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Civil Conflict, Digital Divide, and E-government Service Adoption: A Conflict Theory Approach

Authors: Gohar Feroz Khan, Junghoon Moon, Hangjung Zo, and Jae Jeung

RhoDepartment of Management Science, ITTP, Korea Advanced Institute of Technology and Science (KAIST), Daejeon, South Korea.

Paper presented in the International Conference on e-Democracy, e-Government and e-Society, Paris, June 2010 organized by WASET. http://waset.org/programs/Paris10.pd

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Introduction

SystemDesign

Conclusion

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Introduction

Example

•Afghanistan•Colombia•Congo•Georgia •India•Iran•Iraq •Mexico•Myanmar •Nigeria•Pakistan •Philippines •Russia•Somalia, and •Sri Lanka•(HIIK, 2008).

Civil Conflicts

& violence

According to a survey conducted by HIIK (2008) at global level a total of 345 conflicts were re-ported. 111 conflicts were lo-

cated in Asia and Ocea-nia,

79 in Africa, 65 in Europe, 47 in the Middle East

and Maghreb, and 43 were located in the

Americas.

Psychological, Environmental, and Economical effects (Noel, 1976; UN, 1991; (Pedersen, 2002; Landrigan et al., 2004).

HasHowever

E-government literature is silent on the issue

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Introduction Continue…

Furthermore,

MIS Research Mainly

Deals with

Organizational (Smith and McK-een, 1992) and

Interpersonal Conflicts (Barki & Hartwick, 2001) focused on:

BUT

What about potential influence of Civil Conflicts and violence on online service use??

NOT EXPLORED

relationship conflict (Atreyi et al., 2007)

task conflict (Trimmer et al., 2000) and

process conflict (Robey et al., 1989; Robey et al., 1993)

Focused on

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Research Questions (RQ)

How civil conflict in a region affects e-government ser-vice adoption?

How behavioral conflict toward online service does af-fects e-government service use intention?

What components of digital divide will shape e-gov-ernment service use intention in less developed coun-tries having civil conflict, political instability, and a low level of ICT awareness?

Do demographics can explain e-government service use in digitally divided conflict zone?

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Literature Review

Conflict theory Conflict is a natural and integral part of social life (Simmel,

1950). Conflict has been classified in several ways in the literature

for Instance: Affective and Substantive conflict (Guetzkow and Gyr, 1954). Bargaining, Bureaucratic, and Systems conflict (Pondy, 1967). “conflict arising from conditions” (Brett,1984). relationship versus task, emotional versus intellectual, and

compromise versus win (Pinkley, 1990).

However, the subject of this study is to test consequences of

Civil conflict (Wall and Callister, 1995) Behavioral (inner) conflict (Argyris, 1957; Thomas 1992) and Digital Divide (Norris, 2001; Harper, 2003) On e-govern-

ment use intention

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Literature Review

E-government and Behavioral conflict:

Behavioral (or inner) conflict is “actual or perceived op-position of needs, values and interests which is internal (within oneself) to individuals” [28] (pp. 47-54).

Individuals with individualistic values assess the useful-ness of the technology with respect to their own needs without taking into consideration the needs of others [45].

[46] Studied the influence of values on technology adoption and found that technology use varies as a function of cultural values

In their study, [47] showed that people’s usage of the In-ternet service is mainly based on interest and relevance.

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Literature Review

E-government and Civil Conflict: Not much of research dealing with topic

The issue is slightly touched in e-government literature[37] in form of political instability.

Elsewhere, the effect of social conflicts on natural re-sources management (NRM) technology adoption has been studied [38] leading to positive association be-tween technology adoption and conflicts among social entities.

However, [39] pointed out that the level of civil conflict in a country may explain their new technology adoption behavior; countries engaged in civil conflicts are less likely to adopt new technology, as their recourses and efforts are diverted to winning the war instead of adopt-ing new civilian technologies

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Literature Review Con-tinue…

Two parallel research streamsIntroduction

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Technology Adoption

• From adoption and usage perspective, research has identified several factors that affect e-government service adoption for instant

• Trust• Quality (info, system, and service)• Compatibility of the service• Ease of use• Relative advantage• etc

Digital Divide

• Digital divide can be classified as access divide and social digital divide.

• Access digital divide is the gap between people who have access to digital infrastructure and information and those who have no or limited access.

• Social digital divide exist due to perception, culture, and interpersonal relationships

• DD factors affecting e-government use: ethnicity, skills, education ,information divide etc

(Al-adawi, 2005; TEO et al., 2008; Harper, 2003; Mehra et al, 2004; Gefen et al 2002)

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Literature Review Con-tinue… Digital divide: Access Divide and Social Divide

Access Divide: E-service access

Resource availability and convenience of access E-service access quality

Timeliness (speed), Trust, and Stability E-service access Skills

Technical and applied e-skills

Social Divide: E-service Awareness

Knowledge of e-gov services availability E-service Social Support

Technical assistance and emotional reinforcement from friends and family

E-service Culturability National colors, pictures, and local language

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Proposed Research Model

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Research Method

Assessing E-government in Afghanistan: We surveyed websites of 14 government bodies and examined the

online services provided to the citizens. initial stage of development—one way information flow.

Subjects: Around 360 citizens Afghanistan in two provinces: Kabul and Nan-

grahar (see table 1 for sample characteristics) Instrument Development:An instrument consisting of 33 items was developed based previous research. A Pilot-test:

was carried out in which 4 experts were asked to give their judg-ments on the questionnaire. Back Translation:

Furthermore, back translation method (Brislin, 1970) was used for translating an English version of the original survey items to:

Pashtu and Dari—two major languages in Afghanistan; Pre-test:

Later, the questionnaire was distributed to 60 citizens of Afghanistan for a pre-test.

Respondents consisted of 45% female and 55% male. Problematic Items revised

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Results: Sample Characteristics

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Frequency Percentage

Gender

Male 222 62

Female 138 38

Age Frequency PercentageBelow 17 44 12

18 to 24 166 46

25 to 34 79 22

Above 35 29 8

Missing 42 12

Internet Use Frequency PercentageLess than 1 hour 144 32

1 to 2 hours 109 30

3 to 4 hours 71 20

5 to 6 hours 21 6

More than 7 hours 40 11

Missing 5 1

Education Frequency PercentageElementary School 68 19High School 100 28

Bachelors degree 154 43

Masters 11 3

PhD 16 4

Missing 11 3

Total 360

Table 1 Sample Characteristics

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Results Continue…

HML (Hierarchal Multiple Regression) Using smart PLS (Partial least square) were used for data analysis.

Construct Validity TestIntroduction

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 Composite Reliabili-ty AVE

Behavioral Conflict (BC) 0.77 0.73Civil Conflict (CC) 0.82 0.78E-service Access (EA) 0.87 0.88E-service Access Quality (EAQ) 0.75 0.78E-service Awareness (ESA) 0.78 0.74E-service Culturability (ESC) 0.84 0.85E-service Social Support (ESS) 0.80 0.76E-service Usage Skills (EUS) 0.89 0.90E-service use Intention (EUI) 0.88 0.88

Table 2 Composite Reliability and Average Varian ex-tracted

  BC CC EA EAQ ESA ESC ESS EUS UseBC 0.73                CC -0.08 0.78              EA 0.13 -0.07 0.88            

EAQ 0.37 -0.04 -0.03 0.78          ESA 0.22 -0.04 -0.10 0.34 0.74        ESC -0.03 0.01 0.23 -0.15 -0.31 0.85      ESS 0.26 -0.03 0.07 0.20 0.11 -0.05 0.76    EUS 0.31 -0.08 0.27 0.22 0.13 0.12 0.41 0.90  

Marker 0.22 0.05 -0.01 0.17 0.29 -0.11 0.06 0.15  Use 0.25 -0.11 -0.11 0.27 0.33 -0.09 0.20 0.22 0.88

Table 3 Discriminant Validity (Inter-correlation) of Latent Variables

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TABLE 3 LOADINGS AND CROSS LOADINGS

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  BC CC EA EAQ ESA ESC ESS EUS UseBC1 0.87 -0.06 0.12 0.36 0.27 -0.08 0.22 0.24 0.25BC2 0.69 -0.10 0.06 0.22 0.07 0.07 0.18 0.22 0.15BC3 0.62 0.00 0.13 0.19 0.08 -0.03 0.18 0.25 0.09CC2 -0.03 0.71 -0.04 -0.04 -0.01 -0.03 0.06 0.00 -0.06CC3 -0.03 0.89 -0.03 -0.01 -0.03 0.04 0.00 -0.06 -0.12CC4 -0.14 0.73 -0.09 -0.06 -0.05 -0.01 -0.12 -0.12 -0.08EA1 0.13 -0.08 0.98 -0.04 -0.13 0.20 0.07 0.26 -0.12EA2 0.11 -0.02 0.77 -0.01 0.03 0.26 0.06 0.22 -0.04EAQ2 0.34 -0.09 -0.05 0.86 0.30 -0.20 0.10 0.13 0.25EAQ3 0.22 0.04 0.01 0.68 0.23 0.01 0.24 0.23 0.17ESA1 0.14 -0.05 -0.15 0.34 0.81 -0.23 0.14 0.01 0.29ESA2 0.17 -0.01 0.06 0.17 0.69 -0.16 0.07 0.28 0.25ESA3 0.20 -0.04 -0.12 0.24 0.72 -0.31 0.00 0.01 0.19ESC2 -0.02 0.03 0.25 -0.15 -0.29 0.93 -0.02 0.13 -0.09ESC3 -0.04 -0.04 0.12 -0.09 -0.22 0.76 -0.09 0.05 -0.05ESS1 0.20 0.00 0.14 0.11 -0.02 0.01 0.70 0.39 0.09ESS2 0.28 -0.03 0.09 0.17 0.08 0.03 0.71 0.41 0.12ESS3 0.16 -0.02 0.00 0.17 0.13 -0.11 0.86 0.24 0.21EUS1 0.29 -0.08 0.26 0.28 0.15 0.11 0.33 0.87 0.18EUS2 0.27 -0.07 0.23 0.13 0.10 0.10 0.41 0.92 0.22EUI1 0.20 -0.11 -0.12 0.22 0.30 -0.05 0.18 0.17 0.88EUI2 0.24 -0.09 -0.08 0.26 0.29 -0.10 0.17 0.22 0.88

Reliability of measurement scale: Convergent validity

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Assessment of the structural model using HMR

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E-government Service Use intentionModel 1 Model 2 Model 3 Model 4 Model 5

R² 0.13 0.18 0.27 0.32 0.36ΔR² 0.05 0.09 0.05 (from model 3) 0.09 (from model 3)

Y Y Y Y YBlock 1: Access Divide E-service Access (H3) -0.163***(0.066) - 0.137**(0.051) -0.198**(0.085) 0.0.164 (0.123) -0.205*** (0.048)E-service Access Quality (H4) 0.224*** (0.051) 0.136**(0.054) 0.135**(0.056) 0.377* *(0.135) 0.150*** (0.040)E-service Usage Skills (H5) 0.216** *(0.056) 0.152**(0.074) 0.016 (0.070) -0.344* (0.144) -0.026 (0.052)Block 2: Social Divide

E-service Awareness (H6) 0.249*** (0.051) 0.259** (0.050) 0.246* (0.104) 0.238*** ( 0.037)E-service Social Support (H7) 0.094*(0.049) 0.069 (0.053) -0.045 (0.095) 0.065 (0.036)E-service Culturability (H8) 0.025 (0.060) 0.073 (0.050) -0.300* (0.143) 0.061 (0.042)Block 3: Control Variables

Age -0.024 (0.046) -0.028 (0.046) -0.005 (0.047)Gender -0.170** (0.064) -0.172** (0.064) -0.197*** (0.070)Internet Use 0.139* (0.055) 0.151* **(0.057) 0.153***(0.054)Income 0.130*(0.055) 0.110* (0.056) 0.104** (0.057)Education 0.0623(0.049) -0.064 (0.049) -0.044 (0.048)Block 4: CC ModeratorHypothesis 1a:CC x EA -0.418* *(0.150)CC x EAQ -0.417* (0.192)CC x EUS 0.491* (0.194)Hypothesis 1b:CC x ESA -0.027(0.154)CC x ESS 0.237 (0.181)CC x ESC 0.526**(0.171)Block 5: BC Moderator Hypothesis 2a:BC x EA 0.009 (0.038)BC x EAQ -0.075 (0.070)BC x EUS -0.181*(0.052)Hypothesis 2b:BC x ESA 0.211 *(0.111)BC x ESS -0.027 (0.060)BC x ESC 0.023 (0.037)Direct effect

CC-0.332* (0.171)

BC-0.002 ns

Table 5 HLM Model Predicting E-government Service Use Intention

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Structure Model Results: Access Divide

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E-service Access

Use IntentionR² =0.13

E-service access Quality

E-service Usage Skills

β =-0.163***

*p<.05; **p<.01; ***p<.001

β =0.224***

β =0. 0.216***

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Structure Model Results: Social Divide

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E-service Awarenes

sUse

IntentionR² =0.18ΔR²=0.0

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E-service Social

Support

E-service Culturabilit

y

β = 0.249***

*p<.05; **p<.01; ***p<.001

β = 0.094***

β = ns

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Structure Model Results: Control Variables

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Age

Use IntentionR² =0.27ΔR²=0.0

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Gender

Internet Use

β = ns

*p<.05; **p<.01; ***p<.001

β = -0.170**

β = 0.130*

Income

Educ.

β = 0.139*

β = ns

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Structure Model Results: Access Divide X Civil Con-flict

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E-service Access

Use IntentionR² =0.32ΔR²=0.0

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E-service access Quality

E-service Usage Skills

β = -0.418**

*p<.05; **p<.01; ***p<.001

β = -0.417*

β = 0.491*

Civil Conflict

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Structure Model Results: Access Divide X Civil Con-flict

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Use IntentionR² =0.32ΔR²=0.0

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β = ns

*p<.05; **p<.01; ***p<.001

β = ns

β = 0.526**

Civil Conflict

E-service Awarenes

s

E-service Social

Support

E-service Culturabilit

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Structure Model Results: Access Divide X BC

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E-service Access

Use IntentionR² =0.36ΔR²=0.0

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E-service access Quality

E-service Usage Skills

β = ns

*p<.05; **p<.01; ***p<.001

β = ns

β = -0.181**

Behavioral

Conflict

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Structure Model Results: Social Divide X BC

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Use IntentionR² =0.36ΔR²=0.0

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β = 0.211*

significance level:*p<.05; **p<.01; ***p<.001

β = ns

β = ns

Behavioral

Conflict

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E-service Culturabili

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Discussion and Implications

For Research:

Integrated model Civil and behavioral conflicts as moderators Agenda setting for researchers working in the fields of conflict, and

their effects on technology adoption. Reliable measures for digital divide: access divide and social divide

For practice: The study will help policy makers in formulating policies in conflict

zones. E-service Access can have negative effect on use under influence of

civil conflict; policies for secure access needed Providing access doesn’t quarantine use: Access Quality and e-skills

are crucial. Equipping citizens with high e-skills may offset side effects of con-

flict Culturability of e-government website: colors, pictures, and local

language is more crucial in conflict zones Need for providing high quality access as it increase use intention;

but in conflict zone high Q has negative effect on use. The more the website according to the needs, desires, and feelings

of citizens the more they will be aware of it and may use it. Special polices for motivating citizens with the help of peers to use

e-service

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Limitations and Future Work

First, we carried our analysis in one country facing civil conflict; differ-ent countries may have different forms of conflict which may influence user’s intention toward an e-service; thus, the results cannot be com-pletely generalized.

Secondly, the study looked only into the e-government services pro-vided in the first stage of e-government development, since e-gov-ernment in the target country was in an initial stage.

Cross sectional study

Fourth, present research investigated only G2C side of e-government service, whereas the influence of civil and behavioral conflicts on G2E, G2B, and G2G services can be the subjects of future studies.

Future research may also focus on consequences of different forms of civil conflicts on users’ intention toward online services.

Another area opened for future research is to look into cross-cultural effects of civil conflict and violence on e-government service use be-havior.

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Conclusion

Utilizing conflict theory, technology adoption, and digital divide litera-ture, this study took first step toward understanding consequences of civil and behavioral conflict in a digitally divided conflict zone by proposing and empirically validating an integrated model.

Results suggest that civil and behavioral conflict play moderating roles between the relationship of some of the access divide, social divide components and e-service use intention.

The study will server as agenda setting for IS researchers to look into the issues of conflict and violence on e-government.

More research is need to explore the issue under consideration

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Thank You!Comments and Suggestions

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