is to test empirically a new theoretical model in
understanding determinants in freshman and sophomore students’ decision-making
processes of choosing hospitality business as their major. These underclassmen and
women are in the midst of making a decision on academic major because, in MSU’s
College of Business, and several other colleges on campus, the junior year marks the time

56

when students apply to the academic major of his/her choice and move from “declared”
or “no-preference” to “admitted” into that major. In the modified and extended TPB
model proposed in this study, the intention construct was removed since the respondents
gave a strong indication of what their choice of major would be by asking the
respondents about their current major or, if classified as no-preference major of choice.
Additionally, the three SA constructs were added. As presented in Figure 2, the
conceptual model of this study was proposed to examine relationships among the
constructs with six hypotheses. The six identified constructs (attitude, subjective norms,
perceived behavioral control, external formulas, crossroads, and early self-authorship)
were proposed to be direct antecedents of the outcome variable (choose hospitality
business). Testing showed that overall fit for this model was good. Findings were
generally consistent with the proposed hypotheses. All hypothesized relationships were
strong and positive, as predicted, except for the hypothesized relationship between the
crossroads construct and the choose hospitality business construct. The link between
these two was calculated to be positive, but not statistically significant.
As the findings for each of the six hypotheses are discussed, none of the
suggestions discussed here, or in the implications section, work in isolation.

Hypothesis H1: Attitude construct is expected to have a direct positive influence on the
Choose Hospitality Business construct
The hypothesis of direct influence of the attitude construct on the choose
hospitality business construct was supported. Attitude has the fourth highest indicator of
strength, (=.206), of the 6 constructs. Comparing the means of the hospitality business
majors to those of the non-hospitality business majors (62.93 to 6.87, respectively), the

57

non-hospitality business majors perceived less importance of the academic major
characteristics, like choosing a major that is exciting or choosing a career with
increasing salary and advancement potential. Students who are interested in hospitality
business perceive more importance of characteristics of a major, such as gaining
transferrable skills and building on volunteer and work experiences and they feel more
strongly that choosing hospitality business will likely result in these outcomes than do
students evaluating other majors when considering other majors than hospitality
business. To attract students to hospitality business, showcasing characteristics such as
these will speak to students who perceive these as important.

Hypothesis H2: Subjective Norms construct is expected to have a direct positive
influence on Choose Hospitality Business construct
The hypothesis regarding the direct influence of subjective norms on choose
hospitality business was supported. Subjective norms is the construct that is the
strongest predictor of choose hospitality business (=.526). The group of seven
referents measured in this construct (parents, professors, classmates, most business
people I know, siblings, advisers, and friends) is part of the outcome to the secondary
objective of this study, which is to understand which groups of determinants are the
strongest predictors of students choosing hospitality business as an academic major.
Comparing the means of the hospitality business majors to those of the non-hospitality
business majors for this construct (86.69 to -25.18, respectively), the non-hospitality
business majors perceived much less importance of important referents’ influences.
Considering both results, hospitality business majors care very much about whether their
referents approve or disapprove of their choice of academic major and perceive that their

58

families, friends, advisors, and professors would support them in choosing hospitality
business as an academic major.

Hypothesis H3: Perceived Behavioral Control construct is expected to have a direct
positive influence on Choose Hospitality Business construct
The hypothesis regarding the direct influence of perceived behavioral control
construct on the choose hospitality business construct was supported. Perceived
behavioral control has the second highest indicator of strength, (=.408), of the 6
constructs. Comparing the means of the hospitality business majors to those of the nonhospitality business majors (1.95 to -0.83, respectively), the non-hospitality business
majors perceived less control over the choice of academic major. Items like the required
statistics and math background or class performance being affected by a major’s
workload are answered from different frames of reference for different students in
various majors.
This construct speaks to confidence in major success, availability of job
opportunities, ease of choosing a major, and performance in other classes due to major
work load. When it comes to a student changing his/her major, ease is related to
different stages. First, students must have access to advisors quickly and any advisor
should be allowed to help a student change a major, instead of requiring multiple steps
and office visits. Ease also is related to access to courses. A student wants to know if
he/she can pursue academic interests or not. Third, advisors need the time to evaluate
the student’s position and give good advice. Professional advisors of today do a better
job of this, like creating walk-in hours and availability during peak times, and asking the
questions students don’t know to ask, than some advising situations of years past.

59

Unfortunately, not all offices on campus have the availability to see students all day, like
lunch times and breaks. Finally, advisors, professors, and mentors need to coach
students on how to succeed in the classroom. One method for success is different study
approaches for different courses. Many students study one way for all of their classes,
relying on the way they have always done it. Therefore feeling that if they didn’t do
well in math, science, or writing, for instance, that they cannot do well and don’t pursue
a major that requires those types of classes. Advisors, professors, and upper class
students can help the underclass students understand university support resources and
give specifics for each class. One advisor coaches students to realize that past grades
don’t matter for future success.

Hypothesis H4: External Formulas construct is expected to have a direct positive
influence on Choose Hospitality Business construct
The hypothesis regarding the direct influence of external formulas on choose
hospitality business was supported. External formulas has the third highest indicator of
strength, (=.255), of the 6 constructs. The tenets of self-authorship theory posit that
making your own meaning and self-reliance are not the norm for young college students.
Seeking direction from advisors and experts, and gathering facts and information are
very important to people in this phase; it is a slow process to move to the second and
third stages of self-authorship. This reliance on other referents is characteristic of
collectivism, important here because of the high percentage of Asian students in this
study. There is .69 for mean difference between the hospitality business students and
the non-hospitality business students.

60

Upper class students are a source of facts, expertise, and direction that not all
underclass students search out. Upper class students in hospitality business have
typically one or both required internships and had opportunities to participate in
hospitality student clubs and events. Whether involvement one-on-one or in interest
group settings, underclass students must be informed of and invited repeatedly to take
advantage of this relationship-building opportunity. While reluctance to participate and
form relationships can be common for young students, lack of information and invitation
is not acceptable, as was the case with many of the students in the 100-level classes
surveyed for this study.

Hypothesis H5: Crossroads construct is expected to have a direct positive influence on
Choose Hospitality Business construct
The hypothesis of the direct influence of the crossroads construct on the construct
of choose hospitality business was not supported. Crossroads has the lowest indicator of
strength, (=.091), of the 6 constructs. In fact, it is not significant at p<.05, so it does not
increase the predictability nor enhance understanding of the proposed model. The
crossroads construct attempts to identify young people who are trying to be more selfreliant, yet still need facts, advice, and direction. This is an unexpected finding since
this is a likely phase, according to the theory, for students to be moving into during the
college years. Possibly as a result of the collectivistic study composition, students in
this study could be distinctly ‘stuck’ in the external formulas stage rather than moving
along the self-authorship path.

61

Hypothesis H6: Early Self-Authorship construct is expected to have a direct positive
influence on Choose Hospitality Business construct
The hypothesis regarding the direct influence of the construct of early selfauthorship on the choose hospitality business construct was supported. Early selfauthorship has the fifth highest indicator of strength, (=.192), of the 6 constructs. With
the means of the two groups very nearly identical (23.58 for hospitality majors and
23.53 for non-hospitality majors), this construct points toward self-reliance in decisions
as well as weighing a person’s own values and interests into everyday judgments. Key
indicators for this construct are 1] matching information with personal views, interests,
and skills, and 2] making personally-fulfilling decisions, rather than relying on others to
decide for you. The hospitality business and non-hospitality business groups may not be
very different from each other and may not be very influential overall because,
according to the theory of self-authorship, not many college students usually find
themselves in this stage at their age and number of life-experiences.

Implications
The findings of this study have both theoretical and practical implications. This
section presents the theoretical contributions of this study to existing literature, and its
practical implications for hospitality business faculty, advisors, administrators, student
leaders, and the industry.
Theoretical Implications
The primary purpose of this study is to expand the theory of planned behavior
with the addition of the self-authorship theory constructs to check for increased
explanation in variance. The theory of planned behavior model has been used in a variety

62

of past studies (Mayhew, et al., 2009; Phillips, 2009; Yu, 2011; Wu, 2008), but none in
combination with the theory of self-authorship. The proposed combined model increases
the explained variance in Choose Hospitality Business by 19%. As shown in Table 20, R

2

increases from .47 to .66, when the three self-authorship constructs, external formulas,
crossroads, and early self-authorship, are added to the model of the theory of planned
behavior model. This TPB model expanded with SA constructs is the first study this
researcher is aware of where a behaviorist theory and a constructivist learning theory are
blended in such a way. Based on the results, this new model is this study’s contribution
to the body of literature through increased explanation and understanding of the social,
cognitive, and emotional developmental characteristics of undergraduate students
(typically 18-22 years of age) that influence them to choose hospitality business for their
academic major.

Practical Implications
This study provides insight into how freshmen and sophomore students weigh
perceived decision determinants relative to choosing their major. The model provides an
opportunity to evaluate which constructs hold the greatest level of prediction power and
how, collectively, those determinants could help inform stakeholders of hospitality
business programs. The results can have an impact on the academic process, student
educational experience, and industry perspectives.
Academic Process. From the results, the constructs of subjective norms and
perceived behavioral control are the first and second strongest predictors of choosing
hospitality business (=.526 and =.408, respectively). Understanding the determinants

63

that students who are interested in hospitality business rely on most frequently can be
used to design strategies to attract and capable students into the hospitality business field.
For example, the results of this study indicate that the construct of subjective norms is the
most predictive determinant of choosing hospitality business. Yet, many times, students
don’t know that they don’t have to be a junior or senior, or even a declared hospitality
business student, to use the hospitality business advising office. Administrators need to
get in front of all advisors and university admissions officers (they help students declare a
major and help transfer students) to continually educate the leaders about the hospitality
programs and what kinds of opportunities the program offers.
The construct of perceived behavioral control used four items: the difficulty of
choosing hospitality business based on the statistics and math background required for a
hospitality business major, based on the availability of job opportunities for hospitality
business graduates, based on performance in other classes because of the hospitality
business workload, and the personal ease of simply choosing a major. These things that
could be perceived to be out of the control of potential students, yet good information,
structure, and access to resources like study partners for classes or big hospitality
brothers/big hospitality sisters might allow some students to perceive they can take back
the control.
Educational Experience. Subjective norms is comprised of the combined
perceived importance of the opinions of parents, professors, classmates, most business
people the student knows, siblings, advisers, and friends. If potential students are
inclined to rely on these important referents, professors, advisers, administrators, and
student leaders can be better prepared and willing to be the knowledgeable expert to

64

students asking choice of major-type questions. Students don’t always take the initiative
to get involved in the exploration process. Encouraging students to understand the
importance of relationships with academic advisors, talking to professors, talking to
career development advisors and getting involved in student-led activities leads to
strengthening relationships and building peer-to-peer mentoring, a part of the key
referents group . This is a win-win for students as well as major programs. Hospitality
programs could also help themselves by connecting with parents and being visible to all
students, hospitality business major or not, to educate those potential unofficial
“recruiters.”
Beyond the opportunities for assistance with classroom success, an implication
for individual courses or curriculum based on how students choose hospitality business is
encouraging alumni and other business people in the community to connect with students
of all grade levels for education, mentoring, and job shadowing experiences, which could
lead to additional students choosing hospitality business through relationships with
successful business people, deeper understanding, and tangible opportunities.
Hospitality Industry. The findings of this study can be of interest to the industry
through understanding what the students perceive to be important in making their
decision of an academic major. While a career earning a good salary is important, so is
having an increasing salary and advancement potential. Also, the perception that the
field offers a number of job opportunities and the major offers a chance to become an
owner is important to students. These opportunities can be discussed during recruitment
and hiring to attract the students who are committed to companies or positions which
might offer lower starting salaries and could lead to better fitting employees in field. The

65

results indicated, too, that the approval of business people the subjects knew was
important and choosing hospitality business as a career would likely result in obtaining
that approval.

Limitations
Despite its theoretical and practical contributions to the field of hospitality
business education, several limitations of the present study need to be addressed. These
include: 1) generalizability of results due to the convenience sample, 2) TPB model
construct of intention was removed, and 3) freshmen and sophomore populations have a
greater chance of changing majors.

Generalizability of Results
Convenience sampling using only students in 100- and 200-level hospitality
business courses at Michigan State University limits the generalizability of the findings
of this study to a broader population of college students. The ideal sample to use would
be a random sample of the total population of all college students who have not been
formally admitted to a hospitality business program. Obtaining such a sample was not
possible due to the lack of access and the fact that admittance timing is not consistent
among all colleges, therefore a convenience sample was used. While this sampling limits
generalizability of the study, the focus of this study is primarily on relationships between
variables in testing the model. While this study focuses primarily on relationships
between variables and this type of research question is typically less vulnerable to
generalizability problems (Burnett and Dunne, 1986; Sears, 1986), the group used in this

66

study was not similar enough to comparison groups to be able to generalize beyond the
study respondents. The large Chinese student population in this study alters the
demographics profile away from being similar to the overall university student
composition, but this international mix could be the trend for the future.

Instructors at

other universities with hospitality programs have volunteered their students for future
phases of this study which will help broaden the sample demographics. Future studies
are needed that apply the same theoretical framework to other hospitality programs and
other majors. For example, it would be interesting to examine the relationships of TPB
and SA factors on the decision-making process of students at European and /or Asian
universities, private universities, and smaller institutions.

TPB Construct of Intention was Removed
Because of the context of the study, the original theory of planned behavior model
construct of intention was removed which might limit the inferences that can be drawn
about the validity of the model. However, Ajzen (1991) and Perugini and Bagozzi
(2001) noted that modifying the TPB model can contribute to increasing the prediction
power for individuals’ intention/behavior in that specific context. Broadening and
deepening of the theory can happen through such a process (Ajzen, 1991; Perugini and
Bagozzi, 2001). The model is explaining 66% of variance now, but perhaps putting the
intention back into the model would yield a still better explanation.

67

Freshmen and Sophomore Populations Changing Majors
A major can be changed at any point during a student’s academic career and this
study focuses on freshmen and sophomores, not students who are already deeply
involved in the program or graduated with a Hospitality Business degree. Underclassmen
and women have greater opportunity to change their major than junior and senior
students so their reported major in this study might not end up being accurate. The study
does, however, provide evidence concerning students who were attracted to Hospitality
Business in the first years of their academic career.

Future Research
Future studies need to address these identified issues and limitations to extend the
body of knowledge on the effects of TPB and SA constructs on choice of academic
major. Two interesting components of further study could enhance the research. First
would be to compare no-preference students (undecided) who identified hospitality
business to declared hospitality business students when the sample is larger. In the
current study, the numbers were too small to have any meaningful outcome. As the study
is replicated, those group sizes should increase. Second, create a longitudinal study over
the four years in college to explore if students are staying in hospitality business
(retention in the major), how the demographic profile changes semester by semester or
year by year, what proportion of hospitality business majors have parents with hospitality
experience, and how the amount of hospitality work experience as a young person
influences a choice of hospitality business as a major. Third, surveying students during
MSU’s academic orientation program would allow access to a cross-section of a wide

68

variety of academic interest as all incoming freshmen are required to participate in this
program each summer. This would also be a broad audience to begin informing about
hospitality business as a major. Fourth, exploring the data from a cultural collectivism
vs. independence stance would be interesting. The Asian dominance of this study may be
similar to other college campuses where the insight into the differences in influences in
choice of major could be helpful. Fifth, studying other hospitality students in other
colleges could be beneficial as the ages and stages of decision making can be different as
other schools might have different admittance procedures and time frames for making
academic major choices. Lastly, because of the timing of the two surveys, the question of
a pre-/post-test situation arises: would model perform differently if all students took at
end of the semester instead of one at the beginning of a semester instead of one at the
beginning and one at the end?

69

APPENDICES

70

APPENDIX A
Consent Form and Survey Tool
You are invited to participate in the research study, “Determinants that Influence
College Students in Considering Hospitality Business as their Major.” The
purposes of this study are to examine what determinants influence college student
decision-making related to your future major and any intent to choose Hospitality
Business as your major. This survey asks you for information about your
attitudes, beliefs, and behaviors about choosing your major and your intent of
majoring in The School of Hospitality Business. This survey also seeks
information about satisfaction with The School of Hospitality Business, past work
experience, and general demographic questions.
The survey will take approximately 20 minutes. This study is for research
purposes only. Your responses will not be associated with you in any way when
analyzed and will remain strictly confidential. Your privacy will be protected to
the maximum extent allowable by law. There are no anticipated risks associated
with participation beyond possible stress from thinking about these questions.
Data will be stored for a minimum of three years and only researchers listed
below will have access to the data.
As an incentive to take this survey, you will be entered in a drawing to receive
one of two $50 Meijer gift cards. Providing your email address on the last part of
the survey is completely voluntary, but is needed to enter you in the drawing for a
chance at one of the gift cards.
Participation in this study is voluntary, and you may choose not to participate at
all, you may decline to participate in certain sections or answer certain questions,
or you may discontinue your participation at any point without penalty or loss of
benefits. You also have the right to withdraw your consent to participate from this
study at any time without penalty.
If you have concerns or questions about this study, such as scientific issues, how
to do any part of it, or to report an injury, please contact the researcher Julie
Tkach at 517-353-9211, Fax 517-432-1170, or e-mail tkach@msu.edu, or the
Dissertation Director, Dr. Bonnie Knutson, at 517-353-9211, Fax 517-432-1170,
or email drbonnie@msu.edu.
If you have any questions or concerns about your role and rights as a research
participant, or would like to register a complaint about this study, you may
contact, anonymously if you wish, the Director of MSU’s Human Research
Protection Program at 517-355-2180, Fax 517-432-4503, or e-mail irb@msu.edu,
or regular mail at 207 Olds Hall, MSU, East Lansing, MI 48824.
You indicate your voluntary agreement to participate in this study by clicking the
link below:

71

DETERMINANTS THAT INFLUENCE COLLEGE STUDENTS IN
CONSIDERING HOSPITALITY BUSINESS
AS THEIR MAJOR: A NEW MODEL
Section 1: Diverse Viewpoints and Decision Making
The following questions are about your viewpoints toward diverse situations. Please
answer the following questions indicating how much you agree or disagree with each
of the following statements.
1. My primary role in making an education decision, such as choosing my major, is to ________
Disagree
Acquire as much information as
possible.
Seek direction from informed
experts.
Make a decision considering all
the available information and my
own views.
Consider my own views.

1

Slightly
Disagree
2

Slightly
Agree
3

Agree
4

1

2

3

4

1

2

3

4

1

2

3

4

2. If a teacher or adviser recommended a career in a field that I have never considered
before, _____________________
Disagree
I would listen, but I probably
wouldn’t seriously consider it
because I have already made a
decision.
I would try to understand their point
of view and figure out an option that
would best fit my needs and interests.
I would give it some thought because
they probably know better than I do
about what might suite me.
I would try to explain my point of
view.

Slightly
Disagree

Slightly
Agree

Agree

1

2

3

4

1

2

3

4

1

2

3

4

1

2

3

4

72

3. To make a good choice about a career, I think that _____________________
Disagree
facts are the strongest basis for a
good decision.

Slightly
Disagree

Slightly
Agree

Agree

1

2

3

4

it is largely a matter of personal
opinion.

1

2

3

4

experts are in the best position to
advise me about a good choice.

1

2

3

4

1

2

3

4

it is not a matter of facts or expert
judgment, but a match between my
values, interests, and skills and those
of the job.

4. In my opinion, the most important role of an effective career counselor or adviser is to_______
_____________________
Disagree
be an expert on a variety of career
options.

Slightly
Disagree

Slightly
Agree

Agree

1

2

3

4

provide guidance about a choice that
is appropriate for me.

1

2

3

4

help students to think through
multiple options.

1

2

3

4

1

2

3

4

direct students to information that
will help them to make a decision on
their own.

73

5. When I am in the process of making an important decision and people give me conflicting
advice, _____________________
Disagree
I get confused.
I don’t listen.
I try to listen and consider all of their
advice carefully.
I try to make a judgment if they are
someone I should listen to.

1

Slightly
Disagree
2

Slightly
Agree
3

Agree
4

1

2

3

4

1

2

3

4

1

2

3

4

6. When people have different interpretations of a book, I think that _____________________
Disagree
the author has done a poor job of
communicating the true meaning.
some books are just that way. It is
possible for all interpretations to be
correct.
only the expert(s) can really say
which interpretation is correct.
multiple interpretations are possible,
but some are closer to the truth than
others.

Slightly
Disagree

Slightly
Agree

Agree

1

2

3

4

1

2

3

4

1

2

3

4

1

2

3

4

74

7. Experts are divided on some scientific issues, such as the causes of global warming. In a
situation like this, _____________________
Disagree

Slightly
Disagree
2

Slightly
Agree
3

Agree

I rely on the experts to tell me.

1

I would have to look at the evidence
and come to my own conclusions.

1

2

3

4

1

2

3

4

1

2

3

4

I think it is best to accept the
uncertainty and try to understand the
principal arguments behind the
different points of view.
I try not to judge as long as different
scientists have different opinions on
these kinds of issues.

4

Section 2: Choosing a Major
The following questions are about your viewpoints toward choosing a major. Please
answer the following questions indicating the level of importance or unimportance with
each of the following statements.

8. Thinking of a major or career for you, in general:
Very
Unimportant
Earning a good salary initially is

Very
Important

Neutral

1

7

2

3

4

5

6

7

2

3

4

5

6

7

2

3

4

5

6

7

2

3

4

5

6

7

1

75

6

1

Choosing an academic major that is exciting
is

5

1

Choosing an academic major that is not
boring is

4

1

Entering a field that offers a chance to
become an owner is
Choosing a career that provides social status
is

3

1

Choosing a career with increasing salary and
advancement potential is

2

2

3

4

5

6

7

Choosing a major with easy courses is

1

6

7

2

3

4

5

6

7

2

3

4

5

6

7

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

Having a degree with transferable skills and
knowledge is
Being a part of a major that has social/job
perks is

5

1

Being a part of a department or school that is
prestigious is

4

1

Choosing a major with the least cost of
education is
Choosing a major that builds on previous or
current volunteer/employment experience is

3

1

Choosing a major that prepares me for a field
with a number of job opportunities is

2

2

3

4

5

6

7

9. What is the likelihood that majoring in Hospitality Business will result in this outcome?
Very
Unlikely
Earning a good salary initially

Very
Likely

Neutral

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

Choosing a major with the least cost of
education
Choosing a major that builds on previous or
current volunteer/employment experience

1

2

3

4

5

6

7

1

2

3

4

5

6

7

Being a part of a department or school that is
prestigious

1

2

3

4

5

6

7

Choosing a career with increasing salary and
advancement potential
Entering a field that offers a chance to
become an owner
Choosing a career that provides social status
Choosing an academic major that is not
boring
Choosing an academic major that is exciting
Choosing a major with easy courses
Choosing a major that prepares me for a field
with a number of job opportunities

76

1

2

3

4

5

6

7

1

Having a degree with transferable skills and
knowledge
Being a part of a major that has social/job
perks

2

3

4

5

6

7

10. What is the likelihood that majoring in a major OTHER THAN Hospitality Business will
result in this outcome?
Very
Unlikely
Earning a good salary initially

Very
Likely

Neutral

1

5

6

7

2

3

4

5

6

7

2

3

4

5

6

7

2

3

4

5

6

7

2

3

4

5

6

7

2

3

4

5

6

7

2

3

4

5

6

7

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

77

4

1

Having a degree with transferable skills and
knowledge
Being a part of a major that has social/job
perks

3

1

Being a part of a department or school that is
prestigious

2

1

Choosing a major with the least cost of
education
Choosing a major that builds on previous or
current volunteer/employment experience

7

1

Choosing a major that prepares me for a field
with a number of job opportunities

6

1

Choosing an academic major that is exciting
Choosing a major with easy courses

5

1

Choosing an academic major that is not
boring

4

1

Entering a field that offers a chance to
become an owner
Choosing a career that provides social status

3

1

Choosing a career with increasing salary and
advancement potential

2

2

3

4

5

6

7

11. Please answer the following questions indicating your level of caring:
Very
Much

Not
at all

Some

How much do you care whether your parents
approve or disapprove of your choice of an
academic major?

1

2

3

4

5

6

7

How much do you care whether your
professors approve or disapprove of your
choice of an academic major?

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

How much do you care whether your
classmates approve or disapprove of your
choice of an academic major?
How much do you care whether most
business people you know approve or
disapprove of your choice of an academic
major?
How much do you care whether your
siblings approve or disapprove of your
choice of an academic major?
How much do you care whether your
advisors approve or disapprove of your
choice of an academic major?
How much do you care whether your friends
approve or disapprove of your choice of an
academic major?

12. The following people think I should major in a field OTHER THAN Hospitality Business:
Very
Unlikely
My parents

Very
Likely

Neither

1

2

3

4

5

6

7

My professors

1

2

3

4

5

6

7

My classmates
Most business people I know

1

2

3

4

5

6

7

1

2

3

4

5

6

7

My siblings

1

2

3

4

5

6

7

My advisors
My friends

1

2

3

4

5

6

7

1

2

3

4

5

6

7

78

13. The following people think I should major in Hospitality Business:
Very
Unlikely
My parents

Very
Likely

Neither

1

2

3

4

5

6

7

My professors

1

2

3

4

5

6

7

My classmates
Most business people I know

1

2

3

4

5

6

7

1

2

3

4

5

6

7

My siblings

1

2

3

4

5

6

7

My advisors
My friends

1

2

3

4

5

6

7

1

2

3

4

5

6

7

14. Please answer the following questions indicating your level of agreement:
Strongly
Disagree
The statistics and math background required
in Hospitality Business made or would make
it difficult for me to choose Hospitality
Business as my major.

Strongly
Agree

Neither

1

5

6

7

2

3

4

5

6

7

2

3

4

5

6

7

1

79

4

1

It was easy for me to choose a major other
than Hospitality Business.
My performance in other classes has been or
would be hurt because of the workload of
Hospitality Business courses.

3

1

The availability of job opportunities for
Hospitality Business graduates made or
would make it difficult for me to choose
Hospitality Business as my major.

2

2

3

4

5

6

7

15. Please answer the following questions indicating your level of agreement:
Strongly
Disagree
The statistics and math background required
in a major other than Hospitality Business
made or would make it difficult for me to
choose a major other than Hospitality
Business.

Strongly
Agree

Neither

1

4

5

6

7

2

3

4

5

6

7

1

2

3

4

5

6

7

1

It was easy for me to choose Hospitality
Business.
My performance in Hospitality Business
courses has been or would be hurt because of
the workload in courses of other majors.

3

1

The availability of job opportunities for
Hospitality Business graduates made or
would make it difficult for me to choose a
major other than Hospitality Business.

2

2

3

4

5

6

7

Section 3: Descriptive Information
This information will be held in the strictest confidence and will only be used for statistical
purposes and only in aggregate form.

16. Please select the gender you identify with. Please select a response.
 Male
 Female
 Transgender
17. What is your age: Please type a number.

____________

18. Of which country are you a citizen? Please type it. 

19. Please select the ethnic background you identify with? Please select all that apply.
 African American/ Black
 European American/ Middle East/White
 American Indian
 Hispanic/ Latino/ Latina
 Asian or Pacific Islander
 Other (please specify) ________________
20. Is English your native language? Please select a response.

 Yes

 No

21. What is your major today? Please type it. 
22. If you are no-preference, what academic major would you pick if asked to choose one today?
Please type it. 
23. Please select your class level. Please select a response.

80

 Freshman

 Sophomore

 Junior

 Senior

24. Please select your overall MSU GPA range: Please select one.
 3.80 – 4.0
 3.00 – 3.24
 2.25 – 2.49
 3.50 – 3.79
 2.75 – 2.99
 2.00 – 2.24
 3.25 – 3.49
 2.50 – 2.74
 1.50 – 1.99

 1.00 – 1.49
 Under 1.00

25. Which income category best describes your family’s total annual income before taxes in
2011? Please select one.
 Less than $25,000
 $50,000- $74,999
 $150,000-$199,999
 $25,000- $34,999
 $75,000 - $99,999
 $200,000 or more
 $35,000- $49,999
 $100,000-$149,999

Thank you for completing this survey.
To enter a chance to win one of the Meijer gift cards, please fill out your contact information on
the drawing ticket.

81

APPENDIX B

Example Calculation of Differential Perception- summary of procedure

1. Step 1. Outcome assessment = having a degree with transferable skills
and knowledge is (important) (unimportant) – (scale 1-7).
2. Step 2. Likelihood assessment of target and non-target behaviors (scale
1-7):
a. Choosing to major in hospitality business will result in having
a degree with transferable skills and knowledge (likely)
(unlikely) = likelihood of outcome resulting from target
behavior.
b. Choosing to a major other than hospitality business will result
in having a degree with transferable skills and knowledge
(likely) (unlikely) = likelihood of outcome resulting from nontarget behavior.
3. Step 3. Difference score = (Step 2a – Step 2b) (scale 0-minus 6).
4. Step 4. Differential personal perception = (Step 1) x (Step 3) (scale 0minus 42) (per personal factor).
5. Step 5. Differential personal perception = Step 4 summed across the
13 personal attitude factors (see Table 2: Description of factors and
observed variables in the TPB constructs of the proposed model).
Similarly, important referents’ differential perceptions of choosing a
major in hospitality business are summed across the seven important
referent factors for each sample participant to represent the differential
perception of important people construct (variable) in the model and
the differential control perceptions are summed across the four control
factors for each sample participant to represent the differential
perceived control construct (variable) in the model.

Taken from Allen, 2004

82

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83

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?accountid=12598

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