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Examining Marketing Officers'Demographic Factors' Influence on MIHEScores at California Community CollegesZachary Martin Hall aa Cuesta College , Communication Studies , San Luis Obispo,California, USAPublished online: 12 Dec 2011.

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Examining Marketing Officers’ DemographicFactors’ Influence on MIHE Scoresat California Community Colleges

Zachary Martin Hall

Cuesta College, Communication Studies, San Luis Obispo, California, USA

Research indicates that one way to investigate a college’s dedication to marketing is to examine the

role, influence, and support the marketing officer receives on their campus. Based on the literature’s

premise that marketing officers are a measure of commitment, this study explored the relationship

between Marketing Index of Higher Education (MIHE) scores and marketing officers’ demographic

factors of gender, pay, education, staff support, and education. This study found a marketing offi-

cer’s demographic factors had little to no influence on a California community college’s score on

the MIHE. Thirty one California community college marketing officers participated in the on-line

survey. T tests and Pearson’s correlations were utilized to measure the relationship between MIHE

score and the officer’s demographic factors. One of the major implications of this study is that a mar-

keting officer’s gender, pay, education, staff support, and education do not alone predict whether a

community college is a marketing organization. However, as the extant literature suggests, a better

indicator of a college’s ability to market itself may be the president’s commitment to marketing’s

philosophy and practices. Therefore, when college leaders want to improve their college’s reputation

they may want to first determine their own commitment to marketing before they hire personnel to

staff their marketing offices and implement their campaigns.

California’s 109 community colleges annually spend millions of tax dollars on their marketing

staffs and promotional campaigns (Hall, 2007). Yet, despite this large investment, they are still

struggling in their competition for students and resources (Gould, 2004) against other tax sup-

ported institutions such as the California State University (CSU) system, the University of

California (UC) system, the K–12 system, and numerous private colleges and universities.

Numerous studies have addressed the presence and desirability of marketing in American

higher education for attracting resources and students (Kotler, 1975; LaFleur, 1990; Scigliano,

1983). However, no studies have been found in the extant literature that investigated the relation-

ship between a marketing officer’s educational level, amount of compensation, years of appro-

priate experience, staffing support or gender and their college’s score on the Marketing Index of

Higher Education (MIHE) (Scigliano, 1983).

Address correspondence to Zachary Martin Hall, Cuesta College, Communication Studies, Highway 1, San Luis

Obispo, CA 93403. E-mail: zachary_hall@cuesta.edu

Community College Journal of Research and Practice, 36: 131–145, 2012

Copyright # Taylor & Francis Group, LLC

ISSN: 1066-8926 print=1521-0413 online

DOI: 10.1080/10668920802708512

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This article examines the influence of marketing officers’ demographic factors on the MIHE

scores at California community colleges. It provides background information about California’s

community colleges; the study’s conceptual underpinnings; and a discussion of the study’s

problem, research questions, methods, results, implications, and limitations.

HISTORY

The seeds of California’s community college marketing and ‘‘image’’ challenges were planted

as a result of their conception and history (Denton, 1970, p. 22; Zeiss, 1986, p. 1). California

started its first community college nearly 100 years ago as a high school extension program

in Fresno (Palinchak, 1973; Witt, Wattenbarger, Gollattscheck, & Suppiger, 1994) to offer lower

division college course work and vocational ‘‘technical work’’ (Witt et al., 1994, pp. 36–39). At

the same time, administrators at the University of California at Berkeley agreed to accept the

transfer students on their campus as juniors (Witt et al., 1994). In 1909, the state provided high

schools the resources to create ‘‘junior colleges’’ (Witt et al., 1994, p. 37). Almost 70 years later,

in the early 1970s, the state system officially adopted the name, ‘‘Community College’’ to

reflect its local community education focus (Palinchak, 1973; Witt et al., 1994).

The California state legislature created the first comprehensive master plan for higher edu-

cation in the United States in 1960 in conjunction with the University of California (UC) and

the California State University (CSU) systems (Kerr, 1994). The master plan established a role

and position for each system within the state’s higher education hierarchy. The community col-

leges would provide vocational and lower division education and award associate’s of arts

degrees while the CSUs would offer lower and upper division courses and award bachelor’s

and master’s degrees. The UCs were to focus on research and provide academic course work

for bachelor’s, master’s, and doctorate degrees (Kerr, 1994).

Community colleges receive financial resources based on daily attendance. The Full Time

Equivalent students (FTEs) student contact hours accounting system, based on the state master

plan’s mandate, means that community colleges are dependent on steady enrollment for steady

funding (California Community College Chancellor’s Office [CCCO], 1999). The funding sys-

tem inextricably ties enrollment and funding together and, therefore, community colleges must

constantly attract more students and greater community support to maintain resource levels and

relevancy.

Marketing and Image Problems

Community colleges are struggling to overcome prestige, reputation, and image problems to

compete for students and resources (Consand, 1968, p. 136). Watts and Barista (2005) write,

‘‘Warranted or not, community colleges have gotten a reputation for being ‘junior’ institutions

that provide a second-rate education compared to four-year schools’’ (p. 26). A review of the

extant literature suggests that community colleges face specific image and marketing problems

including elitism (Palinchak, 1973; Witt et al., 1994); a lack of scarcity (Lynn, 1992); myths,

misconceptions (LeClaire, 2006); insufficient information (Hayward, Jones, McGuinness, &

Timar, 2004); and fragmentation (Ryans & Shanklin, 1986).

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The extant literature also suggests that it is these challenges that have greatly contributed to

the community college’s enrollment and funding deficits. This literature demonstrates that many

American colleges and universities have faced and overcome these and other challenges. This is

because they have leaders who recognize and embrace the potential offered by marketing philo-

sophy and are committed to making the needs of their students and community a top priority on

campus (Hanson, 2003; Kotler & Goldgehn, 1981; LaFleur, 1990).

CONCEPTUAL UNDERPINNINGS

Marketing in Higher Education

Business and public policy literature indicates that marketing is a concern for universities and

colleges, and these institutions are engaged in marketing whether their leaders intend to be or

not (Berry & Allen, 1977; Kotler, 1979). For example, higher education institutions must recruit

prospective students and donors (customers); create compelling courses; determine appropriate

tuition and fees; schedule the products (classes) at appropriate times and locations; and promote

the products and the institution’s benefits through catalogs, publicity campaigns, and web sites

(Kotler, Ferrell, & Lamb, 1987). The literature also shows that marketing can help higher edu-

cation leaders respond to image, enrollment, and funding challenges (Gould, 2004; Kirp, 2003;

Kotler & Fox, 1985; LaFleur, 1990; Watts & Barista, 2005).

Kotler (1975) writes that marketing is the studying, planning, execution, and operation of

‘‘carefully formulated programs designed to bring about voluntary exchanges of values with tar-

get markets for the purpose of achieving organizational objectives’’ (p. 5). The emphasis of a

marketing-based organization is a customer-centric orientation; the constituent’s needs and

desires must be understood to plan pricing, production, distribution, and communication to

efficiently service the organization’s markets (Kotler, 1975).

Since their inception, California’s community colleges have had an ‘‘image’’ problem

(Curtis, 2006; Gould, 2004, p. 3; Zeiss, 1986, p. 1). Originally called junior colleges, they were

designed to be a local and affordable alternative to four-year universities for students wishing to

enter the state’s higher education system or learn vocational skills (Palinchak, 1973; Witt et al.,

1994). However, research has repeatedly demonstrated that California’s community colleges

have been relegated to second-class status compared to their four-year counterparts, the Univer-

sity of California (UC) and the California State University (CSU) (Palinchak, 1973; Witt et al.,

1994; Zeiss, 1986). The 109 California community colleges continue to struggle against the UC

and CSU for state funding and students due to the common belief that community colleges pro-

vide low quality education for students not academically qualified to enter either the CSU or UC

systems (Gould, 2004; LeClaire, 2006; Nussbaum, 2003).

Extant literature has provided evidence of the importance of marketing in the area of high

education and the influence of the college president in empowering an organization to success-

fully market itself (Hall, 2007).

LaFleur (1990) and others have studied the link between college and university presidents

and higher education marketing in the past (Kotler, 1975; Scigliano, 1983); however, a review

of the extant literature has not uncovered any studies that specifically investigated California’s

community colleges.

DEMOGRAPHIC FACTORS’ INFLUENCE ON MIHE SCORES 133

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This study addressed six research questions:

1. How do California community colleges rank in terms of the MIHE?

2. Is there a correlation between gender and MIHE score?

3. Is there a correlation between education MIHE score?

4. Is there a correlation between experience and MIHE score?

5. Is there a correlation between and MIHE score?

6. Is there a correlation between staff size and MIHE score?

METHOD

Marketing Index for Higher Education

In 1990, LaFleur conducted a nationwide study investigating the relationship between a

four-year university’s score on the MIHE and the college’s commitment to higher education

marketing. His study showed most universities scored poorly on the MIHE and, consequently,

had not fully committed to marketing. LaFleur used the description of the ultimate marketing

officer as a lens to describe the colleges’ level of commitment. LaFleur recommended in his

study that future research into the relationship between college=university presidents and orga-

nizational commitment to marketing should be conducted at the community college level.

Scigliano (1983) designed the MIHE based on Kotler’s (1977) business marketing audit to

study the marketing activities of universities and colleges. According to LaFleur (1990), more

than 600 universities and colleges have been studied using the MIHE since the 1980s. LaFleur

noted further that there have been no reported weaknesses in the scale’s methodology that would

undermine the results. The MIHE is a 15-item questionnaire that measures a college’s environ-

mental awareness, marketing organization, and the performance of the marketing office

(Scigliano, 1983). Each question is worth two points for a total of 30. The higher the score,

the more successfully the college has integrated marketing philosophy in to its organization.

For this study, a college that scored 20 or more points was considered ‘‘high performing’’ while

19 or less points was considered ‘‘low performing.’’ The MIHE survey instrument is located in

the Appendix.

Procedures

On behalf of the author, the Community College Public Relations Officers’ Organization

(CCPro) president invited her organization’s members to participate in this study. She e-mailed

a letter to her members explaining the study and inviting them to participate. The letter included

a hyper-link to an online version of the MIHE that utilized Dillman’s (2000, pp. 150–153, pp.

352–412) five step total design method for mailing and web-based surveys as a framework to

design the introductory letter and subsequent follow-up e-mails. These letters informed the

respondents of the study’s goals and suggested that their participation was integral to its success.

The letters asked for their participation and assistance in contacting their presidents in the event

that their college was chosen for further study. The letter offered a copy of an executive sum-

mary of the study’s conclusions for participating in the study. All participants were instructed

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that their participation was voluntary and that all information would be kept confidential and

would only be viewed by the researcher.

Descriptive Statistics

Descriptive statistics were constructed on the total number of respondents in the sample using

the Statistical Package for Social Sciences (SPSS, 2002), version 11.0. Descriptive statistics

are provided in the results section of this study to demonstrate means and correlations for each

item of the marketing officers’ demographic factors of gender, experience level, salary level,

staff level, and education level, MIHE surveys and Q-sorts. Close examination of these descrip-

tive statistics also provided the researcher a method for inspecting the data for possible input

errors, missing observations, and normality potential inconsistencies.

Demographic Characteristics

The total number of respondents consisted of two groups: California community college presi-

dents and California community college chief marketing officers. The 109 (N¼ 109) community

college marketing officers were e-mailed an invitation to participate in the online MIHE survey.

Approximately 28% (n¼ 31) of the invited marketing officers consented to participate in the

study. There are many possible reasons why more than two-thirds of the state’s marketing offi-

cers did not respond such as being too busy or not wanting to ask their presidents to take part in

the follow up interview. However, participating colleges represented all parts of the state includ-

ing northern and southern California coastal community colleges as well as those located in the

central valley. Presidents and chief marketing officers from the five high scoring colleges were

selected for further study.

Data Analysis

Coding

The officers’ education, experience, salary, and staff size factors levels were coded to calculate

statistical differences in educational level between the high and low performing colleges and

MIHE score. The demographic factors and their corresponding codes are represented in the

Tables 1 through 4. Education level is represented in Table 1, experience in Table 2, salary level

in Table 3, and staff size in Table 4.

TABLE 1

Education Level Coding

Education level (degree earned) Code

Doctorate 3

Master’s 2

Bachelor’s 1

DEMOGRAPHIC FACTORS’ INFLUENCE ON MIHE SCORES 135

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EXAMINING HIGH PERFORMING CALIFORNIA COMMUNITY COLLEGES

The tabulated MIHE score revealed an identifiable stratification between high and low perform-

ing colleges. High scoring, or high performing colleges, scored 20 or more points while low per-

forming colleges scored 19 or less points. Eleven of the 31 colleges in the study were considered

high performing. Table 5 shows the mean MIHE scores collected from the community colleges

participating in the online survey.

A t test was used to explore any statistical difference in the MIHE mean scores between the

high performing group in total and the colleges selected for participation, ‘‘Participating Col-

leges.’’ A two-tailed P value of .88, with a .09 difference in means indicates that the difference

in mean scores between the high- performing colleges and those studied was not statistically sig-

nificant. The absence of a statistical difference between the total number of high performing col-

leges and those participating in this investigation indicates the members of the sample pool were

statistically similar and, therefore, a valuable measure of the entire high performing population.

TABLE 2

Experience Level Coding

Experience level (years in current position) Code

6þ 4

5–6 3

2–4 2

2 or less 1

TABLE 3

Salary Level Coding

Salary level (thousands of dollars per year) Code

80þ 5

80–60 4

60–50 3

40–30 2

30 or less 1

TABLE 4

Staff Level Coding

Staff level (number of people working with the

marketing officer as part of their staff) Code

6þ 5

6–4 4

4–2 3

2–1 2

0 (no support staff) 1

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When the mean scores for high performing colleges were compared to low performing col-

leges, a P value of less than .0001 was calculated, with a difference in means of 7.56, a differ-

ence that was statistically significant. The significant statistical difference between high and low

performing colleges demonstrates that there were real differences in the MIHE scores between

the two clusters of colleges.

Demographic Data

Five demographic characteristics were tracked for each of the 31 marketing officers that parti-

cipated in the MIHE online survey including gender, education, experience, salary, and support

staff. The demographic data was aggregated and averaged; then t tests, where appropriate, wereused to determine if there was any statistical difference between low and high performing col-

leges’ MIHE scores and those demographic characteristics. Pearson correlation tests were also

utilized to further determine if there was any statistically significant relationship between the

marketing officers’ demographic factors and MIHE score. The following are tables of the demo-

graphic data and discussion of the connections between that data and MIHE score. It must be

noted that because there were only a total of 31 respondents, the conclusions that can be drawn

from this investigation are preliminary and directional at best. Further research must be conduc-

ted to answer this study’s research questions.

Gender

Table 6 shows the gender of the marketing officers who participated in this study.

Table 6 shows that nearly 75% of the marketing officers that participated in the online MIHE

were women. Three out of every four marketing officers in the low performing group were also

women. In the high performing group, women were in still in majority but were approximately

TABLE 5

Mean MIHE Scores from Participating Community Colleges

Total (n) Mean Low High SD

All colleges 31 16.03 6 23 4.59

High performing 11 20.91 20 23 1.04

Low performing 20 13.35 6 19 3.36

TABLE 6

Gender of Participating Marketing Officers by MIHE Performance

Women Men

All colleges 23 8

Low performing 16 4

High performing 7 4

DEMOGRAPHIC FACTORS’ INFLUENCE ON MIHE SCORES 137

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66% of the marketing officers. In the studied group, 60% of the marketing officers were women.

By looking at this data, gender seems to provide no indication of whether a college would be

high or low performing.

Education

Table 7 below presents the education level of the marketing officers that participated in the

MIHE.

A t test was used to determine if there was a statistical difference between a marketing offi-

cers’ education level and their college’s MIHE score. The two-tailed P value between the high

performing group and low performing group is .33 with a 95% confidence interval. There is only

a �.25 difference between the high and low performers mean scores from: �.77 to .27. By con-

ventional criteria, this difference is considered to not be statistically significant, and therefore

education level does not seem to be a predictor for a high MIHE score. The Pearson correlation

test reveals �.03 relationship between education level and MIHE score. The �.03 score indi-

cates that there is not a correlation between education level and MIHE score.

Experience

Table 8 represents the experience level of the marketing officers that participated in the MIHE.

A t test was used to determine if there was a statistical difference between marketing officers’

experience level and their college’s MIHE score. The two-tailed P value for high performing and

low performing in terms of experience is .68 with a 95% confidence interval. The difference in

means of high minus low equals .16 from �.64 to .96. By conventional criteria, this difference is

considered to not be statistically significant; therefore, experience level does not seem to be a

predictor for a high MIHE score.

TABLE 7

Education Level of Participating Marketing Officers by MIHE Performance

BA MA PhD

All colleges 15 (48%) 18 (60%) 3 (9.7%)

Low performing 8 (38%) 9 (43%) 3 (14%)

High performing 5 (45%) 6 (55%) 0

TABLE 8

Experience Level of Participating Marketing Officers by MIHE Performance

2 or < 2 to 4 5 to 6 6>

All colleges 3 (9.7%) 3 (9.7%) 3 (9.7%) 22 (71%)

Low performing 3 (15%) 1 (5%) 1 (5%) 15 (75%)

High performing 0 2 (18%) 2 (18%) 7 (64%)

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The Pearson correlation test reveals .08 relationship between experience level and MIHE

score. The .08 score indicates that there is little-to-no relationship between experience level

and MIHE score.

Salary

The marketing officers’ salary level data by thousands of dollars earned annually is shown in

Table 9.

A t test was used to determine if there was a statistical difference between a marketing offi-

cers’ salary level and their college’s MIHE score. The two-tailed P value equals .88. The differ-

ence in means of high minus low performing equals �.05 from �.73 to .63 with a 95%confidence interval. By conventional criteria, this difference is considered to not be statistically

significant; therefore, salary level does not seem to be a predictor for a high MIHE score.

The Pearson correlation test reveals .07 relationship between salary level and MIHE score.

The .07 score indicates that there is little-to-no relationship between salary level and MIHE

score.

Staff

The staff level data are shown in Table 10.

A t test was used to determine if there was a statistical difference between a staff level and the

college’s MIHE score. The staff level P value is .27 with a 95% confidence interval of this dif-

ference. The difference in means of high versus low performing is .60 from �.49 to 1.69. By

conventional criteria, this difference is considered to not be statistically significant; therefore,

staff level does not seem to be a predictor for a high MIHE score.

The Pearson correlation test reveals .32 relationship between staff level and MIHE score. The

.32 score indicates that there may be a relationship between staff level and MIHE score. One

TABLE 10

Staff Level of Participating Colleges by MIHE Performance

1 2 3 4–6 6>

All colleges 6 (19%) 12 (39%) 4 (13%) 4 (13%) 5 (16%)

Low performing 5 (25%) 8 (40%) 2 (10%) 2 (10%) 3 (15%)

High performing 1 (9%) 4 (36%) 2 (18%) 2 (18%) 2 (18%)

TABLE 9

Salary Level of Participating Marketing Officers by MIHE Performance

20–30 30–40 50–60 60–80 80þ

All colleges 1 (3%) 0 1 (3%) 8 (26%) 21 (68%)

Low performing 0 0 1 (5%) 7 (35%) 12 (60%)

High performing 1 (9%) 0 0 1 (9%) 9 (82%)

DEMOGRAPHIC FACTORS’ INFLUENCE ON MIHE SCORES 139

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explanation for the correlation between staff level and MIHE score might be that a robust sup-

port staff for the marketing officer is an acknowledgement by administrators that marketing is

important and is a worthwhile investment.

SUMMARY OF STUDY

Research indicates that one way to investigate a college’s dedication to marketing is to examine

the role, influence, and support the marketing officer receives on their campus. Based on the

literature’s premise that marketing officers are a measure of commitment, this study explored

the relationship between Marketing Index of Higher Education (MIHE) scores and marketing

officers’ demographic factors.

A statistically significant relationship between gender, pay, experience, staff size, and edu-

cation and MIHE score was not found using t tests and Pearson’s correlation tests. As this study

indicates, many marketing officers within the California community college system are highly

educated, well paid, have many years of experience, and have staff to support their missions.

However none of these demographic factors seemed to strongly predict high MIHE scores.

Colleges can continue to hire well educated marketing officers and pay them handsomely.

But if, as the research indicates, they fail to give those officers authority within the administrat-

ive hierarchy, their investment will not help transform the colleges into more student and com-

munity focused organizations. As the literature indicates (Ryans & Shanklin, 1986) college

leaders’ commit to marketing not by a hiring highly paid and experienced marketing officers;

they commit by doing all these things and then giving the officer the authority, position, and

resources to enact researched based, student and community centered change. Highly educated,

well paid, and supported marketing officers are necessary but not sufficient to guarantee an edu-

cational organization will remain sensitive and responsive to its fiscal, political, and competitive

environment.

Implications

California’s community colleges are struggling. They are competing for students and resources

in the face of ‘‘prestige,’’ reputation, and image problems (Consand, 1968, p. 136). As the litera-

ture indicates, American colleges and universities can succeed in the educational market place by

having leaders and organizations that are committed to marketing (Hanson, 2003; Kotler &

Goldgehn, 1981; LaFleur, 1990; Ryans & Shanklin, 1986; Scigliano, 1983).

One of the major implications of this study is that a marketing officer’s gender, pay,

education, staff support, and education do not alone predict whether a community college is a

marketing organization. However, as the extant literature suggests (Ryans & Shanklin, 1986),

a better indicator of a college’s ability to market itself may be the president’s commitment to

marketing’s philosophy and practices. Therefore, when college leaders want to improve their

college’s reputation, they may want to first determine their own commitment to marketing before

they hire personnel to staff their marketing offices and implement their campaigns.

If California’s community college leaders want to increase the system’s and their college’s

reputation, prestige, and public investment, they must embrace marketing philosophy and prac-

tice. Hall’s (2007) exploratory study noted that the presidents participating in his study had no

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formal marketing training in their career path to their presidency. One remedy for the lack of

commitment to marketing may be intensive workshops and training programs for college leaders

to help them understand marketing’s potential to help them overcome the challenges facing their

colleges.

Limitations of the Study

The highest score on the MIHE was 23; a study that included colleges that scored higher could

generate more specific conclusions. A greater sample rate may also enhance the study’s results

since only 31 of the 109 campuses in the California community college system agreed to par-

ticipate in the study. Moreover, there were less than 30 respondents in the high and low perform-

ing groups. Therefore, the conclusions that can be drawn from the data can only be preliminary

and not statistically significant. Though, the patterns in the data that are present should be con-

sidered directional in nature and as a call for further study. The conclusions from this study are

intended for scholars and educators in higher education leadership and California community

college administrators and their trustees.

REFERENCES

Berry, L. L., & Allen, B. H. (1977). Marketing’s crucial role for institutions of higher education. Atlanta Economic

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from http://www.cccco.edu/divisions/tris/rp/rp_doc/3part2.doc

Consand, J. (1968). The community college in 1980. In A. C. Eurich (Ed.), Campus 1980 (pp. 134–138). New York, NY:

Delacorte Press.

Curtis, E. (2006, April). Using marketing strategies to address low enrollment. Association of California Community

College Administrators Reports. p. 1.Denton, C. (1970). Community colleges pioneer the open door policy. Pennsylvania Education, 2, 18–23.

Dillman, D. A. (2000). Mail and internet surveys: The tailored design method. 2nd ed., New York, NY: John Wiley &

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Gould, D. (2004). Bridges to opportunity: Initiative overview. Retrieved from http://fordfound.adhostclient.com/Publica-

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Hall, Z. M. (2007). An exploratory investigation of the influence of college president perceptions on organizational com-

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sertation). University of California, Santa Barbara, CA.

Hanson, M. E. (2003). Educational administration and organizational behavior. 5th ed., Boston, MA: Allyn & Bacon.

Hayward, G. C., Jones, D. P., Mc Guinness, A. C., & , Timar, A. (2004). Ensuring access with quality to California’s

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Kerr, C. (1994). Higher Education cannot escape history: Issues for the twenty-first century. Albany, NY: State Univer-

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APPENDIX

Marketing of Index of Higher Education Adapted for California Community Colleges(Scigliano, 1983)

Demographic questions

1. What is your name, phone number, and which community college do you work for?

2. My official title is:

3. Please specify your level of education:

Associate’s degree

Bachelor’s degree

Master’s degree

Doctorate

4. Please specify your years of experience in the higher education marketing field. If you’ve

been in your current institution less than 2 years please mark other in the box below.

0–1 years

2–4 years

5–6 years

6 or more years

Other (please specify)

5. Gender

Female

Male

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6. Please designate your salary range

20–30k per year

30–40k per year

40–50k per year

50–60k per year

60–80k per year

80–100k per year

7. Please indicate the size of your staff excluding yourself

0

1–2 people

3–4 people

5–6 people

7þ people

8. How many colleges are in your district?

1

2–3

4–5

6þ

9. Do you work for a

campus wide marketing organization?

system wide marketing organization?

10. Are you the primary decision maker for the marketing expenditures, functions, and opera-

tions for your college?

Yes

No

Other

11. Are you involved in new instructional program and student service development?

Yes

No

Somewhat

Items 1 through 5 can be used to audit environmental awareness.

1. My administration recognizes the importance of designing the college to serve the needs and wants

of chosen markets (students and community members)?

1. The administration primarily thinks in terms of promoting current and new programs to whoever

will buy them.

2. Administration thinks in terms of serving a wide range of markets and needs with equal effec-

tiveness.

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3. Administration thinks in terms of serving the needs and wants of well-defined markets for their

long-run growth and income potential for the institution.

2. My administration develop different offerings and marketing plans for different segments of the

markets?

0. No.

1. Somewhat.

2. To a good extent

3. My administration takes a whole marketing systems view (suppliers, delivery systems, competitors,

customers, environment) in planning its programs?

1. No. Administration concentrates on enrolling and servicing its immediate students.

2. Somewhat. Administration takes a long view of its delivery systems although the bulk of its

efforts goes to enrolling the immediate students.

3. Yes. Administration takes a whole marketing systems view recognizing the threats and oppor-

tunities for the institution by changes in any part of the system.

4. When were the last marketing research studies of students, tuition, delivery systems, and competition

conducted?

1. Several years ago. (5 years or more)

2. A few years ago. (1–4 years)

3. Recently. (within the past year)

5. How well does your administration know the enrollment potential and profitability of different

market segments, students, territories, programs, and delivery systems?

1. Not at all.

2. Somewhat.

3. Very well.

Items 6 through 10 can be used to audit the college’s organization

6. Is there high-level marketing integration and control of the major marketing functions?

1. No. Recruiting and other marketing functions are not integrated at the top and there is some

unproductive conflict.

2. Somewhat. There is formal integration and control of the major marketing functions but less than

satisfactory coordination cooperation.

3. Yes. The major marketing functions are effectively integrated.

7. How well organized is the new program development process?

1. The system is ill-defined and poorly handled.

2. The system is formally exists but lacks sophistication.

3. The system is well-structured and professionally staffed.

8. What effort is expended to measure the cost-effectiveness of different marketing expenditures?

1. Little to no effort.

2. Some effort.

3. Substantial effort.

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9. What is the extent of formal marketing planning?

1. Administration does little to no formal marketing planning.

2. Administration develops an annual marketing plan.

3. Administration develops a detailed annual plan and a careful long-range plan that is updated

annually.

10. What is the quality of the current marketing strategy?

1. The current strategy is not clear.

2. The current strategy is clear and represents a continuation of traditional strategy.

3. The current strategy is clear, innovative, data-based, and well-reasoned.

Items 11 through 15 can be used to audit the performance of the marketing office.

11. Do those individuals for the marketing function work well with other college personnel in research,

program development, purchasing, and finance?

1. No. There are complaints that marketing is unreasonable in the demands and costs it places on

other departments.

2. Somewhat. The relations are amicable although each department pretty much acts to serve it own

interests.

3. Yes. The departments cooperate effectively and resolve issues in the best interest of the

institution as a whole.

12. What is the extent of contingency thinking and planning?

1. My administration does little or no contingency thinking.

2. My administration does some contingency thinking although little sound contingency planning.

3. My administration formally identifies the most important contingencies and develops contin-

gency plans.

13. How well is the marketing thinking at the top communicated and implemented down the line?

1. Poorly.

2. Fairly.

3. Successfully.

14. Is my administration doing an efficient job with the marketing resources?

1. No. The marketing resources are inadequate for the job to be done.

2. Somewhat. The marketing resources are adequate but they are not employed optimally. Or we

are doing the best we can with what little we have.

3. Yes. The marketing resources are adequate and are deployed efficiently.

15. Does my administration show a high capacity to react quickly and effectively to on-the-spot devel-

opments?

1. No. Enrollment and market information is not very current and the administration reaction time

is slow.

2. Somewhat. My administration receives fairly up-to-date sales and market information; reaction

time varies.

3. Yes. My administration has installed systems yielding highly current information and fast reac-

tion time.

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