Network Effects and Implications for Local Governments

December 19, 2022

In today’s world, the word “network” is most likely to evoke references to social media. Twenty years ago, the same word would likely induce thoughts of the expansion of broadband, fiber and wireless telecommunications to business and the public. Put simply, a network is a connection of at least two things and, generally speaking, the larger the network, the more power and value it has.

Local Governments Function Like Collections of Networks

A network’s power is generally observed in its effects. A “network effect,” then, is the phenomenon whereby a product, service or community gains or loses power and value based on the number of people who use and participate in it. In the context of social media, services such as Twitter and Facebook experience strong network effects, both positive and negative, based on usership, with the platforms experiencing large swings in value depending on user opinion and engagement. In the context of governments big and small, they can experience and facilitate positive network effects by investing in expansion of the networks they create and maintain.

Local governments function like collections of networks, and the development and use of data analytics has the potential to assist in reconnecting neighborhoods with surrounding communities and regions, enabling or restoring equitable levels of goods and services, and conceiving win-win-win opportunities in poorly connected areas. By fostering inclusion and connection between people, families and neighborhoods, the local government networks can benefit from increased influence, power and value. Well-connected and maintained communities, just like the latest social media trend or platform, entice people to join it, to stay in it and to engage with it. Conversely, areas that are isolated from a larger network suffer a loss of power and value because no one wants to join it, those who are there wish to leave, and without change, the area will eventually deteriorate severely.

Network Effects

Network effects are primarily caused by the change in the benefit obtained from a good or service when other consumers or users consume the same good or participate in the same network. The value of a network is directly related to the number of connected users as determined by Robert Metcalfe, writing in Forbes, and David Reed, writing in Harvard Business Review. Governments recognize the tremendous power of networks and accordingly regulate several types of networks through operation of various agencies, such as the Federal Communications Commission, Federal Energy Regulatory Commission and Federal Trade Commission, among others. While network effects are now most often associated with digital economies, network effects have enormous implications for local governments, as well. “Cities are more than governments, they’re networks,” according to Bruce Katz, Centennial Scholar at the Brookings Institution.

Impact of Local Governments

Local governments impact network effects through use of many powers: zoning and entitlements, transportation, utilities, education, law enforcement and taxation, among other areas. Network effects facilitated by local governments can be reflected in various metrics. The impact of a local government on network effects can be observed in collected data in numerous areas such as:

  • Population and households
  • Home sale pricing and volume
  • Building permits
  • Tax revenue
  • Traffic counts
  • Utility usage
  • Crime reports

Local governments can use data analytics to understand strengths, weaknesses, opportunities and threats and model the impact of investments, policy changes or other actions to help inform decision making pertinent to network effects.

With the Department of Transportation’s recent announcement of an initiative and funding to remove the scarring that bad infrastructure planning, or intentional dissociation and isolation of groups has caused, it has been recognized at the highest levels of government the power that government can have to induce positive network effects. While the City of Akron is currently evaluating how to best approach the reactivation of a portion of the city impacted by its Innerbelt, examples of the success that these initiatives can have can be seen throughout the country.


In 2007, the City of Boston completed the “Big Dig”– a massive reimagining of the traffic flow and location of Interstate 93 through the heart of downtown Boston. Over the course of a decade, the massive highway, which had previously cut the North End in half, was routed through a series of new underground tunnels, restoring the connectivity of the city and implementing new walkable routes and green spaces. Since its completion, the Big Dig has resulted in massively improved traffic flow through one of America’s oldest cities and has led to the creation of jobs and an increase in private investment.

San Francisco

On the other end of the country, in 1989, the Loma Prieta earthquake heavily damaged the old Embarcadero Freeway (also known as California State Route 480) in San Francisco, reopening a longstanding debate about the future of the neighborhood and what to do with the highway. It was determined that the best option was to remove the freeway and restore the Embarcadero to a walkable space, unmarred by monstrous concrete pillars and the roar of traffic overhead. Since the redevelopment of the Embarcadero, values in adjoining neighborhoods soared by 300%, with many new developments seeing investment, including the restoration of the iconic Ferry Building.

While it was previously considered that enhanced urban networks connected by superhighways would bring prosperity, it has turned out that a more nuanced approach, focusing on the connection, integration and investment in communities and common gathering spaces has been the more successful approach.

Negative Network Effects

Network effects can be negative; however, there are ways to manage through negative network effects. One example of negative network effects is congestion. The overabundance of choice or usage can lead to opposite intended effects where less goods are used or less users participate in a network. A practical example of congestion is rush hour on highways, causing people to seek ways to avoid certain routes or areas. Another example of negative network effects is dissociative groups, or groups with which others do not wish to be associated. Dissociation of a group causes a decrease in usage of goods or services to those groups. This lack of usage can subsequently lead to a lack of supply, exacerbating and perpetuating a cycle of dissociation. The horrific effects of redlining – the financial network’s withholding of investment in areas defined by the ethnicity of residents – are still observable and lingering in areas of Cleveland and other major cities to this day.

Connections Matter

Connections are vital to a network’s function. Healthy and functional connections ensure the flow of benefits within a network. The axiomatic importance of location in real estate and economic development is directly related to the presence or absence of network effects. All things being equal, sites that are more centrally located with respect to various networks tend to be more valuable than sites that are less centrally located with respect to the same networks whether related to roads and highways, utility infrastructure or civic and cultural institutions, to name a few. The Opportunity Corridor in the Cleveland has tremendous potential to better connect and introduce positive network effects to an area of Cleveland that has long suffered from negative network effects. What was once the largest concentration of vacant property in the City of Cleveland is now poised for significant growth, in large part due to being better connected with the surrounding community and region.

KJK will continue to monitor network effects and the implications for local governments. If you have any questions, please contact KJK Economic Development & Incentives Partner Richard Morehouse (RAM@kjk.com; 216.736.7292).