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| 2. |
- Bani Hani, Imad, et al.
(författare)
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The Triadic Relationship of Sense-Making, Analytics, and Institutional Influences
- 2022
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Ingår i: Informatics. - : MDPI. - 2227-9709. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- The current business environment demands the enablement of organization-wide use of analytics to support a fact-based decision making. Such movement within the organization require employees to take advantage of the self-service business analytics tools to independently fulfil their needs. However, assuming independence in data analytics requires employees to make sense of several elements which collectively contribute to the generation of required insights. Building on sense-making, self-service business analytics, and institutions literature, this paper explores the relationship between sense-making and self-service business analytics and how institutions influence and shape such relationship. By adopting a qualitative perspective and using 22 interviews, we have empirically investigated a model developed through our literature review and provided more understanding of the sense-making concept in a self-service business analytics context.
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| 3. |
- Chowdhury, Soumitra, 1983-, et al.
(författare)
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Service innovation in digitalized product platforms : An illustration of the implications of generativity on remote diagnostics of public transport buses
- 2021
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Ingår i: Technology in society. - Oxford : Elsevier. - 0160-791X .- 1879-3274. ; 65
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Tidskriftsartikel (refereegranskat)abstract
- The digitalization of products stimulates service innovation and new business opportunities for industrial manufacturing firms. These opportunities are driven by generativity, which denotes digital technology's capacity in enabling organizations to innovate. While generativity on the one hand provides opportunities for digital service innovation, on the other hand it challenges the traditional business logic of industrial manufacturing firms. The traditional stable product-centric businesses where resources of a product platform are controlled by industrial manufacturing firms become destabilized and driven towards a flexible service innovation. The aim of this research is to explore the implications of generativity for service innovation in digitalized product platforms. We show the paradoxical relationship between generativity and control by following a bus manufacturer's endeavour in service innovation with digitalized public transport buses. We contribute with empirical illustrations of the implications for service innovation with three different degrees of control in digitalized product platforms.
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| 4. |
- McConnon, Paul John, et al.
(författare)
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Agility in the Age of Cloud Computing
- 2020
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Ingår i: <em>AMCIS 2020 Proceedings</em>. - : Association for Information Systems (AIS). - 9781733632546 ; , s. 1-10
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Konferensbidrag (refereegranskat)abstract
- Although agile development has been studied in both software development and project management, little is known about the use of an agile methodology in cloud service delivery. Cloud computing has become more and more ubiquitous in everyday life. Opportunities to develop powerful cloud-enabled digital services have pushed organizations to explore novel ways of delivering the services. Conventional top-down waterfall approaches do not allow for swift change, adaptation, and the speed required to manage the complexities involved in cloud service delivery. This research presents the principles for successful agile driven cloud service delivery by examining the professional services organization of a global company. The findings show what is important to be successful in cloud service delivery projects in an evolving organizational setting with an explanation of the emergence of certain patterns.
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| 5. |
- Ostheimer, Julia, et al.
(författare)
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An alliance of humans and machines for machine learning : Hybrid intelligent systems and their design principles
- 2021
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Ingår i: Technology in society. - : Elsevier. - 0160-791X .- 1879-3274. ; 66
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Tidskriftsartikel (refereegranskat)abstract
- With the growing number of applications of artificial intelligence such as autonomous cars or smart industrial equipment, the inaccuracy of utilized machine learning algorithms could lead to catastrophic outcomes. Human-in-the-loop computing combines human and machine intelligence resulting in a hybrid intelligence of complementary strengths. Whereas machines are unbeatable in logic and computation speed, humans are contributing with their creative and dynamic minds. Hybrid intelligent systems are necessary to achieve high accuracy and reliability of machine learning algorithms. In a design science research project with a Swedish manufacturing company, this paper presents an application of human-in-the-loop computing to make operational processes more efficient. While conceptualizing a Smart Power Distribution for electric industrial equipment, this research presents a set of principles to design machine-learning algorithms for hybrid intelligence. From being AI-ready as an organization to clearly focusing on the customer benefits of a hybrid intelligent system, designers need to build and strengthen the trust in the human-AI relationship to make future applications successful and reliable. With the growing trends of technological advancements and incorporation of artificial intelligence in more and more applications, the alliance of humans and machines have become even more crucial.
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| 6. |
- Ramasamy, Anandhi, et al.
(författare)
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Big data quality dimensions : a systematic literature review
- 2020
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Ingår i: Journal of Information Systems and Technology Management. - : Universidade de São Paulo. - 1809-2640 .- 1807-1775. ; 17
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Tidskriftsartikel (refereegranskat)abstract
- Although big data has become an integral part of businesses and society, there is still concern about the quality aspects of big data. Past research has focused on identifying various dimensions of big data. However, the research is scattered and there is a need to synthesize the ever evolving phenomenon of big data. This research aims at providing a systematic literature review of the quality dimension of big data. Based on a review of 17 articles from academic research, we have presented a set of key quality dimensions of big data.
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