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Article

Modeling the Barriers Surrounding Digital Government Implementation: Revealing Prospect Opportunities in Saudi Arabia

by
Anas A. Makki
1,* and
Ammar Y. Alqahtani
2
1
Department of Industrial Engineering, Faculty of Engineering—Rabigh Branch, King Abdulaziz University, Jeddah 21589, Saudi Arabia
2
Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(23), 15780; https://doi.org/10.3390/su142315780
Submission received: 2 November 2022 / Revised: 24 November 2022 / Accepted: 24 November 2022 / Published: 27 November 2022
(This article belongs to the Topic Digital Transformation and E-Government)
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Abstract

:
Digital government (DG) is key to more efficient, transparent, and successful governance processes in meeting beneficiaries’ demands. However, its implementation challenges traditional conceptions. This research study aims at modeling barriers surrounding DG implementation in Saudi Arabia. The interpretive structural modeling (ISM) approach was followed. Thirteen barriers to DG implementation were identified and used to collect DG experts’ opinions on the barriers. The developed model classifies the barriers based on their dependence and driving powers and reveals interrelationships among them on multiple levels. Key findings showed that institutional habits are a foundational barrier affecting political coordination. Both, in turn, lead to ethical concerns and perceived barriers related to law, organizational practice, finances, and technological resources, which all lead to risk aversion and capacity and skills barriers, consequently resulting in a lack of engagement with and demand from users/citizens, a lack of awareness/strategic thinking, and legal framework issues, thereby resulting in technological infrastructure issues, difficulty articulating benefits to beneficiaries, and political management support and leadership barriers. Implications of the developed model include providing a better understanding of the contextual interrelationships between the barriers, which will, in turn, assist in fostering current implementation successes and opening prospects for future opportunities in Saudi Arabia.

1. Introduction

Unintended social and environmental ramifications have resulted from strong economic expansion in the previous century, threatening the health and well-being of the present generation and those to follow. Sustainable development is integral to greening the national accounts as policymakers shift their attention from economic growth to social and environmental issues [1]. Sustainable development is defined by the United Nations’ World Commission on Environment and Development as “development that satisfies the present demands without compromising the ability of future generations to satisfy their own needs”. Development that meets present demands without sacrificing the ability of future generations to meet their own is what this term means. Consequently, the issue arose of how to measure sustainability, and many indicators were devised as a result. Sustainability may be measured concerning the World Bank’s adjusted net savings, a well-known and regarded metric [2,3]. After accounting for investments in human capital, depletion of natural resources, and environmental implications, the “real saving rate” is defined as the “saving rate in an economy” [4]. In 2020, the World Bank is believed to have established this indicator based on the economic premise that savings equal investment and measures the change in wealth based on this concept [5]. The sustainability of development is linked to changes in wealth because a country’s resources are depleted if it progresses on a path that is not sustainable [6]. The economic, social, and environmental progress are independently considered when calculating overall savings.
Several studies have demonstrated that the quality of institutions significantly impacts the possibility of attaining sustainable development [7,8,9]. A system of institutions capable of managing natural resources, collecting resource rents, and redirecting these revenues into profitable investments is necessary to achieve this goal. Consequently, other authors describe that inadequate governance is the primary cause of the resource curse [10,11]. When allocating resources, good governance may positively impact sustainable development outcomes [9,12]. The United Nations [13] defines “governance” as “the process of decision-making and the process by which decisions are implemented (or not implemented)”. The term “governance” has a wide range of applications, including corporate, international, national, and even municipal spheres of influence. There are eight main factors of good governance. It is democratic in the sense that everyone has a voice, works toward agreement, is held to account, is open and honest, acts swiftly and efficiently, is fair, and includes everyone. It also guarantees that corruption is kept to a minimum, that minority opinions are considered, and that those most at risk in society have a say in policymaking. In addition, it adapts to the changing demands of society. Technological advancements are essential, but improvements in politics, society, philosophy, ethics, and culture are also necessary for good governance to become a reality [14]. If the project hopes to survive the test of time, everyone participating must put up their entire effort. Each component, such as hardware, software, services, and people, must play a critical role in long-term, sustainable growth in today’s “age of e” [15].
Therefore, to ensure long-term prosperity, governments throughout the globe are embracing the digital revolution by using information and communications technologies (ICTs) that improve policy and public service integration while also reinforcing and improving institutional transparency [16]. According to the United Nations, despite achieving better governance based on many factors, technical developments are essential for sustainable development [17]. Accordingly, e-government (EG) might help avert future environmental damage by enhancing resource management in the present. A large body of research has well-documented the positive impact of EG on transparency, participation, and accountability [18,19,20,21,22,23]. Digital government (DG) refers to the government’s all-encompassing digital policies and structures designed to address people’s demands and worries. However, EG is concerned with how ICT is actually used to achieve government objectives [24].
Accordingly, in March 2021, a Digital Government Authority (DGA) was established by the Saudi Arabian government [25]. The DGA acts as the national point of reference for the DG and is responsible for overseeing all aspects of its implementation. Ultimately, the goal is to create a digital and proactive government capable of delivering high-quality digital services and integrating all government departments in the area of DG. As the title suggests, this paper is concerned with how issues are framed and how technology might be used to resolve those difficulties. Disruptive digitalization poses new challenges to many nations’ economies, necessitating new management and institutional approaches to deal with them [25].
The current study focuses on identifying a wide range of barriers to implementing and sustaining digital governance. Then, the interrelationships between DG barriers are to be modeled using a well-established method, interpretive structural modeling (ISM). Following is a rundown of relevant research literature on DG, its current implementation status in Saudi Arabia, barriers to its implementation, and studies following the ISM approach to model such barriers.

2. Literature Review

2.1. Digital Government (DG)

Information and technology are central to almost every government activity and governance process. Movements toward a more efficient, transparent, and successful government could be achieved through information and communication technology. These movements are challenging traditional administrative, management, and responsibility conceptions.
Technology and emerging technologies are being used at all levels and in all government branches today to meet the demands of citizens, residents, service providers, public workers, leaders, and decision-makers. When it comes to the government’s working environment, there is a wide range of technological tools available, from mobile applications to social media to open government data. In DG, there is a shift from the previous concept of government administration based only on using ICTs toward the current understanding of their impact on governance, management, and administration. The phenomenon of digital control requires new leadership styles, mechanisms for making decisions, strategies for organizing and delivering services, and emerging concepts of the citizenry. These are all examples of digital governance. UNESCO’s e-governance concept aligns with our understanding of DG: “technology-enabled improvements in public information and services, more citizen participation in decision-making, and increased accountability and openness in government” [26]. Furthermore, digital governance is a model for defining who is responsible for what in terms of the organization’s online presence, as well as who has the power to make decisions and implement changes. A well-designed digital governance structure is essential to guarantee digital business maturity with little expenditure and maximum efficiency [27].
The computer, political, information, and administrative science disciplines all contributed to the development of digital governance. As a result, it encompasses various perspectives, methodologies, and topics that draw from standard academic domains in some way or that reach beyond them. Consequently, it has been suggested that the field of public administration is more appropriate to study than digital governance [28]. For example, they see digital governance as a subfield of public administration study. Contrast this with another view suggesting that DG is intrinsically interdisciplinary and represents the convergence of fundamental problems about governance, individual rights, and technological advances [29]. As a result of this ever-changing environment, it is essential to have a perspective on both government and administration that is more expansive and more receptive to new ideas in this age. It was persuasively demonstrated that digital governance is an innovative field of research that takes a cross-disciplinary approach to address the barriers posed by today’s information society [30].
The same could be said for the various multi- and cross-disciplinary research attempts that have been made to define the progression of DG research and its trajectory [31,32,33]. DG experts from different academic backgrounds, competence, locations, research focuses, and outputs have been recognized and categorized in the literature [34]. The concepts and variables that DG academics utilize in their research frameworks and theories were the primary subjects of the study [35]. Other researchers have also investigated the research methodology and data used in studies of digital governance [36,37]. Due to the rapid growth of digital governance, policies and practices within the public sector have also been scrutinized [38,39,40].
Other researchers focus on how new technologies and different data types and applications will affect government operations and how research into DG might be translated into valuable recommendations for public officials. For instance, researchers in this field are researching topics such as the modernization of government, digital democracy, citizen involvement, information access, and improved public services, in addition to a variety of other significant themes and research efforts relevant to this field [41]. Other key unanswered questions include how to integrate studies of digital governance more effectively with traditional research on public administration. Another question is how to assess and evaluate both performance and implications more effectively [42]. These are only a few of the many questions that could be asked.

2.2. Digital Government (DG) in Saudi Arabia

Many researchers on the Arabian Peninsula have studied EG, but just a few studies have focused on Saudi Arabia’s DG [43,44]. DG and EG should not be used interchangeably. DG refers to a government that fully uses digital tactics and structures due to its citizens’ increasing need for better services. EG emphasizes the communication and information technology used to accomplish the government’s objectives [45]. However, sometimes the terms are used interchangeably in the literature.
The EG of Saudi Arabia was established in the first decade of the twenty-first century, and the achievements of such an administration are discussed in a research article [46]. Since the beginning of the EG used in Saudi Arabia, a significant amount of research conducted on the topic has been published. The most recently conducted research effort on adopting the EG in Saudi Arabia was a developed conceptual model [47].
Despite the current successes of the DG in Saudi Arabia, it has been observed that there are some barriers surrounding its implementation and use to the full extent. These include the lack of some information technology infrastructure in the public sector and widespread indifference toward it; inadequate security and privacy safeguards of data; and an overall deficiency of trained information technology and government service expertise. Furthermore, cultural factors are partially to blame for the deferred adoption of EG in Saudi Arabia [48].
Therefore, the DGA in Saudi Arabia has established an inclusive government program to offer the government sector integrated digital services [25]. DG transformation must be accelerated, and data exchange across government institutions must be expanded to build an integrated and sustainable system. The Government Electronic and Mobile Services (GEMS) Maturity Index, published by the United Nations Economic and Social Commission for Western Asia (ESCWA), placed Saudi Arabia at the top in 2022 [49]. The index includes e-portals and mobile applications from various industries, including education, the legal system, financial services, business, and tourism. According to the Digital Maturity index published in 2021 by the World Bank, the country ranks among the highest in the world in terms of its ability to provide DG services and engage with its citizens [50].

2.3. Interpretive Structural Modeling (ISM) and Barriers to Digital Government (DG)

Identifying and describing interrelationships between specific components that constitute a problem, ranking the variables according to the importance of their effects, and providing a cognitive inference are all functions of ISM. Researchers in various fields have used ISM extensively to decipher raw data and unclear situations. Converting muddled mental system conceptions into observable, precise models that may be put forward for many uses is a common justification for using ISM [51]. ISM may be used in a wide variety of industries and applications. For instance, it was used with an analytic hierarchy approach to examine green suppliers [52]. ISM was also used in vendor selection [53]. Another example is a recent research study using ISM to examine green entrepreneurship barriers [54].
However, studies modeling the barriers to DG using ISM have been sparse. The literature review shows that DG is a potential service delivery method for the government and the public by employing information and communication technology that has yet to be fully utilized in practice. The primary cause of this inefficiency is the absence of models identifying connections between enablers or barriers affecting government entities. Therefore, modeling barriers to the implementation of DG is crucial. Previous research studies have found a range of barriers to DG. It routinely highlights the needs of in-charge persons who traverse government institutional environments and proactively seek DG solutions.
Thus, this research study aims to model DG implementation’s barriers using ISM. After an extensive literature review, thirteen barriers to implementing DG were extracted and are listed in Table 1, with their associated references, to be the focus of the herein research study. To accomplish this objective, interrelationships between these barriers and their priorities are modeled by exploring how Saudi Arabian experts perceive the extracted barriers to digital governance and their ability to overcome them. This is based on their experience during the considerable progress that has been made in Saudi Arabia’s digital governance. This research study attempts to better understand the interrelationships between the barriers to implementing the DG, which will, in turn, assist in fostering current successes in this field and open up prospects for future opportunities in Saudi Arabia. The materials and methods used to achieve the objective of this research study, the developed model, a discussion, and conclusions are described in the remainder of this research article.

3. Materials and Methods

This research study aims at modeling barriers surrounding DG. In order to attain the objective, the ISM technique was used. This is due to its ability to deal with interconnected elements, such as the barriers of DG herein, establish relationships among them, and capture the complexities of those relationships and the problem under study [79,80,81]. Studying barriers surrounding DG requires input information from experts and decision-makers in the field who are closely working on the digitalization plan and responsible for designing the overarching digital strategy and setting up needed structures. This ensures the accuracy of the information provided as inputs to the modeling and analysis and, in turn, the accuracy of findings. Due to the nature of the study, a few experts fit such criteria to be targeted for their input. However, another strength of the ISM technique is that it enables a better understanding of complex problems and synthesizes relationships among its elements by providing input from a small group of experts [82]. The ISM technique follows a systematic and iterative approach based on Boolean mathematics and the application of graph theory [83]. According to [54,80,81], seven steps can be followed to conduct the ISM technique and its analysis, as presented in Figure 1. These seven steps were adopted for this research study as indicated in the following research methodology flowchart illustrated in Figure 2.
In order to achieve the objective of this study, the research methodology flowchart presented in Figure 2 was followed. In the first step of the ISM technique (Figure 1), the thirteen barriers surrounding DG (i.e., DG-B1 to DG-B13) listed in Table 1 were identified through an extensive literature review. Subsequently, the ISM technique was selected for the reasons mentioned earlier. Accordingly, a questionnaire was designed following a pairwise format to collect data on experts’ opinions who determined the direction of effect between pairs of the thirteen barriers relative to each other. Next, twenty-four Saudi DG experts were targeted and provided input data through the questionnaire. The experts involved in this research study are all leaders and decision-makers working in Saudi government agencies responsible for digital transformation programs, digitalization plan implementation, designing the overarching digital strategy, and setting up their needed structures. All experts are working in the Saudi National Digital Transformation Unit. The collected data were used to identify the contextual relationships among the barriers, which is the second step of the ISM technique (Figure 1). Considering the rules presented in Table 2, the ISM steps 3 to 7 (Figure 1) were applied. This included the construction of the structural self-interaction matrix (SSIM), forming the initial reachability matrix (IRM) and forming the final reachability matrix (FRM) after checking the transitivity between the barriers based on Warshall’s algorithm [84], determining barrier levels using the partitioning matrix (PM) and classifying the studied barriers based on their dependence and driving powers, and finally, structuring the ISM digraph or network. As shown in Figure 2, the resulting ISM digraph is checked for contextual inconsistencies with this research study’s involved group of experts. Once agreed upon, the resulting ISM digraph is considered the final interpretive structure model of barriers surrounding DG implementation in Saudi Arabia. The application of the materials and methods, along with the results and findings, are presented in the subsequent section.

4. Results

The study’s objective is accomplished by applying the ISM seven steps presented in Figure 1 and following the methodology flowchart illustrated in Figure 2. Experts’ opinion data on the direction of relationships of seventy-eight unique pair combinations of barriers (i.e., 13!/(2! × 11!) = 78) were collected using the designed questionnaire. Following the rules presented in Table 2, the collected data were used as inputs and consolidated to construct the SSIM shown in Table 3.
The construction of the SSIM was performed by assigning directions of relationships indicated by experts using the entry codes: V, A, X, and O. The constructed SSIM was then used to form the IRM presented in Table 4 by converting the entry codes to 0–1 format based on the rules in Table 2. The formed IRM enabled the calculating of the driving and dependence powers of barriers understudy, as shown in Table 4.
However, to account for indirect and higher-order relationships, a transitivity test was conducted to form the FRM (Table 5). The driving and dependence powers of barriers were recalculated, as presented in Table 5.
In order to determine barrier levels, six iterations were performed in the PM (i.e., 1–6 in Table 6), which classified the barriers based on their dependence and driving powers into six levels (i.e., I–IV in Table 6).
The barriers were charted into a quadrant chart illustrated in Figure 3 to visualize their classifications into four categories: autonomous, dependent, linkage, and independent barriers. The resulting classification of barriers in Figure 3 revealed that none of the thirteen barriers classify as autonomous barriers. However, the barriers (DG-B2: institutional habits and established “ways of doing things”), (DG-B13: political coordination), (DG-B3: ethical concerns), (DG-B5: perceived barriers related to law, organizational practice, and finances), and (DG-B9: technological resources) all classify as dependent barriers, indicating that they are influenced or led to by other barriers. Moreover, results show that (DG-B4: risk aversion) and (DG-B7: capacity and skills) classify as linkage barriers. Furthermore, (DG-B8: lack of engagement with and demand from users/citizens), (DG-B6: lack of awareness/strategic thinking), (DG-B1: legal framework), (DG-B10: technological infrastructure), (DG-B11: difficulty articulating benefits to others), and (DG-B12: political and management support and leadership) all classify as dependent barriers.
The ISM diagraph was then configured using the revealed levels of barriers. In order to check for the contextual consistency of the developed ISM diagraph, as shown in the methodology flowchart in Figure 2, it was presented to the experts and confirmed. The final ISM diagraph of barriers surrounding DG implementation is illustrated in Figure 4. The resulting model in Figure 4 classifies the barriers based on dependence and driving powers and reveals interrelationships among them in six levels. Key findings showed that (DG-B2: institutional habits and established “ways of doing things”) is a foundational barrier affecting (DG-B13: political coordination). Both, in turn, lead to (DG-B3: ethical concerns), (DG-B5: perceived barriers related to law, organizational practice, and finances), and (DG-B9: technological resources) issues related to software and standards, which all lead to (DG-B4: risk aversion) and (DG-B7: capacity and skills) barriers related to project management. Consequently, this results in (DG-B8: lack of engagement with and demand from users/citizens), (DG-B6: lack of awareness/strategic thinking), and (DG-B1: legal framework) issues related to privacy and security, which thereby results in (DG-B10: technological infrastructure) issues related to computers and networks, (DG-B11: difficulty articulating benefits to others), and (DG-B12: political and management support and leadership) barriers. A discussion of the developed model is provided in the next section.

5. Discussion

While the DG’s established advantages are undeniable, its acceptance has not been as great as expected. DG deployment has been hampered by various barriers, including managerial, technical, procedural, and cultural, in this research. An initial set of thirteen barriers to the effective adoption of DG were identified after an extensive literature review of previous research studies and talks with government professionals. Using an ISM model, a hierarchy of barriers was devised to accomplish this. This paper’s results identify the most influential barriers and their pertaining causal linkages. Governments, in turn, use this information to plan tactics to counteract the most powerful barriers. The following are some of the study’s most significant results.
Eight of the thirteen studied barriers to DG adoption mentioned in Table 1 are deemed extremely critical. Therefore, they should be given serious attention prior to participating in any DG implementation strategy. With these barriers, the most essential is institutional habits and established “ways of doing things”, which can potentially exacerbate other problems. An important quality of effective management teams is the ability to figure out new ways to do things, which may elevate people and foster an internal and external collaborative culture. Collaborating with others would be a lengthy and fruitless trip without strong leadership. The most common barriers include political coordination, ethics, “perceived barriers linked to legislation, organizational practice, and economics”, and technical resources (software and standards) skills. This demonstrates that institutional habits and established “ways of doing things” may aggravate political coordination, influencing other barriers. The developed model revealed that it is very influential in political coordination, technical resources (software and standards), skills, and ethical concerns.
Four of the five most powerful barriers the ISM revealed are in the model’s bottom three layers. The analysis demonstrated that political coordination is a critical inhibitor, which also has a strong driving power after the institutional habits and established “ways of doing things” barrier, leading to eleven more barriers. This model demonstrates that five of the most influential barriers fall into the process category, with perceived barriers relating to legislation, organizational practice, and money as major driving barriers. Project management and risk aversion might be placed higher in the developed structure due to this barrier.
In the FRM (Table 5) and the final ISM model (Figure 4), seven more barriers are linked to risk aversion. As observed in a recent study, risk aversion is the most significant and fundamental reason for many DG adoption difficulties [80]. It was commonplace to depict them as being averse to risk, afraid, and lacking in incentives to change the way things had always been done.
According to the final ISM model (Figure 4), a few of the observed barriers amplify each other considerably. Political and managerial support, as well as difficulties in conveying the advantages to others, are both interconnected. That is to say, those who lack political and managerial support and leadership have a difficult time articulating the benefits to others, and the converse is true. As a further example, risk aversion and difficulty communicating advantages to others influence each other in the capacity and skills necessary to manage projects. Technology infrastructure (computers and networks), difficulty explaining the benefits to others, and political and management support and leadership were found to be the most influenced by other barriers.
As demonstrated in Figure 3, none of the thirteen barriers is classified as autonomous to the DG’s overall implementation process. This result indicates the nonexistence of self-governing barriers, indicating that studied barriers cannot be isolated when making decisions on DG implementation plans. Based on the findings, the barriers, risk aversion, capacity, and skills (project management) classify as linkage barriers. This indicates that any action affecting these barriers will lead to a ripple effect that impacts other barriers, and so on and so forth. Furthermore, given the technical resources (software and standards) barrier driving power and its intensification connection with other barriers, it could be suggested that the correct technology resources and standards are crucial to a successful DG deployment process.

6. Conclusions

DG is a potential service delivery method for the government and the public by employing information and communication technology that has yet to be utilized to its fullest extent in practice. This shortcoming is because its implementation challenges traditional administrative, management, and responsibility conceptions. Therefore, this research study aimed to model barriers surrounding its implementation in the context of Saudi Arabia. Thirteen barriers were extracted from the literature and used to design a questionnaire as the data collection tool. Input data from twenty-four DG experts were utilized to model interrelationships between the studied barriers using ISM. Key findings of the developed model showed that institutional habits and established “ways of doing things” are foundational barriers affecting political coordination. Both, in turn, lead to ethical concerns and perceived barriers related to law, organizational practice, finances, and technological resources, which all lead to risk avoidance and capacity and skills barriers, consequently resulting in a lack of engagement with and demand from users/citizens, a lack of awareness/strategic thinking, and legal framework issues. This therefore results in technological infrastructure issues, difficulty articulating benefits to others, and political and management support and leadership barriers.
The developed model of barriers interrelationships in this study opens up opportunities for successful DG implementation and improvements when viewed as a roadmap of enablers. From this standpoint, reviewing and changing organizational culture and habits of doing things is the primary enabler and the starting point to its implementation. Then, once institutional culture and internal processes are ready, coordination with external entities comes into place. This will enable the determination of the required technological resources and standards, clarifying ways to overcome related ethical concerns, and changing perceptions of law, organizational practice, finances, and technical resources. This, in turn, enables governments to avoid risks and improve capacity and human capital skills in managing projects and executing plans, thus increasing the ability to better engage with and satisfy demand from users/citizens, achieve better awareness spread, have a capacity for strategic thinking, and make improvements in the legal framework. This results in overcoming technological infrastructure issues, better articulating benefits to others, and assuring political and management support and leadership.
Implications of the developed model include providing a better understanding of the interrelationships between the barriers to implementing the DG. This will, in turn, assist government agencies responsible for digital transformation programs, digitalization plans implementation, designing the overarching digital strategy, and setting up their needed structures in fostering current implementation successes and opening up prospects for future opportunities in Saudi Arabia.
The developed ISM model in this study heavily depends on the engaged experts’ opinions reflecting the current case in Saudi Arabia and the recent advancement in DG implementation. Therefore, reconducting the study in other timeframes and countries is a future research direction that may confirm the developed model or adjust it better to reflect its implementation’s spatial and timeframe contexts. Furthermore, the resulting model in this study is developed following a well-established numerical approach and deemed reflective based on reliable experts’ opinions. However, reconducting the study following a statistical approach with a larger sample size is the next research direction to ensure its validity and generalizability. Finally, the developed model in this study reflects barriers to DG implementation from the provider side. Studying barriers to DG adoption from the beneficiaries’ side is another future research direction.

Author Contributions

Conceptualization, A.A.M. and A.Y.A.; methodology, A.A.M. and A.Y.A.; software, A.A.M. and A.Y.A.; validation, A.A.M. and A.Y.A.; formal analysis, A.A.M. and A.Y.A.; investigation, A.A.M. and A.Y.A.; resources, A.A.M. and A.Y.A.; data curation, A.A.M. and A.Y.A.; writing—original draft preparation, A.A.M. and A.Y.A.; writing—review and editing, A.A.M. and A.Y.A.; visualization, A.A.M. and A.Y.A.; supervision, A.A.M. and A.Y.A.; project administration, A.A.M. and A.Y.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy and ethical restrictions.

Acknowledgments

The authors acknowledge and thank all the questionnaire respondents in this research study.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Seven implementation steps of the ISM technique.
Figure 1. Seven implementation steps of the ISM technique.
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Figure 2. Research Methodology Flowchart.
Figure 2. Research Methodology Flowchart.
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Figure 3. Classification of Thirteen Barriers Surrounding Digital Government (DG) Implementation.
Figure 3. Classification of Thirteen Barriers Surrounding Digital Government (DG) Implementation.
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Figure 4. Final ISM Diagraph of Barriers Surrounding Digital Government (DG) Implementation.
Figure 4. Final ISM Diagraph of Barriers Surrounding Digital Government (DG) Implementation.
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Table
Table 1. Extracted Barriers to Digital Government (DG) from the Literature with Associated References.
Table 1. Extracted Barriers to Digital Government (DG) from the Literature with Associated References.
AcronymBarrierReferences
DG-B1Legal frameworks (privacy and security)[55,56,57,58,59,60,61,62,63,64,65,66,67]
DG-B2Institutional habits and established “ways of doing things”[56,58,63,64,67,68,69,70,71,72]
DG-B3Ethical concerns[56]
DG-B4Risk aversion[59,60,68,70,71,72,73,74,75,76]
DG-B5Perceived barriers related to law, organizational practice, finances[64,68,70,71,76]
DG-B6Lack of awareness/strategic thinking[55,57,61,62,64]
DG-B7Capacity and skills (project management)[61,63]
DG-B8Lack of engagement with and demand from users/citizens[55,56,60,62,63,64,65,67,74,77]
DG-B9Technological resources (software and standards)[62,63]
DG-B10Technological infrastructure (computers and networks)[56,58,60,61,62,63,65,66,67]
DG-B11Difficulty articulating benefits to others[64,68,77,78]
DG-B12Political and management support and leadership[55,57,58,60,61,62,63,64,65,70,71,73,75]
DG-B13Political coordination[58,62,63,70]
Table
Table 2. Rules of constructing the Structural Self-Interaction Matrix (SSIM) and the Initial Reachability Matrix (IRM).
Table 2. Rules of constructing the Structural Self-Interaction Matrix (SSIM) and the Initial Reachability Matrix (IRM).
ScenarioDirection of RelationshipSSIM EntryIRM Entries
(DG-Bi, DG-Bj) *(DG-Bi, DG-Bj) *(DG-Bi, DG-Bj) *(DG-Bj, DG-Bi) *
1DG-Bi → DG-BjV10
2DG-Bi ← DG-BjA01
3DG-Bi ↔ DG-BjX11
4DG-Bi × DG-BjO00
* i and j indicate the barrier number in a row and column in the associated matrix, respectively.
Table
Table 3. Structural Self-Interaction Matrix (SSIM) of Thirteen Barriers Surrounding Digital Government (DG) Implementation.
Table 3. Structural Self-Interaction Matrix (SSIM) of Thirteen Barriers Surrounding Digital Government (DG) Implementation.
BarrierDG-B1DG-B2DG-B3DG-B4DG-B5DG-B6DG-B7DG-B8DG-B9DG-B10DG-B11DG-B12DG-B13
DG-B1 AAAAXAXAVVVA
DG-B2 VVVVVVVVVVV
DG-B3 VXVVVXVVVA
DG-B4 AVXVAVVVA
DG-B5 VVVXVVVA
DG-B6 AXAVVVA
DG-B7 VAVVVA
DG-B8 AVVVA
DG-B9 VVVA
DG-B10 XXA
DG-B11 XA
DG-B12 A
DG-B13
Table
Table 4. Initial Reachability Matrix (IRM) of Thirteen Barriers Surrounding Digital Government (DG) Implementation.
Table 4. Initial Reachability Matrix (IRM) of Thirteen Barriers Surrounding Digital Government (DG) Implementation.
BarrierDG-B1DG-B2DG-B3DG-B4DG-B5DG-B6DG-B7DG-B8DG-B9DG-B10DG-B11DG-B12DG-B13Driving Power
DG-B110000101011106
DG-B2111111111111113
DG-B3101111111111011
DG-B410010111011108
DG-B5101111111111011
DG-B610000101011106
DG-B710010111011108
DG-B810000101011106
DG-B9101111111111011
DG-B1000000000011103
DG-B1100000000011103
DG-B1200000000011103
DG-B13101111111111112
Dependence Power1015751071051313132
Table
Table 5. Final Reachability Matrix (FRM) * of Thirteen Barriers Surrounding Digital Government (DG) Implementation.
Table 5. Final Reachability Matrix (FRM) * of Thirteen Barriers Surrounding Digital Government (DG) Implementation.
BarrierDG-B1DG-B2DG-B3DG-B4DG-B5DG-B6DG-B7DG-B8DG-B9DG-B10DG-B11DG-B12DG-B13Driving Power
DG-B110000101011106
DG-B2111111111111113
DG-B3101111111111011
DG-B410010111011108
DG-B5101111111111011
DG-B610000101011106
DG-B710010111011108
DG-B810000101011106
DG-B9101111111111011
DG-B1000000000011103
DG-B1100000000011103
DG-B1200000000011103
DG-B13101111111111112
Dependence Power1015751071051313132
* Transitivity test was conducted based on Warshall’s algorithm [84].
Table
Table 6. Partitioning Matrix (PM) of Thirteen Barriers Surrounding Digital Government (DG) Implementation.
Table 6. Partitioning Matrix (PM) of Thirteen Barriers Surrounding Digital Government (DG) Implementation.
IterationBarrierReachability SetAntecedent SetIntersection SetLevel
1DG-B1DG-B1, DG-B6, DG-B8, DG-B10, DG-B11, DG-B12DG-B1, DG-B2, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B13DG-B1, DG-B6, DG-8
DG-B2DG-B1, DG-B2, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B10, DG-B11, DG-B12, DG-B13DG-B2DG-B2
DG-B3DG-B1, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B10, DG-B11, DG-B12DG-B2, DG-B3, DG-B5, DG-B9, DG-B13DG-B3, DG-B5, DG-B9
DG-B4DG-B1, DG-B4, DG-B6, DG-B7, DG-B8, DG-B10, DG-B11, DG-B12DG-B2, DG-B3, DG-B4, DG-B5, DG-B7, DG-B9, DG-B13DG-B4, DG-B7
DG-B5DG-B1, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B10, DG-B11, DG-B12DG-B2, DG-B3, DG-B5, DG-B9, DG-B13DG-B3, DG-B5, DG-B9
DG-B6DG-B1, DG-B6, DG-B8, DG-B10, DG-B11, DG-B12DG-B1, DG-B2, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B13DG-B1, DG-B6, DG-B8
DG-B7DG-B1, DG-B4, DG-B6, DG-B7, DG-B8, DG-B10, DG-B11, DG-B12DG-B2, DG-B3, DG-B4, DG-B5, DG-B7, DG-B9, DG-B13DG-B4, DG-B7
DG-B8DG-B1, DG-B6, DG-B8, DG-B10, DG-B11, DG-B12DG-B1, DG-B2, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B13DG-B1, DG-B6, DG-B8
DG-B9DG-B1, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B10, DG-B11, DG-B12DG-B2, DG-B3, DG-B5, DG-B9, DG-B13DG-B3, DG-B5, DG-B9
DG-B10DG-B10, DG-B11, DG-B12DG-B1, DG-B2, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B10, DG-B11, DG-B12, DG-B13DG-B10, DG-B11, DG-B12I
DG-B11DG-B10, DG-B11, DG-B12DG-B1, DG-B2, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B10, DG-B11, DG-B12, DG-B13DG-B10, DG-B11, DG-B12I
DG-B12DG-B10, DG-B11, DG-B12DG-B1, DG-B2, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B10, DG-B11, DG-B12, DG-B13DG-B10, DG-B11, DG-B12I
DG-B13DG-B1, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B10, DG-B11, DG-B12, DG-B13DG-B2, DG-B13DG-B13
2DG-B1DG-B1, DG-B6, DG-B8DG-B1, DG-B2, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B13DG-B1, DG-B6, DG-B8II
DG-B2DG-B1, DG-B2, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B13DG-B2DG-B2
DG-B3DG-B1, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9DG-B2, DG-B3, DG-B5, DG-B9, DG-B13DG-B3, DG-B5, DG-B9
DG-B4DG-B1, DG-B4, DG-B6, DG-B7, DG-B8DG-B2, DG-B3, DG-B4, DG-B5, DG-B7, DG-B9, DG-B13DG-B4, DG-B7
DG-B5DG-B1, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9DG-B2, DG-B3, DG-B5, DG-B9, DG-B13DG-B3, DG-B5, DG-B9
DG-B6DG-B1, DG-B6, DG-B8DG-B1, DG-B2, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B13DG-B1, DG-B6, DG-B8II
DG-B7DG-B1, DG-B4, DG-B6, DG-B7, DG-B8DG-B2, DG-B3, DG-B4, DG-B5, DG-B7, DG-B9, DG-B13DG-B4, DG-B7
DG-B8DG-B1, DG-B6, DG-B8DG-B1, DG-B2, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B13DG-B1, DG-B6, DG-B8II
DG-B9DG-B1, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9DG-B2, DG-B3, DG-B5, DG-B9, DG-B13DG-B3, DG-B5, DG-B9
DG-B13DG-B1, DG-B3, DG-B4, DG-B5, DG-B6, DG-B7, DG-B8, DG-B9, DG-B10, DG-B11, DG-B12, DG-B13DG-B2, DG-B13DG-B13
3DG-B2DG-B2, DG-B3, DG-B4, DG-B5, DG-B7, DG-B9, DG-B13DG-B2DG-B2
DG-B3DG-B3, DG-B4, DG-B5, DG-B7, DG-B9DG-B2, DG-B3, DG-B5, DG-B9, DG-B13DG-B3, DG-B5, DG-B9
DG-B4DG-B4, DG-B7DG-B2, DG-B3, DG-B4, DG-B5, DG-B7, DG-B9, DG-B13DG-B4, DG-B7III
DG-B5DG-B3, DG-B4, DG-B5, DG-B7, DG-B9DG-B2, DG-B3, DG-B5, DG-B9, DG-B13DG-B3, DG-B5, DG-B9
DG-B7DG-B4, DG-B7DG-B2, DG-B3, DG-B4, DG-B5, DG-B7, DG-B9, DG-B13DG-B4, DG-B7III
DG-B9DG-B3, DG-B4, DG-B5, DG-B7, DG-B9DG-B2, DG-B3, DG-B5, DG-B9, DG-B13DG-B3, DG-B5, DG-B9
DG-B13DG-B3, DG-B4, DG-B5, DG-B7, DG-B9, DG-B13DG-B2, DG-B13DG-B13
4DG-B2DG-B2, DG-B3, DG-B5, DG-B9, DG-B13DG-B2DG-B2
DG-B3DG-B3, DG-B5, DG-B9DG-B2, DG-B3, DG-B5, DG-B9, DG-B13DG-B3, DG-B5, DG-B9IV
DG-B5DG-B3, DG-B5, DG-B9DG-B2, DG-B3, DG-B5, DG-B9, DG-B13DG-B3, DG-B5, DG-B9IV
DG-B9DG-B3, DG-B5, DG-B9DG-B2, DG-B3, DG-B5, DG-B9, DG-B13DG-B3, DG-B5, DG-B9IV
DG-B13DG-B3, DG-B5, DG-B9, DG-B13DG-B2, DG-B13DG-B13
5DG-B2DG-B2, DG-B13DG-B2DG-B2
DG-B13DG-B13DG-B2, DG-B13DG-B13V
6DG-B2DG-B2DG-B2DG-B2VI
Shaded cells indicate the eliminated sets of barriers in each iteration and the assigned level of the related barrier.
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Makki, A.A.; Alqahtani, A.Y. Modeling the Barriers Surrounding Digital Government Implementation: Revealing Prospect Opportunities in Saudi Arabia. Sustainability 2022, 14, 15780. https://doi.org/10.3390/su142315780

AMA Style

Makki AA, Alqahtani AY. Modeling the Barriers Surrounding Digital Government Implementation: Revealing Prospect Opportunities in Saudi Arabia. Sustainability. 2022; 14(23):15780. https://doi.org/10.3390/su142315780

Chicago/Turabian Style

Makki, Anas A., and Ammar Y. Alqahtani. 2022. "Modeling the Barriers Surrounding Digital Government Implementation: Revealing Prospect Opportunities in Saudi Arabia" Sustainability 14, no. 23: 15780. https://doi.org/10.3390/su142315780

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