Archive for Economic Development, Resilience, and Innovation

Testing biasedness of self-reported microbusiness innovation in the annual business survey

This study tests for potential bias in self-reported innovation due to the inclusion of a research and development (R&D) module that only microbusinesses (less than 10 employees) receive in the Annual Business Survey (ABS). Previous research found that respondents to combined innovation/R&D surveys reported innovation at lower rates than respondents to innovation-only surveys. A regression discontinuity design is used to test whether microbusinesses, which constitute a significant portion of U.S. firms with employees, are less likely to report innovation compared to other small businesses. In the vicinity of the 10-employee threshold, the study does not detect statistically significant biases for new-to-market and new-to-business product innovation. Statistical power analysis confirms the nonexistence of biases with a high power. Comparing the survey design of ABS to earlier combined innovation/R&D surveys provides valuable insights for the proposed integration of multiple Federal surveys into a single enterprise platform survey. The findings also have important implications for the accuracy and reliability of innovation data used as an input to policymaking and business development strategies in the United States.

Authors: Luyi Han, Zheng Tian, Timothy R. Wojan, and Stephan J. Goetz

Publication: Plos ONE   Date Published: January 12, 2024

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Experimenting in the Cloud: The Digital Divide’s Impact on Innovation

This paper builds on a National Science Foundation working paper that identified a strong association between cloud use and various types of innovation but did not consider whether 1) cloud adoption is a reliable indicator of the innovation orientation of a firm, or 2) cloud adoption enables various types of innovation. The researchers estimate propensity score matching and endogenous treatment effect models to control for innovation orientation, producing evidence to test the second explanation. Findings support an enabling effect of the cloud on innovation providing concrete evidence of the adverse impact of the digital divide.

Authors: Luyi Han, Timothy R. Wojan, and Stephan J. Goetz

Publication: Telecommunications Policy   Date Published: August 1, 2023

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