Management and Computer Science Synergies: A Theoretical Framework for Context Sensitive Simulation Environment
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- 关键词：Computer science ; Management ; Structural equation modeling ; Fuzzy theory ; DSS
- 刊名：Lecture Notes in Computer Science
- 出版年：2015
- 出版时间：2015
- 年：2015
- 卷：9380
- 期：1
- 页码：1-16
- 全文大小：618 KB
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Giuseppe Fenza (16)
Vincenzo Loia (16)
Aurelio Tommasetti (17)
Orlando Troisi (17)
Massimiliano Vesci (17)
16. Deparment of Computer Science, University of Salerno, Fisciano, SA, Italy
17. Department of Management and Information Technology, University of Salerno, Fisciano, SA, Italy - 丛书名：Transactions on Computational Collective Intelligence XIX
- ISBN：978-3-662-49017-4
- 刊物类别：Computer Science
- 刊物主题：Artificial Intelligence and Robotics
Computer Communication Networks
Software Engineering
Data Encryption
Database Management
Computation by Abstract Devices
Algorithm Analysis and Problem Complexity - 出版者：Springer Berlin / Heidelberg
- ISSN：1611-3349
文摘
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.