1. Subjective and Objective Performance Measures
The Case of Local County E-Government
Dr. James McQuiston, University of Akron
Dr. Aroon Manoharan, University of Massachusetts Boston
Midwest Public Affairs Conference
Columbus OH, June 4, 2016
2. This paper seeks to examine the relationship between subjective and objective
measures of performance using a sample of US county governments.
The research also determines the factors affecting both types of performance
measures.
The objective measures were obtained from a content analysis of their official
websites, while the subjective measures were based on a survey of the county IT
administrators.
The research addresses an important question concerning the value and performance
of governments, and the relationship between subjective and objective performance
measures of government.
Research Focus
3. E-Government is “the use of information technology to support government
operations, engage citizens, and provide government services via the
Internet”
What is E-Government?
4. Benefits of E-Government:
increased government accountability to citizens
greater public access to information
more efficient, and effective government
Potential of E-Government:
A major transformation of the way the government conducts
business
Reversal of long-term loss of social capital
Transformation to E-Government
E-Government Paradigm
•coordinated network building
•external collaboration
•customer services
Traditional Bureaucratic Paradigm
•standardization
•departmentalization
•operational cost-efficiency
5. Stages of E-Government Development
Layne, K. and Lee, J. (2001). Developing full functional e-government: A four stage model. Government Information Quarterly. 18:122-136.
6. E-Government Success Measures
Two important measures of ‘Success’–
- Hard measures – cost benefit analysis, benchmarks
- Soft measures – improved decision-making, citizen/customer satisfaction,
employee productivity
7. Challenges to E-Government
Three types of e-government failures (Goldfinch, 2007)
Project failure, system failure, user failure
Reasons for e-government failures (Sarantis, 2007)
1. Goal definition of public organizations is usually vague, compared to the private
sector.
2. The analysis of the e-government projects indicate that their structures are more
complex with interactions from the technical, managerial, political, social, cultural,
and legal dimensions.
3. Planning for IT projects in the public sector is much more instable, largely due to the
electoral process.
4. The management of government transformation projects in e-government cuts across
agencies, and there are few best practices exclusively used for the public sector.
5. The legal and regulatory issues in the public sector come from legal and
constitutional arrangements.
8. As governments incorporate various technologies, it is important
to measure the performance of e-government and develop
strategies to improve such performance.
Much of the studies on e-government performance tend to focus
primarily on the official websites of cities and states, while some
studies are based on survey of public administrators involved in
the e-government development process.
However, would adopting both methods result in wide variances
in performance measures for local governments?
Subjective and Objective Performance Measures
9. What is the relationship between objective and
subjective measures of e-government
performance?
What are the factors affecting both types of
performance measures?
Does higher e-government performance lead to
higher managerial satisfaction?
Research Questions
10. No. Dimension Features
1 E-information
Information on public employees, location of government
offices, GIS mapping, FAQ (Frequently Asked Questions),
job/position vacancies calendar of events, video clips/minutes of
public meetings, targeted audience links
2 E-transaction
Utility bills, fines/tickets, filing taxes, books/reports purchase,
permit applications, event tickets licenses applications, e-
procurement
3 E-participation
Online policy forums, bulletin boards, e-petitions, e-meetings,
community newsletter, online survey polls, crime report, file
complaints, feedback forms
E-Government Performance Measures
The highest possible e-government score for any one county is 72, while the highest possible score on each of
the three dimensions is 24.
• Content analysis of official websites using a 24 point index
• Measures coded on a scale of 0, 1, 2 or 3 based on the levels of sophistication
Methodology
Dependent Variables
10
11. Methodology
Independent Variables
- Survey sent to county Chief Information Officers/IT managers between March and May 2009.
- NACO, has a membership of over 2,000 counties representing over 80% of the national population,
maintains a comprehensive database and periodically gathers and disseminates information on both
counties and county officials.
-The survey was administered via the Internet, which has the advantage of both cost and time
savings over regular mail surveys involving significant printing and mailing resources.
-The survey was divided into two main sections: (institutional variables + contextual variables)
-The survey also included two questions assessing county managers’ success and satisfaction with
the implementation of e-government services.
- Questionnaires for the online survey were emailed through Survey Monkey to counties across the
United States that have official websites.
- Overall survey response rate of 17.8%
11
12. County Adoption of Official Websites
12
- Identification of counties with websites by accessing the corresponding links on the NACO website.
- The absence of county website confirmed through a query to the Google search engine.
- Overall, a total of 2,376 counties have official websites.
Percentage of Counties with Official Websites by Region
The states with the highest percentage of county website adoption (100%) are
Arizona (15), California (58), Delaware (3), Florida (67), New Hampshire (10), New Jersey (21).
13. Difference Groups
Group A – Respondents that had a greater actual than
perceived e-government score (n=37).
Group B – Respondents that had an greater perceived than
actual e-government score (n=145).
14. Regression Analysis Results – Actual
Performance v Perceived Performance
Variables/
Parameters Scale
Form of Government
1 = Board of Commissioners
(BC), 0 = non-BC
IT Budget
1 = Above $500,000,
0 = $500,00 and below
IT Contracting 1 = Yes, 0 = No
Stakeholder Support (Elected Officials)
1 = Not supportive to
4 = Extremely supportive
Stakeholder Support (Top Administrators)
1 = Not supportive to
4 = Extremely supportive
Stakeholder Support (County Employees)
1 = Not supportive to
4 = Extremely supportive
Organizational Size (No. of Functions)
Neighboring Websites 1 = Yes, 0 = No
External Collaboration (Counties)
1 = Not that closely to
4 = Extremely closely
External Collaboration (Nonprofits)
1 = Not that closely to
4 = Extremely closely
External Collaboration (Businesses)
1 = Not that closely to
4 = Extremely closely
Population US Census Data
Education US Census Data
F
Constant
Adjusted R-Square
*p<0.10; **p<0.05; ***p<0.01
15. 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20%
1
2
3
4
5
6
7
8
9
10
Self-reported
Success of
E-Government
Overall, how would you rate the success of your county in the area of e-government?
(1 = “Not successful at all” to 10 = “Very Successful”)
County’s Self-Reported Success in Implementing E-Government
16. Research Question 1
Correlation of Subjective Measures and Objective Measures of Performance
E-Information E-Transaction E-Participation E-Government
Self-Reported
Success
E-Information
PC 1
Sig. (2-tailed)
E-Transaction
PC 0.224
**
1
Sig. (2-tailed) 0.002
E-Participation
PC 0.100 0.301
**
1
Sig. (2-tailed) 0.177 0
E-Government
PC 0.525
**
0.913
**
0.516
**
1
Sig. (2-tailed) 0 0 0
Self-Reported
Success
PC 0.239
**
0.237
**
0.032 0.268
**
1
Sig. (2-tailed) 0.001 0.001 0.664 0
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
17. Research Question 2
Factors Affecting Objective Measures of Performance
Performance – Actual Coefficient (s.e.)
(Constant) -8.395 (5.594)
CountyYears .229 (.120)*
IT Department .643 (.295)**
IT Employed .397 (.117)**
County Form Govt .061 (.194)
EGovtSupport - County -.091 (.160)
EGovtAdminSupport .213 (.164)
EGovtEmploySupport .392 (.162)**
EGovtCitizenSupport -.271 (.143)*
ChampionEGovt -.197 (.201)
ITBudget -.094 (.096)
NeighboringCtyWebSite .078 (.091)
ITWorkOutsource .076 (.098)
PrivateNonfarmEstablish -1.115E-005 (.000)
PopulationLog .228 (.153)
HSEducation 1.243 (1.192)
Satisfaction .018 (.551)
19. Research Question 2
Factors Affecting the Difference between Objective and Subjective Performance
Difference Coefficient (s.e.)
Constant 15.65 (3.90)***
Population -.43 (.29)
NeighboringCtyWebSite -.31 (.20)
HighSchoolGrad -.03 (.03)
NumberSourcesCtygovt -.15 (.04)***
EGovtCountySupport -.41 (.29)
EGovtEmploySupport -.42 (.32)
PrivateNonfarmEstablish 4.60
-5
(.00)*
ITBudget -.22 (.16)
*=p<.10, **=p<.05, ***=p<.01
20. Satisfaction
Can the below measures be considered satisfaction measures or do these questions
measure perceived performance?
21. E-Information E-Transaction E-Participation E-Government
Resulted in saving of
financial resources
PC
0.174
*
-0.013 -0.058 0.033
Sig. (2-tailed) 0.018 0.863 0.434 0.662
Increased government
transparency and
accountability
PC 0.150
*
0.150
*
0.012 0.167
*
Sig. (2-tailed) 0.043 0.044 0.869 0.025
Increased collaboration
with other levels
of government
PC 0.039 0.007 -0.096 -0.006
Sig. (2-tailed) 0.599 0.924 0.197 0.936
Enhanced the county’s
ability to hire, manage
and oversee contractors
PC 0.200
**
0.232
**
0.024 0.249
**
Sig. (2-tailed) 0.007 0.002 0.749 0.001
Increased the interactions
between citizens and
county government
PC
0.206
** 0.134 -0.049 0.157
*
Sig. (2-tailed) 0.005 0.071 0.508 0.034
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
Research Question 3
Performance v Satisfaction
Does a higher e-government performance lead to a higher managerial satisfaction?
22. Research Findings
Actual performance is impacted by shareholder support, the presence and size of IT department,
and the experience that the county has had with ICT.
Perceived performance is influenced in both groups by the existence of an e-government champion,
but the variable possesses different signs. IT size matters in perceived performance, while the
county's experience with ICT and support levels of a workforce towards e-government has a varied
effect depending on the sign of the difference variable.
Different variables matter in explaining the difference between perceived and actual levels of e-
government success; the number of sources of county government and amount of private firms are
significant.
