Social Entrepreneurship for the Generation of Networking Capabilities

Abstract

Supporting networks within and between entrepreneurial companies to facilitate knowledge and innovation diffusion and to drive industrial change and economic growth are important for all countries. In less developed countries, despite a higher proportion of necessity based entrepreneurial firms relative to opportunity based entrepreneurial firms, policy tends to support the latter, leaving the former more vulnerable and exposed. In this paper, we explore the emergent role that individual behavior and networks of necessity-based and opportunity-based firms have in climbing the technological ladder and creating an economy and society capable of undertaking complex activities and adding value. We develop and simulate a model based on network theory, the exploitation and exploration of knowledge and individual and team motivations, and draw conclusions from the analysis about how technological diffusion and growth can stem from increased collaboration of necessity-based and opportunity-based firms within strong inter-firm networks. Our paper contributes to the current debate on the need for social and productive technological change in less developed countries and calls for increased collaboration between the two types of entrepreneurial firms: by generating organizational capabilities to build dense networks of cohesion, trust and inclusiveness, necessity-based firms can be integrated into the networks of opportunity-based firms, providing the conditions to stimulate innovation and growth.

Mathematical Appendix

1.1 Terminology

• t : time measured in hours

• x : level of collaboration in the instant t (time)

• y : level of opportunism in the instant t (time)

• ${A_x}$: rate of growth of the collaboration in time t

• ${A_y}$: rate of growth of the opportunism in time t

• ${A_{{xy}}}$: probability that the opportunism obtain the collaboration’ information

• ${A_{{yx}}}$: probability that the collaboration allow the opportunism to obtain information

• ${\Omega_t}$: matrix of an individual’s contacts z in the time t

• I : new information

• F : filtered information

• i = 1, 2, 3…, N

• N: individuals’ number in the company

• ${\alpha_{{{i_t}}}}^{*}\!:$ the organizational practice of de agent i adapted to the new knowledge acquired in the time t

• σ: percentage of contacts in the firm $\sigma = \frac{1}{N}\sum\limits_{{i = 1}}^N {{\xi_i}}$ and, ${\xi_i} = \frac{{{L_i}}}{{N - 1}}$, ${L_i} = \sum\limits_{{j = 1}}^N {{l_{{ij}}}}$

• ${l_{{ij}}}$: contact between the agent i with j, component ij of the matrix Ω _t

• ${{\hbox{k}}_{{{i_t}}}}$: knowledge of the agent i in the time t

• ${\mu_{{{i_t}}}}$: weight of knowledge of the agent i in the time t

  $$ {\mu_{{{i_t}}}} = \frac{{{k_{{{i_t}}}}}}{{\sum\nolimits_{{i = 1}}^N {{k_{{{i_t}}}}} }} $$

• ${\theta_{{{i_t}}}}$: the knowledge acquired by the agent i, because of the interaction with other individuals in the instant t

• ${\lambda_{{{i_t}}}}$: the cognitive dimension of the agent i in the time t

  $$ {\lambda_{{{i_t}}}} = {\mu_{{{i_t}}}} + {\xi_{{{i_t}}}} $$