Market Feedback and Team Commitment in Radical Product Innovation Process

Previous research has considered how exploratory market learning processes moderate market and technological uncertainty in radical product development. Scholars argue that new product development (NPD) teams may increase the chances of success of radically new projects by acquiring, assimilating and implementing new information from market feedback. However, research has not tackled how information is assimilated by the NPD team and to what extent the process of information implementation occurs. In this article, we begin to fill the need for such research by investigating the interaction between internal team values (beliefs and possibly ideology) and external market feedback / information in radical projects. Via the lens of a 2-year longitudinal participant-observation study, we suggest that information assimilation is not automatic, but rather influenced in interesting ways by internal team values. The findings imply that shared team values act as a selective assimilation mechanism determining whether a development team will act on user feedback. Furthermore, the type of information (e.g., functional vs. conceptual feedback) processed by the development team acts as a moderating factor on the relationship between the team values and information processing

The Strategic Determinants of Tardy Entry: Is Timeliness Next to Godliness?

Previous research has considered extensively the causes and effects of market entry order and timing. It has neglected, however, the timeliness of such entry — the degree to which a firm delivered a new product on the date it had set for its release. In this article, we begin to fill the need for such research by evaluating some strategic explanations for why a firm might miss a scheduled entry date. We then test whether such “tardy entry” influences sales performance in the new market

Whole-genome sequencing reveals host factors underlying critical COVID-19

Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease