Methodological pluralism and innovation in data-driven organizations (Record no. 530983)

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Personal name Ryan Allen, T. and McDonald, Rory M.
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Title Methodological pluralism and innovation in data-driven organizations
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Place of publication, distribution, etc Administrative Science Quarterly
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Extent 70(2), Jun, 2025: p.403-443
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Summary, etc Prior research on data-driven innovation, which assumes quantitative analysis as the default, suggests a tradeoff: Organizations that rely heavily on data-driven analysis tend to produce familiar, incremental innovations with moderate commercial potential, at the expense of risky, novel breakthroughs or hit products. We argue that this tradeoff does not hold when quantitative and qualitative analysis are used together. Organizations that substantially rely on both types of analysis in the new-product innovation process will benefit by triangulating quantifiably verifiable demand (which prompts more moderate successes but fewer hits) with qualitatively discernible potential (which prompts more novelty but more flops). Although relying primarily on either type of analysis has little impact on overall new-product sales due to the countervailing strengths and weaknesses inherent in each, together they have a complementary positive effect on new-product sales as each compensates for the weaknesses of the other. Drawing on a unique dataset of 3,768 new-product innovations from NielsenIQ linked to employee résumé job descriptions from 55 consumer-product firms, we find support for our hypothesis. The highest sales and number of hits were observed in organizations that demonstrated methodological pluralism: substantial reliance on both types of analyses. Further mixed-method research examining related outcomes—hits, flops, and novelty—corroborates our theory and confirms its underlying mechanisms.- Reproduced

https://journals.sagepub.com/doi/full/10.1177/00018392251313737
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Topical term or geographic name as entry element Strategy, Innovation, Product development, Research and development (R&D), Data-driven decision making, Behavioral strategy Qualitative analysis.
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Main entry heading Administrative Science Quarterly
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Item type Articles
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Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent location Current location Date acquired Serial Enumeration / chronology Barcode Date last seen Koha item type
          Indian Institute of Public Administration Indian Institute of Public Administration 2025-07-22 70(2), Jun, 2025: p.403-443 AR136696 2025-07-22 Articles

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