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Decision Support Framework for Composing of Different Questionnaires Based on Business Model with Optimization

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Abstract

The digital transformation requires not only involving contemporary information technologies but also a business model that is capable to cope with specific challenges. These models should be integrated properly in a decision support system closely related to the business activities of the company. The current article describes a framework of a decision-support system for composing different questionnaires for specific survey taking into account several predefined target groups. A proper business model able to determine the most suitable questions for generating different target groups’ questionnaires is formulated. This is realized by involving an expert that acts as a decision-maker to evaluate a predefined set of questions covering different sociological aspects toward predefined target groups. The distinguishing feature of this model is the ability to select a different number of questions for the questionnaires. Along with the formulated mathematical model, a software architecture framework for the implementation of this model is proposed. The numerical testing is done in case of the determination of four different questionnaires composed of an equal number of questions. Obtained results show the applicability of the formulated business model and the functionality of the proposed software framework.

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Acknowledgment

This work is supported by the Bulgarian National Science Fund, Project title “Synthesis of a dynamic model for assessing the psychological and physical impacts of excessive use of smart technologies”, KP-06-N 32/4/07.12.2019.

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Correspondence to Daniela Borissova .

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Borissova, D., Garvanova, M., Dimitrova, Z., Pandulis, A., Garvanov, I. (2020). Decision Support Framework for Composing of Different Questionnaires Based on Business Model with Optimization. In: Huynh, VN., Entani, T., Jeenanunta, C., Inuiguchi, M., Yenradee, P. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2020. Lecture Notes in Computer Science(), vol 12482. Springer, Cham. https://doi.org/10.1007/978-3-030-62509-2_5

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  • DOI: https://doi.org/10.1007/978-3-030-62509-2_5

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