Public Sector Transformation Through E-Government

by Christopher G Reddick

ated under the Telecommunications Act of 1996 and was set up as a $2.25

  billion annual fund to provide discounts (between 20 percent and 90 per-

  cent) to schools and libraries for connectivity costs for the Internet (Carvin,

  Conte, & Gilbert, 2001).

  Programs meant to expand Internet access were downsized or eliminated

  under the George W. Bush administration. During his tenure, the problem

  of disparities in Internet usage was recast in terms of technological literacy.

  His administration worked to reduce inequalities in usage by improving

  computer skills through the No Child Left Behind Act (NCLB). This act

  expanded the defi

  finition of literacy to include technical competence and

  information literacy and provided money to schools for a broader variety

  of Internet resources such as teacher training, support staff, and software

  (Dickard, 2003).

  State Response to Obama’s Broadband Access Policy 245

  The Obama administration has redirected the federal government

  response to Internet inequalities to a strategy more closely resembling Bill

  Clinton’s by focusing on increasing Internet access but with an emphasis of

  addressing infrastructure barriers to residential areas. Under the American

  Recovery and Reinvestment Act of 2009, $7.2 billion was provided to states

  and local governments to extend high-speed broadband access to rural areas

  that have not been served by existing broadband providers. The money was

  distributed through the Broadband Technology Opportunities Program

  (BTOP) and the Broadband Initiatives Program (BIP). The two programs

  provide grants and loans to state and local communities to either update

  existing telecommunication infrastructure or to put into place necessary

  infrastructure to provide broadband service to areas that do not currently

  have broadband access or are underserved. The Obama administration has

  also enlisted the aid of the private sector through awarding $100 million

  dollars under the Recovery Act to four satellite companies to help broaden-

  ing access to broadband in rural area (Recovery Accountability and Trans-

  parency Board, 2010). Additionally, these programs are complemented by

  the State Broadband Initiative. This program was created in 2009 as a joint

  venture between the Recovery Act and the Broadband Data Improvement

  Act. Currently, it has awarded $293 million in grants to support the use of

  broadband for projects that help the states compete in the digital economy,

  including expansion of Internet access (NTIA, 2011a).

  3 COMMUNICATIONS MODEL

  While each of the three administrations took a diff

  fferent approach to

  addressing the issue of inequality in Internet usage, the success of each of

  the policies relied heavily on the cooperation from state and local govern-

  ments. In exploring variation to state compliance with the current adminis-

  tration’s policy, this study turns to Goggin et al.’s (1990) Communications

  Model designed to frame intergovernmental policy. The goal of this model

  is to depict implementation over time and determine why there is variation

  in how states implement federal laws. The dependent variable under this

  framework is state implementation. Specifi

  fically, the dependent variables

  include outputs and outcomes. Outputs can be characterized as agency

  eff

  fforts. Outcomes involve the impact that the law had on society (1990).

  The intervening variables are state organizational and ecological capaci-

  ties or resources that allow the state to ignore messages from other politi-

  cal actors. State organizational capacity refers to items such as a state’s

  administrative effi

  fficiency and competency. State ecological capacity refers

  to factors such as the partisan make-up of the governor’s offi

  ffice and the

  state legislature (1990). The independent variables are federal-level and

  state-level inducements and constraints. An example of a federal level

  inducement is the allocation of resources to implement a law. Conversely, a

  246 Ramona

  McNeal

  restraint would include sanctions against states that fail to implement a law

  as directed (Goggin et al., 1990).

  Goggin et al. (1990) argue that communications takes center stage in imple-

  mentation. The message and content of the policy, in addition to the level of

  communication federal agencies have with state and local implementation

  agencies, is also likely to aff e

  ff ct the success or failure of the implementation

  of a law. If state and local implementers regard the message and content as

  credible, their execution of the law is more likely to mirror its original intent.

  Typically, higher levels of communication facilitate better implementation.

  Also, the less communication there is, the more likely that competing mes-

  sages from other political actors will result in the implementation of policy

  that deviates from its original design (Goggin et al., 1990).

  A review of the Communication Models suggests a number of factors

  that can infl uenc

  fl

  e state compliance with federal policy. In the next section,

  their infl u

  fl ence—including that of state organizational and ecological capac-

  ity on the state-level response to one such U.S. telecommunication policy,

  the Obama administration’s programs to extend Internet access—will be

  examined. Multivariate logistic regression analysis of fi

  fifty state data will

  be used to test rival factors for state response as of December 2010.

  4 DATA AND MEASUREMENT

  The dependent variable is constructed to measure the extent of broadband/

  high-speed Internet access policy in a state. It measures whether the state

  has taken action that is in compliance with the Obama’s administration

  policy to expand broadband access either through authorizing fi

  financial

  support to provide infrastructure to facilitate broadband access or working

  with local government to provide municipal owned broadband service. It

  is coded 1 if such actions were taken and 0 otherwise. The dependent vari-

  able was created from a summary of current state broadband laws avail-

  able through the National Council of State Legislatures (2010a). Because

  of problems related to multicollinearity, two models will be presented. The

  dependent variable remains the same but several independent and control

  variables change between models.

  The main independent variables under the Communication Model are

  federal-level and state-level inducements and constraints. The federal gov-

  ernment can compel the states to act through inducements such as grants,

  constraints such as sanctions, or a combination of both. The Obama

  administration is relying entirely on inducements in the form or grants

  and loans to encourage state compliance. In Model 1, two variables are

  included to measures these inducements. The fi

  first measure is the amount of

  grants in 100’s of millions of dollars awarded to each state under the State

  Broadband Initiative program (NTIA, 2011a). The second is the amou
nt of

  grants rewarded to the states for infrastructure under the BTOP program

  State Response to Obama’s Broadband Access Policy 247

  in millions of dollars (NTIA, 2011b). This second measure is not included

  in Model 2.

  Actors at the state and local level (interest groups, local offi

  fficials and

  agencies) can shape the implementation of legislation. Depending on how

  legislation impacts local groups, they may act either to boost or to hinder

  implementation. Because e-government may have the ability to increase

  political engagement and facilitate a more participatory democracy (Pardo,

  2000), it is expected that good government groups would play an impor-

  tant role in supporting the extension of broadband. The number of good

  government groups in a state was included as a control for interest group

  strength (Project Vote Smart, 2009). One group proven to influenc

  fl

  e state

  Internet access policy is the telecommunication service providers. Acting as

  a proxy for the strength of telecommunication service providers is whether

  or not a state has passed laws that either restrict or prohibit municipal

  owned broadband service (a policy that was hard fought for by service pro-

  viders). The measure is coded 1 if the state has such a law and 0 otherwise

  (Baller Herbst Law Group, 2011).

  Although actors at the federal, state, and local levels may attempt to influ-

  fl

  ence state policy, states may still disregard these players and enact its own

  preferences. This can occur if the “messages” sent by these actors are not

  considered credible. Credibility is based on a number of factors including clar-

  ity of message, accompanying resources to implement a policy and whether

  the “message” came from an actor who is perceived to be credible and legiti-

  mate. How much leeway a state has in disregarding such messages is based on

  state resources. The ability of states to discount outside messages is defi ne

  fi d by

  Goggin et al. (1990, p. 119) as state capacity. This capacity falls into two cat-

  egories: ecological capacity and organizational capacity. Ecological capacity

  concerns the “contextual environment in which state government operates”

  (Goggin et al. 1990, p. 911). The state operates within three environments:

  economical, situational and political. Economical capacity concerns the avail-

  ability of monetary resources. The ability of a state to decline federal grants

  and loans for Internet access depends on state wealth. Following Walker

  (1969) in Model 2, educational attainment measured as the percent of the

  state population over the age of 25 with a bachelor’s degree or higher (U.S.

  Census Bureau, 2012) is included as a measure of societal resources.

  The political environment includes both the attitudes of the citizens as well

  as public offic

  ffi ials. A number of factors can infl uenc

  fl

  e the opinion of policymak-

  ers. The fi r

  fi st is partisanship. A measure of party control of the government is

  included, coded 1 if the Republican Party controls both houses of the legis-

  lature and the governorship, 0 if control is divided between the two parties,

  and–1 if the Democratic Party controls both houses of the state legislature and

  the governorship (National Council of State Legislatures, 2010b). Research

  on partisanship and e-government (McNeal et al., 2003; Tolbert, Mossberger,

  & McNeal, 2008) found a positive relationship between Republican con-

  trolled legislatures and implementation of e-government policies. Both studies

  248 Ramona

  McNeal

  concluded that states with Republican controlled legislatures were more likely

  to be innovators in e-government because of the belief that e-government would

  increase both effi

  c

  ffi iency and cost savings. To control for the possible response

  to citizen concerns, included in the models is the voting age turnout in the state

  for the 2010 midterm election (United States Election Project, 2011).

  The fi

  final area of ecological capacity is state situational capacity. Goggin

  et al. (1990, pp. 145–6) include in this category such factors as public aware-

  ness. States are more likely to respond to an issue if the public believes that

  a problem exists. Measures of demand, such as the number of Internet users

  in a state or problem severity, may also aff e

  ff ct policy adoption and the scope

  of implementation (Goggin et al., 1990). Several measures were included for

  barriers to Internet access. The fi

  first is the average number of computers avail-

  able for public use per public library in 2009 (U.S. Census Bureau, 2012).

  The greater the access to the Internet in public places such as the library, the

  severity of the problem may not seem as acute. The second measure is the per-

  centage of rural areas in a state with three or fewer wireless providers (NTIA,

  2011c). Citizens living in rural areas often have limited choices for service

  providers and therefore connection fees that are considerably higher than in

  urban/suburban areas (Stover, 1999). Because the cost of Internet service tends

  to be lower in more densely populated areas, a measure of state population

  density calculated by the population per square mile was included (U.S. Cen-

  sus Bureau, 2011). In states with greater population density, there may be less

  of a pressing need to implement these policies. In Model 2, a fourth variable

  measuring the percentage of households with Internet access within the state

  in 2009 was included (U.S. Census Bureau, 2012). The greater the percent-

  age of households with Internet access, the less likely the state will feel that it

  needs to implement additional policies to further extend broadband access.

  While ecological capacity focuses on the environment in which policy

  implementation takes place, organizational capacity concerns the resources

  available to the state agencies that oversee policy implementation. Institutional

  capacity includes items such as a state’s administrative effi

  c

  ffi iency and compe-

  tency (Goggin et al., 1990). As a measure of ecological capacity, included is

  an indicator of whether the state has an existing broadband task force, com-

  mission, or authority to oversee state-level broadband initiatives (National

  Council of State Legislatures 2010c). It is coded 1 if such an agency exists and

  0 otherwise.

  Markell (1993) suggests that measures of resources include a strong record

  of policy implementation. States that have a history of innovation in an issue

  area may be more likely to continue placing new ideas on the table and imple-

  ment additional programs. Several measures of innovation in e-government

  are included. In Model 2 is included an index that measure state innovation

  in electronic commerce (Atkinson & Wilhelm, 2002). The second measure

  is West’s (2007) innovation index—a measure of the overall state ranking of

  government websites. The fi

  final measure is a count of social network sites such

  as Faceboo
k and Twitter being utilized by legislative agencies and caucuses in

  a state (National Council of State Legislatures, 2011).

  State Response to Obama’s Broadband Access Policy 249

  5 FINDINGS

  AND DISCUSSION

  In Table 18.1, the dependent variable is coded so that higher scores are associated with increased likelihood of adopting state policies that are

  in compliance with the Obama administration’s policy goals of extend-

  ing Internet access to underserved areas. Because the dependent variable

  is binary, logistic regression models are used. Although two models were

  explored because of muticollinearity concerns, the fi

  findings were the same.

  The same subset of variables was found to be significant in both mod-

  els. The fi

  findings suggest that a limited number of variables including State

  Broadband Initiative grants, good government interest groups, Republi-

  can control of state government, number of computers per library, West’s

  Table 18.1 State-Level Broadband Access Policy Implementation

  Gov’t Ownership or

  Gov’t Ownership or

  Financing (Model 1)

  Financing (Model 2)

  Variables

  b (se)

  p>|z|

  b (se)

  p>|z|

  Federal-Level Inducements and

  Constraints

  State Broadband Initiative

  .22(0.09)

  .019

  .27(0.13)

  .042

  Grants

  BTOP Infrastructure Monies

  .02(0.14)

  .225

  —

  —

  State-Level Inducements and

  Constraints

  Barrier Laws

  4.12(2.76)

  .132

  2.87(2.02)

  .156

  Good Government Interest

  -1.46(0.68)

  .033

  -1.28(0.60)

  .034

  Group Strength

  Ecological Capacity

  Republican Government

  3.97(2.41)

  .098

  3.03(1.69)

  .073

  Control

  Voter Age Population Turnout

  -.45(0.31)

  .140

  -.35(0.24)

  .145

  Percent With Bachelor’s Degree

  —

  —

  -.34(0.46)

  .457

  Rural Broadband Availablity

  .06(0.05)

  .250

  .06(0.05)

  .166

  Population Density

  3.4E-3(3.7E-3)