Adaptive Trust: Usage-Based Trust in Crowdsourced IoT Services

Does IoT service orchestration in public services enrich the citizens’ perceived value of digital society?

“…performance expectancy, information privacy and trust in government are factors that create public trust, which was hypothesised as H1(a-c). The results show a significant relation to our hypotheses and are consistent with the previous studies of (Bahutair et al, 2019;Liang et al, 2017;Ranaweera, 2016;Tam, 2019). These factors are considered important to create public trust concerning IoT public services.…”

“…Furthermore, results highlight that perceived value provided a considerable amount of explanatory power as 59% on the intention to use. The public trust had a stronger relationship with the perceived value which implies that stronger trust in smart government services will create the more perceived value of such services, which is consistent with the studies of (Bahutair et al, 2019;Mahmood et al, 2019). The impact of digital society affinity on IoT usage intention was hypothesised as H7 and its result was significant as (β = 0.117, p < 0.007) which implies that digital society affinity is an important factor influencing citizens' future use intention.…”

“…The individual citizens' adoption behaviour regarding smart government services is influenced by various factors and the most important factors are performance expectancy and trust (Liang et al, 2017). This is hypothesised as H1a: Performance expectancy of smart government IoT service orchestration will positively influence the public trust Information privacy is considered another important aspect in smart government IoT services orchestration, which can be discussed as citizens' control over the information provided during the use of IoT service (Bahutair et al, 2019). Citizens are sometimes reluctant to provide personal information over the internet (Moqbel & Bartelt, 2015), and the same in the case of IoT where a host of convenient smart devices continuously gather, process, and send data to perform various services which have magnified the threat of information privacy.…”

“…In quest of the research objectives, we have conducted a study on the conceptual phenomena of Unified Theory of Acceptance and Use of Technology (UTAUT), Technology Acceptance Model (TAM), and Theory of Planned Behaviour (TPB). The success of IoT service orchestration in the public sector requires the integration of citizens' trust (Bahutair et al, 2019;Nelson & Gorichanaz, 2019) and digital social affinity (Bigné et al, 2007;Manca et al, 2019). We have developed a conceptual model IoT-PVM after formulating the research hypotheses and it was subsequently tested through PLS-SEM.…”

Towards Crowdsourcing Internet of Things (Crowd-IoT): Architectures, Security and Applications

“…Another challenge of assessing trust in dynamic nature is its dependability on how the service is used. To overcome this challenge, the same author Bahutair [49], proposed an approach termed Adaptive Trust framework for crowdsourced IoT services. The framework of usage-based trust assigns trust values to IoT services based on the consumers' usage.…”