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- Achi, Abdelkader, et al.
(författare)
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Innovation capacity and the role of information systems : a qualitative study
- 2016
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Ingår i: Journal of Management Analytics. - : Taylor & Francis. - 2327-0012 .- 2327-0039. ; 3:4, s. 333-360
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Tidskriftsartikel (refereegranskat)abstract
- Today businesses are facing radical transformations through digitalization of services and products. Accordingly, their ability to innovate is increasingly linked to the capacity to innovate through information and communication technologies (ICTs). This article investigates the role of information systems (IS) as a key factor for innovation capacity. To this end, the article discusses an interpretive framework for understanding the degree of capacity of innovation through information systems (IS) reached by a given company and the contradictions that bound its evolution. An interpretive study is also presented, where the framework has been applied to seven French companies from various industries. Consistently with the framework, the interviews address process areas and practices related to three core categories: management, innovation engineering and support. The study reveals seven fundamental contradictions that can explain the main tendencies observed across the companies.
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| 2. |
- Norinder, Ulf, et al.
(författare)
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Predicting Amazon customer reviews with deep confidence using deep learning and conformal prediction
- 2022
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Ingår i: Journal of Management Analytics. - : Informa UK Limited. - 2327-0012 .- 2327-0039. ; 9:1, s. 1-16
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Tidskriftsartikel (refereegranskat)abstract
- In this investigation, we have shown that the combination of deep learning, including natural language processing, and conformal prediction results in highly predictive and efficient temporal test set sentiment estimates for 12 categories of Amazon product reviews using either in-category predictions, i.e. the model and the test set are from the same review category or cross-category predictions, i.e. using a model of another review category for predicting the test set. The similar results from in- and cross-category predictions indicate high degree of generalizability across product review categories. The investigation also shows that the combination of deep learning and conformal prediction gracefully handles class imbalances without explicit class balancing measures.
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