Abstract
The first months of the COVID-19 crisis offer the possibility to observe patterns of innovation in response to a large, unanticipated shock, simultaneously creating severe adversity and new opportunities. Using new survey data on 22,102 small businesses, we study the amounts, types, and determinants of innovation, particularly firm age, size, factor adjustment, and prior capabilities. Results imply high rates of innovation during the pandemic, including new products, processes, and modes of delivery. Regressions show that rates are higher for younger and larger firms, where younger firms show a greater propensity for product innovations and larger firms for process innovations. Innovation is higher for firms that adjust factors (employment) less. Firms with either extensive or zero pre-pandemic capabilities to accommodate social distancing innovated the least in directions that would expand this capability, while firms with some prior capability innovated the most to expand upon process innovations related to social distancing. Young firms are more likely to increase E-sales, while large firms are more likely to adjust the share of teleworkers.
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Notes
The OECD defines innovation as “the implementation of a new or significantly improved product (good or service), or process, a new marketing method, or a new organizational method in business practices, workplace organization or external relations” (OECD, Eurostat , 2018). This focus on innovation activities implies we do not study patents, data for which are not yet available in any case and which are largely irrelevant in many industries and smaller firm size categories.
More details about COVID crisis is available in the following link. https://www.cdc.gov/museum/timeline/covid19.html
Brown et al. (2020) use the ASE data to study innovation differences between immigrant- and native-owned firms in the high-tech sector.
For details about the SBTC and descriptive statistics, please see Dani et al. (2021).
The Small Business Development Center (SBDC) Program is an extensive national network of close to 1,000 small business service centers leading the charge in providing no-cost tools and guidance needed to help entrepreneurs and small businesses realize their full potential. The California SBDCs include five regional networks covering the state, devoted to helping all industries and all levels of small businesses with accessing capital, human resources, marketing/social media, e-commerce, accounting, disaster resources and pivoting strategies and any other business needs.
A pilot survey covering the period of January through April was disseminated to clients only in the Los Angeles and San Diego SBDC regional networks in April 2020.
In the first months of 2020, California’s SBDCs had counseled more than 44,000 small business clients over 172,000 hours, supported over $1.27 billion dollars in small business funding, including COVID assistance, and helped 938 entrepreneurs establish new startups during the crisis. Between March and April alone, CA SBDCs client engagement increased by over 191 percent.
Based on the Longitudinal Business Database (LBD) covering all U.S. private sector employers, the BDS provides aggregate-level information on the number of firms, establishments, and employment as well as dynamics including entry, exit, job creation, and job destruction.
Mairesse and Mohnen (2010) reviewed qualitative questions on product and process innovations in innovation surveys, including the Community Innovation Surveys (CIS) in Europe and the Business Research and Development and Innovation Survey (BRDIS) in the U.S. More recently, the 2014 Annual Survey of Entrepreneurs by the U.S. Census Bureau provided similar product and process innovation measures, which were studied in the context of immigrant entrepreneurs (Brown et al. , 2020) and black entrepreneurs (Lee et al. , 2022).
The SBTC measures innovations during the first six months of the pandemic while the ASE measures innovations in the last three years at the time of the interview. In order to compare these for the same length of time period, we computed the innovation rate for a six month period in the ASE as follows: \(Innovation_{6months} = 1 - (1 - Innovation_{36months})^{1/6}\).
Aggregated innovation measures (e.g., any, product, or process innovation) are excluded from this analysis because they are highly correlated with each innovation measure by construction.
Despite the low correlations, we also estimate using seemingly unrelated regression methods as robustness checks to see if the correlations among innovation measures affect the main findings.
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Acknowledgements
This paper is based on research supported by California’s Small Business Development Center (SBDC) and partly by the National Science Foundation under Grants No. 1719201 and 2152456 to George Mason University. We are very grateful for helpful comments from the referees and editors of the Journal and from participants of the Mannheim Center for Competition and Innovation and International Schumpeter Conferences. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not represent the views of the SBDC, the NSF, or the World Bank.
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National Science Foundation under Grants No. 1719201 and 2152456 to George Mason University.
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Appendix A
Appendix A
This appendix provides the definitions of variables, descriptive statistics, and robustness checks for the main results.
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Lee, K.M., Earle, J.S., Dani, L. et al. Who innovates during a crisis? Evidence from small businesses in the COVID-19 pandemic. J Evol Econ 33, 893–950 (2023). https://doi.org/10.1007/s00191-023-00824-8
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DOI: https://doi.org/10.1007/s00191-023-00824-8