Government Telecommunications Regulation and Incentive … · 2017-03-01 · GOVERNMENT REGULATION...

Government Telecommunications Regulation and Incentive Programs: The Need for Regulatory Recalibration in a Broadband Era

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ABSTRACT

Federal, state and local government have focused significant resources to subsidize and encourage industry to invest in building out broadband infrastructure to bridge the “digital divide” among rural and poor areas of the U.S.

These broadband initiatives build upon a rich history of telecommunications industry evolution, regulation, and more recent technology advances. Government policy created a regulatory environment based on natural monopolies and focused almost exclusively on the supply side of broadband, ensuring connectivity to every household.

Government regulation has been focused on controlling anti-competitive behavior of large telecommunications monopolies and protecting consumer welfare. Today, with new service delivery paradigms, expanded digital communications services, and new forms of competition, these regulatory practices are now in question. The traditional views of universal service and technology adoption are challenged by the diversification of access technologies, new industry dynamics that result in new models for competition, and regulatory jurisdiction and oversight. This paper explores the regulatory environment, potential areas of reform, and implications to universal service and broadband.

Keywords: Broadband, Regulation, Government Incentive Programs, High-speed

Internet

GOVERNMENT REGULATION AND INCENTIVE PROGRAMS: THE NEED FOR REGULATORY RECALIBRATION SECOND DRAFT

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This paper discusses two distinct elements of the current telecommunications

environment: the policies and regulations that have dominated the birth and growth of the

current telecommunications environment and the current imperatives and programs that

address remaining challenges in today’s environment. Section 1 describes the current

regulatory environment, reflecting path dependencies focused largely on a monopoly

environment and supply side economics. While it has allowed an industry to grow, it

created the adverse impact of limiting both innovation and investment. New technologies,

new market entrants, and interdependence of other critical infrastructures mandate that

regulation must migrate from ex ante regulation inherently based on a monopoly

environment to ex post regulation to protect against anti-competitive behavior and ensure

consumer welfare.

Section 2 describes the premise of “universal service” and the current inequities associated

with access to high-speed information services, or “broadband,” services. Broadband is

considered essential to the country’s economic growth and robust consumer services. Left

to market forces, industry has underserved rural and low-income areas, and the lack of

service has put these areas at risk of falling further behind. Government resources have

largely focused on the supply side of broadband penetration, recognizing that availability

will enable adoption. The second section addresses both the broadband “divide” as well as

government initiatives to help foster the supply of broadband services.

1. U.S. TELECOMMUNICATIONS REGULATION: THE LONG ROAD AND NEW DIRECTIONS

U.S. government regulation over the past century has helped to foster and control

infrastructure development in transportation, energy, and telecommunications. It has also

taken a role in managing other industries including agriculture, commerce, banking,

education, and health care. While these infrastructures have grown and developed, they


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have become more complex and difficult to regulate. Information asymmetries between

government and industry have led to forms of regulatory capture to close the gap, but often

bias regulation. This bias can lead to restrictions on market entry, suppression of

innovation (protecting the incumbents’ capital investments), and market inefficiencies. It

has had an adverse impact in limiting broadband infrastructure in rural and low-income

areas, as carriers did not realize the return on investment. While independent carriers

eligible for subsidies fared better, price cap regulation has made incentives to invest more

difficult.

This section characterizes the regulation path dependencies, the pressure points for

change, and the direction of change that is necessary in a highly dynamic technology

environment. This section also discusses the inherent shortcomings in developing

regulatory and incentive programs based on legacy technology and monopoly constructs,

and introduces new potential regulatory concepts to address the rapidly evolving

environment.

Introduction.

U.S. telecommunications regulation over the past 100 years set the table for today’s

environment. U.S. telecommunications policies have centered on the conviction that only a

natural monopoly could achieve economies of scale to deliver affordable, ubiquitous

telephone service. This view led to a regulatory environment that protected that monopoly

from new market entrants, allowed network providers relief from antitrust regulation to

acquire other competitors, and created a more integrated network. Internal subsidies were

permitted to maintain artificially high prices in some market segments (long distance) to

help offset the costs in other segments (local telephone service). Local regulation provided

few incentives for monopolies to upgrade their infrastructure and granted these


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monopolies broad leeway to capitalize and utilize local rights of way. To date, regulation

and incentive programs have largely focused on the supply side of telecommunications –

ensuring affordable and ubiquitous telephone service.

The information asymmetry between government and industry allowed for a form of

cognitive capture – a reliance on industry to provide the economic rationale and

information necessary to implement any changes in regulation and rates. The government

would codify into law its practices of enabling and protecting the telecommunications

natural monopolies. For example, to influence government regulators, AT&T used

respected economists to create and publish a highly regarded academic journal, The Bell

Journal of Economics and Management Science (now the Rand Journal), to provide insights

into regulatory economics, ultimately influencing government regulation.1 Government

dependence on industry created an environment that ultimately stifled certain kinds of

investment, limited competition, and guaranteed investors healthy profits for over a

century.

The path dependency of policy and regulation at the federal, state and local level have

created a difficult dynamic in today’s environment of rapidly emerging technologies,

alternate means of access, and new industry players. The emergence of microwave

transport, cable television and cellular telephones changed the fundamental premise that

services could only be delivered through one central network provider. With new means of

access to voice, data, and video services, businesses and consumers have more choices and

more competitive pricing to meet their needs. As a result of court rulings in recent years,

changes in the regulatory environment have manifested as government agencies try to

1 Crew, Michael A., and Paul R. Kleindorfer. 2012. “Regulatory Economics and the Journal of Regulatory Economics: A 30-Year Retrospective.” Journal of Regulatory Economics 41 (1): p.11.


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anticipate technological changes (both in terms of capacity and capability) as well as its

role as a platform for new service innovations.

The Role of Federal Telecommunications Regulation

To understand today’s regulatory environment, it is critical to understand the

circumstances and conditions that created the inherent path dependencies. This section

provides key elements of the history of the regulatory environment and sets the stage to

understand the necessity for regulatory reform.

With the invention of the telephone in 1876 and the creation of AT&T, a series of patent

and regulatory milestones marked the evolution of industry over time. The expiration of

the patents in the mid-1890s ushered in an era of competition, but networks were

physically isolated.2 To complete a call, the originating subscriber must belong on the same

network as the called subscriber – the bigger the network the more calls that could be

completed. This gave rise to access competition, with each network provider seeking to

increase the number of households they could connect to maximize network size and

therefore attract still more subscribers. Businesses would often have multiple phone lines

connected to different networks to reach customers (and suppliers) on those networks.

Access competition created a race to connect more subscribers, with independent

telephone companies connecting many rural or suburban communities while the larger

AT&T focused on the high margin urban areas. It put a premium on being the first to

connect to a subscriber and put downward pressure on pricing to attract and maintain that

subscriber. It also provided incentives for connectivity between local exchanges (toll

lines).3

2 Mueller, Milton. 1993. “Universal Service in Telephone History: A Reconstruction.” Telecommunications Policy 17 (5): p.357. 3 Ibid. p.359.


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While access competition offered many benefits, it created a more fractured system. In

1907, AT&T suggested that “universal service” was needed to connect these disparate

networks as to allow end-to-end call completion.4,5 In the ensuing decade, state and local

government allowed widespread mergers and acquisitions, giving critical mass to AT&T. In

1921, the Willis Graham Act exempted telephone companies from antitrust regulation,

allowing AT&T to expand into a large scale, albeit regulated monopoly.6

The Communications Act of 1934 created the Federal Communications Commission, and

established the regulatory authority of federal, state and local governments.7 It crafted the

role of federal oversight of national resources (e.g., radio spectrum) and interstate

communications (e.g., toll), leaving the state utility commissions to govern intrastate

communications. 8 It also set up the standards for communications commerce to prevent

anti-competitive behavior to ensure monopolies are fair and equitable in transacting

commerce.

Deregulation with the 1983 Consent Decree (U.S. vs. AT&T) disbanded AT&T’s component

businesses (long distance, local, and product companies).9 Each of these components could

compete with one another and expand into broader, more diversified services (e.g., cable

television). More competition was thought to bring more diversity of services and lower

prices.

4 Ibid. pp.352-3. 5 Mueller, Milton. 1997. “Universal Service and the Telecommunications Act: Myth Made Law.” Communications of the ACM 40 (3): p.41 6 Mueller. 1993 p.365 7 73rd Congress. 1934. Communications Act of 1934. Title 47 of the United States Code. 8 Santorelli, Michael J. 2010. “Regulatory Federalism in the Age of Broadband: A U.S. Perspective.” Policy & Internet 2 (3): pp.102-103 9 Ibid. p.104


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Even with greater competition, local exchange carriers continued to maintain their

monopoly position and control access to the local loop, which was the sole connection to

households. Computer Inquiry III (1985) put in place a means by which competition could,

for a fee, access the local loop and provide direct services to subscribers.10,11 However,

because the government could not accurately estimate the cost of providing local loop

access, local carriers often engaged in predatory practices by setting high prices for these

local access arrangements, making it costly for competitors to lease access. It was both

capital intensive and risky for competitors to build out their own local access, so many

were forced to pay the inflated rates or search for other means of access.

Empirical research showed that if carriers are allowed to charge high prices for local loop

access, they are more willing to invest in high-bandwidth, high technology services, but this

has the adverse impact on affordability for leasing access by competitors. If carriers can

only recoup cost then they are less willing to invest.12 Regulators must not only strike a

balance between the two, but also encourage competitors to build out their own

infrastructure to ensure competition over the long run. In time, competitors successfully

implemented alternate means of access to the home through small aperture satellite

services, and eventually over television cable.

The Telecommunications Act of 1996 established the guidelines for interconnection and

opened the door for providers to connect with one another and share resources across the

network. It also established restrictions for the Regional Bell Operating Companies

10 Yoo, Christopher S. 2011. “Deregulation vs. Reregulation of Telecommunications: A Clash of Regulatory Paradigms.” Journal of Corporation Law 36 (4): p.856 11 Shelanski, Howard A. 2007. “Adjusting Regulation to Competition: Toward a New Model for U.S. Telecommunications Policy.” Yale Journal on Regulation 24: p.64, p.72 12 Yoo. p.863


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(RBOCs) to enter into partnerships with alternative providers of information or video

services, with the single exception of rural areas.

The 1996 Act did create new directions for regulatory oversight. Specifically:

“The Commission and each State commission with regulatory jurisdiction over

telecommunications services shall encourage the deployment on a reasonable and timely

basis of advanced telecommunications capability to all Americans (including, in particular,

elementary and secondary schools and classrooms) by utilizing, in a manner consistent with

the public interest, convenience, and necessity, price cap regulation, regulatory forbearance,

measures that promote competition in the local telecommunications market, or other

regulating methods that remove barriers to infrastructure investment.

The term ‘advanced telecommunications capability’ is defined, without regard to any

transmission media or technology, as high-speed, switched, broadband telecommunications

capability that enables users to originate and receive high-quality voice, data, graphics, and

video telecommunications using any technology.”13

These provisions set the stage for the modern era of regulation. The 2010 FCC Rulemaking

to “classify broadband internet access as an telecommunications service” allowed the FCC

to take a more expansive role in regulating broadband as an “information service.” For the

FCC, classifying broadband as a telecommunications service meant that it is inherently an

interstate service, limiting the states purview over the regulation of broadband. Even with

these provisions, the FCC allowed states to work with the federal government on universal

13 104th Congress. 1996. Telecommunications Act of 1996.


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service initiatives, and to exercise “core competencies in areas where they have direct

domain responsibilities.14

State and Local Regulation

While federal policy and regulation govern the broader anti-trust practices and use of

national resources (e.g., spectrum), state and local government also play a role in

regulating telecommunications services. Since provision of telephone services historically

relied on copper wire infrastructure owned by industry but traversing public and private

land, state and local regulators must ensure appropriate access and controls. State public

utility commissions (PUCs) implement regulations for local provision and pricing

structures (e.g. price caps) to ensure fair and reasonable rates. These PUCs were also

responsible for overseeing cross-subsidies among services (e.g., long distance and local

services). However, given that historically there has been no competition, fair and

reasonable rates are often determined through negotiation with the local network

provider, based on selectively disclosed costs.

For most of the century, state PUCs used rate of return legislation to regulate network

providers, allowing carriers to recoup a small profit for every dollar of cost. However, this

regulatory practice did not encourage cost reduction and fostered an over investment in

fixed assets.15 Beginning in 1987, the majority of states turned to price cap regulation to

ensure affordability of services. This practice incents operators to reduce costs (and keep

the profit) but does not necessarily encourage investment. Seo and Shin (2011) conducted

a study of 25 local exchange carriers (LECs) over the 1988-1998 time period and found that

price cap was a more effective means than rate of return regulation to encourage

14 Santorelli, Michael J. 2010. “Regulatory Federalism in the Age of Broadband: A U.S. Perspective.” Policy & Internet 2 (3): pp.110 15 Cambini, Carlo, and Yanyan Jiang. 2009. “Broadband Investment and Regulation: A Literature Review.” Telecommunications Policy 33 (10–11): p.562


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productivity growth and technological progress. However, they also found a distinct

difference in the size of investment and debt between network providers with broad and

deep resources vice those independent telephone companies that rely on rates to subsidize

investment. 16 State PUCs must make the trade between affordability and infrastructure

investment, which can be particularly important to small independents that most often

serve rural communities where investment is constrained by both the high cost to connect

and the relatively small size of the market.

A significant amount of research has focused on the implications of price cap regulation.

Sanyal and Bulan (2011) studied rate-regulated electric utilities and found that regulations

that increased regulatory risk and market uncertainty can materially affect firm leverage

and willingness to invest. 17 Graeme (2006) noted that rate-of-return guarantees

shareholders a return on investment, while price cap regulation shifts more risk to the

shareholders, which fundamentally changes investment strategy as a result of competition

uncertainties.18 Majumdar (1997) found that providers under price cap regulation

measurably improved efficiency; drawing the conclusion that rate of return induced

unnecessary capital investments.19 This is consistent with the shift of risk to shareholders

(and firm management) theorized by Graeme. These considerations must be factored into

the firm’s investment in infrastructure such as broadband.

16 Seo, Daigyo, and Jonghyup Shin. 2011. “The Impact of Incentive Regulation on Productivity in the US Telecommunications Industry: A Stochastic Frontier Approach.” Information Economics and Policy 23 (1): 17 Sanyal, Paroma, and Laarni T. Bulan. 2011. “Regulatory Risk, Market Uncertainties, and Firm Financing Choices: Evidence from U.S. Electricity Market Restructuring.” The Quarterly Review of Economics and Finance 51 (3): p.260 18 Guthrie, Graeme. 2006. “Regulating Infrastructure: The Impact on Risk and Investment.” Journal of Economic Literature 44 (4): p.968 19 Majumdar, Sumit K. 1997. “Incentive Regulation and Productive Efficiency in the U.S. Telecommunications Industry.” The Journal of Business 70 (4): pp.569-571


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Local regulation is typically manifested in controls over zoning and rights of way.20 As

network providers seek access to cable routes under highways or adjacent to pipelines, this

becomes the purview of local governments. More recently, demand for cell tower

placement has become a consistent agenda item for local zoning boards, as providers seek

to improved coverage to meet increasing demand from higher cell phone density. Creative

solutions such as cell towers disguised as pine trees and light poles at high school stadiums

have reduced the public push back regarding unsightly towers, but perceived health risks

from proximity to cell towers remain a local political hotbed.

Information Asymmetries and Regulatory Capture

The government must rely on information regarding industry dynamics, business capital

and operating costs to effectively regulate. Regulators must understand the dynamics of

the industry to ensure fair competition, ensure service coverage, and protect consumer

welfare. However, the information needed to establish price caps and make other

regulatory decisions is often proprietary to the regulated firms, and only shared when it is

in the firm’s best interests. These asymmetries create a reliance on industry knowledge

and disclosure that can create adverse impact on capital invested in broadband

infrastructure, competitive market entry, and consumer service rates.

To reduce information asymmetry, government uses several methods to gain insight into

cost and incentives for industry initiatives. Industry councils are organized to give a

unified voice to industry, providing responses to proposed rulemaking or lobbying on

behalf of industry. Interest groups of consumers have also formed to better educate the

consumer base as well as lawmakers and regulators on important issues of consumers.21

20 Santorelli. p.109 21 Holburn, Guy L. F., and Richard G. Vanden Bergh. 2006. “Consumer Capture of Regulatory Institutions: The Creation of Public Utility Consumer Advocates in the United States.” Public Choice 126 (1-2): 45–73.


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Using state utility consumer advocate data, Holburn and Vanden Bergh (2006) found that

democrats most often institutionalized consumer groups to advise on policy issues and had

a meaningful and significant influence on decisions.22 However, in a study on influence

regarding environmental interest groups, Laffont and Tirole (1991) showed that where

multiple interest groups are involved, they often compound the issue and create inefficient

solutions.23

Over time, a form of regulatory capture has taken place to reduce the asymmetry, in which

the regulated entities control the agencies that oversee them.24 In general, regulatory

capture is the propensity of the regulator to rule favorably or be lenient with restrictions

on industry. 25 This could come in the form of a “revolving door” in which regulators leave

office to take roles in the industry they regulate, or industry players take on regulatory

roles for a period of time before returning back to industry. This can lead to favorable

regulatory rulings for industry in exchange for future jobs.26,27

Regulatory capture is also influenced by institutional structure, specifically the length of

term for regulators. The longer the tenure of the regulator the less likely they are to be

lenient, although some evidence shows that in the final year of their tenure they tend to

make more favorable rulings, ostensibly in exchange for future employment. Elected

officials who rely on campaign contributions from powerful industry players can also be

influenced to affect laws and regulations that impact industry. Appendix A shows a table of

22 Ibid. p.56-66 23 Laffont, Jean-Jacques, and Jean Tirole. 1991. “The Politics of Government Decision-Making: A Theory of Regulatory Capture.” The Quarterly Journal of Economics 106 (4): p.1117. 24 Bó, Ernesto Dal. 2006. “Regulatory Capture: A Review.” Oxford Review of Economic Policy 22 (2): p.203. 25 Ibid. p.220 26 Ibid. p.214 27 English, William. 2014. “Economic and Ideological Corruptions of the Regulatory State.” Society 51 (3): p.264.


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players and descriptive characteristics and the types of information asymmetries that are

common.

Capture is not limited to state PUCs, but is evident in federal financial, energy, and

agricultural oversight as well. The more government relies on information gathering from

industry, the more intellectual and cognitive capture is possible by industry.28 Government

regulation and programs still largely follow paradigms established to control monopolistic

behavior, and the information asymmetry between industry and government has become

wider.

Telecommunication regulation has traditionally focused on controlling potential

anticompetitive behavior of monopolies, setting prices, and subsidizing access. With

increased means of access, expanding service alternatives and continuously emerging

technologies, ensuring fair competition and universal service has become more

sophisticated and complex. Service and access substitution (e.g., VOIP, email,

internet/social media services and wireless phones) have allowed greater competition,

suggesting government intervention should diminish. High administrative costs and the

inability of the government to predict any/all changes in industry dynamics and

technologies has led to significant inefficiencies and losses in consumer welfare. 29

Antitrust regulation against vertical integration should be relaxed as the empirical

evidence shows that consumer welfare is reduced with regulation.30 Government

regulation, based on history of natural monopoly rationale, often comes with the

unintended consequences of limiting new market entry and distorts effective competition.

28 Baker, Andrew. 2010. “Restraining Regulatory Capture? Anglo-America, Crisis Politics and Trajectories of Change in Global Financial Governance.” International Affairs 86 (3): p.655. 29 Shelanski. p.55 30 Brenner, Daniel L. 2010. “Creating Effective Broadband Network Regulation.” Federal Communications Law Journal 62 (1): p.58


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Regulatory Reform.

Regulatory capture will likely be more difficult as multiple industries contend for influence

or control. With many broadband providers and a diversity of service ecosystems that will

rely on broadband, there is no single interest group or focal point to gather information

and exert influence. The multiple layers and broad diversity of interests confound the

regulatory environment going forward. Anticipating technology changes and industry

dynamics and creating appropriate regulations is difficult if not impossible.31

Rapidly advancing technologies, co-dependent infrastructures, and continuing information

asymmetries has generated more calls for government to fundamentally change the way it

regulates – from trying to get ahead and “predict” industry behaviors (ex ante regulation)

to enforcement of egregious anti-competitive behaviors (ex post enforcement).32 Cases

such as Madison River Communications (in which they blocked those competitors using

voice over IP) make evident the role of government to intervene in these instances.33

The diversification of media and the services that are enabled by them fall under multiple

authorities of the federal government and jurisdictions of state and local government. This

will complicate oversight and regulation of broadband going forward. Different federal and

state agencies oversee the health care system, with the federal government funding and

establishing rules and policies on the national Medicare and Medicaid programs while

states administer these systems. While the Federal Energy Regulatory Commission (FERC)

oversees the federal energy standards and energy resources, state PUCs have jurisdiction

31 Brenner. p.76. 32 Shelanski. p.55 33 Brenner. pp.18-19.


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over energy utilities within the states.34 Information and consumer service providers such

as Google and Amazon must follow federal regulation from the Commerce Department

(NTIA, Consumer protection), and also follow state and local restrictions on provision of

services.

For the most part, allowing competition to innovate, create, and differentiate has served

the diverse needs of the public well. When competitive pressures were unregulated, the

market did well to create access competition that facilitated connection to increased

numbers of households. When the government stepped in to regulate, they created the

monopoly environment that ultimately slowed access by rural communities in lieu of the

more profitable urban areas. Sixty years later, with the 1984 Consent decree, the

government broke up the large Bell system monopoly (i.e. AT&T) and unleashed new

competitive industries (information services, long distance services, and mobile telephony)

that innovated, competed, and allowed an industry to flourish.

Creating a regulatory environment that applies broad rules may not be well suited for a

heterogeneous country with diverse geographies, demographics, industries, and even

subcultures. The U.S. has attempted to compete at the international level on broadband

with many countries that are more homogenous, with metrics (fixed household

connectivity) that are based on homogeneous constituencies, with governments often

owning (or heavily subsidizing) their own network providers. Government investment

requires “picking” the technology and industry winners – something that may be best

accomplished by the markets.

34 Santorelli. pp.114-116


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There are however, specific instances where the market will not naturally provide essential

services. For example, public safety will need some intervention to ensure its needs are

satisfied (e.g., spectrum allocation, priority treatment in emergencies, etc.).35 There will

continue to be a need for federal government regulation when it comes to spectrum

allocation and standards, state government licensing and service standards, and local

government zoning and rights of way.36

Government investment may be better spent on the demand side – helping to build

technical literacy and proficiency, assisting rural communities in creating new benefits and

understanding the value of broadband. Government assistance in providing service to

anchor institutions should be coupled with training and awareness programs on the broad

reach for available services. Financial assistance will continue to be needed to ensure

service affordability for lower income subscribers.

The history of government regulation and institutional legacy in place has created a strong

path dependency that influences current government policies and regulations. With rapid

technology advances and diffusion, co-dependent information services and changing

industry dynamics, the traditional approach of regulating the supply side is difficult. New

approaches to foster demand and allow the market to react to meet that demand are in

order. Some government intervention will likely be warranted to assist underrepresented

communities (e.g., public safety, tribal nations, etc.), but most federal regulation should

come in the form of guidelines and standards creation and ex post enforcement of anti-

competitive behavior.

35 Shelanski. p.99 36 McGregor, Michael A. 1994. “Toward a Unifying Regulatory Structure for the Delivery of Broadband Telecommunications Services.” Journal of Broadcasting & Electronic Media 38: p.139


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Going forward, federal programs should focus on demand creation and adoption, and allow

industry and market forces to create new means of access to meet demand.

2. UNIVERSAL SERVICE AND BROADBAND

For the past 100+ years, the U.S. regulatory policy has promoted equity and equality among

consumer telecommunications services. From the initial introduction of the telephone, the

goal has been to promote “universal service,” ensuring that each household is connected to

the broader network resources, while trying to mitigate anticompetitive behavior among

localized monopoly providers. It was considered essential for households to have

affordable access to emergency services and an ability to enhance daily lives through

connectivity. Both private and public subsidy programs emerged to help facilitate

connectivity to areas that could not cost effectively be serviced under normal market

conditions.

Government and industry have invested significantly in broadband technologies,

recognizing its role in enhanced productivity for business, public safety, education, and

health care.37 This section describes the concept of universal service and its new “mission”

to provide universal broadband service. It discusses the broadband imperative, challenges

in measurement, and federal broadband supply-side incentive programs.

What is Universal Service?

Universal service refers to “the ability to make available a basket of telecommunications

services to the public, across the nation, at a reasonable price.”38 The meaning of the term,

“universal service” has changed over time during the nation’s telecommunications

37 National Telecommunications and Information Administration (NTIA). “Broadband Technology Opportunities

Program (BTOP).” 2010. Broadband USA: Connecting America’s Communities. 38 Kruger, Lennard G, Angele A Gilroy, Charles B Goldfarb, Linda K Moore, and Kathleen Ann Ruane. 2010. “National Broadband Plan.” R41324. Resources, Science, and Industry Division (CRS); American Law Division (CRS). p.6


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development.39,40 In the early stages, when provider networks were separate, the term was

used to describe the need for an interconnected infrastructure. With the

Telecommunications Act of 1934, it came to represent geographic ubiquity. The next phase

saw its goals to keep telephone service affordable – keeping installation and recurring costs

more reasonable. Finally, universal service came to mean not only being affordable, but

meeting the special needs of subscribers. It is characterized as both a social and private

good, and a universal “right” for citizens most closely associated with freedom of speech.

Universal service has evolved from connecting independent service centers to a economic

goal that service is both ubiquitous and affordable.41,42 Achieving universal service involved

cross-subsidization within telephone companies – allowing network providers to charge

more for toll service to offset the cost of local service. State PUCs would govern the rates

for installation and monthly usage fees.

During the monopoly era, the FCC and PUCs allowed internal company cross-subsidization.

The 1983 Consent decree broke apart the means for private cross-subsidies within

companies , so carriers had no immediate incentive to serve rural or costly, hard to reach

areas. Through the Telecommunications Act of 1996, the federal government created the

Universal Service Fund (USF) to foster cross-subsidies to independent carriers that did not

have toll revenues. The USF collected subscriber fees that could be used to fund network

39 Blackman, Colin R. 1995. “Universal Service: Obligation or Opportunity?” Telecommunications Policy 19 (3): p.172 40 Mueller. 1997. p.41 41 Blackman, Colin R. 1995. “Universal Service: Obligation or Opportunity?” Telecommunications Policy 19 (3): p.172 42 Mueller. 1997. p.41, 43


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extension to areas that meet strict definitions established under the Act.43,44 Network

providers could petition for access to these funds to subsidize network development.

In addition to establishing the guidelines for the USF, the Telecommunications Act of 1996

also defined reasonable quality and affordable rates, universal access to advanced services

independent of geography, equitable access in rural and high cost areas (as compared to

urban counterparts), equitable and non-discriminatory contributions, and advanced

communications access to health care, schools, and libraries.45 This created the modern era

of regulation and incentive programs that are in place today. However, the rapid pace of

technology advances has challenged current legislation and regulatory rules.

Measurements of the effectiveness of universal service programs are restricted to fixed

(DSL, cable, or fiber) connections to households. In recent years, despite more widespread

physical connectivity, subscribers utilizing these connections have declined to adopt these

services. Government intervention and industry partnerships are necessary to help

provide affordable access, but adoption is not automatic. Complementary programs to

ensure sufficient technical skills and perceived value will help to compel use.

The Broadband Imperative.

Globally, high-speed internet, or “broadband” is now considered a universal right. The

United Nations Declaration of Human Rights states, “Depriving a citizen of access to the

Internet is a violation of the human right to ‘seek, receive and impart information and ideas

of all kinds, regardless of frontiers.’”46 In speaking regarding universal service in October

43 104th Congress. 1996. Telecommunications Act of 1996. 44 Mueller. 1997. p.44 45 104th Congress. 1996. Telecommunications Act of 1996. 46 United Nations. 2014. “The Universal Declaration of Human Rights.” Article 19.


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2011, Julius Genachowski, then Chairman of the FCC, stated that “Broadband has gone from

being a luxury to a necessity for full participation in our economy and society.”47 In 2012,

President Obama signed an Executive Order declaring that broadband is “essential to U.S.

global competitiveness in the 21st century, driving job creation, promoting innovation, and

expanding markets for American businesses.” The Order also stated “too many areas still

lack adequate access to this crucial resource.”48 The U.S. has backed its commitment to

broadband through billions of dollars in investment in broadband infrastructure, local

access, and digital literacy programs.

Broadband has similarities to other national programs in which the government provided

regulatory oversight and resources to industry (e.g., direct monetary incentives, rights of

way, spectrum). Similar to telecommunications, the electrical grid had similar challenges in

creating economies of scale for central facilities and access for local distribution.

Television broadcasters used allocated government spectrum, but did not have the local

access challenges. Television also shared a high cost of entry (television sets) similar to

internet access (computers). Both the electric grid and broadcast television lacked the

network effects of telecommunications (the more that use it, the more benefit), other than

through economies of use (electric grid) or advertising (broadcast television).

Broadband is seen as having a strong return on investment. It is considered essential for

access to educational resources within schools,49 enhanced medical services to rural areas,

expanded job creation and productivity,50 training for the unemployed and under-

47 Genachowski, Julius. 2011. “Connecting America: A Plan To Reform and Modernize the Universal Service Fund and Intercarrier Compensation System.” Prepared Remarks, Washington, D.C., October 6 48 “Executive Order -- Accelerating Broadband Infrastructure Deployment.” 2012. Whitehouse.gov. June 14. 49 National Telecommunications and Information Administration (NTIA). 2015a. “California Broadband Workshop Shows Work Still Needed to Close Digital Divide.” NTIA. BroadandUSA. November 15. 50 Taxalli, Sandeep. 2015. “Broadband Infrastructure Case Studies Released – How Broadband Changes the Game.” NTIA Blog. BroadbandUSA. April 13.


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employed, and the ability for small businesses to expand and reach national and

international markets.51

Similar to the electric grid, broadband is considered a key enabler of other infrastructures

and services that provide both economic and personal benefits. The interdependence of

multiple parallel ecosystems with broadband has increased the essential role of a high-

speed, high capacity physical infrastructure. Systems such as public safety, health care,

transportation, education, energy, entertainment, and the consumer marketplace are

increasingly dependent on a robust end-to-end infrastructure. The “Internet of things”

promises to increase the human-machine and machine-machine interfaces and further

demand higher bandwidth. Regulation and governance for all of these infrastructures and

industries is split among many stakeholders from both government and industry. As they

become more interdependent and distinctions become imprecise, it necessitates an

integrated approach to ensure a cogent regulatory strategy.

Challenges to Broadband Measurement

While most indicators show significant disparity among consumer groups, measuring the

divide is difficult. What type of technology is appropriate and sufficient? While the

government has focused its resources primarily on fixed broadband (cable/fiber to the

home), many subscribers have gone mobile with its low cost of entry, generous data plans,

and greater flexibility. Is the household the most appropriate unit of measurement? Or

should it be by person or device? Typical households have one connection but can have

51 National Telecommunications and Information Administration (NTIA). 2014. “Broadband Technology

Opportunities Program (BTOP) Quarterly Program Status Report.” Report to U.S. Congress. Washington, D.C.


MAY 24, 2016 1-21

many users, making the amount of delivered bandwidth deceptive.52 These factors make

measuring the effectiveness of programs problematic and exceedingly complex. 53

What is sufficient speed? The U.S. ranks 35th out of 148 countries in internet download

speeds and 42nd in upload speeds.54 In the U.S., NTIA defines broadband as a minimum 768

kbps download speed and 200 kbps upload speed. The FCC called out a future minimum

download speeds of 4 mbps.55 While the government has established these speed

thresholds, technology has outpaced these thresholds by the time programs have been

funded and implemented. As more and more households and businesses rely on internet-

connected devices and equipment, broadband is a necessary aggregator to ensure adequate

throughput with low latency.56 More devices require more information, increasing demand

for bandwidth. While mobile devices are generally associated with one person, the number

of applications and services hosted on each device can increase demand for bandwidth as

well. It is increasingly difficult to forecast, monitor, control and create programs when

chasing a moving target.

How affordable is the service? Even when access is available, the U.S. ranks near the

bottom of developed countries in terms of subscriber costs.57 While competition has

demonstrated it can drive increased speeds at lower costs, competition remains thin in

52 Beard, T. Randolph, George S. Ford, Lawrence J. Spiwak, and Michael Stern. 2010. “The Broadband Adoption Index: Improving Measurements and Comparisons of Broadband Deployment and Adoption.” Federal Communications Law Journal 62 (2): p.346 53 Hilbert, Martin. 2011. “The End Justifies the Definition: The Manifold Outlooks on the Digital Divide and Their Practical Usefulness for Policy-Making.” Telecommunications Policy 35 (8): 715–16, p.725 54 Wyatt, Edward. 2013. “U.S. Struggles to Keep Pace in Delivering Broadband Service.” The New York Times,

December 29, sec. Technology. 55 Grimes, Justin, John Bertot, and Ruth Lincoln. 2012. “Public Libraries and the National Broadband Map:

Findings and Recommendations”. Information Policy and Access Center, University of Maryland. 56 Hilbert. p.720 57 Bennett, Richard, Luke Stewart, and Robert Atkinson. 2013. “The Whole Picture: Where America’s Broadband

Networks Really Stand”. The Information Technology and Innovation Foundation.


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rural and economically depressed areas. Affordability is, of course, relative to the amount

of income and perceived benefit of such service. There are currently no defined thresholds

or target price points to measure effectiveness.

Another factor that confounds measurement is the availability of high-speed internet

access through the workplace and community institutions. Those that can not afford or are

not willing to pay for internet access at home may have alternate means by which they can

access the medium. While incentive programs have focused on high-speed internet

availability through schools, libraries and community centers, national broadband

penetration measurement programs have focused on household access. They have not

captured the substitution alternatives that may affect willingness to pay for internet access

at home.

Measuring the effectiveness of government programs relies on industry disclosures to the

FCC. Summary connections are generally reported by county to protect proprietary

subscriber information. However, counties can have significant variations in demographics

within their boundaries, which make measuring a program’s effectiveness difficult.

Program results can also be skewed by inclusion of inner city enclaves of low-income

populations – a low cost distribution to multiple households that can bias program

numbers because they do not address the more difficult, more costly to connect, rural

households.

Finally, rural program metrics are also somewhat biased. Applications for rural grants

often come from universities located in rural areas. These funds generally


MAY 24, 2016 1-23

disproportionately benefit university constituencies vice rural households. 58 Without

clear, consistent metrics for broadband programs, measuring success or completion is

difficult. In fact, these metrics will likely never be constant or fixed, and will continuously

adjust reflecting new consumer needs and emerging capabilities.

Broadband and Co-dependent Ecosystems

The regulatory environment is becoming more complex making information asymmetries

larger and regulatory authority more distributed. Multiple industries now become de facto

players in broadband due to their reliance on the infrastructure and their demands for

varying performance characteristics. For example, health care may demand high

availability and low error rates. The online entertainment industry demands high speeds

with low latency but can be more error tolerant. Energy companies implementing the

smart grid need only low-bandwidth with high availability and low error rates.

The infrastructure itself is changing, with new market entries from cable television,

broadband over power line (BPL), satellite providers, and Worldwide Interoperability for

Microwave Access (WiMAX). These alternatives create greater competition for local access

and offer innovative solutions for hard-to-reach rural areas. Wireless carriers are

increasing data rates and making data plans more affordable as they advance from 3G to

4G, and eventually emerging 5G technologies and services. The FCC has recognized that the

means by which they manage and regulate spectrum by assigned channels is changing with

new technologies that operate efficiently without fixed channels.59 With the diversity of

58 Malecki, Edward J. 2003. “Digital Development in Rural Areas: Potentials and Pitfalls.” Journal of Rural Studies 19 (2): p.206 59 Kruger, Lennard G, Angele A Gilroy, Charles B Goldfarb, Linda K Moore, and Kathleen Ann Ruane. 2010. “National Broadband Plan.” R41324. Resources, Science, and Industry Division (CRS); American Law Division (CRS). p.17-19


MAY 24, 2016 1-24

medium that cater to the varied needs of consumers, no single definition of sufficient and

affordable broadband service may be possible.60

Federal Infrastructure (Supply-side) Broadband Programs

Recognizing the need to bridge the broadband divide, the U.S. put in place subsidy

constructs and incentive programs to foster fixed broadband infrastructure development.

These programs have led to significant investment by both government and industry to

install fiber and connect households. However, despite billions of dollars invested in these

programs, many remain underutilized and fixed broadband adoption is declining.

Nevertheless, connectivity is necessary (but not sufficient) for adoption, and these

programs serve to build a more robust backbone and provide opportunities for adoption

that had not existed.

Universal Service Fund (USF). The USF collects fees from millions of subscribers to help

invest in infrastructure or lower costs for other subscribers. However, issues that include

the high cost of the program and inappropriate beneficiaries have plagued the program.

Costs for the program have progressively risen and the results are not evident. The

program paid some companies as much as $20,000 a year for a single phone line.61 The

USF had distorted the market by paying some network providers and not others in the

same region, or paying for many in the same region where there is sufficient competition.

Finally, companies that currently get subsidies under the program risk losing them if they

upgrade the traditional phone line to high-speed services.

60 Cawley, Richard. 2001. “Universal Service, Specific Services on Generic Networks, Some Logic Begins to Emerge in the Policy Area.” arXiv:cs/0109063, September. p.5 61 Genachowski. 2011.


MAY 24, 2016 1-25

Connect America Fund. In 2011, the Connect America Fund replaced the USF, and

broadened the focus to include affordable broadband to homes and businesses, working

toward universal availability of mobile broadband. The USF High Cost program was

restructured to allow network providers to collect subsidies for the provision of broadband

service. However, of the $300M in incremental support for carriers to provide unserved

locations with high-speed internet (minimum 4 Mbps download and 1 Mbps upload), only

$115M has been utilized, with $185M unclaimed.62

National Broadband Plan/ Broadband Technology Opportunities Program (BTOP). In

2010, the NTIA created the National Broadband Plan, with a goal of 100 million households

receiving broadband at 50 Mbps by 2015, with 100 Mbps by 2020. The goal is to review

minimum broadband speeds once every four years to keep pace with technology changes.

Under the American Recovery and Reinvestment Act (ARRA) of 2009, the U.S. set aside $4.7

billion for the Broadband Technology Opportunities Program (BTOP). This program was

intended to administer grants to organizations (private and public) to increase broadband

penetration and to educate and encourage adoption of these technologies. The BTOP

program only measures the fixed broadband connections (DSL, cable or fiber) to the home.

Broadband access is expected to result in improvements in education, higher productivity

for the work force, greater reach for small businesses, better access to specialized health

expertise, and improved public safety.63

In February of 2016, NTIA announced that BTOP had spent $3.5B to deploy or upgrade

114,697 miles of “new or upgraded network infrastructure” infrastructure, $251M to 44

sustainable broadband adoption (SBA) programs, and $201M on 66 public computing

62 Gilroy, Angele A., and Lennard G. Kruger. 2013. “Rural Broadband: The Roles of the Rural Utilities Service and the Universal Service Fund.” CRS Report for Congress CRS-2013-RSI-0317. Congressional Research Service, Resources, Science, and Industry Division (CRS). p.9 63 NTIA. 2010. p.1


MAY 24, 2016 1-26

center (PCC) projects. The SBA program claims to have added over 671,000 new

subscribers.64 This works out to about $5700 per new subscriber, not including initial

setup and recurring costs.

E-Rate Program. The federal E-Rate program was created in 1998 to offset the costs of

service and subscriber infrastructure at schools and libraries, particularly in rural and

tribal areas. The formula for school assistance is based on the number of free and reduced

lunches in a school district. 65 It can be used to offset telecommunications or internet

service costs, servers and routers, and maintenance. The program explicitly does not cover

computers, software or training.66 It also included the provision for subscribers to spread

up front capital costs over several years.67 As of 2015, the program claims to have

connected over 25,000 anchor institutions. 68 The annual spending cap for E-rate was

initially $2.25 Billion, but in 2014 was raised to $3.9B to meet demand.

Rural Health Care Program. The Rural Health Care program is targeted to connect health

centers, clinics, public or not-for-profit hospitals, and dedicated ER rooms at for-profit

hospitals.69 It is funded at $400M annually to provide up to 65 percent discount to eligible

entities for services and equipment.70 While the program is intended to enable remote

training for physicians and telemedicine, there is no funding for training or mobile health

devices.

64 “NTIA Updates $4 Billion Broadband Stimulus Program Results - Telecompetitor.” 2016. Accessed May 2. 65 Hart, Michael. 2012. “Life, Liberty and the Pursuit of Broadband.” T.H.E. Journal 39 (6). 66 Gilroy and Kruger. p.13 67 Federal Communications Commission. “Moving Forward with a Data-Driven E-Rate Modernization Process.” 2014. Federal Communications Commission. August 12. 68 NTIA. 2015b. “Broadband Technology Opportunities Program (BTOP) Quarterly Program Status Report.” Report to U.S. Congress. Washington, D.C. p.2 69 Federal Communications Commission. 2014. “Universal Service Support Mechanisms.” FCC Guides. April 12. 70 “Rural Health Care Program.” 2010. Federal Communications Commission. November 18.


MAY 24, 2016 1-27

Government programs have influenced industry serving rural areas. Gabel (2007) found

that independent telephone companies are more uniform in their service offerings, offering

94 percent of their subscribers’ high-speed access in non-rural areas, and 85 percent in

rural areas.71 He showed that independents are four times as likely to offer high-speed

access than Verizon, a result that may be due to independent’s eligibility for federal

assistance.

Many of the rural communities continue to be served by analog infrastructure since the

telephone companies that service them do not see sufficient demand for high-speed digital

services, creating a “chicken and egg” dilemma.72 Federal subsidies targeted at

independent telephone companies to build out infrastructure has seen some progress, but

larger companies (e.g. Verizon) do not qualify for such subsidies, so build-out in rural areas

has been more limited. Eligibility is based not only on the size of the company requesting

assistance, but the size of the community targeted. Currently, the size of the rural

community is set to populations of 20,000 or less, but Congress is considering raising the

maximum to 50,000, allowing more communities to be eligible.73

Current State of Broadband Penetration

The FCC continuously collects and synthesizes data from network providers. In a recent

report to Congress, the FCC stated that broadband penetration exists at about 95 percent of

households in 2015.74 They also estimated that approximately 33 million Americans (10

percent) continue to lack access to fixed broadband, with 23 million Americans (39

71 Gabel, David. 2007. “Broadband and Universal Service.” Telecommunications Policy 31 (6–7): p.339 72 Malecki. p.206 73 Gilroy and Kruger.p.3 74 Ibid. p.17


MAY 24, 2016 1-28

percent) in rural areas. Rural areas within tribal lands and territories represent the

greatest percentage of those without fixed access, at 68 and 98 percent respectively.75

There are conditions and caveats with the measured penetration results. First,

penetration is measured by fixed connections to households, not by the number of people

with access. The size of the household (particularly those with school-age children) is

significant when considering access to educational resources. Second, the NTIA defines

broadband as a minimum 768 kbps download speed and 200 kbps upload speed. FCC

established a future minimum download speed of 4 mbps.76 These targets are relatively

low and inadequate considering the bandwidth required for most applications, such as

video streaming. The BTOP program has concluded, but the FCC continues to collect data

on households connected and threshold speeds (both advertised and actual). The National

Broadband Map shows that 98.2 percent of the U.S. population has speeds of at least 768

kbps upload and 3 Mbps download.77

Increasing the number of providers generates competition that fosters lower costs and

improved service. In his influential book, Exit, Voice and Loyalty (1970), Herschman

recognized that there are few incentives for providers to enhance services or lower prices

when there is marginal or no competition.78 Consumer voice is diminished when there are

little or no alternatives. BTOP encourages new market entrants through subsidies for

infrastructure development, and tracks the number of providers in each community

nationwide. Defining “sufficient” competition for any community is difficult. The FCC

75 “FCC Releases 2016 Broadband Progress Report.” 2016. Federal Communications Commission. January 29. p.34 76 Grimes et al. 2012. 77 Kruger, Lennard. 2013. “National Broadband Plan Goals: Where Do We Stand?” Science and Technology Policy R43016. Washington, D.C.: Congressional Research Service. p.6 78 Hirschman, Albert O. 1970. Exit, Voice, and Loyalty: Responses to Decline in Firms, Organizations, and States.

New Ed edition. Cambridge, Mass: Harvard University Press.


MAY 24, 2016 1-29

offered the benchmark that quality, quantity and pricing of services should be comparable

to those with more competition (typically urban areas).

Mobile connectivity through smartphones generally has a lower cost of entry and immense

societal benefits, but is often not measured in national penetration statistics. Success of

current broadband programs is measured by: miles of fiber installed, households

connected, not how consumers may actually use the service in a meaningful way. Recent

studies have shown that smartphones have substituted fixed broadband access for many

Americans, but the impact of that form of access (quantifiable benefits as it relates to

government aspirations) has yet to be determined.

This new “broadband adoption divide” and the relevant theories of adoption are discussed

in a companion paper, ”Technology Adoption Models and Broadband: Examining Alternative

Adoption Models to Improve Understanding and Foster Broadband Adoption.

RON HODGE MAY 24, 2016

The Broadband Divide and Technology Adoption

Models: Examining Alternative Adoption Models to Improve Understanding and Foster Broadband Adoption

ABSTRACT

While broadband penetration has been the focus of government policy and investment, subscription and “meaningful” adoption has lagged significantly in the targeted “digital divide” communities. Nearly 90 percent of the billions of dollars spent on government broadband programs have focused on fixed backbone and local infrastructures to connect households. While the government is closing in on its “100 squared” goal (100 Mbps in 100 million households), adoption is not keeping pace, and in some instances, dropping. In many communities, this leads to a digital gulf that will only widen as they miss opportunities to exploit new digital resources and emerging dependent infrastructures. While the government has focused primarily on broadband penetration and some digital literacy programs, very few resources have focused on other potential adoption factors.

This paper explores various technology adoption models and their applicability to broadband. It recognizes that different consumer groups place different premiums on the value of broadband, and that other means of access (e.g., mobile) may have greater utility for the functions they need or value. This paper compares the components of each model, explores limitations, and suggests models and components that could better characterize and influence adoption. Keywords: Broadband, Broadband Adoption Divide, Diffusion of Innovation, Technology

Adoption, Adoption Models/Theories, Network Effects

EXAMINING ALTERNATIVE ADOPTION MODELS TO IMPROVE UNDERSTANDING AND FOSTER BROADBAND ADOPTION SECOND DRAFT

MAY 24, 2016 2-1

Building on the supply side regulation and incentive programs detailed in Part 1 (Sections

1 and 2), this paper discusses challenges and theories associated with the demand side, or

“broadband adoption.” Section 3 examines the state of broadband adoption in the United

States, the demographics of the current “broadband divide,” and known barriers to

adoption. While government programs and analysis have focused on the demographics of

the divide, there is emerging empirical evidence that “demography is not a destiny”79 – that

technology adoption is more a result of relative value, norms, attitudes, and controls.

There are different value systems in place for distinctive subscriber communities that

affect their market choices (to connect or not, fixed or mobile). There are different

mechanisms for learning (observational or enabled) that come from exposure in schools or

the workplace. These factors must be considered in fostering broadband adoption and

inclusion.

Section 4 presents potential several theories of technology adoption and their applicability

to broadband. Theories in technology adoption and the diffusion of innovation point to

skills and social factors that could play a part in adoption. While many components of each

theory overlap, each offers new aspects and perspectives that comprise a more

comprehensive ontology. Notably, government programs to date have focused on very

narrow aspects of adoption, primarily digital literacy. The section concludes with other

possible elements that are not represented (or underrepresented) in current technology

adoption theory.

79 LaRose, Robert, Kurt DeMaagd, Han Ei Chew, Hsin-yi Sandy Tsai, Charles Steinfield, Steven S. Wildman, and Johannes M. Bauer. 2012. “Broadband Adoption| Measuring Sustainable Broadband Adoption: An Innovative Approach to Understanding Broadband Adoption and Use.” International Journal of Communication 6 (0): 25. p.2588


MAY 24, 2016 2-2

3. THE BROADBAND ADOPTION DIVIDE

Broadband is the new standard for telecommunications, allowing high-speed connectivity

that supports multiple services. Benefits of broadband include increased productivity in

the workplace, expanding small business reach, providing a conduit for education

resources, increasing jobs and job placement, and enabling more robust public safety and

health care. Increasingly, broadband infrastructure provides a foundational element for

the financial industry, energy, transportation, and the consumer marketplace. Cambini and

Jiang (2009) catalogued several research studies demonstrating a direct causal link

between broadband and economic growth.80 The National Telecommunications and

Information Administration (NTIA) estimated that the broadband infrastructure fostered

by the Broadband Technology Opportunity Program (BTOP) will generate 22,000 jobs

worth more than $1B in income each year.81 The benefits of broadband appear clear, but

there is a distinction between penetration (connection) and adoption, a distinction that is

coming in greater focus.

While broadband penetration has been closely associated with GDP growth, it is broadband

adoption that is the more relevant metric. A broadband divide persists despite technology

proliferation and government incentive programs to connect households across the U.S.

The U.S. Census Bureau’s Computer and Internet Use Supplement to the Current Population

Survey (CPS) recently conducted a study of 53,000 households that showed while fixed

broadband adoption peaked in 2013 at 82 percent, it has since dropped to 75 percent in

2015. Despite the success in physically connecting households, an estimated 27 percent

still do not have fixed or mobile internet access at home.82 However, this percentage does

80 Cambini, Carlo, and Yanyan Jiang. 2009. “Broadband Investment and Regulation: A Literature Review.” Telecommunications Policy 33 (10–11): p.560 81 Taxalli, Sandeep. 2015. “Broadband Infrastructure Case Studies Released – How Broadband Changes the Game.” NTIA Blog. BroadbandUSA. April 13. 82 NTIA. 2015. “Current Population Survey Internet and Computer Use.” June.


MAY 24, 2016 2-3

not count those that may have access through the workplace, schools, or community

centers (e.g., libraries). Gideon and Gabel (2011) attribute this decline of fixed connections

to increases in certain demographics (i.e. increases in the black population and the elderly),

inconsistencies and unpredictability in consumer pricing, and increases in mobile

telephony.83

Rural and economically depressed areas are still unserved or underserved.84 Among the

challenges are high cost, low perceived value, technical proficiency, and consistency with

norms. 85 Rural areas are often more difficult and costly to connect, leading to fewer

competitive options for service. Rural consumers are also more likely to be less technically

proficient and lack the compelling social and network effects to connect (e.g., no one else in

their social circles is online). Rural network providers are less likely to invest in

infrastructure (both in the switching centers and local loop) without subsidies, so services

are more likely to be limited to older (lower speed) connections. Since network providers

rely on economies of scale (and queuing theory of shared resources), a smaller subscriber

base may make them unwilling to promote high-demand broadband services (e.g. video)

because they may overload their networks.86,87

Certain demographic communities, particularly Hispanic, non-Asian nonwhite households

and the elderly, are over-represented in rural and low-income areas. Americans under the

83 Gideon, Carolyn, and David Gabel. 2011. “Disconnecting: Understanding Decline in Universal Service.” Telecommunications Policy 35 (8): p.740 84 Seifert, Mark G. 2009. Hearing on Oversight of the American Recovery and Reinvestment Act of 2009: Broadband. Washington, D.C. 85 LaRose, Robert, Jennifer L. Gregg, Sharon Strover, Joseph Straubhaar, and Serena Carpenter. 2007. “Closing the Rural Broadband Gap: Promoting Adoption of the Internet in Rural America.” Telecommunications Policy 31 (6–7): p.360-61 86 Ibid. p.360-61, 371 87 Malecki, Edward J. 2003. “Digital Development in Rural Areas: Potentials and Pitfalls.” Journal of Rural Studies 19 (2): p. 209


MAY 24, 2016 2-4

age of 65 adopt at a rate of 82 percent, while those above the age of 65 drop to 65 percent.

Only 47 percent of those households earning below $20,000 subscribe to broadband, while

nearly 89 percent of those earning more than $50,000 subscribe. The more educated the

consumer, the more likely to adopt, possibly due to high income and greater exposure.

Those with less than a high school diploma have a 54 percent adoption rate, while those

with a bachelors degree (or higher) adopt at a rate of 92 percent. 88 As a result, rural and

low-income population segments will not share in the immediate and future benefits of

broadband, particularly as it becomes an integral part of other public infrastructures. (See

Note 89)

Households with K-12 children are more likely to adopt broadband, but there is still a

disparity among rural and poor households. While more schools utilize technology in the

classroom, some schools in rural or economically depressed areas are reticent to assign

research or homework that requires access at home. Community access through libraries

and computing centers offers some relief, but it has a weak correlation with broadband

adoption in the home.90

While the divide persists, some of these challenged communities have increasingly adopted

wireless technologies. Several surveys show the growing role of mobile devices (i.e.,

smartphones) as the primary means of connection for subscribers. The 2015 CPS showed

that households that utilize solely mobile devices and service doubled from 10 to 20

percent, with as much as 29 percent in low-income households (under $25K annually) and

88 Tomer, Adie, and Jose Kane. 2015. “Broadband Adoption Rates and Gaps in U.S. Metropolitan Areas.” Brookings Metropolitan Policy Program. p.4 89 There is also what is referred to as a rural-rural divide (Gilroy and Kruger, 2013) Many universities are located in rural areas, and often receive rural grant monies to improve the local infrastructure. The areas adjacent to the universities receive a disproportionate share of the money, and those improved infrastructures often skew or bias the reporting numbers (Malecki, 2003). Adoption may be much worse than measured in areas without a university. 90 LaRose et al. 2007. p. 371


MAY 24, 2016 2-5

15 percent in households above $100K in annual income. Nearly 57 percent of households

have access through multiple devices (fixed and mobile).91

Mobile service has a lower cost of entry (a phone vs. a computer), requires lower technical

proficiency, and offers greater flexibility (allowing them to connect nearly anywhere,

anytime). It can also be used to tether to a computer or tablet to allow internet access. In a

recent survey of 2000 households, the Pew Research Center showed the diversity of

Americans representing whites and minorities and all income and education levels

choosing to disconnect from fixed broadband in favor of smartphones.92 Appendix A shows

some of the results of the Pew Study.

Barriers to Broadband Adoption

There are some more obvious barriers to broadband adoption. The high cost of purchasing

a computer (and software) can be a deterrent to broadband adoption. The U.S. Census

Bureau 2013 American Community Survey (ACS) found that 84 percent of Americans have

a computing device at home (including PCs, tablets and smartphones), and 74 percent have

at least low-speed (dial-up) internet access.93 These figures vary widely by geography and

demographics. For example, in a 2011 NTIA study, 45 percent of seniors indicated they did

not have a home computer, compared to only 20 percent of those under age 65.94 NTIA

also found that low-income households who do not own a computer indicated they “don’t

91 McHenry, Giulia. 2016. “Evolving Technologies Change the Nature of Internet Use.” NTIA. April 16. 92 Horrigan, John B., and Maeve Duggan. 2015. “Home Broadband 2015.” Pew Research Center: Internet, Science & Tech. December 21. 93 Bureau, US Census. 2016. “ACS New State & Local Income, Poverty, Health Insurance Statistics.” Accessed May 5. 94 Davidson, Charles M., Michael J. Santorelli, and Thomas Kamber. "Toward an inclusive measure of broadband adoption." International Journal of Communication 6, no. 0 (2012): p.2556


MAY 24, 2016 2-6

need it” or are “not interested.”95 There was no clear value proposition. Owning a personal

computer increases the probability of adopting broadband services by 18.3 percent.96

While the U.S. has competitive pricing for data services at lower speeds, the higher tier

broadband is relatively costly at $76.64 for speeds up to 50 Mbps and 199.99 for speeds up

to 100 Mbps. This ranks the U.S. at 80th in terms of subscriber cost among developed

countries.97 However, prices for broadband are difficult to discern due to bundling and

variations in speed. The NTIA and the FCC only periodically study pricing and the data is

subject to considerable variation across the country.

Thirty-six percent of non-adopters cite the cost of broadband as the reason they do have

service at home.98 The federal government has several programs that help subscribers to

limit installation and recurring costs. The Link-up program offers a $100 discount on

installation fees, while Lifeline offers discounts up to $9.25 per month for fixed or mobile

services.99 A 2011 Study by NTIA reported that the “Internet Essentials” program by

Comcast (mandated as a conditions of their merger agreement with Universal) seeks to

lower the cost of broadband service ($9.95/month), offer low cost computers (149.99

including Microsoft Office), and provide free classes (locally or online) to build digital

literacy.100 While affordability is often cited in surveys as a primary reason for not

95 Ibid p.2564 96 Roycroft, Trevor R. 2013. “Empirical Study of Broadband Adoption Using Data from the 2009 Residential Energy Consumption Survey.” Journal of Regulatory Economics 43 (2): p.225. 97 Bennett, Richard, Luke Stewart, and Robert Atkinson. 2013. “The Whole Picture: Where America’s Broadband Networks Really Stand”. The Information Technology and Innovation Foundation. 98 Gilroy, Angele A., and Lennard G. Kruger. 2013. “Rural Broadband: The Roles of the Rural Utilities Service and the Universal Service Fund.” CRS Report for Congress CRS-2013-RSI-0317. Congressional Research Service, Resources, Science, and Industry Division (CRS). p.12 99 Federal Communications Commission. 2014. “Universal Service Support Mechanisms.” FCC Guides. April 12. 100 Davidson, Charles M., Michael J. Santorelli, and Thomas Kamber. "Toward an inclusive measure of broadband adoption." International Journal of Communication 6, no. 0 (2012): p.2563


MAY 24, 2016 2-7

adopting, other studies show little impact of monthly subscriber costs on adoption.101

These assistance programs can lower costs to subscribers, but it is clear that for many, if it

is not “relevant” or “not interested,” then no price is attractive.

While significant resources have been spent on these programs, they remain underutilized

and some studies suggest that financial assistance has little effect on adoption.102 In fact,

only one-third of those eligible for federal assistance programs for installation and

recurring costs (Link-Up and Lifeline) actually enroll for the subsidy.103

Other technologies serve as indicators of propensity for broadband adoption, including

television sets and television service. Roycroft (2013) studied the relationship of

broadband access with television services, considered to be complementary services.

Network providers often offer these as part of a “bundle” of services. He found that owning

a television set increases probability of broadband adoption by 3.3 percent. He also found

that those that use cable television (pay services) are more likely to adopt broadband,

while rural and elderly communities that often utilize over-the-air television are less likely

to adopt. Subscribing to cable television increases the likelihood of broadband adoption by

about 21 percent over broadcast (over-the-air) television.104 This may be due to lower

incremental monthly costs of adding broadband service as part of a bundle as well as the

ready presence of a physical connection that lowers installation costs. Notably, one

research study found that the length of time a television is turned on lowers the probability

of a broadband connection, indicating potential substitution effects.105

101 Tomer, Adie, and Jose Kane. 2015. “Broadband Adoption Rates and Gaps in U.S. Metropolitan Areas.” Brookings Metropolitan Policy Program. p.2 102 Gideon and Gabel. p.740. 103 Ibid. p.740 104 Roycroft. pp.214, 225-226 105 Ibid. pp.222-24


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4. TECHNOLOGY ADOPTION MODELS/THEORIES.

Recently, research has focused on multiple theories behind technology adoption and

attempted to apply them to broadband adoption. Theories in technology adoption and the

diffusion of innovation point to skills and social factors that could play a part in adoption.

This section explores the different theories, the components considered for each theory

and its appropriateness and challenges toward broadband adoption measurement. It

concludes with potential components that are not included or only partially addressed by

current technology adoption models. These elements could yield insight into additional

causal/contributing factors for broadband adoption.

Diffusion of Innovation Theory

Everett M. Rogers first introduced diffusion of Innovation Theory in 1962, authoring a book

by the same name (the 2nd most cited book in social sciences). In it, he describes how

communications channels spread ideas over time.106 He focused on the social components

of sharing information to help move through the stages of adoption. His theory on the

diffusion of innovation (often characterized as a paradigm) has five distinct characteristics.

The first is relative advantage – is it better than current alternatives? Adopters must

examine current process or product to determine if the new innovation has perceived

advantages over their current environment. The second is compatibility – is it consistent or

a good fit with current lifestyle, beliefs, and values, as well as other adopted technologies?

The closer and more consistent the fit, the more likely they will be to adopt. The third

characteristic is complexity – can I master the skills necessary to utilize this technology? In

this case, it is the belief or confidence in their ability to be proficient at operating the new

technology. The fourth is trialability – can I see if it will work for my skills and my needs?

An ability to experiment is crucial to building confidence and determining fit. Finally the

106 Rogers, Everett M. 2003. Diffusion of Innovations, 5th Edition. 5th edition. New York: Free Press.


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fifth characteristic is observability – can I readily see through others how they use and

benefit from the technology? This exposure is essential in meeting the thresholds of the

previous characteristics. It also adds a social component that allows potential users to see

how it is utilized in their social circles.107

Rogers also illustrated five stages of adoption. The stages were initial exposure, developing

a positive/negative impression of the innovation, decision to accept or reject, actual usage,

and confirmation of if its value and continued use.108 He plotted adopters on the familiar S-

curve, and categorized them as ‘‘innovators, early adopters, early majority, late majority

and laggards.’’109

Hilbert (2011) built on Rogers’ theory and stressed the importance of the communications,

or ties between nodes, not simply the nodes. By observing the attributes (frequency,

direction and strength) as well as the content of the ties, patterns can be discerned that can

shed light on influences in adoption.110

The DoI theory is independent of geography and demographics that define the digital

divide. The theory focuses first on the benefits and value that could be gained through

adoption. These will be different for different groups as their social dynamics and needs

may be unique. The theory then focuses on social networks and learning, the ability to

communicate and share benefits, lessons learned, and confidence building through

observation and trial. While some government and industry programs offer training, they

107 LaRose et al. 2007. p.361 108 Rogers, Everett M. 2003. Diffusion of Innovations, 5th Edition. 5th edition. New York: Free Press. 109 Hilbert, Martin. 2011. “The End Justifies the Definition: The Manifold Outlooks on the Digital Divide and Their Practical Usefulness for Policy-Making.” Telecommunications Policy 35 (8): pp.716 110 Ibid. pp.724


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fail to potentially exploit some of the communal ties and values that might increase

demand.

Social Cognitive Theory (SCT)

Social cognitive theory also focuses on communications and learned behaviors, particularly

observational and enabled learning.111 SCT includes expected outcomes (anticipated

benefit), self-efficacy (confidence that they can master performance even if they haven’t

experienced it yet), habit strength (prior use of the internet), observational learning

(evaluating what others are doing with an innovation), and enactive learning (through

their own experience). 112 Habit strength has a time element embedded in it, since the

more time or exposure to an activity, the greater the habit strength.

SCT theory is closely related to DoI theory and shares some of the same characteristics,

with the possible exception of habit strength (although it could be argued that it is closely

related to complexity). This theory also focuses on learning and its impact on human

behavior, factors that are worthwhile exploring in understanding broadband adoption.

Larose et. al. (2012) used the SCT model to predict broadband adoption intentions. They

found significant positive relationships with expected outcomes, self-efficacy, habit

strength, observational learning, and enactive learning. Notably, the influence of the SCT

variables was twice that of the demographic variables. 113

111 LaRose at al. 2012. p.2583 112 Tsai, Hsin-yi Sandy, and Robert LaRose. 2015. “Broadband Internet Adoption and Utilization in the Inner City: A Comparison of Competing Theories.” Computers in Human Behavior 51, Part A (October): 345. 113 LaRose et al. 2012. p.2588


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Model of Adoption of Technology in Households (MATH)

MATH borrows heavily from the Theory of Planned Behavior (TPB) and focuses primarily

on inherent consumer norms, attitudes, and control beliefs. Normative beliefs are external

to the potential adopter, represented by friends and family, social and media influences,

and the workplace. Attitudinal beliefs are more internal, stemming from personal utility

such as productivity, entertainment, or status gains. Finally, control beliefs stem from fear

of uncertainties, such as ability to use the device or service and the challenge associated

with committing at a time when technology is advancing or costs are declining.114

The MATH model encompasses many of SCT’s concepts, such as attitudinal beliefs that are

similar to expected outcomes, and control beliefs such as ability are similar to self-efficacy.

MATH attitudinal beliefs overlap with the DoI’s compatibility component. The external

factors that influence normative beliefs that are included in MATH are not explicitly

addressed (other than through observational learning) in both DoI and SCT.

In a study of 750 households without a personal computer, Brown and Venkatesh (2005)

used the MATH model to predict intentions to adopt a PC. Results showed that the MATH

model accounted for 50 percent of the variance, with the expected attitudes and norms

showing a significant positive influence (with the exception of status gains for attitudinal

beliefs and workplace influences on normative beliefs), while controls showed the

expected negative influence on adoption (fear of technological advances and cost).

However, when the MATH was run with household life cycle (12 stages arrayed across

marital status, age, children, etc.) and income, the model accounted for 74 percent of the

variance. It reduced the impact of most of the belief variables, with the exception of the

utility for children. Stratifying the MATH variables by household life cycle was the most

114 Tsai and LaRose. p. 346.


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compelling finding. For example, attitudinal beliefs had the highest influence on broadband

adoption intent for single parents and full nesters, specifically the broadband’s utility for

children. Control beliefs had the highest influence on broadband adoption intent among

childless couples and the elderly, specifically requisite knowledge and ease of use.115 These

findings are directly comparable to broadband adoption challenges for specific household

groups.

Technology Acceptance Model (TAM)

TAM builds on the Theory of Reasoned Action (TRA), a model used in social psychology.

TAM contains elements of the TRA (and similar to MATH), including norms and attitudes

combined together to create better predictors of adoption.116 However, TAM also includes

perceived usefulness (defined as productivity improvement) and perceived ease of use,

similar to the relative advantage and complexity components of DoI.117

TAM does not include past experiences (trialability) so is often used when there is limited

or no data on past exposure to the technology (e.g., through dial up, schools, libraries, or

the workplace).118

Unified Theory of the Acceptance and Use of Technology (UTAUT)

The UTUAT model originated via TAM from the TRA. The UTUAT model includes many

familiar elements, including performance expectancy (similar to perceived usefulness in

TAM and relative advantage in the DoI model), effort expectancy (similar to complexity in

the DoI model and self-efficacy in the SCT model), social influence (similar to normative

115 Brown, Susan A., and Viswanath Venkatesh. 2005. “Model of Adoption of Technology in Households: A Baseline Model Test and Extension Incorporating Household Life Cycle1.” MIS Quarterly 29 (3): p.402. 116 Davis, Fred D., Richard P. Bagozzi, and Paul R. Warshaw. 1989. “User Acceptance Of Computer Technology: A Comparison Of Two.” Management Science 35 (8): p.983 117 Ibid. p.985 118 LaRose at al. 2012. p.2584


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beliefs in MATH), and one more appropriate for the workplace adoption, referred to as

facilitating conditions. Facilitating conditions is the trustworthiness of organizational

support and infrastructure, and the organizational commitment to the technology or

innovation long-term. UTUAT also includes interactions with control variables

representing gender, age, and prior experience.119 UTUAT is primarily tailored to the

organizational (workplace) environment and does not include factors that may be more

suitable for technology adoption in the home. 120 In an empirical study of workplace

intentions to adopt, Venkatesh (2003) used the UTUAT model and found that the highest

significant correlation to broadband adoption intent was with performance expectancy.121

UTUAT2

Building on UTUAT, UTUAT2 was extended to include a consumer adoption context.

UTUAT2 includes additional components of hedonic motivation (the “fun” or pleasure

gained, similar to attitudinal beliefs of MATH) and habit strength (similar to habit strength

in the SCT model).122 UTUAT2 also includes the component price value to capture the

perceived benefit over monetary cost preferences of consumers. This is notable because

cost is cited as one of the gating factors for broadband adoption. In this case, it must be

weighed against the perceived value to be gained, and could be considered similar to the

relative advantage component of the DoI model. In the model, when age and gender are

added they may have an influence on price value. Experience is also added as it is expected

to influence habit strength.123

119 Venkatesh, Viswanath, Michael G. Morris, Gordon B. Davis, and Fred D. Davis. 2003. “User Acceptance of Information Technology: Toward a Unified view1.” MIS Quarterly 27 (3): p.447 120 Tsai and LaRose. p.347. 121 Venkatesh at al. 2003. p.462 122 Tsai and LaRose. p.347. 123 Venkatesh, V., J. Thong, and X. Xu. 2012. “Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology.” MIS Quarterly 36 (1): 157–78.


MAY 24, 2016 2-14

The components of UTUAT and UTUAT2, initially developed for workplace technology

adoption, are useful additions in understanding household adoption. In a cross-country

study of mobile health services, Dwivedi et al. (2016) found that price value was a

consistent determinant of adoption, while hedonic motivation was not a significant factor

in the U.S. and Canada.124 This is consistent with previous NTIA studies, where

affordability was consistently cited as an inhibitor to adoption by nearly a third of potential

adopters.

Discussion

Understanding technology adoption theories can help to identify the causalities and

potential barriers to broadband adoption. Table 1 shows the various theories employed to

better understand technology adoption. Only UTAUT2 includes the price value trade-off of

technology adoption, although TAM and DoI do consider relative advantage of adoption

over current methods, which could include an inherent cost consideration. While there is

significant overlap among key components in each of the theories, the underlying

definitions differ somewhat, and empirical studies often use a set of subcomponents that

further define and quantify the component.

Some research has been conducted to test the fit of different models and each of the

associated components. Expected outcomes are consistently the greatest indicator of

broadband intentions, with learning (observational and enabled), and self-efficacy and

habit strength also having a positive influence.125 Given that so many theories rely on a

measure of “relative advantage” in its various permutations, analysis should stratify the

124 Dwivedi, Yogesh K., Mahmud Akhter Shareef, Antonis C. Simintiras, Banita Lal, and Vishanth Weerakkody. 2016. “A Generalised Adoption Model for Services: A Cross-Country Comparison of Mobile Health (m-Health).” Government Information Quarterly. p.9 125 LaRose et al. 2012. p.2588


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Table 1

Potential Models/Theories to Understand Broadband Adoption

Theory ->

Components

Diffusion of Innovations

(DoI)

Social Cognitive

Theory (SCT)

Model of Adoption of Technology

in Households

(MATH)

Technology Adoption

Model (TAM)

Unified Theory of Adoption

and Utilization

of Technology

(UTAUT)

UTAUT2

Relative Advantage

X “expected outcomes”

“perceived usefulness”

“performance expectancy”

“performance expectancy”

Compatibility

X *

Complexity X “self efficacy” “control beliefs”

“perceived ease of use”

“effort expectancy”

“effort expectancy”

Trialability X “enactive learning”

Observability X “observational learning”

Normative Beliefs

X X

Attitudinal Beliefs

X X **

Habit Strength

X X

Hedonic Motivation

X

Price Value Perceptions

X

Facilitating Conditions

X X

Control Variables

Age X X

Gender X X

Experience X X

* Some elements of attitudinal beliefs fall under compatibility ** Some elements for facilitating conditions and hedonic motivation fall under attitudinal beliefs


MAY 24, 2016 2-16

benefits associated with different classes of users. The Brown and Venkatesh (2005)

categorization of households differentiated the different needs based on household life

cycle stages, a potentially useful construct for analysis of future adoption programs.

Trialability, observability and habit strength are key components to many digital literacy

programs, and can have a direct impact on complexity. Programs such as Older Adults

Technology Services (OATS) digital literacy training to seniors claim strong results, with 93

percent of seniors receiving training still using computers after 6 months.126 However,

articulating a compelling relative advantage unique to target communities is critical to

gaining interest from those that do not see it as relevant to their lives. Those communities

are not likely to invest the time in digital literacy training in the first place if broadband is

not relevant to them.

Other Potential Components

While technology adoption models seem robust, some factors are not included either

explicitly or implicitly in current research on broadband adoption. There is recognition

that there are key, known enablers (computers and broadband access), indicators (cable

television), and inhibitors (installation and recurring costs) to broadband adoption. This

section discusses some of additional components that could be considered as indicators or

influences for broadband adoption.

Mobile Broadband. While most global metrics focus on the fixed portion, there is

increasing interest in recognizing the utility and value proposition of mobile broadband.

The U.S. has pursued a largely fixed broadband strategy, even though mobile broadband

may be more appropriate, relevant, and beneficial for major segments of the population. As

126 Davidson, Charles M., Michael J. Santorelli, and Thomas Kamber. "Toward an inclusive measure of broadband adoption." International Journal of Communication 6, no. 0 (2012): p.2560


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discussed earlier, more adopters are choosing mobile broadband over (or in addition to)

fixed broadband. The perceived importance may shift among several factors (at a

minimum: relative advantage, compatibility, complexity, trailability, observability, habit,

norms, attitudes, and price value) that can heavily influence the medium chosen to access

broadband services.

Relative advantage by broadband modality may be a key distiction among different adopter

communities. Fixed broadband is useful for large data transfers, video, and high volume

transactions, while mobile broadband may be more suitable for those in motion (GPS and

navigation tools). Mobile high speed data generally has a smaller entry cost (the cost of a

smartphone) and generally does not require great digital literacy. The needs of the

subscriber may be met through the suite of services available through smartphones, tablets

and laptops using cellular wireless.

Mobile broadband consumers represent a different class of consumers, such that the model

should allow for mobile solution adoption that reflects the different values and beliefs of

different user communities.127

Broadband Services. Broadband itself, fixed or mobile, is insufficient to compel adoption.

The applications for use are what drive relative advantage, and to the extent the types of

applications or services rendered can be characterized and catalogued, it may help to serve

as an indicator for broadband adoption. The perceptions of the relevance and value of

broadband services and its content may drive user decisions about its role in their life.128

Gangadharam et al. (2012) defined meaningful broadband adoption that goes beyond just

127 Beard, T. Randolph, George S. Ford, Lawrence J. Spiwak, and Michael Stern. 2010. “The Broadband Adoption Index: Improving Measurements and Comparisons of Broadband Deployment and Adoption.” Federal Communications Law Journal 62 (2): p.382 128 LaRose et al (2012). p.2579


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connection and subscription. They define it as the “institutions, organizations, and even

informal groups that serve to welcome new users into broadband worlds; share social

norms, practices, and processes related to using these technologies.”129 It is more than a

service; it is entering an environment in which a set of services – unique to each subscriber,

allows them to engage broadband services in a useful and valued way. (See Note 130).

Social Premia. In economic models for adoption, there is a tendency to focus on the

individual benefits and rational behavior. However, including community-level social

components could help to focus on social dimensions of broadband adoption.131

Some of these components have been included in a proposed broadband adoption index

that includes a social premia (benefit spillovers) for different “classes of users” based on the

value they place on different applications that traverse broadband connections.132

Potential adopters could be exposed to broadband through education and entertainment,

the workplace, anchor institutions (libraries, community centers, schools), or social groups.

129 Gangadharan, Seeta Peña, and Greta Byrum. 2012. “Broadband Adoption| Introduction: Defining and Measuring Meaningful Broadband Adoption.” International Journal of Communication 6 (0): 8. p.2602 130 Adoption is not all good. As our nation becomes enamored with the potential of broadband access, policies need to be in place at each level to manage for unintended consequences. Some literature suggests that there is also some less obvious societal complexities and costs, including worker isolation (telework), e-gambling, and the potential for more sedentary lifestyles that could lead to poor health (Firth and Mellor. 2005). While broadband has its potential for enhancing societal goals, it also has its dark side in illicit sites and cybercrime, in addition to consumer commitment to long-term contracts for sizable fees. While much is said about the benefits of technology in the schools, there are policy needs at the local and school level as well. Without limits and controls, information and communications technologies can be a distraction for students. In fact, Belo, Ferreira, and Telang (2013) showed a significant drop in school performance measured in terms of bandwidth consumed. For example, schools with access to bandwidth-intensive Youtube had a more significant drop in student scores than those who restrict its access. 131 Gangadharan, Seeta Peña, and Greta Byrum. 2012. “Broadband Adoption| Introduction: Defining and Measuring Meaningful Broadband Adoption.” International Journal of Communication 6 (0): 8. p.2601 132 Beard, T. Randolph, George S. Ford, Lawrence J. Spiwak, and Michael Stern. 2010. “The Broadband Adoption Index: Improving Measurements and Comparisons of Broadband Deployment and Adoption.” Federal Communications Law Journal 62 (2): p.381.


MAY 24, 2016 2-19

(See Note 133). Social premia is most closely related to the normative beliefs component of

the TAM and MATH theories.

Network Effects. Current research does not explore potential broadband “tipping points”

in which a critical mass is reached that could influence inclusion by remaining non-

adopters. Network effects suggest that the value of the network increases non-linearly

with the addition of each new node.134 Using this construct could illustrate some of the

challenges in rural socio-economically challenged communities – without sufficient

subscribers, the value is diminished to potential adopters. Characterizing this in the

context of broadband adoption may be a useful construct to see if there are “tipping points”

within communities that make the relative advantage much greater. More subscribers

could also have the impact of better economies of scale for network providers or make the

area more enticing for new market entrants (competition), potentially lowering costs and

making the relative advantage even more compelling.

Workplace Exposure. While the UTUAT models both speak to workplace experience, a

broader component may be the trialability or observability of potential subscribers in the

workplace. Understanding how much exposure in the work environment takes place may

be a strong indicator of broadband adoption in the household. One metric to be considered

is the percentage of information technology centric businesses that may be located within

adopter and non-adopter communities.

133 Beard et al. p.353-354. The term social premia is used to “abstract from the rigid economic concept of externalities.” It allows incorporation of social value “without necessarily satisfying the economic criterion of externality.” It can vary across users – such as those that use broadband for education (high social premia) and those that use it for entertainment (low social premia)… There are also negative social premia, which could include terrorist activity, cyber-bullying, identity theft, and any negative consequences associated with online access. With the relative recency of broadband, there are few (and largely imperfect) empirical measurements of social premia. 134 Tilly, Bob Briscoe, Andrew Odlyzko, Benjamin. 2006. “Metcalfe’s Law Is Wrong.” IEEE Spectrum: Technology, Engineering, and Science News. 7–1.


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However, access through the workplace in unserved or underserved communities may be

limited. Among the key considerations for businesses to relocate to areas is the adequacy

of telecommunications infrastructure available to them.135, Businesses will not locate to

areas without robust infrastructure, so the community does not get exposed and is less

likely to adopt, lowering demand, and ultimately lowering investment in infrastructure.

Without a digitally literate workforce, higher income jobs will not come to rural areas and

the cycle begins again, with the workforce not expanding its digital skills. It also forces

rural communities to subsist on lower incomes, making broadband relatively less

affordable, and adoption goes down, as does investment in infrastructure. Out-migration of

children is also a factor – broadband can improve education and reduce exodus of the

young, but without the more educated and young in these communities today, there is less

demand for broadband services, and fewer businesses that create demand. The cycle

continues.

Cost Uncertainty/Volatility. For many potential adopters, the uncertainty of installation

and recurring costs are deterrents to adoption.136 Federal programs such as Link-Up and

Lifeline have attempted to mitigate those concerns with installation discounts and lower

fixed monthly costs, but only a third of those eligible utilize these plans for fixed broadband

connections. Users of mobile broadband service can also experience volatility in the

recurring charges. Many services are usage sensitive and pay as you go, while still others

lock consumers into a plan, and will escalate charges for usage above the minimum.

Capturing pricing dynamics and the perceptions of the potential adopters could

complement the price value component of any model for broadband adoption.

135 Malecki. pp. 204, 212 136 Gideon and Gabel. p.743


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Cost as a Percentage of Income. On average, people spend less than 3 percent of their

income on telecommunications services.137 While costs are relatively uniform for different

levels of service, affordability is a factor when the percentage of income becomes too high

and begins to make trades with other discretionary income. This will factor into the

relative advantage evaluation for households.

Conclusions.

Ninety percent of the government’s $4 billion investment in broadband went to the supply

side, building out infrastructure to ensure households (and anchor institutions) have

access to broadband (BTOP, Connect America Fund and E-Rate). While this is necessary, it

is insufficient. Consumer subsidies were provided to help make service more affordable

(Link-Up and Lifeline), but they have had little impact. In fact, there is a growing number

that have disconnected in favor of mobile broadband (smartphones) or go off the grid

completely.

Some resources have focused on the demand side, most notably the State Broadband

Initiatives. These have primarily focused on digital literacy (training) programs, trying to

increase consumer self-efficacy and confidence in their skills. However, there are no

programs that focus on the relative advantage (perceived effectiveness or expected

outcomes) that have been the focus of adoption theories and models.

The current digital divide is characterized by its geography (primarily rural) socio-

economic (primarily low-income) and demographic inequalities (primarily Hispanics and

non-Asian non-white). While this is a useful construct for fixed broadband penetration, it

is insufficient for adoption. Demographics are not a good indicator of intentions for

137 Hilbert. p.724


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broadband adoption.138 Understanding the target communities by their needs or life stages

can help to define the value proposition that could compel them to seek exposure and

learning and financial assistance to enable adoption.

Existing models may need to be expanded or modified to allow greater insight into

broadband adoption. While there are considerable government efforts to collect, organize

and make available broadband deployment data, there is little data on the broadband

adoption. Recent surveys are beginning to shed light on adoption, and these must be

exploited and combined with other data sources to gain insight. These insights could

create more targeted programs that increase demand in these communities. Government

programs could assist in ensuring business communities have the infrastructure they need,

which will further build the digital literacy and skills in communities through exposure in

the workplace, and foster great demand. Targeted programs to comprehend the inherent

norms and attitudes within consumer communities and influence the trade-offs of relative

advantage will also foster greater demand for broadband services. With increased demand,

suppliers will compete to offer affordable, differentiated services.

Finally, while most global metrics focus on fixed broadband penetration there is increasing

interest in recognizing the utility and value proposition of mobile broadband. The U.S. has

pursued a largely fixed broadband strategy, even though mobile broadband may be more

appropriate, relevant, and beneficial for major segments of the population.

Research methods and empirical models to evaluate the appropriateness of current

technology adoption theories and potential new factors are discussed in a Part 3:

138 LaRose et al. 2007. p.368


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“Evaluating Theories of Adoption for Broadband: Potential Research Methods and Data

sources.

Evaluating Theories of Adoption for Broadband: Potential Research Methods and Data sources

ABSTRACT

In the U.S., broadband adoption still lags behind availability. Most digital divide literature calls attention to the striking demographics that characterize this digital divide. However, technology and adoption theory looks to behavioral attributes of communities as the causal influence whether or not to adopt. Several theories have been offered and tested for technology diffusion and adoption. The models include relative advantage, norms, attributes and controls that influence human behavior. To evaluate these human behavior attributes, they must be explored, captured and analyzed to determine their relative influence on broadband adoption.

This paper explores various research methods to test technology adoption models and their applicability to broadband. It includes both qualitative and quantitative methods, and explores visualization and spatial techniques that could further understanding of contagions and spillovers. It concludes with a set of preliminary data sources unveiled through the literature that could help to quantify and compare behavioral attributes between adopter and non-adopter communities. Keywords: Broadband, Research Methods, Statistical Models, Broadband Data Sources,

Technology Adoption

EVALUATING THEORIES OF ADOPTION FOR BROADBAND: POTENTIAL RESEARCH METHODS AND DATA SOURCES SECOND DRAFT

MAY 24, 2016 3-1

Since the beginning of the telecommunications industry, the U.S. federal government has

created policies, regulations, and incentive programs to ensure universal service

nationwide. What was once an imperative to have a telephone in every household has

evolved into an imperative for internet access – specifically broadband access. In recent

years, the federal government has spent over $4 billion to build out a fixed infrastructure

and provide digital literacy training to unserved Americans. Despite this increased

connectivity, fixed (wired) broadband adoption remains low. Many have adopted mobile

devices for their relatively low cost, flexibility, and ease of use. Still others have simply

disconnected entirely. Rural areas, low-income communities, and the elderly are the least

likely to connect. With society becoming increasingly reliant on high-speed internet for

essential services, the imperative to narrow the digital divide is critical.

State and federal government programs have focused on training consumers how to use the

new services, but they have not assisted consumers in understanding why they should use

them. Technology adoption theories all focus on relative advantage (performance

expectancy, perceived usefulness, or expected outcomes) as the key influence of intent to

adopt technology.

Most of the models for technology adoption have the same key elements. In each of the

prominent models (DoI, SCT, MATH, TAM, UTUAT, and UTUAT2), consumers must see the

relative value over their current environment. Each of the household adoption models (all

but the UTUAT models) also include some other factors that influence human behavior

such as norms, attitudes and control elements. The UTUAT and UTUAT2 were created

more for organizational (workplace) technology adoption, so factors include facilitating

conditions, age, gender and experience. The UTUAT2 model was adapted for a consumer


MAY 24, 2016 3-2

use context, and includes habit strength, hedonic motivation, and price value

considerations.139

5. POTENTIAL RESEARCH METHODS FOR ANALYSIS

In the past 30 years, extensive research has been conducted on technology adoption

models, primarily adoption of equipment or devices, such as personal computers and

tablets. Network effects have been studied in the diffusion of fax machines and cellular

technologies to understand how networks increase in value as more subscribers join the

network, and therefore attract more subscribers.140 New research in technology diffusion

studies the effects of contagion (following the S-curve), information cascades (fostered

through network externalities), density dependence (a certain density of users promotes

more rapid adoption),141 and critical mass or “tipping points” (once a level of adoption is

reached, others are compelled to join or else miss out on the benefits).142,143 Most of the

methods used to measure the influence of these effects on adoption employ instrument

variables and a form of linear regression. The specific method is highly dependent on the

availability and type of data sought. This section will review some of the potential methods

and their appropriateness for analyzing broadband adoption.

139 Venkatesh, V., J. Thong, and X. Xu. 2012. “Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology.” MIS Quarterly 36 (1): p.160. 140 Lee, Sangwon, Justin S. Brown, and Seonmi Lee. 2011. “A Cross-Country Analysis of Fixed Broadband Deployment: Examination of Adoption Factors and Network Effect.” Journalism and Mass Communication Quarterly 88 (3): 580–96. http://search.proquest.com.mutex.gmu.edu/docview/903556245. 141 Geroski, P. A. 2000. “Models of Technology Diffusion.” Research Policy 29 (4–5): 603–25. doi:10.1016/S0048-7333(99)00092-X. 142 Guseo, Renato, and Mariangela Guidolin. 2010. “Cellular Automata with Network Incubation in Information Technology Diffusion.” Physica A: Statistical Mechanics and Its Applications 389 (12): 2422–33. doi:10.1016/j.physa.2010.02.007. 143 Grajek, Michał, and Tobias Kretschmer. 2012. “Identifying Critical Mass in the Global Cellular Telephony Market.” International Journal of Industrial Organization 30 (6): 496–507. doi:10.1016/j.ijindorg.2012.06.003.

http://search.proquest.com.mutex.gmu.edu/docview/903556245

http://dx.doi.org/10.1016/S0048-7333%2899%2900092-X

http://dx.doi.org/10.1016/j.physa.2010.02.007

http://dx.doi.org/10.1016/j.ijindorg.2012.06.003


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The Data. The majority of research completed in this field relies on demographic data

collected from the U.S. Census combined with survey data in targeted regions where there

is a high percentage of non-adopters (e.g. rural areas, low-income areas of inner cities).

The type of method will depend on the type of human behavior data, which is often not

available or highly speculative. For example, expected outcomes could range from a simple

cost-benefit analysis, trade-off with precursors that a consumer is accustomed to, or more

subjective choice based on image or status. Expected outcomes will depend on what

services the consumer values, such as productivity enhancement, education, social

networking, etc. Identifying these services and their value may lead to different technology

choices (e.g. email only needs a slow connection, but streaming video requires a high-speed

connection) and different access technologies (e.g., computer, tablet or smartphone).

The norms, attitudes, and control components of human behavior are more nuanced.

Norms and attitudes lead to more of the cultural and social aspects of human behavior,

where control deals with risks, fears, and uncertainties. Survey questions in the past have

used well-constructed questions and Likert scales to quantify these behavioral elements.

Defining a robust data structure behind each of the human behavior components allows a

more rigorous and defined approach, creating an index or combined variable that can

account for each of the theory components. These variables will not likely be completely

mutually exclusive and will have some correlation with one another that must be measured

and mitigated when running any regression analysis.

Testing Data/Variable Validity. Data should be well understood for its validity before

subjecting it to analysis. Outliers, missing data, and data entry errors can skew and

invalidate results. Researchers conduct visual and statistical tests to determine the validity


MAY 24, 2016 3-4

and completeness of the data. Pearson Product Correlations and VIFs across the

independent variables will yield potential multicollinearity. Lin (1998) and LaRose et al.

(2012) both used the Pearson Product Correlations, 144,145 while Tsai and LaRose (2015)

used VIF in their technology adoption models.146

Heteroskedacity can challenge statistical significance in regression models. It occurs when

the variance of the dependent variable is non-uniform as the independent variable changes

over time. A common way to see if there is heteroskedasticity is to generate a scatterplot

and visualize the data. If the scatter is not uniform along a common line, then

heteroskedasticity exists. Many of the technology adoption models utilize statistical tests

that can detect heteroskedasticity, including Park, Breusch–Pagan, and Cochran’s C.

To perform linear regression, the data also needs to be linear. This may require the

researcher to transform the data to allow it to be utilized in the model. Transformation

generally will require a non-linear manipulation, like taking the log of a variable, squaring

it, or the equivalent.

The methods to analyze the data are varied, but to understand broadband adoption, the

data must reveal indications that change with time and/or place. For example, how do

norms, attitudes, and controls differ between adopter and non-adopter communities? How

do they change over time? Are there treatments that can be attributed to significant

144 LaRose, Robert, Kurt DeMaagd, Han Ei Chew, Hsin-yi Sandy Tsai, Charles Steinfield, Steven S. Wildman, and Johannes M. Bauer. 2012. “Broadband Adoption| Measuring Sustainable Broadband Adoption: An Innovative Approach to Understanding Broadband Adoption and Use.” International Journal of Communication 6 (0): 25. p.2587 145 Lin, Carolyn A. 1998. “Exploring Personal Computer Adoption Dynamics.” Journal of Broadcasting & Electronic Media 42 (1): 95. 146 Tsai, Hsin-yi Sandy, and Robert LaRose. 2015. “Broadband Internet Adoption and Utilization in the Inner City: A Comparison of Competing Theories.” Computers in Human Behavior 51, Part A (October): p.349.


MAY 24, 2016 3-5

changes in the norms, attitudes and controls that will foster broadband adoption? Are

there different weights or attributes that affect the adoption of fixed or mobile broadband?

The methods below will describe and explore different methods to collect and analyze the

data.

Field Research/Case Studies. Field Research could be conducted to explore and compare

communities that are similar in all respects except adoption. Field research can include

document and archival records, observations, structured interviews and surveys, and

focused interviews.147 It allows a more nuanced understanding of the communities and can

help to identify distinctive differences among adopters and non-adopters. It can also shed

light on unknown exogenous factors that are unidentified in current models and datasets

that could influence adoption.

To understand the relative value, norms and social patterns that influence behavior, some

focused interviews are needed to understand the services that are most valued, social

contexts, awareness of others using the technology, self-efficacy, and cost considerations. A

structured interview guide will help to foster consistency and comprehensiveness. A well-

conceived data collection plan is necessary to obtain the best cross-section of a particular

area. To make the research more representative and generalizable, as many paired

research areas (adopters and non-adopters) as possible should be included. While not as

rigorous as statistical analysis, case studies can serve to gain valuable insight and context

that may not be otherwise attainable for technology adoption.

147 Yin, Robert K. 2013. Case Study Research: Design and Methods. 5 edition. Los Angeles: SAGE Publications, Inc. p.121


MAY 24, 2016 3-6

Surveys (Using Cross-Sectional Designs). Several of the research studies on adoption

theory used mailed surveys to gather information on human behavior and their intent to

adopt technologies. Surveys can reach thousands of addresses in targeted areas of interest

(rural, inner cities). For each, pre-notifications, questionnaires, reminder postcards, and a

second, certified mail questionnaire ensure higher response rates. Using this process,

LaRose et al. (2012) achieved an over 40 percent response rate.148 The physical survey

also included a URL to take the survey online, with a 10 percent response rate. In this case,

distributing the URL via the paper survey was appropriate, since some of the intended

respondents may have access through work or through anchor institutions.

These surveys must be designed such that there is little ambiguity and the results are

definitive. Unlike the field research, there is not a researcher present to clarify the

question. With the exception of binary questions, most answers could be provided through

multiple choice or through a Likert scale. Pearson correlations can be calculated to

determine the association among variables. Cronbach’s Alpha can be used to test the

internal consistency of the Likert Scale answers. Composite Reliability (CR) can be tested

to show the reliability of heterogeneous variables.

Longitudinal Studies. Technology adoption is part of a process, that may require

technology exposure, learning, social pressures, or other time consuming elements before a

decision to adopt is made. Longitudinal studies also assist in understanding causality,

which can be especially difficult in technology adoption, particularly broadband. For

example, broadband can lead to better education, and better-educated people often are

early adopters of broadband.

148 LaRose et al. p.2587


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Field research (interviews) and surveys can be done over time to see potential changes in

the data, but the subjects of interviews or survey respondents may change over time. This

creates challenges to replicable data that measures change. The larger the sample size (and

the more it represents a cross-section of the larger population), the more repeatable and

credible the documented changes will be.

The Current Population Survey (CPS) polls over 56,000 households each month, and tries

to keep recipients for four years in a rolling fashion.149 It is large enough and

representative enough to utilize for longitudinal research, to characterize changes over

time. While it has key demographics and some questions on internet use at home, it does

not have the direct human behavior questions sought by technology adoption theories

(unless they can be inferred through proxy variables). It also lacks the granularity to

isolate smaller non-adopter communities, instead only providing information by State. The

CPS was often combined with surveys to complete a well-rounded dataset. Results were

compiled and the general characteristics of the sample can be compared to that of the

general population in the area to determine if there is a response bias. These results can be

analyzed and reliability assessed.

Panel Study. Panel studies survey the same sample at different times and explore the

potential affects of an intervention, or “treatment.” Comparing this sample to a control

group before and after without the treatment, we can see the direct impact of such

treatment. In this case, both groups may have the same endogenous factors affecting them,

leaving the only distinctive cause and effect to be that of the treatment. For example, two

rural areas were selected that were similar in virtually every way, including a low

broadband adoption rate. One of the areas may be subject to the treatment, which could be

149 NTIA. 2015. “Current Population Survey Internet and Computer Use.” June.


MAY 24, 2016 3-8

a digital awareness and literacy program, or introducing high-speed broadband at the

community anchor institution. The two areas could be compared post treatment to

discern if there was a measurable change in broadband adoption, ostensibly due to the

treatment.

Panel studies also offer an advantage in their ability to handle large events outside the

model parameters. For example, both areas may be affected by the economic recession, so

both would be impacted in similar ways, once again making the treatment the only

difference maker. Care must be taken that the two areas indeed are similar – if one area

reacted to the economic recession differently (e.g., launched subsidy programs, invested in

computer programs in schools, or Comcast launched its “Internet Essentials” program in

one area), then the results may not be solely as a result of the treatment.

Stochastic Methods

Empirical models can give statistical significance to findings and determine the degree to

which a dependent variable is determined by a set of independent variables. Data

characteristics of the variables determine the appropriate analytical method.

Factor Analysis. Factor analysis is used if there are underlying (unobserved) factors that

create relationships among variables.150 For the purpose of assessing human behavior, a

set of questions may attempt to characterize a particular attribute (e.g. relative advantage).

Many of the questions collected through surveys will be on the Likert scale, making the

data both continuous and categorical, a requisite condition for factor analysis. Factor

150 Hutcheson, Graeme D., and Nick Sofroniou. 1999. The Multivariate Social Scientist: Introductory Statistics Using Generalized Linear Models. SAGE Publications Ltd.


MAY 24, 2016 3-9

analysis simplifies the data by statistically determining the underlying relationship among

disparate questions. The variables that create the factor will be highly correlated.

Factor scores can be extracted and used as a latent construct in general regression analysis

to eliminate the multicollinearity among the original variables. In a study of mobile health

adoption, Dwivedi et al. (2015) used factor analysis to verify grouping of survey variables

and test the contribution of each variable to the construct, eliminating those that did not

have meaningful contribution.151

Principal Component Analysis (PCA). While factor analysis studies the relationships

among variables, PCA creates a weighted combination of variables that account for large

portions of the variance in the sample. Each component (or combination) must both

account for a significant portion of the variance and be uncorrelated with one another. For

example, it would hopefully be possible to create components for norms, attitudes and

controls, each made up of a weighted combination of underlying variables (based on factor

analysis), with each component being largely uncorrelated with another. This may be

challenging given that elements of human behavior are not finitely measured, and

expectations are that norms, attitudes, and controls will influence each other.

ANOVA. Analysis of Variance (ANOVA) uses the means and variance of each of the

variables and compares them with one another to determine if they are statistically

different. In studying the adoption of personal computers at home, Lin (1998) used ANOVA

to compare communities of adopters, likely adopters, and non-adopters. Her findings

showed that demographic background (education, children, income and age), TV use,

151 Dwivedi, Yogesh K., Mahmud Akhter Shareef, Antonis C. Simintiras, Banita Lal, and Vishanth Weerakkody. 2016. “A Generalised Adoption Model for Services: A Cross-Country Comparison of Mobile Health (m-Health).” Government Information Quarterly. Accessed March 2.


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technology ownership, and most adoption barriers (except complexity) to be significantly

different among communities.152

Ordinary Least Squares (OLS) Regression. Most of the analysis of technology adoption

used some form of least squares regression. This allows the independent variables

(behavioral variables) to predict the dependent variable (broadband adoption) by

minimizing the sum of the square of the residuals (the delta between the predicted value of

the independent variable and the actual value of the variable). The lower the sum of the

squares, the better fit for the model. While the model is relatively straightforward and

simple, an understanding of the data is required to ensure it is unbiased and conforms to

required data properties (e.g., continuous, asymptotic [normal] distribution, free from

collinearity among independent variables). After performing ANOVA to determine the

significant differences among communities, Lin (1998) used multiple regression analysis to

calculate significance of the predictor variables to PC adoption rates, finding that income

and age, television viewing and technology ownership were all significant contributors to

PC adoption. 153

After conducting Pearson correlations and multicollinearity tests on the variables, Tsai and

LaRose (2015) used OLS regressions on the groups of variables associated with each

adoption theory (DoI, SCT, and MATH) in their study of inner city broadband adoption.154

They calculated the R2 to test the “fit” for each of the models. The fit determines how much

of the variance of the independent variable can be explained by the model. In their study of

m-health adoption in multiple countries, Dwivedi at al. used a variety of indexes to measure

152 Lin. 1998. p.95. 153 Lin. 1998 p.95. 154 Tsai and LaRose. 2015. p.349.


MAY 24, 2016 3-11

fit, including Goodness of Fit index (GFI), Root Mean Square Error of Approximation

(RMSEA), Comparative Fit Index (CFI) and the Normed Fit Index (NFI).155

Instrument Variables (IV). In some cases, one or more of the independent variables are

correlated with the error term, possibly to some unknown endogeneity, creating an

asymptotic bias. This requires the creation of a new “Instrument Variable” or IV that is

correlated with the original regressor but not with the error term. There are multiple

approaches to creating IVs including substituting variables with rank orders or finding an

exogenous factor that is correlated with the old regressor but not the error term. For

technology adoption, since omitted variables may appear in the error term and be highly

correlated with the regressor, IVs may be necessary to ensure there is no bias in the model.

For example, Peng et. al. (2011) used mean education, mean number of people in a

household, and mean minority within an MSA to create an IV for technological

embeddedness. This IV was used in a two-stage IV probit model.156

Probit Model. When the dependent variable is dichotomous (e.g. whether or not there is

intent to adopt broadband), the probit model is often used. It converts the normal

distribution function into a cumulative distribution function, so that the probability of

technology adoption results. The unobservable “utility” of a technology is calculated and

compared to a threshold that yields a determination for intent to adopt. Roycroft (2009)

used a probit model to estimate broadband adoption based on sources for television

service. 157

155 Dwivedi. 2016. 156 Peng, Gang, Ying Wang, and Rammohan Kasuganti. 2011. “Technological Embeddedness and Household Computer Adoption.” Information Technology & People 24 (4): 414–36. 157 Roycroft, Trevor R. 2013. “Empirical Study of Broadband Adoption Using Data from the 2009 Residential Energy Consumption Survey.” Journal of Regulatory Economics 43 (2): 214–28.


MAY 24, 2016 3-12

Nonlinear Regression. In a few cases, researchers have found that a non-linear regression

model more appropriate for analysis (e.g., when the model for adoption has an exponential

factor that might reflect contagion). While most often these variables are transformed,

many statistical tools can now function without the transformation, most often using an

iterative model (such as Gauss-Newton or Newton-Rapson).158 In their study of cellular

automata with network incubation and diffusion, Guseo and Guidolin (2010) looked at the

diffusion of U.S. fax machines over 20 years, using weighted nonlinear least squares

methods.159

Spatial models.

Spatial association of variables offers insight into how communities or adjacencies can

influence one another. Tools such as ArcMap offer spatial displays of data to better

comprehend proximities and convey much information in a single visual, typically a map.

The U.S. government is currently using a nationwide broadband mapping tool on their

website to allow researchers and policy-makers to analyze and understand broadband

availability in their area.160

In creating spatial models, researchers assess which of the observations they believe could

be connected or influenced by one another. Then a distance metric is created, which is

often strict geographic proximity. However, there may be other distances that are

meaningful, such as distance to workplace, distances among community anchor

institutions, or distances between geographic “clusters” of similar communities (useful in

looking at isolation or spillovers).

158 Kennedy, Peter. 2008. A Guide to Econometrics. 6th Edition. 6 edition. Malden, MA: Wiley-Blackwell. 159 Guseo and Guidolin. 2010. p.2422–33. 160 NTIA. 2014. “Broadband Map - Technology.” National Broadband Map. June 30.


MAY 24, 2016 3-13

To test spatial correlation, a Local Moran’s I statistic is often used, creating a Z-score with

the mean and variance. In the case of broadband availability, the Local Moran’s I might use

contiguous edges of counties, since it is expected that fixed infrastructure would be

deployed in counties with physical adjacencies. This eliminates the possibility of distance-

based spatial relationships that might have fixed infrastructure “jump” over an adjacent

county to connect with another county.

Local Moran’s I and Getis-Ord General G are used to identify high-high and low-low

adoption clusters. A previous spatial study conducted by the author showed clusters of

high-high broadband penetration near population centers, and low-low concentrations in

Alaska, remote parts of central U.S. and the deep south. However, these results reflect only

broadband availability, not adoption.

Just as a dependent variable might be “lagged” in time to understand causality, spatially

lagged dependent variables may be necessary to understand the influence of adjacent

observations. A spatially lagged dependent variable model can be estimated using two-

stage instrumental variable estimation, instrumenting the variable by both its current value

and those of adjacent observations.

Spatial autocorrelation must be tested to understand the concurrent and lagged

relationship with the observation itself and spatial adjacencies. To test whether the spatial

autocorrelation is spurious (as a result of errors or experimental design) or real (true

relationships exist within observations of the dependent variable and/or with independent

variables), several statistical tests can be used, including the Moran’s I, Mantel, and the

LaGrange multiplier. The LaGrange multiplier is used to test the sample properties for


MAY 24, 2016 3-14

omitted spatially lagged dependent variable, spatial heterogeneity, and spatial error

autocorrelation.161

Mixed Methods.

Finally, the research approach may use a combination of different methods to better

understand the environment, data, and other processes or externalities that could affect

technology adoption. Typically, elements of observation, document/archival research, and

interviews can help set the stage, build context, and help drive the collection of salient

variables. Statistical analysis can provide rigor and expose potential strengths and

weaknesses in the initial assumptions. Follow-up interviews can help to confirm findings

or expose potential externalities that were not initially considered.

161 Anselin, Luc, Anil K. Bera, Raymond Florax, and Mann J. Yoon. 1996. “Simple Diagnostic Tests for Spatial Dependence.” Regional Science and Urban Economics 26 (1): 77–104.

APPENDIX A: REGULATORY CAPTURE: PLAYERS AND INFORMATION ASYMMETRIES

RON HODGE MAY 24, 2016 A-1

Players/

Dynamics Descriptive

Characteristics Information

Asymmetries

Notables Elected Officials

less competition -> more regulation

Fewer, bigger players have incentives to withhold information to maximize revenues

Democrats tend to favor more regulation and will engage consumer advocacy and interest groups

more competition -> less regulation

Many players expose industry competitive cost structures providing more information

Republicans tend to favor less regulation

Regulators

Lobbying or Contract background

Insiders with industry relationships often seek to maximize personal gain through future employment. They are more likely to withhold or misrepresent information.

Appointed regulators often show allegiance to party first, former industry employment second. Elected or legislatively confirmed regulators generally advocate the public (consumer) interests more than appointed

Technical background

Strong technical knowledge reduces the cost of monitoring industry information

Firms

Low competition

Incentivized to withhold cost information – or inflate costs so that regulators set price caps high

Often favor regulation to inhibit market entry by showing high fixed costs and high cross-subsidies. Goal is to maximize margins for high profitability.

High competition

Incentivized to lower the bar for new market entry

Favor less regulation to differentiate products on price or quality

Interest Groups

Public good advocates

Can help to focus and pressure regulators and elected officials to create more available affordable services or mitigate negative externalities

In cases where there are negative externalities, these groups can actually add to the higher prices/margins for industry and higher barriers to entry, inhibiting competition.

Industry Advocates

Can pressure elected officials through election spending, direct consumer advertising/engagement, and/or can influence elected officials and regulators through strategic information sharing

In a competitive environment, these groups will often favor self-regulation for maximum flexibility. In a more monopolistic environment, government regulation can help to raise margins and barriers to entry.

Intellectual/ Cognitive Capture

Inherent industry knowledge

Regulators from industry come with biases and often convinced of industry positions.

Learned industry knowledge

Industry will often target regulators with information (biased toward their position) to compel them to see things their way

Learned Academic Knowledge

Tends to utilize education and academic literature (and institutions) and less reliant on industry information

Institutional Design/ Revolving Doors

Long tenured regulators

Tend to be more agnostic to industry interests until final year in office

Can often be tough on industry to demonstrate their expertise on the issues. However, errors made by regulators (based in poor information or lack of understanding unintended consequences) can lead to diminishing the regulators reputation (and future employability)

Short tenured regulators

Measurably tend to vote with industry interests

APPENDIX B: SELECTED RESULTS OF THE PEW STUDY SECOND DRAFT

RON HODGE MAY 24, 2016 B-1

APPENDIX B: SELECTED RESULTS OF THE PEW STUDY SECOND DRAFT

RON HODGE MAY 24, 2016 B-2

RON HODGE MAY 24, 2016

Appendix C: Potential Datasets

This section contains a sample of datasets that contain relevant fields of interest that could offer insight into broadband adoption. It is by no means exhaustive. The appendix concludes with other programs and research that might offer datasets or leads to other potential data sources.

APPENDIX C: POTENTIAL DATASETS SECOND DRAFT

RON HODGE MAY 24, 2016 C-1

NTIA BroadbandUSA National Broadband Map Datasets Description: The files include all publicly available broadband data from the State Broadband Initiative. Type of files: SHP, CSV Unit of Measure: State Current as of: June 30, 2014 URL: http://www2.ntia.doc.gov/broadband-data Data Fields – Number of providers offering these services (by State) Electric Power line Terrestrial Mobile Wireless Terrestrial Fixed – Licensed Terrestrial Fixed – Unlicensed Satellite Optical Carrier/Fiber to the End User Cable Modem – Other Cable Modem – Docis 3.0 Down Other Copper Wire Symmetric xDSL Asymmetric xDSL All Other US Community Anchor Institutions (separate dataset) Joined NBM Public Schools and NCES Attributes (separate dataset)



FCC Form 477 County Data on Internet Access Services Description: Includes data on residential fixed Internet access connections per 1,000 households by county for both service over 200 kbps in at least one direction and service over 3 Mbps down / 768 kbps up.162 Unit of Measure: County (N = 3,234) Current as of: 12/31/14 URL: https://www.fcc.gov/general/form-477-county-data-internet-access-services Data Fields: Complete County FIPS / ANSI Code State FIPS / ANSI Code County FIPS / ANSI Code State Name County Name Residential Fixed High-Speed Connections over 200 kbps in at least one direction per 1000 Households Residential Fixed High-Speed Connections at least 3 Mbps downstream and at least 768

kbps upstream per 1000 Households Providers of Fixed High-Speed Connections over 200 kbps in at least one direction Providers of Residential Fixed High-Speed Connections over 200 kbps in at least one

direction Providers of Residential Fixed Connections at least 3 Mbps downstream and at least

768 kbps upstream Providers of Mobile High-Speed Connections over 200 kbps in at least one direction

162 “Form 477 County Data on Internet Access Services.” 2014. Federal Communications Commission. February 24.

https://www.fcc.gov/sites/default/files/county_map_dec2014.zip

https://www.fcc.gov/general/form-477-county-data-internet-access-services



American Community Survey Description: The American Community Survey (ACS) is an ongoing survey that provides vital information on a yearly basis about our nation and its people. Information from the survey generates data that help determine how more than $400 billion in federal and state funds are distributed each year. The ACS has data on jobs and occupations, educational attainment, veterans, whether people own or rent their home, and other topics.163 Current as of: 2014 Unit of Measure: County Data Fields: Total Population Population by race Population by age Population by gender Households by type (married, single, dual parent, single parent) Average family size School enrollment by age, gender Educational attainment Citizenship Language Employment status Population by Occupation Household income Per capita income Median Income (by gender) Poverty rates (by family type, age) Population by type of dwelling Household Marital Status Households with a computer Households with a broadband subscription

163 U.S. Census American Community Survey. 2016. “Data Tables & Tools.”



Current Population Survey (CPS) Computer and Internet Use Supplement Description: The Current Population Survey (CPS) is the source of the official government statistics on employment and unemployment. The CPS has been conducted monthly for over 50 years. Currently, it obtains interviews from about 56,000 households monthly, scientifically selected on the basis of area of residence to represent the nation as a whole, individual states, and other specified areas. Each household is interviewed once a month for four consecutive months one year, and again for the corresponding time period a year later. The July 2015 Computer and Internet Use Supplement was conducted as a supplement to that month's Current Population Survey (CPS).164 Current as of: 2015 Unit of Measure: States URL: https://www.ntia.doc.gov/page/download-digital-nation-datasets CPS Data Fields:

Age Allocation Flag Armed Forces Demographic Civilian Labor Force (See Labor Force.) Class of Worker Federal government State government Local government Private industry (including self-employed, incorporated) Self-employed (not incorporated) Working without pay Domain Duration of Unemployment Earners Edited item Education (See Level of School Completed.) Employed (See Labor Force.) Family Family Household Family Weight Final Weight Full-Time Worker Persons Group Quarters

164 National Telecommunications and Information Administration (NTIA). 2015. “Current Population Survey (CPS) Computer and Internet Use Supplement.” July.

https://www.ntia.doc.gov/page/download-digital-nation-datasets



Head Versus Householder Highest Grade of School Attended (See

Level of School Completed.) Hispanic/Non-Hispanic Origin Hours of Work Household Household Weight Householder Householder With No Other Relatives

in Household Householder With Other Relatives

(Including Spouse) in Household Industry, Occupation, and Class of

Worker (I&O) Current Job (basic data) Job Seekers All unemployed persons

who made specific efforts to find a job sometime

Longitudinal Weight Used for gross flows analysis. Only found on adult records matched from month to month.

PEMLR (Major Labor Force Recode) Labor Force Persons Employed Unemployed

Job Leavers Job Losers New Job Entrants Job Reentrants Not in Labor Force Layoff

Level of School Completed/Degree Received

Looking for Work Marital Status Month-In-Sample

Never Worked Nonfamily Householder Nonworker Nonrelative of Householder With No

Own Relatives in Household Nonrelative of Householder With Own

Relatives (Including Spouse)in Household

Other Relative of Householder Own Child Part-Time, Economic Reasons Part-Time, Other Reasons Part-Time Work Persons Part-Year Work Population Coverage Race Re-entrants Related Children Related Subfamily School, Major Activity Secondary Individual Self-Employed Stretches of Unemployment Unable to Work Unemployed (See Labor Force). Unpaid Family Workers Unrelated Individuals Unrelated Subfamily Veteran Status Wage and Salary Workers Workers (See Labor Force--

Employed.) Work Experience Year-Round Full-Time Worker



RAND American Life Panel Description: The My Household questionnaire is asked of each panel member every quarter. Data sets downloaded for the My Household survey contain the data of all panel members who completed the My Household questionnaire within the last year; that is, from May 11, 2015 to May 11, 2016. Fieldwork: This survey went in the field on 2006-01-01. Data Available: 424 unique surveys, of those of interest: Social Networks 2511 observations Cognition and Aging in the USA Internet Decision Making Survey [W01] 2188 observations Cognition and Aging in the USA Internet Decision Making Survey [W02] 2283 observations URL: https://alpdata.rand.org/index.php?page=data Unit of Measure: Household Data Fields: Varies dependent on survey. All include: Demographics (age, gender, ethnicity) Education Type of work Household information Household income Location of internet access Type of internet connection



USC Dornsife Center for Economic and Social Research: Understanding America Study Description. The Understanding America Study (UAS) is a panel at the University of Southern California (USC) of approximately 3100 individuals representing the entire United States. The study is an 'Internet Panel,' which means that respondents answer our surveys on a computer, tablet, or smart phone, wherever they are and whenever they wish to participate. Recruiting takes place via Address Based Sampling (ABS), in which postal records are used. Drawn from across the nation is a random sample, to which is sent a pre-notification letter followed by a mail survey. On the last page of the paper survey, prospective respondents are asked if they want to join the UAS panel. If they express interest, they are invited to regularly participate in online surveys. The majority of the panel members have their own Internet access. The remaining panel members have been provided Internet access by USC through the provision of a tablet and/or an Internet subscription. At this time the UAS only asks surveys of adults aged 18 and over. It is not possible to volunteer for joining the UAS. We randomly select people around the country using postal codes.165 Relevant Surveys include:

Personality (Big 5) Effects of Complexity on Investment Decisions Decision-Making Avoidance Decision-making quality Risk aversion Investment Decisions Financial Services & Decision Making Background, household, health history and cognitive abilities Consumer Financial Well-Being Experiences growing up, religious and political affiliations, and opinions on various

different statements URL: https://uasdata.usc.edu/ Data Fields Common Data fields:

Background demographics (age, gender, ethnicity) Employment status Income

Data fields will differ based on the survey under study

165 USC Dornslife, Center for Economic and Social Research. n.d. “Understanding America Study.” Understanding America Study.

https://uasdata.usc.edu/



Pew Research Center: Internet, Science & Technology: Survey on Gaming, Jobs & Broadband Description: This dataset contains questions about video games and gaming; job seeking and the internet; workforce automation; online dating; and home broadband, cable and smartphone use among Americans. It was conducted through a telephone survey.166 Unit of Measure: Individual by demographic or geography (states) URL: http://www.pewinternet.org/datasets/june-10-july-12-2015-gaming-jobs-and-broadband/ Data Fields: Key demographic identifiers (age, gender, ethnicity) State, zip code Community Rating Economy Rating Internet Use Internet Use Frequency Internet Subscription at Home High-Speed Broadband Subscription at Home Types of Internet Sources Accessed Value of “learning new things” Mobile phone ownership Smartphone internet access Reasons for not owning a smartphone Ever had broadband? Interest in having broadband? Television by satellite or cable Ever had satellite or cable television? Why not cable or satellite television? Use of Cell Phone Access to Video chat, Shop, directions, sports, movies, on line music Series of data questions on use of the internet and cell phone for dating apps Series of data questions on use of the internet and cell phone for gaming apps Employment status Work Environment Type of work (physical labor or not) Type of job Student status (not, full or part time) Ease of use for online job seeking Series of data questions on use of the internet and cell phone for online job search Series of data questions on use of the internet and cell phone regarding job security Longevity of current job Workforce automation perspectives 166 Pew Research Center, Internet, Science & Technology. 2015. “Gaming, Jobs and Broadband.” June 10–12.

http://www.pewinternet.org/datasets/june-10-july-12-2015-gaming-jobs-and-broadband/

http://www.pewinternet.org/datasets/june-10-july-12-2015-gaming-jobs-and-broadband/



U.S. Energy Information Administration: Independent Statistics & Analysis: Residential Energy Consumption Survey Description: This 2009 version represents the 13th iteration of the RECS program. First conducted in 1978, the Residential Energy Consumption Survey is a national sample survey that collects energy-related data for housing units occupied as a primary residence and the households that live in them. Data were collected from 12,083 households selected at random using a complex multistage, area-probability sample design. The sample represents 113.6 million U.S. households, the Census Bureau’s statistical estimate for all occupied housing units in 2009 derived from their American Community Survey (ACS).167 Date: 2009 URL: http://www.eia.gov/consumption/residential/data/2009/index.cfm?view=microdata Data Fields: While there are many fields that could be used to understand energy spending habits and the local infrastructure, some of the fields that stand out are the technology energy consumption indicators. Census Region Census Division Reportable states and groups of states Type of housing unit Number of televisions used Size of most-used TV Display type of most-used TV Cable box or satellite box connected to the most-used TV DVR built into the cable box or satellite box connected to the most-used TV Separate DVR connected to the most-used TV Digital converter box connected to the most-used TV Video game console connected to the most-used TV Combo VCR/DVD connected to the most-used TV VCR connected to the most-used TV DVD player connected to the most-used TV Home theater system connected to the most-used TV Other set-top box connected to the most-used TV Most-used TV usage on weekdays Most-used TV weekday usage spent playing video games Most-used TV usage on weekends Most-used TV weekend usage spent playing video games Size of second most-used TV Display type of second most-used TV

167 U.S. Energy Information Administration, Independent Statistics and Analysis. 2009. “Residential Energy Consumption Survey (RECS).”



Cable box or satellite box connected to the second most-used TV

DVR built into the cable box or satellite box connected to the second most-used TV

Separate DVR connected to the second most-used TV

Digital converter box connected to the second most-used TV

Video game console connected to the second most-used TV

Combo VCR/DVD connected to the second most-used TV

VCR connected to the second most-used TV

DVD player connected to the second most-used TV

Home theater system connected to the second most-used TV

Other set-top box connected to the second most-used TV

Second most-used TV usage on weekdays

Second most-used TV weekday usage spent playing video games

Second most-used TV usage on weekends

Second most-used TV weekend usage spent playing video games

Size of third most-used TV size Display type of third most-used TV Cable box or satellite box connected to

the third most-used TV DVR built into the cable box or

satellite box connected to the third most-used TV

Separate DVR connected to the third most-used TV

Digital converter box connected to the third most-used TV

Video game console connected to the third most-used TV

Combo VCR/DVD connected to the third most-used TV

VCR connected to the third most-used TV

DVD player connected to the third most-used TV

Home theater system connected to the third most-used TV

Other set-top box connected to the third most-used TV

Third most-used TV usage on weekdays

Third most-used TV weekday usage spent playing video games

Third most-used TV usage on weekends

Third most-used TV weekend usage spent playing video games

Computer used at home Number of computers used Most-used computer - desktop or

laptop Monitor type of most-used computer Daily usage of most-used computer Turn off most-used computer when

not in use Sleep or standby mode for most-used

computer when not in use Second most-used computer - desktop

or laptop Monitor type of second most-used

computer Daily usage of second most-used

computer Turn off second most-used computer

when not in use Sleep or standby mode for second

most-used computer when not in use Third most-used computer - desktop

or laptop Monitor type of third most-used

computer Daily usage of third most-used

computer Turn off third most-used computer

when not in use Sleep or standby mode for third most-

used computer when not in use Internet access at home Dial-up internet access



DSL or Fiber Optic internet access Cable internet access Satellite internet access Wireless internet in home Number of printers used Separate fax machine used Separate copy machine used Well water pump used Automotive block or engine heater or

battery blanket used Evaporative cooler used Large heated aquarium used Stereo equipment used Cordless telephone used

Answering machine used Number of rechargeable tools and

appliances used Charging patterns for rechargeable

tools and appliances Chargers for rechargeable tools and

appliances left plugged into wall Number of rechargeable electronic

devices used Charging patterns for rechargeable

electronic devices Chargers for rechargeable electronic

devices left plugged into wall



OECD Broadband Portal Description: The OECD broadband portal provides access to a range of broadband-related statistics gathered by the OECD.168 Unit of Measure: Country Date: June 2015 URL: http://www.oecd.org/internet/broadband/oecdbroadbandportal.htm Data Fields: Fixed and wireless subscriptions Fixed and wireless subscriptions by 100 inhabitants Yearly penetration increase Historical time series: Fixed and wireless penetration Broadband penetration and GDP Percentage of fiber connections in total broadband Machine to machine subscriptions Households with broadband access Households with access to home computer Business use of broadband Fixed broadband penetration and density Broadband penetration and total landmass DSL coverage Cable modem coverage 3G coverage Fixed broadband price ranges Average and median advertised download speeds Average advertised download and upload speeds, fixed broadband by technology Mobile broadband advertised speed ranges Fixed broadband penetration by speed tiers Actual download speeds Broadband connectivity, percentage of enterprises in each employment size class Employment of ICT specialists across the economy, as share of total employment Broadband connectivity, percentage of all enterprises Employment in the ICT sector and sub-sectors

168 OECD. 2015. “OEDC Broadband Portal.”



University of Chicago: NORC General Social Survey Description: The GSS gathers data on contemporary American society in order to monitor and explain trends and constants in attitudes, behaviors, and attributes. Hundreds of trends have been tracked since 1972. In addition, since the GSS adopted questions from earlier surveys, trends can be followed for up to 70 years. The GSS contains a standard core of demographic, behavioral, and attitudinal questions, plus topics of special interest. Among the topics covered are civil liberties, crime and violence, intergroup tolerance, morality, national spending priorities, psychological well-being, social mobility, and stress and traumatic events.169 Date: 2014 Unit of Measure: Individuals by States and Counties URL: http://gss.norc.org/get-the-data Data Fields: The survey contains hundreds of questions that could assist in understanding social norms and attitudes. It also lists internet use as it relates to social variables, belief systems, etc.

169 University of Chicago, NORC. 2014. “The General Social Survey.”

http://gss.norc.org/get-the-data



Other Programs and Research Studies with Potential Datasets Datasets may exist in these programs:

Comcast, Internet Essentials (http://corporate.comcast.com/images/MB-10-56-Comcast-Internet-Essentials-Annual-Report-2014-07-31.pdf)

U.S. Bureau of Economic Analysis Economics and Statistics Administration (ESA) Bureau of Labor Statistics Social Science Research Council (SSRC)

o Dailey, Dharma, Amelia Bryne, Alison Powell, Joe Karaganis, & Jaewon Chung. 2010. “Broadband Adoption in Low Income Communities.” SSRC. (Field Reports). http://eprints.lse.ac.uk/29459/1/Powell_etal_Broadband-adoption-in-low-income-countries_2010.pdf

Joint Center for Political and Economic Studies National Minority Broadband Adoption Study conducted in 2009 and 2010

ITU Broadband Statistics (http://www.itu.int/en/action/broadband/Pages/default.aspx)

Forrester Research (fee-based) https://www.forrester.com/Data-Services/-/E-MPL31

Survey data collected through these research studies:

Dwivedi, Yogesh K., Mahmud Akhter Shareef, Antonis C. Simintiras, Banita Lal, and Vishanth Weerakkody. 2016. “A Generalised Adoption Model for Services: A Cross-Country Comparison of Mobile Health (m-Health).” Government Information Quarterly. Accessed March 2. doi:10.1016/j.giq.2015.06.003.

Tsai, Hsin-yi Sandy, and Robert LaRose. 2015. “Broadband Internet Adoption and Utilization in the Inner City: A Comparison of Competing Theories.” Computers in Human Behavior 51, Part A (October): 344–55. doi:10.1016/j.chb.2015.04.022.

“Corporate Exec Survey Results.” 2016. Area Development. Accessed May 12. http://www.areadevelopment.com/Corporate-Consultants-Survey-Results/.

Percentage of Technology Ownership in the local area or neighborhood: o Goolsbee, Austan, and Peter J. Klenow. 2002. “Evidence on Learning and

Network Externalities in the Diffusion of Home Computers.” The Journal of Law & Economics 45 (2): 317–43. doi:10.1086/344399.

Total number of access channels to the technology by a household: o Swan, Jacky A., and Sue Newell. 1995. “The Role of Professional Associations

in Technology Diffusion.” Organization Studies (Walter de Gruyter GmbH & Co. KG.) 16 (5): 847. http://mutex.gmu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=6497002&site=ehost-live&scope=site.

o Owen-Smith, Jason, and Walter W. Powell. 2004. “Knowledge Networks as Channels and Conduits: The Effects of Spillovers in the Boston Biotechnology Community.” Organization Science 15 (1): 5–21. http://www.jstor.org/stable/30034707.

http://eprints.lse.ac.uk/29459/1/Powell_etal_Broadband-adoption-in-low-income-countries_2010.pdf

http://eprints.lse.ac.uk/29459/1/Powell_etal_Broadband-adoption-in-low-income-countries_2010.pdf

https://www.forrester.com/Data-Services/-/E-MPL31

https://www.forrester.com/Data-Services/-/E-MPL31

http://dx.doi.org/10.1016/j.chb.2015.04.022

http://www.areadevelopment.com/Corporate-Consultants-Survey-Results/

http://dx.doi.org/10.1086/344399

http://mutex.gmu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=6497002&site=ehost-live&scope=site

http://mutex.gmu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=6497002&site=ehost-live&scope=site

http://www.jstor.org/stable/30034707



Interaction Intensity between a household and the technology: o Venkatesh, Viswanath, and Michael G. Morris. 2000. “Why Don’t Men Ever

Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior.” MIS Quarterly 24 (1): 115–39. doi:10.2307/3250981.

o Schultze, Ulrike, and Wanda J. Orlikowski. 2004. “A Practice Perspective on Technology-Mediated Network Relations: The Use of Internet-Based Self-Serve Technologies.” Information Systems Research 15 (1): 87–106. http://www.jstor.org/stable/23015900.

Venkatesh, V., J. Thong, and X. Xu. 2012. “Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology.” MIS Quarterly 36 (1): 157–78. http://misq.org.mutex.gmu.edu/consumer-acceptance-and-use-of-information-technology-extending-the-unified-theory-of-acceptance-and-use-of-technology.html.

Other Notables:

Broadband Occupations (Technet) 170 o Michael Mandel, “Where the Jobs Are: The App Economy.” February 2012.

Available online at: http://www.technet.org/ wp-content/uploads/2012/02/TechNet-App-Economy-Jobs-Study.pdf

170 Technet. 2012. State Broadband Index. http://www.technet.org/wp-content/uploads/2012/12/TechNet_StateBroadband3a.pdf

http://dx.doi.org/10.2307/3250981

http://www.jstor.org/stable/23015900

http://misq.org.mutex.gmu.edu/consumer-acceptance-and-use-of-information-technology-extending-the-unified-theory-of-acceptance-and-use-of-technology.html



http://www.technet.org/wp-content/uploads/2012/12/TechNet_StateBroadband3a.pdf

http://www.technet.org/wp-content/uploads/2012/12/TechNet_StateBroadband3a.pdf

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