The Ethnic Migrant Inventor Effect: Codification and Recombination of Knowledge Across Borders

Prithwiraj  Choudhury; Do Yoon  Kim

Article | Strategic Management Journal | February 2019

The Ethnic Migrant Inventor Effect: Codification and Recombination of Knowledge Across Borders

Abstract

Ethnic migrant inventors may differ from locals in terms of the knowledge they bring to host firms. We study the role of first-generation ethnic migrant inventors in cross-border transfer of knowledge previously locked within the cultural context of their home regions. Using a unique dataset of Chinese and Indian herbal patents filed in the United States, we find that an increase in the supply of first-generation ethnic migrant inventors increases the rate of codification of herbal knowledge at U.S. assignees by 4.5%. Our identification comes from an exogenous shock to the quota of H1B visas and from a list of entities exempted from the shock. We also find that ethnic migrant inventors are more likely to engage in reuse of their prior knowledge, whereas knowledge recombination is more likely to be pursued by teams comprising inventors from other ethnic backgrounds.

Keywords: skilled migration; ethnic migration; first-generation migrant; cultural context; knowledge flows; knowledge reuse; knowledge recombination; recombinant creation; H1B visas; Knowledge Sharing; Knowledge Use and Leverage; Knowledge Dissemination; Immigration; Ethnicity; Cross-Cultural and Cross-Border Issues;

Format: Print

Find at Harvard Read Now

Citation:

Choudhury, Prithwiraj, and Do Yoon Kim. "The Ethnic Migrant Inventor Effect: Codification and Recombination of Knowledge Across Borders." Strategic Management Journal 40, no. 2 (February 2019): 203–229.

Working Paper | HBS Working Paper Series | 2020

(When) Does Appearance Matter? Evidence from a Randomized Controlled Trial

Prithwiraj Choudhury, Tarun Khanna, Christos A. Makridis and Subhradip Sarker

While there is evidence about labor market discrimination based on race, religion, and gender, we know little about whether physical appearance leads to discrimination in labor market outcomes. We deploy a randomized experiment on 1,000 respondents in India between April and May 2020 to investigate how “looks” affect labor market outcomes. Using machine learning and computer face rendering techniques, we simulate North, South, and Northeastern Indian faces and randomize two waves of treatments where we attach faces with otherwise identical CVs. However, the second wave also contains a vignette where we provide respondents with information about the incidence of discrimination. We focus on Northeastern Indian faces that resemble those in China to focus on the potential for discrimination that has historically been present in anecdotal accounts. While we do not find evidence of discrimination against Northeastern faces in the first wave, we do so in the second among those who do not see the vignette. We provide suggestive evidence that these results are consistent with the presence of homophily under limited attention.

Keywords: Behavioral economics; coronavirus; discrimination; homophily; labor market mobility; limited attention; resumes; Personal Characteristics; Prejudice and Bias;

Citation:

Choudhury, Prithwiraj, Tarun Khanna, Christos A. Makridis, and Subhradip Sarker. "(When) Does Appearance Matter? Evidence from a Randomized Controlled Trial." Harvard Business School Working Paper, No. 21-038, September 2020. View Details

Cite View Details Read Now

Irfhan Rawji (MBS 2004) launched MobSquad in October 2018 to help American tech start-ups retain hard-to-find talent, many of whom struggled with U.S. work visa issues, such as software engineers with experience in artificial intelligence, machine learning, or data science. MobSquad also helped companies fill open roles by tapping into its database of pre-vetted foreign tech workers. While there was growing demand for these specialists, the talent supply in the U.S. was relatively constrained and American companies often filled positions with foreign-born workers using a temporary visa called the H-1B. However, U.S. President Donald Trump temporarily suspended immigration in June 2020, including foreign workers on an H-1B visa during the COVID-19 pandemic. Rawji contemplated what kind of impact this would have on MobSquad and the tech industry in Canada. There was already evidence that a growing number of foreign tech workers were choosing Canada over the U.S. due to Trump’s immigration policies. Now Rawji suspected that Trump’s latest move would further accelerate this trend, and he wanted MobSquad to be ready to help companies and workers who had been counting on the H-1B.

Tulsa Remote sought to attract a diverse group of remote workers to the city of Tulsa, Oklahoma—and was willing to put its money where its mouth was, offering $10,000 and a range of wraparound services for its program participants. After a successful pilot year, which saw the program select 100 participants out of more than 10,000 applicants, Tulsa Remote was excited to begin its second round of applications. However, the program faced an ongoing challenge attracting Black men to participate in the program. The team wondered what they could do to make their program—and their community—feel more welcoming. Meanwhile, as the second group of remote workers began making plans to move to Tulsa, the COVID-19 pandemic hit. How would the program deal with the effects of the pandemic, both on the local economy and on remote work in general?

Faculty & Research

The Ethnic Migrant Inventor Effect: Codification and Recombination of Knowledge Across Borders

Abstract

Citation:

About the Author

More from the Author