Information Technology Acceptance in Public Safety in Smart Sustainable Cities: A Qualitative Analysis

Oliveira, V.A.T.; Santos, Gilson Ditzel

doi:10.1016/j.promfg.2020.01.239

Cited by 9 publications

(5 citation statements)

References 15 publications

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“…Therefore, the social relationship between users/providers must be considered during the design phase of social IoT applications. A system of social IoT can be thought of as a peer-to-peer (P2P) web of communities centred on the owner, with devices (owned by people) asking and delivering on behalf of service providers [13,14].…”

Section: Overview Of Iot and Big Data Information Securitymentioning

confidence: 99%

Model Design of Big Data Information Security Management Based on the Internet of Things

Yao¹

2022

Security and Communication Networks

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At present, the level of modernization and informatization is constantly improving, especially in rapidly developing China. A large amount of information is collected every second, forming a huge database and making people live in the “big data era.” Following cloud computing and the Internet of things, big data technology has become another revolutionary change in the global society, changing global development and becoming a new development point for technological innovation, industrial policy, and national information security. Big data in the new age poses new challenges and perspectives for the nation’s infosec development. Big data is a renewed tool for state security. Nations use big data to create state infosec, offering great facilitation, potential for adoption, and business value. This is a “new blue ocean” for competition among countries. Although big data brings convenience to public life, it also poses a serious threat to national information security. After the research and experiment of the model design of big data information security management of the Internet of things, the experimental data have shown that 86.67% set passwords in communication devices and storage devices. 66.67% installed firewalls, and 76.67% ran antivirus software. Compared with before, the total ratio of setting a password increased by 53.34% and the total ratio of installing a firewall and running antivirus software both increased by 26.67%. It can be seen from the above data that the protection of big data information under the Internet of things has been significantly improved. From the above data, through the big data information security management of the Internet of things, a new development direction is proposed for the development of information security.

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Section: Overview Of Iot and Big Data Information Securitymentioning

confidence: 99%

Model Design of Big Data Information Security Management Based on the Internet of Things

Yao¹

2022

Security and Communication Networks

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“…The wide application of the UTAUT2 model has resulted in numerous proposals for its extension for particular contexts, including the smart cities (Tamilmani et al 2021 ). For example, for the acceptance of public safety solutions in the smart city Oliveira et al (Oliveira and Santos 2019 ) suggested the introduction of a way to evaluate how the contribution of the city and the citizens can impact the adoption. For the acceptance of smart government services, authors in Almuraqab and Jasimuddin ( 2017 ) suggested the new variables: Perceived trust in government, Perceived trust in technology, Perceived Compatibility, and Awareness to be considered with the positive impact, while Perceived Cost and Perceived Risk are expected to harm the end user's attitude.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

A readiness assessment framework for the adoption of 5G based smart-living services

Stojanović

Radenković

Popović

et al. 2023

Inf Syst E-Bus Manage

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The subject of this article is to analyze the users’ attitude towards new, 5G-enabled smart living services before their commercial launch. The goal is to offer a framework for the analysis and evaluation of influential factors in the early adoption of 5G residential services. Additionally, the paper examines how mobile operators can leverage their existing infrastructure and services to boost the acceptance of both 5G as a technology and the provided smart-living services. To ascertain the potential impact that mobile operators can have on the adoption of such services, loyalty programs were taken into account as a separate factor in the acceptance study. The study was conducted in Serbia in the form of a survey. The analysis of the results yielded some notable conclusions such as trust in technology playing the leading role in influencing the behavior intention, while loyalty programs showed that they can influence attitudes towards individual smart living services. The presented results can be used to shape any future implementation of 5G-based services in Serbia, or any other country whose 5G infrastructure and services for the residential customer segment are yet to be established.

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“…However, this research was focusing on five variables namely Actual System Use (AU), Perceived Ease of Use (PEOU), Attitude Toward Using (ATU), Behavioral Intention to Use (BIU), and Perceived Usefulness (PU). Furthermore, one way to measure the successful implementation of smart cities is using the technology acceptance model approach (TAM) which has also been widely implemented in many previous studies (Alnemer, 2022;Dirgantari et al, 2020;Jnr & Petersen, 2022;Kabir et al, 2022;Kurdi et al, 2020;Oliveira & Santos, 2019;Rodzi et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis and Identification of Non-Impact Factors on Smart City Readiness Using Technology Acceptance Analysis: A Case Study in Kampar District, Indonesia

Anam,

Yunianta,

Alyamani

et al. 2023

JAETS

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Most countries start to implement Smart Cities as an innovation for urban strategy. However, not all Smart Cities implementations worked and were implemented well, because the community still not ready for the implementation of Smart City. The aim of this research is to investigate community readiness and finding low impact factors for implementing smart cities based on 5 factors, namely AU, PEOU, ATU, BIU, and PU. This research was using a qualitative study with the Technology Acceptance Model approach (TAM) to investigate the relationship between 5 factors. Based on the results of data distribution, there are 2 clusters, namely people who know about public service applications and people who are not aware of any public service applications. Furthermore, there are 3 tests conducted in this research namely T-test, F-test and Coefficient Determination Test to determine the impact and influence of the relationship between each factor. However, from the results of the t-test it was found that there were 2 relationships that had no impact because the t-count was negative and the 2 relationships between these factors were between PU - AU and AU - PU.

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Information Technology Acceptance in Public Safety in Smart Sustainable Cities: A Qualitative Analysis

Cited by 9 publications

References 15 publications

Model Design of Big Data Information Security Management Based on the Internet of Things

Model Design of Big Data Information Security Management Based on the Internet of Things

A readiness assessment framework for the adoption of 5G based smart-living services

Analysis and Identification of Non-Impact Factors on Smart City Readiness Using Technology Acceptance Analysis: A Case Study in Kampar District, Indonesia

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