Business models may be considered as “cognitive” devices since a deep level of knowledge about customers, suppliers, and competitors is needed for their development. Recent studies show that data-mining tools produce a positive interaction with business models, empowering the strategic performance capabilities that drive the achievement of competitive advantage. The present paper aims to discuss whether the adoption in a real context of data mining in support of business modeling may be enabled or hindered by organizational heterogeneity. The Structured Neural Network, adopted in the case study, is particularly suitable in support of strategic management, since it stimulates the convergence of personal knowledge and beliefs toward the exploitation of the key concepts and the cause-and-effect relations needed for the design of the business model. Furthermore, it provides a fact-based test for its robustness. The results provide both scientific and practical implications.

Business models may be considered as “cognitive” devices since a deep level of knowledge about customers, suppliers, and competitors is needed for their development. Recent studies show that data-mining tools produce a positive interaction with business models, empowering the strategic performance capabilities that drive the achievement of competitive advantage. The present paper aims to discuss whether the adoption in a real context of data mining in support of business modeling may be enabled or hindered by organizational heterogeneity. The Structured Neural Network, adopted in the case study, is particularly suitable in support of strategic management, since it stimulates the convergence of personal knowledge and beliefs toward the exploitation of the key concepts and the cause-and-effect relations needed for the design of the business model. Furthermore, it provides a fact-based test for its robustness. The results provide both scientific and practical implications.

Data-mining tools for business model design: The impact of organizational heterogeneity

CASTELLANO, NICOLA GIUSEPPE;
2017

Abstract

Business models may be considered as “cognitive” devices since a deep level of knowledge about customers, suppliers, and competitors is needed for their development. Recent studies show that data-mining tools produce a positive interaction with business models, empowering the strategic performance capabilities that drive the achievement of competitive advantage. The present paper aims to discuss whether the adoption in a real context of data mining in support of business modeling may be enabled or hindered by organizational heterogeneity. The Structured Neural Network, adopted in the case study, is particularly suitable in support of strategic management, since it stimulates the convergence of personal knowledge and beliefs toward the exploitation of the key concepts and the cause-and-effect relations needed for the design of the business model. Furthermore, it provides a fact-based test for its robustness. The results provide both scientific and practical implications.
Castellano, NICOLA GIUSEPPE; Del Gobbo, Roberto
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/872984
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