Social innovations in outsourcing: An empirical investigation of impact sourcing companies in India

This paper was accepted for publication in the journal Journal of Strategic Information Systems and the definitive published version is available at http://dx.doi.org/10.1016/j.jsis.2015.09.002Impact sourcing – the practice of bringing digitally-enabled outsourcing jobs to marginalized individuals – is an important emerging social innovation in the outsourcing industry. The impact sourcing model of delivering Information Technology and Business Process Outsourcing (IT–BPO) services not only seeks to deliver business value for clients, but is also driven by an explicit social mission to help marginalized communities enjoy the benefits of globalization. This dual focus has led to the ambitious claim that social value creation can be integral to (and not always by-products of) innovative IT–BPO models. Given the relative newness of the impact sourcing business model there is scarce research about how impact sourcing companies emerge and the process through which entrepreneurs build and operate such companies. This paper draws on a qualitative study of seven Indian impact sourcing companies and develops a process model of the individual-level motivational triggers of impact sourcing entrepreneurship, the entrepreneurial actions underpinning different phases of venture creation and the positive institutional-level influences on impact sourcing. The paper argues that since deeply personalized values are central to the creation and development of impact sourcing companies, the business model may not be easy to replicate. The analysis highlights an intensive period of embedding and robust alliances with local partners as crucial for the scalability and sustainability of the impact sourcing business model. It also emphasizes the role of ‘social’ encoding and mimicry in determining the extent to which impact sourcing companies are able to retain their commitment to marginalized communities

Genome-wide interaction study of smoking behavior and non-small cell lung cancer risk in Caucasian population.

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer. Both environmental and genetic risk factors contribute to lung carcinogenesis. We conducted a genome-wide interaction analysis between SNPs and smoking status (never vs ever smokers) in a European-descent population. We adopted a two-step analysis strategy in the discovery stage: we first conducted a case-only interaction analysis to assess the relationship between SNPs and smoking behavior using 13,336 NSCLC cases. Candidate SNPs with p-value less than 0.001 were further analyzed using a standard case-control interaction analysis including 13970 controls. The significant SNPs with p-value less than 3.5x10-5 (correcting for multiple tests) from the case-control analysis in the discovery stage were further validated using an independent replication dataset comprising 5377 controls and 3054 NSCLC cases. We further stratified the analysis by histological subtypes. Two novel SNPs, rs6441286 and rs17723637, were identified for overall lung cancer risk. The interaction odds ratio and meta-analysis p-value for these two SNPs were 1.24 with 6.96x10-7 and 1.37 with 3.49x10-7, respectively. Additionally, interaction of smoking with rs4751674 was identified in squamous cell lung carcinoma with an odds ratio of 0.58 and p-value of 8.12x10-7. This study is by far the largest genome-wide SNP-smoking interaction analysis reported for lung cancer. The three identified novel SNPs provide potential candidate biomarkers for lung cancer risk screening and intervention. The results from our study reinforce that gene-smoking interactions play important roles in the etiology of lung cancer and account for part of the missing heritability of this disease