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Lifting the veil: using a quasi-replication approach to assess sample selection bias in patent-based studies

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Title: Lifting the veil: using a quasi-replication approach to assess sample selection bias in patent-based studies
Authors: Criscuolo, P
Alexy, O
Sharapov, D
Salter, A
Item Type: Journal Article
Abstract: Research summary Patent data is a valued source of information for strategy research. However, patent‐based studies may suffer from sample selection bias given that patents result from within‐firm selection processes and hence do not represent the full population of inventions. We assess how incidental and nonincidental data truncation resulting from firm‐level and inventor‐level selection processes may result in sample selection bias using a quasi‐replication approach, drawing on rich qualitative data and a novel, proprietary dataset of all 40,000 invention disclosures within a large multinational firm. We find that accounting for selection both reaffirms and challenges past work, and discuss the implications of our findings for work on the microfoundations of exploratory innovation activities and for strategy research drawing on patent data. Managerial summary Much of what is known about innovation in general, and in particular about what makes inventors prolific, comes from studies that use patent data. However, many ideas are never patented, meaning that these studies may not in reality talk about ideas or inventions, but only about patents. In this paper, we examine the question of whether patent data can accurately be used to represent inventions by using data on all inventions generated within a large multinational firm to explore how and to what degree the selection processes behind firms' patenting decisions may lead to important differences between the two. We find that accounting for selection changes many previously given managerial implications; for example, we show how junior inventors may often not get the credit they deserve.
Issue Date: 1-Feb-2019
Date of Acceptance: 9-Oct-2018
URI: http://hdl.handle.net/10044/1/65157
DOI: 10.1002/smj.2972
ISSN: 0143-2095
Publisher: Wiley
Start Page: 230
End Page: 252
Journal / Book Title: Strategic Management Journal
Volume: 40
Issue: 2
Copyright Statement: © 2018 The Authors. Strategic Management Journal published by John Wiley & Sons, Ltd. This is an open access article under the terms of the Creative Commons Attribution License https://creativecommons.org/licenses/by/4.0/, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: EP/F036930/1
Keywords: Social Sciences
Business & Economics
breakthrough inventions
learning from failure
patent data
sample selection bias
1503 Business and Management
1505 Marketing
Business & Management
Publication Status: Published
Online Publication Date: 2018-11-14
Appears in Collections:Imperial College Business School