Open Data Infrastructures

Charalabidis, Yannis; Alexopoulos, Charalampos; Janssen, Marijn; Lampoltshammer, Thomas J.; Ferro, Enrico

doi:10.1007/978-3-319-90850-2_6

Cited by 4 publications

(7 citation statements)

References 14 publications

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“…The findings from this study suggest that the centralized approach of providing an accredited list of Open Banking providers could be more advantaged, as it may contribute towards building initial trust by enhancing firm reputation. At the same time, the centralized approach of applying a standardized technical standard can enhance interoperability, an element important for data exchange (Charalabidis et al. , 2018) and can stimulate effort expectancy in facilitating consumer adoption of Open Banking.…”

Section: Research Implicationsmentioning

confidence: 99%

“…Third, while our current findings and contribution are specifically related to the Open Banking context, they may be transferable or applicable more widely to other settings where the open data concept is considered such as other FinTech applications, “RegTech” or “SupTech” applications [4] in the public and private sectors (Arner et al. , 2020; Australian Government, 2017; OECD, 2020), thereby potentially improving engagement and participation by citizens in new technology that could improve their daily lives and foster new economic opportunities (Charalabidis et al. , 2018).…”

Section: Introductionmentioning

confidence: 99%

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Towards an understanding of consumers’ FinTech adoption: the case of Open Banking

Chan

Troshani

Hill

et al. 2022

IJBM

102

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PurposeThis study aims to identify key factors driving consumers' adoption of Open Banking. It extends the Unified Theory of Acceptance and Use of Technology (UTAUT) by integrating perceived risk, initial trust and financial literacy into an overarching conceptual model.Design/methodology/approachMeasurement items of the theoretical constructs included in the conceptual model were adapted from related literature and a set of hypotheses was developed. The hypotheses of the conceptual model were subsequently assessed with partial least squares structural equation modeling using a dataset of 456 Australian survey respondents.FindingsThe model has strong explanatory power with an R2 of 69.5%. Performance expectancy, effort expectancy, social influence and perceived risk are direct antecedents of consumers' usage intention of Open Banking. Social influence has a strong mediating effect on usage intention through performance expectancy. The effect of perceived risk is alleviated by effort expectancy and initial trust, while initial trust positively affects the effects of performance expectancy and effort expectancy on consumers' usage intention of Open Banking. Finally, financial literacy lowers initial trust towards Open Banking, possibly inducing consumer skepticism.Practical implicationsThe results suggest that practitioners should focus on performance expectancy as a primary driver of Open Banking adoption, while understanding the role of other drivers, such as social influence and perceived risk in developing marketing strategies. Policy makers are recommended to adopt a governance approach to build initial trust amongst consumers.Originality/valueThis research contributes by providing an integrated and comprehensive model for explaining consumers' FinTech adoptions by extending the existing technology adoption model UTAUT to the Open Banking domain and integrating perceived risk, initial trust and financial literacy, thereby advancing and enriching the conceptual horizon of the extant literature.

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Section: Research Implicationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Towards an understanding of consumers’ FinTech adoption: the case of Open Banking

Chan

Troshani

Hill

et al. 2022

IJBM

102

View full text Add to dashboard Cite

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“…Denmark has a national platform 3 for the cities to publish open data, providing a common entry point for accessing open data. According to the Digital Economy and Society Index (DESI) 2018, Denmark is among the most digital countries in Europe 4 . The report documents that 94 percent of the country's public facilities and services are online and are highly advanced.…”

Section: Motivation and Methodologymentioning

confidence: 99%

“…Diego et al [32] have analyzed the state of the art in open data research using descriptive, conceptual, and co-word analyses in different domains of data; the authors identified health, engineering, public administration, education, and management as the main knowledge areas. Many countries have also taken measures to integrate open data into their schools and have initiated open data projects, including the United Kingdom 3 , Norway 4 , and Spain 5 , among others.…”

Section: Educational Aspects Of Open Datamentioning

confidence: 99%

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Promoting data science in schools: Facilitating the use of open data and sensors in secondary education

Saddiqa

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General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.-Users may download and print one copy of any publication from the public portal for the purpose of private study or research. -You may not further distribute the material or use it for any profit-making activity or commercial gain -You may freely distribute the URL identifying the publication in the public portal -

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Understanding the development of public data ecosystems: from a conceptual model to a six-generation model of the evolution of public data ecosystems

Lnenicka,

Nikiforova,

Luterek

et al. 2024

SSRN Journal

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Open Data Infrastructures

Cited by 4 publications

References 14 publications

Towards an understanding of consumers’ FinTech adoption: the case of Open Banking

Towards an understanding of consumers’ FinTech adoption: the case of Open Banking

Promoting data science in schools: Facilitating the use of open data and sensors in secondary education

Understanding the development of public data ecosystems: from a conceptual model to a six-generation model of the evolution of public data ecosystems

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