We introduce a general framework for analyzing large-scale text-based data, combining the strengths of neural-network language processing and generative statistical modeling. Our methodology generates textual factors by (i) representing texts using vector word embedding, (ii) clustering words...

We introduce a general approach for analyzing large-scale text-based data, combining the strengths of neural network language processing and generative statistical modeling to create a factor structure of unstructured data for downstream regressions typically used in social sciences. We generate...

Drawing upon knowledge-based view and transaction-costs perspective, the study identifies customer relationship orientation and structural flexibility as the two key mechanisms that service multinationals can use to capture the benefits and mitigate the costs of global demand heterogeneity....