Exploring Opportunities for Technological Innovation and Reconfiguration in the Local Food Industry

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Exploring Opportunities for Technological Innovation

and Reconfiguration in the Local Food Sector

A Thesis Submitted to the Faculty of the Design Management Department

in Partial Fulfillment of the Requirements for the

Degree of Master of Fine Arts

By

Dustin Larimer

Savannah, GA

July, 2011


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Prologue

My journey has taken me through many life-changing adventures and challenges, over many

miles and with enough uncertainty to tank the NYSE (again). Through it all I have quietly

carried a belief that in return for the incredible opportunities I have enjoyed, I must find a way to

apply what Ive learned to make a positive contribution to the world around me. Moving the ball

forward is what inspires me to act; it is why I am here.

Through my studies I have learned how to analyze, deconstruct and reframe complex

design problems to discover original, innovative insights and opportunities. When I first began

the Design Management program, I was asked to explain what I thought design was about, to

which I answered Design is about solving problems. If asked again, today, I would answer that

Design is about creating the conditions for people to solve their own problems and improve their

own particular circumstance. Solving problems forpeople only seems to create new problems.

In my previous career as a web technologist I developed a strong appreciation for the

potential web-based frameworks have created for improving quality of life. The best frameworks

are simply tools that put prohibitive complexity to order the epitome of elegance. A well-

designed tool can enable new types of behavior or displace unfavorable ones. It can bring

people together, make tasks more efficient, or sometimes even create entirely new opportunities

that no one not even the designer previously thought possible. I believe such a

technological innovation has the potential to transform the flow of one of our most critical

resources: healthy food.


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Table of Contents

List of Figures 1

List of Tables 4

Abstract 5

Chapter 1: Introduction 6

Another Record Year 7Designing Flexibility Out of the System 8The Problem with Alternatives 13An Opportunity 20

Chapter 2: Literature Review 22

Socio-economic Foundation 23A Well-Coordinated Revolution 27

Chapter 3: Research Methodology 31

Research Design 31Phase 1: Field Study Preparation 33Phase 2: Field Research 38Phase 3: Data Analysis Process & Procedures 42Phase 4: Define an Opportunity Space & Design Criteria 44Research Limitations 44

Chapter 4: Analysis & Findings 45

Identifying Thought-Leaders within the Local Independent Food Network 46


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Field Research: Trends and Patterns 58Hobbyists Becoming Professionals 59Full-time Professionals Moving Forward 67

Chapter 5: Design Concept Development 78

Design Criteria: Stories about the Future 78Concept Exploration 81The Design Solution: NeighborFarms 97

Chapter 6: Conclusions & Directions for Future Research 103

Value Proposition of the Design Solution 105Directions for Future Research 105

Appendices 106

Appendix A: Interview Protocol (90-120 minutes) 106Appendix B: Informed Consent 108Appendix C: Producer Startword List 109Appendix D: Consumer Questionnaire 110Appendix E: Cultural Model of a hobbyist, a part-time pro, and a full-time pro 113Appendix F: Growth trajectory from hobbyists to full-time professional status 114

Glossary 115

Works Cited 118

About the Author 128


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List of Figures

Figure 1.1Customer-facing portion of the Business Model Canvas 15

Figure 1.2Three-dimensional Producer Matrix 18

Figure 1.3Environmental Threats, part 1 19

Figure 1.3Environmental Threats, part 2 20

Figure 3.1Illustrated research design 32

Figure 3.2Project scope 35

Figure 3.3Sortable business attribute cards 39

Figure 3.4Annual timeline template 40

Figure 3.5Affinity Process Illustration 42

Figure 3.6Business Model Canvas 43

Figure 4.1Communication View for local organic near:31401 and localorganic near:30458

47

Figure 4.2Communication View of farmer market near:31401 and farmermarket near:30458

48

Figure 4.3Communication View of local organic near:31401, local organicnear:30458, farmer market near:31401 and farmer market near:30458.

50

Figure 4.4Communication View for forsyth farmers market and statesborofarmers market

51

Figure 4.5Resulting producer list, sorted and numbered by overall frequency ofuse within filtered content.

52

Figure 4.6Chart of responses for How were you first introduced to thisproducer?

56

Figure 4.7Chart of responses for How many of your friends also shop fromthis producer? and How many of your friends shop at the same market(s)?

56

Figure 4.8Word cloud generated with responses to Which other producers doyou buy from frequently, and what do you value most about them?

57

Figure 4.9Stacks of notecards resulting from interview transcripts 58

Figure 4.10Clustering notecards into emergent themes and topics to identifypatterns

59

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Figure 4.11Cultural Model of Hunter Cattle Company, Reads Bees andGratitude Gardens

60

Figure 4.12Growth trajectory from hobbyist to full-time professional 61

Figure 4.13Three sample timeline worksheets completed during interviews

Hope Grows Farm, Hunter Cattle Company, and Reads Bees

65

Figure 4.14Illustrated mashup of timeline worksheets completed duringinterviews Hope Grows Farm, Hunter Cattle Company, and Reads Bees

66

Figure 4.15Clustering notecards into emergent themes and topics to identifypatterns

68

Figure 4.16Cultural Model mapped to the 4 Ps of Marketing: Product,Promotion, Place, Price

69

Figure 4.17Business Model Canvas for individual growers participating in

farmersmarkets

71

Figure 4.18Business Model Canvas for individual growers supplying wholesaledistributors

74

Figure 4.19Business Model Canvas for a collaborative growers networkproviding food boxes

75

Figure 5.1Early concept sketches articulating relationships of exchange 82

Figure 5.2The many relationships and exchange models behind HeritageOrganic Farms

82

Figure 5.3Early concept sketches exploring potential service models 83

Figure 5.4Co-sketch session with Arianne from Hope Grows Farm 84

Figure 5.5Illustration of the collaborative food box model, regularly distributedto customers at pre-arranged locations

85

Figure 5.6Illustrated flow chart of the web service 86

Figure 5.7Exploring an expanding conceptual space 87

Figure 5.8NeighborFarms logo 88

Figure 5.9Evolving interface of NeighborFarms: wireframes, style and layoutiterations

88

Figure 5.10Evolving design of NeighborFarms homepage and dashboard 89

Figure 5.11NeighborFarms homepage featuring a large map for geo-browsing 89

Figure 5.12Producer dashboard view displaying an individual producers bulkinventory and associated project allocations

90


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Figure 5.13NeighborFarms dashboard where teams of producers cancollaborate on projects

90

Figure 5.14Producer dashboard view displaying active and past invoices 92

Figure 5.15Producer dashboard view displaying a map of available projects to

join

93

Figure 5.16Concept illustration, printed and shared at a farmers market in SanAntonio

94

Figure 5.17Website demonstration, printed and shared at a farmers market inSan Antonio

94

Figure 5.18Paper prototype of mobile app demonstrated at a farmers marketin San Antonio

95

Figure 5.19Scenes from the Pearl Brewery Farmers Market in San Antonio 96

Figure 5.20NeighborFarms homepage 97

Figure 5.21NeighborFarms invoice dashboard page 98

Figure 5.22NeighborFarms inventory dashboard page 99

Figure 5.23NeighborFarms projects dashboard page 100

Figure 5.24NeighborFarms projects dashboard page where producers can findprojects to join

101

Figure 5.25NeighborFarms account settings dashboard page 102


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List of Tables

Table 3.1Four-phase Project Timeline 33

Table 4.1Actors listed by betweenness centrality for local organic near:31401

and local organic near:30458

47

Table 4.2Actors listed by betweenness centrality for farmer market near:31401 and farmer market near:30458

49

Table 4.3Actors listed by betweenness centrality for local organic near:31401, local organic near:30458, farmer market near:31401 and farmermarket near:30458

5051

Table 4.4Interviewee types, times and locations 58

Table 4.5Data collected from Attributes of Success exercise 63

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Abstract

Exploring Opportunities for Technological Innovation

and Reconfiguration in the Local Food Sector

Dustin Larimer

July, 2011

This study deconstructs the market mechanics and social dynamics of independent food

networks and explores new opportunities for technological innovation and reconfiguration. The

findings suggest that the independent food movement, as a system of commerce, largely defies

conventional market logic supporting modern industrial food production. What to outsiders may

look like a values-conscious commodities business is actually a rich cascade of dense social

networks, woven together around a mutual determination to thrive in defiance of the ills of an

unsustainable, global calorie-making apparatus. However, small-scale producers cannot be

sustainable if they are not also profitable.

The emergence of an effectively decentralized, resilient food system can be accelerated

by introducing new economic, logistic, and regulatory tools that enhance producer viability while

reinforcing the values that lie at the very heart of the independent food movement itself. Such

tools must be designed by and for dynamic, loosely-coupled communities which are defined by

shared values and independence; they must be effective because ofthese communities' very

nature, rather than in spite of it.

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Chapter 1: Introduction

This project deconstructs the market mechanics and social network dynamics of independent

food systems and explores new opportunities for technological innovation and reconfiguration.

The independent food movement, as a system of commerce, largely defies conventional market

logic supporting modern industrial food production. What to outsiders may look like a values-

conscious commodities business is actually a rich cascade of dense social networks, woven

together around a mutual determination to thrive in defiance of the ills of an ecologically and

socially abusive, global calorie-making apparatus. For some independent producers, food

production is as much a means of protest as it is a means of making a living. For others it is not

just about food, it is about the people that food weaves together; it is about community.

As our civilization ventures forward into an increasingly uncertain future, many influential

institutions the United Nations, among them are calling for decentralized, ecologically

restorative agriculture, or agroecology, that has so far proven to significantly increase production

yields, repair environmental damage and capture massive quantities of carbon from the

atmosphere. Such a model is already being employed by a growing number of independent

food producers across the United States and around the world. Small independent producers

also benefit from these ecologically-intensive production methods. Increased diversity means

not only greater variety for customers but also greater resiliency in the face of single-product

market saturation from large-volume competitors.

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As well-intentioned and environmentally revitalizing as the independent food movement

may be it exists in conflict with many of the expectations and assumptions of the existing

conventional production and consumption paradigms. The emergence of an effectively

decentralized, resilient food system can be accelerated by introducing new economic, logistic,

and regulatory tools that enhance producer viability while reinforcing the values that lie at the

very heart of the movement itself. Such tools must be designed by and for dynamic, loosely-

coupled communities which are defined by shared values and independence; they must be

effective because ofthese communities very nature, rather than in spite of it.

Another Record Year

During the summer of 2010 the jet stream over Eurasia made a sharp kink. Hot, dry air was

drawn up from the Sahara desert northward into the western plains of Russia, diverting heavy

rain systems southward directly into Pakistan's annual summer monsoon (Masters, 2010).

Sporadic weather anomalies are not unheard of, but what is especially unusual about this event

is what the jet stream did next: nothing. It simply froze in place for well over a month

unleashing a catastrophic deluge that submerged nearly 1/5 of Pakistan's land area (CNN Wire

Staff, 2010), affecting nearly 20 million people and inflicting massive damages on the country's

wheat harvest.

A few weeks later record high temperatures and a devastating drought ignited hundreds

of wildfires across Russia's western plains. The fires lasted for nearly two months, eventually

leading the country to ban exports of wheat for the year (Gronholt-pedersen, 2010). Wheat

prices at the Chicago Board of Trade soared, sparking food riots in Mozambique and

heightening anxiety of rising food prices around the globe (Javier, 2010). By late October the

north-central United States was also experiencing the effects of a supercharged jet stream. A

massive storm churning across the Midwest produced the lowest atmospheric pressure

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readings ever recorded for a land-based storm (Spotts, 2010). Winds as strong as 90 mph,

heavy rains, and dozens of tornadoes knocked out power for nearly a quarter of a million people

(MSNBC, 2010). Waves exceeding twenty-six feet in height were recorded on Lake Superior

just past noon on October 27 (Environment Canada, 2010).

These are only a few incidents from what has become an all-around record-breaking

year of weather events. In March of 2010, southwestern China experienced an 80 percent drop

in rainfall, slashing projected summer grain yields and creating water shortages for over 50

million people (AsiaNews, 2010). While it is tempting to correlate the recent outbreak of

destructive weather with anthropogenic climate change, such a connection is not necessary to

understand how the unpredictability of the weather has always been the nemesis of mankind's

agricultural ambition. Rain falls too soon, too late, too much, too little, or sometimes not at all,

crops fail and people starve. It is also not difficult to imagine what kind of scenarios may

emerge if global warming is in fact deteriorating conditions for agriculture: greater intensity at

the extremes; heavier rains and longer droughts, hotter summers and colder winters. A greater

frequency of "record-breaking everything," means smaller yields, higher production costs, higher

consumer prices, and less certainty that food will be available for anyone at any given time.

Designing Flexibility Out of the System

The fact that so much uncertainty continues to haunt modern agriculture is not for a lack of effort

or innovation. Abundant fossil fuels, foreign market liberalization, and the technological

revolutions of the last century have together rapidly transformed food production into a marvel of

hyper-efficiency. What was once a localized political economy of stability is now a globally

rationalized, centrally-coordinated war against uncertainty, marching to a logic of publicly-

subsidized overproduction.

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For decades, the key strategy to fighting this war has been to overpower the odds with

the brute force of energy-intensive biochemical and mechanical intervention. More energy in

means more energy out. Producing far more calories than the market demands forces prices so

low that food is affordable and readily available to (almost) everyone. In the United States,

when prices fall low enough, farmers are compensated for the losses through various subsidy

programs. Minor production shortages are then (hopefully) absorbed by the sheer scale of the

system, and price fluctuations are often absorbed by retailers to avoid losing customers to

competitors.

Producers in this global production strategy must perpetually increase efficiency to stay

competitive, either by innovating away from costs or consolidating with other operations to shed

redundancy, increase volume and amplify savings. This model has resulted in a handful of

massive, tightly coupled market participants at every link in the value chain. For example, an

oligopoly of half a dozen transnational corporations oversees the global seed industry (Howard,

1274). Today producers have fewer upstream input options, fewer downstream market access

options, and virtually no leverage over the terms of exchange after harvest. Their only option is

to keep chasing higher yields and to try to avoid going out of business like so many of their

neighbors.

The rationalization of modern agriculture has dealt a critical blow to the biodiversity of

4.9 billion acres of the Earths surface (FAOSTAT, 2008). Three quarters of the worlds food

supply is derived from just 7 of 200,000 plant species on Earth, with just three of those species

corn, wheat, and rice supplying half of all calories and proteins (Hawken/Lovins, 194). In the

United States, nearly 70% of farmland is dedicated to just three crop species: corn, soybeans

and wheat (USDA NASS, June 2010). Such large populations of a single species are extremely

vulnerable to attack by opportunistic pests, parasites, weeds and disease, and are incapable of

surviving without the support of excessive petroleum-based pesticides and herbicides. Not

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surprisingly, these chemicals must be updated regularly and replaced with more potent

successors, to which insects will inevitably adapt to resist (Hawken/Lovins, 196). The corn and

wheat fields that supposedly feed the world have essentially become battlefields in a chemical

arms race between the Ag sciences six decades of trial and error and insects millions of years

spent perfecting rapid adaption. According to Professor David Pimentel from the Cornell

University, approximately 2/5 of the world's crops are lost in the field to disease, insects and

weeds (Hawken/Lovins, 195).

Conventional agriculture consumes 70% of all freshwater allocation on the planet (FAO

"Depletion of Fresh Water Resources). It takes 1,000 tons of water to produce a single ton of

grain, and since water used for crops in Russia is notwater used in Egypt, for example, around

980 billion tons of water are redistributed around the world every year (Roberts, 227-231).

Through this lens, top grain exporters like the United States, the European Union, India, and

Russia are also top water exporters as well.

The energy consumption of this system is also enormous. On average, every single

calorie of conventionally-produced food is backed by an average 10 calories of fossil fuel,

accounting for an estimated 20% of total energy consumption in the United States (Hawken/

Lovins, 192). Cheap oil lets food production and processing move to where they are most

efficiently operated, and food consumption to where it is most financially rewarded. Geographic

proximity to the consumers whose very survival depends upon its daily availability is no longer a

concern. Affordable overnight cargo flights and low labor wages in developing nations have

made it incredibly cost-effective for vegetables to be grown in a different hemisphere than which

they are consumed. What was once a great step forward for efficiency now looks like a

potentially crippling dependency.

The connection between food, oil and just about everything else is best illustrated by a

series of events during the first half of 2008, when global oil production actually increased and

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demand decreased relative to prior quarters. Investors eager to get away from an imploding

real estate market flooded oil futures, food commodities and other raw materials (Frankel,

2008). A dual increase in the prices of oil and corn slammed the corn-based biofuel industry,

which consumes nearly 1/3 of the United States' annual corn harvest (Roberts, 325). The result

was an autocatalytic price hike for both commodities. A leaked report conducted by the World

Bank claimed biofuel production was inflating food prices by as much as 75% (Chakrabortty,

2008). Higher oil prices means higher prices for petroleum-based agricultural inputs, like

fertilizer and pesticides, as well as near-prohibitive fuel costs for transportation and machine

operation. Since about 1/3 of the global grain harvest is fed to livestock, meat prices also

increased dramatically (Roberts, 325). Commodity speculation seized the industry. Oil hit $100

per barrel on the first trading day of 2008 (Elliott, 2008), and by April skyrocketing food prices

spurred food riots in dozens of countries around the world. Shocked and unprepared,

governments scrambled to maintain order, sometimes by military intervention and severe anti-

hoarding laws (The Economist, 2008). By mid-summer oil hit $144 per barrel (Saefong, 2008).

Oil isn't the only fossil fuel that modern agriculture depends on. The other is natural gas,

which at the moment is a heavily-invested source of energy in a process that yields an even

more important element: nitrogen. Nitrogen plays a vital role in the molecular composition of all

living organisms. Without it, there simply cannot be life. There is a finite amount of nitrogen

available in a readily usable form, effectively capping the ecological carrying capacity of any

given ecosystem. This also limits the production potential for any given plot of land under

cultivation. Then in the early 20th century, a method for chemically deriving a synthetic

concentration of nitrogen was invented: the Haber-Bosch process (Encyclopdia Britannica

"Haber-Bosch process").

The Haber-Bosch process enabled affordable mass-production of ammonia (NH3) a

nitrogen-rich chemical compound that could literally be poured on the ground to increase fertility.

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While artificial fertilizers can greatly improve crop yields, they also devastate the innumerable

microscopic organisms that generate and support the soil that crops need to survive. As these

tiny ecosystems collapse farmers must apply more and more nitrogen to maintain yields. Dead

soil is easily washed or blown away, as has an estimated 1/3 of the topsoil in the United States

since the beginning of the industrial agriculture era (Hawken/Lovins, 192). On a larger scale,

the UN FAO reported in July of 2008 that nearly 1.5 billion people worldwide people rely on

degraded land (FAO, 2008). According to conventional logic, the solution is to apply still more

chemical fertilizer currently more than 210 million tons every year ("Current World Fertilizer

Trends and Outlook to 2011/12" 16).

From the 1960s through the 1990s synthetic nitrogen fertilizer use skyrocketed by 645%,

along with powerful advances in irrigation and farm mechanization (Hawken/Lovins, 191).

During roughly this same period, global grain production increased by 300%, while the human

population grewby 240%. Mathematically, that should mean a 112.5% increase in available

calories for every man, woman and child on this planet (Roberts, 24). In reality, nearly a billion

people worldwide one in seven experience some degree of malnutrition, if not full-fledged

starvation (FAO, 2009), including over 50 million U.S. citizens who in 2009 were classified as

"food insecure" (Nord et al., 6). Equally alarming is that now an enormous percentage of the

global population is entirely dependent on continued artificial nitrogen synthesis, which in turn is

heavily dependent on natural gas (Roberts citing Vaclav Smil from the University of Manitoba,

21). It's also worth mentioning that new natural gas discoveries peaked in the 1970s.

As an exploding global population puts a greater strain on a limited resource base, the

sheer volume of 2010's crop failures has once again sent food prices soaring around the world.

Despite the best laid schemes of conventional wisdom, and decades and fortunes spent

innovating against nature, the modern food system is just as vulnerable as any before it. Only

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now, however, the survival of hundreds of millions of people all around the globe is contingent

on fair weather and endless fossil fuel reserves.

The Problem with Alternatives

Progress in the war against uncertainty has not come without significant economic, social and

environmental costs. Greater transparency of those consequences has fueled a resurgence of

support for alternative production methods most notably the organic and local food

movements, with the latter gaining greater momentum in recent years.

Organic production and handling criteria became federally standardized in 1990, when

the United States Department of Agriculture (USDA) established the Organic Foods Production

Act (OFPA) (Gold, 2007). As defined by the USDAs National Organic Standards Board, organic

agriculture is:

... an ecological production management system that promotes and enhancesbiodiversity, biological cycles and soil biological activity. It is based on minimal use of off-farm inputs and on management practices that restore, maintain and enhance ecologicalharmony.

While the organic food industry was estimated at a mere $1 billion the year the OFPA was

implemented, it weighed in at just over $20 billion in 2008 (Dimitri, iii, 1), and grew an additional

8 percent the following year during one of the worst financial disasters of our countrys history.

This incredible growth appears to have been driven almost exclusively by a previously

unclassified segment of consumers, cutting across consumers of many conventional attributes

of distinction income, ethnic background, family-size, etc. who base buying decisions on

values more important than price alone (Greene, 3-5).

The USDAs 2008 Organic Production Survey revealed that 74 percent of organic sales

distribution occurred within 500 miles of the farm, and 44 percent occurred within 100 miles

(USDA, National Agricultural Statistics Service, 2010), so any attempt at a distinction between

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local food production and organic is problematic. Such comparison implies certified vs.

uncertified within close geographic proximity to consumption, which is simply not accurate,

since many industry organizations have emerged to provide more robust or specialized quality

assurance criteria for specific markets like livestock and poultry. Many local, non-organic

producers also claim to practice the same production methods, but simply refuse to deal with

the time, expense and regulatory obstacles encountered during the certification process (USDA,

National Agricultural Statistics Service, 2010). Some producers invent new descriptors and

qualifiers for their production methods, others make no claim at all.

One particularly promising methodology gaining traction is sustainable agroecology, an

ecologically pro-generative, knowledge-intensive approach to reintegrating natural processes

and biodiversity with modern production practices to foster greater resilience and stability

(Pretty, 2-3). Many prominent institutions the United Nations among them are calling for

increased emphasis on such a model, which have so far proven to significantly increase crop

yields, repair environmental damage and transfer massive quantities of carbon from the

atmosphere back into the soil (Pretty, 3). And for small producers, increased diversity means

not only greater variety for customers but also greater resiliency in the face of such challenges

as single-product market saturation by large-volume competitors.

Sustainable agroecology known by many names is already being employed by a

growing number of growers across the United States and around the world. Its methods do not

fit squarely into any one category, but may be partially exhibited in practice by many producers

across categorical divides. Events like organic-only meetings, however, deny nearby

uncertified producers the opportunity to contribute to and learn from others strategies and

experiences an invaluable step toward fostering more creative and intelligent behavior

among market participants. Today there are literally thousands of groups around the country

that seek to educate the public about sustainable agroecology (Hawken, 174).

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Exclusive categories simply do not hold up in a domain flooded with so many shades of

grey, yet it is this characteristically independent nature that binds these producers together in

purpose. Unfortunately, this identity of independence also has the potential to farmers market

ideological polarity among producers with contrasting methodologies, such as certified vs.

uncertified. Therefore, it is far more productive in the scope of this projectto regard these

producers for what they have in common: they are all independent small business owners who

continuously face threats to their economic viability. Food production at any scale is chock-full

of uncertainty, but small-scale operations that sell directly to consumers assume many of the

same responsibilities that go with any retail business: developing a compelling offering, creating

relationships with prospective customer segments, and exchanging through the right channels

(Figure 1.1).

Figure 1.1. Customer-facing portion of the Business Model Canvas (Osterwalder, 28)

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Over the past two decades the boom of interest in alternative food sources has created

the opportunity for a myriad of hobbyists to consider going pro. Not all have taken the leap,

however. These producers, who are not necessarily concerned with consistent revenues and

cost-based pricing, can occasionally throw a wild-card into the marketplace for producers whose

economic survival depends on those very things. Those who do take the dive into professional

independent agriculture learn very quickly to diversify their offering and add as much value as

possible to the goods they produce (Macher, 127-155). A diverse product mix and value-add

processing can create far greater customer interest and greater profit margins than basic

raw goods alone. Bio-diversity can also foster symbiosis, both in the ground and at the market

(Salatin, 69). Accomplishing these tasks really only comprises the first half of the battle,

however. Producers still need to let consumers in their communities know whats available in

the first place, where to find it, and when.

A 20012002 research project by the Sustainable Agriculture Research and Education

Program at the University of California at Davis conducted foodshed assessments for three

California counties that best reflect the condition of the states food system. The counties

surveyed were either already highly urbanized or were experiencing steep population growth

and land development. This makes the project s findings useful for small-scale producers just

about everywhere, since local means in a city for 82% of the United States population (CIA,

2011). A resonant theme among these three reports is that direct marketing was absolutely

critical to the viability of small farms in every county (King, 37). In Stanislaus county, farms

using direct marketing strategies boosted gross receipts 105% (Anderson, 34), however such

marketing activities required a substantial investment of time and capital (Anderson, 42). By the

end of the study, the number of farms engaged in methods of direct marketing had dropped by

16% (Anderson, 34). This emphasis on direct marketing is echoed by acclaimed permaculture

farmer-turned-author Joel Salatin, who warns that focusing on production without a comparable

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marketing strategy is a guaranteed way to go out of business (Salatin, 77), and that product

development, promotion, and competitive retail pricing are all equally vital to the success of a

small farm (Salatin, 67).

Traditionally, market communication challenges like advertising and valuation have been

tackled collectively through a number of exchange models that reward participants for the

synergy of their collective participation. A farmers market, as an economic event, is the best

example. Producers benefit from shared advertising, cross-exposure to each others

customers, and relatively low managerial overhead. Consumers enjoy great variety and

exposure to producers who they might not otherwise have access to, in one place at one time.

Buyers clubs and farmers cooperatives, on the other hand, emerged as ways for either party to

achieve greater economic leverage by reaching a critical mass of supply (for farmers coops) or

demand (for buyers clubs) which then satisfies a degree of uncertainty for the opposing party in

the transaction. Another emerging model, the CSA (Community Supported Agriculture) is a co-

creation partnership between producers and consumers, where buyers make requests and pay

subscription fees or preseason deposits to producers in exchange for their services. Once

again, a key strategy in the negotiation is for one party to mitigate the uncertainties of the other.

The uncertainties that small-scale farmers face today are daunting enough, but what

about those that havent yet emerged? In 2005 a Whole Foods market study revealed that 73

percent of consumers thought organic food was just too expensive to make the switch (Whole

Foods, 2005), but as was highlighted previously, conventional production has many critical

uncertainties that could at any time cause volatile price shocks, possibly accompanying long-

term shortages. But even if such a shock doesnt occur, gradual changes like waning oil

reserves, shifting rainfall patterns, and the arrival of a few billion more people will certainly drive

conventional prices higher over a longer time horizon. What might happen if the big-box

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grocery store cant compete with the farmers market? This is just one of many possible

scenarios that concern producers in everycategory.

Figure 1.2. Three-dimensional Producer Matrix demonstrating the relationships among

producers of various degrees of certification, geographic participation, and production scale.

Change is inevitable, but will likely affect producers of different scale in different ways.

Such distinctions are shown in Figure 1.2. High oil prices will make distance prohibitive for large

multinational operations, forcing either an active pursuit of new transportation technologies or a

re-localizing of the value web through a round of aggressive acquisitions or possibly both.

Regional producers may likewise be inspired to find new nearby markets, as illustrated in Figure

1.3. The collective variety of farmers markets can shelter specialized producers from this

invasion by offering greater value (in this case, variety in one convenient location) than a single

low-cost product at large volumes. This advantage is not guaranteed, however, and some

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markets may even embrace the large-volume invader for the value their participation would

pass on to customers. How might small-scale, specialized producers cope when increasing

transportation costs or emerging technology inspire large-volume regional producers of a similar

specialty to sell directly to consumers in their own backyards? All participants will be forced to

innovate to stay viable, however the largest operations may be the only ones financially capable

of investing in the profound changes required by this hinge moment in history.

Figure 1.3. Innovative large-volume producers driven by prohibitive transportation costs

enter smaller local markets, saturating entire product categories and driving specialized small-

scale producers out of business.

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An Opportunity

A consequence and perhaps a benefit of the independent food movements decentralized

nature is heavy fragmentation and redundancy. In nature, such abundance of diversity is a sign

of resilience, and greatly strengthens the ecosystem as a whole, since there is no single failure

point threatening to bring the entire system to a halt. Perhaps a new set of tools could be

created which leverage socially-driven exchange models to further mitigate the uncertainties

that accompany small-scale food production and commerce.

Figure 1.4. Network effect of proposed socially-driven collaborative framework creates

instances of greater economic gravity than large-scale suppliers can offer.

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An intelligent web-based platform that gives small-scale producers an opportunity to

team together and collaborate on market strategies and joint offerings could dramatically

enhance the viability of independent food networks. By providing the necessary communication

channels, feedback loops and responsive inventory management tools, these emergent

business clusters could accomplish instances of greater economic gravity than the market

forces which would otherwise undo them (Figure 1.4). Such a framework essentially

commoditizes shelf space rather than food and gives producers and consumers an immediate

communication channel to collaborate and even improvise when needed, alleviating significant

uncertainty on both ends.

The challenge is first to understand how independent food networks might cope with a

series of possible global food system failures, so that the capabilities of the system best reflect

the needs of its users. Not all local food economies are the same. Some are very large and

robust and some just getting off the ground, with many various stages of development in

between, so this framework must be adaptive and structurally renegotiable by the users who will

populate it. Next, what kind of market models would best support and positively reinforce the

"economies of synergy" that independent food systems are capable of achieving? Initial support

of a particular model may be a means of achieving necessary adoption, but how should the

industry look several years out, and what types of economic behaviors can be fostered to get

there? Finally, to ensure that the needs and desires of the locale being studied are accurately

represented, which members of the independent food network in Chatham County, Georgia, are

best positioned to prototype and pioneer this new model?

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Chapter 2: Literature Review

Literature reviewed for this project covers a wide range of topics, from swarm creativity to

business model innovation, from economic calculation to the economic empowerment of the

modern web-enabled world. The purpose of this review is to establish a unifying theoretical lens

through which to view the viability of igniting an explosion of self-organizing value creation

among independent producers and consumers, in an increasingly interconnected environment

of democratized resources and shifting values. The chapter begins with a founding perspective

on how society constructs and implements knowledge to coordinate economic activity. Next,

that perspective is extended to explore the implications and opportunities for entirely new

modes of economic coordination that did not exist within the scope of independent food

production prior to the proliferation of the world wide web.

Humanity has had a dramatic and fundamental relationship with food over the past 12,000

years. At the end of the last ice age the Earth rapidly entered a warming period, which was

catastrophic for most of the large, furry four-legged mammals at that time. This was also bad

news for humans, who had just invested thousands of years constructing a survival strategy that

had suddenly become not only irrelevant but dangerous to pursue. Unless reasonable

alternatives were discovered and adopted, humans very well could have followed the mammoth

into extinction. This wasn't the first ecological shock humanity faced, and it certainly wouldn't be

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the last. Situations change, and when they do only the most flexible, inventive, and adaptive

species will survive.

High-protein hunters soon found themselves relying heavily on plant-based food, and

eventually focused their efforts on the most efficient and calorie-rich species of plants and

animals available. Agriculture was born. Over time, individuals learned to produce more than

enough food to feed themselves, allowing others to focus their time and talents on specialized

pursuits that might generate unique exchangeable value of their own. Similarly, population

centers began to specialize in different domains and trade lines were established to move

goods across land and sea, pulled along by various modes and degrees of economic gravity.

Agriculture emerged as a driving force of modern civilization, turning the raw bounty of nature

into fuel for economic growth. So disruptive was this transition that nearly every aspect of social

life was reconfigured around the new ecological and economic reality. A new balance had to be

discovered, but getting there required the invention of new tools, exchange models, social

configurations and responsibilities, governance, and risk abatement.

Socio-economic Foundation

Information is essential to every human endeavor, and the marketplace is no exception. The

study of economics seeks to explain relationships between production, availability, distribution

and consumption, but at its core it is a social science concerned with the choices and behaviors

people exhibit in response to these factors; it is the science of choice under circumstance. The

more information market participants individuals and organizations alike have at their

disposal, the more intelligent their decisions will be. However, information is not always

available nor easily accessed, especially in times of rapid, turbulent change. People are, as

Peter Schwartz states in The Art of the Long View(1996), the scenario-building animal. By

renegotiating and reassembling the causal relationships and circumstances that led to the

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present, people are able to construct elaborate stories of what couldcome to be, far into the

future, and then consider the implications of the many causal relationships and uncertainties

that connect the distant future back to today (Schwartz, 26-28). The real value of information

comes from the knowledge that is generated through the rich exchange among actors. Thomas

Davenport and Laurence Prusak, in Working Knowledge: How Organizations Manage What

They Know(1998), define knowledge as:

...a fluid mix of framed experience, values, contextual information, and expert insightthat provides a framework for evaluating and incorporating new experiences andinformation. It originates and is applied in the minds of knowers... (5)

Or, more elegantly, knowledge derives from minds at work (5).

Fritjof Capra, in The Hidden Connections(2002), emphasizes that the communication at

the heart of knowledge creation is not simply the passing off of information, but rather a means

of coordinating behavior (83); it is the tethering force that binds all socially-driven endeavors

together. Niklas Luhmann, in Essays on Self-Reference(1990), extends Humberto Maturana

and Francisco Varelas classic contribution of the autopoietic system to social systems, and

establishes communication as the mode of self-production and reproduction (3-9). Essentially,

as Luhmann explains, communicating about communication itself recursive self-referential

renegotiation recycles and reinforces the very composition of the network as well as its identity.

In the words of Maturana, in Autopoiesis: A Theory of Living Organization(1981):

[...] through their interactions, generate and realize the network that produces them andconstitute, in the space in which they exist, the boundaries of the network ascomponents that participate in the realization of the network. (21).

This process self-maintenance that occurs within social systems is the life blood of

creativity and rapid adaptation. The social reconfiguration of disparate concepts and objects

from a past that is as Etienne Wenger says in Communities of Practice(1998) inherently

ambiguous and open for renegotiation, brings forth original ideas, images, and methods that

better address the challenges of the moment (83). Keith Sawyer, in Group Genius(2007),

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expounds on this theory, demonstrating how the complex task of facilitating collaboration among

participants of diverse cultural and experiential backgrounds is rewarded with the richness and

originality of the creative insights that can emerge (124-125).

The inherent conflict of this social reality, as Friedrich Hayek notes in The Use of

Knowledge in Society(1945), is that

...the knowledge of the circumstances of which we must make use never exists inconcentrated or integrated form, but solely at the dispersed bits of incomplete andfrequently contradictory knowledge which all the separate individuals possess. (519)

Therefore the chief economic problem of society, according to Hayek, is the difficulty involved

in quickly and effectively adapting to spontaneous changes in circumstances across a vastly

decentralized array of individual actors, each carrying just a few pieces of the puzzle (524).

Traditionally, widespread economic coordination has been attempted by constructing

hierarchies of command, charged with consolidating information and issuing responses aligned

with a central plan. Centralized decision-making according to Hayek in The Road to Serfdom

(1949) can be not only painstakingly slow but, dangerously also disconnected from the needs

and concerns of the individuals and communities affected by such decisions (57-58). In this

way, the modern rationalization of agriculture has sought to standardize and tightly couple the

interlinking pieces of production to remove variability and improve responsiveness to centrally

administered adjustments.

Conversely, more intelligent and responsive economic coordination can be achieved

because ofdecentralization, with the proper communication device(s) in place to allow the

impact of individual decisions to cascade freely throughout the system. The price mechanism is

just such a communication device, assigning objects an indexical score embodying the core

values required to make a logical choice of substitution. The product of the price mechanism

might actually be price the dominant device coordinating participation across the entirety of

the modern global economy. Hayek demonstrates how, when availability or desire of an object

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change, its price also changes to reflect the adjustment. The man on the spot doesnt need to

know why those changes have occurred, but rather how much more or less difficult achieving

their goal will be (The Use of Knowledge in Society 525). As each decision invokes a reaction

by those also connected to the event, information of the initial change is diffused throughout the

marketplace.

Fundamentally, in a system where the knowledge of the relevant facts is dispersedamong many people, prices can act to coordinate the separate actions of differentpeople in the same way as subjective values help the individual to coordinate the partsof his plan. (The Use of Knowledge in Society 526)

The full realization of these criteria is catallaxy, a more appropriate concept than economy

which Hayek defines in Law, Legislation and Liberty: The Mirage of Social Justice (1978) as

the order brought about by the mutual adjustment of many individual economies in a

market (108-109).

Ultimately, however, the signaling content of the price mechanism the variables

observed and corresponding information shared will be entirely contextual to its respective

social system of production, which, according to J. Rogers Hollingsworth and Karl H. Mller in

Advancing Socio-Economics: An Institutional Perspective(2003)

...consists of a society's norms, rules, habits, conventions, and values, which in turninfluence the institutional arrangements (e.g., markets, the state, association, networks)which are dominant in a society.

In Contemporary Capitalism Hollingsworth and Karl H. Boyer discuss how such forms of

economic coordination are increasingly difficult to establish in environments with a high diversity

of interests and values, resulting in an increased prominence of hierarchical institutions (29).

Communication of any kind economic, interpersonal, political, or other is a means, not an end

in itself. Etienne Wenger, in Communities of Practice (1998), offers a deeper perspective into

how mutually engaged groups of people are constantly at work constructing and renegotiating

meaning, identity, and the very reality of their respective contexts (51, 149). Its not surprising,

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then, that social systems with divergent values and interests would be fundamentally incapable

of responding to changes in a uniform manner, since information flowing among and between

independent worldviews takes on entirely different meanings.

Independent agriculture, as previously described, hosts a vast and dynamic landscape

of interests where value is not determined by traditional means of supply and demand. The

incurred expense of choosing independently produced goods over conventionally mass-

produced food is offset by a wide range of values from an equally diverse assortment of

worldviews. However, these social systems of flexible specialization, which Hollingsworth

defines as diversified low-volume production with an emphasis on economies of scope (1998),

share many of the same goals, opportunities, and threats. How then might these decentralized

and fragmented production systems achieve better coordination so that the entire ecosystem as

a whole may become more flexible and responsive in the face of change?

A Well-Coordinated Revolution

The world is experiencing nothing short of a full scale revolution of collaboration and innovation,

unleashed by the information and communication technology breakthroughs of the past sixty

years. Todays web-enabled global citizen is more interconnected with and perhaps

interdependent upon more people from a greater diversity of cultures and perspectives in their

daily renegotiation of meaning, identity and reality than at any other time in history. What some

claim is an era of runaway individualism, social isolation and abandoned privacy is in fact a

series of examples of humanity doing exactly what it does best: removing constraints and

uncertainty through technological leverage to join together in constructing a better tomorrow.

In Wikinomics: How Mass Collaboration Changes Everything, Don Tapscott and Anthony

Williams describe how people from all walks of life now have access to the tools and channels

necessary to communicate and collaborate in nearly every mode of value creation imaginable,

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and express that it is profoundly changing the world as we know it (10-11, 247). Innovative

companies like Google, Facebook, YouTube, Vimeo, Flickr and Wordpress have driven the

proliferation of this collaborative infrastructure by carefully brokering relationships of exchange

between many different types of customers within multi-sided platforms. Each customer

segment benefits directly from the value created by another. A wide range of previously capital-

intensive web services email and messaging, file sharing, video compression and hosting,

advertising, analytics, and content publishing has now become publicly accessible and

dramatically affordable, dissolving barriers to participation and sparking an explosion of

entrepreneurial innovation and value creation.

For better or for worse information today knows virtually no boundaries, coursing

throughout the connected world to all who seek it faster than ever before. Yochai Benkler, in

The Wealth of Networks(2006), explains how this enhanced access to information has

profoundly empowered individuals to act with greater autonomy than ever before; to do more

for and by themselves, and in loose commonality with others, without being constrained to

organize their relationship through a price system or in traditional hierarchical models (Benkler,

8). The combination of low barriers to participation and this loose commonality among

participants creates conditions for greater experimentation and exploration, particularly as

Benkler emphasizesfor non-market or socially-driven endeavors (11).

Richard Normann notes, in Reframing Business: When the Map Changes the

Landscape(2001), that many business ventures are no longer bound by physical location or

hard assets to operate effectively (28-29). Today its all too common to hear of new companies

launching with entirely virtual, geographically dispersed staff. In a radical reversal of Coases

Theorem1 , eliminating the transaction costs that once justified the consolidation of production

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has now forced these operations back apart, significantly changing the definition of strategic

advantage (Tapscott, 55-57). Employees and independent contractors can now work from

almost anywhere on Earth by leveraging these ubiquitous web-based application frameworks to

communicate and collaborate as if they were in the same room as their peers. Established

businesses are unbundling their non-critical operations, choosing instead to form symbiotic

business webs where each player is free to innovate around their respective core contribution to

the partnership (Normann, 51-55; Tapscott, 214-215). With an innovative vision and the right

business logic, any member of the business web now has the opportunity to fundamentally

reframe the nature of the game and quickly re-bundle the resources necessary to align and

command a larger piece of the value creation process than they may legally own (Normann,

65-67, 83).

The key pattern across all of these different contexts is that the autonomy gained by the

hyper-connectedness and free-flow of information fosters loose coupling a concept renewed

by Orton and Weick in Loosely Coupled Systems: A Reconceptualization(1990) within the

complex, ever-evolving web ecosystem. Participants are free to explore and experiment within

a universe of possibilities and dedicate their efforts where and with whom they choose. The

dynamic topography of the social landscape underlying this environment sets the stage for a

rich collage of perspectives, motivations and norms, and an equally vast mix of possible

configurations and relationships, as well as alternative resources and competing initiatives.

While this diversity suggests extreme discontinuity close-up, social activities coalesce

into recognizable, seemingly intelligent patterns of unified behavior from a far enough vantage

point. Peter Gloor, research scientist at MITs Center for Collective Intelligence, explains how

clouds of interest form around shared pursuits and exciting new ideas, and complex patterns

similar to those seen in swarming organisms such as bees and migratory birds begin to

emerge from human communication structures. As a community takes shape a meritocracy

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emerges within, establishing order based on the contribution and competence of these

collaborative, mutually engaged members near the core of the swarm. In Coolhunting: Chasing

Down the Next Big Thing, Gloor defines these Collaborative Innovation Networks (COINs) as:

cyberteams of self-motivated people with a collective vision, enabled by technology tocollaborate in achieving a common goal an innovation by sharing ideas, information,and work (76).

The diffusion of meaning through diverse social webs is anything but linear or orderly, but

swarming behavior can be identified and even forecasted as people begin gravitating around

original, innovative ideas and the COINs that bring them to fruition (Gloor, 45-46).

Because trust and authenticity are so critical to the continuity of a meritocracy, members

have a genuine incentive to validate their own contributions, as well as the contributions of their

peers. Through this peer-to-peer accreditation, Benkler explains, self-assembled interest

clusters are self-regulating, rewarding favorable behavior and discouraging unfavorable ones,

while filtering out extraneous information (Benkler, 12). This collective validation creates a

structural basis for automatic coordination within the social system by feeding back relevant

information that corrects and reinforces the communitys trajectory toward the ideal state implied

by those very feedback loops.

Given the profound connective potential of the web, a truly powerful realization of Hayek's

catallaxy could be achieved by empowering the autonomous clusters of interest that form

around decentralized and fragmented production systems with a framework composed of

instances of renegotiable forms of coordination. Essentially, such a framework would be

structurally renegotiable with regard to the feedback loops each cluster chooses to coordinate

within itself, while simultaneously promoting the free-flow of salient information among all

clusters throughout the entire ecosystem.

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Chapter 3: Research Methodology

The purpose of this study is to deconstruct the market mechanics and social dynamics that drive

independent food production in Chatham County in southeast Georgia. Specifically, this project

asks Which types of a market models best support and positively reinforce the "economies of

synergy" that independent food networks are capable of achieving? Next, this project asks

Which members of the local community (Chatham County, GA) are best positioned to prototype

and pioneer this new model? And finally, How will independent food networks respond to a

series of possible futures?

While economics seeks to explain the relationships between production, availability,

distribution and consumption, the discipline is essentially a social science concerned with the

choices and behaviors people exhibit in response to these factors. It is the science of choice

within parameters, contexts and circumstances. Independent food networks are as much about

community as they are commerce, so to best understand the dynamics at play within the

complexity one must identify the innovative thought-leaders at core of the social web, and learn

to view the world through their eyes and empathize with their hopes, fears and aspirations.

Research Design

Figure 3.1 illustrates the phase progression of this project. This study progressed from wide

consideration of market participants to the focused and extensive contextual immersion within

the ongoing affairs of a sample of producers who are among the most central and influential in

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the area. Observational and participatory data from these experiences was sorted, clustered,

modeled and mapped to achieve a holistic, systemic perspective of the social and economic

drivers that define the business environment. These models then informed the construction of

several future scenarios which explore global drivers and their possible implications for local

practice. Findings from all of these activities shape final design criteria as well as establish a

roster of the most influential co-design candidates.

Figure 3.1. Illustrated research design

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Project Timeline

This project will be conducted in four phases from May, 2010 to May, 2011 (Table 3.1).

Date Activities Details

Phase 1: Field Study Preparation 4 months

May 2010 Prospectus approval Exploring Opportunities for TechnologicalInnovation and Reconfiguration in the LocalFood Industry

May 2010 Aug. 2010 Secondary research;Developing interview protocol

Exposing known unknowns, assumptionsand biases to initiate secondary research

Aug. 2010 Identifying and contacting interviewprospects

Establishing criteria for innovator profileand filtering of prospects

Phase 2: Field Research 2 months

Aug. Sept. 2010 Contextual immersion and datacollection;Iterative analysis and adaptation

Site visits, semi-structured interviews,hands-on participation, photodocumentation

Phase 3: Data Analysis 7 months

Sept. 2010 March 2011 Ongoing data analysis and modeling;Strategic scenario development

Data modeling, system mapping, businessmodel canvas development

Phase 4: Define an Opportunity Space & Design Criteria 3 months

March May 2011 Formalize findings and design criteria;Identify co-design candidates

May 2011 Project completion and defense

Table 3.1. Four-phase Project Timeline

Phase 1: Field Study Preparation

Revealing Known Unknowns and Assumptions

Known unknowns and general assumptions about independent food commerce must be

confronted for two very critical reasons. First, assumptions and subsequent biases must be

articulated and neutralized to ensure purely objective inquiry and analysis. Second, confronting

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and categorizing known unknowns establishes clear topics for secondary research. This

approach creates a solid foundation for developing an interview protocol with an informed,

refined understanding of the context in question.

Secondary Research

Secondary research explored the global drivers and trends that will affect local practice. The

USDA has been tracking organic production and sales data for several years and is a reliable

and recognized source of national statistics and analysis. The USDA has also produced

extensive forecasts and projections for the U.S. agriculture industry, which indirectly provided a

reliable starting point for constructing logic axes of driving forces. Secondary research was also

drawn from industry reports and trade association publications, and social science journals, as

well as university research projects at other universities. Finally, a series of Condor analyses

were conducted to create a comprehensive view of conversation within the independent food

community.

Identifying the Interviewee Group

Engaging the most innovative and opinion-leading producers is critical to the success of this

project. Innovators and early adopters adopter categories established by Everett Rogers in

Diffusion of Innovations (2003) are generally quite proactive in adopting new ideas, methods

and behaviors, and are widely regarded as such by their peers (Rogers, 283). Opinion leaders

within a community are not only highly influential, but also exemplify and express the systems

structure (Rogers, 27). These participants perspectives and strategies will represent those of

many other producers within their networks, providing a rich view into the community at large.

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Facebook, and newsletter mailing lists to connect with their customers, and are frequently

referenced or cross-linked by other such producers. Many producers names appear on various

online directories and farmers market vendor rosters, but for many that is the extent of their

web presence. Remaining prospects not fitting the profile of the socially-connected curator of

new ideas filtered themselves from the list by simply not responding to the invitation to chat.

However, a few producers who were frequently referenced in conversation by those who fit the

target profile were simply unable to spare the time to meet.

Identifying Leaders through Social Network Analysis

Accurately identifying the innovators and thought-leaders of the local producer community is

absolutely critical to the success of the field research phase. To ensure accuracy, another

perspective had to be woven into analysis: that of the crowd. Two distinct processes were

employed to achieve this, each with a sophisticated piece of software created by Peter Gloor

and his team of fellow researchers at MIT Center for Collective Intelligence. This program is

called Condor.

Condor allows you to create visual maps, movies and many graph metrics ofrelationships. Relationships can come from social networks, Web site link structures,and concept maps of unstructured documents, online forums, phone archives, e-mailnetworks, and many more. (Condor Manual 2.2, 2007)

While Condor is as versatile as it is powerful, this analysis will only require a few key features.

The first is the Web Collector, which will query Google Search for specifically constructed

keywords and compile the results into an SQL database for later analysis. For each initial result

a second query is executed for any possible web entities linking back to that result as well. This

multi-degree search adds a rich layer of interconnectivity, allowing Condor to analyze and

calculate relationships and various modes of centrality. The primary mode of centrality for this

project will be betweenness centrality, which is a relative calculation of importance based on the

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number of shortest paths between nodes that run over each node. A node with the greatest

betweenness centrality, therefore, is essentially a super-connector, enjoying the shortest path to

all other nodes in the network. With regard to social networks, these nodes are the leaders.

The first step in this study was to identify and analyze the communication structure that

supports the collective conversation around such topics as local/organic food producers and

markets within southeastern Georgia. By executing parallel queries that include a Google

Search filter syntax near: followed by the ZIP code for each respective town, the results were

contextualized to a web user from each locale. These localized results were then studied both

independently and together as a merged communication view. This structure was then

analyzed as a web of relationships among and between websites, news articles, blog entries,

directory listings, and forums, revealing the most commonly referenced and interconnected

nodes in the network.

The second step in this study was to analyze the frequency and association of words

and phrases found within the content collected for each of the results of the first step. Several

parallel queries were executed for each locale, and the resulting data sets merged together, so

that an aggregate content analysis could be conducted. One important feature of Condors term

analysis functionality is the ability to feed in a startword list of key terms and phrases to filter

against. In this case, a startword list of every identifiable producer in the region was used so

that the most frequently referenced and interconnected names were highlighted and analyzed

within the data set.

The goal of this phase is to identify the fulcrumof the conversation, where innovators

and common participants collide to share new ideas and learn from one another, and then to

identify the most popular, commonly referenced producers within that conversation. The

resulting list of crowd-elected producers was then approached during the next phase for

interviews and first-hand observation.

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Once interviews were underway, the community was further analyzed through offline

social network analysis coupled with noted actor references and the guiding principle of the

friendship paradox. The friendship paradox, as established by sociologist Scott Feld in Why

Your Friends Have More Friends than You Do (1991), holds that any given person in a social

network tends to have fewer friends than their friends do, and that randomly selected friends of

initial participants will be closer to the center of the social network. By documenting and

mapping early contacts and interviewees references to friends and professional colleagues

involved in the local independent food network, actors of greater centrality and influence were

revealed for later consideration.

Phase 2: Field Research

Data Collection & Documentation

The value of contextual immersion and participant observation cannot be overstated. Primary

research included semi-structured interviews, frequent farm and market visits, hands-on

participation and volunteer work. Data collected from these methods include transcribed

interview audio, field notes, email conversations, newsletters and marketing brochures.

Semi-structured Interviews

A semi-structured interview protocol (Appendix A) was developed to engage interviewees in a

strategic conversation about their current business success and challenges, past lessons

learned, and concerns about the future. The goal of such an extensive protocol is not to cover

each and every question verbatim, but rather to support several conversational elements. The

protocol also includes several exercises and two printed worksheets intended to support a

visual dialogue by engaging interviewees in simple diagramming and concept sketching,

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invoked during various stages of the interview session. All participants signed an informed

consent document (Appendix B), establishing the boundaries and expectations of disclosure for

any data collected from our meeting.

The first set of questions was designed to create a rapport and put the interviewee at

ease by discussing topics like the initial inspiration for getting into and staying in the business,

favorite aspects of the business, significant accomplishments from the past year and goals for

the upcoming year. The interviewees were also asked to sort a deck of seven business attribute

cards (Figure 3.3) in sequence of importance.

Figure 3.3. Sortable business attribute cards invoke a reflective conversation about importance

The second set of questions built off of the first, focusing on the time and techniques that

go into operating their business. This section also introduced a few hypothetical scenarios, like,

If you could avoid doing one thing for the year, what would it be? and If you could only do one

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thing this year, what would it be? The purpose of these questions was to explore the time

expenditures that distract from the real joy of the practice, and, once these truths have been

surfaced, to articulate as many activities and expenses as possible.

The third set of questions shifts perspective to reflect on the partnerships and

relationships that are directly involved in the producers practice, and then to collaboratively

sketch those interactions. This exercise did not produce elaborate diagrams every time, but a

few great system maps were created when the information was forthcoming.

The fourth set of questions focuses on arriving at an informed value proposition by

exploring marketing strategies, differentiation, exchange channels and customer relationships.

Figure 3.4. Annual timeline template

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Agricultural practices change dramatically with the seasons, so an annual timeline exercise was

conducted (Figure 3.4) to help producers articulate shifting operations, expenses or concerns,

as well as different expectations among partners or customers as the year progresses.

The fifth and final set of questions brought everything together and shifted the

conversation forward into the future, beginning with a discussion about the interviewees source

of inspiration and cause for admiration within their profession. After invoking heroes and

thought leaders came probes for concerns about the future, one- and five-year aspirations for

their own business, and ten-year predictions for independent food production at large. Like

each previous set, a hypothetical scenario was proposed. This particular exercise is based on a

question borrowed from Kees van der Heijdens conversation protocol from Scenarios: The Art

of Strategic Conversation (2005). First, the interviewee was asked If you could ask a fortune

teller three questions about the future and get three perfect answers, what would those

questions be? Once the questions are established, the interviewee was asked to imagine that

they are now the fortune teller, and to answer each question so that the future turns out better

than the present. Finally, the interviewee was asked to answer those questions again, however

from a perspective that the future will become much worse than the present. Responses to this

exercise were incorporated into future scenarios which would directly impact this interviewee.

Data Collection Tools & Equipment

Simple data collection tools were employed for this study. An iPhone Voice Memos app was

used for recording interview audio and post-interview reflections, which was then synced to

iTunes for easy playback and transcription. Photo documentation of market events, interviews

and tangible data analysis methods were also used. Condor (social network analysis software

developed at MITs Sloan School of Management) was used to observe and analyze large

virtual communities, as well as online activity concerning local actors within the study scope. All

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digital data was stored on a personal computer, as well as external and cloud backup storage.

Notebooks, sketchbooks and Post-Its were used to capture, sketch, explore and articulate

complex ideas, relationships and systems during the data collection phase.

Phase 3: Data Analysis Process & Procedures

Data collected during the second phase was analyzed extensively through a series of sense-

making and pattern-constructing methodologies.

Affinity Diagramming

Key observations, statements, questions and perspectives were extracted from the transcript

record of each interview and notes from spontaneous encounters. These individual extractions

were saved on 3.5x5 notecards with a small reverse-side mark indicating the interviewee of

origin. This allowed processing of cards both by interviewee and as an aggregated collection.

Notecards were sorted into clusters as new and unique hierarchies and modes of relation

emerged from the data (Figure 3.5). The goal of this process was to give the data voice so that

it might reveal deeper patterns of behavior and causality than that of individual interviews alone.

Figure 3.5. Affinity Process: constructing categorical relationships to make sense of complexity.

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Business Model Canvas

The business model canvas (Figure 3.6), developed by Alexander Osterwalder, Yves Pigneur

and hundreds of volunteer contributors from around the web in their book, The Business Model

Generation, is a tool for spatially reasoning with the many interconnected components of a

business model. A business model is simply too complex and too abstract for a person to hold

the entire concept in their mind. Osterwalder et al. s canvas enables effective deconstruction,

exploration and prototyping of business models, not just by individuals but by collaborative

teams as well.

Figure 3.6. Business Model Canvas: Key Partners (KP), Key Activities (KA), Key Resources

(KR), Costs and Expenses ($C), Value Proposition (VP), Customer Relationships (CR), Channel

(CH), Revenue Stream ($R), and Customer Segments (CS) (Osterwalder)

A series of canvases were created to synthesize secondary research, but were further

refined as primary data became available through research. This iterative process helped

expose initial misconceptions while laying the groundwork for more informed conversations

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about each interviewees business model and strategic approach to surviving in their particular

business environment.

Strategic Scenario Development

Findings from primary and secondary research were combined into a set of three scenarios: one

exploring a future defined by business as usual, as held by the participants of the study as well

as opinions and projections from the industry at large, and two alternative scenarios that cover a

range of possible futures. These scenarios will ultimately provide high-level strategic guidance

and design criteria for the concept development and prototyping phases.

Phase 4: Define an Opportunity Space & Design Criteria

Formalizing Findings and Design Criteria

The final phase of this project was to articulate the findings of this project through the

establishment of design criteria for effective application and implementation. This phase also

presents recommendations for future research and exploration.

Research Limitations

No local food economy is the same as any other. Some are very large and robust and some are

just getting off the ground, with many various stages of development in between. The network

analyzed in this study offers a limited number of actors matching targeted adopter categories.

While the goal is to achieve rich, qualitative depth of understanding, the small sample size

available in this particular context may produce findings that are inherently limited in their

widespread application.

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Chapter 4: Analysis & Findings

The guiding research questions of this project were designed in such a way that satisfying the

first would provide the foundational basis for the next, which would then support the last. This

means analysis was conducted for each question concurrently with preparation for the next.

The first question, Which producers within the local independent food network are best

positioned to represent the community at large?required a blended methodology of

environmental observation and social network analysis. The resulting collection of producers

and affiliations were then approached with a wide array of primary research methods to reveal

greater patterns within the tacit hopes, fears, opportunities and challenges of the community, as

well as which the second question probes the market models which are emerging to face the

gravity of this shared reality. Finally, a series of strategic scenarios will be developed to

concretize th

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Exploring Opportunities for Technological Innovation and Reconfiguration in the Local Food Industry

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