My first response to a thread on Detroit’s Urban Innovation Exchange (UIX) about celebrating failure as an intimate partner to innovation. The original article that spurred the thread is here.

From the website: The UIX is ”an initiative to showcase and advance Detroit’s growing social innovation movement. Led by Issue Media Group withData Driven Detroit, The Civic Commons and a coalition of media and community partners, UIX is made possible thanks to funding from the John S. and James L. Knight Foundation.”

Here’s a profile they did on me and my work at FoodLab.

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I agree that it’s a good idea to create a culture where it’s okay to fail — this ethos was drilled into me early in my professional life working in the tech industry. I’m sure you’ve heard the mantra: “fail early, fail often.” It’s why good angel investors invest in PEOPLE not in IDEAS.

I think for me, failure’s intimately tied to two of the things I value most: humility and constant learning.

When we fail (and recognize our mistakes as such), we realize that not we’re not Gods, we can’t predict or control everything (bad OR good, as Claire pointed out above), but we can strive to pay attention to what we want and whether what we’re doing is actually getting us there… if sometime we’re doing doesn’t serve us, if we’re failing, we try something else. If we pretend we never fail or we’re afraid to, we’ll never innovate, never improve. Einstein supposedly said “Insanity is trying the same thing again and again and expecting different results” — but sometimes trying something different requires messing up.

On the other hand, if we try things willy-nilly and we don’t learn when we fail, though, there isn’t a whole of point to it. There are plenty of examples that we might call failures of society (some really big ones) that we haven’t really learned from. There are plenty of instances where we try to build things from scratch when we could have learned a whole lot from someone who has done something similar before. I’m not sure that type of failure is noble or useful.

How can we harness failure to learn from our mistakes and do better? I think the non-profit/foundation world has a whole lot to contribute here. How do we build a system that doesn’t just reward success, but successful iteration, learning, capacity to change, resilience? Getting rid of “stagnation” as Tunde puts it… but not just no stagnation for the sake of movement but for the sake of betterment. When it comes to social enterprise, SO OFTEN we only talk about what’s working while covering up the things that haven’t worked or the parts of an existing enterprise that are particularly challenging, troubling… One of the things I really admire about the Roberts Enterprise Development Fund is the work they’ve done to document some of the enterprises that just haven’t worked out, and how dedicated they’ve been to working with many of their grantees through problems, not just giving up after one grant cycle…

I also want to mention that we can’t ignore the size of risk & resources involved in an operation. Failure is more tolerable in a fundraising experiment for a small community project, but maybe less tolerable when you’re building a ship or performing heart surgery. In those cases, you’ll want to get all your failures out of the way on LOW-RISK experiments up front before you commit to the real deal.

I’d also point out that we have a tendency to allow some kinds of people the luxury of “failing” and not others. But more on this some other time…

Are the very best way to start the day.

My phone fell out of my pocket while biking to work on Friday. Before I could retrieve it, a construction truck rolled by and crunched it. The guts still work so I can her buzzing every time I get a message, but the screen’s completely kaputt. So I know the messages are there, but I can’t see them: kind of a funny metaphor for how communication goes between people sometimes.

So last night, I got an email from my Jieh telling me that baby eagles are called eaglets (something we’d been trying to remember on our Sunday ride out on Harsen’s Island). In the morning, there was another note telling me to come over for breakfast early because Jieh had made the most delicious rhubarb blackberry buttermilk cake and I should have some.

A little after seven, post a.m. ablutions and some puttering about, I biked over with boiled eggs and strawberries and a tube of sunscreen to stash in Jieh’s car for our next adventure.

I arranged some cake on two of Jieh’s pretty ceramic plates and halved the eggs and sprinkled them with special soy; we made coffee and poured ourselves some mango lassi and went outside to the deck. It was sunny and fresh in that dewy morning sort of way and we enjoyed it as we ate our breakfast and talked about our day and upcoming travel. Jieh’s Asian hubby (the other essential member of our little clan) came down from his apartment with adorable bed head and drip coffee and we enjoyed each others company til it was time for me to go and start my day in earnest.

I miss my Daniels and the Chan Clan, and I feel so blessed to have found my way into our little family here in Detroit. It means a lot to belong.

Photo of Harsen’s Island by mdprovost

When I look at the list of months in my blog archive, it strikes me just how little I’ve written over the past 2 years and a bit, especially compared to my time in Cambodia and on the farm in 2008 and 9. I suppose writing varies inversely to the amount of stuff filling my days.

I’ve noticed, though, that I need write (and talk) to learn. Life over the past couple of years has been so so full of experiences, people, places. I’ve been on the move, constantly changing to the point where it’s hard to describe to people (or sometimes even know myself) who it is that I am and what exactly it is that I do.

Thankfully, I have incredible friends in my life who humor me and listen and help me untangle the sometimes frenetic thinking and doing into something that’s more comprehensible and sometimes even beautiful. They make sure I don’t take myself too seriously (it’s a flaw!) and that I pay attention to the things (usually people) that matter the most.

Even so, with all that reflection in real time, sometimes I feel like I could retreat somewhere and simmer in the sum of life til now… like I could keep myself occupied and become wiser just by being quieter. I’m hoping a 10-day silent retreat in May gives me a little piece of this, and I’m planning something longer — maybe three months — sometime in the next four or five years. A time for silence and ripening.

In the meantime, for the summer, I’m going to hold myself to a stricter schedule of writing. I’ve been trying to maintain a radical openness since coming to Detroit, but recently I’ve been thinking I need to focus in more and process things I’ve heard and overheard, passing thoughts, feelings, into something more coherent (not static or final, but connected… like a mind map, a network of connections).

I guess this is a reminder that this particular blog space isn’t a place where I intend to preach, influence or educate, but to have a conversation with myself and people who care about me who happen to be far away and others who resonate with the questions I’m asking about food and equity and relationships and change in the world.

Making space to actually write things down won’t always be easy, but I think it’s worth it if I can learn something new.

Some things I’d like to take on…

• Social justice and entrepreneurship — tensions between the individual and the collective. Does the fact that a tension is unresolvable mean that the mechanism is flawed, or perhaps even more important?
• Brokering roles & the role of social structure in unlocking creativity
• Arne Naess and the ecological self — is this possible? desirable? true altruism?
• Does creativity require limiting someone else’s capacity to create?
• How do we remind ourselves that every story is incomplete? Is there a prayer? A song?
• Emergence  versus scale?
• Does financial sustainability in a “social enterprise” have to be based on markets as they exist today? (Must we achieve “profits”? What about grants? Unpacking the financials of that biodynamic farm on Lopez Island)

And some more mundane things about day-to-day life and cooking and some creative projects that I’m working on.

I’m getting more excited as I write about it. That’s a good sign

This was written as a response paper for a course on social networks. We were asked to write three essays critiquing network research in our area of interest at the micro (people), meso (organization/community/infrastructure), and macro (nation scale) levels.

Generally, we chose essays that used structural network analysis themselves; in this case, I chose a paper that adopted a network (or relational) way of looking at the world, but didn’t use these formal methods. Structural network methods are a set of (mostly) quantitative approaches that (as their name implies)  describe the structure of relationships (ties) between different actors (nodes) or the position of a particular actor within this structure.

For more on network analysis, here’s a pretty good simple overview of some basic concepts.

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Unraveling Agro-food Network(s)

Drawing inspiration from Granovetter’s (1985) seminal work on embeddedness, food systems researchers in the late 1990s began to integrate economic, social, and political approaches to food systems into a network-based ontology.  Rather than look at global food systems as structurally ossified “regimes,” linear commodity chains, or markets made up of rational, disconnected actors, researchers re-imagined food systems as complex webs of actors linked by social, political, economic, and physical ties. Despite the popularity of the network metaphor, there are still few examples of researchers employing formal network methods to describe the structure of agro-food networks.

Raynolds’ (2004) is no exception. Her study of organic agro-food networks falls within a family of research that has blossomed in the last decade, which focuses on “alternative” agrifood networks (e.g. local and regional, fair trade, artisanal, etc).  She employs commodity network analysis to examine consolidation in global organic networks focusing on network governance, or the mechanisms that underlie the development of network ties. She demonstrates that certification standards play a major role in determining and maintaining an inequitable structure of relations between organic food actors in periphery and core (South-North) nations, but stops short of explicitly specifying and measuring this structure. Finally she observes that there is a “bifurcation” in organic agro-food networks between this “globalized system of formally regulated trade” and networks based in “alternative movement conventions,” and suggests that these alternative networks may offer opportunity to upend the reproduction of traditional South-North inequities, as well as inequities between large and smaller scale firms (Raynolds, 2004:725).

By design, the commodity network approach looks at multiple dimensions of global organic networks simultaneously. It describes social, political, cultural, and economic ties. Nodes aren’t limited to one type, but at times are hemispheres, at times, nations, firms, and individual consumers. The boundaries of analysis shift at times from a North-centered organic processing and distribution network to a movement network of consumers directly connected to local farmers to a global exchange between North-South nations.  What might we might learn by focusing in and using formal network methods to measure the observable interactions between a specified set of actors? In the following paragraphs, I unravel three of the many networks that Raynolds (2004) invokes, specify the nodes, ties, and boundaries, and use her analysis to make guesses at network measures like degree, density, and centrality. Then I describe how network analysis might be used specifically to add depth to Raynolds’ final conclusion about the “bifurcation” between mainstream and alternative organic agro-food networks.

The main thrust of the argument takes place at the macro-level, looking at the relationships between periphery-core nations, specifically between Southern countries (especially in Latin America) and Northern markets (especially in the United States, Canada, Western Europe, and Japan). In this network, the nodes are countries, the ties are imports and exports, and the boundaries are (mostly) limited to Latin America and the major markets described above. From this, we can infer that Northern countries will tend to have higher in-degree centrality than Southern countries (hence their “core” status).  Raynolds also describes a robust “inter-core” trade “dominated by US exports to Europe and Japan, trade between European nations, and exports from Australia, New Zealand, and South Africa to the top markets” (p. 725). Considering this, and that products might flow more than one step (e.g. organic tomatoes produced in Chile, processed and canned in the US, and sold in Japan; peanuts grown and shelled in Canada, included in mueslix in Germany, shipped to the UK), we might meaningfully measure betweenness and closeness centrality. This might help to identify particular Latin American countries as “bridges” that are serving as a gateway between Southern producers and Northern markets; certain Northern countries (the US, for example) with high betweenness scores might also be brokers with more power to set the global organic agenda. These measures would require data measuring the flow of some subset of organic products (all edible organic products, organic fruits and vegetables, all processed products etc.) between each country dyad. With this data, we could also compare a network of actual trade with a network of trade that we might estimate based on a gravity model based on “distance” as measured by cost of transport between countries, and “size” as measured by number of organic hectares, length of growing season, and total population. The differences between the actual and estimated networks would shed light on political, social, and cultural structures that intervene in the network. Though the data required for this analysis would not be easy to compile, it might be possible to get at by combining a variety of sources and using estimates, and the result could a more nuanced view of North-South organic agro-food trade dynamics.

Raynolds (2004) also considers a meso-level network of organic agro-food firms. In this case, the nodes are all organic firms (including farmers, aggregators, distribution companies, processors, and retailers) and the ties could be any type of business relationship (e.g. sales between firms). Raynolds describes a change from a “loosely coordinated local network of producers and consumers to a globalized system of formally regulated trade which links socially and spatially distant sites of production and consumption” (p. 725). The trend is towards greater spatial distance between nodes (which would not necessarily be captured in the network I specified above), and also towards consolidation: in network terms, a decrease in the overall size of the network and increased density. Howard (2009) documents this trend in his visualization of consolidation in the North American organic industry, but his study also does not employ formal network measures. Again, data is difficult to obtain on relationships between organic firms, especially given such a broad boundary; however, it is possible to limit the boundary to a particular commodity or limit the type of firm (e.g. only farmers and distributors) to get at a particular aspect of this broader network. This would make it possible to identify more “powerful” firms, not just in terms of endogenous characteristics like size, but also in terms of their position in the network.

Finally, operating beside the macro and meso-level networks is a micro/meso-level network of movement actors and industry groups that shape and challenge norms within the organic movement as well as certification standards. This network could be operationalized as a two-mode network of organic food movement organizations, industry groups and policy-making bodies like the USDA tied by common individuals (e.g. Deputy Secretary Kathleen Merrigan of the USDA formerly staff at the National Sustainable Agriculture Coalition, or former president of the Organic Farming Research Foundation currently head of an organic department at USDA); it could be a two-mode network of movement organizations tied by association with broader trade associations or participation in specific political campaigns; or it could be a network of social movement organizations tied by some other indicator of collaboration. Specifying and mapping these relationships would allow us to see more clearly which agencies, industry groups, and movement organizations occupy more influential positions in the network. If we notice particular clusters of groups, we might look to see if shared norms exist within these clusters and if they specific capacity for collective action. We might also be able to characterize more clearly the “conflict” that Raynolds (2004) describes between movement actors and industry groups in determining certification standards. If we were able to measure this over time, we might also see whether movement advocates like Fred Kirschenmann (2007), who have advocated for a more harmonious marriage between the organic industry and the organic movement into a more integrated organic community, have had any effect.

The article ends by reasserting this conflict between two parts of the organic agro-food network: the one that is governed by organic certification standards driven by commercial and industrial conventions that privilege economies of scale and efficiency, versus the one that is governed by domestic and civic conventions of trust, tradition, and overall good to society. Raynolds (2004) bases this on her observations of “alternatives” to “mainstream” organic networks that represent the “theoretically important […] contested terrain negotiated within and between commodity networks” (p. 738). This dichotomization of movement-based “alternative” networks versus “mainstream” or “industrial” networks is typical of contemporary food systems studies, yet little research has been done to examine these supposedly different networks systematically to compare their structures and ask whether they are really as “bifurcated” as theory assumes.

To systematically analyze this assumed separation, we might choose a particular organic product within a given geography that we believe has strong “mainstream” and “alternative” networks of production and consumption; say, for example, organic berries in the Pacific Northwest which might be produced by small local farms and sold at Farmers Markets and through Community Supported Agriculture schemes or produced in Latin American countries, imported, and sold at larger retailers. We could set the nodes as all firms that participate in production, aggregation, processing, and sale of the particular product, and stipulate ties as total volume of transactions between firms. The data could be collected through a mix of interviews, publicly available data, and estimates based on observations. With this data, we could do a better job answering questions like: Are “mainstream” and “alternative” networks really so bifurcated, or do firms actually overlap (we might expect, for example, some overlap in mid-sized producers who sell both at farmers markets and to larger supermarkets)? If two separate cliques of firms do emerge, are they different structurally: More or less dense? More or less centralized? Which firms have power in each clique? Are norms really different in each clique? How so?

To date, food systems researchers have not yet embraced structural network analysis despite a network-based ontology that recognizes the relational aspect of both industrial and alternative food chains. For one thing, as in the case of the above examples in the organic agro-food sector, data can be difficult to collect. In network analysis, missing data has particularly strong negative consequences on the statistical validity of the data. Even where it is possible to collect data, social network methods can seem inaccessible and overly technical. Yet these methods have the potential to bring more clarity to specific questions about how global, organizational, and individual actors connect to one another to both uphold and upend our current systems of producing, processing, distributing, selling, and consuming food.

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Works Cited

Granovetter, M. 1985. “Economic action and social structure: the problem of embeddedness.” American journal of sociology 481–510.

Howard, Philip. 2009. “Consolidation in the North American Organic Food Processing Sector, 1997 to 2007.” International Journal of Sociology of Agriculture and Food, 30.

Kirschenmann, Fred. 2007. “Guest Feature: Beyond Organic, What’s Really At Stake?”

Raynolds, Laura T. 2004. “The Globalization of Organic Agro-Food Networks.” World Development 32(5):725-743. Retrieved April 17, 2012.

A short summary that I wrote for a class on Participatory Modes of Inquiry about Action Science — one of many threads in the participatory action research (PAR) tradition. “Participation” is a tricky concept in academic realm where the “experts” who do the studying tend to exert power over “laypeople” who get studied. As I consider the academic lifestyle more seriously, I wonder in what ways my work can subvert this dominant mode of operation? Participatory research tends to take longer and hence be more expensive because it requires real relationships with people and lots of listening. On the other hand, one can argue it’s more likely to have catalytic validity especially when it comes to “wicked problems” — the kind that deal in human values and can’t be solved, but only “managed.”

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The Action Science (AS) approach to action research (AR) distinguishes itself from other forms of AR in its attempt to remarry practical action with scientific method and scientific rigor (Greenwood & Levin, 2007). The strand of research offers a direct response to the problem of “rigor versus relevance” in which norms of ‘rigorous’ positivist science such as experimentation under controlled conditions and separation between the researcher and the researched may produce results that are irrelevant or invalid for practitioners working to affect social change (Friedman, 2001, p. 160); on the other hand, more ‘relevant’ alternative action research methodologies may define validity by the positive social effect they engender and eschew rigorous empirical testing or attempts to develop falsifiable theory. AS attempts to bridge this “widening gap between social science theory/research and social science-based professional practice” (Friedman 2001, p. 159) by arguing that rigor and relevance can both be achieved by collapsing “theory building and theory testing” together into one systematic inquiry (Greenwood & Levin, 2007, p. 224).

Action Science embraces dual objectives of improved social practice and the development of generalizable theories of practice through intervention, in contrast to the detached observation of traditional science. Specifically, AS intervention attempts to address “intractable conflicts and difficult dilemmas faced by social practitioners” through the act of “confrontation” (Friedman, 2001, p. 160). Confrontation requires practitioners to uncover implicit theories of action (also known as “theories in use”) and reconcile them with what they say they believe (“espoused theories”):

The goal of action science inquiry is to help practitioners discover the tacit choices they have made about their perceptions of reality, about their goals and about their strategies for achieving them. The fundamental assumption of action science is that by gaining access to these choices, people can achieve greater control over their own fate. (Friedman, 2001, p. 161):

For example, in his article on the “paradox of participation” in action research, Friedman (2009) and his co-researchers engage in a meta-analysis of a “failed” project between an Israeli university and an Arab-Palestinean NGO. Through critical reflection and analysis of meeting transcripts, the researchers confront the conflict between their espoused values of equal and full participation and an implicit theory of action that required the NGO to take on a role as fully invested co-inquirer regardless of its own perspective and goals. The inquiry helped both to mend the strained relationship between the academic team and the NGO leadership and also developed “actionable knowledge” to help others build better participative relationships (Friedman, 2001, p. 1).

In line with its emphasis on developing generalizable theories of action, AS has its own well-developed set of precepts. For example, AS delineates between Model I and Model II theories of action. A Model I theory of action is characterized by defensiveness and unilateral control, whereas Model II features “minimally defensive interpersonal and group relationships, high freedom of choice, and high risk taking” (Argyris et. al., 1985, p. 102, qtd. in Greenwood & Levin, 2007, p. 226). AS interventions often attempt to move a group from Model I defensiveness to Model II open inquiry. Friedman’s (2001) work with the Open House organization attempted to interrupt a cycle of conflict between two subgroups in the organization by constructing a causal map of the conflict that allowed staff members to “test their own interpretations,” “see clearly their own blindness,” and eventually “redesign their theories of action” (Friedman, 2001, p. 165).

While praising AS for its attempts to address both “scientific clarity and practical utility,” Greenwood & Levin (2007) also point out the shortcomings of the approach. In particular, they note that AS assumes that individuals’ “natural” state is Model I defensiveness. This is problematic for a number of reasons. First, the narrow focus on defensiveness ignores the “richness of human motivations” beoynd defensiveness (Greenwood & Levin, 2007, p. 230). Second, the approach ignores the broader political, economic, and cultural context that may influence or determine Model I or Model II theories of action by placing the onus on individuals or organizations to create internal change. Finally, this view creates a chasm between participants (who are doomed to defensiveness) and action scientists who are presumed to have a special ability to transcend these limitations; this places the researcher in a special elite status, yet AS does not address this difference directly. Friedman’s (2009) previously referenced work on the “paradox of participation” shows that even experienced AS researchers are not immune to acting out Model I theories of action, and glossing over implicit power differentials between researchers and participants can undermine participatory relationships. Thus while AS holds significant promise as an approach to address difficult to solve and unique organizational and social problems, these criticisms point to the need for more reflective work in the vein of Friedman (2007) to develop AS theory further.

Greenwood, Davydd and Levin, Morten. 2007.  Action Science and Organizational Learning, in   Introduction to Action Research, 2^nd Edition.  Thousand Oaks, CA:  Sage, pp  223-235.

Friedman, Victor.  Action Science:  Creating Communities of Inquiry in Communities of Practice.  Chapter 19 in The SAGE Handbook of Action Research, 1st Edition, ed. by P. Reason and H. Bradbury. Thousand Oaks, CA:  Sage, 159-170.

Friedman, Victor.  2009.  The Paradox of Participation in Action Research.  Action Research. 7(2)263-290.

I sometimes wonder whether academic writing has any purpose other than to 1) exclude and create a class of “experts” that have legitimacy and power (check out this great TED talk on when experts are warranted and when they’re dangerous) and 2) to obscure fuzzy thinking in jargon so that it can’t be exposed as such.

I’ve been reading William Zinsser’s classic On Writing Well and trying to apply it to my own writing (it’s a process…. :/)  I find that I’m sometimes able to translate ideas I come across in academia and bring them to everyday conversations, but more often than I’d like (and especially when I’m still working out an idea, or still unclear) I slip into using big words to say not much of anything.

Why do I (why do we as scholars) write the way I (we) do? How might changing the way I (we) write change the way I (we) think?

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FoodLab Detroit is a network of entrepreneurs supporting one another in developing businesses with a “triple-bottom-line” (social environmental and financial). FoodLab was founded at a small informal gathering of peers in January 2011; by August, the group had grown to nearly 30, adopted a charter, and created a steering committee. As of February 2011, we have 73 entrepreneurs on our online listserve and engage in a broadening portfolio of activities including regular meetings and networking events, business planning workshops, coordination of shared use kitchen space and other resources, and advocacy through speaking events and engagement with community partners. The organization participates in Detroit’s good food movement, a meta-movement comprised of diverse sub-movements united by the recognition that “today’s food and farming economy is ‘unsustainable’ – that it can’t go on in its current form much longer without courting a breakdown of some kind.” (Pollan, 2010). The organization is also a part of a movement to “reimagine” the city of Detroit. FoodLab members grapple with questions about GHGs and energy use, how to support local growers and connect people to their food, but also how to create more living-wage jobs, use vacant space, rebuild neighborhoods, connect an otherwise largely segregated city, and build a more participatory, responsive, and democratic community.

Our vision is to build a “network of thriving, diverse locally-owned food production, processing, and retail businesses that contribute to the well-being of our communities and are collectively committed to increasing healthy, green, fair, and accessible food options in Detroit area.” In service of this vision, we support nascent entrepreneurs in order to help them develop socially and environmentally conscious businesses that can be sustained over time. One of our primary strategies is helping to build relationships between entrepreneurs themselves and entrepreneurs and relevant external stakeholders and service providers. As FoodLab grows, how can research help us design more effective activities within this broad strategy?

This essay describes how Davidsson and Honig’s (2003) study of nascent entrepreneurs legitimizes FoodLab’s focus on relationship-building and offers suggestions on how network analysis (to which the authors allude) could provide even more nuanced and useful guidance. I begin with a summary of the authors’ findings on the effects of social capital on early-stage entrepreneurs; I go on to examine how their approach, despite its focus on the importance of relationships and its informal invocation of networks, differs from network analysis; I conclude with examples of how FoodLab could use network analysis to inform what structures of relationships are most beneficial to the development of early-stage social entrepreneurs, and how different activities might foster particular types of structure.

Social capital as a predictor of entrepreneurial “success”

How do different sorts of non-financial capital affect entrepreneurial success? Specifically, Davidsson and Honig (2003) measure the extent to which an individual’s stock of human and social capital can predict three stages in the entrepreneurial process: 1) whether or not she engages in nascent activities; 2) the frequency of her “gestation” activities (e.g. writing a business plan); and 3) first sale or profitability of the business. We will focus primarily on their findings related to social capital.

Researchers collected data from 380 nascent entrepreneurs and 608 non-entrepreneur control participants via an initial phone interview, then followed up with entrepreneur-participants after 6, 12, and 18 months to gauge the life of the venture over time. The data supported the claim that individual social capital is strongly associated with reaching all three stages in the entrepreneurial process (see Figure 1). While the authors characterized certain measures as “strong” versus “weak” ties (e.g. family bonds versus business network bridges) and acknowledged the theoretical difference between the two, data did not support claims about the effect of one type of tie versus another on the entrepreneurial process. Overall though, social capital did appear to explain a greater percentage of entrepreneurial success human capital (including formal education and attendance at business classes), especially when it came to achieving a first sale or profitability. Specifically, the authors found that

• Having parents in business, being encouraged by friends or family, or having close friends or neighbors in business increased the likelihood that someone would become a nascent entrepreneur.
• Being a member of a business network, contact with an assistance agency, being a member of a startup team, being encouraged by family or friends, having close friends or neighbors in business, and being married increased the rate at which entrepreneurs engaged in gestation activities.
• Finally, only one variable reliably predicted whether or not an entrepreneur would achieve sales or profitability within the 18-month study: whether or not the entrepreneur participated in a business network.

The authors highlight that connection with an entrepreneurial assistance agency did not necessarily correlate with whether an entrepreneur made an initial sale or achieved profitability within 18 months. Based on this, they argue,

[Social] relations are more important than maintaining contact with assistance agencies, or even in taking general business classes. […] The facilitation and support of business networks and associations may provide the most consistent and effective support for emerging businesses. […] Furthering our understanding of these specific nascent networks and learning how best to facilitate them represents an important activity for future entrepreneurship research. (P. 324-325)

As a nascent network, FoodLab implicitly recognizes the value of social capital and relationship-building. If Daviddson and Honig’s (2003) findings help to justify our existence and general approach, can they also lend more specific insight into how we should design and structure our activities?

Social capital as an generalized individual attribute versus specific relationship

While this particular study suggests that various relationships, and business networks in particular, can play an important role in entrepreneurial emergence, it does not explain the process by which these networks have an effect. The business network, and the social capital it represents, is a black box. In order to understand how a business network affects an entrepreneur (and not just that it does somehow) we would need first to understand the specific kinds of social capital or ties that are created in the context of a business network, and also to re-imagine social capital as a structure of relationships rather than an endogenous characteristic of an entrepreneur (e.g. membership versus non-membership).

Neal (forthcoming) points out that describing a network as such without engaging in network analysis tells us “very little about what networks are or how they work, frequently because they do not identify exactly who or what is connected or in what ways” (p. 5). In the case of Daviddson and Honig (2003) we see that entrepreneurs who belong to a business network are more likely to achieve a sale or profitability. The authors assume that this is because participation in a business network affords entrepreneurs with more bridging (rather than bonding) capital which Granovetter (1973) and others have suggested is important for the diffusion of new ideas and innovation. This assumption may be true, but there also may be instances in which networks (or dense clusters within networks) provide entrepreneurs with the bonding or “strong” ties that might foster exchange of resources or reinforce norms of behavior (e.g. calculated risk-taking or opportunism) that increase the likelihood of success. Rather than make a priori assumptions, we could define and measure specific ties within a network in order to understand more clearly how the nature and structure of relationships surrounding an entrepreneur contribute to success. Some specific examples of the sorts of ties that might develop within a business network include advice-giving, information or opportunity sharing, business partnership or collaboration, emotional support, inspiration, motivation, or emulation.

This approach would also shift focus from the individual to relationships as the unit of interest, and imagine social capital as a structural pattern of relationships (many or few, dense or thinly spread, reciprocal or not?) rather than an individual characteristic (does someone have it, or not?) Traditional approaches that emphasize personal attributes have a number of drawbacks. For one, they “treat each social system member as an astructural independent unit” which “assume(s) random linkages,” whereas in reality, relationships are not random (Wellman & Berkowitz, 1988, p. 31). Entrepreneurs may exhibit homophilic tendencies along characteristics like race, gender, and  age, as well as industry and level of experience. An emphasis on categorical attributes also creates false groups (for example, people who belong to a business network versus those that don’t) and ties these categories to certain outcomes.

These groupings do not get at the root of the matter. FoodLab entrepreneurs will not succeed because they belong to FoodLab, but because of the specific patterns of relationships they might build as a result of membership. The categorical approach may be expedient, but has less explanatory power and may lead to false conclusions. By actually measuring an entrepreneurial network, we can understand how certain types of social capital as evidenced in particular structures of relationship might facilitate diffusion of information versus actual adoption of new practices (Neal et al., 2011). By comparing more than one network, comparing the structure of an informal social network with an intentional business network, or comparing the effect of different activities in the same network over time, we might understand what types of programs and activities foster what type of social capital to what ends.

Future research: social capital and the individual, social capital and the group

In order to inform FoodLab’s strategic direction, we need to know more about:

1. How different network structures (aka types of social capital) lead to different outcomes. [IND VAR: network structure, DEP VAR: entrepreneurial outcomes]
2. How different activities lead to different network structures (aka types of social capital) [IND VAR: activities, DEP VAR: network structure)

In part one, we might ask questions like, do we prefer a more densely clustered or more loose network? Do reciprocal relationships matter? What effect do bridging versus bonding ties have on outcomes? In part two, we might ask things like: how does operation of a listserve versus in-person meetings affect the structure of relationships that form within FoodLab? How does intentional recruiting of diverse participants affect our network structure?

Borgatti (1998) gives some suggestions on using network measures to describe an individual’s social capital. He suggests looking at network size, density, heterogeneity, compositional quality, effective size, constraint, closeness, betweenness, and eigenvector values. In this case, we would measure the ego-networks of various entrepreneurs and see how they correlate to various entrepreneurial outcomes. However, Borgatti (1998), in line with Coleman (1988) recognizes that social capital doesn’t only belong to an individual, but can be construed as a public good external to the individual and contained within the broader group.

[My thinking on the exact measures I might look at is still in the very very baby stages... as my prof Zach Neal pointed out, there's no point throwing all these measures around if they aren't getting at something we care about (in his words, they need theoretical grounding.. in my words, they need a grounding in measuring some value we care about)]

Entrepreneurism is seen as a uniquely individual pursuit. Why might we be interested in measuring the overall social capital within a group of entrepreneurs? For one, Coleman (1988) argues that even when social capital doesn’t accrue immediate or apparent benefits to the individual, it can benefit a community as a whole by increasing the stock of overall obligation, expectation, and trust, thus facilitating future interactions. Measuring the effect of relationships on an individual entrepreneur’s success would not account for this.

Also, in the case of FoodLab, we are interested not only in supporting the individual success of businesses in creating social, environmental and financial value, but also in fostering a set of shared norms (e.g. a commitment to social and environmental values). We recognize the advantage of fostering closure within the group to facilitate trust, but also in bridging between otherwise disparate clusters of entrepreneurs (and entrepreneurial allies) to encourage innovation and facilitate more effective collective action. Students of the food movement in the US have commented on this bridging capacity as one of the major strengths of the movement (Hassanein, 2003; Starr, 2010). This shift from considering individual outcomes to outcomes for communities or groups marks a significant difference between traditional entrepreneurship and social enterprise, or enterprise in the service of social change (Thekaekara & Thekaekara, 2006). Systematically measuring FoodLab’s network and linking structural methods to outcomes for individual entrepreneur and for the broader community will be useful in articulating and demonstrating our value to members and supporters, as well as in guiding the mix and design of programs and activities.

Works Cited

Borgatti, S.P., C. Jones, and M.G. Everett. 1998. “Network measures of social capital.” Connections 21(2):27–36.

Coleman, J.S. 1988. “Social capital in the creation of human capital.” American journal of sociology 95–120.

Davidsson, Per, and Benson Honig. 2003. “The role of social and human capital among nascent entrepreneurs.” Journal of Business Venturing 18(3):301-331. Retrieved February 12, 2012.

Granovetter, M.S. 1973. “The strength of weak ties.” American journal of sociology 1360–1380.

Hassanein, N. 2003. “Practicing food democracy: a pragmatic politics of transformation.” Journal of Rural Studies 19(1):77–86.

Neal, J.W., Z.P. Neal, M.S. Atkins, D.B. Henry, and S.L. Frazier. 2011. “Channels of Change: Contrasting Network Mechanisms in the Use of Interventions.” American Journal of Community Psychology 1–10.

Starr, Amory. 2010. “Local Food: A Social Movement?” Cultural Studies, Critical Methodologies, 490.

Thekaekara, M.M., and S. Thekaekara. 2007. Social Justice and Social Entrepreneurship: Contradictory Or Complementary? Skoll Centre for Entrepreneurship, Saïd Business School.

Wellman, B., and S.D. Berkowitz. 1988. Social structures: A network approach. Cambridge Univ Pr.

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[1] Including a control sample allowed researchers to test how human and social capital affected whether or not an individual engaged in entrepreneurship at all. The longitudinal design sidestepped the problem of “success bias.” Rather than only measure sustained or successful activity, the data also captured “efforts that fail or are abandoned at early stages,” and shed light on the effect of education and relationships at various stages of the start-up process (p. 311). These two features of the research design set this analysis apart from other research on the emergence of new enterprise, which generally employ cross-sectional data on early-stage businesses.

Some quick thoughts this morning when I came upon an interesting graphic on strategies for on-farm resilience from a project in the area where I used to farm. I love the idea of resilience versus growth as a measure of sustainable development AND personal development.

The Farm Resilience project describes resilience as “a community’s ability to anticipate, adapt to, and successfully overcome what usually amounts to unanticipated, harmful events. Every community faces threats. These threats may come from nature, rather the natural environment, from economic forces within the community, or from external social policies and programs. The most challenging threats are often a combination of all of these. Resilience is the ability to provide the necessary physical, social, cultural, and economic structure for members to live, work, and thrive in the face of chronic and emerging threats.”

I’ve been interested lately in the way that positive action emerges from crisis, but if we remain in a crisis frame, I think we tend to limit our realm of action to building systems capable of adapting to that particular crisis rather than considering that we might also think about this in the reverse… how can we build a system that’s better positioned to take advantage of natural energy (whether you think of low-entropy natural capital, or life-force/Qi, or some other kind of energy that I don’t yet know about).