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Social networks enable innovation. However, social network analysis of Australia’s innovative efforts has thus far been limited.

This research, a joint project between the United States Studies Centre (USSC) and LinkedIn, is one attempt at tackling that challenge. For this project, we looked at LinkedIn connections between start-ups, start-up founders, and venture capital firms in Australia, New Zealand and the United States as proxies for social network connections. We limited our focus to agricultural technology (AgTech) networks, building on prior seminal research from USSC on Australia’s AgTech industry evolution and benchmarking.

We are proud to present one of the first in-depth analyses of a relational network in the VC-entrepreneur economy using the rapidly growing AgTech market as an exemplar.

Australian AgTech networks are not only behind the United States in cohesion and interconnectedness, but they also trail New Zealand in cohesiveness as well as comparative connections to the United States.

While deliberately limited in scope, the data is striking. Australian AgTech networks are not only behind the United States in cohesion and interconnectedness, but they also trail New Zealand in cohesiveness as well as comparative connections to the United States. Australia’s near neighbour has a fifth of Australia’s population yet is somehow performing better in building ties to the world’s largest AgTech market.

To address Australia’s AgTech challenges, we conclude this report with forward-thinking policy recommendations.

We thank LinkedIn, particularly the talented Joel Van Veluwen, for the many hours put into making this research possible.

Executive summary

Social networks are an integral component of entrepreneurial ecosystems.

From Silicon Valley to Israel, dense, globally-minded networks have facilitated the movement of talent, attracted funding, directly affected collaboration and, ultimately, facilitated innovation. Multiple studies indicate shared cultural and physical ties between geographies are key to building some innovation ecosystems.[^1] There is a growing recognition that intra-network density is not the only indicator of innovation success. There is strong evidence to suggest that the best innovation occurs within dense networks which contain actors that are open and receptive to external and novel knowledge flows. The inverse appears not to be the case. It has long been held that networks which are geographically removed from industry-relevant clusters have significantly less innovative output, even when they are located in manufacturing hubs.[^2]

This study builds on an academic body of research into social networks between centres of innovation capital and geographically distant entrepreneurial ecosystems seeking funding. It aims to analyse this connection and ask the following questions: How developed are Australia’s networks in particular innovative sectors? Are Australian networks well connected, or are Australia’s entrepreneurs working in silos? And ultimately, how can policy help build Australian networks further?

According to our analysis of proprietary LinkedIn data on one of Australia’s burgeoning innovative sectors, AgTech (where agriculture meets technology), Australia’s networks are less cohesive and interconnected than US AgTech networks. In comparison, New Zealand’s AgTech networks appear to be smaller yet more cohesive, interconnected and — critically — more connected to the United States AgTech networks. As the largest AgTech market in the world — estimated to be valued at US$10.2 billion,[^3] and accounting for roughly 65 per cent of global AgTech investment[^4] — connections to the United States are vital but Australia is clearly missing out.

Key findings

  • The US AgTech network is bigger but also denser than Australia’s. The US network is more than three times as interconnected as the Australian network.
  • Australia’s AgTech network is dominated by a few key players. Both the United States and New Zealand AgTech networks are more evenly distributed.
  • New Zealand does more with less than Australia. New Zealand’s smaller AgTech network is not only more cohesive and interconnected than its Australian counterpart, but its total number of connections to the United States networks is on par with Australia’s, despite its smaller market size.
  • The AgTech ecosystem in Sydney is more connected than any other Australian city. While it is unsurprising that Melbourne and Brisbane AgTech networks are smaller than Sydney’s, it is surprising that they are considerably less connected.

Policy recommendations

  1. More cohesive and coherent advocacy for Australian AgTech.
    Australia and New Zealand can both expand efforts to collaborate across the Tasman as well as leverage their unique strengths in AgTech in concert. Already a long distance away from most other markets, the two countries are more likely to draw attention when considered together rather than distinct from each other.
  2. Stronger engagement of venture capital as a key component of building networks and growth
    Beyond AgTech, Australian venture capital per capita across all sectors of the economy is a third of New Zealand’s and an eighteenth the size of the United States’.[^5] Foreign venture capital firms can help address this challenge. But they also supply more than money, providing global networks and expertise in how to scale. Ranging from financial incentives to government-sponsored trips, the Australian government can learn from the efforts of other nations like Israel and New Zealand in attracting and welcoming such firms.
  3. Greater support for AgTech from the Australian government
    The Australian government has accomplished a lot on AgTech but it can do more. Austrade can follow New Zealand Trade and Enterprise’s lead and consider subsidising the full costs of trips by qualified AgTech funders from overseas. Such funders could provide both the capital and know-how of global best practices.
  4. A wider understanding of the role of AgTech
    AgTech is part of the knowledge economy and is, therefore, not limited by crop or land sizes — just like any other technology, the whole world is the market. The government should approach AgTech with that mentality and widen its understanding of AgTech, making particular note of its significant economic potential.

What is social network analysis? What are “nodes”?

Social network analysis is exactly what it sounds like: the analysis of social networks. Used for everything from identifying potential terrorists to determining “influencers”, social network analysis is a sociological method.

The method defines social networks in terms of nodes (individual actors, people, or entities within the network) and the ties (relationships, links or interactions) between them. The nodes in our networks are AgTech companies and funders. The ties between them are established by considering the LinkedIn ‘connections’ between the individual sub-nodes of the network: the employees, board members and founders of those companies and funders.

In terms of describing the nodes and ties on the social network maps, there are two primary variables: the centrality of nodes and the density of the ties.

The centrality of nodes indicates the importance of nodes in a network. Stanford University, for example, would likely be the most central node of any social network analysis of Silicon Valley because so many key individuals in Silicon Valley either studied, worked, or lived on Stanford’s Palo Alto campus.

The density of ties is the number of actual connections divided by the maximum potential number of connections. This ratio gives an indication of network cohesiveness. The denser the network, the closer the output of that ratio will be to the number one.

For example, consider a network with six organisations and 15 links between them (Figure 1). In this simulated example, the maximum potential number of links is 15. A graph with a link density of one is also known as a complete graph. In other words, everyone is connected to everyone. As the link density decreases, the cohesiveness of the network declines. Take the same six companies, now with seven links. The link density is now 0.5. Evidently, there are far fewer links between companies. If the companies had no connections, there be a link density of 0 and they would no longer be considered part of a network.

Figure 1: Density of network

This simulated example of a social ecosystem consisting of a set of actors and the existing ties between them could also be a representation of a venture capital social network. In this case, the presence of a tie between any two venture capital firms indicates they have at least one investee company in common: that is, that both VC firms cooperated in the financing of the same company or companies. That connection is indicated in the figure by a tie between two dots.

One previous example of social network analysis studied the network map of Silicon Valley during the 1995-1998 period in this way.[^6] There were 111 firms and 312 links between the firms. The 312 connections represented any time a connection was forged, not the number of total times a co-investment was made. The resulting link density of 0.05 is low — quite a few VC firms had not co-invested in a company over the three years.[^7] Yet there was a subset of the network that was highly dense — they were the important, key players in the network.

This framework measures the importance of individual firms by looking at the number of connections the firm has to other firms that are highly connected in the network. A Silicon Valley firm may have been connected to many other Silicon Valley firms, for example, but if these were isolated connections then they did not matter. Ultimately, start-ups want to be connected to funders who are likely connected to a large number of firms and other potential funders in the network. Social network analysis offers one a measurement of a firm’s success in making such connections.


To conduct our social network analysis, USSC gave LinkedIn a list of key individuals who founded, funded or led AgTech start-ups in the United States, Australia and New Zealand. To give an indication of the strength of the US network vis-à-vis the other AgTech networks, we analysed the number of connections between the individuals within each self-selected start-up and funding entity.

Our conservative selection process was as follows: We chose every AgTech entity we could confirm was both AgTech focused and active as of 2019 in the three countries. Some definitions of AgTech, also referred to as ‘Agrifood Tech’, include technologies relating to consumer-facing components of the agricultural supply chain, such as restaurant and retail innovations — think e-commerce-enabled meal kits such as Blue Apron or HelloFresh. The criteria we used to select firms do not include these sorts of technologies.

Using this definition, USSC used its prior research into AgTech to make lists of active AgTech funders and start-ups in the United States, Australia and New Zealand. It then gave these lists to LinkedIn for it to mine its proprietary data for connections between the lists. At no point did LinkedIn give the United States Studies Centre any private data of LinkedIn users — all data was grouped together by company.

This selection process found a total of 84 AgTech funding and start-up organisations in Australia, 49 such organisations in New Zealand, and 124 in the United States. The AgTech employees and board members of either start-ups or funders totalled 631 in Australia, 609 in New Zealand and 2,467 in the United States. Our analysis encompasses the employees and board members of each funder and start-up — although it should be noted that the data that LinkedIn gave to USSC did not give the connections of each individual.

There is, of course, the potential that one company could have a ‘connection’ with another in the absence of a LinkedIn connection. Attempting to prove the negative in this case is prohibitive when analysing three geographically distinct and dynamic networks.

The inverse is also true. A LinkedIn connection between two individuals of two AgTech firms does not infer that those two firms, or even those two individuals, will ever collaborate in a meaningful way.[^8]

When taken in isolation, the data presented here is limited by these and a series of other external factors, including, for example, whether individuals update their profiles, or whether there are individuals who do not use the platform at all. But as LinkedIn is the most-used online professional networking platform, and AgTech is a highly digitally-literate industry, we see it fitting to use the data as representative and as another block in our ongoing research into innovation and networking in the Australian AgTech sector. Our previous findings regarding the flows of venture capital and attitudes towards innovation allow us to bridge some of these methodological gaps and to use this data as a soft measure of networking proactivity in and across the three markets.

What did our analysis of AgTech networks find?

The US AgTech network is more than three times as interconnected as the Australian network, with AgTech start-ups in Australia having link density of 0.11 compared to a 0.38 link density for their US counterparts.

Since links have a distinct connection — whether directly in joint ventures or peripherally by sharing contacts, link density can also be explained as a measure of the cohesion of the network. The sheer difference in scale between the United States and Australia is made most clear when considering the median number of connections per Australian start-up is 11 while the median number of connections per US start-up is 69.

Figure 2: AgTech in-country networks on LinkedIn