Learning from Failures: : Differentiating Between Slip-ups and Knowledge Gaps
Abstract
Our research investigates firm learning from failures by dividing them into two types, failures that occur due to slip-ups and those that occur due to knowledge gaps, and by examining whether learning occurs in the context of both types of failures. We study these phenomena in the context of product recalls in pharmaceuticals and medical devices. Based on text analysis of recall documents, recalls are divided into process related and design related to represent slip-up failures and knowledge gap failures. We further study how innovation capabilities, represented by accumulated stocks of patents and lagged research and development (R&D) intensity, impact learning from both types of failures. We test our hypotheses using negative binomial generalized linear models to analyze longitudinal data for 108 publicly traded U.S. firms over 2000–2016 comprising 7,984 recalls. Results indicate that design-related recalls generate learning to a greater extent than process-related recalls, and that accumulated patents and lagged R&D intensity enhance learning from design-related recalls. These findings suggest that the learning mechanisms invoked by failures are concentrated more on knowledge gap failures than slip-up failures, and such learning is impacted by innovation capabilities. Overall, this research extends organizational learning theory by differentiating between learning from different types of failures and extends absorptive capacity theory by incorporating the role of innovation capabilities in enhancing learning from failures. We develop recommendations for learning from slip-up failures by focusing on the cultural and social mechanisms of organizational learning in addition to the technical and structural mechanisms that may mainly impact learning from knowledge gap failures.
Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2021.15663.
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- Learning from Failures: Differentiating Between Slip-ups and Knowledge Gaps
Index terms have been assigned to the content through auto-classification.
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Published: 01 November 2024
Accepted: 20 January 2024
Received: 01 September 2021
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