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Alterations in the X‐linked recessive DMD gene cause dystrophinopathies with a broad clinical spectrum most commonly ranging from Duchenne muscular dystrophy (DMD) or Becker muscular dystrophy (BMD) to cardiomyopathy or intellectual disability. Carrier females are commonly unaffected but may show signs of dystrophinopathies. In addition, few asymptomatic male carriers with elevated creatine kinase levels have been described possibly related to deletions around exon 48. We now further support this assumed genotype–phenotype correlation by reporting an attenuated phenotype in a three‐generation family with a deletion of exon 48 of the DMD gene with clinically unaffected carrier males and females. We confirmed deep intronic breakpoints in this family by genome sequencing, but such data are not available for published cases. Therefore, further observations are needed to clarify genotype–phenotype correlation in this region, since few reports also describe predicted in‐frame copy number changes affecting this region in association with classical signs of dystrophinopathies. [ABSTRACT FROM AUTHOR]

Driven by the increased relevance of digitalised and hypercompetitive business environments, companies need to focus on IT-related innovation projects (ITIPs) to guarantee long-term success. Although prior research has illustrated that an appropriate team design can increase project performance, an approach for determining the economically optimal team design from an ex ante perspective is missing. Against this backdrop, we follow analytical modelling research and develop a model that determines the optimal team design for an ITIP by transferring central findings of previous research regarding relevant influencing factors, e.g., team size and academic background diversity, into an ex ante economic evaluation. Thereby, our model allows the comparison of different team designs (i.e., team compositions) with regard to the prospective monetary project performance. Generally, the results show that only about a fifth of the random team designs resulted in a positive profit. In contrast, the well-founded, optimal team designs proposed by our model led to a positive profit in almost 90% of all cases. Regarding the influencing parameters, we observe that team size is the most important factor since a deviation from the optimum has a much more significant effect on the expected profit than do other factors such as work experience. To ensure the real-world fidelity and applicability of our model, we discuss the underlying assumptions with two practitioners. Our contribution is manifold: Inter alia, from an academic perspective, we enhance existing research on team design by converting well-accepted qualitative findings from a frequently investigated field outside business administration (i.e., [social] psychology) into a quantitative model that allows for the ex ante economic evaluation of team design parameters. For practitioners, we provide a model that assists managers in designing ITIP teams that are more likely to deliver desired results. This model enables managers to avoid relying only on gut feeling when designing ITIP teams, as is currently often the case due to a lack of alternative approaches. [ABSTRACT FROM AUTHOR]

In spite of substantial interest in open innovation (OI), both research and practice lack methods that support companies in managing their IT innovation projects (ITIPs) relative to OI. We contribute to the closure of this gap by providing an approach for an ex ante financial evaluation of OI application, which involves developing a theoretical model that determines the optimal degree of openness in ITIPs. Based on our model, we examine relevant causal relationships by analyzing the influence of a company's ability to manage OI and the probability of success in OI application on the theoretical optimum. We find that the optimal openness level is linked with the company's ability to manage OI, which can incorporate organizational, cultural, and technological maturity. To increase the value contribution of OI, companies should focus on a steady improvement in managing OI. The results provide both an indicator for practical decision‐making and a starting point for future research. [ABSTRACT FROM AUTHOR]

Companies regularly face the challenge of deciding whether, when and to which extent they should invest in information technology (IT) innovations with different maturity. The IT innovation strategy thereby should consider mature as well as fashionable IT innovations as investment alternatives. As previous research's focus is rather qualitative, we develop a dynamic optimisation model that determines the optimal strategic allocation of an IT innovation budget to mature and fashionable IT innovations. Using a simulation-based approach, we analyse the essential causal relationships between the theoretical optimum and the factors of major influence. We find that companies should invest in fashionable IT innovations even if their own level of innovativeness is rather low and the technology's success probability has not reached a high threshold yet. Our findings provide a basis for further research on mindful investment decisions in fashionable IT innovations. [ABSTRACT FROM AUTHOR]