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Networking: a business for women

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Abstract

This paper uses firm-level data and Data Envelopment Analysis (DEA) methods to investigate the effects of participation in formal networking activities and of female representation in leadership positions on firm’s economic efficiency. Our findings show that firms belonging to a network have a higher level of technical efficiency (i.e., the position of network members is closer to the technical efficient frontier), while the presence of women in senior roles (CEO, president, or member of the board of directors) is associated to lower efficiency scores. However, the observed performance strongly increases when firms with women in top positions participate to networks, hinting at superior returns for female networking. This interaction effect is found to be stronger in female-intensive working environments and networks, as well as in innovative and digital intensive sectors.

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Notes

  1. According to Parker (2008), a business network is a group of entrepreneurs that voluntarily decide to share knowledge and experiences.

  2. Huggins (2001) defines formal networks as group of firms that voluntarily cooperate with the explicit aim of co-producing, co-marketing, co-purchasing, or co-operating in product or market development. This definition reflects the specific contractual scheme, named network contract, recently introduced in Italy and object of this study. See Appendix for additional details.

  3. Watson (2011) considers firms linked to weak formal networks (industry associations, business consultants, or banks) as well as to strong informal networks (other firms in the industry, family, and friends).

  4. However, networking is a multifaceted phenomenon, and we cannot exclude the existence of other forms of cooperation among firms. See Cisi et al. (2016) for more details on this issue.

  5. There are also some papers that investigated networking by using datasets of students and by conducting laboratory experiments. Lindenlaub and Prummer (2014) analyzed the networks formed by 90,000 US students finding that men’s networks allowed members to have better access to information, while women’s networks were characterized by high peer pressure. Since information is important in contexts of high uncertainty and peer pressure is more valuable when there is limited uncertainty, they argued that men outperform women when there is high earnings uncertainty. Friebel et al. (2017) ran a laboratory experiment using a sample of German students and found that women’s social networks were more stable, path-dependent, and exhibited strong links, while men formed less selective and more opportunistic networks.

  6. Examples are smart factories that operate autonomously, autonomous vehicles, smart electricity grids, 3D printers, the deployment of objects equipped with computing capabilities and connected to communication networks in healthcare and agriculture (the so called internet of things), and so on.

  7. We use labor cost to overcome problems due to the identification of the number of full-time equivalent workers and to the difference in the quality of the workforce.

  8. We gather, respectively, food and beverages, chemical products and pharmaceuticals, and textile and leather products.

  9. Exploiting the panel-dimension to control for firm fixed effects is not easily accommodated within our DEA framework: The assumption of time-invariant firm fixed effects is problematic in the presence of year-specific technical frontiers based on different input bundles or techniques which could be simply not available during different years.

  10. Details on the numerical results of the test are available upon request.

  11. We include also the number of top leaders (Top Leader N), which is never found to be significant.

  12. To compute the average female share on total employees for each two-digit NACE manufacturing sector, we resort a dataset based on an Italian firm-level survey (the Employer and Employee Survey -RIL) conducted by the Institute for the Development of Workers’ Vocational Training (ISFOL).

  13. We are indebted to an anonymous referee for suggesting us such an interpretation.

  14. Note that high-tech sectors and digital intensive industries only partially overlap. For example, wood, paper, printing, and furniture are traditional low-tech sectors characterized by a medium-high digital intensity. Vice versa, chemicals and pharmaceuticals are R&D intensive sectors that exhibit a medium-low degree of digital intensity.

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Funding

Davide Vannoni and Francesco Devicienti gratefully acknowledge the financial support of MIUR—Ministry of Education, University and Research (Financing Fund for Departments of Excellence), Italy.

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Authors and Affiliations

  1. IRCrES-CNR & Department of Management, University of Turin, Via Real Collegio, 30, 10024, Moncalieri, TO, Italy

    Alessandro Manello

  2. Department of Management, University of Turin, Corso Unione Sovietica 218 bis, 10134, Torino, Italy

    Maurizio Cisi

  3. ESOMAS Department of Economics, Mathematics and Statistics, University of Turin & Collegio Carlo Alberto & IRCrES-CNR, Corso Unione Sovietica 218 bis, 10134, Torino, Italy

    Francesco Devicienti & Davide Vannoni

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  1. Alessandro Manello
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Correspondence to Davide Vannoni.

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Appendix. The Italian network contract

Appendix. The Italian network contract

The Italian legislation introduced with Law Decree 5/2009 (converted into Law 33/2009), the contratto di rete (network contract). It allows different companies to “cooperate in order to increase, either individually and collectively their innovative capabilities and competitiveness in the market.” The ambition of this legal instrument is to enhance the growth of SMEs. For these purposes, firms mutually agree to collaborate in predetermined forms and contexts on the base of a shared framework program regarding the management of their own companies, exchange industrial, commercial, technical, or technological information or services, or perform jointly one or more activities that are part of each company’s corporate goals.

The flexible normative background is intentionally weak in terms of binding constraints. The only requirements rely on the definition of the strategic goals aimed to improve innovation capacity and market competitiveness, on the identification of activities and investments needed for the implementation of the strategic goals, and on the specification of rights and duties for each participant. Aspects, such as entry and exit rules, as well conditions for network resolution are determined by the parties, and the ownership of assets, rights, and obligations is respectively legally attributable to each single company. Further governance aspects of the business network agreement rely on the optional creation of a common fund and of a common body in charge of the management of the network. Legal subjectivity and resulting limited liability are elective only when the network provides for the creation of a common capital fund and establishes a separate legal entity.

As compared to other forms of networking, such as informal networks (other firms in the industry, family, and friends) and weak formal networks (industry associations, business consultants, or banks), the Italian network contract is an example of a strong and formal network, where clear objectives are stated and adhesion of members is explicit and based on the voluntary act of signing an agreement.

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Manello, A., Cisi, M., Devicienti, F. et al. Networking: a business for women. Small Bus Econ 55, 329–348 (2020). https://doi.org/10.1007/s11187-019-00300-3

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