1. Introduction
In recent years, the majority of countries around the world have sought to improve the lives of their citizens by transforming traditional cities into smart cities [
1]. This transformation makes the newest information and communication technologies available to citizens, improving sustainability and quality of life [
2]. Although smart cities have many benefits, their adoption still faces critical challenges related to security and privacy issues, trust, and reliability [
3]. In recent years, major advancements have been made in the field of information and communications technology, such as smart city technologies, the IoT, and mobile computing [
3]. This has prompted a shift in many sectors concerning the delivery of these intelligent services via various technologies [
4,
5,
6,
7]. Smart city technologies are examples of such technologies, offering a number of significant opportunities for citizens to enhance their livability, productivity, and sustainability. Smart cities provide intelligent living that is delivered through various intelligent devices [
8,
9,
10], and they have received increasing attention due to their efficiency, convenience, and flexibility [
11,
12,
13].
The adoption of smart cities is considered a vital step in making life easier and more convenient for citizens. The adoption of smart city technologies among citizens is considered the most important step in ensuring the success of smart cities [
14]. In addition, factors related to security and privacy are considered very important for the successful adoption of smart cities to address the risks that arise from their vulnerabilities. These factors also increase citizens’ trust. Ullah and Al-Turjman [
15] revealed that these security- and trust-related factors are interrelated in the adoption of smart cities as citizens’ beliefs about privacy and security may affect their adoption of smart city technologies. Prior studies considered security and privacy as primary factors in predicting the adoption of new technologies [
16]. A limited number of studies have addressed the roles of security- and privacy-related factors in the adoption of smart cities through conceptual models; these studies were focused on factors related to environmental, behavioral, and organizational issues and were missing critical factors such as security, risk, and privacy [
17,
18,
19,
20].
Despite the benefits that smart cities provide for citizens, the rate of the adoption of these technologies around the world is still low [
21,
22,
23,
24,
25]. According to a study conducted by Cao et al. [
26], the adoption percentage of smart cities is only 33%. There is a need to understand the factors associated with the adoption of smart cities to ensure their successful implementation. Regarding smart city adoption, there have been limited studies conducted in the literature [
27,
28,
29,
30] aimed at understanding the security factors related to the adoption of smart cities.
The objective of this research was to investigate the key security and technological factors that influence the adoption of smart cities by developing and validating a conceptual model using structural equation modeling (SEM). A study conducted by Alshuwaikhat [
31] mainly focused on Saudi Arabia, a Middle Eastern country of the Arab world. They found that despite the technical support and infrastructure technologies in Saudi Arabia, its smart city adoption rate is still unsatisfactory [
31]. Given this finding, this study aimed to answer the following question:
What are the primary critical success factors that could lead to the adoption of smart cities?
3. A Security- and Technological-Factors-Based Model for the Adoption of Smart Cities
To explore which user-perspective factors explain smart city adoption in higher education, a conceptual model was developed based on the TAM’s theory. The proposed framework incorporated constructs of the TAM to explain the possible acceptance or rejection of smart cities, as well as cognitive factors supporting the adoption of smart cities, in universities.
The TAM is one of several technology adoption models that has been widely applied to measure the adoption, acceptance, and use of smart cities [
44,
45,
46,
47]. The original version of the TAM can be used to understand usage behavior with respect to new technologies [
48,
49,
50,
51]. The TAM is an extended version of the original UTAUT model and represents a combination of constructs from several models, including the TPB, the TRA, and the TPB [
52].
The TAM includes five constructs: perceived ease of use, perceived usefulness, attitude toward use, intention to use, and actual use [
53]. Previous studies found that the TAM was better than other technology acceptance models at explaining the variance (R2) in usage behaviors (from 40% to 52%) and intention behavior (from 56% to 74%) [
54]. In addition, the TAM was successfully used to predict users’ behavioral intentions and teachers’ attitudes toward online learning systems [
55]. The TAM was selected as a theoretical foundation for our proposed model in this study in order to explain the factors influencing users’ continuous intention to use smart cities.
Figure 1 presents the proposed model of this research.
3.1. Perceived Usefulness
Within the scope of this study, perceived usefulness was defined as the extent to which the utilization of a smart city application offers tangible benefits to clients when conducting financial transactions [
59]. Extensive prior research [
60,
61,
62,
63] established perceived usefulness as a potent predictor within the Technology Acceptance Model (TAM), exerting a positive influence on the attitude toward using technology. In the realm of e-banking, studies [
64,
65] have further corroborated this by demonstrating a positive correlation between perceived usefulness and users’ intentions to adopt e-banking systems. Given this background, we anticipated that perceived usefulness would assume a pivotal role in encouraging bank clients to embrace and utilize smart city applications, particularly if they perceived tangible benefits from adopting this novel technology. Consequently, we formulated the following hypothesis:
H5. Perceived usefulness exerts a positive effect on the attitude toward adopting smart city services.
3.2. Perceived Ease of Use
Perceived ease of use was the second predictor within the Technology Acceptance Model (TAM). In the context of this study, it pertains to the level of ease associated with utilizing a smart city application. We assumed that when bank clients perceived a smart city application to be user-friendly and easy to navigate, it would enhance the likelihood of its adoption. Furthermore, if interactions with a smart city application were characterized by simplicity, clarity, and ease of understanding, it would foster positive attitudes toward using the technology. Existing research [
66,
67,
68] points toward perceived ease of use as the most influential predictor in the TAM, positively impacting the attitude toward using technology. This observation has been substantiated in studies focusing on e-banking [
69,
70] which demonstrated a positive relationship between perceived ease of use and users’ intentions to adopt e-banking systems. Hence, in our study, perceived ease of use was assumed to play a crucial role in motivating users to adopt and utilize smart city applications, particularly if they expected a seamless experience with this technology. Thus, we proposed the following hypothesis:
H6. The perceived ease of use exerts a positive effect on the attitude toward using smart city services.
3.3. Service Quality
The paramount importance of excellent service quality in the success of smart city applications cannot be overstated. Users assess the quality of smart city services based on their experiences with an application and the perceived value it offers them. Prior research [
74,
75,
76,
77] has consistently shown that higher service quality results in higher perceived value, leading to more positive attitudes toward using the technology. As service quality serves as a metric for evaluating the benefits of an application or product’s services, a higher value of a smart city application would be perceived if it offered superior service quality. When users perceive a smart city application as providing high-quality services that meet their expectations, it will significantly increase the likelihood of their adoption of the application. Previous studies [
78,
79,
80] highlighted service quality as a potent predictor in the Delone and Mclean model which positively influences the actual usage of technology. Similar findings have been observed in studies focusing on e-banking [
81,
82,
83,
84] in which service quality demonstrated a positive relationship with users’ intentions to use e-banking systems. Hence, in our study, service quality was assumed to play a critical role in encouraging users to adopt and utilize smart city applications, particularly if they expected high-quality services from the technology. Consequently, we proposed the following hypothesis:
H7. Service quality exerts a positive effect on the attitude toward using smart city services.
3.4. Intention to Adopt Smart City Applications
As per the Technology Acceptance Model (TAM), intention to use refers to the subjective probability of a user adopting a smart city application. Among the various predictors in the TAM and other technology acceptance models such as the UTAUT and TRA, the attitude toward using a technology stands out as significant. Studies focused on e-banking [
85,
86,
87] have consistently demonstrated a positive relationship between users’ attitudes toward use and their intentions to use e-banking systems. Drawing from this understanding, our study emphasized the pivotal role of attitude toward use in predicting users’ adoption and utilization of smart city applications. Thus, we proposed the following hypothesis:
H8. The intention to adopt exerts a positive effect on the attitude toward using smart city services.
6. Discussion
The primary objective of this study was to develop a conceptual model that integrated constructs of the Technology Acceptance Model (TAM) with four external factors: perceived risk, perceived trust, perceived security, and service quality. This comprehensive model sought to investigate the key drivers influencing users’ decisions to exclusively use or not use smart city services. Through this method, this research aimed to gain a deeper understanding of users and ultimately increase the adoption of smart city services offered to them. We aimed to address the research gap pertaining to the limited exploration of smart city acceptance. Specifically, we examined the impact of information security, information privacy, perceived trust, perceived security risk, perceived ease of use, perceived usefulness, and service quality on the intention to adopt smart city services. Our findings will provide valuable insights to policymakers and academic researchers regarding the critical factors that may encourage users to embrace smart city services, especially in the aftermath of the COVID-19 pandemic.
We found that the security of information and online services is considered the primary factor for success of the adoption of smart cities. The results indicated that information security had a positive impact on intention to adopt. Providing security defense techniques to guarantee the security of users’ information and transactions should be considered a top priority. We recommend that information technology providers consistently provide security mechanisms for smart cities, such as multi-factor authentication and transaction encryption. These results were consistent with previous studies on smart city systems [
113,
114,
115]. In addition, the results indicated that information privacy had a positive impact on intention to adopt. Smart city projects should consider the information privacy factor during the creation of infrastructure [
113,
114,
115].
The findings unveiled a positive impact of perceived security risk on intention to adopt smart city services. This can be attributed to the inherent risks associated with these applications as they may be vulnerable to attacks by hackers, impacting users’ trust. These results aligned with the findings of previous studies [
100,
101,
102,
103,
104,
105,
106,
107]. Moreover, this study established a significant link between perceived risk and user trust. When deciding whether to adopt a technology, users often assess the perceived danger against the convenience it offers. Prior studies [
108,
109,
110,
111,
112] also suggested a strong association between perceived risk and perceived trust, indicating that users are more likely to trust a technology when perceived risk levels are minimized.
Furthermore, our findings indicated a positive impact of perceived trust on the intention to adopt smart city services. This can be attributed to user trust being bolstered by the perceived absence of risks in their transactions and activities, coupled with the benefits they receive from smart city applications. Additionally, our study established a significant relationship between perceived trust and user loyalty, especially when smart city services are highly trusted. These results were also consistent with previous studies [
113,
114,
115], which emphasized the pivotal role of user trust in the successful adoption and utilization of smart city services.
The study’s findings revealed a positive impact of perceived security on intention to adopt smart city services. This can be attributed to the implementation of robust security defense techniques, ensuring the safety and confidentiality of users’ services, activities, privacy, and data. The prioritization of users’ information security is crucial for fostering successful adoption and usage of smart city services. Moreover, the study established a significant link between perceived security and user trust. Investing in advanced security mechanisms for smart city applications is recommended. Previous studies in this area [
116] emphasized that the provision of high-quality security procedures leads to increased user trust, subsequently positively influencing user attitudes toward smart city services.
This study also found that perceived ease of use and perceived usefulness positively impact the intention to adopt smart city services. Emphasizing the simplicity of smart city applications is critical for the successful adoption of these services. However, it is important to note that perceived ease of use alone, without a strong sense of usefulness, may not be sufficient. When students find the interaction with smart city applications to be simple, understandable, and clear, it enhances their willingness to use the application. Prior studies [
66,
67,
68] also highlighted perceived ease of use as the strongest predictor in the TAM, positively influencing the attitude toward using technology. In the context of smart cities, other studies [
69,
70] have also confirmed the positive relationship between perceived ease of use and users’ intention to use smart city services.
The findings of this study highlight that service quality significantly and directly influences the intention to adopt smart city services. This underscores the critical importance of focusing on the development of smart city applications with high-quality services. Moreover, this study establishes that the development of smart city applications lacking high-quality features and services may be insufficient. When users perceive that an application offers high-quality services that meet their needs, it enhances the likelihood of their adoption of the application. These results were consistent with prior studies [
78,
79,
80] which emphasized service quality as one of the strongest predictors in the Delone and McLean model which positively affects the actual usage of technology. Additionally, studies in the context of smart cities [
81,
82,
83,
84] have also confirmed the positive relationship between service quality and users’ intention to adopt smart city services. Furthermore, our findings indicated that the intention to adopt had a positive impact on the actual adoption of smart city services. Previous related studies [
85,
86,
87] also confirmed a positive relationship between the intention to adopt and the actual adoption of smart city services.
6.1. Research Implications
This study contributes to the literature by offering both theoretical insights and practical implications for the adoption and utilization of smart city platforms in the post-COVID-19 era. It represents a pioneering effort in extending the Technology Acceptance Model (TAM) to predict the actual usage of smart city platforms in the post-COVID-19 context. This extension was particularly relevant as it anticipated an increase in the adoption of technology among users, thereby enhancing their transactional and lifestyle activities. The study also found empirical evidence for the factors that substantially increase the actual utilization of smart city platforms. The results provide valuable insights into users’ attitudes and their ongoing intention to use smart city platforms in the post-COVID-19 period. The research offers recommendations to gain a deeper understanding of the security and technological considerations that are necessary when adopting smart city platforms. We confirmed the significance of optimizing technological resources within smart city platforms to address technical challenges, such as internet connectivity issues. Adequate infrastructure support, encompassing hardware, software, and internet connectivity, is integral to fostering continuous user engagement. This research also underscored the importance of smart city developers aligning their platforms with user requirements and needs. Finally, this study highlights the role of governments in encouraging users to embrace smart city services as a primary tool for enhancing quality of life.
6.2. Limitations and Future Work
While this research offers valuable insights, certain limitations may serve as guidance for future investigations. Firstly, the model proposed in this study could be improved by the inclusion of additional factors regarding system quality, content quality, and technological aspects, with the aim of providing more comprehensive and robust research solutions for addressing the issue of smart city adoption. Secondly, the study’s scope was confined to the Jordanian population. To ascertain the generalizability of our findings, it is necessary to replicate the study in diverse geographical contexts. Such cross-cultural comparisons could illuminate the cultural dimensions pertinent to the acceptability of smart city initiatives. Finally, our study only focused on users’ perceptions. Future research endeavors could also explore the perspectives and insights of experts in the field regarding the successful adoption of smart city applications. By considering these limitations and potential solutions, this research could further contribute to increasing the adoption of smart city services.
7. Conclusions
The utility of smart city services and applications has become increasingly paramount for the facilitation of transactions and activities. Despite the benefits of smart cities for citizens, the rates of the adoption of these technologies remain low. There is a need to understand the factors associated with the adoption of smart cities in order to ensure their successful implementation.
The primary objective of this study was to understand users’ perspectives and the adoption of smart city services. We used the Technology Acceptance Model (TAM) and incorporated external factors, including information security, information privacy, perceived security risk, perceived trust, perceived ease of use, perceived usefulness, and service quality. The proposed model measured users’ adoption of smart city services. The analytical framework employed in this study to assess the proposed hypotheses was SEM. This study identified the pivotal roles played by perceived security risk, perceived trust, and service quality in motivating the adoption of smart city services. Additionally, the results confirmed the positive influence of information security and information privacy on the intention to adopt smart city services. These research findings offer valuable insights into the critical factors that drive users’ adoption of smart city services. Policymakers and academics could leverage these findings to formulate and implement strategies aimed at increasing the rates of the adoption of smart city services.