The Contribution of Digital Technology to the Forecasting of Supply Chain Development, in IT Products, Modeling and Simulation of the Problem

Dimitrios K. Nasiopoulos (), Dimitrios M. Mastrakoulis and Dimitrios A. Arvanitidis
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Dimitrios K. Nasiopoulos: BICTEVAC Business Information and Communication Technologies in Value Chains Laboratory, Department of Agribusiness and Supply Chain Management, School of Applied Economics and Social Sciences, Agricultural University of Athens, 118 55 Athens, Greece
Dimitrios M. Mastrakoulis: BICTEVAC Business Information and Communication Technologies in Value Chains Laboratory, Department of Agribusiness and Supply Chain Management, School of Applied Economics and Social Sciences, Agricultural University of Athens, 118 55 Athens, Greece
Dimitrios A. Arvanitidis: BICTEVAC Business Information and Communication Technologies in Value Chains Laboratory, Department of Agribusiness and Supply Chain Management, School of Applied Economics and Social Sciences, Agricultural University of Athens, 118 55 Athens, Greece

Forecasting, 2022, vol. 4, issue 4, 1-19

Abstract: Aiming for the forecasting and predictability of their future development, corporations have developed appropriate strategies as a result of the necessity to optimize the distribution networks of new IT products over time. The necessity of diversifying manufacturing was brought on by the fierce competition between businesses and the sophisticated consumer demand trends for personalized items. For businesses looking to create more effective distribution networks for their products, mass adaptability may be advantageous. Fuzzy cognitive mapping (FCM), associations developed from web analytics data, and simulation results based on dynamic and agent-based simulation models work together to practically aid digital marketing experts, decision-makers and analysts in offering answers to their corresponding problems. In order to apply the measures in agent-based modeling, the current work is based on the gathering of web analysis data over a predetermined time period, as well as on identifying the influence correlations between measurements.

Keywords: decision support systems; simulation modeling; fuzzy cognitive maps; digital marketing; web analytics; IT product distribution network; mass customization (search for similar items in EconPapers)
JEL-codes: A1 B4 C0 C1 C2 C3 C4 C5 C8 M0 Q2 Q3 Q4 (search for similar items in EconPapers)
Date: 2022
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