Assessing and Prioritizing Service Innovation Challenges in UAE Government Entities: A Network-Based Approach for Effective Decision-Making

Abstract

Public service innovation research often focuses on the private or general public sectors, leaving the distinct challenges government entities face unexplored. An empirical study was carried out to bridge this gap using survey results from the United Arab Emirates (UAE) government entities. This study built on that research by further analyzing the relationships among these challenges through a social network approach, visualizing and analyzing the connections between them by utilizing betweenness centrality and eigenvector centrality as key metrics. Based on this analysis, the challenges were classified into different categories; 8 out of 22 challenges were identified as critical due to their high values in both metrics. Addressing these critical challenges is expected to create a cascading impact, helping to resolve many others. Targeted strategies are proposed, and leveraging open innovation is highlighted as an effective and versatile solution to address and mitigate these challenges. This study is one of the few to adopt a social network analysis perspective to visualize and analyze the relationships among challenges, enabling the identification of critical ones. This research offers novel and valuable insights that could assist decision-makers in UAE government entities and countries with similar contexts with actionable strategies to advance public service innovation.

1. Introduction

The early view of innovation was dominated by the perception that innovation can assist businesses and entrepreneurs in prospering and gaining a competitive differentiation and market advantage through innovative services or products created to align with customer expectations. Innovation, recognized as a driving force for competitive advantage, enables organizations to deliver valuable, practical, and engaging solutions to their customers [1,2,3]. Service innovation primarily involves developing business models, enhancing processes and service offerings, and creating value for stakeholders, employees, and societies [4]. Its significance extends across private and public sectors, contributing to technological advancements and societal welfare. It is a crucial differentiator, positioning organizations for competitive growth and strategic advantages [5,6]. Moreover, service innovation is vital for organizational survival as it cuts operational expenses, enhances productivity, and drives transformative change [7,8,9]. Therefore, public service innovation research has recently drawn the attention of scholars and professionals, indicating the importance of this field and its significant impact on outcomes [10].

Moreover, regarding value creation, public sector core values are distinct and more intricate [11]. These values include enhancing service quality, improving societal welfare, and building trust in government to deliver effective policies and services. The complexity of public service innovation requires managers to comprehend the external environment and internal organizational context to understand the catalysts of various types of innovation [12].

Fostering innovation in this complex context often spawns several challenges organizations encounter, hindering innovation initiatives. These challenges can significantly impede the progress toward strategic innovation goals and may arise at any stage of the innovation process. Commonly referred to as constraints, barriers, problems, or inhibitors [13], understanding these challenges requires more than identification and ranking; it necessitates a deeper exploration of their interrelationship and dependency. However, as highlighted in Section 3.3, most studies that have explored public sector organizations’ challenges have overlooked how these challenges influence one another, both directly and indirectly. Recognizing these interrelations is essential, as any effort to facilitate innovation without addressing them may ultimately lead to the failure of innovation [13].

To bridge the identified gap, this study presents findings from empirical research focused explicitly on UAE government entities providing direct public services. Expanding on the investigation of Abuzanjal and Bashir [14], this research explores the interrelationships between challenges encountered by the public sector and is designed to achieve the following key objectives:

• To analyze and visualize the interrelationships between challenges impacting innovation in public services by UAE government entities to understand better how these challenges influence each other.
• To provide decision-makers with a tool to swiftly distinguish the most critical challenges and the root causes of innovation ineffectiveness.
• To recommend actionable strategies for tackling the most critical challenges identified through the analysis.

This study’s findings are expected to be of significant value for UAE government entities and other nations with comparable socioeconomic and cultural settings. The valuable insights from this research can enlighten decision-makers and enhance resource allocation and strategic planning, which will result in fostering innovation and driving transformative progress in services.

This article is structured as follows: Section 2 explores key theories that underpin the study, Section 3 reviews the relevant literature, Section 4 details the methodology and describes the approach adopted, and Section 5 provides a thorough discussion of findings. Lastly, Section 6 concludes with insights and highlights potential directions for future research opportunities. This article presents “barriers” and “challenges” interchangeably. While they may have distinct meanings in language, they are treated as synonymous in this context, as the prior literature explains [14].

2. Theoretical Framework

Schumpeter’s foundational work positioned technological advancements as catalysts of competitive advantage and economic growth, paving the path for innovation theory [15]. This aligns with open innovation principles emphasizing leveraging diverse knowledge sources for optimal outcomes [16]. Over time, innovation theories have evolved to address innovation processes’ dynamic, nonlinear, and interdependent nature. Public administration and management have gained prominence in innovation research, with scholars emphasizing the magnitude of the complexity of management in Public Sector Innovation (PSI) [17,18]. Thus, the complexity theory frames innovation as an emergent property of interconnected systems shaped by organizational structure, culture, and external factors [19,20].

Knowledge management is pivotal to generating innovation, with the concept of knowledge as “justified true belief” serving as the foundation for an organization’s ability to create and implement new ideas. This definition highlights the importance of reliable and well-supported information that can effectively inform decision-making and drive innovation. In an organizational context, it highlights the importance of ensuring that knowledge-driven innovation and strategic decisions are both credible and actionable. Complexity theory further reinforces this by emphasizing the need for dynamic knowledge flows, as rigid structures and siloed thinking impede adaptability in complex systems. Effective knowledge management involves systematic processes for acquiring, interpreting, and utilizing knowledge, which not only foster innovation but also serve as a core strategic resource for driving creativity and achieving a competitive advantage [21]. Within this context, the Knowledge-Based View (KBV), along with the Resource-Based View (RBV), frames knowledge as “Valuable, Inimitable, Rare, and supported by Organizational Capabilities (VIRO)” [22,23,24,25]. Complexity theory also reinforces these ideas, emphasizing the interdependencies and emergent behaviors within dynamic environments.

Challenges such as resistance to change, motivational deficits, and insufficient training often hinder innovation within the public sector. Addressing these challenges necessitates a complexity-informed approach that balances structured processes with adaptability [21]. Key practices include fostering open communication, reducing knowledge hiding, and establishing feedback loops, which are essential to address challenges dynamically. Employees feel empowered when they have access to resources and opportunities for continuous learning that enhance engagement, creativity, and adaptability, which are crucial for managing complex innovation systems [26].

Open innovation complements these strategies by integrating internal and external knowledge sources [16] and addressing challenges like siloed thinking and resistance to change. Complexity theory supports open innovation’s iterative processes and diverse perspectives, enabling organizations to adapt to changing environments [27]. The framework proposed by Abdulkader et al. [28] combines open innovation with business process management, emphasizing value co-creation and aligning strategic and operational priorities. Complexity theory enhances this framework by stressing the role of adaptive processes, dynamic networks, and feedback mechanisms.

Integrating RBV, KBV, open innovation, and complexity theory provides a comprehensive and robust framework for navigating PSI challenges to achieve resilience and competitive advantages in increasingly complex, dynamic ecosystems, ensuring their processes remain effective and responsive to change.

3. Literature Review

3.1. Innovation in the Public Sector

A crucial function of the public sector is fostering innovation to create societal stability through service offerings that will strengthen the connection between citizens and the government, thereby reducing conflicts between them [29]. This enhances service quality, economic competitiveness, transparency, accountability, and social well-being [30,31]. PSI is defined as “the creation and implementation of new processes, products, services, and methods of delivery that result in significant improvements in outcomes, efficiency, effectiveness, or quality” [32]. As highlighted by Wipulanusat et al. [33], PSI enhances the outcomes by developing and executing innovative procedures, products, services, and strategies central to government operations. The primary goal is transforming public sector operations, enabling governmental bodies to meet, anticipate, and address society’s changing needs. Raipa and Giedraityte [34] emphasize the essential role of innovation in modernizing public sector service delivery, making innovation not merely a strategic option but a critical necessity. Wipulanusat et al. [33] further demonstrate that PSI strengthens the connection between the government and the community, making it a crucial element for building a more agile, efficient, and interconnected government. Hence, this sector creates value in multiple facets, including improving service quality, enhancing social welfare, and optimizing public sector management [35].

Regardless of its substantial significance and public value creation [36,37], the public sector’s challenges in sustaining or enhancing service delivery are due to limitations in capability [38,39,40,41]. These challenges have prompted a strong emphasis on innovation in public sector entities [42,43,44,45].

Therefore, within the scope of this study, government entities have to recognize the importance of innovating and enhancing their services to manage the dynamic nature of public demand through better resource management and provide distinctive, tailored services that are continuously improved without compromising value creation [32,46,47]. Moreover, citizens expect governments to be more responsive, uphold transparency, and address their needs swiftly, particularly in essential sectors such as healthcare and education [48]. Thus, embedding innovation practices as a core principle within the government’s framework and culture can enhance their capabilities and management systems, which leads to more effective and sustainable service delivery [49,50].

3.2. Public Sector Innovation Within the UAE

The aspiration of the UAE to become a global hub for innovation and service development is outlined in the Centennial Plan 2071; leaders are closely aligned and committed to the envisioned goals and strategies across the economic, tourism, and commercial sectors [51]. The UAE has focused on transitioning toward a knowledge-driven economy, strategically enhancing innovation capabilities among individuals and organizations. The 2014 National Innovation Strategy has laid a robust foundation for improving the country’s global innovation rankings through integrating innovation into government practices, establishing supportive legal and institutional frameworks, supporting private sector research and development (R&D), and modernizing educational systems to nurture innovation skills [52].

The introduction of Centennial Plan 2071 marks the nation’s centenary with a forward-thinking strategy to sustain its innovation trajectory. This ambitious plan emphasizes transforming government services to create a future independent of oil, fostering leadership skilled in navigating future challenges, shifting the economy to a knowledge-driven model, and strengthening the nation’s unity to underpin sustainable development [53]. It reinforces the UAE’s commitment to advancing service innovation, focusing on the public and private sectors. The plan prioritizes developing and delivering high-quality, competitive, knowledge-based services to enhance the UAE’s global standing and economic resilience. Through this comprehensive approach, the UAE continues to align its innovation goals with its long-term vision for international competitiveness and sustainable progress.

More recently, in 2023, the UAE’s government has consistently prioritized innovation and efficiency within its public sector, as exemplified by the Zero Government Bureaucracy programs. This initiative eliminates unnecessary administrative burdens while fostering streamlined, citizen-centric operations. The program seeks to enhance service delivery, reduce response times, and ensure seamless collaboration among government entities by adopting advanced technologies such as AI and blockchain. These initiatives align closely with the UAE’s vision of establishing a future-ready, agile government framework [54].

3.3. Challenges in the Public Sector

Efforts to innovate often encounter challenges that can impede their success; therefore, recognizing these challenges is essential for developing effective strategies to mitigate their impact. In a recent study by Abuzanjal and Bashir [14], these challenges were highlighted. Building on this earlier work, an updated version of the synthesized list of challenges is presented in

Table 1. Challenges to service innovation within public organizations as documented in the literature.

		Prior Studies Targeted Population/Year of Study
		[42] Public sector institutions, Nordic countries/2013	[55] Public services organizations, UK/2013	[56] Public sector e-procurement, Portugal/2013	[57] Municipalities, USA/2013	[58] Public sector organizations, Kenya/2014	[59] Municipality, The Netherlands/2014	[60] Public sector (healthcare), The Netherlands/2014	[61] Central government—Scottish Parliament, Scotland/2014	[62] Public services (education), Italy/2014	[63] Healthcare and education, England/2014	[34] Public sector in Lithuania and European Union/2014	[64] Public sector (justice), USA/2014	[65] Public sector organizations (healthcare), Norway/2014	[66] European parliament/2014	[67] Government organizations, The Netherlands/2015	[68] Public services in municipalities, Finland/2015	[69] Local government, Denmark/2015	[70] Water management, The Netherlands/2015	[71] Municipality, Denmark/2015	[72] Public sector organizations, Kenya/2016	[73] Government/municipalities, Greece/2016	[74] Public sector innovation, USA and UK/2016	[75] Government of Dubai, UAE/2019	[76] Public sector in Italy, Japan, and Turkey/2021	[77] Public institution, Poland/2021	[78] Public sector, Denmark/2021	[79] Public sector (justice), Iran/2023	[27] Organization units—Central Bureau of Statistics, Indonesia/2023	[14] Government entities, UAE/2024	[80] Public sector innovation, Switzerland/2024
No	Challenge
1	“Administrative burdens”					✓						✓	✓								✓				✓			✓	✓
2	“Bureaucratic culture”					✓									✓						✓				✓	✓		✓		✓
3	“Communication issues”																							✓		✓		✓		✓	✓
4	“Complexity challenges”			✓					✓					✓									✓		✓			✓
5	“Environmental challenges”					✓								✓									✓
6	“Geographical challenges”													✓
7	“Government policy issues”					✓															✓	✓
8	“Inadequate public involvement”															✓		✓
9	“Inadequate resources”					✓						✓		✓		✓					✓		✓		✓		✓				✓
10	“Incompatibility issues”													✓					✓				✓		✓
11	“Individual/employees level challenges”											✓									✓		✓	✓		✓		✓
12	“Issues related to businesses”	✓				✓										✓	✓		✓		✓	✓			✓
13	“Issues related to NGOs”																								✓
14	“Issues related to political entities”					✓										✓							✓			✓		✓
15	“Lack of accountability”										✓			✓																	✓
16	“Lack of commitment”							✓											✓			✓								✓	✓
17	“Lack of cooperation”	✓												✓
18	“Lack of funding”				✓			✓						✓														✓
19	“Lack of human resources”											✓									✓
20	“Lack of incentives and rewards”					✓						✓		✓							✓			✓						✓
21	“Lack of innovation support”													✓									✓	✓	✓
22	“Lack of interoperability”			✓
23	“Lack of knowledge”					✓															✓			✓		✓		✓		✓
24	“Lack of motivation/empowerment”																									✓				✓
25	“Lack of mutual benefits”				✓
26	“Lack of shared understanding”						✓	✓																						✓
27	“Lack of skills/unqualified employees”					✓								✓							✓					✓				✓
28	“Lack of standardization”																								✓
29	“Lack of technological compatibility/information”													✓		✓					✓							✓	✓	✓
30	“Lack of top management support”											✓									✓			✓						✓
31	“Lack of trust”									✓
32	“Laws and regulations challenges”											✓		✓	✓		✓				✓		✓		✓			✓		✓	✓
33	“Leadership issues”													✓									✓			✓					✓
34	“Legal barriers to innovation”														✓										✓			✓	✓	✓	✓
35	“There are no good practices to follow.”																									✓
36	“Organizational issues”			✓										✓	✓									✓	✓	✓		✓	✓
37	“Platform/software problems”			✓					✓																✓			✓
38	“Problems with training”			✓										✓																✓
39	“User’s resistance”						✓					✓		✓						✓								✓
40	“Resistance to change”			✓					✓			✓		✓				✓						✓	✓	✓		✓		✓
41	“Risk avoidance/aversion”		✓			✓	✓					✓		✓							✓		✓	✓				✓		✓	✓
42	“Short-term budgets”					✓								✓														✓
43	“Short-term focus on results”					✓								✓
44	“Structural issues/rigidity”																						✓					✓		✓
45	“Cost issues and longer payback”																						✓
46	“Policy issues/lack of intellectual property policy”																											✓		✓
47	“Financial challenges”																											✓
48	“Lack of transparency and data-sharing”																											✓
49	“Partial and short-sighted mindset”																											✓
50	“Absence of innovation strategy/strategy management”																													✓	✓
51	“Lack of time to innovate”																													✓
52	“Rigid rules and processes”																													✓
53	“Absence of customer-centric mindset”																													✓
54	“Service-oriented-thinking gap”																													✓
55	“Overlapping department functions”																													✓
56	“Unclear value proposition”																													✓
57	“Lack of integration between shared service entities”																													✓
58	“Absence of innovation process”																													✓

, incorporating new findings from the literature. The original study synthesized findings from 26 studies covering the period from 2013 to 2021, resulting in a comprehensive list of 45 challenges spanning behavioral, cultural, resource-related, structural, external, and systemic dimensions. The updated version includes findings from four additional studies, adding 13 new challenges to the original list. These studies were incorporated between 2023 and 2024 to provide a more current perspective on the challenges.

An analysis of these 30 studies reveals that only the studies by Abuzanjal and Bashir [14], Caloghirou et al. [73], Ezzamel et al. [61], Meijer [67], Moonesar et al. [75], and Plotnikof [69] focus exclusively on government entities. The first three studies focus on the European public sector and provide insights into the distinct innovation challenges and pathways within the region’s public sector framework. From a comparative perspective, Moonesar et al. [75] have shifted the focus toward the Middle Eastern context, particularly exploring Dubai’s government, aiming to explore how creativity and innovation are understood and perceived and to identify the key challenges that impede innovation within the government sector. The study utilized a survey-based method to examine employees’ perspectives across different entities in the Dubai government; it identified bureaucratic culture as a significant obstacle and found notable communication gaps in how employees understand innovation and creativity.

Additionally, it revealed the disconnection between the governmental entities’ structural framework and the innovation process’s dynamic nature. Regarding top management support, Moonesar et al. [75] showed that employees’ innovative ideas often lacked the necessary support from top management. However, the two main gaps considered in the study by Moonesar et al. [75] include the exclusion of the comprehensive insights of managers, experts, and policymakers into innovation, and the focus on Dubai only, reducing relevance to the broader UAE context. Also, the findings may not truly represent the present situation, considering that over four years have passed since the data was collected. This time gap suggests that the identified challenges may have been addressed, or new ones may have arisen since then.

A recent empirical study by Abuzanjal and Bashir [14] offers further insights into these challenges by identifying and ranking them and examining how they are influenced by adopting the Government Excellence Model (GEM) and by organization size within the UAE government. Using expert consultations and questionnaires, which yielded 28 valid responses out of 37 UAE government entities that deliver services to customers and the general public, the study identified 22 challenges, categorizing them and highlighting 10 as critical, with half linked to innovation culture. The findings revealed that the organization’s size does not significantly affect these challenges, whereas entities adopting GEM perceive six challenges as less critical.

By examining Table 1, it is noticeable that the most reported challenges in these studies were risk avoidance/aversion, resistance to change, law and regulation challenges, and inadequate resources. These challenges represent cultural and organizational issues that impede creativity and innovation. They must receive the most attention from decision-makers to mitigate their effect and understand the relationship between them to reduce their cascading effect, ultimately fostering innovation. Another observation is all the studies summarized—excluding [27,58]—have not examined the interconnectedness of challenges. According to Saatçioğlu and Özmen [81], challenges are often interrelated, with one challenge potentially emerging as a symptom of another. This interconnectedness suggests that challenges can influence one another, either directly or indirectly, and may ultimately cause the innovation process to fail [13]. When one challenge arises due to another, it can trigger a chain reaction, amplifying existing problems or introducing new ones. This cascading effect increases the complexity and difficulty of managing the innovation process. Therefore, examining the interconnectedness of challenges is crucial. Understanding how these challenges are interrelated and identifying pivotal challenges—those whose resolution can mitigate multiple others—enables government entities to develop effective strategies that address the root causes of interconnected challenges. However, none of the previous studies have explored this issue.

4. Methodological Approach

To achieve this study’s objectives and close the aforementioned gaps in the literature, five key steps were undertaken: Step 1: identification of challenges; Step 2: correlation analysis of challenges; Step 3: network centrality analysis; Step 4: visualization of relationships; and Step 5: classification of challenges. Steps 2 and 3 were conducted using social network analysis (SNA).

Originally, SNA was introduced in the literature as a statistical and graphical tool to examine relationships between social entities [82]. However, SNA has recently seen growing applications across various fields as a method for modeling relationships between non-human entities, as presented in research like that of Bashir et al. [83], Mok et al. [84], Pryke et al. [85], and Zaabi and Bashir [86]. A significant feature of SNA is its ability to illustrate the relationships among entities—such as individuals, organizations, components, or barriers—by creating a network of nodes interconnected by directed or undirected linkages. Beyond visualizing these connections, SNA also facilitates the structural analysis of the network using various metrics at both the links and nodes levels.

This study utilized SNA as its analytical method due to its ability to effectively examine the interrelationships and patterns—both direct and indirect—among the challenges within a network [87]. Furthermore, SNA can be implemented using correlation coefficients, a feature not applicable to other comparable methods such as Interpretive Structural Modeling [88], Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) [89], and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) [90].

4.1. Identification of Challenges

As indicated earlier, this study built upon the investigation by Abuzanjal and Bashir [14], which examined the challenges of public service innovation in UAE government entities and identified 22 challenges, as presented in

Table 2. Identified challenges in UAE government entities.

Code	Challenges
C1	“Rigid budgeting process”
C2	“Lack of qualified employees”
C3	“Lack of training and knowledge about service innovation”
C4	“Lack of information about technology to innovate in services”
C5	“Lack of time dedicated to service innovation”
C6	“Rigid and formal organization structure”
C7	“Rigid rules and processes within the government entity”
C8	“A culture of resistance to change among employees”
C9	“Lack of commitment and support from top management”
C10	“Managers’ tendencies to avoid risk”
C11	“Lack of motivation and empowerment for employees”
C12	“Lack of incentives and rewards”
C13	“An absence of a customer-centric mindset to gauge and meet current and future needs”
C14	“The service-oriented-thinking gap between managers and employees”
C15	“Overlapping functions between departments”
C16	“Absence of innovation strategy”
C17	“Unclear value proposition for the new or improved service”
C18	“Lack of coordination and poor internal communication between government entity departments”
C19	“A gap in marketing internally for new or improved services”
C20	“Lack of integration between government entities for the shared services”
C21	“Absence of clear and formalized innovation process”
C22	“Regulations and legislation that limit service innovation”

. These challenges were identified through an extensive literature review and a survey conducted among government entities providing customer services. The profile of the surveyed entities and other relevant survey data can be found in Abuzanjal and Bashir [14]. To maintain consistency with the original survey instrument and ensure the accuracy of respondent interpretation, the challenge names are presented exactly as they were used in the survey. The survey utilized a Likert scale ranging from 1 to 5, where “1” represents “Strongly Disagree”, “2” represents “Disagree”, “3” represents “Neither Agree nor Disagree”, “4” represents “Agree”, and “5” represents “Strongly Agree”, to assess the level of agreement regarding the encountered challenges. The data obtained from this survey served as the input for the subsequent steps of this study.

4.2. Correlation Analysis of Challenges

This step measured the strength of the relationships between the challenges using correlation coefficients. Spearman’s correlation coefficient was selected to achieve this purpose, as it is a nonparametric method suitable for analyzing data collected through the survey on a Likert scale [91]. Only the significant correlations (those at p-value < 0.05) were retained for further analysis [92]. This process produced the correlation coefficient matrix presented in

Table 3. Challenges’ correlation coefficient matrix.

	C1	C2	C3	C4	C5	C6	C7	C8	C9	C10	C11	C12	C13	C14	C15	C16	C17	C18	C19	C20	C21	C22
C1	1	0.418	0.349	0	0	0	0.553	0.388	0	0	0.435	0.546	0	0	0.561	0.382	0.358	0.352	0.393	0	0.495	0
C2	0.418	1	0.528	0.609	0.452	0	0.483	0.399	0.367	0	0.450	0	0.527	0.640	0.431	0.464	0.479	0.557	0	0	0.627	0
C3	0.349	0.528	1	0.602	0.633	0.579	0.736	0.472	0.541	0.526	0.402	0	0.386	0.545	0.603	0.533	0.513	0.447	0	0	0.670	0
C4	0	0.609	0.602	1	0.514	0.458	0.526	0.513	0.445	0.591	0.460	0	0.465	0.712	0.589	0	0.621	0.579	0.517	0.432	0.525	0.414
C5	0	0.452	0.633	0.514	1	0.517	0.515	0.509	0	0.442	0.528	0.483	0.512	0.551	0	0.396	0.528	0.503	0	0	0.655	0.611
C6	0	0	0.579	0.458	0.517	1	0.659	0.537	0.449	0	0	0	0	0.444	0.418	0	0	0.347	0	0.417	0	0
C7	0.553	0.483	0.736	0.526	0.515	0.659	1	0.592	0.575	0.492	0.439	0	0.386	0.631	0.556	0.442	0.325	0.511	0	0	0.595	0
C8	0.388	0.399	0.472	0.513	0.509	0.537	0.592	1	0.557	0.492	0.524	0.345	0	0.530	0	0.381	0.575	0.374	0.504	0.568	0.344	0.350
C9	0	0.367	0.541	0.445	0	0.449	0.575	0.557	1	0.535	0	0	0.372	0.478	0.439	0	0	0	0	0	0	0
C10	0	0	0.526	0.591	0.442	0	0.492	0.492	0.535	1	0.458	0	0.375	0.477	0.362	0	0.433	0.502	0	0	0.482	0
C11	0.435	0.450	0.402	0.460	0.528	0	0.439	0.524	0	0.458	1	0.722	0.491	0.469	0.473	0.540	0.683	0.540	0.564	0.556	0.627	0.467
C12	0.546	0	0	0	0.483	0	0	0.345	0	0	0.722	1	0.375	0	0.351	0.476	0.541	0	0	0.402	0.447	0
C13	0	0.527	0.386	0.465	0.512	0	0.386	0	0.372	0.375	0.491	0.375	1	0.647	0.436	0.347	0	0.484	0.165	0	0.605	0
C14	0	0.640	0.545	0.712	0.551	0.444	0.631	0.530	0.478	0.477	0.469	0	0.647	1	0.640	0.524	0.430	0.738	0.400	0.385	0.607	0.398
C15	0.561	0.431	0.603	0.589	0	0.418	0.556	0	0.439	0.362	0.473	0.351	0.436	0.640	1	0.516	0.471	0.595	0.449	0.417	0.564	0
C16	0.382	0.464	0.533	0.340	0.396	0	0.442	0.381	0	0	0.540	0.476	0.347	0.524	0.516	1	0.620	0.597	0.362	0	0.675	0.420
C17	0.358	0.479	0.513	0.621	0.528	0	0	0.575	0	0.433	0.683	0.541	0	0.430	0.471	0.620	1	0.534	0.451	0.593	0.581	0.590
C18	0.352	0.557	0.447	0.579	0.503	0.347	0.511	0.374	0	0.502	0.540	0	0.484	0.738	0.595	0.597	0.534	1	0.543	0.461	0.739	0.493
C19	0.393	0	0	0.517	0	0	0	0.504	0	0	0.564	0	0	0.400	0.449	0.362	0.451	0.543	1	0.622	0.366	0.608
C20	0	0	0	0.432	0	0.417	0	0.568	0	0	0.556	0.402	0	0.385	0.417	0	0.593	0.461	0.622	1	0	0.400
C21	0.495	0.627	0.670	0.525	0.655	0	0.595	0.344	0	0.482	0.627	0.447	0.605	0.607	0.564	0.675	0.581	0.739	0.366	0.244	1	0.502
C22	0	0	0	0.414	0.611	0	0	0.350	0	0	0.467	0	0	0.398	0	0.420	0.590	0.493	0.608	0.400	0.502	1

. One general observation regarding the correlation coefficients shown in this table is that all of them are positive. This pattern indicates that these challenges are interrelated and may create a compounding effect, where the presence or severity of one challenge tends to amplify the occurrence or impact of others. Such interdependencies highlight the systemic nature of the challenges within the studied context.

4.3. Network Centrality Analysis

In this step, the diagonals of the correlation matrix given in Table 3 were replaced with 0 s, and this matrix was then used as the input to the network centrality to identify and evaluate the relative significance of challenges within the network, providing a deeper understanding of their structural importance and interconnectivity. Two of the most common metrics for assessing the significance of nodes in a network that were used were betweenness centrality and eigenvector centrality [93,94]. These measures offer distinct but complementary perspectives on node importance. Betweenness centrality measures the degree to which a node acts as a bridge positioned along the shortest paths between other nodes in a network, highlighting nodes that act as bridges or intermediaries. Such nodes are critical for controlling and influencing communication or resource flow within the network. Eigenvector centrality provides a more detailed view of centrality by taking into account not just the quantity of a node’s connections but also the quality of those connections. A node with fewer direct links can still achieve high eigenvector centrality if its connections are to other highly influential nodes. The formulas for computing these two metrics are defined in Equations (1) and (2).

Using these two formulas, the computed betweenness centrality and eigenvector centrality values for the 22 challenges are presented in Table 4. These metrics collectively capture the different dimensions of a node’s importance, enabling a comprehensive understanding of its role within the network.

$${BC}_{\left(n_k\right)}=\sum _{i<j}{\displaystyle \frac{g_{ij}\left(n_k\right)}{g_{ij}}}$$

(1)

where ${BC}_{\left(n_k\right)}$ is the betweenness centrality of node $n_k$, $g_{ij}$ is the number of shortest paths connecting node $n_i$ and node $n_j$, and $g_{ij}\left(n_k\right)$ = the number of shortest paths connecting node $n_i$ and node $n_j$ passing through node $n_k$.

$$X_i={\displaystyle \frac{1}{\lambda }}\sum _j{A}_{ij}{X}_j$$

(2)

$X_i$ is the eigenvector centrality of a node $i$, λ is a constant representing the largest eigenvalue in the adjacency matrix $A$, $A_{ij}$ is the adjacency matrix indicating the connection between nodes $i$, and $j, X_j$ is the eigenvector centrality of the neighboring node $j$.

Table 4. Betweenness and eigenvector centrality values for challenges.

Challenges	Betweenness Centrality	Eigenvector Centrality
C1	0.004171	0.145685
C2	0.007325	0.215564
C3	0.013472	0.248666
C4	0.023597	0.260626
C5	0.014524	0.228622
C6	0.004112	0.135462
C7	0.013472	0.239897
C8	0.032888	0.228611
C9	0.002640	0.130718
C10	0.003959	0.181190
C11	0.020128	0.257091
C12	0.004352	0.126861
C13	0.012937	0.185349
C14	0.023597	0.275147
C15	0.027013	0.234005
C16	0.012617	0.218545
C17	0.017781	0.244437
C18	0.021492	0.267401
C19	0.005730	0.161052
C20	0.007918	0.143626
C21	0.020128	0.277100
C22	0.001385	0.151082

Note: Gray shading indicates challenges with the highest betweenness and eigenvector centrality values.

Table 4. Betweenness and eigenvector centrality values for challenges.

Challenges	Betweenness Centrality	Eigenvector Centrality
C1	0.004171	0.145685
C2	0.007325	0.215564
C3	0.013472	0.248666
C4	0.023597	0.260626
C5	0.014524	0.228622
C6	0.004112	0.135462
C7	0.013472	0.239897
C8	0.032888	0.228611
C9	0.002640	0.130718
C10	0.003959	0.181190
C11	0.020128	0.257091
C12	0.004352	0.126861
C13	0.012937	0.185349
C14	0.023597	0.275147
C15	0.027013	0.234005
C16	0.012617	0.218545
C17	0.017781	0.244437
C18	0.021492	0.267401
C19	0.005730	0.161052
C20	0.007918	0.143626
C21	0.020128	0.277100
C22	0.001385	0.151082

Note: Gray shading indicates challenges with the highest betweenness and eigenvector centrality values.

4.4. Visualization of Relationships

This step involves visualizing the relationships among the challenges by constructing networks with nodes and directed edge links. Each node represents a challenge, while a link connecting two nodes illustrates a meaningful relationship between those challenges. Consequently, two networks were established for this purpose, as shown in Figure 1 and Figure 2. In Figure 1, the size of the nodes represents the betweenness centrality values, highlighting the nodes’ roles as bridges within the network. In Figure 2, the node size represents the eigenvector centrality values, emphasizing their influence based on connections to other highly connected nodes. In both figures, larger node sizes and darker color shading indicate higher centrality values, as detailed in Table 4.

4.5. Classification of Challenges

In this step, the challenges are represented in a four-quadrant diagram based on their betweenness centrality and eigenvector centrality values, as shown in Figure 3. This concept is derived from the MICMAC analysis by Duperrin and Godet [89] to determine the influence of challenges. The upper-right quadrant contains critical challenges characterized by high betweenness centrality and high eigenvector centrality values. These challenges are highly influential and central, and they act as bridges to several other important ones in the network. The upper-left quadrant contains localized influence challenges, defined by high eigenvector centrality and low betweenness centrality values. They are influential within their immediate surrounding challenges in the network, but they do not act as bridges to others. The lower-right quadrant contains connector challenges, identified by low eigenvector centrality and high betweenness centrality values. These act as a bridge linking other disconnected challenges in the network, but they are not closely connected to other influential challenges. The lower-left quadrant contains low-connectivity challenges, marked by low eigenvector centrality and low betweenness centrality values. These are less central and less connected to influential challenges, so they have limited influence in the network.

5. Discussion

5.1. Bridging Challenges in the Network

In the network graph shown in Figure 1, challenges with larger nodes represent the betweenness centrality, such as C8 “a culture of resistance to change among employees”, C15 “overlapping functions between departments”, C4 “lack of information about technology to innovate in services”, C14 “the service-oriented-thinking gap between managers and employees”, and C18 “lack of coordination and poor internal communication”, which act as crucial bridges connecting specific clusters of related challenges within the government entity as outlined below, with C8 holding the highest betweenness centrality value, which indicates that this challenge amplifies other challenges in the network:

• C8 bridges between C11, C18, and C21: “Resistance to change among employees” (C8) reinforces demotivation (C11) as employees feel disengaged from or resistant to new initiatives. This resistance also intensifies coordination problems (C18), as employees may resist collaborating effectively. Furthermore, resistance hinders the adoption of structured innovation processes (C21), making formalizing efforts to drive innovation difficult.
• C15 bridges between C18, C7, and C20: “Overlapping functions between departments” (C15) often lead to poor internal coordination and communication (C18) as employees struggle to navigate unclear roles and responsibilities. This overlap is compounded by rigid rules and processes (C7), which prevent departments from adopting flexible approaches to collaboration. The lack of integration between government entities (C20) further intensifies this issue, as interdepartmental inefficiencies spill over into external collaborations. Together, these challenges create a cycle of disorganization and inefficiency that significantly hinders innovation.
• C4 bridges between C3, C12, and C20: The “lack of information about technology to innovate in services” (C4) acts as a bottleneck that impacts employees’ ability to apply knowledge gained from training (C3). Even well-trained employees may find themselves ill-equipped to innovate effectively without adequate technological information. Additionally, this lack of information weakens employees’ incentives and rewards (C12), as their inability to utilize new technologies diminishes motivation and recognition for innovation. Furthermore, “poor integration between government entities for shared services” (C20) exacerbates this challenge, as fragmented systems fail to provide the technological insights or shared resources necessary for driving service innovation.
• C14 bridges between C9, C8, and C13: The “service-oriented-thinking gap between managers and employees” (C14) creates misalignment in innovation efforts, notably when top management lacks commitment and support (C9). This gap reinforces “a culture of resistance to change” (C8), as employees perceive a misalignment between managerial expectations and practical realities. Additionally, “the absence of a customer-centric mindset” (C13) further widens this gap, as neither managers nor employees are aligned on addressing the needs of current and future customers. This misalignment undermines innovation efforts, creating systemic inefficiencies and limiting the government entity’s ability to adapt to evolving service demands.
• C18 bridges between C15, C8, and C21: Coordination and communication issues (C18) often arise from overlapping departmental functions (C15), where unclear roles and responsibilities create inefficiencies. Poor coordination also deepens cultural resistance (C8), as employees struggle to align with unclear communication processes. Additionally, without addressing C18, efforts to implement formalized innovation processes (C21) often fail, as coordination is crucial for systemic alignment and execution.

5.2. Highly Interconnected Challenges

The network graph in Figure 2 highlights the relationships among 22 public service innovation challenges, with node size indicating eigenvector centrality. The largest node, representing C21 “absence of clear and formalized innovation process”, signifies its critical role within the network due to its high eigenvector centrality. This demonstrates that C21 is strongly linked to other highly influential challenges, emphasizing its central connectivity and cascading impact on the overall structure of the challenges network. Other prominent nodes, such as C14 “the service-oriented-thinking gap between managers and employees”, C18 “lack of coordination and poor internal communication between government entity departments”, C4 “lack of information about technology to innovate in services”, and C11 “lack of motivation and empowerment for employees” further highlight challenges that are deeply interconnected and play significant roles in the network.

For instance, C11, representing employees’ disempowerment, likely contributes to poor communication and a lack of motivation, amplifying coordination problems throughout the government entity (C18). Similarly, the relationship between C11 and C14 demonstrates how the gap between managers and employees in terms of a shared mindset and goals can demotivate employees, reducing their empowerment to contribute to innovation efforts. Other highly interconnected challenges linked to C11 include C17 “unclear value proposition for the new or improved services” and C3 “lack of training and knowledge about service innovation”; inadequate training and knowledge regarding innovation and the underlying value proposition can lead to unqualified and demotivated employees, which reduces their engagement and contributions to the innovation process and efforts.

5.3. Classifying Challenges

Figure 3 categorizes the challenges into four distinct groups: critical challenges, connector challenges, localized influence challenges, and low-connectivity challenges. Each group reflects a different significance level of criticality and influence on the overall network.

Critical challenges demand immediate attention and priority in resolution, as they significantly affect the government entity’s service innovation. In contrast, low-connectivity challenges are the least critical, exerting minimal influence and requiring the least priority. Thus, they can be addressed later when resources permit. This prioritization ensures a structured and efficient approach to tackling challenges, focusing first on those with the most significant potential to disrupt innovation.

5.3.1. Critical Challenges

These challenges are strongly connected to key stakeholders or influential processes (high eigenvector centrality) and act as critical intermediaries or connectors between different departments or initiatives (high betweenness centrality). They include “lack of information about technology to innovate in services” (C4), “a culture of resistance to change among employees” (C8), “lack of motivation and empowerment for employees” (C11), “the service-oriented-thinking gap between managers and employees” (C14), “overlapping functions between departments” (C15), “unclear value proposition for the new or improved service” (C17), “lack of coordination and poor internal communication between government entity departments” (C18), and “absence of a clear and formalized innovation process” (C21).

5.3.2. Connector Challenges

Connector challenges are not directly connected to influential innovation drivers but play an essential role in bridging gaps between different processes. However, none of the challenges in this study fall into this category.

5.3.3. Localized Influence Challenges

Challenges with limited roles in bridging or connecting different departments, processes, or clusters within the larger organizational network consist of relationships, interactions, and dependencies among various departments, teams, stakeholders, and processes within a government entity. They are not central to the overall flow of communication, collaboration, or innovation across the government entity. They include “lack of qualified employees” (C2), “lack of training and knowledge about service innovation” (C3), “lack of time dedicated to service innovation” (C5), “rigid rules and processes within the organization” (C7), “managers’ tendencies to avoid risk” (C10), “an absence of a customer-centric mindset to gauge and meet current and future needs” (C13), “absence of innovation strategy” (C16), and “a gap in marketing internally for new or improved services” (C19).

5.3.4. Low-Connectivity Challenges

These have limited influence and connectivity within the organizational network. Their resolution may not have a cascading impact on other innovation challenges. They include “rigid budgeting processes” (C1), “rigid and formal organization structure” (C6), “lack of commitment and support from top management” (C9), “lack of incentives and rewards” (C12), “lack of integration between government entities for shared services” (C20), and “regulations and legislations that limit service innovation” (C22).

5.4. Prioritizing Challenges: Survey Results vs. Network Analysis

We aimed to better understand the key challenges and how they were prioritized according to two different analysis perspectives: survey results and SNA. Figure 4 illustrates the ranking of challenges based on survey results conducted by Abuzanjal and Bashir [14], which employed a Likert scale to gauge participants’ precautions. The percentages reflect the proportion of respondents who rated each challenge as important, based on the combined selection of “Strongly Agree” and “Agree”. In contrast, our study identified the most critical challenges using eigenvector and betweenness centrality measures derived from the correlation coefficients between challenges. While the survey highlights participants’ perceived priorities, our network analysis offers a complementary perspective by revealing the structural significance and interdependencies among the challenges. Together, these methods offer a deeper insight into the factors shaping innovation-related challenges. These two approaches provide differing perspectives on the importance of challenges, with the survey results emphasizing perceived priorities and the network analysis uncovering structural influence and interdependencies.

The survey is particularly useful for identifying and ranking challenges. It provides a clear understanding of the most immediately visible or pressing challenges for respondents. For example, C10, “Managers’ tendencies to avoid risk”, was ranked with the highest percentage in the survey at 82%, reflecting its strong perception as a challenge. Similarly, C20 “Lack of integration between government entities for shared services” ranked second at 79%, indicating its perceived importance for collaboration. However, despite their high survey rankings, these challenges were not identified as critical in our network analysis. This is because challenges such as C10 and C20 have lower structural influence, as they are not strongly interconnected with other challenges nor pivotal for driving innovation across the government entity.

Conversely, the network analysis provides a more appropriate method for ranking challenges that should be tackled first to address interconnected issues and systemic challenges. Some challenges identified as critical in the network analysis were ranked lower in the survey. For instance, C18, ranked at 71% in the survey, was critical in the network due to its high centrality measures, indicating its pivotal role as a structural connector. Improving coordination and communication fosters better collaboration across departments, which helps address related challenges like unclear processes and resistance to change.

Similarly, C21, ranked at 68% in the survey, emerges as critical in the network because it establishes a framework that aligns innovation efforts and provides a structure for addressing other challenges. Formalizing processes can reduce confusion, improve accountability, and create a foundation for implementing new initiatives.

Challenges such as C15 and C17, ranked at 61% and 68%, respectively, in the survey, are identified as critical in the network due to their centrality and the impact they have on organizational effectiveness. Resolving overlapping departmental functions (C15) helps clarify roles and responsibilities, which minimizes redundancies and fosters more efficient workflows. Meanwhile, defining a clear value proposition (C17) ensures alignment in objectives across teams, improving focus and coherence in innovation efforts.

Some challenges are recognized as important in both approaches. For example, C8 “a culture of resistance to change”, ranked at 79% in the survey, aligns with its critical role in the network, where it impacts other key challenges such as C11 “lack of motivation and empowerment”, C18 “coordination issues”, and C21 “innovation process absence”. Similarly, C11 “lack of motivation and empowerment”, ranked at 75% in the survey, is identified as critical in the network for its role in connecting cultural and operational challenges.

This comparison highlights the complementary nature of these two approaches. The survey provides valuable insights into the challenges perceived as most pressing by stakeholders, making it helpful in identifying and ranking challenges based on their immediate visibility and impact. However, our network-based approach is more appropriate for determining which challenges should be prioritized for action. By focusing on central and interconnected challenges in the network, such as C18, C21, C15, and C17, structural challenges can be addressed more effectively, creating cascading benefits and unlocking pathways to resolve other challenges. Combining the survey and network approaches ensures a balanced and comprehensive strategy for addressing innovation challenges and tackling immediate perceptions and long-term structural needs.

5.5. Strategies for Addressing Critical Challenges

We propose a comprehensive set of targeted strategies to mitigate the effects of the addressed critical challenges facing public service innovation. These transformative strategies are tailored to tackle each critical challenge effectively. They highlight how decision-makers can navigate public service innovation challenges and ensure a systematic approach to mitigate their effect and foster innovation in government entities.

Table 5. Proposed strategies to tackle critical challenges.

Critical Challenge	Proposed Strategies
“Lack of information about technology to innovate in services” (C4)	Addressing this challenge requires a multifaceted approach. Bridging the gap in knowledge and expertise requires building knowledge networks and partnerships with academic institutions and private technology providers. Open innovation platforms and peer learning initiatives foster idea-sharing and collaboration across departments, while innovation labs and technology demonstration projects offer safe spaces to test and showcase new solutions [95]. Establishing technology scouting units in governmental entities ensures the constant evaluation of emerging trends, complemented by continuous training programs to enhance employee technological literacy. Participation in initiatives such as hackathons [96] can help to stay informed about emerging technologies and advancements while possessing the essential tools and skills to innovate and design effective solutions in technological disciplines. The access to technology fosters innovation by enabling more efficient processes, expedites the flow of information, and strengthens a government entity’s capacity to innovate [31].
“A culture of resistance to change among employees” (C8)	To overcome resistance to change in government entities, Damawan and Azizah (2020) [97] proposed seven key strategies: (1) gradual implementation of changes allows employees to gather more information and identify needs to adjust; (2) involving employees and encouraging participation; (3) cultivating psychological ownership, where individuals develop a strong sense of connection and engagement with the government entity; (4) communicating the value and advantages of the change and preparing the employees prior to actual implementation; (5) building trust and clarifying and reassuring regarding concerns that the employees have to ease their understanding of the purpose of change; (6) training, reducing workload, and considering employees’ input during the process of change; and (7) introducing a “change agent” who has the skills to facilitate change among employees with transparency about the occurring changes. In addition, effective communication [31] and awards and incentives for additional workloads [98] can mitigate employees’ tendency to resist change.
“Lack of motivation and empowerment for employees” (C11)	Implementing a reward system to recognize employee contributions and acknowledge their support for change can enhance engagement and motivation [99,100]. Moreover, empowerment has a positive influence; when leaders appreciate and recognize their skills and contributions, employees feel more valued, which enhances their sense of meaning and competence [101]. Providing opportunities for professional growth, such as upskilling programs and leadership development initiatives, empowers employees with the confidence to participate and add significant value. Engaging employees in organizational decision-making and co-creation initiatives, such as innovation workshops, builds a sense of ownership and accountability. Government entities can cultivate a motivated workforce that drives positive change by fostering a supportive work environment and recognizing innovation efforts.
“The service-oriented-thinking gap between managers and employees” (C14)	Bridging this gap requires strategies that foster alignment and collaboration. Organizing collaborative workshops and training programs centered on customer-focused strategy can promote a unified understanding of service objectives among managers and employees. Distributed leadership is a dynamic framework that fosters collaboration and narrows the gap between those in leadership and employees by delegating leadership tasks and fostering greater engagement and alignment among employees in achieving organizational goals and strategies [102]. Engaging employees in decision-making processes and ensuring transparent information flow fosters alignment, enhances their sense of ownership, promotes their engagement, and strengthens their commitment to achieving shared objectives [103]. These initiatives contribute to a more integrated approach and enhance collective commitment to delivering exceptional customer experiences.
“Overlapping functions between departments” (C15)	Preventing overlapping responsibilities requires clear communication and consistent collaboration. Transparency in tasks and clearly defined responsibilities and administrative roles are essential for maintaining clarity. Establishing well-defined processes and workflows further minimizes confusion. Utilizing virtual collaboration or knowledge-sharing tools fosters teamwork, facilitates efficient information exchange, and ensures everyone stays informed, creating a cohesive and efficient working environment [104]. Additionally, fostering a culture of interdepartmental collaboration through joint training and shared goals strengthens alignment and improves operational efficiency.
“Unclear value proposition for the new or improved service” (C17)	This ambiguity arises from insufficient communication regarding the objectives and underlying purpose of a new or improved service. Leaders should effectively convey the importance and advantages of the change and improvements in services [98]. Transformational leaders foster innovation and critical thinking by inspiring employees to align their personal values with organizational objectives; they effectively motivate individuals to embrace change, promote analytical reasoning, and nurture an innovative organizational culture, thereby driving both individual growth and overall organizational success [105].
“Lack of coordination and poor internal communication between organization departments” (C18)	Inadequate organizational coordination and communication flow require a strategic focus on fostering collaboration and transparency. Encouraging cross-functional teams promotes a cooperative culture, allowing departments to work more cohesively toward innovative outcomes [106]. The range of expertise, alignment on shared objectives, strong long-term relationships, transparent communication, and ongoing opportunities for learning significantly enhance and promote collaboration within the government entity [107]. This facilitates the flow of information related to responsibilities, ensuring consistency and minimizing misunderstandings.
“Absence of clear and formalized innovation process” (C21)	Addressing this issue requires the implementation of structured and systematic frameworks that guide innovation activities. Developing a formal innovation process with defined goals, roles, and responsibilities ensures clarity and alignment [108]. Implementing standardized innovation systems has been proven to positively impact innovation performance [109]. Tools such as the Innovation Funnel [110] and Open Innovation Funnel [106,111] can systematically generate and evaluate ideas within the government entity and learn from external best practices. Regular training on innovation methodologies equips employees with the skills to participate effectively.

details these strategies, emphasizing their relevance by establishing inspiring long-term objectives and implementing targeted actions; leaders can cultivate a culture of innovation and guide their government entities toward an innovative future that leads to customer satisfaction and value creation.

5.6. Leveraging Open Innovation to Address Critical Challenges

Open innovation utilizes external and internal ideas, knowledge, and resources to formalize innovation processes, tackle challenges, and create value. By promoting collaborative ecosystems, government entities can engage with various stakeholders, including customers, universities, industry peers, and technology providers, to access a broader range of expertise, cut costs, and minimize risks. This cooperative approach overcomes organizational challenges such as resource limitations, lack of knowledge, or resistance to change, which, therefore, results in enabling tailored solutions and fostering active participation from employees and external partners. Hence, in addition to the strategies mentioned earlier (described in Table 5), leveraging open innovation is a common approach to tackling critical challenges, either directly or indirectly. Government entities can overcome internal challenges and drive innovation more effectively by engaging with external stakeholders such as technology providers, customers, research institutions, and industry peers. For instance, C4 “lack of information about technology to innovate in services” is one of the challenges most directly addressed by open innovation. Collaborating with technology providers and research institutions can bridge the knowledge gap, providing access to the latest advancements and best practices [95]. Government entities can also benefit from open innovation, crowdsourcing ideas, and engaging in co-development projects to foster a technology-driven culture and enhance innovation capabilities and strategy formulation [112].

C17 “unclear value proposition for the new or improved service” is another challenge that benefits significantly from open innovation. Collaborating with customers and other external stakeholders allows government entities to gather feedback and insights into market needs through co-creation [113,114]. Co-creation processes and external testing of services help refine and clarify the value proposition, ensuring alignment with customer expectations and increasing the likelihood of successful implementation. C21 “absence of a clear and formalized innovation process” can also be tackled through open innovation frameworks. Collaborating with external entities or participating in innovation ecosystems provides a model for establishing structured and efficient processes [115]. Learning from external best practices helps government entities formalize their unique innovation frameworks, creating clarity and direction for future initiatives.

Open innovation can also indirectly address cultural and communication challenges within the government entity. It plays a transformative role in reshaping organizational culture by encouraging inclusivity, adaptability, and trust in new methodologies. In particular, C8 “a culture of resistance to change among employees” can be mitigated by exposing employees to external success stories and collaborative opportunities. Engaging employees in innovation projects involving external stakeholders can shift mindsets and foster a more open attitude toward change. Similarly, C11 “lack of motivation and empowerment for employees” can be alleviated by involving employees in co-creation initiatives, such as hackathons or innovation challenges, which enhance their engagement and provide recognition for their contributions.

Collaboration also improves coordination and alignment within the government entity, addressing challenges such as C18 “lack of coordination and poor internal communication between government entity departments.” Structured communication protocols developed for external collaborations often serve as a model for improving internal communication processes [107]. Additionally, C14 “the service-oriented-thinking gap between managers and employees” can be bridged by involving both groups in external collaborations focused on customer-centric solutions, aligning perspectives, and fostering mutual understanding. Finally, although primarily a structural issue, C15 “overlapping functions between departments” can benefit from external benchmarking and collaborative frameworks [104]. Government entities can streamline workflows and reduce redundancies by adopting tools and practices from external partners, improving efficiency and interdepartmental coordination.

Open innovation within the public sector addresses the rigidity often present in bureaucratic structures, nurturing a culture of flexibility and agility. Governments and public entities can leverage this model to pilot services, develop scalable solutions, and streamline processes, minimizing delays and inefficiencies. The focus on customer-centric design ensures that public services are more effective, accessible, and impactful. Ultimately, open innovation provides a strong framework for tackling complex problems, enhancing collaboration, and driving sustained innovation.

6. Conclusions

6.1. Concluding Remarks

Public service innovation in governmental entities plays a significant role in value creation and meeting society’s current and future needs. However, the relevant academic literature has not sufficiently addressed the complex interactions among the challenges involved in implementing such innovations. While previous studies have identified and ranked individual challenges, they have largely overlooked how these challenges interact, potentially amplifying their impact and creating multifaceted, systemic obstacles. Understanding these interdependencies is critical as they directly influence the effectiveness of solutions and policy interventions. This study addressed this gap by employing an SNA approach to analyze the interactions among the challenges faced by government entities in the UAE. Data from a prior survey of Abuzanjal and Bashir [14] served as the input, and the analysis involved correlating twenty-two identified challenges using betweenness centrality and eigenvector centrality and visualizing the results within a network framework.

6.2. Public Service Innovation Implications

This research is among the first to apply such an approach in this context. Also, it contributes to the literature by establishing a classification system that categorizes challenges into four groups: critical challenges, localized influence challenges, connector challenges, and low-connectivity challenges. For UAE government entities, efforts to address these challenges should prioritize critical challenges. These include the “lack of information about technology to innovate in services,” “a culture of resistance to change among employees,” and “insufficient employee motivation and empowerment.” Additional critical challenges encompass “the service-oriented-thinking gap between managers and employees,” “overlapping functions between departments,” “unclear value propositions for new or improved services,” “poor internal communication and coordination between departments,” and “the absence of a clear and formalized innovation process.” Strategies for overcoming these challenges were proposed. In addition to these strategies, we have demonstrated that adopting open innovation can collectively address these challenges.

6.3. Limitations and Future Research

While this study offers valuable insights, it is subject to certain limitations. The data was collected from UAE government entities, which may limit the broader applicability and generalizability of the findings to regions with varying socioeconomic or cultural contexts. Additionally, this study primarily focused on direct service delivery organizations, potentially excluding insights from supporting departments or non-customer-facing entities. These limitations warrant further investigation in future studies by broadening the scope to incorporate a broader range of public sector organizations across diverse geographical and cultural contexts. Longitudinal studies could explore how these challenges transform over time and in response to specific context interventions.

The network construction relied solely on correlation coefficients, which indicate associations among the challenges. Future research could address this limitation by validating the network structure using expert panels or other qualitative approaches to confirm and enrich the findings. Furthermore, the analysis considered only two centrality metrics, betweenness centrality and eigenvector centrality, to assess the importance of nodes in the network. Future studies could incorporate additional network metrics to provide a more comprehensive understanding of node significance and network structure.

Future investigations may explore a multi-layer network model to analyze the dynamic relationship between critical challenges and their connections with stakeholders, organizational units, or innovation outcomes. This approach would enable a more nuanced understanding of how the various dimensions of challenges interact with the PSI system. Moreover, in today’s rapidly evolving technological landscape, there is a need to examine how advanced technologies, such as digital platforms and AI, play a pivotal role in overcoming challenges, fostering innovation, and enhancing government service agility [116,117]. Initiatives aimed at accelerating service delivery, such as the Zero Government Bureaucracy program [54], also merit further exploration to understand their potential benefits in addressing these challenges. While this study focuses on the organizational challenges, future research could examine how significant external factors, such as global crises, influence public service innovation [118].