Prediction of Player Churn and Disengagement Based on User Activity Data of a Freemium Online Strategy Game

Churn describes customer defection from a service provider.This can be observed in online freemium games, where userscan leave without further notice. Game companies are lookingfor methods to detect and predict churn to enable managementreaction. The recorded data of games can be analyzed forthis purpose. We conducted a case study based on data fromthe freemium game The Settlers Online. Churn detection wasachieved by application of four different labeling approaches,based on common churn and disengagement definitions within thegame analytics literature.

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Seven Paradoxes of Business Process Management in a Hyper-Connected World

Business Process Management is a boundary-spanning discipline that aligns operational capabilities and technology to design and manage business processes. The Digital Transformation has enabled human actors, information systems, and smart products to interact with each other via multiple digital channels. The emergence of this hyper-connected world greatly leverages the prospects of business processes - but also boosts their complexity to a new level.

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Good gamers, good managers? A proof-of-concept study with Sid Meier's Civilization

Human resource professionals increasingly enhance their assessment tools with game elements—a process typically referred to as “gamification”—to make them more interesting and engaging for candidates, and they design and use “serious games” that can support skill assessment and development. However, commercial, off-the-shelf video games are not or are only rarely used to screen or test candidates, even though there is increasing evidence that they are indicative of various skills that are professionally valuable.

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Semantic Shopping: A Literature Study

The digitalization of the economy and society overall has a significant impact on customers’ shopping behavior. After being conditioned by experiences in entertainment or simple Internet search, customers increasingly expect that a smart shopping assistant understands his/her shopping intentions and transfers these to shopping recommendations. Thus, the emerging opportunity in this context is to facilitate an intention-based shopping experience similar to the way semantic search engines provide responses to enquiries.

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