Modelling The Resilience Capability In E-government Using Human Centric Approach A Case Study In Malaysia Public Sector Nurul Aisyah Sim Binti Abdullah CS990 Supervisor : Prof. Dr. Noor Laila Mohd Noor Co Supervisor : Dr. Emma Nuraihan Mior Ibrahim Service availability and accessibility High speed, can access anytime any where Provide services Use the service Service Continuity Issue
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Modelling The Resilience Capability In E-government
Using Human Centric Approach
A Case Study In Malaysia Public Sector
Nurul Aisyah Sim Binti Abdullah
CS990
Supervisor : Prof. Dr. Noor Laila Mohd Noor
Co Supervisor : Dr. Emma Nuraihan Mior Ibrahim
Service availability
and accessibility
High speed, can
access anytime any
whereProvide services Use the service
Service
Continuity
Issue
Research Outline
1. Research Roadmap
2. Background Study
3. Problem Statement
4. Preliminary Study Result
5. Research Questions and Objectives
6. Research Scope & Limitations
7. Research Methodology
8. Findings and Discussions
9. Contributions
10. Future Works
11. Publications
Review the literature
Conduct preliminary
study
Research Framework
and hypothesis
development
Research design
Measurement and
question- questionnaire
development
Study 2 Study 3
Problem Formulation
Research Approach
(Creswell, 1994, 2003,
Sekaran, 2013)
Research Roadmap
Data collection
Study 1
Understanding research background, issue,
gap, problem and establishing research
domain
Confirmation of the actual issue and the
problems in the domains studied
Identify the theory to refer to determine the
exogenous, endogenous variable,
independent, dependent variable and Identify
the hypothesis statements
Conference paper, ICRIIS, 2013
Conference paper
(PACIS 2014),
Conference paper
(CONF-IRM 2016)
Develop measurements attribute of variables, pilot
study, identify the goodness of measures, identify
the internal consistency and stability of measures
Formulate the research problem Identify
research objectives, scope and produce
research proposal
Determine the most suitable research design and
paradigm
Publications
Identify sampling strategy
Identify respondent
Data analysis Testing
and Evaluation
Identify the character, relationship and patterns of
the phenomena under studies
Identified Model
GeneralizationValidate model
Interpretation of the findings
Discussion on the implication of the findings
Journal (TGPPP 2016)
Definition of Terms
E-government
• the delivery of government information and services via the Internet or other digital means to citizens or businesses or other governmental agencies (Palvia & Sharma, 2007)
Business Continuity Management (BCM)
• is a holistic management process that is used to ensure that operations continue and services are delivered at predefined levels (ISO 22301, 2012)
Resilience
• refers to the maintenance of positive adjustments under challenging conditions (Karl E Weick, Sutcliffe, & Obstfeld, 1999). Introduce by Holling (1973).
• is a growing area of interest within BCM (Burnard & Bhamra, 2011).
• is emerging as a new paradigm where “success” is based on the ability of human to anticipate the changing shape of risk before, during, and after failures (Hollnagel & Woods, 2006)
• Literature perceived resilience as a human-centric approach where it is based on ability of an individual when aggregated to organizational level, which could define the organization resilience capability (Cynthia a. Lengnick-Hall et al., 2011).
• The theoretical and practical knowledge on resilience is still being researched (Wukich, 2013) and empirical literature on resilience is scarce(Barasa, Mbau, & Gilson, 2018)
Resilience capability
• The ability to absorb, ability to adapt and ability to recover in response to unintended event, change or disaster (Abdullah et al., 2013)
Background Study
Background Study
Approach toward service availability & continuity:
Risk Management
Business Continuity Management
Resilience as new safety paradigm based on human ability to organize and adapt
Preliminary study
Prevention/Mitigation Strategy
Theory of Plan Behaviour (TPB)
understanding human
behaviour - triadic reciprocal
determinism explain why
people engage in certain conduct
Resilience Capability Model
resilience element (organizational factor, personal quality, capability factor and person-environment setting factor) antecendant of intention-to-organize (Self
organize, process organize and technology organize) which acts as the main predictor to resilience capability (ability to absorb, adapt and recover)
provide a conceptual
frameworks for the study of
human action for predictionCapability for resilience -Resilience Construct
Wohrle, & Pieter van Oudenhoven, 2010; Westhuizen, 2010)
10 High expectation 4 Items
11 Commitment 3 Items
12 Involvement 3 Items
Capability-to-react
13 High technological competence 3 Items
(Mcmanus & Brunsdon, 2007; Stephenson, 2010b)14 Process Readiness 3 Items
15 Technological readiness 3 Items
Intention to organizing for resilience
16 Self-organize 3 Items (Patil, 2008; Haron et al., 2013; Caralli, 2010; Iii, 2010; Goble
et al., 2002; Vorisek et al., 2011)17 Process-organize 3 Items
18 Technology-organize 3 Items
Resilience behaviour
19 Ability to absorb 3 Items (Erol, Henry, et al., 2010; Erol et al., 2009; Erol, Sauser, et al.,
2010)20 Ability to adapt 3 Items
21 Ability to recover 3 Items
71 item
-reliability
-Validity
-Theoretical
judgement
Study 1
Study 1
Concep
tual
Model
Study 2
Refined
Model
Constructs
Constructs
Refined
Constructs
Study 2
STEP 4Structural model assessment
STEP 3Measurement model assessment
STEP 2Data Screening
STEP 1Data collection phase
Study 1
Concep
tual
Model
Study 2
Refined
Model
Constructs
Constructs
Refined
Constructs
• Convenience sampling
involve 35 Malaysian
public sector Frontline
agencies
• Self-administered
questionnaire
• 700 questionnaires
distributed, 335
completed, 33 uunusable
and only 302 usable
(43.14%)
• the response rate within
the common range of
27.0 to 82.8% public
sector research (Baruch
& C. Holtom, 2008)
• the rate higher then
research by Sakri &
Sembok, (2012)
1. respondents answered at
least 75% of the
questionnaire(Sekaran,
2010),
2. Missing data (less than
5%) - Replaced used
mean substitution (Cohen
& Cohen,1983)
3. Outlier none exceed z >
4(Hair et al., 1998)
4. Eliminated suspicious
response patterns-
straight 4 or 7
5. skewness and kurtosis
values < absolute value
of 2 and 7 respectively.
6. Non-response bias
test(Armstrong &
Overton, 1977)
A quantitative method was applied to confirm the findings of this study.
PLS-SEM evaluation stages adopted
from (Sarstedt et al., 2014)
1. Item reliability – each item loadings
>0.7
2. Internal consistency reliability
evaluated using composite
reliability (Jöreskog, (1971), Hair et
al., 2014). Proposed value > 0.70
<0.95 (Nunally (1978) indicate
measurement model is reliable.
Values > 0.95 indicate items
redundant.
3. Convergent validity examines
whether the measures of the same
construct are highly correlated.
Assessed by the average variance
extracted (AVE) for all items
associated with each construct.
Acceptable AVE is =>0.50.
4. Discriminant validity determines the
extent to which a construct is
empirically distinct from other
constructs in the path model. Two
measures have been put forward—
the Fornell– Larcker criterion &
cross-loadings
1. Collinearity Assess. VIF > 10
=multicollinearity problem
(Nishishiba, et al.2013).
2. Path Coefficient by evaluated
sign, t-value >1.96 (sign. level
= 95%),
3. Model’s predictive accuracy
level of R2 - Values range from
0 to 1. R2 values of 0.67, 0.33,
or 0.19 are described as
substantial, moderate, or weak
by Chin (1998). The impact of
a specific Exogenous on a
Endogenous construct - effect
sizes f2-measures. Values
0.02, 0.15, and 0.35 described
respectively as small,
moderate, and large.
4. Out of sample prediction
(predictive relevance q2) -
(Sarstedt et al., 2014). Values
of 0.02, 0.15, and 0.35 indicate
small, medium, or large
predictive relevance.
CONFIRMATORY PHASE
The investigated factor consisted of all factors stated in the research framework.
CONFIRMATORY PHASE
Study 1
Concep
tual
Model
Study 2
Refined
Model
Constructs
Constructs
Refined Constructs
Study 2
Demographic Profile of Personal
• 55% of the respondent are male and the remaining 45% female.
•Majority of the respondents are under 40 years old (83.1%) and only 16.8 percent aged 40 and above.
•Most of the respondents hold a bachelor degree (54.35%).
•More than half of the respondents (52.3%) claimed that they have experienced a level of proficiency in their work based on Garis Panduan Kepakaran ICT).
Demographic profile of Professional
•high % work at operating agencies (64.5%), central agencies (35.5%).
•Majority has a level of experienced ICT proficiency (39.3%) and a very small level of expertise (13.1%).
•Most hold a bachelor’s degree and most of them are at professional level
•Similar the characteristics of respondents in a previous study (Sakri & Sembok, 2012).
•Therefore, is believed to be representative of the wider population of IT practitioners working in the Malaysian public sector.
Demographic Profile of ICT Service Continuity Practice
•Risk management, prevention and prediction
mechanisms were most widely used (> 80%)
•97.7% admitted they have service continuity
policy in place.
•the majority (77%) respondents, carry out plan
review according to the best practical
recommendation.
•94.4% respondents has gone into the
awareness program.
•The cumulative percentage of service disruption
from always to sometimes is 69.6%) is found to
be more or less the same with the frequency in
preliminary studies (Abdullah, Noor, et al., 2016),
which is 70.2%.
Descriptive analysis of the
investigated construct
•All agencies are hierarchical and bureaucratic organizations (mechanistic structure), that encourage and practice innovative culture. All mean =>5.00
•The mean value for all variable of the personal quality, the person-environments setting, re-organize intention-, the capability-to-react - is above 5.0
•The mean value for all resilience ability variable is above 5.0 which represent the scale of “A day after impact” except for ability to recover had the mean value more than 4.0 which represent the scale of “Not Sure”. This indicates that on average, the public organization ability to absorb risk, adapt to the risk and recover day after impact
Resilient Capability Model developmentFrom the analysis of the empirical data based on the theoretical model, the resilient capability model is proposed for the
Malaysian public sector setting. The ICT Resilience capability model is drawn from the results of the path analysis that indicated:
Study 3
Study 1
Concep
tual
Model
Study 2
Refined
Model
Constructs
Constructs
Refined Constructs
Objective Revisited
Findings and Discussions
Objective Accomplishment
To identify the human-
centric antecedent factor
that would influence the
formation of resilient e-
government
• organizational setting (Inovative culture, mechanistic structure, TTLS) positively affect specific variable of identifying individual intention-
determinant (personal quality, person-environment setting, and capability-to-react).
• Innovative culture significantly affect all elements of personal quality (social competence, sense of purpose, autonomy, self-efficacy and problem-
solving skill), all elements of person-environment setting (caring support relationship, commitment, and involvement) except high expectation and
only one element of capability-to-react construct namely high technological competence.
• Mechanistic structure positively affects an individual sense of purpose, create high expectation, and contribute to develop process and technology
readiness
• TTLS significantly affect individual self-efficacy, and contribute to develop process and technology readiness.
• Personal quality, person-environment setting and the capability-to-react is perceived to be significant elements to predict IT person's intention-to-
organize.
• personal quality, namely self-efficacy and social competence to be the most significant predicting the formation of self-organize,
• person-environment setting, namely caring-supportive relationship, involvement and commitment, to be the most significant predicting the
formation of process-organize
• capability-to-react such as high technical competency, process and technical readiness to be the most significant predicting the formation of
technology-organize.
• three personality qualities (autonomy, sense of purpose and problem-solving skill) and one person-environment setting element (High expectation)
which represents resilience, personal factors in resilience theory were found to be not positively significantly related to intention-to-organize.
• The findings suggested that intention-to-organize perceived to be able to predict ICT resilience capability.
• Empirically, this research indicated that the intention-to-organize in different aspects, generate different resilience capability.
1. self-organize intention is perceived to produce the ability to adapt and ability to recover
2. process-organize intention is perceived to produce the ability to absorb and ability to recover
3. tech-organize intention will produce the ability to absorb and ability to adapt.
• This suggests that the intention of a person to organize is important in determining the resilience behaviour and it is consistent with previous
studies stating that the best way to predict and explain an actual behaviour is through that person’s behavioural intention (Ajzen, 1991; Miles,
Jeffrey, 2012; Roberts, Stout, & Halpern, 2012).
To model the resilience
capability in e-
government
The model indicates that 26% of the ability to absorb incoming risk related to ICT services, 25% of the ability to adapt to disruption or change in order
to maintain ICT services and 36% of the ability to recover from disruption or disaster in order to continuously provide ICT services in Malaysia
government agencies can be explained by the constructs in the proposed model.
To validate the e-
government resilience
capability model
The study has developed The Resilience Capability In E-government Model
The data analysis confirmed that the adjusted measurement model met all the requirements of convergent validity, discriminant validity, indicator
weight, and multicollinearity. The results also appeared to partly support the concept of triadic reciprocity in social cognitive theory (Bandura 1986).
ContributionsValidate resilience antecedent factorEmpirically validate resilience factor identified in the literature
Identified resilience relationship between external & internal factor
toward intention to organize Explore and validate external factor
(organizational setting ) toward Internal factor (intention determinant factor) and their effect
toward intention to organize.
Strengthen Azjen’s TPB model (1985, 1987, 1988, 1991)
The significant relationship between personal quality and self-organize intention,
person-environment setting and process-organize intention, and capability-to-react toward technology-organize intention, all
contribute to strengthening the formation of endogenous variables or intention factors as assumed by Ajzen’s TPB model (1985,
1987, 1988, 1991).
Organizational setting presenting situations in Malaysian public sectororganizational setting presenting clearest indication of external environment at the Malaysia Public sector workplace.
Choice of statistical analysisBy applying SEM, this research was able to demonstrate the joint impact of antecedent variables and the outcomes of organize-intention. The relationships between the factors in the hypothesized model are more accurate (Wan Afthanorhan, 2013).
The finding highlighted the importance resilience factoruseful for organizations to revisit their relevant policies and procedures specifically related to adoption of important factor identified and be strategize in strengthening the identified resilience capability
Resilience ability predictionThe research also contributes to the
theoretical body of knowledge through its uniqueness in predicting an organization's
resilience ability; namely the ability to absorb, ability to adapt and ability to recover.
The findings provide further evidence that intention-to-organize is a transformational
concept to be applied in justifying resilience acts.(Bandura 1996, Kumpfer 2000)
Establishment of ‘ICT Resilience Capability modelEmpirically validated Theory of Planned Behaviour based model and strengthening Ajzen’s Theory of Planned Behaviour model (1985,1987,1988,1991) and thus contribute to the body of knowledge by incorporating factors from different disciplines,
Th
eo
retica
l
• Only involved the given types of antecedent factors. Thus, future works need to explore
others factor as well, such as the BCM maturity, organizational characteristic,
organization core business or the other aspect that would influence the organizes-
intention behavior in the Malaysian public sector.
• Sampling limitations. future research should encompass a wider scope of organizations
may be in their category such as the federal government, state government, local
authority, federal statutory body, or could be private sector.
Limitations and Suggestions for Future Research
Publications
No Title Journal / Conference
1. Resilient Organization: Modelling The Capacity
for Resilience
3rd International Conference on Research and Innovation in
Information Systems – 2013 (ICRIIS’13), UNITEN, Selangor,
Malaysia 27-28 November 2013
(Scopus indexed)
2. Information Technology Service Management
(ITSM): Contributing Factors to IT Service
Disruptions – A Case of Malaysia Public Service
Agencies
The 19th Pacific Asia Conference on Information Systems (PACIS
2017) Chengdu, China, 24-28 Jun 2014
(Scopus indexed, Core rank A)
3. Contributing Factors To E-governments Service
Disruptions
Journal of Transforming Government: People, Process And Policy
Volume 10, Issue 1
(Scopus indexed, Q2)
4. Contributing Factor To Business Continuity
Management (BCM) Failure– A Case Of
Malaysia Public Sector
5th International Conference on Computing and Informatics, ICOCI
11-12 August, 2015 Istanbul, Turkey.
(Scopus indexed)
5. A Conceptual Model of Resilience Capability:
Human Centric Approach
International Conference On Information Resources Management
(Conf-irm) 2016: Digital Emancipation In A Networked Society