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The integration of Artificial Intelligence (AI) in manufacturing is often pursued as technology push. In contrast, this paper looks upon the AI-human interaction from a viewpoint that considers both to play an important role in reshaping their individual capabilities. It specifically focuses on how humans can play an important role in enhancing AI capabilities. The introduced concepts are tested in an industrial case study of vision-based inspection in production lines. Furthermore, the paper highlights the need to consider relevant implications for work design for AI integration. The contribution can be of practical value for system developers and work designers in how to target at the design stage the human contribution in AI-enabled systems for production environments.

Purpose: To facilitate the design of viable business models by proposing a novel business model design framework for viability. Design: A design science research method is adopted to develop a business model design framework for viability. The business model design framework for viability is demonstrated by using it to design a business model for an energy enterprise. The aforementioned framework is validated in theory by using expert opinion. Findings: It is difficult to design viable business models because of the changing market conditions, and competing interests of stakeholders in a business ecosystem setting. Although the literature on business models provides guidance on designing viable business models, the languages (business model ontologies) used to design business models largely ignore such guidelines. Therefore, we propose a business model design framework for viability to overcome the identified shortcomings. The theoretical validation of the business model design framework for viability indicates that it is able to successfully bridge the identified shortcomings, and it is able to facilitate the design of viable business models. Moreover, the validation of the framework in practice is currently underway. Originality / value: Several business model ontologies are used to conceptualise and evaluate business models. However, their rote application will not lead to viable business models, because they largely ignore vital design elements, such as design principles, configuration techniques, business rules, design choices, and assumptions. Therefore, we propose and validate a novel business model design framework for viability that overcomes the aforementioned shortcomings., Journal of Business Models, Vol 3 No 2 (2015): Journal of Business Models

The goal of this paper is twofold: i) to design a viable business model for community owned solar farms that will be setup in the north of the Netherlands. ii) To present the findings from this case study, and to propose generalisations that are relevant for the development of artefacts that can be used to facilitate the design of viable business models in a business ecosystem setting. USE 2015

The current endeavour focuses on the notion of positive versus negative polarity preference of verbs for their direct objects. This preference has to be distinguished from a verb's own prior polarity - for the same verb, these two properties might even be inverse. Polarity preferences of verbs are extracted on the basis of a large and dependency-parsed corpus by means of statistical measures. We observed verbs with a relatively clear positive or negative polarity preference, as well as cases of verbs where positive and negative polarity preference is balanced (we call these bipolar-preference verbs). Given clear-cut polarity preferences of a verb, nouns, whose polarity is yet unknown, can now be classified. We reached a lower bound of 81% precision in our experiments, whereas the upper bound goes up to 92%.