Design Principles for Industrial Data-Driven Services

Azkan, Can; Möller, Frederik; Iggena, Lennart; Otto, Boris

doi:10.1109/tem.2022.3167737

Cited by 6 publications

(3 citation statements)

References 80 publications

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“…Many companies fear that their data could be used by third parties without permission and that trade secrets could be disclosed (Miller, 2012). Close attention must therefore be paid to data security and data protection concerns so that unforeseen potential dangers could be mitigated or prevented altogether (Azkan et al, 2022). In addition to data security, there is also the legal question of data ownership as the data has an unclear status-whether it belongs to the provider or the customer (Marquardt, 2017;Töytäri et al, 2017).…”

Section: Monetizationmentioning

confidence: 99%

Is this nuclear material secure? Examining trust in voice user interfaces for international nuclear safeguards seal examination

Divis,

Coram,

Howell

et al. 2024

Proceedings of the Annual Hawaii International Conference on System Sciences

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Data is nowadays considered as a key resource and represents the most valuable asset of our technology-driven world. However, the ability to use this resource in a value-adding way requires a holistic perspective. Small-and medium-sized enterprises in particular face major challenges in the innovation and development process. Despite preliminary research in the area of data-driven services (DDS), there is a lack of methodological analysis of the key barriers for SMEs in the context of DDS development. To address this shortcoming, we have developed an interpretive structural model based on a two-stage mixed-method approach by combining a structured literature review with practice-oriented focus group interviews to identify key barriers and their interdependencies and interactions. Our paper strengthens the knowledge of DDS development through a methodological barrier analysis and provides a guide for practitioners to eliminate the most relevant barriers to DDS development.

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Section: Monetizationmentioning

confidence: 99%

Is this nuclear material secure? Examining trust in voice user interfaces for international nuclear safeguards seal examination

Divis,

Coram,

Howell

et al. 2024

Proceedings of the Annual Hawaii International Conference on System Sciences

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show abstract

“…Besides technological readiness, the agricultural sector also faces challenges in terms of the maturity of relevant policy frameworks and standards (legal, organizational, technical, semantic, and others) [12,[26][27][28][29][30]. Some studies also highlight the need for interdisciplinary methods for creating value for creating value for all stakeholders due to the complex interactions often involving numerous stakeholders [31,32]. To promote active involvement from all relevant actors in agro-food value chains, there is a need to establish trust as a foundation for facilitating data sharing.…”

Section: Challenges and Solutions For Data Sharing In Agro-food Systemsmentioning

confidence: 99%

Towards Trusted Data Sharing and Exchange in Agro-Food Supply Chains: Design Principles for Agricultural Data Spaces

Šestak,

Copot

2023

Sustainability

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In the modern agricultural landscape, realizing data’s full potential requires a unified infrastructure where stakeholders collaborate and share their data to gain insights and create business value. The agricultural data ecosystem (ADE) serves as a crucial socio-technical infrastructure, aggregating diverse data from various platforms and, thus, advertising sustainable agriculture and digitalization. Establishing trustworthy data sharing and exchange in agro-food value chains involves socioeconomic and technological elements addressed by the agricultural data space (ADS) and its trust principles. This paper outlines key challenges to data sharing in agro-food chains impeding ADE establishment based on the review of 27 studies in scientific literature. Challenges mainly arise from stakeholders’ mistrust in the data-sharing process, inadequate data access and use policies, and unclear data ownership agreements. In the ADE context, interoperability is a particularly challenging topic for ensuring the long-term sustainability of the system. Considering these challenges and data space principles and building blocks, we propose a set of design principles for ADS design and implementation that aim to mitigate the adverse impact of these challenges and facilitate agricultural data sharing and exchange.

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“…As organizações podem utilizar o Big Data e a inteligência gerada como um recurso organizacional chave para a inovação. Azkan et al (2022) acreditam que a incorporação de dados habilita a otimização interna e abre oportunidade de novos negócios baseados em modelos de negócios dirigidos por dados. Poeppelbuss et al (2022) adicionam que as tecnologias digitais habilitam o desenvolvimento de "sistemas de serviços inteligentes" que conectam pessoas e coisas, coletam e processam informação e são capazes de aprender, se adaptar e tomar decisões.…”

Section: Recursosunclassified

Proposal of a Conceptual Model on the Relation Between Digital Transformation and Service Innovation

Vargas¹,

Perez²

19th CONTECSI International Conference on Information Systems and Technology Management

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Digital transformation and service innovation are two contemporary themes and extremely relevant to the organizational and economic context. The objective of this study is to analyze and structure the relationship between the two themes bringing an update of academic publications that address this relation. For doing so, a systematic literature review was conducted based on the databases Scopus and World of Science in August 2022. The resultant articles were the base for the corpus of this investigation through an inductive process (as there were no pre-defined categories). Through a triangulation process among the different articles, 10 (ten) different categories that related digital transformation and service innovation emerged. The main concepts of the articles were organized in each of these 10 categories. Later, these 10 categories were divided in three dimensions: factors that influence digital transformation, factors that influence the relationship between digital transformation and service innovation and results of innovation. Finally, a theoretical and schematic model was proposed organizing the dimensions, categories and main concepts that emerged from the literature. This study may contribute for the understanding of the relationship between both phenomena both for academic and professional purposes.

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Design Principles for Industrial Data-Driven Services

Cited by 6 publications

References 80 publications

Is this nuclear material secure? Examining trust in voice user interfaces for international nuclear safeguards seal examination

Is this nuclear material secure? Examining trust in voice user interfaces for international nuclear safeguards seal examination

Towards Trusted Data Sharing and Exchange in Agro-Food Supply Chains: Design Principles for Agricultural Data Spaces

Proposal of a Conceptual Model on the Relation Between Digital Transformation and Service Innovation

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