Optimizing Software Team Performance with Cultural Differences

Software development is primarily a team task that requires a high degree of coordination among team members. Prior research has indicated that the composition of team member traits such as personality and culture can influence the performance of software teams. However, this line of research does not give practical guidance on how to build teams with personnel constraints. Some research has built teams by starting with personality. However, cultural traits—which are also known to influence team performance—have not been examined in the same manner. This research, therefore, builds upon this stream by: 1) examining the effects of Hofstede’s latest six-dimensional model of national culture, 2) segmenting potential software team members into distinct cultural clusters, and 3) testing the outcomes of teams built upon homogeneous versus heterogeneous cultural compositions over time. Our results indicate that—consistent with prior research—homogenous team compositions are initially better for performance. However, this effect reverses over time, and ultimately heterogenous team compositions are superior

A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry

<p>Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 x 10(-11)) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 x 10(-10)). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 x 10(-8)). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 x 10(-7)), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.</p>