My current research involves understanding how IT start-ups develop, sustain, and create value for their partners and the greater economy that they support. On the other hand, I am interested to understand how established firms change the landscape of innovation and tech entrepreneurship.
For long, organizational researchers in our field, information systems, have focused on understanding how IT as a resource creates value and various capabilities for established firms. However, less is known about nascent organizations that supply such an increasingly valuable resource. Just like stars, IT start-ups are born in large quantities, but only few prevail, shine, and become unicorns. To many, the process of start-up survival and growth into giants appears serendipitous and enigmatic. The end goal of my research is to systematically unfold reliable practices that help IT start-ups grow, compete, outlast, and survive. Likewise, less is known about how established firms impact the tech startup scene, and I intend to shed more light in that area.
Few examples of my ongoing research projects in this area are:
T. Havakhor. “To Break them Up or Not: Venture Capital Investments by the Big Tech and the Impacts on the Landscape of Tech Entrepreneurship” work in progress (initial experiments done )
Abstract: Calls to break up big information technology companies (the Big Tech) have gained momentum amid the recent, major economic and political events. In brief, the rapid horizontal and vertical diversification of the Big Tech has been touted as a monopolizing force that negatively impacted economic growth. One area of horizontal diversification by the Big Tech is entering the venture capital (VC) industry and providing funds to, mainly, tech start-ups. While empirical research has amassed a plethora of evidence regarding the impacts of the Big Tech’s entrance to the production of non-IT goods, there is relatively no insights about the case where they enter the industry of innovation financing.
Aiming to fill this void, we focus on the VC activity of the Big Tech in different metropolitan areas across the world. Recognizing the staggered entrance of these VCs to those metropolitan areas, we design and conduct a difference-in-difference experiment that sheds light on various entrepreneurial impacts of the entrance. The primary findings indicate that the Big Tech’s VC entrance to a metropolitan area in the US enhances entrepreneurial activity as evidenced by the rise in: the number of newly established tech start-ups and the number of IT patents filed. Nonetheless, the staggered entrance of the Big Tech VCs is also followed by a decrease in: the radicalness of patents filed and granted, the total number of patents granted, the life span of tech start-ups (i.e., the time elapsed before they get acquired, merged/absorbed, or disbanded), and the number of tech start-ups that become public. Put together, this primary evidence points to an increase in tech entrepreneurial activity from a nominal view point but also highlights a decrease in radical innovative activities and a dwindle in the growth and maturation of new tech companies. These findings add to the ongoing debate about the Big Tech and their broader economic influence.
“Not-so-Dumb Money: Beating the Competition with Talent Acquisition through Corporate Venture Capital Investments” with Mohammad S. Rahman.
Abstract: The supply of the information technology (IT) entrepreneurial talent, which is an important input to digital innovation, is critically clustered geographically in tech hubs such as Silicon Valley, putting corporations located outside those clusters at a strategic disadvantage. This study focuses on corporate venture capital (CVC) investments, once widely regarded as ‘dumb money,’ as a mechanism for firms that want to access a ‘window of opportunity’ to disruptive innovations and a pool of highly-skilled talents. New ventures have the organic structure to coalesce a set of highly-skilled, entrepreneurial-minded, employees that can be a source of rare and hard-to-get talent for the investing firms. While the innovation acquisition benefits of CVC investments, in form of patent adoption, have taken much of the attention in the literature on CVC value, the returns attributed to talent acquisition have remained largely unexplored, arguably due to the difficulty in identifying and measuring talent movements associated with CVC investments. We capitalize on an opportunity to examine over 70 million online resumes to unfold the patterns of talent movement triggered by major CVC investments in digital start-ups and bridge the above-mentioned gap. As such, this study examines how talent acquisition triggered by CVC investments contributes to generating economic returns for firms. In general, our results suggest that firms benefit significantly from CVC activities when IT entrepreneurial talent is acquired from the ventures, especially when such talent is missing inside the investing firm. In economic terms, an otherwise-average firm that can acquire around 23 employees from the target venture can benefit from approximately 3 percent abnormal market return on its strategic CVC investment. More importantly, the results from a difference-in-difference experiment in our sample show that the talent acquisition benefits are significantly higher for firms that are located near IT labor markets with a shortage of entrepreneurial talent (such as those headquartered in non-coastal states). This finding highlights the role of CVC investments in reducing the IT labor disadvantages for firms that operate outside the tech clusters. The results are robust to several variations in measurement and pass placebo tests.
T. Havakhor, M. Rahman, T. Zhang, C. Zhu. “Not Knowing What to Do With or Without Machine Intelligence: Evidence from a Natural Experiment Involving Retail Investors” work in progress
Abstract: The rapid progress in Big Data technologies is commoditizing their applications and ushering an era of artificial intelligence (AI) where non-traditional users too can take advantage of such advancements. In particular, the ecosystem surrounding application programming interfaces (APIs), which increasingly involves freely available and accessible machine learning tools, is creating and supporting new consumers of data and machine intelligence. Arguably, one of the most vibrant and growing new users of big data and predictions are the retail financial market investors. We are, however, in early stages of understanding to what extent these decision makers rely on machine intelligence as well as the impact of this new input to decision making on the general market outcomes. In this paper, we exploit a natural experiment – the abrupt shutdown of Yahoo! Finance API – to offer initial insights into the impact of big data and machine intelligence on the financial markets. Our difference-in-difference design reveals that retail trades drop by approximately 8.0% in a two-month window centered around the shutdown in firms with below-median institutional ownership, relative to firms with above-median institutional ownership, suggesting that even retail investors are significantly reliant on machine intelligence in making trading decisions. Put differently, a sizable portion of retail investors feel helpless in the absence of machine intelligence. Similarly, the market liquidity deteriorated significantly in the same period, which additionally highlights the pervasiveness of machine intelligence and its role in maintaining the market stability. Additional analysis suggests that the investors who disengaged from the market following the API shutdown were involved in less profitable trades compared to the ones who continued to participate in the market. As such, among the consumers of machine intelligence, those with a lower complementary input (such as financial acumen) may be the ones that depended critically on freely available API-enabled predictions.
T. Zhang, T. Havakhor, D. Biros. “Does Cybersecurity Slow Down Digitization? A Quasi-Experiment of Security Breach Notification Laws” work in progress
Abstract: While digitization necessitates cybersecurity reforms, firms engaging in digitization initiatives may be discouraged by the costs of such major changes. Therefore, it has become increasingly important to understand if concerns about the costs of cybersecurity stifle digital growth. This study seizes an opportunity to address this question by investigating the state- and industry-level economic impacts of the passage of security breach notification laws (SBNLs) in United States, which act as legislative pressure in increasing the cybersecurity costs of digitization. We study the impact of SBNLs on an important economic topic – employment by IT service provider industry. Using a difference in difference design, we found that employment by mature IT service providers decreases following enactment of SBNLs. Impacts on younger IT service firms are not significant. The results hold under various robustness and falsification tests. This study provides fresh evidence related to the unintended and broader impacts of cybersecurity legislation.
T. Havakhor, Golmohammadi, A., D. Gauri, R. Sabherwal. “Success by talking the walk: The role of social media in the success of B2B firms,” in preparation for resubmission to Management Science.
Abstract: Considering a B2B new venture’s (B2BNVs) limited (or non-existent) customer base and limited market presence in the early stages of development, investors cannot directly observe the B2BNV’s ability to differentiate itself from competitors, or its potential for successful collaborations with its customers. This paper focuses on the signaling role that social media communications can play in reducing information asymmetries about such abilities. Based on panel data on 382 Software-as-a-Service (SaaS) new ventures, our results support the idea that the lingual similarity (dissimilarity) of a B2BNVs’ tweets to those of its customers (competitors) signal such abilities and impact fundraising success. Moreover, B2BNVs that concurrently tweet with high levels of both lingual similarity to their customers and dissimilarity to their competitors achieve greater success in raising funds than B2BNVs that tweet only with either lingual similarity to customers or lingual dissimilarity to competitors. The identification strategy in the study includes dynamic paneling with both internal and external instruments, as well as a matched sample analysis that is built by finding comparable counterfactuals for treatment observations (those with either high levels of lingual similarity to customers or high levels of lingual dissimilarity to competitors (or both)).
To further identify the proposed signaling impact, a vector autoregression test of the subsequent rise in scrutinizing the venture, a control function test to evaluate the role of underlying capabilities in driving the value of lingual similarity signals, and a weakened treatment test were followed. These additional analyses unfold that: a) lingual signals granger-cause subsequent scrutinizing of B2BNVs, b) B2BNVs adjust their social media communications according to substantive capabilities, such as their existing human talent; c) investors reward those deeper and substantive capabilities only when they are accompanied by proper lingual signals through social media; d) investors do not reward manipulation of the lingual aspects of social media communication, when not backed by deeper and substantive capabilities, and e) the value of lingual similarity/dissimilarity (i.e., the signals) subsides in major tweets (those related to new product releases, important updates, etc.) relative to routine tweets, consistent with the nature of signals which lose their value in presence of direct information. Overall, our study unfolds the importance of social media in relating to industrial players, which is not hitherto established in the existing literature. As such, the study moves beyond these media’s already-emphasized role in managing micro-customers, broadening set of known stakeholders engaged by social media communications.
Duke, J., Havakhor, T., Mui, R., and Parker, O.“How Performance Failures, Successes, and Network Structure Influence Change in Venture Capital Investment Strategies” under review at Strategic Management Journal.
Abstract: Implicit in the extant research examining the distinctions between venture capital (VC) diversification or specialization portfolio strategies is the notion that these strategies are fairly static. Yet a core strategic management principle is that strategies of all kinds can and do shift. We contend that such shifts might not always be observed because VCs must be first willing and then able to alter their portfolios. We underscore how falling short of investment goals motivates willingness to change portfolio strategies—from specialization to diversification and vice versa—and also elucidate how the structure of the VC’s ties to syndicate partners affects the firm’s ability to make such a change. Utilizing a longitudinal panel of 718 VCs, from 2010 to 2015, we find support for our hypotheses.
“It is a Matter of Who Narrates the Lines and When” being formatted for submission; with Rajiv Sabherwal.
Abstract: New ventures increasingly use Word of Mouth (WoM) communication in both micro- and macro-funding social media platforms to promote products/services and raise the necessary capital. Prior studies highlight the importance of the content of verbal communication with potential investors. This paper focuses on a relative ignored aspect of the communication, the narrator, which is also important, especially in social media. Based on 1,213 Big Data ventures (BDVs), longitudinally tracked from 2011 to 2014, it examines the sequence of narrators in a venture’s communication in one micro-investor platform (Twitter), and one macro-investor platform (AngelList), and how the narrator sequence in one platform affects the success of a new venture in another. The results indicate that compared to organizational and formal aliases, personal aliases are more emphasized when a BDV raises capital for radical innovations. Moreover, following sequences of narrators that resemble those followed by top-performing BDVs increases the raised capital.