and Keil (2008) cite van Dijk’s model. Van Dijk (1999) outlines four kinds
of access which surround the digital divide:
1.
Psychological Access—low digital experience caused by lack of inter-
est, computer fear, and unattractiveness of the new technology;
2.
Material Access—little to no access to computers and network
connections;
3. Skills Access—lack of digital skills caused by inadequate education;
4. Usage Access—little to no signifi
ficant usage opportunities within the
home or workplace.
Psychological access, the “mental barrier,” is commonly thought to only affec
ff t
old people (van Dijk & Hacker, 2000). However, the “mental barrier” affec
ff ts
other groups of people like housewives and illiterates (van Dijk & Hacker,
2000). Researchers hardly address this type of access divide (van Dijk, 2006).
Van Dijk (1999) refers to material access as “hurdles” or “barriers” to the information and network society. Material access is seen to describe both
access to computers and network infrastructure (Epstein et al., 2011). Van
Dijk and Hacker (2000) argue that public policy is “engrossed” with material
access and think the problem of information inequality is solved with just giv-
ing computer and Internet access to the population. The lack of digital skills
is described as inadequate knowledge to operate the technology and manage
hardware and software (van Dijk & Hacker, 2000). Van Dijk (1999) argues
that the skills access is a temporary phenomenon and people overcome the
lack of knowledge after using the technology over a period of time. According
to van Dijk (2006), access problems gradually shift from psychological access
and material access to skills access and usage access. The shift in access prob-
lems results in a larger usage gap where the population is split into those who
gain significan
fi
t benefi t
fi s from technological advancements and those who only
use the technology for basic applications (van Dijk & Hacker, 2000). About
16 percent of non-users live in households where an individual uses the Inter-
net (Smith, 2010a). Those with low interactions with computers cite usability
and availability as the key reasons they do not access the Internet (Smith,
Rational Choice Theory 143
2010a). According to Kettemann (2008), a Working Group on e-inclusion
established within the eEurope Advisory Group approach the divide as “both
a technical (‘access’) and a personal dimension (‘inclusion’, ‘ability’).”
One approach to understanding the full concept is to study the phenom-
enon in a continuum alongside other socioeconomic inequities (Barzilai-
Nahon, 2006). The fi
first step to identifying a problem concerning equality
according to Sen (1992) is answering the question: what inequality does
the digital divide concept refer to? Although social and economic literature
have pointed out ten potential answers to that question, the most popular
is still physical or material access (van Dijk, 2006). A problem with focus-
ing on physical access is the never ending evolution of the technology on
the market (Vehovar, Sicherl, Husing, & Dolnicar, 2006). Van Dijk (2006)
suggests the digital divide phenomenon is always as new as the technology
it is linked to at a particular time.
Dewan and Riggins (2005) link access to ICT to community interac-
tion and e-commerce as well as improving social welfare. Belanger and
Carter (2009) point out the concerns about the digital divide and its impact
on the growth of e-services. Studies found that the digital divide hindered
e-government services (Belanger & Carter, 2009; Fang, 2002). By analyz-
ing the digital divide at three levels—individual level, organizational level,
and global level—researchers found overlapping topics which include the
impact on economies, social opportunities and human capital (Dewan &
Riggins, 2005; Korupp & Szydlik, 2005; Wattal et al., 2011). One general
fi
finding across the digital divide is that the widening or closing of the gap is
parallel to economic inequality and choice (Fontenay & Beltran, 2008).
2.2 Rational Choice Theory
Rational choice theory (RCT) is an approach used to understand human
behavior. RCT is based on the assumption that people make choices that
help them achieve their objective and maximize their utility (Simon, 1955).
Rational choice theorists have become increasingly mathematical and for-
mal (Scott, 2002). However, the trend towards more formal models of ratio-
nal action has not discouraged researchers from adapting the models to
explain diverse domains including political science (Johnson, 1997; Riker,
1990; Simon, 1985), criminology (Akers, 1990; Becker, 1968; Cornish &
Clarke, 1987), and economic growth (North, 1994; Sidrauski, 1967). Soci-
ologists and political scientists now adapt theories around the assumption
that people are essentially rational in character (Masatilioglu & Ok, 2005).
Scott (2002) states that rational choice theory denies the existence of any
actions not directed by ration which distinguishes RCT from other forms
of theory.
One popular study that focuses extensively on behavior and rational
choice theory is Becker (1968). Becker (1968) uses rational choice theory to
understand the impact of human behavior on public and private policies on
144 Porche
Millington and Lemuria Carter
illegal behavior (Becker, 1968). Becker (1978), Hogarth and Reder (1987),
and Green and Shapiro (1996) discuss rational choice theory beyond con-
ventional economic issues. The theory developed by Becker (1968) can be
applied to any eff or
ff t to impede or support human behavior (Li, Zhang, &
Sarathy, 2010).
Various studies apply rational choice theory to explain a multitude of
behavioral topics from security policy compliance to consumption (Chai,
2008; Li et al., 2010; Vale, 2010). Li et al. (2010) applied rational choice
theory to examine employees’ intentions to comply with their workplace
Internet use policy. According to Li et al. (2010), employees’ compliance
intentions are based on competing perceived benefi ts
fi and security risks.
D’Arcy, Hovav, and Galletta (2009) also explores IS security using rational
choice. Vale (2010) analyzes rational choice theory and the standard model
of inter-temporal decision making to reduce the gap between the theory and
clinical defi
finition of addiction. The study also emphasizes one of the theory’s
assumptions—individuals are “forward-looking and their decisions ratio-
nal” (Vale, 2010).
Previous predictive models of behavior have involved economic theory
intertwined with a social dilemma by using rational choice theory as its
framework. According to Chai (2008), further discussion and the call for
more robust knowledge on applying RCT to other disciplines prompted
researchers to use it in more social and economic issues. The subsequent
develo
pment of rational choice theory took place in economics, political
science and sociology (Chai, 2008). Chai (2008) argues that the predictive
behavioral modeling could apply to social sciences as well as hard scientists
like computer scientists approach to technology diffusion. RCT is believed
to assist in the dialogue between social and hard science studying a social
phenomenon (Chai, 2008). Chai (2008) states that “no other existing major
theoretical approach equals conventional rational choice in meeting a com-
bination of criteria” which justifi
fies the dominance the theory has in social
and economic studies. The ability to predict behavior around choosing to
connect to a network or to gain the skills to enhance usage would be an
advantage in closing the technology gap known as the digital divide.
3 RCT AND THE DIGITAL DIVIDE
We draw upon rational choice theory to understand the four types of access
divides. Prior to physical access comes the desire to own a computer and to
be connected to a network. In 2011, the two most commonly cited reasons
for not having Internet access in the home are that the access is not needed
and the access is too expensive (NTIA, 2011). Researchers can use RCT to
develop techniques to engage the population with low motivation. Table
11.1 shows the four types of access divides and examples of each. Table 11.2
includes diverse research questions related to the interaction of the digital
divide and RCT. Each access divide has factors that hinder the population
Rational Choice Theory 145
from receiving the full benefi
fits of technology innovation. We use RCT to
formulate research questions that address how to tackle narrowing each
type of access divide. Backed by the idea that people make decisions based
on rationality, we recommend using research questions to understand the
thought process to reach a rational decision. Tables 11.1 and 11.2 can be used to direct future research on the diverse types of access divides.
Table 11.1 Four Types of Access Divides
Psychological Access
Material Access
• Fear of the unknown
• No network connection
• Lack of interest
• No access to a computer
• Unattractive technology
• Lack of income to purchase computer
or network connection
Skills Access
Usage Access
• Inability to navigate computer system • Limited technology use in the workplace
• Low social support
• Little opportunity to use the computer
• No assistance to grasp digital skills
for personal tasks
• Low interaction with computers
Table 11.2 Rational Choice Theory to Understand the Access Divide
Psychological Access
Material Access
1. How can training be used to mini-
1. What impact will computer/technology
mize computer anxiety in the elderly
subsidies from the government have
population?
on the diff usion of computer
ff
-based
2. How can user awareness programs
systems and services?
be used to increase the perceived
2. Should technology providers be held
benefi
fits of adopting technological
responsible for helping to close the
innovations?
digital divide?
3. What factors entice non-users to try
3. What is the impact of community
technological innovations?
centers equipped with computers and
network connection on the desire to
own a personal computer?
Skills Access
Usage Access
1. What types of programs should be
1. Does access to computers in the
implemented to increase digital skills?
workplace enhance usage at home?
2. What impact does technology design
2. Will the availability of e-services
and the user-interface have on the digi-
increase the use of technology?
tal divide? How can the IS community 3. What types of technological innova-
make technology more user-friendly?
tions promote more computer usage
3. What types of training are most effec-
ff
beyond basic tasks such as sending an
tive at reducing the skill divide?
email?
146 Porche Millington and Lemuria Carter
This chapter explores the growth and use of Internet-based technology as
well as the disparity associated with it. The digital divide is a multifaceted
issue and requires solutions to address all four of the access divides. For this
reason, the identifi
fication of non-user and user groups is an essential step
toward implementing proper policies and recommendations. The quadrant
in the table below provides an initial framework of gaps associated with
each access divide. According to Fuller, Vician, and Brown (2006), there is
a correlation between computer self-effi
fficacy and technology usage. Com-
puter self-effi
fficacy refers to an individual’s judgment of his capabilities to
use computers and complete goals (Venkatesh & Davis, 2000). Researchers
suggest that socio-economic status is the most signifi
ficant power in distin-
guishing non-users from users (Hsieh et al., 2008; Lenhart et al., 2003).
Table 11.3 highlights the relationship between socio-economic status and computer self-effi
fficacy with the four access divides.
We propose this quadrant as an eff
ffort to identify common barriers to
access among certain groups of people. Individuals with high socio-eco-
nomic status and low computer self-effi
fficacy face barriers associated with
psychological and skill access divides. The usage access divide is a potential
barrier for individuals with high socio-economic status and high computer
self-effi
fficacy. Individuals with low socio-economic status and low computer
self-effi
fficacy face barriers associated with material access. Individuals with
low socio-economic status and high computer self-effi
fficacy also face barri-
ers associated with material access but not in its traditional sense. Although
income level and geographical location plays a role in their material access,
they still have access to the Internet through alternative devices. African
Table 11.3 Gaps Associated with the Four Access Divides
1. Age groups
1. Lack of interest
Low
(“Grey Digital Divide”)
2. Computer anxiety or
2. Lack of perceived benefit
fi s
Status
computer fear
Psychological and Skills Access Divides
Usage Access Divide
1. Education level
1. Income level
Socio Economic
2. ICT knowledge
2. Geographical location
3. Income level
High
Material Access Divide
Material Access Divide
&nbs
p; Low
High
Computer Self-Effi
cacy
ffi
Rational Choice Theory 147
Americans and Latinos continue to outpace Caucasians in their use of
handheld devices. According to Smith (2010b), minority Americans lead
the way in mobile access using handheld devices. Additionally, minorities
tend to take advantage of their phones’ data functions compared to Cauca-
sian cell phone owners (Smith, 2010b). This would explain why minorities
with low socio-economic status often have high computer self-effi
c
ffi acy.
As previously stated, rational choice theory assumes that people are essen-
tially rational in character (Masatilioglu & Ok, 2005). Rational choice theory
defi
fines rationality diff eren
ff
t from the philosophical use—behaving sane or in
clear-minded manner. Rationality is defi
fined as an individual’s ability to bal-
ance costs against benefits
fi to arrive at a rational decision (Herrnstein, 1990).
Using rational choice theory to understand individuals who are aff ec
ff ted by
access barriers, garners understanding of their motivations. Individuals with
high socio-economic status but low computer self-effi
c
ffi acy would use rational
choice to weigh the perceived benefi t
fi s against the costs of overcoming their
fear or anxiety. Individuals with high socio-economic status and computer
self-effi
c
ffi acy would be most susceptible to intervention because the benefit
fi s
would most likely outweigh the costs. Individuals with low socio-economic
status as well as low computer self-effi
c
ffi acy might not buy into government
initiatives or social policies to increase their access to ICTs. This group might
be hesitant because the benefi t
fi s might not balance the costs of participating.
Individuals with low socio-economic status but high computer self-effi
ca
ffi cy
would buy into community and pricing initiatives. The perceived benefits
fi of
participating could outweigh costs—if the costs of ICTs were within their
budget or access was free within the community.
Discussion & Limitations
This chapter represents an initial response to Chai’s (2008) call for more
Public Sector Transformation Through E-Government Page 26
