RESEARCH TO REVITALIZE RURAL ECONOMIES · Venture Capital Financing for Entrepreneurs in Rural Businesses 2) Innovation and Sustainability in Rural Communities a. ... Dr. Alison Blay‐Palmer

RESEARCH TO REVITALIZE RURAL ECONOMIES A Report for the Economic Developers Council of Ontario

December 2011

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Contents

Introduction ........................................................................................................................................ iv

Overview .................................................................................................................................................. iv

Acknowledgments .................................................................................................................................... iv

Research Team .......................................................................................................................................... v

Part 1: Advisor Relationships in Rural Businesses .............................................................................. 1‐1

Executive Summary ................................................................................................................................ 1‐2

Introduction ........................................................................................................................................... 1‐3

Literature Review: Small firms’ advisory relationships .......................................................................... 1‐3

Methodology .......................................................................................................................................... 1‐4

Analysis and Findings ............................................................................................................................. 1‐5

Recommendations and Conclusion ..................................................................................................... 1‐25

References ........................................................................................................................................... 1‐27

Appendix A: Comments on public and para‐public programs ............................................................. 1‐29

Appendix B: Reasons for not using an advisor ..................................................................................... 1‐31

Part 2: Venture Capital Financing for Entrepreneurs in Rural Businesses ........................................... 2‐1


Introduction ........................................................................................................................................... 2‐3

Methodology .......................................................................................................................................... 2‐3

Relation to Literature ............................................................................................................................. 2‐4

Analysis and Findings ............................................................................................................................. 2‐5

Recommendations ................................................................................................................................. 2‐5

Conclusion .............................................................................................................................................. 2‐7

References ............................................................................................................................................. 2‐9

Part 3: Building Community Capacity through Sustainable Development .......................................... 3‐1


Introduction: The Context for the Green Economy ............................................................................... 3‐3

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Methodology .......................................................................................................................................... 3‐5

Findings and Analysis ............................................................................................................................. 3‐6

Recommendations ............................................................................................................................... 3‐14

Conclusion: Green Economic Activities in Eastern Ontario ................................................................. 3‐19

References ........................................................................................................................................... 3‐20

Appendix A – Sustainability Value Chain ............................................................................................. 3‐22

Appendix B – Ontario Wind Capacity ................................................................................................... 3‐23

Part 4: Corporate Social Responsibility .............................................................................................. 4‐1


Introduction: The Context for Corporate Social Responsibility ............................................................. 4‐3

Methodology .......................................................................................................................................... 4‐3

Findings .................................................................................................................................................. 4‐3

References ............................................................................................................................................. 4‐6

Appendix A – Interview Questions ......................................................................................................... 4‐7

Part 5: Developing a Rural Public Transportation Network ................................................................ 5‐1


Introduction ........................................................................................................................................... 5‐2

Literature Review ................................................................................................................................... 5‐7

Methodology ........................................................................................................................................ 5‐12

Analysis and Findings ........................................................................................................................... 5‐24

Conclusion and Recommendations for Future Work .......................................................................... 5‐34

References ........................................................................................................................................... 5‐36

Appendix A – Rural Communities with Public Transit Systems ........................................................... 5‐38

Appendix B – How to Develop an Economic Impact Assessment (EIA) ............................................... 5‐40

Appendix C – Output for Weights for PEC using Excel Solver .............................................................. 5‐42

Appendix D – VBA Code for RAS and Ranking ..................................................................................... 5‐43

Appendix E – Route One: Duration Calculation for PEC ...................................................................... 5‐46

Part 6: Understanding Rural Business Enterprise: A Role for Business Incubation and Social

Innovation? ...................................................................................................................................... 6‐1


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Introduction ........................................................................................................................................... 6‐3

Theoretical Context ................................................................................................................................ 6‐4

Research Context: Rural Business Incubation ........................................................................................ 6‐9

Methodology ........................................................................................................................................ 6‐10

Findings ................................................................................................................................................ 6‐14

Discussion............................................................................................................................................. 6‐24

Conclusion ............................................................................................................................................ 6‐29

References ........................................................................................................................................... 6‐32

Appendix A – Sample Interview Questions .......................................................................................... 6‐37

Appendix B – Summary of Key Survey Findings ................................................................................... 6‐40

Appendix C – List of Canadian Incubators and Social Innovation Spaces ............................................ 6‐42

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Introduction

Overview

Led by The Monieson Centre at Queen’s School of Business, the Research to Revitalize Rural Economies project was a research initiative designed to foster practical insights and recommendations that rural Ontario communities can use to enhance their economic and social well‐being. This region is experiencing myriad problems common to many rural Canadian communities. Notable among these are youth out‐migration, an aging population, lower incomes, a smaller tax base to pay for regional/government services delivered over long distances, and fewer educational, cultural, and recreational opportunities as compared with urban areas. The economic gap created by the shrinking large industrial base is being filled by small and medium‐sized enterprises started by entrepreneurs. However, there has been little research identifying the broader economic impacts of new business development on rural communities. Careful study and increased attention are required to assist in escaping a cycle of rural decline and becoming more socially vibrant, resilient, and productive. Communities are in need of evidence‐based, practitioner‐oriented guides and tools, stemming from academic research.

This report comprises six separate studies aimed at economic revitalization in rural Ontario. These studies fall within two major themes:

1) Rural Entrepreneurs and Business Studies a. Advisor Relationships in Rural Businesses b. Venture Capital Financing for Entrepreneurs in Rural Businesses

2) Innovation and Sustainability in Rural Communities a. Building Community Capacity through Sustainable Development b. Corporate Social Responsibility c. Developing a Rural Public Transportation Network d. Understanding Rural Business Enterprise: A Role for Business Incubation and Social

Innovation?

This project is part of the Monieson Centre’s larger body of work on economic revitalization, available at www.economicrevitalization.ca. Founded in November 1998, The Monieson Centre at Queen’s School of Business coordinates leading scholarly research involving academic, business, government, and community partners to create value through knowledge. The Centre focuses on the knowledge economy ‐ how to harness the expertise of individuals, organizations and communities to create knowledge capital. Acclaimed researchers study issues such as governance, corporate culture, innovation, change management, human resource management, and economics. Issues are studied theoretically and practically. The result is imagination, innovation, and insight to grow business, inform policy, and revitalize industries and communities.

Acknowledgments

The Monieson Centre thanks the Economic Developers Council of Ontario (EDCO) for their generous support of this research initiative. The project was also made possible through partnerships with the

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Ontario Association of Community Futures Development Corporations (OACFDC), the Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA), and the Rural Ontario Institute (ROI).

Research Team

Principal Investigator:

Dr. Yolande Chan Yolande E. Chan is a Professor and E. Marie Shantz Research Fellow in MIS at Queen's School of Business, as well as the past Director of The Monieson Centre.

Researchers:

Dr. Alison Blay‐Palmer is an Associate Professor in the Department of Geography and Environmental Studies at Wilfrid Laurier University. Her research focuses on alternative food systems, sustainable economic development, and regional innovation.

Dr. Chialin Chen is an Associate Professor of Operations Management and Technology at Queen's School of Business. He studies supply chain management and new product/process innovations.

Dr. Tina Dacin is the E. Marie Shantz Professor of Strategy and Organizational Behaviour at Queen's School of Business, and Director, Queen's School of Business Centre for Responsible Leadership. Her research interests include social entrepreneurship, institutional change, organizational traditions, and partner selection in alliances.

Dr. Linda Dyer is Professor in the Department of Management, John Molson School of Business, Concordia University. She studies the establishment of trusting relationships between professional business advisors and the owners of small firms, including ethnic businesses.

Dr. Kelley Packalen is Assistant Professor of Strategy and Organization at Queen's School of Business. She studies strategy and entrepreneurship to see how founders influence business outcomes.

Dr. Veikko Thiele is Assistant Professor of Managerial Economics at Queen's School of Business. He studies venture capital attraction, company performance evaluations, and the design of incentive schemes in organizations.

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Part 1: Advisor Relationships in Rural Businesses

Dr. Kelley Packalen

Dr. Linda Dyer

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Executive Summary

The goal of this report is to present our findings on the extent to which owner‐managers of small businesses use business advisory programs and professional and other advisors. In exploring this issue, we consider:

1) The use and perception of public and para‐public business advisory programs; 2) The use and perception of business‐support advisors more broadly; and 3) Characteristics of businesses, owners and advisors that predict successful advisory relationships.

The owner‐managers of 80 small businesses from a wide range of industries responded to our survey. The businesses were located in one of four rural regions in Ontario and were mostly small (average employees of nine). The business owners were experienced (average tenure as owner of 13 years), 58 percent male, and on average 51 years old.

Each of eight public or para‐public programs we studied had been utilized by, on average, 15 percent of all respondents. This spanned from a low of four percent who had used the specialized Canadian Youth Business Foundation Program to a high of 55 percent who had belonged to the local or regional Chamber of Commerce. In general the main reasons for not using the programs were a lack of awareness, or a perceived lack of applicability, desire or need; neither a lack of trust nor time was a popular reason for not using the programs.

Of the 80 owners who responded to our survey, 63 (79%) consulted others either formally or informally about their businesses. On average they spoke with a diverse group of 11 other individuals that included individuals internal to the company, external stakeholders such as customers and suppliers, family members and friends, and business service professionals. In general, our respondents were quite satisfied with their advisors and perceived their advice to be important to the success of their businesses. Among those who didn’t use advisors the three main reasons for not having advisors were they did not feel they needed an advisor, they perceived difficulties in obtaining an advisor, and/or they were advisors themselves.

To investigate predictors of successful advisory relationships we asked individuals to provide us with detailed information on their relationships with up to two primary advisors. Their responses suggested that trust was significantly correlated with the perceived usefulness of the advice and overall satisfaction with that advisor. We also found that the owner‐manager’s primary relationship to the advisor (e.g., co‐owner, spouse), the advisor’s profession (e.g., accountant, other business service professional), and the industry in which the business operated had various influences on the advice process. Finally we found no significant differences between owners who used advisors and those who did not with respect to their satisfaction with their firm’s business performance or their level of dependence on their business revenue to cover their personal expenditures. We did, however, find that those who did not consult others about their businesses had significantly higher levels of financial anxiety than those who did consult others.

From these analyses we generated five recommendations that might be of interest to administrators of public and para‐public business support programs. These recommendations focus on suggested avenues to advertise program offerings, the need to simplify application procedures, and the ways to increase satisfaction both with program offerings in general and advisory relationships in particular.

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Introduction

Entrepreneurs and owner‐managers of small firms are often characterized as uncompromisingly self‐reliant—individuals who treasure their independence (Taylor, 1996). This emphasis on independence can be an advantage in a competitive business environment. On the other hand, independence has drawbacks. Small business owner‐managers need the knowledge to cope with operational, personnel, marketing, and financing issues; at the same time many lack the managerial skills to handle all of these functions. This need has stimulated the growth of a wide variety of advising services that target small firms. These services, external to the firm, include business‐support professionals, primarily accountants, lawyers, bankers, and management consultants. Public‐sector organizations, too, have emerged from government policy initiatives that focus on economic development; the broad mission of these organizations is to encourage business start‐ups and the growth of existing small businesses.

Business organizations in rural communities have been the focus of government business‐support policies in many countries (Cumming & Fischer, 2010; Mole, 2002; Lyons, 2002). In Canada, a recent Senate report pointed out that employment in primary industries such as farming, forestry, fishing and mining has been shrinking, and this means that the rural locations in which these businesses exist are in great need of economic stimulation (Senate report, 2008). While rural areas have proportionately more small businesses then urban areas, the rural businesses are smaller than their counterparts in Canadian cities. The evidence shows that rural firms are also less profitable and they face greater hurdles in getting financing for business start‐up and growth. The report points out that the success of small rural businesses is crucial to the viability of the communities in which they are located, and there is a call for more public sector programs to support small businesses in rural communities (Senate report, 2008).

In this research, we examine the extent to which owner‐managers of small rural businesses use governmental economic development programs when seeking advice about their business, and how the owners evaluate these programs. We also investigate owners’ use and evaluation of other professional business support advisors as well as informal advisors. In exploring this issue, we consider:

1) The use and perception of public and para‐public business advisory programs; 2) The use and perception of business‐support advisors more broadly; and 3) Characteristics of the business, the owner and the advisor that predict successful advisory

relationships.

We begin by providing a brief literature review and an overview of the methodology we used to administer the survey on which our findings are based. We then address each of the aforementioned topics. The quantitative data underlying our key findings are summarized in tables throughout our report.

Literature Review: Small firms’ advisory relationships

To explain the business owner’s decision to enter into an advisory relationship, a wide variety of factors have been studied. These factors have included the age of the business (McGee & Sawyerr 2003; Smeltzer, Van Hook & Hutt, 1991), the functional area of business in which the owner must make an important decision (Pineda, Lerner, Miller & Phillips, 1998), the complexity of the environment in which the firm operates (Dyer & Ross, 2008), and the credibility of the advisor (Gibb, 2000; Mole, 2002). A

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consistent finding, however, is that many business owners are reluctant to seek advice from external providers, preferring to confer with friends or family members, or electing to make their own independent decisions (Curran & Blackburn, 2000; Scott & Irwin, 2009). Indeed, the characteristic self‐reliance of business owners suggests that the process of offering advice to them might be expected to be complex, and even problematic. On the other hand, the scholarly evidence suggests that owners do respect technical information and advice in areas where they may lack expertise, such as accountancy, legal requirements and marketplace issues (Dyer & Ross, 2008; Mole, 2002). Ozgen and Baron (2007) have reported, too, that having mentors and participating in professional forums may create mindsets that help entrepreneurs to recognize new business opportunities. In general, then, we conclude that owners of small firms are sometimes unwilling to seek advice, but when they do, there are conditions under which the advice is seen as satisfactory and helpful to the firm.

When we focus not on advising in general, but on advice from public or para‐public programs for small businesses in particular, the results are less encouraging. Lyons (2002) notes that considerable resources have been devoted to economic development programs in the United States, with the goal of revitalizing rural businesses, but these programs tend to have limited success. In the UK, too, Bennett & Robson (2004) found that compared to other types of business advisors, public business assistance programs engender the lowest levels of trust and satisfaction with services. On the other hand, some researchers have found that public and para‐public advisory programs do work in some circumstances; for example, when the contacts between business owners and advisors are more frequent and intensive, there are positive impacts on business success (Chrisman & McMullan, 2004; Mole, Hart, Roper & Saal, 2009). Similarly Cumming & Fischer (2010) concluded that in their sample of small firms in Ontario, the number of hours of advice received from a public business advisory program was positively correlated with the firms’ sales growth. In sum, the weight of evidence appears to be that providing individualized business advice through public and para‐public programs is a challenge, but when the advisory relationship is intensive, a positive outcome can result.

Finally, we consider the characteristics of a rural environment and the impact this may have on advisory relationships in small rural firms. Ring, Peredo and Chrisman (2010) point out that in rural communities, residents tend to have similar backgrounds and relatively frequent interactions with a restricted range of people (compared to urban communities). For this reason there is great value placed on families, neighbours, and close‐knit relationships. At the same time, the small size of the rural population may constrain the flow of new connections and innovative ideas in some communities, and geographical isolation may make it difficult to access important resources. Together, close relationships with a limited number of people, and the large geographic distance from “outside” influences and resources may have mixed effects on business activities, perhaps facilitating business within the community, but perhaps serving to inhibit new opportunities and thus dampening entrepreneurial activity (Lyons, 2002; Ring et al., 2010). Extrapolating from these ideas, and assuming that advisory relationships are a type of business resource, we explore the extent to which business owners in rural areas seek advisors, the types of advisors they select, and their evaluation of advisory relationships.

Methodology

Data for this report were drawn from an anonymous survey that we administered to a sample of small business owner‐managers in four rural regions in Ontario. The process for developing and administering the survey was as follows. First, we designed a survey to ask small business owner‐managers questions

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about their businesses, themselves, their involvement with public and para‐public programs and services for small business owners, and their relationships with up to two primary advisors. We then pre‐tested the survey with two small business owners and six MBA students who were current business owners. Based on their feedback we made minor revisions to the survey.

We administered the surveys in waves following the same procedure in each region except Central Ontario, where we distributed surveys in person and then followed up with those businesses several days later to see if they had completed the survey. For the remaining three regions we first solicited a mailing list from a local chamber of commerce, economic development group or some other similar organization. We then cleaned the lists to remove companies that were obviously franchises, parts of national chains, non‐profits, etc. We also removed companies for which key contact information was missing and could not be found through additional searching on the internet. We then telephoned each company on the cleaned list and asked whether we could send a survey to them. We sent surveys to those who said yes as well as those who we could not reach and with whom we had left a message. About two weeks after the mailing we again called all businesses to remind them about the survey. The number of businesses contacted, the number of surveys sent, and those returned in each region are summarized in Table 1 below.

Table 1: Response rate by region sampled

Region in Ontario Number of owners contacted

Number of owners who

received surveys

Number of surveys returned

Response rate based on surveys

sent

Northeastern 324 162 37 23%

Central 38 28 16 57%

Southwestern 181 128 16 13%

Southeastern 150 105 14 13%

Distributing the surveys in person proved to be the most effective in terms of response rate. The disadvantage was that doing so was very time consuming. It also meant that only businesses that maintained a physical storefront could be surveyed. The other response rates are more typical of unsolicited survey research.

Analysis and Findings

In our analysis and findings we begin by providing an overview of our sample in terms of the basic demographic features of both the business owners and their businesses. Included in this analysis are several measures of the entrepreneurs’ satisfaction with their financial situations. This information will provide the background for many of the subsequent comparisons that we make between various subsets of the data. We then turn to analyzing the data with respect to our three main research questions or goals for this report.

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We then analyze respondents’ experiences with a number of public and para‐public programs which provide services geared towards small business owners, particularly those in rural regions. We also review and categorize open‐ended comments about owners’ experiences with these programs and services.

About 20 percent of our sample indicated that they did not discuss their business either formally or informally with anyone. Thus, our second major analysis compares those who used advisors with those who did not to determine if there are any significant demographic differences between the two groups. In addition, for the subset of individuals who did not use advisors, even informally, we give examples of the reasons they provided for not consulting others.

The remainder of our analysis focuses on the 63 individuals in our sample who had advisors. First, we provide information on the kinds and numbers of individuals that these owners spoke with about their businesses in general as well as their satisfaction with and perceived importance of that information. Next, demographic features of the advisors and the characteristics of the relationships between the owner‐managers and their main advisors are examined. Within this section we look at variables such as age and experience, as well as trust in and satisfaction with the advisory relationship. Finally we consider how the use of advisors and owners’ relationships with them may differ by the type of connection between the owner and advisor (e.g., co‐owner, spouse), the advisor’s profession and the industry in which the business is located.

Demographic features of the business owners

Overall we received usable responses from 80 owner‐managers of independent for‐profit small businesses. Fifty‐eight percent of our sample was male and the remaining 43 percent was female. On average these business owners were 51 years old (range: 23 years to 79 years). All levels of education were present: four percent had at most completed elementary school, 31 percent had a high school diploma; 46 percent had a college degree; 18 percent had a university degree; and just one percent had a post‐graduate degree.

Eighty‐nine percent of the owners worked on their businesses full‐time; the remaining 11 percent worked on their businesses part‐time. The owner‐managers had been running their businesses for an average of 13 years (range: 6 months to 39 years). A little over half (55%) had founded their companies; another 29 percent had purchased their business. Just 15 percent had inherited their businesses; one individual did not specify how he came to be the owner‐manager of the company. For nearly two‐thirds (63%) of the owners in our sample, this was their only entrepreneurial venture; 24 percent had previously or concurrently owned a second business; 14 percent owned three or more businesses.

Demographic features of the businesses

Our businesses were located in one of four regions in Ontario, namely Northeastern Ontario (n=36), Central Ontario (n=15), Southwestern Ontario (n=15), and Southeastern Ontario (n=14). The firms were located in mostly rural regions, with the average population being 18,000. The largest town in which businesses were located was 80,000. More than half (59%) were located in towns with populations of less than 10,000 individuals.

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The businesses came from a wide range of industries—the modal category was a grouping of firms in the industrial, manufacturing, real estate and agricultural businesses, labelled industrial in our analyses (n=25). The industrial category included businesses focused on construction and related trades (n=12), farming (n=3), and manufacturing (e.g., a fabricator of sheet metal and a small machine shop). Professional and health services (n=23) spanned a wide range of activities from hair dressing and funeral homes to consulting and book‐keeping to fitness studios and veterinary clinics. Hospitality was a relatively small group (n=9) and included hotels, rental cottages and restaurants. Retail (n=21) included several different types of businesses from florists (n=5) to antiques to a video and electronics retailer. Two respondents did not indicate what industry they were in. There was no significant difference in the concentration of the four types of industries across the four regions.

In another approach to understanding the nature of the participating firms, we asked the owners questions about the complexity of their businesses. Complexity was measured using 15 questions about the extent that their business activities involved a broad range of products, various market segments, geographical locations, government regulations, and diverse suppliers and employees, among other factors (scale from Dyer & Ross, 2008). A maximum score of 5 would represent an extremely complex set of business activities. In this sample, the average business complexity score was 3.04, roughly the midpoint of the scale. Scores of individual companies ranged from a low of 1.07 to a high of 4.53. Retail (mean=3.33) and industrial (mean=3.14) companies were described as being slightly more complex than hospitality companies (mean=2.81) and professional and health‐service companies (mean=2.72), but these differences were not significant. Similarly, there was no significant difference in complexity across the regions.

More than half of the owners (58%) were the sole owner‐managers of their companies. About one‐third told us that they had one or more partners who were active in the day‐to‐day activities of the businesses. Similarly, nearly a third (31%) of the sample considered their businesses to be family firms. As not all companies had been founded by the current owners, the average length of time that the companies had been in business was slightly longer—22 years—than the length of time the owners had been running their businesses. One family firm had been in operation for more than 100 years, but the median years for which companies were in business was 16 years, compared to 12 years for which the owner‐managers had been running the businesses.

Our sample comprised mainly micro‐enterprises—the average number of full‐time, part‐time and contract employees combined was nine; 13 percent of the firms hired no employees at all. A significant positive correlation existed between the owners’ report of the complexity of their business activities and the number of employees in their firms.

Business performance

Measuring performance among small businesses is notoriously difficult. Many business‐owners, particularly owners of micro‐businesses are content earning a basic living and thus do not aspire to grow; for this reason, the definition of “good performance” may vary greatly from one owner to another. In addition, different industries have wildly different expectations with respect to profit and sales growth, which makes comparisons between owners from different industries quite challenging.

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To tackle these issues, we looked at performance in several ways. First, we asked our owners about their level of satisfaction on three performance measures—amount of profitability, growth in profitability and growth in sales. We then averaged these three measures and found that, on average, the owner‐managers in our sample tended to be somewhat satisfied with their business’ performance (mean = 2.61 on a scale where 2 = slightly satisfied and 3 = satisfied).

We also looked at the owners’ anxiety about finances as a proximal indicator of performance. We used a version of a financial anxiety scale (Lowenstein, Prelec, & Weber, 1999) that was modified for small business owners. This measure used a five‐point Likert‐type scale. The higher one’s score the more financial anxiety one experienced. The results indicated that business owners’ average fell near the midpoint of the financial anxiety scale (mean = 2.92).

Finally, we asked owners to indicate on a five‐point Likert‐type scale ranging from “strongly disagree” (1) to “to strongly agree” (5) whether they were dependent on the income from the business to meet their personal needs. We found that on average the owners agreed that they were dependent on the income from their businesses (mean = 3.70).

There were no significant differences among industries with respect to business owners’ satisfaction with performance, their level of financial anxiety or dependence on income from their businesses. There was, however, a significant difference with respect to business owners’ satisfaction with performance based on the location of the business; owners in Northeastern (mean=2.70) and Central (mean=3.16) Ontario indicated higher levels of satisfaction than those located in Southwestern (mean=2.20) or Southeastern (mean=2.21) Ontario.

Use of public and para‐public organizations or programs

Having described our sample as a whole, we turn now to our first major objective of this research report, namely to examine the use by small business owners in rural regions of the numerous government sponsored and similar programs designed to support their development. For those who did not take advantage of these largely free services we asked them to provide their reason for not doing so. Table 2 reproduces the grid that we asked owner‐managers to complete. Within each cell the first number provides a raw count of the number of individuals who selected that particular cell and the second number provides the percent based on the row total.1 In addition to the eight programs that we listed, we gave respondents the opportunity to tell us if they had used any additional programs or services. Five additional programs were each mentioned by a single individual—Aboriginal Business Canada (ABC), Ministry of Northern Development, Mines & Forestry (MNDMF), Canadian Independent Small Business (CISB), a high school co‐op program, and the Scientific Research and Experimental Development (SR&ED).

1 Some respondents in Northeastern and Central Ontario who did not have advisors did not fill this section out. Subsequently, a revision in the order of survey questions meant that all respondents completed this section.

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Table 2: Business owners involvement with government‐sponsored and similar programs for small businesses (n=71)

Reason provided for not using program / service

Organization or Program

I have used

them

I have

not

heard of them

Don’t

know

how to access

Not ap

plicab

le

to m

y firm

No interest or

need

I don’t have

time

I don’t trust

them

No

response

given

Local community futures development corporation (CFDC)

13

(18%)

16

(23%)

5

(7%)

13

(18%)

15

(21%)

3

(4%)

3

(4%)

3

(4%)

Local economic development corporation (EDCO)

11

(16%)

10

(14%)

9

(13%)

14

(20%)

15

(21%)

5

(7%)

5

(7%)

2

(3%)

Local or Regional Chamber of Commerce (CoC)

39

(55%)

0

(0%)

4

(6%)

4

6(%)

13

(18%)

7

(10%)

2

(3%)

2

(3%)

Local Business Improvement Association (BIA)

10

(14%)

10

(14%)

7

(10%)

17

(24%)

16

(23%)

6

(8%)

3

(4%)

2

(3%)

Business Development Bank of Canada (BDC)

9

(13%)

3

(4%)

15

(21%)

10

(14%)

22

(31%)

6

(8%)

4

(6%)

2

(3%)

Canadian Youth Business Foundation (CYBF)

3

(4%)

16

(23%)

6

(8%)

19

(27%)

20

(28%)

3

(4%)

2

(3%)

2

(3%)

FedDev Ontario or FedNor

5

(7%)

12

(17%)

14

(20%)

14

(20%)

18

(25%)

5

(7%)

2

(3%)

1

(1%)

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Reason provided for not using program / service

Organization or Program

I have used

them

I have

not

heard of them

Don’t

know

how to access

Not ap

plicab

le

to m

y firm

No interest or

need

I don’t have

time

I don’t trust

them

No

response

given

Self‐employment benefit program (SEBP)

6

(8%)

24

(34%)

5

(7%)

8

(11%)

17

(24%)

3

(4%)

3

(4%)

5

(7%)

We also gave respondents an opportunity to provide us with comments on the programs. Specifically, we asked them: “For the programs you have used please tell us your level of satisfaction with them. We also welcome any other comments about these or other government sponsored programs.” A little over half of the individuals (n=43) provided us with additional feedback. We used these comments to determine their general level of satisfaction with the various programs. The results of our analysis are summarized in Table 3. Specific comments that provided additional details on satisfaction level are highlighted in Appendix A. There did not appear to be any differences in satisfaction based on region or industry.

Table 3: Frequency of comments indicating level of satisfaction with public and para‐public organizations or programs (n=43).a

Organization or Program Positive Neutral or mixed Negative Total

Local community futures development corporation (CFDC)

4 2 3 9

Local economic development corporation (EDCO)

5 0 3 8

Local or Regional Chamber of Commerce (CoC)

15 10 2 27

Local Business Improvement Association (BIA)

4 3 1 8

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Organization or Program Positive Neutral or mixed Negative Total

Business Development Bank of Canada (BDC)

2 2 3 7

Canadian Youth Business Foundation (CYBF)

1 0 1 2

FedDev Ontario or FedNor 1 0 4 5

Self‐employment benefit program (SEBP)

1 1 2 4

Ministry of Northern Development, Mining and Fisheries (MNDMF)

1 0 0 1

Aboriginal Business Canada (ABC) 1 0 0 1

Scientific Research and Experimental Development (SRED)

1 0 0 1

High school Co‐op students 0 1 0 1

a The comments, of which a sample are presented in Appendix A, were coded as positive, neutral or negative.

We are pleased to see that in general, a lack of trust was not a common reason for individuals not utilizing the programs. Similarly, no more than 10 percent indicated that they lacked time to utilize the programs. That said, among those who did utilize certain programs, multiple individuals (see Appendix A for specific comments) indicated that one of the reasons that they were not satisfied with the programs and/or would not use the programs again in the future was due to the time involved in completing the paperwork associated with funding opportunities. A comment by the owner of a veterinary clinic in Northeastern Ontario, reflects the sentiments of several other respondents as well: “Used to be easier to use; now FedNorth [sic] or other employment funding that I have used or tried to use take up too much of my time to apply and take too long to OK. I have lost opportunities because of this.” To that end, we recommend that programs simplify their application processes as much as possible and make a fast turnaround on funding opportunities a priority as well.

For some of the programs, such as the Canadian Business Youth Foundation (CBYF) and the Self‐Employment Benefit Program (SEBP), we are not surprised that the programs were only used by a small number of the respondents. Both of these programs have specific requirements. In the case of the CBYF the demographic information of our business owners indicates that most would not have been eligible

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for the program based on their age at the time of founding their businesses. We think that there may be an opportunity for some targeted advertising by the CBYF to help encourage youth to start businesses in rural regions. Similarly the SEBP is offered to a very specific set of individuals.

For those programs that had a general focus (that is, all but CBYF and SEBP), we examined whether there were any systematic predictors of the owners’ reactions to a specific program or service—that is, their choice to use the program, their interest in the program, their trust of the program, and so on. In this analysis we only included the reasons selected by at least 10 respondents (see Table 2). In particular we looked for possible predictors such as the population of the area in which the business was located, the length of time the business had been in operation and whether the business was a sole proprietorship. We also considered region and industry. With a few exceptions, which we summarize below, there are no significant relationships between these predictors and the owners’ reactions to various programs.

With respect to age of the firm we find marginally significant differences for both EDCO and the BIA. In both cases it was the younger firms that had either used the programs or had not heard of them. Those companies that were older either felt that the program was not applicable to their business or had no interest or need in using its services.

On average, business owners who had used the BDC were located in areas that had the largest population (47,000), as compared to those who felt that the program was not applicable to them (mean=20,650) or had no interest in the program (mean=23,205). Those owners who didn’t know how to access the programs came from the smallest regions (mean=8,907). These results are not surprising as the BDC likely does not maintain branch offices in towns below a certain size. These population differences are reflected in more general differences we found between regions. Two‐thirds of those who indicated that they did not know how to access the BDC were located in the Northeast versus 55 percent of those who had used the BDC being located in the Southwest.

Marginally significant regional differences were also observed with respect to EDCO and FedDev/FedNor. Among the 12 individuals who had not heard of FedDev/FedNor, over half (55%) were located in Central Ontario. All owners located in the Northeast had heard about FedNor, but they were also the most likely to indicate they didn’t know how to access the programs and services offered by the organization; nearly two‐thirds of those who had responded that they didn’t know how to access the program were located in the Northeast. In contrast, not knowing how to access the service was not the reason given for those in the Northeast not using their local economic development office (EDO); rather, this region accounted for 60 percent of individuals who indicated that they were not interested in their local EDO’s offerings.

The only program for which we see marginally significant industry differences is the local Business Improvement Association (BIA). Sixty percent of those who have utilized the BIA were retail business, while half of those who said they had no interest or need for the program were industrial firms.2

2 That said, just as many retail organizations (n=6) indicated that they had no interest or need in the BIA as those who said that they had participated in its programs.

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Overall, the program that had the highest level of participation was the local or regional Chamber of Commerce; more than half of the respondents indicated they had belonged to this organization at some point. Moreover, all of the respondents indicated that they had heard of the Chamber of Commerce and only a small number indicated that they did not know how to access the service. In addition, analysis of the open‐ended responses (Table 3) reveals that only two individuals had had a negative experience with the Chamber of Commerce. This suggests that the Chamber of Commerce could serve as an important partner for some of the other government programs whose services are either not known (e.g., CFDC) or perceived to be inaccessible (e.g., BDC).

Comparison of owners who use advisors and those who do not

To encourage respondents to tell us about their relationships with advisors, we asked them whether, in running the business, they ever turned to other people for advice about business decisions or simply to “bounce ideas around.” We noted that these could be professionals (formal) or they could be family members (informal) or other acquaintances (informal). Participants were encouraged to select up to two such primary advisors as well as to provide us with information on the kinds and numbers of individuals they consulted more generally. Thus in these analyses, we expect a variety of types of advisors to be mentioned, not just employees of public and para‐public firms.

In this section, we look at whether there are any significant differences between those who used advisors and those who did not, based on three dimensions, namely, the demographic features of the owners themselves, the demographic features of their businesses, and the three aforementioned financial‐related measures. Overall we find that advisor use is mostly driven by characteristics of the business rather than of the owners or their financial situations.

For those owners who did not use advisors of any type we explore the specific reasons for not using advisors.

Demographic features of the business owners

Owner‐managers who used advisors do not differ significantly from those who do not use advisors in any of the following ways: gender, age, highest level of education obtained, length of time running the business, or number of businesses owned.

There is a marginally significant difference in advisor use with respect to the level of the owners’ commitment to the venture. Eighty‐two percent of those who are committed to the venture on a full‐time basis used an advisor whereas just 55 percent of those who are committed to the venture on a part‐time basis had an advisor.

Demographic features of the businesses

Owner‐managers from different regions did not differ in their likelihood of using advisors. Those who did not use advisors, however, were significantly more likely to live in areas with smaller populations. For owners who use advisors, their businesses are located in towns with an average population of nearly 21,000 individuals; in comparison, for owners who do not use advisors, their businesses are located in towns with an average population of around 9900 individuals. These findings are in line with previous research highlighted in our literature review which suggested that the geographic distances and small

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size of communities in rural areas might make it challenging for business owners to locate suitable advisors.

There is also a significant industry difference in the proportion of owners who use advisors. All 21 owners with retail businesses use advisors, compared to 68 percent of those in industrial firms, 70 percent in professional and health services and 77 percent in hospitality. We speculate that given the prevalence of retail stores, owners of these types of businesses might find it easier to find others who understand their business and therefore are able to provide them with advice either formally or informally. Alternatively, it is possible that the non‐retail owners have a level of expertise in their specific trades that is higher than the expertise of owners in the more general retail trade, and so the latter feels more open to advice from others.

At first glance, owner‐managers of businesses that are owned by two or more individuals who are active in the business on a regular basis seem significantly more likely to consult others. It is likely, however, that these advisors include their co‐owners; when we only look at the use of advisors who are not co‐owners, business owners who have co‐owners are no more likely to consult others than those who do not have active co‐owners.

We also analyzed the complexity of the business, the number of employees (including a comparison between those companies without employees and those with employees), and the average number of years for which the company had been in business. None of these characteristics differ significantly between owners who use advisors and those who do not.

Business Performance

One of our broad research goals was to explore the extent to which advisory relationships are linked to business performance. To this end, we examined the data to see whether business owners’ average satisfaction with the financial performance of their firms, based on growth in sales, growth in profits and amount of profits, differed significantly between those who use advisors and those who do not use advisors. We found no significant differences. Similarly, whether or not owners have an advisor is unrelated to their level of dependence on their business revenues to cover their personal expenditures.

There is, however, a significant difference between the level of financial anxiety between business owners who have advisors and those who do not. The average level of financial anxiety among owners who do not use advisors is 3.42 (on a 5‐point scale, indicating that they were slightly above a neutral level of anxiety) versus an average of 2.78 among those who do use advisors. While these results provide a connection between the two variables, they do not provide any information about a possible causal direction. In other words we do not know if those who are financially anxious are less likely to seek out advisors or if soliciting advice from outsiders has the effect of reducing financial anxiety. As detailed in the next section, what we can say is that being concerned about finances was rarely given as an explicit reason for not using advisors.

Reasons given for not using advisors

Of the 80 business owners in our sample, 17 indicated that they “never discuss... business with anyone, not even informally.” Among those owners who do not use advisors we asked them to tell us the main reasons for this decision. Most of them (n=14) provided an explanation; some included multiple reasons.

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A complete list of these explanations is included in Appendix B at the end of this report. For each comment we have noted the business owner’s location and industry.

In a qualitative analysis, we categorized the comments into three main themes. The most popular theme was that these owners felt they have the skills needed to make their own decisions and therefore do not need an advisor. Nine of the comments fell into this theme. For example, one owner of a hotel noted, “[I] have learned when and how to get all info required mostly from past experience.” A similar comment was, “Although I am open to good ideas, I feel that I know best.” Even when an owner may not have the knowledge and skills, there are alternatives to approaching an advisor, as mentioned by an owner working in agriculture, “[I don’t consult] any individual [in particular], but [do speak with] company reps with the knowledge needed for individual products.”

In addition, there were five other comments that discussed hurdles to getting an advisor, such as the cost of advisors, not having access to advisory services, and wanting to maintain privacy. An interesting comment within this theme came from an individual who provided public relation services. He wrote, “Highly specialized business depends on one's personality and experience. Not many people to consult in the field. My loss.” With respect to cost one respondent noted that “Good consultants are too expensive. I can't afford them.” Thus hurdles may come from the assumption that the advisor has to be a paid professional. Finally, one respondent indicated that he did not need an advisor because he was an advisor himself.

Use of formal and informal advisors in general

For the 63 business owners in our sample who indicated that they consult others about their businesses, we asked them to provide us with a rough estimate of the different types of individuals they spoke to about their businesses. We also asked them about the extent to which they felt the information that they received from others is important and whether they are satisfied with their advisors in general.

On average individuals talk about their businesses with 11 individuals (median = 8), including the advisors they have described in more detail (see next section of this report). This total includes an average of two people internal to their companies (e.g., trusted employees, board members, partners), three outside stakeholders (e.g., customers, suppliers), three family members (spouse, parents, children, other relatives) and friends, and two business service professionals (e.g., lawyer, accountant). Because so few employees of government sponsored programs, co‐members of service organizations (e.g., Lions), or “other” individuals (e.g., co‐members of an industry association) are mentioned, these individuals are not included in the averages. The predominance of advisors who are family members, friends, people internal to the business and other stakeholders, supports the notion discussed in the literature that in rural communities there may be increased value placed on these “close‐knit” resources.

Overall, business service professionals are the most frequently consulted, with 87 percent of the business owners who use advisors consulting at least one business service professional. Nearly as many business owners consult family members or friends with 84 percent of the business owners who use advisors consulting at least one family member or friend. Also popular are individuals internal to the company with 73 percent of those who use advisors consulting at least one person in this category. A little over half (56%) consult at least one outside stakeholder. Less than a quarter of all business owners

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who use advisors consult an employee of a government sponsored program (21%), a co‐member of a service organization (17%), or another type of individual (11%).

In general, our respondents are quite satisfied with their advisors (mean = 3.73 on a five‐point Likert‐type scale where 3 = satisfied and 4 = quite satisfied) and perceive their advice to be important to the success of their businesses (mean = 3.25 on a five‐point Likert‐type scale where 3 = important and 4 = quite important).

Among the 63 business owners who consult others, there are no significant differences in the proportion of owners who consult any given type of individual. There are also no significant differences in the general satisfaction with advisors or the perceived importance of the advice that they receive from others. We received the same results when we divided the sample by location. The one exception was that there is a marginally significant (p < .1) difference in the proportion of business owners who consult others internal to their company. In Southwestern Ontario this proportion is .92, while in Southeastern Ontario the proportion is .45. The other two regions fall in‐between, with 78 percent of business owners in Central Ontario and 69 percent of those in Northeastern Ontario consulting one more individuals within their firms. These results are driven by the fact that the businesses in Southwestern Ontario, with an average of 27 total employees are significantly larger than the other three regions, which have an average total of employees in the range of three to five. In other words, the opportunity to consult others within the organization is much greater in Southwestern Ontario than in the other regions.

Description of primary advisors used by participants

In addition to asking owners about their use of advisors in general, we also asked them to provide more detailed information on their relationship with up to two primary advisors. Of the 63 business owners who told us that they use advisors, 24 owners (38%) described a single primary advisor and the other 39 (62%) gave us information about two primary advisors. In total, the 63 owner‐managers who use advisors provided information about 102 people from whom they sought advice. Approximately 58 percent of these advisors are men (the gender of two advisors was not recorded). The average age of the advisors is 54 years old and nearly half of them (45%) fall within the 50‐59 age range. They are a well‐educated group—among those for whom education data was provided, 78 percent have a college degree or higher.

The advisors came from a wide variety of occupations. The most popular occupation is accountants (n=24). Other business support professionals, including consultants, lawyers, bankers, financial advisors and insurers, together make up 14 percent (n=14) of the advisors. This group also includes one employee of a local economic development group. Fellow business owners are also a popular choice for advisors among our owner‐managers (n=18). The occupations of the other 43 percent (n=44) of advisors are very diverse—this group includes managers (n=6), a pilot, hair dresser, funeral directors and several retirees (n=4). Occupations are not specified for two of the advisors.

It seems appropriate that a large proportion of advisors are business support professionals—dispensing advice is the raison d’être of these professions—and it is not surprising that accountants predominate. It is likely that every company has one, and the accountant has an intimate knowledge of many business activities though working on tax returns, audits, payroll or other functions. The frequent use of other

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business owners as advisors may come from a sense of “kinship,” a feeling that there is someone who can truly understand the challenges of owning and running a small business. Advice from others who are undergoing parallel experiences with their own firms is likely seen as an asset. Many of those in the other category had professions that were appropriate to the own business owner’s firm (e.g. a hair dresser who sought advice from another hair dresser) or were family members and friends whose specific occupation may have been secondary to other characteristics used in selecting the particular individual as an advisor.

Demographic comparison between business owners and their primary advisors

Seventy‐five of the advisors live in the same geographic location as the business owners. Among the advisors and business owners for whom we have education information, 17 percent of the business owners are more educated than their advisors, 36 percent have the same level of education, and 47 percent are less educated than their advisors. Advisors are in younger age brackets (19%), the same age bracket (34%), or older age brackets (47%) than the business owners.

Finally, at first glance, both male and female business owners are just as likely to select male advisors as female advisors. When we removed the 18 spouses (of whom 17 are heterosexual couples) from the analysis, however, we find that female owners are significantly more likely to select female advisors and male owners to select male advisors.

Taken together these results suggest that—spouses excluded—owners tend to seek out local advisors who are of the same sex, and who are both more educated and older than they are.

Relationships with primary advisors

Business owners indicated that they met their advisors in a variety of different ways. When we coded their open‐ended responses, these could be grouped into four main categories, namely through their current business (31%), through referrals (12%), because they were family or social acquaintances (44%), and other (11%).

The first category included advisors whom owners had first met through external, internal or professional contacts. Of these, the latter group of professional contacts was the largest (n=7). The next group, referrals, was split roughly between business referrals (e.g., through a business service professional) and social referrals (e.g., through a friend).

The third group, family and friends, consisted of the two largest subgroups. Overall, the single most common way in which individuals indicated that they first met their advisors was because they were related to them (n=34). This included lifelong parent/child and sibling relationships as well as spouses and other relatives. Another common way of meeting their advisors was because they were friends with them (n=14). Finally, the category other included meeting places like school (n=6), prior jobs (n=3), and support organizations (n=2) such as industry associations.

In a related question, we asked business owners to select their primary relationship with their advisor from a number of options. While many respondents provided us with this relationship in response to aforementioned open‐ended question “how did you meet?” for those who didn’t this was an opportunity to do so. The most common primary relationship is that of professional service provider

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(n=26). After professionals (e.g., accountants, lawyers, consultants), the owner‐managers in the sample call upon their spouses (n=22); put differently, roughly a third of the owners who use advisors, list their spouse as one of their advisors. After spouse, the owner‐managers in the sample call upon their parents (n=15) friends (n= 11), other relatives (n= 7) and employees (n= 5) most frequently.

In addition to asking the individuals how they first met, we also asked them why they selected the person as an advisor. Coding these open‐ended responses revealed that 74 of the advisors in the sample had been chosen for knowledge‐related reasons, including domain expertise (n=8), general experience (n=30), or knowledge specific to the business and industry (n=6). Among the quarter that didn’t list knowledge‐related reasons, 12 indicated that they had chosen the person for some aspect of their personality (e.g., integrity, honesty), while the other 11 chose the individuals because they were either family members or friends.

While the three questions—how did you meet, why did you choose him/her as an advisor, and what is your primary relationship with him/her—had significant overlap, as we mentioned above, it was also possible for the three questions to provide different information (e.g., met through a prior job, chose because of industry knowledge, is my spouse). Thus, we looked at responses to all three of these questions when grouping advisors into our four primary relationship categories. These groups are business partners and employees (17%), spouses who are not partners or employees (18%), other family members and friends who are not partners or employees (36%), and advisors who are at “arm’s length” (29%), implying that the basis of their relationship is professional rather than social.

Given the largely social nature of these relationships it is not surprising that nearly two‐thirds of our business owners knew their advisors starting at a point before they began to run their firms. Overall, while owner‐managers with advisors had run their businesses for an average of 12 years (median of 10 years), they had known their advisors an average of 23 years (median of 20 years). Advisors began working with the owners an average of six months prior to the time that owner‐managers began running their firms (median is at founding). In other words, about one third of the advisors began providing business owners with advice about their companies prior to the date at which the owners started to run the companies. About 61 percent of these (n=21) were businesses that the owner inherited or purchased. The remainder indicated situations where business owners began working with the advisors during the planning phase that predated the founding of their businesses.

Overall, these owner‐managers met with their advisors frequently. Sixty‐two percent met at least monthly, and of those, 75 percent met at least weekly. Another 30 percent met multiple times a year and the remaining eight percent indicated that they met with their advisors on a yearly basis, as needed, or at an unspecified frequency.

We asked owners about the topics that they discuss with their advisors. Three‐quarters of the advisors are used as general sounding boards. A number of advisors in our sample are also consulted on specific areas of businesses. These include accounting & tax (54%), customer‐related issues (57%), employee‐related issues (50%), production & operations (49%), sales strategy (59%), financing & expansion (59%), marketing communications (47%), and computers & information technology (23%).

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Trust in and satisfaction with advisors

We now turn to another important aspect of their relationship, namely the extent to which business owners have trust in these advisors. Trust researcher, Nicole Gillespie, has defined trust as individuals’ willingness to be vulnerable in work relationships with specified others. Gillespie has identified two aspects of trust. Reliance‐based trust captures individuals’ willingness to rely on specified others’ “skills, knowledge, judgments or actions, including delegating and giving autonomy.” Disclosure‐based trust captures individuals’ willingness to “share work‐related or personal information of a sensitive nature” with specified others (Gillespie 2003, p. 10). We used Gillespie’s Behavioural Trust Inventory to collect data on these two types of trust.

In general, participants report high levels of both types of trust. Means are 4.10 for reliance‐based trust and 4.04 for disclosure‐based trust (on a five‐point Likert‐type scale), meaning that owners are quite willing to rely on their advisors for skills and knowledge and also to share information with them.

We define successful advisory relationships as those in which the owner expresses satisfaction with the advisor and describes the advice provided as useful. Thus we asked business owners to assess their relationships with their specific advisors in two ways. First, we asked them directly about their overall satisfaction with their advisors, by having them answer “Overall, I am satisfied with my relationship with this advisor.” using a five‐point Likert‐type scale from “completely disagree” (1) to “completely agree” (5). Second, we assessed the perceived usefulness of the advisor’s advice using seven items from the nine‐item scale developed by Smither, Wohlers, and London (1995). The scale was modified to ask them about advice received as a business owner instead of as a team coordinator. The items were meant to measure the extent to which the feedback received was “clear, applicable to job behaviour, and generally useful” (Smither, Wohlers, & London, 1995, p. 72). In general the business owners in our sample are very satisfied with their primary advisors (mean = 4.6 on a five‐point Likert scale) and perceive their advice to be useful (mean = 4.10 on a five‐point Likert scale).

We were also interested in the correlation of business owners’ trust in their advisors with the satisfaction with their advisors and the perceived usefulness of their advisors’ advice. Overall both types of trust correlate positively and significantly to both satisfaction with their advisors and the perceived usefulness of their advice.

Comparison across groups of advisor use and primary advisory relationships

In this section we divide the data three different ways: first we make comparisons based on the primary relationship between owners and their advisors; next we make comparisons based on the advisor’s occupation; finally we make comparisons based on the industry of the business. For each of these divisions we evaluate: the frequency of meetings with the advisor, whether they selected their advisor for knowledge‐based reasons, the topics discussed, levels of disclosure‐ and reliance‐based trust, overall satisfaction with the advisory relationship, and the perceived usefulness of advice.

Relationship to advisor and advisor’s profession

When we compared characteristics of the advisory relationship based on the primary connection between the owner‐managers and their advisors as well as based on the advisor’s profession we found a number of significant differences. These results are summarized in Tables 4 and 5.

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We have chosen to discuss the results of these two analyses together as the two variables—relationship with advisor and advisor’s profession—overlap significantly. Importantly, spouses (Table 4) are often also owners of other businesses or have “other” occupations (Table 5). As mentioned earlier, accountants and other business‐service professionals (Table 5) account for 79 percent of the advisors who are considered to be at arm’s length (Table 4).

Table 4: Comparison of advisory relationships based on advisor’s relationship to owner

Relationship to owner

All

advisory

relationships

Employees

&

business

partners

Spouses

Other family &

friends

Arm

’s length

Model test

Number of advisors 102 17 18 37 30

Meet at least monthly (proportion) .63 .88 .88 .69 .30 9.90**

Chose for knowledge (proportion) .76 1.00 .24 .78 .93 17.86**

Topics of advice (proportion):

Accounting & tax .54 .41 .28 .54 .77 4.48**

Customer‐related issues .57 .88 .55 .62 .33 5.21**

Employee‐related issues .50 .71 .72 .49 .27 4.77**

Production & operations .49 .76 .50 .51 .30 3.38*

Sales strategy .59 .65 .50 .70 .47 1.56

Financing & expansion .59 .65 .67 .51 .60 .51

Marketing communications .47 .71 .56 .43 .33 2.33†

Computers & IT .23 .35 .33 .22 .10 1.86

General sounding board .75 .88 .94 .81 .50 6.14**

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Relationship to owner All

advisory

relationships

Employees

&

business

partners

Spouses

Other family &

friends

Arm

’s length

Model test

Trust (mean)

Reliance‐based 4.10 4.35 4.10 4.03 4.04 .64

Disclosure‐based 4.04 4.13 4.58 4.24 3.43 6.67**

Overall satisfaction with advisor 4.61 4.65 4.72 4.65 4.47 .85

Perceived usefulness of advice 4.10 4.37 4.00 4.08 4.03 1.42

† p < .1 * p < .05 ** p < .01

In both Tables 4 and 5 there is a significant difference in the proportion of each sub‐group that meets at least monthly. Business owners meet with advisors who are arm’s length significantly less often than those from the other three categories. Not surprisingly, 88 percent of the owners meet with advisors who are part of their business or who are their spouses at least monthly. When we divide the data based on profession we find owners are significantly less likely to meet with accountants and other business support professionals on at least a monthly basis. In addition to the specific nature of the advice provided (e.g., tax advice from accountants may only be needed once or twice a year), knowing that the majority of advisors from these two professions are at arm’s length helps to explain why these meetings are less frequent.

All co‐owners and employees are selected for knowledge related reasons, in contrast, only about a quarter of spouses were selected primarily for knowledge‐related reasons. There are no significant differences in the reason for selecting an advisor when the sample is divided by profession (Table 5).

Table 5: Comparison of advisory relationships based on advisor’s profession

Advisor’s Profession

All

advisory

relationships

Accountants

Other business

support

professionals

Business

owners

Other

Model test

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Advisor’s Profession All

advisory

relationships

Accountants

Other business

support

professionals

Business

owners

Other

Model test

Number of advisorsa 102 24 14 18 44

Meet at least monthly (proportion) .63 .25 .43 .88 .83 14.03**

Chose for knowledge (proportion) .76 .82 .92 .82 .66 1.74


Accounting & tax .54 1.00 .36 .44 .36 12.68**

Customer‐related issues .57 .25 .50 .94 .64 8.76**

Employee‐related issues .50 .29 .36 .72 .59 3.67*

Production & operations .49 .21 .36 .67 .64 5.46**

Sales strategy .59 .33 .50 .67 .73 3.90*


Marketing communications .47 .17 .57 .50 .61 4.82**

Computers & IT .23 .21 .14 .28 .25 .32

General sounding board .75 .54 .64 .78 .91 4.66**

Trust (mean)

Reliance‐based 4.10 4.12 4.11 4.11 4.06 .04

Disclosure‐based 4.04 3.27 3.80 4.28 4.42 8.51**

Overall satisfaction with advisor 4.61 4.33 4.64 4.61 4.75 2.63†

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Advisor’s Profession All

advisory

relationships

Accountants

Other business

support

professionals

Business

owners

Other

Model test

Perceived usefulness of advice 4.10 3.97 4.27 4.06 4.13 .79

a The occupation of two advisors was not given and therefore these advisors are not included in this analysis.

† p < .1 * p < .05 ** p < .01

Turning now to the topics of advice on which owner‐managers consult their advisors we find a number of significant differences. Looking first to the relationship with advisors, owners whose primary advisors are their co‐owners or employees are likely to discuss issues related to customers, employees, production and operations, and marketing. They also frequently use these types of advisors as general sounding boards. Advisors who are spouses are used most often as sounding boards and for employee‐related issues. Other family members and friends area often used as general sounding boards and to discuss sales strategies. Advisors at arm’s length are called upon most frequently for accounting and tax advice.

As expected, all accountants are consulted regarding accounting and tax issues. The next most likely topic accountants are consulted about is financing and expansion, an issue for which there are accounting and tax implications. Just a little over half of the accountants in the sample are used as general sounding boards, making them the least popular group to be used in such a way. Owners of other businesses are seen as particularly good sources of advice for customer related issues; nearly three‐quarters are also approached about employee‐related issues, while a little over a third are used as general sounding boards. Ninety‐one percent of advisors in the “other” category are used as sounding boards. After being used as sounding boards they are most frequently consulted regarding sales strategies.

Turning to trust we find that business owners are significantly less likely to disclose information to advisors who are classified as being at arm’s length as well as to accountants. Despite having a lower level of disclosure‐based trust, however, they are no more or less likely to rely on advisors from these groups as from any other group.

Owners perceive the advice from their advisors to be similarly useful regardless of their relationship to the advisor or the advisor’s profession. They are marginally less satisfied with the advice that they receive from their accountants than from advisors in other professions. While we can only speculate on the reasons why this might be the case, two possibilities are first, that the advice that they receive from accountants may not always be the advice that they want to hear (e.g., tax law “X” does apply to you and therefore will cost you $Y) and second, that this is the group of advisors that likely has the highest percentage of paid advisors and, as such, the expectations of and demands placed on these advisors may be higher than those in other groups.

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Industry of business

In our final comparison we considered whether there are any differences in how individuals used advisors based on the industry in which their businesses are located. Overall, as highlighted in Table 6 we find few significant differences and only two worth discussing in more detail here. First, we note that there is a significant difference in the extent to which advisors consult others regarding the use of information technology and computers within their businesses. Overall, this tends not to be a popular point of discussion, but it is significantly more popular among those in professional and health services. We suspect that given the plethora of information technology solutions available to individuals in professional and health services, discussions with their advisors may very well focus on which solution or program. This is in comparison to use compared to hardware type issues (e.g., how to set up an internal network) that may be more common in the other industries.

We also find significant industry differences in satisfaction and perceived usefulness; owners in the hospitality industry are most satisfied with their advisors and perceive their advice to be most useful. One possible explanation for this result is that this industry naturally attracts individuals who are more outgoing and are able to easily establish a rapport with others. This same disposition could translate into a more positive opinion of their advisors. Alternatively, picking up on our earlier discussion regarding the generalist versus specialist nature of the hospitality and retail industries versus the industrial and professional and health services industries, it may be that on average it is more difficult for owners in the latter industries to find advisors who are able to provide the specialized advice they need. In turn this may lead to a lower level of perceived usefulness and similarly, lower overall satisfaction.

Table 6: Comparison of advisory relationships based on industry of business

Industry

All

advisory

relationships

Industrial

Professional &

Health

Services

Hospitality

Retail

Model test

Number of advisorsa 102 29 27 11 33

Meet at least monthly (proportion) .63 .48 .67 .82 .69 1.63

Chose for knowledge (proportion) .76 .78 .69 .55 .87 1.88


Accounting & tax .54 .48 .52 .45 .61 .42

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Industry All

advisory

relationships

Industrial

Professional &

Health

Services

Hospitality

Retail

Model test

Customer‐related issues .57 .58 .63 .64 .48 .52

Employee‐related issues .50 .55 .56 .45 .42 .48

Production & operations .49 .48 .52 .64 .42 .52

Sales strategy .59 .48 .52 .82 .64 1.52


Marketing communications .47 .31 .48 .82 .48 2.92*

Computers & IT .23 .17 .44 .09 .12 4.06**

General sounding board .75 .66 .74 .91 .82 1.25

Trust (mean)

Reliance‐based 4.10 4.02 3.94 4.45 4.16 1.15

Disclosure‐based 4.04 4.01 3.85 4.36 4.13 .75

Overall satisfaction with advisor 4.61 4.52 4.48 5.00 4.67 2.38†

Perceived usefulness of advice 4.10 3.89 4.04 4.40 4.23 2.80*

a The industry of two of the businesses was not given and therefore these advisors are not included in this analysis.

† p < .1 * p < .05 ** p < .01

Recommendations and Conclusion

In this section, we focus on aspects of our research that might be of particular interest to the administrators of public and para‐public organizations that provide support to small businesses. Geographic distances and the small size of communities in rural areas might make it challenging for business owners to locate suitable advisors. In those regions where for‐profit business support professionals may be few and far between, governmental agencies have a large role to play in providing advisory resources for these firms.

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Recommendation 1. We found that about 30 percent of our respondents have never heard of or do not know how to access the programs offered by EDOs, CFDCs and FedDev Ontario. Less than 20 percent have used these programs. On the other hand, all respondents have heard of their local or regional Chamber of Commerce; 55 percent of respondents have used them and nearly all have had positive experiences. Perhaps the local or regional Chamber of Commerce could serve as an important partner for some of the other government programs whose services are either not known (e.g., CFDC) or perceived to be inaccessible (e.g., BDC).

Recommendation 2. Other programs are targeted to specific populations (e.g., the CYBF targets young people; the SEBP targets the unemployed). One quarter to one‐third of our respondents have not heard of these programs. While these established business owners would no longer be eligible for such programs, a lack of awareness among those who could have benefited from such programs suggests that targeted advertising to raise the profile of these programs among entrepreneurially inclined individuals might be beneficial. For example, a CYBF ad campaign focused on encouraging youth to start new businesses in rural areas could be an important aid in revitalizing these areas.

Recommendation 3: Success at attracting funding is pivotal for new or growing small businesses. For programs that offer access to funding (e.g., CFDC, FedDev/FedNor), our findings suggest that the applications process needs to be simplified, and speedier response times on funding opportunities should be made a priority.

Recommendation 4: Approximately one‐sixth of business owners in our sample have used public and para‐public agencies to support their business activities. Of these, more than half reported positive experiences. This is encouraging, but there is definitely room for improvement. Our literature search suggested that increasing the frequency and intensity of interactions with advisees might lead to greater success in establishing satisfactory and effective relationships between business owners and these advisors.

Recommendation 5: Owners appear to spontaneously seek out local advisors who are of the same sex, and who are both more educated and older than they are. If this can be seen as a “comfort zone” in advisory relationships, it might be possible for public and para‐public agencies to use this information to create advisor‐owner pairings that will be more trustful and more successful.

In short, our recommendations focus on suggested avenues to advertise program offerings, the need to simplify application procedures, and the ways to increase satisfaction both with program offerings in general and advisory relationships in particular. The recommendations stem from insights gained from both prior literature and from surveying small business owner‐managers in the rural regions that EDCO and its members service.

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References

Bennett, R. & Robson, P. (2004). The role of trust and contract in the supply of business advice, Cambridge Journal of Economics, 28, 471‐488.

Chrisman, J.J., & McMullan, W.E. Outsider assistance as a knowledge resource for new venture survival. Journal of Small Business Management, 42: 229‐44.

Cumming, D. & Fischer, E. (2010). Assessing the Impact of Publicly Funded Business Advisory Services on Entrepreneurial Outcomes” Osgoode‐York Working Paper Series in Policy Research.

Curran, J., & Blackburn, R. (2000). “Panacea or White Elephant? A Critical Examination of the Proposed New Small Business Service and Response to the DTI Consultancy Paper,” Regional Studies, 34 (2), 181–206.

Dyer, L. & Ross, C. (2008).Seeking advice in a dynamic and complex business environment: Impact on the success of small firms. Journal of Developmental Entrepreneurship, 13, 1‐17.

Gibb, A. (2000). “SME Policy, Academic Research and the Growth of Ignorance, Mythical Concepts, Myths, Assumptions, Rituals and Confusions,” International Small Business Journal, 18 (3), 13‐34.

Gillespie, N. (2003). “Measuring Trust in Working Relationships: The Behavioral Trust Inventory,” paper presented at the Academy of Management annual meeting, Seattle, WA, USA, Aug.

Landry, G., Panaccio, A., & Vandenberghe, C. (2010). Dimensionality and Consequences of Employee Commitment to Supervisors: A Two‐Study Examination, Journal of Psychology, 144, 3, 285‐312.

Lowenstein, G., Prelec, D., & Weber, R. (1999). What, Me Worry? A Psychological Perspective on Economic Aspects of Retirement. With Comment by Matthew Rabin. In H. J. Aaron (Ed.), Behavioral Dimensions of Retirement Economics (pp.215‐251). Washington, D.C: Brookings Institution Press.

Lyons, T. (2002). Building Social Capital for Rural Enterprise Development: Three Case Studies in the United States, Journal of Developmental Entrepreneurship, 7, 2, 193‐216.

McGee, J. E., & O. O. Sawyerr (2003). “Strategic Uncertainty and the Information Search Activities of High Technology Manufacturing Firm Managers: Does Venture Age Matter?,” Journal of Small Business Management, 41 (4), 385‐402.

Mole, K. (2002). “Business Advisers Impact on SMEs: An Agency Theory Approach,” International Small Business Journal, 20, 137‐157.

Mole, K., Hard, J. Roper, S. & Saal, D. (2009). Assessing the effectiveness of business support services in England: Evidence from theory based evaluation, International Small Business Journal, 27, 557‐582.

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Ozgen, E. & Baron, R. (2007). Social sources of information in opportunity recognition: Effects of mentors, industry networks, and professional forums, Journal of Business Venturing, 22, 174– 192.

Pineda, R., L. Lerner, C. Miller, and S. Phillips (1998). “An Investigation of Factors Affecting the Information Search Activities of Small Business Managers,” Journal of Small Business Management, 36, (1), 60‐72.

Ring, J. Peredo, A. & Chrisman, J. (2010). Business Networks and Economic Development in Rural Communities in the United States, Entrepreneurship Theory and Practice, January, 171‐195.

Scott, J. M., and D. Irwin (2009). “Discouraged Advisees? The Influence of Gender, Ethnicity, and Education in the Use of Advice and Finance by UK SMEs,” Environment and Planning C: Government and Policy, 27 (2), 230‐245.

Senate of Canada Report (2008). Beyond freefall: Halting Rural Poverty. Final report of the Standing Senate Committee on Agriculture and Forestry, www.parl.gc.ca

Smeltzer, L., H. Van Hook, and R. Hutt (1991). Analysis of the Use of Advisors as Information Sources in Venture Startups, Journal of Small Business Management, 29 (3), 10‐20.

Smither, J.W., A. J. Wohlers, and M. London (1995). “A Field Study of Reactions to Normative Versus Individualized Upward Feedback.” Group and Organization Management, 20, 61‐89.

Taylor, M. P. (1996). “Earnings, Independence or Unemployment: Why Become Self‐employed?,” Oxford Bulletin of Economics and Statistics, 58 (2), 253‐266.

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Appendix A: Comments on public and para‐public programs

Below is a sample of the open‐ended responses to the question: “For the programs you have used please tell us your level of satisfaction with them. We also welcome any other comments about these or other government sponsored programs.”

Location Business Response to Program(s) useda

Positive Comments

Central Hair salon Chamber of commerce have been excellent with building new clientele and putting our business name out there with local advertising in the community.

Central Martial arts school

Local chamber of commerce was helpful in meeting other business people and getting our name out there.

Northeast Convenience store

Ministry of Northern Development, Mines and Forestry ‐ have used them to help pay wages for a summer student working full‐time. They have been VERY helpful.

Northeast Retail The local community futures program and staff are excellent. We would not have made it off the ground without their funding.

Northeast Retail The self‐employment benefit program was crucial to the success of my business. It gave me a chance to get my business established without having to worry about an income. Aboriginal Business Canada Grants were extremely useful for start‐up costs and marketing. Great programs!!

Neutral or Mixed Comments

Central Motel / hotel Business Development Bank of Canada – help the people but wants to lend more money than required and hold all assets.

Central Food / beverage

No particular satisfaction, however one customer did find my establishment through the chamber of commerce/tourism office.

Northeast Tourism cottages

Community Futures Development Corp – great programs in 2004 & 2005, not as good anymore.

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Northeast Gift and flower shop

We live in a small community so we do not have a lot of resources available [Chamber of Commerce, Business Improvement Association].

Negative Comments

Northeast Veterinary clinic

[FedDev] programs were, 10 years ago, easier to use – now have to fill out Internet (?) or other applications – this takes up too much of my time… the application process takes too long and opportunities become lost .

Northeast Veterinary clinic

Used to be easier to use; now [FedNor] or other employment funding that I have used or tried to use take up too much of my time to apply and take too long to OK. I have lost opportunities because of this.

Southwest Agriculture [Community Futures Development Corp] Too much paperwork! Repetition – same questions and answers – too much time.

Southwest Construction For the most part not satisfied. These groups have no interest in my business or operation [Business Development Bank of Canada].

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Appendix B: Reasons for not using an advisor

Below is a complete list of the open‐ended responses that we received to the question: “If you do not consult any individuals on business matters please tell us why not.”

Location Business Reason given for not using advisors

Northeast Automotive repairs, sales, rentals

Good consultants are too expensive. I can't afford them. Although I am open to good ideas, I feel that I know best.

Northeast Auction & storage

I work with my wife. She is responsible for all financial & business matters related to the business, while I am a sole proprietor, our business operates as a true partnership. Thus I did not respond to your questions, as I felt it may skew your results.

Northeast Mobile and on site storage

No one in our area in this business besides us. Lack of support from our bank ‐ again, no knowledge of our mobile business.

Northeast Construction Not enough time. Too distant from advisors ‐ we operate our business in a remote location.

Northeast Hair dressing Because I've been independent.

Northeast Accounting I am an advisor.

Northeast Bookkeeping/ tax services

I am close to retirement and happy with my present business.

Northeast Dental hygiene I have not yet discussed or consulted with anyone as of now because I want to wait until I hit the 2 year mark, and see if things get under control then. If not, I will consult with someone.

Northeast Driving range We are an independent business.

Northeast Public relations

Highly specialized business depends on one's personality and experience. Not many people to consult in the field. My loss. Wish there were but competition is too severe and clients interested in paying less.

Central Motel / hotel Have learned when and how to get all info required mostly from past

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experience.

Southeast Painting contractor

I work by myself and I am trying to slow down. I never have any problems that I cannot solve.

Southeast Seniors residence

Don't know who to talk to.

Southwest Agriculture Not any individual but company reps with the knowledge needed for individual products.

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Part 2: Venture Capital Financing for Entrepreneurs in Rural Businesses

Dr. Veikko Thiele

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Executive Summary

Entrepreneurs in Canada contribute substantially to the development of innovative products, the creation of jobs, and the growth of the economy as a whole. In particular, local communities benefit tremendously from entrepreneurs that are willing to take risk in order to pursue innovative business opportunities. Entrepreneurs, however, are also highly reliant on external financing and vulnerable to market uncertainties that affect not only their long‐run performance, but also their survival. For instance, only 51 percent of all new ventures in Canada survive their first five years (Fisher and Reuber, 2010).

The objective of this study was to derive specific recommendations that will address the following key challenges for fostering entrepreneurship, particularly in rural communities:

Increase the number of start‐ups that receive external financing;

Improve the survival rate of new ventures.

We focused on venture capital financing which is one of the most important types of financing for start‐ups with high growth potential.

As a basis for our recommendations, we developed a dynamic equilibrium model of the venture capital market with heterogeneous entrepreneurs and venture capital firms (VCs). Entrepreneurs differ with respect to the quality (or market potential) of their business ideas, while VCs are heterogeneous with respect to their management expertise. In each period, VCs decide whether to enter the market (endogenous entry), and to provide selected entrepreneurs with start‐up financing in exchange for an equity stake in their ventures.

A key insight from our analysis is that competition among VCs for investment opportunities has a positive effect on (i) the amount of venture capital entrepreneurs receive for their start‐ups; and (ii), the survival rate of their ventures. This implies that lowering barriers to entry in the VC market (e.g., by reducing administrative hurdles), and thus increasing competition, is an important means to foster entrepreneurship in Canada.

Based on our analysis, we make the following recommendations to spur VC investments in start‐ups in rural communities:

1. Establish publicly‐funded VC funds with a mandate to only invest in regions where local entrepreneurs do not have access to private venture capital.

2. Establish programs that assist entrepreneurs in objectively evaluating the potential of their business models, making appropriate adjustments, and preparing professional business plans that specifically cater to VCs.

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Introduction

The venture capital (VC) market is an important source for entrepreneurs to receive start‐up financing, allowing them to exploit innovative business opportunities. Such entrepreneurial activities are not only crucial for local economic growth, but also for the competitiveness of the Canadian economy as a whole.

The VC market, however, has two key characteristics: First, the market for venture capital is highly cyclical, implying that many potentially lucrative business opportunities are forgone during busts (e.g., Gompers and Lerner (1999, 2003)). For instance, the total fund raised in the US at the peak of the economic crisis in 2009 was an estimated $16.3 billion, a 48 percent decline from its pre‐crisis level in 2007 (Thomson Reuters, 2011). Second, VC investments in start‐ups are clustered geographically, mainly to take advantage of networks between (often serial) entrepreneurs as well as VC fund managers (e.g., Hochberg, Ljungqvist, and Lu (2010)). This implies that rural‐based entrepreneurs, in particular, have limited access to venture capital, which is often the only viable form of financing for risky ventures with a high growth potential.

The research study, generously supported by EDCO, had the following three objectives: First, to develop a dynamic model of boom and bust cycles in the VC market in order to identify the causes of such cycles and the implications for the formation of new firms. Second, to analyze the effect of vertical competition among venture capital firms (VCs) for lucrative investment opportunities on the survival rate of start‐ups. Third, to derive specific policy implications aimed at improving (i) the access to venture capital for entrepreneurs in rural communities; and (ii), the success rate of VC‐backed ventures.

Methodology

We formulated a dynamic equilibrium model of the VC market with heterogeneous entrepreneurs and VCs. Entrepreneurs differ with respect to the quality (or market potential) of their business ideas, while VCs are heterogeneous with respect to their management expertise. In each period, each VC matches endogenously with an entrepreneur, providing two critical inputs: capital and management expertise. An important property of our dynamic model is that every successful investment improves the management expertise of the VC (learning by success). This captures the well documented importance of human capital for the performance of VC investments (e.g., Brander, Amit, and Antweiler (2003); Hsu (2004); Kaplan and Schoar (2005); Gompers, Kovner, Lerner, and Scharfstein (2006); S{ø}rensen (2007); and Bottazzi, Da Rin, and Hellmann (2008)). However, the success of a new venture does not only depend on the quality of the business idea and the management expertise of the VC; it also depends on the non‐observable effort of the entrepreneur (moral hazard). We derived the optimal contracts between VCs and entrepreneurs, and the long‐run equilibrium of the entire VC market.

A key element of our model is that we used so‐called Markov chains to characterize the dynamic equilibrium of the VC market. Using Markov chains has the following two advantages. First, it allowed us to derive the long‐run market equilibrium with endogenous matching despite ex‐ante heterogeneity of entrepreneurs and VCs. Second, we obtained a long‐run distribution of the various potential states of the VC market. The two states of particular interest, the boom and the bust state, arise endogenously in our framework. Our model of the VC market therefore generates – unlike many other theoretical studies on industry dynamics – a dynamic equilibrium with endogenous cycles (i.e., we do not rely on external shocks). Finally, using Markov chains allowed us to shed light on some key properties of boom and bust

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cycles in the VC market. For instance, we characterized the duration of economic cycles in the VC market, and derived the expected time for the market to recover from a bust.

Finally, we focused on the supply side of the VC market, namely venture capital firms. More precisely, we took the number of present entrepreneurs with heterogeneous business ideas as given, but endogenized the number of active VCs in this market. We showed that the equilibrium number of active VCs (i.e., VCs investing in start‐ups) can change over time, potentially leading to boom and bust cycles in the VC industry.

Relation to Literature

Our research study is closest in spirit to Gompers and Lerner (2003). They examined how the equilibrium of the VC market responds to external shocks (e.g., technological improvements) by focusing on the interaction of supply and demand. They showed that market rigidities can explain observed cycles in venture financing. Our research study also aimed at explaining cycles in the VC market; however, we developed a dynamic model where heterogeneous entrepreneurs match endogenously with heterogeneous VCs. Moreover, we do not rely on external shocks to explain cycles in the VC market; boom and bust cycles arise endogenously in our dynamic framework.

Gehrig and Stenbacka (2003) also developed a theoretical model to explain VC investment cycles. They considered a setting where a fixed number of homogenous VCs have incomplete information about the actual value of entrepreneurial projects. VCs can then screen these projects, and decide whether to finance or to reject these projects. A key feature of their model is that rejected entrepreneurs can seek financing from another VC. This can reduce the average quality of available entrepreneurs over time, and thus lead to investment cycles. Our study differs in three important aspects. First, we considered a setting with heterogeneous VCs, where the number of active VCs is endogenous. Second, the success of a new venture does not only depend on the quality of the project, but also on entrepreneurial effort (moral hazard) and the management expertise of the VC. This allowed us to endogenize the survival rate of new ventures, and to examine how it is affected by economic cycles. Finally, we used Markov chains to characterize the dynamic equilibrium of the VC market. This approach leads to a more thorough characterization of boom and bust cycles in the VC market that yields a series of novel insights.

Our study is also related to the equilibrium models of the VC market as devised by Inderst and Müller (2004), Sørensen (2007), and Silveira and Wright (2007). Inderst and Müller (2004) and Silveira and Wright (2007) considered search equilibria with ex‐ante homogenous entrepreneurs and VCs. In contrast, we considered an endogenous matching equilibrium with ex‐ante heterogeneous entrepreneurs and VCs. We showed that ex‐ante heterogeneity generates an unsteady dynamic equilibrium that mirrors economic cycles in the VC market. Sørensen (2007) also considered a matching framework with heterogeneous entrepreneurs and VCs, though in a static setting. In addition to developing a dynamic equilibrium model, the key difference to Sørensen (2007) is that we did not treat contracts between entrepreneurs and VCs as exogenous, but explicitly derived the optimal VC contracts conditional on the degree of vertical competition in this market.

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In our analysis we primarily focused on two characteristics of VC markets: (i) the presence of entrepreneurs with innovative business ideas; and (ii), the number of VCs in the market with sufficient funds to invest in these ideas. We showed that these two characteristics have both a positive effect on the degree of vertical competition among VCs for investment opportunities (which will be important for our recommendations). More specifically, VCs make entrepreneurs with promising business ideas more attractive contract offers: they offer more capital and ask for a lower equity stake in the new venture. A higher number of VCs seeking investment opportunities reinforces this competition effect.

Overall we find that a higher degree of competition between VCs has the following effects:

It shortens economic cycles in the VC market, and accelerates the recovery of the market from an economic bust. This implies that more entrepreneurs receive VC financing over time.

It improves the survival rate of VC‐backed start‐ups (after controlling for other market characteristics such as demand uncertainty and market growth).

It makes investments in start‐ups less profitable for VCs.

The last two effects point to an interesting paradox: VCs prefer less intense competition, even though this would impair the success rate of their own investments. This paradox arises because the higher likelihood for successful investments does not fully compensate VCs for their loss of profits in a more competitive environment. Overall, we find that vertical competition impairs the profitability of VC investments over time.

This has another important implication: VCs have a strong incentive to limit competition, particularly in markets where start‐ups have high growth potential, such as the software industry. For instance, strong networks between incumbent VCs constitute a typical barrier to entry in the VC market, and can thus deter competition from ‘outsiders’ (e.g., Hochberg, Ljungqvist, and Lu (2010)). Our analysis revealed the following consequences of such barriers to entry:

Entrepreneurs with the most promising business ideas receive less venture capital for their start‐ups, thus making them less likely to succeed.

A higher portion of entrepreneurs with less lucrative business ideas does not receive VC financing.

These observations will play an important role for our recommendations below.

Recommendations

Our recommendations address the following two key challenges for improving the financing of start‐ups in rural communities:

Increase the number of VC‐backed start‐ups;

Improve the survival rate of ventures founded by entrepreneurs in rural communities.

It is important here to note that the subsequent recommendations refer to start‐ups with high growth potential, which are typical candidates for VC financing. The recommendations are less suitable for self‐

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employed entrepreneurs whose firms are likely to remain small (e.g., small service firms, crafts enterprises).

Our research showed that increasing competition among VCs is key to improving the financing of entrepreneurs. However, what can be done to enhance such competition, in particular in rural communities? For many small rural communities increasing competition among VCs is not the main concern; VC financing is in fact often “out of reach” for entrepreneurs in these communities. The lack of interest for VCs to invest in start‐ups in rural communities can be attributed to two factors: (i) VCs prefer to invest in start‐ups located in geographical clusters to take advantage of network effects; and (ii), start‐ups in rural communities are often deemed low‐growth investments opportunities, and therefore considered to be less suitable for venture capital.

We will briefly outline and discuss two main alternatives to improve the VC financing of start‐ups in rural communities.

1. Establish publicly‐funded VC funds

The first recommendation is to establish publicly‐funded VC funds with a mandate to specifically invest in start‐ups in rural communities. These public VCs should focus on regions where local entrepreneurs do not have access to VC financing. These public funds should then only invest in start‐ups with high prospects of success; the public VC funds should thus be as selective as private VCs when making their investment decisions.

In contrast, in communities where entrepreneurs do already have access to VC financing, increasing competition through publicly‐funded VCs may be counter‐productive. According to our study, more intense competition among VCs for investment opportunities improves the survival rate of new ventures, but at the same time makes investments less profitable for VCs. Intensifying competition through public VCs can thus have a crowding out effect: some private VCs may then refrain from investing in the local start‐ups.3

To summarize, publicly‐funded VCs can help to provide entrepreneurs in rural communities with start‐up capital. However, such initiatives should be targeted at communities where entrepreneurs do not have access to private venture capital in order to avoid crowding out.

2. Provide other non‐financial support to entrepreneurs

A key challenge for entrepreneurs is to convince VCs of their business model, especially since venture capital is scarce and many potential entrepreneurs compete for it. VCs often screen several hundred business plans before making one investment. The ability of entrepreneurs to effectively communicate their business ideas is thus critical for securing start‐up financing. To improve the access of entrepreneurs in rural communities to venture capital, we recommend establishing programs that assist entrepreneurs with the following:

3 Using data of Canadian VC‐backed ventures, Brander, Egan, and Hellmann (2008) provide empirical evidence that public VCs indeed crowd out private VCs.

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Critical and objective (i.e., unbiased) evaluation of business ideas and their growth potentials.

Identification of suitable adjustments aimed at making their business models more attractive to VC investors.

Preparation of professional business plans, which cater specifically to VCs.

This can help improve the perceived quality of business models, and can thus make start‐ups in rural communities more attractive to private VC investors.

Establishing such (non‐financial) entrepreneurship programs in rural communities has the following advantages: First, it improves the chances for entrepreneurs to receive venture capital for their start‐ups, which in turn has a positive effect on the local economy. Second, if a critical mass of local entrepreneurs receives VC financing, it can lead to regional innovation clusters with strong network effects, thus attracting other VCs to invest. This would eventually intensify competition among VCs for investment opportunities in regional start‐ups, and according to our study, improve the survival rate of all VC‐backed ventures. We note, however, that this process will take several years, if not decades; and, the success will inevitably vary across regions depending on local characteristics such as population, proximity to larger cities, and local economic growth.

Conclusion

It has long been recognized that entrepreneurs contribute tremendously not only to their communities, but also to the Canadian economy as a whole. However, securing start‐up financing remains a challenge for many entrepreneurs, particularly in rural communities.

Our study focused on the market for venture capital as one form of start‐up financing. We developed a dynamic model of the VC market to derive specific recommendations on how to improve

1. the access to venture capital for entrepreneurs in rural communities; 2. the success rate of VC‐backed ventures.

In general, we find that vertical competition among VCs for investment opportunities has a considerable impact on the dynamics of start‐up financing. Interestingly, a higher degree of competition enhances the survival rate of new ventures, meaning that more start‐ups succeed over time.

To spur VC investments in start‐ups in rural communities, we derived the following recommendations:

1. Establish publicly‐funded VC funds with a mandate to only invest in regions where local entrepreneurs do not have access to private venture capital.

2. Establish programs that assist entrepreneurs in objectively evaluating the potential of their business models, making appropriate adjustments, and preparing professional business plans which cater to VCs.

Finally we note that such initiatives need to account for regional differences in order to maximize the impact on entrepreneurship in rural communities. Thus, as a next step, it is essential to thoroughly

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analyze data on entrepreneurship in Canada in order to quantify the expected costs and benefits of the proposed programs, and ultimately to tailor them to individual communities.

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References

Bottazzi, Laura, Marco Da Rin, and Thomas Hellmann (2008): Who are the active investors? Evidence from venture capital. Journal of Financial Economics, 89, 488‐512.

Brander, James A., Raphael Amit, and Werner Antweiler (2003): Venture Capital Syndication: Improved Venture Selection versus the Value‐added Hypothesis. Journal of Economics & Management Strategy, 11(3), 423‐452.

Brander, James A., Edward J. Egan, and Thomas F. Hellmann (2008): Government Sponsored versus Private Venture Capital: Canadian Evidence. NBER Working Paper No. 14029.

Fisher, Eileen, and Rebecca Reuber (2010). The State of Entrepreneurship in Canada. Website: www.ic.gc.ca/sbresearch, accessed June 03, 2011.

Gehrig, Thomas, and Rune Stenbacka (2003). Venture Cycles: Theory and Evidence. CESIFO Working Paper No. 882.

Gompers, Paul, Anna Kovner, Josh Lerner, and David Scharfstein (2006): Skill vs. Luck in Entrepreneurship and Venture Capital: Evidence from Serial Entrepreneurs. NBER Working Paper No. 12592.

Gompers, Paul, and Josh Lerner (1999): The Venture Capital Cycle (MIT Press, Cambridge, MA).

Gompers, Paul, and Josh Lerner (2003): Short‐Term America Revisited? Boom and Bust in the Venture Capital Industry and the Impact on Innovation. Innovation Policy and the Economy, 3, 1‐27.

Hochberg, Yael V., Alexander Ljungqvist, and Yang Lu (2010): Networking as a barrier to entry and the competitive supply of venture capital. Journal of Finance, 65, 829‐859.

Hsu, David H. (2004): What Do Entrepreneurs Pay for Venture Capital Affiliation? Journal of Finance, 59(4), 1805‐1844.

Inderst, Roman, and Holger M. Müller (2004): The Effect of Capital Market Characteristics on the Value of Start‐up Firms. Journal of Financial Economics, 72, 319‐356.

Kaplan, Steven N., and Antoinette Schoar (2005): Private Equity Performance: Returns, Persistence, and Capital Flows. Journal of Finance, 60(4), 1791‐1823.

Silveira, Rafael, and Randall Wright (2007): The Venture Capital Cycle. Working Paper.

Sørensen, Morten (2007): How Smart is Smart Money? A two‐sided Matching Model of Venture Capital. Journal of Finance, 62, 2725‐2762.

Thomson Reuters (2011): National Venture Capital Association Yearbook 2011. Website: http://www.nvca.org/index.php?option=com_docman&task=doc_download&gid=710&Itemid=93, accessed May 12, 2011.

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Part 3: Building Community Capacity through Sustainable Development

Dr. Alison Blay‐Palmer

Matthew Murphy, MES Candidate in Business, Queen's University

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Executive Summary

Given the emerging importance of green economic activity as the new development wave (UNEP, 2011; OECD, 2011), it is critical that Canada establish a leadership role in this area. Without taking steps to make this happen we gamble our future prosperity and risk becoming laggards instead of innovators. Given the potential for future economic development, this study looked at the green energy industry in Eastern Ontario as a way to bracket challenges and opportunities for new industries in the green sector. Our key recommendations are provided in Table 1. They can be summarized as the need to:

1. Provide supportive, stable, transparent policy and funding over the medium‐ to long‐term; 2. Create a provincial Green Development Institute to foster knowledge translation and

dissemination; 3. Continue to ensure adequate numbers of skilled labour; 4. Provide fact based information for public education; 5. Develop a strategic approach for the province so all communities have the opportunity to

benefit; and, 6. Ensure an iterative approach to policy and program development and execution.

Table 1: Recommendations: Transferable lessons for green industry

Need for transparent policy and programs that are stable over the medium‐ to long‐term

Stable funding from innovation through to consumer, e.g., World Bank Green Funds

Establish a provincial Green Development Institute with regional affiliates to foster frequent exchanges between all players in the value chain (see Appendix A) from lab to consumer to generate trust, share information, identify opportunities and get products to market

Training programs in step with supply chain needs

Comprehensive Life Cycle Analysis and full cost accounting to facilitate decision/policy‐making and public education

The need for multi‐pronged/market differentiated approaches to sustainable economic development so different regions carve out niches in appropriate and different areas

An iterative approach to policy and program development and execution

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Introduction: The Context for the Green Economy

While we have been talking about the ‘green economy’ since the late 1980s (e.g., Pearce et al., 1989) it has only recently taken off as a foundational principle for corporate and economic development initiatives in the last decade. Given the relatively recent interest, the pace of change is remarkably rapid, transforming the competitive environment at an equally fast rate. The widespread adoption of Corporate Social Responsibility (CSR) initiatives in large corporations and associated policy underlines both the swift uptake and relevance represented by the convergence of ‘green’, the economy and social dimensions of sustainability. On the one hand, this acceleration makes it especially difficult for already challenged regions to keep up. On the other hand, in an economy such as Eastern Ontario where there are new start‐ups and small businesses, this may present an opportunity to develop a competitive edge (what Schaper (2010) and Pastakia (1998) called ecopreneurship).

The United Nations Environment Program (UNEP) defines the green economy as one that results in,

…improved human well‐being and social equity, while significantly reducing environmental risks and ecological scarcities. In its simplest expression, a green economy is low carbon, resource efficient, and socially inclusive. In a green economy, growth in income and employment should be driven by public and private investments that reduce carbon emissions and pollution, enhance energy and resource efficiency, and prevent the loss of biodiversity and ecosystem services. (UNEP, 2011, p. 2)

Accordingly, the green economy is quickly becoming the new standard around the world. For example, while China had a vanishingly small share of the solar panel market in the early 2000s it is now the largest manufacturing country in the world (Brown, 2008). Jurisdictions without the capacity and vision to move into this new reality risk being innovation laggards and as a result economically marginalized. Many global private enterprises support this view. As PricewaterhouseCoopers reminded us there are other reasons to be good corporate citizens, "there is mounting evidence that companies that act in a responsible manner consistently do better than others in the long run” so that while,

...in the last hundred years [we] have seen a tremendous rise in the power of businesses in societies…Well‐run corporate entities have become the primary motors not only of economic progress but also, increasingly, of social change. There are growing expectations that companies should use their significant power and influence for the common good. (PwC, 2005, 7‐8).

There is also evidence that Canadians in government, business associations and non‐ governmental organizations appreciate the potential that green economic activity offers to address convergent goals including: Addressing climate change challenges, 'unifying' policy approaches as a way around silo thinking, promoting economic diversification and the associated benefit of diminishing risk (CIELAP, 2011). Suggested foundational principles for a definition of 'green economy' would include, "ensuring fairness and equity, and addressing unjust disparities; systems based and holistic, integrating all three spheres of sustainability; and strengthening resilience and reducing vulnerability." (CIELAP, 2011, p. i, emphasis in the original).

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As the Organization for Economic Cooperation and Development (OECD) explains, it is important to ensure that green economic development is not conflated with sustainable development but that both approaches are undertaken simultaneously so that,

Green growth is not a replacement for sustainable development, but rather should be considered a subset of it. It is narrower in scope, entailing an operational policy agenda that can help achieve concrete, measurable progress at the interface between the economy and the environment. It focuses on fostering the necessary conditions for innovation, investment and competition that can give rise to new sources of economic growth – consistent with resilient ecosystems. (OECD, 2011, p. 3)

Increased resilience through more diverse, progressive economic opportunities makes green economic development particularly attractive. Interest in green energy is increasing across the country as demonstrated by the growth in both wind and solar electricity generating capacity across the country. Canadian wind energy capacity reached a total of 4,708 MW in 2011 with Ontario producing 35% of this overall capacity (Figure 1; refer to Appendix B for existing and planned Ontario projects).

Ontario is well positioned to take advantage of the multiple opportunities presented by green economic initiatives. Building on earlier programs that supported alternative energy such as solar hot water heaters, the provincial government made a bold move in 2009 and put its Green Energy and Economy

Figure 1: Installed Canadian wind energy capacity, 2011 (Canadian Wind Energy Association, 2011).

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Act into place. The act was modeled after legislation introduced in Germany that has created a vital green energy sector since its inception with over 300,000 jobs (Turner, 2011). The Ontario Feed‐in Tariff (FIT) program, the major pillar of the Green Energy Act, aims to stimulate investment in green energy by guaranteeing prices for energy created using wind, solar, hydro, biomass, biogas and landfill gas over a twenty‐year period. It also supports Ontario manufacturing through its minimum domestic content requirement. While there is room for improvement including a greater emphasis on conservation, "the Green Energy Act is one of strongest pieces of environmental legislation in the country and has situated Ontario as a world leader in renewable energy." (Marshall, 2011) Given this focus by the Ontario government and the importance of this initiative in Eastern Ontario, this sector of the green economy was the logical choice as a primary area of concentration for this research project. It was not the sole focus though, and through interviews we also engaged experts in the fields of green chemistry, biomass and hot water technologies as part of the project as we looked at opportunities for green development. As a subset of this research we also undertook a preliminary study on Corporate Social Responsibility dimensions.

Methodology

To gain an in‐depth understanding of the needs of key players in both areas of interest, we conducted semi‐structured, key informant interviews. The questions were developed with input from economic development officials in Eastern Ontario. In total, forty interviews were conducted with experts in both green economic development (30) and Corporate Social Responsibility (10) in Eastern Ontario between May and mid‐September 2011. To better understand the challenges and opportunities in the area of green economic development, four researchers, twelve business owners/operators (three from multinational corporations and nine from SMEs), five community economic development officials, four sector association officials, one infrastructure key informant, three technology transfer experts and one consultant were interviewed. In the area of Corporate Social Responsibility, interviews were conducted with three head office officials and seven key informants working in branch offices. The majority of the interviews were conducted by phone and all interviews were transcribed. Eighteen of the forty key informants agreed to have their comments directly attributed to them. The balance preferred to remain anonymous.

Given the impressive amount of green economic activity taking place in Eastern Ontario and in the interest of developing a meaningful understanding within the confines of this preliminary project, the research project was necessarily restricted to the green energy sector including solar, wind, biomass and chemical innovations and technologies. By limiting the scope to these areas we were able to develop a broad sense of the vibrancy of and challenges for this sector. This approach has proven fruitful as it provides a snapshot of an emerging green cluster and the lessons that can be transferred beyond this area to other areas of green economic development. In the next phase of this research we will broaden our scope to include other sectors within the green economy and other parts of Ontario.

The priority in both cases is to identify regional economic development opportunities as a vehicle for more vibrant communities. This will build on environmental and other sustainability considerations by different size corporations and institutions in the region, and will help to establish the extent of connectivity with respect to existing and potential transfer of best practices and norms in this vital area.

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Findings and Analysis

The following section presents the findings from key informant interviews with experts in the area of the green economy. The results are presented by category and are structured in keeping with the interview question topics. Accordingly, the themes are challenges (both primary and secondary) and opportunities followed by a section that elaborates recommendations for the sector and also for more general green economic development.

Challenges

Table 2 summarizes the challenges described by key informants. The table is divided into two sections:

1. The primary challenges as identified by the overwhelming majority of key informants; and, 2. Insights into secondary challenges identified by fewer than four key informants.

This distinction is made as there was a notable consistency for what we are calling the primary challenges, and it is worth making note of this as we move forward as addressing these challenges could make a substantial difference to the sector. The secondary set of challenges identified is more specific to a group being interviewed (e.g., researchers or SME owners) as opposed to themes of concern to everyone interviewed.

Table 2: Key sector challenges

Primary challenges Unpredictable government policy and programs and lack of long‐term commitment

Immature supply chain

Inadequate capital to support emerging opportunities throughout the chain from innovation to consumer

Need for more robust networks and connections

Secondary challenges Inability to get installed projects connected in some parts of the province

Bottlenecks in permitting process

Lack of appropriate building codes and city planning

Difficulty interacting with the organizations implementing the programs

Not‐in‐my‐backyard (NIMBY) attitudes

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Primary challenges

The key challenges that can be applied widely to any type of green economic development are discussed in this section. These primary challenges as reported from key informant interviews are:

1. Unpredictable government policy and programs and a lack of long‐term commitment; 2. Immature supply chains; 3. Inadequate capital to support emerging opportunities throughout the chain from innovation to

consumer; and, 4. Lack of understanding about existing and emerging technologies.

Policy and Programs

While several challenges were raised during the interviews, key informants repeatedly and consistently discussed the need for stability with respect to green economic development policy and related programs. This is not surprising given the circumstances at the time of the interviews. Context is important here as the research was conducted in the Summer of 2011 during the lead up to the early October provincial election. At that time most of the key informants’ attention was focused on the threat by the opposition party to cancel the FIT program if elected. This produced a chill that settled on the industry over the summer as researchers, SMEs and consumers waited for the election to take place. Orders dried up, hiring was deferred, people lost their jobs and companies looked for ways to consolidate. Understandably, then, there was a pre‐occupation with the policy and program vulnerability that exists under the current system. One key informant drove this point home:

Without stability, a company can’t plan for the long‐term. They can’t make infrastructure investments and expect a return if they don’t know what is going to happen to the market. What is really needed is something like a five‐year plan and that cannot be done right now [due to the pending election].

Not only is stability needed on the supply side, it is also essential for consumers who can pull product through the supply chain. Additional stability is needed in terms of the types programs offered so that there is adequate time to inform the public and allow them to arrange for installations. In the last five years several programs have been offered for solar hot water heaters and other renewable technologies that were changed or cancelled. This undermines public understanding about the programs, their ability to engage with green energy as a viable solution and ultimately undermines provincial attempts to implement a green energy program. According to one expert,

The biggest challenge is political and/or legislative uncertainty... For example, the Eco Energy Program had just been cancelled when the solar water heater rental program was started. Because the incentives were gone, manufacturers were selling solar hot water heaters at a lower price to stimulate demand...Shortly after the business was launched the Eco Energy Program came back with an incentive of $1,250. That changed the business model. Installation costs went up because installers were back in demand – the incentive changed the way the market operated. Capital costs also went up. Retailers were able to sell solar water heaters at higher margins, which drove all of the costs up. The incentive was then raised to $2,500 for one year. Shortly thereafter, the

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Eco Energy Program was cancelled all together. Now it is back. In between all of this, the FIT Program was launched... All of this means that we have seen the incentives and government policy at both provincial and federal levels bounce around like a yo‐yo over just the last three years. That makes it very difficult...to invest.

Dr. David Hyndman, the CEO of the renewable energy consultancy Hyndman and Associates, made the point that there needs to be a level playing field from a financial and competitive capacity standpoint with respect to other non‐renewable energy options,

So it’s stable policy, fair but not burdensome compliance, and incentives in the short term to get this shift in place...we are competing against coal and petroleum coke industries that are 100 or so years old and have worked out all the bugs in terms of shipping, logistics, cost and don’t seem to be held to as high an environmental standard as something new coming in. We need to make sure that incentives are in place to get over the existing infrastructure.

A related point is the need for comparative costing for consumers that includes externalized costs such as subsidies to fossil fuel based technologies and environmental damage from pollution and greenhouse gas emissions.

Supply chain

Another important consideration is the immaturity of the supply chain that is in part attributable to the age of the industry. Several experts who were interviewed predicted that given the minimum domestic content requirement this should improve over time. As Robert Christie from Cleave Energy explained,

The Ontario domestic requirement demands that solar companies buy from Ontario‐based suppliers. Cleave Energy has its own racking line as well as local suppliers for racking. There is a panel manufacturer coming to Prince Edward County. This is a relatively high‐tech, low‐impact industry ‐ a type that wouldn't necessarily be attracted to the area without the presence of Cleave Energy and the FIT program.

According to Rick Rooney, owner and operator of Quantum Renewable Energy, a company that specializes in solar hot water, photovoltaic and wind energy systems, "there wasn’t an Ontario supplier before the domestic requirements." Rooney then proceeded to explain that while manufacturing is scattered around the province in places like Sault Ste. Marie, firms seem to be clustering in Southwestern Ontario. Along with others, he suggests this is a way to deal with auto industry downsizing and layoffs. This type of opportunity has led some jurisdictions to actively develop supply chain opportunities. Stephen Paul, Manager of Economic Develoment for Lennox and Addington County, stated that,

Their overall strategy is to develop the supply chain for solar/wind power and not necessarily investment attraction. The focus is on how local suppliers can benefit from investments in green technology and attracting manufacturers (e.g., solar panel) so that green initiatives such as a solar park or wind farm have access to the local supply chain they need to comply with Ontario's new domestic content requirements.

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Another key informant identified the potential to build innovation into the domestic requirement in the FIT program as a way to stimulate more provincial R&D.

Funding

There are related funding challenges. These challenges exist throughout the supply chain from people in labs creating new innovations through to the consumer. High capital investment costs up front for researchers; companies undertaking to manufacture, distribute and install systems; as well as consumers, create barriers to the success of these programs. Researchers and some economic development experts indicated the need for more money to fund both basic, curiosity‐driven research as well as money to do research that has immediate applications. There is also, as one key informant put it, “a gap in terms of navigating the funding maze.” On the supply side, more funding is needed to help companies develop the missing pieces in the supply chain that would make the industry more robust. Echoing what many experts interviewed expressed, one key informant explained that, “The first challenge is a lack of money and there is a lot of competition for what is available.” This individual went on to elaborate concerns specific to biomass where,

…there is a great reluctance from angel, venture capital, and traditional investors. They are hesitant to invest in something that has an agricultural base. Agriculture is always susceptible to weather, and one season can be better than another. This has presented a problem in the past.

A key informant from a multi‐national corporation suggested that more support for industry could translate into more opportunities for the region:

The government could increase the level of funding that is available to support green research. For a global company...that has choices around where to do development work, having local funding available certainly helps attract additional work to Canada as opposed to having it done in the United States. If you are involved in R&D then often you have more of an influence on where and how technologies are commercialized.

On the end‐user part of the chain, the upfront capital needed to take advantage of the micro‐FIT and FIT programs can prevent people from getting involved. Despite attractive rates of return, people looking to make the initial investment are unable to find the capital to pay for the installation. Increased flexibility by some banks is helping to overcome these issues but this requires more attention. For businesses, while the investment makes sense in the medium to long‐term (i.e., seven plus years), capital is hard to come by:

The biggest issue with making these switches [to green energy initiatives] is the capital investment involved. That’s where money comes into it. There is some low hanging fruit but a lot of the major returns require significant upfront investment.

However, as the sector becomes increasingly mainstream, more institutions are engaged. This process has begun according to one key informant:

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There are bankers, real estate agents, and lawyers who realize that there is a lot of economic activity going on that they need to be aware of. Bankers need to know whether this is something they can arrange financing for on its own merits or if they need separate collateral. Insurance companies need to figure out how to insure products. Real estate agents need to know how to help people buy and sell homes with a green component and what the value is. This is a subtle but significant development.

In the assessment by Christie from Cleave Energy,

Many people want to install solar, but banks will not attribute value to the contracts. This is changing slightly. Banks are now offering financing, but it is an unsecured line of credit which is very much dependent on personal income. The technology is relatively new to Ontario banks, and banks tend to be conservative.

However, as three key informants noted, there is some progress:

With respect to financing green initiatives, the banks have come a long way. A couple of them like RBC and TD have recognized that ‘green’ is a good industry to be part of. Part of the problem is a lack of understanding about the actual financial returns associated with green products and technologies, although that is lessening.

Networks and flows

A related finding is the lack of connections from and flows between:

1. The lab into commercialization streams; 2. The policymakers to the end‐user of the technologies; and, 3. The policymaker to the public and the extent to which people understand the merits of green

energy options.

There was a pervasive sense and frustration on the part of researchers that the innovation being developed upstream is not making its way through to the commercialization phase. One researcher described the process to get an innovation from the university lab to the commercialization phase as frustrating the innovation process since,

It [innovation] never gets adopted by industry because industry expects so much. They expect kilograms of sample and full development and you can’t do that in a university setting. It is beyond the University’s ability and mandate. So the technology dies, the patent is allowed to lapse and it ends up being a nice paper which is a disaster. Scientifically it is fine, but in terms of benefit to the environment there isn’t any... This is a tremendous waste. All of this talent going toward making green technologies and we are not using it. That is the biggest challenge. How do you get the better ideas – the ones that could actually make it – to the market place?

Funding is part of this challenge as money is needed to do the research:

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We talk about Ontario and Canada being innovative and wanting innovation to be the driver of our economy. Yet everything gets stuck at research and development because we can’t get the funds to get things out the door and onto the shelves so that people can actually buy them.

There is also a disconnect along the supply chain so that researchers may not understand the local resources at hand. In one case, a researcher in a MNC organization explained that one of their processes could draw from many different types of biological energy sources but it wasn't clear to the MNC how they fit into the local supply chain. As a result, an opportunity could be missed as there is a lack of connection between new green initiatives and the opportunities they could offer local firms and suppliers. This seems to be equally true for economic development officers and business. As Kathryn Wood from the environmental consulting firm Natural Capital Resources explained,

It is difficult for those in economic development to talk with those in business. There are often big visions about what we could do in a particular green arena in a region or the province, but these visions never really seem to get down to the level of the individual business. Until we can learn to reach individual businesses, they will be doing green development by themselves.

With respect to policy and its translation the FIT programs highlight several problems. While the program itself receives praise, its implementation has been plagued with several difficulties. As previously mentioned, political uncertainty created a void around the program for several months as people in the industry did not know whether the program would continue. There were also logistical issues,

Part of the government’s argument for taking the entire summer to develop the program was that they wanted to get it right. Eight months into the program, they changed the incentive for the ground mount because the interest was greater than they ever anticipated. They did this without any consultation and shook the confidence of suppliers and outsiders that are participating in the program. So the FIT program was just poorly managed. The government makes changes without consulting the industry. There is a good industry association that will help make educated choices but the government does not engage the stakeholders. These are just a few of the problems. Now there are problems with Hydro One.

This key informant goes on to explain he attributes these problems to poor information flows and a lack of consultation with key players:

This is because Hydro One wasn’t at the table as a stakeholder and they are… [now] rejecting contracts that the OPA [Ontario Power Authority] approves. The net result is that companies are the ones that suffer. There are vast amounts of territory where they can’t install systems.

One result of poor information sharing is the inability of some distribution companies to connect power generation projects to the electricity grid. There are people with signed contracts to provide power at the rate set by the government and who have installed generating capacity on this basis. However, they

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are unable to sell their power and realize revenue on their investment as their power sources are not linked into the electricity distribution infrastructure. As one expert said,

The biggest challenges have been connecting to the grid. Anytime you are out of the Kingston Utilities zone, there is [a] chance that Hydro One will not be able to connect clients. There is a review going on that should help them loosen their criteria so that they let more projects onto the grid, but for now it hasn’t happened.

The extent of disaggregation within the power system into multiple organizations that do not communicate effectively with one another is a substantial challenge to implementing government policy and has created mistrust between people who instead should be working together to create a vibrant green economy in the province,

Studies are now underway to determine what the proper percentage of allocation is on the grid. In Ontario, the cap is 7% of feeder station capacity for PV. This is not a number that was arrived at by studying other grids – they just decided that. A study shouldn’t be necessary to determine the proper allocation – the government should be able to look at Germany and see that some areas have 25‐30% solar. It is not really an engineering or capacity problem. Solar actually alleviates capacity. You don’t have to send 100MW up a high voltage power line if all of the farms in the area have solar panels – they are powering themselves. It is somewhat disingenuous that the government is using this number as a capacity issue. A major complaint is the level of planning that went into the FIT program before it was implemented. The government could have been more prepared.

The final primary barrier raised repeatedly by key informants is the degree of consumer confusion about the potential multiple dividends from green energy alternatives. This is linked to uncertainty about the comparative costs of traditional, fossil fuel technologies with green energy. So while the vision is applauded, there is a disconnect between the goals of the provincial government to develop a green industry and its ability to communicate the real benefits to consumers. As on expert explained,

We should try to focus on economic benefits and on the bottom line. This is something that can get people interested and involved. Pointing a finger at people who do not recycle or drive an SUV is not helpful. If you can demonstrate the benefits of green technologies and products, it will get people involved. It’s all about what is in it for the average person – what will they gain from it in the end (i.e., financially).

Tom Carpenter from the Queen's Institute for Energy and Environmental Policy stated,

There is a need to make people aware not only of environmental problems and the need for change but also that there are solutions and the solutions are things that are available. Many of the solutions offer opportunities in terms of employment and wealth. The challenge is to get people to think of themselves and their community as a potential solution to environmental problems and recipients of the benefits of change.

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Secondary Challenges

This section reports on more specific logistical challenges associated with green energy initiatives. In particular, key informants mentioned the need to streamline the processing of permits, provide appropriate building codes, and for infrastructure to make the process more mainstream. One example that was mentioned by three interviewees is insurance to cover any liabilities associated with, for example, solar panel damage from weather. Several key informants also discussed their difficulties interacting with the organizations implementing the programs beyond getting linked into the grid. Michael Tiffe from Tab Mechanics, a firm that provides services to the building commissioning industry, explained that,

There are challenges with regulatory bodies and building inspectors because green technologies are fairly new. Some inspectors don’t want to learn new technologies and they can create problems.

The lack of appropriate building codes and city planning also makes getting programs out into the field a challenge. In some cases, key informants reported the not‐in‐my‐backyard (NIMBY) problem. This was an issue largely for wind installations.

Opportunities: Ingredients for success

Not unexpectedly, key informants were supportive of the direction taken by the government with many people interviewed indicating that the policy, while not perfect, was a bold step and gave the province the opportunity to become a North American leader as it moves from a fossil‐fuel based economy to a green economy. According to key informants, the benefits of having this kind of commitment in Ontario are manifold and could reverberate throughout the supply chain. However, what was also abundantly clear is the need for a firm commitment going forward.

In addition, as this key informant explained there are other opportunities that could be integrated as a complement to the FIT initiative:

Other areas of government policy that could be improved include carbon credits and sustainable growth. One of the key challenges is that products produced from renewable resources are often more expensive than similar products made from crude oil. The incentives that the Ontario government has put in place for renewable energy have helped to drive that sector. That is another good way the government could look at fostering a strong, renewable economy.

Robert Christie, from Cleave Energy, observed that the industry is offering solutions to persistent challenges for the local community but also in the long‐term when we factor in the future of traditional energy sources,

Solar energy has been good for rural Eastern Ontario. It has created jobs for installers, office staff, and developers. It has created an additional income for businesses, farmers, and homeowners. Farmers are getting their retirement income from installing a couple of microFITs. Some farmers do not have another source of revenue. They are cash‐rich

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from selling their quota and solar gives them a place to put their money to generate income and create long‐term jobs. This is an important feature of distributed generation and the solar model. Overall, solar is creating revenue for people and bringing money into rural communities. It is also creating maintenance, manufacturing, and consulting jobs…Traditional energy sources are becoming less certain. When a nuclear power plant blows up or a war in Libya affects the price of oil or a pipeline under the Yellowstone river fractures, people get interested in alternative sources of energy and energy efficiency. GHG emissions and the climate change debate also bring attention to alternative energy.

A community support that was mentioned repeatedly is the educational institutions. According to key informants, these organizations are punching above their weight. The colleges are doing an excellent job getting skilled labour into the job market. While there are suggestions that more skilled labour is needed, overall the experts interviewed concluded that a good current and upcoming labour pool exists. The not‐for‐profits Kingston Employment Youth Services (KEYS) and Reducing Energy Demand Youth (REDY) were both mentioned as offering important linkages between employers and employees. Universities were cited as developing increasing capacity for green R&D as more projects and labs take on green‐related initiatives. This has been going on for some time, and has provided the leadership and foundation for many of the networks either in existence or emerging today.

Several key informants discussed the opportunities linked to improving conservation efforts as a way to improve efficiencies and educate the public about the benefits of thinking about doing things in a different way. Green energy is part of this equation as one expert pointed out,

Maybe we should be considering much increased conservation measures. An obvious example would be to provide people with a discount on a new energy efficient appliance if they have an old, inefficient one. If we put our heads together we can come up with different ways of providing these types of incentives to the community. Then the whole community psyche is focused on ‘we shouldn’t be doing that because of this’ ‐ either for the environment or for the economy or for society. It starts with education and at the grade school level. You change the attitude of parents because kids are coming home and saying ‘you should be recycling.’

As mentioned earlier, the domestic content requirement is creating market opportunities. Based on responses from SME key informants supply chains are increasingly localized within the province with all of the experts interviewed indicating they are moving as quickly in that direction as possible. There was a higher degree of trust in products manufactured within Canada and preference was given to Ontario sourced products.

Recommendations

There are multiple benefits to the economic activity related to green energy generation in Eastern Ontario. Not only is this good news, it is instructive for other types of green economic activity under consideration. In trying to seed more green industries there are some important points to consider (refer to Table 3).

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Table 3: Recommendations: Transferable lessons for green industry

Need for transparent policy and programs that are stable over the medium‐ to long‐term

Stable funding from innovation through to consumer, e.g., World Bank Green Funds

Establish a provincial Green Development Institute with regional affiliates to foster frequent exchanges between all players in the value chain from lab to consumer to generate trust, share information, identify opportunities and get products to market

Training programs in step with supply chain needs

Comprehensive Life Cycle Analysis and full cost accounting to facilitate decision/policy‐making and public education

The need for multi‐pronged/market differentiated approaches to sustainable economic development so different regions carve out niches in appropriate and different areas

An iterative approach to policy and program development and execution

First, the foremost challenge for the overwhelming majority of key informants was the need for consistent, long‐term policy and related programs to support green economic development. This pointed unequivocally to the need for long‐term commitments to these types of programs for them to be successful. The paralysis that seized the industry during 2011 makes the need for government leadership crystal clear. The positive results of the Green Energy Act as well as other policies and programs are becoming more evident as new companies are attracted to different parts of the province. For example, there are several new green technology‐related manufacturers in Ontario with an estimated thirty related companies in the Kingston area alone. One firm established itself in response to both provincial policy and initiatives by the county to support industries and provide quality of life for its citizens. This points to the synergies that can accrue from forward thinking that provides the supportive policy and program environment combined with local amenities and strengths.

However, in the same way that every region in the province cannot develop a biotechnology cluster, green energy initiatives must build on the real and potential assets of each geographic area. As Kathryn Wood from Natural Capital Resources explained,

More attention should be paid to what in the green economic development arena will differentiate an area from the other places that want to do green development. This involves careful evaluation of an area's assets, infrastructure, human capital, geographic location, and climate among other things. There is a lot of wistful thinking in that many places want to do green development, but have not determined whether it is the right fit or if there is another strategy that is better suited for their development needs.

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For example, according to key informants, Eastern Ontario has access to substantial amounts of non‐food source biomass making it a good place for the development of biomass‐based energy production. It also has relatively inexpensive land. As a result, wind and solar installations are becoming more common. Also of importance is the ability for the utility to act in a streamlined manner. This has facilitated a more coherent implementation of programs and reliable connections of energy‐producers to the grid. In addition to ensuring that investors in green technology are able to realize promised benefits, it is important that the public understands the extent to which programs are successful.

There is also a need for programs that understand and are responsive to the niche opportunities, For example, the long timelines faced by woodlot owners who engage in sustainable forestry practices. Patient capital and/or appropriate taxation programs would help to make that part of the green economy more robust for woodlot owners.

Given the importance of public perception about the efficacy of green energy programs, it is also necessary to ensure that implementation runs as smoothly as possible. To this end, the province can take leadership. They can adopt a facilitative role in getting past bottlenecks impeding the implementation of their policy by creating dialogue between key partners including Hydro One and the Ontario Power Authority. Thinking forward, the implementation of the Green Energy Act provides lessons for future green economic initiatives. In developing policy, it makes sense to engage stakeholders from the outset. There is also the need for feedback loops to be created so that people making decisions can communicate in a meaningful way with policymakers (Westley et al., forthcoming). This will help to ensure that policy can and will be implemented. Given the new four‐year mandate for the provincial government, now is an excellent time to undertake such an initiative.

Clear direction needs to be backed up with other important supports. There is a need to inventory regional organizations, roles and capacity and regularly connect these together through conferences and workshops where people have the opportunity to interact, understand needs and build a coherent strategy and associated supply chain. For example, in and around Kingston, the New Energy Project and Green Centre Canada bring together Queen's University, St. Lawrence College, municipal and regional economic development organizations with a couple of private companies. SWITCH also offers networking opportunities and there are some investment funds available through PARTEQ at Queen's. While these are critical, they are not enough. These excellent initiatives need to be expanded to include manufacturers, financial institutions, policymakers, end‐users and other stakeholders. Regional networks would then need to be connected through, perhaps, the CFDCs or Centres of Excellence to generate a critical mass for the green sector as a whole. A provincial Green Development Institute with regional affiliates could help to fill this gap. Fostering networking opportunities with German cities could provide valuable supports for the existing industry. With respect to program implementation one key informant pointed out that the organizations delivering the programs need to be involved in policy, and especially program, development. There may also be opportunities to learn from other jurisdictions that have implemented similar initiatives. Some examples of how this has succeeded are Ontario`s Toxic Reduction Act that was modelled after policy in Massachusetts and, as stated earlier, the Green Energy Act which was derived from German policy and programs.

At the same time, balance is needed so innovation can get into the hands of end‐users. Rui Resnedes, at Green Centre Canada cautions,

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The challenge has always been one of focus and resources, critical mass and expertise. Green Centre works to address the challenges that have traditionally kept Canadian technologies mired in early‐stage development. The traditional model of technology transfer is institution centric, has limited resources, and personnel are forced to address technologies from every possible facet of physical and sometimes social sciences. Because of these requirements, it has been very difficult if not impossible to undertake any meaningful, targeted development activities intended to de‐risk promising technologies to a point where they become attractive opportunities for established multinationals or the investment community. Green Centre has a number of resources to help bring green technologies to market ‐ capital, expertise, infrastructure, and a well‐established network with industry and regulators. However, the Centre has already become resource limited. There are more opportunities across Canada than they could possibly work on, so one of the challenges is deciding which projects to undertake.

This points to an elaborated role for economic development experts who can provide market research support to communities to determine where their strengths lie and how they can participate in green economic development. Working with market analysts, ED people can decide how to proceed with this kind of initiative, what it should look like and how it should be rolled out. Resendes suggests the questions that need to be asked include,

What are other people doing?

How can this help address problems in my own backyard?

How can this complement technologies in our portfolio and enable/solve problems that we are having in getting products to market?

There is also the opportunity to celebrate successes as a way to educate the industry and the public about the economic benefits such as increased jobs and the environmental benefits of green economic initiatives. As one key informant observed,

The biggest challenge, which is also an opportunity for the area, is that there are a lot of successes already but they are a little bit under the radar. The opportunity is to showcase all of the things that are already going on, perhaps through a web portal or through network meetings and events. Showcasing could help to attract more activity to the area. There is a need to see where the gaps are and try to fill them.

These benefits need to be quantified for industry and the public. So for example, counting the number of jobs created by green industry or celebrating the hiring of all the graduates from the St. Lawrence College wind energy technician program makes a positive impression for the industry and helps to reinforce green economic activity as beneficial in the eyes of the public. This would both normalize the industry as an important part of the economic landscape and help to educate the public about environmental benefits of the industry.

Understanding these benefits could help make the case for increased public investment. As Rui Resendes from the Green Centre Canada stated,

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The government needs to realize that for the time being, the investment community is not ready to address green technology. Venture capital funding is not flowing as freely as it was. A lot of VCs that used to invest in pre‐revenue companies have shifted their policies and now only invest in post‐revenue companies. Someone is going to have to pick up the slack. Whether we like it or not, it is the government who is going to have to do it. If there is not private capital to fuel marketplace innovation because of recent economic trends, the government has to fuel the initial stages of marketplace innovation until such a time as the market recovers. And it will. VCs will build their funds to a comfortable level and resume investing in pre‐revenue companies because the multiplier is much greater.

More money would help to embed the green energy sector in the province and create opportunities well into the future. Some key informants suggested the government could facilitate access to capital to finance installations for consumers. While no one suggested how this could happen, low interest loans could be an option worth considering. More money could also support the creation of innovation at the research and development stage. Researchers called for more money to conduct curiosity and applied driven types of research. We know from the literature that both types of innovation are critical to the long‐term innovative capacity of a region. Ultimately this impacts the extent to which a region leads innovation, the extent to which it can attract talent, and is linked to potential economic success (Blay‐Palmer, 2007; Gertler and Wolfe, 2004). Banks are beginning to understand the advantages of offering credit to various people involved in the sector, but more work is needed. One avenue to explore is the creation of a Green Investment Fund/Bond that people living in Ontario and elsewhere could invest in. A potential model is offered by the World Bank.4 The World Bank Green Bonds offer investors a chance to achieve a return on their investment and help the world deal with climate change. Since beginning the program in 2008, the World Bank has issued over $US2 billion in bonds.

Better consumer education and quality of information would help to alleviate confusion about the merits of green electricity. Two interviewees suggested there is the need for full Life Cycle Analysis so everyone understands the true costs associated with choosing one kind of electrical generating direction over another, as one key informant explained, we need, "a fact‐based, as opposed to an opinion‐based, approach to energy policy." As Jared Mackay at Quantum Renewable Energy explained,

In order to bring more people aboard, a detailed cost‐benefit analysis is needed on what people are actually paying per KWh and what fossil fuel companies are actually receiving in subsidies. If people had a better understanding of where their money is going, they would have a better view of renewable energy.

The Ontario Clean Air Alliance offers a calculator that allows Ontarians a way to estimate their greenhouse gas emissions if they use a conventional electricity provider versus supporting more green energy options.5 The UK Parliamentary Office of Science and Technology provides estimates for the UK for carbon footprints.6 This work could be done for Ontario to give consumers a better sense of how

4 http://treasury.worldbank.org/cmd/htm/WorldBankGreenBonds.html 5 http://www.cleanairalliance.org/choices/greenpower.html 6 http://www.parliament.uk/documents/post/postpn268.pdf

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adopting greener technologies helps to bring about change. At the same time, the cost of fossil fuels is trending up while cost of alternatives is coming down. This also helps to make alternatives more attractive.

It is clear from this research that different scales of operations have different needs and capacities in the green economy chain. To be resilient it would be beneficial to support and grow all of these scales to have a diversified economic base for the province. This will make Ontario competitive in the long‐term. We will have products and expertise to export and be more energy self‐reliant going into the future.

Conclusion: Green Economic Activities in Eastern Ontario

This research confirms the value of clustered economic activity as a way to capitalize on shared human, social and infrastructure resources (Porter, 2000; Gertler and Wolfe, 2004). Eastern Ontario is developing a reputation as a leader in green energy and has the emerging institutions to support these assertions. A momentum is growing that underpins the industry at all scales from the household through to multi‐national corporations. This has been fostered to a large degree by the Green Energy Act layered over existing economic development experts who are committed to growing the industry, researchers able to create an innovative learning environment, manufacturers and installers dedicated to supporting the market, educational institutions flexible enough to roll out technical programs in response to industry needs, and a utility able to manage installations in a coherent manner. Combined, these factors nurture this nascent industry and help to build a solid foundation moving into the future. They also provide signposts for other green economic development and can act as a model for the necessary supports for a green industry to succeed.

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References

Blay‐Palmer, A. 2007. Who is minding the store? Innovation strategy, the social good and agro‐biotechnology research in Canada Canadian Journal of Regional Science. 30(1): 39‐56. (1)

Brown, L. 2008. Plan 3.0: Turning to renewable energy, solar cells and connectors. Earth Policy Institute. Accessed online November 29, 2011 at: http://www.earth‐policy.org/books/pb3/PB3ch12_ss4

Canadian Institute for Environmental Law and Policy. 2011. A Green Economy for Canada: Consulting with Canadians. Accessed online November 29, 2011 at: http://cielap.org/pdf/CIELAP_GreenEconomy.pdf

Canada Wind Energy Association. 2011. Canadian Wind Farms. Accessed online November 29, 2011 at: http://www.canwea.ca/farms/index_e.php

Clean Air Alliance. n.d. Electricity choices: Green power suppliers. Accessed online November 29, 2011 at: http://www.cleanairalliance.org/choices/greenpower.html

Gertler, M. and Wolfe, D. 2004. Local social knowledge management: Community actors, institutions and multilevel governance in regional foresight exercises. Futures 36: 45–65

Marshall, D. 2011. Backgrounder: Ontario's Green Energy Act. David Suzuki Foundation. Accessed online November 12, 2011 at: http://www.davidsuzuki.org/blogs/climate‐blog/2011/08/backgrounder‐ontarios‐green‐energy‐act/

Organization for Economic Cooperation and Development. 2011. Towards Green Growth, Summary. Accessed online November 29, 2011 at: http://www.oecd.org/dataoecd/40/62/47984000.pdf

Pastakia, A. 1998. ‘Grassroots Ecopreneurs: Change Agents for a Sustainable Society’, Journal of Organisational Change Management 11(2): 157‐73.

Pearce, D., Markandya, A., and Barbier, E. 1989. Blueprint for a Green Economy. Earthscan: New York.

Porter, M. 2000. Location, Competition, and Economic Development: Local Clusters in a Global Economy. Economic Development Quarterly 14: 15‐34.

Turner, C. 2011. The Leap: How to Thrive and Survive in the Sustainable Economy. Random House: Toronto.

Schaper, M. 2010. Making Ecopreneurs: developing sustainable entrepreneurship. Second edition. Corporate Social Responsibility Series. Gower Publishing: Surrey.

United Nations Environment Program. 2011. Green Economy: Pathways to Sustainable Development and Poverty Eradication, A Synthesis for Policy Makers. Accessed online November 29, 2011 at: http://www.unep.org/greeneconomy/Portals/88/documents/ger/GER_synthesis_en.pdf

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Whit, The Organizational Behaviourist. 2009. Triple Bottom Line Sustainability and Value Chain Analysis. Accessed online December 14, 2011 at: http://whittblog.wordpress.com/2009/10/20/triple‐bottom‐line‐sustainability‐and‐value‐chain‐analysis/

Westley, F., Antadze, N., Riddell, D., Robinson, K and Geobey, S. (working paper currently under review by publisher) Pathways to system change. Working paper for Social Innovation Generation (SIG) University of Waterloo. Accessed online December 13, 2011 at: http://sig.uwaterloo.ca/sites/default/files/documents/Pathways%20to%20System%20Change%20Working%20Paper_0.pdf

World Bank. 2011. World Bank Green Bonds. Accessed online November 29, 2011 at: (http://treasury.worldbank.org/cmd/htm/WorldBankGreenBonds.html

UK Parliamentary Office of Science and Technology. 2006. Carbon Footprint of Electricity Generation. Postnote 268. Accessed online November 28, 2011 at: http://www.parliament.uk/documents/post/postpn268.pdf

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Appendix A – Sustainability Value Chain7

7 Whit, The Organizational Behaviourist. 2009. Triple Bottom Line Sustainability and Value Chain Analysis. Accessed online December 14, 2011 at: http://whittblog.wordpress.com/2009/10/20/triple‐bottom‐line‐sustainability‐and‐value‐chain‐analysis/ Derived from work by Michael Porter. 1985. Competitive Advantage: Creating and Sustaining Superior Performance. Simon and Shuster, The Free Press: New York.

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Appendix B – Ontario Wind Capacity

Installed Wind Capacity in Ontario (http://www.ieso.ca/imoweb/marketdata/windpower.asp)

Wind Farm Capacity (MW)

Operational

Amaranth I,Township of Melancthon 67.5 Mar. 2006

Kingsbridge I, Huron County 39.6 Mar. 2006

Port Burwell (Erie Shores),Norfolk and Elgin Counties 99 May 2006

Prince I, Sault Ste. Marie District 99 Sep. 2006

Prince II, Sault Ste. Marie District 90 Nov. 2006

Ripley South, Township of Huron‐Kinloss 76 Dec. 2007

Port Alma (T1) (Kruger), Port Alma 101.2 Oct. 2008

Amaranth II, Township of Melancthon 132 Nov. 2008

Underwood (Enbridge), Bruce County 181.5 Feb. 2009

Wolfe Island, Township of Frontenac Islands 197.8 Jun. 2009

Port Alma II (T3) (Kruger),Municipality Chatham‐Kent 101 Dec. 2010

Gosfield Wind Project, Town of Kingsville 50 Jan. 2011

Spence Wind Farm (Talbot), Townships of Howard and Oxford

98.9 Mar. 2011

The following wind projects are currently under development:

Project Capacity (MW)

In Service*

Dillon Wind Centre (Raleigh) 78 2011‐Q1

Greenwich Wind Farm 98.9 2011‐Q3

McLean's Mountain Wind Farm I 50 2011‐Q3

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McLean's Mountain Wind Farm III 10 2011‐Q3

Comber East Wind Project 82.8 2011‐Q3

Comber West Wind Project 82.8 2011‐Q3

Pointe Aux Roche Wind 48.6 2011‐Q3

Conestogo Wind Energy Centre I 69 2011‐Q4

Summerhaven Wind Energy Centre 125 2012‐Q1

Bow Lake Phase I 20 2012‐Q2

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Part 4: Corporate Social Responsibility

Dr. Alison Blay‐Palmer

Matthew Murphy, MES Candidate in Business, Queen's University

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Executive Summary

This study is a preliminary exploration of the relationship between Head Office Corporate Sustainability goals and the extent to which they are taken up by branch offices, and serves as a compendium to the Building Community Capacity through Sustainable Development study above. The rationale for undertaking this project is to scope out opportunities for rural communities through local green development. From the pilot study with ten key informants, key factors appear to be:

1. strong commitment at the director level for CSR; 2. part of the vision for corporate resilience; 3. flexible and realistic targets; 4. capacity to support community‐driven interpretation for CSR‐related projects; 5. understanding from Head Office that CSR is one of a suite of expectations; 6. client pre‐occupation with price usually as primary decision‐maker.

These recommendations need to be qualified by the very supportive comments that all Branch Office employees made about CSR initiatives and the credibility they give to companies within communities across the country.

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Introduction: The Context for Corporate Social Responsibility

The secondary area of research for this project is the extent to which corporations are developing Corporate Social Responsibility (CSR). This area is directly related to the capacity for a region to engage in green economic initiatives. According to the OECD,

Green growth strategies need to pay specific attention to many of the social issues and equity concerns that can arise as a direct result of greening the economy – both at the national and international level. This is essential for successful implementation of green growth policies. Strategies should be implemented in parallel with initiatives centering on the broader social pillar of sustainable development. (OECD, 2011, p. 3)

In keeping with this insight, in addition to the green economy research, this project also undertook a preliminary set of interviews with key informants in head offices and affiliated branch offices on issues related to CSR.

Methodology

Ten key informants were interviewed for this preliminary look at Corporate Social Responsibility. Nine were from insurance and financial institutions with three in head offices and six in branch offices. The tenth expert works in a multi‐national manufacturing corporation. Given the small interview pool, this was intended from the outset to be an initial attempt to explore CSR strategies developed in head offices and determine how they are implemented by branch offices. This work will continue in the summer of 2012.

The interview questions are available in Appendix A. The questions were developed in consultation with CSR and ED experts.

Findings

There was a consensus among those interviewed that the level of commitment by senior directors determines the extent to which CSR programs are successfully adopted and implemented in a company. Accordingly, this commitment to environmental and community needs to be reflected through the allocation of resources,

The first thing you need to put something into action is to have someone at the top that understands and cares. None of this could happen without executive leadership and sponsorship.

The more deeply embedded CSR is in all aspects of organizational philosophy and operations, the greater the chance for acceptance and uptake. One key informant explained that CSR needs to be understood as key to developing organizational resilience for the employees, clients and financially and that it been seen as a "business advantage". As a key informant observed, “[It] helps to build from a solid history of community engagement and commitment with associated robust policies.”

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It was evident to everyone interviewed that there are different challenges and opportunities for Head Office (HO) and Branch Office (BO) locations. The industry key informants work in is a key consideration as the people working in the branch offices all had direct contact with clients. This means that, for example, face‐to‐face contact was part of their jobs limiting the scope they have available for some CSR‐related goals such as reducing carbon footprints through less travel. On the HO side, employees frequently had more flexibility as they are not working within the constraints of direct client‐based operations.

A related consideration is that as companies get larger it is more challenging to implement CSR goals across the entire organization. As key informants all work for companies with national or multi‐national scope and billions of dollars in assets, organizational size is a consideration. This means that different aspects of the organization require different CSR goals so that a strong commitment and vision from Head Office must be accompanied by flexible and realistic targets. Commitment, sincerity and backup from Head Office make a substantial difference on the ground. As one key informant reported this is achievable, “Head Office has been very good in making sure that the programs they install are ones that can be easily maintained by the branches.” This means that programs can be translated into achievable results and are taken seriously. Employee empowerment seems to be another common denominator for successful CSR implementation. As well, there needs to be two‐way open flow for Branch Offices to feel engaged. There is a need to get specific input from the BO to HO about the issues and challenges important to individual communities.

While HO can provide the direction and support, implementation needs to be unique in each community. This has positive and negative dimensions. Implementing some programs can be challenging as not all sustainability initiatives are supported throughout entire communities (e.g., push back regarding wind energy) so initiatives need to be chosen carefully. This requires that BOs be sensitive to individual community needs and priorities. It is important to be informed and able to provide input that makes a difference. CSR can allow the front line offices of an organization to reflect the individual feeling of the community/neighbourhood in which it operates by supporting local initiatives. Effective CSR programs at the community level and autonomy from Head Office allows branches to develop credibility in local communities. Head office needs to be an enabler, “it is about consulting, connecting with and understanding the differences” between communities and regions across the country. It was widely understood, though, that there is huge value in being part of the community and 'giving back'. Oftentimes it is possible to do this in a way that also meets corporate CSR goals. There are many positive results from BO employees engaging with community to bring about lasting change as they work towards sustainability goals. BO staff mentioned the sense of personal satisfaction they get from being part of their community and the associated pride in environmental and other CSR‐based achievements. One key informant commented that it also helps if you can find solutions that save money especially given current economic times.

Not unexpectedly, there is a preoccupation with operational details at the branch level so CSR can be perceived as 'an extra' and that, as one branch key informant stated, "CSR initiatives are on top of everything else." Time is a key constraint for branch offices in implementing HO CSR initiatives. Implementation expectations from HO need to be in line with the realities in the communities and their resources including financial and time considerations. It is important for employees to see how CSR can make their jobs and lives better. So using the earlier example, HO needs to understand the extent to

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which things like reduced drive times by holding conference call meetings instead of every meeting being face‐to‐face do or do not fit into branch office business realities.

For branch operations there is the very real challenge to meet price point with products that are also green as price is reported by HO and BO key informants as the important decision point for most clients. It is also critical to have clear guidelines from regulators to facilitate different physical plant programs or investment tools (e.g., financing for green energy projects) so that on the ground it is clear what is and is not acceptable when developing CSR‐motivated initiatives.

Overall, CSR is seen as a benefit to head offices, branches and their communities as it offers everyone the chance to work towards and achieve better places to live and work. As is widely acknowledged, talented people seek out corporations interested in being good citizens. Effective CSR policy is one way to realize this goal.

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References

Organization for Economic Cooperation and Development. 2011. Towards Green Growth, Summary. Accessed online November 29, 2011 at: http://www.oecd.org/dataoecd/40/62/47984000.pdf

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Appendix A – Interview Questions

Green economic development interviews:

SMEs/other firms and researchers

1. Are you engaged directly or indirectly (e.g. supporting) in ‘green economic’ activity? If yes, how?

Low carbon initiatives: Resource efficiency: Social inclusion: Pollution reduction: Biodiversity‐loss prevention:

SMEs/Other firms/Economic development experts

2. What challenges do you face in adding to green economic activity? Local/regional? Provincial? National? Global?

3. What opportunities are available to help you enhance green economic activity? Local/regional? Provincial? National? Global?

4. What do you need to engage in more green economic activity? Money? A champion? Critical mass in the organization/community so you feel there is more support than perceived risk? Local/regional? Provincial? National? Global?

5. Where are your clients located?

6. Where are your suppliers located?

7. Do you use R&D as part of your business model? Do you work with outside organizations to for R&D?

8. Does the community support/oppose these initiatives?

Researchers

2. What challenges do you face in conducting ‘green’ research? Local/regional? Provincial? National? Global?

3. What opportunities are available to help you enhance ‘green’ research? Local/regional? Provincial? National? Global?

4. What do you need to engage in more green economic activity? Money? A champion? Critical mass in the organization/community so you feel there is more support than perceived risk? Local/regional? Provincial? National? Global?

5. Where are your suppliers located?

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6. Where are your public/private collaborators/clients located?

7. Does the community support/oppose these initiatives?

Corporate Social Responsibility Interviews

1. Are you engaged directly or indirectly (e.g. supporting) in ‘green economic’ activity? If yes, how?

Low carbon initiatives: Resource efficiency: Social inclusion: Pollution reduction: Biodiversity‐loss prevention:

Head office:

2. What are the key principles of your CSR policy?

3. How do you translate your policy into action?

4. How embedded is CSR in organizational policy? Action?

5. Are there differences in what you can achieve in head office/ urban/ peri‐urban/ rural offices?

6. What are the challenges for head office/branch office for implementing CSR policy in smaller urban and rural areas?

7. Does the community support/oppose these initiatives? What do you need to engage in more green economic activity? Money? A champion? Critical mass in the organization/community so you feel there is more support than perceived risk? Local/regional? Provincial? National? Global?

8. What are the benefits for head office/branch office for implementing CSR policy in smaller urban and rural areas?

Branch office:

2. What are the key principles of your corporate head office CSR policy? Do you have your own CSR policy?

3. How do you translate HO policy into action?

4. Are there differences in what can be achieved in head office and in your office?

5. What are the challenges for head office/branch office for implementing CSR policy?

6. What are the benefits for head office/branch office for implementing CSR policy in?

7. Is it realistic to expect that branch offices implement CSR policy? What are the benefits? Drawbacks?

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8. Does the community support/oppose these initiatives? What do you need to engage in more green economic activity? Money? A champion? Critical mass in the organization/community so you feel there is more support than perceived risk? Local/regional? Provincial? National? Global?

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Part 5: Developing a Rural Public Transportation Network

Kevin Majkut, MSc

Under the Supervision of Dr. Chialin Chen

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Executive Summary

The following report discusses an original model and three step framework to develop a public transit system in any rural community equipped with a Geographic Information System (GIS). The report also analyzes and discusses potential rural transit routes for Prince Edward County (PEC) using the aforementioned model and framework. The model and framework used in this report will clearly show how Prince Edward County and other rural communities can optimize their future public transit systems.

Prince Edward County is a municipality in Southern Ontario and is located between Kingston and Toronto, Ontario. Some of the larger communities within the municipality include Picton, Wellington, and Bloomfield. The combined population of the municipality is approximately 25,000, with a population density of 24.3/km2, and an area of 1,000 km2. One of the main attractions for PEC is Sandbanks Provincial Park in Picton, which attracts thousands of tourists during its summer months. PEC has shown interest in further developing its public transit service in order to serve its aging and growing population, as well as its many tourists.

The Monieson Centre at Queen’s School of Business was appointed in 2011 by the Economic Development Council of Ontario (EDCO) to develop a framework that will help PEC and other rural communities create rural public transit systems. The findings of the report will help economic developers and municipal leders foster economic development. Increased public transportation can help citizens access essential destinations such as hospitals, grocery stores, and pharmacies. It can also increase economic activity through local tourism and access to community retail outlets.

This report involves extensive research of existing practices and theories for urban and rural public transit development. Best practices, as well as models from top‐tier journals, were used to develop a comprehensive model and framework to generate rural public transportation routes. The technical model and framework was then validated and applied to PEC to determine optimal public transit routes with the use of its GIS and Google Earth. This same model and framework may be applied to any rural community with active roadways and a community GIS.

This study is designed to provide a practical guide for rural community developers. Some of the technical components in this report are complex, however, the framework is clearly outlined with flowcharts and detailed steps that make analysis quite manageable. This report should be used by rural community leaders as a starting point when deciding which type of public transit to pursue, and how to generate potential routes for a new transit system. More importantly, this report will provide a very useful tool that will allow rural communities to prepare for future growth and foster economic development.

Introduction8

8 This section and the “Rural Public Transportation” section below have been adapted from Majkut (2011) available at www.economicrevitalization.ca.

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Implementing effective rural transportation systems can increase accessibility to essential services, make personal travel easier, and increase the quality of life for citizens in rural communities. Rural transportation systems can lead to lower commuting costs for residents, thereby increasing intercity travel and fostering development of local and regional businesses. Rural community leaders must identify pressing issues of rural transportation systems before strategic plans are developed. Best practices and case studies may be used as a guideline for future transportation systems, while recognizing the need for local, provincial, federal, and stakeholder support. Policy leaders must recognize the need for rural transportation systems to better plan for the future (Majkut, 2011).

There are currently no comprehensive decision support tools available for rural community leaders who are interested in developing a rural transit system. This paper introduces a three step decision‐making process for generating transportation routes for a rural transit system, provides detailed instructions for implementing a unique model, and validates this model through a case study done for a rural community. The model is based on access to a community’s Geographic Information System, and uses information gathered from the system to create rural transportation routes.

The framework included in this paper shows rural community leaders with access to a GIS how to develop potential rural transit routes, compare existing and potential routes, and choose the optimal route for implementation. Step‐by‐step instructions are provided to guide community leaders in the planning, data gathering, model development, and route generation and testing phases. This paper offers a general framework for any rural community to develop and evaluate new and existing rural transportation networks.

There are very few rural accessibility and evaluation models available to rural community leaders. The most commonly used forms of spatial interaction methods are not customized for rural areas and are limited by the number of variables included in the model. Some rural transportation models have been developed, such as the Rural Public Transit Accessibility (RPTA) Model (Sanchez, 2002), but either lack the ability to properly scale variables in the model or have a subjective scaling method that compromises the accuracy of the model. This paper offers a GIS‐based model that is customized for rural areas, uses an objective scaling method, and is applicable to any rural community.

Vehicle Routing and Scheduling (VRS) problems have been studied extensively for many years, including famous routing methods such as the “Sweep” method (Gillet and Miller, 1974) and the “Savings” method (Clarke and Wright, 1964). VRS methods are included in this paper, but only represent a small part of the overall framework. VRS methods focus on visiting a certain number of nodes in a network, while adhering to defined constraints such as capacity, time, distance, and vehicles available. These methods assume that the user already has transportation nodes in place, which will probably not be the case for upcoming rural communities. In addition, rural communities will often lack the data required to solve a transportation route using an advanced VRS method. This paper provides a detailed process to guide rural community leaders when developing nodes for a rural transit network, and VRS methods and iterative techniques are used to solve for optimal transportation routes.

Purpose

The purpose of this report was to develop a GIS‐based framework to help rural community leaders generate optimal transportation networks with standardized routes and schedules. The framework will

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serve as a general tool that may be applied to any rural area, as long as relevant data and technology are available.

Rural Public Transportation

According to Transport Canada (2009), senior citizens use public transportation more than any other age group in Canada. By the year 2031, approximately 25% of Canada’s population will be 65 or older. In addition to this, many young Canadians aged 20 to 44 are moving to large urban centres, which is increasing the proportion of senior citizens in rural communities. This section will discuss some of the challenges, issues, impacts, best practices, and policies for rural public transportation in Canada.

Challenges

Two of the greatest challenges in rural mobility for Eastern Ontario and Western Quebec are residents’ access to healthcare, and the fact that many elderly citizens are unable to drive (Kostiuk, 2009). Rural public transportation can also be important for disabled Canadians and low income families.

Healthcare is an essential service, so it is important that citizens in rural communities have access to sustainable transportation. Personal automobiles are used in many rural communities, obviating the need for public transportation; however, an increasing proportion of senior citizens in rural communities in the near future could create the need for sustainable public transportation. Many senior citizens become unable to drive as they get older. This makes tasks such as grocery shopping, regular pharmacy visits, doctor appointments, dentist appointments, and visiting friends and family increasingly difficult. Different forms of public transportation can provide simple solutions to these types of problems; however, rural public transportation can be quite expensive (Majkut, 2011).

Kings Transit Authority in Nova Scotia uses buses to transport rural citizens back and forth in five different rural communities: Wolfville, Kentville, Berwick, Kings County, and Brooklyn. These communities are challenged by the number of elderly people in need of transportation yet unable to drive. Public transportation to these communities makes personal travel much easier and increases the viability of small business in these communities. Challenges to the public transportation system include: a lack of sidewalks in rural Nova Scotia, large amounts of snow in the winter, higher fares than urban transportation, higher speed limits on rural roads, and inconvenience for residents using wheelchairs where long walks to bus stops are necessary. Another drawback to implementing this type of system is the community attitude towards change. Rural residents are not likely to change transportation modes immediately, so typically a three‐year investment is needed to effectively implement the program (Majkut, 2011).

Policies and Government relations are yet another challenge faced by rural transportation initiatives. The process itself is very complex and includes a number of steps. The Municipal Government must first request funding for a rural transportation project. The amount of “red tape” will increase with the size of the municipality, so it is often more difficult for larger municipalities with more formal government structures to proceed, since more stakeholders and bureaucracy are required (Transport Canada, 2009). Next, approval is requested from the regional government, which is once again an extensive process. The US supports rural transportation at a federal level, while in Canada it is mostly a provincial mandate (Kostiuk, 2009). The Canadian Urban Transit Association (CUTA) is actively pursuing federal funding for

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public transportation initiatives, and Infrastructure Canada’s Public Transportation Fund has supported several rural communities in British Columbia and Nova Scotia. In cases where rural communities have one major employer, municipalities can partner with employers to create special transportation programs. Rabbit Transit in York, Pennsylvania uses this approach with the regional hospital (Transport Canada, 2009).

Financial barriers exist for rural transportation models, since it can be difficult to justify a transportation system that carries a small number of passengers over a large distance (Region of Durham Planning and Works Departments, 2004). The Durham Transportation Master Plan 2003 showed that rural communities in the Region of Durham were better off using demand‐responsive transit services. These include public paratransit, van pools, school buses, and taxis. This is not surprising due to Canada’s low population density, especially in rural areas, and the high operational costs of a full‐service bus line (Majkut, 2011).

Economic Impacts

There are many economic impacts of public transit in rural areas. These impacts can be narrowed down to five major areas, including employment and business activity, increased mobility, cost impacts for users of the system, expenditure patterns, and growth impacts on local economies. Tools can be used to measure these impacts after a system has been implemented.

Employment and Business Activity Most Canadians rely on employment as their primary source of income. Inability to travel to work in rural areas can create obstacles for rural community employees. Public transit systems can lead to increased employment and local business activity (Litman, 2011). Business activity can easily be monitored through revenues from non‐local customers, and increases in employment can be measured in terms of salary or employment per capita.

Increased Mobility Ability to access education and training programs can drastically increase citizens’ long‐term employment prospects (Transportation Research Board, 1998). Increased mobility can also help rural residents continue living independently, with access to essential services such as healthcare, post offices, and grocery stores. Mobility can be monitored by the number and frequency of riders in the rural community.

Transportation Cost Impacts for Users of the System Rural transportation is typically much less expensive per traveller, when compared with other modes of transportation such as taxi service or friends with vehicles (Transportation Research Board, 1998). Cost savings of public transportation can be measured and compared to the baseline, and proven reductions in costs can lead to healthier budgets and improved services.

Impacts on Expenditure Patterns Travelling to larger urban centres or rural communities via public transit can decrease the cost of travel. However, the net economic cost (for the local economy) may remain the same if the

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local resident purchases lower priced products from a non‐local merchant (Transportation Research Board, 1998).

Growth Impacts on Local Economy Property in rural areas is generally less expensive, so operating costs like parking are generally lower than in urban areas. Traffic congestion and accidents are also less likely. Public transit can offer tourists and visitors an affordable way to visit rural communities and, as mentioned, support small and medium‐sized businesses. Rural property value also has the potential to increase with sustainable rural public transit systems in place (Litman, 2011).

These five economic impact areas may be included in an Economic Impact Analysis (EIA) when introducing a new rural public transit system. An EIA may be developed to examine the effects of a potential or existing transit system on a rural community (See Appendix B for detailed steps). This may be useful for general community knowledge, advocacy for funding, or testing the feasibility of a project (Majkut, 2011).

Ontario’s Vision

Canada’s population is expected to rise from 33 million to over 40 million by the year 2040 (CUTA). This has sparked major national interest in public transportation initiatives. Specifically, the Vision 2040 initiative by CUTA aims to maximize the contribution of public transportation to quality of life, develop and support an efficient economy, and maintain a healthy natural environment. This will be accomplished by increasing service options, centralizing transit within communities, developing a national transit policy, ensuring financial funding is available, and maintaining a focus on customers (Majkut, 2011).

Currently in the US, all transportation systems are subsidized, including bus, train, air, and road. This is not the case for Canada, because not all are considered vital community services (Kostiuk, 2009). The goal for Eastern Ontario and Western Quebec has been identified as connecting local public transportation to other local transportation centres. This can be done through regional and intercity bus or rail, with a network of rural and urban transit operators (Majkut, 2011).

Types of Rural Public Transportation

Public transit using buses is present in 46 of Canada’s 49 urban centres with populations of more than 30,000 (Transport Canada, 2009). Rural communities can also use this transportation model; however, operating costs are generally too high for sparsely populated communities. One successful case is Ottawa’s rural routes initiative, which offers service to 13 small communities during peak hours. The additional routes were contracted through Ottawa’s OC Transpo to serve a combined rural population of approximately 84,500. Rural passes cost 64% more than regular adult passes (Transport Canada, 2009). Another successful example is Deseronto Transit, which uses small buses to connect rural communities with small urban centres including Belleville and Napanee (see Appendix A) (Majkut, 2011).

Charter programs are effective for rural communities with smaller populations. Chartering buses and vans for daily routes can provide residents an alternate mode of transportation at a reduced cost. This type of service can also be contracted with large employers in rural areas. Ride sharing and car sharing

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are two other popular alternatives. Ride sharing consists of carpooling with compatible matches found through websites such as Carpool.ca and eRideshare.com. Car sharing involves joining a co‐op where many users have the opportunity to pay for shared vehicle use (Majkut, 2011).

Other approaches to public transportation include:

Active transportation: This method of transportation promotes a healthy lifestyle by promoting cycling, walking and inline skating, and is useful for small communities.

Vanpooling, Ride‐On programs, and guaranteed ride services: Transportation Management Associations in the US provide such services through partial Federal Government funding (Transport Canada, 2009).

Telework programs: Some companies establish remote offices to accommodate rural citizens, reducing the need for public transportation by allowing residents to work from home.

Transit‐Oriented Development (TOD): Community planning organizes new housing and essential services around a public transportation hub, in order to increase ridership and commutability (Majkut, 2011).

Evaluation Processes and Decision Making Tools

Transportation evaluation models are available to generate analyses for potential projects. They typically include government costs, vehicle operating costs, average travel speed, crash risk per kilometre, project construction, and environmental impacts (Litman, 2011). Those unfamiliar with these types of models may overlook many areas, including, but not limited to, parking, vehicle depreciation, project delays due to construction, land use impacts, and public health (Majkut, 2011).

Developing an economic evaluation is a best practice for evaluating a potential project. This includes quantifying the project and comparing different options for various sections of the project. Some of the major foci of the economic evaluation include defining the type of evaluation, evaluation criteria, modeling techniques, base case, and uncertainty (Litman, 2011). The second important evaluation is that of transit service quality. This separate evaluation defines themes such as availability, price structure, security, frequency, and reliability (Litman, 2011). Finally, all stakeholders should be involved with developing plans and making decisions (Kidder, 2006). The range of stakeholders in rural communities is usually broad, since there is no transportation authority in place (Transport Canada, 2009). Other than the local municipal government, stakeholders may include schools, hospitals, transportation companies, employers, and churches, among others (Majkut, 2011).

Literature Review

Transportation / Land Use Models (TLUMs) have been developed to understand the behaviour of urban areas, transportation patterns, environmental impacts, and regional planning (Rodrigue et al, 2009). The Gravity Model and the first ever TLUM, the Lowry Model (Lowry, 1964), will be briefly discussed in this section. Transportation models specific to rural transportation such as the Transportation Land Use Model for Rural Areas (Kau, 1977) and more recently the Rural Public Transportation Accessibility Model (Sanchez, 2002) will also be discussed. The RPTA Model makes use of Geographic Information Systems, while the Lowry Model does not. The Integrated Rural Accessibility Planning (IRAP) model (International Labour Organisation) will show some further scaling and weighting techniques for rural accessibility

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models. Finally, Multi‐Objective Utility Analysis (de Neufville, 1990) and some Vehicle Routing and Scheduling problems (Ballou and Agarwal, 1988) will show methods which can be applied to the development of new rural transit systems.

Brief Overview of GIS

GIS systems are an integration of hardware, software, and data in order to analyze and display information that is geographically referenced. These systems are useful for quickly viewing employment areas, school locations, healthcare facilities, population densities, and areas with low‐income families. These inputs can help determine optimal paths for new transportation networks. The amount of available information and the type of GIS software that a rural community is using will determine the amount of effort needed when gathering data from the GIS.

Land Use Models

Land Use Models can be used to determine spatial interactions between different points in any land‐based region. This may be based on roads, land conditions, populations, and other attributes. Strong spatial interactions between points may suggest the need for transit routes between those points.

Spatial Interaction / Gravity Model

The Gravity Model is the most well‐known form of the spatial interaction method. In this case, spatial interaction refers to the amount of people that travel from place to place based on supply and demand. The Gravity Model follows the same premise as Newton’s Second Law of Gravitation. The Gravity Model states that the “attraction between two objects is proportional to their mass and inversely proportional to their respective distance” (Rodrigue et al, 2009). The basic form of the equation is shown below:

Where Pi and Pj measure the importance of the location of origin i and destination j (i.e., population), dij is the distance between the origin and destination, and k is a proportionality constant. The proportionality constant is higher for longer periods of time considered, and lower for smaller periods of time (e.g., one year versus one week). Tij is the spatial interaction between locations i and j. An optimal transportation network can be created by maximizing a combination of spatial interactions that connect all the required nodes. Extensions of this model, such as transport friction, may be added simply by squaring dij to account for lower efficiency as distance increases.

One of the significant drawbacks to this method is calibration of the model. Parameters must be set in such a way to realistically mimic spatial interactions of the analyzed area. Another downfall is that this is a static model, meaning that it measures the system at a set point in time. However, this may not be an issue in rural transportation planning since traffic congestion will most likely be minimal.

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Lowry Model

Based on the Gravity Model, the Lowry Model includes employment, population, and transportation all in one model. It focuses on three sectors: basic, which are businesses that export their products, retail, which are non‐exporting businesses, and the household sector, which is the population and location of basic and retail employees. The Lowry Model splits a geographic area into different zones and determines total employment and population for each zone through an iterative process. This information can then be used to determine locations with the highest amount of spatial interaction to generate an optimal transportation network.

Rural Transportation Models

Rural Transportation Models have been developed specifically for rural areas, whereas the Land Use Models above can be generically applied to any area. Rural Transportation Models account for attributes, such as further travel distances, that urban models would not consider.

A Transportation Land Use Model for Rural Areas

The Transportation Land Use Model for Rural Areas (TLUMRA) analyzes the interaction of land use and transportation in rural areas. Specifically, it measures the impact of transportation costs on population density, employment density, household density, mean income, and percentage of single families. Transportation costs are measured by accessibility as shown below:

Where j is the community for which accessibility is being calculated, i = 1…n represents all other communities being analyzed, Pi is the population for community i, Tij is the travel time between community i and j, and n is the total number of communities in the study. This model assigns accessibility (ACC) as an independent (exogenous) variable, along with other independent variables specifically related to the population of community j. These include but are not limited to population growth, retail sales, total sales, and the ratio of owners to renters. This regression model uses two stage least squares (2SLS) to isolate the impact of changing transportation costs (ACC) on the dependent (endogenous) variables mentioned above: population density, employment density, household density, mean income, and percentage of single families. For example, regressing ACC and the other independent variables against the dependent variable population density will result in a sensitivity measure for ACC. The result may conclude that a 1% increase in ACC is related to a 2% increase in population for community j. The model can then be used to forecast population density, and other dependent variables, as a result of increasing or decreasing accessibility.

This model could provide a good method for finding a starting point for a rural community’s transportation system. It has the ability to rank communities based on positive effects from increased accessibility, which could help plan a phased approach to implementing rural transit in various communities within the region of study. However, this model requires significant amounts of data and

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may be difficult to gather for many small communities. The calculations and analysis can also be tedious and time consuming, so the cost‐benefit for such a task may be inefficient.

Rural Transportation Accessibility Model

The RPTA Model uses a gravity‐type accessibility method to calculate scores for different segments of a geographic location. Scores for different segments can be aligned with different transportation networks and compared to find an optimal network with the highest score. There are five major steps for this method. The first step is to define the area to be served by the transportation system. Step two is to determine and map all origins and destinations for the targeted population. The third step is to overlay a grid system onto the mapped area. This can be done using a GIS. Step four is to generate accessibility scores using the following formula (Sanchez, 2002, p. 58):

The model can be further expanded to include other variables in the numerator such as low income families, healthcare providers, and grocery stores. In addition, each of these variables is weighted in terms of relative importance to citizens’ accessibility. The denominator’s exponent can also be changed to reflect the friction of increased distance. The final step in the model is to evaluate different transportation networks and choose the model with the highest score. This method can be used to increase existing transportation systems or to create new transportation networks.

One of the issues with this model is scaling. There is no defined method to scale different variables in the above equation. For example, adding the number of schools to the number of jobs does not make sense, since they are not quantified with the same unit of measure. A standardized method for scaling should be used for this model to transform variables into comparable quantities. The following two sections discuss the IRAP model and Multi‐Objective Utility Analysis, which offer some insight to the scaling issue.

IRAP Model

The IRAP model was initially developed by the International Labour Organisation (ILO) in African and Asian countries in the 1980s (International Forum for Rural Transport and Development, 2009). “IRAP has been suggested as a tool for rural road network planning in the development plan of 2025 by Government of India.” (Sarkar, 2008, p. 12) The objective of the model was to allow underfunded rural areas to develop the most efficient transportation networks possible. While the model has many variations in different countries, it is comprised of three major steps:

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1. Data Collection – Collecting information related to household proximity to essential services and population densities, and determining the feasible network area and perimeter.

2. Data Analysis and Prioritization – The first part of this step is to generate Accessibility Indicators (AIs) for each rural town in the transportation network. AIs measure the level of access for particular towns or groups in relation to essential services within the network area. The most basic form of the equation sets AI equal to the product of the number of households requiring access and the average travel time to get to the point of interest. The second part of this step is to locate areas with high AIs on a map. Transportation routes can then be visualized and prioritized.

3. Project Identification and Preparation – Decisions are made as to whether transportation routes and roads should be developed, or if new sites for essential services should be built closer to communities.

The IRAP model offers a scaling method, where the RPTA model does not, however, its scaling method is subjective in nature. This could lead to less meaningful scores for AIs, since they will be based on qualitative opinions of community developers. The following section describes a method that avoids the issue of subjectivity.

Conjoint Analysis

Conjoint analysis (Lilien and Rangaswamy, 2004) is a statistical technique commonly used for market research. The main objective is to determine the importance, or utility, of different options for several factors considered in a decision. For example, three factors considered for rural accessibility could include the number of hospitals, schools, and grocery stores in a given area. For each of these three factors, there are a finite number of options. The number of hospitals in a given area may be zero or one (two options), while the number of grocery stores may range from zero to five (six options). Conjoint analysis consists of generating different combinations of factors and options and having a respondent assign a unique score to each combination. Mathematical techniques are then used to estimate specific utility values (part‐worths) for each option, based on overall respondent preference.

The total number of part‐worths to be estimated is equal to ∑ 1 1, where N is the total number of factors and is the number of options for factor i. For each factor, the lowest option can be set to zero. The maximum score for each combination can be restricted to 100.

If there are a large number of combinations to be ranked by the respondent, dummy variable regression can be used to calculate part‐worths. When using regression to estimate part‐worths, the number of combinations (data samples) ranked by the respondent will depend on the number of parameters (part‐worths), desired probability level, desired statistical power level, and the anticipated effect size. This number will most likely be around 100, which means the respondent would have to rank 100 different combinations. This process can be tedious and tiresome, so another method such as linear programming may be used to solve for unknown part‐worths when a smaller number of combinations are ranked by the respondent. Lilien and Rangaswamy, 2004, suggest that the number of combinations in the evaluation should be twice as many as the number of part‐worths to be estimated, and should not exceed 25 in order to minimize respondent fatigue.

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Vehicle Routing and Scheduling

Most of the methods and models mentioned above can help evaluate existing rural public transportation systems. However, if there is no public transit system in place, best practices must be used to develop an optimal system. VRS problems consist of visiting a certain number of nodes in a transportation network, while adhering to constraints such as time, capacity, safety, and number of vehicles available. Gillett and Miller (1974) developed the original Sweep heuristic in which routes are systematically constructed using a proximity rule. Individual routes are then optimized to minimize distance travelled. Initial routes are constructed by extending a straight line from a depot location in any direction and rotating the line until it intersects a stop. Using the vehicle with the largest capacity first, vehicles are filled with capacity until a full rotation of the line is complete or until vehicle capacity is exceeded. This method is ideal for most rural communities, since it is not very complex and may be accomplished without integration of GIS and other analytical software.

The “Savings” method (Clarke and Wright, 1962) is an alternative solution to the VRS problem and generally has better results than the Sweep method. However, the “Savings” method is extremely complex and difficult to solve, especially if road distances between transportation nodes are not integrated with the rural transportation model. For example, if software such as Microsoft Excel is used in collaboration with a community’s GIS to analyze a rural transportation model, the “Savings” method will be nearly impossible to implement unless the GIS is integrated with Microsoft Excel. Other VRS alternatives such as the Insertion method (Jaw et. al, 1986) are subject to this limitation.

Methodology

This section is split into two parts – model formulation and the three stage decision‐making process. The first section explains how the model was developed and the second section provides a three‐step process that allows use of the model with any rural public transit candidate.

Model Formulation

The following model is applicable to any rural area, and may be customized to fit the specifications of different rural areas. The model’s purpose is to generate accessibility scores for equally sized grid cells in a rural area. The rural area under consideration is split into equally sized grid cells which represent reasonable walking distances to potential bus stops. Grid cells in this report are measured 400m by 400m, since this is considered a reasonable walking distance for rural residents (Lam and Morrall, 1982). Grid cells with higher scores are better candidates for the public transit system and will lead to the identification of potential rural public transit routes.

Notation

Let the Rural Accessibility Score (RAS) of grid cell i be denoted by such that:

∙ 1

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Where:

, ∈

, 1,2, … ,

, ∈

, 1,2, … ,

*Options are listed from least appealing to most appealing, where option is the most appealing option for factor n.

1 , :

1

, 100 , :

(the above constraint is not necessary if the objective function is an equality)

, ∀ ,

Figure 1:

23, 2, 2, 3, 25

1, 0, 0, 1, 0

5, 60, 5, 25, 40

∙

∙ ∙ ∙

1 ∙ 5 0 ∙ 60 0 ∙ 5 1 ∙ 25 0 ∙ 40 ∙ 25 25 ∙ 25 625

Where: 1 and 2

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In this case, there were two options for the number of hospitals ( 2) and three options for the number of schools ( 3); these options are defined by the user. For example, the discrete values for option one and two for hospitals could be 0 and 1, respectively. The discrete values for options one, two, and three for schools could be 0, 1, and 2 schools in the respective grid cell.

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Calculation of Weights

Figure 2 – Calculation of Weights

The process for calculation of weights can be seen above in Figure 2. Dummy variable regression may be used to calculate weights if there are around 100 combinations of factors and options ranked

by the respondent. The following formula can be used to find weights using regression:

Where:

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, , ,

Otherwise, an iterative approach using linear programming and Conjoint Analysis, as described above can be used with the following objective function and constraints:

100 1

Constraints:

, 1 1 ∙ 2 2

1, ∀ , 3

100 4

0, ∀ 5

, , … , , ∀ 6

, ∀ , 7

Where:

1

There are two options for the types of constraints that compare different combinations and their relative rankings. The first are equality constraints, as shown in Constraint (2) above. One drawback to this method is that when large numbers of unknown weights are considered, it is nearly impossible to satisfy all equality constraints due to algebraic restrictions. This drawback can be overcome by using an iterative process that eliminates combinations one by one based on the LP’s solution and the unsatisfied

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constraint with the highest deviation from its equality. Combinations can be removed until the

minimum number of combinations required ∑ 1 1 (since this number is the same as the number of unknown weights) has been reached, or when all equality constraints are satisfied. Another way to overcome the problem of unsatisfied equality constraints is to run a regression to provide a starting point the LP. This can help find a solution where the answer corresponds to a global maxima instead of a local maxima.

The second option for the types of constraints that can help compare different combinations are pairwise inequality constraints. As outlined by Lilien and Rangaswamy, 2004, pairwise evaluations of combinations are completed by asking the respondent to allocate 100 points between two different combinations. This method will always return an optimal solution in the LP, however, a larger sample size is required from the respondent. For example, if there are 12 combinations, the respondent must rank [(12*11)/2] = 66 pairs.

The number of combinations used as constraints in the initial LP – for both equality and pairwise inequality constraints – should be roughly double the number of unknown weights, or part‐worths, as described in the Conjoint Analysis section above.

Calculation of Population

Population for each grid cell can be gathered directly from a community’s GIS, however, it is unlikely that such specific information will be available. Estimates based on land parcel areas, number of houses, and Statistics Canada data may be used for this part of the analysis. For example, the number of houses per grid cell may be multiplied by the average number of people per household, according to the Statistics Canada Community Profile. Another method for approximating population is shown in the case study below.

Calculation of Distance

Distance calculations between potential bus stops should be calculated using a measuring tool in the community’s GIS or Google Earth. Distances must follow roadways, which makes them difficult to calculate using an automated algorithm. If analysts are able to integrate this model with their GIS and incorporate distances through roadways, it would be much less tedious. However, rural areas will typically have few enough points that manual calculation will be feasible.

Evaluation of Existing Routes

If there is currently an existing bus route in the rural community, the route may be evaluated by summing the accessibility scores for the grid cells containing bus stops and dividing by the total road distance of the route. This will be referred to as the Total Route Score per Distance (TRSD), which can be useful for comparing existing routes to new potential routes in order to choose the route with the maximum impact. Grid cells for the community under consideration are labelled from i = 1, 2,…, T, where T is the total number of grid cells in the community.

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∑,

1, 0, 1

Where:

1

Development of Potential Routes

If there are no existing routes in the rural community, VRS techniques can be used to determine potential routes. The Sweep Method can be implemented with the constraint of total bus route time, since community officials may require the bus to run an entire route in one or two hours exactly. Time can be calculated based on distance and speed limits in the area. Other methods such as the Savings or Insertion Method could be used if road distances between points were integrated with this model, however, this will most likely not be the case.

Another simple alternative to finding an optimal route is to assume there will be a maximum of one or two buses running the route, since rural transit budgets are usually restrictive. This will limit the number of grid cells under consideration with a time restriction, leaving only a select number of grid cells with the highest scores. The Traveling Salesman Problem or the “tear drop” approach can then be used to solve for the optimal route that connects all grid cells. Grid cells can be added to the new route one by one with Rural Accessibility Scores in descending order until the time constraint is reached. Keep in mind that when adding grid cells one by one, there may be a grid cell that is geographically distant from the constructed route and may not be feasible. Common sense should be used with this approach, which means a grid cell with a lower score may take precedence over one with a higher score due to geographic location. This approach may be more realistic for communities with no public transit system in place. If specialized transit, such as charter services, already existed, the community might benefit from a combination of scheduled transit and specialized transit. Further analysis would need to be done by community leaders to realized the risks and benefits of such a venture.

Three Stage Decision‐Making Process

The process flowchart below, Figure 3, shows the three step decision‐making process to determine optimal rural transportation routes.

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Figure 3 – Three Stage Decision‐Making Process

Data Gathering and Analysis

The first step of this phase is to meet with the community team responsible for implementing the rural transit system. The three step decision‐making process and model applications should be clearly described to community leaders, making it clear how the model will work for their rural community. Once an agenda has been set, the GIS Technician for the community’s GIS must be asked to develop an Excel spreadsheet that contains information on each 400x400m grid cell in the community. Relevant factors such as hospitals, schools, grocery stores, retirement residences, national parks, and pharmacies may be included in the spreadsheet. Other factors may also be considered important to community leaders, so they may be included in the spreadsheet as well. The spreadsheet should include the latitude and longitude coordinates, the number of relevant factors (e.g., hospitals, schools), and the population for every grid cell within the rural area. In order to develop the spreadsheet, the GIS Technician must be able to overlay the locations of all relevant factors onto the community’s GIS. This can be accomplished by the Technician if these layers are available in the GIS, otherwise Google Earth can be used to pinpoint locations which are labelled and saved as a KML file. The Technician can then overlay the KML file to the community’s GIS and create the desired spreadsheet.


•Meet with Community Team to Define Objective of Transit System

•Give KML Files with Point of Interest Locations to GIS Technician

•Receive Excel Spreadsheet with Grid Cell Information

•Give Survey to Rank Weights of Different Factors

•Receive Survey with Rankings

Model Development

•Determine Weights Based on Rankings

•Calculate Accessibility Scores using Grid Cell Spreadsheeet

•Plot Locations of Grid Cells with Highest Scores to Community Map

Route Generation and Testing

•Evaluate Scores for Existing Routes

•Develop New Routes using VRS or Other Methods

•Compare Different Routes to Find Optimal Route

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The next step in this phase is to determine the weights for all relevant factors, which is done through Multi‐Objective Utility Analysis. Depending on the number of relevant factors and possible options for each of these factors, a utility survey must be submitted to community officials to determine the importance of each factor. The community team should be responsible for ranking different random combinations of factors and options, and a detailed ranking scale should be provided to ensure consistency among rankers. An example of a ranking scale is shown in Figure 10 in the case study. The process flowchart for this phase is shown in Figure 4.

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Figure 4 – Data Gathering and Analysis

Meet with team (define area, factors, options, team leaders

Acceptable? (format, info)

Define requirements (area, grid size, spreadsheet)

Create survey (factors, options, random combinations)

Define inputs and outputs (GIS Technician)

Create layers using KML or SHAPE files (factor locations)

GIS Server(s)

Send files to GIS Technician

Receive spreadsheet (GIS Technician)

Model Development

Data Gathering

Yes

No

Send survey to team leader(s) with instructions

Receive utility survey (team leader(s))

Complete? (correct info)

No

Yes

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Model Development

Weights for different factors can be calculated using the linear program described in the Calculation of Weights section above. The results from the utility survey are used to solve for the associated number of unknown weights. The weights may be calculated using software such as AMPL, Excel Solver, or by using the GIS directly. Once the weights are determined, accessibility scores can be calculated. An example of a linear program in Excel is shown in the case study below.

The Excel spreadsheet provided by the GIS Technician will contain all the necessary information to determine accessibility scores for each grid cell. Equation (1) in the Model Formulation section must be implemented using software such as Visual Basic for Applications (VBA) in Excel, AMPL, or GIS software. Accessibility scores are then calculated for each grid cell, at which point the scores can be ranked from highest to lowest. Since the coordinates for each grid cell are provided in the spreadsheet, the top 25 to 50 grid cells can be plotted on the GIS, which is the final step. The process flowchart for this phase is shown in Figure 4.


If rural transit routes already exist, they can be evaluated with their relative accessibility scores and distance between points. In order to evaluate a route, simply sum the accessibility scores for grid cells where bus stops are present. Next, divide by the total distance for the bus route, which can be found using a measuring tool in the GIS. This will give the Total Route Score as outlined in the Evaluation of Existing Routes section above. New routes can be created and compared with existing routes by comparing the TRSD for each route. New routes may be generated using VRS methods as described in the Development of New Routes section above.

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Figure 5 – Model Development

Define variables for calculation of weights (N, Mn, r, etc…)

Utility Survey (utility scores)


Model Development

Yes

Calculation of weights process

Fi 3 1 2

Weights (spreadsheet or output file)

Define variables for RAS and prepare data sheet / input table (all grid cells)

Create program to calculate RASi and rank in descending order

Input Formatting Required?

Accessibility scores in descending order

No

Plot top 10‐50 points in GIS

KML or SHAPE file with plotted scores

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Results for potential transportation routes should be analyzed and evaluated by the research team, as well as the community team. Changes to relevant factors, ranking methods, and population calculations may be changed to provide a more accurate result. The flowchart for this process is shown in Figure 6.

Figure 6 – Route Generation and Testing


This case study was performed to test and validate the methodology outlined above. The case study for Prince Edward County focused on developing a potential rural transit route for regularly scheduled transit, which could complement its already existing charter‐type transit.

Prince Edward County

Prince Edward County is part of Southern Ontario and is located in between Kingston and Toronto, Ontario. PEC is not officially a county by Ontario standards; it is a municipality with a single government

Calculate value of existing routes (TRSD)

Total Route Score(s)

Plan for Implementation


Compare potential/existing routes and choose one with highest score

Existing Standard Routes?

Use iterative or VRS methods to calculate potential routes and TRSD


Yes No


Maps and details for potential routes

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which handles all municipal services. Communities within the municipality include: Ameliasburg, Bloomfield, Carrying Place, Cherry Valley, Consecon, Demorestville, Fawcettville, Glenora, Hillier, Milford, North Port, Picton, Rednersville, Rosehall, Rossmore, Waupoos, Wellington, and West Lake. According to the Statistics Canada 2006 Census, the combined population of the municipality is approximately 25,000, with a population density of 24.3/km2, and an area of about 1,000 km2. The main attraction for PEC is Sandbanks Provincial Park in Picton, which attracts thousands of tourists during the summer. As can be seen from the map in Figure 7, PEC is an island community. Lake Ontario provides PEC with a mild climate that supports its many wineries and vineyards.

Figure 7 – Prince Edward County Geography

PEC is interested in implementing a rural public transportation system to provide a sustainable and affordable transit option for its citizens. Providing public transportation is vital for senior citizens to have access to essential services, offer low income families cost‐effective local travel, and deliver transportation to employment and business centres to foster local economic growth.

Existing Public Transportation

Quinte Access provides public transportation in the cities of Quinte West, Brighton, and PEC. The service is intended for people who are mentally or physically challenged, unable to walk reasonable distances, or seniors who need transportation assistance. The service has four buses and five vans, all of which are wheelchair accessible. Routes and schedules change daily, based on rider demand, since vehicles pick up passengers at their homes. Subscription fees are paid for riders who need regular access to employment, education, or healthcare. Non‐subscription service requires a rider to call at least 24 hours in advance to book a trip at a determined rate.

PEC Specialized Transit is also used for PEC`s physically disabled and elderly population. This door‐to‐door transit service requires riders to register through an application process and schedule trips one day in advance. Priority is given to riders with physical disabilities, and medical trips take precedence over social trips. The service currently operates four days per week from Tuesday to Friday.

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Developing a Rural Public Transit Route

This section outlines and discusses the application of the three phase methodology discussed in the Methodology section above and shows how any rural community can develop a rural transportation route.


The first step of the process was to arrange a meeting with members of PEC on May 26, 2011 in Picton, Ontario to discuss the scope of the study. Attending members included PEC`s Public Works Commissioner Robert McAuley, Planning Services Manager Jo‐Anne Eagen, and other members of the Planning Services Department including GIS Technicians. The main objectives of the meeting were to discuss the rural transportation model, ensure data would be available for analysis, and to learn about PEC`s existing transportation network. Six factors were selected to determine PEC’s accessibility per grid cell: hospitals, schools, pharmacies, grocery stores, national parks, and retirement residences. Each of these factors had two options – either 0 or 1 factor located in each grid cell – except for schools, which had the option of 0, 1, or 2 schools per grid cell.

After determining the inputs and outputs required from PEC and the area to be served, the GIS Technicians were asked to prepare a spreadsheet that shows information for each 400x400m grid cell in PEC. Information for each grid cell included the number of factors per grid cell, in terms of the option chosen (e.g. 0 or 1 hospitals). Population for each grid cell was also calculated, and is described in detail in the following paragraph. Two separate KML files were sent to the GIS Technician (created in Google Earth). One file included locations for five of the six factors, and the other included polygon overlays for the sixth factor – national parks. A screenshot of the former is shown in Figure 8.

Population for each grid cell was calculated by using Municipal Property Assessment Corporation (MPAC) property codes that show land use for each individual parcel of land. This was combined with the average population per dwelling of 2.4 from Statistics Canada Community Profiles. For example, if the MPAC code said that two households were within a grid cell, then the estimated population for that grid cell would be 4.8. Centroids were created for each parcel in order to prevent parcels from overlapping into more than one grid cell. A screenshot of the finalized spreadsheet provided by the GIS Technician can be seen in Figure 9.

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Figure 8 – Locations for Relevant Factors of Accessibility

Figure 9 – GIS Data Table

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Next, the utility survey for ranking different combinations ( ) of factors was customized to include PEC’s six factors. Linear programming (LP) was used as opposed to multiple regression in order to reduce respondent fatigue when ranking different combinations. Thirteen random combinations of factors and options were generated, since the recommended number of combinations corresponds to ∑ 1 1 ∙ 2 as described in the Conjoint Analysis and Calculation of Weights sections

above. Random combinations were created in Excel using a pseudo random number generator. The survey was then sent to the Planning Services Manager, Jo‐Anne Eagen. After viewing the spreadsheet shown in Figure 10, following the detailed instructions, and filling in the fields that are highlighted in yellow, she returned the updated spreadsheet and it was time to move to the model development phase.

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Figure 10 – Respondent Survey to Rank Combinations

Model Development

Using the utility survey and previously gathered information, variables were defined in order to calculate weights:

6, 2, 3, 2, 2, 2, 2

41, ,85 75, 70, 65, 60, 73, 45, 90, 92,

Combination Hospitals Schools Pharmacies Grocery Stores Parks Retirement Residences = Utility1 0 0 0 1 1 0 = ?2 1 2 1 0 1 1 = ?3 1 1 1 1 0 1 = ?4 0 2 0 1 0 0 = ?5 1 0 0 1 0 1 = ?6 0 1 0 0 0 0 = ?7 1 1 1 0 0 0 = ?8 0 0 1 0 1 0 = ?9 1 2 0 1 1 1 = ?

10 1 1 1 0 0 1 = ?11 0 1 1 1 1 1 = ?12 1 2 1 1 1 0 = ?13 0 2 1 1 0 1 = ?

MAX 1 2 1 1 1 1 = 100

NOTE: Combinations for the different options above were randomly selected.

Instructions1. Rank all 13 options and assign them a utility score between 0 and 100.2. The combination MAX shows that a score of 100 can only be attained from having the highest option for each factor.3. Ranking guide:

Utility0 - 20

21 - 4041 - 6061 - 8080 - 100

4. Place score in highlighted column with "?"

Example 1: Option 1 corresponds to an area of PEC that has 0 hospitals, 0 schools,0 pharmacies, 1 grocery store, 1 park, and 0 retirement residences.If you think that the combination of these items found in Option 1 are important toPEC then a score between 41 - 60 should be assigned as the utility.

Example 2: Option 2 shows that 1 hospital, 2 schools, 1 pharmacy, 1 park, and 1 retirement residence are located in a specific area of PEC. Bob thinks that hospitals are very very important to the accessibility of peoplein PEC, and he also thinks that retirement residences and pharmacies willincrease the importance of an area in PEC. Bob gives a utility score of 95for option 2.

DescriptionNegligible importance to PECNot very important to PECImportant to PECVery important to PECVery very important to PEC

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82, 95, 80

*All 13 combinations and their values can be seen in Figure 10.

Equation (1) from the Calculation of Weights section was used as the objective function for the linear program, with LP constraints (2) to (7) found in the same section above. A linear program was constructed in Excel corresponding to the objective function and related constraints and solved using Excel’s Solver tool and the iterative procedure shown in Figure 2. The spreadsheet and results can be found in Appendix C.

Next, variables for the RAS equation were located in the spreadsheet provided by the GIS Technician. Previously calculated values for weights were also copied into this spreadsheet for easy reference. VBA was used to calculate scores using Equation (1) from the Notation section and the top 50 scores were ranked in descending order using another VBA algorithm (Code can be found in Appendix D). The top 25 grid cells were plotted with their corresponding coordinates in PEC`s GIS, exported as a SHAPE file, and converted to a KML file to be opened in Google Earth. A screenshot of the Google Earth image with the top 25 points can be seen below in Figure 11.

Figure 11 – Top 25 Locations with Highest RAS

After the top 25 grid cells were plotted in Google Earth, it was time to generate and test potential routes.

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PEC did not have existing standard routes, so evaluation of existing routes was not feasible. PEC’s specialized transit service changes routes on an ongoing basis and offers custom service to individual riders. The RAS method is not an appropriate measurement of such service, since transit schedules are based on customized routes and not accessibility. On the other hand, VRS methods could still be used on a daily basis to evaluate daily transit routes and choose routes that minimize distance or time.

When designing potential routes, some assumptions were made for PEC. The first assumption is that PEC will only have enough money in their budget for one bus with a regularly scheduled route. They will also want to test the service and rank its success before implementing service with a second bus. The second assumption is that PEC will offer a bus route with a reliable schedule that is attractive to its citizens. The constraint of 90 minutes was used, which means the bus must leave the depot, stop at every bus stop, and return to the depot within this time limit. The third assumption is that the depot – the starting and ending point – will be the grid cell with the highest accessibility score. The fourth assumption is that the travel speed for the bus is 37 km/h, which is the recorded service speed of PEC’s specialized transit in 2009. Finally, since this is a regularly scheduled route, it is assumed that the bus will stop at each node on the route for one minute.

Different scheduling methods were used in collaboration with rural accessibility scores. The first method used an iterative approach that added grid cells from highest to lowest RAS to the route, one by one, until the 90 minute constraint was exceeded. The second method added the ten grid cells with the highest RAS to the route. Other grid cells were added to the route in order of descending RAS, but only those points located in close proximity to the existing route were added. Finally, the third method uses the same approach as the second, but travels to grid cells in southern PEC within the top 25 to simulate an alternate rural route (e.g., perhaps a route with a standardized schedule could visit southern areas twice per week to serve the more rural population).

The Sweep method was used to develop the routes in all three methods. The Sweep method simply extends a straight line from the depot in any direction and rotates in either direction, adding the next scheduled stop every time a point is intersected by the line. The “tear drop” method is also used to ensure that routes do not cross over themselves. A screenshot of the three potential routes can be seen in Figure 12.

Routes one and two both go through Picton, Bloomfield, and Wellington. The depot or starting point for all three routes is denoted by the green push‐pin icon in Picton; it is the point with the highest accessibility score. The yellow and red paths show routes one and two, respectively. All of the bus stops in route one are also found in route 2, since route 2 was constructed using a similar approach. A close‐up of routes one and two through the town of Picton can be seen in Figure 13. Route three is shown by the blue pathway in Figure 12 and visits more rural areas of PEC.

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Figure 12 – Three Potential Transit Routes

Figure 13 – Routes 1 and 2 through the Town of Picton

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Data for the three routes is shown in Table 1 below. As can be seen in Table 1, the three routes share a similar total distance, and all fall within the 90 minute route constraint (an example of duration calculation can be found in Appendix E). Route one has 10 bus stops, route two has 12 bus stops, and route three has eight stops. The Total Route Scores per Distance (TRSD) were calculated for each route using Equation (1) found in the Evaluation of Existing Routes section above, which divides total the total score by total distance of the route. Route two has a slightly higher accessibility score than route one, which can be expected since route two has more bus stops but equal distance. Route three has a considerably lower score than the other two routes, since fewer bus stops are visited. When comparing these three options, it is easy to see that PEC should choose route 2, since it has the highest TRSD, has more stops than the other routes, and falls within the time constraints.

Table 1– Route Summary

Sensitivity analysis for different routes may also be studied. For example, stopping twice at select bus stops on a route might increase interest for new riders. On route 2, stopping twice per route at points 9, 10, and 13 would prevent potential riders from having to ride the bus in the opposite direction of their destination. While this option could increase ridership, it also adds an additional minute for each extra stop, making the total duration of the trip 85 minutes. PEC would have to determine which element is more important. A possible solution to overcome tight time constraints is increasing average speed per trip. If buses run faster, then more stops can be visited. This could also apply to route three, since the majority of driving is done on rural highways. The average speed per route is 37 km/h, however, route three’s actual average speed may be closer to 60 km/h because buses will travel on rural highways. Increasing the average speed of travel when a route has a lower TRSD may be a reasonable trade‐off, since more riders may be captured per hour. Finally, if slack is available with regards to time

RAS Rank Score RAS Rank Score RAS Rank Score1 1 19645.8 1 19645.8 1 19645.82 4 9741.6 4 9741.6 11 12603 9 2868 9 2868 22 223.24 7 5964.4 15 530.4 12 892.85 8 3978 7 5964.4 21 226.86 6 8035.2 8 3978 18 421.27 2 12240 6 8035.2 17 453.68 10 1264.8 2 12240 25 64.89 3 10530 10 1264.810 5 8893.5 13 680.411 3 1053012 5 8893.5

Total Score: 83161 84372 23188

Total Distance: 42.5 km 43 km 50 kmDuration: 79 mins 82 mins 89 minsTRSD: 1848 1875 483

Bus Stop

Route 1 Route 2 Route 3

Route 1 Route 2 Route 3

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constraints, additional potential stops can be added to the PEC map in order of descending RAS. For example, the 28th highest RAS may fall directly on the path of the proposed bus route, so accommodating the extra stop would be feasible.

Conclusion and Recommendations for Future Work

The purpose of this paper was to develop a GIS‐based framework for developing optimal transportation routes in rural areas. The three‐step decision‐making process described in this paper outlines steps for data gathering and analysis, model development, and route generation and testing. As part of the process, a unique model was developed to determine the importance of specific factors to a community’s accessibility, scores for different grid cells within a rural community, and total scores for existing and potential routes within a community. This three‐step process can be used by any rural community with a GIS in order to create optimal public transit routes.

The models are relatively simple to use and can be designed to work with Microsoft Excel, with the help of VBA. If desired, a community can develop tools in Excel or other software that can easily be re‐used to evaluate existing routes and potential routes for the future. A user‐friendly Excel template for any rural community could also be developed with customizable settings for the number of factors and options, destination cells to retrieve the information from the spreadsheet, and VBA programs to calculate and rank accessibility scores.

While this framework offers some great advantages to rural communities, there are some limitations as well. The model in this paper is GIS‐based, so if a community does not have a GIS, or is unable to speak with Technicians who support the system, this model will be more difficult to use. Rural transit authorities and rural communities are also faced with resource constraints, which could make it difficult to find time for a full analysis. Finally, demand for rural public transit systems is difficult to predict and community leaders must make a serious time commitment to build ridership.

There are numerous opportunities for future work in this area. As discussed above, a user‐friendly template in Excel could be developed for general use by any rural community. This would allow community leaders to develop routes with a basic understanding of rural transportation networks and VRS methods. Another opportunity for future work lies with the GIS software. Instead of simply generating an Excel spreadsheet for manual calculation, GIS Technicians could program the models and equations directly into their GIS software to calculate scores, rank options, and plot points directly in their GIS. An extension of this application would be integrating roadways with grid cells in the rural area so that more advanced VRS methods such as the “Savings” method, Insertion method, and other advanced optimization techniques could be used to find optimal routes. This would need to be customized based on the GIS software used by each community, but a general program template could be developed for all rural communities.

The framework outlined in this paper should be very useful for rural communities. The step‐by‐step process will help transit authorities implement the models described in this paper and design optimal transit routes. This can serve as a starting point for rural transit planning, cost‐benefit analysis of rural transit systems, and may help secure operating and capital grants from various levels of government.

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This study will help increase stakeholder awareness on the importance of sustaining and growing rural public transit systems to meet the needs of an aging and growing population.

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References

Ballou, R.H. and Agarwal, Y.K. “A Performance Comparison of several Popular Algorithms for Vehicle Routing and Scheduling,” Journal of Business Logistics, 9(1), 51‐65. (1988).

Canadian Urban Transit Association. “Transit Vision 2040.” <www.cutaactu.ca/en/publications andresearch/resources/CUTABook_Compressed_complete.pdf>

Clarke, G. and Wright, J.W. “Scheduling of Vehicles from a Central Depot to a Number of Delivery Points,” Operations Research, 12(4), 568‐581. (1964).

de Neufville, R., Applied Systems Analysis: Engineering Planning and Technology Management, New York: McGraw‐Hill, 1990.

Gillet, B.E. and Miller L.R. “A Heuristic Algorithm for the Vehicle‐Dispatch Problem,” Operations Research, 22(2), 340‐349. (1972).

GIS.com. “What is GIS?” <www.gis.com/content/what‐gis>

International Forum for Rural Transport and Development. “IRAP.” <www.ifrtd.org/en/issue.php?id=033>

Jaw, J., Odoni, A. R., Psaraftis, H. N., & Wilson, N. H. M. “A heuristic algorithm for the multi‐vehicle advance‐request dial‐a‐ride problem with time windows.” Transportation Research, 20, 243–257. (1986).

Kau, James B. “A Transportation Land Use Model for Rural Areas.” The Annals of Regional Science, 11(2), 41‐54. (1977).

Kidder, Ben. “The Challenges of Rural Transportation.” <wrdc.usu.edu/files/publications/ publication/pub__9373753.pdf>

Kostiuk, Michael. “Rural Transit Symposium for Eastern Ontario and Western Quebec.” <web.ncf.ca/fd978/transgeo/Rural%20Transit%20Symposium%20Nov%2019%202009.pdf>

Land Use Modeling Workshop. “The State of the Practice in Land use Models.” <www.oregon.gov/ODOT/TD/TP/docs/TMR/General/luwkshpproc.pdf?ga=t>

Lam, W. and J. Morrall. “Bus Passenger Walking Distances and Waiting Times: A Summer‐Winter Comparison.” Transportation Quarterly, 36(3), 407‐421. (1982).

Lilien, Gary L., and Arvind Rangaswamy. “Marketing Engineering: Computer‐assisted Marketing Analysis and Planning.” Trafford. (2004).

Litman, Todd. “Evaluating Public Transit Benefits and Costs.” Victoria Transport Policy Institute. (January 2011).

Lowry, Ira S. “A Model of Metropolis.” RAND Memorandum, RM‐4035. (1964).

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Majkut, Kevin. “Rural Transportation Issues and Strategies.” Knowledge Synthesis for Monieson Centre, Queen’s School of Business. (March 2011).

Quinte Access. <www.quinteaccess.org>

Region of Durham Planning and Works Departments. “Transportation Master Plan.” Regional Municipality of Durham. (2004).

Rodrigue et al. “The Geography of Transport Systems.” Routeledge. (2009).

Sanchez, Thomas. “Rural Public Transportation: Using Geographic Information Systems to Guide Service Planning.” Center for Urban Studies, Transportation Research Group. (June 2002).

Sarkar, Ashoke. “Rural Accessibility Planning: A Review.” Birla Institute of Technology and Science, Pilani. (January 2008).

Statistics Canada 2006 Census. <www12.statcan.ca/census‐recensement/2006/rt‐td/index‐eng.cfm>

Transportation Research Board, National Research Council. “Assessment of the Economic Impacts of Rural Public Transportation.” TCRP Report, 34. (1998).

Transport Canada. “Sustainable Transportation in Small and Rural Communities.” Case Studies in Sustainable Transportation, 61. (2009).

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Appendix A – Rural Communities with Public Transit Systems9

Deseronto Transit – Deseronto, Ontario

http://deseronto.ca/departments/deseronto‐transit

Deseronto’s transit system provides service to Deseronto, Belleville, Napanee, and Prince Edward County. The service operates from Monday to Saturday and uses small buses to serve rural communities.

Green Rider – Hantsport, Nova Scotia

http://www.greenrider.ca

This vanpool service has been running since 1981 and offers rural residents along a commonly travelled route the opportunity to schedule rides to work and school. The service also transports people to Halifax and Dartmouth.

Kings Transit – Berwick, Kentville, Wolfville, and County of Kings, Nova Scotia

http://www.kingstransit.ns.ca

This rural public bus system was established in 1981 and serves the above listed county and towns, who jointly fund the service. In September 2007, the service was expanded to serve Hants County and parts of Annapolis County.

Kootenay Rideshare – Nelson, British Columbia

http://www.kootenayrideshare.com/index.html

This free service helps connect rural residents to share cars and save costs. The website includes emissions calculators and the ability to form ridesharing groups.

Ottawa’s Rural Routes, OC Transpo – Ottawa, Ontario

http://www.octranspo1.com/community‐events/rural_communities

9 Adapted from Majkut (2011).

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OC Transpo introduced service to rural communities in 2002, and now serves 13 communities in the greater Ottawa area. The buses operate during peak hours to serve these small communities.

Specialized Transit – Prince Edward County, Ontario

http://www.pecounty.on.ca/government/rec_parks_culture/properties/transit.php

In 2007, this specialized transit system for elderly and disables citizens was developed. Riders must be eligible and register through an application process. Trips are scheduled at least one day in advance and serve social and health needs.

Trius Transit – Charlottetown, Prince Edward Island

http://www.triustransit.ca

This public bus system started in 2005 and serves Charlottetown, Cornwall, Stratford, and some county lines. Ridership for the transit system is continuing to grow and revenues from transit fares are offsetting the costs for the system.

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Appendix B – How to Develop an Economic Impact Assessment (EIA)10

The following methodology is adapted from the Rural Economic Development Data & Intelligence (REDDI) program, developed by the Ministry of Agriculture, Food, and Rural Affairs. This Government of Ontario guide for creating an EIA uses seven essential steps. The full guide may be found at the following website: http://www.reddi.gov.on.ca/guide_ecimpactassessment.htm.

Step 1: Define the scope.

The objective of an EIA is to compare changes to the status quo to determine economic effects. Defining the scope involves identifying the work that needs to be performed, outlining the purpose of the EIA, and stating feasibility constraints.

Step 2: Define decisions and questions to be answered.

It is important to identify decisions that municipal council or staff will make based on the EIA. Outlining important questions to be answered will focus the analysis on areas of interest and help make better decisions.

Step 3: Determine level of detail.

The level of detail for the EIA will depend on time, budget, and staffing constraints, the size of the local community, information available, and expertise of the project team.

Step 4: List assumptions and limitations.

Assumptions may include topics such as population growth, employment levels, and income levels. Limitations might include time constraints, lack of expertise, and unavailability of information.

Step 5: List economic impacts.

Five economic impact areas were listed in the knowledge synthesis for rural transit systems: employment and business activity, increased mobility, transportation cost impacts for users of the system, impacts on expenditure patterns, and growth impacts on the local economy. This list may be expanded to include other impacts such as existing user impacts, benefits from reduced traffic, and changes in land use patterns (Litman, 2011).

Step 6: Define required and available data.

Key data requirements include, but are not limited to: infrastructure and construction costs, projected number of employees, employee’s annual wages, estimated number of employees living in the local community, and estimated cost of inputs from local suppliers.

10 Adapted from Majkut (2011).

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Step 7: Analyze direct impacts for each impact area and compute indirect and induced effects.

Direct impacts include initial project effects such as job levels and salaries, as a direct result of the rural transit system. Indirect impacts are the changes that occur to job levels, production, and salaries in other businesses in the local community, as a result of the new transit system. Induced impacts include household spending in the local economy as a result of direct and indirect impacts. For example, a bus driver may purchase a new television from a local vendor using the salary provided by the transit system.

Direct impacts are responsible for indirect and induced impacts. This is referred to as the multiplier effect. Multipliers for each impact area can be used to calculate indirect and induced impacts. For example, an economic multiplier of 2.2 for salaries would mean that for each dollar spent on salaries in the rural transit system, a total of $2.20 is generated. Subtracting the initial $1 spent by the rural transit authority means that the indirect and induced impacts, for the local economy, are $1.20 for every dollar spent. These multipliers may be developed through econometric models, input‐output models, or simply by contacting an economic impact consultant in the region.

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Appendix C – Output for Weights for PEC

using Excel Solver

Ho

spita

lsS

cho

ols

Pha

rmac

ies

Gro

cery

Sto

res

Par

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20

10

10

10

1A

11w

11A

12w

12A

21w

21A

22w

22A

23w

23A

31w

31A

32w

32A

41w

41A

42w

42A

51w

51A

52w

52A

61w

61A

62w

62=

Util

ity0

01

6.5

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11

43

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11

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28

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11

40

01

0=

10

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Pha

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ies

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Sum

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11A

12w

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21w

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22w

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31w

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41A

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10

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07

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85

13

60

01

70

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04

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10

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81

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=7

50

10

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70

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71

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31

04

31

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10

00

12

81

00

14

00

10

34

=6

53

11

10

07

00

13

10

43

10

01

01

00

28

10

01

41

00

03

1=

60

29

30

01

70

01

31

04

30

01

10

10

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81

00

14

10

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=7

32

64

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11

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28

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31

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=9

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45

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10

82

=8

20

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11

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=9

5-5

71

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Appendix D – VBA Code for RAS and Ranking

Option Explicit Sub accessibility() Worksheets("Pop_Table").Activate Dim row As Long Dim column As Long Dim Score As Double Score = 0 For row = 2 To 4076 If Cells(row, 24) = 0 Then 'parks Score = Score + Cells(2, 41) Else Score = Score + Cells(2, 42) End If If Cells(row, 25) = 0 Then 'grocery stores Score = Score + Cells(2, 39) Else Score = Score + Cells(2, 40) End If If Cells(row, 26) = 0 Then 'hospitals Score = Score + Cells(2, 32) Else Score = Score + Cells(2, 33) End If If Cells(row, 27) = 0 Then 'pharmacies Score = Score + Cells(2, 37) Else Score = Score + Cells(2, 38) End If If Cells(row, 28) = 0 Then 'schools Score = Score + Cells(2, 34) ElseIf Cells(row, 28) = 1 Then

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Score = Score + Cells(2, 35) Else Score = Score + Cells(2, 36) End If If Cells(row, 29) = 0 Then 'retirement homes Score = Score + Cells(2, 43) Else Score = Score + Cells(2, 44) End If Cells(row, 30) = Score * Cells(row, 23) Score = 0 Next row End Sub Option Explicit Sub top50() Worksheets("Pop_Table").Activate Dim row As Long Dim row2 As Long Dim maxrow As Long Dim max As Double Dim count As Long max = ‐100 For row = 2 To 4076 Cells(row, 31) = Cells(row, 30) Next row For row2 = 6 To 55 For row = 2 To 4076 If Cells(row, 31) > max Then max = Cells(row, 31) maxrow = row End If

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Next row Cells(row2, 33) = Cells(maxrow, 30) Cells(row2, 34) = Cells(maxrow, 21) Cells(row2, 35) = Cells(maxrow, 22) Cells(maxrow, 31) = 0 max = ‐100 Next row2 End Sub

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Appendix E – Route One: Duration Calculation for PEC

42.5

3769

Route 1 has 10 stops, with a one minute duration for each stop, making the total duration of the trip:

69 10 79

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Part 6: Understanding Rural Business Enterprise: A Role for Business Incubation and Social Innovation?

Professor M. Tina Dacin

With Research Assistance from:

Wren Montgomery, PhD Candidate

Gavin McGlaughlin, BComm Student

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Executive Summary

The current literature on diffusion of business and policy practices has been limited in its understanding of the factors that underlie adaptation and variation of practices. Using a case study of the diffusion of business incubation practices across portions of rural Ontario in 2010 this paper examines why rural and urban practices diffused in two distinct phases, and how the practice of rural incubation differed from its urban counterpart. Through the analysis of 13 in‐depth interviews, site observations, and archival data, it is posited that the institutional logics of urban incubation, “innovation and entrepreneurship”, did not fit the social reality of the rural context. Instead, through drawing on local logics of the concept “place”, which has a prominent tradition in the humanistic geography literature, government and change agents were able to change the logics of incubation to one of “community regeneration” and gain legitimacy for local businesses, themselves, and the community as a whole. This paper therefore supplements nascent research on the role of the social and cultural context in understanding business incubation, the role of “place” in organization theory, and on policy and practice diffusion and adaptation more broadly.

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Introduction

The idea that organizations will attempt to imitate one another through mimetic processes is at the heart of institutional theory (DiMaggio & Powell, 1983), as is the link between such practices and the legitimacy conferring benefits to the organization of “sameness” (Dowling & Pfeffer, 1975; Meyer & Rowan, 1977). The traditions of the diffusion literature have generally followed this same path, focusing on the similarities in diffused policies and practices rather than the variations, on the sameness rather than on the multitude of differences, on homogeneity rather than heterogeneity.

The recent growth in the literature on adaptation of diffused practices has attempted to address these issues, examining the variations that occur when cultural (Weber, Davis, & Lounsbury, 2009), organizational (Ansari, Fiss, & Zajac, 2010), temporal (Westphal, Gulati, & Shortell, 1997), and external institutional and environmental factors (Lee, 2009; Zilber, 2006) are taken into account. Yet despite these important developments to the traditional assumptions of homogeneity and isomorphism, and to the idea that practices and ideas are diffused “intact”, a theoretical gap (Lee, 2009; Ansari, Fiss, & Zajac, 2010) still remains in the theoretical understanding of processes of variation, heterogeneity and adaptation as practices diffuse.

This paper examines the case of the diffusion of business incubation practices in select rural Ontario communities in 2010. From the late 1990s on, incubation spread across North America but didn’t become popular as a policy option in Ontario until the early 2000s. However, within just a few short years numerous incubators were founded in urban centres across Ontario including Toronto, London and Ottawa. Yet, it wasn’t until half a decade later, after the end of the first two phases of rural incubator “diffusion” (Bollingtoft & Ulhoi, 2005, p. 268) that the practice began to diffuse to nearby rural communities, with several incubators appearing in rural locations in the spring of 2010 alone (see Appendices B and C). This rapid yet seemingly two‐phase diffusion process poses two questions. First, why the delay in diffusion and what had changed to finally facilitate rapid rural incubator adoption several years after the first urban wave? Second, how, if at all, did rural and urban incubators differ?

Based on the case study and a series of qualitative data on business incubation in rural Ontario, this paper will posit answers to these questions and expand the current adaptation literature on two key dimensions. First, the role of community and individual connection to ‘place’, a concept with a long history in the humanistic geography literature is suggested as an important yet currently unexplored factor in understanding variation and the need for adaptation of diffused practices. Second, the role of institutional logics is explored in changing the understanding of incubation practices from an urban business‐oriented logic of “innovation” to a more rural and place‐oriented logic of “community regeneration”. Third, the role of change agents in facilitating this adaptation in logics and finding legitimacy for a new and external policy practice is explored. Specifically this paper suggests that, when diffusing business and policy practices to a small, tight‐knit or rural community, the current incubation and diffusion literature would be broadened by a deeper understanding of the importance of social and cultural context and the role of community and place in the adaptation process. This paper will also argue that it is through tying external diffused practices specifically to community and place that business, government and local actors transform institutional logics and gain legitimacy and acceptance for new practices, thereby facilitating adoption.

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This research provides several contributions to the literature. First, by examining several instances of rural incubation, which has been little studied in previous literature, this paper supplements the heretofore limited work on the role of local context in understanding incubation and “why” it occurs (Hackett & Dilts, 2004), from both a business and government policy perspective. As well, this paper supplements the current work on incubation, which is limited in its focus almost exclusively on urban examples. Second, the literature on practice and policy diffusion similarly offers a limited explanation for the reasons and motivations behind the spread and adaptation of business and policy practices. The case of the spread of rural incubation, which only occurred some years after urban incubators spread across neighbouring urban communities, offers insight here. Specifically, the rural incubation case allows us to examine the previously unstudied role of space and place as a factor in adaptation of diffused practices and policies. Third, the rural incubation case provides insight into the role of legitimacy in determining which polices and actions change agents and government take at the community level. Finally, the role of “sense of place”, or simply “place” in providing both connection to the local context as well as legitimacy for key actors is developed, thus adding to the limited work on place and space in organization theory literature.

This paper begins with an overview of the current incubation literature, which is primarily focused on urban business incubators, and an overview of the role of business incubation in growing new enterprise and in driving economic development. This is followed by an overview of the relevant work on practice and policy diffusion as well as by a summary of the literature on space and place. The methodological approach and initial interview findings are then described and a framework developed for understanding the role of place in adapting policy and providing legitimacy – to businesses, local government, and the community itself – in a rural context.

Theoretical Context

Business Incubation

Business incubators first emerged as a model to encourage, assist and support nascent and start‐up businesses in the mid‐1950s, yet it wasn’t until the 1980s and 1990s that interest in the model as both a business and policy tool began to expand (Leblebici & Shah, 2004; Bollingtoft & Ulhoi, 2005). Incubators are now seen as both a politically popular tool in the public sector effort to support small business and entrepreneurs while fostering innovation and, by the private sector, as a cost‐effective means of collocating and growing promising new ventures. As such, the growth of incubators across North America and around the world has been rapid and far‐reaching (National Business Incubation Association (NBIA), 2010; Statistics Canada, 2005)

Although goals, practices, objectives, funding bodies, design, and tenants all vary (Bollingtoft & Ulhoi, 2005; Allen & Rahman, 1985), leading to disparate theories and definitions on incubation, incubators are consistently viewed as a vehicle for combining both the physical and social resources required by new ventures, with the aim of reducing early‐stage costs, compensating for failures in the market mechanism, filling knowledge gaps, and generally increasing survival rates (Allen & Rahman, 1985; Bollingtoft & Ulhoi, 2005; Phan, Siegel, & Wright, 2005). Business incubators have therefore been defined as “an enterprise that facilitates early‐stage development of firms by providing office space, shared services and business assistance” (Hackett & Dilts, 2004, p. 55).

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At the most basic level the incubator model provides economies of scale and reduces transaction costs for new businesses, locating them within a shared space where the costs of resources such as office supplies, equipment and services can be shared, to the benefit of the business tenant or incubatee. The provision of physical resources can include, but is certainly not limited to a shared receptionist, mail distribution, shared kitchen or lab facilities, answering services, broadband access, cleaning services, and below market rental rates (Allen & Rahman, 1985).

The social aspects of the incubator are a second, and at least equally vital, component of the incubator model and go well beyond the simple cost sharing measures provided by shared physical collocation of businesses. Research has shown that the ability of the incubator to increase the entrepreneur’s network, both within the incubator and externally in the broader community, is vital to incubatee success (Hackett & Dilts, 2004) and likely the most important value‐added component of the incubator model (Lichtenstein, 1992; Bollingtoft & Ulhoi, 2005). Within the incubator the ability to share ideas, spur creativity, and offer support and assistance between tenants is seen as important in enhancing innovation. The social capital built within the incubator, with both fellow tenants and management, allows the incubatee to learn skills, make contacts and develop social capital, and gather information which may not have been otherwise available (Granovetter, 1973; Burt, 1992; Scillitoe & Chakrabarti, 2009). Externally, the incubator network and resultant social capital benefits available to the nascent business through membership in the incubator may include contacts to universities, government agencies, research institutes, venture capitalists, suppliers, volunteer mentors, graduated firms and others (Scillitoe & Chakrabarti, 2010).

The role of the incubator manager in facilitating access to these social resources is paramount to incubator and incubatee success. First, the manager’s ability to develop trust and stimulate interactions is fundamental in providing access to and facilitating network interactions and helping to build social capital (Totterman & Sten, 2005). Second, the manager is able to provide businesses with mentoring, counseling and technical know‐how on topics from financing and marketing to business planning and technology (Hackett & Dilts, 2004). As such, the degree and quality of interactions with the incubator management have been shown to be key to the success of new ventures (Scillitoe & Chakrabarti, 2010; Allen & Rahman, 1985), as well as essential to the success of the incubator itself (Hackett & Dilts, 2004). The dyadic relationship between the manager, or other mentoring staff, and the incubatee is therefore a fundamental differentiating factor between business incubation models and other more episodic and less structured forms of government assistance, mentoring, and training programs that may be available to small businesses and entrepreneurs (Rice, 2002). This strong connection to the incubator management and network in addition to the important shared physical resources of the incubator suggest that the shared space of the incubator is vital for the effectiveness of the incubator model, making incubation a “geographically anchored arrangement” (Bollingtoft & Ulhoi, 2005, p. 267).

Current literature points to a paucity of research on measures of success and specifically on incubator‐incubatee economic impacts, as well as to more theoretically based answers to “how, “why”, and the contexts in which incubators are likely to succeed (Hackett & Dilts, 2004). Specifically, the social aspects of incubators have been generally neglected in favour of literature focused on the physical aspects and facilities offered by successful incubators. Second, attempts to measure success of incubators have shown differing yet positive results. Yet, for the most part, the effect of incubators and incubatees on the local and regional area and community has generally not been adequately

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considered or well measured and is absent from these important calculations (Mian, 1997). Understanding the role of, and impact on, the social and cultural context and the local community is vital to the study of incubation, specifically rural incubation.

Diffusion and Adaptation

The manner and means by which business and policy practices diffuse within and between organizations, and get from “here to there” (Ansari, Fiss, & Zajac, 2010, p. 67) has spawned an extensive literature in both organization theory and strategy. With its roots in institutional theory (DiMaggio & Powell, 1983) the study of the spread of ideas and diffusion of business practices within a social system (Strang & Soule, 1998) has traditionally focused on the isomorphic effects of institutions and the homogeneity of diffused business practices (Dacin, Munir, & Tracey, 2010).

More recently, this broad attention to mimetic practices and homogeneity has been criticized for its limited attention to the extensive diversity and customization of policies and practices that occurs in reality (Lee, 2009; Ansari, Fiss, & Zajac, 2010). The diffusion literature has been characterized by an extensive focus on the dichotomous adoption decision, with relatively less attention paid to the extent to which processes and structures are translated and transformed in the process of adoption and transmission. It has been posited that this omission may be a direct reflection of the fact that such phenomena are often more complex and therefore more difficult to study empirically (Lee, 2009). However, this lack of theoretical attention has led to a “relative neglect” of the extent of variation of adopted practices that actually occurs (Ansari, Fiss, & Zajac, 2010, p. 67).

Although relatively nascent, the discussion of heterogeneity in diffused practices is not new and has been traced to various causal factors and explanations of variation in adoption practices. In an early and foundational study in this regard Westphal et al. (1997) illustrated the temporal factors that may influence adaptation. The authors’ study of the adoption of total quality management (TQM) business practices in the health care industry illustrated that while customization of practices may be more common among early adopters (Westphal, Gulati, & Shortell, 1997), later adopters tended to be more likely to conform to the norms of practice already accepted. This finding indicated a positive relationship between conformity and the time or phase of TQM adoption.

Similarly, culture was recognized early on as a factor in the adoption of business practices, with local myths, symbols and institutions playing a role in how practices were understood and adopted (Strang & Soule, 1998). One body of literature suggested that a “translation model”, based in linguistics, was a more effective metaphor than the science based “diffusion model” which suggested that ideas and practices were transmitted intact (Zilber, 2006). Based on a study of the Isreali high‐tech industry Zilber (2006) supports and expands this body of literature through an illustration of the processes by which the translation model explains the changes from broad to local contexts, across time, and across institutional spheres, as ideas are spread, adopted and institutionalized.

Along a similar vein, the study of the process of adoption has led to recent work in developing a framework to better understand how practices are adopted and varied within the organization, and to challenge – or at least expand – the traditional and very mechanistic view of diffusion (Ansari, Fiss, & Zajac, 2010). Pointing to technical, cultural and political demands within the organization, Ansari et al. (2010) argue that adaptation is a common response to lack of “fit” between the practice and these factors, and is likely the norm rather than the exception.

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In the literature on diffusion of practices at the government and policy level, studies have similarly shown customization and differentiation in adopted practices and have made recent strides towards understanding the role of agency and context in policy diffusion. Recent studies have focused on the “dynamism of diffusion…documenting elements of heterogeneity, agency and context” (Lee, 2009, p. 1248). Research has illustrated that non‐state actors – social movements, self‐certification organizations, professional groups and trade organizations – can influence policy outcomes and explain regional variation in policy adoption. In a study of the effect of standards‐based certification organizations’ impact on policy adoption across U.S. states, Lee (2009) identifies impacts on policy diffusion at three stages, policy innovation, variation, and elaboration.

Similar work on the policy front has shown the role of local culture and institutions in influencing the manner in which diffused policies are adopted, why they are adopted, and their subsequent success (Weber, Davis, & Lounsbury, 2009). In a study of the adoption and varied success of stock exchanges in the post‐World War II period, Weber et al. (2009) identify several means by which policies were diffused internationally – coercion, learning, emulation and competition – all with varying levels of later success. These findings indicate the importance of understanding variations in idea adoption and adaptation, and suggest that adaptation processes may be fundamentally linked to success of adoption.

Despite this expanded understanding of how diffused practices are adapted at the organizational level there still remains a paucity of research on the role of agency (Zilber, 2006) and individual change agents (Ansari, Fiss, & Zajac, 2010) in the translation and adaptation of diffused ideas, as well as studies across firms and organizations. In addition, researchers have pointed to a lack of understanding of the meanings attached to practices (Zilber, 2006) and the micro‐institutional process by which practices are adopted (Weber, Davis, & Lounsbury, 2009). But more generally, the overall understanding of customization and variation of diffused policies and business practices remains limited (Lee, 2009; Ansari, Fiss, & Zajac, 2010).

The case of the spread of business incubation, and later rural business incubation, in Ontario provides a classic example of diffusion. It should first be noted that although much of the diffusion literature has focused on the spread of new business “practices” to pre‐existing organizations – such as the Poison Pill (Davis, 1991) or TQM practices (Westphal, Gulati, & Shortell, 1997) – the literature on policy diffusion has taken a somewhat broader perspective. In this body of literature, diffusion of policy “practices” includes the imitation and introduction of broader forms of practices such as new regulatory regimes (Lee, 2009) or the introduction of new government sponsored organizational forms themselves, including stock exchanges (Weber, Davis, & Lounsbury, 2009). As business incubators are primarily government‐sponsored in both Canada and the U.S. (Statistics Canada, 2005; NBIA, 2010), it is in this later light that diffusion of incubation is considered.

A Sense of Place

Despite the growing number of studies on the factors that may explain adaptation of diffused policies and practices, one factor which has previously been overlooked in the literature on variation and customization of diffused business and policy practices is the connection which regions, businesses, cities and towns have with their geographical location, or “place”.

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The role of the external and institutional environment has played a prominent role in organizational studies and strategy research since the late 1970s in theories including resource dependence theory (Pfeffer & Salancik, 1978), population ecology (Astley & Fombrun, 1983; Hannan & Freeman, 1977) and institutional theory (DiMaggio & Powell, 1983). Yet across these various approaches the external environment has generally been understood in terms of outside actors, values, and constraints on the organization. While these approaches have been valuable and yielded important insights into diffusion practices, their view of the environment is limited to social, cultural, normative and economic factors. The geography literature expands this understanding of the environment to include the physical and cognitive aspects of location.

The literature in geography and the organization theory, strategy and diffusion literatures are by no means strangers to one another, with geography long deemed to have a place in determining the nature of organizational responses to external pressures (Suddaby, Elsbach, Greenwood, Meyer, & Zilber, 2010). The importance of distance, local context, and spatial structures to innovation has been established both theoretically (McCann, 2007) and empirically (Shearmur & Doloreux, 2009) in the geography literature, linking local innovation to both local and broader spatial interactions of businesses. Similarly, the business and policy literature has recognized the role of location in understanding business decisions, practices, vocabulary, and practices. Most prominently, in groundbreaking work on the development of networks and clusters in Silicon Valley, Saxenian (1996) underlined the importance of understanding what occurs in the external environment or “outside” the firm, specifically the impact of the “social structures and institutions of a particular locality” (Saxenian, 1996, p. 42), in order to understand differences in regional clusters and regional practice variations and adaptations.

The diffusion literature has similarly had ideas of relative location and distance at its core since its foundations (Rogers, 1962; Tolbert & Zucker, 1983), and they continue to grow with the ongoing popularity of research on the role of business clusters and knowledge spillovers (Howells, 2002), and social networks (Burt, 1992; Xiao & Tsui, 2007; Saxenian, 1994) in understanding diffusion. These ideas are all at least somewhat tied to geographic proximity, either directly, or indirectly through concepts such as ‘relational proximity’ which are often highly related to geographic propinquity (Howells, 2002).

Although this body of research linking diffusion and geography is an important basis for the current analysis, it is not the focus. Instead we look to the body of work in humanistic geography on the “sense of place” and “sense of community”, and bring this more meanings based and social constructionist view of locality to the diffusion discussion. Seminal political geographer John Agnew is noted for initially outlining three fundamental aspects of place which have informed much of the later literature (Creswell, 2004): 1) Location or geographical site, 2) Locale or the material setting for social relations such as a building or specific place, and 3) Sense of Place or an emotional connection with the location and locale.

Geographic literature has focused on the social, rather than simply locational, aspects of ‘place’, seeing the place as a geographical locale within which an individual routinely travels, is aware of and has become bonded to (Hay, 1998). As such a ‘place’ becomes a “repository of meaning” (Hay, 1998), a “center of felt value” (Eyles, 1985), a “historically contingent process” (Pred, 1984), a “social field”

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(Stokols & Schumaker, 1981), or a “meaningful location” (Agnew, 1987) complete with shared meanings among its members.

In this approach the geographical location is much more than simply a spot on the map, but instead becomes an “anchor for identity” (Hay, 1998) with which individuals have subjective and emotional attachment (Agnew, 1987). Place is therefore seen as a way of seeing and understanding the world (Creswell, 2004). As such, place has been suggested as a key concept in understanding links between agency, context and political or social actions (Agnew, 1987), and has been linked with structuration theory to explain how agency effects social structures and political behaviour (Agnew, 1987; Pred, 1984).

In both the current case and the social science literature the concepts of community and place are tightly linked and the distinction between the two is often difficult to tease out. Although geographers admit the high degree of overlap between the two, they suggest that it is only the social sciences literature that experiences a “high degree of confusion” (Agnew & Duncan, 1989, p. 10). So as not to fall victim to such criticism in the current paper it is important to point out that community is a concept which suggests collective social interactions and a sense of belonging, while ‘place’ is the “emotional attachment people have to a place” (Creswell, 2004, p. 7) and the context and structure within which those social relations occur (Agnew & Duncan, 1989).

Research Context: Rural Business Incubation

Business “incubation”, as a practice to spur or “hatch” innovation and support start‐up businesses, can be traced back to the mid‐1950s, when the first incubator emerged in New York state in 1959 (NBIA, 2010). Despite this long history it wasn’t until the 1990s that the practice became more widespread, with the idea diffusing rapidly in both business and policy circles, and university and technology‐based incubators emerging across North America and around the world. The U.S.‐based National Business Incubation Association (NBIA) reports their numbers expanding from only 12 members in the mid‐1980s to well over 2,000 members by 2005 (NBIA, 2010), while Statistics Canada reports roughly 83 operating incubators in the same year (Statistics Canada, 2005). However, research conducted as a portion of the current project suggests that incubator and social innovation hub numbers in Canada may in fact be closer to 140 (see Appendix C).

The idea of business incubation has spread rapidly across North America and around the world in the last decade, as Western economies struggled to increase innovation and entrepreneurship in the name of economic growth. While incubators have emerged across Canada, they have been particularly popular in the recent decade in the technology and manufacturing hubs of Ontario. The business incubation model has had prominent government and private support, leading to several new incubator facilities opening in the mid‐2000s. Prominent incubators such as MaRS Discovery District in Toronto, the Innovation Fusion Centre in Markham, and nGen in London have received broad‐based public and media attention, business interest and investment, and government funding and assistance (Laurin, 2011).

Despite the attention and recognition that incubators were receiving among various groups of actors, it wasn’t until the spring of 2010 – half a decade after incubators had dominated business and policy discussions and been opened in nearby urban centres – that the practice began to make its first real

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foray into the rural areas of the province. The spring of 2010 saw several new incubators opening their doors within months of one another in Picton, Haliburton, Elgin and Port Hope, to name just a few, and with others in the planning stages in the nearby communities of Belleville and Renfrew, among others.

Yet with small community populations and few, if any, technology‐based businesses and university partners to collaborate with, the model that was adopted varied significantly from the urban model. While fostering and supporting small business remained a primary objective, technological innovation was no longer a key motivating factor for attracting public, government and business support for investment dollars. Instead, rural incubators turned to other factors such as community preservation, heritage, and roots as they built support among stakeholders. As such, the case of the spread and diffusion of business incubation as a policy practice in rural Ontario, and the methods by which it was adapted to the local social and cultural context, provides a valuable opportunity for further analysis.

Methodology

Project Overview

This project consisted of four phases as outlined below:

Phase I:

Due to the limited data available on rural business incubation in Canada, in the late spring and summer of 2011 Dr. Tina Dacin and Wren Montgomery worked with local CFDCs (Community Futures Development Corporations) as they designed and implemented a national rural incubation survey.

A brief overview of results is included as Appendix B of the research paper.

Phase II:

Due to the fact that a comprehensive and current list or database of incubator and social innovation spaces in Canada did not previously exist, the second phase of the project was to compile a list of all such spaces as of August 2011.

Results are summarized in Appendix C of the research paper.

Phase III:

Ongoing interviews at social innovation spaces and business incubator facilities conducted throughout 2011 led to the completion of a preliminary research paper on diffusion of incubation policies from urban to rural communities and on adaptation of, and variation in, incubation practices.

The research paper is attached on the following pages.

Phase IV:

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Due to practitioner and policymaker interest in rural incubation and social innovation, the research team was asked to present their findings on business incubation at the Ontario East Municipalities Conference, held in Kingston Ontario in September 2011.

Data Sources

A grounded interpretive approach was selected to answer the research questions regarding the spread of rural incubation and how it differed from the extant literature on urban incubation. Grounded theory building has been shown to offer unique insights into phenomenon (Brown & Eisenhardt, 1997; Glaser & Strauss, 1967). Theory development is enhanced through understanding the “properly contextualized experiences of those involved” (Dacin, Munir, & Tracey, 2010, p. 1399), and can permit the inclusion of several different actors’ perspectives in the data collection. Towards this end, several qualitative methods of data collection were utilized during the course of this study. Data was gathered from four separate sources: semi‐structured interviews; participant and non‐participant observation and visits to the incubator sites; archival data from media sources; and, the collection of materials, data and documents from other key actors including government and industry associations, community groups, and the incubators themselves. In addition, the author participated in the design and implementation of a survey of economic development offices across Ontario, formally termed Community Futures Development Corporations, or CFDCs.

The utility of the case study approach in investigating little understood phenomena and developing new theoretical insights has been well established (Yin, 1984; Eisenhardt, 1989). Building theory using case studies involves selecting cases that offer unique access, are exemplars, or may provide important and revealing opportunities to develop theory from empirical evidence (Eisenhardt & Graebner, 2007). As such, the current study was developed based on insights gained from preliminary research on the case of business incubation in rural Ontario.

In addition to providing context for the interviews, the external and archival data collected allowed for analysis to be conducted using an insider‐outsider approach (Dutton & Dukerich, 1991; Gioia, Price, Hamilton, & Thomas, 2010). Understanding the diffusion of rural incubation practices, their adaptation, and the role of place and legitimacy in those changes involves researching both the actors within the incubator itself as well as those in the broader community, this technique was therefore relevant and necessary to adequately address the research questions.

Table 1: Data Inventory

Data Type

Quantity Original Data Source

Original (intended) Data Audience

Interviews (see Table 2) 13 long‐interviews (30 to 90 minutes)

Informants Analysis for current study

Observational Data Approximately 30 hours Principal investigator’s notes from multiple site visits, meetings attended, and community

Analysis for current study

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observations and public events

Survey Responses (see Appendix B)

36 responses Survey conducted by Ontario CFDC bodies, with Queen’s assistance, on incubation

CFDCs, municipalities, regional government, academia, public.

Government, Academic and Industry Association Documents on Incubation

300 pages Meeting materials, slides presentations, press releases, memos, vision documents etc.

Community members, meeting participants, current and potential incubator tenants, media, public

Consultants and Advisory Reports

61 pages Press releases, posters, website, flyers, letters to CSC and Ministerial staff etc.

Local and/or regional government officials, incubator managers, community panels, media, public

Local Incubator Materials and Press

50 pages Promotional materials, press releases, websites, vision documents, administrative materials, newspaper and third‐party website articles and editorials

Tenants, prospective tenants, government bodies, funding agencies, managers, media, public.

Archives, online data and popular press.

Given the important role of the media, consultants, experts, industry incubator associations, and government agencies in diffusing information on incubation practices and policies, materials from several sources were collected and analyzed to provide context for the qualitative interviews and further analysis. Further details of all data sources, quantities of materials, and the original intended audience for the material, are displayed in Table 1.

Interviews and observations.

The second phase of data collection included semi‐structured interviews with key informants, including incubator tenants and managerial staff, local community actors and local government officials in various roles. The sampling technique used was both deliberate and emergent (Eisenhardt, 1989), using a “snowballing” technique whereby certain participants were selected outright but others were suggested to the interviewer by initial interviewees. Purposeful sampling of informants has been shown to be relevant and effective where data comparison across participants is required for effective data gathering and analysis (Gioia, Price, Hamilton, & Thomas, 2010). These interviews were conducted in person, digitally recorded and later transcribed. At this stage of the research project

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thirteen long interviews were conducted (McCracken, 1988) ranging between 30‐90 minutes in length. Sample interview questions are included in Appendix 1.

These interviews were supplemented with field observations and attendance at several events. These included visits to several incubator facilities and government offices, as well as attendance at meetings and at two conferences on incubation and economic development, which were attended by communities that had incubators already in operation or were considering establishing one. Materials, proceedings and field notes taken at or after these events provided further insight into the communities and incubators under study, and the ability to hone interview questions and techniques accordingly (Dacin, Munir, & Tracey, 2010).

Rural incubation survey.

In the course of conducting this research the author was asked to advise on and assist with a survey conducted by local economic development officials at a regional CFDC on rural incubation. The survey consisted of 92 questions as well as a series of demographic data. The survey was sent to 259 CFDCs across Canada and was completed by 36 respondents, a 14% response rate. Key findings are compiled in Appendix B. However, given the fact that the author was only a contributor to this project, and had no influence over survey distribution, ethics, or data collection techniques, these results are only offered as a reference source in the current research and no further quantitative analysis has been conducted.

Data Analysis

Qualitative data were analyzed using NVivo 9.1 which allowed for the organizing and analysis of large amounts of qualitative data including interviews, archival data, and observation notes. The results assisted in the categorization and structuring of data, particularly interview data, that follows. The qualitative data were analyzed using a multi‐step process (Nag, Corley, & Gioia, 2007; Dacin, Munir, & Tracey, 2010) whereby data were first analyzed or ‘coded’ using “in vivo” words and statements. Second, this data was then grouped into first order themes using and retaining the language and meaning of the informants. Second, second order themes or analytical categories were identified. Finally, theoretical categories were developed grouping together analytical categories into overarching dimensions. Thus, as stages progressed data were analyzed at progressively higher levels of abstraction, while ensuring that analysis accurately reflected the data (Brown & Eisenhardt, 1997). This process is briefly summarized in Diagram 1. Although data was collected by a sole researcher, and inter‐coder checks for reliability of analysis and coding were therefore not possible, the author conducted an iterative interpretation process and “member check” with key informants including both one‐on‐one meetings, as well as the preparation of a research document to inform participants of the findings as they progressed and the presentation and discussion of findings at three practitioner oriented conferences where input was encouraged. Accordingly, analysis and interpretation was verified with informants in order to ensure that they adequately and credibly captured the original data and informants’ meanings.

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Diagram 1: Data Analysis and Structure

Findings

At the outset of this research project little was known about the new rural Ontario incubators in question, including their design, purpose, goals, participants and objectives. It was assumed that, as in the more extensively studied case of urban incubation, these new organizations were being utilized as an economic development tool and as an instrument to drive technical innovation. However, as the project progressed we found that the role of these incubators in rural communities differed in many important respects from their urban neighbours. Instead of simply a driver to expand business and spur innovation, the rural incubators played a much more fundamental role in the heart of their communities in several ways: by offering needed resources and a chance for both tenants and the broader population to connect in a shared physical space; serving as an opportunity for both government and community players to demonstrate their commitment to the community; functioning as a symbol and a driver of a growing entrepreneurial culture within the community; and, as a signaling device to the external environment as to the community’s commitment and openness to business.

At the heart of all of these aspects we found a commitment and tie to the local community, the desire to preserve its history and traditions, and the important connection to the “place” in which they were located. This importance of place is evident in three key aspects. First, in the interactions within the shared physical space of the incubator itself whereby place allows for reduced isolation, a sense of community, as well as the collaboration, social ties, and cooperation that would be expected from an

A. Availability of office space limiting business growth

B. Access to required technology in central rural hubs Physical Resources

First‐Order Categories Second‐Order Themes Overarching Dimensions

Social Resources

Government

Change Agents

Image

Identity

Incubator: Connections to Place

Actor Legitimacy: Logics of Place

Community Sense of Place

C. Access to mentoring and other services within space

D. Business networks within incubator space

E.Governmentsignalssupportandfacilitatesbusiness F.Promotionofcommunitytoexternalstakeholders

G. Leading or spearheading development of incubators

H.Activeagentsinbothgovernmentandprivatesector

K.Abilitytoretainyouthandofferopportunities L.Communityseenasviabledestinationforbusiness

M.Placeafocusfortraditionalandnewbusiness B.Renewedbeliefinvitalityofcommunity

J. Recognition of the importance of place to community

I.Broad‐basedcommunityinvolvementinnewbusiness Grassroots

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incubator. Second, place provided a vehicle for key actors, both government and other community agents, to change the traditional framing or logics of the business incubation policy idea to one that more closely matched, and was thereby accepted, in smaller rural communities. Finally, the commitment to place was at the heart of a growing connection to the local community and how that identity was spread between actors within the community while also altering the image of the community held by outside actors. More in‐depth detail as to the specificities of these findings are elaborated below and in Table 2, they are then followed by a broader discussion of the implications of these findings for theory.

Connections and Legitimacy: Incubator as “Place”

Previous studies have outlined the role of the incubator in offering both shared physical resources, such as office space and equipment, and shared social resources, including mentoring, training and enhanced networks both within and outside the incubator (Allen & Rahman, 1985; Hackett & Dilts, 2004; Bollingtoft & Ulhoi, 2005). These findings were both replicated in the current study of rural incubation. However, within the incubators themselves, the nature of the businesses and the dynamics were somewhat different. Instead of innovation, profits and business growth being the primary driving force, as is the case in the majority of urban incubators, the rural incubator tenants were focused on the legitimacy benefits of getting out of their home offices (often basements and drive sheds), finding practical office space, and reducing the extreme isolation of a rural home office.

Physical resources through shared space.

One of the central purposes of a business incubator is to assist new businesses by offering physical resources at lower cost through collocation of businesses, economies of scale, and potentially through government subsidies. This was certainly true in the rural case as well. However, the need for physical resources, and the importance of collocation and shared space was even more profound in this case. Instead of simply reducing costs of physical resources, the incubator often proved to be the only source of such services in small communities. In several communities incubator tenants commented that there was no other suitable office space for rent in the community, regardless of cost. In addition, limited access to broadband networks in Ontario’s rural communities meant that many tenants could only access high‐speed connections at the incubator, and not at their homes or prior office locations. As one government official commented on the business limitations that this imposed,

They are sending out these huge files and without that infrastructure in place it was hard for them to take on some of the extra projects they had demand for.

As a result of the lack of necessary physical resources in small rural communities, respondents felt that their professionalism and legitimacy was impacted, thus even affecting the bottom line of their businesses. As a result, moving to the incubator allowed respondents to feel more professional and more legitimate as business people, a feeling which was reflected in their bottom lines. As one tenant commented,

…when they know you have an office space you can quote the upper end of what you were prepared to quote before. But when they know you are working from your basement there is an element of ‘it’s a hobby’ what you’re doing.

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The physical resources provided by the incubator are only a portion of the incubation model, social resources are likewise important in the rural context.

Social resources through shared space.

The incubation literature has illustrated the importance of the multitude of social resources provided to entrepreneurs through the incubation model (e.g., Bollingtoft & Ulhoi, 2005). First, the role of the incubator management in providing mentoring, training, and counseling services to tenants has been shown in numerous studies to be among the most important variables in determining incubatee success (Hackett & Dilts, 2004), providing services from marketing training and business plan development to advice on technology and financing. In a rural environment this business knowledge is likely to be even more scarce, making the incubator manager a valuable resource of information both for the tenants and the broader community. As one manager and business owner commented,

We probably get three to five calls a week from people. “I just want to pick your brain. How did you make this work? How did you pitch that [product]? And then what happened? How did you talk to this bank manager?” We get these calls a lot. Which is great, wonderful.

In addition to providing business knowledge, the incubator management is also essential in enhancing the social capital and networks of the new business venture. This occurs first by working to convene the tenants themselves, providing opportunities for tenants to come together, collaborate, and share ideas in order to foster innovation, creativity and business relationships. Second, the management functions as a liaison to a broader network of contacts, business people, universities, investors, advisors and funding agencies. While this is fundamental in the urban context, in the rural context the business incubator is often one of the only business‐oriented organizations in a community where entrepreneurs may have little other formal opportunity to collaborate. The importance of both of these dynamics was apparent to the informants. One tenant notices that moving from a rural home office to the town’s centre “helps keep you in the loop” while another, commenting on his experience after just a few months in the incubator, describes the space as,

…an environment with other people where there is a collision of ideas and some new streams of revenue just from other people in the building…

The physical and social aspects of the incubator, while important in an urban incubator, appear to be even more important in a rural environment. The role of physical objects and resources has been shown to be important in shaping workplace identity and attachment to the individual’s workspace (Elsbach, 2003), as is illustrated here. The traditional role of the incubator space in assisting the business and individual in enhancing legitimacy and shaping identity may be even more prominent in the rural environment where these resources may only be available through the incubator. The emotional attachment, bond (Hay, 1998) and meaningfulness (Agnew, 1987) of the incubator as a place is therefore enhanced, and is critical to understanding the important role of the incubator as a centre of community and collaboration in rural communities.

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Policy and Actor Legitimacy through the Logics of Place

As business incubation was introduced to the rural communities in question it appeared that the underlying rationale for their emergence was fundamentally different from that of the urban communities, which touted the incubator’s potential for “innovation” and “growth” (e.g., MaRS Discovery District, 2011). Instead, rural actors, both government policy actors and community members, relied on different language, symbols, and techniques to gain legitimacy and acceptance of this new policy and organizational form in rural communities. At the heart of this difference was drawing on the important connection to place in the rural environment. We now turn to the use of place as a source of both policy and personal legitimacy on the part of actors at both the government and community level. Although groups such as city councils and not‐for‐profit organizations played an important role, individual change agents were at the forefront of the introduction of incubation to these rural communities.

Government agents.

Economic development staff, municipal government politicians and staff, and CFDC staff were all of primary importance in the introduction of the incubator model to rural communities. Incubators have been shown to offer local governments a source of legitimacy in that they are a concrete and highly visible commitment to, and investment in, the business community (Lalkak, 2001). Although government as a whole may benefit, the role of key policy actors in facilitating the introduction and establishment of incubators, and championing the model, is also well documented, as are the legitimacy conferring effect to actors of being at the forefront of incubator introduction (Aaboen, 2009).

In the rural context these factors are very much at play. However, in small regions government actors are highly dependent on community buy‐in to establish incubators and ensure funding. As a result, government actors utilize the language of place in an effort to gain legitimacy for the relatively foreign concept of business incubation. A government staff member pitches the local incubator as first and foremost a community benefit, with individual incubatees second,

Skills training for the community, for their businesses, and the businesses that are in there.

This connection to the community and feeling that the model was a community initiative was important in the perception and acceptance of the incubator, even when the incubator was not in fact exclusively or even primarily a community project. As a government official recounts,

So my view on incubation is that if there is a way to engage the private sector to lead and run with it the chances of success will be far greater than if it is government. And the reason is, even if an incubator may either be a not for profit or both real and perceived as a community initiative, there are going to be people at the helm who have vested interest and self‐interest, and self‐benefit.

Maximizing the sense of place is essential to the government actors’ ability to execute their own jobs in drawing business to the community and expanding opportunities. Incubators can be used as a “tool for policy actors” in order to demonstrate to both the community and to their own superiors that they

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are taking action on economic development (Aaboen, 2009, p. 668). As one economic development officers comments,

So how we work [here] is we let everybody else in the world know as much as we can, through public relations and social media, what a wonderful place it is, and people just come knocking on our door and say “how do we invest in that community”. It has worked great, I am like a, to a certain degree I am like the guy on the tarmac landing planes, we just land the planes. Most of my counterparts are in a shark fight, dog fight, with their briefcase, knocking on doors trying to convince people to move there. I don’t know how to do that.

Community agents.

Although grassroots community organizations were later adopters of the idea of incubation they seem to have quickly recognized the benefits of the model to their own purposes, and its legitimacy enhancing benefits. In one community several arts, cultural and social not‐for‐profit organizations were grouped under one roof with a government economic development agency and began to refer to themselves as an “incubator”, quickly realizing the benefits of shared space in order to build their own brands, gain legitimacy, and enhance support and buy‐in among members. As one arts association director recalls,

Being here, rather than being a kitchen table operation, we can meet in our office rather than “I will come in from my home” or “do you want to meet at my home”. Now we can partner with the libraries and the wineries and so it has been huge in terms of perception, credibility, whatever.

In addition, community groups rapidly began to adopt the language of incubation as the model became accepted in the community, rebranding existing services with new terminology, even though the services being offered were not in a collocation model or shared space but simply mentoring services. As one community group leader recounts regarding the group’s long‐standing mentoring services for new community arts initiatives,

Participant: They think we are big. We help them get going, we have a whole incubation policy.

Interviewer: Do you actually refer to it as incubation or…

Participant: Yeah, yeah we do, we have our events, we have our core services which are membership services things, and we have our incubation. I will send you our incubation policy, it’s one page or two pages.

In small rural communities the language of place and community connection was utilized in order to gain local acceptance for the incubator model at the outset. As interest and knowledge about the incubation model grew in the local community the idea of incubation itself then began to offer legitimacy for local business, community groups, and change agents. Although touched on briefly in prior research (Aaboen, 2009; Lalkak, 2001), this effect appears to be much more profound, and much

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more fundamental to understanding the social and cultural conditions of rural incubator diffusion, than in the urban context.

Renewed Sense of Place: Identity and Image

In addition to establishing a sense of community connection and legitimacy within the actual shared space of the incubator and for key actors and groups, we saw evidence that the incubator was at the heart of a stronger connection and sense of shared mission within the community as a whole. This occurred as a result of both the incubator’s ability to inspire a renewed feeling of connection between businesses and the community, and by illustrating the community’s commitment to business through the willingness to provide funds and social support for its entrepreneurs. This in turn both enhanced an entrepreneurial culture within the community and reinforced the traditional community bonds. This renewed pride and internal perception of what it meant to be a member of these rural communities impacted the community identity or self‐perception (Dutton & Dukerich, 1991). In addition, it was also perceived as likely to provide enhanced legitimacy in the eyes of outside actors thereby also improving the community’s image (Dutton & Dukerich, 1991) and ability to attract both business investors and tourists.

Community connections and identity.

Many of the rural communities studied had undergone, and were continuing to suffer from, economic hardship, a greying population, and an exodus of business and youth. As a result, the community identity had suffered. The addition of a business incubator appeared to provide an important rallying point for the community and a clear indication to its own members of the commitment and viability of business, as well as the vitality of the community as a whole, aiding in redefining and shaping a new identity (Gioia, Price, Hamilton, & Thomas, 2010). As one Incubator Manager comments on the important role of government funding from the community economic development office for the incubator,

So what the money has allowed us to do has been wonderful. It would have taken us a few more years to get to that point but I have no doubt that we would have gotten to that point. And to us it is more than the money, it is the expression of support from the community that is so important.

Just as community support for the incubator helped to illustrate the community’s belief in its business people and entrepreneurs, the incubator and the businesses located within it were able to help change community attitudes towards business and opportunities for success. As one incubator Manager observes on the changing community attitude towards business and entrepreneurship,

We are starting to see a bit of a shift through these monthly [business support group] gatherings…and that’s I think a big wake‐up call for the community.

This changing attitude towards the community’s identity was also seen as an important factor in retaining young people in the community, seen as an important aspect of revitalization by numerous informants. As one young incubator staff member hopes,

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…it is just about creating a new opportunity for the community so that young people, they might go away to get their post‐secondary education but they don’t need to stay away, they can come back because the opportunity is here for them to do something fun and be their own boss.

Community external image.

Just as the internal perception or identity of the community was changing in the eyes of the inhabitants in light of the growing support for an entrepreneurial culture, so too is the perception of the community’s external identity. The incubator allowed government officials, and other actors tasked with promoting the community to outside investors, an opportunity to tell a unique story about their community. These stories of the success of opening the incubator, or of its tenants, were told with pride and were pervasive throughout the incubator as an organization and the community as a whole. A local government official recounts the surprised reaction that the incubator and the global success of one of its anchor tenants elicits from external audiences and how it changes perceptions of the community,

“What?” No its 3D television production. 3D television production in a rural area and there is a 6,000 square foot building with 25 people working in it, pumping out product that goes out around the globe. So it becomes iconic and it gives us a story to tell. Concrete. It concretizes the concept.

The establishment of an active and growing incubator also is perceived to provide both the community and the government with increased legitimacy in the eyes of external stakeholders and businesses. On the role of signaling this commitment to outside audiences an incubator tenant remarks,

From a business perspective, if you have a municipality that shows time and time again that you are willing to work with local businesses to build the local economy, that is a godsend to draw people from Toronto or Ottawa or wherever else. And it is a huge repulsion when they do the opposite.

Although the funding commitment and government and community support for business are important to drawing investment, informants were very aware that the traditions of the community, quality of life, and the bonds of its members to the community are likewise important components of the community’s external image. A tenant speculates,

I am not sure exactly the reasons they want to move here. I think there is a cost advantage, lower operating costs, quality of community, sense of place.

In numerous aspects it was apparent from respondents in various roles that the incubator had been fundamental in regenerating and renewing the traditional and historic connection to the locale, bringing renewed meaningfulness and connection to the place in the eyes of both the local community and outside stakeholders.

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Table 2: Dimensions, Themes, Categories and Data

Overarching Dimensions, Second‐Order Themes and First‐Order Categories

Representative Data

I. Overarching Dimension: Connections & Legitimacy – Incubator as “Place”

1. Physical Resources through Shared SpaceA. Availability of office space limiting business potential and growth

B. Access to required technology for business often available only in central meeting spaces/hubs in rural areas

A1. “Finding space was tough, there was not a lot of affordable office space available” (incubator manager)

A2. “There is really a lack of suitable office space in [town] at the moment, so this is one way to try to give a more professional atmosphere. You can’t bring somebody into your basement if you are trying to win a big contract.” (local government official) B1. “We have 16 megabit service over there so we are as fast as fibre optics, which in a rural area is huge.” (economic development staff member)

B2. “They are sending out these huge files and without that infrastructure in place it was hard for them to take on some of the extra projects they had demand for.” (municipal government official)

2. Social Resources through Shared SpaceC. Access to mentoring and other services through incubator space

D. Business networks within incubators built through shared space/collocation

C1. “We learned totally by trial and error. We have seminars and informational situations where young entrepreneurs and tenants can also learn from our trial and error” (incubator tenant with established business)

C2. We are partnered with the CFDC, we are partnered with the business advisory centre, so we provide mentors and advisors through them.” (incubator manager on access to services for tenants)

D1. “When you get in a group setting or get together, that is when people start talking and that is so important and I think the idea of a creative space is a very good idea.” (incubator tenant)

D2. “But we wouldn’t have worked with them if they hadn’t been collocated.” (incubator tenant on another tenant)

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II. Overarching Dimension: Policy and Actor Legitimacy through the Logics of Place

3. Role of government in strengthening place E. Signals business support and facilitates business interactions through community events and financing

F. Promotion of community to external stakeholders, tenants and customers

E1. “They came to us with a bit of a vision about the [incubator] and we acted as a facilitator to try and build some infrastructure and some funding to allow them to realize their vision.” (government official on government support role in incubator start‐up)

E2. “You might find that there are more grants get distributed [here] then somewhere else, not because there are more people that want more, because people probably want them everywhere, but people find out about them more here.” (incubator tenant on government involvement in community)

F1. “So the ones that are here we are cataloguing them and articulating that they exist.” (government official)

F2. “So what the [incubator] does next for us in the community is to say ‘you know we’ve been talking about creative economy and you kind of get it but you kind of still think it is art’. ….So it becomes iconic and it gives us a story to tell. Concrete. It concretizes the concept.” (government official)

4. Role of change agents in building sense of place G. Agents leading or spearheading development of incubators H. Active change agents in both government and private sector/community

G1. “And [the investor] said ‘I’d be willing to provide a building and maybe even free rent and take a piece of the action. So it really started from another discussion, back to my earlier – we are engaged.” (government official on role of private incubator investor)

G2. “We had a consultant who recommended a “creative business incubator” to attract knowledge‐based businesses as an economic development mechanism.” (incubator manger on origins of the incubator idea)

H1. “[She] always thought that a business incubator would be a really great idea to integrate all of those separate programs.” (incubator manager on government official who funded incubator)

H2. “And then you have people …here in economic development and they are doing everything they can to maintain a local economy and foster creativity and fuel the flame that is here, and they are on our side so to

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speak.” (incubator tenant on importance of two municipal leaders)

5. Active grassroots support for place I. Broad‐based involvement of community in supporting new business ventures

J. Grassroots recognition of the role of place in the strength and survival of the community

I1. “So our role is to listen, to understand, and then figure out how to facilitate. So that kind of model. So it was bottom up, totally bottom up So we did not have a strategy that said we need incubators.” (government official on origination of idea)

I2. “Things tend to happen more organically here…there us a real culture here about buying local, buying from one another.” (community group leader)

J1. “So we have these design flaws but these design flaws automatically create a sense of community. Because you have the downtown core who are connected to each other, you have the folks at the far end who are disconnected from the rest so that creates a different sense of community – “top of town”. They have their own relationship up there because they are isolated from the main core. Again, that’s where the shared synergy comes into effect.” (government official discussing community geography)

J2: “And part of the reason for operating here is that there is such a focus on creativity. If you do something creative there are lots of spotlights and lots of searchlights and everyone is going “hey, that’s great”. If you were in a big city you just end up being…but here you are near enough with the people in the community to get to know and trust people”. (incubator tenant)

III. Overarching Dimension: Renewed Community Sense of Place: Identity & Image

6. Community connections and identity K. Relationship to place a focus of changing (traditional vs. new) businesses and potential conflict

K1. “We are sensing that more and more as we moved into the [incubator], for a long time people could sort of ignore us, we could fly under the radar. It is back, the elephant.” (incubator tenant on clashes between new and old economies)

K2. “People are starting to move on from the idea that they are going to come here and create a business and their customers are going to be right here. We have really struggled lately to say “you know what, we are a factory, we make a product, maybe we don’t make Kellogg’s and tires.” (incubator manager)

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L. Renewed internal belief in the vitality and business opportunities available in the community

L1. “It gives people a really good feeling to build something themselves. So I just envision a really good positive vibe…more young people and more diversity within the community.” (incubator manager on how the incubator may change youth opportunities)

L2. “Here is a fellow from this area that says to himself ‘I would really like to come back’, you know, that whole quality of place, this is a great place to raise your children, have a high quality of life.” (government official)

7. Community image and perception M. Ability to attract and retain youth and offer opportunities in the community

N. External stakeholders seeing community as viable destination for business

M1. “Selfishly we have [children] and one of them has started to work with us part time, and we want to create work for people in this area. ” (incubator tenant)

M2. “It is vital to the continued growth of the area that we are able to attract and retain, especially retain, younger people. This is one of the greyest areas in Ontario I think. The tax base is so unbalanced here right now.” (incubator manager)

N1. “If it fulfills the goals it does a couple of things. I think that it raises the profile of [town] by having something here that could perhaps get in recognition outside the community.” (incubator tenant)

N2. “Toronto, London, Tokyo, New York, [town] – what? Well, we don’t have the big urban stuff, we can’t give you that, but we have the opposite, you might enjoy it. But you can do your thing and you can plug in and you are good to go.” (government official)

Discussion

From the findings above it is evident that the rural incubation model differed in important respects to its urban counterpart, which has been more broadly studied. Rural incubation played an important role not simply for the incubator tenants but in building a sense of community, connection, and legitimacy for actors throughout the community. This research points to important social and cultural aspects of the context in which incubation occurs that have been previously unstudied (Bollingtoft & Ulhoi, 2005). Here, we turn to a more in‐depth discussion of three of the key mechanisms by which the incubator is impacted by, and impacts, the community in a rural context – institutional logics, the use of place, and the role of key change agents.

The Role of Institutional Logics in Adaptation

The work on institutional logics has a solid foundation in organization theory. First introduced by Alford and Friedland (1985) to explain the contradictory political practices and beliefs in the political

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institutions of modern society, institutional logics were seen as “the core logic” of the institutions of society, which both constrain action and provide sources of agency and change (Friedland & Alford, 1991). Early work by Thornton and Ocasio on the logics of the educational publishing industry defines logics as a “socially constructed pattern of material practices, beliefs, and rules by which individuals produce and reproduce their material subsistence, organize time and space, and provide meaning to their social reality” (Thornton & Ocasio, 1999). Although definitions and approaches to institutional logics do change, the underlying “meta‐theory” or concept is that the behaviour of individuals and organizations cannot be fully understood if it is not located in the “social and institutional context” in which it occurs (Thornton & Ocasio, 2008).

Institutional logics have been illustrated to influence the spread and adoption of new practices in the publishing, banking and architecture industries (Thornton & Ocasio, 2008). Of particular interest to the current study is work on the role of institutional logics in explaining phases of diffusion and adoption. Recent work in this vein has made a convincing argument that institutional logics are essential for understanding phases of practice adoption in firms, with the logics adopted along with practices in early waves facilitating later practice adoption (Shiplov, Greve, & Rowley, 2010). Although Shiplov et al. (2010) address drivers of adoption of diffused practices in multiple waves of adoption where the institutional logics are the same, there has to date been no attempt to explain the effects of changing logics on diffusion practices. However, work on differing adoption of practices across the mutual fund industry based on variations in institutional logics does make an initial case for the role of logics in explaining variations in practice adoption (Lounsbury, 2007). Following on this nascent body of literature, the construct of institutional logics is used here to develop the understanding of diffusion and adaptation of incubation as both a business and policy practice in the current case.

In the case of business incubation, the dominant logic of the majority of urban incubators, which proliferated in Ontario in the early 2000s, appeared to be one of “entrepreneurship” and “innovation”. This was reflected in the vision statement of the U.S. based NBIA to “support innovative and dynamic entrepreneurship” in the small and medium‐sized enterprises sector (NBIA, 2010). As the predominant global industry association in the sector, the NBIA set the tone and provided the research for the majority of North American incubators being founded during this period. Statistics Canada, in a 2005 review of incubation practices in Canada, uses self‐report surveys from incubator management and indicates a slightly higher focus on job creation, but “technology commercialization” is a key objective of the incubators surveyed (Statistics Canada, 2005).

The dominance of this innovation and entrepreneurship logic is likewise evident on the websites of the major urban incubators themselves. The Toronto based MaRS Discovery District incubator states that its mission is to “foster and promote Canadian innovation” (MaRS Discovery District, 2011). Similarly, the Markham Innovation Synergy Centre states that its focus is “accelerating the growth and development of enterprises” (ISCM, 2011). This logic is supported by the fact that the primary supporting government agencies for many of these incubators are the National Research Council and the Ontario Ministry of Research and Innovation (ISCM, 2011). This dominant institutional logic proved extremely popular among both government and business policy makers and led to the rapid expansion and diffusion of the practice of incubation, as a policy tool for growth and innovation, in urban areas across the province. This rapid expansion occurred even in the absence of solid evidence that incubators were a successful policy measure (Hackett & Dilts, 2004).

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Despite this popularity and widespread interest in policy and business circles, the practice of business incubation did not spread to the rural communities in the province during this phase of diffusion. The diffusion literature is by no means new to questions of why practices diffuse in different phases. Early work on TQM practices differentiated between early and late adopters (Westphal, Gulati, & Shortell, 1997), while work on policy diffusion has looked to differences in take‐up between states which were more or less exposed to competitors, foreign markets, and traditions (Weber, Davis, & Lounsbury, 2009). Organizations have also been found to adopt practices or policies more rapidly when those with which they have the most contact do so. This has been illustrated in the case of board interlocks predicting adoption of the Poison Pill (Davis, 1991) and in trade relations and common colonial backgrounds predicting the adoption of stock exchanges in the post World War II era (Weber, Davis, & Lounsbury, 2009), to name just two.

However, in the current case, the qualitative findings indicate that something more may have been at play in determining the urban versus rural phases of incubation adoption. First, the rural communities in question were in many cases much closer geographically to the urban centres in Ontario than the urban centres were to one another. Second, both rural and urban municipalities and economic development policy‐makers are funded and regulated by the same provincial authorities, attend similar conferences, and have access to similar information. These similarities would indicate that the rural policymakers were aware of both the concept of incubation as well as the policy “norms” in these circles. Yet, regardless, they did not follow the urban lead despite the effects of such isomorphic pressures (DiMaggio & Powell, 1983), as the current diffusion literature would suggest (Davis, 1991; Westphal, Gulati, & Shortell, 1997).

Instead, rural communities at this stage were dominated by an entirely different set of issues. The populations were greying and youth were leaving farming and traditional rural occupations in droves for the city, not staying home to try their hand at local entrepreneurship. Businesses were predominately small family‐owned operations focused on providing necessary basic services and goods, not new innovations. Overall, local economies were looking simply to retain and maintain the populations and businesses they had and business and economic ‘growth’ seemed to be a distant dream. Despite the fact that they desperately needed economic development assistance, the dominant practice in the development policy field at the time – incubation – was not looked to as a practical or relevant solution. In this environment, it appears that the practice of incubation with “innovation and entrepreneurship” as the dominant institutional logic, was not seen as a viable “fit” for rural communities.

Yet despite this apparent lack of fit between the idea of the rapidly diffusing economic development practice of “incubation” and the reality of the situation in rural Ontario, five years later the practice of incubation was rapidly adopted across rural Ontario in a second wave of diffusion. Turning back to the literature on adaptation of disused practices we might expect that the practice itself has been changed or “translated” (Zilber, 2006) to better “fit” (Ansari, Fiss, & Zajac, 2010) the institutional, organizational and political context. However, while the structure of the incubation model is somewhat different in rural communities than in urban centres these differences, especially considering the wide variation in the concept of diffusion across North America (Hackett & Dilts, 2004) and even between the major Ontario incubators, seems hardly fundamental. In fact, had the rural Ontario communities sought to find a more viable incubation structure with better fit for the local needs, a simple search of the multitude of resource offered by the NBIA would have offered numerous alternatives.

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The fact that the current literature on the adaptation of the practice itself does not supply sufficient explanation for the current case does not negate the applicability of the body of adaptation and variation literature itself. Instead, the current case suggests that it was not the practice of incubation that was adapted but the institutional logics to which it related. The case and data suggest that institutional logics used in the current rural incubator start‐ups are much more based on “community”, “place” and “community renewal” than on the more prevalent and traditional logics of “innovation and entrepreneurship”. It was only when the idea of incubation became associated with the possibility for redefining the local community, promoting traditional values, and “saving” the towns themselves that it was seen to fit the rural “social reality” (Thornton & Ocasio, 1999) and became relevant. In effect, the adaptation in logics facilitated the change in adoption rates and allowed the normative and isomorphic pressures for diffusion to take their course.

Recent work by Lounsbury and others (Shiplov, Greve, & Rowley, 2010) has already argued that dominant institutional logics will be a factor in whether a practice is adopted or not. In the next section the role of “place” is developed as both one of those logics and one of the mechanisms which influence practice translation and adaptation – one which has been previously virtually neglected in the organization theory and diffusion literature. Place is therefore suggested as an important factor in framing logics, and that logics themselves are important for understanding phases of diffusion – not simply waves of diffusion within an organization as has been previously posited (Shiplov, Greve, & Rowley, 2010).

The Role of ‘Place’

Although the current literature provides a theoretical basis for understanding stages of adoption based on temporal, cultural or efficiency arguments in individual communities, there is no reasonable explanation for the urban‐rural divide and delay in the diffusion of business incubation practices in the current literature. The case illustrates that what all of these rural communities had in common was a transformation of institutional logics from “innovation” to more local and community‐based concerns.

The role of geography has been used to explain differing adoption and diffusion of practices. In comparing differing institutional logics in the mutual fund industry in the business centres of New York and Boston, Lounsbury (2007) has shown that geographical communities can also be a source of the institutionalization of logics. Similarly, although not arguing for institutional logics outright, Weber illustrates how existing colonial institutional logics eased the introduction of Western stock exchanges to developing nations (Weber, Davis, & Lounsbury, 2009). However, where these two bodies of work show that geographical heterogeneity can be a source of differing logics, the current case illustrates that geography and community, or the combined ‘sense of place’, was the defining logic itself.

A sense of place is an important aspect of many urban and rural locations but has been specifically linked to temporal aspects of residency and to ancestral links to the location (Hay, 1998). In a study of several disparate communities on New Zealand’s Banks Peninsula, Hay (1998) finds that this sense of place is strongest among those who have ancestral attachments (individuals with roots) to a location, and stronger still among those with cultural attachment (roots plus spiritual or cultural ties), illuminating the deep emotional and spiritual bonds individuals have with places. Therefore, such antecedents of a sense of place are more likely to be found in rural communities where both roots and

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cultural ties are strengthened with relatively stable and elderly populations, rather than in more transient and youthful urban communities.

In the current case we see the prevalence of this sense of community and place in the rationale for adopting the practice of business incubation by government, management, tenants and communities alike. For example, the website for The Headland incubator in Picton Ontario lists “community revitalization”, development of local industry, and working with community colleges among its primary goals (The Headland, 2011). Other policy makers have pointed to the fact that their incubators “create a new opportunity for the community” and allow youth to remain in or return to the community as primary drivers of their investment in incubation.

In fact, the power of this sense of place, as both a connection which people have with the physical location of their communities and with the social aspects of community, can be used as a powerful political and social lever (Agnew & Duncan, 1989). The sense of place has, like institutional logics, also been seen as one of the important links between micro individual actions and macro institutional and organizational behaviour. As prominent place theorists Agnew and Duncan describe, “place…serves as a constantly re‐energized repository of socially and politically relevant traditions and identity which serves to mediate between the everyday lives of individuals on the one hand and the…institutions which constrain and enable those lives, on the other ” (Agnew & Duncan, 1989, p. 7).

The fact that this sense of place is so emotionally powerful, and is particularly strong in these rural communities, makes it a valuable and viable tool to be used to gain legitimacy and support for new ideas by linking them to the meaning laden concept of place. Aside from the powerful role of institutional logics themselves in facilitating legitimacy and acceptance of new practices (Shiplov, Greve, & Rowley, 2010; Lounsbury, 2007), the concept of place has also been historically linked to legitimacy in the humanistic geography literature. Creswell points to a strong link between “place and assumptions about normative behaviour” whereby people and practices are deemed to be either “in‐place” or “out‐of‐place” (Creswell, 2004, p. 103). For our current purposes the interesting connection here is between the role of place as a normative concept and the organization theory traditions of legitimacy and isomorphism, which similarly stress the importance of normative actions.

It seems apparent that communities and local governments utilized the logic of place to successfully introduce a previously ‘foreign’ practice to rural communities. We now turn briefly to the role of change agents as a third mechanism in understanding the sociocultural context in which the diffusion of rural incubation occurred.

The Role of Change Agents

The role of agents and individual change agents has been recently suggested by various authors as an important area of future research in the diffusion and adaptation literature, and has been conspicuous by its absence to date (Ansari, Fiss, & Zajac, 2010; Zilber, 2006). The institutional logics literature also provides a link between micro level “individual agency and cognition” and macro level “socially constructed institutional practices and rule structures” (Thornton & Ocasio, 2008, p. 101) – a link which is frequently missing in the organization theory literature.

The current case illustrates that many of the rural communities that adopted incubators in the initial 2010 stage of start‐ups had influential and highly active business and policy leaders to credit. Although

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institutional and organizational support from the community, town council, regional development bodies, and the business community were all required at later stages of the process of funding and opening an incubator, the initial introduction of the ideas was often attributed to one or two key individuals. These agents appear to have utilized strong contacts and networks externally to access new ideas on incubation, and combined these with powerful personal networks within the community. These external and internal social ties allowed agents to both access new ideas from outside stakeholders and to introduce these ideas to the community.

However, despite the agents’ role and prominence in the community, they were not able to adapt and introduce the practice of innovation using the current logics of innovation. Instead, these agents were instrumental in changing and adapting the institutional logics to fit the local reality of community and place, and thus gain legitimacy for the idea of incubation.

Conclusion

The framework identified here seeks to expand the theoretical understanding of the factors that contribute to practice diffusion and how adaptation occurs at the local level. This paper argues that in a community that has a strong sense of tradition and rootedness the ‘sense of place’ is a key concept in gaining acceptance of new ideas and understanding the adaptations to diffused processes and policies that occur. This sense of place has previously been neglected in the organization theory, diffusion and adaptation literature.

Specifically, this paper uses the illustrative case of the diffusion of incubation practices across Ontario, and asks why widespread urban diffusion took over half a decade to reach the nearby rural communities of the province. It has been posited that the delay was a result of the fact that the predominant institutional logics of incubation, namely “innovation and entrepreneurship” did not fit the local context (Ansari, Fiss, & Zajac, 2010). It was only when local communities were able to adapt the underlying logic of the practice that incubation began to spread rapidly in rural population centres. Through community groups, government and instrumental change agents the institutional logic of innovation was changed to match the dominant social reality (Thornton & Ocasio, 1999) of rural Ontario, which was a deep‐seeded attachment to the importance of community, traditions, rootedness, and a sense of place. As institutional logics were adapted incubators became first and foremost a vehicle for “community regeneration” rather than “innovation”, and were rapidly accepted and diffused.

This paper contributes to literature in several areas. First, it expands the diffusion literature by adding to the nascent but growing body of research on adaptation of business practices. Although previous research has posited many factors which can explain and predict adaptations of practices, the role of location, rootedness, and community – as summarized by the literature on place – has not yet been among them. Given its long and powerful history in the geography literature, organization theory no doubt has much more to learn from theories of place. Second, by linking the humanistic geography and institutional theory literatures, this framework also supplements the geography research on the importance of place, expanding its influence from simply politics and social dynamics (Agnew, 1987) to policy, business and strategic decision‐making. Third, this paper supplements the policy literature by expanding the understanding of the processes by which local roots may impact policy implementation, not simply across state (Lee, 2009) or national boundaries (Weber, Davis, & Lounsbury, 2009) but also

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across what appear to be very narrow, or almost non‐existent, geographic boundaries within the same region.

However, the analysis here has several limitations which have not been fully explored in the current study. Foremost among these is the fact that the current analysis has focused on the diffusion of a government policy practice. While much of the diffusion literature seems to move interchangeably (Lee, 2009; Weber, Davis, & Lounsbury, 2009) between policy and business practice diffusion, the reality is that there may be distinct differences between the two and the mechanisms that underlie each. Therefore, while the current study has developed a framework based on policy practices that it is hoped may also provide insight to the diffusion of business practices, this is a feasible boundary condition and should be further studied. A second limitation is the fact that the rural communities in question are all located in Eastern Ontario, regions with a proud and well‐documented tradition of Loyalist settlement and a vital role in the founding of Canada. In addition, many of these communities have also experienced a recent artistic and agri‐tourism resurgence, bringing these historic ties to the forefront of the local consciousness. Therefore, it is not clear whether the important ties to community and place which were identified here will be found across other rural communities with less of a sense of local history. Third, the current study provides only a limited sampling of relevant actors and archival data. Further research is required to expand the interview sample size, access a broader cross‐section of actors and communities, and more rigorously test these findings.

The current research suggests several interesting directions for further developing our understanding of how practices diffuse and the role of institutional logics and place in adaptation. First and foremost, the current framework has been developed based on a case study that occurred primarily in the policy and public/not‐for‐profit spheres. Although firm analogies have been successfully used to explain incubation models (Aaboen, 2009), organization type has been shown to have an important role in the type of response organizations will have to institutional pressures (Suddaby, Elsbach, Greenwood, Meyer, & Zilber, 2010). It will therefore be imperative to test whether the importance of place, and the legitimacy conferring benefits it might have, translate to private organizations and corporations operating in smaller communities or other locations with a strong sense of rootedness. Anecdotal evidence would suggest that this does apply as we look to the ability of corporations such as HSBC, Coca‐Cola or Visa to carefully tailor advertising to match the sense of place and rootedness of the local community.

Second, although the current framework does propose a role for change agents in the process of adapting institutional logics and gaining legitimacy for practices in the local community, future research should expand the understanding of the role of such actors (Agnew, 1987; Zilber, 2006). Of particular interest in this regard will be asking whether the institutional logic of place was itself diffused between communities by change agents, or whether this adaptation of the diffused logics occurred virtually simultaneously across communities given pre‐existing isomorphic pressures to adopt incubation and the vital importance of place in rural life across communities.

Third, as explained previously, the current case was analyzed in light of the diffusion and adaptation literature based on the assumption that incubation was a policy ‘practice’ and therefore followed along the lines of previous work on policy diffusion (Weber, Davis, & Lounsbury, 2009; Lee, 2009). However, the work on diffusion in organizations takes a narrower view of the term ‘practice’. Taking

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this view, looking at the spread of rural incubation from the perspective of the literature on organizational founding may also offer interesting insights, as may the literature on framing.

Finally, the current study has focused only on the importance of place in explaining variations in logics and practice adoption across very narrow geographical distances. As globalization continues, the role of place in understanding diffusion of policy and business practices across national borders is likely to bring additional insights to the existing diffusion literature (Creswell, 2004).

Introducing the important geographical concept of place to the organization theory literature has offered some advancement to the current literature on diffusion, adaptation, and institutional logics. Similarly, bringing the solid body of research on diffusion to the place literature can only enhance sharing of insights across the social sciences. Further, this research was intended to answer important questions posed by practitioners in their attempts to introduce new policy projects to rural regions. It is therefore hoped that any theoretical contribution made also offers some insight to the important practitioner work on economic development and rural economic regeneration.

Geographers see connections with place and rootedness to local traditions becoming more rather than less salient in the years ahead. Even as communities become globalized and technology appears to reduce geographical boundaries, individuals are searching out roots, ties and connections like never before – a need that a sense of place often fills (Creswell, 2004). Continuing to draw on the concept of place as a socially and politically powerful social construction, and remembering that individuals and communities have a deep sense of connectedness with their locales, will no doubt assist business and policy‐makers in adapting and diffusing practices to diverse communities. For, if nothing else, the existing adaptation literature and the case of business incubation in Ontario demonstrate that practice certainly does not “fit” (Ansari, Fiss, & Zajac, 2010) every situation or organization and that changes and translation (Zilber, 2006) of concepts are key to spreading new ideas and innovations. Therefore, among the factors that must be considered in moving ideas form “here to there” (Ansari, Fiss, & Zajac, 2010) are the identity and meaning which place represents for the local community, and how the attachment and meanings associated with place will effect adoption. Incorporating local meanings and values associated with place into new practices can facilitate adoption and enhance legitimacy. Or, as the old saying so succinctly states, “When in Rome do as the Romans do”.

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Appendix A – Sample Interview Questions

A) Private Firm

1. Rapport‐establishing questions:

Standard conversational openers and icebreakers regarding introductions, weather etc.

An explanation of how the interview process will proceed (interview, questions, note taking etc.) and asking “Do you have any questions about the process?

2. A “grand tour” question will be used to start the discussion:

The grand tour question will be a broad based question used to frame the interview boundaries and to guide the interview.

For example: “Tell me about your operation and what factors drew you to locate in (town/region)?

3. Essential questions:

What factors led you to locate your operations in (town/region)??

Were you aware of the business incubator before looking at (town/region)? as a possible location for your business?

Would you have located in (town/region)? without local government/CFDC support?

Would you have located in (town/region)? if this incubator had not been available?

Has locating in (town/region)? and/or the incubator been of value to your business?

How has being located in a rural community impacted your business?

Tell me about your interactions and relations with the local economic development community

Tell me about your interactions and relations with other local businesses, specifically the businesses co‐located in the incubator

How does being located so closely to other similar businesses effect your business?

How do you feel your businesses growth would have been different if you had not located in the incubator?

4. Prompts:

During the interview, the researcher will pick up on the responses given by the participant and prompt further discussions by using prompt questions such as:

Can you tell me more about that?

So that’s important because…

What did you think about that?

Can you give me an example?

You mentioned ___________________. Can you please explain to me what you meant?

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B) Government/Development Organizations:

1. Rapport‐establishing questions:

Standard conversational openers and icebreakers regarding introductions, weather etc.

An explanation of how the interview process will proceed (interview, questions, note taking etc.) and asking “Do you have any questions about the process?

2. A “grand tour” question will be used to start the discussion:

The grand tour question will be a broad based question used to frame the interview boundaries and to guide the interview.

For example: “Tell me about your operation and how you are involved in the economic development of the region?”

3. Essential questions:

What factors led you to introduce the idea of incubators to (town/region)?

Had you worked with or studied urban business incubators?

How, if at all, has your approach been different in a rural setting than that taken by urban incubators?

How did you select the areas of specialty for the incubators?

How did you select the firms and/or how did you find firms to participate?

Would these firms have located in (town/region)? without the incubator?

What other programs are in place within, or outside, of the incubator that make this appealing to businesses?

Do you believe the incubator has been a success a) for businesses, b) for the community? And Why?

What would you do differently in future?

What lessons do you think other communities could learn from (town/region)?’s incubators?

Was there a reason (town/region)? was more appealing for these businesses, or suitable for incubation, than other rural communities?

Do you think these businesses will stay in the community once they become successful?

What do you see as being the overall impact on the community?

How does this program rank among, or compare with, other economic development tools available to you?

4. Prompts:

During the interview, the researcher will pick up on the responses given by the participant and prompt further discussions by using prompt questions such as:

Can you tell me more about that?

So that’s important because…

What did you think about that?

Can you give me an example?

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You mentioned ___________________. Can you please explain to me what you meant?

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Appendix B – Summary of Key Survey Findings

This rural incubation survey was administered in May 2011 to 259 Canadian Community Future Development Corporations (CFDCs) across Canada regarding incubator planning and activity in their regions. The survey was spearheaded by Northumberland County (John Hayden), Renfrew County (Keanan Hunt), and Elgin County (John Regan) CFDC staff with input and assistance from the primary investigator of this project, Wren Montgomery. Only a sample of results have been included in the current paper as a reference, no qualitative analysis has been performed.

Surveysize: 259CFDCS

Responserate: 36(14%)

ResponseratefromCFDCswithexistingincubators: 14(5.5%)

AVERAGE RURAL CANADIAN INCUBATOR

Size (sq. ft) 7,100

Legal Status Most often run directly by a CFDC, or separate NFP

Years in operation 1

Initial funding $275,000

Annual Operating Cost $38,000 (64% are financially sustainable)

Partnerships Federal Government, Municipality, other NFPs, building owner or private sector partner

Strategic Focus None

Special Equipment None

Lease rates ($/sq. ft): $5.50 (no graduated lease rate schedule)

Current occupancy rate on average 66%

CFDC involvement High ‐ providing staff resources (direct management) or committee members for incubator board of directors or advisory committee

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Average amount of time to move from planning to implementation

1.5 years

*Only two survey respondents out of fourteen indicated that the incubator in their area had been running for more than 5 years. Most are a recent phenomenon (2010).

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Appendix C – List of Can

adian In

cubators and Social In

novation Spaces

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Blay: Yes, agreed; agreed. But the dark night …kryten.mm.rpi.edu/PRES/MURIBOSTON121814/MURI_Slides_SB_JL_1… · Blay: Yes, agreed; agreed. ! But the dark night inexorably ... Mumbai

Blay Et Al. (AJPT, 2011)

Ecosystem Services and · Ecosystem Services and California’s Working Landscapes Market Mechanisms to Revitalize Rural Economies By Daniel O’Connell, Ph.D., and Adam Livingston

REVITalize Bridge Design