In the light of contemporary management trends and on the basis of the theory of “open innovation”, derives the concept of “crossfertilization”. Crossfertilization, i.e. profitable inter-group knowledge exchange facilitates the fusion of input from different disciplinary communities. In such a scenario, the study highlights the opportunities deriving from the cross-fertilization between management and computer science domains, and yields in terms of cognitive synergies results that exceeds by far the individual outputs of the parties involved. The approach we propose is a full mode generation of knowledge starting from the hypothetical assumptions relative to simulation using context data. A general workflow complementary Structural Equation Modeling (SEM) is defining being the most appropriate mathematical technique for testing causal relationships between latent variables with Fuzzy Data Analysis techniques in order to tailor Decision Support System (DSS) to the context of application. The main contribution of our study is the definition of a theoretical framework to address contextual decision making concerning relations between commitment, loyalty and customer satisfaction.

Management and Computer Science Synergies: A Theoretical Framework for Context Sensitive Simulation Environment

DE MAIO, CARMEN;FENZA, GIUSEPPE;LOIA, Vincenzo;TOMMASETTI, Aurelio;TROISI, ORLANDO;VESCI, Massimiliano
2015-01-01

Abstract

In the light of contemporary management trends and on the basis of the theory of “open innovation”, derives the concept of “crossfertilization”. Crossfertilization, i.e. profitable inter-group knowledge exchange facilitates the fusion of input from different disciplinary communities. In such a scenario, the study highlights the opportunities deriving from the cross-fertilization between management and computer science domains, and yields in terms of cognitive synergies results that exceeds by far the individual outputs of the parties involved. The approach we propose is a full mode generation of knowledge starting from the hypothetical assumptions relative to simulation using context data. A general workflow complementary Structural Equation Modeling (SEM) is defining being the most appropriate mathematical technique for testing causal relationships between latent variables with Fuzzy Data Analysis techniques in order to tailor Decision Support System (DSS) to the context of application. The main contribution of our study is the definition of a theoretical framework to address contextual decision making concerning relations between commitment, loyalty and customer satisfaction.
2015
978-3-662-49016-7
978-3-662-49017-4
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4658017
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