Browsing by Author "Topcu, Taylan G."

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    Does Open Innovation Open Doors for Underrepresented Groups to Contribute to Technology Innovation?: Evidence from a Space Robotics Challenge
    Topcu, Taylan G.; Zhang, Lihui Lydia; Szajnfarber, Zoe (Elsevier, 2023-05)
    Diversity, equity, and inclusion (DEI) are increasingly being recognized as important policy goals for organizations across government and the industry. Improved DEI has been linked to both substantive improvement in innovation performance and societal good. However, despite a stated emphasis on DEI, progress has not kept up with aspirations. One indirect policy approach that holds promise is wider adoption of Open Innovation (OI) as part of an innovation toolkit. Proponents contend that OI reduces barriers to entry and garners productive contributions from diverse contributors. While there is anecdotal support for the diversifying potential of OI, so far, there is a dearth of empirical evidence connecting OI to DEI with consideration of performance outcomes, beyond `winners´. To study this link directly, this article leverages data from a previously conducted unique field experiment that explicitly tracked the population of potential solvers and their performance on a National Aeronautics and Space Administration (NASA) space robotics problem. We found that while OI attracted different solvers than the reference internal workforce, there was important variation in both the extent and direction of the observed differences, with respect to attributes of DEI. For instance, OI attracted proportionally fewer female solvers than the already male-dominated space workforce; and that proportion decreased further among solvers providing quality solutions. On the other hand, OI proved effective at granting access to an international pool of young professionals with potentially novel perspectives. Overall, our findings suggest OI can be an effective tool for achieving some diversity policy goals, but it is not well-suited for achieving all stated aspects of diversity. Therefore, we suggest a more targeted approach to matching the opportunities for OI to achieve specific policy objectives.
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    A Systematic Literature Review of Digital Twin Research for Healthcare Systems: Research Trends, Gaps, and Realization Challenges
    Xames, Md. Doulotuzzaman; Topcu, Taylan G. (IEEE, 2024-01-03)
    Using the PRISMA approach, we present the first systematic literature review of digital twin (DT) research in healthcare systems (HSs). This endeavor stems from the pressing need for a thorough analysis of this emerging yet fragmented research area, with the goal of consolidating knowledge to catalyze its growth. Our findings are structured around three research questions aimed at identifying: (i) current research trends, (ii) gaps, and (iii) realization challenges. Current trends indicate global interest and interdisciplinary collaborations to address complex HS challenges. However, existing research predominantly focuses on conceptualization; research on integration, verification, and implementation is nascent. Additionally, we document that a substantial body of papers mislabel their work, often disregarding modeling and twinning methods that are necessary elements of a DT. Furthermore, we provide a non-exhaustive classification of the literature based on two axes: the object (i.e., product or process) and the context (i.e., patient’s body, medical procedures, healthcare facilities, and public health). While this is a testament to the diversity of the field, it implies a specific pattern that could be reimagined. We also identify two gaps: (i) considering the human-in-the-loop nature of HSs with a focus on provider decision-making and (ii) implementation research. Lastly, we discuss two challenges for broad-scale implementation of DTs in HSs: improving virtual-to-physical connectivity and data-related issues. In conclusion, this study suggests that DT research could potentially help alleviate the acute shortcomings of HSs that are often manifested in the inability to concurrently improve the quality of care, provider wellbeing, and cost efficiency.
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    Towards a solver-aware systems architecting framework: leveraging experts, specialists and the crowd to design innovative complex systems
    Szajnfarber, Zoe; Topcu, Taylan G.; Lifshitz-Assaf, Hila (Cambridge University Press, 2022-03-11)
    This article proposes the solver-aware system architecting framework for leveraging the combined strengths of experts, crowds and specialists to design innovative complex systems. Although system architecting theory has extensively explored the relationship between alternative architecture forms and performance under operational uncertainty, limited attention has been paid to differences due to who generates the solutions. The recent rise in alternative solving methods, from gig workers to crowdsourcing to novel contracting structures emphasises the need for deeper consideration of the link between architecting and solver-capability in the context of complex system innovation. We investigate these interactions through an abstract problem-solving simulation, representing alternative decompositions and solver archetypes of varying expertise, engaged through contractual structures that match their solving type. We find that the preferred architecture changes depending on which combinations of solvers are assigned. In addition, the best hybrid decomposition-solver combinations simultaneously improve performance and cost, while reducing expert reliance. To operationalise this new solver-aware framework, we induce two heuristics for decomposition-assignment pairs and demonstrate the scale of their value in the simulation. We also apply these two heuristics to reason about an example of a robotic manipulator design problem to demonstrate their relevance in realistic complex system settings.