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  • February 2025
  • Article

Seeing the Whole: Configurational Cognition and New Venture Resource Mobilization

By: Goran Calic, François Neville, Santi Furnari and C. S. Richard Chan
Research is scant on how multiple venture attributes combine as “whole packages” of signals (or cognitive configurations) in resource holders’ eyes, shaping a venture’s ability to mobilize resources. Drawing on a Qualitative Comparative Analysis of 1,395 crowdfunding... View Details
Keywords: Crowdfunding; Mission and Purpose; Entrepreneurship; Communication; Perception
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  • January 2023
  • Article

Firm-Induced Migration Paths and Strategic Human-Capital Outcomes

By: Prithwiraj (Raj) Choudhury, Tarun Khanna and Victoria Sevcenko
Firm-induced migration typically entails firms relocating workers to fill value-creating positions at destination locations. But such relocated workers are often exposed to external employment opportunities at their destinations, possibly triggering turnover. We... View Details
Keywords: Worker Relocation; Turnover; Firm-induced Migration; Smaller Towns; Employee Mobility; Geographic Mobility; Migration; Clusters; Employees; Geographic Location; Performance; Opportunities; Retention; Human Capital; Talent and Talent Management
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  • 2023
  • Working Paper

Virtual Water Coolers: A Field Experiment on the Role of Virtual Interactions on Organizational Newcomer Performance

By: Prithwiraj Choudhury, Jacqueline N. Lane and Iavor Bojinov
Designing management practices to better onboard organizational newcomers working remotely is a key priority for firms. We report results from a randomized field experiment conducted at a large global firm that estimates the performance effects of different types of... View Details
Keywords: Remote Work; Virtual Water Coolers; Social Interactions; Careers; Field Experiment; Employees; Interpersonal Communication; Internet and the Web; Performance; Personal Development and Career
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  • January 2021
  • Article

Machine Learning for Pattern Discovery in Management Research

By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect... View Details
Keywords: Machine Learning; Supervised Machine Learning; Induction; Abduction; Exploratory Data Analysis; Pattern Discovery; Decision Trees; Random Forests; Neural Networks; ROC Curve; Confusion Matrix; Partial Dependence Plots; AI and Machine Learning
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  • 2020
  • Working Paper

Machine Learning for Pattern Discovery in Management Research

By: Prithwiraj Choudhury
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used as an observation for further inductive or abductive research, but should not be treated as the result of a... View Details
Keywords: Machine Learning; Theory Building; Induction; Decision Trees; Random Forests; K-nearest Neighbors; Neural Network; P-hacking; Analytics and Data Science; Analysis
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