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THE VALUED RELATIONSHIP BETWEEN WORKFORCE TRAINING AND

ECONOMIC DEVELOPMENT: A CORRELATION STUDY

By

Kevin A. Cojanu

JOHN DeNIGRIS, Ph.D., Faculty Mentor and Chair

JOHNNY MORRIS, Ph.D., Committee Member

ADOLFO GORRIARAN, Ph.D., Committee Member

Kurt Linberg, Ph.D., Dean, School of Business & Technology

A Dissertation Presented in Partial Fulfillment

Of the Requirements for the Degree

Doctor of Philosophy

Capella University

December 2007

UMI Number: 3288820

3288820 2008

UMI Microform Copyright

All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code.

ProQuest Information and Learning Company 300 North Zeeb Road

P.O. Box 1346 Ann Arbor, MI 48106-1346

by ProQuest Information and Learning Company.

© Kevin A. Cojanu, 2007

Abstract

The purpose of this study was to determine if workforce development has an impact on

changing the economic growth of rural communities in the state of Florida. Currently

there are no consistent strategies for developing workforce ready individuals in the many

rural communities of the United States. This research provides data as a point of

correlation for defining how workforce development affects the business opportunities

for economic growth in rural communities in Florida. This study develops ideas

regarding the impact of workforce development programs based on the two age

categories of “45 and Under” and “Over 45”, as this relates to the advancement of

economic growth of rural communities in the state of Florida. Participants for this study

were drawn from the members in the National Rural Economic Developers Association

(NREDA). A researcher-designed questionnaire was used to determine self-reported

viewpoints, divided by the two age categories above, regarding business, community, and

workforce issues as related to economic development in rural communities that can be

applied to the state of Florida. The results indicated that those National Rural Economic

Developers Association (NREDA) members who self-identified in the researcher’s

survey as “45 and Under” and those who self-identified as “Over 45” recognize that (a)

businesses have an influence on the workforce development levels in rural communities

as this impacts economic development, (b) communities, themselves, have an influence

on the workforce development levels in rural communities as this impacts economic

development, and (c) community workforce development agencies and educational

systems focused on developing workforce ready individuals within rural communities do

have an impact on economic development.

Dedication

This dissertation is dedicated to the most important person in my life, Susan.

Susan’s love, caring, dedication, and just plain old patience of a saint made all of this

possible. Susan was my rock, my motivation, and my love. She provided me with the

stamina to be something more than I thought I could be. In this dedication, I can only tell

her that the deep love we have for each other has helped us to overcome the hardships we

faced. This has made us stronger together and forged a bond that is unbreakable – I love

you Suzy!

Acknowledgments

There are many people that need to be part of this acknowledgement. First and

foremost, my mother, Marlene, who forever pushed me to be all I could be in life, and not

because she wanted a doctor in the family. My father, Stan, who will not see the

successful completion of this milestone because of his passing in 2005, but I know he is

watching with pride. I truly need to acknowledge the unwavering support of my in-laws,

Joni and Charlie. They have supported my every effort and my direction in this world,

and Charlie always had a joke or story that put everything into perspective. My friend,

my brother in this world, Randy, who was always asking how it was going and presented

me with a sounding board when life got tough. In every aspect of life, we meet people

that become family whom you love and care for, unconditionally. Trisha and Erik, of the

Hornitos family, have become just such family. I cannot fail to mention Dave and Loree,

who left me this year, 2007. I missed their tough love, but their faith helped me through

some difficult times. My daughter, Megan, who I tried to set an example for in that life is

full of challenges, but one must persevere to see success. I have great hopes for her

future. I cannot forget my Aunt Angela in this dedication. I believe her love, her

attention, and her example created the desire I had to learn all that I could, no matter

what. My Little Grandpa, gone these many years, still provides the life lessons I have

daily in my life. I know he is standing proud looking upon my accomplishment and

telling everyone “That’s my Grandson.”

I wish to acknowledge my superior dissertation committee, Drs. John DeNigris,

Johnny Morris, and Adolfo Gorriaran for all of their guidance, patience, and well-timed

encouragement. Also, I would like to acknowledge Dr. Susan Pettine who was an

excellent sounding board when the well ran dry. Her profound knowledge and ideas

allowed my creativity to flow.

Table of Contents

Acknowledgments iv

List of Tables ix

CHAPTER 1: INTRODUCTION 1

Introduction to the Problem 1

Statement of the Problem 3

Purpose of the Study 5

Rationale 6

Research Questions and Hypothesis 7

Significance of the Study 7

Definition of Terms 9

Assumptions 10

Limitations 11

Nature of the Study 11

Organization of the Remainder of the Study 12

CHAPTER 2: LITERATURE REVIEW 14

Introduction 14

Overview 14

Community Involvement 16

Workforce Development Associations 31

Business Involvement 42

CHAPTER 3: METHODOLOGY 51

Introduction 51

Foundation for the Methodology 51

Research Design Strategy 54

Sampling Design: Population and Sample 55

Measures 56

Data Collection Procedures 57

Pilot Testing 58

Data Analysis Procedures 58

Limitations of Methodology 59

Internal Validity 60

External Validity 61

Expected Findings 61

Ethical Issues 62

Conclusion 63

CHAPTER 4: DATA COLLECTION AND ANALYSIS 64

Introduction 64

Review of Research Questions and Hypotheses 64

Review of Data Collection 65

Pilot Study 66

Findings Related to Hypothesis 1 67

Question 1 67

Question 2 69

Question 3 70

Question 4 72

Question 5 74

Overall Discussion of Hypothesis 1 Findings 76

Findings Related to Hypothesis 2 76

Question 1 77

Question 2 78

Question 3 80

Question 4 82

Question 5 84

Overall Discussion of Hypothesis 2 Findings 85

Findings Related to Hypothesis 3 86

Question 1 86

Question 2 88

Question 3 89

Question 4 91

Question 5 93

Overall Discussion of Hypothesis 3 Findings 95

Summary of Data Collection and Analysis 95

CHAPTER 5. RESULTS, CONCLUSIONS, AND RECOMMENDATIONS 98

Introduction 98

Summary of the Study 98

Discussion of the Results 99

Hypothesis 1 99

Hypothesis 2 101

Hypothesis 3 102

Conclusions 104

Recommendations for Future Research 105

REFERENCES 107

APPENDIX A: SURVEY QUESTIONS AND INFORMED CONSENT 117

APPENDIX B: SURVEY DATA: HYPOTHESIS #1 126

APPENDIX C: SURVEY DATA: HYPOTHESIS #2 131 APPENDIX D: SURVEY DATA: HYPOTHESIS #3 136

List of Tables

Table 1. Survey Response 66

Table 2. Participant Age Categories as Recorded by the Researcher’s Survey

Instrument 66

Table 3. Question 1 Age Categories and Responses 68

Table 4. Question 2 Age Categories and Responses 69

Table 5. Question 3 Age Categories and Responses 71

Table 6. Question 4 Age Categories and Responses 73

Table 7. Question 5 Age Categories and Responses 75

Table 8. Question 1 Age Categories and Responses 77

Table 9. Question 2 Age Categories and Responses 79

Table 10. Question 3 Age Categories and Responses 81

Table 11. Question 4 Age Categories and Responses 82

Table 12. Question 5 Age Categories and Responses 84

Table 13. Question 1 Age Categories and Responses 87

Table 14. Question 2 Age Categories and Responses 88

Table 15. Question 3 Age Categories and Responses 90

Table 16. Question 4 Age Categories and Responses 92

Table 17. Question 5 Age Categories and Responses 94

Table B1. Hypothesis 1, Question 1 126

Table B2. Hypothesis 1, Question 2 127

Table B3. Hypothesis 1, Question 3 128

Table B4. Hypothesis 1, Question 4 129

Table B5. Hypothesis 1, Question 5 130

Table C1. Hypothesis 2, Question 1 131

Table C2. Hypothesis 2, Question 2 132

Table C3. Hypothesis 2, Question 3 133

Table C4. Hypothesis 2, Question 4 134

Table C5. Hypothesis 2, Question 5 135

Table D1. Hypothesis 3, Question 1 136

Table D2. Hypothesis 3, Question 2 137

Table D3. Hypothesis 3, Question 3 138

Table D4. Hypothesis 3, Question 4 139

Table D5. Hypothesis 3, Question 5 140

CHAPTER 1: INTRODUCTION

Introduction to the Problem

The state of Florida has put forth the Rural Economic Development Initiative

(REDI) to assist rural Florida communities to become more viable economically (Florida

Statute 288.0656). Section 2 Article (a) says:

Economic distress" means conditions affecting the fiscal and economic viability

of a rural community, including such factors as low per capita income, low per

capita taxable values, high unemployment, high underemployment, low weekly

earned wages compared to the state average, low housing values compared to the

state average, high percentages of the population receiving public assistance, high

poverty levels compared to the state average, and a lack of year-round stable

employment opportunities (Florida Statute 288.0656) .

In addition Section seven states:

… A rural area of critical economic concern must be a rural community, or a

region composed of such, that has been adversely affected by an extraordinary

economic event or a natural disaster or that presents a unique economic

development opportunity of regional impact that will create more than 1,000 jobs

over a 5-year period (Florida Statute 288.0656).

Workforce development in rural communities of Florida is not treated equally

across the state because there are no viable programs that can properly educate or train

the existing workforce to advance the viability of the community (Garlich & Tesinsky,

2005). This research study evaluates the impact of an unskilled workforce on business

opportunities for economic growth in rural communities in Florida.

Workforce Training and Economic Development 2

Ulrich Research (2002) provided research that determined workforce availability

compared to workforce development opportunities in Highlands County Florida were at

risk based on the level of training and education within the available workforce.

Davenport (2006) suggests that according to corporate executives the United States must

increase the education and skills of rural and urban communities in order to remain

competitive in retaining jobs. Dychtwald, Erickson, and Morrison (2006) cite that fewer

degreed people in the workforce significantly influence economic growth of business in

urban and rural communities. There appears to be fewer and fewer skilled workers to

address the needs of corporations in leadership and problems solving to meet the

demands of the global market (Davenport, 2006).

Highlands County Florida is a region of Florida that is designated agricultural.

Highlands County Florida’s focus is the citrus and cattle industries, which is beginning to

fade due to foreign competition (Pfeifer, 2006). The shift away from agriculture is

beginning to have an impact on the population of the Highlands County Florida and there

is a need to develop the existing workforce to become viable for other business and

industry to maintain economic development opportunities (Dalton, 2004). Ulrich

Research in September of 2000 indicated that based on the estimated 99,718 adults 18

and over that less then 12% have a college education, 7% have some specific trades

training, and 30% have high school diplomas (Ulrich Research, 2000). The range of

career opportunities reside in office and clerical, service related positions, and a large mix

related to agriculture in numerous forms (Ulrich Research, 2000).

One example of the relationship of workforce training linkages and economic

development is in Massachusetts, where roughly 1.1 million workers have not obtained,

Workforce Training and Economic Development 3

or have the means to obtain needed skills to support economic growth (Business West

Editorial, 2005). These workers will become an unskilled labor force that will be

recognized as at-risk for low-income output and impact the economic viability of the

economic position of the United States (Sperling, 2005). At the current rate, Both China

and India will annually graduate five times the number of engineers compared to the

United States (Sperling, 2005). In the new global economy, foreign labor is effectively

replacing the United States as the premier labor market.

Kastsinas and Moeck (2002) compare the ‘have’ and the ‘have–nots’ in the

ability to offer technology availability and training to different communities. A study by

Kastsinas and Moeck (2002) outlined that most rural communities struggle to be

technologically perceptive because of the economic resources available to them. Rural

colleges face the same issues because of available funding to develop and deliver new

workforce training programs. Therefore, these communities are behind in developing

into economic centers that focus on developing workforce skills at the earliest possible

learning levels and or delivering workforce training. Kastsinas and Moeck (2003)

expands on this position to promote a review of current funding models for college

tuition. This review should account for the real cost of tuition including items such as

childcare, transportation, and living expenses.

Statement of the Problem

The lack of a skilled workforce is having an impact on businesses and the

economic development of rural communities in the State of Florida. Highlands County

Florida is one example that finds the most educated of the available workforce making on

the range of $26,000 to $32,000 in 2000 according to the Ulrich Research (2000) study.

Workforce Training and Economic Development 4

Additionally, the highest paid positions make up less than 12% of the total population of

Highlands County Florida (Ulrich Research, 2000). Some of the conditions can relate to

the actual level of skills that are available from high school and college graduates

entering into the workforce. In some cases workforce resources do not have the

knowledge to contribute to the business objectives that relate to the growth of local and

relocated businesses (Andersson & Karlsson, 2007).

The Academy of Management Review (Tallman, Jenkins, Henry & Pinch, 2004)

promotes the definition of Industrial District as a single focused geography to promote

the industry of choice. This definition identifies that the knowledge sharing for the

development of specialized workforces occurs at all levels of business, education, and

local government to develop the Industrial District to meet the current and future needs of

the specific industry.

Markusen (2004) promotes the concept of ’Industrial Targeting’ as a form of

industrial districting. The concept looks at the methodology of corporations building a

strategic plan that ideally looks for the logistical attributes that exist in a community and

then begins the process of knowledge sharing with community and education leaders to

begin the potential transformation. Markusen (2004) warns that this methodology is not

always the most effective method of creating economic growth in a community.

Markusen’s reasoning resonates around the theory that much of the available

demographics for a community may lack consistency and validity.

Patrucco (2003) introduces the concept of agglomeration as the development of

loosely connected communities that offer the impression of a solid workforce

development program that could support the needs of one or multiple industries. The

Workforce Training and Economic Development 5

benefit to the economic growth is the knowledge and training of the workforce. These

agglomerations provide effectively for the growth of businesses into three different

districts; the actual industry it supports, the technical support services, and the

community services that are provided to the workforce. As Patrucco (2003) suggests, the

community develops, hence bringing economic growth as a natural progression for

supporting the industrial district with a well-trained workforce.

Workforce investment planning appears to play a crucial role in the success or

failure of economic development. To understand how workforce training and

development influences to economic growth it will be necessary to understand the

relationship and its presumed effects.

Purpose of the Study

The purpose of this study was to determine what degree of impact workforce

development has on changing the economic growth of rural communities in the State of

Florida. Currently there are no consistent strategies for developing workforce ready

individuals in the many rural communities of the United States. This research provides

data as a point of correlation for defining how workforce development affects the

business opportunities for economic growth in rural communities in Florida.

Swager (2000) defines economic development as a method of utilizing resources

such as land, buildings, and people to provide for underdeveloped regions and countries.

Sperling (2005) states:

Over the past two decades, the share of workers with at least a high school degree

grew by 19 percent; over the next two decades, it will grow by only 4 percent. At

the same time, high-skilled technical jobs have grown five times faster than the

Workforce Training and Economic Development 6

population since 1980. Unless we expect massive new immigration or increased

fertility rates, we will need to increase the pool of highly skilled workers or face a

growing labor shortage (p.137).

Sperling (2005) implies there is a lack of highly skilled workers to support the

potential requirements of businesses in the United States. This research study examines

how a dwindling skilled workforce could influence business and economic growth. The

research study also focuses on the levels of education within the workforce and the

possible impact on businesses and economic growth of local communities within the

United States. To provide the necessary workforce for a business and to contribute to

economic growth, businesses may need to contribute to the learning outcomes and

potentially work with the community (or country) to develop that potential workforce

resource (Preparing for tomorrow through education and workforce development, 2006).

Specifically, economic development is a focus for developing economic growth

with no real specific boundaries or limitation. Economic development has assumed the

role as one of the dominating issues in the world today. There is a great deal to be said

for acting global and working local when the competition for economic business has no

country or continent boundaries, but the maintenance of global business relies solely on

available resources within the village, town, city or metropolitan urban center (Koehler &

Wurzel, 2003).

Rationale

This study adds to the body of knowledge as it relates to the development of

workforce skills and its possible impact on the economic development of the

communities they serve. Economic development is a global movement driven by local

Workforce Training and Economic Development 7

business and communities as a point of survival for future generations (Holliday, 2006).

This study provides information about the role businesses, communities, government,

education, and workforce development agencies have in creating programs for

encouraging workforce development to enhance the economic development of a given

community and/or region.

Research Questions and Hypothesis

A sample survey of the National Rural Economic Developers Association

(NREDA) members was conducted, as they represent the interest of the rural

communities in Florida and the United States. This association represents the leadership

of rural communities and can effectively provide knowledge and validity to the research.

These research propositions were framed by these research questions:

1) Does business influence the level of workforce development in rural

communities to impact economic development?

2) Do communities influence level of workforce development to impact

economic development?

3) Do community workforce development agencies and educational

systems focused on developing workforce ready individuals’ impact

economic development?

Harvard Economist, Ed Glaeser outlines the need for communities, businesses,

education, and governments to come together and positively impact the economic growth

of communities big and small (Bowles, 2005).

Significance of Study

Workforce Training and Economic Development 8

In the Southeastern United States the wages per-capita are the lowest in the

nation. Florida is one of the largest states in the geography and it represents about 35%

of the total workforce in the Southeast. The quality of workforce development is

dramatically impacted in rural areas and hit harder with potentially fewer opportunities

(Shuptrine, 2006).

The Work Readiness Credential is a voluntary program created by the U.S.

Department of Commerce to promote a ready workforce. Florida is a participant, but

does not have a solid base for running the program in urban or rural communities. The

program does not focus on developing workforce skills in specific areas. It will make the

resource a better candidate for providing basic job skills (Olson, 2006).

Workforce development is rural communities like Highlands County Florida

suffer from a potential lack of direction in developing programs to educate and train the

workforce to open opportunities for business development and relocation. Some

communities establish themselves as a leader in specific industry clusters. The ability to

promote a specialization based on workforce skills works to establish the community and

draw the interest of businesses in that industry (Romanelli & Khessina, 2005). The

challenge to meet any specific industry criteria may relate to the demographics of the

community, which provide a workforce that is trained and or trainable with the required

business skills. In cluster opportunities, communities look to the business seeking to

locate to assist in the training process (Jeter, 2004).

This study seeks to create new avenues of opportunity for businesses and

communities to evaluate current workforce development activities and determine if the

specifics of the strategy are in the best interest of the workforce being developed and

Workforce Training and Economic Development 9

hence the impact to the economic position of the community. Developing and

redeveloping a workforce strategy could keep communities like Highlands County

Florida in the forefront of the business needs of specialized industries solely based on the

development of a workforce that is equipped to support any possible requirements.

Definition of Terms

There are several key terms used in this study that require a clear definition. They

are as follows:

Workforce Development: Knowledge and skills that relate specifically to the work

delivered in a community. Managing strategy to maintain the viability of business based

on the available labor force skills (Voorhees & Harvey, 2005).

Economic development: The combination of specific elements education,

employment opportunities grow, income rises, innovation in business becomes the rule,

and there is a steady increase in productivity (Schweke, 2000).

Economic growth: Utilizing the Endogenous Growth Theory, which measures

growth based on employment numbers and income growth among the workforce, this

includes the monitoring of the human capital components for education, training and

workforce-ready individuals. Additionally, the theory includes the impact of government

policy, trade, and local and foreign investment (Ericsson & Irandoust, 2000).

Secondary institutions: Comprehensive high schools that cover Basic English,

Mathematics, Social Studies, Science, and some basic vocational instruction.

Post-secondary institution: Higher education focusing on providing specific

vocations by way of degree in a specialized subject matter that can be applied to a job or

Workforce Training and Economic Development 10

career. Cleveland (1981) defines the outcome, as students are employable to the

community for which they live.

Workforce-capable: Possessing the level of skill to deliver on new processes and

providing current and new services to business and or customers (OECD economic

surveys, 2005).

Community leadership: People and organizations, government or public support,

that provides opportunities for success in the communities in which they live. Providing

strategy to stir new growth starts with the commitment and leadership within the

communities (Walsh, 2006).

Resources: Workforce-capable individuals that are ready, willing, and able to fill

the needs of industry and business in the communities for which they reside. These

resources are not defined by any gender, race, sexual preference, or ethnic background.

Global Economy: The ability to sell products and services globally by allowing

for businesses to create products and services in geographical regions that take advantage

of low-cost resources to create competitive costs of productions and or delivery of

services.

Assumptions

For the purpose of this study, the following assumptions were made: (a) voluntary

participants from the National Rural Economic Developers Association (NREDA)

members were surveyed, (b) this study rigorously focused on the ethical codes and

regulations of Human Subjects in Research for the data collected, processed and

analyzed, (c) interview questions produced impartial, and unbiased statements in the

design format when it was provided to the NREDA membership, (d) analysis took place

Workforce Training and Economic Development 11

to reduce bias interpretation as patterns began to develop outcomes, and (e) the study was

limited to focusing on rural communities in Florida.

Limitations

This study was limited by these elements: (a) representation in the study only

came from the NREDA membership, and (b) the definition of a resource was not based

on gender, race, sexual preference, or ethnic background.

Nature of the Study

The primary research that was performed focused on the impact of workforce

development on the economic growth in rural communities in the state of Florida. The

process was to focus on determining if there was a correlation between workforce

development and the influence from business, community, and workforce development

agencies and economic development as it relates to economic development for rural

communities. The researcher was looking for common results in the research that outline

possible strategies that can be utilized to build stronger workforce development programs

in rural communities. These results come as a result of the knowledge and experiences

from the membership of the NREDA. These economic development professionals

provided quantitative data to determine specific areas of concern and successes.

Additionally, they provided anecdotal feedback that provided a qualitative review of

possible workforce strategies for rural communities. Mason (1996) outlines three

specific types of understanding in qualitative research, which each have an individual

threat to validity. Description threat occurs when partial or an inaccurate collection of

data exists. As such, supporting material from viable alternative sources can be used to

compensate. Interpretation threat occurs when a framework of position is forced rather

Workforce Training and Economic Development 12

than allowing interpretation to unfold. Mason (1996) explains that interpretation must be

openly demonstrated to offset to prevent any threat to validity of the research. Theory

threat diminishes when different explanations of the phenomena are ignored. To meet

this objective, the researcher must aggressively pursue data that is independent of the

theory.

Organization of the Remainder of the Study

This research study was organized into five specific chapters. Chapter 1 has

outlined an introduction of the proposed research study, which includes the background

of the study, the statement of the problem, the purpose of the study, the rationale,

research questions, significance of the study, definition of terms, assumptions, and

limitations, and the nature of the study.

Chapter 2 provides a review of the literature on the impact of community,

education, business leadership on the economic development of regions, rural and urban

centers. There is a perception that economic development is directly related to

participation of outside organizations in creating the right conditions, including

workforce-capable resources. Additionally, Chapter 2 provides a review of the literature

relating to qualitative research methods. The findings of this literature review provide the

foundation for the research methodology for this study.

Chapter 3 provides a detailed description of the proposed research methodology,

criteria, dependent and independent variables, cause and effect relationship maps for all

of the defined variables, and a review of the measurement instrument for testing. This

chapter also includes the proposed methods of data analysis.

Workforce Training and Economic Development 13

Chapter 4 presents the research data and the analysis of the data relating to the

research questions.

Chapter 5 provides a summary and discussion of the results, conclusions and

recommendations, and connects the research results with the literature review.

CHAPTER 2: LITERATURE REVIEW

Introduction

Maslow's hierarchy (1998) teaches us the importance of understanding our needs

and how those needs can be satisfied. Denton (1994) notes that diversifying by

understanding what the community has to offer presents a plethora of economic growth

opportunities focused on the community. Garza and Eller (1998) outlined that

educational systems needed to open themselves to a greater understanding of what impact

they have on the economic development of a community. Martinez-Carbonell (2000)

emphasizes that business supporters view government officials as mechanisms for valued

contacts for growth. These statements are the basis for the research that will be

conducted on the impact of community, education, and business on the workforce in

order to create economic development (Martinez-Carbonell, 2000).

This literature review addresses the following situations: (a) communities

influence the level of workforce development and available job opportunities in the

workforce by promoting only the immediate needs of businesses, (b) secondary education

systems fail to provide educational standards and skills that are based on preparing the

workforce, and (c) business leaders are promoting changes in the level of workforce

capabilities. There is a perceived need for basic skills, which is not being heard in the

educational institutions. Adults are entering the workforce with little or no customer

service or basic life mathematical skills.

Overview

The literature review conducts an overview of the influence community,

workforce development agencies, education, and business leadership has on the economic

Workforce Training and Economic Development 15

development of a region or a rural or urban center. The analysis in the literature review

focuses on the positive and negative influences these independent organizations have on

promoting development for the communities, and also focuses on the influences of the

workforce-capable resources that will potentially drive the economic direction of the

community.

Developing economic success is a possibly important component for any

community. An important factor that contributes to this success is the level of linkages

between training and employment opportunities within communities, and the businesses

they ultimately support. This communication is not solely the process of interacting. The

exchange of knowledge and information develops a measure of mutual success for the

community and business. These mutual-success factors have the best possible impact

when collaboration on knowledge is shared effectively between all parties involved. The

ability of organizations to share information and knowledge to bring about success in the

global business environment can be as simple as supplying the mission and objectives for

the people in the organization to accomplish. Some of these same approaches are

effective in the development of programs within a community. The coordination of

information and knowledge with community and industry assists in creating a

competitive workforce through workforce training and development programs that

transform the community workforce to be a positive contributor to the local economy by

maintaining a steady flow of resources to support the industrial and economic viability of

the community. It is important that economic development organizations of communities

that are in critical need of knowledge sharing across business and industries, as well as

knowledge gained by training and development institutions of a community, be fluent in

Workforce Training and Economic Development 16

communication and knowledge sharing. The ability to develop economic growth within

a community may depend greatly on the ability of economic development leaders to

manage the knowledge shared to present a complete portfolio of available resources the

community has to offer to any potential business looking to locate or even expand within

the community. This portfolio should be designed to present a clear definition of

resources, educational programs, business support, and community viability as in the

conditions of the community to support potential development activities.

Community Involvement

In every community, rural and urban, there are economic development

opportunity possibilities. These communities are subject to developing strategies that

government officials create to begin the process of developing and redeveloping the

communities to increase the positive impact to the city, town, village, county, or

metropolitan area. This impact is measured in the job opportunities that are created.

Impact is also measured in how areas are developed or revitalized. It is important for

leadership in these rural or urban centers to provide planning that encompasses a strategy

that can be developed for three, five, ten, and even twenty years of development and

planning.

Moses (1991) expresses the importance of avoiding the pitfalls of economic

development strategies. Much of the planning process needs to consider the importance

of setting realistic goals that match the community. In a number of cases, there is the

copycat effect that finds leadership focusing on what other communities have done

successfully and attempting to apply the same effort in their community. Moses (1991)

states that failure to understand the economic base of the community is a critical error in

Workforce Training and Economic Development 17

effort. The understanding of the available labor resources is a common mistake.

Sometimes the combination of census data with state and federal employment data is not

a viable option for determining what a community has to offer in a labor market for

development. Some of these numbers are skewed, and when combined, do not offer

details in regards to skills and/or true educational advantage for the community.

Successes in economic development planning can be viewed in a number of

different models and the processes associated to determine the right plan. The town of

Mentor, Ohio is one such example of collaboration and research to develop a plan to

sustain the community in the immediate and long term. Having suffered a number of

manufacturing plant closures that affected 5,000 people in the workforce, the community

leadership developed a strategy that looked to attract a large heavy manufacturing facility

to help the displaced workforce. At the onset of the process, community business leaders

recommended an alternative method of reviewing that decision. In a collaborative effort

analysis utilizing the Cambridge Systematics' growth and risk indicators database, it was

indicated that a focus on small homegrown businesses showed greater promise to address

the workforce displacement that had occurred. This evidence provided for a change in

strategy with a focus on small local businesses. This resulted in 4,000 new positions over

the first few years of the strategy being implemented (Moses, 1991).

Cambridge Systematics is a private company that specializes in the review of

businesses and industries’ growth patterns. The types of establishments included in the

review are branch, headquarters, and single locations based on size and vitality. As a

company for hire, Cambridge Systematics provides solutions that build economic

Workforce Training and Economic Development 18

development planning that makes effective use of the core infrastructure components that

exist in a region, city, town, or metropolitan setting (About us, n.d.).

In the mid-1990’s, Shore (1995) began research that started to raise the level of

information as it related to the urban centers, or downtown areas of large cities and their

degradation. Economic development was focused on areas that were suburban or rural

based on expansion possibilities. Downtown areas were ignored as unusable. This belief

in the early 1990’s that downtown areas were unusable did not take into account the

numbers of people living in the downtown areas. The workforce-capable resources were

becoming stagnant and losing their worthiness to the community (downtown areas).

Shore’s efforts began the process of outlining the critical benefits of downtown living and

the city dwellers that could contribute to the workforce-capable resources to revitalize

these communities. The Ford Foundation established the Local Initiatives Support

Corporation (LISC) with the sole purpose of revitalizing communities through

communities by providing financing for rebuilding and for workforce development

programs for the city. The LISC created opportunities to address specific needs in the

community and provide skills for the forgotten workforce.

Talen (2002) promotes the transect approach to development. The transect model

is described as an analytical approach to putting things in the right places. As an

example, in an urban center there are opportunities to promote the use of existing

structures to support new business opportunities, whereas in a rural community, there is a

need to focus land use that takes into consideration the ecology of the region and not

affect possible agri-businesses that currently exist. One of the key factors in the

development process is the use of designed transect zones for rural and urban

Workforce Training and Economic Development 19

development. As an example, the transect approach sub-divides urban centers as: sub-

urban that is primarily residential and significantly void of businesses; general-urban that

has a mix of residential and business interaction; urban center which is a more dense area

of multi-residential buildings and businesses; and urban core that has the densest of

community population with business and multi-residential buildings and contains the

cultural and entertainment core of the urban community.

Gomez and Muntaner (2005) offer research that discusses the community health

and the importance of re-development of depressed areas such as East Baltimore. In the

research, the indications are that the failure of communities to maintain social

involvement through regular community leadership such as associations’ results in a

failure to maintain a level of pride in how a community looks, and the sense that it is a

desirable place to be. Gomez and Muntaner (2005) cite the works of Woolcock and

Narayan (2000) and North (1990) which outline the importance of these communities to

force its role with the local and state governments to become a decision-maker in how

redevelopment is handled. This political control offers the community the position to

control its destiny in creating redevelopment and economic growth for its urban

community.

Porter (1998) adheres to the revitalization model of economic development in

urban city cores. The author’s claim is this has become a cyclical effort. Ultimately, this

resulted in a failure in the long term to maintain a successful environment for economic

growth. Some of the conditions outlined focus on the simple services that draw growth to

a city core, such as security, opportunity, and money to sustain the progress. In an effort

to support, yet refute Porter, Amirkhanian and Habiby (2003) promote that these are

Workforce Training and Economic Development 20

necessary services, but a collaborative effort from government, community, and

businesses can and will create an effective revitalization of a failing city core. Nunn

(2001) disputes Porter's position by emphasizing the overall advantages of an inner city.

He promotes the facts of logistical access, trainable workforce, and government support

for revitalization.

Fredericksen and London (2000) caution that revitalization efforts in certain

regions and inner city locations present serious risks based on the social and ethnic make-

up of these areas. Ultimately, what you find are low income and poorly educated social

and ethnic groups. If a revitalization plan does not review the community dynamics, the

ultimate result will be failure.

Jeter (2001) outlined the process that the Tupelo, Mississippi Community

Development Foundation (CDF) used as it entered into a $1.6 billion dollar investment in

to the Future Focus campaign for the development of economic and quality of life

opportunities. After completing the study, the CDF established a series of proposed

directives to resolve area workforce development issues, technology initiative, and the

retention of current businesses, and attracting new business. Additionally, there would be

a focus on providing leadership and organization development including quality of life

issues.

Lofton (2006) provided a follow up to the initiatives for Tupelo, Mississippi

Community Development Foundation (CDF) which provided significant results. The

CDF found itself in the number two metropolitan areas of the 19 designated areas in

Mississippi. Much of the success was due to the level of communication and

involvement of the Tupelo community. In addition to communication, the CDF involved

Workforce Training and Economic Development 21

any and all business and educational and workforce development organizations to share

in the work, but also to share in the rewards of success.

Stafford (2000) outlines that in most cases communities and governments are very

willing to reduce environmental conditions for the opportunity to gain an edge for

businesses of medium to large-size to move into any urban or rural community. It is

clearly represented that there is no noteworthy restrictions for businesses or corporations

to move into a region and begin the process of developing an effective enterprise.

During the Clinton administration there was a concerted effort to bring about a

National Information infrastructure that focused on increasing information access by

every American citizen. President Clinton on February 8, 1996 signed the

Telecommunications Act of 1996. This Act was an overhaul of the Communications Act

of 1934. This action promoted open competition across all elements of the of the

telecommunications industry (Beachboard & McClure, 1997).

Hausman (1997) indicates that the telecommunication conditions created greater

opportunities for everyone from urban to rural communities to obtain cost-effective

services based on competition of local providers. These efforts also created growth

opportunity for rural communities that did not previously receive the modernized

telecommunication services. In a twist of fate, these communities were defined as

growth areas for smaller telecommunication companies to enter into relationships with

rural communities and expand the possibilities of those communities with a technology

infrastructure. These relationships resulted in relationships expanding to other technical

companies allowing for a network to become established, and these networks viewed the

small rural communities as growth opportunities at a low cost (Gillette, 1997).

Workforce Training and Economic Development 22

Denton (1994) acknowledges the importance of communities recognizing the

risks and potential opportunities for economic growth. The Virginia Peninsula was a

rural community that was rich in government military contracts for technology

production. What presented a problem to the community was the ongoing ebb and flow

of very lucrative contracts. Denton (1994) presented material that the region received a

$700 Million military contract one week and the next week businesses that supported the

Navy were forced to lay-off 2200 workers due to reduced spending for naval technology.

Most of these positions were non-transferable across the industries in the industry cluster.

The community provided a visionary approach creating economic diversity. Creating the

Virginia Peninsula Economic Development Council (VPEDC), it developed a report

called the "Peninsula Focus 2000." The report outlined the assets and characteristics that

the region offered. It outlined the critical characteristics of the type of businesses that

would benefit from the community. The key characteristics identified focused on

technology-based manufacturing and development firms as the center of its economic

diversification. In the next phase of the VPEDC initiative, it targeted the desired industry

clusters for developing economic diversification. The "Peninsula Focus 2000" references

the engagement of the local workforce training organizations to support and assist in

developing the skills training plan that would continually make the community workforce

ready for all opportunities.

Kemp (2000) warns that in some cases the planning occurs with government and

business participation with little or no involvement from community organizations that

represent the social and ethnic viewpoints of the community to be revitalized. In reality,

the planning process often promotes the gentrification of an urban core.

Workforce Training and Economic Development 23

Scott (2005) outlines the endless possibilities of economic growth from

developing an industry cluster. The industry cluster model has the ability of developing

multiple tiers of services and businesses to support a singular industry. The aspects of

developing a community, or region, into an industry cluster depends greatly on the ability

to assess current assets such as land for development, existing structures, workforce,

logistical applications (transportation), utility foundations (power, water etc.), technology

availability, workforce development, and educational institutions (Allen & Taylor,

2005). What is important for these regions and/or communities is the ability to present a

constructive view as to how they measure up to the needs of industries they may be able

to support as an industry cluster community.

There are a number of examples where industry evaluated the region and based on

specific regional and federal government concessions developed the industry cluster by

providing all of the critical components to ensure the businesses’ efforts would not result

in failure. This undertaking would be a collaboration to develop land use criteria, utility

infrastructure, logistical supply-chains, transportation, and workforce education.

Ultimately, the cluster industries would share in the responsibility to build vitality based

on core needs (Howard, 2005).

Rozycki (2006) cited a plan by the New York State Thruway Authority,

Department of Transportation, and Metro-North Railroad to open a possible industry

cluster growth opportunity by creating rail service that would link the combined outer

suburb communities and urban centers to significant land use to develop industry clusters

at any point in the rail map. The estimated $11.5 to $14.5 billion dollar project has come

under fire from a number of impact agencies such as Inter-Metropolitan Planning

Workforce Training and Economic Development 24

Organization, and additional concerns reported by Environmental Protection, which

believes consideration for the environment, needs to be defined before the project can be

initiated.

Gillette (2004) outlines the success of George County, Mississippi, which had

been working with community leaders to develop a “mega site” to build economic

development opportunities. Surrounding counties had been able to develop “mega sites”

due to rail export services. The Greater Mississippi Economic Development Foundation

negotiated with the Mississippi Export Rail a spur that would provide access to a 1,200-

acre site that would allow George County to compete for industry clusters along with

other counties already benefiting from the same rail services that link to the other clusters

as well as to Mississippi ports.

Technology infrastructure is a critical component of the overall infrastructure

within a region or community or as defined by Brynjolffson and Hitt (2000). The

authors' state “General-purpose technologies are substantially larger than would be

predicted by simply multiplying the quantity of capital investment devoted to them by a

normal rate of return. Instead, such technologies are economically beneficial mostly

because they facilitate complementary innovations” (p.31).

Clearly, the importance of technology infrastructure includes the impact of

supporting the expected needs of industry in order for the regions or community to

become a player in soliciting economic growth opportunities.

China has incorporated a number of initiatives aimed at become a monopoly in

providing economic development opportunities by providing technology zones that are in

conjunction with its economic zones claims Smart and Hsu (2004). China has set these

Workforce Training and Economic Development 25

economic and technology zones to encourage foreign investment into the country. The

zones are equipped with the entire latest technology infrastructure and are capable of

offering quick adjustments.

The Economic Development Board of Singapore (2000) established a set of

operating criteria that focused on supporting all possible industries by creating the best

possible information technology (IT) infrastructure in the country. The undertaking was

to establish within the country regions of support. These regions of support were adept at

providing the technology needs for subject industries because they were clustered to

support the specific criteria of that industry. In conjunction with technology specific

requirements, they would outline a complete economic development plan that includes

specific workforce skills and appropriate manufacturing real estate requirements. This

detailed philosophy is developed to grow the economic development of the country by

design.

It is common that technology can sometimes be a scary object with people who do

not have any technical background, according to Lauderman (2004) who promotes the

services of the Georgia Tech Community Innovations Services Group. He indicates that

organizations attempting to grow economic development programs need to consider

starting with small phases. Entering into technology slowly can and will lead to steady

growth with the development of local talent and commitment from those who have

something to offer in this growth opportunity. As an example, Lauderman (2004)

presented the case study of the Carroll Tomorrow, an economic development group in

Carrollton County, Georgia. Carroll Tomorrow started with a small GIS (global

information system) program that outlined available land use opportunities in the county.

Workforce Training and Economic Development 26

After great success in developing this small technology program, the organization

connected with leaders in the community that have extensive technical backgrounds.

These leaders have become part of the organization, which is now developing a complete

economic development strategy and the technical infrastructure to support and maintain

the economic growth of Carrollton County.

Black (1990) promotes the visionary strategy of South Carolina in positioning the

state for economic development in the long-term. The focus of the economic

development program was to collaborate with other state agencies to have a better

understanding of the available resources across the state. The development of a database

to manage and describe what the state had to offer potential industries was a key point in

the process. Such planning tools were available to the economic development agencies to

develop and outline proposals to bring business to the state. The infrastructure provided

mobility infrastructure (roadways), infrastructure banking (low interest loans), and utility

infrastructure bonds for building and utilities, and block grants for communities to

determine infrastructure needs. All of these opportunities for development were housed

in a technical database that was accessible from all over the state to benefit economic

growth.

Patrucco (2003) introduces the concept of agglomeration as the development of

loosely connected communities that offer the impression of a solid community available

to support the needs of one or multiple industries. The benefit to the economic growth of

this community is the knowledge that is shared at all levels of government, community,

education, and workforce development agencies. These agglomerations provide

effectively for the growth of communities into three different districts; the actual industry

Workforce Training and Economic Development 27

it supports, the technical support services, and the community services that are provided

to the workforce and associated family. As Patrucco (2003) suggests, the community

develops, hence bringing economic growth as a natural progression for supporting the

industrial district. The author warns that it is a critical component of the process to

ensure that infrastructure planning is conducted to share knowledge across the industry,

community, education, and government.

Coy and Arndt (2005) depict international community’s provide support for the

concepts of knowledge sharing across business, education, workforce development

agencies, and economic development organizations and/or government. One topic of

discussion over the last five years has been the impact of outsourcing. Some key factors

that drive outsourcing by major corporations include the cost of performing functions

such as manufacturing, research, and business management functions. The key success

indicator of outsourcing can be defined as economic growth for the countries that provide

outsourcing (Garten, 2005). The reasoning behind this success is the knowledge sharing

that occurs between government and workforce development agencies to provide the

correct workforce for businesses looking for outsourcing advantages. There is

misconception that corporations are the controlling entities in an outsourcing program to

other countries. Henley (2006) outlines that some of the countries, like India, involved in

outsourcing provides a complete set of attributes or a portfolio of available services they

can provide to a perspective corporation. One component of the portfolio is the available

workforce, including projected workforce availability, training opportunities that can be

customized to support the requirements, and the government initiatives to support the

specific requirements, or in other words government leadership willing to make changes

Workforce Training and Economic Development 28

in the laws of the country to meet the needs of the corporation. The duality of

outsourcing and economic development is the ability and willingness to change for the

right reasons (Siems & Ratner, 2006).

On the global scale, countries perform similar knowledge exchanges. India has

been preparing for economic development as a nation over the last decade. The focus

was to develop a portfolio that global corporations would view positively and be willing

to invest in the country infrastructure to support specialized outsourcing requirements.

The portfolio for India was based on factors of workforce availability, labor costs, and

most importantly the availability of quality education of the workforce to meet the needs

of specific industries (Das, 2006). India supports a number in different industrial districts

(Kaushik, 1997). The districts range from technology to business process management.

The key factor of India's success is the ability of government (Economic Development

Organizations) and the education institutions of India to develop curriculum to support

the industries by sharing knowledge (Surahmanian, 1999).

Rosenfeld (2003) performed a study that looked at marginalized areas of Europe

and the United States that did not have the desired government and workforce

development structure to support industrial district or industry cluster. Rosenfeld (2003)

determined that these economically distressed urban and rural communities had some

value to the corporations looking to develop an industry district or industry cluster. In

order to develop these potential districts, corporations would enter the community and

bolster the infrastructure and training and development systems. This effort will

ultimately develop the community to increasing the development of the district to support

economic development. These attempts are not without risk. In some cases, you will

Workforce Training and Economic Development 29

find that there is a great mistrust in because communities are insulated or even non-

hospitable to strangers attempting to impact or change the current lifestyle (Frankema &

Lindblad, 2006).

Economic development is a part of every community with the objectives to

provide positive economic impact on the community to maintain its vitality. When you

compare economic organizations around the United States and globally, you find a

dichotomy as it relates to the level of diversity, knowledge, workforce development, and

commitment to the process (Jolly 2004). Maslow's Needs Hierarchy (1998) represents

the simplest way to present the dichotomy of economic development globally. As an

example, you have the Asian geography that falls within the ego and self-actualizing type

of need outlined in Maslow's Hierarchy. One of the reasons Asia has reached these levels

is their willingness to make change and become an advocate for promoting the needs of

the country economically and utilizing available resources. The Unites States struggles

to advance from the physiological and security rungs on Maslow's ladder. The

explanation for the placement on the ladder relates to the overwhelming need for

individuals to be self-serving and to focus on what the benefit is for them as individuals

versus the greater good of community (Gendzier, 1998).

The United States trade agreements with Latin American countries, North

American Free Trade Agreement (NAFTA) and the Central American Free Trade

Agreement (CAFTA), may be a risk to economic development of the United States.

Anner (2001) outlines that as we continue to develop foreign labor in economically

challenged countries; we run the risk of continually removing jobs from our business

sector.

Workforce Training and Economic Development 30

The United States faces challenges from low cost countries that provide

outsourcing options. Farrell, Laboissiere, and Rosenfeld (2005) have analyzed the impact

of off shoring and outsourcing for developed countries, and they have concluded that this

could result in 4.1 million jobs moving to offshore countries by 2008.

The United States is encountering challenges in its attempts to secure economic

growth for communities within its borders. It is possible to define some of these

challenges as free enterprise challenges that the United States has to face and overcome

as its own developing country. Focusing on building partnerships by collaborating with

communities, businesses, and local, state, and federal governments can reduce the

external factors and maintain business locally (Gold, 2004). The literature promotes the

opportunity to develop an infrastructure within small rural regions that would allow

additional options for businesses to retain economic opportunities in country versus off

shoring (Richard, 2005).

Wolfe and Gertler (2004) outline that the development of industry districts or

clusters in Canada are the result of entrepreneurs migrating to interact with other

entrepreneurs in a cluster in order to share innovative ideas, and evolve the community

into a cluster leading to economic development. Henderson (2002) promotes that

communities are looking for entrepreneurs to develop their innovations in communities in

much the same manner. Most entrepreneurs have a large complement of people in their

business and innovation networks. Communities can possibly establish greater

opportunities by engaging and presenting assets that are needed for the entrepreneurs to

produce innovative products and services. This level of cooperation can establish

Workforce Training and Economic Development 31

relationships across government, education, entrepreneurs, and business (Pierce &

Marshall, 1996).

In a review of existing literature, it is possible to theorize that infrastructure,

utility and technology are part of the economic development of communities. The

literature supports the theory that business and industry have the ability to develop an

industry cluster in a rural community. Toyota is one example based on its venture into

rural communities of the southern United States. Toyota used the portfolio of Alabama

to understand the assets of the rural region (CanagaRetna, 2004). As noted by Denton

(1994) diversifying by understanding what the community has to offer presents a plethora

of economic growth opportunities focused on the community.

Workforce Development Association

The research attempts to determine if workforce development and training can

sustain economic development for communities. The research can also develop a

determination if education is capable of collaborating with other community resources to

provide for economic development for the communities in which they live. There are

rural and urban colleges and universities that engage in establishing guidelines for

economic growth within a community they support. These groups are taking a leadership

role and soliciting conferences and forums to connect with the people involved in

understanding the needs of the community (Roman, 2007). The research looks at two

distinct criteria, urban and rural centers, with a specific look at the organizations that take

a leadership role in the economic development of the communities for which they reside.

Workforce Training and Economic Development 32

The literature indicates that workforce and education can be deemed as

infrastructure. The book titled, It Takes a Village (Clinton, 1996), it presents the impact

that a village has on the economic development of the people and the community.

Eller et al. (1998) outlined that educational systems needed to open themselves to

a greater understanding of what impact they have on the economic development of a

community. Additionally, taking a greater leadership role in the community by

developing and understanding what the community could offer are factors. The

development of a strategic vision for developing workforce training programs in any

given community can become a tool that can increase the vision of the community and its

leaders to take steps that would increase the prosperity of the community and raise the

level of living conditions that hence create economic growth (Kulaas, 2006).

Kastsinas and Moeck (2002) compare the ‘have’ and the ‘have–nots’ in the ability

to offer technology availability and training to different communities. In the study, they

outlined that most rural communities struggle to be technologically perceptive because of

the economic resources available to them. Colleges face similar issues because of

available funding to develop and deliver new educational programs that can affect the

development of economic centers to promote growth and educational opportunities.

Murray and Greer (1999) outline in a discussion about Northern Ireland larger

cities and how educators went into the communities of Northern Ireland to determine

how and what kind of training would benefit the communities to better understand what

economic development opportunities they could impact. These actions led to Northern

Ireland’s ability to compete in the global marketplace by providing a tailored set of

educational programs, which focused on manufacturing and services industries. Over the

Workforce Training and Economic Development 33

half-decade, Ireland as a whole has become a popular offshore site for European

businesses. The significant reason has been the level of workforce-capable resources to

meet demand.

In a recent study by Lu and Chen (2006) about the urbanization and the urban-

rural inequities during the development era dating from 1987-2001, the researchers

outline the economic development that is based on the wealthy rural communities that

have the means for education. The study outlines during this time that China based the

economic growth of the country on these wealthy rural communities, which soon would

become a new urban center providing workforce-capable resources.

Because of the world marketplace, there is an overwhelming need for talented,

skilled, and educated resources for the some multinational businesses. Khanna and

Rivkin (2006) present the case that in India, especially in urban cities like Delhi and

Bangalore workforce-capable resources are becoming scarce to fill the needs of

multinational corporations. These companies are willing to continue to make the

investments in these locations because India is producing educated resources in the

millions. In 2005, China and India graduated roughly one million engineers to the 75,000

graduated in the United States (Donofrio, 2006).

Freedman (2000) provides details on how educators are fighting to make a

difference in educational programs focused at developing a workforce ready resource by

seeking government grants to expand the ways education is delivered in urban centers.

The educators were seeking to deliver education that matches the needs of the community

as well as industry. The respective roadblocks are the related to the types of grants

available. The two kinds of grant funding are for funding materials for teachers'

Workforce Training and Economic Development 34

classrooms and professional development and those promoting school-wide programs,

such as school based-management, community, and parent outreach.

Kanji, Malek, Tambi, and Wallace (1999) compare the higher educational

institutions of the United States and Malaysia. The authors indicate there is a significant

difference in the quality of operation between the two countries. An important point of

reference is the level of quality provided from the Malaysian educational institutions.

There are governmental policies in Malaysia that provide direction for maintaining the

level of quality in process and value of education provided to meet the growing needs of

the cluster industries supported in the country. The authors indicate in comparison that

with the United States there is the unstructured nature of American education. There is

no standard for delivering quality or focus of educational needs to support industry.

Berry (2002) presents the process of applying ’quality systems’ to the educational

sectors of Australia over the last decade. The author’s observations have implied that the

method of delivering quality is focused on process and quality in student understanding

and has provided positive results in the level of learning and in the management of the

process. School communities were formed to review results and processes and

recommend solutions to positively impact results at a greater level. Senge (1990)

expresses the application of systems thinking, which could be applied in this instance, as

"a shift of mind from seeing parts to seeing wholes; a framework for seeing patterns and

inter-relationships rather than things; a discipline for seeing the structures that underlie

complex situations (p. 328)." The process within the Australian school system focused

greatly on the interactions and cross-organizational connections at the school, learning

center, district, and even at the country level to adjust to the changing needs by building a

Workforce Training and Economic Development 35

learning community established for the student, customer, and stakeholder (Nakata,

2006).

The Hampton Roads Innovation and Technological Education Consortium

(HITEC) and the Southeast Virginia Technology Association (SVTA) are groups that

were formed to provide business service and technology training development. The

consortium pooled the five local community colleges and universities to become a

supporting player in the program created by the VPEDC. HITEC was a key player in

developing regional cooperation among agencies involved in economic development and

technology transfer (Denton, 1994).

In a study about The Personal Responsibility and Work Opportunity Act

(PRWOA) of 1996, McCormick (2003) promotes that there has been little positive

impact in the training of an unskilled labor force within the City of New York. The

author indicates that there has been some improvement since the PRWOA has changed

its focus to utilize a “work first” approach to put underprivileged welfare recipients to

work and educate them along the way to develop the more desired soft skills and hard

skills to make an impact on the available workforce-capable resources.

In an attempt to increase the female workforce, GirlsREACH is a program

directed at high school girls ready to enter college. These girls will have an opportunity

to work directly with female mentor who will work directly to promote college and

opportunities in the workforce (City REACH-ing future female workforce, 2006).

The New Hampshire Higher Education Assistance Foundation (NHHEAF) is

providing education for parents and students to help in the determination of how to gain

financing for higher education in the institutions in the State. The effort is being

Workforce Training and Economic Development 36

conducted in conjunction with the local colleges to make the transition process to college

easier and contributing to the community and workforce development programs

(Discover U, 2006).

Organizations like the Regional Community College Initiative (RCCI) focus

energy on distressed rural communities that have poor relationships between government,

local businesses, and industry (Jensen, 2003). The Ford Foundation has invested $20

million in the RCCI to help economically challenged regions become viable for

development through workforce development planning, training programs, and education

through community involvement. Baldwin (2001) expresses that the foundation of RCCI

is leadership, strategic planning, inclusion, team building, community development, and

understanding of local cultures. Much of the effort of RCCI focuses on the need for

change and engagement at multiple levels, government, community, workforce

development agencies, and educational institutions. The 2003 Annual Report from the

Ford Foundation (2003) reports the necessity of building partnerships with local

community and local government leaders. The marketing process of promoting the what,

the why, and the benefit to the community is the first step in a series of steps to broaden

the development of the community. Establishing trust is critical to the objectives of the

program. Some of these communities operate under a local culture that needs to be

understood and then access can be made. RCCI attempts to drive community leadership

to become involved in the development of community workforce planning where the

local community colleges develop training programs that raise the level of condition by

where communities can compete for business and industry. One possible key to the

process is to become the catalyst to break down barriers in community-based programs.

Workforce Training and Economic Development 37

Community colleges and universities sometimes find themselves providing stratification,

or neutral ground to bring about change that could influence the community. Karl

Stauber, President, of the Northwest Area Foundation, offered this opening statement at

the Rural Community College Initiative (RCCI) conference in 2002, “Rural America is in

trouble, and you are part of its hope (Barnett, 2002, p.5).” Stauber’s challenge was meant

to raise the attention of two hundred collegiate educators from twenty-four colleges from

depressed areas in the southwest, Appalachia, south, and tribal reservations. These

regions were defined as the most critically economically distressed regions of the United

States.

The development of workforce resources to increase the assets of a rural

community is an additional criteria attempted by the RCCI. In some communities, there

are resource-poor colleges that cannot provide new programs that increase the learning

capabilities of the community. RCCI engages with the surrounding colleges and works to

develop intercollegiate partnerships that share the economies of scale to enhance the

delivery systems to the community. In some of these cases, it can coordinate governance

policies with state leadership to allow for the collaboration across the learning systems

(Chesson & Rubin, 2003). The RCCI attempts to use flexibility to change the conditions

to increase the potential economic value of a community.

Pittman (1998) express the criticality in some cases, depressed rural communities

are under the belief that skills training and even higher education are out of reach due to

cost and availability. RCCI has taken action that works with the community to present

options that can range from job skill training to outreach programs. It also presents

opportunities for local community leaders to apply for grant programs that are geared for

Workforce Training and Economic Development 38

developing communities to enhance the skills of the local workforce. Additionally, RCCI

attempts to provide assistance to the local educational institutions on development of

technology centers utilizing government grant money to entice business participation.

RCCI has a charter to focus on the social, educational, and economic directions of

communities by developing relationships to grow opportunities across a regional base.

These efforts could entail the development of research studies that create networks and

programs of people that will increase attention to the development of rural communities.

Richard (2005) reports that a new center has been established to research rural workforce

development and education, the National Research Center on Rural Education Support

has received a grant that will be utilized to train and retrain educators from rural

communities to raise the level of workforce development for the community. Included in

this program will be the application materials to deliver what they have learned.

The changing economic conditions present career opportunities across the globe.

Some of the students in rural communities get little or no visibility to these opportunities.

Some times what they see are the jobs that drive the community for which they live. The

RCCI in conjunction with Iowa Public Television coordinated the Star School grant to

provide regular programming that present professionals from different careers (Kiley,

2004). The program provides details and information to promote individuals who are

interested in specific careers. This process is enhanced by presenting materials that will

assist the student in understanding what local resources are available to pursue different

career options (Kiley, 2004).

Similar organizations to RCCI are not without challenges. The works these

organizations perform can require the development of outside supports. Richard (2005)

Workforce Training and Economic Development 39

expresses that there are certain rural communities that resist the process of organizations

like RCCI because they are culturally closed to outsiders. Educated outsiders who are

not part of the trusted class in the community lead some of the small rural community

colleges. Some of the efforts to promote training, and opportunity are ignored. Even

more difficult is the attempt to develop relationships with government and community

organizations (Pittman, 2006).

Richard (2005) continues to report the plight of rural America. In the report,

"Why Rural Matters 2005,” the author reports that there is a great divide that almost

could be viewed as a breach in understanding about the training and development needs

of rural American. Local, state and federal government have almost dismissed the needs

of these communities. Some of these training needs are not just related to primary

schools, but to rural colleges as well. The RCCI has engaged in a marketing campaign to

re-educate our governments on the specifics of these requirements and the impact that

failure to take action will have on the economic systems of these communities.

Rivard (2002) promoted the strategic planning accomplished by RCCI in the rural

community of Nelsonville, Ohio. This community suffered greatly due to its location in

the mountainous area of Ohio. It was suffering from a number of community ills, which

were the community’s ability to draw business and industry into the area. The RCCI in

conjunction with MDC Incorporated (a non-profit specializing in recognizing challenges

that affect workforce and economic development) collaborated with the community, local

government, and a scattered group of regional colleges to develop a strategic plan. The

plan focused on the assets of the regions and developed a training program that centered

around educating the community on how to recognize opportunities, such as land use,

Workforce Training and Economic Development 40

and technology. Additionally, as part of the training program was the development of

strategic plans and providing skills in grant writing, this resulted in a plethora of grants

that dramatically affected the development of the region into an economic center.

Maslow's Needs Hierarchy (1998) offers a significant explanation on how

people/organizations are categorized in the quest for development and growth. Much can

be said about the process of exchanging knowledge between economic development

organizations and workforce development organizations. There are varying positions on

Maslow's scale where organizations categorize themselves in the relationships they share.

When you compare small rural communities and the workforce skills they possess, the

position they have on Maslow's Needs Hierarchy (1998) most likely will fall within the

physiological and security hierarchy. The reasoning is supported by the limited

employment linkages with business and communities to assist economic development to

be successful because there is a limit to what growth can be achieved. An example of

this can be found in a number of rural communities that are agricultural in nature.

Highlands County, Florida is an excellent example. The county is defined as strictly

agricultural. The primary business is citrus and cattle. The economic viability of these

industries varies. Citrus is the largest of the agri-businesses in the area, but the support or

growth potential of this industry has waned over the last decade. The cattle industry has

also suffered over the last decade to maintain significant growth. The underlying concern

is the ability of the local economic development leadership to bring viable industries to

the area to support a medium- to low-income population (Englund, 2000).

Murray and Greer (1999) offer Northern Ireland as another example of a rural

center providing direction for developing economically by promoting the assets available

Workforce Training and Economic Development 41

and collaborating with education and government to create vitality in the number of rural

communities. One striking difference in the Northern Ireland model is the development

of volunteer communities to become educated in the economic development practices.

This effort reported by Department of Agriculture of Northern Ireland (DANI) indicates

that 450 community organizations with over 700 individuals trained in community

economic development and the management of economic development projects. This

effort created a web of individuals that engaged community groups, community

government, and educational institutions to participate in growing the opportunities of

rural Ireland. The results were an increase in jobs of over 400, 42 local projects, and the

support of roughly 24 million pounds (Scott, 2003).

In rural Washington State, the Community Economic Revitalization Board

(CERB) has taken steps to make an impact and create opportunities for rural

communities. Governor Locke offered this comment,

CERB support and funding is a powerful validation of the partnership momentum

that is building for technology job creation and training through North Central

Washington. This project was very well received at the state level and, because of

that; we have had a ton of inquiries from other communities anxious to replicate

what we are doing here (Dudley, 2000).

Locke and CERB are promoting technology projects focused on the development

of rural communities. The development of technology infrastructure will increase the

level of interest by technology companies or industries that would invest in the

community and its growth. As part of this investment, the CERB invested in the future

workforce by developing an industry complex to host the Community Technology

Workforce Training and Economic Development 42

Center. This center will be the focal point to develop the workforce to support the

economic growth of the rural region (Wenatchee Business Journal, 2003).

Johnston (1998) expresses that the concern goes deeper in providing training

programs for rural communities. The concern that arises is that rural children and adult

learners are not educated in technology, business, and workforce skills in and out of their

community. The opportunity for training and employment linkages within their

community is not a driving factor in rural schools.

Dolan (2004) expressed concern on an international level for the education

provided to Kenyan families located in the rural farming areas of the country. Much of

the effort to educate is focused on providing basic education in an attempt to maintain the

generational status quo and keep the farming districts populated with minimally educated

individuals.

Business Involvement

Bee (2004) writes that failure to involve the businesses in the community to assist

in the economic development planning is a critical failure to understand what industries

are best suited for the community. The importance of vitality for businesses is crucial to

community growth. The failure to involve local businesses in the economic planning can

have a significant impact on the perception of the community. Bee (2004) and Moses

(1991) emphasize the importance of utilizing business advocates to make connections

with possible businesses looking to relocate or develop new opportunities. The

indication of failing to accomplish this collaboration could result in the community being

labeled as anti-business. This leads to conditions that are indicative of slow responses to

inquiries.

Workforce Training and Economic Development 43

One example is the auto industry and the location of production plants to rural

communities in the southern United States. Examples are BMW in Spartanburg, South

Carolina; Mercedes Benz in Vance, Alabama; Toyota in Georgetown, Kentucky; and

Nissan in Madison County, Mississippi. Incentives were offered for the opportunity to

build the cluster. The government, local and federal, provided the economic

considerations based on the needs of the automakers. The automakers themselves had to

provide a complete list of requirements in order to prepare the community for its entry

(CanagaRetna, 2004).

The industry clusters were created by the automakers that brought with them the

other key support factors – the elements of a support structure. The Toyota plant in

Georgetown, Kentucky is designed to operate in the same Just-In-Time (JIT) productions

process as do all Toyota productions locations worldwide. The need for suppliers to be

located in surrounding areas is necessary to maintain the JIT process. Johnson Controls

located a plant in Georgetown to supply seats for the vehicles produced at the plant.

Additionally the trucking industry moved geographically close to support the specialized

needs of the plant. Move material within hours of the actual production time (Liker &

Wu, 2000).

Industry clusters are not without concerns claim Benneworth and Henry (2004).

Local governments in Kentucky, North Carolina, and Alabama indicate that the process

for developing an industry cluster for a region or community presents flaws that are

ignored by those involved in the process. One of those concerns centers on the granting

decision-making power to the industry attempting to develop the cluster. In some cases

the governments present economic proposals that can dramatically reduce the taxable

Workforce Training and Economic Development 44

base upon which the government relies. Additionally, the industry can create a situation

by which it can control entry by other industries and/or suppliers outside of their support

process. This can ultimately limit additional economic development for the region based

on its level of control.

The World Business Council for Sustainable Business (WBCSB) promotes the

concept of Corporate Social Responsibility (CSR) as critical for businesses to be morally

responsible and committed to the economic development with societal issues at the head

of any economic growth initiatives. Blowfield and Frynas (2005) indicate that there is

less CSR being applied in economic development activities. What the authors’ research

indicates is there is more of a non-social response to business objectives in business

planning and execution. The overwhelming driver is financial viability. This in some

cases is an abuse of the available workforce-capable resources in an underdeveloped area.

Moreover, corporations are capitalizing on setting the economic development growth to

meet corporate objectives versus collaborative goals for everyone’s interests.

The electric industry has some significant concerns about available workforce-

capable individuals. Nolan (2006) reports that power companies like American Electric

Power Company, the largest in the mid-western United States is creating partnerships

with a conglomerate of universities and colleges to create programs that will create a flow

of basic skilled resources to begin filling the expected retirement of the baby-boomers.

The electric industry is planning for the expected 25% loss in their workforce over the

next 2-5 years.

Economic development ultimately cannot be accomplished without some level of

collaboration with the exchange of knowledge between business, workforce development

Workforce Training and Economic Development 45

agencies, communities, and economic development agencies. There are a number of

factors that are involved for businesses to relocate, or plan new development in a specific

region or country. These factors in some cases look at cost as one of the critical drivers

in the process. These reviews focus on the cost of the available workforce, economic

conditions of the location to support the businesses’ long-term goals, and ultimately the

cost of re-educating the workforce. In some of these cases, the industry is looking at the

development of an industrial district or cluster that will be the ultimate economic driver

for that area. One significant example is the auto industry and the location of production

plants to rural communities in the southern United States. Examples are BMW in

Spartanburg, South Carolina; Mercedes Benz in Vance, Alabama; Toyota in Georgetown,

Kentucky; and Nissan in Madison County, Mississippi. The criteria for these selections

fell firmly on the available workforce, available training programs, and cost of living

within the area. Granted there were a number of incentives offered for the opportunity to

build the district, but it is important to remember that communication and knowledge

sharing occurred at all levels of discussion in order for these plants to be developed. The

government, local and federal, provided the economic considerations based on the needs

of the automakers. The local educational institutions were involved to present the

training capacity for startup and increased training and development to support future

development. Lastly, the automakers themselves had to provide a complete list of

requirements in order to prepare the community for its entry (CanagaRetna, 2004).

Fort Monmouth in Eatontown New Jersey faces closure and the impact to the

community would equate to a workforce of 5,200. Goldstein (2005) indicates that

closure of the base would affect a Cluster of 25 companies that receive contracts in

Workforce Training and Economic Development 46

excess of over $2 billion annually to support high-tech military research. The impact in

this case is not just the impact of closing a military base, but also the impact to the greater

community. Businesses that ultimately hire an even greater number in the workforce

along with the impact to the logistical support services in the community will be greatly

felt as well.

In comparison with the impact felt when Bethlehem Steel closed in Pittsburgh,

Pennsylvania in the 1970's, the community was devastated from the impact where the

entire community existed to support an industrial district. Ultimately, the importance of

knowledge sharing across government, community workforce development agencies, and

government agencies becomes critical to the success of the community at large.

Providing a forum for developing communication in an attempt to share knowledge

becomes critical in the attempt to move economic development forward. Wright (2004)

notes that community revitalization efforts that Middlesex, Connecticut attempted

included a workforce-training program directed at minorities and displaced workers. The

program came about because of a grant to increase safety at a hazardous waste plant. The

need for experienced workers was becoming critical, and the local government connected

with the plant leadership. This resulted in a knowledge transfer to the community. This

included help in creating a community advisory committee in conjunction with the local

community college to form the Brownfield Job Training Program. The ultimate result of

the process was the community commitment to the program as well as an economic

opportunity for the community.

Commissioner Karen Miller of Boone County Missouri was elected to take on the

role of President of the National Association of Counties (NACo). Ursery (2003)

Workforce Training and Economic Development 47

presented a case study for NACo of how government, education, workforce development

agencies, community leadership, and eventually business would benefit from the ability

to share knowledge that would grow the economic growth of non-urban areas of

Missouri. Commissioner Miller pointed out the most important issues on the radar were

economic development in conjunction with workforce training and development. When

asked how she, Commissioner Miller, planned to address the issues, the response

reinforced that there would have to be collaboration on some different levels. Workforce

development agencies, local, state, and the federal government would need to work on

strategic planning to grow rural communities that have had zero growth. This planning

would have to have a level focus of creating economic growth as well as the ability to

develop the workforce to support it.

Garfield County Oklahoma has developed a program that engages community

leadership to increase the quality of life within the rural community. Oklahoma's Career

Tech system has opened the eyes of some rural communities across the state. There has

been an economic decline in the heartland of America. To change the direction, the

formation of the Rural Leadership Garfield County program works to engage rural

community leadership and educate them on opportunities offered in the Career Tech

system. Conducting strategic planning and business workshops, they are attempting to

raise the social and economic standing of the rural community they proudly support

(Warnock, 2004).

Collaboration between business, workforce development agencies, educational

institutions and government agencies involved in economic development are plentiful. In

the case of RCCI, the ability to measure the success of the programs is difficult. One

Workforce Training and Economic Development 48

qualitative measurement promoted has been the impact on a developing workforce

involved in the process. Jenson (2003) reports on one assessment they conducted in

Appalachia. In developing an improved process of managing the workforce resources

and collaboration, they conducted a critical review to gather qualitative data. What they

determined, as the most prominent result was the workforce involved 'became changed'

by the experience. The change that was experienced was one of renewed commitment to

making the process better for the communities. The actual 'how' of this change is yet to

be determined, the commitment to the process appeared to be understood. The

underlying success will yet to be determined as the region continues to change.

Schmitz (2000) questioned the importance of collaboration between government

and business on clusters in Asia and Latin America. The four case studies presented a

unique set of qualitative conditions that are outlined in the review. From the study, the

author theorized that business and government that collaborate to develop the right

conditions for economic growth see greater success. The study also outlined that there

are additional levels of collaboration. Additionally, when competition applies pressure

there is an effort undertaken to take action in a vertical direction instead of a normal

horizontal collaborative process. Lastly, the study presented that vertical collaboration

increases at a higher level when critical quality improvements and an increase in speed

are needed. This collaborative effort is promoted when there seems to be a concern that

production is decreasing and affecting the business. Schmitz (2000) implies there are a

great number of additional research topics in the government and business collaboration

area of study.

Workforce Training and Economic Development 49

Bryant (1997) acknowledges the importance of collaboration between business,

government workforce development, and education, but adds that without involving the

ecological sector or the ’Ecotrust’ there are extreme risks to the local economy. One

aspect presented is that the Ecotrust completely understand the importance of economic

growth in rural communities across the world. The factors that need to be considered are

to ensure that the ecosystem can be maintained and even prosper under new development.

Ecotrust has built bioregional institutions to assist in its relationship with its partners.

Industry leaders, such as Intel, and some universities, support some of these bioregions.

These organizations utilize geographic information systems (GIS) and technologies

designed to measure and observe pattern changes in social, economic, and rural

ecosystems. In one such project, the Willapa Bay Project, Ecotrust recognized that the

local community did not have the knowledge to impact the needs of the project. Missing

from the workforce were business and marketing skills that were critical for the success

of the economic development venture. Ecotrust engaged Chicago's Shorebank

Corporation, the sponsor of the project, to engage with the local educational institutions

to begin a training program aimed at developing the workforce to meet the requirements

for the project (Bryant, 1997).

The literature also describes the importance of partnership, collaboration, and

evolution in order for economic development to evolve. Maslow's Hierarchy (1998)

teaches us the importance of understanding our needs and how those needs can be

satisfied. Infrastructure is more of an unknown in the literature. This can be viewed

from the perspective that infrastructure, specifically utility and technology, is defined

Workforce Training and Economic Development 50

more on how it can be changed to meet a need versus its necessity as a requirement to fill

a specific need.

The adopted slogan is “West Michigan is open for business!” The Grand Rapids

Business Journal (2006) reports that local governments in the Kentwood area have made

significant strides in collaborating with biotech companies to streamline all of the

government processes, and in conjunction working with all of the local colleges and

universities to develop training to support the industry cluster developing in the region.

The collaboration effort has provided significant results: $47M real property taxes,

$118M in personal taxes, 1,500 new jobs, from 2003 through 2005. In addition, the

government leadership has provided an open door policy to community leadership,

neighboring communities, and businesses to make a positive impact in the region.

CHAPTER 3: METHODOLOGY

Introduction

The purpose of this chapter is to outline the research methodology that was used

to establish the study that correlates the opinions of rural economic growth experts. The

correlation evaluates the perspectives of two age categories of “45 and Under” and

“Over 45”, with their value of workforce development as a positive factor for economic

growth of rural communities in the state of Florida.

By employing a correlation study, the researcher attempts to determine if the

differing age groups amongst workforce development organizations that participate in

this study apply different amounts of effort for workforce development within the

communities across the state of Florida. These workforce development leaders are

striving to develop missions, visions, and specialized programs to influence the growth

within the communities that are represented. This chapter defines the researcher’s

theoretical and philosophical framework for use of the correlation study.

Foundations for the Methodology

A correlation study examines the relationship that could exist between two or

more variables (Cooper & Schindler, 2003). The researcher uses hypotheses to identify

causes that promote certain observable facts. Correlation studies can include both

qualitative and quantitative data and methods. As a result, these studies can use a mixed

method approach.

The use of qualitative research offers specific definitions that in some cases are

difficult to agree upon across research communities. In all cases, the researcher needs to

detail those definitions and how they relate to the research. Creswell (2003) characterizes

Workforce Training and Economic Development 52

qualitative research as an approach where the researcher makes knowledgeable claims

based principally on perspectives that have validity. The claims can be perceived based

on patterns, or theory, that can derive a set of consistent variables that can be repeatable.

It can use such strategies as ethnographies, narratives, case studies and grounded theory

to provide unrestricted development themes to develop research (p. 8). Erickson

describes qualitative research as interpretive due to its involvement in “the study of the

immediate and local meanings of social actions for the actors involved in them” (Gall,

Gall, & Borg, 2003, p. 24).

Wallen and Fraenkel (2001) contend that “research studies that investigate the

quality of relationships, activities, situations, or materials are frequently referred to as

qualitative research” (p. 430). Creswell (2003) depicts that there are multiple variations

of qualitative methodologies. Some of the most common with distinctive relationships

for qualitative research are:

1. Interest in how subjects articulate life lessons and gain knowledge from that

perspective.

2. Participation in the subject matter’s environment, or natural setting to gain

knowledge from the comfort of the subject(s).

3. The analysis of data from a personal perspective resulting in research

interpretation.

4. Evolving research that changes as the researcher learns new information and

follows a new line of questioning.

5. The attempt to gain knowledge through multiple methods is utilized.

6. The researcher uses a real-time iterative process (Creswell, 2003).

Workforce Training and Economic Development 53

In this research, there were specific approaches such as ‘participation in the

subject matter’s environment, or natural setting to gain knowledge from the comfort of

the subjects’ and ‘the analysis of the data from a personal perspective resulting in

research interpretation.’ The researcher used a real-time iterative process to define the

qualitative research used by the researcher. Creswell (2003) promotes that individualized

research methods are utilized to meet exacting philosophical assumptions. Interpretive

paradigms are a result of the researcher defining a specific set of ideals about the specific

outcomes of the research. This can result in shortsighted views based on incomplete or

single-path research focused on a single-minded outcome (Gall, Gall, & Borg. 2003).

Creswell (2003) outlines four specific areas of knowledge claim paradigms: (a) post-

positivism, (b) constructivism, (c) advocacy/participatory, and (d) pragmatism. Crotty

(1998) indicates that a constructivist paradigm assumes that “meanings are constructed

by human beings as they engage with the world” and these subjects define the expression

of their knowledge based on the experiences of interacting in the world or environment

for which they live (p. 9). Moreover, Hein (1991) adds that a subject will change or

allow his/her assumptions to change as they learn more and can apply this to a more clear

theory of the information or perceptions they currently hold.

Creswell’s (2003) knowledge claim paradigm, a constructivist philosophy,

strongly supports the correlation method as the selection of this researcher. With the

ability to engage in inquiry promoted by the correlation methodology, the researcher

engaged in a learning process that constructed qualitative research as it is related to the

impact of workforce planning and development on the economic growth of communities

within the state of Florida.

Workforce Training and Economic Development 54

The definition of this study utilizing the correlation method empowered the

researcher to understand the perspectives of leadership engaged in the development of

economic growth and the workforce as this relates to creating growth in their rural

community. Cooper and Schindler (2003) note the uses of hypotheses to determine and

account for the causes that support certain phenomenon. Correlation studies can include

a combination of qualitative and quantitative data and methodologies. All of this offers

support for the use of a mixed method approach.

Research Design Strategy

The purpose of this study is exploratory. This study develops ideas regarding the

impact of workforce development programs based on the two age categories of “45 and

Under” and “Over 45”, as this relates to the advancement of economic growth of rural

communities in the state of Florida. In the research conducted by Cooper and Schindler

(2003), they state the “exploration is particularly useful when researchers lack a clear

idea of the problems they will meet during the study” (p. 23). The exploratory

correlation studies can be useful in situations where the researcher will need to explore

situations that may appear new in economic development circles (Cooper & Schindler,

2003). If variables may not be understood or well defined in these cases, a researcher

will need to put forth appropriate hypotheses. The continued emphasis on job creation

and economic growth in less than optimal communities will be necessary to understand

these positions from the professionals who engage in creating new opportunities. This

research study examines the correlation of workforce development programs and the

impact to rural communities in the state of Florida based on the two age categories of “45

and Under” and “Over 45” for the workforce development leadership.

Workforce Training and Economic Development 55

Sampling Design: Population and Sample

A panel drawn from the population of members in the National Rural Economic

Developers Association (NREDA) was the target population of the study. The

participants should have the professional knowledge to provide the necessary information

from the survey instrument based on their participation in this organization, as well as

based on their professional position defined in their membership application. The

participants are representative of the overall population and can represent the population

based on their position, and they hold the necessary information (Fraenkel & Wallen,

2001).

The survey population through the National Rural Economic Developers

Association (NREDA) includes the members of the NREDA, which includes educators,

workforce development professionals, as well as independent leaders of rural

communities. The research study relied on a volunteer sampling of interested NREDA

members to create the survey population. The NREDA consists of membership focused

on the development of rural communities. The membership consists of rural utility and

economic development professionals focusing on growing the economic position of rural

communities across the United States (About us, n.d.).

The research uses a sample plan for the correlation study seeking to correlate the

opinions of rural economic growth experts from the NREDA, in the two age categories of

“45 and Under” and “Over 45”, with their value of workforce development as a positive

factor for economic growth of rural communities in the State of Florida. The research

focused on interaction where it is determined that changes in the independent variable is

the reason for changes in the dependent variable.

Workforce Training and Economic Development 56

This research study utilized a sampling of professional individuals that take part

in the daily delivery of workforce development activities and are aware of the possible

impacts on economic development of the areas they live. The NREDA volunteer

participants were separated into two age categories of “45 and Under” and “Over 45”,

with their value of workforce development as a positive factor for economic growth of

rural communities in the State of Florida (Tashakkori & Teddlie, 2003). This type of

non-probability sampling technique is commonly associated with qualitative methods and

it can be effectively used in mixed methods studies (Tashakkori & Teddlie, 2003).

The population size of National Rural Economic Developers Association

(NREDA) is roughly 300 plus members scattered across rural communities in the United

States (About the National Rural Economic Developers Association, n.d.). There was an

email invitation to the membership of the NREDA requesting participation in the

research.

Utilizing a flexible design research study, the sample size can vary depending on

various factors that can include: (a) study’s scope, (b) nature of research, (c) quality of

the data, (d) design of the specific study, and (e) research method (Robson, 2002). The

scope of this proposed research focused on volunteer participants from the NREDA who

engage in supporting workforce development for economic growth in rural communities.

Measures

The correlation study consists of four basic features used in the overall process:

structured questioning, iteration, feedback, and anonymity for the respondents (Lang,

1995; Linstone & Turoff, 1979). The questionnaire process is the most common

approach for this mixed methods study, by structuring questions to focus on the research.

Workforce Training and Economic Development 57

The research study focuses on the initiation and management of programs provided by

NREDA professionals. Data collection was provided by a questionnaire developed with

a focus on the results of workforce development programs and the impact of economic

development in the rural communities the NREDA professionals support.

These research propositions were framed by these research questions:

1. Does business influence the level of workforce development in rural

communities to impact economic development?

2. Do communities influence level of workforce development to impact

economic development?

3. Do community workforce development agencies and educational systems

focused on developing workforce ready individuals’ impact economic

development?

Scheibe, Skutsch, and Schofer (1979) emphasize that the Likert-type scale is one

of the most commonly used in correlation research. One specific reason for the use of the

Likert-type scale is the ease of understanding and the ability to display research results

clearly. Turoff and Hiltz (1995) promote the use of the Likert-type scale with the

correlation method because of the iterative process of managing responses that are based

on human judgment, opinion, and knowledge from the panel’s expertise. The ability to

compare and share information in this manner increases the open sharing of information.

Data Collection Procedures

All participants from National Rural Economic Developers Association (NREDA)

received a special invitation e-mail that linked them to the my3q.com questionnaire POP

application. The survey process was designed to provide guaranteed anonymity with the

Workforce Training and Economic Development 58

researcher having access to responses. All survey data was reviewed and tabulated

utilizing the Statistical Package of the Social Sciences (SPSS). The entire data collection

process was conducted online using e-mail and the my3q.com survey system.

Pilot Testing

A researcher-developed data collection questionnaire instrument requires that

field studies or pilot studies be completed. Pilot studies can be small versions of the

proposed research study. These assist in determining the feasibility of the proposed study

(Robson, 2002). The developed data collection questionnaire instrument was tested

during a pilot study utilizing 11 respondents. The results were used to adjust the data

collection questionnaire instrument before it was used in the final research study. The

wording on two questions was clarified as a result of this pilot testing.

The pilot was used to establish the questions that were used as part of the

correlation research. The researcher was looking for a minimum of eight with a

maximum of 16 participants as part of the pilot who are members of the National Rural

Economic Developers Association (NREDA) and consisted of economic development

professionals ranging from Directors of Economic Councils to Development

Coordinators. There were a total of 11 participants. These individuals provided valuable

feedback to the overall process. These members were asked to participate in the overall

research.

Data Analysis Procedures

The Statistical Package of the Social Sciences (SPSS) software was used on the

survey results to determine the mean and standard deviations. The Likert 5-point scale

was used on the survey instrument. Items that are scored with a 3.0 and above were

Workforce Training and Economic Development 59

analyzed in the final evaluation as possible results and impact areas as they related to the

research conducted in the following areas: (a) does business influence the level of

workforce development in rural communities to impact economic development? (b) do

communities influence level of workforce development to impact economic

development? and (c) do community workforce development agencies and educational

systems focused on developing workforce ready individual’s impact economic

development? SPSS analyses were used to locate items that have comparatively stronger

differences in opinions as they related to the NREDA volunteer participants separated in

the two age categories of “45 and Under” and “Over 45”, with their value of workforce

development as a positive factor for economic growth of rural communities in the State

of Florida. It is important to note that the focus of the study does not rely on personal

comments of the individuals, but the collective responses of the participants (Lee, 2002;

Scheibe, Skutsch, & Schofer, 1979).

Limitations of Methodology

The correlation research methodology faces criticism in some circles of the

research community. There are other researchers like Makridakis and Wheelright (1977)

that indicate that the correlation methodology lacks accuracy and is questionable as a

scientific methodology that produces valued results for any research (Lang, 1995). Lee

(2002) notes that there is hardly any tangible information in research text to support its

use in research studies. Makridakis and Wheelright (1977) also present three criticisms

in the correlation methodology: (a) the use of expert opinions can result in low reliability

of the results, (b) the questionnaires used may be ambiguous resulting in questionable

data, and (c) the assessment of the degree of expertise of the panelists can be

Workforce Training and Economic Development 60

questionable. Steel, Shane, and Griffeth (2003) offer caution that to ensure that the

correlation research is without question, and these authors caution the researcher must not

change the responses of the participants. The correlation methodology has provided

significant results in the past three decades (Steel, Shane, & Griffeth, 2003).

Internal Validity

Utilizing the correlation methodology provides some very specific concerns.

Lang (1995) cites Masini who believes that the researcher maintains bias from the start of

the study. This ultimately occurs in the development of the participants for they may

present bias to the subject in favor of the research. The researcher selected

knowledgeable economic development and workforce development professionals from

the National Rural Economic Developers Association (NREDA).

Creswell (2003) promotes two very pointed safeguards to reduce the risk of bias

by the researcher; (a) the researcher must outline all biases as they relate to any part of

the study; and (b) development of the survey instrument should be created in or as a part

of an unbiased community. In response to these safeguards, this researcher has put forth

his interest in how workforce development and training influences economic

development. The researcher also recognizes that there are some other players involved

in both workforce development and economic development that influence positive and

negative outcomes. In order to prevent any bias in the question development for this

study, the researcher relied on a group of professionals in the field to develop the survey

instrument questions. The researcher did not have any personal or professional contact

with these individuals. Linstone and Turoff (1979) recommend developing questions that

have simple descriptive statements of 20-25 words that are associated with a limited

Workforce Training and Economic Development 61

number of selected responses. There should also be an open forum for the respondents of

the panel to expand on their responses, which can add positively to future rounds of

questioning (Lang, 1995, p. 10).

External Validity

Yin (2003) clearly articulates that there is still a stigma associated with most

qualitative research methods because the populations receiving the associated data are

concerned about opinions and biases contaminating results of the study in question. In

contrast to other methodologies, the correlation method utilizes a survey instrument and

because the process is iterative, the application of questions change focus specifically on

the research. The qualitative methodologies, when used effectively and without bias by

the researcher, can and will present a focus on the studied content preventing the research

from moving beyond the initial scope of the study. This research adds to the body of

knowledge for future researchers to validate and/or expand the knowledge presented in

relationship to workforce development and training and its impact on economic

development.

Expected Findings

The researcher theorized that there are outside influences that are affecting

workforce development, training, and reducing its ability to have a positive impact on

economic development to rural communities in Florida. These influences are, in some

cases, out of the control of community and business leaders, which ultimately leads to a

movement to provide programs outside of these influences in order to gain control of

economic development. The researcher expected to find issues that relate to the

workforce in general. The researcher believes there is a gap of understanding within the

Workforce Training and Economic Development 62

workforce on what role they, as the workforce, play to grow themselves and the

community in which they live. Shankar (2007) promotes the performance of rehab

training facilities in the city of Baltimore are turning out trade workers from the

workforce development programs with skills that are defined by the business community.

The reason for the success is based on the level of communication within the Baltimore

business and workforce development communities. In Indiana, Snyder (2007) discusses

the impact poor communication between government, community businesses, and local

community colleges and the lack of training and college programs to develop the next

level of workforce to support the manufacturing jobs that are leaving the state in mass.

Ethical Issues

One significant expectation from this study was the anonymity of the participants

of the panels. Ethically, and for the validity of the study, protecting the panels from

psychological or even physical harm is crucial and should be one of the primary

directives (Fraenkel & Wallen, 2001). In order for all studies that rely on individuals to

volunteer their time and knowledge, it is imperative that there is a complete disclosure

about the purpose of the study in conjunction with allowing individuals the right to ask

questions prior to participation (Creswell, 2003). The use of secure technology clearly

provides for the anonymity of the panel participants. The use of the my3q.com survey

system provides security for the users and the researcher did not know who individually

responded, only that there are responses for analysis. The correlation method is

structured to manage the responses from the participants. In order to promote honesty

and integrity of the responses, it also prevents coercion from other participants to keep

the integrity of the study intact (Linstone & Turoff, 1979).

Workforce Training and Economic Development 63

Conclusion

In order to understand the critical factors that have an influence on workforce

development and training and its impact on economic development in rural communities

in Florida, it is necessary to keep the research questions as the focus of the study: (a)

does business influence the level of workforce development in rural communities to

impact economic development? (b) do communities influence level of workforce

development to impact economic development? and (c) do community workforce

development agencies and educational systems focused on developing workforce ready

individual’s impact economic development?

In order to maximize the economic development and workforce development and

training professionals’ input to this research, the correlation methodology provided the

right qualitative research process to pull the knowledge from a large knowledgebase.

Linstone and Turoff (1979) acknowledge that the correlation methodology is excellent at

structuring groups of necessary resources of a study to manage a complex issue, which

would lend to the point that the issue of workforce development’s impact on economic

development is a complex issue.

Technology advances the ability of the correlation method to be more time

sensitive and effective over long distances, or globally if applicable to a study. Utilizing

the Statistical Package for Social Sciences (SPSS) along with e-mail and survey

applications like my3q.com, data was processed and available for effective use within

hours versus months.

CHAPTER 4. DATA COLLECTION AND ANALYSIS

Introduction

The purpose of this chapter is to provide the results of the correlation research that

correlates the opinions of rural economic growth experts. The correlation evaluated the

perspectives of two age categories of “45 and Under” and “Over 45”, with their value of

workforce development as a positive factor for economic growth of rural communities in

the State of Florida.

Review of Research Questions and Hypotheses

The research questions and hypotheses are presented in Chapter 1. As a review,

the study develops ideas regarding the impact of workforce development programs based

on the two age categories of “45 and Under” and “Over 45”,as they relate to the

advancement of economic growth of rural communities in the state of Florida. The

research propositions were framed by these research questions:

1. Does business influence the level of workforce development in rural

communities to impact economic development?

2. Do communities influence level of workforce development to impact

economic development?

3. Do community workforce development agencies and educational systems

focused on developing workforce ready individuals’ impact economic

development?

The researcher’s hypotheses:

1. National Rural Economic Developers Association members who self-identify

in the researcher’s survey as “45 and Under” will be better prepared than

Workforce Training and Economic Development 65

those who self-identify as “Over 45” to recognize the influence that

businesses have on the level of workforce development in rural communities

to impact economic development.

2. National Rural Economic Developers Association members who self-identify

in the researcher’s survey as “Over 45” will be better prepared than those

who self-identify as “45 and Under” to recognize the influence that

communities have on the level of workforce development in rural

communities to impact economic development.

3. National Rural Economic Developers Association members who self-identify

in the researcher’s survey as “45 and Under” and those who self-identify as

“Over 45” will both recognize that community workforce development

agencies and educational systems focused on developing workforce ready

individuals in rural communities do impact economic development.

Review of Data Collection

Data collection was accomplished through the use of a questionnaire instrument

created the researcher. The survey instrument consisted of 15 questions, five questions

for each of the research propositions. The five questions for each proposition were the

built on a consistent premise to maintain the same context and consistency for the two

specific age groups providing their self-assessment of opinions and practices. The

participating subjects were able to present and comment on their individual ideas

regarding the impact of workforce development programs based on the two age

categories of “45 and Under” and “Over 45”, as it relates to the advancement of

economic growth of rural communities in the state of Florida. The participants in the

Workforce Training and Economic Development 66

survey were members of the National Rural Economic Developers Association

(NREDA). The researcher, with the assistance of Ms. Sherry Rose, President, Ms. Molly

Lopez, Executive Director, of the NREDA, and all 254 members were polled to

participate, utilizing electronic communication that provided a link to a web-based survey

to protect the anonymity of the participants. The end results were 97 members voluntarily

took part in the research survey. Please see below for an overview:

Table 1. Survey Response

Issued Returned

Workforce Development Survey 254 97

___________________________________________________________

The table below provides an overview of the self-identified age categories of the

participants as recorded by the researcher’s survey instrument. This provides some

insight into the age category demographics of the research study population.

Additionally, the hypotheses deal with the research study population's age categories.

Table 2. Participant Age Categories as Recorded by the Researcher’s Survey Instrument

___________________________________________________________ “45 and Under” “Over 45”

47 50

Pilot Study

The pilot study data collection and validation of the survey instrument was

performed with 11 members of the National Rural Economic Developers Association

(NREDA) who were individuals that the researcher had been involved with on economic

Workforce Training and Economic Development 67

development forums over the past few years. This pilot group provided feedback on the

content of the survey instrument and its refinement. The pilot was completed using 11

members of the NREDA membership. The pilot group assisted in rephrasing two

questions that were difficult to understand. The pilot group members provided useful

specifics that guided the researcher to clarify the focus of the survey questions. These 11

pilot participants were included in the overall research study.

Findings Related to Hypothesis 1

Hypothesis 1 states: National Rural Economic Developers Association members

who self-identify in the researcher’s survey as “45 and Under” will be better prepared

than those who self-identify as “Over 45” to recognize the influence that businesses have

on the level of workforce development in rural communities to impact economic

development.

Question 1

Question 1 states: I feel that it is important that local businesses influence the

level of workforce development in rural communities.

The null hypothesis states: H0 – There is no significant difference between the

responses of the age groups "45 and Under" and "Over 45".

The alternate hypothesis states: H1 – There is a significant difference between

the responses of the age groups "45 and Under" and "Over 45".

The table below provides an overview of the participants' age categories and

responses. Please see Appendix B1 for further results.

Workforce Training and Economic Development 68

Question 1 Age Categories and Responses

Table 3. Question 1 Age Categories and Responses

Strongly Agree Neither Disagree Strongly Agree A/D Disagree “45 and Under” 1 11 6 16 13 (self-identified)

“Over 45” 1 9 11 21 8 (self-identified)

The decision takes into consideration that the Pearson chi-square observed

Asymp. Sig. 2-sided is .486, which is above the significance level of .05. Therefore, the

null hypothesis above cannot be rejected. Additionally, the Lambda statistic is calculated

as .149. The Lambda statistic describes the proportional error reduction when predicting

the dependent variable with the independent variable. A value of 0 for Lambda means

the independent variable is of no help in predicting the dependent variable. When two

variables are statistically independent, Lambda is 0. However, a Lambda of 0 does not

always imply statistical independence. This value of .149 implies that the age

demographics of the respondents is a fairly good predictor of the dependent variable or

the observed response.

The nominal directional measures indicate the strength as well as the significance

of the relationship between the row and column variables of a crosstabulation. The value

of each statistic can range from 0 to 1, and this indicates the proportional reduction in

error in predicting the value of one variable, based on the value of the other variable. The

Goodman and Kruskal tau is a modification of Lambda. This means instead of predicting

the group with the largest number of cases when making a prediction, one uses a

Workforce Training and Economic Development 69

proportional prediction rule. Each category is viewed with a probability equal to the

percentage proportion of cases in that category. The Goodman and Kruskal tau values of

.036 and .011 indicate that the error rate has been reduced by 3.6% and 1.1%, for the age

demographics dependent and observed frequencies dependent, respectively, over what

could be expected by random chance.

Question 2

Question 2 states: I feel that it is important that outside businesses seeking to

relocate influence the level of workforce development in rural communities.

The null hypothesis states: H0 – There is no significant difference between the

responses of the age groups "45 and Under" and "Over 45".

The alternate hypothesis states: H1 – There is a significant difference between

the responses of the age groups "45 and Under" and "Over 45".

The table below provides an overview of the participants' age categories and

responses. Please see Appendix B2 for further results.

Question 2 Age Categories and Responses

Table 4. Question 2 Age Categories and Responses

Strongly Agree Neither Disagree Strongly Agree A/D Disagree “45 and Under” 3 19 6 10 9 (self-identified)

“Over 45” 2 19 10 17 2 (self-identified)

Workforce Training and Economic Development 70

The decision takes into consideration that the Pearson chi-square observed

Asymp. Sig. 2-sided is .117, which is above the significance level of .05. Therefore, the

null hypothesis above cannot be rejected. Additionally, the Lambda statistic is calculated

as .170. The Lambda statistic describes the proportional error reduction when predicting

the dependent variable with the independent variable. A value of 0 for Lambda means

the independent variable is of no help in predicting the dependent variable. When two

variables are statistically independent, Lambda is 0. However, a Lambda of 0 does not

always imply statistical independence. This value of .170 implies that the age

demographics of the respondents is a fairly good predictor of the dependent variable or

the observed response.

The nominal directional measures indicate the strength as well as the significance

of the relationship between the row and column variables of a crosstabulation. The value

of each statistic can range from 0 to 1, and this indicates the proportional reduction in

error in predicting the value of one variable, based on the value of the other variable. The

Goodman and Kruskal tau is a modification of Lambda. This means instead of predicting

the group with the largest number of cases when making a prediction, one uses a

proportional prediction rule. Each category is viewed with a probability equal to the

percentage proportion of cases in that category. The Goodman and Kruskal tau values of

.076 and .016 indicate that the error rate has been reduced by 7.6% and 1.6%, for the age

demographics dependent and observed frequencies dependent, respectively, over what

could be expected by random chance.

Question 3

Workforce Training and Economic Development 71

Question 3 states: I feel that it is important for businesses to be able to work with

local training organizations to influence the level of workforce development in rural

communities.

The null hypothesis states: H0 – There is no significant difference between the

responses of the age groups "45 and Under" and "Over 45".

The alternate hypothesis states: H1 – There is a significant difference between

the responses of the age groups "45 and Under" and "Over 45".

The table below provides an overview of the participants' age categories and

responses. Please see Appendix B3 for further results.

Question 3 Age Categories and Responses

Table 5. Question 3 Age Categories and Responses

Strongly Agree Neither Disagree Strongly Agree A/D Disagree “45 and Under” 4 33 10 0 0 (self-identified)

“Over 45” 2 33 10 4 1 (self-identified)

The decision takes into consideration that the Pearson chi-square observed

Asymp. Sig. 2-sided is .233, which is above the significance level of .05. Therefore, the

null hypothesis above cannot be rejected. Additionally, the Lambda statistic is calculated

as .043. The Lambda statistic describes the proportional error reduction when predicting

the dependent variable with the independent variable. A value of 0 for Lambda means

the independent variable is of no help in predicting the dependent variable. When two

Workforce Training and Economic Development 72

variables are statistically independent, Lambda is 0. However, a Lambda of 0 does not

always imply statistical independence. This value of .043 implies that the age

demographics of the respondents may not be a good predictor of the dependent variable

or the observed response.

The nominal directional measures indicate the strength as well as the significance

of the relationship between the row and column variables of a crosstabulation. The value

of each statistic can range from 0 to 1, and this indicates the proportional reduction in

error in predicting the value of one variable, based on the value of the other variable. The

Goodman and Kruskal tau is a modification of Lambda. This means instead of predicting

the group with the largest number of cases when making a prediction, one uses a

proportional prediction rule. Each category is viewed with a probability equal to the

percentage proportion of cases in that category. The Goodman and Kruskal tau values of

.058 and .006 indicate that the error rate has been reduced by 5.8% and 0.6%, for the age

demographics dependent and observed frequencies dependent, respectively, over what

could be expected by random chance.

Question 4

Question 4 states: I believe that it is important for businesses to have a

cooperative plan in place with local training organizations to influence the level of

workforce development in rural communities.

The null hypothesis states: H0 – There is no significant difference between the

responses of the age groups "45 and Under" and "Over 45".

The alternate hypothesis states: H1 – There is a significant difference between

the responses of the age groups "45 and Under" and "Over 45".

Workforce Training and Economic Development 73

The table below provides an overview of the participants' age categories and

responses. Please see Appendix B4 for further results.

Question 4 Age Categories and Responses

Table 6. Question 4 Age Categories and Responses

Strongly Agree Neither Disagree Strongly Agree A/D Disagree “45 and Under” 3 35 7 2 0 (self-identified)

“Over 45” 2 32 11 3 2 (self-identified)

The decision takes into consideration that the Pearson chi-square observed

Asymp. Sig. 2-sided is .504, which is above the significance level of .05. Therefore, the

null hypothesis above cannot be rejected. Additionally, the Lambda statistic is calculated

as .085. The Lambda statistic describes the proportional error reduction when predicting

the dependent variable with the independent variable. A value of 0 for Lambda means

the independent variable is of no help in predicting the dependent variable. When two

variables are statistically independent, Lambda is 0. However, a Lambda of 0 does not

always imply statistical independence. This value of .085 implies that the age

demographics of the respondents is a somewhat good predictor of the dependent variable

or the observed response.

The nominal directional measures indicate the strength as well as the significance

of the relationship between the row and column variables of a crosstabulation. The value

of each statistic can range from 0 to 1, and this indicates the proportional reduction in

Workforce Training and Economic Development 74

error in predicting the value of one variable, based on the value of the other variable. The

Goodman and Kruskal tau is a modification of Lambda. This means instead of predicting

the group with the largest number of cases when making a prediction, one uses a

proportional prediction rule. Each category is viewed with a probability equal to the

percentage proportion of cases in that category. The Goodman and Kruskal tau values of

.034 and .010 indicate that the error rate has been reduced by 3.4% and 1.0%, for the age

demographics dependent and observed frequencies dependent, respectively, over what

could be expected by random chance.

Question 5

Question 5 states: I value the input of business interests in influencing the level of

workforce development in rural communities.

The null hypothesis states: H0 – There is no significant difference between the

responses of the age groups "45 and Under" and "Over 45".

The alternate hypothesis states: H1 – There is a significant difference between

the responses of the age groups "45 and Under" and "Over 45".

The table below provides an overview of the participants' age categories and

responses. Please see Appendix B5 for further results.

Workforce Training and Economic Development 75

Question 5 Age Categories and Responses

Table 7. Question 5 Age Categories and Responses

Strongly Agree Neither Disagree Strongly Agree A/D Disagree “45 and Under” 6 30 10 1 0 (self-identified)

“Over 45” 3 32 12 3 0 (self-identified)

The decision takes into consideration that the Pearson chi-square observed

Asymp. Sig. 2-sided is .541, which is above the significance level of .05. Therefore, the

null hypothesis above cannot be rejected. Additionally, the Lambda statistic is calculated

as .064. The Lambda statistic describes the proportional error reduction when predicting

the dependent variable with the independent variable. A value of 0 for Lambda means

the independent variable is of no help in predicting the dependent variable. When two

variables are statistically independent, Lambda is 0. However, a Lambda of 0 does not

always imply statistical independence. This value of .064 implies that the age

demographics of the respondents is a somewhat good predictor of the dependent variable

or the observed response.

The nominal directional measures indicate the strength as well as the significance

of the relationship between the row and column variables of a crosstabulation. The value

of each statistic can range from 0 to 1, and this indicates the proportional reduction in

error in predicting the value of one variable, based on the value of the other variable. The

Goodman and Kruskal tau is a modification of Lambda. This means instead of predicting

the group with the largest number of cases when making a prediction, one uses a

Workforce Training and Economic Development 76

proportional prediction rule. Each category is viewed with a probability equal to the

percentage proportion of cases in that category. The Goodman and Kruskal tau values of

.022 and .003 indicate that the error rate has been reduced by 2.2% and 0.3%, for the age

demographics dependent and observed frequencies dependent, respectively, over what

could be expected by random chance.

Overall Discussion of Hypothesis 1 Findings

In the tests performed, the Pearson chi-square observed Asymp. Sig. 2-sided

levels for questions 1, 2, 3, 4, and 5 were above the significance level of .05. Therefore,

the null hypothesis for each cannot be rejected. It is interesting to note that there is no

significant difference in the responses between the age categories of “45 and Under” and

“Over 45”. This suggests that each age category is equally prepared to recognize the

influence that businesses have on the level of workforce development in rural

communities to impact economic development. This is interesting since the division of

“45 and Under” and “Over 45” categories in the National Rural Economic Developers

Association (NREDA) was nearly even with 47 participants “45 and Under” and 50

participants “Over 45”. Therefore, it can be anticipated that there would be about equal

influence by these NREDA members in this area of economic development.

Findings Related to Hypothesis 2

Hypothesis 2 states: National Rural Economic Developers Association members

who self-identify in the researcher’s survey as “Over 45” will be better prepared than

those who self-identify as “45 and Under” to recognize the influence that communities

have on the level of workforce development in rural communities to impact economic

development.

Workforce Training and Economic Development 77

Question 1

Question 1 states: I feel that local community leaders influence the level of

workforce development to impact economic development.

The null hypothesis states: H0 – There is no significant difference between the

responses of the age groups "45 and Under" and "Over 45".

The alternate hypothesis states: H1 – There is a significant difference between

the responses of the age groups "45 and Under" and "Over 45".

The table below provides an overview of the participants' age categories and

responses. Please see Appendix C1 for further results.

Question 1 Age Categories and Responses

Table 8. Question 1 Age Categories and Responses

Strongly Agree Neither Disagree Strongly Agree A/D Disagree “45 and Under” 2 31 7 7 0 (self-identified)

“Over 45” 2 26 15 7 0 (self-identified)

The decision takes into consideration that the Pearson chi-square observed

Asymp. Sig. 2-sided is .354, which is above the significance level of .05. Therefore, the

null hypothesis above cannot be rejected. Additionally, the Lambda statistic is calculated

as .106. The Lambda statistic describes the proportional error reduction when predicting

the dependent variable with the independent variable. A value of 0 for Lambda means

the independent variable is of no help in predicting the dependent variable. When two

Workforce Training and Economic Development 78

variables are statistically independent, Lambda is 0. However, a Lambda of 0 does not

always imply statistical independence. This value of .106 implies that the age

demographics of the respondents is a fairly good predictor of the dependent variable or

the observed response.

The nominal directional measures indicate the strength as well as the significance

of the relationship between the row and column variables of a crosstabulation. The value

of each statistic can range from 0 to 1, and this indicates the proportional reduction in

error in predicting the value of one variable, based on the value of the other variable. The

Goodman and Kruskal tau is a modification of Lambda. This means instead of predicting

the group with the largest number of cases when making a prediction, one uses a

proportional prediction rule. Each category is viewed with a probability equal to the

percentage proportion of cases in that category. The Goodman and Kruskal tau values of

.034 and .018 indicate that the error rate has been reduced by 3.4% and 1.8%, for the age

demographics dependent and observed frequencies dependent, respectively, over what

could be expected by random chance.

Question 2

Question 2 states: I feel that it is important that individual citizens influence the

level of workforce development to impact economic development.

The null hypothesis states: H0 – There is no significant difference between the

responses of the age groups "45 and Under" and "Over 45".

The alternate hypothesis states: H1 – There is a significant difference between

the responses of the age groups "45 and Under" and "Over 45".

Workforce Training and Economic Development 79

The table below provides an overview of the participants' age categories and

responses. Please see Appendix C2 for further results.

Question 2 Age Categories and Responses

Table 9. Question 2 Age Categories and Responses

Strongly Agree Neither Disagree Strongly Agree A/D Disagree “45 and Under” 5 30 6 6 0 (self-identified)

“Over 45” 4 29 13 4 0 (self-identified)

The decision takes into consideration that the Pearson chi-square observed

Asymp. Sig. 2-sided is .389, which is above the significance level of .05. Therefore, the

null hypothesis above cannot be rejected. Additionally, the Lambda statistic is calculated

as .085. The Lambda statistic describes the proportional error reduction when predicting

the dependent variable with the independent variable. A value of 0 for Lambda means

the independent variable is of no help in predicting the dependent variable. When two

variables are statistically independent, Lambda is 0. However, a Lambda of 0 does not

always imply statistical independence. This value of .085 implies that the age

demographics of the respondents is a somewhat good predictor of the dependent variable

or the observed response.

The nominal directional measures indicate the strength as well as the significance

of the relationship between the row and column variables of a crosstabulation. The value

of each statistic can range from 0 to 1, and this indicates the proportional reduction in

Workforce Training and Economic Development 80

error in predicting the value of one variable, based on the value of the other variable. The

Goodman and Kruskal tau is a modification of Lambda. This means instead of predicting

the group with the largest number of cases when making a prediction, one uses a

proportional prediction rule. Each category is viewed with a probability equal to the

percentage proportion of cases in that category. The Goodman and Kruskal tau values of

.031 and .010 indicate that the error rate has been reduced by 3.1% and 1.0%, for the age

demographics dependent and observed frequencies dependent, respectively, over what

could be expected by random chance.

Question 3

Question 3 states: I feel that it is important that local community groups influence

the level of workforce development to impact economic development.

The null hypothesis states: H0 – There is no significant difference between the

responses of the age groups "45 and Under" and "Over 45".

The alternate hypothesis states: H1 – There is a significant difference between

the responses of the age groups "45 and Under" and "Over 45".

The table below provides an overview of the participants' age categories and

responses. Please see Appendix C3 for further results.

Workforce Training and Economic Development 81

Question 3 Age Categories and Responses

Table 10. Question 3 Age Categories and Responses

Strongly Agree Neither Disagree Strongly Agree A/D Disagree “45 and Under” 4 29 9 5 0 (self-identified)

“Over 45” 4 31 13 2 0 (self-identified)

The decision takes into consideration that the Pearson chi-square observed

Asymp. Sig. 2-sided is .575, which is above the significance level of .05. Therefore, the

null hypothesis above cannot be rejected. Additionally, the Lambda statistic is calculated

as .064. The Lambda statistic describes the proportional error reduction when predicting

the dependent variable with the independent variable. A value of 0 for Lambda means

the independent variable is of no help in predicting the dependent variable. When two

variables are statistically independent, Lambda is 0. However, a Lambda of 0 does not

always imply statistical independence. This value of .064 implies that the age

demographics of the respondents is a somewhat good predictor of the dependent variable

or the observed response.

The nominal directional measures indicate the strength as well as the significance

of the relationship between the row and column variables of a crosstabulation. The value

of each statistic can range from 0 to 1, and this indicates the proportional reduction in

error in predicting the value of one variable, based on the value of the other variable. The

Goodman and Kruskal tau is a modification of Lambda. This means instead of predicting

Workforce Training and Economic Development 82

the group with the largest number of cases when making a prediction, one uses a

proportional prediction rule. Each category is viewed with a probability equal to the

percentage proportion of cases in that category. The Goodman and Kruskal tau values of

.021 and .004 indicate that the error rate has been reduced by 2.1% and 0.4%, for the age

demographics dependent and observed frequencies dependent, respectively, over what

could be expected by random chance.

Question 4

Question 4 states: I believe that it is important for local communities to have input

into a cooperative plan with local training organizations to influence the level of

workforce development to impact economic development.

The null hypothesis states: H0 – There is no significant difference between the

responses of the age groups "45 and Under" and "Over 45".

The alternate hypothesis states: H1 – There is a significant difference between

the responses of the age groups "45 and Under" and "Over 45".

The table below provides an overview of the participants' age categories and

responses. Please see Appendix C4 for further results.

Question 4 Age Categories and Responses

Table 11. Question 4 Age Categories and Responses

Strongly Agree Neither Disagree Strongly Agree A/D Disagree “45 and Under” 4 32 7 4 0 (self-identified)

“Over 45” 6 28 13 3 0 (self-identified)

Workforce Training and Economic Development 83

The decision takes into consideration that the Pearson chi-square observed

Asymp. Sig. 2-sided is .472, which is above the significance level of .05. Therefore, the

null hypothesis above cannot be rejected. Additionally, the Lambda statistic is calculated

as .106. The Lambda statistic describes the proportional error reduction when predicting

the dependent variable with the independent variable. A value of 0 for Lambda means

the independent variable is of no help in predicting the dependent variable. When two

variables are statistically independent, Lambda is 0. However, a Lambda of 0 does not

always imply statistical independence. This value of .106 implies that the age

demographics of the respondents is a fairly good predictor of the dependent variable or

the observed response.

The nominal directional measures indicate the strength as well as the significance

of the relationship between the row and column variables of a crosstabulation. The value

of each statistic can range from 0 to 1, and this indicates the proportional reduction in

error in predicting the value of one variable, based on the value of the other variable. The

Goodman and Kruskal tau is a modification of Lambda. This means instead of predicting

the group with the largest number of cases when making a prediction, one uses a

proportional prediction rule. Each category is viewed with a probability equal to the

percentage proportion of cases in that category. The Goodman and Kruskal tau values of

.026 and .013 indicate that the error rate has been reduced by 2.6% and 1.3%, for the age

demographics dependent and observed frequencies dependent, respectively, over what

could be expected by random chance.

Workforce Training and Economic Development 84

Question 5

Question 5 states: I value the input of local communities in influencing the level

of workforce development to impact economic development.

The null hypothesis states: H0 – There is no significant difference between the

responses of the age groups "45 and Under" and "Over 45".

The alternate hypothesis states: H1 – There is a significant difference between

the responses of the age groups "45 and Under" and "Over 45".

The table below provides an overview of the participants' age categories and

responses. Please see Appendix C5 for further results.

Question 5 Age Categories and Responses

Table 12. Question 5 Age Categories and Responses

Strongly Agree Neither Disagree Strongly Agree A/D Disagree “45 and Under” 5 32 8 2 0 (self-identified)

“Over 45” 4 29 12 5 0 (self-identified)

The decision takes into consideration that the Pearson chi-square observed

Asymp. Sig. 2-sided is .521, which is above the significance level of .05. Therefore, the

null hypothesis above cannot be rejected. Additionally, the Lambda statistic is calculated

as .064. The Lambda statistic describes the proportional error reduction when predicting

the dependent variable with the independent variable. A value of 0 for Lambda means

the independent variable is of no help in predicting the dependent variable. When two

Workforce Training and Economic Development 85

variables are statistically independent, Lambda is 0. However, a Lambda of 0 does not

always imply statistical independence. This value of .064 implies that the age

demographics of the respondents is a somewhat good predictor of the dependent variable

or the observed response.

The nominal directional measures indicate the strength as well as the significance

of the relationship between the row and column variables of a crosstabulation. The value

of each statistic can range from 0 to 1, and this indicates the proportional reduction in

error in predicting the value of one variable, based on the value of the other variable. The

Goodman and Kruskal tau is a modification of Lambda. This means instead of predicting

the group with the largest number of cases when making a prediction, one uses a

proportional prediction rule. Each category is viewed with a probability equal to the

percentage proportion of cases in that category. The Goodman and Kruskal tau values of

.023 and .009 indicate that the error rate has been reduced by 2.3% and 0.9%, for the age

demographics dependent and observed frequencies dependent, respectively, over what

could be expected by random chance.

Overall Discussion of Hypothesis 2 Findings

In the tests performed, the Pearson chi-square observed Asymp. Sig. 2-sided

levels for questions 1, 2, 3, 4, and 5 were above the significance level of .05. Therefore,

the null hypothesis for each cannot be rejected. It is interesting to note that there is no

significant difference in the responses between the age categories of “45 and Under” and

“Over 45”. This suggests that each age category is equally prepared to recognize the

influence that communities have on the level of workforce development in rural

communities to impact economic development. This is interesting since the division of

Workforce Training and Economic Development 86

“45 and Under” and “Over 45” categories in the National Rural Economic Developers

Association (NREDA) was nearly even with 47 participants “45 and Under” and 50

participants “Over 45”. Therefore, it can be anticipated that there would be about equal

influence by these NREDA members in this area of economic development.

Findings Related to Hypothesis 3

Hypothesis 3 states: National Rural Economic Developers Association members

who self-identify in the researcher’s survey as “45 and Under” and those who self-

identify as “Over 45” will both recognize that community workforce development

agencies and educational systems focused on developing workforce ready individuals in

rural communities do impact economic development.

Question 1

Question 1 states: I feel that it is important that workforce development agencies

and educational systems collaborate to develop workforce-ready individuals.

The null hypothesis states: H0 – There is no significant difference between the

responses of the age groups "45 and Under" and "Over 45".

The alternate hypothesis states: H1 – There is a significant difference between

the responses of the age groups "45 and Under" and "Over 45".

The table below provides an overview of the participants' age categories and

responses. Please see Appendix D1 for further results.

Workforce Training and Economic Development 87

Question 1 Age Categories and Responses

Table 13. Question 1 Age Categories and Responses

Strongly Agree Neither Disagree Strongly Agree A/D Disagree “45 and Under” 0 34 10 2 1 (self-identified)

“Over 45” 5 29 13 3 0 (self-identified)

The decision takes into consideration that the Pearson chi-square observed

Asymp. Sig. 2-sided is .141, which is above the significance level of .05. Therefore, the

null hypothesis above cannot be rejected. Additionally, the Lambda statistic is calculated

as .128. The Lambda statistic describes the proportional error reduction when predicting

the dependent variable with the independent variable. A value of 0 for Lambda means

the independent variable is of no help in predicting the dependent variable. When two

variables are statistically independent, Lambda is 0. However, a Lambda of 0 does not

always imply statistical independence. This value of .128 implies that the age

demographics of the respondents is a fairly good predictor of the dependent variable or

the observed response.

The nominal directional measures indicate the strength as well as the significance

of the relationship between the row and column variables of a crosstabulation. The value

of each statistic can range from 0 to 1, and this indicates the proportional reduction in

error in predicting the value of one variable, based on the value of the other variable. The

Goodman and Kruskal tau is a modification of Lambda. This means instead of predicting

Workforce Training and Economic Development 88

the group with the largest number of cases when making a prediction, one uses a

proportional prediction rule. Each category is viewed with a probability equal to the

percentage proportion of cases in that category. The Goodman and Kruskal tau values of

.071 and .016 indicate that the error rate has been reduced by 7.1% and 1.6%, for the age

demographics dependent and observed frequencies dependent, respectively, over what

could be expected by random chance.

Question 2

Question 2 states: I feel that it is important that workforce development agencies

and educational systems reach out to businesses and include them in the process to

develop workforce-ready individuals.

The null hypothesis states: H0 – There is no significant difference between the

responses of the age groups "45 and Under" and "Over 45".

The alternate hypothesis states: H1 – There is a significant difference between

the responses of the age groups "45 and Under" and "Over 45".

The table below provides an overview of the participants' age categories and

responses. Please see Appendix D2 for further results.

Question 2 Age Categories and Responses

Table 14. Question 2 Age Categories and Responses

Strongly Agree Neither Disagree Strongly Agree A/D Disagree “45 and Under” 6 29 10 2 0 (self-identified)

“Over 45” 5 34 10 1 0 (self-identified)

Workforce Training and Economic Development 89

The decision takes into consideration that the Pearson chi-square observed

Asymp. Sig. 2-sided is .866, which is above the significance level of .05. Therefore, the

null hypothesis above cannot be rejected. Additionally, the Lambda statistic is calculated

as .043. The Lambda statistic describes the proportional error reduction when predicting

the dependent variable with the independent variable. A value of 0 for Lambda means

the independent variable is of no help in predicting the dependent variable. When two

variables are statistically independent, Lambda is 0. However, a Lambda of 0 does not

always imply statistical independence. This value of .043 implies that the age

demographics of the respondents may not be a good predictor of the dependent variable

or the observed response.

The nominal directional measures indicate the strength as well as the significance

of the relationship between the row and column variables of a crosstabulation. The value

of each statistic can range from 0 to 1, and this indicates the proportional reduction in

error in predicting the value of one variable, based on the value of the other variable. The

Goodman and Kruskal tau is a modification of Lambda. This means instead of predicting

the group with the largest number of cases when making a prediction, one uses a

proportional prediction rule. Each category is viewed with a probability equal to the

percentage proportion of cases in that category. The Goodman and Kruskal tau values of

.008 and .003 indicate that the error rate has been reduced by 0.8% and 0.3%, for the age

demographics dependent and observed frequencies dependent, respectively, over what

could be expected by random chance.

Question 3

Workforce Training and Economic Development 90

Question 3 states: I feel that it is important that workforce development agencies

and educational systems reach out to communities and include them in the process to

develop workforce-ready individuals.

The null hypothesis states: H0 – There is no significant difference between the

responses of the age groups "45 and Under" and "Over 45".

The alternate hypothesis states: H1 – There is a significant difference between

the responses of the age groups "45 and Under" and "Over 45".

The table below provides an overview of the participants' age categories and

responses. Please see Appendix D3 for further results.

Question 3 Age Categories and Responses

Table 15. Question 3 Age Categories and Responses

Strongly Agree Neither Disagree Strongly Agree A/D Disagree “45 and Under” 4 34 8 1 0 (self-identified)

“Over 45” 4 30 13 3 0 (self-identified)

The decision takes into consideration that the Pearson chi-square observed

Asymp. Sig. 2-sided is .503, which is above the significance level of .05. Therefore, the

null hypothesis above cannot be rejected. Additionally, the Lambda statistic is calculated

as .085. The Lambda statistic describes the proportional error reduction when predicting

the dependent variable with the independent variable. A value of 0 for Lambda means

the independent variable is of no help in predicting the dependent variable. When two

variables are statistically independent, Lambda is 0. However, a Lambda of 0 does not

Workforce Training and Economic Development 91

always imply statistical independence. This value of .085 implies that the age

demographics of the respondents is a somewhat good predictor of the dependent variable

or the observed response.

The nominal directional measures indicate the strength as well as the significance

of the relationship between the row and column variables of a crosstabulation. The value

of each statistic can range from 0 to 1, and this indicates the proportional reduction in

error in predicting the value of one variable, based on the value of the other variable. The

Goodman and Kruskal tau is a modification of Lambda. This means instead of predicting

the group with the largest number of cases when making a prediction, one uses a

proportional prediction rule. Each category is viewed with a probability equal to the

percentage proportion of cases in that category. The Goodman and Kruskal tau values of

.024 and .012 indicate that the error rate has been reduced by 2.4% and 1.2%, for the age

demographics dependent and observed frequencies dependent, respectively, over what

could be expected by random chance.

Question 4

Question 4 states: I believe that it is important for workforce development

agencies and educational systems to create a system that provides a continuous flow of

workforce-ready individuals.

The null hypothesis states: H0 – There is no significant difference between the

responses of the age groups "45 and Under" and "Over 45".

The alternate hypothesis states: H1 – There is a significant difference between

the responses of the age groups "45 and Under" and "Over 45".

Workforce Training and Economic Development 92

The table below provides an overview of the participants' age categories and

responses. Please see Appendix D4 for further results.

Question 4 Age Categories and Responses

Table 16. Question 4 Age Categories and Responses

Strongly Agree Neither Disagree Strongly Agree A/D Disagree “45 and Under” 3 33 10 0 1 (self-identified)

“Over 45” 3 29 13 5 0 (self-identified)

The decision takes into consideration that the Pearson chi-square observed

Asymp. Sig. 2-sided is .161, which is above the significance level of .05. Therefore, the

null hypothesis above cannot be rejected. Additionally, the Lambda statistic is calculated

as .106. The Lambda statistic describes the proportional error reduction when predicting

the dependent variable with the independent variable. A value of 0 for Lambda means

the independent variable is of no help in predicting the dependent variable. When two

variables are statistically independent, Lambda is 0. However, a Lambda of 0 does not

always imply statistical independence. This value of .106 implies that the age

demographics of the respondents is a fairly good predictor of the dependent variable or

the observed response.

The nominal directional measures indicate the strength as well as the significance

of the relationship between the row and column variables of a crosstabulation. The value

of each statistic can range from 0 to 1, and this indicates the proportional reduction in

Workforce Training and Economic Development 93

error in predicting the value of one variable, based on the value of the other variable. The

Goodman and Kruskal tau is a modification of Lambda. This means instead of predicting

the group with the largest number of cases when making a prediction, one uses a

proportional prediction rule. Each category is viewed with a probability equal to the

percentage proportion of cases in that category. The Goodman and Kruskal tau values of

.068 and .013 indicate that the error rate has been reduced by 6.8% and 1.3%, for the age

demographics dependent and observed frequencies dependent, respectively, over what

could be expected by random chance.

Question 5

Question 5 states: I value the input of workforce development agencies in creating

an educational system that develops workforce-ready individuals.

The null hypothesis states: H0 – There is no significant difference between the

responses of the age groups "45 and Under" and "Over 45".

The alternate hypothesis states: H1 – There is a significant difference between

the responses of the age groups "45 and Under" and "Over 45".

The table below provides an overview of the participants' age categories and

responses. Please see Appendix D5 for further results.

Workforce Training and Economic Development 94

Question 5 Age Categories and Responses

Table 17. Question 5 Age Categories and Responses

Strongly Agree Neither Disagree Strongly Agree A/D Disagree “45 and Under” 2 32 11 2 0 (self-identified)

“Over 45” 6 28 12 4 0 (self-identified)

The decision takes into consideration that the Pearson chi-square observed

Asymp. Sig. 2-sided is .409, which is above the significance level of .05. Therefore, the

null hypothesis above cannot be rejected. Additionally, the Lambda statistic is calculated

as .064. The Lambda statistic describes the proportional error reduction when predicting

the dependent variable with the independent variable. A value of 0 for Lambda means

the independent variable is of no help in predicting the dependent variable. When two

variables are statistically independent, Lambda is 0. However, a Lambda of 0 does not

always imply statistical independence. This value of .064 implies that the age

demographics of the respondents is a somewhat good predictor of the dependent variable

or the observed response.

The nominal directional measures indicate the strength as well as the significance

of the relationship between the row and column variables of a crosstabulation. The value

of each statistic can range from 0 to 1, and this indicates the proportional reduction in

error in predicting the value of one variable, based on the value of the other variable. The

Goodman and Kruskal tau is a modification of Lambda. This means instead of predicting

the group with the largest number of cases when making a prediction, one uses a

Workforce Training and Economic Development 95

proportional prediction rule. Each category is viewed with a probability equal to the

percentage proportion of cases in that category. The Goodman and Kruskal tau values of

.030 and .010 indicate that the error rate has been reduced by 3.0% and 1.0%, for the age

demographics dependent and observed frequencies dependent, respectively, over what

could be expected by random chance.

Overall Discussion of Hypothesis 3 Findings

In the tests performed, the Pearson chi-square observed Asymp. Sig. 2-sided

levels for questions 1, 2, 3, 4, and 5 were above the significance level of .05. Therefore,

the null hypothesis for each cannot be rejected. This suggests that each age category is

equally prepared to recognize that community workforce development agencies and

educational systems focused on developing workforce ready individuals do impact

economic development. This is interesting since the division of “45 and Under” and

“Over 45” categories in the National Rural Economic Developers Association (NREDA)

was nearly even with 47 participants “45 and Under” and 50 participants “Over 45”.

Therefore, it can be anticipated that there would be about equal influence by these

NREDA members in this area of economic development.

Summary of Data Collection and Analysis

Chapter 4 began with a review of the research questions and hypotheses. Data

collection and the pilot study were discussed as well. Finally, an analysis of the research

and the three hypotheses was covered.

The focus of this correlation study was to assess which age category of National

Rural Economic Developers Association members best recognized as valuable the

possible elements that impact the development of workforce skills and its possible impact

Workforce Training and Economic Development 96

on the economic development of the communities they serve. This study’s participants

drew upon a pool of members from the National Rural Economic Developers

Association. There were a total of 97 participants that responded to the survey.

The results from the pilot study were used to better focus the survey questions to

properly address related workforce development issues within rural communities. The

data from the pilot study is included in the full research study and data analysis.

Hypothesis 1 stated that National Rural Economic Developers Association

(NREDA) members who self-identify in the researcher’s survey as “45 and Under” will

be better prepared than those who self-identify as “Over 45” to recognize the influence

that businesses have on the level of workforce development in rural communities to

impact economic development. Analysis of the data has shown that in one hundred

percent of the 5 individual questions given to participants that there was no difference

between the two age category responses. Therefore, it would seem that both age

categories, “45 and Under” and “Over 45” within the NREDA recognize that businesses

have an influence on the workforce development levels in rural communities as this

impacts economic development.

Hypothesis 2 stated that National Rural Economic Developers Association

members who self-identify in the researcher’s survey as “Over 45” will be better

prepared than those who self-identify as “45 and Under” to recognize the influence that

communities have on the level of workforce development in rural communities to impact

economic development. Analysis of the data has shown that in one hundred percent of

the 5 individual questions given to participants that there was no difference between the

two age category responses. Therefore, it would seem that both age categories, “45 and

Workforce Training and Economic Development 97

Under” and “Over 45” within the NREDA recognize that communities, themselves, have

an influence on the workforce development levels in rural communities as this impacts

economic development.

Hypothesis 3 stated that National Rural Economic Developers Association

members who self-identify in the researcher’s survey as “45 and Under” and those who

self-identify as “Over 45” will both recognize that community workforce development

agencies and educational systems focused on developing workforce ready individuals in

rural communities do impact economic development. Analysis of the data has shown that

in one hundred percent of the 5 individual questions given to participants that there was,

indeed, no difference between the two age category responses. Therefore, it would seem

that both age categories, “45 and Under” and “Over 45” within the NREDA recognize

that community workforce development agencies and educational systems focused on

developing workforce ready individuals within rural communities do have an impact on

economic development.

The presentation within this chapter has provided a comprehensive review to

include the research questions, hypotheses, data collection, pilot study, and the analysis

of the data. A further discussion of the results of the above analyses, conclusion that can

be drawn, potential limitations of the study, as well as suggestions for future areas of

research regarding workforce development in rural communities and the impact on

economic development are discussed in the next chapter.

CHAPTER 5. RESULTS, CONCLUSIONS, AND RECOMMENDATIONS

Introduction

The purpose of chapter 5 is to provide an overview of the research study, an

interpretation of the results and findings that were presented in chapter 4, and conclusions

that were drawn by the researcher. Also presented are any potential limitations of this

study, as well as recommendations for future study.

Summary of the Study

The focus of this correlation study was to assess which age category of National

Rural Economic Developers Association members best recognized as valuable the

possible elements that influence the development of workforce skills and its possible

impact on the economic development of the communities they serve. Ulrich Research

(2002) provided research that determined workforce availability compared to workforce

development opportunities in Highlands County Florida were at risk based on the level of

training and education within the available workforce. Davenport (2006) suggests that

according to corporate executives the United States must increase the education and skills

of rural and urban communities in order to remain competitive in retaining jobs.

Dychtwald, Erickson, and Morrison (2006) cite that fewer degreed people in the

workforce significantly influence economic growth of business in urban and rural

communities. There appears to be fewer and fewer skilled workers to address the needs

of corporations in leadership and problems solving to meet the demands of the global

market (Davenport, 2006).

The review of the literature included an in-depth discussion of business,

community, and workforce development agencies and educational systems as they

Workforce Training and Economic Development 98

influence workforce development in rural communities to impact economic development.

The potential abilities of each of these areas to impact workforce development were

examined. The analysis in the literature review focused on the positive and negative

influences these independent organizations have on promoting development for the

communities, and focused on the influences of the workforce-capable resources that will

potentially drive the economic direction of the community.

The literature review highlighted the complex dimensions that this confluence of

issues poses for rural communities. In order to address the influence of business,

communities, and workforce development agencies and educational systems, there must

be an understanding of how the age demographics of economic development

professionals can affect these rural communities and the associated economic

development.

The population for this correlation study drew on the membership of the National

Rural Economic Developers Association (NREDA). To maintain the confidentiality, as

well as the anonymity of the organizations involved, names have not been included.

There were a total of 97 participants that completed the survey instrument.

The researcher developed a survey instrument that was administered to determine

self-perceptive age categories of the NREDA participants as well as qualitative issues

regarding the influence of business, communities, and workforce development agencies

and educational systems as they relate to impacting economic development in rural

communities. The researcher utilized an online survey service, and the NREDA was kind

enough to facilitate e-mail communication to its full membership of the availability of

this online survey.

Workforce Training and Economic Development 99

The pilot study data collection and validation of the survey instrument was

performed with 11 members of the National Rural Economic Developers Association

(NREDA) who were individuals that the researcher had been involved with on economic

development forums over the past few years. This pilot group provided feedback on the

content of the survey instrument and its refinement. The pilot was completed using 11

members of the NREDA membership. The pilot group assisted in rephrasing two

questions that were difficult to understand. The pilot group members provided useful

specifics that guided the researcher to clarify the focus of the survey questions. These 11

pilot participants were included in the overall research study. A discussion of the results

and the conclusions of this full research study are presented below.

Discussion of the Results

The overview of data collection results in chapter 4 provided a comprehensive

analysis of the study's findings. Presented below is a further discussion of the results of

the data analysis regarding each hypothesis.

Hypothesis 1

Hypothesis 1 states: National Rural Economic Developers Association members

who self-identify in the researcher’s survey as “45 and Under” will be better prepared

than those who self-identify as “Over 45” to recognize the influence that businesses have

on the level of workforce development in rural communities to impact economic

development. Study participants completed a research-developed survey instrument.

This survey instrument was used to determine self-perceptive qualitative issues regarding

the influence of businesses on workforce development in rural communities to impact

economic development. This research study sought to determine a correlation between

Workforce Training and Economic Development 100

the age categories (“45 and Under” and “Over 45”) and the recognition of the value of

workforce development training with regard to businesses and communities and the

impact on economic development in rural communities. This survey instrument provided

the correlational data necessary for this study. The value of understanding how age

categories of National Rural Economic Developers Association (NREDA) members

respond to workforce development issues in their communities can have an impact on the

ability of rural communities in the state of Florida to address workforce development to

positively impact economic development. In the Southeastern United States the wages

per-capita are the lowest in the nation. Florida is one of the largest states in the

geography and it represents about 35% of the total workforce in the Southeast. The

quality of workforce development is dramatically impacted in rural areas and hit harder

with potentially fewer opportunities (Shuptrine, 2006). Therefore, a better understanding

of how to maximize this area can be quite beneficial for rural communities in the state of

Florida.

The results of the data show there is a correlation between both age categories

(“45 and Under” and “Over 45”) and the ability to recognize the value of workforce

development training with regard to businesses and the impact on economic development

in rural communities. This suggests that rural economic development professionals in the

state of Florida, in both age categories, would understand the influence that businesses

have on the level of workforce development in rural communities to impact economic

development, and can seek to capitalize on this. This would make some sense when one

considers that the ability to promote a specialization based on workforce skills works to

Workforce Training and Economic Development 101

establish the community and draw the interest of businesses in that industry is vital

(Khessina & Romanelli, 2005).

Hypothesis 2

Hypothesis 2 states: National Rural Economic Developers Association members

who self-identify in the researcher’s survey as “Over 45” will be better prepared than

those who self-identify as “45 and Under” to recognize the influence that communities

have on the level of workforce development in rural communities to impact economic

development. Study participants completed a research-developed survey instrument.

This survey instrument was used to determine self-perceptive qualitative issues regarding

the influence of communities on workforce development in rural communities to impact

economic development. This research study sought to determine a correlation between

the age categories (“45 and Under” and “Over 45”) and the recognition of the value of

workforce development training with regard to businesses and communities and the

impact on economic development in rural communities. This survey instrument provided

the correlational data necessary for this study. The value of understanding how age

categories of National Rural Economic Developers Association (NREDA) members

respond to workforce development issues in their communities can have an impact on the

ability of rural communities in the state of Florida to address workforce development to

positively impact economic development. Moses (1991) expresses the importance of

avoiding the pitfalls of economic development strategies. Much of the planning process

needs to consider the importance of setting realistic goals that match the community.

Moses (1991) states that failure to understand the economic base of the community is a

Workforce Training and Economic Development 102

critical error in effort. Therefore, a better understanding of how to maximize this area

can be quite beneficial for rural communities in the state of Florida.

The results of the data show there is a correlation between both age categories

(“45 and Under” and “Over 45”) and the ability to recognize the value of workforce

development training with regard to communities and the impact on economic

development in rural communities. This suggests that rural economic development

professionals in the state of Florida, in both age categories, would understand the

influence that communities have on the level of workforce development in rural

communities to impact economic development, and can seek to capitalize on this. This

would make some sense when one considers that the challenge to meet any specific

industry criteria may relate to the demographics of the community, which provide a

workforce that is trained and or trainable with the required business skills. In cluster

opportunities, communities look to the business seeking to locate to assist in the training

process (Jeter, 2004).

Hypothesis 3

Hypothesis 3 states: National Rural Economic Developers Association members

who self-identify in the researcher’s survey as “45 and Under” and those who self-

identify as “Over 45” will both recognize that community workforce development

agencies and educational systems focused on developing workforce ready individuals in

rural communities do impact economic development. Study participants completed a

research-developed survey instrument. This survey instrument was used to determine

self-perceptive qualitative issues regarding the influence of workforce development

agencies and educational systems on workforce development in rural communities to

Workforce Training and Economic Development 103

impact economic development. This research study sought to determine a correlation

between the age categories (“45 and Under” and “Over 45”) and the recognition of the

value of workforce development training with regard to businesses and communities and

the impact on economic development in rural communities. This survey instrument

provided the correlational data necessary for this study. The value of understanding how

age categories of National Rural Economic Developers Association members respond to

workforce development issues in their communities can have an impact on the ability of

rural communities in the state of Florida to address workforce development to positively

impact economic development. Eller et al. (1998) outlined that educational systems

needed to open themselves to a greater understanding of what impact they have on the

economic development of a community. Additionally, taking a greater leadership role in

the community by developing and understanding what the community could offer are

factors. The development of a strategic vision for developing workforce training

programs in any given community can become a tool that can increase the vision of the

community and its leaders to take steps that would increase the prosperity of the

community and raise the level of living conditions that hence create economic growth

(Kulaas, 2006).

The results of the data show there is a correlation between both age categories (“45

and Under” and “Over 45”) and the ability to recognize the value of workforce

development training with regard to workforce development agencies and educational

systems and the impact on economic development in rural communities. This suggests

that rural economic development professionals in the state of Florida, in both age

categories, would understand the influence that workforce development agencies and

Workforce Training and Economic Development 104

educational systems have on the level of workforce development in rural communities to

impact economic development, and can seek to capitalize on this. This would make

sense when one considers that organizations like the Regional Community College

Initiative (RCCI) have focused on distressed rural communities that have poor

relationships between government, local businesses, and industry (Jensen, 2003). The

Ford Foundation has invested $20 million in the RCCI to help economically challenged

regions become viable for development through workforce development planning,

training programs, and education through community involvement. Baldwin (2001)

expresses that the foundation of RCCI is leadership, strategic planning, inclusion, team

building, community development, and understanding of local cultures. Opportunities

such as this would bode well for rural communities in the state of Florida.

Conclusions

The development of workforce resources to increase the assets of a rural

community is a critical factor for the state of Florida. The National Rural Economic

Developers Association (NREDA) provides a unique perspective for rural communities

with regard to economic development issues. Economic development is a global

movement driven by local business and communities as a point of survival for future

generations (Holliday, 2006). Economic development has assumed the role as one of the

dominating issues in the world today. There is a great deal to be said for acting globally

and working locally when the competition for economic business has no country or

continent boundaries, but the maintenance of global business relies solely on available

resources within the village, town, city or metropolitan urban center (Koehler & Wurzel,

2003). Workforce investment planning appears to play a crucial role in the success or

Workforce Training and Economic Development 105

failure of economic development. For instance, Highlands County Florida is a region of

Florida that is designated agricultural. Highlands County Florida’s focus is the citrus and

cattle industries, which is beginning to fade due to foreign competition (Pfeifer, 2006).

The shift away from agriculture is beginning to have an impact on the population of the

Highlands County Florida and there is a need to develop the existing workforce to

become viable for other business and industry to maintain economic development

opportunities (Dalton, 2004). The significance of this study may possibly create new

avenues of opportunity for businesses and communities to evaluate current workforce

development activities and determine if the specifics of the strategy are in the best

interest of the workforce being developed and hence the impact to the economic position

of these rural communities in the state of Florida.

Recommendations for Future Research

This correlation research study has provided a contribution to the current body of

knowledge in regards to what degree of impact businesses, communities, and workforce

development has on changing the economic growth of rural communities in the state of

Florida. There are additional research opportunities that could be pursued because of this

research into workforce development and economic growth. Future research can address

gender-related issue from multiple perspectives such as the workforce development and

economic development professionals and the impact that gender has on how programs are

developed, communicated, executed as related to success factors in rural and/or urban

settings (Nielsen-Farrell, 2006). The opportunity exist to take this research and apply it

to urban centers with various opportunities to look at depressed minority impact factors

for achieving successful opportunities.

Workforce Training and Economic Development 106

With the push for globalization of economic development, there are a number of

research areas that relate to methodologies required to develop the work-local/think-

global mantra used in many of the current peer reviewed materials (Heshmati & Oh,

2006). The competition for economic growth provides a number of research

opportunities in the areas of development and creation of the appropriate environmental

conditions. These conditions relate to different infrastructures in a local community or

the possibilities of the workforce/business readiness of a small labor intense country

(Hess, 2005). The creation of industrial clusters to bring about successful workforce and

economic development can be a fruitful research opportunity.

In addition, there are a number of research opportunities as related to educational

institutions, both primary and secondary. The possible research could look at how

educational programs influences economic development in rural and urban centers.

Additional avenues could include the success of programs based on business growth in

communities where they are provided. Our educational systems face fierce challenges in

providing education to new and expanding workforce individuals (Bloom, 2006). There

is an ever-moving target because the needs of business leaders and manufacturing

clusters change on an almost regular basis. The opportunity to research many of these

areas of impact could provide valuable research to increase the body of knowledge and

better our economic futures.

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APPENDIX A: SURVEY QUESTIONS AND INFORMED CONSENT

Participant Invitation – Copy of Electronic Invitation to Par ticipants ATTENTION: ECONOMIC DEVELOPMENT AND EDUCATION

PROFESSIONALS!

PARTICIPANTS FOR A PEER’S RESEARCH STUDY ARE NEEDED!

Allow me to introduce myself to those who may not already know me. My name

is Kevin Cojanu, and I am an economic development and education supporter who is also

working on a Ph.D. in Organization and Management from Capella University. I am in

the final stages of my doctoral journey at Capella with only the dissertation research

project to complete. The focus of my research is on developing an understanding of the

impact education is having on economic development in the United States. There are a

number of theories of what is necessary to establish educational efforts that will bolster

the economic growth in our communities across the United States.

I am seeking to identify a population of professionals from the National Rural

Economic Developers Association (NREDA) to assist me in my research. I will be

utilizing the correlation methodology to start the research survey that will focus on three

specific areas. These research propositions will be framed by these research questions

with a focus towards the state of Florida: (1) does business influence the level of

workforce development in rural communities to impact economic development? (2) do

communities influence level of workforce development to impact economic

development? and (3) do community workforce development agencies and educational

Workforce Training and Economic Development 118

systems focused on developing workforce ready individuals impact economic

development? These research questions will be the framework for a series of multiple-

choice questions. Additionally at the end of the questionnaire, there will be a set of

demographic questions that are important to the results of the research.

There is no sponsor of my doctoral journey and there is no outside financial

support or research time. For my peers, the only cost would be in terms of the time spent

by the volunteering participants to complete the survey over the next 45 days. I also

welcome any feedback you may have and I will be very pleased to provide any and all

detail on the study. Otherwise, participants in the research will have complete anonymity

in order to protect your individual rights to privacy.

The use of human subjects in research is carefully controlled by academic

establishments. Any research involving human participants has to be approved by the

Institutional Review Board at Capella University. This approval is the final step of the

dissertation proposal stage, which I expect to reach within the next 45 days. The actual

research would then be conducted during September and October of 2007.

I am writing to you today to invite you to be a member of the volunteer

population to participate in my doctoral research. I would be delighted if you would agree

to be included.

Workforce Training and Economic Development 119

Thank you for your consideration. I look forward to hearing from you. If you

would be interested in participating, please contact me in response to this message. Many

thanks!

Best regards, Kevin A. Cojanu

Workforce Training and Economic Development 120

INFORMED CONSENT

Please read this page carefully and check the box at the bottom of the page

to indicate your agreement to participate.

I am a doctoral candidate in the School of Business and Technology, Capella University

(225 South 6th Street, Minneapolis, MN 55402). In partial fulfillment of my degree

requirements, I am conducting research into workforce development organizations and

their contribution to economic growth. Specifically, I am interested in how workforce

development organizations impact the economic development of rural communities. I will

be conducting my research based on responses to the attached questionnaires. I need your

consent to include the information you provide, via this questionnaire in the research.

1. The purpose of this study is to determine the impact of workforce development and

training on economic development within the United States. 2. The nature of the study is research, which may result in a contribution to the

literature, which may or may not be of value to you personally. 3. Participation in this study is voluntary. You may refuse to enter or may withdraw at

any time without harmful consequences to you. There is no financial gain for participating and no penalty for withdrawing.

4. There are no specific risks to you participating in this study. If any questions cause you personal anxiety, you may decline to answer.

5. As a participant in this study, you will be asked to complete three questionnaires. 6. You understand that the data from the questionnaires will be kept strictly confidential.

Digital records and all related research materials will be kept in a secure file cabinet and destroyed seven years after the completion of the study.

7. If you are interested in receiving a summary of the findings of the research, check the box at the bottom of the page.

8. If you have any questions, please contact me at the address on the previous page. 9. The Institutional Review Board of Capella University retains access to all materials

pertinent to the evaluation of research ethics. I greatly appreciate your participation in this study. I am confident that your contribution will contribute to the knowledge of factors that influence economic development and workforce

Workforce Training and Economic Development 121

development. If you agree, please check the box below to indicate that you have read and understood the process of this research study and that you agree to participate.

I [ NAME ] have read and understood the process of this research study and agree to participate.

I wish to receive a copy of the summary of findings.

Faculty Advisor: Dr. DeNigris

Workforce Training and Economic Development 122

Questionnaire (Self-reporting):

Review Statement: Does business influence the level of workforce development in rural communities to impact economic development? As a member of NREDA:

Strongly disagree

Disagree Neither

agree nor disagree

Agree Strongly

agree

I feel that it is important that local businesses influence the level of workforce development in rural communities.

I feel that it is important that outside businesses seeking to relocate influence the level of workforce development in rural communities

I feel that it is important for businesses to be able to work with local training organizations to influence the level of workforce development in rural communities

I believe that it is important for businesses to have a cooperative plan in place with local training organizations to influence the level of workforce development in rural communities

I value the input of business interests in influencing the level of workforce development in rural communities.

Workforce Training and Economic Development 123

Review Statement: Do communities influence level of workforce development to impact economic development? As a member of NREDA:

Strongly disagree

Disagree Neither

agree nor disagree

Agree Strongly

agree

I feel that it is important that local community leaders influence the level of workforce development to impact economic development

I feel that it is important that individual citizens influence the level of workforce development to impact economic development

I feel that it is important that local community groups influence the level of workforce development to impact economic development

I believe that it is important for local communities to have input into a cooperative plan with local training organizations to influence the level of workforce development to impact economic development

I value the input of local communities in influencing the level of workforce development to impact economic development

Workforce Training and Economic Development 124

Review Statement: Do community workforce development agencies and educational systems focused on developing workforce ready individuals impact economic development? As a member of NREDA:

Strongly disagree

Disagree Neither

agree nor disagree

Agree Strongly

agree

I feel that it is important that workforce development agencies and educational systems collaborate to develop workforce-ready individuals

I feel that it is important that workforce development agencies and educational systems reach out to businesses and include them in the process to develop workforce-ready individuals

I feel that it is important that workforce development agencies and educational systems reach out to communities and include them in the process to develop workforce-ready individuals

I believe that it is important for workforce development agencies and educational systems to create a system that provides a continuous flow of workforce-ready individuals

I value the input of workforce development agencies in creating an educational system that develops workforce-ready individuals

Workforce Training and Economic Development 125

Demographic Information: The purpose of these final few questions is to collect some demographic information in order to analyze responses. Whether you email or fax your completed questionnaire to me, the documents will be stored securely to ensure the confidentiality of your responses. (NOTE: If you are completing the form on a computer, place cursor between brackets and tab to next field)

Age?

18 and under 19-24 25-34 35-44 45-54 55-64 65 and over

Gender? Male Female

There are no further questions. Thank you for the time and effort you have devoted to completing this questionnaire. Your participation and contribution are greatly appreciated. This form should be returned before: October 15, 2007.

APPENDIX B: SURVEY DATA: HYPOTHESIS #1

Table B1. Hypothesis 1, Question 1

Question 1: I feel that it is important that local businesses influence the level of workforce development in rural communities.

Age Demographics * Observed Frequencies Crosstabulation

13 16 6 11 1 47

10.2 17.9 8.2 9.7 1.0 47.0

8 21 11 9 1 50

10.8 19.1 8.8 10.3 1.0 50.0

21 37 17 20 2 97

21.0 37.0 17.0 20.0 2.0 97.0

Count

Expected Count

Count

Expected Count

Count

Expected Count

45 and under

over 45

Age Demographics

Total

Strongly Disagree Disagree

Neither Agree Nor Disagree Agree

Strongly Agree

Observed Frequencies

Total

Chi-Square Tests

3.447a 4 .486

3.480 4 .481

.186 1 .666

97

Pearson Chi-Square

Likelihood Ratio

Linear-by-Linear Association

N of Valid Cases

Value df Asymp. Sig.

(2-sided)

2 cells (20.0%) have expected count less than 5. The minimum expected count is .97.

a.

Directional Measures

.065 .059 1.074 .283

.149 .129 1.074 .283

.000 .000 . c

. c

.036 .037 .491 d

.011 .012 .393 d

.017 .018 .944 .481e

.026 .027 .944 .481 e

.013 .013 .944 .481 e

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Age Demographics Dependent

Observed Frequencies Dependent

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Lambda

Goodman and Kruskal tau

Uncertainty Coefficient

Nominal by Nominal

Value Asymp.

Std. Error a

Approx. T b

Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Workforce Training and Economic Development 127

Table B2. Hypothesis 1, Question 2

Question 2: I feel that it is important that outside businesses seeking to relocate influence the level of workforce development in rural communities.

Age Demographics * Observed Frequencies Crosstabulation

9 10 6 19 3 47

5.3 13.1 7.8 18.4 2.4 47.0

2 17 10 19 2 50

5.7 13.9 8.2 19.6 2.6 50.0

11 27 16 38 5 97

11.0 27.0 16.0 38.0 5.0 97.0

Count

Expected Count

Count

Expected Count

Count

Expected Count

45 and under

over 45

Age Demographics

Total

Strongly Disagree Disagree

Neither Agree Nor Disagree Agree

Strongly Agree

Observed Frequencies

Total

Chi-Square Tests

7.384a 4 .117

7.773 4 .100

.194 1 .659

97

Pearson Chi-Square

Likelihood Ratio

Linear-by-Linear Association

N of Valid Cases

Value df Asymp. Sig.

(2-sided)

2 cells (20.0%) have expected count less than 5. The minimum expected count is 2.42.

a.

Directional Measures

.075 .066 1.095 .273

.170 .142 1.095 .273

.000 .000 . c

. c

.076 .047 .121 d

.016 .012 .198 d

.038 .026 1.474 .100e

.058 .039 1.474 .100 e

.028 .019 1.474 .100 e

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Age Demographics Dependent

Observed Frequencies Dependent

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Lambda

Goodman and Kruskal tau

Uncertainty Coefficient

Nominal by Nominal

Value Asymp.

Std. Error a

Approx. T b

Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Workforce Training and Economic Development 128

Table B3. Hypothesis 1, Question 3

Question 3: I feel that it is important for businesses to be able to work with local training organizations to influence the level of workforce development in rural communities.

Age Demographics * Observed Frequencies Crosstabulation

0 0 10 33 4 47

.5 1.9 9.7 32.0 2.9 47.0

1 4 10 33 2 50

.5 2.1 10.3 34.0 3.1 50.0

1 4 20 66 6 97

1.0 4.0 20.0 66.0 6.0 97.0

Count

Expected Count

Count

Expected Count

Count

Expected Count

45 and under

over 45

Age Demographics

Total

Strongly Disagree Disagree

Neither Agree Nor Disagree Agree

Strongly Agree

Observed Frequencies

Total

Chi-Square Tests

5.579a 4 .233

7.518 4 .111

3.324 1 .068

97

Pearson Chi-Square

Likelihood Ratio Linear-by-Linear Association

N of Valid Cases

Value df Asymp. Sig.

(2-sided)

6 cells (60.0%) have expected count less than 5. The minimum expected count is .48.

a.

Directional Measures

.026 .121 .209 .835

.043 .200 .209 .835

.000 .000 . c

. c

.058 .018 .238 d

.006 .005 .715 d

.048 .020 2.200 .111e

.056 .025 2.200 .111 e

.041 .017 2.200 .111 e

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Age Demographics Dependent

Observed Frequencies Dependent

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Lambda

Goodman and Kruskal tau

Uncertainty Coefficient

Nominal by Nominal

Value Asymp.

Std. Error a

Approx. T b

Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Workforce Training and Economic Development 129

Table B4. Hypothesis 1, Question 4

Question 4: I believe that it is important for businesses to have a cooperative plan in place with local training organizations to influence the level of workforce development in rural communities.

Age Demographics * Observed Frequencies Crosstabulation

0 2 7 35 3 47

1.0 2.4 8.7 32.5 2.4 47.0 2 3 11 32 2 50

1.0 2.6 9.3 34.5 2.6 50.0

2 5 18 67 5 97 2.0 5.0 18.0 67.0 5.0 97.0

Count Expected Count

Count

Expected Count Count

Expected Count

45 and under

over 45

Age Demographics

Total

Strongly Disagree Disagree

Neither Agree Nor Disagree Agree

Strongly Agree

Observed Frequencies

Total

Chi-Square Tests

3.334a 4 .504

4.113 4 .391

2.773 1 .096

97

Pearson Chi-Square

Likelihood Ratio Linear-by-Linear Association

N of Valid Cases

Value df Asymp. Sig.

(2-sided)

6 cells (60.0%) have expected count less than 5. The minimum expected count is .97.

a.

Directional Measures

.052 .107 .472 .637

.085 .173 .472 .637

.000 .000 . c

. c

.034 .024 .509 d

.010 .015 .452 d

.026 .019 1.361 .391e

.031 .022 1.361 .391 e

.022 .016 1.361 .391 e

Symmetric Age Demographics Dependent Observed Frequencies Dependent Age Demographics Dependent Observed Frequencies Dependent Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Lambda

Goodman and Kruskal tau

Uncertainty Coefficient

Nominal by Nominal

Value Asymp.

Std. Error a

Approx. T b

Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Workforce Training and Economic Development 130

Table B5. Hypothesis 1, Question 5

Question 5: I believe that it is important for businesses to have a cooperative plan in place with local training organizations to influence the level of workforce development in rural communities.

Age Demographics * Observed Frequencies Crosstabulation

1 10 30 6 47

1.9 10.7 30.0 4.4 47.0

3 12 32 3 50

2.1 11.3 32.0 4.6 50.0

4 22 62 9 97

4.0 22.0 62.0 9.0 97.0

Count

Expected Count

Count

Expected Count

Count

Expected Count

45 and under

over 45

Age Demographics

Total

Disagree Neither Agree Nor Disagree Agree

Strongly Agree

Observed Frequencies

Total

Chi-Square Tests

2.156a 3 .541

2.220 3 .528

1.627 1 .202

97

Pearson Chi-Square

Likelihood Ratio

Linear-by-Linear Association

N of Valid Cases

Value df Asymp. Sig.

(2-sided)

4 cells (50.0%) have expected count less than 5. The minimum expected count is 1.94.

a.

Directional Measures

.037 .036 1.005 .315

.064 .062 1.005 .315

.000 .000 . c

. c

.022 .028 .545 d

.003 .005 .819 d

.014 .018 .765 .528e

.017 .022 .765 .528 e

.012 .015 .765 .528 e

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Age Demographics Dependent

Observed Frequencies Dependent

Symmetric Age Demographics Dependent

Observed Frequencies Dependent

Lambda

Goodman and Kruskal tau

Uncertainty Coefficient

Nominal by Nominal

Value Asymp.

Std. Error a

Approx. T b

Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

APPENDIX C: SURVEY DATA: HYPOTHESIS #2

Table C1. Hypothesis 2, Question 1

Question 1: I feel that it is important that local community leaders influence the level of workforce development to impact economic development.

Age Demographics * Observed Frequencies Crosstabulation

7 7 31 2 47

6.8 10.7 27.6 1.9 47.0

7 15 26 2 50

7.2 11.3 29.4 2.1 50.0

14 22 57 4 97

14.0 22.0 57.0 4.0 97.0

Count

Expected Count

Count

Expected Count

Count

Expected Count

45 and under

over 45

Age Demographics

Total

Disagree Neither Agree Nor Disagree Agree

Strongly Agree

Observed Frequencies

Total

Chi-Square Tests

3.258a 3 .354

3.323 3 .344

.712 1 .399

97

Pearson Chi-Square

Likelihood Ratio

Linear-by-Linear Association

N of Valid Cases

Value df Asymp. Sig.

(2-sided)

2 cells (25.0%) have expected count less than 5. The minimum expected count is 1.94.

a.

Directional Measures

.057 .097 .578 .563

.106 .174 .578 .563

.000 .000 . c

. c

.034 .035 .358 d

.018 .020 .154 d

.020 .021 .928 .344e

.025 .027 .928 .344 e

.016 .017 .928 .344 e

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Age Demographics Dependent

Observed Frequencies Dependent

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Lambda

Goodman and Kruskal tau

Uncertainty Coefficient

Nominal by Nominal

Value Asymp.

Std. Error a

Approx. T b

Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Workforce Training and Economic Development 132

Table C2. Hypothesis 2, Question 2

Question 2: I feel that it is important that individual citizens influence the level of workforce development to impact economic development.

Age Demographics * Observed Frequencies Crosstabulation

6 6 30 5 47

4.8 9.2 28.6 4.4 47.0

4 13 29 4 50

5.2 9.8 30.4 4.6 50.0

10 19 59 9 97

10.0 19.0 59.0 9.0 97.0

Count

Expected Count

Count Expected Count

Count

Expected Count

45 and under

over 45

Age Demographics

Total

Disagree Neither Agree Nor Disagree Agree

Strongly Agree

Observed Frequencies

Total

Chi-Square Tests

3.017a 3 .389

3.079 3 .380

.159 1 .690

97

Pearson Chi-Square

Likelihood Ratio

Linear-by-Linear Association

N of Valid Cases

Value df Asymp. Sig.

(2-sided)

3 cells (37.5%) have expected count less than 5. The minimum expected count is 4.36.

a.

Directional Measures

.047 .101 .453 .650

.085 .180 .453 .650

.000 .000 . c

. c

.031 .034 .394 d

.010 .013 .392 d

.018 .020 .894 .380e

.023 .026 .894 .380 e

.015 .016 .894 .380 e

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Age Demographics Dependent

Observed Frequencies Dependent

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Lambda

Goodman and Kruskal tau

Uncertainty Coefficient

Nominal by Nominal

Value Asymp.

Std. Error a

Approx. T b

Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Workforce Training and Economic Development 133

Table C3. Hypothesis 2, Question 3

Question 3: I feel that it is important that local community groups influence the level of workforce development to impact economic development.

Age Demographics * Observed Frequencies Crosstabulation

5 9 29 4 47

3.4 10.7 29.1 3.9 47.0

2 13 31 4 50

3.6 11.3 30.9 4.1 50.0

7 22 60 8 97

7.0 22.0 60.0 8.0 97.0

Count

Expected Count

Count

Expected Count

Count

Expected Count

45 and under

over 45

Age Demographics

Total

Disagree Neither Agree Nor Disagree Agree

Strongly Agree

Observed Frequencies

Total

Chi-Square Tests

1.989a 3 .575

2.034 3 .565

.163 1 .686

97

Pearson Chi-Square

Likelihood Ratio

Linear-by-Linear Association

N of Valid Cases

Value df Asymp. Sig.

(2-sided)

4 cells (50.0%) have expected count less than 5. The minimum expected count is 3.39.

a.

Directional Measures

.036 .045 .777 .437

.064 .080 .777 .437

.000 .000 . c

. c

.021 .027 .579 d

.004 .006 .756 d

.012 .017 .729 .565e

.015 .021 .729 .565 e

.010 .014 .729 .565 e

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Age Demographics Dependent

Observed Frequencies Dependent

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Lambda

Goodman and Kruskal tau

Uncertainty Coefficient

Nominal by Nominal

Value Asymp.

Std. Error a

Approx. T b

Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Workforce Training and Economic Development 134

Table C4. Hypothesis 2, Question 4

Question 4: I believe that it is important for local communities to have input into a cooperative plan with local training organizations to influence the level of workforce development to impact economic development.

Age Demographics * Observed Frequencies Crosstabulation

4 7 32 4 47

3.4 9.7 29.1 4.8 47.0

3 13 28 6 50

3.6 10.3 30.9 5.2 50.0

7 20 60 10 97

7.0 20.0 60.0 10.0 97.0

Count

Expected Count

Count Expected Count

Count

Expected Count

45 and under

over 45

Age Demographics

Total

Disagree Neither Agree Nor Disagree Agree

Strongly Agree

Observed Frequencies

Total

Chi-Square Tests

2.519a 3 .472

2.548 3 .467

.030 1 .862

97

Pearson Chi-Square

Likelihood Ratio Linear-by-Linear Association

N of Valid Cases

Value df Asymp. Sig.

(2-sided)

3 cells (37.5%) have expected count less than 5. The minimum expected count is 3.39.

a.

Directional Measures

.060 .094 .612 .541

.106 .165 .612 .541

.000 .000 . c

. c

.026 .032 .477 d

.013 .017 .295 d

.015 .019 .807 .467e

.019 .023 .807 .467 e

.013 .016 .807 .467 e

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Age Demographics Dependent

Observed Frequencies Dependent

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Lambda

Goodman and Kruskal tau

Uncertainty Coefficient

Nominal by Nominal

Value Asymp.

Std. Error a

Approx. T b

Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Workforce Training and Economic Development 135

Table C5. Hypothesis 2, Question 5

Question 5: I value the input of local communities in influencing the level of workforce development to impact economic development.

Age Demographics * Observed Frequencies Crosstabulation

2 8 32 5 47

3.4 9.7 29.6 4.4 47.0

5 12 29 4 50

3.6 10.3 31.4 4.6 50.0

7 20 61 9 97

7.0 20.0 61.0 9.0 97.0

Count

Expected Count

Count

Expected Count

Count

Expected Count

45 and under

over 45

Age Demographics

Total

Disagree Neither Agree Nor Disagree Agree

Strongly Agree

Observed Frequencies

Total

Chi-Square Tests

2.254a 3 .521

2.300 3 .513

2.049 1 .152

97

Pearson Chi-Square Likelihood Ratio

Linear-by-Linear Association

N of Valid Cases

Value df Asymp. Sig.

(2-sided)

4 cells (50.0%) have expected count less than 5. The minimum expected count is 3.39.

a.

Directional Measures

.048 .098 .479 .632

.085 .170 .479 .632

.000 .000 . c

. c

.023 .029 .526 d

.009 .013 .476 d

.014 .018 .772 .513e

.017 .022 .772 .513 e

.012 .015 .772 .513 e

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Age Demographics Dependent

Observed Frequencies Dependent

Symmetric

Age Demographics Dependent Observed Frequencies Dependent

Lambda

Goodman and Kruskal tau

Uncertainty Coefficient

Nominal by Nominal

Value Asymp.

Std. Error a

Approx. T b

Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

APPENDIX D: SURVEY DATA: HYPOTHESIS #3

Table D1. Hypothesis 3, Question 1

Question 1: I feel that it is important that workforce development agencies and educational systems collaborate to develop workforce-ready individuals.

Age Demographics * Observed Frequencies Crosstabulation

1 2 10 34 0 47

.5 2.4 11.1 30.5 2.4 47.0

0 3 13 29 5 50

.5 2.6 11.9 32.5 2.6 50.0

1 5 23 63 5 97

1.0 5.0 23.0 63.0 5.0 97.0

Count

Expected Count

Count

Expected Count

Count

Expected Count

45 and under

over 45

Age Demographics

Total

Strongly Disagree Disagree

Neither Agree Nor Disagree Agree

Strongly Agree

Observed Frequencies

Total

Chi-Square Tests

6.902a 4 .141

9.216 4 .056

.330 1 .566

97

Pearson Chi-Square

Likelihood Ratio

Linear-by-Linear Association

N of Valid Cases

Value df Asymp. Sig.

(2-sided)

6 cells (60.0%) have expected count less than 5. The minimum expected count is .48.

a.

Directional Measures

.074 .095 .752 .452

.128 .159 .752 .452

.000 .000 . c

. c

.071 .022 .145 d

.016 .018 .183 d

.057 .022 2.416 .056e

.069 .028 2.416 .056 e

.049 .018 2.416 .056 e

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Age Demographics Dependent

Observed Frequencies Dependent

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Lambda

Goodman and Kruskal tau

Uncertainty Coefficient

Nominal by Nominal

Value Asymp.

Std. Error a

Approx. T b

Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Workforce Training and Economic Development 137

Table D2. Hypothesis 3, Question 2

Question 2: I feel that it is important that workforce development agencies and educational systems reach out to businesses and include them in the process to develop workforce-ready individuals.

Age Demographics * Observed Frequencies Crosstabulation

2 10 29 6 47

1.5 9.7 30.5 5.3 47.0 1 10 34 5 50

1.5 10.3 32.5 5.7 50.0

3 20 63 11 97

3.0 20.0 63.0 11.0 97.0

Count

Expected Count

Count

Expected Count

Count Expected Count

45 and under

over 45

Age Demographics

Total

Disagree Neither Agree Nor Disagree Agree

Strongly Agree

Observed Frequencies

Total

Chi-Square Tests

.729a 3 .866

.735 3 .865

.052 1 .819

97

Pearson Chi-Square

Likelihood Ratio Linear-by-Linear Association

N of Valid Cases

Value df Asymp. Sig.

(2-sided)

2 cells (25.0%) have expected count less than 5. The minimum expected count is 1.45.

a.

Directional Measures

.025 .071 .343 .731

.043 .121 .343 .731

.000 .000 . c

. c

.008 .017 .868 d

.003 .008 .863 d

.005 .011 .432 .865e

.005 .013 .432 .865 e

.004 .009 .432 .865 e

Symmetric

Age Demographics Dependent Observed Frequencies Dependent

Age Demographics Dependent

Observed Frequencies Dependent

Symmetric Age Demographics Dependent

Observed Frequencies Dependent

Lambda

Goodman and Kruskal tau

Uncertainty Coefficient

Nominal by Nominal

Value Asymp.

Std. Error a

Approx. T b

Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Workforce Training and Economic Development 138

Table D3. Hypothesis 3, Question 3

Question 3: I feel that it is important that workforce development agencies and educational systems reach out to communities and include them in the process to develop workforce-ready individuals.

Age Demographics * Observed Frequencies Crosstabulation

1 8 34 4 47

1.9 10.2 31.0 3.9 47.0

3 13 30 4 50

2.1 10.8 33.0 4.1 50.0

4 21 64 8 97

4.0 21.0 64.0 8.0 97.0

Count

Expected Count

Count

Expected Count

Count

Expected Count

45 and under

over 45

Age Demographics

Total

Disagree Neither Agree Nor Disagree Agree

Strongly Agree

Observed Frequencies

Total

Chi-Square Tests

2.350a 3 .503

2.406 3 .493

1.708 1 .191

97

Pearson Chi-Square

Likelihood Ratio

Linear-by-Linear Association

N of Valid Cases

Value df Asymp. Sig.

(2-sided)

4 cells (50.0%) have expected count less than 5. The minimum expected count is 1.94.

a.

Directional Measures

.050 .103 .472 .637

.085 .173 .472 .637

.000 .000 . c

. c

.024 .030 .508 d

.012 .018 .320 d

.015 .019 .791 .493e

.018 .023 .791 .493 e

.013 .017 .791 .493 e

Symmetric

Age Demographics Dependent Observed Frequencies Dependent

Age Demographics Dependent

Observed Frequencies Dependent Symmetric

Age Demographics Dependent Observed Frequencies Dependent

Lambda

Goodman and Kruskal tau

Uncertainty Coefficient

Nominal by Nominal

Value Asymp.

Std. Error a

Approx. T b

Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Workforce Training and Economic Development 139

Table D4. Hypothesis 3, Question 4

Question 4: I believe that it is important for workforce development agencies and educational systems to create a system that provides a continuous flow of workforce- ready individuals.

Age Demographics * Observed Frequencies Crosstabulation

1 0 10 33 3 47 .5 2.4 11.1 30.0 2.9 47.0

0 5 13 29 3 50 .5 2.6 11.9 32.0 3.1 50.0

1 5 23 62 6 97 1.0 5.0 23.0 62.0 6.0 97.0

Count

Expected Count Count

Expected Count

Count Expected Count

45 and under

over 45

Age Demographics

Total

Strongly Disagree Disagree

Neither Agree Nor Disagree Agree

Strongly Agree

Observed Frequencies

Total

Chi-Square Tests

6.563a 4 .161

8.876 4 .064

1.673 1 .196

97

Pearson Chi-Square

Likelihood Ratio

Linear-by-Linear Association

N of Valid Cases

Value df Asymp. Sig.

(2-sided)

6 cells (60.0%) have expected count less than 5. The minimum expected count is .48.

a.

Directional Measures

.061 .098 .603 .546

.106 .167 .603 .546

.000 .000 . c

. c

.068 .018 .165 d

.013 .015 .286 d

.054 .021 2.437 .064e

.066 .027 2.437 .064 e

.046 .017 2.437 .064 e

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Age Demographics Dependent

Observed Frequencies Dependent

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Lambda

Goodman and Kruskal tau

Uncertainty Coefficient

Nominal by Nominal

Value Asymp.

Std. Error a

Approx. T b

Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.

Workforce Training and Economic Development 140

Table D5. Hypothesis 3, Question 5

Question 5: I value the input of workforce development agencies in creating an educational system that develops workforce-ready individuals.

Age Demographics * Observed Frequencies Crosstabulation

2 11 32 2 47

2.9 11.1 29.1 3.9 47.0

4 12 28 6 50 3.1 11.9 30.9 4.1 50.0

6 23 60 8 97

6.0 23.0 60.0 8.0 97.0

Count Expected Count

Count

Expected Count Count

Expected Count

45 and under

over 45

Age Demographics

Total

Disagree Neither Agree Nor Disagree Agree

Strongly Agree

Observed Frequencies

Total

Chi-Square Tests

2.887a 3 .409 2.990 3 .393

.001 1 .981

97

Pearson Chi-Square

Likelihood Ratio

Linear-by-Linear Association N of Valid Cases

Value df Asymp. Sig.

(2-sided)

4 cells (50.0%) have expected count less than 5. The minimum expected count is 2.91.

a.

Directional Measures

.048 .090 .517 .605

.085 .158 .517 .605

.000 .000 . c

. c

.030 .032 .414 d

.010 .013 .411 d

.018 .020 .891 .393e

.022 .025 .891 .393 e

.015 .017 .891 .393 e

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Age Demographics Dependent

Observed Frequencies Dependent

Symmetric

Age Demographics Dependent

Observed Frequencies Dependent

Lambda

Goodman and Kruskal tau

Uncertainty Coefficient

Nominal by Nominal

Value Asymp.

Std. Error a

Approx. T b

Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

Likelihood ratio chi-square probability.e.