Labor Flows, Diversity, and Technological Performance
Grenoble Ecole de Management, France
This study addresses the question of how the level and composition (diversity) of the R&D worker flows (both inbound flow, outbound flow, and aggregated total flow) affect the technological performance (namely, patenting activity) of organizations.
Researchers have long studied the different sources of spillovers and their distinct effects on organizational performance. Worker-mobility in particular has attracted the attention of many scholars (e.g. Arrow, 1962; Rao and Drazin, 2002; Agrawal et al., 2006) due to its importance as a distinct source of knowledge spillover. The flow of incoming and outgoing employees enables a dynamic rejuvenation of knowledge and social capital, which plays an important role in furthering technological performance. However, this workers flow can cut both ways. Integration of many new employees or the departure of many existing employees can disrupt knowledge flows within the company (Herstad et al., 2015). Moreover, this flow of workers is a rather heterogeneous group in terms of their background and employment experience. Thus, its potential knowledge and social capital assets are not only contingent on the levels of workers’ flows, but also on the composition of these flows.
The literature treats the flows of incoming and outgoing employees as separate processes, focuses mainly on the impact of inbound mobility on performance and assumes a positive effect of total mobility (without considering the effect of outbound mobility). The effect of the composition of these flows have not been addressed.
How does the inbound, outbound and total R&D worker flows, respectively, impact technological performance?
How does the interplay between the levels and the composition of the R&D worker flows affect technological performance.
Quantitative - using biannual data on 7492 firm-year observations on French firms involved in R&D activities between 2007 and 2013.
We ran our analysis using a Zero inflated negative binomial regression.
The quantitative analysis is based on firm-level data from the “annual survey on resources devoted to research and development in business enterprises” and the “survey on R&D researchers and engineers in business enterprises and institutes of professional and technical studies” conducted by the French ministry of higher education and research.
We use biannual data on 7492 firm-year observations on French firms involved in R&D activities between 2007 and 2013.
Our findings suggest that the levels of worker flows (both incoming and/or outgoing) have a positive impact on technological performance, but only up to a threshold after which, increases in the levels of worker flows engenders a negative effect. At low levels of worker flows (for both inbound and outbound flows), a diverse composition of these flows improves performance, while it negatively affects performance at high levels, accentuating the complexity and management costs of the reorganization of working teams.
Contribution to Scholarship
Our findings extend previous works that have been done on the effect of labor mobility on organizational performance by undertaking a more rigorous analysis that accounts for the effect of both inbound and outbound worker flows simultaneously, as well as their aggregated impact. Moreover, the findings offer compelling evidence for the importance of labor flows composition (the composition of both inbound and outbound flows) and its effect on the relationship between the levels of labor flows and performance. We thus suggest a more comprehensive framework that accounts for both levels and composition of worker flows, in order to understand the impact of these flows on organizational performance.
Contribution to Practice
Our results offer important insights to managers, mainly related to human resources management. We suggest that human resource management should be expanded to recognize that where employees are lost to and acquired from is a key factor to improving technological performance. Since excessive worker flows can have adverse effects on performance, managers need to find the right balance between new hires and separations. Our results may also encourage managers to manage the relationships they possess with former employees, in order to access new knowledge and social capital.
We believe that our research fits the theme of the R&D Management conference in general as it looks at how the R&D worker flows, in terms of levels and composition, impact technological performance.
Agrawal, A., Cockburn, I. and McHale, J. (2006). Gone but not forgotten: knowledge flows, labor mobility, and enduring social relationships. Journal of Economic Geography, 6(5), pp.571-591.
Arrow, K.J. (1962), Economic Welfare and the Allocation of Resources for Innovation. In: Nelson, R.R. Editor, The Rate and Direction of Inventive Activity Princeton University Press, Princeton, NJ, 609–626.
Herstad, S., Sandven, T. and Ebersberger, B. (2015). Recruitment, knowledge integration and modes of innovation. Research Policy, 44(1), pp.138-153.
Rao, H., and Drazin, R. (2002). Overcoming resource constraints on product innovation by recruiting talent from rivals: A study on the mutual fund industry, 1986-94. Academy of Management Journal, 45(3), 491-507.
Taking a holistic view on the relevance of internal promoter roles for corporate innovation performance
1Alpen-Adria University, Austria; 2University of Southern Denmark
Innovation activities in organizations often face significant barriers, internal resistance, and resource uncertainties (O'Connor and Rice, 2013). To overcome these barriers, innovation projects rely on the support of individuals within the organization that are committed to innovation and show a high personal involvement.
The literature on these supporters highlights the role of innovation champions (Schon, 1963, Markham and Griffin, 1998), and with a more differentiated view the role of innovation promoters. Whereas in the mono-personally centered concept of innovation champions innovations depend on the committed, confident, persistent individual (Howell et al., 2005), the concept of promoters acknowledges that innovation activities require support from different people in different roles, organizational functions, and hierarchical levels (Hauschildt, 2003). Innovation promoters are “individuals who actively and intensively support the innovation process” (Witte, 1973:15). There are four promoter roles: the power promoter supports innovation through the higher hierarchical position. Expert promoters possess the necessary knowledge to support technical project progress. Process promoters facilitate the interaction between departments and smoothen the processes for the project. The relationship promoter has strong personal ties reaching beyond the organization setting the pathways to external knowledge and collaborations (Hauschildt and Kirchmann, 2001).
Qualitative research shows that promoters can contribute to innovation success (Hüsig and Mann, 2010; Goduscheit, 2014). However, quantitative studies are rare and have only focused on performance of individual projects (Gemünden et al., 2007; Rost et al., 2007) or have only investigated specific promoter roles (e.g., Walter & Gemünden, 2000).
Thus, we do not know about the overall performance impact of a full implementation of all promoter roles on the firm’s innovation portfolio, and the underlying mechanisms through which promoters facilitate superior innovation portfolio success. Thus, what is the impact of full promoter implementation implementation on innovation portfolio performance?
We consider all promoter roles and investigate whether their general presence and involvement in the firm’s innovation activities improves overall innovation performance. As the core mechanisms explaining this relationship, we propose that a full implementation of promoter roles improves (i) information flows within and beyond the firm boundaries and (ii) facilitates innovation activities through motivation, protection, and resource support.
Drawing on information processing theory (Galbraith, 1974) and promoter theory (Witte, 1973) we develop hypotheses and test them with field survey data.
To test the hypotheses, we used cross-sectional, multi-respondent data collected from 986 informants of 125 firms. The independent variables were assessed by aggregating responses from multiple employees involved in innovation activities, whereas innovation portfolio performance was evaluated by the CEO. Multi-item measures were used to capture all variables. Structural equation modeling was used to assess the relationships. To assess overall promoter implementation, we created a Type II second-order factor model by capturing the four promoter roles separately using reflective items, and then modeling the four promoter constructs as formative factors informing the index at the higher level.
First, the significant factor weights of all promoter roles support that a full promoter implementation requires all four roles. Second, the path model results support total mediation of the effect of promoter implementation on innovation portfolio performance: Higher levels of promoter implementation facilitate information flows (β=.51; p<.001), which in turn increases innovation portfolio performance (β=.20; p<.05). Furthermore, promoter implementation increases innovation facilitation (β=.35; p<.001), which is positively associated with performance (β=.22; p<.05). The direct path is not significant.
Contribution to Scholarship
This is the first research that takes a holistic view on the promoter concept that goes beyond specific roles and their effects on individual projects. We provide a comprehensive empirical test of promoter theory by considering all promoter roles, the portfolio performance level, and intermediate outcomes (i.e., mediators) that explain the underlying mechanisms.
Contribution to Practice
While not all projects might require the same support of innovation promoters, their overall presence within the company goes beyond the single project and allows for a knowledge-sharing appreciative, innovation-friendly culture. In addition, a consequent implementation of the promoter concept also yields higher financial returns through higher innovation portfolio performance. Thus, mangers should encourage employees to take over these informal roles of innovation promoters.
Innovation requires bridging internal as well as external stakeholders. Our research centers on those individuals who actively engage in these bridging activities.
GEMÜNDEN, H. G., SALOMO, S. & HÖLZLE, K. 2007. Role Models for Radical Innovations in Times of Open Innovation. Creativity and Innovation Management, 16, 408-421.
GALBRAIGHT, J. R. 1974. Organization design: An information processing view. Interfaces, 4(3): 28-36.
GODUSCHEIT, R. C. 2014. Innovation promoters — A multiple case study. Industrial Marketing Management, 43, 525-534.
HAUSCHILDT, J. 2003. Promoters and champions in innovations: Development of a research paradigm. In L. V. Shavinina (Ed.), The international handbook on innovation, 804- 811, London, UK: Pergamon.
HAUSCHILDT, J. & KIRCHMANN, E. 2001. Teamwork for innovation – the ‘troika’ of promotors. R&D Management, 31, 41-49.
HOWELL, J. M., SHEA, C. M. & HIGGINS, C. A. 2005. Champions of product innovations: defining, developing, and validating a measure of champion behavior. Journal of Business Venturing, 20, 641-661.
HÜSIG, S. & MANN, H.-G. 2010. The role of promoters in effecting innovation in higher education institutions. Innovation: Management, Policy & Practice, 12, 180-191.
MARKHAM, S. K. & GRIFFIN, A. 1998. The breakfast of champions: associations between champions and product development environments, practices and performance. Journal of Product Innovation Management, 15, 436-454.
O'CONNOR, G. C. & RICE, M. P. 2013. A Comprehensive Model of Uncertainty Associated with Radical Innovation. Journal of Product Innovation Management, 30, 2-18.
ROST, K., HÖLZLE, K. & GEMÜNDEN, H. G. 2007. Promoters or Champions? Pros and Cons of Role Specialization for Economic Progress. Schmalenbachs Business Review, 340-363.
SCHON, D.A. (1963). Champions for radical new inventions. Harvard Business Review, 41 (2), 77-86.
WITTE, E. 1973. Organisation für Innovationsentscheidungen – Das Promotorenmodell, Göttingen, Vahlen.
Top manager’s human capital and the innovation of young businesses in sub-Saharan Africa
Toulouse Business School, France
While most scholars agree that entrepreneurship is critical to economic development as it provides product and service innovation, the source of such innovativeness is still the subject of heated debate; especially in emergent economies, as sub-Saharan African countries, where the current economic upheaval appeal entrepreneurs to seize new business opportunities.
Our study engages with two main literature. First, we use the human capital literature through which entrepreneurship scholars proposed relevant frameworks to better understand the relationship between the top manager and the innovativeness of a young business (Unger et al., 2011; Weterings & Koster, 2007). Second, we draw upon the institutional theory which is critical to study business environments where formal and informal activities are intertwined, as in sub-Saharan African countries (Armanios et al., 2016; George et al., 2016; Webb et al., 2013).
Scholars are still uncertain about the effect of top managers’ human capital on the in-novative performance of a venture. In sub-Saharan African countries characterized by high inequalities, it is of great importance to shed light on the link between top manager’s human capital and the innovative performance of local ventures.
Under what conditions does top managers’ human capital impacts the innovativeness of young businesses in sub-Saharan African countries?
We employ firm-level data from the World Bank enterprise survey. The World Bank periodically collects data on enterprises operating in many emerging and developing countries about various business environment factors their growth and innovativeness. We chose three criteria to select our sample: (1) Being a sub-Saharan African firm, (2) having less than 10 years old and (3) having less than 50 employees (Nuscheler, Engelen & Zahra, 2019).
The final sample yields 2205 year-observations and 700 companies operating in 19 countries.
As our dependent variable is a dummy variable we use a Probit model with the analysis of the marginal effects.
Our findings show, that top managers’ experience in a specific industry increases the likelihood that their firms introduce new products or services on the market (p<0.001) whereas the high degree of education has the opposite impact (p<0.001). Both effects are contingent to top managers’ capacity to manage versus circumvent government requirements (i.e., taxes, licensing, etc.). While the former capacity amplified the positive effect of top managers’ experience on new products or services introduction (p<0.001), the latter reduces it (p<0.001). On the contrary, both the capacity to manage and circumvent government requirements amplify the negative effect of a high degree of education on new products or services introduction (p<0.001, p<0.001, respectively).
Contribution to Scholarship
Our study contributes to the human capital literature by showing the importance of top managers’ human capital in the innovativeness of young firms. In line with Unger et al. (2011) characterizing the human capital by the sectorial experience and the educational background, our contribution is twofold. First, in contrast with Weterings & Koster (2007) who didn’t find a significant link between top managers’ experience and firms’ innovative performance in a context of developed countries, our study shows that this relationship exists, is positive and significant in a context of developing countries. Second, we show that top managers’ educational background is negatively related to innovativeness as it may lead to an excessive conformity that may preclude risks taking and therefore innovativeness in developing countries’ context. This finding is contrary to previous research rather indicating a positive effect (Martin et al., 2013).
Contribution to Practice
First, our findings suggest that the entrepreneurs willing to innovate in developing countries need to consider their own human capital to better assess their strength or weakness-es vis-à-vis their competitors. In addition, we show the relevance of young business top man-agers’ capacity to manage or circumvent government requirements (eg. taxes, customs, labor regulations, licensing and registration) for innovativeness in developing countries. Second, for institutional and private actors willing to stimulate the entrepreneurial dynamic in developing countries, this research suggests taking into account top managers’ human capital and adjust their accompaniment accordingly.
Few studies have investigated the impact of top managers’ human capital on young firm growth or innovativeness in the specific context of developing countries where there is high level of uncertainty in the business environment. Our paper attempts to meet this gap between research, business and society in emerging markets.
Armanios, D. E., Eesley, C. E., Li, J., & Eisenhardt, K. M. (2017). How entrepreneurs leverage institutional intermediaries in emerging economies to acquire public resources. Strategic Management Journal, 38(7), 1373-1390.
Balsmeier, B., & Czarnitzki, D. (2014). How important is industry-specific managerial experience for innovative firm performance? ZEW- Centre for European Economic Research Discussion Paper.
George, G., Corbishley, C., Khayesi, J. N., Haas, M. R., & Tihanyi, L. (2016). From The Editors: Bringing Africa in: Promising directions for management research. Academy of Management Journal, 59(2), 377–393.
Martin, B.C., McNally, J.J., Kay, M.J., 2013. Examining the formation of human capital in entrepreneurship: a meta-analysis of entrepreneurship education outcomes. Journal of Business Venturing, 28 (2), 211–224.
Nuscheler, D., Engelen, A., & Zahra, S. A. (2019). The role of top management teams in transforming technology-based new ventures' product introductions into growth. Journal of Business Venturing, 34(1), 122-140.
Unger, J. M., Rauch, A., Frese, M., & Rosenbusch, N. (2011). Human capital and entrepreneurial success: A meta-analytical review. Journal of Business Venturing, 26(3), 341-358.
Webb, J. W., Bruton, G. D., Tihanyi, L., & Ireland, R. D. (2013). Research on entrepreneurship in the informal economy: Framing a research agenda. Journal of Business Venturing, 28(5), 598-614.
Weterings, A., & Koster, S. (2007). Inheriting knowledge and sustaining relationships: What stimulates the innovative performance of small software firms in the Netherlands?. Research Policy, 36(3), 320-335.
Survival of the Funded? An Econometric Analysis of New-Firm Survival and Success
The failure rate of startups has steadily climbed, reaching 90% in 2012 (Marmer et al., 2012). Yet startups account for as much as 50% of new job creation year-to-year (Fairlie et al. 2016). Investors value analytical evidence on quantitative traits (Macmillan et al. 1985; Fulghieri and Sevilir 2009).
Startups lack long trends of performance to empirically evaluate their odds of success (Cooper et al. 1994). Hence, the question of how to identify and measure startup-firm success is an ongoing argument (Baluku et al., 2016). Research has diverged into two directions: a) metrics to evaluate older ventures (firm survival, sales, growth) and b) successful financing (assuming that investment is a signal). Thus, objective success and financing outcomes are inextricably linked (Baum and Silverman 2004; Cooper et al. 1994).
Typically, Cox proportional hazard functions are used to measure new-venture survival (Audretch and Mahmood 1995; Cader and Letherman 2009; Delmar and Shane, 2006). For non-binary indicators such as revenues or employment, maximum likelihood estimation is traditional (Bosma et al., 2002; Delmar and Shane, 2006). However, there is inherent bias in these non-binary regressions as data panels are invariably unbalanced with missing values from failed firms.
There is active debate on effective factors (Baum et al. 2004; Bosma et al. 2005; Delmar and Shane 2006; Yankov et al. 2014). We believe that the literature is limited in its focus on the interactions between factors, and has improperly considered survival bias. Our study corrects those omissions.
We test a vector of explanatory and control variables, along with their interactions, to determine their empirical impact on new-firm survival and then subsequent revenues and employment levels.
We test the statistical significance and economic importance of each X and Z variable informed by the literature: founder attributes (race, age), social and human capital (education, experience, previous startups), funding strategy (angels, debt, venture capital, etc.), market competitiveness (intellectual property, collaborations with universities, governments, and companies) and interactions of those attributes.
We first use a Cox proportional hazard model to estimate the impact of each proposed attribute on new-firm survival duration, and then leverage instrumental variables in a limited information maximum likelihood regression context to estimate the marginal impact on revenues and employment, conditional on survival.
Our data come from the Kauffman Firm Survey (KFS), which was conducted annually (2005-2012) to contain 4,298 firms, registering questions on the founders and the firms spanning demographics, financials, strategy, and organization.
Most notably, firms financed by a government source are much more likely to fail, at a hazard rate 3.6 times the failure rate of other sample firms. At the other extreme, FFF funding improves survival, cutting hazard rates almost in half. Safest of all are angel investments and debt financing, which reduce the risk of failure by 71 and 86 percent respectively, both remarkable risk reductions not only statistically but financially.
Competitive advantages reduce the risk of failure as well, especially for university partnerships (by 32 percent) and commercial partnerships (by 82 percent). Those are particularly strong in the presence of specific founder attributes like education and industry experience. More copyrights, more patents and especially more trademarks all serve to significantly reduce the risk of failure with each additional piece of IP.
Founder education and previous experience in the industry both reduce failure risk, but previous startup leadership by the founder has no statistical relevance. Interestingly, Hispanic founders have a much higher hazard rate than others. Age serves to reduce risk, with older founders failing less often at the rate of roughly 4 percent per 10-year age tranche.
Contribution to Scholarship
We believe that this is the first thorough statistical exploration of new-firm success while appropriately instrumenting for survival in other metrics of firm success. While it confirms some intuitive insights, it also quantifies the impact of financing strategies and intellectual property in a new way. Most importantly, this work identifies and measures the potential role of interactions between a founder’s social capital (education and experience) and subsequent choices by the new firm.
Contribution to Practice
These results have implications for the thousands of new firms facing financing and strategic choices every year. It is our hope that the tables in the full paper will communicate best paths to entrepreneurs, best potential investments to financiers, and even reflections on the lifespan of government contractors to policymakers with funding authority.
While this research is clearly within the scope of R&D funding and impact, we believe that it hits the interstices of the thematic groups proposed for this year’s conference. It could reasonably be paired with Co-creation, Creativity and Design; Ecosystems; Organizational and Management Innovation; or R&D.
Audretsch, David B., and Talat Mahmood. "New firm survival: new results using a hazard function." The Review of Economics and Statistics (1995): 97-103.
Baluku, Martin Mabunda, Julius Fred Kikooma, and Grace Milly Kibanja. "Psychological capital and the startup capital–entrepreneurial success
relationship." Journal of Small Business & Entrepreneurship 28, no. 1 (2016): 27-54.
Baum, Joel AC, and Brian S. Silverman. "Picking winners or building them? Alliance, intellectual, and human capital as selection criteria in venture financing and performance of biotechnology startups." Journal of business venturing 19, no. 3 (2004): 411-436.
Bosma, Niels, Mirjam Van Praag, Roy Thurik, and Gerrit De Wit. "The value of human and social capital investments for the business performance of startups." Small Business Economics 23, no. 3 (2004): 227-236.
Cader, Hanas A., and John C. Leatherman. "Small business survival and sample selection bias." Small Business Economics 37, no. 2 (2011): 155-165.
Cooper, Arnold C., F. Javier Gimeno-Gascon, and Carolyn Y. Woo. "Initial human and financial capital as predictors of new venture performance." Journal of business venturing 9, no. 5 (1994): 371-395.
Delmar, Frédéric, and Scott Shane. "Does experience matter? The effect of founding team experience on the survival and sales of newly founded ventures." Strategic Organization 4, no. 3 (2006): 215-247.
Fairlie, Robert W., Arnobio Morelix, E. J. Reedy, and Joshua Russell. "The Kauffman Index 2016: Startup Activity| National Trends." (2016).
Fulghieri, Paolo, and Merih Sevilir. "Size and focus of a venture capitalist's portfolio." Review of Financial Studies 22, no. 11 (2009): 4643-4680.
Marmer, Max, Bjoern Lasse Herrmann, Ertan Dogrultan, Ron Berman, C. Eesley, and S. Blank. "Startup genome report extra: Premature scaling." Startup Genome 10 (2011).
MacMillan, Ian C., Robin Siegel, and PN Subba Narasimha. "Criteria used by venture capitalists to evaluate new venture proposals." Journal of Business venturing 1, no. 1 (1985): 119-128.
Sandberg, William R., and Charles W. Hofer. "Improving new venture performance: The role of strategy, industry structure, and the entrepreneur." Journal of Business Venturing 2, no. 1 (1987): 5-28.
Yankov, B., Ruskov, P. and Haralampiev, K., 2014. Models and Tools for Technology Start-Up Companies Success Analysis. Journal Economic Alternatives, 3, pp.15-24.