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Innovations and Organizational Structures
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Author(s): Marco Valente (University of L'Aquila, Italy)
Copyright: 2016
Pages: 17
Source title:
Relational Methodologies and Epistemology in Economics and Management Sciences
Source Author(s)/Editor(s): Lucio Biggiero (Università dell’ Aquila, Italy), Pier Paolo Angelini (Interuniversity Research Centre for Sustainable Development (CIRPS), Italy), Mario Basevi (Italian National Institute of Statistics, Italy), Nunzia Carbonara (Politecnico di Bari, Italy), Antonio Mastrogiorgio (Interuniversity Research Centre for Sustainable Development (CIRPS), Italy), Eliano Pessa (University of Pavia, Italy), Enrico Sevi (Università dell’ Aquila, Italy)and Marco Valente (Università dell’ Aquila, Italy)
DOI: 10.4018/978-1-4666-9770-6.ch010
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Abstract
This chapter presents a novel model to represent the relative results that different innovation strategies can be expected to attain in respect of technological spaces defined by different complexity levels. The model representing complexity is based on Kauffman's fitness landscape (known, also, as NK fitness landscape). However, contrary to the original proposal, we used a functional and deterministic representation of complexity defined over a real-valued space, replacing a stochastic and statistical-based definition of complexity in binary-valued spaces. The search strategies proposed are inspired to hierarchical organizations like companies. Low-level employees are assumed to have a full (technical) knowledge of a sub-set of the organization's functions, but lack the global vision necessary to assess the impact of a change on the overall organization's performance. Higher-level management has the task to weight different alternative proposals and select the best one for the benefit of the company as a whole, even though they are not able to explore directly technical solutions. The results confirm the results already known in the literature, though in much clearer and robust way, and suggest a large number of possible extensions.
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