Knowledge transfer in offshoring arrangements: the roles of social capital, efficacy and outcome expectations

Prior research has shown that social capital is as a vital factor for knowledge transfer, but has hardly examined this within an offshoring context. Moreover, the social capital lens is not sufficient for explaining motivational mechanisms of knowledge transfer. Our qualitative case study demonstrates that social capital as well as efficacy beliefs and outcome expectations affected the ability and willingness of German IT developers to transfer knowledge to their Indian offshore colleagues. We highlight interrelations between these knowledge transfer mechanisms, and we discuss results with regard to new insights for offshoring and knowledge transfer research, limitations, and practical implications

A systems perspective on offshoring strategy and motivational drivers amongst onshore and offshore employees

Extant research tends to view firm level offshoring strategies and micro level motivational drivers as self-contained units of analysis. By contrast, this paper draws on an inductive study of two global service firms to demonstrate how the implementation and success of an advanced task offshoring strategy depends on certain systemic interdependencies between (a) the strategy, (b) onshore employees’ motivation to transfer advanced tasks and (c) offshore employees’ motivation to spend effort on their tasks and stay with the firm. We analyse how these three elements interact and produce feedback loops to create an ‘offshoring system’. Extrapolating from our findings, we propose how the offshoring system is likely to develop within the external constraints set by the attainable expertise of offshore employees and by client demands

Knowledge transfer in IT offshoring relationships: the roles of social capital, efficacy and outcome expectations

Information technology (IT) development in global organisations relies heavily on the transfer of tacit and complex knowledge from onshore units to offshore subsidiaries. A central concern of such organisations is the development of social capital, which is known to facilitate the smooth transfer of knowledge. However, only a few studies in IS research have explicitly examined the role of social capital for knowledge transfer in an IT offshoring context. In this paper, we argue that such knowledge transfer mechanisms can be understood better by considering social capital in concert with knowledge senders' efficacy and outcome expectations, two of the potentially keymotivational drivers of knowledge transfer.We develop our arguments through a qualitative case study of a large German multinational company. German IT developers in this firm provided in-depth accounts of their experience with offshore colleagues in an Indian captive subsidiary unit. Drawing on our analysis, we develop a model that depicts the influence of social capital, efficacy and outcome expectations on onshore IT developers' ability and willingness to transfer knowledge to offshore colleagues. Through the model, we also explain how social capital, efficacy and outcome expectations are interrelated and generate three interlocked, self-reinforcing circles of knowledge transfer success in IToffshoring relationships

Task allocation strategies and motivational processes in advanced services offshoring

Global service firms are increasingly moving advanced tasks to popular offshoring destinations such as India. Despite the significant influence of micro-level motivational mechanisms on the implementation and success of such offshoring strategies, empirical research in this area is still in its early stages. In this paper, taking a grounded theory approach, we present qualitative data from a German electronics firm working with IT developers in a Bangalore subsidiary, and the UK division of a large global professional services firm which has offshored its tax reporting work to a captive unit in Bangalore. From a cross-case analysis of these two settings, we develop a grounded model of the complex interdependencies between offshoring strategies and offshore-onshore motivational processes. We identify three interlocking and self-reinforcing circles between (a) task allocation strategies, (b) motivational processes onshore, and (c) motivational processes offshore. These circles function to either inhibit or support the offshoring strategies. We highlight several theoretical and practical contributions with regard to micro-macro level interdependencies in offshoring strategies of global firms

An horizon scan of biogeography

The opportunity to reflect broadly on the accomplishments, prospects, and reach of a field may present itself relatively infrequently. Each biennial meeting of the International Biogeography Society showcases ideas solicited and developed largely during the preceding year, by individuals or teams from across the breadth of the discipline. Here, we highlight challenges, developments, and opportunities in biogeography from that biennial synthesis. We note the realized and potential impact of rapid data accumulation in several fields, a renaissance for inter-disciplinary research, the importance of recognizing the evolution-ecology continuum across spatial and temporal scales and at different taxonomic, phylogenetic and functional levels, and re-exploration of classical assumptions and hypotheses using new tools. However, advances are taxonomically and geographically biased, and key theoretical frameworks await tools to handle, or strategies to simplify, the biological complexity seen in empirical systems. Current threats to biodiversity require unprecedented integration of knowledge and development of predictive capacity that may enable biogeography to unite its descriptive and hypothetico-deductive branches and establish a greater role within and outside academia

Acute alcohol does not impair attentional inhibition as measured with Stroop interference scores but impairs Stroop performance

Rationale: Inhibition is a core executive function and refers to the ability to deliberately suppress attention, behavior, thoughts, and/or emotions and instead act in a specific manner. While acute alcohol exposure has been shown to impair response inhibition in the stop-signal and Go/NoGo tasks, reported alcohol effects on attentional inhibition in the Stroop task are inconsistent. Notably, studies have operationalized attentional inhibition variably and there has been intra- and inter-individual variability in alcohol exposure. Objective: This study aimed to examine the acute effects of alcohol on attentional inhibition, considering previous limitations. Methods: In a single-blind, cross-over design, 40 non-dependent participants with a medium-to-high risk drinking behavior performed a Counting Stroop task (CST) under a baseline and an arterial blood alcohol concentration (aBAC) clamp at 80 mg%. Attentional inhibition was assessed as the alteration of reaction times (RT), error rates (ER), and inverse efficiency scores (IES) between incongruent and congruent trials (interference score). Stroop performance was also assessed regardless of trial-type. Results: Compared to saline, acute alcohol exposure via an aBAC clamp did not affect CST interference scores but increased RTs and IES in both incongruent and congruent trials. Conclusions: Attentional inhibition (Stroop interference score) was not impaired by clamped moderate alcohol exposure. Acute alcohol impaired Stroop performance evidenced by a general increase in response times. Our findings suggest that response and attentional inhibition do not share the same neurocognitive mechanisms and are affected differently by alcohol. Results could also be explained by automated behaviors known to be relatively unaffected by acute alcohol

Therapy reduction in patients with Down syndrome and myeloid leukemia: the international ML-DS 2006 trial

Children with myeloid leukemia associated with Down syndrome (ML-DS) have superior outcome compared with non-DS patients, but suffer from higher constitutional cytotoxic drug susceptibility. We analyzed the outcome of 170 pediatric patients with ML-DS enrolled in the prospective, multicenter, open-label, nonrandomized ML-DS 2006 trial by Nordic Society for Pediatric Hematology and Oncology (NOPHO), Dutch Childhood Oncology Group (DCOG), and Acute Myeloid Leukemia–Berlin-Frankfurt-Münster (AML-BFM) study group. Compared with the historical control arm (reduced-intensity protocol for ML-DS patients from the AML-BFM 98 trial), treatment intensity was reduced by lowering the cumulative dose of etoposide (950 to 450 mg/m2) and intrathecal central nervous system prophylaxis while omitting maintenance therapy. Still, 5-year overall survival (89% 6 3% vs 90% 6 4%; Plog-rank 5 .64), event-free survival (EFS; 87% 6 3% vs 89% 6 4%; Plog-rank 5 .71), and cumulative incidence of relapse/ nonresponse (CIR/NR; 6% 6 3% vs 6% 6 2%; PGray 5 .03) did not significantly differ between the ML-DS 2006 trial and the historical control arm. Poor early treatment response (5-year EFS, 58% 6 16% vs 88% 6 3%; Plog rank 5 .0008) and gain of chromosome 8 (CIR/NR, 16% 6 7% vs 3% 6 2%, PGray 5 .02; 5-year EFS, 73% 6 8% vs 91% 6 4%, Plog rank 5 .018) were identified as independent prognostic factors predicting a worse EFS. Five of 7 relapsed patients (71%) with cytogenetic data had trisomy 8. Our study reveals prognostic markers for children with ML-DS and illustrates that reducing therapy did not impair excellent outcome. The trial was registered at EudraCT as #2007-006219-2. (Blood. 2017;129(25): 3314-3321

Renormalization of the commutative scalar theory with harmonic term to all orders

The noncommutative scalar theory with harmonic term (on the Moyal space) has a vanishing beta function. In this paper, we prove the renormalizability of the commutative scalar field theory with harmonic term to all orders by using multiscale analysis in the momentum space. Then, we consider and compute its one-loop beta function, as well as the one on the degenerate Moyal space. We can finally compare both to the vanishing beta function of the theory with harmonic term on the Moyal space.Comment: 16 page

A self-interaction corrected pseudopotential scheme for magnetic and strongly-correlated systems

Local-spin-density functional calculations may be affected by severe errors when applied to the study of magnetic and strongly-correlated materials. Some of these faults can be traced back to the presence of the spurious self-interaction in the density functional. Since the application of a fully self-consistent self-interaction correction is highly demanding even for moderately large systems, we pursue a strategy of approximating the self-interaction corrected potential with a non-local, pseudopotential-like projector, first generated within the isolated atom and then updated during the self-consistent cycle in the crystal. This scheme, whose implementation is totally uncomplicated and particularly suited for the pseudopotental formalism, dramatically improves the LSDA results for a variety of compounds with a minimal increase of computing cost.Comment: 18 pages, 14 figure

Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization