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This study investigates the strategic orchestration of New Product Development (NPD) teams, focusing on how age diversity influences their innovation capabilities within the competitive landscape of firms. As firms encounter an evolving demographic landscape, the role of team composition, particularly age diversity, becomes critical in tuning innovation and market alignment. This paper synthesises the disparate findings from the innovation management literature on the impact of age diversity, employing dual theoretical perspectives: information/decision-making and similarity/categorisation. The former suggests that age diversity brings diverse knowledge that boosts innovation, while the latter indicates it might hinder social cohesion and team performance. Addressing the gaps in existing research, this study explores tenure diversity and team familiarity as moderators in the age diversity–performance relationship. It hypothesises that tenure diversity can enhance knowledge exchange and innovation but may complicate social interactions, whereas high team familiarity might restrict new idea generation by homogenising knowledge. Empirical analysis conducted on a dataset of 21,370 observations from Japanese sake breweries reveals that tenure diversity and team familiarity are critical in moderating the effects of age diversity on NPD outcomes. These findings enrich the NPD literature by highlighting the importance of demographic diversity and provide new insights into managing age-related dynamics in team settings. The study underscores the need for managerial strategies that leverage demographic diversity to enhance NPD effectiveness.

Diversity in teams has become an important societal and economic issue which is studied in various scientific domains. In organizational sciences, particularly empirical research methods prevail. This paper proposes to explore agent-based computational economics as a research approach for workforce diversity more intensely due to its inherent properties like capturing heterogeneous interacting agents. For highlighting this, this paper presents an agent-based computational model based on the framework of NK fitness landscapes. In the simulations, artificial organizations search for superior levels of organizational performance with search being delegated to several and potentially diverse decision-making agents. The experiments control for the level of task complexity and reflects four different attributes of workplace diversity among agents: cognitive capabilities to (i) generate and (ii) evaluate new solutions, (iii) effort efficiency and (iv) commitment to the overall organizational objective. The results suggest that the effects of workforce diversity differ across task complexity and attributes of diversity. Diversity of commitment has the strongest impact which results from interactions among local maximizers and agents seeking to globally maximize with only local means. Moreover, the results point to nonlinear effects of multi-attributive diversity on organizational performance.

Polygenic risk scores (PRS) have led to enthusiasm for precision medicine. However, it is well documented that PRS do not generalize across groups differing in ancestry or sample characteristics e.g., age. Quantifying performance of PRS across different groups of study participants, using genome-wide association study (GWAS) summary statistics from multiple ancestry groups and sample sizes, and using different linkage disequilibrium (LD) reference panels may clarify which factors are limiting PRS transferability. To evaluate these factors in the PRS generation process, we generated body mass index (BMI) PRS (PRS_BMI) in the Electronic Medical Records and Genomics (eMERGE) network (N=75,661). Analyses were conducted in two ancestry groups (European and African) and three age ranges (adult, teenagers, and children). For PRS_BMI calculations, we evaluated five LD reference panels and three sets of GWAS summary statistics of varying sample size and ancestry. PRS_BMI performance increased for both African and European ancestry individuals using cross-ancestry GWAS summary statistics compared to European-only summary statistics (6.3% and 3.7% relative R² increase, respectively, p_African=0.038, p_European=6.26x10^-4). The effects of LD reference panels were more pronounced in African ancestry study datasets. PRS_BMI performance degraded in children; R² was less than half of teenagers or adults. The effect of GWAS summary statistics sample size was small when modeled with the other factors. Additionally, the potential of using a PRS generated for one trait to predict risk for comorbid diseases is not well understood especially in the context of cross-ancestry analyses – we explored clinical comorbidities from the electronic health record associated with PRS_BMI and identified significant associations with type 2 diabetes and coronary atherosclerosis. In summary, this study quantifies the effects that ancestry, GWAS summary statistic sample size, and LD reference panel have on PRS performance, especially in cross-ancestry and age-specific analyses.

The Diversity and Disparity in Biomedical Informatics (DDBI) workshop will be focused on complementary and critical issues concerned with enhancing diversity in the informatics workforce as well as diversity in patient cohorts. According to the National Institute of Minority Health and Health Disparities (NIMHD) at the NIH, diversity refers to the inclusion of the following traditionally underrepresented groups: African Americans/Blacks, Asians (>30 countries), American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, Latino or Hispanic (20 countries). Gender, culture, and socioeconomic status are also important dimensions of diversity, which may define some underrepresented groups. The under-representation of specific groups in both the biomedical informatics workforce as well as in the patient-derived data that is being used for research purposes has contributed to an ongoing disparity; these groups have not experienced equity in contributing to or benefiting from advancements in informatics research. This workshop will highlight innovative efforts to increase the pool of minority informaticians and discuss examples of informatics research that addresses the health concerns that impact minority populations. This workshop topics will provide insight into overcoming pipeline issues in the development of minority informaticians while emphasizing the importance of minority participation in health related research. The DDBI workshop will occur in two parts. Part I will discuss specific minority health & health disparities research topics and Part II will cover discussions related to overcoming pipeline issues in the training of minority informaticians.